[
    {
        "id": 281136,
        "commit_id": "ea964109d654394cc0a5237e6ec5510ba6404097",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/cryptocurrency/due_diligence/dd_controller.py",
        "file_name": "dd_controller.py",
        "fun_name": "call_bc",
        "commit_message": "Crypto menu refactor (#1119)\n\n* enabled some crypto commands in dd to be called independent of source loaded\r\n\r\n* support for coin_map_df in all dd functions + load ta and plot chart refactor\r\n\r\n* updated tests and removed coingecko scrapping where possible\r\n\r\n* removed ref of command from hugo\r\n\r\n* updated pycoingecko version\r\n\r\n* refactoring load\r\n\r\n* refactored load to fetch prices; pred can run independent of source now\r\n\r\n* load by default usd on cp/cg and usdt on cb/bin\r\n\r\n* updated to rich for formatting and updated dependencies\r\n\r\n* fixed changes requested\r\n\r\n* update docs\r\n\r\n* revert discord requirements\r\n\r\n* removed absolute from calculate change for price\r\n\r\n* fixing pr issues\r\n\r\n* fix loading issue when similar coins exist, move coins to home, fill n/a\r\n\r\n* update docs for coins\r\n\r\n* adds load to ta and pred menu",
        "code": "def call_bc(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            prog=\"bc\",\n            description=,\n        )\n        ns_parser = parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n\n        if ns_parser:\n            pycoingecko_view.display_bc(self.coin_map_df[\"CoinGecko\"], ns_parser.export)\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 130,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 61,
        "n_ast_nodes": 97,
        "n_identifiers": 18,
        "d_id": 83548,
        "documentation": {
            "docstring": "Process bc command\n            Blockchain explorers URLs for loaded coin. Those are sites like etherescan.io or polkascan.io\n            in which you can see all blockchain data e.g. all txs, all tokens, all contracts...\n                                ",
            "n_words": 31,
            "vocab_size": 28,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 30126,
        "commit_id": "fa2ad657482aca9dc628e6d7062b8badf2706bb6",
        "repo": "spotify-downloader",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "communicate",
        "commit_message": "v4 init",
        "code": "async def communicate(self):\n        \n        assert self._input.is_file()\n        self._output.open(\"w\").close()\n        return (None, None)\n",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 37,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 57,
        "n_identifiers": 7,
        "d_id": 5330,
        "documentation": {
            "docstring": "\n        Ensure that the file has been download, and create empty output file,\n        to avoid infinite loop.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 138092,
        "commit_id": "1510fb2cd631b2776092fb45ee4082e5e65f16f8",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_actor_reuse.py",
        "file_name": "test_actor_reuse.py",
        "fun_name": "test_multi_trial_reuse_with_failing",
        "commit_message": "[air/tune] Internal resource management 2 - Ray Tune to use new Ray AIR resource manager (#30016)\n\nIncludes/depends on #30777\r\n\r\nTLDR: This PR refactors Ray Tune's resource management to use a central AIR resource management package instead of the tightly coupled PlacementGroupManager.\r\n\r\nRay Tune's resource management currently uses a tightly coupled placement group manager. This leads to a number of shortcomings:\r\n- The tight coupling on the manager side (e.g. PG manager keeps track of trials) prevents re-usability\r\n- The tight coupling on the trial executor side prevents using different resource management strategies (e.g. shared or budget-based)\r\n- It's hard to test independently. Tests for the resource management require a simulated tune setup.\r\n\r\nTo improve stability, extensibility, and maintainability, this PR moves the resource management logic into a central `ray.air.execution.resources` subpackage. The resource management has a simple API that works with `ResourceRequest`s and `AllocatedResources` to manage requested and assigned resources, respectively. The actual resource management can then be anything - per default it is a placement group based manager, but this PR also introduces a PoC budget-based manager that can be plugged in.\r\n\r\nThe PR does not substantially change existing tests, so we can be certain that the new resource model is a fully compatible replacement for the old placement group manager.\r\n\r\nSigned-off-by: Kai Fricke <kai@anyscale.com>",
        "code": "def test_multi_trial_reuse_with_failing(ray_start_4_cpus_extra):\n    \n    os.environ[\"TUNE_MAX_PENDING_TRIALS_PG\"] = \"2\"\n\n    register_trainable(\"foo2\", MyResettableClass)\n\n    [trial1, trial2, trial3, trial4] = tune.run(\n        \"foo2\",\n        config={\n            \"fail\": tune.grid_search([False, True, False, False]),\n            \"id\": -1,\n            \"sleep\": 2,\n        },\n        reuse_actors=True,\n        resources_per_trial={\"cpu\": 2},\n        raise_on_failed_trial=False,\n    ).trials\n\n    assert trial1.last_result[\"num_resets\"] == 0\n    assert trial3.last_result[\"num_resets\"] == 0\n    assert trial4.last_result[\"num_resets\"] == 1\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 141,
        "n_words": 42,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 113,
        "n_ast_nodes": 183,
        "n_identifiers": 19,
        "d_id": 31314,
        "documentation": {
            "docstring": "Test that failing trial's actors are not reused.\n\n    - 2 trials can run at the same time\n    - Trial 1 succeeds, trial 2 fails\n    - Trial 3 will be scheduled after trial 2 failed, so won't reuse actor\n    - Trial 4 will be scheduled after trial 1 succeeded, so will reuse actor\n    ",
            "n_words": 52,
            "vocab_size": 34,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 145482,
        "commit_id": "b5b4460932505912d88d65134931e0da170fb467",
        "repo": "ray",
        "path": "python/ray/data/impl/block_list.py",
        "file_name": "block_list.py",
        "fun_name": "size_bytes",
        "commit_message": "Support creating a DatasetPipeline windowed by bytes (#22577)",
        "code": "def size_bytes(self) -> int:\n        \n        size = 0\n        has_size = False\n        for m in self.get_metadata():\n            if m.size_bytes is not None:\n                has_size = True\n                size += m.size_bytes\n        if not has_size:\n            return -1\n        else:\n            return size\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 138,
        "n_words": 33,
        "vocab_size": 24,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 50,
        "n_ast_nodes": 84,
        "n_identifiers": 7,
        "d_id": 33465,
        "documentation": {
            "docstring": "Returns the total size in bytes of the blocks, or -1 if not known.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 108335,
        "commit_id": "0abe0ce2f2748d1d0383154d045da3609a4b871b",
        "repo": "matplotlib",
        "path": "lib/matplotlib/colors.py",
        "file_name": "colors.py",
        "fun_name": "unregister",
        "commit_message": "Add a registry for color sequences\n\nColor sequences are simply lists of colors, that we store by name in\na registry. The registry is modelled similar to the ColormapRegistry\nto 1) support immutable builtin color sequences and 2) to return copies\nso that one cannot mess with the global definition of the color sequence\nthrough an obtained instance.\n\nFor now, I've made the sequences used for `ListedColormap`s available\nas builtin sequences, but that's open for discussion.\n\nMore usage documentation should be added in the color examples and/or\ntutorials, but I'll wait with that till after the general approval of\nthe structure and API. One common use case will be\n\n```\nplt.rc_params['axes.prop_cycle'] = plt.cycler(color=plt.color_sequences['Pastel1')\n```\n\nCo-authored-by: Elliott Sales de Andrade <quantum.analyst@gmail.com>",
        "code": "def unregister(self, name):\n        \n        if name in self._BUILTIN_COLOR_SEQUENCES:\n            raise ValueError(\n                f\"Cannot unregister builtin color sequence {name!r}\")\n        self._color_sequences.pop(name, None)\n\n\n_color_sequences = ColorSequenceRegistry()\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 66,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 31,
        "n_ast_nodes": 65,
        "n_identifiers": 8,
        "d_id": 23145,
        "documentation": {
            "docstring": "\n        Remove a sequence from the registry.\n\n        You cannot remove built-in color sequences.\n\n        If the name is not registered, returns with no error.\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 218114,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "source_from_cache",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def source_from_cache(path):\n    \n    if sys.implementation.cache_tag is None:\n        raise NotImplementedError('sys.implementation.cache_tag is None')\n    path = _os.fspath(path)\n    head, pycache_filename = _path_split(path)\n    found_in_pycache_prefix = False\n    if sys.pycache_prefix is not None:\n        stripped_path = sys.pycache_prefix.rstrip(path_separators)\n        if head.startswith(stripped_path + path_sep):\n            head = head[len(stripped_path):]\n            found_in_pycache_prefix = True\n    if not found_in_pycache_prefix:\n        head, pycache = _path_split(head)\n        if pycache != _PYCACHE:\n            raise ValueError(f'{_PYCACHE} not bottom-level directory in '\n                             f'{path!r}')\n    dot_count = pycache_filename.count('.')\n    if dot_count not in {2, 3}:\n        raise ValueError(f'expected only 2 or 3 dots in {pycache_filename!r}')\n    elif dot_count == 3:\n        optimization = pycache_filename.rsplit('.', 2)[-2]\n        if not optimization.startswith(_OPT):\n            raise ValueError(\"optimization portion of filename does not start \"\n                             f\"with {_OPT!r}\")\n        opt_level = optimization[len(_OPT):]\n        if not opt_level.isalnum():\n            raise ValueError(f\"optimization level {optimization!r} is not an \"\n                             \"alphanumeric value\")\n    base_filename = pycache_filename.partition('.')[0]\n    return _path_join(head, base_filename + SOURCE_SUFFIXES[0])\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 366,
        "n_words": 121,
        "vocab_size": 79,
        "complexity": 10,
        "nloc": 30,
        "token_counts": 212,
        "n_ast_nodes": 378,
        "n_identifiers": 33,
        "d_id": 55140,
        "documentation": {
            "docstring": "Given the path to a .pyc. file, return the path to its .py file.\n\n    The .pyc file does not need to exist; this simply returns the path to\n    the .py file calculated to correspond to the .pyc file.  If path does\n    not conform to PEP 3147/488 format, ValueError will be raised. If\n    sys.implementation.cache_tag is None then NotImplementedError is raised.\n\n    ",
            "n_words": 59,
            "vocab_size": 37,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 47665,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/serialization/test_dag_serialization.py",
        "file_name": "test_dag_serialization.py",
        "fun_name": "test_deps_sorted",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def test_deps_sorted(self):\n        \n        from airflow.operators.empty import EmptyOperator\n        from airflow.sensors.external_task import ExternalTaskSensor\n\n        execution_date = datetime(2020, 1, 1)\n        with DAG(dag_id=\"test_deps_sorted\", start_date=execution_date) as dag:\n            task1 = ExternalTaskSensor(\n                task_id=\"task1\",\n                external_dag_id=\"external_dag_id\",\n                mode=\"reschedule\",\n            )\n            task2 = EmptyOperator(task_id=\"task2\")\n            task1 >> task2\n\n        serialize_op = SerializedBaseOperator.serialize_operator(dag.task_dict[\"task1\"])\n        deps = serialize_op[\"deps\"]\n        assert deps == [\n            'airflow.ti_deps.deps.not_in_retry_period_dep.NotInRetryPeriodDep',\n            'airflow.ti_deps.deps.not_previously_skipped_dep.NotPreviouslySkippedDep',\n            'airflow.ti_deps.deps.prev_dagrun_dep.PrevDagrunDep',\n            'airflow.ti_deps.deps.ready_to_reschedule.ReadyToRescheduleDep',\n            'airflow.ti_deps.deps.trigger_rule_dep.TriggerRuleDep',\n        ]\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 256,
        "n_words": 49,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 109,
        "n_ast_nodes": 186,
        "n_identifiers": 25,
        "d_id": 9201,
        "documentation": {
            "docstring": "\n        Tests serialize_operator, make sure the deps is in order\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 140203,
        "commit_id": "f67871c1f7e79adc727b2a15311d9332832d2e8a",
        "repo": "ray",
        "path": "python/ray/workflow/workflow_storage.py",
        "file_name": "workflow_storage.py",
        "fun_name": "load_workflow_status",
        "commit_message": "[workflow] Fast workflow indexing (#24767)\n\n* workflow indexing\r\n\r\n* simplify workflow storage API\r\n\r\n* Only fix workflow status when updating the status.\r\n\r\n* support status filter",
        "code": "def load_workflow_status(self):\n        \n        return self._status_storage.load_workflow_status(self._workflow_id)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 18,
        "n_words": 4,
        "vocab_size": 4,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 31892,
        "documentation": {
            "docstring": "Load workflow status. If we find the previous status updating failed,\n        fix it with redo-log transaction recovery.",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 178678,
        "commit_id": "c723f658e8c11ec92d6ef90c2f42527c67d3f318",
        "repo": "Nuitka",
        "path": "nuitka/PythonFlavors.py",
        "file_name": "PythonFlavors.py",
        "fun_name": "isCPythonOfficialPackage",
        "commit_message": "Added CPython Official flavor, so far only detected on macOS",
        "code": "def isCPythonOfficialPackage():\n    \n\n    # For macOS however, it's very knowable.\n    if isMacOS() and sys.executable.startswith(\n        \"/Library/Frameworks/Python.framework/Versions/\"\n    ):\n        return True\n\n    return False\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 48,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 23,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 42789,
        "documentation": {
            "docstring": "Official CPython download, kind of hard to detect since self-compiled doesn't change much.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 86527,
        "commit_id": "bc59434031930199dcdc056943c2ba4a17bbd5c8",
        "repo": "sentry",
        "path": "src/sentry/tasks/post_process.py",
        "file_name": "post_process.py",
        "fun_name": "update_existing_attachments",
        "commit_message": "ref(perf-issues): Modularize post_process_group (ISP-11) (#39594)\n\nFully modularizes `post_process_group` as final step before adding\r\nmultiple event types to it.",
        "code": "def update_existing_attachments(job):\n    \n    # Patch attachments that were ingested on the standalone path.\n    with sentry_sdk.start_span(op=\"tasks.post_process_group.update_existing_attachments\"):\n        try:\n            from sentry.models import EventAttachment\n\n            event = job[\"event\"]\n\n            EventAttachment.objects.filter(\n                project_id=event.project_id, event_id=event.event_id\n            ).update(group_id=event.group_id)\n        except Exception:\n            logger.exception(\"Failed to update existing attachments\")\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 126,
        "n_words": 33,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 66,
        "n_ast_nodes": 116,
        "n_identifiers": 18,
        "d_id": 18118,
        "documentation": {
            "docstring": "\n    Attaches the group_id to all event attachments that were either:\n\n    1) ingested prior to the event via the standalone attachment endpoint.\n    2) part of a different group before reprocessing started.\n    ",
            "n_words": 30,
            "vocab_size": 26,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 204338,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/staticfiles/finders.py",
        "file_name": "finders.py",
        "fun_name": "list",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def list(self, ignore_patterns):\n        \n        raise NotImplementedError(\n            \"subclasses of BaseFinder must provide a list() method\"\n        )\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 46,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 13,
        "n_ast_nodes": 25,
        "n_identifiers": 4,
        "d_id": 50701,
        "documentation": {
            "docstring": "\n        Given an optional list of paths to ignore, return a two item iterable\n        consisting of the relative path and storage instance.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 3800,
        "commit_id": "a3aae8017a0a40ff2006e2567f71dccb04c997a5",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/unit_tests/test_async_job.py",
        "file_name": "test_async_job.py",
        "fun_name": "test_less_jobs",
        "commit_message": "🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805)\n\n* Facebook Marketing performance improvement\r\n\r\n* add comments and little refactoring\r\n\r\n* fix integration tests with the new config\r\n\r\n* improve job status handling, limit concurrency to 10\r\n\r\n* fix campaign jobs, refactor manager\r\n\r\n* big refactoring of async jobs, support random order of slices\r\n\r\n* update source _read_incremental to hook new state logic\r\n\r\n* fix issues with timeout\r\n\r\n* remove debugging and clean up, improve retry logic\r\n\r\n* merge changes from #8234\r\n\r\n* fix call super _read_increment\r\n\r\n* generalize batch execution, add use_batch flag\r\n\r\n* improve coverage, do some refactoring of spec\r\n\r\n* update test, remove overrides of source\r\n\r\n* add split by AdSet\r\n\r\n* add smaller insights\r\n\r\n* fix end_date < start_date case\r\n\r\n* add account_id to PK\r\n\r\n* add notes\r\n\r\n* fix new streams\r\n\r\n* fix reversed incremental stream\r\n\r\n* update spec.json for SAT\r\n\r\n* upgrade CDK and bump version\r\n\r\nCo-authored-by: Dmytro Rezchykov <dmitry.rezchykov@zazmic.com>\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>",
        "code": "def test_less_jobs(self, api, started_job, batch):\n        \n        jobs = [started_job for _ in range(49)]\n\n        update_in_batch(api=api, jobs=jobs)\n\n        assert started_job.update_job.call_count == 49\n        assert len(api.new_batch.return_value) == 49\n        batch.execute.assert_called_once()\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 65,
        "n_words": 23,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 60,
        "n_ast_nodes": 93,
        "n_identifiers": 16,
        "d_id": 563,
        "documentation": {
            "docstring": "Should update all jobs when number of jobs less than max size of batch",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 118684,
        "commit_id": "dd9084523e365e637443ea351eaaaa25f52d8412",
        "repo": "streamlit",
        "path": "lib/tests/streamlit/config_test.py",
        "file_name": "config_test.py",
        "fun_name": "test_load_global_local_flag_config",
        "commit_message": "Report sharing removal (#4260)\n\nThe report sharing feature is a substantial but completely unused portion of the code in Streamlit's underlying machinery. The feature was created early on, used by just a few groups, and has not been used by anyone for a while, as indicated by no activity in the associated S3 buckets. This commit removes that code to make the remaining code easier to navigate and understand.",
        "code": "def test_load_global_local_flag_config(self):\n        \n\n        global_config = \n\n        local_config = \n\n        global_config_path = \"/mock/home/folder/.streamlit/config.toml\"\n        local_config_path = os.path.join(os.getcwd(), \".streamlit/config.toml\")\n\n        global_open = mock_open(read_data=global_config)\n        local_open = mock_open(read_data=local_config)\n        open = mock_open()\n        open.side_effect = [global_open.return_value, local_open.return_value]\n\n        open_patch = patch(\"streamlit.config.open\", open)\n        # patch streamlit.*.os.* instead of os.* for py35 compat\n        makedirs_patch = patch(\"streamlit.config.os.makedirs\")\n        makedirs_patch.return_value = True\n        pathexists_patch = patch(\"streamlit.config.os.path.exists\")\n        pathexists_patch.side_effect = lambda path: path in [\n            global_config_path,\n            local_config_path,\n        ]\n\n        with open_patch, makedirs_patch, pathexists_patch:\n            config.get_config_options(options_from_flags={\"theme.font\": \"monospace\"})\n\n            self.assertEqual(\"light\", config.get_option(\"theme.base\"))\n            self.assertEqual(\"#FFFFFF\", config.get_option(\"theme.textColor\"))\n            self.assertEqual(\"monospace\", config.get_option(\"theme.font\"))\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 257,
        "n_words": 70,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 163,
        "n_ast_nodes": 292,
        "n_identifiers": 26,
        "d_id": 26359,
        "documentation": {
            "docstring": "Test that CLI flags have higher priority than both\n        ~/.streamlit/config.toml and $CWD/.streamlit/config.toml at parse time.\n        \n        [theme]\n        base = \"dark\"\n        font = \"sans serif\"\n        textColor = \"#FFFFFF\"\n        \n        [theme]\n        base = \"light\"\n        font = \"serif\"\n        ",
            "n_words": 33,
            "vocab_size": 26,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 166376,
        "commit_id": "864729813a0203af8bb0d30b6c883588ae2c96f8",
        "repo": "pandas",
        "path": "pandas/tests/io/test_pickle.py",
        "file_name": "test_pickle.py",
        "fun_name": "test_pickle_binary_object_compression",
        "commit_message": "ENH: add support for reading .tar archives (#44787)\n\n* Add reproduction test for .tar.gz archives\r\n\r\nco-authored-by: Margarete Dippel <margarete01@users.noreply.github.com>\r\n\r\n* add support for .tar archives\r\n\r\npython's `tarfile` supports gzip, xz and bz2 encoding,\r\nso we don't need to make any special cases for that.\r\n\r\nco-authored-by: Margarete Dippel <margarete01@users.noreply.github.com>\r\n\r\n* update doc comments\r\n\r\n* fix: pep8 errors\r\n\r\n* refactor: flip _compression_to_extension around to support multiple extensions on same compression\r\n\r\nco-authored-by: Margarete Dippel <margarete01@users.norepl\r\ny.github.com>\r\n\r\n* refactor: detect tar files using existing extension mapping\r\n\r\nco-authored-by: Margarete Dippel <margarete01@users.noreply.github.com>\r\n\r\n* feat: add support for writing tar files\r\n\r\nco-authored-by: Margarete Dippel <margarete01@users.noreply.github.com>\r\n\r\n* feat: assure it respects .gz endings\r\n\r\n* feat: add \"tar\" entry to compressionoptions\r\n\r\n* chore: add whatsnew entry\r\n\r\n* fix: test_compression_size_fh\r\n\r\n* add tarfile to shared compression docs\r\n\r\n* fix formatting\r\n\r\n* pass through \"mode\" via compression args\r\n\r\n* fix pickle test\r\n\r\n* add class comment\r\n\r\n* sort imports\r\n\r\n* add _compression_to_extension back for backwards compatibility\r\n\r\n* fix some type warnings\r\n\r\n* fix: formatting\r\n\r\n* fix: mypy complaints\r\n\r\n* fix: more tests\r\n\r\n* fix: some error with xml\r\n\r\n* fix: interpreted text role\r\n\r\n* move to v1.5 whatsnw\r\n\r\n* add versionadded note\r\n\r\n* don't leave blank lines\r\n\r\n* add tests for zero files / multiple files\r\n\r\n* move _compression_to_extension to tests\r\n\r\n* revert added \"mode\" argument\r\n\r\n* add test to ensure that `compression.mode` works\r\n\r\n* compare strings, not bytes\r\n\r\n* replace carriage returns\r\n\r\nCo-authored-by: Margarete Dippel <margarete01@users.noreply.github.com>",
        "code": "def test_pickle_binary_object_compression(compression):\n    \n    df = tm.makeDataFrame()\n\n    # reference for compression\n    with tm.ensure_clean() as path:\n        df.to_pickle(path, compression=compression)\n        reference = Path(path).read_bytes()\n\n    # write\n    buffer = io.BytesIO()\n    df.to_pickle(buffer, compression=compression)\n    buffer.seek(0)\n\n    # gzip  and zip safe the filename: cannot compare the compressed content\n    assert buffer.getvalue() == reference or compression in (\"gzip\", \"zip\", \"tar\")\n\n    # read\n    read_df = pd.read_pickle(buffer, compression=compression)\n    buffer.seek(0)\n    tm.assert_frame_equal(df, read_df)\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 114,
        "n_words": 57,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 109,
        "n_ast_nodes": 188,
        "n_identifiers": 20,
        "d_id": 39808,
        "documentation": {
            "docstring": "\n    Read/write from binary file-objects w/wo compression.\n\n    GH 26237, GH 29054, and GH 29570\n    ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 70980,
        "commit_id": "de3fcba9e95818e9634ab7de6bfcb1f4221f2775",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/views.py",
        "file_name": "views.py",
        "fun_name": "get_filtering",
        "commit_message": "Fix warnings from flake8-comprehensions.",
        "code": "def get_filtering(self):\n        \n        self.select_date_form = SelectDateForm(self.request.GET)\n        result = {}\n        if self.select_date_form.is_valid():\n            date_from = self.select_date_form.cleaned_data.get('date_from')\n            date_to = self.select_date_form.cleaned_data.get('date_to')\n            if date_to:\n                # careful: date_to must be increased by 1 day\n                # as submit_time is a time so will always be greater\n                date_to += datetime.timedelta(days=1)\n                if date_from:\n                    result['submit_time__range'] = [date_from, date_to]\n                else:\n                    result['submit_time__lte'] = date_to\n            elif date_from:\n                result['submit_time__gte'] = date_from\n        return result\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 265,
        "n_words": 58,
        "vocab_size": 42,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 100,
        "n_ast_nodes": 174,
        "n_identifiers": 15,
        "d_id": 15592,
        "documentation": {
            "docstring": " Return filering as a dict for submissions queryset ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 67799,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/get_item_details.py",
        "file_name": "get_item_details.py",
        "fun_name": "get_so_reservation_for_item",
        "commit_message": "style: format code with black",
        "code": "def get_so_reservation_for_item(args):\n\treserved_so = None\n\tif args.get(\"against_sales_order\"):\n\t\tif get_reserved_qty_for_so(args.get(\"against_sales_order\"), args.get(\"item_code\")):\n\t\t\treserved_so = args.get(\"against_sales_order\")\n\telif args.get(\"against_sales_invoice\"):\n\t\tsales_order = frappe.db.sql(\n\t\t\t,\n\t\t\t(args.get(\"against_sales_invoice\"), args.get(\"item_code\")),\n\t\t)\n\t\tif sales_order and sales_order[0]:\n\t\t\tif get_reserved_qty_for_so(sales_order[0][0], args.get(\"item_code\")):\n\t\t\t\treserved_so = sales_order[0]\n\telif args.get(\"sales_order\"):\n\t\tif get_reserved_qty_for_so(args.get(\"sales_order\"), args.get(\"item_code\")):\n\t\t\treserved_so = args.get(\"sales_order\")\n\treturn reserved_so\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 25,
        "n_words": 42,
        "vocab_size": 26,
        "complexity": 9,
        "nloc": 18,
        "token_counts": 146,
        "n_ast_nodes": 253,
        "n_identifiers": 9,
        "d_id": 14622,
        "documentation": {
            "docstring": "select sales_order from `tabSales Invoice Item` where\n\t\tparent=%s and item_code=%s",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 248585,
        "commit_id": "fe1daad67237c2154a3d8d8cdf6c603f0d33682e",
        "repo": "synapse",
        "path": "tests/util/test_macaroons.py",
        "file_name": "test_macaroons.py",
        "fun_name": "test_short_term_login_token",
        "commit_message": "Move the \"email unsubscribe\" resource, refactor the macaroon generator & simplify the access token verification logic. (#12986)\n\nThis simplifies the access token verification logic by removing the `rights`\r\nparameter which was only ever used for the unsubscribe link in email\r\nnotifications. The latter has been moved under the `/_synapse` namespace,\r\nsince it is not a standard API.\r\n\r\nThis also makes the email verification link more secure, by embedding the\r\napp_id and pushkey in the macaroon and verifying it. This prevents the user\r\nfrom tampering the query parameters of that unsubscribe link.\r\n\r\nMacaroon generation is refactored:\r\n\r\n- Centralised all macaroon generation and verification logic to the\r\n  `MacaroonGenerator`\r\n- Moved to `synapse.utils`\r\n- Changed the constructor to require only a `Clock`, hostname, and a secret key\r\n  (instead of a full `Homeserver`).\r\n- Added tests for all methods.",
        "code": "def test_short_term_login_token(self):\n        \n        token = self.macaroon_generator.generate_short_term_login_token(\n            user_id=\"@user:tesths\",\n            auth_provider_id=\"oidc\",\n            auth_provider_session_id=\"sid\",\n            duration_in_ms=2 * 60 * 1000,\n        )\n\n        info = self.macaroon_generator.verify_short_term_login_token(token)\n        self.assertEqual(info.user_id, \"@user:tesths\")\n        self.assertEqual(info.auth_provider_id, \"oidc\")\n        self.assertEqual(info.auth_provider_session_id, \"sid\")\n\n        # Raises with another secret key\n        with self.assertRaises(MacaroonVerificationFailedException):\n            self.other_macaroon_generator.verify_short_term_login_token(token)\n\n        # Wait a minute\n        self.reactor.pump([60])\n        # Shouldn't raise\n        self.macaroon_generator.verify_short_term_login_token(token)\n        # Wait another minute\n        self.reactor.pump([60])\n        # Should raise since it expired\n        with self.assertRaises(MacaroonVerificationFailedException):\n            self.macaroon_generator.verify_short_term_login_token(token)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 240,
        "n_words": 55,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 135,
        "n_ast_nodes": 233,
        "n_identifiers": 17,
        "d_id": 72365,
        "documentation": {
            "docstring": "Test the generation and verification of short-term login tokens",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 42601,
        "commit_id": "74bb3c28ce9f2cd2be4cd9176747d59a0d67285d",
        "repo": "nltk",
        "path": "nltk/sentiment/vader.py",
        "file_name": "vader.py",
        "fun_name": "polarity_scores",
        "commit_message": "Add a note stating that a hashtag is unsupported in VADER",
        "code": "def polarity_scores(self, text):\n        \n        # text, words_and_emoticons, is_cap_diff = self.preprocess(text)\n        sentitext = SentiText(\n            text, self.constants.PUNC_LIST, self.constants.REGEX_REMOVE_PUNCTUATION\n        )\n        sentiments = []\n        words_and_emoticons = sentitext.words_and_emoticons\n        for item in words_and_emoticons:\n            valence = 0\n            i = words_and_emoticons.index(item)\n            if (\n                i < len(words_and_emoticons) - 1\n                and item.lower() == \"kind\"\n                and words_and_emoticons[i + 1].lower() == \"of\"\n            ) or item.lower() in self.constants.BOOSTER_DICT:\n                sentiments.append(valence)\n                continue\n\n            sentiments = self.sentiment_valence(valence, sentitext, item, i, sentiments)\n\n        sentiments = self._but_check(words_and_emoticons, sentiments)\n\n        return self.score_valence(sentiments, text)\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 274,
        "n_words": 70,
        "vocab_size": 53,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 138,
        "n_ast_nodes": 218,
        "n_identifiers": 21,
        "d_id": 7656,
        "documentation": {
            "docstring": "\n        Return a float for sentiment strength based on the input text.\n        Positive values are positive valence, negative value are negative\n        valence.\n\n        :note: Hashtags are not taken into consideration (e.g. #BAD is neutral). If you\n            are interested in processing the text in the hashtags too, then we recommend\n            preprocessing your data to remove the #, after which the hashtag text may be\n            matched as if it was a normal word in the sentence.\n        ",
            "n_words": 72,
            "vocab_size": 59,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 110450,
        "commit_id": "7a1df7830f7685a99291d90c5e79bfc5e7876f31",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/tests/test_axes3d.py",
        "file_name": "test_axes3d.py",
        "fun_name": "test_mutating_input_arrays_y_and_z",
        "commit_message": "Test that plot results aren't affected by mutating input arrays",
        "code": "def test_mutating_input_arrays_y_and_z(fig_test, fig_ref):\n    \n    ax1 = fig_test.add_subplot(111, projection='3d')\n    x = [1, 2, 3]\n    y = [0.0, 0.0, 0.0]\n    z = [0.0, 0.0, 0.0]\n    ax1.plot(x, y, z, 'o-')\n\n    ax1.set_ylim([0, 4])\n    ax1.set_zlim([0, 4])\n    fig_test.draw_without_rendering()\n\n    # mutate y,z to get a nontrivial line\n    y[:] = [1, 2, 3]\n    z[:] = [1, 2, 3]\n\n    # draw the same plot without mutating x and y\n    ax2 = fig_ref.add_subplot(111, projection='3d')\n    x = [1, 2, 3]\n    y = [0.0, 0.0, 0.0]\n    z = [0.0, 0.0, 0.0]\n    ax2.plot(x, y, z, 'o-')\n\n    ax2.set_ylim([0, 4])\n    ax2.set_zlim([0, 4])\n    fig_test.draw_without_rendering()\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 150,
        "n_words": 87,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 208,
        "n_ast_nodes": 277,
        "n_identifiers": 14,
        "d_id": 24166,
        "documentation": {
            "docstring": "\n    Test to see if the `z` axis does not get mutated\n    after a call to `Axes3D.plot`\n\n    test cases came from GH#8990\n    ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 45441,
        "commit_id": "bb26f96665567325a7fbb810249820e7dac0322a",
        "repo": "airflow",
        "path": "airflow/www/views.py",
        "file_name": "views.py",
        "fun_name": "dag_edges",
        "commit_message": "Make Grid and and Graph view work with task mapping (#21740)\n\n* Expand mapped tasks in the Scheduler\r\n\r\nTechnically this is done inside\r\nDagRun.task_instance_scheduling_decisions, but the only place that is\r\ncurrently called is the Scheduler\r\n\r\nThe way we are getting `upstream_ti` to pass to expand_mapped_task is\r\nall sorts of wrong and will need fixing, I think the interface for that\r\nmethod is wrong and the mapped task should be responsible for finding\r\nthe right upstream TI itself.\r\n\r\n* make UI and tree work with mapped tasks\r\n\r\n* add graph tooltip and map count\r\n\r\n* simplify node label redraw logic\r\n\r\n* add utils.js and map_index to /taskInstances\r\n\r\n* use TaskInstanceState instead of strings\r\n\r\n* move map_index on /taskinstance to separate PR\r\n\r\n* check to use Task or Tasks\r\n\r\n* remove `no_status` and use TaskInstanceState\r\n\r\nCo-authored-by: Ash Berlin-Taylor <ash@apache.org>",
        "code": "def dag_edges(dag):\n    \n    # Edges to add between TaskGroup\n    edges_to_add = set()\n    # Edges to remove between individual tasks that are replaced by edges_to_add.\n    edges_to_skip = set()\n\n    task_group_map = dag.task_group.get_task_group_dict()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 29,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 115,
        "n_ast_nodes": 48,
        "n_identifiers": 8,
        "d_id": 8568,
        "documentation": {
            "docstring": "\n    Create the list of edges needed to construct the Graph view.\n\n    A special case is made if a TaskGroup is immediately upstream/downstream of another\n    TaskGroup or task. Two dummy nodes named upstream_join_id and downstream_join_id are\n    created for the TaskGroup. Instead of drawing an edge onto every task in the TaskGroup,\n    all edges are directed onto the dummy nodes. This is to cut down the number of edges on\n    the graph.\n\n    For example: A DAG with TaskGroups group1 and group2:\n        group1: task1, task2, task3\n        group2: task4, task5, task6\n\n    group2 is downstream of group1:\n        group1 >> group2\n\n    Edges to add (This avoids having to create edges between every task in group1 and group2):\n        task1 >> downstream_join_id\n        task2 >> downstream_join_id\n        task3 >> downstream_join_id\n        downstream_join_id >> upstream_join_id\n        upstream_join_id >> task4\n        upstream_join_id >> task5\n        upstream_join_id >> task6\n    ",
            "n_words": 132,
            "vocab_size": 81,
            "n_whitespaces": 233,
            "language": "en"
        }
    },
    {
        "id": 37492,
        "commit_id": "57e6464ac9a31156f1c93e59107323e6ec01309e",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_tokenizers",
        "commit_message": "Update all require decorators to use skipUnless when possible (#16999)",
        "code": "def require_tokenizers(test_case):\n    \n    return unittest.skipUnless(is_tokenizers_available(), \"test requires tokenizers\")(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 6797,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires 🤗 Tokenizers. These tests are skipped when 🤗 Tokenizers isn't installed.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 291628,
        "commit_id": "1c0f9cf941f77d6e3d299f98d5174f0a2953f236",
        "repo": "core",
        "path": "homeassistant/components/overkiz/water_heater_entities/hitachi_dhw.py",
        "file_name": "hitachi_dhw.py",
        "fun_name": "current_operation",
        "commit_message": "Add Overkiz Hitachi DHW (#81536)\n\n* Port ha-tahome hitachi dhw\r\n\r\n* Use int for setting temperature\r\n\r\n* Use value as float when possible\r\n\r\n* Use device state for current operation\r\n\r\n* Update homeassistant/components/overkiz/water_heater_entities/hitachi_dhw.py\r\n\r\nCo-authored-by: Quentame <polletquentin74@me.com>\r\n\r\n* Update homeassistant/components/overkiz/water_heater_entities/hitachi_dhw.py\r\n\r\nCo-authored-by: Quentame <polletquentin74@me.com>\r\n\r\n* Use ON instead of ECO for standard operation mode\r\n\r\nCo-authored-by: Quentame <polletquentin74@me.com>",
        "code": "def current_operation(self) -> str | None:\n        \n        modbus_control = self.device.states[OverkizState.MODBUS_CONTROL_DHW]\n        if modbus_control and modbus_control.value_as_str == OverkizCommandParam.STOP:\n            return STATE_OFF\n\n        current_mode = self.device.states[OverkizState.MODBUS_DHW_MODE]\n        if current_mode and current_mode.value_as_str in OVERKIZ_TO_OPERATION_MODE:\n            return OVERKIZ_TO_OPERATION_MODE[current_mode.value_as_str]\n\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 94,
        "n_words": 30,
        "vocab_size": 23,
        "complexity": 5,
        "nloc": 9,
        "token_counts": 65,
        "n_ast_nodes": 102,
        "n_identifiers": 15,
        "d_id": 90732,
        "documentation": {
            "docstring": "Return current operation ie. eco, electric, performance, ...",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 42453,
        "commit_id": "8ffd0d8190552d45f8b92e18da3fc41639e5185d",
        "repo": "nltk",
        "path": "nltk/corpus/reader/wordnet.py",
        "file_name": "wordnet.py",
        "fun_name": "add_provs",
        "commit_message": "Initialize empty provenance for default English",
        "code": "def add_provs(self, reader):\n        \n        fileids = reader.fileids()\n        for fileid in fileids:\n            prov, langfile = os.path.split(fileid)\n            file_name, file_extension = os.path.splitext(langfile)\n            if file_extension == \".tab\":\n                lang = file_name.split(\"-\")[-1]\n                if lang in self.provenances.keys():\n                    # We already have another resource for this lang,\n                    # so we need to further specify the lang id:\n                    lang = f\"{lang}_{prov}\"\n                self.provenances[lang] = prov\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 210,
        "n_words": 54,
        "vocab_size": 41,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 84,
        "n_ast_nodes": 150,
        "n_identifiers": 16,
        "d_id": 7546,
        "documentation": {
            "docstring": "Add languages from Multilingual Wordnet to the provenance dictionary",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 20229,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/platformdirs/unix.py",
        "file_name": "unix.py",
        "fun_name": "site_data_dir",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def site_data_dir(self) -> str:\n        \n        # XDG default for $XDG_DATA_DIRS; only first, if multipath is False\n        path = os.environ.get(\"XDG_DATA_DIRS\", \"\")\n        if not path.strip():\n            path = f\"/usr/local/share{os.pathsep}/usr/share\"\n        return self._with_multi_path(path)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 27,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 39,
        "n_ast_nodes": 78,
        "n_identifiers": 10,
        "d_id": 3281,
        "documentation": {
            "docstring": "\n        :return: data directories shared by users (if `multipath <platformdirs.api.PlatformDirsABC.multipath>` is\n         enabled and ``XDG_DATA_DIR`` is set and a multi path the response is also a multi path separated by the OS\n         path separator), e.g. ``/usr/local/share/$appname/$version`` or ``/usr/share/$appname/$version``\n        ",
            "n_words": 36,
            "vocab_size": 27,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 197540,
        "commit_id": "7fe8e027ae1d7f683243c0229b961671a6cbb4c5",
        "repo": "sympy",
        "path": "sympy/stats/stochastic_process_types.py",
        "file_name": "stochastic_process_types.py",
        "fun_name": "absorbing_probabilities",
        "commit_message": "Improved some documentation in the stats module",
        "code": "def absorbing_probabilities(self):\n        \n        _, _, R, _ = self.decompose()\n        N = self.fundamental_matrix()\n        if R is None or N is None:\n            return None\n        return N*R\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 69,
        "n_words": 23,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 41,
        "n_ast_nodes": 67,
        "n_identifiers": 7,
        "d_id": 48618,
        "documentation": {
            "docstring": "\n        Computes the absorbing probabilities, i.e.\n        the ij-th entry of the matrix denotes the\n        probability of Markov chain being absorbed\n        in state j starting from state i.\n        ",
            "n_words": 26,
            "vocab_size": 21,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 20520,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/util.py",
        "file_name": "util.py",
        "fun_name": "doctype_matches",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def doctype_matches(text, regex):\n    \n    m = doctype_lookup_re.search(text)\n    if m is None:\n        return False\n    doctype = m.group(1)\n    return re.compile(regex, re.I).match(doctype.strip()) is not None\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 43,
        "n_words": 21,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 54,
        "n_ast_nodes": 87,
        "n_identifiers": 13,
        "d_id": 3407,
        "documentation": {
            "docstring": "Check if the doctype matches a regular expression (if present).\n\n    Note that this method only checks the first part of a DOCTYPE.\n    eg: 'html PUBLIC \"-//W3C//DTD XHTML 1.0 Strict//EN\"'\n    ",
            "n_words": 29,
            "vocab_size": 27,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 100170,
        "commit_id": "096b5511e244eecd8799b2a0324655207ce8985e",
        "repo": "sentry",
        "path": "tests/sentry/data_export/endpoints/test_data_export.py",
        "file_name": "test_data_export.py",
        "fun_name": "test_converts_stats_period_start_end",
        "commit_message": "ref(tests): Remove `get_valid_response()` (#34822)",
        "code": "def test_converts_stats_period_start_end(self):\n        \n        payload = self.make_payload(\"discover\", {\"statsPeriodStart\": \"1w\", \"statsPeriodEnd\": \"5d\"})\n        with self.feature(\"organizations:discover-query\"):\n            response = self.get_success_response(self.org.slug, status_code=201, **payload)\n        data_export = ExportedData.objects.get(id=response.data[\"id\"])\n        query_info = data_export.query_info\n        assert parse_datetime_string(query_info[\"start\"]) == parse_datetime_string(\n            \"2020-05-12T14:00:00\"\n        )\n        assert parse_datetime_string(query_info[\"end\"]) == parse_datetime_string(\n            \"2020-05-14T14:00:00\"\n        )\n        assert \"statsPeriod\" not in query_info\n        assert \"statsPeriodStart\" not in query_info\n        assert \"statsPeriodSEnd\" not in query_info\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 166,
        "n_words": 49,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 114,
        "n_ast_nodes": 205,
        "n_identifiers": 18,
        "d_id": 19764,
        "documentation": {
            "docstring": "\n        Ensures that statsPeriodStart and statsPeriodEnd is converted to start/end.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 203593,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/auth/admin.py",
        "file_name": "admin.py",
        "fun_name": "response_add",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def response_add(self, request, obj, post_url_continue=None):\n        \n        # We should allow further modification of the user just added i.e. the\n        # 'Save' button should behave like the 'Save and continue editing'\n        # button except in two scenarios:\n        # * The user has pressed the 'Save and add another' button\n        # * We are adding a user in a popup\n        if \"_addanother\" not in request.POST and IS_POPUP_VAR not in request.POST:\n            request.POST = request.POST.copy()\n            request.POST[\"_continue\"] = 1\n        return super().response_add(request, obj, post_url_continue)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 155,
        "n_words": 77,
        "vocab_size": 52,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 61,
        "n_ast_nodes": 102,
        "n_identifiers": 9,
        "d_id": 50467,
        "documentation": {
            "docstring": "\n        Determine the HttpResponse for the add_view stage. It mostly defers to\n        its superclass implementation but is customized because the User model\n        has a slightly different workflow.\n        ",
            "n_words": 26,
            "vocab_size": 24,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 296690,
        "commit_id": "b0ed42a5a58976ebe82b5bbbb60c499648a1718b",
        "repo": "core",
        "path": "tests/components/daikin/test_temperature_format.py",
        "file_name": "test_temperature_format.py",
        "fun_name": "test_decimal_conversion_more_digits",
        "commit_message": "Fix #69952: Daikin AC Temperature jumps after being set (#70326)",
        "code": "def test_decimal_conversion_more_digits():\n    \n    formatted = format_target_temperature(\"16.09\")\n    assert formatted == \"16.1\"\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 18,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 15,
        "n_ast_nodes": 32,
        "n_identifiers": 3,
        "d_id": 95665,
        "documentation": {
            "docstring": "Check at most 1 decimal is kept when target temp is a decimal with more than 1 decimal.",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 70608,
        "commit_id": "60ba39ffb5ec6d760efa6e2ecbff7ede53b12464",
        "repo": "wagtail",
        "path": "wagtail/admin/views/workflows.py",
        "file_name": "workflows.py",
        "fun_name": "get_task_chosen_response",
        "commit_message": "replace get_task_result_data helper with more useful one get_task_chosen_response",
        "code": "def get_task_chosen_response(request, task):\n    \n    result_data = {\n        'id': task.id,\n        'name': task.name,\n        'edit_url': reverse('wagtailadmin_workflows:edit_task', args=[task.id]),\n    }\n    return render_modal_workflow(\n        request, None, None,\n        None, json_data={'step': 'task_chosen', 'result': result_data}\n    )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 75,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 62,
        "n_ast_nodes": 103,
        "n_identifiers": 10,
        "d_id": 15531,
        "documentation": {
            "docstring": "\n    helper function: given a task, return the response indicating that it has been chosen\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 176513,
        "commit_id": "c3e1e7f4c6a4edb968494cd4775574ad26f2a96b",
        "repo": "networkx",
        "path": "networkx/algorithms/matching.py",
        "file_name": "matching.py",
        "fun_name": "min_weight_matching",
        "commit_message": "Fix min_weight_matching to convert edge weights without reciprocal (#5394)\n\n* Add test and then fix code and docs\r\n\r\n* Correct and improve docs. Change 1e-6 to 1 to maintain integers.\r\n\r\nInclude argument in docstring for why adding the 1 doesn't impact the min",
        "code": "def min_weight_matching(G, maxcardinality=None, weight=\"weight\"):\n    \n    if maxcardinality not in (True, None):\n        raise nx.NetworkXError(\n            \"The argument maxcardinality does not make sense \"\n            \"in the context of minimum weight matchings.\"\n            \"It is deprecated and will be removed in v3.0.\"\n        )\n    if len(G.edges) == 0:\n        return max_weight_matching(G, maxcardinality=True, weight=weight)\n    G_edges = G.edges(data=weight, default=1)\n    max_weight = 1 + max(w for _, _, w in G_edges)\n    InvG = nx.Graph()\n    edges = ((u, v, max_weight - w) for u, v, w in G_edges)\n    InvG.add_weighted_edges_from(edges, weight=weight)\n    return max_weight_matching(InvG, maxcardinality=True, weight=weight)\n\n\n@not_implemented_for(\"multigraph\")\n@not_implemented_for(\"directed\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"multigraph\")\n@not_implemented_for(\"directed\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 163,
        "n_words": 84,
        "vocab_size": 65,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 137,
        "n_ast_nodes": 231,
        "n_identifiers": 22,
        "d_id": 41940,
        "documentation": {
            "docstring": "Computing a minimum-weight maximal matching of G.\n\n    Use the maximum-weight algorithm with edge weights subtracted\n    from the maximum weight of all edges.\n\n    A matching is a subset of edges in which no node occurs more than once.\n    The weight of a matching is the sum of the weights of its edges.\n    A maximal matching cannot add more edges and still be a matching.\n    The cardinality of a matching is the number of matched edges.\n\n    This method replaces the edge weights with 1 plus the maximum edge weight\n    minus the original edge weight.\n\n    new_weight = (max_weight + 1) - edge_weight\n\n    then runs :func:`max_weight_matching` with the new weights.\n    The max weight matching with these new weights corresponds\n    to the min weight matching using the original weights.\n    Adding 1 to the max edge weight keeps all edge weights positive\n    and as integers if they started as integers.\n\n    You might worry that adding 1 to each weight would make the algorithm\n    favor matchings with more edges. But we use the parameter\n    `maxcardinality=True` in `max_weight_matching` to ensure that the\n    number of edges in the competing matchings are the same and thus\n    the optimum does not change due to changes in the number of edges.\n\n    Read the documentation of `max_weight_matching` for more information.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n      Undirected graph\n\n    maxcardinality: bool\n        .. deprecated:: 2.8\n            The `maxcardinality` parameter will be removed in v3.0.\n            It doesn't make sense to set it to False when looking for\n            a min weight matching because then we just return no edges.\n\n        If maxcardinality is True, compute the maximum-cardinality matching\n        with minimum weight among all maximum-cardinality matchings.\n\n    weight: string, optional (default='weight')\n       Edge data key corresponding to the edge weight.\n       If key not found, uses 1 as weight.\n\n    Returns\n    -------\n    matching : set\n        A minimal weight matching of the graph.\n\n    See Also\n    --------\n    max_weight_matching\n    ",
            "n_words": 302,
            "vocab_size": 163,
            "n_whitespaces": 476,
            "language": "en"
        }
    },
    {
        "id": 216056,
        "commit_id": "a5679caf65c7c79cd72841b6e5793b9b693744c9",
        "repo": "salt",
        "path": "salt/cloud/clouds/proxmox.py",
        "file_name": "proxmox.py",
        "fun_name": "_find_agent_ip",
        "commit_message": "Add support for get IP-address from agent",
        "code": "def _find_agent_ip(vm_, vmid):\n    \n\n    # This functionality is only available on qemu\n    if not vm_.get(\"technology\") == \"qemu\":\n        log.warning(\"Find agent IP is only available under `qemu`\")\n        return\n\n    # Create an empty list of IP-addresses:\n    ips = []\n\n    endpoint = \"nodes/{}/qemu/{}/agent/network-get-interfaces\".format(vm_[\"host\"], vmid)\n    interfaces = query(\"get\", endpoint)\n\n    # If we get a result from the agent, parse it\n    for interface in interfaces[\"result\"]:\n\n        # Skip interface if hardware-address is 00:00:00:00:00:00 (loopback interface)\n        if str(interface.get(\"hardware-address\")) == \"00:00:00:00:00:00\":\n            continue\n\n        # Skip entries without ip-addresses information\n        if \"ip-addresses\" not in interface:\n            continue\n\n        for if_addr in interface[\"ip-addresses\"]:\n            ip_addr = if_addr.get(\"ip-address\")\n            if ip_addr is not None:\n                ips.append(str(ip_addr))\n\n    if len(ips) > 0:\n        return preferred_ip(vm_, ips)\n\n    raise SaltCloudExecutionFailure\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 254,
        "n_words": 106,
        "vocab_size": 78,
        "complexity": 8,
        "nloc": 19,
        "token_counts": 128,
        "n_ast_nodes": 231,
        "n_identifiers": 19,
        "d_id": 54362,
        "documentation": {
            "docstring": "\n    If VM is started we would return the IP-addresses that are returned by the qemu agent on the VM.\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 215737,
        "commit_id": "3bb43882e727b1d36abe2e501759c9c5e9048ecf",
        "repo": "salt",
        "path": "tests/pytests/unit/utils/win_dacl/test_get_name.py",
        "file_name": "test_get_name.py",
        "fun_name": "test_get_name_error",
        "commit_message": "Add tests, migrate some tests to pytest",
        "code": "def test_get_name_error():\n    \n    test_sid = \"S-1-2-3-4\"\n    sid_obj = win32security.ConvertStringSidToSid(test_sid)\n    with pytest.raises(salt.exceptions.CommandExecutionError) as exc:\n        salt.utils.win_dacl.get_name(sid_obj)\n    assert \"No mapping between account names\" in exc.value.message\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 43,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 48,
        "n_ast_nodes": 87,
        "n_identifiers": 16,
        "d_id": 54131,
        "documentation": {
            "docstring": "\n    Test get_name with an un mapped SID, should throw a CommandExecutionError\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 205195,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/sqlite3/introspection.py",
        "file_name": "introspection.py",
        "fun_name": "get_relations",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_relations(self, cursor, table_name):\n        \n        cursor.execute(\n            \"PRAGMA foreign_key_list(%s)\" % self.connection.ops.quote_name(table_name)\n        )\n        return {\n            column_name: (ref_column_name, ref_table_name)\n            for _, _, ref_table_name, column_name, ref_column_name, *_ in cursor.fetchall()\n        }\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 93,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 56,
        "n_ast_nodes": 85,
        "n_identifiers": 13,
        "d_id": 51029,
        "documentation": {
            "docstring": "\n        Return a dictionary of {column_name: (ref_column_name, ref_table_name)}\n        representing all foreign keys in the given table.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 247442,
        "commit_id": "26211fec24d8d0a967de33147e148166359ec8cb",
        "repo": "synapse",
        "path": "synapse/storage/background_updates.py",
        "file_name": "background_updates.py",
        "fun_name": "average_items_per_ms",
        "commit_message": "Fix a bug in background updates wherein background updates are never run using the default batch size (#12157)",
        "code": "def average_items_per_ms(self) -> Optional[float]:\n        \n        # We want to return None if this is the first background update item\n        if self.total_item_count == 0:\n            return None\n        # Avoid dividing by zero\n        elif self.avg_duration_ms == 0:\n            return 0\n        else:\n            # Use the exponential moving average so that we can adapt to\n            # changes in how long the update process takes.\n            return float(self.avg_item_count) / float(self.avg_duration_ms)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 158,
        "n_words": 61,
        "vocab_size": 47,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 45,
        "n_ast_nodes": 78,
        "n_identifiers": 7,
        "d_id": 71674,
        "documentation": {
            "docstring": "An estimate of how long it takes to do a single update.\n        Returns:\n            A duration in ms as a float\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 307669,
        "commit_id": "26251895295d74fcd2c73e37804c23675c433247",
        "repo": "core",
        "path": "homeassistant/components/forked_daapd/media_player.py",
        "file_name": "media_player.py",
        "fun_name": "_pause_and_wait_for_callback",
        "commit_message": "Use async_timeout in forked_daapd (#78451)",
        "code": "async def _pause_and_wait_for_callback(self):\n        \n        self._pause_requested = True\n        await self.async_media_pause()\n        try:",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "async def _pause_and_wait_for_callback(self):\n        \"\"\"Send pause and wait for the pause callback to be received.\"\"\"\n        self._pause_requested = True\n        await self.async_media_pause()\n        try:",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 37,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 53,
        "n_ast_nodes": 34,
        "n_identifiers": 4,
        "d_id": 106437,
        "documentation": {
            "docstring": "Send pause and wait for the pause callback to be received.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 212865,
        "commit_id": "07bb93d47f01468660a01f42150e87e5cb08d546",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "set_options",
        "commit_message": "Addition of tooltip_offset parm to set_options call (major hack to get around 8.6.12 problem). Backed out the  experiments to try and fix new problem with Ubuntu",
        "code": "def set_options(icon=None, button_color=None, element_size=(None, None), button_element_size=(None, None),\n                margins=(None, None),\n                element_padding=(None, None), auto_size_text=None, auto_size_buttons=None, font=None, border_width=None,\n                slider_border_width=None, slider_relief=None, slider_orientation=None,\n                autoclose_time=None, message_box_line_width=None,\n                progress_meter_border_depth=None, progress_meter_style=None,\n                progress_meter_relief=None, progress_meter_color=None, progress_meter_size=None,\n                text_justification=None, background_color=None, element_background_color=None,\n                text_element_background_color=None, input_elements_background_color=None, input_text_color=None,\n                scrollbar_color=None, text_color=None, element_text_color=None, debug_win_size=(None, None),\n                window_location=(None, None), error_button_color=(None, None), tooltip_time=None, tooltip_font=None, use_ttk_buttons=None, ttk_theme=None,\n                suppress_error_popups=None, suppress_raise_key_errors=None, suppress_key_guessing=None,warn_button_key_duplicates=False, enable_treeview_869_patch=None,\n                enable_mac_notitlebar_patch=None, use_custom_titlebar=None, titlebar_background_color=None, titlebar_text_color=None, titlebar_font=None,\n                titlebar_icon=None, user_settings_path=None, pysimplegui_settings_path=None, pysimplegui_settings_filename=None, keep_on_top=None, dpi_awareness=None, scaling=None, disable_modal_windows=None, tooltip_offset=(None, None)):\n    \n\n    global DEFAULT_ELEMENT_SIZE\n    global DEFAULT_BUTTON_ELEMENT_SIZE\n    global DEFAULT_MARGINS  # Margins for each LEFT/RIGHT margin is first term\n    global DEFAULT_ELEMENT_PADDING  # Padding between elements (row, col) in pixels\n    global DEFAULT_AUTOSIZE_TEXT\n    global DEFAULT_AUTOSIZE_BUTTONS\n    global DEFAULT_FONT\n    global DEFAULT_BORDER_WIDTH\n    global DEFAULT_AUTOCLOSE_TIME\n    global DEFAULT_BUTTON_COLOR\n    global MESSAGE_BOX_LINE_WIDTH\n    global DEFAULT_PROGRESS_BAR_BORDER_WIDTH\n    global DEFAULT_PROGRESS_BAR_STYLE\n    global DEFAULT_PROGRESS_BAR_RELIEF\n    global DEFAULT_PROGRESS_BAR_COLOR\n    global DEFAULT_PROGRESS_BAR_SIZE\n    global DEFAULT_TEXT_JUSTIFICATION\n    global DEFAULT_DEBUG_WINDOW_SIZE\n    global DEFAULT_SLIDER_BORDER_WIDTH\n    global DEFAULT_SLIDER_RELIEF\n    global DEFAULT_SLIDER_ORIENTATION\n    global DEFAULT_BACKGROUND_COLOR\n    global DEFAULT_INPUT_ELEMENTS_COLOR\n    global DEFAULT_ELEMENT_BACKGROUND_COLOR\n    global DEFAULT_TEXT_ELEMENT_BACKGROUND_COLOR\n    global DEFAULT_SCROLLBAR_COLOR\n    global DEFAULT_TEXT_COLOR\n    global DEFAULT_WINDOW_LOCATION\n    global DEFAULT_ELEMENT_TEXT_COLOR\n    global DEFAULT_INPUT_TEXT_COLOR\n    global DEFAULT_TOOLTIP_TIME\n    global DEFAULT_ERROR_BUTTON_COLOR\n    global DEFAULT_TTK_THEME\n    global USE_TTK_BUTTONS\n    global TOOLTIP_FONT\n    global SUPPRESS_ERROR_POPUPS\n    global SUPPRESS_RAISE_KEY_ERRORS\n    global SUPPRESS_KEY_GUESSING\n    global WARN_DUPLICATE_BUTTON_KEY_ERRORS\n    global ENABLE_TREEVIEW_869_PATCH\n    global ENABLE_MAC_NOTITLEBAR_PATCH\n    global USE_CUSTOM_TITLEBAR\n    global CUSTOM_TITLEBAR_BACKGROUND_COLOR\n    global CUSTOM_TITLEBAR_TEXT_COLOR\n    global CUSTOM_TITLEBAR_ICON\n    global CUSTOM_TITLEBAR_FONT\n    global DEFAULT_USER_SETTINGS_PATH\n    global DEFAULT_USER_SETTINGS_PYSIMPLEGUI_PATH\n    global DEFAULT_USER_SETTINGS_PYSIMPLEGUI_FILENAME\n    global DEFAULT_KEEP_ON_TOP\n    global DEFAULT_SCALING\n    global DEFAULT_MODAL_WINDOWS_ENABLED\n    global DEFAULT_TOOLTIP_OFFSET\n    global _pysimplegui_user_settings\n    # global _my_windows\n\n    if icon:\n        Window._user_defined_icon = icon\n        # _my_windows._user_defined_icon = icon\n\n    if button_color != None:\n        if button_color == COLOR_SYSTEM_DEFAULT:\n            DEFAULT_BUTTON_COLOR = (COLOR_SYSTEM_DEFAULT, COLOR_SYSTEM_DEFAULT)\n        else:\n            DEFAULT_BUTTON_COLOR = button_color\n\n    if element_size != (None, None):\n        DEFAULT_ELEMENT_SIZE = element_size\n\n    if button_element_size != (None, None):\n        DEFAULT_BUTTON_ELEMENT_SIZE = button_element_size\n\n    if margins != (None, None):\n        DEFAULT_MARGINS = margins\n\n    if element_padding != (None, None):\n        DEFAULT_ELEMENT_PADDING = element_padding\n\n    if auto_size_text != None:\n        DEFAULT_AUTOSIZE_TEXT = auto_size_text\n\n    if auto_size_buttons != None:\n        DEFAULT_AUTOSIZE_BUTTONS = auto_size_buttons\n\n    if font != None:\n        DEFAULT_FONT = font\n\n    if border_width != None:\n        DEFAULT_BORDER_WIDTH = border_width\n\n    if autoclose_time != None:\n        DEFAULT_AUTOCLOSE_TIME = autoclose_time\n\n    if message_box_line_width != None:\n        MESSAGE_BOX_LINE_WIDTH = message_box_line_width\n\n    if progress_meter_border_depth != None:\n        DEFAULT_PROGRESS_BAR_BORDER_WIDTH = progress_meter_border_depth\n\n    if progress_meter_style != None:\n        warnings.warn('You can no longer set a progress bar style. All ttk styles must be the same for the window', UserWarning)\n        # DEFAULT_PROGRESS_BAR_STYLE = progress_meter_style\n\n    if progress_meter_relief != None:\n        DEFAULT_PROGRESS_BAR_RELIEF = progress_meter_relief\n\n    if progress_meter_color != None:\n        DEFAULT_PROGRESS_BAR_COLOR = progress_meter_color\n\n    if progress_meter_size != None:\n        DEFAULT_PROGRESS_BAR_SIZE = progress_meter_size\n\n    if slider_border_width != None:\n        DEFAULT_SLIDER_BORDER_WIDTH = slider_border_width\n\n    if slider_orientation != None:\n        DEFAULT_SLIDER_ORIENTATION = slider_orientation\n\n    if slider_relief != None:\n        DEFAULT_SLIDER_RELIEF = slider_relief\n\n    if text_justification != None:\n        DEFAULT_TEXT_JUSTIFICATION = text_justification\n\n    if background_color != None:\n        DEFAULT_BACKGROUND_COLOR = background_color\n\n    if text_element_background_color != None:\n        DEFAULT_TEXT_ELEMENT_BACKGROUND_COLOR = text_element_background_color\n\n    if input_elements_background_color != None:\n        DEFAULT_INPUT_ELEMENTS_COLOR = input_elements_background_color\n\n    if element_background_color != None:\n        DEFAULT_ELEMENT_BACKGROUND_COLOR = element_background_color\n\n    if window_location != (None, None):\n        DEFAULT_WINDOW_LOCATION = window_location\n\n    if debug_win_size != (None, None):\n        DEFAULT_DEBUG_WINDOW_SIZE = debug_win_size\n\n    if text_color != None:\n        DEFAULT_TEXT_COLOR = text_color\n\n    if scrollbar_color != None:\n        DEFAULT_SCROLLBAR_COLOR = scrollbar_color\n\n    if element_text_color != None:\n        DEFAULT_ELEMENT_TEXT_COLOR = element_text_color\n\n    if input_text_color is not None:\n        DEFAULT_INPUT_TEXT_COLOR = input_text_color\n\n    if tooltip_time is not None:\n        DEFAULT_TOOLTIP_TIME = tooltip_time\n\n    if error_button_color != (None, None):\n        DEFAULT_ERROR_BUTTON_COLOR = error_button_color\n\n    if ttk_theme is not None:\n        DEFAULT_TTK_THEME = ttk_theme\n\n    if use_ttk_buttons is not None:\n        USE_TTK_BUTTONS = use_ttk_buttons\n\n    if tooltip_font is not None:\n        TOOLTIP_FONT = tooltip_font\n\n    if suppress_error_popups is not None:\n        SUPPRESS_ERROR_POPUPS = suppress_error_popups\n\n    if suppress_raise_key_errors is not None:\n        SUPPRESS_RAISE_KEY_ERRORS = suppress_raise_key_errors\n\n    if suppress_key_guessing is not None:\n        SUPPRESS_KEY_GUESSING = suppress_key_guessing\n\n    if warn_button_key_duplicates is not None:\n        WARN_DUPLICATE_BUTTON_KEY_ERRORS = warn_button_key_duplicates\n\n    if enable_treeview_869_patch is not None:\n        ENABLE_TREEVIEW_869_PATCH = enable_treeview_869_patch\n\n    if enable_mac_notitlebar_patch is not None:\n        ENABLE_MAC_NOTITLEBAR_PATCH = enable_mac_notitlebar_patch\n\n    if use_custom_titlebar is not None:\n        USE_CUSTOM_TITLEBAR = use_custom_titlebar\n\n    if titlebar_background_color is not None:\n        CUSTOM_TITLEBAR_BACKGROUND_COLOR = titlebar_background_color\n\n    if titlebar_text_color is not None:\n        CUSTOM_TITLEBAR_TEXT_COLOR = titlebar_text_color\n\n    if titlebar_font is not None:\n        CUSTOM_TITLEBAR_FONT = titlebar_font\n\n    if titlebar_icon is not None:\n        CUSTOM_TITLEBAR_ICON = titlebar_icon\n\n    if user_settings_path is not None:\n        DEFAULT_USER_SETTINGS_PATH = user_settings_path\n\n    if pysimplegui_settings_path is not None:\n        DEFAULT_USER_SETTINGS_PYSIMPLEGUI_PATH = pysimplegui_settings_path\n\n    if pysimplegui_settings_filename is not None:\n        DEFAULT_USER_SETTINGS_PYSIMPLEGUI_FILENAME = pysimplegui_settings_filename\n\n    if pysimplegui_settings_filename is not None or pysimplegui_settings_filename is not None:\n        _pysimplegui_user_settings = UserSettings(filename=DEFAULT_USER_SETTINGS_PYSIMPLEGUI_FILENAME,\n                                                  path=DEFAULT_USER_SETTINGS_PYSIMPLEGUI_PATH)\n\n    if keep_on_top is not None:\n        DEFAULT_KEEP_ON_TOP = keep_on_top\n\n    if dpi_awareness is True:\n        if running_windows():\n            if platform.release() == \"7\":\n                ctypes.windll.user32.SetProcessDPIAware()\n            elif platform.release() == \"8\" or platform.release() == \"10\":\n                ctypes.windll.shcore.SetProcessDpiAwareness(1)\n\n    if scaling is not None:\n        DEFAULT_SCALING = scaling\n\n    if disable_modal_windows is not None:\n        DEFAULT_MODAL_WINDOWS_ENABLED = not disable_modal_windows\n\n    if tooltip_offset != (None, None):\n        DEFAULT_TOOLTIP_OFFSET = tooltip_offset\n\n    return True\n\n\n# ----------------------------------------------------------------- #\n\n# .########.##.....##.########.##.....##.########..######.\n# ....##....##.....##.##.......###...###.##.......##....##\n# ....##....##.....##.##.......####.####.##.......##......\n# ....##....#########.######...##.###.##.######....######.\n# ....##....##.....##.##.......##.....##.##.............##\n# ....##....##.....##.##.......##.....##.##.......##....##\n# ....##....##.....##.########.##.....##.########..######.\n\n# ----------------------------------------------------------------- #\n\n# The official Theme code\n\n#################### ChangeLookAndFeel #######################\n# Predefined settings that will change the colors and styles #\n# of the elements.                                           #\n##############################################################\nLOOK_AND_FEEL_TABLE = {\n    \"SystemDefault\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT, \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT,\n                      \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": OFFICIAL_PYSIMPLEGUI_BUTTON_COLOR, \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1,\n                      \"SLIDER_DEPTH\": 1, \"PROGRESS_DEPTH\": 0, },\n    \"SystemDefaultForReal\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT,\n                             \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT, \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": COLOR_SYSTEM_DEFAULT,\n                             \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1, \"PROGRESS_DEPTH\": 0, },\n    \"SystemDefault1\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT, \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT,\n                       \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": COLOR_SYSTEM_DEFAULT, \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1,\n                       \"PROGRESS_DEPTH\": 0, },\n    \"Material1\": {\"BACKGROUND\": \"#E3F2FD\", \"TEXT\": \"#000000\", \"INPUT\": \"#86A8FF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#86A8FF\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#5079D3\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 0, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"ACCENT1\": \"#FF0266\", \"ACCENT2\": \"#FF5C93\", \"ACCENT3\": \"#C5003C\", },\n    \"Material2\": {\"BACKGROUND\": \"#FAFAFA\", \"TEXT\": \"#000000\", \"INPUT\": \"#004EA1\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#5EA7FF\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#0079D3\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 0, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"ACCENT1\": \"#FF0266\", \"ACCENT2\": \"#FF5C93\", \"ACCENT3\": \"#C5003C\", },\n    \"Reddit\": {\"BACKGROUND\": \"#ffffff\", \"TEXT\": \"#1a1a1b\", \"INPUT\": \"#dae0e6\", \"TEXT_INPUT\": \"#222222\", \"SCROLL\": \"#a5a4a4\", \"BUTTON\": (\"#FFFFFF\", \"#0079d3\"),\n               \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, \"ACCENT1\": \"#ff5414\", \"ACCENT2\": \"#33a8ff\",\n               \"ACCENT3\": \"#dbf0ff\", },\n    \"Topanga\": {\"BACKGROUND\": \"#282923\", \"TEXT\": \"#E7DB74\", \"INPUT\": \"#393a32\", \"TEXT_INPUT\": \"#E7C855\", \"SCROLL\": \"#E7C855\", \"BUTTON\": (\"#E7C855\", \"#284B5A\"),\n                \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, \"ACCENT1\": \"#c15226\", \"ACCENT2\": \"#7a4d5f\",\n                \"ACCENT3\": \"#889743\", },\n    \"GreenTan\": {\"BACKGROUND\": \"#9FB8AD\", \"TEXT\": '#000000', \"INPUT\": \"#F7F3EC\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#F7F3EC\", \"BUTTON\": (\"#FFFFFF\", \"#475841\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Dark\": {\"BACKGROUND\": \"#404040\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#4D4D4D\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#707070\", \"BUTTON\": (\"#FFFFFF\", \"#004F00\"),\n             \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightGreen\": {\"BACKGROUND\": \"#B7CECE\", \"TEXT\": \"#000000\", \"INPUT\": \"#FDFFF7\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#FDFFF7\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#658268\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"ACCENT1\": \"#76506d\",\n                   \"ACCENT2\": \"#5148f1\", \"ACCENT3\": \"#0a1c84\", \"PROGRESS_DEPTH\": 0, },\n    \"Dark2\": {\"BACKGROUND\": \"#404040\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#FFFFFF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#707070\", \"BUTTON\": (\"#FFFFFF\", \"#004F00\"),\n              \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Black\": {\"BACKGROUND\": \"#000000\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#4D4D4D\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#707070\", \"BUTTON\": (\"#000000\", \"#FFFFFF\"),\n              \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Tan\": {\"BACKGROUND\": \"#fdf6e3\", \"TEXT\": \"#268bd1\", \"INPUT\": \"#eee8d5\", \"TEXT_INPUT\": \"#6c71c3\", \"SCROLL\": \"#eee8d5\", \"BUTTON\": (\"#FFFFFF\", \"#063542\"),\n            \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"TanBlue\": {\"BACKGROUND\": \"#e5dece\", \"TEXT\": \"#063289\", \"INPUT\": \"#f9f8f4\", \"TEXT_INPUT\": \"#242834\", \"SCROLL\": \"#eee8d5\", \"BUTTON\": (\"#FFFFFF\", \"#063289\"),\n                \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkTanBlue\": {\"BACKGROUND\": \"#242834\", \"TEXT\": \"#dfe6f8\", \"INPUT\": \"#97755c\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#a9afbb\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#063289\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkAmber\": {\"BACKGROUND\": \"#2c2825\", \"TEXT\": \"#fdcb52\", \"INPUT\": \"#705e52\", \"TEXT_INPUT\": \"#fdcb52\", \"SCROLL\": \"#705e52\",\n                  \"BUTTON\": (\"#000000\", \"#fdcb52\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlue\": {\"BACKGROUND\": \"#1a2835\", \"TEXT\": \"#d1ecff\", \"INPUT\": \"#335267\", \"TEXT_INPUT\": \"#acc2d0\", \"SCROLL\": \"#1b6497\", \"BUTTON\": (\"#000000\", \"#fafaf8\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Reds\": {\"BACKGROUND\": \"#280001\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#d8d584\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#763e00\", \"BUTTON\": (\"#000000\", \"#daad28\"),\n             \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Green\": {\"BACKGROUND\": \"#82a459\", \"TEXT\": \"#000000\", \"INPUT\": \"#d8d584\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e3ecf3\", \"BUTTON\": (\"#FFFFFF\", \"#517239\"),\n              \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"BluePurple\": {\"BACKGROUND\": \"#A5CADD\", \"TEXT\": \"#6E266E\", \"INPUT\": \"#E0F5FF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#E0F5FF\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#303952\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Purple\": {\"BACKGROUND\": \"#B0AAC2\", \"TEXT\": \"#000000\", \"INPUT\": \"#F2EFE8\", \"SCROLL\": \"#F2EFE8\", \"TEXT_INPUT\": \"#000000\", \"BUTTON\": (\"#000000\", \"#C2D4D8\"),\n               \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"BlueMono\": {\"BACKGROUND\": \"#AAB6D3\", \"TEXT\": \"#000000\", \"INPUT\": \"#F1F4FC\", \"SCROLL\": \"#F1F4FC\", \"TEXT_INPUT\": \"#000000\", \"BUTTON\": (\"#FFFFFF\", \"#7186C7\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"GreenMono\": {\"BACKGROUND\": \"#A8C1B4\", \"TEXT\": \"#000000\", \"INPUT\": \"#DDE0DE\", \"SCROLL\": \"#E3E3E3\", \"TEXT_INPUT\": \"#000000\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#6D9F85\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"BrownBlue\": {\"BACKGROUND\": \"#64778d\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#f0f3f7\", \"SCROLL\": \"#A6B2BE\", \"TEXT_INPUT\": \"#000000\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#283b5b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"BrightColors\": {\"BACKGROUND\": \"#b4ffb4\", \"TEXT\": \"#000000\", \"INPUT\": \"#ffff64\", \"SCROLL\": \"#ffb482\", \"TEXT_INPUT\": \"#000000\",\n                     \"BUTTON\": (\"#000000\", \"#ffa0dc\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"NeutralBlue\": {\"BACKGROUND\": \"#92aa9d\", \"TEXT\": \"#000000\", \"INPUT\": \"#fcfff6\", \"SCROLL\": \"#fcfff6\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#000000\", \"#d0dbbd\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Kayak\": {\"BACKGROUND\": \"#a7ad7f\", \"TEXT\": \"#000000\", \"INPUT\": \"#e6d3a8\", \"SCROLL\": \"#e6d3a8\", \"TEXT_INPUT\": \"#000000\", \"BUTTON\": (\"#FFFFFF\", \"#5d907d\"),\n              \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"SandyBeach\": {\"BACKGROUND\": \"#efeccb\", \"TEXT\": \"#012f2f\", \"INPUT\": \"#e6d3a8\", \"SCROLL\": \"#e6d3a8\", \"TEXT_INPUT\": \"#012f2f\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#046380\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"TealMono\": {\"BACKGROUND\": \"#a8cfdd\", \"TEXT\": \"#000000\", \"INPUT\": \"#dfedf2\", \"SCROLL\": \"#dfedf2\", \"TEXT_INPUT\": \"#000000\", \"BUTTON\": (\"#FFFFFF\", \"#183440\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"Default\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT, \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT,\n                \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": OFFICIAL_PYSIMPLEGUI_BUTTON_COLOR, \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1,\n                \"PROGRESS_DEPTH\": 0, },\n    \"Default1\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT, \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT,\n                 \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": COLOR_SYSTEM_DEFAULT, \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1,\n                 \"PROGRESS_DEPTH\": 0, },\n    \"DefaultNoMoreNagging\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT,\n                             \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT, \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": OFFICIAL_PYSIMPLEGUI_BUTTON_COLOR,\n                             \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1, \"PROGRESS_DEPTH\": 0, },\n    \"GrayGrayGray\": {\"BACKGROUND\": COLOR_SYSTEM_DEFAULT, \"TEXT\": COLOR_SYSTEM_DEFAULT, \"INPUT\": COLOR_SYSTEM_DEFAULT, \"TEXT_INPUT\": COLOR_SYSTEM_DEFAULT,\n                     \"SCROLL\": COLOR_SYSTEM_DEFAULT, \"BUTTON\": COLOR_SYSTEM_DEFAULT, \"PROGRESS\": COLOR_SYSTEM_DEFAULT, \"BORDER\": 1, \"SLIDER_DEPTH\": 1,\n                     \"PROGRESS_DEPTH\": 0, },\n    \"LightBlue\": {\"BACKGROUND\": \"#E3F2FD\", \"TEXT\": \"#000000\", \"INPUT\": \"#86A8FF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#86A8FF\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#5079D3\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 0, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"ACCENT1\": \"#FF0266\", \"ACCENT2\": \"#FF5C93\", \"ACCENT3\": \"#C5003C\", },\n    \"LightGrey\": {\"BACKGROUND\": \"#FAFAFA\", \"TEXT\": \"#000000\", \"INPUT\": \"#004EA1\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#5EA7FF\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#0079D3\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 0, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"ACCENT1\": \"#FF0266\", \"ACCENT2\": \"#FF5C93\", \"ACCENT3\": \"#C5003C\", },\n    \"LightGrey1\": {\"BACKGROUND\": \"#ffffff\", \"TEXT\": \"#1a1a1b\", \"INPUT\": \"#dae0e6\", \"TEXT_INPUT\": \"#222222\", \"SCROLL\": \"#a5a4a4\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#0079d3\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"ACCENT1\": \"#ff5414\", \"ACCENT2\": \"#33a8ff\", \"ACCENT3\": \"#dbf0ff\", },\n    \"DarkBrown\": {\"BACKGROUND\": \"#282923\", \"TEXT\": \"#E7DB74\", \"INPUT\": \"#393a32\", \"TEXT_INPUT\": \"#E7C855\", \"SCROLL\": \"#E7C855\",\n                  \"BUTTON\": (\"#E7C855\", \"#284B5A\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"ACCENT1\": \"#c15226\", \"ACCENT2\": \"#7a4d5f\", \"ACCENT3\": \"#889743\", },\n    \"LightGreen1\": {\"BACKGROUND\": \"#9FB8AD\", \"TEXT\": \"#000000\", \"INPUT\": \"#F7F3EC\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#F7F3EC\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#475841\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey\": {\"BACKGROUND\": \"#404040\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#4D4D4D\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#707070\", \"BUTTON\": (\"#FFFFFF\", \"#004F00\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightGreen2\": {\"BACKGROUND\": \"#B7CECE\", \"TEXT\": \"#000000\", \"INPUT\": \"#FDFFF7\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#FDFFF7\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#658268\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"ACCENT1\": \"#76506d\",\n                    \"ACCENT2\": \"#5148f1\", \"ACCENT3\": \"#0a1c84\", \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey1\": {\"BACKGROUND\": \"#404040\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#FFFFFF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#707070\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#004F00\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlack\": {\"BACKGROUND\": \"#000000\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#4D4D4D\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#707070\",\n                  \"BUTTON\": (\"#000000\", \"#FFFFFF\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBrown\": {\"BACKGROUND\": \"#fdf6e3\", \"TEXT\": \"#268bd1\", \"INPUT\": \"#eee8d5\", \"TEXT_INPUT\": \"#6c71c3\", \"SCROLL\": \"#eee8d5\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#063542\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBrown1\": {\"BACKGROUND\": \"#e5dece\", \"TEXT\": \"#063289\", \"INPUT\": \"#f9f8f4\", \"TEXT_INPUT\": \"#242834\", \"SCROLL\": \"#eee8d5\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#063289\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlue1\": {\"BACKGROUND\": \"#242834\", \"TEXT\": \"#dfe6f8\", \"INPUT\": \"#97755c\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#a9afbb\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#063289\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBrown1\": {\"BACKGROUND\": \"#2c2825\", \"TEXT\": \"#fdcb52\", \"INPUT\": \"#705e52\", \"TEXT_INPUT\": \"#fdcb52\", \"SCROLL\": \"#705e52\",\n                   \"BUTTON\": (\"#000000\", \"#fdcb52\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlue2\": {\"BACKGROUND\": \"#1a2835\", \"TEXT\": \"#d1ecff\", \"INPUT\": \"#335267\", \"TEXT_INPUT\": \"#acc2d0\", \"SCROLL\": \"#1b6497\",\n                  \"BUTTON\": (\"#000000\", \"#fafaf8\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBrown2\": {\"BACKGROUND\": \"#280001\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#d8d584\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#763e00\",\n                   \"BUTTON\": (\"#000000\", \"#daad28\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGreen\": {\"BACKGROUND\": \"#82a459\", \"TEXT\": \"#000000\", \"INPUT\": \"#d8d584\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e3ecf3\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#517239\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBlue1\": {\"BACKGROUND\": \"#A5CADD\", \"TEXT\": \"#6E266E\", \"INPUT\": \"#E0F5FF\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#E0F5FF\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#303952\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightPurple\": {\"BACKGROUND\": \"#B0AAC2\", \"TEXT\": \"#000000\", \"INPUT\": \"#F2EFE8\", \"SCROLL\": \"#F2EFE8\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#000000\", \"#C2D4D8\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBlue2\": {\"BACKGROUND\": \"#AAB6D3\", \"TEXT\": \"#000000\", \"INPUT\": \"#F1F4FC\", \"SCROLL\": \"#F1F4FC\", \"TEXT_INPUT\": \"#000000\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#7186C7\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightGreen3\": {\"BACKGROUND\": \"#A8C1B4\", \"TEXT\": \"#000000\", \"INPUT\": \"#DDE0DE\", \"SCROLL\": \"#E3E3E3\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#6D9F85\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlue3\": {\"BACKGROUND\": \"#64778d\", \"TEXT\": \"#FFFFFF\", \"INPUT\": \"#f0f3f7\", \"SCROLL\": \"#A6B2BE\", \"TEXT_INPUT\": \"#000000\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#283b5b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightGreen4\": {\"BACKGROUND\": \"#b4ffb4\", \"TEXT\": \"#000000\", \"INPUT\": \"#ffff64\", \"SCROLL\": \"#ffb482\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#000000\", \"#ffa0dc\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightGreen5\": {\"BACKGROUND\": \"#92aa9d\", \"TEXT\": \"#000000\", \"INPUT\": \"#fcfff6\", \"SCROLL\": \"#fcfff6\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#000000\", \"#d0dbbd\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBrown2\": {\"BACKGROUND\": \"#a7ad7f\", \"TEXT\": \"#000000\", \"INPUT\": \"#e6d3a8\", \"SCROLL\": \"#e6d3a8\", \"TEXT_INPUT\": \"#000000\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#5d907d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBrown3\": {\"BACKGROUND\": \"#efeccb\", \"TEXT\": \"#012f2f\", \"INPUT\": \"#e6d3a8\", \"SCROLL\": \"#e6d3a8\", \"TEXT_INPUT\": \"#012f2f\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#046380\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBlue3\": {\"BACKGROUND\": \"#a8cfdd\", \"TEXT\": \"#000000\", \"INPUT\": \"#dfedf2\", \"SCROLL\": \"#dfedf2\", \"TEXT_INPUT\": \"#000000\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#183440\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"LightBrown4\": {\"BACKGROUND\": \"#d7c79e\", \"TEXT\": \"#a35638\", \"INPUT\": \"#9dab86\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#a35638\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#a35638\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#a35638\", \"#9dab86\", \"#e08f62\", \"#d7c79e\"], },\n    \"DarkTeal\": {\"BACKGROUND\": \"#003f5c\", \"TEXT\": \"#fb5b5a\", \"INPUT\": \"#bc4873\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#bc4873\", \"BUTTON\": (\"#FFFFFF\", \"#fb5b5a\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                 \"COLOR_LIST\": [\"#003f5c\", \"#472b62\", \"#bc4873\", \"#fb5b5a\"], },\n    \"DarkPurple\": {\"BACKGROUND\": \"#472b62\", \"TEXT\": \"#fb5b5a\", \"INPUT\": \"#bc4873\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#bc4873\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#472b62\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#003f5c\", \"#472b62\", \"#bc4873\", \"#fb5b5a\"], },\n    \"LightGreen6\": {\"BACKGROUND\": \"#eafbea\", \"TEXT\": \"#1f6650\", \"INPUT\": \"#6f9a8d\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#1f6650\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#1f6650\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#1f6650\", \"#6f9a8d\", \"#ea5e5e\", \"#eafbea\"], },\n    \"DarkGrey2\": {\"BACKGROUND\": \"#2b2b28\", \"TEXT\": \"#f8f8f8\", \"INPUT\": \"#f1d6ab\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f1d6ab\",\n                  \"BUTTON\": (\"#2b2b28\", \"#e3b04b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#2b2b28\", \"#e3b04b\", \"#f1d6ab\", \"#f8f8f8\"], },\n    \"LightBrown6\": {\"BACKGROUND\": \"#f9b282\", \"TEXT\": \"#8f4426\", \"INPUT\": \"#de6b35\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#8f4426\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#8f4426\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#8f4426\", \"#de6b35\", \"#64ccda\", \"#f9b282\"], },\n    \"DarkTeal1\": {\"BACKGROUND\": \"#396362\", \"TEXT\": \"#ffe7d1\", \"INPUT\": \"#f6c89f\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f6c89f\",\n                  \"BUTTON\": (\"#ffe7d1\", \"#4b8e8d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#396362\", \"#4b8e8d\", \"#f6c89f\", \"#ffe7d1\"], },\n    \"LightBrown7\": {\"BACKGROUND\": \"#f6c89f\", \"TEXT\": \"#396362\", \"INPUT\": \"#4b8e8d\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#396362\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#396362\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#396362\", \"#4b8e8d\", \"#f6c89f\", \"#ffe7d1\"], },\n    \"DarkPurple1\": {\"BACKGROUND\": \"#0c093c\", \"TEXT\": \"#fad6d6\", \"INPUT\": \"#eea5f6\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#eea5f6\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#df42d1\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#0c093c\", \"#df42d1\", \"#eea5f6\", \"#fad6d6\"], },\n    \"DarkGrey3\": {\"BACKGROUND\": \"#211717\", \"TEXT\": \"#dfddc7\", \"INPUT\": \"#f58b54\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f58b54\",\n                  \"BUTTON\": (\"#dfddc7\", \"#a34a28\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#211717\", \"#a34a28\", \"#f58b54\", \"#dfddc7\"], },\n    \"LightBrown8\": {\"BACKGROUND\": \"#dfddc7\", \"TEXT\": \"#211717\", \"INPUT\": \"#a34a28\", \"TEXT_INPUT\": \"#dfddc7\", \"SCROLL\": \"#211717\",\n                    \"BUTTON\": (\"#dfddc7\", \"#a34a28\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#211717\", \"#a34a28\", \"#f58b54\", \"#dfddc7\"], },\n    \"DarkBlue4\": {\"BACKGROUND\": \"#494ca2\", \"TEXT\": \"#e3e7f1\", \"INPUT\": \"#c6cbef\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#c6cbef\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#8186d5\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#494ca2\", \"#8186d5\", \"#c6cbef\", \"#e3e7f1\"], },\n    \"LightBlue4\": {\"BACKGROUND\": \"#5c94bd\", \"TEXT\": \"#470938\", \"INPUT\": \"#1a3e59\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#470938\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#470938\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#470938\", \"#1a3e59\", \"#5c94bd\", \"#f2d6eb\"], },\n    \"DarkTeal2\": {\"BACKGROUND\": \"#394a6d\", \"TEXT\": \"#c0ffb3\", \"INPUT\": \"#52de97\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#52de97\",\n                  \"BUTTON\": (\"#c0ffb3\", \"#394a6d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#394a6d\", \"#3c9d9b\", \"#52de97\", \"#c0ffb3\"], },\n    \"DarkTeal3\": {\"BACKGROUND\": \"#3c9d9b\", \"TEXT\": \"#c0ffb3\", \"INPUT\": \"#52de97\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#52de97\",\n                  \"BUTTON\": (\"#c0ffb3\", \"#394a6d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#394a6d\", \"#3c9d9b\", \"#52de97\", \"#c0ffb3\"], },\n    \"DarkPurple5\": {\"BACKGROUND\": \"#730068\", \"TEXT\": \"#f6f078\", \"INPUT\": \"#01d28e\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#01d28e\",\n                    \"BUTTON\": (\"#f6f078\", \"#730068\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#730068\", \"#434982\", \"#01d28e\", \"#f6f078\"], },\n    \"DarkPurple2\": {\"BACKGROUND\": \"#202060\", \"TEXT\": \"#b030b0\", \"INPUT\": \"#602080\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#602080\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#202040\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#202040\", \"#202060\", \"#602080\", \"#b030b0\"], },\n    \"DarkBlue5\": {\"BACKGROUND\": \"#000272\", \"TEXT\": \"#ff6363\", \"INPUT\": \"#a32f80\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#a32f80\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#341677\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#000272\", \"#341677\", \"#a32f80\", \"#ff6363\"], },\n    \"LightGrey2\": {\"BACKGROUND\": \"#f6f6f6\", \"TEXT\": \"#420000\", \"INPUT\": \"#d4d7dd\", \"TEXT_INPUT\": \"#420000\", \"SCROLL\": \"#420000\",\n                   \"BUTTON\": (\"#420000\", \"#d4d7dd\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#420000\", \"#d4d7dd\", \"#eae9e9\", \"#f6f6f6\"], },\n    \"LightGrey3\": {\"BACKGROUND\": \"#eae9e9\", \"TEXT\": \"#420000\", \"INPUT\": \"#d4d7dd\", \"TEXT_INPUT\": \"#420000\", \"SCROLL\": \"#420000\",\n                   \"BUTTON\": (\"#420000\", \"#d4d7dd\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#420000\", \"#d4d7dd\", \"#eae9e9\", \"#f6f6f6\"], },\n    \"DarkBlue6\": {\"BACKGROUND\": \"#01024e\", \"TEXT\": \"#ff6464\", \"INPUT\": \"#8b4367\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#8b4367\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#543864\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#01024e\", \"#543864\", \"#8b4367\", \"#ff6464\"], },\n    \"DarkBlue7\": {\"BACKGROUND\": \"#241663\", \"TEXT\": \"#eae7af\", \"INPUT\": \"#a72693\", \"TEXT_INPUT\": \"#eae7af\", \"SCROLL\": \"#a72693\",\n                  \"BUTTON\": (\"#eae7af\", \"#160f30\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#160f30\", \"#241663\", \"#a72693\", \"#eae7af\"], },\n    \"LightBrown9\": {\"BACKGROUND\": \"#f6d365\", \"TEXT\": \"#3a1f5d\", \"INPUT\": \"#c83660\", \"TEXT_INPUT\": \"#f6d365\", \"SCROLL\": \"#3a1f5d\",\n                    \"BUTTON\": (\"#f6d365\", \"#c83660\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#3a1f5d\", \"#c83660\", \"#e15249\", \"#f6d365\"], },\n    \"DarkPurple3\": {\"BACKGROUND\": \"#6e2142\", \"TEXT\": \"#ffd692\", \"INPUT\": \"#e16363\", \"TEXT_INPUT\": \"#ffd692\", \"SCROLL\": \"#e16363\",\n                    \"BUTTON\": (\"#ffd692\", \"#943855\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#6e2142\", \"#943855\", \"#e16363\", \"#ffd692\"], },\n    \"LightBrown10\": {\"BACKGROUND\": \"#ffd692\", \"TEXT\": \"#6e2142\", \"INPUT\": \"#943855\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#6e2142\",\n                     \"BUTTON\": (\"#FFFFFF\", \"#6e2142\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                     \"COLOR_LIST\": [\"#6e2142\", \"#943855\", \"#e16363\", \"#ffd692\"], },\n    \"DarkPurple4\": {\"BACKGROUND\": \"#200f21\", \"TEXT\": \"#f638dc\", \"INPUT\": \"#5a3d5c\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#5a3d5c\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#382039\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#200f21\", \"#382039\", \"#5a3d5c\", \"#f638dc\"], },\n    \"LightBlue5\": {\"BACKGROUND\": \"#b2fcff\", \"TEXT\": \"#3e64ff\", \"INPUT\": \"#5edfff\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#3e64ff\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#3e64ff\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#3e64ff\", \"#5edfff\", \"#b2fcff\", \"#ecfcff\"], },\n    \"DarkTeal4\": {\"BACKGROUND\": \"#464159\", \"TEXT\": \"#c7f0db\", \"INPUT\": \"#8bbabb\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#8bbabb\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#6c7b95\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#464159\", \"#6c7b95\", \"#8bbabb\", \"#c7f0db\"], },\n    \"LightTeal\": {\"BACKGROUND\": \"#c7f0db\", \"TEXT\": \"#464159\", \"INPUT\": \"#6c7b95\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#464159\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#464159\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#464159\", \"#6c7b95\", \"#8bbabb\", \"#c7f0db\"], },\n    \"DarkTeal5\": {\"BACKGROUND\": \"#8bbabb\", \"TEXT\": \"#464159\", \"INPUT\": \"#6c7b95\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#464159\",\n                  \"BUTTON\": (\"#c7f0db\", \"#6c7b95\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#464159\", \"#6c7b95\", \"#8bbabb\", \"#c7f0db\"], },\n    \"LightGrey4\": {\"BACKGROUND\": \"#faf5ef\", \"TEXT\": \"#672f2f\", \"INPUT\": \"#99b19c\", \"TEXT_INPUT\": \"#672f2f\", \"SCROLL\": \"#672f2f\",\n                   \"BUTTON\": (\"#672f2f\", \"#99b19c\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#672f2f\", \"#99b19c\", \"#d7d1c9\", \"#faf5ef\"], },\n    \"LightGreen7\": {\"BACKGROUND\": \"#99b19c\", \"TEXT\": \"#faf5ef\", \"INPUT\": \"#d7d1c9\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#d7d1c9\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#99b19c\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#672f2f\", \"#99b19c\", \"#d7d1c9\", \"#faf5ef\"], },\n    \"LightGrey5\": {\"BACKGROUND\": \"#d7d1c9\", \"TEXT\": \"#672f2f\", \"INPUT\": \"#99b19c\", \"TEXT_INPUT\": \"#672f2f\", \"SCROLL\": \"#672f2f\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#672f2f\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#672f2f\", \"#99b19c\", \"#d7d1c9\", \"#faf5ef\"], },\n    \"DarkBrown3\": {\"BACKGROUND\": \"#a0855b\", \"TEXT\": \"#f9f6f2\", \"INPUT\": \"#f1d6ab\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f1d6ab\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#38470b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#38470b\", \"#a0855b\", \"#f1d6ab\", \"#f9f6f2\"], },\n    \"LightBrown11\": {\"BACKGROUND\": \"#f1d6ab\", \"TEXT\": \"#38470b\", \"INPUT\": \"#a0855b\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#38470b\",\n                     \"BUTTON\": (\"#f9f6f2\", \"#a0855b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                     \"COLOR_LIST\": [\"#38470b\", \"#a0855b\", \"#f1d6ab\", \"#f9f6f2\"], },\n    \"DarkRed\": {\"BACKGROUND\": \"#83142c\", \"TEXT\": \"#f9d276\", \"INPUT\": \"#ad1d45\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#ad1d45\", \"BUTTON\": (\"#f9d276\", \"#ad1d45\"),\n                \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                \"COLOR_LIST\": [\"#44000d\", \"#83142c\", \"#ad1d45\", \"#f9d276\"], },\n    \"DarkTeal6\": {\"BACKGROUND\": \"#204969\", \"TEXT\": \"#fff7f7\", \"INPUT\": \"#dadada\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#dadada\",\n                  \"BUTTON\": (\"#000000\", \"#fff7f7\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#204969\", \"#08ffc8\", \"#dadada\", \"#fff7f7\"], },\n    \"DarkBrown4\": {\"BACKGROUND\": \"#252525\", \"TEXT\": \"#ff0000\", \"INPUT\": \"#af0404\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#af0404\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#252525\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#252525\", \"#414141\", \"#af0404\", \"#ff0000\"], },\n    \"LightYellow\": {\"BACKGROUND\": \"#f4ff61\", \"TEXT\": \"#27aa80\", \"INPUT\": \"#32ff6a\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#27aa80\",\n                    \"BUTTON\": (\"#f4ff61\", \"#27aa80\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#27aa80\", \"#32ff6a\", \"#a8ff3e\", \"#f4ff61\"], },\n    \"DarkGreen1\": {\"BACKGROUND\": \"#2b580c\", \"TEXT\": \"#fdef96\", \"INPUT\": \"#f7b71d\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f7b71d\",\n                   \"BUTTON\": (\"#fdef96\", \"#2b580c\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#2b580c\", \"#afa939\", \"#f7b71d\", \"#fdef96\"], },\n    \"LightGreen8\": {\"BACKGROUND\": \"#c8dad3\", \"TEXT\": \"#63707e\", \"INPUT\": \"#93b5b3\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#63707e\",\n                    \"BUTTON\": (\"#FFFFFF\", \"#63707e\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#63707e\", \"#93b5b3\", \"#c8dad3\", \"#f2f6f5\"], },\n    \"DarkTeal7\": {\"BACKGROUND\": \"#248ea9\", \"TEXT\": \"#fafdcb\", \"INPUT\": \"#aee7e8\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#aee7e8\",\n                  \"BUTTON\": (\"#000000\", \"#fafdcb\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#248ea9\", \"#28c3d4\", \"#aee7e8\", \"#fafdcb\"], },\n    \"DarkBlue8\": {\"BACKGROUND\": \"#454d66\", \"TEXT\": \"#d9d872\", \"INPUT\": \"#58b368\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#58b368\",\n                  \"BUTTON\": (\"#000000\", \"#009975\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#009975\", \"#454d66\", \"#58b368\", \"#d9d872\"], },\n    \"DarkBlue9\": {\"BACKGROUND\": \"#263859\", \"TEXT\": \"#ff6768\", \"INPUT\": \"#6b778d\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#6b778d\",\n                  \"BUTTON\": (\"#ff6768\", \"#263859\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#17223b\", \"#263859\", \"#6b778d\", \"#ff6768\"], },\n    \"DarkBlue10\": {\"BACKGROUND\": \"#0028ff\", \"TEXT\": \"#f1f4df\", \"INPUT\": \"#10eaf0\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#10eaf0\",\n                   \"BUTTON\": (\"#f1f4df\", \"#24009c\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#24009c\", \"#0028ff\", \"#10eaf0\", \"#f1f4df\"], },\n    \"DarkBlue11\": {\"BACKGROUND\": \"#6384b3\", \"TEXT\": \"#e6f0b6\", \"INPUT\": \"#b8e9c0\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#b8e9c0\",\n                   \"BUTTON\": (\"#e6f0b6\", \"#684949\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#684949\", \"#6384b3\", \"#b8e9c0\", \"#e6f0b6\"], },\n    \"DarkTeal8\": {\"BACKGROUND\": \"#71a0a5\", \"TEXT\": \"#212121\", \"INPUT\": \"#665c84\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#212121\",\n                  \"BUTTON\": (\"#fab95b\", \"#665c84\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#212121\", \"#665c84\", \"#71a0a5\", \"#fab95b\"], },\n    \"DarkRed1\": {\"BACKGROUND\": \"#c10000\", \"TEXT\": \"#eeeeee\", \"INPUT\": \"#dedede\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#dedede\", \"BUTTON\": (\"#c10000\", \"#eeeeee\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                 \"COLOR_LIST\": [\"#c10000\", \"#ff4949\", \"#dedede\", \"#eeeeee\"], },\n    \"LightBrown5\": {\"BACKGROUND\": \"#fff591\", \"TEXT\": \"#e41749\", \"INPUT\": \"#f5587b\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e41749\",\n                    \"BUTTON\": (\"#fff591\", \"#e41749\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#e41749\", \"#f5587b\", \"#ff8a5c\", \"#fff591\"], },\n    \"LightGreen9\": {\"BACKGROUND\": \"#f1edb3\", \"TEXT\": \"#3b503d\", \"INPUT\": \"#4a746e\", \"TEXT_INPUT\": \"#f1edb3\", \"SCROLL\": \"#3b503d\",\n                    \"BUTTON\": (\"#f1edb3\", \"#3b503d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#3b503d\", \"#4a746e\", \"#c8cf94\", \"#f1edb3\"], \"DESCRIPTION\": [\"Green\", \"Turquoise\", \"Yellow\"], },\n    \"DarkGreen2\": {\"BACKGROUND\": \"#3b503d\", \"TEXT\": \"#f1edb3\", \"INPUT\": \"#c8cf94\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#c8cf94\",\n                   \"BUTTON\": (\"#f1edb3\", \"#3b503d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#3b503d\", \"#4a746e\", \"#c8cf94\", \"#f1edb3\"], \"DESCRIPTION\": [\"Green\", \"Turquoise\", \"Yellow\"], },\n    \"LightGray1\": {\"BACKGROUND\": \"#f2f2f2\", \"TEXT\": \"#222831\", \"INPUT\": \"#393e46\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#222831\",\n                   \"BUTTON\": (\"#f2f2f2\", \"#222831\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#222831\", \"#393e46\", \"#f96d00\", \"#f2f2f2\"], \"DESCRIPTION\": [\"#000000\", \"Grey\", \"Orange\", \"Grey\", \"Autumn\"], },\n    \"DarkGrey4\": {\"BACKGROUND\": \"#52524e\", \"TEXT\": \"#e9e9e5\", \"INPUT\": \"#d4d6c8\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#d4d6c8\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#9a9b94\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#52524e\", \"#9a9b94\", \"#d4d6c8\", \"#e9e9e5\"], \"DESCRIPTION\": [\"Grey\", \"Pastel\", \"Winter\"], },\n    \"DarkBlue12\": {\"BACKGROUND\": \"#324e7b\", \"TEXT\": \"#f8f8f8\", \"INPUT\": \"#86a6df\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#86a6df\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#5068a9\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#324e7b\", \"#5068a9\", \"#86a6df\", \"#f8f8f8\"], \"DESCRIPTION\": [\"Blue\", \"Grey\", \"Cold\", \"Winter\"], },\n    \"DarkPurple6\": {\"BACKGROUND\": \"#070739\", \"TEXT\": \"#e1e099\", \"INPUT\": \"#c327ab\", \"TEXT_INPUT\": \"#e1e099\", \"SCROLL\": \"#c327ab\",\n                    \"BUTTON\": (\"#e1e099\", \"#521477\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                    \"COLOR_LIST\": [\"#070739\", \"#521477\", \"#c327ab\", \"#e1e099\"], \"DESCRIPTION\": [\"#000000\", \"Purple\", \"Yellow\", \"Dark\"], },\n    \"DarkPurple7\": {\"BACKGROUND\": \"#191930\", \"TEXT\": \"#B1B7C5\", \"INPUT\": \"#232B5C\", \"TEXT_INPUT\": \"#D0E3E7\", \"SCROLL\": \"#B1B7C5\",\n                    \"BUTTON\": (\"#272D38\", \"#B1B7C5\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkBlue13\": {\"BACKGROUND\": \"#203562\", \"TEXT\": \"#e3e8f8\", \"INPUT\": \"#c0c5cd\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#c0c5cd\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#3e588f\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#203562\", \"#3e588f\", \"#c0c5cd\", \"#e3e8f8\"], \"DESCRIPTION\": [\"Blue\", \"Grey\", \"Wedding\", \"Cold\"], },\n    \"DarkBrown5\": {\"BACKGROUND\": \"#3c1b1f\", \"TEXT\": \"#f6e1b5\", \"INPUT\": \"#e2bf81\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e2bf81\",\n                   \"BUTTON\": (\"#3c1b1f\", \"#f6e1b5\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#3c1b1f\", \"#b21e4b\", \"#e2bf81\", \"#f6e1b5\"], \"DESCRIPTION\": [\"Brown\", \"Red\", \"Yellow\", \"Warm\"], },\n    \"DarkGreen3\": {\"BACKGROUND\": \"#062121\", \"TEXT\": \"#eeeeee\", \"INPUT\": \"#e4dcad\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e4dcad\",\n                   \"BUTTON\": (\"#eeeeee\", \"#181810\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#062121\", \"#181810\", \"#e4dcad\", \"#eeeeee\"], \"DESCRIPTION\": [\"#000000\", \"#000000\", \"Brown\", \"Grey\"], },\n    \"DarkBlack1\": {\"BACKGROUND\": \"#181810\", \"TEXT\": \"#eeeeee\", \"INPUT\": \"#e4dcad\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e4dcad\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#062121\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#062121\", \"#181810\", \"#e4dcad\", \"#eeeeee\"], \"DESCRIPTION\": [\"#000000\", \"#000000\", \"Brown\", \"Grey\"], },\n    \"DarkGrey5\": {\"BACKGROUND\": \"#343434\", \"TEXT\": \"#f3f3f3\", \"INPUT\": \"#e9dcbe\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e9dcbe\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#8e8b82\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#343434\", \"#8e8b82\", \"#e9dcbe\", \"#f3f3f3\"], \"DESCRIPTION\": [\"Grey\", \"Brown\"], },\n    \"LightBrown12\": {\"BACKGROUND\": \"#8e8b82\", \"TEXT\": \"#f3f3f3\", \"INPUT\": \"#e9dcbe\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e9dcbe\",\n                     \"BUTTON\": (\"#f3f3f3\", \"#8e8b82\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                     \"COLOR_LIST\": [\"#343434\", \"#8e8b82\", \"#e9dcbe\", \"#f3f3f3\"], \"DESCRIPTION\": [\"Grey\", \"Brown\"], },\n    \"DarkTeal9\": {\"BACKGROUND\": \"#13445a\", \"TEXT\": \"#fef4e8\", \"INPUT\": \"#446878\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#446878\",\n                  \"BUTTON\": (\"#fef4e8\", \"#446878\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#13445a\", \"#970747\", \"#446878\", \"#fef4e8\"], \"DESCRIPTION\": [\"Red\", \"Grey\", \"Blue\", \"Wedding\", \"Retro\"], },\n    \"DarkBlue14\": {\"BACKGROUND\": \"#21273d\", \"TEXT\": \"#f1f6f8\", \"INPUT\": \"#b9d4f1\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#b9d4f1\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#6a759b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#21273d\", \"#6a759b\", \"#b9d4f1\", \"#f1f6f8\"], \"DESCRIPTION\": [\"Blue\", \"#000000\", \"Grey\", \"Cold\", \"Winter\"], },\n    \"LightBlue6\": {\"BACKGROUND\": \"#f1f6f8\", \"TEXT\": \"#21273d\", \"INPUT\": \"#6a759b\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#21273d\",\n                   \"BUTTON\": (\"#f1f6f8\", \"#6a759b\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#21273d\", \"#6a759b\", \"#b9d4f1\", \"#f1f6f8\"], \"DESCRIPTION\": [\"Blue\", \"#000000\", \"Grey\", \"Cold\", \"Winter\"], },\n    \"DarkGreen4\": {\"BACKGROUND\": \"#044343\", \"TEXT\": \"#e4e4e4\", \"INPUT\": \"#045757\", \"TEXT_INPUT\": \"#e4e4e4\", \"SCROLL\": \"#045757\",\n                   \"BUTTON\": (\"#e4e4e4\", \"#045757\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#222222\", \"#044343\", \"#045757\", \"#e4e4e4\"], \"DESCRIPTION\": [\"#000000\", \"Turquoise\", \"Grey\", \"Dark\"], },\n    \"DarkGreen5\": {\"BACKGROUND\": \"#1b4b36\", \"TEXT\": \"#e0e7f1\", \"INPUT\": \"#aebd77\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#aebd77\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#538f6a\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#1b4b36\", \"#538f6a\", \"#aebd77\", \"#e0e7f1\"], \"DESCRIPTION\": [\"Green\", \"Grey\"], },\n    \"DarkTeal10\": {\"BACKGROUND\": \"#0d3446\", \"TEXT\": \"#d8dfe2\", \"INPUT\": \"#71adb5\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#71adb5\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#176d81\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#0d3446\", \"#176d81\", \"#71adb5\", \"#d8dfe2\"], \"DESCRIPTION\": [\"Grey\", \"Turquoise\", \"Winter\", \"Cold\"], },\n    \"DarkGrey6\": {\"BACKGROUND\": \"#3e3e3e\", \"TEXT\": \"#ededed\", \"INPUT\": \"#68868c\", \"TEXT_INPUT\": \"#ededed\", \"SCROLL\": \"#68868c\",\n                  \"BUTTON\": (\"#FFFFFF\", \"#405559\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#3e3e3e\", \"#405559\", \"#68868c\", \"#ededed\"], \"DESCRIPTION\": [\"Grey\", \"Turquoise\", \"Winter\"], },\n    \"DarkTeal11\": {\"BACKGROUND\": \"#405559\", \"TEXT\": \"#ededed\", \"INPUT\": \"#68868c\", \"TEXT_INPUT\": \"#ededed\", \"SCROLL\": \"#68868c\",\n                   \"BUTTON\": (\"#ededed\", \"#68868c\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#3e3e3e\", \"#405559\", \"#68868c\", \"#ededed\"], \"DESCRIPTION\": [\"Grey\", \"Turquoise\", \"Winter\"], },\n    \"LightBlue7\": {\"BACKGROUND\": \"#9ed0e0\", \"TEXT\": \"#19483f\", \"INPUT\": \"#5c868e\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#19483f\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#19483f\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#19483f\", \"#5c868e\", \"#ff6a38\", \"#9ed0e0\"], \"DESCRIPTION\": [\"Orange\", \"Blue\", \"Turquoise\"], },\n    \"LightGreen10\": {\"BACKGROUND\": \"#d8ebb5\", \"TEXT\": \"#205d67\", \"INPUT\": \"#639a67\", \"TEXT_INPUT\": \"#FFFFFF\", \"SCROLL\": \"#205d67\",\n                     \"BUTTON\": (\"#d8ebb5\", \"#205d67\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                     \"COLOR_LIST\": [\"#205d67\", \"#639a67\", \"#d9bf77\", \"#d8ebb5\"], \"DESCRIPTION\": [\"Blue\", \"Green\", \"Brown\", \"Vintage\"], },\n    \"DarkBlue15\": {\"BACKGROUND\": \"#151680\", \"TEXT\": \"#f1fea4\", \"INPUT\": \"#375fc0\", \"TEXT_INPUT\": \"#f1fea4\", \"SCROLL\": \"#375fc0\",\n                   \"BUTTON\": (\"#f1fea4\", \"#1c44ac\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#151680\", \"#1c44ac\", \"#375fc0\", \"#f1fea4\"], \"DESCRIPTION\": [\"Blue\", \"Yellow\", \"Cold\"], },\n    \"DarkBlue16\": {\"BACKGROUND\": \"#1c44ac\", \"TEXT\": \"#f1fea4\", \"INPUT\": \"#375fc0\", \"TEXT_INPUT\": \"#f1fea4\", \"SCROLL\": \"#375fc0\",\n                   \"BUTTON\": (\"#f1fea4\", \"#151680\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#151680\", \"#1c44ac\", \"#375fc0\", \"#f1fea4\"], \"DESCRIPTION\": [\"Blue\", \"Yellow\", \"Cold\"], },\n    \"DarkTeal12\": {\"BACKGROUND\": \"#004a7c\", \"TEXT\": \"#fafafa\", \"INPUT\": \"#e8f1f5\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#e8f1f5\",\n                   \"BUTTON\": (\"#fafafa\", \"#005691\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#004a7c\", \"#005691\", \"#e8f1f5\", \"#fafafa\"], \"DESCRIPTION\": [\"Grey\", \"Blue\", \"Cold\", \"Winter\"], },\n    \"LightBrown13\": {\"BACKGROUND\": \"#ebf5ee\", \"TEXT\": \"#921224\", \"INPUT\": \"#bdc6b8\", \"TEXT_INPUT\": \"#921224\", \"SCROLL\": \"#921224\",\n                     \"BUTTON\": (\"#FFFFFF\", \"#921224\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                     \"COLOR_LIST\": [\"#921224\", \"#bdc6b8\", \"#bce0da\", \"#ebf5ee\"], \"DESCRIPTION\": [\"Red\", \"Blue\", \"Grey\", \"Vintage\", \"Wedding\"], },\n    \"DarkBlue17\": {\"BACKGROUND\": \"#21294c\", \"TEXT\": \"#f9f2d7\", \"INPUT\": \"#f2dea8\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#f2dea8\",\n                   \"BUTTON\": (\"#f9f2d7\", \"#141829\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#141829\", \"#21294c\", \"#f2dea8\", \"#f9f2d7\"], \"DESCRIPTION\": [\"#000000\", \"Blue\", \"Yellow\"], },\n    \"DarkBrown6\": {\"BACKGROUND\": \"#785e4d\", \"TEXT\": \"#f2eee3\", \"INPUT\": \"#baaf92\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#baaf92\",\n                   \"BUTTON\": (\"#FFFFFF\", \"#785e4d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#785e4d\", \"#ff8426\", \"#baaf92\", \"#f2eee3\"], \"DESCRIPTION\": [\"Grey\", \"Brown\", \"Orange\", \"Autumn\"], },\n    \"DarkGreen6\": {\"BACKGROUND\": \"#5c715e\", \"TEXT\": \"#f2f9f1\", \"INPUT\": \"#ddeedf\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"#ddeedf\",\n                   \"BUTTON\": (\"#f2f9f1\", \"#5c715e\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#5c715e\", \"#b6cdbd\", \"#ddeedf\", \"#f2f9f1\"], \"DESCRIPTION\": [\"Grey\", \"Green\", \"Vintage\"], },\n    \"DarkGreen7\": {\"BACKGROUND\": \"#0C231E\", \"TEXT\": \"#efbe1c\", \"INPUT\": \"#153C33\", \"TEXT_INPUT\": \"#efbe1c\", \"SCROLL\": \"#153C33\",\n                   \"BUTTON\": (\"#efbe1c\", \"#153C33\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey7\": {\"BACKGROUND\": \"#4b586e\", \"TEXT\": \"#dddddd\", \"INPUT\": \"#574e6d\", \"TEXT_INPUT\": \"#dddddd\", \"SCROLL\": \"#574e6d\",\n                  \"BUTTON\": (\"#dddddd\", \"#43405d\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                  \"COLOR_LIST\": [\"#43405d\", \"#4b586e\", \"#574e6d\", \"#dddddd\"], \"DESCRIPTION\": [\"Grey\", \"Winter\", \"Cold\"], },\n    \"DarkRed2\": {\"BACKGROUND\": \"#ab1212\", \"TEXT\": \"#f6e4b5\", \"INPUT\": \"#cd3131\", \"TEXT_INPUT\": \"#f6e4b5\", \"SCROLL\": \"#cd3131\", \"BUTTON\": (\"#f6e4b5\", \"#ab1212\"),\n                 \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                 \"COLOR_LIST\": [\"#ab1212\", \"#1fad9f\", \"#cd3131\", \"#f6e4b5\"], \"DESCRIPTION\": [\"Turquoise\", \"Red\", \"Yellow\"], },\n    \"LightGrey6\": {\"BACKGROUND\": \"#e3e3e3\", \"TEXT\": \"#233142\", \"INPUT\": \"#455d7a\", \"TEXT_INPUT\": \"#e3e3e3\", \"SCROLL\": \"#233142\",\n                   \"BUTTON\": (\"#e3e3e3\", \"#455d7a\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0,\n                   \"COLOR_LIST\": [\"#233142\", \"#455d7a\", \"#f95959\", \"#e3e3e3\"], \"DESCRIPTION\": [\"#000000\", \"Blue\", \"Red\", \"Grey\"], },\n    \"HotDogStand\": {\"BACKGROUND\": \"red\", \"TEXT\": \"yellow\", \"INPUT\": \"yellow\", \"TEXT_INPUT\": \"#000000\", \"SCROLL\": \"yellow\", \"BUTTON\": (\"red\", \"yellow\"),\n                    \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey8\": {\"BACKGROUND\": \"#19232D\", \"TEXT\": \"#ffffff\", \"INPUT\": \"#32414B\", \"TEXT_INPUT\": \"#ffffff\", \"SCROLL\": \"#505F69\",\n                  \"BUTTON\": (\"#ffffff\", \"#32414B\"), \"PROGRESS\": (\"#505F69\", \"#32414B\"), \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey9\": {\"BACKGROUND\": \"#36393F\", \"TEXT\": \"#DCDDDE\", \"INPUT\": \"#40444B\", \"TEXT_INPUT\": \"#ffffff\", \"SCROLL\": \"#202225\",\n                  \"BUTTON\": (\"#202225\", \"#B9BBBE\"), \"PROGRESS\": (\"#202225\", \"#40444B\"), \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey10\": {\"BACKGROUND\": \"#1c1e23\", \"TEXT\": \"#cccdcf\", \"INPUT\": \"#272a31\", \"TEXT_INPUT\": \"#8b9fde\", \"SCROLL\": \"#313641\",\n                   \"BUTTON\": (\"#f5f5f6\", \"#2e3d5a\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey11\": {\"BACKGROUND\": \"#1c1e23\", \"TEXT\": \"#cccdcf\", \"INPUT\": \"#313641\", \"TEXT_INPUT\": \"#cccdcf\", \"SCROLL\": \"#313641\",\n                   \"BUTTON\": (\"#f5f5f6\", \"#313641\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey12\": {\"BACKGROUND\": \"#1c1e23\", \"TEXT\": \"#8b9fde\", \"INPUT\": \"#313641\", \"TEXT_INPUT\": \"#8b9fde\", \"SCROLL\": \"#313641\",\n                   \"BUTTON\": (\"#cccdcf\", \"#2e3d5a\"), \"PROGRESS\": DEFAULT_PROGRESS_BAR_COMPUTE, \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey13\": {\"BACKGROUND\": \"#1c1e23\", \"TEXT\": \"#cccdcf\", \"INPUT\": \"#272a31\", \"TEXT_INPUT\": \"#cccdcf\", \"SCROLL\": \"#313641\",\n                   \"BUTTON\": (\"#8b9fde\", \"#313641\"), \"PROGRESS\": (\"#cccdcf\", \"#272a31\"), \"BORDER\": 1, \"SLIDER_DEPTH\": 0, \"PROGRESS_DEPTH\": 0, },\n    \"DarkGrey14\": {\"BACKGROUND\": \"#24292e\", \"TEXT\": \"#fafbfc\", \"INPUT\": \"#1d2125\", \"TEXT_INPUT\": \"#fafbfc\", \"SCROLL\": 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        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
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        "documentation": {
            "docstring": "\n    :param icon:                            Can be either a filename or Base64 value. For Windows if filename, it MUST be ICO format. For Linux, must NOT be ICO. Most portable is to use a Base64 of a PNG file. This works universally across all OS's\n    :type icon:                             bytes | str\n    :param button_color:                    Color of the button (text, background)\n    :type button_color:                     (str, str) or str\n    :param element_size:                    element size (width, height) in characters\n    :type element_size:                     (int, int)\n    :param button_element_size:             Size of button\n    :type button_element_size:              (int, int)\n    :param margins:                         (left/right, top/bottom) tkinter margins around outsize. Amount of pixels to leave inside the window's frame around the edges before your elements are shown.\n    :type margins:                          (int, int)\n    :param element_padding:                 Default amount of padding to put around elements in window (left/right, top/bottom) or ((left, right), (top, bottom))\n    :type element_padding:                  (int, int) or ((int, int),(int,int))\n    :param auto_size_text:                  True if the Widget should be shrunk to exactly fit the number of chars to show\n    :type auto_size_text:                   bool\n    :param auto_size_buttons:               True if Buttons in this Window should be sized to exactly fit the text on this.\n    :type auto_size_buttons:                (bool)\n    :param font:                            specifies the  font family, size, etc. Tuple or Single string format 'name size styles'. Styles: italic * roman bold normal underline overstrike\n    :type font:                             (str or (str, int[, str]) or None)\n    :param border_width:                    width of border around element\n    :type border_width:                     (int)\n    :param slider_border_width:             Width of the border around sliders\n    :type slider_border_width:              (int)\n    :param slider_relief:                   Type of relief to use for sliders\n    :type slider_relief:                    (str)\n    :param slider_orientation:              ???\n    :type slider_orientation:               ???\n    :param autoclose_time:                  ???\n    :type autoclose_time:                   ???\n    :param message_box_line_width:          ???\n    :type message_box_line_width:           ???\n    :param progress_meter_border_depth:     ???\n    :type progress_meter_border_depth:      ???\n    :param progress_meter_style:            You can no longer set a progress bar style. All ttk styles must be the same for the window\n    :type progress_meter_style:             ???\n    :param progress_meter_relief:\n    :type progress_meter_relief:            ???\n    :param progress_meter_color:            ???\n    :type progress_meter_color:             ???\n    :param progress_meter_size:             ???\n    :type progress_meter_size:              ???\n    :param text_justification:              Default text justification for all Text Elements in window\n    :type text_justification:               'left' | 'right' | 'center'\n    :param background_color:                color of background\n    :type background_color:                 (str)\n    :param element_background_color:        element background color\n    :type element_background_color:         (str)\n    :param text_element_background_color:   text element background color\n    :type text_element_background_color:    (str)\n    :param input_elements_background_color: Default color to use for the background of input elements\n    :type input_elements_background_color:  (str)\n    :param input_text_color:                Default color to use for the text for Input elements\n    :type input_text_color:                 (str)\n    :param scrollbar_color:                 Default color to use for the slider trough\n    :type scrollbar_color:                  (str)\n    :param text_color:                      color of the text\n    :type text_color:                       (str)\n    :param element_text_color:              Default color to use for Text elements\n    :type element_text_color:               (str)\n    :param debug_win_size:                  window size\n    :type debug_win_size:                   (int, int)\n    :param window_location:                 Default location to place windows. Not setting will center windows on the display\n    :type window_location:                  (int, int) | None\n    :param error_button_color:              (Default = (None))\n    :type error_button_color:               ???\n    :param tooltip_time:                    time in milliseconds to wait before showing a tooltip. Default is 400ms\n    :type tooltip_time:                     (int)\n    :param tooltip_font:                    font to use for all tooltips\n    :type tooltip_font:                     str or Tuple[str, int] or Tuple[str, int, str]\n    :param use_ttk_buttons:                 if True will cause all buttons to be ttk buttons\n    :type use_ttk_buttons:                  (bool)\n    :param ttk_theme:                       Theme to use with ttk widgets.  Choices (on Windows) include - 'default', 'winnative', 'clam', 'alt', 'classic', 'vista', 'xpnative'\n    :type ttk_theme:                        (str)\n    :param suppress_error_popups:           If True then error popups will not be shown if generated internally to PySimpleGUI\n    :type suppress_error_popups:            (bool)\n    :param suppress_raise_key_errors:       If True then key errors won't be raised (you'll still get popup error)\n    :type suppress_raise_key_errors:        (bool)\n    :param suppress_key_guessing:           If True then key errors won't try and find closest matches for you\n    :type suppress_key_guessing:            (bool)\n    :param warn_button_key_duplicates:      If True then duplicate Button Keys generate warnings (not recommended as they're expected)\n    :type warn_button_key_duplicates:       (bool)    \n    :param enable_treeview_869_patch:       If True, then will use the treeview color patch for tk 8.6.9\n    :type enable_treeview_869_patch:        (bool)\n    :param enable_mac_notitlebar_patch:     If True then Windows with no titlebar use an alternative technique when tkinter version < 8.6.10\n    :type enable_mac_notitlebar_patch:      (bool)\n    :param use_custom_titlebar:             If True then a custom titlebar is used instead of the normal system titlebar\n    :type use_custom_titlebar:              (bool)\n    :param titlebar_background_color:       If custom titlebar indicated by use_custom_titlebar, then use this as background color\n    :type titlebar_background_color:        str | None\n    :param titlebar_text_color:             If custom titlebar indicated by use_custom_titlebar, then use this as text color\n    :type titlebar_text_color:              str | None\n    :param titlebar_font:                   If custom titlebar indicated by use_custom_titlebar, then use this as title font\n    :type titlebar_font:                    (str or (str, int[, str]) or None) | None\n    :param titlebar_icon:                   If custom titlebar indicated by use_custom_titlebar, then use this as the icon (file or base64 bytes)\n    :type titlebar_icon:                    bytes | str\n    :param user_settings_path:              default path for user_settings API calls. Expanded with os.path.expanduser so can contain ~ to represent user\n    :type user_settings_path:               (str)\n    :param pysimplegui_settings_path:       default path for the global PySimpleGUI user_settings\n    :type pysimplegui_settings_path:        (str)\n    :param pysimplegui_settings_filename:   default filename for the global PySimpleGUI user_settings\n    :type pysimplegui_settings_filename:    (str)\n    :param keep_on_top:                     If True then all windows will automatically be set to keep_on_top=True\n    :type keep_on_top:                      (bool)\n    :param dpi_awareness:                   If True then will turn on DPI awareness (Windows only at the moment)\n    :type dpi_awareness:                    (bool)\n    :param scaling:                         Sets the default scaling for all windows including popups, etc.\n    :type scaling:                          (float)\n    :param disable_modal_windows:           If True then all windows, including popups, will not be modal windows\n    :type disable_modal_windows:            (bool)\n    :param tooltip_offset:                  Offset to use for tooltips as a tuple. These values will be added to the mouse location when the widget was entered.\n    :type tooltip_offset:                   ((None, None) | (int, int))\n    :return:                                None\n    :rtype:                                 None\n    ",
            "n_words": 889,
            "vocab_size": 356,
            "n_whitespaces": 2847,
            "language": "en"
        }
    },
    {
        "id": 296961,
        "commit_id": "46500beefcccd8106718a8172a5078bbe5579765",
        "repo": "core",
        "path": "tests/components/analytics/test_analytics.py",
        "file_name": "test_analytics.py",
        "fun_name": "test_load_with_supervisor_without_diagnostics",
        "commit_message": "Enable strict typing of analytics (#83119)",
        "code": "async def test_load_with_supervisor_without_diagnostics(hass):\n    \n    analytics = Analytics(hass)\n    analytics._data.preferences[ATTR_DIAGNOSTICS] = True\n\n    assert analytics.preferences[ATTR_DIAGNOSTICS]\n\n    with patch(\n        \"homeassistant.components.hassio.get_supervisor_info\",\n        side_effect=Mock(return_value={\"diagnostics\": False}),\n    ), patch(\n        \"homeassistant.components.hassio.is_hassio\",\n        side_effect=Mock(return_value=True),\n    ):\n        await analytics.load()\n\n    assert not analytics.preferences[ATTR_DIAGNOSTICS]\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 85,
        "n_words": 26,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 78,
        "n_ast_nodes": 132,
        "n_identifiers": 12,
        "d_id": 95933,
        "documentation": {
            "docstring": "Test loading with a supervisor that has not diagnostics enabled.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 93204,
        "commit_id": "db35e231ceababe8c9f5ca7b5d2ca685f07c7d5b",
        "repo": "sentry",
        "path": "tests/sentry/integrations/msteams/test_message_builder.py",
        "file_name": "test_message_builder.py",
        "fun_name": "test_issue_message_builder",
        "commit_message": "test(msteams): Add tests for building group card (#36834)\n\nAdd tests for build_group_card which builds issues cards. Does NOT test all visual aspects of the card. Only ensures that certain important elements are present and the basic structure of the card is correct.",
        "code": "def test_issue_message_builder(self):\n        self.event1.data[\"metadata\"].update({\"value\": \"some error\"})\n        self.group1.data[\"metadata\"].update({\"value\": \"some error\"})\n        self.event1.data[\"type\"] = self.group1.data[\"type\"] = \"error\"\n\n        issue_card = build_group_card(\n            group=self.group1, event=self.event1, rules=self.rules, integration=self.integration\n        )\n\n        body = issue_card[\"body\"]\n        assert 4 == len(body)\n\n        title = body[0]\n        assert \"oh no\" in title[\"text\"]\n        assert TextSize.LARGE == title[\"size\"]\n        assert TextWeight.BOLDER == title[\"weight\"]\n\n        description = body[1]\n        assert \"some error\" == description[\"text\"]\n        assert TextWeight.BOLDER == description[\"weight\"]\n\n        footer = body[2]\n        assert \"ColumnSet\" == footer[\"type\"]\n        assert 3 == len(footer[\"columns\"])\n\n        logo = footer[\"columns\"][0][\"items\"][0]\n        assert \"20px\" == logo[\"height\"]\n\n        issue_id_and_rule = footer[\"columns\"][1][\"items\"][0]\n        assert self.group1.qualified_short_id in issue_id_and_rule[\"text\"]\n        assert \"rule1\" in issue_id_and_rule[\"text\"]\n        assert \"+1 other\" in issue_id_and_rule[\"text\"]\n\n        date = footer[\"columns\"][2][\"items\"][0]\n        assert (\n            re.match(\n                r,\n                date[\"text\"],\n                re.VERBOSE,\n            )\n            is not None\n        )\n\n        actions_container = body[3]\n        assert \"Container\" == actions_container[\"type\"]\n\n        action_set = actions_container[\"items\"][0]\n        assert \"ActionSet\" == action_set[\"type\"]\n\n        actions = action_set[\"actions\"]\n        for action in actions:\n            assert ActionType.SHOW_CARD == action[\"type\"]\n            card_body = action[\"card\"][\"body\"]\n            assert 1 <= len(card_body)\n            assert \"Input.ChoiceSet\" == card_body[-1][\"type\"]\n\n        resolve_action, ignore_action, assign_action = actions\n        assert \"Resolve\" == resolve_action[\"title\"]\n        assert \"Ignore\" == ignore_action[\"title\"]\n        assert \"Assign\" == assign_action[\"title\"]\n\n        # Check if card is serializable to json\n        card_json = json.dumps(issue_card)\n        assert card_json[0] == \"{\" and card_json[-1] == \"}\"\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 581,
        "n_words": 176,
        "vocab_size": 110,
        "complexity": 3,
        "nloc": 60,
        "token_counts": 402,
        "n_ast_nodes": 694,
        "n_identifiers": 41,
        "d_id": 18974,
        "documentation": {
            "docstring": "\\{\\{                # {{\n                DATE\\(                  # DATE(\n                    [0-9T+:\\-]+,\\ SHORT #   2022-07-14T19:30:34, SHORT\n                \\)                      # )\n                \\}\\}                    # }}\n                \\                       # whitespace\n                at                      # at\n                \\                       # whitespace\n                \\{\\{                    # {{\n                TIME\\([0-9T+:\\-]+\\)     # TIME(2022-07-14T19:30:34)\n                \\}\\}                    # }}",
            "n_words": 35,
            "vocab_size": 17,
            "n_whitespaces": 369,
            "language": "en"
        }
    },
    {
        "id": 206296,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/loaders/cached.py",
        "file_name": "cached.py",
        "fun_name": "cache_key",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def cache_key(self, template_name, skip=None):\n        \n        skip_prefix = \"\"\n\n        if skip:\n            matching = [\n                origin.name for origin in skip if origin.template_name == template_name\n            ]\n            if matching:\n                skip_prefix = self.generate_hash(matching)\n\n        return \"-\".join(s for s in (str(template_name), skip_prefix) if s)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 127,
        "n_words": 36,
        "vocab_size": 28,
        "complexity": 7,
        "nloc": 9,
        "token_counts": 66,
        "n_ast_nodes": 106,
        "n_identifiers": 12,
        "d_id": 51474,
        "documentation": {
            "docstring": "\n        Generate a cache key for the template name and skip.\n\n        If skip is provided, only origins that match template_name are included\n        in the cache key. This ensures each template is only parsed and cached\n        once if contained in different extend chains like:\n\n            x -> a -> a\n            y -> a -> a\n            z -> a -> a\n        ",
            "n_words": 57,
            "vocab_size": 39,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 178712,
        "commit_id": "77e7c06c0f9c5c0735b5a65c72abcd243d8e3640",
        "repo": "Nuitka",
        "path": "nuitka/PythonFlavors.py",
        "file_name": "PythonFlavors.py",
        "fun_name": "isNuitkaPython",
        "commit_message": "Minor cleanups",
        "code": "def isNuitkaPython():\n    \n\n    # spell-checker: ignore nuitkapython\n\n    if python_version >= 0x300:\n        return sys.implementation.name == \"nuitkapython\"\n    else:\n        return sys.subversion[0] == \"nuitkapython\"\n\n\n_is_anaconda = None\n\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 47,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 29,
        "n_ast_nodes": 59,
        "n_identifiers": 7,
        "d_id": 42801,
        "documentation": {
            "docstring": "Is this our own fork of CPython named Nuitka-Python.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 60555,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/cli/req_command.py",
        "file_name": "req_command.py",
        "fun_name": "handle_pip_version_check",
        "commit_message": "upd; format",
        "code": "def handle_pip_version_check(self, options):\n        # type: (Values) -> None\n        \n        # Make sure the index_group options are present.\n        assert hasattr(options, \"no_index\")\n\n        if options.disable_pip_version_check or options.no_index:\n            return\n\n        # Otherwise, check if we're using the latest version of pip available.\n        session = self._build_session(\n            options, retries=0, timeout=min(5, options.timeout)\n        )\n        with session:\n            pip_self_version_check(session, options)\n\n\nKEEPABLE_TEMPDIR_TYPES = [\n    tempdir_kinds.BUILD_ENV,\n    tempdir_kinds.EPHEM_WHEEL_CACHE,\n    tempdir_kinds.REQ_BUILD,\n]\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 158,
        "n_words": 55,
        "vocab_size": 50,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 57,
        "n_ast_nodes": 117,
        "n_identifiers": 17,
        "d_id": 12206,
        "documentation": {
            "docstring": "\n        Do the pip version check if not disabled.\n\n        This overrides the default behavior of not doing the check.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 203500,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/templatetags/admin_modify.py",
        "file_name": "admin_modify.py",
        "fun_name": "submit_row",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def submit_row(context):\n    \n    add = context[\"add\"]\n    change = context[\"change\"]\n    is_popup = context[\"is_popup\"]\n    save_as = context[\"save_as\"]\n    show_save = context.get(\"show_save\", True)\n    show_save_and_add_another = context.get(\"show_save_and_add_another\", True)\n    show_save_and_continue = context.get(\"show_save_and_continue\", True)\n    has_add_permission = context[\"has_add_permission\"]\n    has_change_permission = context[\"has_change_permission\"]\n    has_view_permission = context[\"has_view_permission\"]\n    has_editable_inline_admin_formsets = context[\"has_editable_inline_admin_formsets\"]\n    can_save = (\n        (has_change_permission and change)\n        or (has_add_permission and add)\n        or has_editable_inline_admin_formsets\n    )\n    can_save_and_add_another = (\n        has_add_permission\n        and not is_popup\n        and (not save_as or add)\n        and can_save\n        and show_save_and_add_another\n    )\n    can_save_and_continue = (\n        not is_popup and can_save and has_view_permission and show_save_and_continue\n    )\n    can_change = has_change_permission or has_editable_inline_admin_formsets\n    ctx = Context(context)\n    ctx.update(\n        {\n            \"can_change\": can_change,\n            \"show_delete_link\": (\n                not is_popup\n                and context[\"has_delete_permission\"]\n                and change\n                and context.get(\"show_delete\", True)\n            ),\n            \"show_save_as_new\": not is_popup\n            and has_change_permission\n            and change\n            and save_as,\n            \"show_save_and_add_another\": can_save_and_add_another,\n            \"show_save_and_continue\": can_save_and_continue,\n            \"show_save\": show_save and can_save,\n            \"show_close\": not (show_save and can_save),\n        }\n    )\n    return ctx\n\n\n@register.tag(name=\"submit_row\")",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag(name=\"submit_row\")",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 457,
        "n_words": 131,
        "vocab_size": 64,
        "complexity": 22,
        "nloc": 49,
        "token_counts": 213,
        "n_ast_nodes": 380,
        "n_identifiers": 24,
        "d_id": 50412,
        "documentation": {
            "docstring": "\n    Display the row of buttons for delete and save.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 259066,
        "commit_id": "f14af688b7e77ecb6df9dfee93ec39b6c0334b86",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/tests/test_ridge.py",
        "file_name": "test_ridge.py",
        "fun_name": "test_ridgecv_normalize_deprecated",
        "commit_message": "FIX Make Ridge*CV warn about rescaling alphas with scaling (#22585)",
        "code": "def test_ridgecv_normalize_deprecated(Estimator):\n    \n    X = np.array([[1, -1], [1, 1]])\n    y = np.array([0, 1])\n\n    estimator = Estimator(normalize=True)\n\n    with pytest.warns(\n        FutureWarning, match=r\"Set parameter alphas to: original_alphas \\* n_samples\"\n    ):\n        estimator.fit(X, y)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 60,
        "n_words": 28,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 68,
        "n_ast_nodes": 108,
        "n_identifiers": 13,
        "d_id": 75551,
        "documentation": {
            "docstring": "Check that the normalize deprecation warning mentions the rescaling of alphas\n\n    Non-regression test for issue #22540\n    ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 308815,
        "commit_id": "10027b20904b678d8baecbc6e72c5bcc3f4f24b2",
        "repo": "core",
        "path": "homeassistant/components/nissan_leaf/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "async_start_charging",
        "commit_message": "Add button to start leaf charge (#62948)\n\nCo-authored-by: Bruce Duncan <bwduncan@gmail.com>",
        "code": "async def async_start_charging(self) -> None:\n        \n        await self.hass.async_add_executor_job(self.leaf.start_charging)\n        self.schedule_update()\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 29,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 47,
        "n_identifiers": 7,
        "d_id": 107548,
        "documentation": {
            "docstring": "Request to start charging the car. Used by the button platform.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 306486,
        "commit_id": "0c767bd0d37a41af37728b1d8b4eae8dceb7e188",
        "repo": "core",
        "path": "homeassistant/components/smappee/binary_sensor.py",
        "file_name": "binary_sensor.py",
        "fun_name": "async_update",
        "commit_message": "Improve entity type hints [s] (part 1/2) (#77881)",
        "code": "async def async_update(self) -> None:\n        \n        await self._smappee_base.async_update()\n\n        self._state = self._service_location.is_present\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 25,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 105270,
        "documentation": {
            "docstring": "Get the latest data from Smappee and update the state.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 265126,
        "commit_id": "103729c0855aad2f45fcaa2cf680799236f3e201",
        "repo": "netbox",
        "path": "netbox/dcim/tests/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_mount_half_u_devices",
        "commit_message": "Add test for 0.5U devices",
        "code": "def test_mount_half_u_devices(self):\n        \n        rack = Rack.objects.first()\n        attrs = {\n            'device_type': DeviceType.objects.get(u_height=0.5),\n            'device_role': DeviceRole.objects.first(),\n            'site': Site.objects.first(),\n            'rack': rack,\n            'face': DeviceFaceChoices.FACE_FRONT,\n        }\n\n        Device(name='Device 1', position=1, **attrs).save()\n        Device(name='Device 2', position=1.5, **attrs).save()\n\n        self.assertEqual(len(rack.get_available_units()), rack.u_height * 2 - 3)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 137,
        "n_words": 33,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 121,
        "n_ast_nodes": 196,
        "n_identifiers": 21,
        "d_id": 77999,
        "documentation": {
            "docstring": "\n        Check that two 0.5U devices can be mounted in the same rack unit.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 248955,
        "commit_id": "922b771337f6d14a556fa761c783748f698e924b",
        "repo": "synapse",
        "path": "tests/unittest.py",
        "file_name": "unittest.py",
        "fun_name": "make_homeserver",
        "commit_message": "Add missing type hints for tests.unittest. (#13397)",
        "code": "def make_homeserver(self, reactor, clock):\n        \n        hs = self.setup_test_homeserver()\n        return hs\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 32,
        "n_identifiers": 6,
        "d_id": 72530,
        "documentation": {
            "docstring": "\n        Make and return a homeserver.\n\n        Args:\n            reactor: A Twisted Reactor, or something that pretends to be one.\n            clock (synapse.util.Clock): The Clock, associated with the reactor.\n\n        Returns:\n            A homeserver suitable for testing.\n\n        Function to be overridden in subclasses.\n        ",
            "n_words": 37,
            "vocab_size": 34,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 205746,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "ordered",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def ordered(self):\n        \n        if isinstance(self, EmptyQuerySet):\n            return True\n        if self.query.extra_order_by or self.query.order_by:\n            return True\n        elif (\n            self.query.default_ordering\n            and self.query.get_meta().ordering\n            and\n            # A default ordering doesn't affect GROUP BY queries.\n            not self.query.group_by\n        ):\n            return True\n        else:\n            return False\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 177,
        "n_words": 36,
        "vocab_size": 29,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 63,
        "n_ast_nodes": 103,
        "n_identifiers": 11,
        "d_id": 51188,
        "documentation": {
            "docstring": "\n        Return True if the QuerySet is ordered -- i.e. has an order_by()\n        clause or a default ordering on the model (or is empty).\n        ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 72414,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/views/generic/multiple_upload.py",
        "file_name": "multiple_upload.py",
        "fun_name": "get_invalid_response_data",
        "commit_message": "Reformat with black",
        "code": "def get_invalid_response_data(self, form):\n        \n        return {\n            \"success\": False,\n            \"error_message\": \"\\n\".join(form.errors[\"file\"]),\n        }\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 53,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 29,
        "n_ast_nodes": 54,
        "n_identifiers": 5,
        "d_id": 15887,
        "documentation": {
            "docstring": "\n        Return the JSON response data for an invalid form submission\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 264915,
        "commit_id": "6ff2e55ce408f0f7f2fe99129048421c25ecafe6",
        "repo": "netbox",
        "path": "netbox/dcim/models/cables.py",
        "file_name": "cables.py",
        "fun_name": "path_objects",
        "commit_message": "Add origins, destinations properties on CablePath",
        "code": "def path_objects(self):\n        \n        if not hasattr(self, '_path_objects'):\n            self._path_objects = self._get_path()\n        return self._path_objects\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 28,
        "n_ast_nodes": 50,
        "n_identifiers": 5,
        "d_id": 77911,
        "documentation": {
            "docstring": "\n        Cache and return the complete path as lists of objects, derived from their annotation within the path.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 107757,
        "commit_id": "e1eca0aa8bf0b51009e012cd37d3e95f364d0ee9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backends/backend_wx.py",
        "file_name": "backend_wx.py",
        "fun_name": "gui_repaint",
        "commit_message": "Expire deprecations in backends",
        "code": "def gui_repaint(self, drawDC=None):\n        \n        _log.debug(\"%s - gui_repaint()\", type(self))\n        # The \"if self\" check avoids a \"wrapped C/C++ object has been deleted\"\n        # RuntimeError if doing things after window is closed.\n        if not (self and self.IsShownOnScreen()):\n            return\n        if not drawDC:  # not called from OnPaint use a ClientDC\n            drawDC = wx.ClientDC(self)\n        # For 'WX' backend on Windows, the bitmap can not be in use by another\n        # DC (see GraphicsContextWx._cache).\n        bmp = (self.bitmap.ConvertToImage().ConvertToBitmap()\n               if wx.Platform == '__WXMSW__'\n                  and isinstance(self.figure._cachedRenderer, RendererWx)\n               else self.bitmap)\n        drawDC.DrawBitmap(bmp, 0, 0)\n        if self._rubberband_rect is not None:\n            # Some versions of wx+python don't support numpy.float64 here.\n            x0, y0, x1, y1 = map(int, self._rubberband_rect)\n            drawDC.DrawLineList(\n                [(x0, y0, x1, y0), (x1, y0, x1, y1),\n                 (x0, y0, x0, y1), (x0, y1, x1, y1)],\n                wx.Pen('BLACK', 1, wx.PENSTYLE_SHORT_DASH))\n\n    filetypes = {\n        **FigureCanvasBase.filetypes,\n        'bmp': 'Windows bitmap',\n        'jpeg': 'JPEG',\n        'jpg': 'JPEG',\n        'pcx': 'PCX',\n        'png': 'Portable Network Graphics',\n        'tif': 'Tagged Image Format File',\n        'tiff': 'Tagged Image Format File',\n        'xpm': 'X pixmap',\n    }\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 448,
        "n_words": 155,
        "vocab_size": 121,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 175,
        "n_ast_nodes": 350,
        "n_identifiers": 31,
        "d_id": 22898,
        "documentation": {
            "docstring": "\n        Update the displayed image on the GUI canvas, using the supplied\n        wx.PaintDC device context.\n\n        The 'WXAgg' backend sets origin accordingly.\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 266161,
        "commit_id": "540bba4544d9f31c126571cc1a45a6783b3b6a89",
        "repo": "netbox",
        "path": "netbox/utilities/utils.py",
        "file_name": "utils.py",
        "fun_name": "copy_safe_request",
        "commit_message": "Closes #10920: Include request cookies when queuing a custom script",
        "code": "def copy_safe_request(request):\n    \n    meta = {\n        k: request.META[k]\n        for k in HTTP_REQUEST_META_SAFE_COPY\n        if k in request.META and isinstance(request.META[k], str)\n    }\n    return NetBoxFakeRequest({\n        'META': meta,\n        'COOKIES': request.COOKIES,\n        'POST': request.POST,\n        'GET': request.GET,\n        'FILES': request.FILES,\n        'user': request.user,\n        'path': request.path,\n        'id': getattr(request, 'id', None),  # UUID assigned by middleware\n    })\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 138,
        "n_words": 45,
        "vocab_size": 43,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 97,
        "n_ast_nodes": 158,
        "n_identifiers": 16,
        "d_id": 78322,
        "documentation": {
            "docstring": "\n    Copy selected attributes from a request object into a new fake request object. This is needed in places where\n    thread safe pickling of the useful request data is needed.\n    ",
            "n_words": 29,
            "vocab_size": 25,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 26250,
        "commit_id": "3f773c3890aead936949bd6923d2d7f669e1c68f",
        "repo": "saleor",
        "path": "saleor/graphql/product/tests/test_product_filtering_and_sorting_with_channels.py",
        "file_name": "test_product_filtering_and_sorting_with_channels.py",
        "fun_name": "products_for_sorting_with_channels",
        "commit_message": "Add sorting by LAST_MODIFIED_AT field to GraphQL schema (#9245)\n\n* Add sorting by LAST_MODIFIED_AT to new types\r\n\r\n* Add LAST_MODIFIED_AT to sorting exported files\r\n\r\n* Update schema, fix variant sorter\r\n\r\n* Update changelog\r\n\r\n* Rebase and update changelog\r\n\r\nCo-authored-by: Marcin Gębala <5421321+maarcingebala@users.noreply.github.com>",
        "code": "def products_for_sorting_with_channels(category, channel_USD, channel_PLN):\n    product_type = ProductType.objects.create(name=\"Apple\", kind=ProductTypeKind.NORMAL)\n    products = Product.objects.bulk_create(\n        [\n            Product(\n                name=\"Product1\",\n                slug=\"prod1\",\n                category=category,\n                product_type=product_type,\n                description=dummy_editorjs(\"Test description 1.\"),\n            ),\n            Product(\n                name=\"ProductProduct1\",\n                slug=\"prod_prod1\",\n                category=category,\n                product_type=product_type,\n            ),\n            Product(\n                name=\"ProductProduct2\",\n                slug=\"prod_prod2\",\n                category=category,\n                product_type=product_type,\n            ),\n            Product(\n                name=\"Product2\",\n                slug=\"prod2\",\n                category=category,\n                product_type=product_type,\n                description=dummy_editorjs(\"Test description 2.\"),\n            ),\n            Product(\n                name=\"Product3\",\n                slug=\"prod3\",\n                category=category,\n                product_type=product_type,\n                description=dummy_editorjs(\"Test description 3.\"),\n            ),\n        ]\n    )\n    ProductChannelListing.objects.bulk_create(\n        [\n            ProductChannelListing(\n                product=products[0],\n                channel=channel_USD,\n                is_published=True,\n                discounted_price_amount=Decimal(5),\n                publication_date=datetime.date(2002, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[1],\n                channel=channel_USD,\n                is_published=True,\n                discounted_price_amount=Decimal(15),\n                publication_date=datetime.date(2000, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[2],\n                channel=channel_USD,\n                is_published=False,\n                discounted_price_amount=Decimal(4),\n                publication_date=datetime.date(1999, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[3],\n                channel=channel_USD,\n                is_published=True,\n                discounted_price_amount=Decimal(7),\n                publication_date=datetime.date(2001, 1, 1),\n            ),\n            # Second channel\n            ProductChannelListing(\n                product=products[0],\n                channel=channel_PLN,\n                is_published=False,\n                discounted_price_amount=Decimal(15),\n                publication_date=datetime.date(2003, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[1],\n                channel=channel_PLN,\n                is_published=True,\n                discounted_price_amount=Decimal(4),\n                publication_date=datetime.date(1999, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[2],\n                channel=channel_PLN,\n                is_published=True,\n                discounted_price_amount=Decimal(5),\n                publication_date=datetime.date(2000, 1, 1),\n            ),\n            ProductChannelListing(\n                product=products[4],\n                channel=channel_PLN,\n                is_published=True,\n                discounted_price_amount=Decimal(7),\n                publication_date=datetime.date(1998, 1, 1),\n            ),\n        ]\n    )\n    variants = ProductVariant.objects.bulk_create(\n        [\n            ProductVariant(\n                product=products[0],\n                sku=str(uuid.uuid4()).replace(\"-\", \"\"),\n                track_inventory=True,\n                name=\"XS\",\n            ),\n            ProductVariant(\n                product=products[1],\n                sku=str(uuid.uuid4()).replace(\"-\", \"\"),\n                track_inventory=True,\n                name=\"S\",\n            ),\n            ProductVariant(\n                product=products[2],\n                sku=str(uuid.uuid4()).replace(\"-\", \"\"),\n                track_inventory=True,\n                name=\"M\",\n            ),\n            ProductVariant(\n                product=products[3],\n                sku=str(uuid.uuid4()).replace(\"-\", \"\"),\n                track_inventory=True,\n                name=\"L\",\n            ),\n            ProductVariant(\n                product=products[4],\n                sku=str(uuid.uuid4()).replace(\"-\", \"\"),\n                track_inventory=True,\n                name=\"XL\",\n            ),\n        ]\n    )\n    ProductVariantChannelListing.objects.bulk_create(\n        [\n            ProductVariantChannelListing(\n                variant=variants[0],\n                channel=channel_USD,\n                price_amount=Decimal(10),\n                currency=channel_USD.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[1],\n                channel=channel_USD,\n                price_amount=Decimal(15),\n                currency=channel_USD.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[2],\n                channel=channel_USD,\n                price_amount=Decimal(8),\n                currency=channel_USD.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[3],\n                channel=channel_USD,\n                price_amount=Decimal(7),\n                currency=channel_USD.currency_code,\n            ),\n            # Second channel\n            ProductVariantChannelListing(\n                variant=variants[0],\n                channel=channel_PLN,\n                price_amount=Decimal(15),\n                currency=channel_PLN.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[1],\n                channel=channel_PLN,\n                price_amount=Decimal(8),\n                currency=channel_PLN.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[2],\n                channel=channel_PLN,\n                price_amount=Decimal(10),\n                currency=channel_PLN.currency_code,\n            ),\n            ProductVariantChannelListing(\n                variant=variants[4],\n                channel=channel_PLN,\n                price_amount=Decimal(7),\n                currency=channel_PLN.currency_code,\n            ),\n        ]\n    )\n\n    products[3].save()\n    products[4].save()\n    products[0].save()\n    products[2].save()\n    products[1].save()\n\n    variants[2].save()\n    variants[0].save()\n    variants[4].save()\n    variants[1].save()\n    variants[3].save()\n\n    return products\n\n\nQUERY_PRODUCTS_WITH_SORTING_AND_FILTERING = \n\n\n@pytest.mark.parametrize(\n    \"sort_by\",\n    [\n        {\"field\": \"PUBLISHED\", \"direction\": \"ASC\"},\n        {\"field\": \"PRICE\", \"direction\": \"DESC\"},\n        {\"field\": \"MINIMAL_PRICE\", \"direction\": \"DESC\"},\n        {\"field\": \"PUBLICATION_DATE\", \"direction\": \"DESC\"},\n    ],\n)",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"sort_by\",\n    [\n        {\"field\": \"PUBLISHED\", \"direction\": \"ASC\"},\n        {\"field\": \"PRICE\", \"direction\": \"DESC\"},\n        {\"field\": \"MINIMAL_PRICE\", \"direction\": \"DESC\"},\n        {\"field\": \"PUBLICATION_DATE\", \"direction\": \"DESC\"},\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 18,
        "n_whitespaces": 2732,
        "n_words": 263,
        "vocab_size": 105,
        "complexity": 1,
        "nloc": 196,
        "token_counts": 991,
        "n_ast_nodes": 1552,
        "n_identifiers": 45,
        "d_id": 4954,
        "documentation": {
            "docstring": "\n    query ($sortBy: ProductOrder, $filter: ProductFilterInput, $channel: String){\n        products (\n            first: 10, sortBy: $sortBy, filter: $filter, channel: $channel\n        ) {\n            edges {\n                node {\n                    name\n                    slug\n                }\n            }\n        }\n    }\n",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 223085,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/tests/test_build_ext.py",
        "file_name": "test_build_ext.py",
        "fun_name": "_try_compile_deployment_target",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _try_compile_deployment_target(self, operator, target):\n        orig_environ = os.environ\n        os.environ = orig_environ.copy()\n        self.addCleanup(setattr, os, 'environ', orig_environ)\n\n        if target is None:\n            if os.environ.get('MACOSX_DEPLOYMENT_TARGET'):\n                del os.environ['MACOSX_DEPLOYMENT_TARGET']\n        else:\n            os.environ['MACOSX_DEPLOYMENT_TARGET'] = target\n\n        deptarget_c = os.path.join(self.tmp_dir, 'deptargetmodule.c')\n\n        with open(deptarget_c, 'w') as fp:\n            fp.write(textwrap.dedent( % operator))\n\n        # get the deployment target that the interpreter was built with\n        target = sysconfig.get_config_var('MACOSX_DEPLOYMENT_TARGET')\n        target = tuple(map(int, target.split('.')[0:2]))\n        # format the target value as defined in the Apple\n        # Availability Macros.  We can't use the macro names since\n        # at least one value we test with will not exist yet.\n        if target[:2] < (10, 10):\n            # for 10.1 through 10.9.x -> \"10n0\"\n            target = '%02d%01d0' % target\n        else:\n            # for 10.10 and beyond -> \"10nn00\"\n            if len(target) >= 2:\n                target = '%02d%02d00' % target\n            else:\n                # 11 and later can have no minor version (11 instead of 11.0)\n                target = '%02d0000' % target\n        deptarget_ext = Extension(\n            'deptarget',\n            [deptarget_c],\n            extra_compile_args=['-DTARGET=%s'%(target,)],\n        )\n        dist = Distribution({\n            'name': 'deptarget',\n            'ext_modules': [deptarget_ext]\n        })\n        dist.package_dir = self.tmp_dir\n        cmd = self.build_ext(dist)\n        cmd.build_lib = self.tmp_dir\n        cmd.build_temp = self.tmp_dir\n\n        try:\n            old_stdout = sys.stdout\n            if not support.verbose:\n                # silence compiler output\n                sys.stdout = StringIO()\n            try:\n                cmd.ensure_finalized()\n                cmd.run()\n            finally:\n                sys.stdout = old_stdout\n\n        except CompileError:\n            self.fail(\"Wrong deployment target during compilation\")\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 704,
        "n_words": 196,
        "vocab_size": 129,
        "complexity": 8,
        "nloc": 55,
        "token_counts": 288,
        "n_ast_nodes": 500,
        "n_identifiers": 47,
        "d_id": 56858,
        "documentation": {
            "docstring": "\\\n                #include <AvailabilityMacros.h>\n\n                int dummy;\n\n                #if TARGET %s MAC_OS_X_VERSION_MIN_REQUIRED\n                #else\n                #error \"Unexpected target\"\n                #endif\n\n            ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 115,
            "language": "en"
        }
    },
    {
        "id": 80233,
        "commit_id": "10dbbddaf35607e4257f50dd960520a1268dd225",
        "repo": "wagtail",
        "path": "wagtail/snippets/tests/test_locking.py",
        "file_name": "test_locking.py",
        "fun_name": "test_edit_post_locked_by_self",
        "commit_message": "Add tests for locking snippets",
        "code": "def test_edit_post_locked_by_self(self):\n        \n        # Lock the snippet\n        self.lock_snippet(self.user)\n\n        # Try to edit the snippet\n        response = self.client.post(\n            self.get_url(\"edit\"),\n            {\"text\": \"Edited while locked\"},\n            follow=True,\n        )\n        self.refresh_snippet()\n\n        # Should not show error message\n        self.assertNotContains(\n            response,\n            f\"The {self.model_name} could not be saved as it is locked\",\n        )\n\n        # Check that the snippet is still locked\n        self.assertTrue(self.snippet.locked)\n\n        # Check that the snippet is edited\n        self.assertEqual(self.snippet.text, \"Edited while locked\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 216,
        "n_words": 63,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 77,
        "n_ast_nodes": 142,
        "n_identifiers": 17,
        "d_id": 17037,
        "documentation": {
            "docstring": "A user can edit a snippet that is locked by themselves.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 131233,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tests/test_advanced_4.py",
        "file_name": "test_advanced_4.py",
        "fun_name": "test_jemalloc_env_var_propagate",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_jemalloc_env_var_propagate():\n    \n    gcs_ptype = ray.ray_constants.PROCESS_TYPE_GCS_SERVER\n    \n    expected = {}\n    actual = ray._private.services.propagate_jemalloc_env_var(\n        jemalloc_path=\"\", jemalloc_conf=\"\", jemalloc_comps=[], process_type=gcs_ptype\n    )\n    assert actual == expected\n    actual = ray._private.services.propagate_jemalloc_env_var(\n        jemalloc_path=None,\n        jemalloc_conf=\"a,b,c\",\n        jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER],\n        process_type=gcs_ptype,\n    )\n    assert actual == expected\n    \n    library_path = \"/abc\"\n    expected = {\"LD_PRELOAD\": library_path}\n    actual = ray._private.services.propagate_jemalloc_env_var(\n        jemalloc_path=library_path,\n        jemalloc_conf=\"\",\n        jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER],\n        process_type=gcs_ptype,\n    )\n    assert actual == expected\n\n    # comps should be a list type.\n    with pytest.raises(AssertionError):\n        ray._private.services.propagate_jemalloc_env_var(\n            jemalloc_path=library_path,\n            jemalloc_conf=\"\",\n            jemalloc_comps=\"ray.ray_constants.PROCESS_TYPE_GCS_SERVER,\",\n            process_type=gcs_ptype,\n        )\n\n    # When comps don't match the process_type, it should return an empty dict.\n    expected = {}\n    actual = ray._private.services.propagate_jemalloc_env_var(\n        jemalloc_path=library_path,\n        jemalloc_conf=\"\",\n        jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_RAYLET],\n        process_type=gcs_ptype,\n    )\n    \n    library_path = \"/abc\"\n    malloc_conf = \"a,b,c\"\n    expected = {\"LD_PRELOAD\": library_path, \"MALLOC_CONF\": malloc_conf}\n    actual = ray._private.services.propagate_jemalloc_env_var(\n        jemalloc_path=library_path,\n        jemalloc_conf=malloc_conf,\n        jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER],\n        process_type=gcs_ptype,\n    )\n    assert actual == expected\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 381,
        "n_words": 114,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 57,
        "token_counts": 258,
        "n_ast_nodes": 420,
        "n_identifiers": 20,
        "d_id": 29488,
        "documentation": {
            "docstring": "Test `propagate_jemalloc_env_var`\n    If the shared library path is not specified,\n    it should return an empty dict.\n    \n    When the shared library is specified\n    \n    When the malloc config is specified\n    ",
            "n_words": 28,
            "vocab_size": 20,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 264682,
        "commit_id": "1636508a6ac8df6b93d0ea5c621c174f605fd47a",
        "repo": "netbox",
        "path": "netbox/users/models.py",
        "file_name": "models.py",
        "fun_name": "create_userconfig",
        "commit_message": "Fixes #9156: Fix loading UserConfig data from fixtures",
        "code": "def create_userconfig(instance, created, raw=False, **kwargs):\n    \n    if created and not raw:\n        config = get_config()\n        UserConfig(user=instance, data=config.DEFAULT_USER_PREFERENCES).save()\n\n\n#\n# REST API\n#\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 37,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 42,
        "n_ast_nodes": 71,
        "n_identifiers": 12,
        "d_id": 77785,
        "documentation": {
            "docstring": "\n    Automatically create a new UserConfig when a new User is created. Skip this if importing a user from a fixture.\n    ",
            "n_words": 20,
            "vocab_size": 16,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 167375,
        "commit_id": "7d2f9b8d59908fbf57c6453bc41891efbfe981a6",
        "repo": "pandas",
        "path": "pandas/io/pytables.py",
        "file_name": "pytables.py",
        "fun_name": "validate_attr",
        "commit_message": "TYP: some return annotations in pytables.py (#47512)",
        "code": "def validate_attr(self, append) -> None:\n        \n        if append:\n            existing_fields = getattr(self.attrs, self.kind_attr, None)\n            if existing_fields is not None and existing_fields != list(self.values):\n                raise ValueError(\"appended items do not match existing items in table!\")\n\n            existing_dtype = getattr(self.attrs, self.dtype_attr, None)\n            if existing_dtype is not None and existing_dtype != self.dtype:\n                raise ValueError(\n                    \"appended items dtype do not match existing items dtype in table!\"\n                )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 181,
        "n_words": 59,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 11,
        "token_counts": 78,
        "n_ast_nodes": 124,
        "n_identifiers": 13,
        "d_id": 39982,
        "documentation": {
            "docstring": "validate that we have the same order as the existing & same dtype",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 180326,
        "commit_id": "cb2713e7050f2783493736e43a6b704865ce61c5",
        "repo": "gradio",
        "path": "gradio/external.py",
        "file_name": "external.py",
        "fun_name": "load_blocks_from_repo",
        "commit_message": "Getting Interface.load() working for 2.x and 3.x models and Spaces (#1361)\n\n* version\r\n\r\n* refactor for model and 2.x spaces\r\n\r\n* fixing tests\r\n\r\n* fixed tests\r\n\r\n* getting there...\r\n\r\n* formatting\r\n\r\n* formatting\r\n\r\n* fixes\r\n\r\n* formatting\r\n\r\n* external dependencies working\r\n\r\n* formatting\r\n\r\n* loading from 3.x\r\n\r\n* changes\r\n\r\n* wow finally it's working\r\n\r\n* fixed formatting\r\n\r\n* better error for spaces\r\n\r\n* better error for spaces\r\n\r\n* fixed 3.x bug\r\n\r\n* formatting",
        "code": "def load_blocks_from_repo(name, src=None, api_key=None, alias=None, **kwargs):\n    \n    if src is None:\n        tokens = name.split(\n            \"/\"\n        )  # Separate the source (e.g. \"huggingface\") from the repo name (e.g. \"google/vit-base-patch16-224\")\n        assert (\n            len(tokens) > 1\n        ), \"Either `src` parameter must be provided, or `name` must be formatted as {src}/{repo name}\"\n        src = tokens[0]\n        name = \"/\".join(tokens[1:])\n    assert src.lower() in factory_methods, \"parameter: src must be one of {}\".format(\n        factory_methods.keys()\n    )\n    blocks: gradio.Blocks = factory_methods[src](name, api_key, alias, **kwargs)\n    return blocks\n\n",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 165,
        "n_words": 75,
        "vocab_size": 61,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 104,
        "n_ast_nodes": 167,
        "n_identifiers": 17,
        "d_id": 43144,
        "documentation": {
            "docstring": "Creates and returns a Blocks instance from several kinds of Hugging Face repos:\n    1) A model repo\n    2) A Spaces repo running Gradio 2.x\n    3) A Spaces repo running Gradio 3.x\n    ",
            "n_words": 31,
            "vocab_size": 24,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 61419,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "get_backend_for_dir",
        "commit_message": "upd; format",
        "code": "def get_backend_for_dir(self, location):\n        # type: (str) -> Optional[VersionControl]\n        \n        vcs_backends = {}\n        for vcs_backend in self._registry.values():\n            repo_path = vcs_backend.get_repository_root(location)\n            if not repo_path:\n                continue\n            logger.debug('Determine that %s uses VCS: %s',\n                         location, vcs_backend.name)\n            vcs_backends[repo_path] = vcs_backend\n\n        if not vcs_backends:\n            return None\n\n        # Choose the VCS in the inner-most directory. Since all repository\n        # roots found here would be either `location` or one of its\n        # parents, the longest path should have the most path components,\n        # i.e. the backend representing the inner-most repository.\n        inner_most_repo_path = max(vcs_backends, key=len)\n        return vcs_backends[inner_most_repo_path]\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 257,
        "n_words": 86,
        "vocab_size": 67,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 75,
        "n_ast_nodes": 126,
        "n_identifiers": 16,
        "d_id": 12562,
        "documentation": {
            "docstring": "\n        Return a VersionControl object if a repository of that type is found\n        at the given directory.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 208258,
        "commit_id": "3a7a82af9588629dad5807e0862bacbbd5d7a7f2",
        "repo": "celery",
        "path": "celery/canvas.py",
        "file_name": "canvas.py",
        "fun_name": "_stamp_regen_task",
        "commit_message": "Canvas.py doc enhancement (#7889)\n\n* Enhanced doc for canvas.maybe_unroll_group()\r\n\r\n* Enhanced doc for canvas._stamp_regen_task()\r\n\r\n* Enhanced doc for canvas._merge_dictionaries()",
        "code": "def _stamp_regen_task(task, visitor, **headers):\n    \n\n    task.stamp(visitor=visitor, **headers)\n    return task\n\n",
        "url": "https://github.com/celery/celery.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 52267,
        "documentation": {
            "docstring": "When stamping a sequence of tasks created by a generator,\n    we use this function to stamp each task in the generator\n    without exhausting it.",
            "n_words": 24,
            "vocab_size": 23,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 191835,
        "commit_id": "11e1a8a3fa8d13513fe926b731fb907a066af2a1",
        "repo": "ydata-profiling",
        "path": "src/pandas_profiling/visualisation/context.py",
        "file_name": "context.py",
        "fun_name": "manage_matplotlib_context",
        "commit_message": "fix: change context managed backend (#1149)",
        "code": "def manage_matplotlib_context() -> Any:\n    \n    originalRcParams = matplotlib.rcParams.copy()\n\n    # Credits for this style go to the ggplot and seaborn packages.\n    #   We copied the style file to remove dependencies on the Seaborn package.\n    #   Check it out, it's an awesome library for plotting\n    customRcParams = {\n        \"patch.facecolor\": \"#348ABD\",  # blue\n        \"patch.antialiased\": True,\n        \"font.size\": 10.0,\n        \"figure.edgecolor\": \"0.50\",\n        # Seaborn common parameters\n        \"figure.facecolor\": \"white\",\n        \"text.color\": \".15\",\n        \"axes.labelcolor\": \".15\",\n        \"legend.numpoints\": 1,\n        \"legend.scatterpoints\": 1,\n        \"xtick.direction\": \"out\",\n        \"ytick.direction\": \"out\",\n        \"xtick.color\": \".15\",\n        \"ytick.color\": \".15\",\n        \"axes.axisbelow\": True,\n        \"image.cmap\": \"Greys\",\n        \"font.family\": [\"sans-serif\"],\n        \"font.sans-serif\": [\n            \"Arial\",\n            \"Liberation Sans\",\n            \"Bitstream Vera Sans\",\n            \"sans-serif\",\n        ],\n        \"grid.linestyle\": \"-\",\n        \"lines.solid_capstyle\": \"round\",\n        # Seaborn darkgrid parameters\n        # .15 = dark_gray\n        # .8 = light_gray\n        \"axes.grid\": True,\n        \"axes.facecolor\": \"#EAEAF2\",\n        \"axes.edgecolor\": \"white\",\n        \"axes.linewidth\": 0,\n        \"grid.color\": \"white\",\n        # Seaborn notebook context\n        \"figure.figsize\": [8.0, 5.5],\n        \"axes.labelsize\": 11,\n        \"axes.titlesize\": 12,\n        \"xtick.labelsize\": 10,\n        \"ytick.labelsize\": 10,\n        \"legend.fontsize\": 10,\n        \"grid.linewidth\": 1,\n        \"lines.linewidth\": 1.75,\n        \"patch.linewidth\": 0.3,\n        \"lines.markersize\": 7,\n        \"lines.markeredgewidth\": 0,\n        \"xtick.major.width\": 1,\n        \"ytick.major.width\": 1,\n        \"xtick.minor.width\": 0.5,\n        \"ytick.minor.width\": 0.5,\n        \"xtick.major.pad\": 7,\n        \"ytick.major.pad\": 7,\n        \"backend\": \"agg\",\n    }\n\n    try:\n        register_matplotlib_converters()\n        matplotlib.rcParams.update(customRcParams)\n        sns.set_style(style=\"white\")\n        yield\n    finally:\n        deregister_matplotlib_converters()  # revert to original unit registries\n        with warnings.catch_warnings():\n            warnings.filterwarnings(\"ignore\", category=matplotlib.cbook.mplDeprecation)\n            matplotlib.rcParams.update(originalRcParams)  # revert to original rcParams\n",
        "url": "https://github.com/ydataai/ydata-profiling.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 662,
        "n_words": 184,
        "vocab_size": 139,
        "complexity": 2,
        "nloc": 62,
        "token_counts": 273,
        "n_ast_nodes": 503,
        "n_identifiers": 19,
        "d_id": 46847,
        "documentation": {
            "docstring": "Return a context manager for temporarily changing matplotlib unit registries and rcParams.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 102175,
        "commit_id": "bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d",
        "repo": "pytorch",
        "path": "tools/test/test_gen_backend_stubs.py",
        "file_name": "test_gen_backend_stubs.py",
        "fun_name": "test_empty_backend",
        "commit_message": "Revert \"Revert D32498569: allow external backend codegen to toggle whether to generate out= and inplace kernels\" (#69950)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/69950\n\nThis reverts commit f6cad53443704dfe5a20cc62bee14d91e3bffcaa.\n\nTest Plan: Imported from OSS\n\nReviewed By: albanD\n\nDifferential Revision: D33113545\n\nPulled By: bdhirsh\n\nfbshipit-source-id: d6590294662588d36c09662dea65919ad4e1e288",
        "code": "def test_empty_backend(self) -> None:\n        yaml_str = \n        output_error = self.get_errors_from_gen_backend_stubs(yaml_str)\n        self.assertExpectedInline(output_error, )\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 26,
        "n_ast_nodes": 47,
        "n_identifiers": 6,
        "d_id": 21490,
        "documentation": {
            "docstring": "\\\nbackend:\ncpp_namespace: torch_xla\nsupported:\n- absYou must provide a value for \"backend\"",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 136419,
        "commit_id": "e368dd9b4e10026767df66d1811a92bd8ca2d8f9",
        "repo": "ray",
        "path": "rllib/algorithms/algorithm.py",
        "file_name": "algorithm.py",
        "fun_name": "_run_offline_evaluation",
        "commit_message": "[RLlib] By-pass Evaluation workers when doing OPE (#30135)\n\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def _run_offline_evaluation(self):\n        \n        assert len(self.workers.local_worker().policy_map) == 1\n\n        parallelism = self.evaluation_config.evaluation_num_workers or 1\n        offline_eval_results = {\"off_policy_estimator\": {}}\n        for evaluator_name, offline_evaluator in self.reward_estimators.items():\n            offline_eval_results[\"off_policy_estimator\"][\n                evaluator_name\n            ] = offline_evaluator.estimate_on_dataset(\n                self.evaluation_dataset,\n                n_parallelism=parallelism,\n            )\n        return offline_eval_results\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 150,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 74,
        "n_ast_nodes": 121,
        "n_identifiers": 17,
        "d_id": 30913,
        "documentation": {
            "docstring": "Runs offline evaluation via `OfflineEvaluator.estimate_on_dataset()` API.\n\n        This method will be used when `evaluation_dataset` is provided.\n        Note: This will only work if the policy is a single agent policy.\n\n        Returns:\n            The results dict from the offline evaluation call.\n        ",
            "n_words": 37,
            "vocab_size": 31,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 112126,
        "commit_id": "14d2966b9e91ae16dcc39de8f41017a75cec8ff9",
        "repo": "nni",
        "path": "nni/retiarii/oneshot/pytorch/base_lightning.py",
        "file_name": "base_lightning.py",
        "fun_name": "configure_optimizers",
        "commit_message": "Valuechoice oneshot lightning (#4602)",
        "code": "def configure_optimizers(self):\n        \n        # pylint: disable=assignment-from-none\n        arc_optimizers = self.configure_architecture_optimizers()\n        if arc_optimizers is None:\n            return self.model.configure_optimizers()\n\n        if isinstance(arc_optimizers, optim.Optimizer):\n            arc_optimizers = [arc_optimizers]\n        self.arc_optim_count = len(arc_optimizers)\n\n        # The return values ``frequency`` and ``monitor`` are ignored because lightning requires\n        # ``len(optimizers) == len(frequency)``, and gradient backword is handled manually.\n        # For data structure of variables below, please see pytorch lightning docs of ``configure_optimizers``.\n        w_optimizers, lr_schedulers, self.frequencies, monitor = \\\n            self.trainer._configure_optimizers(self.model.configure_optimizers())\n        lr_schedulers = self.trainer._configure_schedulers(lr_schedulers, monitor, not self.automatic_optimization)\n        if any(sch[\"scheduler\"].optimizer not in w_optimizers for sch in lr_schedulers):\n            raise Exception(\n                \"Some schedulers are attached with an optimizer that wasn't returned from `configure_optimizers`.\"\n            )\n\n        # variables used to handle optimizer frequency\n        self.cur_optimizer_step = 0\n        self.cur_optimizer_index = 0\n\n        return arc_optimizers + w_optimizers, lr_schedulers\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 296,
        "n_words": 114,
        "vocab_size": 85,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 130,
        "n_ast_nodes": 211,
        "n_identifiers": 24,
        "d_id": 24584,
        "documentation": {
            "docstring": "\n        Combine architecture optimizers and user's model optimizers.\n        You can overwrite configure_architecture_optimizers if architecture optimizers are needed in your NAS algorithm.\n        For now ``self.model`` is tested against :class:`nni.retiarii.evaluator.pytorch.lightning._SupervisedLearningModule`\n        and it only returns 1 optimizer.\n        But for extendibility, codes for other return value types are also implemented.\n        ",
            "n_words": 45,
            "vocab_size": 40,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 192419,
        "commit_id": "289fce29b3e2392114aadbe7a419df0f2e3ac1be",
        "repo": "vision",
        "path": "torchvision/transforms/_functional_video.py",
        "file_name": "_functional_video.py",
        "fun_name": "crop",
        "commit_message": "Replace asserts with exceptions (#5587)\n\n* replace most asserts with exceptions\r\n\r\n* fix formating issues\r\n\r\n* fix linting and remove more asserts\r\n\r\n* fix regresion\r\n\r\n* fix regresion\r\n\r\n* fix bug\r\n\r\n* apply ufmt\r\n\r\n* apply ufmt\r\n\r\n* fix tests\r\n\r\n* fix format\r\n\r\n* fix None check\r\n\r\n* fix detection models tests\r\n\r\n* non scriptable any\r\n\r\n* add more checks for None values\r\n\r\n* fix retinanet test\r\n\r\n* fix retinanet test\r\n\r\n* Update references/classification/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update references/classification/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update references/optical_flow/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update references/optical_flow/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update references/optical_flow/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* make value checks more pythonic:\r\n\r\n* Update references/optical_flow/transforms.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* make value checks more pythonic\r\n\r\n* make more checks pythonic\r\n\r\n* fix bug\r\n\r\n* appy ufmt\r\n\r\n* fix tracing issues\r\n\r\n* fib typos\r\n\r\n* fix lint\r\n\r\n* remove unecessary f-strings\r\n\r\n* fix bug\r\n\r\n* Update torchvision/datasets/mnist.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/datasets/mnist.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/ops/boxes.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/ops/poolers.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/utils.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* address PR comments\r\n\r\n* Update torchvision/io/_video_opt.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/models/detection/generalized_rcnn.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/models/feature_extraction.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* Update torchvision/models/optical_flow/raft.py\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>\r\n\r\n* address PR comments\r\n\r\n* addressing further pr comments\r\n\r\n* fix bug\r\n\r\n* remove unecessary else\r\n\r\n* apply ufmt\r\n\r\n* last pr comment\r\n\r\n* replace RuntimeErrors\r\n\r\nCo-authored-by: Nicolas Hug <contact@nicolas-hug.com>",
        "code": "def crop(clip, i, j, h, w):\n    \n    if len(clip.size()) != 4:\n        raise ValueError(\"clip should be a 4D tensor\")\n    return clip[..., i : i + h, j : j + w]\n\n",
        "url": "https://github.com/pytorch/vision.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 45,
        "n_words": 29,
        "vocab_size": 24,
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        "nloc": 4,
        "token_counts": 48,
        "n_ast_nodes": 74,
        "n_identifiers": 9,
        "d_id": 46893,
        "documentation": {
            "docstring": "\n    Args:\n        clip (torch.tensor): Video clip to be cropped. Size is (C, T, H, W)\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 269598,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "binary_crossentropy",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def binary_crossentropy(target, output, from_logits=False):\n    \n    target = tf.convert_to_tensor(target)\n    output = tf.convert_to_tensor(output)\n\n    # Use logits whenever they are available. `softmax` and `sigmoid`\n    # activations cache logits on the `output` Tensor.\n    if hasattr(output, \"_keras_logits\"):\n        output = output._keras_logits  # pylint: disable=protected-access\n        if from_logits:\n            warnings.warn(\n                '\"`binary_crossentropy` received `from_logits=True`, but the `output`'\n                \" argument was produced by a sigmoid or softmax activation and thus \"\n                'does not represent logits. Was this intended?\"',\n                stacklevel=2,\n            )\n        from_logits = True\n\n    if from_logits:\n        return tf.nn.sigmoid_cross_entropy_with_logits(\n            labels=target, logits=output\n        )\n\n    if (\n        not isinstance(output, (tf.__internal__.EagerTensor, tf.Variable))\n        and output.op.type == \"Sigmoid\"\n    ) and not hasattr(output, \"_keras_history\"):\n        # When sigmoid activation function is used for output operation, we\n        # use logits from the sigmoid function directly to compute loss in order\n        # to prevent collapsing zero when training.\n        assert len(output.op.inputs) == 1\n        output = output.op.inputs[0]\n        return tf.nn.sigmoid_cross_entropy_with_logits(\n            labels=target, logits=output\n        )\n\n    epsilon_ = _constant_to_tensor(epsilon(), output.dtype.base_dtype)\n    output = tf.clip_by_value(output, epsilon_, 1.0 - epsilon_)\n\n    # Compute cross entropy from probabilities.\n    bce = target * tf.math.log(output + epsilon())\n    bce += (1 - target) * tf.math.log(1 - output + epsilon())\n    return -bce\n\n\n@keras_export(\"keras.backend.binary_focal_crossentropy\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.binary_focal_crossentropy\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 421,
        "n_words": 176,
        "vocab_size": 121,
        "complexity": 7,
        "nloc": 31,
        "token_counts": 222,
        "n_ast_nodes": 387,
        "n_identifiers": 37,
        "d_id": 80219,
        "documentation": {
            "docstring": "Binary crossentropy between an output tensor and a target tensor.\n\n    Args:\n        target: A tensor with the same shape as `output`.\n        output: A tensor.\n        from_logits: Whether `output` is expected to be a logits tensor.\n            By default, we consider that `output`\n            encodes a probability distribution.\n\n    Returns:\n        A tensor.\n    ",
            "n_words": 46,
            "vocab_size": 37,
            "n_whitespaces": 105,
            "language": "en"
        }
    },
    {
        "id": 281704,
        "commit_id": "6a66f3f3ed934e0615ff4ba283ee67fcc43d3656",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/custom/quantitative_analysis/qa_controller.py",
        "file_name": "qa_controller.py",
        "fun_name": "print_help",
        "commit_message": "Custom data context (#1193)\n\n* Add first iteration of custom context\r\n\r\n* Add sample data + improve plot\r\n\r\n* Change `head` to `show` with sorting and limit.  Add \"-x\" to plot and dynamic update of completer\r\n\r\n* generate random time series for test csv\r\n\r\n* Make columns lower case.  Check if date is in columns and convert to timestamp.  Improve plotting for dates\r\n\r\n* Add qa to custom\r\n\r\n* Add pred to custom\r\n\r\n* Hugooooo\r\n\r\n* Testing\r\n\r\n* dang whitespace\r\n\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>",
        "code": "def print_help(self):\n        \n        help_text = f\n        console.print(text=help_text, menu=\"Custom - Quantitative Analysis\")\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 22,
        "n_ast_nodes": 54,
        "n_identifiers": 9,
        "d_id": 83981,
        "documentation": {
            "docstring": "Print help[cmds]\n   load        load new data file\n   pick        pick target column for analysis[/cmds]\n\n[param]File: [/param]{self.file}\n[param]Target Column: [/param]{self.target}\n[cmds]\n[info]Statistics:[/info]\n    summary     brief summary statistics of loaded stock.\n    normality   normality statistics and tests\n    unitroot    unit root test for stationarity (ADF, KPSS)\n[info]Plots:[/info]\n    line        line plot of selected target\n    hist        histogram with density plot\n    cdf         cumulative distribution function\n    bw          box and whisker plot\n    acf         (partial) auto-correlation function differentials of prices\n    qqplot      residuals against standard normal curve\n[info]Rolling Metrics:[/info]\n    rolling     rolling mean and std deviation of prices\n    spread      rolling variance and std deviation of prices\n    quantile    rolling median and quantile of prices\n    skew        rolling skewness of distribution of prices\n    kurtosis    rolling kurtosis of distribution of prices\n[info]Other:[/info]\n    raw         print raw data\n    decompose   decomposition in cyclic-trend, season, and residuals of prices\n    cusum       detects abrupt changes using cumulative sum algorithm of prices[/cmds]\n        ",
            "n_words": 137,
            "vocab_size": 89,
            "n_whitespaces": 297,
            "language": "en"
        }
    },
    {
        "id": 217668,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/html/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "unescape",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def unescape(s):\n    \n    if '&' not in s:\n        return s\n    return _charref.sub(_replace_charref, s)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 28,
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        "vocab_size": 11,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 23,
        "n_ast_nodes": 40,
        "n_identifiers": 5,
        "d_id": 54879,
        "documentation": {
            "docstring": "\n    Convert all named and numeric character references (e.g. &gt;, &#62;,\n    &x3e;) in the string s to the corresponding unicode characters.\n    This function uses the rules defined by the HTML 5 standard\n    for both valid and invalid character references, and the list of\n    HTML 5 named character references defined in html.entities.html5.\n    ",
            "n_words": 50,
            "vocab_size": 36,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 9407,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/external/stylegan2/dnnlib/tflib/ops/upfirdn_2d.py",
        "file_name": "upfirdn_2d.py",
        "fun_name": "upsample_conv_2d",
        "commit_message": "initialize ostec",
        "code": "def upsample_conv_2d(x, w, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):\n    r\n\n    assert isinstance(factor, int) and factor >= 1\n\n    # Check weight shape.\n    w = tf.convert_to_tensor(w)\n    assert w.shape.rank == 4\n    convH = w.shape[0].value\n    convW = w.shape[1].value\n    inC = _shape(w, 2)\n    outC = _shape(w, 3)\n    assert convW == convH\n\n    # Setup filter kernel.\n    if k is None:\n        k = [1] * factor\n    k = _setup_kernel(k) * (gain * (factor ** 2))\n    p = (k.shape[0] - factor) - (convW - 1)\n\n    # Determine data dimensions.\n    if data_format == 'NCHW':\n        stride = [1, 1, factor, factor]\n        output_shape = [_shape(x, 0), outC, (_shape(x, 2) - 1) * factor + convH, (_shape(x, 3) - 1) * factor + convW]\n        num_groups = _shape(x, 1) // inC\n    else:\n        stride = [1, factor, factor, 1]\n        output_shape = [_shape(x, 0), (_shape(x, 1) - 1) * factor + convH, (_shape(x, 2) - 1) * factor + convW, outC]\n        num_groups = _shape(x, 3) // inC\n\n    # Transpose weights.\n    w = tf.reshape(w, [convH, convW, inC, num_groups, -1])\n    w = tf.transpose(w[::-1, ::-1], [0, 1, 4, 3, 2])\n    w = tf.reshape(w, [convH, convW, -1, num_groups * inC])\n\n    # Execute.\n    x = tf.nn.conv2d_transpose(x, w, output_shape=output_shape, strides=stride, padding='VALID', data_format=data_format)\n    return _simple_upfirdn_2d(x, k, pad0=(p+1)//2+factor-1, pad1=p//2+1, data_format=data_format, impl=impl)\n\n#----------------------------------------------------------------------------\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 317,
        "n_words": 198,
        "vocab_size": 110,
        "complexity": 4,
        "nloc": 48,
        "token_counts": 387,
        "n_ast_nodes": 602,
        "n_identifiers": 34,
        "d_id": 1607,
        "documentation": {
            "docstring": "Fused `upsample_2d()` followed by `tf.nn.conv2d()`.\n\n    Padding is performed only once at the beginning, not between the operations.\n    The fused op is considerably more efficient than performing the same calculation\n    using standard TensorFlow ops. It supports gradients of arbitrary order.\n\n    Args:\n        x:            Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.\n        w:            Weight tensor of the shape `[filterH, filterW, inChannels, outChannels]`.\n                      Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`.\n        k:            FIR filter of the shape `[firH, firW]` or `[firN]` (separable).\n                      The default is `[1] * factor`, which corresponds to nearest-neighbor\n                      upsampling.\n        factor:       Integer upsampling factor (default: 2).\n        gain:         Scaling factor for signal magnitude (default: 1.0).\n        data_format:  `'NCHW'` or `'NHWC'` (default: `'NCHW'`).\n        impl:         Name of the implementation to use. Can be `\"ref\"` or `\"cuda\"` (default).\n\n    Returns:\n        Tensor of the shape `[N, C, H * factor, W * factor]` or\n        `[N, H * factor, W * factor, C]`, and same datatype as `x`.\n    ",
            "n_words": 158,
            "vocab_size": 114,
            "n_whitespaces": 358,
            "language": "en"
        }
    },
    {
        "id": 65150,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/asset_depreciations_and_balances/asset_depreciations_and_balances.py",
        "file_name": "asset_depreciations_and_balances.py",
        "fun_name": "get_assets",
        "commit_message": "style: format code with black",
        "code": "def get_assets(filters):\n\treturn frappe.db.sql(\n\t\t,\n\t\t{\"to_date\": filters.to_date, \"from_date\": filters.from_date, \"company\": filters.company},\n\t\tas_dict=1,\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 7,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 49,
        "token_counts": 39,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 13808,
        "documentation": {
            "docstring": "\n\t\tSELECT results.asset_category,\n\t\t\t   sum(results.accumulated_depreciation_as_on_from_date) as accumulated_depreciation_as_on_from_date,\n\t\t\t   sum(results.depreciation_eliminated_during_the_period) as depreciation_eliminated_during_the_period,\n\t\t\t   sum(results.depreciation_amount_during_the_period) as depreciation_amount_during_the_period\n\t\tfrom (SELECT a.asset_category,\n\t\t\t\t   ifnull(sum(case when ds.schedule_date < %(from_date)s and (ifnull(a.disposal_date, 0) = 0 or a.disposal_date >= %(from_date)s) then\n\t\t\t\t\t\t\t\t   ds.depreciation_amount\n\t\t\t\t\t\t\t  else\n\t\t\t\t\t\t\t\t   0\n\t\t\t\t\t\t\t  end), 0) as accumulated_depreciation_as_on_from_date,\n\t\t\t\t   ifnull(sum(case when ifnull(a.disposal_date, 0) != 0 and a.disposal_date >= %(from_date)s\n\t\t\t\t\t\t\t\t\t\tand a.disposal_date <= %(to_date)s and ds.schedule_date <= a.disposal_date then\n\t\t\t\t\t\t\t\t   ds.depreciation_amount\n\t\t\t\t\t\t\t  else\n\t\t\t\t\t\t\t\t   0\n\t\t\t\t\t\t\t  end), 0) as depreciation_eliminated_during_the_period,\n\t\t\t\t   ifnull(sum(case when ds.schedule_date >= %(from_date)s and ds.schedule_date <= %(to_date)s\n\t\t\t\t\t\t\t\t\t\tand (ifnull(a.disposal_date, 0) = 0 or ds.schedule_date <= a.disposal_date) then\n\t\t\t\t\t\t\t\t   ds.depreciation_amount\n\t\t\t\t\t\t\t  else\n\t\t\t\t\t\t\t\t   0\n\t\t\t\t\t\t\t  end), 0) as depreciation_amount_during_the_period\n\t\t\tfrom `tabAsset` a, `tabDepreciation Schedule` ds\n\t\t\twhere a.docstatus=1 and a.company=%(company)s and a.purchase_date <= %(to_date)s and a.name = ds.parent and ifnull(ds.journal_entry, '') != ''\n\t\t\tgroup by a.asset_category\n\t\t\tunion\n\t\t\tSELECT a.asset_category,\n\t\t\t\t   ifnull(sum(case when ifnull(a.disposal_date, 0) != 0 and (a.disposal_date < %(from_date)s or a.disposal_date > %(to_date)s) then\n\t\t\t\t\t\t\t\t\t0\n\t\t\t\t\t\t\t   else\n\t\t\t\t\t\t\t\t\ta.opening_accumulated_depreciation\n\t\t\t\t\t\t\t   end), 0) as accumulated_depreciation_as_on_from_date,\n\t\t\t\t   ifnull(sum(case when a.disposal_date >= %(from_date)s and a.disposal_date <= %(to_date)s then\n\t\t\t\t\t\t\t\t   a.opening_accumulated_depreciation\n\t\t\t\t\t\t\t  else\n\t\t\t\t\t\t\t\t   0\n\t\t\t\t\t\t\t  end), 0) as depreciation_eliminated_during_the_period,\n\t\t\t\t   0 as depreciation_amount_during_the_period\n\t\t\tfrom `tabAsset` a\n\t\t\twhere a.docstatus=1 and a.company=%(company)s and a.purchase_date <= %(to_date)s\n\t\t\tgroup by a.asset_category) as results\n\t\tgroup by results.asset_category\n\t\t",
            "n_words": 178,
            "vocab_size": 61,
            "n_whitespaces": 209,
            "language": "en"
        }
    },
    {
        "id": 198878,
        "commit_id": "68bd82de645a61f4bbc0b6246e70959373c9cba2",
        "repo": "sympy",
        "path": "sympy/printing/aesaracode.py",
        "file_name": "aesaracode.py",
        "fun_name": "_get_or_create",
        "commit_message": "fix(printing): change Aesara argument broadcastable to shape",
        "code": "def _get_or_create(self, s, name=None, dtype=None, broadcastable=None):\n        \n\n        # Defaults\n        if name is None:\n            name = s.name\n        if dtype is None:\n            dtype = 'floatX'\n        if broadcastable is None:\n            broadcastable = ()\n\n        key = self._get_key(s, name, dtype=dtype, broadcastable=broadcastable)\n\n        if key in self.cache:\n            return self.cache[key]\n\n        value = aet.tensor(name=name, dtype=dtype, shape=broadcastable)\n        self.cache[key] = value\n        return value\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 165,
        "n_words": 51,
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        "complexity": 5,
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        "token_counts": 107,
        "n_ast_nodes": 164,
        "n_identifiers": 13,
        "d_id": 49056,
        "documentation": {
            "docstring": "\n        Get the Aesara variable for a SymPy symbol from the cache, or create it\n        if it does not exist.\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 265204,
        "commit_id": "fcd1daaf798d62023f999c3e09e035f7b3f47c8f",
        "repo": "netbox",
        "path": "netbox/dcim/models/device_components.py",
        "file_name": "device_components.py",
        "fun_name": "get_downstream_powerports",
        "commit_message": "Update power utilization calculations for new cabling model",
        "code": "def get_downstream_powerports(self, leg=None):\n        \n        poweroutlets = self.poweroutlets.filter(cable__isnull=False)\n        if leg:\n            poweroutlets = poweroutlets.filter(feed_leg=leg)\n        if not poweroutlets:\n            return PowerPort.objects.none()\n\n        q = Q()\n        for poweroutlet in poweroutlets:\n            q |= Q(\n                cable=poweroutlet.cable,\n                cable_end=poweroutlet.opposite_cable_end\n            )\n\n        return PowerPort.objects.filter(q)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 154,
        "n_words": 31,
        "vocab_size": 24,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 82,
        "n_ast_nodes": 132,
        "n_identifiers": 16,
        "d_id": 78026,
        "documentation": {
            "docstring": "\n        Return a queryset of all PowerPorts connected via cable to a child PowerOutlet.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 284320,
        "commit_id": "e59a30b18873f7449bc59a88c3da21894e0dbe0a",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/due_diligence/dd_controller.py",
        "file_name": "dd_controller.py",
        "fun_name": "call_news",
        "commit_message": "Add crypto DD commands (#1710)\n\n* Add github activity over time\r\n\r\n* Create tests\r\n\r\n* Update default days in chart command\r\n\r\n* Add san package to poetry\r\n\r\n* Fix tests failed\r\n\r\n* Generate fixtures\r\n\r\n* Fix tests failed\r\n\r\n* Remove sanpy package and use requests instead\r\n\r\n* Adjust index\r\n\r\n* Add hugo server\r\n\r\n* Fix datetime\r\n\r\n* Update tests\r\n\r\n* Revert \"Update tests\"\r\n\r\nThis reverts commit ffe03a7224cd830a14d2f425d7d59f00a10f27ac.\r\n\r\n* Fix tests\r\n\r\n* Regenerate cassettes & filter api tokens\r\n\r\n* Fix windows issues\r\n\r\n* Fix PR comments\r\n\r\n* Pass tests & fix comments",
        "code": "def call_news(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            prog=\"news\",\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            description=,\n        )\n\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            dest=\"limit\",\n            type=check_positive,\n            help=\"display N number records\",\n            default=10,\n        )\n\n        parser.add_argument(\n            \"-k\",\n            \"--kind\",\n            dest=\"kind\",\n            type=str,\n            help=\"Filter by category of news. Available values: news or media.\",\n            default=\"news\",\n            choices=cryptopanic_model.CATEGORIES,\n        )\n\n        parser.add_argument(\n            \"-f\",\n            \"--filter\",\n            dest=\"filter\",\n            type=str,\n            help=\"Filter by kind of news. One from list: rising|hot|bullish|bearish|important|saved|lol\",\n            default=None,\n            required=False,\n            choices=cryptopanic_model.FILTERS,\n        )\n\n        parser.add_argument(\n            \"-r\",\n            \"--region\",\n            dest=\"region\",\n            type=str,\n            help=\"Filter news by regions. Available regions are: en (English), de (Deutsch), nl (Dutch), es (Español), \"\n            \"fr (Français), it (Italiano), pt (Português), ru (Русский)\",\n            default=\"en\",\n            choices=cryptopanic_model.REGIONS,\n        )\n\n        parser.add_argument(\n            \"-s\",\n            \"--sort\",\n            dest=\"sortby\",\n            type=str,\n            help=\"Sort by given column. Default: published_at\",\n            default=\"published_at\",\n            choices=cryptopanic_model.SORT_FILTERS,\n        )\n\n        parser.add_argument(\n            \"--descend\",\n            action=\"store_false\",\n            help=\"Flag to sort in descending order (lowest first)\",\n            dest=\"descend\",\n            default=True,\n        )\n\n        parser.add_argument(\n            \"-u\",\n            \"--urls\",\n            dest=\"urls\",\n            action=\"store_false\",\n            help=\"Flag to disable urls. If you will use the flag you will hide the column with urls\",\n            default=True,\n        )\n\n        ns_parser = parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n\n        if ns_parser:\n            cryptopanic_view.display_news(\n                top=ns_parser.limit,\n                source=self.source,\n                currency=self.coin,\n                export=ns_parser.export,\n                descend=ns_parser.descend,\n                post_kind=ns_parser.kind,\n                filter_=ns_parser.filter,\n                region=ns_parser.region,\n            )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 1015,
        "n_words": 161,
        "vocab_size": 126,
        "complexity": 2,
        "nloc": 83,
        "token_counts": 301,
        "n_ast_nodes": 480,
        "n_identifiers": 43,
        "d_id": 84695,
        "documentation": {
            "docstring": "Process news commandDisplay most recent news on the given coin from CryptoPanic aggregator platform.\n            [Source: https://cryptopanic.com/]",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 107046,
        "commit_id": "c682ca40c647770a967b6b8a7615eb91c7cb3fc9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/_constrained_layout.py",
        "file_name": "_constrained_layout.py",
        "fun_name": "make_layoutgrids_gs",
        "commit_message": "FIX: better repr for subgridspecs",
        "code": "def make_layoutgrids_gs(layoutgrids, gs):\n    \n\n    if gs in layoutgrids or gs.figure is None:\n        return layoutgrids\n    # in order to do constrained_layout there has to be at least *one*\n    # gridspec in the tree:\n    layoutgrids['hasgrids'] = True\n    if not hasattr(gs, '_subplot_spec'):\n        # normal gridspec\n        parent = layoutgrids[gs.figure]\n        layoutgrids[gs] = mlayoutgrid.LayoutGrid(\n                parent=parent,\n                parent_inner=True,\n                name='gridspec',\n                ncols=gs._ncols, nrows=gs._nrows,\n                width_ratios=gs.get_width_ratios(),\n                height_ratios=gs.get_height_ratios())\n    else:\n        # this is a gridspecfromsubplotspec:\n        subplot_spec = gs._subplot_spec\n        parentgs = subplot_spec.get_gridspec()\n        # if a nested gridspec it is possible the parent is not in there yet:\n        if parentgs not in layoutgrids:\n            layoutgrids = make_layoutgrids_gs(layoutgrids, parentgs)\n        subspeclb = layoutgrids[parentgs]\n        # get a unique representation:\n        rep = object.__repr__(gs) + 'top'\n        # gridspecfromsubplotspec need an outer container:\n        if rep not in layoutgrids:\n            layoutgrids[rep] = mlayoutgrid.LayoutGrid(\n                parent=subspeclb,\n                name='top',\n                nrows=1, ncols=1,\n                parent_pos=(subplot_spec.rowspan, subplot_spec.colspan))\n        layoutgrids[gs] = mlayoutgrid.LayoutGrid(\n                parent=layoutgrids[rep],\n                name='gridspec',\n                nrows=gs._nrows, ncols=gs._ncols,\n                width_ratios=gs.get_width_ratios(),\n                height_ratios=gs.get_height_ratios())\n    return layoutgrids\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 510,
        "n_words": 134,
        "vocab_size": 80,
        "complexity": 6,
        "nloc": 33,
        "token_counts": 230,
        "n_ast_nodes": 361,
        "n_identifiers": 29,
        "d_id": 22565,
        "documentation": {
            "docstring": "\n    Make the layoutgrid for a gridspec (and anything nested in the gridspec)\n    ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 220737,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/sslproto.py",
        "file_name": "sslproto.py",
        "fun_name": "data_received",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def data_received(self, data):\n        \n        if self._sslpipe is None:\n            # transport closing, sslpipe is destroyed\n            return\n\n        try:\n            ssldata, appdata = self._sslpipe.feed_ssldata(data)\n        except (SystemExit, KeyboardInterrupt):\n            raise\n        except BaseException as e:\n            self._fatal_error(e, 'SSL error in data received')\n            return\n\n        for chunk in ssldata:\n            self._transport.write(chunk)\n\n        for chunk in appdata:\n            if chunk:\n                try:\n                    if self._app_protocol_is_buffer:\n                        protocols._feed_data_to_buffered_proto(\n                            self._app_protocol, chunk)\n                    else:\n                        self._app_protocol.data_received(chunk)\n                except (SystemExit, KeyboardInterrupt):\n                    raise\n                except BaseException as ex:\n                    self._fatal_error(\n                        ex, 'application protocol failed to receive SSL data')\n                    return\n            else:\n                self._start_shutdown()\n                break\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 488,
        "n_words": 74,
        "vocab_size": 55,
        "complexity": 10,
        "nloc": 29,
        "token_counts": 130,
        "n_ast_nodes": 217,
        "n_identifiers": 21,
        "d_id": 56109,
        "documentation": {
            "docstring": "Called when some SSL data is received.\n\n        The argument is a bytes object.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 226141,
        "commit_id": "43e3a4011080911901176aab919c0ecf5046ddd3",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/figure_factory/_candlestick.py",
        "file_name": "_candlestick.py",
        "fun_name": "make_increasing_candle",
        "commit_message": "switch to black .22",
        "code": "def make_increasing_candle(open, high, low, close, dates, **kwargs):\n    \n    increase_x, increase_y = _Candlestick(\n        open, high, low, close, dates, **kwargs\n    ).get_candle_increase()\n\n    if \"line\" in kwargs:\n        kwargs.setdefault(\"fillcolor\", kwargs[\"line\"][\"color\"])\n    else:\n        kwargs.setdefault(\"fillcolor\", _DEFAULT_INCREASING_COLOR)\n    if \"name\" in kwargs:\n        kwargs.setdefault(\"showlegend\", True)\n    else:\n        kwargs.setdefault(\"showlegend\", False)\n    kwargs.setdefault(\"name\", \"Increasing\")\n    kwargs.setdefault(\"line\", dict(color=_DEFAULT_INCREASING_COLOR))\n\n    candle_incr_data = dict(\n        type=\"box\",\n        x=increase_x,\n        y=increase_y,\n        whiskerwidth=0,\n        boxpoints=False,\n        **kwargs,\n    )\n\n    return [candle_incr_data]\n\n",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 165,
        "n_words": 52,
        "vocab_size": 41,
        "complexity": 3,
        "nloc": 23,
        "token_counts": 145,
        "n_ast_nodes": 237,
        "n_identifiers": 21,
        "d_id": 57816,
        "documentation": {
            "docstring": "\n    Makes boxplot trace for increasing candlesticks\n\n    _make_increasing_candle() and _make_decreasing_candle separate the\n    increasing traces from the decreasing traces so kwargs (such as\n    color) can be passed separately to increasing or decreasing traces\n    when direction is set to 'increasing' or 'decreasing' in\n    FigureFactory.create_candlestick()\n\n    :param (list) open: opening values\n    :param (list) high: high values\n    :param (list) low: low values\n    :param (list) close: closing values\n    :param (list) dates: list of datetime objects. Default: None\n    :param kwargs: kwargs to be passed to increasing trace via\n        plotly.graph_objs.Scatter.\n\n    :rtype (list) candle_incr_data: list of the box trace for\n        increasing candlesticks.\n    ",
            "n_words": 92,
            "vocab_size": 58,
            "n_whitespaces": 149,
            "language": "en"
        }
    },
    {
        "id": 97246,
        "commit_id": "6c49c2ff46496809d6620ac3746262c66f02142e",
        "repo": "sentry",
        "path": "src/sentry/snuba/discover.py",
        "file_name": "discover.py",
        "fun_name": "normalize_span_histogram_resutls",
        "commit_message": "ref(spans): Normalize exclusive time histogram results (#32762)\n\n* ref(spans): Normalize exclusive time histogram results\r\n\r\n* test normalized data",
        "code": "def normalize_span_histogram_resutls(span, histogram_params, results):\n    \n\n    histogram_column = get_span_histogram_column(span, histogram_params)\n    bin_name = get_function_alias(histogram_column)\n\n    # zerofill and rename the columns while making sure to adjust for precision\n    bucket_map = {}\n    for row in results[\"data\"]:\n        # we expect the bin the be an integer, this is because all floating\n        # point values are rounded during the calculation\n        bucket = int(row[bin_name])\n        bucket_map[bucket] = row[\"count\"]\n\n    new_data = []\n    for i in range(histogram_params.num_buckets):\n        bucket = histogram_params.start_offset + histogram_params.bucket_size * i\n        row = {\"bin\": bucket, \"count\": bucket_map.get(bucket, 0)}\n        if histogram_params.multiplier > 1:\n            row[\"bin\"] /= float(histogram_params.multiplier)\n        new_data.append(row)\n\n    return new_data\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 184,
        "n_words": 90,
        "vocab_size": 71,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 124,
        "n_ast_nodes": 203,
        "n_identifiers": 22,
        "d_id": 19394,
        "documentation": {
            "docstring": "\n    Normalizes the span histogram results by renaming the columns to key and bin\n    and make sure to zerofill any missing values.\n\n    :param [Span] span: The span for which you want to generate the\n        histograms for.\n    :param HistogramParams histogram_params: The histogram parameters used.\n    :param any results: The results from the histogram query that may be missing\n        bins and needs to be normalized.\n    ",
            "n_words": 61,
            "vocab_size": 42,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 156742,
        "commit_id": "2820bae493a49cb1d0a6e376985c5473b8f04fa8",
        "repo": "dask",
        "path": "dask/array/core.py",
        "file_name": "core.py",
        "fun_name": "round",
        "commit_message": "Don't include docs in ``Array`` methods, just refer to module docs (#9244)\n\nCo-authored-by: James Bourbeau <jrbourbeau@users.noreply.github.com>",
        "code": "def round(self, decimals=0):\n        \n        from dask.array.routines import round\n\n        return round(self, decimals=decimals)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 42,
        "n_identifiers": 6,
        "d_id": 36752,
        "documentation": {
            "docstring": "Return array with each element rounded to the given number of decimals.\n\n        Refer to :func:`dask.array.round` for full documentation.\n\n        See Also\n        --------\n        dask.array.round : equivalent function\n        ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 164632,
        "commit_id": "c055dc4e6be9fc1b68d873a1ace286322dadd5e1",
        "repo": "pandas",
        "path": "pandas/tests/io/test_stata.py",
        "file_name": "test_stata.py",
        "fun_name": "test_encoding_latin1_118",
        "commit_message": "TST: Don't use autouse fixture in test_stata (#45831)",
        "code": "def test_encoding_latin1_118(self, datapath):\n        # GH 25960\n        msg = \n        with tm.assert_produces_warning(UnicodeWarning) as w:\n            encoded = read_stata(\n                datapath(\"io\", \"data\", \"stata\", \"stata1_encoding_118.dta\")\n            )\n            assert len(w) == 151\n            assert w[0].message.args[0] == msg\n\n        expected = DataFrame([[\"Düsseldorf\"]] * 151, columns=[\"kreis1849\"])\n        tm.assert_frame_equal(encoded, expected)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 130,
        "n_words": 36,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 82,
        "n_ast_nodes": 141,
        "n_identifiers": 17,
        "d_id": 39577,
        "documentation": {
            "docstring": "\nOne or more strings in the dta file could not be decoded using utf-8, and\nso the fallback encoding of latin-1 is being used.  This can happen when a file\nhas been incorrectly encoded by Stata or some other software. You should verify\nthe string values returned are correct.",
            "n_words": 49,
            "vocab_size": 45,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 107364,
        "commit_id": "6010bb43ed01c48c7c403569dd210490b236a853",
        "repo": "matplotlib",
        "path": "lib/matplotlib/colorbar.py",
        "file_name": "colorbar.py",
        "fun_name": "locator",
        "commit_message": "MNT: make colorbars locators and formatters properties",
        "code": "def locator(self, loc):\n        \n        self._long_axis().set_major_locator(loc)\n        self._locator = loc\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 28,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 40,
        "n_identifiers": 6,
        "d_id": 22709,
        "documentation": {
            "docstring": "\n        Set the major locator being used for colorbar\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 314737,
        "commit_id": "26a85c6644991f626ccce62c05665095c2577234",
        "repo": "core",
        "path": "tests/helpers/test_entity.py",
        "file_name": "test_entity.py",
        "fun_name": "test_removing_entity_unavailable",
        "commit_message": "Add Entity.has_entity_name attribute (#73217)",
        "code": "async def test_removing_entity_unavailable(hass):\n    \n    entry = er.RegistryEntry(\n        entity_id=\"hello.world\",\n        unique_id=\"test-unique-id\",\n        platform=\"test-platform\",\n        disabled_by=None,\n    )\n\n    ent = entity.Entity()\n    ent.hass = hass\n    ent.entity_id = \"hello.world\"\n    ent.registry_entry = entry\n    ent.async_write_ha_state()\n\n    state = hass.states.get(\"hello.world\")\n    assert state is not None\n    assert state.state == STATE_UNKNOWN\n\n    await ent.async_remove()\n\n    state = hass.states.get(\"hello.world\")\n    assert state is not None\n    assert state.state == STATE_UNAVAILABLE\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 123,
        "n_words": 50,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 104,
        "n_ast_nodes": 178,
        "n_identifiers": 20,
        "d_id": 113341,
        "documentation": {
            "docstring": "Test removing an entity that is still registered creates an unavailable state.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 80597,
        "commit_id": "604cbc17376620dc67df35386421835d43732a4e",
        "repo": "awx",
        "path": "awx/main/managers.py",
        "file_name": "managers.py",
        "fun_name": "capacity_values",
        "commit_message": "Consume control capacity (#11665)\n\n* Select control node before start task\r\n\r\nConsume capacity on control nodes for controlling tasks and consider\r\nremainging capacity on control nodes before selecting them.\r\n\r\nThis depends on the requirement that control and hybrid nodes should all\r\nbe in the instance group named 'controlplane'. Many tests do not satisfy that\r\nrequirement. I'll update the tests in another commit.\r\n\r\n* update tests to use controlplane\r\n\r\nWe don't start any tasks if we don't have a controlplane instance group\r\n\r\nDue to updates to fixtures, update tests to set node type and capacity\r\nexplicitly so they get expected result.\r\n\r\n* Fixes for accounting of control capacity consumed\r\n\r\nUpdate method is used to account for currently consumed capacity for\r\ninstance groups in the in-memory capacity tracking data structure we initialize in\r\nafter_lock_init and then update via calculate_capacity_consumed (both in\r\ntask_manager.py)\r\n\r\nAlso update fit_task_to_instance to consider control impact on instances\r\n\r\nTrust that these functions do the right thing looking for a\r\nnode with capacity, and cut out redundant check for the whole group's\r\ncapacity per Alan's reccomendation.\r\n\r\n* Refactor now redundant code\r\n\r\nDeal with control type tasks before we loop over the preferred instance\r\ngroups, which cuts out the need for some redundant logic.\r\n\r\nAlso, fix a bug where I was missing assigning the execution node in one case!\r\n\r\n* set job explanation on tasks that need capacity\r\n\r\nmove the job explanation for jobs that need capacity to a function\r\nso we can re-use it in the three places we need it.\r\n\r\n* project updates always run on the controlplane\r\n\r\nInstance group ordering makes no sense on project updates because they\r\nalways need to run on the control plane.\r\n\r\nAlso, since hybrid nodes should always run the control processes for the\r\njobs running on them as execution nodes, account for this when looking for a\r\nexecution node.\r\n\r\n* fix misleading message\r\n\r\nthe variables and wording were both misleading, fix to be more accurate\r\ndescription in the two different cases where this log may be emitted.\r\n\r\n* use settings correctly\r\n\r\nuse settings.DEFAULT_CONTROL_PLANE_QUEUE_NAME instead of a hardcoded\r\nname\r\ncache the controlplane_ig object during the after lock init to avoid\r\nan uneccesary query\r\neliminate mistakenly duplicated AWX_CONTROL_PLANE_TASK_IMPACT and use\r\nonly AWX_CONTROL_NODE_TASK_IMPACT\r\n\r\n* add test for control capacity consumption\r\n\r\nadd test to verify that when there are 2 jobs and only capacity for one\r\nthat one will move into waiting and the other stays in pending\r\n\r\n* add test for hybrid node capacity consumption\r\n\r\nassert that the hybrid node is used for both control and execution and\r\ncapacity is deducted correctly\r\n\r\n* add test for task.capacity_type = control\r\n\r\nTest that control type tasks have the right capacity consumed and\r\nget assigned to the right instance group\r\n\r\nAlso fix lint in the tests\r\n\r\n* jobs_running not accurate for control nodes\r\n\r\nWe can either NOT use \"idle instances\" for control nodes, or we need\r\nto update the jobs_running property on the Instance model to count\r\njobs where the node is the controller_node.\r\n\r\nI didn't do that because it may be an expensive query, and it would be\r\nhard to make it match with jobs_running on the InstanceGroup which\r\nfilters on tasks assigned to the instance group.\r\n\r\nThis change chooses to stop considering \"idle\" control nodes an option,\r\nsince we can't acurrately identify them.\r\n\r\nThe way things are without any change, is we are continuing to over consume capacity on control nodes\r\nbecause this method sees all control nodes as \"idle\" at the beginning\r\nof the task manager run, and then only counts jobs started in that run\r\nin the in-memory tracking. So jobs which last over a number of task\r\nmanager runs build up consuming capacity, which is accurately reported\r\nvia Instance.consumed_capacity\r\n\r\n* Reduce default task impact for control nodes\r\n\r\nThis is something we can experiment with as far as what users\r\nwant at install time, but start with just 1 for now.\r\n\r\n* update capacity docs\r\n\r\nDescribe usage of the new setting and the concept of control impact.\r\n\r\nCo-authored-by: Alan Rominger <arominge@redhat.com>\r\nCo-authored-by: Rebeccah <rhunter@redhat.com>",
        "code": "def capacity_values(self, qs=None, tasks=None, breakdown=False, graph=None):\n        \n        if qs is None:  # Optionally BYOQS - bring your own queryset\n            qs = self.all().prefetch_related('instances')\n        instance_ig_mapping, ig_ig_mapping = self.capacity_mapping(qs=qs)\n\n        if tasks is None:\n            tasks = self.model.unifiedjob_set.related.related_model.objects.filter(status__in=('running', 'waiting'))\n\n        if graph is None:\n            graph = {group.name: {} for group in qs}\n        for group_name in graph:\n            self.zero_out_group(graph, group_name, breakdown)\n        for t in tasks:\n            # TODO: dock capacity for isolated job management tasks running in queue\n            impact = t.task_impact\n            control_groups = []\n            if t.controller_node:\n                control_groups = instance_ig_mapping.get(t.controller_node, [])\n                if not control_groups:\n                    logger.warn(f\"No instance group found for {t.controller_node}, capacity consumed may be innaccurate.\")\n\n            if t.status == 'waiting' or (not t.execution_node and not t.is_container_group_task):\n                # Subtract capacity from any peer groups that share instances\n                if not t.instance_group:\n                    impacted_groups = []\n                elif t.instance_group.name not in ig_ig_mapping:\n                    # Waiting job in group with 0 capacity has no collateral impact\n                    impacted_groups = [t.instance_group.name]\n                else:\n                    impacted_groups = ig_ig_mapping[t.instance_group.name]\n                for group_name in impacted_groups:\n                    if group_name not in graph:\n                        self.zero_out_group(graph, group_name, breakdown)\n                    graph[group_name]['consumed_capacity'] += impact\n                    capacity_type = get_capacity_type(t)\n                    graph[group_name][f'consumed_{capacity_type}_capacity'] += impact\n                    if breakdown:\n                        graph[group_name]['committed_capacity'] += impact\n                for group_name in control_groups:\n                    if group_name not in graph:\n                        self.zero_out_group(graph, group_name, breakdown)\n                    graph[group_name][f'consumed_control_capacity'] += settings.AWX_CONTROL_NODE_TASK_IMPACT\n                    if breakdown:\n                        graph[group_name]['committed_capacity'] += settings.AWX_CONTROL_NODE_TASK_IMPACT\n            elif t.status == 'running':\n                # Subtract capacity from all groups that contain the instance\n                if t.execution_node not in instance_ig_mapping:\n                    if not t.is_container_group_task:\n                        logger.warning('Detected %s running inside lost instance, ' 'may still be waiting for reaper.', t.log_format)\n                    if t.instance_group:\n                        impacted_groups = [t.instance_group.name]\n                    else:\n                        impacted_groups = []\n                else:\n                    impacted_groups = instance_ig_mapping[t.execution_node]\n\n                for group_name in impacted_groups:\n                    if group_name not in graph:\n                        self.zero_out_group(graph, group_name, breakdown)\n                    graph[group_name]['consumed_capacity'] += impact\n                    capacity_type = get_capacity_type(t)\n                    graph[group_name][f'consumed_{capacity_type}_capacity'] += impact\n                    if breakdown:\n                        graph[group_name]['running_capacity'] += impact\n                for group_name in control_groups:\n                    if group_name not in graph:\n                        self.zero_out_group(graph, group_name, breakdown)\n                    graph[group_name][f'consumed_control_capacity'] += settings.AWX_CONTROL_NODE_TASK_IMPACT\n                    if breakdown:\n                        graph[group_name]['running_capacity'] += settings.AWX_CONTROL_NODE_TASK_IMPACT\n            else:\n                logger.error('Programming error, %s not in [\"running\", \"waiting\"]', t.log_format)\n        return graph\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1412,
        "n_words": 296,
        "vocab_size": 129,
        "complexity": 30,
        "nloc": 65,
        "token_counts": 503,
        "n_ast_nodes": 817,
        "n_identifiers": 42,
        "d_id": 17078,
        "documentation": {
            "docstring": "\n        Returns a dictionary of capacity values for all IGs\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 268361,
        "commit_id": "4260b71cc77b7a44e061668d0d408d847f550156",
        "repo": "ansible",
        "path": "test/units/plugins/test_plugins.py",
        "file_name": "test_plugins.py",
        "fun_name": "test_all_no_duplicate_names",
        "commit_message": "refactor and fixes for doc parsing (#77719)\n\n* refactor and remove redundant code in documentation\r\n\r\n  allow location and building api to be more accessible\r\n  fix issues with displaying ansible.legacy and ansible.builtin\r\n  ensure we don't x2 process tokens (some modules reference them also) fixes #77764\r\n  move to constants vs hardcoded\r\n  more informative errors and comments\r\n  now have actual filter/test plugins, which expose the filter/test functions\r\n  moved filter/test loading/finding logic into jinja2pluginloader, removed dupe implementations\r\n  added tests for case in which we unique by basename when listing\r\n\r\nUpdate lib/ansible/utils/plugin_docs.py\r\nCo-authored-by: Sloane Hertel <19572925+s-hertel@users.noreply.github.com>",
        "code": "def test_all_no_duplicate_names(self, gp_mock, glob_mock):\n        \n\n        fixture_path = os.path.join(os.path.dirname(__file__), 'loader_fixtures')\n\n        gp_mock.return_value = [\n            fixture_path,\n            '/path/to'\n        ]\n\n        glob_mock.glob.side_effect = [\n            [os.path.join(fixture_path, 'import_fixture.py')],\n            ['/path/to/import_fixture.py']\n        ]\n\n        pl = PluginLoader('test', '', 'test', 'test_plugins')\n        # Aside from needing ``list()`` so we can do a len, ``PluginLoader.all`` returns a generator\n        # so ``list()`` actually causes ``PluginLoader.all`` to run.\n        plugins = list(pl.all())\n        self.assertEqual(len(plugins), 1)\n\n        self.assertIn(os.path.join(fixture_path, 'import_fixture.py'), pl._module_cache)\n        self.assertNotIn('/path/to/import_fixture.py', pl._module_cache)\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 195,
        "n_words": 60,
        "vocab_size": 48,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 124,
        "n_ast_nodes": 209,
        "n_identifiers": 23,
        "d_id": 79491,
        "documentation": {
            "docstring": "\n        This test goes along with ``test__load_module_source_no_duplicate_names``\n        and ensures that we ignore duplicate imports on multiple paths\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 268987,
        "commit_id": "119cd4655d01570a70c70879dff4461ea46161bf",
        "repo": "keras",
        "path": "keras/utils/metrics_utils.py",
        "file_name": "metrics_utils.py",
        "fun_name": "binary_matches",
        "commit_message": "Added util metric method for binary_matches. Decoupled from public metric binarry_acc",
        "code": "def binary_matches(y_true, y_pred, threshold=0.5):\n  \n  y_pred = tf.convert_to_tensor(y_pred)\n  threshold = tf.cast(threshold, y_pred.dtype)\n  y_pred = tf.cast(y_pred > threshold, y_pred.dtype)\n  return tf.cast(tf.equal(y_true, y_pred), tf.int8)",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 26,
        "n_words": 21,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 66,
        "n_ast_nodes": 98,
        "n_identifiers": 10,
        "d_id": 79806,
        "documentation": {
            "docstring": "Creates int Tensor, 1 for label-prediction match, 0 for mismatch.\n\n  Args:\n    y_true: Ground truth values. shape = `[batch_size, d0, .. dN]`.\n    y_pred: The predicted values. shape = `[batch_size, d0, .. dN]`.\n    threshold: (Optional) Float representing the threshold for deciding whether\n      prediction values are 1 or 0.\n\n  Returns:\n    Binary matches. shape = `[batch_size, d0, .. dN]`\n  ",
            "n_words": 55,
            "vocab_size": 40,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 197113,
        "commit_id": "cba899d4137b0b65f6850120ee42cd4fcd4f9dbf",
        "repo": "sympy",
        "path": "sympy/tensor/tensor.py",
        "file_name": "tensor.py",
        "fun_name": "get_matrix",
        "commit_message": "Update the various tensor deprecations",
        "code": "def get_matrix(self):\n        \n        from sympy.matrices.dense import Matrix\n        deprecate_data()\n        with ignore_warnings(SymPyDeprecationWarning):\n            if 0 < self.rank <= 2:\n                rows = self.data.shape[0]\n                columns = self.data.shape[1] if self.rank == 2 else 1\n                if self.rank == 2:\n                    mat_list = [] * rows\n                    for i in range(rows):\n                        mat_list.append([])\n                        for j in range(columns):\n                            mat_list[i].append(self[i, j])\n                else:\n                    mat_list = [None] * rows\n                    for i in range(rows):\n                        mat_list[i] = self[i]\n                return Matrix(mat_list)\n            else:\n                raise NotImplementedError(\n                    \"missing multidimensional reduction to matrix.\")\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 401,
        "n_words": 70,
        "vocab_size": 49,
        "complexity": 7,
        "nloc": 21,
        "token_counts": 148,
        "n_ast_nodes": 235,
        "n_identifiers": 20,
        "d_id": 48346,
        "documentation": {
            "docstring": "\n        DEPRECATED: do not use.\n\n        Returns ndarray components data as a matrix, if components data are\n        available and ndarray dimension does not exceed 2.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 241712,
        "commit_id": "b56d8677ad0ff8513e566334f4a78a24b88480c3",
        "repo": "lightning",
        "path": "tests/callbacks/test_device_stats_monitor.py",
        "file_name": "test_device_stats_monitor.py",
        "fun_name": "test_device_stats_gpu_from_torch",
        "commit_message": "Update test_pruning.py to use `devices` instead of `gpus` or `ipus` (#11339)",
        "code": "def test_device_stats_gpu_from_torch(tmpdir):\n    \n    model = BoringModel()\n    device_stats = DeviceStatsMonitor()\n",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 82,
        "n_ast_nodes": 31,
        "n_identifiers": 6,
        "d_id": 69665,
        "documentation": {
            "docstring": "Test GPU stats are logged using a logger with Pytorch >= 1.8.0.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 21185,
        "commit_id": "4b996c0fa85824b323ad9eff3364dbe2213ebb4c",
        "repo": "pipenv",
        "path": "pipenv/environment.py",
        "file_name": "environment.py",
        "fun_name": "expand_egg_links",
        "commit_message": "Convert type comments to type annotations",
        "code": "def expand_egg_links(self) -> None:\n        \n        prefixes = [\n            Path(prefix)\n            for prefix in self.base_paths[\"libdirs\"].split(os.pathsep)\n            if vistir.path.is_in_path(prefix, self.prefix.as_posix())\n        ]\n        for loc in prefixes:\n            if not loc.exists():\n                continue\n            for pth in loc.iterdir():\n                if not pth.suffix == \".egg-link\":\n                    continue\n                contents = [\n                    vistir.path.normalize_path(line.strip())\n                    for line in pth.read_text().splitlines()\n                ]\n                pth.write_text(\"\\n\".join(contents))\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 259,
        "n_words": 44,
        "vocab_size": 31,
        "complexity": 8,
        "nloc": 21,
        "token_counts": 120,
        "n_ast_nodes": 200,
        "n_identifiers": 26,
        "d_id": 3716,
        "documentation": {
            "docstring": "\n        Expand paths specified in egg-link files to prevent pip errors during\n        reinstall\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 205712,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/manager.py",
        "file_name": "manager.py",
        "fun_name": "deconstruct",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def deconstruct(self):\n        \n        qs_class = self._queryset_class\n        if getattr(self, \"_built_with_as_manager\", False):\n            # using MyQuerySet.as_manager()\n            return (\n                True,  # as_manager\n                None,  # manager_class\n                \"%s.%s\" % (qs_class.__module__, qs_class.__name__),  # qs_class\n                None,  # args\n                None,  # kwargs\n            )\n        else:\n            module_name = self.__module__\n            name = self.__class__.__name__\n            # Make sure it's actually there and not an inner class\n            module = import_module(module_name)\n            if not hasattr(module, name):\n                raise ValueError(\n                    \"Could not find manager %s in %s.\\n\"\n                    \"Please note that you need to inherit from managers you \"\n                    \"dynamically generated with 'from_queryset()'.\"\n                    % (name, module_name)\n                )\n            return (\n                False,  # as_manager\n                \"%s.%s\" % (module_name, name),  # manager_class\n                None,  # qs_class\n                self._constructor_args[0],  # args\n                self._constructor_args[1],  # kwargs\n            )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 511,
        "n_words": 107,
        "vocab_size": 73,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 115,
        "n_ast_nodes": 192,
        "n_identifiers": 15,
        "d_id": 51170,
        "documentation": {
            "docstring": "\n        Return a 5-tuple of the form (as_manager (True), manager_class,\n        queryset_class, args, kwargs).\n\n        Raise a ValueError if the manager is dynamically generated.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 168085,
        "commit_id": "62a69beddbedde349891378992c902c0b9341a9f",
        "repo": "pandas",
        "path": "pandas/core/arrays/interval.py",
        "file_name": "interval.py",
        "fun_name": "right",
        "commit_message": "DOC: Add numpydoc SS06 validation (#47885)",
        "code": "def right(self):\n        \n        from pandas import Index\n\n        return Index(self._right, copy=False)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 21,
        "n_ast_nodes": 36,
        "n_identifiers": 6,
        "d_id": 40192,
        "documentation": {
            "docstring": "\n        Return the right endpoints of each Interval in the IntervalArray as an Index.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 63010,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pep517/wrappers.py",
        "file_name": "wrappers.py",
        "fun_name": "get_requires_for_build_sdist",
        "commit_message": "upd; format",
        "code": "def get_requires_for_build_sdist(self, config_settings=None):\n        \n        return self._call_hook('get_requires_for_build_sdist', {\n            'config_settings': config_settings\n        })\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 41,
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        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 4,
        "d_id": 13098,
        "documentation": {
            "docstring": "Identify packages required for building a wheel\n\n        Returns a list of dependency specifications, e.g.::\n\n            [\"setuptools >= 26\"]\n\n        This does not include requirements specified in pyproject.toml.\n        It returns the result of calling the equivalently named hook in a\n        subprocess.\n        ",
            "n_words": 38,
            "vocab_size": 33,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 148044,
        "commit_id": "d96ac251d7c9d12fadedfdfd903dc393f5bae217",
        "repo": "ray",
        "path": "python/ray/ml/checkpoint.py",
        "file_name": "checkpoint.py",
        "fun_name": "as_directory",
        "commit_message": "[air] Add `Checkpoint.as_directory()` for efficient checkpoint fs processing (#23908)\n\nThis PR adds a `Checkpoint_as_directory()` context manager that either returns the local path (if checkpoint is already a directory) or a temporary directory path containing the checkpoint data, which is cleaned up after use. The path should be considered as a read-only source for loading data from the checkpoint.\r\n\r\nA common use case for processing checkpoint data is to convert it into a directory with `Checkpoint.to_directory()` and then do some read-only processing (e.g. restoring a ML model).\r\n\r\nThis process has two flaws: First, `to_directory()` creates a temporary directory that has to be explicitly cleaned up by the user after use. Secondly, if the checkpoint is already a directory checkpoint, it is copied over, which is inefficient for large checkpoints (e.g. huggingface models) and then even more prone to unwanted side effects if not cleaned up properly. \r\n\r\nWith this context manager that effectively returns a directory that is to be used as a read-only data source, we can avoid manual cleaning up and unnecessary data copies (or avoid internal inspection as e.g. in https://github.com/ray-project/ray/pull/23876/files#diff-47db2f054ca359879f77306e7b054dd8b780aab994961e3b4911330ae15eeae3R57-R60)\r\n\r\nSee also discussion in https://github.com/ray-project/ray/pull/23850/files#r850036905",
        "code": "def as_directory(self) -> Iterator[str]:\n        \n        if self._local_path:\n            yield self._local_path\n        else:\n            temp_dir = self.to_directory()\n            yield temp_dir\n            shutil.rmtree(temp_dir, ignore_errors=True)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 81,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 29,
        "token_counts": 41,
        "n_ast_nodes": 70,
        "n_identifiers": 10,
        "d_id": 34158,
        "documentation": {
            "docstring": "Return checkpoint directory path in a context.\n\n        This function makes checkpoint data available as a directory while avoiding\n        unnecessary copies and left-over temporary data.\n\n        If the checkpoint is already a directory checkpoint, it will return\n        the existing path. If it is not, it will create a temporary directory,\n        which will be deleted after the context is exited.\n\n        Users should treat the returned checkpoint directory as read-only and avoid\n        changing any data within it, as it might get deleted when exiting the context.\n\n        Example:\n\n            with checkpoint.as_directory() as checkpoint_dir:\n                # Do some read-only processing of files within checkpoint_dir\n                pass\n\n            # At this point, if a temporary directory was created, it will have\n            # been deleted.\n\n        ",
            "n_words": 113,
            "vocab_size": 75,
            "n_whitespaces": 239,
            "language": "en"
        }
    },
    {
        "id": 64242,
        "commit_id": "ce0b84f54d495fc78a6792a9b05d0eb1dc799ed2",
        "repo": "erpnext",
        "path": "erpnext/stock/doctype/delivery_note/delivery_note.py",
        "file_name": "delivery_note.py",
        "fun_name": "update_billed_amount_based_on_so",
        "commit_message": "refactor: use frappe.qb instead of sql\n\n(cherry picked from commit 0a9ec9f591f8b4d0e630a3c902b69c9996f080dd)",
        "code": "def update_billed_amount_based_on_so(so_detail, update_modified=True):\n\tfrom frappe.query_builder.functions import Sum\n\n\t# Billed against Sales Order directly\n\tsi = frappe.qb.DocType(\"Sales Invoice\").as_(\"si\")\n\tsi_item = frappe.qb.DocType(\"Sales Invoice Item\").as_(\"si_item\")\n\tsum_amount = Sum(si_item.amount).as_(\"amount\")\n\n\tbilled_against_so = frappe.qb.from_(si).from_(si_item).select(sum_amount).where(\n\t\t(si_item.parent == si.name) &\n\t\t(si_item.so_detail == so_detail) &\n\t\t((si_item.dn_detail.isnull()) | (si_item.dn_detail == '')) &\n\t\t(si_item.docstatus == 1) &\n\t\t(si.update_stock == 0)\n\t).run()\n\tbilled_against_so = billed_against_so and billed_against_so[0][0] or 0\n\n\t# Get all Delivery Note Item rows against the Sales Order Item row\n\n\tdn = frappe.qb.DocType(\"Delivery Note\").as_(\"dn\")\n\tdn_item = frappe.qb.DocType(\"Delivery Note Item\").as_(\"dn_item\")\n\n\tdn_details = frappe.qb.from_(dn).from_(dn_item).select(dn_item.name, dn_item.amount, dn_item.si_detail, dn_item.parent, dn_item.stock_qty, dn_item.returned_qty).where(\n\t\t(dn.name == dn_item.parent) &\n\t\t(dn_item.so_detail == so_detail) &\n\t\t(dn.docstatus == 1) &\n\t\t(dn.is_return == 0)\n\t).orderby(\n\t\tdn.posting_date, dn.posting_time, dn.name\n\t).run(as_dict=True)\n\n\tupdated_dn = []\n\tfor dnd in dn_details:\n\t\tbilled_amt_agianst_dn = 0\n\n\t\t# If delivered against Sales Invoice\n\t\tif dnd.si_detail:\n\t\t\tbilled_amt_agianst_dn = flt(dnd.amount)\n\t\t\tbilled_against_so -= billed_amt_agianst_dn\n\t\telse:\n\t\t\t# Get billed amount directly against Delivery Note\n\t\t\tbilled_amt_agianst_dn = frappe.db.sql(, dnd.name)\n\t\t\tbilled_amt_agianst_dn = billed_amt_agianst_dn and billed_amt_agianst_dn[0][0] or 0\n\n\t\t# Distribute billed amount directly against SO between DNs based on FIFO\n\t\tif billed_against_so and billed_amt_agianst_dn < dnd.amount:\n\t\t\tif dnd.returned_qty:\n\t\t\t\tpending_to_bill = flt(dnd.amount) * (dnd.stock_qty - dnd.returned_qty) / dnd.stock_qty\n\t\t\telse:\n\t\t\t\tpending_to_bill = flt(dnd.amount)\n\t\t\tpending_to_bill -= billed_amt_agianst_dn\n\t\t\tif pending_to_bill <= billed_against_so:\n\t\t\t\tbilled_amt_agianst_dn += pending_to_bill\n\t\t\t\tbilled_against_so -= pending_to_bill\n\t\t\telse:\n\t\t\t\tbilled_amt_agianst_dn += billed_against_so\n\t\t\t\tbilled_against_so = 0\n\n\t\tfrappe.db.set_value(\"Delivery Note Item\", dnd.name, \"billed_amt\", billed_amt_agianst_dn, update_modified=update_modified)\n\n\t\tupdated_dn.append(dnd.parent)\n\n\treturn updated_dn\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 162,
        "n_words": 214,
        "vocab_size": 120,
        "complexity": 11,
        "nloc": 48,
        "token_counts": 440,
        "n_ast_nodes": 708,
        "n_identifiers": 45,
        "d_id": 13585,
        "documentation": {
            "docstring": "select sum(amount) from `tabSales Invoice Item`\n\t\t\t\twhere dn_detail=%s and docstatus=1",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 151551,
        "commit_id": "2b6d00dde449934db8789c860d5e0e9dc9c528ab",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/api_server/ws/channel.py",
        "file_name": "channel.py",
        "fun_name": "send",
        "commit_message": "initial channel api change",
        "code": "async def send(self, data) -> bool:\n        \n        try:\n            await asyncio.wait_for(\n                self.queue.put(data),\n                timeout=self.drain_timeout\n            )\n            return True\n        except asyncio.TimeoutError:\n            return False\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 113,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 41,
        "n_ast_nodes": 68,
        "n_identifiers": 11,
        "d_id": 35044,
        "documentation": {
            "docstring": "\n        Add the data to the queue to be sent.\n        :returns: True if data added to queue, False otherwise\n        ",
            "n_words": 18,
            "vocab_size": 14,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 248060,
        "commit_id": "8a87b4435a736cd42454cad7e57b65ec911f01fa",
        "repo": "synapse",
        "path": "tests/storage/databases/main/test_events_worker.py",
        "file_name": "test_events_worker.py",
        "fun_name": "test_second_get_event_cancelled",
        "commit_message": "Handle cancellation in `EventsWorkerStore._get_events_from_cache_or_db` (#12529)\n\nMultiple calls to `EventsWorkerStore._get_events_from_cache_or_db` can\r\nreuse the same database fetch, which is initiated by the first call.\r\nEnsure that cancelling the first call doesn't cancel the other calls\r\nsharing the same database fetch.\r\n\r\nSigned-off-by: Sean Quah <seanq@element.io>",
        "code": "def test_second_get_event_cancelled(self):\n        \n        with self.blocking_get_event_calls() as (unblock, get_event1, get_event2):\n            # Cancel the second `get_event` call.\n            get_event2.cancel()\n            # The first `get_event` call must not be cancelled.\n            self.assertNoResult(get_event1)\n            # The second `get_event` call gets cancelled immediately.\n            exc = self.get_failure(get_event2, CancelledError).value\n            self.assertIsInstance(exc, CancelledError)\n\n            # Unblock the database fetch.\n            unblock.callback(None)\n            # The first `get_event` call should complete successfully.\n            self.get_success(get_event1)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 189,
        "n_words": 54,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 64,
        "n_ast_nodes": 112,
        "n_identifiers": 15,
        "d_id": 72077,
        "documentation": {
            "docstring": "Test cancellation of the second `get_event` call sharing a database fetch.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 104416,
        "commit_id": "e35be138148333078284b942ccc9ed7b1d826f97",
        "repo": "datasets",
        "path": "src/datasets/table.py",
        "file_name": "table.py",
        "fun_name": "remove_column",
        "commit_message": "Update docs to new frontend/UI (#3690)\n\n* WIP: update docs to new UI\r\n\r\n* make style\r\n\r\n* Rm unused\r\n\r\n* inject_arrow_table_documentation __annotations__\r\n\r\n* hasattr(arrow_table_method, \"__annotations__\")\r\n\r\n* Update task_template.rst\r\n\r\n* Codeblock PT-TF-SPLIT\r\n\r\n* Convert loading scripts\r\n\r\n* Convert docs to mdx\r\n\r\n* Fix mdx\r\n\r\n* Add <Tip>\r\n\r\n* Convert mdx tables\r\n\r\n* Fix codeblock\r\n\r\n* Rm unneded hashlinks\r\n\r\n* Update index.mdx\r\n\r\n* Redo dev change\r\n\r\n* Rm circle ci `build_doc` & `deploy_doc`\r\n\r\n* Rm unneeded files\r\n\r\n* Update docs reamde\r\n\r\n* Standardize to `Example::`\r\n\r\n* mdx logging levels doc\r\n\r\n* Table properties inject_arrow_table_documentation\r\n\r\n* ``` to ```py mdx\r\n\r\n* Add Tips mdx\r\n\r\n* important,None -> <Tip warning={true}>\r\n\r\n* More misc\r\n\r\n* Center imgs\r\n\r\n* Update instllation page\r\n\r\n* `setup.py` docs section\r\n\r\n* Rm imgs since they are in hf.co\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* Update index mdx\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* just `Dataset` obj\r\n\r\n* Addedversion just italics\r\n\r\n* Update ReadInstruction doc example syntax\r\n\r\n* Change docstring for `prepare_for_task`\r\n\r\n* Chore\r\n\r\n* Remove `code` syntax from headings\r\n\r\n* Rm `code` syntax from headings\r\n\r\n* Hashlink backward compatability\r\n\r\n* S3FileSystem doc\r\n\r\n* S3FileSystem doc updates\r\n\r\n* index.mdx updates\r\n\r\n* Add darkmode gifs\r\n\r\n* Index logo img css classes\r\n\r\n* Index mdx dataset logo img size\r\n\r\n* Docs for DownloadMode class\r\n\r\n* Doc DownloadMode table\r\n\r\n* format docstrings\r\n\r\n* style\r\n\r\n* Add doc builder scripts (#3790)\r\n\r\n* add doc builder scripts\r\n\r\n* fix docker image\r\n\r\n* Docs new UI actions no self hosted (#3793)\r\n\r\n* No self hosted\r\n\r\n* replace doc injection by actual docstrings\r\n\r\n* Docstring formatted\r\n\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\n* Rm notebooks from docs actions since they dont exi\r\n\r\n* Update tsting branch\r\n\r\n* More docstring\r\n\r\n* Chore\r\n\r\n* bump up node version\r\n\r\n* bump up node\r\n\r\n* ``` -> ```py for audio_process.mdx\r\n\r\n* Update .github/workflows/build_documentation.yml\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\n\r\n* Uodate dev doc build\r\n\r\n* remove run on PR\r\n\r\n* fix action\r\n\r\n* Fix gh doc workflow\r\n\r\n* forgot this change when merging master\r\n\r\n* Update build doc\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>",
        "code": "def remove_column(self, i, *args, **kwargs):\n        \n        table = self.table.remove_column(i, *args, **kwargs)\n        name = self.table.column_names[i]\n        blocks = []\n        for tables in self.blocks:\n            blocks.append(\n                [\n                    t.remove_column(t.column_names.index(name), *args, **kwargs) if name in t.column_names else t\n                    for t in tables\n                ]\n            )\n        return ConcatenationTable(table, blocks)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 172,
        "n_words": 40,
        "vocab_size": 29,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 96,
        "n_ast_nodes": 145,
        "n_identifiers": 14,
        "d_id": 21852,
        "documentation": {
            "docstring": "\n        Create new Table with the indicated column removed.\n\n        Args:\n            i (:obj:`int`):\n                Index of column to remove.\n\n        Returns:\n            :class:`datasets.table.Table`:\n                New table without the column.\n        ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 250282,
        "commit_id": "652d1669c5a103b1c20478770c4aaf18849c09a3",
        "repo": "synapse",
        "path": "tests/handlers/test_e2e_room_keys.py",
        "file_name": "test_e2e_room_keys.py",
        "fun_name": "test_upload_room_keys_bogus_version",
        "commit_message": "Add missing type hints to tests.handlers. (#14680)\n\nAnd do not allow untyped defs in tests.handlers.",
        "code": "def test_upload_room_keys_bogus_version(self) -> None:\n        \n        version = self.get_success(\n            self.handler.create_version(\n                self.local_user,\n                {\n                    \"algorithm\": \"m.megolm_backup.v1\",\n                    \"auth_data\": \"first_version_auth_data\",\n                },\n            )\n        )\n        self.assertEqual(version, \"1\")\n\n        e = self.get_failure(\n            self.handler.upload_room_keys(self.local_user, \"bogus_version\", room_keys),\n            SynapseError,\n        )\n        res = e.value.code\n        self.assertEqual(res, 404)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 215,
        "n_words": 32,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 84,
        "n_ast_nodes": 139,
        "n_identifiers": 16,
        "d_id": 73360,
        "documentation": {
            "docstring": "Check that we get a 404 on uploading keys when an nonexistent version\n        is specified\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 288603,
        "commit_id": "47d0598e75487f63901931875f69f802a477df13",
        "repo": "core",
        "path": "tests/util/test_color.py",
        "file_name": "test_color.py",
        "fun_name": "test_white_levels_to_color_temperature",
        "commit_message": "Use Kelvin as the preferred color temperature unit (#79591)\n\n* Use Kelvin as the preferred white temperature unit\r\n\r\n* Update homekit\r\n\r\n* Adjust tests",
        "code": "def test_white_levels_to_color_temperature():\n    \n    # Only cold channel enabled -> coldest color temperature\n    assert color_util._white_levels_to_color_temperature(255, 0, 2000, 6535) == (\n        6535,\n        255,\n    )\n    assert color_util._white_levels_to_color_temperature(128, 0, 2000, 6535) == (\n        6535,\n        128,\n    )\n    # Only warm channel enabled -> warmest color temperature\n    assert color_util._white_levels_to_color_temperature(0, 255, 2000, 6535) == (\n        2000,\n        255,\n    )\n    assert color_util._white_levels_to_color_temperature(0, 128, 2000, 6535) == (\n        2000,\n        128,\n    )\n    assert color_util._white_levels_to_color_temperature(112, 143, 2000, 6535) == (\n        2876,\n        255,\n    )\n    assert color_util._white_levels_to_color_temperature(56, 72, 2000, 6535) == (\n        2872,\n        128,\n    )\n    # Both channels turned off -> warmest color temperature\n    assert color_util._white_levels_to_color_temperature(0, 0, 2000, 6535) == (\n        2000,\n        0,\n    )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 251,
        "n_words": 99,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 145,
        "n_ast_nodes": 197,
        "n_identifiers": 3,
        "d_id": 87759,
        "documentation": {
            "docstring": "Test warm, cold conversion to color temp.\n\n    Temperature values must be in mireds\n    Home Assistant uses rgbcw for rgbww\n    ",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 220194,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ast.py",
        "file_name": "ast.py",
        "fun_name": "_write_str_avoiding_backslashes",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _write_str_avoiding_backslashes(self, string, *, quote_types=_ALL_QUOTES):\n        \n        string, quote_types = self._str_literal_helper(string, quote_types=quote_types)\n        quote_type = quote_types[0]\n        self.write(f\"{quote_type}{string}{quote_type}\")\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 41,
        "n_ast_nodes": 77,
        "n_identifiers": 8,
        "d_id": 55932,
        "documentation": {
            "docstring": "Write string literal value with a best effort attempt to avoid backslashes.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 275052,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/mixed_precision/loss_scale_optimizer.py",
        "file_name": "loss_scale_optimizer.py",
        "fun_name": "strategy_supports_loss_scaling",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def strategy_supports_loss_scaling():\n    \n    if not tf.distribute.has_strategy():\n        return True\n    strategy = tf.distribute.get_strategy()\n    # Strategies are supported if either there is only one replica or if variables\n    # are replicated per device. Otherwise, the current model.fit() implementation\n    # and most custom training loops incorrectly unscale the gradients. Currently,\n    # gradients are unscaled once per compute replica, but they should be unscaled\n    # once per variable replica. When there is one variable replica for each\n    # compute replica, this works fine, but otherwise issues will occur.\n    # TODO(reedwm): Support all strategies.\n    return isinstance(\n        strategy,\n        (\n            tf.distribute.MultiWorkerMirroredStrategy,\n            tf.compat.v1.distribute.experimental.MultiWorkerMirroredStrategy,\n            tf.distribute.OneDeviceStrategy,\n            tf.compat.v1.distribute.OneDeviceStrategy,\n            tf.distribute.MirroredStrategy,\n            tf.compat.v1.distribute.MirroredStrategy,\n        ),\n    )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 229,
        "n_words": 99,
        "vocab_size": 75,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 85,
        "n_ast_nodes": 136,
        "n_identifiers": 13,
        "d_id": 81301,
        "documentation": {
            "docstring": "Returns True if the current Strategy supports loss scaling.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 72433,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/views/mixins.py",
        "file_name": "mixins.py",
        "fun_name": "stream_csv",
        "commit_message": "Reformat with black",
        "code": "def stream_csv(self, queryset):\n        \n        writer = csv.DictWriter(Echo(), fieldnames=self.list_export)\n        yield writer.writerow(\n            {field: self.get_heading(queryset, field) for field in self.list_export}\n        )\n\n        for item in queryset:\n            yield self.write_csv_row(writer, self.to_row_dict(item))\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 81,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 67,
        "n_ast_nodes": 105,
        "n_identifiers": 15,
        "d_id": 15895,
        "documentation": {
            "docstring": "Generate a csv file line by line from queryset, to be used in a StreamingHTTPResponse",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 154619,
        "commit_id": "e5b1888cd932909e49194d58035da34b210b91c4",
        "repo": "modin",
        "path": "modin/experimental/core/storage_formats/hdk/query_compiler.py",
        "file_name": "query_compiler.py",
        "fun_name": "_agg",
        "commit_message": "FEAT-#4946: Replace OmniSci with HDK (#4947)\n\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Andrey Pavlenko <andrey.a.pavlenko@gmail.com>",
        "code": "def _agg(self, agg, axis=0, level=None, **kwargs):\n        \n        if level is not None or axis != 0:\n            raise NotImplementedError(\n                \"HDK's aggregation functions does not support 'level' and 'axis' parameters.\"\n            )\n\n        # TODO: Do filtering on numeric columns if `numeric_only=True`\n        if not kwargs.get(\"skipna\", True) or kwargs.get(\"numeric_only\"):\n            raise NotImplementedError(\n                \"HDK's aggregation functions does not support 'skipna' and 'numeric_only' parameters.\"\n            )\n        # Processed above, so can be omitted\n        kwargs.pop(\"skipna\", None)\n        kwargs.pop(\"numeric_only\", None)\n\n        new_frame = self._modin_frame.agg(agg)\n        new_frame = new_frame._set_index(\n            pandas.Index.__new__(\n                pandas.Index, data=[MODIN_UNNAMED_SERIES_LABEL], dtype=\"O\"\n            )\n        )\n        return self.__constructor__(new_frame, shape_hint=\"row\")\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 270,
        "n_words": 82,
        "vocab_size": 60,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 121,
        "n_ast_nodes": 202,
        "n_identifiers": 20,
        "d_id": 36114,
        "documentation": {
            "docstring": "\n        Perform specified aggregation along rows/columns.\n\n        Parameters\n        ----------\n        agg : str\n            Name of the aggregation function to perform.\n        axis : {0, 1}, default: 0\n            Axis to perform aggregation along. 0 is to apply function against each column,\n            all the columns will be reduced into a single scalar. 1 is to aggregate\n            across rows.\n            *Note:* HDK storage format supports aggregation for 0 axis only, aggregation\n            along rows will be defaulted to pandas.\n        level : None, default: None\n            Serves the compatibility purpose, always have to be None.\n        **kwargs : dict\n            Additional parameters to pass to the aggregation function.\n\n        Returns\n        -------\n        DFAlgQueryCompiler\n            New single-column (``axis=1``) or single-row (``axis=0``) query compiler containing\n            the result of aggregation.\n        ",
            "n_words": 111,
            "vocab_size": 81,
            "n_whitespaces": 299,
            "language": "en"
        }
    },
    {
        "id": 58169,
        "commit_id": "3fd5aef3a1b94ac270e7325aa75d534e4f412d5c",
        "repo": "prefect",
        "path": "src/prefect/orion/services/loop_service.py",
        "file_name": "loop_service.py",
        "fun_name": "run_once",
        "commit_message": "Clean up loop service methods",
        "code": "async def run_once(self) -> None:\n        \n        raise NotImplementedError(\"LoopService subclasses must implement this method.\")\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 26,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 13,
        "n_ast_nodes": 27,
        "n_identifiers": 3,
        "d_id": 11732,
        "documentation": {
            "docstring": "\n        Represents one loop of the service.\n\n        Users should override this method.\n\n        To actually run the service once, call `LoopService().start(loops=1)`\n        instead of `LoopService().run_once()`, because this method will not invoke setup\n        and teardown methods properly.\n        ",
            "n_words": 33,
            "vocab_size": 30,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 246015,
        "commit_id": "7a1cefc6e37aa583647f2804c9d9c9765712c59a",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_no_auth",
        "commit_message": "Add admin API to get users' account data (#11664)\n\nCo-authored-by: reivilibre <olivier@librepush.net>",
        "code": "def test_no_auth(self) -> None:\n        \n        channel = self.make_request(\"GET\", self.url, {})\n\n        self.assertEqual(HTTPStatus.UNAUTHORIZED, channel.code, msg=channel.json_body)\n        self.assertEqual(Codes.MISSING_TOKEN, channel.json_body[\"errcode\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 56,
        "n_ast_nodes": 90,
        "n_identifiers": 13,
        "d_id": 70945,
        "documentation": {
            "docstring": "Try to get information of a user without authentication.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 200621,
        "commit_id": "1823aa534e379b9123f70389f5818ac4d24015a0",
        "repo": "sympy",
        "path": "sympy/algebras/quaternion.py",
        "file_name": "quaternion.py",
        "fun_name": "_is_extrinsic",
        "commit_message": "Changed _check_sequence to _is_extrinsic\r\n\r\nAs suggested by @smichr\n\nCo-authored-by: Christopher Smith <smichr@gmail.com>",
        "code": "def _is_extrinsic(seq):\n    \n    if len(seq) != 3:\n        raise ValueError(\"Expected 3 axes, got `{}`.\".format(seq))\n    if type(seq) != str:\n        raise ValueError('Expected seq to be a string.')\n\n    intrinsic = seq.isupper()\n    extrinsic = seq.islower()\n    if not (intrinsic or extrinsic):\n        raise ValueError(\"seq must either be fully uppercase (for extrinsic \"\n                         \"rotations), or fully lowercase, for intrinsic \"\n                         \"rotations).\")\n\n    i, j, k = seq.lower()\n    if (i == j) or (j == k):\n        raise ValueError(\"Consecutive axes must be different\")\n\n    bad = set(seq) - set('xyzXYZ')\n    if bad:\n        raise ValueError(\"Expected axes from `seq` to be from \"\n                         \"['x', 'y', 'z'] or ['X', 'Y', 'Z'], \"\n                         \"got {}\".format(''.join(bad)))\n\n    return extrinsic\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 263,
        "n_words": 99,
        "vocab_size": 68,
        "complexity": 8,
        "nloc": 20,
        "token_counts": 128,
        "n_ast_nodes": 231,
        "n_identifiers": 18,
        "d_id": 49735,
        "documentation": {
            "docstring": "validate seq and return True if seq is lowercase and False if uppercase",
            "n_words": 13,
            "vocab_size": 10,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 31488,
        "commit_id": "3eed5530ec74bb60ad9f8f612717d0f6ccf820f2",
        "repo": "transformers",
        "path": "src/transformers/tokenization_utils_base.py",
        "file_name": "tokenization_utils_base.py",
        "fun_name": "sep_token",
        "commit_message": "Fix properties of unset special tokens in non verbose mode (#17797)\n\nCo-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>",
        "code": "def sep_token(self) -> str:\n        \n        if self._sep_token is None:\n            if self.verbose:\n                logger.error(\"Using sep_token, but it is not set yet.\")\n            return None\n        return str(self._sep_token)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 80,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 35,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 5763,
        "documentation": {
            "docstring": "\n        `str`: Separation token, to separate context and query in an input sequence. Log an error if used while not\n        having been set.\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 206849,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/generic/dates.py",
        "file_name": "dates.py",
        "fun_name": "get_year",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_year(self):\n        \n        year = self.year\n        if year is None:\n            try:\n                year = self.kwargs[\"year\"]\n            except KeyError:\n                try:\n                    year = self.request.GET[\"year\"]\n                except KeyError:\n                    raise Http404(_(\"No year specified\"))\n        return year\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 160,
        "n_words": 27,
        "vocab_size": 17,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 54,
        "n_ast_nodes": 96,
        "n_identifiers": 9,
        "d_id": 51751,
        "documentation": {
            "docstring": "Return the year for which this view should display data.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 125703,
        "commit_id": "de7bd015a4867317569cb0ad775015f6f35fdd1e",
        "repo": "ray",
        "path": "python/ray/tune/execution/trial_runner.py",
        "file_name": "trial_runner.py",
        "fun_name": "_validate_result_metrics",
        "commit_message": "[air/tune/docs] Change Tuner() occurences in rest of ray/tune (#26961)",
        "code": "def _validate_result_metrics(self, result):\n        \n        if int(os.environ.get(\"TUNE_DISABLE_STRICT_METRIC_CHECKING\", 0)) != 1 and (\n            len({k for k in result if k not in list(DEBUG_METRICS) + [DONE]}) > 1\n        ):\n            base_metric = self._metric if self._metric != DEFAULT_METRIC else None\n            scheduler_metric = (\n                self._scheduler_alg.metric\n                if self._scheduler_alg.metric != DEFAULT_METRIC\n                else None\n            )\n            search_metrics = (\n                self._search_alg.metric\n                if self._search_alg.metric != DEFAULT_METRIC\n                else None\n            )\n\n            if isinstance(search_metrics, str):\n                search_metrics = [search_metrics]\n\n            if base_metric and base_metric not in result:\n                report_metric = base_metric\n                location = \"tune.TuneConfig()\"\n            elif scheduler_metric and scheduler_metric not in result:\n                report_metric = scheduler_metric\n                location = type(self._scheduler_alg).__name__\n            elif search_metrics and any(\n                search_metric not in result for search_metric in search_metrics\n            ):\n                report_metric = list(\n                    filter(\n                        lambda search_metric: search_metric not in result,\n                        search_metrics,\n                    )\n                )\n                if len(report_metric) == 1:\n                    report_metric = report_metric[0]\n                location = type(self._search_alg).__name__\n            else:\n                report_metric = None\n                location = None\n\n            if report_metric:\n                raise ValueError(\n                    \"Trial returned a result which did not include the \"\n                    \"specified metric(s) `{}` that `{}` expects. \"\n                    \"Make sure your calls to `tune.report()` include the \"\n                    \"metric, or set the \"\n                    \"TUNE_DISABLE_STRICT_METRIC_CHECKING \"\n                    \"environment variable to 1. Result: {}\".format(\n                        report_metric, location, result\n                    )\n                )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 902,
        "n_words": 179,
        "vocab_size": 88,
        "complexity": 18,
        "nloc": 49,
        "token_counts": 238,
        "n_ast_nodes": 379,
        "n_identifiers": 31,
        "d_id": 27954,
        "documentation": {
            "docstring": "\n        Check if any of the required metrics was not reported\n        in the last result. If the only items are ``done`` or any of\n        DEBUG_METRICS, this means that no result was ever received and\n        the trial just returned. This is also okay and will not raise\n        an error.\n\n        This will ignore checking for the DEFAULT_METRIC.\n        ",
            "n_words": 54,
            "vocab_size": 43,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 204301,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/sessions/backends/db.py",
        "file_name": "db.py",
        "fun_name": "save",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def save(self, must_create=False):\n        \n        if self.session_key is None:\n            return self.create()\n        data = self._get_session(no_load=must_create)\n        obj = self.create_model_instance(data)\n        using = router.db_for_write(self.model, instance=obj)\n        try:\n            with transaction.atomic(using=using):\n                obj.save(\n                    force_insert=must_create, force_update=not must_create, using=using\n                )\n        except IntegrityError:\n            if must_create:\n                raise CreateError\n            raise\n        except DatabaseError:\n            if not must_create:\n                raise UpdateError\n            raise\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 244,
        "n_words": 43,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 103,
        "n_ast_nodes": 168,
        "n_identifiers": 23,
        "d_id": 50688,
        "documentation": {
            "docstring": "\n        Save the current session data to the database. If 'must_create' is\n        True, raise a database error if the saving operation doesn't create a\n        new entry (as opposed to possibly updating an existing entry).\n        ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 43921,
        "commit_id": "d48a3a357fd89ec805d086d5b6c1f1d4daf77b9a",
        "repo": "airflow",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "dag_maker",
        "commit_message": "Add TaskMap and TaskInstance.map_id (#20286)\n\nCo-authored-by: Ash Berlin-Taylor <ash_github@firemirror.com>",
        "code": "def dag_maker(request):\n    \n    import lazy_object_proxy\n\n    # IMPORTANT: Delay _all_ imports from `airflow.*` to _inside a method_.\n    # This fixture is \"called\" early on in the pytest collection process, and\n    # if we import airflow.* here the wrong (non-test) config will be loaded\n    # and \"baked\" in to various constants\n\n    want_serialized = False\n\n    # Allow changing default serialized behaviour with `@pytest.mark.need_serialized_dag` or\n    # `@pytest.mark.need_serialized_dag(False)`\n    serialized_marker = request.node.get_closest_marker(\"need_serialized_dag\")\n    if serialized_marker:\n        (want_serialized,) = serialized_marker.args or (True,)\n\n    from airflow.utils.log.logging_mixin import LoggingMixin\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 119,
        "n_words": 76,
        "vocab_size": 60,
        "complexity": 4,
        "nloc": 25,
        "token_counts": 100,
        "n_ast_nodes": 83,
        "n_identifiers": 13,
        "d_id": 8096,
        "documentation": {
            "docstring": "\n    The dag_maker helps us to create DAG, DagModel, and SerializedDAG automatically.\n\n    You have to use the dag_maker as a context manager and it takes\n    the same argument as DAG::\n\n        with dag_maker(dag_id=\"mydag\") as dag:\n            task1 = DummyOperator(task_id='mytask')\n            task2 = DummyOperator(task_id='mytask2')\n\n    If the DagModel you want to use needs different parameters than the one\n    automatically created by the dag_maker, you have to update the DagModel as below::\n\n        dag_maker.dag_model.is_active = False\n        session.merge(dag_maker.dag_model)\n        session.commit()\n\n    For any test you use the dag_maker, make sure to create a DagRun::\n\n        dag_maker.create_dagrun()\n\n    The dag_maker.create_dagrun takes the same arguments as dag.create_dagrun\n\n    If you want to operate on serialized DAGs, then either pass ``serialized=True` to the ``dag_maker()``\n    call, or you can mark your test/class/file with ``@pytest.mark.need_serialized_dag(True)``. In both of\n    these cases the ``dag`` returned by the context manager will be a lazily-evaluated proxy object to the\n    SerializedDAG.\n    ",
            "n_words": 137,
            "vocab_size": 90,
            "n_whitespaces": 231,
            "language": "en"
        }
    },
    {
        "id": 160188,
        "commit_id": "f404e9e92e87a3990712d723d5c562a89300ac01",
        "repo": "numpy",
        "path": "numpy/lib/function_base.py",
        "file_name": "function_base.py",
        "fun_name": "rot90",
        "commit_message": "Add space after argument name",
        "code": "def rot90(m, k=1, axes=(0, 1)):\n    \n    axes = tuple(axes)\n    if len(axes) != 2:\n        raise ValueError(\"len(axes) must be 2.\")\n\n    m = asanyarray(m)\n\n    if axes[0] == axes[1] or absolute(axes[0] - axes[1]) == m.ndim:\n        raise ValueError(\"Axes must be different.\")\n\n    if (axes[0] >= m.ndim or axes[0] < -m.ndim\n        or axes[1] >= m.ndim or axes[1] < -m.ndim):\n        raise ValueError(\"Axes={} out of range for array of ndim={}.\"\n            .format(axes, m.ndim))\n\n    k %= 4\n\n    if k == 0:\n        return m[:]\n    if k == 2:\n        return flip(flip(m, axes[0]), axes[1])\n\n    axes_list = arange(0, m.ndim)\n    (axes_list[axes[0]], axes_list[axes[1]]) = (axes_list[axes[1]],\n                                                axes_list[axes[0]])\n\n    if k == 1:\n        return transpose(flip(m, axes[1]), axes_list)\n    else:\n        # k == 3\n        return flip(transpose(m, axes_list), axes[1])\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 265,
        "n_words": 105,
        "vocab_size": 68,
        "complexity": 11,
        "nloc": 79,
        "token_counts": 250,
        "n_ast_nodes": 377,
        "n_identifiers": 15,
        "d_id": 38560,
        "documentation": {
            "docstring": "\n    Rotate an array by 90 degrees in the plane specified by axes.\n\n    Rotation direction is from the first towards the second axis.\n\n    Parameters\n    ----------\n    m : array_like\n        Array of two or more dimensions.\n    k : integer\n        Number of times the array is rotated by 90 degrees.\n    axes : (2,) array_like\n        The array is rotated in the plane defined by the axes.\n        Axes must be different.\n\n        .. versionadded:: 1.12.0\n\n    Returns\n    -------\n    y : ndarray\n        A rotated view of `m`.\n\n    See Also\n    --------\n    flip : Reverse the order of elements in an array along the given axis.\n    fliplr : Flip an array horizontally.\n    flipud : Flip an array vertically.\n\n    Notes\n    -----\n    ``rot90(m, k=1, axes=(1,0))``  is the reverse of\n    ``rot90(m, k=1, axes=(0,1))``\n\n    ``rot90(m, k=1, axes=(1,0))`` is equivalent to\n    ``rot90(m, k=-1, axes=(0,1))``\n\n    Examples\n    --------\n    >>> m = np.array([[1,2],[3,4]], int)\n    >>> m\n    array([[1, 2],\n           [3, 4]])\n    >>> np.rot90(m)\n    array([[2, 4],\n           [1, 3]])\n    >>> np.rot90(m, 2)\n    array([[4, 3],\n           [2, 1]])\n    >>> m = np.arange(8).reshape((2,2,2))\n    >>> np.rot90(m, 1, (1,2))\n    array([[[1, 3],\n            [0, 2]],\n           [[5, 7],\n            [4, 6]]])\n\n    ",
            "n_words": 170,
            "vocab_size": 108,
            "n_whitespaces": 378,
            "language": "en"
        }
    },
    {
        "id": 244350,
        "commit_id": "9a3bf7660e6ced54672741095f96df07919f9ba7",
        "repo": "mmdetection",
        "path": "mmdet/models/dense_heads/dense_test_mixins.py",
        "file_name": "dense_test_mixins.py",
        "fun_name": "aug_test_rpn",
        "commit_message": "[Refactor] Refactor dense head outputs to InstanceResults.",
        "code": "def aug_test_rpn(self, feats, img_metas):\n        \n        samples_per_gpu = len(img_metas[0])\n        aug_proposals = [[] for _ in range(samples_per_gpu)]\n        for x, img_meta in zip(feats, img_metas):\n            results_list = self.simple_test_rpn(x, img_meta)\n            for i, results in enumerate(results_list):\n                proposals = torch.cat(\n                    [results.bboxes, results.scores[:, None]], dim=-1)\n                aug_proposals[i].append(proposals)\n        # reorganize the order of 'img_metas' to match the dimensions\n        # of 'aug_proposals'\n        aug_img_metas = []\n        for i in range(samples_per_gpu):\n            aug_img_meta = []\n            for j in range(len(img_metas)):\n                aug_img_meta.append(img_metas[j][i])\n            aug_img_metas.append(aug_img_meta)\n        # after merging, proposals will be rescaled to the original image size\n\n        merged_proposals = []\n        for proposals, aug_img_meta in zip(aug_proposals, aug_img_metas):\n            merged_proposal = merge_aug_proposals(proposals, aug_img_meta,\n                                                  self.test_cfg)\n            results = InstanceData()\n            results.bboxes = merged_proposal[:, :4]\n            results.scores = merged_proposal[:, 4]\n            merged_proposals.append(results)\n        return merged_proposals\n\n    if sys.version_info >= (3, 7):\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 421,
        "n_words": 111,
        "vocab_size": 77,
        "complexity": 7,
        "nloc": 24,
        "token_counts": 206,
        "n_ast_nodes": 335,
        "n_identifiers": 34,
        "d_id": 70342,
        "documentation": {
            "docstring": "Test with augmentation for only for ``RPNHead`` and its variants,\n        e.g., ``GARPNHead``, etc.\n\n        Args:\n            feats (tuple[Tensor]): Features from the upstream network, each is\n                        a 4D-tensor.\n            img_metas (list[dict]): Meta info of each image.\n\n        Returns:\n            list[Tensor]: Proposals of each image, each item has shape (n, 5),\n                where 5 represent (tl_x, tl_y, br_x, br_y, score).\n        ",
            "n_words": 52,
            "vocab_size": 47,
            "n_whitespaces": 151,
            "language": "en"
        }
    },
    {
        "id": 64314,
        "commit_id": "a3e69cf75d27198132d05c7c10475a0297b1e190",
        "repo": "erpnext",
        "path": "erpnext/utilities/bulk_transaction.py",
        "file_name": "bulk_transaction.py",
        "fun_name": "show_job_status",
        "commit_message": "feat: Bulk Transaction Processing (#28580)\n\n* feat: Bulk Transaction Processing\r\n\r\n* fix: add flags to ignore validations and exception handling correction\r\n\r\n* fix: remove duplicate code, added logger functionality and improved notifications\r\n\r\n* fix: linting and sider issues\r\n\r\n* test: added tests\r\n\r\n* fix: linter issues\r\n\r\n* fix: failing test case\r\n\r\n* fix: sider issues and test cases\r\n\r\n* refactor: mapping function calls to create order/invoice\r\n\r\n* fix: added more test cases to increase coverage\r\n\r\n* fix: test cases\r\n\r\n* fix: sider issue\r\n\r\n* fix: rename doctype, improve formatting and minor refactor\r\n\r\n* fix: update doctype name in hooks and sider issues\r\n\r\n* fix: entry log test case\r\n\r\n* fix: typos, translations and company name in tests\r\n\r\n* fix: linter issues and translations\r\n\r\n* fix: linter issue\r\n\r\n* fix: split into separate function for marking failed transaction\r\n\r\n* fix: typos, retry failed transaction logic and make log read only\r\n\r\n* fix: hide retry button when no failed transactions and remove test cases not rrelevant\r\n\r\n* fix: sider issues and indentation to tabs\r\n\r\nCo-authored-by: Ankush Menat <ankush@frappe.io>",
        "code": "def show_job_status(failed_history, deserialized_data, to_doctype):\n\tif not failed_history:\n\t\tfrappe.msgprint(\n\t\t\t_(\"Creation of {0} successful\").format(to_doctype),\n\t\t\ttitle=\"Successful\",\n\t\t\tindicator=\"green\",\n\t\t)\n\n\tif len(failed_history) != 0 and len(failed_history) < len(deserialized_data):\n\t\tfrappe.msgprint(\n\t\t\t_().format(\n\t\t\t\tto_doctype\n\t\t\t),\n\t\t\ttitle=\"Partially successful\",\n\t\t\tindicator=\"orange\",\n\t\t)\n\n\tif len(failed_history) == len(deserialized_data):\n\t\tfrappe.msgprint(\n\t\t\t_().format(\n\t\t\t\tto_doctype\n\t\t\t),\n\t\t\ttitle=\"Failed\",\n\t\t\tindicator=\"red\",\n\t\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 19,
        "n_words": 42,
        "vocab_size": 30,
        "complexity": 5,
        "nloc": 25,
        "token_counts": 111,
        "n_ast_nodes": 187,
        "n_identifiers": 11,
        "d_id": 13603,
        "documentation": {
            "docstring": "Creation of {0} partially successful.\n\t\t\t\tCheck <b><a href=\"/app/bulk-transaction-log\">Bulk Transaction Log</a></b>Creation of {0} failed.\n\t\t\t\tCheck <b><a href=\"/app/bulk-transaction-log\">Bulk Transaction Log</a></b>",
            "n_words": 18,
            "vocab_size": 12,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 212228,
        "commit_id": "560a57e166a1f54319df57127502d48ee4ecc72e",
        "repo": "bokeh",
        "path": "bokeh/models/util/structure.py",
        "file_name": "structure.py",
        "fun_name": "_make_prop_dict",
        "commit_message": "Generalize filtering on CDS views (#12054)\n\n* Generalize filtering on CDS views\r\n\r\n* Add type information to us_{counties,states}\r\n\r\n* Add plotting/file/filtering example\r\n\r\n* Add a migration note\r\n\r\n* Update models.util.structure and tests\r\n\r\n* Fix a pandas' deprecation warning\r\n\r\n* Update CDSView.{filters->filter}\r\n\r\n* Update documentation\r\n\r\n* Add more unit tests for BitSet (Indices)\r\n\r\n* Add unit tests\r\n\r\n* Add CDSView.filters back-compat to bokehjs",
        "code": "def _make_prop_dict(self) -> pd.DataFrame:\n        \n        pd = import_required(\"pandas\", \"Structure graphs require Pandas (http://pandas.pydata.org) to be installed\")\n        df = pd.DataFrame()\n        for x in self._graph.nodes(data=True):\n            M = self._model.select_one(dict(id=x[0]))\n            Z = pd.DataFrame(self._obj_props_to_df2(M))\n            Z[\"id\"] = x[0]\n            Z[\"model\"] = str(M)\n            Z[\"values\"] = Z[\"values\"].map(lambda x: str(x))\n            Z[\"types\"] = Z[\"types\"].map(lambda x: str(x))\n            df = pd.concat([df, Z])\n        return df\n",
        "url": "https://github.com/bokeh/bokeh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 162,
        "n_words": 50,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 142,
        "n_ast_nodes": 239,
        "n_identifiers": 20,
        "d_id": 53207,
        "documentation": {
            "docstring": " Returns a dataframe containing all the properties of all the submodels of the model being\n        analyzed. Used as datasource to show attributes.\n\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 242436,
        "commit_id": "a0e1fde1eddf45f26653e2ff6080d31e177adbec",
        "repo": "Pillow",
        "path": "src/PIL/ImageFile.py",
        "file_name": "ImageFile.py",
        "fun_name": "encode_to_file",
        "commit_message": "Added PyEncoder",
        "code": "def encode_to_file(self, fh, bufsize):\n        \n        errcode = 0\n        while errcode == 0:\n            status, errcode, buf = self.encode(bufsize)\n            if status > 0:\n                fh.write(buf[status:])\n        return errcode\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 88,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 75,
        "n_identifiers": 9,
        "d_id": 69858,
        "documentation": {
            "docstring": "\n        :param fh: File handle.\n        :param bufsize: Buffer size.\n\n        :returns: If finished successfully, return 0.\n            Otherwise, return an error code. Err codes are from\n            :data:`.ImageFile.ERRORS`.\n        ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 276953,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/layer_utils.py",
        "file_name": "layer_utils.py",
        "fun_name": "count_params",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def count_params(weights):\n    \n    unique_weights = {id(w): w for w in weights}.values()\n    # Ignore TrackableWeightHandlers, which will not have a shape defined.\n    unique_weights = [w for w in unique_weights if hasattr(w, \"shape\")]\n    weight_shapes = [w.shape.as_list() for w in unique_weights]\n    standardized_weight_shapes = [\n        [0 if w_i is None else w_i for w_i in w] for w in weight_shapes\n    ]\n    return int(sum(np.prod(p) for p in standardized_weight_shapes))\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 93,
        "n_words": 62,
        "vocab_size": 39,
        "complexity": 9,
        "nloc": 8,
        "token_counts": 93,
        "n_ast_nodes": 145,
        "n_identifiers": 17,
        "d_id": 81800,
        "documentation": {
            "docstring": "Count the total number of scalars composing the weights.\n\n    Args:\n        weights: An iterable containing the weights on which to compute params\n\n    Returns:\n        The total number of scalars composing the weights\n    ",
            "n_words": 30,
            "vocab_size": 21,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 266015,
        "commit_id": "e7f54c5867cf49126bbf95e28633e4283c2bbcb2",
        "repo": "netbox",
        "path": "netbox/extras/plugins/templates.py",
        "file_name": "templates.py",
        "fun_name": "render",
        "commit_message": "Reorganize plugin resources",
        "code": "def render(self, template_name, extra_context=None):\n        \n        if extra_context is None:\n            extra_context = {}\n        elif not isinstance(extra_context, dict):\n            raise TypeError(\"extra_context must be a dictionary\")\n\n        return get_template(template_name).render({**self.context, **extra_context})\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 74,
        "n_words": 24,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 9,
        "d_id": 78268,
        "documentation": {
            "docstring": "\n        Convenience method for rendering the specified Django template using the default context data. An additional\n        context dictionary may be passed as `extra_context`.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 24488,
        "commit_id": "ddaa2c2552e19635cd6cdf38619f1f176c358f89",
        "repo": "PaddleOCR",
        "path": "ppstructure/table/table_master_match.py",
        "file_name": "table_master_match.py",
        "fun_name": "deal_bb",
        "commit_message": "add SLANet",
        "code": "def deal_bb(result_token):\n    \n    # find out <thead></thead> parts.\n    thead_pattern = '<thead>(.*?)</thead>'\n    if re.search(thead_pattern, result_token) is None:\n        return result_token\n    thead_part = re.search(thead_pattern, result_token).group()\n    origin_thead_part = copy.deepcopy(thead_part)\n\n    # check \"rowspan\" or \"colspan\" occur in <thead></thead> parts or not .\n    span_pattern = \"<td rowspan=\\\"(\\d)+\\\" colspan=\\\"(\\d)+\\\">|<td colspan=\\\"(\\d)+\\\" rowspan=\\\"(\\d)+\\\">|<td rowspan=\\\"(\\d)+\\\">|<td colspan=\\\"(\\d)+\\\">\"\n    span_iter = re.finditer(span_pattern, thead_part)\n    span_list = [s.group() for s in span_iter]\n    has_span_in_head = True if len(span_list) > 0 else False\n\n    if not has_span_in_head:\n        # <thead></thead> not include \"rowspan\" or \"colspan\" branch 1.\n        # 1. replace <td> to <td><b>, and </td> to </b></td>\n        # 2. it is possible to predict text include <b> or </b> by Text-line recognition,\n        #    so we replace <b><b> to <b>, and </b></b> to </b>\n        thead_part = thead_part.replace('<td>', '<td><b>')\\\n            .replace('</td>', '</b></td>')\\\n            .replace('<b><b>', '<b>')\\\n            .replace('</b></b>', '</b>')\n    else:\n        # <thead></thead> include \"rowspan\" or \"colspan\" branch 2.\n        # Firstly, we deal rowspan or colspan cases.\n        # 1. replace > to ><b>\n        # 2. replace </td> to </b></td>\n        # 3. it is possible to predict text include <b> or </b> by Text-line recognition,\n        #    so we replace <b><b> to <b>, and </b><b> to </b>\n\n        # Secondly, deal ordinary cases like branch 1\n\n        # replace \">\" to \"<b>\"\n        replaced_span_list = []\n        for sp in span_list:\n            replaced_span_list.append(sp.replace('>', '><b>'))\n        for sp, rsp in zip(span_list, replaced_span_list):\n            thead_part = thead_part.replace(sp, rsp)\n\n        # replace \"</td>\" to \"</b></td>\"\n        thead_part = thead_part.replace('</td>', '</b></td>')\n\n        # remove duplicated <b> by re.sub\n        mb_pattern = \"(<b>)+\"\n        single_b_string = \"<b>\"\n        thead_part = re.sub(mb_pattern, single_b_string, thead_part)\n\n        mgb_pattern = \"(</b>)+\"\n        single_gb_string = \"</b>\"\n        thead_part = re.sub(mgb_pattern, single_gb_string, thead_part)\n\n        # ordinary cases like branch 1\n        thead_part = thead_part.replace('<td>', '<td><b>').replace('<b><b>',\n                                                                   '<b>')\n\n    # convert <tb><b></b></tb> back to <tb></tb>, empty cell has no <b></b>.\n    # but space cell(<tb> </tb>)  is suitable for <td><b> </b></td>\n    thead_part = thead_part.replace('<td><b></b></td>', '<td></td>')\n    # deal with duplicated <b></b>\n    thead_part = deal_duplicate_bb(thead_part)\n    # deal with isolate span tokens, which causes by wrong predict by structure prediction.\n    # eg.PMC5994107_011_00.png\n    thead_part = deal_isolate_span(thead_part)\n    # replace original result with new thead part.\n    result_token = result_token.replace(origin_thead_part, thead_part)\n    return result_token\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 720,
        "n_words": 324,
        "vocab_size": 170,
        "complexity": 7,
        "nloc": 35,
        "token_counts": 264,
        "n_ast_nodes": 484,
        "n_identifiers": 30,
        "d_id": 4740,
        "documentation": {
            "docstring": "\n    In our opinion, <b></b> always occurs in <thead></thead> text's context.\n    This function will find out all tokens in <thead></thead> and insert <b></b> by manual.\n    :param result_token:\n    :return:\n    ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 298979,
        "commit_id": "8745401af59da209e6304911f81e5416d4f18bd7",
        "repo": "core",
        "path": "homeassistant/components/zha/climate.py",
        "file_name": "climate.py",
        "fun_name": "_rm_rs_action",
        "commit_message": "Use climate enums in zha (#70754)",
        "code": "def _rm_rs_action(self) -> HVACAction | None:\n        \n\n        if (running_state := self._thrm.running_state) is None:\n            return None\n        if running_state & (\n            T.RunningState.Heat_State_On | T.RunningState.Heat_2nd_Stage_On\n        ):\n            return HVACAction.HEATING\n        if running_state & (\n            T.RunningState.Cool_State_On | T.RunningState.Cool_2nd_Stage_On\n        ):\n            return HVACAction.COOLING\n        if running_state & (\n            T.RunningState.Fan_State_On\n            | T.RunningState.Fan_2nd_Stage_On\n            | T.RunningState.Fan_3rd_Stage_On\n        ):\n            return HVACAction.FAN\n        if running_state & T.RunningState.Idle:\n            return HVACAction.IDLE\n        if self.hvac_mode != HVACMode.OFF:\n            return HVACAction.IDLE\n        return HVACAction.OFF\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 258,
        "n_words": 60,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 23,
        "token_counts": 124,
        "n_ast_nodes": 193,
        "n_identifiers": 22,
        "d_id": 97918,
        "documentation": {
            "docstring": "Return the current HVAC action based on running mode and running state.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 321317,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/misc/miscwidgets.py",
        "file_name": "miscwidgets.py",
        "fun_name": "mousePressEvent",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def mousePressEvent(self, e):\n        \n        if e.button() == Qt.MouseButton.LeftButton:\n            e.accept()\n            self.toggle()\n        else:\n            super().mousePressEvent(e)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 65,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 41,
        "n_ast_nodes": 72,
        "n_identifiers": 10,
        "d_id": 117657,
        "documentation": {
            "docstring": "Toggle the fold if the widget was pressed.\n\n        Args:\n            e: The QMouseEvent.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 174994,
        "commit_id": "99eab68bf959e4c71c2688e4b1675ce9147ee785",
        "repo": "pip",
        "path": "src/pip/_vendor/pygments/formatters/img.py",
        "file_name": "img.py",
        "fun_name": "get_text_size",
        "commit_message": "Upgrade pygments to 2.13.0",
        "code": "def get_text_size(self, text):\n        \n        font = self.fonts['NORMAL']\n        if hasattr(font, 'getbbox'):  # Pillow >= 9.2.0\n            return font.getbbox(text)[2:4]\n        else:\n            return font.getsize(text)\n",
        "url": "https://github.com/pypa/pip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 69,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 77,
        "n_identifiers": 8,
        "d_id": 41534,
        "documentation": {
            "docstring": "\n        Get the text size (width, height).\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 246925,
        "commit_id": "02d708568b476f2f7716000b35c0adfa4cbd31b3",
        "repo": "synapse",
        "path": "tests/rest/client/test_upgrade_room.py",
        "file_name": "test_upgrade_room.py",
        "fun_name": "test_power_levels",
        "commit_message": "Replace assertEquals and friends with non-deprecated versions. (#12092)",
        "code": "def test_power_levels(self):\n        \n        # The other user doesn't have the proper power level.\n        channel = self._upgrade_room(self.other_token)\n        self.assertEqual(403, channel.code, channel.result)\n\n        # Increase the power levels so that this user can upgrade.\n        power_levels = self.helper.get_state(\n            self.room_id,\n            \"m.room.power_levels\",\n            tok=self.creator_token,\n        )\n        power_levels[\"users\"][self.other] = 100\n        self.helper.send_state(\n            self.room_id,\n            \"m.room.power_levels\",\n            body=power_levels,\n            tok=self.creator_token,\n        )\n\n        # The upgrade should succeed!\n        channel = self._upgrade_room(self.other_token)\n        self.assertEqual(200, channel.code, channel.result)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 224,
        "n_words": 56,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 109,
        "n_ast_nodes": 172,
        "n_identifiers": 17,
        "d_id": 71409,
        "documentation": {
            "docstring": "\n        Another user can upgrade the room if their power level is increased.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 176628,
        "commit_id": "de1d00f20e0bc14f1cc911b3486e50225a8fa168",
        "repo": "networkx",
        "path": "networkx/generators/classic.py",
        "file_name": "classic.py",
        "fun_name": "wheel_graph",
        "commit_message": "Adjust the usage of nodes_or_number decorator (#5599)\n\n* recorrect typo in decorators.py\r\n\r\n* Update tests to show troubles in current code\r\n\r\n* fix troubles with usage of nodes_or_number\r\n\r\n* fix typo\r\n\r\n* remove nodes_or_number where that makes sense\r\n\r\n* Reinclude nodes_or_numbers and add some tests for nonstandard usage\r\n\r\n* fix typowq\r\n\r\n* hopefully final tweaks (no behavior changes\r\n\r\n* Update test_classic.py\r\n\r\nCo-authored-by: Jarrod Millman <jarrod.millman@gmail.com>",
        "code": "def wheel_graph(n, create_using=None):\n    \n    _, nodes = n\n    G = empty_graph(nodes, create_using)\n    if G.is_directed():\n        raise NetworkXError(\"Directed Graph not supported\")\n\n    if len(nodes) > 1:\n        hub, *rim = nodes\n        G.add_edges_from((hub, node) for node in rim)\n        if len(rim) > 1:\n            G.add_edges_from(pairwise(rim, cyclic=True))\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 97,
        "n_words": 40,
        "vocab_size": 32,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 86,
        "n_ast_nodes": 139,
        "n_identifiers": 16,
        "d_id": 42010,
        "documentation": {
            "docstring": "Return the wheel graph\n\n    The wheel graph consists of a hub node connected to a cycle of (n-1) nodes.\n\n    Parameters\n    ----------\n    n : int or iterable\n        If an integer, node labels are 0 to n with center 0.\n        If an iterable of nodes, the center is the first.\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Node labels are the integers 0 to n - 1.\n    ",
            "n_words": 76,
            "vocab_size": 51,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 337582,
        "commit_id": "23c0341262bd396a3ba9265614b3818d6e08a6c1",
        "repo": "accelerate",
        "path": "tests/test_examples.py",
        "file_name": "test_examples.py",
        "fun_name": "test_checkpointing_by_steps",
        "commit_message": "Refactor tests to use accelerate launch (#373)\n\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def test_checkpointing_by_steps(self):\n        testargs = f.split()\n        _ = subprocess.run(self._launch_args + testargs, stdout=subprocess.PIPE, env=os.environ)\n        self.assertTrue(os.path.exists(os.path.join(self.tmpdir, \"step_4\")))\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 34,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 61,
        "n_ast_nodes": 104,
        "n_identifiers": 18,
        "d_id": 121081,
        "documentation": {
            "docstring": "\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps 2\n        --output_dir {self.tmpdir}\n        ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 316275,
        "commit_id": "7cd68381f1d4f58930ffd631dfbfc7159d459832",
        "repo": "core",
        "path": "tests/components/soma/test_config_flow.py",
        "file_name": "test_config_flow.py",
        "fun_name": "test_exception",
        "commit_message": "Search/replace RESULT_TYPE_* by FlowResultType enum (#74642)",
        "code": "async def test_exception(hass):\n    \n    flow = config_flow.SomaFlowHandler()\n    flow.hass = hass\n    with patch.object(SomaApi, \"list_devices\", side_effect=RequestException()):\n        result = await flow.async_step_import({\"host\": MOCK_HOST, \"port\": MOCK_PORT})\n    assert result[\"type\"] == data_entry_flow.FlowResultType.ABORT\n    assert result[\"reason\"] == \"connection_error\"\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 53,
        "n_words": 28,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 69,
        "n_ast_nodes": 124,
        "n_identifiers": 17,
        "d_id": 114853,
        "documentation": {
            "docstring": "Test if RequestException fires when no connection can be made.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 266036,
        "commit_id": "ea6d86e6c4bb6037465410db6205a7471bc81a6c",
        "repo": "netbox",
        "path": "netbox/extras/tests/test_customfields.py",
        "file_name": "test_customfields.py",
        "fun_name": "test_cf_data",
        "commit_message": "Closes #10052: The cf attribute now returns deserialized custom field data",
        "code": "def test_cf_data(self):\n        \n        site = Site(name='Test Site', slug='test-site')\n\n        # Check custom field data on new instance\n        site.custom_field_data['foo'] = 'abc'\n        self.assertEqual(site.cf['foo'], 'abc')\n\n        # Check custom field data from database\n        site.save()\n        site = Site.objects.get(name='Test Site')\n        self.assertEqual(site.cf['foo'], 'abc')\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 97,
        "n_words": 34,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 69,
        "n_ast_nodes": 129,
        "n_identifiers": 12,
        "d_id": 78273,
        "documentation": {
            "docstring": "\n        Check that custom field data is present on the instance immediately after being set and after being fetched\n        from the database.\n        ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 34277,
        "commit_id": "841d979190319098adc8101f9820a02ee3be4c8b",
        "repo": "transformers",
        "path": "src/transformers/models/realm/tokenization_realm.py",
        "file_name": "tokenization_realm.py",
        "fun_name": "tokenize",
        "commit_message": "Add FastTokenizer to REALM (#15211)\n\n* Remove BertTokenizer abstraction\r\n\r\n* Add FastTokenizer to REALM\r\n\r\n* Fix config archive map\r\n\r\n* Fix copies\r\n\r\n* Update realm.mdx\r\n\r\n* Apply suggestions from code review",
        "code": "def tokenize(self, text, never_split=None):\n        \n        # union() returns a new set by concatenating the two sets.\n        never_split = self.never_split.union(set(never_split)) if never_split else self.never_split\n        text = self._clean_text(text)\n\n        # This was added on November 1st, 2018 for the multilingual and Chinese\n        # models. This is also applied to the English models now, but it doesn't\n        # matter since the English models were not trained on any Chinese data\n        # and generally don't have any Chinese data in them (there are Chinese\n        # characters in the vocabulary because Wikipedia does have some Chinese\n        # words in the English Wikipedia.).\n        if self.tokenize_chinese_chars:\n            text = self._tokenize_chinese_chars(text)\n        orig_tokens = whitespace_tokenize(text)\n        split_tokens = []\n        for token in orig_tokens:\n            if token not in never_split:\n                if self.do_lower_case:\n                    token = token.lower()\n                    if self.strip_accents is not False:\n                        token = self._run_strip_accents(token)\n                elif self.strip_accents:\n                    token = self._run_strip_accents(token)\n            split_tokens.extend(self._run_split_on_punc(token, never_split))\n\n        output_tokens = whitespace_tokenize(\" \".join(split_tokens))\n        return output_tokens\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 396,
        "n_words": 141,
        "vocab_size": 89,
        "complexity": 8,
        "nloc": 18,
        "token_counts": 140,
        "n_ast_nodes": 232,
        "n_identifiers": 21,
        "d_id": 6238,
        "documentation": {
            "docstring": "\n        Basic Tokenization of a piece of text. Split on \"white spaces\" only, for sub-word tokenization, see\n        WordPieceTokenizer.\n\n        Args:\n            never_split (`List[str]`, *optional*)\n                Kept for backward compatibility purposes. Now implemented directly at the base class level (see\n                [`PreTrainedTokenizer.tokenize`]) List of token not to split.\n        ",
            "n_words": 42,
            "vocab_size": 39,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 289733,
        "commit_id": "2f1138562720cd50343d2fedd4981913a9ef6bd9",
        "repo": "core",
        "path": "homeassistant/components/mqtt/mixins.py",
        "file_name": "mixins.py",
        "fun_name": "async_mqtt_connect",
        "commit_message": "Add typing hints for MQTT mixins (#80702)\n\n* Add typing hints for MQTT mixins\r\n\r\n* Follow up comments\r\n\r\n* config_entry is always set\r\n\r\n* typing discovery_data - substate None assignment\r\n\r\n* Rename `config[CONF_DEVICE]` -> specifications",
        "code": "def async_mqtt_connect(self) -> None:\n        \n        if not self.hass.is_stopping:\n            self.async_write_ha_state()\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 88869,
        "documentation": {
            "docstring": "Update state on connection/disconnection to MQTT broker.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 78814,
        "commit_id": "8a7e0884d789449ddbbd08ddae48374d92a14d11",
        "repo": "wagtail",
        "path": "wagtail/tests/test_rich_text.py",
        "file_name": "test_rich_text.py",
        "fun_name": "test_count_characters",
        "commit_message": "Finish implementing rich text max length with identical client & server count",
        "code": "def test_count_characters(self):\n        \n        validator = RichTextMaxLengthValidator(50)\n        self.assertEqual(validator.clean(\"<p>Plain text</p>\"), 10)\n        # HTML entities should be un-escaped.\n        self.assertEqual(validator.clean(\"<p>There&#x27;s quote</p>\"), 13)\n        # BR should be ignored.\n        self.assertEqual(validator.clean(\"<p>Line<br/>break</p>\"), 9)\n        # Content over multiple blocks should be treated as a single line of text with no joiner.\n        self.assertEqual(validator.clean(\"<p>Multi</p><p>blocks</p>\"), 11)\n        # Empty blocks should be ignored.\n        self.assertEqual(validator.clean(\"<p>Empty</p><p></p><p>blocks</p>\"), 11)\n        # HR should be ignored.\n        self.assertEqual(validator.clean(\"<p>With</p><hr/><p>HR</p>\"), 6)\n        # Embed blocks should be ignored.\n        self.assertEqual(validator.clean(\"<p>With</p><embed/><p>embed</p>\"), 9)\n        # Counts symbols with multiple code units (heart unicode + variation selector).\n        self.assertEqual(validator.clean(\"<p>U+2764 U+FE0F ❤️</p>\"), 16)\n        # Counts symbols with zero-width joiners.\n        self.assertEqual(validator.clean(\"<p>👨‍👨‍👧</p>\"), 5)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 223,
        "n_words": 90,
        "vocab_size": 61,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 129,
        "n_ast_nodes": 229,
        "n_identifiers": 6,
        "d_id": 16821,
        "documentation": {
            "docstring": "Keep those tests up-to-date with MaxLength tests client-side.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 94500,
        "commit_id": "7bbb85a0d95d23620228a02bb4401fc09658f5f1",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_all_indexers.py",
        "file_name": "test_all_indexers.py",
        "fun_name": "test_already_created_plus_written_results",
        "commit_message": "ref(metrics): Split caching out of indexers, random test refactoring [sns-1606] (#37714)",
        "code": "def test_already_created_plus_written_results(indexer, indexer_cache) -> None:\n    \n    org_id = 1234\n\n    raw_indexer = indexer\n    indexer = CachingIndexer(indexer_cache, indexer)\n\n    v0 = raw_indexer.record(use_case_id, org_id, \"v1.2.0\")\n    v1 = raw_indexer.record(use_case_id, org_id, \"v1.2.1\")\n    v2 = raw_indexer.record(use_case_id, org_id, \"v1.2.2\")\n\n    expected_mapping = {\"v1.2.0\": v0, \"v1.2.1\": v1, \"v1.2.2\": v2}\n\n    results = indexer.bulk_record(\n        use_case_id=use_case_id, org_strings={org_id: {\"v1.2.0\", \"v1.2.1\", \"v1.2.2\"}}\n    )\n    assert len(results[org_id]) == len(expected_mapping) == 3\n\n    for string, id in results[org_id].items():\n        assert expected_mapping[string] == id\n\n    results = indexer.bulk_record(\n        use_case_id=use_case_id,\n        org_strings={org_id: {\"v1.2.0\", \"v1.2.1\", \"v1.2.2\", \"v1.2.3\"}},\n    )\n    v3 = raw_indexer.resolve(use_case_id, org_id, \"v1.2.3\")\n    expected_mapping[\"v1.2.3\"] = v3\n\n    assert len(results[org_id]) == len(expected_mapping) == 4\n\n    for string, id in results[org_id].items():\n        assert expected_mapping[string] == id\n\n    fetch_meta = results.get_fetch_metadata()\n    assert_fetch_type_for_tag_string_set(\n        fetch_meta[org_id], FetchType.CACHE_HIT, {\"v1.2.0\", \"v1.2.1\", \"v1.2.2\"}\n    )\n    assert_fetch_type_for_tag_string_set(fetch_meta[org_id], FetchType.FIRST_SEEN, {\"v1.2.3\"})\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 216,
        "n_words": 108,
        "vocab_size": 62,
        "complexity": 3,
        "nloc": 32,
        "token_counts": 257,
        "n_ast_nodes": 411,
        "n_identifiers": 27,
        "d_id": 19097,
        "documentation": {
            "docstring": "\n    Test that we correctly combine db read results with db write results\n    for the same organization.\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 61474,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/cachecontrol/caches/file_cache.py",
        "file_name": "file_cache.py",
        "fun_name": "url_to_file_path",
        "commit_message": "upd; format",
        "code": "def url_to_file_path(url, filecache):\n    \n    key = CacheController.cache_url(url)\n    return filecache._fn(key)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 39,
        "n_identifiers": 7,
        "d_id": 12586,
        "documentation": {
            "docstring": "Return the file cache path based on the URL.\n\n    This does not ensure the file exists!\n    ",
            "n_words": 16,
            "vocab_size": 13,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 40175,
        "commit_id": "c3c84b9ecf16bcc61ed80ec39d511af92fe07f2c",
        "repo": "dash",
        "path": "dash/_validate.py",
        "file_name": "_validate.py",
        "fun_name": "validate_multi_return",
        "commit_message": "f-strings everywhere! fffff",
        "code": "def validate_multi_return(outputs_list, output_value, callback_id):\n    if not isinstance(output_value, (list, tuple)):\n        raise exceptions.InvalidCallbackReturnValue(\n            dedent(\n                f\n            )\n        )\n\n    if len(output_value) != len(outputs_list):\n        raise exceptions.InvalidCallbackReturnValue(\n            f\n        )\n\n    for i, outi in enumerate(outputs_list):\n        if isinstance(outi, list):\n            vi = output_value[i]\n            if not isinstance(vi, (list, tuple)):\n                raise exceptions.InvalidCallbackReturnValue(\n                    dedent(\n                        f\n                    )\n                )\n\n            if len(vi) != len(outi):\n                raise exceptions.InvalidCallbackReturnValue(\n                    dedent(\n                        f\n                    )\n                )\n\n",
        "url": "https://github.com/plotly/dash.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 361,
        "n_words": 55,
        "vocab_size": 30,
        "complexity": 7,
        "nloc": 43,
        "token_counts": 122,
        "n_ast_nodes": 275,
        "n_identifiers": 15,
        "d_id": 7339,
        "documentation": {
            "docstring": "\n                The callback {callback_id} is a multi-output.\n                Expected the output type to be a list or tuple but got:\n                {output_value!r}.\n                \n            Invalid number of output values for {callback_id}.\n            Expected {len(outputs_list)}, got {len(output_value)}\n            \n                        The callback {callback_id} output {i} is a wildcard multi-output.\n                        Expected the output type to be a list or tuple but got:\n                        {vi!r}.\n                        output spec: {outi!r}\n                        \n                        Invalid number of output values for {callback_id} item {i}.\n                        Expected {len(vi)}, got {len(outi)}\n                        output spec: {outi!r}\n                        output value: {vi!r}\n                        ",
            "n_words": 74,
            "vocab_size": 38,
            "n_whitespaces": 401,
            "language": "en"
        }
    },
    {
        "id": 262862,
        "commit_id": "1a7d704ffbabb433007e3ba04750c2f13ade48e5",
        "repo": "pyinstaller",
        "path": "tests/unit/test_isolation.py",
        "file_name": "test_isolation.py",
        "fun_name": "test_pipe_leakage",
        "commit_message": "Fix typos (#6782) [skip ci]",
        "code": "def test_pipe_leakage():\n    \n\n    from psutil import Process\n    parent = Process()\n\n    # Get this platform's *count open handles* method.\n    open_fds = parent.num_handles if os.name == \"nt\" else parent.num_fds\n    old = open_fds()\n\n    # Creating an isolated.Python() does nothing.\n    child = isolated.Python()\n    assert open_fds() == old\n\n    # Entering its context creates the child process and 4 handles for sending/receiving to/from it. Then on Windows,\n    # opening the parent's ends of the two pipes creates another two handles and starting the subprocess adds another\n    # two (although I don't know what for).\n    EXPECTED_INCREASE_IN_FDS = (4 if os.name != \"nt\" else 8)\n\n    with child:\n        assert open_fds() == old + EXPECTED_INCREASE_IN_FDS\n    # Exiting must close them all immediately. No implicit closure by garbage collect.\n    assert open_fds() == old\n\n    # Do it again just to be sure that the context manager properly restarts.\n    with child:\n        assert open_fds() == old + EXPECTED_INCREASE_IN_FDS\n    assert open_fds() == old\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 218,
        "n_words": 147,
        "vocab_size": 96,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 94,
        "n_ast_nodes": 171,
        "n_identifiers": 14,
        "d_id": 77412,
        "documentation": {
            "docstring": "\n    There is a finite number of open pipes/file handles/file descriptors allowed per process. Ensure that all\n    opened handles eventually get closed to prevent such *leakages* causing crashes in very long processes (such as\n    the rest of our test suite).\n    ",
            "n_words": 39,
            "vocab_size": 38,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 56293,
        "commit_id": "c33f87fc7e0b6fb4714a88b492e7545f4dbd821f",
        "repo": "prefect",
        "path": "tests/utilities/test_collections.py",
        "file_name": "test_collections.py",
        "fun_name": "test_visit_collection_with_private_pydantic",
        "commit_message": "get private attrs working",
        "code": "async def test_visit_collection_with_private_pydantic(self):\n        \n        input = PrivatePydantic(x=1)\n        input._y = 2\n        input._z = 4\n\n        result = await visit_collection(\n            input, visit_fn=visit_even_numbers, return_data=False\n        )\n        assert result is None\n        assert EVEN == {2, 4}\n\n        result = await visit_collection(\n            input, visit_fn=negative_even_numbers, return_data=True\n        )\n        assert result == input\n        assert result.__private_attributes__ == input.__private_attributes__\n        breakpoint()\n        assert result._y == -2\n        assert result._z == -4\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 181,
        "n_words": 54,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 95,
        "n_ast_nodes": 150,
        "n_identifiers": 16,
        "d_id": 11499,
        "documentation": {
            "docstring": "Check that we successfully capture private pydantic fields",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 60651,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/commands/show.py",
        "file_name": "show.py",
        "fun_name": "search_packages_info",
        "commit_message": "upd; format",
        "code": "def search_packages_info(query):\n    # type: (List[str]) -> Iterator[Dict[str, str]]\n    \n    installed = {}\n    for p in pkg_resources.working_set:\n        installed[canonicalize_name(p.project_name)] = p\n\n    query_names = [canonicalize_name(name) for name in query]\n    missing = sorted(\n        [name for name, pkg in zip(query, query_names) if pkg not in installed]\n    )\n    if missing:\n        logger.warning('Package(s) not found: %s', ', '.join(missing))\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 94,
        "n_words": 49,
        "vocab_size": 37,
        "complexity": 28,
        "nloc": 58,
        "token_counts": 483,
        "n_ast_nodes": 130,
        "n_identifiers": 17,
        "d_id": 12227,
        "documentation": {
            "docstring": "\n    Gather details from installed distributions. Print distribution name,\n    version, location, and installed files. Installed files requires a\n    pip generated 'installed-files.txt' in the distributions '.egg-info'\n    directory.\n    ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 66552,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v11_0/refactor_naming_series.py",
        "file_name": "refactor_naming_series.py",
        "fun_name": "get_series_to_preserve",
        "commit_message": "style: format code with black",
        "code": "def get_series_to_preserve(doctype):\n\tseries_to_preserve = frappe.db.sql_list(\n\t\t.format(\n\t\t\tdoctype=doctype\n\t\t)\n\t)\n\tseries_to_preserve.sort()\n\treturn series_to_preserve\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 4,
        "n_words": 12,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 29,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 14213,
        "documentation": {
            "docstring": "select distinct naming_series from `tab{doctype}` where ifnull(naming_series, '') != ''",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 123306,
        "commit_id": "63977ebdffb9e54978da337a7ec3ce8200723162",
        "repo": "sqlmap",
        "path": "lib/core/common.py",
        "file_name": "common.py",
        "fun_name": "extractRegexResult",
        "commit_message": "Minor update",
        "code": "def extractRegexResult(regex, content, flags=0):\n    \n\n    retVal = None\n\n    if regex and content and \"?P<result>\" in regex:\n        if isinstance(content, six.binary_type) and isinstance(regex, six.text_type):\n            regex = getBytes(regex)\n\n        match = re.search(regex, content, flags)\n\n        if match:\n            retVal = match.group(\"result\")\n\n    return retVal\n",
        "url": "https://github.com/sqlmapproject/sqlmap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 91,
        "n_words": 36,
        "vocab_size": 25,
        "complexity": 7,
        "nloc": 9,
        "token_counts": 74,
        "n_ast_nodes": 119,
        "n_identifiers": 14,
        "d_id": 27333,
        "documentation": {
            "docstring": "\n    Returns 'result' group value from a possible match with regex on a given\n    content\n\n    >>> extractRegexResult(r'a(?P<result>[^g]+)g', 'abcdefg')\n    'bcdef'\n    >>> extractRegexResult(r'a(?P<result>[^g]+)g', 'ABCDEFG', re.I)\n    'BCDEF'\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 33630,
        "commit_id": "59407bbeb31fff8340938768051c9daabd38d7a7",
        "repo": "transformers",
        "path": "src/transformers/models/deformable_detr/modeling_deformable_detr.py",
        "file_name": "modeling_deformable_detr.py",
        "fun_name": "loss_cardinality",
        "commit_message": "Add Deformable DETR (#17281)\n\n* First draft\r\n\r\n* More improvements\r\n\r\n* Improve model, add custom CUDA code\r\n\r\n* Import torch before\r\n\r\n* Add script that imports custom layer\r\n\r\n* Add everything in new ops directory\r\n\r\n* Import custom layer in modeling file\r\n\r\n* Fix ARCHIVE_MAP typo\r\n\r\n* Creating the custom kernel on the fly.\r\n\r\n* Import custom layer in modeling file\r\n\r\n* More improvements\r\n\r\n* Fix CUDA loading\r\n\r\n* More improvements\r\n\r\n* Improve conversion script\r\n\r\n* Improve conversion script\r\n\r\n* Make it work until encoder_outputs\r\n\r\n* Make forward pass work\r\n\r\n* More improvements\r\n\r\n* Make logits match original implementation\r\n\r\n* Make implementation also support single_scale model\r\n\r\n* Add support for single_scale and dilation checkpoint\r\n\r\n* Add support for with_box_refine model\r\n\r\n* Support also two stage model\r\n\r\n* Improve tests\r\n\r\n* Fix more tests\r\n\r\n* Make more tests pass\r\n\r\n* Upload all models to the hub\r\n\r\n* Clean up some code\r\n\r\n* Improve decoder outputs\r\n\r\n* Rename intermediate hidden states and reference points\r\n\r\n* Improve model outputs\r\n\r\n* Move tests to dedicated folder\r\n\r\n* Improve model outputs\r\n\r\n* Fix retain_grad test\r\n\r\n* Improve docs\r\n\r\n* Clean up and make test_initialization pass\r\n\r\n* Improve variable names\r\n\r\n* Add copied from statements\r\n\r\n* Improve docs\r\n\r\n* Fix style\r\n\r\n* Improve docs\r\n\r\n* Improve docs, move tests to model folder\r\n\r\n* Fix rebase\r\n\r\n* Remove DetrForSegmentation from auto mapping\r\n\r\n* Apply suggestions from code review\r\n\r\n* Improve variable names and docstrings\r\n\r\n* Apply some more suggestions from code review\r\n\r\n* Apply suggestion from code review\r\n\r\n* better docs and variables names\r\n\r\n* hint to num_queries and two_stage confusion\r\n\r\n* remove asserts and code refactor\r\n\r\n* add exception if two_stage is True and with_box_refine is False\r\n\r\n* use f-strings\r\n\r\n* Improve docs and variable names\r\n\r\n* Fix code quality\r\n\r\n* Fix rebase\r\n\r\n* Add require_torch_gpu decorator\r\n\r\n* Add pip install ninja to CI jobs\r\n\r\n* Apply suggestion of @sgugger\r\n\r\n* Remove DeformableDetrForObjectDetection from auto mapping\r\n\r\n* Remove DeformableDetrModel from auto mapping\r\n\r\n* Add model to toctree\r\n\r\n* Add model back to mappings, skip model in pipeline tests\r\n\r\n* Apply @sgugger's suggestion\r\n\r\n* Fix imports in the init\r\n\r\n* Fix copies\r\n\r\n* Add CPU implementation\r\n\r\n* Comment out GPU function\r\n\r\n* Undo previous change\r\n\r\n* Apply more suggestions\r\n\r\n* Remove require_torch_gpu annotator\r\n\r\n* Fix quality\r\n\r\n* Add logger.info\r\n\r\n* Fix logger\r\n\r\n* Fix variable names\r\n\r\n* Fix initializaztion\r\n\r\n* Add missing initialization\r\n\r\n* Update checkpoint name\r\n\r\n* Add model to doc tests\r\n\r\n* Add CPU/GPU equivalence test\r\n\r\n* Add Deformable DETR to pipeline tests\r\n\r\n* Skip model for object detection pipeline\r\n\r\nCo-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>\r\nCo-authored-by: Nouamane Tazi <nouamane98@gmail.com>\r\nCo-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>",
        "code": "def loss_cardinality(self, outputs, targets, indices, num_boxes):\n        \n        logits = outputs[\"logits\"]\n        device = logits.device\n        target_lengths = torch.as_tensor([len(v[\"class_labels\"]) for v in targets], device=device)\n        # Count the number of predictions that are NOT \"no-object\" (which is the last class)\n        card_pred = (logits.argmax(-1) != logits.shape[-1] - 1).sum(1)\n        card_err = nn.functional.l1_loss(card_pred.float(), target_lengths.float())\n        losses = {\"cardinality_error\": card_err}\n        return losses\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 115,
        "n_words": 52,
        "vocab_size": 45,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 104,
        "n_ast_nodes": 167,
        "n_identifiers": 23,
        "d_id": 6125,
        "documentation": {
            "docstring": "\n        Compute the cardinality error, i.e. the absolute error in the number of predicted non-empty boxes.\n\n        This is not really a loss, it is intended for logging purposes only. It doesn't propagate gradients.\n        ",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 248428,
        "commit_id": "1e453053cb12ff084fdcdc2f75c08ced274dff21",
        "repo": "synapse",
        "path": "tests/handlers/test_message.py",
        "file_name": "test_message.py",
        "fun_name": "test_duplicated_txn_id_one_call",
        "commit_message": "Rename storage classes (#12913)",
        "code": "def test_duplicated_txn_id_one_call(self):\n        \n\n        txn_id = \"something_else_suitably_random\"\n\n        # Create two duplicate events to persist at the same time\n        event1, context1 = self._create_duplicate_event(txn_id)\n        event2, context2 = self._create_duplicate_event(txn_id)\n\n        # Ensure their event IDs are different to start with\n        self.assertNotEqual(event1.event_id, event2.event_id)\n\n        events, _ = self.get_success(\n            self._persist_event_storage_controller.persist_events(\n                [(event1, context1), (event2, context2)]\n            )\n        )\n\n        # Check that we've deduplicated the events.\n        self.assertEqual(len(events), 2)\n        self.assertEqual(events[0].event_id, events[1].event_id)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 179,
        "n_words": 58,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 99,
        "n_ast_nodes": 158,
        "n_identifiers": 17,
        "d_id": 72277,
        "documentation": {
            "docstring": "Test that we correctly handle duplicates that we try and persist at\n        the same time.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 176433,
        "commit_id": "f11068c0115ede0c7b631f771c10be7efd0b950b",
        "repo": "networkx",
        "path": "networkx/algorithms/tests/test_polynomials.py",
        "file_name": "test_polynomials.py",
        "fun_name": "test_tutte_polynomial_disjoint_K1",
        "commit_message": "Add Tutte polynomial (#5265)\n\nAdd a new polynomial module to algorithms for characteristic polynomials.\r\nAdds the Tutte polynomial, which is computed and ultimate represented as a\r\nsympy expression.\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def test_tutte_polynomial_disjoint_K1():\n    \n    g = nx.complete_graph(1)\n    t_g = nx.tutte_polynomial(g)\n    h = nx.disjoint_union(g, g)\n    t_h = nx.tutte_polynomial(h)\n    assert sympy.simplify(t_g * t_g).equals(t_h)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 37,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 88,
        "n_identifiers": 12,
        "d_id": 41896,
        "documentation": {
            "docstring": "Tutte polynomial factors into the Tutte polynomials of its components.\n    Verify this property with the disjoint union of two copies of `K_1`.\n    ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 9559,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/utils/ganfit_camera.py",
        "file_name": "ganfit_camera.py",
        "fun_name": "perspective",
        "commit_message": "initialize ostec",
        "code": "def perspective(aspect_ratio, fov_y, near_clip, far_clip):\n    \n    focal_lengths_y = 1.0 / np.tan(fov_y * (math.pi / 360.0))\n    depth_range = far_clip - near_clip\n    p_22 = -(far_clip + near_clip) / depth_range\n    p_23 = -2.0 * (far_clip * near_clip / depth_range)\n\n    zeros = np.zeros_like(p_23, dtype=np.float32)\n    # pyformat: disable\n    perspective_transform = np.concatenate(\n      [\n          focal_lengths_y / aspect_ratio, zeros, zeros, zeros,\n          zeros, focal_lengths_y, zeros, zeros,\n          zeros, zeros, p_22, p_23,\n          zeros, zeros, -np.ones_like(p_23, dtype=np.float32), zeros\n      ], axis=0)\n    # pyformat: enable\n    perspective_transform = np.reshape(perspective_transform, [4, 4, -1])\n    return np.transpose(perspective_transform, [2, 0, 1])\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 160,
        "n_words": 81,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 167,
        "n_ast_nodes": 229,
        "n_identifiers": 23,
        "d_id": 1634,
        "documentation": {
            "docstring": "Computes perspective transformation matrices.\n    Functionality mimes gluPerspective (third_party/GL/glu/include/GLU/glu.h).\n    Args:\n      aspect_ratio: float value specifying the image aspect ratio (width/height).\n      fov_y: 1-D float32 Tensor with shape [batch_size] specifying output vertical\n          field of views in degrees.\n      near_clip: 1-D float32 Tensor with shape [batch_size] specifying near\n          clipping plane distance.\n      far_clip: 1-D float32 Tensor with shape [batch_size] specifying far clipping\n          plane distance.\n    Returns:\n      A [batch_size, 4, 4] float tensor that maps from right-handed points in eye\n      space to left-handed points in clip space.\n    ",
            "n_words": 78,
            "vocab_size": 56,
            "n_whitespaces": 147,
            "language": "en"
        }
    },
    {
        "id": 101138,
        "commit_id": "26e26c628803e592ce876e101a45033c87a5a97b",
        "repo": "faceswap",
        "path": "lib/cli/launcher.py",
        "file_name": "launcher.py",
        "fun_name": "_test_tkinter",
        "commit_message": "Update TF to 2.9\n    - Update TF to 2.7 to 2.9\n    - Bump dependencies\n    - Remove decode from pynvml calls\n    - force keras predict functions to non-verbose\n    - update tests\n    - update Tensorboard logging\n    - Update docs",
        "code": "def _test_tkinter(cls) -> None:\n        \n        try:\n            import tkinter  # noqa pylint: disable=unused-import,import-outside-toplevel\n        except ImportError as err:\n            logger.error(\"It looks like TkInter isn't installed for your OS, so the GUI has been \"\n                         \"disabled. To enable the GUI please install the TkInter application. You \"\n                         \"can try:\")\n            logger.info(\"Anaconda: conda install tk\")\n            logger.info(\"Windows/macOS: Install ActiveTcl Community Edition from \"\n                        \"http://www.activestate.com\")\n            logger.info(\"Ubuntu/Mint/Debian: sudo apt install python3-tk\")\n            logger.info(\"Arch: sudo pacman -S tk\")\n            logger.info(\"CentOS/Redhat: sudo yum install tkinter\")\n            logger.info(\"Fedora: sudo dnf install python3-tkinter\")\n            raise FaceswapError(\"TkInter not found\") from err\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 274,
        "n_words": 82,
        "vocab_size": 67,
        "complexity": 2,
        "nloc": 26,
        "token_counts": 69,
        "n_ast_nodes": 141,
        "n_identifiers": 9,
        "d_id": 20568,
        "documentation": {
            "docstring": " If the user is running the GUI, test whether the tkinter app is available on their\n        machine. If not exit gracefully.\n\n        This avoids having to import every tkinter function within the GUI in a wrapper and\n        potentially spamming traceback errors to console.\n\n        Raises\n        ------\n        FaceswapError\n            If tkinter cannot be imported\n        ",
            "n_words": 50,
            "vocab_size": 41,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 163673,
        "commit_id": "acd7218f67fbe31308db7482e11fb9c8f30b51a8",
        "repo": "pandas",
        "path": "pandas/core/base.py",
        "file_name": "base.py",
        "fun_name": "is_monotonic_increasing",
        "commit_message": "DEPR: Index.is_monotonic for Index.is_monotonic_increasing (#45422)",
        "code": "def is_monotonic_increasing(self) -> bool:\n        \n        from pandas import Index\n\n        return Index(self).is_monotonic_increasing\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 39484,
        "documentation": {
            "docstring": "\n        Return boolean if values in the object are\n        monotonic_increasing.\n\n        Returns\n        -------\n        bool\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 320623,
        "commit_id": "9c4169c7b7d96a10012a72c70fc38c6154f7481f",
        "repo": "qutebrowser",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "check_yaml_c_exts",
        "commit_message": "tests: Remove some unused imports",
        "code": "def check_yaml_c_exts():\n    \n    if testutils.ON_CI and sys.version_info[:2] != (3, 10):\n        from yaml import CLoader  # pylint: disable=unused-import\n\n\n@pytest.hookimpl(tryfirst=True, hookwrapper=True)",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "@pytest.hookimpl(tryfirst=True, hookwrapper=True)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 68,
        "n_identifiers": 11,
        "d_id": 117234,
        "documentation": {
            "docstring": "Make sure PyYAML C extensions are available on CI.\n\n    Not available yet with a nightly Python, see:\n    https://github.com/yaml/pyyaml/issues/416\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 276584,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/tests/temporal_sample_weights_correctness_test.py",
        "file_name": "temporal_sample_weights_correctness_test.py",
        "fun_name": "custom_generator_multi_io_temporal",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def custom_generator_multi_io_temporal(self, sample_weights=None):\n        \n        batch_size = 3\n        num_samples = 3\n        iteration = 0\n        while True:\n            batch_index = iteration * batch_size % num_samples\n            iteration += 1\n            start = batch_index\n            end = start + batch_size\n            x = [self.x[start:end], self.x[start:end]]\n            y = [self.y1[start:end], self.y2[start:end]]\n            if sample_weights:\n                sw = tf.nest.map_structure(\n                    lambda w: w[start:end], sample_weights\n                )\n            else:\n                sw = None\n            yield x, y, sw\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 256,
        "n_words": 58,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 116,
        "n_ast_nodes": 180,
        "n_identifiers": 18,
        "d_id": 81689,
        "documentation": {
            "docstring": "Generator for getting data for temporal multi io model.\n\n        Args:\n          sample_weights: List of sample_weights.\n\n        Yields:\n          Tuple of inputs, label, sample weights data.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 204321,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/sitemaps/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "ping_google",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def ping_google(sitemap_url=None, ping_url=PING_URL, sitemap_uses_https=True):\n    \n    sitemap_full_url = _get_sitemap_full_url(sitemap_url, sitemap_uses_https)\n    params = urlencode({\"sitemap\": sitemap_full_url})\n    urlopen(\"%s?%s\" % (ping_url, params))\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 44,
        "n_ast_nodes": 73,
        "n_identifiers": 10,
        "d_id": 50695,
        "documentation": {
            "docstring": "\n    Alert Google that the sitemap for the current site has been updated.\n    If sitemap_url is provided, it should be an absolute path to the sitemap\n    for this site -- e.g., '/sitemap.xml'. If sitemap_url is not provided, this\n    function will attempt to deduce it by using urls.reverse().\n    ",
            "n_words": 46,
            "vocab_size": 34,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 292434,
        "commit_id": "137793c06748b3914ae4906c9d11599dbd83d1fd",
        "repo": "core",
        "path": "tests/components/picnic/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_sensors_no_data",
        "commit_message": "Add sensors for next Picnic deliveries (#66474)",
        "code": "async def test_sensors_no_data(self):\n        \n        # Setup platform with default responses\n        await self._setup_platform(use_default_responses=True)\n\n        # Change mock responses to empty data and refresh the coordinator\n        self.picnic_mock().get_user.return_value = {}\n        self.picnic_mock().get_cart.return_value = None\n        self.picnic_mock().get_deliveries.return_value = None\n        self.picnic_mock().get_delivery_position.side_effect = ValueError\n        await self._coordinator.async_refresh()\n\n        # Assert all default-enabled sensors have STATE_UNAVAILABLE because the last update failed\n        assert self._coordinator.last_update_success is False\n        self._assert_sensor(\"sensor.picnic_cart_total_price\", STATE_UNAVAILABLE)\n        self._assert_sensor(\"sensor.picnic_selected_slot_start\", STATE_UNAVAILABLE)\n        self._assert_sensor(\"sensor.picnic_selected_slot_end\", STATE_UNAVAILABLE)\n        self._assert_sensor(\n            \"sensor.picnic_selected_slot_max_order_time\", STATE_UNAVAILABLE\n        )\n        self._assert_sensor(\n            \"sensor.picnic_selected_slot_min_order_value\", STATE_UNAVAILABLE\n        )\n        self._assert_sensor(\n            \"sensor.picnic_last_order_max_order_time\", STATE_UNAVAILABLE\n        )\n        self._assert_sensor(\"sensor.picnic_last_order_delivery_time\", STATE_UNAVAILABLE)\n        self._assert_sensor(\"sensor.picnic_next_delivery_eta_start\", STATE_UNAVAILABLE)\n        self._assert_sensor(\"sensor.picnic_next_delivery_eta_end\", STATE_UNAVAILABLE)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 270,
        "n_words": 76,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 148,
        "n_ast_nodes": 258,
        "n_identifiers": 17,
        "d_id": 91520,
        "documentation": {
            "docstring": "Test sensor states when the api only returns empty objects.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 204814,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/base.py",
        "file_name": "base.py",
        "fun_name": "get_rollback",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_rollback(self):\n        \n        if not self.in_atomic_block:\n            raise TransactionManagementError(\n                \"The rollback flag doesn't work outside of an 'atomic' block.\"\n            )\n        return self.needs_rollback\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 78,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 21,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 50899,
        "documentation": {
            "docstring": "Get the \"needs rollback\" flag -- for *advanced use* only.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 221103,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/bdb.py",
        "file_name": "bdb.py",
        "fun_name": "get_file_breaks",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_file_breaks(self, filename):\n        \n        filename = self.canonic(filename)\n        if filename in self.breaks:\n            return self.breaks[filename]\n        else:\n            return []\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 65,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 35,
        "n_ast_nodes": 58,
        "n_identifiers": 5,
        "d_id": 56206,
        "documentation": {
            "docstring": "Return all lines with breakpoints for filename.\n\n        If no breakpoints are set, return an empty list.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 264301,
        "commit_id": "54834c47f8870e7faabcd847c3270da0bd3d2884",
        "repo": "netbox",
        "path": "netbox/netbox/views/generic/object_views.py",
        "file_name": "object_views.py",
        "fun_name": "get",
        "commit_message": "Refactor generic views; add plugins dev documentation",
        "code": "def get(self, request, **kwargs):\n        \n        instance = self.get_object(**kwargs)\n\n        return render(request, self.get_template_name(), {\n            'object': instance,\n            **self.get_extra_context(request, instance),\n        })\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 66,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 48,
        "n_ast_nodes": 76,
        "n_identifiers": 9,
        "d_id": 77673,
        "documentation": {
            "docstring": "\n        GET request handler. `*args` and `**kwargs` are passed to identify the object being queried.\n\n        Args:\n            request: The current request\n        ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 197261,
        "commit_id": "c52d6ce2c8d5eecc5b891d05b1c32a456c4cd308",
        "repo": "sympy",
        "path": "sympy/polys/densetools.py",
        "file_name": "densetools.py",
        "fun_name": "dup_eval",
        "commit_message": "fixed error in primitive_element for some case when ext=False",
        "code": "def dup_eval(f, a, K):\n    \n    result = K.zero\n\n    for c in f:\n        result *= a\n        result += c\n\n    return result\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 45,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 40,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 48415,
        "documentation": {
            "docstring": "\n    Evaluate a polynomial at ``x = a`` in ``K[x]`` using Horner scheme.\n\n    Examples\n    ========\n\n    >>> from sympy.polys import ring, ZZ\n    >>> R, x = ring(\"x\", ZZ)\n\n    >>> R.dup_eval(x**2 + 2*x + 3, 2)\n    11\n\n    ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 196116,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/pc_groups.py",
        "file_name": "pc_groups.py",
        "fun_name": "map_relation",
        "commit_message": "Updated import locations",
        "code": "def map_relation(self, w):\n        \n        array = w.array_form\n        s1 = array[0][0]\n        s2 = array[1][0]\n        key = ((s2, -1), (s1, 1), (s2, 1))\n        key = self.free_group.dtype(key)\n        return self.pc_presentation[key]\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 74,
        "n_words": 25,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 70,
        "n_ast_nodes": 104,
        "n_identifiers": 11,
        "d_id": 47616,
        "documentation": {
            "docstring": "\n        Return a conjugate relation.\n\n        Explanation\n        ===========\n\n        Given a word formed by two free group elements, the\n        corresponding conjugate relation with those free\n        group elements is formed and mapped with the collected\n        word in the polycyclic presentation.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics.named_groups import SymmetricGroup\n        >>> from sympy.combinatorics import free_group\n        >>> G = SymmetricGroup(3)\n        >>> PcGroup = G.polycyclic_group()\n        >>> collector = PcGroup.collector\n        >>> F, x0, x1 = free_group(\"x0, x1\")\n        >>> w = x1*x0\n        >>> collector.map_relation(w)\n        x1**2\n\n        See Also\n        ========\n\n        pc_presentation\n\n        ",
            "n_words": 78,
            "vocab_size": 55,
            "n_whitespaces": 233,
            "language": "en"
        }
    },
    {
        "id": 265988,
        "commit_id": "484efdaf75f267a43f9321b938fda1bc967b9e53",
        "repo": "netbox",
        "path": "netbox/utilities/templatetags/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "applied_filters",
        "commit_message": "Closes #9623: Implement saved filters (#10801)\n\n* Initial work on saved filters\r\n\r\n* Return only enabled/shared filters\r\n\r\n* Add tests\r\n\r\n* Clean up filtering of usable SavedFilters",
        "code": "def applied_filters(context, model, form, query_params):\n    \n    user = context['request'].user\n    form.is_valid()  # Ensure cleaned_data has been set\n\n    applied_filters = []\n    for filter_name in form.changed_data:\n        if filter_name not in form.cleaned_data:\n            continue\n\n        querydict = query_params.copy()\n        if filter_name not in querydict:\n            continue\n\n        bound_field = form.fields[filter_name].get_bound_field(form, filter_name)\n        querydict.pop(filter_name)\n        display_value = ', '.join([str(v) for v in get_selected_values(form, filter_name)])\n\n        applied_filters.append({\n            'name': filter_name,\n            'value': form.cleaned_data[filter_name],\n            'link_url': f'?{querydict.urlencode()}',\n            'link_text': f'{bound_field.label}: {display_value}',\n        })\n\n    save_link = None\n    if user.has_perm('extras.add_savedfilter') and 'filter' not in context['request'].GET:\n        content_type = ContentType.objects.get_for_model(model).pk\n        parameters = context['request'].GET.urlencode()\n        url = reverse('extras:savedfilter_add')\n        save_link = f\"{url}?content_types={content_type}&parameters={quote(parameters)}\"\n\n    return {\n        'applied_filters': applied_filters,\n        'save_link': save_link,\n    }\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 283,
        "n_words": 91,
        "vocab_size": 69,
        "complexity": 7,
        "nloc": 29,
        "token_counts": 198,
        "n_ast_nodes": 370,
        "n_identifiers": 36,
        "d_id": 78255,
        "documentation": {
            "docstring": "\n    Display the active filters for a given filter form.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 320783,
        "commit_id": "a20bb67a878b2e68abf8268c1b0a27f018d01352",
        "repo": "qutebrowser",
        "path": "qutebrowser/keyinput/keyutils.py",
        "file_name": "keyutils.py",
        "fun_name": "text",
        "commit_message": "mypy: Upgrade to PyQt5-stubs 5.15.6.0\n\nFor some unknown reason, those new stubs cause a *lot* of things now to be\nchecked by mypy which formerly probably got skipped due to Any being implied\nsomewhere.\n\nThe stubs themselves mainly improved, with a couple of regressions too.\n\nIn total, there were some 337 (!) new mypy errors. This commit fixes almost all\nof them, and the next commit improves a fix to get things down to 0 errors\nagain.\n\nOverview of the changes:\n\n==== qutebrowser/app.py\n\n- Drop type ignore due to improved stubs.\n\n==== qutebrowser/browser/browsertab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  This is debatable: I suppose the abstract stuff shouldn't need to know\n  anything about the concrete backends at all. But it seems like we cut some\n  corners when initially implementing things, and put some code in browsertab.py\n  just because the APIs of both backends happened to be compatible. Perhaps\n  something to reconsider once we drop QtWebKit and hopefully implement a dummy\n  backend.\n\n- Add an additional assertion in AbstractAction.run_string. This is already\n  covered by the isinstance(member, self.action_base) above it, but that's too\n  dynamic for mypy to understand.\n\n- Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x\n  and y components), not a single int.\n\n- Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x\n  and y components), not a single int.\n\n- Fix the argument types of AbstractScroller.to_perc, as it's possible to pass\n  fractional percentages too.\n\n- Specify the type for AbstractHistoryPrivate._history. See above (_widget) re\n  this being debatable.\n\n- Fix the return type of AbstractTabPrivate.event_target(), which can be None\n  (see #3888).\n\n- Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS\n  return value), not None.\n\n- Fix the argument type for AbstractTabPrivate.toggle_inspector: position can\n  be None to use the last used position.\n\n- Declare the type of sub-objects of AbstractTab.\n\n- Fix the return value of AbstractTab.icon(), which is the QIcon, not None.\n\n==== qutebrowser/browser/commands.py\n\n- Make sure the active window is a MainWindow (with a .win_id attribute).\n\n==== qutebrowser/browser/downloadview.py\n\n- Add _model() which makes sure that self.model() is a DownloadModel, not None\n  or any other model. This is needed because other methods access a variety of\n  custom attributes on it, e.g. last_index().\n\n==== qutebrowser/browser/greasemonkey.py\n\n- Add an ignore for AbstractDownload.requested_url which we patch onto the\n  downloads. Probably would be nicer to add it as a proper attribute which always\n  gets set by the DownloadManager.\n\n==== qutebrowser/browser/hints.py\n\n- Remove type ignores for QUrl.toString().\n- Add a new type ignore for combining different URL flags (which works, but is\n  not exactly type safe... still probably a regression in the stubs).\n- Make sure the things we get back from self._get_keyparser are what we actually\n  expect. Probably should introduce a TypedDict (and/or overloads for\n  _get_keyparser with typing.Literal) to teach mypy about the exact return value.\n  See #7098.\n  This is needed because we access Hint/NormalKeyParser-specific attributes such\n  as .set_inhibited_timout() or .update_bindings().\n\n==== qutebrowser/browser/inspector.py\n\n- Similar changes than in browsertab.py to make some types where we share API\n  (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next\n  commit.\n\n==== qutebrowser/browser/network/pac.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/qtnetworkdownloads.py\n\n- Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an\n  AbstractDownload), so that we can call ._uses_nam() on it.\n\n==== qutebrowser/browser/qutescheme.py\n\n- Remove now unneeded type ignore for QUrl flags.\n\n==== qutebrowser/browser/urlmarks.py\n\n- Specify the type of UrlMarkManager._lineparser, as those only get initialized\n  in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist.\n\n==== qutebrowser/browser/webelem.py\n\n- New casts to turn single KeyboardModifier (enum) entries into\n  KeyboardModifiers (flags). Might not be needed anymore with Qt 6.\n- With that, casting the final value is now unneeded.\n\n==== qutebrowser/browser/webengine/notification.py\n\n- Remove now unneeded type ignore for signal.\n- Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished()\n  is a QProcess, not just any QObject.\n\n==== qutebrowser/browser/webengine/webenginedownloads.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webengine/webengineelem.py\n\n- Specify the type of WebEngineElement._tab.\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webengineinspector.py\n\n- See changes to inspector.py and next commit.\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/webengine/webenginequtescheme.py\n\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webenginesettings.py\n\n- Ignore access of .setter attribute which we patch onto QWebEngineProfile.\n  Would be nice to have a subclass or wrapper-class instead.\n\n==== qutebrowser/browser/webengine/webenginetab.py\n\n- Specified the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Remove some now-unneeded type ignores for creating FindFlags.\n- Specify more concrete types for WebEngineTab members where we actually need to\n  access WebEngine-specific attributes.\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webengine/webview.py\n\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webkit/network/networkreply.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webkit/webkitinspector.py\n\n- See changes to inspector.py and next commit.\n\n==== qutebrowser/browser/webkit/webkittab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Add a type ignore for WebKitAction because our workaround needs to\n  treat them as ints (which is allowed by PyQt, even if not type-safe).\n- Add new ignores for findText calls: The text is a QString and can be None; the\n  flags are valid despite mypy thinking they aren't (stubs regression?).\n- Specify the type for WebKitHistoryPrivate._history, because we access\n  WebKit-specific attributes. See above (_widget) re this being debatable.\n- Make mypy aware that .currentFrame() and .frameAt() can return None (stubs\n  regression?).\n- Make sure the .page() and .page().networkAccessManager() are our subclasses\n  rather than the more generic QtWebKit objects, as we use custom attributes.\n- Add new type ignores for signals (stubs regression!)\n\n==== qutebrowser/browser/webkit/webpage.py\n\n- Make sure the .networkAccessManager() is our subclass rather than the more\n  generic QtWebKit object, as we use custom attributes.\n- Replace a cast by a type ignore. The cast didn't work anymore.\n\n==== qutebrowser/browser/webkit/webview.py\n\n- Make sure the .page() is our subclass rather than the more generic QtWebKit\n  object, as we use custom attributes.\n\n==== qutebrowser/commands/userscripts.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/completion/completer.py\n\n- Add a new _completion() getter (which ensures it actually gets the completion\n  view) rather than accessing the .parent() directly (which could be any QObject).\n\n==== qutebrowser/completion/completiondelegate.py\n\n- Make sure self.parent() is a CompletionView (no helper method as there is only\n  one instance).\n- Remove a now-unneeded type ignore for adding QSizes.\n\n==== qutebrowser/completion/completionwidget.py\n\n- Add a ._model() getter which ensures that we get a CompletionModel (with\n  custom attributes) rather than Qt's .model() which can be any QAbstractItemModel\n  (or None).\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/completion/models/completionmodel.py\n\n- Remove now unneeded type ignores for signals.\n- Ignore a complaint about .set_pattern() not being defined. Completion\n  categories don't share any common parent class, so it would be good to introduce\n  a typing.Protocol for this. See #7098.\n\n==== qutebrowser/components/misccommands.py\n\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/components/readlinecommands.py\n\n- Make sure QApplication.instance() is a QApplication (and not just a\n  QCoreApplication). This includes the former \"not None\" check.\n\n==== qutebrowser/components/scrollcommands.py\n\n- Add basic annotation for \"funcs\" dict. Could have a callable protocol to\n  specify it needs a count kwarg, see #7098.\n\n==== qutebrowser/config/stylesheet.py\n\n- Correctly specify that stylesheet apply to QWidgets, not any QObject.\n- Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy\n  about this with overloads and protocols (stylesheet for set_register being None\n  => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not\n  worth the troble. See #7098.\n\n==== qutebrowser/keyinput/keyutils.py\n\n- Remove some now-unneeded type ignores and add a cast for using a single enum\n  value as flags. Might need to look at this again with Qt 6 support.\n\n==== qutebrowser/keyinput/modeman.py\n\n- Add a FIXME for using a TypedDict, see comments for hints.py above.\n\n==== qutebrowser/mainwindow/mainwindow.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n- Improve where we cast from WindowType to WindowFlags, no int needed\n- Use new .tab_bar() getter, see below.\n\n==== qutebrowser/mainwindow/prompt.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n\n==== qutebrowser/mainwindow/statusbar/bar.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/statusbar/command.py\n\n- Fix type for setText() override (from QLineEdit): text can be None\n  (QString in C++).\n\n==== qutebrowser/mainwindow/statusbar/url.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/tabbedbrowser.py\n\n- Specify that TabDeque manages browser tabs, not any QWidgets. It accesses\n  AbstractTab-specific attributes.\n- Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access\n  .maybe_hide.\n- Fix the annotations for stored marks: Scroll positions are a QPoint, not int.\n- Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and\n  .widget(), which ensures that the return values are valid AbstractTabs (or None\n  for _tab_by_idx). This is needed because we access AbstractTab-specific\n  attributes.\n- For some places, where the tab can be None, continue using .currentTab() but\n  add asserts.\n- Remove some now-unneeded [unreachable] ignores, as mypy knows about the None\n  possibility now.\n\n==== qutebrowser/mainwindow/tabwidget.py\n\n- Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and\n  .widget() are of type TabBar and AbstractTab, respectively.\n- Add additional assertions where we expect ._tab_by_idx() to never be None.\n- Remove dead code in get_tab_fields for handling a None y scroll position. I\n  was unable to find any place in the code where this could be set to None.\n- Remove some now-unneeded type ignores and casts, as mypy now knows that\n  _type_by_idx() could be None.\n- Work around a strange instance where mypy complains about not being able to\n  find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility,\n  despite it clearly being shown as a bool *inside* that class without any\n  annotation.\n- Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in\n  fact a TabWidget.\n\n==== qutebrowser/misc/crashsignal.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/editor.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/ipc.py\n\n- Remove now unneeded type ignores for signals.\n- Add new type ignores for .error() which is both a signal and a getter\n  (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was\n  renamed to errorOccurred in 5.15.\n\n==== qutebrowser/misc/objects.py\n\n- Make sure mypy knows that objects.app is our custom Application (with custom\n  attributes) rather than any QApplication.\n\n==== qutebrowser/utils/objreg.py\n\n- Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol,\n  but ideally, the whole objreg stuff should die one day anyways.\n\n==== tests/unit/completion/test_completer.py\n\n- Make CompletionWidgetStub inherit from CompletionView so that it passes the\n  new isinstance() asserts in completer.py (see above).",
        "code": "def text(self) -> str:\n        \n        control = {\n            Qt.Key_Space: ' ',\n            Qt.Key_Tab: '\\t',\n            Qt.Key_Backspace: '\\b',\n            Qt.Key_Return: '\\r',\n            Qt.Key_Enter: '\\r',\n            Qt.Key_Escape: '\\x1b',\n        }\n\n        if self.key in control:\n            return control[self.key]\n        elif not _is_printable(self.key):\n            return ''\n\n        text = QKeySequence(self.key).toString()\n        if not self.modifiers & Qt.ShiftModifier:\n            text = text.lower()\n        return text\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 200,
        "n_words": 45,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 104,
        "n_ast_nodes": 180,
        "n_identifiers": 18,
        "d_id": 117350,
        "documentation": {
            "docstring": "Get the text which would be displayed when pressing this key.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 147843,
        "commit_id": "00922817b66ee14ba215972a98f416f3d6fef1ba",
        "repo": "ray",
        "path": "rllib/execution/train_ops.py",
        "file_name": "train_ops.py",
        "fun_name": "train_one_step",
        "commit_message": "[RLlib] Rewrite PPO to use training_iteration + enable DD-PPO for Win32. (#23673)",
        "code": "def train_one_step(trainer, train_batch, policies_to_train=None) -> Dict:\n    \n\n    config = trainer.config\n    workers = trainer.workers\n    local_worker = workers.local_worker()\n    num_sgd_iter = config.get(\"num_sgd_iter\", 1)\n    sgd_minibatch_size = config.get(\"sgd_minibatch_size\", 0)\n\n    learn_timer = trainer._timers[LEARN_ON_BATCH_TIMER]\n    with learn_timer:\n        # Subsample minibatches (size=`sgd_minibatch_size`) from the\n        # train batch and loop through train batch `num_sgd_iter` times.\n        if num_sgd_iter > 1 or sgd_minibatch_size > 0:\n            info = do_minibatch_sgd(\n                train_batch,\n                {\n                    pid: local_worker.get_policy(pid)\n                    for pid in policies_to_train\n                    or local_worker.get_policies_to_train(train_batch)\n                },\n                local_worker,\n                num_sgd_iter,\n                sgd_minibatch_size,\n                [],\n            )\n        # Single update step using train batch.\n        else:\n            info = local_worker.learn_on_batch(train_batch)\n\n    learn_timer.push_units_processed(train_batch.count)\n    trainer._counters[NUM_ENV_STEPS_TRAINED] += train_batch.count\n    trainer._counters[NUM_AGENT_STEPS_TRAINED] += train_batch.agent_steps()\n\n    return info\n\n\n@DeveloperAPI",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@DeveloperAPI",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 357,
        "n_words": 92,
        "vocab_size": 72,
        "complexity": 5,
        "nloc": 40,
        "token_counts": 151,
        "n_ast_nodes": 245,
        "n_identifiers": 27,
        "d_id": 34101,
        "documentation": {
            "docstring": "Function that improves the all policies in `train_batch` on the local worker.\n\n    Examples:\n        >>> from ray.rllib.execution.rollout_ops import synchronous_parallel_sample\n        >>> trainer = [...] # doctest: +SKIP\n        >>> train_batch = synchronous_parallel_sample(trainer.workers) # doctest: +SKIP\n        >>> # This trains the policy on one batch.\n        >>> results = train_one_step(trainer, train_batch)) # doctest: +SKIP\n        {\"default_policy\": ...}\n\n    Updates the NUM_ENV_STEPS_TRAINED and NUM_AGENT_STEPS_TRAINED counters as well as\n    the LEARN_ON_BATCH_TIMER timer of the `trainer` object.\n    ",
            "n_words": 67,
            "vocab_size": 47,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 197360,
        "commit_id": "65be461082dda54c8748922f9c29a19af1279fe1",
        "repo": "sympy",
        "path": "sympy/solvers/deutils.py",
        "file_name": "deutils.py",
        "fun_name": "_preprocess",
        "commit_message": "Remove abbreviations in documentation",
        "code": "def _preprocess(expr, func=None, hint='_Integral'):\n    \n    if isinstance(expr, Pow):\n        # if f(x)**p=0 then f(x)=0 (p>0)\n        if (expr.exp).is_positive:\n            expr = expr.base\n    derivs = expr.atoms(Derivative)\n    if not func:\n        funcs = set().union(*[d.atoms(AppliedUndef) for d in derivs])\n        if len(funcs) != 1:\n            raise ValueError('The function cannot be '\n                'automatically detected for %s.' % expr)\n        func = funcs.pop()\n    fvars = set(func.args)\n    if hint is None:\n        return expr, func\n    reps = [(d, d.doit()) for d in derivs if not hint.endswith('_Integral') or\n            d.has(func) or set(d.variables) & fvars]\n    eq = expr.subs(reps)\n    return eq, func\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 200,
        "n_words": 83,
        "vocab_size": 61,
        "complexity": 11,
        "nloc": 18,
        "token_counts": 163,
        "n_ast_nodes": 268,
        "n_identifiers": 29,
        "d_id": 48503,
        "documentation": {
            "docstring": "Prepare expr for solving by making sure that differentiation\n    is done so that only func remains in unevaluated derivatives and\n    (if hint does not end with _Integral) that doit is applied to all\n    other derivatives. If hint is None, do not do any differentiation.\n    (Currently this may cause some simple differential equations to\n    fail.)\n\n    In case func is None, an attempt will be made to autodetect the\n    function to be solved for.\n\n    >>> from sympy.solvers.deutils import _preprocess\n    >>> from sympy import Derivative, Function\n    >>> from sympy.abc import x, y, z\n    >>> f, g = map(Function, 'fg')\n\n    If f(x)**p == 0 and p>0 then we can solve for f(x)=0\n    >>> _preprocess((f(x).diff(x)-4)**5, f(x))\n    (Derivative(f(x), x) - 4, f(x))\n\n    Apply doit to derivatives that contain more than the function\n    of interest:\n\n    >>> _preprocess(Derivative(f(x) + x, x))\n    (Derivative(f(x), x) + 1, f(x))\n\n    Do others if the differentiation variable(s) intersect with those\n    of the function of interest or contain the function of interest:\n\n    >>> _preprocess(Derivative(g(x), y, z), f(y))\n    (0, f(y))\n    >>> _preprocess(Derivative(f(y), z), f(y))\n    (0, f(y))\n\n    Do others if the hint does not end in '_Integral' (the default\n    assumes that it does):\n\n    >>> _preprocess(Derivative(g(x), y), f(x))\n    (Derivative(g(x), y), f(x))\n    >>> _preprocess(Derivative(f(x), y), f(x), hint='')\n    (0, f(x))\n\n    Do not do any derivatives if hint is None:\n\n    >>> eq = Derivative(f(x) + 1, x) + Derivative(f(x), y)\n    >>> _preprocess(eq, f(x), hint=None)\n    (Derivative(f(x) + 1, x) + Derivative(f(x), y), f(x))\n\n    If it's not clear what the function of interest is, it must be given:\n\n    >>> eq = Derivative(f(x) + g(x), x)\n    >>> _preprocess(eq, g(x))\n    (Derivative(f(x), x) + Derivative(g(x), x), g(x))\n    >>> try: _preprocess(eq)\n    ... except ValueError: print(\"A ValueError was raised.\")\n    A ValueError was raised.\n\n    ",
            "n_words": 276,
            "vocab_size": 153,
            "n_whitespaces": 402,
            "language": "en"
        }
    },
    {
        "id": 266301,
        "commit_id": "80ced6b782e15179e7f35f0ef6737a65ddd60f92",
        "repo": "netbox",
        "path": "netbox/utilities/forms/forms.py",
        "file_name": "forms.py",
        "fun_name": "_clean_yaml",
        "commit_message": "Closes #11163: Auto-detect data format during bulk import",
        "code": "def _clean_yaml(self, data):\n        \n        records = []\n        try:\n            for data in yaml.load_all(data, Loader=yaml.SafeLoader):\n                if type(data) == list:\n                    records.extend(data)\n                elif type(data) == dict:\n                    records.append(data)\n                else:\n                    raise forms.ValidationError({\n                        self.data_field: _(\n                            \"Invalid YAML data. Data must be in the form of multiple documents, or a single document \"\n                            \"comprising a list of dictionaries.\"\n                        )\n                    })\n        except yaml.error.YAMLError as err:\n            raise forms.ValidationError({\n                self.data_field: f\"Invalid YAML data: {err}\"\n            })\n\n        return records\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 369,
        "n_words": 65,
        "vocab_size": 54,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 102,
        "n_ast_nodes": 174,
        "n_identifiers": 20,
        "d_id": 78362,
        "documentation": {
            "docstring": "\n        Clean YAML-formatted data. Data must be either\n          a) A single document comprising a list of dictionaries (each representing an object), or\n          b) Multiple documents, separated with the '---' token\n        ",
            "n_words": 29,
            "vocab_size": 29,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 246053,
        "commit_id": "18862f20b5495bdc556c54e92fd4b1efdc718ba7",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_requester_is_no_admin",
        "commit_message": "Remove the 'password_hash' from the Users Admin API endpoint response dictionary (#11576)",
        "code": "def test_requester_is_no_admin(self):\n        \n        url = self.url_prefix % \"@bob:test\"\n\n        channel = self.make_request(\n            \"GET\",\n            url,\n            access_token=self.other_user_token,\n        )\n\n        self.assertEqual(HTTPStatus.FORBIDDEN, channel.code, msg=channel.json_body)\n        self.assertEqual(\"You are not a server admin\", channel.json_body[\"error\"])\n\n        channel = self.make_request(\n            \"PUT\",\n            url,\n            access_token=self.other_user_token,\n            content=b\"{}\",\n        )\n\n        self.assertEqual(HTTPStatus.FORBIDDEN, channel.code, msg=channel.json_body)\n        self.assertEqual(\"You are not a server admin\", channel.json_body[\"error\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 189,
        "n_words": 42,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 114,
        "n_ast_nodes": 183,
        "n_identifiers": 15,
        "d_id": 70969,
        "documentation": {
            "docstring": "\n        If the user is not a server admin, an error is returned.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 261218,
        "commit_id": "537c325f2927895449ce418b3a77750135c0ba7b",
        "repo": "scikit-learn",
        "path": "sklearn/utils/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "axis0_safe_slice",
        "commit_message": "DOC Ensure that sklearn.utils.axis0_safe_slice passes numpydoc (#24561)",
        "code": "def axis0_safe_slice(X, mask, len_mask):\n    \n    if len_mask != 0:\n        return X[safe_mask(X, mask), :]\n    return np.zeros(shape=(0, X.shape[1]))\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 31,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 45,
        "n_ast_nodes": 68,
        "n_identifiers": 8,
        "d_id": 76691,
        "documentation": {
            "docstring": "Return a mask which is safer to use on X than safe_mask.\n\n    This mask is safer than safe_mask since it returns an\n    empty array, when a sparse matrix is sliced with a boolean mask\n    with all False, instead of raising an unhelpful error in older\n    versions of SciPy.\n\n    See: https://github.com/scipy/scipy/issues/5361\n\n    Also note that we can avoid doing the dot product by checking if\n    the len_mask is not zero in _huber_loss_and_gradient but this\n    is not going to be the bottleneck, since the number of outliers\n    and non_outliers are typically non-zero and it makes the code\n    tougher to follow.\n\n    Parameters\n    ----------\n    X : {array-like, sparse matrix}\n        Data on which to apply mask.\n\n    mask : ndarray\n        Mask to be used on X.\n\n    len_mask : int\n        The length of the mask.\n\n    Returns\n    -------\n    mask : ndarray\n        Array that is safe to use on X.\n    ",
            "n_words": 140,
            "vocab_size": 91,
            "n_whitespaces": 225,
            "language": "en"
        }
    },
    {
        "id": 780,
        "commit_id": "b61c1fc4b83fc740d3d9d0d84d0ca6022a3c49bb",
        "repo": "PySyft",
        "path": "packages/syft/tests/syft/core/io/location/specific_test.py",
        "file_name": "specific_test.py",
        "fun_name": "test_binary_serialization",
        "commit_message": "Refactored store interface to eliminate confusion with __getitem__\n\n- Fixed serde tests effected by protobuf magic bytes",
        "code": "def test_binary_serialization() -> None:\n    \n\n    uid = UID(value=uuid.UUID(int=333779996850170035686993356951732753684))\n    obj = SpecificLocation(id=uid, name=\"Test\")\n    assert sy.serialize(obj, to_bytes=True) == blob_bytes\n\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 78,
        "n_identifiers": 15,
        "d_id": 118,
        "documentation": {
            "docstring": "Tests that binary SpecificLocation serializes as expected",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 196400,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/matrices/repmatrix.py",
        "file_name": "repmatrix.py",
        "fun_name": "col_op",
        "commit_message": "Moved imports to higher level",
        "code": "def col_op(self, j, f):\n        \n        for i in range(self.rows):\n            self[i, j] = f(self[i, j], i)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 39,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 38,
        "n_ast_nodes": 56,
        "n_identifiers": 7,
        "d_id": 47900,
        "documentation": {
            "docstring": "In-place operation on col j using two-arg functor whose args are\n        interpreted as (self[i, j], i).\n\n        Examples\n        ========\n\n        >>> from sympy import eye\n        >>> M = eye(3)\n        >>> M.col_op(1, lambda v, i: v + 2*M[i, 0]); M\n        Matrix([\n        [1, 2, 0],\n        [0, 1, 0],\n        [0, 0, 1]])\n\n        See Also\n        ========\n        col\n        row_op\n        ",
            "n_words": 52,
            "vocab_size": 45,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 269566,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "update_sub",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def update_sub(x, decrement):\n    \n    return tf.compat.v1.assign_sub(x, decrement)\n\n\n@keras_export(\"keras.backend.moving_average_update\")\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.moving_average_update\")\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 12,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 51,
        "n_identifiers": 10,
        "d_id": 80190,
        "documentation": {
            "docstring": "Update the value of `x` by subtracting `decrement`.\n\n    Args:\n        x: A Variable.\n        decrement: A tensor of same shape as `x`.\n\n    Returns:\n        The variable `x` updated.\n    ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 271241,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/functional.py",
        "file_name": "functional.py",
        "fun_name": "_insert_layers",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _insert_layers(self, layers, relevant_nodes=None):\n        \n        layers = tf.nest.flatten(layers)\n        tf_utils.assert_no_legacy_layers(layers)\n        node_to_depth = {}\n        for depth, nodes in self._nodes_by_depth.items():\n            node_to_depth.update({node: depth for node in nodes})\n        # The nodes of these Layers that are relevant to this Network. If not\n        # provided, assume all Nodes are relevant\n        if not relevant_nodes:\n            relevant_nodes = tf.nest.flatten(\n                [layer._inbound_nodes for layer in layers]\n            )\n        network_nodes = set(relevant_nodes + list(node_to_depth.keys()))\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 171,
        "n_words": 60,
        "vocab_size": 48,
        "complexity": 11,
        "nloc": 44,
        "token_counts": 275,
        "n_ast_nodes": 155,
        "n_identifiers": 22,
        "d_id": 80733,
        "documentation": {
            "docstring": "Inserts Layers into the Network after Network creation.\n\n        This is only valid for Keras Graph Networks.  Layers added via this function\n        will be included in the `call` computation and `get_config` of this Network.\n        They will not be added to the Network's outputs.\n\n        Args:\n          layers: Arbitrary nested structure of Layers. Layers must be reachable\n            from one or more of the `keras.Input` Tensors that correspond to this\n            Network's inputs.\n          relevant_nodes: Nodes from the Layers that should be considered part of\n            this Network. If `None`, all Nodes will be considered part of this\n            Network.\n\n        Raises:\n          ValueError: If the layers depend on `Input`s not found in this Model.\n        ",
            "n_words": 104,
            "vocab_size": 67,
            "n_whitespaces": 218,
            "language": "en"
        }
    },
    {
        "id": 56283,
        "commit_id": "5afded9fe6724d9e336f59792ee1d60656a2d94d",
        "repo": "prefect",
        "path": "tests/cli/test_deployment_preview.py",
        "file_name": "test_deployment_preview.py",
        "fun_name": "test_previewing_multiple_kubernetes_deployments_from_python",
        "commit_message": "Add a CLI command to preview how a FlowRun will appear in any FlowRunner's execution environment (PrefectHQ/orion#1971)\n\nCo-authored-by: Terrence Dorsey <terrence@prefect.io>\r\nCo-authored-by: Michael Adkins <madkinszane@gmail.com>",
        "code": "def test_previewing_multiple_kubernetes_deployments_from_python():\n    \n\n    result = invoke_and_assert(\n        [\n            \"deployment\",\n            \"preview\",\n            \"./tests/deployment_test_files/multiple_kubernetes_deployments.py\",\n        ],\n        expected_output_contains=\"kind: Job\",\n    )\n    assert result.stdout.endswith(\"\\n\")\n\n    previews = [p.strip() for p in re.split(\"Preview for .+:\", result.stdout) if p]\n    assert len(previews) == 4  # there should be 3 K8s and 1 non-K8s in the file\n\n    # spot-check a few attributes of the first one\n    manifest = yaml.load(previews[0], yaml.SafeLoader)\n    assert manifest[\"apiVersion\"] == \"batch/v1\"\n    assert manifest[\"kind\"] == \"Job\"\n    assert manifest[\"metadata\"][\"generateName\"] == \"cool-name\"\n\n    container = manifest[\"spec\"][\"template\"][\"spec\"][\"containers\"][0]\n    assert \"PREFECT_TEST_MODE\" in [variable[\"name\"] for variable in container[\"env\"]]\n\n    # spot-check a few attributes of the third one, which is customized\n    manifest = yaml.load(previews[2], yaml.SafeLoader)\n    assert manifest[\"apiVersion\"] == \"batch/v1\"\n    assert manifest[\"kind\"] == \"Job\"\n    assert manifest[\"metadata\"][\"generateName\"] == \"cool-name\"\n\n    container = manifest[\"spec\"][\"template\"][\"spec\"][\"containers\"][0]\n    assert \"MY_ENV_VAR\" in [variable[\"name\"] for variable in container[\"env\"]]\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 233,
        "n_words": 118,
        "vocab_size": 68,
        "complexity": 5,
        "nloc": 24,
        "token_counts": 209,
        "n_ast_nodes": 375,
        "n_identifiers": 18,
        "d_id": 11494,
        "documentation": {
            "docstring": "`prefect deployment preview my-flow-file.py` should render multiple\n    Kubernetes Jobs from a deployment file",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 157475,
        "commit_id": "ca86da3a30c4e080d4db8c25fca73de843663cb4",
        "repo": "stablediffusion",
        "path": "ldm/modules/ema.py",
        "file_name": "ema.py",
        "fun_name": "restore",
        "commit_message": "release more models",
        "code": "def restore(self, parameters):\n        \n        for c_param, param in zip(self.collected_params, parameters):\n            param.data.copy_(c_param.data)\n",
        "url": "https://github.com/Stability-AI/stablediffusion.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 32,
        "n_ast_nodes": 51,
        "n_identifiers": 9,
        "d_id": 36941,
        "documentation": {
            "docstring": "\n        Restore the parameters stored with the `store` method.\n        Useful to validate the model with EMA parameters without affecting the\n        original optimization process. Store the parameters before the\n        `copy_to` method. After validation (or model saving), use this to\n        restore the former parameters.\n        Args:\n          parameters: Iterable of `torch.nn.Parameter`; the parameters to be\n            updated with the stored parameters.\n        ",
            "n_words": 55,
            "vocab_size": 36,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 261292,
        "commit_id": "e41753ebd57c44ae91b389f190c43ddc0b384a75",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/tests/test_least_angle.py",
        "file_name": "test_least_angle.py",
        "fun_name": "test_lassolarsic_alpha_selection",
        "commit_message": "MAINT Clean deprecation for 1.2: normalize in linear models (#24391)",
        "code": "def test_lassolarsic_alpha_selection(criterion):\n    \n    model = make_pipeline(StandardScaler(), LassoLarsIC(criterion=criterion))\n    model.fit(X, y)\n\n    best_alpha_selected = np.argmin(model[-1].criterion_)\n    assert best_alpha_selected == 7\n\n\n@pytest.mark.parametrize(\"fit_intercept\", [True, False])",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"fit_intercept\", [True, False])",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 101,
        "n_identifiers": 16,
        "d_id": 76733,
        "documentation": {
            "docstring": "Check that we properly compute the AIC and BIC score.\n\n    In this test, we reproduce the example of the Fig. 2 of Zou et al.\n    (reference [1] in LassoLarsIC) In this example, only 7 features should be\n    selected.\n    ",
            "n_words": 38,
            "vocab_size": 32,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 104415,
        "commit_id": "e35be138148333078284b942ccc9ed7b1d826f97",
        "repo": "datasets",
        "path": "src/datasets/table.py",
        "file_name": "table.py",
        "fun_name": "equals",
        "commit_message": "Update docs to new frontend/UI (#3690)\n\n* WIP: update docs to new UI\r\n\r\n* make style\r\n\r\n* Rm unused\r\n\r\n* inject_arrow_table_documentation __annotations__\r\n\r\n* hasattr(arrow_table_method, \"__annotations__\")\r\n\r\n* Update task_template.rst\r\n\r\n* Codeblock PT-TF-SPLIT\r\n\r\n* Convert loading scripts\r\n\r\n* Convert docs to mdx\r\n\r\n* Fix mdx\r\n\r\n* Add <Tip>\r\n\r\n* Convert mdx tables\r\n\r\n* Fix codeblock\r\n\r\n* Rm unneded hashlinks\r\n\r\n* Update index.mdx\r\n\r\n* Redo dev change\r\n\r\n* Rm circle ci `build_doc` & `deploy_doc`\r\n\r\n* Rm unneeded files\r\n\r\n* Update docs reamde\r\n\r\n* Standardize to `Example::`\r\n\r\n* mdx logging levels doc\r\n\r\n* Table properties inject_arrow_table_documentation\r\n\r\n* ``` to ```py mdx\r\n\r\n* Add Tips mdx\r\n\r\n* important,None -> <Tip warning={true}>\r\n\r\n* More misc\r\n\r\n* Center imgs\r\n\r\n* Update instllation page\r\n\r\n* `setup.py` docs section\r\n\r\n* Rm imgs since they are in hf.co\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* Update index mdx\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* just `Dataset` obj\r\n\r\n* Addedversion just italics\r\n\r\n* Update ReadInstruction doc example syntax\r\n\r\n* Change docstring for `prepare_for_task`\r\n\r\n* Chore\r\n\r\n* Remove `code` syntax from headings\r\n\r\n* Rm `code` syntax from headings\r\n\r\n* Hashlink backward compatability\r\n\r\n* S3FileSystem doc\r\n\r\n* S3FileSystem doc updates\r\n\r\n* index.mdx updates\r\n\r\n* Add darkmode gifs\r\n\r\n* Index logo img css classes\r\n\r\n* Index mdx dataset logo img size\r\n\r\n* Docs for DownloadMode class\r\n\r\n* Doc DownloadMode table\r\n\r\n* format docstrings\r\n\r\n* style\r\n\r\n* Add doc builder scripts (#3790)\r\n\r\n* add doc builder scripts\r\n\r\n* fix docker image\r\n\r\n* Docs new UI actions no self hosted (#3793)\r\n\r\n* No self hosted\r\n\r\n* replace doc injection by actual docstrings\r\n\r\n* Docstring formatted\r\n\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\n* Rm notebooks from docs actions since they dont exi\r\n\r\n* Update tsting branch\r\n\r\n* More docstring\r\n\r\n* Chore\r\n\r\n* bump up node version\r\n\r\n* bump up node\r\n\r\n* ``` -> ```py for audio_process.mdx\r\n\r\n* Update .github/workflows/build_documentation.yml\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\n\r\n* Uodate dev doc build\r\n\r\n* remove run on PR\r\n\r\n* fix action\r\n\r\n* Fix gh doc workflow\r\n\r\n* forgot this change when merging master\r\n\r\n* Update build doc\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>",
        "code": "def equals(self, *args, **kwargs):\n        \n        args = tuple(arg.table if isinstance(arg, Table) else arg for arg in args)\n        kwargs = {k: v.table if isinstance(v, Table) else v for k, v in kwargs}\n        return self.table.equals(*args, **kwargs)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 61,
        "n_words": 33,
        "vocab_size": 25,
        "complexity": 5,
        "nloc": 4,
        "token_counts": 70,
        "n_ast_nodes": 105,
        "n_identifiers": 11,
        "d_id": 21851,
        "documentation": {
            "docstring": "\n        Check if contents of two tables are equal.\n\n        Args:\n            other (:class:`datasets.table.Table`):\n                Table to compare against.\n            check_metadata (:obj:`bool`, defaults to :obj:`False`):\n                Whether schema metadata equality should be checked as well.\n\n        Returns:\n            :obj:`bool`\n        ",
            "n_words": 31,
            "vocab_size": 30,
            "n_whitespaces": 123,
            "language": "en"
        }
    },
    {
        "id": 21391,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py",
        "file_name": "tarfile.py",
        "fun_name": "makelink",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def makelink(self, tarinfo, targetpath):\n        \n        try:\n            # For systems that support symbolic and hard links.\n            if tarinfo.issym():\n                os.symlink(tarinfo.linkname, targetpath)\n            else:\n                # See extract().\n                if os.path.exists(tarinfo._link_target):\n                    os.link(tarinfo._link_target, targetpath)\n                else:\n                    self._extract_member(self._find_link_target(tarinfo),\n                                         targetpath)\n        except symlink_exception:\n            if tarinfo.issym():\n                linkpath = os.path.join(os.path.dirname(tarinfo.name),\n                                        tarinfo.linkname)\n            else:\n                linkpath = tarinfo.linkname\n        else:\n            try:\n                self._extract_member(self._find_link_target(tarinfo),\n                                     targetpath)\n            except KeyError:\n                raise ExtractError(\"unable to resolve link inside archive\")\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 432,
        "n_words": 54,
        "vocab_size": 39,
        "complexity": 6,
        "nloc": 22,
        "token_counts": 133,
        "n_ast_nodes": 219,
        "n_identifiers": 21,
        "d_id": 3804,
        "documentation": {
            "docstring": "Make a (symbolic) link called targetpath. If it cannot be created\n          (platform limitation), we try to make a copy of the referenced file\n          instead of a link.\n        ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 221364,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/codecs.py",
        "file_name": "codecs.py",
        "fun_name": "getincrementaldecoder",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getincrementaldecoder(encoding):\n\n    \n    decoder = lookup(encoding).incrementaldecoder\n    if decoder is None:\n        raise LookupError(encoding)\n    return decoder\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 32,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 56378,
        "documentation": {
            "docstring": " Lookup up the codec for the given encoding and return\n        its IncrementalDecoder class or factory function.\n\n        Raises a LookupError in case the encoding cannot be found\n        or the codecs doesn't provide an incremental decoder.\n\n    ",
            "n_words": 34,
            "vocab_size": 29,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 164583,
        "commit_id": "ee6b0a09fff7789879c3322edffe9f84d10acee3",
        "repo": "pandas",
        "path": "pandas/tests/reshape/concat/test_append_common.py",
        "file_name": "test_append_common.py",
        "fun_name": "_check_expected_dtype",
        "commit_message": "ENH: Index[bool] (#45061)",
        "code": "def _check_expected_dtype(self, obj, label):\n        \n        if isinstance(obj, Index):\n            assert obj.dtype == label\n        elif isinstance(obj, Series):\n            if label.startswith(\"period\"):\n                assert obj.dtype == \"Period[M]\"\n            else:\n                assert obj.dtype == label\n        else:\n            raise ValueError\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 130,
        "n_words": 28,
        "vocab_size": 18,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 58,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 39575,
        "documentation": {
            "docstring": "\n        Check whether obj has expected dtype depending on label\n        considering not-supported dtypes\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 206991,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_changelist/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_no_duplicates_for_m2m_in_list_filter",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_no_duplicates_for_m2m_in_list_filter(self):\n        \n        blues = Genre.objects.create(name=\"Blues\")\n        band = Band.objects.create(name=\"B.B. King Review\", nr_of_members=11)\n\n        band.genres.add(blues)\n        band.genres.add(blues)\n\n        m = BandAdmin(Band, custom_site)\n        request = self.factory.get(\"/band/\", data={\"genres\": blues.pk})\n        request.user = self.superuser\n\n        cl = m.get_changelist_instance(request)\n        cl.get_results(request)\n\n        # There's only one Group instance\n        self.assertEqual(cl.result_count, 1)\n        # Queryset must be deletable.\n        self.assertIs(cl.queryset.query.distinct, False)\n        cl.queryset.delete()\n        self.assertEqual(cl.queryset.count(), 0)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 159,
        "n_words": 47,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 144,
        "n_ast_nodes": 238,
        "n_identifiers": 33,
        "d_id": 51826,
        "documentation": {
            "docstring": "\n        Regression test for #13902: When using a ManyToMany in list_filter,\n        results shouldn't appear more than once. Basic ManyToMany.\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 189462,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/svg/svg_mobject.py",
        "file_name": "svg_mobject.py",
        "fun_name": "handle_transforms",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _handle_transforms(self, element, mobject):\n        \n\n        if element.hasAttribute(\"x\") and element.hasAttribute(\"y\"):\n            x = self._attribute_to_float(element.getAttribute(\"x\"))\n            # Flip y\n            y = -self._attribute_to_float(element.getAttribute(\"y\"))\n            mobject.shift(x * RIGHT + y * UP)\n\n        transform_attr_value = element.getAttribute(\"transform\")\n\n        # parse the various transforms in the attribute value\n        transform_names = [\"matrix\", \"translate\", \"scale\", \"rotate\", \"skewX\", \"skewY\"]\n\n        # Borrowed/Inspired from:\n        # https://github.com/cjlano/svg/blob/3ea3384457c9780fa7d67837c9c5fd4ebc42cb3b/svg/svg.py#L75\n\n        # match any SVG transformation with its parameter (until final parenthesis)\n        # [^)]*    == anything but a closing parenthesis\n        # '|'.join == OR-list of SVG transformations\n        transform_regex = \"|\".join([x + r\"[^)]*\\)\" for x in transform_names])\n        transforms = re.findall(transform_regex, transform_attr_value)\n\n        number_regex = r\"[-+]?(?:\\d+(?:\\.\\d*)?|\\.\\d+)(?:[eE][-+]?\\d+)?\"\n\n        for t in transforms:\n            op_name, op_args = t.split(\"(\")\n            op_name = op_name.strip()\n            op_args = [float(x) for x in re.findall(number_regex, op_args)]\n\n            if op_name == \"matrix\":\n                transform_args = np.array(op_args).reshape([3, 2])\n                x = transform_args[2][0]\n                y = -transform_args[2][1]\n                matrix = np.identity(self.dim)\n                matrix[:2, :2] = transform_args[:2, :]\n                matrix[1] *= -1\n                matrix[:, 1] *= -1\n\n                for mob in mobject.family_members_with_points():\n                    if config[\"renderer\"] == \"opengl\":\n                        mob.points = np.dot(mob.points, matrix)\n                    else:\n                        mob.points = np.dot(mob.points, matrix)\n                mobject.shift(x * RIGHT + y * UP)\n\n            elif op_name == \"scale\":\n                scale_values = op_args\n                if len(scale_values) == 2:\n                    scale_x, scale_y = scale_values\n                    mobject.scale(np.array([scale_x, scale_y, 1]), about_point=ORIGIN)\n                elif len(scale_values) == 1:\n                    scale = scale_values[0]\n                    mobject.scale(np.array([scale, scale, 1]), about_point=ORIGIN)\n\n            elif op_name == \"translate\":\n                if len(op_args) == 2:\n                    x, y = op_args\n                else:\n                    x = op_args\n                    y = 0\n                mobject.shift(x * RIGHT + y * DOWN)\n\n            else:\n                # TODO: handle rotate, skewX and skewY\n                # for now adding a warning message\n                logger.warning(\n                    \"Handling of %s transform is not supported yet!\",\n                    op_name,\n                )\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1007,
        "n_words": 245,
        "vocab_size": 143,
        "complexity": 14,
        "nloc": 48,
        "token_counts": 429,
        "n_ast_nodes": 706,
        "n_identifiers": 48,
        "d_id": 46070,
        "documentation": {
            "docstring": "Applies the SVG transform to the specified mobject. Transforms include:\n        ``matrix``, ``translate``, and ``scale``.\n\n        Parameters\n        ----------\n        element : :class:`minidom.Element`\n            The transform command to perform\n\n        mobject : :class:`Mobject`\n            The Mobject to transform.\n        ",
            "n_words": 31,
            "vocab_size": 25,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 181835,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/base.py",
        "file_name": "base.py",
        "fun_name": "fit_predict",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def fit_predict(self, features, target, sample_weight=None, groups=None):\n        \n        self.fit(features, target, sample_weight=sample_weight, groups=groups)\n\n        return self.predict(features)\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 41,
        "n_ast_nodes": 60,
        "n_identifiers": 8,
        "d_id": 43611,
        "documentation": {
            "docstring": "Call fit and predict in sequence.\n\n        Parameters\n        ----------\n        features: array-like {n_samples, n_features}\n            Feature matrix\n        target: array-like {n_samples}\n            List of class labels for prediction\n        sample_weight: array-like {n_samples}, optional\n            Per-sample weights. Higher weights force TPOT to put more emphasis on those points\n        groups: array-like, with shape {n_samples, }, optional\n            Group labels for the samples used when performing cross-validation.\n            This parameter should only be used in conjunction with sklearn's Group cross-validation\n            functions, such as sklearn.model_selection.GroupKFold\n\n        Returns\n        ----------\n        array-like: {n_samples}\n            Predicted target for the provided features\n\n        ",
            "n_words": 82,
            "vocab_size": 68,
            "n_whitespaces": 229,
            "language": "en"
        }
    },
    {
        "id": 308619,
        "commit_id": "0bcad5579b806284ae0c565bb27ca59ea061b4a1",
        "repo": "core",
        "path": "tests/components/nest/test_climate_sdm.py",
        "file_name": "test_climate_sdm.py",
        "fun_name": "test_thermostat_missing_set_point",
        "commit_message": "Set nest climate hvac_action to report idle when hvac mode is not off (#62811)",
        "code": "async def test_thermostat_missing_set_point(hass):\n    \n    await setup_climate(\n        hass,\n        {\n            \"sdm.devices.traits.ThermostatHvac\": {\"status\": \"OFF\"},\n            \"sdm.devices.traits.ThermostatMode\": {\n                \"availableModes\": [\"HEAT\", \"COOL\", \"HEATCOOL\", \"OFF\"],\n                \"mode\": \"HEATCOOL\",\n            },\n        },\n    )\n\n    assert len(hass.states.async_all()) == 1\n    thermostat = hass.states.get(\"climate.my_thermostat\")\n    assert thermostat is not None\n    assert thermostat.state == HVAC_MODE_HEAT_COOL\n    assert thermostat.attributes[ATTR_HVAC_ACTION] == CURRENT_HVAC_IDLE\n    assert thermostat.attributes[ATTR_CURRENT_TEMPERATURE] is None\n    assert set(thermostat.attributes[ATTR_HVAC_MODES]) == {\n        HVAC_MODE_HEAT,\n        HVAC_MODE_COOL,\n        HVAC_MODE_HEAT_COOL,\n        HVAC_MODE_OFF,\n    }\n    assert thermostat.attributes[ATTR_TEMPERATURE] is None\n    assert thermostat.attributes[ATTR_TARGET_TEMP_LOW] is None\n    assert thermostat.attributes[ATTR_TARGET_TEMP_HIGH] is None\n    assert ATTR_PRESET_MODE not in thermostat.attributes\n    assert ATTR_PRESET_MODES not in thermostat.attributes\n    assert ATTR_FAN_MODE not in thermostat.attributes\n    assert ATTR_FAN_MODES not in thermostat.attributes\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 253,
        "n_words": 87,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 30,
        "token_counts": 172,
        "n_ast_nodes": 275,
        "n_identifiers": 26,
        "d_id": 107367,
        "documentation": {
            "docstring": "Test a thermostat missing many thermostat traits in api response.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 217944,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/imaplib.py",
        "file_name": "imaplib.py",
        "fun_name": "setacl",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def setacl(self, mailbox, who, what):\n        \n        return self._simple_command('SETACL', mailbox, who, what)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 55029,
        "documentation": {
            "docstring": "Set a mailbox acl.\n\n        (typ, [data]) = <instance>.setacl(mailbox, who, what)\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 42078,
        "commit_id": "6460a21555ba6557e1f6f06f4d677d9c19148169",
        "repo": "seaborn",
        "path": "seaborn/utils.py",
        "file_name": "utils.py",
        "fun_name": "_disable_autolayout",
        "commit_message": "Workaround for matplotlib rc_context issue (#2925)\n\n* Workaround for matplotlib rc_context issue\r\n\r\nFixes #2914\r\n\r\n* Add some additional comments about this workaround",
        "code": "def _disable_autolayout():\n    \n    # This is a workaround for an issue in matplotlib, for details see\n    # https://github.com/mwaskom/seaborn/issues/2914\n    # The only affect of this rcParam is to set the default value for\n    # layout= in plt.figure, so we could just do that instead.\n    # But then we would need to own the complexity of the transition\n    # from tight_layout=True -> layout=\"tight\". This seems easier,\n    # but can be removed when (if) that is simpler on the matplotlib side,\n    # or if the layout algorithms are improved to handle figure legends.\n    orig_val = mpl.rcParams[\"figure.autolayout\"]\n    try:\n        mpl.rcParams[\"figure.autolayout\"] = False\n        yield\n    finally:\n        mpl.rcParams[\"figure.autolayout\"] = orig_val\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 158,
        "n_words": 101,
        "vocab_size": 74,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 34,
        "n_ast_nodes": 73,
        "n_identifiers": 4,
        "d_id": 7478,
        "documentation": {
            "docstring": "Context manager for preventing rc-controlled auto-layout behavior.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 101363,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "scripts/convert.py",
        "file_name": "convert.py",
        "fun_name": "_get_frame_ranges",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _get_frame_ranges(self) -> Optional[List[Tuple[int, int]]]:\n        \n        if not self._args.frame_ranges:\n            logger.debug(\"No frame range set\")\n            return None\n\n        minframe, maxframe = None, None\n        if self._images.is_video:\n            minframe, maxframe = 1, self._images.count\n        else:\n            indices = [int(self._imageidxre.findall(os.path.basename(filename))[0])\n                       for filename in self._images.file_list]\n            if indices:\n                minframe, maxframe = min(indices), max(indices)\n        logger.debug(\"minframe: %s, maxframe: %s\", minframe, maxframe)\n\n        if minframe is None or maxframe is None:\n            raise FaceswapError(\"Frame Ranges specified, but could not determine frame numbering \"\n                                \"from filenames\")\n\n        retval = []\n        for rng in self._args.frame_ranges:\n            if \"-\" not in rng:\n                raise FaceswapError(\"Frame Ranges not specified in the correct format\")\n            start, end = rng.split(\"-\")\n            retval.append((max(int(start), minframe), min(int(end), maxframe)))\n        logger.debug(\"frame ranges: %s\", retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 362,
        "n_words": 103,
        "vocab_size": 70,
        "complexity": 9,
        "nloc": 34,
        "token_counts": 206,
        "n_ast_nodes": 336,
        "n_identifiers": 32,
        "d_id": 20778,
        "documentation": {
            "docstring": " Obtain the frame ranges that are to be converted.\n\n        If frame ranges have been specified, then split the command line formatted arguments into\n        ranges that can be used.\n\n        Returns\n        list or ``None``\n            A list of  frames to be processed, or ``None`` if the command line argument was not\n            used\n        ",
            "n_words": 49,
            "vocab_size": 35,
            "n_whitespaces": 108,
            "language": "en"
        }
    },
    {
        "id": 32334,
        "commit_id": "99eb9b523f9b9ea6096323ce5610ce6633acc88a",
        "repo": "transformers",
        "path": "examples/pytorch/test_accelerate_examples.py",
        "file_name": "test_accelerate_examples.py",
        "fun_name": "test_run_translation_no_trainer",
        "commit_message": "Fix `no_trainer` CI (#18242)\n\n* Fix all tests",
        "code": "def test_run_translation_no_trainer(self):\n        tmp_dir = self.get_auto_remove_tmp_dir()\n        testargs = f.split()\n\n        run_command(self._launch_args + testargs)\n        result = get_results(tmp_dir)\n        self.assertGreaterEqual(result[\"eval_bleu\"], 30)\n        self.assertTrue(os.path.exists(os.path.join(tmp_dir, \"epoch_0\")))\n        self.assertTrue(os.path.exists(os.path.join(tmp_dir, \"translation_no_trainer\")))\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 68,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 89,
        "n_ast_nodes": 159,
        "n_identifiers": 17,
        "d_id": 5908,
        "documentation": {
            "docstring": "\n            {self.examples_dir}/pytorch/translation/run_translation_no_trainer.py\n            --model_name_or_path sshleifer/student_marian_en_ro_6_1\n            --source_lang en\n            --target_lang ro\n            --train_file tests/fixtures/tests_samples/wmt16/sample.json\n            --validation_file tests/fixtures/tests_samples/wmt16/sample.json\n            --output_dir {tmp_dir}\n            --max_train_steps=50\n            --num_warmup_steps=8\n            --learning_rate=3e-3\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --source_lang en_XX\n            --target_lang ro_RO\n            --checkpointing_steps epoch\n            --with_tracking\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 209,
            "language": "en"
        }
    },
    {
        "id": 322992,
        "commit_id": "93cae49c0c572b5c1ac972759140fbe924b0374d",
        "repo": "PaddleNLP",
        "path": "examples/model_interpretation/task/similarity/simnet/utils.py",
        "file_name": "utils.py",
        "fun_name": "convert_example",
        "commit_message": "Add NLP model interpretation (#1752)\n\n* upload NLP interpretation\r\n\r\n* fix problems and relocate project\r\n\r\n* remove abandoned picture\r\n\r\n* remove abandoned picture\r\n\r\n* fix dead link in README\r\n\r\n* fix dead link in README\r\n\r\n* fix code style problems\r\n\r\n* fix CR round 1\r\n\r\n* remove .gitkeep files\r\n\r\n* fix code style\r\n\r\n* fix file encoding problem\r\n\r\n* fix code style\r\n\r\n* delete duplicated files due to directory rebuild\r\n\r\n* fix CR round 2\r\n\r\n* fix code style\r\n\r\n* fix ernie tokenizer\r\n\r\n* fix code style\r\n\r\n* fix problem from CR round 1\r\n\r\n* fix bugs\r\n\r\n* fix README\r\n\r\n* remove duplicated files\r\n\r\n* deal with diff of old and new tokenizer results\r\n\r\n* fix CR round 4\r\n\r\n* fix code style\r\n\r\n* add missing dependence\r\n\r\n* fix broken import path\r\n\r\n* move some data file to cloud\r\n\r\n* MRC upper case to lower case\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>\r\nCo-authored-by: binlinquge <xxx>\r\nCo-authored-by: Guo Sheng <guosheng@baidu.com>",
        "code": "def convert_example(example, tokenizer, is_test=False, language='en'):\n    \n    if language == 'ch':\n        q_name = \"query\"\n        t_name = \"title\"\n        label = \"label\"\n    else:\n        q_name = \"sentence1\"\n        t_name = \"sentence2\"\n        label = \"labels\"\n\n    query, title = example[q_name], example[t_name]\n    query_ids = np.array(tokenizer.encode(query), dtype=\"int64\")\n    query_seq_len = np.array(len(query_ids), dtype=\"int64\")\n    title_ids = np.array(tokenizer.encode(title), dtype=\"int64\")\n    title_seq_len = np.array(len(title_ids), dtype=\"int64\")\n    result = [query_ids, title_ids, query_seq_len, title_seq_len]\n    if not is_test:\n        label = np.array(example[label], dtype=\"int64\")\n        result.append(label)\n    return result\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 154,
        "n_words": 65,
        "vocab_size": 43,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 156,
        "n_ast_nodes": 266,
        "n_identifiers": 21,
        "d_id": 118323,
        "documentation": {
            "docstring": "\n    Builds model inputs from a sequence for sequence classification tasks. \n    It use `jieba.cut` to tokenize text.\n\n    Args:\n        example(obj:`list[str]`): List of input data, containing text and label if it have label.\n        tokenizer(obj: paddlenlp.data.JiebaTokenizer): It use jieba to cut the chinese string.\n        is_test(obj:`False`, defaults to `False`): Whether the example contains label or not.\n\n    Returns:\n        query_ids(obj:`list[int]`): The list of query ids.\n        title_ids(obj:`list[int]`): The list of title ids.\n        query_seq_len(obj:`int`): The input sequence query length.\n        title_seq_len(obj:`int`): The input sequence title length.\n        label(obj:`numpy.array`, data type of int64, optional): The input label if not is_test.\n    ",
            "n_words": 88,
            "vocab_size": 62,
            "n_whitespaces": 161,
            "language": "en"
        }
    },
    {
        "id": 268291,
        "commit_id": "42d8a9daa89907545ebd208f4fd0a9192738c6a6",
        "repo": "ansible",
        "path": "lib/ansible/plugins/strategy/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_load_included_file",
        "commit_message": "Prevent double failing hosts for includes in loops (#76928)\n\nFixes #23161",
        "code": "def _load_included_file(self, included_file, iterator, is_handler=False):\n        \n        display.debug(\"loading included file: %s\" % included_file._filename)\n        try:\n            data = self._loader.load_from_file(included_file._filename)\n            if data is None:\n                return []\n            elif not isinstance(data, list):\n                raise AnsibleError(\"included task files must contain a list of tasks\")\n\n            ti_copy = self._copy_included_file(included_file)\n\n            block_list = load_list_of_blocks(\n                data,\n                play=iterator._play,\n                parent_block=ti_copy.build_parent_block(),\n                role=included_file._task._role,\n                use_handlers=is_handler,\n                loader=self._loader,\n                variable_manager=self._variable_manager,\n            )\n\n            # since we skip incrementing the stats when the task result is\n            # first processed, we do so now for each host in the list\n            for host in included_file._hosts:\n                self._tqm._stats.increment('ok', host.name)\n        except AnsibleParserError:\n            raise\n        except AnsibleError as e:\n            if isinstance(e, AnsibleFileNotFound):\n                reason = \"Could not find or access '%s' on the Ansible Controller.\" % to_text(e.file_name)\n            else:\n                reason = to_text(e)\n\n            for r in included_file._results:\n                r._result['failed'] = True\n\n            for host in included_file._hosts:\n                tr = TaskResult(host=host, task=included_file._task, return_data=dict(failed=True, reason=reason))\n                self._tqm._stats.increment('failures', host.name)\n                self._tqm.send_callback('v2_runner_on_failed', tr)\n            raise AnsibleError(reason) from e\n\n        # finally, send the callback and return the list of blocks loaded\n        self._tqm.send_callback('v2_playbook_on_include', included_file)\n        display.debug(\"done processing included file\")\n        return block_list\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 621,
        "n_words": 153,
        "vocab_size": 112,
        "complexity": 9,
        "nloc": 37,
        "token_counts": 267,
        "n_ast_nodes": 427,
        "n_identifiers": 51,
        "d_id": 79472,
        "documentation": {
            "docstring": "\n        Loads an included YAML file of tasks, applying the optional set of variables.\n\n        Raises AnsibleError exception in case of a failure during including a file,\n        in such case the caller is responsible for marking the host(s) as failed\n        using PlayIterator.mark_host_failed().\n        ",
            "n_words": 40,
            "vocab_size": 33,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 207677,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_named_group_field_choices_change_list",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_named_group_field_choices_change_list(self):\n        \n        link1 = reverse(\"admin:admin_views_fabric_change\", args=(self.fab1.pk,))\n        link2 = reverse(\"admin:admin_views_fabric_change\", args=(self.fab2.pk,))\n        response = self.client.get(reverse(\"admin:admin_views_fabric_changelist\"))\n        fail_msg = (\n            \"Changelist table isn't showing the right human-readable values \"\n            \"set by a model field 'choices' option named group.\"\n        )\n        self.assertContains(\n            response,\n            '<a href=\"%s\">Horizontal</a>' % link1,\n            msg_prefix=fail_msg,\n            html=True,\n        )\n        self.assertContains(\n            response,\n            '<a href=\"%s\">Vertical</a>' % link2,\n            msg_prefix=fail_msg,\n            html=True,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 233,
        "n_words": 53,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 97,
        "n_ast_nodes": 160,
        "n_identifiers": 16,
        "d_id": 52047,
        "documentation": {
            "docstring": "\n        Ensures the admin changelist shows correct values in the relevant column\n        for rows corresponding to instances of a model in which a named group\n        has been used in the choices option of a field.\n        ",
            "n_words": 34,
            "vocab_size": 27,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 48735,
        "commit_id": "48a21aa0eb3a95d32456c2a927eff9552a04231e",
        "repo": "django-rest-framework",
        "path": "tests/test_routers.py",
        "file_name": "test_routers.py",
        "fun_name": "test_nonconflicting_mixed_basenames",
        "commit_message": "raise ImproperlyConfigured exception if `basename` is not unique (#8438)\n\n* raise ImproperlyConfigured if basename already exists\r\n\r\n* rename already_registered function; return True/False\r\n\r\n* additional basename tests\r\n\r\n* additional basename tests\r\n\r\n* Update rest_framework/routers.py\r\n\r\nCo-authored-by: David Graves <dgraves@lrtcapitalgroup.com>\r\nCo-authored-by: Asif Saif Uddin <auvipy@gmail.com>",
        "code": "def test_nonconflicting_mixed_basenames(self):\n        \n        self.router.register(r'notes', NoteViewSet)\n        self.router.register(r'notes_kwduplicate', KWargedNoteViewSet, basename='routertestmodel_kwduplicate')\n        self.router.register(r'notes_duplicate', NoteViewSet, basename='routertestmodel_duplicate')\n",
        "url": "https://github.com/encode/django-rest-framework.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 38,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 47,
        "n_ast_nodes": 78,
        "n_identifiers": 7,
        "d_id": 9586,
        "documentation": {
            "docstring": "\n        Ensure 2 routers with the same model, and a distinct basename\n        specified on the second router does not fail\n        ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 60859,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/models/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "find_most_preferred_tag",
        "commit_message": "upd; format",
        "code": "def find_most_preferred_tag(self, tags, tag_to_priority):\n        # type: (List[Tag], Dict[Tag, int]) -> int\n        \n        return min(\n            tag_to_priority[tag] for tag in self.file_tags if tag in tag_to_priority\n        )\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 62,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 28,
        "n_ast_nodes": 44,
        "n_identifiers": 7,
        "d_id": 12306,
        "documentation": {
            "docstring": "Return the priority of the most preferred tag that one of the wheel's file\n        tag combinations acheives in the given list of supported tags using the given\n        tag_to_priority mapping, where lower priorities are more-preferred.\n\n        This is used in place of support_index_min in some cases in order to avoid\n        an expensive linear scan of a large list of tags.\n\n        :param tags: the PEP 425 tags to check the wheel against.\n        :param tag_to_priority: a mapping from tag to priority of that tag, where\n            lower is more preferred.\n\n        :raises ValueError: If none of the wheel's file tags match one of\n            the supported tags.\n        ",
            "n_words": 100,
            "vocab_size": 61,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 268984,
        "commit_id": "01c906c4178db5ae03b7eb2d298a052c952a0667",
        "repo": "keras",
        "path": "keras/saving/saved_model/load.py",
        "file_name": "load.py",
        "fun_name": "_finalize_config_layers",
        "commit_message": "Reorganize RNN layers, cells and wrappers into smaller logically organized files hosted under an `rnn` directory.\n\nPiperOrigin-RevId: 428841673",
        "code": "def _finalize_config_layers(layers):\n  \n  for layer in layers:\n    # It is assumed that layers define their unconditional losses after being\n    # recreated from the config and built. The exceptions to this\n    # are Functional and Sequential models, which only store conditional losses\n    # (losses dependent on the inputs) in the config. Unconditional losses like\n    # weight regularization must be revived from the SavedModel.\n    if _is_graph_network(layer):\n      _restore_layer_unconditional_losses(layer)\n\n    # Some layers, like Dense, record their activation loss function in the\n    # config. However, not all layers do this, so the activation loss may be\n    # missing when restored from the config/hdf5.\n    # TODO(kathywu): Investigate ways to improve the config to ensure consistent\n    # loading behavior between HDF5 and SavedModel.\n    _restore_layer_activation_loss(layer)\n\n    # Restore metrics list.\n    _restore_layer_metrics(layer)\n\n    # Restore RNN layer states.\n    if (isinstance(layer, base_rnn.RNN) and\n        layer.stateful and\n        hasattr(_get_keras_attr(layer), 'states')):\n      layer.states = getattr(_get_keras_attr(layer), 'states', None)\n      for variable in tf.nest.flatten(layer.states):\n        backend.track_variable(variable)\n\n    # Perform any layer defined finalization of the layer state.\n    layer.finalize_state()\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 247,
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        "vocab_size": 107,
        "complexity": 7,
        "nloc": 13,
        "token_counts": 95,
        "n_ast_nodes": 169,
        "n_identifiers": 22,
        "d_id": 79804,
        "documentation": {
            "docstring": "Runs the final steps of loading Keras Layers from config.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 176447,
        "commit_id": "cc1db275efc709cb964ce88abbfa877798d58c10",
        "repo": "networkx",
        "path": "networkx/algorithms/approximation/connectivity.py",
        "file_name": "connectivity.py",
        "fun_name": "local_node_connectivity",
        "commit_message": "Minor improvements from general code readthrough (#5414)\n\n* Add deprecated directive to reversed docstring.\r\n\r\n* Add missing dep directives to shpfiles.\r\n\r\n* Remove defn of INF sentinel.\r\n\r\n* typo.\r\n\r\n* str -> comment in forloop.\r\n\r\n* STY: appropriate casing for var name.",
        "code": "def local_node_connectivity(G, source, target, cutoff=None):\n    \n    if target == source:\n        raise nx.NetworkXError(\"source and target have to be different nodes.\")\n\n    # Maximum possible node independent paths\n    if G.is_directed():\n        possible = min(G.out_degree(source), G.in_degree(target))\n    else:\n        possible = min(G.degree(source), G.degree(target))\n\n    K = 0\n    if not possible:\n        return K\n\n    if cutoff is None:\n        cutoff = float(\"inf\")\n\n    exclude = set()\n    for i in range(min(possible, cutoff)):\n        try:\n            path = _bidirectional_shortest_path(G, source, target, exclude)\n            exclude.update(set(path))\n            K += 1\n        except nx.NetworkXNoPath:\n            break\n\n    return K\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 200,
        "n_words": 74,
        "vocab_size": 56,
        "complexity": 7,
        "nloc": 21,
        "token_counts": 143,
        "n_ast_nodes": 232,
        "n_identifiers": 23,
        "d_id": 41908,
        "documentation": {
            "docstring": "Compute node connectivity between source and target.\n\n    Pairwise or local node connectivity between two distinct and nonadjacent\n    nodes is the minimum number of nodes that must be removed (minimum\n    separating cutset) to disconnect them. By Menger's theorem, this is equal\n    to the number of node independent paths (paths that share no nodes other\n    than source and target). Which is what we compute in this function.\n\n    This algorithm is a fast approximation that gives an strict lower\n    bound on the actual number of node independent paths between two nodes [1]_.\n    It works for both directed and undirected graphs.\n\n    Parameters\n    ----------\n\n    G : NetworkX graph\n\n    source : node\n        Starting node for node connectivity\n\n    target : node\n        Ending node for node connectivity\n\n    cutoff : integer\n        Maximum node connectivity to consider. If None, the minimum degree\n        of source or target is used as a cutoff. Default value None.\n\n    Returns\n    -------\n    k: integer\n       pairwise node connectivity\n\n    Examples\n    --------\n    >>> # Platonic octahedral graph has node connectivity 4\n    >>> # for each non adjacent node pair\n    >>> from networkx.algorithms import approximation as approx\n    >>> G = nx.octahedral_graph()\n    >>> approx.local_node_connectivity(G, 0, 5)\n    4\n\n    Notes\n    -----\n    This algorithm [1]_ finds node independents paths between two nodes by\n    computing their shortest path using BFS, marking the nodes of the path\n    found as 'used' and then searching other shortest paths excluding the\n    nodes marked as used until no more paths exist. It is not exact because\n    a shortest path could use nodes that, if the path were longer, may belong\n    to two different node independent paths. Thus it only guarantees an\n    strict lower bound on node connectivity.\n\n    Note that the authors propose a further refinement, losing accuracy and\n    gaining speed, which is not implemented yet.\n\n    See also\n    --------\n    all_pairs_node_connectivity\n    node_connectivity\n\n    References\n    ----------\n    .. [1] White, Douglas R., and Mark Newman. 2001 A Fast Algorithm for\n        Node-Independent Paths. Santa Fe Institute Working Paper #01-07-035\n        http://eclectic.ss.uci.edu/~drwhite/working.pdf\n\n    ",
            "n_words": 314,
            "vocab_size": 192,
            "n_whitespaces": 494,
            "language": "en"
        }
    },
    {
        "id": 212886,
        "commit_id": "935e430420f5ac18df67233040ba86359d98a579",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "easy_print",
        "commit_message": "Addition of blocking parameter to debug printing.  IF True, then execution of your code is stopped until the \"Quit\" button / \"X\" is clicked on the Debug Window.",
        "code": "def easy_print(*args, size=(None, None), end=None, sep=None, location=(None, None), relative_location=(None, None), font=None, no_titlebar=False,\n               no_button=False, grab_anywhere=False, keep_on_top=None, do_not_reroute_stdout=True, echo_stdout=False, text_color=None, background_color=None, colors=None, c=None,\n               erase_all=False, resizable=True, blocking=None):\n    \n    if _DebugWin.debug_window is None:\n        _DebugWin.debug_window = _DebugWin(size=size, location=location, relative_location=relative_location, font=font, no_titlebar=no_titlebar,\n                                           no_button=no_button, grab_anywhere=grab_anywhere, keep_on_top=keep_on_top,\n                                           do_not_reroute_stdout=do_not_reroute_stdout, echo_stdout=echo_stdout, resizable=resizable, blocking=blocking)\n    txt_color, bg_color = _parse_colors_parm(c or colors)\n    _DebugWin.debug_window.Print(*args, end=end, sep=sep, text_color=text_color or txt_color, background_color=background_color or bg_color,\n                                 erase_all=erase_all, font=font, blocking=blocking)\n\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 223,
        "n_words": 60,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 94,
        "n_ast_nodes": 279,
        "n_identifiers": 27,
        "d_id": 53492,
        "documentation": {
            "docstring": "\n    Works like a \"print\" statement but with windowing options.  Routes output to the \"Debug Window\"\n\n    In addition to the normal text and background colors, you can use a \"colors\" tuple/string\n    The \"colors\" or \"c\" parameter defines both the text and background in a single parm.\n    It can be a tuple or a single single. Both text and background colors need to be specified\n    colors -(str, str) or str.  A combined text/background color definition in a single parameter\n    c - (str, str) - Colors tuple has format (foreground, backgrouned)\n    c - str - can also be a string of the format \"foreground on background\"  (\"white on red\")\n\n    :param *args:                 stuff to output\n    :type *args:                  (Any)\n    :param size:                  (w,h) w=characters-wide, h=rows-high\n    :type size:                   (int, int)\n    :param end:                   end character\n    :type end:                    (str)\n    :param sep:                   separator character\n    :type sep:                    (str)\n    :param location:              Location of upper left corner of the window\n    :type location:               (int, int)\n    :param relative_location:     (x,y) location relative to the default location of the window, in pixels. Normally the window centers.  This location is relative to the location the window would be created. Note they can be negative.\n    :type relative_location:      (int, int)\n    :param font:                  specifies the  font family, size, etc. Tuple or Single string format 'name size styles'. Styles: italic * roman bold normal underline overstrike\n    :type font:                   (str or (str, int[, str]) or None)\n    :param no_titlebar:           If True no titlebar will be shown\n    :type no_titlebar:            (bool)\n    :param no_button:             don't show button\n    :type no_button:              (bool)\n    :param grab_anywhere:         If True: can grab anywhere to move the window (Default = False)\n    :type grab_anywhere:          (bool)\n    :param background_color:      color of background\n    :type background_color:       (str)\n    :param text_color:            color of the text\n    :type text_color:             (str)\n    :param keep_on_top:           If True the window will remain above all current windows\n    :type keep_on_top:            (bool)\n    :param location:              Location of upper left corner of the window\n    :type location:               (int, int)\n    :param do_not_reroute_stdout: do not reroute stdout and stderr. If False, both stdout and stderr will reroute to here\n    :type do_not_reroute_stdout:  (bool)\n    :param echo_stdout:           If True stdout is sent to both the console and the debug window\n    :type echo_stdout:            (bool)\n    :param colors:                Either a tuple or a string that has both the text and background colors\n    :type colors:                 (str) or (str, str)\n    :param c:                     Either a tuple or a string that has both the text and background colors\n    :type c:                      (str) or (str, str)\n    :param resizable:             if True, the user can resize the debug window. Default is True\n    :type resizable:              (bool)\n    :param erase_all:             If True when erase the output before printing\n    :type erase_all:              (bool)\n    :param blocking:              if True, makes the window block instead of returning immediately. The \"Quit\" button changers to \"More\"\n    :type blocking:               (bool | None)\n    :return:\n    :rtype:\n    ",
            "n_words": 444,
            "vocab_size": 200,
            "n_whitespaces": 1135,
            "language": "en"
        }
    },
    {
        "id": 264108,
        "commit_id": "f57e15ae14d2370cba7a14cfae97d2c29b5c8154",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/win32/versioninfo.py",
        "file_name": "versioninfo.py",
        "fun_name": "load_version_info_from_text_file",
        "commit_message": "building: EXE: load version info structure before comparing guts\n\nLoad the version information structure in `EXE` constructor, so that\nthe comparison against cached state is done with the structure instead\nof the filen name. This way, changing the contents of the version\ninformation file triggers rebuild of the EXE.\n\nSplit and clean-up related functions in the `utils.win32.versioninfo`\nmodule as well as in `pyi-grab_version` and `pyi-set_version`\nutility scripts.",
        "code": "def load_version_info_from_text_file(filename):\n    \n\n    # Read and parse the version file. It may have a byte order marker or encoding cookie - respect it if it does.\n    import PyInstaller.utils.misc as miscutils\n    with open(filename, 'rb') as fp:\n        text = miscutils.decode(fp.read())\n\n    # Deserialize via eval()\n    try:\n        info = eval(text)\n    except Exception as e:\n        raise ValueError(\"Failed to deserialize VSVersionInfo from text-based representation!\") from e\n\n    # Sanity check\n    assert isinstance(info, VSVersionInfo), \\\n        f\"Loaded incompatible structure type! Expected VSVersionInfo, got: {type(info)!r}\"\n\n    return info\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 134,
        "n_words": 76,
        "vocab_size": 68,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 69,
        "n_ast_nodes": 129,
        "n_identifiers": 19,
        "d_id": 77609,
        "documentation": {
            "docstring": "\n    Load the `VSVersionInfo` structure from its string-based (`VSVersionInfo.__str__`) serialization by reading the\n    text from the file and running it through `eval()`.\n    ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 250580,
        "commit_id": "ede269fce40ec4000a4717d5f5aec7835d9931c2",
        "repo": "mitmproxy",
        "path": "mitmproxy/flow.py",
        "file_name": "flow.py",
        "fun_name": "intercept",
        "commit_message": "Flow.intercept: use an Event instead of the reply system\n\nThis is patch 3/4 of the reply-ectomy.",
        "code": "def intercept(self):\n        \n        if self.intercepted:\n            return\n        self.intercepted = True\n        if self._resume_event is not None:\n            self._resume_event.clear()\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 64,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 32,
        "n_ast_nodes": 55,
        "n_identifiers": 5,
        "d_id": 73511,
        "documentation": {
            "docstring": "\n        Intercept this Flow. Processing will stop until resume is\n        called.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 145520,
        "commit_id": "6f68c74a5dbfbb936cb675781acb2a36eae10984",
        "repo": "ray",
        "path": "python/ray/_private/resource_spec.py",
        "file_name": "resource_spec.py",
        "fun_name": "_autodetect_num_gpus",
        "commit_message": "Use GPUtil for gpu detection when available (#18938)\n\nIn Envs with K8S and enabled SELinux there is a bug:\r\n\"/proc/nvidia/\" is not allowed to mount in container\r\nSo, i made a rework for GPU detection based on GPutil package.\r\n\r\n\r\n\r\n## Checks\r\n\r\n- [x] I've run `scripts/format.sh` to lint the changes in this PR.\r\n- [x] I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/\r\n- Testing Strategy\r\n   - [x] Release tests\r\n\r\nCo-authored-by: Mopga <a14415641@cab-wsm-0010669.sigma.sbrf.ru>\r\nCo-authored-by: Julius <juliustfrost@gmail.com>",
        "code": "def _autodetect_num_gpus():\n    \n    result = 0\n    if sys.platform.startswith(\"linux\"):\n        if importlib.util.find_spec(\"GPUtil\"):\n            gpu_list = GPUtil.getGPUs()\n            result = len(gpu_list)\n        else:\n            proc_gpus_path = \"/proc/driver/nvidia/gpus\"\n            if os.path.isdir(proc_gpus_path):\n                result = len(os.listdir(proc_gpus_path))\n    elif sys.platform == \"win32\":\n        props = \"AdapterCompatibility\"\n        cmdargs = [\"WMIC\", \"PATH\", \"Win32_VideoController\", \"GET\", props]\n        lines = subprocess.check_output(cmdargs).splitlines()[1:]\n        result = len([x.rstrip() for x in lines if x.startswith(b\"NVIDIA\")])\n    return result\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 168,
        "n_words": 52,
        "vocab_size": 36,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 132,
        "n_ast_nodes": 231,
        "n_identifiers": 25,
        "d_id": 33474,
        "documentation": {
            "docstring": "Attempt to detect the number of GPUs on this machine.\n\n    TODO(rkn): This currently assumes NVIDIA GPUs on Linux.\n    TODO(mehrdadn): Use a better mechanism for Windows.\n\n    Returns:\n        The number of GPUs if any were detected, otherwise 0.\n    ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 64391,
        "commit_id": "0ca58d762715fd10c751c4497f3037908f4dfb20",
        "repo": "erpnext",
        "path": "erpnext/patches/v14_0/set_work_order_qty_in_so_from_mr.py",
        "file_name": "set_work_order_qty_in_so_from_mr.py",
        "fun_name": "execute",
        "commit_message": "chore: Patch to update SO work_order_qty and Linter fix",
        "code": "def execute():\n    \n    work_order = frappe.qb.DocType(\"Work Order\")\n    query = (\n        frappe.qb.from_(work_order)\n        .select(\n            work_order.name, work_order.produced_qty,\n            work_order.material_request,\n            work_order.material_request_item,\n            work_order.sales_order\n        ).where(\n            (work_order.material_request.isnotnull())\n            & (work_order.material_request_item.isnotnull())\n            & (work_order.sales_order.isnotnull())\n            & (work_order.docstatus == 1)\n            & (work_order.produced_qty > 0)\n        )\n    )\n    results = query.run(as_dict=True)\n\n    for row in results:\n        so_item = frappe.get_value(\n            \"Material Request Item\", row.material_request_item, \"sales_order_item\"\n        )\n        frappe.db.set_value(\"Work Order\", row.name, \"sales_order_item\", so_item)\n\n        if so_item:\n            wo = frappe.get_doc(\"Work Order\", row.name)\n            wo.update_work_order_qty_in_so()\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 267,
        "n_words": 61,
        "vocab_size": 51,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 164,
        "n_ast_nodes": 264,
        "n_identifiers": 27,
        "d_id": 13623,
        "documentation": {
            "docstring": "\n    1. Get submitted Work Orders with MR, MR Item and SO set\n    2. Get SO Item detail from MR Item detail in WO, and set in WO\n    3. Update work_order_qty in SO\n    ",
            "n_words": 32,
            "vocab_size": 21,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 110170,
        "commit_id": "8ef4e017f8a95db8704728a5fffd2c0384afc525",
        "repo": "matplotlib",
        "path": "lib/matplotlib/offsetbox.py",
        "file_name": "offsetbox.py",
        "fun_name": "_get_packed_offsets",
        "commit_message": "Don't pass unused xdescent to _get_packed_offsets.\n\nInstead of passing a list of (widths, xdescents) where xdescent is\nunused, just pass a list of widths.  This helper is private so we just\nneed to adjust the call sites and tests with no deprecation.\n\nThis patch is preliminary work for some further cleanup on the offsetbox\nmodule.",
        "code": "def _get_packed_offsets(widths, total, sep, mode=\"fixed\"):\n    r\n    _api.check_in_list([\"fixed\", \"expand\", \"equal\"], mode=mode)\n\n    if mode == \"fixed\":\n        offsets_ = np.cumsum([0] + [w + sep for w in widths])\n        offsets = offsets_[:-1]\n        if total is None:\n            total = offsets_[-1] - sep\n        return total, offsets\n\n    elif mode == \"expand\":\n        # This is a bit of a hack to avoid a TypeError when *total*\n        # is None and used in conjugation with tight layout.\n        if total is None:\n            total = 1\n        if len(widths) > 1:\n            sep = (total - sum(widths)) / (len(widths) - 1)\n        else:\n            sep = 0\n        offsets_ = np.cumsum([0] + [w + sep for w in widths])\n        offsets = offsets_[:-1]\n        return total, offsets\n\n    elif mode == \"equal\":\n        maxh = max(widths)\n        if total is None:\n            if sep is None:\n                raise ValueError(\"total and sep cannot both be None when \"\n                                 \"using layout mode 'equal'\")\n            total = (maxh + sep) * len(widths)\n        else:\n            sep = total / len(widths) - maxh\n        offsets = (maxh + sep) * np.arange(len(widths))\n        return total, offsets\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 420,
        "n_words": 163,
        "vocab_size": 79,
        "complexity": 11,
        "nloc": 74,
        "token_counts": 231,
        "n_ast_nodes": 381,
        "n_identifiers": 18,
        "d_id": 23960,
        "documentation": {
            "docstring": "\n    Pack boxes specified by their *widths*.\n\n    For simplicity of the description, the terminology used here assumes a\n    horizontal layout, but the function works equally for a vertical layout.\n\n    There are three packing *mode*\\s:\n\n    - 'fixed': The elements are packed tight to the left with a spacing of\n      *sep* in between. If *total* is *None* the returned total will be the\n      right edge of the last box. A non-*None* total will be passed unchecked\n      to the output. In particular this means that right edge of the last\n      box may be further to the right than the returned total.\n\n    - 'expand': Distribute the boxes with equal spacing so that the left edge\n      of the first box is at 0, and the right edge of the last box is at\n      *total*. The parameter *sep* is ignored in this mode. A total of *None*\n      is accepted and considered equal to 1. The total is returned unchanged\n      (except for the conversion *None* to 1). If the total is smaller than\n      the sum of the widths, the laid out boxes will overlap.\n\n    - 'equal': If *total* is given, the total space is divided in N equal\n      ranges and each box is left-aligned within its subspace.\n      Otherwise (*total* is *None*), *sep* must be provided and each box is\n      left-aligned in its subspace of width ``(max(widths) + sep)``. The\n      total width is then calculated to be ``N * (max(widths) + sep)``.\n\n    Parameters\n    ----------\n    widths : list of float\n        Widths of boxes to be packed.\n    total : float or None\n        Intended total length. *None* if not used.\n    sep : float\n        Spacing between boxes.\n    mode : {'fixed', 'expand', 'equal'}\n        The packing mode.\n\n    Returns\n    -------\n    total : float\n        The total width needed to accommodate the laid out boxes.\n    offsets : array of float\n        The left offsets of the boxes.\n    ",
            "n_words": 298,
            "vocab_size": 150,
            "n_whitespaces": 460,
            "language": "en"
        }
    },
    {
        "id": 278305,
        "commit_id": "b0ffc0031e9c1964e7398ca47c6666bbfc0d5086",
        "repo": "keras",
        "path": "keras/saving/saved_model/load.py",
        "file_name": "load.py",
        "fun_name": "del_tracking",
        "commit_message": "resolve line-too-long in saving",
        "code": "def del_tracking(self):\n        \n        # Now that the node object has been fully loaded, and the checkpoint has\n        # been restored, the object no longer needs to track objects added from\n        # SerializedAttributes. (Note that saving a training checkpoint still\n        # functions correctly, because layers and variables are tracked\n        # separately by the Layer object.)\n        # TODO(kathywu): Instead of outright deleting these nodes (which would\n        # make restoring from a different checkpoint tricky), mark them as extra\n        # dependencies that are OK to overwrite.\n        for node in self.loaded_nodes.values():\n            node = node[0]\n            if not isinstance(node, base_layer.Layer):\n                # Loaded nodes can contain other trackable objects created when\n                # loading layers from the config, such as variables.\n                continue\n            for name in PUBLIC_ATTRIBUTES:\n                node._delete_tracking(name)  # pylint: disable=protected-access\n\n            if isinstance(node, functional_lib.Functional):\n                # Delete the temporary layer dependencies, which were used to\n                # restore the checkpointed values. When the model is live, the\n                # user can delete or add layers to the model at any time, so\n                # these layer dependencies may be obsolete.\n                dependencies = list(\n                    node._self_unconditional_dependency_names\n                )  # pylint: disable=protected-access\n                for name in dependencies:\n                    if (\n                        re.match(r\"^layer(_with_weights)?-[\\d+]\", name)\n                        is not None\n                    ):\n                        node._delete_tracking(\n                            name\n                        )  # pylint: disable=protected-access\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 650,
        "n_words": 192,
        "vocab_size": 122,
        "complexity": 7,
        "nloc": 19,
        "token_counts": 91,
        "n_ast_nodes": 161,
        "n_identifiers": 18,
        "d_id": 82463,
        "documentation": {
            "docstring": "Removes tracked references that are only used when loading the\n        model.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 166950,
        "commit_id": "89be1f053b695c4ce1c0569f737caf3f03c12128",
        "repo": "pandas",
        "path": "pandas/tests/arrays/floating/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "all_data",
        "commit_message": "DOC: Added docstrings to fixtures defined in array module (#47211)",
        "code": "def all_data(request, data, data_missing):\n    \n    if request.param == \"data\":\n        return data\n    elif request.param == \"data_missing\":\n        return data_missing\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 39,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 28,
        "n_ast_nodes": 49,
        "n_identifiers": 5,
        "d_id": 39882,
        "documentation": {
            "docstring": "Parametrized fixture returning 'data' or 'data_missing' float arrays.\n\n    Used to test dtype conversion with and without missing values.\n    ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 168829,
        "commit_id": "f77dbfb5af93faf9425c5d717a93ea7f6f26b3fd",
        "repo": "pandas",
        "path": "pandas/core/series.py",
        "file_name": "series.py",
        "fun_name": "iteritems",
        "commit_message": "DOC: Add deprecation marks to deprecated functions (#48183)\n\n* DOC: Add deprecation marks to deprecated functions\r\n\r\n* Address docs\r\n\r\n* docstrings",
        "code": "def iteritems(self) -> Iterable[tuple[Hashable, Any]]:\n        \n        warnings.warn(\n            \"iteritems is deprecated and will be removed in a future version. \"\n            \"Use .items instead.\",\n            FutureWarning,\n            stacklevel=find_stack_level(inspect.currentframe()),\n        )\n        return self.items()\n\n    # ----------------------------------------------------------------------\n    # Misc public methods\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 110,
        "n_words": 32,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 30,
        "token_counts": 43,
        "n_ast_nodes": 74,
        "n_identifiers": 14,
        "d_id": 40335,
        "documentation": {
            "docstring": "\n        Lazily iterate over (index, value) tuples.\n\n        .. deprecated:: 1.5.0\n            iteritems is deprecated and will be removed in a future version.\n            Use .items instead.\n\n        This method returns an iterable tuple (index, value). This is\n        convenient if you want to create a lazy iterator.\n\n        Returns\n        -------\n        iterable\n            Iterable of tuples containing the (index, value) pairs from a\n            Series.\n\n        See Also\n        --------\n        Series.items : Recommended alternative.\n        DataFrame.items : Iterate over (column name, Series) pairs.\n        DataFrame.iterrows : Iterate over DataFrame rows as (index, Series) pairs.\n        ",
            "n_words": 81,
            "vocab_size": 65,
            "n_whitespaces": 217,
            "language": "en"
        }
    },
    {
        "id": 132382,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_api.py",
        "file_name": "test_api.py",
        "fun_name": "checkAndReturnConsistentLogs",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def checkAndReturnConsistentLogs(self, results, sleep_per_iter=None):\n        \n        class_results = copy.deepcopy(results)\n        function_results = copy.deepcopy(results)\n\n        class_output = []\n        function_output = []\n        scheduler_notif = []\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 61,
        "n_words": 19,
        "vocab_size": 12,
        "complexity": 4,
        "nloc": 63,
        "token_counts": 306,
        "n_ast_nodes": 67,
        "n_identifiers": 11,
        "d_id": 29747,
        "documentation": {
            "docstring": "Checks logging is the same between APIs.\n\n        Ignore \"DONE\" for logging but checks that the\n        scheduler is notified properly with the last result.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 77078,
        "commit_id": "1822d7eee23cf5fceff8b1f58f3ca2f0a32c6e34",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_widgets.py",
        "file_name": "test_widgets.py",
        "fun_name": "test_tags_help_text_spaces_allowed",
        "commit_message": "display help text message for tag field\n\n- resolves #1874\n- ensure message is dynamic based on the setting TAG_SPACES_ALLOWED\n- Update wagtail/admin/templates/wagtailadmin/widgets/tag_widget.html",
        "code": "def test_tags_help_text_spaces_allowed(self):\n        \n        widget = widgets.AdminTagWidget()\n        help_text = widget.get_context(None, None, {})[\"widget\"][\"help_text\"]\n\n        html = widget.render(\"tags\", None, {})\n        help_text_html_element = self.get_help_text_html_element(html)\n\n        self.assertEqual(\n            help_text,\n            'Multi-word tags with spaces will automatically be enclosed in double quotes (\").',\n        )\n\n        self.assertHTMLEqual(\n            help_text_html_element,\n             % help_text,\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 146,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 73,
        "n_ast_nodes": 123,
        "n_identifiers": 13,
        "d_id": 16620,
        "documentation": {
            "docstring": "Checks that the tags help text html element content is correct when TAG_SPACES_ALLOWED is True<p class=\"help\">%s</p>",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 181840,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/base.py",
        "file_name": "base.py",
        "fun_name": "clean_pipeline_string",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def clean_pipeline_string(self, individual):\n        \n        dirty_string = str(individual)\n        # There are many parameter prefixes in the pipeline strings, used solely for\n        # making the terminal name unique, eg. LinearSVC__.\n        parameter_prefixes = [\n            (m.start(), m.end()) for m in re.finditer(\", [\\w]+__\", dirty_string)\n        ]\n        # We handle them in reverse so we do not mess up indices\n        pretty = dirty_string\n        for (start, end) in reversed(parameter_prefixes):\n            pretty = pretty[: start + 2] + pretty[end:]\n\n        return pretty\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 162,
        "n_words": 70,
        "vocab_size": 55,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 74,
        "n_ast_nodes": 120,
        "n_identifiers": 13,
        "d_id": 43614,
        "documentation": {
            "docstring": "Provide a string of the individual without the parameter prefixes.\n\n        Parameters\n        ----------\n        individual: individual\n            Individual which should be represented by a pretty string\n\n        Returns\n        -------\n        A string like str(individual), but with parameter prefixes removed.\n\n        ",
            "n_words": 34,
            "vocab_size": 28,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 301868,
        "commit_id": "62a5854e40cb554fecb1eec897d7bcb4c94628fe",
        "repo": "core",
        "path": "homeassistant/components/feedreader/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "put_timestamp",
        "commit_message": "Fix bare except (#72906)",
        "code": "def put_timestamp(self, feed_id, timestamp):\n        \n        self._fetch_data()\n        with self._lock, open(self._data_file, \"wb\") as myfile:\n            self._data.update({feed_id: timestamp})\n            _LOGGER.debug(\n                \"Overwriting feed %s timestamp in storage file %s\",\n                feed_id,\n                self._data_file,\n            )\n            try:\n                pickle.dump(self._data, myfile)\n            except Exception:  # pylint: disable=broad-except\n                _LOGGER.error(\"Error saving pickled data to %s\", self._data_file)\n        self._cache_outdated = True\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 202,
        "n_words": 43,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 86,
        "n_ast_nodes": 144,
        "n_identifiers": 18,
        "d_id": 100706,
        "documentation": {
            "docstring": "Update timestamp for given feed id (usually the url).",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 130998,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/serve/tests/test_deployment_state.py",
        "file_name": "test_deployment_state.py",
        "fun_name": "test_deploy_with_transient_constructor_failure",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_deploy_with_transient_constructor_failure(mock_deployment_state):\n    \n    deployment_state, timer, goal_manager = mock_deployment_state\n\n    b_info_1, b_version_1 = deployment_info(num_replicas=2)\n    create_goal, updating = deployment_state.deploy(b_info_1)\n    goal_obj = goal_manager.get_goal(create_goal)\n\n    # Burn 4 retries from both replicas.\n    deleted = _constructor_failure_loop_two_replica(deployment_state, 2)\n    assert not deleted\n\n    # Let both replicas succeed in last try.\n    deployment_state.update()\n    check_counts(deployment_state, total=2, by_state=[(ReplicaState.STARTING, 2)])\n\n    assert deployment_state._replica_constructor_retry_counter == 4\n    replica_1 = deployment_state._replicas.get()[0]\n    replica_2 = deployment_state._replicas.get()[1]\n\n    replica_1._actor.set_ready()\n    replica_2._actor.set_ready()\n    deployment_state.update()\n    check_counts(deployment_state, total=2, by_state=[(ReplicaState.RUNNING, 2)])\n\n    assert deployment_state._replica_constructor_retry_counter == 4\n    assert goal_manager.check_complete(create_goal)\n    assert goal_obj.exception is None\n\n\n@pytest.fixture",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 135,
        "n_words": 73,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 165,
        "n_ast_nodes": 268,
        "n_identifiers": 34,
        "d_id": 29444,
        "documentation": {
            "docstring": "\n    Test deploy() multiple replicas with transient constructor failure.\n    Ensures:\n        1) Async goal manager can correctly recognize deployment goal as\n            successful\n        2) There should be expected # of RUNNING replicas eventually that\n            matches user intent\n        3) Replica counter set as -1 to stop tracking current goal as it's\n            already completed\n\n    Same testing for same test case in test_deploy.py.\n    ",
            "n_words": 57,
            "vocab_size": 52,
            "n_whitespaces": 124,
            "language": "en"
        }
    },
    {
        "id": 101978,
        "commit_id": "2e8ef5e3c8f2df0f1cca9b342baa8aaa6f620650",
        "repo": "faceswap",
        "path": "lib/gui/utils/image.py",
        "file_name": "image.py",
        "fun_name": "image",
        "commit_message": "GUI - Preview updates\n  - Training preview. Embed preview pop-out window\n  - Bugfix - convert/extract previews",
        "code": "def image(self) -> ImageTk.PhotoImage:\n        \n        assert self._preview_image_tk is not None\n        return self._preview_image_tk\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 21352,
        "documentation": {
            "docstring": ":class:`PIL.ImageTk.PhotoImage` The preview image for displaying in a tkinter canvas ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 154556,
        "commit_id": "e5b1888cd932909e49194d58035da34b210b91c4",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "_join_by_index",
        "commit_message": "FEAT-#4946: Replace OmniSci with HDK (#4947)\n\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Andrey Pavlenko <andrey.a.pavlenko@gmail.com>",
        "code": "def _join_by_index(self, other_modin_frames, how, sort, ignore_index):\n        \n        if how == \"outer\":\n            raise NotImplementedError(\"outer join is not supported in HDK engine\")\n\n        lhs = self._maybe_materialize_rowid()\n        reset_index_names = False\n        for rhs in other_modin_frames:\n            rhs = rhs._maybe_materialize_rowid()\n            if len(lhs._index_cols) != len(rhs._index_cols):\n                raise NotImplementedError(\n                    \"join by indexes with different sizes is not supported\"\n                )\n\n            reset_index_names = reset_index_names or lhs._index_cols != rhs._index_cols\n\n            condition = lhs._build_equi_join_condition(\n                rhs, lhs._index_cols, rhs._index_cols\n            )\n\n            exprs = lhs._index_exprs()\n            new_columns = lhs.columns.to_list()\n            for col in lhs.columns:\n                exprs[col] = lhs.ref(col)\n            for col in rhs.columns:\n                # Handle duplicating column names here. When user specifies\n                # suffixes to make a join, actual renaming is done in front-end.\n                new_col_name = col\n                rename_idx = 0\n                while new_col_name in exprs:\n                    new_col_name = f\"{col}{rename_idx}\"\n                    rename_idx += 1\n                exprs[new_col_name] = rhs.ref(col)\n                new_columns.append(new_col_name)\n\n            op = JoinNode(\n                lhs,\n                rhs,\n                how=how,\n                exprs=exprs,\n                condition=condition,\n            )\n\n            new_columns = Index.__new__(\n                Index, data=new_columns, dtype=self.columns.dtype\n            )\n            lhs = lhs.__constructor__(\n                dtypes=lhs._dtypes_for_exprs(exprs),\n                columns=new_columns,\n                index_cols=lhs._index_cols,\n                op=op,\n                force_execution_mode=self._force_execution_mode,\n            )\n\n        if sort:\n            lhs = lhs.sort_rows(\n                lhs._index_cols,\n                ascending=True,\n                ignore_index=False,\n                na_position=\"last\",\n            )\n\n        if reset_index_names:\n            lhs = lhs._reset_index_names()\n\n        if ignore_index:\n            new_columns = Index.__new__(RangeIndex, data=range(len(lhs.columns)))\n            lhs = lhs._set_columns(new_columns)\n\n        return lhs\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 912,
        "n_words": 171,
        "vocab_size": 113,
        "complexity": 11,
        "nloc": 57,
        "token_counts": 315,
        "n_ast_nodes": 498,
        "n_identifiers": 44,
        "d_id": 36066,
        "documentation": {
            "docstring": "\n        Perform equi-join operation for multiple frames by index columns.\n\n        Parameters\n        ----------\n        other_modin_frames : list of HdkOnNativeDataframe\n            Frames to join with.\n        how : str\n            A type of join.\n        sort : bool\n            Sort the result by join keys.\n        ignore_index : bool\n            If True then reset column index for the resulting frame.\n\n        Returns\n        -------\n        HdkOnNativeDataframe\n            The new frame.\n        ",
            "n_words": 55,
            "vocab_size": 43,
            "n_whitespaces": 188,
            "language": "en"
        }
    },
    {
        "id": 106288,
        "commit_id": "92d73ef3936ed6de9770f613fddf2260731becc9",
        "repo": "youtube-dl",
        "path": "youtube_dl/downloader/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_get_suitable_downloader",
        "commit_message": "[niconico] Implement heartbeat for download",
        "code": "def _get_suitable_downloader(info_dict, params={}):\n    \n\n    # if (info_dict.get('start_time') or info_dict.get('end_time')) and not info_dict.get('requested_formats') and FFmpegFD.can_download(info_dict):\n    #     return FFmpegFD\n\n    external_downloader = params.get('external_downloader')\n    if external_downloader is not None:\n        ed = get_external_downloader(external_downloader)\n        if ed.can_download(info_dict):\n            return ed\n\n    protocol = info_dict['protocol']\n    if protocol.startswith('m3u8') and info_dict.get('is_live'):\n        return FFmpegFD\n\n    if protocol == 'm3u8' and params.get('hls_prefer_native') is True:\n        return HlsFD\n\n    if protocol == 'm3u8_native' and params.get('hls_prefer_native') is False:\n        return FFmpegFD\n\n    return PROTOCOL_MAP.get(protocol, HttpFD)\n\n\n__all__ = [\n    'get_suitable_downloader',\n    'FileDownloader',\n]\n",
        "url": "https://github.com/ytdl-org/youtube-dl.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 153,
        "n_words": 69,
        "vocab_size": 40,
        "complexity": 9,
        "nloc": 14,
        "token_counts": 105,
        "n_ast_nodes": 200,
        "n_identifiers": 15,
        "d_id": 22343,
        "documentation": {
            "docstring": "Get the downloader class that can handle the info dict.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 93148,
        "commit_id": "d3b8c9dd7bef6bccb5e70d2ccf3cda8463444a34",
        "repo": "sentry",
        "path": "tests/snuba/api/endpoints/test_organization_events_mep.py",
        "file_name": "test_organization_events_mep.py",
        "fun_name": "test_having_condition_with_preventing_aggregate_metrics_only",
        "commit_message": "chore(discover): Cleanup events tests (#36797)\n\n- Delete the deprecated eventsv2 tests\r\n- Move MEP tests to its own file",
        "code": "def test_having_condition_with_preventing_aggregate_metrics_only(self):\n        \n        response = self.do_request(\n            {\n                \"field\": [\"transaction\", \"project\", \"p50(transaction.duration)\"],\n                \"query\": \"event.type:transaction p50(transaction.duration):<50\",\n                \"dataset\": \"metrics\",\n                \"preventMetricAggregates\": \"1\",\n                \"per_page\": 50,\n                \"project\": self.project.id,\n            }\n        )\n        assert response.status_code == 400, response.content\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 168,
        "n_words": 28,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 59,
        "n_ast_nodes": 109,
        "n_identifiers": 8,
        "d_id": 18970,
        "documentation": {
            "docstring": "same as the previous test, but with the dataset on explicit metrics\n        which should throw a 400 error instead",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 185184,
        "commit_id": "3f0955cbe5405bdb3d1dda756ee3a1e000695dff",
        "repo": "textual",
        "path": "tests/test_xterm_parser.py",
        "file_name": "test_xterm_parser.py",
        "fun_name": "test_unknown_sequence_followed_by_known_sequence",
        "commit_message": "fix tests",
        "code": "def test_unknown_sequence_followed_by_known_sequence(parser, chunk_size):\n    \n    unknown_sequence = \"\\x1b[?\"\n    known_sequence = \"\\x1b[8~\"  # key = 'end'\n\n    sequence = unknown_sequence + known_sequence\n\n    events = []\n    parser.more_data = lambda: True\n    for chunk in chunks(sequence, chunk_size):\n        events.append(parser.feed(chunk))\n\n    events = list(itertools.chain.from_iterable(list(event) for event in events))\n\n    assert [event.key for event in events] == [\n        \"circumflex_accent\",\n        \"left_square_bracket\",\n        \"question_mark\",\n        \"end\",\n    ]\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 117,
        "n_words": 51,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 92,
        "n_ast_nodes": 156,
        "n_identifiers": 18,
        "d_id": 44934,
        "documentation": {
            "docstring": "When we feed the parser an unknown sequence followed by a known\n    sequence. The characters in the unknown sequence are delivered as keys,\n    and the known escape sequence that follows is delivered as expected.\n    ",
            "n_words": 34,
            "vocab_size": 26,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 82563,
        "commit_id": "b8750ebc0ebaa52ec51945f1d4824a80d806f479",
        "repo": "django-cms",
        "path": "cms/tests/test_toolbar.py",
        "file_name": "test_toolbar.py",
        "fun_name": "test_block_tag",
        "commit_message": "ci: sync isort line length (#7353)",
        "code": "def test_block_tag(self):\n        user = self.get_staff()\n        page = create_page('Test', 'col_two.html', 'en', published=True)\n        ex1 = Example1(\n            date_field=datetime.date(2012, 1, 1),\n            **FOUR_CHARS\n        )\n        ex1.save()\n\n        # This template does not render anything as content is saved in a\n        # variable and never inserted in the page\n        template_text = \n        request = self.get_page_request(page, user, edit=True)\n        response = detail_view(request, ex1.pk, template_string=template_text)\n        self.assertNotContains(\n            response,\n            '<template class=\"cms-plugin cms-plugin-start cms-plugin-{0}-{1}-{2} cms-render-model-icon\"></template>'\n            '<img src=\"/static/cms/img/toolbar/render_model_icon.png\">'\n            '<template class=\"cms-plugin cms-plugin-end cms-plugin-{0}-{1}-{2} cms-render-model-icon\">'\n            '</template>'.format(\n                'placeholderapp', 'example1', ex1.pk\n            )\n        )\n\n        # This template does not render anything as content is saved in a\n        # variable and inserted in the page afterwards\n        template_text = \n        request = self.get_page_request(page, user, edit=True)\n        response = detail_view(request, ex1.pk, template_string=template_text)\n        # Assertions on the content of the block tag\n        self.assertContains(\n            response,\n            '<template class=\"cms-plugin cms-plugin-start cms-plugin-{}-{}-{} '\n            'cms-render-model cms-render-model-block\">'.format(\n                'placeholderapp', 'example1', ex1.pk\n            )\n        )\n        self.assertContains(response, f'<h1>{ex1.char_1} - {ex1.char_2}</h1>')\n        self.assertContains(response, '<span class=\"date\">%s</span>' % (ex1.date_field.strftime(\"%Y\")))\n        self.assertContains(\n            response, '<a href=\"%s\">successful if</a>\\n    \\n<template' % (reverse('detail', args=(ex1.pk,)))\n        )\n\n        # This template is rendered directly\n        template_text = \n        request = self.get_page_request(page, user, edit=True)\n        response = detail_view(request, ex1.pk, template_string=template_text)\n        # Assertions on the content of the block tag\n        self.assertContains(\n            response,\n            '<template class=\"cms-plugin cms-plugin-start cms-plugin-{}-{}-{} cms-render-model '\n            'cms-render-model-block\">'.format(\n                'placeholderapp', 'example1', ex1.pk\n            )\n        )\n        self.assertContains(response, f'<h1>{ex1.char_1} - {ex1.char_2}</h1>')\n        self.assertContains(response, '<span class=\"date\">%s</span>' % (ex1.date_field.strftime(\"%Y\")))\n        self.assertContains(\n            response, '<a href=\"%s\">successful if</a>\\n    \\n<template' % (reverse('detail', args=(ex1.pk,)))\n        )\n\n        # Changelist check\n        template_text = \n        request = self.get_page_request(page, user, edit=True)\n        response = detail_view(request, ex1.pk, template_string=template_text)\n        # Assertions on the content of the block tag\n        self.assertContains(\n            response,\n            '<template class=\"cms-plugin cms-plugin-start cms-plugin-{}-{}-changelist-{} cms-render-model '\n            'cms-render-model-block\"></template>'.format(\n                'placeholderapp', 'example1', ex1.pk\n            )\n        )\n        self.assertContains(\n            response,\n            \"edit_plugin: '{}?language={}&amp;edit_fields=changelist'\".format(\n                admin_reverse('placeholderapp_example1_changelist'), 'en'\n            )\n        )\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 921,
        "n_words": 254,
        "vocab_size": 97,
        "complexity": 1,
        "nloc": 114,
        "token_counts": 379,
        "n_ast_nodes": 672,
        "n_identifiers": 31,
        "d_id": 17440,
        "documentation": {
            "docstring": "{% extends \"base.html\" %}\n{% load cms_tags %}\n\n{% block content %}\n{% render_model_block instance as rendered_model %}\n    {{ instance }}\n    <h1>{{ instance.char_1 }} - {{  instance.char_2 }}</h1>\n    {{ instance.date_field|date:\"Y\" }}\n    {% if instance.char_1 %}\n    <a href=\"{% url 'detail' instance.pk %}\">successful if</a>\n    {% endif %}\n{% endrender_model_block %}\n{% endblock content %}\n{% extends \"base.html\" %}\n{% load cms_tags %}\n\n{% block content %}\n{% render_model_block instance as rendered_model %}\n    {{ instance }}\n    <h1>{{ instance.char_1 }} - {{  instance.char_2 }}</h1>\n    <span class=\"date\">{{ instance.date_field|date:\"Y\" }}</span>\n    {% if instance.char_1 %}\n    <a href=\"{% url 'detail' instance.pk %}\">successful if</a>\n    {% endif %}\n{% endrender_model_block %}\n{{ rendered_model }}\n{% endblock content %}\n{% extends \"base.html\" %}\n{% load cms_tags %}\n\n{% block content %}\n{% render_model_block instance %}\n    {{ instance }}\n    <h1>{{ instance.char_1 }} - {{  instance.char_2 }}</h1>\n    <span class=\"date\">{{ instance.date_field|date:\"Y\" }}</span>\n    {% if instance.char_1 %}\n    <a href=\"{% url 'detail' instance.pk %}\">successful if</a>\n    {% endif %}\n{% endrender_model_block %}\n{% endblock content %}\n{% extends \"base.html\" %}\n{% load cms_tags %}\n\n{% block content %}\n{% render_model_block instance 'changelist' %}\n    {{ instance }}\n{% endrender_model_block %}\n{% endblock content %}\n",
            "n_words": 186,
            "vocab_size": 35,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 251848,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_connect_more_newlines",
        "commit_message": "make it black!",
        "code": "def test_connect_more_newlines(tctx):\n    \n    server = Placeholder(Server)\n    playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular))\n    nl = Placeholder(layer.NextLayer)\n\n    assert (\n        playbook\n        >> DataReceived(tctx.client, b\"CONNECT example.com:80 HTTP/1.1\\r\\n\\r\\n\\r\\n\")\n        << http.HttpConnectHook(Placeholder())\n        >> reply()\n        << OpenConnection(server)\n        >> reply(None)\n        << SendData(tctx.client, b\"HTTP/1.1 200 Connection established\\r\\n\\r\\n\")\n        >> DataReceived(tctx.client, b\"\\x16\\x03\\x03\\x00\\xb3\\x01\\x00\\x00\\xaf\\x03\\x03\")\n        << layer.NextLayerHook(nl)\n    )\n    assert nl().data_client() == b\"\\x16\\x03\\x03\\x00\\xb3\\x01\\x00\\x00\\xaf\\x03\\x03\"\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 128,
        "n_words": 44,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 118,
        "n_ast_nodes": 212,
        "n_identifiers": 22,
        "d_id": 73851,
        "documentation": {
            "docstring": "Ignore superfluous \\r\\n in CONNECT request, https://github.com/mitmproxy/mitmproxy/issues/4870",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 204842,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/creation.py",
        "file_name": "creation.py",
        "fun_name": "set_as_test_mirror",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def set_as_test_mirror(self, primary_settings_dict):\n        \n        self.connection.settings_dict[\"NAME\"] = primary_settings_dict[\"NAME\"]\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 50921,
        "documentation": {
            "docstring": "\n        Set this database up to be used in testing as a mirror of a primary\n        database whose settings are given.\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 212474,
        "commit_id": "528d85e642340ef30ec91f30b65c7c43370f648d",
        "repo": "bokeh",
        "path": "bokeh/core/has_props.py",
        "file_name": "has_props.py",
        "fun_name": "themed_values",
        "commit_message": "Normalize built-in types and remove `Unknown` (#12252)\n\n* Use lower case names for built-in types\r\n\r\nAlso incidentally apply TypeAlias marker.\r\n\r\n* Drop `Unknown` in favour of consistent usage of `Any`\r\n\r\n* Enable lazy annotations in conftest.py",
        "code": "def themed_values(self) -> dict[str, Any] | None:\n        \n        return getattr(self, '__themed_values__', None)\n",
        "url": "https://github.com/bokeh/bokeh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 24,
        "n_ast_nodes": 39,
        "n_identifiers": 6,
        "d_id": 53247,
        "documentation": {
            "docstring": " Get any theme-provided overrides.\n\n        Results are returned as a dict from property name to value, or\n        ``None`` if no theme overrides any values for this instance.\n\n        Returns:\n            dict or None\n\n        ",
            "n_words": 30,
            "vocab_size": 27,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 217867,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/server.py",
        "file_name": "server.py",
        "fun_name": "is_cgi",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def is_cgi(self):\n        \n        collapsed_path = _url_collapse_path(self.path)\n        dir_sep = collapsed_path.find('/', 1)\n        while dir_sep > 0 and not collapsed_path[:dir_sep] in self.cgi_directories:\n            dir_sep = collapsed_path.find('/', dir_sep+1)\n        if dir_sep > 0:\n            head, tail = collapsed_path[:dir_sep], collapsed_path[dir_sep+1:]\n            self.cgi_info = head, tail\n            return True\n        return False\n\n\n    cgi_directories = ['/cgi-bin', '/htbin']\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 132,
        "n_words": 43,
        "vocab_size": 30,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 85,
        "n_ast_nodes": 153,
        "n_identifiers": 11,
        "d_id": 54974,
        "documentation": {
            "docstring": "Test whether self.path corresponds to a CGI script.\n\n        Returns True and updates the cgi_info attribute to the tuple\n        (dir, rest) if self.path requires running a CGI script.\n        Returns False otherwise.\n\n        If any exception is raised, the caller should assume that\n        self.path was rejected as invalid and act accordingly.\n\n        The default implementation tests whether the normalized url\n        path begins with one of the strings in self.cgi_directories\n        (and the next character is a '/' or the end of the string).\n\n        ",
            "n_words": 78,
            "vocab_size": 59,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 200603,
        "commit_id": "69baa8d90fe079b799a80c8c06735c3ebd4bfe33",
        "repo": "sympy",
        "path": "sympy/algebras/quaternion.py",
        "file_name": "quaternion.py",
        "fun_name": "to_euler",
        "commit_message": "added reference",
        "code": "def to_euler(self, seq):\n        \n        extrinsic = _check_sequence(seq)\n        i, j, k = seq.lower()\n        i = _elementary_axis_index(i)\n        j = _elementary_axis_index(j)\n        k = _elementary_axis_index(k)\n\n        if not extrinsic:\n            i, k = k, i\n\n        # check if sequence is symmetric\n        symmetric = i == k\n        if symmetric:\n            k = 6 - i - j\n\n        # parity of the permutation\n        sign = (i - j) * (j - k) * (k - i) // 2\n\n        # permutate elements\n        elements = [self.a, self.b, self.c, self.d]\n        a = elements[0]\n        b = elements[i]\n        c = elements[j]\n        d = elements[k] * sign\n\n        if not symmetric:\n            a, b, c, d = a - c, b + d, c + a, d - b\n\n        # calculate angles\n        half_sum = atan2(b, a)\n        half_diff = atan2(d, c)\n\n        angle_2 = 2*atan2(sqrt(c*c + d*d), sqrt(a*a + b*b))\n        # alternatively, we can use this to avoid the square root:\n        # angle_2 = acos(2*(a*a + b*b)/(a*a + b*b + c*c + d*d) - 1)\n\n        angle_1 = half_sum + half_diff\n        angle_3 = half_sum - half_diff\n\n        if extrinsic:\n            angle_1, angle_3 = angle_3, angle_1\n\n        # for Tait-Bryan angles\n        if not symmetric:\n            angle_2 -= pi / 2\n            if extrinsic:\n                angle_3 *= sign\n            else:\n                angle_1 *= sign\n\n        return Matrix([angle_1, angle_2, angle_3])\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 521,
        "n_words": 197,
        "vocab_size": 104,
        "complexity": 7,
        "nloc": 33,
        "token_counts": 258,
        "n_ast_nodes": 404,
        "n_identifiers": 26,
        "d_id": 49727,
        "documentation": {
            "docstring": "Returns Euler angles representing same in the sequence given by\n        `seq`. This implements the method described in [1]_.\n\n        Parameters\n        ==========\n\n        seq : string of length 3\n            Represents the sequence of rotations.\n            For intrinsic rotations, seq but be all lowercase and its elements\n            must be from the set `['x', 'y', 'z']`\n            For extrinsic rotations, seq but be all uppercase and its elements\n            must be from the set `['X', 'Y', 'Z']`\n\n        Returns\n        =======\n\n        Matrix\n            The Euler angles calculated from the quaternion\n\n        Examples\n        ========\n\n        >>> from sympy import Quaternion\n        >>> from sympy.abc import a, b, c, d\n        >>> euler = Quaternion(a, b, c, d).to_euler('zyz')\n        >>> euler\n        Matrix([[-atan2(-b, c) + atan2(d, a)],\n                [2*atan2(sqrt(b**2 + c**2), sqrt(a**2 + d**2))],\n                [atan2(-b, c) + atan2(d, a)]])\n\n        References\n        ==========\n\n        .. [1] https://doi.org/10.1371/journal.pone.0276302\n\n        ",
            "n_words": 124,
            "vocab_size": 82,
            "n_whitespaces": 346,
            "language": "en"
        }
    },
    {
        "id": 144040,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/utils/metrics/window_stat.py",
        "file_name": "window_stat.py",
        "fun_name": "quantiles",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def quantiles(self) -> np.ndarray:\n        \n        if not self.count:\n            return np.ndarray([], dtype=np.float32)\n        else:\n            return np.nanpercentile(\n                self.items[: self.count], [0, 10, 50, 90, 100]\n            ).tolist()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 90,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 63,
        "n_ast_nodes": 97,
        "n_identifiers": 10,
        "d_id": 33098,
        "documentation": {
            "docstring": "Returns ndarray with 0, 10, 50, 90, and 100 percentiles.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 45916,
        "commit_id": "401419432082d222b823e4f2a66f21e5cc3ab28d",
        "repo": "airflow",
        "path": "tests/providers/databricks/operators/test_databricks_sql.py",
        "file_name": "test_databricks_sql.py",
        "fun_name": "test_copy_with_credential",
        "commit_message": "Add new options to DatabricksCopyIntoOperator (#22076)\n\nThis includes:\r\n* `encryption` - to specify encryption options for a given location\r\n* `credential` - to specify authentication options for a given location\r\n* `validate` - to control validation of schema & data",
        "code": "def test_copy_with_credential(self):\n        expression = \"col1, col2\"\n        op = DatabricksCopyIntoOperator(\n            file_location=COPY_FILE_LOCATION,\n            file_format='CSV',\n            table_name='test',\n            task_id=TASK_ID,\n            expression_list=expression,\n            credential={'AZURE_SAS_TOKEN': 'abc'},\n        )\n        assert (\n            op._create_sql_query()\n            == f.strip()\n        )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 145,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 56,
        "n_ast_nodes": 102,
        "n_identifiers": 15,
        "d_id": 8743,
        "documentation": {
            "docstring": "COPY INTO test\nFROM (SELECT {expression} FROM '{COPY_FILE_LOCATION}' WITH (CREDENTIAL (AZURE_SAS_TOKEN = 'abc') ))\nFILEFORMAT = CSV\n",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 311454,
        "commit_id": "58b8c30221a6f6e5acbbe98b7e3298b03fb741f5",
        "repo": "core",
        "path": "tests/components/homekit_controller/test_button.py",
        "file_name": "test_button.py",
        "fun_name": "test_press_button",
        "commit_message": "Improve homekit_controller tests (#65266)",
        "code": "async def test_press_button(hass):\n    \n    helper = await setup_test_component(hass, create_switch_with_setup_button)\n\n    # Helper will be for the primary entity, which is the outlet. Make a helper for the button.\n    button = Helper(\n        hass,\n        \"button.testdevice_setup\",\n        helper.pairing,\n        helper.accessory,\n        helper.config_entry,\n    )\n\n    await hass.services.async_call(\n        \"button\",\n        \"press\",\n        {\"entity_id\": \"button.testdevice_setup\"},\n        blocking=True,\n    )\n    button.async_assert_service_values(\n        ServicesTypes.OUTLET,\n        {\n            CharacteristicsTypes.Vendor.HAA_SETUP: \"#HAA@trcmd\",\n        },\n    )\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 172,
        "n_words": 50,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 78,
        "n_ast_nodes": 129,
        "n_identifiers": 19,
        "d_id": 110119,
        "documentation": {
            "docstring": "Test a switch service that has a button characteristic is correctly handled.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 131108,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tests/aws/utils/stubs.py",
        "file_name": "stubs.py",
        "fun_name": "describe_an_sg_2",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def describe_an_sg_2(ec2_client_stub, security_group):\n    \n    ec2_client_stub.add_response(\n        \"describe_security_groups\",\n        expected_params={\"GroupIds\": [security_group[\"GroupId\"]]},\n        service_response={\"SecurityGroups\": [security_group]},\n    )\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 40,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 38,
        "n_ast_nodes": 66,
        "n_identifiers": 6,
        "d_id": 29476,
        "documentation": {
            "docstring": "Same as last function, different input param format.\n\n    A call with this input parameter format is made when sg.ip_permissions is\n    accessed in aws/config.py.\n    ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 40221,
        "commit_id": "c3c84b9ecf16bcc61ed80ec39d511af92fe07f2c",
        "repo": "dash",
        "path": "dash/testing/browser.py",
        "file_name": "browser.py",
        "fun_name": "wait_for_style_to_equal",
        "commit_message": "f-strings everywhere! fffff",
        "code": "def wait_for_style_to_equal(self, selector, style, val, timeout=None):\n        \n        return self._wait_for(\n            method=style_to_equal,\n            args=(selector, style, val),\n            timeout=timeout,\n            msg=f\"style val => {style} {val} not found within {timeout or self._wait_timeout}s\",\n        )\n",
        "url": "https://github.com/plotly/dash.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 90,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 45,
        "n_ast_nodes": 81,
        "n_identifiers": 12,
        "d_id": 7360,
        "documentation": {
            "docstring": "Explicit wait until the element's style has expected `value` timeout\n        if not set, equals to the fixture's `wait_timeout` shortcut to\n        `WebDriverWait` with customized `style_to_equal` condition.",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 48672,
        "commit_id": "c10f2266222c434485889b08cc1463acdb8fa169",
        "repo": "django-rest-framework",
        "path": "rest_framework/renderers.py",
        "file_name": "renderers.py",
        "fun_name": "get_rendered_html_form",
        "commit_message": "Refactor: Replace try/except with contextlib.suppress() (#8676)",
        "code": "def get_rendered_html_form(self, data, view, method, request):\n        \n        # See issue #2089 for refactoring this.\n        serializer = getattr(data, 'serializer', None)\n        if serializer and not getattr(serializer, 'many', False):\n            instance = getattr(serializer, 'instance', None)\n            if isinstance(instance, Page):\n                instance = None\n        else:\n            instance = None\n\n        # If this is valid serializer data, and the form is for the same\n        # HTTP method as was used in the request then use the existing\n        # serializer instance, rather than dynamically creating a new one.\n        if request.method == method and serializer is not None:\n            try:\n                kwargs = {'data': request.data}\n            except ParseError:\n                kwargs = {}\n            existing_serializer = serializer\n        else:\n            kwargs = {}\n            existing_serializer = None\n\n        with override_method(view, request, method) as request:\n            if not self.show_form_for_method(view, method, request, instance):\n                return\n\n            if method in ('DELETE', 'OPTIONS'):\n                return True  # Don't actually need to return a form\n\n            has_serializer = getattr(view, 'get_serializer', None)\n            has_serializer_class = getattr(view, 'serializer_class', None)\n\n            if (\n                (not has_serializer and not has_serializer_class) or\n                not any(is_form_media_type(parser.media_type) for parser in view.parser_classes)\n            ):\n                return\n\n            if existing_serializer is not None:\n                with contextlib.suppress(TypeError):\n                    return self.render_form_for_serializer(existing_serializer)\n            if has_serializer:\n                if method in ('PUT', 'PATCH'):\n                    serializer = view.get_serializer(instance=instance, **kwargs)\n                else:\n                    serializer = view.get_serializer(**kwargs)\n            else:\n                # at this point we must have a serializer_class\n                if method in ('PUT', 'PATCH'):\n                    serializer = self._get_serializer(view.serializer_class, view,\n                                                      request, instance=instance, **kwargs)\n                else:\n                    serializer = self._get_serializer(view.serializer_class, view,\n                                                      request, **kwargs)\n\n            return self.render_form_for_serializer(serializer)\n",
        "url": "https://github.com/encode/django-rest-framework.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 902,
        "n_words": 215,
        "vocab_size": 111,
        "complexity": 17,
        "nloc": 45,
        "token_counts": 308,
        "n_ast_nodes": 503,
        "n_identifiers": 30,
        "d_id": 9563,
        "documentation": {
            "docstring": "\n        Return a string representing a rendered HTML form, possibly bound to\n        either the input or output data.\n\n        In the absence of the View having an associated form then return None.\n        ",
            "n_words": 30,
            "vocab_size": 27,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 276385,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/testing_infra/test_utils.py",
        "file_name": "test_utils.py",
        "fun_name": "get_expected_metric_variable_names",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_expected_metric_variable_names(var_names, name_suffix=\"\"):\n    \n    if tf.__internal__.tf2.enabled() or tf.executing_eagerly():\n        # In V1 eager mode and V2 variable names are not made unique.\n        return [n + \":0\" for n in var_names]\n    # In V1 graph mode variable names are made unique using a suffix.\n    return [n + name_suffix + \":0\" for n in var_names]\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 77,
        "n_words": 51,
        "vocab_size": 34,
        "complexity": 5,
        "nloc": 4,
        "token_counts": 49,
        "n_ast_nodes": 85,
        "n_identifiers": 9,
        "d_id": 81647,
        "documentation": {
            "docstring": "Returns expected metric variable names given names and prefix/suffix.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 207811,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_incorrect_lookup_parameters",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_incorrect_lookup_parameters(self):\n        \n        changelist_url = reverse(\"admin:admin_views_thing_changelist\")\n        response = self.client.get(changelist_url, {\"notarealfield\": \"5\"})\n        self.assertRedirects(response, \"%s?e=1\" % changelist_url)\n\n        # Spanning relationships through a nonexistent related object (Refs #16716)\n        response = self.client.get(changelist_url, {\"notarealfield__whatever\": \"5\"})\n        self.assertRedirects(response, \"%s?e=1\" % changelist_url)\n\n        response = self.client.get(\n            changelist_url, {\"color__id__exact\": \"StringNotInteger!\"}\n        )\n        self.assertRedirects(response, \"%s?e=1\" % changelist_url)\n\n        # Regression test for #18530\n        response = self.client.get(changelist_url, {\"pub_date__gte\": \"foo\"})\n        self.assertRedirects(response, \"%s?e=1\" % changelist_url)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 160,
        "n_words": 58,
        "vocab_size": 35,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 116,
        "n_ast_nodes": 207,
        "n_identifiers": 8,
        "d_id": 52112,
        "documentation": {
            "docstring": "Ensure incorrect lookup parameters are handled gracefully.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 101759,
        "commit_id": "c79175cbde5600bebd65785f3821fc74b3a80cbe",
        "repo": "faceswap",
        "path": "tools/alignments/media.py",
        "file_name": "media.py",
        "fun_name": "load_items",
        "commit_message": "Alignments Tool updates\n  - Copy info back to alignments file from faces",
        "code": "def load_items(self) -> Dict[str, List[int]]:\n        \n        faces: Dict[str, List[int]] = {}\n        for face in cast(List[Tuple[str, \"PNGHeaderDict\"]], self.file_list_sorted):\n            src = face[1][\"source\"]\n            faces.setdefault(src[\"source_filename\"], []).append(src[\"face_index\"])\n        logger.trace(faces)  # type: ignore\n        return faces\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 85,
        "n_words": 27,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 87,
        "n_ast_nodes": 138,
        "n_identifiers": 16,
        "d_id": 21163,
        "documentation": {
            "docstring": " Load the face names into dictionary.\n\n        Returns\n        -------\n        dict\n            The source filename as key with list of face indices for the frame as value\n        ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 200153,
        "commit_id": "9b2351534f8f02bcd5b9691d5e7a06150685beca",
        "repo": "sympy",
        "path": "sympy/matrices/common.py",
        "file_name": "common.py",
        "fun_name": "row_join",
        "commit_message": "Make ShapeError more readable",
        "code": "def row_join(self, other):\n        \n        # A null matrix can always be stacked (see  #10770)\n        if self.cols == 0 and self.rows != other.rows:\n            return self._new(other.rows, 0, []).row_join(other)\n\n        if self.rows != other.rows:\n            raise ShapeError(\n                \"The matrices have incompatible number of rows ({} and {})\"\n                .format(self.rows, other.rows))\n        return self._eval_row_join(other)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 133,
        "n_words": 45,
        "vocab_size": 39,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 74,
        "n_ast_nodes": 118,
        "n_identifiers": 9,
        "d_id": 49553,
        "documentation": {
            "docstring": "Concatenates two matrices along self's last and rhs's first column\n\n        Examples\n        ========\n\n        >>> from sympy import zeros, ones\n        >>> M = zeros(3)\n        >>> V = ones(3, 1)\n        >>> M.row_join(V)\n        Matrix([\n        [0, 0, 0, 1],\n        [0, 0, 0, 1],\n        [0, 0, 0, 1]])\n\n        See Also\n        ========\n\n        row\n        col_join\n        ",
            "n_words": 47,
            "vocab_size": 34,
            "n_whitespaces": 152,
            "language": "en"
        }
    },
    {
        "id": 201335,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/auth_tests/test_management.py",
        "file_name": "test_management.py",
        "fun_name": "test_permission_with_proxy_content_type_created",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_permission_with_proxy_content_type_created(self):\n        \n        opts = UserProxy._meta\n        codename = get_permission_codename(\"add\", opts)\n        self.assertTrue(\n            Permission.objects.filter(\n                content_type__model=opts.model_name,\n                content_type__app_label=opts.app_label,\n                codename=codename,\n            ).exists()\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 118,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 51,
        "n_ast_nodes": 83,
        "n_identifiers": 16,
        "d_id": 49919,
        "documentation": {
            "docstring": "\n        A proxy model's permissions use its own content type rather than the\n        content type of the concrete model.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 24519,
        "commit_id": "ddaa2c2552e19635cd6cdf38619f1f176c358f89",
        "repo": "PaddleOCR",
        "path": "ppstructure/table/table_master_match.py",
        "file_name": "table_master_match.py",
        "fun_name": "get_bboxes_list",
        "commit_message": "add SLANet",
        "code": "def get_bboxes_list(end2end_result, structure_master_result):\n    \n    # end2end\n    end2end_xyxy_list = []\n    end2end_xywh_list = []\n    for end2end_item in end2end_result:\n        src_bbox = end2end_item['bbox']\n        end2end_xyxy_list.append(src_bbox)\n        xywh_bbox = xyxy2xywh(src_bbox)\n        end2end_xywh_list.append(xywh_bbox)\n    end2end_xyxy_bboxes = np.array(end2end_xyxy_list)\n    end2end_xywh_bboxes = np.array(end2end_xywh_list)\n\n    # structure master\n    src_bboxes = structure_master_result['bbox']\n    src_bboxes = remove_empty_bboxes(src_bboxes)\n    # structure_master_xywh_bboxes = src_bboxes\n    # xyxy_bboxes = xywh2xyxy(src_bboxes)\n    # structure_master_xyxy_bboxes = xyxy_bboxes\n    structure_master_xyxy_bboxes = src_bboxes\n    xywh_bbox = xyxy2xywh(src_bboxes)\n    structure_master_xywh_bboxes = xywh_bbox\n\n    return end2end_xyxy_bboxes, end2end_xywh_bboxes, structure_master_xywh_bboxes, structure_master_xyxy_bboxes\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 143,
        "n_words": 64,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 93,
        "n_ast_nodes": 159,
        "n_identifiers": 18,
        "d_id": 4761,
        "documentation": {
            "docstring": "\n    This function is use to convert end2end results and structure master results to\n    List of xyxy bbox format and List of xywh bbox format\n    :param end2end_result: bbox's format is xyxy\n    :param structure_master_result: bbox's format is xywh\n    :return: 4 kind list of bbox ()\n    ",
            "n_words": 43,
            "vocab_size": 26,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 212647,
        "commit_id": "ef3746cb06a9ee6bc93bc3c163ba961fd1b9c413",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "make_modal",
        "commit_message": "set_options - new parm disable_modal_windows provides ability to disable modal setting for all windows including popups",
        "code": "def make_modal(self):\n        \n        if not self._is_window_created('tried Window.make_modal'):\n            return\n\n        if running_mac() and ENABLE_MAC_MODAL_DISABLE_PATCH:\n            return\n\n        # if modal windows have been disabled globally\n        if not DEFAULT_MODAL_WINDOWS_ENABLED:\n            return\n\n        try:\n            self.TKroot.transient()\n            self.TKroot.grab_set()\n            self.TKroot.focus_force()\n        except Exception as e:\n            print('Exception trying to make modal', e)\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 164,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 6,
        "nloc": 13,
        "token_counts": 63,
        "n_ast_nodes": 116,
        "n_identifiers": 13,
        "d_id": 53310,
        "documentation": {
            "docstring": "\n        Makes a window into a \"Modal Window\"\n        This means user will not be able to interact with other windows until this one is closed\n\n        NOTE - Sorry Mac users - you can't have modal windows.... lobby your tkinter Mac devs\n        ",
            "n_words": 40,
            "vocab_size": 37,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 179703,
        "commit_id": "9e4541822770333ab5191bc01aa3edc9738f17ff",
        "repo": "gradio",
        "path": "gradio/components.py",
        "file_name": "components.py",
        "fun_name": "set_interpret_parameters",
        "commit_message": "Blocks-Components\n- move audio component",
        "code": "def set_interpret_parameters(self, segments=8):\n        \n        self.interpretation_segments = segments\n        return self\n",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 29,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 17,
        "n_ast_nodes": 29,
        "n_identifiers": 4,
        "d_id": 43002,
        "documentation": {
            "docstring": "\n        Calculates interpretation score of audio subsections by splitting the audio into subsections, then using a \"leave one out\" method to calculate the score of each subsection by removing the subsection and measuring the delta of the output value.\n        Parameters:\n        segments (int): Number of interpretation segments to split audio into.\n        ",
            "n_words": 49,
            "vocab_size": 34,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 167592,
        "commit_id": "f538568afc2c76c2d738d32e3544cf9fe6742960",
        "repo": "pandas",
        "path": "pandas/_testing/contexts.py",
        "file_name": "contexts.py",
        "fun_name": "with_csv_dialect",
        "commit_message": "TYP: misc return type annotations (#47558)",
        "code": "def with_csv_dialect(name, **kwargs) -> Iterator[None]:\n    \n    import csv\n\n    _BUILTIN_DIALECTS = {\"excel\", \"excel-tab\", \"unix\"}\n\n    if name in _BUILTIN_DIALECTS:\n        raise ValueError(\"Cannot override builtin dialect.\")\n\n    csv.register_dialect(name, **kwargs)\n    try:\n        yield\n    finally:\n        csv.unregister_dialect(name)\n\n\n@contextmanager",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 69,
        "n_words": 28,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 55,
        "n_ast_nodes": 103,
        "n_identifiers": 10,
        "d_id": 40048,
        "documentation": {
            "docstring": "\n    Context manager to temporarily register a CSV dialect for parsing CSV.\n\n    Parameters\n    ----------\n    name : str\n        The name of the dialect.\n    kwargs : mapping\n        The parameters for the dialect.\n\n    Raises\n    ------\n    ValueError : the name of the dialect conflicts with a builtin one.\n\n    See Also\n    --------\n    csv : Python's CSV library.\n    ",
            "n_words": 51,
            "vocab_size": 36,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 42077,
        "commit_id": "6460a21555ba6557e1f6f06f4d677d9c19148169",
        "repo": "seaborn",
        "path": "seaborn/utils.py",
        "file_name": "utils.py",
        "fun_name": "adjust_legend_subtitles",
        "commit_message": "Workaround for matplotlib rc_context issue (#2925)\n\n* Workaround for matplotlib rc_context issue\r\n\r\nFixes #2914\r\n\r\n* Add some additional comments about this workaround",
        "code": "def adjust_legend_subtitles(legend):\n    \n    # Legend title not in rcParams until 3.0\n    font_size = plt.rcParams.get(\"legend.title_fontsize\", None)\n    hpackers = legend.findobj(mpl.offsetbox.VPacker)[0].get_children()\n    for hpack in hpackers:\n        draw_area, text_area = hpack.get_children()\n        handles = draw_area.get_children()\n        if not all(artist.get_visible() for artist in handles):\n            draw_area.set_width(0)\n            for text in text_area.get_children():\n                if font_size is not None:\n                    text.set_size(font_size)\n\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 138,
        "n_words": 46,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 11,
        "token_counts": 100,
        "n_ast_nodes": 165,
        "n_identifiers": 22,
        "d_id": 7477,
        "documentation": {
            "docstring": "\n    Make invisible-handle \"subtitles\" entries look more like titles.\n\n    Note: This function is not part of the public API and may be changed or removed.\n\n    ",
            "n_words": 24,
            "vocab_size": 24,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 272002,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_v1.py",
        "file_name": "training_v1.py",
        "fun_name": "_prepare_skip_target_masks",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _prepare_skip_target_masks(self):\n        \n        return [l is None for l in self.loss_functions]\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 18,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 80930,
        "documentation": {
            "docstring": "Boolean mask for whether the target in the output list should be skipped.\n\n        If the loss function corresponding to a model output is None, then this\n        output will be skipped during total loss calculation and feed targets\n        preparation.\n\n        Returns:\n          A boolean list for whether the corresponding target in the output list\n          should be skipped during loss calculation.\n        ",
            "n_words": 57,
            "vocab_size": 36,
            "n_whitespaces": 110,
            "language": "en"
        }
    },
    {
        "id": 281593,
        "commit_id": "82747072c511beb1b2672846ae2ee4aec53eb562",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/terminal_helper.py",
        "file_name": "terminal_helper.py",
        "fun_name": "update_terminal",
        "commit_message": "Terminal Wide Rich (#1161)\n\n* My idea for how we handle Rich moving forward\r\n\r\n* remove independent consoles\r\n\r\n* FIxed pylint issues\r\n\r\n* add a few vars\r\n\r\n* Switched print to console\r\n\r\n* More transitions\r\n\r\n* Changed more prints\r\n\r\n* Replaced all prints\r\n\r\n* Fixing tabulate\r\n\r\n* Finished replace tabulate\r\n\r\n* Finished removing rich from Tabulate\r\n\r\n* add Panel around menu\r\n\r\n* add GST watermark under feature flag\r\n\r\n* Fixed 46 tests\r\n\r\n* Delete test_screener[False].yaml\r\n\r\n* Delete test_screener[True].yaml\r\n\r\n* Fixed the rest of the tests\r\n\r\n* add help and source color vars and use rgb\r\n\r\n* rich on stocks/options\r\n\r\n* update rich on disc, dps, sia\r\n\r\n* rich in gov, ins and scr menus\r\n\r\n* ba and ca menus with rich\r\n\r\n* Fixed import issue\r\n\r\n* Fixed some tests\r\n\r\n* removed termcolor\r\n\r\n* Removed prettytable\r\n\r\n* add rich to remaining stocks menus\r\n\r\n* FIxed linting issue\r\n\r\n* Added James' changes\r\n\r\n* Updated dependencies\r\n\r\n* Add rich to cryptocurrency menu\r\n\r\n* refactor economy and forex\r\n\r\n* refactor etf with rich\r\n\r\n* refactor mfunds\r\n\r\n* refactor rich rest\r\n\r\n* not specify style so default color works well on any background\r\n\r\n* Fixing mypy issues\r\n\r\n* Updated tests\r\n\r\n* More test fixes\r\n\r\n* James' test fixes\r\n\r\n* Updating tests : stocks/screener - fix cassettes using BR\r\n\r\n* Updating tests : crypto\r\n\r\n* Updating tests : disable DEBUG_MODE\r\n\r\n* Updating tests : stocks/fa/yfinance\r\n\r\n* minor fixes that escape\r\n\r\n* Improve the rich table function (that replaces tabulate :D )\r\n\r\n* Fixed bad code\r\n\r\n* delete rogue file + dcf fix + NoConsole\r\n\r\n* sia mypy\r\n\r\n* fuck you linter\r\n\r\n* fuck you linter pt 2\r\n\r\n* skip hehe\r\n\r\n* i hate the black linter\r\n\r\n* ubuntu mypy attempt\r\n\r\n* Update : rich_config + gtff\r\n\r\n* Updating tests : conftest\r\n\r\n* Updating tests : stocks\r\n\r\n* Update : rich_config\r\n\r\n* Updating : rich_config\r\n\r\n* make panel configurable for Theodore :b\r\n\r\n* colors update\r\n\r\n* Merged\r\n\r\n* Updating : rich_config + feature_flags\r\n\r\n* Updating : rich_config\r\n\r\n* Updating tests : stocks\r\n\r\n* Updating : feature_flags\r\n\r\nCo-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt>\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>\r\nCo-authored-by: james <jmaslek11@gmail.com>\r\nCo-authored-by: jose-donato <zmcdonato@gmail.com>",
        "code": "def update_terminal():\n    \n    poetry_hash = sha256sum(\"poetry.lock\")\n\n    completed_process = subprocess.run(\"git pull\", shell=True, check=False)  # nosec\n    if completed_process.returncode != 0:\n        return completed_process.returncode\n\n    new_poetry_hash = sha256sum(\"poetry.lock\")\n\n    if poetry_hash == new_poetry_hash:\n        console.print(\"Great, seems like poetry hasn't been updated!\")\n        return completed_process.returncode\n    console.print(\n        \"Seems like more modules have been added, grab a coke, this may take a while.\"\n    )\n\n    completed_process = subprocess.run(\n        \"poetry install\", shell=True, check=False\n    )  # nosec\n    if completed_process.returncode != 0:\n        return completed_process.returncode\n\n    return 0\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 150,
        "n_words": 70,
        "vocab_size": 46,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 94,
        "n_ast_nodes": 163,
        "n_identifiers": 12,
        "d_id": 83890,
        "documentation": {
            "docstring": "Updates the terminal by running git pull in the directory.  Runs poetry install if needed",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 321448,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/utils/test_qtutils.py",
        "file_name": "test_qtutils.py",
        "fun_name": "test_serialize_post_error_mock",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_serialize_post_error_mock(self, stream_mock):\n        \n        obj = QPoint()\n        stream_mock.__lshift__.side_effect = lambda _other: self._set_status(\n            stream_mock, QDataStream.Status.ReadCorruptData)\n\n        with pytest.raises(OSError, match=\"The data stream has read corrupt \"\n                                          \"data.\"):\n            qtutils.serialize_stream(stream_mock, obj)\n\n        assert stream_mock.__lshift__.called_once_with(obj)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 125,
        "n_words": 27,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 64,
        "n_ast_nodes": 108,
        "n_identifiers": 19,
        "d_id": 117730,
        "documentation": {
            "docstring": "Test serialize_stream with an error while serializing.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 163219,
        "commit_id": "3977d7335f0792c012013e3b459a7950dfd31a7d",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "_validate_fill_value",
        "commit_message": "REF: consolidate _validate_fill_logic in np_can_hold_element (#45216)",
        "code": "def _validate_fill_value(self, value):\n        \n        dtype = self.dtype\n        if isinstance(dtype, np.dtype) and dtype.kind not in [\"m\", \"M\"]:\n            try:\n                return np_can_hold_element(dtype, value)\n            except ValueError as err:\n                # re-raise as TypeError for consistency\n                raise TypeError from err\n        if not can_hold_element(self._values, value):\n            raise TypeError\n        return value\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 154,
        "n_words": 41,
        "vocab_size": 33,
        "complexity": 5,
        "nloc": 10,
        "token_counts": 67,
        "n_ast_nodes": 109,
        "n_identifiers": 13,
        "d_id": 39405,
        "documentation": {
            "docstring": "\n        Check if the value can be inserted into our array without casting,\n        and convert it to an appropriate native type if necessary.\n\n        Raises\n        ------\n        TypeError\n            If the value cannot be inserted into an array of this dtype.\n        ",
            "n_words": 37,
            "vocab_size": 29,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 14004,
        "commit_id": "5a0830cfb6bfa33dcffb38681f86efe5f6f0f97c",
        "repo": "jina",
        "path": "jina/serve/stream/helper.py",
        "file_name": "helper.py",
        "fun_name": "__anext__",
        "commit_message": "refactor: avoid run in executor creating threads (#5518)",
        "code": "async def __anext__(self):\n        if isinstance(self.iterator, Iterator):\n            \n\n            if not self._iterate_sync_in_thread:",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 38,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 7,
        "nloc": 27,
        "token_counts": 108,
        "n_ast_nodes": 39,
        "n_identifiers": 6,
        "d_id": 2797,
        "documentation": {
            "docstring": "\n            An `Iterator` indicates \"blocking\" code, which might block all tasks in the event loop.\n            Hence we iterate in the default executor provided by asyncio.\n            ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 20914,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/typing_extensions.py",
        "file_name": "typing_extensions.py",
        "fun_name": "__new__",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def __new__(cls, name, bases, ns, total=True):\n            # Create new typed dict class object.\n            # This method is called directly when TypedDict is subclassed,\n            # or via _typeddict_new when TypedDict is instantiated. This way\n            # TypedDict supports all three syntaxes described in its docstring.\n            # Subclasses and instances of TypedDict return actual dictionaries\n            # via _dict_new.\n            ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new\n            tp_dict = super().__new__(cls, name, (dict,), ns)\n\n            annotations = {}\n            own_annotations = ns.get('__annotations__', {})\n            own_annotation_keys = set(own_annotations.keys())\n            msg = \"TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type\"\n            own_annotations = {\n                n: typing._type_check(tp, msg) for n, tp in own_annotations.items()\n            }\n            required_keys = set()\n            optional_keys = set()\n\n            for base in bases:\n                annotations.update(base.__dict__.get('__annotations__', {}))\n                required_keys.update(base.__dict__.get('__required_keys__', ()))\n                optional_keys.update(base.__dict__.get('__optional_keys__', ()))\n\n            annotations.update(own_annotations)\n            if total:\n                required_keys.update(own_annotation_keys)\n            else:\n                optional_keys.update(own_annotation_keys)\n\n            tp_dict.__annotations__ = annotations\n            tp_dict.__required_keys__ = frozenset(required_keys)\n            tp_dict.__optional_keys__ = frozenset(optional_keys)\n            if not hasattr(tp_dict, '__total__'):\n                tp_dict.__total__ = total\n            return tp_dict\n\n        __instancecheck__ = __subclasscheck__ = _check_fails\n\n    TypedDict = _TypedDictMeta('TypedDict', (dict,), {})\n    TypedDict.__module__ = __name__\n    TypedDict.__doc__ = \\\n        ",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "\"\"\"A simple typed name space. At runtimeequivalent to a plain dict.\n\n        TypedDict creates a dictionary type that expects all ofto a plain dictinstances to have a certain set ofwith eachassociated with a value of a consistent type. This expectation\n        is not checked at runtime but is only enforced by type checkers.\n        Usage::a value of a consistent type. Thisat runtime butonly enforced by type",
        "n_ast_errors": 9,
        "ast_levels": 12,
        "n_whitespaces": 565,
        "n_words": 162,
        "vocab_size": 116,
        "complexity": 6,
        "nloc": 27,
        "token_counts": 221,
        "n_ast_nodes": 495,
        "n_identifiers": 80,
        "d_id": 3614,
        "documentation": {
            "docstring": "A simple typed name space. At runtime it is equivalent to a plain dict.\n\n        TypedDict creates a dictionary type that expects all of its\n        instances to have a certain set of keys, with each key\n        associated with a value of a consistent type. This expectation\n        is not checked at runtime but is only enforced by type checkers.\n        Usage::\n",
            "n_words": 58,
            "vocab_size": 46,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 263997,
        "commit_id": "04984a040c2396127f234518f783cbed088408bb",
        "repo": "pyinstaller",
        "path": "PyInstaller/building/api.py",
        "file_name": "api.py",
        "fun_name": "_set_dependencies",
        "commit_message": "building: move filename processing of EXTENSION entries to analysis stage\n\nMove filename processing of EXTENSION TOC entries (i.e., converting\nthe module name to file path and adding the suffix) from the\nbuild stage (i.e., `assemble` in `PKG`, `COLLECT`, and `BUNDLE`)\ninto analysis stage.\n\nThis ensures that during the build stage, the EXTENSION entries\nin the TOC are already full filenames, same as other file-based\nentries (DATA, BINARY, etc.).\n\nThis in turn means that the `add_suffix_to_extension` helper does\nnot need to worry about DEPENDENCY entries anymore, and can\nprocess only EXTENSION ones, as implied by its name.\n\nEarly conversion of EXTENSION module names to file names also\nprevents duplication when the same file is collected as both\nan EXTENSION and some other type, for example DATA:\n```\n('torch._C',\n   '...\\\\site-packages\\\\torch\\\\_C.cp39-win_amd64.pyd',\n   'EXTENSION'),\n('torch\\\\_C.cp39-win_amd64.pyd',\n   '...\\\\site-pakages\\\\torch\\\\_C.cp39-win_amd64.pyd',\n   'DATA'),\n```\nPrior to this commit, the entries were considered different\nfrom the `TOC` perspective, but led to duplication in onefile\nbuild's PKG once extension's name was changed to the file name\n(whereas in onedir build, the first entry was overwritten by\nthe second).",
        "code": "def _set_dependencies(self, analysis, path):\n        \n        for toc in (analysis.binaries, analysis.datas):\n            for i, tpl in enumerate(toc):\n                if not tpl[1] in self._dependencies:\n                    logger.debug(\"Adding dependency %s located in %s\", tpl[1], path)\n                    self._dependencies[tpl[1]] = path\n                else:\n                    dep_path = self._get_relative_path(path, self._dependencies[tpl[1]])\n                    # Ignore references that point to the origin package. This can happen if the same resource is listed\n                    # multiple times in TOCs (e.g., once as binary and once as data).\n                    if dep_path.endswith(path):\n                        logger.debug(\n                            \"Ignoring self-reference of %s for %s, located in %s - duplicated TOC entry?\", tpl[1], path,\n                            dep_path\n                        )\n                        # Clear the entry as it is a duplicate.\n                        toc[i] = (None, None, None)\n                        continue\n                    logger.debug(\"Referencing %s to be a dependency for %s, located in %s\", tpl[1], path, dep_path)\n                    # Determine the path relative to dep_path (i.e, within the target directory) from the 'name'\n                    # component of the TOC tuple.\n                    rel_path = os.path.dirname(tpl[0])\n                    # Take filename from 'path' (second component of TOC tuple); this way, we don't need to worry about\n                    # suffix of extensions.\n                    filename = os.path.basename(tpl[1])\n                    # Construct the full file path relative to dep_path...\n                    filename = os.path.join(rel_path, filename)\n                    # ...and use it in new DEPENDENCY entry\n                    analysis.dependencies.append((\":\".join((dep_path, filename)), tpl[1], \"DEPENDENCY\"))\n                    toc[i] = (None, None, None)\n            # Clean the list\n            toc[:] = [tpl for tpl in toc if tpl != (None, None, None)]\n\n    # TODO: use pathlib.Path.relative_to() instead.",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 807,
        "n_words": 216,
        "vocab_size": 129,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 237,
        "n_ast_nodes": 365,
        "n_identifiers": 24,
        "d_id": 77548,
        "documentation": {
            "docstring": "\n        Synchronize the Analysis result with the needed dependencies.\n        ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 189478,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/svg/tex_mobject.py",
        "file_name": "tex_mobject.py",
        "fun_name": "break_up_by_substrings",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _break_up_by_substrings(self):\n        \n        new_submobjects = []\n        curr_index = 0\n        for tex_string in self.tex_strings:\n            sub_tex_mob = SingleStringMathTex(\n                tex_string,\n                tex_environment=self.tex_environment,\n                tex_template=self.tex_template,\n            )\n            num_submobs = len(sub_tex_mob.submobjects)\n            new_index = (\n                curr_index + num_submobs + len(\"\".join(self.arg_separator.split()))\n            )\n            if num_submobs == 0:\n                # For cases like empty tex_strings, we want the corresponding\n                # part of the whole MathTex to be a VectorizedPoint\n                # positioned in the right part of the MathTex\n                sub_tex_mob.submobjects = [VectorizedPoint()]\n                last_submob_index = min(curr_index, len(self.submobjects) - 1)\n                sub_tex_mob.move_to(self.submobjects[last_submob_index], RIGHT)\n            else:\n                sub_tex_mob.submobjects = self.submobjects[curr_index:new_index]\n            new_submobjects.append(sub_tex_mob)\n            curr_index = new_index\n        self.submobjects = new_submobjects\n        return self\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 394,
        "n_words": 88,
        "vocab_size": 61,
        "complexity": 3,
        "nloc": 23,
        "token_counts": 142,
        "n_ast_nodes": 230,
        "n_identifiers": 23,
        "d_id": 46082,
        "documentation": {
            "docstring": "\n        Reorganize existing submobjects one layer\n        deeper based on the structure of tex_strings (as a list\n        of tex_strings)\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 63322,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "delimitedList",
        "commit_message": "upd; format",
        "code": "def delimitedList(expr, delim=\",\", combine=False):\n    \n    dlName = _ustr(expr) + \" [\" + _ustr(delim) + \" \" + _ustr(expr) + \"]...\"\n    if combine:\n        return Combine(expr + ZeroOrMore(delim + expr)).setName(dlName)\n    else:\n        return (expr + ZeroOrMore(Suppress(delim) + expr)).setName(dlName)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 60,
        "n_words": 34,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 77,
        "n_ast_nodes": 132,
        "n_identifiers": 10,
        "d_id": 13253,
        "documentation": {
            "docstring": "Helper to define a delimited list of expressions - the delimiter\n    defaults to ','. By default, the list elements and delimiters can\n    have intervening whitespace, and comments, but this can be\n    overridden by passing ``combine=True`` in the constructor. If\n    ``combine`` is set to ``True``, the matching tokens are\n    returned as a single token string, with the delimiters included;\n    otherwise, the matching tokens are returned as a list of tokens,\n    with the delimiters suppressed.\n\n    Example::\n\n        delimitedList(Word(alphas)).parseString(\"aa,bb,cc\") # -> ['aa', 'bb', 'cc']\n        delimitedList(Word(hexnums), delim=':', combine=True).parseString(\"AA:BB:CC:DD:EE\") # -> ['AA:BB:CC:DD:EE']\n    ",
            "n_words": 86,
            "vocab_size": 61,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 218095,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap.py",
        "file_name": "_bootstrap.py",
        "fun_name": "_gcd_import",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _gcd_import(name, package=None, level=0):\n    \n    _sanity_check(name, package, level)\n    if level > 0:\n        name = _resolve_name(name, package, level)\n    return _find_and_load(name, _gcd_import)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 38,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 44,
        "n_ast_nodes": 66,
        "n_identifiers": 7,
        "d_id": 55125,
        "documentation": {
            "docstring": "Import and return the module based on its name, the package the call is\n    being made from, and the level adjustment.\n\n    This function represents the greatest common denominator of functionality\n    between import_module and __import__. This includes setting __package__ if\n    the loader did not.\n\n    ",
            "n_words": 43,
            "vocab_size": 35,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 286538,
        "commit_id": "8e9e6bd57f4bc5d57ccedfacccda6342d5881266",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/portfolio/portfolio_model.py",
        "file_name": "portfolio_model.py",
        "fun_name": "get_transactions",
        "commit_message": "Incorporate portfolio class into SDK (#3401)\n\n* create functions to interact with portfolio\r\n\r\n* fix some docstrings\r\n\r\n* view docstrings\r\n\r\n* make portfolio loading available in sdk\r\n\r\n* reorder some methods\r\n\r\n* fix bug\r\n\r\n* update controller\r\n\r\n* update website\r\n\r\n* remove import\r\n\r\n* change input name\r\n\r\n* regenerate website\r\n\r\n* change portfolio arg name\r\n\r\n* fix metrics bugs\r\n\r\n* fix report\r\n\r\n* refactor assets alloc\r\n\r\n* refactor assets sectors alloc\r\n\r\n* remove unecessary attributes\r\n\r\n* refactor allocaasset sector\r\n\r\n* reorganize class\r\n\r\n* first refactor alloc\r\n\r\n* refactor portfolio alloc\r\n\r\n* black\r\n\r\n* fix alloc bug\r\n\r\n* regenerate sdk website\r\n\r\n* fix alloc bugs\r\n\r\n* forgot this exception\r\n\r\n* some refactor on portfolio alloc country region\r\n\r\n* fix some allocation bugs\r\n\r\n* add examples\r\n\r\n* regenerate website\r\n\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>",
        "code": "def get_transactions(self):\n        \n\n        df = self.__transactions[\n            [\n                \"Date\",\n                \"Type\",\n                \"Ticker\",\n                \"Side\",\n                \"Price\",\n                \"Quantity\",\n                \"Fees\",\n                \"Investment\",\n                \"Currency\",\n                \"Sector\",\n                \"Industry\",\n                \"Country\",\n                \"Region\",\n            ]\n        ]\n        df = df.replace(np.nan, \"-\")\n        df[\"Date\"] = df[\"Date\"].dt.strftime(\"%Y-%m-%d\")\n        df.sort_values(by=\"Date\", ascending=False, inplace=True)\n        return df\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 299,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 87,
        "n_ast_nodes": 157,
        "n_identifiers": 13,
        "d_id": 85861,
        "documentation": {
            "docstring": "Get formatted transactions\n\n        Returns\n        -------\n            pd.DataFrame: formatted transactions\n        ",
            "n_words": 8,
            "vocab_size": 6,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 23379,
        "commit_id": "6e607a0fa1cefbf0388dac86c84debf4781cec48",
        "repo": "PaddleOCR",
        "path": "ppocr/modeling/backbones/rec_efficientb3_pren.py",
        "file_name": "rec_efficientb3_pren.py",
        "fun_name": "get_global_params",
        "commit_message": "[Feature] Add PREN Scene Text Recognition Model(Accepted in CVPR2021) (#5563)\n\n* [Feature] add PREN scene text recognition model\r\n\r\n* [Patch] Optimize yml File\r\n\r\n* [Patch] Save Label/Pred Preprocess Time Cost\r\n\r\n* [BugFix] Modify Shape Conversion to Fit for Inference Model Exportion\r\n\r\n* [Patch] ?\r\n\r\n* [Patch] ?\r\n\r\n* 啥情况...",
        "code": "def get_global_params():\n        \n        GlobalParams = namedtuple('GlobalParams', [\n            'drop_connect_rate', 'width_coefficient', 'depth_coefficient',\n            'depth_divisor', 'image_size'\n        ])\n        global_params = GlobalParams(\n            drop_connect_rate=0.3,\n            width_coefficient=1.2,\n            depth_coefficient=1.4,\n            depth_divisor=8,\n            image_size=64)\n        return global_params\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 134,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 55,
        "n_ast_nodes": 83,
        "n_identifiers": 9,
        "d_id": 4585,
        "documentation": {
            "docstring": "\n        The fllowing are efficientnetb3's arch superparams, but to fit for scene \n        text recognition task, the resolution(image_size) here is changed \n        from 300 to 64.\n        ",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 265553,
        "commit_id": "8b1a462a6070cb6054af8bb59589c9a2e785afc2",
        "repo": "netbox",
        "path": "netbox/netbox/views/generic/object_views.py",
        "file_name": "object_views.py",
        "fun_name": "get_extra_addanother_params",
        "commit_message": "#10094 changes from code review",
        "code": "def get_extra_addanother_params(self, request, params):\n        \n        return {}\n\n    #\n    # Request handlers\n    #\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 34,
        "n_words": 11,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 13,
        "n_ast_nodes": 25,
        "n_identifiers": 4,
        "d_id": 78139,
        "documentation": {
            "docstring": "\n        Return a dictionary of extra parameters to use on the Add Another button.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 60723,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/index/collector.py",
        "file_name": "collector.py",
        "fun_name": "_ensure_html_header",
        "commit_message": "upd; format",
        "code": "def _ensure_html_header(response):\n    # type: (Response) -> None\n    \n    content_type = response.headers.get(\"Content-Type\", \"\")\n    if not content_type.lower().startswith(\"text/html\"):\n        raise _NotHTML(content_type, response.request.method)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 36,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 42,
        "n_ast_nodes": 76,
        "n_identifiers": 10,
        "d_id": 12262,
        "documentation": {
            "docstring": "Check the Content-Type header to ensure the response contains HTML.\n\n    Raises `_NotHTML` if the content type is not text/html.\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 247791,
        "commit_id": "9d21ecf7ceab55bc19c4457b8b07401b0b1623a7",
        "repo": "synapse",
        "path": "tests/storage/test_id_generators.py",
        "file_name": "test_id_generators.py",
        "fun_name": "test_get_next_txn",
        "commit_message": "Add type hints to tests files. (#12256)",
        "code": "def test_get_next_txn(self) -> None:\n        \n\n        # Prefill table with 7 rows written by 'master'\n        self._insert_rows(\"master\", 7)\n\n        id_gen = self._create_id_generator()\n\n        self.assertEqual(id_gen.get_positions(), {\"master\": 7})\n        self.assertEqual(id_gen.get_current_token_for_writer(\"master\"), 7)\n\n        # Try allocating a new ID gen and check that we only see position\n        # advanced after we leave the context manager.\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 101,
        "n_words": 45,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 98,
        "n_ast_nodes": 94,
        "n_identifiers": 8,
        "d_id": 71924,
        "documentation": {
            "docstring": "Test that the `get_next_txn` function works correctly.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 156063,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/array/slicing.py",
        "file_name": "slicing.py",
        "fun_name": "sanitize_index",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def sanitize_index(ind):\n    \n    from dask.array.utils import asanyarray_safe\n\n    if ind is None:\n        return None\n    elif isinstance(ind, slice):\n        return slice(\n            _sanitize_index_element(ind.start),\n            _sanitize_index_element(ind.stop),\n            _sanitize_index_element(ind.step),\n        )\n    elif isinstance(ind, Number):\n        return _sanitize_index_element(ind)\n    elif is_dask_collection(ind):\n        return ind\n    index_array = asanyarray_safe(ind, like=ind)\n    if index_array.dtype == bool:\n        nonzero = np.nonzero(index_array)\n        if len(nonzero) == 1:\n            # If a 1-element tuple, unwrap the element\n            nonzero = nonzero[0]\n        if is_arraylike(nonzero):\n            return nonzero\n        else:\n            return np.asanyarray(nonzero)\n    elif np.issubdtype(index_array.dtype, np.integer):\n        return index_array\n    elif np.issubdtype(index_array.dtype, np.floating):\n        int_index = index_array.astype(np.intp)\n        if np.allclose(index_array, int_index):\n            return int_index\n        else:\n            check_int = np.isclose(index_array, int_index)\n            first_err = index_array.ravel()[np.flatnonzero(~check_int)[0]]\n            raise IndexError(\"Bad index.  Must be integer-like: %s\" % first_err)\n    else:\n        raise TypeError(\"Invalid index type\", type(ind), ind)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 356,
        "n_words": 103,
        "vocab_size": 72,
        "complexity": 11,
        "nloc": 35,
        "token_counts": 235,
        "n_ast_nodes": 371,
        "n_identifiers": 38,
        "d_id": 36528,
        "documentation": {
            "docstring": "Sanitize the elements for indexing along one axis\n\n    >>> sanitize_index([2, 3, 5])\n    array([2, 3, 5])\n    >>> sanitize_index([True, False, True, False])\n    array([0, 2])\n    >>> sanitize_index(np.array([1, 2, 3]))\n    array([1, 2, 3])\n    >>> sanitize_index(np.array([False, True, True]))\n    array([1, 2])\n    >>> type(sanitize_index(np.int32(0)))\n    <class 'int'>\n    >>> sanitize_index(1.0)\n    1\n    >>> sanitize_index(0.5)\n    Traceback (most recent call last):\n    ...\n    IndexError: Bad index.  Must be integer-like: 0.5\n    ",
            "n_words": 57,
            "vocab_size": 45,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 85651,
        "commit_id": "c48fda09e252018a4d2b831bb84e1c68a739c085",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_multiprocess_steps.py",
        "file_name": "test_multiprocess_steps.py",
        "fun_name": "test_process_messages_cardinality_limited",
        "commit_message": "feat(metrics): Add  cardinality limiter to indexer [sns-1651] (#38428)\n\nReopen of https://github.com/getsentry/sentry/pull/38302 to avoid\r\nnotification spam\r\n\r\nSee #38257 and\r\nhttps://www.notion.so/sentry/Metrics-Dimensionality-Limiting-df010a6a6d4e467ca3c5c19230db862b#4966fb9c07fc4394b720ad161c99a096.\r\nThis is just the glue code and configuration options for using the\r\ncardinality limiter in the indexer. The actual implementation is TBD.\r\nThis is safe to merge because the stub implementation does not actually\r\nlimit anything at all, so it should be fast enough to do synchronously\r\nfor now\r\n\r\n## rollout plan\r\n\r\n- [x] https://github.com/getsentry/sentry/pull/38446\r\n- [x] set options to nothing in prod\r\n- [ ] merge + deploy this PR\r\n- [ ] check prod metrics: redis should not be used\r\n- [ ] https://github.com/getsentry/sentry/pull/38445\r\n- [ ] check prod metrics: redis should still not be used\r\n- [ ] run qe tests?\r\n- [ ] get a redis cluster and configure it\r\n- [ ] run use_quota on a separate thread\r\n- [ ] set a quota\r\n- [ ] get rid of writes limiter?\r\n- [ ] stop indexing tag values\r\n\r\nCo-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>\r\nCo-authored-by: Nikhar Saxena <nikhar.saxena@sentry.io>",
        "code": "def test_process_messages_cardinality_limited(caplog, settings, monkeypatch) -> None:\n    \n    settings.SENTRY_METRICS_INDEXER_DEBUG_LOG_SAMPLE_RATE = 1.0\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 15,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 28,
        "token_counts": 170,
        "n_ast_nodes": 28,
        "n_identifiers": 5,
        "d_id": 18024,
        "documentation": {
            "docstring": "\n    Test that the message processor correctly calls the cardinality limiter.\n    ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 46825,
        "commit_id": "34154803ac73d62d3e969e480405df3073032622",
        "repo": "airflow",
        "path": "airflow/models/taskmixin.py",
        "file_name": "taskmixin.py",
        "fun_name": "dag_id",
        "commit_message": "Show tasks in grid view based on topological sort. (#22741)\n\nThis takes the existing topological sort that existed on a DAG and moves\r\nit down to TaskGroup.\r\n\r\nIn order to do this (and not have duplicated sort) the existing sort on\r\nDAG is re-implemented on top of the new method.\r\n\r\nThis also surfaced a tiny bug in deserialize_task_group where the\r\nSerializedTaskGroup did not have `dag` set -- it didn't cause any\r\nproblems until now but was needed to call `upstream_list` on a\r\nSerializedTaskGroup object.",
        "code": "def dag_id(self) -> str:\n        \n        if self.dag:\n            return self.dag.dag_id\n        return \"_in_memory_dag_\"\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
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        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 9007,
        "documentation": {
            "docstring": "Returns dag id if it has one or an adhoc/meaningless ID",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 272922,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/layers/preprocessing/discretization.py",
        "file_name": "discretization.py",
        "fun_name": "compress",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def compress(summary, epsilon):\n    \n    # TODO(b/184863356): remove the numpy escape hatch here.\n    return tf.numpy_function(\n        lambda s: _compress_summary_numpy(s, epsilon), [summary], tf.float32\n    )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 39,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 49,
        "n_identifiers": 8,
        "d_id": 81077,
        "documentation": {
            "docstring": "Compress a summary to within `epsilon` accuracy.\n\n    The compression step is needed to keep the summary sizes small after merging,\n    and also used to return the final target boundaries. It finds the new bins\n    based on interpolating cumulative weight percentages from the large summary.\n    Taking the difference of the cumulative weights from the previous bin's\n    cumulative weight will give the new weight for that bin.\n\n    Args:\n        summary: 2D `np.ndarray` summary to be compressed.\n        epsilon: A `'float32'` that determines the approxmiate desired precision.\n\n    Returns:\n        A 2D `np.ndarray` that is a compressed summary. First column is the\n        interpolated partition values, the second is the weights (counts).\n    ",
            "n_words": 104,
            "vocab_size": 71,
            "n_whitespaces": 156,
            "language": "en"
        }
    },
    {
        "id": 269278,
        "commit_id": "2d1086447a25d281f9428832d046c473d80ad761",
        "repo": "keras",
        "path": "keras/applications/convnext.py",
        "file_name": "convnext.py",
        "fun_name": "Head",
        "commit_message": "Corrected preprocess_input docstring in regnet.py and convnext.py",
        "code": "def Head(num_classes=1000, name=None):\n    \n    if name is None:\n        name = str(backend.get_uid(\"head\"))\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 23,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 32,
        "n_ast_nodes": 49,
        "n_identifiers": 6,
        "d_id": 79999,
        "documentation": {
            "docstring": "Implementation of classification head of RegNet.\n\n  Args:\n    num_classes: number of classes for Dense layer\n    name: name prefix\n\n  Returns:\n    Classification head function.\n  ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 337462,
        "commit_id": "e5c17f36a8b5bf8b9478d416c4a80841a353fb19",
        "repo": "accelerate",
        "path": "src/accelerate/test_utils/testing.py",
        "file_name": "testing.py",
        "fun_name": "require_tpu",
        "commit_message": "Clean up tests + fix import (#330)",
        "code": "def require_tpu(test_case):\n    \n    return unittest.skipUnless(is_tpu_available(), \"test requires TPU\")(test_case)\n\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
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        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 121064,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires TPUs. These tests are skipped when there are no TPUs available.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 259201,
        "commit_id": "7f0006c8aad1a09621ad19c3db19c3ff0555a183",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/_encoders.py",
        "file_name": "_encoders.py",
        "fun_name": "_identify_infrequent",
        "commit_message": "ENH Adds infrequent categories to OneHotEncoder (#16018)\n\n* ENH Completely adds infrequent categories\r\n\r\n* STY Linting\r\n\r\n* STY Linting\r\n\r\n* DOC Improves wording\r\n\r\n* DOC Lint\r\n\r\n* BUG Fixes\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* DOC Uses math to description float min_frequency\r\n\r\n* DOC Adds comment regarding drop\r\n\r\n* BUG Fixes method name\r\n\r\n* DOC Clearer docstring\r\n\r\n* TST Adds more tests\r\n\r\n* FIX Fixes mege\r\n\r\n* CLN More pythonic\r\n\r\n* CLN Address comments\r\n\r\n* STY Flake8\r\n\r\n* CLN Address comments\r\n\r\n* DOC Fix\r\n\r\n* MRG\r\n\r\n* WIP\r\n\r\n* ENH Address comments\r\n\r\n* STY Fix\r\n\r\n* ENH Use functiion call instead of property\r\n\r\n* ENH Adds counts feature\r\n\r\n* CLN Rename variables\r\n\r\n* DOC More details\r\n\r\n* CLN Remove unneeded line\r\n\r\n* CLN Less lines is less complicated\r\n\r\n* CLN Less diffs\r\n\r\n* CLN Improves readiabilty\r\n\r\n* BUG Fix\r\n\r\n* CLN Address comments\r\n\r\n* TST Fix\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* CLN Move docstring to userguide\r\n\r\n* DOC Better wrapping\r\n\r\n* TST Adds test to handle_unknown='error'\r\n\r\n* ENH Spelling error in docstring\r\n\r\n* BUG Fixes counter with nan values\r\n\r\n* BUG Removes unneeded test\r\n\r\n* BUG Fixes issue\r\n\r\n* ENH Sync with main\r\n\r\n* DOC Correct settings\r\n\r\n* DOC Adds docstring\r\n\r\n* DOC Immprove user guide\r\n\r\n* DOC Move to 1.0\r\n\r\n* DOC Update docs\r\n\r\n* TST Remove test\r\n\r\n* DOC Update docstring\r\n\r\n* STY Linting\r\n\r\n* DOC Address comments\r\n\r\n* ENH Neater code\r\n\r\n* DOC Update explaination for auto\r\n\r\n* Update sklearn/preprocessing/_encoders.py\r\n\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\n\r\n* TST Uses docstring instead of comments\r\n\r\n* TST Remove call to fit\r\n\r\n* TST Spelling error\r\n\r\n* ENH Adds support for drop + infrequent categories\r\n\r\n* ENH Adds infrequent_if_exist option\r\n\r\n* DOC Address comments for user guide\r\n\r\n* DOC Address comments for whats_new\r\n\r\n* DOC Update docstring based on comments\r\n\r\n* CLN Update test with suggestions\r\n\r\n* ENH Adds computed property infrequent_categories_\r\n\r\n* DOC Adds where the infrequent column is located\r\n\r\n* TST Adds more test for infrequent_categories_\r\n\r\n* DOC Adds docstring for _compute_drop_idx\r\n\r\n* CLN Moves _convert_to_infrequent_idx into its own method\r\n\r\n* TST Increases test coverage\r\n\r\n* TST Adds failing test\r\n\r\n* CLN Careful consideration of dropped and inverse_transform\r\n\r\n* STY Linting\r\n\r\n* DOC Adds docstrinb about dropping infrequent\r\n\r\n* DOC Uses only\r\n\r\n* DOC Numpydoc\r\n\r\n* TST Includes test for get_feature_names_out\r\n\r\n* DOC Move whats new\r\n\r\n* DOC Address docstring comments\r\n\r\n* DOC Docstring changes\r\n\r\n* TST Better comments\r\n\r\n* TST Adds check for handle_unknown='ignore' for infrequent\r\n\r\n* CLN Make _infrequent_indices private\r\n\r\n* CLN Change min_frequency default to None\r\n\r\n* DOC Adds comments\r\n\r\n* ENH adds support for max_categories=1\r\n\r\n* ENH Describe lexicon ordering for ties\r\n\r\n* DOC Better docstring\r\n\r\n* STY Fix\r\n\r\n* CLN Error when explicity dropping an infrequent category\r\n\r\n* STY Grammar\r\n\r\nCo-authored-by: Joel Nothman <joel.nothman@gmail.com>\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def _identify_infrequent(self, category_count, n_samples, col_idx):\n        \n        if isinstance(self.min_frequency, numbers.Integral):\n            infrequent_mask = category_count < self.min_frequency\n        elif isinstance(self.min_frequency, numbers.Real):\n            min_frequency_abs = n_samples * self.min_frequency\n            infrequent_mask = category_count < min_frequency_abs\n        else:\n            infrequent_mask = np.zeros(category_count.shape[0], dtype=bool)\n\n        n_current_features = category_count.size - infrequent_mask.sum() + 1\n        if self.max_categories is not None and self.max_categories < n_current_features:\n            # stable sort to preserve original count order\n            smallest_levels = np.argsort(category_count, kind=\"mergesort\")[\n                : -self.max_categories + 1\n            ]\n            infrequent_mask[smallest_levels] = True\n\n        output = np.flatnonzero(infrequent_mask)\n        return output if output.size > 0 else None\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 237,
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        "nloc": 16,
        "token_counts": 146,
        "n_ast_nodes": 227,
        "n_identifiers": 26,
        "d_id": 75639,
        "documentation": {
            "docstring": "Compute the infrequent indices.\n\n        Parameters\n        ----------\n        category_count : ndarray of shape (n_cardinality,)\n            Category counts.\n\n        n_samples : int\n            Number of samples.\n\n        col_idx : int\n            Index of the current category. Only used for the error message.\n\n        Returns\n        -------\n        output : ndarray of shape (n_infrequent_categories,) or None\n            If there are infrequent categories, indices of infrequent\n            categories. Otherwise None.\n        ",
            "n_words": 55,
            "vocab_size": 41,
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            "language": "en"
        }
    },
    {
        "id": 143428,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/env/wrappers/tests/test_unity3d_env.py",
        "file_name": "test_unity3d_env.py",
        "fun_name": "test_port_editor",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_port_editor(self, mock_unity3d):\n        \n\n        _ = Unity3DEnv(port=None)\n        args, kwargs = mock_unity3d.call_args\n        mock_unity3d.assert_called_once()\n        self.assertEqual(5004, kwargs.get(\"base_port\"))\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "n_ast_nodes": 70,
        "n_identifiers": 12,
        "d_id": 32988,
        "documentation": {
            "docstring": "Test if the environment uses the editor port\n        when no environment file is provided",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 72986,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/forms.py",
        "file_name": "forms.py",
        "fun_name": "get_create_field_function",
        "commit_message": "Reformat with black",
        "code": "def get_create_field_function(self, type):\n        \n        create_field_function = getattr(self, \"create_%s_field\" % type, None)\n        if create_field_function:\n            return create_field_function\n        else:\n            import inspect\n\n            method_list = [\n                f[0]\n                for f in inspect.getmembers(self.__class__, inspect.isfunction)\n                if f[0].startswith(\"create_\") and f[0].endswith(\"_field\")\n            ]\n            raise AttributeError(\n                \"Could not find function matching format \\\n                create_<fieldname>_field for type: \"\n                + type,\n                \"Must be one of: \" + \", \".join(method_list),\n            )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 254,
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        "token_counts": 89,
        "n_ast_nodes": 149,
        "n_identifiers": 15,
        "d_id": 15920,
        "documentation": {
            "docstring": "\n        Takes string of field type and returns a Django Form Field Instance.\n        Assumes form field creation functions are in the format:\n        'create_fieldtype_field'\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 75104,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/rich_text/contentstate.py",
        "file_name": "contentstate.py",
        "fun_name": "image_entity",
        "commit_message": "Reformat with black",
        "code": "def image_entity(props):\n    \n    return DOM.create_element(\n        \"embed\",\n        {\n            \"embedtype\": \"image\",\n            \"format\": props.get(\"format\"),\n            \"id\": props.get(\"id\"),\n            \"alt\": props.get(\"alt\"),\n        },\n    )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 90,
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        "n_identifiers": 5,
        "d_id": 16356,
        "documentation": {
            "docstring": "\n    Helper to construct elements of the form\n    <embed alt=\"Right-aligned image\" embedtype=\"image\" format=\"right\" id=\"1\"/>\n    when converting from contentstate data\n    ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 196419,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/solvers/bivariate.py",
        "file_name": "bivariate.py",
        "fun_name": "_linab",
        "commit_message": "Moved imports to higher level",
        "code": "def _linab(arg, symbol):\n    \n    arg = factor_terms(arg.expand())\n    ind, dep = arg.as_independent(symbol)\n    if arg.is_Mul and dep.is_Add:\n        a, b, x = _linab(dep, symbol)\n        return ind*a, ind*b, x\n    if not arg.is_Add:\n        b = 0\n        a, x = ind, dep\n    else:\n        b = ind\n        a, x = separatevars(dep).as_independent(symbol, as_Add=False)\n    if x.could_extract_minus_sign():\n        a = -a\n        x = -x\n    return a, b, x\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 136,
        "n_words": 56,
        "vocab_size": 33,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 118,
        "n_ast_nodes": 188,
        "n_identifiers": 16,
        "d_id": 47919,
        "documentation": {
            "docstring": "Return ``a, b, X`` assuming ``arg`` can be written as ``a*X + b``\n    where ``X`` is a symbol-dependent factor and ``a`` and ``b`` are\n    independent of ``symbol``.\n\n    Examples\n    ========\n\n    >>> from sympy.solvers.bivariate import _linab\n    >>> from sympy.abc import x, y\n    >>> from sympy import exp, S\n    >>> _linab(S(2), x)\n    (2, 0, 1)\n    >>> _linab(2*x, x)\n    (2, 0, x)\n    >>> _linab(y + y*x + 2*x, x)\n    (y + 2, y, x)\n    >>> _linab(3 + 2*exp(x), x)\n    (2, 3, exp(x))\n    ",
            "n_words": 78,
            "vocab_size": 55,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 267520,
        "commit_id": "34f8168afc1d7047c47adec3730c591a58f4f899",
        "repo": "ansible",
        "path": "lib/ansible/cli/console.py",
        "file_name": "console.py",
        "fun_name": "__getattr__",
        "commit_message": "ansible-console fixes (#78064)\n\n* list collection task actions too\r\n* dynamically add execute/help functions when module is found\r\n* handle redirection and short names",
        "code": "def __getattr__(self, name):\n        \n        attr = None\n\n        if name.startswith('do_'):\n            module = name.replace('do_', '')\n            if module_loader.find_plugin(module):\n                setattr(self, name, lambda arg, module=module: self.default(module + ' ' + arg))\n                attr = object.__getattr__(self, name)\n        elif name.startswith('help_'):\n            module = name.replace('help_', '')\n            if module_loader.find_plugin(module):\n                setattr(self, name, lambda module=module: self.helpdefault(module))\n                attr = object.__getattr__(self, name)\n\n        if attr is None:\n            raise AttributeError(f\"{self.__class__} does not have a {name} attribute\")\n\n        return attr\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 217,
        "n_words": 60,
        "vocab_size": 38,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 138,
        "n_ast_nodes": 240,
        "n_identifiers": 16,
        "d_id": 78939,
        "documentation": {
            "docstring": " handle not found to populate dynamically a module function if module matching name exists ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 247541,
        "commit_id": "32c828d0f760492711a98b11376e229d795fd1b3",
        "repo": "synapse",
        "path": "tests/rest/media/v1/test_url_preview.py",
        "file_name": "test_url_preview.py",
        "fun_name": "test_blacklisted_ip_specific",
        "commit_message": "Add type hints to `tests/rest`. (#12208)\n\nCo-authored-by: Patrick Cloke <clokep@users.noreply.github.com>",
        "code": "def test_blacklisted_ip_specific(self) -> None:\n        \n        self.lookups[\"example.com\"] = [(IPv4Address, \"192.168.1.1\")]\n\n        channel = self.make_request(\n            \"GET\", \"preview_url?url=http://example.com\", shorthand=False\n        )\n\n        # No requests made.\n        self.assertEqual(len(self.reactor.tcpClients), 0)\n        self.assertEqual(channel.code, 502)\n        self.assertEqual(\n            channel.json_body,\n            {\n                \"errcode\": \"M_UNKNOWN\",\n                \"error\": \"DNS resolution failure during URL preview generation\",\n            },\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 175,
        "n_words": 38,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 81,
        "n_ast_nodes": 139,
        "n_identifiers": 13,
        "d_id": 71729,
        "documentation": {
            "docstring": "\n        Blacklisted IP addresses, found via DNS, are not spidered.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 206254,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/defaulttags.py",
        "file_name": "defaulttags.py",
        "fun_name": "verbatim",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def verbatim(parser, token):\n    \n    nodelist = parser.parse((\"endverbatim\",))\n    parser.delete_first_token()\n    return VerbatimNode(nodelist.render(Context()))\n\n\n@register.tag",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 21,
        "n_words": 10,
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        "complexity": 1,
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        "token_counts": 36,
        "n_ast_nodes": 70,
        "n_identifiers": 11,
        "d_id": 51443,
        "documentation": {
            "docstring": "\n    Stop the template engine from rendering the contents of this block tag.\n\n    Usage::\n\n        {% verbatim %}\n            {% don't process this %}\n        {% endverbatim %}\n\n    You can also designate a specific closing tag block (allowing the\n    unrendered use of ``{% endverbatim %}``)::\n\n        {% verbatim myblock %}\n            ...\n        {% endverbatim myblock %}\n    ",
            "n_words": 50,
            "vocab_size": 33,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 201942,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/bulk_create/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_large_batch_mixed_efficiency",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_large_batch_mixed_efficiency(self):\n        \n        with override_settings(DEBUG=True):\n            connection.queries_log.clear()\n            TwoFields.objects.bulk_create(\n                [\n                    TwoFields(id=i if i % 2 == 0 else None, f1=i, f2=i + 1)\n                    for i in range(100000, 101000)\n                ]\n            )\n            self.assertLess(len(connection.queries), 10)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 155,
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        "complexity": 3,
        "nloc": 10,
        "token_counts": 76,
        "n_ast_nodes": 120,
        "n_identifiers": 18,
        "d_id": 50024,
        "documentation": {
            "docstring": "\n        Test inserting a large batch with objects having primary key set\n        mixed together with objects without PK set.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 47650,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/operators/test_subdag_operator.py",
        "file_name": "test_subdag_operator.py",
        "fun_name": "test_subdag_pools",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def test_subdag_pools(self):\n        \n        dag = DAG('parent', default_args=default_args)\n        subdag = DAG('parent.child', default_args=default_args)\n\n        session = airflow.settings.Session()\n        pool_1 = airflow.models.Pool(pool='test_pool_1', slots=1)\n        pool_10 = airflow.models.Pool(pool='test_pool_10', slots=10)\n        session.add(pool_1)\n        session.add(pool_10)\n        session.commit()\n\n        EmptyOperator(task_id='dummy', dag=subdag, pool='test_pool_1')\n\n        with pytest.raises(AirflowException):\n            SubDagOperator(task_id='child', dag=dag, subdag=subdag, pool='test_pool_1')\n\n        # recreate dag because failed subdagoperator was already added\n        dag = DAG('parent', default_args=default_args)\n        SubDagOperator(task_id='child', dag=dag, subdag=subdag, pool='test_pool_10')\n\n        session.delete(pool_1)\n        session.delete(pool_10)\n        session.commit()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 183,
        "n_words": 53,
        "vocab_size": 38,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 169,
        "n_ast_nodes": 287,
        "n_identifiers": 25,
        "d_id": 9191,
        "documentation": {
            "docstring": "\n        Subdags and subdag tasks can't both have a pool with 1 slot\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 259435,
        "commit_id": "75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc",
        "repo": "scikit-learn",
        "path": "sklearn/_loss/tests/test_loss.py",
        "file_name": "test_loss.py",
        "fun_name": "test_loss_of_perfect_prediction",
        "commit_message": "ENH migrate GLMs / TweedieRegressor to linear loss (#22548)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def test_loss_of_perfect_prediction(loss, sample_weight):\n    \n    if not loss.is_multiclass:\n        # Use small values such that exp(value) is not nan.\n        raw_prediction = np.array([-10, -0.1, 0, 0.1, 3, 10])\n        # If link is identity, we must respect the interval of y_pred:\n        if isinstance(loss.link, IdentityLink):\n            eps = 1e-10\n            low = loss.interval_y_pred.low\n            if not loss.interval_y_pred.low_inclusive:\n                low = low + eps\n            high = loss.interval_y_pred.high\n            if not loss.interval_y_pred.high_inclusive:\n                high = high - eps\n            raw_prediction = np.clip(raw_prediction, low, high)\n        y_true = loss.link.inverse(raw_prediction)\n    else:\n        # HalfMultinomialLoss\n        y_true = np.arange(loss.n_classes).astype(float)\n        # raw_prediction with entries -exp(10), but +exp(10) on the diagonal\n        # this is close enough to np.inf which would produce nan\n        raw_prediction = np.full(\n            shape=(loss.n_classes, loss.n_classes),\n            fill_value=-np.exp(10),\n            dtype=float,\n        )\n        raw_prediction.flat[:: loss.n_classes + 1] = np.exp(10)\n\n    if sample_weight == \"range\":\n        sample_weight = np.linspace(1, y_true.shape[0], num=y_true.shape[0])\n\n    loss_value = loss.loss(\n        y_true=y_true,\n        raw_prediction=raw_prediction,\n        sample_weight=sample_weight,\n    )\n    constant_term = loss.constant_to_optimal_zero(\n        y_true=y_true, sample_weight=sample_weight\n    )\n    # Comparing loss_value + constant_term to zero would result in large\n    # round-off errors.\n    assert_allclose(loss_value, -constant_term, atol=1e-14, rtol=1e-15)\n\n\n@pytest.mark.parametrize(\"loss\", LOSS_INSTANCES, ids=loss_instance_name)\n@pytest.mark.parametrize(\"sample_weight\", [None, \"range\"])",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"loss\", LOSS_INSTANCES, ids=loss_instance_name)\n@pytest.mark.parametrize(\"sample_weight\", [None, \"range\"])",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 438,
        "n_words": 159,
        "vocab_size": 110,
        "complexity": 6,
        "nloc": 32,
        "token_counts": 266,
        "n_ast_nodes": 446,
        "n_identifiers": 43,
        "d_id": 75769,
        "documentation": {
            "docstring": "Test value of perfect predictions.\n\n    Loss of y_pred = y_true plus constant_to_optimal_zero should sums up to\n    zero.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 109381,
        "commit_id": "a17f4f3bd63e3ca3754f96d7db4ce5197720589b",
        "repo": "matplotlib",
        "path": "lib/matplotlib/pyplot.py",
        "file_name": "pyplot.py",
        "fun_name": "set_cmap",
        "commit_message": "MNT: convert tests and internal usage way from using mpl.cm.get_cmap",
        "code": "def set_cmap(cmap):\n    \n    cmap = colormaps[cmap]\n\n    rc('image', cmap=cmap.name)\n    im = gci()\n\n    if im is not None:\n        im.set_cmap(cmap)\n\n\n@_copy_docstring_and_deprecators(matplotlib.image.imread)",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "@_copy_docstring_and_deprecators(matplotlib.image.imread)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 38,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 82,
        "n_identifiers": 11,
        "d_id": 23562,
        "documentation": {
            "docstring": "\n    Set the default colormap, and applies it to the current image if any.\n\n    Parameters\n    ----------\n    cmap : `~matplotlib.colors.Colormap` or str\n        A colormap instance or the name of a registered colormap.\n\n    See Also\n    --------\n    colormaps\n    matplotlib.cm.register_cmap\n    matplotlib.cm.get_cmap\n    ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 241581,
        "commit_id": "650c710efacd633fa283955145342bb64063c883",
        "repo": "lightning",
        "path": "tests/strategies/test_sharded_strategy.py",
        "file_name": "test_sharded_strategy.py",
        "fun_name": "test_ddp_sharded_strategy_fit_ckpt_path",
        "commit_message": "Rename training plugin test files & names to strategy (#11303)",
        "code": "def test_ddp_sharded_strategy_fit_ckpt_path(tmpdir):\n    \n    model = BoringModel()\n    trainer = Trainer(strategy=\"ddp_sharded_spawn\", num_processes=2, fast_dev_run=True)\n\n    trainer.fit(model)\n\n    checkpoint_path = os.path.join(tmpdir, \"model.pt\")\n    trainer.save_checkpoint(checkpoint_path)\n\n    model = BoringModel()\n\n    trainer = Trainer(strategy=\"ddp_sharded_spawn\", num_processes=2, fast_dev_run=True)\n\n    trainer.fit(model, ckpt_path=checkpoint_path)\n\n\n@pytest.mark.skip(reason=\"Not a critical test, skip till drone CI performance improves.\")  # todo\n@pytest.mark.skip(reason=\"Currently unsupported restarting training on different number of devices.\")\n@RunIf(min_gpus=2, skip_windows=True, fairscale=True)",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.skip(reason=\"Not a critical test, skip till drone CI performance improves.\")  # todo\n@pytest.mark.skip(reason=\"Currently unsupported restarting training on different number of devices.\")\n@RunIf(min_gpus=2, skip_windows=True, fairscale=True)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 75,
        "n_words": 50,
        "vocab_size": 40,
        "complexity": 1,
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        "n_identifiers": 24,
        "d_id": 69606,
        "documentation": {
            "docstring": "Test to ensure that resuming from checkpoint works.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 63100,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_provider",
        "commit_message": "upd; format",
        "code": "def get_provider(moduleOrReq):\n    \n    if isinstance(moduleOrReq, Requirement):\n        return working_set.find(moduleOrReq) or require(str(moduleOrReq))[0]\n    try:\n        module = sys.modules[moduleOrReq]\n    except KeyError:\n        __import__(moduleOrReq)\n        module = sys.modules[moduleOrReq]\n    loader = getattr(module, '__loader__', None)\n    return _find_adapter(_provider_factories, loader)(module)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 73,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 77,
        "n_ast_nodes": 124,
        "n_identifiers": 17,
        "d_id": 13146,
        "documentation": {
            "docstring": "Return an IResourceProvider for the named module or requirement",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 44167,
        "commit_id": "ff3bbc3db24f9f3f4f88033d48859fb08fc3237b",
        "repo": "airflow",
        "path": "airflow/models/base.py",
        "file_name": "base.py",
        "fun_name": "get_template_env",
        "commit_message": "Implement enough interface for MappedOperator to be baggable (#20945)",
        "code": "def get_template_env(self) -> jinja2.Environment:\n        \n        dag = self.get_dag()\n        if dag:\n            return dag.get_template_env()\n        return SandboxedEnvironment(cache_size=0)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 52,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 8,
        "d_id": 8186,
        "documentation": {
            "docstring": "Fetch a Jinja template environment from the DAG or instantiate empty environment if no DAG.",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 204312,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/sessions/backends/signed_cookies.py",
        "file_name": "signed_cookies.py",
        "fun_name": "load",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def load(self):\n        \n        try:\n            return signing.loads(\n                self.session_key,\n                serializer=self.serializer,\n                # This doesn't handle non-default expiry dates, see #19201\n                max_age=self.get_session_cookie_age(),\n                salt=\"django.contrib.sessions.backends.signed_cookies\",\n            )\n        except Exception:\n            # BadSignature, ValueError, or unpickling exceptions. If any of\n            # these happen, reset the session.\n            self.create()\n        return {}\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 197,
        "n_words": 39,
        "vocab_size": 36,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 47,
        "n_ast_nodes": 81,
        "n_identifiers": 11,
        "d_id": 50693,
        "documentation": {
            "docstring": "\n        Load the data from the key itself instead of fetching from some\n        external data store. Opposite of _get_session_key(), raise BadSignature\n        if signature fails.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 217427,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ftplib.py",
        "file_name": "ftplib.py",
        "fun_name": "mlsd",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def mlsd(self, path=\"\", facts=[]):\n        \n        if facts:\n            self.sendcmd(\"OPTS MLST \" + \";\".join(facts) + \";\")\n        if path:\n            cmd = \"MLSD %s\" % path\n        else:\n            cmd = \"MLSD\"\n        lines = []\n        self.retrlines(cmd, lines.append)\n        for line in lines:\n            facts_found, _, name = line.rstrip(CRLF).partition(' ')\n            entry = {}\n            for fact in facts_found[:-1].split(\";\"):\n                key, _, value = fact.partition(\"=\")\n                entry[key.lower()] = value\n            yield (name, entry)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 214,
        "n_words": 58,
        "vocab_size": 45,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 129,
        "n_ast_nodes": 222,
        "n_identifiers": 23,
        "d_id": 54776,
        "documentation": {
            "docstring": "List a directory in a standardized format by using MLSD\n        command (RFC-3659). If path is omitted the current directory\n        is assumed. \"facts\" is a list of strings representing the type\n        of information desired (e.g. [\"type\", \"size\", \"perm\"]).\n\n        Return a generator object yielding a tuple of two elements\n        for every file found in path.\n        First element is the file name, the second one is a dictionary\n        including a variable number of \"facts\" depending on the server\n        and whether \"facts\" argument has been provided.\n        ",
            "n_words": 82,
            "vocab_size": 60,
            "n_whitespaces": 145,
            "language": "en"
        }
    },
    {
        "id": 147576,
        "commit_id": "2eaa54bd763ae0e63158ae0d939633c804394b78",
        "repo": "ray",
        "path": "rllib/agents/trainer_config.py",
        "file_name": "trainer_config.py",
        "fun_name": "callbacks",
        "commit_message": "[RLlib] POC: Config objects instead of dicts (PPO only). (#23491)",
        "code": "def callbacks(self, callbacks_class) -> \"TrainerConfig\":\n        \n        self.callbacks_class = callbacks_class\n\n        return self\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 17,
        "n_ast_nodes": 31,
        "n_identifiers": 3,
        "d_id": 34012,
        "documentation": {
            "docstring": "Sets the callbacks configuration.\n\n        Args:\n            callbacks_class: Callbacks class, whose methods will be run during\n                various phases of training and environment sample collection.\n                See the `DefaultCallbacks` class and\n                `examples/custom_metrics_and_callbacks.py` for more usage information.\n\n        Returns:\n            This updated TrainerConfig object.\n        ",
            "n_words": 37,
            "vocab_size": 35,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 284582,
        "commit_id": "a6f7e111e68346aeab315985b3704c2710693b38",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/due_diligence/dd_controller.py",
        "file_name": "dd_controller.py",
        "fun_name": "print_help",
        "commit_message": "Bounty Hunter mood: 11 bugs fixed (#1853)\n\n* fix #1850\r\n\r\n* fix #1831\r\n\r\n* add extra check to Reddit API keys\r\n\r\n* ignore warning message to update praw api\r\n\r\n* improve OpenBB links\r\n\r\n* fix quick performance only on stocks class because I'm James bitch\r\n\r\n* fix quick performance only on stocks class because I'm James bitch\r\n\r\n* fix #1829\r\n\r\n* fix #1821\r\n\r\n* add messari to keys - fix #1819\r\n\r\n* example of multiple oclumns to check on options/chains\r\n\r\n* minor improvement in xlabel re. #1814\r\n\r\n* remove repeated command\r\n\r\n* fix #1698\r\n\r\n* fix line too long\r\n\r\n* fix #1814 fr now\r\n\r\n* fix tests",
        "code": "def print_help(self):\n        \n        source_txt = CRYPTO_SOURCES.get(self.source, \"?\") if self.source != \"\" else \"\"\n        help_text = f\n        console.print(text=help_text, menu=\"Crypto - Due Diligence\")\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 48,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 56,
        "token_counts": 42,
        "n_ast_nodes": 86,
        "n_identifiers": 12,
        "d_id": 84832,
        "documentation": {
            "docstring": "Print help[cmds]\n    load             load a specific cryptocurrency for analysis\n\n[param]Coin: [/param]{self.coin}\n[param]Source: [/param]{source_txt}\n\n[src]CoinGecko[/src]\n    info             basic information about loaded coin\n    market           market stats about loaded coin\n    ath              all time high related stats for loaded coin\n    atl              all time low related stats for loaded coin\n    web              found websites for loaded coin e.g forum, homepage\n    social           social portals urls for loaded coin, e.g reddit, twitter\n    score            different kind of scores for loaded coin, e.g developer score, sentiment score\n    dev              github, bitbucket coin development statistics\n    bc               links to blockchain explorers for loaded coin\n[src]Glassnode[/src]\n    active           active addresses\n    nonzero          addresses with non-zero balances\n    change           30d change of supply held on exchange wallets\n    eb               total balance held on exchanges (in percentage and units)\n[src]Coinglass[/src]\n    oi               open interest per exchange\n[src]CoinPaprika[/src]\n    basic            basic information about loaded coin\n    ps               price and supply related metrics for loaded coin\n    mkt              all markets for loaded coin\n    ex               all exchanges where loaded coin is listed\n    twitter          tweets for loaded coin\n    events           events related to loaded coin\n[src]Binance[/src]\n    binbook          order book\n    balance          coin balance\n[src]Coinbase[/src]\n    cbbook           order book\n    trades           last trades\n    stats            coin stats\n[src]Messari[/src]\n    mcapdom          market cap dominance\n    mt               messari timeseries e.g. twitter followers, circ supply, etc\n    rm               roadmap\n    tk               tokenomics e.g. circulating/max/total supply, emission type, etc\n    pi               project information e.g. technology details, public repos, audits, vulns\n    team             contributors (individuals and organizations)\n    inv              investors (individuals and organizations)\n    gov              governance details\n    fr               fundraising details e.g. treasury accounts, sales rounds, allocation\n    links            links e.g. whitepaper, github, twitter, youtube, reddit, telegram\n[src]Santiment[/src]\n    gh               github activity over time\n[src]CryptoPanic[/src]\n    news             loaded coin's most recent news[/cmds]\n",
            "n_words": 260,
            "vocab_size": 163,
            "n_whitespaces": 814,
            "language": "en"
        }
    },
    {
        "id": 31263,
        "commit_id": "a72f1c9f5b907f96cbb7de3bbb02a1d431d34071",
        "repo": "transformers",
        "path": "src/transformers/models/longt5/modeling_flax_longt5.py",
        "file_name": "modeling_flax_longt5.py",
        "fun_name": "__call__",
        "commit_message": "Add `LongT5` model (#16792)\n\n* Initial commit\r\n\r\n* Make some fixes\r\n\r\n* Make PT model full forward pass\r\n\r\n* Drop TF & Flax implementation, fix copies etc\r\n\r\n* Add Flax model and update some corresponding stuff\r\n\r\n* Drop some TF things\r\n\r\n* Update config and flax local attn\r\n\r\n* Add encoder_attention_type to config\r\n\r\n* .\r\n\r\n* Update docs\r\n\r\n* Do some cleansing\r\n\r\n* Fix some issues -> make style; add some docs\r\n\r\n* Fix position_bias + mask addition + Update tests\r\n\r\n* Fix repo consistency\r\n\r\n* Fix model consistency by removing flax operation over attn_mask\r\n\r\n* [WIP] Add PT TGlobal LongT5\r\n\r\n* .\r\n\r\n* [WIP] Add flax tglobal model\r\n\r\n* [WIP] Update flax model to use the right attention type in the encoder\r\n\r\n* Fix flax tglobal model forward pass\r\n\r\n* Make the use of global_relative_attention_bias\r\n\r\n* Add test suites for TGlobal model\r\n\r\n* Fix minor bugs, clean code\r\n\r\n* Fix pt-flax equivalence though not convinced with correctness\r\n\r\n* Fix LocalAttn implementation to match the original impl. + update READMEs\r\n\r\n* Few updates\r\n\r\n* Update: [Flax] improve large model init and loading #16148\r\n\r\n* Add ckpt conversion script accoring to #16853 + handle torch device placement\r\n\r\n* Minor updates to conversion script.\r\n\r\n* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM\r\n\r\n* gpu support + dtype fix\r\n\r\n* Apply some suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* * Remove (de)parallelize stuff\r\n* Edit shape comments\r\n* Update README.md\r\n* make fix-copies\r\n\r\n* Remove caching logic for local & tglobal attention\r\n\r\n* Apply another batch of suggestions from code review\r\n\r\n* Add missing checkpoints\r\n* Format converting scripts\r\n* Drop (de)parallelize links from longT5 mdx\r\n\r\n* Fix converting script + revert config file change\r\n\r\n* Revert \"Remove caching logic for local & tglobal attention\"\r\n\r\nThis reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.\r\n\r\n* Stash caching logic in Flax model\r\n\r\n* Make side relative bias used always\r\n\r\n* Drop caching logic in PT model\r\n\r\n* Return side bias as it was\r\n\r\n* Drop all remaining model parallel logic\r\n\r\n* Remove clamp statements\r\n\r\n* Move test files to the proper place\r\n\r\n* Update docs with new version of hf-doc-builder\r\n\r\n* Fix test imports\r\n\r\n* Make some minor improvements\r\n\r\n* Add missing checkpoints to docs\r\n* Make TGlobal model compatible with torch.onnx.export\r\n* Replace some np.ndarray with jnp.ndarray\r\n\r\n* Fix TGlobal for ONNX conversion + update docs\r\n\r\n* fix _make_global_fixed_block_ids and masked neg  value\r\n\r\n* update flax model\r\n\r\n* style and quality\r\n\r\n* fix imports\r\n\r\n* remove load_tf_weights_in_longt5 from init and fix copies\r\n\r\n* add slow test for TGlobal model\r\n\r\n* typo fix\r\n\r\n* Drop obsolete is_parallelizable and one warning\r\n\r\n* Update __init__ files to fix repo-consistency\r\n\r\n* fix pipeline test\r\n\r\n* Fix some device placements\r\n\r\n* [wip]: Update tests -- need to generate summaries to update expected_summary\r\n\r\n* Fix quality\r\n\r\n* Update LongT5 model card\r\n\r\n* Update (slow) summarization tests\r\n\r\n* make style\r\n\r\n* rename checkpoitns\r\n\r\n* finish\r\n\r\n* fix flax tests\r\n\r\nCo-authored-by: phungvanduy <pvduy23@gmail.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\nCo-authored-by: patil-suraj <surajp815@gmail.com>",
        "code": "def __call__(self, hidden_states):\n        \n        # layer norm should always be calculated in float32\n        variance = jnp.power(hidden_states.astype(\"f4\"), 2).mean(axis=-1, keepdims=True)\n        hidden_states = hidden_states / jnp.sqrt(variance + self.eps)\n\n        return self.weight * hidden_states\n\n\n# Copied from transformers.models.t5.modeling_flax_t5.FlaxT5DenseActDense with T5->LongT5",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 68,
        "n_words": 34,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 55,
        "n_ast_nodes": 91,
        "n_identifiers": 13,
        "d_id": 5713,
        "documentation": {
            "docstring": "\n        Construct a layernorm module in the LongT5 style; No bias and no subtraction of mean.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 155618,
        "commit_id": "2a9d34aff0a38be5fc8bfcdec38e5c4a7bafcf0e",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "partitionwise_graph",
        "commit_message": "Move DataFrame ACA aggregations to HLG (#8468)",
        "code": "def partitionwise_graph(func, layer_name, *args, **kwargs):\n    \n    pairs = []\n    numblocks = {}\n    for arg in args:\n        if isinstance(arg, _Frame):\n            pairs.extend([arg._name, \"i\"])\n            numblocks[arg._name] = (arg.npartitions,)\n        elif isinstance(arg, Scalar):\n            pairs.extend([arg._name, \"i\"])\n            numblocks[arg._name] = (1,)\n        elif isinstance(arg, Array):\n            if arg.ndim == 1:\n                pairs.extend([arg.name, \"i\"])\n            elif arg.ndim == 0:\n                pairs.extend([arg.name, \"\"])\n            elif arg.ndim == 2:\n                pairs.extend([arg.name, \"ij\"])\n            else:\n                raise ValueError(\"Can't add multi-dimensional array to dataframes\")\n            numblocks[arg._name] = arg.numblocks\n        elif isinstance(arg, BlockwiseDep):\n            if len(arg.numblocks) == 1:\n                pairs.extend([arg, \"i\"])\n            elif len(arg.numblocks) == 2:\n                pairs.extend([arg, \"ij\"])\n            else:\n                raise ValueError(\n                    f\"BlockwiseDep arg {arg!r} has {len(arg.numblocks)} dimensions; only 1 or 2 are supported.\"\n                )\n        else:\n            pairs.extend([arg, None])\n    return blockwise(\n        func, layer_name, \"i\", *pairs, numblocks=numblocks, concatenate=True, **kwargs\n    )\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 449,
        "n_words": 107,
        "vocab_size": 67,
        "complexity": 11,
        "nloc": 34,
        "token_counts": 264,
        "n_ast_nodes": 437,
        "n_identifiers": 22,
        "d_id": 36437,
        "documentation": {
            "docstring": "\n    Apply a function partition-wise across arguments to create layer of a graph\n\n    This applies a function, ``func``, in an embarrassingly parallel fashion\n    across partitions/chunks in the provided arguments.  It handles Dataframes,\n    Arrays, and scalars smoothly, and relies on the ``blockwise`` machinery\n    to provide a nicely symbolic graph.\n\n    It is most commonly used in other graph-building functions to create the\n    appropriate layer of the resulting dataframe.\n\n    Parameters\n    ----------\n    func: callable\n    layer_name: str\n        Descriptive name for the operation. Used as the output name\n        in the resulting ``Blockwise`` graph layer.\n    *args:\n    **kwargs:\n\n    Returns\n    -------\n    out: Blockwise graph\n\n    Examples\n    --------\n    >>> subgraph = partitionwise_graph(function, x, y, z=123)  # doctest: +SKIP\n    >>> layer = partitionwise_graph(function, df, x, z=123)  # doctest: +SKIP\n    >>> graph = HighLevelGraph.from_collections(name, layer, dependencies=[df, x])  # doctest: +SKIP\n    >>> result = new_dd_object(graph, name, metadata, df.divisions)  # doctest: +SKIP\n\n    See Also\n    --------\n    map_partitions\n    ",
            "n_words": 140,
            "vocab_size": 95,
            "n_whitespaces": 238,
            "language": "en"
        }
    },
    {
        "id": 220825,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/tasks.py",
        "file_name": "tasks.py",
        "fun_name": "cancel",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def cancel(self, msg=None):\n        \n        self._log_traceback = False\n        if self.done():\n            return False\n        if self._fut_waiter is not None:\n            if self._fut_waiter.cancel(msg=msg):\n                # Leave self._fut_waiter; it may be a Task that\n                # catches and ignores the cancellation so we may have\n                # to cancel it again later.\n                return True\n        # It must be the case that self.__step is already scheduled.\n        self._must_cancel = True\n        self._cancel_message = msg\n        return True\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 201,
        "n_words": 63,
        "vocab_size": 45,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 58,
        "n_ast_nodes": 98,
        "n_identifiers": 8,
        "d_id": 56134,
        "documentation": {
            "docstring": "Request that this task cancel itself.\n\n        This arranges for a CancelledError to be thrown into the\n        wrapped coroutine on the next cycle through the event loop.\n        The coroutine then has a chance to clean up or even deny\n        the request using try/except/finally.\n\n        Unlike Future.cancel, this does not guarantee that the\n        task will be cancelled: the exception might be caught and\n        acted upon, delaying cancellation of the task or preventing\n        cancellation completely.  The task may also return a value or\n        raise a different exception.\n\n        Immediately after this method is called, Task.cancelled() will\n        not return True (unless the task was already cancelled).  A\n        task will be marked as cancelled when the wrapped coroutine\n        terminates with a CancelledError exception (even if cancel()\n        was not called).\n        ",
            "n_words": 122,
            "vocab_size": 83,
            "n_whitespaces": 229,
            "language": "en"
        }
    },
    {
        "id": 60671,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/configuration.py",
        "file_name": "configuration.py",
        "fun_name": "_dictionary",
        "commit_message": "upd; format",
        "code": "def _dictionary(self):\n        # type: () -> Dict[str, Any]\n        \n        # NOTE: Dictionaries are not populated if not loaded. So, conditionals\n        #       are not needed here.\n        retval = {}\n\n        for variant in OVERRIDE_ORDER:\n            retval.update(self._config[variant])\n\n        return retval\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 100,
        "n_words": 34,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 28,
        "n_ast_nodes": 50,
        "n_identifiers": 7,
        "d_id": 12237,
        "documentation": {
            "docstring": "A dictionary representing the loaded configuration.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 121058,
        "commit_id": "4e224bcfb99c3bd9b6a32b8ad7836d12517e788f",
        "repo": "jax",
        "path": "jax/experimental/jax2tf/impl_no_xla.py",
        "file_name": "impl_no_xla.py",
        "fun_name": "_transpose_for_tf_conv",
        "commit_message": "[jax2tf] Add support for common audio convolutions (1D variants, dilated depthwise, transpose with SAME padding).\n\nPiperOrigin-RevId: 458266485",
        "code": "def _transpose_for_tf_conv(lhs, rhs, dimension_numbers):\n  \n  # TODO(marcvanzee): Add tests for this ops for shape polymorphism.\n  lhs_perm, rhs_perm, _ = dimension_numbers\n\n  # TODO(marcvanzee): Consider merging tranposes if we want to optimize.\n  # For `lhs_perm` / `output_perm`, perm (0, 1, 2, 3) corresponds to \"NCHW\".\n  lhs = tf.transpose(lhs, lhs_perm)  # lhs --> \"NCHW\"\n  if len(lhs_perm) == 3:\n    # For 1D convolution, we add a trivial \"W\" dimension, so that 2D Convolution\n    # logic can be applied downstream.\n    lhs = lhs[:, :, :, np.newaxis]\n  # However, the TF ops only support \"NHWC\" on CPU, so we transpose again.\n  lhs = tf.transpose(lhs, (0, 2, 3, 1))  # \"NCHW\" --> \"NHWC\"\n\n  # For `rhs_perm`, perm (0, 1, 2, 3) corresponds to \"OIHW\".\n  rhs = tf.transpose(rhs, rhs_perm)  # rhs --> \"OIHW\"\n  # Handle conv1d case.\n  if len(rhs_perm) == 3:\n    rhs = rhs[:, :, :, np.newaxis]\n  # For the tf ops, rhs is expected to be \"OIHW\".\n  rhs = tf.transpose(rhs, (2, 3, 1, 0))  # \"OIHW\" --> \"HWIO\"\n  return lhs, rhs\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 195,
        "n_words": 163,
        "vocab_size": 96,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 121,
        "n_ast_nodes": 192,
        "n_identifiers": 12,
        "d_id": 27024,
        "documentation": {
            "docstring": "Tranposes lhs and rhs to respectively NHWC and HWIO so they can be passed to TF functions.",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 208740,
        "commit_id": "d858213d4088237e1481038865bc52ccdd074053",
        "repo": "ipython",
        "path": "IPython/lib/tests/test_pretty.py",
        "file_name": "test_pretty.py",
        "fun_name": "test_pprint_heap_allocated_type",
        "commit_message": "xxlimited_35 module now has the same name in repr in Py 3.11\n\nSee https://github.com/python/cpython/commit/a87c9b538fbfc42883417c4d5e69f1a5922690e3",
        "code": "def test_pprint_heap_allocated_type():\n    \n    module_name = \"xxlimited\" if sys.version_info < (3, 10) else \"xxlimited_35\"\n    expected_output = (\n        \"xxlimited.Null\" if sys.version_info < (3, 11) else \"xxlimited_35.Null\"\n    )\n    xxlimited = pytest.importorskip(module_name)\n    output = pretty.pretty(xxlimited.Null)\n    assert output == expected_output\n\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 62,
        "n_words": 34,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 59,
        "n_ast_nodes": 100,
        "n_identifiers": 11,
        "d_id": 52497,
        "documentation": {
            "docstring": "\n    Test that pprint works for heap allocated types.\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 250281,
        "commit_id": "652d1669c5a103b1c20478770c4aaf18849c09a3",
        "repo": "synapse",
        "path": "tests/handlers/test_e2e_room_keys.py",
        "file_name": "test_e2e_room_keys.py",
        "fun_name": "test_delete_missing_version",
        "commit_message": "Add missing type hints to tests.handlers. (#14680)\n\nAnd do not allow untyped defs in tests.handlers.",
        "code": "def test_delete_missing_version(self) -> None:\n        \n        e = self.get_failure(\n            self.handler.delete_version(self.local_user, \"1\"), SynapseError\n        )\n        res = e.value.code\n        self.assertEqual(res, 404)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 62,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 44,
        "n_ast_nodes": 72,
        "n_identifiers": 12,
        "d_id": 73359,
        "documentation": {
            "docstring": "Check that we get a 404 on deleting nonexistent versions",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 20087,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distro.py",
        "file_name": "distro.py",
        "fun_name": "name",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def name(self, pretty=False):\n        # type: (bool) -> str\n        \n        name = (\n            self.os_release_attr(\"name\")\n            or self.lsb_release_attr(\"distributor_id\")\n            or self.distro_release_attr(\"name\")\n            or self.uname_attr(\"name\")\n        )\n        if pretty:\n            name = self.os_release_attr(\"pretty_name\") or self.lsb_release_attr(\n                \"description\"\n            )\n            if not name:\n                name = self.distro_release_attr(\"name\") or self.uname_attr(\"name\")\n                version = self.version(pretty=True)\n                if version:\n                    name = name + \" \" + version\n        return name or \"\"\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 251,
        "n_words": 53,
        "vocab_size": 31,
        "complexity": 10,
        "nloc": 17,
        "token_counts": 102,
        "n_ast_nodes": 186,
        "n_identifiers": 8,
        "d_id": 3230,
        "documentation": {
            "docstring": "\n        Return the name of the OS distribution, as a string.\n\n        For details, see :func:`distro.name`.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 44997,
        "commit_id": "0ebd6428e6b484790bfbbe1b8687ef4e6cae10e9",
        "repo": "airflow",
        "path": "tests/serialization/test_dag_serialization.py",
        "file_name": "test_dag_serialization.py",
        "fun_name": "test_extra_serialized_field_and_multiple_operator_links",
        "commit_message": "Switch XCom implementation to use run_id (#20975)",
        "code": "def test_extra_serialized_field_and_multiple_operator_links(self, dag_maker):\n        \n        test_date = timezone.DateTime(2019, 8, 1, tzinfo=timezone.utc)\n        with dag_maker(dag_id='simple_dag', start_date=test_date) as dag:\n            CustomOperator(task_id='simple_task', bash_command=[\"echo\", \"true\"])\n\n        serialized_dag = SerializedDAG.to_dict(dag)\n        assert \"bash_command\" in serialized_dag[\"dag\"][\"tasks\"][0]\n\n        dag = SerializedDAG.from_dict(serialized_dag)\n        simple_task = dag.task_dict[\"simple_task\"]\n        assert getattr(simple_task, \"bash_command\") == [\"echo\", \"true\"]\n\n        #########################################################\n        # Verify Operator Links work with Serialized Operator\n        #########################################################\n        # Check Serialized version of operator link only contains the inbuilt Op Link\n        assert serialized_dag[\"dag\"][\"tasks\"][0][\"_operator_extra_links\"] == [\n            {'tests.test_utils.mock_operators.CustomBaseIndexOpLink': {'index': 0}},\n            {'tests.test_utils.mock_operators.CustomBaseIndexOpLink': {'index': 1}},\n        ]\n\n        # Test all the extra_links are set\n        assert set(simple_task.extra_links) == {\n            'BigQuery Console #1',\n            'BigQuery Console #2',\n            'airflow',\n            'github',\n            'google',\n        }\n\n        dag_maker.create_dagrun(execution_date=test_date)\n        XCom.set(\n            key='search_query',\n            value=[\"dummy_value_1\", \"dummy_value_2\"],\n            task_id=simple_task.task_id,\n            dag_id=simple_task.dag_id,\n            execution_date=test_date,\n        )\n\n        # Test Deserialized inbuilt link #1\n        custom_inbuilt_link = simple_task.get_extra_links(test_date, \"BigQuery Console #1\")\n        assert 'https://console.cloud.google.com/bigquery?j=dummy_value_1' == custom_inbuilt_link\n\n        # Test Deserialized inbuilt link #2\n        custom_inbuilt_link = simple_task.get_extra_links(test_date, \"BigQuery Console #2\")\n        assert 'https://console.cloud.google.com/bigquery?j=dummy_value_2' == custom_inbuilt_link\n\n        # Test Deserialized link registered via Airflow Plugin\n        google_link_from_plugin = simple_task.get_extra_links(test_date, GoogleLink.name)\n        assert \"https://www.google.com\" == google_link_from_plugin\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 494,
        "n_words": 148,
        "vocab_size": 98,
        "complexity": 1,
        "nloc": 34,
        "token_counts": 246,
        "n_ast_nodes": 430,
        "n_identifiers": 33,
        "d_id": 8435,
        "documentation": {
            "docstring": "\n        Assert extra field exists & OperatorLinks defined in Plugins and inbuilt Operator Links.\n\n        This tests also depends on GoogleLink() registered as a plugin\n        in tests/plugins/test_plugin.py\n\n        The function tests that if extra operator links are registered in plugin\n        in ``operator_extra_links`` and the same is also defined in\n        the Operator in ``BaseOperator.operator_extra_links``, it has the correct\n        extra link.\n        ",
            "n_words": 56,
            "vocab_size": 40,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 313595,
        "commit_id": "a0974e0c7297537149985f93544dd6f8ed8cfded",
        "repo": "core",
        "path": "homeassistant/components/lifx/light.py",
        "file_name": "light.py",
        "fun_name": "get_mac_addr",
        "commit_message": "Refactor LIFX discovery to prevent duplicate discovery response handling (#72213)\n\n* Partially revert #70458 and allow duplicate LIFX discoveries\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Only process one discovery at a time\r\n\r\n* Revert all LIFX duplicate/inflight discovery checks\r\n\r\nAlso remember LIFX Switches and do as little processing for them\r\nas possible.\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Bump aiolifx version to support the latest LIFX devices\r\n\r\nLIFX added 22 new product definitions to their public product\r\nlist at the end of January and those new products are defined in\r\naiolifx v0.8.1, so bump the dependency version.\r\n\r\nAlso switched to testing for relays instead of maintaining a\r\nseperate list of switch product IDs.\r\n\r\nFixes #72894.\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Refactor LIFX discovery to better handle duplicate responses\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Update clear_inflight_discovery with review suggestion\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Move the existing entity check to before the asyncio lock\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\n* Bail out of discovery early and if an entity was created\r\n\r\nAlso ensure that the entity always has a unique ID even if the bulb was\r\nnot successfully discovered.\r\n\r\nSigned-off-by: Avi Miller <me@dje.li>\r\n\r\nCo-authored-by: J. Nick Koston <nick@koston.org>",
        "code": "def get_mac_addr(self):\n        \n        if (\n            self.bulb.host_firmware_version\n            and AwesomeVersion(self.bulb.host_firmware_version) >= FIX_MAC_FW\n        ):\n            octets = [int(octet, 16) for octet in self.mac_addr.split(\":\")]\n            octets[5] = (octets[5] + 1) % 256\n            return \":\".join(f\"{octet:02x}\" for octet in octets)\n        return self.mac_addr\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 116,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 9,
        "token_counts": 78,
        "n_ast_nodes": 131,
        "n_identifiers": 12,
        "d_id": 112213,
        "documentation": {
            "docstring": "Increment the last byte of the mac address by one for FW>3.70.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 271550,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training.py",
        "file_name": "training.py",
        "fun_name": "metrics_names",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def metrics_names(self):\n        \n\n        # This property includes all output names including `loss` and per-output\n        # losses for backward compatibility.\n        return [m.name for m in self.metrics]\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 52,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 18,
        "n_ast_nodes": 32,
        "n_identifiers": 5,
        "d_id": 80791,
        "documentation": {
            "docstring": "Returns the model's display labels for all outputs.\n\n        Note: `metrics_names` are available only after a `keras.Model` has been\n        trained/evaluated on actual data.\n\n        Examples:\n\n        >>> inputs = tf.keras.layers.Input(shape=(3,))\n        >>> outputs = tf.keras.layers.Dense(2)(inputs)\n        >>> model = tf.keras.models.Model(inputs=inputs, outputs=outputs)\n        >>> model.compile(optimizer=\"Adam\", loss=\"mse\", metrics=[\"mae\"])\n        >>> model.metrics_names\n        []\n\n        >>> x = np.random.random((2, 3))\n        >>> y = np.random.randint(0, 2, (2, 2))\n        >>> model.fit(x, y)\n        >>> model.metrics_names\n        ['loss', 'mae']\n\n        >>> inputs = tf.keras.layers.Input(shape=(3,))\n        >>> d = tf.keras.layers.Dense(2, name='out')\n        >>> output_1 = d(inputs)\n        >>> output_2 = d(inputs)\n        >>> model = tf.keras.models.Model(\n        ...    inputs=inputs, outputs=[output_1, output_2])\n        >>> model.compile(optimizer=\"Adam\", loss=\"mse\", metrics=[\"mae\", \"acc\"])\n        >>> model.fit(x, (y, y))\n        >>> model.metrics_names\n        ['loss', 'out_loss', 'out_1_loss', 'out_mae', 'out_acc', 'out_1_mae',\n        'out_1_acc']\n\n        ",
            "n_words": 105,
            "vocab_size": 70,
            "n_whitespaces": 290,
            "language": "en"
        }
    },
    {
        "id": 155542,
        "commit_id": "dfdc4bbab43678927e30866f06df509483ac5d24",
        "repo": "dask",
        "path": "dask/highlevelgraph.py",
        "file_name": "highlevelgraph.py",
        "fun_name": "from_collections",
        "commit_message": "Collections with HLG must always implement __dask_layers__ (#8548)\n\nWithout ``__dask_layers__``, ``HighLevelGraph.from_collections`` will produce a broken layer dependency graph and things will fall apart down the line. Given this, it seems likely that no users should have the use case in production, so it should be safe not to have a deprecation cycle here.",
        "code": "def from_collections(cls, name, layer, dependencies=()):\n        \n        if len(dependencies) == 1:\n            return cls._from_collection(name, layer, dependencies[0])\n        layers = {name: layer}\n        deps = {name: set()}\n        for collection in toolz.unique(dependencies, key=id):\n            if is_dask_collection(collection):\n                graph = collection.__dask_graph__()\n                if isinstance(graph, HighLevelGraph):\n                    layers.update(graph.layers)\n                    deps.update(graph.dependencies)\n                    deps[name] |= set(collection.__dask_layers__())\n                else:\n                    key = _get_some_layer_name(collection)\n                    layers[key] = graph\n                    deps[name].add(key)\n                    deps[key] = set()\n            else:\n                raise TypeError(type(collection))\n\n        return cls(layers, deps)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 324,
        "n_words": 56,
        "vocab_size": 44,
        "complexity": 5,
        "nloc": 53,
        "token_counts": 165,
        "n_ast_nodes": 260,
        "n_identifiers": 26,
        "d_id": 36421,
        "documentation": {
            "docstring": "Construct a HighLevelGraph from a new layer and a set of collections\n\n        This constructs a HighLevelGraph in the common case where we have a single\n        new layer and a set of old collections on which we want to depend.\n\n        This pulls out the ``__dask_layers__()`` method of the collections if\n        they exist, and adds them to the dependencies for this new layer.  It\n        also merges all of the layers from all of the dependent collections\n        together into the new layers for this graph.\n\n        Parameters\n        ----------\n        name : str\n            The name of the new layer\n        layer : Mapping\n            The graph layer itself\n        dependencies : List of Dask collections\n            A list of other dask collections (like arrays or dataframes) that\n            have graphs themselves\n\n        Examples\n        --------\n\n        In typical usage we make a new task layer, and then pass that layer\n        along with all dependent collections to this method.\n\n        >>> def add(self, other):\n        ...     name = 'add-' + tokenize(self, other)\n        ...     layer = {(name, i): (add, input_key, other)\n        ...              for i, input_key in enumerate(self.__dask_keys__())}\n        ...     graph = HighLevelGraph.from_collections(name, layer, dependencies=[self])\n        ...     return new_collection(name, graph)\n        ",
            "n_words": 179,
            "vocab_size": 105,
            "n_whitespaces": 407,
            "language": "en"
        }
    },
    {
        "id": 116887,
        "commit_id": "cc6313a0f791ba42782082b1161b6a62578e45f4",
        "repo": "mindsdb",
        "path": "tests/unit/test_ml_handlers.py",
        "file_name": "test_ml_handlers.py",
        "fun_name": "test_hf_classification_bin",
        "commit_message": "fixed one line prediction for new ml handler api",
        "code": "def test_hf_classification_bin(self, mock_handler):\n\n\n        # create predictor\n        create_sql = \n\n        model_name = 'spam_classifier'\n\n        predict_sql = \n        self.hf_test_run(mock_handler, model_name, create_sql, predict_sql)\n\n        # one line prediction\n        predict_sql = \n        # use predictor\n        ret = self.command_executor.execute_command(parse_sql(predict_sql, dialect='mindsdb'))\n        assert ret.error_code is None\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 106,
        "n_words": 34,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 54,
        "n_ast_nodes": 98,
        "n_identifiers": 13,
        "d_id": 25865,
        "documentation": {
            "docstring": "\n            CREATE PREDICTOR huggingface.spam_classifier\n            predict PRED\n            USING\n                task='text-classification',\n                model_name= \"mrm8488/bert-tiny-finetuned-sms-spam-detection\",\n                input_column = 'text_spammy',\n                labels=['ham','spam']\n        \n            SELECT h.*\n            FROM pg.df as t \n            JOIN huggingface.spam_classifier as h\n        \n            SELECT * from huggingface.spam_classifier\n            where text_spammy= 'It is the best time to launch the Robot to get more money. https:\\\\/\\\\/Gof.bode-roesch.de\\\\/Gof'\n        ",
            "n_words": 43,
            "vocab_size": 37,
            "n_whitespaces": 216,
            "language": "en"
        }
    },
    {
        "id": 265476,
        "commit_id": "e96620260a6c1b5cf8cff2112d40d061984a7b2c",
        "repo": "netbox",
        "path": "netbox/netbox/denormalized.py",
        "file_name": "denormalized.py",
        "fun_name": "update_denormalized_fields",
        "commit_message": "Closes #9903: Implement a mechanism for automatically updating denormalized fields",
        "code": "def update_denormalized_fields(sender, instance, created, raw, **kwargs):\n    \n    # Skip for new objects or those being populated from raw data\n    if created or raw:\n        return\n\n    # Look up any denormalized fields referencing this model from the application registry\n    for model, field_name, mappings in registry['denormalized_fields'].get(sender, []):\n        logger.debug(f'Updating denormalized values for {model}.{field_name}')\n        filter_params = {\n            field_name: instance.pk,\n        }\n        update_params = {\n            # Map the denormalized field names to the instance's values\n            denorm: getattr(instance, origin) for denorm, origin in mappings.items()\n        }\n\n        # TODO: Improve efficiency here by placing conditions on the query?\n        # Update all the denormalized fields with the triggering object's new values\n        count = model.objects.filter(**filter_params).update(**update_params)\n        logger.debug(f'Updated {count} rows')\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 223,
        "n_words": 105,
        "vocab_size": 79,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 104,
        "n_ast_nodes": 180,
        "n_identifiers": 24,
        "d_id": 78111,
        "documentation": {
            "docstring": "\n    Check if the sender has denormalized fields registered, and update them as necessary.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 208820,
        "commit_id": "8a66e854a87b5147d811bd3bc92c5c2a382633e1",
        "repo": "ipython",
        "path": "IPython/extensions/autoreload.py",
        "file_name": "autoreload.py",
        "fun_name": "aimport",
        "commit_message": "Improve parsing for `%aimport`",
        "code": "def aimport(self, parameter_s=\"\", stream=None):\n        \n        modname = parameter_s\n        if not modname:\n            to_reload = sorted(self._reloader.modules.keys())\n            to_skip = sorted(self._reloader.skip_modules.keys())\n            if stream is None:\n                stream = sys.stdout\n            if self._reloader.check_all:\n                stream.write(\"Modules to reload:\\nall-except-skipped\\n\")\n            else:\n                stream.write(\"Modules to reload:\\n%s\\n\" % \" \".join(to_reload))\n            stream.write(\"\\nModules to skip:\\n%s\\n\" % \" \".join(to_skip))\n        else:\n            for _module in [_.strip() for _ in modname.split(\",\")]:\n                if _module.startswith(\"-\"):\n                    _module = _module[1:].strip()\n                    self._reloader.mark_module_skipped(_module)\n                else:\n                    top_module, top_name = self._reloader.aimport_module(_module)\n\n                    # Inject module to user namespace\n                    self.shell.push({top_name: top_module})\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 344,
        "n_words": 69,
        "vocab_size": 49,
        "complexity": 7,
        "nloc": 20,
        "token_counts": 175,
        "n_ast_nodes": 308,
        "n_identifiers": 28,
        "d_id": 52549,
        "documentation": {
            "docstring": "%aimport => Import modules for automatic reloading.\n\n        %aimport\n        List modules to automatically import and not to import.\n\n        %aimport foo\n        Import module 'foo' and mark it to be autoreloaded for %autoreload 1\n\n        %aimport foo, bar\n        Import modules 'foo', 'bar' and mark them to be autoreloaded for %autoreload 1\n\n        %aimport -foo, bar\n        Mark module 'foo' to not be autoreloaded for %autoreload 1, 2, or 3, and 'bar'\n        to be autoreloaded for 1.\n        ",
            "n_words": 70,
            "vocab_size": 35,
            "n_whitespaces": 140,
            "language": "en"
        }
    },
    {
        "id": 223881,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/utils.py",
        "file_name": "utils.py",
        "fun_name": "format_datetime",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def format_datetime(dt, usegmt=False):\n    \n    now = dt.timetuple()\n    if usegmt:\n        if dt.tzinfo is None or dt.tzinfo != datetime.timezone.utc:\n            raise ValueError(\"usegmt option requires a UTC datetime\")\n        zone = 'GMT'\n    elif dt.tzinfo is None:\n        zone = '-0000'\n    else:\n        zone = dt.strftime(\"%z\")\n    return _format_timetuple_and_zone(now, zone)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 97,
        "n_words": 40,
        "vocab_size": 31,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 72,
        "n_ast_nodes": 125,
        "n_identifiers": 13,
        "d_id": 57131,
        "documentation": {
            "docstring": "Turn a datetime into a date string as specified in RFC 2822.\n\n    If usegmt is True, dt must be an aware datetime with an offset of zero.  In\n    this case 'GMT' will be rendered instead of the normal +0000 required by\n    RFC2822.  This is to support HTTP headers involving date stamps.\n    ",
            "n_words": 51,
            "vocab_size": 44,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 268035,
        "commit_id": "3eb0485dd92c88cc92152d3656d94492db44b183",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/provisioning.py",
        "file_name": "provisioning.py",
        "fun_name": "get_controller_target_connections",
        "commit_message": "ansible-test - Use more native type hints. (#78435)\n\n* ansible-test - Use more native type hints.\r\n\r\nSimple search and replace to switch from comments to native type hints for return types of functions with no arguments.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of simple single-line function annotation type comments to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of single-line function annotation type comments with default values to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nManual conversion of type annotation comments for functions which have pylint directives.",
        "code": "def get_controller_target_connections(self) -> t.List[SshConnection]:\n        \n        return list(itertools.chain.from_iterable([target.get_controller_target_connections() for\n                                                   target in self.target_profiles if isinstance(target, SshTargetHostProfile)]))\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 77,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 44,
        "n_ast_nodes": 70,
        "n_identifiers": 13,
        "d_id": 79309,
        "documentation": {
            "docstring": "Return SSH connection(s) for accessing all target hosts from the controller.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 22423,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "Eight_Puzzle_Solver/eight_puzzle.py",
        "file_name": "eight_puzzle.py",
        "fun_name": "getAvailableActions",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def getAvailableActions(self):\n        \n        action = list()\n        for i in range(self.size):\n            for j in range(self.size):\n                if self.state[i][j] == 0:\n                    if i > 0:\n                        action.append(2)\n                    if j > 0:\n                        action.append(0)\n                    if i < self.size - 1:\n                        action.append(3)\n                    if j < self.size - 1:\n                        action.append(1)\n                    return action\n        return action\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 286,
        "n_words": 45,
        "vocab_size": 24,
        "complexity": 8,
        "nloc": 15,
        "token_counts": 100,
        "n_ast_nodes": 161,
        "n_identifiers": 10,
        "d_id": 4328,
        "documentation": {
            "docstring": "\n        Parameters: Current State\n        Returns: Available Actions for Current State\n        0 - Left    1 - Right   2 - Top     3 - Bottom\n        Restrictions: state is self.size x self.size Array\n        ",
            "n_words": 28,
            "vocab_size": 22,
            "n_whitespaces": 73,
            "language": "en"
        }
    },
    {
        "id": 56867,
        "commit_id": "83002be7b3d6ec51edcb8252484e52d918c514c1",
        "repo": "prefect",
        "path": "src/prefect/packaging/serializers.py",
        "file_name": "serializers.py",
        "fun_name": "check_picklelib",
        "commit_message": "Begin sketch of deployment/packager/manifest relationship",
        "code": "def check_picklelib(cls, value):\n        \n        try:\n            pickler = from_qualified_name(value)\n        except (ImportError, AttributeError) as exc:\n            raise ValueError(\n                f\"Failed to import requested pickle library: {value!r}.\"\n            ) from exc\n\n        if not hasattr(pickler, \"dumps\"):\n            raise ValueError(\n                f\"Pickle library at {value!r} does not have a 'dumps' method.\"\n            )\n\n        if not hasattr(pickler, \"loads\"):\n            raise ValueError(\n                f\"Pickle library at {value!r} does not have a 'loads' method.\"\n            )\n\n        return value\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 224,
        "n_words": 60,
        "vocab_size": 41,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 65,
        "n_ast_nodes": 125,
        "n_identifiers": 10,
        "d_id": 11574,
        "documentation": {
            "docstring": "\n        Check that the given pickle library is importable and has dumps/loads methods.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 205782,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "dates",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def dates(self, field_name, kind, order=\"ASC\"):\n        \n        if kind not in (\"year\", \"month\", \"week\", \"day\"):\n            raise ValueError(\"'kind' must be one of 'year', 'month', 'week', or 'day'.\")\n        if order not in (\"ASC\", \"DESC\"):\n            raise ValueError(\"'order' must be either 'ASC' or 'DESC'.\")\n        return (\n            self.annotate(\n                datefield=Trunc(field_name, kind, output_field=DateField()),\n                plain_field=F(field_name),\n            )\n            .values_list(\"datefield\", flat=True)\n            .distinct()\n            .filter(plain_field__isnull=False)\n            .order_by((\"-\" if order == \"DESC\" else \"\") + \"datefield\")\n        )\n\n    # RemovedInDjango50Warning: when the deprecation ends, remove is_dst\n    # argument.",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 229,
        "n_words": 70,
        "vocab_size": 58,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 113,
        "n_ast_nodes": 197,
        "n_identifiers": 19,
        "d_id": 51213,
        "documentation": {
            "docstring": "\n        Return a list of date objects representing all available dates for\n        the given field_name, scoped to 'kind'.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 178405,
        "commit_id": "a24d709ad2350c081a9a41cd76db72288b8ab014",
        "repo": "Nuitka",
        "path": "nuitka/Options.py",
        "file_name": "Options.py",
        "fun_name": "commentArgs",
        "commit_message": "UI: Added warning when following stdlib in accelerated mode\n\n* That's not going to work at this time, so we should inform the\n  user to not use it.",
        "code": "def commentArgs():\n    \n    # A ton of cases to consider, pylint: disable=too-many-branches,too-many-statements\n\n    # Inform the user about potential issues with the running version. e.g. unsupported\n    # version.\n    if python_version_str not in getSupportedPythonVersions():\n        # Do not disturb run of automatic tests with, detected from the presence of\n        # that environment variable.\n        if \"PYTHON\" not in os.environ:\n            Tracing.general.warning(\n                \"The version %r is not currently supported. Expect problems.\"\n                % python_version_str,\n            )\n\n    default_reference_mode = (\n        \"runtime\" if shallMakeModule() or isStandaloneMode() else \"original\"\n    )\n\n    if getFileReferenceMode() is None:\n        options.file_reference_mode = default_reference_mode\n    else:\n        if options.file_reference_mode != default_reference_mode:\n            Tracing.options_logger.warning(\n                \"Using non-default file reference mode '%s' rather than '%s' may cause runtime issues.\"\n                % (getFileReferenceMode(), default_reference_mode)\n            )\n        else:\n            Tracing.options_logger.info(\n                \"Using default file reference mode '%s' need not be specified.\"\n                % default_reference_mode\n            )\n\n    # TODO: Not all of these are usable with MSYS2 really, split those off.\n    if getOS() != \"Windows\":\n        # Too many Windows specific options clearly, pylint: disable=too-many-boolean-expressions\n        if (\n            getWindowsIconExecutablePath()\n            or shallAskForWindowsAdminRights()\n            or shallAskForWindowsUIAccessRights()\n            or getWindowsCompanyName()\n            or getWindowsProductName()\n            or getWindowsProductVersion()\n            or getWindowsFileVersion()\n            or getForcedStderrPath()  # not yet for other platforms\n            or getForcedStdoutPath()\n            or getWindowsSplashScreen()\n            or getIntendedPythonArch()\n        ):\n            Tracing.options_logger.warning(\n                \"Using Windows specific options has no effect on other platforms.\"\n            )\n\n        if options.mingw64 or options.msvc_version:\n            Tracing.options_logger.warning(\n                \"Requesting Windows specific compilers has no effect on other platforms.\"\n            )\n\n    if isMingw64() and getMsvcVersion():\n        Tracing.options_logger.sysexit(\n            \"Requesting both Windows specific compilers makes no sense.\"\n        )\n\n    if isOnefileMode():\n        standalone_mode = \"onefile\"\n    elif isStandaloneMode():\n        standalone_mode = \"standalone\"\n    else:\n        standalone_mode = None\n\n    if standalone_mode and not hasStandaloneSupportedOS():\n        Tracing.options_logger.warning(\n            \"Standalone mode on %s is not known to be supported, might fail to work.\"\n            % getOS()\n        )\n\n    if options.follow_all and standalone_mode:\n        Tracing.options_logger.info(\n            \"Following all imports is the default for %s mode and need not be specified.\"\n            % standalone_mode\n        )\n\n    if options.follow_none and standalone_mode:\n        Tracing.options_logger.warning(\n            \"Following no imports is unlikely to work for %s mode and should not be specified.\"\n            % standalone_mode\n        )\n\n    if options.follow_stdlib and not standalone_mode:\n        Tracing.options_logger.warning(\n            \"Following imports to stdlib is unlikely to work without --standalone/--onefile and should not be specified.\"\n        )\n\n    if (\n        not shallDumpBuiltTreeXML()\n        and not standalone_mode\n        and not options.follow_all\n        and not options.follow_none\n        and not options.follow_modules\n        and not options.follow_stdlib\n        and not options.include_modules\n        and not options.include_packages\n        and not options.include_extra\n        and not options.follow_not_modules\n    ):\n        Tracing.options_logger.warning(\n            \n            % (\"module\" if shallMakeModule() else \"program\")\n        )\n\n    if options.dependency_tool:\n        Tracing.options_logger.warning(\n            \"Using removed option '--windows-dependency-tool' is deprecated and has no impact anymore.\"\n        )\n\n    if shallMakeModule() and options.static_libpython == \"yes\":\n        Tracing.options_logger.warning(\n            \"In module mode, providing '--static-libpython' has no effect, it's not used.\"\n        )\n\n        options.static_libpython = \"no\"\n\n    if (\n        not isPgoMode()\n        and not isPythonPgoMode()\n        and (getPgoArgs() or getPgoExecutable())\n    ):\n        Tracing.optimization_logger.warning(\n            \"Providing PGO arguments without enabling PGO mode has no effect.\"\n        )\n\n    if isPgoMode():\n        if isStandaloneMode():\n            Tracing.optimization_logger.warning(\n                \"Using PGO with standalone/onefile mode is not currently working. Expect errors.\"\n            )\n\n        if shallMakeModule():\n            Tracing.optimization_logger.warning(\n                \"Using PGO with module mode is not currently working. Expect errors.\"\n            )\n\n    if (\n        options.static_libpython == \"auto\"\n        and not shallMakeModule()\n        and not shallDumpBuiltTreeXML()\n        and not shallUseStaticLibPython()\n        and getSystemStaticLibPythonPath() is not None\n    ):\n        Tracing.options_logger.info(\n            \n        )\n\n    if not shallExecuteImmediately():\n        if shallRunInDebugger():\n            Tracing.options_logger.warning(\n                \"The '--debugger' option has no effect outside of '--debug' without '--run' option.\"\n            )\n\n        if not shallClearPythonPathEnvironment():\n            Tracing.options_logger.warning(\n                \"The '--execute-with-pythonpath' option has no effect without '--run' option.\"\n            )\n\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1656,
        "n_words": 514,
        "vocab_size": 221,
        "complexity": 62,
        "nloc": 136,
        "token_counts": 523,
        "n_ast_nodes": 941,
        "n_identifiers": 57,
        "d_id": 42687,
        "documentation": {
            "docstring": "Comment on options, where we know something is not having the intended effect.\n\n    :meta private:\n\n    You did not specify to follow or include anything but main %s. Check options and \\\nmake sure that is intended.Detected static libpython to exist, consider '--static-libpython=yes' for better performance, \\\nbut errors may happen.",
            "n_words": 50,
            "vocab_size": 45,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 161257,
        "commit_id": "0caed984e39c07849a13662894f4cbdbe0a98091",
        "repo": "MockingBird",
        "path": "vocoder/fregan/modules.py",
        "file_name": "modules.py",
        "fun_name": "forward",
        "commit_message": "The new vocoder Fre-GAN is now supported (#546)\n\n* The new vocoder Fre-GAN is now supported\r\n\r\n* Improved some fregan details",
        "code": "def forward(self, c):\n        \n        batch, cond_channels, cond_length = c.shape\n\n        c = self.input_conv(c)\n        c = c + self.residual_conv(c)\n        k = self.kernel_conv(c)\n        b = self.bias_conv(c)\n\n        kernels = k.contiguous().view(batch,\n                                      self.conv_layers,\n                                      self.conv_in_channels,\n                                      self.conv_out_channels,\n                                      self.conv_kernel_size,\n                                      cond_length)\n        bias = b.contiguous().view(batch,\n                                   self.conv_layers,\n                                   self.conv_out_channels,\n                                   cond_length)\n        return kernels, bias\n\n",
        "url": "https://github.com/babysor/MockingBird.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 389,
        "n_words": 39,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 107,
        "n_ast_nodes": 163,
        "n_identifiers": 21,
        "d_id": 38950,
        "documentation": {
            "docstring": "\n        Args:\n            c (Tensor): the conditioning sequence (batch, cond_channels, cond_length)\n        Returns:\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 242744,
        "commit_id": "ee85e387bab535e2339b9d3cd1ab87c61d23af15",
        "repo": "Pillow",
        "path": "src/PIL/Jpeg2KImagePlugin.py",
        "file_name": "Jpeg2KImagePlugin.py",
        "fun_name": "_parse_codestream",
        "commit_message": "Remove redundant parentheses",
        "code": "def _parse_codestream(fp):\n    \n\n    hdr = fp.read(2)\n    lsiz = struct.unpack(\">H\", hdr)[0]\n    siz = hdr + fp.read(lsiz - 2)\n    lsiz, rsiz, xsiz, ysiz, xosiz, yosiz, _, _, _, _, csiz = struct.unpack_from(\n        \">HHIIIIIIIIH\", siz\n    )\n    ssiz = [None] * csiz\n    xrsiz = [None] * csiz\n    yrsiz = [None] * csiz\n    for i in range(csiz):\n        ssiz[i], xrsiz[i], yrsiz[i] = struct.unpack_from(\">BBB\", siz, 36 + 3 * i)\n\n    size = (xsiz - xosiz, ysiz - yosiz)\n    if csiz == 1:\n        if (yrsiz[0] & 0x7F) > 8:\n            mode = \"I;16\"\n        else:\n            mode = \"L\"\n    elif csiz == 2:\n        mode = \"LA\"\n    elif csiz == 3:\n        mode = \"RGB\"\n    elif csiz == 4:\n        mode = \"RGBA\"\n    else:\n        mode = None\n\n    return size, mode\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 244,
        "n_words": 115,
        "vocab_size": 67,
        "complexity": 7,
        "nloc": 27,
        "token_counts": 196,
        "n_ast_nodes": 311,
        "n_identifiers": 23,
        "d_id": 69907,
        "documentation": {
            "docstring": "Parse the JPEG 2000 codestream to extract the size and component\n    count from the SIZ marker segment, returning a PIL (size, mode) tuple.",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 203832,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/db/backends/postgis/operations.py",
        "file_name": "operations.py",
        "fun_name": "_get_postgis_func",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get_postgis_func(self, func):\n        \n        # Close out the connection.  See #9437.\n        with self.connection.temporary_connection() as cursor:\n            cursor.execute(\"SELECT %s()\" % func)\n            return cursor.fetchone()[0]\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 64,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 36,
        "n_ast_nodes": 66,
        "n_identifiers": 8,
        "d_id": 50549,
        "documentation": {
            "docstring": "\n        Helper routine for calling PostGIS functions and returning their result.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 73833,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "can_publish_subpage",
        "commit_message": "Reformat with black",
        "code": "def can_publish_subpage(self):\n        \n        if not self.user.is_active:\n            return False\n        specific_class = self.page.specific_class\n        if specific_class is None or not specific_class.creatable_subpage_models():\n            return False\n\n        return self.user.is_superuser or (\"publish\" in self.permissions)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 82,
        "n_words": 25,
        "vocab_size": 18,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 51,
        "n_ast_nodes": 86,
        "n_identifiers": 9,
        "d_id": 16134,
        "documentation": {
            "docstring": "\n        Niggly special case for creating and publishing a page in one go.\n        Differs from can_publish in that we want to be able to publish subpages of root, but not\n        to be able to publish root itself. (Also, can_publish_subpage returns false if the page\n        does not allow subpages at all.)\n        ",
            "n_words": 49,
            "vocab_size": 39,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 244031,
        "commit_id": "cac356380d505bf15587f07c0529218cc36b9652",
        "repo": "mmdetection",
        "path": "mmdet/core/bbox/match_costs/match_cost.py",
        "file_name": "match_cost.py",
        "fun_name": "binary_mask_dice_loss",
        "commit_message": "[Feature] Add Maskformer to mmdet (#7212)\n\n* first commit\r\n\r\n* add README\r\n\r\n* move model description from config to readme\r\n\r\nadd description for binary_input\r\n\r\nadd description for dice loss\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nremove compatibility of pretrain in maskformer\r\n\r\n* update comments in maskformer_head\r\n\r\n* update docs format",
        "code": "def binary_mask_dice_loss(self, mask_preds, gt_masks):\n        \n        mask_preds = mask_preds.flatten(1)\n        gt_masks = gt_masks.flatten(1).float()\n        numerator = 2 * torch.einsum('nc,mc->nm', mask_preds, gt_masks)\n        denominator = mask_preds.sum(-1)[:, None] + gt_masks.sum(-1)[None, :]\n        loss = 1 - (numerator + self.eps) / (denominator + self.eps)\n        return loss\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 86,
        "n_words": 37,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 92,
        "n_ast_nodes": 146,
        "n_identifiers": 13,
        "d_id": 70203,
        "documentation": {
            "docstring": "\n        Args:\n            mask_preds (Tensor): Mask prediction in shape (num_query, *).\n            gt_masks (Tensor): Ground truth in shape (num_gt, *)\n                store 0 or 1, 0 for negative class and 1 for\n                positive class.\n\n        Returns:\n            Tensor: Dice cost matrix in shape (num_query, num_gt).\n        ",
            "n_words": 39,
            "vocab_size": 31,
            "n_whitespaces": 124,
            "language": "en"
        }
    },
    {
        "id": 60412,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/scripts/cpp_lint.py",
        "file_name": "cpp_lint.py",
        "fun_name": "_DropCommonSuffixes",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def _DropCommonSuffixes(filename):\n  \n  for suffix in ('test.cc', 'regtest.cc', 'unittest.cc',\n                 'inl.h', 'impl.h', 'internal.h'):\n    if (filename.endswith(suffix) and len(filename) > len(suffix) and\n        filename[-len(suffix) - 1] in ('-', '_')):\n      return filename[:-len(suffix) - 1]\n  return os.path.splitext(filename)[0]\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 64,
        "n_words": 30,
        "vocab_size": 25,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 84,
        "n_ast_nodes": 143,
        "n_identifiers": 8,
        "d_id": 12140,
        "documentation": {
            "docstring": "Drops common suffixes like _test.cc or -inl.h from filename.\n\n  For example:\n    >>> _DropCommonSuffixes('foo/foo-inl.h')\n    'foo/foo'\n    >>> _DropCommonSuffixes('foo/bar/foo.cc')\n    'foo/bar/foo'\n    >>> _DropCommonSuffixes('foo/foo_internal.h')\n    'foo/foo'\n    >>> _DropCommonSuffixes('foo/foo_unusualinternal.h')\n    'foo/foo_unusualinternal'\n\n  Args:\n    filename: The input filename.\n\n  Returns:\n    The filename with the common suffix removed.\n  ",
            "n_words": 36,
            "vocab_size": 29,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 206737,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/text.py",
        "file_name": "text.py",
        "fun_name": "_text_words",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _text_words(self, length, truncate):\n        \n        words = self._wrapped.split()\n        if len(words) > length:\n            words = words[:length]\n            return self.add_truncation_text(\" \".join(words), truncate)\n        return \" \".join(words)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 55,
        "n_ast_nodes": 92,
        "n_identifiers": 10,
        "d_id": 51669,
        "documentation": {
            "docstring": "\n        Truncate a string after a certain number of words.\n\n        Strip newlines in the string.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 299641,
        "commit_id": "2a9f043039dc60fc25bc14bab724419bedf746bb",
        "repo": "core",
        "path": "homeassistant/util/ulid.py",
        "file_name": "ulid.py",
        "fun_name": "ulid",
        "commit_message": "Use ULID short format for context ids (#71119)",
        "code": "def ulid() -> str:\n    \n    ulid_bytes = int(time.time() * 1000).to_bytes(6, byteorder=\"big\") + int(\n        getrandbits(80)\n    ).to_bytes(10, byteorder=\"big\")\n\n    # This is base32 crockford encoding with the loop unrolled for performance\n    #\n    # This code is adapted from:\n    # https://github.com/ahawker/ulid/blob/06289583e9de4286b4d80b4ad000d137816502ca/ulid/base32.py#L102\n    #\n    enc = \"0123456789ABCDEFGHJKMNPQRSTVWXYZ\"\n    return (\n        enc[(ulid_bytes[0] & 224) >> 5]\n        + enc[ulid_bytes[0] & 31]\n        + enc[(ulid_bytes[1] & 248) >> 3]\n        + enc[((ulid_bytes[1] & 7) << 2) | ((ulid_bytes[2] & 192) >> 6)]\n        + enc[((ulid_bytes[2] & 62) >> 1)]\n        + enc[((ulid_bytes[2] & 1) << 4) | ((ulid_bytes[3] & 240) >> 4)]\n        + enc[((ulid_bytes[3] & 15) << 1) | ((ulid_bytes[4] & 128) >> 7)]\n        + enc[(ulid_bytes[4] & 124) >> 2]\n        + enc[((ulid_bytes[4] & 3) << 3) | ((ulid_bytes[5] & 224) >> 5)]\n        + enc[ulid_bytes[5] & 31]\n        + enc[(ulid_bytes[6] & 248) >> 3]\n        + enc[((ulid_bytes[6] & 7) << 2) | ((ulid_bytes[7] & 192) >> 6)]\n        + enc[(ulid_bytes[7] & 62) >> 1]\n        + enc[((ulid_bytes[7] & 1) << 4) | ((ulid_bytes[8] & 240) >> 4)]\n        + enc[((ulid_bytes[8] & 15) << 1) | ((ulid_bytes[9] & 128) >> 7)]\n        + enc[(ulid_bytes[9] & 124) >> 2]\n        + enc[((ulid_bytes[9] & 3) << 3) | ((ulid_bytes[10] & 224) >> 5)]\n        + enc[ulid_bytes[10] & 31]\n        + enc[(ulid_bytes[11] & 248) >> 3]\n        + enc[((ulid_bytes[11] & 7) << 2) | ((ulid_bytes[12] & 192) >> 6)]\n        + enc[(ulid_bytes[12] & 62) >> 1]\n        + enc[((ulid_bytes[12] & 1) << 4) | ((ulid_bytes[13] & 240) >> 4)]\n        + enc[((ulid_bytes[13] & 15) << 1) | ((ulid_bytes[14] & 128) >> 7)]\n        + enc[(ulid_bytes[14] & 124) >> 2]\n        + enc[((ulid_bytes[14] & 3) << 3) | ((ulid_bytes[15] & 224) >> 5)]\n        + enc[ulid_bytes[15] & 31]\n    )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 36,
        "n_whitespaces": 484,
        "n_words": 262,
        "vocab_size": 99,
        "complexity": 1,
        "nloc": 49,
        "token_counts": 614,
        "n_ast_nodes": 856,
        "n_identifiers": 9,
        "d_id": 98556,
        "documentation": {
            "docstring": "Generate a ULID.\n\n    This ulid should not be used for cryptographically secure\n    operations.\n\n     01AN4Z07BY      79KA1307SR9X4MV3\n    |----------|    |----------------|\n     Timestamp          Randomness\n       48bits             80bits\n\n    This string can be loaded directly with https://github.com/ahawker/ulid\n\n    import homeassistant.util.ulid as ulid_util\n    import ulid\n    ulid.parse(ulid_util.ulid())\n    ",
            "n_words": 36,
            "vocab_size": 32,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 272207,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/integration_test/gradient_checkpoint_test.py",
        "file_name": "gradient_checkpoint_test.py",
        "fun_name": "_train_with_recompute",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _train_with_recompute(n_steps):\n    \n    img_dim, n_channels, batch_size = 256, 1, 4\n    x, y = _get_dummy_data(img_dim, n_channels, batch_size)\n    # This model is the same model as _get_big_cnn_model but split into 3 parts.\n    models = _get_split_cnn_model(\n        img_dim, n_channels, num_partitions=3, blocks_per_partition=2\n    )\n    model1, model2, model3 = models\n    # Apply gradient checkpointing to the submodels using tf.recompute_grad.\n    model1_re = tf.recompute_grad(model1)\n    model2_re = tf.recompute_grad(model2)\n    model3_re = tf.recompute_grad(model3)\n    optimizer = optimizers.SGD()\n    tr_vars = (\n        model1.trainable_variables\n        + model2.trainable_variables\n        + model3.trainable_variables\n    )\n    losses = []\n    for _ in range(n_steps):\n        with tf.GradientTape() as tape:\n            logits1 = model1_re(x)\n            logits2 = model2_re(logits1)\n            logits3 = model3_re(logits2)\n            loss = _compute_loss(logits3, y)\n            losses.append(loss)\n            grads = tape.gradient(loss, tr_vars)  # tr_vars\n            optimizer.apply_gradients(zip(grads, tr_vars))\n            del grads\n    return losses\n\n\n@tf_test_utils.with_eager_op_as_function",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@tf_test_utils.with_eager_op_as_function",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 284,
        "n_words": 110,
        "vocab_size": 82,
        "complexity": 2,
        "nloc": 28,
        "token_counts": 176,
        "n_ast_nodes": 288,
        "n_identifiers": 42,
        "d_id": 80977,
        "documentation": {
            "docstring": "Trains a single large model with gradient checkpointing using tf.recompute_grad.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 74807,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/documents/tests/test_admin_views.py",
        "file_name": "test_admin_views.py",
        "fun_name": "test_edit_post",
        "commit_message": "Reformat with black",
        "code": "def test_edit_post(self):\n        \n        # Send request\n        response = self.client.post(\n            reverse(\"wagtaildocs:edit_multiple\", args=(self.doc.id,)),\n            {\n                \"doc-%d-%s\" % (self.doc.id, field): data\n                for field, data in self.edit_post_data.items()\n            },\n        )\n\n        # Check response\n        self.assertEqual(response.status_code, 200)\n        self.assertEqual(response[\"Content-Type\"], \"application/json\")\n\n        # Check JSON\n        response_json = json.loads(response.content.decode())\n        self.assertIn(\"doc_id\", response_json)\n        self.assertNotIn(\"form\", response_json)\n        self.assertIn(\"success\", response_json)\n        self.assertEqual(response_json[\"doc_id\"], self.doc.id)\n        self.assertTrue(response_json[\"success\"])\n\n        self.check_doc_after_edit()\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 214,
        "n_words": 46,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 147,
        "n_ast_nodes": 246,
        "n_identifiers": 24,
        "d_id": 16323,
        "documentation": {
            "docstring": "\n        This tests that a POST request to the edit view edits the document\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 185337,
        "commit_id": "7bca184192191689b8a7247c92392d6b238df3d7",
        "repo": "textual",
        "path": "src/textual/geometry.py",
        "file_name": "geometry.py",
        "fun_name": "clamped",
        "commit_message": "tweak for colors",
        "code": "def clamped(self) -> Offset:\n        \n        x, y = self\n        return Offset(max(x, 0), max(y, 0))\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 30,
        "n_ast_nodes": 48,
        "n_identifiers": 6,
        "d_id": 44981,
        "documentation": {
            "docstring": "Ensure x and y are above zero.\n\n        Returns:\n            Offset: New offset.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 195742,
        "commit_id": "5373c833ee895fb95f791849c6082ceb698b8dcc",
        "repo": "sympy",
        "path": "bin/mailmap_check.py",
        "file_name": "mailmap_check.py",
        "fun_name": "make_authors_file_lines",
        "commit_message": "maint: tweaks in mailmap_check.py",
        "code": "def make_authors_file_lines(git_people):\n    # define new lines for the file\n    header = filldedent().lstrip()\n    header_extra = f\"There are a total of {len(git_people)} authors.",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 29,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 53,
        "n_ast_nodes": 108,
        "n_identifiers": 11,
        "d_id": 47395,
        "documentation": {
            "docstring": "\n        All people who contributed to SymPy by sending at least a patch or\n        more (in the order of the date of their first contribution), except\n        those who explicitly didn't want to be mentioned. People with a * next\n        to their names are not found in the metadata of the git history. This\n        file is generated automatically by running `./bin/authors_update.py`.\n        \n    lines = header.splitlines()\n    lines.append('')\n    lines.append(header_extra)\n    lines.append('')\n    lines.extend(git_people)\n    return lines\n\n",
            "n_words": 68,
            "vocab_size": 55,
            "n_whitespaces": 129,
            "language": "en"
        }
    },
    {
        "id": 118532,
        "commit_id": "704eab3478cf69847825b23dabf15813a8ac9fa2",
        "repo": "streamlit",
        "path": "lib/streamlit/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "spinner",
        "commit_message": "Rename and refactor `Report` machinery (#4141)\n\nThis refactor renames (almost) everything related to the outdated \"report\" concept with more precise concepts that we use throughout our code, primarily \"script run\", \"session\", and \"app\".",
        "code": "def spinner(text=\"In progress...\"):\n    \n    import streamlit.legacy_caching.caching as legacy_caching\n    import streamlit.caching as caching\n    from streamlit.elements.utils import clean_text\n    from streamlit.proto.Spinner_pb2 import Spinner as SpinnerProto\n\n    # @st.cache optionally uses spinner for long-running computations.\n    # Normally, streamlit warns the user when they call st functions\n    # from within an @st.cache'd function. But we do *not* want to show\n    # these warnings for spinner's message, so we create and mutate this\n    # message delta within the \"suppress_cached_st_function_warning\"\n    # context.\n    with legacy_caching.suppress_cached_st_function_warning():\n        with caching.suppress_cached_st_function_warning():\n            message = empty()\n\n    try:\n        # Set the message 0.1 seconds in the future to avoid annoying\n        # flickering if this spinner runs too quickly.\n        DELAY_SECS = 0.1\n        display_message = True\n        display_message_lock = _threading.Lock()\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "def spinner(text=\"In progress...\"):\n    \"\"\"Temporarily displays a message while executing a block of code.\n\n    Parameters\n    ----------\n    text : str\n        A message to display while executing that block\n\n    Example\n    -------\n\n    >>> with st.spinner('Wait for it...'):\n    >>>     time.sleep(5)\n    >>> st.success('Done!')\n\n    \"\"\"\n    import streamlit.legacy_caching.caching as legacy_caching\n    import streamlit.caching as caching\n    from streamlit.elements.utils import clean_text\n    from streamlit.proto.Spinner_pb2 import Spinner as SpinnerProto\n\n    # @st.cache optionally uses spinner for long-running computations.\n    # Normally, streamlit warns the user when they call st functions\n    # from within an @st.cache'd function. But we do *not* want to show\n    # these warnings for spinner's message, so we create and mutate this\n    # message delta within the \"suppress_cached_st_function_warning\"\n    # context.\n    with legacy_caching.suppress_cached_st_function_warning():\n        with caching.suppress_cached_st_function_warning():\n            message = empty()\n\n    try:\n        # Set the message 0.1 seconds in the future to avoid annoying\n        # flickering if this spinner runs too quickly.\n        DELAY_SECS = 0.1\n        display_message = True\n        display_message_lock = _threading.Lock()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 202,
        "n_words": 110,
        "vocab_size": 80,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 124,
        "n_ast_nodes": 132,
        "n_identifiers": 20,
        "d_id": 26274,
        "documentation": {
            "docstring": "Temporarily displays a message while executing a block of code.\n\n    Parameters\n    ----------\n    text : str\n        A message to display while executing that block\n\n    Example\n    -------\n\n    >>> with st.spinner('Wait for it...'):\n    >>>     time.sleep(5)\n    >>> st.success('Done!')\n\n    ",
            "n_words": 34,
            "vocab_size": 27,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 266109,
        "commit_id": "a5308ea28e851a4ddb65a4e7ca2297b641e5891f",
        "repo": "netbox",
        "path": "netbox/netbox/staging.py",
        "file_name": "staging.py",
        "fun_name": "process_queue",
        "commit_message": "Closes #10851: New staging mechanism (#10890)\n\n* WIP\r\n\r\n* Convert checkout() context manager to a class\r\n\r\n* Misc cleanup\r\n\r\n* Drop unique constraint from Change model\r\n\r\n* Extend staging tests\r\n\r\n* Misc cleanup\r\n\r\n* Incorporate M2M changes\r\n\r\n* Don't cancel wipe out creation records when an object is deleted\r\n\r\n* Rename Change to StagedChange\r\n\r\n* Add documentation for change staging",
        "code": "def process_queue(self):\n        \n        if not self.queue:\n            logger.debug(f\"No queued changes; aborting\")\n            return\n        logger.debug(f\"Processing {len(self.queue)} queued changes\")\n\n        # Iterate through the in-memory queue, creating Change instances\n        changes = []\n        for key, change in self.queue.items():\n            logger.debug(f'  {key}: {change}')\n            object_type, pk = key\n            action, data = change\n\n            changes.append(StagedChange(\n                branch=self.branch,\n                action=action,\n                object_type=object_type,\n                object_id=pk,\n                data=data\n            ))\n\n        # Save all Change instances to the database\n        StagedChange.objects.bulk_create(changes)\n\n    #\n    # Signal handlers\n    #\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 281,
        "n_words": 63,
        "vocab_size": 52,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 98,
        "n_ast_nodes": 183,
        "n_identifiers": 20,
        "d_id": 78296,
        "documentation": {
            "docstring": "\n        Create Change instances for all actions stored in the queue.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 206002,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/models.py",
        "file_name": "models.py",
        "fun_name": "save",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def save(self, commit=True):\n        \n        if self.errors:\n            raise ValueError(\n                \"The %s could not be %s because the data didn't validate.\"\n                % (\n                    self.instance._meta.object_name,\n                    \"created\" if self.instance._state.adding else \"changed\",\n                )\n            )\n        if commit:\n            # If committing, save the instance and the m2m data immediately.\n            self.instance.save()\n            self._save_m2m()\n        else:\n            # If not committing, add a method to the form to allow deferred\n            # saving of m2m data.\n            self.save_m2m = self._save_m2m\n        return self.instance\n\n    save.alters_data = True\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 279,
        "n_words": 70,
        "vocab_size": 54,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 71,
        "n_ast_nodes": 130,
        "n_identifiers": 13,
        "d_id": 51322,
        "documentation": {
            "docstring": "\n        Save this form's self.instance object if commit=True. Otherwise, add\n        a save_m2m() method to the form which can be called after the instance\n        is saved manually at a later time. Return the model instance.\n        ",
            "n_words": 33,
            "vocab_size": 30,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 198419,
        "commit_id": "bd9f607176c58dfba01e27c05c2b7d49ff97c901",
        "repo": "sympy",
        "path": "sympy/solvers/diophantine/diophantine.py",
        "file_name": "diophantine.py",
        "fun_name": "solve",
        "commit_message": "Improve loop performance in solvers",
        "code": "def solve(self, parameters=None, limit=None):\n        self.pre_solve(parameters)\n\n        coeff = self.coeff\n        var = self.free_symbols\n\n        if 1 in coeff:\n            # negate coeff[] because input is of the form: ax + by + c ==  0\n            #                              but is used as: ax + by     == -c\n            c = -coeff[1]\n        else:\n            c = 0\n\n        result = DiophantineSolutionSet(var, parameters=self.parameters)\n        params = result.parameters\n\n        if len(var) == 1:\n            q, r = divmod(c, coeff[var[0]])\n            if not r:\n                result.add((q,))\n                return result\n            else:\n                return result\n\n        \n\n        A = [coeff[v] for v in var]\n        B = []\n        if len(var) > 2:\n            B.append(igcd(A[-2], A[-1]))\n            A[-2] = A[-2] // B[0]\n            A[-1] = A[-1] // B[0]\n            for i in range(len(A) - 3, 0, -1):\n                gcd = igcd(B[0], A[i])\n                B[0] = B[0] // gcd\n                A[i] = A[i] // gcd\n                B.insert(0, gcd)\n        B.append(A[-1])\n\n        \n        solutions = []\n        for Ai, Bi in zip(A, B):\n            tot_x, tot_y = [], []\n\n            for j, arg in enumerate(Add.make_args(c)):\n                if arg.is_Integer:\n                    # example: 5 -> k = 5\n                    k, p = arg, S.One\n                    pnew = params[0]\n                else:  # arg is a Mul or Symbol\n                    # example: 3*t_1 -> k = 3\n                    # example: t_0 -> k = 1\n                    k, p = arg.as_coeff_Mul()\n                    pnew = params[params.index(p) + 1]\n\n                sol = sol_x, sol_y = base_solution_linear(k, Ai, Bi, pnew)\n\n                if p is S.One:\n                    if None in sol:\n                        return result\n                else:\n                    # convert a + b*pnew -> a*p + b*pnew\n                    if isinstance(sol_x, Add):\n                        sol_x = sol_x.args[0]*p + sol_x.args[1]\n                    if isinstance(sol_y, Add):\n                        sol_y = sol_y.args[0]*p + sol_y.args[1]\n\n                tot_x.append(sol_x)\n                tot_y.append(sol_y)\n\n            solutions.append(Add(*tot_x))\n            c = Add(*tot_y)\n\n        solutions.append(c)\n        result.add(solutions)\n        return result\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 1068,
        "n_words": 246,
        "vocab_size": 136,
        "complexity": 14,
        "nloc": 148,
        "token_counts": 454,
        "n_ast_nodes": 727,
        "n_identifiers": 51,
        "d_id": 48926,
        "documentation": {
            "docstring": "\n        base_solution_linear() can solve diophantine equations of the form:\n\n        a*x + b*y == c\n\n        We break down multivariate linear diophantine equations into a\n        series of bivariate linear diophantine equations which can then\n        be solved individually by base_solution_linear().\n\n        Consider the following:\n\n        a_0*x_0 + a_1*x_1 + a_2*x_2 == c\n\n        which can be re-written as:\n\n        a_0*x_0 + g_0*y_0 == c\n\n        where\n\n        g_0 == gcd(a_1, a_2)\n\n        and\n\n        y == (a_1*x_1)/g_0 + (a_2*x_2)/g_0\n\n        This leaves us with two binary linear diophantine equations.\n        For the first equation:\n\n        a == a_0\n        b == g_0\n        c == c\n\n        For the second:\n\n        a == a_1/g_0\n        b == a_2/g_0\n        c == the solution we find for y_0 in the first equation.\n\n        The arrays A and B are the arrays of integers used for\n        'a' and 'b' in each of the n-1 bivariate equations we solve.\n        \n        Consider the trivariate linear equation:\n\n        4*x_0 + 6*x_1 + 3*x_2 == 2\n\n        This can be re-written as:\n\n        4*x_0 + 3*y_0 == 2\n\n        where\n\n        y_0 == 2*x_1 + x_2\n        (Note that gcd(3, 6) == 3)\n\n        The complete integral solution to this equation is:\n\n        x_0 ==  2 + 3*t_0\n        y_0 == -2 - 4*t_0\n\n        where 't_0' is any integer.\n\n        Now that we have a solution for 'x_0', find 'x_1' and 'x_2':\n\n        2*x_1 + x_2 == -2 - 4*t_0\n\n        We can then solve for '-2' and '-4' independently,\n        and combine the results:\n\n        2*x_1a + x_2a == -2\n        x_1a == 0 + t_0\n        x_2a == -2 - 2*t_0\n\n        2*x_1b + x_2b == -4*t_0\n        x_1b == 0*t_0 + t_1\n        x_2b == -4*t_0 - 2*t_1\n\n        ==>\n\n        x_1 == t_0 + t_1\n        x_2 == -2 - 6*t_0 - 2*t_1\n\n        where 't_0' and 't_1' are any integers.\n\n        Note that:\n\n        4*(2 + 3*t_0) + 6*(t_0 + t_1) + 3*(-2 - 6*t_0 - 2*t_1) == 2\n\n        for any integral values of 't_0', 't_1'; as required.\n\n        This method is generalised for many variables, below.\n\n        ",
            "n_words": 307,
            "vocab_size": 153,
            "n_whitespaces": 695,
            "language": "en"
        }
    },
    {
        "id": 183771,
        "commit_id": "fe151a7f25cfd7f1134ebafbddc7eeade1c18ccb",
        "repo": "textual",
        "path": "src/textual/driver.py",
        "file_name": "driver.py",
        "fun_name": "disable_bracketed_paste",
        "commit_message": "Support for bracketed paste mode (#567)\n\n* Detecting bracketed paste, sending paste events\r\n\r\n* Bracketed pasting support in TextInput\r\n\r\n* Restore debugging conditional\r\n\r\n* Handle pasting of text in text-input, improve scrolling\r\n\r\n* Fix ordering of handling in parser for bracketed pastes\r\n\r\n* Docstrings\r\n\r\n* Add docstrings",
        "code": "def disable_bracketed_paste(self) -> None:\n        \n        self.console.file.write(\"\\x1b[?2004l\")\n        self.console.file.flush()\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 27,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 27,
        "n_ast_nodes": 50,
        "n_identifiers": 6,
        "d_id": 44330,
        "documentation": {
            "docstring": "Write the ANSI escape code `ESC[?2004l`, which\n        disables bracketed paste mode.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 125331,
        "commit_id": "ac1d21027da8a8c002cc7c28b8d1dc89c0d72fcf",
        "repo": "ray",
        "path": "python/ray/train/huggingface/huggingface_checkpoint.py",
        "file_name": "huggingface_checkpoint.py",
        "fun_name": "get_training_arguments",
        "commit_message": "[AIR] Add framework-specific checkpoints (#26777)",
        "code": "def get_training_arguments(self) -> transformers.training_args.TrainingArguments:\n        \n        with self.as_directory() as checkpoint_path:\n            training_args_path = os.path.join(checkpoint_path, TRAINING_ARGS_NAME)\n            if os.path.exists(training_args_path):\n                with open(training_args_path, \"rb\") as f:\n                    training_args = torch.load(f, map_location=\"cpu\")\n            else:\n                training_args = None\n        return training_args\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 132,
        "n_words": 29,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 72,
        "n_ast_nodes": 126,
        "n_identifiers": 18,
        "d_id": 27836,
        "documentation": {
            "docstring": "Retrieve the training arguments stored in this checkpoint.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 284458,
        "commit_id": "33a041e5bf93ce93ab1a19adbc5ed74c2f1eb337",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/stocks/tradinghours/bursa_model.py",
        "file_name": "bursa_model.py",
        "fun_name": "all_bursa",
        "commit_message": "Trading hours stock feature (#1697)",
        "code": "def all_bursa():\n    \n    path = os.path.join(os.path.dirname(__file__), \"data/bursa_open_hours.json\")\n    bursa = pd.read_json(path)  # , orient=\"index\")\n    return bursa\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 27,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 60,
        "n_identifiers": 9,
        "d_id": 84728,
        "documentation": {
            "docstring": "Get all exchanges from dictionary\n\n    Parameters\n    __________\n\n    Returns\n    _______\n    pd.DataFrame\n        All exchanges\n    ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 206790,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/version.py",
        "file_name": "version.py",
        "fun_name": "get_git_changeset",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_git_changeset():\n    \n    # Repository may not be found if __file__ is undefined, e.g. in a frozen\n    # module.\n    if \"__file__\" not in globals():\n        return None\n    repo_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\n    git_log = subprocess.run(\n        \"git log --pretty=format:%ct --quiet -1 HEAD\",\n        capture_output=True,\n        shell=True,\n        cwd=repo_dir,\n        text=True,\n    )\n    timestamp = git_log.stdout\n    tz = datetime.timezone.utc\n    try:\n        timestamp = datetime.datetime.fromtimestamp(int(timestamp), tz=tz)\n    except ValueError:\n        return None\n    return timestamp.strftime(\"%Y%m%d%H%M%S\")\n\n\nversion_component_re = _lazy_re_compile(r\"(\\d+|[a-z]+|\\.)\")\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 153,
        "n_words": 62,
        "vocab_size": 49,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 107,
        "n_ast_nodes": 188,
        "n_identifiers": 27,
        "d_id": 51708,
        "documentation": {
            "docstring": "Return a numeric identifier of the latest git changeset.\n\n    The result is the UTC timestamp of the changeset in YYYYMMDDHHMMSS format.\n    This value isn't guaranteed to be unique, but collisions are very unlikely,\n    so it's sufficient for generating the development version numbers.\n    ",
            "n_words": 42,
            "vocab_size": 38,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 177316,
        "commit_id": "8a325d26aa7fdd3a72580c4720fa97f971bbefcb",
        "repo": "networkx",
        "path": "networkx/algorithms/tournament.py",
        "file_name": "tournament.py",
        "fun_name": "tournament_matrix",
        "commit_message": "Use scipy.sparse array datastructure (#6037)\n\n* Use scipy.sparse array datastructure\r\n\r\n* Add reminder to rm wrapper when scipy adds creation fns.\r\n\r\n* Rm mention of np matrix from code comment.\r\n\r\n* Update networkx/algorithms/bipartite/matrix.py\r\n\r\nCo-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>\r\nCo-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>",
        "code": "def tournament_matrix(G):\n    r\n    A = nx.adjacency_matrix(G)\n    return A - A.T\n\n\n@not_implemented_for(\"undirected\")\n@not_implemented_for(\"multigraph\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"undirected\")\n@not_implemented_for(\"multigraph\")",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 18,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 38,
        "token_counts": 21,
        "n_ast_nodes": 56,
        "n_identifiers": 7,
        "d_id": 42336,
        "documentation": {
            "docstring": "Returns the tournament matrix for the given tournament graph.\n\n    This function requires SciPy.\n\n    The *tournament matrix* of a tournament graph with edge set *E* is\n    the matrix *T* defined by\n\n    .. math::\n\n       T_{i j} =\n       \\begin{cases}\n       +1 & \\text{if } (i, j) \\in E \\\\\n       -1 & \\text{if } (j, i) \\in E \\\\\n       0 & \\text{if } i == j.\n       \\end{cases}\n\n    An equivalent definition is `T = A - A^T`, where *A* is the\n    adjacency matrix of the graph `G`.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n        A directed graph representing a tournament.\n\n    Returns\n    -------\n    SciPy sparse array\n        The tournament matrix of the tournament graph `G`.\n\n    Raises\n    ------\n    ImportError\n        If SciPy is not available.\n\n    ",
            "n_words": 114,
            "vocab_size": 77,
            "n_whitespaces": 219,
            "language": "en"
        }
    },
    {
        "id": 244119,
        "commit_id": "3f0f2a059743593fd07b629c261b609bd9a767e6",
        "repo": "mmdetection",
        "path": "mmdet/models/backbones/efficientnet.py",
        "file_name": "efficientnet.py",
        "fun_name": "model_scaling",
        "commit_message": "[Feature] Support efficientnet in mmdetection. (#7514)\n\n* Initial implementation\r\n\r\n* Add missing import\r\n\r\n* Add MemoryEfficientSwishImplementation. Add docstrings\r\n\r\n* Add efficientnet2mmdet tool\r\n\r\n* Add config folder\r\n\r\n* Flake8\r\n\r\n* Flake8\r\n\r\n* Flake8\r\n\r\n* Fix config\r\n\r\n* Requested changes\r\n\r\n* docformatter\r\n\r\n* Update train config from https://github.com/google/automl/blob/master/efficientdet\r\n\r\n* Run pre-commit\r\n\r\n* Fix schedule\r\n\r\n* Set by_epoch=False in scheduler\r\n\r\n* Train 80 epochs\r\n\r\n* Remove duplicated arg\r\n\r\n* Update README.md\r\n\r\n* efficient3 efficient0\r\n\r\n* efficientNet imports\r\n\r\n* efficientNet\r\n\r\n* config edit path for eff3 and dropout for eff0\r\n\r\n* efficientnet review2\r\n\r\n* fix model_converter location and drop path\r\n\r\n* fix model converter  and efficientnet import\r\n\r\n* register memoryefficietnswish\r\n\r\n* eff0, eff3\r\n\r\n* fix  flake8 yapf isort\r\n\r\n* same padding in tensorflow and edit drop path rate\r\n\r\n* fix init of utils\r\n\r\n* Align mmdet utils with mmcls\r\n\r\n* Align mmdet.models.utils with mmcls\r\n\r\n* Use mmcls efficientnet backbone\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update metafile\r\n\r\nCo-authored-by: David de la Iglesia Castro <daviddelaiglesiacastro@gmail.com>\r\nCo-authored-by: David de la Iglesia Castro <diglesia@gradiant.org>\r\nCo-authored-by: jiangyitong <jiangyitong1@sensetime.com>\r\nCo-authored-by: jiangyitong <jiangyitong1998@outlook.com>",
        "code": "def model_scaling(layer_setting, arch_setting):\n    \n    # scale width\n    new_layer_setting = copy.deepcopy(layer_setting)\n    for layer_cfg in new_layer_setting:\n        for block_cfg in layer_cfg:\n            block_cfg[1] = make_divisible(block_cfg[1] * arch_setting[0], 8)\n\n    # scale depth\n    split_layer_setting = [new_layer_setting[0]]\n    for layer_cfg in new_layer_setting[1:-1]:\n        tmp_index = [0]\n        for i in range(len(layer_cfg) - 1):\n            if layer_cfg[i + 1][1] != layer_cfg[i][1]:\n                tmp_index.append(i + 1)\n        tmp_index.append(len(layer_cfg))\n        for i in range(len(tmp_index) - 1):\n            split_layer_setting.append(layer_cfg[tmp_index[i]:tmp_index[i +\n                                                                        1]])\n    split_layer_setting.append(new_layer_setting[-1])\n\n    num_of_layers = [len(layer_cfg) for layer_cfg in split_layer_setting[1:-1]]\n    new_layers = [\n        int(math.ceil(arch_setting[1] * num)) for num in num_of_layers\n    ]\n\n    merge_layer_setting = [split_layer_setting[0]]\n    for i, layer_cfg in enumerate(split_layer_setting[1:-1]):\n        if new_layers[i] <= num_of_layers[i]:\n            tmp_layer_cfg = layer_cfg[:new_layers[i]]\n        else:\n            tmp_layer_cfg = copy.deepcopy(layer_cfg) + [layer_cfg[-1]] * (\n                new_layers[i] - num_of_layers[i])\n        if tmp_layer_cfg[0][3] == 1 and i != 0:\n            merge_layer_setting[-1] += tmp_layer_cfg.copy()\n        else:\n            merge_layer_setting.append(tmp_layer_cfg.copy())\n    merge_layer_setting.append(split_layer_setting[-1])\n\n    return merge_layer_setting\n\n\n@BACKBONES.register_module()",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "@BACKBONES.register_module()",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 415,
        "n_words": 123,
        "vocab_size": 78,
        "complexity": 13,
        "nloc": 33,
        "token_counts": 325,
        "n_ast_nodes": 510,
        "n_identifiers": 26,
        "d_id": 70249,
        "documentation": {
            "docstring": "Scaling operation to the layer's parameters according to the\n    arch_setting.",
            "n_words": 10,
            "vocab_size": 8,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 119831,
        "commit_id": "603bb3c5ca288674579211e64fa47c6b2b0fb7a6",
        "repo": "jax",
        "path": "jax/_src/numpy/polynomial.py",
        "file_name": "polynomial.py",
        "fun_name": "polyfit",
        "commit_message": "lax_numpy: move poly functions into numpy.polynomial",
        "code": "def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False):\n  _check_arraylike(\"polyfit\", x, y)\n  deg = core.concrete_or_error(int, deg, \"deg must be int\")\n  order = deg + 1\n  # check arguments\n  if deg < 0:\n    raise ValueError(\"expected deg >= 0\")\n  if x.ndim != 1:\n    raise TypeError(\"expected 1D vector for x\")\n  if x.size == 0:\n    raise TypeError(\"expected non-empty vector for x\")\n  if y.ndim < 1 or y.ndim > 2:\n    raise TypeError(\"expected 1D or 2D array for y\")\n  if x.shape[0] != y.shape[0]:\n    raise TypeError(\"expected x and y to have same length\")\n\n  # set rcond\n  if rcond is None:\n    rcond = len(x) * finfo(x.dtype).eps\n  rcond = core.concrete_or_error(float, rcond, \"rcond must be float\")\n  # set up least squares equation for powers of x\n  lhs = vander(x, order)\n  rhs = y\n\n  # apply weighting\n  if w is not None:\n    _check_arraylike(\"polyfit\", w)\n    w, = _promote_dtypes_inexact(w)\n    if w.ndim != 1:\n      raise TypeError(\"expected a 1-d array for weights\")\n    if w.shape[0] != y.shape[0]:\n      raise TypeError(\"expected w and y to have the same length\")\n    lhs *= w[:, np.newaxis]\n    if rhs.ndim == 2:\n      rhs *= w[:, np.newaxis]\n    else:\n      rhs *= w\n\n  # scale lhs to improve condition number and solve\n  scale = sqrt((lhs*lhs).sum(axis=0))\n  lhs /= scale[np.newaxis,:]\n  c, resids, rank, s = linalg.lstsq(lhs, rhs, rcond)\n  c = (c.T/scale).T  # broadcast scale coefficients\n\n  if full:\n    return c, resids, rank, s, rcond\n  elif cov:\n    Vbase = linalg.inv(dot(lhs.T, lhs))\n    Vbase /= outer(scale, scale)\n    if cov == \"unscaled\":\n      fac = 1\n    else:\n      if len(x) <= order:\n        raise ValueError(\"the number of data points must exceed order \"\n                            \"to scale the covariance matrix\")\n      fac = resids / (len(x) - order)\n      fac = fac[0] #making np.array() of shape (1,) to int\n    if y.ndim == 1:\n      return c, Vbase * fac\n    else:\n      return c, Vbase[:, :, np.newaxis] * fac\n  else:\n    return c\n\n\n_POLY_DOC = \n\n@_wraps(np.poly, lax_description=_POLY_DOC)\n@jit",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.poly, lax_description=_POLY_DOC)\n@jit",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 463,
        "n_words": 293,
        "vocab_size": 155,
        "complexity": 17,
        "nloc": 54,
        "token_counts": 424,
        "n_ast_nodes": 700,
        "n_identifiers": 50,
        "d_id": 26696,
        "documentation": {
            "docstring": "\\\nThis differs from np.poly when an integer array is given.\nnp.poly returns a result with dtype float64 in this case.\njax returns a result with an inexact type, but not necessarily\nfloat64.\n\nThis also differs from np.poly when the input array strictly\ncontains pairs of complex conjugates, e.g. [1j, -1j, 1-1j, 1+1j].\nnp.poly returns an array with a real dtype in such cases.\njax returns an array with a complex dtype in such cases.\n",
            "n_words": 75,
            "vocab_size": 44,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 44419,
        "commit_id": "6fc6edf6af7f676bfa54ff3a2e6e6d2edb938f2e",
        "repo": "airflow",
        "path": "airflow/models/taskinstance.py",
        "file_name": "taskinstance.py",
        "fun_name": "key",
        "commit_message": "Make `airflow dags test` be able to execute Mapped Tasks (#21210)\n\n* Make `airflow dags test` be able to execute Mapped Tasks\r\n\r\nIn order to do this there were two steps required:\r\n\r\n- The BackfillJob needs to know about mapped tasks, both to expand them,\r\n  and in order to update it's TI tracking\r\n- The DebugExecutor needed to \"unmap\" the mapped task to get the real\r\n  operator back\r\n\r\nI was testing this with the following dag:\r\n\r\n```\r\nfrom airflow import DAG\r\nfrom airflow.decorators import task\r\nfrom airflow.operators.python import PythonOperator\r\nimport pendulum\r\n\r\n@task\r\ndef make_list():\r\n    return list(map(lambda a: f'echo \"{a!r}\"', [1, 2, {'a': 'b'}]))\r\n\r\ndef consumer(*args):\r\n     print(repr(args))\r\n\r\nwith DAG(dag_id='maptest', start_date=pendulum.DateTime(2022, 1, 18)) as dag:\r\n    PythonOperator(task_id='consumer', python_callable=consumer).map(op_args=make_list())\r\n```\r\n\r\nIt can't \"unmap\" decorated operators successfully yet, so we're using\r\nold-school PythonOperator\r\n\r\nWe also just pass the whole value to the operator, not just the current\r\nmapping value(s)\r\n\r\n* Always have a `task_group` property on DAGNodes\r\n\r\nAnd since TaskGroup is a DAGNode, we don't need to store parent group\r\ndirectly anymore -- it'll already be stored\r\n\r\n* Add \"integation\" tests for running mapped tasks via BackfillJob\r\n\r\n* Only show \"Map Index\" in Backfill report when relevant\r\n\r\nCo-authored-by: Tzu-ping Chung <uranusjr@gmail.com>",
        "code": "def key(self) -> TaskInstanceKey:\n        \n        return TaskInstanceKey(self.dag_id, self.task_id, self.run_id, self.try_number, self.map_index)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 47,
        "n_identifiers": 8,
        "d_id": 8256,
        "documentation": {
            "docstring": "Returns a tuple that identifies the task instance uniquely",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 264086,
        "commit_id": "f5925fa56f713e78ab5723de2a58195ca346847f",
        "repo": "pyinstaller",
        "path": "PyInstaller/building/utils.py",
        "file_name": "utils.py",
        "fun_name": "_check_guts_toc_mtime",
        "commit_message": "building: cleanup remove pyc argument from _check_guts_toc_mtime\n\nThe only place where we use `_check_guts_toc_mtime` with `pyc`\nargument enabled is when checking the `Analysis.pure` TOC, and\nthe source names of those entries already point to source .py files.\nSo shortening the filenames by one character results in checking\nfor non-existant .p files.\n\nEven if an entry happened to point to a .pyc file, it is highly\nunlikely that there would be an adjacent .py file available,\nbecause under contemporary python 3 versions, that would hide the\n.pyc file from the loader.",
        "code": "def _check_guts_toc_mtime(attr_name, old_toc, new_toc, last_build):\n    \n    for dest_name, src_name, typecode in old_toc:\n        if misc.mtime(src_name) > last_build:\n            logger.info(\"Building because %s changed\", src_name)\n            return True\n    return False\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 62,
        "n_words": 24,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 67,
        "n_identifiers": 12,
        "d_id": 77596,
        "documentation": {
            "docstring": "\n    Rebuild is required if mtimes of files listed in old TOC are newer than last_build.\n\n    Use this for calculated/analysed values read from cache.\n    ",
            "n_words": 23,
            "vocab_size": 23,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 258487,
        "commit_id": "8b6b519caf3b3b9602958a859b4d3a7eb1d9eadd",
        "repo": "scikit-learn",
        "path": "sklearn/random_projection.py",
        "file_name": "random_projection.py",
        "fun_name": "fit",
        "commit_message": "ENH Preserving dtype for np.float32 in RandomProjection (#22114)\n\nCo-authored-by: takoika <>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def fit(self, X, y=None):\n        \n        X = self._validate_data(\n            X, accept_sparse=[\"csr\", \"csc\"], dtype=[np.float64, np.float32]\n        )\n\n        n_samples, n_features = X.shape\n\n        if self.n_components == \"auto\":\n            self.n_components_ = johnson_lindenstrauss_min_dim(\n                n_samples=n_samples, eps=self.eps\n            )\n\n            if self.n_components_ <= 0:\n                raise ValueError(\n                    \"eps=%f and n_samples=%d lead to a target dimension of \"\n                    \"%d which is invalid\" % (self.eps, n_samples, self.n_components_)\n                )\n\n            elif self.n_components_ > n_features:\n                raise ValueError(\n                    \"eps=%f and n_samples=%d lead to a target dimension of \"\n                    \"%d which is larger than the original space with \"\n                    \"n_features=%d\"\n                    % (self.eps, n_samples, self.n_components_, n_features)\n                )\n        else:\n            if self.n_components <= 0:\n                raise ValueError(\n                    \"n_components must be greater than 0, got %s\" % self.n_components\n                )\n\n            elif self.n_components > n_features:\n                warnings.warn(\n                    \"The number of components is higher than the number of\"\n                    \" features: n_features < n_components (%s < %s).\"\n                    \"The dimensionality of the problem will not be reduced.\"\n                    % (n_features, self.n_components),\n                    DataDimensionalityWarning,\n                )\n\n            self.n_components_ = self.n_components\n\n        # Generate a projection matrix of size [n_components, n_features]\n        self.components_ = self._make_random_matrix(\n            self.n_components_, n_features\n        ).astype(X.dtype, copy=False)\n\n        # Check contract\n        assert self.components_.shape == (self.n_components_, n_features), (\n            \"An error has occurred the self.components_ matrix has \"\n            \" not the proper shape.\"\n        )\n\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 760,
        "n_words": 185,
        "vocab_size": 109,
        "complexity": 6,
        "nloc": 43,
        "token_counts": 220,
        "n_ast_nodes": 357,
        "n_identifiers": 25,
        "d_id": 75247,
        "documentation": {
            "docstring": "Generate a sparse random projection matrix.\n\n        Parameters\n        ----------\n        X : {ndarray, sparse matrix} of shape (n_samples, n_features)\n            Training set: only the shape is used to find optimal random\n            matrix dimensions based on the theory referenced in the\n            afore mentioned papers.\n\n        y : Ignored\n            Not used, present here for API consistency by convention.\n\n        Returns\n        -------\n        self : object\n            BaseRandomProjection class instance.\n        ",
            "n_words": 60,
            "vocab_size": 53,
            "n_whitespaces": 171,
            "language": "en"
        }
    },
    {
        "id": 196300,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/geometry/polygon.py",
        "file_name": "polygon.py",
        "fun_name": "bisectors",
        "commit_message": "Updated import locations",
        "code": "def bisectors(self):\n        \n        # use lines containing sides so containment check during\n        # intersection calculation can be avoided, thus reducing\n        # the processing time for calculating the bisectors\n        s = [Line(l) for l in self.sides]\n        v = self.vertices\n        c = self.incenter\n        l1 = Segment(v[0], Line(v[0], c).intersection(s[1])[0])\n        l2 = Segment(v[1], Line(v[1], c).intersection(s[2])[0])\n        l3 = Segment(v[2], Line(v[2], c).intersection(s[0])[0])\n        return {v[0]: l1, v[1]: l2, v[2]: l3}\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 139,
        "n_words": 62,
        "vocab_size": 53,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 143,
        "n_ast_nodes": 213,
        "n_identifiers": 15,
        "d_id": 47800,
        "documentation": {
            "docstring": "The angle bisectors of the triangle.\n\n        An angle bisector of a triangle is a straight line through a vertex\n        which cuts the corresponding angle in half.\n\n        Returns\n        =======\n\n        bisectors : dict\n            Each key is a vertex (Point) and each value is the corresponding\n            bisector (Segment).\n\n        See Also\n        ========\n\n        sympy.geometry.point.Point, sympy.geometry.line.Segment\n\n        Examples\n        ========\n\n        >>> from sympy import Point, Triangle, Segment\n        >>> p1, p2, p3 = Point(0, 0), Point(1, 0), Point(0, 1)\n        >>> t = Triangle(p1, p2, p3)\n        >>> from sympy import sqrt\n        >>> t.bisectors()[p2] == Segment(Point(1, 0), Point(0, sqrt(2) - 1))\n        True\n\n        ",
            "n_words": 91,
            "vocab_size": 63,
            "n_whitespaces": 232,
            "language": "en"
        }
    },
    {
        "id": 90548,
        "commit_id": "a68089d62f514557ec38e3744593e20af484e5e2",
        "repo": "sentry",
        "path": "src/sentry/testutils/cases.py",
        "file_name": "cases.py",
        "fun_name": "get_success_response",
        "commit_message": "ref(tests): Infer `status_code` from `method` (#34825)",
        "code": "def get_success_response(self, *args, **params):\n        \n        status_code = params.pop(\"status_code\", None)\n\n        if status_code and status_code >= 400:\n            raise Exception(\"status_code must be < 400\")\n\n        method = params.pop(\"method\", self.method).lower()\n\n        response = self.get_response(*args, method=method, **params)\n\n        if status_code:\n            assert_status_code(response, status_code)\n        elif method == \"get\":\n            assert_status_code(response, status.HTTP_200_OK)\n        # TODO(mgaeta): Add the other methods.\n        # elif method == \"post\":\n        #     assert_status_code(response, status.HTTP_201_CREATED)\n        elif method == \"put\":\n            assert_status_code(response, status.HTTP_200_OK)\n        elif method == \"delete\":\n            assert_status_code(response, status.HTTP_204_NO_CONTENT)\n        else:\n            # TODO(mgaeta): Add other methods.\n            assert_status_code(response, 200, 300)\n\n        return response\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
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        "token_counts": 126,
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        "n_identifiers": 15,
        "d_id": 18674,
        "documentation": {
            "docstring": "\n        Call `get_response` (see above) and assert the response's status code.\n\n        :param params:\n            * status_code: (Optional) Assert that the response's status code is\n            a specific code. Omit to assert any successful status_code.\n        :returns Response object\n        ",
            "n_words": 34,
            "vocab_size": 29,
            "n_whitespaces": 85,
            "language": "en"
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    },
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        "id": 133189,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/multiprocessing/pool.py",
        "file_name": "pool.py",
        "fun_name": "starmap",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def starmap(self, func, iterable, chunksize=None):\n        \n\n        return self._map_async(\n            func, iterable, chunksize=chunksize, unpack_args=True\n        ).get()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 10,
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        "d_id": 29954,
        "documentation": {
            "docstring": "Same as `map`, but unpacks each element of the iterable as the\n        arguments to func like: [func(*args) for args in iterable].\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 20359,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/formatters/img.py",
        "file_name": "img.py",
        "fun_name": "_get_char_x",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _get_char_x(self, linelength):\n        \n        return linelength + self.image_pad + self.line_number_width\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "n_ast_nodes": 30,
        "n_identifiers": 5,
        "d_id": 3344,
        "documentation": {
            "docstring": "\n        Get the X coordinate of a character position.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 9740,
        "commit_id": "ac3bbcdf87b263f79d5e19cce173e6c709a15f9d",
        "repo": "gensim",
        "path": "gensim/test/test_word2vec.py",
        "file_name": "test_word2vec.py",
        "fun_name": "test_evaluate_word_analogies",
        "commit_message": "streamlining most_similar_cosmul and evaluate_word_analogies (#2656)\n\n* streamlining most_similar_cosmul\r\n\r\n* Fix PR requested changes and add unit test\r\n\r\n* fix merge artifacts\r\n\r\nCo-authored-by: n3hrox <n3hrox@gmail.com>\r\nCo-authored-by: Michael Penkov <m@penkov.dev>",
        "code": "def test_evaluate_word_analogies(self):\n        \n        model = word2vec.Word2Vec(LeeCorpus())\n        score, sections = model.wv.evaluate_word_analogies(datapath('questions-words.txt'))\n        score_cosmul, sections_cosmul = model.wv.evaluate_word_analogies(\n            datapath('questions-words.txt'),\n            similarity_function='most_similar_cosmul'\n        )\n        self.assertEqual(score, score_cosmul)\n        self.assertEqual(sections, sections_cosmul)\n        self.assertGreaterEqual(score, 0.0)\n        self.assertLessEqual(score, 1.0)\n        self.assertGreater(len(sections), 0)\n        # Check that dict contains the right keys\n        first_section = sections[0]\n        self.assertIn('section', first_section)\n        self.assertIn('correct', first_section)\n        self.assertIn('incorrect', first_section)\n",
        "url": "https://github.com/RaRe-Technologies/gensim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 170,
        "n_words": 43,
        "vocab_size": 38,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 127,
        "n_ast_nodes": 206,
        "n_identifiers": 21,
        "d_id": 1666,
        "documentation": {
            "docstring": "Test that evaluating analogies on KeyedVectors give sane results",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 73813,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_default_locale",
        "commit_message": "Reformat with black",
        "code": "def get_default_locale(self):\n        \n        parent = self.get_parent()\n        if parent is not None:\n            return (\n                parent.specific_class.objects.defer()\n                .select_related(\"locale\")\n                .get(id=parent.id)\n                .locale\n            )\n\n        return super().get_default_locale()\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 129,
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        "nloc": 10,
        "token_counts": 55,
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        "n_identifiers": 12,
        "d_id": 16124,
        "documentation": {
            "docstring": "\n        Finds the default locale to use for this page.\n\n        This will be called just before the initial save.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 220750,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/streams.py",
        "file_name": "streams.py",
        "fun_name": "_wait_for_data",
        "commit_message": "add python 3.10.4 for windows",
        "code": "async def _wait_for_data(self, func_name):\n        \n        # StreamReader uses a future to link the protocol feed_data() method\n        # to a read coroutine. Running two read coroutines at the same time\n        # would have an unexpected behaviour. It would not possible to know\n        # which coroutine would get the next data.\n        if self._waiter is not None:\n            raise RuntimeError(\n                f'{func_name}() called while another coroutine is '\n                f'already waiting for incoming data')\n\n        assert not self._eof, '_wait_for_data after EOF'\n\n        # Waiting for data while paused will make deadlock, so prevent it.\n        # This is essential for readexactly(n) for case when n > self._limit.\n        if self._paused:\n            self._paused = False\n            self._transport.resume_reading()\n\n        self._waiter = self._loop.create_future()\n        try:\n            await self._waiter\n        finally:\n            self._waiter = None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 289,
        "n_words": 113,
        "vocab_size": 85,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 72,
        "n_ast_nodes": 133,
        "n_identifiers": 11,
        "d_id": 56110,
        "documentation": {
            "docstring": "Wait until feed_data() or feed_eof() is called.\n\n        If stream was paused, automatically resume it.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 258531,
        "commit_id": "432778464cbffc8ca675c1df786c31f8c23fc62c",
        "repo": "scikit-learn",
        "path": "sklearn/feature_selection/_univariate_selection.py",
        "file_name": "_univariate_selection.py",
        "fun_name": "chi2",
        "commit_message": "[MRG] chi2: reduce memory footprint (#21837)\n\n* added sparse_output=True to LabelBinarizer in chi2\n\n* added changelog entry\n\n* Update sklearn/feature_selection/_univariate_selection.py\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\n\n* Update sklearn/feature_selection/_univariate_selection.py\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\n\nCo-authored-by: Wagner, Louis <louis.wagner@cgm.com>\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>",
        "code": "def chi2(X, y):\n    \n\n    # XXX: we might want to do some of the following in logspace instead for\n    # numerical stability.\n    X = check_array(X, accept_sparse=\"csr\")\n    if np.any((X.data if issparse(X) else X) < 0):\n        raise ValueError(\"Input X must be non-negative.\")\n\n    # Use a sparse representation for Y by default to reduce memory usage when\n    # y has many unique classes.\n    Y = LabelBinarizer(sparse_output=True).fit_transform(y)\n    if Y.shape[1] == 1:\n        Y = Y.toarray()\n        Y = np.append(1 - Y, Y, axis=1)\n\n    observed = safe_sparse_dot(Y.T, X)  # n_classes * n_features\n\n    if issparse(observed):\n        # convert back to a dense array before calling _chisquare\n        # XXX: could _chisquare be reimplement to accept sparse matrices for\n        # cases where both n_classes and n_features are large (and X is\n        # sparse)?\n        observed = observed.toarray()\n\n    feature_count = X.sum(axis=0).reshape(1, -1)\n    class_prob = Y.mean(axis=0).reshape(1, -1)\n    expected = np.dot(class_prob.T, feature_count)\n\n    return _chisquare(observed, expected)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 241,
        "n_words": 139,
        "vocab_size": 99,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 168,
        "n_ast_nodes": 275,
        "n_identifiers": 29,
        "d_id": 75276,
        "documentation": {
            "docstring": "Compute chi-squared stats between each non-negative feature and class.\n\n    This score can be used to select the n_features features with the\n    highest values for the test chi-squared statistic from X, which must\n    contain only non-negative features such as booleans or frequencies\n    (e.g., term counts in document classification), relative to the classes.\n\n    Recall that the chi-square test measures dependence between stochastic\n    variables, so using this function \"weeds out\" the features that are the\n    most likely to be independent of class and therefore irrelevant for\n    classification.\n\n    Read more in the :ref:`User Guide <univariate_feature_selection>`.\n\n    Parameters\n    ----------\n    X : {array-like, sparse matrix} of shape (n_samples, n_features)\n        Sample vectors.\n\n    y : array-like of shape (n_samples,)\n        Target vector (class labels).\n\n    Returns\n    -------\n    chi2 : ndarray of shape (n_features,)\n        Chi2 statistics for each feature.\n\n    p_values : ndarray of shape (n_features,)\n        P-values for each feature.\n\n    Notes\n    -----\n    Complexity of this algorithm is O(n_classes * n_features).\n\n    See Also\n    --------\n    f_classif : ANOVA F-value between label/feature for classification tasks.\n    f_regression : F-value between label/feature for regression tasks.\n    ",
            "n_words": 167,
            "vocab_size": 119,
            "n_whitespaces": 270,
            "language": "en"
        }
    },
    {
        "id": 197297,
        "commit_id": "65be461082dda54c8748922f9c29a19af1279fe1",
        "repo": "sympy",
        "path": "sympy/combinatorics/fp_groups.py",
        "file_name": "fp_groups.py",
        "fun_name": "equals",
        "commit_message": "Remove abbreviations in documentation",
        "code": "def equals(self, word1, word2):\n        \n        if self.reduce(word1*word2**-1) == self.identity:\n            return True\n        elif self._rewriting_system.is_confluent:\n            return False\n        return None\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 66,
        "n_words": 16,
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        "complexity": 3,
        "nloc": 6,
        "token_counts": 40,
        "n_ast_nodes": 64,
        "n_identifiers": 8,
        "d_id": 48440,
        "documentation": {
            "docstring": "\n        Compare `word1` and `word2` for equality in the group\n        using the group's rewriting system. If the system is\n        confluent, the returned answer is necessarily correct.\n        (If it is not, `False` could be returned in some cases\n        where in fact `word1 == word2`)\n\n        ",
            "n_words": 42,
            "vocab_size": 34,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 206250,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/defaulttags.py",
        "file_name": "defaulttags.py",
        "fun_name": "now",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def now(parser, token):\n    \n    bits = token.split_contents()\n    asvar = None\n    if len(bits) == 4 and bits[-2] == \"as\":\n        asvar = bits[-1]\n        bits = bits[:-2]\n    if len(bits) != 2:\n        raise TemplateSyntaxError(\"'now' statement takes one argument\")\n    format_string = bits[1][1:-1]\n    return NowNode(format_string, asvar)\n\n\n@register.tag",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag",
        "n_ast_errors": 1,
        "ast_levels": 11,
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        "d_id": 51441,
        "documentation": {
            "docstring": "\n    Display the date, formatted according to the given string.\n\n    Use the same format as PHP's ``date()`` function; see https://php.net/date\n    for all the possible values.\n\n    Sample usage::\n\n        It is {% now \"jS F Y H:i\" %}\n    ",
            "n_words": 35,
            "vocab_size": 32,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 196310,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/geometry/polygon.py",
        "file_name": "polygon.py",
        "fun_name": "exradii",
        "commit_message": "Updated import locations",
        "code": "def exradii(self):\n        \n\n        side = self.sides\n        a = side[0].length\n        b = side[1].length\n        c = side[2].length\n        s = (a+b+c)/2\n        area = self.area\n        exradii = {self.sides[0]: simplify(area/(s-a)),\n                   self.sides[1]: simplify(area/(s-b)),\n                   self.sides[2]: simplify(area/(s-c))}\n\n        return exradii\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "documentation": {
            "docstring": "The radius of excircles of a triangle.\n\n        An excircle of the triangle is a circle lying outside the triangle,\n        tangent to one of its sides and tangent to the extensions of the\n        other two.\n\n        Returns\n        =======\n\n        exradii : dict\n\n        See Also\n        ========\n\n        sympy.geometry.polygon.Triangle.inradius\n\n        Examples\n        ========\n\n        The exradius touches the side of the triangle to which it is keyed, e.g.\n        the exradius touching side 2 is:\n\n        >>> from sympy import Point, Triangle\n        >>> p1, p2, p3 = Point(0, 0), Point(6, 0), Point(0, 2)\n        >>> t = Triangle(p1, p2, p3)\n        >>> t.exradii[t.sides[2]]\n        -2 + sqrt(10)\n\n        References\n        ==========\n\n        [1] http://mathworld.wolfram.com/Exradius.html\n        [2] http://mathworld.wolfram.com/Excircles.html\n\n        ",
            "n_words": 99,
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            "language": "en"
        }
    },
    {
        "id": 196398,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/matrices/repmatrix.py",
        "file_name": "repmatrix.py",
        "fun_name": "col_swap",
        "commit_message": "Moved imports to higher level",
        "code": "def col_swap(self, i, j):\n        \n        for k in range(0, self.rows):\n            self[k, i], self[k, j] = self[k, j], self[k, i]\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
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        "vocab_size": 15,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 49,
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        "d_id": 47898,
        "documentation": {
            "docstring": "Swap the two given columns of the matrix in-place.\n\n        Examples\n        ========\n\n        >>> from sympy import Matrix\n        >>> M = Matrix([[1, 0], [1, 0]])\n        >>> M\n        Matrix([\n        [1, 0],\n        [1, 0]])\n        >>> M.col_swap(0, 1)\n        >>> M\n        Matrix([\n        [0, 1],\n        [0, 1]])\n\n        See Also\n        ========\n\n        col\n        row_swap\n        ",
            "n_words": 45,
            "vocab_size": 31,
            "n_whitespaces": 171,
            "language": "en"
        }
    },
    {
        "id": 20769,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/rich/live.py",
        "file_name": "live.py",
        "fun_name": "renderable",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def renderable(self) -> RenderableType:\n        \n        renderable = self.get_renderable()\n        return Screen(renderable) if self._alt_screen else renderable\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "vocab_size": 12,
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        "d_id": 3534,
        "documentation": {
            "docstring": "Get the renderable that is being displayed\n\n        Returns:\n            RenderableType: Displayed renderable.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 75927,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/snippets/action_menu.py",
        "file_name": "action_menu.py",
        "fun_name": "get_base_snippet_action_menu_items",
        "commit_message": "Reformat with black",
        "code": "def get_base_snippet_action_menu_items(model):\n    \n    menu_items = [\n        SaveMenuItem(order=0),\n        DeleteMenuItem(order=10),\n    ]\n\n    for hook in hooks.get_hooks(\"register_snippet_action_menu_item\"):\n        action_menu_item = hook(model)\n        if action_menu_item:\n            menu_items.append(action_menu_item)\n\n    return menu_items\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 74,
        "n_words": 20,
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        "nloc": 10,
        "token_counts": 51,
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        "n_identifiers": 11,
        "d_id": 16441,
        "documentation": {
            "docstring": "\n    Retrieve the global list of menu items for the snippet action menu,\n    which may then be customised on a per-request basis\n    ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 204387,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/cache/backends/base.py",
        "file_name": "base.py",
        "fun_name": "has_key",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def has_key(self, key, version=None):\n        \n        return (\n            self.get(key, self._missing_key, version=version) is not self._missing_key\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 10,
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        "d_id": 50721,
        "documentation": {
            "docstring": "\n        Return True if the key is in the cache and has not expired.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 319887,
        "commit_id": "0fdd3d56f43c8442a0c9ecd3cad07a88137ff7de",
        "repo": "paperless-ngx",
        "path": ".github/scripts/cleanup-tags.py",
        "file_name": "cleanup-tags.py",
        "fun_name": "_read_all_pages",
        "commit_message": "Changes the cleanup images workflow so it uses a OAuth token with the correct scope (GITHUB_TOKEN is not enough).  Also prevents running if the token is not defined and generally does commenting/cleanups\"",
        "code": "def _read_all_pages(self, endpoint):\n        \n        internal_data = []\n\n        while True:\n            resp = self._session.get(endpoint)\n            if resp.status_code == 200:\n                internal_data += resp.json()\n                if \"next\" in resp.links:\n                    endpoint = resp.links[\"next\"][\"url\"]\n                else:\n                    logger.debug(\"Exiting pagination loop\")\n                    break\n            else:\n                logger.warning(f\"Request to {endpoint} return HTTP {resp.status_code}\")\n                break\n\n        return internal_data\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 233,
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        "vocab_size": 32,
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        "nloc": 15,
        "token_counts": 78,
        "n_ast_nodes": 149,
        "n_identifiers": 13,
        "d_id": 117014,
        "documentation": {
            "docstring": "\n        Internal function to read all pages of an endpoint, utilizing the\n        next.url until exhausted\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 224209,
        "commit_id": "dca7cbb43fcd6ea7c677c98ba585395b070d387b",
        "repo": "mkdocs",
        "path": "mkdocs/commands/build.py",
        "file_name": "build.py",
        "fun_name": "_build_template",
        "commit_message": "Format code with `black -l100 --skip-string-normalization`",
        "code": "def _build_template(name, template, files, config, nav):\n    \n\n    # Run `pre_template` plugin events.\n    template = config['plugins'].run_event(\n        'pre_template', template, template_name=name, config=config\n    )\n\n    if utils.is_error_template(name):\n        # Force absolute URLs in the nav of error pages and account for the\n        # possibility that the docs root might be different than the server root.\n        # See https://github.com/mkdocs/mkdocs/issues/77.\n        # However, if site_url is not set, assume the docs root and server root\n        # are the same. See https://github.com/mkdocs/mkdocs/issues/1598.\n        base_url = urlsplit(config['site_url'] or '/').path\n    else:\n        base_url = utils.get_relative_url('.', name)\n\n    context = get_context(nav, files, config, base_url=base_url)\n\n    # Run `template_context` plugin events.\n    context = config['plugins'].run_event(\n        'template_context', context, template_name=name, config=config\n    )\n\n    output = template.render(context)\n\n    # Run `post_template` plugin events.\n    output = config['plugins'].run_event('post_template', output, template_name=name, config=config)\n\n    return output\n\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 221,
        "n_words": 116,
        "vocab_size": 73,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 134,
        "n_ast_nodes": 221,
        "n_identifiers": 18,
        "d_id": 57244,
        "documentation": {
            "docstring": "\n    Return rendered output for given template as a string.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 224944,
        "commit_id": "df3739d51903ab56771ac071a05b5aa9cdf9e129",
        "repo": "mkdocs",
        "path": "mkdocs/utils/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_build_datetime",
        "commit_message": "Add a lot more type annotations, fix new type warnings (#2970)\n\n(including some behavior changes, assumed to be no-op)\r\n\r\nThis is based on auto-generated annotations from \"monkeytype\".",
        "code": "def get_build_datetime() -> datetime:\n    \n    source_date_epoch = os.environ.get('SOURCE_DATE_EPOCH')\n    if source_date_epoch is None:\n        return datetime.now(timezone.utc)\n\n    return datetime.fromtimestamp(int(source_date_epoch), timezone.utc)\n\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 45,
        "n_ast_nodes": 76,
        "n_identifiers": 11,
        "d_id": 57432,
        "documentation": {
            "docstring": "\n    Returns an aware datetime object.\n\n    Support SOURCE_DATE_EPOCH environment variable for reproducible builds.\n    See https://reproducible-builds.org/specs/source-date-epoch/\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 192301,
        "commit_id": "c50d48845f7b1ca86d6a3b7f37a59be0ae11e36b",
        "repo": "vision",
        "path": "test/test_video_reader.py",
        "file_name": "test_video_reader.py",
        "fun_name": "test_read_video_from_file_audio_resampling",
        "commit_message": "Improve test_video_reader (#5498)\n\n* Improve test_video_reader\r\n\r\n* Fix linter error",
        "code": "def test_read_video_from_file_audio_resampling(self, test_video, samples):\n        \n        # video related\n        width, height, min_dimension, max_dimension = 0, 0, 0, 0\n        video_start_pts, video_end_pts = 0, -1\n        video_timebase_num, video_timebase_den = 0, 1\n        # audio related\n        channels = 0\n        audio_start_pts, audio_end_pts = 0, -1\n        audio_timebase_num, audio_timebase_den = 0, 1\n\n        full_path = os.path.join(VIDEO_DIR, test_video)\n\n        tv_result = torch.ops.video_reader.read_video_from_file(\n            full_path,\n            SEEK_FRAME_MARGIN,\n            0,  # getPtsOnly\n            1,  # readVideoStream\n            width,\n            height,\n            min_dimension,\n            max_dimension,\n            video_start_pts,\n            video_end_pts,\n            video_timebase_num,\n            video_timebase_den,\n            1,  # readAudioStream\n            samples,\n            channels,\n            audio_start_pts,\n            audio_end_pts,\n            audio_timebase_num,\n            audio_timebase_den,\n        )\n        (\n            vframes,\n            vframe_pts,\n            vtimebase,\n            vfps,\n            vduration,\n            aframes,\n            aframe_pts,\n            atimebase,\n            asample_rate,\n            aduration,\n        ) = tv_result\n        if aframes.numel() > 0:\n            assert samples == asample_rate.item()\n            assert 1 == aframes.size(1)\n            # when audio stream is found\n            duration = float(aframe_pts[-1]) * float(atimebase[0]) / float(atimebase[1])\n            assert aframes.size(0) == approx(int(duration * asample_rate.item()), abs=0.1 * asample_rate.item())\n",
        "url": "https://github.com/pytorch/vision.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 605,
        "n_words": 123,
        "vocab_size": 80,
        "complexity": 2,
        "nloc": 46,
        "token_counts": 228,
        "n_ast_nodes": 327,
        "n_identifiers": 46,
        "d_id": 46871,
        "documentation": {
            "docstring": "\n        Test the case when decoder starts with a video file to decode frames, and\n        audio waveform are resampled\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 66950,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/payroll/report/income_tax_deductions/income_tax_deductions.py",
        "file_name": "income_tax_deductions.py",
        "fun_name": "get_data",
        "commit_message": "style: format code with black",
        "code": "def get_data(filters):\n\n\tdata = []\n\n\tif erpnext.get_region() == \"India\":\n\t\temployee_pan_dict = frappe._dict(\n\t\t\tfrappe.db.sql()\n\t\t)\n\n\tcomponent_types = frappe.db.sql(\n\t\t\n\t)\n\n\tcomponent_types = [comp_type[0] for comp_type in component_types]\n\n\tif not len(component_types):\n\t\treturn []\n\n\tconditions = get_conditions(filters)\n\n\tentry = frappe.db.sql(\n\t\t\n\t\t% (conditions, \", \".join([\"%s\"] * len(component_types))),\n\t\ttuple(component_types),\n\t\tas_dict=1,\n\t)\n\n\tfor d in entry:\n\n\t\temployee = {\n\t\t\t\"employee\": d.employee,\n\t\t\t\"employee_name\": d.employee_name,\n\t\t\t\"it_comp\": d.salary_component,\n\t\t\t\"posting_date\": d.posting_date,\n\t\t\t# \"pan_number\": employee_pan_dict.get(d.employee),\n\t\t\t\"it_amount\": d.amount,\n\t\t\t\"gross_pay\": d.gross_pay,\n\t\t}\n\n\t\tif erpnext.get_region() == \"India\":\n\t\t\temployee[\"pan_number\"] = employee_pan_dict.get(d.employee)\n\n\t\tdata.append(employee)\n\n\treturn data\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 47,
        "n_words": 78,
        "vocab_size": 57,
        "complexity": 6,
        "nloc": 40,
        "token_counts": 184,
        "n_ast_nodes": 310,
        "n_identifiers": 28,
        "d_id": 14386,
        "documentation": {
            "docstring": " select employee, pan_number from `tabEmployee` select name from `tabSalary Component`\n\t\twhere is_income_tax_component = 1  select sal.employee, sal.employee_name, sal.posting_date, ded.salary_component, ded.amount,sal.gross_pay\n\t\tfrom `tabSalary Slip` sal, `tabSalary Detail` ded\n\t\twhere sal.name = ded.parent\n\t\tand ded.parentfield = 'deductions'\n\t\tand ded.parenttype = 'Salary Slip'\n\t\tand sal.docstatus = 1 %s\n\t\tand ded.salary_component in (%s)\n\t",
            "n_words": 49,
            "vocab_size": 34,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 206640,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/encoding.py",
        "file_name": "encoding.py",
        "fun_name": "smart_str",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def smart_str(s, encoding=\"utf-8\", strings_only=False, errors=\"strict\"):\n    \n    if isinstance(s, Promise):\n        # The input is the result of a gettext_lazy() call.\n        return s\n    return force_str(s, encoding, strings_only, errors)\n\n\n_PROTECTED_TYPES = (\n    type(None),\n    int,\n    float,\n    Decimal,\n    datetime.datetime,\n    datetime.date,\n    datetime.time,\n)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 78,
        "n_words": 36,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 97,
        "n_identifiers": 16,
        "d_id": 51599,
        "documentation": {
            "docstring": "\n    Return a string representing 's'. Treat bytestrings using the 'encoding'\n    codec.\n\n    If strings_only is True, don't convert (some) non-string-like objects.\n    ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 178818,
        "commit_id": "613c31d98f20bdd9a4e5884c99826a06a3328438",
        "repo": "Nuitka",
        "path": "nuitka/Options.py",
        "file_name": "Options.py",
        "fun_name": "mayDisableConsoleWindow",
        "commit_message": "Standalone: Added support for requiring modes\n\n* For wx on macOS, console must be disabled, avoid the trap.\n\n* For the PySide2, on macOS the --onefile must be used when the\n  application bundle is built or else signing has issues.\n\n* Recommend to use new option --disable-console for PySide2, PySide6\n and wx on non-macOS",
        "code": "def mayDisableConsoleWindow():\n    \n\n    # TODO: What about MSYS2?\n    return isWin32Windows() or isMacOS()\n\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 13,
        "n_ast_nodes": 27,
        "n_identifiers": 3,
        "d_id": 42834,
        "documentation": {
            "docstring": ":returns: bool derived from platform support of disabling the console,",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 248480,
        "commit_id": "7bc08f320147a1d80371eb13258328c88073fad0",
        "repo": "synapse",
        "path": "tests/test_mau.py",
        "file_name": "test_mau.py",
        "fun_name": "test_as_ignores_mau",
        "commit_message": "Remove remaining bits of groups code. (#12936)\n\n* Update worker docs to remove group endpoints.\r\n* Removes an unused parameter to `ApplicationService`.\r\n* Break dependency between media repo and groups.\r\n* Avoid copying `m.room.related_groups` state events during room upgrades.",
        "code": "def test_as_ignores_mau(self):\n        \n\n        # Create and sync so that the MAU counts get updated\n        token1 = self.create_user(\"kermit1\")\n        self.do_sync_for_user(token1)\n        token2 = self.create_user(\"kermit2\")\n        self.do_sync_for_user(token2)\n\n        # check we're testing what we think we are: there should be two active users\n        self.assertEqual(self.get_success(self.store.get_monthly_active_count()), 2)\n\n        # We've created and activated two users, we shouldn't be able to\n        # register new users\n        with self.assertRaises(SynapseError) as cm:\n            self.create_user(\"kermit3\")\n\n        e = cm.exception\n        self.assertEqual(e.code, 403)\n        self.assertEqual(e.errcode, Codes.RESOURCE_LIMIT_EXCEEDED)\n\n        # Cheekily add an application service that we use to register a new user\n        # with.\n        as_token = \"foobartoken\"\n        self.store.services_cache.append(\n            ApplicationService(\n                token=as_token,\n                id=\"SomeASID\",\n                sender=\"@as_sender:test\",\n                namespaces={\"users\": [{\"regex\": \"@as_*\", \"exclusive\": True}]},\n            )\n        )\n\n        self.create_user(\"as_kermit4\", token=as_token, appservice=True)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 333,
        "n_words": 100,
        "vocab_size": 79,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 163,
        "n_ast_nodes": 272,
        "n_identifiers": 28,
        "d_id": 72300,
        "documentation": {
            "docstring": "Test that application services can still create users when the MAU\n        limit has been reached. This only works when application service\n        user ip tracking is disabled.\n        ",
            "n_words": 26,
            "vocab_size": 24,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 86878,
        "commit_id": "941184cd24186324fd9f7f304b7f713041834726",
        "repo": "sentry",
        "path": "src/sentry/region_to_control/producer.py",
        "file_name": "producer.py",
        "fun_name": "get_region_to_control_producer",
        "commit_message": "chore(hybrid-cloud): AuditLogEntry is a control silo model now (#39890)\n\nIn the control silo, creating an audit log entry writes to the db\r\ndirectly, whilst in region silo mode creating an audit log entry will\r\ninstead push to a new kafka producer that consumes into the control silo\r\nasynchronously.",
        "code": "def get_region_to_control_producer() -> KafkaProducer:\n    \n    global _publisher\n    if _publisher is None:\n        config = settings.KAFKA_TOPICS.get(settings.KAFKA_REGION_TO_CONTROL)\n        _publisher = KafkaProducer(\n            kafka_config.get_kafka_producer_cluster_options(config[\"cluster\"])\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 59,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 48,
        "n_ast_nodes": 69,
        "n_identifiers": 10,
        "d_id": 18181,
        "documentation": {
            "docstring": "\n    Creates, if necessary, an arroyo.KafkaProducer client configured for region to control communication and returns\n    it, caching it for future calls.  Installs an exit handler to close the worker thread processes.\n    ",
            "n_words": 30,
            "vocab_size": 27,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 240862,
        "commit_id": "5dc67fa7a7314cab97d4c96a30fdf4c5661c9039",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/basedatatypes.py",
        "file_name": "basedatatypes.py",
        "fun_name": "get_subplot",
        "commit_message": "fix subplot imports",
        "code": "def get_subplot(self, row, col, secondary_y=False):\n        \n        from plotly._subplots import _get_grid_subplot\n\n        return _get_grid_subplot(self, row, col, secondary_y)\n\n    # Child property operations\n    # -------------------------",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 47,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 47,
        "n_identifiers": 8,
        "d_id": 68972,
        "documentation": {
            "docstring": "\n        Return an object representing the subplot at the specified row\n        and column.  May only be used on Figures created using\n        plotly.tools.make_subplots\n\n        Parameters\n        ----------\n        row: int\n            1-based index of subplot row\n        col: int\n            1-based index of subplot column\n        secondary_y: bool\n            If True, select the subplot that consists of the x-axis and the\n            secondary y-axis at the specified row/col. Only valid if the\n            subplot at row/col is an 2D cartesian subplot that was created\n            with a secondary y-axis.  See the docstring for the specs argument\n            to make_subplots for more info on creating a subplot with a\n            secondary y-axis.\n        Returns\n        -------\n        subplot\n            * None: if subplot is empty\n            * plotly.graph_objs.layout.Scene: if subplot type is 'scene'\n            * plotly.graph_objs.layout.Polar: if subplot type is 'polar'\n            * plotly.graph_objs.layout.Ternary: if subplot type is 'ternary'\n            * plotly.graph_objs.layout.Mapbox: if subplot type is 'ternary'\n            * SubplotDomain namedtuple with `x` and `y` fields:\n              if subplot type is 'domain'.\n                - x: length 2 list of the subplot start and stop width\n                - y: length 2 list of the subplot start and stop height\n            * SubplotXY namedtuple with `xaxis` and `yaxis` fields:\n              if subplot type is 'xy'.\n                - xaxis: plotly.graph_objs.layout.XAxis instance for subplot\n                - yaxis: plotly.graph_objs.layout.YAxis instance for subplot\n        ",
            "n_words": 195,
            "vocab_size": 99,
            "n_whitespaces": 533,
            "language": "en"
        }
    },
    {
        "id": 199152,
        "commit_id": "e0aaa724190c49f2725bb7880eddd13ce4fef4b7",
        "repo": "sympy",
        "path": "sympy/polys/matrices/linsolve.py",
        "file_name": "linsolve.py",
        "fun_name": "_linear_eq_to_dict",
        "commit_message": "more efficient coefficient extraction",
        "code": "def _linear_eq_to_dict(eqs, syms):\n    \n    coeffs = []\n    ind = []\n    symset = set(syms)\n    for i, e in enumerate(eqs):\n        c, d = _lin_eq2dict(e, symset)\n        coeffs.append(d)\n        ind.append(c)\n    return coeffs, ind\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 66,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 58,
        "n_ast_nodes": 95,
        "n_identifiers": 14,
        "d_id": 49169,
        "documentation": {
            "docstring": "Convert a system Expr/Eq equations into dict form, returning\n    the coefficient dictionaries and a list of syms-independent terms\n    from each expression in ``eqs```.\n\n    Examples\n    ========\n\n    >>> from sympy.polys.matrices.linsolve import _linear_eq_to_dict\n    >>> from sympy.abc import x\n    >>> _linear_eq_to_dict([2*x + 3], {x})\n    ([{x: 2}], [3])\n    ",
            "n_words": 43,
            "vocab_size": 37,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 136916,
        "commit_id": "b52a81b3de6f4b7015c6694049d094f2964e1c96",
        "repo": "ray",
        "path": "rllib/env/wrappers/model_vector_env.py",
        "file_name": "model_vector_env.py",
        "fun_name": "vector_reset",
        "commit_message": "[RLlib] Preparation for gymnasium/gym0.26 upgrade: Deprecate `horizon` and `soft_horizon` settings. (#30583)",
        "code": "def vector_reset(self):\n        \n        self.cur_obs = [e.reset() for e in self.envs]\n        self._timesteps = [0 for _ in range(self.num_envs)]\n        return self.cur_obs\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 46,
        "n_words": 18,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 43,
        "n_ast_nodes": 69,
        "n_identifiers": 10,
        "d_id": 31023,
        "documentation": {
            "docstring": "Override parent to store actual env obs for upcoming predictions.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 100610,
        "commit_id": "60291d49c4da1cd260fbc0b04aa6a312eedfefbb",
        "repo": "faceswap",
        "path": "plugins/convert/writer/_base.py",
        "file_name": "_base.py",
        "fun_name": "cache_frame",
        "commit_message": "ffmpeg writer: Create new filename if output pre-exists",
        "code": "def cache_frame(self, filename, image) -> None:\n        \n        frame_no = int(re.search(self.re_search, filename).group())\n        self.cache[frame_no] = image\n        logger.trace(\"Added to cache. Frame no: %s\", frame_no)\n        logger.trace(\"Current cache: %s\", sorted(self.cache.keys()))\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 59,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 64,
        "n_ast_nodes": 105,
        "n_identifiers": 15,
        "d_id": 20072,
        "documentation": {
            "docstring": " Add the incoming converted frame to the cache ready for writing out.\n\n        Used for ffmpeg and gif writers to ensure that the frames are written out in the correct\n        order.\n\n        Parameters\n        ----------\n        filename: str\n            The filename of the incoming frame, where the frame index can be extracted from\n        image: class:`numpy.ndarray`\n            The converted frame corresponding to the given filename\n        ",
            "n_words": 58,
            "vocab_size": 43,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 64335,
        "commit_id": "b68a99675d12a1ffbda538ee07a2020ba66fb3cc",
        "repo": "erpnext",
        "path": "erpnext/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "allow_regional",
        "commit_message": "fix: allow `regional_overrides` hook to be set in subsequent apps",
        "code": "def allow_regional(fn):\n\t\n\n\tdef caller(*args, **kwargs):\n\t\toverrides = frappe.get_hooks(\"regional_overrides\", {}).get(get_region())\n\t\tfunction_path = f\"{inspect.getmodule(fn).__name__}.{fn.__name__}\"\n\n\t\tif not overrides or function_path not in overrides:\n\t\t\treturn fn(*args, **kwargs)\n\n\t\t# Priority given to last installed app\n\t\treturn frappe.get_attr(overrides[function_path][-1])(*args, **kwargs)\n\n\treturn caller\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 26,
        "n_words": 35,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 10,
        "n_ast_nodes": 152,
        "n_identifiers": 15,
        "d_id": 13605,
        "documentation": {
            "docstring": "Decorator to make a function regionally overridable\n\n\tExample:\n\t@erpnext.allow_regional\n\tdef myfunction():\n\t  pass",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 243725,
        "commit_id": "2ae55ccbdad9c842929fb238ea1eb81d1f999024",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "getchannel",
        "commit_message": "Improve exception traceback readability",
        "code": "def getchannel(self, channel):\n        \n        self.load()\n\n        if isinstance(channel, str):\n            try:\n                channel = self.getbands().index(channel)\n            except ValueError as e:\n                msg = f'The image has no channel \"{channel}\"'\n                raise ValueError(msg) from e\n\n        return self._new(self.im.getband(channel))\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 124,
        "n_words": 29,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 65,
        "n_ast_nodes": 112,
        "n_identifiers": 14,
        "d_id": 70094,
        "documentation": {
            "docstring": "\n        Returns an image containing a single channel of the source image.\n\n        :param channel: What channel to return. Could be index\n          (0 for \"R\" channel of \"RGB\") or channel name\n          (\"A\" for alpha channel of \"RGBA\").\n        :returns: An image in \"L\" mode.\n\n        .. versionadded:: 4.3.0\n        ",
            "n_words": 44,
            "vocab_size": 36,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 100872,
        "commit_id": "94c3dcff7ebd02a5a5758f33a3eb2bfc66282117",
        "repo": "faceswap",
        "path": "plugins/train/model/_base/model.py",
        "file_name": "model.py",
        "fun_name": "_update_legacy_config",
        "commit_message": "Training updates\n  - Add multiple selected loss functions\n  - Unlock loss as a model configuration\n  - Phaze-A remove encoder scaling max xap",
        "code": "def _update_legacy_config(self) -> bool:\n        \n        logger.debug(\"Checking for legacy state file update\")\n        priors = [\"dssim_loss\", \"mask_type\", \"mask_type\", \"l2_reg_term\"]\n        new_items = [\"loss_function\", \"learn_mask\", \"mask_type\", \"loss_function_2\"]\n        updated = False\n        for old, new in zip(priors, new_items):\n            if old not in self._config:\n                logger.debug(\"Legacy item '%s' not in config. Skipping update\", old)\n                continue\n\n            # dssim_loss > loss_function\n            if old == \"dssim_loss\":\n                self._config[new] = \"ssim\" if self._config[old] else \"mae\"\n                del self._config[old]\n                updated = True\n                logger.info(\"Updated config from legacy dssim format. New config loss \"\n                            \"function: '%s'\", self._config[new])\n                continue\n\n            # Add learn mask option and set to True if model has \"penalized_mask_loss\" specified\n            if old == \"mask_type\" and new == \"learn_mask\" and new not in self._config:\n                self._config[new] = self._config[\"mask_type\"] is not None\n                updated = True\n                logger.info(\"Added new 'learn_mask' config item for this model. Value set to: %s\",\n                            self._config[new])\n                continue\n\n            # Replace removed masks with most similar equivalent\n            if old == \"mask_type\" and new == \"mask_type\" and self._config[old] in (\"facehull\",\n                                                                                   \"dfl_full\"):\n                old_mask = self._config[old]\n                self._config[new] = \"components\"\n                updated = True\n                logger.info(\"Updated 'mask_type' from '%s' to '%s' for this model\",\n                            old_mask, self._config[new])\n\n            # Replace l2_reg_term with the correct loss_2_function and update the value of\n            # loss_2_weight\n            if old == \"l2_reg_term\":\n                self._config[new] = \"mse\"\n                self._config[\"loss_weight_2\"] = self._config[old]\n                del self._config[old]\n                updated = True\n                logger.info(\"Updated config from legacy 'l2_reg_term' to 'loss_function_2'\")\n\n        logger.debug(\"State file updated for legacy config: %s\", updated)\n        return updated\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 846,
        "n_words": 217,
        "vocab_size": 116,
        "complexity": 12,
        "nloc": 60,
        "token_counts": 272,
        "n_ast_nodes": 471,
        "n_identifiers": 14,
        "d_id": 20323,
        "documentation": {
            "docstring": " Legacy updates for new config additions.\n\n        When new config items are added to the Faceswap code, existing model state files need to be\n        updated to handle these new items.\n\n        Current existing legacy update items:\n\n            * loss - If old `dssim_loss` is ``true`` set new `loss_function` to `ssim` otherwise\n            set it to `mae`. Remove old `dssim_loss` item\n\n            * l2_reg_term - If this exists, set loss_function_2 to ``mse`` and loss_weight_2 to\n            the value held in the old ``l2_reg_term`` item\n\n            * masks - If `learn_mask` does not exist then it is set to ``True`` if `mask_type` is\n            not ``None`` otherwise it is set to ``False``.\n\n            * masks type - Replace removed masks 'dfl_full' and 'facehull' with `components` mask\n\n        Returns\n        -------\n        bool\n            ``True`` if legacy items exist and state file has been updated, otherwise ``False``\n        ",
            "n_words": 131,
            "vocab_size": 82,
            "n_whitespaces": 269,
            "language": "en"
        }
    },
    {
        "id": 102634,
        "commit_id": "89f15f591cc3cc3e8ae40e95ffc802f7f2561ece",
        "repo": "chia-blockchain",
        "path": "chia/types/spend_bundle.py",
        "file_name": "spend_bundle.py",
        "fun_name": "get_memos",
        "commit_message": "Merge standalone wallet into main (#9793)\n\n* wallet changes from pac\r\n\r\n* cat changes\r\n\r\n* pool tests\r\n\r\n* pooling tests passing\r\n\r\n* offers\r\n\r\n* lint\r\n\r\n* mempool_mode\r\n\r\n* black\r\n\r\n* linting\r\n\r\n* workflow files\r\n\r\n* flake8\r\n\r\n* more cleanup\r\n\r\n* renamed\r\n\r\n* remove obsolete test, don't cast announcement\r\n\r\n* memos are not only bytes32\r\n\r\n* trade renames\r\n\r\n* fix rpcs, block_record\r\n\r\n* wallet rpc, recompile settlement clvm\r\n\r\n* key derivation\r\n\r\n* clvm tests\r\n\r\n* lgtm issues and wallet peers\r\n\r\n* stash\r\n\r\n* rename\r\n\r\n* mypy linting\r\n\r\n* flake8\r\n\r\n* bad initializer\r\n\r\n* flaky tests\r\n\r\n* Make CAT wallets only create on verified hints (#9651)\r\n\r\n* fix clvm tests\r\n\r\n* return to log lvl warn\r\n\r\n* check puzzle unhardened\r\n\r\n* public key, not bytes. api caching change\r\n\r\n* precommit changes\r\n\r\n* remove unused import\r\n\r\n* mypy ci file, tests\r\n\r\n* ensure balance before creating a tx\r\n\r\n* Remove CAT logic from full node test (#9741)\r\n\r\n* Add confirmations and sleeps for wallet (#9742)\r\n\r\n* use pool executor\r\n\r\n* rever merge mistakes/cleanup\r\n\r\n* Fix trade test flakiness (#9751)\r\n\r\n* remove precommit\r\n\r\n* older version of black\r\n\r\n* lint only in super linter\r\n\r\n* Make announcements in RPC be objects instead of bytes (#9752)\r\n\r\n* Make announcements in RPC be objects instead of bytes\r\n\r\n* Lint\r\n\r\n* misc hint'ish cleanup (#9753)\r\n\r\n* misc hint'ish cleanup\r\n\r\n* unremove some ci bits\r\n\r\n* Use main cached_bls.py\r\n\r\n* Fix bad merge in main_pac (#9774)\r\n\r\n* Fix bad merge at 71da0487b9cd5564453ec24b76f1ac773c272b75\r\n\r\n* Remove unused ignores\r\n\r\n* more unused ignores\r\n\r\n* Fix bad merge at 3b143e705057d6c14e2fb3e00078aceff0552d7e\r\n\r\n* One more byte32.from_hexstr\r\n\r\n* Remove obsolete test\r\n\r\n* remove commented out\r\n\r\n* remove duplicate payment object\r\n\r\n* remove long sync\r\n\r\n* remove unused test, noise\r\n\r\n* memos type\r\n\r\n* bytes32\r\n\r\n* make it clear it's a single state at a time\r\n\r\n* copy over asset ids from pacr\r\n\r\n* file endl linter\r\n\r\n* Update chia/server/ws_connection.py\r\n\r\nCo-authored-by: dustinface <35775977+xdustinface@users.noreply.github.com>\r\n\r\nCo-authored-by: Matt Hauff <quexington@gmail.com>\r\nCo-authored-by: Kyle Altendorf <sda@fstab.net>\r\nCo-authored-by: dustinface <35775977+xdustinface@users.noreply.github.com>",
        "code": "def get_memos(self) -> Dict[bytes32, List[bytes]]:\n        \n        memos: Dict[bytes32, List[bytes]] = {}\n        for coin_spend in self.coin_spends:\n            result = Program.from_bytes(bytes(coin_spend.puzzle_reveal)).run(\n                Program.from_bytes(bytes(coin_spend.solution))\n            )\n            for condition in result.as_python():\n                if condition[0] == ConditionOpcode.CREATE_COIN and len(condition) >= 4:\n                    # If only 3 elements (opcode + 2 args), there is no memo, this is ph, amount\n                    coin_added = Coin(coin_spend.coin.name(), bytes32(condition[1]), int_from_bytes(condition[2]))\n                    if type(condition[3]) != list:\n                        # If it's not a list, it's not the correct format\n                        continue\n                    memos[coin_added.name()] = condition[3]\n        return memos\n\n    # Note that `coin_spends` used to have the bad name `coin_solutions`.\n    # Some API still expects this name. For now, we accept both names.\n    #\n    # TODO: continue this deprecation. Eventually, all code below here should be removed.\n    #  1. set `exclude_modern_keys` to `False` (and manually set to `True` where necessary)\n    #  2. set `include_legacy_keys` to `False` (and manually set to `False` where necessary)\n    #  3. remove all references to `include_legacy_keys=True`\n    #  4. remove all code below this point\n",
        "url": "https://github.com/Chia-Network/chia-blockchain.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 394,
        "n_words": 153,
        "vocab_size": 109,
        "complexity": 6,
        "nloc": 18,
        "token_counts": 146,
        "n_ast_nodes": 235,
        "n_identifiers": 27,
        "d_id": 21558,
        "documentation": {
            "docstring": "\n        Retrieves the memos for additions in this spend_bundle, which are formatted as a list in the 3rd parameter of\n        CREATE_COIN. If there are no memos, the addition coin_id is not included. If they are not formatted as a list\n        of bytes, they are not included. This is expensive to call, it should not be used in full node code.\n        ",
            "n_words": 59,
            "vocab_size": 40,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 261652,
        "commit_id": "758fe0d9c72ba343097003e7992c9239e58bfc63",
        "repo": "scikit-learn",
        "path": "sklearn/model_selection/tests/test_plot.py",
        "file_name": "test_plot.py",
        "fun_name": "test_learning_curve_display_default_usage",
        "commit_message": "FEA add LearningCurveDisplay to show plot learning curve (#24084)\n\nCo-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>\r\nCo-authored-by: Arturo Amor <86408019+ArturoAmorQ@users.noreply.github.com>",
        "code": "def test_learning_curve_display_default_usage(pyplot, data):\n    \n    X, y = data\n    estimator = DecisionTreeClassifier(random_state=0)\n\n    train_sizes = [0.3, 0.6, 0.9]\n    display = LearningCurveDisplay.from_estimator(\n        estimator, X, y, train_sizes=train_sizes\n    )\n\n    import matplotlib as mpl\n\n    assert display.errorbar_ is None\n\n    assert isinstance(display.lines_, list)\n    for line in display.lines_:\n        assert isinstance(line, mpl.lines.Line2D)\n\n    assert isinstance(display.fill_between_, list)\n    for fill in display.fill_between_:\n        assert isinstance(fill, mpl.collections.PolyCollection)\n        assert fill.get_alpha() == 0.5\n\n    assert display.score_name == \"Score\"\n    assert display.ax_.get_xlabel() == \"Number of samples in the training set\"\n    assert display.ax_.get_ylabel() == \"Score\"\n\n    _, legend_labels = display.ax_.get_legend_handles_labels()\n    assert legend_labels == [\"Testing metric\"]\n\n    train_sizes_abs, train_scores, test_scores = learning_curve(\n        estimator, X, y, train_sizes=train_sizes\n    )\n\n    assert_array_equal(display.train_sizes, train_sizes_abs)\n    assert_allclose(display.train_scores, train_scores)\n    assert_allclose(display.test_scores, test_scores)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 199,
        "n_words": 98,
        "vocab_size": 68,
        "complexity": 3,
        "nloc": 27,
        "token_counts": 211,
        "n_ast_nodes": 313,
        "n_identifiers": 39,
        "d_id": 76917,
        "documentation": {
            "docstring": "Check the default usage of the LearningCurveDisplay class.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 303231,
        "commit_id": "5ee2f4f438f8acb119308738639169138b15662c",
        "repo": "core",
        "path": "tests/components/sensibo/test_climate.py",
        "file_name": "test_climate.py",
        "fun_name": "test_climate_find_valid_targets",
        "commit_message": "Sensibo Set temperature improvement (#72992)",
        "code": "async def test_climate_find_valid_targets():\n    \n\n    valid_targets = [10, 16, 17, 18, 19, 20]\n\n    assert _find_valid_target_temp(7, valid_targets) == 10\n    assert _find_valid_target_temp(10, valid_targets) == 10\n    assert _find_valid_target_temp(11, valid_targets) == 16\n    assert _find_valid_target_temp(15, valid_targets) == 16\n    assert _find_valid_target_temp(16, valid_targets) == 16\n    assert _find_valid_target_temp(18.5, valid_targets) == 19\n    assert _find_valid_target_temp(20, valid_targets) == 20\n    assert _find_valid_target_temp(25, valid_targets) == 20\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 81,
        "n_words": 51,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 94,
        "n_ast_nodes": 135,
        "n_identifiers": 3,
        "d_id": 102059,
        "documentation": {
            "docstring": "Test function to return temperature from valid targets.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 249919,
        "commit_id": "854a6884d81c95297bf93badcddc00a4cab93418",
        "repo": "synapse",
        "path": "tests/replication/test_pusher_shard.py",
        "file_name": "test_pusher_shard.py",
        "fun_name": "test_send_push_single_worker",
        "commit_message": "Modernize unit tests configuration settings for workers. (#14568)\n\nUse the newer foo_instances configuration instead of the\r\ndeprecated flags to enable specific features (e.g. start_pushers).",
        "code": "def test_send_push_single_worker(self):\n        \n        http_client_mock = Mock(spec_set=[\"post_json_get_json\"])\n        http_client_mock.post_json_get_json.side_effect = (\n            lambda *_, **__: defer.succeed({})\n        )\n\n        self.make_worker_hs(\n            \"synapse.app.generic_worker\",\n            {\"worker_name\": \"pusher1\", \"pusher_instances\": [\"pusher1\"]},\n            proxied_blacklisted_http_client=http_client_mock,\n        )\n\n        event_id = self._create_pusher_and_send_msg(\"user\")\n\n        # Advance time a bit, so the pusher will register something has happened\n        self.pump()\n\n        http_client_mock.post_json_get_json.assert_called_once()\n        self.assertEqual(\n            http_client_mock.post_json_get_json.call_args[0][0],\n            \"https://push.example.com/_matrix/push/v1/notify\",\n        )\n        self.assertEqual(\n            event_id,\n            http_client_mock.post_json_get_json.call_args[0][1][\"notification\"][\n                \"event_id\"\n            ],\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 261,
        "n_words": 49,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 125,
        "n_ast_nodes": 213,
        "n_identifiers": 19,
        "d_id": 73196,
        "documentation": {
            "docstring": "Test that registration works when using a pusher worker.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 247794,
        "commit_id": "9d21ecf7ceab55bc19c4457b8b07401b0b1623a7",
        "repo": "synapse",
        "path": "tests/storage/test_id_generators.py",
        "file_name": "test_id_generators.py",
        "fun_name": "test_load_existing_stream",
        "commit_message": "Add type hints to tests files. (#12256)",
        "code": "def test_load_existing_stream(self) -> None:\n        \n        self._insert_rows(\"foobar1\", \"first\", 3)\n        self._insert_rows(\"foobar2\", \"second\", 3)\n        self._insert_rows(\"foobar2\", \"second\", 1, update_stream_table=False)\n\n        first_id_gen = self._create_id_generator(\"first\", writers=[\"first\", \"second\"])\n        second_id_gen = self._create_id_generator(\"second\", writers=[\"first\", \"second\"])\n\n        # The first ID gen will notice that it can advance its token to 7 as it\n        # has no in progress writes...\n        self.assertEqual(first_id_gen.get_positions(), {\"first\": 7, \"second\": 6})\n        self.assertEqual(first_id_gen.get_current_token_for_writer(\"first\"), 7)\n        self.assertEqual(first_id_gen.get_current_token_for_writer(\"second\"), 6)\n        self.assertEqual(first_id_gen.get_persisted_upto_position(), 7)\n\n        # ... but the second ID gen doesn't know that.\n        self.assertEqual(second_id_gen.get_positions(), {\"first\": 3, \"second\": 7})\n        self.assertEqual(second_id_gen.get_current_token_for_writer(\"first\"), 3)\n        self.assertEqual(second_id_gen.get_current_token_for_writer(\"second\"), 7)\n        self.assertEqual(first_id_gen.get_persisted_upto_position(), 7)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 198,
        "n_words": 79,
        "vocab_size": 61,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 190,
        "n_ast_nodes": 330,
        "n_identifiers": 12,
        "d_id": 71927,
        "documentation": {
            "docstring": "Test creating ID gens with multiple tables that have rows from after\n        the position in `stream_positions` table.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 71800,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_account_management.py",
        "file_name": "test_account_management.py",
        "fun_name": "test_notification_preferences_panel_reduced_for_non_moderators",
        "commit_message": "Reformat with black",
        "code": "def test_notification_preferences_panel_reduced_for_non_moderators(self):\n        \n        response = self.client.get(reverse(\"wagtailadmin_account\"))\n\n        # Find notifications panel through context\n        notifications_panel = None\n        for panelset in response.context[\"panels_by_tab\"].values():\n            for panel in panelset:\n                if panel.name == \"notifications\":\n                    notifications_panel = panel\n                    break\n\n        notifications_form = notifications_panel.get_form()\n        self.assertIn(\"approved_notifications\", notifications_form.fields.keys())\n        self.assertIn(\"rejected_notifications\", notifications_form.fields.keys())\n        self.assertNotIn(\"submitted_notifications\", notifications_form.fields.keys())\n        self.assertIn(\n            \"updated_comments_notifications\", notifications_form.fields.keys()\n        )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 195,
        "n_words": 43,
        "vocab_size": 33,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 115,
        "n_ast_nodes": 200,
        "n_identifiers": 18,
        "d_id": 15750,
        "documentation": {
            "docstring": "\n        This tests that a user without publish permissions is not shown the\n        notification preference for 'submitted' items\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 159507,
        "commit_id": "9fc462da870f69f9976be3bc081675844b9f64c2",
        "repo": "rasa",
        "path": "rasa/engine/graph.py",
        "file_name": "graph.py",
        "fun_name": "as_dict",
        "commit_message": "fix type annotation in rasa.engine",
        "code": "def as_dict(self) -> Dict[Text, Any]:\n        \n        serializable_graph_schema: Dict[Text, Dict[Text, Any]] = {\"nodes\": {}}\n        for node_name, node in self.nodes.items():\n            serializable = dataclasses.asdict(node)\n\n            # Classes are not JSON serializable (surprise)\n            serializable[\"uses\"] = f\"{node.uses.__module__}.{node.uses.__name__}\"\n\n            serializable_graph_schema[\"nodes\"][node_name] = serializable\n\n        return serializable_graph_schema\n",
        "url": "https://github.com/RasaHQ/rasa.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 107,
        "n_words": 35,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 72,
        "n_ast_nodes": 137,
        "n_identifiers": 16,
        "d_id": 38299,
        "documentation": {
            "docstring": "Returns graph schema in a serializable format.\n\n        Returns:\n            The graph schema in a format which can be dumped as JSON or other formats.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 81965,
        "commit_id": "68a44529b6b77d2d43d7099b654560bfd8bbf518",
        "repo": "awx",
        "path": "awxkit/awxkit/api/pages/page.py",
        "file_name": "page.py",
        "fun_name": "page_identity",
        "commit_message": "Register pages for the Instance peers and install bundle endpoints\n\nThis includes exposing a new interface for Page objects, Page.bytes,\nto return the full bytestring contents of the response.",
        "code": "def page_identity(self, response, request_json=None):\n        \n        request_path = response.request.path_url\n        if request_path == '/migrations_notran/':\n            raise exc.IsMigrating('You have been redirected to the migration-in-progress page.')\n        request_method = response.request.method.lower()\n\n        self.last_elapsed = response.elapsed\n\n        if isinstance(request_json, dict) and 'ds' in request_json:\n            ds = request_json.ds\n        else:\n            ds = None\n\n        data = self.extract_data(response)\n        exc_str = \"%s (%s) received\" % (http.responses[response.status_code], response.status_code)\n\n        exception = exception_from_status_code(response.status_code)\n        if exception:\n            raise exception(exc_str, data)\n\n        if response.status_code in (http.OK, http.CREATED, http.ACCEPTED):\n\n            # Not all JSON responses include a URL.  Grab it from the request\n            # object, if needed.\n            if 'url' in data:\n                endpoint = data['url']\n            else:\n                endpoint = request_path\n\n            data = objectify_response_json(response)\n\n            if request_method in ('get', 'patch', 'put'):\n                #  Update existing resource and return it\n                if are_same_endpoint(self.endpoint, request_path):\n                    self.json = data\n                    self.r = response\n                    return self\n\n            registered_type = get_registered_page(request_path, request_method)\n            return registered_type(self.connection, endpoint=endpoint, json=data, last_elapsed=response.elapsed, r=response, ds=ds)\n\n        elif response.status_code == http.FORBIDDEN:\n            if is_license_invalid(response):\n                raise exc.LicenseInvalid(exc_str, data)\n            elif is_license_exceeded(response):\n                raise exc.LicenseExceeded(exc_str, data)\n            else:\n                raise exc.Forbidden(exc_str, data)\n\n        elif response.status_code == http.BAD_REQUEST:\n            if is_license_invalid(response):\n                raise exc.LicenseInvalid(exc_str, data)\n            if is_duplicate_error(response):\n                raise exc.Duplicate(exc_str, data)\n            else:\n                raise exc.BadRequest(exc_str, data)\n        else:\n            raise exc.Unknown(exc_str, data)\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 694,
        "n_words": 171,
        "vocab_size": 104,
        "complexity": 15,
        "nloc": 44,
        "token_counts": 337,
        "n_ast_nodes": 536,
        "n_identifiers": 47,
        "d_id": 17285,
        "documentation": {
            "docstring": "Takes a `requests.Response` and\n        returns a new __item_class__ instance if the request method is not a get, or returns\n           a __class__ instance if the request path is different than the caller's `endpoint`.\n        ",
            "n_words": 32,
            "vocab_size": 22,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 286399,
        "commit_id": "09f753da1c2a2f03c41fe6a3ca2eb79f6ea58995",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/overview/overview_controller.py",
        "file_name": "overview_controller.py",
        "fun_name": "call_categories",
        "commit_message": "More Fixes to Crypto + key sort (#3244)\n\n* fix #3095 - autocomplete and command working + key sort\r\n\r\n* fix #3056\r\n\r\n* fix [Bug]  bugs #3048\r\n\r\n* fix [Bug]  bug #3017\r\n\r\n* sort -> sortby, not ascend, tests\r\n\r\n* fix my goof ups\r\n\r\nCo-authored-by: james <jmaslek11@gmail.com>",
        "code": "def call_categories(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            prog=\"categories\",\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            description=,\n        )\n\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            dest=\"limit\",\n            type=check_positive,\n            help=\"display N number of records\",\n            default=15,\n        )\n\n        parser.add_argument(\n            \"-s\",\n            \"--sortby\",\n            dest=\"sortby\",\n            type=str,\n            help=\"Sort by given column. Default: market_cap_desc\",\n            default=pycoingecko_model.SORT_VALUES[0],\n            choices=pycoingecko_model.SORT_VALUES,\n        )\n\n        parser.add_argument(\n            \"--pie\",\n            action=\"store_true\",\n            help=\"Flag to show pie chart\",\n            dest=\"pie\",\n            default=False,\n        )\n\n        ns_parser = self.parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n        if ns_parser:\n            pycoingecko_view.display_categories(\n                limit=ns_parser.limit,\n                export=ns_parser.export,\n                sortby=ns_parser.sortby,\n                pie=ns_parser.pie,\n            )\n\n    # TODO: solve sort (similar to losers from discovery)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 494,
        "n_words": 72,
        "vocab_size": 63,
        "complexity": 2,
        "nloc": 43,
        "token_counts": 161,
        "n_ast_nodes": 254,
        "n_identifiers": 31,
        "d_id": 85786,
        "documentation": {
            "docstring": "Process top_categories commandShows top cryptocurrency categories by market capitalization. It includes categories like:\n            stablecoins, defi, solana ecosystem, polkadot ecosystem and many others.\n            You can sort by {}, using --sortby parameter",
            "n_words": 30,
            "vocab_size": 28,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 273362,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/layers/preprocessing/preprocessing_utils.py",
        "file_name": "preprocessing_utils.py",
        "fun_name": "listify_tensors",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def listify_tensors(x):\n    \n    if tf.is_tensor(x):\n        x = x.numpy()\n    if isinstance(x, np.ndarray):\n        x = x.tolist()\n    return x\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 41,
        "n_words": 15,
        "vocab_size": 11,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 40,
        "n_ast_nodes": 68,
        "n_identifiers": 9,
        "d_id": 81118,
        "documentation": {
            "docstring": "Convert any tensors or numpy arrays to lists for config serialization.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 249472,
        "commit_id": "d3d9ca156e323fe194b1bcb1af1628f65a2f3c1c",
        "repo": "synapse",
        "path": "tests/rest/client/test_keys.py",
        "file_name": "test_keys.py",
        "fun_name": "test_key_query_cancellation",
        "commit_message": "Cancel the processing of key query requests when they time out. (#13680)",
        "code": "def test_key_query_cancellation(self) -> None:\n        \n        self.register_user(\"alice\", \"wonderland\")\n        alice_token = self.login(\"alice\", \"wonderland\")\n\n        bob = self.register_user(\"bob\", \"uncle\")\n\n        channel = make_request_with_cancellation_test(\n            \"test_key_query_cancellation\",\n            self.reactor,\n            self.site,\n            \"POST\",\n            \"/_matrix/client/r0/keys/query\",\n            {\n                \"device_keys\": {\n                    # Empty list means we request keys for all bob's devices\n                    bob: [],\n                },\n            },\n            token=alice_token,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.result[\"body\"])\n        self.assertIn(bob, channel.json_body[\"device_keys\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 259,
        "n_words": 47,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 104,
        "n_ast_nodes": 177,
        "n_identifiers": 17,
        "d_id": 72939,
        "documentation": {
            "docstring": "\n        Tests that /keys/query is cancellable and does not swallow the\n        CancelledError.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 195664,
        "commit_id": "5fc97f8ef40cbc9363c7f7e0ff25f12c45a2203e",
        "repo": "sympy",
        "path": "sympy/simplify/trigsimp.py",
        "file_name": "trigsimp.py",
        "fun_name": "trigsimp",
        "commit_message": "implemented inverse option for trigsimp",
        "code": "def trigsimp(expr, inverse=False, **opts):\n    \n    from sympy.simplify.fu import fu\n\n    expr = sympify(expr)\n\n    _eval_trigsimp = getattr(expr, '_eval_trigsimp', None)\n    if _eval_trigsimp is not None:\n        return _eval_trigsimp(**opts)\n\n    old = opts.pop('old', False)\n    if not old:\n        opts.pop('deep', None)\n        opts.pop('recursive', None)\n        method = opts.pop('method', 'matching')\n    else:\n        method = 'old'\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 101,
        "n_words": 42,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 26,
        "token_counts": 202,
        "n_ast_nodes": 160,
        "n_identifiers": 13,
        "d_id": 47355,
        "documentation": {
            "docstring": "Returns a reduced expression by using known trig identities.\n\n    Parameters\n    ==========\n\n    inverse : bool, optional\n        If ``inverse=True``, it will be assumed that a composition of inverse\n        functions, such as sin and asin, can be cancelled in any order.\n        For example, ``asin(sin(x))`` will yield ``x`` without checking whether\n        x belongs to the set where this relation is true. The default is False.\n        Default : True\n\n    method : string, optional\n        Specifies the method to use. Valid choices are:\n\n        - ``'matching'``, default\n        - ``'groebner'``\n        - ``'combined'``\n        - ``'fu'``\n        - ``'old'``\n\n        If ``'matching'``, simplify the expression recursively by targeting\n        common patterns. If ``'groebner'``, apply an experimental groebner\n        basis algorithm. In this case further options are forwarded to\n        ``trigsimp_groebner``, please refer to\n        its docstring. If ``'combined'``, it first runs the groebner basis\n        algorithm with small default parameters, then runs the ``'matching'``\n        algorithm. If ``'fu'``, run the collection of trigonometric\n        transformations described by Fu, et al. (see the\n        :py:func:`~sympy.simplify.fu.fu` docstring). If ``'old'``, the original\n        SymPy trig simplification function is run.\n    opts :\n        Optional keyword arguments passed to the method. See each method's\n        function docstring for details.\n\n    Examples\n    ========\n\n    >>> from sympy import trigsimp, sin, cos, log\n    >>> from sympy.abc import x\n    >>> e = 2*sin(x)**2 + 2*cos(x)**2\n    >>> trigsimp(e)\n    2\n\n    Simplification occurs wherever trigonometric functions are located.\n\n    >>> trigsimp(log(e))\n    log(2)\n\n    Using ``method='groebner'`` (or ``method='combined'``) might lead to\n    greater simplification.\n\n    The old trigsimp routine can be accessed as with method ``method='old'``.\n\n    >>> from sympy import coth, tanh\n    >>> t = 3*tanh(x)**7 - 2/coth(x)**7\n    >>> trigsimp(t, method='old') == t\n    True\n    >>> trigsimp(t)\n    tanh(x)**7\n\n    ",
            "n_words": 255,
            "vocab_size": 181,
            "n_whitespaces": 491,
            "language": "en"
        }
    },
    {
        "id": 47330,
        "commit_id": "d8889da29ccfcbecd2c89b9e8e278c480767d678",
        "repo": "airflow",
        "path": "airflow/utils/sqlalchemy.py",
        "file_name": "sqlalchemy.py",
        "fun_name": "db_supports_json",
        "commit_message": "Move the database configuration to a new section (#22284)\n\nCo-authored-by: gitstart-airflow <gitstart@users.noreply.github.com>\r\nCo-authored-by: GitStart <1501599+gitstart@users.noreply.github.com>\r\nCo-authored-by: Egbosi Kelechi <egbosikelechi@gmail.com>",
        "code": "def db_supports_json(self):\n        \n        return not conf.get(\"database\", \"sql_alchemy_conn\").startswith(\"mssql\")\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 42,
        "n_identifiers": 5,
        "d_id": 9072,
        "documentation": {
            "docstring": "Checks if the database supports JSON (i.e. is NOT MSSQL)",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 60232,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/coord_map.py",
        "file_name": "coord_map.py",
        "fun_name": "coord_map_from_to",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def coord_map_from_to(top_from, top_to):\n    \n    # We need to find a common ancestor of top_from and top_to.\n    # We'll assume that all ancestors are equivalent here (otherwise the graph\n    # is an inconsistent state (which we could improve this to check for)).\n    # For now use a brute-force algorithm.\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 62,
        "n_words": 47,
        "vocab_size": 42,
        "complexity": 8,
        "nloc": 28,
        "token_counts": 177,
        "n_ast_nodes": 19,
        "n_identifiers": 3,
        "d_id": 12025,
        "documentation": {
            "docstring": "\n    Determine the coordinate mapping betweeen a top (from) and a top (to).\n    Walk the graph to find a common ancestor while composing the coord maps for\n    from and to until they meet. As a last step the from map is inverted.\n    ",
            "n_words": 41,
            "vocab_size": 31,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 151197,
        "commit_id": "86aa875bc9d5edeba04f908fe45b011e52045c83",
        "repo": "freqtrade",
        "path": "freqtrade/freqai/utils.py",
        "file_name": "utils.py",
        "fun_name": "plot_feature_importance",
        "commit_message": "plot features as html instead of png",
        "code": "def plot_feature_importance(model, feature_names, pair, train_dir, count_max=50) -> None:\n    \n    try:\n        import plotly.graph_objects as go\n        from plotly.subplots import make_subplots\n    except ImportError:\n        logger.exception(\"Module plotly not found \\n Please install using `pip3 install plotly`\")\n        exit(1)\n\n    from freqtrade.plot.plotting import store_plot_file\n\n    # Gather feature importance from model\n    if \"catboost.core\" in str(model.__class__):\n        feature_importance = model.get_feature_importance()\n    elif \"lightgbm.sklearn\" in str(model.__class__):\n        feature_importance = model.feature_importances_\n    else:\n        raise NotImplementedError(f\"Cannot extract feature importance for {model.__class__}\")\n\n    # Data preparation\n    fi_df = pd.DataFrame({\n        \"feature_names\": np.array(feature_names),\n        \"feature_importance\": np.array(feature_importance)\n    })\n    fi_df_top = fi_df.nlargest(count_max, \"feature_importance\")[::-1]\n    fi_df_worst = fi_df.nsmallest(count_max, \"feature_importance\")[::-1]\n\n    # Plotting",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 189,
        "n_words": 84,
        "vocab_size": 67,
        "complexity": 4,
        "nloc": 37,
        "token_counts": 229,
        "n_ast_nodes": 261,
        "n_identifiers": 34,
        "d_id": 34972,
        "documentation": {
            "docstring": "\n        Plot Best and Worst Features by importance for CatBoost model.\n        Called once per sub-train.\n        Usage: plot_feature_importance(\n            model=model,\n            feature_names=dk.training_features_list,\n            pair=pair,\n            train_dir=dk.data_path)\n    ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 89,
            "language": "en"
        }
    },
    {
        "id": 138395,
        "commit_id": "30ab5458a7e4ba2351d5e1beef8c8797b5946493",
        "repo": "ray",
        "path": "dashboard/state_aggregator.py",
        "file_name": "state_aggregator.py",
        "fun_name": "get_objects",
        "commit_message": "[State Observability] Tasks and Objects API (#23912)\n\nThis PR implements ray list tasks and ray list objects APIs.\r\n\r\nNOTE: You can ignore the merge conflict for now. It is because the first PR was reverted. There's a fix PR open now.",
        "code": "async def get_objects(self) -> dict:\n        \n        replies = await asyncio.gather(\n            *[\n                self._client.get_object_info(node_id, timeout=DEFAULT_RPC_TIMEOUT)\n                for node_id in self._client.get_all_registered_raylet_ids()\n            ]\n        )\n\n        worker_stats = []\n        for reply in replies:\n            for core_worker_stat in reply.core_workers_stats:\n                # NOTE: Set preserving_proto_field_name=False here because\n                # `construct_memory_table` requires a dictionary that has\n                # modified protobuf name\n                # (e.g., workerId instead of worker_id) as a key.\n                worker_stats.append(\n                    self._message_to_dict(\n                        message=core_worker_stat,\n                        fields_to_decode=[\"object_id\"],\n                        preserving_proto_field_name=False,\n                    )\n                )\n        result = {}\n        memory_table = memory_utils.construct_memory_table(worker_stats)\n        for entry in memory_table.table:\n            data = entry.as_dict()\n            # `construct_memory_table` returns object_ref field which is indeed\n            # object_id. We do transformation here.\n            # TODO(sang): Refactor `construct_memory_table`.\n            data[\"object_id\"] = data[\"object_ref\"]\n            del data[\"object_ref\"]\n            data = filter_fields(data, ObjectState)\n            result[data[\"object_id\"]] = data\n        return result\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 518,
        "n_words": 107,
        "vocab_size": 80,
        "complexity": 5,
        "nloc": 32,
        "token_counts": 140,
        "n_ast_nodes": 234,
        "n_identifiers": 31,
        "d_id": 31404,
        "documentation": {
            "docstring": "List all object information from the cluster.\n\n        Returns:\n            {object_id -> object_data_in_dict}\n            object_data_in_dict's schema is in ObjectState\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 63729,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/six.py",
        "file_name": "six.py",
        "fun_name": "exec_",
        "commit_message": "upd; format",
        "code": "def exec_(_code_, _globs_=None, _locs_=None):\n        \n        if _globs_ is None:\n            frame = sys._getframe(1)\n            _globs_ = frame.f_globals\n            if _locs_ is None:\n                _locs_ = frame.f_locals\n            del frame\n        elif _locs_ is None:\n            _locs_ = _globs_\n        exec()\n\n    exec_()\n\n\nif sys.version_info[:2] > (3,):\n    exec_()\nelse:",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 140,
        "n_words": 38,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 56,
        "n_ast_nodes": 136,
        "n_identifiers": 11,
        "d_id": 13487,
        "documentation": {
            "docstring": "Execute code in a namespace.exec _code_ in _globs_, _locs_def reraise(tp, value, tb=None):\n    try:\n        raise tp, value, tb\n    finally:\n        tb = None\ndef raise_from(value, from_value):\n    try:\n        raise value from from_value\n    finally:\n        value = None\n",
            "n_words": 33,
            "vocab_size": 24,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 264128,
        "commit_id": "fa1e28e860c4bdb3e585a968bd248a2ac666e1f6",
        "repo": "netbox",
        "path": "netbox/extras/tests/test_customfields.py",
        "file_name": "test_customfields.py",
        "fun_name": "test_create_single_object_with_values",
        "commit_message": "Initial work on #7006",
        "code": "def test_create_single_object_with_values(self):\n        \n        data = {\n            'name': 'Site 3',\n            'slug': 'site-3',\n            'custom_fields': {\n                'text_field': 'bar',\n                'longtext_field': 'blah blah blah',\n                'number_field': 456,\n                'boolean_field': True,\n                'date_field': '2020-01-02',\n                'url_field': 'http://example.com/2',\n                'json_field': '{\"foo\": 1, \"bar\": 2}',\n                'choice_field': 'Bar',\n                'object_field': VLAN.objects.get(vid=2).pk,\n            },\n        }\n        url = reverse('dcim-api:site-list')\n        self.add_permissions('dcim.add_site')\n\n        response = self.client.post(url, data, format='json', **self.header)\n        self.assertHttpStatus(response, status.HTTP_201_CREATED)\n\n        # Validate response data\n        response_cf = response.data['custom_fields']\n        data_cf = data['custom_fields']\n        self.assertEqual(response_cf['text_field'], data_cf['text_field'])\n        self.assertEqual(response_cf['longtext_field'], data_cf['longtext_field'])\n        self.assertEqual(response_cf['number_field'], data_cf['number_field'])\n        self.assertEqual(response_cf['boolean_field'], data_cf['boolean_field'])\n        self.assertEqual(response_cf['date_field'], data_cf['date_field'])\n        self.assertEqual(response_cf['url_field'], data_cf['url_field'])\n        self.assertEqual(response_cf['json_field'], data_cf['json_field'])\n        self.assertEqual(response_cf['choice_field'], data_cf['choice_field'])\n        self.assertEqual(response_cf['object_field']['id'], data_cf['object_field'])\n\n        # Validate database data\n        site = Site.objects.get(pk=response.data['id'])\n        self.assertEqual(site.custom_field_data['text_field'], data_cf['text_field'])\n        self.assertEqual(site.custom_field_data['longtext_field'], data_cf['longtext_field'])\n        self.assertEqual(site.custom_field_data['number_field'], data_cf['number_field'])\n        self.assertEqual(site.custom_field_data['boolean_field'], data_cf['boolean_field'])\n        self.assertEqual(str(site.custom_field_data['date_field']), data_cf['date_field'])\n        self.assertEqual(site.custom_field_data['url_field'], data_cf['url_field'])\n        self.assertEqual(site.custom_field_data['json_field'], data_cf['json_field'])\n        self.assertEqual(site.custom_field_data['choice_field'], data_cf['choice_field'])\n        self.assertEqual(site.custom_field_data['object_field'], data_cf['object_field'])\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 491,
        "n_words": 102,
        "vocab_size": 82,
        "complexity": 1,
        "nloc": 41,
        "token_counts": 420,
        "n_ast_nodes": 735,
        "n_identifiers": 26,
        "d_id": 77615,
        "documentation": {
            "docstring": "\n        Create a single new site with a value for each type of custom field.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 155537,
        "commit_id": "336aac39ee8a616ac2645e532392123ae1bfddd1",
        "repo": "dask",
        "path": "dask/dataframe/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "shift",
        "commit_message": "Add groupby shift method (#8522)\n\nImplements the shift `method` following the `transform` and `apply` methods.",
        "code": "def shift(self, periods=1, freq=None, axis=0, fill_value=None, meta=no_default):\n        \n        if meta is no_default:\n            with raise_on_meta_error(\"groupby.shift()\", udf=False):\n                meta_kwargs = _extract_meta(\n                    {\n                        \"periods\": periods,\n                        \"freq\": freq,\n                        \"axis\": axis,\n                        \"fill_value\": fill_value,\n                    },\n                    nonempty=True,\n                )\n                meta = self._meta_nonempty.shift(**meta_kwargs)\n\n            msg = (\n                \"`meta` is not specified, inferred from partial data. \"\n                \"Please provide `meta` if the result is unexpected.\\n\"\n                \"  Before: .shift(1)\\n\"\n                \"  After:  .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\\n\"\n                \"  or:     .shift(1, meta=('x', 'f8'))            for series result\"\n            )\n            warnings.warn(msg, stacklevel=2)\n\n        meta = make_meta(meta, parent_meta=self._meta.obj)\n\n        # Validate self.by\n        if isinstance(self.by, list) and any(\n            isinstance(item, Series) for item in self.by\n        ):\n            raise NotImplementedError(\n                \"groupby-shift with a multiple Series is currently not supported\"\n            )\n        df = self.obj\n        should_shuffle = not (df.known_divisions and df._contains_index_name(self.by))\n\n        if should_shuffle:\n            df2, by = self._shuffle(meta)\n        else:\n            df2 = df\n            by = self.by\n\n        # Perform embarrassingly parallel groupby-shift\n        result = map_partitions(\n            _groupby_slice_shift,\n            df2,\n            by,\n            self._slice,\n            periods=periods,\n            freq=freq,\n            axis=axis,\n            fill_value=fill_value,\n            token=\"groupby-shift\",\n            group_keys=self.group_keys,\n            meta=meta,\n            **self.observed,\n            **self.dropna,\n        )\n        return result\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 807,
        "n_words": 153,
        "vocab_size": 115,
        "complexity": 7,
        "nloc": 51,
        "token_counts": 246,
        "n_ast_nodes": 391,
        "n_identifiers": 43,
        "d_id": 36420,
        "documentation": {
            "docstring": "Parallel version of pandas GroupBy.shift\n\n        This mimics the pandas version except for the following:\n\n        If the grouper does not align with the index then this causes a full\n        shuffle.  The order of rows within each group may not be preserved.\n\n        Parameters\n        ----------\n        periods : Delayed, Scalar or int, default 1\n            Number of periods to shift.\n        freq : Delayed, Scalar or str, optional\n            Frequency string.\n        axis : axis to shift, default 0\n            Shift direction.\n        fill_value : Scalar, Delayed or object, optional\n            The scalar value to use for newly introduced missing values.\n        $META\n\n        Returns\n        -------\n        shifted : Series or DataFrame shifted within each group.\n\n        Examples\n        --------\n        >>> import dask\n        >>> ddf = dask.datasets.timeseries(freq=\"1H\")\n        >>> result = ddf.groupby(\"name\").shift(1, meta={\"id\": int, \"x\": float, \"y\": float})\n        ",
            "n_words": 121,
            "vocab_size": 89,
            "n_whitespaces": 299,
            "language": "en"
        }
    },
    {
        "id": 70108,
        "commit_id": "917f01a8306055b21437deac35333dddd1210e39",
        "repo": "glances",
        "path": "glances/processes.py",
        "file_name": "processes.py",
        "fun_name": "nice_decrease",
        "commit_message": "Update formater in the Makefile with flake8 and autopep8/autoflake",
        "code": "def nice_decrease(self, pid):\n        \n        p = psutil.Process(pid)\n        try:\n            p.nice(p.nice() - 1)\n            logger.info('Set nice level of process {} to {} (higher the priority)'.format(pid, p.nice()))\n        except psutil.AccessDenied:\n            logger.warning(\n                'Can not decrease (higher the priority) the nice level of process {} (access denied)'.format(pid)\n            )\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 127,
        "n_words": 40,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 63,
        "n_ast_nodes": 109,
        "n_identifiers": 12,
        "d_id": 15339,
        "documentation": {
            "docstring": "Decrease nice level\n        On UNIX this is a number which usually goes from -20 to 20.\n        The higher the nice value, the lower the priority of the process.",
            "n_words": 28,
            "vocab_size": 24,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 100267,
        "commit_id": "444762114c1b1ad2e72c871e825373bd74880aba",
        "repo": "faceswap",
        "path": "lib/gpu_stats.py",
        "file_name": "gpu_stats.py",
        "fun_name": "_get_device_count",
        "commit_message": "Initial somewhat working version",
        "code": "def _get_device_count(self):\n        \n        if self._is_plaidml:\n            self._device_count = self._plaid.device_count\n        elif IS_MACOS:\n            self._device_count = metal.get_device_count()\n        else:\n            try:\n                self._device_count = pynvml.nvmlDeviceGetCount()\n            except pynvml.NVMLError:\n                self._device_count = 0\n        self._log(\"debug\", \"GPU Device count: {}\".format(self._device_count))\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 136,
        "n_words": 27,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 70,
        "n_ast_nodes": 121,
        "n_identifiers": 14,
        "d_id": 19777,
        "documentation": {
            "docstring": " Detect the number of GPUs attached to the system and allocate to\n        :attr:`_device_count`. ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 150869,
        "commit_id": "2b5f0678772bea0abaf4abe93efc55de43ea3e0e",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/rpc.py",
        "file_name": "rpc.py",
        "fun_name": "_handle_analyzed_df_message",
        "commit_message": "Refactoring, minor improvements, data provider improvements",
        "code": "def _handle_analyzed_df_message(self, type, data):\n        \n        key, value = data[\"key\"], data[\"value\"]\n        pair, timeframe, candle_type = key\n\n        # Skip any pairs that we don't have in the pairlist?\n        # leader_pairlist = self._freqtrade.pairlists._whitelist\n        # if pair not in leader_pairlist:\n        #     return\n\n        dataframe = json_to_dataframe(value)\n\n        if self._config.get('external_signal', {}).get('remove_signals_analyzed_df', False):\n            dataframe = remove_entry_exit_signals(dataframe)\n\n        logger.debug(f\"Handling analyzed dataframe for {pair}\")\n        logger.debug(dataframe.tail())\n\n        # Add the dataframe to the dataprovider\n        dataprovider = self._freqtrade.dataprovider\n        dataprovider.add_external_df(pair, timeframe, dataframe, candle_type)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 180,
        "n_words": 67,
        "vocab_size": 49,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 98,
        "n_ast_nodes": 169,
        "n_identifiers": 20,
        "d_id": 34859,
        "documentation": {
            "docstring": "\n        Handles the analyzed dataframes from the Leaders\n\n        :param type: The data_type of the data\n        :param data: The data\n        ",
            "n_words": 18,
            "vocab_size": 13,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 242037,
        "commit_id": "3a3727c022a361a0bc8a519ebc60e7de8124a5d9",
        "repo": "scipy",
        "path": "scipy/stats/_levy_stable/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "pdf",
        "commit_message": "DOC: stats: add levy_stable pdf/cdf/rvs docstring",
        "code": "def pdf(self, x, *args, **kwds):\n        \n        # override base class version to correct\n        # location for S1 parameterization\n        if self._parameterization() == \"S0\":\n            return super().pdf(x, *args, **kwds)\n        elif self._parameterization() == \"S1\":\n            (alpha, beta), delta, gamma = self._parse_args(*args, **kwds)\n            if np.all(np.reshape(alpha, (1, -1))[0, :] != 1):\n                return super().pdf(x, *args, **kwds)\n            else:\n                # correct location for this parameterisation\n                x = np.reshape(x, (1, -1))[0, :]\n                x, alpha, beta = np.broadcast_arrays(x, alpha, beta)\n\n                data_in = np.dstack((x, alpha, beta))[0]\n                data_out = np.empty(shape=(len(data_in), 1))\n                # group data in unique arrays of alpha, beta pairs\n                uniq_param_pairs = np.unique(data_in[:, 1:], axis=0)\n                for pair in uniq_param_pairs:\n                    _alpha, _beta = pair\n                    _delta = (\n                        delta + 2 * _beta * gamma * np.log(gamma) / np.pi\n                        if _alpha == 1.0\n                        else delta\n                    )\n                    data_mask = np.all(data_in[:, 1:] == pair, axis=-1)\n                    _x = data_in[data_mask, 0]\n                    data_out[data_mask] = (\n                        super()\n                        .pdf(_x, _alpha, _beta, loc=_delta, scale=gamma)\n                        .reshape(len(_x), 1)\n                    )\n                output = data_out.T[0]\n                if output.shape == (1,):\n                    return output[0]\n                return output\n",
        "url": "https://github.com/scipy/scipy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 703,
        "n_words": 154,
        "vocab_size": 101,
        "complexity": 7,
        "nloc": 31,
        "token_counts": 330,
        "n_ast_nodes": 498,
        "n_identifiers": 37,
        "d_id": 69756,
        "documentation": {
            "docstring": "Probability density function of the Levy-stable distribution\n\n        Parameters\n        ----------\n        x : array_like\n            quantiles\n        alpha, beta : array_like\n            The shape parameters of the distribution. See the `levy_stable`\n            object docstring for more information.\n        loc : array_like, optional\n            location parameter (default=0)\n        scale : array_like, optional\n            scale parameter (default=1)\n\n        Returns\n        -------\n        pdf : ndarray\n            Probability density function evaluated at x\n        ",
            "n_words": 56,
            "vocab_size": 40,
            "n_whitespaces": 192,
            "language": "en"
        }
    },
    {
        "id": 156466,
        "commit_id": "b946406a30cd12cd6989df3440011a734441a200",
        "repo": "dask",
        "path": "dask/dataframe/io/orc/core.py",
        "file_name": "core.py",
        "fun_name": "project_columns",
        "commit_message": "Add from_map function to Dask-DataFrame (#8911)",
        "code": "def project_columns(self, columns):\n        \n        if columns == self.columns:\n            return self\n        func = copy.deepcopy(self)\n        func._columns = columns\n        return func\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 63,
        "n_words": 17,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 32,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 36647,
        "documentation": {
            "docstring": "Return a new ORCFunctionWrapper object with\n        a sub-column projection.\n        ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 113257,
        "commit_id": "97d067e614243f06ed1f8e2d389512977fff8828",
        "repo": "nni",
        "path": "nni/compression/pytorch/speedup/compress_modules.py",
        "file_name": "compress_modules.py",
        "fun_name": "replace_embedding",
        "commit_message": "Speedup enhancement (#4925)",
        "code": "def replace_embedding(embedding, masks):\n    \n    # currently we donnot support replace the embedding layer\n    # because we donnot have the corressponding pruner\n    return embedding\n\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 34,
        "n_words": 22,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 20,
        "n_identifiers": 3,
        "d_id": 24867,
        "documentation": {
            "docstring": "\n    Replace the embedding layer according the infered masks.\n    We replace the embedding layer according the weight masks,\n    ",
            "n_words": 17,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 76705,
        "commit_id": "470d39e1fe86084f729997f7c4e13f551e7e8c73",
        "repo": "wagtail",
        "path": "wagtail/admin/panels.py",
        "file_name": "panels.py",
        "fun_name": "get_edit_handler",
        "commit_message": "Split out bind_to(model) into a separate bind_to_model method",
        "code": "def get_edit_handler(cls):\n    \n    if hasattr(cls, \"edit_handler\"):\n        edit_handler = cls.edit_handler\n    else:\n        # construct a TabbedInterface made up of content_panels, promote_panels\n        # and settings_panels, skipping any which are empty\n        tabs = []\n\n        if cls.content_panels:\n            tabs.append(ObjectList(cls.content_panels, heading=gettext_lazy(\"Content\")))\n        if cls.promote_panels:\n            tabs.append(ObjectList(cls.promote_panels, heading=gettext_lazy(\"Promote\")))\n        if cls.settings_panels:\n            tabs.append(\n                ObjectList(\n                    cls.settings_panels,\n                    heading=gettext_lazy(\"Settings\"),\n                    classname=\"settings\",\n                )\n            )\n\n        edit_handler = TabbedInterface(tabs, base_form_class=cls.base_form_class)\n\n    return edit_handler.bind_to_model(cls)\n\n\nPage.get_edit_handler = get_edit_handler\n\n\n@receiver(setting_changed)",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@receiver(setting_changed)",
        "n_ast_errors": 1,
        "ast_levels": 18,
        "n_whitespaces": 253,
        "n_words": 56,
        "vocab_size": 47,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 118,
        "n_ast_nodes": 216,
        "n_identifiers": 19,
        "d_id": 16572,
        "documentation": {
            "docstring": "\n    Get the panel to use in the Wagtail admin when editing this page type.\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 177116,
        "commit_id": "4a019f04d0e304ecd2f28b15d854e1282e03461d",
        "repo": "networkx",
        "path": "networkx/algorithms/traversal/breadth_first_search.py",
        "file_name": "breadth_first_search.py",
        "fun_name": "descendants_at_distance",
        "commit_message": "Adds ```nx.bfs_layers``` method (#5879)\n\n* reformatted the files\r\n\r\n* reformatted the files\r\n\r\n* added final changes\r\n\r\n* changed descendants_at_distance\r\n\r\n* fixed comment in bfs_layers\r\n\r\n* fixed comment in bfs_layers",
        "code": "def descendants_at_distance(G, source, distance):\n    \n    if source not in G:\n        raise nx.NetworkXError(f\"The node {source} is not in the graph.\")\n\n    bfs_generator = nx.bfs_layers(G, source)\n    for i, layer in enumerate(bfs_generator):\n        if i == distance:\n            return set(layer)\n    return set()\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 75,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 58,
        "n_ast_nodes": 96,
        "n_identifiers": 12,
        "d_id": 42274,
        "documentation": {
            "docstring": "Returns all nodes at a fixed `distance` from `source` in `G`.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n        A graph\n    source : node in `G`\n    distance : the distance of the wanted nodes from `source`\n\n    Returns\n    -------\n    set()\n        The descendants of `source` in `G` at the given `distance` from `source`\n\n    Examples\n    --------\n    >>> G = nx.path_graph(5)\n    >>> nx.descendants_at_distance(G, 2, 2)\n    {0, 4}\n    >>> H = nx.DiGraph()\n    >>> H.add_edges_from([(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)])\n    >>> nx.descendants_at_distance(H, 0, 2)\n    {3, 4, 5, 6}\n    >>> nx.descendants_at_distance(H, 5, 0)\n    {5}\n    >>> nx.descendants_at_distance(H, 5, 1)\n    set()\n    ",
            "n_words": 96,
            "vocab_size": 61,
            "n_whitespaces": 176,
            "language": "en"
        }
    },
    {
        "id": 249080,
        "commit_id": "c97042f7eef3748e17c90e48a4122389a89c4735",
        "repo": "synapse",
        "path": "tests/rest/admin/test_device.py",
        "file_name": "test_device.py",
        "fun_name": "test_unknown_device",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13469)",
        "code": "def test_unknown_device(self) -> None:\n        \n        url = \"/_synapse/admin/v2/users/%s/devices/unknown_device\" % urllib.parse.quote(\n            self.other_user\n        )\n\n        channel = self.make_request(\n            \"GET\",\n            url,\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(HTTPStatus.NOT_FOUND, channel.code, msg=channel.json_body)\n        self.assertEqual(Codes.NOT_FOUND, channel.json_body[\"errcode\"])\n\n        channel = self.make_request(\n            \"PUT\",\n            url,\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n\n        channel = self.make_request(\n            \"DELETE\",\n            url,\n            access_token=self.admin_user_tok,\n        )\n\n        # Delete unknown device returns status 200\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 258,
        "n_words": 50,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 26,
        "token_counts": 138,
        "n_ast_nodes": 215,
        "n_identifiers": 18,
        "d_id": 72587,
        "documentation": {
            "docstring": "\n        Tests that a lookup for a device that does not exist returns either HTTPStatus.NOT_FOUND or 200.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 30157,
        "commit_id": "fa2ad657482aca9dc628e6d7062b8badf2706bb6",
        "repo": "spotify-downloader",
        "path": "tests/utils/test_config.py",
        "file_name": "test_config.py",
        "fun_name": "test_get_cache_path",
        "commit_message": "v4 init",
        "code": "def test_get_cache_path(setup):\n    \n\n    assert get_cache_path() == Path(setup.directory, \".spotdl\", \".spotipy\")\n\n",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 14,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 5356,
        "documentation": {
            "docstring": "\n    Tests if the path to the cache file is correct.\n    ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 60149,
        "commit_id": "9ab65f6480a31ba022d9846fdfbfca1d17da8164",
        "repo": "prefect",
        "path": "src/prefect/infrastructure/kubernetes.py",
        "file_name": "kubernetes.py",
        "fun_name": "_get_cluster_uid",
        "commit_message": "Add `PREFECT_KUBERNETES_CLUSTER_UID` to allow bypass of `kube-system` namespace read (#7864)\n\nCo-authored-by: Peyton <44583861+peytonrunyan@users.noreply.github.com>",
        "code": "def _get_cluster_uid(self) -> str:\n        \n        # Default to an environment variable\n        env_cluster_uid = os.environ.get(\"PREFECT_KUBERNETES_CLUSTER_UID\")\n        if env_cluster_uid:\n            return env_cluster_uid\n\n        # Read the UID from the cluster namespace\n        with self.get_client() as client:\n            namespace = client.read_namespace(\"kube-system\")\n        cluster_uid = namespace.metadata.uid\n\n        return cluster_uid\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 115,
        "n_words": 37,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 49,
        "n_ast_nodes": 91,
        "n_identifiers": 14,
        "d_id": 11992,
        "documentation": {
            "docstring": "\n        Gets a unique id for the current cluster being used.\n\n        There is no real unique identifier for a cluster. However, the `kube-system`\n        namespace is immutable and has a persistence UID that we use instead.\n\n        PREFECT_KUBERNETES_CLUSTER_UID can be set in cases where the `kube-system`\n        namespace cannot be read e.g. when a cluster role cannot be created. If set,\n        this variable will be used and we will not attempt to read the `kube-system`\n        namespace.\n\n        See https://github.com/kubernetes/kubernetes/issues/44954\n        ",
            "n_words": 74,
            "vocab_size": 53,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 270593,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/dtensor/layout_map.py",
        "file_name": "layout_map.py",
        "fun_name": "get_default_mesh",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_default_mesh(self):\n        \n        return self._default_mesh\n\n\nLayoutMap.get.__doc__ = LayoutMap.__getitem__.__doc__\n\n\n@keras_export(\"keras.dtensor.experimental.layout_map_scope\", v1=[])\n@contextlib.contextmanager",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.dtensor.experimental.layout_map_scope\", v1=[])\n@contextlib.contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 21,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 60,
        "n_identifiers": 11,
        "d_id": 80492,
        "documentation": {
            "docstring": "Return the default `Mesh` set at instance creation.\n\n        The `Mesh` can be used to create default replicated `Layout` when there\n        isn't a match of the input string query.\n        ",
            "n_words": 28,
            "vocab_size": 25,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 306974,
        "commit_id": "52b5e1779f1ed6e5005dc0bdff4137040d7216fb",
        "repo": "core",
        "path": "homeassistant/components/philips_js/media_player.py",
        "file_name": "media_player.py",
        "fun_name": "state",
        "commit_message": "Use new media player enums [p] (#78058)",
        "code": "def state(self) -> MediaPlayerState:\n        \n        if self._tv.on and (self._tv.powerstate == \"On\" or self._tv.powerstate is None):\n            return MediaPlayerState.ON\n        return MediaPlayerState.OFF\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 50,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 41,
        "n_ast_nodes": 68,
        "n_identifiers": 8,
        "d_id": 105754,
        "documentation": {
            "docstring": "Get the device state. An exception means OFF state.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 275788,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/preprocessing/text.py",
        "file_name": "text.py",
        "fun_name": "to_json",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def to_json(self, **kwargs):\n        \n        config = self.get_config()\n        tokenizer_config = {\n            \"class_name\": self.__class__.__name__,\n            \"config\": config,\n        }\n        return json.dumps(tokenizer_config, **kwargs)\n\n\n@keras_export(\"keras.preprocessing.text.tokenizer_from_json\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.preprocessing.text.tokenizer_from_json\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 74,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 82,
        "n_identifiers": 11,
        "d_id": 81467,
        "documentation": {
            "docstring": "Returns a JSON string containing the tokenizer configuration.\n\n        To load a tokenizer from a JSON string, use\n        `keras.preprocessing.text.tokenizer_from_json(json_string)`.\n\n        Args:\n            **kwargs: Additional keyword arguments\n                to be passed to `json.dumps()`.\n\n        Returns:\n            A JSON string containing the tokenizer configuration.\n        ",
            "n_words": 36,
            "vocab_size": 25,
            "n_whitespaces": 108,
            "language": "en"
        }
    },
    {
        "id": 207766,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_delete_view",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_delete_view(self):\n        \n        delete_dict = {\"post\": \"yes\"}\n        delete_url = reverse(\"admin:admin_views_article_delete\", args=(self.a1.pk,))\n\n        # add user should not be able to delete articles\n        self.client.force_login(self.adduser)\n        response = self.client.get(delete_url)\n        self.assertEqual(response.status_code, 403)\n        post = self.client.post(delete_url, delete_dict)\n        self.assertEqual(post.status_code, 403)\n        self.assertEqual(Article.objects.count(), 3)\n        self.client.logout()\n\n        # view user should not be able to delete articles\n        self.client.force_login(self.viewuser)\n        response = self.client.get(delete_url)\n        self.assertEqual(response.status_code, 403)\n        post = self.client.post(delete_url, delete_dict)\n        self.assertEqual(post.status_code, 403)\n        self.assertEqual(Article.objects.count(), 3)\n        self.client.logout()\n\n        # Delete user can delete\n        self.client.force_login(self.deleteuser)\n        response = self.client.get(\n            reverse(\"admin:admin_views_section_delete\", args=(self.s1.pk,))\n        )\n        self.assertContains(response, \"<h2>Summary</h2>\")\n        self.assertContains(response, \"<li>Articles: 3</li>\")\n        # test response contains link to related Article\n        self.assertContains(response, \"admin_views/article/%s/\" % self.a1.pk)\n\n        response = self.client.get(delete_url)\n        self.assertContains(response, \"admin_views/article/%s/\" % self.a1.pk)\n        self.assertContains(response, \"<h2>Summary</h2>\")\n        self.assertContains(response, \"<li>Articles: 1</li>\")\n        post = self.client.post(delete_url, delete_dict)\n        self.assertRedirects(post, self.index_url)\n        self.assertEqual(Article.objects.count(), 2)\n        self.assertEqual(len(mail.outbox), 1)\n        self.assertEqual(mail.outbox[0].subject, \"Greetings from a deleted object\")\n        article_ct = ContentType.objects.get_for_model(Article)\n        logged = LogEntry.objects.get(content_type=article_ct, action_flag=DELETION)\n        self.assertEqual(logged.object_id, str(self.a1.pk))\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 410,
        "n_words": 126,
        "vocab_size": 71,
        "complexity": 1,
        "nloc": 36,
        "token_counts": 387,
        "n_ast_nodes": 624,
        "n_identifiers": 40,
        "d_id": 52091,
        "documentation": {
            "docstring": "Delete view should restrict access and actually delete items.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 177869,
        "commit_id": "d8d6a0554bfd263f8ce12ff3ce5a69986edd9bc0",
        "repo": "label-studio",
        "path": "label_studio/data_import/uploader.py",
        "file_name": "uploader.py",
        "fun_name": "tasks_from_url",
        "commit_message": "fix: DEV-2361: Fix bandit check in LabelStudio Opensource (#2379)",
        "code": "def tasks_from_url(file_upload_ids, project, request, url):\n    \n    # process URL with tasks\n    ctx = ssl.create_default_context()\n    ctx.check_hostname = False\n    ctx.verify_mode = ssl.CERT_NONE\n    try:\n        filename = url.rsplit('/', 1)[-1]\n        with urlopen(url, context=ctx) as file:   # nosec\n            # check size\n            meta = file.info()\n            file.size = int(meta.get(\"Content-Length\"))\n            file.urlopen = True\n            check_file_sizes_and_number({url: file})\n            file_content = file.read()\n            if isinstance(file_content, str):\n                file_content = file_content.encode()\n            file_upload = create_file_upload(request, project, SimpleUploadedFile(filename, file_content))\n            file_upload_ids.append(file_upload.id)\n            tasks, found_formats, data_keys = FileUpload.load_tasks_from_uploaded_files(project, file_upload_ids)\n\n    except ValidationError as e:\n        raise e\n    except Exception as e:\n        raise ValidationError(str(e))\n    return data_keys, found_formats, tasks, file_upload_ids\n\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 266,
        "n_words": 84,
        "vocab_size": 62,
        "complexity": 4,
        "nloc": 22,
        "token_counts": 179,
        "n_ast_nodes": 291,
        "n_identifiers": 40,
        "d_id": 42529,
        "documentation": {
            "docstring": " Download file using URL and read tasks from it\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 271583,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training.py",
        "file_name": "training.py",
        "fun_name": "_multi_worker_concat",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _multi_worker_concat(v, strategy):\n    \n    replicas = strategy.gather(v, axis=0)\n    # v might not have the same shape on different replicas\n    if _is_per_replica_instance(v):\n        shapes = tf.concat(\n            [\n                tf.expand_dims(tf.shape(single_value)[0], axis=0)\n                for single_value in v.values\n            ],\n            axis=0,\n        )\n        all_shapes = strategy.gather(shapes, axis=0)\n    else:\n        # v is a tensor. This may happen when, say, we have 2x1 multi-worker.\n        all_shapes = strategy.gather(\n            tf.expand_dims(tf.shape(v)[0], axis=0), axis=0\n        )\n\n    replicas = tf.split(\n        replicas,\n        num_or_size_splits=all_shapes,\n        num=strategy.num_replicas_in_sync,\n    )\n    ordered_replicas = []\n    num_replicas_per_worker = len(strategy.extended.worker_devices)\n    for replica_id in range(num_replicas_per_worker):\n        ordered_replicas += replicas[replica_id::num_replicas_per_worker]\n    return concat(ordered_replicas)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 258,
        "n_words": 81,
        "vocab_size": 62,
        "complexity": 4,
        "nloc": 25,
        "token_counts": 161,
        "n_ast_nodes": 248,
        "n_identifiers": 26,
        "d_id": 80811,
        "documentation": {
            "docstring": "Order PerReplica objects for CollectiveAllReduceStrategy and concat.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 196041,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/codegen/fnodes.py",
        "file_name": "fnodes.py",
        "fun_name": "shape",
        "commit_message": "Updated import locations",
        "code": "def shape(source, kind=None):\n    \n    return FunctionCall(\n        'shape',\n        [_printable(source)] +\n        ([_printable(kind)] if kind else [])\n    )\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 44,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 36,
        "n_ast_nodes": 59,
        "n_identifiers": 5,
        "d_id": 47541,
        "documentation": {
            "docstring": " Creates an AST node for a function call to Fortran's \"shape(...)\"\n\n    Parameters\n    ==========\n\n    source : Symbol or String\n    kind : expr\n\n    Examples\n    ========\n\n    >>> from sympy import fcode\n    >>> from sympy.codegen.fnodes import shape\n    >>> shp = shape('x')\n    >>> fcode(shp, source_format='free')\n    'shape(x)'\n\n    ",
            "n_words": 41,
            "vocab_size": 35,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 177774,
        "commit_id": "4ec4614e5e8b74795ecf8620e414f0340c6b94ef",
        "repo": "label-studio",
        "path": "label_studio/tests/test_predictions.py",
        "file_name": "test_predictions.py",
        "fun_name": "test_interactive_annotating_with_drafts",
        "commit_message": "fix: DEV-2138: In interactive prediction only current user's draft should be sent (#2233)\n\n* fix: DEV-2138: In interactive prediction only current user's draft should be sent\r\n\r\n* Add test to check drafts in interactive prediction\r\n\r\nCo-authored-by: hlomzik <hlomzik@gmail.com>",
        "code": "def test_interactive_annotating_with_drafts(business_client, configured_project):\n    \n    # create project with predefined task set\n    ml_backend = configured_project.ml_backends.first()\n    ml_backend.is_interactive = True\n    ml_backend.save()\n\n    users = list(User.objects.all())\n\n    task = configured_project.tasks.first()\n    AnnotationDraft.objects.create(task=task, user=users[0], result={}, lead_time=1)\n    AnnotationDraft.objects.create(task=task, user=users[1], result={}, lead_time=2)\n    # run prediction\n    with requests_mock.Mocker(real_http=True) as m:\n        m.register_uri('POST', f'{ml_backend.url}/predict', json={'results': [{'x': 'x'}]}, status_code=200)\n\n        r = business_client.post(\n            f'/api/ml/{ml_backend.pk}/interactive-annotating',\n            data=json.dumps(\n                {\n                    'task': task.id,\n                    'context': {'y': 'y'},\n                }\n            ),\n            content_type=\"application/json\",\n        )\n        r.status_code = 200\n\n        result = r.json()\n\n        assert 'data' in result\n        assert 'x' in result['data']\n        assert result['data']['x'] == 'x'\n\n        history = [req for req in m.request_history if 'predict' in req.path][0]\n        assert history.text\n\n        js = json.loads(history.text)\n\n        assert len(js['tasks'][0]['drafts']) == 1",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 326,
        "n_words": 97,
        "vocab_size": 74,
        "complexity": 3,
        "nloc": 29,
        "token_counts": 260,
        "n_ast_nodes": 448,
        "n_identifiers": 43,
        "d_id": 42498,
        "documentation": {
            "docstring": "\n    Test interactive annotating with drafts\n    :param business_client:\n    :param configured_project:\n    :return:\n    ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 20072,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distro.py",
        "file_name": "distro.py",
        "fun_name": "_parse_distro_release_file",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _parse_distro_release_file(self, filepath):\n        # type: (str) -> Dict[str, str]\n        \n        try:\n            with open(filepath) as fp:\n                # Only parse the first line. For instance, on SLES there\n                # are multiple lines. We don't want them...\n                return self._parse_distro_release_content(fp.readline())\n        except (OSError, IOError):\n            # Ignore not being able to read a specific, seemingly version\n            # related file.\n            # See https://github.com/python-distro/distro/issues/162\n            return {}\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 185,
        "n_words": 57,
        "vocab_size": 51,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 74,
        "n_identifiers": 9,
        "d_id": 3218,
        "documentation": {
            "docstring": "\n        Parse a distro release file.\n\n        Parameters:\n\n        * filepath: Path name of the distro release file.\n\n        Returns:\n            A dictionary containing all information items.\n        ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 253601,
        "commit_id": "19aba1f059efad45e1466d47954b2cf54d45b106",
        "repo": "d2l-en",
        "path": "d2l/mxnet.py",
        "file_name": "mxnet.py",
        "fun_name": "save_hyperparameters",
        "commit_message": "simplify d2l lib",
        "code": "def save_hyperparameters(self, ignore=[]):\n        \n        frame = inspect.currentframe().f_back\n        _, _, _, local_vars = inspect.getargvalues(frame)\n        self.hparams = {k:v for k, v in local_vars.items()\n                        if k not in set(ignore+['self']) and not k.startswith('_')}\n        for k, v in self.hparams.items():\n            setattr(self, k, v)\n",
        "url": "https://github.com/d2l-ai/d2l-en.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 105,
        "n_words": 36,
        "vocab_size": 25,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 94,
        "n_ast_nodes": 150,
        "n_identifiers": 17,
        "d_id": 74148,
        "documentation": {
            "docstring": "Save function arguments into class attributes.\n\n        Defined in :numref:`sec_utils`",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 74148,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_blocks.py",
        "file_name": "test_blocks.py",
        "fun_name": "test_str_structvalue",
        "commit_message": "Reformat with black",
        "code": "def test_str_structvalue(self):\n        \n        block = SectionBlock()\n        value = block.to_python({\"title\": \"Hello\", \"body\": \"<i>italic</i> world\"})\n        result = str(value)\n        self.assertNotIn(\"<h1>\", result)\n        # The expected rendering should correspond to the native representation of an OrderedDict:\n        # \"StructValue([('title', u'Hello'), ('body', <wagtail.core.rich_text.RichText object at 0xb12d5eed>)])\"\n        # - give or take some quoting differences between Python versions\n        self.assertIn(\"StructValue\", result)\n        self.assertIn(\"title\", result)\n        self.assertIn(\"Hello\", result)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 132,
        "n_words": 55,
        "vocab_size": 48,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 65,
        "n_ast_nodes": 123,
        "n_identifiers": 10,
        "d_id": 16224,
        "documentation": {
            "docstring": "\n        The str() representation of a StructValue should NOT render the template, as that's liable\n        to cause an infinite loop if any debugging / logging code attempts to log the fact that\n        it rendered a template with this object in the context:\n        https://github.com/wagtail/wagtail/issues/2874\n        https://github.com/jazzband/django-debug-toolbar/issues/950\n        ",
            "n_words": 43,
            "vocab_size": 39,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 251362,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "mitmproxy/flow.py",
        "file_name": "flow.py",
        "fun_name": "revert",
        "commit_message": "make it black!",
        "code": "def revert(self):\n        \n        if self._backup:\n            self.set_state(self._backup)\n            self._backup = None\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 44,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 42,
        "n_identifiers": 4,
        "d_id": 73697,
        "documentation": {
            "docstring": "\n        Revert to the last backed up state.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 289375,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/components/history/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_fetch_period_api_with_no_timestamp",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "async def test_fetch_period_api_with_no_timestamp(recorder_mock, hass, hass_client):\n    \n    await async_setup_component(hass, \"history\", {})\n    client = await hass_client()\n    response = await client.get(\"/api/history/period\")\n    assert response.status == HTTPStatus.OK\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 36,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 75,
        "n_identifiers": 11,
        "d_id": 88517,
        "documentation": {
            "docstring": "Test the fetch period view for history with no timestamp.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 271626,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_arrays_test.py",
        "file_name": "training_arrays_test.py",
        "fun_name": "test_print_info_with_numpy",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def test_print_info_with_numpy(self, do_validation):\n        \n\n        model = keras.models.Sequential(\n            [keras.layers.Dense(1, input_shape=(2,))]\n        )\n        model.compile(loss=\"mse\", optimizer=\"sgd\")\n\n        dataset = np.arange(200).reshape(100, 2)\n\n        if do_validation:\n            val_data = (\n                np.arange(100).reshape(50, 2),\n                np.arange(50).reshape(50, 1),\n            )\n        else:\n            val_data = None\n\n        mock_stdout = io.StringIO()\n        with tf.compat.v1.test.mock.patch.object(sys, \"stdout\", mock_stdout):\n            model.fit(\n                dataset, batch_size=10, epochs=2, validation_data=val_data\n            )\n\n        self.assertIn(\"Train on 100 samples\", mock_stdout.getvalue())\n\n        if do_validation:\n            self.assertIn(\", validate on 50 samples\", mock_stdout.getvalue())\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 254,
        "n_words": 55,
        "vocab_size": 43,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 175,
        "n_ast_nodes": 280,
        "n_identifiers": 35,
        "d_id": 80835,
        "documentation": {
            "docstring": "Print training info should work with val datasets (b/133391839).",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 157317,
        "commit_id": "ca86da3a30c4e080d4db8c25fca73de843663cb4",
        "repo": "stablediffusion",
        "path": "ldm/models/diffusion/ddpm.py",
        "file_name": "ddpm.py",
        "fun_name": "q_mean_variance",
        "commit_message": "release more models",
        "code": "def q_mean_variance(self, x_start, t):\n        \n        mean = (extract_into_tensor(self.sqrt_alphas_cumprod, t, x_start.shape) * x_start)\n        variance = extract_into_tensor(1.0 - self.alphas_cumprod, t, x_start.shape)\n        log_variance = extract_into_tensor(self.log_one_minus_alphas_cumprod, t, x_start.shape)\n        return mean, variance, log_variance\n",
        "url": "https://github.com/Stability-AI/stablediffusion.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 62,
        "n_words": 27,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 66,
        "n_ast_nodes": 94,
        "n_identifiers": 12,
        "d_id": 36898,
        "documentation": {
            "docstring": "\n        Get the distribution q(x_t | x_0).\n        :param x_start: the [N x C x ...] tensor of noiseless inputs.\n        :param t: the number of diffusion steps (minus 1). Here, 0 means one step.\n        :return: A tuple (mean, variance, log_variance), all of x_start's shape.\n        ",
            "n_words": 42,
            "vocab_size": 36,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 242362,
        "commit_id": "6be87277f71948bc7e4b945c46660cac3e5ce919",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "getpalette",
        "commit_message": "Allow rawmode None to return the palette in the current mode",
        "code": "def getpalette(self, rawmode=\"RGB\"):\n        \n\n        self.load()\n        try:\n            mode = self.im.getpalettemode()\n        except ValueError:\n            return None  # no palette\n        if rawmode is None:\n            rawmode = mode\n        return list(self.im.getpalette(mode, rawmode))\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 101,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 53,
        "n_ast_nodes": 91,
        "n_identifiers": 9,
        "d_id": 69846,
        "documentation": {
            "docstring": "\n        Returns the image palette as a list.\n\n        :param rawmode: The mode in which to return the palette. ``None`` will\n           return the palette in its current mode.\n        :returns: A list of color values [r, g, b, ...], or None if the\n           image has no palette.\n        ",
            "n_words": 44,
            "vocab_size": 36,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 321036,
        "commit_id": "8eecf3af83fc9a4e465744a83e86856fe1c6df10",
        "repo": "qutebrowser",
        "path": "tests/unit/config/test_config.py",
        "file_name": "test_config.py",
        "fun_name": "test_get_mutable_invalid_value",
        "commit_message": "config: Discard prior mutables before applying\n\nIf we only clear existing mutables *after* applying, we get into an\ninconsistent state if there was an error in one of the config values:\n\nThe improper value lingers around in self._mutables, and then gets\nreturned when get_mutable_obj() (or update_mutables()) gets called the\nnext time.\n\nReproducer:\n\n    qutebrowser --debug --temp-basedir \\\n        ':config-dict-add content.javascript.log_message.levels example.org bla' \\\n        ':later 1000 config-dict-add content.javascript.log_message.levels example.org bla'\n\nResults in:\n\n    ERROR: Invalid value 'bla' - expected a value of type list but got str.\n    ERROR: example.org already exists in content.javascript.log_message - use --replace to overwrite!\n\nFixes the second part of #7343.\n\nnb: As before, the mutable updating actually gets interrupted by a\nfailing update, instead of it e.g. collecting all errors but carrying\non. With this change, the remaining updates will thus also be discarded,\nbut that does not seem to be a problem with how mutables are currently\nused. Ideally, we should get rid of the mutable handling entirely\nanyways, at least for qutebrowser internal code - see #4344.",
        "code": "def test_get_mutable_invalid_value(self, conf):\n        \n        option = 'keyhint.blacklist'\n        obj = conf.get_mutable_obj(option)\n        assert obj == []\n        obj.append(42)\n\n        with pytest.raises(configexc.ValidationError):\n            conf.update_mutables()\n\n        obj = conf.get_mutable_obj(option)\n        assert obj == []\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 24,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 58,
        "n_ast_nodes": 101,
        "n_identifiers": 12,
        "d_id": 117490,
        "documentation": {
            "docstring": "Make sure invalid values aren't stored in mutables.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 278640,
        "commit_id": "3613c3defc39c236fb1592c4f7ba1a9cc887343a",
        "repo": "keras",
        "path": "keras/callbacks.py",
        "file_name": "callbacks.py",
        "fun_name": "keras_model_summary",
        "commit_message": "Remove pylint comments.\n\nPiperOrigin-RevId: 452353044",
        "code": "def keras_model_summary(name, data, step=None):\n    \n    summary_metadata = tf.compat.v1.SummaryMetadata()\n    # Hard coding a plugin name. Please refer to go/tb-plugin-name-hardcode for\n    # the rationale.\n    summary_metadata.plugin_data.plugin_name = \"graph_keras_model\"\n    # version number = 1\n    summary_metadata.plugin_data.content = b\"1\"\n\n    try:\n        json_string = data.to_json()\n    except Exception as exc:\n        # An exception should not break a model code.\n        logging.warning(\n            \"Model failed to serialize as JSON. Ignoring... %s\", exc\n        )\n        return False\n\n    with tf.summary.experimental.summary_scope(\n        name, \"graph_keras_model\", [data, step]\n    ) as (tag, _):\n        with tf.device(\"cpu:0\"):\n            tensor = tf.constant(json_string, dtype=tf.string)\n        return tf.summary.write(\n            tag=tag, tensor=tensor, step=step, metadata=summary_metadata\n        )\n\n\n@keras_export(\"keras.callbacks.TensorBoard\", v1=[])",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.callbacks.TensorBoard\", v1=[])",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 215,
        "n_words": 87,
        "vocab_size": 71,
        "complexity": 2,
        "nloc": 19,
        "token_counts": 133,
        "n_ast_nodes": 239,
        "n_identifiers": 31,
        "d_id": 82645,
        "documentation": {
            "docstring": "Writes a Keras model as JSON to as a Summary.\n\n    Writing the Keras model configuration allows the TensorBoard graph plugin to\n    render a conceptual graph, as opposed to graph of ops. In case the model\n    fails to serialize as JSON, it ignores and returns False.\n\n    Args:\n      name: A name for this summary. The summary tag used for TensorBoard will\n        be this name prefixed by any active name scopes.\n      data: A Keras Model to write.\n      step: Explicit `int64`-castable monotonic step value for this summary. If\n        omitted, this defaults to `tf.summary.experimental.get_step()`, which\n        must not be None.\n\n    Returns:\n      True on success, or False if no summary was written because no default\n      summary writer was available.\n\n    Raises:\n      ValueError: if a default writer exists, but no step was provided and\n        `tf.summary.experimental.get_step()` is None.\n    ",
            "n_words": 128,
            "vocab_size": 87,
            "n_whitespaces": 207,
            "language": "en"
        }
    },
    {
        "id": 44415,
        "commit_id": "6fc6edf6af7f676bfa54ff3a2e6e6d2edb938f2e",
        "repo": "airflow",
        "path": "airflow/jobs/backfill_job.py",
        "file_name": "backfill_job.py",
        "fun_name": "_update_counters",
        "commit_message": "Make `airflow dags test` be able to execute Mapped Tasks (#21210)\n\n* Make `airflow dags test` be able to execute Mapped Tasks\r\n\r\nIn order to do this there were two steps required:\r\n\r\n- The BackfillJob needs to know about mapped tasks, both to expand them,\r\n  and in order to update it's TI tracking\r\n- The DebugExecutor needed to \"unmap\" the mapped task to get the real\r\n  operator back\r\n\r\nI was testing this with the following dag:\r\n\r\n```\r\nfrom airflow import DAG\r\nfrom airflow.decorators import task\r\nfrom airflow.operators.python import PythonOperator\r\nimport pendulum\r\n\r\n@task\r\ndef make_list():\r\n    return list(map(lambda a: f'echo \"{a!r}\"', [1, 2, {'a': 'b'}]))\r\n\r\ndef consumer(*args):\r\n     print(repr(args))\r\n\r\nwith DAG(dag_id='maptest', start_date=pendulum.DateTime(2022, 1, 18)) as dag:\r\n    PythonOperator(task_id='consumer', python_callable=consumer).map(op_args=make_list())\r\n```\r\n\r\nIt can't \"unmap\" decorated operators successfully yet, so we're using\r\nold-school PythonOperator\r\n\r\nWe also just pass the whole value to the operator, not just the current\r\nmapping value(s)\r\n\r\n* Always have a `task_group` property on DAGNodes\r\n\r\nAnd since TaskGroup is a DAGNode, we don't need to store parent group\r\ndirectly anymore -- it'll already be stored\r\n\r\n* Add \"integation\" tests for running mapped tasks via BackfillJob\r\n\r\n* Only show \"Map Index\" in Backfill report when relevant\r\n\r\nCo-authored-by: Tzu-ping Chung <uranusjr@gmail.com>",
        "code": "def _update_counters(self, ti_status, session=None):\n        \n        tis_to_be_scheduled = []\n        refreshed_tis = []\n        TI = TaskInstance\n\n        filter_for_tis = TI.filter_for_tis(list(ti_status.running.values()))\n        if filter_for_tis is not None:\n            refreshed_tis = session.query(TI).filter(filter_for_tis).all()\n\n        for ti in refreshed_tis:\n            # Here we remake the key by subtracting 1 to match in memory information\n            reduced_key = ti.key.reduced\n            if ti.state == TaskInstanceState.SUCCESS:\n                ti_status.succeeded.add(reduced_key)\n                self.log.debug(\"Task instance %s succeeded. Don't rerun.\", ti)\n                ti_status.running.pop(reduced_key)\n                continue\n            if ti.state == TaskInstanceState.SKIPPED:\n                ti_status.skipped.add(reduced_key)\n                self.log.debug(\"Task instance %s skipped. Don't rerun.\", ti)\n                ti_status.running.pop(reduced_key)\n                continue\n            if ti.state == TaskInstanceState.FAILED:\n                self.log.error(\"Task instance %s failed\", ti)\n                ti_status.failed.add(reduced_key)\n                ti_status.running.pop(reduced_key)\n                continue\n            # special case: if the task needs to run again put it back\n            if ti.state == TaskInstanceState.UP_FOR_RETRY:\n                self.log.warning(\"Task instance %s is up for retry\", ti)\n                ti_status.running.pop(reduced_key)\n                ti_status.to_run[ti.key] = ti\n            # special case: if the task needs to be rescheduled put it back\n            elif ti.state == TaskInstanceState.UP_FOR_RESCHEDULE:\n                self.log.warning(\"Task instance %s is up for reschedule\", ti)\n                # During handling of reschedule state in ti._handle_reschedule, try number is reduced\n                # by one, so we should not use reduced_key to avoid key error\n                ti_status.running.pop(ti.key)\n                ti_status.to_run[ti.key] = ti\n            # special case: The state of the task can be set to NONE by the task itself\n            # when it reaches concurrency limits. It could also happen when the state\n            # is changed externally, e.g. by clearing tasks from the ui. We need to cover\n            # for that as otherwise those tasks would fall outside of the scope of\n            # the backfill suddenly.\n            elif ti.state == State.NONE:\n                self.log.warning(\n                    \"FIXME: task instance %s state was set to none externally or \"\n                    \"reaching concurrency limits. Re-adding task to queue.\",\n                    ti,\n                )\n                tis_to_be_scheduled.append(ti)\n                ti_status.running.pop(reduced_key)\n                ti_status.to_run[ti.key] = ti\n\n        # Batch schedule of task instances\n        if tis_to_be_scheduled:\n            filter_for_tis = TI.filter_for_tis(tis_to_be_scheduled)\n            session.query(TI).filter(filter_for_tis).update(\n                values={TI.state: TaskInstanceState.SCHEDULED}, synchronize_session=False\n            )\n            session.flush()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1009,
        "n_words": 279,
        "vocab_size": 148,
        "complexity": 10,
        "nloc": 47,
        "token_counts": 350,
        "n_ast_nodes": 578,
        "n_identifiers": 43,
        "d_id": 8254,
        "documentation": {
            "docstring": "\n        Updates the counters per state of the tasks that were running. Can re-add\n        to tasks to run in case required.\n\n        :param ti_status: the internal status of the backfill job tasks\n        ",
            "n_words": 30,
            "vocab_size": 23,
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        "id": 20223,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/platformdirs/macos.py",
        "file_name": "macos.py",
        "fun_name": "user_config_dir",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def user_config_dir(self) -> str:\n        \n        return self._append_app_name_and_version(os.path.expanduser(\"~/Library/Preferences/\"))\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 10,
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        "n_identifiers": 7,
        "d_id": 3275,
        "documentation": {
            "docstring": ":return: config directory tied to the user, e.g. ``~/Library/Preferences/$appname/$version``",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
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    {
        "id": 65680,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/controllers/stock_controller.py",
        "file_name": "stock_controller.py",
        "fun_name": "future_sle_exists",
        "commit_message": "style: format code with black",
        "code": "def future_sle_exists(args, sl_entries=None):\n\tkey = (args.voucher_type, args.voucher_no)\n\n\tif validate_future_sle_not_exists(args, key, sl_entries):\n\t\treturn False\n\telif get_cached_data(args, key):\n\t\treturn True\n\n\tif not sl_entries:\n\t\tsl_entries = get_sle_entries_against_voucher(args)\n\t\tif not sl_entries:\n\t\t\treturn\n\n\tor_conditions = get_conditions_to_validate_future_sle(sl_entries)\n\n\tdata = frappe.db.sql(\n\t\t.format(\n\t\t\t\" or \".join(or_conditions)\n\t\t),\n\t\targs,\n\t\tas_dict=1,\n\t)\n\n\tfor d in data:\n\t\tfrappe.local.future_sle[key][(d.item_code, d.warehouse)] = d.total_row\n\n\treturn len(data)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 13986,
        "documentation": {
            "docstring": "\n\t\tselect item_code, warehouse, count(name) as total_row\n\t\tfrom `tabStock Ledger Entry` force index (item_warehouse)\n\t\twhere\n\t\t\t({})\n\t\t\tand timestamp(posting_date, posting_time)\n\t\t\t\t>= timestamp(%(posting_date)s, %(posting_time)s)\n\t\t\tand voucher_no != %(voucher_no)s\n\t\t\tand is_cancelled = 0\n\t\tGROUP BY\n\t\t\titem_code, warehouse\n\t\t",
            "n_words": 33,
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            "n_whitespaces": 23,
            "language": "en"
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    },
    {
        "id": 90529,
        "commit_id": "6307cf52c4c7f185f9023c6279e565dd7812c202",
        "repo": "sentry",
        "path": "src/sentry/snuba/metrics_performance.py",
        "file_name": "metrics_performance.py",
        "fun_name": "normalize_histogram_results",
        "commit_message": "feat(mep): Adding histogram support to metrics enhanced perf (#34462)\n\n- This uses the metrics dataset to supply histogram data in the same\r\n  format discover expects\r\n- Outlier is currently based on p25 and p75, may change to using tags\r\n  later",
        "code": "def normalize_histogram_results(fields, histogram_params, results):\n    \n\n    # zerofill and rename the columns while making sure to adjust for precision\n    bucket_maps = {field: {} for field in fields}\n    # Only one row in metrics result\n    data = results[\"data\"][0]\n    for field in fields:\n        histogram_column = f\"histogram({field})\"\n        histogram_alias = get_function_alias(histogram_column)\n        bucket_maps[field] = {start: height for start, end, height in data[histogram_alias]}\n\n    new_data = {field: [] for field in fields}\n    for i in range(histogram_params.num_buckets):\n        bucket = histogram_params.start_offset + histogram_params.bucket_size * i\n        for field in fields:\n            row = {\n                \"bin\": bucket,\n                \"count\": bucket_maps[field].get(bucket, 0),\n            }\n            # make sure to adjust for the precision if necessary\n            if histogram_params.multiplier > 1:\n                row[\"bin\"] /= float(histogram_params.multiplier)\n            new_data[field].append(row)\n\n    return new_data\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
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        "complexity": 8,
        "nloc": 19,
        "token_counts": 157,
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        "n_identifiers": 25,
        "d_id": 18673,
        "documentation": {
            "docstring": "\n    Normalizes the histogram results by renaming the columns to key and bin\n    and make sure to zerofill any missing values.\n\n    :param [str] fields: The list of fields for which you want to generate the\n        histograms for.\n    :param str key_column: The column of the key name.\n    :param HistogramParams histogram_params: The histogram parameters used.\n    :param any results: The results from the histogram query that may be missing\n        bins and needs to be normalized.\n    :param str array_column: Array column prefix\n    ",
            "n_words": 77,
            "vocab_size": 51,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 260053,
        "commit_id": "a2c4d8b1f4471f52a4fcf1026f495e637a472568",
        "repo": "scikit-learn",
        "path": "sklearn/utils/sparsefuncs.py",
        "file_name": "sparsefuncs.py",
        "fun_name": "inplace_swap_column",
        "commit_message": "DOC Ensures that inplace_swap_column passes numpydoc validation (#23476)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: harshit5674 <harshit@Harshits-MacBook-Air.local>",
        "code": "def inplace_swap_column(X, m, n):\n    \n    if m < 0:\n        m += X.shape[1]\n    if n < 0:\n        n += X.shape[1]\n    if isinstance(X, sp.csc_matrix):\n        inplace_swap_row_csr(X, m, n)\n    elif isinstance(X, sp.csr_matrix):\n        inplace_swap_row_csc(X, m, n)\n    else:\n        _raise_typeerror(X)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "nloc": 11,
        "token_counts": 78,
        "n_ast_nodes": 120,
        "n_identifiers": 12,
        "d_id": 76051,
        "documentation": {
            "docstring": "\n    Swap two columns of a CSC/CSR matrix in-place.\n\n    Parameters\n    ----------\n    X : sparse matrix of shape (n_samples, n_features)\n        Matrix whose two columns are to be swapped. It should be of\n        CSR or CSC format.\n\n    m : int\n        Index of the column of X to be swapped.\n\n    n : int\n        Index of the column of X to be swapped.\n    ",
            "n_words": 58,
            "vocab_size": 34,
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            "language": "en"
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    {
        "id": 163192,
        "commit_id": "521259299f7829da667ba39302ec77acedde9e5e",
        "repo": "pandas",
        "path": "pandas/core/indexes/category.py",
        "file_name": "category.py",
        "fun_name": "map",
        "commit_message": "DOC: Improve doc summaries in series.rst (#45237)",
        "code": "def map(self, mapper):\n        \n        mapped = self._values.map(mapper)\n        return Index(mapped, name=self.name)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
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        "d_id": 39400,
        "documentation": {
            "docstring": "\n        Map values using input an input mapping or function.\n\n        Maps the values (their categories, not the codes) of the index to new\n        categories. If the mapping correspondence is one-to-one the result is a\n        :class:`~pandas.CategoricalIndex` which has the same order property as\n        the original, otherwise an :class:`~pandas.Index` is returned.\n\n        If a `dict` or :class:`~pandas.Series` is used any unmapped category is\n        mapped to `NaN`. Note that if this happens an :class:`~pandas.Index`\n        will be returned.\n\n        Parameters\n        ----------\n        mapper : function, dict, or Series\n            Mapping correspondence.\n\n        Returns\n        -------\n        pandas.CategoricalIndex or pandas.Index\n            Mapped index.\n\n        See Also\n        --------\n        Index.map : Apply a mapping correspondence on an\n            :class:`~pandas.Index`.\n        Series.map : Apply a mapping correspondence on a\n            :class:`~pandas.Series`.\n        Series.apply : Apply more complex functions on a\n            :class:`~pandas.Series`.\n\n        Examples\n        --------\n        >>> idx = pd.CategoricalIndex(['a', 'b', 'c'])\n        >>> idx\n        CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'],\n                          ordered=False, dtype='category')\n        >>> idx.map(lambda x: x.upper())\n        CategoricalIndex(['A', 'B', 'C'], categories=['A', 'B', 'C'],\n                         ordered=False, dtype='category')\n        >>> idx.map({'a': 'first', 'b': 'second', 'c': 'third'})\n        CategoricalIndex(['first', 'second', 'third'], categories=['first',\n                         'second', 'third'], ordered=False, dtype='category')\n\n        If the mapping is one-to-one the ordering of the categories is\n        preserved:\n\n        >>> idx = pd.CategoricalIndex(['a', 'b', 'c'], ordered=True)\n        >>> idx\n        CategoricalIndex(['a', 'b', 'c'], categories=['a', 'b', 'c'],\n                         ordered=True, dtype='category')\n        >>> idx.map({'a': 3, 'b': 2, 'c': 1})\n        CategoricalIndex([3, 2, 1], categories=[3, 2, 1], ordered=True,\n                         dtype='category')\n\n        If the mapping is not one-to-one an :class:`~pandas.Index` is returned:\n\n        >>> idx.map({'a': 'first', 'b': 'second', 'c': 'first'})\n        Index(['first', 'second', 'first'], dtype='object')\n\n        If a `dict` is used, all unmapped categories are mapped to `NaN` and\n        the result is an :class:`~pandas.Index`:\n\n        >>> idx.map({'a': 'first', 'b': 'second'})\n        Index(['first', 'second', nan], dtype='object')\n        ",
            "n_words": 256,
            "vocab_size": 131,
            "n_whitespaces": 734,
            "language": "en"
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    },
    {
        "id": 178013,
        "commit_id": "583b3cb3b03a36a30b3ce9fe96eb4fb28548a070",
        "repo": "label-studio",
        "path": "label_studio/core/label_config.py",
        "file_name": "label_config.py",
        "fun_name": "get_original_fromname_by_regex",
        "commit_message": "fix: DEV-1462: Fix changing label config for repeater tag  (#2725)\n\n* fix: DEV-1462: Fix changing label config for repeater tag with created annotations",
        "code": "def get_original_fromname_by_regex(config_string, fromname):\n    \n    c = parse_config(config_string)\n    for control in c:\n        item = c[control].get('regex', {})\n        expression = control\n        for key in item:\n            expression = expression.replace(key, item[key])\n        pattern = re.compile(expression)\n        full_match = pattern.fullmatch(fromname)\n        if full_match:\n            return control\n    return fromname\n\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "token_counts": 77,
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        "n_identifiers": 16,
        "d_id": 42571,
        "documentation": {
            "docstring": "\n    Get from_name from config on from_name key from data after applying regex search or original fromname\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 72652,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/api/v2/filters.py",
        "file_name": "filters.py",
        "fun_name": "filter_queryset",
        "commit_message": "Reformat with black",
        "code": "def filter_queryset(self, request, queryset, view):\n        \n        fields = set(view.get_available_fields(queryset.model, db_fields_only=True))\n\n        # Locale is a database field, but we provide a separate filter for it\n        if \"locale\" in fields:\n            fields.remove(\"locale\")\n\n        for field_name, value in request.GET.items():\n            if field_name in fields:\n                try:\n                    field = queryset.model._meta.get_field(field_name)\n                except LookupError:\n                    field = None\n\n                # Convert value into python\n                try:\n                    if isinstance(\n                        field, (models.BooleanField, models.NullBooleanField)\n                    ):\n                        value = parse_boolean(value)\n                    elif isinstance(field, (models.IntegerField, models.AutoField)):\n                        value = int(value)\n                    elif isinstance(field, models.ForeignKey):\n                        value = field.target_field.get_prep_value(value)\n                except ValueError as e:\n                    raise BadRequestError(\n                        \"field filter error. '%s' is not a valid value for %s (%s)\"\n                        % (value, field_name, str(e))\n                    )\n\n                if isinstance(field, TaggableManager):\n                    for tag in value.split(\",\"):\n                        queryset = queryset.filter(**{field_name + \"__name\": tag})\n\n                    # Stick a message on the queryset to indicate that tag filtering has been performed\n                    # This will let the do_search method know that it must raise an error as searching\n                    # and tag filtering at the same time is not supported\n                    queryset._filtered_by_tag = True\n                else:\n                    queryset = queryset.filter(**{field_name: value})\n\n        return queryset\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 758,
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        "vocab_size": 108,
        "complexity": 11,
        "nloc": 31,
        "token_counts": 220,
        "n_ast_nodes": 359,
        "n_identifiers": 39,
        "d_id": 15909,
        "documentation": {
            "docstring": "\n        This performs field level filtering on the result set\n        Eg: ?title=James Joyce\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 91126,
        "commit_id": "3535fa83a743f6967a92e0afdbba2b633236bf67",
        "repo": "sentry",
        "path": "src/sentry/snuba/metrics/utils.py",
        "file_name": "utils.py",
        "fun_name": "generate_operation_regex",
        "commit_message": "fix(metrics): Restrict public name regex [TET-111] (#35305)\n\n* fix(metrics): Restrict public name regex\r\n\r\nRestricts the public name regex for metrics\r\nby separating out the public name regex\r\nand the mri name regex from the shared field\r\nregex and removing characters that are not\r\nexpected to be in public facing names\r\n\r\n* Update mri regex and public regex + add tests\r\n\r\n* Add better tests\r\n\r\n* PR comments",
        "code": "def generate_operation_regex():\n    \n    operations = []\n    for item in OP_TO_SNUBA_FUNCTION.values():\n        operations += list(item.keys())\n    return rf\"({'|'.join(map(str, operations))})\"\n\n\nOP_REGEX = generate_operation_regex()\n\n\nAVAILABLE_OPERATIONS = {\n    type_: sorted(mapping.keys()) for type_, mapping in OP_TO_SNUBA_FUNCTION.items()\n}\nOPERATIONS_TO_ENTITY = {\n    op: entity for entity, operations in AVAILABLE_OPERATIONS.items() for op in operations\n}\n\n# ToDo add guages/summaries\nMETRIC_TYPE_TO_ENTITY: Mapping[MetricType, EntityKey] = {\n    \"counter\": EntityKey.MetricsCounters,\n    \"set\": EntityKey.MetricsSets,\n    \"distribution\": EntityKey.MetricsDistributions,\n}\n\nFIELD_ALIAS_MAPPINGS = {\"project\": \"project_id\"}\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 89,
        "n_words": 64,
        "vocab_size": 46,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 31,
        "n_ast_nodes": 216,
        "n_identifiers": 27,
        "d_id": 18716,
        "documentation": {
            "docstring": "\n    Generates a regex of all supported operations defined in OP_TO_SNUBA_FUNCTION\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 243053,
        "commit_id": "c854bf8d1c05022bec4309fbf6b547e494db9373",
        "repo": "Pillow",
        "path": "src/PIL/ImageFont.py",
        "file_name": "ImageFont.py",
        "fun_name": "getbbox",
        "commit_message": "add getbbox and getlength to basic ImageFont and update related tests",
        "code": "def getbbox(self, text, *args, **kwargs):\n        \n        width, height = self.font.getsize(text)\n        return 0, 0, width, height\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
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        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 52,
        "n_identifiers": 9,
        "d_id": 69963,
        "documentation": {
            "docstring": "\n        Returns bounding box (in pixels) of given text.\n\n        .. versionadded:: 9.2.0\n\n        :param text: Text to render.\n        :param mode: Used by some graphics drivers to indicate what mode the\n                     driver prefers; if empty, the renderer may return either\n                     mode. Note that the mode is always a string, to simplify\n                     C-level implementations.\n\n        :return: ``(left, top, right, bottom)`` bounding box\n        ",
            "n_words": 57,
            "vocab_size": 49,
            "n_whitespaces": 160,
            "language": "en"
        }
    },
    {
        "id": 101720,
        "commit_id": "e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_validate",
        "commit_message": "Alignments Tool - Typing, Documentation + Re-org",
        "code": "def _validate(self) -> None:\n        \n        if self._job == \"missing-frames\" and self._output == \"move\":\n            logger.warning(\"Missing_frames was selected with move output, but there will \"\n                           \"be nothing to move. Defaulting to output: console\")\n            self._output = \"console\"\n        if self._type == \"faces\" and self._job != \"multi-faces\":\n            logger.error(\"The selected folder is not valid. Faces folder (-fc) is only \"\n                         \"supported for 'multi-faces'\")\n            sys.exit(1)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 172,
        "n_words": 57,
        "vocab_size": 46,
        "complexity": 5,
        "nloc": 10,
        "token_counts": 59,
        "n_ast_nodes": 116,
        "n_identifiers": 10,
        "d_id": 21124,
        "documentation": {
            "docstring": " Check that the selected type is valid for selected task and job ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 176718,
        "commit_id": "2a05ccdb07cff88e56661dee8a9271859354027f",
        "repo": "networkx",
        "path": "networkx/algorithms/link_analysis/pagerank_alg.py",
        "file_name": "pagerank_alg.py",
        "fun_name": "pagerank_numpy",
        "commit_message": "Remove redundant py2 numeric conversions (#5661)\n\n* Remove redundant float conversion\r\n\r\n* Remove redundant int conversion\r\n\r\n* Use integer division\r\n\r\nCo-authored-by: Miroslav Šedivý <6774676+eumiro@users.noreply.github.com>",
        "code": "def pagerank_numpy(G, alpha=0.85, personalization=None, weight=\"weight\", dangling=None):\n    \n    msg = \"networkx.pagerank_numpy is deprecated and will be removed in NetworkX 3.0, use networkx.pagerank instead.\"\n    warn(msg, DeprecationWarning, stacklevel=2)\n    import numpy as np\n\n    if len(G) == 0:\n        return {}\n    M = google_matrix(\n        G, alpha, personalization=personalization, weight=weight, dangling=dangling\n    )\n    # use numpy LAPACK solver\n    eigenvalues, eigenvectors = np.linalg.eig(M.T)\n    ind = np.argmax(eigenvalues)\n    # eigenvector of largest eigenvalue is at ind, normalized\n    largest = np.array(eigenvectors[:, ind]).flatten().real\n    norm = largest.sum()\n    return dict(zip(G, map(float, largest / norm)))\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 133,
        "n_words": 77,
        "vocab_size": 65,
        "complexity": 2,
        "nloc": 14,
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        "n_identifiers": 32,
        "d_id": 42053,
        "documentation": {
            "docstring": "Returns the PageRank of the nodes in the graph.\n\n    PageRank computes a ranking of the nodes in the graph G based on\n    the structure of the incoming links. It was originally designed as\n    an algorithm to rank web pages.\n\n    Parameters\n    ----------\n    G : graph\n      A NetworkX graph.  Undirected graphs will be converted to a directed\n      graph with two directed edges for each undirected edge.\n\n    alpha : float, optional\n      Damping parameter for PageRank, default=0.85.\n\n    personalization: dict, optional\n      The \"personalization vector\" consisting of a dictionary with a\n      key some subset of graph nodes and personalization value each of those.\n      At least one personalization value must be non-zero.\n      If not specfiied, a nodes personalization value will be zero.\n      By default, a uniform distribution is used.\n\n    weight : key, optional\n      Edge data key to use as weight.  If None weights are set to 1.\n\n    dangling: dict, optional\n      The outedges to be assigned to any \"dangling\" nodes, i.e., nodes without\n      any outedges. The dict key is the node the outedge points to and the dict\n      value is the weight of that outedge. By default, dangling nodes are given\n      outedges according to the personalization vector (uniform if not\n      specified) This must be selected to result in an irreducible transition\n      matrix (see notes under google_matrix). It may be common to have the\n      dangling dict to be the same as the personalization dict.\n\n    Returns\n    -------\n    pagerank : dictionary\n       Dictionary of nodes with PageRank as value.\n\n    Examples\n    --------\n    >>> G = nx.DiGraph(nx.path_graph(4))\n    >>> pr = nx.pagerank_numpy(G, alpha=0.9)\n\n    Notes\n    -----\n    The eigenvector calculation uses NumPy's interface to the LAPACK\n    eigenvalue solvers.  This will be the fastest and most accurate\n    for small graphs.\n\n    This implementation works with Multi(Di)Graphs. For multigraphs the\n    weight between two nodes is set to be the sum of all edge weights\n    between those nodes.\n\n    See Also\n    --------\n    pagerank, pagerank_scipy, google_matrix\n\n    References\n    ----------\n    .. [1] A. Langville and C. Meyer,\n       \"A survey of eigenvector methods of web information retrieval.\"\n       http://citeseer.ist.psu.edu/713792.html\n    .. [2] Page, Lawrence; Brin, Sergey; Motwani, Rajeev and Winograd, Terry,\n       The PageRank citation ranking: Bringing order to the Web. 1999\n       http://dbpubs.stanford.edu:8090/pub/showDoc.Fulltext?lang=en&doc=1999-66&format=pdf\n    ",
            "n_words": 344,
            "vocab_size": 202,
            "n_whitespaces": 556,
            "language": "en"
        }
    },
    {
        "id": 269365,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/applications/densenet.py",
        "file_name": "densenet.py",
        "fun_name": "decode_predictions",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def decode_predictions(preds, top=5):\n    return imagenet_utils.decode_predictions(preds, top=top)\n\n\npreprocess_input.__doc__ = imagenet_utils.PREPROCESS_INPUT_DOC.format(\n    mode=\"\",\n    ret=imagenet_utils.PREPROCESS_INPUT_RET_DOC_TORCH,\n    error=imagenet_utils.PREPROCESS_INPUT_ERROR_DOC,\n)\ndecode_predictions.__doc__ = imagenet_utils.decode_predictions.__doc__\n\nDOC = \n\nsetattr(DenseNet121, \"__doc__\", DenseNet121.__doc__ + DOC)\nsetattr(DenseNet169, \"__doc__\", DenseNet169.__doc__ + DOC)\nsetattr(DenseNet201, \"__doc__\", DenseNet201.__doc__ + DOC)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 38,
        "n_words": 33,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 149,
        "n_identifiers": 18,
        "d_id": 80037,
        "documentation": {
            "docstring": "\n\n  Reference:\n  - [Densely Connected Convolutional Networks](\n      https://arxiv.org/abs/1608.06993) (CVPR 2017)\n\n  Optionally loads weights pre-trained on ImageNet.\n  Note that the data format convention used by the model is\n  the one specified in your Keras config at `~/.keras/keras.json`.\n\n  Note: each Keras Application expects a specific kind of input preprocessing.\n  For DenseNet, call `tf.keras.applications.densenet.preprocess_input` on your\n  inputs before passing them to the model.\n\n  Args:\n    include_top: whether to include the fully-connected\n      layer at the top of the network.\n    weights: one of `None` (random initialization),\n      'imagenet' (pre-training on ImageNet),\n      or the path to the weights file to be loaded.\n    input_tensor: optional Keras tensor (i.e. output of `layers.Input()`)\n      to use as image input for the model.\n    input_shape: optional shape tuple, only to be specified\n      if `include_top` is False (otherwise the input shape\n      has to be `(224, 224, 3)` (with `'channels_last'` data format)\n      or `(3, 224, 224)` (with `'channels_first'` data format).\n      It should have exactly 3 inputs channels,\n      and width and height should be no smaller than 32.\n      E.g. `(200, 200, 3)` would be one valid value.\n    pooling: Optional pooling mode for feature extraction\n      when `include_top` is `False`.\n      - `None` means that the output of the model will be\n          the 4D tensor output of the\n          last convolutional block.\n      - `avg` means that global average pooling\n          will be applied to the output of the\n          last convolutional block, and thus\n          the output of the model will be a 2D tensor.\n      - `max` means that global max pooling will\n          be applied.\n    classes: optional number of classes to classify images\n      into, only to be specified if `include_top` is True, and\n      if no `weights` argument is specified.\n    classifier_activation: A `str` or callable. The activation function to use\n      on the \"top\" layer. Ignored unless `include_top=True`. Set\n      `classifier_activation=None` to return the logits of the \"top\" layer.\n      When loading pretrained weights, `classifier_activation` can only\n      be `None` or `\"softmax\"`.\n\n  Returns:\n    A Keras model instance.\n",
            "n_words": 307,
            "vocab_size": 181,
            "n_whitespaces": 500,
            "language": "en"
        }
    },
    {
        "id": 320280,
        "commit_id": "4aa318598fd0dc6c5d4e08dd2a13e7bf614511ec",
        "repo": "paperless-ngx",
        "path": "src/paperless_mail/tests/test_parsers.py",
        "file_name": "test_parsers.py",
        "fun_name": "test_tika_parse_unreachable",
        "commit_message": "add test comments",
        "code": "def test_tika_parse_unreachable(self):\n        \n        html = '<html><head><meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\"></head><body><p>Some Text</p></body></html>'\n\n        # Check if exception is raised when Tika cannot be reached.\n        self.parser.tika_server = \"\"\n        self.assertRaises(ParseError, self.parser.tika_parse, html)\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 61,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 30,
        "n_ast_nodes": 54,
        "n_identifiers": 8,
        "d_id": 117110,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - Fresh start\n        WHEN:\n            - tika parsing is called but tika is not available\n        THEN:\n            - a ParseError Exception is thrown\n        ",
            "n_words": 22,
            "vocab_size": 17,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 117210,
        "commit_id": "7c02e15aa403a4ca1fa34489dd2df9136d6c961c",
        "repo": "mindsdb",
        "path": "tests/integration_tests/flows/test_mysql_api.py",
        "file_name": "test_mysql_api.py",
        "fun_name": "test_train_model_from_files",
        "commit_message": "Projects structure (#3532)\n\nProjects structure",
        "code": "def test_train_model_from_files(self):\n        df = pd.DataFrame({\n            'x1': [x for x in range(100, 210)] + [x for x in range(100, 210)],\n            'x2': [x * 2 for x in range(100, 210)] + [x * 3 for x in range(100, 210)],\n            'y': [x * 3 for x in range(100, 210)] + [x * 2 for x in range(100, 210)]\n        })\n        file_predictor_name = \"predictor_from_file\"\n        self.upload_ds(df, self.file_datasource_name)\n        self.verify_file_ds(self.file_datasource_name)\n\n        _query = f\n        self.query(_query)\n        self.check_predictor_readiness(file_predictor_name)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 155,
        "n_words": 67,
        "vocab_size": 29,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 142,
        "n_ast_nodes": 228,
        "n_identifiers": 14,
        "d_id": 25923,
        "documentation": {
            "docstring": "\n            CREATE MODEL {file_predictor_name}\n            from files (select * from {self.file_datasource_name})\n            predict y;\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 320858,
        "commit_id": "265b018c172f8c1f6d9e7f8850256363f0629f82",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/commands.py",
        "file_name": "commands.py",
        "fun_name": "_search_cb",
        "commit_message": "Add a SearchMatch helper class",
        "code": "def _search_cb(self, found, *, tab, old_match, options, text, prev):\n        \n        # :search/:search-next without reverse -> down\n        # :search/:search-next    with reverse -> up\n        # :search-prev         without reverse -> up\n        # :search-prev            with reverse -> down\n        going_up = options['reverse'] ^ prev\n\n        if found:\n            if not config.val.search.wrap_messages:\n                return\n\n            # Check if the match count change is opposite to the search direction\n            if old_match.current > 0:\n                if not going_up:\n                    if old_match.current > tab.search.match.current:\n                        message.info(\"Search hit BOTTOM, continuing at TOP\",\n                                     replace=\"search-hit-msg\")\n                    elif old_match.current == tab.search.match.current:\n                        message.info(\"Search hit BOTTOM\", replace=\"search-hit-msg\")\n                elif going_up:\n                    if old_match.current < tab.search.match.current:\n                        message.info(\"Search hit TOP, continuing at BOTTOM\",\n                                     replace=\"search-hit-msg\")\n                    elif old_match.current == tab.search.match.current:\n                        message.info(\"Search hit TOP\", replace=\"search-hit-msg\")\n        else:\n            message.warning(f\"Text '{text}' not found on page!\",\n                            replace='find-in-page')\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 546,
        "n_words": 112,
        "vocab_size": 62,
        "complexity": 10,
        "nloc": 21,
        "token_counts": 161,
        "n_ast_nodes": 276,
        "n_identifiers": 19,
        "d_id": 117399,
        "documentation": {
            "docstring": "Callback called from search/search_next/search_prev.\n\n        Args:\n            found: Whether the text was found.\n            tab: The AbstractTab in which the search was made.\n            old_match: The previously active search match before the search was\n                       performed.\n            options: The options (dict) the search was made with.\n            text: The text searched for.\n            prev: Whether we're searching backwards (i.e. :search-prev)\n        ",
            "n_words": 52,
            "vocab_size": 38,
            "n_whitespaces": 154,
            "language": "en"
        }
    },
    {
        "id": 217383,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/fractions.py",
        "file_name": "fractions.py",
        "fun_name": "from_decimal",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def from_decimal(cls, dec):\n        \n        from decimal import Decimal\n        if isinstance(dec, numbers.Integral):\n            dec = Decimal(int(dec))\n        elif not isinstance(dec, Decimal):\n            raise TypeError(\n                \"%s.from_decimal() only takes Decimals, not %r (%s)\" %\n                (cls.__name__, dec, type(dec).__name__))\n        return cls(*dec.as_integer_ratio())\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 119,
        "n_words": 32,
        "vocab_size": 30,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 70,
        "n_ast_nodes": 114,
        "n_identifiers": 13,
        "d_id": 54739,
        "documentation": {
            "docstring": "Converts a finite Decimal instance to a rational number, exactly.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 244103,
        "commit_id": "0932ab787d58eead15b5f823fbcca5351ceb90f7",
        "repo": "mmdetection",
        "path": "mmdet/models/plugins/pixel_decoder.py",
        "file_name": "pixel_decoder.py",
        "fun_name": "forward",
        "commit_message": "add msdeformattn pixel decoder (#7466)\n\nfix typo\r\n\r\nrm img_metas\r\n\r\nrename in pixel_decoder\r\n\r\nupdate comments\r\n\r\nrename\r\n\r\nfix typo\r\n\r\ngenerae points with MlvlPointGenerator",
        "code": "def forward(self, feats, img_metas):\n        \n        y = self.last_feat_conv(feats[-1])\n        for i in range(self.num_inputs - 2, -1, -1):\n            x = feats[i]\n            cur_feat = self.lateral_convs[i](x)\n            y = cur_feat + \\\n                F.interpolate(y, size=cur_feat.shape[-2:], mode='nearest')\n            y = self.output_convs[i](y)\n\n        mask_feature = self.mask_feature(y)\n        memory = feats[-1]\n        return mask_feature, memory\n\n\n@PLUGIN_LAYERS.register_module()",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "@PLUGIN_LAYERS.register_module()",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 142,
        "n_words": 42,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 113,
        "n_ast_nodes": 186,
        "n_identifiers": 22,
        "d_id": 70240,
        "documentation": {
            "docstring": "\n        Args:\n            feats (list[Tensor]): Feature maps of each level. Each has\n                shape of (batch_size, c, h, w).\n            img_metas (list[dict]): List of image information. Pass in\n                for creating more accurate padding mask. Not used here.\n\n        Returns:\n            tuple: a tuple containing the following:\n                - mask_feature (Tensor): Shape (batch_size, c, h, w).\n                - memory (Tensor): Output of last stage of backbone.\\\n                        Shape (batch_size, c, h, w).\n        ",
            "n_words": 62,
            "vocab_size": 47,
            "n_whitespaces": 200,
            "language": "en"
        }
    },
    {
        "id": 301136,
        "commit_id": "3f8c896cb20526ef59e285b1f0eeb9b4e734efee",
        "repo": "core",
        "path": "tests/components/google/test_config_flow.py",
        "file_name": "test_config_flow.py",
        "fun_name": "primary_calendar_error",
        "commit_message": "Set user friendly name for Google Calendar config entry (#72243)\n\n* Set user friendly name for Google Calendar config entry\r\n\r\n* Add a new auth implementation for use during the config flow",
        "code": "async def primary_calendar_error() -> ClientError | None:\n    \n    return None\n\n\n@pytest.fixture(autouse=True)",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(autouse=True)",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 15,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 11,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 99984,
        "documentation": {
            "docstring": "Fixture for tests to inject an error during calendar lookup.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 137593,
        "commit_id": "98fef7732852cdb3e9377cd87c1ee1085b894928",
        "repo": "ray",
        "path": "python/ray/tests/test_runtime_env.py",
        "file_name": "test_runtime_env.py",
        "fun_name": "test_get_release_wheel_url",
        "commit_message": "[runtime env] Support python 3.10 for runtime_env conda (#30970)\n\nSigned-off-by: Archit Kulkarni <architkulkarni@users.noreply.github.com>\r\n\r\nconda environments are isolated, so when runtime_env sets up a conda environment it must download the Ray wheel into the conda environment. It must download the wheel that matches the current Python and Ray version running, otherwise there will be incompatibility issues between the workers that use this runtime_env and the other workers and Ray processes.\r\n\r\nThis PR updates the wheel name format logic to support Python 3.10.",
        "code": "def test_get_release_wheel_url():\n    \n    # This should be a commit for which wheels have already been built for\n    # all platforms and python versions at\n    # `s3://ray-wheels/releases/2.2.0/<commit>/`.\n    test_commits = {\"2.2.0\": \"b6af0887ee5f2e460202133791ad941a41f15beb\"}\n    for sys_platform in [\"darwin\", \"linux\", \"win32\"]:\n        for py_version in ray_constants.RUNTIME_ENV_CONDA_PY_VERSIONS:\n            for version, commit in test_commits.items():\n                if sys_platform == \"win32\" and py_version == (3, 6):\n                    # Windows wheels are not built for py3.6 anymore\n                    continue\n                url = get_release_wheel_url(commit, sys_platform, version, py_version)\n                assert requests.head(url).status_code == 200, url\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 193,
        "n_words": 74,
        "vocab_size": 53,
        "complexity": 6,
        "nloc": 9,
        "token_counts": 80,
        "n_ast_nodes": 136,
        "n_identifiers": 14,
        "d_id": 31197,
        "documentation": {
            "docstring": "Test the code that generates the filenames of the `release` branch wheels.",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 45563,
        "commit_id": "3aebb21c523c0eea0d4a1518d502ff95fd98011b",
        "repo": "airflow",
        "path": "airflow/models/connection.py",
        "file_name": "connection.py",
        "fun_name": "_validate_extra",
        "commit_message": "Deprecate non-JSON conn.extra (#21816)\n\nConnection extra field is generally assumed to be JSON but we don't actually require it.  Here we deprecate non-JSON extra so that in 3.0 we can require it.  Further, we require that it not just be any json but must also parse as dict, because a string value such as '\"hi\"' or '[1,2,3]' is json, but a very bad practice.",
        "code": "def _validate_extra(extra, conn_id) -> None:\n        \n        if extra is None:\n            return None\n        try:\n            extra_parsed = json.loads(extra)\n            if not isinstance(extra_parsed, dict):\n                warnings.warn(\n                    \"Encountered JSON value in `extra` which does not parse as a dictionary in \"\n                    f\"connection {conn_id!r}. From Airflow 3.0, the `extra` field must contain a JSON \"\n                    \"representation of a Python dict.\",\n                    DeprecationWarning,\n                    stacklevel=3,\n                )\n        except json.JSONDecodeError:\n            warnings.warn(\n                f\"Encountered non-JSON in `extra` field for connection {conn_id!r}. Support for \"\n                \"non-JSON `extra` will be removed in Airflow 3.0\",\n                DeprecationWarning,\n                stacklevel=2,\n            )\n        return None\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 357,
        "n_words": 82,
        "vocab_size": 59,
        "complexity": 4,
        "nloc": 25,
        "token_counts": 74,
        "n_ast_nodes": 132,
        "n_identifiers": 13,
        "d_id": 8648,
        "documentation": {
            "docstring": "\n        Here we verify that ``extra`` is a JSON-encoded Python dict.  From Airflow 3.0, we should no\n        longer suppress these errors but raise instead.\n        ",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 122898,
        "commit_id": "9f811ba54d16d1acc4c0950dd3608d0b59d1af82",
        "repo": "jax",
        "path": "jax/_src/third_party/scipy/betaln.py",
        "file_name": "betaln.py",
        "fun_name": "algdiv",
        "commit_message": "Address drastic slowdown in mypy runtime",
        "code": "def algdiv(a, b):\n    \n    c0 = 0.833333333333333e-01\n    c1 = -0.277777777760991e-02\n    c2 = 0.793650666825390e-03\n    c3 = -0.595202931351870e-03\n    c4 = 0.837308034031215e-03\n    c5 = -0.165322962780713e-02\n    h = a / b\n    c = h / (1 + h)\n    x = h / (1 + h)\n    d = b + (a - 0.5)\n    # Set sN = (1 - x**n)/(1 - x)\n    x2 = x * x\n    s3 = 1.0 + (x + x2)\n    s5 = 1.0 + (x + x2 * s3)\n    s7 = 1.0 + (x + x2 * s5)\n    s9 = 1.0 + (x + x2 * s7)\n    s11 = 1.0 + (x + x2 * s9)\n    # Set w = del(b) - del(a + b)\n    # where del(x) is defined by ln(gamma(x)) = (x - 0.5)*ln(x) - x + 0.5*ln(2*pi) + del(x)\n    t = (1.0 / b) ** 2\n    w = ((((c5 * s11 * t + c4 * s9) * t + c3 * s7) * t + c2 * s5) * t + c1 * s3) * t + c0\n    w = w * (c / b)\n    # Combine the results\n    u = d * lax.log1p(a / b)\n    v = a * (lax.log(b) - 1.0)\n    return jnp.where(u <= v, (w - v) - u, (w - u) - v)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 290,
        "n_words": 209,
        "vocab_size": 82,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 269,
        "n_ast_nodes": 362,
        "n_identifiers": 28,
        "d_id": 27264,
        "documentation": {
            "docstring": "\n    Compute ``log(gamma(a))/log(gamma(a + b))`` when ``b >= 8``.\n\n    Derived from scipy's implmentation of `algdiv`_.\n\n    This differs from the scipy implementation in that it assumes a <= b\n    because recomputing ``a, b = jnp.minimum(a, b), jnp.maximum(a, b)`` might\n    be expensive and this is only called by ``betaln``.\n\n    .. _algdiv:\n        https://github.com/scipy/scipy/blob/c89dfc2b90d993f2a8174e57e0cbc8fbe6f3ee19/scipy/special/cdflib/algdiv.f\n    ",
            "n_words": 49,
            "vocab_size": 47,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 168150,
        "commit_id": "6ba2a67556526db2e5b0b60a566b5f2039cf4a46",
        "repo": "pandas",
        "path": "pandas/core/indexes/frozen.py",
        "file_name": "frozen.py",
        "fun_name": "_disabled",
        "commit_message": "TYP: annotate functions that always error with NoReturn (#48002)",
        "code": "def _disabled(self, *args, **kwargs) -> NoReturn:\n        \n        raise TypeError(f\"'{type(self).__name__}' does not support mutable operations.\")\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 27,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 20,
        "n_ast_nodes": 46,
        "n_identifiers": 8,
        "d_id": 40216,
        "documentation": {
            "docstring": "\n        This method will not function because object is immutable.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 100389,
        "commit_id": "c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf",
        "repo": "faceswap",
        "path": "plugins/train/trainer/_base.py",
        "file_name": "_base.py",
        "fun_name": "_set_preview_feed",
        "commit_message": "Update code to support Tensorflow versions up to 2.8 (#1213)\n\n* Update maximum tf version in setup + requirements\r\n\r\n* - bump max version of tf version in launcher\r\n- standardise tf version check\r\n\r\n* update keras get_custom_objects  for tf>2.6\r\n\r\n* bugfix: force black text in GUI file dialogs (linux)\r\n\r\n* dssim loss - Move to stock tf.ssim function\r\n\r\n* Update optimizer imports for compatibility\r\n\r\n* fix logging for tf2.8\r\n\r\n* Fix GUI graphing for TF2.8\r\n\r\n* update tests\r\n\r\n* bump requirements.txt versions\r\n\r\n* Remove limit on nvidia-ml-py\r\n\r\n* Graphing bugfixes\r\n  - Prevent live graph from displaying if data not yet available\r\n\r\n* bugfix: Live graph. Collect loss labels correctly\r\n\r\n* fix: live graph - swallow inconsistent loss errors\r\n\r\n* Bugfix: Prevent live graph from clearing during training\r\n\r\n* Fix graphing for AMD",
        "code": "def _set_preview_feed(self):\n        \n        retval = {}\n        for idx, side in enumerate((\"a\", \"b\")):\n            logger.debug(\"Setting preview feed: (side: '%s')\", side)\n            preview_images = self._config.get(\"preview_images\", 14)\n            preview_images = min(max(preview_images, 2), 16)\n            batchsize = min(len(self._images[side]), preview_images)\n            retval[side] = self._load_generator(idx).minibatch_ab(self._images[side],\n                                                                  batchsize,\n                                                                  side,\n                                                                  do_shuffle=True,\n                                                                  is_preview=True)\n        logger.debug(\"Set preview feed. Batchsize: %s\", batchsize)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 395,
        "n_words": 45,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 116,
        "n_ast_nodes": 184,
        "n_identifiers": 20,
        "d_id": 19874,
        "documentation": {
            "docstring": " Set the preview feed for this feeder.\n\n        Creates a generator from :class:`lib.training_data.TrainingDataGenerator` specifically\n        for previews for the feeder.\n\n        Returns\n        -------\n        dict\n            The side (\"a\" or \"b\") as key, :class:`~lib.training_data.TrainingDataGenerator` as\n            value.\n        ",
            "n_words": 31,
            "vocab_size": 26,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 118611,
        "commit_id": "704eab3478cf69847825b23dabf15813a8ac9fa2",
        "repo": "streamlit",
        "path": "lib/tests/streamlit/forward_msg_queue_test.py",
        "file_name": "forward_msg_queue_test.py",
        "fun_name": "test_multiple_containers",
        "commit_message": "Rename and refactor `Report` machinery (#4141)\n\nThis refactor renames (almost) everything related to the outdated \"report\" concept with more precise concepts that we use throughout our code, primarily \"script run\", \"session\", and \"app\".",
        "code": "def test_multiple_containers(self):\n        \n        rq = ForwardMsgQueue()\n        self.assertTrue(rq.is_empty())\n\n        rq.enqueue(NEW_SESSION_MSG)\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 114,
        "n_ast_nodes": 49,
        "n_identifiers": 8,
        "d_id": 26316,
        "documentation": {
            "docstring": "Deltas should only be coalesced if they're in the same container",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 124273,
        "commit_id": "89b0b82c13568254d179e63cb1a43b95fe632bd9",
        "repo": "ray",
        "path": "python/ray/serve/tests/test_json_serde.py",
        "file_name": "test_json_serde.py",
        "fun_name": "test_simple_class_node_json_serde",
        "commit_message": "[Deployment Graph] Move `Deployment` creation outside to build function (#26129)",
        "code": "def test_simple_class_node_json_serde(serve_instance):\n    \n    hello_actor = ClassHello.bind()\n    original_dag_node = hello_actor.hello.bind()\n    _test_deployment_json_serde_helper(\n        original_dag_node,\n        expected_num_deployments=1,\n    )\n\n    model_actor = Model.bind(1)\n    original_dag_node = model_actor.forward.bind(1)\n    _test_deployment_json_serde_helper(\n        original_dag_node,\n        expected_num_deployments=1,\n    )\n\n    model_actor = Model.bind(1, ratio=0.5)\n    original_dag_node = model_actor.forward.bind(1)\n    _test_deployment_json_serde_helper(\n        original_dag_node,\n        expected_num_deployments=1,\n    )\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 114,
        "n_words": 33,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 91,
        "n_ast_nodes": 142,
        "n_identifiers": 13,
        "d_id": 27557,
        "documentation": {
            "docstring": "\n    Test the following behavior\n        1) Ray DAG node can go through full JSON serde cycle\n        2) Ray DAG node and deserialized DAG node produces same actor instances\n            with same method call output\n        3) Ray DAG node can go through multiple rounds of JSON serde and still\n            provides the same value as if it's only JSON serde once\n    Against following test cases\n        - Simple class with no args\n        - Simple class with only args, all primitive types\n        - Simple class with args + kwargs, all primitive types\n        - Simple chain of class method calls, all primitive types\n    ",
            "n_words": 96,
            "vocab_size": 54,
            "n_whitespaces": 177,
            "language": "en"
        }
    },
    {
        "id": 322359,
        "commit_id": "487162262196bead8d9b4c2306f313b8f64edf9b",
        "repo": "PaddleNLP",
        "path": "examples/text_summarization/prophetnet/evaluate/cnndm/bs_pyrouge.py",
        "file_name": "bs_pyrouge.py",
        "fun_name": "evaluate",
        "commit_message": "Add model Prohetnet (#1698)\n\n* add Prohetnet model\r\n\r\n* update prohetnet\r\n\r\n* update format\r\n\r\n* pre commit\r\n\r\n* add prophetnet example\r\n\r\n* update tokenizer.py,run_train.sh,train_prophetnet.py\r\n\r\n* remove evaluate/gigaword/__init__.py\r\n\r\nCo-authored-by: smallv0221 <33639025+smallv0221@users.noreply.github.com>",
        "code": "def evaluate(self, system_id=1, rouge_args=None):\n        \n        self.write_config(system_id=system_id)\n        options = self.__get_options(rouge_args)\n        command = [self._bin_path] + options\n        self.log.info(\"Running ROUGE with command {}\".format(\" \".join(command)))\n        rouge_output = check_output(command).decode(\"UTF-8\")\n        return rouge_output\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 73,
        "n_words": 24,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 70,
        "n_ast_nodes": 119,
        "n_identifiers": 16,
        "d_id": 118144,
        "documentation": {
            "docstring": "\n        Run ROUGE to evaluate the system summaries in system_dir against\n        the model summaries in model_dir. The summaries are assumed to\n        be in the one-sentence-per-line HTML format ROUGE understands.\n\n            system_id:  Optional system ID which will be printed in\n                        ROUGE's output.\n\n        Returns: Rouge output as string.\n\n        ",
            "n_words": 44,
            "vocab_size": 33,
            "n_whitespaces": 115,
            "language": "en"
        }
    },
    {
        "id": 209484,
        "commit_id": "e6eaa484b8fa3d10051e82f5a784fe8dedbd5592",
        "repo": "scapy",
        "path": "scapy/contrib/automotive/scanner/executor.py",
        "file_name": "executor.py",
        "fun_name": "execute_test_case",
        "commit_message": "Add assert to GMLAN Scanner to enforce fast fail on to many open TestSockets\n\nFix bugs in TestSocket\nFix bugs in the AutomotiveScanner execution_time handling\nSimplify test code for UDS_Scanner and reuse ObjectPipes to avoid mass\ncreation",
        "code": "def execute_test_case(self, test_case, kill_time=None):\n        # type: (AutomotiveTestCaseABC, Optional[float]) -> None\n        \n\n        test_case.pre_execute(\n            self.socket, self.target_state, self.configuration)\n\n        try:\n            test_case_kwargs = self.configuration[test_case.__class__.__name__]\n        except KeyError:\n            test_case_kwargs = dict()\n\n        if kill_time:\n            max_execution_time = max(int(kill_time - time.time()), 5)\n            cur_execution_time = test_case_kwargs.get(\"execution_time\", 1200)\n            test_case_kwargs[\"execution_time\"] = min(max_execution_time,\n                                                     cur_execution_time)\n\n        log_interactive.debug(\"[i] Execute test_case %s with args %s\",\n                              test_case.__class__.__name__, test_case_kwargs)\n\n        test_case.execute(self.socket, self.target_state, **test_case_kwargs)\n        test_case.post_execute(\n            self.socket, self.target_state, self.configuration)\n\n        self.check_new_states(test_case)\n        self.check_new_testcases(test_case)\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 292,
        "n_words": 57,
        "vocab_size": 48,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 148,
        "n_ast_nodes": 234,
        "n_identifiers": 26,
        "d_id": 52688,
        "documentation": {
            "docstring": "\n        This function ensures the correct execution of a testcase, including\n        the pre_execute, execute and post_execute.\n        Finally the testcase is asked if a new edge or a new testcase was\n        generated.\n\n        :param test_case: A test case to be executed\n        :param kill_time: If set, this defines the maximum execution time for\n                          the current test_case\n        :return: None\n        ",
            "n_words": 54,
            "vocab_size": 44,
            "n_whitespaces": 136,
            "language": "en"
        }
    },
    {
        "id": 107061,
        "commit_id": "da31ed386482845629a8505f81810ddb341514fb",
        "repo": "matplotlib",
        "path": "lib/matplotlib/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "update",
        "commit_message": "Fix drawing animated artists changed in selector callback",
        "code": "def update(self):\n        \n        if not self.ax.get_visible() or self.ax.figure._cachedRenderer is None:\n            return False\n        if self.useblit:\n            if self.background is not None:\n                self.canvas.restore_region(self.background)\n            else:\n                self.update_background(None)\n            for artist in self.artists + self._get_animated_artists():\n                if artist.stale:\n                    self.ax.draw_artist(artist)\n            self.canvas.blit(self.ax.bbox)\n        else:\n            self.canvas.draw_idle()\n        return False\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 200,
        "n_words": 35,
        "vocab_size": 26,
        "complexity": 7,
        "nloc": 15,
        "token_counts": 108,
        "n_ast_nodes": 177,
        "n_identifiers": 19,
        "d_id": 22575,
        "documentation": {
            "docstring": "Draw using blit() or draw_idle(), depending on ``self.useblit``.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 152959,
        "commit_id": "3c740dbfcdd69ddc3ab45a42be996e5c61104342",
        "repo": "modin",
        "path": "modin/core/dataframe/pandas/dataframe/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "synchronize_labels",
        "commit_message": "FEAT-#3111: Ensure relabeling Modin Frame does not lose partition shape (#3662)\n\nCo-authored-by: Devin Petersohn <devin.petersohn@gmail.com>\r\nSigned-off-by: Naren Krishna <naren@ponder.io>",
        "code": "def synchronize_labels(self, axis=None):\n        \n        if axis is None:\n            self._deferred_index = True\n            self._deferred_column = True\n        elif axis == 0:\n            self._deferred_index = True\n        else:\n            self._deferred_column = True\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 96,
        "n_words": 24,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 42,
        "n_ast_nodes": 70,
        "n_identifiers": 5,
        "d_id": 35205,
        "documentation": {
            "docstring": "\n        Set the deferred axes variables for the ``PandasDataframe``.\n\n        Parameters\n        ----------\n        axis : int, default: None\n            The deferred axis.\n            0 for the index, 1 for the columns.\n        ",
            "n_words": 26,
            "vocab_size": 20,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 181817,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/base.py",
        "file_name": "base.py",
        "fun_name": "_impute_values",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def _impute_values(self, features):\n        \n        if self.verbosity > 1:\n            print(\"Imputing missing values in feature set\")\n\n        if self._fitted_imputer is None:\n            self._fitted_imputer = SimpleImputer(strategy=\"median\")\n            self._fitted_imputer.fit(features)\n\n        return self._fitted_imputer.transform(features)\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 84,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 53,
        "n_ast_nodes": 91,
        "n_identifiers": 10,
        "d_id": 43601,
        "documentation": {
            "docstring": "Impute missing values in a feature set.\n\n        Parameters\n        ----------\n        features: array-like {n_samples, n_features}\n            A feature matrix\n\n        Returns\n        -------\n        array-like {n_samples, n_features}\n        ",
            "n_words": 21,
            "vocab_size": 17,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 122415,
        "commit_id": "2416d154355f19e77b5c1ddf1de1f8552e4a98ad",
        "repo": "jax",
        "path": "jax/_src/third_party/numpy/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_multi_dot_three",
        "commit_message": "Call _check_arraylike for jnp.linalg & jnp.fft functions",
        "code": "def _multi_dot_three(A, B, C, precision):\n  \n  a0, a1b0 = A.shape\n  b1c0, c1 = C.shape\n  # cost1 = cost((AB)C) = a0*a1b0*b1c0 + a0*b1c0*c1\n  cost1 = a0 * b1c0 * (a1b0 + c1)\n  # cost2 = cost(A(BC)) = a1b0*b1c0*c1 + a0*a1b0*c1\n  cost2 = a1b0 * c1 * (a0 + b1c0)\n\n  if cost1 < cost2:\n    return jnp.dot(jnp.dot(A, B, precision=precision), C, precision=precision)\n  else:\n    return jnp.dot(A, jnp.dot(B, C, precision=precision), precision=precision)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 79,
        "n_words": 64,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 103,
        "n_ast_nodes": 155,
        "n_identifiers": 14,
        "d_id": 27182,
        "documentation": {
            "docstring": "\n  Find the best order for three arrays and do the multiplication.\n  For three arguments `_multi_dot_three` is approximately 15 times faster\n  than `_multi_dot_matrix_chain_order`\n  ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 135845,
        "commit_id": "2ed09c54459cc3f74e2dab13406018698559856c",
        "repo": "ray",
        "path": "rllib/policy/tests/test_compute_log_likelihoods.py",
        "file_name": "test_compute_log_likelihoods.py",
        "fun_name": "test_dqn",
        "commit_message": "[RLlib] Move all config validation logic into AlgorithmConfig classes. (#29854)",
        "code": "def test_dqn(self):\n        \n        config = dqn.DQNConfig()\n        # Soft-Q for DQN.\n        config.exploration(exploration_config={\"type\": \"SoftQ\", \"temperature\": 0.5})\n        config.debugging(seed=42)\n        do_test_log_likelihood(dqn.DQN, config)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 58,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 81,
        "n_identifiers": 11,
        "d_id": 30746,
        "documentation": {
            "docstring": "Tests, whether DQN correctly computes logp in soft-q mode.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 223448,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/doctest.py",
        "file_name": "doctest.py",
        "fun_name": "_extract_future_flags",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _extract_future_flags(globs):\n    \n    flags = 0\n    for fname in __future__.all_feature_names:\n        feature = globs.get(fname, None)\n        if feature is getattr(__future__, fname):\n            flags |= feature.compiler_flag\n    return flags\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 60,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 43,
        "n_ast_nodes": 69,
        "n_identifiers": 10,
        "d_id": 56906,
        "documentation": {
            "docstring": "\n    Return the compiler-flags associated with the future features that\n    have been imported into the given namespace (globs).\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 72341,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_send_html_email",
        "commit_message": "Reformat with black",
        "code": "def test_send_html_email(self):\n        \n\n        send_mail(\n            \"Test HTML subject\",\n            \"TEXT content\",\n            [\"has.html@email.com\"],\n            html_message=\"<h2>Test HTML content</h2>\",\n        )\n        send_mail(\"Test TEXT subject\", \"TEXT content\", [\"mr.plain.text@email.com\"])\n\n        # Check that the emails were sent\n        self.assertEqual(len(mail.outbox), 2)\n\n        # check that the first email is the HTML email\n        email_message = mail.outbox[0]\n        self.assertEqual(email_message.subject, \"Test HTML subject\")\n        self.assertEqual(\n            email_message.alternatives, [(\"<h2>Test HTML content</h2>\", \"text/html\")]\n        )\n        self.assertEqual(\n            email_message.body, \"TEXT content\"\n        )  # note: plain text will always be added to body, even with alternatives\n        self.assertEqual(email_message.to, [\"has.html@email.com\"])\n\n        # confirm that without html_message kwarg we do not get 'alternatives'\n        email_message = mail.outbox[1]\n        self.assertEqual(email_message.subject, \"Test TEXT subject\")\n        self.assertEqual(email_message.alternatives, [])\n        self.assertEqual(email_message.body, \"TEXT content\")\n        self.assertEqual(email_message.to, [\"mr.plain.text@email.com\"])\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 304,
        "n_words": 97,
        "vocab_size": 67,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 151,
        "n_ast_nodes": 261,
        "n_identifiers": 13,
        "d_id": 15875,
        "documentation": {
            "docstring": "Test that the kwarg 'html_message' works as expected on send_mail by creating 'alternatives' on the EmailMessage object",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 68856,
        "commit_id": "74a782d81d8f8c4a4d9214a9c06377e5e6e464dd",
        "repo": "erpnext",
        "path": "erpnext/selling/doctype/quotation/quotation.py",
        "file_name": "quotation.py",
        "fun_name": "set_expired_status",
        "commit_message": "refactor: DB independent quoting and truthy/falsy values (#31358)\n\n* refactor: DB independent quoting and truthy/falsy values\r\n\r\n* style: reformat to black spec\r\n\r\n* fix: ifnull -> coalesce\r\n\r\n* fix: coalesce -> Coalesce\r\n\r\n* fix: revert pypika comparison\r\n\r\n* refactor: convert queries to QB\r\n\r\n* fix: incorrect value types for query\r\n\r\n`=` query makes no sense with list of values\r\n\r\n* fix: remove warehouse docstatus condition\r\n\r\n* fix: keep using base rate as rate\r\n\r\nCo-authored-by: Ankush Menat <ankush@frappe.io>",
        "code": "def set_expired_status():\n\t# filter out submitted non expired quotations whose validity has been ended\n\tcond = \"`tabQuotation`.docstatus = 1 and `tabQuotation`.status != 'Expired' and `tabQuotation`.valid_till < %s\"\n\t# check if those QUO have SO against it\n\tso_against_quo = \n\n\t# if not exists any SO, set status as Expired\n\tfrappe.db.multisql(\n\t\t{\n\t\t\t\"mariadb\": .format(\n\t\t\t\tcond=cond, so_against_quo=so_against_quo\n\t\t\t),\n\t\t\t\"postgres\": .format(\n\t\t\t\tcond=cond, so_against_quo=so_against_quo\n\t\t\t),\n\t\t},\n\t\t(nowdate()),\n\t)\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 47,
        "n_words": 64,
        "vocab_size": 54,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 56,
        "n_ast_nodes": 111,
        "n_identifiers": 9,
        "d_id": 14922,
        "documentation": {
            "docstring": "\n\t\tSELECT\n\t\t\tso.name FROM `tabSales Order` so, `tabSales Order Item` so_item\n\t\tWHERE\n\t\t\tso_item.docstatus = 1 and so.docstatus = 1\n\t\t\tand so_item.parent = so.name\n\t\t\tand so_item.prevdoc_docname = `tabQuotation`.nameUPDATE `tabQuotation`  SET `tabQuotation`.status = 'Expired' WHERE {cond} and not exists({so_against_quo})UPDATE `tabQuotation` SET status = 'Expired' FROM `tabSales Order`, `tabSales Order Item` WHERE {cond} and not exists({so_against_quo})",
            "n_words": 52,
            "vocab_size": 28,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 65117,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/general_ledger.py",
        "file_name": "general_ledger.py",
        "fun_name": "check_freezing_date",
        "commit_message": "style: format code with black",
        "code": "def check_freezing_date(posting_date, adv_adj=False):\n\t\n\tif not adv_adj:\n\t\tacc_frozen_upto = frappe.db.get_value(\"Accounts Settings\", None, \"acc_frozen_upto\")\n\t\tif acc_frozen_upto:\n\t\t\tfrozen_accounts_modifier = frappe.db.get_value(\n\t\t\t\t\"Accounts Settings\", None, \"frozen_accounts_modifier\"\n\t\t\t)\n\t\t\tif getdate(posting_date) <= getdate(acc_frozen_upto) and (\n\t\t\t\tfrozen_accounts_modifier not in frappe.get_roles() or frappe.session.user == \"Administrator\"\n\t\t\t):\n\t\t\t\tfrappe.throw(\n\t\t\t\t\t_(\"You are not authorized to add or update entries before {0}\").format(\n\t\t\t\t\t\tformatdate(acc_frozen_upto)\n\t\t\t\t\t)\n\t\t\t\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 37,
        "n_words": 52,
        "vocab_size": 41,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 92,
        "n_ast_nodes": 157,
        "n_identifiers": 16,
        "d_id": 13794,
        "documentation": {
            "docstring": "\n\tNobody can do GL Entries where posting date is before freezing date\n\texcept authorized person\n\n\tAdministrator has all the roles so this check will be bypassed if any role is allowed to post\n\tHence stop admin to bypass if accounts are freezed\n\t",
            "n_words": 42,
            "vocab_size": 38,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 163539,
        "commit_id": "2e5b05e5773f02b653d66373787b493bc3cf3abc",
        "repo": "pandas",
        "path": "pandas/tests/test_expressions.py",
        "file_name": "test_expressions.py",
        "fun_name": "test_run_binary",
        "commit_message": "STYLE: use option_context almost always (#45407)",
        "code": "def test_run_binary(self, df, flex, comparison_op):\n        \n        arith = comparison_op.__name__\n        with option_context(\"compute.use_numexpr\", False):\n            other = df.copy() + 1\n\n        expr._MIN_ELEMENTS = 0\n        expr.set_test_mode(True)\n\n        result, expected = self.call_op(df, other, flex, arith)\n\n        used_numexpr = expr.get_test_result()\n        assert used_numexpr, \"Did not use numexpr as expected.\"\n        tm.assert_equal(expected, result)\n\n        # FIXME: dont leave commented-out\n        # series doesn't uses vec_compare instead of numexpr...\n        # for i in range(len(df.columns)):\n        #     binary_comp = other.iloc[:, i] + 1\n        #     self.run_binary(df.iloc[:, i], binary_comp, flex)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 187,
        "n_words": 70,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 80,
        "n_ast_nodes": 134,
        "n_identifiers": 20,
        "d_id": 39456,
        "documentation": {
            "docstring": "\n        tests solely that the result is the same whether or not numexpr is\n        enabled.  Need to test whether the function does the correct thing\n        elsewhere.\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 73961,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/templatetags/wagtailcore_tags.py",
        "file_name": "wagtailcore_tags.py",
        "fun_name": "wagtail_site",
        "commit_message": "Reformat with black",
        "code": "def wagtail_site(context):\n    \n    try:\n        request = context[\"request\"]\n    except KeyError:\n        return None\n\n    return Site.find_for_request(request=request)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 38,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 28,
        "n_ast_nodes": 50,
        "n_identifiers": 6,
        "d_id": 16194,
        "documentation": {
            "docstring": "\n    Returns the Site object for the given request\n    ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 128216,
        "commit_id": "18b38c5e23fc54bf0baf7e7dbfcb07640e81f5ef",
        "repo": "ray",
        "path": "python/ray/serve/schema.py",
        "file_name": "schema.py",
        "fun_name": "get_user_configured_option_names",
        "commit_message": "[Serve] Track user-configured options in Serve deployments (#28313)",
        "code": "def get_user_configured_option_names(self) -> Set[str]:\n        \n\n        return {\n            field for field, value in self.dict().items() if value is not DEFAULT.VALUE\n        }\n\n\n@PublicAPI(stability=\"beta\")",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@PublicAPI(stability=\"beta\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 50,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 36,
        "n_ast_nodes": 72,
        "n_identifiers": 12,
        "d_id": 28630,
        "documentation": {
            "docstring": "Get set of names for all user-configured options.\n\n        Any field not set to DEFAULT.VALUE is considered a user-configured option.\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 209791,
        "commit_id": "a2b7a28faff1db058dd22ce097a268e0ad5d1d33",
        "repo": "scapy",
        "path": "scapy/arch/windows/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "setmodulation",
        "commit_message": "[Hinty] Core typing: windows (#3684)\n\n* Core typing: windows\r\n\r\nCo-authored-by: Pierre <pierre@droids-corp.org>",
        "code": "def setmodulation(self, modu):\n        # type: (int) -> bool\n        \n        # According to https://nmap.org/npcap/guide/npcap-devguide.html#npcap-feature-dot11  # noqa: E501\n        self._check_npcap_requirement()\n        _modus = {\n            0: \"dsss\",\n            1: \"fhss\",\n            2: \"irbaseband\",\n            3: \"ofdm\",\n            4: \"hrdss\",\n            5: \"erp\",\n            6: \"ht\",\n            7: \"vht\",\n            8: \"ihv\",\n            9: \"mimo-ofdm\",\n            10: \"mimo-ofdm\",\n        }\n        m = _modus.get(modu, \"unknown\") if isinstance(modu, int) else modu\n        return self._npcap_set(\"modu\", str(m))\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 232,
        "n_words": 54,
        "vocab_size": 50,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 92,
        "n_ast_nodes": 159,
        "n_identifiers": 11,
        "d_id": 52781,
        "documentation": {
            "docstring": "Set the interface modulation. It can be:\n           - 0: dsss\n           - 1: fhss\n           - 2: irbaseband\n           - 3: ofdm\n           - 4: hrdss\n           - 5: erp\n           - 6: ht\n           - 7: vht\n           - 8: ihv\n           - 9: mimo-ofdm\n           - 10: mimo-ofdm\n           - the value directly\n        Only available with Npcap.",
            "n_words": 48,
            "vocab_size": 35,
            "n_whitespaces": 174,
            "language": "en"
        }
    },
    {
        "id": 60680,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/distributions/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "make_distribution_for_install_requirement",
        "commit_message": "upd; format",
        "code": "def make_distribution_for_install_requirement(install_req):\n    # type: (InstallRequirement) -> AbstractDistribution\n    \n    # Editable requirements will always be source distributions. They use the\n    # legacy logic until we create a modern standard for them.\n    if install_req.editable:\n        return SourceDistribution(install_req)\n\n    # If it's a wheel, it's a WheelDistribution\n    if install_req.is_wheel:\n        return WheelDistribution(install_req)\n\n    # Otherwise, a SourceDistribution\n    return SourceDistribution(install_req)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 92,
        "n_words": 51,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 31,
        "n_ast_nodes": 58,
        "n_identifiers": 6,
        "d_id": 12243,
        "documentation": {
            "docstring": "Returns a Distribution for the given InstallRequirement",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 46606,
        "commit_id": "b5a786b38148295c492da8ab731d5e2f6f86ccf7",
        "repo": "airflow",
        "path": "airflow/providers_manager.py",
        "file_name": "providers_manager.py",
        "fun_name": "_discover_all_providers_from_packages",
        "commit_message": "Suppress import errors for providers from sources (#22579)\n\nWhen we are running airflow locally with providers installed from sources, often many providers will be discovered which we haven't installed the deps for.  This generally results in a very large amount of traceback logging, which has a very negative effect on usefulness of terminal output.  Here we suppress this error logging for providers that are installed from sources.",
        "code": "def _discover_all_providers_from_packages(self) -> None:\n        \n        for entry_point, dist in entry_points_with_dist('apache_airflow_provider'):\n            package_name = dist.metadata['name']\n            if self._provider_dict.get(package_name) is not None:\n                continue\n            log.debug(\"Loading %s from package %s\", entry_point, package_name)\n            version = dist.version\n            provider_info = entry_point.load()()\n            self._provider_schema_validator.validate(provider_info)\n            provider_info_package_name = provider_info['package-name']\n            if package_name != provider_info_package_name:\n                raise Exception(\n                    f\"The package '{package_name}' from setuptools and \"\n                    f\"{provider_info_package_name} do not match. Please make sure they are aligned\"\n                )\n            if package_name not in self._provider_dict:\n                self._provider_dict[package_name] = ProviderInfo(version, provider_info, 'package')\n            else:\n                log.warning(\n                    \"The provider for package '%s' could not be registered from because providers for that \"\n                    \"package name have already been registered\",\n                    package_name,\n                )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 403,
        "n_words": 94,
        "vocab_size": 72,
        "complexity": 5,
        "nloc": 31,
        "token_counts": 126,
        "n_ast_nodes": 221,
        "n_identifiers": 20,
        "d_id": 8934,
        "documentation": {
            "docstring": "\n        Discovers all providers by scanning packages installed. The list of providers should be returned\n        via the 'apache_airflow_provider' entrypoint as a dictionary conforming to the\n        'airflow/provider_info.schema.json' schema. Note that the schema is different at runtime\n        than provider.yaml.schema.json. The development version of provider schema is more strict and changes\n        together with the code. The runtime version is more relaxed (allows for additional properties)\n        and verifies only the subset of fields that are needed at runtime.\n        ",
            "n_words": 73,
            "vocab_size": 55,
            "n_whitespaces": 123,
            "language": "en"
        }
    },
    {
        "id": 251191,
        "commit_id": "fdde9ba3b3caaa2654048cec0af07bfcc3a6a3f8",
        "repo": "mitmproxy",
        "path": "mitmproxy/addons/modifybody.py",
        "file_name": "modifybody.py",
        "fun_name": "load",
        "commit_message": "use Python 3.9+ typing",
        "code": "def load(self, loader):\n        loader.add_option(\n            \"modify_body\", Sequence[str], [],\n            \n        )\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 44,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 23,
        "n_ast_nodes": 37,
        "n_identifiers": 6,
        "d_id": 73629,
        "documentation": {
            "docstring": "\n            Replacement pattern of the form \"[/flow-filter]/regex/[@]replacement\", where\n            the separator can be any character. The @ allows to provide a file path that\n            is used to read the replacement string.\n            ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 140298,
        "commit_id": "eaed256d6863c529b8ada42514f7fba12d146f22",
        "repo": "ray",
        "path": "rllib/execution/parallel_requests.py",
        "file_name": "parallel_requests.py",
        "fun_name": "get_ready",
        "commit_message": "[RLlib] Async parallel execution manager. (#24423)",
        "code": "def get_ready(self) -> Dict[ActorHandle, List[Any]]:\n        \n        ready_requests_dict = defaultdict(list)\n        ready_requests, self._pending_remotes = ray.wait(\n            self._pending_remotes,\n            timeout=self._ray_wait_timeout_s,\n            num_returns=len(self._pending_remotes),\n        )\n        if not self._return_object_refs:\n            objs = ray.get(ready_requests)\n        else:\n            objs = ready_requests\n        for req, obj in zip(ready_requests, objs):\n            actor = self._pending_to_actor[req]\n            self._remote_requests_in_flight[actor].remove(req)\n            ready_requests_dict[actor].append(obj)\n            del self._pending_to_actor[req]\n        del ready_requests\n        return dict(ready_requests_dict)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 205,
        "n_words": 43,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 125,
        "n_ast_nodes": 193,
        "n_identifiers": 29,
        "d_id": 31919,
        "documentation": {
            "docstring": "Get results that are ready to be returned\n\n        Returns:\n            A dictionary of actor handles to lists of returns from tasks that were\n             previously submitted to this actor pool that are now ready to be returned.\n             If return_object_refs\n\n        ",
            "n_words": 37,
            "vocab_size": 27,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 222578,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/ccompiler.py",
        "file_name": "ccompiler.py",
        "fun_name": "set_link_objects",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def set_link_objects(self, objects):\n        \n        self.objects = objects[:]\n\n\n    # -- Private utility methods --------------------------------------\n    # (here for the convenience of subclasses)\n\n    # Helper method to prep compiler in subclass compile() methods\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 52,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 16,
        "n_ast_nodes": 31,
        "n_identifiers": 3,
        "d_id": 56651,
        "documentation": {
            "docstring": "Set the list of object files (or analogues) to be included in\n        every link to 'objects'.  This does not affect any standard object\n        files that the linker may include by default (such as system\n        libraries).\n        ",
            "n_words": 35,
            "vocab_size": 31,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 126155,
        "commit_id": "4ab97399cda80be1e146946c43d6fb2926248b28",
        "repo": "ray",
        "path": "dashboard/modules/serve/serve_agent.py",
        "file_name": "serve_agent.py",
        "fun_name": "get_serve_client",
        "commit_message": "[Serve] Only start Serve in the CLI through the `serve deploy` command (#27063)\n\nThese Serve CLI commands start Serve if it's not already running:\r\n\r\n* `serve deploy`\r\n* `serve config`\r\n* `serve status`\r\n* `serve shutdown`\r\n\r\n#27026 introduces the ability to specify a `host` and `port` in the Serve config file. However, once Serve starts running, changing these options requires tearing down the entire Serve application and relaunching it. This limitation is an issue because users can inadvertently start Serve by running one of the `GET`-based CLI commands (i.e. `serve config` or `serve status`) before running `serve deploy`.\r\n\r\nThis change makes `serve deploy` the only CLI command that can start a Serve application on a Ray cluster. The other commands have updated behavior when Serve is not yet running on the cluster.\r\n\r\n* `serve config`: prints an empty config body.\r\n\r\n```yaml\r\nimport_path: ''\r\nruntime_env: {}\r\ndeployments: []\r\n```\r\n\r\n* `serve status`: prints an empty status body, with a new `app_status` `status` value: `NOT_STARTED`.\r\n\r\n```yaml\r\napp_status:\r\n  status: NOT_STARTED\r\n  message: ''\r\n  deployment_timestamp: 0\r\ndeployment_statuses: []\r\n```\r\n\r\n* `serve shutdown`: performs a no-op.",
        "code": "def get_serve_client(self):\n        \n\n        from ray.serve.context import get_global_client\n        from ray.serve.exceptions import RayServeException\n\n        try:\n            return get_global_client(_health_check_controller=True)\n        except RayServeException:\n            logger.debug(\"There's no Serve app running on this Ray cluster.\")\n            return None\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 94,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 42,
        "n_ast_nodes": 70,
        "n_identifiers": 11,
        "d_id": 28078,
        "documentation": {
            "docstring": "Gets the ServeControllerClient to the this cluster's Serve app.\n\n        return: If Serve is running on this Ray cluster, returns a client to\n            the Serve controller. If Serve is not running, returns None.\n        ",
            "n_words": 32,
            "vocab_size": 22,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 49439,
        "commit_id": "9b3119dfb63c4cbb7acfb9f1f1c09ac24e6d68d2",
        "repo": "PaddleHub",
        "path": "modules/image/text_recognition/ppocrv3_det_ch/processor.py",
        "file_name": "processor.py",
        "fun_name": "resize_image_type0",
        "commit_message": "add module",
        "code": "def resize_image_type0(self, img):\n        \n        limit_side_len = self.max_side_len\n        h, w, _ = img.shape\n\n        # limit the max side\n        if max(h, w) > limit_side_len:\n            if h > w:\n                ratio = float(limit_side_len) / h\n            else:\n                ratio = float(limit_side_len) / w\n        else:\n            ratio = 1.\n        resize_h = int(h * ratio)\n        resize_w = int(w * ratio)\n\n        resize_h = int(round(resize_h / 32) * 32)\n        resize_w = int(round(resize_w / 32) * 32)\n\n        try:\n            if int(resize_w) <= 0 or int(resize_h) <= 0:\n                return None, (None, None)\n            img = cv2.resize(img, (int(resize_w), int(resize_h)))\n        except:\n            print(img.shape, resize_w, resize_h)\n            sys.exit(0)\n        ratio_h = resize_h / float(h)\n        ratio_w = resize_w / float(w)\n        # return img, np.array([h, w])\n        return img, [ratio_h, ratio_w]\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 340,
        "n_words": 106,
        "vocab_size": 66,
        "complexity": 6,
        "nloc": 24,
        "token_counts": 190,
        "n_ast_nodes": 302,
        "n_identifiers": 23,
        "d_id": 9744,
        "documentation": {
            "docstring": "\n        resize image to a size multiple of 32 which is required by the network\n        args:\n            img(array): array with shape [h, w, c]\n        return(tuple):\n            img, (ratio_h, ratio_w)\n        ",
            "n_words": 26,
            "vocab_size": 26,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 247312,
        "commit_id": "2ffaf30803f93273a4d8a65c9e6c3110c8433488",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "test_finds_message",
        "commit_message": "Add type hints to `tests/rest/client` (#12108)\n\n* Add type hints to `tests/rest/client`\r\n\r\n* newsfile\r\n\r\n* fix imports\r\n\r\n* add `test_account.py`\r\n\r\n* Remove one type hint in `test_report_event.py`\r\n\r\n* change `on_create_room` to `async`\r\n\r\n* update new functions in `test_third_party_rules.py`\r\n\r\n* Add `test_filter.py`\r\n\r\n* add `test_rooms.py`\r\n\r\n* change to `assertEquals` to `assertEqual`\r\n\r\n* lint",
        "code": "def test_finds_message(self) -> None:\n        \n        # The other user sends some messages\n        self.helper.send(self.room, body=\"Hi!\", tok=self.other_access_token)\n        self.helper.send(self.room, body=\"There!\", tok=self.other_access_token)\n\n        channel = self.make_request(\n            \"POST\",\n            \"/search?access_token=%s\" % (self.access_token,),\n            {\n                \"search_categories\": {\n                    \"room_events\": {\"keys\": [\"content.body\"], \"search_term\": \"Hi\"}\n                }\n            },\n        )\n\n        # Check we get the results we expect -- one search result, of the sent\n        # messages\n        self.assertEqual(channel.code, 200)\n        results = channel.json_body[\"search_categories\"][\"room_events\"]\n        self.assertEqual(results[\"count\"], 1)\n        self.assertEqual(results[\"results\"][0][\"result\"][\"content\"][\"body\"], \"Hi!\")\n\n        # No context was requested, so we should get none.\n        self.assertEqual(results[\"results\"][0][\"context\"], {})\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 264,
        "n_words": 73,
        "vocab_size": 60,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 159,
        "n_ast_nodes": 277,
        "n_identifiers": 15,
        "d_id": 71583,
        "documentation": {
            "docstring": "\n        The search functionality will search for content in messages if asked to\n        do so.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 100443,
        "commit_id": "aa39234538a8f83e6aa2b60b8275a570e8876ac2",
        "repo": "faceswap",
        "path": "plugins/extract/detect/s3fd.py",
        "file_name": "s3fd.py",
        "fun_name": "conv_block",
        "commit_message": "Update all Keras Imports to be conditional (#1214)\n\n* Remove custom keras importer\r\n\r\n* first round keras imports fix\r\n\r\n* launcher.py: Remove KerasFinder references\r\n\r\n* 2nd round keras imports update (lib and extract)\r\n\r\n* 3rd round keras imports update (train)\r\n\r\n* remove KerasFinder from tests\r\n\r\n* 4th round keras imports update (tests)",
        "code": "def conv_block(cls, inputs, filters, idx, recursions):\n        \n        name = f\"conv{idx}\"\n        var_x = inputs\n        for i in range(1, recursions + 1):\n            rec_name = f\"{name}_{i}\"\n            var_x = ZeroPadding2D(1, name=f\"{rec_name}.zeropad\")(var_x)\n            var_x = Conv2D(filters,\n                           kernel_size=3,\n                           strides=1,\n                           activation=\"relu\",\n                           name=rec_name)(var_x)\n        return var_x\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 207,
        "n_words": 35,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 78,
        "n_ast_nodes": 135,
        "n_identifiers": 16,
        "d_id": 19921,
        "documentation": {
            "docstring": " First round convolutions with zero padding added.\n\n        Parameters\n        ----------\n        inputs: tensor\n            The input tensor to the convolution block\n        filters: int\n            The number of filters\n        idx: int\n            The layer index for naming\n        recursions: int\n            The number of recursions of the block to perform\n\n        Returns\n        -------\n        tensor\n            The output tensor from the convolution block\n        ",
            "n_words": 52,
            "vocab_size": 34,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 119172,
        "commit_id": "2388e353da9768a5e714a83b360bac1e920ff7ae",
        "repo": "jax",
        "path": "build/build.py",
        "file_name": "build.py",
        "fun_name": "get_bazel_path",
        "commit_message": "Increase bazel version to 5.0.0 to match TensorFlow\n(https://github.com/tensorflow/tensorflow/commit/8871926b0aa9d5b0e819d12f6945bce752fde610).",
        "code": "def get_bazel_path(bazel_path_flag):\n  \n  for path in filter(None, get_bazel_paths(bazel_path_flag)):\n    version = get_bazel_version(path)\n    if version is not None and version >= (5, 0, 0):\n      return path, \".\".join(map(str, version))\n\n  print(\"Cannot find or download a suitable version of bazel.\"\n        \"Please install bazel >= 5.0.0.\")\n  sys.exit(-1)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 62,
        "n_words": 40,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 67,
        "n_ast_nodes": 112,
        "n_identifiers": 13,
        "d_id": 26549,
        "documentation": {
            "docstring": "Returns the path to a Bazel binary, downloading Bazel if not found. Also,\n  checks Bazel's version is at least newer than 5.0.0\n\n  A manual version check is needed only for really old bazel versions.\n  Newer bazel releases perform their own version check against .bazelversion\n  (see for details\n  https://blog.bazel.build/2019/12/19/bazel-2.0.html#other-important-changes).\n  ",
            "n_words": 48,
            "vocab_size": 41,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 244223,
        "commit_id": "24f2fdb38481e6c013a588660c044e410148ce1e",
        "repo": "mmdetection",
        "path": "mmdet/utils/util_distribution.py",
        "file_name": "util_distribution.py",
        "fun_name": "build_ddp",
        "commit_message": "fix lint (#7793)",
        "code": "def build_ddp(model, device='cuda', *args, **kwargs):\n    \n    assert device in ['cuda', 'mlu'], 'Only available for cuda or mlu devices.'\n    if device == 'cuda':\n        model = model.cuda()\n    elif device == 'mlu':\n        from mmcv.device.mlu import MLUDistributedDataParallel\n        ddp_factory['mlu'] = MLUDistributedDataParallel\n        model = model.mlu()\n\n    return ddp_factory[device](model, *args, **kwargs)\n\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 85,
        "n_words": 42,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 78,
        "n_ast_nodes": 133,
        "n_identifiers": 10,
        "d_id": 70288,
        "documentation": {
            "docstring": "Build DistributedDataParallel module by device type.\n\n    If device is cuda, return a MMDistributedDataParallel model;\n    if device is mlu, return a MLUDistributedDataParallel model.\n\n    Args:\n        model (:class:`nn.Module`): module to be parallelized.\n        device (str): device type, mlu or cuda.\n\n    Returns:\n        :class:`nn.Module`: the module to be parallelized\n\n    References:\n        .. [1] https://pytorch.org/docs/stable/generated/torch.nn.parallel.\n                     DistributedDataParallel.html\n    ",
            "n_words": 48,
            "vocab_size": 37,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 241553,
        "commit_id": "a610e043d797ca0bae1ce186829fece79077407a",
        "repo": "lightning",
        "path": "pytorch_lightning/utilities/enums.py",
        "file_name": "enums.py",
        "fun_name": "detect_current_mode",
        "commit_message": "Add typing for utilities/enums.py (#11298)",
        "code": "def detect_current_mode(cls) -> _FaultTolerantMode:\n        \n        env_value = os.getenv(\"PL_FAULT_TOLERANT_TRAINING\", \"0\").lower()\n        # the int values are kept for backwards compatibility, but long-term we want to keep only the strings\n        if env_value in (\"0\", \"disabled\"):\n            return _FaultTolerantMode.DISABLED\n        elif env_value in (\"1\", \"automatic\"):\n            return _FaultTolerantMode.AUTOMATIC\n        elif env_value in (\"2\", \"manual\"):\n            return _FaultTolerantMode.MANUAL\n        raise MisconfigurationException(\n            \"The environment flag `PL_FAULT_TOLERANT_TRAINING` should be either 'disabled', 'automatic', or 'manual'.\"\n        )\n",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 161,
        "n_words": 61,
        "vocab_size": 52,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 66,
        "n_ast_nodes": 122,
        "n_identifiers": 11,
        "d_id": 69581,
        "documentation": {
            "docstring": "This classmethod detects if `Fault Tolerant` is activated and maps its value to `_FaultTolerantMode`.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 203297,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/apps/config.py",
        "file_name": "config.py",
        "fun_name": "_path_from_module",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _path_from_module(self, module):\n        \n        # See #21874 for extended discussion of the behavior of this method in\n        # various cases.\n        # Convert to list because __path__ may not support indexing.\n        paths = list(getattr(module, \"__path__\", []))\n        if len(paths) != 1:\n            filename = getattr(module, \"__file__\", None)\n            if filename is not None:\n                paths = [os.path.dirname(filename)]\n            else:\n                # For unknown reasons, sometimes the list returned by __path__\n                # contains duplicates that must be removed (#25246).\n                paths = list(set(paths))\n        if len(paths) > 1:\n            raise ImproperlyConfigured(\n                \"The app module %r has multiple filesystem locations (%r); \"\n                \"you must configure this app with an AppConfig subclass \"\n                \"with a 'path' class attribute.\" % (module, paths)\n            )\n        elif not paths:\n            raise ImproperlyConfigured(\n                \"The app module %r has no filesystem location, \"\n                \"you must configure this app with an AppConfig subclass \"\n                \"with a 'path' class attribute.\" % module\n            )\n        return paths[0]\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 432,
        "n_words": 142,
        "vocab_size": 91,
        "complexity": 5,
        "nloc": 21,
        "token_counts": 108,
        "n_ast_nodes": 191,
        "n_identifiers": 13,
        "d_id": 50287,
        "documentation": {
            "docstring": "Attempt to determine app's filesystem path from its module.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 212222,
        "commit_id": "c9751009161f092b2e403d8cccccf5252c0dce1a",
        "repo": "bokeh",
        "path": "bokeh/models/widgets/sliders.py",
        "file_name": "sliders.py",
        "fun_name": "value_as_datetime",
        "commit_message": "Add DatetimeRangeSlider (#12034)\n\n* Add DatetimeRangeSlider\r\n\r\n* Add tests\r\n\r\n* Add docs",
        "code": "def value_as_datetime(self) -> tp.Tuple[datetime, datetime] | None:\n        \n        if self.value is None:\n            return None\n        v1, v2 = self.value\n        if isinstance(v1, numbers.Number):\n            d1 = datetime.utcfromtimestamp(v1 / 1000)\n        else:\n            d1 = v1\n        if isinstance(v2, numbers.Number):\n            d2 = datetime.utcfromtimestamp(v2 / 1000)\n        else:\n            d2 = v2\n        return d1, d2\n\n    value = NonNullable(Tuple(Datetime, Datetime), help=)\n\n    value_throttled = Readonly(NonNullable(Tuple(Datetime, Datetime)), help=)\n\n    start = NonNullable(Datetime, help=)\n\n    end = NonNullable(Datetime, help=)\n\n    step = Int(default=3_600_000, help=)\n\n    format = Override(default=\"%d %b %Y %H:%M:%S\")\n\n#-----------------------------------------------------------------------------\n# Private API\n#-----------------------------------------------------------------------------\n\n#-----------------------------------------------------------------------------\n# Code\n#-----------------------------------------------------------------------------\n",
        "url": "https://github.com/bokeh/bokeh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 204,
        "n_words": 81,
        "vocab_size": 49,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 87,
        "n_ast_nodes": 267,
        "n_identifiers": 26,
        "d_id": 53206,
        "documentation": {
            "docstring": " Convenience property to retrieve the value tuple as a tuple of\n        datetime objects.\n        \n    Initial or selected range.\n    \n    Initial or selected value, throttled to report only on mouseup.\n    \n    The minimum allowable value.\n    \n    The maximum allowable value.\n    \n    The step between consecutive values, in units of milliseconds.\n    Default is one hour.\n    ",
            "n_words": 48,
            "vocab_size": 38,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 176595,
        "commit_id": "8bea55e3071ed71eab4fb6650a45f0cdf5c911d4",
        "repo": "networkx",
        "path": "networkx/generators/spectral_graph_forge.py",
        "file_name": "spectral_graph_forge.py",
        "fun_name": "spectral_graph_forge",
        "commit_message": "Remove `_mat_spect_approx` in favor of simpler procedure (#5624)\n\n* Replace _mat_spect_approx func internal usage.\r\n\r\n* Rm _mat_spect_approx helper function.",
        "code": "def spectral_graph_forge(G, alpha, transformation=\"identity\", seed=None):\n    \n    import numpy as np\n    import scipy as sp\n    import scipy.stats  # call as sp.stats\n\n    available_transformations = [\"identity\", \"modularity\"]\n    alpha = np.clip(alpha, 0, 1)\n    A = nx.to_numpy_array(G)\n    n = A.shape[1]\n    level = int(round(n * alpha))\n\n    if transformation not in available_transformations:\n        msg = f\"{transformation!r} is not a valid transformation. \"\n        msg += f\"Transformations: {available_transformations}\"\n        raise nx.NetworkXError(msg)\n\n    K = np.ones((1, n)) @ A\n\n    B = A\n    if transformation == \"modularity\":\n        B -= K.T @ K / K.sum()\n\n    # Compute low-rank approximation of B\n    evals, evecs = np.linalg.eigh(B)\n    k = np.argsort(np.abs(evals))[::-1]  # indices of evals in descending order\n    evecs[:, k[np.arange(level, n)]] = 0  # set smallest eigenvectors to 0\n    B = evecs @ np.diag(evals) @ evecs.T\n\n    if transformation == \"modularity\":\n        B += K.T @ K / K.sum()\n\n    B = np.clip(B, 0, 1)\n    np.fill_diagonal(B, 0)\n\n    for i in range(n - 1):\n        B[i, i + 1 :] = sp.stats.bernoulli.rvs(B[i, i + 1 :], random_state=seed)\n        B[i + 1 :, i] = np.transpose(B[i, i + 1 :])\n\n    H = nx.from_numpy_array(B)\n\n    return H\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 293,
        "n_words": 169,
        "vocab_size": 105,
        "complexity": 5,
        "nloc": 30,
        "token_counts": 306,
        "n_ast_nodes": 494,
        "n_identifiers": 45,
        "d_id": 41994,
        "documentation": {
            "docstring": "Returns a random simple graph with spectrum resembling that of `G`\n\n    This algorithm, called Spectral Graph Forge (SGF), computes the\n    eigenvectors of a given graph adjacency matrix, filters them and\n    builds a random graph with a similar eigenstructure.\n    SGF has been proved to be particularly useful for synthesizing\n    realistic social networks and it can also be used to anonymize\n    graph sensitive data.\n\n    Parameters\n    ----------\n    G : Graph\n    alpha :  float\n        Ratio representing the percentage of eigenvectors of G to consider,\n        values in [0,1].\n    transformation : string, optional\n        Represents the intended matrix linear transformation, possible values\n        are 'identity' and 'modularity'\n    seed : integer, random_state, or None (default)\n        Indicator of numpy random number generation state.\n        See :ref:`Randomness<randomness>`.\n\n    Returns\n    -------\n    H : Graph\n        A graph with a similar eigenvector structure of the input one.\n\n    Raises\n    ------\n    NetworkXError\n        If transformation has a value different from 'identity' or 'modularity'\n\n    Notes\n    -----\n    Spectral Graph Forge (SGF) generates a random simple graph resembling the\n    global properties of the given one.\n    It leverages the low-rank approximation of the associated adjacency matrix\n    driven by the *alpha* precision parameter.\n    SGF preserves the number of nodes of the input graph and their ordering.\n    This way, nodes of output graphs resemble the properties of the input one\n    and attributes can be directly mapped.\n\n    It considers the graph adjacency matrices which can optionally be\n    transformed to other symmetric real matrices (currently transformation\n    options include *identity* and *modularity*).\n    The *modularity* transformation, in the sense of Newman's modularity matrix\n    allows the focusing on community structure related properties of the graph.\n\n    SGF applies a low-rank approximation whose fixed rank is computed from the\n    ratio *alpha* of the input graph adjacency matrix dimension.\n    This step performs a filtering on the input eigenvectors similar to the low\n    pass filtering common in telecommunications.\n\n    The filtered values (after truncation) are used as input to a Bernoulli\n    sampling for constructing a random adjacency matrix.\n\n    References\n    ----------\n    ..  [1] L. Baldesi, C. T. Butts, A. Markopoulou, \"Spectral Graph Forge:\n        Graph Generation Targeting Modularity\", IEEE Infocom, '18.\n        https://arxiv.org/abs/1801.01715\n    ..  [2] M. Newman, \"Networks: an introduction\", Oxford university press,\n        2010\n\n    Examples\n    --------\n    >>> G = nx.karate_club_graph()\n    >>> H = nx.spectral_graph_forge(G, 0.3)\n    >>>\n    ",
            "n_words": 358,
            "vocab_size": 213,
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        }
    },
    {
        "id": 218101,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "find_loader",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def find_loader(self, fullname):\n        \n        _warnings.warn(\"FileFinder.find_loader() is deprecated and \"\n                       \"slated for removal in Python 3.12; use find_spec() instead\",\n                       DeprecationWarning)\n        spec = self.find_spec(fullname)\n        if spec is None:\n            return None, []\n        return spec.loader, spec.submodule_search_locations or []\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
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        "d_id": 55131,
        "documentation": {
            "docstring": "Try to find a loader for the specified module, or the namespace\n        package portions. Returns (loader, list-of-portions).\n\n        This method is deprecated.  Use find_spec() instead.\n\n        ",
            "n_words": 24,
            "vocab_size": 23,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 19671,
        "commit_id": "9a3b3ce70621af6f9adaa9eeac9cf83fa149319c",
        "repo": "pipenv",
        "path": "pipenv/environment.py",
        "file_name": "environment.py",
        "fun_name": "sys_path",
        "commit_message": "Issue 4993 Add standard pre commit hooks and apply linting. (#4994)\n\n* Add .pre-commit-config.yaml to the project and exclude tests (for now).  This does not include the MyPy linting that pip does but does include everything else.",
        "code": "def sys_path(self):\n        # type: () -> List[str]\n        \n\n        from .vendor.vistir.compat import JSONDecodeError\n\n        current_executable = Path(sys.executable).as_posix()\n        if not self.python or self.python == current_executable:\n            return sys.path\n        elif any([sys.prefix == self.prefix, not self.is_venv]):\n            return sys.path\n        cmd_args = [self.python, \"-c\", \"import json, sys; print(json.dumps(sys.path))\"]\n        path, _ = vistir.misc.run(\n            cmd_args,\n            return_object=False,\n            nospin=True,\n            block=True,\n            combine_stderr=False,\n            write_to_stdout=False,\n        )\n        try:\n            path = json.loads(path.strip())\n        except JSONDecodeError:\n            path = sys.path\n        return path\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 255,
        "n_words": 61,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 21,
        "token_counts": 134,
        "n_ast_nodes": 212,
        "n_identifiers": 28,
        "d_id": 3055,
        "documentation": {
            "docstring": "\n        The system path inside the environment\n\n        :return: The :data:`sys.path` from the environment\n        :rtype: list\n        ",
            "n_words": 14,
            "vocab_size": 11,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 104228,
        "commit_id": "6ed6ac9448311930557810383d2cfd4fe6aae269",
        "repo": "datasets",
        "path": "src/datasets/arrow_writer.py",
        "file_name": "arrow_writer.py",
        "fun_name": "parquet_to_arrow",
        "commit_message": "Better TQDM output (#3654)\n\n* Show progress bar when generating examples\r\n\r\n* Consistent utils.is_progress_bar_enabled calls\r\n\r\n* Fix tqdm in notebook\r\n\r\n* Add missing params to DatasetDict.map\r\n\r\n* Specify total in tqdm progress bar in map\r\n\r\n* Fix total computation\r\n\r\n* Small fix\r\n\r\n* Add desc to map_nested\r\n\r\n* Add more precise descriptions to download\r\n\r\n* Address comments\r\n\r\n* Fix docstring\r\n\r\n* Final changes\r\n\r\n* Minor change",
        "code": "def parquet_to_arrow(sources, destination):\n    \n    stream = None if isinstance(destination, str) else destination\n    disable = not utils.is_progress_bar_enabled()\n    with ArrowWriter(path=destination, stream=stream) as writer:\n        for source in utils.tqdm(sources, unit=\"sources\", disable=disable):\n            pf = pa.parquet.ParquetFile(source)\n            for i in utils.tqdm(range(pf.num_row_groups), unit=\"row_groups\", leave=False, disable=disable):\n                df = pf.read_row_group(i).to_pandas()\n                for col in df.columns:\n                    df[col] = df[col].apply(json.loads)\n                reconstructed_table = pa.Table.from_pandas(df)\n                writer.write_table(reconstructed_table)\n    return destination\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 175,
        "n_words": 52,
        "vocab_size": 41,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 150,
        "n_ast_nodes": 236,
        "n_identifiers": 35,
        "d_id": 21787,
        "documentation": {
            "docstring": "Convert parquet files to arrow file. Inputs can be str paths or file-like objects",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 185240,
        "commit_id": "e61eaf7597a1050e80e7ce029737b5544743a2f5",
        "repo": "textual",
        "path": "src/textual/widgets/_input.py",
        "file_name": "_input.py",
        "fun_name": "cursor_width",
        "commit_message": "replace TextInput with Input",
        "code": "def cursor_width(self) -> int:\n        \n        if self.placeholder and not self.value:\n            return cell_len(self.placeholder)\n        return self._position_to_cell(len(self.value)) + 1\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 47,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 39,
        "n_ast_nodes": 65,
        "n_identifiers": 8,
        "d_id": 44947,
        "documentation": {
            "docstring": "Get the width of the input (with extra space for cursor at the end).",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 247719,
        "commit_id": "96274565ff0dbb7d21b02b04fcef115330426707",
        "repo": "synapse",
        "path": "tests/rest/client/test_relations.py",
        "file_name": "test_relations.py",
        "fun_name": "test_bundled_aggregations_with_filter",
        "commit_message": "Fix bundling aggregations if unsigned is not a returned event field. (#12234)\n\nAn error occured if a filter was supplied with `event_fields` which did not include\r\n`unsigned`.\r\n\r\nIn that case, bundled aggregations are still added as the spec states it is allowed\r\nfor servers to add additional fields.",
        "code": "def test_bundled_aggregations_with_filter(self) -> None:\n        \n        self._send_relation(RelationTypes.ANNOTATION, \"m.reaction\", \"a\")\n\n        # Note that the sync filter does not include \"unsigned\" as a field.\n        filter = urllib.parse.quote_plus(\n            b'{\"event_fields\": [\"content\", \"event_id\"], \"room\": {\"timeline\": {\"limit\": 3}}}'\n        )\n        channel = self.make_request(\n            \"GET\", f\"/sync?filter={filter}\", access_token=self.user_token\n        )\n        self.assertEqual(200, channel.code, channel.json_body)\n\n        # Ensure the timeline is limited, find the parent event.\n        room_timeline = channel.json_body[\"rooms\"][\"join\"][self.room][\"timeline\"]\n        self.assertTrue(room_timeline[\"limited\"])\n        parent_event = self._find_event_in_chunk(room_timeline[\"events\"])\n\n        # Ensure there's bundled aggregations on it.\n        self.assertIn(\"unsigned\", parent_event)\n        self.assertIn(\"m.relations\", parent_event[\"unsigned\"])\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 196,
        "n_words": 69,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 120,
        "n_ast_nodes": 211,
        "n_identifiers": 22,
        "d_id": 71871,
        "documentation": {
            "docstring": "\n        If \"unsigned\" is an omitted field (due to filtering), adding the bundled\n        aggregations should not break.\n\n        Note that the spec allows for a server to return additional fields beyond\n        what is specified.\n        ",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 23176,
        "commit_id": "9f62b610dea6161627200ed85d92e19b1923279a",
        "repo": "PaddleOCR",
        "path": "ppocr/data/imaug/fce_aug.py",
        "file_name": "fce_aug.py",
        "fun_name": "sample_crop_box",
        "commit_message": "add fcenet",
        "code": "def sample_crop_box(self, img_size, results):\n        \n\n        assert isinstance(img_size, tuple)\n        h, w = img_size[:2]\n\n        key_masks = results['polys']\n\n        x_valid_array = np.ones(w, dtype=np.int32)\n        y_valid_array = np.ones(h, dtype=np.int32)\n\n        selected_mask = key_masks[np.random.randint(0, len(key_masks))]\n        selected_mask = selected_mask.reshape((-1, 2)).astype(np.int32)\n        max_x_start = max(np.min(selected_mask[:, 0]) - 2, 0)\n        min_x_end = min(np.max(selected_mask[:, 0]) + 3, w - 1)\n        max_y_start = max(np.min(selected_mask[:, 1]) - 2, 0)\n        min_y_end = min(np.max(selected_mask[:, 1]) + 3, h - 1)\n\n        # for key in results.get('mask_fields', []):\n        #     if len(results[key].masks) == 0:\n        #         continue\n        #     masks = results[key].masks\n        for mask in key_masks:\n            # assert len(mask) == 1\n            mask = mask.reshape((-1, 2)).astype(np.int32)\n            clip_x = np.clip(mask[:, 0], 0, w - 1)\n            clip_y = np.clip(mask[:, 1], 0, h - 1)\n            min_x, max_x = np.min(clip_x), np.max(clip_x)\n            min_y, max_y = np.min(clip_y), np.max(clip_y)\n\n            x_valid_array[min_x - 2:max_x + 3] = 0\n            y_valid_array[min_y - 2:max_y + 3] = 0\n\n        min_w = int(w * self.min_side_ratio)\n        min_h = int(h * self.min_side_ratio)\n\n        x1, x2 = self.sample_valid_start_end(x_valid_array, min_w, max_x_start,\n                                             min_x_end)\n        y1, y2 = self.sample_valid_start_end(y_valid_array, min_h, max_y_start,\n                                             min_y_end)\n\n        return np.array([x1, y1, x2, y2])\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 507,
        "n_words": 161,
        "vocab_size": 98,
        "complexity": 2,
        "nloc": 27,
        "token_counts": 370,
        "n_ast_nodes": 561,
        "n_identifiers": 45,
        "d_id": 4526,
        "documentation": {
            "docstring": "Generate crop box and make sure not to crop the polygon instances.\n\n        Args:\n            img_size (tuple(int)): The image size (h, w).\n            results (dict): The results dict.\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 167144,
        "commit_id": "25749d29dbbb8c6ae7a05f4661948d03c17b20ae",
        "repo": "pandas",
        "path": "pandas/core/arrays/period.py",
        "file_name": "period.py",
        "fun_name": "dt64arr_to_periodarr",
        "commit_message": "ENH: DTA.to_period support non-nano (#47324)\n\n* ENH: DTA.to_period support non-nano\r\n\r\n* update test",
        "code": "def dt64arr_to_periodarr(data, freq, tz=None):\n    \n    if not isinstance(data.dtype, np.dtype) or data.dtype.kind != \"M\":\n        raise ValueError(f\"Wrong dtype: {data.dtype}\")\n\n    if freq is None:\n        if isinstance(data, ABCIndex):\n            data, freq = data._values, data.freq\n        elif isinstance(data, ABCSeries):\n            data, freq = data._values, data.dt.freq\n\n    elif isinstance(data, (ABCIndex, ABCSeries)):\n        data = data._values\n\n    reso = get_unit_from_dtype(data.dtype)\n    freq = Period._maybe_convert_freq(freq)\n    base = freq._period_dtype_code\n    return c_dt64arr_to_periodarr(data.view(\"i8\"), base, tz, reso=reso), freq\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 132,
        "n_words": 58,
        "vocab_size": 42,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 142,
        "n_ast_nodes": 229,
        "n_identifiers": 21,
        "d_id": 39943,
        "documentation": {
            "docstring": "\n    Convert an datetime-like array to values Period ordinals.\n\n    Parameters\n    ----------\n    data : Union[Series[datetime64[ns]], DatetimeIndex, ndarray[datetime64ns]]\n    freq : Optional[Union[str, Tick]]\n        Must match the `freq` on the `data` if `data` is a DatetimeIndex\n        or Series.\n    tz : Optional[tzinfo]\n\n    Returns\n    -------\n    ordinals : ndarray[int64]\n    freq : Tick\n        The frequency extracted from the Series or DatetimeIndex if that's\n        used.\n\n    ",
            "n_words": 55,
            "vocab_size": 44,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 36650,
        "commit_id": "5b40a37bc4da9dc6cd33876ce9bb3f7f48450a03",
        "repo": "transformers",
        "path": "src/transformers/models/vit_mae/modeling_tf_vit_mae.py",
        "file_name": "modeling_tf_vit_mae.py",
        "fun_name": "get_2d_sincos_pos_embed",
        "commit_message": "Add TF ViT MAE (#16255)\n\n* ported TFViTMAEIntermediate and TFViTMAEOutput.\r\n\r\n* added TFViTMAEModel and TFViTMAEDecoder.\r\n\r\n* feat: added a noise argument in the implementation for reproducibility.\r\n\r\n* feat: vit mae models with an additional noise argument for reproducibility.\r\n\r\nCo-authored-by: ariG23498 <aritra.born2fly@gmail.com>\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>",
        "code": "def get_2d_sincos_pos_embed(embed_dim, grid_size, add_cls_token=False):\n    \n    grid_h = tf.range(grid_size, dtype=tf.float32)\n    grid_w = tf.range(grid_size, dtype=tf.float32)\n    grid = tf.meshgrid(grid_w, grid_h)  # here w goes first\n    grid = tf.stack(grid, axis=0)\n\n    grid = tf.reshape(grid, [2, 1, grid_size, grid_size])\n    pos_embed = get_2d_sincos_pos_embed_from_grid(embed_dim, grid)\n    if add_cls_token:\n        pos_embed = tf.concat([tf.zeros((1, embed_dim)), pos_embed], axis=0)\n    return pos_embed\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 81,
        "n_words": 46,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 118,
        "n_ast_nodes": 176,
        "n_identifiers": 19,
        "d_id": 6659,
        "documentation": {
            "docstring": "\n    Create 2D sin/cos positional embeddings.\n\n    Args:\n        embed_dim (`int`):\n            Embedding dimension.\n        grid_size (`int`):\n            The grid height and width.\n        add_cls_token (`bool`, *optional*, defaults to `False`):\n            Whether or not to add a classification (CLS) token.\n\n    Returns:\n        (`tf.Tensor` of shape (grid_size*grid_size, embed_dim) or (1+grid_size*grid_size, embed_dim): the position\n        embeddings (with or without classification token)\n    ",
            "n_words": 49,
            "vocab_size": 44,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 153819,
        "commit_id": "57e29bc5d82348006c5170ef9ac0a9eedcd9acf9",
        "repo": "modin",
        "path": "modin/core/storage_formats/base/query_compiler.py",
        "file_name": "query_compiler.py",
        "fun_name": "df_update",
        "commit_message": "REFACTOR-#4513: Fix spelling mistakes in docs and docstrings (#4514)\n\nCo-authored-by: Rehan Sohail Durrani <rdurrani@berkeley.edu>\r\nSigned-off-by: jeffreykennethli <jkli@ponder.io>",
        "code": "def df_update(self, other, **kwargs):  # noqa: PR02\n        \n        return BinaryDefault.register(pandas.DataFrame.update, inplace=True)(\n            self, other=other, **kwargs\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 47,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 36,
        "n_ast_nodes": 56,
        "n_identifiers": 10,
        "d_id": 35634,
        "documentation": {
            "docstring": "\n        Update values of `self` using non-NA values of `other` at the corresponding positions.\n\n        If axes are not equal, perform frames alignment first.\n\n        Parameters\n        ----------\n        other : BaseQueryCompiler\n            Frame to grab replacement values from.\n        join : {\"left\"}\n            Specify type of join to align frames if axes are not equal\n            (note: currently only one type of join is implemented).\n        overwrite : bool\n            Whether to overwrite every corresponding value of self, or only if it's NAN.\n        filter_func : callable(pandas.Series, pandas.Series) -> numpy.ndarray<bool>\n            Function that takes column of the self and return bool mask for values, that\n            should be overwritten in the self frame.\n        errors : {\"raise\", \"ignore\"}\n            If \"raise\", will raise a ``ValueError`` if `self` and `other` both contain\n            non-NA data in the same place.\n        **kwargs : dict\n            Serves the compatibility purpose. Does not affect the result.\n\n        Returns\n        -------\n        BaseQueryCompiler\n            New QueryCompiler with updated values.\n        ",
            "n_words": 142,
            "vocab_size": 100,
            "n_whitespaces": 351,
            "language": "en"
        }
    },
    {
        "id": 167007,
        "commit_id": "3350f95c017a68644e8577651af743413532356f",
        "repo": "pandas",
        "path": "pandas/core/arrays/timedeltas.py",
        "file_name": "timedeltas.py",
        "fun_name": "total_seconds",
        "commit_message": "REF: share DTA/TDA/PA arithmetic methods (#47205)\n\n* REF: share DTA/TDA/PA arithmetic methods\r\n\r\n* troubleshoot npdev build",
        "code": "def total_seconds(self) -> npt.NDArray[np.float64]:\n        \n        return self._maybe_mask_results(1e-9 * self.asi8, fill_value=None)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 23,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 56,
        "token_counts": 32,
        "n_ast_nodes": 48,
        "n_identifiers": 9,
        "d_id": 39917,
        "documentation": {
            "docstring": "\n        Return total duration of each element expressed in seconds.\n\n        This method is available directly on TimedeltaArray, TimedeltaIndex\n        and on Series containing timedelta values under the ``.dt`` namespace.\n\n        Returns\n        -------\n        seconds : [ndarray, Float64Index, Series]\n            When the calling object is a TimedeltaArray, the return type\n            is ndarray.  When the calling object is a TimedeltaIndex,\n            the return type is a Float64Index. When the calling object\n            is a Series, the return type is Series of type `float64` whose\n            index is the same as the original.\n\n        See Also\n        --------\n        datetime.timedelta.total_seconds : Standard library version\n            of this method.\n        TimedeltaIndex.components : Return a DataFrame with components of\n            each Timedelta.\n\n        Examples\n        --------\n        **Series**\n\n        >>> s = pd.Series(pd.to_timedelta(np.arange(5), unit='d'))\n        >>> s\n        0   0 days\n        1   1 days\n        2   2 days\n        3   3 days\n        4   4 days\n        dtype: timedelta64[ns]\n\n        >>> s.dt.total_seconds()\n        0         0.0\n        1     86400.0\n        2    172800.0\n        3    259200.0\n        4    345600.0\n        dtype: float64\n\n        **TimedeltaIndex**\n\n        >>> idx = pd.to_timedelta(np.arange(5), unit='d')\n        >>> idx\n        TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'],\n                       dtype='timedelta64[ns]', freq=None)\n\n        >>> idx.total_seconds()\n        Float64Index([0.0, 86400.0, 172800.0, 259200.00000000003, 345600.0],\n                     dtype='float64')\n        ",
            "n_words": 172,
            "vocab_size": 105,
            "n_whitespaces": 569,
            "language": "en"
        }
    },
    {
        "id": 271853,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_utils_v1.py",
        "file_name": "training_utils_v1.py",
        "fun_name": "batch_shuffle",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def batch_shuffle(index_array, batch_size):\n    \n    batch_count = int(len(index_array) / batch_size)\n    # to reshape we need to be cleanly divisible by batch size\n    # we stash extra items and reappend them after shuffling\n    last_batch = index_array[batch_count * batch_size :]\n    index_array = index_array[: batch_count * batch_size]\n    index_array = index_array.reshape((batch_count, batch_size))\n    np.random.shuffle(index_array)\n    index_array = index_array.flatten()\n    return np.append(index_array, last_batch)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 83,
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        "vocab_size": 42,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 73,
        "n_ast_nodes": 119,
        "n_identifiers": 13,
        "d_id": 80870,
        "documentation": {
            "docstring": "Shuffles an array in a batch-wise fashion.\n\n    Useful for shuffling HDF5 arrays\n    (where one cannot access arbitrary indices).\n\n    Args:\n        index_array: array of indices to be shuffled.\n        batch_size: integer.\n\n    Returns:\n        The `index_array` array, shuffled in a batch-wise fashion.\n    ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 73,
            "language": "en"
        }
    },
    {
        "id": 196246,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/functions/elementary/piecewise.py",
        "file_name": "piecewise.py",
        "fun_name": "_intervals",
        "commit_message": "Updated import locations",
        "code": "def _intervals(self, sym):\n        \n        from sympy.solvers.inequalities import _solve_inequality\n\n        assert isinstance(self, Piecewise)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 31,
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        "complexity": 31,
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        "token_counts": 577,
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        "n_identifiers": 9,
        "d_id": 47746,
        "documentation": {
            "docstring": "Return a list of unique tuples, (a, b, e, i), where a and b\n        are the lower and upper bounds in which the expression e of\n        argument i in self is defined and $a < b$ (when involving\n        numbers) or $a \\le b$ when involving symbols.\n\n        If there are any relationals not involving sym, or any\n        relational cannot be solved for sym, NotImplementedError is\n        raised. The calling routine should have removed such\n        relationals before calling this routine.\n\n        The evaluated conditions will be returned as ranges.\n        Discontinuous ranges will be returned separately with\n        identical expressions. The first condition that evaluates to\n        True will be returned as the last tuple with a, b = -oo, oo.\n        ",
            "n_words": 114,
            "vocab_size": 84,
            "n_whitespaces": 198,
            "language": "en"
        }
    },
    {
        "id": 268879,
        "commit_id": "b4dca51d0558e788f62a96d1009a07f773a202f4",
        "repo": "keras",
        "path": "keras/metrics/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get",
        "commit_message": "Refactor disparate metrics-related files into a single metrics folder.\n\nFurther work may be needed to split up the long file with individual metric definitions. However having a single file per metric may be too granular. TBD.\n\nPiperOrigin-RevId: 425248502",
        "code": "def get(identifier):\n  \n  if isinstance(identifier, dict):\n    return deserialize(identifier)\n  elif isinstance(identifier, str):\n    return deserialize(str(identifier))\n  elif callable(identifier):\n    return identifier\n  else:\n    raise ValueError(\n        f'Could not interpret metric identifier: {identifier}')\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 49,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 51,
        "n_ast_nodes": 89,
        "n_identifiers": 8,
        "d_id": 79746,
        "documentation": {
            "docstring": "Retrieves a Keras metric as a `function`/`Metric` class instance.\n\n  The `identifier` may be the string name of a metric function or class.\n\n  >>> metric = tf.keras.metrics.get(\"categorical_crossentropy\")\n  >>> type(metric)\n  <class 'function'>\n  >>> metric = tf.keras.metrics.get(\"CategoricalCrossentropy\")\n  >>> type(metric)\n  <class '...metrics.CategoricalCrossentropy'>\n\n  You can also specify `config` of the metric to this function by passing dict\n  containing `class_name` and `config` as an identifier. Also note that the\n  `class_name` must map to a `Metric` class\n\n  >>> identifier = {\"class_name\": \"CategoricalCrossentropy\",\n  ...               \"config\": {\"from_logits\": True}}\n  >>> metric = tf.keras.metrics.get(identifier)\n  >>> type(metric)\n  <class '...metrics.CategoricalCrossentropy'>\n\n  Args:\n    identifier: A metric identifier. One of None or string name of a metric\n      function/class or metric configuration dictionary or a metric function or\n      a metric class instance\n\n  Returns:\n    A Keras metric as a `function`/ `Metric` class instance.\n\n  Raises:\n    ValueError: If `identifier` cannot be interpreted.\n  ",
            "n_words": 132,
            "vocab_size": 72,
            "n_whitespaces": 184,
            "language": "en"
        }
    },
    {
        "id": 223513,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_header_value_parser.py",
        "file_name": "_header_value_parser.py",
        "fun_name": "get_attrtext",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_attrtext(value):\n    \n    m = _non_attribute_end_matcher(value)\n    if not m:\n        raise errors.HeaderParseError(\n            \"expected attrtext but found {!r}\".format(value))\n    attrtext = m.group()\n    value = value[len(attrtext):]\n    attrtext = ValueTerminal(attrtext, 'attrtext')\n    _validate_xtext(attrtext)\n    return attrtext, value\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 29,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 61,
        "n_ast_nodes": 106,
        "n_identifiers": 12,
        "d_id": 56942,
        "documentation": {
            "docstring": "attrtext = 1*(any non-ATTRIBUTE_ENDS character)\n\n    We allow any non-ATTRIBUTE_ENDS in attrtext, but add defects to the\n    token's defects list if we find non-attrtext characters.  We also register\n    defects for *any* non-printables even though the RFC doesn't exclude all of\n    them, because we follow the spirit of RFC 5322.\n\n    ",
            "n_words": 48,
            "vocab_size": 39,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 157120,
        "commit_id": "c4d35f5515191409913827fd4faa3b69a3d7399a",
        "repo": "dask",
        "path": "dask/dataframe/io/io.py",
        "file_name": "io.py",
        "fun_name": "from_dict",
        "commit_message": "Backend library dispatching for IO in Dask-Array and Dask-DataFrame (#9475)",
        "code": "def from_dict(data, npartitions, orient=\"columns\", dtype=None, columns=None):\n    \n\n    collection_types = {type(v) for v in data.values() if is_dask_collection(v)}\n    if collection_types:\n        raise NotImplementedError(\n            \"from_dict doesn't currently support Dask collections as inputs. \"\n            f\"Objects of type {collection_types} were given in the input dict.\"\n        )\n\n    return from_pandas(\n        pd.DataFrame.from_dict(data, orient, dtype, columns),\n        npartitions,\n    )\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 112,
        "n_words": 47,
        "vocab_size": 43,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 72,
        "n_ast_nodes": 116,
        "n_identifiers": 15,
        "d_id": 36860,
        "documentation": {
            "docstring": "\n    Construct a Dask DataFrame from a Python Dictionary\n\n    Parameters\n    ----------\n    data : dict\n        Of the form {field : array-like} or {field : dict}.\n    npartitions : int\n        The number of partitions of the index to create. Note that depending on\n        the size and index of the dataframe, the output may have fewer\n        partitions than requested.\n    orient : {'columns', 'index', 'tight'}, default 'columns'\n        The \"orientation\" of the data. If the keys of the passed dict\n        should be the columns of the resulting DataFrame, pass 'columns'\n        (default). Otherwise if the keys should be rows, pass 'index'.\n        If 'tight', assume a dict with keys\n        ['index', 'columns', 'data', 'index_names', 'column_names'].\n    dtype: bool\n        Data type to force, otherwise infer.\n    columns: string, optional\n        Column labels to use when ``orient='index'``. Raises a ValueError\n        if used with ``orient='columns'`` or ``orient='tight'``.\n\n    Examples\n    --------\n    >>> import dask.dataframe as dd\n    >>> ddf = dd.from_dict({\"num1\": [1, 2, 3, 4], \"num2\": [7, 8, 9, 10]}, npartitions=2)\n    ",
            "n_words": 152,
            "vocab_size": 111,
            "n_whitespaces": 276,
            "language": "en"
        }
    },
    {
        "id": 63195,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_is_unpacked_egg",
        "commit_message": "upd; format",
        "code": "def _is_unpacked_egg(path):\n    \n    return (\n        _is_egg_path(path) and\n        os.path.isfile(os.path.join(path, 'EGG-INFO', 'PKG-INFO'))\n    )\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 33,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 6,
        "d_id": 13197,
        "documentation": {
            "docstring": "\n    Determine if given path appears to be an unpacked egg.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 206404,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/test/runner.py",
        "file_name": "runner.py",
        "fun_name": "shuffle",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def shuffle(self, items, key):\n        \n        hashes = {}\n        for item in items:\n            hashed = self._hash_item(item, key)\n            if hashed in hashes:\n                msg = \"item {!r} has same hash {!r} as item {!r}\".format(\n                    item,\n                    hashed,\n                    hashes[hashed],\n                )\n                raise RuntimeError(msg)\n            hashes[hashed] = item\n        return [hashes[hashed] for hashed in sorted(hashes)]\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 208,
        "n_words": 45,
        "vocab_size": 34,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 75,
        "n_ast_nodes": 115,
        "n_identifiers": 12,
        "d_id": 51514,
        "documentation": {
            "docstring": "\n        Return a new list of the items in a shuffled order.\n\n        The `key` is a function that accepts an item in `items` and returns\n        a string unique for that item that can be viewed as a string id. The\n        order of the return value is deterministic. It depends on the seed\n        and key function but not on the original order.\n        ",
            "n_words": 60,
            "vocab_size": 41,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 260503,
        "commit_id": "01fcf8a0acc7e6517faa4fc6887eb45f5d2ea77b",
        "repo": "scikit-learn",
        "path": "sklearn/decomposition/tests/test_sparse_pca.py",
        "file_name": "test_sparse_pca.py",
        "fun_name": "test_transform_inverse_transform_round_trip",
        "commit_message": "ENH add inverse_transform in *SparsePCA (#23905)",
        "code": "def test_transform_inverse_transform_round_trip(SPCA):\n    \n    rng = np.random.RandomState(0)\n    n_samples, n_features = 10, 5\n    X = rng.randn(n_samples, n_features)\n\n    n_components = n_features\n    spca = SPCA(\n        n_components=n_components, alpha=1e-12, ridge_alpha=1e-12, random_state=0\n    )\n    X_trans_spca = spca.fit_transform(X)\n    assert_allclose(spca.inverse_transform(X_trans_spca), X)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 64,
        "n_words": 30,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 79,
        "n_ast_nodes": 118,
        "n_identifiers": 19,
        "d_id": 76298,
        "documentation": {
            "docstring": "Check the `transform` and `inverse_transform` round trip with no loss of\n    information.\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 195437,
        "commit_id": "0f129e9c38b6b10d80982ecc412785db62842938",
        "repo": "ParlAI",
        "path": "parlai/tasks/reasoning/reason_types/step_by_step.py",
        "file_name": "step_by_step.py",
        "fun_name": "extract_operations",
        "commit_message": "ROSCOE suite of metrics (#4839)\n\n* ROSCOE suite of metrics\r\n\r\n* updating tests\r\n\r\n* lint\r\n\r\n* fixing protobuf version to stop cleaninstall failures\r\n\r\n* updating requirements\r\n\r\n* convert to absolute path\r\n\r\n* moving tests because of the dependency issues\r\n\r\n* adding new dependencies in tests\r\n\r\n* add test dependencies\r\n\r\n* fixing deps\r\n\r\n* updating task list\r\n\r\n* checklist deps can't be installed on circleci\r\n\r\n* actually fix protobuf version\r\n\r\n* protobuf range\r\n\r\n* protobuf conflict with google-api-core\r\n\r\n* return tests\r\n\r\n* convert imports to absolute path\r\n\r\n* trying checklist again\r\n\r\n* trying to avoid checklist failures\r\n\r\n* checklist to teacher tests\r\n\r\n* add user option to avoid installation failure\r\n\r\n* jupiter as well\r\n\r\n* typo\r\n\r\n* moving into virtual env setup\r\n\r\n* user param not allowed in virtual env\r\n\r\n* move spacy to circleCI because it's big\r\n\r\n* replace local model with HF\r\n\r\n* fixes based on comments\r\n\r\n* remove unused nli scores, fix tests\r\n\r\n* Added path to BART model\r\n\r\nCo-authored-by: Spencer Poff <spencerpoff@gmail.com>",
        "code": "def extract_operations(self) -> List[str]:\n        \n        if not self.step:\n            return []\n        try:\n            operations = re.findall(r'[-+*^/]', self.step)\n        except TypeError as e:\n            print(f\"TYPE: {type(self.step)}\")\n            print(f\"STEP: {self.step}\")\n            raise e\n        return operations\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 116,
        "n_words": 26,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 54,
        "n_ast_nodes": 111,
        "n_identifiers": 12,
        "d_id": 47260,
        "documentation": {
            "docstring": "\n        Finds all instances of the math operations: -, +, *, ^, / in the step.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 269604,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "less_equal",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def less_equal(x, y):\n    \n    return tf.less_equal(x, y)\n\n\n@keras_export(\"keras.backend.maximum\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.maximum\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 12,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 57,
        "n_identifiers": 10,
        "d_id": 80224,
        "documentation": {
            "docstring": "Element-wise truth value of (x <= y).\n\n    Args:\n        x: Tensor or variable.\n        y: Tensor or variable.\n\n    Returns:\n        A bool tensor.\n    ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 65410,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/utils.py",
        "file_name": "utils.py",
        "fun_name": "update_reference_in_journal_entry",
        "commit_message": "style: format code with black",
        "code": "def update_reference_in_journal_entry(d, journal_entry, do_not_save=False):\n\t\n\tjv_detail = journal_entry.get(\"accounts\", {\"name\": d[\"voucher_detail_no\"]})[0]\n\n\tif flt(d[\"unadjusted_amount\"]) - flt(d[\"allocated_amount\"]) != 0:\n\t\t# adjust the unreconciled balance\n\t\tamount_in_account_currency = flt(d[\"unadjusted_amount\"]) - flt(d[\"allocated_amount\"])\n\t\tamount_in_company_currency = amount_in_account_currency * flt(jv_detail.exchange_rate)\n\t\tjv_detail.set(d[\"dr_or_cr\"], amount_in_account_currency)\n\t\tjv_detail.set(\n\t\t\t\"debit\" if d[\"dr_or_cr\"] == \"debit_in_account_currency\" else \"credit\",\n\t\t\tamount_in_company_currency,\n\t\t)\n\telse:\n\t\tjournal_entry.remove(jv_detail)\n\n\t# new row with references\n\tnew_row = journal_entry.append(\"accounts\")\n\n\tnew_row.update((frappe.copy_doc(jv_detail)).as_dict())\n\n\tnew_row.set(d[\"dr_or_cr\"], d[\"allocated_amount\"])\n\tnew_row.set(\n\t\t\"debit\" if d[\"dr_or_cr\"] == \"debit_in_account_currency\" else \"credit\",\n\t\td[\"allocated_amount\"] * flt(jv_detail.exchange_rate),\n\t)\n\n\tnew_row.set(\n\t\t\"credit_in_account_currency\"\n\t\tif d[\"dr_or_cr\"] == \"debit_in_account_currency\"\n\t\telse \"debit_in_account_currency\",\n\t\t0,\n\t)\n\tnew_row.set(\"credit\" if d[\"dr_or_cr\"] == \"debit_in_account_currency\" else \"debit\", 0)\n\n\tnew_row.set(\"reference_type\", d[\"against_voucher_type\"])\n\tnew_row.set(\"reference_name\", d[\"against_voucher\"])\n\n\tnew_row.against_account = cstr(jv_detail.against_account)\n\tnew_row.is_advance = cstr(jv_detail.is_advance)\n\tnew_row.docstatus = 1\n\n\t# will work as update after submit\n\tjournal_entry.flags.ignore_validate_update_after_submit = True\n\tif not do_not_save:\n\t\tjournal_entry.save(ignore_permissions=True)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 75,
        "n_words": 112,
        "vocab_size": 76,
        "complexity": 7,
        "nloc": 34,
        "token_counts": 283,
        "n_ast_nodes": 495,
        "n_identifiers": 26,
        "d_id": 13890,
        "documentation": {
            "docstring": "\n\tUpdates against document, if partial amount splits into rows\n\t",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 135567,
        "commit_id": "d329147ae28c57b290f6b932f9f3044523f67c4e",
        "repo": "ray",
        "path": "rllib/utils/tests/test_actor_manager.py",
        "file_name": "test_actor_manager.py",
        "fun_name": "test_sync_call_healthy_only",
        "commit_message": "[RLlib] Introduce FaultTolerantActorManager (#29703)\n\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def test_sync_call_healthy_only(self):\n        \n        actors = [Actor.remote(i) for i in range(4)]\n        manager = FaultTolerantActorManager(actors=actors)\n\n        results = []\n        for _ in range(10):\n            results.extend(\n                manager.foreach_actor(\n                    lambda w: w.call(), healthy_only=True\n                ).ignore_errors()\n            )\n            # Wait for actors to recover.\n            wait_for_restore()\n\n        # Notice that since we only fire calls against healthy actors,\n        # we wouldn't be aware that the actors have been recovered.\n        # So once an actor is taken out of the lineup (10% chance),\n        # it will not go back in, and we should have few results here.\n        # Basically takes us 10 calls to kill all the actors.\n        # Note that we can hardcode 10 here because we are using deterministic\n        # sequences of random numbers.\n        self.assertEqual(len(results), 10)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 298,
        "n_words": 114,
        "vocab_size": 86,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 83,
        "n_ast_nodes": 144,
        "n_identifiers": 20,
        "d_id": 30658,
        "documentation": {
            "docstring": "Test synchronous remote calls to only healthy actors.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 71720,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/pages/test_revisions.py",
        "file_name": "test_revisions.py",
        "fun_name": "test_base_form_class_used",
        "commit_message": "Reformat with black",
        "code": "def test_base_form_class_used(self):\n        \n        edit_url = reverse(\n            \"wagtailadmin_pages:add\",\n            args=(\"tests\", \"formclassadditionalfieldpage\", self.test_page.id),\n        )\n        response = self.client.get(edit_url)\n        self.assertContains(\n            response,\n            '<input type=\"text\" name=\"code\" required id=\"id_code\" maxlength=\"5\" />',\n            html=True,\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 121,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 50,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 15715,
        "documentation": {
            "docstring": "First ensure that the non-model field is appearing in edit.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 257346,
        "commit_id": "f6e3a639063887f9f5b27f574a04c7fe602b3185",
        "repo": "haystack",
        "path": "haystack/pipelines/base.py",
        "file_name": "base.py",
        "fun_name": "components",
        "commit_message": "Prevent losing names of utilized components when loaded from config (#2525)\n\n* Prevent losing names of utilized components when loaded from config\r\n\r\n* Update Documentation & Code Style\r\n\r\n* update test\r\n\r\n* fix failing tests\r\n\r\n* Update Documentation & Code Style\r\n\r\n* fix even more tests\r\n\r\n* Update Documentation & Code Style\r\n\r\n* incorporate review feedback\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def components(self) -> Dict[str, BaseComponent]:\n        \n        all_components = self._find_all_components()\n        return {component.name: component for component in all_components if component.name is not None}\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 41,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 39,
        "n_ast_nodes": 61,
        "n_identifiers": 9,
        "d_id": 75070,
        "documentation": {
            "docstring": "\n        Returns all components used by this pipeline.\n        Note that this also includes such components that are being utilized by other components only and are not being used as a pipeline node directly.\n        ",
            "n_words": 32,
            "vocab_size": 24,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 163213,
        "commit_id": "b5c6e4713ae4397cd047cb41f11aca4d27fb6096",
        "repo": "pandas",
        "path": "pandas/core/indexing.py",
        "file_name": "indexing.py",
        "fun_name": "_ensure_iterable_column_indexer",
        "commit_message": "CLN: suppress warnings (#45212)",
        "code": "def _ensure_iterable_column_indexer(self, column_indexer):\n        \n        ilocs: Sequence[int]\n        if is_integer(column_indexer):\n            ilocs = [column_indexer]\n        elif isinstance(column_indexer, slice):\n            ilocs = np.arange(len(self.obj.columns))[column_indexer]\n        elif isinstance(column_indexer, np.ndarray) and is_bool_dtype(\n            column_indexer.dtype\n        ):\n            ilocs = np.arange(len(column_indexer))[column_indexer]\n        else:\n            ilocs = column_indexer\n        return ilocs\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 143,
        "n_words": 32,
        "vocab_size": 23,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 89,
        "n_ast_nodes": 143,
        "n_identifiers": 17,
        "d_id": 39403,
        "documentation": {
            "docstring": "\n        Ensure that our column indexer is something that can be iterated over.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 168252,
        "commit_id": "2f8d0a36703e81e4dca52ca9fe4f58c910c1b304",
        "repo": "pandas",
        "path": "pandas/core/indexes/range.py",
        "file_name": "range.py",
        "fun_name": "_start",
        "commit_message": "PERF cache find_stack_level (#48023)\n\ncache stacklevel",
        "code": "def _start(self) -> int:\n        \n        warnings.warn(\n            self._deprecation_message.format(\"_start\", \"start\"),\n            FutureWarning,\n            stacklevel=find_stack_level(inspect.currentframe()),\n        )\n        return self.start\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 73,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 41,
        "n_ast_nodes": 69,
        "n_identifiers": 13,
        "d_id": 40259,
        "documentation": {
            "docstring": "\n        The value of the `start` parameter (``0`` if this was not supplied).\n\n         .. deprecated:: 0.25.0\n            Use ``start`` instead.\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 247957,
        "commit_id": "2e2d8cc2f9b9af5f8b48d75e22c474e08feca236",
        "repo": "synapse",
        "path": "tests/rest/admin/test_server_notice.py",
        "file_name": "test_server_notice.py",
        "fun_name": "test_update_notice_user_name_when_changed",
        "commit_message": "Update the server notices user profile in room if changed. (#12115)",
        "code": "def test_update_notice_user_name_when_changed(self) -> None:\n        \n        server_notice_request_content = {\n            \"user_id\": self.other_user,\n            \"content\": {\"msgtype\": \"m.text\", \"body\": \"test msg one\"},\n        }\n\n        self.make_request(\n            \"POST\",\n            self.url,\n            access_token=self.admin_user_tok,\n            content=server_notice_request_content,\n        )\n\n        # simulate a change in server config after a server restart.\n        new_display_name = \"new display name\"\n        self.server_notices_manager._config.servernotices.server_notices_mxid_display_name = (\n            new_display_name\n        )\n        self.server_notices_manager.get_or_create_notice_room_for_user.cache.invalidate_all()\n\n        self.make_request(\n            \"POST\",\n            self.url,\n            access_token=self.admin_user_tok,\n            content=server_notice_request_content,\n        )\n\n        invited_rooms = self._check_invite_and_join_status(self.other_user, 1, 0)\n        notice_room_id = invited_rooms[0].room_id\n        self.helper.join(\n            room=notice_room_id, user=self.other_user, tok=self.other_user_token\n        )\n\n        notice_user_state_in_room = self.helper.get_state(\n            notice_room_id,\n            \"m.room.member\",\n            self.other_user_token,\n            state_key=\"@notices:test\",\n        )\n        self.assertEqual(notice_user_state_in_room[\"displayname\"], new_display_name)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 383,
        "n_words": 74,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 38,
        "token_counts": 175,
        "n_ast_nodes": 282,
        "n_identifiers": 31,
        "d_id": 72024,
        "documentation": {
            "docstring": "\n        Tests that existing server notices user name in room is updated after\n        server notice config changes.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 249764,
        "commit_id": "6a6e1e8c0711939338f25d8d41d1e4d33d984949",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "_create_basic_room",
        "commit_message": "Fix room creation being rate limited too aggressively since Synapse v1.69.0. (#14314)\n\n* Introduce a test for the old behaviour which we want to restore\r\n\r\n* Reintroduce the old behaviour in a simpler way\r\n\r\n* Newsfile\r\n\r\nSigned-off-by: Olivier Wilkinson (reivilibre) <oliverw@matrix.org>\r\n\r\n* Use 1 credit instead of 2 for creating a room: be more lenient than before\r\n\r\nNotably, the UI in Element Web was still broken after restoring to prior behaviour.\r\n\r\nAfter discussion, we agreed that it would be sensible to increase the limit.\r\n\r\nSigned-off-by: Olivier Wilkinson (reivilibre) <oliverw@matrix.org>",
        "code": "def _create_basic_room(self) -> Tuple[int, object]:\n        \n        channel = self.make_request(\n            \"POST\",\n            \"/createRoom\",\n            {},\n        )\n        return channel.code, channel.json_body\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 76,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 35,
        "n_ast_nodes": 58,
        "n_identifiers": 9,
        "d_id": 73110,
        "documentation": {
            "docstring": "\n        Tries to create a basic room and returns the response code.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 155711,
        "commit_id": "5e8a4813cf948250608b16747773a7dc52088eb6",
        "repo": "dask",
        "path": "dask/dataframe/methods.py",
        "file_name": "methods.py",
        "fun_name": "boundary_slice",
        "commit_message": "Deprecate `is_monotonic` (#8653)\n\nThis PR deprecates `is_monotonic` to follow what `pandas` is doing upstream. This also resolves some test failures in our `upstream` build",
        "code": "def boundary_slice(df, start, stop, right_boundary=True, left_boundary=True, kind=None):\n    \n    if len(df.index) == 0:\n        return df\n\n    if PANDAS_GT_131:\n        if kind is not None:\n            warnings.warn(\n                \"The `kind` argument is no longer used/supported. \"\n                \"It will be dropped in a future release.\",\n                category=FutureWarning,\n            )\n        kind_opts = {}\n        kind = \"loc\"\n    else:\n        kind = kind or \"loc\"\n        kind_opts = {\"kind\": kind}\n\n    if kind == \"loc\" and not df.index.is_monotonic_increasing:\n        # Pandas treats missing keys differently for label-slicing\n        # on monotonic vs. non-monotonic indexes\n        # If the index is monotonic, `df.loc[start:stop]` is fine.\n        # If it's not, `df.loc[start:stop]` raises when `start` is missing\n        if start is not None:\n            if left_boundary:\n                df = df[df.index >= start]\n            else:\n                df = df[df.index > start]\n        if stop is not None:\n            if right_boundary:\n                df = df[df.index <= stop]\n            else:\n                df = df[df.index < stop]\n        return df\n\n    result = getattr(df, kind)[start:stop]\n    if not right_boundary and stop is not None:\n        right_index = result.index.get_slice_bound(stop, \"left\", **kind_opts)\n        result = result.iloc[:right_index]\n    if not left_boundary and start is not None:\n        left_index = result.index.get_slice_bound(start, \"right\", **kind_opts)\n        result = result.iloc[left_index:]\n    return result\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 488,
        "n_words": 171,
        "vocab_size": 95,
        "complexity": 15,
        "nloc": 35,
        "token_counts": 233,
        "n_ast_nodes": 378,
        "n_identifiers": 22,
        "d_id": 36453,
        "documentation": {
            "docstring": "Index slice start/stop. Can switch include/exclude boundaries.\n\n    Examples\n    --------\n    >>> df = pd.DataFrame({'x': [10, 20, 30, 40, 50]}, index=[1, 2, 2, 3, 4])\n    >>> boundary_slice(df, 2, None)\n        x\n    2  20\n    2  30\n    3  40\n    4  50\n    >>> boundary_slice(df, 1, 3)\n        x\n    1  10\n    2  20\n    2  30\n    3  40\n    >>> boundary_slice(df, 1, 3, right_boundary=False)\n        x\n    1  10\n    2  20\n    2  30\n\n    Empty input DataFrames are returned\n\n    >>> df_empty = pd.DataFrame()\n    >>> boundary_slice(df_empty, 1, 3)\n    Empty DataFrame\n    Columns: []\n    Index: []\n    ",
            "n_words": 80,
            "vocab_size": 49,
            "n_whitespaces": 184,
            "language": "en"
        }
    },
    {
        "id": 53859,
        "commit_id": "f97603bba836c215e153d7d3d5b3b9de4d0ae822",
        "repo": "prefect",
        "path": "src/prefect/task_runners.py",
        "file_name": "task_runners.py",
        "fun_name": "_ray",
        "commit_message": "First draft `RayTaskRunner` implementation",
        "code": "def _ray(self) -> \"ray\":\n        \n        global ray\n\n        if ray is None:\n            try:\n                import ray\n            except ImportError as exc:\n                raise RuntimeError(\n                    \"Using the `RayTaskRunner` requires `ray` to be installed.\"\n                ) from exc\n\n        return ray\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 146,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 33,
        "n_ast_nodes": 61,
        "n_identifiers": 6,
        "d_id": 10926,
        "documentation": {
            "docstring": "\n        Delayed import of `ray` allowing configuration of the task runner\n        without the extra installed and improves `prefect` import times.\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 27993,
        "commit_id": "5d1a36b9aaf408016957db04f86397b2e53c2500",
        "repo": "saleor",
        "path": "saleor/thumbnail/utils.py",
        "file_name": "utils.py",
        "fun_name": "preprocess_WEBP",
        "commit_message": "Better media thumbnails including WebP support (#9988)\n\n* Add thumbnail app\r\n\r\n* Update get_thumbnail_size method and add tests\r\n\r\n* Add logic for creating thumbnails\r\n\r\n* Update logic for getting thumbnail\r\n\r\n* Allow defining format for tumbnail generation\r\n\r\n* Clear handle_thumbnail views\r\n\r\n* Add prepare_image_proxy_url method\r\n\r\n* Use ImageField for user avatar\r\n\r\n* Allow defining thumbnail format when querying user avatar\r\n\r\n* Use ImageField for category backgound_image\r\n\r\n* Use ImageField for Collection backgound_image\r\n\r\n* Use ImageField for ProductMedia image\r\n\r\n* Ensure that thumbnails are deleted when category background_image is changed or deleted\r\n\r\n* Ensure that thumbnails are deleted when collection background_image is changed or deleted\r\n\r\n* Update product media deleteion task and failing tests\r\n\r\n* Delete thumbnail from storage when thumbnail objects is deleted\r\n\r\n* Fix import in product test_bulk_delete\r\n\r\n* Drop create_thumbnails command\r\n\r\n* Update Product.thumbnail resolver\r\n\r\n* Update OrderLine thumbnail resolver\r\n\r\n* Add missing ADDED_IN_35 and PREVIEW_FEATURE labels\r\n\r\n* Update account and product signals - ensure the image is deleted from storage\r\n\r\n* Refactor product_images methods\r\n\r\n* Add signal for product media image delete\r\n\r\n* Drop create_thumbnails method and not longer valid settings fields\r\n\r\n* Clean the ProcessedImage class\r\n\r\n* Drop versatileimagefield from INSTALLED_APPS\r\n\r\n* Update changelog\r\n\r\n* Drop comments from ThumbnailFormat\r\n\r\n* Add get_image_or_proxy_url method\r\n\r\n* Apply reiew suggestions - add ThumbnailField and use get_image_or_proxy_ur when it's possible\r\n\r\n* Update changelog\r\n\r\n* Replace ADDED_IN_35 with ADDED_IN_36 label\r\n\r\n* Update changelog\r\n\r\nCo-authored-by: Marcin Gębala <5421321+maarcingebala@users.noreply.github.com>",
        "code": "def preprocess_WEBP(self, image):\n        \n        save_kwargs = {\n            \"quality\": self.WEBP_QUAL,\n            \"lossless\": self.LOSSLESS_WEBP,\n            \"icc_profile\": image.info.get(\"icc_profile\", \"\"),\n        }\n\n        return (image, save_kwargs)\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 78,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 43,
        "n_ast_nodes": 74,
        "n_identifiers": 8,
        "d_id": 5150,
        "documentation": {
            "docstring": "Receive a PIL Image instance of a WEBP and return 2-tuple.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 199697,
        "commit_id": "d1d46df73ebaad94089847558d00a8b7269f554d",
        "repo": "sympy",
        "path": "sympy/polys/orthopolys.py",
        "file_name": "orthopolys.py",
        "fun_name": "spherical_bessel_fn",
        "commit_message": "Run orthopolys and appellseqs through a common interface\n\nIncluding unifying the two Chebyshev generators into one function.\nThere are also two kinds of Hermite polynomials, and they too share the\nsame recurrence, but the second type He_n(x) (aka the probabilist,\nreduced or small polynomials) will not be added here.",
        "code": "def spherical_bessel_fn(n, x=None, polys=False):\n    \n    if x is None:\n        x = Dummy(\"x\")\n    f = dup_spherical_bessel_fn_minus if n < 0 else dup_spherical_bessel_fn\n    return named_poly(abs(n), f, ZZ, \"\", (QQ(1)/x,), polys)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 46,
        "n_words": 27,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 60,
        "n_ast_nodes": 93,
        "n_identifiers": 12,
        "d_id": 49353,
        "documentation": {
            "docstring": "\n    Coefficients for the spherical Bessel functions.\n\n    These are only needed in the jn() function.\n\n    The coefficients are calculated from:\n\n    fn(0, z) = 1/z\n    fn(1, z) = 1/z**2\n    fn(n-1, z) + fn(n+1, z) == (2*n+1)/z * fn(n, z)\n\n    Parameters\n    ==========\n\n    n : int\n        Degree of the polynomial.\n    x : optional\n    polys : bool, optional\n        If True, return a Poly, otherwise (default) return an expression.\n\n    Examples\n    ========\n\n    >>> from sympy.polys.orthopolys import spherical_bessel_fn as fn\n    >>> from sympy import Symbol\n    >>> z = Symbol(\"z\")\n    >>> fn(1, z)\n    z**(-2)\n    >>> fn(2, z)\n    -1/z + 3/z**3\n    >>> fn(3, z)\n    -6/z**2 + 15/z**4\n    >>> fn(4, z)\n    1/z - 45/z**3 + 105/z**5\n\n    ",
            "n_words": 105,
            "vocab_size": 75,
            "n_whitespaces": 195,
            "language": "en"
        }
    },
    {
        "id": 321054,
        "commit_id": "d47cfd99d7374a41b4c228c21221c7850e65d0b1",
        "repo": "qutebrowser",
        "path": "qutebrowser/misc/backendproblem.py",
        "file_name": "backendproblem.py",
        "fun_name": "_try_import_backends",
        "commit_message": "Run scripts/dev/rewrite_qt_imports.sh",
        "code": "def _try_import_backends(self) -> _BackendImports:\n        \n        # pylint: disable=unused-import\n        results = _BackendImports()\n\n        try:\n            from qutebrowser.qt import webkit as QtWebKit\n            from qutebrowser.qt.webkit import qWebKitVersion\n            from qutebrowser.qt import webkit as QtWebKitWidgets\n        except (ImportError, ValueError) as e:\n            results.webkit_error = str(e)\n        else:\n            if not qtutils.is_new_qtwebkit():\n                results.webkit_error = \"Unsupported legacy QtWebKit found\"\n\n        try:\n            from qutebrowser.qt import webengine as QtWebEngineWidgets\n        except (ImportError, ValueError) as e:\n            results.webengine_error = str(e)\n\n        return results\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 217,
        "n_words": 62,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 100,
        "n_ast_nodes": 166,
        "n_identifiers": 20,
        "d_id": 117494,
        "documentation": {
            "docstring": "Check whether backends can be imported and return BackendImports.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 305503,
        "commit_id": "1bc8770b51658f0dc1bd076b392d70be5a7433bc",
        "repo": "core",
        "path": "tests/components/google_assistant/test_smart_home.py",
        "file_name": "test_smart_home.py",
        "fun_name": "test_sync_in_area",
        "commit_message": "Remove area_id from entity_registry.async_get_or_create (#77700)\n\n* Remove area_id from entity_registry.async_get_or_create\r\n\r\n* Adjust tests\r\n\r\n* Fix lying comment in test",
        "code": "async def test_sync_in_area(area_on_device, hass, registries):\n    \n    area = registries.area.async_create(\"Living Room\")\n\n    device = registries.device.async_get_or_create(\n        config_entry_id=\"1234\",\n        manufacturer=\"Someone\",\n        model=\"Some model\",\n        sw_version=\"Some Version\",\n        connections={(device_registry.CONNECTION_NETWORK_MAC, \"12:34:56:AB:CD:EF\")},\n    )\n    registries.device.async_update_device(\n        device.id, area_id=area.id if area_on_device else None\n    )\n\n    entity = registries.entity.async_get_or_create(\n        \"light\",\n        \"test\",\n        \"1235\",\n        suggested_object_id=\"demo_light\",\n        device_id=device.id,\n    )\n    entity = registries.entity.async_update_entity(\n        entity.entity_id, area_id=area.id if not area_on_device else None\n    )\n\n    light = DemoLight(\n        None,\n        \"Demo Light\",\n        state=False,\n        hs_color=(180, 75),\n        effect_list=LIGHT_EFFECT_LIST,\n        effect=LIGHT_EFFECT_LIST[0],\n    )\n    light.hass = hass\n    light.entity_id = entity.entity_id\n    await light.async_update_ha_state()\n\n    config = MockConfig(should_expose=lambda _: True, entity_config={})\n\n    events = async_capture_events(hass, EVENT_SYNC_RECEIVED)\n\n    result = await sh.async_handle_message(\n        hass,\n        config,\n        \"test-agent\",\n        {\"requestId\": REQ_ID, \"inputs\": [{\"intent\": \"action.devices.SYNC\"}]},\n        const.SOURCE_CLOUD,\n    )\n\n    assert result == {\n        \"requestId\": REQ_ID,\n        \"payload\": {\n            \"agentUserId\": \"test-agent\",\n            \"devices\": [\n                {\n                    \"id\": \"light.demo_light\",\n                    \"name\": {\"name\": \"Demo Light\"},\n                    \"traits\": [\n                        trait.TRAIT_BRIGHTNESS,\n                        trait.TRAIT_ONOFF,\n                        trait.TRAIT_COLOR_SETTING,\n                        trait.TRAIT_MODES,\n                    ],\n                    \"type\": const.TYPE_LIGHT,\n                    \"willReportState\": False,\n                    \"attributes\": {\n                        \"availableModes\": [\n                            {\n                                \"name\": \"effect\",\n                                \"name_values\": [\n                                    {\"lang\": \"en\", \"name_synonym\": [\"effect\"]}\n                                ],\n                                \"ordered\": False,\n                                \"settings\": [\n                                    {\n                                        \"setting_name\": \"rainbow\",\n                                        \"setting_values\": [\n                                            {\n                                                \"lang\": \"en\",\n                                                \"setting_synonym\": [\"rainbow\"],\n                                            }\n                                        ],\n                                    },\n                                    {\n                                        \"setting_name\": \"none\",\n                                        \"setting_values\": [\n                                            {\"lang\": \"en\", \"setting_synonym\": [\"none\"]}\n                                        ],\n                                    },\n                                ],\n                            }\n                        ],\n                        \"colorModel\": \"hsv\",\n                        \"colorTemperatureRange\": {\n                            \"temperatureMinK\": 2000,\n                            \"temperatureMaxK\": 6535,\n                        },\n                    },\n                    \"deviceInfo\": {\n                        \"manufacturer\": \"Someone\",\n                        \"model\": \"Some model\",\n                        \"swVersion\": \"Some Version\",\n                    },\n                    \"roomHint\": \"Living Room\",\n                }\n            ],\n        },\n    }\n    await hass.async_block_till_done()\n\n    assert len(events) == 1\n    assert events[0].event_type == EVENT_SYNC_RECEIVED\n    assert events[0].data == {\"request_id\": REQ_ID, \"source\": \"cloud\"}\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 26,
        "n_whitespaces": 1944,
        "n_words": 213,
        "vocab_size": 139,
        "complexity": 3,
        "nloc": 105,
        "token_counts": 466,
        "n_ast_nodes": 798,
        "n_identifiers": 55,
        "d_id": 104292,
        "documentation": {
            "docstring": "Test a sync message where room hint comes from area.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 74901,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/documents/views/chooser.py",
        "file_name": "chooser.py",
        "fun_name": "get_document_chosen_response",
        "commit_message": "Reformat with black",
        "code": "def get_document_chosen_response(request, document):\n    \n    return render_modal_workflow(\n        request,\n        None,\n        None,\n        None,\n        json_data={\n            \"step\": \"document_chosen\",\n            \"result\": {\n                \"id\": document.id,\n                \"title\": document.title,\n                \"url\": document.url,\n                \"filename\": document.filename,\n                \"edit_link\": reverse(\"wagtaildocs:edit\", args=(document.id,)),\n            },\n        },\n    )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 187,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 74,
        "n_ast_nodes": 121,
        "n_identifiers": 11,
        "d_id": 16329,
        "documentation": {
            "docstring": "\n    helper function: given a document, return the modal workflow response that returns that\n    document back to the calling page\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 63798,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/tenacity/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "call",
        "commit_message": "upd; format",
        "code": "def call(self, *args, **kwargs):\n        \n        warnings.warn(\n            \"'call()' method is deprecated. \" + \"Use '__call__()' instead\",\n            DeprecationWarning,\n        )\n        return self.__call__(*args, **kwargs)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 69,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 34,
        "n_ast_nodes": 58,
        "n_identifiers": 8,
        "d_id": 13507,
        "documentation": {
            "docstring": "Use ``__call__`` instead because this method is deprecated.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 64559,
        "commit_id": "fe4b6771b5fd935ed278cf553c864a18e3356a33",
        "repo": "erpnext",
        "path": "erpnext/regional/report/irs_1099/irs_1099.py",
        "file_name": "irs_1099.py",
        "fun_name": "execute",
        "commit_message": "refactor: Remove dead code (#30140)",
        "code": "def execute(filters=None):\n\tfilters = filters if isinstance(filters, frappe._dict) else frappe._dict(filters)\n\tif not filters:\n\t\tfilters.setdefault('fiscal_year', get_fiscal_year(nowdate())[0])\n\t\tfilters.setdefault('company', frappe.db.get_default(\"company\"))\n\n\tregion = frappe.db.get_value(\"Company\",\n\t\tfilters={\"name\": filters.company},\n\t\tfieldname=[\"country\"])\n\n\tif region != 'United States':\n\t\treturn [], []\n\n\tcolumns = get_columns()\n\tconditions = \"\"\n\tif filters.supplier_group:\n\t\tconditions += \"AND s.supplier_group = %s\" %frappe.db.escape(filters.get(\"supplier_group\"))\n\n\tdata = frappe.db.sql(.format(conditions=conditions), {\n\t\t\t\t\"fiscal_year\": filters.fiscal_year,\n\t\t\t\t\"company\": filters.company\n\t\t\t}, as_dict=True)\n\n\treturn columns, data\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 40,
        "n_words": 59,
        "vocab_size": 46,
        "complexity": 5,
        "nloc": 41,
        "token_counts": 171,
        "n_ast_nodes": 283,
        "n_identifiers": 25,
        "d_id": 13666,
        "documentation": {
            "docstring": "\n\t\tSELECT\n\t\t\ts.supplier_group as \"supplier_group\",\n\t\t\tgl.party AS \"supplier\",\n\t\t\ts.tax_id as \"tax_id\",\n\t\t\tSUM(gl.debit_in_account_currency) AS \"payments\"\n\t\tFROM\n\t\t\t`tabGL Entry` gl\n\t\t\t\tINNER JOIN `tabSupplier` s\n\t\tWHERE\n\t\t\ts.name = gl.party\n\t\t\t\tAND s.irs_1099 = 1\n\t\t\t\tAND gl.fiscal_year = %(fiscal_year)s\n\t\t\t\tAND gl.party_type = \"Supplier\"\n\t\t\t\tAND gl.company = %(company)s\n\t\t\t\t{conditions}\n\n\t\tGROUP BY\n\t\t\tgl.party\n\n\t\tORDER BY\n\t\t\tgl.party DESC",
            "n_words": 49,
            "vocab_size": 36,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 65944,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/report/student_batch_wise_attendance/student_batch_wise_attendance.py",
        "file_name": "student_batch_wise_attendance.py",
        "fun_name": "get_student_group_strength",
        "commit_message": "style: format code with black",
        "code": "def get_student_group_strength(student_group):\n\tstudent_group_strength = frappe.db.sql(\n\t\t,\n\t\tstudent_group,\n\t)[0][0]\n\treturn student_group_strength\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 4,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 26,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 14064,
        "documentation": {
            "docstring": "select count(*) from `tabStudent Group Student`\n\t\twhere parent = %s and active=1",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 101569,
        "commit_id": "7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5",
        "repo": "faceswap",
        "path": "lib/training/preview_tk.py",
        "file_name": "preview_tk.py",
        "fun_name": "source",
        "commit_message": "Training - Use custom preview pop-out",
        "code": "def source(self) -> \"np.ndarray\":\n        \n        assert self._source is not None\n        return self._source\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 3,
        "d_id": 20979,
        "documentation": {
            "docstring": " :class:`PIL.Image.Image`: The current source preview image ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 108516,
        "commit_id": "032316bc6c7798fca6c82de24167c975f237687f",
        "repo": "matplotlib",
        "path": "lib/matplotlib/pyplot.py",
        "file_name": "pyplot.py",
        "fun_name": "summer",
        "commit_message": "Cleanup documentation generation for pyplot\n\n- remove the awkward `pyplot.plotting()` function, which only served\n  as a namespace to take up the docs for pyplot and output them via\n  `.. autofunction`\n- Instead generate the same information using `.. autosummary::`. We\n  have to list the desired methods here explicitly. I've added a test\n  that these are the same as previously auto-generated in the\n  `plotting()` docstring. If we change anything in pyplot, we'll be\n  notified through the test failure that we have to adapt the\n  autosummary list.\n- Removed the docstring generation logic\n  `_setup_pyplot_info_docstrings()`. Apart from generating the\n  `plotting()` docstring, this added docstrings to the pyplot colormap\n  setters. Instead, we now add these docstrings directly via\n  boilerplate.py\n\nCo-authored-by: Elliott Sales de Andrade <quantum.analyst@gmail.com>",
        "code": "def summer():\n    \n    set_cmap('summer')\n\n\n# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 9,
        "n_ast_nodes": 22,
        "n_identifiers": 2,
        "d_id": 23227,
        "documentation": {
            "docstring": "\n    Set the colormap to 'summer'.\n\n    This changes the default colormap as well as the colormap of the current\n    image if there is one. See ``help(colormaps)`` for more information.\n    ",
            "n_words": 28,
            "vocab_size": 22,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 246168,
        "commit_id": "901b264c0c88f39cbfb8b2229e0dc57968882658",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_all_users",
        "commit_message": "Add type hints to `tests/rest/admin` (#11851)",
        "code": "def test_all_users(self) -> None:\n        \n        self._create_users(2)\n\n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?deactivated=true\",\n            {},\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)\n        self.assertEqual(3, len(channel.json_body[\"users\"]))\n        self.assertEqual(3, channel.json_body[\"total\"])\n\n        # Check that all fields are available\n        self._check_fields(channel.json_body[\"users\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 137,
        "n_words": 30,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 96,
        "n_ast_nodes": 157,
        "n_identifiers": 16,
        "d_id": 71062,
        "documentation": {
            "docstring": "\n        List all users, including deactivated users.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 133619,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "release/tune_tests/cloud_tests/workloads/run_cloud_test.py",
        "file_name": "run_cloud_test.py",
        "fun_name": "test_ssh_sync",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_ssh_sync():\n    \n    experiment_name = \"cloud_ssh_sync\"\n    indicator_file = f\"/tmp/{experiment_name}_indicator\"\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 70,
        "n_ast_nodes": 30,
        "n_identifiers": 3,
        "d_id": 30062,
        "documentation": {
            "docstring": "\n    SSH syncing, so:\n\n        syncer=\"auto\"\n        upload_dir=None\n\n    Expected results after first checkpoint:\n\n        - 4 trials are running\n        - At least one trial ran on the head node\n        - At least one trial ran remotely\n        - Driver has trial checkpoints from head node trial\n        - Driver has trial checkpoints from remote node trials\n        - Remote trial dirs only have data for one trial\n        - Remote trial dirs have checkpoints for node-local trials\n\n    Then, remote checkpoint directories are cleaned up.\n\n    Expected results after second checkpoint:\n\n        - 4 trials are running\n        - All trials progressed with training\n\n    ",
            "n_words": 92,
            "vocab_size": 47,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 46884,
        "commit_id": "91832a42d8124b040073481fd93c54e9e64c2609",
        "repo": "airflow",
        "path": "airflow/models/mappedoperator.py",
        "file_name": "mappedoperator.py",
        "fun_name": "parse_time_mapped_ti_count",
        "commit_message": "Expand mapped tasks at DagRun.Veriy_integrity (#22679)\n\nCreate the necessary task instances for a mapped task at dagrun.verify_integrity\r\n\r\nCo-authored-by: Ash Berlin-Taylor <ash@apache.org>",
        "code": "def parse_time_mapped_ti_count(self) -> Optional[int]:\n        \n        total = 0\n\n        for value in self._get_expansion_kwargs().values():\n            if not isinstance(value, MAPPABLE_LITERAL_TYPES):\n                # None literal type encountered, so give up\n                return None\n            total += len(value)\n        return total\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 110,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 46,
        "n_ast_nodes": 77,
        "n_identifiers": 11,
        "d_id": 9032,
        "documentation": {
            "docstring": "\n        Number of mapped TaskInstances that can be created at DagRun create time.\n\n        :return: None if non-literal mapped arg encountered, or else total number of mapped TIs this task\n            should have\n        ",
            "n_words": 30,
            "vocab_size": 27,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 62143,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/util.py",
        "file_name": "util.py",
        "fun_name": "convert_path",
        "commit_message": "upd; format",
        "code": "def convert_path(pathname):\n    \n    if os.sep == '/':\n        return pathname\n    if not pathname:\n        return pathname\n    if pathname[0] == '/':\n        raise ValueError(\"path '%s' cannot be absolute\" % pathname)\n    if pathname[-1] == '/':\n        raise ValueError(\"path '%s' cannot end with '/'\" % pathname)\n\n    paths = pathname.split('/')\n    while os.curdir in paths:\n        paths.remove(os.curdir)\n    if not paths:\n        return os.curdir\n    return os.path.join(*paths)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 122,
        "n_words": 53,
        "vocab_size": 32,
        "complexity": 7,
        "nloc": 15,
        "token_counts": 93,
        "n_ast_nodes": 163,
        "n_identifiers": 11,
        "d_id": 12879,
        "documentation": {
            "docstring": "Return 'pathname' as a name that will work on the native filesystem.\n\n    The path is split on '/' and put back together again using the current\n    directory separator.  Needed because filenames in the setup script are\n    always supplied in Unix style, and have to be converted to the local\n    convention before we can actually use them in the filesystem.  Raises\n    ValueError on non-Unix-ish systems if 'pathname' either starts or\n    ends with a slash.\n    ",
            "n_words": 73,
            "vocab_size": 60,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 298084,
        "commit_id": "653805584bac4907ba6da527071bceb9d7313019",
        "repo": "core",
        "path": "homeassistant/components/lookin/coordinator.py",
        "file_name": "coordinator.py",
        "fun_name": "_async_update_data",
        "commit_message": "Improve `lookin` generic typing (#84636)",
        "code": "async def _async_update_data(self) -> _DataT:\n        \n        interval = self.update_interval\n        if (\n            interval is not None\n            and self.last_update_success\n            and self.data\n            and self.push_coordinator.active(interval)\n        ):\n            data = self.data\n        else:\n            data = await super()._async_update_data()\n        return data\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 139,
        "n_words": 31,
        "vocab_size": 23,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 57,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 97031,
        "documentation": {
            "docstring": "Fetch data only if we have not received a push inside the interval.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 110331,
        "commit_id": "383de519505964ed879c40b23ef36e90c17ebe0d",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backends/backend_ps.py",
        "file_name": "backend_ps.py",
        "fun_name": "gs_distill",
        "commit_message": "[Doc] fix more spelling and grammar",
        "code": "def gs_distill(tmpfile, eps=False, ptype='letter', bbox=None, rotated=False):\n    \n\n    if eps:\n        paper_option = \"-dEPSCrop\"\n    else:\n        paper_option = \"-sPAPERSIZE=%s\" % ptype\n\n    psfile = tmpfile + '.ps'\n    dpi = mpl.rcParams['ps.distiller.res']\n\n    cbook._check_and_log_subprocess(\n        [mpl._get_executable_info(\"gs\").executable,\n         \"-dBATCH\", \"-dNOPAUSE\", \"-r%d\" % dpi, \"-sDEVICE=ps2write\",\n         paper_option, \"-sOutputFile=%s\" % psfile, tmpfile],\n        _log)\n\n    os.remove(tmpfile)\n    shutil.move(psfile, tmpfile)\n\n    # While it is best if above steps preserve the original bounding\n    # box, there seem to be cases when it is not. For those cases,\n    # the original bbox can be restored during the pstoeps step.\n\n    if eps:\n        # For some versions of gs, above steps result in a ps file where the\n        # original bbox is no more correct. Do not adjust bbox for now.\n        pstoeps(tmpfile, bbox, rotated=rotated)\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 213,
        "n_words": 112,
        "vocab_size": 85,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 110,
        "n_ast_nodes": 189,
        "n_identifiers": 21,
        "d_id": 24070,
        "documentation": {
            "docstring": "\n    Use ghostscript's pswrite or epswrite device to distill a file.\n    This yields smaller files without illegal encapsulated postscript\n    operators. The output is low-level, converting text to outlines.\n    ",
            "n_words": 27,
            "vocab_size": 26,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 222526,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/dis.py",
        "file_name": "dis.py",
        "fun_name": "_get_const_info",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _get_const_info(const_index, const_list):\n    \n    argval = const_index\n    if const_list is not None:\n        argval = const_list[const_index]\n    return argval, repr(argval)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 36,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 49,
        "n_identifiers": 5,
        "d_id": 56617,
        "documentation": {
            "docstring": "Helper to get optional details about const references\n\n       Returns the dereferenced constant and its repr if the constant\n       list is defined.\n       Otherwise returns the constant index and its repr().\n    ",
            "n_words": 29,
            "vocab_size": 23,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 200032,
        "commit_id": "2ddc46704dffa81a5a2a8df4348bf98dff07ebd5",
        "repo": "sympy",
        "path": "sympy/physics/continuum_mechanics/truss.py",
        "file_name": "truss.py",
        "fun_name": "draw",
        "commit_message": "subs_dict added to the draw method",
        "code": "def draw(self, subs_dict=None):\n        \n        if not numpy:\n            raise ImportError(\"To use this function numpy module is required\")\n\n        x = Symbol('x')\n\n        markers = []\n        annotations = []\n        rectangles = []\n\n        node_markers = self._draw_nodes(subs_dict)\n        markers += node_markers\n\n        member_rectangles = self._draw_members()\n        rectangles += member_rectangles\n\n        support_markers = self._draw_supports()\n        markers += support_markers\n\n        load_annotations = self._draw_loads()\n        annotations += load_annotations\n\n        xmax = -INF\n        xmin = INF\n        ymax = -INF\n        ymin = INF\n\n        for node in list(self._node_coordinates):\n            xmax = max(xmax, self._node_coordinates[node][0])\n            xmin = min(xmin, self._node_coordinates[node][0])\n            ymax = max(ymax, self._node_coordinates[node][1])\n            ymin = min(ymin, self._node_coordinates[node][1])\n\n        lim = max(xmax*1.1-xmin*0.8+1, ymax*1.1-ymin*0.8+1)\n\n        if lim==xmax*1.1-xmin*0.8+1:\n            sing_plot = plot(1, (x, 1, 1), markers=markers, show=False, annotations=annotations, xlim=(xmin-0.05*lim, xmax*1.1), ylim=(xmin-0.05*lim, xmax*1.1), axis=False, rectangles=rectangles)\n        else:\n            sing_plot = plot(1, (x, 1, 1), markers=markers, show=False, annotations=annotations, xlim=(ymin-0.05*lim, ymax*1.1), ylim=(ymin-0.05*lim, ymax*1.1), axis=False, rectangles=rectangles)\n\n        return sing_plot\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 360,
        "n_words": 122,
        "vocab_size": 69,
        "complexity": 4,
        "nloc": 30,
        "token_counts": 359,
        "n_ast_nodes": 495,
        "n_identifiers": 35,
        "d_id": 49498,
        "documentation": {
            "docstring": "\n        Returns a plot object of the Truss with all its nodes, members,\n        supports and loads.\n\n        .. note::\n            The user must be careful while entering load values in their\n            directions. The draw function assumes a sign convention that\n            is used for plotting loads.\n\n            Given a right-handed coordinate system with XYZ coordinates,\n            the supports are assumed to be such that the reaction forces of a\n            pinned support is in the +X and +Y direction while those of a\n            roller support is in the +Y direction. For the load, the range\n            of angles, one can input goes all the way to 360 degrees which, in the\n            the plot is the angle that the load vector makes with the positive x-axis in the anticlockwise direction.\n\n            For example, for a 90-degree angle, the load will be a vertically\n            directed along +Y while a 270-degree angle denotes a vertical\n            load as well but along -Y.\n\n        Examples\n        ========\n\n        .. plot::\n            :context: close-figs\n            :format: doctest\n            :include-source: True\n\n            >>> from sympy.physics.continuum_mechanics.truss import Truss\n            >>> import math\n            >>> t = Truss()\n            >>> t.add_node(\"A\", -4, 0)\n            >>> t.add_node(\"B\", 0, 0)\n            >>> t.add_node(\"C\", 4, 0)\n            >>> t.add_node(\"D\", 8, 0)\n            >>> t.add_node(\"E\", 6, 2/math.sqrt(3))\n            >>> t.add_node(\"F\", 2, 2*math.sqrt(3))\n            >>> t.add_node(\"G\", -2, 2/math.sqrt(3))\n            >>> t.add_member(\"AB\",\"A\",\"B\")\n            >>> t.add_member(\"BC\",\"B\",\"C\")\n            >>> t.add_member(\"CD\",\"C\",\"D\")\n            >>> t.add_member(\"AG\",\"A\",\"G\")\n            >>> t.add_member(\"GB\",\"G\",\"B\")\n            >>> t.add_member(\"GF\",\"G\",\"F\")\n            >>> t.add_member(\"BF\",\"B\",\"F\")\n            >>> t.add_member(\"FC\",\"F\",\"C\")\n            >>> t.add_member(\"CE\",\"C\",\"E\")\n            >>> t.add_member(\"FE\",\"F\",\"E\")\n            >>> t.add_member(\"DE\",\"D\",\"E\")\n            >>> t.apply_support(\"A\",\"pinned\")\n            >>> t.apply_support(\"D\",\"roller\")\n            >>> t.apply_load(\"G\", 3, 90)\n            >>> t.apply_load(\"E\", 3, 90)\n            >>> t.apply_load(\"F\", 2, 90)\n            >>> p = t.draw()\n            >>> p\n            Plot object containing:\n            [0]: cartesian line: 1 for x over (1.0, 1.0)\n            >>> p.show()\n        ",
            "n_words": 257,
            "vocab_size": 156,
            "n_whitespaces": 813,
            "language": "en"
        }
    },
    {
        "id": 31221,
        "commit_id": "49becbaa5549b477b0d96c55f207614773c0ab42",
        "repo": "transformers",
        "path": "src/transformers/image_utils.py",
        "file_name": "image_utils.py",
        "fun_name": "center_crop",
        "commit_message": "Enable crop_center method to handle (W, H, C) images (#17626)\n\n* enable crop_center method to handle (W, H, C) images\r\n\r\n* minor style and comment edits",
        "code": "def center_crop(self, image, size):\n        \n        self._ensure_format_supported(image)\n\n        if not isinstance(size, tuple):\n            size = (size, size)\n\n        # PIL Image.size is (width, height) but NumPy array and torch Tensors have (height, width)\n        if is_torch_tensor(image) or isinstance(image, np.ndarray):\n            if image.ndim == 2:\n                image = self.expand_dims(image)\n            image_shape = image.shape[1:] if image.shape[0] in [1, 3] else image.shape[:2]\n        else:\n            image_shape = (image.size[1], image.size[0])\n\n        top = (image_shape[0] - size[0]) // 2\n        bottom = top + size[0]  # In case size is odd, (image_shape[0] + size[0]) // 2 won't give the proper result.\n        left = (image_shape[1] - size[1]) // 2\n        right = left + size[1]  # In case size is odd, (image_shape[1] + size[1]) // 2 won't give the proper result.\n\n        # For PIL Images we have a method to crop directly.\n        if isinstance(image, PIL.Image.Image):\n            return image.crop((left, top, right, bottom))\n\n        # Check if image is in (n_channels, height, width) or (height, width, n_channels) format\n        channel_first = True if image.shape[0] in [1, 3] else False\n\n        # Transpose (height, width, n_channels) format images\n        if not channel_first:\n            if isinstance(image, np.ndarray):\n                image = image.transpose(2, 0, 1)\n            if is_torch_tensor(image):\n                image = image.permute(2, 0, 1)\n\n        # Check if cropped area is within image boundaries\n        if top >= 0 and bottom <= image_shape[0] and left >= 0 and right <= image_shape[1]:\n            return image[..., top:bottom, left:right]\n\n        # Otherwise, we may need to pad if the image is too small. Oh joy...\n        new_shape = image.shape[:-2] + (max(size[0], image_shape[0]), max(size[1], image_shape[1]))\n        if isinstance(image, np.ndarray):\n            new_image = np.zeros_like(image, shape=new_shape)\n        elif is_torch_tensor(image):\n            new_image = image.new_zeros(new_shape)\n\n        top_pad = (new_shape[-2] - image_shape[0]) // 2\n        bottom_pad = top_pad + image_shape[0]\n        left_pad = (new_shape[-1] - image_shape[1]) // 2\n        right_pad = left_pad + image_shape[1]\n        new_image[..., top_pad:bottom_pad, left_pad:right_pad] = image\n\n        top += top_pad\n        bottom += top_pad\n        left += left_pad\n        right += left_pad\n\n        new_image = new_image[\n            ..., max(0, top) : min(new_image.shape[-2], bottom), max(0, left) : min(new_image.shape[-1], right)\n        ]\n\n        return new_image\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 707,
        "n_words": 301,
        "vocab_size": 156,
        "complexity": 17,
        "nloc": 42,
        "token_counts": 474,
        "n_ast_nodes": 714,
        "n_identifiers": 34,
        "d_id": 5704,
        "documentation": {
            "docstring": "\n        Crops `image` to the given size using a center crop. Note that if the image is too small to be cropped to the\n        size given, it will be padded (so the returned result has the size asked).\n\n        Args:\n            image (`PIL.Image.Image` or `np.ndarray` or `torch.Tensor` of shape (n_channels, height, width) or (height, width, n_channels)):\n                The image to resize.\n            size (`int` or `Tuple[int, int]`):\n                The size to which crop the image.\n\n        Returns:\n            new_image: A center cropped `PIL.Image.Image` or `np.ndarray` or `torch.Tensor` of shape: (n_channels,\n            height, width).\n        ",
            "n_words": 84,
            "vocab_size": 55,
            "n_whitespaces": 194,
            "language": "en"
        }
    },
    {
        "id": 270710,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/base_layer.py",
        "file_name": "base_layer.py",
        "fun_name": "input",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def input(self):\n        \n        if not self._inbound_nodes:\n            raise AttributeError(\n                \"Layer \" + self.name + \" is not connected, no input to return.\"\n            )\n        return self._get_node_attribute_at_index(0, \"input_tensors\", \"input\")\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 83,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 34,
        "n_ast_nodes": 63,
        "n_identifiers": 6,
        "d_id": 80534,
        "documentation": {
            "docstring": "Retrieves the input tensor(s) of a layer.\n\n        Only applicable if the layer has exactly one input,\n        i.e. if it is connected to one incoming layer.\n\n        Returns:\n            Input tensor or list of input tensors.\n\n        Raises:\n          RuntimeError: If called in Eager mode.\n          AttributeError: If no inbound nodes are found.\n        ",
            "n_words": 47,
            "vocab_size": 40,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 22541,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "XORcipher/XOR_cipher.py",
        "file_name": "XOR_cipher.py",
        "fun_name": "decrypt_file",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def decrypt_file(self, file, key):\n        \n\n        # precondition\n        assert isinstance(file, str) and isinstance(key, int)\n\n        try:\n            with open(file, \"r\") as fin:\n                with open(\"decrypt.out\", \"w+\") as fout:\n                    # actual encrypt-process\n                    for line in fin:\n                        fout.write(self.decrypt_string(line, key))\n\n        except:\n            return False\n\n        return True\n\n\n# Tests\n# crypt = XORCipher()\n# key = 67\n\n# # test enrcypt\n# print crypt.encrypt(\"hallo welt\",key)\n# # test decrypt\n# print crypt.decrypt(crypt.encrypt(\"hallo welt\",key), key)\n\n# # test encrypt_string\n# print crypt.encrypt_string(\"hallo welt\",key)\n\n# # test decrypt_string\n# print crypt.decrypt_string(crypt.encrypt_string(\"hallo welt\",key),key)\n\n# if (crypt.encrypt_file(\"test.txt\",key)):\n# \tprint \"encrypt successful\"\n# else:\n# \tprint \"encrypt unsuccessful\"\n\n# if (crypt.decrypt_file(\"encrypt.out\",key)):\n# \tprint \"decrypt successful\"\n# else:\n# \tprint \"decrypt unsuccessful\"\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 227,
        "n_words": 106,
        "vocab_size": 60,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 70,
        "n_ast_nodes": 141,
        "n_identifiers": 13,
        "d_id": 4357,
        "documentation": {
            "docstring": "\n        input: filename (str) and a key (int)\n        output: returns true if decrypt process was\n        successful otherwise false\n        if key not passed the method uses the key by the constructor.\n        otherwise key = 1\n        ",
            "n_words": 33,
            "vocab_size": 26,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 248275,
        "commit_id": "57f6c496d0e26b1b455de936bd950e1899a5ae25",
        "repo": "synapse",
        "path": "synapse/rest/media/v1/preview_url_resource.py",
        "file_name": "preview_url_resource.py",
        "fun_name": "_expire_url_cache_data",
        "commit_message": "URL preview cache expiry logs: INFO -> DEBUG, text clarifications (#12720)",
        "code": "async def _expire_url_cache_data(self) -> None:\n        \n\n        assert self._worker_run_media_background_jobs\n\n        now = self.clock.time_msec()\n\n        logger.debug(\"Running url preview cache expiry\")\n\n        if not (await self.store.db_pool.updates.has_completed_background_updates()):\n            logger.debug(\"Still running DB updates; skipping url preview cache expiry\")\n            return\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 86,
        "n_words": 29,
        "vocab_size": 25,
        "complexity": 12,
        "nloc": 68,
        "token_counts": 329,
        "n_ast_nodes": 92,
        "n_identifiers": 12,
        "d_id": 72189,
        "documentation": {
            "docstring": "Clean up expired url cache content, media and thumbnails.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 104387,
        "commit_id": "e35be138148333078284b942ccc9ed7b1d826f97",
        "repo": "datasets",
        "path": "src/datasets/dataset_dict.py",
        "file_name": "dataset_dict.py",
        "fun_name": "reset_format",
        "commit_message": "Update docs to new frontend/UI (#3690)\n\n* WIP: update docs to new UI\r\n\r\n* make style\r\n\r\n* Rm unused\r\n\r\n* inject_arrow_table_documentation __annotations__\r\n\r\n* hasattr(arrow_table_method, \"__annotations__\")\r\n\r\n* Update task_template.rst\r\n\r\n* Codeblock PT-TF-SPLIT\r\n\r\n* Convert loading scripts\r\n\r\n* Convert docs to mdx\r\n\r\n* Fix mdx\r\n\r\n* Add <Tip>\r\n\r\n* Convert mdx tables\r\n\r\n* Fix codeblock\r\n\r\n* Rm unneded hashlinks\r\n\r\n* Update index.mdx\r\n\r\n* Redo dev change\r\n\r\n* Rm circle ci `build_doc` & `deploy_doc`\r\n\r\n* Rm unneeded files\r\n\r\n* Update docs reamde\r\n\r\n* Standardize to `Example::`\r\n\r\n* mdx logging levels doc\r\n\r\n* Table properties inject_arrow_table_documentation\r\n\r\n* ``` to ```py mdx\r\n\r\n* Add Tips mdx\r\n\r\n* important,None -> <Tip warning={true}>\r\n\r\n* More misc\r\n\r\n* Center imgs\r\n\r\n* Update instllation page\r\n\r\n* `setup.py` docs section\r\n\r\n* Rm imgs since they are in hf.co\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* Update index mdx\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* just `Dataset` obj\r\n\r\n* Addedversion just italics\r\n\r\n* Update ReadInstruction doc example syntax\r\n\r\n* Change docstring for `prepare_for_task`\r\n\r\n* Chore\r\n\r\n* Remove `code` syntax from headings\r\n\r\n* Rm `code` syntax from headings\r\n\r\n* Hashlink backward compatability\r\n\r\n* S3FileSystem doc\r\n\r\n* S3FileSystem doc updates\r\n\r\n* index.mdx updates\r\n\r\n* Add darkmode gifs\r\n\r\n* Index logo img css classes\r\n\r\n* Index mdx dataset logo img size\r\n\r\n* Docs for DownloadMode class\r\n\r\n* Doc DownloadMode table\r\n\r\n* format docstrings\r\n\r\n* style\r\n\r\n* Add doc builder scripts (#3790)\r\n\r\n* add doc builder scripts\r\n\r\n* fix docker image\r\n\r\n* Docs new UI actions no self hosted (#3793)\r\n\r\n* No self hosted\r\n\r\n* replace doc injection by actual docstrings\r\n\r\n* Docstring formatted\r\n\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\n* Rm notebooks from docs actions since they dont exi\r\n\r\n* Update tsting branch\r\n\r\n* More docstring\r\n\r\n* Chore\r\n\r\n* bump up node version\r\n\r\n* bump up node\r\n\r\n* ``` -> ```py for audio_process.mdx\r\n\r\n* Update .github/workflows/build_documentation.yml\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\n\r\n* Uodate dev doc build\r\n\r\n* remove run on PR\r\n\r\n* fix action\r\n\r\n* Fix gh doc workflow\r\n\r\n* forgot this change when merging master\r\n\r\n* Update build doc\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>",
        "code": "def reset_format(self):\n        \n        self._check_values_type()\n        for dataset in self.values():\n            dataset.set_format()\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 40,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 25,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 21824,
        "documentation": {
            "docstring": "Reset ``__getitem__`` return format to python objects and all columns.\n        The transformation is applied to all the datasets of the dataset dictionary.\n\n        Same as ``self.set_format()``\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 118633,
        "commit_id": "704eab3478cf69847825b23dabf15813a8ac9fa2",
        "repo": "streamlit",
        "path": "lib/tests/streamlit/scriptrunner/script_runner_test.py",
        "file_name": "script_runner_test.py",
        "fun_name": "_assert_text_deltas",
        "commit_message": "Rename and refactor `Report` machinery (#4141)\n\nThis refactor renames (almost) everything related to the outdated \"report\" concept with more precise concepts that we use throughout our code, primarily \"script run\", \"session\", and \"app\".",
        "code": "def _assert_text_deltas(self, scriptrunner, text_deltas):\n        \n        self.assertEqual(text_deltas, scriptrunner.text_deltas())\n\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 22,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 26337,
        "documentation": {
            "docstring": "Asserts that the scriptrunner's ForwardMsgQueue contains text deltas\n        with the given contents.\n\n        Parameters\n        ----------\n        scriptrunner : TestScriptRunner\n        text_deltas : List[str]\n\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 156222,
        "commit_id": "261bf174931580230717abca93fe172e166cc1e8",
        "repo": "dask",
        "path": "dask/utils.py",
        "file_name": "utils.py",
        "fun_name": "typename",
        "commit_message": "Add mild typing to common utils functions (#8848)",
        "code": "def typename(typ, short=False) -> str:\n    \n    if not isinstance(typ, type):\n        return typename(type(typ))\n    try:\n        if not typ.__module__ or typ.__module__ == \"builtins\":\n            return typ.__name__\n        else:\n            if short:\n                module, *_ = typ.__module__.split(\".\")\n            else:\n                module = typ.__module__\n            return module + \".\" + typ.__name__\n    except AttributeError:\n        return str(typ)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 156,
        "n_words": 42,
        "vocab_size": 29,
        "complexity": 6,
        "nloc": 28,
        "token_counts": 88,
        "n_ast_nodes": 150,
        "n_identifiers": 12,
        "d_id": 36605,
        "documentation": {
            "docstring": "\n    Return the name of a type\n\n    Examples\n    --------\n    >>> typename(int)\n    'int'\n\n    >>> from dask.core import literal\n    >>> typename(literal)\n    'dask.core.literal'\n    >>> typename(literal, short=True)\n    'dask.literal'\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 128150,
        "commit_id": "9c39a28ba2f6221ffd8327fa21cb8294f0390fee",
        "repo": "ray",
        "path": "python/ray/data/tests/test_batch_mapper.py",
        "file_name": "test_batch_mapper.py",
        "fun_name": "test_batch_mapper_pandas_data_format",
        "commit_message": "[AIR][Numpy] Add numpy narrow waist to `Preprocessor` and `BatchMapper` (#28418)\n\nCo-authored-by: Eric Liang <ekhliang@gmail.com>\r\nCo-authored-by: Clark Zinzow <clarkzinzow@gmail.com>\r\nCo-authored-by: Amog Kamsetty <amogkamsetty@yahoo.com>",
        "code": "def test_batch_mapper_pandas_data_format(ds_with_expected_pandas_numpy_df):\n    \n    ds, expected_df, expected_numpy_df = ds_with_expected_pandas_numpy_df\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 145,
        "n_ast_nodes": 23,
        "n_identifiers": 5,
        "d_id": 28613,
        "documentation": {
            "docstring": "Tests batch mapper functionality for pandas data format.\n\n    Note:\n        For single column pandas dataframes, we automatically convert it to\n        single column tensor with column name as `__value__`.\n    ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 20845,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/rich/syntax.py",
        "file_name": "syntax.py",
        "fun_name": "lexer",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def lexer(self) -> Optional[Lexer]:\n        \n\n        if isinstance(self._lexer, Lexer):\n            return self._lexer\n        try:\n            return get_lexer_by_name(\n                self._lexer,\n                stripnl=False,\n                ensurenl=True,\n                tabsize=self.tab_size,\n            )\n        except ClassNotFound:\n            return None\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 153,
        "n_words": 21,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 54,
        "n_ast_nodes": 83,
        "n_identifiers": 12,
        "d_id": 3587,
        "documentation": {
            "docstring": "The lexer for this syntax, or None if no lexer was found.\n\n        Tries to find the lexer by name if a string was passed to the constructor.\n        ",
            "n_words": 27,
            "vocab_size": 21,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 125637,
        "commit_id": "90cea203befa8f2e86e9c1c18bb3972296358e7b",
        "repo": "ray",
        "path": "python/ray/runtime_context.py",
        "file_name": "runtime_context.py",
        "fun_name": "get_placement_group_id",
        "commit_message": "Ray 2.0 API deprecation (#26116)\n\nRay 2.0 API deprecation for:\r\n\r\n ray.remote(): placement_group\r\n ray.remote(): placement_group_bundle_index\r\n ray.remote(): placement_group_capture_child_tasks\r\n ray.get_dashboard_url()\r\n ray.get_resource_ids()\r\n ray.disconnect()\r\n ray.connect()\r\n ray.util.ActorGroup\r\n ray.util.ActorPool\r\n Add get_xx_id() to return hex (rather than object), and then deprecate the xx_id() (which returns Cython object): the xx here can be node, task etc.\r\n ray start: --plasma-store-socket-name\r\n ray start: --raylet-socket-name",
        "code": "def get_placement_group_id(self) -> Optional[str]:\n        \n        pg_id = self.worker.placement_group_id\n        return pg_id.hex() if not pg_id.is_nil() else None\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 33,
        "n_ast_nodes": 55,
        "n_identifiers": 9,
        "d_id": 27934,
        "documentation": {
            "docstring": "Get the current Placement group ID of this worker.\n\n        Returns:\n            The current placement group id in hex format of this worker.\n        ",
            "n_words": 21,
            "vocab_size": 16,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 160837,
        "commit_id": "cafec60a5e28af98fb8798049edd7942720d2d74",
        "repo": "numpy",
        "path": "numpy/testing/tests/test_utils.py",
        "file_name": "test_utils.py",
        "fun_name": "test_array_vs_scalar_is_equal",
        "commit_message": "ENH: Add strict parameter to assert_array_equal. (#21595)\n\nFixes #9542\r\n\r\nCo-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>",
        "code": "def test_array_vs_scalar_is_equal(self):\n        \n        a = np.array([1., 1., 1.])\n        b = 1.\n\n        self._test_equal(a, b)\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 50,
        "n_identifiers": 7,
        "d_id": 38756,
        "documentation": {
            "docstring": "Test comparing an array with a scalar when all values are equal.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 189736,
        "commit_id": "5b11a0e48b5564cdf02c11dd177f7f5c9f0b9f7a",
        "repo": "manim",
        "path": "manim/utils/tex_file_writing.py",
        "file_name": "tex_file_writing.py",
        "fun_name": "generate_tex_file",
        "commit_message": "Improved Error in :mod:`.utils.tex_file_writing` (#2574)\n\n* Better Error and insight\r\n\r\n* Do not use keywords as identifiers\r\n\r\n* add_tests\r\n\r\n* Nasty comma\r\n\r\n* Windows does its own thing\r\n\r\n* Use os.path.join for windows\r\n\r\n* Do not log path\r\n\r\n* Include Insights\r\n\r\n* Full stop.\r\n\r\nCo-authored-by: Darylgolden <darylgolden@gmail.com>\r\n\r\n* Full stop to test data.\r\n\r\nCo-authored-by: Darylgolden <darylgolden@gmail.com>",
        "code": "def generate_tex_file(expression, environment=None, tex_template=None):\n    \n    if tex_template is None:\n        tex_template = config[\"tex_template\"]\n    if environment is not None:\n        output = tex_template.get_texcode_for_expression_in_env(expression, environment)\n    else:\n        output = tex_template.get_texcode_for_expression(expression)\n\n    tex_dir = config.get_dir(\"tex_dir\")\n    if not os.path.exists(tex_dir):\n        os.makedirs(tex_dir)\n\n    result = os.path.join(tex_dir, tex_hash(output)) + \".tex\"\n    if not os.path.exists(result):\n        logger.info(f\"Writing {expression} to %(path)s\", {\"path\": f\"{result}\"})\n        with open(result, \"w\", encoding=\"utf-8\") as outfile:\n            outfile.write(output)\n    return result\n\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 135,
        "n_words": 55,
        "vocab_size": 41,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 140,
        "n_ast_nodes": 245,
        "n_identifiers": 23,
        "d_id": 46189,
        "documentation": {
            "docstring": "Takes a tex expression (and an optional tex environment),\n    and returns a fully formed tex file ready for compilation.\n\n    Parameters\n    ----------\n    expression : :class:`str`\n        String containing the TeX expression to be rendered, e.g. ``\\\\sqrt{2}`` or ``foo``\n    environment : Optional[:class:`str`], optional\n        The string containing the environment in which the expression should be typeset, e.g. ``align*``\n    tex_template : Optional[:class:`~.TexTemplate`], optional\n        Template class used to typesetting. If not set, use default template set via `config[\"tex_template\"]`\n\n    Returns\n    -------\n    :class:`str`\n        Path to generated TeX file\n    ",
            "n_words": 80,
            "vocab_size": 59,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 61320,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/unpacking.py",
        "file_name": "unpacking.py",
        "fun_name": "has_leading_dir",
        "commit_message": "upd; format",
        "code": "def has_leading_dir(paths):\n    # type: (Iterable[str]) -> bool\n    \n    common_prefix = None\n    for path in paths:\n        prefix, rest = split_leading_dir(path)\n        if not prefix:\n            return False\n        elif common_prefix is None:\n            common_prefix = prefix\n        elif prefix != common_prefix:\n            return False\n    return True\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 114,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 45,
        "n_ast_nodes": 76,
        "n_identifiers": 7,
        "d_id": 12506,
        "documentation": {
            "docstring": "Returns true if all the paths have the same leading path name\n    (i.e., everything is in one subdirectory in an archive)",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 3876,
        "commit_id": "2282a4ae0221b1fb88e16eca8bc14a166998d2d2",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-hubspot/unit_tests/test_source.py",
        "file_name": "test_source.py",
        "fun_name": "test_stream_with_splitting_properties_with_new_record",
        "commit_message": "🎉 Source Hubspot: Migrate to CDK (#10177)\n\n* migrate SourceHubspot to cdk\r\n\r\n* refactor discover method\r\n\r\n* change method name\r\n\r\n* deleted Client class\r\n\r\n* remove comment\r\n\r\n* added get_updated_state\r\n\r\n* fix setting initial state\r\n\r\n* fix stream_state dict key\r\n\r\n* fix cursor_field\r\n\r\n* change check test case status\r\n\r\n* refactor streams method\r\n\r\n* remove comment\r\n\r\n* remove TODOs\r\n\r\n* remove comments\r\n\r\n* fix get_updated_state\r\n\r\n* refactor chunk_read\r\n\r\n* override _read_incremental\r\n\r\n* fix unit tests\r\n\r\n* remove comments\r\n\r\n* fix test_check_connection_backoff_on_server_error\r\n\r\n* fix test_check_connection_backoff_on_server_error 2\r\n\r\n* fix test_check_connection_backoff_on_limit_reached\r\n\r\n* fix unit tests\r\n\r\n* clear comments\r\n\r\n* override read method on Source\r\n\r\n* added comments to overriding methods\r\n\r\n* some improvements\r\n\r\n* reafactor overridden _read_incremental\r\n\r\n* format code\r\n\r\n* refactor discovery\r\n\r\n* remove discover\r\n\r\n* format code 2\r\n\r\n* added return types\r\n\r\n* refactor template stream classes\r\n\r\n* remove comments\r\n\r\n* remove _name field\r\n\r\n* rename api.py to streams.py\r\n\r\n* move to HttpStream\r\n\r\n* refactor FormSubmissions\r\n\r\n* refactor Campaings\r\n\r\n* refactor ContactsListMemberships\r\n\r\n* CRMSearchStream refactor\r\n\r\n* CRMSearchStream refactor 2\r\n\r\n* CRMObjectStream refactor\r\n\r\n* DealStageHistoryStream refactor\r\n\r\n* Deals refactor\r\n\r\n* Engagements refactor\r\n\r\n* path method refactor\r\n\r\n* refactor authentication\r\n\r\n* fix check_connection\r\n\r\n* fix call parse_response\r\n\r\n* fix Engagements stream\r\n\r\n* fix CRMSearchStream\r\n\r\n* fix CRMObjectIncremental stream\r\n\r\n* override _read_incremental\r\n\r\n* remove commented codes\r\n\r\n* format code\r\n\r\n* update cdk version\r\n\r\n* fix cursor field\r\n\r\n* fix unit tests\r\n\r\n* removed client\r\n\r\n* clear comments\r\n\r\n* clear comments 2\r\n\r\n* clear comments 3\r\n\r\n* clear comments 4\r\n\r\n* override backoff_time\r\n\r\n* remove comment\r\n\r\n* format code\r\n\r\n* backoff_time modified\r\n\r\n* refactor backoff_time\r\n\r\n* format code\r\n\r\n* added return typing\r\n\r\n* format code\r\n\r\n* removed cursor_paths\r\n\r\n* bump version\r\n\r\n* updated spec and def yaml\r\n\r\nCo-authored-by: auganbay <auganenu@gmail.com>",
        "code": "def test_stream_with_splitting_properties_with_new_record(self, requests_mock, common_params, api, fake_properties_list):\n        \n\n        parsed_properties = list(split_properties(fake_properties_list))\n        self.set_mock_properties(requests_mock, \"/properties/v2/deal/properties\", fake_properties_list)\n\n        test_stream = Deals(**common_params)\n\n        deal_stage_history_response = {\n            \"deals\": [\n                {\n                    \"portalId\": 123,\n                    \"dealId\": 111,\n                    \"isDeleted\": False,\n                    \"associations\": None,\n                    \"properties\": {\n                        \"dealstage\": {\n                            \"value\": \"appointmentscheduled\",\n                            \"timestamp\": 1610533842221,\n                            \"source\": \"API\",\n                            \"sourceId\": None,\n                            \"updatedByUserId\": None,\n                            \"versions\": [\n                                {\n                                    \"name\": \"dealstage\",\n                                    \"value\": \"appointmentscheduled\",\n                                    \"timestamp\": 1610533842221,\n                                    \"source\": \"API\",\n                                    \"sourceVid\": [],\n                                    \"requestId\": \"19f07c43-b187-4ab6-9fab-4a0f261f0a8c\",\n                                }\n                            ],\n                        }\n                    },\n                    \"stateChanges\": [],\n                },\n                {\n                    \"portalId\": 123,\n                    \"dealId\": 112,\n                    \"isDeleted\": False,\n                    \"associations\": None,\n                    \"properties\": {\n                        \"dealstage\": {\n                            \"value\": \"appointmentscheduled\",\n                            \"timestamp\": 1610533911154,\n                            \"source\": \"API\",\n                            \"sourceId\": None,\n                            \"updatedByUserId\": None,\n                            \"versions\": [\n                                {\n                                    \"name\": \"dealstage\",\n                                    \"value\": \"appointmentscheduled\",\n                                    \"timestamp\": 1610533911154,\n                                    \"source\": \"API\",\n                                    \"sourceVid\": [],\n                                    \"requestId\": \"41a1eeff-569b-4193-ba80-238d3bd13f56\",\n                                }\n                            ],\n                        }\n                    },\n                    \"stateChanges\": [],\n                },\n            ]\n        }\n\n        requests_mock.register_uri(\n            \"GET\",\n            test_stream._stage_history.path(),\n            [\n                {\n                    \"json\": deal_stage_history_response,\n                    \"status_code\": 200,\n                }\n            ],\n        )\n\n        ids_list = [\"6043593519\", \"1092593519\", \"1092593518\", \"1092593517\", \"1092593516\"]\n        for property_slice in parsed_properties:\n            record_responses = [\n                {\n                    \"json\": {\n                        \"results\": [\n                            {**self.BASE_OBJECT_BODY, **{\"id\": id, \"properties\": {p: \"fake_data\" for p in property_slice}}}\n                            for id in ids_list\n                        ],\n                        \"paging\": {},\n                    },\n                    \"status_code\": 200,\n                }\n            ]\n            requests_mock.register_uri(\"GET\", f\"{test_stream.url}?properties={','.join(property_slice)}\", record_responses)\n            ids_list.append(\"1092593513\")\n\n        stream_records = list(test_stream.read_records(sync_mode=SyncMode.incremental))\n\n        assert len(stream_records) == 6\n\n\n@pytest.fixture(name=\"configured_catalog\")",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(name=\"configured_catalog\")",
        "n_ast_errors": 1,
        "ast_levels": 21,
        "n_whitespaces": 1988,
        "n_words": 177,
        "vocab_size": 92,
        "complexity": 4,
        "nloc": 88,
        "token_counts": 357,
        "n_ast_nodes": 673,
        "n_identifiers": 34,
        "d_id": 582,
        "documentation": {
            "docstring": "\n        Check working stream `workflows` with large list of properties using new functionality with splitting properties\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 261691,
        "commit_id": "86080bbd5fe9513cd42cf34148ea5907a1a9fc6c",
        "repo": "scikit-learn",
        "path": "sklearn/utils/tests/test_extmath.py",
        "file_name": "test_extmath.py",
        "fun_name": "test_cartesian_mix_types",
        "commit_message": "ENH cartesian accepts mixed dtypes arrays (#25067)\n\nCo-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com>",
        "code": "def test_cartesian_mix_types(arrays, output_dtype):\n    \n    output = cartesian(arrays)\n\n    assert output.dtype == output_dtype\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 20,
        "n_ast_nodes": 34,
        "n_identifiers": 6,
        "d_id": 76936,
        "documentation": {
            "docstring": "Check that the cartesian product works with mixed types.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 262448,
        "commit_id": "a0a9279e4b8c306875b6437f853bdcc31ee5f1cf",
        "repo": "TTS",
        "path": "TTS/vocoder/models/gan.py",
        "file_name": "gan.py",
        "fun_name": "get_optimizer",
        "commit_message": "Fix GAN optimizer order\n\ncommit 212d330929c22d0cd970be2023770dc1e39449ab\nAuthor: Edresson Casanova <edresson1@gmail.com>\nDate:   Fri Apr 29 16:29:44 2022 -0300\n\n    Fix unit test\n\ncommit 44456b0483bf42b1337a8e408ac17af38b26b1fa\nAuthor: Edresson Casanova <edresson1@gmail.com>\nDate:   Fri Apr 29 07:28:39 2022 -0300\n\n    Fix style\n\ncommit d545beadb932758eb7d1c632778fe317d467a6a4\nAuthor: Edresson Casanova <edresson1@gmail.com>\nDate:   Thu Apr 28 17:08:04 2022 -0300\n\n    Change order of HIFI-GAN optimizers to be equal than the original repository\n\ncommit 657c5442e5339581e5c09168f5212112a342d97a\nAuthor: Edresson Casanova <edresson1@gmail.com>\nDate:   Thu Apr 28 15:40:16 2022 -0300\n\n    Remove audio padding before mel spec extraction\n\ncommit 76b274e6901495ffe62ec745fd8ca9fd010f4857\nMerge: 379ccd7b 6233f4fc\nAuthor: Edresson Casanova <edresson1@gmail.com>\nDate:   Wed Apr 27 07:28:48 2022 -0300\n\n    Merge pull request #1541 from coqui-ai/comp_emb_fix\n\n    Bug fix in compute embedding without eval partition\n\ncommit 379ccd7ba6b7e7b550e7d6acf55760c6d0623ba8\nAuthor: WeberJulian <julian.weber@hotmail.fr>\nDate:   Wed Apr 27 10:42:26 2022 +0200\n\n    returns y_mask in VITS inference (#1540)\n\n    * returns y_mask\n\n    * make style",
        "code": "def get_optimizer(self) -> List:\n        \n        optimizer1 = get_optimizer(\n            self.config.optimizer, self.config.optimizer_params, self.config.lr_gen, self.model_g\n        )\n        optimizer2 = get_optimizer(\n            self.config.optimizer, self.config.optimizer_params, self.config.lr_disc, self.model_d\n        )\n        return [optimizer2, optimizer1]\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 87,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 66,
        "n_ast_nodes": 98,
        "n_identifiers": 12,
        "d_id": 77223,
        "documentation": {
            "docstring": "Initiate and return the GAN optimizers based on the config parameters.\n\n        It returnes 2 optimizers in a list. First one is for the generator and the second one is for the discriminator.\n\n        Returns:\n            List: optimizers.\n        ",
            "n_words": 35,
            "vocab_size": 26,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 120628,
        "commit_id": "b64e36b60fca9661ca2c8ae51a56fae07bf5efe6",
        "repo": "jax",
        "path": "jax/_src/lax/eigh.py",
        "file_name": "eigh.py",
        "fun_name": "_update_slice",
        "commit_message": "Make QDWH-eig implementation jit-table.\n\nMove QDWH-eig from jax._src.scipy.eigh to jax._src.lax.eigh, in preparation for using it to back `lax.eigh` in a future change.\n\nPiperOrigin-RevId: 449362382",
        "code": "def _update_slice(operand, update, start_indices, update_dims):\n  \n  operand_shape = operand.shape\n  operand = lax.pad(operand,\n                    jnp.array(0, operand.dtype),\n                    [(0, d, 0) for d in update.shape])\n  start_indices = tuple(jnp.int32(i) for i in start_indices)\n  t = lax.dynamic_slice(operand, start_indices, update.shape)\n  t = _mask(update, update_dims, t)\n  operand = lax.dynamic_update_slice(operand, t, start_indices)\n  return lax.slice(operand, [0] * operand.ndim, operand_shape)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 94,
        "n_words": 48,
        "vocab_size": 37,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 120,
        "n_ast_nodes": 173,
        "n_identifiers": 22,
        "d_id": 26903,
        "documentation": {
            "docstring": "\n  Similar to lax.dynamic_update_slice, but handles padded updates where padding\n  values should not overwrite existing values in the array.\n\n  Args:\n  operand: the array to update\n  update: the padded array to write\n  start_indices: the offset at which to write `update`.\n  update_dims: the true dimensions of the padded update `update`. Only values\n    inside the rectangle given by `update_dims` will be overwritten.",
            "n_words": 58,
            "vocab_size": 41,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 296453,
        "commit_id": "23264c8fd4a3f8bcff5961ed11cab6388d3c67a4",
        "repo": "core",
        "path": "homeassistant/components/roon/config_flow.py",
        "file_name": "config_flow.py",
        "fun_name": "async_step_link",
        "commit_message": "Improve roon integraton (#66000)\n\n* Update to new library, revise discovery to work with new library, specify port to work with new library.\r\n\r\n* Move user gui to fallback.\r\n\r\n* Revise tests.\r\n\r\n* Handle old config.\r\n\r\n* Improve debugging, refresh faster on load.\r\n\r\n* Remove duplicate.\r\n\r\n* Bump library version.\r\n\r\n* Fix docstring per review.\r\n\r\n* Review suggestion\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Review suggestion\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Add check for duplicate host.\r\n\r\n* Add error message to strings.\r\n\r\n* Tidy.\r\n\r\n* Review changes.\r\n\r\n* Remove default.\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "async def async_step_link(self, user_input=None):\n        \n        errors = {}\n        if user_input is not None:\n            # Do not authenticate if the host is already configured\n            self._async_abort_entries_match({CONF_HOST: self._host})\n\n            try:\n                info = await authenticate(\n                    self.hass, self._host, self._port, self._servers\n                )\n\n            except InvalidAuth:\n                errors[\"base\"] = \"invalid_auth\"\n            except Exception:  # pylint: disable=broad-except\n                _LOGGER.exception(\"Unexpected exception\")\n                errors[\"base\"] = \"unknown\"\n            else:\n                return self.async_create_entry(title=DEFAULT_NAME, data=info)\n\n        return self.async_show_form(step_id=\"link\", errors=errors)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 260,
        "n_words": 56,
        "vocab_size": 46,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 107,
        "n_ast_nodes": 182,
        "n_identifiers": 22,
        "d_id": 95433,
        "documentation": {
            "docstring": "Handle linking and authenticting with the roon server.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 80125,
        "commit_id": "ad65741b94f36fbe793cf15f0ab002482070cdb6",
        "repo": "wagtail",
        "path": "wagtail/tests/streamfield_migrations/test_migrations.py",
        "file_name": "test_migrations.py",
        "fun_name": "_test_migrate_stream_data",
        "commit_message": "Add tests for streamfield migration helpers\n\nCurrently failing due to wagtail-factories being broken on Wagtail 4.1: https://github.com/wagtail/wagtail-factories/issues/65",
        "code": "def _test_migrate_stream_data(self):\n        \n\n        self.apply_migration()\n\n        instances = self.model.objects.all().annotate(\n            raw_content=Cast(F(\"content\"), JSONField())\n        )\n\n        for instance in instances:\n            prev_content = self.original_raw_data[instance.id]\n            self.assertBlocksRenamed(\n                old_content=prev_content, new_content=instance.raw_content\n            )\n\n    # TODO test multiple operations applied in one migration\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 126,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 68,
        "n_ast_nodes": 113,
        "n_identifiers": 19,
        "d_id": 17011,
        "documentation": {
            "docstring": "Test whether the stream data of the model instances have been updated properly\n\n        Apply the migration and then query the raw data of the updated instances. Compare with\n        original raw data and check whether all relevant `char1` blocks have been renamed and\n        whether ids and other block types are intact.\n        ",
            "n_words": 50,
            "vocab_size": 34,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 183574,
        "commit_id": "7f27e70440c177b2a047b7f74a78ed5cd5b4b596",
        "repo": "textual",
        "path": "src/textual/_terminal_features.py",
        "file_name": "_terminal_features.py",
        "fun_name": "synchronized_output_end_sequence",
        "commit_message": "[terminal buffering] Address PR feedback",
        "code": "def synchronized_output_end_sequence(self) -> str:\n        \n        if self.synchronised_output:\n            return TERMINAL_MODES_ANSI_SEQUENCES[Mode.SynchronizedOutput][\"end_sync\"]\n        return \"\"\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 25,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 44257,
        "documentation": {
            "docstring": "\n        Returns the ANSI sequence that we should send to the terminal to tell it that\n        it should stop buffering the content we're about to send.\n        If the terminal doesn't seem to support synchronised updates the string will be empty.\n\n        Returns:\n            str: the \"synchronised output stop\" ANSI sequence. It will be ab empty string\n                if the terminal emulator doesn't seem to support the \"synchronised updates\" mode.\n        ",
            "n_words": 65,
            "vocab_size": 41,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 104765,
        "commit_id": "445107bae3fcd6ac9eeae503232960fa4ba8ccfd",
        "repo": "datasets",
        "path": "src/datasets/arrow_dataset.py",
        "file_name": "arrow_dataset.py",
        "fun_name": "num_rows",
        "commit_message": "Add code examples to API docs (#4168)\n\n* add code examples for functions related to the base dataset class\r\n\r\n* ✨ make style\r\n\r\n* 🖍 make each code example fully reproducible where applicable\r\n\r\n* 🖍 show parameter usage for some functions\r\n\r\n* 🖍 add examples for DatasetInfo functions",
        "code": "def num_rows(self) -> int:\n        \n        if self._indices is not None:\n            return self._indices.num_rows\n        return self._data.num_rows\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 45,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 28,
        "n_ast_nodes": 46,
        "n_identifiers": 5,
        "d_id": 21960,
        "documentation": {
            "docstring": "Number of rows in the dataset (same as :meth:`Dataset.__len__`).\n\n        Example:\n\n        ```py\n        >>> from datasets import load_dataset\n        >>> ds = load_dataset(\"rotten_tomatoes\", split=\"validation\")\n        >>> ds.num_rows\n        1066\n        ```\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 314397,
        "commit_id": "10dc38e0ec27f7bef990ee431459342f9c3c52b4",
        "repo": "core",
        "path": "homeassistant/components/acmeda/cover.py",
        "file_name": "cover.py",
        "fun_name": "current_cover_position",
        "commit_message": "Adjust CoverEntity property type hints in components (#73943)\n\n* Adjust CoverEntity property type hints in components\r\n\r\n* Revert changes to rflink\r\n\r\n* Revert changes to wilight",
        "code": "def current_cover_position(self) -> int | None:\n        \n        position = None\n        if self.roller.type != 7:\n            position = 100 - self.roller.closed_percent\n        return position\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 59,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 33,
        "n_ast_nodes": 55,
        "n_identifiers": 7,
        "d_id": 113004,
        "documentation": {
            "docstring": "Return the current position of the roller blind.\n\n        None is unknown, 0 is closed, 100 is fully open.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 167449,
        "commit_id": "e48c9c3973286e257f6da1966c91806d86b917e0",
        "repo": "pandas",
        "path": "pandas/io/parsers/readers.py",
        "file_name": "readers.py",
        "fun_name": "TextParser",
        "commit_message": "TYP: more return annotations for io/* (#47524)\n\n* TYP: more return annotations for io/*\r\n\r\n* import future",
        "code": "def TextParser(*args, **kwds) -> TextFileReader:\n    \n    kwds[\"engine\"] = \"python\"\n    return TextFileReader(*args, **kwds)\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 58,
        "token_counts": 27,
        "n_ast_nodes": 49,
        "n_identifiers": 4,
        "d_id": 40021,
        "documentation": {
            "docstring": "\n    Converts lists of lists/tuples into DataFrames with proper type inference\n    and optional (e.g. string to datetime) conversion. Also enables iterating\n    lazily over chunks of large files\n\n    Parameters\n    ----------\n    data : file-like object or list\n    delimiter : separator character to use\n    dialect : str or csv.Dialect instance, optional\n        Ignored if delimiter is longer than 1 character\n    names : sequence, default\n    header : int, default 0\n        Row to use to parse column labels. Defaults to the first row. Prior\n        rows will be discarded\n    index_col : int or list, optional\n        Column or columns to use as the (possibly hierarchical) index\n    has_index_names: bool, default False\n        True if the cols defined in index_col have an index name and are\n        not in the header.\n    na_values : scalar, str, list-like, or dict, optional\n        Additional strings to recognize as NA/NaN.\n    keep_default_na : bool, default True\n    thousands : str, optional\n        Thousands separator\n    comment : str, optional\n        Comment out remainder of line\n    parse_dates : bool, default False\n    keep_date_col : bool, default False\n    date_parser : function, optional\n    skiprows : list of integers\n        Row numbers to skip\n    skipfooter : int\n        Number of line at bottom of file to skip\n    converters : dict, optional\n        Dict of functions for converting values in certain columns. Keys can\n        either be integers or column labels, values are functions that take one\n        input argument, the cell (not column) content, and return the\n        transformed content.\n    encoding : str, optional\n        Encoding to use for UTF when reading/writing (ex. 'utf-8')\n    squeeze : bool, default False\n        returns Series if only one column.\n    infer_datetime_format: bool, default False\n        If True and `parse_dates` is True for a column, try to infer the\n        datetime format based on the first datetime string. If the format\n        can be inferred, there often will be a large parsing speed-up.\n    float_precision : str, optional\n        Specifies which converter the C engine should use for floating-point\n        values. The options are `None` or `high` for the ordinary converter,\n        `legacy` for the original lower precision pandas converter, and\n        `round_trip` for the round-trip converter.\n\n        .. versionchanged:: 1.2\n    ",
            "n_words": 331,
            "vocab_size": 197,
            "n_whitespaces": 588,
            "language": "en"
        }
    },
    {
        "id": 204805,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/base.py",
        "file_name": "base.py",
        "fun_name": "_nodb_cursor",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _nodb_cursor(self):\n        \n        conn = self.__class__({**self.settings_dict, \"NAME\": None}, alias=NO_DB_ALIAS)\n        try:\n            with conn.cursor() as cursor:\n                yield cursor\n        finally:\n            conn.close()\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 82,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 85,
        "n_identifiers": 9,
        "d_id": 50892,
        "documentation": {
            "docstring": "\n        Return a cursor from an alternative connection to be used when there is\n        no need to access the main database, specifically for test db\n        creation/deletion. This also prevents the production database from\n        being exposed to potential child threads while (or after) the test\n        database is destroyed. Refs #10868, #17786, #16969.\n        ",
            "n_words": 50,
            "vocab_size": 42,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 131451,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tests/test_command_runner.py",
        "file_name": "test_command_runner.py",
        "fun_name": "test_command_runner_interface_abstraction_violation",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_command_runner_interface_abstraction_violation():\n    \n\n    cmd_runner_interface_public_functions = dir(CommandRunnerInterface)\n    allowed_public_interface_functions = {\n        func\n        for func in cmd_runner_interface_public_functions\n        if not func.startswith(\"_\")\n    }\n    for subcls in [SSHCommandRunner, DockerCommandRunner, KubernetesCommandRunner]:\n        subclass_available_functions = dir(subcls)\n        subclass_public_functions = {\n            func for func in subclass_available_functions if not func.startswith(\"_\")\n        }\n        assert allowed_public_interface_functions == subclass_public_functions\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 117,
        "n_words": 42,
        "vocab_size": 23,
        "complexity": 6,
        "nloc": 13,
        "token_counts": 66,
        "n_ast_nodes": 108,
        "n_identifiers": 13,
        "d_id": 29533,
        "documentation": {
            "docstring": "Enforces the CommandRunnerInterface functions on the subclasses.\n\n    This is important to make sure the subclasses do not violate the\n    function abstractions. If you need to add a new function to one of\n    the CommandRunnerInterface subclasses, you have to add it to\n    CommandRunnerInterface and all of its subclasses.\n    ",
            "n_words": 47,
            "vocab_size": 32,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 96190,
        "commit_id": "cf30c11a194aa5e61d8d7c7fc506764f846fcf82",
        "repo": "sentry",
        "path": "src/sentry/search/events/builder.py",
        "file_name": "builder.py",
        "fun_name": "resolve_granularity",
        "commit_message": "feat(MEP): Add initial framework for metric queries (#31649)\n\n- This adds a MetricsQueryBuilder, which works very similarily to our\r\n  QueryBuilder, but with specific handlers for how metrics construct\r\n  queries\r\n- This MetricsQueryBuilder does not yet construct snql queries, and will\r\n  not because table queries will require multiple queries to construct\r\n  similar table data\r\n  - that is, if we want [transaction, p95, count_unique(user)], we need\r\n    a query against distributions with [transaction, p95] followed by a\r\n    second query for [transaction, count_unique(user)] against the sets\r\n    table\r\n    - This is so we can maintain a sortby",
        "code": "def resolve_granularity(self) -> Granularity:\n        \n        start = cast(datetime, self.params[\"start\"])\n        end = cast(datetime, self.params[\"end\"])\n        duration = (end - start).seconds\n\n        # TODO: could probably allow some leeway on the start & end (a few minutes) and use a bigger granularity\n        # eg. yesterday at 11:59pm to tomorrow at 12:01am could still use the day bucket\n\n        # Query is at least an hour\n        if start.minute == end.minute == 0 and duration % 3600 == 0:\n            # we're going from midnight -> midnight which aligns with our daily buckets\n            if start.hour == end.hour == 0 and duration % 86400 == 0:\n                granularity = 86400\n            # we're roughly going from start of hour -> next which aligns with our hourly buckets\n            else:\n                granularity = 3600\n        # We're going from one random minute to another, we could use the 10s bucket, but no reason for that precision\n        # here\n        else:\n            granularity = 60\n        return Granularity(granularity)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 317,
        "n_words": 148,
        "vocab_size": 91,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 95,
        "n_ast_nodes": 160,
        "n_identifiers": 13,
        "d_id": 19289,
        "documentation": {
            "docstring": "Granularity impacts metric queries even when they aren't timeseries because the data needs to be\n        pre-aggregated\n\n        Granularity is determined by checking the alignment of our start & end timestamps with the timestamps in\n        snuba. eg. we can only use the daily granularity if the query starts and ends at midnight\n        Seconds are ignored under the assumption that there currently isn't a valid use case to have\n        to-the-second accurate information\n        ",
            "n_words": 69,
            "vocab_size": 60,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 125751,
        "commit_id": "5030a4c1d384e4bb1a25169384d7465e718e99a5",
        "repo": "ray",
        "path": "rllib/connectors/tests/test_agent.py",
        "file_name": "test_agent.py",
        "fun_name": "test_vr_connector_respects_training_or_inference_vr_flags",
        "commit_message": "[RLlib] Simplify agent collector (#26803)",
        "code": "def test_vr_connector_respects_training_or_inference_vr_flags(self):\n        \n        view_rq_dict = {\n            \"both\": ViewRequirement(\n                \"obs\", used_for_training=True, used_for_compute_actions=True\n            ),\n            \"only_inference\": ViewRequirement(\n                \"obs\", used_for_training=False, used_for_compute_actions=True\n            ),\n            \"none\": ViewRequirement(\n                \"obs\", used_for_training=False, used_for_compute_actions=False\n            ),\n            \"only_training\": ViewRequirement(\n                \"obs\", used_for_training=True, used_for_compute_actions=False\n            ),\n        }\n\n        obs_arr = np.array([0, 1, 2, 3])\n        agent_data = dict(obs=obs_arr)\n        data = AgentConnectorDataType(0, 1, agent_data)\n\n        ctx = ConnectorContext(view_requirements=view_rq_dict)\n\n        # TODO @jun What is the expected behavior of this test?\n        for_action_expected_list = [\n            # is_training = False\n            SampleBatch({\"both\": obs_arr, \"only_inference\": obs_arr}),\n            # is_training = True\n            SampleBatch({\"both\": obs_arr, \"only_inference\": obs_arr}),\n        ]\n\n        for_training_expected_list = [\n            # is_training = False\n            None,\n            # is_training = True\n            agent_data,\n        ]\n\n        for is_training in [True, False]:\n            c = ViewRequirementAgentConnector(ctx)\n            c.is_training(is_training)\n            processed = c([data])\n\n            for_training = processed[0].data.for_training\n            for_training_expected = for_training_expected_list[is_training]\n            for_action = processed[0].data.for_action\n            for_action_expected = for_action_expected_list[is_training]\n\n            print(\"-\" * 30)\n            print(f\"is_training = {is_training}\")\n            print(\"for action:\")\n            print(for_action)\n            print(\"for training:\")\n            print(for_training)\n\n            # TODO @jun is for_training expected to always be equal to data?\n            check(for_training, for_training_expected)\n            check(for_action, for_action_expected)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 647,
        "n_words": 144,
        "vocab_size": 88,
        "complexity": 2,
        "nloc": 43,
        "token_counts": 250,
        "n_ast_nodes": 414,
        "n_identifiers": 30,
        "d_id": 27968,
        "documentation": {
            "docstring": "Tests that the connector respects the flags within view_requirements (i.e.\n        used_for_training, used_for_compute_actions) under different is_training modes.\n        For inference,\n            the returned data should be state -> obs\n        For training,\n            the returned data should be the data itself. The higher level policy\n            collector in env_runner will construct the proper data structure.\n        ",
            "n_words": 49,
            "vocab_size": 37,
            "n_whitespaces": 110,
            "language": "en"
        }
    },
    {
        "id": 204647,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/management/commands/loaddata.py",
        "file_name": "loaddata.py",
        "fun_name": "fixture_dirs",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def fixture_dirs(self):\n        \n        dirs = []\n        fixture_dirs = settings.FIXTURE_DIRS\n        if len(fixture_dirs) != len(set(fixture_dirs)):\n            raise ImproperlyConfigured(\"settings.FIXTURE_DIRS contains duplicates.\")\n        for app_config in apps.get_app_configs():\n            app_label = app_config.label\n            app_dir = os.path.join(app_config.path, \"fixtures\")\n            if app_dir in fixture_dirs:\n                raise ImproperlyConfigured(\n                    \"'%s' is a default fixture directory for the '%s' app \"\n                    \"and cannot be listed in settings.FIXTURE_DIRS.\"\n                    % (app_dir, app_label)\n                )\n\n            if self.app_label and app_label != self.app_label:\n                continue\n            if os.path.isdir(app_dir):\n                dirs.append(app_dir)\n        dirs.extend(fixture_dirs)\n        dirs.append(\"\")\n        return [os.path.realpath(d) for d in dirs]\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 311,
        "n_words": 72,
        "vocab_size": 57,
        "complexity": 8,
        "nloc": 21,
        "token_counts": 134,
        "n_ast_nodes": 225,
        "n_identifiers": 22,
        "d_id": 50825,
        "documentation": {
            "docstring": "\n        Return a list of fixture directories.\n\n        The list contains the 'fixtures' subdirectory of each installed\n        application, if it exists, the directories in FIXTURE_DIRS, and the\n        current directory.\n        ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 159323,
        "commit_id": "6339856514897056716bb531acb8489c9cf05d26",
        "repo": "rasa",
        "path": "rasa/shared/importers/importer.py",
        "file_name": "importer.py",
        "fun_name": "get_config_file_for_auto_config",
        "commit_message": "Add support for different recipes (#10641)\n\n* Add support for different recipes\r\n\r\nFixes https://github.com/RasaHQ/rasa/issues/10473\r\n\r\n* Update docs/docs/graph-recipe.mdx\r\n\r\nCo-authored-by: Joe Juzl <joejuzl@gmail.com>",
        "code": "def get_config_file_for_auto_config(self) -> Optional[Text]:\n        \n        return self.config_file\n",
        "url": "https://github.com/RasaHQ/rasa.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 15,
        "n_ast_nodes": 26,
        "n_identifiers": 5,
        "d_id": 38195,
        "documentation": {
            "docstring": "Returns config file path for auto-config only if there is a single one.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 22626,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "ftp_send_receive.py",
        "file_name": "ftp_send_receive.py",
        "fun_name": "receive_file",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def receive_file(filename=\"example.txt\"):\n    with open(filename, \"wb\") as out_file:\n        ftp.retrbinary(\"RETR \" + filename, out_file.write, 1024)\n        ftp.quit()\n\n\n\n\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 30,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 36,
        "n_ast_nodes": 69,
        "n_identifiers": 8,
        "d_id": 4380,
        "documentation": {
            "docstring": "\n\tThe file which will be sent via the FTP server\n\tThe file send will be send to the current working directory\n",
            "n_words": 21,
            "vocab_size": 15,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 203545,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/views/autocomplete.py",
        "file_name": "autocomplete.py",
        "fun_name": "get_queryset",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_queryset(self):\n        \n        qs = self.model_admin.get_queryset(self.request)\n        qs = qs.complex_filter(self.source_field.get_limit_choices_to())\n        qs, search_use_distinct = self.model_admin.get_search_results(\n            self.request, qs, self.term\n        )\n        if search_use_distinct:\n            qs = qs.distinct()\n        return qs\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 94,
        "n_words": 23,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 104,
        "n_identifiers": 12,
        "d_id": 50441,
        "documentation": {
            "docstring": "Return queryset based on ModelAdmin.get_search_results().",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 315483,
        "commit_id": "b09aaba421d6d6178d582bef9ea363017e55639d",
        "repo": "core",
        "path": "tests/components/mikrotik/test_device_tracker.py",
        "file_name": "test_device_tracker.py",
        "fun_name": "test_hub_not_support_wireless",
        "commit_message": "Add type hints and code cleanup for mikrotik (#74296)\n\n* Add type hints and code cleanup for mikrotik\r\n\r\n* update test and increase coverage\r\n\r\n* move setup_mikrotik_entry to __init__.py",
        "code": "async def test_hub_not_support_wireless(hass, mock_device_registry_devices):\n    \n\n    await setup_mikrotik_entry(hass, support_wireless=False)\n    device_1 = hass.states.get(\"device_tracker.device_1\")\n    assert device_1\n    assert device_1.state == \"home\"\n    # device_2 is added from DHCP\n    device_2 = hass.states.get(\"device_tracker.device_2\")\n    assert device_2\n    assert device_2.state == \"home\"\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 58,
        "n_words": 31,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 53,
        "n_ast_nodes": 95,
        "n_identifiers": 10,
        "d_id": 114071,
        "documentation": {
            "docstring": "Test device_trackers created when hub doesn't support wireless.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 156510,
        "commit_id": "1e783d9a714160e968936cb22d54d085959ab09e",
        "repo": "dask",
        "path": "dask/typing.py",
        "file_name": "typing.py",
        "fun_name": "__dask_postcompute__",
        "commit_message": "Collection Protocol (#8674)\n\n[PEP 544](https://www.python.org/dev/peps/pep-0544/) introduces the `Protocol` class to the `typing` module in Python 3.8 (the soon be the minimum supported version, https://github.com/dask/community/issues/213). Writing new Dask collections for [dask-awkward](https://github.com/ContinuumIO/dask-awkward/) has had me thinking about working on a `DaskCollection` protocol. I imagine the benefits to be:\r\n\r\n- usage with static type checkers\r\n  - other activity in this area at\r\n    - #8295 \r\n    - #8706 \r\n    -  #8854\r\n  - Python supporting IDEs take advantage of typing\r\n- self-documenting; some improvements to [the custom collections page](https://docs.dask.org/en/latest/custom-collections.html) of the docs. The protocol docs can be autogenerated and added to that page.\r\n- purely opt-in feature\r\n\r\nThe `typing.runtime_checkable` decorator allows use of `isinstance(x, DaskCollection)` in any code base\r\nthat uses Dask collections; for example:\r\n\r\n```python\r\n>>> from dask.typing import DaskCollection\r\n>>> import dask.array as da\r\n>>> x = da.zeros((10, 3))\r\n>>> isinstance(x, DaskCollection)\r\nTrue\r\n```\r\n(though this is an order of magnitude slower than `dask.base.is_dask_collection` which only checks for `x.__dask_graph__() is not None`; static typing checking & built-in interface documentation are the core benefits IMO)\r\n\r\nSomething else that came up in the brief discussion on a call last week was having `{Scheduler,Worker,Nanny}Plugin` protocols in `distributed`; and perhaps those are better places to start introducing protocols to Dask since on the user side typically more folks would write plugins than new collections.",
        "code": "def __dask_postcompute__(self) -> tuple[PostComputeCallable, tuple]:\n        \n        raise NotImplementedError(\"Inheriting class must implement this method.\")\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 26,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 18,
        "n_ast_nodes": 32,
        "n_identifiers": 5,
        "d_id": 36663,
        "documentation": {
            "docstring": "Finalizer function and optional arguments to construct final result.\n\n        Upon computation each key in the collection will have an in\n        memory result, the postcompute function combines each key's\n        result into a final in memory representation. For example,\n        dask.array.Array concatenates the arrays at each chunk into a\n        final in-memory array.\n\n        Returns\n        -------\n        PostComputeCallable\n            Callable that recieves the sequence of the results of each\n            final key along with optional arguments. An example signature\n            would be ``finalize(results: Sequence[Any], *args)``.\n        tuple[Any, ...]\n            Optional arguments passed to the function following the\n            key results (the `*args` part of the\n            ``PostComputeCallable``. If no additional arguments are to\n            be passed then this must be an empty tuple.\n\n        ",
            "n_words": 109,
            "vocab_size": 75,
            "n_whitespaces": 256,
            "language": "en"
        }
    },
    {
        "id": 31114,
        "commit_id": "34097b3304d79ace845316d4929220623279c8bc",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_intel_extension_for_pytorch",
        "commit_message": "Extend Transformers Trainer Class to Enable CPU AMP and Integrate Intel Extension for PyTorch (#17138)\n\n* init PR\r\n\r\n* fix import ipex\r\n\r\n* minor fix on bf16\r\n\r\n* refine optimizer\r\n\r\n* refine args notes\r\n\r\n* refine code\r\n\r\n* refine ipex optimize args\r\n\r\n* refine half_precision_backend\r\n\r\n* black format\r\n\r\n* isort format\r\n\r\n* isort format files\r\n\r\n* flake8 format\r\n\r\n* doc builder format\r\n\r\n* refine codes\r\n\r\n* remove jit and optim bits\r\n\r\n* black preview format\r\n\r\n* Update src/transformers/trainer.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* refine code\r\n\r\n* refine notes\r\n\r\n* Update src/transformers/trainer.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/trainer.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* code refine\r\n\r\n* add ipex ut\r\n\r\n* add performance cpu doc\r\n\r\n* link to the cpu doc from main perf doc\r\n\r\n* install ipex into CI's docker\r\n\r\n* Update perf_train_cpu.mdx\r\n\r\n* Update docs/source/en/perf_train_cpu.mdx\r\n\r\nCo-authored-by: Stas Bekman <stas00@users.noreply.github.com>\r\n\r\n* Update perf_train_cpu.mdx\r\n\r\n* Update perf_train_cpu.mdx\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Stas Bekman <stas@stason.org>\r\nCo-authored-by: Stas Bekman <stas00@users.noreply.github.com>",
        "code": "def require_intel_extension_for_pytorch(test_case):\n    \n    return unittest.skipUnless(is_ipex_available(), \"test requires Intel Extension for PyTorch\")(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 16,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 5681,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires Intel Extension for PyTorch.\n\n    These tests are skipped when Intel Extension for PyTorch isn't installed.\n\n    ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 103383,
        "commit_id": "45bbe17559a541289699643ef0b541a2138a09d6",
        "repo": "kitty",
        "path": "kitty/cli.py",
        "file_name": "cli.py",
        "fun_name": "options_spec",
        "commit_message": "Docs: Minor improvements to the kitty cli help documentation\n\nAdd some text roles.\nUse `kitty --hold`.\nUse `appname` and `conf_name`.\n`appname` is also applied to the system-wide configuration path.",
        "code": "def options_spec() -> str:\n    if not hasattr(options_spec, 'ans'):\n        OPTIONS = \n        setattr(options_spec, 'ans', OPTIONS.format(\n            appname=appname, conf_name=appname,\n            config_help=CONFIG_HELP.format(appname=appname, conf_name=appname),\n        ))\n    ans: str = getattr(options_spec, 'ans')\n    return ans\n\n",
        "url": "https://github.com/kovidgoyal/kitty.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 77,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 166,
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        "n_identifiers": 12,
        "d_id": 21638,
        "documentation": {
            "docstring": "\n--class\ndest=cls\ndefault={appname}\ncondition=not is_macos\nSet the class part of the :italic:`WM_CLASS` window property. On Wayland, it\nsets the app id.\n\n\n--name\ncondition=not is_macos\nSet the name part of the :italic:`WM_CLASS` property. Defaults to using the\nvalue from :option:`{appname} --class`.\n\n\n--title -T\nSet the OS window title. This will override any title set by the program running\ninside kitty, permanently fixing the OS window's title. So only use this if you\nare running a program that does not set titles.\n\n\n--config -c\ntype=list\n{config_help}\n\n\n--override -o\ntype=list\nOverride individual configuration options, can be specified multiple times.\nSyntax: :italic:`name=value`. For example: :option:`{appname} -o` font_size=20\n\n\n--directory --working-directory -d\ndefault=.\nChange to the specified directory when launching.\n\n\n--detach\ntype=bool-set\ncondition=not is_macos\nDetach from the controlling terminal, if any.\n\n\n--session\nPath to a file containing the startup :italic:`session` (tabs, windows, layout,\nprograms). Use - to read from STDIN. See the :file:`README` file for details and\nan example.\n\n\n--hold\ntype=bool-set\nRemain open after child process exits. Note that this only affects the first\nwindow. You can quit by either using the close window shortcut or pressing any\nkey.\n\n\n--single-instance -1\ntype=bool-set\nIf specified only a single instance of :italic:`{appname}` will run. New\ninvocations will instead create a new top-level window in the existing\n:italic:`{appname}` instance. This allows :italic:`{appname}` to share a single\nsprite cache on the GPU and also reduces startup time. You can also have\nseparate groups of :italic:`{appname}` instances by using the :option:`{appname}\n--instance-group` option.\n\n\n--instance-group\nUsed in combination with the :option:`{appname} --single-instance` option. All\n:italic:`{appname}` invocations with the same :option:`{appname}\n--instance-group` will result in new windows being created in the first\n:italic:`{appname}` instance within that group.\n\n\n--wait-for-single-instance-window-close\ntype=bool-set\nNormally, when using :option:`{appname} --single-instance`, :italic:`{appname}`\nwill open a new window in an existing instance and quit immediately. With this\noption, it will not quit till the newly opened window is closed. Note that if no\nprevious instance is found, then :italic:`{appname}` will wait anyway,\nregardless of this option.\n\n\n--listen-on\nListen on the specified socket address for control messages. For example,\n:option:`{appname} --listen-on`=unix:/tmp/mykitty or\n:option:`{appname} --listen-on`=tcp:localhost:12345. On Linux systems, you can\nalso use abstract UNIX sockets, not associated with a file, like this:\n:option:`{appname} --listen-on`=unix:@mykitty. Environment variables are\nexpanded and relative paths are resolved with respect to the temporary\ndirectory. To control kitty, you can send commands to it with\n:italic:`{appname} @` using the :option:`{appname} @ --to` option to specify\nthis address. Unless you enabled :opt:`allow_remote_control` in\n:file:`{conf_name}.conf`, this option will be ignored. Note that if you run\n:italic:`{appname} @` within a kitty window, there is\nno need to specify the :option:`{appname} @ --to` option as it will\nautomatically read from the environment. For UNIX sockets, this can also be\nspecified in :file:`{conf_name}.conf`.\n\n\n--start-as\ntype=choices\ndefault=normal\nchoices=normal,fullscreen,maximized,minimized\nControl how the initial kitty window is created.\n\n\n# Debugging options\n\n--version -v\ntype=bool-set\nThe current {appname} version.\n\n\n--dump-commands\ntype=bool-set\nOutput commands received from child process to STDOUT.\n\n\n--replay-commands\nReplay previously dumped commands. Specify the path to a dump file previously\ncreated by :option:`{appname} --dump-commands`. You\ncan open a new kitty window to replay the commands with::\n\n    {appname} --hold {appname} --replay-commands /path/to/dump/file\n\n\n--dump-bytes\nPath to file in which to store the raw bytes received from the child process.\n\n\n--debug-rendering --debug-gl\ntype=bool-set\nDebug rendering commands. This will cause all OpenGL calls to check for errors\ninstead of ignoring them. Also prints out miscellaneous debug information.\nUseful when debugging rendering problems.\n\n\n--debug-input --debug-keyboard\ndest=debug_keyboard\ntype=bool-set\nPrint out key and mouse events as they are received.\n\n\n--debug-font-fallback\ntype=bool-set\nPrint out information about the selection of fallback fonts for characters not\npresent in the main font.\n\n\n--watcher\nThis option is deprecated in favor of the :opt:`watcher` option in\n:file:`{conf_name}.conf` and should not be used.\n\n\n--execute -e\ntype=bool-set\n!\n",
            "n_words": 617,
            "vocab_size": 336,
            "n_whitespaces": 511,
            "language": "en"
        }
    },
    {
        "id": 66656,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v12_0/repost_stock_ledger_entries_for_target_warehouse.py",
        "file_name": "repost_stock_ledger_entries_for_target_warehouse.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\twarehouse_perm = frappe.get_all(\n\t\t\"User Permission\",\n\t\tfields=[\"count(*) as p_count\", \"is_default\", \"user\"],\n\t\tfilters={\"allow\": \"Warehouse\"},\n\t\tgroup_by=\"user\",\n\t)\n\n\tif not warehouse_perm:\n\t\treturn\n\n\texecute_patch = False\n\tfor perm_data in warehouse_perm:\n\t\tif perm_data.p_count == 1 or (\n\t\t\tperm_data.p_count > 1\n\t\t\tand frappe.get_all(\n\t\t\t\t\"User Permission\",\n\t\t\t\tfilters={\"user\": perm_data.user, \"allow\": \"warehouse\", \"is_default\": 1},\n\t\t\t\tlimit=1,\n\t\t\t)\n\t\t):\n\t\t\texecute_patch = True\n\t\t\tbreak\n\n\tif not execute_patch:\n\t\treturn\n\n\tfor doctype in [\"Sales Invoice\", \"Delivery Note\"]:\n\t\tif not frappe.get_meta(doctype + \" Item\").get_field(\"target_warehouse\").hidden:\n\t\t\tcontinue\n\n\t\tcond = \"\"\n\t\tif doctype == \"Sales Invoice\":\n\t\t\tcond = \" AND parent_doc.update_stock = 1\"\n\n\t\tdata = frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tdoctype=doctype, cond=cond\n\t\t\t),\n\t\t\tas_dict=1,\n\t\t)\n\n\t\tif data:\n\t\t\tnames = [d.child_name for d in data]\n\t\t\tfrappe.db.sql(\n\t\t\t\t.format(\n\t\t\t\t\tdoctype, \",\".join([\"%s\"] * len(names))\n\t\t\t\t),\n\t\t\t\ttuple(names),\n\t\t\t)\n\n\t\t\tfrappe.db.sql(\n\t\t\t\t.format(\n\t\t\t\t\tdoctype, \",\".join([\"%s\"] * len(names))\n\t\t\t\t),\n\t\t\t\ttuple(names),\n\t\t\t)\n\n\t\t\tparent_names = list(set([d.name for d in data]))\n\n\t\t\tfor d in parent_names:\n\t\t\t\tdoc = frappe.get_doc(doctype, d)\n\t\t\t\tif doc.docstatus != 1:\n\t\t\t\t\tcontinue\n\n\t\t\t\tdoc.docstatus = 2\n\t\t\t\tdoc.update_stock_ledger()\n\t\t\t\tdoc.make_gl_entries_on_cancel(repost_future_gle=False)\n\n\t\t\t\t# update stock & gl entries for submit state of PR\n\t\t\t\tdoc.docstatus = 1\n\t\t\t\tdoc.update_stock_ledger()\n\t\t\t\tdoc.make_gl_entries()\n\n\tif frappe.get_meta(\"Sales Order Item\").get_field(\"target_warehouse\").hidden:\n\t\tfrappe.db.sql(\n\t\t\t\n\t\t)\n\n\t\tfrappe.db.sql(\n\t\t\t\n\t\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 105,
        "n_words": 171,
        "vocab_size": 103,
        "complexity": 16,
        "nloc": 79,
        "token_counts": 351,
        "n_ast_nodes": 599,
        "n_identifiers": 39,
        "d_id": 14274,
        "documentation": {
            "docstring": " SELECT parent_doc.name as name, child_doc.name as child_name\n\t\t\tFROM\n\t\t\t\t`tab{doctype}` parent_doc, `tab{doctype} Item` child_doc\n\t\t\tWHERE\n\t\t\t\tparent_doc.name = child_doc.parent AND parent_doc.docstatus < 2\n\t\t\t\tAND child_doc.target_warehouse is not null AND child_doc.target_warehouse != ''\n\t\t\t\tAND child_doc.creation > '2020-04-16' {cond}\n\t\t UPDATE `tab{0} Item` set target_warehouse = null\n\t\t\t\tWHERE name in ({1})  UPDATE `tabPacked Item` set target_warehouse = null\n\t\t\t\tWHERE parenttype = '{0}' and parent_detail_docname in ({1})\n\t\t\t UPDATE `tabSales Order Item` set target_warehouse = null\n\t\t\tWHERE creation > '2020-04-16' and docstatus < 2  UPDATE `tabPacked Item` set target_warehouse = null\n\t\t\tWHERE creation > '2020-04-16' and docstatus < 2 and parenttype = 'Sales Order' ",
            "n_words": 97,
            "vocab_size": 47,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 19478,
        "commit_id": "2669b4ce0696de02610cbea1b7547d53cead85bb",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/setup_info.py",
        "file_name": "setup_info.py",
        "fun_name": "build_wheel",
        "commit_message": "patch newly occuring test failure where the base_dir does not contain the subdirectory.",
        "code": "def build_wheel(self):\n        # type: () -> S\n        need_delete = False\n        if not self.pyproject.exists():\n            if not self.build_requires:\n                build_requires = '\"setuptools\", \"wheel\"'\n            else:\n                build_requires = \", \".join(\n                    ['\"{0}\"'.format(r) for r in self.build_requires]\n                )\n            self.pyproject.write_text(\n                str(\n                    .format(\n                        build_requires, self.build_backend\n                    ).strip()\n                )\n            )\n            need_delete = True\n\n        parsed = urlparse(str(self.ireq.link))\n        subdir = parse_qs(parsed.fragment).get('subdirectory', [])\n        if subdir:\n            directory = f\"{self.base_dir}/{subdir[0]}\"\n        else:\n            directory = self.base_dir\n        result = build_pep517(\n            directory,\n            self.extra_kwargs[\"build_dir\"],\n            config_settings=self.pep517_config,\n            dist_type=\"wheel\",\n        )\n        if need_delete:\n            self.pyproject.unlink()\n        return result\n\n    # noinspection PyPackageRequirements",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 440,
        "n_words": 74,
        "vocab_size": 53,
        "complexity": 6,
        "nloc": 36,
        "token_counts": 156,
        "n_ast_nodes": 279,
        "n_identifiers": 30,
        "d_id": 2994,
        "documentation": {
            "docstring": "\n[build-system]\nrequires = [{0}]\nbuild-backend = \"{1}\"\n                ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 61411,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "make_rev_options",
        "commit_message": "upd; format",
        "code": "def make_rev_options(cls, rev=None, extra_args=None):\n        # type: (Optional[str], Optional[CommandArgs]) -> RevOptions\n        \n        return RevOptions(cls, rev, extra_args=extra_args)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 12556,
        "documentation": {
            "docstring": "\n        Return a RevOptions object.\n\n        Args:\n          rev: the name of a revision to install.\n          extra_args: a list of extra options.\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 112723,
        "commit_id": "cbac2c5c0f7606aca8ccf08fbd418ffe3adfe427",
        "repo": "nni",
        "path": "nni/algorithms/compression/v2/pytorch/base/compressor.py",
        "file_name": "compressor.py",
        "fun_name": "generate_module_groups",
        "commit_message": "[Compression] fix typehints (#4800)",
        "code": "def generate_module_groups(self) -> Dict[int, List[str]]:\n        \n        assert self.bound_model is not None, 'No model bounded in this compressor, please use Compressor.reset(model, config_list) to set it.'\n        assert self.config_list is not None, 'No config_list set in this compressor, please use Compressor.reset(model, config_list) to set it.'\n\n        self._unwrap_model()\n        module_groups = {}\n        for name, module in self.bound_model.named_modules():\n            if module == self.bound_model:\n                continue\n            layer = LayerInfo(name, module)\n            ret = None\n            for idx, config in enumerate(self.config_list):\n                config = config.copy()\n                # expand config if key `default` is in config['op_types']\n                if 'op_types' in config and 'default' in config['op_types']:\n                    expanded_op_types = []\n                    for op_type in config['op_types']:\n                        if op_type == 'default':\n                            expanded_op_types.extend(weighted_modules)\n                        else:\n                            expanded_op_types.append(op_type)\n                    config['op_types'] = expanded_op_types\n                # check if condition is satisified\n                if 'op_types' in config and layer.type not in config['op_types']:\n                    continue\n                if 'op_names' in config and layer.name not in config['op_names']:\n                    continue\n                ret = (idx, config)\n            if ret is not None and 'exclude' not in ret[1]:\n                module_groups.setdefault(ret[0], [])\n                module_groups[ret[0]].append(name)\n\n        self._wrap_model()\n        return module_groups\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 606,
        "n_words": 150,
        "vocab_size": 78,
        "complexity": 14,
        "nloc": 38,
        "token_counts": 227,
        "n_ast_nodes": 377,
        "n_identifiers": 28,
        "d_id": 24731,
        "documentation": {
            "docstring": "\n        Get all module names in each config in config_list.\n\n        Returns\n        -------\n        Dict[int, List[str]]\n            A dict. The key is the config idx in config_list, the value is the module name list. i.e., {1: ['layer.0', 'layer.2']}.\n        ",
            "n_words": 34,
            "vocab_size": 27,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 282800,
        "commit_id": "635851cbf633a6ea9423ba31fe8f68ab34423a8c",
        "repo": "OpenBBTerminal",
        "path": "bots/telegram/run_telegram.py",
        "file_name": "run_telegram.py",
        "fun_name": "send_welcome",
        "commit_message": "Telegram Bot (#1458)\n\n* added initial code for telegram\r\n\r\n* improving suggestions and messages\r\n\r\n* improving messages\r\n\r\n* typo\r\n\r\nCo-authored-by: teh_coderer <me@tehcoderer.com>",
        "code": "def send_welcome(message):\n    text = \n    markdown = telebot.types.InlineKeyboardMarkup()\n    markdown.add(\n        telebot.types.InlineKeyboardButton(\n            \"Star us on GitHub\",\n            url=\"https://github.com/GamestonkTerminal/GamestonkTerminal\",\n        )\n    )\n    markdown.add(\n        telebot.types.InlineKeyboardButton(\n            \"Join us on Discord\", url=\"https://discord.gg/XHsYvvjjWg\"\n        )\n    )\n    bot.send_message(\n        chat_id=message.chat.id, text=text, reply_markup=markdown, parse_mode=\"MARKDOWN\"\n    )\n    # bot.reply_to(markdown, text, parse_mode=\"MARKDOWN\")\n    # bot.reply_to(message, text, parse_mode=\"MARKDOWN\")\n\n\n@bot.message_handler(commands=[\"cmds\", \"commands\"])",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@bot.message_handler(commands=[\"cmds\", \"commands\"])",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 138,
        "n_words": 41,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 76,
        "n_ast_nodes": 154,
        "n_identifiers": 19,
        "d_id": 84305,
        "documentation": {
            "docstring": "\nWelcome to *Gamestonk Terminal Bot* 🦋\nInvestment Research for Everyone\nCheck the available commands with /cmds\n    ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 217382,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/fnmatch.py",
        "file_name": "fnmatch.py",
        "fun_name": "filter",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def filter(names, pat):\n    \n    result = []\n    pat = os.path.normcase(pat)\n    match = _compile_pattern(pat)\n    if os.path is posixpath:\n        # normcase on posix is NOP. Optimize it away from the loop.\n        for name in names:\n            if match(name):\n                result.append(name)\n    else:\n        for name in names:\n            if match(os.path.normcase(name)):\n                result.append(name)\n    return result\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 139,
        "n_words": 45,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 13,
        "token_counts": 80,
        "n_ast_nodes": 132,
        "n_identifiers": 12,
        "d_id": 54738,
        "documentation": {
            "docstring": "Construct a list from those elements of the iterable NAMES that match PAT.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 3401,
        "commit_id": "0a3713a5a52995dc0dc205d8edfd097bf625899f",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-salesforce/unit_tests/unit_test.py",
        "file_name": "unit_test.py",
        "fun_name": "test_stream_unsupported_by_bulk",
        "commit_message": "Source Salesforce: Deprecate API Type parameter (#9302)\n\n* use BULK for the first sync, REST for incremental sync\r\n\r\n* if stream contains compound data or/and base64 use always REST\r\n\r\n* fix get stream state from connector state\r\n\r\n* fix integration test\r\n\r\n* refactor catalog name\r\n\r\n* format code\r\n\r\n* refactor unit tests\r\n\r\n* refactor unit tests 2\r\n\r\n* format code 2\r\n\r\n* Set additionalProperties to true not to break test temporarily\r\n\r\n* fix unit test and remove unnecessary filtering fields\r\n\r\n* bump version\r\n\r\n* updated spec and def yaml\r\n\r\nCo-authored-by: auganbay <auganenu@gmail.com>",
        "code": "def test_stream_unsupported_by_bulk(stream_config, stream_api, caplog):\n    \n    stream_name = \"AcceptedEventRelation\"\n    stream = _generate_stream(stream_name, stream_config, stream_api)\n    assert not isinstance(stream, BulkSalesforceStream)\n\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 50,
        "n_identifiers": 9,
        "d_id": 469,
        "documentation": {
            "docstring": "\n    Stream `AcceptedEventRelation` is not supported by BULK API, so that REST API stream will be used for it.\n    ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 220367,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/base_events.py",
        "file_name": "base_events.py",
        "fun_name": "call_exception_handler",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def call_exception_handler(self, context):\n        \n        if self._exception_handler is None:\n            try:\n                self.default_exception_handler(context)\n            except (SystemExit, KeyboardInterrupt):\n                raise\n            except BaseException:\n                # Second protection layer for unexpected errors\n                # in the default implementation, as well as for subclassed\n                # event loops with overloaded \"default_exception_handler\".\n                logger.error('Exception in default exception handler',\n                             exc_info=True)\n        else:\n            try:\n                self._exception_handler(self, context)\n            except (SystemExit, KeyboardInterrupt):\n                raise\n            except BaseException as exc:\n                # Exception in the user set custom exception handler.\n                try:\n                    # Let's try default handler.\n                    self.default_exception_handler({\n                        'message': 'Unhandled error in exception handler',\n                        'exception': exc,\n                        'context': context,\n                    })\n                except (SystemExit, KeyboardInterrupt):\n                    raise\n                except BaseException:\n                    # Guard 'default_exception_handler' in case it is\n                    # overloaded.\n                    logger.error('Exception in default exception handler '\n                                 'while handling an unexpected error '\n                                 'in custom exception handler',\n                                 exc_info=True)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 708,
        "n_words": 115,
        "vocab_size": 69,
        "complexity": 8,
        "nloc": 28,
        "token_counts": 113,
        "n_ast_nodes": 202,
        "n_identifiers": 12,
        "d_id": 55979,
        "documentation": {
            "docstring": "Call the current event loop's exception handler.\n\n        The context argument is a dict containing the following keys:\n\n        - 'message': Error message;\n        - 'exception' (optional): Exception object;\n        - 'future' (optional): Future instance;\n        - 'task' (optional): Task instance;\n        - 'handle' (optional): Handle instance;\n        - 'protocol' (optional): Protocol instance;\n        - 'transport' (optional): Transport instance;\n        - 'socket' (optional): Socket instance;\n        - 'asyncgen' (optional): Asynchronous generator that caused\n                                 the exception.\n\n        New keys maybe introduced in the future.\n\n        Note: do not overload this method in an event loop subclass.\n        For custom exception handling, use the\n        `set_exception_handler()` method.\n        ",
            "n_words": 91,
            "vocab_size": 64,
            "n_whitespaces": 228,
            "language": "en"
        }
    },
    {
        "id": 71,
        "commit_id": "10ae1d589044a6ae4722ead7aedc63fcdc4923b5",
        "repo": "PySyft",
        "path": "packages/syft/tests/syft/core/tensor/tensor_serde_test.py",
        "file_name": "tensor_serde_test.py",
        "fun_name": "test_sept_child",
        "commit_message": "Started DPTensor resource optimization\n\n- Added initial REPT and SEPT benchmarking tests\n- Deleted unused old Tensor classes\n- Added pympler for memory size tests\n\nCo-authored-by: @IshanMi\nCo-authored-by: @rasswanth-s",
        "code": "def test_sept_child() -> None:\n    \n    rows = 10_000\n    cols = 7\n    # these times and sizes are based on the above constants and Madhavas MacBook Pro 2019\n    expected_sept_mem_size = 0.8035125732421875\n    expected_sept_ser_size = 1.4993972778320312\n    macbook_pro_2019_ser_time = 0.03371272199999975\n    macbook_pro_2019_de_time = 0.02922678500000009\n\n    sept = make_sept(rows=rows, cols=cols)\n\n    start = timeit.default_timer()\n    ser = sy.serialize(sept, to_bytes=True)\n    end = timeit.default_timer()\n    time_ser = end - start\n\n    start = timeit.default_timer()\n    de = sy.deserialize(ser, from_bytes=True)\n    end = timeit.default_timer()\n    time_de = end - start\n\n    assert sept == de\n\n    current_sept_mem_size = size(sept)\n    mem_diff = (current_sept_mem_size / expected_sept_mem_size * 100) - 100\n\n    current_sept_bytes_size = size(ser)\n    bytes_diff = (current_sept_bytes_size / expected_sept_ser_size * 100) - 100\n\n    ser_time_diff = (time_ser / macbook_pro_2019_ser_time * 100) - 100\n    de_time_diff = (time_de / macbook_pro_2019_de_time * 100) - 100\n\n    print(\"SEPT Stats\")\n    print(\"==========\")\n    print(\"In-memory size of SEPT\", size(sept))\n    print(\"Serialized size of SEPT\", size(ser))\n    print(f\"Serializing {rows}x{cols} took {time_ser} secs\")\n    print(f\"Deserializing {rows}x{cols} took {time_de} secs\")\n\n    print(\"Current Results\")\n    print(\"===============\")\n    print(f\"In-memory size delta: {mem_diff}%\")\n    print(f\"Serialized size delta: {bytes_diff}%\")\n    print(f\"Serializing time delta: {ser_time_diff}%\")\n    print(f\"Deserializing time delta: {de_time_diff}%\")\n\n    # we want to assert that our calculated values are smaller than the old values with\n    # some tolerance\n    assert (current_sept_mem_size - expected_sept_mem_size) < 1e-3\n    assert (current_sept_bytes_size - expected_sept_ser_size) < 2e-3\n    # TODO: make time benchmarks stable (probably can't run in parallel)\n    # assert (time_ser - macbook_pro_2019_ser_time) < 2e-1\n    # assert (time_de - macbook_pro_2019_de_time) < 2e-1\n\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 345,
        "n_words": 216,
        "vocab_size": 123,
        "complexity": 1,
        "nloc": 38,
        "token_counts": 251,
        "n_ast_nodes": 449,
        "n_identifiers": 30,
        "d_id": 45,
        "documentation": {
            "docstring": "We need to benchmark both the size and time to serialize and deserialize SEPTs",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 47362,
        "commit_id": "8b687ec82a7047fc35410f5c5bb0726de434e749",
        "repo": "airflow",
        "path": "tests/models/test_taskinstance.py",
        "file_name": "test_taskinstance.py",
        "fun_name": "test_xcom_pull_after_deferral",
        "commit_message": "Do not clear XCom when resuming from deferral (#22932)",
        "code": "def test_xcom_pull_after_deferral(self, create_task_instance, session):\n        \n\n        key = 'xcom_key'\n        value = 'xcom_value'\n\n        ti = create_task_instance(\n            dag_id='test_xcom',\n            schedule_interval='@monthly',\n            task_id='test_xcom',\n            pool='test_xcom',\n        )\n\n        ti.run(mark_success=True)\n        ti.xcom_push(key=key, value=value)\n\n        ti.next_method = \"execute\"\n        session.merge(ti)\n        session.commit()\n\n        ti.run(ignore_all_deps=True)\n        assert ti.xcom_pull(task_ids='test_xcom', key=key) == value\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 160,
        "n_words": 32,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 96,
        "n_ast_nodes": 165,
        "n_identifiers": 20,
        "d_id": 9082,
        "documentation": {
            "docstring": "\n        tests xcom will not clear before a task runs its next method after deferral.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 244730,
        "commit_id": "9d7511d8c35df1f9c13b17eb770136859bf370be",
        "repo": "mmdetection",
        "path": "tests/test_models/test_dense_heads/test_pisa_ssd_head.py",
        "file_name": "test_pisa_ssd_head.py",
        "fun_name": "test_pisa_ssd_head_loss",
        "commit_message": "Update SSD and PISA-SSD model config",
        "code": "def test_pisa_ssd_head_loss(self):\n        \n        s = 300\n        img_metas = [{\n            'img_shape': (s, s, 3),\n            'scale_factor': 1,\n        }]\n        cfg = Config(\n            dict(\n                assigner=dict(\n                    type='MaxIoUAssigner',\n                    pos_iou_thr=0.5,\n                    neg_iou_thr=0.5,\n                    min_pos_iou=0.,\n                    ignore_iof_thr=-1,\n                    gt_max_assign_all=False),\n                sampler=dict(type='PseudoSampler'),\n                smoothl1_beta=1.,\n                allowed_border=-1,\n                pos_weight=-1,\n                neg_pos_ratio=3,\n                debug=False))\n        pisa_ssd_head = PISASSDHead(\n            num_classes=4,\n            in_channels=(1, 1, 1, 1, 1, 1),\n            anchor_generator=dict(\n                type='SSDAnchorGenerator',\n                scale_major=False,\n                input_size=s,\n                basesize_ratio_range=(0.15, 0.9),\n                strides=[8, 16, 32, 64, 100, 300],\n                ratios=[[2], [2, 3], [2, 3], [2, 3], [2], [2]]),\n            train_cfg=cfg)\n\n        # PISA SSD head expects a multiple levels of features per image\n        feats = (\n            torch.rand(1, 1, ceil(s / stride[0]), ceil(s / stride[0]))\n            for stride in pisa_ssd_head.prior_generator.strides)\n        cls_scores, bbox_preds = pisa_ssd_head.forward(feats)\n\n        # test without isr and carl\n        # Test that empty ground truth encourages the network to\n        # predict background\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.empty((0, 4))\n        gt_instances.labels = torch.LongTensor([])\n\n        empty_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds,\n                                             [gt_instances], img_metas)\n        # When there is no truth, cls_loss and box_loss should all be zero.\n        empty_cls_loss = sum(empty_gt_losses['loss_cls'])\n        empty_box_loss = sum(empty_gt_losses['loss_bbox'])\n        self.assertEqual(\n            empty_cls_loss.item(), 0,\n            'there should be no cls loss when there are no true boxes')\n        self.assertEqual(\n            empty_box_loss.item(), 0,\n            'there should be no box loss when there are no true boxes')\n\n        # When truth is non-empty then both cls and box loss\n        # should be nonzero for random inputs\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.Tensor(\n            [[23.6667, 23.8757, 238.6326, 151.8874]])\n        gt_instances.labels = torch.LongTensor([2])\n\n        one_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds,\n                                           [gt_instances], img_metas)\n        onegt_cls_loss = sum(one_gt_losses['loss_cls'])\n        onegt_box_loss = sum(one_gt_losses['loss_bbox'])\n        self.assertGreater(onegt_cls_loss.item(), 0,\n                           'cls loss should be non-zero')\n        self.assertGreater(onegt_box_loss.item(), 0,\n                           'box loss should be non-zero')\n\n        pisa_ssd_head.train_cfg.update(\n            dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2)))\n\n        # test with isr and carl\n        # Test that empty ground truth encourages the network to\n        # predict background\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.empty((0, 4))\n        gt_instances.labels = torch.LongTensor([])\n\n        empty_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds,\n                                             [gt_instances], img_metas)\n        # When there is no truth, cls_loss and box_loss should all be zero.\n        empty_cls_loss = sum(empty_gt_losses['loss_cls'])\n        empty_box_loss = sum(empty_gt_losses['loss_bbox'])\n        self.assertEqual(\n            empty_cls_loss.item(), 0,\n            'there should be no cls loss when there are no true boxes')\n        self.assertEqual(\n            empty_box_loss.item(), 0,\n            'there should be no box loss when there are no true boxes')\n\n        # When truth is non-empty then both cls and box loss\n        # should be nonzero for random inputs\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.Tensor(\n            [[23.6667, 23.8757, 238.6326, 151.8874]])\n        gt_instances.labels = torch.LongTensor([2])\n\n        one_gt_losses = pisa_ssd_head.loss(cls_scores, bbox_preds,\n                                           [gt_instances], img_metas)\n        onegt_cls_loss = sum(one_gt_losses['loss_cls'])\n        onegt_box_loss = sum(one_gt_losses['loss_bbox'])\n        self.assertGreater(onegt_cls_loss.item(), 0,\n                           'cls loss should be non-zero')\n        self.assertGreater(onegt_box_loss.item(), 0,\n                           'box loss should be non-zero')\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 1565,
        "n_words": 382,
        "vocab_size": 162,
        "complexity": 2,
        "nloc": 88,
        "token_counts": 698,
        "n_ast_nodes": 1025,
        "n_identifiers": 63,
        "d_id": 70500,
        "documentation": {
            "docstring": "Tests pisa ssd head loss when truth is empty and non-empty.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 61060,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/resolution/legacy/resolver.py",
        "file_name": "resolver.py",
        "fun_name": "get_installation_order",
        "commit_message": "upd; format",
        "code": "def get_installation_order(self, req_set):\n        # type: (RequirementSet) -> List[InstallRequirement]\n        \n        # The current implementation, which we may change at any point\n        # installs the user specified things in the order given, except when\n        # dependencies must come earlier to achieve topological order.\n        order = []\n        ordered_reqs = set()  # type: Set[InstallRequirement]\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 99,
        "n_words": 49,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 36,
        "n_identifiers": 6,
        "d_id": 12403,
        "documentation": {
            "docstring": "Create the installation order.\n\n        The installation order is topological - requirements are installed\n        before the requiring thing. We break cycles at an arbitrary point,\n        and make no other guarantees.\n        ",
            "n_words": 29,
            "vocab_size": 27,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 76287,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/utils/setup.py",
        "file_name": "setup.py",
        "fun_name": "bump_client_version",
        "commit_message": "Reformat with black",
        "code": "def bump_client_version(self):\n        \n        path = os.path.join(\".\", \"client\", \"package.json\")\n        input_file = io.open(path, \"r\")\n\n        try:\n            package = json.loads(input_file.read().decode(\"utf-8\"))\n        except (ValueError) as e:\n            print(\"Unable to read \" + path + \" \" + e)  # noqa\n            raise SystemExit(1)\n\n        package[\"version\"] = __semver__\n\n        try:\n            with io.open(path, \"w\", encoding=\"utf-8\") as f:\n                f.write(str(json.dumps(package, indent=2, ensure_ascii=False)))\n        except (IOError) as e:\n            print(\"Error setting the version for front-end assets: \" + str(e))  # noqa\n            raise SystemExit(1)\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 204,
        "n_words": 65,
        "vocab_size": 45,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 138,
        "n_ast_nodes": 247,
        "n_identifiers": 26,
        "d_id": 16486,
        "documentation": {
            "docstring": "\n        Writes the current Wagtail version number into package.json\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 316830,
        "commit_id": "5b32eea3d04d223b01efddb5c13a88e540df8741",
        "repo": "core",
        "path": "homeassistant/components/wallbox/number.py",
        "file_name": "number.py",
        "fun_name": "native_min_value",
        "commit_message": "Add support for bidirectional chargers to Wallbox integration (#74313)\n\n* Add support for the Quasar bidirectional charger to the Wallbox integration, including ability to control charger while discharging, set a negative charge rate and monitor discharged amount\r\n\r\n* Make code more generic in order to support other bidirectional models in the future\r\n\r\n* Updates to files to comply with HA formatting rules\r\n\r\n* Change const file to fix black check failure\r\n\r\n* Remove unnecessay loop in number entity",
        "code": "def native_min_value(self) -> float:\n        \n        return (self.max_value * -1) if self._is_bidirectional else 6\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 26,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 115406,
        "documentation": {
            "docstring": "Return the minimum available current based on charger type - some chargers can discharge.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 82360,
        "commit_id": "c412e97acba65a2a68e70ca15ea950bd31f90d3e",
        "repo": "django-cms",
        "path": "cms/tests/test_cache.py",
        "file_name": "test_cache.py",
        "fun_name": "test_cache_limit_ttl_greater_than_default_cache_ttl",
        "commit_message": "feat: add cache ttl extension point (#7299)\n\nAdds the setting `CMS_CACHE_LIMIT_TTL_CLASS` that should have a\r\n`limit_page_cache_ttl` method that would be called to limit the cache\r\nttl of a page using business logic.\r\nCloses #7296",
        "code": "def test_cache_limit_ttl_greater_than_default_cache_ttl(self):\n        \n        page1 = create_page('test page 1', 'nav_playground.html', 'en',\n                            published=True)\n        page1_url = page1.get_absolute_url()\n\n        limit_page_cache_ttl_function = \".\".join([PlaceholderCacheTestCase.__module__, limit_page_cache_ttl_test_500.__name__])\n        with self.settings(CMS_LIMIT_TTL_CACHE_FUNCTION=limit_page_cache_ttl_function):\n            page1.publish('en')\n            request = self.get_request(page1_url)\n            request.current_page = Page.objects.get(pk=page1.pk)\n            response = self.client.get(page1_url)\n            self.assertTrue('max-age=40' in response['Cache-Control'], response['Cache-Control'])  # noqa\n\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 153,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 109,
        "n_ast_nodes": 190,
        "n_identifiers": 26,
        "d_id": 17357,
        "documentation": {
            "docstring": "\n        Test the `CMS_LIMIT_TTL_CACHE_FUNCTION` setting with a class that returns a value much\n        greater thant the default value of 40 seconds.\n        ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 82288,
        "commit_id": "a3110e1ff24085373898c7d2a85f628abeb8518d",
        "repo": "django-cms",
        "path": "cms/models/managers.py",
        "file_name": "managers.py",
        "fun_name": "subordinate_to_user",
        "commit_message": "Enabled isort workflow (#7200)\n\n* Ran isort\r\n\r\n* Enabled isort workflow\r\n\r\nCo-authored-by: Vinit Kumar <mail@vinitkumar.me>",
        "code": "def subordinate_to_user(self, user, site):\n        \n        # get user level\n        from cms.utils.page_permissions import get_change_permissions_id_list\n        from cms.utils.permissions import get_user_permission_level\n\n        try:\n            user_level = get_user_permission_level(user, site)\n        except NoPermissionsException:\n            return self.none()\n\n        if user_level == ROOT_USER_LEVEL:\n            return self.all()\n\n        # get all permissions\n        page_id_allow_list = get_change_permissions_id_list(user, site, check_global=False)\n\n        # get permission set, but without objects targeting user, or any group\n        # in which he can be\n        qs = self.filter(\n            page__id__in=page_id_allow_list,\n            page__node__depth__gte=user_level,\n        )\n        qs = qs.exclude(user=user).exclude(group__user=user)\n        return qs\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 229,
        "n_words": 69,
        "vocab_size": 53,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 102,
        "n_ast_nodes": 168,
        "n_identifiers": 23,
        "d_id": 17339,
        "documentation": {
            "docstring": "Get all page permission objects on which user/group is lover in\n        hierarchy then given user and given user can change permissions on them.\n\n        !IMPORTANT, but exclude objects with given user, or any group containing\n        this user - he can't be able to change his own permissions, because if\n        he does, and removes some permissions from himself, he will not be able\n        to add them anymore.\n\n        Example:\n                                       A\n                                    /    \\\n                                  user    B,E\n                                /     \\\n                              C,X     D,Y\n\n            Gives permission nodes C,X,D,Y under user, so he can edit\n            permissions if he haves can_change_permission.\n\n        Example:\n                                      A,Y\n                                    /    \\\n                                  user    B,E,X\n                                /     \\\n                              C,X     D,Y\n\n            Gives permission nodes C,D under user, so he can edit, but not\n            anymore to X,Y, because this users are on the same level or higher\n            in page hierarchy. (but only if user have can_change_permission)\n\n        Example:\n                                        A\n                                    /      \\\n                                  user     B,E\n                                /     |      \\\n                              C,X     D,Y    user\n                                            /    \\\n                                           I      J,A\n\n            User permissions can be assigned to multiple page nodes, so merge of\n            all of them is required. In this case user can see permissions for\n            users C,X,D,Y,I,J but not A, because A user in higher in hierarchy.\n\n        If permission object holds group, this permission object can be visible\n        to user only if all of the group members are lover in hierarchy. If any\n        of members is higher then given user, this entry must stay invisible.\n\n        If user is superuser, or haves global can_change_permission permissions,\n        show him everything.\n\n        Result of this is used in admin for page permissions inline.\n        ",
            "n_words": 248,
            "vocab_size": 119,
            "n_whitespaces": 1085,
            "language": "en"
        }
    },
    {
        "id": 263956,
        "commit_id": "dc12cb59559f99110917bcbd21c9960ab57d994f",
        "repo": "pyinstaller",
        "path": "tests/unit/test_bytecode.py",
        "file_name": "test_bytecode.py",
        "fun_name": "test_finditer",
        "commit_message": "tests: fix test_finditer\n\nHave the test use bytestrings instead of strings.\n\nAlso assert that the bytecode string passed to bytecode.finditer()\nis in fact a bytestring.",
        "code": "def test_finditer():\n    \n    matches = list(finditer(re.compile(rb\"\\d+\"), b\"0123 4567 890 12 3 4\"))\n    aligned = [i.group() for i in matches]\n    assert aligned == [b\"0123\", b\"567\", b\"890\", b\"12\"]\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 37,
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        "vocab_size": 23,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 52,
        "n_ast_nodes": 84,
        "n_identifiers": 9,
        "d_id": 77525,
        "documentation": {
            "docstring": "\n    Test that bytecode.finditer() yields matches only that start on an even byte (``match.start() % 2 == 0``).\n\n    There are 3 permutations here when considering a match:\n    - A match starts on an even byte:\n        That's good! Include that sequence.\n    - A single character match starts on an odd byte:\n        Ignore it. It's a false positive.\n    - A multi-character match starts on an odd byte:\n        This match will be a false positive but there may be a genuine match shortly afterwards (in the case of the\n        # test below - it'll be the next character) which overlaps with this one so we must override regex's\n        behaviour of ignoring overlapping matches to prevent these from getting lost.\n    ",
            "n_words": 115,
            "vocab_size": 82,
            "n_whitespaces": 169,
            "language": "en"
        }
    },
    {
        "id": 167802,
        "commit_id": "f65417656ba8c59438d832b6e2a431f78d40c21c",
        "repo": "pandas",
        "path": "pandas/core/reshape/util.py",
        "file_name": "util.py",
        "fun_name": "cartesian_product",
        "commit_message": "TYP: more return annotations in core/ (#47618)\n\n* TYP: more return annotations in core/\r\n\r\n* from __future__ import annotations\r\n\r\n* more __future__",
        "code": "def cartesian_product(X) -> list[np.ndarray]:\n    \n    msg = \"Input must be a list-like of list-likes\"\n    if not is_list_like(X):\n        raise TypeError(msg)\n    for x in X:\n        if not is_list_like(x):\n            raise TypeError(msg)\n\n    if len(X) == 0:\n        return []\n\n    lenX = np.fromiter((len(x) for x in X), dtype=np.intp)\n    cumprodX = np.cumproduct(lenX)\n\n    if np.any(cumprodX < 0):\n        raise ValueError(\"Product space too large to allocate arrays!\")\n\n    a = np.roll(cumprodX, 1)\n    a[0] = 1\n\n    if cumprodX[-1] != 0:\n        b = cumprodX[-1] / cumprodX\n    else:\n        # if any factor is empty, the cartesian product is empty\n        b = np.zeros_like(cumprodX)\n\n    return [tile_compat(np.repeat(x, b[i]), np.product(a[i])) for i, x in enumerate(X)]\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 195,
        "n_words": 96,
        "vocab_size": 68,
        "complexity": 9,
        "nloc": 42,
        "token_counts": 182,
        "n_ast_nodes": 290,
        "n_identifiers": 27,
        "d_id": 40127,
        "documentation": {
            "docstring": "\n    Numpy version of itertools.product.\n    Sometimes faster (for large inputs)...\n\n    Parameters\n    ----------\n    X : list-like of list-likes\n\n    Returns\n    -------\n    product : list of ndarrays\n\n    Examples\n    --------\n    >>> cartesian_product([list('ABC'), [1, 2]])\n    [array(['A', 'A', 'B', 'B', 'C', 'C'], dtype='<U1'), array([1, 2, 1, 2, 1, 2])]\n\n    See Also\n    --------\n    itertools.product : Cartesian product of input iterables.  Equivalent to\n        nested for-loops.\n    ",
            "n_words": 56,
            "vocab_size": 46,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 168092,
        "commit_id": "62a69beddbedde349891378992c902c0b9341a9f",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "is_monotonic_decreasing",
        "commit_message": "DOC: Add numpydoc SS06 validation (#47885)",
        "code": "def is_monotonic_decreasing(self) -> bool:\n        \n        return self._engine.is_monotonic_decreasing\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 14,
        "n_ast_nodes": 25,
        "n_identifiers": 4,
        "d_id": 40199,
        "documentation": {
            "docstring": "\n        Return a boolean if the values are equal or decreasing.\n\n        Examples\n        --------\n        >>> Index([3, 2, 1]).is_monotonic_decreasing\n        True\n        >>> Index([3, 2, 2]).is_monotonic_decreasing\n        True\n        >>> Index([3, 1, 2]).is_monotonic_decreasing\n        False\n        ",
            "n_words": 27,
            "vocab_size": 20,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 206808,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/debug.py",
        "file_name": "debug.py",
        "fun_name": "get_traceback_frame_variables",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_traceback_frame_variables(self, request, tb_frame):\n        \n        # Loop through the frame's callers to see if the sensitive_variables\n        # decorator was used.\n        current_frame = tb_frame.f_back\n        sensitive_variables = None\n        while current_frame is not None:\n            if (\n                current_frame.f_code.co_name == \"sensitive_variables_wrapper\"\n                and \"sensitive_variables_wrapper\" in current_frame.f_locals\n            ):\n                # The sensitive_variables decorator was used, so we take note\n                # of the sensitive variables' names.\n                wrapper = current_frame.f_locals[\"sensitive_variables_wrapper\"]\n                sensitive_variables = getattr(wrapper, \"sensitive_variables\", None)\n                break\n            current_frame = current_frame.f_back\n\n        cleansed = {}\n        if self.is_active(request) and sensitive_variables:\n            if sensitive_variables == \"__ALL__\":\n                # Cleanse all variables\n                for name in tb_frame.f_locals:\n                    cleansed[name] = self.cleansed_substitute\n            else:\n                # Cleanse specified variables\n                for name, value in tb_frame.f_locals.items():\n                    if name in sensitive_variables:\n                        value = self.cleansed_substitute\n                    else:\n                        value = self.cleanse_special_types(request, value)\n                    cleansed[name] = value\n        else:\n            # Potentially cleanse the request and any MultiValueDicts if they\n            # are one of the frame variables.\n            for name, value in tb_frame.f_locals.items():\n                cleansed[name] = self.cleanse_special_types(request, value)\n\n        if (\n            tb_frame.f_code.co_name == \"sensitive_variables_wrapper\"\n            and \"sensitive_variables_wrapper\" in tb_frame.f_locals\n        ):\n            # For good measure, obfuscate the decorated function's arguments in\n            # the sensitive_variables decorator's frame, in case the variables\n            # associated with those arguments were meant to be obfuscated from\n            # the decorated function's frame.\n            cleansed[\"func_args\"] = self.cleansed_substitute\n            cleansed[\"func_kwargs\"] = self.cleansed_substitute\n\n        return cleansed.items()\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 757,
        "n_words": 195,
        "vocab_size": 105,
        "complexity": 13,
        "nloc": 34,
        "token_counts": 209,
        "n_ast_nodes": 355,
        "n_identifiers": 19,
        "d_id": 51719,
        "documentation": {
            "docstring": "\n        Replace the values of variables marked as sensitive with\n        stars (*********).\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 123112,
        "commit_id": "803b90729d25fda253011c505d0189e8e63cc039",
        "repo": "EasyOCR",
        "path": "easyocr/DBNet/DBNet.py",
        "file_name": "DBNet.py",
        "fun_name": "image2hmap",
        "commit_message": "add dbnet",
        "code": "def image2hmap(self, image_tensor):\n        \n        return self.model.forward(image_tensor, training=False)\n        ",
        "url": "https://github.com/JaidedAI/EasyOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 28,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 34,
        "n_identifiers": 6,
        "d_id": 27289,
        "documentation": {
            "docstring": "\n        Run the model to obtain a heatmap tensor from a image tensor. The heatmap\n        tensor indicates the probability of each pixel being a part of text area.\n\n        Parameters\n        ----------\n        image_tensor : torch.tensor\n            Image tensor.\n\n        Returns\n        -------\n        torch.tensor\n            Probability heatmap tensor.\n        ",
            "n_words": 40,
            "vocab_size": 30,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 223533,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_header_value_parser.py",
        "file_name": "_header_value_parser.py",
        "fun_name": "get_extended_attribute",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_extended_attribute(value):\n    \n    # XXX: should we have an ExtendedAttribute TokenList?\n    attribute = Attribute()\n    if value and value[0] in CFWS_LEADER:\n        token, value = get_cfws(value)\n        attribute.append(token)\n    if value and value[0] in EXTENDED_ATTRIBUTE_ENDS:\n        raise errors.HeaderParseError(\n            \"expected token but found '{}'\".format(value))\n    token, value = get_extended_attrtext(value)\n    attribute.append(token)\n    if value and value[0] in CFWS_LEADER:\n        token, value = get_cfws(value)\n        attribute.append(token)\n    return attribute, value\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 129,
        "n_words": 56,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 99,
        "n_ast_nodes": 164,
        "n_identifiers": 13,
        "d_id": 56956,
        "documentation": {
            "docstring": " [CFWS] 1*extended_attrtext [CFWS]\n\n    This is like the non-extended version except we allow % characters, so that\n    we can pick up an encoded value as a single string.\n\n    ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 73597,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/table_block/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_table_options_language",
        "commit_message": "Reformat with black",
        "code": "def test_table_options_language(self):\n        \n        # default must always contain a language value\n        block = TableBlock()\n        self.assertIn(\"language\", block.table_options)\n        # French\n        translation.activate(\"fr-fr\")\n        block_fr = TableBlock()\n        self.assertEqual(\"fr-fr\", block_fr.table_options[\"language\"])\n        translation.activate(\"it\")\n        # Italian\n        block_it = TableBlock()\n        self.assertEqual(\"it\", block_it.table_options[\"language\"])\n        # table_options with language provided, different to environment\n        block_with_lang = TableBlock(table_options={\"language\": \"ja\"})\n        self.assertNotEqual(\"it\", block_with_lang.table_options[\"language\"])\n        self.assertEqual(\"ja\", block_with_lang.table_options[\"language\"])\n        translation.activate(\"en\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 167,
        "n_words": 48,
        "vocab_size": 38,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 113,
        "n_ast_nodes": 212,
        "n_identifiers": 13,
        "d_id": 16063,
        "documentation": {
            "docstring": "\n        Test that the environment's language is used if no language provided.\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 271831,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_utils.py",
        "file_name": "training_utils.py",
        "fun_name": "get_static_batch_size",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_static_batch_size(layer):\n    \n    batch_input_shape, _ = get_input_shape_and_dtype(layer)\n    if batch_input_shape is not None:\n        return tf.compat.v1.Dimension(batch_input_shape[0]).value\n    return None\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 34,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 38,
        "n_ast_nodes": 62,
        "n_identifiers": 10,
        "d_id": 80855,
        "documentation": {
            "docstring": "Gets the static batch size of a Layer.\n\n    Args:\n      layer: a `Layer` instance.\n\n    Returns:\n      The static batch size of a Layer.\n    ",
            "n_words": 21,
            "vocab_size": 14,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 176475,
        "commit_id": "f6755ffa00211b523c6c0bec5398bc6c3c43c8b1",
        "repo": "networkx",
        "path": "networkx/algorithms/community/quality.py",
        "file_name": "quality.py",
        "fun_name": "modularity",
        "commit_message": "Update black (#5438)\n\n* CI: sync up black dev requirements version with precommit\r\n\r\n* Run black\r\n\r\nCo-authored-by: Jarrod Millman <jarrod.millman@gmail.com>",
        "code": "def modularity(G, communities, weight=\"weight\", resolution=1):\n    r\n    if not isinstance(communities, list):\n        communities = list(communities)\n    if not is_partition(G, communities):\n        raise NotAPartition(G, communities)\n\n    directed = G.is_directed()\n    if directed:\n        out_degree = dict(G.out_degree(weight=weight))\n        in_degree = dict(G.in_degree(weight=weight))\n        m = sum(out_degree.values())\n        norm = 1 / m**2\n    else:\n        out_degree = in_degree = dict(G.degree(weight=weight))\n        deg_sum = sum(out_degree.values())\n        m = deg_sum / 2\n        norm = 1 / deg_sum**2\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 145,
        "n_words": 58,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 99,
        "token_counts": 152,
        "n_ast_nodes": 226,
        "n_identifiers": 20,
        "d_id": 41926,
        "documentation": {
            "docstring": "Returns the modularity of the given partition of the graph.\n\n    Modularity is defined in [1]_ as\n\n    .. math::\n        Q = \\frac{1}{2m} \\sum_{ij} \\left( A_{ij} - \\gamma\\frac{k_ik_j}{2m}\\right)\n            \\delta(c_i,c_j)\n\n    where $m$ is the number of edges, $A$ is the adjacency matrix of `G`,\n    $k_i$ is the degree of $i$, $\\gamma$ is the resolution parameter,\n    and $\\delta(c_i, c_j)$ is 1 if $i$ and $j$ are in the same community else 0.\n\n    According to [2]_ (and verified by some algebra) this can be reduced to\n\n    .. math::\n       Q = \\sum_{c=1}^{n}\n       \\left[ \\frac{L_c}{m} - \\gamma\\left( \\frac{k_c}{2m} \\right) ^2 \\right]\n\n    where the sum iterates over all communities $c$, $m$ is the number of edges,\n    $L_c$ is the number of intra-community links for community $c$,\n    $k_c$ is the sum of degrees of the nodes in community $c$,\n    and $\\gamma$ is the resolution parameter.\n\n    The resolution parameter sets an arbitrary tradeoff between intra-group\n    edges and inter-group edges. More complex grouping patterns can be\n    discovered by analyzing the same network with multiple values of gamma\n    and then combining the results [3]_. That said, it is very common to\n    simply use gamma=1. More on the choice of gamma is in [4]_.\n\n    The second formula is the one actually used in calculation of the modularity.\n    For directed graphs the second formula replaces $k_c$ with $k^{in}_c k^{out}_c$.\n\n    Parameters\n    ----------\n    G : NetworkX Graph\n\n    communities : list or iterable of set of nodes\n        These node sets must represent a partition of G's nodes.\n\n    weight : string or None, optional (default=\"weight\")\n        The edge attribute that holds the numerical value used\n        as a weight. If None or an edge does not have that attribute,\n        then that edge has weight 1.\n\n    resolution : float (default=1)\n        If resolution is less than 1, modularity favors larger communities.\n        Greater than 1 favors smaller communities.\n\n    Returns\n    -------\n    Q : float\n        The modularity of the paritition.\n\n    Raises\n    ------\n    NotAPartition\n        If `communities` is not a partition of the nodes of `G`.\n\n    Examples\n    --------\n    >>> import networkx.algorithms.community as nx_comm\n    >>> G = nx.barbell_graph(3, 0)\n    >>> nx_comm.modularity(G, [{0, 1, 2}, {3, 4, 5}])\n    0.35714285714285715\n    >>> nx_comm.modularity(G, nx_comm.label_propagation_communities(G))\n    0.35714285714285715\n\n    References\n    ----------\n    .. [1] M. E. J. Newman \"Networks: An Introduction\", page 224.\n       Oxford University Press, 2011.\n    .. [2] Clauset, Aaron, Mark EJ Newman, and Cristopher Moore.\n       \"Finding community structure in very large networks.\"\n       Phys. Rev. E 70.6 (2004). <https://arxiv.org/abs/cond-mat/0408187>\n    .. [3] Reichardt and Bornholdt \"Statistical Mechanics of Community Detection\"\n       Phys. Rev. E 74, 016110, 2006. https://doi.org/10.1103/PhysRevE.74.016110\n    .. [4] M. E. J. Newman, \"Equivalence between modularity optimization and\n       maximum likelihood methods for community detection\"\n       Phys. Rev. E 94, 052315, 2016. https://doi.org/10.1103/PhysRevE.94.052315\n\n    ",
            "n_words": 425,
            "vocab_size": 259,
            "n_whitespaces": 682,
            "language": "en"
        }
    },
    {
        "id": 114143,
        "commit_id": "3023d6e0223e50c2d7cbe850f1c5355e5d505ceb",
        "repo": "mindsdb",
        "path": "mindsdb/api/mongo/classes/responder.py",
        "file_name": "responder.py",
        "fun_name": "handle",
        "commit_message": "renaming",
        "code": "def handle(self, query, args, env, session):\n        \n        if isinstance(self.result, dict):\n            return self.result\n        else:\n            return self.result(query, args, env, session)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 60,
        "n_words": 17,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 63,
        "n_identifiers": 9,
        "d_id": 25106,
        "documentation": {
            "docstring": " making answer based on params:\n\n        query (dict): document(s) from request\n        args (dict): all other significant information from request: flags, collection name, rows to return, etc\n        env (dict): config, model_interface instance, and other mindsdb related stuff\n        session (object): current session\n\n        returns documents as dict or list of dicts\n        ",
            "n_words": 47,
            "vocab_size": 42,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 276712,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/control_flow_util.py",
        "file_name": "control_flow_util.py",
        "fun_name": "GetContainingXLAContext",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def GetContainingXLAContext(ctxt):\n    \n    while ctxt:\n        if ctxt.IsXLAContext():\n            return ctxt\n        ctxt = ctxt.outer_context\n    return None\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 25,
        "n_ast_nodes": 44,
        "n_identifiers": 4,
        "d_id": 81705,
        "documentation": {
            "docstring": "Returns the first ancestor XLAContext of `ctxt`.\n\n    Returns `ctxt` if `ctxt` is a XLAContext, or None if `ctxt` is not in a\n    while loop.\n\n    Args:\n      ctxt: ControlFlowContext\n\n    Returns:\n      `ctxt` if `ctxt` is a XLAContext, the most nested XLAContext containing\n      `ctxt`, or None if `ctxt` is not in a while loop.\n    ",
            "n_words": 50,
            "vocab_size": 26,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 100921,
        "commit_id": "f2e6f24651f62b28ccfb412180baca0aa7baf96a",
        "repo": "faceswap",
        "path": "lib/vgg_face.py",
        "file_name": "vgg_face.py",
        "fun_name": "get_model",
        "commit_message": "Centralize model storage",
        "code": "def get_model(self, git_model_id, model_filename, backend):\n        \n        model = GetModel(model_filename, git_model_id).model_path\n        model = cv2.dnn.readNetFromCaffe(model[1], model[0])\n        model.setPreferableTarget(self.get_backend(backend))\n        return model\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 51,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 53,
        "n_ast_nodes": 81,
        "n_identifiers": 13,
        "d_id": 20368,
        "documentation": {
            "docstring": " Check if model is available, if not, download and unzip it ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 219662,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "copy_sign",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def copy_sign(self, a, b):\n        \n        a = _convert_other(a, raiseit=True)\n        return a.copy_sign(b)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 43,
        "n_identifiers": 6,
        "d_id": 55690,
        "documentation": {
            "docstring": "Copies the second operand's sign to the first one.\n\n        In detail, it returns a copy of the first operand with the sign\n        equal to the sign of the second operand.\n\n        >>> ExtendedContext.copy_sign(Decimal( '1.50'), Decimal('7.33'))\n        Decimal('1.50')\n        >>> ExtendedContext.copy_sign(Decimal('-1.50'), Decimal('7.33'))\n        Decimal('1.50')\n        >>> ExtendedContext.copy_sign(Decimal( '1.50'), Decimal('-7.33'))\n        Decimal('-1.50')\n        >>> ExtendedContext.copy_sign(Decimal('-1.50'), Decimal('-7.33'))\n        Decimal('-1.50')\n        >>> ExtendedContext.copy_sign(1, -2)\n        Decimal('-1')\n        >>> ExtendedContext.copy_sign(Decimal(1), -2)\n        Decimal('-1')\n        >>> ExtendedContext.copy_sign(1, Decimal(-2))\n        Decimal('-1')\n        ",
            "n_words": 60,
            "vocab_size": 32,
            "n_whitespaces": 179,
            "language": "en"
        }
    },
    {
        "id": 244039,
        "commit_id": "cac356380d505bf15587f07c0529218cc36b9652",
        "repo": "mmdetection",
        "path": "mmdet/models/dense_heads/maskformer_head.py",
        "file_name": "maskformer_head.py",
        "fun_name": "forward",
        "commit_message": "[Feature] Add Maskformer to mmdet (#7212)\n\n* first commit\r\n\r\n* add README\r\n\r\n* move model description from config to readme\r\n\r\nadd description for binary_input\r\n\r\nadd description for dice loss\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nremove compatibility of pretrain in maskformer\r\n\r\n* update comments in maskformer_head\r\n\r\n* update docs format",
        "code": "def forward(self, feats, img_metas):\n        \n        batch_size = len(img_metas)\n        input_img_h, input_img_w = img_metas[0]['batch_input_shape']\n        padding_mask = feats[-1].new_ones(\n            (batch_size, input_img_h, input_img_w), dtype=torch.float32)\n        for i in range(batch_size):\n            img_h, img_w, _ = img_metas[i]['img_shape']\n            padding_mask[i, :img_h, :img_w] = 0\n        padding_mask = F.interpolate(\n            padding_mask.unsqueeze(1),\n            size=feats[-1].shape[-2:],\n            mode='nearest').to(torch.bool).squeeze(1)\n        # when backbone is swin, memory is output of last stage of swin.\n        # when backbone is r50, memory is output of tranformer encoder.\n        mask_features, memory = self.pixel_decoder(feats, img_metas)\n        pos_embed = self.decoder_pe(padding_mask)\n        memory = self.decoder_input_proj(memory)\n        # shape (batch_size, c, h, w) -> (h*w, batch_size, c)\n        memory = memory.flatten(2).permute(2, 0, 1)\n        pos_embed = pos_embed.flatten(2).permute(2, 0, 1)\n        # shape (batch_size, h * w)\n        padding_mask = padding_mask.flatten(1)\n        # shape = (num_queries, embed_dims)\n        query_embed = self.query_embed.weight\n        # shape = (num_queries, batch_size, embed_dims)\n        query_embed = query_embed.unsqueeze(1).repeat(1, batch_size, 1)\n        target = torch.zeros_like(query_embed)\n        # shape (num_decoder, num_queries, batch_size, embed_dims)\n        out_dec = self.transformer_decoder(\n            query=target,\n            key=memory,\n            value=memory,\n            key_pos=pos_embed,\n            query_pos=query_embed,\n            key_padding_mask=padding_mask)\n        # shape (num_decoder, batch_size, num_queries, embed_dims)\n        out_dec = out_dec.transpose(1, 2)\n\n        # cls_scores\n        all_cls_scores = self.cls_embed(out_dec)\n\n        # mask_preds\n        mask_embed = self.mask_embed(out_dec)\n        all_mask_preds = torch.einsum('lbqc,bchw->lbqhw', mask_embed,\n                                      mask_features)\n\n        return all_cls_scores, all_mask_preds\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 553,
        "n_words": 167,
        "vocab_size": 97,
        "complexity": 2,
        "nloc": 34,
        "token_counts": 302,
        "n_ast_nodes": 475,
        "n_identifiers": 54,
        "d_id": 70209,
        "documentation": {
            "docstring": "Forward function.\n\n        Args:\n            feats (list[Tensor]): Features from the upstream network, each\n                is a 4D-tensor.\n            img_metas (list[dict]): List of image information.\n\n        Returns:\n            all_cls_scores (Tensor): Classification scores for each\\\n                scale level. Each is a 4D-tensor with shape\\\n                (num_decoder, batch_size, num_queries, cls_out_channels).\\\n                Note `cls_out_channels` should includes background.\n            all_mask_preds (Tensor): Mask scores for each decoder\\\n                layer. Each with shape (num_decoder, batch_size,\\\n                num_queries, h, w).\n        ",
            "n_words": 60,
            "vocab_size": 50,
            "n_whitespaces": 215,
            "language": "en"
        }
    },
    {
        "id": 321379,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/keyinput/test_keyutils.py",
        "file_name": "test_keyutils.py",
        "fun_name": "test_text",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_text(self, qt_key, upper):\n        \n        modifiers = Qt.KeyboardModifier.ShiftModifier if upper else Qt.KeyboardModifiers()\n        info = keyutils.KeyInfo(qt_key.member, modifiers=modifiers)\n        expected = qt_key.uppertext if upper else qt_key.text\n        assert info.text() == expected\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 61,
        "n_words": 26,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 58,
        "n_ast_nodes": 90,
        "n_identifiers": 16,
        "d_id": 117685,
        "documentation": {
            "docstring": "Test KeyInfo.text() with all possible keys.\n\n        See key_data.py for inputs and expected values.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 215977,
        "commit_id": "f2a783643de61cac1ff3288b40241e5ce6e1ddc8",
        "repo": "salt",
        "path": "salt/states/linux_acl.py",
        "file_name": "linux_acl.py",
        "fun_name": "present",
        "commit_message": "Update to latest ``pyupgrade`` hook. Stop skipping it on CI.\n\nSigned-off-by: Pedro Algarvio <palgarvio@vmware.com>",
        "code": "def present(name, acl_type, acl_name=\"\", perms=\"\", recurse=False, force=False):\n    \n    ret = {\"name\": name, \"result\": True, \"changes\": {}, \"comment\": \"\"}\n\n    _octal = {\"r\": 4, \"w\": 2, \"x\": 1, \"-\": 0}\n    _octal_lookup = {0: \"-\", 1: \"r\", 2: \"w\", 4: \"x\"}\n\n    if not os.path.exists(name):\n        ret[\"comment\"] = \"{} does not exist\".format(name)\n        ret[\"result\"] = False\n        return ret\n\n    __current_perms = __salt__[\"acl.getfacl\"](name, recursive=recurse)\n\n    if acl_type.startswith((\"d:\", \"default:\")):\n        _acl_type = \":\".join(acl_type.split(\":\")[1:])\n        _current_perms = __current_perms[name].get(\"defaults\", {})\n        _default = True\n    else:\n        _acl_type = acl_type\n        _current_perms = __current_perms[name]\n        _default = False\n\n    # The getfacl execution module lists default with empty names as being\n    # applied to the user/group that owns the file, e.g.,\n    # default:group::rwx would be listed as default:group:root:rwx\n    # In this case, if acl_name is empty, we really want to search for root\n    # but still uses '' for other\n\n    # We search through the dictionary getfacl returns for the owner of the\n    # file if acl_name is empty.\n    if acl_name == \"\":\n        _search_name = __current_perms[name].get(\"comment\").get(_acl_type, \"\")\n    else:\n        _search_name = acl_name\n\n    if _current_perms.get(_acl_type, None) or _default:\n        try:\n            user = [\n                i\n                for i in _current_perms[_acl_type]\n                if next(iter(i.keys())) == _search_name\n            ].pop()\n        except (AttributeError, IndexError, StopIteration, KeyError):\n            user = None\n\n        if user:\n            octal_sum = sum(_octal.get(i, i) for i in perms)\n            need_refresh = False\n            # If recursive check all paths retrieved via acl.getfacl\n            if recurse:\n                for path in __current_perms:\n                    acl_found = False\n                    if _default:\n                        # Recusive default acls only apply to directories\n                        if not os.path.isdir(path):\n                            continue\n                        _current_perms_path = __current_perms[path].get(\"defaults\", {})\n                    else:\n                        _current_perms_path = __current_perms[path]\n                    for user_acl in _current_perms_path.get(_acl_type, []):\n                        if (\n                            _search_name in user_acl\n                            and user_acl[_search_name][\"octal\"] == octal_sum\n                        ):\n                            acl_found = True\n                    if not acl_found:\n                        need_refresh = True\n                        break\n\n            # Check the permissions from the already located file\n            elif user[_search_name][\"octal\"] == sum(_octal.get(i, i) for i in perms):\n                need_refresh = False\n            # If they don't match then refresh\n            else:\n                need_refresh = True\n\n            if not need_refresh:\n                ret[\"comment\"] = \"Permissions are in the desired state\"\n            else:\n                _num = user[_search_name][\"octal\"]\n                new_perms = \"{}{}{}\".format(\n                    _octal_lookup[_num & 1],\n                    _octal_lookup[_num & 2],\n                    _octal_lookup[_num & 4],\n                )\n                changes = {\n                    \"new\": {\"acl_name\": acl_name, \"acl_type\": acl_type, \"perms\": perms},\n                    \"old\": {\n                        \"acl_name\": acl_name,\n                        \"acl_type\": acl_type,\n                        \"perms\": new_perms,\n                    },\n                }\n\n                if __opts__[\"test\"]:\n                    ret.update(\n                        {\n                            \"comment\": (\n                                \"Updated permissions will be applied for \"\n                                \"{}: {} -> {}\".format(acl_name, new_perms, perms)\n                            ),\n                            \"result\": None,\n                            \"changes\": changes,\n                        }\n                    )\n                    return ret\n                try:\n                    if force:\n                        __salt__[\"acl.wipefacls\"](\n                            name, recursive=recurse, raise_err=True\n                        )\n\n                    __salt__[\"acl.modfacl\"](\n                        acl_type,\n                        acl_name,\n                        perms,\n                        name,\n                        recursive=recurse,\n                        raise_err=True,\n                    )\n                    ret.update(\n                        {\n                            \"comment\": \"Updated permissions for {}\".format(acl_name),\n                            \"result\": True,\n                            \"changes\": changes,\n                        }\n                    )\n                except CommandExecutionError as exc:\n                    ret.update(\n                        {\n                            \"comment\": \"Error updating permissions for {}: {}\".format(\n                                acl_name, exc.strerror\n                            ),\n                            \"result\": False,\n                        }\n                    )\n        else:\n            changes = {\n                \"new\": {\"acl_name\": acl_name, \"acl_type\": acl_type, \"perms\": perms}\n            }\n\n            if __opts__[\"test\"]:\n                ret.update(\n                    {\n                        \"comment\": \"New permissions will be applied for {}: {}\".format(\n                            acl_name, perms\n                        ),\n                        \"result\": None,\n                        \"changes\": changes,\n                    }\n                )\n                ret[\"result\"] = None\n                return ret\n\n            try:\n                if force:\n                    __salt__[\"acl.wipefacls\"](name, recursive=recurse, raise_err=True)\n\n                __salt__[\"acl.modfacl\"](\n                    acl_type, acl_name, perms, name, recursive=recurse, raise_err=True\n                )\n                ret.update(\n                    {\n                        \"comment\": \"Applied new permissions for {}\".format(acl_name),\n                        \"result\": True,\n                        \"changes\": changes,\n                    }\n                )\n            except CommandExecutionError as exc:\n                ret.update(\n                    {\n                        \"comment\": \"Error updating permissions for {}: {}\".format(\n                            acl_name, exc.strerror\n                        ),\n                        \"result\": False,\n                    }\n                )\n\n    else:\n        ret[\"comment\"] = \"ACL Type does not exist\"\n        ret[\"result\"] = False\n\n    return ret\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 3212,
        "n_words": 522,
        "vocab_size": 248,
        "complexity": 28,
        "nloc": 155,
        "token_counts": 807,
        "n_ast_nodes": 1365,
        "n_identifiers": 51,
        "d_id": 54297,
        "documentation": {
            "docstring": "\n    Ensure a Linux ACL is present\n\n    name\n        The acl path\n\n    acl_type\n        The type of the acl is used for it can be 'user' or 'group'\n\n    acl_name\n        The  user or group\n\n    perms\n        Set the permissions eg.: rwx\n\n    recurse\n        Set the permissions recursive in the path\n\n    force\n        Wipe out old permissions and ensure only the new permissions are set\n    ",
            "n_words": 57,
            "vocab_size": 43,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 92391,
        "commit_id": "c4cc0467974bcfb2b3c95120bd19c337aa977183",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_postgres_indexer.py",
        "file_name": "test_postgres_indexer.py",
        "fun_name": "test_rate_limited",
        "commit_message": "feat(metrics_indexer): Add rate limits functionality to indexer [INGEST-1380] (#36263)\n\n* feat(metrics_indexer): Add rate limits functionality to indexer [INGEST-1380]\r\n\r\nThe postgres string indexer now is able to rate limit writes using four\r\nsentry options. If that happens, `None` is returned in place of an\r\ninteger, and the FetchType is RATE_LIMITED.\r\n\r\nThe kafka consumer/message processor explicitly checks for those `None`\r\nvalues and throws away every message that references a rate-limited\r\nstring. It logs a Sentry error for every dropped message just because\r\nthat's already what we do for other kinds of dropped messages.\r\n\r\nRate limiting and quota management currently creates a ton of\r\ndataclasses and that probably wastes time. There are a ton of\r\nlow-hanging fruits:\r\n\r\n* the return value of _construct_quotas could be globally cached, as\r\n  long as the cache is wiped when the sentry options change.\r\n\r\n* the same Quota object (for global limits) is referenced from multiple\r\n  RequestedQuota instances (one for each org).\r\n  `sentry.ratelimits.sliding_windows` could check the `id()` of the\r\n  quota (if there is no prefix override) to avoid computing and checking\r\n  the same quota multiple times.\r\n\r\nAn even lower hanging fruit is that we're fetching the same keys from\r\nRedis multiple times, because multiple organizations (and therefore\r\nmultiple RequestedQuota instances) adhere to the global quota. So that's\r\nbeen fixed, but as for the rest let's wait for timings from prod.\r\n\r\n* fix typo\r\n\r\n* fix typing\r\n\r\n* apply review feedback\r\n\r\n* fix typing, add test\r\n\r\n* fix tests\r\n\r\n* apply review feedback about logging too many msgs\r\n\r\n* fix leaking option in test\r\n\r\n* sike, more test failures",
        "code": "def test_rate_limited(self):\n        \n        org_strings = {1: {\"a\", \"b\", \"c\"}, 2: {\"e\", \"f\"}, 3: {\"g\"}}\n\n        with override_options(\n            {\n                \"sentry-metrics.writes-limiter.limits.releasehealth.per-org\": [\n                    {\"window_seconds\": 10, \"granularity_seconds\": 10, \"limit\": 1}\n                ],\n            }\n        ):\n            results = self.indexer.bulk_record(\n                use_case_id=self.use_case_id, org_strings=org_strings\n            )\n\n        assert len(results[1]) == 3\n        assert len(results[2]) == 2\n        assert len(results[3]) == 1\n        assert results[3][\"g\"] is not None\n\n        rate_limited_strings = set()\n\n        for org_id in 1, 2, 3:\n            for k, v in results[org_id].items():\n                if v is None:\n                    rate_limited_strings.add(k)\n\n        assert len(rate_limited_strings) == 3\n        assert \"g\" not in rate_limited_strings\n\n        for string in rate_limited_strings:\n            assert results.get_fetch_metadata()[string] == (\n                None,\n                FetchType.RATE_LIMITED,\n                FetchTypeExt(is_global=False),\n            )\n\n        org_strings = {1: rate_limited_strings}\n\n        with override_options(\n            {\n                \"sentry-metrics.writes-limiter.limits.releasehealth.global\": [\n                    {\"window_seconds\": 10, \"granularity_seconds\": 10, \"limit\": 2}\n                ],\n            }\n        ):\n            results = self.indexer.bulk_record(\n                use_case_id=self.use_case_id, org_strings=org_strings\n            )\n\n        rate_limited_strings2 = set()\n        for k, v in results[1].items():\n            if v is None:\n                rate_limited_strings2.add(k)\n\n        assert len(rate_limited_strings2) == 1\n        assert len(rate_limited_strings - rate_limited_strings2) == 2\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 631,
        "n_words": 137,
        "vocab_size": 75,
        "complexity": 7,
        "nloc": 46,
        "token_counts": 294,
        "n_ast_nodes": 476,
        "n_identifiers": 23,
        "d_id": 18908,
        "documentation": {
            "docstring": "\n        Assert that rate limits per-org and globally are applied at all.\n\n        Since we don't have control over ordering in sets/dicts, we have no\n        control over which string gets rate-limited. That makes assertions\n        quite awkward and imprecise.\n        ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 34808,
        "commit_id": "44b21f117bcf71e3d88a11c3523c94b27949fdbf",
        "repo": "transformers",
        "path": "src/transformers/modeling_flax_utils.py",
        "file_name": "modeling_flax_utils.py",
        "fun_name": "register_for_auto_class",
        "commit_message": "Save code of registered custom models (#15379)\n\n* Allow dynamic modules to use relative imports\r\n\r\n* Work for configs\r\n\r\n* Fix last merge conflict\r\n\r\n* Save code of registered custom objects\r\n\r\n* Map strings to strings\r\n\r\n* Fix test\r\n\r\n* Add tokenizer\r\n\r\n* Rework tests\r\n\r\n* Tests\r\n\r\n* Ignore fixtures py files for tests\r\n\r\n* Tokenizer test + fix collection\r\n\r\n* With full path\r\n\r\n* Rework integration\r\n\r\n* Fix typo\r\n\r\n* Remove changes in conftest\r\n\r\n* Test for tokenizers\r\n\r\n* Add documentation\r\n\r\n* Update docs/source/custom_models.mdx\r\n\r\nCo-authored-by: Lysandre Debut <lysandre@huggingface.co>\r\n\r\n* Add file structure and file content\r\n\r\n* Add more doc\r\n\r\n* Style\r\n\r\n* Update docs/source/custom_models.mdx\r\n\r\nCo-authored-by: Suraj Patil <surajp815@gmail.com>\r\n\r\n* Address review comments\r\n\r\nCo-authored-by: Lysandre Debut <lysandre@huggingface.co>\r\nCo-authored-by: Suraj Patil <surajp815@gmail.com>",
        "code": "def register_for_auto_class(cls, auto_class=\"FlaxAutoModel\"):\n        \n        if not isinstance(auto_class, str):\n            auto_class = auto_class.__name__\n\n        import transformers.models.auto as auto_module\n\n        if not hasattr(auto_module, auto_class):\n            raise ValueError(f\"{auto_class} is not a valid auto class.\")\n\n        cls._auto_class = auto_class\n\n\n# To update the docstring, we need to copy the method, otherwise we change the original docstring.\nFlaxPreTrainedModel.push_to_hub = copy_func(FlaxPreTrainedModel.push_to_hub)\nFlaxPreTrainedModel.push_to_hub.__doc__ = FlaxPreTrainedModel.push_to_hub.__doc__.format(\n    object=\"model\", object_class=\"FlaxAutoModel\", object_files=\"model checkpoint\"\n)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 113,
        "n_words": 57,
        "vocab_size": 47,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 52,
        "n_ast_nodes": 150,
        "n_identifiers": 21,
        "d_id": 6342,
        "documentation": {
            "docstring": "\n        Register this class with a given auto class. This should only be used for custom models as the ones in the\n        library are already mapped with an auto class.\n\n        Args:\n            auto_class (`str` or `type`, *optional*, defaults to `\"FlaxAutoModel\"`):\n                The auto class to register this new model with.\n        ",
            "n_words": 47,
            "vocab_size": 39,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 70498,
        "commit_id": "4248d406c011d6ba6207bb0e0e9b885813d961be",
        "repo": "wagtail",
        "path": "wagtail/search/backends/database/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "SearchBackend",
        "commit_message": "Test for presence of fts5 extension in sqlite backend initialisation and migration",
        "code": "def SearchBackend(params):\n    \n    if connection.vendor == 'postgresql':\n        from .postgres.postgres import PostgresSearchBackend\n        return PostgresSearchBackend(params)\n    elif connection.vendor == 'mysql':\n        from .mysql.mysql import MySQLSearchBackend\n        return MySQLSearchBackend(params)\n    elif connection.vendor == 'sqlite':\n        from .sqlite.utils import fts5_available\n        if fts5_available():\n            from .sqlite.sqlite import SQLiteSearchBackend\n            return SQLiteSearchBackend(params)\n        else:\n            from .fallback import DatabaseSearchBackend\n            return DatabaseSearchBackend(params)\n    else:\n        from .fallback import DatabaseSearchBackend\n        return DatabaseSearchBackend(params)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 174,
        "n_words": 52,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 99,
        "n_ast_nodes": 177,
        "n_identifiers": 14,
        "d_id": 15513,
        "documentation": {
            "docstring": "\n    Returns the appropriate search backend for the current 'default' database system\n    ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 258535,
        "commit_id": "330881a21ca48c543cc8a67aa0d4e4c1dc1001ab",
        "repo": "scikit-learn",
        "path": "sklearn/neighbors/tests/test_nca.py",
        "file_name": "test_nca.py",
        "fun_name": "test_nca_feature_names_out",
        "commit_message": "ENH Adds get_feature_names_out to neighbors module (#22212)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>",
        "code": "def test_nca_feature_names_out():\n    \n\n    X = iris_data\n    y = iris_target\n\n    est = NeighborhoodComponentsAnalysis().fit(X, y)\n    names_out = est.get_feature_names_out()\n\n    class_name_lower = est.__class__.__name__.lower()\n    expected_names_out = np.array(\n        [f\"{class_name_lower}{i}\" for i in range(est.components_.shape[1])],\n        dtype=object,\n    )\n    assert_array_equal(names_out, expected_names_out)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 71,
        "n_words": 30,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 77,
        "n_ast_nodes": 132,
        "n_identifiers": 24,
        "d_id": 75280,
        "documentation": {
            "docstring": "Check `get_feature_names_out` for `NeighborhoodComponentsAnalysis`.",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 3,
            "language": "en"
        }
    },
    {
        "id": 257593,
        "commit_id": "632cd1c141a8b485c6ef8695685d2d8eef3ca50f",
        "repo": "haystack",
        "path": "rest_api/test/test_rest_api.py",
        "file_name": "test_rest_api.py",
        "fun_name": "test_query_with_bool_in_params",
        "commit_message": "Allow values that are not dictionaries in the request params in the `/search` endpoint (#2720)\n\n* let params contain something else than dictionaries\r\n\r\n* rewrite the test same style as the main branch",
        "code": "def test_query_with_bool_in_params(client):\n    \n    with mock.patch(\"rest_api.controller.search.query_pipeline\") as mocked_pipeline:\n        # `run` must return a dictionary containing a `query` key\n        mocked_pipeline.run.return_value = {\"query\": TEST_QUERY}\n        request_body = {\n            \"query\": TEST_QUERY,\n            \"params\": {\"debug\": True, \"Retriever\": {\"top_k\": 5}, \"Reader\": {\"top_k\": 3}},\n        }\n        response = client.post(url=\"/query\", json=request_body)\n        assert 200 == response.status_code\n        response_json = response.json()\n        assert response_json[\"documents\"] == []\n        assert response_json[\"answers\"] == []\n\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 145,
        "n_words": 54,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 102,
        "n_ast_nodes": 185,
        "n_identifiers": 15,
        "d_id": 75098,
        "documentation": {
            "docstring": "\n    Ensure items of params can be other types than dictionary, see\n    https://github.com/deepset-ai/haystack/issues/2656\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 100531,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/cli/launcher.py",
        "file_name": "launcher.py",
        "fun_name": "_setup_amd",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def _setup_amd(cls, arguments):\n        \n        logger.debug(\"Setting up for AMD\")\n        try:\n            import plaidml  # noqa pylint:disable=unused-import,import-outside-toplevel\n        except ImportError:\n            logger.error(\"PlaidML not found. Run `pip install plaidml-keras` for AMD support\")\n            return False\n        from lib.gpu_stats import setup_plaidml  # pylint:disable=import-outside-toplevel\n        setup_plaidml(arguments.loglevel, arguments.exclude_gpus)\n        logger.debug(\"setup up for PlaidML\")\n        return True\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 132,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 53,
        "n_ast_nodes": 96,
        "n_identifiers": 13,
        "d_id": 19995,
        "documentation": {
            "docstring": " Test for plaidml and perform setup for AMD.\n\n        Parameters\n        ----------\n        arguments: :class:`argparse.Namespace`\n            The command line arguments passed to Faceswap.\n        ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 176550,
        "commit_id": "5a7985fc41bc0c686c035de43c66cf4fb5fcc94f",
        "repo": "networkx",
        "path": "networkx/algorithms/tree/recognition.py",
        "file_name": "recognition.py",
        "fun_name": "is_arborescence",
        "commit_message": "Added examples in tournament and tree functions (#5536)\n\n* examples\r\n\r\n* examples\r\n\r\n* examples\r\n\r\n* Example changed\r\n\r\n* improved styling\r\n\r\n* revised\r\n\r\n* edge labels\r\n\r\n* improved styling\r\n\r\n* spacing\r\n\r\n* error testing\r\n\r\n* examples\r\n\r\n* styling\r\n\r\n* add_nodes removed\r\n\r\n* spaceing\r\n\r\n* spacing\r\n\r\n* spacing\r\n\r\n* added examples\r\n\r\n* removed random_tournament example\r\n\r\n* added examples in branching and aborescence\r\n\r\n* error removed",
        "code": "def is_arborescence(G):\n    \n    return is_tree(G) and max(d for n, d in G.in_degree()) <= 1\n\n\n@nx.utils.not_implemented_for(\"undirected\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@nx.utils.not_implemented_for(\"undirected\")",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 19,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 2,
        "token_counts": 28,
        "n_ast_nodes": 64,
        "n_identifiers": 10,
        "d_id": 41959,
        "documentation": {
            "docstring": "\n    Returns True if `G` is an arborescence.\n\n    An arborescence is a directed tree with maximum in-degree equal to 1.\n\n    Parameters\n    ----------\n    G : graph\n        The graph to test.\n\n    Returns\n    -------\n    b : bool\n        A boolean that is True if `G` is an arborescence.\n\n    Examples\n    --------\n    >>> G = nx.DiGraph([(0, 1), (0, 2), (2, 3), (3, 4)])\n    >>> nx.is_arborescence(G)\n    True\n    >>> G.remove_edge(0, 1)\n    >>> G.add_edge(1, 2)  # maximum in-degree is 2\n    >>> nx.is_arborescence(G)\n    False\n\n    Notes\n    -----\n    In another convention, an arborescence is known as a *tree*.\n\n    See Also\n    --------\n    is_tree\n\n    ",
            "n_words": 89,
            "vocab_size": 62,
            "n_whitespaces": 177,
            "language": "en"
        }
    },
    {
        "id": 248167,
        "commit_id": "116a4c8340b729ffde43be33df24d417384cb28b",
        "repo": "synapse",
        "path": "tests/rest/client/test_sync.py",
        "file_name": "test_sync.py",
        "fun_name": "test_public_receipt_can_override_private",
        "commit_message": "Implement changes to MSC2285 (hidden read receipts) (#12168)\n\n* Changes hidden read receipts to be a separate receipt type\r\n  (instead of a field on `m.read`).\r\n* Updates the `/receipts` endpoint to accept `m.fully_read`.",
        "code": "def test_public_receipt_can_override_private(self) -> None:\n        \n        # Send a message as the first user\n        res = self.helper.send(self.room_id, body=\"hello\", tok=self.tok)\n\n        # Send a private read receipt\n        channel = self.make_request(\n            \"POST\",\n            f\"/rooms/{self.room_id}/receipt/{ReceiptTypes.READ_PRIVATE}/{res['event_id']}\",\n            {},\n            access_token=self.tok2,\n        )\n        self.assertEqual(channel.code, 200)\n        self.assertIsNone(self._get_read_receipt())\n\n        # Send a public read receipt\n        channel = self.make_request(\n            \"POST\",\n            f\"/rooms/{self.room_id}/receipt/{ReceiptTypes.READ}/{res['event_id']}\",\n            {},\n            access_token=self.tok2,\n        )\n        self.assertEqual(channel.code, 200)\n\n        # Test that we did override the private read receipt\n        self.assertNotEqual(self._get_read_receipt(), None)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 248,
        "n_words": 62,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 114,
        "n_ast_nodes": 232,
        "n_identifiers": 20,
        "d_id": 72135,
        "documentation": {
            "docstring": "\n        Sending a public read receipt to the same event which has a private read\n        receipt should cause that receipt to become public.\n        ",
            "n_words": 22,
            "vocab_size": 17,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 108693,
        "commit_id": "7bafb8be7c6e81180e9518a91d10da9422321a0c",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backends/backend_pgf.py",
        "file_name": "backend_pgf.py",
        "fun_name": "_print_pgf_to_fh",
        "commit_message": "Deprecate internal use of get/set dpi",
        "code": "def _print_pgf_to_fh(self, fh, *, bbox_inches_restore=None):\n\n        header_text = \n\n        # append the preamble used by the backend as a comment for debugging\n        header_info_preamble = [\"%% Matplotlib used the following preamble\"]\n        for line in _get_preamble().splitlines():\n            header_info_preamble.append(\"%%   \" + line)\n        header_info_preamble.append(\"%%\")\n        header_info_preamble = \"\\n\".join(header_info_preamble)\n\n        # get figure size in inch\n        w, h = self.figure.get_figwidth(), self.figure.get_figheight()\n        dpi = self.figure.dpi\n\n        # create pgfpicture environment and write the pgf code\n        fh.write(header_text)\n        fh.write(header_info_preamble)\n        fh.write(\"\\n\")\n        _writeln(fh, r\"\\begingroup\")\n        _writeln(fh, r\"\\makeatletter\")\n        _writeln(fh, r\"\\begin{pgfpicture}\")\n        _writeln(fh,\n                 r\"\\pgfpathrectangle{\\pgfpointorigin}{\\pgfqpoint{%fin}{%fin}}\"\n                 % (w, h))\n        _writeln(fh, r\"\\pgfusepath{use as bounding box, clip}\")\n        renderer = MixedModeRenderer(self.figure, w, h, dpi,\n                                     RendererPgf(self.figure, fh),\n                                     bbox_inches_restore=bbox_inches_restore)\n        self.figure.draw(renderer)\n\n        # end the pgfpicture environment\n        _writeln(fh, r\"\\end{pgfpicture}\")\n        _writeln(fh, r\"\\makeatother\")\n        _writeln(fh, r\"\\endgroup\")\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 389,
        "n_words": 104,
        "vocab_size": 77,
        "complexity": 2,
        "nloc": 46,
        "token_counts": 195,
        "n_ast_nodes": 327,
        "n_identifiers": 23,
        "d_id": 23310,
        "documentation": {
            "docstring": "%% Creator: Matplotlib, PGF backend\n%%\n%% To include the figure in your LaTeX document, write\n%%   \\\\input{<filename>.pgf}\n%%\n%% Make sure the required packages are loaded in your preamble\n%%   \\\\usepackage{pgf}\n%%\n%% Also ensure that all the required font packages are loaded; for instance,\n%% the lmodern package is sometimes necessary when using math font.\n%%   \\\\usepackage{lmodern}\n%%\n%% Figures using additional raster images can only be included by \\\\input if\n%% they are in the same directory as the main LaTeX file. For loading figures\n%% from other directories you can use the `import` package\n%%   \\\\usepackage{import}\n%%\n%% and then include the figures with\n%%   \\\\import{<path to file>}{<filename>.pgf}\n%%\n",
            "n_words": 113,
            "vocab_size": 74,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 130580,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/data/dataset.py",
        "file_name": "dataset.py",
        "fun_name": "to_pandas_refs",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def to_pandas_refs(self) -> List[ObjectRef[\"pandas.DataFrame\"]]:\n        \n\n        block_to_df = cached_remote_fn(_block_to_df)\n        return [block_to_df.remote(block) for block in self._blocks.get_blocks()]\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 39,
        "n_ast_nodes": 65,
        "n_identifiers": 11,
        "d_id": 29316,
        "documentation": {
            "docstring": "Convert this dataset into a distributed set of Pandas dataframes.\n\n        This is only supported for datasets convertible to Arrow records.\n        This function induces a copy of the data. For zero-copy access to the\n        underlying data, consider using ``.to_arrow()`` or\n        ``.get_internal_block_refs()``.\n\n        Time complexity: O(dataset size / parallelism)\n\n        Returns:\n            A list of remote Pandas dataframes created from this dataset.\n        ",
            "n_words": 57,
            "vocab_size": 49,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 275252,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_experimental/adamw.py",
        "file_name": "adamw.py",
        "fun_name": "build",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def build(self, var_list, exclude_from_weight_decay=None):\n        \n        super().build(var_list)\n        if hasattr(self, \"_built\") and self._built:\n            return\n        self._built = True\n        if not hasattr(self, \"_exclude_from_weight_decay\"):\n            self._exclude_from_weight_decay = exclude_from_weight_decay or []\n        self._momentums = []\n        self._velocities = []\n        for var in var_list:\n            self._momentums.append(\n                self.add_variable_from_reference(\n                    model_variable=var, variable_name=\"m\"\n                )\n            )\n            self._velocities.append(\n                self.add_variable_from_reference(\n                    model_variable=var, variable_name=\"v\"\n                )\n            )\n        if self.amsgrad:\n            self._velocity_hats = []\n            for var in var_list:\n                self._velocity_hats.append(\n                    self.add_variable_from_reference(\n                        model_variable=var, variable_name=\"vhat\"\n                    )\n                )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 400,
        "n_words": 60,
        "vocab_size": 37,
        "complexity": 8,
        "nloc": 28,
        "token_counts": 145,
        "n_ast_nodes": 238,
        "n_identifiers": 17,
        "d_id": 81348,
        "documentation": {
            "docstring": "Initialize optimizer variables.\n\n        AdamW optimizer has 3 types of variables: momentums, velocities and\n        velocity_hat (only set when amsgrad is applied),\n\n        Args:\n          var_list: list of model variables to build AdamW variables on.\n          exclude_from_weight_decay: list of model variables that will be excluded\n            from weight decay.\n        ",
            "n_words": 43,
            "vocab_size": 35,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 312993,
        "commit_id": "243d003acc11d638feb3867410c3cbb1987520bc",
        "repo": "core",
        "path": "homeassistant/components/moehlenhoff_alpha2/config_flow.py",
        "file_name": "config_flow.py",
        "fun_name": "validate_input",
        "commit_message": "Add Moehlenhoff Alpha2 underfloor heating system integration (#42771)\n\n* Add Moehlenhoff Alpha2 underfloor heating system integration\r\n\r\n* isort changes\r\n\r\n* flake8 changes\r\n\r\n* Do not exclude config_flow.py\r\n\r\n* pylint changes\r\n\r\n* Add config_flow test\r\n\r\n* correct requirements_test_all.txt\r\n\r\n* more tests\r\n\r\n* Update test description\r\n\r\n* Test connection and catch TimeoutError in async_setup_entry\r\n\r\n* Add version to manifest file\r\n\r\n* Remove version from manifest file\r\n\r\n* Replace tests.async_mock.patch by unittest.mock.patch\r\n\r\n* Update moehlenhoff-alpha2 to version 1.0.1\r\n\r\n* Update requirements for moehlenhoff-alpha2 1.0.1\r\n\r\n* Update moehlenhoff-alpha2 to 1.0.2\r\n\r\n* Use async_setup_platforms\r\n\r\n* Use async_unload_platforms\r\n\r\n* Separate connection and devices for each entry_id\r\n\r\n* Use async_track_time_interval to schedule updates\r\n\r\n* Check if input is valid before checking uniqueness\r\n\r\n* Move Exception handling to validate_input\r\n\r\n* Catch aiohttp.client_exceptions.ClientConnectorError\r\n\r\n* Remove translation files\r\n\r\n* Mock TimeoutError\r\n\r\n* Fix data update\r\n\r\n* Replace current callback implementation with ha dispatcher\r\n\r\n* Return False in should_poll\r\n\r\n* Remove unused argument\r\n\r\n* Remove CONNECTION_CLASS\r\n\r\n* Use _async_current_entries\r\n\r\n* Call async_schedule_update_ha_state after data update\r\n\r\n* Remove unneeded async_setup\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* Remove unneeded async_setup_platform\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* Set Schema attribute host required\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* Remove unused Exception class\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* Update manifest.json\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* pylint constructor return type None\r\n\r\n* Replace properties by class variables\r\n\r\n* use pass instead of return\r\n\r\n* Remove unused sync update method\r\n\r\n* remove property hvac_action\r\n\r\n* remove pass\r\n\r\n* rework exception handling\r\n\r\n* Update homeassistant/components/moehlenhoff_alpha2/config_flow.py\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>\r\n\r\n* Correct indentation\r\n\r\n* catch Exception in validate_input\r\n\r\n* Replace HomeAssistantType with HomeAssistant\r\n\r\n* Update to moehlenhoff-alpha2 1.0.3\r\n\r\n* Allow to switch between heating and cooling mode\r\n\r\n* Update moehlenhoff-alpha2 to version 1.0.4\r\n\r\n* Update heatarea data after setting target temperature\r\n\r\n* Support hvac_action\r\n\r\n* Fix heatarea update with multiple bases\r\n\r\n* Update data after setting preset mode\r\n\r\n* Use custom preset modes like defined by device\r\n\r\n* Fix config flow test\r\n\r\n* Fix test_duplicate_error\r\n\r\n* Rename property to extra_state_attributes\r\n\r\nRename property device_state_attributes to extra_state_attributes and\r\nreturn lowercase keys in dict.\r\n\r\n* Refactor using DataUpdateCoordinator\r\n\r\n* Remove _attr_should_poll\r\n\r\n* Raise HomeAssistantError on communication error\r\n\r\nCatch HTTPError instead of broad except and reraise as HomeAssistantError\r\n\r\n* Change DataUpdateCoordinator name to alpha2_base\r\n\r\n* Refresh coordinator before setting data\r\n\r\n* Raise ValueError on invalid heat area mode\r\n\r\n* Rename heatarea to heat_area\r\n\r\n* Set type annotation in class attribute\r\n\r\n* Move coordinator to top\r\n\r\n* Move exception handling to the coordinator\r\n\r\n* Use heat_area_id directly\r\n\r\n* Sore get_cooling() result into local var\r\n\r\n* Add explanation of status attributes\r\n\r\nand remove BLOCK_HC\r\n\r\n* Fix pylint warnings\r\n\r\n* from __future__ import annotations\r\n\r\n* Use Platform Enum\r\n\r\n* Move data handling to coordinator\r\n\r\n* Remove property extra_state_attributes\r\n\r\n* Add missing annotations\r\n\r\n* Update moehlenhoff-alpha2 to version 1.1.2\r\n\r\n* Rework tests based on the scaffold template\r\n\r\n* Set also heat/cool/day/night temp with target temp\r\n\r\n* Remove unneeded code from tests\r\n\r\nCo-authored-by: Milan Meulemans <milan.meulemans@live.be>",
        "code": "async def validate_input(data):\n    \n\n    base = Alpha2Base(data[\"host\"])\n    try:\n        await base.update_data()\n    except (aiohttp.client_exceptions.ClientConnectorError, asyncio.TimeoutError):\n        return {\"error\": \"cannot_connect\"}\n    except Exception:  # pylint: disable=broad-except\n        _LOGGER.exception(\"Unexpected exception\")\n        return {\"error\": \"unknown\"}\n\n    # Return info that you want to store in the config entry.\n    return {\"title\": base.name}\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 90,
        "n_words": 40,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 65,
        "n_ast_nodes": 123,
        "n_identifiers": 14,
        "d_id": 111624,
        "documentation": {
            "docstring": "Validate the user input allows us to connect.\n\n    Data has the keys from DATA_SCHEMA with values provided by the user.\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 101682,
        "commit_id": "e5356a417e7c2124e75c4a2994ed604fc0a3cc74",
        "repo": "faceswap",
        "path": "lib/align/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "_update",
        "commit_message": "Alignments update:\n  - Store face embeddings in PNG header when sorting\n  - typing + refactor\n  - Update alignments keys for 'identity' and 'video_meta' + bump to v2.3\n  - General typing fixes",
        "code": "def _update(self) -> int:\n        \n        retval = self.update()\n        logger.debug(\"Updated %s: %s\", self.__class__.__name__, retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 31,
        "n_ast_nodes": 53,
        "n_identifiers": 9,
        "d_id": 21086,
        "documentation": {
            "docstring": " Calls the child's :func:`update` method, logs output and sets the\n        :attr:`is_updated` flag\n\n        Returns\n        -------\n        int\n            The number of items that were updated\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 176142,
        "commit_id": "0dada08f4eedb104bfa40932b576e44d82218547",
        "repo": "edgedb",
        "path": "tests/test_edgeql_scope.py",
        "file_name": "test_edgeql_scope.py",
        "fun_name": "test_edgeql_scope_for_with_computable_01",
        "commit_message": "Always include the definition context namespace in computable contexts (#3331)\n\nWe need to include the *original* source namespace in our ctx\r\nnamespace when compiling computables. The current mechanism of trying\r\nto look up in view_sets or failing that using the source namespace\r\nfrom the computable use, but this was failing to find it in some cases\r\nwith FOR.\r\n\r\nFix this by instead directly pulling in the namespace from qlctx. The\r\ninclusion of qlctx's namespace nicely allows us to ditch so later\r\nlogic as well.\r\n\r\nAdditionally we need to merge the namespace into *both* sides in\r\nget_view_map_remapping, to handle cases like referencing a `FOR`\r\nvariable where the current ns doesn't get merged in.\r\n\r\nFixes #3323.",
        "code": "async def test_edgeql_scope_for_with_computable_01(self):\n        await self.assert_query_result(\n            r,\n            tb.bag([\n                {\"name\": \"Alice\", \"namelen\": 5},\n                {\"name\": \"Bob\", \"namelen\": 3},\n                {\"name\": \"Carol\", \"namelen\": 5},\n                {\"name\": \"Dave\", \"namelen\": 4}\n            ])\n        )\n",
        "url": "https://github.com/edgedb/edgedb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 131,
        "n_words": 25,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 60,
        "n_ast_nodes": 111,
        "n_identifiers": 5,
        "d_id": 41718,
        "documentation": {
            "docstring": "\n            with props := (\n              for h in User union (\n                select h {namelen := len(h.name)}\n              )\n            )\n            select props {\n              name,\n              namelen\n            };\n            ",
            "n_words": 23,
            "vocab_size": 17,
            "n_whitespaces": 146,
            "language": "en"
        }
    },
    {
        "id": 261613,
        "commit_id": "e2e7d75d1e81ce3b67257fcc4cce32ab2d2acd2f",
        "repo": "scikit-learn",
        "path": "sklearn/manifold/_isomap.py",
        "file_name": "_isomap.py",
        "fun_name": "transform",
        "commit_message": "MAINT Extend dtype preserved common test to check transform (#24982)",
        "code": "def transform(self, X):\n        \n        check_is_fitted(self)\n        if self.n_neighbors is not None:\n            distances, indices = self.nbrs_.kneighbors(X, return_distance=True)\n        else:\n            distances, indices = self.nbrs_.radius_neighbors(X, return_distance=True)\n\n        # Create the graph of shortest distances from X to\n        # training data via the nearest neighbors of X.\n        # This can be done as a single array operation, but it potentially\n        # takes a lot of memory.  To avoid that, use a loop:\n\n        n_samples_fit = self.nbrs_.n_samples_fit_\n        n_queries = distances.shape[0]\n\n        if hasattr(X, \"dtype\") and X.dtype == np.float32:\n            dtype = np.float32\n        else:\n            dtype = np.float64\n\n        G_X = np.zeros((n_queries, n_samples_fit), dtype)\n        for i in range(n_queries):\n            G_X[i] = np.min(self.dist_matrix_[indices[i]] + distances[i][:, None], 0)\n\n        G_X **= 2\n        G_X *= -0.5\n\n        return self.kernel_pca_.transform(G_X)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 283,
        "n_words": 108,
        "vocab_size": 85,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 170,
        "n_ast_nodes": 261,
        "n_identifiers": 27,
        "d_id": 76893,
        "documentation": {
            "docstring": "Transform X.\n\n        This is implemented by linking the points X into the graph of geodesic\n        distances of the training data. First the `n_neighbors` nearest\n        neighbors of X are found in the training data, and from these the\n        shortest geodesic distances from each point in X to each point in\n        the training data are computed in order to construct the kernel.\n        The embedding of X is the projection of this kernel onto the\n        embedding vectors of the training set.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix}, shape (n_queries, n_features)\n            If neighbors_algorithm='precomputed', X is assumed to be a\n            distance matrix or a sparse graph of shape\n            (n_queries, n_samples_fit).\n\n        Returns\n        -------\n        X_new : array-like, shape (n_queries, n_components)\n            X transformed in the new space.\n        ",
            "n_words": 120,
            "vocab_size": 71,
            "n_whitespaces": 262,
            "language": "en"
        }
    },
    {
        "id": 114694,
        "commit_id": "ef0262e95a1e1a5403896088ca3938adb895a8d6",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/mysql_handler/mysql_handler.py",
        "file_name": "mysql_handler.py",
        "fun_name": "check_status",
        "commit_message": "Add mysql handler",
        "code": "def check_status(self):\n        \n        status = {\n            'success': False\n        }\n        try:\n            con = self.__connect()\n            with closing(con) as con:\n                status['success'] = con.is_connected()\n        except Exception as e:\n            log.error(f'Error connecting to MySQL {self.database}, {e}!')\n            status['error'] = e\n        return status\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 146,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 60,
        "n_ast_nodes": 122,
        "n_identifiers": 12,
        "d_id": 25250,
        "documentation": {
            "docstring": "\n        Check the connection of the MySQL database\n        :return: success status and error message if error occurs\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 66747,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v13_0/delete_report_requested_items_to_order.py",
        "file_name": "delete_report_requested_items_to_order.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\t\n\tauto_email_reports = frappe.db.get_values(\n\t\t\"Auto Email Report\", {\"report\": \"Requested Items to Order\"}, [\"name\"]\n\t)\n\tfor auto_email_report in auto_email_reports:\n\t\tfrappe.delete_doc(\"Auto Email Report\", auto_email_report[0])\n\n\tfrappe.db.sql(\n\t\t\n\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 17,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 49,
        "n_ast_nodes": 89,
        "n_identifiers": 8,
        "d_id": 14316,
        "documentation": {
            "docstring": "Check for one or multiple Auto Email Reports and delete\n\t\tDELETE FROM `tabReport`\n\t\tWHERE name = 'Requested Items to Order'\n\t",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 173321,
        "commit_id": "fbac3e38ac116855b930ee60fb3c997337ae17b7",
        "repo": "calibre-web",
        "path": "cps/helper.py",
        "file_name": "helper.py",
        "fun_name": "check_send_to_ereader",
        "commit_message": "Eenabled send epubs to E-Reader devices",
        "code": "def check_send_to_ereader(entry):\n    \n    formats = list()\n    book_formats = list()\n    if len(entry.data):\n        for ele in iter(entry.data):\n            if ele.uncompressed_size < config.mail_size:\n                formats.append(ele.format)\n        if 'EPUB' in formats:\n            book_formats.append({'format': 'Epub',\n                                 'convert': 0,\n                                 'text': _('Send %(format)s to E-Reader', format='Epub')})\n        if 'MOBI' in formats:\n            book_formats.append({'format': 'Mobi',\n                                 'convert': 0,\n                                 'text': _('Send %(format)s to E-Reader', format='Mobi')})\n        if 'PDF' in formats:\n            book_formats.append({'format': 'Pdf',\n                                 'convert': 0,\n                                 'text': _('Send %(format)s to E-Reader', format='Pdf')})\n        if 'AZW' in formats:\n            book_formats.append({'format': 'Azw',\n                                 'convert': 0,\n                                 'text': _('Send %(format)s to E-Reader', format='Azw')})\n        if config.config_converterpath:\n            book_formats.extend(check_send_to_ereader_with_converter(formats))\n        return book_formats\n    else:\n        log.error(u'Cannot find book entry %d', entry.id)\n        return None\n\n\n# Check if a reader is existing for any of the book formats, if not, return empty list, otherwise return\n# list with supported formats",
        "url": "https://github.com/janeczku/calibre-web.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 527,
        "n_words": 114,
        "vocab_size": 65,
        "complexity": 9,
        "nloc": 29,
        "token_counts": 202,
        "n_ast_nodes": 370,
        "n_identifiers": 21,
        "d_id": 40835,
        "documentation": {
            "docstring": "\n        returns all available book formats for sending to E-Reader\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 289390,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/components/history_stats/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_async_on_entire_period",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "async def test_async_on_entire_period(recorder_mock, hass):\n    \n    start_time = dt_util.utcnow() - timedelta(minutes=60)\n    t0 = start_time + timedelta(minutes=20)\n    t1 = t0 + timedelta(minutes=10)\n    t2 = t1 + timedelta(minutes=10)\n\n    # Start     t0        t1        t2        End\n    # |--20min--|--20min--|--10min--|--10min--|\n    # |---on----|--off----|---on----|--off----|\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 83,
        "n_words": 34,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 62,
        "token_counts": 284,
        "n_ast_nodes": 90,
        "n_identifiers": 11,
        "d_id": 88532,
        "documentation": {
            "docstring": "Test the history statistics sensor measuring as on the entire period.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 224461,
        "commit_id": "f79b34d174e41084391868e7b503f5c61b8b1bdf",
        "repo": "mkdocs",
        "path": "mkdocs/plugins.py",
        "file_name": "plugins.py",
        "fun_name": "on_post_template",
        "commit_message": "Move plugin events docs into source code + refactor\n\n* Create real (no-op) methods for each event in the base class.\n* Refactor event dispatcher to not check for methods' existence, instead just call them.\n* Move documentation from Markdown into docstrings of these methods.\n* Activate the 'mkdocstrings' plugin.\n* Use 'mkdocstrings' to insert documentation from those docstrings into the site.",
        "code": "def on_post_template(self, output_content, template_name, config):\n        \n        return output_content\n\n    # Page events\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 27,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 14,
        "n_ast_nodes": 23,
        "n_identifiers": 5,
        "d_id": 57306,
        "documentation": {
            "docstring": "\n        The `post_template` event is called after the template is rendered, but before\n        it is written to disc and can be used to alter the output of the template.\n        If an empty string is returned, the template is skipped and nothing is is\n        written to disc.\n\n        Parameters:\n            output_content: output of rendered template as string\n            template_name: string filename of template\n            config: global configuration object\n\n        Returns:\n            output of rendered template as string\n        ",
            "n_words": 69,
            "vocab_size": 42,
            "n_whitespaces": 163,
            "language": "en"
        }
    },
    {
        "id": 101218,
        "commit_id": "5e73437be47f2410439a3c6716de96354e6a0c94",
        "repo": "faceswap",
        "path": "lib/align/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "frame_has_faces",
        "commit_message": "lib.align updates:\n  - alignments.py\n    - Add typed dicts for imported alignments\n    - Explicitly check for presence of thumb value in alignments dict\n    - linting\n  - detected_face.py\n    - Typing\n    - Linting\n    - Legacy support for pre-aligned face\n    - Update dependencies to new property names",
        "code": "def frame_has_faces(self, frame_name):\n        \n        retval = bool(self._data.get(frame_name, {}).get(\"faces\", []))\n        logger.trace(\"'%s': %s\", frame_name, retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 44,
        "n_ast_nodes": 73,
        "n_identifiers": 9,
        "d_id": 20638,
        "documentation": {
            "docstring": " Check whether a given frame_name exists within the alignments :attr:`data` and contains\n        at least 1 face.\n\n        Parameters\n        ----------\n        frame_name: str\n            The frame name to check. This should be the base name of the frame, not the full path\n\n        Returns\n        -------\n        bool\n            ``True`` if the given frame_name exists within the alignments :attr:`data` and has at\n            least 1 face associated with it, otherwise ``False``\n        ",
            "n_words": 62,
            "vocab_size": 46,
            "n_whitespaces": 152,
            "language": "en"
        }
    },
    {
        "id": 269108,
        "commit_id": "9dc9a78cc6502226775a99725c654fab3298aa5f",
        "repo": "keras",
        "path": "keras/utils/image_utils.py",
        "file_name": "image_utils.py",
        "fun_name": "smart_resize",
        "commit_message": "Expose all utilities in `keras.utils.__init__.py`, and resolve the hourglass import issues that led to the creation of an extraneous `all_utils.py` file / library.\n\nPiperOrigin-RevId: 435725558",
        "code": "def smart_resize(x, size, interpolation='bilinear'):\n  \n  if len(size) != 2:\n    raise ValueError('Expected `size` to be a tuple of 2 integers, '\n                     f'but got: {size}.')\n  img = tf.convert_to_tensor(x)\n  if img.shape.rank is not None:\n    if img.shape.rank < 3 or img.shape.rank > 4:\n      raise ValueError(\n          'Expected an image array with shape `(height, width, channels)`, '\n          'or `(batch_size, height, width, channels)`, but '\n          f'got input with incorrect rank, of shape {img.shape}.')\n  shape = tf.shape(img)\n  height, width = shape[-3], shape[-2]\n  target_height, target_width = size\n  if img.shape.rank is not None:\n    static_num_channels = img.shape[-1]\n  else:\n    static_num_channels = None\n\n  crop_height = tf.cast(\n      tf.cast(width * target_height, 'float32') / target_width, 'int32')\n  crop_width = tf.cast(\n      tf.cast(height * target_width, 'float32') / target_height, 'int32')\n\n  # Set back to input height / width if crop_height / crop_width is not smaller.\n  crop_height = tf.minimum(height, crop_height)\n  crop_width = tf.minimum(width, crop_width)\n\n  crop_box_hstart = tf.cast(\n      tf.cast(height - crop_height, 'float32') / 2, 'int32')\n  crop_box_wstart = tf.cast(tf.cast(width - crop_width, 'float32') / 2, 'int32')\n\n  if img.shape.rank == 4:\n    crop_box_start = tf.stack([0, crop_box_hstart, crop_box_wstart, 0])\n    crop_box_size = tf.stack([-1, crop_height, crop_width, -1])\n  else:\n    crop_box_start = tf.stack([crop_box_hstart, crop_box_wstart, 0])\n    crop_box_size = tf.stack([crop_height, crop_width, -1])\n\n  img = tf.slice(img, crop_box_start, crop_box_size)\n  img = tf.image.resize(images=img, size=size, method=interpolation)\n  # Apparent bug in resize_images_v2 may cause shape to be lost\n  if img.shape.rank is not None:\n    if img.shape.rank == 4:\n      img.set_shape((None, None, None, static_num_channels))\n    if img.shape.rank == 3:\n      img.set_shape((None, None, static_num_channels))\n  if isinstance(x, np.ndarray):\n    return img.numpy()\n  return img\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 360,
        "n_words": 226,
        "vocab_size": 122,
        "complexity": 11,
        "nloc": 43,
        "token_counts": 404,
        "n_ast_nodes": 646,
        "n_identifiers": 35,
        "d_id": 79905,
        "documentation": {
            "docstring": "Resize images to a target size without aspect ratio distortion.\n\n  Warning: `tf.keras.preprocessing.image.smart_resize` is not recommended for\n  new code. Prefer `tf.keras.layers.Resizing`, which provides the same\n  functionality as a preprocessing layer and adds `tf.RaggedTensor` support. See\n  the [preprocessing layer guide](\n  https://www.tensorflow.org/guide/keras/preprocessing_layers)\n  for an overview of preprocessing layers.\n\n  TensorFlow image datasets typically yield images that have each a different\n  size. However, these images need to be batched before they can be\n  processed by Keras layers. To be batched, images need to share the same height\n  and width.\n\n  You could simply do:\n\n  ```python\n  size = (200, 200)\n  ds = ds.map(lambda img: tf.image.resize(img, size))\n  ```\n\n  However, if you do this, you distort the aspect ratio of your images, since\n  in general they do not all have the same aspect ratio as `size`. This is\n  fine in many cases, but not always (e.g. for GANs this can be a problem).\n\n  Note that passing the argument `preserve_aspect_ratio=True` to `resize`\n  will preserve the aspect ratio, but at the cost of no longer respecting the\n  provided target size. Because `tf.image.resize` doesn't crop images,\n  your output images will still have different sizes.\n\n  This calls for:\n\n  ```python\n  size = (200, 200)\n  ds = ds.map(lambda img: smart_resize(img, size))\n  ```\n\n  Your output images will actually be `(200, 200)`, and will not be distorted.\n  Instead, the parts of the image that do not fit within the target size\n  get cropped out.\n\n  The resizing process is:\n\n  1. Take the largest centered crop of the image that has the same aspect ratio\n  as the target size. For instance, if `size=(200, 200)` and the input image has\n  size `(340, 500)`, we take a crop of `(340, 340)` centered along the width.\n  2. Resize the cropped image to the target size. In the example above,\n  we resize the `(340, 340)` crop to `(200, 200)`.\n\n  Args:\n    x: Input image or batch of images (as a tensor or NumPy array). Must be in\n      format `(height, width, channels)` or `(batch_size, height, width,\n      channels)`.\n    size: Tuple of `(height, width)` integer. Target size.\n    interpolation: String, interpolation to use for resizing. Defaults to\n      `'bilinear'`. Supports `bilinear`, `nearest`, `bicubic`, `area`,\n      `lanczos3`, `lanczos5`, `gaussian`, `mitchellcubic`.\n\n  Returns:\n    Array with shape `(size[0], size[1], channels)`. If the input image was a\n    NumPy array, the output is a NumPy array, and if it was a TF tensor,\n    the output is a TF tensor.\n  ",
            "n_words": 383,
            "vocab_size": 215,
            "n_whitespaces": 460,
            "language": "en"
        }
    },
    {
        "id": 69882,
        "commit_id": "be927fda3dc4118b77ad0f88d5e6deb652a5f5b3",
        "repo": "glances",
        "path": "glances/plugins/glances_ports.py",
        "file_name": "glances_ports.py",
        "fun_name": "_port_scan_icmp",
        "commit_message": "Prepare memory leak test. Not active for the moment",
        "code": "def _port_scan_icmp(self, port):\n        \n        ret = None\n\n        # Create the ping command\n        # Use the system ping command because it already have the sticky bit set\n        # Python can not create ICMP packet with non root right\n        if WINDOWS:\n            timeout_opt = '-w'\n            count_opt = '-n'\n        elif MACOS or BSD:\n            timeout_opt = '-t'\n            count_opt = '-c'\n        else:\n            # Linux and co...\n            timeout_opt = '-W'\n            count_opt = '-c'\n        # Build the command line\n        # Note: Only string are allowed\n        cmd = [\n            'ping',\n            count_opt,\n            '1',\n            timeout_opt,\n            str(self._resolv_name(port['timeout'])),\n            self._resolv_name(port['host']),\n        ]\n        fnull = open(os.devnull, 'w')\n\n        try:\n            counter = Counter()\n            ret = subprocess.check_call(cmd, stdout=fnull, stderr=fnull, close_fds=True)\n            if ret == 0:\n                port['status'] = counter.get()\n            else:\n                port['status'] = False\n        except subprocess.CalledProcessError:\n            # Correct issue #1084: No Offline status for timed-out ports\n            port['status'] = False\n        except Exception as e:\n            logger.debug(\"{}: Error while pinging host {} ({})\".format(self.plugin_name, port['host'], e))\n\n        fnull.close()\n\n        return ret\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 518,
        "n_words": 142,
        "vocab_size": 103,
        "complexity": 7,
        "nloc": 33,
        "token_counts": 177,
        "n_ast_nodes": 314,
        "n_identifiers": 32,
        "d_id": 15135,
        "documentation": {
            "docstring": "Scan the (ICMP) port structure (dict) and update the status key.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 182936,
        "commit_id": "36d7973c7c6792fd1100d5512140a4701b53ba3d",
        "repo": "textual",
        "path": "src/textual/devtools/service.py",
        "file_name": "service.py",
        "fun_name": "shutdown",
        "commit_message": "Code review actions",
        "code": "async def shutdown(self) -> None:\n        \n\n        # Stop polling/writing Console dimensions to clients\n        self.shutdown_event.set()\n        await self.size_poll_task\n\n        # We're shutting down the server, so inform all connected clients\n        for client in self.clients:\n            await client.close()\n        self.clients.clear()\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 93,
        "n_words": 33,
        "vocab_size": 30,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 39,
        "n_ast_nodes": 71,
        "n_identifiers": 9,
        "d_id": 44013,
        "documentation": {
            "docstring": "Stop server async tasks and clean up all client handlers",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 166669,
        "commit_id": "7e23a37e1c5bda81234801a6584563e2880769eb",
        "repo": "pandas",
        "path": "pandas/core/indexes/interval.py",
        "file_name": "interval.py",
        "fun_name": "_intersection",
        "commit_message": "ENH: consistency of input args for boundaries - Interval (#46522)",
        "code": "def _intersection(self, other, sort):\n        \n        # For IntervalIndex we also know other.inclusive == self.inclusive\n        if self.left.is_unique and self.right.is_unique:\n            taken = self._intersection_unique(other)\n        elif other.left.is_unique and other.right.is_unique and self.isna().sum() <= 1:\n            # Swap other/self if other is unique and self does not have\n            # multiple NaNs\n            taken = other._intersection_unique(self)\n        else:\n            # duplicates\n            taken = self._intersection_non_unique(other)\n\n        if sort is None:\n            taken = taken.sort_values()\n\n        return taken\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 187,
        "n_words": 61,
        "vocab_size": 45,
        "complexity": 7,
        "nloc": 10,
        "token_counts": 88,
        "n_ast_nodes": 147,
        "n_identifiers": 13,
        "d_id": 39853,
        "documentation": {
            "docstring": "\n        intersection specialized to the case with matching dtypes.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 276218,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/saving/saved_model_experimental.py",
        "file_name": "saved_model_experimental.py",
        "fun_name": "load_from_saved_model",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def load_from_saved_model(saved_model_path, custom_objects=None):\n    \n    warnings.warn(\n        \"`tf.keras.experimental.load_from_saved_model` is deprecated\"\n        \"and will be removed in a future version. \"\n        \"Please switch to `tf.keras.models.load_model`.\",\n        stacklevel=2,\n    )\n    # restore model topology from json string\n    model_json_filepath = tf.io.gfile.join(\n        tf.compat.as_bytes(saved_model_path),\n        tf.compat.as_bytes(tf.saved_model.ASSETS_DIRECTORY),\n        tf.compat.as_bytes(SAVED_MODEL_FILENAME_JSON),\n    )\n    with tf.io.gfile.GFile(model_json_filepath, \"r\") as f:\n        model_json = f.read()\n    model = model_config.model_from_json(\n        model_json, custom_objects=custom_objects\n    )\n\n    # restore model weights\n    checkpoint_prefix = tf.io.gfile.join(\n        tf.compat.as_text(saved_model_path),\n        tf.compat.as_text(tf.saved_model.VARIABLES_DIRECTORY),\n        tf.compat.as_text(tf.saved_model.VARIABLES_FILENAME),\n    )\n    model.load_weights(checkpoint_prefix)\n    return model\n\n\n#### Directory / path helpers\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 194,
        "n_words": 69,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 154,
        "n_ast_nodes": 250,
        "n_identifiers": 28,
        "d_id": 81599,
        "documentation": {
            "docstring": "Loads a keras Model from a SavedModel created by `export_saved_model()`.\n\n    This function reinstantiates model state by:\n    1) loading model topology from json (this will eventually come\n       from metagraph).\n    2) loading model weights from checkpoint.\n\n    Example:\n\n    ```python\n    import tensorflow as tf\n\n    # Create a tf.keras model.\n    model = tf.keras.Sequential()\n    model.add(tf.keras.layers.Dense(1, input_shape=[10]))\n    model.summary()\n\n    # Save the tf.keras model in the SavedModel format.\n    path = '/tmp/simple_keras_model'\n    tf.keras.experimental.export_saved_model(model, path)\n\n    # Load the saved keras model back.\n    new_model = tf.keras.experimental.load_from_saved_model(path)\n    new_model.summary()\n    ```\n\n    Args:\n      saved_model_path: a string specifying the path to an existing SavedModel.\n      custom_objects: Optional dictionary mapping names\n          (strings) to custom classes or functions to be\n          considered during deserialization.\n\n    Returns:\n      a keras.Model instance.\n    ",
            "n_words": 108,
            "vocab_size": 82,
            "n_whitespaces": 207,
            "language": "en"
        }
    },
    {
        "id": 109556,
        "commit_id": "e87416b33b01f6fc4e3b2290d6e8a60e6ddb6e55",
        "repo": "matplotlib",
        "path": "doc/conf.py",
        "file_name": "conf.py",
        "fun_name": "add_html_cache_busting",
        "commit_message": "DOC: Add cache busting to all static assets\n\nWe have seen both in `/stable` and `/3.6.0`, some styling is broken\nbecause old CSS is cached. CSS might change from updating\nsphinx-gallery, mpl-sphinx-theme, pydata-sphinx-theme, etc. Adding a\nversioned query breaks the cache. It's a bit over-eager to base it on\nMatplotlib version and not the file contents (since those dependencies\nmay not have updated), but this should work well enough.",
        "code": "def add_html_cache_busting(app, pagename, templatename, context, doctree):\n    \n    from sphinx.builders.html import Stylesheet, JavaScript\n\n    css_tag = context['css_tag']\n    js_tag = context['js_tag']\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 29,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 52,
        "n_ast_nodes": 57,
        "n_identifiers": 13,
        "d_id": 23644,
        "documentation": {
            "docstring": "\n    Add cache busting query on CSS and JavaScript assets.\n\n    This adds the Matplotlib version as a query to the link reference in the\n    HTML, if the path is not absolute (i.e., it comes from the `_static`\n    directory) and doesn't already have a query.\n    ",
            "n_words": 43,
            "vocab_size": 36,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 298684,
        "commit_id": "04b9c9300645fb30541e2bf0881d35cc698a47c5",
        "repo": "core",
        "path": "homeassistant/components/econet/climate.py",
        "file_name": "climate.py",
        "fun_name": "target_temperature_high",
        "commit_message": "Use climate enums in econet (#70633)",
        "code": "def target_temperature_high(self):\n        \n        if self.hvac_mode == HVACMode.HEAT_COOL:\n            return self._econet.cool_set_point\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 23,
        "n_ast_nodes": 39,
        "n_identifiers": 7,
        "d_id": 97626,
        "documentation": {
            "docstring": "Return the higher bound temperature we try to reach.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 119183,
        "commit_id": "d9dcd1394aedf760272f14c3560cd5415495c28a",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "_promote_shapes",
        "commit_message": "djax: let make_jaxpr build dyn shape jaxprs",
        "code": "def _promote_shapes(fun_name, *args):\n  \n  if len(args) < 2:\n    return args\n  else:\n    shapes = [shape(arg) for arg in args]\n    if _all(len(shapes[0]) == len(s) for s in shapes[1:]):\n      return args  # no need for rank promotion, so rely on lax promotion\n    nonscalar_ranks = {len(shp) for shp in shapes if shp}\n    if len(nonscalar_ranks) < 2:\n      return args\n    else:\n      if config.jax_numpy_rank_promotion != \"allow\":\n        _rank_promotion_warning_or_error(fun_name, shapes)\n      result_shape = lax.broadcast_shapes(*shapes)\n      return [broadcast_to(arg, result_shape) for arg, shp in zip(args, shapes)]\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 126,
        "n_words": 72,
        "vocab_size": 49,
        "complexity": 10,
        "nloc": 15,
        "token_counts": 128,
        "n_ast_nodes": 203,
        "n_identifiers": 19,
        "d_id": 26552,
        "documentation": {
            "docstring": "Apply NumPy-style broadcasting, making args shape-compatible for lax.py.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 176008,
        "commit_id": "b97d27d2e916025f65fed751d54c089d4d4bd022",
        "repo": "autokeras",
        "path": "autokeras/keras_layers.py",
        "file_name": "keras_layers.py",
        "fun_name": "_build_attention",
        "commit_message": "clean up imports",
        "code": "def _build_attention(self, qkv_rank):\n        \n        if self._attention_axes is None:\n            self._attention_axes = tuple(range(1, qkv_rank - 2))\n        else:\n            self._attention_axes = tuple(self._attention_axes)  # pragma: no cover\n        (\n            self._dot_product_equation,\n            self._combine_equation,\n            attn_scores_rank,\n        ) = _build_attention_equation(qkv_rank, attn_axes=self._attention_axes)\n        norm_axes = tuple(\n            range(attn_scores_rank - len(self._attention_axes), attn_scores_rank)\n        )\n        self._masked_softmax = MaskedSoftmax(\n            mask_expansion_axes=[1], normalization_axes=norm_axes\n        )\n        self._dropout_layer = layers.Dropout(rate=self._dropout)\n",
        "url": "https://github.com/keras-team/autokeras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 194,
        "n_words": 46,
        "vocab_size": 36,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 113,
        "n_ast_nodes": 176,
        "n_identifiers": 22,
        "d_id": 41666,
        "documentation": {
            "docstring": "Builds multi-head dot-product attention computations.\n\n        This function builds attributes necessary for `_compute_attention` to\n        costomize attention computation to replace the default dot-product\n        attention.\n\n        Args:\n          qkv_rank: the rank of query, key, value tensors.\n        ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 248358,
        "commit_id": "4cc4229cd7a55d2556c798fecbb1c9660dc821c8",
        "repo": "synapse",
        "path": "tests/rest/client/test_retention.py",
        "file_name": "test_retention.py",
        "fun_name": "test_visibility_when_disabled",
        "commit_message": "Prevent expired events from being filtered out when retention is disabled (#12611)\n\nCo-authored-by: Richard van der Hoff <1389908+richvdh@users.noreply.github.com>\r\nCo-authored-by: Patrick Cloke <clokep@users.noreply.github.com>",
        "code": "def test_visibility_when_disabled(self) -> None:\n        \n        room_id = self.helper.create_room_as(self.user_id, tok=self.token)\n\n        self.helper.send_state(\n            room_id=room_id,\n            event_type=EventTypes.Retention,\n            body={\"max_lifetime\": one_day_ms},\n            tok=self.token,\n        )\n\n        resp = self.helper.send(room_id=room_id, body=\"test\", tok=self.token)\n\n        self.reactor.advance(one_day_ms * 2 / 1000)\n\n        self.get_event(room_id, resp[\"event_id\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 120,
        "n_words": 27,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 102,
        "n_ast_nodes": 160,
        "n_identifiers": 19,
        "d_id": 72235,
        "documentation": {
            "docstring": "Retention policies should be ignored when the retention feature is disabled.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 65709,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/crm/doctype/contract/contract.py",
        "file_name": "contract.py",
        "fun_name": "update_status_for_contracts",
        "commit_message": "style: format code with black",
        "code": "def update_status_for_contracts():\n\t\n\n\tcontracts = frappe.get_all(\n\t\t\"Contract\",\n\t\tfilters={\"is_signed\": True, \"docstatus\": 1},\n\t\tfields=[\"name\", \"start_date\", \"end_date\"],\n\t)\n\n\tfor contract in contracts:\n\t\tstatus = get_status(contract.get(\"start_date\"), contract.get(\"end_date\"))\n\n\t\tfrappe.db.set_value(\"Contract\", contract.get(\"name\"), \"status\", status)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 17,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 78,
        "n_ast_nodes": 138,
        "n_identifiers": 12,
        "d_id": 13992,
        "documentation": {
            "docstring": "\n\tRun the daily hook to update the statuses for all signed\n\tand submitted Contracts\n\t",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 308463,
        "commit_id": "d26275011ae4e8ba0a8dcdc2a7ef81b5911d3900",
        "repo": "core",
        "path": "tests/components/command_line/test_cover.py",
        "file_name": "test_cover.py",
        "fun_name": "test_unique_id",
        "commit_message": "Add unique_id configuration variable to command_line integration (#58596)",
        "code": "async def test_unique_id(hass):\n    \n    await setup_test_entity(\n        hass,\n        {\n            \"unique\": {\n                \"command_open\": \"echo open\",\n                \"command_close\": \"echo close\",\n                \"command_stop\": \"echo stop\",\n                \"unique_id\": \"unique\",\n            },\n            \"not_unique_1\": {\n                \"command_open\": \"echo open\",\n                \"command_close\": \"echo close\",\n                \"command_stop\": \"echo stop\",\n                \"unique_id\": \"not-so-unique-anymore\",\n            },\n            \"not_unique_2\": {\n                \"command_open\": \"echo open\",\n                \"command_close\": \"echo close\",\n                \"command_stop\": \"echo stop\",\n                \"unique_id\": \"not-so-unique-anymore\",\n            },\n        },\n    )\n\n    assert len(hass.states.async_all()) == 2\n\n    ent_reg = entity_registry.async_get(hass)\n\n    assert len(ent_reg.entities) == 2\n    assert ent_reg.async_get_entity_id(\"cover\", \"command_line\", \"unique\") is not None\n    assert (\n        ent_reg.async_get_entity_id(\"cover\", \"command_line\", \"not-so-unique-anymore\")\n        is not None\n    )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 386,
        "n_words": 78,
        "vocab_size": 38,
        "complexity": 1,
        "nloc": 32,
        "token_counts": 138,
        "n_ast_nodes": 264,
        "n_identifiers": 11,
        "d_id": 107219,
        "documentation": {
            "docstring": "Test unique_id option and if it only creates one cover per id.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 197534,
        "commit_id": "7fe8e027ae1d7f683243c0229b961671a6cbb4c5",
        "repo": "sympy",
        "path": "sympy/stats/joint_rv_types.py",
        "file_name": "joint_rv_types.py",
        "fun_name": "MultivariateT",
        "commit_message": "Improved some documentation in the stats module",
        "code": "def MultivariateT(syms, mu, sigma, v):\n    \n    return multivariate_rv(MultivariateTDistribution, syms, mu, sigma, v)\n\n\n#-------------------------------------------------------------------------------\n# Multivariate Normal Gamma distribution ---------------------------------------\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 22,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 37,
        "n_identifiers": 7,
        "d_id": 48612,
        "documentation": {
            "docstring": "\n    Creates a joint random variable with multivariate T-distribution.\n\n    Parameters\n    ==========\n\n    syms : A symbol/str\n        For identifying the random variable.\n    mu : A list/matrix\n        Representing the location vector\n    sigma : The shape matrix for the distribution\n\n    Examples\n    ========\n\n    >>> from sympy.stats import density, MultivariateT\n    >>> from sympy import Symbol\n\n    >>> x = Symbol(\"x\")\n    >>> X = MultivariateT(\"x\", [1, 1], [[1, 0], [0, 1]], 2)\n\n    >>> density(X)(1, 2)\n    2/(9*pi)\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    ",
            "n_words": 70,
            "vocab_size": 56,
            "n_whitespaces": 139,
            "language": "en"
        }
    },
    {
        "id": 128291,
        "commit_id": "db2f84bdfa49d218f97bf7f10678232bff8c48d5",
        "repo": "ray",
        "path": "dashboard/modules/job/job_head.py",
        "file_name": "job_head.py",
        "fun_name": "choose_agent",
        "commit_message": "[Job Submission][refactor 5/N] Remove the head node dependency on the `Raylet` process (#28599)\n\n* introduce stop_job\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* head rayletless\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* fix UT\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* fix UT\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* refactor choose_agent\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* fix\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* save\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* fix UT\r\n\r\n* delete mock\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\n\r\n* Use \"auto\" for entrypoint script\r\n\r\nSigned-off-by: Archit Kulkarni <architkulkarni@users.noreply.github.com>\r\n\r\nSigned-off-by: Catch-Bull <burglarralgrub@gmail.com>\r\nSigned-off-by: Archit Kulkarni <architkulkarni@users.noreply.github.com>\r\nCo-authored-by: Archit Kulkarni <architkulkarni@users.noreply.github.com>",
        "code": "async def choose_agent(self) -> Optional[JobAgentSubmissionClient]:\n        \n        # the number of agents which has an available HTTP port.\n        while True:\n            raw_agent_infos = await DataOrganizer.get_all_agent_infos()\n            agent_infos = {\n                key: value\n                for key, value in raw_agent_infos.items()\n                if value.get(\"httpPort\", -1) > 0\n            }\n            if len(agent_infos) > 0:\n                break\n            await asyncio.sleep(dashboard_consts.TRY_TO_GET_AGENT_INFO_INTERVAL_SECONDS)\n        # delete dead agents.\n        for dead_node in set(self._agents) - set(agent_infos):\n            client = self._agents.pop(dead_node)\n            await client.close()\n\n        if len(self._agents) >= dashboard_consts.CANDIDATE_AGENT_NUMBER:\n            node_id = sample(set(self._agents), 1)[0]\n            return self._agents[node_id]\n        else:\n            # Randomly select one from among all agents, it is possible that\n            # the selected one already exists in `self._agents`\n            node_id = sample(set(agent_infos), 1)[0]\n            agent_info = agent_infos[node_id]\n\n            if node_id not in self._agents:\n                node_ip = agent_info[\"ipAddress\"]\n                http_port = agent_info[\"httpPort\"]\n                agent_http_address = f\"http://{node_ip}:{http_port}\"\n                self._agents[node_id] = JobAgentSubmissionClient(agent_http_address)\n\n            return self._agents[node_id]\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 451,
        "n_words": 117,
        "vocab_size": 86,
        "complexity": 8,
        "nloc": 40,
        "token_counts": 199,
        "n_ast_nodes": 333,
        "n_identifiers": 30,
        "d_id": 28655,
        "documentation": {
            "docstring": "\n        Try to disperse as much as possible to select one of\n        the `CANDIDATE_AGENT_NUMBER` agents to solve requests.\n        the agents will not pop from `self._agents` unless\n        it's dead. Saved in `self._agents` is the agent that was\n        used before.\n        Strategy:\n            1. if the number of `self._agents` has reached\n               `CANDIDATE_AGENT_NUMBER`, randomly select one agent from\n               `self._agents`.\n            2. if not, randomly select one agent from all available agents,\n               it is possible that the selected one already exists in\n               `self._agents`.\n        ",
            "n_words": 75,
            "vocab_size": 48,
            "n_whitespaces": 203,
            "language": "en"
        }
    },
    {
        "id": 311447,
        "commit_id": "58b8c30221a6f6e5acbbe98b7e3298b03fb741f5",
        "repo": "core",
        "path": "tests/components/homekit_controller/test_alarm_control_panel.py",
        "file_name": "test_alarm_control_panel.py",
        "fun_name": "test_switch_read_alarm_state",
        "commit_message": "Improve homekit_controller tests (#65266)",
        "code": "async def test_switch_read_alarm_state(hass, utcnow):\n    \n    helper = await setup_test_component(hass, create_security_system_service)\n\n    await helper.async_update(\n        ServicesTypes.SECURITY_SYSTEM,\n        {CharacteristicsTypes.SECURITY_SYSTEM_STATE_CURRENT: 0},\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"armed_home\"\n    assert state.attributes[\"battery_level\"] == 50\n\n    await helper.async_update(\n        ServicesTypes.SECURITY_SYSTEM,\n        {CharacteristicsTypes.SECURITY_SYSTEM_STATE_CURRENT: 1},\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"armed_away\"\n\n    await helper.async_update(\n        ServicesTypes.SECURITY_SYSTEM,\n        {CharacteristicsTypes.SECURITY_SYSTEM_STATE_CURRENT: 2},\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"armed_night\"\n\n    await helper.async_update(\n        ServicesTypes.SECURITY_SYSTEM,\n        {CharacteristicsTypes.SECURITY_SYSTEM_STATE_CURRENT: 3},\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"disarmed\"\n\n    await helper.async_update(\n        ServicesTypes.SECURITY_SYSTEM,\n        {CharacteristicsTypes.SECURITY_SYSTEM_STATE_CURRENT: 4},\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"triggered\"\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 222,
        "n_words": 83,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 33,
        "token_counts": 186,
        "n_ast_nodes": 305,
        "n_identifiers": 14,
        "d_id": 110112,
        "documentation": {
            "docstring": "Test that we can read the state of a HomeKit alarm accessory.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 320067,
        "commit_id": "5b66ef0a748fd5570361a2a1ed6147e0462568d2",
        "repo": "paperless-ngx",
        "path": "src/documents/tests/test_api.py",
        "file_name": "test_api.py",
        "fun_name": "test_task_name_consume_folder",
        "commit_message": "Updates how task_args and task_kwargs are parsed, adds testing to cover everything I can think of",
        "code": "def test_task_name_consume_folder(self):\n        \n        result1 = TaskResult.objects.create(\n            task_id=str(uuid.uuid4()),\n            task_name=\"documents.tasks.some_task\",\n            status=celery.states.SUCCESS,\n            task_args=\"\\\"('/consume/anothertest.pdf',)\\\"\",\n            task_kwargs=\"\\\"{'override_tag_ids': None}\\\"\",\n        )\n        _ = PaperlessTask.objects.create(attempted_task=result1)\n\n        response = self.client.get(self.ENDPOINT)\n\n        self.assertEqual(response.status_code, 200)\n        self.assertEqual(len(response.data), 1)\n\n        returned_data = response.data[0]\n\n        self.assertEqual(returned_data[\"name\"], \"anothertest.pdf\")\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 145,
        "n_words": 27,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 112,
        "n_ast_nodes": 186,
        "n_identifiers": 29,
        "d_id": 117052,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - Attempted celery task\n            - Task was created through the consume folder\n        WHEN:\n            - API call is made to get tasks\n        THEN:\n            - Returned data include the filename\n        ",
            "n_words": 29,
            "vocab_size": 25,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 114339,
        "commit_id": "30877cf7ead465750763822b3c88f970c870d9dd",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/mlflow_handler/mlflow/mlflow_integration.py",
        "file_name": "mlflow_integration.py",
        "fun_name": "_prepare_registry",
        "commit_message": "feat: add mlflow, mysql, base handlers",
        "code": "def _prepare_registry(self):\n          # noqa\n        cur = self.internal_registry.cursor()\n        if ('models',) not in list(cur.execute(\"SELECT name FROM sqlite_master WHERE type='table';\")):\n            cur.execute()  # TODO: dtype_dict?\n            self.internal_registry.commit()\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 67,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 45,
        "n_ast_nodes": 84,
        "n_identifiers": 8,
        "d_id": 25156,
        "documentation": {
            "docstring": " Checks that sqlite records of registered models exists, otherwise creates it. create table models (model_name text, format text, target text, url text)",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 101382,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "scripts/convert.py",
        "file_name": "convert.py",
        "fun_name": "_get_threads",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _get_threads(self) -> MultiThread:\n        \n        # TODO Check if multiple threads actually speeds anything up\n        save_queue = queue_manager.get_queue(\"convert_out\")\n        patch_queue = queue_manager.get_queue(\"patch\")\n        return MultiThread(self._converter.process, patch_queue, save_queue,\n                           thread_count=self._pool_processes, name=\"patch\")\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 87,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 47,
        "n_ast_nodes": 80,
        "n_identifiers": 12,
        "d_id": 20797,
        "documentation": {
            "docstring": " Get the threads for patching the converted faces onto the frames.\n\n        Returns\n        :class:`lib.multithreading.MultiThread`\n            The threads that perform the patching of swapped faces onto the output frames\n        ",
            "n_words": 26,
            "vocab_size": 18,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 221346,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/cmd.py",
        "file_name": "cmd.py",
        "fun_name": "parseline",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parseline(self, line):\n        \n        line = line.strip()\n        if not line:\n            return None, None, line\n        elif line[0] == '?':\n            line = 'help ' + line[1:]\n        elif line[0] == '!':\n            if hasattr(self, 'do_shell'):\n                line = 'shell ' + line[1:]\n            else:\n                return None, None, line\n        i, n = 0, len(line)\n        while i < n and line[i] in self.identchars: i = i+1\n        cmd, arg = line[:i], line[i:].strip()\n        return cmd, arg, line\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 203,
        "n_words": 66,
        "vocab_size": 41,
        "complexity": 7,
        "nloc": 15,
        "token_counts": 129,
        "n_ast_nodes": 211,
        "n_identifiers": 11,
        "d_id": 56361,
        "documentation": {
            "docstring": "Parse the line into a command name and a string containing\n        the arguments.  Returns a tuple containing (command, args, line).\n        'command' and 'args' may be None if the line couldn't be parsed.\n        ",
            "n_words": 32,
            "vocab_size": 24,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 107070,
        "commit_id": "334cc617b8ed3b6b4ec6cb64ff16a040ef454149",
        "repo": "matplotlib",
        "path": "lib/matplotlib/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "_get_animated_artists",
        "commit_message": "Fix z_order",
        "code": "def _get_animated_artists(self):\n        \n        return tuple([a for ax_ in self.ax.get_figure().get_axes()\n                      for a in ax_.get_children()\n                      if a.get_animated() and a not in self.artists])\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 75,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 5,
        "nloc": 4,
        "token_counts": 48,
        "n_ast_nodes": 78,
        "n_identifiers": 11,
        "d_id": 22584,
        "documentation": {
            "docstring": "\n        Convenience method to get all animated artists of a figure, except\n        those already present in self.artists. 'z_order' is ignored.\n        ",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 247069,
        "commit_id": "1901cb1d4a8b7d9af64493fbd336e9aa2561c20c",
        "repo": "synapse",
        "path": "tests/rest/client/test_shadow_banned.py",
        "file_name": "test_shadow_banned.py",
        "fun_name": "test_message",
        "commit_message": "Add type hints to `tests/rest/client` (#12084)",
        "code": "def test_message(self) -> None:\n        \n\n        room_id = self.helper.create_room_as(\n            self.other_user_id, tok=self.other_access_token\n        )\n\n        # The user should be in the room.\n        self.helper.join(room_id, self.banned_user_id, tok=self.banned_access_token)\n\n        # Sending a message should complete successfully.\n        result = self.helper.send_event(\n            room_id=room_id,\n            type=EventTypes.Message,\n            content={\"msgtype\": \"m.text\", \"body\": \"with right label\"},\n            tok=self.banned_access_token,\n        )\n        self.assertIn(\"event_id\", result)\n        event_id = result[\"event_id\"]\n\n        latest_events = self.get_success(\n            self.store.get_latest_event_ids_in_room(room_id)\n        )\n        self.assertNotIn(event_id, latest_events)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 210,
        "n_words": 53,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 118,
        "n_ast_nodes": 192,
        "n_identifiers": 24,
        "d_id": 71479,
        "documentation": {
            "docstring": "Messages from shadow-banned users don't actually get sent.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 187530,
        "commit_id": "08209aecf41706dc1eb0171466d88d7fb02aefca",
        "repo": "streamlink",
        "path": "src/streamlink/plugins/mediaklikk.py",
        "file_name": "mediaklikk.py",
        "fun_name": "_get_streams",
        "commit_message": "plugins: refactor validation schemas\n\nRefactor validation schemas of plugins where schemas are not defined as\nclass attributes or where no major changes are needed:\n\n- Use `validate.none_or_all(...)`\n- Replace `validate.transform(pattern.search)` with `pattern` and fix\n  schemas using `validate.regex(pattern)` where a regex has to match\n  - Move pattern definitions from class attributes to schema definitions\n  - Fix some patterns in regards to quotation matching\n- Remove unneeded type validations, like `str` for example\n- Remove unneeded `TypeError` exceptions from try-except code blocks\n- Fix minor style issues where it makes sense\n  - use double quotes\n  - add trailing commas\n  - fix indentation",
        "code": "def _get_streams(self):\n        params = self.session.http.get(self.url, schema=validate.Schema(\n            re.compile(\n                r,\n                re.VERBOSE | re.DOTALL,\n            ),\n            validate.none_or_all(\n                validate.get(\"json\"),\n                validate.parse_json(),\n                {\n                    \"contentId\": validate.any(str, int),\n                    validate.optional(\"streamId\"): str,\n                    validate.optional(\"idec\"): str,\n                    validate.optional(\"token\"): str,\n                },\n            ),\n        ))\n        if not params:\n            log.error(\"Could not find player manager data\")\n            return\n\n        params.update({\n            \"video\": (unquote(params.pop(\"token\"))\n                      if params.get(\"token\") is not None else\n                      params.pop(\"streamId\")),\n            \"noflash\": \"yes\",\n            \"embedded\": \"0\",\n        })\n\n        url_parsed = urlparse(self.url)\n        skip_vods = url_parsed.netloc.endswith(\"m4sport.hu\") and url_parsed.path.startswith(\"/elo\")\n\n        self.session.http.headers.update({\"Referer\": self.url})\n        playlists = self.session.http.get(self.PLAYER_URL, params=params, schema=validate.Schema(\n            re.compile(r\"pl\\.setup\\s*\\(\\s*(?P<json>{.*?})\\s*\\)\\s*;\", re.DOTALL),\n            validate.none_or_all(\n                validate.get(\"json\"),\n                validate.parse_json(),\n                {\"playlist\": [{\n                    \"file\": validate.url(),\n                    \"type\": str,\n                }]},\n                validate.get(\"playlist\"),\n                validate.filter(lambda p: p[\"type\"] == \"hls\"),\n                validate.filter(lambda p: not skip_vods or \"vod\" not in p[\"file\"]),\n                validate.map(lambda p: update_scheme(\"https://\", p[\"file\"])),\n            ),\n        ))\n\n        for url in playlists or []:\n            yield from HLSStream.parse_variant_playlist(self.session, url).items()\n\n\n__plugin__ = Mediaklikk\n",
        "url": "https://github.com/streamlink/streamlink.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 698,
        "n_words": 114,
        "vocab_size": 88,
        "complexity": 7,
        "nloc": 52,
        "token_counts": 367,
        "n_ast_nodes": 609,
        "n_identifiers": 44,
        "d_id": 45798,
        "documentation": {
            "docstring": "\n                    mtva_player_manager\\.player\\s*\\(\\s*\n                        document\\.getElementById\\(\\s*\"\\w+\"\\s*\\)\\s*,\\s*\n                        (?P<json>{.*?})\\s*\n                    \\)\\s*;\n                ",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 84169,
        "commit_id": "a142fbff85302c5e3acb2e204eca2e9c75dbc74b",
        "repo": "zulip",
        "path": "zerver/tests/test_upload.py",
        "file_name": "test_upload.py",
        "fun_name": "test_upload_file_with_supplied_mimetype",
        "commit_message": "tests: Refactor away result.json() calls with helpers.\n\nSigned-off-by: Zixuan James Li <p359101898@gmail.com>",
        "code": "def test_upload_file_with_supplied_mimetype(self) -> None:\n        \n        fp = StringIO(\"zulip!\")\n        fp.name = \"pasted_file\"\n        result = self.api_post(\n            self.example_user(\"hamlet\"), \"/api/v1/user_uploads?mimetype=image/png\", {\"file\": fp}\n        )\n        uri = self.assert_json_success(result)[\"uri\"]\n        self.assertTrue(uri.endswith(\"pasted_file.png\"))\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 82,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 62,
        "n_ast_nodes": 114,
        "n_identifiers": 12,
        "d_id": 17798,
        "documentation": {
            "docstring": "\n        When files are copied into the system clipboard and pasted for upload\n        the filename may not be supplied so the extension is determined from a\n        query string parameter.\n        ",
            "n_words": 28,
            "vocab_size": 26,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 177121,
        "commit_id": "9b63ca1a0d46a1f50bcc59eda52be02721a134db",
        "repo": "networkx",
        "path": "networkx/readwrite/graph6.py",
        "file_name": "graph6.py",
        "fun_name": "write_graph6",
        "commit_message": "Remove old Appveyor cruft (#5924)\n\n* Remove old Appveyor cruft\r\n\r\n* Fix Windows issue",
        "code": "def write_graph6(G, path, nodes=None, header=True):\n    \n    return write_graph6_file(G, path, nodes=nodes, header=header)\n\n\n@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 16,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 31,
        "n_ast_nodes": 67,
        "n_identifiers": 7,
        "d_id": 42276,
        "documentation": {
            "docstring": "Write a simple undirected graph to a path in graph6 format.\n\n    Parameters\n    ----------\n    G : Graph (undirected)\n\n    path : str\n       The path naming the file to which to write the graph.\n\n    nodes: list or iterable\n       Nodes are labeled 0...n-1 in the order provided.  If None the ordering\n       given by ``G.nodes()`` is used.\n\n    header: bool\n       If True add '>>graph6<<' string to head of data\n\n    Raises\n    ------\n    NetworkXNotImplemented\n        If the graph is directed or is a multigraph.\n\n    ValueError\n        If the graph has at least ``2 ** 36`` nodes; the graph6 format\n        is only defined for graphs of order less than ``2 ** 36``.\n\n    Examples\n    --------\n    You can write a graph6 file by giving the path to a file::\n\n        >>> import tempfile\n        >>> with tempfile.NamedTemporaryFile(delete=False) as f:\n        ...     nx.write_graph6(nx.path_graph(2), f.name)\n        ...     _ = f.seek(0)\n        ...     print(f.read())\n        b'>>graph6<<A_\\\\n'\n\n    See Also\n    --------\n    from_graph6_bytes, read_graph6\n\n    Notes\n    -----\n    The function writes a newline character after writing the encoding\n    of the graph.\n\n    The format does not support edge or node labels, parallel edges or\n    self loops.  If self loops are present they are silently ignored.\n\n    References\n    ----------\n    .. [1] Graph6 specification\n           <http://users.cecs.anu.edu.au/~bdm/data/formats.html>\n\n    ",
            "n_words": 184,
            "vocab_size": 127,
            "n_whitespaces": 373,
            "language": "en"
        }
    },
    {
        "id": 250105,
        "commit_id": "3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b",
        "repo": "synapse",
        "path": "tests/storage/test_cleanup_extrems.py",
        "file_name": "test_cleanup_extrems.py",
        "fun_name": "test_forked_graph_cleanup",
        "commit_message": "Require types in tests.storage. (#14646)\n\nAdds missing type hints to `tests.storage` package\r\nand does not allow untyped definitions.",
        "code": "def test_forked_graph_cleanup(self) -> None:\n        r\n\n        # Create the room graph\n        event_id_a = self.create_and_send_event(self.room_id, self.user)\n        event_id_b = self.create_and_send_event(self.room_id, self.user)\n        event_id_sf1 = self.create_and_send_event(\n            self.room_id, self.user, True, [event_id_a]\n        )\n        event_id_sf2 = self.create_and_send_event(\n            self.room_id, self.user, True, [event_id_a, event_id_b]\n        )\n        event_id_sf3 = self.create_and_send_event(\n            self.room_id, self.user, True, [event_id_sf1]\n        )\n        self.create_and_send_event(\n            self.room_id, self.user, True, [event_id_sf2, event_id_sf3]\n        )  # SF4\n        event_id_c = self.create_and_send_event(\n            self.room_id, self.user, False, [event_id_sf3]\n        )\n\n        # Add the new extremity and check the latest events are as expected\n        self.add_extremity(self.room_id, event_id_a)\n\n        latest_event_ids = self.get_success(\n            self.store.get_latest_event_ids_in_room(self.room_id)\n        )\n        self.assertEqual(set(latest_event_ids), {event_id_a, event_id_b, event_id_c})\n\n        # Run the background update and check it did the right thing\n        self.run_background_update()\n\n        latest_event_ids = self.get_success(\n            self.store.get_latest_event_ids_in_room(self.room_id)\n        )\n        self.assertEqual(set(latest_event_ids), {event_id_b, event_id_c})\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 350,
        "n_words": 105,
        "vocab_size": 61,
        "complexity": 1,
        "nloc": 46,
        "token_counts": 220,
        "n_ast_nodes": 327,
        "n_identifiers": 19,
        "d_id": 73272,
        "documentation": {
            "docstring": "Test that extremities are correctly calculated in the presence of\n        soft failed events.\n\n        Tests a graph like, where time flows down the page:\n\n                A     B\n               / \\   /\n              /   \\ /\n            SF1   SF2\n             |     |\n            SF3    |\n           /   \\   |\n           |    \\  |\n           C     SF4\n\n        Where SF* are soft failed, and with them A, B and C marked as\n        extremities. This should resolve to B and C being marked as extremity.\n        ",
            "n_words": 71,
            "vocab_size": 48,
            "n_whitespaces": 241,
            "language": "en"
        }
    },
    {
        "id": 205061,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/oracle/creation.py",
        "file_name": "creation.py",
        "fun_name": "_test_settings_get",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _test_settings_get(self, key, default=None, prefixed=None):\n        \n        settings_dict = self.connection.settings_dict\n        val = settings_dict[\"TEST\"].get(key, default)\n        if val is None and prefixed:\n            val = TEST_DATABASE_PREFIX + settings_dict[prefixed]\n        return val\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 71,
        "n_words": 25,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 83,
        "n_identifiers": 10,
        "d_id": 51003,
        "documentation": {
            "docstring": "\n        Return a value from the test settings dict, or a given default, or a\n        prefixed entry from the main settings dict.\n        ",
            "n_words": 21,
            "vocab_size": 15,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 219497,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_collections_abc.py",
        "file_name": "_collections_abc.py",
        "fun_name": "throw",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def throw(self, typ, val=None, tb=None):\n        \n        if val is None:\n            if tb is None:\n                raise typ\n            val = typ()\n        if tb is not None:\n            val = val.with_traceback(tb)\n        raise val\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 104,
        "n_words": 28,
        "vocab_size": 16,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 49,
        "n_ast_nodes": 78,
        "n_identifiers": 6,
        "d_id": 55605,
        "documentation": {
            "docstring": "Raise an exception in the coroutine.\n        Return next yielded value or raise StopIteration.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 125913,
        "commit_id": "c4a259828b9cfbfb4f09059f74808893a6d20b76",
        "repo": "ray",
        "path": "python/ray/tests/kuberay/scripts/non_terminated_nodes_count.py",
        "file_name": "non_terminated_nodes_count.py",
        "fun_name": "count_non_terminated_nodes",
        "commit_message": "[kuberay] Update KubeRay operator commit, turn autoscaler RPC drain back on (#27077)\n\nThis PR:\r\n\r\n- Updates the KubeRay operator commit used in the Ray CI autoscaling test\r\n- Uses the RayCluster autoscaling sample config from the KubeRay repo in place of of a config from the Ray repo\r\n- Turns the autoscaler RPC worker drain back on, as I saw some dead node messages from the GCS, and the RPC drain is supposed to avoid those.\r\n\r\nSigned-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>",
        "code": "def count_non_terminated_nodes() -> int:\n    \n    provider_config = _generate_provider_config(ray_cluster_namespace=\"default\")\n    kuberay_node_provider = _get_node_provider(\n        provider_config=provider_config, cluster_name=\"raycluster-autoscaler\"\n    )\n    nodes = kuberay_node_provider.non_terminated_nodes({})\n    return len(nodes)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 41,
        "n_ast_nodes": 73,
        "n_identifiers": 11,
        "d_id": 28023,
        "documentation": {
            "docstring": "Get the count of non terminated nodes for the Ray cluster raycluster-autoscaler\n    in namespace default.\n    ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 111439,
        "commit_id": "8f1ba4de582c5e5282c022a7713a56b47302cabe",
        "repo": "spaCy",
        "path": "spacy/util.py",
        "file_name": "util.py",
        "fun_name": "all_equal",
        "commit_message": "Backport parser/alignment optimizations from `feature/refactor-parser` (#10952)",
        "code": "def all_equal(iterable):\n    \n    g = itertools.groupby(iterable)\n    return next(g, True) and not next(g, False)\n",
        "url": "https://github.com/explosion/spaCy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 21,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 29,
        "n_ast_nodes": 48,
        "n_identifiers": 6,
        "d_id": 24410,
        "documentation": {
            "docstring": "Return True if all the elements are equal to each other\n    (or if the input is an empty sequence), False otherwise.",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 71277,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/templatetags/wagtailadmin_tags.py",
        "file_name": "wagtailadmin_tags.py",
        "fun_name": "pagination_querystring",
        "commit_message": "Reformat with black",
        "code": "def pagination_querystring(context, page_number, page_key=\"p\"):\n    \n    return querystring(context, **{page_key: page_number})\n\n\n@register.inclusion_tag(\n    \"wagtailadmin/pages/listing/_pagination.html\", takes_context=True\n)",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@register.inclusion_tag(\n    \"wagtailadmin/pages/listing/_pagination.html\", takes_context=True\n)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 19,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 24,
        "n_ast_nodes": 59,
        "n_identifiers": 8,
        "d_id": 15657,
        "documentation": {
            "docstring": "\n    Print out a querystring with an updated page number:\n\n        {% if page.has_next_page %}\n            <a href=\"{% pagination_link page.next_page_number %}\">Next page</a>\n        {% endif %}\n    ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 261584,
        "commit_id": "d8fa96c29828e3ca79ddd5d7466521ac4d95213c",
        "repo": "scikit-learn",
        "path": "sklearn/impute/tests/test_impute.py",
        "file_name": "test_impute.py",
        "fun_name": "test_knn_imputer_keep_empty_features",
        "commit_message": "ENH keep features with all missing values during imputation (#24770)\n\nCo-authored-by: Chiara Marmo <cmarmo@users.noreply.github.com>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>\r\nCo-authored-by: Vitor SRG <vitorssrg@gmail.com>\r\nFixes https://github.com/scikit-learn/scikit-learn/pull/16695\r\nFixes https://github.com/scikit-learn/scikit-learn/issues/16426\r\nFixes https://github.com/scikit-learn/scikit-learn/issues/16977",
        "code": "def test_knn_imputer_keep_empty_features(keep_empty_features):\n    \n    X = np.array([[1, np.nan, 2], [3, np.nan, np.nan]])\n\n    imputer = KNNImputer(keep_empty_features=keep_empty_features)\n\n    for method in [\"fit_transform\", \"transform\"]:\n        X_imputed = getattr(imputer, method)(X)\n        if keep_empty_features:\n            assert X_imputed.shape == X.shape\n            assert_array_equal(X_imputed[:, 1], 0)\n        else:\n            assert X_imputed.shape == (X.shape[0], X.shape[1] - 1)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 105,
        "n_words": 39,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 110,
        "n_ast_nodes": 168,
        "n_identifiers": 13,
        "d_id": 76878,
        "documentation": {
            "docstring": "Check the behaviour of `keep_empty_features` for `KNNImputer`.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 241678,
        "commit_id": "8a549a550cb10189ff1db382f546a40cd1c6c5b3",
        "repo": "lightning",
        "path": "pytorch_lightning/callbacks/progress/base.py",
        "file_name": "base.py",
        "fun_name": "test_batch_idx",
        "commit_message": "Integrate progress tracking into the progress bar (#11213)",
        "code": "def test_batch_idx(self) -> int:\n        \n        if self.trainer is None:\n            return 0\n        return self.trainer.test_loop.epoch_loop.batch_progress.current.processed\n",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 44,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 31,
        "n_ast_nodes": 51,
        "n_identifiers": 9,
        "d_id": 69648,
        "documentation": {
            "docstring": "The number of batches processed during testing.\n\n        Use this to update your progress bar.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 112855,
        "commit_id": "98c1a77f61900d486f46d284c49fb65675dbee6a",
        "repo": "nni",
        "path": "nni/algorithms/hpo/bohb_advisor/bohb_advisor.py",
        "file_name": "bohb_advisor.py",
        "fun_name": "_get_one_trial_job",
        "commit_message": "Support multiple HPO experiments in one process (#4855)",
        "code": "def _get_one_trial_job(self):\n        \n        if not self.generated_hyper_configs:\n            ret = {\n                'parameter_id': '-1_0_0',\n                'parameter_source': 'algorithm',\n                'parameters': ''\n            }\n            self.send(CommandType.NoMoreTrialJobs, nni.dump(ret))\n            return None\n        assert self.generated_hyper_configs\n        params = self.generated_hyper_configs.pop(0)\n        ret = {\n            'parameter_id': params[0],\n            'parameter_source': 'algorithm',\n            'parameters': params[1]\n        }\n        self.parameters[params[0]] = params[1]\n        return ret\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 217,
        "n_words": 39,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 18,
        "token_counts": 95,
        "n_ast_nodes": 164,
        "n_identifiers": 12,
        "d_id": 24770,
        "documentation": {
            "docstring": "get one trial job, i.e., one hyperparameter configuration.\n\n        If this function is called, Command will be sent by BOHB:\n        a. If there is a parameter need to run, will return \"NewTrialJob\" with a dict:\n        {\n            'parameter_id': id of new hyperparameter\n            'parameter_source': 'algorithm'\n            'parameters': value of new hyperparameter\n        }\n        b. If BOHB don't have parameter waiting, will return \"NoMoreTrialJobs\" with\n        {\n            'parameter_id': '-1_0_0',\n            'parameter_source': 'algorithm',\n            'parameters': ''\n        }\n        ",
            "n_words": 67,
            "vocab_size": 48,
            "n_whitespaces": 189,
            "language": "en"
        }
    },
    {
        "id": 77976,
        "commit_id": "b8a9a2d319b06fc2318d68d05b5a6cdf85b5b33d",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/options.py",
        "file_name": "options.py",
        "fun_name": "get_menu_item",
        "commit_message": "Deprecate wagtail.contrib.modeladmin.menus.SubMenu in favour of wagtail.admin.menu.Menu\n\nThe Menu class was not originally designed to accept menu items at constructor time (instead requiring them to be passed via hooks); ModelAdmin's SubMenu class patched this functionality in, and the documentation for extending admin views piggybacked on this. Add this functionality to the base Menu class so that we don't have this unnecessary dependency on ModelAdmin.",
        "code": "def get_menu_item(self, order=None):\n        \n        return ModelAdminMenuItem(self, order or self.get_menu_order())\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 23,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 16727,
        "documentation": {
            "docstring": "\n        Utilised by Wagtail's 'register_menu_item' hook to create a menu item\n        to access the listing view, or can be called by ModelAdminGroup\n        to create a submenu\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 247885,
        "commit_id": "33ebee47e4e96a2b6fdf72091769e59034dc550f",
        "repo": "synapse",
        "path": "tests/unittest.py",
        "file_name": "unittest.py",
        "fun_name": "get_failure",
        "commit_message": "Remove redundant `get_success` calls in test code (#12346)\n\nThere are a bunch of places we call get_success on an immediate value, which is unnecessary. Let's rip them out, and remove the redundant functionality in get_success and friends.",
        "code": "def get_failure(self, d, exc):\n        \n        deferred: Deferred[Any] = ensureDeferred(d)\n        self.pump()\n        return self.failureResultOf(deferred, exc)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 56,
        "n_identifiers": 10,
        "d_id": 71975,
        "documentation": {
            "docstring": "\n        Run a Deferred and get a Failure from it. The failure must be of the type `exc`.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 265175,
        "commit_id": "a38a880e67d78eba52f19cc4c2613e9399939c2f",
        "repo": "netbox",
        "path": "netbox/utilities/request.py",
        "file_name": "request.py",
        "fun_name": "get_client_ip",
        "commit_message": "Refactor source IP resolution logic",
        "code": "def get_client_ip(request, additional_headers=()):\n    \n    HTTP_HEADERS = (\n        'HTTP_X_REAL_IP',\n        'HTTP_X_FORWARDED_FOR',\n        'REMOTE_ADDR',\n        *additional_headers\n    )\n    for header in HTTP_HEADERS:\n        if header in request.META:\n            client_ip = request.META[header].split(',')[0]\n            try:\n                return ipaddress.ip_address(client_ip)\n            except ValueError:\n                raise ValueError(f\"Invalid IP address set for {header}: {client_ip}\")\n\n    # Could not determine the client IP address from request headers\n    return None\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 164,
        "n_words": 48,
        "vocab_size": 41,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 71,
        "n_ast_nodes": 128,
        "n_identifiers": 11,
        "d_id": 78016,
        "documentation": {
            "docstring": "\n    Return the client (source) IP address of the given request.\n    ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 101210,
        "commit_id": "5e73437be47f2410439a3c6716de96354e6a0c94",
        "repo": "faceswap",
        "path": "lib/align/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "save_video_meta_data",
        "commit_message": "lib.align updates:\n  - alignments.py\n    - Add typed dicts for imported alignments\n    - Explicitly check for presence of thumb value in alignments dict\n    - linting\n  - detected_face.py\n    - Typing\n    - Linting\n    - Legacy support for pre-aligned face\n    - Update dependencies to new property names",
        "code": "def save_video_meta_data(self, pts_time, keyframes):\n        \n        if pts_time[0] != 0:\n            pts_time, keyframes = self._pad_leading_frames(pts_time, keyframes)\n\n        sample_filename = next(fname for fname in self.data)\n        basename = sample_filename[:sample_filename.rfind(\"_\")]\n        logger.debug(\"sample filename: %s, base filename: %s\", sample_filename, basename)\n        logger.info(\"Saving video meta information to Alignments file\")\n\n        for idx, pts in enumerate(pts_time):\n            meta = dict(pts_time=pts, keyframe=idx in keyframes)\n            key = f\"{basename}_{idx + 1:06d}.png\"\n            if key not in self.data:\n                self.data[key] = dict(video_meta=meta, faces=[])\n            else:\n                self.data[key][\"video_meta\"] = meta\n\n        logger.debug(\"Alignments count: %s, timestamp count: %s\", len(self.data), len(pts_time))\n        if len(self.data) != len(pts_time):\n            raise FaceswapError(\n                \"There is a mismatch between the number of frames found in the video file \"\n                f\"({len(pts_time)}) and the number of frames found in the alignments file \"\n                f\"({len(self.data)}).\\nThis can be caused by a number of issues:\"\n                \"\\n  - The video has a Variable Frame Rate and FFMPEG is having a hard time \"\n                \"calculating the correct number of frames.\"\n                \"\\n  - You are working with a Merged Alignments file. This is not supported for \"\n                \"your current use case.\"\n                \"\\nYou should either extract the video to individual frames, re-encode the \"\n                \"video at a constant frame rate and re-run extraction or work with a dedicated \"\n                \"alignments file for your requested video.\")\n        self.save()\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 512,
        "n_words": 194,
        "vocab_size": 128,
        "complexity": 6,
        "nloc": 28,
        "token_counts": 189,
        "n_ast_nodes": 353,
        "n_identifiers": 26,
        "d_id": 20631,
        "documentation": {
            "docstring": " Save video meta data to the alignments file.\n\n        If the alignments file does not have an entry for every frame (e.g. if Extract Every N\n        was used) then the frame is added to the alignments file with no faces, so that they video\n        meta data can be stored.\n\n        Parameters\n        ----------\n        pts_time: list\n            A list of presentation timestamps (`float`) in frame index order for every frame in\n            the input video\n        keyframes: list\n            A list of frame indices corresponding to the key frames in the input video\n        ",
            "n_words": 85,
            "vocab_size": 55,
            "n_whitespaces": 175,
            "language": "en"
        }
    },
    {
        "id": 42483,
        "commit_id": "692adaff901dd9daf29400fdf3385130aefbfb2a",
        "repo": "nltk",
        "path": "nltk/util.py",
        "file_name": "util.py",
        "fun_name": "unweighted_minimum_spanning_digraph",
        "commit_message": "Fix some tests in Wordnet-related DocStrings",
        "code": "def unweighted_minimum_spanning_digraph(tree, children=iter, shapes=None, attr=None):\n    \n    return edges2dot(\n        edge_closure(\n            tree, lambda node: unweighted_minimum_spanning_dict(tree, children)[node]\n        ),\n        shapes,\n        attr,\n    )\n\n\n##########################################################################\n# Breadth-First / Depth-first Searches with Cycle Detection\n##########################################################################\n\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 72,
        "n_words": 27,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 44,
        "n_ast_nodes": 67,
        "n_identifiers": 10,
        "d_id": 7568,
        "documentation": {
            "docstring": "\n\n    Build a Minimum Spanning Tree (MST) of an unweighted graph,\n    by traversing the nodes of a tree in breadth-first order,\n    discarding eventual cycles.\n\n    Return a representation of this MST as a string in the DOT graph language,\n    which can be converted to an image by the 'dot' program from the Graphviz\n    package, or nltk.parse.dependencygraph.dot2img(dot_string).\n\n    The first argument should be the tree root;\n    children should be a function taking as argument a tree node\n    and returning an iterator of the node's children.\n\n    >>> import nltk\n    >>> wn=nltk.corpus.wordnet\n    >>> from nltk.util import unweighted_minimum_spanning_digraph as umsd\n    >>> print(umsd(wn.synset('bound.a.01'), lambda s:s.also_sees()))\n    digraph G {\n    \"Synset('bound.a.01')\" -> \"Synset('unfree.a.02')\";\n    \"Synset('unfree.a.02')\" -> \"Synset('confined.a.02')\";\n    \"Synset('unfree.a.02')\" -> \"Synset('dependent.a.01')\";\n    \"Synset('unfree.a.02')\" -> \"Synset('restricted.a.01')\";\n    \"Synset('restricted.a.01')\" -> \"Synset('classified.a.02')\";\n    }\n    <BLANKLINE>\n    ",
            "n_words": 117,
            "vocab_size": 81,
            "n_whitespaces": 184,
            "language": "en"
        }
    },
    {
        "id": 20942,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/typing_extensions.py",
        "file_name": "typing_extensions.py",
        "fun_name": "_gorg",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _gorg(cls):\n    \n    assert isinstance(cls, GenericMeta)\n    if hasattr(cls, '_gorg'):\n        return cls._gorg\n    while cls.__origin__ is not None:\n        cls = cls.__origin__\n    return cls\n\n\n_PROTO_WHITELIST = ['Callable', 'Awaitable',\n                    'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator',\n                    'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',\n                    'ContextManager', 'AsyncContextManager']\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 120,
        "n_words": 35,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 40,
        "n_ast_nodes": 124,
        "n_identifiers": 7,
        "d_id": 3622,
        "documentation": {
            "docstring": "This function exists for compatibility with old typing versions.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 42476,
        "commit_id": "75f4e2183a80904dd3a6f958072ae2d063b51fad",
        "repo": "nltk",
        "path": "nltk/corpus/reader/wordnet.py",
        "file_name": "wordnet.py",
        "fun_name": "lemmas",
        "commit_message": "Handle wordnet synsets that were lost in mapping",
        "code": "def lemmas(self, lang=\"eng\"):\n        \n        if lang == \"eng\":\n            return self._lemmas\n        elif self._name:\n            self._wordnet_corpus_reader._load_lang_data(lang)\n            lemmark = []\n            lemmy = self.lemma_names(lang)\n            for lem in lemmy:\n                temp = Lemma(\n                    self._wordnet_corpus_reader,\n                    self,\n                    lem,\n                    self._wordnet_corpus_reader._lexnames.index(self.lexname()),\n                    0,\n                    None,\n                )\n                temp._lang = lang\n                lemmark.append(temp)\n            return lemmark\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 299,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 19,
        "token_counts": 94,
        "n_ast_nodes": 150,
        "n_identifiers": 18,
        "d_id": 7561,
        "documentation": {
            "docstring": "Return all the lemma objects associated with the synset",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 337588,
        "commit_id": "23c0341262bd396a3ba9265614b3818d6e08a6c1",
        "repo": "accelerate",
        "path": "tests/test_examples.py",
        "file_name": "test_examples.py",
        "fun_name": "test_cross_validation",
        "commit_message": "Refactor tests to use accelerate launch (#373)\n\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def test_cross_validation(self):\n        testargs = .split()\n        with mock.patch.dict(os.environ, {\"TESTING_MOCKED_DATALOADERS\": \"0\"}):\n            output = subprocess.run(\n                self._launch_args + testargs, universal_newlines=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE\n            ).stdout\n            results = ast.literal_eval(re.findall(\"({.+})\", output)[-1])\n            self.assertGreaterEqual(results[\"accuracy\"], 0.75)\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 97,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 92,
        "n_ast_nodes": 148,
        "n_identifiers": 23,
        "d_id": 121085,
        "documentation": {
            "docstring": "\n        examples/by_feature/cross_validation.py\n        --num_folds 2\n        ",
            "n_words": 3,
            "vocab_size": 3,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 217736,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/client.py",
        "file_name": "client.py",
        "fun_name": "parse_headers",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parse_headers(fp, _class=HTTPMessage):\n    \n    headers = _read_headers(fp)\n    hstring = b''.join(headers).decode('iso-8859-1')\n    return email.parser.Parser(_class=_class).parsestr(hstring)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 23,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 46,
        "n_ast_nodes": 78,
        "n_identifiers": 13,
        "d_id": 54906,
        "documentation": {
            "docstring": "Parses only RFC2822 headers from a file pointer.\n\n    email Parser wants to see strings rather than bytes.\n    But a TextIOWrapper around self.rfile would buffer too many bytes\n    from the stream, bytes which we later need to read as bytes.\n    So we read the correct bytes here, as bytes, for email Parser\n    to parse.\n\n    ",
            "n_words": 53,
            "vocab_size": 40,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 266521,
        "commit_id": "fee90b15a25b588bfb8a9ff047e851d43e78511f",
        "repo": "ansible",
        "path": "lib/ansible/module_utils/common/file.py",
        "file_name": "file.py",
        "fun_name": "is_executable",
        "commit_message": "Misc typo fixes in module_utils (#76564)",
        "code": "def is_executable(path):\n    # This function's signature needs to be repeated\n    # as the first line of its docstring.\n    # This method is reused by the basic module,\n    # the repetition helps the basic module's html documentation come out right.\n    # http://www.sphinx-doc.org/en/master/usage/extensions/autodoc.html#confval-autodoc_docstring_signature\n    \n    # These are all bitfields so first bitwise-or all the permissions we're\n    # looking for, then bitwise-and with the file's mode to determine if any\n    # execute bits are set.\n    return ((stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH) & os.stat(path)[stat.ST_MODE])\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 109,
        "n_words": 79,
        "vocab_size": 60,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 34,
        "n_ast_nodes": 63,
        "n_identifiers": 8,
        "d_id": 78454,
        "documentation": {
            "docstring": "is_executable(path)\n\n    is the given path executable?\n\n    :arg path: The path of the file to check.\n\n    Limitations:\n\n    * Does not account for FSACLs.\n    * Most times we really want to know \"Can the current user execute this\n      file\".  This function does not tell us that, only if any execute bit is set.\n    ",
            "n_words": 51,
            "vocab_size": 43,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 31755,
        "commit_id": "6c8f4c9a938a09749ea1b19a5fa2a8dd27e99a29",
        "repo": "transformers",
        "path": "src/transformers/models/groupvit/modeling_groupvit.py",
        "file_name": "modeling_groupvit.py",
        "fun_name": "project_group_token",
        "commit_message": "Adding GroupViT Models (#17313)\n\n* add group vit and fixed test (except slow)\r\n\r\n* passing slow test\r\n\r\n* addressed some comments\r\n\r\n* fixed test\r\n\r\n* fixed style\r\n\r\n* fixed copy\r\n\r\n* fixed segmentation output\r\n\r\n* fixed test\r\n\r\n* fixed relative path\r\n\r\n* fixed copy\r\n\r\n* add ignore non auto configured\r\n\r\n* fixed docstring, add doc\r\n\r\n* fixed copies\r\n\r\n* Apply suggestions from code review\r\n\r\nmerge suggestions\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* resolve comment, renaming model\r\n\r\n* delete unused attr\r\n\r\n* use fix copies\r\n\r\n* resolve comments\r\n\r\n* fixed attn\r\n\r\n* remove unused vars\r\n\r\n* refactor tests\r\n\r\n* resolve final comments\r\n\r\n* add demo notebook\r\n\r\n* fixed inconsitent default\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\n\r\n* rename stage->stages\r\n\r\n* Create single GroupViTEncoderLayer class\r\n\r\n* Update conversion script\r\n\r\n* Simplify conversion script\r\n\r\n* Remove cross-attention class in favor of GroupViTAttention\r\n\r\n* Convert other model as well, add processor to conversion script\r\n\r\n* addressing final comment\r\n\r\n* fixed args\r\n\r\n* Update src/transformers/models/groupvit/modeling_groupvit.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def project_group_token(self, group_tokens):\n        \n        # [B, num_output_groups, C] <- [B, num_group_tokens, C]\n        projected_group_tokens = self.mlp_inter(group_tokens)\n        projected_group_tokens = self.norm_post_tokens(projected_group_tokens)\n        return projected_group_tokens\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 54,
        "n_words": 19,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 5800,
        "documentation": {
            "docstring": "\n        Args:\n            group_tokens (torch.Tensor): group tokens, [batch_size, num_group_tokens, channels]\n\n        Returns:\n            projected_group_tokens (torch.Tensor): [batch_size, num_output_groups, channels]\n        ",
            "n_words": 14,
            "vocab_size": 11,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 292690,
        "commit_id": "cfd763db40544c31077b46631bbdd9655581dfe9",
        "repo": "core",
        "path": "homeassistant/components/sonos/media.py",
        "file_name": "media.py",
        "fun_name": "write_media_player_states",
        "commit_message": "Refactor Sonos media metadata handling (#66840)\n\nCo-authored-by: Paulus Schoutsen <paulus@home-assistant.io>",
        "code": "def write_media_player_states(self) -> None:\n        \n        dispatcher_send(self.hass, SONOS_MEDIA_UPDATED, self.soco.uid)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 36,
        "n_identifiers": 7,
        "d_id": 91764,
        "documentation": {
            "docstring": "Send a signal to media player(s) to write new states.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 203524,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/tests.py",
        "file_name": "tests.py",
        "fun_name": "select_option",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def select_option(self, selector, value):\n        \n        from selenium.webdriver.common.by import By\n        from selenium.webdriver.support.ui import Select\n\n        select = Select(self.selenium.find_element(By.CSS_SELECTOR, selector))\n        select.select_by_value(value)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 52,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 53,
        "n_ast_nodes": 79,
        "n_identifiers": 16,
        "d_id": 50427,
        "documentation": {
            "docstring": "\n        Select the <OPTION> with the value `value` inside the <SELECT> widget\n        identified by the CSS selector `selector`.\n        ",
            "n_words": 17,
            "vocab_size": 14,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 101421,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "_random_choice",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _random_choice(self) -> List[int]:\n        \n        retval = [random.choice(indices) for indices in self._indices]\n        logger.debug(retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 35,
        "n_ast_nodes": 57,
        "n_identifiers": 11,
        "d_id": 20835,
        "documentation": {
            "docstring": " list: Random indices from the :attr:`_indices` group ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 207724,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_has_related_field_in_list_display_fk",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_has_related_field_in_list_display_fk(self):\n        \n        state = State.objects.create(name=\"Karnataka\")\n        City.objects.create(state=state, name=\"Bangalore\")\n        response = self.client.get(reverse(\"admin:admin_views_city_changelist\"), {})\n\n        response.context[\"cl\"].list_display = [\"id\", \"name\", \"state\"]\n        self.assertIs(response.context[\"cl\"].has_related_field_in_list_display(), True)\n\n        response.context[\"cl\"].list_display = [\"id\", \"name\", \"state_id\"]\n        self.assertIs(response.context[\"cl\"].has_related_field_in_list_display(), False)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 81,
        "n_words": 25,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 114,
        "n_ast_nodes": 200,
        "n_identifiers": 16,
        "d_id": 52071,
        "documentation": {
            "docstring": "Joins shouldn't be performed for <FK>_id fields in list display.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 55137,
        "commit_id": "c0cb1fee460c1bded9e3eb741ad7979402844bf8",
        "repo": "prefect",
        "path": "src/prefect/cli/base.py",
        "file_name": "base.py",
        "fun_name": "exit_with_error",
        "commit_message": "Update `set` command; allow CLI `console` object to be patched",
        "code": "def exit_with_error(message, code=1, **kwargs):\n    \n    kwargs.setdefault(\"style\", \"red\")\n    app.console.print(message, **kwargs)\n    raise typer.Exit(code)\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 22,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 66,
        "n_identifiers": 10,
        "d_id": 11226,
        "documentation": {
            "docstring": "\n    Utility to print a stylized error message and exit with a non-zero code\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 109095,
        "commit_id": "eec341a3a5918a59b212afffc2f9285bada1f276",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backend_managers.py",
        "file_name": "backend_managers.py",
        "fun_name": "trigger_tool",
        "commit_message": "Remove several unused variables",
        "code": "def trigger_tool(self, name, sender=None, canvasevent=None, data=None):\n        \n        tool = self.get_tool(name)\n        if tool is None:\n            return\n\n        if sender is None:\n            sender = self\n\n        if isinstance(tool, backend_tools.ToolToggleBase):\n            self._handle_toggle(tool, canvasevent, data)\n\n        tool.trigger(sender, canvasevent, data)  # Actually trigger Tool.\n\n        s = 'tool_trigger_%s' % name\n        event = ToolTriggerEvent(s, sender, tool, canvasevent, data)\n        self._callbacks.process(s, event)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 145,
        "n_words": 48,
        "vocab_size": 35,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 101,
        "n_ast_nodes": 153,
        "n_identifiers": 18,
        "d_id": 23434,
        "documentation": {
            "docstring": "\n        Trigger a tool and emit the ``tool_trigger_{name}`` event.\n\n        Parameters\n        ----------\n        name : str\n            Name of the tool.\n        sender : object\n            Object that wishes to trigger the tool.\n        canvasevent : Event\n            Original Canvas event or None.\n        data : object\n            Extra data to pass to the tool when triggering.\n        ",
            "n_words": 47,
            "vocab_size": 35,
            "n_whitespaces": 148,
            "language": "en"
        }
    },
    {
        "id": 118262,
        "commit_id": "7f0d38c3925c981d015e8624662c8e0c13aa4d97",
        "repo": "mindsdb",
        "path": "mindsdb/interfaces/file/file_controller.py",
        "file_name": "file_controller.py",
        "fun_name": "save_file",
        "commit_message": "get company_id from context",
        "code": "def save_file(self, name, file_path, file_name=None):\n        \n        files_metadata = self.get_files()\n        if name in [x['name'] for x in files_metadata]:\n            raise Exception(f'File already exists: {name}')\n\n        if file_name is None:\n            file_name = Path(file_path).name\n\n        file_dir = None\n        try:\n            df, _col_map = FileHandler._handle_source(file_path)\n\n            ds_meta = {\n                'row_count': len(df),\n                'column_names': list(df.columns)\n            }\n\n            file_record = db.File(\n                name=name,\n                company_id=ctx.company_id,\n                source_file_path=file_name,\n                file_path='',\n                row_count=ds_meta['row_count'],\n                columns=ds_meta['column_names']\n            )\n            db.session.add(file_record)\n            db.session.commit()\n            store_file_path = f'file_{ctx.company_id}_{file_record.id}'\n            file_record.file_path = store_file_path\n            db.session.commit()\n\n            file_dir = Path(self.dir).joinpath(store_file_path)\n            file_dir.mkdir(parents=True, exist_ok=True)\n            source = file_dir.joinpath(file_name)\n            # NOTE may be delay between db record exists and file is really in folder\n            shutil.move(file_path, str(source))\n\n            self.fs_store.put(store_file_path, base_dir=self.dir)\n        except Exception as e:\n            log.logger.error(e)\n            raise\n        finally:\n            if file_dir is not None:\n                shutil.rmtree(file_dir)\n\n        return file_record.id\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 534,
        "n_words": 105,
        "vocab_size": 83,
        "complexity": 7,
        "nloc": 38,
        "token_counts": 247,
        "n_ast_nodes": 417,
        "n_identifiers": 48,
        "d_id": 26200,
        "documentation": {
            "docstring": " Save the file to our store\n\n            Args:\n                name (str): with that name file will be available in sql api\n                file_name (str): file name\n                file_path (str): path to the file\n\n            Returns:\n                int: id of 'file' record in db\n        ",
            "n_words": 37,
            "vocab_size": 27,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 5791,
        "commit_id": "2a157d452611d37cf50ccb7d56ff1a06e9790ecb",
        "repo": "InstaPy",
        "path": "instapy/clarifai_util.py",
        "file_name": "clarifai_util.py",
        "fun_name": "get_source_link",
        "commit_message": "PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438)\n\n* Updated getUserData() and find_element*\r\nSigned-off-by: elulcao <elulcao@icloud.com>\r\n\r\nThanks @breuerfelix for reviewing, 🚀 \r\nPeople in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her",
        "code": "def get_source_link(browser):\n    \n    source = []\n\n    try:\n        source.append(\n            browser.find_element(\n                By.XPATH, read_xpath(get_source_link.__name__, \"image\")\n            ).get_attribute(\"src\")\n        )\n    except NoSuchElementException:\n        source.append(\n            browser.find_element(\n                By.XPATH, read_xpath(get_source_link.__name__, \"video\")\n            ).get_attribute(\"src\")\n        )\n        source.append(\n            browser.find_element(\n                By.XPATH, read_xpath(get_source_link.__name__, \"image_alt\")\n            ).get_attribute(\"src\")\n        )\n\n    return source\n\n",
        "url": "https://github.com/InstaPy/InstaPy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 199,
        "n_words": 31,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 98,
        "n_ast_nodes": 167,
        "n_identifiers": 11,
        "d_id": 821,
        "documentation": {
            "docstring": "Checks to see if a post is an image. If so, returns list with image\n    source URL.\n    If a NoSuchElement exception occurs, checks post for video and returns\n    the source URLs\n    for both the video and the video's keyframe.",
            "n_words": 39,
            "vocab_size": 29,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 207873,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_changelist_with_no_change_url",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_changelist_with_no_change_url(self):\n        \n        o = UnchangeableObject.objects.create()\n        response = self.client.get(\n            reverse(\"admin:admin_views_unchangeableobject_changelist\")\n        )\n        # Check the format of the shown object -- shouldn't contain a change link\n        self.assertContains(\n            response, '<th class=\"field-__str__\">%s</th>' % o, html=True\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 103,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 42,
        "n_ast_nodes": 74,
        "n_identifiers": 12,
        "d_id": 52142,
        "documentation": {
            "docstring": "\n        ModelAdmin.changelist_view shouldn't result in a NoReverseMatch if url\n        for change_view is removed from get_urls (#20934).\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 247581,
        "commit_id": "605d161d7d585847fd1bb98d14d5281daeac8e86",
        "repo": "synapse",
        "path": "tests/util/test_rwlock.py",
        "file_name": "test_rwlock.py",
        "fun_name": "test_cancellation_while_waiting_for_write_lock",
        "commit_message": "Add cancellation support to `ReadWriteLock` (#12120)\n\nAlso convert `ReadWriteLock` to use async context managers.\r\n\r\nSigned-off-by: Sean Quah <seanq@element.io>",
        "code": "def test_cancellation_while_waiting_for_write_lock(self):\n        \n        rwlock = ReadWriteLock()\n        key = \"key\"\n\n        # 1. A reader takes the lock and blocks.\n        reader_d, _, unblock_reader = self._start_blocking_reader(\n            rwlock, key, \"read completed\"\n        )\n\n        # 2. A writer waits for the reader to complete.\n        writer1_d, _, unblock_writer1 = self._start_blocking_writer(\n            rwlock, key, \"write 1 completed\"\n        )\n\n        # 3. A second writer waits for both the reader and first writer to complete.\n        #    This writer will be cancelled later.\n        writer2_d, _ = self._start_nonblocking_writer(rwlock, key, \"write 2 completed\")\n        self.assertFalse(writer2_d.called)\n\n        # 4. A third writer waits for the second writer to complete.\n        writer3_d, _ = self._start_nonblocking_writer(rwlock, key, \"write 3 completed\")\n        self.assertFalse(writer3_d.called)\n\n        # 5. The second writer is cancelled, but continues waiting for the lock.\n        #    The reader, first writer and third writer should not be cancelled.\n        #    The first writer should still be waiting on the reader.\n        #    The third writer should still be waiting on the second writer.\n        writer2_d.cancel()\n        self.assertNoResult(writer2_d)\n        self.assertFalse(reader_d.called, \"Reader was unexpectedly cancelled\")\n        self.assertFalse(writer1_d.called, \"First writer was unexpectedly cancelled\")\n        self.assertFalse(\n            writer3_d.called,\n            \"Third writer was unexpectedly cancelled or given the lock before the first \"\n            \"writer finished\",\n        )\n\n        # 6. Unblock the reader, which should complete.\n        #    The first writer should be given the lock and block.\n        #    The third writer should still be waiting on the second writer.\n        unblock_reader.callback(None)\n        self.assertEqual(\"read completed\", self.successResultOf(reader_d))\n        self.assertNoResult(writer2_d)\n        self.assertFalse(\n            writer3_d.called,\n            \"Third writer was unexpectedly given the lock before the first writer \"\n            \"finished\",\n        )\n\n        # 7. Unblock the first writer, which should complete.\n        unblock_writer1.callback(None)\n        self.assertEqual(\"write 1 completed\", self.successResultOf(writer1_d))\n\n        # 8. The second writer should take the lock and release it immediately, since it\n        #    has been cancelled.\n        self.failureResultOf(writer2_d, CancelledError)\n\n        # 9. The third writer should take the lock and complete.\n        self.assertTrue(\n            writer3_d.called, \"Third writer is stuck waiting for a cancelled writer\"\n        )\n        self.assertEqual(\"write 3 completed\", self.successResultOf(writer3_d))\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 721,
        "n_words": 293,
        "vocab_size": 120,
        "complexity": 1,
        "nloc": 37,
        "token_counts": 220,
        "n_ast_nodes": 385,
        "n_identifiers": 25,
        "d_id": 71756,
        "documentation": {
            "docstring": "Test cancellation while waiting for a write lock.\n\n        Tests that cancelling a waiting writer:\n         * does not cancel the reader or writer it is waiting on\n         * does not cancel the next writer waiting on it\n         * does not allow the next writer to acquire the lock before an earlier reader\n           and writer have finished\n         * does not keep the next writer waiting indefinitely\n\n        These correspond to the asserts with explicit messages.\n        ",
            "n_words": 72,
            "vocab_size": 42,
            "n_whitespaces": 135,
            "language": "en"
        }
    },
    {
        "id": 169203,
        "commit_id": "bbf17ea692e437cec908eae6759ffff8092fb42e",
        "repo": "pandas",
        "path": "web/pandas_web.py",
        "file_name": "pandas_web.py",
        "fun_name": "current_year",
        "commit_message": "WEB: Add new footer to web (#48557)",
        "code": "def current_year(context):\n        \n        context[\"current_year\"] = datetime.datetime.now().year\n        return context\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 28,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 40,
        "n_identifiers": 5,
        "d_id": 40398,
        "documentation": {
            "docstring": "\n        Add the current year to the context, so it can be used for the copyright\n        note, or other places where it is needed.\n        ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 204933,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/schema.py",
        "file_name": "schema.py",
        "fun_name": "remove_field",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def remove_field(self, model, field):\n        \n        # Special-case implicit M2M tables\n        if field.many_to_many and field.remote_field.through._meta.auto_created:\n            return self.delete_model(field.remote_field.through)\n        # It might not actually have a column behind it\n        if field.db_parameters(connection=self.connection)[\"type\"] is None:\n            return\n        # Drop any FK constraints, MySQL requires explicit deletion\n        if field.remote_field:\n            fk_names = self._constraint_names(model, [field.column], foreign_key=True)\n            for fk_name in fk_names:\n                self.execute(self._delete_fk_sql(model, fk_name))\n        # Delete the column\n        sql = self.sql_delete_column % {\n            \"table\": self.quote_name(model._meta.db_table),\n            \"column\": self.quote_name(field.column),\n        }\n        self.execute(sql)\n        # Reset connection if required\n        if self.connection.features.connection_persists_old_columns:\n            self.connection.close()\n        # Remove all deferred statements referencing the deleted column.\n        for sql in list(self.deferred_sql):\n            if isinstance(sql, Statement) and sql.references_column(\n                model._meta.db_table, field.column\n            ):\n                self.deferred_sql.remove(sql)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 346,
        "n_words": 97,
        "vocab_size": 79,
        "complexity": 10,
        "nloc": 21,
        "token_counts": 190,
        "n_ast_nodes": 304,
        "n_identifiers": 32,
        "d_id": 50985,
        "documentation": {
            "docstring": "\n        Remove a field from a model. Usually involves deleting a column,\n        but for M2Ms may involve deleting a table.\n        ",
            "n_words": 19,
            "vocab_size": 15,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 111194,
        "commit_id": "91ccacea12a46c62ccb5e7f6de891a37cb71e184",
        "repo": "spaCy",
        "path": "spacy/ml/models/multi_task.py",
        "file_name": "multi_task.py",
        "fun_name": "get_characters_loss",
        "commit_message": "Auto-format code with black (#10209)\n\n* Auto-format code with black\r\n\r\n* add black requirement to dev dependencies and pin to 22.x\r\n\r\n* ignore black dependency for comparison with setup.cfg\r\n\r\nCo-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>\r\nCo-authored-by: svlandeg <svlandeg@github.com>",
        "code": "def get_characters_loss(ops, docs, prediction, nr_char):\n    \n    target_ids = numpy.vstack([doc.to_utf8_array(nr_char=nr_char) for doc in docs])\n    target_ids = target_ids.reshape((-1,))\n    target = ops.asarray(to_categorical(target_ids, n_classes=256), dtype=\"f\")\n    target = target.reshape((-1, 256 * nr_char))\n    diff = prediction - target\n    loss = (diff**2).sum()\n    d_target = diff / float(prediction.shape[0])\n    return loss, d_target\n\n",
        "url": "https://github.com/explosion/spaCy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 69,
        "n_words": 42,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 112,
        "n_ast_nodes": 175,
        "n_identifiers": 22,
        "d_id": 24357,
        "documentation": {
            "docstring": "Compute a loss based on a number of characters predicted from the docs.",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 181658,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/one_hot_encoder_tests.py",
        "file_name": "one_hot_encoder_tests.py",
        "fun_name": "test_k_fold_cv",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_k_fold_cv():\n    \n    boston = load_boston()\n    clf = make_pipeline(\n        OneHotEncoder(\n            categorical_features='auto',\n            sparse=False,\n            minimum_fraction=0.05\n        ),\n        LinearRegression()\n    )\n\n    cross_val_score(clf, boston.data, boston.target, cv=KFold(n_splits=10, shuffle=True))\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 89,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 60,
        "n_ast_nodes": 92,
        "n_identifiers": 17,
        "d_id": 43446,
        "documentation": {
            "docstring": "Test OneHotEncoder with categorical_features='auto'.",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 3,
            "language": "en"
        }
    },
    {
        "id": 118583,
        "commit_id": "704eab3478cf69847825b23dabf15813a8ac9fa2",
        "repo": "streamlit",
        "path": "lib/tests/server_test_case.py",
        "file_name": "server_test_case.py",
        "fun_name": "_create_mock_app_session",
        "commit_message": "Rename and refactor `Report` machinery (#4141)\n\nThis refactor renames (almost) everything related to the outdated \"report\" concept with more precise concepts that we use throughout our code, primarily \"script run\", \"session\", and \"app\".",
        "code": "def _create_mock_app_session(*args, **kwargs):\n        \n        mock_id = mock.PropertyMock(\n            return_value=\"mock_id:%s\" % ServerTestCase._next_session_id\n        )\n        ServerTestCase._next_session_id += 1\n\n        mock_session = mock.MagicMock(AppSession, autospec=True, *args, **kwargs)\n        type(mock_session).id = mock_id\n        return mock_session\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 84,
        "n_words": 24,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 57,
        "n_ast_nodes": 93,
        "n_identifiers": 15,
        "d_id": 26306,
        "documentation": {
            "docstring": "Create a mock AppSession. Each mocked instance will have\n        its own unique ID.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 100667,
        "commit_id": "a9908b46f77dc66ac7efe7100ea0eed4b1f2b460",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_check_folder",
        "commit_message": "Alignments tool - Replace 'extract-large' with 'min-size'",
        "code": "def _check_folder(self) -> None:\n        \n        err = None\n        if not self._faces_dir:\n            err = \"ERROR: Output faces folder not provided.\"\n        elif not os.path.isdir(self._faces_dir):\n            logger.debug(\"Creating folder: '%s'\", self._faces_dir)\n            os.makedirs(self._faces_dir)\n        elif os.listdir(self._faces_dir):\n            err = f\"ERROR: Output faces folder should be empty: '{self._faces_dir}'\"\n        if err:\n            logger.error(err)\n            sys.exit(0)\n        logger.verbose(\"Creating output folder at '%s'\", self._faces_dir)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 163,
        "n_words": 48,
        "vocab_size": 34,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 90,
        "n_ast_nodes": 161,
        "n_identifiers": 15,
        "d_id": 20125,
        "documentation": {
            "docstring": " Check that the faces folder doesn't pre-exist and create. ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 230977,
        "commit_id": "1d82b8822120db088bfeb6c8eae7ec8df9703783",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/version.py",
        "file_name": "version.py",
        "fun_name": "stable_semver",
        "commit_message": "Updated distutils.Version to packaging.Version",
        "code": "def stable_semver():\n    \n    from packaging.version import Version\n\n    return Version(__version__).base_version\n",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 18,
        "n_ast_nodes": 32,
        "n_identifiers": 6,
        "d_id": 62618,
        "documentation": {
            "docstring": "\n    Get the stable portion of the semantic version string (the first three\n    numbers), without any of the trailing labels\n\n    '3.0.0rc11' -> '3.0.0'\n    ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 7805,
        "commit_id": "1e6dbeff57fc5065b97dd018b904b9907468676f",
        "repo": "ludwig",
        "path": "tests/integration_tests/test_preprocessing.py",
        "file_name": "test_preprocessing.py",
        "fun_name": "test_column_feature_type_mismatch_fill",
        "commit_message": "Treat dataset columns as object dtype during first pass of handle_missing_values (#2398)",
        "code": "def test_column_feature_type_mismatch_fill():\n    \n    cat_feat = category_feature()\n    bin_feat = binary_feature()\n    input_features = [cat_feat]\n    output_features = [bin_feat]\n    config = {\"input_features\": input_features, \"output_features\": output_features}\n\n    # Construct dataframe with int-like column representing a categorical feature\n    df = pd.DataFrame(\n        {\n            cat_feat[NAME]: pd.Series(pd.array([None] + [1] * 24, dtype=pd.Int64Dtype())),\n            bin_feat[NAME]: pd.Series([True] * 25),\n        }\n    )\n\n    # run preprocessing\n    backend = LocalTestBackend()\n    ludwig_model = LudwigModel(config, backend=backend)\n    train_ds, val_ds, test_ds, _ = ludwig_model.preprocess(dataset=df)\n\n\n@pytest.mark.parametrize(\"format\", [\"file\", \"df\"])",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"format\", [\"file\", \"df\"])",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 140,
        "n_words": 66,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 125,
        "n_ast_nodes": 230,
        "n_identifiers": 29,
        "d_id": 1273,
        "documentation": {
            "docstring": "Tests that we are able to fill missing values even in columns where the column dtype and desired feature\n    dtype do not match.",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 38308,
        "commit_id": "afe5d42d8d1d80af911ed980c2936bfe887078f6",
        "repo": "transformers",
        "path": "tests/models/bart/test_modeling_bart.py",
        "file_name": "test_modeling_bart.py",
        "fun_name": "test_xsum_summarization_same_as_fairseq",
        "commit_message": "Black preview (#17217)\n\n* Black preview\r\n\r\n* Fixup too!\r\n\r\n* Fix check copies\r\n\r\n* Use the same version as the CI\r\n\r\n* Bump black",
        "code": "def test_xsum_summarization_same_as_fairseq(self):\n        model = BartForConditionalGeneration.from_pretrained(\"facebook/bart-large-xsum\").to(torch_device)\n        tok = self.default_tokenizer\n\n        PGE_ARTICLE = \n\n        EXPECTED_SUMMARY = (\n            \"California's largest power company has begun shutting off electricity to thousands of customers in the\"\n            \" state.\"\n        )\n        dct = tok.batch_encode_plus(\n            [PGE_ARTICLE],\n            max_length=1024,\n            padding=\"max_length\",\n            truncation=True,\n            return_tensors=\"pt\",\n        ).to(torch_device)\n\n        hypotheses_batch = model.generate(\n            input_ids=dct[\"input_ids\"],\n            attention_mask=dct[\"attention_mask\"],\n            num_beams=2,\n            max_length=62,\n            min_length=11,\n            length_penalty=1.0,\n            no_repeat_ngram_size=3,\n            early_stopping=True,\n            decoder_start_token_id=model.config.eos_token_id,\n        )\n\n        decoded = tok.batch_decode(\n            hypotheses_batch,\n            skip_special_tokens=True,\n        )\n        self.assertEqual(EXPECTED_SUMMARY, decoded[0])\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 343,
        "n_words": 61,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 143,
        "n_ast_nodes": 220,
        "n_identifiers": 33,
        "d_id": 6963,
        "documentation": {
            "docstring": " PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.",
            "n_words": 47,
            "vocab_size": 40,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 26316,
        "commit_id": "41b87559118f560c223f83d405efe9b406701d17",
        "repo": "saleor",
        "path": "saleor/graphql/core/tests/test_graphql.py",
        "file_name": "test_graphql.py",
        "fun_name": "test_get_nodes_for_order_with_uuid_id",
        "commit_message": "Migrate order id from int to UUID (#9324)\n\n* Add migration to change order id from int to UUID (#9281)\r\n\r\n* Change order token to uuid\r\n\r\n* Migrate order id to uuid\r\n\r\n* Fix failing tests\r\n\r\n* Apply code review suggestions\r\n\r\n* Fix payment migration dependencies\r\n\r\n* Fix typo in order migration name\r\n\r\n* Handle old order ids for order queries\r\n\r\n* Hanlde old order ids for order mutations\r\n\r\n* Add order relation to GiftCardEvent model\r\n\r\n* Deprecate order token related queries and fields (#9295)\r\n\r\n* Deprecate order.token field\r\n\r\n* Update description of orderByToken query\r\n\r\n* Update prepare_order_search_document_value method\r\n\r\n* Update changelog\r\n\r\n* Update schema file",
        "code": "def test_get_nodes_for_order_with_uuid_id(order_list):\n    \n    # given\n    global_ids = [to_global_id(\"Order\", order.pk) for order in order_list]\n\n    # Make sure function works even if duplicated ids are provided\n    global_ids.append(to_global_id(\"Order\", order_list[0].pk))\n\n    # when\n    orders = get_nodes(global_ids, Order)\n\n    # then\n    assert orders == order_list\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 64,
        "n_words": 37,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 50,
        "n_ast_nodes": 86,
        "n_identifiers": 10,
        "d_id": 4964,
        "documentation": {
            "docstring": "Ensure that `get_nodes` returns correct nodes, when the new uuid order id\n    is used.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 20500,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/token.py",
        "file_name": "token.py",
        "fun_name": "string_to_tokentype",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def string_to_tokentype(s):\n    \n    if isinstance(s, _TokenType):\n        return s\n    if not s:\n        return Token\n    node = Token\n    for item in s.split('.'):\n        node = getattr(node, item)\n    return node\n\n\n# Map standard token types to short names, used in CSS class naming.\n# If you add a new item, please be sure to run this file to perform\n# a consistency check for duplicate values.\nSTANDARD_TYPES = {\n    Token:                         '',\n\n    Text:                          '',\n    Whitespace:                    'w',\n    Escape:                        'esc',\n    Error:                         'err',\n    Other:                         'x',\n\n    Keyword:                       'k',\n    Keyword.Constant:              'kc',\n    Keyword.Declaration:           'kd',\n    Keyword.Namespace:             'kn',\n    Keyword.Pseudo:                'kp',\n    Keyword.Reserved:              'kr',\n    Keyword.Type:                  'kt',\n\n    Name:                          'n',\n    Name.Attribute:                'na',\n    Name.Builtin:                  'nb',\n    Name.Builtin.Pseudo:           'bp',\n    Name.Class:                    'nc',\n    Name.Constant:                 'no',\n    Name.Decorator:                'nd',\n    Name.Entity:                   'ni',\n    Name.Exception:                'ne',\n    Name.Function:                 'nf',\n    Name.Function.Magic:           'fm',\n    Name.Property:                 'py',\n    Name.Label:                    'nl',\n    Name.Namespace:                'nn',\n    Name.Other:                    'nx',\n    Name.Tag:                      'nt',\n    Name.Variable:                 'nv',\n    Name.Variable.Class:           'vc',\n    Name.Variable.Global:          'vg',\n    Name.Variable.Instance:        'vi',\n    Name.Variable.Magic:           'vm',\n\n    Literal:                       'l',\n    Literal.Date:                  'ld',\n\n    String:                        's',\n    String.Affix:                  'sa',\n    String.Backtick:               'sb',\n    String.Char:                   'sc',\n    String.Delimiter:              'dl',\n    String.Doc:                    'sd',\n    String.Double:                 's2',\n    String.Escape:                 'se',\n    String.Heredoc:                'sh',\n    String.Interpol:               'si',\n    String.Other:                  'sx',\n    String.Regex:                  'sr',\n    String.Single:                 's1',\n    String.Symbol:                 'ss',\n\n    Number:                        'm',\n    Number.Bin:                    'mb',\n    Number.Float:                  'mf',\n    Number.Hex:                    'mh',\n    Number.Integer:                'mi',\n    Number.Integer.Long:           'il',\n    Number.Oct:                    'mo',\n\n    Operator:                      'o',\n    Operator.Word:                 'ow',\n\n    Punctuation:                   'p',\n\n    Comment:                       'c',\n    Comment.Hashbang:              'ch',\n    Comment.Multiline:             'cm',\n    Comment.Preproc:               'cp',\n    Comment.PreprocFile:           'cpf',\n    Comment.Single:                'c1',\n    Comment.Special:               'cs',\n\n    Generic:                       'g',\n    Generic.Deleted:               'gd',\n    Generic.Emph:                  'ge',\n    Generic.Error:                 'gr',\n    Generic.Heading:               'gh',\n    Generic.Inserted:              'gi',\n    Generic.Output:                'go',\n    Generic.Prompt:                'gp',\n    Generic.Strong:                'gs',\n    Generic.Subheading:            'gu',\n    Generic.Traceback:             'gt',\n}\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 1759,
        "n_words": 221,
        "vocab_size": 205,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 45,
        "n_ast_nodes": 841,
        "n_identifiers": 77,
        "d_id": 3398,
        "documentation": {
            "docstring": "\n    Convert a string into a token type::\n\n        >>> string_to_token('String.Double')\n        Token.Literal.String.Double\n        >>> string_to_token('Token.Literal.Number')\n        Token.Literal.Number\n        >>> string_to_token('')\n        Token\n\n    Tokens that are already tokens are returned unchanged:\n\n        >>> string_to_token(String)\n        Token.Literal.String\n    ",
            "n_words": 27,
            "vocab_size": 22,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 66909,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/payroll/doctype/payroll_entry/payroll_entry.py",
        "file_name": "payroll_entry.py",
        "fun_name": "get_emp_list",
        "commit_message": "style: format code with black",
        "code": "def get_emp_list(sal_struct, cond, end_date, payroll_payable_account):\n\treturn frappe.db.sql(\n\t\t\n\t\t% cond,\n\t\t{\n\t\t\t\"sal_struct\": tuple(sal_struct),\n\t\t\t\"from_date\": end_date,\n\t\t\t\"payroll_payable_account\": payroll_payable_account,\n\t\t},\n\t\tas_dict=True,\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 9,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 45,
        "n_ast_nodes": 70,
        "n_identifiers": 10,
        "d_id": 14375,
        "documentation": {
            "docstring": "\n\t\t\tselect\n\t\t\t\tdistinct t1.name as employee, t1.employee_name, t1.department, t1.designation\n\t\t\tfrom\n\t\t\t\t`tabEmployee` t1, `tabSalary Structure Assignment` t2\n\t\t\twhere\n\t\t\t\tt1.name = t2.employee\n\t\t\t\tand t2.docstatus = 1\n\t\t\t\tand t1.status != 'Inactive'\n\t\t%s order by t2.from_date desc\n\t\t",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 130251,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/_private/thirdparty/pathspec/pathspec.py",
        "file_name": "pathspec.py",
        "fun_name": "match_tree_files",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def match_tree_files(self, root, on_error=None, follow_links=None):\n        \n        files = util.iter_tree_files(root, on_error=on_error, follow_links=follow_links)\n        return self.match_files(files)\n\n    # Alias `match_tree_files()` as `match_tree()`.\n    match_tree = match_tree_files\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 39,
        "n_ast_nodes": 65,
        "n_identifiers": 10,
        "d_id": 29176,
        "documentation": {
            "docstring": "\n        Walks the specified root path for all files and matches them to this\n        path-spec.\n\n        *root* (:class:`str`; or :class:`pathlib.PurePath`) is the root\n        directory to search for files.\n\n        *on_error* (:class:`~collections.abc.Callable` or :data:`None`)\n        optionally is the error handler for file-system exceptions. See\n        :func:`~pathspec.util.iter_tree_files` for more information.\n\n        *follow_links* (:class:`bool` or :data:`None`) optionally is whether\n        to walk symbolic links that resolve to directories. See\n        :func:`~pathspec.util.iter_tree_files` for more information.\n\n        Returns the matched files (:class:`~collections.abc.Iterable` of\n        :class:`str`).\n        ",
            "n_words": 70,
            "vocab_size": 48,
            "n_whitespaces": 162,
            "language": "en"
        }
    },
    {
        "id": 206265,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/defaulttags.py",
        "file_name": "defaulttags.py",
        "fun_name": "cycle",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def cycle(parser, token):\n    \n    # Note: This returns the exact same node on each {% cycle name %} call;\n    # that is, the node object returned from {% cycle a b c as name %} and the\n    # one returned from {% cycle name %} are the exact same object. This\n    # shouldn't cause problems (heh), but if it does, now you know.\n    #\n    # Ugly hack warning: This stuffs the named template dict into parser so\n    # that names are only unique within each template (as opposed to using\n    # a global variable, which would make cycle names have to be unique across\n    # *all* templates.\n    #\n    # It keeps the last node in the parser to be able to reset it with\n    # {% resetcycle %}.\n\n    args = token.split_contents()\n\n    if len(args) < 2:\n        raise TemplateSyntaxError(\"'cycle' tag requires at least two arguments\")\n\n    if len(args) == 2:\n        # {% cycle foo %} case.\n        name = args[1]\n        if not hasattr(parser, \"_named_cycle_nodes\"):\n            raise TemplateSyntaxError(\n                \"No named cycles in template. '%s' is not defined\" % name\n            )\n        if name not in parser._named_cycle_nodes:\n            raise TemplateSyntaxError(\"Named cycle '%s' does not exist\" % name)\n        return parser._named_cycle_nodes[name]\n\n    as_form = False\n\n    if len(args) > 4:\n        # {% cycle ... as foo [silent] %} case.\n        if args[-3] == \"as\":\n            if args[-1] != \"silent\":\n                raise TemplateSyntaxError(\n                    \"Only 'silent' flag is allowed after cycle's name, not '%s'.\"\n                    % args[-1]\n                )\n            as_form = True\n            silent = True\n            args = args[:-1]\n        elif args[-2] == \"as\":\n            as_form = True\n            silent = False\n\n    if as_form:\n        name = args[-1]\n        values = [parser.compile_filter(arg) for arg in args[1:-2]]\n        node = CycleNode(values, name, silent=silent)\n        if not hasattr(parser, \"_named_cycle_nodes\"):\n            parser._named_cycle_nodes = {}\n        parser._named_cycle_nodes[name] = node\n    else:\n        values = [parser.compile_filter(arg) for arg in args[1:]]\n        node = CycleNode(values)\n    parser._last_cycle_node = node\n    return node\n\n\n@register.tag",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 661,
        "n_words": 291,
        "vocab_size": 155,
        "complexity": 13,
        "nloc": 39,
        "token_counts": 247,
        "n_ast_nodes": 428,
        "n_identifiers": 20,
        "d_id": 51453,
        "documentation": {
            "docstring": "\n    Cycle among the given strings each time this tag is encountered.\n\n    Within a loop, cycles among the given strings each time through\n    the loop::\n\n        {% for o in some_list %}\n            <tr class=\"{% cycle 'row1' 'row2' %}\">\n                ...\n            </tr>\n        {% endfor %}\n\n    Outside of a loop, give the values a unique name the first time you call\n    it, then use that name each successive time through::\n\n            <tr class=\"{% cycle 'row1' 'row2' 'row3' as rowcolors %}\">...</tr>\n            <tr class=\"{% cycle rowcolors %}\">...</tr>\n            <tr class=\"{% cycle rowcolors %}\">...</tr>\n\n    You can use any number of values, separated by spaces. Commas can also\n    be used to separate values; if a comma is used, the cycle values are\n    interpreted as literal strings.\n\n    The optional flag \"silent\" can be used to prevent the cycle declaration\n    from returning any value::\n\n        {% for o in some_list %}\n            {% cycle 'row1' 'row2' as rowcolors silent %}\n            <tr class=\"{{ rowcolors }}\">{% include \"subtemplate.html \" %}</tr>\n        {% endfor %}\n    ",
            "n_words": 156,
            "vocab_size": 89,
            "n_whitespaces": 310,
            "language": "en"
        }
    },
    {
        "id": 217342,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/filecmp.py",
        "file_name": "filecmp.py",
        "fun_name": "cmpfiles",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def cmpfiles(a, b, common, shallow=True):\n    \n    res = ([], [], [])\n    for x in common:\n        ax = os.path.join(a, x)\n        bx = os.path.join(b, x)\n        res[_cmp(ax, bx, shallow)].append(x)\n    return res\n\n\n# Compare two files.\n# Return:\n#       0 for equal\n#       1 for different\n#       2 for funny cases (can't stat, etc.)\n#",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 95,
        "n_words": 50,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 73,
        "n_ast_nodes": 115,
        "n_identifiers": 14,
        "d_id": 54725,
        "documentation": {
            "docstring": "Compare common files in two directories.\n\n    a, b -- directory names\n    common -- list of file names found in both directories\n    shallow -- if true, do comparison based solely on stat() information\n\n    Returns a tuple of three lists:\n      files that compare equal\n      files that are different\n      filenames that aren't regular files.\n\n    ",
            "n_words": 51,
            "vocab_size": 41,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 197279,
        "commit_id": "f3b08522003f40868afb20304fc0fa5b16d13f6a",
        "repo": "sympy",
        "path": "sympy/utilities/iterables.py",
        "file_name": "iterables.py",
        "fun_name": "_set_partitions",
        "commit_message": "Cleanup documentation",
        "code": "def _set_partitions(n):\n    \n    p = [0]*n\n    q = [0]*n\n    nc = 1\n    yield nc, q\n    while nc != n:\n        m = n\n        while 1:\n            m -= 1\n            i = q[m]\n            if p[i] != 1:\n                break\n            q[m] = 0\n        i += 1\n        q[m] = i\n        m += 1\n        nc += m - n\n        p[0] += n - m\n        if i == nc:\n            p[nc] = 0\n            nc += 1\n        p[i - 1] -= 1\n        p[i] += 1\n        yield nc, q\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 253,
        "n_words": 77,
        "vocab_size": 31,
        "complexity": 5,
        "nloc": 24,
        "token_counts": 119,
        "n_ast_nodes": 191,
        "n_identifiers": 7,
        "d_id": 48426,
        "documentation": {
            "docstring": "Cycle through all partions of n elements, yielding the\n    current number of partitions, ``m``, and a mutable list, ``q``\n    such that ``element[i]`` is in part ``q[i]`` of the partition.\n\n    NOTE: ``q`` is modified in place and generally should not be changed\n    between function calls.\n\n    Examples\n    ========\n\n    >>> from sympy.utilities.iterables import _set_partitions, _partition\n    >>> for m, q in _set_partitions(3):\n    ...     print('%s %s %s' % (m, q, _partition('abc', q, m)))\n    1 [0, 0, 0] [['a', 'b', 'c']]\n    2 [0, 0, 1] [['a', 'b'], ['c']]\n    2 [0, 1, 0] [['a', 'c'], ['b']]\n    2 [0, 1, 1] [['a'], ['b', 'c']]\n    3 [0, 1, 2] [['a'], ['b'], ['c']]\n\n    Notes\n    =====\n\n    This algorithm is similar to, and solves the same problem as,\n    Algorithm 7.2.1.5H, from volume 4A of Knuth's The Art of Computer\n    Programming.  Knuth uses the term \"restricted growth string\" where\n    this code refers to a \"partition vector\". In each case, the meaning is\n    the same: the value in the ith element of the vector specifies to\n    which part the ith set element is to be assigned.\n\n    At the lowest level, this code implements an n-digit big-endian\n    counter (stored in the array q) which is incremented (with carries) to\n    get the next partition in the sequence.  A special twist is that a\n    digit is constrained to be at most one greater than the maximum of all\n    the digits to the left of it.  The array p maintains this maximum, so\n    that the code can efficiently decide when a digit can be incremented\n    in place or whether it needs to be reset to 0 and trigger a carry to\n    the next digit.  The enumeration starts with all the digits 0 (which\n    corresponds to all the set elements being assigned to the same 0th\n    part), and ends with 0123...n, which corresponds to each set element\n    being assigned to a different, singleton, part.\n\n    This routine was rewritten to use 0-based lists while trying to\n    preserve the beauty and efficiency of the original algorithm.\n\n    References\n    ==========\n\n    .. [1] Nijenhuis, Albert and Wilf, Herbert. (1978) Combinatorial Algorithms,\n        2nd Ed, p 91, algorithm \"nexequ\". Available online from\n        https://www.math.upenn.edu/~wilf/website/CombAlgDownld.html (viewed\n        November 17, 2012).\n\n    ",
            "n_words": 351,
            "vocab_size": 221,
            "n_whitespaces": 497,
            "language": "en"
        }
    },
    {
        "id": 221074,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/base64.py",
        "file_name": "base64.py",
        "fun_name": "standard_b64decode",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def standard_b64decode(s):\n    \n    return b64decode(s)\n\n\n_urlsafe_encode_translation = bytes.maketrans(b'+/', b'-_')\n_urlsafe_decode_translation = bytes.maketrans(b'-_', b'+/')\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 16,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 11,
        "n_ast_nodes": 59,
        "n_identifiers": 7,
        "d_id": 56186,
        "documentation": {
            "docstring": "Decode bytes encoded with the standard Base64 alphabet.\n\n    Argument s is a bytes-like object or ASCII string to decode.  The result\n    is returned as a bytes object.  A binascii.Error is raised if the input\n    is incorrectly padded.  Characters that are not in the standard alphabet\n    are discarded prior to the padding check.\n    ",
            "n_words": 52,
            "vocab_size": 41,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 297632,
        "commit_id": "3884e16b46f438e4a13bcab4fe0df3b2188de767",
        "repo": "core",
        "path": "tests/common.py",
        "file_name": "common.py",
        "fun_name": "__repr__",
        "commit_message": "Add tests.common.ANY (#84240)",
        "code": "def __repr__(self):\n        \n        if self._other is _SENTINEL:\n            return \"<ANY>\"\n        return repr(self._other)\n\n\nANY = _HA_ANY()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 44,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 22,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 96599,
        "documentation": {
            "docstring": "Return repr() other to not show up in pytest quality diffs.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 118799,
        "commit_id": "2a0ec52386e6d1594aa5cfe39bef2bfb89a59416",
        "repo": "streamlit",
        "path": "lib/streamlit/script_runner.py",
        "file_name": "script_runner.py",
        "fun_name": "_set_execing_flag",
        "commit_message": "Saner \"execution control request\" handling (#4383)\n\n### Background\r\n\r\nCurrently, a `ForwardMsg` enqueued from an `st.foo()` call results in a twisty path:\r\n\r\n1. `st.foo()` retrieves the current `ScriptRunContext` and calls its `enqueue` function\r\n1. `ScriptRunContext.enqueue` calls the `AppSession.enqueue` callback\r\n2. `AppSession.enqueue` retrieves the current `ScriptRunner` and calls its `maybe_handle_execution_control_request` function\r\n3. `ScriptRunner.maybe_handle_execution_control_request` optionally interrupts its own script's execution to respond to a STOP or RERUN request.\r\n\r\n(In other words, the message results in this call chain: ScriptRunContext -> AppSession -> ScriptRunner.)\r\n\r\nThis is weird for a couple reasons:\r\n1. `ScriptRunner.maybe_handle_execution_control_request` should be private. The circumstances in which it's legal to be called are very specific, and `AppSession.enqueue` currently has some ScriptRunner \"business logic\" inside it.\r\n2. The call chain should really be ScriptRunContext -> ScriptRunner -> AppSession. (AppSession creates ScriptRunner which in turn creates ScriptRunContext. After creation, AppSession should ideally never have to communicate directly with its ScriptRunner - especially in a future where there may be multiple ScriptRunners attached to a single AppSession.)\r\n\r\n### Resolution\r\n\r\nWith this PR, `maybe_handle_execution_control_request` is a private method, and an enqueued `ForwardMsg` now \"bubbles up\" from ScriptRunContext -> ScriptRunner -> AppSession. AppSession no longer knows about execution control requests; they are handled internally by ScriptRunner.\r\n\r\n(The salient change is that ScriptRunner gets a new `_enqueue` function that is called by `ScriptRunContext.enqueue`, rather than `ScriptRunContext.enqueue` calling `AppSession.enqueue` directly. The execution control request handling happens inside this new `ScriptRunner.enqueue` function, which then calls up to `AppSession.enqueue`.)",
        "code": "def _set_execing_flag(self):\n        \n        if self._execing:\n            raise RuntimeError(\"Nested set_execing_flag call\")\n        self._execing = True\n        try:\n            yield\n        finally:\n            self._execing = False\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 85,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 31,
        "n_ast_nodes": 58,
        "n_identifiers": 4,
        "d_id": 26433,
        "documentation": {
            "docstring": "A context for setting the ScriptRunner._execing flag.\n\n        Used by _maybe_handle_execution_control_request to ensure that\n        we only handle requests while we're inside an exec() call\n        ",
            "n_words": 23,
            "vocab_size": 23,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 204917,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/schema.py",
        "file_name": "schema.py",
        "fun_name": "column_sql",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def column_sql(self, model, field, include_default=False):\n        \n        # Get the column's type and use that as the basis of the SQL.\n        db_params = field.db_parameters(connection=self.connection)\n        column_db_type = db_params[\"type\"]\n        # Check for fields that aren't actually columns (e.g. M2M).\n        if column_db_type is None:\n            return None, None\n        params = []\n        return (\n            \" \".join(\n                # This appends to the params being returned.\n                self._iter_column_sql(\n                    column_db_type, params, model, field, include_default\n                )\n            ),\n            params,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 238,
        "n_words": 67,
        "vocab_size": 52,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 70,
        "n_ast_nodes": 111,
        "n_identifiers": 12,
        "d_id": 50974,
        "documentation": {
            "docstring": "\n        Return the column definition for a field. The field must already have\n        had set_attributes_from_name() called.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 100668,
        "commit_id": "a9908b46f77dc66ac7efe7100ea0eed4b1f2b460",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_set_output",
        "commit_message": "Alignments tool - Replace 'extract-large' with 'min-size'",
        "code": "def _set_output(self):\n        \n        now = datetime.now().strftime(\"%Y%m%d_%H%M%S\")\n        folder_name = f\"drawn_landmarks_{now}\"\n        if self._frames.is_video:\n            dest_folder = os.path.dirname(self._frames.folder)\n        else:\n            dest_folder = self._frames.folder\n        output_folder = os.path.join(dest_folder, folder_name)\n        logger.debug(\"Creating folder: '%s'\", output_folder)\n        os.makedirs(output_folder)\n        return output_folder\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 113,
        "n_words": 28,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 80,
        "n_ast_nodes": 139,
        "n_identifiers": 18,
        "d_id": 20126,
        "documentation": {
            "docstring": " Set the output folder path.\n\n        If annotating a folder of frames, output will be placed in a sub folder within the frames\n        folder. If annotating a video, output will be a folder next to the original video.\n\n        Returns\n        -------\n        str\n            Full path to the output folder\n\n        ",
            "n_words": 46,
            "vocab_size": 28,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 137985,
        "commit_id": "8e680c483ce326cefc62e44f68ab1a6948b1c3d2",
        "repo": "ray",
        "path": "rllib/tests/backward_compat/test_gym_env_apis.py",
        "file_name": "test_gym_env_apis.py",
        "fun_name": "test_gymnasium_old_api_but_wrapped",
        "commit_message": "[RLlib] gymnasium support (new `Env.reset()/step()/seed()/render()` APIs). (#28369)",
        "code": "def test_gymnasium_old_api_but_wrapped(self):\n        \n\n        from gymnasium.wrappers import EnvCompatibility\n\n        register_env(\n            \"test\",\n            lambda env_ctx: EnvCompatibility(GymnasiumOldAPI(env_ctx)),\n        )\n\n        algo = (\n            PPOConfig()\n            .environment(env=\"test\")\n            .rollouts(num_envs_per_worker=2, num_rollout_workers=2)\n            .build()\n        )\n        algo.train()\n        algo.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 145,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 67,
        "n_ast_nodes": 115,
        "n_identifiers": 18,
        "d_id": 31268,
        "documentation": {
            "docstring": "Tests a gymnasium Env that uses the old API, but is correctly wrapped.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 261492,
        "commit_id": "b1807ff8ead319a08294beeaae90c3f03b2bb8ac",
        "repo": "scikit-learn",
        "path": "sklearn/ensemble/tests/test_stacking.py",
        "file_name": "test_stacking.py",
        "fun_name": "test_stacking_classifier_base_regressor",
        "commit_message": "ENH StackingClassifier allows regressors in its first layer (#24538)\n\nCo-authored-by: Tom Dupré la Tour <tom.duprelatour.10@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_stacking_classifier_base_regressor():\n    \n    X_train, X_test, y_train, y_test = train_test_split(\n        scale(X_iris), y_iris, stratify=y_iris, random_state=42\n    )\n    clf = StackingClassifier(estimators=[(\"ridge\", Ridge())])\n    clf.fit(X_train, y_train)\n    clf.predict(X_test)\n    clf.predict_proba(X_test)\n    assert clf.score(X_test, y_test) > 0.8\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 57,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 79,
        "n_ast_nodes": 121,
        "n_identifiers": 19,
        "d_id": 76836,
        "documentation": {
            "docstring": "Check that a regressor can be used as the first layer in `StackingClassifier`.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 253414,
        "commit_id": "8c2428c9d355ca5fbc3dd90e9820ceb1cc795837",
        "repo": "mitmproxy",
        "path": "examples/contrib/webscanner_helper/watchdog.py",
        "file_name": "watchdog.py",
        "fun_name": "error",
        "commit_message": "[autofix.ci] apply automated fixes",
        "code": "def error(self, flow):\n        \n        if (\n            self.not_in_timeout(self.last_trigger, self.timeout)\n            and flow.error is not None\n            and not isinstance(flow.error, HttpSyntaxException)\n        ):\n\n            self.last_trigger = time.time()\n            logger.error(f\"Watchdog triggered! Cause: {flow}\")\n            self.error_event.set()\n\n            # save the request which might have caused the problem\n            if flow.request:\n                with (self.flow_dir / f\"{datetime.utcnow().isoformat()}.curl\").open(\n                    \"w\"\n                ) as f:\n                    f.write(curl_command(flow))\n                with (self.flow_dir / f\"{datetime.utcnow().isoformat()}.raw\").open(\n                    \"wb\"\n                ) as f:\n                    f.write(raw(flow))\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 300,
        "n_words": 55,
        "vocab_size": 45,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 121,
        "n_ast_nodes": 246,
        "n_identifiers": 22,
        "d_id": 74071,
        "documentation": {
            "docstring": "Checks if the watchdog will be triggered.\n\n        Only triggers watchdog for timeouts after last reset and if flow.error is set (shows that error is a server\n        error). Ignores HttpSyntaxException Errors since this can be triggered on purpose by web application scanner.\n\n        Args:\n            flow: mitmproxy.http.flow\n        ",
            "n_words": 44,
            "vocab_size": 40,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 314495,
        "commit_id": "10dc38e0ec27f7bef990ee431459342f9c3c52b4",
        "repo": "core",
        "path": "homeassistant/components/velux/cover.py",
        "file_name": "cover.py",
        "fun_name": "device_class",
        "commit_message": "Adjust CoverEntity property type hints in components (#73943)\n\n* Adjust CoverEntity property type hints in components\r\n\r\n* Revert changes to rflink\r\n\r\n* Revert changes to wilight",
        "code": "def device_class(self) -> CoverDeviceClass:\n        \n        if isinstance(self.node, Awning):\n            return CoverDeviceClass.AWNING\n        if isinstance(self.node, Blind):\n            return CoverDeviceClass.BLIND\n        if isinstance(self.node, GarageDoor):\n            return CoverDeviceClass.GARAGE\n        if isinstance(self.node, Gate):\n            return CoverDeviceClass.GATE\n        if isinstance(self.node, RollerShutter):\n            return CoverDeviceClass.SHUTTER\n        if isinstance(self.node, Window):\n            return CoverDeviceClass.WINDOW\n        return CoverDeviceClass.WINDOW\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 158,
        "n_words": 36,
        "vocab_size": 19,
        "complexity": 7,
        "nloc": 15,
        "token_counts": 96,
        "n_ast_nodes": 148,
        "n_identifiers": 17,
        "d_id": 113101,
        "documentation": {
            "docstring": "Define this cover as either awning, blind, garage, gate, shutter or window.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 42516,
        "commit_id": "ea006df9885bd1e5f439cd05359d047d83276b73",
        "repo": "nltk",
        "path": "nltk/tokenize/sonority_sequencing.py",
        "file_name": "sonority_sequencing.py",
        "fun_name": "validate_syllables",
        "commit_message": "Greatly improve SyllableTokenizer time performance on some edge cases\n\nMainly when tokenizing numbers",
        "code": "def validate_syllables(self, syllable_list):\n        \n        valid_syllables = []\n        front = \"\"\n        vowel_pattern = re.compile(\"|\".join(self.vowels))\n        for i, syllable in enumerate(syllable_list):\n            if syllable in punctuation:\n                valid_syllables.append(syllable)\n                continue\n            if not vowel_pattern.search(syllable):\n                if len(valid_syllables) == 0:\n                    front += syllable\n                else:\n                    valid_syllables = valid_syllables[:-1] + [\n                        valid_syllables[-1] + syllable\n                    ]\n            else:\n                if len(valid_syllables) == 0:\n                    valid_syllables.append(front + syllable)\n                else:\n                    valid_syllables.append(syllable)\n\n        return valid_syllables\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 338,
        "n_words": 55,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 120,
        "n_ast_nodes": 202,
        "n_identifiers": 17,
        "d_id": 7584,
        "documentation": {
            "docstring": "\n        Ensures each syllable has at least one vowel.\n        If the following syllable doesn't have vowel, add it to the current one.\n\n        :param syllable_list: Single word or token broken up into syllables.\n        :type syllable_list: list(str)\n        :return: Single word or token broken up into syllables\n                 (with added syllables if necessary)\n        :rtype: list(str)\n        ",
            "n_words": 50,
            "vocab_size": 38,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 259742,
        "commit_id": "8d7935827d01d95239710c9c519bb1905f46b645",
        "repo": "scikit-learn",
        "path": "sklearn/utils/tests/test_validation.py",
        "file_name": "test_validation.py",
        "fun_name": "test_check_dataframe_with_only_boolean",
        "commit_message": "ENH check_array returns numeric array w/ mixed typed dataframes (#22237)\n\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_check_dataframe_with_only_boolean():\n    \n    pd = importorskip(\"pandas\", minversion=\"1.0\")\n    df = pd.DataFrame({\"bool\": pd.Series([True, False, True], dtype=\"boolean\")})\n\n    array = check_array(df, dtype=None)\n    assert array.dtype == np.float64\n    assert_array_equal(array, [[True], [False], [True]])\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 43,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 78,
        "n_ast_nodes": 126,
        "n_identifiers": 13,
        "d_id": 75889,
        "documentation": {
            "docstring": "Check that dataframe with boolean return a float array with dtype=None",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 67755,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/doctype/stock_entry/stock_entry.py",
        "file_name": "stock_entry.py",
        "fun_name": "get_used_alternative_items",
        "commit_message": "style: format code with black",
        "code": "def get_used_alternative_items(purchase_order=None, work_order=None):\n\tcond = \"\"\n\n\tif purchase_order:\n\t\tcond = \"and ste.purpose = 'Send to Subcontractor' and ste.purchase_order = '{0}'\".format(\n\t\t\tpurchase_order\n\t\t)\n\telif work_order:\n\t\tcond = \"and ste.purpose = 'Material Transfer for Manufacture' and ste.work_order = '{0}'\".format(\n\t\t\twork_order\n\t\t)\n\n\tif not cond:\n\t\treturn {}\n\n\tused_alternative_items = {}\n\tdata = frappe.db.sql(\n\t\t.format(\n\t\t\tcond\n\t\t),\n\t\tas_dict=1,\n\t)\n\n\tfor d in data:\n\t\tused_alternative_items[d.original_item] = d\n\n\treturn used_alternative_items\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 42,
        "n_words": 64,
        "vocab_size": 40,
        "complexity": 5,
        "nloc": 28,
        "token_counts": 82,
        "n_ast_nodes": 137,
        "n_identifiers": 13,
        "d_id": 14612,
        "documentation": {
            "docstring": " select sted.original_item, sted.uom, sted.conversion_factor,\n\t\t\tsted.item_code, sted.item_name, sted.conversion_factor,sted.stock_uom, sted.description\n\t\tfrom\n\t\t\t`tabStock Entry` ste, `tabStock Entry Detail` sted\n\t\twhere\n\t\t\tsted.parent = ste.name and ste.docstatus = 1 and sted.original_item !=  sted.item_code\n\t\t\t{0} ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 85409,
        "commit_id": "4319707cbd0d7783596fd4a4b7e707d55f97f629",
        "repo": "sentry",
        "path": "tests/sentry/apidocs/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "generate_schema",
        "commit_message": "feat(apidocs): Added the framework for schema tests (#38422)\n\nThe functions shown, gives us a way to test any changes we make to SentrySchema",
        "code": "def generate_schema(route, viewset=None, view=None, view_function=None, patterns=None):\n    \n    from django.urls import path\n    from drf_spectacular.generators import SchemaGenerator\n    from rest_framework import routers\n    from rest_framework.viewsets import ViewSetMixin\n\n    if viewset:\n        assert issubclass(viewset, ViewSetMixin)\n        router = routers.SimpleRouter()\n        router.register(route, viewset, basename=route)\n        patterns = router.urls\n    elif view:\n        patterns = [path(route, view.as_view())]\n    elif view_function:\n        patterns = [path(route, view_function)]\n    else:\n        assert route is None and isinstance(patterns, list)\n\n    generator = SchemaGenerator(patterns=patterns)\n    schema = generator.get_schema(request=None, public=True)\n    validate_schema(schema)  # make sure generated schemas are always valid\n    return schema\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 163,
        "n_words": 74,
        "vocab_size": 57,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 149,
        "n_ast_nodes": 231,
        "n_identifiers": 30,
        "d_id": 17986,
        "documentation": {
            "docstring": "\n    Taken from drf_spectacular tests\n    https://github.com/tfranzel/drf-spectacular/blob/590a2f7f053fbe83446aa453cb4d4a3025410609/tests/__init__.py#L64\n    ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 120213,
        "commit_id": "3f9e45e0c5b035de27b14588cd3b4cfd5f3c1f04",
        "repo": "jax",
        "path": "tests/mesh_utils_test.py",
        "file_name": "mesh_utils_test.py",
        "fun_name": "mock_4x4x4_devices",
        "commit_message": "[mesh_utils] Support creating device meshes for hybrid networks\n\nAlso makes some NFCs to other mesh_utils code.\n\nPiperOrigin-RevId: 442581767",
        "code": "def mock_4x4x4_devices(one_device_per_chip):\n  \n  return mock_devices(4, 4, 4, 'TPU v4', one_device_per_chip)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 11,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 19,
        "n_ast_nodes": 31,
        "n_identifiers": 3,
        "d_id": 26800,
        "documentation": {
            "docstring": "Hard-coded reproduction of jax.devices() output on 4x4x4.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 266714,
        "commit_id": "a06fa496d3f837cca3c437ab6e9858525633d147",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/classification/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "categorize_changes",
        "commit_message": "ansible-test - Code cleanup and refactoring. (#77169)\n\n* Remove unnecessary PyCharm ignores.\r\n* Ignore intentional undefined attribute usage.\r\n* Add missing type hints. Fix existing type hints.\r\n* Fix docstrings and comments.\r\n* Use function to register completion handler.\r\n* Pass strings to display functions.\r\n* Fix CompositeAction handling of dest argument.\r\n* Use consistent types in expressions/assignments.\r\n* Use custom function to keep linters happy.\r\n* Add missing raise for custom exception.\r\n* Clean up key/value type handling in cloud plugins.\r\n* Use dataclass instead of dict for results.\r\n* Add custom type_guard function to check lists.\r\n* Ignore return type that can't be checked (yet).\r\n* Avoid changing types on local variables.",
        "code": "def categorize_changes(args, paths, verbose_command=None):  # type: (TestConfig, t.List[str], t.Optional[str]) -> ChangeDescription\n    \n    mapper = PathMapper(args)\n\n    commands = {\n        'sanity': set(),\n        'units': set(),\n        'integration': set(),\n        'windows-integration': set(),\n        'network-integration': set(),\n    }  # type: t.Dict[str, t.Set[str]]\n\n    focused_commands = collections.defaultdict(set)\n\n    deleted_paths = set()  # type: t.Set[str]\n    original_paths = set()  # type: t.Set[str]\n    additional_paths = set()  # type: t.Set[str]\n    no_integration_paths = set()  # type: t.Set[str]\n\n    for path in paths:\n        if not os.path.exists(path):\n            deleted_paths.add(path)\n            continue\n\n        original_paths.add(path)\n\n        dependent_paths = mapper.get_dependent_paths(path)\n\n        if not dependent_paths:\n            continue\n\n        display.info('Expanded \"%s\" to %d dependent file(s):' % (path, len(dependent_paths)), verbosity=2)\n\n        for dependent_path in dependent_paths:\n            display.info(dependent_path, verbosity=2)\n            additional_paths.add(dependent_path)\n\n    additional_paths -= set(paths)  # don't count changed paths as additional paths\n\n    if additional_paths:\n        display.info('Expanded %d changed file(s) into %d additional dependent file(s).' % (len(paths), len(additional_paths)))\n        paths = sorted(set(paths) | additional_paths)\n\n    display.info('Mapping %d changed file(s) to tests.' % len(paths))\n\n    none_count = 0\n\n    for path in paths:\n        tests = mapper.classify(path)\n\n        if tests is None:\n            focused_target = False\n\n            display.info('%s -> all' % path, verbosity=1)\n            tests = all_tests(args)  # not categorized, run all tests\n            display.warning('Path not categorized: %s' % path)\n        else:\n            focused_target = bool(tests.pop(FOCUSED_TARGET, None)) and path in original_paths\n\n            tests = dict((key, value) for key, value in tests.items() if value)\n\n            if focused_target and not any('integration' in command for command in tests):\n                no_integration_paths.add(path)  # path triggers no integration tests\n\n            if verbose_command:\n                result = '%s: %s' % (verbose_command, tests.get(verbose_command) or 'none')\n\n                # identify targeted integration tests (those which only target a single integration command)\n                if 'integration' in verbose_command and tests.get(verbose_command):\n                    if not any('integration' in command for command in tests if command != verbose_command):\n                        if focused_target:\n                            result += ' (focused)'\n\n                        result += ' (targeted)'\n            else:\n                result = '%s' % tests\n\n            if not tests.get(verbose_command):\n                # minimize excessive output from potentially thousands of files which do not trigger tests\n                none_count += 1\n                verbosity = 2\n            else:\n                verbosity = 1\n\n            if args.verbosity >= verbosity:\n                display.info('%s -> %s' % (path, result), verbosity=1)\n\n        for command, target in tests.items():\n            commands[command].add(target)\n\n            if focused_target:\n                focused_commands[command].add(target)\n\n    if none_count > 0 and args.verbosity < 2:\n        display.notice('Omitted %d file(s) that triggered no tests.' % none_count)\n\n    for command, targets in commands.items():\n        targets.discard('none')\n\n        if any(target == 'all' for target in targets):\n            commands[command] = {'all'}\n\n    sorted_commands = dict((c, sorted(targets)) for c, targets in commands.items() if targets)\n    focused_commands = dict((c, sorted(targets)) for c, targets in focused_commands.items())\n\n    for command, targets in sorted_commands.items():\n        if targets == ['all']:\n            sorted_commands[command] = []  # changes require testing all targets, do not filter targets\n\n    changes = ChangeDescription()\n    changes.command = verbose_command\n    changes.changed_paths = sorted(original_paths)\n    changes.deleted_paths = sorted(deleted_paths)\n    changes.regular_command_targets = sorted_commands\n    changes.focused_command_targets = focused_commands\n    changes.no_integration_paths = sorted(no_integration_paths)\n\n    return changes\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1141,
        "n_words": 412,
        "vocab_size": 206,
        "complexity": 36,
        "nloc": 83,
        "token_counts": 637,
        "n_ast_nodes": 1067,
        "n_identifiers": 55,
        "d_id": 78529,
        "documentation": {
            "docstring": "Categorize the given list of changed paths and return a description of the changes.",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 200902,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/aggregation/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_grouped_annotation_in_group_by",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_grouped_annotation_in_group_by(self):\n        \n        qs = (\n            Book.objects.annotate(xprice=F(\"price\"))\n            .filter(rating=4.0)\n            .values(\"rating\", \"xprice\")\n            .annotate(count=Count(\"publisher_id\", distinct=True))\n            .values(\"count\", \"rating\")\n            .order_by(\"count\")\n        )\n        self.assertEqual(\n            list(qs),\n            [\n                {\"rating\": 4.0, \"count\": 1},\n                {\"rating\": 4.0, \"count\": 2},\n            ],\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 192,
        "n_words": 28,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 102,
        "n_ast_nodes": 168,
        "n_identifiers": 17,
        "d_id": 49825,
        "documentation": {
            "docstring": "\n        An annotation included in values() before an aggregate should be\n        included in the group by clause.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 203510,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/templatetags/log.py",
        "file_name": "log.py",
        "fun_name": "get_admin_log",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_admin_log(parser, token):\n    \n    tokens = token.contents.split()\n    if len(tokens) < 4:\n        raise template.TemplateSyntaxError(\n            \"'get_admin_log' statements require two arguments\"\n        )\n    if not tokens[1].isdigit():\n        raise template.TemplateSyntaxError(\n            \"First argument to 'get_admin_log' must be an integer\"\n        )\n    if tokens[2] != \"as\":\n        raise template.TemplateSyntaxError(\n            \"Second argument to 'get_admin_log' must be 'as'\"\n        )\n    if len(tokens) > 4:\n        if tokens[4] != \"for_user\":\n            raise template.TemplateSyntaxError(\n                \"Fourth argument to 'get_admin_log' must be 'for_user'\"\n            )\n    return AdminLogNode(\n        limit=tokens[1],\n        varname=tokens[3],\n        user=(tokens[5] if len(tokens) > 5 else None),\n    )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 240,
        "n_words": 76,
        "vocab_size": 46,
        "complexity": 7,
        "nloc": 24,
        "token_counts": 124,
        "n_ast_nodes": 204,
        "n_identifiers": 14,
        "d_id": 50415,
        "documentation": {
            "docstring": "\n    Populate a template variable with the admin log for the given criteria.\n\n    Usage::\n\n        {% get_admin_log [limit] as [varname] for_user [context_var_containing_user_obj] %}\n\n    Examples::\n\n        {% get_admin_log 10 as admin_log for_user 23 %}\n        {% get_admin_log 10 as admin_log for_user user %}\n        {% get_admin_log 10 as admin_log %}\n\n    Note that ``context_var_containing_user_obj`` can be a hard-coded integer\n    (user ID) or the name of a template context variable containing the user\n    object whose ID you want.\n    ",
            "n_words": 70,
            "vocab_size": 44,
            "n_whitespaces": 120,
            "language": "en"
        }
    },
    {
        "id": 101616,
        "commit_id": "98d01760e469fd2108eed8d0b0a1ba6297c3177c",
        "repo": "faceswap",
        "path": "tools/sort/sort_methods.py",
        "file_name": "sort_methods.py",
        "fun_name": "binned",
        "commit_message": "Overhaul sort:\n  - Standardize image data reading and writing\n  - Optimize loading (just one pass required)\n  - Make all sort groups binnable (to greater or lesser results)\n  - Add sort by pitch\n  - Deprecate multiple options\n  - linting, docs + locales",
        "code": "def binned(self) -> List[List[str]]:\n        \n        if not self._binned:\n            self._binned = self._binning()\n            logger.debug({f\"bin_{idx}\": len(bin_) for idx, bin_ in enumerate(self._binned)})\n        return self._binned\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 62,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 58,
        "n_ast_nodes": 98,
        "n_identifiers": 12,
        "d_id": 21024,
        "documentation": {
            "docstring": " list: List of bins (list) containing the filenames belonging to the bin. The binning\n        process is called when this property is first accessed",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 259364,
        "commit_id": "e5736afb316038c43301d2c53ce39f9a89b64495",
        "repo": "scikit-learn",
        "path": "sklearn/ensemble/_base.py",
        "file_name": "_base.py",
        "fun_name": "_make_estimator",
        "commit_message": "API Deprecate max_feature=`auto` for tree classes (#22476)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def _make_estimator(self, append=True, random_state=None):\n        \n        estimator = clone(self.base_estimator_)\n        estimator.set_params(**{p: getattr(self, p) for p in self.estimator_params})\n\n        # TODO: Remove in v1.2\n        # criterion \"mse\" and \"mae\" would cause warnings in every call to\n        # DecisionTreeRegressor.fit(..)\n        if isinstance(estimator, (DecisionTreeRegressor, ExtraTreeRegressor)):\n            if getattr(estimator, \"criterion\", None) == \"mse\":\n                estimator.set_params(criterion=\"squared_error\")\n            elif getattr(estimator, \"criterion\", None) == \"mae\":\n                estimator.set_params(criterion=\"absolute_error\")\n\n        # TODO(1.3): Remove\n        # max_features = 'auto' would cause warnings in every call to\n        # Tree.fit(..)\n        if isinstance(estimator, BaseDecisionTree):\n            if getattr(estimator, \"max_features\", None) == \"auto\":\n                if isinstance(estimator, DecisionTreeClassifier):\n                    estimator.set_params(max_features=\"sqrt\")\n                elif isinstance(estimator, DecisionTreeRegressor):\n                    estimator.set_params(max_features=1.0)\n\n        if random_state is not None:\n            _set_random_states(estimator, random_state)\n\n        if append:\n            self.estimators_.append(estimator)\n\n        return estimator\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 347,
        "n_words": 96,
        "vocab_size": 62,
        "complexity": 11,
        "nloc": 19,
        "token_counts": 175,
        "n_ast_nodes": 288,
        "n_identifiers": 20,
        "d_id": 75735,
        "documentation": {
            "docstring": "Make and configure a copy of the `base_estimator_` attribute.\n\n        Warning: This method should be used to properly instantiate new\n        sub-estimators.\n        ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 176340,
        "commit_id": "bd56814a8e9c988fc3d12801315226f249af1419",
        "repo": "networkx",
        "path": "networkx/algorithms/smallworld.py",
        "file_name": "smallworld.py",
        "fun_name": "lattice_reference",
        "commit_message": "Keep omega within [-1, 1] bounds (#5216)\n\n* Adjusted calculation of small-world metric omega to be within the correct bounds\r\n\r\n* Update docstring to reflect that there is no hard bound on omega\r\n\r\n* add release note\r\n\r\n* maint: rm print statements from tests.\r\n\r\n* Update release file per comment\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def lattice_reference(G, niter=5, D=None, connectivity=True, seed=None):\n    \n    import numpy as np\n    from networkx.utils import cumulative_distribution, discrete_sequence\n\n    local_conn = nx.connectivity.local_edge_connectivity\n\n    if len(G) < 4:\n        raise nx.NetworkXError(\"Graph has less than four nodes.\")\n    # Instead of choosing uniformly at random from a generated edge list,\n    # this algorithm chooses nonuniformly from the set of nodes with\n    # probability weighted by degree.\n    G = G.copy()\n    keys, degrees = zip(*G.degree())  # keys, degree\n    cdf = cumulative_distribution(degrees)  # cdf of degree\n\n    nnodes = len(G)\n    nedges = nx.number_of_edges(G)\n    if D is None:\n        D = np.zeros((nnodes, nnodes))\n        un = np.arange(1, nnodes)\n        um = np.arange(nnodes - 1, 0, -1)\n        u = np.append((0,), np.where(un < um, un, um))\n\n        for v in range(int(np.ceil(nnodes / 2))):\n            D[nnodes - v - 1, :] = np.append(u[v + 1 :], u[: v + 1])\n            D[v, :] = D[nnodes - v - 1, :][::-1]\n\n    niter = niter * nedges\n    # maximal number of rewiring attempts per 'niter'\n    max_attempts = int(nnodes * nedges / (nnodes * (nnodes - 1) / 2))\n\n    for _ in range(niter):\n        n = 0\n        while n < max_attempts:\n            # pick two random edges without creating edge list\n            # choose source node indices from discrete distribution\n            (ai, ci) = discrete_sequence(2, cdistribution=cdf, seed=seed)\n            if ai == ci:\n                continue  # same source, skip\n            a = keys[ai]  # convert index to label\n            c = keys[ci]\n            # choose target uniformly from neighbors\n            b = seed.choice(list(G.neighbors(a)))\n            d = seed.choice(list(G.neighbors(c)))\n            bi = keys.index(b)\n            di = keys.index(d)\n\n            if b in [a, c, d] or d in [a, b, c]:\n                continue  # all vertices should be different\n\n            # don't create parallel edges\n            if (d not in G[a]) and (b not in G[c]):\n                if D[ai, bi] + D[ci, di] >= D[ai, ci] + D[bi, di]:\n                    # only swap if we get closer to the diagonal\n                    G.add_edge(a, d)\n                    G.add_edge(c, b)\n                    G.remove_edge(a, b)\n                    G.remove_edge(c, d)\n\n                    # Check if the graph is still connected\n                    if connectivity and local_conn(G, a, b) == 0:\n                        # Not connected, revert the swap\n                        G.remove_edge(a, d)\n                        G.remove_edge(c, b)\n                        G.add_edge(a, b)\n                        G.add_edge(c, d)\n                    else:\n                        break\n            n += 1\n\n    return G\n\n\n@py_random_state(3)\n@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@py_random_state(3)\n@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 976,
        "n_words": 339,
        "vocab_size": 216,
        "complexity": 14,
        "nloc": 50,
        "token_counts": 516,
        "n_ast_nodes": 829,
        "n_identifiers": 57,
        "d_id": 41846,
        "documentation": {
            "docstring": "Latticize the given graph by swapping edges.\n\n    Parameters\n    ----------\n    G : graph\n        An undirected graph with 4 or more nodes.\n\n    niter : integer (optional, default=1)\n        An edge is rewired approximatively niter times.\n\n    D : numpy.array (optional, default=None)\n        Distance to the diagonal matrix.\n\n    connectivity : boolean (optional, default=True)\n        Ensure connectivity for the latticized graph when set to True.\n\n    seed : integer, random_state, or None (default)\n        Indicator of random number generation state.\n        See :ref:`Randomness<randomness>`.\n\n    Returns\n    -------\n    G : graph\n        The latticized graph.\n\n    Notes\n    -----\n    The implementation is adapted from the algorithm by Sporns et al. [1]_.\n    which is inspired from the original work by Maslov and Sneppen(2002) [2]_.\n\n    References\n    ----------\n    .. [1] Sporns, Olaf, and Jonathan D. Zwi.\n       \"The small world of the cerebral cortex.\"\n       Neuroinformatics 2.2 (2004): 145-162.\n    .. [2] Maslov, Sergei, and Kim Sneppen.\n       \"Specificity and stability in topology of protein networks.\"\n       Science 296.5569 (2002): 910-913.\n    ",
            "n_words": 146,
            "vocab_size": 110,
            "n_whitespaces": 276,
            "language": "en"
        }
    },
    {
        "id": 253767,
        "commit_id": "f0be7e672bc0a7c77005d5c79452d796cfe1a06b",
        "repo": "d2l-en",
        "path": "d2l/mxnet.py",
        "file_name": "mxnet.py",
        "fun_name": "transpose_output",
        "commit_message": "Refactor Multihead Attn, Self Attn, and Transformer (#2096)\n\n* multihead attn\r\n\r\n* self attn and pos encoding\r\n\r\n* simplify\r\n\r\n* before EncoderBlock\r\n\r\n* before tmencoder\r\n\r\n* before decoder block\r\n\r\n* before training\r\n\r\n* transformer code\r\n\r\n* rm seq2seq encoder old\r\n\r\n* fix bahdanau attn map\r\n\r\n* transformer done, perf tuned\r\n\r\n* clean super",
        "code": "def transpose_output(self, X):\n        \n        X = X.reshape(-1, self.num_heads, X.shape[1], X.shape[2])\n        X = X.transpose(0, 2, 1, 3)\n        return X.reshape(X.shape[0], X.shape[1], -1)\n",
        "url": "https://github.com/d2l-ai/d2l-en.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 47,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 71,
        "n_ast_nodes": 103,
        "n_identifiers": 7,
        "d_id": 74224,
        "documentation": {
            "docstring": "Reverse the operation of transpose_qkv.\n    \n        Defined in :numref:`sec_multihead-attention`",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 35527,
        "commit_id": "8635407bc724c45142c1f91dbc9ef3ea681e1a56",
        "repo": "transformers",
        "path": "templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/test_modeling_tf_{{cookiecutter.lowercase_modelname}}.py",
        "file_name": "test_modeling_tf_{{cookiecutter.lowercase_modelname}}.py",
        "fun_name": "test_decoder_model_past_with_large_inputs",
        "commit_message": "Fix tf.concatenate + test past_key_values for TF models (#15774)\n\n* fix wrong method name tf.concatenate\r\n\r\n* add tests related to causal LM / decoder\r\n\r\n* make style and quality\r\n\r\n* clean-up\r\n\r\n* Fix TFBertModel's extended_attention_mask when past_key_values is provided\r\n\r\n* Fix tests\r\n\r\n* fix copies\r\n\r\n* More tf.int8 -> tf.int32 in TF test template\r\n\r\n* clean-up\r\n\r\n* Update TF test template\r\n\r\n* revert the previous commit + update the TF test template\r\n\r\n* Fix TF template extended_attention_mask when past_key_values is provided\r\n\r\n* Fix some styles manually\r\n\r\n* clean-up\r\n\r\n* Fix ValueError: too many values to unpack in the test\r\n\r\n* Fix more: too many values to unpack in the test\r\n\r\n* Add a comment for extended_attention_mask when there is past_key_values\r\n\r\n* Fix TFElectra extended_attention_mask when past_key_values is provided\r\n\r\n* Add tests to other TF models\r\n\r\n* Fix for TF Electra test: add prepare_config_and_inputs_for_decoder\r\n\r\n* Fix not passing training arg to lm_head in TFRobertaForCausalLM\r\n\r\n* Fix tests (with past) for TF Roberta\r\n\r\n* add testing for pask_key_values for TFElectra model\r\n\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>",
        "code": "def test_decoder_model_past_with_large_inputs(self):\n        \n        config_and_inputs = self.model_tester.prepare_config_and_inputs_for_decoder()\n        self.model_tester.create_and_check_decoder_model_past_large_inputs(*config_and_inputs)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 27,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 43,
        "n_identifiers": 6,
        "d_id": 6470,
        "documentation": {
            "docstring": "Similar to `test_causal_lm_model_past_with_large_inputs` but with cross-attention",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 5,
            "language": "en"
        }
    },
    {
        "id": 22226,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/dependencies.py",
        "file_name": "dependencies.py",
        "fun_name": "get_dependencies_from_index",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def get_dependencies_from_index(dep, sources=None, pip_options=None, wheel_cache=None):\n    \n\n    session, finder = get_finder(sources=sources, pip_options=pip_options)\n    dep.is_direct = True\n    requirements = None\n    setup_requires = {}\n    with temp_environ(), ExitStack() as stack:\n        if not wheel_cache:\n            wheel_cache = stack.enter_context(_get_wheel_cache())\n        os.environ[\"PIP_EXISTS_ACTION\"] = \"i\"\n        if dep.editable and not dep.prepared and not dep.req:\n            setup_info = SetupInfo.from_ireq(dep)\n            results = setup_info.get_info()\n            setup_requires.update(results[\"setup_requires\"])\n            requirements = set(results[\"requires\"].values())\n        else:\n            results = shims.resolve(dep)\n            requirements = [v for v in results.values() if v.name != dep.name]\n        requirements = set([format_requirement(r) for r in requirements])\n    if not dep.editable and is_pinned_requirement(dep) and requirements is not None:\n        DEPENDENCY_CACHE[dep] = list(requirements)\n    return requirements\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 231,
        "n_words": 88,
        "vocab_size": 57,
        "complexity": 11,
        "nloc": 21,
        "token_counts": 202,
        "n_ast_nodes": 333,
        "n_identifiers": 38,
        "d_id": 4270,
        "documentation": {
            "docstring": "Retrieves dependencies for the given install requirement from the pip\n    resolver.\n\n    :param dep: A single InstallRequirement\n    :type dep: :class:`~pipenv.patched.pip._internal.req.req_install.InstallRequirement`\n    :param sources: Pipfile-formatted sources, defaults to None\n    :type sources: list[dict], optional\n    :return: A set of dependency lines for generating new InstallRequirements.\n    :rtype: set(str) or None\n    ",
            "n_words": 44,
            "vocab_size": 36,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 218147,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "_get_sourcefile",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _get_sourcefile(bytecode_path):\n    \n    if len(bytecode_path) == 0:\n        return None\n    rest, _, extension = bytecode_path.rpartition('.')\n    if not rest or extension.lower()[-3:-1] != 'py':\n        return bytecode_path\n    try:\n        source_path = source_from_cache(bytecode_path)\n    except (NotImplementedError, ValueError):\n        source_path = bytecode_path[:-1]\n    return source_path if _path_isfile(source_path) else bytecode_path\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 87,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 6,
        "nloc": 11,
        "token_counts": 81,
        "n_ast_nodes": 135,
        "n_identifiers": 13,
        "d_id": 55163,
        "documentation": {
            "docstring": "Convert a bytecode file path to a source path (if possible).\n\n    This function exists purely for backwards-compatibility for\n    PyImport_ExecCodeModuleWithFilenames() in the C API.\n\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 167566,
        "commit_id": "f538568afc2c76c2d738d32e3544cf9fe6742960",
        "repo": "pandas",
        "path": "pandas/_testing/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "reset_display_options",
        "commit_message": "TYP: misc return type annotations (#47558)",
        "code": "def reset_display_options() -> None:\n    \n    pd.reset_option(\"^display.\", silent=True)\n\n\n# -----------------------------------------------------------------------------\n# Comparators\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 14,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 17,
        "n_ast_nodes": 34,
        "n_identifiers": 4,
        "d_id": 40037,
        "documentation": {
            "docstring": "\n    Reset the display options for printing and representing objects.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 207868,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_edit_save_as_delete_inline",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_edit_save_as_delete_inline(self):\n        \n        post_data = self.inline_post_data.copy()\n        post_data.update(\n            {\n                \"_saveasnew\": \"Save+as+new\",\n                \"article_set-1-section\": \"1\",\n                \"article_set-2-section\": \"1\",\n                \"article_set-2-DELETE\": \"1\",\n                \"article_set-3-section\": \"1\",\n            }\n        )\n        response = self.client.post(\n            reverse(\"admin:admin_views_section_change\", args=(self.s1.pk,)), post_data\n        )\n        self.assertEqual(response.status_code, 302)\n        # started with 3 articles, one was deleted.\n        self.assertEqual(Section.objects.latest(\"id\").article_set.count(), 2)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 209,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 99,
        "n_ast_nodes": 176,
        "n_identifiers": 20,
        "d_id": 52139,
        "documentation": {
            "docstring": "\n        Should be able to \"Save as new\" while also deleting an inline.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 272135,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/initializers/initializers_test.py",
        "file_name": "initializers_test.py",
        "fun_name": "_compute_fans",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _compute_fans(shape):\n    \n    if len(shape) < 1:  # Just to avoid errors for constants.\n        fan_in = fan_out = 1\n    elif len(shape) == 1:\n        fan_in = fan_out = shape[0]\n    elif len(shape) == 2:\n        fan_in = shape[0]\n        fan_out = shape[1]\n    else:\n        # Assuming convolution kernels (2D, 3D, or more).\n        # kernel shape: (..., input_depth, depth)\n        receptive_field_size = 1\n        for dim in shape[:-2]:\n            receptive_field_size *= dim\n        fan_in = shape[-2] * receptive_field_size\n        fan_out = shape[-1] * receptive_field_size\n    return int(fan_in), int(fan_out)\n\n\n@test_combinations.generate(test_combinations.combine(mode=[\"graph\", \"eager\"]))",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@test_combinations.generate(test_combinations.combine(mode=[\"graph\", \"eager\"]))",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 176,
        "n_words": 77,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 102,
        "n_ast_nodes": 198,
        "n_identifiers": 12,
        "d_id": 80963,
        "documentation": {
            "docstring": "Computes the number of input and output units for a weight shape.\n\n    Args:\n      shape: Integer shape tuple or TF tensor shape.\n\n    Returns:\n      A tuple of integer scalars (fan_in, fan_out).\n    ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 276986,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/metrics_utils.py",
        "file_name": "metrics_utils.py",
        "fun_name": "sparse_categorical_matches",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def sparse_categorical_matches(y_true, y_pred):\n    \n    reshape_matches = False\n    y_pred = tf.convert_to_tensor(y_pred)\n    y_true = tf.convert_to_tensor(y_true)\n    y_true_org_shape = tf.shape(y_true)\n    y_pred_rank = y_pred.shape.ndims\n    y_true_rank = y_true.shape.ndims\n\n    # If the shape of y_true is (num_samples, 1), squeeze to (num_samples,)\n    if (\n        (y_true_rank is not None)\n        and (y_pred_rank is not None)\n        and (len(backend.int_shape(y_true)) == len(backend.int_shape(y_pred)))\n    ):\n        y_true = tf.squeeze(y_true, [-1])\n        reshape_matches = True\n    y_pred = tf.math.argmax(y_pred, axis=-1)\n\n    # If the predicted output and actual output types don't match, force cast them\n    # to match.\n    if backend.dtype(y_pred) != backend.dtype(y_true):\n        y_pred = tf.cast(y_pred, backend.dtype(y_true))\n    matches = tf.cast(tf.equal(y_true, y_pred), backend.floatx())\n    if reshape_matches:\n        matches = tf.reshape(matches, shape=y_true_org_shape)\n    return matches\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 198,
        "n_words": 98,
        "vocab_size": 66,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 187,
        "n_ast_nodes": 297,
        "n_identifiers": 24,
        "d_id": 81817,
        "documentation": {
            "docstring": "Creates float Tensor, 1.0 for label-prediction match, 0.0 for mismatch.\n\n    You can provide logits of classes as `y_pred`, since argmax of\n    logits and probabilities are same.\n\n    Args:\n      y_true: Integer ground truth values.\n      y_pred: The prediction values.\n\n    Returns:\n      Match tensor: 1.0 for label-prediction match, 0.0 for mismatch.\n    ",
            "n_words": 46,
            "vocab_size": 35,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 123265,
        "commit_id": "7bf15bf33644ef13e34dff63beaf8d19387219be",
        "repo": "hosts",
        "path": "updateHostsFile.py",
        "file_name": "updateHostsFile.py",
        "fun_name": "query_yes_no",
        "commit_message": "Use https in more places",
        "code": "def query_yes_no(question, default=\"yes\"):\n    \n\n    valid = {\"yes\": \"yes\", \"y\": \"yes\", \"ye\": \"yes\", \"no\": \"no\", \"n\": \"no\"}\n    prompt = {None: \" [y/n] \", \"yes\": \" [Y/n] \", \"no\": \" [y/N] \"}.get(default, None)\n\n    if not prompt:\n        raise ValueError(\"invalid default answer: '%s'\" % default)\n\n    reply = None\n\n    while not reply:\n        sys.stdout.write(colorize(question, Colors.PROMPT) + prompt)\n\n        choice = input().lower()\n        reply = None\n\n        if default and not choice:\n            reply = default\n        elif choice in valid:\n            reply = valid[choice]\n        else:\n            print_failure(\"Please respond with 'yes' or 'no' (or 'y' or 'n').\\n\")\n\n    return reply == \"yes\"\n\n",
        "url": "https://github.com/StevenBlack/hosts.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 189,
        "n_words": 86,
        "vocab_size": 62,
        "complexity": 6,
        "nloc": 17,
        "token_counts": 132,
        "n_ast_nodes": 245,
        "n_identifiers": 18,
        "d_id": 27310,
        "documentation": {
            "docstring": "\n    Ask a yes/no question via input() and get answer from the user.\n\n    Inspired by the following implementation:\n\n    https://code.activestate.com/recipes/577058/\n\n    Parameters\n    ----------\n    question : str\n        The question presented to the user.\n    default : str, default \"yes\"\n        The presumed answer if the user just hits <Enter>. It must be \"yes\",\n        \"no\", or None (means an answer is required of the user).\n\n    Returns\n    -------\n    yes : Whether or not the user replied yes to the question.\n    ",
            "n_words": 72,
            "vocab_size": 53,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 9892,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/peapods/pods/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "wait_start_success",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def wait_start_success(self) -> None:\n        \n        if not self.args.noblock_on_start:\n            raise ValueError(\n                f'{self.wait_start_success!r} should only be called when `noblock_on_start` is set to True'\n            )\n        try:\n            if self.uses_before_pea is not None:\n                self.uses_before_pea.wait_start_success()\n            if self.uses_after_pea is not None:\n                self.uses_after_pea.wait_start_success()\n            if self.head_pea is not None:\n                self.head_pea.wait_start_success()\n            for shard_id in self.shards:\n                self.shards[shard_id].wait_start_success()\n            self.activate()\n        except:\n            self.close()\n            raise\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 251,
        "n_words": 49,
        "vocab_size": 36,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 99,
        "n_ast_nodes": 173,
        "n_identifiers": 12,
        "d_id": 1759,
        "documentation": {
            "docstring": "Block until all peas starts successfully.\n\n        If not successful, it will raise an error hoping the outer function to catch it\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 197011,
        "commit_id": "e0dc14eca132f37c5f49369eb4051eae37c9b119",
        "repo": "sympy",
        "path": "sympy/functions/combinatorial/numbers.py",
        "file_name": "numbers.py",
        "fun_name": "nD",
        "commit_message": "Refactored import ordering in functions",
        "code": "def nD(i=None, brute=None, *, n=None, m=None):\n    \n    from sympy.integrals.integrals import integrate\n    from sympy.functions.special.polynomials import laguerre\n    from sympy.abc import x",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 30,
        "n_words": 18,
        "vocab_size": 14,
        "complexity": 40,
        "nloc": 67,
        "token_counts": 562,
        "n_ast_nodes": 67,
        "n_identifiers": 14,
        "d_id": 48287,
        "documentation": {
            "docstring": "return the number of derangements for: ``n`` unique items, ``i``\n    items (as a sequence or multiset), or multiplicities, ``m`` given\n    as a sequence or multiset.\n\n    Examples\n    ========\n\n    >>> from sympy.utilities.iterables import generate_derangements as enum\n    >>> from sympy.functions.combinatorial.numbers import nD\n\n    A derangement ``d`` of sequence ``s`` has all ``d[i] != s[i]``:\n\n    >>> set([''.join(i) for i in enum('abc')])\n    {'bca', 'cab'}\n    >>> nD('abc')\n    2\n\n    Input as iterable or dictionary (multiset form) is accepted:\n\n    >>> assert nD([1, 2, 2, 3, 3, 3]) == nD({1: 1, 2: 2, 3: 3})\n\n    By default, a brute-force enumeration and count of multiset permutations\n    is only done if there are fewer than 9 elements. There may be cases when\n    there is high multiplicty with few unique elements that will benefit\n    from a brute-force enumeration, too. For this reason, the `brute`\n    keyword (default None) is provided. When False, the brute-force\n    enumeration will never be used. When True, it will always be used.\n\n    >>> nD('1111222233', brute=True)\n    44\n\n    For convenience, one may specify ``n`` distinct items using the\n    ``n`` keyword:\n\n    >>> assert nD(n=3) == nD('abc') == 2\n\n    Since the number of derangments depends on the multiplicity of the\n    elements and not the elements themselves, it may be more convenient\n    to give a list or multiset of multiplicities using keyword ``m``:\n\n    >>> assert nD('abc') == nD(m=(1,1,1)) == nD(m={1:3}) == 2\n\n    ",
            "n_words": 217,
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            "n_whitespaces": 304,
            "language": "en"
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    },
    {
        "id": 124395,
        "commit_id": "b9a4f64f32389a1f76a7f74103b4d5da089ebb2b",
        "repo": "ray",
        "path": "python/ray/train/tests/test_examples.py",
        "file_name": "test_examples.py",
        "fun_name": "test_tf_non_distributed",
        "commit_message": "[AIR/train] Use new Train API (#25735)\n\nUses the new AIR Train API for examples and tests.\r\n\r\nThe `Result` object gets a new attribute - `log_dir`, pointing to the Trial's `logdir` allowing users to access tensorboard logs and artifacts of other loggers.\r\n\r\nThis PR only deals with \"low hanging fruit\" - tests that need substantial rewriting or Train user guide are not touched. Those will be updated in followup PRs.\r\n\r\nTests and examples that concern deprecated features or which are duplicated in AIR have been removed or disabled.\r\n\r\nRequires https://github.com/ray-project/ray/pull/25943 to be merged in first",
        "code": "def test_tf_non_distributed(ray_start_4_cpus):\n    \n\n    trainer = TorchTrainer(\n        tf_quick_start_train_func, scaling_config=dict(num_workers=1)\n    )\n    trainer.fit()\n\n\n# TODO: Refactor as a backend test.",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "n_identifiers": 9,
        "d_id": 27594,
        "documentation": {
            "docstring": "Make sure Ray Train works without TF MultiWorkerMirroredStrategy.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 337288,
        "commit_id": "fb5ed62c102c0323486b89805e1888495de3db15",
        "repo": "accelerate",
        "path": "src/accelerate/checkpointing.py",
        "file_name": "checkpointing.py",
        "fun_name": "load_accelerator_state",
        "commit_message": "Convert documentation to the new front (#271)\n\n* Main conversion\r\n\r\n* Doc styling\r\n\r\n* Style\r\n\r\n* New front deploy\r\n\r\n* Fixes\r\n\r\n* Fixes\r\n\r\n* Fix new docstrings\r\n\r\n* Style",
        "code": "def load_accelerator_state(input_dir, models, optimizers, process_index, scaler=None):\n    \n    # Model states\n    for i, model in enumerate(models):\n        weights_name = f\"{MODEL_NAME}.bin\" if i == 0 else f\"{MODEL_NAME}_{i}.bin\"\n        input_model_file = os.path.join(input_dir, weights_name)\n        models[i].load_state_dict(torch.load(input_model_file))\n    logger.info(\"All model weights loaded successfully\")\n\n    # Optimizer states\n    for i, opt in enumerate(optimizers):\n        optimizer_name = f\"{OPTIMIZER_NAME}.bin\" if i == 0 else f\"{OPTIMIZER_NAME}_{i}.bin\"\n        input_optimizer_file = os.path.join(input_dir, optimizer_name)\n        optimizers[i].load_state_dict(torch.load(input_optimizer_file))\n    logger.info(\"All optimizer states loaded successfully\")\n\n    # GradScaler state\n    if scaler is not None:\n        input_scaler_file = os.path.join(input_dir, SCALER_NAME)\n        scaler.load_state_dict(torch.load(input_scaler_file))\n        logger.info(\"GradScaler state loaded successfully\")\n\n    # Random states\n    states = torch.load(os.path.join(input_dir, f\"{RNG_STATE_NAME}_{process_index}.pkl\"))\n    random.setstate(states[\"random_state\"])\n    np.random.set_state(states[\"numpy_random_seed\"])\n    torch.set_rng_state(states[\"torch_manual_seed\"])\n    torch.cuda.set_rng_state_all(states[\"torch_cuda_manual_seed\"])\n    # ^^ safe to call this function even if cuda is not available\n    if is_tpu_available():\n        xm.set_rng_state(states[\"xm_seed\"])\n    logger.info(\"All random states loaded successfully\")\n\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_identifiers": 37,
        "d_id": 121002,
        "documentation": {
            "docstring": "\n    Loads states of the models, optimizers, scaler, and RNG generators from a given directory.\n\n    Args:\n        input_dir (`str` or `os.PathLike`):\n            The name of the folder to load all relevant weights and states.\n        model_stmodelsates (`List[torch.nn.Module]`):\n            A list of model instances\n        optimizers (`List[torch.optim.Optimizer]`):\n            A list of optimizer instances\n        process_index (`int`):\n            The current process index in the Accelerator state\n        scaler (`torch.cuda.amp.GradScaler`, *optional*):\n            An optional *GradScaler* instance to load\n    ",
            "n_words": 64,
            "vocab_size": 52,
            "n_whitespaces": 164,
            "language": "en"
        }
    },
    {
        "id": 244099,
        "commit_id": "86037650f243a1ab0a515a22e831ea5dcddd6a7d",
        "repo": "mmdetection",
        "path": "mmdet/datasets/pipelines/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "__call__",
        "commit_message": "Unified name of orig as ori (#7456)",
        "code": "def __call__(self, results):\n        \n        if random.random() < self.shift_ratio:\n            img_shape = results['img'].shape[:2]\n\n            random_shift_x = random.randint(-self.max_shift_px,\n                                            self.max_shift_px)\n            random_shift_y = random.randint(-self.max_shift_px,\n                                            self.max_shift_px)\n            new_x = max(0, random_shift_x)\n            ori_x = max(0, -random_shift_x)\n            new_y = max(0, random_shift_y)\n            ori_y = max(0, -random_shift_y)\n\n            # TODO: support mask and semantic segmentation maps.\n            for key in results.get('bbox_fields', []):\n                bboxes = results[key].copy()\n                bboxes[..., 0::2] += random_shift_x\n                bboxes[..., 1::2] += random_shift_y\n\n                # clip border\n                bboxes[..., 0::2] = np.clip(bboxes[..., 0::2], 0, img_shape[1])\n                bboxes[..., 1::2] = np.clip(bboxes[..., 1::2], 0, img_shape[0])\n\n                # remove invalid bboxes\n                bbox_w = bboxes[..., 2] - bboxes[..., 0]\n                bbox_h = bboxes[..., 3] - bboxes[..., 1]\n                valid_inds = (bbox_w > self.filter_thr_px) & (\n                    bbox_h > self.filter_thr_px)\n                # If the shift does not contain any gt-bbox area, skip this\n                # image.\n                if key == 'gt_bboxes' and not valid_inds.any():\n                    return results\n                bboxes = bboxes[valid_inds]\n                results[key] = bboxes\n\n                # label fields. e.g. gt_labels and gt_labels_ignore\n                label_key = self.bbox2label.get(key)\n                if label_key in results:\n                    results[label_key] = results[label_key][valid_inds]\n\n            for key in results.get('img_fields', ['img']):\n                img = results[key]\n                new_img = np.zeros_like(img)\n                img_h, img_w = img.shape[:2]\n                new_h = img_h - np.abs(random_shift_y)\n                new_w = img_w - np.abs(random_shift_x)\n                new_img[new_y:new_y + new_h, new_x:new_x + new_w] \\\n                    = img[ori_y:ori_y + new_h, ori_x:ori_x + new_w]\n                results[key] = new_img\n\n        return results\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
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        "d_id": 70237,
        "documentation": {
            "docstring": "Call function to random shift images, bounding boxes.\n\n        Args:\n            results (dict): Result dict from loading pipeline.\n\n        Returns:\n            dict: Shift results.\n        ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 160044,
        "commit_id": "40747ae50620631941e43dbbd5baaccab669922f",
        "repo": "numpy",
        "path": "numpy/linalg/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "svd",
        "commit_message": "clarify svd documentation\n\n`u @ np.diag(s) @ vh` can only reproduce the original matrix when `full_matrices` is `False`, otherwise dimension does not match.",
        "code": "def svd(a, full_matrices=True, compute_uv=True, hermitian=False):\n    \n    import numpy as _nx\n    a, wrap = _makearray(a)\n\n    if hermitian:\n        # note: lapack svd returns eigenvalues with s ** 2 sorted descending,\n        # but eig returns s sorted ascending, so we re-order the eigenvalues\n        # and related arrays to have the correct order\n        if compute_uv:\n            s, u = eigh(a)\n            sgn = sign(s)\n            s = abs(s)\n            sidx = argsort(s)[..., ::-1]\n            sgn = _nx.take_along_axis(sgn, sidx, axis=-1)\n            s = _nx.take_along_axis(s, sidx, axis=-1)\n            u = _nx.take_along_axis(u, sidx[..., None, :], axis=-1)\n            # singular values are unsigned, move the sign into v\n            vt = transpose(u * sgn[..., None, :]).conjugate()\n            return wrap(u), s, wrap(vt)\n        else:\n            s = eigvalsh(a)\n            s = s[..., ::-1]\n            s = abs(s)\n            return sort(s)[..., ::-1]\n\n    _assert_stacked_2d(a)\n    t, result_t = _commonType(a)\n\n    extobj = get_linalg_error_extobj(_raise_linalgerror_svd_nonconvergence)\n\n    m, n = a.shape[-2:]\n    if compute_uv:\n        if full_matrices:\n            if m < n:\n                gufunc = _umath_linalg.svd_m_f\n            else:\n                gufunc = _umath_linalg.svd_n_f\n        else:\n            if m < n:\n                gufunc = _umath_linalg.svd_m_s\n            else:\n                gufunc = _umath_linalg.svd_n_s\n\n        signature = 'D->DdD' if isComplexType(t) else 'd->ddd'\n        u, s, vh = gufunc(a, signature=signature, extobj=extobj)\n        u = u.astype(result_t, copy=False)\n        s = s.astype(_realType(result_t), copy=False)\n        vh = vh.astype(result_t, copy=False)\n        return wrap(u), s, wrap(vh)\n    else:\n        if m < n:\n            gufunc = _umath_linalg.svd_m\n        else:\n            gufunc = _umath_linalg.svd_n\n\n        signature = 'D->d' if isComplexType(t) else 'd->d'\n        s = gufunc(a, signature=signature, extobj=extobj)\n        s = s.astype(_realType(result_t), copy=False)\n        return s\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 658,
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        "n_ast_nodes": 635,
        "n_identifiers": 48,
        "d_id": 38474,
        "documentation": {
            "docstring": "\n    Singular Value Decomposition.\n\n    When `a` is a 2D array, and when `full_matrices` is `False`,\n    it is factorized as ``u @ np.diag(s) @ vh = (u * s) @ vh``,\n    where `u` and `vh` are 2D unitary arrays and `s` is a 1D\n    array of `a`'s singular values. When `a` is higher-dimensional, SVD is\n    applied in stacked mode as explained below.\n\n    Parameters\n    ----------\n    a : (..., M, N) array_like\n        A real or complex array with ``a.ndim >= 2``.\n    full_matrices : bool, optional\n        If True (default), `u` and `vh` have the shapes ``(..., M, M)`` and\n        ``(..., N, N)``, respectively.  Otherwise, the shapes are\n        ``(..., M, K)`` and ``(..., K, N)``, respectively, where\n        ``K = min(M, N)``.\n    compute_uv : bool, optional\n        Whether or not to compute `u` and `vh` in addition to `s`.  True\n        by default.\n    hermitian : bool, optional\n        If True, `a` is assumed to be Hermitian (symmetric if real-valued),\n        enabling a more efficient method for finding singular values.\n        Defaults to False.\n\n        .. versionadded:: 1.17.0\n\n    Returns\n    -------\n    u : { (..., M, M), (..., M, K) } array\n        Unitary array(s). The first ``a.ndim - 2`` dimensions have the same\n        size as those of the input `a`. The size of the last two dimensions\n        depends on the value of `full_matrices`. Only returned when\n        `compute_uv` is True.\n    s : (..., K) array\n        Vector(s) with the singular values, within each vector sorted in\n        descending order. The first ``a.ndim - 2`` dimensions have the same\n        size as those of the input `a`.\n    vh : { (..., N, N), (..., K, N) } array\n        Unitary array(s). The first ``a.ndim - 2`` dimensions have the same\n        size as those of the input `a`. The size of the last two dimensions\n        depends on the value of `full_matrices`. Only returned when\n        `compute_uv` is True.\n\n    Raises\n    ------\n    LinAlgError\n        If SVD computation does not converge.\n\n    See Also\n    --------\n    scipy.linalg.svd : Similar function in SciPy.\n    scipy.linalg.svdvals : Compute singular values of a matrix.\n\n    Notes\n    -----\n\n    .. versionchanged:: 1.8.0\n       Broadcasting rules apply, see the `numpy.linalg` documentation for\n       details.\n\n    The decomposition is performed using LAPACK routine ``_gesdd``.\n\n    SVD is usually described for the factorization of a 2D matrix :math:`A`.\n    The higher-dimensional case will be discussed below. In the 2D case, SVD is\n    written as :math:`A = U S V^H`, where :math:`A = a`, :math:`U= u`,\n    :math:`S= \\\\mathtt{np.diag}(s)` and :math:`V^H = vh`. The 1D array `s`\n    contains the singular values of `a` and `u` and `vh` are unitary. The rows\n    of `vh` are the eigenvectors of :math:`A^H A` and the columns of `u` are\n    the eigenvectors of :math:`A A^H`. In both cases the corresponding\n    (possibly non-zero) eigenvalues are given by ``s**2``.\n\n    If `a` has more than two dimensions, then broadcasting rules apply, as\n    explained in :ref:`routines.linalg-broadcasting`. This means that SVD is\n    working in \"stacked\" mode: it iterates over all indices of the first\n    ``a.ndim - 2`` dimensions and for each combination SVD is applied to the\n    last two indices. The matrix `a` can be reconstructed from the\n    decomposition with either ``(u * s[..., None, :]) @ vh`` or\n    ``u @ (s[..., None] * vh)``. (The ``@`` operator can be replaced by the\n    function ``np.matmul`` for python versions below 3.5.)\n\n    If `a` is a ``matrix`` object (as opposed to an ``ndarray``), then so are\n    all the return values.\n\n    Examples\n    --------\n    >>> a = np.random.randn(9, 6) + 1j*np.random.randn(9, 6)\n    >>> b = np.random.randn(2, 7, 8, 3) + 1j*np.random.randn(2, 7, 8, 3)\n\n    Reconstruction based on full SVD, 2D case:\n\n    >>> u, s, vh = np.linalg.svd(a, full_matrices=True)\n    >>> u.shape, s.shape, vh.shape\n    ((9, 9), (6,), (6, 6))\n    >>> np.allclose(a, np.dot(u[:, :6] * s, vh))\n    True\n    >>> smat = np.zeros((9, 6), dtype=complex)\n    >>> smat[:6, :6] = np.diag(s)\n    >>> np.allclose(a, np.dot(u, np.dot(smat, vh)))\n    True\n\n    Reconstruction based on reduced SVD, 2D case:\n\n    >>> u, s, vh = np.linalg.svd(a, full_matrices=False)\n    >>> u.shape, s.shape, vh.shape\n    ((9, 6), (6,), (6, 6))\n    >>> np.allclose(a, np.dot(u * s, vh))\n    True\n    >>> smat = np.diag(s)\n    >>> np.allclose(a, np.dot(u, np.dot(smat, vh)))\n    True\n\n    Reconstruction based on full SVD, 4D case:\n\n    >>> u, s, vh = np.linalg.svd(b, full_matrices=True)\n    >>> u.shape, s.shape, vh.shape\n    ((2, 7, 8, 8), (2, 7, 3), (2, 7, 3, 3))\n    >>> np.allclose(b, np.matmul(u[..., :3] * s[..., None, :], vh))\n    True\n    >>> np.allclose(b, np.matmul(u[..., :3], s[..., None] * vh))\n    True\n\n    Reconstruction based on reduced SVD, 4D case:\n\n    >>> u, s, vh = np.linalg.svd(b, full_matrices=False)\n    >>> u.shape, s.shape, vh.shape\n    ((2, 7, 8, 3), (2, 7, 3), (2, 7, 3, 3))\n    >>> np.allclose(b, np.matmul(u * s[..., None, :], vh))\n    True\n    >>> np.allclose(b, np.matmul(u, s[..., None] * vh))\n    True\n\n    ",
            "n_words": 746,
            "vocab_size": 328,
            "n_whitespaces": 1180,
            "language": "en"
        }
    },
    {
        "id": 82432,
        "commit_id": "c1290c9ff89cb00caa5469129fd527e9d82cd820",
        "repo": "django-cms",
        "path": "cms/tests/test_templatetags.py",
        "file_name": "test_templatetags.py",
        "fun_name": "test_create_placeholder_if_not_exist_in_template",
        "commit_message": "ci: Added codespell (#7355)\n\nCo-authored-by: Christian Clauss <cclauss@me.com>\r\n\r\n* ci: codespell config taken from #7292",
        "code": "def test_create_placeholder_if_not_exist_in_template(self):\n        \n        page = create_page('Test', 'col_two.html', 'en')\n        # I need to make it seem like the user added another placeholder to the SAME template.\n        page._template_cache = 'col_three.html'\n\n        request = self.get_request(page=page)\n        context = SekizaiContext()\n        context['request'] = request\n\n        self.assertObjectDoesNotExist(page.placeholders.all(), slot='col_right')\n        context = self.get_context(page=page)\n        renderer = self.get_content_renderer(request)\n        renderer.render_page_placeholder(\n            'col_right',\n            context,\n            inherit=False,\n            page=page,\n        )\n        self.assertObjectExist(page.placeholders.all(), slot='col_right')\n\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 187,
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        "token_counts": 109,
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        "n_identifiers": 19,
        "d_id": 17398,
        "documentation": {
            "docstring": "\n        Tests that adding a new placeholder to an existing page's template\n        creates the placeholder.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 310960,
        "commit_id": "d15d081646c26d32f860d8f84b4f29d848dab148",
        "repo": "core",
        "path": "homeassistant/components/whois/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "extra_state_attributes",
        "commit_message": "Add data update coordinator to Whois (#64846)\n\nCo-authored-by: Joakim Sørensen <joasoe@gmail.com>",
        "code": "def extra_state_attributes(self) -> dict[str, int | float | None] | None:\n        \n\n        # Only add attributes to the original sensor\n        if self.entity_description.key != \"days_until_expiration\":\n            return None\n\n        if self.coordinator.data is None:\n            return None\n\n        attrs = {\n            ATTR_EXPIRES: self.coordinator.data.expiration_date.isoformat(),\n        }\n\n        if self.coordinator.data.name_servers:\n            attrs[ATTR_NAME_SERVERS] = \" \".join(self.coordinator.data.name_servers)\n\n        if self.coordinator.data.last_updated:\n            attrs[ATTR_UPDATED] = self.coordinator.data.last_updated.isoformat()\n\n        if self.coordinator.data.registrar:\n            attrs[ATTR_REGISTRAR] = self.coordinator.data.registrar\n\n        return attrs\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 191,
        "n_words": 55,
        "vocab_size": 41,
        "complexity": 6,
        "nloc": 16,
        "token_counts": 133,
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        "n_identifiers": 21,
        "d_id": 109631,
        "documentation": {
            "docstring": "Return the state attributes of the monitored installation.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 268861,
        "commit_id": "85ccb4e108551b7444213276ffb4c4c09f22f886",
        "repo": "keras",
        "path": "keras/layers/serialization.py",
        "file_name": "serialization.py",
        "fun_name": "populate_deserializable_objects",
        "commit_message": "Refactor `merge.py` into smaller logically organized files hosted under a `merging` directory.\n\nPiperOrigin-RevId: 424162837",
        "code": "def populate_deserializable_objects():\n  \n  global LOCAL\n  if not hasattr(LOCAL, 'ALL_OBJECTS'):\n    LOCAL.ALL_OBJECTS = {}\n    LOCAL.GENERATED_WITH_V2 = None\n\n  if LOCAL.ALL_OBJECTS and LOCAL.GENERATED_WITH_V2 == tf.__internal__.tf2.enabled(\n  ):\n    # Objects dict is already generated for the proper TF version:\n    # do nothing.\n    return\n\n  LOCAL.ALL_OBJECTS = {}\n  LOCAL.GENERATED_WITH_V2 = tf.__internal__.tf2.enabled()\n\n  base_cls = base_layer.Layer\n  generic_utils.populate_dict_with_module_objects(\n      LOCAL.ALL_OBJECTS,\n      ALL_MODULES,\n      obj_filter=lambda x: inspect.isclass(x) and issubclass(x, base_cls))\n\n  # Overwrite certain V1 objects with V2 versions\n  if tf.__internal__.tf2.enabled():\n    generic_utils.populate_dict_with_module_objects(\n        LOCAL.ALL_OBJECTS,\n        ALL_V2_MODULES,\n        obj_filter=lambda x: inspect.isclass(x) and issubclass(x, base_cls))\n\n  # These deserialization aliases are added for backward compatibility,\n  # as in TF 1.13, \"BatchNormalizationV1\" and \"BatchNormalizationV2\"\n  # were used as class name for v1 and v2 version of BatchNormalization,\n  # respectively. Here we explicitly convert them to their canonical names.\n  LOCAL.ALL_OBJECTS[\n      'BatchNormalizationV1'] = batch_normalization_v1.BatchNormalization\n  LOCAL.ALL_OBJECTS[\n      'BatchNormalizationV2'] = batch_normalization.BatchNormalization\n\n  # Prevent circular dependencies.\n  from keras import models  # pylint: disable=g-import-not-at-top\n  from keras.premade.linear import LinearModel  # pylint: disable=g-import-not-at-top\n  from keras.premade.wide_deep import WideDeepModel  # pylint: disable=g-import-not-at-top\n  from keras.feature_column.sequence_feature_column import SequenceFeatures  # pylint: disable=g-import-not-at-top\n\n  LOCAL.ALL_OBJECTS['Input'] = input_layer.Input\n  LOCAL.ALL_OBJECTS['InputSpec'] = input_spec.InputSpec\n  LOCAL.ALL_OBJECTS['Functional'] = models.Functional\n  LOCAL.ALL_OBJECTS['Model'] = models.Model\n  LOCAL.ALL_OBJECTS['SequenceFeatures'] = SequenceFeatures\n  LOCAL.ALL_OBJECTS['Sequential'] = models.Sequential\n  LOCAL.ALL_OBJECTS['LinearModel'] = LinearModel\n  LOCAL.ALL_OBJECTS['WideDeepModel'] = WideDeepModel\n\n  if tf.__internal__.tf2.enabled():\n    from keras.feature_column.dense_features_v2 import DenseFeatures  # pylint: disable=g-import-not-at-top\n    LOCAL.ALL_OBJECTS['DenseFeatures'] = DenseFeatures\n  else:\n    from keras.feature_column.dense_features import DenseFeatures  # pylint: disable=g-import-not-at-top\n    LOCAL.ALL_OBJECTS['DenseFeatures'] = DenseFeatures\n\n  # Merging layers, function versions.\n  LOCAL.ALL_OBJECTS['add'] = merging.add\n  LOCAL.ALL_OBJECTS['subtract'] = merging.subtract\n  LOCAL.ALL_OBJECTS['multiply'] = merging.multiply\n  LOCAL.ALL_OBJECTS['average'] = merging.average\n  LOCAL.ALL_OBJECTS['maximum'] = merging.maximum\n  LOCAL.ALL_OBJECTS['minimum'] = merging.minimum\n  LOCAL.ALL_OBJECTS['concatenate'] = merging.concatenate\n  LOCAL.ALL_OBJECTS['dot'] = merging.dot\n\n\n@keras_export('keras.layers.serialize')",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export('keras.layers.serialize')",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 353,
        "n_words": 231,
        "vocab_size": 141,
        "complexity": 8,
        "nloc": 50,
        "token_counts": 387,
        "n_ast_nodes": 659,
        "n_identifiers": 54,
        "d_id": 79730,
        "documentation": {
            "docstring": "Populates dict ALL_OBJECTS with every built-in layer.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 73082,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/views.py",
        "file_name": "views.py",
        "fun_name": "get_ordering",
        "commit_message": "Reformat with black",
        "code": "def get_ordering(self):\n        \n        ordering = self.get_validated_ordering()\n        return [values[0] + name for name, values in ordering.items()]\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 32,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 15950,
        "documentation": {
            "docstring": "Return the field or fields to use for ordering the queryset",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 127793,
        "commit_id": "42da4445e7a3cb358a1a02ae433a004e9fa836b5",
        "repo": "ray",
        "path": "python/ray/tests/test_metrics_head.py",
        "file_name": "test_metrics_head.py",
        "fun_name": "test_metrics_folder",
        "commit_message": "Export default configurations for grafana and prometheus (#28286)",
        "code": "def test_metrics_folder():\n    \n    with _ray_start(include_dashboard=True) as context:\n        session_dir = context[\"session_dir\"]\n        assert os.path.exists(\n            f\"{session_dir}/metrics/grafana/provisioning/dashboards/default.yml\"\n        )\n        assert os.path.exists(\n            f\"{session_dir}/metrics/grafana/provisioning/dashboards\"\n            \"/default_grafana_dashboard.json\"\n        )\n        assert os.path.exists(\n            f\"{session_dir}/metrics/grafana/provisioning/datasources/default.yml\"\n        )\n        assert os.path.exists(f\"{session_dir}/metrics/prometheus/prometheus.yml\")\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 130,
        "n_words": 24,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 62,
        "n_ast_nodes": 126,
        "n_identifiers": 8,
        "d_id": 28528,
        "documentation": {
            "docstring": "\n    Tests that the default dashboard files get created.\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 219615,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "logical_or",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def logical_or(self, other, context=None):\n        \n        if context is None:\n            context = getcontext()\n\n        other = _convert_other(other, raiseit=True)\n\n        if not self._islogical() or not other._islogical():\n            return context._raise_error(InvalidOperation)\n\n        # fill to context.prec\n        (opa, opb) = self._fill_logical(context, self._int, other._int)\n\n        # make the operation, and clean starting zeroes\n        result = \"\".join([str(int(a)|int(b)) for a,b in zip(opa,opb)])\n        return _dec_from_triple(0, result.lstrip('0') or '0', 0)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 139,
        "n_words": 54,
        "vocab_size": 45,
        "complexity": 6,
        "nloc": 9,
        "token_counts": 122,
        "n_ast_nodes": 197,
        "n_identifiers": 23,
        "d_id": 55652,
        "documentation": {
            "docstring": "Applies an 'or' operation between self and other's digits.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 221279,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/cgi.py",
        "file_name": "cgi.py",
        "fun_name": "parse_header",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parse_header(line):\n    \n    parts = _parseparam(';' + line)\n    key = parts.__next__()\n    pdict = {}\n    for p in parts:\n        i = p.find('=')\n        if i >= 0:\n            name = p[:i].strip().lower()\n            value = p[i+1:].strip()\n            if len(value) >= 2 and value[0] == value[-1] == '\"':\n                value = value[1:-1]\n                value = value.replace('\\\\\\\\', '\\\\').replace('\\\\\"', '\"')\n            pdict[name] = value\n    return key, pdict\n\n\n# Classes for field storage\n# =========================\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 165,
        "n_words": 61,
        "vocab_size": 43,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 128,
        "n_ast_nodes": 224,
        "n_identifiers": 16,
        "d_id": 56315,
        "documentation": {
            "docstring": "Parse a Content-type like header.\n\n    Return the main content-type and a dictionary of options.\n\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 77194,
        "commit_id": "4cc10322a1c86c1137f5042a13d94d8017498bf7",
        "repo": "wagtail",
        "path": "wagtail/contrib/simple_translation/tests/test_wagtail_hooks.py",
        "file_name": "test_wagtail_hooks.py",
        "fun_name": "test_unmovable_translation_pages",
        "commit_message": "Sync tree: cascade unpublish, move and delete (#7984)\n\n* Add construct_synced_page_tree_list hook and use in page unpublish view\r\n\r\n* Implement construct_synced_page_tree_list in simple_translation\r\n\r\nbut only when sync page tree is enabled\r\n\r\n* Add hook documentation\r\n\r\n* Add construct_synced_page_tree_list hook tests (#8058)\r\n\r\n* Move translated and alias pages when WAGTAIL_I18N_ENABLED and WAGTAILSIMPLETRANSLATION_SYNC_PAGE_TREE are enabled\r\n\r\nCo-Authored-By: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com>\r\n\r\n* Delete corresponding translations when WAGTAIL_I18N_ENABLED and WAGTAILSIMPLETRANSLATION_SYNC_PAGE_TREE are true\r\n\r\nCo-Authored-By: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com>\r\n\r\n* Rename the hook to be more specific\r\n\r\n* Update singular string version in confirm_move.html\r\n\r\n* Update test test_translation_count_in_context\r\n\r\nCo-authored-by: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com>\r\nCo-authored-by: Karl Hobley <karl@kaed.uk>",
        "code": "def test_unmovable_translation_pages(self):\n        \n        self.login()\n\n        # BlogIndex needs translated pages before child pages can be translated\n        self.fr_blog_index = self.en_blog_index.copy_for_translation(self.fr_locale)\n        self.de_blog_index = self.en_blog_index.copy_for_translation(self.de_locale)\n\n        # Create blog_post copies for translation\n        self.fr_blog_post = self.en_blog_post.copy_for_translation(self.fr_locale)\n        self.de_blog_post = self.en_blog_post.copy_for_translation(self.de_locale)\n\n        # Confirm location of English blog post page before it is moved\n        # Should be living at /blog/blog-post/ right now. But will eventually\n        # exist at /blog-post/\n        self.assertEqual(self.en_blog_post.get_parent().id, self.en_blog_index.id)\n\n        # Confirm the fr and de blog post pages are under the blog index page\n        # We'll confirm these have not moved after ther POST request.\n        original_translated_parent_ids = [\n            p.id for p in self.en_blog_index.get_translations()\n        ]\n        self.assertIn(self.fr_blog_post.get_parent().id, original_translated_parent_ids)\n        self.assertIn(self.de_blog_post.get_parent().id, original_translated_parent_ids)\n\n        response = self.client.post(\n            reverse(\n                \"wagtailadmin_pages:move_confirm\",\n                args=(\n                    self.en_blog_post.id,\n                    self.en_homepage.id,\n                ),\n            ),\n            follow=True,\n        )\n        self.assertEqual(response.status_code, 200)\n\n        self.en_blog_post.refresh_from_db()\n        self.fr_blog_post.refresh_from_db()\n        self.de_blog_post.refresh_from_db()\n\n        # Check that the en_blog_post page has moved directly under the home page.\n        self.assertEqual(\n            self.en_blog_post.get_parent(update=True).id, self.en_homepage.id\n        )\n\n        # Check if the fr and de pages exist under their original parent page (/blog/)\n        self.assertIn(\n            self.fr_blog_post.get_parent(update=True).id, original_translated_parent_ids\n        )\n        self.assertIn(\n            self.de_blog_post.get_parent(update=True).id, original_translated_parent_ids\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 541,
        "n_words": 157,
        "vocab_size": 108,
        "complexity": 2,
        "nloc": 35,
        "token_counts": 264,
        "n_ast_nodes": 423,
        "n_identifiers": 29,
        "d_id": 16633,
        "documentation": {
            "docstring": "\n        Test that moving a page with WAGTAILSIMPLETRANSLATION_SYNC_PAGE_TREE\n        disabled doesn't apply to its translations.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 196277,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/geometry/point.py",
        "file_name": "point.py",
        "fun_name": "canberra_distance",
        "commit_message": "Updated import locations",
        "code": "def canberra_distance(self, p):\n        \n\n        s, p = Point._normalize_dimension(self, Point(p))\n        if self.is_zero and p.is_zero:\n            raise ValueError(\"Cannot project to the zero vector.\")\n        return Add(*((abs(a - b)/(abs(a) + abs(b))) for a, b in zip(s, p)))\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 70,
        "n_words": 31,
        "vocab_size": 31,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 75,
        "n_ast_nodes": 120,
        "n_identifiers": 13,
        "d_id": 47777,
        "documentation": {
            "docstring": "The Canberra Distance from self to point p.\n\n        Returns the weighted sum of horizontal and vertical distances to\n        point p.\n\n        Parameters\n        ==========\n\n        p : Point\n\n        Returns\n        =======\n\n        canberra_distance : The weighted sum of horizontal and vertical\n        distances to point p. The weight used is the sum of absolute values\n        of the coordinates.\n\n        Examples\n        ========\n\n        >>> from sympy import Point\n        >>> p1, p2 = Point(1, 1), Point(3, 3)\n        >>> p1.canberra_distance(p2)\n        1\n        >>> p1, p2 = Point(0, 0), Point(3, 3)\n        >>> p1.canberra_distance(p2)\n        2\n\n        Raises\n        ======\n\n        ValueError when both vectors are zero.\n\n        See Also\n        ========\n\n        sympy.geometry.point.Point.distance\n\n        ",
            "n_words": 93,
            "vocab_size": 58,
            "n_whitespaces": 275,
            "language": "en"
        }
    },
    {
        "id": 133858,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/agents/sac/tests/test_sac.py",
        "file_name": "test_sac.py",
        "fun_name": "test_sac_compilation",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_sac_compilation(self):\n        \n        config = sac.DEFAULT_CONFIG.copy()\n        config[\"Q_model\"] = sac.DEFAULT_CONFIG[\"Q_model\"].copy()\n        config[\"num_workers\"] = 0  # Run locally.\n        config[\"n_step\"] = 3\n        config[\"twin_q\"] = True\n        config[\"learning_starts\"] = 0\n        config[\"prioritized_replay\"] = True\n        config[\"rollout_fragment_length\"] = 10\n        config[\"train_batch_size\"] = 10\n        # If we use default buffer size (1e6), the buffer will take up\n        # 169.445 GB memory, which is beyond travis-ci's current (Mar 19, 2021)\n        # available system memory (8.34816 GB).\n        config[\"buffer_size\"] = 40000\n        # Test with saved replay buffer.\n        config[\"store_buffer_in_checkpoints\"] = True\n        num_iterations = 1\n\n        ModelCatalog.register_custom_model(\"batch_norm\", KerasBatchNormModel)\n        ModelCatalog.register_custom_model(\"batch_norm_torch\", TorchBatchNormModel)\n\n        image_space = Box(-1.0, 1.0, shape=(84, 84, 3))\n        simple_space = Box(-1.0, 1.0, shape=(3,))\n\n        tune.register_env(\n            \"random_dict_env\",\n            lambda _: RandomEnv(\n                {\n                    \"observation_space\": Dict(\n                        {\n                            \"a\": simple_space,\n                            \"b\": Discrete(2),\n                            \"c\": image_space,\n                        }\n                    ),\n                    \"action_space\": Box(-1.0, 1.0, shape=(1,)),\n                }\n            ),\n        )\n        tune.register_env(\n            \"random_tuple_env\",\n            lambda _: RandomEnv(\n                {\n                    \"observation_space\": Tuple(\n                        [simple_space, Discrete(2), image_space]\n                    ),\n                    \"action_space\": Box(-1.0, 1.0, shape=(1,)),\n                }\n            ),\n        )\n\n        for fw in framework_iterator(config, with_eager_tracing=True):\n            # Test for different env types (discrete w/ and w/o image, + cont).\n            for env in [\n                \"random_dict_env\",\n                \"random_tuple_env\",\n                # \"MsPacmanNoFrameskip-v4\",\n                \"CartPole-v0\",\n            ]:\n                print(\"Env={}\".format(env))\n                # Test making the Q-model a custom one for CartPole, otherwise,\n                # use the default model.\n                config[\"Q_model\"][\"custom_model\"] = (\n                    \"batch_norm{}\".format(\"_torch\" if fw == \"torch\" else \"\")\n                    if env == \"CartPole-v0\"\n                    else None\n                )\n                trainer = sac.SACTrainer(config=config, env=env)\n                for i in range(num_iterations):\n                    results = trainer.train()\n                    check_train_results(results)\n                    print(results)\n                check_compute_single_action(trainer)\n\n                # Test, whether the replay buffer is saved along with\n                # a checkpoint (no point in doing it for all frameworks since\n                # this is framework agnostic).\n                if fw == \"tf\" and env == \"CartPole-v0\":\n                    checkpoint = trainer.save()\n                    new_trainer = sac.SACTrainer(config, env=env)\n                    new_trainer.restore(checkpoint)\n                    # Get some data from the buffer and compare.\n                    data = trainer.local_replay_buffer.replay_buffers[\n                        \"default_policy\"\n                    ]._storage[: 42 + 42]\n                    new_data = new_trainer.local_replay_buffer.replay_buffers[\n                        \"default_policy\"\n                    ]._storage[: 42 + 42]\n                    check(data, new_data)\n                    new_trainer.stop()\n\n                trainer.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1496,
        "n_words": 285,
        "vocab_size": 177,
        "complexity": 8,
        "nloc": 74,
        "token_counts": 447,
        "n_ast_nodes": 735,
        "n_identifiers": 47,
        "d_id": 30126,
        "documentation": {
            "docstring": "Tests whether an SACTrainer can be built with all frameworks.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 88296,
        "commit_id": "102ca3bf902d7af977b0528f89fbd23415825fe3",
        "repo": "sentry",
        "path": "src/sentry/signals.py",
        "file_name": "signals.py",
        "fun_name": "send_robust",
        "commit_message": "ref(hybrid-cloud): Enforce silo isolation on many model tests (#40946)\n\nGreatly increase the number of stable hybrid cloud model tests, adding more hybrid cloud service interfaces.",
        "code": "def send_robust(self, sender, **named):\n        \n        responses = []\n        if not self.receivers or self.sender_receivers_cache.get(sender) is NO_RECEIVERS:\n            return responses\n\n        # Call each receiver with whatever arguments it can accept.\n        # Return a list of tuple pairs [(receiver, response), ... ].\n        for receiver in self._live_receivers(sender):\n            try:\n                response = receiver(signal=self, sender=sender, **named)\n            except Exception as err:\n                if \"pytest\" in sys.modules:\n                    if _receivers_that_raise is _all or receiver in _receivers_that_raise:\n                        raise\n\n                logging.error(\"signal.failure\", extra={\"receiver\": repr(receiver)}, exc_info=True)\n                responses.append((receiver, err))\n            else:\n                responses.append((receiver, response))\n        return responses\n\n\nbuffer_incr_complete = BetterSignal(providing_args=[\"model\", \"columns\", \"extra\", \"result\"])\npending_delete = BetterSignal(providing_args=[\"instance\", \"actor\"])\nevent_processed = BetterSignal(providing_args=[\"project\", \"event\"])\n\n# This signal should eventually be removed as we should not send\n# transactions through post processing\ntransaction_processed = BetterSignal(providing_args=[\"project\", \"event\"])\n\n# DEPRECATED\nevent_received = BetterSignal(providing_args=[\"ip\", \"project\"])\nevent_accepted = BetterSignal(providing_args=[\"ip\", \"data\", \"project\"])\n\n# Organization Onboarding Signals\nproject_created = BetterSignal(providing_args=[\"project\", \"user\", \"default_rules\"])\nfirst_event_pending = BetterSignal(providing_args=[\"project\", \"user\"])\n\nfirst_event_received = BetterSignal(providing_args=[\"project\", \"event\"])\nfirst_transaction_received = BetterSignal(providing_args=[\"project\", \"event\"])\nfirst_profile_received = BetterSignal(providing_args=[\"project\"])\nfirst_replay_received = BetterSignal(providing_args=[\"project\"])\nmember_invited = BetterSignal(providing_args=[\"member\", \"user\"])\nmember_joined = BetterSignal(providing_args=[\"member\", \"organization\"])\nissue_tracker_used = BetterSignal(providing_args=[\"plugin\", \"project\", \"user\"])\nplugin_enabled = BetterSignal(providing_args=[\"plugin\", \"project\", \"user\"])\n\nemail_verified = BetterSignal(providing_args=[\"email\"])\n\nmocks_loaded = BetterSignal(providing_args=[\"project\"])\n\nuser_feedback_received = BetterSignal(providing_args=[\"project\"])\n\nadvanced_search = BetterSignal(providing_args=[\"project\"])\nadvanced_search_feature_gated = BetterSignal(providing_args=[\"organization\", \"user\"])\nsave_search_created = BetterSignal(providing_args=[\"project\", \"user\"])\ninbound_filter_toggled = BetterSignal(providing_args=[\"project\"])\nsso_enabled = BetterSignal(providing_args=[\"organization\", \"user\", \"provider\"])\ndata_scrubber_enabled = BetterSignal(providing_args=[\"organization\"])\nalert_rule_created = BetterSignal(\n    providing_args=[\n        \"project\",\n        \"rule\",\n        \"user\",\n        \"rule_type\",\n        \"is_api_token\",\n        \"duplicate_rule\",\n        \"wizard_v3\",\n    ]\n)\nalert_rule_edited = BetterSignal(\n    providing_args=[\"project\", \"rule\", \"user\", \"rule_type\", \"is_api_token\"]\n)\nrepo_linked = BetterSignal(providing_args=[\"repo\", \"user\"])\nrelease_created = BetterSignal(providing_args=[\"release\"])\ndeploy_created = BetterSignal(providing_args=[\"deploy\"])\nownership_rule_created = BetterSignal(providing_args=[\"project\"])\n\n# issues\nissue_assigned = BetterSignal(providing_args=[\"project\", \"group\", \"user\"])\nissue_deleted = BetterSignal(providing_args=[\"group\", \"user\", \"delete_type\"])\nissue_resolved = BetterSignal(\n    providing_args=[\"organization_id\", \"project\", \"group\", \"user\", \"resolution_type\"]\n)\nissue_unresolved = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"transition_type\"])\nissue_ignored = BetterSignal(providing_args=[\"project\", \"user\", \"group_list\", \"activity_data\"])\nissue_unignored = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"transition_type\"])\nissue_mark_reviewed = BetterSignal(providing_args=[\"project\", \"user\", \"group\"])\n\n# comments\ncomment_created = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"activity_data\"])\ncomment_updated = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"activity_data\"])\ncomment_deleted = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"activity_data\"])\ninbox_in = BetterSignal(providing_args=[\"project\", \"user\", \"group\", \"reason\"])\ninbox_out = BetterSignal(\n    providing_args=[\"project\", \"user\", \"group\", \"action\", \"inbox_date_added\", \"referrer\"]\n)\n\nterms_accepted = BetterSignal(providing_args=[\"organization\", \"user\", \"ip_address\"])\nteam_created = BetterSignal(providing_args=[\"organization\", \"user\", \"team\"])\nintegration_added = BetterSignal(providing_args=[\"integration\", \"organization\", \"user\"])\nintegration_issue_created = BetterSignal(providing_args=[\"integration\", \"organization\", \"user\"])\nintegration_issue_linked = BetterSignal(providing_args=[\"integration\", \"organization\", \"user\"])\n\nmonitor_failed = BetterSignal(providing_args=[\"monitor\"])\n\n# experiments\njoin_request_created = BetterSignal(providing_args=[\"member\"])\njoin_request_link_viewed = BetterSignal(providing_args=[\"organization\"])\nuser_signup = BetterSignal(providing_args=[\"user\", \"source\"])\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 563,
        "n_words": 352,
        "vocab_size": 190,
        "complexity": 8,
        "nloc": 16,
        "token_counts": 128,
        "n_ast_nodes": 1481,
        "n_identifiers": 79,
        "d_id": 18372,
        "documentation": {
            "docstring": "\n        A reimplementation of send_robust which logs failures, thus recovering stacktraces.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 204538,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/handlers/exception.py",
        "file_name": "exception.py",
        "fun_name": "convert_exception_to_response",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def convert_exception_to_response(get_response):\n    \n    if asyncio.iscoroutinefunction(get_response):\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 10,
        "n_words": 4,
        "vocab_size": 4,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 35,
        "n_ast_nodes": 26,
        "n_identifiers": 4,
        "d_id": 50777,
        "documentation": {
            "docstring": "\n    Wrap the given get_response callable in exception-to-response conversion.\n\n    All exceptions will be converted. All known 4xx exceptions (Http404,\n    PermissionDenied, MultiPartParserError, SuspiciousOperation) will be\n    converted to the appropriate response, and all other exceptions will be\n    converted to 500 responses.\n\n    This decorator is automatically applied to all middleware to ensure that\n    no middleware leaks an exception and that the next middleware in the stack\n    can rely on getting a response instead of an exception.\n    ",
            "n_words": 72,
            "vocab_size": 51,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 22466,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "JsonParser.py",
        "file_name": "JsonParser.py",
        "fun_name": "convert_python_to_json",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def convert_python_to_json(self, par_data_dic, par_json_file=\"\"):\n        \n        if par_json_file:\n            with open(par_json_file, \"w\") as outfile:\n                return json.dump(par_data_dic, outfile)\n        else:\n            return json.dump(par_data_dic)\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 75,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 75,
        "n_identifiers": 8,
        "d_id": 4347,
        "documentation": {
            "docstring": "\n        this function converts dictionary of data to json string and store it in json file if\n        json file pass provided if not it only returns the json string\n        args:\n             par_data_dic: dictionary of data\n             par_json_file: the output json file\n        return: json string\n        ",
            "n_words": 41,
            "vocab_size": 26,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 271043,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/compile_utils.py",
        "file_name": "compile_utils.py",
        "fun_name": "_maybe_broadcast_to_outputs",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _maybe_broadcast_to_outputs(self, outputs, objects):\n        \n        if not self._should_broadcast(objects):\n            return objects\n\n        # When there is more than one Model output, this is needed to keep\n        # each Metric / Loss separate. When there is only one Model output,\n        # the user-supplied object should be used.\n        should_copy_objects = len(tf.nest.flatten(outputs)) > 1\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 101,
        "n_words": 48,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 54,
        "n_ast_nodes": 62,
        "n_identifiers": 10,
        "d_id": 80680,
        "documentation": {
            "docstring": "Determines if losses / metrics should be applied to all outputs.\n\n        NOTE: This method should only be called for Metrics / Losses, not for\n        y_true / sample_weight.\n\n        Args:\n          outputs: Model predictions.\n          objects: Arbitrary nested structure (e.g. of losses or metrics)\n\n        Returns:\n          Arbitrary nested structure of objects, maybe copied to each output.\n\n        Applies a Loss / Metric to all outputs.\n        ",
            "n_words": 59,
            "vocab_size": 44,
            "n_whitespaces": 128,
            "language": "en"
        }
    },
    {
        "id": 207061,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_custom_urls/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_post_save_add_redirect",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_post_save_add_redirect(self):\n        \n        post_data = {\"name\": \"John Doe\"}\n        self.assertEqual(Person.objects.count(), 0)\n        response = self.client.post(\n            reverse(\"admin_custom_urls:admin_custom_urls_person_add\"), post_data\n        )\n        persons = Person.objects.all()\n        self.assertEqual(len(persons), 1)\n        redirect_url = reverse(\n            \"admin_custom_urls:admin_custom_urls_person_history\", args=[persons[0].pk]\n        )\n        self.assertRedirects(response, redirect_url)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 120,
        "n_words": 28,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 87,
        "n_ast_nodes": 146,
        "n_identifiers": 18,
        "d_id": 51853,
        "documentation": {
            "docstring": "\n        ModelAdmin.response_post_save_add() controls the redirection after\n        the 'Save' button has been pressed when adding a new object.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 60993,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/req/req_install.py",
        "file_name": "req_install.py",
        "fun_name": "prepare_metadata",
        "commit_message": "upd; format",
        "code": "def prepare_metadata(self):\n        # type: () -> None\n        \n        assert self.source_dir\n\n        with indent_log():\n            self.metadata_directory = self._generate_metadata()\n\n        # Act on the newly generated metadata, based on the name and version.\n        if not self.name:\n            self._set_requirement()\n        else:\n            self.warn_on_mismatching_name()\n\n        self.assert_source_matches_version()\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 123,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 47,
        "n_ast_nodes": 88,
        "n_identifiers": 10,
        "d_id": 12377,
        "documentation": {
            "docstring": "Ensure that project metadata is available.\n\n        Under PEP 517, call the backend hook to prepare the metadata.\n        Under legacy processing, call setup.py egg-info.\n        ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 220267,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asynchat.py",
        "file_name": "asynchat.py",
        "fun_name": "set_terminator",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def set_terminator(self, term):\n        \n        if isinstance(term, str) and self.use_encoding:\n            term = bytes(term, self.encoding)\n        elif isinstance(term, int) and term < 0:\n            raise ValueError('the number of received bytes must be positive')\n        self.terminator = term\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 81,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 5,
        "nloc": 6,
        "token_counts": 52,
        "n_ast_nodes": 84,
        "n_identifiers": 11,
        "d_id": 55951,
        "documentation": {
            "docstring": "Set the input delimiter.\n\n        Can be a fixed string of any length, an integer, or None.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 612,
        "commit_id": "5dad7d57c63189553eaa303ece930c639c1b6196",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/node/common/action/run_class_method_smpc_action.py",
        "file_name": "run_class_method_smpc_action.py",
        "fun_name": "_object2proto",
        "commit_message": "modified action creation context to sharetensor level\ncreated global location for context retrieval during multiplication",
        "code": "def _object2proto(self) -> RunClassMethodSMPCAction_PB:\n        \n\n        return RunClassMethodSMPCAction_PB(\n            path=self.path,\n            _self=sy.serialize(self._self),\n            args=list(map(lambda x: sy.serialize(x), self.args)),\n            kwargs={k: sy.serialize(v) for k, v in self.kwargs.items()},\n            id_at_location=sy.serialize(self.id_at_location),\n            seed_id_locations=self.seed_id_locations,\n            address=sy.serialize(self.address),\n            msg_id=sy.serialize(self.id),\n        )\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 133,
        "n_words": 24,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 25,
        "token_counts": 115,
        "n_ast_nodes": 173,
        "n_identifiers": 20,
        "d_id": 91,
        "documentation": {
            "docstring": "Returns a protobuf serialization of self.\n\n        As a requirement of all objects which inherit from Serializable,\n        this method transforms the current object into the corresponding\n        Protobuf object so that it can be further serialized.\n\n        :return: returns a protobuf object\n        :rtype: RunClassMethodSMPCAction_PB\n\n        .. note::\n            This method is purely an internal method. Please use sy.serialize(object) or one of\n            the other public serialization methods if you wish to serialize an\n            object.\n        ",
            "n_words": 68,
            "vocab_size": 56,
            "n_whitespaces": 150,
            "language": "en"
        }
    },
    {
        "id": 53964,
        "commit_id": "38a7efafd45dbe64b292593461330a2de6499bb1",
        "repo": "prefect",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "pytest_collection_modifyitems",
        "commit_message": "Cleanup pytest service CLI options",
        "code": "def pytest_collection_modifyitems(session, config, items):\n    \n    not_services = set(config.getoption(\"--not-service\"))\n\n    if config.getoption(\"--all-services\"):\n        skip_exclude_services(not_services, items)\n\n        if config.getoption(\"--only-service\") or config.getoption(\"--only-services\"):\n            warnings.warn(\n                \"`--only-service` cannot be used with `--all-services`. \"\n                \"`--only-service` will be ignored.\"\n            )\n        return\n\n    only_services = set(config.getoption(\"--only-services\"))\n    if only_services:\n        for item in items:\n            item_services = {mark.args[0] for mark in item.iter_markers(name=\"service\")}\n            if not item_services:\n                item.add_marker(pytest.mark.skip(\"Only running tests for services.\"))\n\n        skip_exclude_services(not_services, items)\n\n        if config.getoption(\"--service\"):\n            warnings.warn(\n                \"`--service` cannot be used with `--only-services`. \"\n                \"`--service` will be ignored.\"\n            )\n        return\n\n    only_service = set(config.getoption(\"--only-service\"))\n    if only_service:\n        only_running_blurb = f\"Only running tests for service(s): {', '.join(repr(s) for s in only_service)}.\"\n        for item in items:\n            item_services = {mark.args[0] for mark in item.iter_markers(name=\"service\")}\n            not_in_only_services = only_services.difference(item_services)\n            if not_in_only_services:\n                item.add_marker(pytest.mark.skip(only_running_blurb))\n\n        if config.getoption(\"--service\"):\n            warnings.warn(\n                \"`--service` cannot be used with `--only-service`. \"\n                \"`--service` will be ignored.\"\n            )\n        return\n\n    run_services = set(config.getoption(\"--service\"))\n    for item in items:\n        item_services = {mark.args[0] for mark in item.iter_markers(name=\"service\")}\n        missing_services = item_services.difference(run_services)\n        if missing_services:\n            item.add_marker(\n                pytest.mark.skip(\n                    f\"Requires service(s): {', '.join(repr(s) for s in missing_services)}. \"\n                    \"Use '--service NAME' to include.\"\n                )\n            )\n\n\n@pytest.fixture(scope=\"session\")",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(scope=\"session\")",
        "n_ast_errors": 1,
        "ast_levels": 20,
        "n_whitespaces": 615,
        "n_words": 160,
        "vocab_size": 76,
        "complexity": 17,
        "nloc": 48,
        "token_counts": 284,
        "n_ast_nodes": 558,
        "n_identifiers": 31,
        "d_id": 10960,
        "documentation": {
            "docstring": "\n    Update tests to skip in accordance with service requests\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 72276,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_workflows.py",
        "file_name": "test_workflows.py",
        "fun_name": "test_approve_task_and_workflow",
        "commit_message": "Reformat with black",
        "code": "def test_approve_task_and_workflow(self):\n        \n        # Unset WAGTAIL_FINISH_WORKFLOW_ACTION - default action should be to publish\n        del settings.WAGTAIL_FINISH_WORKFLOW_ACTION\n        # Connect a mock signal handler to page_published signal\n        mock_handler = mock.MagicMock()\n        page_published.connect(mock_handler)\n\n        # Post\n        self.client.post(\n            reverse(\n                \"wagtailadmin_pages:workflow_action\",\n                args=(\n                    self.page.id,\n                    \"approve\",\n                    self.page.current_workflow_task_state.id,\n                ),\n            ),\n            {\"comment\": \"my comment\"},\n        )\n\n        # Check that the workflow was approved\n\n        workflow_state = WorkflowState.objects.get(\n            page=self.page, requested_by=self.submitter\n        )\n\n        self.assertEqual(workflow_state.status, workflow_state.STATUS_APPROVED)\n\n        # Check that the task was approved\n\n        task_state = workflow_state.current_task_state\n\n        self.assertEqual(task_state.status, task_state.STATUS_APPROVED)\n\n        # Check that the comment was added to the task state correctly\n\n        self.assertEqual(task_state.comment, \"my comment\")\n\n        page = Page.objects.get(id=self.page.id)\n        # Page must be live\n        self.assertTrue(page.live, \"Approving moderation failed to set live=True\")\n        # Page should now have no unpublished changes\n        self.assertFalse(\n            page.has_unpublished_changes,\n            \"Approving moderation failed to set has_unpublished_changes=False\",\n        )\n\n        # Check that the page_published signal was fired\n        self.assertEqual(mock_handler.call_count, 1)\n        mock_call = mock_handler.mock_calls[0][2]\n\n        self.assertEqual(mock_call[\"sender\"], self.page.specific_class)\n        self.assertEqual(mock_call[\"instance\"], self.page)\n        self.assertIsInstance(mock_call[\"instance\"], self.page.specific_class)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 513,
        "n_words": 135,
        "vocab_size": 89,
        "complexity": 1,
        "nloc": 33,
        "token_counts": 223,
        "n_ast_nodes": 365,
        "n_identifiers": 38,
        "d_id": 15869,
        "documentation": {
            "docstring": "\n        This posts to the approve task view and checks that the page was approved and published\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 64771,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/accounting_dimension/accounting_dimension.py",
        "file_name": "accounting_dimension.py",
        "fun_name": "delete_accounting_dimension",
        "commit_message": "style: format code with black",
        "code": "def delete_accounting_dimension(doc):\n\tdoclist = get_doctypes_with_dimensions()\n\n\tfrappe.db.sql(\n\t\t\n\t\t% (\"%s\", \", \".join([\"%s\"] * len(doclist))),  # nosec\n\t\ttuple([doc.fieldname] + doclist),\n\t)\n\n\tfrappe.db.sql(\n\t\t\n\t\t% (\"%s\", \", \".join([\"%s\"] * len(doclist))),  # nosec\n\t\ttuple([doc.fieldname] + doclist),\n\t)\n\n\tbudget_against_property = frappe.get_doc(\"Property Setter\", \"Budget-budget_against-options\")\n\tvalue_list = budget_against_property.value.split(\"\\n\")[3:]\n\n\tif doc.document_type in value_list:\n\t\tvalue_list.remove(doc.document_type)\n\n\tbudget_against_property.value = \"\\nCost Center\\nProject\\n\" + \"\\n\".join(value_list)\n\tbudget_against_property.save()\n\n\tfor doctype in doclist:\n\t\tfrappe.clear_cache(doctype=doctype)\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 40,
        "n_words": 57,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 155,
        "n_ast_nodes": 285,
        "n_identifiers": 22,
        "d_id": 13719,
        "documentation": {
            "docstring": "\n\t\tDELETE FROM `tabCustom Field`\n\t\tWHERE fieldname = %s\n\t\tAND dt IN (%s)\n\t\tDELETE FROM `tabProperty Setter`\n\t\tWHERE field_name = %s\n\t\tAND doc_type IN (%s)",
            "n_words": 24,
            "vocab_size": 16,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 257301,
        "commit_id": "738e008020f146ff9820c290311782f515749c48",
        "repo": "haystack",
        "path": "haystack/nodes/base.py",
        "file_name": "base.py",
        "fun_name": "_dispatch_run_batch",
        "commit_message": "Add `run_batch` method to all nodes and `Pipeline` to allow batch querying (#2481)\n\n* Add run_batch methods for batch querying\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix mypy\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix mypy\r\n\r\n* Fix linter\r\n\r\n* Fix tests\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix tests\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix mypy\r\n\r\n* Fix rest api test\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Add Doc strings\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Add batch_size as attribute to nodes supporting batching\r\n\r\n* Adapt error messages\r\n\r\n* Adapt type of filters in retrievers\r\n\r\n* Revert change about truncation_warning in summarizer\r\n\r\n* Unify multiple_doc_lists tests\r\n\r\n* Use smaller models in extractor tests\r\n\r\n* Add return types to JoinAnswers and RouteDocuments\r\n\r\n* Adapt return statements in reader's run_batch method\r\n\r\n* Allow list of filters\r\n\r\n* Adapt error messages\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix tests\r\n\r\n* Fix mypy\r\n\r\n* Adapt print_questions\r\n\r\n* Remove disabling warning about too many public methods\r\n\r\n* Add flag for pylint to disable warning about too many public methods in pipelines/base.py and document_stores/base.py\r\n\r\n* Add type check\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Adapt tutorial 11\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Add query_batch method for DCDocStore\r\n\r\n* Update Documentation & Code Style\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def _dispatch_run_batch(self, **kwargs):\n        \n        return self._dispatch_run_general(self.run_batch, **kwargs)\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 75061,
        "documentation": {
            "docstring": "\n        The Pipelines call this method when run_batch() is executed. This method in turn executes the\n        _dispatch_run_general() method with the correct run method.\n        ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 246381,
        "commit_id": "250104d357c17a1c87fa46af35bbf3612f4ef171",
        "repo": "synapse",
        "path": "tests/rest/client/test_account.py",
        "file_name": "test_account.py",
        "fun_name": "test_local_user_not_exists",
        "commit_message": "Implement account status endpoints (MSC3720) (#12001)\n\nSee matrix-org/matrix-doc#3720\r\n\r\nCo-authored-by: Sean Quah <8349537+squahtx@users.noreply.github.com>",
        "code": "def test_local_user_not_exists(self):\n        \n        user = \"@unknown:\" + self.hs.config.server.server_name\n\n        self._test_status(\n            users=[user],\n            expected_statuses={\n                user: {\n                    \"exists\": False,\n                },\n            },\n            expected_failures=[],\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 139,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 49,
        "n_ast_nodes": 80,
        "n_identifiers": 11,
        "d_id": 71189,
        "documentation": {
            "docstring": "Tests that the account status endpoints correctly reports that a user doesn't\n        exist.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 204175,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/messages/storage/base.py",
        "file_name": "base.py",
        "fun_name": "add",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def add(self, level, message, extra_tags=\"\"):\n        \n        if not message:\n            return\n        # Check that the message level is not less than the recording level.\n        level = int(level)\n        if level < self.level:\n            return\n        # Add the message.\n        self.added_new = True\n        message = Message(level, message, extra_tags=extra_tags)\n        self._queued_messages.append(message)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 128,
        "n_words": 43,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 58,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 50670,
        "documentation": {
            "docstring": "\n        Queue a message to be stored.\n\n        The message is only queued if it contained something and its level is\n        not less than the recording level (``self.level``).\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 176450,
        "commit_id": "cc1db275efc709cb964ce88abbfa877798d58c10",
        "repo": "networkx",
        "path": "networkx/readwrite/nx_shp.py",
        "file_name": "nx_shp.py",
        "fun_name": "read_shp",
        "commit_message": "Minor improvements from general code readthrough (#5414)\n\n* Add deprecated directive to reversed docstring.\r\n\r\n* Add missing dep directives to shpfiles.\r\n\r\n* Remove defn of INF sentinel.\r\n\r\n* typo.\r\n\r\n* str -> comment in forloop.\r\n\r\n* STY: appropriate casing for var name.",
        "code": "def read_shp(path, simplify=True, geom_attrs=True, strict=True):\n    \n    msg = (\n        \"read_shp is deprecated and will be removed in 3.0.\"\n        \"See https://networkx.org/documentation/latest/auto_examples/index.html#geospatial.\"\n    )\n    warnings.warn(msg, DeprecationWarning, stacklevel=2)\n    try:\n        from osgeo import ogr\n    except ImportError as err:\n        raise ImportError(\"read_shp requires OGR: http://www.gdal.org/\") from err\n\n    if not isinstance(path, str):\n        return\n\n    net = nx.DiGraph()\n    shp = ogr.Open(path)\n    if shp is None:\n        raise RuntimeError(f\"Unable to open {path}\")\n    for lyr in shp:\n        fields = [x.GetName() for x in lyr.schema]\n        for f in lyr:\n            g = f.geometry()\n            if g is None:\n                if strict:\n                    raise nx.NetworkXError(\"Bad data: feature missing geometry\")\n                else:\n                    continue\n            flddata = [f.GetField(f.GetFieldIndex(x)) for x in fields]\n            attributes = dict(zip(fields, flddata))\n            attributes[\"ShpName\"] = lyr.GetName()\n            # Note:  Using layer level geometry type\n            if g.GetGeometryType() == ogr.wkbPoint:\n                net.add_node((g.GetPoint_2D(0)), **attributes)\n            elif g.GetGeometryType() in (ogr.wkbLineString, ogr.wkbMultiLineString):\n                for edge in edges_from_line(g, attributes, simplify, geom_attrs):\n                    e1, e2, attr = edge\n                    net.add_edge(e1, e2)\n                    net[e1][e2].update(attr)\n            else:\n                if strict:\n                    raise nx.NetworkXError(\n                        f\"GeometryType {g.GetGeometryType()} not supported\"\n                    )\n\n    return net\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 573,
        "n_words": 150,
        "vocab_size": 109,
        "complexity": 14,
        "nloc": 41,
        "token_counts": 280,
        "n_ast_nodes": 463,
        "n_identifiers": 50,
        "d_id": 41911,
        "documentation": {
            "docstring": "Generates a networkx.DiGraph from shapefiles.\n\n    .. deprecated:: 2.6\n\n       read_shp is deprecated and will be removed in NetworkX 3.0.\n       See https://networkx.org/documentation/latest/auto_examples/index.html#geospatial.\n\n    Point geometries are\n    translated into nodes, lines into edges. Coordinate tuples are used as\n    keys. Attributes are preserved, line geometries are simplified into start\n    and end coordinates. Accepts a single shapefile or directory of many\n    shapefiles.\n\n    \"The Esri Shapefile or simply a shapefile is a popular geospatial vector\n    data format for geographic information systems software [1]_.\"\n\n    Parameters\n    ----------\n    path : file or string\n       File, directory, or filename to read.\n\n    simplify:  bool\n        If True, simplify line geometries to start and end coordinates.\n        If False, and line feature geometry has multiple segments, the\n        non-geometric attributes for that feature will be repeated for each\n        edge comprising that feature.\n\n    geom_attrs: bool\n        If True, include the Wkb, Wkt and Json geometry attributes with\n        each edge.\n\n        NOTE:  if these attributes are available, write_shp will use them\n        to write the geometry.  If nodes store the underlying coordinates for\n        the edge geometry as well (as they do when they are read via\n        this method) and they change, your geomety will be out of sync.\n\n    strict: bool\n        If True, raise NetworkXError when feature geometry is missing or\n        GeometryType is not supported.\n        If False, silently ignore missing or unsupported geometry in features.\n\n    Returns\n    -------\n    G : NetworkX graph\n\n    Raises\n    ------\n    ImportError\n       If ogr module is not available.\n\n    RuntimeError\n       If file cannot be open or read.\n\n    NetworkXError\n       If strict=True and feature is missing geometry or GeometryType is\n       not supported.\n\n    Examples\n    --------\n    >>> G = nx.read_shp(\"test.shp\")  # doctest: +SKIP\n\n    References\n    ----------\n    .. [1] https://en.wikipedia.org/wiki/Shapefile\n    ",
            "n_words": 262,
            "vocab_size": 163,
            "n_whitespaces": 486,
            "language": "en"
        }
    },
    {
        "id": 155358,
        "commit_id": "2bb9a1fab7b0092974853e616dfd5e7ed98f085d",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "__copy__",
        "commit_message": "REFACTOR-#5363: introduce partition constructor; move `add_to_apply_calls` impl in base class (#5354)\n\nSigned-off-by: Myachev <anatoly.myachev@intel.com>",
        "code": "def __copy__(self):\n        \n        # Shallow copy.\n        return self.__constructor__(\n            self.gpu_manager, self.key, self._length_cache, self._width_cache\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 51,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 27,
        "n_ast_nodes": 43,
        "n_identifiers": 7,
        "d_id": 36353,
        "documentation": {
            "docstring": "\n        Create a copy of this object.\n\n        Returns\n        -------\n        cuDFOnRayDataframePartition\n            A copy of this object.\n        ",
            "n_words": 14,
            "vocab_size": 10,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 115431,
        "commit_id": "fc9776d9b342f873cbb3f36fd39955b9e1ea6f76",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/sqlite_handler/sqlite_handler.py",
        "file_name": "sqlite_handler.py",
        "fun_name": "disconnect",
        "commit_message": "added connection_args and connection_args_example dicts",
        "code": "def disconnect(self):\r\n        \r\n\r\n        if self.is_connected is False:\r\n            return\r\n\r\n        self.connection.close()\r\n        self.is_connected = False\r\n        return self.is_connected\r\n\r",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 59,
        "n_words": 13,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 30,
        "n_ast_nodes": 52,
        "n_identifiers": 5,
        "d_id": 25459,
        "documentation": {
            "docstring": "\r\n        Close any existing connections.\r\n        ",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 240298,
        "commit_id": "c95b4fa4388f29e50b6966e45c94c5980013a01d",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/graph_objs/_figurewidget.py",
        "file_name": "_figurewidget.py",
        "fun_name": "for_each_smith",
        "commit_message": "type annotations for chainable Figure methods",
        "code": "def for_each_smith(self, fn, selector=None, row=None, col=None) -> \"FigureWidget\":\n        \n        for obj in self.select_smiths(selector=selector, row=row, col=col):\n            fn(obj)\n\n        return self\n",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 49,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 32,
        "token_counts": 48,
        "n_ast_nodes": 73,
        "n_identifiers": 8,
        "d_id": 68409,
        "documentation": {
            "docstring": "\n        Apply a function to all smith objects that satisfy the\n        specified selection criteria\n\n        Parameters\n        ----------\n        fn:\n            Function that inputs a single smith object.\n        selector: dict, function, or None (default None)\n            Dict to use as selection criteria.\n            smith objects will be selected if they contain\n            properties corresponding to all of the dictionary's keys, with\n            values that exactly match the supplied values. If None\n            (the default), all smith objects are selected. If a\n            function, it must be a function accepting a single argument and\n            returning a boolean. The function will be called on each\n            smith and those for which the function returned True will\n            be in the selection.\n        row, col: int or None (default None)\n            Subplot row and column index of smith objects to select.\n            To select smith objects by row and column, the Figure\n            must have been created using plotly.subplots.make_subplots.\n            If None (the default), all smith objects are selected.\n        Returns\n        -------\n        self\n            Returns the FigureWidget object that the method was called on\n        ",
            "n_words": 161,
            "vocab_size": 96,
            "n_whitespaces": 404,
            "language": "en"
        }
    },
    {
        "id": 225565,
        "commit_id": "32359f3e93f5ca7778b9f7c3d6d92f49a629c84c",
        "repo": "mkdocs",
        "path": "mkdocs/structure/pages.py",
        "file_name": "pages.py",
        "fun_name": "is_homepage",
        "commit_message": "Relative links end with slash even for homepage links (#3022)\n\nFixes #3015",
        "code": "def is_homepage(self) -> bool:\n        \n        return self.is_top_level and self.is_index and self.file.url in ('.', './', 'index.html')\n\n    previous_page: Optional[Page]\n    \n\n    next_page: Optional[Page]\n    \n\n    parent: Optional[Section]\n    \n\n    children: None = None\n    \n\n    is_section: bool = False\n    \n\n    is_page: bool = True\n    \n\n    is_link: bool = False\n    \n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 99,
        "n_words": 36,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 30,
        "n_ast_nodes": 143,
        "n_identifiers": 17,
        "d_id": 57470,
        "documentation": {
            "docstring": "Evaluates to `True` for the homepage of the site and `False` for all other pages.The [page][mkdocs.structure.pages.Page] object for the previous page or `None`.\n    The value will be `None` if the current page is the first item in the site navigation\n    or if the current page is not included in the navigation at all.The [page][mkdocs.structure.pages.Page] object for the next page or `None`.\n    The value will be `None` if the current page is the last item in the site navigation\n    or if the current page is not included in the navigation at all.The immediate parent of the page in the site navigation. `None` if the\n    page is at the top level.Pages do not contain children and the attribute is always `None`.Indicates that the navigation object is a \"section\" object. Always `False` for page objects.Indicates that the navigation object is a \"page\" object. Always `True` for page objects.Indicates that the navigation object is a \"link\" object. Always `False` for page objects.",
            "n_words": 158,
            "vocab_size": 57,
            "n_whitespaces": 172,
            "language": "en"
        }
    },
    {
        "id": 1393,
        "commit_id": "dadbb7dfe1062f94e2d95e7670d0a7a4602460c4",
        "repo": "PySyft",
        "path": "packages/syft/tests/syft/core/io/route_test.py",
        "file_name": "route_test.py",
        "fun_name": "test_solo_route_send_immediate_msg_with_reply",
        "commit_message": "fixed signature of send_immediate_msg_with_reply\n\n- changing default timeouts",
        "code": "def test_solo_route_send_immediate_msg_with_reply() -> None:\n    \n    node = MockNode()\n    destination = SpecificLocation()\n    server = VirtualServerConnection(node=node)\n    connection = VirtualClientConnection(server=server)\n\n    h_solo = SoloRoute(destination=destination, connection=connection)\n    msg = construct_dummy_message(SignedImmediateSyftMessageWithReply)\n    ret = h_solo.send_immediate_msg_with_reply(msg=msg)\n\n    assert isinstance(\n        ret,\n        SignedImmediateSyftMessageWithoutReply,\n    )\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 75,
        "n_words": 31,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 69,
        "n_ast_nodes": 114,
        "n_identifiers": 18,
        "d_id": 187,
        "documentation": {
            "docstring": "Test SoloRoute.send_immediate_msg_with_reply method works.",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 3,
            "language": "en"
        }
    },
    {
        "id": 260513,
        "commit_id": "91f02270a8f49e3e52882dc0fa634eff4d138fc8",
        "repo": "scikit-learn",
        "path": "sklearn/utils/_param_validation.py",
        "file_name": "_param_validation.py",
        "fun_name": "validate_parameter_constraints",
        "commit_message": "MAINT Add one-sided set differences for clarity in param validation (#23772)\n\n\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def validate_parameter_constraints(parameter_constraints, params, caller_name):\n    \n    if len(set(parameter_constraints) - set(params)) != 0:\n        raise ValueError(\n            f\"The parameter constraints {list(parameter_constraints)}\"\n            \" contain unexpected parameters\"\n            f\" {set(parameter_constraints) - set(params)}\"\n        )\n\n    for param_name, param_val in params.items():\n        # We allow parameters to not have a constraint so that third party estimators\n        # can inherit from sklearn estimators without having to necessarily use the\n        # validation tools.\n        if param_name not in parameter_constraints:\n            continue\n\n        constraints = parameter_constraints[param_name]\n\n        if constraints == \"no_validation\":\n            continue\n\n        constraints = [make_constraint(constraint) for constraint in constraints]\n\n        for constraint in constraints:\n            if constraint.is_satisfied_by(param_val):\n                # this constraint is satisfied, no need to check further.\n                break\n        else:\n            # No constraint is satisfied, raise with an informative message.\n\n            # Ignore constraints that we don't want to expose in the error message,\n            # i.e. options that are for internal purpose or not officially supported.\n            constraints = [\n                constraint for constraint in constraints if not constraint.hidden\n            ]\n\n            if len(constraints) == 1:\n                constraints_str = f\"{constraints[0]}\"\n            else:\n                constraints_str = (\n                    f\"{', '.join([str(c) for c in constraints[:-1]])} or\"\n                    f\" {constraints[-1]}\"\n                )\n\n            raise ValueError(\n                f\"The {param_name!r} parameter of {caller_name} must be\"\n                f\" {constraints_str}. Got {param_val!r} instead.\"\n            )\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 25,
        "n_whitespaces": 590,
        "n_words": 181,
        "vocab_size": 117,
        "complexity": 11,
        "nloc": 32,
        "token_counts": 137,
        "n_ast_nodes": 330,
        "n_identifiers": 20,
        "d_id": 76307,
        "documentation": {
            "docstring": "Validate types and values of given parameters.\n\n    Parameters\n    ----------\n    parameter_constraints : dict or {\"no_validation\"}\n        If \"no_validation\", validation is skipped for this parameter.\n\n        If a dict, it must be a dictionary `param_name: list of constraints`.\n        A parameter is valid if it satisfies one of the constraints from the list.\n        Constraints can be:\n        - an Interval object, representing a continuous or discrete range of numbers\n        - the string \"array-like\"\n        - the string \"sparse matrix\"\n        - the string \"random_state\"\n        - callable\n        - None, meaning that None is a valid value for the parameter\n        - any type, meaning that any instance of this type is valid\n        - a StrOptions object, representing a set of strings\n        - the string \"boolean\"\n        - the string \"verbose\"\n\n    params : dict\n        A dictionary `param_name: param_value`. The parameters to validate against the\n        constraints.\n\n    caller_name : str\n        The name of the estimator or function or method that called this function.\n    ",
            "n_words": 149,
            "vocab_size": 89,
            "n_whitespaces": 286,
            "language": "en"
        }
    },
    {
        "id": 180689,
        "commit_id": "b1dfc9a172440e9c9736566f326ba339ff559604",
        "repo": "gradio",
        "path": "gradio/event_queue.py",
        "file_name": "event_queue.py",
        "fun_name": "notify_clients",
        "commit_message": "Release new queue beta (#1969)\n\n* queue-refactor-backend (#1489)\r\n\r\n* queue-refactor-backend\r\n\r\n- create a template for the new design\r\n\r\n* queue-refactor-backend\r\n\r\n- clean after the old queue\r\n\r\n* queue-refactor-backend\r\n\r\n- add basic test to websocket endpoint\r\n\r\n* queue-refactor-backend\r\n\r\n- small fix\r\n\r\n* queue-refactor-backend\r\n\r\n- debugs&fixes&finalizations\r\n- test the flow with postman\r\n\r\n* queue-refactor-backend\r\n\r\n- tweaks on websocket closing\r\n\r\n* queue-refactor-backend\r\n\r\n- cleanup\r\n\r\n* queue-refactor-backend\r\n\r\n- cleanup & tweaks\r\n\r\n* queue-refactor-backend\r\n\r\n- cleanup & tweaks\r\n\r\n* queue-refactor-backend\r\n\r\n- cleanup & tweaks\r\n- correct the exception handling\r\n\r\n* queue-refactor-backend\r\n\r\n- add websockets dependency\r\n\r\n* queue-refactor-backend\r\n- reformat\r\n\r\n* queue-refactor-backend\r\n- add single event test\r\n\r\n* queue-refactor-backend\r\n- tweaks\r\n- remove outdated tests\r\n\r\n* queue-refactor-backend\r\n- reformat\r\n\r\n* queue-refactor-backend\r\n- reformat\r\n\r\n* queue-refactor-backend\r\n- reformat\r\n\r\n* queue-refactor-backend\r\n- add Queue configurations to Blocks.launch()\r\n- add live_queue_update to send estimations whenever a job gets fetched from the Queue\r\n\r\n* queue-refactor-backend\r\n- add Queue configurations to Blocks.launch()\r\n- add live_queue_update to send estimations whenever a job gets fetched from the Queue\r\n\r\n* queue-refactor-backend\r\n- tweaks\r\n\r\n* queue-refactor-backend\r\n- make SLEEP_WHEN_FREE shorter\r\n\r\nCo-authored-by: Ali Abid <aabid94@gmail.com>\r\n\r\n* Add estimation parameters to queue (#1889)\r\n\r\n* - tweaks on Estimation\r\n\r\n* version\r\n\r\n* Revert \"version\"\r\n\r\nThis reverts commit bd1f4d7bfe3658a4967b93126859a62a511a70e2.\r\n\r\n* some fix and tweaks\r\n\r\n* implement queue frontend (#1950)\r\n\r\n* implement queue frontend\r\n\r\n* fix types\r\n\r\n* fix ws endpoint in build mode\r\n\r\n* cleanup\r\n\r\n* Queue tweaks (#1909)\r\n\r\n* tweaks on estimation payload\r\n\r\n* Queue keep ws connections open (#1910)\r\n\r\n* 1. keep ws connections open after the event process is completed\r\n2. do not send estimations periodically if live queue updates is open\r\n\r\n* fix calculation\r\n\r\n* 1. tweaks on event_queue\r\n\r\n* fix issue - create new ws for each request\r\n\r\n* format\r\n\r\n* fix\r\n\r\n* fix tests\r\n\r\n* fix tests\r\n\r\n* tets\r\n\r\n* test\r\n\r\n* changes\r\n\r\n* changes\r\n\r\n* changes\r\n\r\n* change'\r\n\r\n* wtf\r\n\r\n* changes\r\n\r\n* changes\r\n\r\n* file perms\r\n\r\n* Release queue beta v1 (#1971)\r\n\r\n* - release the new queue\r\n\r\n* - bypass the issue in the tests\r\n- rewrite the lost part in the codebase\r\n\r\n* - add concurrent queue example (#1978)\r\n\r\n* rank_eta calc\r\n\r\n* Queue fixes (#1981)\r\n\r\n* change\r\n\r\n* format\r\n\r\n* - comment out queue tests as they dont work well\r\n\r\n* - reformat\r\n\r\n* Update gradio/event_queue.py\r\n\r\nCo-authored-by: Ömer Faruk Özdemir <farukozderim@gmail.com>\r\n\r\n* changes\r\n\r\n* changes\r\n\r\n* change\r\n\r\n* weird fix\r\n\r\nCo-authored-by: Ömer Faruk Özdemir <farukozderim@gmail.com>\r\n\r\n* release-queue-v3 (#1988)\r\n\r\n* Fix frontend queuing to target secure WSS (#1996)\r\n\r\n* change\r\n\r\n* format\r\n\r\n* changes\r\n\r\n* queue-concurrency-tweaks (#2002)\r\n\r\n1. make gather_data and broadcast_estimation sequential instead of concurrent because they were deleting elements at the same time and raising expections which was lowering the performance\r\n\r\n* Update Queue API, documentation (#2026)\r\n\r\n* changes\r\n\r\n* changes\r\n\r\n* fixes\r\n\r\n* changes\r\n\r\n* change\r\n\r\n* fix\r\n\r\nCo-authored-by: Ömer Faruk Özdemir <farukozderim@gmail.com>\r\nCo-authored-by: pngwn <hello@pngwn.io>",
        "code": "async def notify_clients(cls) -> None:\n        \n        while not cls.STOP:\n            await asyncio.sleep(cls.UPDATE_INTERVALS)\n            if cls.EVENT_QUEUE:\n                await cls.broadcast_estimations()\n",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 65,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 34,
        "n_ast_nodes": 61,
        "n_identifiers": 8,
        "d_id": 43215,
        "documentation": {
            "docstring": "\n        Notify clients about events statuses in the queue periodically.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 305522,
        "commit_id": "56278a4421209a475558600d220906e35df80fe0",
        "repo": "core",
        "path": "homeassistant/helpers/device_registry.py",
        "file_name": "device_registry.py",
        "fun_name": "async_purge_expired_orphaned_devices",
        "commit_message": "Simplify device registry (#77715)\n\n* Simplify device registry\r\n\r\n* Fix test fixture\r\n\r\n* Update homeassistant/helpers/device_registry.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update device_registry.py\r\n\r\n* Remove dead code\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "def async_purge_expired_orphaned_devices(self) -> None:\n        \n        now_time = time.time()\n        for deleted_device in list(self.deleted_devices.values()):\n            if deleted_device.orphaned_timestamp is None:\n                continue\n\n            if (\n                deleted_device.orphaned_timestamp + ORPHANED_DEVICE_KEEP_SECONDS\n                < now_time\n            ):\n                del self.deleted_devices[deleted_device.id]\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 140,
        "n_words": 26,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 57,
        "n_ast_nodes": 93,
        "n_identifiers": 11,
        "d_id": 104308,
        "documentation": {
            "docstring": "Purge expired orphaned devices from the registry.\n\n        We need to purge these periodically to avoid the database\n        growing without bound.\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 202398,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/csrf_tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_https_bad_referer",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_https_bad_referer(self):\n        \n        req = self._get_POST_request_with_token()\n        req._is_secure_override = True\n        req.META[\"HTTP_HOST\"] = \"www.example.com\"\n        req.META[\"HTTP_REFERER\"] = \"https://www.evil.org/somepage\"\n        req.META[\"SERVER_PORT\"] = \"443\"\n        mw = CsrfViewMiddleware(post_form_view)\n        response = mw.process_view(req, post_form_view, (), {})\n        self.assertContains(\n            response,\n            \"Referer checking failed - https://www.evil.org/somepage does not \"\n            \"match any trusted origins.\",\n            status_code=403,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 156,
        "n_words": 42,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 78,
        "n_ast_nodes": 138,
        "n_identifiers": 13,
        "d_id": 50106,
        "documentation": {
            "docstring": "\n        A POST HTTPS request with a bad referer is rejected\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 153042,
        "commit_id": "58bbcc37477866d19c8b092a0e1974a4f0baa586",
        "repo": "modin",
        "path": "modin/core/dataframe/algebra/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "call",
        "commit_message": "REFACTOR-#2656: Update modin to fit algebra (code only) (#3717)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>\r\nCo-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>\r\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: Rehan Durrani <rehan@ponder.io>",
        "code": "def call(cls, map_func, reduce_func=None, **call_kwds):\n        \n        if isinstance(map_func, str):\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 107,
        "n_ast_nodes": 36,
        "n_identifiers": 7,
        "d_id": 35226,
        "documentation": {
            "docstring": "\n        Build template GroupBy aggregation function.\n\n        Resulted function is applied in parallel via TreeReduce algorithm.\n\n        Parameters\n        ----------\n        map_func : str, dict or callable(pandas.DataFrameGroupBy) -> pandas.DataFrame\n            If `str` this parameter will be treated as a function name to register,\n            so `map_func` and `reduce_func` will be grabbed from `groupby_reduce_functions`.\n            If dict or callable then this will be treated as a function to apply to the `GroupByObject`\n            at the map phase.\n        reduce_func : str, dict or callable(pandas.DataFrameGroupBy) -> pandas.DataFrame, optional\n            Function to apply to the `GroupByObject` at the reduce phase. If not specified\n            will be set the same as 'map_func'.\n        **call_kwds : kwargs\n            Kwargs that will be passed to the returned function.\n\n        Returns\n        -------\n        callable\n            Function that takes query compiler and executes GroupBy aggregation\n            with TreeReduce algorithm.\n        ",
            "n_words": 123,
            "vocab_size": 74,
            "n_whitespaces": 300,
            "language": "en"
        }
    },
    {
        "id": 192382,
        "commit_id": "3aa2a93d1e2df140866e1937767b83dc27dcf89e",
        "repo": "vision",
        "path": "references/optical_flow/train.py",
        "file_name": "train.py",
        "fun_name": "_evaluate",
        "commit_message": "RAFT training reference Improvement (#5590)\n\n* Change optical flow train.py function name from validate to evaluate so it is similar to other references\r\n\r\n* Add --device as parameter and enable to run in non distributed mode\r\n\r\n* Format with ufmt\r\n\r\n* Fix unneccessary param and bug\r\n\r\n* Enable saving the optimizer and scheduler on the checkpoint\r\n\r\n* Fix bug when evaluate before resume and save or load model without ddp\r\n\r\n* Fix case where --train-dataset is None\r\n\r\nCo-authored-by: Nicolas Hug <nicolashug@fb.com>",
        "code": "def _evaluate(model, args, val_dataset, *, padder_mode, num_flow_updates=None, batch_size=None, header=None):\n    \n    batch_size = batch_size or args.batch_size\n    device = torch.device(args.device)\n\n    model.eval()\n\n    if args.distributed:\n        sampler = torch.utils.data.distributed.DistributedSampler(val_dataset, shuffle=False, drop_last=True)\n    else:\n        sampler = torch.utils.data.SequentialSampler(val_dataset)\n\n    val_loader = torch.utils.data.DataLoader(\n        val_dataset,\n        sampler=sampler,\n        batch_size=batch_size,\n        pin_memory=True,\n        num_workers=args.num_workers,\n    )\n\n    num_flow_updates = num_flow_updates or args.num_flow_updates\n",
        "url": "https://github.com/pytorch/vision.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 119,
        "n_words": 43,
        "vocab_size": 33,
        "complexity": 9,
        "nloc": 35,
        "token_counts": 256,
        "n_ast_nodes": 190,
        "n_identifiers": 23,
        "d_id": 46885,
        "documentation": {
            "docstring": "Helper function to compute various metrics (epe, etc.) for a model on a given dataset.\n\n    We process as many samples as possible with ddp, and process the rest on a single worker.\n    ",
            "n_words": 32,
            "vocab_size": 27,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 21259,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/build_env.py",
        "file_name": "build_env.py",
        "fun_name": "_create_standalone_pip",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def _create_standalone_pip() -> Generator[str, None, None]:\n    \n    source = pathlib.Path(pip_location).resolve().parent\n\n    # Return the current instance if `source` is not a directory. We can't build\n    # a zip from this, and it likely means the instance is already standalone.\n    if not source.is_dir():\n        yield str(source)\n        return\n\n    with TempDirectory(kind=\"standalone-pip\") as tmp_dir:\n        pip_zip = os.path.join(tmp_dir.path, \"__env_pip__.zip\")\n        kwargs = {}\n        if sys.version_info >= (3, 8):\n            kwargs[\"strict_timestamps\"] = False\n        with zipfile.ZipFile(pip_zip, \"w\", **kwargs) as zf:\n            for child in source.rglob(\"*\"):\n                zf.write(child, child.relative_to(source.parent).as_posix())\n        yield os.path.join(pip_zip, \"pip\")\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 181,
        "n_words": 77,
        "vocab_size": 63,
        "complexity": 4,
        "nloc": 19,
        "token_counts": 142,
        "n_ast_nodes": 244,
        "n_identifiers": 28,
        "d_id": 3739,
        "documentation": {
            "docstring": "Create a \"standalone pip\" zip file.\n\n    The zip file's content is identical to the currently-running pip.\n    It will be used to install requirements into the build environment.\n    ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 124152,
        "commit_id": "7d3ceb222c8af98a5c101b1c28ab37ffcb0a3793",
        "repo": "ray",
        "path": "python/ray/tests/kuberay/test_autoscaling_config.py",
        "file_name": "test_autoscaling_config.py",
        "fun_name": "_get_ray_cr_with_overrides",
        "commit_message": "[kuberay][autoscaler] Improve CPU, GPU, and memory detection. (#26219)\n\nThis PR improves the autoscaler's resource detection logic",
        "code": "def _get_ray_cr_with_overrides() -> dict:\n    \n    cr = _get_basic_ray_cr()\n    cr[\"spec\"][\"workerGroupSpecs\"][0][\"rayStartParams\"][\"memory\"] = \"300000000\"\n    # num-gpus rayStartParam with no gpus in container limits\n    cr[\"spec\"][\"workerGroupSpecs\"][0][\"rayStartParams\"][\"num-gpus\"] = \"100\"\n    # num-gpus rayStartParam overriding gpus in container limits\n    cr[\"spec\"][\"workerGroupSpecs\"][1][\"rayStartParams\"][\"num-gpus\"] = \"100\"\n    cr[\"spec\"][\"workerGroupSpecs\"][0][\"rayStartParams\"][\"num-cpus\"] = \"100\"\n    return cr\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 65,
        "n_words": 38,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 86,
        "n_ast_nodes": 169,
        "n_identifiers": 4,
        "d_id": 27527,
        "documentation": {
            "docstring": "CR with memory, cpu, and gpu overrides from rayStartParams.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 309483,
        "commit_id": "b52a8ba37a5e5e05b80beddff06b116371941d86",
        "repo": "core",
        "path": "tests/components/tradfri/test_util.py",
        "file_name": "test_util.py",
        "fun_name": "test_from_percentage",
        "commit_message": "Bump pytradfri to 8.0.1 and fix fan preset mode \"Auto\" bug (#63920)\n\n* Move util functions\r\n\r\n* Fix errors\r\n\r\n* Revert changes\r\n\r\n* Fix tests\r\n\r\n* Use self.async_set_percentage()\r\n\r\n* Fix calculation functions and associated tests\r\n\r\n* Handle case of 0\r\n\r\n* Update tests/components/tradfri/test_util.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update tests/components/tradfri/test_util.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update tests/components/tradfri/test_util.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Handle case of 0\r\n\r\n* Update homeassistant/components/tradfri/fan.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "def test_from_percentage(percentage, expected_result):\n    \n    assert _from_fan_percentage(percentage) == expected_result\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 15,
        "n_ast_nodes": 26,
        "n_identifiers": 4,
        "d_id": 108183,
        "documentation": {
            "docstring": "Test that we can convert percentage value to fan speed.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 109920,
        "commit_id": "df6f95703b60348e01603f98a439b133da2938a0",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/art3d.py",
        "file_name": "art3d.py",
        "fun_name": "set_3d_properties",
        "commit_message": "Improve mpl_toolkit documentation",
        "code": "def set_3d_properties(self, z=0, zdir='z'):\n        \n        self._z = z\n        self._dir_vec = get_dir_vector(zdir)\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 41,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 54,
        "n_identifiers": 8,
        "d_id": 23827,
        "documentation": {
            "docstring": "\n        Set the *z* position and direction of the text.\n\n        Parameters\n        ----------\n        z : float\n            The z-position in 3D space.\n        zdir : {'x', 'y', 'z', 3-tuple}\n            The direction of the text. Default: 'z'.\n            See `.get_dir_vector` for a description of the values.\n        ",
            "n_words": 40,
            "vocab_size": 31,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 224171,
        "commit_id": "372384d8102ddb4be6360f44d1bfddb8b45435a4",
        "repo": "mkdocs",
        "path": "mkdocs/tests/structure/nav_tests.py",
        "file_name": "nav_tests.py",
        "fun_name": "test_nav_missing_page",
        "commit_message": "Some manual changes ahead of formatting code with Black",
        "code": "def test_nav_missing_page(self):\n        nav_cfg = [\n            {'Home': 'index.md'},\n        ]\n        expected = dedent(\n            \n        )\n        cfg = load_config(nav=nav_cfg, site_url='http://example.com/')\n        fs = [\n            File('index.md', cfg['docs_dir'], cfg['site_dir'], cfg['use_directory_urls']),\n            File('page_not_in_nav.md', cfg['docs_dir'], cfg['site_dir'], cfg['use_directory_urls'])\n        ]\n        files = Files(fs)\n        site_navigation = get_navigation(files, cfg)\n        self.assertEqual(str(site_navigation).strip(), expected)\n        self.assertEqual(len(site_navigation.items), 1)\n        self.assertEqual(len(site_navigation.pages), 1)\n        for file in files:\n            self.assertIsInstance(file.page, Page)\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 193,
        "n_words": 47,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 146,
        "n_ast_nodes": 240,
        "n_identifiers": 25,
        "d_id": 57224,
        "documentation": {
            "docstring": "\n            Page(title='Home', url='/')\n            ",
            "n_words": 2,
            "vocab_size": 2,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 133953,
        "commit_id": "297341e107daee1ea3aff991ae8ea8c90993c683",
        "repo": "ray",
        "path": "python/ray/tests/test_client.py",
        "file_name": "test_client.py",
        "fun_name": "test_large_remote_call",
        "commit_message": "[Test][Client] Only start ray once in client tests (#28835)\n\nIt looks like we're frequently starting and shutting down Ray in this test because `ray_start_client_server` isn't connecting to the Ray created by `ray_start_regular_shared`, and is instead starting a new Ray head process every time it launches.\r\n\r\nRay client tests are failing frequently with:\r\n\r\n```\r\n[2022-10-06 07:31:46,253 E 13235 13751] core_worker_process.cc:277: The core worker has already been shutdown. This happens when the language frontend accesses the Ray's worker after it is shutdown. The process will exit\r\n```\r\n\r\nWhich is probably caused by having multiple ray clusters running simultaneous, with some shutting down asynchronously. This refactor forces all of the tests in the module to use the same Ray cluster.\r\n\r\nAlso fixes two other sources of potential flakiness:\r\n* Joins the thread in test_client_thread_safe (seems like this has a bad interaction when the client server is cleaned up)\r\n* Calls ray.get in `test_stdout_log_stream`, to make sure that the remote function is done running before we try searching for its output\r\n\r\nShould also have the happy side effect of speeding up test_client.\r\n\r\nRan the `Small & Client` tests (regular and external redis) twice each, no flakes, and windows version of test_client.",
        "code": "def test_large_remote_call(call_ray_start_shared):\n    \n    with ray_start_client_server_for_address(call_ray_start_shared) as ray:\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 12,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 157,
        "n_ast_nodes": 29,
        "n_identifiers": 4,
        "d_id": 30161,
        "documentation": {
            "docstring": "\n    Test remote calls with large (multiple chunk) arguments\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 109334,
        "commit_id": "7c67cadfd903a26b3d56dd2c95faf2365367fd1a",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "legend",
        "commit_message": "Highlight information about avoiding labels in legend",
        "code": "def legend(self, *args, **kwargs):\n        \n        handles, labels, extra_args, kwargs = mlegend._parse_legend_args(\n                [self],\n                *args,\n                **kwargs)\n        if len(extra_args):\n            raise TypeError('legend only accepts two non-keyword arguments')\n        self.legend_ = mlegend.Legend(self, handles, labels, **kwargs)\n        self.legend_._remove_method = self._remove_legend\n        return self.legend_\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 131,
        "n_words": 33,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 75,
        "n_ast_nodes": 116,
        "n_identifiers": 15,
        "d_id": 23529,
        "documentation": {
            "docstring": "\n        Place a legend on the Axes.\n\n        Call signatures::\n\n            legend()\n            legend(handles, labels)\n            legend(handles=handles)\n            legend(labels)\n\n        The call signatures correspond to the following different ways to use\n        this method:\n\n        **1. Automatic detection of elements to be shown in the legend**\n\n        The elements to be added to the legend are automatically determined,\n        when you do not pass in any extra arguments.\n\n        In this case, the labels are taken from the artist. You can specify\n        them either at artist creation or by calling the\n        :meth:`~.Artist.set_label` method on the artist::\n\n            ax.plot([1, 2, 3], label='Inline label')\n            ax.legend()\n\n        or::\n\n            line, = ax.plot([1, 2, 3])\n            line.set_label('Label via method')\n            ax.legend()\n\n        .. note::\n            Specific artists can be excluded from the automatic legend element\n            selection by using a label starting with an underscore, \"_\".\n            A string starting with an underscore is the default label for all\n            artists, so calling `.Axes.legend` without any arguments and\n            without setting the labels manually will result in no legend being\n            drawn.\n\n\n        **2. Explicitly listing the artists and labels in the legend**\n\n        For full control of which artists have a legend entry, it is possible\n        to pass an iterable of legend artists followed by an iterable of\n        legend labels respectively::\n\n            ax.legend([line1, line2, line3], ['label1', 'label2', 'label3'])\n\n\n        **3. Explicitly listing the artists in the legend**\n\n        This is similar to 2, but the labels are taken from the artists'\n        label properties. Example::\n\n            line1, = ax.plot([1, 2, 3], label='label1')\n            line2, = ax.plot([1, 2, 3], label='label2')\n            ax.legend(handles=[line1, line2])\n\n\n        **4. Labeling existing plot elements**\n\n        .. admonition:: Discouraged\n\n            This call signature is discouraged, because the relation between\n            plot elements and labels is only implicit by their order and can\n            easily be mixed up.\n\n        To make a legend for all artists on an Axes, call this function with\n        an iterable of strings, one for each legend item. For example::\n\n            ax.plot([1, 2, 3])\n            ax.plot([5, 6, 7])\n            ax.legend(['First line', 'Second line'])\n\n\n        Parameters\n        ----------\n        handles : sequence of `.Artist`, optional\n            A list of Artists (lines, patches) to be added to the legend.\n            Use this together with *labels*, if you need full control on what\n            is shown in the legend and the automatic mechanism described above\n            is not sufficient.\n\n            The length of handles and labels should be the same in this\n            case. If they are not, they are truncated to the smaller length.\n\n        labels : list of str, optional\n            A list of labels to show next to the artists.\n            Use this together with *handles*, if you need full control on what\n            is shown in the legend and the automatic mechanism described above\n            is not sufficient.\n\n        Returns\n        -------\n        `~matplotlib.legend.Legend`\n\n        Other Parameters\n        ----------------\n        %(_legend_kw_doc)s\n\n        See Also\n        --------\n        .Figure.legend\n\n        Notes\n        -----\n        Some artists are not supported by this function.  See\n        :doc:`/tutorials/intermediate/legend_guide` for details.\n\n        Examples\n        --------\n        .. plot:: gallery/text_labels_and_annotations/legend.py\n        ",
            "n_words": 446,
            "vocab_size": 237,
            "n_whitespaces": 1141,
            "language": "en"
        }
    },
    {
        "id": 269969,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/callbacks.py",
        "file_name": "callbacks.py",
        "fun_name": "_disallow_batch_hooks_in_ps_strategy",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _disallow_batch_hooks_in_ps_strategy(self):\n        \n        # pylint: disable=protected-access\n        strategy = tf.distribute.get_strategy()\n        if strategy._should_use_with_coordinator:\n            unsupported_callbacks = []\n            for cb in self.callbacks:\n                # These Callbacks can accept RemoteValues directly.\n                if getattr(cb, \"_supports_tf_logs\", False):\n                    continue\n                if (\n                    cb._implements_train_batch_hooks()\n                    or cb._implements_test_batch_hooks()\n                    or cb._implements_predict_batch_hooks()\n                ):\n                    unsupported_callbacks.append(cb)\n            if unsupported_callbacks:\n                raise ValueError(\n                    \"Batch-level `Callback`s are not supported with \"\n                    \"`ParameterServerStrategy`. Found unsupported \"\n                    f\"callbacks: {unsupported_callbacks}\"\n                )\n        # pylint: enable=protected-access\n\n\n@keras_export(\"keras.callbacks.Callback\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.callbacks.Callback\")",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 369,
        "n_words": 60,
        "vocab_size": 51,
        "complexity": 8,
        "nloc": 19,
        "token_counts": 80,
        "n_ast_nodes": 156,
        "n_identifiers": 17,
        "d_id": 80365,
        "documentation": {
            "docstring": "Error out if batch-level callbacks are passed with PSStrategy.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 21648,
        "commit_id": "8a4d2eb130fd173466310f59df607ea59bfc44a5",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/dependencies.py",
        "file_name": "dependencies.py",
        "fun_name": "compatible_abstract_dep",
        "commit_message": "Vendor in latest requirements lib and pip-shims in order to drop packaging and resolve differences in sourcing it.",
        "code": "def compatible_abstract_dep(self, other):\n        \n\n        from .requirements import Requirement\n\n        if len(self.candidates) == 1 and next(iter(self.candidates)).editable:\n            return self\n        elif len(other.candidates) == 1 and next(iter(other.candidates)).editable:\n            return other\n        new_specifiers = self.specifiers & other.specifiers\n        markers = set(self.markers) if self.markers else set()\n        if other.markers:\n            markers.add(other.markers)\n        new_markers = None\n        if markers:\n            new_markers = Marker(\" or \".join(str(m) for m in sorted(markers)))\n        new_ireq = copy.deepcopy(self.requirement.ireq)\n        new_ireq.req.specifier = new_specifiers\n        new_ireq.req.marker = new_markers\n        new_requirement = Requirement.from_line(format_requirement(new_ireq))\n        compatible_versions = self.compatible_versions(other)\n        if isinstance(compatible_versions, AbstractDependency):\n            return compatible_versions\n        candidates = [\n            c\n            for c in self.candidates\n            if parse(version_from_ireq(c)) in compatible_versions\n        ]\n        dep_dict = {}\n        candidate_strings = [format_requirement(c) for c in candidates]\n        for c in candidate_strings:\n            if c in self.dep_dict:\n                dep_dict[c] = self.dep_dict.get(c)\n        return AbstractDependency(\n            name=self.name,\n            specifiers=new_specifiers,\n            markers=new_markers,\n            candidates=candidates,\n            requirement=new_requirement,\n            parent=self.parent,\n            dep_dict=dep_dict,\n            finder=self.finder,\n        )\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 473,
        "n_words": 117,
        "vocab_size": 76,
        "complexity": 15,
        "nloc": 40,
        "token_counts": 285,
        "n_ast_nodes": 444,
        "n_identifiers": 44,
        "d_id": 3973,
        "documentation": {
            "docstring": "Merge this abstract dependency with another one.\n\n        Return the result of the merge as a new abstract dependency.\n\n        :param other: An abstract dependency to merge with\n        :type other: :class:`~requirementslib.models.dependency.AbstractDependency`\n        :return: A new, combined abstract dependency\n        :rtype: :class:`~requirementslib.models.dependency.AbstractDependency`\n        ",
            "n_words": 37,
            "vocab_size": 27,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 110839,
        "commit_id": "f16da868d016363c4cd734b2abd6535230b094df",
        "repo": "matplotlib",
        "path": "lib/matplotlib/colors.py",
        "file_name": "colors.py",
        "fun_name": "shade_normals",
        "commit_message": "[Doc] Fix ndarray-links for arguments",
        "code": "def shade_normals(self, normals, fraction=1.):\n        \n\n        intensity = normals.dot(self.direction)\n\n        # Apply contrast stretch\n        imin, imax = intensity.min(), intensity.max()\n        intensity *= fraction\n\n        # Rescale to 0-1, keeping range before contrast stretch\n        # If constant slope, keep relative scaling (i.e. flat should be 0.5,\n        # fully occluded 0, etc.)\n        if (imax - imin) > 1e-6:\n            # Strictly speaking, this is incorrect. Negative values should be\n            # clipped to 0 because they're fully occluded. However, rescaling\n            # in this manner is consistent with the previous implementation and\n            # visually appears better than a \"hard\" clip.\n            intensity -= imin\n            intensity /= (imax - imin)\n        intensity = np.clip(intensity, 0, 1)\n\n        return intensity\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 248,
        "n_words": 105,
        "vocab_size": 79,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 78,
        "n_ast_nodes": 124,
        "n_identifiers": 13,
        "d_id": 24318,
        "documentation": {
            "docstring": "\n        Calculate the illumination intensity for the normal vectors of a\n        surface using the defined azimuth and elevation for the light source.\n\n        Imagine an artificial sun placed at infinity in some azimuth and\n        elevation position illuminating our surface. The parts of the surface\n        that slope toward the sun should brighten while those sides facing away\n        should become darker.\n\n        Parameters\n        ----------\n        fraction : number, optional\n            Increases or decreases the contrast of the hillshade.  Values\n            greater than one will cause intermediate values to move closer to\n            full illumination or shadow (and clipping any values that move\n            beyond 0 or 1). Note that this is not visually or mathematically\n            the same as vertical exaggeration.\n\n        Returns\n        -------\n        `~numpy.ndarray`\n            A 2D array of illumination values between 0-1, where 0 is\n            completely in shadow and 1 is completely illuminated.\n        ",
            "n_words": 132,
            "vocab_size": 96,
            "n_whitespaces": 302,
            "language": "en"
        }
    },
    {
        "id": 243970,
        "commit_id": "301d4a2d4cfe1cdb62608e2892924be3e67e3098",
        "repo": "mmdetection",
        "path": "mmdet/datasets/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_loading_pipeline",
        "commit_message": "[Feature] Support visualization for Panoptic Segmentation (#7041)\n\n* First commit of v2\r\n\r\n* split the functions\r\n\r\n* Support to show panoptic result\r\n\r\n* temp\r\n\r\n* Support to show gt\r\n\r\n* support show gt\r\n\r\n* fix lint\r\n\r\n* Support to browse datasets\r\n\r\n* Fix unit tests\r\n\r\n* Fix findContours\r\n\r\n* fix comments\r\n\r\n* Fix pre-commit\r\n\r\n* fix lint\r\n\r\n* Add the type of an argument",
        "code": "def get_loading_pipeline(pipeline):\n    \n    loading_pipeline_cfg = []\n    for cfg in pipeline:\n        obj_cls = PIPELINES.get(cfg['type'])\n        # TODO：use more elegant way to distinguish loading modules\n        if obj_cls is not None and obj_cls in (LoadImageFromFile,\n                                               LoadAnnotations,\n                                               LoadPanopticAnnotations):\n            loading_pipeline_cfg.append(cfg)\n    assert len(loading_pipeline_cfg) == 2, \\\n        'The data pipeline in your config file must include ' \\\n        'loading image and annotations related pipeline.'\n    return loading_pipeline_cfg\n\n\n@HOOKS.register_module()",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "@HOOKS.register_module()",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 210,
        "n_words": 58,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 62,
        "n_ast_nodes": 113,
        "n_identifiers": 14,
        "d_id": 70172,
        "documentation": {
            "docstring": "Only keep loading image and annotations related configuration.\n\n    Args:\n        pipeline (list[dict]): Data pipeline configs.\n\n    Returns:\n        list[dict]: The new pipeline list with only keep\n            loading image and annotations related configuration.\n\n    Examples:\n        >>> pipelines = [\n        ...    dict(type='LoadImageFromFile'),\n        ...    dict(type='LoadAnnotations', with_bbox=True),\n        ...    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),\n        ...    dict(type='RandomFlip', flip_ratio=0.5),\n        ...    dict(type='Normalize', **img_norm_cfg),\n        ...    dict(type='Pad', size_divisor=32),\n        ...    dict(type='DefaultFormatBundle'),\n        ...    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])\n        ...    ]\n        >>> expected_pipelines = [\n        ...    dict(type='LoadImageFromFile'),\n        ...    dict(type='LoadAnnotations', with_bbox=True)\n        ...    ]\n        >>> assert expected_pipelines ==\\\n        ...        get_loading_pipeline(pipelines)\n    ",
            "n_words": 79,
            "vocab_size": 50,
            "n_whitespaces": 271,
            "language": "en"
        }
    },
    {
        "id": 251888,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http2.py",
        "file_name": "test_http2.py",
        "fun_name": "test_cancel_during_response_hook",
        "commit_message": "make it black!",
        "code": "def test_cancel_during_response_hook(tctx):\n    \n    playbook, cff = start_h2_client(tctx)\n    flow = Placeholder(HTTPFlow)\n    server = Placeholder(Server)\n\n    assert (\n        playbook\n        >> DataReceived(\n            tctx.client,\n            cff.build_headers_frame(\n                example_request_headers, flags=[\"END_STREAM\"]\n            ).serialize(),\n        )\n        << http.HttpRequestHeadersHook(flow)\n        >> reply()\n        << http.HttpRequestHook(flow)\n        >> reply()\n        << OpenConnection(server)\n        >> reply(None)\n        << SendData(server, b\"GET / HTTP/1.1\\r\\nHost: example.com\\r\\n\\r\\n\")\n        >> DataReceived(server, b\"HTTP/1.1 204 No Content\\r\\n\\r\\n\")\n        << http.HttpResponseHeadersHook(flow)\n        << CloseConnection(server)\n        >> reply(to=-2)\n        << http.HttpResponseHook(flow)\n        >> DataReceived(\n            tctx.client, cff.build_rst_stream_frame(1, ErrorCodes.CANCEL).serialize()\n        )\n        >> reply(to=-2)\n    )\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 30,
        "n_whitespaces": 267,
        "n_words": 64,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 175,
        "n_ast_nodes": 266,
        "n_identifiers": 29,
        "d_id": 73878,
        "documentation": {
            "docstring": "\n    Test that we properly handle the case of the following event sequence:\n        - we receive a server response\n        - we trigger the response hook\n        - the client cancels the stream\n        - the response hook completes\n\n    Given that we have already triggered the response hook, we don't want to trigger the error hook.\n    ",
            "n_words": 52,
            "vocab_size": 32,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 206035,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "__getitem__",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def __getitem__(self, name):\n        \n        if name in MEDIA_TYPES:\n            return Media(**{str(name): getattr(self, \"_\" + name)})\n        raise KeyError('Unknown media type \"%s\"' % name)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 52,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 40,
        "n_ast_nodes": 69,
        "n_identifiers": 8,
        "d_id": 51333,
        "documentation": {
            "docstring": "Return a Media object that only contains media of the given type.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 123418,
        "commit_id": "b1881129b6201ffd7d2ea01754ca2c76479776a3",
        "repo": "sqlmap",
        "path": "lib/core/agent.py",
        "file_name": "agent.py",
        "fun_name": "payload",
        "commit_message": "Bug for JSON-like bug (#5013)",
        "code": "def payload(self, place=None, parameter=None, value=None, newValue=None, where=None):\n        \n\n        if conf.direct:\n            return self.payloadDirect(newValue)\n\n        retVal = \"\"\n\n        if kb.forceWhere:\n            where = kb.forceWhere\n        elif where is None and isTechniqueAvailable(getTechnique()):\n            where = getTechniqueData().where\n\n        if kb.injection.place is not None:\n            place = kb.injection.place\n\n        if kb.injection.parameter is not None:\n            parameter = kb.injection.parameter\n\n        paramString = conf.parameters[place]\n        paramDict = conf.paramDict[place]\n        origValue = getUnicode(paramDict[parameter])\n        newValue = getUnicode(newValue) if newValue else newValue\n        base64Encoding = re.sub(r\" \\(.+\", \"\", parameter) in conf.base64Parameter\n\n        if place == PLACE.URI or BOUNDED_INJECTION_MARKER in origValue:\n            paramString = origValue\n            if place == PLACE.URI:\n                origValue = origValue.split(kb.customInjectionMark)[0]\n            else:\n                origValue = filterNone(re.search(_, origValue.split(BOUNDED_INJECTION_MARKER)[0]) for _ in (r\"\\w+\\Z\", r\"[^\\\"'><]+\\Z\", r\"[^ ]+\\Z\"))[0].group(0)\n            origValue = origValue[origValue.rfind('/') + 1:]\n            for char in ('?', '=', ':', ',', '&'):\n                if char in origValue:\n                    origValue = origValue[origValue.rfind(char) + 1:]\n        elif place == PLACE.CUSTOM_POST:\n            paramString = origValue\n            origValue = origValue.split(kb.customInjectionMark)[0]\n            if kb.postHint in (POST_HINT.SOAP, POST_HINT.XML):\n                origValue = re.split(r\"['\\\">]\", origValue)[-1]\n            elif kb.postHint in (POST_HINT.JSON, POST_HINT.JSON_LIKE):\n                origValue = extractRegexResult(r\":\\s*['\\\"]?(?P<result>\\w+\\Z)\", origValue) or extractRegexResult(r'(?s)[\\s:]*(?P<result>[^\"\\[,]+\\Z)', origValue)\n            else:\n                _ = extractRegexResult(r\"(?s)(?P<result>[^\\s<>{}();'\\\"&]+\\Z)\", origValue) or \"\"\n                origValue = _.split('=', 1)[1] if '=' in _ else \"\"\n        elif place == PLACE.CUSTOM_HEADER:\n            paramString = origValue\n            origValue = origValue[origValue.find(',') + 1:]\n            origValue = origValue.split(kb.customInjectionMark)[0]\n            match = re.search(r\"([^;]+)=(?P<value>[^;]*);?\\Z\", origValue)\n            if match:\n                origValue = match.group(\"value\")\n            elif ',' in paramString:\n                header = paramString.split(',')[0]\n\n                if header.upper() == HTTP_HEADER.AUTHORIZATION.upper():\n                    origValue = origValue.split(' ')[-1].split(':')[-1]\n\n        origValue = origValue or \"\"\n\n        if value is None:\n            if where == PAYLOAD.WHERE.ORIGINAL:\n                value = origValue\n            elif where == PAYLOAD.WHERE.NEGATIVE:\n                if conf.invalidLogical:\n                    match = re.search(r\"\\A[^ ]+\", newValue)\n                    newValue = newValue[len(match.group() if match else \"\"):]\n                    _ = randomInt(2)\n                    value = \"%s%s AND %s LIKE %s\" % (origValue, match.group() if match else \"\", _, _ + 1)\n                elif conf.invalidBignum:\n                    value = randomInt(6)\n                elif conf.invalidString:\n                    value = randomStr(6)\n                else:\n                    if newValue.startswith(\"-\"):\n                        value = \"\"\n                    else:\n                        value = \"-%s\" % randomInt()\n            elif where == PAYLOAD.WHERE.REPLACE:\n                value = \"\"\n            else:\n                value = origValue\n\n            newValue = \"%s%s\" % (value, newValue)\n\n        newValue = self.cleanupPayload(newValue, origValue) or \"\"\n\n        if base64Encoding:\n            _newValue = newValue\n            _origValue = origValue\n\n            if newValue:\n                newValue = newValue.replace(BOUNDARY_BACKSLASH_MARKER, '\\\\')\n                newValue = self.adjustLateValues(newValue)\n\n            # TODO: support for POST_HINT\n            newValue = \"%s%s%s\" % (BOUNDED_BASE64_MARKER, newValue, BOUNDED_BASE64_MARKER)\n\n            if parameter in kb.base64Originals:\n                origValue = kb.base64Originals[parameter]\n            else:\n                origValue = encodeBase64(origValue, binary=False, encoding=conf.encoding or UNICODE_ENCODING)\n\n        if place in (PLACE.URI, PLACE.CUSTOM_POST, PLACE.CUSTOM_HEADER):\n            _ = \"%s%s\" % (origValue, kb.customInjectionMark)\n\n            if kb.postHint == POST_HINT.JSON and not isNumber(newValue) and '\"%s\"' % _ not in paramString:\n                newValue = '\"%s\"' % self.addPayloadDelimiters(newValue)\n            elif kb.postHint == POST_HINT.JSON_LIKE and not isNumber(newValue) and re.search(r\"['\\\"]%s['\\\"]\" % re.escape(_), paramString) is None:\n                newValue = \"'%s'\" % self.addPayloadDelimiters(newValue)\n            else:\n                newValue = self.addPayloadDelimiters(newValue)\n\n            if newValue:\n                newValue = newValue.replace(kb.customInjectionMark, REPLACEMENT_MARKER)\n                retVal = paramString.replace(_, newValue)\n\n            retVal = retVal.replace(kb.customInjectionMark, \"\").replace(REPLACEMENT_MARKER, kb.customInjectionMark)\n        elif BOUNDED_INJECTION_MARKER in paramDict[parameter]:\n            if base64Encoding:\n                retVal = paramString.replace(\"%s%s\" % (_origValue, BOUNDED_INJECTION_MARKER), _newValue)\n                match = re.search(r\"(%s)=([^&]*)\" % re.sub(r\" \\(.+\", \"\", parameter), retVal)\n                if match:\n                    retVal = retVal.replace(match.group(0), \"%s=%s\" % (match.group(1), encodeBase64(match.group(2), binary=False, encoding=conf.encoding or UNICODE_ENCODING)))\n            else:\n                retVal = paramString.replace(\"%s%s\" % (origValue, BOUNDED_INJECTION_MARKER), self.addPayloadDelimiters(newValue))\n        elif place in (PLACE.USER_AGENT, PLACE.REFERER, PLACE.HOST):\n            retVal = paramString.replace(origValue, self.addPayloadDelimiters(newValue))\n        else:",
        "url": "https://github.com/sqlmapproject/sqlmap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 1802,
        "n_words": 474,
        "vocab_size": 188,
        "complexity": 58,
        "nloc": 118,
        "token_counts": 1255,
        "n_ast_nodes": 1733,
        "n_identifiers": 83,
        "d_id": 27346,
        "documentation": {
            "docstring": "\n        This method replaces the affected parameter with the SQL\n        injection statement to request\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 101327,
        "commit_id": "326110f09d45dbdce2e490fa1ae4b1208e5efe2c",
        "repo": "faceswap",
        "path": "lib/multithreading.py",
        "file_name": "multithreading.py",
        "fun_name": "is_alive",
        "commit_message": "bugfix - timelapse image loader\nmultithreading.py - typing + docs",
        "code": "def is_alive(self) -> bool:\n        \n        return any(thread.is_alive() for thread in self._threads)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 23,
        "n_ast_nodes": 39,
        "n_identifiers": 6,
        "d_id": 20745,
        "documentation": {
            "docstring": " Check if any threads are still alive\n\n        Returns\n        -------\n        bool\n            ``True`` if any threads are alive. ``False`` if no threads are alive\n        ",
            "n_words": 22,
            "vocab_size": 14,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 22785,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "sha1.py",
        "file_name": "sha1.py",
        "fun_name": "expand_block",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def expand_block(self, block):\n        \n        w = list(struct.unpack(\">16L\", block)) + [0] * 64\n        for i in range(16, 80):\n            w[i] = self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16]), 1)\n        return w\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 75,
        "n_words": 36,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 80,
        "n_ast_nodes": 122,
        "n_identifiers": 10,
        "d_id": 4456,
        "documentation": {
            "docstring": "\n        Takes a bytestring-block of length 64, unpacks it to a list of integers and returns a\n        list of 80 integers pafter some bit operations\n        ",
            "n_words": 24,
            "vocab_size": 18,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 247440,
        "commit_id": "f63bedef07360216a8de71dc38f00f1aea503903",
        "repo": "synapse",
        "path": "tests/rest/client/test_relations.py",
        "file_name": "test_relations.py",
        "fun_name": "test_redact_relation_annotation",
        "commit_message": "Invalidate caches when an event with a relation is redacted. (#12121)\n\nThe caches for the target of the relation must be cleared\r\nso that the bundled aggregations are re-calculated after\r\nthe redaction is processed.",
        "code": "def test_redact_relation_annotation(self) -> None:\n        \n        channel = self._send_relation(RelationTypes.ANNOTATION, \"m.reaction\", \"a\")\n        self.assertEqual(200, channel.code, channel.json_body)\n        to_redact_event_id = channel.json_body[\"event_id\"]\n\n        channel = self._send_relation(\n            RelationTypes.ANNOTATION, \"m.reaction\", \"a\", access_token=self.user2_token\n        )\n        self.assertEqual(200, channel.code, channel.json_body)\n        unredacted_event_id = channel.json_body[\"event_id\"]\n\n        # Both relations should exist.\n        event_ids, relations = self._make_relation_requests()\n        self.assertCountEqual(event_ids, [to_redact_event_id, unredacted_event_id])\n        self.assertEquals(\n            relations[\"m.annotation\"],\n            {\"chunk\": [{\"type\": \"m.reaction\", \"key\": \"a\", \"count\": 2}]},\n        )\n\n        # Both relations appear in the aggregation.\n        chunk = self._get_aggregations()\n        self.assertEqual(chunk, [{\"type\": \"m.reaction\", \"key\": \"a\", \"count\": 2}])\n\n        # Redact one of the reactions.\n        self._redact(to_redact_event_id)\n\n        # The unredacted relation should still exist.\n        event_ids, relations = self._make_relation_requests()\n        self.assertEquals(event_ids, [unredacted_event_id])\n        self.assertEquals(\n            relations[\"m.annotation\"],\n            {\"chunk\": [{\"type\": \"m.reaction\", \"key\": \"a\", \"count\": 1}]},\n        )\n\n        # The unredacted aggregation should still exist.\n        chunk = self._get_aggregations()\n        self.assertEqual(chunk, [{\"type\": \"m.reaction\", \"key\": \"a\", \"count\": 1}])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 352,
        "n_words": 115,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 33,
        "token_counts": 250,
        "n_ast_nodes": 435,
        "n_identifiers": 21,
        "d_id": 71672,
        "documentation": {
            "docstring": "\n        Test that annotations of an event are properly handled after the\n        annotation is redacted.\n\n        The redacted relation should not be included in bundled aggregations or\n        the response to relations.\n        ",
            "n_words": 29,
            "vocab_size": 28,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 5647,
        "commit_id": "aa9251872136235be81f5d5f6d97eec00928a992",
        "repo": "airbyte",
        "path": "airbyte-cdk/python/unit_tests/sources/declarative/parsers/test_yaml_parser.py",
        "file_name": "test_yaml_parser.py",
        "fun_name": "test_collision",
        "commit_message": "Low-code connectors: configurable source from yaml (#13038)\n\n* checkout from alex/cac\r\n\r\n* checkout from alex/cac\r\n\r\n* checkout from alex/cac\r\n\r\n* checkout from alex/cac\r\n\r\n* Add missing tests\r\n\r\n* Add missing files\r\n\r\n* Add missing tests\r\n\r\n* add missing file\r\n\r\n* missing file\r\n\r\n* missing file\r\n\r\n* sengrid low code connector\r\n\r\n* rename\r\n\r\n* doc\r\n\r\n* doc\r\n\r\n* remove broken test\r\n\r\n* rename\r\n\r\n* jinja dependency\r\n\r\n* Add comment\r\n\r\n* comment\r\n\r\n* comment\r\n\r\n* pyjq dependency\r\n\r\n* update import\r\n\r\n* rename file\r\n\r\n* delete unused file\r\n\r\n* Revert \"delete unused file\"\r\n\r\nThis reverts commit 758e939367775ddbefcd52c6e1e832976d3ba9fe.\r\n\r\n* fix\r\n\r\n* rename\r\n\r\n* abstract property\r\n\r\n* delete unused field\r\n\r\n* delete unused field\r\n\r\n* rename\r\n\r\n* pass kwargs directly\r\n\r\n* isort\r\n\r\n* Revert \"isort\"\r\n\r\nThis reverts commit 4a792239440bc9950813ccc6ed368641ce2a96e4.\r\n\r\n* isort\r\n\r\n* update state\r\n\r\n* fix imports\r\n\r\n* update\r\n\r\n* update dependency\r\n\r\n* remove dead code\r\n\r\n* remove dead code\r\n\r\n* format\r\n\r\n* rename file\r\n\r\n* decoder\r\n\r\n* Use decoder\r\n\r\n* Update comment\r\n\r\n* dict_state is actually backed by a dict\r\n\r\n* Add a comment\r\n\r\n* update state takes kwargs\r\n\r\n* move state out of offset paginator\r\n\r\n* fix\r\n\r\n* update jq parameter order\r\n\r\n* fix\r\n\r\n* pass config\r\n\r\n* update\r\n\r\n* update\r\n\r\n* remove incremental mixin\r\n\r\n* delete comment\r\n\r\n* start workin on yaml parser\r\n\r\n* fix test\r\n\r\n* progress\r\n\r\n* refer and overwrite partials\r\n\r\n* factory tests pass\r\n\r\n* fix\r\n\r\n* reset\r\n\r\n* Assert http_method is an enum value\r\n\r\n* fix auth\r\n\r\n* read lists works\r\n\r\n* fix test\r\n\r\n* comment\r\n\r\n* implement all streams\r\n\r\n* build connection checker\r\n\r\n* update comments\r\n\r\n* update comments\r\n\r\n* remove no_state\r\n\r\n* rename package\r\n\r\n* checkout from alex/cac\r\n\r\n* Add missing tests\r\n\r\n* Add missing files\r\n\r\n* missing file\r\n\r\n* rename\r\n\r\n* jinja dependency\r\n\r\n* Add comment\r\n\r\n* comment\r\n\r\n* comment\r\n\r\n* Revert \"delete unused file\"\r\n\r\nThis reverts commit 758e939367775ddbefcd52c6e1e832976d3ba9fe.\r\n\r\n* delete unused field\r\n\r\n* delete unused field\r\n\r\n* rename\r\n\r\n* pass kwargs directly\r\n\r\n* isort\r\n\r\n* Revert \"isort\"\r\n\r\nThis reverts commit 4a792239440bc9950813ccc6ed368641ce2a96e4.\r\n\r\n* format\r\n\r\n* decoder\r\n\r\n* better error handling\r\n\r\n* remove nostate\r\n\r\n* isort\r\n\r\n* remove print\r\n\r\n* move test\r\n\r\n* delete duplicates\r\n\r\n* update\r\n\r\n* delete dead code\r\n\r\n* Update mapping type to [str, Any]\r\n\r\n* add comment\r\n\r\n* Add comment\r\n\r\n* pass parameters through kwargs\r\n\r\n* pass parameters through kwargs\r\n\r\n* fix test\r\n\r\n* update interface\r\n\r\n* update interface to pass source in interface\r\n\r\n* update interface to pass source in interface\r\n\r\n* rename to stream_slicer\r\n\r\n* Allow passing a string or an enum\r\n\r\n* Define StateType enum\r\n\r\n* unit tests pass\r\n\r\n* update dict state\r\n\r\n* update\r\n\r\n* can read\r\n\r\n* fix test\r\n\r\n* fix from yaml update\r\n\r\n* elif\r\n\r\n* convert state_type if not of type type\r\n\r\n* convert state_type if not of type type\r\n\r\n* Add a test\r\n\r\n* Low code connectors: string interpolation with jinja (#12852)\r\n\r\n* checkout from alex/cac\r\n\r\n* Add missing tests\r\n\r\n* Add missing files\r\n\r\n* missing file\r\n\r\n* rename\r\n\r\n* jinja dependency\r\n\r\n* Add comment\r\n\r\n* comment\r\n\r\n* comment\r\n\r\n* Revert \"delete unused file\"\r\n\r\nThis reverts commit 758e939367775ddbefcd52c6e1e832976d3ba9fe.\r\n\r\n* delete unused field\r\n\r\n* delete unused field\r\n\r\n* rename\r\n\r\n* pass kwargs directly\r\n\r\n* isort\r\n\r\n* Revert \"isort\"\r\n\r\nThis reverts commit 4a792239440bc9950813ccc6ed368641ce2a96e4.\r\n\r\n* format\r\n\r\n* decoder\r\n\r\n* better error handling\r\n\r\n* remove nostate\r\n\r\n* isort\r\n\r\n* delete dead code\r\n\r\n* Update mapping type to [str, Any]\r\n\r\n* add comment\r\n\r\n* Add comment\r\n\r\n* pass parameters through kwargs\r\n\r\n* move test to right module\r\n\r\n* Add missing test\r\n\r\n* Use authbase instead of deprecated class\r\n\r\n* leverage generator\r\n\r\n* remove sendgrid specific code\r\n\r\n* update\r\n\r\n* update\r\n\r\n* delete comment\r\n\r\n* remove sendgrid specific file\r\n\r\n* remove unused file\r\n\r\n* Delete dead code\r\n\r\n* rename methods\r\n\r\n* rename to declarative\r\n\r\n* rename the classes too\r\n\r\n* select streams to check\r\n\r\n* nit\r\n\r\n* rename method\r\n\r\n* rename class\r\n\r\n* {} is faster than dict()\r\n\r\n* Update airbyte-cdk/python/airbyte_cdk/sources/declarative/parsers/yaml_parser.py\r\n\r\nCo-authored-by: Sherif A. Nada <snadalive@gmail.com>\r\n\r\n* more precise exception\r\n\r\n* rename class\r\n\r\n* add comment\r\n\r\n* Try to install packages to build jq\r\n\r\n* isort\r\n\r\n* only automake\r\n\r\n* Revert \"only automake\"\r\n\r\nThis reverts commit c8fe154ffcbec3fa05289a7b6f087e5711622c87.\r\n\r\n* remove git\r\n\r\n* rename file\r\n\r\n* create components in kwargs\r\n\r\n* Use tuple of strings\r\n\r\n* parser doesn't need to be stored\r\n\r\n* move file and delete duplicates\r\n\r\n* Revert \"Use tuple of strings\"\r\n\r\nThis reverts commit ab5a7afd08ef9a781f067389bc93c19240964e41.\r\n\r\n* raise error if streams to check are not in the catalog\r\n\r\n* Revert \"Revert \"Use tuple of strings\"\"\r\n\r\nThis reverts commit 7c9fb8eb3390cb36ea53fccce4a39c618eba9327.\r\n\r\n* traverse tree\r\n\r\n* rename to options\r\n\r\n* move docstring\r\n\r\n* Update airbyte-cdk/python/airbyte_cdk/sources/declarative/checks/check_stream.py\r\n\r\nCo-authored-by: Sherif A. Nada <snadalive@gmail.com>\r\n\r\n* fix tests and format\r\n\r\n* format\r\n\r\n* update\r\n\r\n* better error message\r\n\r\n* Add jq dependency\r\n\r\n* Use request header provider\r\n\r\n* rename\r\n\r\n* rename field\r\n\r\n* remove get_context method\r\n\r\n* rename\r\n\r\n* add a comment\r\n\r\n* format\r\n\r\nCo-authored-by: Sherif A. Nada <snadalive@gmail.com>",
        "code": "def test_collision():\n    content = \n    config = parser.parse(content)\n    assert config[\"example\"][\"nested\"][\"path\"] == \"first one\"\n    assert config[\"example\"][\"nested.path\"] == \"uh oh\"\n    assert config[\"reference_to_nested_path\"] == \"uh oh\"\n    assert config[\"example\"][\"nested\"][\"more_nested\"][\"value\"] == \"found it!\"\n    assert config[\"reference_to_nested_nested_value\"] == \"found it!\"\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 53,
        "n_words": 32,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 68,
        "n_ast_nodes": 134,
        "n_identifiers": 5,
        "d_id": 795,
        "documentation": {
            "docstring": "\nexample:\n  nested:\n    path: \"first one\"\n    more_nested:\n        value: \"found it!\"\n  nested.path: \"uh oh\"\nreference_to_nested_path:\n  ref: \"*ref(example.nested.path)\"\nreference_to_nested_nested_value:\n  ref: \"*ref(example.nested.more_nested.value)\"\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 133204,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/rpdb.py",
        "file_name": "rpdb.py",
        "fun_name": "do_get",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def do_get(self, arg):\n        \n        ray.worker.global_worker.debugger_get_breakpoint = self._breakpoint_uuid\n        self.__restore()\n        self.handle.connection.close()\n        return Pdb.do_continue(self, arg)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 46,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 42,
        "n_ast_nodes": 69,
        "n_identifiers": 14,
        "d_id": 29957,
        "documentation": {
            "docstring": "get\n        Skip to where the current task returns to.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 121807,
        "commit_id": "260f1d8b843483df46cf397ae5a1afc0abc9c64f",
        "repo": "jax",
        "path": "jax/_src/profiler.py",
        "file_name": "profiler.py",
        "fun_name": "trace",
        "commit_message": "Add option to generate perfetto trace without generating link",
        "code": "def trace(log_dir, create_perfetto_link=False, create_perfetto_trace=False):\n  \n  start_trace(log_dir, create_perfetto_link, create_perfetto_trace)\n  try:\n    yield\n  finally:\n    stop_trace()\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 21,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 30,
        "n_ast_nodes": 51,
        "n_identifiers": 6,
        "d_id": 27075,
        "documentation": {
            "docstring": "Context manager to take a profiler trace.\n\n  The trace will capture CPU, GPU, and/or TPU activity, including Python\n  functions and JAX on-device operations.\n\n  The resulting trace can be viewed with TensorBoard. Note that TensorBoard\n  doesn't need to be running when collecting the trace.\n\n  Only once trace may be collected a time. A RuntimeError will be raised if a\n  trace is started while another trace is running.\n\n  Args:\n    log_dir: The directory to save the profiler trace to (usually the\n      TensorBoard log directory).\n    create_perfetto_link: A boolean which, if true, creates and prints link to\n      the Perfetto trace viewer UI (https://ui.perfetto.dev). The program will\n      block until the link is opened and Perfetto loads the trace.\n    create_perfetto_trace: A boolean which, if true, additionally dumps a\n      ``perfetto_trace.json.gz`` file that is compatible for upload with the\n      Perfetto trace viewer UI (https://ui.perfetto.dev). The file will also be\n      generated if ``create_perfetto_link`` is true. This could be useful if you\n      want to generate a Perfetto-compatible trace without blocking the\n      processs.\n  ",
            "n_words": 161,
            "vocab_size": 97,
            "n_whitespaces": 218,
            "language": "en"
        }
    },
    {
        "id": 211057,
        "commit_id": "b29aa30f650b06bea79698adfb3392cc96feb583",
        "repo": "PaddleDetection",
        "path": "deploy/pipeline/download.py",
        "file_name": "download.py",
        "fun_name": "get_weights_path",
        "commit_message": "given inference model path, download model automatically (#6403)\n\n* given inference model path, download model automatically\r\n\r\n* encapsulate auto download model as a function\r\n\r\n* given note that default model dir is download link\r\n\r\n* change attr model download path to https://bj.bcebos.com/v1/paddledet/models/pipeline/PPLCNet_x1_0_person_attribute_945_infer.zip",
        "code": "def get_weights_path(url):\n    \n    url = parse_url(url)\n    path, _ = get_path(url, WEIGHTS_HOME)\n    return path\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleDetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 53022,
        "documentation": {
            "docstring": "Get weights path from WEIGHTS_HOME, if not exists,\n    download it from url.\n    ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 37529,
        "commit_id": "18df440709f1b19d1c5617c0d987c5ff8fd0915d",
        "repo": "transformers",
        "path": "src/transformers/trainer_pt_utils.py",
        "file_name": "trainer_pt_utils.py",
        "fun_name": "find_batch_size",
        "commit_message": "Replace dict/BatchEncoding instance checks by Mapping (#17014)\n\n* Replace dict/BatchEncoding instance checks by Mapping\r\n\r\n* Typo",
        "code": "def find_batch_size(tensors):\n    \n    if isinstance(tensors, (list, tuple)):\n        for t in tensors:\n            result = find_batch_size(t)\n            if result is not None:\n                return result\n    elif isinstance(tensors, Mapping):\n        for key, value in tensors.items():\n            result = find_batch_size(value)\n            if result is not None:\n                return result\n    elif isinstance(tensors, torch.Tensor):\n        return tensors.shape[0] if len(tensors.shape) >= 1 else None\n    elif isinstance(tensors, np.ndarray):\n        return tensors.shape[0] if len(tensors.shape) >= 1 else None\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 177,
        "n_words": 60,
        "vocab_size": 31,
        "complexity": 11,
        "nloc": 15,
        "token_counts": 126,
        "n_ast_nodes": 192,
        "n_identifiers": 17,
        "d_id": 6828,
        "documentation": {
            "docstring": "\n    Find the first dimension of a tensor in a nested list/tuple/dict of tensors.\n    ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 250390,
        "commit_id": "652d1669c5a103b1c20478770c4aaf18849c09a3",
        "repo": "synapse",
        "path": "tests/handlers/test_register.py",
        "file_name": "test_register.py",
        "fun_name": "test_spam_checker_shadow_ban",
        "commit_message": "Add missing type hints to tests.handlers. (#14680)\n\nAnd do not allow untyped defs in tests.handlers.",
        "code": "def test_spam_checker_shadow_ban(self) -> None:\n        \n        user_id = self.get_success(self.handler.register_user(localpart=\"user\"))\n\n        # Get an access token.\n        token = \"testtok\"\n        self.get_success(\n            self.store.add_access_token_to_user(\n                user_id=user_id, token=token, device_id=None, valid_until_ms=None\n            )\n        )\n\n        # Ensure the user was marked as shadow-banned.\n        request = Mock(args={})\n        request.args[b\"access_token\"] = [token.encode(\"ascii\")]\n        request.requestHeaders.getRawHeaders = mock_getRawHeaders()\n        auth = Auth(self.hs)\n        requester = self.get_success(auth.get_user_by_req(request))\n\n        self.assertTrue(requester.shadow_banned)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 175,
        "n_words": 47,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 118,
        "n_ast_nodes": 197,
        "n_identifiers": 26,
        "d_id": 73413,
        "documentation": {
            "docstring": "A spam checker can choose to shadow-ban a user, which allows registration to succeed.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 90724,
        "commit_id": "5c0c82919f14654cc18405384654fa792d12e31a",
        "repo": "sentry",
        "path": "tests/acceptance/test_organization_global_selection_header.py",
        "file_name": "test_organization_global_selection_header.py",
        "fun_name": "test_global_selection_header_updates_environment_with_browser_navigation_buttons",
        "commit_message": "ref(page-filters): Remove mentions of global header in acceptance tests (#35075)",
        "code": "def test_global_selection_header_updates_environment_with_browser_navigation_buttons(self):\n        \n        with self.feature(\"organizations:global-views\"):\n            self.create_issues()\n\n            \n            self.issues_list.visit_issue_list(self.org.slug)\n            self.issues_list.wait_until_loaded()\n            assert \"environment=\" not in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"All Env\"\n\n            self.browser.click('[data-test-id=\"page-filter-environment-selector\"]')\n            self.browser.click('[data-test-id=\"environment-prod\"]')\n            self.issues_list.wait_until_loaded()\n            assert \"environment=prod\" in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"prod\"\n\n            # clear environment prod\n            self.browser.click('[data-test-id=\"page-filter-environment-selector\"]')\n            self.browser.click('[data-test-id=\"environment-prod\"] [role=\"checkbox\"]')\n            self.browser.click('[data-test-id=\"page-filter-environment-selector\"]')\n            self.issues_list.wait_until_loaded()\n            assert \"environment=\" not in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"All Env\"\n\n            \n            self.browser.back()\n            self.issues_list.wait_until_loaded()\n            assert \"environment=prod\" in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"prod\"\n\n            self.browser.back()\n            self.issues_list.wait_until_loaded()\n            assert \"environment=\" not in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"All Env\"\n\n            \n            self.browser.forward()\n            self.issues_list.wait_until_loaded()\n            assert \"environment=prod\" in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"prod\"\n\n            self.browser.forward()\n            self.issues_list.wait_until_loaded()\n            assert \"environment=\" not in self.browser.current_url\n            assert self.issue_details.global_selection.get_selected_environment() == \"All Env\"\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 504,
        "n_words": 91,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 50,
        "token_counts": 295,
        "n_ast_nodes": 527,
        "n_identifiers": 17,
        "d_id": 18685,
        "documentation": {
            "docstring": "\n        Global Selection Header should:\n        1) load project from URL if it exists\n        2) clear the current environment if the user clicks clear\n        3) reload the environment from URL if it exists on browser navigation\n        \n            set up workflow:\n            1) environment=All environments\n            2) environment=prod\n            3) environment=All environments\n            \n            navigate back through history to the beginning\n            1) environment=All Env -> environment=prod\n            2) environment=prod -> environment=All Env\n            \n            navigate forward through history to the end\n            1) environment=All Env -> environment=prod\n            2) environment=prod -> environment=All Env\n            ",
            "n_words": 79,
            "vocab_size": 40,
            "n_whitespaces": 261,
            "language": "en"
        }
    },
    {
        "id": 109681,
        "commit_id": "fd5cf5c88123653b656a8f908aa611e5a20dc923",
        "repo": "matplotlib",
        "path": "examples/style_sheets/style_sheets_reference.py",
        "file_name": "style_sheets_reference.py",
        "fun_name": "plot_colored_circles",
        "commit_message": "[DOC]: adding a grid to the style sheet reference. (#24020)\n\n* add divider and annotation.\r\n\r\nCo-authored-by: Kinza Raza <kanza.imran@careem.com>\r\n\r\n* fix flake8\r\n\r\n* change from annotate to title\r\n\r\n* Update examples/style_sheets/style_sheets_reference.py\r\n\r\nCo-authored-by: Jody Klymak <jklymak@gmail.com>\r\n\r\n* Update examples/style_sheets/style_sheets_reference.py\r\n\r\nCo-authored-by: Jody Klymak <jklymak@gmail.com>\r\n\r\nCo-authored-by: Kinza Raza <kanza.imran@careem.com>\r\nCo-authored-by: Jody Klymak <jklymak@gmail.com>",
        "code": "def plot_colored_circles(ax, prng, nb_samples=15):\n    \n    for sty_dict, j in zip(plt.rcParams['axes.prop_cycle'], range(nb_samples)):\n        ax.add_patch(plt.Circle(prng.normal(scale=3, size=2),\n                                radius=1.0, color=sty_dict['color']))\n    ax.grid(visible=True)\n\n    # Add title for enabling grid\n    plt.title('ax.grid(True)', family='monospace', fontsize='small')\n\n    ax.set_xlim([-4, 8])\n    ax.set_ylim([-5, 6])\n    ax.set_aspect('equal', adjustable='box')  # to plot circles as circles\n    return ax\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 104,
        "n_words": 38,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 123,
        "n_ast_nodes": 198,
        "n_identifiers": 26,
        "d_id": 23704,
        "documentation": {
            "docstring": "\n    Plot circle patches.\n\n    NB: draws a fixed amount of samples, rather than using the length of\n    the color cycle, because different styles may have different numbers\n    of colors.\n    ",
            "n_words": 28,
            "vocab_size": 24,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 286413,
        "commit_id": "19660ff3ee39458bd78e729b97fca4a4e552c160",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/keys_model.py",
        "file_name": "keys_model.py",
        "fun_name": "first_time_user",
        "commit_message": "Updated check for new user (#3302)\n\n* Updated check for new user\r\n\r\n* Update docstring\r\n\r\n* Fixed import error\r\n\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>",
        "code": "def first_time_user() -> bool:\n    \n    if USER_ENV_FILE.stat().st_size == 0:\n        set_key(\"OPENBB_PREVIOUS_USE\", \"True\", True)\n        return True\n    return False\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 38,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 30,
        "n_ast_nodes": 54,
        "n_identifiers": 6,
        "d_id": 85800,
        "documentation": {
            "docstring": "Whether a user is a first time user. A first time user is someone with an empty .env file.\n    If this is true, it also adds an env variable to make sure this does not run again.\n\n    Returns\n    ----------\n    bool\n        Whether or not the user is a first time user\n    ",
            "n_words": 50,
            "vocab_size": 34,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 85650,
        "commit_id": "c48fda09e252018a4d2b831bb84e1c68a739c085",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_batch.py",
        "file_name": "test_batch.py",
        "fun_name": "test_cardinality_limiter",
        "commit_message": "feat(metrics): Add  cardinality limiter to indexer [sns-1651] (#38428)\n\nReopen of https://github.com/getsentry/sentry/pull/38302 to avoid\r\nnotification spam\r\n\r\nSee #38257 and\r\nhttps://www.notion.so/sentry/Metrics-Dimensionality-Limiting-df010a6a6d4e467ca3c5c19230db862b#4966fb9c07fc4394b720ad161c99a096.\r\nThis is just the glue code and configuration options for using the\r\ncardinality limiter in the indexer. The actual implementation is TBD.\r\nThis is safe to merge because the stub implementation does not actually\r\nlimit anything at all, so it should be fast enough to do synchronously\r\nfor now\r\n\r\n## rollout plan\r\n\r\n- [x] https://github.com/getsentry/sentry/pull/38446\r\n- [x] set options to nothing in prod\r\n- [ ] merge + deploy this PR\r\n- [ ] check prod metrics: redis should not be used\r\n- [ ] https://github.com/getsentry/sentry/pull/38445\r\n- [ ] check prod metrics: redis should still not be used\r\n- [ ] run qe tests?\r\n- [ ] get a redis cluster and configure it\r\n- [ ] run use_quota on a separate thread\r\n- [ ] set a quota\r\n- [ ] get rid of writes limiter?\r\n- [ ] stop indexing tag values\r\n\r\nCo-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>\r\nCo-authored-by: Nikhar Saxena <nikhar.saxena@sentry.io>",
        "code": "def test_cardinality_limiter(caplog, settings):\n    \n    settings.SENTRY_METRICS_INDEXER_DEBUG_LOG_SAMPLE_RATE = 1.0\n\n    outer_message = _construct_outer_message(\n        [\n            (counter_payload, []),\n            (distribution_payload, []),\n            (set_payload, []),\n        ]\n    )\n\n    batch = IndexerBatch(UseCaseKey.PERFORMANCE, outer_message)\n    keys_to_remove = list(batch.parsed_payloads_by_offset)[:2]\n    # the messages come in a certain order, and Python dictionaries preserve\n    # their insertion order. So we can hardcode offsets here.\n    assert keys_to_remove == [\n        PartitionIdxOffset(partition_idx=0, offset=0),\n        PartitionIdxOffset(partition_idx=0, offset=1),\n    ]\n    batch.filter_messages(keys_to_remove)\n    assert batch.extract_strings() == {\n        1: {\n            \"environment\",\n            \"errored\",\n            \"production\",\n            # Note, we only extracted one MRI, of the one metric that we didn't\n            # drop\n            \"s:sessions/error@none\",\n            \"session.status\",\n        },\n    }\n\n    snuba_payloads = batch.reconstruct_messages(\n        {\n            1: {\n                \"environment\": 1,\n                \"errored\": 2,\n                \"production\": 3,\n                \"s:sessions/error@none\": 4,\n                \"session.status\": 5,\n            },\n        },\n        {\n            1: {\n                \"environment\": Metadata(id=1, fetch_type=FetchType.CACHE_HIT),\n                \"errored\": Metadata(id=2, fetch_type=FetchType.CACHE_HIT),\n                \"production\": Metadata(id=3, fetch_type=FetchType.CACHE_HIT),\n                \"s:sessions/error@none\": Metadata(id=4, fetch_type=FetchType.CACHE_HIT),\n                \"session.status\": Metadata(id=5, fetch_type=FetchType.CACHE_HIT),\n            }\n        },\n    )\n\n    assert _deconstruct_messages(snuba_payloads) == [\n        (\n            {\n                \"mapping_meta\": {\n                    \"c\": {\n                        \"1\": \"environment\",\n                        \"2\": \"errored\",\n                        \"3\": \"production\",\n                        \"4\": \"s:sessions/error@none\",\n                        \"5\": \"session.status\",\n                    },\n                },\n                \"metric_id\": 4,\n                \"org_id\": 1,\n                \"project_id\": 3,\n                \"retention_days\": 90,\n                \"tags\": {\"1\": 3, \"5\": 2},\n                \"timestamp\": ts,\n                \"type\": \"s\",\n                \"use_case_id\": \"performance\",\n                \"value\": [3],\n            },\n            [\n                (\"mapping_sources\", b\"c\"),\n                (\"metric_type\", \"s\"),\n            ],\n        )\n    ]\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 1008,
        "n_words": 177,
        "vocab_size": 115,
        "complexity": 1,
        "nloc": 73,
        "token_counts": 344,
        "n_ast_nodes": 567,
        "n_identifiers": 30,
        "d_id": 18023,
        "documentation": {
            "docstring": "\n    Test functionality of the indexer batch related to cardinality-limiting. More concretely, assert that `IndexerBatch.filter_messages`:\n\n    1. removes the messages from the outgoing batch\n    2. prevents strings from filtered messages from being extracted & indexed\n    3. does not crash when strings from filtered messages are not passed into reconstruct_messages\n    4. still extracts strings that exist both in filtered and unfiltered messages (eg \"environment\")\n    ",
            "n_words": 61,
            "vocab_size": 46,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 269300,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/activations.py",
        "file_name": "activations.py",
        "fun_name": "linear",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def linear(x):\n    \n    return x\n\n\n@keras_export(\"keras.activations.serialize\")\n@tf.__internal__.dispatch.add_dispatch_support",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.activations.serialize\")\n@tf.__internal__.dispatch.add_dispatch_support",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 10,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 8,
        "n_ast_nodes": 39,
        "n_identifiers": 7,
        "d_id": 80014,
        "documentation": {
            "docstring": "Linear activation function (pass-through).\n\n    For example:\n\n    >>> a = tf.constant([-3.0,-1.0, 0.0,1.0,3.0], dtype = tf.float32)\n    >>> b = tf.keras.activations.linear(a)\n    >>> b.numpy()\n    array([-3., -1.,  0.,  1.,  3.], dtype=float32)\n\n    Args:\n        x: Input tensor.\n\n    Returns:\n        The input, unmodified.\n    ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 101950,
        "commit_id": "dab823a3eb7a5257cb1e0818ee10ed234d3de97f",
        "repo": "faceswap",
        "path": "lib/gui/wrapper.py",
        "file_name": "wrapper.py",
        "fun_name": "build_args",
        "commit_message": "Typing - lib.gui.display_command",
        "code": "def build_args(self, category, command=None, generate=False):\n        \n        logger.debug(\"Build cli arguments: (category: %s, command: %s, generate: %s)\",\n                     category, command, generate)\n        command = self.command if not command else command\n        script = f\"{category}.py\"\n        pathexecscript = os.path.join(self.pathscript, script)\n\n        args = [sys.executable] if generate else [sys.executable, \"-u\"]\n        args.extend([pathexecscript, command])\n\n        cli_opts = get_config().cli_opts\n        for cliopt in cli_opts.gen_cli_arguments(command):\n            args.extend(cliopt)\n            if command == \"train\" and not generate:\n                self._get_training_session_info(cliopt)\n\n        if not generate:\n            args.append(\"-gui\")  # Indicate to Faceswap that we are running the GUI\n        if generate:\n            # Delimit args with spaces\n            args = [f'\"{arg}\"' if \" \" in arg and not arg.startswith((\"[\", \"(\"))\n                    and not arg.endswith((\"]\", \")\")) else arg\n                    for arg in args]\n        logger.debug(\"Built cli arguments: (%s)\", args)\n        return args\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 328,
        "n_words": 108,
        "vocab_size": 70,
        "complexity": 12,
        "nloc": 21,
        "token_counts": 183,
        "n_ast_nodes": 309,
        "n_identifiers": 26,
        "d_id": 21327,
        "documentation": {
            "docstring": " Build the faceswap command and arguments list.\n\n        If training, pass the model folder and name to the training\n        :class:`lib.gui.analysis.Session` for the GUI.\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 153185,
        "commit_id": "8d1004fdbdaa05700613c8e6287641a732acf606",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py",
        "file_name": "virtual_partition.py",
        "fun_name": "length",
        "commit_message": "FIX-#3675: Expand virtual partitioning utility (#3886)\n\nCo-authored-by: mvashishtha <mahesh@ponder.io>\r\nCo-authored-by: jeffreykennethli <jkli@ponder.io>\r\nCo-authored-by: Anatoly Myachev <anatoly.myachev@intel.com>\r\nCo-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>\r\nCo-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>\r\nCo-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>\r\nCo-authored-by: Naren Krishna <92325366+naren-ponder@users.noreply.github.com>\r\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Dmitry Chigarev <62142979+dchigarev@users.noreply.github.com>\r\nCo-authored-by: Yaroslav Igoshev <yaroslav.igoshev@intel.com>\r\nCo-authored-by: Doris Lee <dorisjunglinlee@gmail.com>\r\nCo-authored-by: Aditya Parameswaran <adityagp@gmail.com>\r\nCo-authored-by: Rehan Sohail Durrani <rehan@ponder.io>\r\nCo-authored-by: Susmit Vengurlekar <susmit.py@gmail.com>\r\nSigned-off-by: Devin Petersohn <devin.petersohn@gmail.com>",
        "code": "def length(self):\n        \n        if self._length_cache is None:\n            if self.axis == 0:\n                self._length_cache = sum(\n                    o.length() for o in self.list_of_partitions_to_combine\n                )\n            else:\n                self._length_cache = self.list_of_partitions_to_combine[0].length()\n        return self._length_cache\n\n    _width_cache = None\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 138,
        "n_words": 28,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 58,
        "n_ast_nodes": 100,
        "n_identifiers": 8,
        "d_id": 35286,
        "documentation": {
            "docstring": "\n        Get the length of this partition.\n\n        Returns\n        -------\n        int\n            The length of the partition.\n        ",
            "n_words": 14,
            "vocab_size": 10,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 19475,
        "commit_id": "0788b0122e75ca5244ff4185336dc7958543f165",
        "repo": "pipenv",
        "path": "tests/integration/test_lock.py",
        "file_name": "test_lock.py",
        "fun_name": "test_pipenv_respects_package_index_restrictions",
        "commit_message": "Refactor test into a version that also check quiet mode, move to correct test file.\nAdd test cases for pip freeze has expected output\nAdd test for the package index restrictions.",
        "code": "def test_pipenv_respects_package_index_restrictions(PipenvInstance):\n    with PipenvInstance() as p:\n        with open(p.pipfile_path, 'w') as f:\n            contents = .strip().format(url=p.pypi, requirement='{version=\"*\", index=\"local\"}')\n            f.write(contents)\n\n        c = p.pipenv('lock')\n        assert c.returncode == 0\n        assert 'requests' in p.lockfile['default']\n        assert 'idna' in p.lockfile['default']\n        assert 'certifi' in p.lockfile['default']\n        assert 'urllib3' in p.lockfile['default']\n        assert 'chardet' in p.lockfile['default']\n        # this is the newest version we have in our private pypi (but pypi.org has 2.27.1 at present)\n        expected_result = {'hashes': ['sha256:63b52e3c866428a224f97cab011de738c36aec0185aa91cfacd418b5d58911d1',\n                                      'sha256:ec22d826a36ed72a7358ff3fe56cbd4ba69dd7a6718ffd450ff0e9df7a47ce6a'],\n                           'index': 'local', 'version': '==2.19.1'}\n        assert p.lockfile['default']['requests'] == expected_result\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 239,
        "n_words": 75,
        "vocab_size": 54,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 140,
        "n_ast_nodes": 263,
        "n_identifiers": 18,
        "d_id": 2991,
        "documentation": {
            "docstring": "\n[[source]]\nurl = \"https://pypi.org/simple\"\nverify_ssl = true\nname = \"pypi\"\n\n[[source]]\nurl = \"{url}/simple\"\nverify_ssl = true\nname = \"local\"\n\n[packages]\nrequests = {requirement}\n                ",
            "n_words": 24,
            "vocab_size": 13,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 248471,
        "commit_id": "5949ab86f8db0ef3dac2063e42210030f17786fb",
        "repo": "synapse",
        "path": "synapse/rest/media/v1/thumbnailer.py",
        "file_name": "thumbnailer.py",
        "fun_name": "transpose",
        "commit_message": "Fix potential thumbnail memory leaks. (#12932)",
        "code": "def transpose(self) -> Tuple[int, int]:\n        \n        if self.transpose_method is not None:\n            # Safety: `transpose` takes an int rather than e.g. an IntEnum.\n            # self.transpose_method is set above to be a value in\n            # EXIF_TRANSPOSE_MAPPINGS, and that only contains correct values.\n            with self.image:\n                self.image = self.image.transpose(self.transpose_method)  # type: ignore[arg-type]\n            self.width, self.height = self.image.size\n            self.transpose_method = None\n            # We don't need EXIF any more\n            self.image.info[\"exif\"] = None\n        return self.image.size\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 191,
        "n_words": 66,
        "vocab_size": 53,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 74,
        "n_ast_nodes": 125,
        "n_identifiers": 10,
        "d_id": 72299,
        "documentation": {
            "docstring": "Transpose the image using its EXIF Orientation tag\n\n        Returns:\n            A tuple containing the new image size in pixels as (width, height).\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 249408,
        "commit_id": "37f329c9adf6ed02df15661850f999edd9e5fd93",
        "repo": "synapse",
        "path": "tests/rest/admin/test_server_notice.py",
        "file_name": "test_server_notice.py",
        "fun_name": "test_displayname_is_set_avatar_is_none",
        "commit_message": "Fix that sending server notices fail if avatar is `None` (#13566)\n\nIndroduced in #11846.",
        "code": "def test_displayname_is_set_avatar_is_none(self) -> None:\n        \n        channel = self.make_request(\n            \"POST\",\n            self.url,\n            access_token=self.admin_user_tok,\n            content={\n                \"user_id\": self.other_user,\n                \"content\": {\"msgtype\": \"m.text\", \"body\": \"test msg\"},\n            },\n        )\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n\n        # user has one invite\n        self._check_invite_and_join_status(self.other_user, 1, 0)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 159,
        "n_words": 32,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 78,
        "n_ast_nodes": 129,
        "n_identifiers": 14,
        "d_id": 72899,
        "documentation": {
            "docstring": "\n        Tests that sending a server notices is successfully,\n        if a display_name is set, avatar_url is `None` and\n        \"check avatar size and mime type\" is set.\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 28430,
        "commit_id": "fd5a3b24bcb941180bf2c27e6d0c34022d9e3ecd",
        "repo": "saleor",
        "path": "saleor/graphql/warehouse/dataloaders.py",
        "file_name": "dataloaders.py",
        "fun_name": "prepare_stocks_reservations_map",
        "commit_message": "Fix quantity available for stocks with cc warehouses (#10343)\n\n* Refactor AvailableQuantityByProductVariantIdCountryCodeAndChannelSlugLoader and fix quantity available calculation\r\n\r\n* Add more tests for variant quantity available",
        "code": "def prepare_stocks_reservations_map(self, variant_ids):\n        \n        stocks_reservations = defaultdict(int)\n        if is_reservation_enabled(self.context.site.settings):  # type: ignore\n            # Can't do second annotation on same queryset because it made\n            # available_quantity annotated value incorrect thanks to how\n            # Django's ORM builds SQLs with annotations\n            reservations_qs = (\n                Stock.objects.using(self.database_connection_name)\n                .filter(product_variant_id__in=variant_ids)\n                .annotate_reserved_quantity()\n                .values_list(\"id\", \"reserved_quantity\")\n            )\n            for stock_id, quantity_reserved in reservations_qs:\n                stocks_reservations[stock_id] = quantity_reserved\n        return stocks_reservations\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 226,
        "n_words": 56,
        "vocab_size": 49,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 73,
        "n_ast_nodes": 124,
        "n_identifiers": 21,
        "d_id": 5169,
        "documentation": {
            "docstring": "Prepare stock id to quantity reserved map for provided variant ids.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 65955,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_current_student",
        "commit_message": "style: format code with black",
        "code": "def get_current_student():\n\t\n\temail = frappe.session.user\n\tif email in (\"Administrator\", \"Guest\"):\n\t\treturn None\n\ttry:\n\t\tstudent_id = frappe.get_all(\"Student\", {\"student_email_id\": email}, [\"name\"])[0].name\n\t\treturn frappe.get_doc(\"Student\", student_id)\n\texcept (IndexError, frappe.DoesNotExistError):\n\t\treturn None\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 18,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 68,
        "n_ast_nodes": 117,
        "n_identifiers": 11,
        "d_id": 14069,
        "documentation": {
            "docstring": "Returns current student from frappe.session.user\n\n\tReturns:\n\t        object: Student Document\n\t",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 178965,
        "commit_id": "c2e2b6fd58f535c3419f21a84c54ead13968ddd2",
        "repo": "Nuitka",
        "path": "nuitka/freezer/IncludedDataFiles.py",
        "file_name": "IncludedDataFiles.py",
        "fun_name": "copyDataFiles",
        "commit_message": "Plugins: Cleanups to how data files are handled",
        "code": "def copyDataFiles():\n    \n\n    for included_datafile in getIncludedDataFiles():\n        # TODO: directories should be resolved to files.\n        if (\n            not isinstance(included_datafile, (IncludedDataFile))\n            or included_datafile.needsCopy()\n        ):\n            if shallMakeModule():\n                options_logger.sysexit(\n                    \n                )\n            elif not isStandaloneMode():\n                options_logger.sysexit(\n                    \n                )\n\n            _handleDataFile(\n                included_datafile,\n            )\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 242,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 59,
        "n_ast_nodes": 108,
        "n_identifiers": 11,
        "d_id": 42880,
        "documentation": {
            "docstring": "Copy the data files needed for standalone distribution.\n\n    Notes:\n        This is for data files only, not DLLs or even extension modules,\n        those must be registered as entry points, and would not go through\n        necessary handling if provided like this.\n    \\\nError, data files for modules must be done via wheels, or commercial plugins '--embed-*' options.\\\nError, data files cannot be included in accelerated mode unless using commercial plugins '--embed-*' options.",
            "n_words": 70,
            "vocab_size": 53,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 207377,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_scripts/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_commands_with_invalid_settings",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_commands_with_invalid_settings(self):\n        \n        args = [\"startproject\"]\n        out, err = self.run_django_admin(args, settings_file=\"bad_settings\")\n        self.assertNoOutput(out)\n        self.assertOutput(err, \"You must provide a project name\", regex=True)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 54,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 75,
        "n_identifiers": 10,
        "d_id": 51944,
        "documentation": {
            "docstring": "\n        Commands that don't require settings succeed if the settings file\n        doesn't exist.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 206286,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/loader_tags.py",
        "file_name": "loader_tags.py",
        "fun_name": "do_block",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def do_block(parser, token):\n    \n    # token.split_contents() isn't useful here because this tag doesn't accept variable as arguments\n    bits = token.contents.split()\n    if len(bits) != 2:\n        raise TemplateSyntaxError(\"'%s' tag takes only one argument\" % bits[0])\n    block_name = bits[1]\n    # Keep track of the names of BlockNodes found in this template, so we can\n    # check for duplication.\n    try:\n        if block_name in parser.__loaded_blocks:\n            raise TemplateSyntaxError(\n                \"'%s' tag with name '%s' appears more than once\" % (bits[0], block_name)\n            )\n        parser.__loaded_blocks.append(block_name)\n    except AttributeError:  # parser.__loaded_blocks isn't a list yet\n        parser.__loaded_blocks = [block_name]\n    nodelist = parser.parse((\"endblock\",))\n\n    # This check is kept for backwards-compatibility. See #3100.\n    endblock = parser.next_token()\n    acceptable_endblocks = (\"endblock\", \"endblock %s\" % block_name)\n    if endblock.contents not in acceptable_endblocks:\n        parser.invalid_block_tag(endblock, \"endblock\", acceptable_endblocks)\n\n    return BlockNode(block_name, nodelist)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 237,
        "n_words": 119,
        "vocab_size": 93,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 134,
        "n_ast_nodes": 226,
        "n_identifiers": 19,
        "d_id": 51468,
        "documentation": {
            "docstring": "\n    Define a block that can be overridden by child templates.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 287754,
        "commit_id": "1b144c0e4dd683e3b47668a89da5eb6da4ae5e08",
        "repo": "core",
        "path": "tests/components/bluetooth/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_wrapped_bleak_scanner",
        "commit_message": "Update to bleak 0.18.0 (#79008)",
        "code": "async def test_wrapped_bleak_scanner(hass, enable_bluetooth):\n    \n    scanner = HaBleakScannerWrapper()\n    switchbot_device = BLEDevice(\"44:44:33:11:23:45\", \"wohand\")\n    switchbot_adv = AdvertisementData(\n        local_name=\"wohand\", service_uuids=[], manufacturer_data={1: b\"\\x01\"}\n    )\n    inject_advertisement(hass, switchbot_device, switchbot_adv)\n    assert scanner.discovered_devices == [switchbot_device]\n    assert await scanner.discover() == [switchbot_device]\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 62,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 70,
        "n_ast_nodes": 118,
        "n_identifiers": 15,
        "d_id": 86942,
        "documentation": {
            "docstring": "Test wrapped bleak scanner dispatches calls as expected.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 112742,
        "commit_id": "cbac2c5c0f7606aca8ccf08fbd418ffe3adfe427",
        "repo": "nni",
        "path": "nni/algorithms/compression/v2/pytorch/pruning/tools/base.py",
        "file_name": "base.py",
        "fun_name": "get_best_result",
        "commit_message": "[Compression] fix typehints (#4800)",
        "code": "def get_best_result(self) -> Optional[Tuple[Union[int, str], Module, Dict[str, Dict[str, Tensor]], Optional[float], List[Dict]]]:\n        \n        if self._best_task_id is not None:\n            compact_model = torch.load(Path(self._log_dir_root, 'best_result', 'model.pth'))\n            compact_model_masks = torch.load(Path(self._log_dir_root, 'best_result', 'masks.pth'))\n            with Path(self._log_dir_root, 'best_result', 'config_list.json').open('r') as f:\n                config_list = json_tricks.load(f)\n            return self._best_task_id, compact_model, compact_model_masks, self._best_score, config_list\n        return None\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 123,
        "n_words": 43,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 128,
        "n_ast_nodes": 199,
        "n_identifiers": 24,
        "d_id": 24742,
        "documentation": {
            "docstring": "\n        Returns\n        -------\n        Optional[Tuple[int, Module, Dict[str, Dict[str, Tensor]], float, List[Dict]]]\n            If self._best_task_id is not None,\n            return best task id, best compact model, masks on the compact model, score, config list used in this task.\n        ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 62040,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/manifest.py",
        "file_name": "manifest.py",
        "fun_name": "_parse_directive",
        "commit_message": "upd; format",
        "code": "def _parse_directive(self, directive):\n        \n        words = directive.split()\n        if len(words) == 1 and words[0] not in ('include', 'exclude',\n                                                'global-include',\n                                                'global-exclude',\n                                                'recursive-include',\n                                                'recursive-exclude',\n                                                'graft', 'prune'):\n            # no action given, let's use the default 'include'\n            words.insert(0, 'include')\n\n        action = words[0]\n        patterns = thedir = dir_pattern = None\n\n        if action in ('include', 'exclude',\n                      'global-include', 'global-exclude'):\n            if len(words) < 2:\n                raise DistlibException(\n                    '%r expects <pattern1> <pattern2> ...' % action)\n\n            patterns = [convert_path(word) for word in words[1:]]\n\n        elif action in ('recursive-include', 'recursive-exclude'):\n            if len(words) < 3:\n                raise DistlibException(\n                    '%r expects <dir> <pattern1> <pattern2> ...' % action)\n\n            thedir = convert_path(words[1])\n            patterns = [convert_path(word) for word in words[2:]]\n\n        elif action in ('graft', 'prune'):\n            if len(words) != 2:\n                raise DistlibException(\n                    '%r expects a single <dir_pattern>' % action)\n\n            dir_pattern = convert_path(words[1])\n\n        else:\n            raise DistlibException('unknown action %r' % action)\n\n        return action, patterns, thedir, dir_pattern\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 670,
        "n_words": 132,
        "vocab_size": 72,
        "complexity": 11,
        "nloc": 31,
        "token_counts": 211,
        "n_ast_nodes": 359,
        "n_identifiers": 14,
        "d_id": 12847,
        "documentation": {
            "docstring": "\n        Validate a directive.\n        :param directive: The directive to validate.\n        :return: A tuple of action, patterns, thedir, dir_patterns\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 155337,
        "commit_id": "14015de80f2387703ca7be52ff917c99ef05fc68",
        "repo": "modin",
        "path": "modin/experimental/core/storage_formats/pyarrow/parsers.py",
        "file_name": "parsers.py",
        "fun_name": "parse",
        "commit_message": "REFACTOR-#5359: Fix code scanning alert - File is not always closed (#5362)\n\nSigned-off-by: Myachev <anatoly.myachev@intel.com>",
        "code": "def parse(self, fname, num_splits, start, end, header, **kwargs):\n        \n        import pyarrow as pa\n        import pyarrow.csv as csv\n\n        with open(fname, \"rb\") as bio:\n            # The header line for the CSV file\n            first_line = bio.readline()\n            bio.seek(start)\n            to_read = header + first_line + bio.read(end - start)\n\n        table = csv.read_csv(\n            BytesIO(to_read), parse_options=csv.ParseOptions(header_rows=1)\n        )\n        chunksize = compute_chunksize(table.num_columns, num_splits)\n        chunks = [\n            pa.Table.from_arrays(table.columns[chunksize * i : chunksize * (i + 1)])\n            for i in range(num_splits)\n        ]\n        return chunks + [\n            table.num_rows,\n            pandas.Series(\n                [t.to_pandas_dtype() for t in table.schema.types],\n                index=table.schema.names,\n            ),\n        ]\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 300,
        "n_words": 83,
        "vocab_size": 62,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 171,
        "n_ast_nodes": 264,
        "n_identifiers": 42,
        "d_id": 36340,
        "documentation": {
            "docstring": "\n        Parse CSV file into PyArrow tables.\n\n        Parameters\n        ----------\n        fname : str\n            Name of the CSV file to parse.\n        num_splits : int\n            Number of partitions to split the resulted PyArrow table into.\n        start : int\n            Position in the specified file to start parsing from.\n        end : int\n            Position in the specified file to end parsing at.\n        header : str\n            Header line that will be interpret as the first line of the parsed CSV file.\n        **kwargs : kwargs\n            Serves the compatibility purpose. Does not affect the result.\n\n        Returns\n        -------\n        list\n            List with split parse results and it's metadata:\n\n            - First `num_split` elements are PyArrow tables, representing the corresponding chunk.\n            - Next element is the number of rows in the parsed table.\n            - Last element is the pandas Series, containing the data-types for each column of the parsed table.\n        ",
            "n_words": 136,
            "vocab_size": 85,
            "n_whitespaces": 338,
            "language": "en"
        }
    },
    {
        "id": 251118,
        "commit_id": "56eea20f6389b751d38079fb09b29237a0d2b262",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_request_streaming",
        "commit_message": "tutils: add BytesMatching placeholder",
        "code": "def test_request_streaming(tctx, why, transfer_encoding, response):\n    \n    server = Placeholder(Server)\n    flow = Placeholder(HTTPFlow)\n    playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular))\n\n    if why.startswith(\"body_size\"):\n        tctx.options.stream_large_bodies = why.replace(\"body_size=\", \"\")\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 43,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 15,
        "nloc": 104,
        "token_counts": 683,
        "n_ast_nodes": 102,
        "n_identifiers": 20,
        "d_id": 73598,
        "documentation": {
            "docstring": "\n    Test HTTP request streaming\n\n    This is a bit more contrived as we may receive server data while we are still sending the request.\n    ",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 65377,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/trial_balance/trial_balance.py",
        "file_name": "trial_balance.py",
        "fun_name": "get_data",
        "commit_message": "style: format code with black",
        "code": "def get_data(filters):\n\n\taccounts = frappe.db.sql(\n\t\t,\n\t\tfilters.company,\n\t\tas_dict=True,\n\t)\n\tcompany_currency = filters.presentation_currency or erpnext.get_company_currency(filters.company)\n\n\tif not accounts:\n\t\treturn None\n\n\taccounts, accounts_by_name, parent_children_map = filter_accounts(accounts)\n\n\tmin_lft, max_rgt = frappe.db.sql(\n\t\t,\n\t\t(filters.company,),\n\t)[0]\n\n\tgl_entries_by_account = {}\n\n\topening_balances = get_opening_balances(filters)\n\n\t# add filter inside list so that the query in financial_statements.py doesn't break\n\tif filters.project:\n\t\tfilters.project = [filters.project]\n\n\tset_gl_entries_by_account(\n\t\tfilters.company,\n\t\tfilters.from_date,\n\t\tfilters.to_date,\n\t\tmin_lft,\n\t\tmax_rgt,\n\t\tfilters,\n\t\tgl_entries_by_account,\n\t\tignore_closing_entries=not flt(filters.with_period_closing_entry),\n\t)\n\n\ttotal_row = calculate_values(\n\t\taccounts, gl_entries_by_account, opening_balances, filters, company_currency\n\t)\n\taccumulate_values_into_parents(accounts, accounts_by_name)\n\n\tdata = prepare_data(accounts, filters, total_row, parent_children_map, company_currency)\n\tdata = filter_out_zero_value_rows(\n\t\tdata, parent_children_map, show_zero_values=filters.get(\"show_zero_values\")\n\t)\n\n\treturn data\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 55,
        "n_words": 93,
        "vocab_size": 67,
        "complexity": 4,
        "nloc": 40,
        "token_counts": 187,
        "n_ast_nodes": 279,
        "n_identifiers": 35,
        "d_id": 13872,
        "documentation": {
            "docstring": "select name, account_number, parent_account, account_name, root_type, report_type, lft, rgt\n\n\t\tfrom `tabAccount` where company=%s order by lftselect min(lft), max(rgt) from `tabAccount`\n\t\twhere company=%s",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 75606,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/search/management/commands/update_index.py",
        "file_name": "update_index.py",
        "fun_name": "queryset_chunks",
        "commit_message": "Reformat with black",
        "code": "def queryset_chunks(self, qs, chunk_size=DEFAULT_CHUNK_SIZE):\n        \n        i = 0\n        while True:\n            items = list(qs[i * chunk_size :][:chunk_size])\n            if not items:\n                break\n            yield items\n            i += 1\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 104,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 44,
        "n_ast_nodes": 73,
        "n_identifiers": 8,
        "d_id": 16427,
        "documentation": {
            "docstring": "\n        Yield a queryset in chunks of at most ``chunk_size``. The chunk yielded\n        will be a list, not a queryset. Iterating over the chunks is done in a\n        transaction so that the order and count of items in the queryset\n        remains stable.\n        ",
            "n_words": 41,
            "vocab_size": 31,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 204857,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/operations.py",
        "file_name": "operations.py",
        "fun_name": "prepare_sql_script",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def prepare_sql_script(self, sql):\n        \n        return [\n            sqlparse.format(statement, strip_comments=True)\n            for statement in sqlparse.split(sql)\n            if statement\n        ]\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 68,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 32,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 50934,
        "documentation": {
            "docstring": "\n        Take an SQL script that may contain multiple lines and return a list\n        of statements to feed to successive cursor.execute() calls.\n\n        Since few databases are able to process raw SQL scripts in a single\n        cursor.execute() call and PEP 249 doesn't talk about this use case,\n        the default implementation is conservative.\n        ",
            "n_words": 50,
            "vocab_size": 44,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 19322,
        "commit_id": "32b545fe7c35b57f280cd9d570f62839886f2e4b",
        "repo": "PythonRobotics",
        "path": "utils/angle.py",
        "file_name": "angle.py",
        "fun_name": "angle_mod",
        "commit_message": "Enhance dubins path docs (#664)\n\n* Engance dubins path docs\r\n\r\n* Update dubins_path.rst\r\n\r\n* fix doc artifact link in CI\r\n\r\n* wip\r\n\r\n* wip\r\n\r\n* wip\r\n\r\n* Update dubins_path.rst\r\n\r\n* wip\r\n\r\n* wip\r\n\r\n* wip\r\n\r\n* wip\r\n\r\n* wip",
        "code": "def angle_mod(x, zero_2_2pi=False, degree=False):\n    \n    if isinstance(x, float):\n        is_float = True\n    else:\n        is_float = False\n\n    x = np.asarray(x).flatten()\n    if degree:\n        x = np.deg2rad(x)\n\n    if zero_2_2pi:\n        mod_angle = x % (2 * np.pi)\n    else:\n        mod_angle = (x + np.pi) % (2 * np.pi) - np.pi\n\n    if degree:\n        mod_angle = np.rad2deg(mod_angle)\n\n    if is_float:\n        return mod_angle.item()\n    else:\n        return mod_angle\n",
        "url": "https://github.com/AtsushiSakai/PythonRobotics.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 141,
        "n_words": 55,
        "vocab_size": 30,
        "complexity": 6,
        "nloc": 18,
        "token_counts": 114,
        "n_ast_nodes": 185,
        "n_identifiers": 15,
        "d_id": 2936,
        "documentation": {
            "docstring": "\n    Angle modulo operation\n    Default angle modulo range is [-pi, pi)\n\n    Parameters\n    ----------\n    x : float or array_like\n        A angle or an array of angles. This array is flattened for\n        the calculation. When an angle is provided, a float angle is returned.\n    zero_2_2pi : bool, optional\n        Change angle modulo range to [0, 2pi)\n        Default is False.\n    degree : bool, optional\n        If True, then the given angles are assumed to be in degrees.\n        Default is False.\n\n    Returns\n    -------\n    ret : float or ndarray\n        an angle or an array of modulated angle.\n\n    Examples\n    --------\n    >>> angle_mod(-4.0)\n    2.28318531\n\n    >>> angle_mod([-4.0])\n    np.array(2.28318531)\n\n    >>> angle_mod([-150.0, 190.0, 350], degree=True)\n    array([-150., -170.,  -10.])\n\n    >>> angle_mod(-60.0, zero_2_2pi=True, degree=True)\n    array([300.])\n\n    ",
            "n_words": 110,
            "vocab_size": 72,
            "n_whitespaces": 224,
            "language": "en"
        }
    },
    {
        "id": 20578,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pyparsing/core.py",
        "file_name": "core.py",
        "fun_name": "__ror__",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def __ror__(self, other):\n        \n        if isinstance(other, str_type):\n            other = self._literalStringClass(other)\n        if not isinstance(other, ParserElement):\n            raise TypeError(\n                \"Cannot combine element of type {} with ParserElement\".format(\n                    type(other).__name__\n                )\n            )\n        return other | self\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 140,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 52,
        "n_ast_nodes": 86,
        "n_identifiers": 11,
        "d_id": 3433,
        "documentation": {
            "docstring": "\n        Implementation of ``|`` operator when left operand is not a :class:`ParserElement`\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 116838,
        "commit_id": "e1d031d0375f0a3575fa2c4607fc0f5d5bc8044d",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers_client/db_client.py",
        "file_name": "db_client.py",
        "fun_name": "get_tables",
        "commit_message": "Move DB handlers in a separate service (#3063)\n\n* Move DB handlers in a separate service\r\n* add docker-compose initial",
        "code": "def get_tables(self) -> Response:\n        \n\n        response = None\n        log.info(\"%s: calling 'get_tables'\", self.__class__.__name__)\n\n        try:\n            r = self._do(\"/get_tables\")\n            r = self._convert_response(r.json())\n            response = Response(data_frame=r.get(\"data_frame\", None),\n                                resp_type=r.get(\"resp_type\"),\n                                error_code=r.get(\"error_code\", 0),\n                                error_message=r.get(\"error_message\", None),\n                                query=r.get(\"query\"))\n            log.info(\"%s: db service has replied. error_code - %s\", self.__class__.__name__, response.error_code)\n\n        except Exception as e:\n            response = Response(error_message=str(e),\n                                error_code=1,\n                                resp_type=RESPONSE_TYPE.ERROR)\n            log.error(\"call to db service has finished with an error: %s\", traceback.format_exc())\n\n        return response\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 354,
        "n_words": 60,
        "vocab_size": 46,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 156,
        "n_ast_nodes": 258,
        "n_identifiers": 26,
        "d_id": 25846,
        "documentation": {
            "docstring": "List all tabels in the database without the system data.\n\n        Returns:\n            A list of all records in the database in case of success\n            An error message and error code if case of fail\n        ",
            "n_words": 33,
            "vocab_size": 23,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 288765,
        "commit_id": "3ab294e8efc00c9f3cda2993318bb582ba675f8c",
        "repo": "core",
        "path": "homeassistant/components/hunterdouglas_powerview/cover.py",
        "file_name": "cover.py",
        "fun_name": "close_tilt_position",
        "commit_message": "Powerview refactor prep for all shade types (#79862)",
        "code": "def close_tilt_position(self) -> PowerviewShadeMove:\n        \n        return PowerviewShadeMove(self._shade.close_position_tilt, {})\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 21,
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        "complexity": 1,
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        "token_counts": 20,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 87917,
        "documentation": {
            "docstring": "Return the close tilt position and required additional positions.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 21764,
        "commit_id": "8faa74cdc9da20cfdcc69f5ec29b91112c95b4c9",
        "repo": "pipenv",
        "path": "pipenv/vendor/tomlkit/items.py",
        "file_name": "items.py",
        "fun_name": "append",
        "commit_message": "Update tomlkit==0.9.2\n\nUsed:\n\n python -m invoke vendoring.update --package=tomlkit",
        "code": "def append(self, key, _item):\n        \n        if not isinstance(_item, Item):\n            _item = item(_item)\n\n        self._value.append(key, _item)\n\n        if isinstance(key, Key):\n            key = next(iter(key)).key\n            _item = self._value[key]\n\n        if key is not None:\n            dict.__setitem__(self, key, _item)\n\n        m = re.match(r\"(?s)^[^ ]*([ ]+).*$\", self._trivia.indent)\n        if not m:\n            return self\n\n        indent = m.group(1)\n\n        if not isinstance(_item, Whitespace):\n            m = re.match(\"(?s)^([^ ]*)(.*)$\", _item.trivia.indent)\n            if not m:\n                _item.trivia.indent = indent\n            else:\n                _item.trivia.indent = m.group(1) + indent + m.group(2)\n\n        return self\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
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        "complexity": 7,
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        "token_counts": 166,
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        "n_identifiers": 21,
        "d_id": 4037,
        "documentation": {
            "docstring": "\n        Appends a (key, item) to the table.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 267451,
        "commit_id": "143e7fb45e7b916fa973613000e97ee889f5666c",
        "repo": "ansible",
        "path": "lib/ansible/galaxy/dependency_resolution/providers.py",
        "file_name": "providers.py",
        "fun_name": "get_preference",
        "commit_message": "ansible-galaxy - support resolvelib versions >= 0.5.3, < 0.9.0 (#77649)\n\n* ansible-galaxy - support resolvelib versions >= 0.5.3, <= 0.8.1\r\n\r\nTest incompatibilities are removed for resolvelib >= 0.6.0\r\n\r\nTest against the latest 0.8.x version and fix requirements\r\n\r\n* Fix tests - use a venv for testing the range of resolvelib versions\r\n\r\n* Update temporary hardcoded fallback for ansible-test\r\n\r\n* Update hardcoded upperbound for sanity tests\r\n\r\n* Make error check more flexible",
        "code": "def get_preference(self, *args, **kwargs):\n        # type: (t.Any, t.Any) -> t.Union[float, int]\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 14,
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        "n_identifiers": 5,
        "d_id": 78911,
        "documentation": {
            "docstring": "Return sort key function return value for given requirement.\n\n        This result should be based on preference that is defined as\n        \"I think this requirement should be resolved first\".\n        The lower the return value is, the more preferred this\n        group of arguments is.\n\n        resolvelib >=0.5.3, <0.7.0\n\n        :param resolution: Currently pinned candidate, or ``None``.\n\n        :param candidates: A list of possible candidates.\n\n        :param information: A list of requirement information.\n\n        Each ``information`` instance is a named tuple with two entries:\n\n          * ``requirement`` specifies a requirement contributing to\n            the current candidate list\n\n          * ``parent`` specifies the candidate that provides\n            (dependend on) the requirement, or `None`\n            to indicate a root requirement.\n\n        resolvelib >=0.7.0, < 0.8.0\n\n        :param identifier: The value returned by ``identify()``.\n\n        :param resolutions: Mapping of identifier, candidate pairs.\n\n        :param candidates: Possible candidates for the identifer.\n            Mapping of identifier, list of candidate pairs.\n\n        :param information: Requirement information of each package.\n            Mapping of identifier, list of named tuple pairs.\n            The named tuples have the entries ``requirement`` and ``parent``.\n\n        resolvelib >=0.8.0, <= 0.8.1\n\n        :param identifier: The value returned by ``identify()``.\n\n        :param resolutions: Mapping of identifier, candidate pairs.\n\n        :param candidates: Possible candidates for the identifer.\n            Mapping of identifier, list of candidate pairs.\n\n        :param information: Requirement information of each package.\n            Mapping of identifier, list of named tuple pairs.\n            The named tuples have the entries ``requirement`` and ``parent``.\n\n        :param backtrack_causes: Sequence of requirement information that were\n            the requirements that caused the resolver to most recently backtrack.\n\n        The preference could depend on a various of issues, including\n        (not necessarily in this order):\n\n          * Is this package pinned in the current resolution result?\n\n          * How relaxed is the requirement? Stricter ones should\n            probably be worked on first? (I don't know, actually.)\n\n          * How many possibilities are there to satisfy this\n            requirement? Those with few left should likely be worked on\n            first, I guess?\n\n          * Are there any known conflicts for this requirement?\n            We should probably work on those with the most\n            known conflicts.\n\n        A sortable value should be returned (this will be used as the\n        `key` parameter of the built-in sorting function). The smaller\n        the value is, the more preferred this requirement is (i.e. the\n        sorting function is called with ``reverse=False``).\n        ",
            "n_words": 358,
            "vocab_size": 170,
            "n_whitespaces": 766,
            "language": "en"
        }
    },
    {
        "id": 106941,
        "commit_id": "6ef6b37fc2113c041f7d2643d70b553ec335d597",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/axes3d.py",
        "file_name": "axes3d.py",
        "fun_name": "plot_wireframe",
        "commit_message": "Remove *args deprecations",
        "code": "def plot_wireframe(self, X, Y, Z, **kwargs):\n        \n\n        had_data = self.has_data()\n        if Z.ndim != 2:\n            raise ValueError(\"Argument Z must be 2-dimensional.\")\n        # FIXME: Support masked arrays\n        X, Y, Z = np.broadcast_arrays(X, Y, Z)\n        rows, cols = Z.shape\n\n        has_stride = 'rstride' in kwargs or 'cstride' in kwargs\n        has_count = 'rcount' in kwargs or 'ccount' in kwargs\n\n        if has_stride and has_count:\n            raise ValueError(\"Cannot specify both stride and count arguments\")\n\n        rstride = kwargs.pop('rstride', 1)\n        cstride = kwargs.pop('cstride', 1)\n        rcount = kwargs.pop('rcount', 50)\n        ccount = kwargs.pop('ccount', 50)\n\n        if rcParams['_internal.classic_mode']:\n            # Strides have priority over counts in classic mode.\n            # So, only compute strides from counts\n            # if counts were explicitly given\n            if has_count:\n                rstride = int(max(np.ceil(rows / rcount), 1)) if rcount else 0\n                cstride = int(max(np.ceil(cols / ccount), 1)) if ccount else 0\n        else:\n            # If the strides are provided then it has priority.\n            # Otherwise, compute the strides from the counts.\n            if not has_stride:\n                rstride = int(max(np.ceil(rows / rcount), 1)) if rcount else 0\n                cstride = int(max(np.ceil(cols / ccount), 1)) if ccount else 0\n\n        # We want two sets of lines, one running along the \"rows\" of\n        # Z and another set of lines running along the \"columns\" of Z.\n        # This transpose will make it easy to obtain the columns.\n        tX, tY, tZ = np.transpose(X), np.transpose(Y), np.transpose(Z)\n\n        if rstride:\n            rii = list(range(0, rows, rstride))\n            # Add the last index only if needed\n            if rows > 0 and rii[-1] != (rows - 1):\n                rii += [rows-1]\n        else:\n            rii = []\n        if cstride:\n            cii = list(range(0, cols, cstride))\n            # Add the last index only if needed\n            if cols > 0 and cii[-1] != (cols - 1):\n                cii += [cols-1]\n        else:\n            cii = []\n\n        if rstride == 0 and cstride == 0:\n            raise ValueError(\"Either rstride or cstride must be non zero\")\n\n        # If the inputs were empty, then just\n        # reset everything.\n        if Z.size == 0:\n            rii = []\n            cii = []\n\n        xlines = [X[i] for i in rii]\n        ylines = [Y[i] for i in rii]\n        zlines = [Z[i] for i in rii]\n\n        txlines = [tX[i] for i in cii]\n        tylines = [tY[i] for i in cii]\n        tzlines = [tZ[i] for i in cii]\n\n        lines = ([list(zip(xl, yl, zl))\n                 for xl, yl, zl in zip(xlines, ylines, zlines)]\n                 + [list(zip(xl, yl, zl))\n                 for xl, yl, zl in zip(txlines, tylines, tzlines)])\n\n        linec = art3d.Line3DCollection(lines, **kwargs)\n        self.add_collection(linec)\n        self.auto_scale_xyz(X, Y, Z, had_data)\n\n        return linec\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 1017,
        "n_words": 393,
        "vocab_size": 193,
        "complexity": 30,
        "nloc": 54,
        "token_counts": 539,
        "n_ast_nodes": 846,
        "n_identifiers": 52,
        "d_id": 22518,
        "documentation": {
            "docstring": "\n        Plot a 3D wireframe.\n\n        .. note::\n\n           The *rcount* and *ccount* kwargs, which both default to 50,\n           determine the maximum number of samples used in each direction.  If\n           the input data is larger, it will be downsampled (by slicing) to\n           these numbers of points.\n\n        Parameters\n        ----------\n        X, Y, Z : 2D arrays\n            Data values.\n\n        rcount, ccount : int\n            Maximum number of samples used in each direction.  If the input\n            data is larger, it will be downsampled (by slicing) to these\n            numbers of points.  Setting a count to zero causes the data to be\n            not sampled in the corresponding direction, producing a 3D line\n            plot rather than a wireframe plot.  Defaults to 50.\n\n        rstride, cstride : int\n            Downsampling stride in each direction.  These arguments are\n            mutually exclusive with *rcount* and *ccount*.  If only one of\n            *rstride* or *cstride* is set, the other defaults to 1.  Setting a\n            stride to zero causes the data to be not sampled in the\n            corresponding direction, producing a 3D line plot rather than a\n            wireframe plot.\n\n            'classic' mode uses a default of ``rstride = cstride = 1`` instead\n            of the new default of ``rcount = ccount = 50``.\n\n        **kwargs\n            Other arguments are forwarded to `.Line3DCollection`.\n        ",
            "n_words": 198,
            "vocab_size": 105,
            "n_whitespaces": 474,
            "language": "en"
        }
    },
    {
        "id": 181702,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_source_decode_2",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_source_decode_2():\n    \n    import_str, op_str, op_obj = source_decode(\"sklearn.linear_model.LogisticReg\")\n    from sklearn.linear_model import LogisticRegression\n    assert import_str == \"sklearn.linear_model\"\n    assert op_str == \"LogisticReg\"\n    assert op_obj is None\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 41,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 33,
        "n_ast_nodes": 60,
        "n_identifiers": 8,
        "d_id": 43489,
        "documentation": {
            "docstring": "Assert that the source_decode return None when sourcecode is not available.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 42087,
        "commit_id": "762db897b52d16ab2f164d5103df4cc26c1d0503",
        "repo": "seaborn",
        "path": "seaborn/_core/plot.py",
        "file_name": "plot.py",
        "fun_name": "save",
        "commit_message": "Add rudimentary themeing support (#2929)\n\n* WIP Plot.theme\r\n\r\n* Add default values for theme to match set_theme()\r\n\r\n* Depend on matplotib style defaults and update rcParams more selectively\r\n\r\n* Fix lines test\r\n\r\n* Improve test coverage",
        "code": "def save(self, loc, **kwargs) -> Plot:\n        \n        # TODO expose important keyword arguments in our signature?\n        with theme_context(self._theme_with_defaults()):\n            self._plot().save(loc, **kwargs)\n        return self\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 60,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 38,
        "n_ast_nodes": 66,
        "n_identifiers": 8,
        "d_id": 7483,
        "documentation": {
            "docstring": "\n        Compile the plot and write it to a buffer or file on disk.\n\n        Parameters\n        ----------\n        loc : str, path, or buffer\n            Location on disk to save the figure, or a buffer to write into.\n        kwargs\n            Other keyword arguments are passed through to\n            :meth:`matplotlib.figure.Figure.savefig`.\n\n        ",
            "n_words": 43,
            "vocab_size": 32,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 264131,
        "commit_id": "fa1e28e860c4bdb3e585a968bd248a2ac666e1f6",
        "repo": "netbox",
        "path": "netbox/extras/tests/test_customfields.py",
        "file_name": "test_customfields.py",
        "fun_name": "test_update_single_object_with_values",
        "commit_message": "Initial work on #7006",
        "code": "def test_update_single_object_with_values(self):\n        \n        site2 = Site.objects.get(name='Site 2')\n        original_cfvs = {**site2.custom_field_data}\n        data = {\n            'custom_fields': {\n                'text_field': 'ABCD',\n                'number_field': 1234,\n            },\n        }\n        url = reverse('dcim-api:site-detail', kwargs={'pk': site2.pk})\n        self.add_permissions('dcim.change_site')\n\n        response = self.client.patch(url, data, format='json', **self.header)\n        self.assertHttpStatus(response, status.HTTP_200_OK)\n\n        # Validate response data\n        response_cf = response.data['custom_fields']\n        self.assertEqual(response_cf['text_field'], data['custom_fields']['text_field'])\n        self.assertEqual(response_cf['number_field'], data['custom_fields']['number_field'])\n        self.assertEqual(response_cf['longtext_field'], original_cfvs['longtext_field'])\n        self.assertEqual(response_cf['boolean_field'], original_cfvs['boolean_field'])\n        self.assertEqual(response_cf['date_field'], original_cfvs['date_field'])\n        self.assertEqual(response_cf['url_field'], original_cfvs['url_field'])\n        self.assertEqual(response_cf['json_field'], original_cfvs['json_field'])\n        self.assertEqual(response_cf['choice_field'], original_cfvs['choice_field'])\n\n        # Validate database data\n        site2.refresh_from_db()\n        self.assertEqual(site2.custom_field_data['text_field'], data['custom_fields']['text_field'])\n        self.assertEqual(site2.custom_field_data['number_field'], data['custom_fields']['number_field'])\n        self.assertEqual(site2.custom_field_data['longtext_field'], original_cfvs['longtext_field'])\n        self.assertEqual(site2.custom_field_data['boolean_field'], original_cfvs['boolean_field'])\n        self.assertEqual(site2.custom_field_data['date_field'], original_cfvs['date_field'])\n        self.assertEqual(site2.custom_field_data['url_field'], original_cfvs['url_field'])\n        self.assertEqual(site2.custom_field_data['json_field'], original_cfvs['json_field'])\n        self.assertEqual(site2.custom_field_data['choice_field'], original_cfvs['choice_field'])\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 333,
        "n_words": 78,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 361,
        "n_ast_nodes": 623,
        "n_identifiers": 26,
        "d_id": 77617,
        "documentation": {
            "docstring": "\n        Update an object with existing custom field values. Ensure that only the updated custom field values are\n        modified.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 215170,
        "commit_id": "4e3632254fb73210ce3e1954ec507473433018b8",
        "repo": "salt",
        "path": "salt/beacons/napalm_beacon.py",
        "file_name": "napalm_beacon.py",
        "fun_name": "__virtual__",
        "commit_message": "Align enhanced logging accross beacons",
        "code": "def __virtual__():\n    \n    if salt.utils.napalm.virtual(__opts__, __virtualname__, __file__):\n        return __virtualname__\n    else:\n        err_msg = \"NAPALM is not installed.\"\n        log.error(\"Unable to load %s beacon: %s\", __virtualname__, err_msg)\n        return False, err_msg\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 63,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 71,
        "n_identifiers": 11,
        "d_id": 53868,
        "documentation": {
            "docstring": "\n    This beacon can only work when running under a regular or a proxy minion, managed through napalm.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 72424,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/views/mixins.py",
        "file_name": "mixins.py",
        "fun_name": "get_preprocess_function",
        "commit_message": "Reformat with black",
        "code": "def get_preprocess_function(self, field, value, export_format):\n        \n\n        # Try to find a field specific function and return it\n        format_dict = self.custom_field_preprocess.get(field, {})\n        if export_format in format_dict:\n            return format_dict[export_format]\n\n        # Otherwise check for a value class specific function\n        for value_classes, format_dict in self.custom_value_preprocess.items():\n            if isinstance(value, value_classes) and export_format in format_dict:\n                return format_dict[export_format]\n\n        # Finally resort to force_str to prevent encoding errors\n        return force_str\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 153,
        "n_words": 60,
        "vocab_size": 40,
        "complexity": 5,
        "nloc": 8,
        "token_counts": 67,
        "n_ast_nodes": 105,
        "n_identifiers": 13,
        "d_id": 15891,
        "documentation": {
            "docstring": "Returns the preprocessing function for a given field name, field value, and export format",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 262392,
        "commit_id": "72d85e53c98b908345bbff70f7cfba2174e883ce",
        "repo": "TTS",
        "path": "TTS/utils/generic_utils.py",
        "file_name": "generic_utils.py",
        "fun_name": "remove_experiment_folder",
        "commit_message": "Update model file extension (#1422)\n\n* Update model file ext to ```.pth```\r\n\r\n* Update docs\r\n\r\n* Rename more\r\n\r\n* Find model files",
        "code": "def remove_experiment_folder(experiment_path):\n    \n    fs = fsspec.get_mapper(experiment_path).fs\n    checkpoint_files = fs.glob(experiment_path + \"/*.pth\")\n    if not checkpoint_files:\n        if fs.exists(experiment_path):\n            fs.rm(experiment_path, recursive=True)\n            print(\" ! Run is removed from {}\".format(experiment_path))\n    else:\n        print(\" ! Run is kept in {}\".format(experiment_path))\n\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 83,
        "n_words": 32,
        "vocab_size": 25,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 68,
        "n_ast_nodes": 120,
        "n_identifiers": 12,
        "d_id": 77203,
        "documentation": {
            "docstring": "Check folder if there is a checkpoint, otherwise remove the folder",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 102073,
        "commit_id": "48c886b3dce3d3117ad16edaf35c8abd28dc51f5",
        "repo": "faceswap",
        "path": "lib/sysinfo.py",
        "file_name": "sysinfo.py",
        "fun_name": "full_info",
        "commit_message": "Allow decoding errors",
        "code": "def full_info(self):\n        \n        retval = \"\\n============ System Information ============\\n\"\n        sys_info = {\"os_platform\": self._system[\"platform\"],\n                    \"os_machine\": self._system[\"machine\"],\n                    \"os_release\": self._system[\"release\"],\n                    \"py_conda_version\": self._conda_version,\n                    \"py_implementation\": self._python[\"implementation\"],\n                    \"py_version\": self._python[\"version\"],\n                    \"py_command\": self._fs_command,\n                    \"py_virtual_env\": self._is_virtual_env,\n                    \"sys_cores\": self._system[\"cpu_count\"],\n                    \"sys_processor\": self._system[\"processor\"],\n                    \"sys_ram\": self._format_ram(),\n                    \"encoding\": self._encoding,\n                    \"git_branch\": self._git_branch,\n                    \"git_commits\": self._git_commits,\n                    \"gpu_cuda\": self._cuda_version,\n                    \"gpu_cudnn\": self._cudnn_version,\n                    \"gpu_driver\": self._gpu[\"driver\"],\n                    \"gpu_devices\": \", \".join([f\"GPU_{idx}: {device}\"\n                                              for idx, device in enumerate(self._gpu[\"devices\"])]),\n                    \"gpu_vram\": \", \".join([f\"GPU_{idx}: {int(vram)}MB\"\n                                           for idx, vram in enumerate(self._gpu[\"vram\"])]),\n                    \"gpu_devices_active\": \", \".join([f\"GPU_{idx}\"\n                                                     for idx in self._gpu[\"devices_active\"]])}\n        for key in sorted(sys_info.keys()):\n            retval += (f\"{key + ':':<20} {sys_info[key]}\\n\")\n        retval += \"\\n=============== Pip Packages ===============\\n\"\n        retval += self._installed_pip\n        if self._is_conda:\n            retval += \"\\n\\n============== Conda Packages ==============\\n\"\n            retval += self._installed_conda\n        retval += self._state_file\n        retval += \"\\n\\n================= Configs ==================\"\n        retval += self._configs\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 722,
        "n_words": 112,
        "vocab_size": 84,
        "complexity": 6,
        "nloc": 36,
        "token_counts": 267,
        "n_ast_nodes": 519,
        "n_identifiers": 30,
        "d_id": 21438,
        "documentation": {
            "docstring": " Obtain extensive system information stats, formatted into a human readable format.\n\n        Returns\n        -------\n        str\n            The system information for the currently running system, formatted for output to\n            console or a log file.\n        ",
            "n_words": 31,
            "vocab_size": 26,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 100266,
        "commit_id": "444762114c1b1ad2e72c871e825373bd74880aba",
        "repo": "faceswap",
        "path": "lib/gpu_stats.py",
        "file_name": "gpu_stats.py",
        "fun_name": "_get_handles",
        "commit_message": "Initial somewhat working version",
        "code": "def _get_handles(self):\n        \n        if self._is_plaidml:\n            self._handles = self._plaid.devices\n        elif IS_MACOS:\n            self._handles = metal.get_handles()\n        else:\n            self._handles = [pynvml.nvmlDeviceGetHandleByIndex(i)\n                             for i in range(self._device_count)]\n        self._log(\"debug\", \"GPU Handles found: {}\".format(len(self._handles)))\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 121,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 73,
        "n_ast_nodes": 123,
        "n_identifiers": 17,
        "d_id": 19776,
        "documentation": {
            "docstring": " Obtain the internal handle identifiers for the system GPUs and allocate to\n        :attr:`_handles`. ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 308133,
        "commit_id": "7a6897c7578dffd6b67f57747ebd81b67b153e01",
        "repo": "core",
        "path": "tests/components/deconz/test_climate.py",
        "file_name": "test_climate.py",
        "fun_name": "test_boost_mode",
        "commit_message": "Add deconz current hvac operation to thermostate based on \"state\" (#59989)\n\n* deconz - add current hvac operation to thermostate based on \"state\"\r\n\r\n* deconz - extend current hvac operation to thermostate based on \"state\" and \"mode\"\r\n\r\n* Add tests for current hvac action\r\n\r\n* Add boost mode as special case\r\n\r\n* format using Black\r\n\r\n* sort imports\r\n\r\n* Add test for device with mode none and state none\r\n\r\n* Update homeassistant/components/deconz/climate.py\r\n\r\nCo-authored-by: Robert Svensson <Kane610@users.noreply.github.com>\r\n\r\n* Fix test_climate.py test_no_mode_no_state\r\n\r\n* Add test for boost mode\r\n\r\nCo-authored-by: Robert Svensson <Kane610@users.noreply.github.com>",
        "code": "async def test_boost_mode(hass, aioclient_mock, mock_deconz_websocket):\n    \n    data = {\n        \"sensors\": {\n            \"0\": {\n                \"config\": {\n                    \"battery\": 58,\n                    \"heatsetpoint\": 2200,\n                    \"locked\": False,\n                    \"mode\": \"heat\",\n                    \"offset\": -200,\n                    \"on\": True,\n                    \"preset\": \"manual\",\n                    \"reachable\": True,\n                    \"schedule\": {},\n                    \"schedule_on\": False,\n                    \"setvalve\": False,\n                    \"windowopen_set\": False,\n                },\n                \"ep\": 1,\n                \"etag\": \"404c15db68c318ebe7832ce5aa3d1e30\",\n                \"lastannounced\": \"2022-08-31T03:00:59Z\",\n                \"lastseen\": \"2022-09-19T11:58Z\",\n                \"manufacturername\": \"_TZE200_b6wax7g0\",\n                \"modelid\": \"TS0601\",\n                \"name\": \"Thermostat\",\n                \"state\": {\n                    \"lastupdated\": \"2022-09-19T11:58:24.204\",\n                    \"lowbattery\": False,\n                    \"on\": False,\n                    \"temperature\": 2200,\n                    \"valve\": 0,\n                },\n                \"type\": \"ZHAThermostat\",\n                \"uniqueid\": \"84:fd:27:ff:fe:8a:eb:89-01-0201\",\n            }\n        }\n    }\n    with patch.dict(DECONZ_WEB_REQUEST, data):\n        config_entry = await setup_deconz_integration(hass, aioclient_mock)\n\n    assert len(hass.states.async_all()) == 3\n\n    climate_thermostat = hass.states.get(\"climate.thermostat\")\n\n    assert climate_thermostat.state == HVACMode.HEAT\n\n    assert climate_thermostat.attributes[\"preset_mode\"] is DECONZ_PRESET_MANUAL\n    assert climate_thermostat.attributes[\"hvac_action\"] is HVACAction.IDLE\n\n    # Event signals thermostat preset boost and valve 100 (real data)\n    event_changed_sensor = {\n        \"t\": \"event\",\n        \"e\": \"changed\",\n        \"r\": \"sensors\",\n        \"id\": \"0\",\n        \"config\": {\"preset\": \"boost\"},\n        \"state\": {\"valve\": 100},\n    }\n\n    await mock_deconz_websocket(data=event_changed_sensor)\n    await hass.async_block_till_done()\n\n    climate_thermostat = hass.states.get(\"climate.thermostat\")\n    assert climate_thermostat.attributes[\"preset_mode\"] is PRESET_BOOST\n    assert climate_thermostat.attributes[\"hvac_action\"] is HVACAction.HEATING\n\n    # Verify service calls\n    mock_deconz_put_request(aioclient_mock, config_entry.data, \"/sensors/0/config\")\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 811,
        "n_words": 151,
        "vocab_size": 112,
        "complexity": 1,
        "nloc": 58,
        "token_counts": 297,
        "n_ast_nodes": 549,
        "n_identifiers": 27,
        "d_id": 106894,
        "documentation": {
            "docstring": "Test that a climate device with boost mode and different state works.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 321260,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/mainwindow/prompt.py",
        "file_name": "prompt.py",
        "fun_name": "keyPressEvent",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def keyPressEvent(self, e):\n        \n        if e.key() == Qt.Key.Key_Insert and e.modifiers() == Qt.KeyboardModifier.ShiftModifier:\n            try:\n                text = utils.get_clipboard(selection=True, fallback=True)\n            except utils.ClipboardError:  # pragma: no cover\n                e.ignore()\n            else:\n                e.accept()\n                self.insert(text)\n            return\n        super().keyPressEvent(e)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 154,
        "n_words": 28,
        "vocab_size": 27,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 81,
        "n_ast_nodes": 137,
        "n_identifiers": 20,
        "d_id": 117615,
        "documentation": {
            "docstring": "Override keyPressEvent to paste primary selection on Shift + Ins.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 248920,
        "commit_id": "0f971ca68e808dd16f53f5594a6b33b7bddcc9a9",
        "repo": "synapse",
        "path": "tests/federation/test_federation_client.py",
        "file_name": "test_federation_client.py",
        "fun_name": "test_get_pdu_returns_nothing_when_event_does_not_exist",
        "commit_message": "Update `get_pdu` to return the original, pristine `EventBase` (#13320)\n\nUpdate `get_pdu` to return the untouched, pristine `EventBase` as it was originally seen over federation (no metadata added). Previously, we returned the same `event` reference that we stored in the cache which downstream code modified in place and added metadata like setting it as an `outlier`  and essentially poisoned our cache. Now we always return a copy of the `event` so the original can stay pristine in our cache and re-used for the next cache call.\r\n\r\nSplit out from https://github.com/matrix-org/synapse/pull/13205\r\n\r\nAs discussed at:\r\n\r\n - https://github.com/matrix-org/synapse/pull/13205#discussion_r918365746\r\n - https://github.com/matrix-org/synapse/pull/13205#discussion_r918366125\r\n\r\nRelated to https://github.com/matrix-org/synapse/issues/12584. This PR doesn't fix that issue because it hits [`get_event` which exists from the local database before it tries to `get_pdu`](https://github.com/matrix-org/synapse/blob/7864f33e286dec22368dc0b11c06eebb1462a51e/synapse/federation/federation_client.py#L581-L594).",
        "code": "def test_get_pdu_returns_nothing_when_event_does_not_exist(self):\n        \n        remote_pdu = self.get_success(\n            self.hs.get_federation_client().get_pdu(\n                [\"yet.another.server\"],\n                \"event_should_not_exist\",\n                RoomVersions.V9,\n            )\n        )\n        self.assertEqual(remote_pdu, None)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 108,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 42,
        "n_ast_nodes": 71,
        "n_identifiers": 10,
        "d_id": 72511,
        "documentation": {
            "docstring": "No event should be returned when the event does not exist",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 76676,
        "commit_id": "5fe2554934e5f9d6f27cf2bd4333b8ebe24ae592",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_edit_handlers.py",
        "file_name": "test_edit_handlers.py",
        "fun_name": "test_form",
        "commit_message": "Refactor commenting forms to receive the user object on instantiation\n\nUse the inherit_kwargs feature added to django-modelcluster in https://github.com/wagtail/django-modelcluster/pull/156 / https://github.com/wagtail/django-modelcluster/pull/157 to pass the for_user attribute from the root form to the comments formset; this means we don't have to construct a form class on the fly with the user embedded, and so don't need to bind to a request object before retrieving the form definition.",
        "code": "def test_form(self):\n        \n        form = self.EventPageForm(\n            instance=self.event_page, for_user=self.commenting_user\n        )\n\n        self.assertIn(\"comments\", form.formsets)\n\n        comments_formset = form.formsets[\"comments\"]\n        self.assertEqual(len(comments_formset.forms), 1)\n        self.assertEqual(comments_formset.forms[0].for_user, self.commenting_user)\n\n        replies_formset = comments_formset.forms[0].formsets[\"replies\"]\n        self.assertEqual(len(replies_formset.forms), 2)\n        self.assertEqual(replies_formset.forms[0].for_user, self.commenting_user)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 105,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 115,
        "n_ast_nodes": 182,
        "n_identifiers": 15,
        "d_id": 16567,
        "documentation": {
            "docstring": "\n        Check that the form has the comments/replies formsets, and that the\n        user has been set on each CommentForm/CommentReplyForm instance\n        ",
            "n_words": 19,
            "vocab_size": 15,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 60247,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/draw.py",
        "file_name": "draw.py",
        "fun_name": "get_pydot_graph",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def get_pydot_graph(caffe_net, rankdir, label_edges=True, phase=None):\n    \n    pydot_graph = pydot.Dot(caffe_net.name if caffe_net.name else 'Net',\n                            graph_type='digraph',\n                            rankdir=rankdir)\n    pydot_nodes = {}\n    pydot_edges = []\n    for layer in caffe_net.layer:\n        if phase is not None:\n          included = False\n          if len(layer.include) == 0:\n            included = True\n          if len(layer.include) > 0 and len(layer.exclude) > 0:\n            raise ValueError('layer ' + layer.name + ' has both include '\n                             'and exclude specified.')\n          for layer_phase in layer.include:\n            included = included or layer_phase.phase == phase\n          for layer_phase in layer.exclude:\n            included = included and not layer_phase.phase == phase\n          if not included:\n            continue\n        node_label = get_layer_label(layer, rankdir)\n        node_name = \"%s_%s\" % (layer.name, layer.type)\n        if (len(layer.bottom) == 1 and len(layer.top) == 1 and\n           layer.bottom[0] == layer.top[0]):\n            # We have an in-place neuron layer.\n            pydot_nodes[node_name] = pydot.Node(node_label,\n                                                **NEURON_LAYER_STYLE)\n        else:\n            layer_style = LAYER_STYLE_DEFAULT\n            layer_style['fillcolor'] = choose_color_by_layertype(layer.type)\n            pydot_nodes[node_name] = pydot.Node(node_label, **layer_style)\n        for bottom_blob in layer.bottom:\n            pydot_nodes[bottom_blob + '_blob'] = pydot.Node('%s' % bottom_blob,\n                                                            **BLOB_STYLE)\n            edge_label = '\"\"'\n            pydot_edges.append({'src': bottom_blob + '_blob',\n                                'dst': node_name,\n                                'label': edge_label})\n        for top_blob in layer.top:\n            pydot_nodes[top_blob + '_blob'] = pydot.Node('%s' % (top_blob))\n            if label_edges:\n                edge_label = get_edge_label(layer)\n            else:\n                edge_label = '\"\"'\n            pydot_edges.append({'src': node_name,\n                                'dst': top_blob + '_blob',\n                                'label': edge_label})\n    # Now, add the nodes and edges to the graph.\n    for node in pydot_nodes.values():\n        pydot_graph.add_node(node)\n    for edge in pydot_edges:\n        pydot_graph.add_edge(\n            pydot.Edge(pydot_nodes[edge['src']],\n                       pydot_nodes[edge['dst']],\n                       label=edge['label']))\n    return pydot_graph\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 946,
        "n_words": 208,
        "vocab_size": 121,
        "complexity": 20,
        "nloc": 54,
        "token_counts": 406,
        "n_ast_nodes": 667,
        "n_identifiers": 43,
        "d_id": 12040,
        "documentation": {
            "docstring": "Create a data structure which represents the `caffe_net`.\n\n    Parameters\n    ----------\n    caffe_net : object\n    rankdir : {'LR', 'TB', 'BT'}\n        Direction of graph layout.\n    label_edges : boolean, optional\n        Label the edges (default is True).\n    phase : {caffe_pb2.Phase.TRAIN, caffe_pb2.Phase.TEST, None} optional\n        Include layers from this network phase.  If None, include all layers.\n        (the default is None)\n\n    Returns\n    -------\n    pydot graph object\n    ",
            "n_words": 58,
            "vocab_size": 50,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 120239,
        "commit_id": "bb2682db6df5b9388ce0b161e3f449624238718b",
        "repo": "jax",
        "path": "jax/_src/numpy/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_lstsq",
        "commit_message": "remove numpy.linalg._promote_arg_dtypes\n\nin favor of numpy.util._promote_dtypes_inexact",
        "code": "def _lstsq(a, b, rcond, *, numpy_resid=False):\n  # TODO: add lstsq to lax_linalg and implement this function via those wrappers.\n  # TODO: add custom jvp rule for more robust lstsq differentiation\n  a, b = _promote_dtypes_inexact(a, b)\n  if a.shape[0] != b.shape[0]:\n    raise ValueError(\"Leading dimensions of input arrays must match\")\n  b_orig_ndim = b.ndim\n  if b_orig_ndim == 1:\n    b = b[:, None]\n  if a.ndim != 2:\n    raise TypeError(\n      f\"{a.ndim}-dimensional array given. Array must be two-dimensional\")\n  if b.ndim != 2:\n    raise TypeError(\n      f\"{b.ndim}-dimensional array given. Array must be one or two-dimensional\")\n  m, n = a.shape\n  dtype = a.dtype\n  if rcond is None:\n    rcond = jnp.finfo(dtype).eps * max(n, m)\n  else:\n    rcond = jnp.where(rcond < 0, jnp.finfo(dtype).eps, rcond)\n  u, s, vt = svd(a, full_matrices=False)\n  mask = s >= rcond * s[0]\n  rank = mask.sum()\n  safe_s = jnp.where(mask, s, 1)\n  s_inv = jnp.where(mask, 1 / safe_s, 0)[:, jnp.newaxis]\n  uTb = jnp.matmul(u.conj().T, b, precision=lax.Precision.HIGHEST)\n  x = jnp.matmul(vt.conj().T, s_inv * uTb, precision=lax.Precision.HIGHEST)\n  # Numpy returns empty residuals in some cases. To allow compilation, we\n  # default to returning full residuals in all cases.\n  if numpy_resid and (rank < n or m <= n):\n    resid = jnp.asarray([])\n  else:\n    b_estimate = jnp.matmul(a, x, precision=lax.Precision.HIGHEST)\n    resid = norm(b - b_estimate, axis=0) ** 2\n  if b_orig_ndim == 1:\n    x = x.ravel()\n  return x, resid, rank, s\n\n_jit_lstsq = jit(partial(_lstsq, numpy_resid=False))\n\n@_wraps(np.linalg.lstsq, lax_description=textwrap.dedent())",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.linalg.lstsq, lax_description=textwrap.dedent(\"\"\"\\\n    It has two important differences:\n\n    1. In `numpy.linalg.lstsq`, the default `rcond` is `-1`, and warns that in the future\n       the default will be `None`. Here, the default rcond is `None`.\n    2. In `np.linalg.lstsq` the returned residuals are empty for low-rank or over-determined\n       solutions. Here, the residuals are returned in all cases, to make the function\n       compatible with jit. The non-jit compatible numpy behavior can be recovered by\n       passing numpy_resid=True.\n\n    The lstsq function does not currently have a custom JVP rule, so the gradient is\n    poorly behaved for some inputs, particularly for low-rank `a`.\n    \"\"\"))",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 280,
        "n_words": 218,
        "vocab_size": 145,
        "complexity": 10,
        "nloc": 34,
        "token_counts": 336,
        "n_ast_nodes": 580,
        "n_identifiers": 55,
        "d_id": 26804,
        "documentation": {
            "docstring": "\\\n    It has two important differences:\n\n    1. In `numpy.linalg.lstsq`, the default `rcond` is `-1`, and warns that in the future\n       the default will be `None`. Here, the default rcond is `None`.\n    2. In `np.linalg.lstsq` the returned residuals are empty for low-rank or over-determined\n       solutions. Here, the residuals are returned in all cases, to make the function\n       compatible with jit. The non-jit compatible numpy behavior can be recovered by\n       passing numpy_resid=True.\n\n    The lstsq function does not currently have a custom JVP rule, so the gradient is\n    poorly behaved for some inputs, particularly for low-rank `a`.\n    ",
            "n_words": 94,
            "vocab_size": 69,
            "n_whitespaces": 136,
            "language": "en"
        }
    },
    {
        "id": 140345,
        "commit_id": "d2f0c3b2f64b41f6541f6521e98cf3a37577c016",
        "repo": "ray",
        "path": "python/ray/tune/automlboard/backend/collector.py",
        "file_name": "collector.py",
        "fun_name": "_add_results",
        "commit_message": "Clean up docstyle in data, ml, and tune packages (#25188)",
        "code": "def _add_results(self, results, trial_id):\n        \n        for result in results:\n            self.logger.debug(\"Appending result: %s\" % result)\n            result[\"trial_id\"] = trial_id\n            result_record = ResultRecord.from_json(result)\n            result_record.save()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 78,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 44,
        "n_ast_nodes": 75,
        "n_identifiers": 11,
        "d_id": 31929,
        "documentation": {
            "docstring": "Add a list of results into db.\n\n        Args:\n            results: A list of json results.\n            trial_id: Id of the trial.\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 201522,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/auth_tests/test_views.py",
        "file_name": "test_views.py",
        "fun_name": "test_login_session_without_hash_session_key",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_login_session_without_hash_session_key(self):\n        \n        user = User.objects.get(username=\"testclient\")\n        engine = import_module(settings.SESSION_ENGINE)\n        session = engine.SessionStore()\n        session[SESSION_KEY] = user.id\n        session.save()\n        original_session_key = session.session_key\n        self.client.cookies[settings.SESSION_COOKIE_NAME] = original_session_key\n\n        self.login()\n        self.assertNotEqual(original_session_key, self.client.session.session_key)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 94,
        "n_words": 24,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 82,
        "n_ast_nodes": 136,
        "n_identifiers": 23,
        "d_id": 49961,
        "documentation": {
            "docstring": "\n        Session without django.contrib.auth.HASH_SESSION_KEY should login\n        without an exception.\n        ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 176154,
        "commit_id": "dec723f072eb997a497a159dbe8674cd39999ee9",
        "repo": "networkx",
        "path": "networkx/generators/small.py",
        "file_name": "small.py",
        "fun_name": "house_graph",
        "commit_message": "Docstrings for the small.py module (#5240)\n\n* added description for the first 5 small graphs\r\n\r\n* modified descriptions based on comment and added description for two more functions\r\n\r\n* added doctrings to all the functions\r\n\r\n* Minor touchups.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def house_graph(create_using=None):\n    \n    description = [\n        \"adjacencylist\",\n        \"House Graph\",\n        5,\n        [[2, 3], [1, 4], [1, 4, 5], [2, 3, 5], [3, 4]],\n    ]\n    G = make_small_undirected_graph(description, create_using)\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 71,
        "n_words": 28,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 90,
        "n_identifiers": 5,
        "d_id": 41724,
        "documentation": {
            "docstring": "\n    Returns the House graph (square with triangle on top)\n\n    The house graph is a simple undirected graph with\n    5 nodes and 6 edges [1]_.\n\n    Parameters\n    ----------\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Returns\n    -------\n    G : networkx Graph\n        House graph in the form of a square with a triangle on top\n\n    References\n    ----------\n    .. [1] https://mathworld.wolfram.com/HouseGraph.html\n    ",
            "n_words": 68,
            "vocab_size": 51,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 218397,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/inspect.py",
        "file_name": "inspect.py",
        "fun_name": "getclosurevars",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getclosurevars(func):\n    \n\n    if ismethod(func):\n        func = func.__func__\n\n    if not isfunction(func):\n        raise TypeError(\"{!r} is not a Python function\".format(func))\n\n    code = func.__code__\n    # Nonlocal references are named in co_freevars and resolved\n    # by looking them up in __closure__ by positional index\n    if func.__closure__ is None:\n        nonlocal_vars = {}\n    else:\n        nonlocal_vars = {\n            var : cell.cell_contents\n            for var, cell in zip(code.co_freevars, func.__closure__)\n       }\n\n    # Global and builtin references are named in co_names and resolved\n    # by looking them up in __globals__ or __builtins__\n    global_ns = func.__globals__\n    builtin_ns = global_ns.get(\"__builtins__\", builtins.__dict__)\n    if ismodule(builtin_ns):\n        builtin_ns = builtin_ns.__dict__\n    global_vars = {}\n    builtin_vars = {}\n    unbound_names = set()\n    for name in code.co_names:\n        if name in (\"None\", \"True\", \"False\"):\n            # Because these used to be builtins instead of keywords, they\n            # may still show up as name references. We ignore them.\n            continue\n        try:\n            global_vars[name] = global_ns[name]\n        except KeyError:\n            try:\n                builtin_vars[name] = builtin_ns[name]\n            except KeyError:\n                unbound_names.add(name)\n\n    return ClosureVars(nonlocal_vars, global_vars,\n                       builtin_vars, unbound_names)\n\n# -------------------------------------------------- stack frame extraction\n\nTraceback = namedtuple('Traceback', 'filename lineno function code_context index')\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 419,
        "n_words": 165,
        "vocab_size": 113,
        "complexity": 10,
        "nloc": 32,
        "token_counts": 181,
        "n_ast_nodes": 319,
        "n_identifiers": 34,
        "d_id": 55282,
        "documentation": {
            "docstring": "\n    Get the mapping of free variables to their current values.\n\n    Returns a named tuple of dicts mapping the current nonlocal, global\n    and builtin references as seen by the body of the function. A final\n    set of unbound names that could not be resolved is also provided.\n    ",
            "n_words": 46,
            "vocab_size": 38,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 250719,
        "commit_id": "6f0587734e2525eab49ba9a1d2052c87922125c7",
        "repo": "mitmproxy",
        "path": "mitmproxy/optmanager.py",
        "file_name": "optmanager.py",
        "fun_name": "process_deferred",
        "commit_message": "Refactor how we process `--set` options (#5067)\n\n* refactor how we process `--set` options\r\n\r\n* minor improvements based on @marwinxxii's review\r\n\r\n* fix nits\r\n\r\n* update changelog",
        "code": "def process_deferred(self) -> None:\n        \n        update: typing.Dict[str, typing.Any] = {}\n        for optname, value in self.deferred.items():\n            if optname in self._options:\n                if isinstance(value, _UnconvertedStrings):\n                    value = self._parse_setval(self._options[optname], value.val)\n                update[optname] = value\n        self.update(**update)\n        for k in update.keys():\n            del self.deferred[k]\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 141,
        "n_words": 35,
        "vocab_size": 27,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 97,
        "n_ast_nodes": 151,
        "n_identifiers": 18,
        "d_id": 73536,
        "documentation": {
            "docstring": "\n            Processes options that were deferred in previous calls to set, and\n            have since been added.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 119845,
        "commit_id": "6cd9804163203e4da13b33171c5889b6d17e5f43",
        "repo": "jax",
        "path": "jax/interpreters/mlir.py",
        "file_name": "mlir.py",
        "fun_name": "_minmax_mhlo",
        "commit_message": "Replace (deprecated) StrEnumAttr with EnumAttr.\n\nref: https://reviews.llvm.org/D120834\nPiperOrigin-RevId: 435550738",
        "code": "def _minmax_mhlo(op, cmp, x, y):\n  \n  tensor_type = ir.RankedTensorType(x.type)\n  if ir.ComplexType.isinstance(tensor_type.element_type):\n    rx = mhlo.RealOp(x).result\n    ry = mhlo.RealOp(y).result\n    dims = [tensor_type.get_dim_size(i) for i in range(tensor_type.rank)]\n    bool_shape = ir.RankedTensorType.get(dims, ir.IntegerType.get_signless(1))\n    if jax._src.lib.mlir_api_version >= 3:\n      real_eq = mhlo.CompareOp(bool_shape, rx, ry,\n                               mhlo.ComparisonDirectionAttr.get(\"EQ\"),\n                               mhlo.ComparisonTypeAttr.get(\"FLOAT\"))\n      real_cmp = mhlo.CompareOp(bool_shape, rx, ry,\n                                mhlo.ComparisonDirectionAttr.get(cmp),\n                                mhlo.ComparisonTypeAttr.get(\"FLOAT\"))\n      imag_cmp = mhlo.CompareOp(bool_shape,\n                                mhlo.ImagOp(x).result,\n                                mhlo.ImagOp(y).result,\n                                mhlo.ComparisonDirectionAttr.get(cmp),\n                                mhlo.ComparisonTypeAttr.get(\"FLOAT\"))\n    else:\n      real_eq = mhlo.CompareOp(bool_shape, rx, ry, ir.StringAttr.get(\"EQ\"),\n                               ir.StringAttr.get(\"FLOAT\"))\n      real_cmp = mhlo.CompareOp(bool_shape, rx, ry, ir.StringAttr.get(cmp),\n                                ir.StringAttr.get(\"FLOAT\"))\n      imag_cmp = mhlo.CompareOp(bool_shape,\n                                mhlo.ImagOp(x).result,\n                                mhlo.ImagOp(y).result, ir.StringAttr.get(cmp),\n                                ir.StringAttr.get(\"FLOAT\"))\n    which = mhlo.SelectOp(real_eq, imag_cmp, real_cmp).result\n    return mhlo.SelectOp(which, x, y)\n  else:\n    return op(x, y)\n\nmin_mhlo = partial(_minmax_mhlo, mhlo.MinOp, \"LT\")\nmax_mhlo = partial(_minmax_mhlo, mhlo.MaxOp, \"GT\")\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 556,
        "n_words": 97,
        "vocab_size": 56,
        "complexity": 4,
        "nloc": 32,
        "token_counts": 347,
        "n_ast_nodes": 570,
        "n_identifiers": 45,
        "d_id": 26700,
        "documentation": {
            "docstring": "Min/max that compares complex values lexicographically as pairs.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 247311,
        "commit_id": "2ffaf30803f93273a4d8a65c9e6c3110c8433488",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "test_invites_by_users_ratelimit",
        "commit_message": "Add type hints to `tests/rest/client` (#12108)\n\n* Add type hints to `tests/rest/client`\r\n\r\n* newsfile\r\n\r\n* fix imports\r\n\r\n* add `test_account.py`\r\n\r\n* Remove one type hint in `test_report_event.py`\r\n\r\n* change `on_create_room` to `async`\r\n\r\n* update new functions in `test_third_party_rules.py`\r\n\r\n* Add `test_filter.py`\r\n\r\n* add `test_rooms.py`\r\n\r\n* change to `assertEquals` to `assertEqual`\r\n\r\n* lint",
        "code": "def test_invites_by_users_ratelimit(self) -> None:\n        \n\n        for _ in range(3):\n            room_id = self.helper.create_room_as(self.user_id)\n            self.helper.invite(room_id, self.user_id, \"@other-users:red\")\n\n        room_id = self.helper.create_room_as(self.user_id)\n        self.helper.invite(room_id, self.user_id, \"@other-users:red\", expect_code=429)\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 71,
        "n_words": 21,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 72,
        "n_ast_nodes": 115,
        "n_identifiers": 10,
        "d_id": 71582,
        "documentation": {
            "docstring": "Tests that invites to a specific user are actually rate-limited.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 218384,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/inspect.py",
        "file_name": "inspect.py",
        "fun_name": "get_annotations",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_annotations(obj, *, globals=None, locals=None, eval_str=False):\n    \n    if isinstance(obj, type):\n        # class\n        obj_dict = getattr(obj, '__dict__', None)\n        if obj_dict and hasattr(obj_dict, 'get'):\n            ann = obj_dict.get('__annotations__', None)\n            if isinstance(ann, types.GetSetDescriptorType):\n                ann = None\n        else:\n            ann = None\n\n        obj_globals = None\n        module_name = getattr(obj, '__module__', None)\n        if module_name:\n            module = sys.modules.get(module_name, None)\n            if module:\n                obj_globals = getattr(module, '__dict__', None)\n        obj_locals = dict(vars(obj))\n        unwrap = obj\n    elif isinstance(obj, types.ModuleType):\n        # module\n        ann = getattr(obj, '__annotations__', None)\n        obj_globals = getattr(obj, '__dict__')\n        obj_locals = None\n        unwrap = None\n    elif callable(obj):\n        # this includes types.Function, types.BuiltinFunctionType,\n        # types.BuiltinMethodType, functools.partial, functools.singledispatch,\n        # \"class funclike\" from Lib/test/test_inspect... on and on it goes.\n        ann = getattr(obj, '__annotations__', None)\n        obj_globals = getattr(obj, '__globals__', None)\n        obj_locals = None\n        unwrap = obj\n    else:\n        raise TypeError(f\"{obj!r} is not a module, class, or callable.\")\n\n    if ann is None:\n        return {}\n\n    if not isinstance(ann, dict):\n        raise ValueError(f\"{obj!r}.__annotations__ is neither a dict nor None\")\n\n    if not ann:\n        return {}\n\n    if not eval_str:\n        return dict(ann)\n\n    if unwrap is not None:\n        while True:\n            if hasattr(unwrap, '__wrapped__'):\n                unwrap = unwrap.__wrapped__\n                continue\n            if isinstance(unwrap, functools.partial):\n                unwrap = unwrap.func\n                continue\n            break\n        if hasattr(unwrap, \"__globals__\"):\n            obj_globals = unwrap.__globals__\n\n    if globals is None:\n        globals = obj_globals\n    if locals is None:\n        locals = obj_locals\n\n    return_value = {key:\n        value if not isinstance(value, str) else eval(value, globals, locals)\n        for key, value in ann.items() }\n    return return_value\n\n\n# ----------------------------------------------------------- type-checking",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 676,
        "n_words": 222,
        "vocab_size": 108,
        "complexity": 22,
        "nloc": 56,
        "token_counts": 347,
        "n_ast_nodes": 573,
        "n_identifiers": 38,
        "d_id": 55272,
        "documentation": {
            "docstring": "Compute the annotations dict for an object.\n\n    obj may be a callable, class, or module.\n    Passing in an object of any other type raises TypeError.\n\n    Returns a dict.  get_annotations() returns a new dict every time\n    it's called; calling it twice on the same object will return two\n    different but equivalent dicts.\n\n    This function handles several details for you:\n\n      * If eval_str is true, values of type str will\n        be un-stringized using eval().  This is intended\n        for use with stringized annotations\n        (\"from __future__ import annotations\").\n      * If obj doesn't have an annotations dict, returns an\n        empty dict.  (Functions and methods always have an\n        annotations dict; classes, modules, and other types of\n        callables may not.)\n      * Ignores inherited annotations on classes.  If a class\n        doesn't have its own annotations dict, returns an empty dict.\n      * All accesses to object members and dict values are done\n        using getattr() and dict.get() for safety.\n      * Always, always, always returns a freshly-created dict.\n\n    eval_str controls whether or not values of type str are replaced\n    with the result of calling eval() on those values:\n\n      * If eval_str is true, eval() is called on values of type str.\n      * If eval_str is false (the default), values of type str are unchanged.\n\n    globals and locals are passed in to eval(); see the documentation\n    for eval() for more information.  If either globals or locals is\n    None, this function may replace that value with a context-specific\n    default, contingent on type(obj):\n\n      * If obj is a module, globals defaults to obj.__dict__.\n      * If obj is a class, globals defaults to\n        sys.modules[obj.__module__].__dict__ and locals\n        defaults to the obj class namespace.\n      * If obj is a callable, globals defaults to obj.__globals__,\n        although if obj is a wrapped function (using\n        functools.update_wrapper()) it is first unwrapped.\n    ",
            "n_words": 290,
            "vocab_size": 146,
            "n_whitespaces": 468,
            "language": "en"
        }
    },
    {
        "id": 266206,
        "commit_id": "d4a231585ac9a25d9739552d8c9e433dbf9398af",
        "repo": "netbox",
        "path": "netbox/ipam/tests/test_ordering.py",
        "file_name": "test_ordering.py",
        "fun_name": "test_prefix_complex_ordering",
        "commit_message": "Clean up tests",
        "code": "def test_prefix_complex_ordering(self):\n        \n        vrf1, vrf2, vrf3 = list(VRF.objects.all())\n        prefixes = [\n            Prefix(status=PrefixStatusChoices.STATUS_CONTAINER, vrf=None, prefix=netaddr.IPNetwork('10.0.0.0/8')),\n            Prefix(status=PrefixStatusChoices.STATUS_CONTAINER, vrf=None, prefix=netaddr.IPNetwork('10.0.0.0/16')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=None, prefix=netaddr.IPNetwork('10.1.0.0/16')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=None, prefix=netaddr.IPNetwork('192.168.0.0/16')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.0.0/24')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.1.0/24')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.0.1.0/25')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.1.0.0/24')),\n            Prefix(status=PrefixStatusChoices.STATUS_ACTIVE, vrf=vrf1, prefix=netaddr.IPNetwork('10.1.1.0/24')),\n        ]\n        Prefix.objects.bulk_create(prefixes)\n\n        # Test\n        self._compare(Prefix.objects.all(), prefixes)\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 191,
        "n_words": 43,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 246,
        "n_ast_nodes": 378,
        "n_identifiers": 21,
        "d_id": 78338,
        "documentation": {
            "docstring": "\n        This function tests a complex ordering of interwoven prefixes and vrfs.  This is the current expected ordering of VRFs\n        This includes the testing of the Container status.\n\n        The proper ordering, to get proper containerization should be:\n            None:10.0.0.0/8\n            None:10.0.0.0/16\n            VRF A:10.0.0.0/24\n            VRF A:10.0.1.0/24\n            VRF A:10.0.1.0/25\n            None:10.1.0.0/16\n            VRF A:10.1.0.0/24\n            VRF A:10.1.1.0/24\n            None: 192.168.0.0/16\n        ",
            "n_words": 51,
            "vocab_size": 39,
            "n_whitespaces": 180,
            "language": "en"
        }
    },
    {
        "id": 177007,
        "commit_id": "8522eea3955f5cf3da43cacc27643d93768aeb03",
        "repo": "networkx",
        "path": "networkx/algorithms/community/tests/test_louvain.py",
        "file_name": "test_louvain.py",
        "fun_name": "test_directed_partition",
        "commit_message": "Correct louvain formula, solve infinite loops (#5713)\n\nFixes the formulae used to calculate gain and removal cost in calculation\r\nof one level of the Louvain partition tree. Errors here were causing infinite loops\r\nfor some cases in the past, see gh-5175 and gh-5704.\r\n\r\nThis PR also adds test cases to ensure infinite loops are not entered for these cases.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def test_directed_partition():\n    \n    G = nx.DiGraph()\n    H = nx.DiGraph()\n    G.add_nodes_from(range(10))\n    H.add_nodes_from([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])\n    G_edges = [\n        (0, 2),\n        (0, 1),\n        (1, 0),\n        (2, 1),\n        (2, 0),\n        (3, 4),\n        (4, 3),\n        (7, 8),\n        (8, 7),\n        (9, 10),\n        (10, 9),\n    ]\n    H_edges = [\n        (1, 2),\n        (1, 6),\n        (1, 9),\n        (2, 3),\n        (2, 4),\n        (2, 5),\n        (3, 4),\n        (4, 3),\n        (4, 5),\n        (5, 4),\n        (6, 7),\n        (6, 8),\n        (9, 10),\n        (9, 11),\n        (10, 11),\n        (11, 10),\n    ]\n    G.add_edges_from(G_edges)\n    H.add_edges_from(H_edges)\n\n    G_expected_partition = [{0, 1, 2}, {3, 4}, {5}, {6}, {8, 7}, {9, 10}]\n    G_partition = louvain_communities(G, seed=123, weight=None)\n\n    H_expected_partition = [{2, 3, 4, 5}, {8, 1, 6, 7}, {9, 10, 11}]\n    H_partition = louvain_communities(H, seed=123, weight=None)\n\n    assert G_partition == G_expected_partition\n    assert H_partition == H_expected_partition\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 368,
        "n_words": 128,
        "vocab_size": 72,
        "complexity": 1,
        "nloc": 44,
        "token_counts": 342,
        "n_ast_nodes": 442,
        "n_identifiers": 17,
        "d_id": 42220,
        "documentation": {
            "docstring": "\n    Test 2 cases that were looping infinitely\n    from issues #5175 and #5704\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 243702,
        "commit_id": "2ae55ccbdad9c842929fb238ea1eb81d1f999024",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "tobitmap",
        "commit_message": "Improve exception traceback readability",
        "code": "def tobitmap(self, name=\"image\"):\n        \n\n        self.load()\n        if self.mode != \"1\":\n            msg = \"not a bitmap\"\n            raise ValueError(msg)\n        data = self.tobytes(\"xbm\")\n        return b\"\".join(\n            [\n                f\"#define {name}_width {self.size[0]}\\n\".encode(\"ascii\"),\n                f\"#define {name}_height {self.size[1]}\\n\".encode(\"ascii\"),\n                f\"static char {name}_bits[] = {{\\n\".encode(\"ascii\"),\n                data,\n                b\"};\",\n            ]\n        )\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 197,
        "n_words": 36,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 76,
        "n_ast_nodes": 173,
        "n_identifiers": 12,
        "d_id": 70075,
        "documentation": {
            "docstring": "\n        Returns the image converted to an X11 bitmap.\n\n        .. note:: This method only works for mode \"1\" images.\n\n        :param name: The name prefix to use for the bitmap variables.\n        :returns: A string containing an X11 bitmap.\n        :raises ValueError: If the mode is not \"1\"\n        ",
            "n_words": 44,
            "vocab_size": 35,
            "n_whitespaces": 87,
            "language": "en"
        }
    },
    {
        "id": 109359,
        "commit_id": "438d30b227b1fef7e8733578f851e76a8e360f24",
        "repo": "matplotlib",
        "path": "lib/matplotlib/offsetbox.py",
        "file_name": "offsetbox.py",
        "fun_name": "set_fontsize",
        "commit_message": "Get rcParams from mpl",
        "code": "def set_fontsize(self, s=None):\n        \n        if s is None:\n            s = mpl.rcParams[\"legend.fontsize\"]\n\n        self.prop = FontProperties(size=s)\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 55,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 38,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 23550,
        "documentation": {
            "docstring": "\n        Set the fontsize in points.\n\n        If *s* is not given, reset to :rc:`legend.fontsize`.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 101553,
        "commit_id": "7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5",
        "repo": "faceswap",
        "path": "lib/training/preview_tk.py",
        "file_name": "preview_tk.py",
        "fun_name": "slider_var",
        "commit_message": "Training - Use custom preview pop-out",
        "code": "def slider_var(self) -> tk.IntVar:\n        \n        retval = self._vars[\"slider\"]\n        assert isinstance(retval, tk.IntVar)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 29,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 20963,
        "documentation": {
            "docstring": ":class:`tkinter.IntVar`: The variable holding the currently selected percentage scaling\n        amount in the slider. ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 331789,
        "commit_id": "c6e4b7895a7dbcd9b98396cbef383dd1c72b0ad3",
        "repo": "pytorch-image-models",
        "path": "timm/models/swin_transformer_v2_cr.py",
        "file_name": "swin_transformer_v2_cr.py",
        "fun_name": "_make_pair_wise_relative_positions",
        "commit_message": "Swin V2 CR impl refactor.\n* reformat and change some naming so closer to existing timm vision transformers\n* remove typing that wasn't adding clarity (or causing torchscript issues)\n* support non-square windows\n* auto window size adjust from image size\n* post-norm + main-branch no",
        "code": "def _make_pair_wise_relative_positions(self) -> None:\n        \n        device = self.tau.device\n        coordinates = torch.stack(torch.meshgrid([\n            torch.arange(self.window_size[0], device=device),\n            torch.arange(self.window_size[1], device=device)]), dim=0).flatten(1)\n        relative_coordinates = coordinates[:, :, None] - coordinates[:, None, :]\n        relative_coordinates = relative_coordinates.permute(1, 2, 0).reshape(-1, 2).float()\n        relative_coordinates_log = torch.sign(relative_coordinates) * torch.log(\n            1.0 + relative_coordinates.abs())\n        self.register_buffer(\"relative_coordinates_log\", relative_coordinates_log, persistent=False)\n",
        "url": "https://github.com/huggingface/pytorch-image-models.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 123,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 147,
        "n_ast_nodes": 223,
        "n_identifiers": 22,
        "d_id": 119926,
        "documentation": {
            "docstring": "Method initializes the pair-wise relative positions to compute the positional biases.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 101499,
        "commit_id": "dc18c74eea0c7837a820d27628cb12b0824fa30e",
        "repo": "faceswap",
        "path": "lib/gui/utils.py",
        "file_name": "utils.py",
        "fun_name": "_get_newest_folder",
        "commit_message": "Bugfix: Preview for extract in batch mode",
        "code": "def _get_newest_folder(self) -> str:\n        \n        assert self._pathoutput is not None\n        folders = [os.path.join(self._pathoutput, folder)\n                   for folder in os.listdir(self._pathoutput)\n                   if os.path.isdir(os.path.join(self._pathoutput, folder))]\n        folders.sort(key=os.path.getmtime)\n        retval = folders[-1] if folders else self._pathoutput\n        logger.debug(\"sorted folders: %s, return value: %s\", folders, retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 123,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 19,
        "token_counts": 99,
        "n_ast_nodes": 153,
        "n_identifiers": 17,
        "d_id": 20911,
        "documentation": {
            "docstring": " Obtain the most recent folder created in the extraction output folder when processing\n        in batch mode.\n\n        Returns\n        -------\n        str\n            The most recently modified folder within the parent output folder. If no folders have\n            been created, returns the parent output folder\n\n        ",
            "n_words": 40,
            "vocab_size": 29,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 176291,
        "commit_id": "b5d41847b8db0c82372faf69cd3a339d11da7ef0",
        "repo": "networkx",
        "path": "networkx/algorithms/shortest_paths/generic.py",
        "file_name": "generic.py",
        "fun_name": "average_shortest_path_length",
        "commit_message": "DOC: Update documentation to include callables for weight argument (#5307)\n\nUpdate docs to include functions as valid input for weight argument.",
        "code": "def average_shortest_path_length(G, weight=None, method=None):\n    r\n    single_source_methods = [\"unweighted\", \"dijkstra\", \"bellman-ford\"]\n    all_pairs_methods = [\"floyd-warshall\", \"floyd-warshall-numpy\"]\n    supported_methods = single_source_methods + all_pairs_methods\n\n    if method is None:\n        method = \"unweighted\" if weight is None else \"dijkstra\"\n    if method not in supported_methods:\n        raise ValueError(f\"method not supported: {method}\")\n\n    n = len(G)\n    # For the special case of the null graph, raise an exception, since\n    # there are no paths in the null graph.\n    if n == 0:\n        msg = (\n            \"the null graph has no paths, thus there is no average\"\n            \"shortest path length\"\n        )\n        raise nx.NetworkXPointlessConcept(msg)\n    # For the special case of the trivial graph, return zero immediately.\n    if n == 1:\n        return 0\n    # Shortest path length is undefined if the graph is disconnected.\n    if G.is_directed() and not nx.is_weakly_connected(G):\n        raise nx.NetworkXError(\"Graph is not weakly connected.\")\n    if not G.is_directed() and not nx.is_connected(G):\n        raise nx.NetworkXError(\"Graph is not connected.\")\n\n    # Compute all-pairs shortest paths.",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 272,
        "n_words": 147,
        "vocab_size": 85,
        "complexity": 16,
        "nloc": 93,
        "token_counts": 239,
        "n_ast_nodes": 248,
        "n_identifiers": 17,
        "d_id": 41808,
        "documentation": {
            "docstring": "Returns the average shortest path length.\n\n    The average shortest path length is\n\n    .. math::\n\n       a =\\sum_{s,t \\in V} \\frac{d(s, t)}{n(n-1)}\n\n    where `V` is the set of nodes in `G`,\n    `d(s, t)` is the shortest path from `s` to `t`,\n    and `n` is the number of nodes in `G`.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n\n    weight : None, string or function, optional (default = None)\n        If None, every edge has weight/distance/cost 1.\n        If a string, use this edge attribute as the edge weight.\n        Any edge attribute not present defaults to 1.\n        If this is a function, the weight of an edge is the value\n        returned by the function. The function must accept exactly\n        three positional arguments: the two endpoints of an edge and\n        the dictionary of edge attributes for that edge.\n        The function must return a number.\n\n    method : string, optional (default = 'unweighted' or 'djikstra')\n        The algorithm to use to compute the path lengths.\n        Supported options are 'unweighted', 'dijkstra', 'bellman-ford',\n        'floyd-warshall' and 'floyd-warshall-numpy'.\n        Other method values produce a ValueError.\n        The default method is 'unweighted' if `weight` is None,\n        otherwise the default method is 'dijkstra'.\n\n    Raises\n    ------\n    NetworkXPointlessConcept\n        If `G` is the null graph (that is, the graph on zero nodes).\n\n    NetworkXError\n        If `G` is not connected (or not weakly connected, in the case\n        of a directed graph).\n\n    ValueError\n        If `method` is not among the supported options.\n\n    Examples\n    --------\n    >>> G = nx.path_graph(5)\n    >>> nx.average_shortest_path_length(G)\n    2.0\n\n    For disconnected graphs, you can compute the average shortest path\n    length for each component\n\n    >>> G = nx.Graph([(1, 2), (3, 4)])\n    >>> for C in (G.subgraph(c).copy() for c in nx.connected_components(G)):\n    ...     print(nx.average_shortest_path_length(C))\n    1.0\n    1.0\n\n    ",
            "n_words": 269,
            "vocab_size": 156,
            "n_whitespaces": 489,
            "language": "en"
        }
    },
    {
        "id": 119250,
        "commit_id": "b7e1fec2500daec9e42e79c5983183c759e318ed",
        "repo": "jax",
        "path": "tests/transfer_guard_test.py",
        "file_name": "transfer_guard_test.py",
        "fun_name": "assertDisallows",
        "commit_message": "Implement the JAX transfer guard API\n\nAdds `--jax_transfer_guard` flag and `jax.transfer_guard()` context manager that allows logging or disallowing unintended transfers.\n\nThe API distinguishes between two types of transfers:\n* explicit transfers: `jax.device_put*()` and `jax.device_get()` calls.\n* implicit transfers: Other transfers (e.g., printing a `DeviceArray`).\n\nThe transfer guard can take an action based on its guard level:\n\n* \"allow\": Silently allow all transfers (default; same as the previous behavior).\n* \"log\": Log and allow implicit transfers. Silently allow explicit transfers.\n* \"disallow\": Disallow implicit transfers. Silently allow explicit transfers.\n* \"log_explicit\": Log and allow all transfers.\n* \"disallow_explicit\": Disallow all transfers.\n\nThe API also allows fine-control the transfer guard level of individual transfer directions. Their flag and context manager names are suffixed with the transfer direction:\n\n* \"host_to_device\": Converting a Python value into a `DeviceBuffer`.\n* \"device_to_device\": Copying a `DeviceBuffer` to a different device.\n* \"device_to_host\": Fetching the value of a `DeviceBuffer`.\n\nExample:\n```\nx = jnp.array(1)\ny = jnp.array(2)\nz = jnp.array(3)\n\nprint(x)  # No error\nwith jax.transfer_guard(\"disallow\"):\n  print(x)  # No error; x is already fetched\n  print(jax.device_get(y))  # No error\n  print(z)  # Error!\n```\n\nPiperOrigin-RevId: 427562278",
        "code": "def assertDisallows(self, func_name):\n      \n      try:\n        with self.assertRaises(Exception):\n          yield\n      except Exception as e:  # pylint: disable=broad-except\n        raise RuntimeError(\n            f\"Expected a transfer to be disallowed while running: {func_name}\"\n        ) from e\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 85,
        "n_words": 28,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 32,
        "n_ast_nodes": 63,
        "n_identifiers": 7,
        "d_id": 26562,
        "documentation": {
            "docstring": "Asserts that a transfer in the context is disallowed.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 178559,
        "commit_id": "31e4a7edb61212d4dddafb281ea9c842e646e508",
        "repo": "Nuitka",
        "path": "nuitka/plugins/PluginBase.py",
        "file_name": "PluginBase.py",
        "fun_name": "onModuleEncounter",
        "commit_message": "Cleanup, avoid \"shlib\" naming, and use \"extension\" instead.\n\n* This should make the code more clear for others to read.",
        "code": "def onModuleEncounter(self, module_filename, module_name, module_kind):\n        \n        # Virtual method, pylint: disable=no-self-use,unused-argument\n        return None\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 14,
        "n_ast_nodes": 23,
        "n_identifiers": 5,
        "d_id": 42744,
        "documentation": {
            "docstring": "Help decide whether to include a module.\n\n        Args:\n            module_filename: filename\n            module_name: full module name\n            module_kind: one of \"py\", \"extension\" (shared library)\n        Returns:\n            True or False\n        ",
            "n_words": 25,
            "vocab_size": 25,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 82410,
        "commit_id": "c1290c9ff89cb00caa5469129fd527e9d82cd820",
        "repo": "django-cms",
        "path": "cms/tests/test_nested_plugins.py",
        "file_name": "test_nested_plugins.py",
        "fun_name": "copy_placeholders_and_check_results",
        "commit_message": "ci: Added codespell (#7355)\n\nCo-authored-by: Christian Clauss <cclauss@me.com>\r\n\r\n* ci: codespell config taken from #7292",
        "code": "def copy_placeholders_and_check_results(self, placeholders):\n        \n\n        for original_placeholder in placeholders:\n\n            # get the plugins\n            original_plugins = original_placeholder.get_plugins()\n\n            # copy them to a new placeholder\n            copied_placeholder = Placeholder.objects.create(slot=original_placeholder.slot)\n            copy_plugins_to(\n                original_placeholder.get_plugins(),\n                copied_placeholder\n            )\n\n            copied_plugins = copied_placeholder.get_plugins()\n\n            # we should find the same number of plugins in both placeholders\n            self.assertEqual(\n                original_plugins.count(),\n                copied_plugins.count()\n            )\n\n            # quick check: make sure the two querysets match:\n            for original, copy in zip(original_plugins, copied_plugins):\n                self.assertEqual(\n                    Text.objects.get(id=original.id).body,\n                    Text.objects.get(id=copy.id).body\n                )\n\n            # Now build a *tree* of the plugins, and match those - it's not\n            # enough just to compare querysets as above; we should *also* check\n            # that when we build a tree, the various nodes are assembled as we\n            # would expect. We will pump the trees into a pair of lists:\n            original_plugins_list = []\n            copied_plugins_list = []\n\n            # This function builds the tree of plugins, starting from its roots.\n            # In that respect it's like many of the plugin tree-building\n            # routines elsewhere in the system.",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 527,
        "n_words": 154,
        "vocab_size": 103,
        "complexity": 4,
        "nloc": 54,
        "token_counts": 321,
        "n_ast_nodes": 204,
        "n_identifiers": 24,
        "d_id": 17385,
        "documentation": {
            "docstring": "\n        This function is not itself a test; rather, it can be used by any test\n        that has created placeholders. It will check that whatever the plugin\n        structure in the placeholder, it will be copied accurately when they are\n        copied.\n\n        placeholders is a list of placeholders\n        ",
            "n_words": 45,
            "vocab_size": 37,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 321856,
        "commit_id": "ee4d6e0396a6b570f4d5592a9c4c1a9fee1027b6",
        "repo": "qutebrowser",
        "path": "tests/unit/misc/test_sql.py",
        "file_name": "test_sql.py",
        "fun_name": "test_sqlite_error_codes",
        "commit_message": "sql: Add *all* primary sqlite result codes\n\nFor three reasons:\n\n- There are only 31 of them, and we don't really expect any more to\n  turn up (last happened in 2013, and we have a test for it happening)\n- It makes for nicer debug output\n- It always felt strange to only have a small subset in the enum",
        "code": "def test_sqlite_error_codes(self, code):\n        \n        pyvalue = getattr(sqlite3, f\"SQLITE_{code.name}\")\n        assert pyvalue == code.value\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 45,
        "n_identifiers": 8,
        "d_id": 117948,
        "documentation": {
            "docstring": "Cross check our error codes with the ones in Python 3.11+.\n\n        See https://github.com/python/cpython/commit/86d8b465231\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 79156,
        "commit_id": "cf3cea9a5b171efff525baefe7d25df6f7cd2c60",
        "repo": "wagtail",
        "path": "wagtail/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_latest_revision_as_object",
        "commit_message": "Add docs for RevisionMixin",
        "code": "def get_latest_revision_as_object(self):\n        \n        latest_revision = self.get_latest_revision()\n        if latest_revision:\n            return latest_revision.as_object()\n        return self\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 50,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 24,
        "n_ast_nodes": 43,
        "n_identifiers": 5,
        "d_id": 16874,
        "documentation": {
            "docstring": "\n        Returns the latest revision of the object as an instance of the model.\n        If no latest revision exists, returns the object itself.\n        ",
            "n_words": 22,
            "vocab_size": 15,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 133942,
        "commit_id": "297341e107daee1ea3aff991ae8ea8c90993c683",
        "repo": "ray",
        "path": "python/ray/tests/test_client.py",
        "file_name": "test_client.py",
        "fun_name": "test_empty_objects",
        "commit_message": "[Test][Client] Only start ray once in client tests (#28835)\n\nIt looks like we're frequently starting and shutting down Ray in this test because `ray_start_client_server` isn't connecting to the Ray created by `ray_start_regular_shared`, and is instead starting a new Ray head process every time it launches.\r\n\r\nRay client tests are failing frequently with:\r\n\r\n```\r\n[2022-10-06 07:31:46,253 E 13235 13751] core_worker_process.cc:277: The core worker has already been shutdown. This happens when the language frontend accesses the Ray's worker after it is shutdown. The process will exit\r\n```\r\n\r\nWhich is probably caused by having multiple ray clusters running simultaneous, with some shutting down asynchronously. This refactor forces all of the tests in the module to use the same Ray cluster.\r\n\r\nAlso fixes two other sources of potential flakiness:\r\n* Joins the thread in test_client_thread_safe (seems like this has a bad interaction when the client server is cleaned up)\r\n* Calls ray.get in `test_stdout_log_stream`, to make sure that the remote function is done running before we try searching for its output\r\n\r\nShould also have the happy side effect of speeding up test_client.\r\n\r\nRan the `Small & Client` tests (regular and external redis) twice each, no flakes, and windows version of test_client.",
        "code": "def test_empty_objects(call_ray_start_shared):\n    \n    objects = [0, b\"\", \"\", [], np.array(()), {}, set(), None]\n    with ray_start_client_server_for_address(call_ray_start_shared) as ray:\n        for obj in objects:\n            ref = ray.put(obj)\n            if isinstance(obj, np.ndarray):\n                assert np.array_equal(ray.get(ref), obj)\n            else:\n                assert ray.get(ref) == obj\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 113,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 92,
        "n_ast_nodes": 147,
        "n_identifiers": 15,
        "d_id": 30158,
        "documentation": {
            "docstring": "\n    Tests that client works with \"empty\" objects. Sanity check, since put requests\n    will fail if the serialized version of an object consists of zero bytes.\n    ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 140353,
        "commit_id": "d2f0c3b2f64b41f6541f6521e98cf3a37577c016",
        "repo": "ray",
        "path": "python/ray/tune/automlboard/common/utils.py",
        "file_name": "utils.py",
        "fun_name": "parse_multiple_json",
        "commit_message": "Clean up docstyle in data, ml, and tune packages (#25188)",
        "code": "def parse_multiple_json(json_file, offset=None):\n    \n    json_info_list = []\n    if not os.path.exists(json_file):\n        return json_info_list\n\n    try:\n        with open(json_file, \"r\") as f:\n            if offset:\n                f.seek(offset)\n            for line in f:\n                if line[-1] != \"\\n\":\n                    # Incomplete line\n                    break\n                json_info = json.loads(line)\n                json_info_list.append(json_info)\n                offset += len(line)\n    except BaseException as e:\n        logging.error(e.message)\n\n    return json_info_list, offset\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 221,
        "n_words": 47,
        "vocab_size": 38,
        "complexity": 6,
        "nloc": 17,
        "token_counts": 100,
        "n_ast_nodes": 173,
        "n_identifiers": 21,
        "d_id": 31937,
        "documentation": {
            "docstring": "Parse multiple json records from the given file.\n\n    Seek to the offset as the start point before parsing\n    if offset set. return empty list if the json file does\n    not exists or exception occurs.\n\n    Args:\n        json_file: File path to be parsed.\n        offset: Initial seek position of the file.\n\n    Returns:\n        A dict of json info.\n        New offset after parsing.\n\n    ",
            "n_words": 58,
            "vocab_size": 46,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 248221,
        "commit_id": "699192fc1a1055a4bec2345bc80f120f28470c73",
        "repo": "synapse",
        "path": "tests/config/test_workers.py",
        "file_name": "test_workers.py",
        "fun_name": "test_worker_duty_configs",
        "commit_message": "Add the `update_user_directory_from_worker` configuration option (superseding `update_user_directory`) to allow a generic worker to be designated as the worker to update the user directory. (#12654)\n\nCo-authored-by: Shay <hillerys@element.io>",
        "code": "def test_worker_duty_configs(self) -> None:\n        \n\n        worker1_config = self._make_worker_config(\n            worker_app=\"synapse.app.generic_worker\",\n            worker_name=\"worker1\",\n            extras={\n                \"notify_appservices_from_worker\": \"worker2\",\n                \"update_user_directory_from_worker\": \"worker1\",\n            },\n        )\n        self.assertFalse(worker1_config.should_notify_appservices)\n        self.assertTrue(worker1_config.should_update_user_directory)\n\n        worker2_config = self._make_worker_config(\n            worker_app=\"synapse.app.generic_worker\",\n            worker_name=\"worker2\",\n            extras={\n                \"notify_appservices_from_worker\": \"worker2\",\n                \"update_user_directory_from_worker\": \"worker1\",\n            },\n        )\n        self.assertTrue(worker2_config.should_notify_appservices)\n        self.assertFalse(worker2_config.should_update_user_directory)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 243,
        "n_words": 32,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 96,
        "n_ast_nodes": 170,
        "n_identifiers": 12,
        "d_id": 72159,
        "documentation": {
            "docstring": "\n        Additional tests for the worker duties\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 45476,
        "commit_id": "69f6f9e01b6df76c3c8fa266d460324163957887",
        "repo": "airflow",
        "path": "airflow/migrations/versions/8d48763f6d53_add_unique_constraint_to_conn_id.py",
        "file_name": "8d48763f6d53_add_unique_constraint_to_conn_id.py",
        "fun_name": "upgrade",
        "commit_message": "Autogenerate migration reference doc (#21601)\n\n* document airflow version in each alembic migration module and use this to autogen the doc\r\n* update each migration module to have the same description used in migration ref (so it can be used in autogen)",
        "code": "def upgrade():\n    \n    try:\n        with op.batch_alter_table('connection') as batch_op:\n            batch_op.alter_column(\"conn_id\", nullable=False, existing_type=sa.String(250, **COLLATION_ARGS))\n            batch_op.create_unique_constraint(constraint_name=\"unique_conn_id\", columns=[\"conn_id\"])\n\n    except sa.exc.IntegrityError:\n        raise Exception(\"Make sure there are no duplicate connections with the same conn_id or null values\")\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 75,
        "n_words": 30,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 65,
        "n_ast_nodes": 117,
        "n_identifiers": 16,
        "d_id": 8603,
        "documentation": {
            "docstring": "Apply Add unique constraint to ``conn_id`` and set it as non-nullable",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 198452,
        "commit_id": "6a9ff86786f73ca07fa9004913037de6ba5cb155",
        "repo": "sympy",
        "path": "sympy/solvers/pde.py",
        "file_name": "pde.py",
        "fun_name": "classify_pde",
        "commit_message": "More list comprehensions",
        "code": "def classify_pde(eq, func=None, dict=False, *, prep=True, **kwargs):\n    \n\n    if func and len(func.args) != 2:\n        raise NotImplementedError(\"Right now only partial \"\n            \"differential equations of two variables are supported\")\n\n    if prep or func is None:\n        prep, func_ = _preprocess(eq, func)\n        if func is None:\n            func = func_\n\n    if isinstance(eq, Equality):\n        if eq.rhs != 0:\n            return classify_pde(eq.lhs - eq.rhs, func)\n        eq = eq.lhs\n\n    f = func.func\n    x = func.args[0]\n    y = func.args[1]\n    fx = f(x,y).diff(x)\n    fy = f(x,y).diff(y)\n\n    # TODO : For now pde.py uses support offered by the ode_order function\n    # to find the order with respect to a multi-variable function. An\n    # improvement could be to classify the order of the PDE on the basis of\n    # individual variables.\n    order = ode_order(eq, f(x,y))\n\n    # hint:matchdict or hint:(tuple of matchdicts)\n    # Also will contain \"default\":<default hint> and \"order\":order items.\n    matching_hints = {'order': order}\n\n    if not order:\n        if dict:\n            matching_hints[\"default\"] = None\n            return matching_hints\n        else:\n            return ()\n\n    eq = expand(eq)\n\n    a = Wild('a', exclude = [f(x,y)])\n    b = Wild('b', exclude = [f(x,y), fx, fy, x, y])\n    c = Wild('c', exclude = [f(x,y), fx, fy, x, y])\n    d = Wild('d', exclude = [f(x,y), fx, fy, x, y])\n    e = Wild('e', exclude = [f(x,y), fx, fy])\n    n = Wild('n', exclude = [x, y])\n    # Try removing the smallest power of f(x,y)\n    # from the highest partial derivatives of f(x,y)\n    reduced_eq = None\n    if eq.is_Add:\n        var = set(combinations_with_replacement((x,y), order))\n        dummyvar = var.copy()\n        power = None\n        for i in var:\n            coeff = eq.coeff(f(x,y).diff(*i))\n            if coeff != 1:\n                match = coeff.match(a*f(x,y)**n)\n                if match and match[a]:\n                    power = match[n]\n                    dummyvar.remove(i)\n                    break\n            dummyvar.remove(i)\n        for i in dummyvar:\n            coeff = eq.coeff(f(x,y).diff(*i))\n            if coeff != 1:\n                match = coeff.match(a*f(x,y)**n)\n                if match and match[a] and match[n] < power:\n                    power = match[n]\n        if power:\n            den = f(x,y)**power\n            reduced_eq = Add(*[arg/den for arg in eq.args])\n    if not reduced_eq:\n        reduced_eq = eq\n\n    if order == 1:\n        reduced_eq = collect(reduced_eq, f(x, y))\n        r = reduced_eq.match(b*fx + c*fy + d*f(x,y) + e)\n        if r:\n            if not r[e]:\n                ## Linear first-order homogeneous partial-differential\n                ## equation with constant coefficients\n                r.update({'b': b, 'c': c, 'd': d})\n                matching_hints[\"1st_linear_constant_coeff_homogeneous\"] = r\n            else:\n                if r[b]**2 + r[c]**2 != 0:\n                    ## Linear first-order general partial-differential\n                    ## equation with constant coefficients\n                    r.update({'b': b, 'c': c, 'd': d, 'e': e})\n                    matching_hints[\"1st_linear_constant_coeff\"] = r\n                    matching_hints[\n                        \"1st_linear_constant_coeff_Integral\"] = r\n\n        else:\n            b = Wild('b', exclude=[f(x, y), fx, fy])\n            c = Wild('c', exclude=[f(x, y), fx, fy])\n            d = Wild('d', exclude=[f(x, y), fx, fy])\n            r = reduced_eq.match(b*fx + c*fy + d*f(x,y) + e)\n            if r:\n                r.update({'b': b, 'c': c, 'd': d, 'e': e})\n                matching_hints[\"1st_linear_variable_coeff\"] = r\n\n    # Order keys based on allhints.\n    retlist = [i for i in allhints if i in matching_hints]\n\n    if dict:\n        # Dictionaries are ordered arbitrarily, so make note of which\n        # hint would come first for pdsolve().  Use an ordered dict in Py 3.\n        matching_hints[\"default\"] = None\n        matching_hints[\"ordered_hints\"] = tuple(retlist)\n        for i in allhints:\n            if i in matching_hints:\n                matching_hints[\"default\"] = i\n                break\n        return matching_hints\n    else:\n        return tuple(retlist)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 1390,
        "n_words": 489,
        "vocab_size": 234,
        "complexity": 33,
        "nloc": 89,
        "token_counts": 837,
        "n_ast_nodes": 1330,
        "n_identifiers": 54,
        "d_id": 48937,
        "documentation": {
            "docstring": "\n    Returns a tuple of possible pdsolve() classifications for a PDE.\n\n    The tuple is ordered so that first item is the classification that\n    pdsolve() uses to solve the PDE by default.  In general,\n    classifications near the beginning of the list will produce\n    better solutions faster than those near the end, though there are\n    always exceptions.  To make pdsolve use a different classification,\n    use pdsolve(PDE, func, hint=<classification>).  See also the pdsolve()\n    docstring for different meta-hints you can use.\n\n    If ``dict`` is true, classify_pde() will return a dictionary of\n    hint:match expression terms. This is intended for internal use by\n    pdsolve().  Note that because dictionaries are ordered arbitrarily,\n    this will most likely not be in the same order as the tuple.\n\n    You can get help on different hints by doing help(pde.pde_hintname),\n    where hintname is the name of the hint without \"_Integral\".\n\n    See sympy.pde.allhints or the sympy.pde docstring for a list of all\n    supported hints that can be returned from classify_pde.\n\n\n    Examples\n    ========\n\n    >>> from sympy.solvers.pde import classify_pde\n    >>> from sympy import Function, Eq\n    >>> from sympy.abc import x, y\n    >>> f = Function('f')\n    >>> u = f(x, y)\n    >>> ux = u.diff(x)\n    >>> uy = u.diff(y)\n    >>> eq = Eq(1 + (2*(ux/u)) + (3*(uy/u)), 0)\n    >>> classify_pde(eq)\n    ('1st_linear_constant_coeff_homogeneous',)\n    ",
            "n_words": 204,
            "vocab_size": 136,
            "n_whitespaces": 296,
            "language": "en"
        }
    },
    {
        "id": 243052,
        "commit_id": "c854bf8d1c05022bec4309fbf6b547e494db9373",
        "repo": "Pillow",
        "path": "src/PIL/ImageFont.py",
        "file_name": "ImageFont.py",
        "fun_name": "getlength",
        "commit_message": "add getbbox and getlength to basic ImageFont and update related tests",
        "code": "def getlength(self, text, *args, **kwargs):\n        \n        width, height = self.font.getsize(text)\n        return width\n\n\n##\n# Wrapper for FreeType fonts.  Application code should use the\n# <b>truetype</b> factory function to create font objects.\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 49,
        "n_words": 30,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 48,
        "n_identifiers": 9,
        "d_id": 69962,
        "documentation": {
            "docstring": "\n        Returns length (in pixels) of given text.\n        This is the amount by which following text should be offset.\n\n        .. versionadded:: 9.2.0\n        ",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 64544,
        "commit_id": "517fbf1d1f0a7d44e817b3f22ae30142e7bdf4c8",
        "repo": "erpnext",
        "path": "erpnext/stock/doctype/pick_list/pick_list.py",
        "file_name": "pick_list.py",
        "fun_name": "get_available_item_locations_for_batched_item",
        "commit_message": "fix: Ambigous column in picklist query",
        "code": "def get_available_item_locations_for_batched_item(item_code, from_warehouses, required_qty, company):\n\twarehouse_condition = 'and warehouse in %(warehouses)s' if from_warehouses else ''\n\tbatch_locations = frappe.db.sql(.format(warehouse_condition=warehouse_condition), { #nosec\n\t\t'item_code': item_code,\n\t\t'company': company,\n\t\t'today': today(),\n\t\t'warehouses': from_warehouses\n\t}, as_dict=1)\n\n\treturn batch_locations\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 23,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 30,
        "token_counts": 61,
        "n_ast_nodes": 102,
        "n_identifiers": 13,
        "d_id": 13659,
        "documentation": {
            "docstring": "\n\t\tSELECT\n\t\t\tsle.`warehouse`,\n\t\t\tsle.`batch_no`,\n\t\t\tSUM(sle.`actual_qty`) AS `qty`\n\t\tFROM\n\t\t\t`tabStock Ledger Entry` sle, `tabBatch` batch\n\t\tWHERE\n\t\t\tsle.batch_no = batch.name\n\t\t\tand sle.`item_code`=%(item_code)s\n\t\t\tand sle.`company` = %(company)s\n\t\t\tand batch.disabled = 0\n\t\t\tand sle.is_cancelled=0\n\t\t\tand IFNULL(batch.`expiry_date`, '2200-01-01') > %(today)s\n\t\t\t{warehouse_condition}\n\t\tGROUP BY\n\t\t\tsle.`warehouse`,\n\t\t\tsle.`batch_no`,\n\t\t\tsle.`item_code`\n\t\tHAVING `qty` > 0\n\t\tORDER BY IFNULL(batch.`expiry_date`, '2200-01-01'), batch.`creation`\n\t",
            "n_words": 49,
            "vocab_size": 36,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 308103,
        "commit_id": "f453726b1862d1d247f6aefdd5f23455b87c11cf",
        "repo": "core",
        "path": "tests/components/homekit/test_type_thermostats.py",
        "file_name": "test_type_thermostats.py",
        "fun_name": "test_thermostat_hvac_modes",
        "commit_message": "Cleanup HVACAction and HVACMode in tests (#78813)",
        "code": "async def test_thermostat_hvac_modes(hass, hk_driver):\n    \n    entity_id = \"climate.test\"\n\n    hass.states.async_set(\n        entity_id, HVACMode.OFF, {ATTR_HVAC_MODES: [HVACMode.HEAT, HVACMode.OFF]}\n    )\n\n    await hass.async_block_till_done()\n    acc = Thermostat(hass, hk_driver, \"Climate\", entity_id, 1, None)\n    hk_driver.add_accessory(acc)\n\n    await acc.run()\n    await hass.async_block_till_done()\n    hap = acc.char_target_heat_cool.to_HAP()\n    assert hap[\"valid-values\"] == [0, 1]\n    assert acc.char_target_heat_cool.value == 0\n\n    with pytest.raises(ValueError):\n        acc.char_target_heat_cool.set_value(3)\n    await hass.async_block_till_done()\n    assert acc.char_target_heat_cool.value == 0\n\n    acc.char_target_heat_cool.set_value(1)\n    await hass.async_block_till_done()\n    assert acc.char_target_heat_cool.value == 1\n\n    with pytest.raises(ValueError):\n        acc.char_target_heat_cool.set_value(2)\n    await hass.async_block_till_done()\n    assert acc.char_target_heat_cool.value == 1\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 150,
        "n_words": 66,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 187,
        "n_ast_nodes": 307,
        "n_identifiers": 23,
        "d_id": 106864,
        "documentation": {
            "docstring": "Test if unsupported HVAC modes are deactivated in HomeKit.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 170154,
        "commit_id": "d2e972301c099967ef3050c9feda1d116e1dd85a",
        "repo": "pandas",
        "path": "pandas/tests/io/parser/test_parse_dates.py",
        "file_name": "test_parse_dates.py",
        "fun_name": "test_datetime_fractional_seconds",
        "commit_message": "DEP: Enforce deprecation of date converters for csv (#49086)\n\n* DEP: Enforce deprecation of date converters for csv\r\n\r\n* Add whatsnew\r\n\r\n* Add check",
        "code": "def test_datetime_fractional_seconds(all_parsers):\n    parser = all_parsers\n    data = \n    result = parser.read_csv(\n        StringIO(data),\n        header=0,\n        date_parser=lambda x: pd.to_datetime(x, format=\"%Y %m %d %H %M %S.%f\"),\n        parse_dates={\"ymdHMS\": [0, 1, 2, 3, 4, 5]},\n    )\n    expected = DataFrame(\n        [\n            [datetime(2001, 1, 5, 10, 0, 0, microsecond=123456), 0.0, 10.0],\n            [datetime(2001, 1, 5, 10, 0, 0, microsecond=500000), 1.0, 11.0],\n        ],\n        columns=[\"ymdHMS\", \"a\", \"b\"],\n    )\n    tm.assert_frame_equal(result, expected)\n\n\n@xfail_pyarrow",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@xfail_pyarrow",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 150,
        "n_words": 59,
        "vocab_size": 47,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 147,
        "n_ast_nodes": 202,
        "n_identifiers": 22,
        "d_id": 40537,
        "documentation": {
            "docstring": "\\\nyear,month,day,hour,minute,second,a,b\n2001,01,05,10,00,0.123456,0.0,10.\n2001,01,5,10,0,0.500000,1.,11.\n",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 0,
            "language": "en"
        }
    },
    {
        "id": 60719,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/index/collector.py",
        "file_name": "collector.py",
        "fun_name": "_get_html_response",
        "commit_message": "upd; format",
        "code": "def _get_html_response(url, session):\n    # type: (str, PipSession) -> Response\n    \n    if is_archive_file(Link(url).filename):\n        _ensure_html_response(url, session=session)\n\n    logger.debug('Getting page %s', redact_auth_from_url(url))\n\n    resp = session.get(\n        url,\n        headers={\n            \"Accept\": \"text/html\",\n            # We don't want to blindly returned cached data for\n            # /simple/, because authors generally expecting that\n            # twine upload && pip install will function, but if\n            # they've done a pip install in the last ~10 minutes\n            # it won't. Thus by setting this to zero we will not\n            # blindly use any cached data, however the benefit of\n            # using max-age=0 instead of no-cache, is that we will\n            # still support conditional requests, so we will still\n            # minimize traffic sent in cases where the page hasn't\n            # changed at all, we will just always incur the round\n            # trip for the conditional GET now instead of only\n            # once per 10 minutes.\n            # For more information, please see pypa/pip#5670.\n            \"Cache-Control\": \"max-age=0\",\n        },\n    )\n    raise_for_status(resp)\n\n    # The check for archives above only works if the url ends with\n    # something that looks like an archive. However that is not a\n    # requirement of an url. Unless we issue a HEAD request on every\n    # url we cannot know ahead of time for sure if something is HTML\n    # or not. However we can check after we've downloaded it.\n    _ensure_html_header(resp)\n\n    return resp\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 452,
        "n_words": 217,
        "vocab_size": 149,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 70,
        "n_ast_nodes": 139,
        "n_identifiers": 15,
        "d_id": 12260,
        "documentation": {
            "docstring": "Access an HTML page with GET, and return the response.\n\n    This consists of three parts:\n\n    1. If the URL looks suspiciously like an archive, send a HEAD first to\n       check the Content-Type is HTML, to avoid downloading a large file.\n       Raise `_NotHTTP` if the content type cannot be determined, or\n       `_NotHTML` if it is not HTML.\n    2. Actually perform the request. Raise HTTP exceptions on network failures.\n    3. Check the Content-Type header to make sure we got HTML, and raise\n       `_NotHTML` otherwise.\n    ",
            "n_words": 82,
            "vocab_size": 66,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 120400,
        "commit_id": "bf4c3b64af43b86c3005c0f8bec450655ab47a8d",
        "repo": "jax",
        "path": "jax/experimental/sparse/bcoo.py",
        "file_name": "bcoo.py",
        "fun_name": "bcoo_update_layout",
        "commit_message": "[sparse] add bcoo_update_layout utility",
        "code": "def bcoo_update_layout(mat, *, n_batch=None, n_dense=None, on_inefficient='error'):\n  \n  # TODO(jakevdp): allow specification of nse?\n  # TODO(jakevdp): there is room for some improvements here:\n  # - we could probably do better in the case of converting a dense dim to\n  #   a batch dim or vice-versa. Worth adding that special case?\n  # - we could work to preserve broadcasted batch dimensions when possible.\n  # - if indices are known to be unique, we can convert them to batch/dense\n  #   dimensions more efficiently.\n  n_batch = mat.n_batch if n_batch is None else operator.index(n_batch)\n  n_dense = mat.n_dense if n_dense is None else operator.index(n_dense)\n\n  if (n_batch, n_dense) == (mat.n_batch, mat.n_dense):\n    return mat\n\n  n_sparse = mat.ndim - n_batch - n_dense\n  if on_inefficient not in ['error', 'warn', None]:\n    raise ValueError(\"on_inefficent={on_inefficient!r}; expected one of ['error', 'warn', None].\")\n\n  if n_batch < 0:\n    raise ValueError(f\"n_batch must be non-negative; got {n_batch}\")\n  if n_dense < 0:\n    raise ValueError(f\"n_dense must be non-negative; got {n_dense}\")\n  if n_sparse < 0:\n    raise ValueError(f\"sum of n_batch={n_batch} and n_dense={n_dense} \"\n                     f\"cannot be larger than mat.ndim={mat.ndim}.\")\n\n  def _maybe_err_or_warn(msg):\n    if on_inefficient == 'error':\n      msg += (\" To disable this error, set the on_inefficient argument \"\n              \"of bcoo_update_layout to 'warn' or None.\")\n      raise SparseEfficiencyError(msg)\n    elif on_inefficient == 'warn':\n      msg += (\" To disable this warning, set the on_inefficient argument \"\n              \"of bcoo_update_layout to None.\")\n      warnings.warn(msg, category=SparseEfficiencyWarning)\n\n  # TODO(jakevdp): are efficiency warnings necessary when nse is 0 or 1?\n  if (n_dense > mat.n_dense and\n      any(d > 1 for d in mat.shape[-n_dense:mat.ndim - mat.n_dense])):\n    _maybe_err_or_warn(f\"For matrix of shape {mat.shape}, increasing n_dense from \"\n                       f\"{mat.n_dense} to {n_dense} results in inefficient storage.\")\n  if n_batch > mat.n_batch and any(d > 1 for d in mat.shape[mat.n_batch:n_batch]):\n    _maybe_err_or_warn(f\"For matrix of shape {mat.shape}, increasing n_batch from \"\n                       f\"{mat.n_batch} to {n_batch} results in inefficient storage.\")\n\n  new_data, new_indices = mat.data, mat.indices\n  shape = mat.shape\n  current_n_batch = mat.n_batch\n  current_n_dense = mat.n_dense\n\n  if n_dense < current_n_dense:\n    n = current_n_dense - n_dense",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 480,
        "n_words": 306,
        "vocab_size": 162,
        "complexity": 22,
        "nloc": 62,
        "token_counts": 492,
        "n_ast_nodes": 531,
        "n_identifiers": 27,
        "d_id": 26831,
        "documentation": {
            "docstring": "Update the storage layout of a BCOO matrix.\n\n  In general, increasing ``mat.n_batch`` or ``mat.n_dense`` will lead to very inefficient\n  storage, with many explicitly-stored zeros, unless the new batch or dense dimensions have\n  size 0 or 1. In such cases, ``bcoo_update_layout`` will raise a :class:`SparseEfficiencyError`.\n  This can be silenced by specifying the ``on_inefficient`` argument.\n\n  Args:\n    mat : BCOO array\n    n_batch : optional(int) the number of batch dimensions in the output matrix. If None,\n      then n_batch = mat.n_batch.\n    n_dense : optional(int) the number of dense dimensions in the output matrix. If None,\n      then n_dense = mat.n_dense.\n    on_inefficient : optional(string), one of ``['error', 'warn', None]``. Specify the\n      behavior in case of an inefficient reconfiguration. This is defined as a reconfiguration\n      where the size of the resulting representation is much larger than the size of the\n      input representation.\n\n  Returns:\n    mat_out : BCOO array\n      A BCOO array representing the same sparse array as the input, with the specified\n      layout. ``mat_out.todense()`` will match ``mat.todense()`` up to appropriate precision.\n  ",
            "n_words": 162,
            "vocab_size": 100,
            "n_whitespaces": 219,
            "language": "en"
        }
    },
    {
        "id": 124998,
        "commit_id": "569fe0109629048d08e1d9e023f7769f10bd2244",
        "repo": "ray",
        "path": "rllib/offline/tests/test_dataset_reader.py",
        "file_name": "test_dataset_reader.py",
        "fun_name": "test_s3_zip",
        "commit_message": "[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)",
        "code": "def test_s3_zip(self):\n        \n        unzipped_paths = _unzip_if_needed([self.s3_path + \"/enormous.zip\"], \"json\")\n        self.assertEqual(\n            str(Path(unzipped_paths[0]).absolute()),\n            str(Path(\"./\").absolute() / \"enormous.json\"),\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 64,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 54,
        "n_ast_nodes": 96,
        "n_identifiers": 9,
        "d_id": 27738,
        "documentation": {
            "docstring": "Tests whether the unzip_if_needed function works correctly on s3 zip\n        files",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 311451,
        "commit_id": "58b8c30221a6f6e5acbbe98b7e3298b03fb741f5",
        "repo": "core",
        "path": "tests/components/homekit_controller/test_binary_sensor.py",
        "file_name": "test_binary_sensor.py",
        "fun_name": "test_occupancy_sensor_read_state",
        "commit_message": "Improve homekit_controller tests (#65266)",
        "code": "async def test_occupancy_sensor_read_state(hass, utcnow):\n    \n    helper = await setup_test_component(hass, create_occupancy_sensor_service)\n\n    await helper.async_update(\n        ServicesTypes.OCCUPANCY_SENSOR, {CharacteristicsTypes.OCCUPANCY_DETECTED: False}\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"off\"\n\n    await helper.async_update(\n        ServicesTypes.OCCUPANCY_SENSOR, {CharacteristicsTypes.OCCUPANCY_DETECTED: True}\n    )\n    state = await helper.poll_and_get_state()\n    assert state.state == \"on\"\n\n    assert state.attributes[\"device_class\"] == BinarySensorDeviceClass.OCCUPANCY\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 88,
        "n_words": 41,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 90,
        "n_ast_nodes": 150,
        "n_identifiers": 16,
        "d_id": 110116,
        "documentation": {
            "docstring": "Test that we can read the state of a HomeKit occupancy sensor accessory.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 4112,
        "commit_id": "706d7f16868f062d89e9d24e37ab059ae1a6d8b2",
        "repo": "airbyte",
        "path": "octavia-cli/octavia_cli/apply/resources.py",
        "file_name": "resources.py",
        "fun_name": "get_diff_with_remote_resource",
        "commit_message": "🐙 octavia-cli: implement `apply` (#10703)",
        "code": "def get_diff_with_remote_resource(self) -> str:\n        \n        if not self.was_created:\n            raise NonExistingResourceError(\"Cannot compute diff with a non existing remote resource.\")\n        current_config = self.configuration\n        remote_config = self.remote_resource.connection_configuration\n        diff = compute_diff(remote_config, current_config)\n        return diff.pretty()\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 82,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 45,
        "n_ast_nodes": 77,
        "n_identifiers": 13,
        "d_id": 623,
        "documentation": {
            "docstring": "Compute the diff between current resource and the remote resource.\n\n        Raises:\n            NonExistingResourceError: Raised if the remote resource does not exist.\n\n        Returns:\n            str: The prettyfied diff.\n        ",
            "n_words": 25,
            "vocab_size": 21,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 207585,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_i18n_language_non_english_default",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_i18n_language_non_english_default(self):\n        \n        with self.settings(LANGUAGE_CODE=\"fr\"), translation.override(\"en-us\"):\n            response = self.client.get(reverse(\"admin:jsi18n\"))\n            self.assertNotContains(response, \"Choisir une heure\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 48,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 44,
        "n_ast_nodes": 83,
        "n_identifiers": 11,
        "d_id": 52010,
        "documentation": {
            "docstring": "\n        Check if the JavaScript i18n view returns an empty language catalog\n        if the default language is non-English but the selected language\n        is English. See #13388 and #3594 for more details.\n        ",
            "n_words": 30,
            "vocab_size": 24,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 134391,
        "commit_id": "182744bbd151c166b8028355eae12a5da63fb3cc",
        "repo": "ray",
        "path": "rllib/algorithms/algorithm_config.py",
        "file_name": "algorithm_config.py",
        "fun_name": "callbacks",
        "commit_message": "[RLlib] AlgorithmConfig: Next steps (volume 01); Algos, RolloutWorker, PolicyMap, WorkerSet use AlgorithmConfig objects under the hood. (#29395)",
        "code": "def callbacks(self, callbacks_class) -> \"AlgorithmConfig\":\n        \n        if callbacks_class is None:\n            callbacks_class = DefaultCallbacks\n        # Check, whether given `callbacks` is a callable.\n        if not callable(callbacks_class):\n            raise ValueError(\n                \"`config.callbacks_class` must be a callable method that \"\n                \"returns a subclass of DefaultCallbacks, got \"\n                f\"{callbacks_class}!\"\n            )\n        self.callbacks_class = callbacks_class\n\n        return self\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 167,
        "n_words": 47,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 40,
        "n_ast_nodes": 78,
        "n_identifiers": 6,
        "d_id": 30282,
        "documentation": {
            "docstring": "Sets the callbacks configuration.\n\n        Args:\n            callbacks_class: Callbacks class, whose methods will be run during\n                various phases of training and environment sample collection.\n                See the `DefaultCallbacks` class and\n                `examples/custom_metrics_and_callbacks.py` for more usage information.\n\n        Returns:\n            This updated AlgorithmConfig object.\n        ",
            "n_words": 37,
            "vocab_size": 35,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 247085,
        "commit_id": "7754af24ab163a3666bc04c7df409e59ace0d763",
        "repo": "synapse",
        "path": "tests/handlers/test_room_summary.py",
        "file_name": "test_room_summary.py",
        "fun_name": "test_fed_filtering",
        "commit_message": "Remove the unstable `/spaces` endpoint. (#12073)\n\n...and various code supporting it.\r\n\r\nThe /spaces endpoint was from an old version of MSC2946 and included\r\nboth a Client-Server and Server-Server API. Note that the unstable\r\n/hierarchy endpoint (from the final version of MSC2946) is not yet\r\nremoved.",
        "code": "def test_fed_filtering(self):\n        \n        fed_hostname = self.hs.hostname + \"2\"\n        subspace = \"#subspace:\" + fed_hostname\n\n        # Create a few rooms which will have different properties.\n        public_room = \"#public:\" + fed_hostname\n        knock_room = \"#knock:\" + fed_hostname\n        not_invited_room = \"#not_invited:\" + fed_hostname\n        invited_room = \"#invited:\" + fed_hostname\n        restricted_room = \"#restricted:\" + fed_hostname\n        restricted_accessible_room = \"#restricted_accessible:\" + fed_hostname\n        world_readable_room = \"#world_readable:\" + fed_hostname\n        joined_room = self.helper.create_room_as(self.user, tok=self.token)\n\n        # Poke an invite over federation into the database.\n        self._poke_fed_invite(invited_room, \"@remote:\" + fed_hostname)\n\n        # Note that these entries are brief, but should contain enough info.\n        children_rooms = (\n            (\n                public_room,\n                {\n                    \"room_id\": public_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.PUBLIC,\n                },\n            ),\n            (\n                knock_room,\n                {\n                    \"room_id\": knock_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.KNOCK,\n                },\n            ),\n            (\n                not_invited_room,\n                {\n                    \"room_id\": not_invited_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.INVITE,\n                },\n            ),\n            (\n                invited_room,\n                {\n                    \"room_id\": invited_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.INVITE,\n                },\n            ),\n            (\n                restricted_room,\n                {\n                    \"room_id\": restricted_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.RESTRICTED,\n                    \"allowed_room_ids\": [],\n                },\n            ),\n            (\n                restricted_accessible_room,\n                {\n                    \"room_id\": restricted_accessible_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.RESTRICTED,\n                    \"allowed_room_ids\": [self.room],\n                },\n            ),\n            (\n                world_readable_room,\n                {\n                    \"room_id\": world_readable_room,\n                    \"world_readable\": True,\n                    \"join_rules\": JoinRules.INVITE,\n                },\n            ),\n            (\n                joined_room,\n                {\n                    \"room_id\": joined_room,\n                    \"world_readable\": False,\n                    \"join_rules\": JoinRules.INVITE,\n                },\n            ),\n        )\n\n        subspace_room_entry = _RoomEntry(\n            subspace,\n            {\n                \"room_id\": subspace,\n                \"world_readable\": True,\n            },\n            # Place each room in the sub-space.\n            [\n                {\n                    \"type\": EventTypes.SpaceChild,\n                    \"room_id\": subspace,\n                    \"state_key\": room_id,\n                    \"content\": {\"via\": [fed_hostname]},\n                }\n                for room_id, _ in children_rooms\n            ],\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1598,
        "n_words": 218,
        "vocab_size": 104,
        "complexity": 2,
        "nloc": 129,
        "token_counts": 484,
        "n_ast_nodes": 544,
        "n_identifiers": 33,
        "d_id": 71495,
        "documentation": {
            "docstring": "\n        Rooms returned over federation should be properly filtered to only include\n        rooms the user has access to.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 37511,
        "commit_id": "57e6464ac9a31156f1c93e59107323e6ec01309e",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_soundfile",
        "commit_message": "Update all require decorators to use skipUnless when possible (#16999)",
        "code": "def require_soundfile(test_case):\n    \n    return unittest.skipUnless(is_soundfile_availble(), \"test requires soundfile\")(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 6816,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires soundfile\n\n    These tests are skipped when soundfile isn't installed.\n\n    ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 93967,
        "commit_id": "e1b25d625b185588fc7c2834dff5ea5bb3a98ce0",
        "repo": "sentry",
        "path": "src/sentry/search/events/datasets/metrics.py",
        "file_name": "metrics.py",
        "fun_name": "_resolve_project_threshold_config",
        "commit_message": "fix(mep): Use project thresholds for apdex calculation (#37256)\n\n- Currently apdex is always based on the satisfaction tags in the\r\n  transaction.duration metrics. This updates the apdex function so we\r\n  read the threshold config, and use that to determine which metric we\r\n  should read the satisfaction tags from instead",
        "code": "def _resolve_project_threshold_config(self) -> SelectType:\n        \n        org_id = self.builder.params.get(\"organization_id\")\n        project_ids = self.builder.params.get(\"project_id\")\n\n        project_threshold_configs = (\n            ProjectTransactionThreshold.objects.filter(\n                organization_id=org_id,\n                project_id__in=project_ids,\n            )\n            .order_by(\"project_id\")\n            .values_list(\"project_id\", \"threshold\", \"metric\")\n        )\n\n        transaction_threshold_configs = (\n            ProjectTransactionThresholdOverride.objects.filter(\n                organization_id=org_id,\n                project_id__in=project_ids,\n            )\n            .order_by(\"project_id\")\n            .values_list(\"transaction\", \"project_id\", \"threshold\", \"metric\")\n        )\n\n        num_project_thresholds = project_threshold_configs.count()\n        sentry_sdk.set_tag(\"project_threshold.count\", num_project_thresholds)\n        sentry_sdk.set_tag(\n            \"project_threshold.count.grouped\",\n            format_grouped_length(num_project_thresholds, [10, 100, 250, 500]),\n        )\n\n        num_transaction_thresholds = transaction_threshold_configs.count()\n        sentry_sdk.set_tag(\"txn_threshold.count\", num_transaction_thresholds)\n        sentry_sdk.set_tag(\n            \"txn_threshold.count.grouped\",\n            format_grouped_length(num_transaction_thresholds, [10, 100, 250, 500]),\n        )\n\n        if (\n            num_project_thresholds + num_transaction_thresholds\n            > constants.MAX_QUERYABLE_TRANSACTION_THRESHOLDS\n        ):\n            raise InvalidSearchQuery(\n                f\"Exceeded {constants.MAX_QUERYABLE_TRANSACTION_THRESHOLDS} configured transaction thresholds limit, try with fewer Projects.\"\n            )\n\n        # Arrays need to have toUint64 casting because clickhouse will define the type as the narrowest possible type\n        # that can store listed argument types, which means the comparison will fail because of mismatched types\n        project_thresholds = {}\n        project_threshold_config_keys = []\n        project_threshold_config_values = []\n        for project_id, threshold, metric in project_threshold_configs:\n            metric = TRANSACTION_METRICS[metric]\n            if (\n                threshold == constants.DEFAULT_PROJECT_THRESHOLD\n                and metric == constants.DEFAULT_PROJECT_THRESHOLD_METRIC\n            ):\n                # small optimization, if the configuration is equal to the default,\n                # we can skip it in the final query\n                continue\n\n            project_thresholds[project_id] = (metric, threshold)\n            project_threshold_config_keys.append(Function(\"toUInt64\", [project_id]))\n            project_threshold_config_values.append((metric, threshold))\n\n        project_threshold_override_config_keys = []\n        project_threshold_override_config_values = []\n        for transaction, project_id, threshold, metric in transaction_threshold_configs:\n            metric = TRANSACTION_METRICS[metric]\n            if (\n                project_id in project_thresholds\n                and threshold == project_thresholds[project_id][1]\n                and metric == project_thresholds[project_id][0]\n            ):\n                # small optimization, if the configuration is equal to the project\n                # configs, we can skip it in the final query\n                continue\n\n            elif (\n                project_id not in project_thresholds\n                and threshold == constants.DEFAULT_PROJECT_THRESHOLD\n                and metric == constants.DEFAULT_PROJECT_THRESHOLD_METRIC\n            ):\n                # small optimization, if the configuration is equal to the default\n                # and no project configs were set, we can skip it in the final query\n                continue\n\n            transaction_id = self.resolve_tag_value(transaction)\n            # Don't add to the config if we can't resolve it\n            if transaction_id is None:\n                continue\n            project_threshold_override_config_keys.append(\n                (Function(\"toUInt64\", [project_id]), (Function(\"toUInt64\", [transaction_id])))\n            )\n            project_threshold_override_config_values.append((metric, threshold))\n\n        project_threshold_config_index: SelectType = Function(\n            \"indexOf\",\n            [\n                project_threshold_config_keys,\n                self.builder.column(\"project_id\"),\n            ],\n            constants.PROJECT_THRESHOLD_CONFIG_INDEX_ALIAS,\n        )\n\n        project_threshold_override_config_index: SelectType = Function(\n            \"indexOf\",\n            [\n                project_threshold_override_config_keys,\n                (self.builder.column(\"project_id\"), self.builder.column(\"transaction\")),\n            ],\n            constants.PROJECT_THRESHOLD_OVERRIDE_CONFIG_INDEX_ALIAS,\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1399,
        "n_words": 318,
        "vocab_size": 165,
        "complexity": 15,
        "nloc": 117,
        "token_counts": 513,
        "n_ast_nodes": 741,
        "n_identifiers": 48,
        "d_id": 19036,
        "documentation": {
            "docstring": "This is mostly duplicated code from the discover dataset version\n        TODO: try to make this more DRY with the discover version\n        ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 26497,
        "commit_id": "aca6418d6c36956bc1ab530e6ef7e146ec9df90c",
        "repo": "saleor",
        "path": "saleor/plugins/webhook/tests/subscription_webhooks/test_create_deliveries_for_subscription.py",
        "file_name": "test_create_deliveries_for_subscription.py",
        "fun_name": "test_validate_invalid_subscription_and_query",
        "commit_message": "Add Webhook payload via graphql subscriptions (#9394)\n\n* Add PoC of webhook subscriptions\r\n\r\n* add async webhooks subscription payloads feature\r\n\r\n* remove unneeded file\r\n\r\n* add translations subscription handling, fixes after review\r\n\r\n* remove todo\r\n\r\n* add descriptions\r\n\r\n* add descriptions, move subsrciption_payloads.py\r\n\r\n* refactor\r\n\r\n* fix imports, add changelog\r\n\r\n* check_document_is_single_subscription refactor\r\n\r\nCo-authored-by: Maciej Korycinski <maciej@mirumee.com>\r\nCo-authored-by: Marcin Gębala <5421321+maarcingebala@users.noreply.github.com>",
        "code": "def test_validate_invalid_subscription_and_query():\n\n    result = validate_subscription_query(TEST_INVALID_MULTIPLE_SUBSCRIPTION_AND_QUERY)\n    assert result is False\n\n\nTEST_INVALID_MULTIPLE_SUBSCRIPTION = \n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 16,
        "n_words": 11,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 14,
        "n_ast_nodes": 31,
        "n_identifiers": 5,
        "d_id": 5024,
        "documentation": {
            "docstring": "\nsubscription{\n  event{\n    ...on ProductUpdated{\n      product{\n        id\n      }\n    }\n  }\n}\nsubscription{\n  event{\n    ...on ProductCreated{\n      product{\n        id\n      }\n    }\n  }\n}\n",
            "n_words": 20,
            "vocab_size": 8,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 42524,
        "commit_id": "8b43b49b0cd8c12cae1d48df27edfdd98cf859fd",
        "repo": "nltk",
        "path": "nltk/corpus/reader/verbnet.py",
        "file_name": "verbnet.py",
        "fun_name": "_get_semantics_within_frame",
        "commit_message": "Read 'bool' field from VerbNet",
        "code": "def _get_semantics_within_frame(self, vnframe):\n        \n        semantics_within_single_frame = []\n        for pred in vnframe.findall(\"SEMANTICS/PRED\"):\n            arguments = [\n                {\"type\": arg.get(\"type\"), \"value\": arg.get(\"value\")}\n                for arg in pred.findall(\"ARGS/ARG\")\n            ]\n            semantics_within_single_frame.append(\n                {\n                    \"predicate_value\": pred.get(\"value\"),\n                    \"arguments\": arguments,\n                    \"negated\": pred.get(\"bool\") == \"!\",\n                }\n            )\n        return semantics_within_single_frame\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 225,
        "n_words": 36,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 87,
        "n_ast_nodes": 158,
        "n_identifiers": 10,
        "d_id": 7591,
        "documentation": {
            "docstring": "Returns semantics within a single frame\n\n        A utility function to retrieve semantics within a frame in VerbNet\n        Members of the semantics dictionary:\n        1) Predicate value\n        2) Arguments\n\n        :param vnframe: An ElementTree containing the xml contents of\n            a VerbNet frame.\n        :return: semantics: semantics dictionary\n        ",
            "n_words": 43,
            "vocab_size": 33,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 153059,
        "commit_id": "58bbcc37477866d19c8b092a0e1974a4f0baa586",
        "repo": "modin",
        "path": "modin/core/storage_formats/base/doc_utils.py",
        "file_name": "doc_utils.py",
        "fun_name": "doc_resample_reduce",
        "commit_message": "REFACTOR-#2656: Update modin to fit algebra (code only) (#3717)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>\r\nCo-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>\r\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: Rehan Durrani <rehan@ponder.io>",
        "code": "def doc_resample_reduce(result, refer_to, params=None, compatibility_params=True):\n    \n    action = f\"compute {result} for each group\"\n\n    params_substitution = (\n        (\n            \n        )\n        if compatibility_params\n        else \"\"\n    )\n\n    if params:\n        params_substitution = format_string(\n            \"{params}\\n{params_substitution}\",\n            params=params,\n            params_substitution=params_substitution,\n        )\n\n    build_rules = f\n    return doc_resample(\n        action=action,\n        extra_params=params_substitution,\n        build_rules=build_rules,\n        refer_to=refer_to,\n    )\n\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 180,
        "n_words": 41,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 31,
        "token_counts": 73,
        "n_ast_nodes": 123,
        "n_identifiers": 11,
        "d_id": 35243,
        "documentation": {
            "docstring": "\n    Build decorator which adds docstring for the resample reduce method.\n\n    Parameters\n    ----------\n    result : str\n        The result of the method.\n    refer_to : str\n        Method name in ``modin.pandas.base.Resampler`` module to refer to for\n        more information about parameters and output format.\n    params : str, optional\n        Method parameters in the NumPy docstyle format to substitute\n        to the docstring template.\n    compatibility_params : bool, default: True\n        Whether method takes `*args` and `**kwargs` that do not affect\n        the result.\n\n    Returns\n    -------\n    callable\n    \n        *args : iterable\n            Serves the compatibility purpose. Does not affect the result.\n        **kwargs : dict\n            Serves the compatibility purpose. Does not affect the result.\n        \n            - Labels on the specified axis are the group names (time-stamps)\n            - Labels on the opposit of specified axis are preserved.\n            - Each element of QueryCompiler is the {result} for the\n              corresponding group and column/row.",
            "n_words": 135,
            "vocab_size": 83,
            "n_whitespaces": 308,
            "language": "en"
        }
    },
    {
        "id": 205831,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/sql/compiler.py",
        "file_name": "compiler.py",
        "fun_name": "quote_name_unless_alias",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def quote_name_unless_alias(self, name):\n        \n        if name in self.quote_cache:\n            return self.quote_cache[name]\n        if (\n            (name in self.query.alias_map and name not in self.query.table_map)\n            or name in self.query.extra_select\n            or (\n                self.query.external_aliases.get(name)\n                and name not in self.query.table_map\n            )\n        ):\n            self.quote_cache[name] = name\n            return name\n        r = self.connection.ops.quote_name(name)\n        self.quote_cache[name] = r\n        return r\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 202,
        "n_words": 46,
        "vocab_size": 24,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 106,
        "n_ast_nodes": 163,
        "n_identifiers": 14,
        "d_id": 51230,
        "documentation": {
            "docstring": "\n        A wrapper around connection.ops.quote_name that doesn't quote aliases\n        for table names. This avoids problems with some SQL dialects that treat\n        quoted strings specially (e.g. PostgreSQL).\n        ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 203453,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/options.py",
        "file_name": "options.py",
        "fun_name": "formfield_for_manytomany",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def formfield_for_manytomany(self, db_field, request, **kwargs):\n        \n        # If it uses an intermediary model that isn't auto created, don't show\n        # a field in admin.\n        if not db_field.remote_field.through._meta.auto_created:\n            return None\n        db = kwargs.get(\"using\")\n\n        if \"widget\" not in kwargs:\n            autocomplete_fields = self.get_autocomplete_fields(request)\n            if db_field.name in autocomplete_fields:\n                kwargs[\"widget\"] = AutocompleteSelectMultiple(\n                    db_field,\n                    self.admin_site,\n                    using=db,\n                )\n            elif db_field.name in self.raw_id_fields:\n                kwargs[\"widget\"] = widgets.ManyToManyRawIdWidget(\n                    db_field.remote_field,\n                    self.admin_site,\n                    using=db,\n                )\n            elif db_field.name in [*self.filter_vertical, *self.filter_horizontal]:\n                kwargs[\"widget\"] = widgets.FilteredSelectMultiple(\n                    db_field.verbose_name, db_field.name in self.filter_vertical\n                )\n        if \"queryset\" not in kwargs:\n            queryset = self.get_field_queryset(db, db_field, request)\n            if queryset is not None:\n                kwargs[\"queryset\"] = queryset\n\n        form_field = db_field.formfield(**kwargs)\n        if isinstance(form_field.widget, SelectMultiple) and not isinstance(\n            form_field.widget, (CheckboxSelectMultiple, AutocompleteSelectMultiple)\n        ):\n            msg = _(\n                \"Hold down “Control”, or “Command” on a Mac, to select more than one.\"\n            )\n            help_text = form_field.help_text\n            form_field.help_text = (\n                format_lazy(\"{} {}\", help_text, msg) if help_text else msg\n            )\n        return form_field\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 627,
        "n_words": 139,
        "vocab_size": 89,
        "complexity": 11,
        "nloc": 38,
        "token_counts": 237,
        "n_ast_nodes": 376,
        "n_identifiers": 36,
        "d_id": 50383,
        "documentation": {
            "docstring": "\n        Get a form Field for a ManyToManyField.\n        ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 32431,
        "commit_id": "8e8384663d716d4b5a4f510070ff954fc0ba4a52",
        "repo": "transformers",
        "path": "src/transformers/models/swin/modeling_tf_swin.py",
        "file_name": "modeling_tf_swin.py",
        "fun_name": "serving",
        "commit_message": "Update serving code to enable `saved_model=True` (#18153)\n\n* Add serving_output and serving methods to some vision models\r\n\r\n* Add serving outputs for DeiT\r\n\r\n* Don't convert hidden states - differing shapes\r\n\r\n* Make saveable\r\n\r\n* Fix up\r\n\r\n* Make swin saveable\r\n\r\n* Add in tests\r\n\r\n* Fix funnel tests (can't convert to tensor)\r\n\r\n* Fix numpy call\r\n\r\n* Tidy up a bit\r\n\r\n* Add in hidden states - resnet\r\n\r\n* Remove numpy\r\n\r\n* Fix failing tests - tensor shape and skipping tests\r\n\r\n* Remove duplicated function\r\n\r\n* PR comments - formatting and var names\r\n\r\n* PR comments\r\nAdd suggestions made by Joao Gante:\r\n* Use tf.shape instead of shape_list\r\n* Use @tooslow decorator on tests\r\n* Simplify some of the logic\r\n\r\n* PR comments\r\nAddress Yih-Dar Sheih comments - making tensor names consistent and make types float\r\n\r\n* Types consistent with docs; disable test on swin (slow)\r\n\r\n* CI trigger\r\n\r\n* Change input_features to float32\r\n\r\n* Add serving_output for segformer\r\n\r\n* Fixup\r\n\r\nCo-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>",
        "code": "def serving(self, inputs):\n        output = self.call(inputs)\n        return self.serving_output(output)\n\n\nSWIN_START_DOCSTRING = r\n\nSWIN_INPUTS_DOCSTRING = r\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 14,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 49,
        "n_identifiers": 8,
        "d_id": 5928,
        "documentation": {
            "docstring": "\n    This model is a Tensorflow\n    [tf.keras.layers.Layer](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Layer) sub-class. Use it as a\n    regular Tensorflow Module and refer to the Tensorflow documentation for all matter related to general usage and\n    behavior.\n\n    Parameters:\n        config ([`SwinConfig`]): Model configuration class with all the parameters of the model.\n            Initializing with a config file does not load the weights associated with the model, only the\n            configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.\n\n    Args:\n        pixel_values (`tf.Tensor` of shape `(batch_size, num_channels, height, width)`):\n            Pixel values. Pixel values can be obtained using [`AutoFeatureExtractor`]. See\n            [`AutoFeatureExtractor.__call__`] for details.\n        head_mask (`tf.Tensor` of shape `(num_heads,)` or `(num_layers, num_heads)`, *optional*):\n            Mask to nullify selected heads of the self-attention modules. Mask values selected in `[0, 1]`:\n\n            - 1 indicates the head is **not masked**,\n            - 0 indicates the head is **masked**.\n\n        output_attentions (`bool`, *optional*):\n            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned\n            tensors for more detail.\n        output_hidden_states (`bool`, *optional*):\n            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for\n            more detail.\n        return_dict (`bool`, *optional*):\n            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n",
            "n_words": 190,
            "vocab_size": 113,
            "n_whitespaces": 382,
            "language": "en"
        }
    },
    {
        "id": 44543,
        "commit_id": "8fe9783fcd813dced8de849c8130d0eb7f90bac3",
        "repo": "airflow",
        "path": "airflow/decorators/task_group.py",
        "file_name": "task_group.py",
        "fun_name": "task_group",
        "commit_message": "Typing support for operator mapping functions (#21415)",
        "code": "def task_group(python_callable=None, **tg_kwargs):\n    \n    if callable(python_callable):\n        return TaskGroupDecorator(function=python_callable, kwargs=tg_kwargs)\n    return cast(Callable[[F], F], functools.partial(TaskGroupDecorator, kwargs=tg_kwargs))\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 29,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 51,
        "n_ast_nodes": 78,
        "n_identifiers": 12,
        "d_id": 8287,
        "documentation": {
            "docstring": "\n    Python TaskGroup decorator.\n\n    This wraps a function into an Airflow TaskGroup. When used as the\n    ``@task_group()`` form, all arguments are forwarded to the underlying\n    TaskGroup class. Can be used to parametrize TaskGroup.\n\n    :param python_callable: Function to decorate.\n    :param tg_kwargs: Keyword arguments for the TaskGroup object.\n    ",
            "n_words": 45,
            "vocab_size": 35,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 208746,
        "commit_id": "ebea766ceb57ec0080300b246be0699f41957e26",
        "repo": "ipython",
        "path": "IPython/core/history.py",
        "file_name": "history.py",
        "fun_name": "get_tail",
        "commit_message": "Fix HistoryAccessor.get_tail bug (#13666)\n\nCurrent implementation of get_tail in HistoryAccessor assumes context\npresent only in subclass , so it's moved there and the old\nimplementation is restored.",
        "code": "def get_tail(self, n=10, raw=True, output=False, include_latest=False):\n        \n        self.writeout_cache()\n        if not include_latest:\n            n += 1\n        cur = self._run_sql(\"ORDER BY session DESC, line DESC LIMIT ?\",\n                                (n,), raw=raw, output=output)\n        if not include_latest:\n            return reversed(list(cur)[1:])\n        return reversed(list(cur))\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 128,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 79,
        "n_ast_nodes": 124,
        "n_identifiers": 11,
        "d_id": 52500,
        "documentation": {
            "docstring": "Get the last n lines from the history database.\n\n        Parameters\n        ----------\n        n : int\n            The number of lines to get\n        raw, output : bool\n            See :meth:`get_range`\n        include_latest : bool\n            If False (default), n+1 lines are fetched, and the latest one\n            is discarded. This is intended to be used where the function\n            is called by a user command, which it should not return.\n\n        Returns\n        -------\n        Tuples as :meth:`get_range`\n        ",
            "n_words": 67,
            "vocab_size": 54,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 265551,
        "commit_id": "7ba0b420f181cffac86a9de384a1ec9d8a9a07dd",
        "repo": "netbox",
        "path": "netbox/ipam/models/ip.py",
        "file_name": "ip.py",
        "fun_name": "get_available_prefixes",
        "commit_message": "Fixes #10109: Fix available prefixes calculation for container prefixes in the global table",
        "code": "def get_available_prefixes(self):\n        \n        params = {\n            'prefix__net_contained': str(self.prefix)\n        }\n        if hasattr(self, 'vrf'):\n            params['vrf'] = self.vrf\n\n        child_prefixes = Prefix.objects.filter(**params).values_list('prefix', flat=True)\n        return netaddr.IPSet(self.prefix) - netaddr.IPSet(child_prefixes)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 86,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 70,
        "n_ast_nodes": 120,
        "n_identifiers": 15,
        "d_id": 78137,
        "documentation": {
            "docstring": "\n        Return all available prefixes within this Aggregate or Prefix as an IPSet.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 152977,
        "commit_id": "0faf4675140415e17d4112f9d0d37cfe87770b9e",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/pandas_on_ray/io/io.py",
        "file_name": "io.py",
        "fun_name": "to_sql",
        "commit_message": "REFACTOR-#3871: move related to pandas functionality into 'PandasOnRayIO' class (#3872)\n\nSigned-off-by: Anatoly Myachev <anatoly.myachev@intel.com>",
        "code": "def to_sql(cls, qc, **kwargs):\n        \n        # we first insert an empty DF in order to create the full table in the database\n        # This also helps to validate the input against pandas\n        # we would like to_sql() to complete only when all rows have been inserted into the database\n        # since the mapping operation is non-blocking, each partition will return an empty DF\n        # so at the end, the blocking operation will be this empty DF to_pandas\n\n        empty_df = qc.getitem_row_array([0]).to_pandas().head(0)\n        empty_df.to_sql(**kwargs)\n        # so each partition will append its respective DF\n        kwargs[\"if_exists\"] = \"append\"\n        columns = qc.columns\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 172,
        "n_words": 95,
        "vocab_size": 65,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 77,
        "n_ast_nodes": 89,
        "n_identifiers": 9,
        "d_id": 35219,
        "documentation": {
            "docstring": "\n        Write records stored in the `qc` to a SQL database.\n\n        Parameters\n        ----------\n        qc : BaseQueryCompiler\n            The query compiler of the Modin dataframe that we want to run ``to_sql`` on.\n        **kwargs : dict\n            Parameters for ``pandas.to_sql(**kwargs)``.\n        ",
            "n_words": 35,
            "vocab_size": 31,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 320701,
        "commit_id": "ab7a2ee55811c1d25dc482f4d5126eb4d7bbe714",
        "repo": "qutebrowser",
        "path": "scripts/link_pyqt.py",
        "file_name": "link_pyqt.py",
        "fun_name": "run_py",
        "commit_message": "Switch to Python 3.7 subprocess API\n\nFollow-up for #6905",
        "code": "def run_py(executable, *code):\n    \n    if os.name == 'nt' and len(code) > 1:\n        # Windows can't do newlines in arguments...\n        oshandle, filename = tempfile.mkstemp()\n        with os.fdopen(oshandle, 'w') as f:\n            f.write('\\n'.join(code))\n        cmd = [executable, filename]\n        try:\n            ret = subprocess.run(cmd, text=True, check=True,\n                                 stdout=subprocess.PIPE).stdout\n        finally:\n            os.remove(filename)\n    else:\n        cmd = [executable, '-c', '\\n'.join(code)]\n        ret = subprocess.run(cmd, text=True, check=True,\n                             stdout=subprocess.PIPE).stdout\n    return ret.rstrip()\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 216,
        "n_words": 55,
        "vocab_size": 44,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 142,
        "n_ast_nodes": 236,
        "n_identifiers": 24,
        "d_id": 117293,
        "documentation": {
            "docstring": "Run the given python code with the given executable.",
            "n_words": 9,
            "vocab_size": 7,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 159675,
        "commit_id": "4cdceaab5271a5b51463ec562c8eb55f96b771c5",
        "repo": "rasa",
        "path": "rasa/shared/nlu/training_data/features.py",
        "file_name": "features.py",
        "fun_name": "fingerprint",
        "commit_message": "Bump numpy from 1.19.5 to 1.21.6 (#11078)\n\n* Bump numpy from 1.19.5 to 1.21.6\r\n\r\nBumps [numpy](https://github.com/numpy/numpy) from 1.19.5 to 1.21.6.\r\n- [Release notes](https://github.com/numpy/numpy/releases)\r\n- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst.txt)\r\n- [Commits](https://github.com/numpy/numpy/compare/v1.19.5...v1.21.6)\r\n\r\n---\r\nupdated-dependencies:\r\n- dependency-name: numpy\r\n  dependency-type: direct:production\r\n  update-type: version-update:semver-minor\r\n...\r\n\r\nSigned-off-by: dependabot[bot] <support@github.com>\r\n\r\n* fixed mypy errors for numpy 1.21.6 upgrade\r\n\r\n* removed duplicate np.array call\r\n\r\nSigned-off-by: dependabot[bot] <support@github.com>\r\nCo-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>\r\nCo-authored-by: Thomas Werkmeister <thomas@werkmeister.me>\r\nCo-authored-by: melindaloubser1 <melinda.loubser@gmail.com>",
        "code": "def fingerprint(self) -> Text:\n        \n        if self.is_dense():\n            f_as_text = self.features.tobytes()\n        else:\n            f_as_text = rasa.shared.nlu.training_data.util.sparse_matrix_to_string(\n                self.features\n            )\n\n        return rasa.shared.utils.io.deep_container_fingerprint(\n            [self.type, self.origin, self.attribute, f_as_text]\n        )\n",
        "url": "https://github.com/RasaHQ/rasa.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 116,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 71,
        "n_ast_nodes": 113,
        "n_identifiers": 19,
        "d_id": 38391,
        "documentation": {
            "docstring": "Calculate a stable string fingerprint for the features.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 181724,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_stop_by_max_time_mins",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_stop_by_max_time_mins():\n    \n    tpot_obj = TPOTClassifier(config_dict='TPOT light')\n    tpot_obj._start_datetime = datetime.now()\n    sleep(0.11)\n    tpot_obj.max_time_mins = 0.1/60.\n    assert_raises(KeyboardInterrupt, tpot_obj._stop_by_max_time_mins)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 46,
        "n_ast_nodes": 72,
        "n_identifiers": 12,
        "d_id": 43511,
        "documentation": {
            "docstring": "Assert that _stop_by_max_time_mins raises KeyboardInterrupt when maximum minutes have elapsed.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 61284,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/packaging.py",
        "file_name": "packaging.py",
        "fun_name": "get_requires_python",
        "commit_message": "upd; format",
        "code": "def get_requires_python(dist):\n    # type: (pkg_resources.Distribution) -> Optional[str]\n    \n    pkg_info_dict = get_metadata(dist)\n    requires_python = pkg_info_dict.get(\"Requires-Python\")\n\n    if requires_python is not None:\n        # Convert to a str to satisfy the type checker, since requires_python\n        # can be a Header object.\n        requires_python = str(requires_python)\n\n    return requires_python\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 80,
        "n_words": 41,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 34,
        "n_ast_nodes": 63,
        "n_identifiers": 7,
        "d_id": 12487,
        "documentation": {
            "docstring": "\n    Return the \"Requires-Python\" metadata for a distribution, or None\n    if not present.\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 215105,
        "commit_id": "b2f8271fed3f05160431c55ad7c4e8f3e3e95c3e",
        "repo": "salt",
        "path": "tests/pytests/unit/modules/test_aixpkg.py",
        "file_name": "test_aixpkg.py",
        "fun_name": "test_remove_failure",
        "commit_message": "Complete intial tests for AIX yum and dnf support",
        "code": "def test_remove_failure():\n    \n\n    fileset_pkg_name = \"info_fake\"\n    fileset_lslpp_error = \n    lslpp_call = MagicMock(return_value=fileset_lslpp_error)\n    list_pkgs_mock = MagicMock(\n        side_effect=[\n            {\"bos.net.tcp.tcpdump\": \"7.2.4.1\"},\n            {\"bos.net.tcp.tcpdump\": \"7.2.4.1\"},\n        ]\n    )\n    with patch.dict(\n        aixpkg.__salt__,\n        {\n            \"cmd.run_all\": lslpp_call,\n            \"config.get\": MagicMock(return_value=False),\n        },\n    ), patch.object(aixpkg, \"list_pkgs\", list_pkgs_mock):\n        expected = {\n            \"changes\": {},\n            \"errors\": [f\"Fileset {fileset_pkg_name} not installed.\"],\n        }\n        with pytest.raises(CommandExecutionError) as exc_info:\n            result = aixpkg.remove(fileset_pkg_name)\n        assert exc_info.value.info == expected, exc_info.value.info\n        assert lslpp_call.call_count == 1\n        lslpp_call.assert_any_call(\n            [\"/usr/bin/lslpp\", \"-Lc\", f\"{fileset_pkg_name}\"],\n            python_shell=False,\n        )\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 274,
        "n_words": 66,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 150,
        "n_ast_nodes": 266,
        "n_identifiers": 25,
        "d_id": 53822,
        "documentation": {
            "docstring": "\n    Test remove package / fileset and experience failure\n    #Package Name:Fileset:Level:State:PTF Id:Fix State:Type:Description:Destination Dir.:Uninstaller:Message Catalog:Message Set:Message Number:Parent:Automatic:EFIX Locked:Install Path:Build Date\nlslpp: Fileset info_fake not installed.\n",
            "n_words": 24,
            "vocab_size": 24,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 181771,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_evaluated_individuals_",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_evaluated_individuals_():\n    \n    tpot_obj = TPOTClassifier(\n        random_state=42,\n        population_size=2,\n        offspring_size=4,\n        generations=1,\n        verbosity=0,\n        config_dict='TPOT light'\n    )\n    tpot_obj.fit(training_features, training_target)\n    assert isinstance(tpot_obj.evaluated_individuals_, dict)\n    for pipeline_string in sorted(tpot_obj.evaluated_individuals_.keys()):\n        deap_pipeline = creator.Individual.from_string(pipeline_string, tpot_obj._pset)\n        sklearn_pipeline = tpot_obj._toolbox.compile(expr=deap_pipeline)\n        operator_count = tpot_obj._operator_count(deap_pipeline)\n\n        try:\n            cv_scores = model_selection.cross_val_score(sklearn_pipeline, training_features, training_target, cv=5, scoring='accuracy', verbose=0)\n            mean_cv_scores = np.mean(cv_scores)\n        except Exception:\n            mean_cv_scores = -float('inf')\n        assert np.allclose(tpot_obj.evaluated_individuals_[pipeline_string]['internal_cv_score'], mean_cv_scores)\n        assert np.allclose(tpot_obj.evaluated_individuals_[pipeline_string]['operator_count'], operator_count)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 197,
        "n_words": 55,
        "vocab_size": 46,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 176,
        "n_ast_nodes": 274,
        "n_identifiers": 41,
        "d_id": 43557,
        "documentation": {
            "docstring": "Assert that evaluated_individuals_ stores current pipelines and their CV scores.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 73139,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/helpers/permission.py",
        "file_name": "permission.py",
        "fun_name": "user_can_delete_obj",
        "commit_message": "Reformat with black",
        "code": "def user_can_delete_obj(self, user, obj):\n        \n        perm_codename = self.get_perm_codename(\"delete\")\n        return self.user_has_specific_permission(user, perm_codename)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 15953,
        "documentation": {
            "docstring": "\n        Return a boolean to indicate whether `user` is permitted to 'delete'\n        a specific `self.model` instance.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 176781,
        "commit_id": "5c0b11afb4c0882a070d522ef3fa41482ba935d3",
        "repo": "networkx",
        "path": "networkx/drawing/tests/test_pylab.py",
        "file_name": "test_pylab.py",
        "fun_name": "test_draw_edges_toggling_with_arrows_kwarg",
        "commit_message": "Use isort with pre-commit to enforce import guidelines (#5659)\n\n* Add isort to pre-commit\r\n\r\n* Run isort on all python files (except __init__.py ones)",
        "code": "def test_draw_edges_toggling_with_arrows_kwarg():\n    \n    import matplotlib.collections\n    import matplotlib.patches\n\n    UG = nx.path_graph(3)\n    DG = nx.path_graph(3, create_using=nx.DiGraph)\n    pos = {n: (n, n) for n in UG}\n\n    # Use FancyArrowPatches when arrows=True, regardless of graph type\n    for G in (UG, DG):\n        edges = nx.draw_networkx_edges(G, pos, arrows=True)\n        assert len(edges) == len(G.edges)\n        assert isinstance(edges[0], mpl.patches.FancyArrowPatch)\n\n    # Use LineCollection when arrows=False, regardless of graph type\n    for G in (UG, DG):\n        edges = nx.draw_networkx_edges(G, pos, arrows=False)\n        assert isinstance(edges, mpl.collections.LineCollection)\n\n    # Default behavior when arrows=None: FAPs for directed, LC's for undirected\n    edges = nx.draw_networkx_edges(UG, pos)\n    assert isinstance(edges, mpl.collections.LineCollection)\n    edges = nx.draw_networkx_edges(DG, pos)\n    assert len(edges) == len(G.edges)\n    assert isinstance(edges[0], mpl.patches.FancyArrowPatch)\n\n\n@pytest.mark.parametrize(\"drawing_func\", (nx.draw, nx.draw_networkx))",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"drawing_func\", (nx.draw, nx.draw_networkx))",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 184,
        "n_words": 102,
        "vocab_size": 59,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 190,
        "n_ast_nodes": 316,
        "n_identifiers": 26,
        "d_id": 42097,
        "documentation": {
            "docstring": "\n    The `arrows` keyword argument is used as a 3-way switch to select which\n    type of object to use for drawing edges:\n      - ``arrows=None`` -> default (FancyArrowPatches for directed, else LineCollection)\n      - ``arrows=True`` -> FancyArrowPatches\n      - ``arrows=False`` -> LineCollection\n    ",
            "n_words": 38,
            "vocab_size": 32,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 95400,
        "commit_id": "8f22ac2a9290cb173f1dcdcf7b680c7992c6d4ad",
        "repo": "sentry",
        "path": "tests/sentry/api/endpoints/test_organization_metrics.py",
        "file_name": "test_organization_metrics.py",
        "fun_name": "test_unknown_filter",
        "commit_message": "fix: remove print statement (#31046)",
        "code": "def test_unknown_filter(self):\n        \n        # Insert session metrics:\n        self.store_session(self.build_session(project_id=self.project.id))\n\n        response = self.get_response(\n            self.organization.slug,\n            field=\"sum(sentry.sessions.session)\",\n            statsPeriod=\"1h\",\n            interval=\"1h\",\n            datasource=\"snuba\",\n            query=\"foo:123\",  # Unknown tag key\n        )\n        assert response.status_code == 400\n\n        response = self.get_success_response(\n            self.organization.slug,\n            field=\"sum(sentry.sessions.session)\",\n            statsPeriod=\"1h\",\n            interval=\"1h\",\n            datasource=\"snuba\",\n            query=\"release:123\",  # Unknown tag value is fine.\n        )\n\n        groups = response.data[\"groups\"]\n        assert len(groups) == 0\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 252,
        "n_words": 48,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 116,
        "n_ast_nodes": 187,
        "n_identifiers": 21,
        "d_id": 19204,
        "documentation": {
            "docstring": "Use a tag key/value in filter that does not exist in the indexer",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 33727,
        "commit_id": "fc21c9be62483d06adae6239ebe6ca77c2cb6269",
        "repo": "transformers",
        "path": "src/transformers/commands/add_new_model_like.py",
        "file_name": "add_new_model_like.py",
        "fun_name": "get_user_input",
        "commit_message": "[CookieCutter] Clarify questions (#18959)\n\n* Clarify cookiecutter questions\r\n\r\n* Update first question\r\n\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def get_user_input():\n    \n    model_types = list(auto_module.configuration_auto.MODEL_NAMES_MAPPING.keys())\n\n    # Get old model type\n    valid_model_type = False\n    while not valid_model_type:\n        old_model_type = input(\n            \"What is the model you would like to duplicate? Please provide the lowercase `model_type` (e.g. roberta): \"\n        )\n        if old_model_type in model_types:\n            valid_model_type = True\n        else:\n            print(f\"{old_model_type} is not a valid model type.\")\n            near_choices = difflib.get_close_matches(old_model_type, model_types)\n            if len(near_choices) >= 1:\n                if len(near_choices) > 1:\n                    near_choices = \" or \".join(near_choices)\n                print(f\"Did you mean {near_choices}?\")\n\n    old_model_info = retrieve_info_for_model(old_model_type)\n    old_tokenizer_class = old_model_info[\"model_patterns\"].tokenizer_class\n    old_feature_extractor_class = old_model_info[\"model_patterns\"].feature_extractor_class\n    old_processor_class = old_model_info[\"model_patterns\"].processor_class\n    old_frameworks = old_model_info[\"frameworks\"]\n\n    old_checkpoint = None\n    if len(old_model_info[\"model_patterns\"].checkpoint) == 0:\n        old_checkpoint = get_user_field(\n            \"We couldn't find the name of the base checkpoint for that model, please enter it here.\"\n        )\n\n    model_name = get_user_field(\n        \"What is the name (with no special casing) for your new model in the paper (e.g. RoBERTa)? \"\n    )\n    default_patterns = ModelPatterns(model_name, model_name)\n\n    model_type = get_user_field(\n        \"What identifier would you like to use for the `model_type` of this model? \",\n        default_value=default_patterns.model_type,\n    )\n    model_lower_cased = get_user_field(\n        \"What lowercase name would you like to use for the module (folder) of this model? \",\n        default_value=default_patterns.model_lower_cased,\n    )\n    model_camel_cased = get_user_field(\n        \"What prefix (camel-cased) would you like to use for the model classes of this model (e.g. Roberta)? \",\n        default_value=default_patterns.model_camel_cased,\n    )\n    model_upper_cased = get_user_field(\n        \"What prefix (upper-cased) would you like to use for the constants relative to this model? \",\n        default_value=default_patterns.model_upper_cased,\n    )\n    config_class = get_user_field(\n        \"What will be the name of the config class for this model? \", default_value=f\"{model_camel_cased}Config\"\n    )\n    checkpoint = get_user_field(\n        \"Please give a checkpoint identifier (on the model Hub) for this new model (e.g. facebook/roberta-base): \"\n    )\n\n    old_processing_classes = [\n        c for c in [old_feature_extractor_class, old_tokenizer_class, old_processor_class] if c is not None\n    ]\n    old_processing_classes = \", \".join(old_processing_classes)\n    keep_processing = get_user_field(\n        f\"Will your new model use the same processing class as {old_model_type} ({old_processing_classes}) (yes/no)? \",\n        convert_to=convert_to_bool,\n        fallback_message=\"Please answer yes/no, y/n, true/false or 1/0. \",\n    )\n    if keep_processing:\n        feature_extractor_class = old_feature_extractor_class\n        processor_class = old_processor_class\n        tokenizer_class = old_tokenizer_class\n    else:\n        if old_tokenizer_class is not None:\n            tokenizer_class = get_user_field(\n                \"What will be the name of the tokenizer class for this model? \",\n                default_value=f\"{model_camel_cased}Tokenizer\",\n            )\n        else:\n            tokenizer_class = None\n        if old_feature_extractor_class is not None:\n            feature_extractor_class = get_user_field(\n                \"What will be the name of the feature extractor class for this model? \",\n                default_value=f\"{model_camel_cased}FeatureExtractor\",\n            )\n        else:\n            feature_extractor_class = None\n        if old_processor_class is not None:\n            processor_class = get_user_field(\n                \"What will be the name of the processor class for this model? \",\n                default_value=f\"{model_camel_cased}Processor\",\n            )\n        else:\n            processor_class = None\n\n    model_patterns = ModelPatterns(\n        model_name,\n        checkpoint,\n        model_type=model_type,\n        model_lower_cased=model_lower_cased,\n        model_camel_cased=model_camel_cased,\n        model_upper_cased=model_upper_cased,\n        config_class=config_class,\n        tokenizer_class=tokenizer_class,\n        feature_extractor_class=feature_extractor_class,\n        processor_class=processor_class,\n    )\n\n    add_copied_from = get_user_field(\n        \"Should we add # Copied from statements when creating the new modeling file (yes/no)? \",\n        convert_to=convert_to_bool,\n        default_value=\"yes\",\n        fallback_message=\"Please answer yes/no, y/n, true/false or 1/0.\",\n    )\n\n    all_frameworks = get_user_field(\n        \"Should we add a version of your new model in all the frameworks implemented by\"\n        f\" {old_model_type} ({old_frameworks}) (yes/no)? \",\n        convert_to=convert_to_bool,\n        default_value=\"yes\",\n        fallback_message=\"Please answer yes/no, y/n, true/false or 1/0.\",\n    )\n    if all_frameworks:\n        frameworks = None\n    else:\n        frameworks = get_user_field(\n            \"Please enter the list of framworks you want (pt, tf, flax) separated by spaces\",\n            is_valid_answer=lambda x: all(p in [\"pt\", \"tf\", \"flax\"] for p in x.split(\" \")),\n        )\n        frameworks = list(set(frameworks.split(\" \")))\n\n    return (old_model_type, model_patterns, add_copied_from, frameworks, old_checkpoint)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 1351,
        "n_words": 525,
        "vocab_size": 224,
        "complexity": 14,
        "nloc": 121,
        "token_counts": 503,
        "n_ast_nodes": 870,
        "n_identifiers": 53,
        "d_id": 6143,
        "documentation": {
            "docstring": "\n    Ask the user for the necessary inputs to add the new model.\n    ",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 55188,
        "commit_id": "4adc737611ffa284d9952779ba2f68174a7e73cc",
        "repo": "prefect",
        "path": "src/prefect/context.py",
        "file_name": "context.py",
        "fun_name": "__enter__",
        "commit_message": "Squash issues with tests",
        "code": "def __enter__(self):\n        \n        return_value = super().__enter__()\n\n        try:\n            os.makedirs(self.settings.value_of(PREFECT_HOME), exist_ok=True)\n        except OSError:\n            warnings.warn(\n                \"Failed to create the Prefect home directory at \"\n                f\"{self.settings.value_of(PREFECT_HOME)}\",\n                stacklevel=2,\n            )\n\n        return return_value\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 138,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 52,
        "n_ast_nodes": 104,
        "n_identifiers": 14,
        "d_id": 11265,
        "documentation": {
            "docstring": "\n        Upon initialization, we can create the home directory contained in the settings and\n        configure logging. These steps are optional. Logging can only be set up once per\n        process and later attempts to configure logging will fail.\n        ",
            "n_words": 36,
            "vocab_size": 32,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 20651,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pyparsing/results.py",
        "file_name": "results.py",
        "fun_name": "get_name",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def get_name(self):\n        r\n        if self._name:\n            return self._name\n        elif self._parent:\n            par = self._parent()\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 54,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 7,
        "nloc": 39,
        "token_counts": 103,
        "n_ast_nodes": 47,
        "n_identifiers": 5,
        "d_id": 3468,
        "documentation": {
            "docstring": "\n        Returns the results name for this token expression. Useful when several\n        different expressions might match at a particular location.\n\n        Example::\n\n            integer = Word(nums)\n            ssn_expr = Regex(r\"\\d\\d\\d-\\d\\d-\\d\\d\\d\\d\")\n            house_number_expr = Suppress('#') + Word(nums, alphanums)\n            user_data = (Group(house_number_expr)(\"house_number\")\n                        | Group(ssn_expr)(\"ssn\")\n                        | Group(integer)(\"age\"))\n            user_info = OneOrMore(user_data)\n\n            result = user_info.parse_string(\"22 111-22-3333 #221B\")\n            for item in result:\n                print(item.get_name(), ':', item[0])\n\n        prints::\n\n            age : 22\n            ssn : 111-22-3333\n            house_number : 221B\n        ",
            "n_words": 64,
            "vocab_size": 54,
            "n_whitespaces": 271,
            "language": "en"
        }
    },
    {
        "id": 65123,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/party.py",
        "file_name": "party.py",
        "fun_name": "get_party_shipping_address",
        "commit_message": "style: format code with black",
        "code": "def get_party_shipping_address(doctype, name):\n\t\n\tout = frappe.db.sql(\n\t\t\"SELECT dl.parent \"\n\t\t\"from `tabDynamic Link` dl join `tabAddress` ta on dl.parent=ta.name \"\n\t\t\"where \"\n\t\t\"dl.link_doctype=%s \"\n\t\t\"and dl.link_name=%s \"\n\t\t'and dl.parenttype=\"Address\" '\n\t\t\"and ifnull(ta.disabled, 0) = 0 and\"\n\t\t'(ta.address_type=\"Shipping\" or ta.is_shipping_address=1) '\n\t\t\"order by ta.is_shipping_address desc, ta.address_type desc limit 1\",\n\t\t(doctype, name),\n\t)\n\tif out:\n\t\treturn out[0][0]\n\telse:\n\t\treturn \"\"\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 57,
        "vocab_size": 49,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 48,
        "n_ast_nodes": 91,
        "n_identifiers": 7,
        "d_id": 13797,
        "documentation": {
            "docstring": "\n\tReturns an Address name (best guess) for the given doctype and name for which `address_type == 'Shipping'` is true.\n\tand/or `is_shipping_address = 1`.\n\n\tIt returns an empty string if there is no matching record.\n\n\t:param doctype: Party Doctype\n\t:param name: Party name\n\t:return: String\n\t",
            "n_words": 44,
            "vocab_size": 37,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 142916,
        "commit_id": "8a2f6bda62378c07a66169ee49504cc3703f7d35",
        "repo": "ray",
        "path": "python/ray/tune/experiment/trial.py",
        "file_name": "trial.py",
        "fun_name": "_trainable_name",
        "commit_message": "[tune/structure] Introduce experiment package (#26033)\n\nExperiment, Trial, and config parsing moves into an `experiment` package.\r\n\r\nNotably, the new public facing APIs will be\r\n\r\n```\r\nfrom ray.tune.experiment import Experiment\r\nfrom ray.tune.experiment import Trial\r\n```",
        "code": "def _trainable_name(self, include_trial_id=False):\n        \n        if self.custom_trial_name:\n            return self.custom_trial_name\n\n        if \"env\" in self.config:\n            env = self.config[\"env\"]\n            if isinstance(env, type):\n                env = env.__name__\n            identifier = \"{}_{}\".format(self.trainable_name, env)\n        else:\n            identifier = self.trainable_name\n        if include_trial_id:\n            identifier += \"_\" + self.trial_id\n        return identifier.replace(\"/\", \"_\")\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 161,
        "n_words": 38,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 85,
        "n_ast_nodes": 146,
        "n_identifiers": 14,
        "d_id": 32846,
        "documentation": {
            "docstring": "Combines ``env`` with ``trainable_name`` and ``trial_id``.\n\n        Can be overridden with a custom string creator.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 260959,
        "commit_id": "e4a7edc4aec597cba8b2bbce704772c7872e55f8",
        "repo": "scikit-learn",
        "path": "sklearn/utils/multiclass.py",
        "file_name": "multiclass.py",
        "fun_name": "class_distribution",
        "commit_message": "DOC ensures sklearn.utils.multiclass.class_distribution passes numpydoc validation (#24452)",
        "code": "def class_distribution(y, sample_weight=None):\n    \n    classes = []\n    n_classes = []\n    class_prior = []\n\n    n_samples, n_outputs = y.shape\n    if sample_weight is not None:\n        sample_weight = np.asarray(sample_weight)\n\n    if issparse(y):\n        y = y.tocsc()\n        y_nnz = np.diff(y.indptr)\n\n        for k in range(n_outputs):\n            col_nonzero = y.indices[y.indptr[k] : y.indptr[k + 1]]\n            # separate sample weights for zero and non-zero elements\n            if sample_weight is not None:\n                nz_samp_weight = sample_weight[col_nonzero]\n                zeros_samp_weight_sum = np.sum(sample_weight) - np.sum(nz_samp_weight)\n            else:\n                nz_samp_weight = None\n                zeros_samp_weight_sum = y.shape[0] - y_nnz[k]\n\n            classes_k, y_k = np.unique(\n                y.data[y.indptr[k] : y.indptr[k + 1]], return_inverse=True\n            )\n            class_prior_k = np.bincount(y_k, weights=nz_samp_weight)\n\n            # An explicit zero was found, combine its weight with the weight\n            # of the implicit zeros\n            if 0 in classes_k:\n                class_prior_k[classes_k == 0] += zeros_samp_weight_sum\n\n            # If an there is an implicit zero and it is not in classes and\n            # class_prior, make an entry for it\n            if 0 not in classes_k and y_nnz[k] < y.shape[0]:\n                classes_k = np.insert(classes_k, 0, 0)\n                class_prior_k = np.insert(class_prior_k, 0, zeros_samp_weight_sum)\n\n            classes.append(classes_k)\n            n_classes.append(classes_k.shape[0])\n            class_prior.append(class_prior_k / class_prior_k.sum())\n    else:\n        for k in range(n_outputs):\n            classes_k, y_k = np.unique(y[:, k], return_inverse=True)\n            classes.append(classes_k)\n            n_classes.append(classes_k.shape[0])\n            class_prior_k = np.bincount(y_k, weights=sample_weight)\n            class_prior.append(class_prior_k / class_prior_k.sum())\n\n    return (classes, n_classes, class_prior)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 598,
        "n_words": 185,
        "vocab_size": 106,
        "complexity": 9,
        "nloc": 38,
        "token_counts": 348,
        "n_ast_nodes": 541,
        "n_identifiers": 33,
        "d_id": 76590,
        "documentation": {
            "docstring": "Compute class priors from multioutput-multiclass target data.\n\n    Parameters\n    ----------\n    y : {array-like, sparse matrix} of size (n_samples, n_outputs)\n        The labels for each example.\n\n    sample_weight : array-like of shape (n_samples,), default=None\n        Sample weights.\n\n    Returns\n    -------\n    classes : list of size n_outputs of ndarray of size (n_classes,)\n        List of classes for each column.\n\n    n_classes : list of int of size n_outputs\n        Number of classes in each column.\n\n    class_prior : list of size n_outputs of ndarray of size (n_classes,)\n        Class distribution of each column.\n    ",
            "n_words": 81,
            "vocab_size": 46,
            "n_whitespaces": 146,
            "language": "en"
        }
    },
    {
        "id": 113152,
        "commit_id": "5a3d82e842906dc8f695fafe52434fde781615be",
        "repo": "nni",
        "path": "nni/algorithms/compression/v2/pytorch/utils/evaluator.py",
        "file_name": "evaluator.py",
        "fun_name": "evaluate",
        "commit_message": "[Compression] lightning & legacy evaluator - step 1 (#4950)",
        "code": "def evaluate(self) -> float | None | Tuple[float, Any] | Tuple[None, Any]:\n        \n        # Note that the first item of the returned value will be used as the default metric used by NNI.\n        raise NotImplementedError\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 55,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 26,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 24843,
        "documentation": {
            "docstring": "\n        NNI assume the evaluation function user passed in should return a float number or a dict as metric.\n        If the evaluation function returned a dict, take the value with dict key ``default`` as the first element of ``evaluate`` returned value,\n        and put the dict as the second element of the returned value.\n        For any other type of the metric returned by evaluation function, ``evaluate`` will directly returned\n        (it should be a float, but NNI does not prevent other types from being returned, this will handle by the object calling ``evaluate``).\n        ",
            "n_words": 90,
            "vocab_size": 59,
            "n_whitespaces": 133,
            "language": "en"
        }
    },
    {
        "id": 275528,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_v2/optimizer_v2.py",
        "file_name": "optimizer_v2.py",
        "fun_name": "_get_gradients",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _get_gradients(self, tape, loss, var_list, grad_loss=None):\n        \n        grads = tape.gradient(loss, var_list, grad_loss)\n        return list(zip(grads, var_list))\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 38,
        "n_ast_nodes": 56,
        "n_identifiers": 10,
        "d_id": 81418,
        "documentation": {
            "docstring": "Called in `minimize` to compute gradients from loss.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 334468,
        "commit_id": "1e21f061601dda0aa9740e88bfce68bf4aac4acd",
        "repo": "diffusers",
        "path": "models/vision/glide/modeling_glide.py",
        "file_name": "modeling_glide.py",
        "fun_name": "p_mean_variance",
        "commit_message": "Classifier-free guidance scheduler + GLIDe pipeline",
        "code": "def p_mean_variance(self, model, x, t, transformer_out, clip_denoised=True, model_kwargs=None):\n        \n        if model_kwargs is None:\n            model_kwargs = {}\n\n        B, C = x.shape[:2]\n        assert t.shape == (B,)\n        model_output = model(x, t, transformer_out)\n\n        assert model_output.shape == (B, C * 2, *x.shape[2:])\n        model_output, model_var_values = torch.split(model_output, C, dim=1)\n        min_log = _extract_into_tensor(self.noise_scheduler.posterior_log_variance_clipped, t, x.shape)\n        max_log = _extract_into_tensor(np.log(self.noise_scheduler.betas), t, x.shape)\n        # The model_var_values is [-1, 1] for [min_var, max_var].\n        frac = (model_var_values + 1) / 2\n        model_log_variance = frac * max_log + (1 - frac) * min_log\n        model_variance = torch.exp(model_log_variance)\n\n        pred_xstart = self._predict_xstart_from_eps(x_t=x, t=t, eps=model_output)\n        if clip_denoised:\n            pred_xstart = pred_xstart.clamp(-1, 1)\n        model_mean, _, _ = self.q_posterior_mean_variance(x_start=pred_xstart, x_t=x, t=t)\n\n        assert model_mean.shape == model_log_variance.shape == pred_xstart.shape == x.shape\n        return model_mean, model_variance, model_log_variance, pred_xstart\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 261,
        "n_words": 113,
        "vocab_size": 77,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 243,
        "n_ast_nodes": 356,
        "n_identifiers": 37,
        "d_id": 120634,
        "documentation": {
            "docstring": "\n        Apply the model to get p(x_{t-1} | x_t), as well as a prediction of\n        the initial x, x_0.\n\n        :param model: the model, which takes a signal and a batch of timesteps\n                      as input.\n        :param x: the [N x C x ...] tensor at time t.\n        :param t: a 1-D Tensor of timesteps.\n        :param clip_denoised: if True, clip the denoised signal into [-1, 1].\n        :param model_kwargs: if not None, a dict of extra keyword arguments to\n            pass to the model. This can be used for conditioning.\n        :return: a dict with the following keys:\n                 - 'mean': the model mean output.\n                 - 'variance': the model variance output.\n                 - 'log_variance': the log of 'variance'.\n                 - 'pred_xstart': the prediction for x_0.\n        ",
            "n_words": 116,
            "vocab_size": 76,
            "n_whitespaces": 276,
            "language": "en"
        }
    },
    {
        "id": 313967,
        "commit_id": "4bc5d7bfed07c20d6f3438ab91c734a620505a33",
        "repo": "core",
        "path": "tests/components/zha/test_button.py",
        "file_name": "test_button.py",
        "fun_name": "button_platform_only",
        "commit_message": "Speed up zha tests (#73627)",
        "code": "def button_platform_only():\n    \n    with patch(\n        \"homeassistant.components.zha.PLATFORMS\",\n        (\n            Platform.BINARY_SENSOR,\n            Platform.BUTTON,\n            Platform.DEVICE_TRACKER,\n            Platform.NUMBER,\n            Platform.SELECT,\n            Platform.SENSOR,\n        ),\n    ):\n        yield\n\n\n@pytest.fixture",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 118,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 40,
        "n_ast_nodes": 71,
        "n_identifiers": 11,
        "d_id": 112578,
        "documentation": {
            "docstring": "Only setup the button and required base platforms to speed up tests.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 130603,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/data/impl/block_list.py",
        "file_name": "block_list.py",
        "fun_name": "get_blocks_with_metadata",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def get_blocks_with_metadata(self) -> List[Tuple[ObjectRef[Block], BlockMetadata]]:\n        \n        self.get_blocks()  # Force bulk evaluation in LazyBlockList.\n        return list(self.iter_blocks_with_metadata())\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 36,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 33,
        "n_ast_nodes": 55,
        "n_identifiers": 10,
        "d_id": 29329,
        "documentation": {
            "docstring": "Bulk version of iter_blocks_with_metadata().\n\n        Prefer calling this instead of the iter form for performance if you\n        don't need lazy evaluation.\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 109533,
        "commit_id": "87197156eb299c1f37ac23c16c83ecb000e9872b",
        "repo": "matplotlib",
        "path": "lib/matplotlib/artist.py",
        "file_name": "artist.py",
        "fun_name": "get_setters",
        "commit_message": "improve matplotlib import time by caching ArtistInspector",
        "code": "def get_setters(self):\n        \n        setters = []\n        for name in dir(self.o):\n            if not name.startswith('set_'):\n                continue\n            func = getattr(self.o, name)\n            if (not callable(func)\n                    or self.number_of_parameters(func) < 2\n                    or self.is_alias(func)):\n                continue\n            setters.append(name[4:])\n        return setters\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 170,
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        "vocab_size": 25,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 78,
        "n_ast_nodes": 130,
        "n_identifiers": 13,
        "d_id": 23628,
        "documentation": {
            "docstring": "\n        Get the attribute strings with setters for object.\n\n        For example, for a line, return ``['markerfacecolor', 'linewidth',\n        ....]``.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 264889,
        "commit_id": "3a461d02793e6f9d41c2b1a92647e691de1abaac",
        "repo": "netbox",
        "path": "netbox/dcim/tests/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_cable_cannot_have_the_same_terminination_on_both_ends",
        "commit_message": "Update Cable instantiations to match new signature",
        "code": "def test_cable_cannot_have_the_same_terminination_on_both_ends(self):\n        \n        cable = Cable(a_terminations=[self.interface1], b_terminations=[self.interface1])\n        with self.assertRaises(ValidationError):\n            cable.clean()\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 67,
        "n_identifiers": 10,
        "d_id": 77900,
        "documentation": {
            "docstring": "\n        A cable cannot be made with the same A and B side terminations\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 245152,
        "commit_id": "36c1f477b273cb2fb0dea3c921ec267db877c039",
        "repo": "mmdetection",
        "path": "mmdet/datasets/openimages.py",
        "file_name": "openimages.py",
        "fun_name": "_parse_img_level_ann",
        "commit_message": "Refactor OpenImages.",
        "code": "def _parse_img_level_ann(self, image_level_ann_file):\n        \n\n        item_lists = defaultdict(list)\n        with self.file_client.get_local_path(\n                image_level_ann_file) as local_path:\n            with open(local_path, 'r') as f:\n                reader = csv.reader(f)\n                i = -1\n                for line in reader:\n                    i += 1\n                    if i == 0:\n                        continue\n                    else:\n                        img_id = line[0]\n                        label_id = line[1]\n                        assert label_id in self.label_id_mapping\n                        image_level_label = int(\n                            self.label_id_mapping[label_id])\n                        confidence = float(line[2])\n                        item_lists[img_id].append(\n                            dict(\n                                image_level_label=image_level_label,\n                                confidence=confidence))\n        return item_lists\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 491,
        "n_words": 58,
        "vocab_size": 45,
        "complexity": 3,
        "nloc": 23,
        "token_counts": 122,
        "n_ast_nodes": 201,
        "n_identifiers": 24,
        "d_id": 70677,
        "documentation": {
            "docstring": "Parse image level annotations from csv style ann_file.\n\n        Args:\n            image_level_ann_file (str): CSV style image level annotation\n                file path.\n\n        Returns:\n            defaultdict[list[dict]]: Annotations where item of the defaultdict\n            indicates an image, each of which has (n) dicts.\n            Keys of dicts are:\n\n                - `image_level_label` (int): of shape 1.\n                - `confidence` (float): of shape 1.\n        ",
            "n_words": 51,
            "vocab_size": 41,
            "n_whitespaces": 161,
            "language": "en"
        }
    },
    {
        "id": 35045,
        "commit_id": "7732d0fe7a759c9844215920e9f1c5540eafb1a6",
        "repo": "transformers",
        "path": "src/transformers/models/funnel/modeling_tf_funnel.py",
        "file_name": "modeling_tf_funnel.py",
        "fun_name": "stride_pool_pos",
        "commit_message": "Upgrade black to version ~=22.0 (#15565)\n\n* Upgrade black to version ~=22.0\r\n\r\n* Check copies\r\n\r\n* Fix code",
        "code": "def stride_pool_pos(self, pos_id, block_index):\n        \n        if self.separate_cls:\n            # Under separate <cls>, we treat the <cls> as the first token in\n            # the previous block of the 1st real block. Since the 1st real\n            # block always has position 1, the position of the previous block\n            # will be at `1 - 2 ** block_index`.\n            cls_pos = tf.constant([-(2**block_index) + 1], dtype=pos_id.dtype)\n            pooled_pos_id = pos_id[1:-1] if self.truncate_seq else pos_id[1:]\n            return tf.concat([cls_pos, pooled_pos_id[::2]], 0)\n        else:\n            return pos_id[::2]\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 182,
        "n_words": 73,
        "vocab_size": 54,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 82,
        "n_ast_nodes": 131,
        "n_identifiers": 12,
        "d_id": 6387,
        "documentation": {
            "docstring": "\n        Pool `pos_id` while keeping the cls token separate (if `self.separate_cls=True`).\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 269615,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "_mark_func_graph_as_unsaveable",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _mark_func_graph_as_unsaveable(graph, learning_phase):\n    \n    if graph.building_function and is_placeholder(learning_phase):\n        graph.mark_as_unsaveable(\n            \"The keras learning phase placeholder was used inside a function. \"\n            \"Exporting placeholders is not supported when saving out a SavedModel. \"\n            \"Please call `tf.keras.backend.set_learning_phase(0)` in the function \"\n            \"to set the learning phase to a constant value.\"\n        )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 111,
        "n_words": 47,
        "vocab_size": 40,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 27,
        "n_ast_nodes": 53,
        "n_identifiers": 6,
        "d_id": 80234,
        "documentation": {
            "docstring": "Mark func graph as unsaveable due to use of symbolic keras learning phase.\n\n    Functions that capture the symbolic learning phase cannot be exported to\n    SavedModel. Mark the funcgraph as unsaveable, so that an error will be raised\n    if it is exported.\n\n    Args:\n      graph: Graph or FuncGraph object.\n      learning_phase: Learning phase placeholder or int defined in the graph.\n    ",
            "n_words": 57,
            "vocab_size": 46,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 194805,
        "commit_id": "5322cd4f5821e339bf1edab98d93b5a008b97a2b",
        "repo": "ParlAI",
        "path": "parlai/utils/fsdp.py",
        "file_name": "fsdp.py",
        "fun_name": "maybe_fsdp_wrap",
        "commit_message": "[circle] Fixing broken unit tests (#4343)",
        "code": "def maybe_fsdp_wrap(opt):\n    \n    if not should_use_fsdp(opt):\n        # make a no-op\n        yield\n        return\n\n    # zero3 not supported at this time. Throw an exception\n    if opt['ddp_backend'] == 'zero3':\n        raise NotImplementedError(\n            '--ddp-backend zero3 is not supported at this time. For details, see '\n            'https://github.com/facebookresearch/ParlAI/issues/3753.'\n        )\n\n    reshard_after_forward = opt['ddp_backend'] == 'zero3'\n    compute_dtype = torch.float16 if opt['fp16'] else torch.float32\n    mixed_precision = opt['fp16'] and opt['fp16_impl'] == 'safe'\n    fsdp_args = dict(\n        reshard_after_forward=reshard_after_forward,\n        mixed_precision=mixed_precision,\n        compute_dtype=compute_dtype,\n        state_dict_device=torch.device('cpu'),\n        flatten_parameters=False,\n        process_group=get_dist_group(),\n    )\n    with fairscale_enable_wrap(wrapper_cls=FSDP, **fsdp_args):\n        yield\n\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 210,
        "n_words": 74,
        "vocab_size": 55,
        "complexity": 5,
        "nloc": 22,
        "token_counts": 112,
        "n_ast_nodes": 200,
        "n_identifiers": 20,
        "d_id": 47093,
        "documentation": {
            "docstring": "\n    Context manager for enabling wrapping in FullyShardedDataParallel.\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 258733,
        "commit_id": "5f75acdd12d77b973471961ad716367c6199d01c",
        "repo": "scikit-learn",
        "path": "sklearn/ensemble/_forest.py",
        "file_name": "_forest.py",
        "fun_name": "apply",
        "commit_message": "MNT Bump joblib version dependency to 1.0.0 (#22365)",
        "code": "def apply(self, X):\n        \n        X = self._validate_X_predict(X)\n        results = Parallel(\n            n_jobs=self.n_jobs,\n            verbose=self.verbose,\n            prefer=\"threads\",\n        )(delayed(tree.apply)(X, check_input=False) for tree in self.estimators_)\n\n        return np.array(results).T\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 88,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 67,
        "n_ast_nodes": 105,
        "n_identifiers": 16,
        "d_id": 75393,
        "documentation": {
            "docstring": "\n        Apply trees in the forest to X, return leaf indices.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix} of shape (n_samples, n_features)\n            The input samples. Internally, its dtype will be converted to\n            ``dtype=np.float32``. If a sparse matrix is provided, it will be\n            converted into a sparse ``csr_matrix``.\n\n        Returns\n        -------\n        X_leaves : ndarray of shape (n_samples, n_estimators)\n            For each datapoint x in X and for each tree in the forest,\n            return the index of the leaf x ends up in.\n        ",
            "n_words": 78,
            "vocab_size": 56,
            "n_whitespaces": 190,
            "language": "en"
        }
    },
    {
        "id": 215653,
        "commit_id": "fbecbe82483ffed562c0d2673d5a5e792553aec2",
        "repo": "salt",
        "path": "tests/pytests/scenarios/multimaster/test_multimaster.py",
        "file_name": "test_multimaster.py",
        "fun_name": "_get_all_ret_events_after_time",
        "commit_message": "fix multimaster tests failing",
        "code": "def _get_all_ret_events_after_time(masters, minions, event_listener, start_time):\n    \n    minion_pattern = \"salt/job/*/ret/{}\"\n    events = []\n\n    for minion in minions:\n        tag = minion_pattern.format(minion.id)\n        matchers = [(master.id, tag) for master in masters]\n        ret_events = event_listener.get_events(matchers, after_time=start_time)\n        events.append([event for event in ret_events if event.data[\"fun\"] == \"test.echo\"])\n\n    return tuple(events)\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 84,
        "n_words": 41,
        "vocab_size": 32,
        "complexity": 5,
        "nloc": 9,
        "token_counts": 87,
        "n_ast_nodes": 138,
        "n_identifiers": 20,
        "d_id": 54075,
        "documentation": {
            "docstring": "\n    Get all the ret events that happened after `start_time`\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 47760,
        "commit_id": "197cff3194e855b9207c3c0da8ae093a0d5dda55",
        "repo": "airflow",
        "path": "tests/models/test_taskinstance.py",
        "file_name": "test_taskinstance.py",
        "fun_name": "test_not_recorded_if_not_used",
        "commit_message": "Ensure TaskMap only checks \"relevant\" dependencies (#23053)\n\nWhen looking for \"mapped dependants\" of a task, we only want a task if\r\nit not only is a direct downstream of the task, but also it actually\r\n\"uses\" the task's pushed XCom for task mapping. So we need to peek into\r\nthe mapped downstream task's expansion kwargs, and only count it as a\r\nmapped dependant if the upstream is referenced there.",
        "code": "def test_not_recorded_if_not_used(self, dag_maker, xcom_value):\n        \n        with dag_maker(dag_id=\"test_not_recorded_for_unused\") as dag:\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 86,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 9249,
        "documentation": {
            "docstring": "Return value should not be recorded if no downstreams are mapped.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 5822,
        "commit_id": "2a157d452611d37cf50ccb7d56ff1a06e9790ecb",
        "repo": "InstaPy",
        "path": "instapy/util.py",
        "file_name": "util.py",
        "fun_name": "get_active_users",
        "commit_message": "PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438)\n\n* Updated getUserData() and find_element*\r\nSigned-off-by: elulcao <elulcao@icloud.com>\r\n\r\nThanks @breuerfelix for reviewing, 🚀 \r\nPeople in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her",
        "code": "def get_active_users(browser, username, posts, boundary, logger):\n    \n\n    user_link = \"https://www.instagram.com/{}/\".format(username)\n\n    # check URL of the webpage, if it already is user's profile page,\n    # then do not navigate to it again\n    web_address_navigator(browser, user_link)\n\n    try:\n        total_posts = browser.execute_script(\n            \"return window._sharedData.entry_data.\"\n            \"ProfilePage[0].graphql.user.edge_owner_to_timeline_media.count\"\n        )\n    except WebDriverException:\n        try:\n            topCount_elements = browser.find_elements(\n                By.XPATH, read_xpath(get_active_users.__name__, \"topCount_elements\")\n            )\n\n            if topCount_elements:  # prevent an empty string scenario\n                total_posts = format_number(topCount_elements[0].text)\n            else:\n                logger.info(\"Failed to get posts count on your profile!  ~empty string\")\n                total_posts = None\n        except NoSuchElementException:\n            logger.info(\"Failed to get posts count on your profile!\")\n            total_posts = None\n\n    # if posts > total user posts, assume total posts\n    posts = (\n        posts if total_posts is None else total_posts if posts > total_posts else posts\n    )\n\n    active_users = []\n    sc_rolled = 0\n    start_time = time.time()\n    too_many_requests = 0  # helps to prevent misbehaviours when requests\n    # list of active users repeatedly within less than 10 min of breaks\n\n    message = (\n        \"~collecting the entire usernames from posts without a boundary!\\n\"\n        if boundary is None\n        else \"~collecting only the visible usernames from posts without scrolling \"\n        \"at the boundary of zero..\\n\"\n        if boundary == 0\n        else \"~collecting the usernames from posts with the boundary of {}\"\n        \"\\n\".format(boundary)\n    )\n    # posts argument is the number of posts to collect usernames\n    logger.info(\n        \"Getting active users who liked the latest {} posts:\\n {}\".format(\n            posts, message\n        )\n    )\n\n    count = 1\n    checked_posts = 0\n    user_list = []\n\n    while count <= posts:\n        # load next post\n        try:\n            latest_post = browser.find_element(\n                By.XPATH,\n                read_xpath(get_active_users.__name__, \"profile_posts\").format(count),\n            )\n            # avoid no posts\n            if latest_post:\n                click_element(browser, latest_post)\n        except (NoSuchElementException, WebDriverException):\n            logger.warning(\"Failed to click on the latest post to grab active likers!\")\n            return []\n        try:\n            checked_posts += 1\n            sleep_actual(2)\n\n            try:\n                likers_count = browser.find_element(\n                    By.XPATH, read_xpath(get_active_users.__name__, \"likers_count\")\n                ).text\n                if likers_count:  # prevent an empty string scenarios\n                    likers_count = format_number(likers_count)\n                    # liked by 'username' AND 165 others (166 in total)\n                    likers_count += 1\n                else:\n                    logger.info(\n                        \"Failed to get likers count on your post {} \"\n                        \"~empty string\".format(count)\n                    )\n                    likers_count = None\n            except NoSuchElementException:\n                logger.info(\"Failed to get likers count on your post {}\".format(count))\n                likers_count = None\n            try:\n                likes_button = browser.find_elements(\n                    By.XPATH, read_xpath(get_active_users.__name__, \"likes_button\")\n                )\n\n                if likes_button != []:\n                    if likes_button[1] is not None:\n                        likes_button = likes_button[1]\n                    else:\n                        likes_button = likes_button[0]\n                    click_element(browser, likes_button)\n                    sleep_actual(3)\n                else:\n                    raise NoSuchElementException\n\n            except (IndexError, NoSuchElementException):\n                # Video have no likes button / no posts in page\n                logger.info(\"Video found, try next post until we run out of posts\")\n\n                # edge case of account having only videos,  or last post is a video.\n                if checked_posts >= total_posts:\n                    break\n                # if not reached posts(parameter) value, continue (but load next post)\n                browser.back()\n                # go to next post\n                count += 1\n                continue\n\n            # get a reference to the 'Likes' dialog box\n            dialog = browser.find_element(\n                By.XPATH, read_xpath(\"class_selectors\", \"likes_dialog_body_xpath\")\n            )\n\n            scroll_it = True\n            try_again = 0\n            start_time = time.time()\n\n            if likers_count:\n                amount = (\n                    likers_count\n                    if boundary is None\n                    else None\n                    if boundary == 0\n                    else (boundary if boundary < likers_count else likers_count)\n                )\n            else:\n                amount = None\n            tmp_scroll_height = 0\n            user_list_len = -1\n            while scroll_it is not False and boundary != 0:\n                scroll_height = browser.execute_script(\n                    \n                )\n                # check if it should keep scrolling down or exit\n                if (\n                    scroll_height >= tmp_scroll_height\n                    and len(user_list) > user_list_len\n                ):\n                    tmp_scroll_height = scroll_height\n                    user_list_len = len(user_list)\n                    scroll_it = True\n                else:\n                    scroll_it = False\n\n                if scroll_it is True:\n                    scroll_it = browser.execute_script(\"window.scrollBy(0, 1000)\")\n                    update_activity(browser, state=None)\n\n                if sc_rolled > 91 or too_many_requests > 1:  # old value 100\n                    print(\"\\n\")\n                    logger.info(\"Too Many Requests sent! ~will sleep some :>\\n\")\n                    sleep_actual(600)\n                    sc_rolled = 0\n                    too_many_requests = (\n                        0 if too_many_requests >= 1 else too_many_requests\n                    )\n\n                else:\n                    sleep_actual(1.2)  # old value 5.6\n                    sc_rolled += 1\n\n                user_list = get_users_from_dialog(user_list, dialog, logger)\n\n                # write & update records at Progress Tracker\n                if amount:\n                    progress_tracker(len(user_list), amount, start_time, None)\n                    print(\"\\n\")\n\n                if boundary is not None:\n                    if len(user_list) >= boundary:\n                        break\n\n                if (\n                    scroll_it is False\n                    and likers_count\n                    and likers_count - 1 > len(user_list)\n                ):\n\n                    if (\n                        boundary is not None and likers_count - 1 > boundary\n                    ) or boundary is None:\n\n                        if try_again <= 1:  # can increase the amount of tries\n                            logger.info(\n                                \"Failed to get the desired amount of \"\n                                \"usernames but trying again...\"\n                                \"\\t|> post: {} |> attempt: {}\\n\".format(\n                                    posts, try_again + 1\n                                )\n                            )\n                            try_again += 1\n                            too_many_requests += 1\n                            scroll_it = True\n                            nap_it = 4 if try_again == 0 else 7\n                            sleep_actual(nap_it)\n\n            user_list = get_users_from_dialog(user_list, dialog, logger)\n\n            logger.info(\n                \"Post {} | Likers: found {}, catched {}\\n\\n\".format(\n                    count, likers_count, len(user_list)\n                )\n            )\n        except NoSuchElementException as exc:\n            logger.error(\n                \"Ku-ku! There is an error searching active users\"\n                \"~\\t{}\\n\\n\".format(str(exc).encode(\"utf-8\"))\n            )\n\n        for user in user_list:\n            active_users.append(user)\n\n        sleep_actual(1)\n\n        # if not reached posts(parameter) value, continue\n        if count != posts + 1:\n            try:\n                # click close button\n                close_dialog_box(browser)\n                browser.back()\n            except Exception:\n                logger.error(\"Unable to go to next profile post\")\n        count += 1\n\n    real_time = time.time()\n    diff_in_minutes = int((real_time - start_time) / 60)\n    diff_in_seconds = int((real_time - start_time) % 60)\n\n    # delete duplicated users\n    active_users = list(set(active_users))\n\n    logger.info(\n        \"Gathered total of {} unique active followers from the latest {} \"\n        \"posts in {} minutes and {} seconds\".format(\n            len(active_users), posts, diff_in_minutes, diff_in_seconds\n        )\n    )\n\n    return active_users\n\n",
        "url": "https://github.com/InstaPy/InstaPy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 3763,
        "n_words": 836,
        "vocab_size": 340,
        "complexity": 44,
        "nloc": 203,
        "token_counts": 882,
        "n_ast_nodes": 1504,
        "n_identifiers": 68,
        "d_id": 844,
        "documentation": {
            "docstring": "Returns a list with usernames who liked the latest n posts\n                    let main = document.getElementsByTagName('main')\n                    return main[0].scrollHeight\n                    ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 258375,
        "commit_id": "9ebf164cfdfb320503b7161493420c1b0ec577a3",
        "repo": "haystack",
        "path": "test/nodes/test_prompt_node.py",
        "file_name": "test_prompt_node.py",
        "fun_name": "test_complex_pipeline_with_shared_prompt_model_yaml",
        "commit_message": "feat: Expand LLM support with PromptModel, PromptNode, and PromptTemplate (#3667)\n\nCo-authored-by: ZanSara <sarazanzo94@gmail.com>",
        "code": "def test_complex_pipeline_with_shared_prompt_model_yaml(tmp_path):\n    with open(tmp_path / \"tmp_config.yml\", \"w\") as tmp_file:\n        tmp_file.write(\n            f\n        )\n    pipeline = Pipeline.load_from_yaml(path=tmp_path / \"tmp_config.yml\")\n    result = pipeline.run(query=\"not relevant\", documents=[Document(\"Berlin is an amazing city.\")])\n    assert \"Berlin\" in result[\"results\"][0]\n    assert len(result[\"meta\"][\"invocation_context\"]) > 0\n\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 73,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 34,
        "token_counts": 78,
        "n_ast_nodes": 141,
        "n_identifiers": 15,
        "d_id": 75230,
        "documentation": {
            "docstring": "\n            version: ignore\n            components:\n            - name: pmodel\n              type: PromptModel\n            - name: p1\n              params:\n                model_name_or_path: pmodel\n                default_prompt_template: question-generation\n                output_variable: questions\n              type: PromptNode\n            - name: p2\n              params:\n                model_name_or_path: pmodel\n                default_prompt_template: question-answering\n              type: PromptNode\n            pipelines:\n            - name: query\n              nodes:\n              - name: p1\n                inputs:\n                - Query\n              - name: p2\n                inputs:\n                - p1\n        ",
            "n_words": 47,
            "vocab_size": 23,
            "n_whitespaces": 371,
            "language": "en"
        }
    },
    {
        "id": 100179,
        "commit_id": "096b5511e244eecd8799b2a0324655207ce8985e",
        "repo": "sentry",
        "path": "tests/sentry/data_export/endpoints/test_data_export.py",
        "file_name": "test_data_export.py",
        "fun_name": "test_new_export",
        "commit_message": "ref(tests): Remove `get_valid_response()` (#34822)",
        "code": "def test_new_export(self):\n        \n        payload = self.make_payload(\"issue\")\n        with self.feature(\"organizations:discover-query\"):\n            response = self.get_success_response(self.org.slug, status_code=201, **payload)\n        data_export = ExportedData.objects.get(id=response.data[\"id\"])\n        assert response.data == {\n            \"id\": data_export.id,\n            \"user\": {\n                \"id\": str(self.user.id),\n                \"email\": self.user.email,\n                \"username\": self.user.username,\n            },\n            \"dateCreated\": data_export.date_added,\n            \"dateFinished\": None,\n            \"dateExpired\": None,\n            \"query\": {\n                \"type\": payload[\"query_type\"],\n                \"info\": payload[\"query_info\"],\n            },\n            \"status\": ExportStatus.Early,\n            \"checksum\": None,\n            \"fileName\": None,\n        }\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 299,
        "n_words": 50,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 150,
        "n_ast_nodes": 258,
        "n_identifiers": 23,
        "d_id": 19772,
        "documentation": {
            "docstring": "\n        Ensures that a request to this endpoint returns a 201 status code\n        and an appropriate response object\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 202367,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/csrf_tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_masked_unmasked_combinations",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_masked_unmasked_combinations(self):\n        \n        cases = [\n            (TEST_SECRET, TEST_SECRET, None),\n            (TEST_SECRET, MASKED_TEST_SECRET2, None),\n            (TEST_SECRET, None, TEST_SECRET),\n            (TEST_SECRET, None, MASKED_TEST_SECRET2),\n            (MASKED_TEST_SECRET1, TEST_SECRET, None),\n            (MASKED_TEST_SECRET1, MASKED_TEST_SECRET2, None),\n            (MASKED_TEST_SECRET1, None, TEST_SECRET),\n            (MASKED_TEST_SECRET1, None, MASKED_TEST_SECRET2),\n        ]\n        for args in cases:\n            with self.subTest(args=args):\n                cookie, post_token, meta_token = args\n                req = self._get_POST_csrf_cookie_request(\n                    cookie=cookie,\n                    post_token=post_token,\n                    meta_token=meta_token,\n                )\n                mw = CsrfViewMiddleware(token_view)\n                mw.process_request(req)\n                resp = mw.process_view(req, token_view, (), {})\n                self.assertIsNone(resp)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 348,
        "n_words": 59,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 23,
        "token_counts": 149,
        "n_ast_nodes": 207,
        "n_identifiers": 20,
        "d_id": 50085,
        "documentation": {
            "docstring": "\n        All combinations are allowed of (1) masked and unmasked cookies,\n        (2) masked and unmasked tokens, and (3) tokens provided via POST and\n        the X-CSRFToken header.\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 153816,
        "commit_id": "57e29bc5d82348006c5170ef9ac0a9eedcd9acf9",
        "repo": "modin",
        "path": "modin/core/storage_formats/base/query_compiler.py",
        "file_name": "query_compiler.py",
        "fun_name": "mode",
        "commit_message": "REFACTOR-#4513: Fix spelling mistakes in docs and docstrings (#4514)\n\nCo-authored-by: Rehan Sohail Durrani <rdurrani@berkeley.edu>\r\nSigned-off-by: jeffreykennethli <jkli@ponder.io>",
        "code": "def mode(self, **kwargs):  # noqa: PR02\n        \n        return DataFrameDefault.register(pandas.DataFrame.mode)(self, **kwargs)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 24,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 26,
        "n_ast_nodes": 44,
        "n_identifiers": 7,
        "d_id": 35631,
        "documentation": {
            "docstring": "\n        Get the modes for every column or row.\n\n        Parameters\n        ----------\n        axis : {0, 1}\n        numeric_only : bool\n        dropna : bool\n        **kwargs : dict\n            Serves the compatibility purpose. Does not affect the result.\n\n        Returns\n        -------\n        BaseQueryCompiler\n            New QueryCompiler with modes calculated along given axis.\n        ",
            "n_words": 43,
            "vocab_size": 36,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 198364,
        "commit_id": "7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c",
        "repo": "sympy",
        "path": "sympy/combinatorics/rewritingsystem.py",
        "file_name": "rewritingsystem.py",
        "fun_name": "reduce_using_automaton",
        "commit_message": "Cleanup loops and ranges",
        "code": "def reduce_using_automaton(self, word):\n        \n        # Modify the automaton if new rules are found.\n        if self._new_rules:\n            self._add_to_automaton(self._new_rules)\n            self._new_rules = {}\n\n        flag = 1\n        while flag:\n            flag = 0\n            current_state = self.reduction_automaton.states['start']\n            for i, s in enumerate(word.letter_form_elm):\n                next_state_name = current_state.transitions[s]\n                next_state = self.reduction_automaton.states[next_state_name]\n                if next_state.state_type == 'd':\n                    subst = next_state.rh_rule\n                    word = word.substituted_word(i - len(next_state_name) + 1, i+1, subst)\n                    flag = 1\n                    break\n                current_state = next_state\n        return word\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 298,
        "n_words": 65,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 118,
        "n_ast_nodes": 191,
        "n_identifiers": 21,
        "d_id": 48884,
        "documentation": {
            "docstring": "\n        Reduce a word using an automaton.\n\n        Summary:\n        All the symbols of the word are stored in an array and are given as the input to the automaton.\n        If the automaton reaches a dead state that subword is replaced and the automaton is run from the beginning.\n        The complete word has to be replaced when the word is read and the automaton reaches a dead state.\n        So, this process is repeated until the word is read completely and the automaton reaches the accept state.\n\n        Arguments:\n            word (instance of FreeGroupElement) -- Word that needs to be reduced.\n\n        ",
            "n_words": 95,
            "vocab_size": 53,
            "n_whitespaces": 163,
            "language": "en"
        }
    },
    {
        "id": 125184,
        "commit_id": "adf24bfa9723b0621183bb27f0c889b813c06e8a",
        "repo": "ray",
        "path": "python/ray/_private/thirdparty/tabulate/tabulate.py",
        "file_name": "tabulate.py",
        "fun_name": "_format",
        "commit_message": "[State Observability] Use a table format by default (#26159)\n\nNOTE: tabulate is copied/pasted to the codebase for table formatting.\r\n\r\nThis PR changes the default layout to be the table format for both summary and list APIs.",
        "code": "def _format(val, valtype, floatfmt, missingval=\"\", has_invisible=True):\n      # noqa\n    if val is None:\n        return missingval\n\n    if valtype in [int, _text_type]:\n        return \"{0}\".format(val)\n    elif valtype is _binary_type:\n        try:\n            return _text_type(val, \"ascii\")\n        except TypeError:\n            return _text_type(val)\n    elif valtype is float:\n        is_a_colored_number = has_invisible and isinstance(\n            val, (_text_type, _binary_type)\n        )\n        if is_a_colored_number:\n            raw_val = _strip_invisible(val)\n            formatted_val = format(float(raw_val), floatfmt)\n            return val.replace(raw_val, formatted_val)\n        else:\n            return format(float(val), floatfmt)\n    else:\n        return \"{0}\".format(val)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 224,
        "n_words": 65,
        "vocab_size": 47,
        "complexity": 8,
        "nloc": 22,
        "token_counts": 132,
        "n_ast_nodes": 251,
        "n_identifiers": 18,
        "d_id": 27798,
        "documentation": {
            "docstring": "Format a value according to its type.\n\n    Unicode is supported:\n\n    >>> hrow = ['\\u0431\\u0443\\u043a\\u0432\\u0430', '\\u0446\\u0438\\u0444\\u0440\\u0430'] ; \\\n        tbl = [['\\u0430\\u0437', 2], ['\\u0431\\u0443\\u043a\\u0438', 4]] ; \\\n        good_result = '\\\\u0431\\\\u0443\\\\u043a\\\\u0432\\\\u0430      \\\\u0446\\\\u0438\\\\u0444\\\\u0440\\\\u0430\\\\n-------  -------\\\\n\\\\u0430\\\\u0437             2\\\\n\\\\u0431\\\\u0443\\\\u043a\\\\u0438           4' ; \\\n        tabulate(tbl, headers=hrow) == good_result\n    True\n\n    ",
            "n_words": 39,
            "vocab_size": 32,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 319518,
        "commit_id": "8a6aaf4e2d05021a14adc681c66dff6a815aa2a0",
        "repo": "paperless-ngx",
        "path": "src/paperless/tests/test_settings.py",
        "file_name": "test_settings.py",
        "fun_name": "test_single_ignore_dates_set",
        "commit_message": "Adds additional testing for both date parsing and consumed document created date",
        "code": "def test_single_ignore_dates_set(self):\n        \n        test_cases = [\n            (\"1985-05-01\", [datetime.date(1985, 5, 1)]),\n            (\n                \"1985-05-01,1991-12-05\",\n                [datetime.date(1985, 5, 1), datetime.date(1991, 12, 5)],\n            ),\n            (\"2010-12-13\", [datetime.date(2010, 12, 13)]),\n        ]\n        for env_str, expected_dates in test_cases:\n            expected_date_set = set()\n\n            for expected_date in expected_dates:\n                expected_date_set.add(expected_date)\n\n            self.assertSetEqual(\n                _parse_ignore_dates(env_str),\n                expected_date_set,\n            )\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 231,
        "n_words": 40,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 108,
        "n_ast_nodes": 161,
        "n_identifiers": 13,
        "d_id": 116958,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - Ignore dates are set per certain inputs\n        THEN:\n            - All ignore dates are parsed\n        ",
            "n_words": 16,
            "vocab_size": 13,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 221805,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ctypes/_aix.py",
        "file_name": "_aix.py",
        "fun_name": "get_version",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_version(name, members):\n    \n    # the expression ending for versions must start as\n    # '.so.[0-9]', i.e., *.so.[at least one digit]\n    # while multiple, more specific expressions could be specified\n    # to search for .so.X, .so.X.Y and .so.X.Y.Z\n    # after the first required 'dot' digit\n    # any combination of additional 'dot' digits pairs are accepted\n    # anything more than libFOO.so.digits.digits.digits\n    # should be seen as a member name outside normal expectations\n    exprs = [rf'lib{name}\\.so\\.[0-9]+[0-9.]*',\n        rf'lib{name}_?64\\.so\\.[0-9]+[0-9.]*']\n    for expr in exprs:\n        versions = []\n        for line in members:\n            m = re.search(expr, line)\n            if m:\n                versions.append(m.group(0))\n        if versions:\n            return _last_version(versions, '.')\n    return None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 210,
        "n_words": 98,
        "vocab_size": 77,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 67,
        "n_ast_nodes": 124,
        "n_identifiers": 13,
        "d_id": 56521,
        "documentation": {
            "docstring": "\n    Sort list of members and return highest numbered version - if it exists.\n    This function is called when an unversioned libFOO.a(libFOO.so) has\n    not been found.\n\n    Versioning for the member name is expected to follow\n    GNU LIBTOOL conventions: the highest version (x, then X.y, then X.Y.z)\n     * find [libFoo.so.X]\n     * find [libFoo.so.X.Y]\n     * find [libFoo.so.X.Y.Z]\n\n    Before the GNU convention became the standard scheme regardless of\n    binary size AIX packagers used GNU convention \"as-is\" for 32-bit\n    archive members but used an \"distinguishing\" name for 64-bit members.\n    This scheme inserted either 64 or _64 between libFOO and .so\n    - generally libFOO_64.so, but occasionally libFOO64.so\n    ",
            "n_words": 101,
            "vocab_size": 75,
            "n_whitespaces": 147,
            "language": "en"
        }
    },
    {
        "id": 73191,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/templatetags/modeladmin_tags.py",
        "file_name": "modeladmin_tags.py",
        "fun_name": "result_list",
        "commit_message": "Reformat with black",
        "code": "def result_list(context):\n    \n    view = context[\"view\"]\n    object_list = context[\"object_list\"]\n    headers = list(result_headers(view))\n    num_sorted_fields = 0\n    for h in headers:\n        if h[\"sortable\"] and h[\"sorted\"]:\n            num_sorted_fields += 1\n    context.update(\n        {\n            \"result_headers\": headers,\n            \"num_sorted_fields\": num_sorted_fields,\n            \"results\": list(results(view, object_list, context[\"request\"])),\n        }\n    )\n    return context\n\n\n@register.simple_tag",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@register.simple_tag",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 131,
        "n_words": 40,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 83,
        "n_ast_nodes": 150,
        "n_identifiers": 13,
        "d_id": 15981,
        "documentation": {
            "docstring": "\n    Displays the headers and data list together\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 287751,
        "commit_id": "1b144c0e4dd683e3b47668a89da5eb6da4ae5e08",
        "repo": "core",
        "path": "tests/components/bluetooth/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_wrapped_bleak_client_raises_device_missing",
        "commit_message": "Update to bleak 0.18.0 (#79008)",
        "code": "async def test_wrapped_bleak_client_raises_device_missing(hass, enable_bluetooth):\n    \n    switchbot_device = BLEDevice(\"44:44:33:11:23:45\", \"wohand\")\n    client = HaBleakClientWrapper(switchbot_device)\n    assert client.is_connected is False\n    with pytest.raises(bleak.BleakError):\n        await client.connect()\n    assert client.is_connected is False\n    await client.disconnect()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 53,
        "n_words": 25,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 56,
        "n_ast_nodes": 100,
        "n_identifiers": 14,
        "d_id": 86939,
        "documentation": {
            "docstring": "Test wrapped bleak client dispatches calls as expected.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 42454,
        "commit_id": "8ffd0d8190552d45f8b92e18da3fc41639e5185d",
        "repo": "nltk",
        "path": "nltk/corpus/reader/wordnet.py",
        "file_name": "wordnet.py",
        "fun_name": "add_exomw",
        "commit_message": "Initialize empty provenance for default English",
        "code": "def add_exomw(self):\n        \n        from nltk.corpus import extended_omw\n\n        self._exomw_reader = extended_omw\n        self.add_provs(self._exomw_reader)\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 38,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 25,
        "n_ast_nodes": 43,
        "n_identifiers": 7,
        "d_id": 7547,
        "documentation": {
            "docstring": "\n        Add languages from Extended OMW\n\n        >>> import nltk\n        >>> from nltk.corpus import wordnet as wn\n        >>> wn.add_exomw()\n        >>> print(wn.synset('intrinsically.r.01').lemmas(lang=\"eng_wikt\"))\n        [Lemma('intrinsically.r.01.per_se'), Lemma('intrinsically.r.01.as_such')]\n        ",
            "n_words": 21,
            "vocab_size": 16,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 137621,
        "commit_id": "608276bb96b5b49769cd8816414c280c5431d843",
        "repo": "ray",
        "path": "python/ray/util/client/server/logservicer.py",
        "file_name": "logservicer.py",
        "fun_name": "log_status_change_thread",
        "commit_message": "Simplify logging configuration. (#30863)",
        "code": "def log_status_change_thread(log_queue, request_iterator):\n    \n    std_handler = StdStreamHandler(log_queue)\n    current_handler = None\n    root_logger = logging.getLogger(\"ray\")\n    default_level = root_logger.getEffectiveLevel()\n    try:\n        for req in request_iterator:\n            if current_handler is not None:\n                root_logger.setLevel(default_level)\n                root_logger.removeHandler(current_handler)\n                std_handler.unregister_global()\n            if not req.enabled:\n                current_handler = None\n                continue\n            current_handler = LogstreamHandler(log_queue, req.loglevel)\n            std_handler.register_global()\n            root_logger.addHandler(current_handler)\n            root_logger.setLevel(req.loglevel)\n    except grpc.RpcError as e:\n        logger.debug(f\"closing log thread \" f\"grpc error reading request_iterator: {e}\")\n    finally:\n        if current_handler is not None:\n            root_logger.setLevel(default_level)\n            root_logger.removeHandler(current_handler)\n            std_handler.unregister_global()\n        log_queue.put(None)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 291,
        "n_words": 65,
        "vocab_size": 45,
        "complexity": 7,
        "nloc": 26,
        "token_counts": 148,
        "n_ast_nodes": 254,
        "n_identifiers": 26,
        "d_id": 31203,
        "documentation": {
            "docstring": "This is run in a separate thread and therefore needs a separate logging\n    configuration outside of the default ray logging configuration.\n    ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 268567,
        "commit_id": "ff6e4da36addccb06001f7b05b1a9c04ae1d7984",
        "repo": "ansible",
        "path": "lib/ansible/playbook/base.py",
        "file_name": "base.py",
        "fun_name": "set_to_context",
        "commit_message": "fixes to FA inheritance (#78990)\n\nfinalized applies to all field attributes\r\nfix getting parent value\r\nalso remove unused/needed extend/prepend signature\r\nmoar testing",
        "code": "def set_to_context(self, name):\n        \n\n        attribute = self.fattributes[name]\n        if isinstance(attribute, NonInheritableFieldAttribute):\n            # setting to sentinel will trigger 'default/default()' on getter\n            setattr(self, name, Sentinel)\n        else:\n            try:\n                setattr(self, name, self._get_parent_attribute(name, omit=True))\n            except AttributeError:\n                # mostly playcontext as only tasks/handlers/blocks really resolve parent\n                setattr(self, name, Sentinel)\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 158,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 100,
        "n_identifiers": 12,
        "d_id": 79551,
        "documentation": {
            "docstring": " set to parent inherited value or Sentinel as appropriate",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 314785,
        "commit_id": "efbd47c828c6c2e1cd967df2a4cefd2b00c60c25",
        "repo": "core",
        "path": "tests/components/soundtouch/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "device2_info",
        "commit_message": "Rewrite SoundTouch tests to use mocked payloads (#72984)",
        "code": "def device2_info() -> str:\n    \n    return load_fixture(\"soundtouch/device2_info.xml\")\n\n\n@pytest.fixture(scope=\"session\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(scope=\"session\")",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 12,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 12,
        "n_ast_nodes": 42,
        "n_identifiers": 6,
        "d_id": 113386,
        "documentation": {
            "docstring": "Load SoundTouch device 2 info response and return it.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 110209,
        "commit_id": "84def85c848a172afab987298eb402bd39aceeaa",
        "repo": "matplotlib",
        "path": "lib/matplotlib/colors.py",
        "file_name": "colors.py",
        "fun_name": "autoscale",
        "commit_message": "FIX: CenteredNorm use vmin/vmax for halfrange\n\nThis changes CenteredNorm to use vmin and vmax to represent the\nhalfrange rather than storing it separately and needing to update\nthe vmin/vmax in all of the methods.\n\nAdditionally, if you now change vcenter, the halfrange does not\nautomatically update.",
        "code": "def autoscale(self, A):\n        \n        A = np.asanyarray(A)\n        self.halfrange = max(self._vcenter-A.min(),\n                             A.max()-self._vcenter)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 59,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 42,
        "n_ast_nodes": 69,
        "n_identifiers": 9,
        "d_id": 23974,
        "documentation": {
            "docstring": "\n        Set *halfrange* to ``max(abs(A-vcenter))``, then set *vmin* and *vmax*.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 279716,
        "commit_id": "062073cfc4a5fe4c24ed3e326c673951c040982f",
        "repo": "keras",
        "path": "keras/integration_test/parameter_server_training_metric_test.py",
        "file_name": "parameter_server_training_metric_test.py",
        "fun_name": "test_pss_evaluate_metric_batch_counter",
        "commit_message": "Use Model metrics as logs in `fit` and `evaluate` instead of last worker train or test step result\n\nCurrently the model evaluate returns the last scheduled worker metrics. This is troublesome when using distributed workers as the last one could fail. in Parameter Server Strategy, the last worker may finish sooner than earlier scheduled worker resulting in incorrect metrics being returned. So always rely on current model metrics.\n\nPiperOrigin-RevId: 471137058",
        "code": "def test_pss_evaluate_metric_batch_counter(self):\n        \n        strategy = tf.distribute.ParameterServerStrategy(\n            self.cluster_resolver,\n            variable_partitioner=None,\n        )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 51,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 171,
        "n_ast_nodes": 38,
        "n_identifiers": 8,
        "d_id": 83101,
        "documentation": {
            "docstring": "Verify that metric data is complete during evaluate when using\n        ParameterServerStrategy\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 321087,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/eventfilter.py",
        "file_name": "eventfilter.py",
        "fun_name": "_handle_mouse_press",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def _handle_mouse_press(self, e):\n        \n        is_rocker_gesture = (config.val.input.mouse.rocker_gestures and\n                             e.buttons() == Qt.MouseButton.LeftButton | Qt.MouseButton.RightButton)\n\n        if e.button() in [Qt.MouseButton.XButton1, Qt.MouseButton.XButton2] or is_rocker_gesture:\n            self._mousepress_backforward(e)\n            return True\n\n        self._ignore_wheel_event = True\n\n        pos = e.pos()\n        if pos.x() < 0 or pos.y() < 0:\n            log.mouse.warning(\"Ignoring invalid click at {}\".format(pos))\n            return False\n\n        if e.button() != Qt.MouseButton.NoButton:\n            self._tab.elements.find_at_pos(pos, self._mousepress_insertmode_cb)\n\n        return False\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 190,
        "n_words": 51,
        "vocab_size": 40,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 143,
        "n_ast_nodes": 230,
        "n_identifiers": 30,
        "d_id": 117521,
        "documentation": {
            "docstring": "Handle pressing of a mouse button.\n\n        Args:\n            e: The QMouseEvent.\n\n        Return:\n            True if the event should be filtered, False otherwise.\n        ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 149702,
        "commit_id": "b58e811b1486ae62e835cbea3e40cf88128243a0",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/trade_model.py",
        "file_name": "trade_model.py",
        "fun_name": "_calc_open_trade_value",
        "commit_message": "Move trade/order Models to their own class",
        "code": "def _calc_open_trade_value(self) -> float:\n        \n        open_trade = Decimal(self.amount) * Decimal(self.open_rate)\n        fees = open_trade * Decimal(self.fee_open)\n        if self.is_short:\n            return float(open_trade - fees)\n        else:\n            return float(open_trade + fees)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 82,
        "n_words": 25,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 54,
        "n_ast_nodes": 90,
        "n_identifiers": 10,
        "d_id": 34492,
        "documentation": {
            "docstring": "\n        Calculate the open_rate including open_fee.\n        :return: Price in of the open trade incl. Fees\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 83069,
        "commit_id": "ba7ea7cc809ace3e8ecf25311e54d78f62b0d0c8",
        "repo": "zulip",
        "path": "zerver/tests/test_upload.py",
        "file_name": "test_upload.py",
        "fun_name": "test_file_upload_authed",
        "commit_message": "test_classes: Extract assert_streaming_content helper.\n\nThis also fixes a warning from\nRealmExportTest.test_endpoint_local_uploads: “ResourceWarning:\nunclosed file <_io.BufferedReader\nname='/srv/zulip/var/…/test-export.tar.gz'>”.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def test_file_upload_authed(self) -> None:\n        \n        self.login(\"hamlet\")\n        fp = StringIO(\"zulip!\")\n        fp.name = \"zulip.txt\"\n\n        result = self.client_post(\"/json/user_uploads\", {\"file\": fp})\n        self.assert_json_success(result)\n        self.assertIn(\"uri\", result.json())\n        uri = result.json()[\"uri\"]\n        base = \"/user_uploads/\"\n        self.assertEqual(base, uri[: len(base)])\n\n        # In the future, local file requests will follow the same style as S3\n        # requests; they will be first authenthicated and redirected\n        self.assert_streaming_content(self.client_get(uri), b\"zulip!\")\n\n        # check if DB has attachment marked as unclaimed\n        entry = Attachment.objects.get(file_name=\"zulip.txt\")\n        self.assertEqual(entry.is_claimed(), False)\n\n        self.subscribe(self.example_user(\"hamlet\"), \"Denmark\")\n        body = \"First message ...[zulip.txt](http://localhost:9991\" + uri + \")\"\n        self.send_stream_message(self.example_user(\"hamlet\"), \"Denmark\", body, \"test\")\n\n        # Now try the endpoint that's supposed to return a temporary URL for access\n        # to the file.\n        result = self.client_get(\"/json\" + uri)\n        self.assert_json_success(result)\n        data = result.json()\n        url_only_url = data[\"url\"]\n        # Ensure this is different from the original uri:\n        self.assertNotEqual(url_only_url, uri)\n        self.assertIn(\"user_uploads/temporary/\", url_only_url)\n        self.assertTrue(url_only_url.endswith(\"zulip.txt\"))\n        # The generated URL has a token authorizing the requestor to access the file\n        # without being logged in.\n        self.logout()\n        self.assert_streaming_content(self.client_get(url_only_url), b\"zulip!\")\n        # The original uri shouldn't work when logged out:\n        result = self.client_get(uri)\n        self.assertEqual(result.status_code, 401)\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 414,
        "n_words": 162,
        "vocab_size": 117,
        "complexity": 1,
        "nloc": 32,
        "token_counts": 253,
        "n_ast_nodes": 450,
        "n_identifiers": 34,
        "d_id": 17592,
        "documentation": {
            "docstring": "\n        A call to /json/user_uploads should return a uri and actually create an\n        entry in the database. This entry will be marked unclaimed till a message\n        refers it.\n        ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 61366,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/git.py",
        "file_name": "git.py",
        "fun_name": "get_current_branch",
        "commit_message": "upd; format",
        "code": "def get_current_branch(cls, location):\n        # type: (str) -> Optional[str]\n        \n        # git-symbolic-ref exits with empty stdout if \"HEAD\" is a detached\n        # HEAD rather than a symbolic ref.  In addition, the -q causes the\n        # command to exit with status code 1 instead of 128 in this case\n        # and to suppress the message to stderr.\n        args = ['symbolic-ref', '-q', 'HEAD']\n        output = cls.run_command(\n            args,\n            extra_ok_returncodes=(1, ),\n            show_stdout=False,\n            stdout_only=True,\n            cwd=location,\n        )\n        ref = output.strip()\n\n        if ref.startswith('refs/heads/'):\n            return ref[len('refs/heads/'):]\n\n        return None\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 229,
        "n_words": 78,
        "vocab_size": 64,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 71,
        "n_ast_nodes": 122,
        "n_identifiers": 14,
        "d_id": 12532,
        "documentation": {
            "docstring": "\n        Return the current branch, or None if HEAD isn't at a branch\n        (e.g. detached HEAD).\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 206326,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/templatetags/l10n.py",
        "file_name": "l10n.py",
        "fun_name": "localize_tag",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def localize_tag(parser, token):\n    \n    use_l10n = None\n    bits = list(token.split_contents())\n    if len(bits) == 1:\n        use_l10n = True\n    elif len(bits) > 2 or bits[1] not in (\"on\", \"off\"):\n        raise TemplateSyntaxError(\"%r argument should be 'on' or 'off'\" % bits[0])\n    else:\n        use_l10n = bits[1] == \"on\"\n    nodelist = parser.parse((\"endlocalize\",))\n    parser.delete_first_token()\n    return LocalizeNode(nodelist, use_l10n)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 97,
        "n_words": 49,
        "vocab_size": 39,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 95,
        "n_ast_nodes": 161,
        "n_identifiers": 13,
        "d_id": 51487,
        "documentation": {
            "docstring": "\n    Force or prevents localization of values, regardless of the value of\n    `settings.USE_L10N`.\n\n    Sample usage::\n\n        {% localize off %}\n            var pi = {{ 3.1415 }};\n        {% endlocalize %}\n    ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 182967,
        "commit_id": "3b40eb828b5217fd023c07694a02f148664b9588",
        "repo": "textual",
        "path": "src/textual/devtools/redirect_output.py",
        "file_name": "redirect_output.py",
        "fun_name": "flush",
        "commit_message": "Redirecting stdout to both devtools and logfile",
        "code": "def flush(self) -> None:\n        \n        self._write_to_log_file()\n        self._write_to_devtools()\n        self._buffer.clear()\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 35,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 25,
        "n_ast_nodes": 46,
        "n_identifiers": 6,
        "d_id": 44020,
        "documentation": {
            "docstring": "Flush the buffer. This will send all buffered log messages to\n        the devtools server and the log file. In the case of the devtools,\n        where possible, log messages will be batched and sent as one.\n        ",
            "n_words": 35,
            "vocab_size": 26,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 130122,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/_private/function_manager.py",
        "file_name": "function_manager.py",
        "fun_name": "get_execution_info",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def get_execution_info(self, job_id, function_descriptor):\n        \n        function_id = function_descriptor.function_id\n        # If the function has already been loaded,\n        # There's no need to load again\n        if function_id in self._function_execution_info:\n            return self._function_execution_info[function_id]\n        if self._worker.load_code_from_local:\n            # Load function from local code.\n            if not function_descriptor.is_actor_method():\n                # If the function is not able to be loaded,\n                # try to load it from GCS,\n                # even if load_code_from_local is set True\n                if self._load_function_from_local(function_descriptor) is True:\n                    return self._function_execution_info[function_id]\n        # Load function from GCS.\n        # Wait until the function to be executed has actually been\n        # registered on this worker. We will push warnings to the user if\n        # we spend too long in this loop.\n        # The driver function may not be found in sys.path. Try to load\n        # the function from GCS.\n        with profiling.profile(\"wait_for_function\"):\n            self._wait_for_function(function_descriptor, job_id)\n        try:\n            function_id = function_descriptor.function_id\n            info = self._function_execution_info[function_id]\n        except KeyError as e:\n            message = (\n                \"Error occurs in get_execution_info: \"\n                \"job_id: %s, function_descriptor: %s. Message: %s\"\n                % (job_id, function_descriptor, e)\n            )\n            raise KeyError(message)\n        return info\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 497,
        "n_words": 162,
        "vocab_size": 99,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 118,
        "n_ast_nodes": 206,
        "n_identifiers": 17,
        "d_id": 29113,
        "documentation": {
            "docstring": "Get the FunctionExecutionInfo of a remote function.\n        Args:\n            job_id: ID of the job that the function belongs to.\n            function_descriptor: The FunctionDescriptor of the function to get.\n        Returns:\n            A FunctionExecutionInfo object.\n        ",
            "n_words": 30,
            "vocab_size": 23,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 43885,
        "commit_id": "dba00ce6a32b7f50153887c6974f62985ca8023f",
        "repo": "airflow",
        "path": "airflow/jobs/local_task_job.py",
        "file_name": "local_task_job.py",
        "fun_name": "_enable_task_listeners",
        "commit_message": "Add Listener Plugin API that tracks TaskInstance state changes (#20443)\n\nThis adds new Plugin API - \"listeners\". It enables plugin authors to write\r\n[pluggy hook implementation][1] that will be called on certain formalized extension\r\npoints. To differentiate between current Airflow extension points, like\r\nplugins, and current Airflow hooks, implementations of those hooks are called\r\nlisteners.\r\n\r\nThe API is ment to be called across all dags, and all operators - in contrast\r\nto current on_success_callback, pre_execute and related family which are meant\r\nto provide callbacks for particular dag authors, or operator creators.\r\n\r\npluggy mechanism enables us to execute multiple, or none, listeners that\r\nimplement particular extension point, so that users can use multiple listeners\r\nseamlessly.\r\n\r\nIn this PR, three such extension points are added. When TaskInstance's state is\r\nchanged to RUNNING, on_task_instance_running hook is called. On change\r\ntoSUCCESS on_task_instance_success is called, similarly on FAILED\r\non_task_instance_failed is called.\r\n\r\nActual notification mechanism is be implemented using [SQLAlchemy’s events\r\nmechanism][2]. This ensures that plugins will get every change of state,\r\nregardless of where in the codebase it happened, and not require manual\r\nannotation of TI state changes across the codebase.\r\n\r\nTo make sure that this change is not affecting performance, running this\r\nmechanism on scheduler is disabled by default. The SQLAlchemy event mechanism\r\nis also not affected by default - the event listener is only added if we have\r\nany plugin which actually provides any listener.\r\n\r\n[1]: https://pluggy.readthedocs.io/en/stable/\r\n[2]: https://docs.sqlalchemy.org/en/13/orm/session_events.html#after-flush\r\n\r\nSigned-off-by: Maciej Obuchowski <obuchowski.maciej@gmail.com>",
        "code": "def _enable_task_listeners():\n        \n        if get_listener_manager().has_listeners:\n            register_task_instance_state_events()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 30,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 15,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 8086,
        "documentation": {
            "docstring": "\n        Check if we have any registered listeners, then register sqlalchemy hooks for\n        TI state change if we do.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 286564,
        "commit_id": "59d8b36bb0467a1a99513b10e8b8471afaa56fd6",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/due_diligence/binance_model.py",
        "file_name": "binance_model.py",
        "fun_name": "get_binance_available_quotes_for_each_coin",
        "commit_message": "[IMPROVE] Fix Docstring formatting/Fix missing, incomplete type hints (#3412)\n\n* Fixes\r\n\r\n* Update stocks_helper.py\r\n\r\n* update git-actions set-output to new format\r\n\r\n* Update stocks_helper.py\r\n\r\n* Update terminal_helper.py\r\n\r\n* removed LineAnnotateDrawer from qa_view\r\n\r\n* lint\r\n\r\n* few changes\r\n\r\n* updates\r\n\r\n* sdk auto gen modules done\r\n\r\n* Update stocks_helper.py\r\n\r\n* updates to changed imports, and remove first sdk_modules\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* pylint\r\n\r\n* revert stocks_helper\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* full auto generation, added sdk.py/controllers creation\r\n\r\n* missed enable forecasting\r\n\r\n* added running black in subprocess after sdk files generation completes\r\n\r\n* removed deleted sdk_arg_logger\r\n\r\n* comment out tests\r\n\r\n* property doc fix\r\n\r\n* clean up\r\n\r\n* Update generate_sdk.py\r\n\r\n* make trailmap classes useable for doc generation\r\n\r\n* Update generate_sdk.py\r\n\r\n* added lineon to trailmap class for linking to func in markdown\r\n\r\n* changed lineon to dict\r\n\r\n* added full_path to trailmap for linking in docs\r\n\r\n* updated portfolio\r\n\r\n* feat: initial files\r\n\r\n* feat: added meta head\r\n\r\n* feat: added funcdef\r\n\r\n* added func_def to trailmap attributes for markdown in docs, added missing type hints to covid functions\r\n\r\n* feat: added view and merged with jaun\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* init\r\n\r\n* fix returns\r\n\r\n* fix: random stuff\r\n\r\n* fix: random\r\n\r\n* fixed encoding issue on windows\r\n\r\n* fix: generate tabs\r\n\r\n* update\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Create .pydocstyle.ini\r\n\r\n* added type hint classes for views\r\n\r\n* fixes\r\n\r\n* alt, ba\r\n\r\n* alt-economy\r\n\r\n* Update finviz_compare_model.py\r\n\r\n* fixs\r\n\r\n* Update substack_model.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* last of my section\r\n\r\n* porfolio\r\n\r\n* po\r\n\r\n* Update optimizer_model.py\r\n\r\n* fixing more things\r\n\r\n* few more\r\n\r\n* keys done\r\n\r\n* update\r\n\r\n* fixes\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* mypy forecast fix\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* fixes\r\n\r\n* forecast fixes\r\n\r\n* one more fix\r\n\r\n* Update coinbase_model.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>\r\nCo-authored-by: jose-donato <zmcdonato@gmail.com>\r\nCo-authored-by: andrewkenreich <andrew.kenreich@gmail.com>",
        "code": "def get_binance_available_quotes_for_each_coin() -> dict:\n    \n    trading_pairs = _get_trading_pairs()\n    results = defaultdict(list)\n    for pair in trading_pairs:\n        results[pair[\"baseAsset\"]].append(pair[\"quoteAsset\"])\n    return results\n\n\n@log_start_end(log=logger)\n@check_api_key([\"API_BINANCE_KEY\", \"API_BINANCE_SECRET\"])",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)\n@check_api_key([\"API_BINANCE_KEY\", \"API_BINANCE_SECRET\"])",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 40,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 40,
        "n_ast_nodes": 99,
        "n_identifiers": 13,
        "d_id": 85880,
        "documentation": {
            "docstring": "Helper methods that for every coin available on Binance add all quote assets. [Source: Binance]\n\n    Returns\n    -------\n    dict\n        All quote assets for given coin\n        {'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...]\n\n    ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 156098,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "nunique_approx",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def nunique_approx(self, split_every=None):\n        \n        from dask.dataframe import hyperloglog  # here to avoid circular import issues\n\n        return aca(\n            [self],\n            chunk=hyperloglog.compute_hll_array,\n            combine=hyperloglog.reduce_state,\n            aggregate=hyperloglog.estimate_count,\n            split_every=split_every,\n            b=16,\n            meta=float,\n        )\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 130,
        "n_words": 24,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 54,
        "n_ast_nodes": 79,
        "n_identifiers": 16,
        "d_id": 36555,
        "documentation": {
            "docstring": "Approximate number of unique rows.\n\n        This method uses the HyperLogLog algorithm for cardinality\n        estimation to compute the approximate number of unique rows.\n        The approximate error is 0.406%.\n\n        Parameters\n        ----------\n        split_every : int, optional\n            Group partitions into groups of this size while performing a\n            tree-reduction. If set to False, no tree-reduction will be used.\n            Default is 8.\n\n        Returns\n        -------\n        a float representing the approximate number of elements\n        ",
            "n_words": 66,
            "vocab_size": 52,
            "n_whitespaces": 169,
            "language": "en"
        }
    },
    {
        "id": 222412,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/datetime.py",
        "file_name": "datetime.py",
        "fun_name": "fromisoformat",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def fromisoformat(cls, date_string):\n        \n        if not isinstance(date_string, str):\n            raise TypeError('fromisoformat: argument must be str')\n\n        try:\n            assert len(date_string) == 10\n            return cls(*_parse_isoformat_date(date_string))\n        except Exception:\n            raise ValueError(f'Invalid isoformat string: {date_string!r}')\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 99,
        "n_words": 27,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 49,
        "n_ast_nodes": 89,
        "n_identifiers": 10,
        "d_id": 56569,
        "documentation": {
            "docstring": "Construct a date from the output of date.isoformat().",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 219940,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_strptime.py",
        "file_name": "_strptime.py",
        "fun_name": "__seqToRE",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def __seqToRE(self, to_convert, directive):\n        \n        to_convert = sorted(to_convert, key=len, reverse=True)\n        for value in to_convert:\n            if value != '':\n                break\n        else:\n            return ''\n        regex = '|'.join(re_escape(stuff) for stuff in to_convert)\n        regex = '(?P<%s>%s' % (directive, regex)\n        return '%s)' % regex\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 124,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 67,
        "n_ast_nodes": 113,
        "n_identifiers": 13,
        "d_id": 55908,
        "documentation": {
            "docstring": "Convert a list to a regex string for matching a directive.\n\n        Want possible matching values to be from longest to shortest.  This\n        prevents the possibility of a match occurring for a value that also\n        a substring of a larger value that should have matched (e.g., 'abc'\n        matching when 'abcdef' should have been the match).\n\n        ",
            "n_words": 54,
            "vocab_size": 37,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 127694,
        "commit_id": "8ffe435173aee0f313f786e7301d05f608b6d5be",
        "repo": "ray",
        "path": "python/ray/runtime_context.py",
        "file_name": "runtime_context.py",
        "fun_name": "node_id",
        "commit_message": "[core/docs] Update worker docstring (#28495)\n\nCo-authored-by: Philipp Moritz <pcmoritz@gmail.com>",
        "code": "def node_id(self):\n        \n        node_id = self.worker.current_node_id\n        assert not node_id.is_nil()\n        return node_id\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 38,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 22,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 28506,
        "documentation": {
            "docstring": "Get current node ID for this worker or driver.\n\n        Node ID is the id of a node that your driver, task, or actor runs.\n\n        Returns:\n            A node id for this worker or driver.\n        ",
            "n_words": 33,
            "vocab_size": 23,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 289015,
        "commit_id": "8dc3ff72c6ff6f9591151759465ac5d8a20e2b2f",
        "repo": "core",
        "path": "tests/test_config.py",
        "file_name": "test_config.py",
        "fun_name": "test_loading_configuration_from_packages",
        "commit_message": "Cleanup config deprecation warning (#80251)",
        "code": "async def test_loading_configuration_from_packages(hass):\n    \n    await config_util.async_process_ha_core_config(\n        hass,\n        {\n            \"latitude\": 39,\n            \"longitude\": -1,\n            \"elevation\": 500,\n            \"name\": \"Huis\",\n            CONF_UNIT_SYSTEM: CONF_UNIT_SYSTEM_METRIC,\n            \"time_zone\": \"Europe/Madrid\",\n            \"external_url\": \"https://www.example.com\",\n            \"internal_url\": \"http://example.local\",\n            \"packages\": {\n                \"package_1\": {\"wake_on_lan\": None},\n                \"package_2\": {\n                    \"light\": {\"platform\": \"hue\"},\n                    \"media_extractor\": None,\n                    \"sun\": None,\n                },\n            },\n        },\n    )\n\n    # Empty packages not allowed\n    with pytest.raises(MultipleInvalid):\n        await config_util.async_process_ha_core_config(\n            hass,\n            {\n                \"latitude\": 39,\n                \"longitude\": -1,\n                \"elevation\": 500,\n                \"name\": \"Huis\",\n                CONF_UNIT_SYSTEM: CONF_UNIT_SYSTEM_METRIC,\n                \"time_zone\": \"Europe/Madrid\",\n                \"packages\": {\"empty_package\": None},\n            },\n        )\n\n\n@patch(\"homeassistant.helpers.check_config.async_check_ha_config_file\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@patch(\"homeassistant.helpers.check_config.async_check_ha_config_file\")",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 469,
        "n_words": 70,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 35,
        "token_counts": 136,
        "n_ast_nodes": 264,
        "n_identifiers": 10,
        "d_id": 88164,
        "documentation": {
            "docstring": "Test loading packages config onto hass object config.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 195124,
        "commit_id": "73a395fd457d5f56463f4f72e5b65919db3f1f96",
        "repo": "ParlAI",
        "path": "tests/nightly/gpu/test_torchscript.py",
        "file_name": "test_torchscript.py",
        "fun_name": "test_torchscript_bart_agent",
        "commit_message": "Add TorchScriptable transformer classifier and subword BPE tokenizer (#4566)\n\n* Add torchscript classes for Transformer classifier and subword BPE tokenizer\r\n\r\n* Add unit tests\r\n\r\n* Remove debugging code\r\n\r\n* Resolve comments\r\n\r\n* Rerun autoformat.sh\r\n\r\n* Update parlai/torchscript/tokenizer.py\r\n\r\nCo-authored-by: Eric Smith <EricMichaelSmith@users.noreply.github.com>\r\n\r\nCo-authored-by: Eric Smith <EricMichaelSmith@users.noreply.github.com>",
        "code": "def test_torchscript_bart_agent(self):\n        \n\n        from parlai.scripts.torchscript import TorchScript\n\n        test_phrase = \"Don't have a cow, man!\"  # From test_bart.py\n\n        with testing_utils.tempdir() as tmpdir:\n\n            scripted_model_file = os.path.join(tmpdir, 'scripted_model.pt')\n\n            # Export the BART model\n            export_opt = TorchScript.setup_args().parse_kwargs(\n                model='bart', scripted_model_file=scripted_model_file, no_cuda=True\n            )\n            TorchScript(export_opt).run()\n\n            # Test the scripted BART model\n            scripted_opt = ParlaiParser(True, True).parse_kwargs(\n                model='parlai.torchscript.agents:TorchScriptAgent',\n                model_file=scripted_model_file,\n            )\n            bart = create_agent(scripted_opt)\n            bart.observe({'text': test_phrase, 'episode_done': True})\n            act = bart.act()\n            self.assertEqual(act['text'], test_phrase)\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 268,
        "n_words": 62,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 126,
        "n_ast_nodes": 217,
        "n_identifiers": 28,
        "d_id": 47209,
        "documentation": {
            "docstring": "\n        Test exporting a BART model to TorchScript and then testing it on sample data.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 42070,
        "commit_id": "34662f4be5c364e7518f9c1118c9b362038ee5dd",
        "repo": "seaborn",
        "path": "seaborn/rcmod.py",
        "file_name": "rcmod.py",
        "fun_name": "set_context",
        "commit_message": "Convert docs to pydata-sphinx-theme and add new material (#2842)\n\n* Do basic conversion of site to pydata_sphinx_theme\r\n\r\n* Remove some pae structure customizations we no longer need\r\n\r\n* Add some custom CSS\r\n\r\n* Tweak a few more colors\r\n\r\n* Remove vestigial div closing tag\r\n\r\n* Reorganize release notes into hierarchical pages\r\n\r\n* Rebuild full docs and fix some resulting issues\r\n\r\n* Make release note doc refs absolute\r\n\r\n* Convert homepage to use sphinx-design instead of hand-crafted html\r\n\r\n* Remove original custom css\r\n\r\n* Simplify header and put archive switcher in footer\r\n\r\n* Streamline API docs for objects\r\n\r\n* Play around with templates to fix shrinking content (not perfect yet)\r\n\r\n* Improve use of horizontal space without sidebars\r\n\r\n* Various tweaks\r\n\r\n* Convert tutorial homepage source to native sphinx-design directives\r\n\r\n* Move intro page into tutorial\r\n\r\n* More tweaks\r\n\r\n* Tweak theme colors and footer\r\n\r\n* Remove reference to navbar version\r\n\r\n* Note that error bar tutorial demonstrates new features as of v0.12\r\n\r\n* Update layout customization for new theme features\r\n\r\n* Various layout and CSS tweaks\r\n\r\n* Narrow support guidance to StackOverflow\r\n\r\n* Run all notebooks\r\n\r\n* Adapt to new dropdown navbar in pydata theme\r\n\r\n* Separate tutorial source and outputs\r\n\r\n* Separate dostring source and outputs\r\n\r\n* Add scale API template\r\n\r\n* Update API docs\r\n\r\n* Fix requirements\r\n\r\n* Add new objects\r\n\r\n* Point doc requirements at v0.10 RC for theme",
        "code": "def set_context(context=None, font_scale=1, rc=None):\n    \n    context_object = plotting_context(context, font_scale, rc)\n    mpl.rcParams.update(context_object)\n\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 53,
        "n_identifiers": 9,
        "d_id": 7474,
        "documentation": {
            "docstring": "\n    Set the parameters that control the scaling of plot elements.\n\n    This affects things like the size of the labels, lines, and other elements\n    of the plot, but not the overall style. This is accomplished using the\n    matplotlib rcParams system.\n\n    The base context is \"notebook\", and the other contexts are \"paper\", \"talk\",\n    and \"poster\", which are version of the notebook parameters scaled by different\n    values. Font elements can also be scaled independently of (but relative to)\n    the other values.\n\n    See :func:`plotting_context` to get the parameter values.\n\n    Parameters\n    ----------\n    context : dict, or one of {paper, notebook, talk, poster}\n        A dictionary of parameters or the name of a preconfigured set.\n    font_scale : float, optional\n        Separate scaling factor to independently scale the size of the\n        font elements.\n    rc : dict, optional\n        Parameter mappings to override the values in the preset seaborn\n        context dictionaries. This only updates parameters that are\n        considered part of the context definition.\n\n    Examples\n    --------\n\n    .. include:: ../docstrings/set_context.rst\n\n    ",
            "n_words": 157,
            "vocab_size": 101,
            "n_whitespaces": 254,
            "language": "en"
        }
    },
    {
        "id": 100521,
        "commit_id": "8ab085fae0193bb507fd5ad582668d19d56bea3d",
        "repo": "faceswap",
        "path": "lib/gui/popup_configure.py",
        "file_name": "popup_configure.py",
        "fun_name": "_process_sections",
        "commit_message": "bugfix: gui - settings popup. Always reload config",
        "code": "def _process_sections(cls, tree, sections, category, is_open):\n        \n        seen = set()\n        for section in sections:\n            if section[-1] == \"global\":  # Global categories get escalated to parent\n                continue\n            sect = section[0]\n            section_id = f\"{category}|{sect}\"\n            if sect not in seen:\n                seen.add(sect)\n                text = sect.replace(\"_\", \" \").title()\n                tree.insert(category, \"end\", section_id, text=text, open=is_open, tags=\"section\")\n            if len(section) == 2:\n                opt = section[-1]\n                opt_id = f\"{section_id}|{opt}\"\n                opt_text = opt.replace(\"_\", \" \").title()\n                tree.insert(section_id, \"end\", opt_id, text=opt_text, open=is_open, tags=\"option\")\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 266,
        "n_words": 69,
        "vocab_size": 53,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 147,
        "n_ast_nodes": 256,
        "n_identifiers": 22,
        "d_id": 19985,
        "documentation": {
            "docstring": " Process the sections of a category's configuration.\n\n        Creates a category's sections, then the sub options for that category\n\n        Parameters\n        ----------\n        tree: :class:`tkinter.ttk.TreeView`\n            The tree view to insert sections into\n        sections: list\n            The sections to insert into the Tree View\n        category: str\n            The category node that these sections sit in\n        is_open: bool\n            ``True`` if the node should be created in \"open\" mode. ``False`` if it should be\n            closed.\n        ",
            "n_words": 67,
            "vocab_size": 47,
            "n_whitespaces": 179,
            "language": "en"
        }
    },
    {
        "id": 37626,
        "commit_id": "1ac698744c4dbdf1495d303246d08ffacdf4f5b8",
        "repo": "transformers",
        "path": "src/transformers/models/yolos/feature_extraction_yolos.py",
        "file_name": "feature_extraction_yolos.py",
        "fun_name": "corners_to_center_format",
        "commit_message": "Add YOLOS (#16848)\n\n* First draft\r\n\r\n* Add YolosForObjectDetection\r\n\r\n* Make forward pass work\r\n\r\n* Add mid position embeddings\r\n\r\n* Add interpolation of position encodings\r\n\r\n* Add expected values\r\n\r\n* Add YOLOS to tests\r\n\r\n* Add integration test\r\n\r\n* Support tiny model as well\r\n\r\n* Support all models in conversion script\r\n\r\n* Remove mid_pe_size attribute\r\n\r\n* Make more tests pass\r\n\r\n* Add model to README and fix config\r\n\r\n* Add copied from statements\r\n\r\n* Rename base_model_prefix to vit\r\n\r\n* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP\r\n\r\n* Apply suggestions from code review\r\n\r\n* Apply more suggestions from code review\r\n\r\n* Convert remaining checkpoints\r\n\r\n* Improve docstrings\r\n\r\n* Add YolosFeatureExtractor\r\n\r\n* Add feature extractor to docs\r\n\r\n* Add corresponding tests\r\n\r\n* Fix style\r\n\r\n* Fix docs\r\n\r\n* Apply suggestion from code review\r\n\r\n* Fix bad rebase\r\n\r\n* Fix some more bad rebase\r\n\r\n* Fix missing character\r\n\r\n* Improve docs and variable names\r\n\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def corners_to_center_format(x):\n    \n    x_transposed = x.T\n    x0, y0, x1, y1 = x_transposed[0], x_transposed[1], x_transposed[2], x_transposed[3]\n    b = [(x0 + x1) / 2, (y0 + y1) / 2, (x1 - x0), (y1 - y0)]\n    return np.stack(b, axis=-1)\n\n\n# Copied from transformers.models.detr.feature_extraction_detr.masks_to_boxes",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 53,
        "n_words": 39,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 81,
        "n_ast_nodes": 119,
        "n_identifiers": 12,
        "d_id": 6837,
        "documentation": {
            "docstring": "\n    Converts a NumPy array of bounding boxes of shape (number of bounding boxes, 4) of corners format (x_0, y_0, x_1,\n    y_1) to center format (center_x, center_y, width, height).\n    ",
            "n_words": 28,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 65836,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/e_commerce/variant_selector/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_attributes_and_values",
        "commit_message": "style: format code with black",
        "code": "def get_attributes_and_values(item_code):\n\t\n\titem_cache = ItemVariantsCacheManager(item_code)\n\titem_variants_data = item_cache.get_item_variants_data()\n\n\tattributes = get_item_attributes(item_code)\n\tattribute_list = [a.attribute for a in attributes]\n\n\tvalid_options = {}\n\tfor item_code, attribute, attribute_value in item_variants_data:\n\t\tif attribute in attribute_list:\n\t\t\tvalid_options.setdefault(attribute, set()).add(attribute_value)\n\n\titem_attribute_values = frappe.db.get_all(\n\t\t\"Item Attribute Value\", [\"parent\", \"attribute_value\", \"idx\"], order_by=\"parent asc, idx asc\"\n\t)\n\tordered_attribute_value_map = frappe._dict()\n\tfor iv in item_attribute_values:\n\t\tordered_attribute_value_map.setdefault(iv.parent, []).append(iv.attribute_value)\n\n\t# build attribute values in idx order\n\tfor attr in attributes:\n\t\tvalid_attribute_values = valid_options.get(attr.attribute, [])\n\t\tordered_values = ordered_attribute_value_map.get(attr.attribute, [])\n\t\tattr[\"values\"] = [v for v in ordered_values if v in valid_attribute_values]\n\n\treturn attributes\n\n\n@frappe.whitelist(allow_guest=True)",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist(allow_guest=True)",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 67,
        "n_words": 89,
        "vocab_size": 62,
        "complexity": 8,
        "nloc": 20,
        "token_counts": 170,
        "n_ast_nodes": 290,
        "n_identifiers": 33,
        "d_id": 14028,
        "documentation": {
            "docstring": "Build a list of attributes and their possible values.\n\tThis will ignore the values upon selection of which there cannot exist one item.\n\t",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 262100,
        "commit_id": "ea965a5683c56a39570b4cc91e86cd2bb9799308",
        "repo": "TTS",
        "path": "TTS/tts/models/vits.py",
        "file_name": "vits.py",
        "fun_name": "test_run",
        "commit_message": "Update VITS for the new API",
        "code": "def test_run(self) -> Tuple[Dict, Dict]:\n        \n        print(\" | > Synthesizing test sentences.\")\n        test_audios = {}\n        test_figures = {}\n        test_sentences = self.config.test_sentences\n        for idx, s_info in enumerate(test_sentences):\n            try:\n                aux_inputs = self.get_aux_input_from_test_sentences(s_info)\n                wav, alignment, _, _ = synthesis(\n                    self,\n                    aux_inputs[\"text\"],\n                    self.config,\n                    \"cuda\" in str(next(self.parameters()).device),\n                    ap,\n                    speaker_id=aux_inputs[\"speaker_id\"],\n                    d_vector=aux_inputs[\"d_vector\"],\n                    style_wav=aux_inputs[\"style_wav\"],\n                    language_id=aux_inputs[\"language_id\"],\n                    language_name=aux_inputs[\"language_name\"],\n                    enable_eos_bos_chars=self.config.enable_eos_bos_chars,\n                    use_griffin_lim=True,\n                    do_trim_silence=False,\n                ).values()\n                test_audios[\"{}-audio\".format(idx)] = wav\n                test_figures[\"{}-alignment\".format(idx)] = plot_alignment(alignment.T, output_fig=False)\n            except:  # pylint: disable=bare-except\n                print(\" !! Error creating Test Sentence -\", idx)\n        return test_figures, test_audios\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 482,
        "n_words": 73,
        "vocab_size": 63,
        "complexity": 3,
        "nloc": 35,
        "token_counts": 190,
        "n_ast_nodes": 304,
        "n_identifiers": 36,
        "d_id": 77125,
        "documentation": {
            "docstring": "Generic test run for `tts` models used by `Trainer`.\n\n        You can override this for a different behaviour.\n\n        Returns:\n            Tuple[Dict, Dict]: Test figures and audios to be projected to Tensorboard.\n        ",
            "n_words": 29,
            "vocab_size": 27,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 101280,
        "commit_id": "2beceffad9b15c1fd78f06b9b272563321c5a41e",
        "repo": "faceswap",
        "path": "lib/image.py",
        "file_name": "image.py",
        "fun_name": "read_image_batch",
        "commit_message": "Data Augmentation update (#1263)\n\n- lib.detected_face\r\n    - Subclass Masks for Landmark based masks\r\n    - Add training mask propery + methods to DetectedFace\r\n  - lib.training_training\r\n    - subclass TrainingDataGenerator for training and preview data\r\n    - Split cache into own module\r\n    - Reduce thread count to 1 to prevent image corruption + data re-use\r\n    - Process on largest model input/output size rather than stored image size\r\n    - Size and crop masks during caching stage\r\n    - Implement ring buffer for data flow\r\n    - Fix preview reload bug\r\n  - augmentation\r\n    - typing\r\n    - switch color aug order\r\n    - better initialization\r\n    - Fix warp + landmark warp to correctly apply at different image scales\r\n    - Slightly improved warp caching\r\n    - Don't store whether image is_preview. Handle all data as training images implicitly\r\n  - plugins.trainer: Typing and fixes to work with trainingdata refactor",
        "code": "def read_image_batch(filenames, with_metadata=False):\n    \n    logger.trace(\"Requested batch: '%s'\", filenames)\n    batch = [None for _ in range(len(filenames))]\n    if with_metadata:\n        meta = [None for _ in range(len(filenames))]\n\n    with futures.ThreadPoolExecutor() as executor:\n        images = {executor.submit(read_image, filename,\n                                  raise_error=True, with_metadata=with_metadata): idx\n                  for idx, filename in enumerate(filenames)}\n        for future in futures.as_completed(images):\n            ret_idx = images[future]\n            if with_metadata:\n                batch[ret_idx], meta[ret_idx] = future.result()\n            else:\n                batch[ret_idx] = future.result()\n\n    batch = np.array(batch)\n    retval = (batch, meta) if with_metadata else batch\n    logger.trace(\"Returning images: (filenames: %s, batch shape: %s, with_metadata: %s)\",\n                 filenames, batch.shape, with_metadata)\n    return retval\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 258,
        "n_words": 81,
        "vocab_size": 55,
        "complexity": 8,
        "nloc": 20,
        "token_counts": 172,
        "n_ast_nodes": 269,
        "n_identifiers": 28,
        "d_id": 20699,
        "documentation": {
            "docstring": " Load a batch of images from the given file locations.\n\n    Leverages multi-threading to load multiple images from disk at the same time leading to vastly\n    reduced image read times.\n\n    Parameters\n    ----------\n    filenames: list\n        A list of ``str`` full paths to the images to be loaded.\n    with_metadata: bool, optional\n        Only returns a value if the images loaded are extracted Faceswap faces. If ``True`` then\n        returns the Faceswap metadata stored with in a Face images .png exif header.\n        Default: ``False``\n\n    Returns\n    -------\n    numpy.ndarray\n        The batch of images in `BGR` channel order returned in the order of :attr:`filenames`\n\n    Notes\n    -----\n    As the images are compiled into a batch, they must be all of the same dimensions.\n\n    Example\n    -------\n    >>> image_filenames = [\"/path/to/image_1.png\", \"/path/to/image_2.png\", \"/path/to/image_3.png\"]\n    >>> images = read_image_batch(image_filenames)\n    ",
            "n_words": 125,
            "vocab_size": 87,
            "n_whitespaces": 212,
            "language": "en"
        }
    },
    {
        "id": 77545,
        "commit_id": "39f7886a6f8ee98db7e73ce33d94c06139f35bd8",
        "repo": "wagtail",
        "path": "wagtail/admin/widgets/chooser.py",
        "file_name": "chooser.py",
        "fun_name": "get_instance",
        "commit_message": "Split out common logic from get_value_data",
        "code": "def get_instance(self, value):\n        \n        if value is None:\n            return None\n        elif isinstance(value, self.model):\n            return value\n        else:  # assume instance ID\n            return self.model.objects.get(pk=value)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 83,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 69,
        "n_identifiers": 8,
        "d_id": 16671,
        "documentation": {
            "docstring": "\n        Given a value passed to this widget for rendering (which may be None, an id, or a model\n        instance), return a model instance or None\n        ",
            "n_words": 25,
            "vocab_size": 21,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 207623,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_change_view_save_as_new",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_change_view_save_as_new(self):\n        \n        change_dict_save_as_new = {\n            \"_saveasnew\": \"Save as new\",\n            \"title\": \"Ikke fordømt\",\n            \"content\": \"<p>edited article</p>\",\n            \"date_0\": \"2008-03-18\",\n            \"date_1\": \"10:54:39\",\n            \"section\": self.s1.pk,\n        }\n        article_change_url = reverse(\n            \"admin:admin_views_article_change\", args=(self.a1.pk,)\n        )\n\n        # Add user can perform \"Save as new\".\n        article_count = Article.objects.count()\n        self.client.force_login(self.adduser)\n        post = self.client.post(article_change_url, change_dict_save_as_new)\n        self.assertRedirects(post, self.index_url)\n        self.assertEqual(Article.objects.count(), article_count + 1)\n        self.client.logout()\n\n        # Change user cannot perform \"Save as new\" (no 'add' permission).\n        article_count = Article.objects.count()\n        self.client.force_login(self.changeuser)\n        post = self.client.post(article_change_url, change_dict_save_as_new)\n        self.assertEqual(post.status_code, 403)\n        self.assertEqual(Article.objects.count(), article_count)\n\n        # User with both add and change permissions should be redirected to the\n        # change page for the newly created object.\n        article_count = Article.objects.count()\n        self.client.force_login(self.superuser)\n        post = self.client.post(article_change_url, change_dict_save_as_new)\n        self.assertEqual(Article.objects.count(), article_count + 1)\n        new_article = Article.objects.latest(\"id\")\n        self.assertRedirects(\n            post, reverse(\"admin:admin_views_article_change\", args=(new_article.pk,))\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 392,
        "n_words": 115,
        "vocab_size": 79,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 251,
        "n_ast_nodes": 419,
        "n_identifiers": 26,
        "d_id": 52024,
        "documentation": {
            "docstring": "\n        'Save as new' should raise PermissionDenied for users without the 'add'\n        permission.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 53477,
        "commit_id": "29f4c75e3a605e29987e856204a2441b31f4a6df",
        "repo": "prefect",
        "path": "src/prefect/orion/database/orm_models.py",
        "file_name": "orm_models.py",
        "fun_name": "estimated_run_time",
        "commit_message": "Repair imports as needed",
        "code": "def estimated_run_time(self):\n        \n        if self.state and self.state_type == schemas.states.StateType.RUNNING:\n            return self.total_run_time + (pendulum.now() - self.state.timestamp)\n        else:\n            return self.total_run_time\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 60,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 77,
        "n_identifiers": 12,
        "d_id": 10820,
        "documentation": {
            "docstring": "Total run time is incremented in the database whenever a RUNNING\n        state is exited. To give up-to-date estimates, we estimate incremental\n        run time for any runs currently in a RUNNING state.",
            "n_words": 31,
            "vocab_size": 25,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 196104,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/partitions.py",
        "file_name": "partitions.py",
        "fun_name": "from_rgs",
        "commit_message": "Updated import locations",
        "code": "def from_rgs(self, rgs, elements):\n        \n        if len(rgs) != len(elements):\n            raise ValueError('mismatch in rgs and element lengths')\n        max_elem = max(rgs) + 1\n        partition = [[] for i in range(max_elem)]\n        j = 0\n        for i in rgs:\n            partition[i].append(elements[j])\n            j += 1\n        if not all(p for p in partition):\n            raise ValueError('some blocks of the partition were empty.')\n        return Partition(*partition)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 155,
        "n_words": 55,
        "vocab_size": 42,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 92,
        "n_ast_nodes": 150,
        "n_identifiers": 16,
        "d_id": 47604,
        "documentation": {
            "docstring": "\n        Creates a set partition from a restricted growth string.\n\n        Explanation\n        ===========\n\n        The indices given in rgs are assumed to be the index\n        of the element as given in elements *as provided* (the\n        elements are not sorted by this routine). Block numbering\n        starts from 0. If any block was not referenced in ``rgs``\n        an error will be raised.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Partition\n        >>> Partition.from_rgs([0, 1, 2, 0, 1], list('abcde'))\n        Partition({c}, {a, d}, {b, e})\n        >>> Partition.from_rgs([0, 1, 2, 0, 1], list('cbead'))\n        Partition({e}, {a, c}, {b, d})\n        >>> a = Partition([1, 4], [2], [3, 5])\n        >>> Partition.from_rgs(a.RGS, a.members)\n        Partition({2}, {1, 4}, {3, 5})\n        ",
            "n_words": 104,
            "vocab_size": 81,
            "n_whitespaces": 238,
            "language": "en"
        }
    },
    {
        "id": 167451,
        "commit_id": "e48c9c3973286e257f6da1966c91806d86b917e0",
        "repo": "pandas",
        "path": "pandas/io/sas/sas_xport.py",
        "file_name": "sas_xport.py",
        "fun_name": "get_chunk",
        "commit_message": "TYP: more return annotations for io/* (#47524)\n\n* TYP: more return annotations for io/*\r\n\r\n* import future",
        "code": "def get_chunk(self, size=None) -> pd.DataFrame:\n        \n        if size is None:\n            size = self._chunksize\n        return self.read(nrows=size)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 46,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 33,
        "n_ast_nodes": 54,
        "n_identifiers": 8,
        "d_id": 40022,
        "documentation": {
            "docstring": "\n        Reads lines from Xport file and returns as dataframe\n\n        Parameters\n        ----------\n        size : int, defaults to None\n            Number of lines to read.  If None, reads whole file.\n\n        Returns\n        -------\n        DataFrame\n        ",
            "n_words": 30,
            "vocab_size": 28,
            "n_whitespaces": 99,
            "language": "en"
        }
    },
    {
        "id": 196207,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/subsets.py",
        "file_name": "subsets.py",
        "fun_name": "iterate_graycode",
        "commit_message": "Updated import locations",
        "code": "def iterate_graycode(self, k):\n        \n        unranked_code = GrayCode.unrank(self.superset_size,\n                                       (self.rank_gray + k) % self.cardinality)\n        return Subset.subset_from_bitlist(self.superset,\n                                          unranked_code)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 114,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 41,
        "n_ast_nodes": 64,
        "n_identifiers": 12,
        "d_id": 47707,
        "documentation": {
            "docstring": "\n        Helper function used for prev_gray and next_gray.\n        It performs ``k`` step overs to get the respective Gray codes.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Subset\n        >>> a = Subset([1, 2, 3], [1, 2, 3, 4])\n        >>> a.iterate_graycode(3).subset\n        [1, 4]\n        >>> a.iterate_graycode(-2).subset\n        [1, 2, 4]\n\n        See Also\n        ========\n\n        next_gray, prev_gray\n        ",
            "n_words": 49,
            "vocab_size": 39,
            "n_whitespaces": 148,
            "language": "en"
        }
    },
    {
        "id": 203310,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/conf/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "__getattr__",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def __getattr__(self, name):\n        \n        if self._wrapped is empty:\n            self._setup(name)\n        val = getattr(self._wrapped, name)\n\n        # Special case some settings which require further modification.\n        # This is done here for performance reasons so the modified value is cached.\n        if name in {\"MEDIA_URL\", \"STATIC_URL\"} and val is not None:\n            val = self._add_script_prefix(val)\n        elif name == \"SECRET_KEY\" and not val:\n            raise ImproperlyConfigured(\"The SECRET_KEY setting must not be empty.\")\n\n        self.__dict__[name] = val\n        return val\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 164,
        "n_words": 68,
        "vocab_size": 53,
        "complexity": 6,
        "nloc": 10,
        "token_counts": 76,
        "n_ast_nodes": 130,
        "n_identifiers": 11,
        "d_id": 50295,
        "documentation": {
            "docstring": "Return the value of a setting and cache it in self.__dict__.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 183781,
        "commit_id": "bfb962bacf274373e5706090cd854b6aa0857270",
        "repo": "textual",
        "path": "tests/test_xterm_parser.py",
        "file_name": "test_xterm_parser.py",
        "fun_name": "test_escape_sequence_resulting_in_multiple_keypresses",
        "commit_message": "Backtracking unknown escape sequences, various tests for XTermParser",
        "code": "def test_escape_sequence_resulting_in_multiple_keypresses(parser):\n    \n    events = list(parser.feed(\"\\x1b[2;4~\"))\n    assert len(events) == 2\n    assert events[0].key == \"escape\"\n    assert events[1].key == \"shift+insert\"\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 17,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 42,
        "n_ast_nodes": 75,
        "n_identifiers": 7,
        "d_id": 44334,
        "documentation": {
            "docstring": "Some sequences are interpreted as more than 1 keypress",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 167274,
        "commit_id": "d40c37192b3d38a3c9a0d248dc612ac9dd56e506",
        "repo": "pandas",
        "path": "pandas/tests/extension/test_arrow.py",
        "file_name": "test_arrow.py",
        "fun_name": "all_data",
        "commit_message": "ENH/TST: Add BaseInterfaceTests tests for ArrowExtensionArray (#47377)",
        "code": "def all_data(request, data, data_missing):\n    \n    if request.param == \"data\":\n        return data\n    elif request.param == \"data_missing\":\n        return data_missing\n\n\n@pytest.fixture",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 39,
        "n_words": 17,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 28,
        "n_ast_nodes": 56,
        "n_identifiers": 7,
        "d_id": 39962,
        "documentation": {
            "docstring": "Parametrized fixture returning 'data' or 'data_missing' integer arrays.\n\n    Used to test dtype conversion with and without missing values.\n    ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 209532,
        "commit_id": "08b1f9d67c8e716fd44036a027bdc90dcb9fcfdf",
        "repo": "scapy",
        "path": "scapy/contrib/igmpv3.py",
        "file_name": "igmpv3.py",
        "fun_name": "encode_maxrespcode",
        "commit_message": "E275 - Missing whitespace after keyword (#3711)\n\nCo-authored-by: Alexander Aring <alex.aring@gmail.com>\r\nCo-authored-by: Anmol Sarma <me@anmolsarma.in>\r\nCo-authored-by: antoine.torre <torreantoine1@gmail.com>\r\nCo-authored-by: Antoine Vacher <devel@tigre-bleu.net>\r\nCo-authored-by: Arnaud Ebalard <arno@natisbad.org>\r\nCo-authored-by: atlowl <86038305+atlowl@users.noreply.github.com>\r\nCo-authored-by: Brian Bienvenu <brian@bienvenu.id.au>\r\nCo-authored-by: Chris Packham <chris.packham@alliedtelesis.co.nz>\r\nCo-authored-by: CQ <cq674350529@163.com>\r\nCo-authored-by: Daniel Collins <kinap@users.noreply.github.com>\r\nCo-authored-by: Federico Maggi <federico.maggi@gmail.com>\r\nCo-authored-by: Florian Maury <florian.maury@ssi.gouv.fr>\r\nCo-authored-by: _Frky <3105926+Frky@users.noreply.github.com>\r\nCo-authored-by: g-mahieux <37588339+g-mahieux@users.noreply.github.com>\r\nCo-authored-by: gpotter2 <gabriel@potter.fr>\r\nCo-authored-by: Guillaume Valadon <guillaume@valadon.net>\r\nCo-authored-by: Hao Zheng <haozheng10@gmail.com>\r\nCo-authored-by: Haresh Khandelwal <hareshkhandelwal@gmail.com>\r\nCo-authored-by: Harri Hämäläinen <hhamalai@iki.fi>\r\nCo-authored-by: hecke <hecke@naberius.de>\r\nCo-authored-by: Jan Romann <jan.romann@gmail.com>\r\nCo-authored-by: Jan Sebechlebsky <sebechlebskyjan@gmail.com>\r\nCo-authored-by: jdiog0 <43411724+jdiog0@users.noreply.github.com>\r\nCo-authored-by: jockque <38525640+jockque@users.noreply.github.com>\r\nCo-authored-by: Julien Bedel <30991560+JulienBedel@users.noreply.github.com>\r\nCo-authored-by: Keith Scott <kscott@mitre.org>\r\nCo-authored-by: Kfir Gollan <kfir@drivenets.com>\r\nCo-authored-by: Lars Munch <lars@segv.dk>\r\nCo-authored-by: ldp77 <52221370+ldp77@users.noreply.github.com>\r\nCo-authored-by: Leonard Crestez <cdleonard@gmail.com>\r\nCo-authored-by: Marcel Patzlaff <mpatzlaff@benocs.com>\r\nCo-authored-by: Martijn Thé <martijnthe@users.noreply.github.com>\r\nCo-authored-by: Martine Lenders <authmillenon@gmail.com>\r\nCo-authored-by: Michael Farrell <micolous+git@gmail.com>\r\nCo-authored-by: Michał Mirosław <mirq-linux@rere.qmqm.pl>\r\nCo-authored-by: mkaliszan <mkaliszan@benocs.com>\r\nCo-authored-by: mtury <maxence.tury@ssi.gouv.fr>\r\nCo-authored-by: Neale Ranns <nranns@cisco.com>\r\nCo-authored-by: Octavian Toader <Octavian.Toader@belden.com>\r\nCo-authored-by: Peter Eisenlohr <peter@eisenlohr.org>\r\nCo-authored-by: Phil <phil@secdev.org>\r\nCo-authored-by: Pierre Lalet <pierre@droids-corp.org>\r\nCo-authored-by: Pierre Lorinquer <pierre.lorinquer@ssi.gouv.fr>\r\nCo-authored-by: piersoh <42040737+piersoh@users.noreply.github.com>\r\nCo-authored-by: plorinquer <pierre.lorinquer@ssi.gouv.fr>\r\nCo-authored-by: pvinci <pvinci@users.noreply.github.com>\r\nCo-authored-by: Rahul Jadhav <nyrahul@gmail.com>\r\nCo-authored-by: Robin Jarry <robin.jarry@6wind.com>\r\nCo-authored-by: romain-perez <51962832+romain-perez@users.noreply.github.com>\r\nCo-authored-by: rperez <rperez@debian>\r\nCo-authored-by: Sabrina Dubroca <sd@queasysnail.net>\r\nCo-authored-by: Sebastian Baar <sebastian.baar@gmx.de>\r\nCo-authored-by: sebastien mainand <sebastien.mainand@ssi.gouv.fr>\r\nCo-authored-by: smehner1 <smehner1@gmail.com>\r\nCo-authored-by: speakinghedge <hecke@naberius.de>\r\nCo-authored-by: Steven Van Acker <steven@singularity.be>\r\nCo-authored-by: Thomas Faivre <thomas.faivre@6wind.com>\r\nCo-authored-by: Tran Tien Dat <peter.trantiendat@gmail.com>\r\nCo-authored-by: Wael Mahlous <wael.mahlous@gmail.com>\r\nCo-authored-by: waeva <74464394+waeva@users.noreply.github.com>\r\n\r\nCo-authored-by: Alexander Aring <alex.aring@gmail.com>\r\nCo-authored-by: Anmol Sarma <me@anmolsarma.in>\r\nCo-authored-by: antoine.torre <torreantoine1@gmail.com>\r\nCo-authored-by: Antoine Vacher <devel@tigre-bleu.net>\r\nCo-authored-by: Arnaud Ebalard <arno@natisbad.org>\r\nCo-authored-by: atlowl <86038305+atlowl@users.noreply.github.com>\r\nCo-authored-by: Brian Bienvenu <brian@bienvenu.id.au>\r\nCo-authored-by: Chris Packham <chris.packham@alliedtelesis.co.nz>\r\nCo-authored-by: CQ <cq674350529@163.com>\r\nCo-authored-by: Daniel Collins <kinap@users.noreply.github.com>\r\nCo-authored-by: Federico Maggi <federico.maggi@gmail.com>\r\nCo-authored-by: Florian Maury <florian.maury@ssi.gouv.fr>\r\nCo-authored-by: _Frky <3105926+Frky@users.noreply.github.com>\r\nCo-authored-by: g-mahieux <37588339+g-mahieux@users.noreply.github.com>\r\nCo-authored-by: gpotter2 <gabriel@potter.fr>\r\nCo-authored-by: Guillaume Valadon <guillaume@valadon.net>\r\nCo-authored-by: Hao Zheng <haozheng10@gmail.com>\r\nCo-authored-by: Haresh Khandelwal <hareshkhandelwal@gmail.com>\r\nCo-authored-by: Harri Hämäläinen <hhamalai@iki.fi>\r\nCo-authored-by: hecke <hecke@naberius.de>\r\nCo-authored-by: Jan Romann <jan.romann@gmail.com>\r\nCo-authored-by: Jan Sebechlebsky <sebechlebskyjan@gmail.com>\r\nCo-authored-by: jdiog0 <43411724+jdiog0@users.noreply.github.com>\r\nCo-authored-by: jockque <38525640+jockque@users.noreply.github.com>\r\nCo-authored-by: Julien Bedel <30991560+JulienBedel@users.noreply.github.com>\r\nCo-authored-by: Keith Scott <kscott@mitre.org>\r\nCo-authored-by: Kfir Gollan <kfir@drivenets.com>\r\nCo-authored-by: Lars Munch <lars@segv.dk>\r\nCo-authored-by: ldp77 <52221370+ldp77@users.noreply.github.com>\r\nCo-authored-by: Leonard Crestez <cdleonard@gmail.com>\r\nCo-authored-by: Marcel Patzlaff <mpatzlaff@benocs.com>\r\nCo-authored-by: Martijn Thé <martijnthe@users.noreply.github.com>\r\nCo-authored-by: Martine Lenders <authmillenon@gmail.com>\r\nCo-authored-by: Michael Farrell <micolous+git@gmail.com>\r\nCo-authored-by: Michał Mirosław <mirq-linux@rere.qmqm.pl>\r\nCo-authored-by: mkaliszan <mkaliszan@benocs.com>\r\nCo-authored-by: mtury <maxence.tury@ssi.gouv.fr>\r\nCo-authored-by: Neale Ranns <nranns@cisco.com>\r\nCo-authored-by: Octavian Toader <Octavian.Toader@belden.com>\r\nCo-authored-by: Peter Eisenlohr <peter@eisenlohr.org>\r\nCo-authored-by: Phil <phil@secdev.org>\r\nCo-authored-by: Pierre Lalet <pierre@droids-corp.org>\r\nCo-authored-by: Pierre Lorinquer <pierre.lorinquer@ssi.gouv.fr>\r\nCo-authored-by: piersoh <42040737+piersoh@users.noreply.github.com>\r\nCo-authored-by: pvinci <pvinci@users.noreply.github.com>\r\nCo-authored-by: Rahul Jadhav <nyrahul@gmail.com>\r\nCo-authored-by: Robin Jarry <robin.jarry@6wind.com>\r\nCo-authored-by: romain-perez <51962832+romain-perez@users.noreply.github.com>\r\nCo-authored-by: rperez <rperez@debian>\r\nCo-authored-by: Sabrina Dubroca <sd@queasysnail.net>\r\nCo-authored-by: Sebastian Baar <sebastian.baar@gmx.de>\r\nCo-authored-by: sebastien mainand <sebastien.mainand@ssi.gouv.fr>\r\nCo-authored-by: smehner1 <smehner1@gmail.com>\r\nCo-authored-by: Steven Van Acker <steven@singularity.be>\r\nCo-authored-by: Thomas Faivre <thomas.faivre@6wind.com>\r\nCo-authored-by: Tran Tien Dat <peter.trantiendat@gmail.com>\r\nCo-authored-by: Wael Mahlous <wael.mahlous@gmail.com>\r\nCo-authored-by: waeva <74464394+waeva@users.noreply.github.com>",
        "code": "def encode_maxrespcode(self):\n        \n        value = self.mrcode\n        if value < 128:\n            code = value\n        elif value > 31743:\n            code = 255\n        else:\n            exp = 0\n            value >>= 3\n            while value > 31:\n                exp += 1\n                value >>= 1\n            exp <<= 4\n            code = 0x80 | exp | (value & 0x0F)\n        self.mrcode = code\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 200,
        "n_words": 51,
        "vocab_size": 29,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 65,
        "n_ast_nodes": 109,
        "n_identifiers": 6,
        "d_id": 52724,
        "documentation": {
            "docstring": "Encode and replace the mrcode value to its IGMPv3 encoded time value if needed,  # noqa: E501\n        as specified in rfc3376#section-4.1.1.\n\n        If value < 128, return the value specified. If >= 128, encode as a floating  # noqa: E501\n        point value. Value can be 0 - 31744.\n        ",
            "n_words": 47,
            "vocab_size": 37,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 47416,
        "commit_id": "a801ea3927b8bf3ca154fea3774ebf2d90e74e50",
        "repo": "airflow",
        "path": "tests/system/providers/elasticsearch/example_elasticsearch_query.py",
        "file_name": "example_elasticsearch_query.py",
        "fun_name": "show_tables",
        "commit_message": "es new system tests (#22811)",
        "code": "def show_tables():\n    \n    # [START howto_elasticsearch_query]\n    es = ElasticsearchHook(elasticsearch_conn_id=CONN_ID)\n\n    # Handle ES conn with context manager\n    with es.get_conn() as es_conn:\n        tables = es_conn.execute('SHOW TABLES')\n        for table, *_ in tables:\n            print(f\"table: {table}\")\n    return True\n    # [END howto_elasticsearch_query]\n\n\nwith models.DAG(\n    DAG_ID,\n    schedule_interval=\"@once\",\n    start_date=datetime(2021, 1, 1),\n    catchup=False,\n    tags=[\"example\", \"elasticsearch\"],\n) as dag:\n    execute_query = show_tables()\n    (\n        # TEST BODY\n        execute_query\n    )\n\nfrom tests.system.utils import get_test_run  # noqa: E402\n\n# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)\ntest_run = get_test_run(dag)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 158,
        "n_words": 78,
        "vocab_size": 63,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 45,
        "n_ast_nodes": 187,
        "n_identifiers": 27,
        "d_id": 9105,
        "documentation": {
            "docstring": "\n    show_tables queries elasticsearch to list available tables\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 94332,
        "commit_id": "39cfdcb446e74732c67ce07d7dd8d8d5ace471b1",
        "repo": "sentry",
        "path": "tests/sentry/event_manager/test_event_manager.py",
        "file_name": "test_event_manager.py",
        "fun_name": "test_category_match_in_app",
        "commit_message": "test(event_manager): Fix incorrect invocations of manager.save (#36615)",
        "code": "def test_category_match_in_app(self):\n        \n        from sentry.grouping.enhancer import Enhancements\n\n        enhancement = Enhancements.from_config_string(\n            ,\n        )\n\n        event = make_event(\n            platform=\"native\",\n            exception={\n                \"values\": [\n                    {\n                        \"type\": \"Hello\",\n                        \"stacktrace\": {\n                            \"frames\": [\n                                {\n                                    \"function\": \"foo\",\n                                    \"in_app\": True,\n                                },\n                                {\"function\": \"bar\"},\n                            ]\n                        },\n                    }\n                ]\n            },\n        )\n\n        manager = EventManager(event)\n        manager.normalize()\n        manager.get_data()[\"grouping_config\"] = {\n            \"enhancements\": enhancement.dumps(),\n            \"id\": \"mobile:2021-02-12\",\n        }\n        event1 = manager.save(self.project.id)\n        assert event1.data[\"exception\"][\"values\"][0][\"stacktrace\"][\"frames\"][0][\"in_app\"] is False\n\n        event = make_event(\n            platform=\"native\",\n            exception={\n                \"values\": [\n                    {\n                        \"type\": \"Hello\",\n                        \"stacktrace\": {\n                            \"frames\": [\n                                {\n                                    \"function\": \"foo2\",\n                                    \"in_app\": True,\n                                },\n                                {\"function\": \"bar\"},\n                            ]\n                        },\n                    }\n                ]\n            },\n        )\n\n        manager = EventManager(event)\n        manager.normalize()\n        manager.get_data()[\"grouping_config\"] = {\n            \"enhancements\": enhancement.dumps(),\n            \"id\": \"mobile:2021-02-12\",\n        }\n        event2 = manager.save(self.project.id)\n        assert event2.data[\"exception\"][\"values\"][0][\"stacktrace\"][\"frames\"][0][\"in_app\"] is False\n        assert event1.group_id == event2.group_id\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1085,
        "n_words": 109,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 64,
        "token_counts": 277,
        "n_ast_nodes": 492,
        "n_identifiers": 24,
        "d_id": 19067,
        "documentation": {
            "docstring": "\n        Regression test to ensure that grouping in-app enhancements work in\n        principle.\n        \n            function:foo category=bar\n            function:foo2 category=bar\n            category:bar -app\n            ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 194793,
        "commit_id": "82df52b4431f3573ca2c93dd4bb3098992968acc",
        "repo": "ParlAI",
        "path": "tests/nightly/gpu/test_style_gen.py",
        "file_name": "test_style_gen.py",
        "fun_name": "test_curr_only_accuracy",
        "commit_message": "[Style-Controlled Generation] Open-source a second style classifier (#4380)\n\n* Add model to model list\r\n\r\n* Curr only classifier download page\r\n\r\n* Add test case\r\n\r\n* Update version\r\n\r\n* Update with some results\r\n\r\n* Wording",
        "code": "def test_curr_only_accuracy(self):\n        \n        _, test = testing_utils.eval_model(\n            opt={\n                'batchsize': 4,\n                'fp16': True,\n                'num_examples': 16,\n                'model_file': 'zoo:style_gen/curr_only_classifier/model',\n                'model': 'projects.style_gen.classifier:ClassifierAgent',\n                'classes_from_file': 'image_chat_personalities_file',\n                'task': 'style_gen:CurrUttOnlyStyle',\n                'wrapper_task': 'style_gen:LabeledBlendedSkillTalk',\n            },\n            skip_valid=True,\n        )\n        self.assertAlmostEqual(test['accuracy'], 0.4375, delta=0.0)\n\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 210,
        "n_words": 29,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 75,
        "n_ast_nodes": 129,
        "n_identifiers": 10,
        "d_id": 47085,
        "documentation": {
            "docstring": "\n        Test the accuracy of the classifier trained on current utterances only.\n\n        The accuracy is low here because the task was labeled using a different\n        classifier, zoo:style_gen/prev_curr_classifier/model.\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 186003,
        "commit_id": "c57f6b90259c8193e3aa9c3453a02b4043873381",
        "repo": "textual",
        "path": "src/textual/widgets/_list_view.py",
        "file_name": "_list_view.py",
        "fun_name": "highlighted_child",
        "commit_message": "Fix click handler",
        "code": "def highlighted_child(self) -> ListItem | None:\n        \n        if self.index is None:\n            return None\n        elif 0 <= self.index < len(self.children):\n            return self.children[self.index]\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 42,
        "n_ast_nodes": 67,
        "n_identifiers": 6,
        "d_id": 45287,
        "documentation": {
            "docstring": "Get the currently highlighted ListItem\n\n        Returns:\n            ListItem | None: The currently highlighted ListItem, or None if nothing is highlighted.\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 197943,
        "commit_id": "32e337616722ceae757c23ad1fe2f3465c629a47",
        "repo": "sympy",
        "path": "sympy/core/expr.py",
        "file_name": "expr.py",
        "fun_name": "_expand_hint",
        "commit_message": "Fix MatAdd.expand( ) not expanding completely",
        "code": "def _expand_hint(expr, hint, deep=True, **hints):\n        \n        hit = False\n        # XXX: Hack to support non-Basic args\n        #              |\n        #              V\n        if deep and getattr(expr, 'args', ()) and not expr.is_Atom:\n            sargs = []\n            for arg in expr.args:\n                arg, arghit = Expr._expand_hint(arg, hint, **hints)\n                hit |= arghit\n                sargs.append(arg)\n\n            if hit:\n                expr = expr.func(*sargs)\n                expr = expr._evaluate(expr)\n\n        if hasattr(expr, hint):\n            newexpr = getattr(expr, hint)(**hints)\n            if newexpr != expr:\n                return (newexpr, True)\n\n        return (expr, hit)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 297,
        "n_words": 70,
        "vocab_size": 52,
        "complexity": 8,
        "nloc": 16,
        "token_counts": 128,
        "n_ast_nodes": 203,
        "n_identifiers": 18,
        "d_id": 48749,
        "documentation": {
            "docstring": "\n        Helper for ``expand()``.  Recursively calls ``expr._eval_expand_hint()``.\n\n        Returns ``(expr, hit)``, where expr is the (possibly) expanded\n        ``expr`` and ``hit`` is ``True`` if ``expr`` was truly expanded and\n        ``False`` otherwise.\n        ",
            "n_words": 28,
            "vocab_size": 24,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 53193,
        "commit_id": "a452d8b8917000774302411a7aeb949f7e326814",
        "repo": "prefect",
        "path": "src/prefect/utilities/settings.py",
        "file_name": "settings.py",
        "fun_name": "get_extra_loggers",
        "commit_message": "Strip logger name to prevent accidental spaces",
        "code": "def get_extra_loggers(self) -> List[str]:\n        \n        return (\n            [name.strip() for name in self.extra_loggers.split(\",\")]\n            if self.extra_loggers\n            else []\n        )\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 70,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 39,
        "n_ast_nodes": 64,
        "n_identifiers": 8,
        "d_id": 10735,
        "documentation": {
            "docstring": "\n        Parse the `extra_loggers` CSV and trim whitespace from logger names\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 322099,
        "commit_id": "b0c35d5e1ff02a634fa26392b60d3885c2c78677",
        "repo": "PaddleNLP",
        "path": "paddlenlp/transformers/mbart/modeling.py",
        "file_name": "modeling.py",
        "fun_name": "forward",
        "commit_message": "Fix the attention mask for fp16 (#1585)",
        "code": "def forward(self, input_ids=None, attention_mask=None, **kwargs):\n        \n        if input_ids is None:\n            raise ValueError(\"Input_ids cannot be None.\")\n        inputs_embeds = self.d_model**0.5 * self.embed_tokens(input_ids)\n        inputs_embed_pos = self.encoder_embed_positions(input_ids.shape)\n        hidden_states = inputs_embeds + inputs_embed_pos\n        hidden_states = self.encoder_layernorm_embedding(hidden_states)\n        encoder_input = self.encoder_dropout(hidden_states)\n\n        if attention_mask is None:\n            attention_mask = paddle.cast(\n                input_ids == self.pad_token_id,\n                dtype=paddle.get_default_dtype()).unsqueeze([1, 2]) * -1e4\n            attention_mask.stop_gradient = True\n\n        encoder_output = self.encoder(encoder_input, src_mask=attention_mask)\n        return encoder_output\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 189,
        "n_words": 56,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 130,
        "n_ast_nodes": 203,
        "n_identifiers": 26,
        "d_id": 118056,
        "documentation": {
            "docstring": "\n        The MBartEncoder forward method, overrides the `__call__()` special method.\n\n        Args:\n            input_ids (Tensor, optional):\n                See :class:`MBartModel`.\n            attention_mask (Tensor, optional):\n                See :class:`MBartModel`.\n\n        Returns:\n            Tensor: Returns tensor `encoder_output`, which is the output at the last layer of the model.\n            Its data type should be float32 and has a shape of [batch_size, sequence_length, hidden_size].\n\n        ",
            "n_words": 50,
            "vocab_size": 42,
            "n_whitespaces": 153,
            "language": "en"
        }
    },
    {
        "id": 6299,
        "commit_id": "20a8a6fdb516e543d4598c852063ba0fb407f3ba",
        "repo": "ludwig",
        "path": "ludwig/utils/entmax/root_finding.py",
        "file_name": "root_finding.py",
        "fun_name": "sparsemax_bisect",
        "commit_message": "Removes dependency on entmax from PyPI, adds entmax source to utils (#1778)\n\n* Removes dependency on entmax from PyPi, add entmax source code into utils instead.\r\n\r\n* Removes build status and image from README\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fix python formatting in docs for pre-commit.\r\n\r\n* Removes __main__ from test_losses.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Update entmax imports.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\nCo-authored-by: Daniel Treiman <daniel@predibase.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def sparsemax_bisect(X, dim=-1, n_iter=50, ensure_sum_one=True):\n    \n    return SparsemaxBisectFunction.apply(X, dim, n_iter, ensure_sum_one)\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 16,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 32,
        "n_ast_nodes": 47,
        "n_identifiers": 7,
        "d_id": 957,
        "documentation": {
            "docstring": "sparsemax: normalizing sparse transform (a la softmax), via bisection.\n\n    Solves the projection:\n\n        min_p ||x - p||_2   s.t.    p >= 0, sum(p) == 1.\n\n    Parameters\n    ----------\n    X : torch.Tensor\n        The input tensor.\n\n    dim : int\n        The dimension along which to apply sparsemax.\n\n    n_iter : int\n        Number of bisection iterations. For float32, 24 iterations should\n        suffice for machine precision.\n\n    ensure_sum_one : bool,\n        Whether to divide the result by its sum. If false, the result might\n        sum to close but not exactly 1, which might cause downstream problems.\n\n    Note: This function does not yet support normalizing along anything except\n    the last dimension. Please use transposing and views to achieve more\n    general behavior.\n\n    Returns\n    -------\n    P : torch tensor, same shape as X\n        The projection result, such that P.sum(dim=dim) == 1 elementwise.\n    ",
            "n_words": 128,
            "vocab_size": 107,
            "n_whitespaces": 231,
            "language": "en"
        }
    },
    {
        "id": 84423,
        "commit_id": "bfd9fc86223c2446e8b38d2cdd5876caed50bfda",
        "repo": "zulip",
        "path": "zerver/webhooks/newrelic/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_missing_fields_old",
        "commit_message": "integration: Fix integration with newrelic.\n\nNewrelic updated the payload that's sent via the webhook incoming call\ncausing a bug in the newrelic webhook endpoint.\nThis fixes the bug by updating the endpoint to respect the new format\nof the payload as well as the old format. This should be updated once\nthe old format is EOLed.\n\nFixes #22338.",
        "code": "def test_missing_fields_old(self) -> None:\n        expected_topic = \"Unknown Policy (Unknown ID)\"\n        expected_message = .strip()\n\n        self.check_webhook(\n            \"incident_default_fields_old\",\n            expected_topic,\n            expected_message,\n            content_type=\"application/json\",\n        )\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 90,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 32,
        "n_ast_nodes": 57,
        "n_identifiers": 7,
        "d_id": 17836,
        "documentation": {
            "docstring": "\n[Incident](https://alerts.newrelic.com) **opened** for condition: **Unknown condition** at <time:2020-11-11 22:32:11.151000+00:00>\n``` quote\nNo details.\n```\n",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 44155,
        "commit_id": "44df1420582b358594c8d7344865811cff02956c",
        "repo": "airflow",
        "path": "tests/www/views/test_views_connection.py",
        "file_name": "test_views_connection.py",
        "fun_name": "test_process_form_extras",
        "commit_message": "fix: Update custom connection field processing (#20883)\n\n* fix: Update custom connection field processing\r\n\r\nFixes issue where custom connectionfields are not updated because `extra` field is in form and has previous values, overriding custom field values.\r\nAdds portion of connection form tests to test functionality.",
        "code": "def test_process_form_extras():\n    \n\n    # Testing parameters set in both `Extra` and custom fields.\n    mock_form = mock.Mock()\n    mock_form.data = {\n        \"conn_type\": \"test\",\n        \"conn_id\": \"extras_test\",\n        \"extra\": '{\"param1\": \"param1_val\"}',\n        \"extra__test__custom_field\": \"custom_field_val\",\n    }\n\n    cmv = ConnectionModelView()\n    cmv.extra_fields = [\"extra__test__custom_field\"]  # Custom field\n    cmv.process_form(form=mock_form, is_created=True)\n\n    assert json.loads(mock_form.extra.data) == {\n        \"extra__test__custom_field\": \"custom_field_val\",\n        \"param1\": \"param1_val\",\n    }\n\n    # Testing parameters set in `Extra` field only.\n    mock_form = mock.Mock()\n    mock_form.data = {\n        \"conn_type\": \"test2\",\n        \"conn_id\": \"extras_test2\",\n        \"extra\": '{\"param2\": \"param2_val\"}',\n    }\n\n    cmv = ConnectionModelView()\n    cmv.process_form(form=mock_form, is_created=True)\n\n    assert json.loads(mock_form.extra.data) == {\"param2\": \"param2_val\"}\n\n    # Testing parameters set in custom fields only.\n    mock_form = mock.Mock()\n    mock_form.data = {\n        \"conn_type\": \"test3\",\n        \"conn_id\": \"extras_test3\",\n        \"extra__test3__custom_field\": \"custom_field_val3\",\n    }\n\n    cmv = ConnectionModelView()\n    cmv.extra_fields = [\"extra__test3__custom_field\"]  # Custom field\n    cmv.process_form(form=mock_form, is_created=True)\n\n    assert json.loads(mock_form.extra.data) == {\"extra__test3__custom_field\": \"custom_field_val3\"}\n\n    # Testing parameters set in both extra and custom fields (cunnection updates).\n    mock_form = mock.Mock()\n    mock_form.data = {\n        \"conn_type\": \"test4\",\n        \"conn_id\": \"extras_test4\",\n        \"extra\": '{\"extra__test4__custom_field\": \"custom_field_val3\"}',\n        \"extra__test4__custom_field\": \"custom_field_val4\",\n    }\n\n    cmv = ConnectionModelView()\n    cmv.extra_fields = [\"extra__test4__custom_field\"]  # Custom field\n    cmv.process_form(form=mock_form, is_created=True)\n\n    assert json.loads(mock_form.extra.data) == {\"extra__test4__custom_field\": \"custom_field_val4\"}\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 375,
        "n_words": 161,
        "vocab_size": 67,
        "complexity": 1,
        "nloc": 45,
        "token_counts": 275,
        "n_ast_nodes": 510,
        "n_identifiers": 14,
        "d_id": 8180,
        "documentation": {
            "docstring": "\n    Test the handling of connection parameters set with the classic `Extra` field as well as custom fields.\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 203999,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/gdal/raster/band.py",
        "file_name": "band.py",
        "fun_name": "data",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def data(self, data=None, offset=None, size=None, shape=None, as_memoryview=False):\n        \n        offset = offset or (0, 0)\n        size = size or (self.width - offset[0], self.height - offset[1])\n        shape = shape or size\n        if any(x <= 0 for x in size):\n            raise ValueError(\"Offset too big for this raster.\")\n\n        if size[0] > self.width or size[1] > self.height:\n            raise ValueError(\"Size is larger than raster.\")\n\n        # Create ctypes type array generator\n        ctypes_array = GDAL_TO_CTYPES[self.datatype()] * (shape[0] * shape[1])\n\n        if data is None:\n            # Set read mode\n            access_flag = 0\n            # Prepare empty ctypes array\n            data_array = ctypes_array()\n        else:\n            # Set write mode\n            access_flag = 1\n\n            # Instantiate ctypes array holding the input data\n            if isinstance(data, (bytes, memoryview)) or (\n                numpy and isinstance(data, numpy.ndarray)\n            ):\n                data_array = ctypes_array.from_buffer_copy(data)\n            else:\n                data_array = ctypes_array(*data)\n\n        # Access band\n        capi.band_io(\n            self._ptr,\n            access_flag,\n            offset[0],\n            offset[1],\n            size[0],\n            size[1],\n            byref(data_array),\n            shape[0],\n            shape[1],\n            self.datatype(),\n            0,\n            0,\n        )\n\n        # Return data as numpy array if possible, otherwise as list\n        if data is None:\n            if as_memoryview:\n                return memoryview(data_array)\n            elif numpy:\n                # reshape() needs a reshape parameter with the height first.\n                return numpy.frombuffer(\n                    data_array, dtype=numpy.dtype(data_array)\n                ).reshape(tuple(reversed(size)))\n            else:\n                return list(data_array)\n        else:\n            self._flush()\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 740,
        "n_words": 181,
        "vocab_size": 118,
        "complexity": 15,
        "nloc": 45,
        "token_counts": 299,
        "n_ast_nodes": 460,
        "n_identifiers": 33,
        "d_id": 50604,
        "documentation": {
            "docstring": "\n        Read or writes pixel values for this band. Blocks of data can\n        be accessed by specifying the width, height and offset of the\n        desired block. The same specification can be used to update\n        parts of a raster by providing an array of values.\n\n        Allowed input data types are bytes, memoryview, list, tuple, and array.\n        ",
            "n_words": 54,
            "vocab_size": 45,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 286857,
        "commit_id": "7e4a657333c8b7bb1ebdcb7a4c8f06e8dc0d66f6",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/stocks/tradinghours/pandas_market_cal_model.py",
        "file_name": "pandas_market_cal_model.py",
        "fun_name": "get_all_holiday_exchange_short_names",
        "commit_message": "Addition of exchange holiday functionality under stocks/th (#3486)\n\n* Addition of exchange holiday calendars using PandasMarketCalendar\r\n\r\n* website update for holidays functionality\r\n\r\n* Disable pylint too many attributes\r\n\r\n* Changes to not show index for dataframe and include metavar\r\n\r\n* Setting of default value for holidays\r\n\r\n* Merge + black linter\r\n\r\n* test fix\r\n\r\nCo-authored-by: james <jmaslek11@gmail.com>\r\nCo-authored-by: Jeroen Bouma <jer.bouma@gmail.com>",
        "code": "def get_all_holiday_exchange_short_names() -> pd.DataFrame:\n    \n    exchange_short_names = mcal.calendar_registry.get_calendar_names()\n\n    df = pd.DataFrame(exchange_short_names, columns=[\"short_name\"])\n\n    return df\n\n\n@log_start_end(log=logger)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 25,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 34,
        "n_ast_nodes": 71,
        "n_identifiers": 12,
        "d_id": 86066,
        "documentation": {
            "docstring": "Get all holiday exchanges short names.\n\n    Returns\n    -------\n    pd.DataFrame\n        All available exchanges with holiday data (short names)\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 163504,
        "commit_id": "ab42f85f192ab054a18f94825ced1bb4c1ab7d3f",
        "repo": "pandas",
        "path": "pandas/core/indexing.py",
        "file_name": "indexing.py",
        "fun_name": "_tupleize_axis_indexer",
        "commit_message": "REF: implement LocationIndexer._tupleize_axis_indexer (#45378)",
        "code": "def _tupleize_axis_indexer(self, key) -> tuple:\n        \n        new_key = [slice(None)] * self.ndim\n        # error: Invalid index type \"Optional[Any]\" for \"List[slice]\"; expected\n        # type \"SupportsIndex\"\n        new_key[self.axis] = key  # type:ignore[index]\n        return tuple(new_key)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 72,
        "n_words": 29,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 35,
        "n_ast_nodes": 60,
        "n_identifiers": 8,
        "d_id": 39447,
        "documentation": {
            "docstring": "\n        If we have an axis, adapt the given key to be axis-independent.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 120043,
        "commit_id": "bc658e74567ffa941b31f4e89463dc713d2ecbf4",
        "repo": "jax",
        "path": "jax/_src/lax/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_broadcasting_select_mhlo",
        "commit_message": "[MHLO] Add direct MHLO lowerings for most linear algebra kernels.\n\nPiperOrigin-RevId: 439927594",
        "code": "def _broadcasting_select_mhlo(which, x, y):\n  \n  which_type, x_type, y_type = (\n    ir.RankedTensorType(v.type) for v in (which, x, y))\n  out_shape = list(lax_internal.broadcast_shapes(\n      tuple(which_type.shape), tuple(x_type.shape), tuple(y_type.shape)))\n  bcast_dims = lambda shape: mlir.dense_int_elements(\n      range(len(out_shape) - len(shape), len(out_shape)))\n  if which_type.shape != out_shape:\n    which = mhlo.BroadcastInDimOp(\n        ir.RankedTensorType.get(out_shape, which_type.element_type), which,\n        bcast_dims(which_type.shape))\n  if x_type.shape != out_shape:\n    x = mhlo.BroadcastInDimOp(\n        ir.RankedTensorType.get(out_shape, x_type.element_type), x,\n        bcast_dims(x_type.shape))\n  if y_type.shape != out_shape:\n    y = mhlo.BroadcastInDimOp(\n        ir.RankedTensorType.get(out_shape, y_type.element_type), y,\n        bcast_dims(y_type.shape))\n  return mhlo.SelectOp(which, x, y).result\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 140,
        "n_words": 68,
        "vocab_size": 50,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 211,
        "n_ast_nodes": 316,
        "n_identifiers": 28,
        "d_id": 26747,
        "documentation": {
            "docstring": "Wrapper around XLA `Select` that broadcasts its arguments.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 271833,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_utils.py",
        "file_name": "training_utils.py",
        "fun_name": "list_to_tuple",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def list_to_tuple(maybe_list):\n    \n    if isinstance(maybe_list, list):\n        return tuple(maybe_list)\n    return maybe_list\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 25,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 80856,
        "documentation": {
            "docstring": "Datasets will stack the list of tensor, so switch them to tuples.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 264030,
        "commit_id": "d789a7daa7712716c89259b987349917a89aece7",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/qt/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "collect_extra_binaries",
        "commit_message": "hookutils: reorganize the Qt hook utilities\n\nReorganize the Qt module information to provide information necessary\nto deal with variations between different python Qt bindings (PySide2,\nPyQt5, PySide6, and PyQt6). Replace the existing table-like dictionary\nwith list of entries, which is easier to format and document. From this\nlist, we now generate two dictionaries; one that maps Qt module (shared\nlibrary) names to the module info entries (the same role as the old\ndictionary), and one that maps python module names to the module info\nentries. The latter is necessary to accommodate python modules that do\nnot have corresponding Qt shared libraries (header-only Qt modules,\nsuch as QtAxContainer; or statically-linked module, such as QSci), but\nwe still need to provide information about plugins or translation\nfiles.\n\nThe new information list is based on manual inspection of source code\nfor Qt 5.15 and 6.3, and should provide comprehensive information about\nall plugin names and translation file basenames.\n\nIn addition, most of the helper functions, which take a reference to\nthe `QtLibraryInfo` class as their first argument, have been turned\ninto methods of the `QtLibraryInfo` class. The corresponding hooks\nhave also been adjusted.",
        "code": "def collect_extra_binaries(self):\n        \n\n        binaries = []\n\n        # Applicable only to Windows.\n        if not compat.is_win:\n            return []\n\n        # OpenGL: EGL/GLES via ANGLE, software OpenGL renderer.\n        binaries += self._collect_all_or_none(['libEGL.dll', 'libGLESv2.dll'], ['d3dcompiler_??.dll'])\n        binaries += self._collect_all_or_none(['opengl32sw.dll'])\n\n        # Include ICU files, if they exist.\n        # See the \"Deployment approach\" section in ``PyInstaller/utils/hooks/qt.py``.\n        binaries += self._collect_all_or_none(['icudt??.dll', 'icuin??.dll', 'icuuc??.dll'])\n\n        return binaries\n\n    # Collect additional shared libraries required for SSL support in QtNetwork, if they are available.\n    # Applicable only to Windows. See issue #3520, #4048.",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 171,
        "n_words": 77,
        "vocab_size": 55,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 61,
        "n_ast_nodes": 117,
        "n_identifiers": 6,
        "d_id": 77569,
        "documentation": {
            "docstring": "\n        Collect extra binaries/DLLs required by Qt. These include ANGLE DLLs, OpenGL software renderer DLL, and ICU\n        DLLs. Applicable only on Windows (on other OSes, empty list is returned).\n        ",
            "n_words": 28,
            "vocab_size": 28,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 331749,
        "commit_id": "90dc74c450a0ec671af0e7f73d6b4a7b5396a7af",
        "repo": "pytorch-image-models",
        "path": "timm/models/swin_transformer_v2.py",
        "file_name": "swin_transformer_v2.py",
        "fun_name": "__make_attention_mask",
        "commit_message": "Add code from https://github.com/ChristophReich1996/Swin-Transformer-V2 and change docstring style to match timm",
        "code": "def __make_attention_mask(self) -> None:\n        \n        # Make masks for shift case\n        if self.shift_size > 0:\n            height, width = self.input_resolution  # type: int, int\n            mask: torch.Tensor = torch.zeros(height, width, device=self.window_attention.tau.device)\n            height_slices: Tuple = (slice(0, -self.window_size),\n                                    slice(-self.window_size, -self.shift_size),\n                                    slice(-self.shift_size, None))\n            width_slices: Tuple = (slice(0, -self.window_size),\n                                   slice(-self.window_size, -self.shift_size),\n                                   slice(-self.shift_size, None))\n            counter: int = 0\n            for height_slice in height_slices:\n                for width_slice in width_slices:\n                    mask[height_slice, width_slice] = counter\n                    counter += 1\n            mask_windows: torch.Tensor = unfold(mask[None, None], self.window_size)\n            mask_windows: torch.Tensor = mask_windows.reshape(-1, self.window_size * self.window_size)\n            attention_mask: Optional[torch.Tensor] = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2)\n            attention_mask: Optional[torch.Tensor] = attention_mask.masked_fill(attention_mask != 0, float(-100.0))\n            attention_mask: Optional[torch.Tensor] = attention_mask.masked_fill(attention_mask == 0, float(0.0))\n        else:\n            attention_mask: Optional[torch.Tensor] = None\n        # Save mask\n        self.register_buffer(\"attention_mask\", attention_mask)\n",
        "url": "https://github.com/huggingface/pytorch-image-models.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 474,
        "n_words": 108,
        "vocab_size": 69,
        "complexity": 4,
        "nloc": 24,
        "token_counts": 279,
        "n_ast_nodes": 420,
        "n_identifiers": 31,
        "d_id": 119894,
        "documentation": {
            "docstring": " Method generates the attention mask used in shift case. ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 102171,
        "commit_id": "bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d",
        "repo": "pytorch",
        "path": "tools/test/test_gen_backend_stubs.py",
        "file_name": "test_gen_backend_stubs.py",
        "fun_name": "test_valid_zero_ops_doesnt_require_backend_dispatch_key",
        "commit_message": "Revert \"Revert D32498569: allow external backend codegen to toggle whether to generate out= and inplace kernels\" (#69950)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/69950\n\nThis reverts commit f6cad53443704dfe5a20cc62bee14d91e3bffcaa.\n\nTest Plan: Imported from OSS\n\nReviewed By: albanD\n\nDifferential Revision: D33113545\n\nPulled By: bdhirsh\n\nfbshipit-source-id: d6590294662588d36c09662dea65919ad4e1e288",
        "code": "def test_valid_zero_ops_doesnt_require_backend_dispatch_key(self) -> None:\n        yaml_str = \n        # External codegen on a yaml file with no operators is effectively a no-op,\n        # so there's no reason to parse the backend\n        self.assert_success_from_gen_backend_stubs(yaml_str)\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 58,
        "n_words": 30,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 16,
        "n_ast_nodes": 32,
        "n_identifiers": 4,
        "d_id": 21486,
        "documentation": {
            "docstring": "\\\nbackend: BAD_XLA\ncpp_namespace: torch_xla\nsupported:",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 2,
            "language": "en"
        }
    },
    {
        "id": 305777,
        "commit_id": "852b0caf5be4bba0dcaaf5f6a38221d1590c4ed9",
        "repo": "core",
        "path": "tests/components/stream/test_worker.py",
        "file_name": "test_worker.py",
        "fun_name": "test_worker_disable_ll_hls",
        "commit_message": "Add orientation transforms to stream (#77439)",
        "code": "async def test_worker_disable_ll_hls(hass):\n    \n    stream_settings = StreamSettings(\n        ll_hls=True,\n        min_segment_duration=TARGET_SEGMENT_DURATION_NON_LL_HLS\n        - SEGMENT_DURATION_ADJUSTER,\n        part_target_duration=TARGET_SEGMENT_DURATION_NON_LL_HLS,\n        hls_advance_part_limit=3,\n        hls_part_timeout=TARGET_SEGMENT_DURATION_NON_LL_HLS,\n        orientation=1,\n    )\n    py_av = MockPyAv()\n    py_av.container.format.name = \"hls\"\n    await async_decode_stream(\n        hass,\n        PacketSequence(TEST_SEQUENCE_LENGTH),\n        py_av=py_av,\n        stream_settings=stream_settings,\n    )\n    assert stream_settings.ll_hls is False\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 133,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 76,
        "n_ast_nodes": 117,
        "n_identifiers": 20,
        "d_id": 104561,
        "documentation": {
            "docstring": "Test that the worker disables ll-hls for hls inputs.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 67473,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/setup/doctype/company/company.py",
        "file_name": "company.py",
        "fun_name": "update_company_monthly_sales",
        "commit_message": "style: format code with black",
        "code": "def update_company_monthly_sales(company):\n\t\n\timport json\n\n\tfrom frappe.utils.goal import get_monthly_results\n\n\tfilter_str = \"company = {0} and status != 'Draft' and docstatus=1\".format(\n\t\tfrappe.db.escape(company)\n\t)\n\tmonth_to_value_dict = get_monthly_results(\n\t\t\"Sales Invoice\", \"base_grand_total\", \"posting_date\", filter_str, \"sum\"\n\t)\n\n\tfrappe.db.set_value(\"Company\", company, \"sales_monthly_history\", json.dumps(month_to_value_dict))\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 25,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 64,
        "n_ast_nodes": 111,
        "n_identifiers": 14,
        "d_id": 14538,
        "documentation": {
            "docstring": "Cache past year monthly sales of every company based on sales invoices",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 222842,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/dep_util.py",
        "file_name": "dep_util.py",
        "fun_name": "newer_pairwise",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def newer_pairwise (sources, targets):\n    \n    if len(sources) != len(targets):\n        raise ValueError(\"'sources' and 'targets' must be same length\")\n\n    # build a pair of lists (sources, targets) where  source is newer\n    n_sources = []\n    n_targets = []\n    for i in range(len(sources)):\n        if newer(sources[i], targets[i]):\n            n_sources.append(sources[i])\n            n_targets.append(targets[i])\n\n    return (n_sources, n_targets)\n\n# newer_pairwise ()\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 106,
        "n_words": 49,
        "vocab_size": 43,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 81,
        "n_ast_nodes": 132,
        "n_identifiers": 11,
        "d_id": 56774,
        "documentation": {
            "docstring": "Walk two filename lists in parallel, testing if each source is newer\n    than its corresponding target.  Return a pair of lists (sources,\n    targets) where source is newer than target, according to the semantics\n    of 'newer()'.\n    ",
            "n_words": 35,
            "vocab_size": 29,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 156730,
        "commit_id": "2820bae493a49cb1d0a6e376985c5473b8f04fa8",
        "repo": "dask",
        "path": "dask/array/core.py",
        "file_name": "core.py",
        "fun_name": "mean",
        "commit_message": "Don't include docs in ``Array`` methods, just refer to module docs (#9244)\n\nCo-authored-by: James Bourbeau <jrbourbeau@users.noreply.github.com>",
        "code": "def mean(self, axis=None, dtype=None, keepdims=False, split_every=None, out=None):\n        \n        from dask.array.reductions import mean\n\n        return mean(\n            self,\n            axis=axis,\n            dtype=dtype,\n            keepdims=keepdims,\n            split_every=split_every,\n            out=out,\n        )\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 114,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 60,
        "n_ast_nodes": 83,
        "n_identifiers": 10,
        "d_id": 36740,
        "documentation": {
            "docstring": "Returns the average of the array elements along given axis.\n\n        Refer to :func:`dask.array.mean` for full documentation.\n\n        See Also\n        --------\n        dask.array.mean : equivalent function\n        ",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 307538,
        "commit_id": "4e32bf2ac910e38695a1b9bf9b610c717db97998",
        "repo": "core",
        "path": "tests/helpers/test_entity_registry.py",
        "file_name": "test_entity_registry.py",
        "fun_name": "test_filter_on_load",
        "commit_message": "Drop old migration code from entity registry (#78278)",
        "code": "async def test_filter_on_load(hass, hass_storage):\n    \n    hass_storage[er.STORAGE_KEY] = {\n        \"version\": er.STORAGE_VERSION_MAJOR,\n        \"minor_version\": 1,\n        \"data\": {\n            \"entities\": [\n                {\n                    \"entity_id\": \"test.named\",\n                    \"platform\": \"super_platform\",\n                    \"unique_id\": \"with-name\",\n                    \"name\": \"registry override\",\n                },\n                # This entity's name should be None\n                {\n                    \"entity_id\": \"test.no_name\",\n                    \"platform\": \"super_platform\",\n                    \"unique_id\": \"without-name\",\n                },\n                {\n                    \"entity_id\": \"test.disabled_user\",\n                    \"platform\": \"super_platform\",\n                    \"unique_id\": \"disabled-user\",\n                    \"disabled_by\": \"user\",  # We store the string representation\n                },\n                {\n                    \"entity_id\": \"test.disabled_hass\",\n                    \"platform\": \"super_platform\",\n                    \"unique_id\": \"disabled-hass\",\n                    \"disabled_by\": \"hass\",  # We store the string representation\n                },\n                # This entry should have the entity_category reset to None\n                {\n                    \"entity_id\": \"test.system_entity\",\n                    \"platform\": \"super_platform\",\n                    \"unique_id\": \"system-entity\",\n                    \"entity_category\": \"system\",\n                },\n            ]\n        },\n    }\n\n    await er.async_load(hass)\n    registry = er.async_get(hass)\n\n    assert len(registry.entities) == 5\n    assert set(registry.entities.keys()) == {\n        \"test.disabled_hass\",\n        \"test.disabled_user\",\n        \"test.named\",\n        \"test.no_name\",\n        \"test.system_entity\",\n    }\n\n    entry_with_name = registry.async_get_or_create(\n        \"test\", \"super_platform\", \"with-name\"\n    )\n    entry_without_name = registry.async_get_or_create(\n        \"test\", \"super_platform\", \"without-name\"\n    )\n    assert entry_with_name.name == \"registry override\"\n    assert entry_without_name.name is None\n    assert not entry_with_name.disabled\n\n    entry_disabled_hass = registry.async_get_or_create(\n        \"test\", \"super_platform\", \"disabled-hass\"\n    )\n    entry_disabled_user = registry.async_get_or_create(\n        \"test\", \"super_platform\", \"disabled-user\"\n    )\n    assert entry_disabled_hass.disabled\n    assert entry_disabled_hass.disabled_by is er.RegistryEntryDisabler.HASS\n    assert entry_disabled_user.disabled\n    assert entry_disabled_user.disabled_by is er.RegistryEntryDisabler.USER\n\n    entry_system_category = registry.async_get_or_create(\n        \"test\", \"system_entity\", \"system-entity\"\n    )\n    assert entry_system_category.entity_category is None\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 919,
        "n_words": 178,
        "vocab_size": 92,
        "complexity": 1,
        "nloc": 77,
        "token_counts": 305,
        "n_ast_nodes": 535,
        "n_identifiers": 26,
        "d_id": 106309,
        "documentation": {
            "docstring": "Test we transform some data when loading from storage.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 21835,
        "commit_id": "8faa74cdc9da20cfdcc69f5ec29b91112c95b4c9",
        "repo": "pipenv",
        "path": "pipenv/vendor/tomlkit/toml_file.py",
        "file_name": "toml_file.py",
        "fun_name": "read",
        "commit_message": "Update tomlkit==0.9.2\n\nUsed:\n\n python -m invoke vendoring.update --package=tomlkit",
        "code": "def read(self) -> TOMLDocument:\n        \n        with open(self._path, encoding=\"utf-8\", newline=\"\") as f:\n            return loads(f.read())\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 37,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 4068,
        "documentation": {
            "docstring": "Read the file content as a :class:`tomlkit.toml_document.TOMLDocument`.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 60201,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/examples/pycaffe/layers/pascal_multilabel_datalayers.py",
        "file_name": "pascal_multilabel_datalayers.py",
        "fun_name": "load_pascal_annotation",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def load_pascal_annotation(index, pascal_root):\n    \n    classes = ('__background__',  # always index 0\n               'aeroplane', 'bicycle', 'bird', 'boat',\n               'bottle', 'bus', 'car', 'cat', 'chair',\n                         'cow', 'diningtable', 'dog', 'horse',\n                         'motorbike', 'person', 'pottedplant',\n                         'sheep', 'sofa', 'train', 'tvmonitor')\n    class_to_ind = dict(zip(classes, xrange(21)))\n\n    filename = osp.join(pascal_root, 'Annotations', index + '.xml')\n    # print 'Loading: {}'.format(filename)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 161,
        "n_words": 45,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 33,
        "token_counts": 317,
        "n_ast_nodes": 153,
        "n_identifiers": 11,
        "d_id": 12009,
        "documentation": {
            "docstring": "\n    This code is borrowed from Ross Girshick's FAST-RCNN code\n    (https://github.com/rbgirshick/fast-rcnn).\n    It parses the PASCAL .xml metadata files.\n    See publication for further details: (http://arxiv.org/abs/1504.08083).\n\n    Thanks Ross!\n\n    ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 215826,
        "commit_id": "a35b29b2651bf33c5d5b45e64bc7765ffde4aff4",
        "repo": "salt",
        "path": "tests/pytests/functional/states/file/test_rename.py",
        "file_name": "test_rename.py",
        "fun_name": "test_target_exists_force",
        "commit_message": "Add some funtional tests\n\nAdd functional tests for the following:\n- file.readlink\n- file.replace\n- file.symlink\n\nRemove unit tests for file.replace as they are duplicated in the added\nfunctional test",
        "code": "def test_target_exists_force(file, source):\n    \n    new_name = source.parent / \"new_name.txt\"\n    new_name.write_text(\"existing file\")\n    try:\n        file.rename(name=str(new_name), source=str(source), force=True)\n        assert new_name.exists()\n        assert not source.exists()\n        assert new_name.read_text() == \"Source content\"\n    finally:\n        new_name.unlink()\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 76,
        "n_words": 26,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 73,
        "n_ast_nodes": 127,
        "n_identifiers": 13,
        "d_id": 54193,
        "documentation": {
            "docstring": "\n    Test file.rename when there is an existing file with the new name and\n    force=True\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 7086,
        "commit_id": "48731ae5ca98d4a1e92374af30f060408f14d91a",
        "repo": "ludwig",
        "path": "ludwig/features/binary_feature.py",
        "file_name": "binary_feature.py",
        "fun_name": "cast_column",
        "commit_message": "Fix postprocessing on binary feature columns with number dtype (#2189)\n\n* Fixes binary postprocessing for number dtype\r\n\r\n* ensure calibration work retained\r\n\r\n* cleanup\r\n\r\n* removed script postprocessing caveat\r\n\r\n* added ray/dask test\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* adds mock.patch behavior\r\n\r\n* allow type inference for visualization\r\n\r\n* add pytest mark distributed\r\n\r\n* removed mock.patch call\r\n\r\n* add try/finally clause like test_ray.py\r\n\r\n* increasing epochs to 2 as workaround\r\n\r\n* increased number of samples and add back mock.patch\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def cast_column(column, backend):\n        \n        values = backend.df_engine.compute(column.drop_duplicates())\n\n        if strings_utils.values_are_pandas_numbers(values):\n            # If numbers, convert to float so it can be converted to bool\n            column = column.astype(float).astype(bool)\n        elif strings_utils.values_are_pandas_bools(values):\n            # If booleans, manually assign boolean values\n            column = backend.df_engine.map_objects(\n                column, lambda x: x.lower() in strings_utils.PANDAS_TRUE_STRS\n            ).astype(bool)\n        else:\n            # If neither numbers or booleans, they are strings (objects)\n            column = column.astype(object)\n        return column\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 193,
        "n_words": 59,
        "vocab_size": 46,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 91,
        "n_ast_nodes": 152,
        "n_identifiers": 18,
        "d_id": 1116,
        "documentation": {
            "docstring": "Cast column of dtype object to bool.\n\n        Unchecked casting to boolean when given a column of dtype object converts all non-empty cells to True. We check\n        the values of the column directly and manually determine the best dtype to use.\n        ",
            "n_words": 40,
            "vocab_size": 28,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 93031,
        "commit_id": "522d6f27c28dc5fd4d996ed605865c42fbda0da8",
        "repo": "sentry",
        "path": "src/sentry/utils/meta.py",
        "file_name": "meta.py",
        "fun_name": "enter",
        "commit_message": "ref: replace legacy compat.map with list comprehensions (#36372)",
        "code": "def enter(self, *path):\n        \n        return Meta(self._meta, path=self._path + [str(p) for p in path])\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 26,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 33,
        "n_ast_nodes": 52,
        "n_identifiers": 8,
        "d_id": 18968,
        "documentation": {
            "docstring": "\n        Enters into sub meta data at the specified path. This always returns a\n        new ``Meta`` object, regardless whether the path already exists.\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 181854,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/builtins/feature_set_selector.py",
        "file_name": "feature_set_selector.py",
        "fun_name": "_get_support_mask",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def _get_support_mask(self):\n        \n\n        n_features = len(self.feature_names)\n        mask = np.zeros(n_features, dtype=bool)\n        mask[np.asarray(self.feat_list_idx)] = True\n\n        return mask\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 49,
        "n_words": 14,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 41,
        "n_ast_nodes": 67,
        "n_identifiers": 12,
        "d_id": 43623,
        "documentation": {
            "docstring": "\n        Get the boolean mask indicating which features are selected\n        Returns\n        -------\n        support : boolean array of shape [# input features]\n            An element is True iff its corresponding feature is selected for\n            retention.\n        ",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 73589,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/table_block/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_do_not_render_html",
        "commit_message": "Reformat with black",
        "code": "def test_do_not_render_html(self):\n        \n        value = {\n            \"first_row_is_table_header\": False,\n            \"first_col_is_header\": False,\n            \"data\": [\n                [\"<p><strong>Test</strong></p>\", None, None],\n                [None, None, None],\n                [None, None, None],\n            ],\n        }\n\n        expected = \n\n        block = TableBlock()\n        result = block.render(value)\n        self.assertHTMLEqual(result, expected)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 171,
        "n_words": 32,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 71,
        "n_ast_nodes": 113,
        "n_identifiers": 9,
        "d_id": 16056,
        "documentation": {
            "docstring": "\n        Ensure that raw html doesn't render\n        by default.\n        \n            <table>\n                <tbody>\n                    <tr><td>&lt;p&gt;&lt;strong&gt;Test&lt;/strong&gt;&lt;/p&gt;</td><td></td><td></td></tr>\n                    <tr><td></td><td></td><td></td></tr>\n                    <tr><td></td><td></td><td></td></tr>\n                </tbody>\n            </table>\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 154,
            "language": "en"
        }
    },
    {
        "id": 321095,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/navigate.py",
        "file_name": "navigate.py",
        "fun_name": "path_up",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def path_up(url, count):\n    \n    urlutils.ensure_valid(url)\n    url = url.adjusted(QUrl.UrlFormattingOption.RemoveFragment | QUrl.UrlFormattingOption.RemoveQuery)\n    path = url.path(QUrl.ComponentFormattingOption.FullyEncoded)\n    if not path or path == '/':\n        raise Error(\"Can't go up!\")\n    for _i in range(0, min(count, path.count('/'))):\n        path = posixpath.join(path, posixpath.pardir)\n    path = posixpath.normpath(path)\n    url.setPath(path, QUrl.ParsingMode.StrictMode)\n    return url\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 81,
        "n_words": 40,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 111,
        "n_ast_nodes": 180,
        "n_identifiers": 24,
        "d_id": 117525,
        "documentation": {
            "docstring": "Helper method for :navigate when `where' is up.\n\n    Args:\n        url: The current url.\n        count: The number of levels to go up in the url.\n    ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 101899,
        "commit_id": "dab823a3eb7a5257cb1e0818ee10ed234d3de97f",
        "repo": "faceswap",
        "path": "lib/gui/display_command.py",
        "file_name": "display_command.py",
        "fun_name": "_smooth_amount_callback",
        "commit_message": "Typing - lib.gui.display_command",
        "code": "def _smooth_amount_callback(self, *args) -> None:\n        \n        try:\n            smooth_amount = self.vars[\"smoothgraph\"].get()\n        except tk.TclError:\n            # Don't update when there is no value in the variable\n            return\n        logger.debug(\"Updating graph smooth_amount: (new_value: %s, args: %s)\",\n                     smooth_amount, args)\n        for graph in self.subnotebook.children.values():\n            graph.calcs.set_smooth_amount(smooth_amount)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 136,
        "n_words": 37,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 62,
        "n_ast_nodes": 105,
        "n_identifiers": 16,
        "d_id": 21281,
        "documentation": {
            "docstring": " Update each graph's smooth amount on variable change ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 321240,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/completion/models/listcategory.py",
        "file_name": "listcategory.py",
        "fun_name": "set_pattern",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def set_pattern(self, val):\n        \n        if len(val) > 5000:  # avoid crash on huge search terms (#5973)\n            log.completion.warning(f\"Trimming {len(val)}-char pattern to 5000\")\n            val = val[:5000]\n        self._pattern = val\n        val = re.sub(r' +', r' ', val)  # See #1919\n        val = re.escape(val)\n        val = val.replace(r'\\ ', '.*')\n        rx = QRegularExpression(val, QRegularExpression.PatternOption.CaseInsensitiveOption)\n        qtutils.ensure_valid(rx)\n        self.setFilterRegularExpression(rx)\n        self.invalidate()\n        sortcol = 0\n        self.sort(sortcol)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 163,
        "n_words": 55,
        "vocab_size": 43,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 108,
        "n_ast_nodes": 188,
        "n_identifiers": 22,
        "d_id": 117601,
        "documentation": {
            "docstring": "Setter for pattern.\n\n        Args:\n            val: The value to set.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 207716,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_generic_relations_with_related_query_name",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_generic_relations_with_related_query_name(self):\n        \n        bookmark = Bookmark.objects.create(name=\"djangoproject\")\n        tag = FunkyTag.objects.create(content_object=bookmark, name=\"django\")\n        tag_url = reverse(\"admin:admin_views_funkytag_change\", args=(tag.id,))\n        should_contain = '<li>Funky tag: <a href=\"%s\">django' % tag_url\n        response = self.client.get(\n            reverse(\"admin:admin_views_bookmark_delete\", args=(bookmark.pk,))\n        )\n        self.assertContains(response, should_contain)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 96,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 84,
        "n_ast_nodes": 141,
        "n_identifiers": 20,
        "d_id": 52066,
        "documentation": {
            "docstring": "\n        If a deleted object has GenericForeignKey with\n        GenericRelation(related_query_name='...') pointing to it, those objects\n        should be listed for deletion.\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 186624,
        "commit_id": "7d9e9a49005de7961e84d2a7c608db57dbab3046",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/augeasparser.py",
        "file_name": "augeasparser.py",
        "fun_name": "parsed_paths",
        "commit_message": "Add typing to certbot.apache (#9071)\n\n* Add typing to certbot.apache\r\n\r\nCo-authored-by: Adrien Ferrand <ferrand.ad@gmail.com>",
        "code": "def parsed_paths(self) -> List[str]:\n        \n\n        res_paths: List[str] = []\n\n        paths = self.parser.existing_paths\n        for directory in paths:\n            for filename in paths[directory]:\n                res_paths.append(os.path.join(directory, filename))\n\n        return res_paths\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 84,
        "n_words": 23,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 57,
        "n_ast_nodes": 89,
        "n_identifiers": 14,
        "d_id": 45535,
        "documentation": {
            "docstring": "\n        Returns a list of file paths that have currently been parsed into the parser\n        tree. The returned list may include paths with wildcard characters, for\n        example: ['/etc/apache2/conf.d/*.load']\n\n        This is typically called on the root node of the ParserNode tree.\n\n        :returns: list of file paths of files that have been parsed\n        ",
            "n_words": 50,
            "vocab_size": 35,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 111340,
        "commit_id": "a322d6d5f2f85c2da6cded4fcd6143d41b5a9e96",
        "repo": "spaCy",
        "path": "spacy/pipeline/span_ruler.py",
        "file_name": "span_ruler.py",
        "fun_name": "ids",
        "commit_message": "Add SpanRuler component (#9880)\n\n* Add SpanRuler component\r\n\r\nAdd a `SpanRuler` component similar to `EntityRuler` that saves a list\r\nof matched spans to `Doc.spans[spans_key]`. The matches from the token\r\nand phrase matchers are deduplicated and sorted before assignment but\r\nare not otherwise filtered.\r\n\r\n* Update spacy/pipeline/span_ruler.py\r\n\r\nCo-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>\r\n\r\n* Fix cast\r\n\r\n* Add self.key property\r\n\r\n* Use number of patterns as length\r\n\r\n* Remove patterns kwarg from init\r\n\r\n* Update spacy/tests/pipeline/test_span_ruler.py\r\n\r\nCo-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>\r\n\r\n* Add options for spans filter and setting to ents\r\n\r\n* Add `spans_filter` option as a registered function'\r\n* Make `spans_key` optional and if `None`, set to `doc.ents` instead of\r\n`doc.spans[spans_key]`.\r\n\r\n* Update and generalize tests\r\n\r\n* Add test for setting doc.ents, fix key property type\r\n\r\n* Fix typing\r\n\r\n* Allow independent doc.spans and doc.ents\r\n\r\n* If `spans_key` is set, set `doc.spans` with `spans_filter`.\r\n* If `annotate_ents` is set, set `doc.ents` with `ents_fitler`.\r\n  * Use `util.filter_spans` by default as `ents_filter`.\r\n  * Use a custom warning if the filter does not work for `doc.ents`.\r\n\r\n* Enable use of SpanC.id in Span\r\n\r\n* Support id in SpanRuler as Span.id\r\n\r\n* Update types\r\n\r\n* `id` can only be provided as string (already by `PatternType`\r\ndefinition)\r\n\r\n* Update all uses of Span.id/ent_id in Doc\r\n\r\n* Rename Span id kwarg to span_id\r\n\r\n* Update types and docs\r\n\r\n* Add ents filter to mimic EntityRuler overwrite_ents\r\n\r\n* Refactor `ents_filter` to take `entities, spans` args for more\r\n  filtering options\r\n* Give registered filters more descriptive names\r\n* Allow registered `filter_spans` filter\r\n  (`spacy.first_longest_spans_filter.v1`) to take any number of\r\n  `Iterable[Span]` objects as args so it can be used for spans filter\r\n  or ents filter\r\n\r\n* Implement future entity ruler as span ruler\r\n\r\nImplement a compatible `entity_ruler` as `future_entity_ruler` using\r\n`SpanRuler` as the underlying component:\r\n* Add `sort_key` and `sort_reverse` to allow the sorting behavior to be\r\n  customized. (Necessary for the same sorting/filtering as in\r\n  `EntityRuler`.)\r\n* Implement `overwrite_overlapping_ents_filter` and\r\n  `preserve_existing_ents_filter` to support\r\n  `EntityRuler.overwrite_ents` settings.\r\n* Add `remove_by_id` to support `EntityRuler.remove` functionality.\r\n* Refactor `entity_ruler` tests to parametrize all tests to test both\r\n  `entity_ruler` and `future_entity_ruler`\r\n* Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns`\r\n  properties.\r\n\r\nAdditional changes:\r\n\r\n* Move all config settings to top-level attributes to avoid duplicating\r\n  settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of\r\n  casting.)\r\n\r\n* Format\r\n\r\n* Fix filter make method name\r\n\r\n* Refactor to use same error for removing by label or ID\r\n\r\n* Also provide existing spans to spans filter\r\n\r\n* Support ids property\r\n\r\n* Remove token_patterns and phrase_patterns\r\n\r\n* Update docstrings\r\n\r\n* Add span ruler docs\r\n\r\n* Fix types\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>\r\n\r\n* Move sorting into filters\r\n\r\n* Check for all tokens in seen tokens in entity ruler filters\r\n\r\n* Remove registered sort key\r\n\r\n* Set Token.ent_id in a backwards-compatible way in Doc.set_ents\r\n\r\n* Remove sort options from API docs\r\n\r\n* Update docstrings\r\n\r\n* Rename entity ruler filters\r\n\r\n* Fix and parameterize scoring\r\n\r\n* Add id to Span API docs\r\n\r\n* Fix typo in API docs\r\n\r\n* Include explicit labeled=True for scorer\r\n\r\nCo-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>",
        "code": "def ids(self) -> Tuple[str, ...]:\n        \n        return tuple(\n            sorted(set([cast(str, p.get(\"id\")) for p in self._patterns]) - set([None]))\n        )\n",
        "url": "https://github.com/explosion/spaCy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 48,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 49,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 24383,
        "documentation": {
            "docstring": "All IDs present in the match patterns.\n\n        RETURNS (set): The string IDs.\n\n        DOCS: https://spacy.io/api/spanruler#ids\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 132826,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/trial.py",
        "file_name": "trial.py",
        "fun_name": "__call__",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def __call__(self, checkpoint):\n        \n        if not self.runner:\n            return\n\n        if checkpoint.storage == Checkpoint.PERSISTENT and checkpoint.value:\n            checkpoint_path = checkpoint.value\n\n            logger.debug(\n                \"Trial %s: Deleting checkpoint %s\", self.trial_id, checkpoint_path\n            )\n\n            # TODO(ujvl): Batch remote deletes.\n            # We first delete the remote checkpoint. If it is on the same\n            # node as the driver, it will also remove the local copy.\n            ray.get(self.runner.delete_checkpoint.remote(checkpoint_path))\n\n            # Delete local copy, if any exists.\n            if os.path.exists(checkpoint_path):\n                try:\n                    checkpoint_dir = TrainableUtil.find_checkpoint_dir(checkpoint_path)\n                    shutil.rmtree(checkpoint_dir)\n                except FileNotFoundError:\n                    logger.debug(\"Local checkpoint dir not found during deletion.\")\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 312,
        "n_words": 79,
        "vocab_size": 63,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 95,
        "n_ast_nodes": 162,
        "n_identifiers": 25,
        "d_id": 29818,
        "documentation": {
            "docstring": "Requests checkpoint deletion asynchronously.\n\n        Args:\n            checkpoint (Checkpoint): Checkpoint to delete.\n        ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 246626,
        "commit_id": "64c73c6ac88a740ee480a0ad1f9afc8596bccfa4",
        "repo": "synapse",
        "path": "tests/rest/client/test_sync.py",
        "file_name": "test_sync.py",
        "fun_name": "test_unread_counts",
        "commit_message": "Add type hints to `tests/rest/client` (#12066)",
        "code": "def test_unread_counts(self) -> None:\n        \n\n        # Check that our own messages don't increase the unread count.\n        self.helper.send(self.room_id, \"hello\", tok=self.tok)\n        self._check_unread_count(0)\n\n        # Join the new user and check that this doesn't increase the unread count.\n        self.helper.join(room=self.room_id, user=self.user2, tok=self.tok2)\n        self._check_unread_count(0)\n\n        # Check that the new user sending a message increases our unread count.\n        res = self.helper.send(self.room_id, \"hello\", tok=self.tok2)\n        self._check_unread_count(1)\n\n        # Send a read receipt to tell the server we've read the latest event.\n        body = json.dumps({\"m.read\": res[\"event_id\"]}).encode(\"utf8\")\n        channel = self.make_request(\n            \"POST\",\n            \"/rooms/%s/read_markers\" % self.room_id,\n            body,\n            access_token=self.tok,\n        )\n        self.assertEqual(channel.code, 200, channel.json_body)\n\n        # Check that the unread counter is back to 0.\n        self._check_unread_count(0)\n\n        # Check that hidden read receipts don't break unread counts\n        res = self.helper.send(self.room_id, \"hello\", tok=self.tok2)\n        self._check_unread_count(1)\n\n        # Send a read receipt to tell the server we've read the latest event.\n        body = json.dumps({ReadReceiptEventFields.MSC2285_HIDDEN: True}).encode(\"utf8\")\n        channel = self.make_request(\n            \"POST\",\n            \"/rooms/%s/receipt/m.read/%s\" % (self.room_id, res[\"event_id\"]),\n            body,\n            access_token=self.tok,\n        )\n        self.assertEqual(channel.code, 200, channel.json_body)\n\n        # Check that the unread counter is back to 0.\n        self._check_unread_count(0)\n\n        # Check that room name changes increase the unread counter.\n        self.helper.send_state(\n            self.room_id,\n            \"m.room.name\",\n            {\"name\": \"my super room\"},\n            tok=self.tok2,\n        )\n        self._check_unread_count(1)\n\n        # Check that room topic changes increase the unread counter.\n        self.helper.send_state(\n            self.room_id,\n            \"m.room.topic\",\n            {\"topic\": \"welcome!!!\"},\n            tok=self.tok2,\n        )\n        self._check_unread_count(2)\n\n        # Check that encrypted messages increase the unread counter.\n        self.helper.send_event(self.room_id, EventTypes.Encrypted, {}, tok=self.tok2)\n        self._check_unread_count(3)\n\n        # Check that custom events with a body increase the unread counter.\n        self.helper.send_event(\n            self.room_id,\n            \"org.matrix.custom_type\",\n            {\"body\": \"hello\"},\n            tok=self.tok2,\n        )\n        self._check_unread_count(4)\n\n        # Check that edits don't increase the unread counter.\n        self.helper.send_event(\n            room_id=self.room_id,\n            type=EventTypes.Message,\n            content={\n                \"body\": \"hello\",\n                \"msgtype\": \"m.text\",\n                \"m.relates_to\": {\"rel_type\": RelationTypes.REPLACE},\n            },\n            tok=self.tok2,\n        )\n        self._check_unread_count(4)\n\n        # Check that notices don't increase the unread counter.\n        self.helper.send_event(\n            room_id=self.room_id,\n            type=EventTypes.Message,\n            content={\"body\": \"hello\", \"msgtype\": \"m.notice\"},\n            tok=self.tok2,\n        )\n        self._check_unread_count(4)\n\n        # Check that tombstone events changes increase the unread counter.\n        self.helper.send_state(\n            self.room_id,\n            EventTypes.Tombstone,\n            {\"replacement_room\": \"!someroom:test\"},\n            tok=self.tok2,\n        )\n        self._check_unread_count(5)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1076,
        "n_words": 290,
        "vocab_size": 121,
        "complexity": 1,
        "nloc": 76,
        "token_counts": 498,
        "n_ast_nodes": 815,
        "n_identifiers": 35,
        "d_id": 71305,
        "documentation": {
            "docstring": "Tests that /sync returns the right value for the unread count (MSC2654).",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 208719,
        "commit_id": "dc5bcc1c50892a5128fcf128af28887226144927",
        "repo": "ipython",
        "path": "IPython/core/history.py",
        "file_name": "history.py",
        "fun_name": "get_tail",
        "commit_message": "This fixed the mixing of multiple history seen in #13631\n\nIt forces get_tail to put the current session last in the returned\nresults.",
        "code": "def get_tail(self, n=10, raw=True, output=False, include_latest=False):\n        \n        self.writeout_cache()\n        if not include_latest:\n            n += 1\n        # cursor/line/entry\n        this_cur = list(\n            self._run_sql(\n                \"WHERE session == ? ORDER BY line DESC LIMIT ?  \",\n                (self.session_number, n),\n                raw=raw,\n                output=output,\n            )\n        )\n        other_cur = list(\n            self._run_sql(\n                \"WHERE session != ? ORDER BY session DESC, line DESC LIMIT ?\",\n                (self.session_number, n),\n                raw=raw,\n                output=output,\n            )\n        )\n\n        everything = this_cur + other_cur\n\n        everything = everything[:n]\n\n        if not include_latest:\n            return list(everything)[:0:-1]\n        return list(everything)[::-1]\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 344,
        "n_words": 73,
        "vocab_size": 44,
        "complexity": 3,
        "nloc": 25,
        "token_counts": 128,
        "n_ast_nodes": 198,
        "n_identifiers": 13,
        "d_id": 52478,
        "documentation": {
            "docstring": "Get the last n lines from the history database.\n\n        Most recent entry last.\n\n        Completion will be reordered so that that the last ones are when\n        possible from current session.\n\n        Parameters\n        ----------\n        n : int\n            The number of lines to get\n        raw, output : bool\n            See :meth:`get_range`\n        include_latest : bool\n            If False (default), n+1 lines are fetched, and the latest one\n            is discarded. This is intended to be used where the function\n            is called by a user command, which it should not return.\n\n        Returns\n        -------\n        Tuples as :meth:`get_range`\n        ",
            "n_words": 87,
            "vocab_size": 68,
            "n_whitespaces": 226,
            "language": "en"
        }
    },
    {
        "id": 43879,
        "commit_id": "2fdc23333909096d427171002582e2906f8bbc0a",
        "repo": "airflow",
        "path": "airflow/providers_manager.py",
        "file_name": "providers_manager.py",
        "fun_name": "_discover_all_airflow_builtin_providers_from_local_sources",
        "commit_message": "Fix remaining mypy issues in \"core\" Airflow (#20795)\n\nCo-authored-by: Josh Fell <josh.d.fell@astronomer.io>\r\nCo-authored-by: Tzu-ping Chung <tp@astronomer.io>\r\nCo-authored-by: Jarek Potiuk <jarek@potiuk.com>",
        "code": "def _discover_all_airflow_builtin_providers_from_local_sources(self) -> None:\n        \n        try:\n            import airflow.providers\n        except ImportError:\n            log.info(\"You have no providers installed.\")\n            return\n        try:\n            for path in airflow.providers.__path__:  # type: ignore[attr-defined]\n                self._add_provider_info_from_local_source_files_on_path(path)\n        except Exception as e:\n            log.warning(\"Error when loading 'provider.yaml' files from airflow sources: %s\", e)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 144,
        "n_words": 38,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 19,
        "token_counts": 54,
        "n_ast_nodes": 96,
        "n_identifiers": 13,
        "d_id": 8082,
        "documentation": {
            "docstring": "\n        Finds all built-in airflow providers if airflow is run from the local sources.\n        It finds `provider.yaml` files for all such providers and registers the providers using those.\n\n        This 'provider.yaml' scanning takes precedence over scanning packages installed\n        in case you have both sources and packages installed, the providers will be loaded from\n        the \"airflow\" sources rather than from the packages.\n        ",
            "n_words": 59,
            "vocab_size": 44,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 260489,
        "commit_id": "47dd54f727f09a47e84fb4cb53d33f9b0f239edb",
        "repo": "scikit-learn",
        "path": "sklearn/covariance/_robust_covariance.py",
        "file_name": "_robust_covariance.py",
        "fun_name": "fit",
        "commit_message": "MAINT validate parameter in `EmpiricalCovariance`, `MinCovDet`, and `EllipticEnvelope` (#23842)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def fit(self, X, y=None):\n        \n        self._validate_params()\n        X = self._validate_data(X, ensure_min_samples=2, estimator=\"MinCovDet\")\n        random_state = check_random_state(self.random_state)\n        n_samples, n_features = X.shape\n        # check that the empirical covariance is full rank\n        if (linalg.svdvals(np.dot(X.T, X)) > 1e-8).sum() != n_features:\n            warnings.warn(\n                \"The covariance matrix associated to your dataset is not full rank\"\n            )\n        # compute and store raw estimates\n        raw_location, raw_covariance, raw_support, raw_dist = fast_mcd(\n            X,\n            support_fraction=self.support_fraction,\n            cov_computation_method=self._nonrobust_covariance,\n            random_state=random_state,\n        )\n        if self.assume_centered:\n            raw_location = np.zeros(n_features)\n            raw_covariance = self._nonrobust_covariance(\n                X[raw_support], assume_centered=True\n            )\n            # get precision matrix in an optimized way\n            precision = linalg.pinvh(raw_covariance)\n            raw_dist = np.sum(np.dot(X, precision) * X, 1)\n        self.raw_location_ = raw_location\n        self.raw_covariance_ = raw_covariance\n        self.raw_support_ = raw_support\n        self.location_ = raw_location\n        self.support_ = raw_support\n        self.dist_ = raw_dist\n        # obtain consistency at normal models\n        self.correct_covariance(X)\n        # re-weight estimator\n        self.reweight_covariance(X)\n\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 439,
        "n_words": 123,
        "vocab_size": 90,
        "complexity": 3,
        "nloc": 31,
        "token_counts": 211,
        "n_ast_nodes": 331,
        "n_identifiers": 41,
        "d_id": 76285,
        "documentation": {
            "docstring": "Fit a Minimum Covariance Determinant with the FastMCD algorithm.\n\n        Parameters\n        ----------\n        X : array-like of shape (n_samples, n_features)\n            Training data, where `n_samples` is the number of samples\n            and `n_features` is the number of features.\n\n        y : Ignored\n            Not used, present for API consistency by convention.\n\n        Returns\n        -------\n        self : object\n            Returns the instance itself.\n        ",
            "n_words": 54,
            "vocab_size": 44,
            "n_whitespaces": 154,
            "language": "en"
        }
    },
    {
        "id": 154526,
        "commit_id": "1dc16415333bf2428ee2b1f4d31ff94e66b9a0a6",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py",
        "file_name": "partition_manager.py",
        "fun_name": "from_pandas",
        "commit_message": "REFACTOR-#5009: use RayWrapper.materialize instead of ray.get (#5010)\n\nSigned-off-by: Myachev <anatoly.myachev@intel.com>",
        "code": "def from_pandas(cls, df, return_dims=False):\n        \n        num_splits = GpuCount.get()\n        put_func = cls._partition_class.put\n        # For now, we default to row partitioning\n        pandas_dfs = split_result_of_axis_func_pandas(0, num_splits, df)\n        keys = [\n            put_func(cls._get_gpu_managers()[i], pandas_dfs[i])\n            for i in range(num_splits)\n        ]\n        keys = RayWrapper.materialize(keys)\n        parts = cls._create_partitions(keys, cls._get_gpu_managers()).reshape(\n            (num_splits, 1)\n        )\n        if not return_dims:\n            return parts\n        else:\n            row_lengths = [len(df.index) for df in pandas_dfs]\n            col_widths = [\n                len(df.columns)\n            ]  # single value since we only have row partitions\n            return parts, row_lengths, col_widths\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 262,
        "n_words": 74,
        "vocab_size": 56,
        "complexity": 4,
        "nloc": 20,
        "token_counts": 132,
        "n_ast_nodes": 206,
        "n_identifiers": 26,
        "d_id": 36049,
        "documentation": {
            "docstring": "\n        Create partitions from ``pandas.DataFrame/pandas.Series``.\n\n        Parameters\n        ----------\n        df : pandas.DataFrame/pandas.Series\n            A ``pandas.DataFrame`` to add.\n        return_dims : boolean, default: False\n            Is return dimensions or not.\n\n        Returns\n        -------\n        list or tuple\n            List of partitions in case `return_dims` == False,\n            tuple (partitions, row lengths, col widths) in other case.\n        ",
            "n_words": 45,
            "vocab_size": 40,
            "n_whitespaces": 153,
            "language": "en"
        }
    },
    {
        "id": 132059,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/automl/genetic_searcher.py",
        "file_name": "genetic_searcher.py",
        "fun_name": "_crossover",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _crossover(candidate):\n        \n        sample_index1 = np.random.choice(len(candidate))\n        sample_index2 = np.random.choice(len(candidate))\n        sample_1 = candidate[sample_index1]\n        sample_2 = candidate[sample_index2]\n        cross_index = int(len(sample_1) * np.random.uniform(low=0.3, high=0.7))\n        logger.info(\n            LOGGING_PREFIX + \"Perform crossover between %sth and %sth at index=%s\",\n            sample_index1,\n            sample_index2,\n            cross_index,\n        )\n\n        next_gen = []\n        for i in range(len(sample_1)):\n            sample = sample_2[i] if i > cross_index else sample_1[i]\n            next_gen.append(sample)\n        return next_gen\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 197,
        "n_words": 54,
        "vocab_size": 43,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 125,
        "n_ast_nodes": 190,
        "n_identifiers": 23,
        "d_id": 29658,
        "documentation": {
            "docstring": "Perform crossover action to candidates.\n\n        For example, new gene = 60% sample_1 + 40% sample_2.\n\n        Args:\n            candidate: List of candidate genes (encodings).\n\n        Examples:\n            >>> # Genes that represent 3 parameters\n            >>> gene1 = np.array([[0, 0, 1], [0, 1], [1, 0]])\n            >>> gene2 = np.array([[0, 1, 0], [1, 0], [0, 1]])\n            >>> new_gene = _crossover([gene1, gene2])\n            >>> # new_gene could be the first [n=1] parameters of\n            >>> # gene1 + the rest of gene2\n            >>> # in which case:\n            >>> #   new_gene[0] = gene1[0]\n            >>> #   new_gene[1] = gene2[1]\n            >>> #   new_gene[2] = gene1[1]\n\n        Returns:\n            New gene (encoding)\n        ",
            "n_words": 97,
            "vocab_size": 62,
            "n_whitespaces": 270,
            "language": "en"
        }
    },
    {
        "id": 309801,
        "commit_id": "dadcc5ebcbcf951ff677568b281c5897d990c8ae",
        "repo": "core",
        "path": "homeassistant/components/august/activity.py",
        "file_name": "activity.py",
        "fun_name": "get_latest_device_activity",
        "commit_message": "spelling: components/august (#64232)\n\nCo-authored-by: Josh Soref <jsoref@users.noreply.github.com>",
        "code": "def get_latest_device_activity(self, device_id, activity_types):\n        \n        if device_id not in self._latest_activities:\n            return None\n\n        latest_device_activities = self._latest_activities[device_id]\n        latest_activity = None\n\n        for activity_type in activity_types:\n            if activity_type in latest_device_activities:\n                if (\n                    latest_activity is not None\n                    and latest_device_activities[activity_type].activity_start_time\n                    <= latest_activity.activity_start_time\n                ):\n                    continue\n                latest_activity = latest_device_activities[activity_type]\n\n        return latest_activity\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 227,
        "n_words": 42,
        "vocab_size": 28,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 69,
        "n_ast_nodes": 106,
        "n_identifiers": 9,
        "d_id": 108496,
        "documentation": {
            "docstring": "Return latest activity that is one of the activity_types.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 292459,
        "commit_id": "b19bf9b147f4321e89d1f7f01e68337f2102f460",
        "repo": "core",
        "path": "tests/components/dlna_dms/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "upnp_factory_mock",
        "commit_message": "Add dlna_dms integration to support DLNA Digital Media Servers (#66437)",
        "code": "def upnp_factory_mock() -> Iterable[Mock]:\n    \n    with patch(\n        \"homeassistant.components.dlna_dms.dms.UpnpFactory\",\n        autospec=True,\n        spec_set=True,\n    ) as upnp_factory:\n        upnp_device = create_autospec(UpnpDevice, instance=True)\n        upnp_device.name = MOCK_DEVICE_NAME\n        upnp_device.udn = MOCK_DEVICE_UDN\n        upnp_device.device_url = MOCK_DEVICE_LOCATION\n        upnp_device.device_type = MOCK_DEVICE_TYPE\n        upnp_device.available = True\n        upnp_device.parent_device = None\n        upnp_device.root_device = upnp_device\n        upnp_device.all_devices = [upnp_device]\n        upnp_device.services = {\n            \"urn:schemas-upnp-org:service:ContentDirectory:1\": create_autospec(\n                UpnpService,\n                instance=True,\n                service_type=\"urn:schemas-upnp-org:service:ContentDirectory:1\",\n                service_id=\"urn:upnp-org:serviceId:ContentDirectory\",\n            ),\n            \"urn:schemas-upnp-org:service:ConnectionManager:1\": create_autospec(\n                UpnpService,\n                instance=True,\n                service_type=\"urn:schemas-upnp-org:service:ConnectionManager:1\",\n                service_id=\"urn:upnp-org:serviceId:ConnectionManager\",\n            ),\n        }\n        seal(upnp_device)\n        upnp_factory_instance = upnp_factory.return_value\n        upnp_factory_instance.async_create_device.return_value = upnp_device\n\n        yield upnp_factory_instance\n\n\n@pytest.fixture",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 366,
        "n_words": 68,
        "vocab_size": 50,
        "complexity": 1,
        "nloc": 34,
        "token_counts": 143,
        "n_ast_nodes": 241,
        "n_identifiers": 33,
        "d_id": 91545,
        "documentation": {
            "docstring": "Mock the UpnpFactory class to construct DMS-style UPnP devices.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 203320,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/conf/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_setup",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _setup(self, name=None):\n        \n        settings_module = os.environ.get(ENVIRONMENT_VARIABLE)\n        if not settings_module:\n            desc = (\"setting %s\" % name) if name else \"settings\"\n            raise ImproperlyConfigured(\n                \"Requested %s, but settings are not configured. \"\n                \"You must either define the environment variable %s \"\n                \"or call settings.configure() before accessing settings.\"\n                % (desc, ENVIRONMENT_VARIABLE)\n            )\n\n        self._wrapped = Settings(settings_module)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 172,
        "n_words": 51,
        "vocab_size": 45,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 56,
        "n_ast_nodes": 99,
        "n_identifiers": 12,
        "d_id": 50300,
        "documentation": {
            "docstring": "\n        Load the settings module pointed to by the environment variable. This\n        is used the first time settings are needed, if the user hasn't\n        configured settings manually.\n        ",
            "n_words": 26,
            "vocab_size": 21,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 75054,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/image_operations.py",
        "file_name": "image_operations.py",
        "fun_name": "transform_vector",
        "commit_message": "Reformat with black",
        "code": "def transform_vector(self, vector):\n        \n        return Vector(\n            (vector.x + self.offset[0]) * self.scale[0],\n            (vector.y + self.offset[1]) * self.scale[1],\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 59,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 52,
        "n_ast_nodes": 78,
        "n_identifiers": 8,
        "d_id": 16345,
        "documentation": {
            "docstring": "\n        Transforms the given vector into the coordinate space of the final image.\n\n        Use this to find out where a point on the source image would end up in the\n        final image after cropping/resizing has been performed.\n\n        Returns a new vector.\n        ",
            "n_words": 40,
            "vocab_size": 33,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 261762,
        "commit_id": "1f3c1be77a5b15d6bc1a5bfd9eb64315928679b1",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/tests/test_discretization.py",
        "file_name": "test_discretization.py",
        "fun_name": "test_kbinsdiscretizer_effect_sample_weight",
        "commit_message": "ENH add support for sample_weight in KBinsDiscretizer with strategy=\"quantile\" (#24935)\n\nCo-authored-by: seladus <clement.blancovolle@insa-rouen.fr>\r\nCo-authored-by: Seladus <71873495+Seladus@users.noreply.github.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_kbinsdiscretizer_effect_sample_weight():\n    \n    X = np.array([[-2], [-1], [1], [3], [500], [1000]])\n    # add a large number of bins such that each sample with a non-null weight\n    # will be used as bin edge\n    est = KBinsDiscretizer(n_bins=10, encode=\"ordinal\", strategy=\"quantile\")\n    est.fit(X, sample_weight=[1, 1, 1, 1, 0, 0])\n    assert_allclose(est.bin_edges_[0], [-2, -1, 1, 3])\n    assert_allclose(est.transform(X), [[0.0], [1.0], [2.0], [2.0], [2.0], [2.0]])\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 80,
        "n_words": 56,
        "vocab_size": 48,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 145,
        "n_ast_nodes": 194,
        "n_identifiers": 14,
        "d_id": 76979,
        "documentation": {
            "docstring": "Check the impact of `sample_weight` one computed quantiles.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 259752,
        "commit_id": "0822851f5cb17827939a7d7b4f8c84f43184ae89",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/_bisect_k_means.py",
        "file_name": "_bisect_k_means.py",
        "fun_name": "_predict_recursive",
        "commit_message": "FEA Bisecting K-Means (#20031)\n\nCo-authored-by: Gael Varoquaux <gael.varoquaux@normalesup.org>\r\nCo-authored-by: Tom Dupré la Tour <tom.dupre-la-tour@m4x.org>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def _predict_recursive(self, X, x_squared_norms, sample_weight, cluster_node):\n        \n        if cluster_node.left is None:\n            # This cluster has no subcluster. Labels are just the label of the cluster.\n            return np.full(X.shape[0], cluster_node.label, dtype=np.int32)\n\n        # Determine if data points belong to the left or right subcluster\n        centers = np.vstack((cluster_node.left.center, cluster_node.right.center))\n        if hasattr(self, \"_X_mean\"):\n            centers += self._X_mean\n\n        cluster_labels = _labels_inertia_threadpool_limit(\n            X,\n            sample_weight,\n            x_squared_norms,\n            centers,\n            self._n_threads,\n            return_inertia=False,\n        )\n        mask = cluster_labels == 0\n\n        # Compute the labels for each subset of the data points.\n        labels = np.full(X.shape[0], -1, dtype=np.int32)\n\n        labels[mask] = self._predict_recursive(\n            X[mask], x_squared_norms[mask], sample_weight[mask], cluster_node.left\n        )\n\n        labels[~mask] = self._predict_recursive(\n            X[~mask], x_squared_norms[~mask], sample_weight[~mask], cluster_node.right\n        )\n\n        return labels\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 325,
        "n_words": 99,
        "vocab_size": 70,
        "complexity": 3,
        "nloc": 23,
        "token_counts": 186,
        "n_ast_nodes": 272,
        "n_identifiers": 25,
        "d_id": 75897,
        "documentation": {
            "docstring": "Predict recursively by going down the hierarchical tree.\n\n        Parameters\n        ----------\n        X : {ndarray, csr_matrix} of shape (n_samples, n_features)\n            The data points, currently assigned to `cluster_node`, to predict between\n            the subclusters of this node.\n\n        x_squared_norms : ndarray of shape (n_samples,)\n            Squared euclidean norm of each data point.\n\n        sample_weight : ndarray of shape (n_samples,)\n            The weights for each observation in X.\n\n        cluster_node : _BisectingTree node object\n            The cluster node of the hierarchical tree.\n\n        Returns\n        -------\n        labels : ndarray of shape (n_samples,)\n            Index of the cluster each sample belongs to.\n        ",
            "n_words": 87,
            "vocab_size": 56,
            "n_whitespaces": 223,
            "language": "en"
        }
    },
    {
        "id": 75348,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_get",
        "commit_message": "Reformat with black",
        "code": "def test_get(self):\n        \n        # Generate signature\n        signature = generate_signature(self.image.id, \"fill-800x600\")\n\n        # Get the image\n        response = self.client.get(\n            reverse(\n                \"wagtailimages_serve\", args=(signature, self.image.id, \"fill-800x600\")\n            )\n        )\n\n        # Check response\n        self.assertEqual(response.status_code, 200)\n        self.assertTrue(response.streaming)\n        self.assertEqual(response[\"Content-Type\"], \"image/png\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 138,
        "n_words": 31,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 74,
        "n_ast_nodes": 127,
        "n_identifiers": 15,
        "d_id": 16397,
        "documentation": {
            "docstring": "\n        Test a valid GET request to the view\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 298672,
        "commit_id": "7b1d5fb10af9cf71fae27f9e1020e18bd1fc2510",
        "repo": "core",
        "path": "homeassistant/components/ecobee/climate.py",
        "file_name": "climate.py",
        "fun_name": "set_temp_hold",
        "commit_message": "Use climate enums in ecobee (#70632)",
        "code": "def set_temp_hold(self, temp):\n        \n        if self.hvac_mode in (HVACMode.HEAT, HVACMode.COOL):\n            heat_temp = temp\n            cool_temp = temp\n        else:\n            delta = self.thermostat[\"settings\"][\"heatCoolMinDelta\"] / 10.0\n            heat_temp = temp - delta\n            cool_temp = temp + delta\n        self.set_auto_temp_hold(heat_temp, cool_temp)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 115,
        "n_words": 32,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 102,
        "n_identifiers": 12,
        "d_id": 97614,
        "documentation": {
            "docstring": "Set temperature hold in modes other than auto.\n\n        Ecobee API: It is good practice to set the heat and cool hold\n        temperatures to be the same, if the thermostat is in either heat, cool,\n        auxHeatOnly, or off mode. If the thermostat is in auto mode, an\n        additional rule is required. The cool hold temperature must be greater\n        than the heat hold temperature by at least the amount in the\n        heatCoolMinDelta property.\n        https://www.ecobee.com/home/developer/api/examples/ex5.shtml\n        ",
            "n_words": 72,
            "vocab_size": 49,
            "n_whitespaces": 128,
            "language": "en"
        }
    },
    {
        "id": 85040,
        "commit_id": "033d2615f6614b06c8268fe60c6ee2a37892c204",
        "repo": "zulip",
        "path": "zerver/tests/test_retention.py",
        "file_name": "test_retention.py",
        "fun_name": "test_archiving_interrupted",
        "commit_message": "ruff: Fix B017 `assertRaises(Exception):` should be considered evil.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def test_archiving_interrupted(self) -> None:\n        \n        expired_msg_ids = self._make_expired_zulip_messages(7)\n        expired_usermsg_ids = self._get_usermessage_ids(expired_msg_ids)\n\n        # Insert an exception near the end of the archiving process of a chunk:\n        with mock.patch(\n            \"zerver.lib.retention.delete_messages\", side_effect=Exception(\"delete_messages error\")\n        ):\n            with self.assertRaisesRegex(Exception, r\"^delete_messages error$\"):\n                # Specify large chunk_size to ensure things happen in a single batch\n                archive_messages(chunk_size=1000)\n\n            # Archiving code has been executed, but because we got an exception, things should have been rolled back:\n            self._verify_archive_data([], [])\n\n            self.assertEqual(\n                set(Message.objects.filter(id__in=expired_msg_ids).values_list(\"id\", flat=True)),\n                set(expired_msg_ids),\n            )\n            self.assertEqual(\n                set(\n                    UserMessage.objects.filter(id__in=expired_usermsg_ids).values_list(\n                        \"id\", flat=True\n                    )\n                ),\n                set(expired_usermsg_ids),\n            )\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 377,
        "n_words": 81,
        "vocab_size": 68,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 132,
        "n_ast_nodes": 223,
        "n_identifiers": 23,
        "d_id": 17912,
        "documentation": {
            "docstring": "Check that queries get rolled back to a consistent state\n        if archiving gets interrupted in the middle of processing a chunk.",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 183789,
        "commit_id": "bfb962bacf274373e5706090cd854b6aa0857270",
        "repo": "textual",
        "path": "tests/test_xterm_parser.py",
        "file_name": "test_xterm_parser.py",
        "fun_name": "test_unknown_sequence_followed_by_known_sequence",
        "commit_message": "Backtracking unknown escape sequences, various tests for XTermParser",
        "code": "def test_unknown_sequence_followed_by_known_sequence(parser):\n    \n    unknown_sequence = \"\\x1b[?\"\n    known_sequence = \"\\x1b[8~\"  # key = 'end'\n\n    sequence = unknown_sequence + known_sequence\n    events = parser.feed(sequence)\n\n    assert next(events).key == \"escape\"\n    assert next(events).key == \"[\"\n    assert next(events).key == \"?\"\n    assert next(events).key == \"end\"\n\n    with pytest.raises(StopIteration):\n        next(events)\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 77,
        "n_words": 39,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 73,
        "n_ast_nodes": 137,
        "n_identifiers": 12,
        "d_id": 44340,
        "documentation": {
            "docstring": " When we feed the parser an unknown sequence followed by a known\n    sequence. The characters in the unknown sequence are delivered as keys,\n    and the known escape sequence that follows is delivered as expected.\n    ",
            "n_words": 34,
            "vocab_size": 26,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 104689,
        "commit_id": "98f2f1390d558d54faa84ae9d2c503d624c7a9ef",
        "repo": "datasets",
        "path": "src/datasets/info.py",
        "file_name": "info.py",
        "fun_name": "write_to_directory",
        "commit_message": "Pretty print dataset info files (#4116)\n\n* Pass indent to `json.dumps`\r\n\r\n* Minor fix\r\n\r\n* Pretty print GH dataset infos\r\n\r\n* Style\r\n\r\n* Revert \"Pretty print GH dataset infos\"\r\n\r\nThis reverts commit cf0523d4c9c176271cad44cd0d9dd595d233e817.\r\n\r\n* Add pretty print option",
        "code": "def write_to_directory(self, metric_info_dir, pretty_print=False):\n        \n        with open(os.path.join(metric_info_dir, config.METRIC_INFO_FILENAME), \"w\", encoding=\"utf-8\") as f:\n            json.dump(asdict(self), f, indent=4 if pretty_print else None)\n\n        if self.license:\n            with open(os.path.join(metric_info_dir, config.LICENSE_FILENAME), \"w\", encoding=\"utf-8\") as f:\n                f.write(self.license)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 86,
        "n_words": 28,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 94,
        "n_ast_nodes": 154,
        "n_identifiers": 19,
        "d_id": 21931,
        "documentation": {
            "docstring": "Write `MetricInfo` as JSON to `metric_info_dir`.\n        Also save the license separately in LICENCE.\n        If `pretty_print` is True, the JSON will be pretty-printed with the indent level of 4.\n        ",
            "n_words": 28,
            "vocab_size": 25,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 110316,
        "commit_id": "383de519505964ed879c40b23ef36e90c17ebe0d",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "axvline",
        "commit_message": "[Doc] fix more spelling and grammar",
        "code": "def axvline(self, x=0, ymin=0, ymax=1, **kwargs):\n        \n        self._check_no_units([ymin, ymax], ['ymin', 'ymax'])\n        if \"transform\" in kwargs:\n            raise ValueError(\"'transform' is not allowed as a keyword \"\n                             \"argument; axvline generates its own transform.\")\n        xmin, xmax = self.get_xbound()\n\n        # Strip away the units for comparison with non-unitized bounds.\n        xx, = self._process_unit_info([(\"x\", x)], kwargs)\n        scalex = (xx < xmin) or (xx > xmax)\n\n        trans = self.get_xaxis_transform(which='grid')\n        l = mlines.Line2D([x, x], [ymin, ymax], transform=trans, **kwargs)\n        self.add_line(l)\n        if scalex:\n            self._request_autoscale_view(\"x\")\n        return l\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 208,
        "n_words": 74,
        "vocab_size": 66,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 139,
        "n_ast_nodes": 227,
        "n_identifiers": 23,
        "d_id": 24055,
        "documentation": {
            "docstring": "\n        Add a vertical line across the Axes.\n\n        Parameters\n        ----------\n        x : float, default: 0\n            x position in data coordinates of the vertical line.\n\n        ymin : float, default: 0\n            Should be between 0 and 1, 0 being the bottom of the plot, 1 the\n            top of the plot.\n\n        ymax : float, default: 1\n            Should be between 0 and 1, 0 being the bottom of the plot, 1 the\n            top of the plot.\n\n        Returns\n        -------\n        `~matplotlib.lines.Line2D`\n\n        Other Parameters\n        ----------------\n        **kwargs\n            Valid keyword arguments are `.Line2D` properties, except for\n            'transform':\n\n            %(Line2D:kwdoc)s\n\n        See Also\n        --------\n        vlines : Add vertical lines in data coordinates.\n        axvspan : Add a vertical span (rectangle) across the axis.\n        axline : Add a line with an arbitrary slope.\n\n        Examples\n        --------\n        * draw a thick red vline at *x* = 0 that spans the yrange::\n\n            >>> axvline(linewidth=4, color='r')\n\n        * draw a default vline at *x* = 1 that spans the yrange::\n\n            >>> axvline(x=1)\n\n        * draw a default vline at *x* = .5 that spans the middle half of\n          the yrange::\n\n            >>> axvline(x=.5, ymin=0.25, ymax=0.75)\n        ",
            "n_words": 173,
            "vocab_size": 87,
            "n_whitespaces": 465,
            "language": "en"
        }
    },
    {
        "id": 107629,
        "commit_id": "d69be2554cf6d1ac711bf433b1d6f176e3290d4f",
        "repo": "matplotlib",
        "path": "lib/matplotlib/artist.py",
        "file_name": "artist.py",
        "fun_name": "update",
        "commit_message": "Clarify error message for bad keyword arguments.\n\n`plot([], [], foo=42)` previously emitted\n```\n'Line2D' object has no property 'foo'\n```\nwhich refers to the Matplotlib-specific concept of \"properties\".  It now\ninstead emits\n```\nLine2D.set() got an unexpected keyword argument 'foo'\n```\nwhich is modeled after the standard error message for unknown keyword\narguments.\n\n(To maximize backcompat, the implementation goes through a new\n_internal_update, which does *not* error when the same prop is passed\nunder different aliases.  This could be changed later, but is not the\ngoal of this PR.)",
        "code": "def update(self, props):\n        \n        return self._update_props(\n            props, \"{cls.__name__!r} object has no property {prop_name!r}\")\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 37,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 17,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 22841,
        "documentation": {
            "docstring": "\n        Update this artist's properties from the dict *props*.\n\n        Parameters\n        ----------\n        props : dict\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 215126,
        "commit_id": "fae5bc757ad0f1716483ce7ae180b451545c2058",
        "repo": "salt",
        "path": "salt/modules/aixpkg.py",
        "file_name": "aixpkg.py",
        "fun_name": "remove",
        "commit_message": "Updated to remove use of f-strings, and review comments",
        "code": "def remove(name=None, pkgs=None, **kwargs):\n    \n    targets = salt.utils.args.split_input(pkgs) if pkgs else [name]\n    if not targets:\n        return {}\n\n    if pkgs:\n        log.debug(\"Removing these fileset(s)/rpm package(s) %s: %s\", name, targets)\n\n    errors = []\n\n    # Get a list of the currently installed pkgs.\n    old = list_pkgs()\n\n    # Remove the fileset or rpm package(s)\n    for target in targets:\n        cmd = \"\"\n        out = {}\n        try:\n            named, versionpkg, rpmpkg = _check_pkg(target)\n        except CommandExecutionError as exc:\n            if exc.info:\n                errors.append(exc.info[\"errors\"])\n            continue\n\n        if rpmpkg:\n\n            # assume use dnf or yum\n            cmdflags = \"-y remove\"\n            libpathenv = {\"LIBPATH\": \"/opt/freeware/lib:/usr/lib\"}\n            if pathlib.Path(\"/opt/freeware/bin/dnf\").is_file():\n                cmdexe = \"/opt/freeware/bin/dnf\"\n                cmd = \"{} {} {}\".format(cmdexe, cmdflags, target)\n                out = __salt__[\"cmd.run_all\"](\n                    cmd,\n                    python_shell=False,\n                    env=libpathenv,\n                    ignore_retcode=True,\n                )\n            elif pathlib.Path(\"/opt/freeware/bin/yum\").is_file():\n                cmdexe = \"/opt/freeware/bin/yum\"\n                cmd = \"{} {} {}\".format(cmdexe, cmdflags, target)\n                out = __salt__[\"cmd.run_all\"](\n                    cmd,\n                    python_shell=False,\n                    env=libpathenv,\n                    ignore_retcode=True,\n                )\n            elif pathlib.Path(\"/usr/bin/yum\").is_file():\n                cmdexe = \"/usr/bin/yum\"\n                cmd = \"{} {} {}\".format(cmdexe, cmdflags, target)\n                out = __salt__[\"cmd.run_all\"](\n                    cmd,\n                    python_shell=False,\n                    env=libpathenv,\n                    ignore_retcode=True,\n                )\n            else:\n                cmdexe = \"/usr/bin/rpm\"\n                cmdflags = \"-e\"\n                cmd = \"{} {} {}\".format(cmdexe, cmdflags, target)\n                out = __salt__[\"cmd.run_all\"](cmd, python_shell=False)\n        else:\n            cmd = [\"/usr/sbin/installp\", \"-u\", named]\n            out = __salt__[\"cmd.run_all\"](cmd, python_shell=False)\n\n        log.debug(\"result of removal command %s, returned result %s\", cmd, out)\n\n    # Get a list of the packages after the uninstall\n    __context__.pop(\"pkg.list_pkgs\", None)\n    new = list_pkgs()\n    ret = salt.utils.data.compare_dicts(old, new)\n\n    if errors:\n        raise CommandExecutionError(\n            \"Problems encountered removing filesets(s)/package(s)\",\n            info={\"changes\": ret, \"errors\": errors},\n        )\n\n    return ret\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 979,
        "n_words": 220,
        "vocab_size": 123,
        "complexity": 12,
        "nloc": 65,
        "token_counts": 385,
        "n_ast_nodes": 648,
        "n_identifiers": 42,
        "d_id": 53843,
        "documentation": {
            "docstring": "\n    Remove specified fileset(s)/rpm package(s).\n\n    name\n        The name of the fileset or rpm package to be deleted.\n\n    .. versionchanged:: 3005\n\n        preference to install rpm packages are to use in the following order:\n            /opt/freeware/bin/dnf\n            /opt/freeware/bin/yum\n            /usr/bin/yum\n            /usr/bin/rpm\n\n    pkgs\n        A list of filesets and/or rpm packages to delete.\n        Must be passed as a python list. The ``name`` parameter will be\n        ignored if this option is passed.\n\n\n    Returns a list containing the removed packages.\n\n    CLI Example:\n\n    .. code-block:: bash\n\n        salt '*' pkg.remove <fileset/rpm package name>\n        salt '*' pkg.remove tcsh\n        salt '*' pkg.remove xlC.rte\n        salt '*' pkg.remove Firefox.base.adt\n        salt '*' pkg.remove pkgs='[\"foo\", \"bar\"]'\n    ",
            "n_words": 98,
            "vocab_size": 69,
            "n_whitespaces": 237,
            "language": "en"
        }
    },
    {
        "id": 156683,
        "commit_id": "ecbab9d7cb52a2d96cb1b8dc397a87811e6f8059",
        "repo": "dask",
        "path": "dask/dataframe/categorical.py",
        "file_name": "categorical.py",
        "fun_name": "codes",
        "commit_message": "Add ``AttributeNotImplementedError`` for properties so IPython glob search works (#9231)",
        "code": "def codes(self):\n        \n        if not self.known:\n            msg = (\n                \"`df.column.cat.codes` with unknown categories is not \"\n                \"supported.  Please use `column.cat.as_known()` or \"\n                \"`df.categorize()` beforehand to ensure known categories\"\n            )\n            raise AttributeNotImplementedError(msg)\n        return self._property_map(\"codes\")\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 132,
        "n_words": 32,
        "vocab_size": 30,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 31,
        "n_ast_nodes": 61,
        "n_identifiers": 6,
        "d_id": 36714,
        "documentation": {
            "docstring": "The codes of this categorical.\n\n        If categories are unknown, an error is raised",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 30374,
        "commit_id": "e96e8ed7ec7e7cdffceaeb2c42e0396d4e3a8906",
        "repo": "spotify-downloader",
        "path": "spotdl/utils/ffmpeg.py",
        "file_name": "ffmpeg.py",
        "fun_name": "get_local_ffmpeg",
        "commit_message": "fixed local path creation on *nix machines",
        "code": "def get_local_ffmpeg() -> Optional[Path]:\n    \n\n    ffmpeg_path = Path(get_spotdl_path()) / (\"ffmpeg\" + (\".exe\" if platform.system() == \"Windows\" else \"\"))\n\n    if ffmpeg_path.is_file():\n        return ffmpeg_path\n\n    return None\n\n",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 42,
        "n_words": 23,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 47,
        "n_ast_nodes": 86,
        "n_identifiers": 8,
        "d_id": 5524,
        "documentation": {
            "docstring": "\n    Get local ffmpeg binary path.\n\n    ### Returns\n    - Path to ffmpeg binary or None if not found.\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 206860,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/generic/dates.py",
        "file_name": "dates.py",
        "fun_name": "get_date_list",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_date_list(self, queryset, date_type=None, ordering=\"ASC\"):\n        \n        date_field = self.get_date_field()\n        allow_empty = self.get_allow_empty()\n        if date_type is None:\n            date_type = self.get_date_list_period()\n\n        if self.uses_datetime_field:\n            date_list = queryset.datetimes(date_field, date_type, ordering)\n        else:\n            date_list = queryset.dates(date_field, date_type, ordering)\n        if date_list is not None and not date_list and not allow_empty:\n            raise Http404(\n                _(\"No %(verbose_name_plural)s available\")\n                % {\n                    \"verbose_name_plural\": queryset.model._meta.verbose_name_plural,\n                }\n            )\n\n        return date_list\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 230,
        "n_words": 55,
        "vocab_size": 38,
        "complexity": 6,
        "nloc": 17,
        "token_counts": 108,
        "n_ast_nodes": 175,
        "n_identifiers": 19,
        "d_id": 51761,
        "documentation": {
            "docstring": "\n        Get a date list by calling `queryset.dates/datetimes()`, checking\n        along the way for empty lists that aren't allowed.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 261573,
        "commit_id": "3714c900fc6ddcc87ad4486a41e0d1a4324d7209",
        "repo": "scikit-learn",
        "path": "sklearn/datasets/tests/test_lfw.py",
        "file_name": "test_lfw.py",
        "fun_name": "test_fetch_lfw_people_internal_cropping",
        "commit_message": "FIX crop properly the image in fetch_lfw_people (#24951)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def test_fetch_lfw_people_internal_cropping():\n    \n    # If cropping was not done properly and we don't resize the images, the images would\n    # have their original size (250x250) and the image would not fit in the NumPy array\n    # pre-allocated based on `slice_` parameter.\n    slice_ = (slice(70, 195), slice(78, 172))\n    lfw = fetch_lfw_people(\n        data_home=SCIKIT_LEARN_DATA,\n        min_faces_per_person=3,\n        download_if_missing=False,\n        resize=None,\n        slice_=slice_,\n    )\n    assert lfw.images[0].shape == (\n        slice_[0].stop - slice_[0].start,\n        slice_[1].stop - slice_[1].start,\n    )\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 142,
        "n_words": 66,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 87,
        "n_ast_nodes": 129,
        "n_identifiers": 14,
        "d_id": 76869,
        "documentation": {
            "docstring": "Check that we properly crop the images.\n\n    Non-regression test for:\n    https://github.com/scikit-learn/scikit-learn/issues/24942\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 203504,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/templatetags/admin_modify.py",
        "file_name": "admin_modify.py",
        "fun_name": "prepopulated_fields_js",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def prepopulated_fields_js(context):\n    \n    prepopulated_fields = []\n    if \"adminform\" in context:\n        prepopulated_fields.extend(context[\"adminform\"].prepopulated_fields)\n    if \"inline_admin_formsets\" in context:\n        for inline_admin_formset in context[\"inline_admin_formsets\"]:\n            for inline_admin_form in inline_admin_formset:\n                if inline_admin_form.original is None:\n                    prepopulated_fields.extend(inline_admin_form.prepopulated_fields)\n\n    prepopulated_fields_json = []\n    for field in prepopulated_fields:\n        prepopulated_fields_json.append(\n            {\n                \"id\": \"#%s\" % field[\"field\"].auto_id,\n                \"name\": field[\"field\"].name,\n                \"dependency_ids\": [\n                    \"#%s\" % dependency.auto_id for dependency in field[\"dependencies\"]\n                ],\n                \"dependency_list\": [\n                    dependency.name for dependency in field[\"dependencies\"]\n                ],\n                \"maxLength\": field[\"field\"].field.max_length or 50,\n                \"allowUnicode\": getattr(field[\"field\"].field, \"allow_unicode\", False),\n            }\n        )\n\n    context.update(\n        {\n            \"prepopulated_fields\": prepopulated_fields,\n            \"prepopulated_fields_json\": json.dumps(prepopulated_fields_json),\n        }\n    )\n    return context\n\n\n@register.tag(name=\"prepopulated_fields_js\")",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag(name=\"prepopulated_fields_js\")",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 396,
        "n_words": 81,
        "vocab_size": 57,
        "complexity": 10,
        "nloc": 32,
        "token_counts": 178,
        "n_ast_nodes": 322,
        "n_identifiers": 20,
        "d_id": 50414,
        "documentation": {
            "docstring": "\n    Create a list of prepopulated_fields that should render JavaScript for\n    the prepopulated fields for both the admin form and inlines.\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 268366,
        "commit_id": "8ebca4a6a3a9836ce515a4dc60044c52465ef170",
        "repo": "ansible",
        "path": "lib/ansible/module_utils/urls.py",
        "file_name": "urls.py",
        "fun_name": "_split_multiext",
        "commit_message": "fetch_file - properly split files with multi-part file extensions (#75257)",
        "code": "def _split_multiext(name, min=3, max=4, count=2):\n    \n    extension = ''\n    for i, sfx in enumerate(reversed(_suffixes(name))):\n        if i >= count:\n            break\n\n        if min <= len(sfx) <= max:\n            extension = '%s%s' % (sfx, extension)\n            name = name.rstrip(sfx)\n        else:\n            # Stop on the first invalid extension\n            break\n\n    return name, extension\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 133,
        "n_words": 45,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 77,
        "n_ast_nodes": 126,
        "n_identifiers": 13,
        "d_id": 79494,
        "documentation": {
            "docstring": "Split a multi-part extension from a file name.\n\n    Returns '([name minus extension], extension)'.\n\n    Define the valid extension length (including the '.') with 'min' and 'max',\n    'count' sets the number of extensions, counting from the end, to evaluate.\n    Evaluation stops on the first file extension that is outside the min and max range.\n\n    If no valid extensions are found, the original ``name`` is returned\n    and ``extension`` is empty.\n\n    :arg name: File name or path.\n    :kwarg min: Minimum length of a valid file extension.\n    :kwarg max: Maximum length of a valid file extension.\n    :kwarg count: Number of suffixes from the end to evaluate.\n\n    ",
            "n_words": 101,
            "vocab_size": 67,
            "n_whitespaces": 134,
            "language": "en"
        }
    },
    {
        "id": 71596,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/pages/test_edit_page.py",
        "file_name": "test_edit_page.py",
        "fun_name": "test_upload_file_publish",
        "commit_message": "Reformat with black",
        "code": "def test_upload_file_publish(self):\n        \n        file_upload = ContentFile(b\"A new file\", name=\"published-file.txt\")\n        post_data = {\n            \"title\": \"New file\",\n            \"slug\": \"new-file\",\n            \"file_field\": file_upload,\n            \"action-publish\": \"Publish\",\n        }\n        response = self.client.post(\n            reverse(\"wagtailadmin_pages:edit\", args=[self.file_page.id]), post_data\n        )\n\n        # Should be redirected to explorer\n        self.assertRedirects(\n            response, reverse(\"wagtailadmin_explore\", args=[self.root_page.id])\n        )\n\n        # Check the new file exists\n        file_page = FilePage.objects.get()\n\n        self.assertEqual(file_page.file_field.name, file_upload.name)\n        self.assertTrue(os.path.exists(file_page.file_field.path))\n        self.assertEqual(file_page.file_field.read(), b\"A new file\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 219,
        "n_words": 55,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 138,
        "n_ast_nodes": 234,
        "n_identifiers": 25,
        "d_id": 15695,
        "documentation": {
            "docstring": "\n        Check that file uploads work when directly publishing\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 204045,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/geos/geometry.py",
        "file_name": "geometry.py",
        "fun_name": "__eq__",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def __eq__(self, other):\n        \n        if isinstance(other, str):\n            try:\n                other = GEOSGeometry.from_ewkt(other)\n            except (ValueError, GEOSException):\n                return False\n        return (\n            isinstance(other, GEOSGeometry)\n            and self.srid == other.srid\n            and self.equals_exact(other)\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 139,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 59,
        "n_ast_nodes": 93,
        "n_identifiers": 11,
        "d_id": 50623,
        "documentation": {
            "docstring": "\n        Equivalence testing, a Geometry may be compared with another Geometry\n        or an EWKT representation.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 205923,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/boundfield.py",
        "file_name": "boundfield.py",
        "fun_name": "id_for_label",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def id_for_label(self):\n        \n        widget = self.field.widget\n        id_ = widget.attrs.get(\"id\") or self.auto_id\n        return widget.id_for_label(id_)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 59,
        "n_identifiers": 8,
        "d_id": 51284,
        "documentation": {
            "docstring": "\n        Wrapper around the field widget's `id_for_label` method.\n        Useful, for example, for focusing on this field regardless of whether\n        it has a single widget or a MultiWidget.\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 269382,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/applications/imagenet_utils.py",
        "file_name": "imagenet_utils.py",
        "fun_name": "decode_predictions",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def decode_predictions(preds, top=5):\n    \n    global CLASS_INDEX\n\n    if len(preds.shape) != 2 or preds.shape[1] != 1000:\n        raise ValueError(\n            \"`decode_predictions` expects \"\n            \"a batch of predictions \"\n            \"(i.e. a 2D array of shape (samples, 1000)). \"\n            \"Found array with shape: \" + str(preds.shape)\n        )\n    if CLASS_INDEX is None:\n        fpath = data_utils.get_file(\n            \"imagenet_class_index.json\",\n            CLASS_INDEX_PATH,\n            cache_subdir=\"models\",\n            file_hash=\"c2c37ea517e94d9795004a39431a14cb\",\n        )\n        with open(fpath) as f:\n            CLASS_INDEX = json.load(f)\n    results = []\n    for pred in preds:\n        top_indices = pred.argsort()[-top:][::-1]\n        result = [tuple(CLASS_INDEX[str(i)]) + (pred[i],) for i in top_indices]\n        result.sort(key=lambda x: x[2], reverse=True)\n        results.append(result)\n    return results\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 268,
        "n_words": 85,
        "vocab_size": 66,
        "complexity": 6,
        "nloc": 25,
        "token_counts": 164,
        "n_ast_nodes": 271,
        "n_identifiers": 30,
        "d_id": 80052,
        "documentation": {
            "docstring": "Decodes the prediction of an ImageNet model.\n\n    Args:\n      preds: Numpy array encoding a batch of predictions.\n      top: Integer, how many top-guesses to return. Defaults to 5.\n\n    Returns:\n      A list of lists of top class prediction tuples\n      `(class_name, class_description, score)`.\n      One list of tuples per sample in batch input.\n\n    Raises:\n      ValueError: In case of invalid shape of the `pred` array\n        (must be 2D).\n    ",
            "n_words": 62,
            "vocab_size": 49,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 217864,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/server.py",
        "file_name": "server.py",
        "fun_name": "handle_expect_100",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def handle_expect_100(self):\n        \n        self.send_response_only(HTTPStatus.CONTINUE)\n        self.end_headers()\n        return True\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 34,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 54971,
        "documentation": {
            "docstring": "Decide what to do with an \"Expect: 100-continue\" header.\n\n        If the client is expecting a 100 Continue response, we must\n        respond with either a 100 Continue or a final response before\n        waiting for the request body. The default is to always respond\n        with a 100 Continue. You can behave differently (for example,\n        reject unauthorized requests) by overriding this method.\n\n        This method should either return True (possibly after sending\n        a 100 Continue response) or send an error response and return\n        False.\n\n        ",
            "n_words": 80,
            "vocab_size": 60,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 203487,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/templatetags/admin_list.py",
        "file_name": "admin_list.py",
        "fun_name": "paginator_number",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def paginator_number(cl, i):\n    \n    if i == cl.paginator.ELLIPSIS:\n        return format_html(\"{} \", cl.paginator.ELLIPSIS)\n    elif i == cl.page_num:\n        return format_html('<span class=\"this-page\">{}</span> ', i)\n    else:\n        return format_html(\n            '<a href=\"{}\"{}>{}</a> ',\n            cl.get_query_string({PAGE_VAR: i}),\n            mark_safe(' class=\"end\"' if i == cl.paginator.num_pages else \"\"),\n            i,\n        )\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 122,
        "n_words": 38,
        "vocab_size": 30,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 78,
        "n_ast_nodes": 128,
        "n_identifiers": 11,
        "d_id": 50406,
        "documentation": {
            "docstring": "\n    Generate an individual page index link in a paginated list.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 247511,
        "commit_id": "32c828d0f760492711a98b11376e229d795fd1b3",
        "repo": "synapse",
        "path": "tests/rest/media/v1/test_media_storage.py",
        "file_name": "test_media_storage.py",
        "fun_name": "test_thumbnail_repeated_thumbnail",
        "commit_message": "Add type hints to `tests/rest`. (#12208)\n\nCo-authored-by: Patrick Cloke <clokep@users.noreply.github.com>",
        "code": "def test_thumbnail_repeated_thumbnail(self) -> None:\n        \n        self._test_thumbnail(\n            \"scale\", self.test_image.expected_scaled, self.test_image.expected_found\n        )\n\n        if not self.test_image.expected_found:\n            return\n\n        # Fetching again should work, without re-requesting the image from the\n        # remote.\n        params = \"?width=32&height=32&method=scale\"\n        channel = make_request(\n            self.reactor,\n            FakeSite(self.thumbnail_resource, self.reactor),\n            \"GET\",\n            self.media_id + params,\n            shorthand=False,\n            await_result=False,\n        )\n        self.pump()\n\n        self.assertEqual(channel.code, 200)\n        if self.test_image.expected_scaled:\n            self.assertEqual(\n                channel.result[\"body\"],\n                self.test_image.expected_scaled,\n                channel.result[\"body\"],\n            )\n\n        # Deleting the thumbnail on disk then re-requesting it should work as\n        # Synapse should regenerate missing thumbnails.\n        origin, media_id = self.media_id.split(\"/\")\n        info = self.get_success(self.store.get_cached_remote_media(origin, media_id))\n        file_id = info[\"filesystem_id\"]\n\n        thumbnail_dir = self.media_repo.filepaths.remote_media_thumbnail_dir(\n            origin, file_id\n        )\n        shutil.rmtree(thumbnail_dir, ignore_errors=True)\n\n        channel = make_request(\n            self.reactor,\n            FakeSite(self.thumbnail_resource, self.reactor),\n            \"GET\",\n            self.media_id + params,\n            shorthand=False,\n            await_result=False,\n        )\n        self.pump()\n\n        self.assertEqual(channel.code, 200)\n        if self.test_image.expected_scaled:\n            self.assertEqual(\n                channel.result[\"body\"],\n                self.test_image.expected_scaled,\n                channel.result[\"body\"],\n            )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 586,
        "n_words": 112,
        "vocab_size": 68,
        "complexity": 4,
        "nloc": 49,
        "token_counts": 263,
        "n_ast_nodes": 414,
        "n_identifiers": 33,
        "d_id": 71705,
        "documentation": {
            "docstring": "Test that fetching the same thumbnail works, and deleting the on disk\n        thumbnail regenerates it.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 203341,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/checks.py",
        "file_name": "checks.py",
        "fun_name": "_check_readonly_fields",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _check_readonly_fields(self, obj):\n        \n\n        if obj.readonly_fields == ():\n            return []\n        elif not isinstance(obj.readonly_fields, (list, tuple)):\n            return must_be(\n                \"a list or tuple\", option=\"readonly_fields\", obj=obj, id=\"admin.E034\"\n            )\n        else:\n            return list(\n                chain.from_iterable(\n                    self._check_readonly_fields_item(\n                        obj, field_name, \"readonly_fields[%d]\" % index\n                    )\n                    for index, field_name in enumerate(obj.readonly_fields)\n                )\n            )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 250,
        "n_words": 42,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 85,
        "n_ast_nodes": 137,
        "n_identifiers": 16,
        "d_id": 50315,
        "documentation": {
            "docstring": "Check that readonly_fields refers to proper attribute or field.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 110323,
        "commit_id": "383de519505964ed879c40b23ef36e90c17ebe0d",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "semilogy",
        "commit_message": "[Doc] fix more spelling and grammar",
        "code": "def semilogy(self, *args, **kwargs):\n        \n        d = {k: v for k, v in kwargs.items()\n             if k in ['base', 'subs', 'nonpositive',\n                      'basey', 'subsy', 'nonposy']}\n        self.set_yscale('log', **d)\n        return self.plot(\n            *args, **{k: v for k, v in kwargs.items() if k not in d})\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 111,
        "n_words": 39,
        "vocab_size": 27,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 84,
        "n_ast_nodes": 139,
        "n_identifiers": 10,
        "d_id": 24062,
        "documentation": {
            "docstring": "\n        Make a plot with log scaling on the y-axis.\n\n        Call signatures::\n\n            semilogy([x], y, [fmt], data=None, **kwargs)\n            semilogy([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n\n        This is just a thin wrapper around `.plot` which additionally changes\n        the y-axis to log scaling. All the concepts and parameters of plot can\n        be used here as well.\n\n        The additional parameters *base*, *subs*, and *nonpositive* control the\n        y-axis properties. They are just forwarded to `.Axes.set_yscale`.\n\n        Parameters\n        ----------\n        base : float, default: 10\n            Base of the y logarithm.\n\n        subs : array-like, optional\n            The location of the minor yticks. If *None*, reasonable locations\n            are automatically chosen depending on the number of decades in the\n            plot. See `.Axes.set_yscale` for details.\n\n        nonpositive : {'mask', 'clip'}, default: 'mask'\n            Non-positive values in y can be masked as invalid, or clipped to a\n            very small positive number.\n\n        **kwargs\n            All parameters supported by `.plot`.\n\n        Returns\n        -------\n        list of `.Line2D`\n            Objects representing the plotted data.\n        ",
            "n_words": 151,
            "vocab_size": 112,
            "n_whitespaces": 381,
            "language": "en"
        }
    },
    {
        "id": 91382,
        "commit_id": "284e980df0018f8baee659999268bdd4c7d08255",
        "repo": "sentry",
        "path": "tests/sentry/integrations/vercel/test_integration.py",
        "file_name": "test_integration.py",
        "fun_name": "test_upgrade_org_config_no_source_code_provider",
        "commit_message": "ref: replace self.assertRaises with pytest.raises (#35685)\n\n* add flake8 plugin to detect assertRaises\r\n\r\n* ref: replace self.assertRaises with pytest.raises\r\n\r\n* non-sed fixes",
        "code": "def test_upgrade_org_config_no_source_code_provider(self):\n        \n\n        with self.tasks():\n            self.assert_setup_flow()\n\n        project_id = self.project.id\n        org = self.organization\n        data = {\n            \"project_mappings\": [[project_id, \"Qme9NXBpguaRxcXssZ1NWHVaM98MAL6PHDXUs1jPrgiM8H\"]]\n        }\n        integration = Integration.objects.get(provider=self.provider.key)\n        installation = integration.get_installation(org.id)\n\n        responses.add(\n            responses.GET,\n            \"https://api.vercel.com/v1/projects/%s\"\n            % \"Qme9NXBpguaRxcXssZ1NWHVaM98MAL6PHDXUs1jPrgiM8H\",\n            json={},\n        )\n        with pytest.raises(ValidationError):\n            installation.update_organization_config(data)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 188,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 101,
        "n_ast_nodes": 174,
        "n_identifiers": 26,
        "d_id": 18763,
        "documentation": {
            "docstring": "Test that the function doesn't progress if the Vercel project hasn't been connected to a Git repository",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 196786,
        "commit_id": "f757f3daae6e11ea0cfb7dadc133274d8d74315f",
        "repo": "sympy",
        "path": "sympy/integrals/meijerint.py",
        "file_name": "meijerint.py",
        "fun_name": "_get_coeff_exp",
        "commit_message": "Reordered imports 2",
        "code": "def _get_coeff_exp(expr, x):\n    \n    from sympy.simplify import powsimp\n    (c, m) = expand_power_base(powsimp(expr)).as_coeff_mul(x)\n    if not m:\n        return c, S.Zero\n    [m] = m\n    if m.is_Pow:\n        if m.base != x:\n            raise _CoeffExpValueError('expr not of form a*x**b')\n        return c, m.exp\n    elif m == x:\n        return c, S.One\n    else:\n        raise _CoeffExpValueError('expr not of form a*x**b: %s' % expr)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 122,
        "n_words": 52,
        "vocab_size": 37,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 90,
        "n_ast_nodes": 148,
        "n_identifiers": 17,
        "d_id": 48173,
        "documentation": {
            "docstring": "\n    When expr is known to be of the form c*x**b, with c and/or b possibly 1,\n    return c, b.\n\n    Examples\n    ========\n\n    >>> from sympy.abc import x, a, b\n    >>> from sympy.integrals.meijerint import _get_coeff_exp\n    >>> _get_coeff_exp(a*x**b, x)\n    (a, b)\n    >>> _get_coeff_exp(x, x)\n    (1, 1)\n    >>> _get_coeff_exp(2*x, x)\n    (2, 1)\n    >>> _get_coeff_exp(x**3, x)\n    (1, 3)\n    ",
            "n_words": 53,
            "vocab_size": 40,
            "n_whitespaces": 99,
            "language": "en"
        }
    },
    {
        "id": 101389,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "scripts/convert.py",
        "file_name": "convert.py",
        "fun_name": "process",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def process(self) -> None:\n        \n        logger.debug(\"Starting Conversion\")\n        # queue_manager.debug_monitor(5)\n        try:\n            self._convert_images()\n            self._disk_io.save_thread.join()\n            queue_manager.terminate_queues()\n\n            finalize(self._images.count,\n                     self._predictor.faces_count,\n                     self._predictor.verify_output)\n            logger.debug(\"Completed Conversion\")\n        except MemoryError as err:\n            msg = (\"Faceswap ran out of RAM running convert. Conversion is very system RAM \"\n                   \"heavy, so this can happen in certain circumstances when you have a lot of \"\n                   \"cpus but not enough RAM to support them all.\"\n                   \"\\nYou should lower the number of processes in use by either setting the \"\n                   \"'singleprocess' flag (-sp) or lowering the number of parallel jobs (-j).\")\n            raise FaceswapError(msg) from err\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 313,
        "n_words": 89,
        "vocab_size": 77,
        "complexity": 2,
        "nloc": 26,
        "token_counts": 82,
        "n_ast_nodes": 150,
        "n_identifiers": 20,
        "d_id": 20804,
        "documentation": {
            "docstring": " The entry point for triggering the Conversion Process.\n\n        Should only be called from  :class:`lib.cli.launcher.ScriptExecutor`\n\n        Raises\n        ------\n        FaceswapError\n            Error raised if the process runs out of memory\n        ",
            "n_words": 26,
            "vocab_size": 25,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 261801,
        "commit_id": "a4d470838fe0cc31ba838594e4c8b0ff15be91f8",
        "repo": "scikit-learn",
        "path": "sklearn/covariance/_shrunk_covariance.py",
        "file_name": "_shrunk_covariance.py",
        "fun_name": "_oas",
        "commit_message": "MAINT Parameters validation for `covariance.oas` (#24904)\n\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>\r\nCo-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>",
        "code": "def _oas(X, *, assume_centered=False):\n    \n    # for only one feature, the result is the same whatever the shrinkage\n    if len(X.shape) == 2 and X.shape[1] == 1:\n        if not assume_centered:\n            X = X - X.mean()\n        return np.atleast_2d((X**2).mean()), 0.0\n\n    n_samples, n_features = X.shape\n\n    emp_cov = empirical_covariance(X, assume_centered=assume_centered)\n    mu = np.trace(emp_cov) / n_features\n\n    # formula from Chen et al.'s **implementation**\n    alpha = np.mean(emp_cov**2)\n    num = alpha + mu**2\n    den = (n_samples + 1.0) * (alpha - (mu**2) / n_features)\n\n    shrinkage = 1.0 if den == 0 else min(num / den, 1.0)\n    shrunk_cov = (1.0 - shrinkage) * emp_cov\n    shrunk_cov.flat[:: n_features + 1] += shrinkage * mu\n\n    return shrunk_cov, shrinkage\n\n\n###############################################################################\n# Public API\n# ShrunkCovariance estimator\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 176,
        "n_words": 112,
        "vocab_size": 75,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 176,
        "n_ast_nodes": 266,
        "n_identifiers": 21,
        "d_id": 77005,
        "documentation": {
            "docstring": "Estimate covariance with the Oracle Approximating Shrinkage algorithm.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 258820,
        "commit_id": "1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe",
        "repo": "scikit-learn",
        "path": "sklearn/covariance/_shrunk_covariance.py",
        "file_name": "_shrunk_covariance.py",
        "fun_name": "ledoit_wolf",
        "commit_message": "MNT Update black to stable version (#22474)",
        "code": "def ledoit_wolf(X, *, assume_centered=False, block_size=1000):\n    \n    X = check_array(X)\n    # for only one feature, the result is the same whatever the shrinkage\n    if len(X.shape) == 2 and X.shape[1] == 1:\n        if not assume_centered:\n            X = X - X.mean()\n        return np.atleast_2d((X**2).mean()), 0.0\n    if X.ndim == 1:\n        X = np.reshape(X, (1, -1))\n        warnings.warn(\n            \"Only one sample available. You may want to reshape your data array\"\n        )\n        n_features = X.size\n    else:\n        _, n_features = X.shape\n\n    # get Ledoit-Wolf shrinkage\n    shrinkage = ledoit_wolf_shrinkage(\n        X, assume_centered=assume_centered, block_size=block_size\n    )\n    emp_cov = empirical_covariance(X, assume_centered=assume_centered)\n    mu = np.sum(np.trace(emp_cov)) / n_features\n    shrunk_cov = (1.0 - shrinkage) * emp_cov\n    shrunk_cov.flat[:: n_features + 1] += shrinkage * mu\n\n    return shrunk_cov, shrinkage\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 229,
        "n_words": 109,
        "vocab_size": 76,
        "complexity": 5,
        "nloc": 22,
        "token_counts": 182,
        "n_ast_nodes": 284,
        "n_identifiers": 26,
        "d_id": 75444,
        "documentation": {
            "docstring": "Estimates the shrunk Ledoit-Wolf covariance matrix.\n\n    Read more in the :ref:`User Guide <shrunk_covariance>`.\n\n    Parameters\n    ----------\n    X : array-like of shape (n_samples, n_features)\n        Data from which to compute the covariance estimate\n\n    assume_centered : bool, default=False\n        If True, data will not be centered before computation.\n        Useful to work with data whose mean is significantly equal to\n        zero but is not exactly zero.\n        If False, data will be centered before computation.\n\n    block_size : int, default=1000\n        Size of blocks into which the covariance matrix will be split.\n        This is purely a memory optimization and does not affect results.\n\n    Returns\n    -------\n    shrunk_cov : ndarray of shape (n_features, n_features)\n        Shrunk covariance.\n\n    shrinkage : float\n        Coefficient in the convex combination used for the computation\n        of the shrunk estimate.\n\n    Notes\n    -----\n    The regularized (shrunk) covariance is:\n\n    (1 - shrinkage) * cov + shrinkage * mu * np.identity(n_features)\n\n    where mu = trace(cov) / n_features\n    ",
            "n_words": 145,
            "vocab_size": 104,
            "n_whitespaces": 263,
            "language": "en"
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    },
    {
        "id": 21486,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py",
        "file_name": "tarfile.py",
        "fun_name": "create_pax_global_header",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def create_pax_global_header(cls, pax_headers):\n        \n        return cls._create_pax_generic_header(pax_headers, XGLTYPE, \"utf8\")\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
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        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 19,
        "n_ast_nodes": 32,
        "n_identifiers": 5,
        "d_id": 3872,
        "documentation": {
            "docstring": "Return the object as a pax global header block sequence.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 278703,
        "commit_id": "3613c3defc39c236fb1592c4f7ba1a9cc887343a",
        "repo": "keras",
        "path": "keras/engine/base_preprocessing_layer.py",
        "file_name": "base_preprocessing_layer.py",
        "fun_name": "adapt",
        "commit_message": "Remove pylint comments.\n\nPiperOrigin-RevId: 452353044",
        "code": "def adapt(self, data, batch_size=None, steps=None):\n        \n        _disallow_inside_tf_function(\"adapt\")\n        if not version_utils.should_use_v2():\n            raise RuntimeError(\"`adapt` is only supported in tensorflow v2.\")\n        if not self._is_compiled:\n            self.compile()  # Compile with defaults.\n        if self.built:\n            self.reset_state()\n        data_handler = data_adapter.DataHandler(\n            data,\n            batch_size=batch_size,\n            steps_per_epoch=steps,\n            epochs=1,\n            steps_per_execution=self._steps_per_execution,\n            distribute=False,\n        )\n        self._adapt_function = self.make_adapt_function()\n        for _, iterator in data_handler.enumerate_epochs():\n            with data_handler.catch_stop_iteration():\n                for _ in data_handler.steps():\n                    self._adapt_function(iterator)\n                    if data_handler.should_sync:\n                        context.async_wait()\n        self.finalize_state()\n        self._is_adapted = True\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 324,
        "n_words": 60,
        "vocab_size": 49,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 147,
        "n_ast_nodes": 241,
        "n_identifiers": 32,
        "d_id": 82685,
        "documentation": {
            "docstring": "Fits the state of the preprocessing layer to the data being passed.\n\n        After calling `adapt` on a layer, a preprocessing layer's state will not\n        update during training. In order to make preprocessing layers efficient\n        in any distribution context, they are kept constant with respect to any\n        compiled `tf.Graph`s that call the layer. This does not affect the layer\n        use when adapting each layer only once, but if you adapt a layer\n        multiple times you will need to take care to re-compile any compiled\n        functions as follows:\n\n         * If you are adding a preprocessing layer to a `keras.Model`, you need\n           to call `model.compile` after each subsequent call to `adapt`.\n         * If you are calling a preprocessing layer inside\n          `tf.data.Dataset.map`, you should call `map` again on the input\n          `tf.data.Dataset` after each `adapt`.\n         * If you are using a `tf.function` directly which calls a preprocessing\n           layer, you need to call `tf.function` again on your callable after\n           each subsequent call to `adapt`.\n\n        `tf.keras.Model` example with multiple adapts:\n\n        >>> layer = tf.keras.layers.Normalization(\n        ...     axis=None)\n        >>> layer.adapt([0, 2])\n        >>> model = tf.keras.Sequential(layer)\n        >>> model.predict([0, 1, 2])\n        array([-1.,  0.,  1.], dtype=float32)\n        >>> layer.adapt([-1, 1])\n        >>> model.compile() # This is needed to re-compile model.predict!\n        >>> model.predict([0, 1, 2])\n        array([0., 1., 2.], dtype=float32)\n\n        `tf.data.Dataset` example with multiple adapts:\n\n        >>> layer = tf.keras.layers.Normalization(\n        ...     axis=None)\n        >>> layer.adapt([0, 2])\n        >>> input_ds = tf.data.Dataset.range(3)\n        >>> normalized_ds = input_ds.map(layer)\n        >>> list(normalized_ds.as_numpy_iterator())\n        [array([-1.], dtype=float32),\n         array([0.], dtype=float32),\n         array([1.], dtype=float32)]\n        >>> layer.adapt([-1, 1])\n        >>> normalized_ds = input_ds.map(layer) # Re-map over the input dataset.\n        >>> list(normalized_ds.as_numpy_iterator())\n        [array([0.], dtype=float32),\n         array([1.], dtype=float32),\n         array([2.], dtype=float32)]\n\n        `adapt()` is meant only as a single machine utility to compute layer\n        state.  To analyze a dataset that cannot fit on a single machine, see\n        [Tensorflow Transform](\n        https://www.tensorflow.org/tfx/transform/get_started)\n        for a multi-machine, map-reduce solution.\n\n        Arguments:\n            data: The data to train on. It can be passed either as a tf.data\n              Dataset, or as a numpy array.\n            batch_size: Integer or `None`.\n                Number of samples per state update. If unspecified,\n                `batch_size` will default to 32.  Do not specify the\n                `batch_size` if your data is in the form of datasets,\n                generators, or `keras.utils.Sequence` instances (since they\n                generate batches).\n            steps: Integer or `None`.\n                Total number of steps (batches of samples)\n                When training with input tensors such as\n                TensorFlow data tensors, the default `None` is equal to\n                the number of samples in your dataset divided by\n                the batch size, or 1 if that cannot be determined. If x is a\n                `tf.data` dataset, and 'steps' is None, the epoch will run until\n                the input dataset is exhausted. When passing an infinitely\n                repeating dataset, you must specify the `steps` argument. This\n                argument is not supported with array inputs.\n        ",
            "n_words": 434,
            "vocab_size": 227,
            "n_whitespaces": 1065,
            "language": "en"
        }
    },
    {
        "id": 159757,
        "commit_id": "66a61b03658f3c9f312505dcf7eab07e4cf91ac6",
        "repo": "numpy",
        "path": "numpy/lib/tests/test_io.py",
        "file_name": "test_io.py",
        "fun_name": "test_loadtxt_float_conversion",
        "commit_message": "Port over tests from npreadtext test suite\n\n- Add test for parsing scientific notation.\n- Add multiple-char comment test.\n- Port over tests for structured dtypes.\n- Add tests for exceptions on skiprows/max_rows.\n- port over ndmin tests.\n- Make structured data reusable, add unpack tests.\n- Port over delimiter tests.\n- Port over maxrows test w/ various dtypes.\n- Port over test of exception msg on parse failure.\n- Port over test for converters w/neg indices.\n- Port over usecols tests\n- Port over unicode tests.\n- Port over more converter tests.\n- Port over test for large rows.\n- Port over test for string-len discovery.\n- Port over float conversion accuracy test.\n- Port over bool test.\n- Add test for implicit float->int conversion.\n- Port over complex parsing tests.\n- Port over tests for reading from generator.\n- Port over object cleanup test.\n- Port over bytes incompat test.\n- Port over converters tests.\n\nCo-authored-by: Warren Weckesser <warren.weckesser@gmail.com>\nCo-authored-by: Sebastian Berg <sebastian@sipsolutions.net>",
        "code": "def test_loadtxt_float_conversion():\n    \n    strings = [\n        '0.9999999999999999',\n        '9876543210.123456',\n        '5.43215432154321e+300',\n        '0.901',\n        '0.333',\n    ]\n    txt = TextIO('\\n'.join(strings))\n    res = np.loadtxt(txt)\n    expected = np.array([float(s) for s in strings])\n    assert_equal(res, expected)\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 82,
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        "token_counts": 61,
        "n_ast_nodes": 108,
        "n_identifiers": 13,
        "d_id": 38418,
        "documentation": {
            "docstring": "\n    Some tests that the conversion to float64 works as accurately as the Python\n    built-in `float` function. In a naive version of the float parser, these\n    strings resulted in values that were off by an ULP or two.\n    ",
            "n_words": 37,
            "vocab_size": 33,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 126889,
        "commit_id": "f084546d41f0533c1e9e96a7249532d0eb4ff47d",
        "repo": "ray",
        "path": "python/ray/actor.py",
        "file_name": "actor.py",
        "fun_name": "__reduce__",
        "commit_message": "Fix out-of-band deserialization of actor handle (#27700)\n\nWhen we deserialize actor handle via pickle, we will register it with an outer object ref equaling to itself which is wrong. For out-of-band deserialization, there should be no outer object ref.\r\n\r\nSigned-off-by: Jiajun Yao <jeromeyjj@gmail.com>",
        "code": "def __reduce__(self):\n        \n        (serialized, _) = self._serialization_helper()\n        # There is no outer object ref when the actor handle is\n        # deserialized out-of-band using pickle.\n        return ActorHandle._deserialization_helper, (serialized, None)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 62,
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        "vocab_size": 24,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 46,
        "n_identifiers": 7,
        "d_id": 28292,
        "documentation": {
            "docstring": "This code path is used by pickling but not by Ray forking.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 112187,
        "commit_id": "14d2966b9e91ae16dcc39de8f41017a75cec8ff9",
        "repo": "nni",
        "path": "nni/retiarii/oneshot/pytorch/supermodule/sampling.py",
        "file_name": "sampling.py",
        "fun_name": "resample",
        "commit_message": "Valuechoice oneshot lightning (#4602)",
        "code": "def resample(self, memo):\n        \n        if self.label in memo:\n            self._sampled = memo[self.label]\n        else:\n            self._sampled = random.choice(self.op_names)\n        return {self.label: self._sampled}\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 67,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 49,
        "n_ast_nodes": 79,
        "n_identifiers": 8,
        "d_id": 24618,
        "documentation": {
            "docstring": "Random choose one path if label is not found in memo.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 206594,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/datastructures.py",
        "file_name": "datastructures.py",
        "fun_name": "__getitem__",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def __getitem__(self, key):\n        \n        use_func = key.startswith(self.prefix)\n        if use_func:\n            key = key[len(self.prefix) :]\n        value = super().__getitem__(key)\n        if use_func:\n            return self.func(value)\n        return value\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 85,
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        "vocab_size": 15,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 55,
        "n_ast_nodes": 91,
        "n_identifiers": 10,
        "d_id": 51581,
        "documentation": {
            "docstring": "\n        Retrieve the real value after stripping the prefix string (if\n        present). If the prefix is present, pass the value through self.func\n        before returning, otherwise return the raw value.\n        ",
            "n_words": 28,
            "vocab_size": 22,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 251401,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "mitmproxy/net/http/cookies.py",
        "file_name": "cookies.py",
        "fun_name": "_read_until",
        "commit_message": "make it black!",
        "code": "def _read_until(s, start, term):\n    \n    if start == len(s):\n        return \"\", start + 1\n    for i in range(start, len(s)):\n        if s[i] in term:\n            return s[start:i], i\n    return s[start : i + 1], i + 1\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "token_counts": 67,
        "n_ast_nodes": 104,
        "n_identifiers": 7,
        "d_id": 73717,
        "documentation": {
            "docstring": "\n    Read until one of the characters in term is reached.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 101557,
        "commit_id": "7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5",
        "repo": "faceswap",
        "path": "lib/training/preview_tk.py",
        "file_name": "preview_tk.py",
        "fun_name": "save_preview",
        "commit_message": "Training - Use custom preview pop-out",
        "code": "def save_preview(self, *args) -> None:\n        \n        if not self._save_var.get() and not isinstance(args[0], tk.Event):\n            return\n\n        root_path = os.path.join(os.path.realpath(os.path.dirname(sys.argv[0])))\n        now = datetime.now().strftime(\"%Y-%m-%d_%H.%M.%S\")\n        filename = os.path.join(root_path, f\"preview_{now}.png\")\n        cv2.imwrite(filename, self.source)\n        print(\"\")\n        logger.info(\"Saved preview to: '%s'\", filename)\n        self._save_var.set(False)\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 106,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 119,
        "n_ast_nodes": 200,
        "n_identifiers": 27,
        "d_id": 20967,
        "documentation": {
            "docstring": " Save out the full size preview to the faceswap folder on a save button press\n\n        Parameters\n        ----------\n        args: tuple\n            Tuple containing either the key press event (Ctrl+s shortcut) or the tk variable\n            arguments (save button press)\n        ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 87,
            "language": "en"
        }
    },
    {
        "id": 110284,
        "commit_id": "9b6abd0b4933811e0a45c2535ab8fd107db65dd9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/gridspec.py",
        "file_name": "gridspec.py",
        "fun_name": "subgridspec",
        "commit_message": "DOC: improve grammar and consistency",
        "code": "def subgridspec(self, nrows, ncols, **kwargs):\n        \n        return GridSpecFromSubplotSpec(nrows, ncols, self, **kwargs)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 37,
        "n_identifiers": 6,
        "d_id": 24026,
        "documentation": {
            "docstring": "\n        Create a GridSpec within this subplot.\n\n        The created `.GridSpecFromSubplotSpec` will have this `SubplotSpec` as\n        a parent.\n\n        Parameters\n        ----------\n        nrows : int\n            Number of rows in grid.\n\n        ncols : int\n            Number of columns in grid.\n\n        Returns\n        -------\n        `.GridSpecFromSubplotSpec`\n\n        Other Parameters\n        ----------------\n        **kwargs\n            All other parameters are passed to `.GridSpecFromSubplotSpec`.\n\n        See Also\n        --------\n        matplotlib.pyplot.subplots\n\n        Examples\n        --------\n        Adding three subplots in the space occupied by a single subplot::\n\n            fig = plt.figure()\n            gs0 = fig.add_gridspec(3, 1)\n            ax1 = fig.add_subplot(gs0[0])\n            ax2 = fig.add_subplot(gs0[1])\n            gssub = gs0[2].subgridspec(1, 3)\n            for i in range(3):\n                fig.add_subplot(gssub[0, i])\n        ",
            "n_words": 88,
            "vocab_size": 70,
            "n_whitespaces": 343,
            "language": "en"
        }
    },
    {
        "id": 275725,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/preprocessing/image.py",
        "file_name": "image.py",
        "fun_name": "random_brightness",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def random_brightness(x, brightness_range, scale=True):\n    \n    if len(brightness_range) != 2:\n        raise ValueError(\n            \"`brightness_range should be tuple or list of two floats. \"\n            \"Received: %s\" % (brightness_range,)\n        )\n\n    u = np.random.uniform(brightness_range[0], brightness_range[1])\n    return apply_brightness_shift(x, u, scale)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 81,
        "n_words": 33,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 58,
        "n_ast_nodes": 92,
        "n_identifiers": 11,
        "d_id": 81454,
        "documentation": {
            "docstring": "Performs a random brightness shift.\n\n    Deprecated: `tf.keras.preprocessing.image.random_brightness` does not operate\n    on tensors and is not recommended for new code. Prefer\n    `tf.keras.layers.RandomBrightness` which provides equivalent functionality as\n    a preprocessing layer. For more information, see the tutorial for\n    [augmenting images](\n    https://www.tensorflow.org/tutorials/images/data_augmentation), as well as\n    the [preprocessing layer guide](\n    https://www.tensorflow.org/guide/keras/preprocessing_layers).\n\n    Args:\n        x: Input tensor. Must be 3D.\n        brightness_range: Tuple of floats; brightness range.\n        scale: Whether to rescale the image such that minimum and maximum values\n            are 0 and 255 respectively. Default: True.\n\n    Returns:\n        Numpy image tensor.\n\n    Raises:\n        ValueError if `brightness_range` isn't a tuple.\n    ",
            "n_words": 90,
            "vocab_size": 77,
            "n_whitespaces": 172,
            "language": "en"
        }
    },
    {
        "id": 125635,
        "commit_id": "90cea203befa8f2e86e9c1c18bb3972296358e7b",
        "repo": "ray",
        "path": "python/ray/runtime_context.py",
        "file_name": "runtime_context.py",
        "fun_name": "get_job_id",
        "commit_message": "Ray 2.0 API deprecation (#26116)\n\nRay 2.0 API deprecation for:\r\n\r\n ray.remote(): placement_group\r\n ray.remote(): placement_group_bundle_index\r\n ray.remote(): placement_group_capture_child_tasks\r\n ray.get_dashboard_url()\r\n ray.get_resource_ids()\r\n ray.disconnect()\r\n ray.connect()\r\n ray.util.ActorGroup\r\n ray.util.ActorPool\r\n Add get_xx_id() to return hex (rather than object), and then deprecate the xx_id() (which returns Cython object): the xx here can be node, task etc.\r\n ray start: --plasma-store-socket-name\r\n ray start: --raylet-socket-name",
        "code": "def get_job_id(self) -> str:\n        \n        job_id = self.worker.current_job_id\n        assert not job_id.is_nil()\n        return job_id.hex()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 28,
        "n_ast_nodes": 49,
        "n_identifiers": 8,
        "d_id": 27932,
        "documentation": {
            "docstring": "Get current job ID for this worker or driver.\n\n        Job ID is the id of your Ray drivers that create tasks or actors.\n\n        Returns:\n            If called by a driver, this returns the job ID. If called in\n                a task, return the job ID of the associated driver. The\n                job ID will be hex format.\n        ",
            "n_words": 54,
            "vocab_size": 38,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 73513,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/settings/tests/test_model.py",
        "file_name": "test_model.py",
        "fun_name": "test_select_related",
        "commit_message": "Reformat with black",
        "code": "def test_select_related(self, expected_queries=4):\n        \n        request = self.get_request()\n\n        self._create_importantpages_object()\n\n        # force site query beforehand\n        Site.find_for_request(request)\n\n        # fetch settings and access foreiegn keys\n        with self.assertNumQueries(expected_queries):\n            settings = ImportantPages.for_request(request)\n            settings.sign_up_page\n            settings.general_terms_page\n            settings.privacy_policy_page\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 121,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 53,
        "n_ast_nodes": 94,
        "n_identifiers": 15,
        "d_id": 16035,
        "documentation": {
            "docstring": "The `select_related` attribute on setting models is `None` by default, so fetching foreign keys values requires additional queries",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 101393,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "scripts/fsmedia.py",
        "file_name": "fsmedia.py",
        "fun_name": "_check_input_folder",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _check_input_folder(self) -> bool:\n        \n        if not os.path.exists(self._args.input_dir):\n            logger.error(\"Input location %s not found.\", self._args.input_dir)\n            sys.exit(1)\n        if (os.path.isfile(self._args.input_dir) and\n                os.path.splitext(self._args.input_dir)[1].lower() in _video_extensions):\n            logger.info(\"Input Video: %s\", self._args.input_dir)\n            retval = True\n        else:\n            logger.info(\"Input Directory: %s\", self._args.input_dir)\n            retval = False\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 153,
        "n_words": 37,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 19,
        "token_counts": 113,
        "n_ast_nodes": 186,
        "n_identifiers": 18,
        "d_id": 20808,
        "documentation": {
            "docstring": " Check whether the input is a folder or video.\n\n        Returns\n        -------\n        bool\n            ``True`` if the input is a video otherwise ``False``\n        ",
            "n_words": 21,
            "vocab_size": 17,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 207903,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_empty",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_empty(self):\n        \n        response = self.client.get(reverse(\"admin:admin_views_podcast_changelist\"))\n        self.assertNotContains(response, \"release_date__year=\")\n        self.assertNotContains(response, \"release_date__month=\")\n        self.assertNotContains(response, \"release_date__day=\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 46,
        "n_words": 11,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 78,
        "n_identifiers": 7,
        "d_id": 52156,
        "documentation": {
            "docstring": "\n        No date hierarchy links display with empty changelist.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 308838,
        "commit_id": "7872f87dd74fb4e2b610bb589facc0f763f153ae",
        "repo": "core",
        "path": "tests/components/webhook/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_async_generate_path",
        "commit_message": "Allow registering a webhook as local only (#63516)",
        "code": "async def test_async_generate_path(hass):\n    \n    path = webhook.async_generate_path(\"some_id\")\n    assert path == \"/api/webhook/some_id\"\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 18,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 107567,
        "documentation": {
            "docstring": "Test generating just the path component of the url correctly.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 71787,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_account_management.py",
        "file_name": "test_account_management.py",
        "fun_name": "test_not_logged_in_redirect_default_settings",
        "commit_message": "Reformat with black",
        "code": "def test_not_logged_in_redirect_default_settings(self):\n        \n        # Get dashboard with default LOGIN_URL setting\n        with self.settings(LOGIN_URL=\"django.contrib.auth.views.login\"):\n            response = self.client.get(reverse(\"wagtailadmin_home\"))\n\n        # Check that the user was redirected to the login page and that next was set correctly\n        # Note: The user will be redirected to 'django.contrib.auth.views.login' but\n        # this must be the same URL as 'wagtailadmin_login'\n        self.assertEqual(response.status_code, 302)\n        self.assertRedirects(\n            response,\n            reverse(\"wagtailadmin_login\") + \"?next=\" + reverse(\"wagtailadmin_home\"),\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 156,
        "n_words": 60,
        "vocab_size": 47,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 58,
        "n_ast_nodes": 110,
        "n_identifiers": 11,
        "d_id": 15743,
        "documentation": {
            "docstring": "\n        This does the same as the above test but checks that it\n        redirects to the correct place when the user has not set\n        the LOGIN_URL setting correctly\n        ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 92011,
        "commit_id": "1c949dfcf87384cdf976710ebf8fe3c536e26807",
        "repo": "sentry",
        "path": "src/sentry/tasks/beacon.py",
        "file_name": "beacon.py",
        "fun_name": "send_beacon",
        "commit_message": "feat(locks): Add locks count metrics tagged with name (#36002)",
        "code": "def send_beacon():\n    \n    from sentry import options\n    from sentry.models import Broadcast, Organization, Project, Team, User\n\n    install_id = get_install_id()\n\n    if should_skip_beacon(install_id):\n        return\n\n    end = timezone.now()\n    events_24h = tsdb.get_sums(\n        model=tsdb.models.internal, keys=[\"events.total\"], start=end - timedelta(hours=24), end=end\n    )[\"events.total\"]\n\n    # we need this to be explicitly configured and it defaults to None,\n    # which is the same as False\n    anonymous = options.get(\"beacon.anonymous\") is not False\n\n    payload = {\n        \"install_id\": install_id,\n        \"version\": sentry.get_version(),\n        \"docker\": sentry.is_docker(),\n        \"python_version\": platform.python_version(),\n        \"data\": {\n            \"users\": User.objects.count(),\n            \"projects\": Project.objects.count(),\n            \"teams\": Team.objects.count(),\n            \"organizations\": Organization.objects.count(),\n            \"events.24h\": events_24h,\n        },\n        \"packages\": get_all_package_versions(),\n        \"anonymous\": anonymous,\n    }\n\n    if not anonymous:\n        payload[\"admin_email\"] = options.get(\"system.admin-email\")\n\n    # TODO(dcramer): relay the response 'notices' as admin broadcasts\n    try:\n        request = safe_urlopen(BEACON_URL, json=payload, timeout=5)\n        response = safe_urlread(request)\n    except Exception:\n        logger.warning(\"beacon.failed\", exc_info=True, extra={\"install_id\": install_id})\n        return\n    else:\n        logger.info(\"beacon.sent\", extra={\"install_id\": install_id})\n\n    data = json.loads(response)\n\n    if \"version\" in data:\n        options.set(\"sentry:latest_version\", data[\"version\"][\"stable\"])\n\n    if \"notices\" in data:\n        upstream_ids = set()\n        for notice in data[\"notices\"]:\n            upstream_ids.add(notice[\"id\"])\n            defaults = {\n                \"title\": notice[\"title\"],\n                \"link\": notice.get(\"link\"),\n                \"message\": notice[\"message\"],\n            }\n            # XXX(dcramer): we're missing a unique constraint on upstream_id\n            # so we're using a lock to work around that. In the future we'd like\n            # to have a data migration to clean up the duplicates and add the constraint\n            lock = locks.get(\"broadcasts:{}\".format(notice[\"id\"]), duration=60, name=\"broadcasts\")\n            with lock.acquire():\n                affected = Broadcast.objects.filter(upstream_id=notice[\"id\"]).update(**defaults)\n                if not affected:\n                    Broadcast.objects.create(upstream_id=notice[\"id\"], **defaults)\n\n        Broadcast.objects.filter(upstream_id__isnull=False).exclude(\n            upstream_id__in=upstream_ids\n        ).update(is_active=False)\n\n\n@instrumented_task(name=\"sentry.tasks.send_beacon_metric\", queue=\"update\")",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "@instrumented_task(name=\"sentry.tasks.send_beacon_metric\", queue=\"update\")",
        "n_ast_errors": 1,
        "ast_levels": 19,
        "n_whitespaces": 670,
        "n_words": 213,
        "vocab_size": 159,
        "complexity": 8,
        "nloc": 56,
        "token_counts": 434,
        "n_ast_nodes": 772,
        "n_identifiers": 71,
        "d_id": 18853,
        "documentation": {
            "docstring": "\n    Send a Beacon to a remote server operated by the Sentry team.\n\n    See the documentation for more details.\n    ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 155188,
        "commit_id": "193505fdf0c984743397ba3df56262f30aee13a8",
        "repo": "modin",
        "path": "modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "add_to_apply_calls",
        "commit_message": "FEAT-#5053: Add pandas on unidist execution with MPI backend (#5059)\n\nSigned-off-by: Igoshev, Iaroslav <iaroslav.igoshev@intel.com>",
        "code": "def add_to_apply_calls(self, func, *args, length=None, width=None, **kwargs):\n        \n        return PandasOnUnidistDataframePartition(\n            self._data,\n            call_queue=self.call_queue + [[func, args, kwargs]],\n            length=length,\n            width=width,\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 83,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 54,
        "n_ast_nodes": 76,
        "n_identifiers": 10,
        "d_id": 36279,
        "documentation": {
            "docstring": "\n        Add a function to the call queue.\n\n        Parameters\n        ----------\n        func : callable or unidist.ObjectRef\n            Function to be added to the call queue.\n        *args : iterable\n            Additional positional arguments to be passed in `func`.\n        length : unidist.ObjectRef or int, optional\n            Length, or reference to length, of wrapped ``pandas.DataFrame``.\n        width : unidist.ObjectRef or int, optional\n            Width, or reference to width, of wrapped ``pandas.DataFrame``.\n        **kwargs : dict\n            Additional keyword arguments to be passed in `func`.\n\n        Returns\n        -------\n        PandasOnUnidistDataframePartition\n            A new ``PandasOnUnidistDataframePartition`` object.\n\n        Notes\n        -----\n        It does not matter if `func` is callable or an ``unidist.ObjectRef``. Unidist will\n        handle it correctly either way. The keyword arguments are sent as a dictionary.\n        ",
            "n_words": 107,
            "vocab_size": 70,
            "n_whitespaces": 286,
            "language": "en"
        }
    },
    {
        "id": 177254,
        "commit_id": "50ff08de69c6e9541cd6c029bede5dabf56cfe73",
        "repo": "networkx",
        "path": "networkx/algorithms/operators/all.py",
        "file_name": "all.py",
        "fun_name": "compose_all",
        "commit_message": "Make all.py generator friendly (#5984)\n\n* Make compose_all generator friendly\r\n\r\n* Make disjoint_union_all and intersection_all generator friendly\r\n\r\n* Refactor disjoint_union_all to yield relabeled graphs\r\n\r\n* Make union_all generator friendly\r\n\r\n* Fix intersection_all\r\n\r\n* Fix union_all signature\r\n\r\n* Allow passing an infinite rename generator to union_all\r\n\r\n* Copy over generalizations to binary.py\r\n\r\n* Clean up rename\r\n\r\n* Simplify first_label in disjoint_union_all\r\n\r\n* Simplify disjoint_union_all\r\n\r\n* Add missing R.graph.update in intersection_all",
        "code": "def compose_all(graphs):\n    \n    R = None\n\n    # add graph attributes, H attributes take precedent over G attributes\n    for i, G in enumerate(graphs):\n        if i == 0:\n            # create new graph\n            R = G.__class__()\n        elif G.is_multigraph() != R.is_multigraph():\n            raise nx.NetworkXError(\"All graphs must be graphs or multigraphs.\")\n\n        R.graph.update(G.graph)\n        R.add_nodes_from(G.nodes(data=True))\n        R.add_edges_from(\n            G.edges(keys=True, data=True) if G.is_multigraph() else G.edges(data=True)\n        )\n\n    if R is None:\n        raise ValueError(\"cannot apply compose_all to an empty list\")\n\n    return R\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 179,
        "n_words": 68,
        "vocab_size": 55,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 118,
        "n_ast_nodes": 197,
        "n_identifiers": 19,
        "d_id": 42318,
        "documentation": {
            "docstring": "Returns the composition of all graphs.\n\n    Composition is the simple union of the node sets and edge sets.\n    The node sets of the supplied graphs need not be disjoint.\n\n    Parameters\n    ----------\n    graphs : iterable\n       Iterable of NetworkX graphs\n\n    Returns\n    -------\n    C : A graph with the same type as the first graph in list\n\n    Raises\n    ------\n    ValueError\n       If `graphs` is an empty list.\n\n    Notes\n    -----\n    It is recommended that the supplied graphs be either all directed or all\n    undirected.\n\n    Graph, edge, and node attributes are propagated to the union graph.\n    If a graph attribute is present in multiple graphs, then the value\n    from the last graph in the list with that attribute is used.\n    ",
            "n_words": 114,
            "vocab_size": 73,
            "n_whitespaces": 183,
            "language": "en"
        }
    },
    {
        "id": 247729,
        "commit_id": "9e06e220649cc0139749c388a894bee0d65d5f4e",
        "repo": "synapse",
        "path": "tests/handlers/test_federation.py",
        "file_name": "test_federation.py",
        "fun_name": "test_backfill_with_many_backward_extremities",
        "commit_message": "Add type hints to more tests files. (#12240)",
        "code": "def test_backfill_with_many_backward_extremities(self) -> None:\n        \n        # create the room\n        user_id = self.register_user(\"kermit\", \"test\")\n        tok = self.login(\"kermit\", \"test\")\n        requester = create_requester(user_id)\n\n        room_id = self.helper.create_room_as(room_creator=user_id, tok=tok)\n\n        ev1 = self.helper.send(room_id, \"first message\", tok=tok)\n\n        # Create \"many\" backward extremities. The magic number we're trying to\n        # create more than is 5 which corresponds to the number of backward\n        # extremities we slice off in `_maybe_backfill_inner`\n        for _ in range(0, 8):\n            event_handler = self.hs.get_event_creation_handler()\n            event, context = self.get_success(\n                event_handler.create_event(\n                    requester,\n                    {\n                        \"type\": \"m.room.message\",\n                        \"content\": {\n                            \"msgtype\": \"m.text\",\n                            \"body\": \"message connected to fake event\",\n                        },\n                        \"room_id\": room_id,\n                        \"sender\": user_id,\n                    },\n                    prev_event_ids=[\n                        ev1[\"event_id\"],\n                        # We're creating an backward extremity each time thanks\n                        # to this fake event\n                        generate_fake_event_id(),\n                    ],\n                )\n            )\n            self.get_success(\n                event_handler.handle_new_client_event(requester, event, context)\n            )\n\n        current_depth = 1\n        limit = 100\n        with LoggingContext(\"receive_pdu\"):\n            # Make sure backfill still works\n            d = run_in_background(\n                self.hs.get_federation_handler().maybe_backfill,\n                room_id,\n                current_depth,\n                limit,\n            )\n        self.get_success(d)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 795,
        "n_words": 141,
        "vocab_size": 106,
        "complexity": 2,
        "nloc": 47,
        "token_counts": 197,
        "n_ast_nodes": 335,
        "n_identifiers": 33,
        "d_id": 71879,
        "documentation": {
            "docstring": "\n        Check that we can backfill with many backward extremities.\n        The goal is to make sure that when we only use a portion\n        of backwards extremities(the magic number is more than 5),\n        no errors are thrown.\n\n        Regression test, see #11027\n        ",
            "n_words": 39,
            "vocab_size": 36,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 87840,
        "commit_id": "b3ce25d7c3ce85a9b7195f97c6d3d76c764e1808",
        "repo": "sentry",
        "path": "src/sentry/auth/access.py",
        "file_name": "access.py",
        "fun_name": "project_ids_with_team_membership",
        "commit_message": "ref(access): Remove models from Access fields (#40940)\n\nAnticipating changes for Hybrid Cloud silo boundaries, change the public\r\ninterface of the `Access` class to not expose any ORM models as\r\ndataclass fields. As a first step, replace all such objects with their\r\nraw IDs. (Credit to @corps for the underlying idea. Future steps:\r\nreplace models as method parameters; replace raw IDs with API object\r\nrepresentations.)",
        "code": "def project_ids_with_team_membership(self) -> FrozenSet[int]:\n        \n\n        teams = self._team_memberships.keys()\n        if not teams:\n            return frozenset()\n\n        with sentry_sdk.start_span(op=\"get_project_access_in_teams\") as span:\n            projects = frozenset(\n                Project.objects.filter(status=ProjectStatus.VISIBLE, teams__in=teams)\n                .distinct()\n                .values_list(\"id\", flat=True)\n            )\n            span.set_data(\"Project Count\", len(projects))\n            span.set_data(\"Team Count\", len(teams))\n\n        return projects\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 168,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 22,
        "token_counts": 98,
        "n_ast_nodes": 168,
        "n_identifiers": 25,
        "d_id": 18338,
        "documentation": {
            "docstring": "Return the IDs of projects to which the user has access via actual team membership.\n\n        This represents the set of all projects for which `has_project_membership`\n        returns true. Use that method where possible and use this property only when\n        you need to iterate or query for all such teams.\n\n        Compare to accessible_project_ids, which is equal to this property in the\n        typical case but represents a superset of IDs in case of superuser access.\n        ",
            "n_words": 72,
            "vocab_size": 52,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 119872,
        "commit_id": "466bea1662ea13d1c5334f4db414bec20deb1fb4",
        "repo": "jax",
        "path": "jax/_src/numpy/setops.py",
        "file_name": "setops.py",
        "fun_name": "setdiff1d",
        "commit_message": "lax_numpy: refactor set operations into separate private submodule",
        "code": "def setdiff1d(ar1, ar2, assume_unique=False, *, size=None, fill_value=None):\n  _check_arraylike(\"setdiff1d\", ar1, ar2)\n  if size is None:\n    ar1 = core.concrete_or_error(None, ar1, \"The error arose in setdiff1d()\")\n  else:\n    size = core.concrete_or_error(operator.index, size, \"The error arose in setdiff1d()\")\n  ar1 = asarray(ar1)\n  fill_value = asarray(0 if fill_value is None else fill_value, dtype=ar1.dtype)\n  if ar1.size == 0:\n    return full_like(ar1, fill_value, shape=size or 0)\n  if not assume_unique:\n    ar1 = unique(ar1, size=size and ar1.size)\n  mask = in1d(ar1, ar2, invert=True)\n  if size is None:\n    return ar1[mask]\n  else:\n    if not (assume_unique or size is None):\n      # Set mask to zero at locations corresponding to unique() padding.\n      n_unique = ar1.size + 1 - (ar1 == ar1[0]).sum()\n      mask = where(arange(ar1.size) < n_unique, mask, False)\n    return where(arange(size) < mask.sum(), ar1[where(mask, size=size)], fill_value)\n\n\n@_wraps(np.union1d,\n  lax_description=_dedent(),\n  extra_params=_dedent())",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.union1d,\n  lax_description=_dedent(\"\"\"\n    Because the size of the output of ``union1d`` is data-dependent, the function is not\n    typically compatible with JIT. The JAX version adds the optional ``size`` argument which\n    must be specified statically for ``jnp.union1d`` to be used within some of JAX's\n    transformations.\"\"\"),\n  extra_params=_dedent(\"\"\"\n    size : int, optional\n        If specified, the first ``size`` elements of the result will be returned. If there are\n        fewer elements than ``size`` indicates, the return value will be padded with ``fill_value``.\n    fill_value : array_like, optional\n        When ``size`` is specified and there are fewer than the indicated number of elements, the\n        remaining elements will be filled with ``fill_value``, which defaults to the minimum\n        value of the union.\"\"\"))",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 167,
        "n_words": 121,
        "vocab_size": 80,
        "complexity": 10,
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        "n_identifiers": 29,
        "d_id": 26702,
        "documentation": {
            "docstring": "\n    Because the size of the output of ``union1d`` is data-dependent, the function is not\n    typically compatible with JIT. The JAX version adds the optional ``size`` argument which\n    must be specified statically for ``jnp.union1d`` to be used within some of JAX's\n    transformations.\n    size : int, optional\n        If specified, the first ``size`` elements of the result will be returned. If there are\n        fewer elements than ``size`` indicates, the return value will be padded with ``fill_value``.\n    fill_value : array_like, optional\n        When ``size`` is specified and there are fewer than the indicated number of elements, the\n        remaining elements will be filled with ``fill_value``, which defaults to the minimum\n        value of the union.",
            "n_words": 108,
            "vocab_size": 65,
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            "language": "en"
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    },
    {
        "id": 205781,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "select_related",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def select_related(self, *fields):\n        \n        self._not_support_combined_queries(\"select_related\")\n        if self._fields is not None:\n            raise TypeError(\n                \"Cannot call select_related() after .values() or .values_list()\"\n            )\n\n        obj = self._chain()\n        if fields == (None,):\n            obj.query.select_related = False\n        elif fields:\n            obj.query.add_select_related(fields)\n        else:\n            obj.query.select_related = True\n        return obj\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 164,
        "n_words": 38,
        "vocab_size": 33,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 72,
        "n_ast_nodes": 122,
        "n_identifiers": 10,
        "d_id": 51212,
        "documentation": {
            "docstring": "\n        Return a new QuerySet instance that will select related objects.\n\n        If fields are specified, they must be ForeignKey fields and only those\n        related objects are included in the selection.\n\n        If select_related(None) is called, clear the list.\n        ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 271475,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/partial_batch_padding_handler.py",
        "file_name": "partial_batch_padding_handler.py",
        "fun_name": "update_mask",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def update_mask(self, padding_mask, dataset_batch):\n        \n        original_batch_size = self.get_real_batch_size(dataset_batch)\n        missing_count = self.padded_batch_size - original_batch_size\n        mask = backend.concatenate(\n            [tf.ones(original_batch_size), tf.zeros(missing_count)], axis=0\n        )\n        return backend.concatenate([padding_mask, mask], axis=0)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 76,
        "n_words": 23,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 66,
        "n_ast_nodes": 101,
        "n_identifiers": 15,
        "d_id": 80781,
        "documentation": {
            "docstring": "Calculate and cache the amount of padding required for a batch.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 107500,
        "commit_id": "f156db08eee54d285ab0fb4e031e48d078ba6aa3",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backend_bases.py",
        "file_name": "backend_bases.py",
        "fun_name": "release_zoom",
        "commit_message": "DOC: More cleanup axes -> Axes",
        "code": "def release_zoom(self, event):\n        \n        if self._zoom_info is None:\n            return\n\n        # We don't check the event button here, so that zooms can be cancelled\n        # by (pressing and) releasing another mouse button.\n        self.canvas.mpl_disconnect(self._zoom_info.cid)\n        self.remove_rubberband()\n\n        start_x, start_y = self._zoom_info.start_xy\n        key = event.key\n        # Force the key on colorbars to ignore the zoom-cancel on the\n        # short-axis side\n        if self._zoom_info.cbar == \"horizontal\":\n            key = \"x\"\n        elif self._zoom_info.cbar == \"vertical\":\n            key = \"y\"\n        # Ignore single clicks: 5 pixels is a threshold that allows the user to\n        # \"cancel\" a zoom action by zooming by less than 5 pixels.\n        if ((abs(event.x - start_x) < 5 and key != \"y\") or\n                (abs(event.y - start_y) < 5 and key != \"x\")):\n            self.canvas.draw_idle()\n            self._zoom_info = None\n            return\n\n        for i, ax in enumerate(self._zoom_info.axes):\n            # Detect whether this Axes is twinned with an earlier Axes in the\n            # list of zoomed Axes, to avoid double zooming.\n            twinx = any(ax.get_shared_x_axes().joined(ax, prev)\n                        for prev in self._zoom_info.axes[:i])\n            twiny = any(ax.get_shared_y_axes().joined(ax, prev)\n                        for prev in self._zoom_info.axes[:i])\n            ax._set_view_from_bbox(\n                (start_x, start_y, event.x, event.y),\n                self._zoom_info.direction, key, twinx, twiny)\n\n        self.canvas.draw_idle()\n        self._zoom_info = None\n        self.push_current()\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 521,
        "n_words": 176,
        "vocab_size": 118,
        "complexity": 11,
        "nloc": 27,
        "token_counts": 240,
        "n_ast_nodes": 392,
        "n_identifiers": 31,
        "d_id": 22787,
        "documentation": {
            "docstring": "Callback for mouse button release in zoom to rect mode.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 107638,
        "commit_id": "d69be2554cf6d1ac711bf433b1d6f176e3290d4f",
        "repo": "matplotlib",
        "path": "lib/matplotlib/table.py",
        "file_name": "table.py",
        "fun_name": "set_text_props",
        "commit_message": "Clarify error message for bad keyword arguments.\n\n`plot([], [], foo=42)` previously emitted\n```\n'Line2D' object has no property 'foo'\n```\nwhich refers to the Matplotlib-specific concept of \"properties\".  It now\ninstead emits\n```\nLine2D.set() got an unexpected keyword argument 'foo'\n```\nwhich is modeled after the standard error message for unknown keyword\narguments.\n\n(To maximize backcompat, the implementation goes through a new\n_internal_update, which does *not* error when the same prop is passed\nunder different aliases.  This could be changed later, but is not the\ngoal of this PR.)",
        "code": "def set_text_props(self, **kwargs):\n        \n        self._text._internal_update(kwargs)\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 28,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 22849,
        "documentation": {
            "docstring": "\n        Update the text properties.\n\n        Valid keyword arguments are:\n\n        %(Text:kwdoc)s\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 206725,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/regex_helper.py",
        "file_name": "regex_helper.py",
        "fun_name": "get_quantifier",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_quantifier(ch, input_iter):\n    \n    if ch in \"*?+\":\n        try:\n            ch2, escaped = next(input_iter)\n        except StopIteration:\n            ch2 = None\n        if ch2 == \"?\":\n            ch2 = None\n        if ch == \"+\":\n            return 1, ch2\n        return 0, ch2\n\n    quant = []\n    while ch != \"}\":\n        ch, escaped = next(input_iter)\n        quant.append(ch)\n    quant = quant[:-1]\n    values = \"\".join(quant).split(\",\")\n\n    # Consume the trailing '?', if necessary.\n    try:\n        ch, escaped = next(input_iter)\n    except StopIteration:\n        ch = None\n    if ch == \"?\":\n        ch = None\n    return int(values[0]), ch\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 226,
        "n_words": 79,
        "vocab_size": 39,
        "complexity": 8,
        "nloc": 24,
        "token_counts": 128,
        "n_ast_nodes": 225,
        "n_identifiers": 13,
        "d_id": 51659,
        "documentation": {
            "docstring": "\n    Parse a quantifier from the input, where \"ch\" is the first character in the\n    quantifier.\n\n    Return the minimum number of occurrences permitted by the quantifier and\n    either None or the next character from the input_iter if the next character\n    is not part of the quantifier.\n    ",
            "n_words": 45,
            "vocab_size": 29,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 186002,
        "commit_id": "8d3b0f22eca8babf95470acf39fc626a1b0be1b4",
        "repo": "textual",
        "path": "src/textual/_spatial_map.py",
        "file_name": "_spatial_map.py",
        "fun_name": "placement_map",
        "commit_message": "first iteration of spatial map",
        "code": "def placement_map(self) -> Mapping[tuple[int, int], list[WidgetPlacement]]:\n        \n        if self._map is None:\n            self._map = self._build_placements(self._placements)\n            return self._map\n        return self._map\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 60,
        "n_words": 17,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 48,
        "n_ast_nodes": 74,
        "n_identifiers": 10,
        "d_id": 45286,
        "documentation": {
            "docstring": "A mapping of block coordinate on to widget placement.\n\n        Returns:\n            Mapping[tuple[int, int], list[WidgetPlacement]]: Mapping.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 110244,
        "commit_id": "9b6abd0b4933811e0a45c2535ab8fd107db65dd9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/artist.py",
        "file_name": "artist.py",
        "fun_name": "_get_tightbbox_for_layout_only",
        "commit_message": "DOC: improve grammar and consistency",
        "code": "def _get_tightbbox_for_layout_only(obj, *args, **kwargs):\n    \n    try:\n        return obj.get_tightbbox(*args, **{**kwargs, \"for_layout_only\": True})\n    except TypeError:\n        return obj.get_tightbbox(*args, **kwargs)\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 38,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 76,
        "n_identifiers": 6,
        "d_id": 23986,
        "documentation": {
            "docstring": "\n    Matplotlib's `.Axes.get_tightbbox` and `.Axis.get_tightbbox` support a\n    *for_layout_only* kwarg; this helper tries to use the kwarg but skips it\n    when encountering third-party subclasses that do not support it.\n    ",
            "n_words": 27,
            "vocab_size": 26,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 135997,
        "commit_id": "e707ce4fb3717e3c05118c57f503dfbd03552ca9",
        "repo": "ray",
        "path": "rllib/evaluation/worker_set.py",
        "file_name": "worker_set.py",
        "fun_name": "_worker_health_check",
        "commit_message": "[RLlib] Refactor `WorkerSet` on top of `FaultTolerantActorManager`. (#29938)\n\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def _worker_health_check(self) -> List[int]:\n        \n        logger.info(\"Health checking all workers ...\")\n\n        remote_results = self.__worker_manager.foreach_actor(\n            lambda w: w.sample_with_count(),\n            healthy_only=False,\n        )\n\n        return [\n            r.actor_id\n            for r in remote_results\n            if not r.ok and isinstance(r.get(), RayError)\n        ]\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 128,
        "n_words": 31,
        "vocab_size": 30,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 65,
        "n_ast_nodes": 105,
        "n_identifiers": 18,
        "d_id": 30789,
        "documentation": {
            "docstring": "Performs a health-check on each remote worker.\n\n        Returns:\n            List of indices (into `self._remote_workers` list) of faulty workers.\n            Note that index=1 is the 0th item in `self._remote_workers`.\n        ",
            "n_words": 26,
            "vocab_size": 25,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 220442,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/events.py",
        "file_name": "events.py",
        "fun_name": "get_running_loop",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_running_loop():\n    \n    # NOTE: this function is implemented in C (see _asynciomodule.c)\n    loop = _get_running_loop()\n    if loop is None:\n        raise RuntimeError('no running event loop')\n    return loop\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 48,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 22,
        "n_ast_nodes": 43,
        "n_identifiers": 4,
        "d_id": 55997,
        "documentation": {
            "docstring": "Return the running event loop.  Raise a RuntimeError if there is none.\n\n    This function is thread-specific.\n    ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 261669,
        "commit_id": "c1cfc4d4f36f9c00413e20d0ef85bed208a502ca",
        "repo": "scikit-learn",
        "path": "sklearn/inspection/_pd_utils.py",
        "file_name": "_pd_utils.py",
        "fun_name": "_get_feature_index",
        "commit_message": "ENH Extend PDP for nominal categorical features (#18298)\n\nCo-authored-by: Jérémie du Boisberranger <jeremiedbb@users.noreply.github.com>\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>\r\n\r\nCloses https://github.com/scikit-learn/scikit-learn/issues/14969",
        "code": "def _get_feature_index(fx, feature_names=None):\n    \n    if isinstance(fx, str):\n        if feature_names is None:\n            raise ValueError(\n                f\"Cannot plot partial dependence for feature {fx!r} since \"\n                \"the list of feature names was not provided, neither as \"\n                \"column names of a pandas data-frame nor via the feature_names \"\n                \"parameter.\"\n            )\n        try:\n            return feature_names.index(fx)\n        except ValueError as e:\n            raise ValueError(f\"Feature {fx!r} not in feature_names\") from e\n    return fx\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 196,
        "n_words": 62,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 56,
        "n_ast_nodes": 107,
        "n_identifiers": 8,
        "d_id": 76930,
        "documentation": {
            "docstring": "Get feature index.\n\n    Parameters\n    ----------\n    fx : int or str\n        Feature index or name.\n\n    feature_names : list of str, default=None\n        All feature names from which to search the indices.\n\n    Returns\n    -------\n    idx : int\n        Feature index.\n    ",
            "n_words": 36,
            "vocab_size": 29,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 196699,
        "commit_id": "9ad8ab9fe58051cf11626ba6654852fcfec60147",
        "repo": "sympy",
        "path": "sympy/stats/joint_rv_types.py",
        "file_name": "joint_rv_types.py",
        "fun_name": "GeneralizedMultivariateLogGamma",
        "commit_message": "Documentation cleanup 5",
        "code": "def GeneralizedMultivariateLogGamma(syms, delta, v, lamda, mu):\n    \n    return multivariate_rv(GeneralizedMultivariateLogGammaDistribution,\n                            syms, delta, v, lamda, mu)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 46,
        "n_words": 13,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 29,
        "n_ast_nodes": 39,
        "n_identifiers": 8,
        "d_id": 48117,
        "documentation": {
            "docstring": "\n    Creates a joint random variable with generalized multivariate log gamma\n    distribution.\n\n    The joint pdf can be found at [1].\n\n    Parameters\n    ==========\n\n    syms: list/tuple/set of symbols for identifying each component\n    delta: A constant in range $[0, 1]$\n    v: Positive real number\n    lamda: List of positive real numbers\n    mu: List of positive real numbers\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    Examples\n    ========\n\n    >>> from sympy.stats import density\n    >>> from sympy.stats.joint_rv_types import GeneralizedMultivariateLogGamma\n    >>> from sympy import symbols, S\n    >>> v = 1\n    >>> l, mu = [1, 1, 1], [1, 1, 1]\n    >>> d = S.Half\n    >>> y = symbols('y_1:4', positive=True)\n    >>> Gd = GeneralizedMultivariateLogGamma('G', d, v, l, mu)\n    >>> density(Gd)(y[0], y[1], y[2])\n    Sum(exp((n + 1)*(y_1 + y_2 + y_3) - exp(y_1) - exp(y_2) -\n    exp(y_3))/(2**n*gamma(n + 1)**3), (n, 0, oo))/2\n\n    References\n    ==========\n\n    .. [1] https://en.wikipedia.org/wiki/Generalized_multivariate_log-gamma_distribution\n    .. [2] https://www.researchgate.net/publication/234137346_On_a_multivariate_log-gamma_distribution_and_the_use_of_the_distribution_in_the_Bayesian_analysis\n\n    Note\n    ====\n\n    If the GeneralizedMultivariateLogGamma is too long to type use,\n    ``from sympy.stats.joint_rv_types import GeneralizedMultivariateLogGamma as GMVLG``\n    If you want to pass the matrix omega instead of the constant delta, then use,\n    ``GeneralizedMultivariateLogGammaOmega``.\n\n    ",
            "n_words": 167,
            "vocab_size": 122,
            "n_whitespaces": 279,
            "language": "en"
        }
    },
    {
        "id": 127648,
        "commit_id": "7ba37885c67844d2eb18a63dcf3b7ac7f66ce89f",
        "repo": "ray",
        "path": "rllib/algorithms/dqn/tests/test_dqn.py",
        "file_name": "test_dqn.py",
        "fun_name": "test_dqn_compilation_integer_rewards",
        "commit_message": "Cast rewards as tf.float32 to fix error in DQN in tf2 (#28384)\n\n* Cast rewards as tf.float32 to fix error in DQN in tf2\r\n\r\nSigned-off-by: mgerstgrasser <matthias@gerstgrasser.net>\r\n\r\n* Add test case for DQN with integer rewards\r\n\r\nSigned-off-by: mgerstgrasser <matthias@gerstgrasser.net>\r\n\r\nSigned-off-by: mgerstgrasser <matthias@gerstgrasser.net>",
        "code": "def test_dqn_compilation_integer_rewards(self):\n        \n        num_iterations = 1\n        config = (\n            dqn.dqn.DQNConfig()\n            .rollouts(num_rollout_workers=2)\n            .training(num_steps_sampled_before_learning_starts=0)\n        )\n\n        for _ in framework_iterator(config, with_eager_tracing=True):\n            # Double-dueling DQN.\n            print(\"Double-dueling\")\n            plain_config = deepcopy(config)\n            trainer = dqn.DQN(config=plain_config, env=\"Taxi-v3\")\n            for i in range(num_iterations):\n                results = trainer.train()\n                check_train_results(results)\n                print(results)\n\n            check_compute_single_action(trainer)\n            trainer.stop()\n\n            # Rainbow.\n            print(\"Rainbow\")\n            rainbow_config = deepcopy(config).training(\n                num_atoms=10, noisy=True, double_q=True, dueling=True, n_step=5\n            )\n            trainer = dqn.DQN(config=rainbow_config, env=\"Taxi-v3\")\n            for i in range(num_iterations):\n                results = trainer.train()\n                check_train_results(results)\n                print(results)\n\n            check_compute_single_action(trainer)\n\n            trainer.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 404,
        "n_words": 66,
        "vocab_size": 43,
        "complexity": 4,
        "nloc": 28,
        "token_counts": 181,
        "n_ast_nodes": 300,
        "n_identifiers": 32,
        "d_id": 28479,
        "documentation": {
            "docstring": "Test whether DQN can be built on all frameworks.\n        Unlike the previous test, this uses an environment with integer rewards\n        in order to test that type conversions are working correctly.",
            "n_words": 30,
            "vocab_size": 30,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 259191,
        "commit_id": "a794c58692a1f3e7a85a42d8c7f7ddd5fcf18baa",
        "repo": "scikit-learn",
        "path": "sklearn/ensemble/_bagging.py",
        "file_name": "_bagging.py",
        "fun_name": "_estimator_has",
        "commit_message": "MNT Replace if_delegate_has_method with available_if in ensemble and semi_supervised (#20545)\n\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def _estimator_has(attr):\n    \n    return lambda self: (\n        hasattr(self.estimators_[0], attr)\n        if hasattr(self, \"estimators_\")\n        else hasattr(self.base_estimator, attr)\n    )\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 45,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 62,
        "n_identifiers": 6,
        "d_id": 75632,
        "documentation": {
            "docstring": "Check if we can delegate a method to the underlying estimator.\n\n    First, we check the first fitted estimator if available, otherwise we\n    check the base estimator.\n    ",
            "n_words": 26,
            "vocab_size": 19,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 87078,
        "commit_id": "e0e2c4ff4248042abda3cc93024930dada416af8",
        "repo": "sentry",
        "path": "tests/sentry/relay/test_config.py",
        "file_name": "test_config.py",
        "fun_name": "test_project_config_dynamic_sampling_is_none",
        "commit_message": "feat(dynamic-sampling): Handles updating ProjectConfig with uniform DS rule for v2 [TET-465] (#40268)\n\nThis PR forces your uniform rule by your plan\r\nor respect old logic. If both feature flags are enabled\r\ndynamic-sampling-basic flag takes the highest precedence.\r\n\r\nOriginal PR https://github.com/getsentry/sentry/pull/40180 was reverted\r\nvia https://github.com/getsentry/sentry/pull/40266 due to issue of\r\nremoving incorrect line.\r\n\r\nCo-authored-by: Joris Bayer <joris.bayer@sentry.io>",
        "code": "def test_project_config_dynamic_sampling_is_none(default_project):\n    \n    default_project.update_option(\"sentry:dynamic_sampling\", None)\n\n    with Feature({\"organizations:server-side-sampling\": True}):\n        cfg = get_project_config(default_project)\n\n    cfg = cfg.to_dict()\n    dynamic_sampling = get_path(cfg, \"config\", \"dynamicSampling\")\n\n    assert dynamic_sampling is None\n\n\n@pytest.mark.django_db",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.django_db",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 47,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 51,
        "n_ast_nodes": 103,
        "n_identifiers": 12,
        "d_id": 18216,
        "documentation": {
            "docstring": "\n    Tests test check inc-237 that dynamic sampling is None,\n    so it's pass when we have fix and fails when we dont\n    ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 62028,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/locators.py",
        "file_name": "locators.py",
        "fun_name": "get_all_distribution_names",
        "commit_message": "upd; format",
        "code": "def get_all_distribution_names(url=None):\n    \n    if url is None:\n        url = DEFAULT_INDEX\n    client = ServerProxy(url, timeout=3.0)\n    try:\n        return client.list_packages()\n    finally:\n        client('close')()\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 54,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 44,
        "n_ast_nodes": 75,
        "n_identifiers": 7,
        "d_id": 12837,
        "documentation": {
            "docstring": "\n    Return all distribution names known by an index.\n    :param url: The URL of the index.\n    :return: A list of all known distribution names.\n    ",
            "n_words": 23,
            "vocab_size": 18,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 32198,
        "commit_id": "c1c79b06550b587b2a975016ef9d18b53258025b",
        "repo": "transformers",
        "path": "src/transformers/models/nllb/tokenization_nllb.py",
        "file_name": "tokenization_nllb.py",
        "fun_name": "convert_tokens_to_string",
        "commit_message": "NLLB tokenizer (#18126)\n\n* NLLB tokenizer\r\n\r\n* Apply suggestions from code review - Thanks Stefan!\r\n\r\nCo-authored-by: Stefan Schweter <stefan@schweter.it>\r\n\r\n* Final touches\r\n\r\n* Style :)\r\n\r\n* Update docs/source/en/model_doc/nllb.mdx\r\n\r\nCo-authored-by: Stefan Schweter <stefan@schweter.it>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* PR reviews\r\n\r\n* Auto models\r\n\r\nCo-authored-by: Stefan Schweter <stefan@schweter.it>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def convert_tokens_to_string(self, tokens):\n        \n        out_string = \"\".join(tokens).replace(SPIECE_UNDERLINE, \" \").strip()\n        return out_string\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 29,
        "n_ast_nodes": 52,
        "n_identifiers": 8,
        "d_id": 5877,
        "documentation": {
            "docstring": "Converts a sequence of tokens (strings for sub-words) in a single string.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 73775,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "start",
        "commit_message": "Reformat with black",
        "code": "def start(self, workflow_state, user=None):\n        \n        task_state = self.get_task_state_class()(workflow_state=workflow_state)\n        task_state.status = TaskState.STATUS_IN_PROGRESS\n        task_state.page_revision = workflow_state.page.get_latest_revision()\n        task_state.task = self\n        task_state.save()\n        task_submitted.send(\n            sender=task_state.specific.__class__,\n            instance=task_state.specific,\n            user=user,\n        )\n        return task_state\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 120,
        "n_words": 24,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 77,
        "n_ast_nodes": 122,
        "n_identifiers": 20,
        "d_id": 16102,
        "documentation": {
            "docstring": "Start this task on the provided workflow state by creating an instance of TaskState",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 187150,
        "commit_id": "3d44da082b3ba202b9d0557bfd8ce747a1d7960c",
        "repo": "streamlink",
        "path": "tests/test_api_validate.py",
        "file_name": "test_api_validate.py",
        "fun_name": "test_parse_qsd",
        "commit_message": "plugin.api.validate: implement ValidationError\n\n- Implement `ValidationError`\n  - Inherit from `ValueError` to preserve backwards compatiblity\n  - Allow collecting multiple errors (AnySchema)\n  - Keep an error stack of parent `ValidationError`s or other exceptions\n  - Format error stack when converting error to string\n- Raise `ValidationError` instead of `ValueError`\n  - Add error contexts where it makes sense\n  - Add schema names to error instances\n- Add and update tests",
        "code": "def test_parse_qsd(self):\n        assert validate(parse_qsd(), 'foo=bar&foo=baz') == {\"foo\": \"baz\"}\n        with self.assertRaises(ValueError) as cm:\n            validate(parse_qsd(), 123)\n        assert_validationerror(cm.exception, )\n\n",
        "url": "https://github.com/streamlink/streamlink.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 47,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 46,
        "n_ast_nodes": 84,
        "n_identifiers": 9,
        "d_id": 45710,
        "documentation": {
            "docstring": "\n            ValidationError:\n              Unable to parse query string: 'int' object has no attribute 'decode' (123)\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 59614,
        "commit_id": "0f0430b003e710f2e59a7e575dd2fac183b9ca28",
        "repo": "prefect",
        "path": "src/prefect/orion/database/migrations/versions/postgresql/2022_10_31_161719_41e5ed9e1034_.py",
        "file_name": "2022_10_31_161719_41e5ed9e1034_.py",
        "fun_name": "upgrade",
        "commit_message": "Allow filtering of Work Queues via the API based on name prefix (#7394)",
        "code": "def upgrade():\n    # install pg_trgm\n    op.execute(\"CREATE EXTENSION IF NOT EXISTS pg_trgm;\")\n\n    with op.get_context().autocommit_block():\n        op.execute(\n            \n        )\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 49,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 27,
        "n_ast_nodes": 54,
        "n_identifiers": 5,
        "d_id": 11915,
        "documentation": {
            "docstring": "\n            CREATE INDEX CONCURRENTLY\n            trgm_ix_work_queue_name\n            ON work_queue USING gin (name gin_trgm_ops);\n            ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 60907,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/network/session.py",
        "file_name": "session.py",
        "fun_name": "add_trusted_host",
        "commit_message": "upd; format",
        "code": "def add_trusted_host(self, host, source=None, suppress_logging=False):\n        # type: (str, Optional[str], bool) -> None\n        \n        if not suppress_logging:\n            msg = f'adding trusted host: {host!r}'\n            if source is not None:\n                msg += f' (from {source})'\n            logger.info(msg)\n\n        host_port = parse_netloc(host)\n        if host_port not in self.pip_trusted_origins:\n            self.pip_trusted_origins.append(host_port)\n\n        self.mount(\n            build_url_from_netloc(host) + '/',\n            self._trusted_host_adapter\n        )\n        if not host_port[1]:\n            # Mount wildcard ports for the same host.\n            self.mount(\n                build_url_from_netloc(host) + ':',\n                self._trusted_host_adapter\n            )\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 264,
        "n_words": 64,
        "vocab_size": 49,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 99,
        "n_ast_nodes": 172,
        "n_identifiers": 15,
        "d_id": 12338,
        "documentation": {
            "docstring": "\n        :param host: It is okay to provide a host that has previously been\n            added.\n        :param source: An optional source string, for logging where the host\n            string came from.\n        ",
            "n_words": 28,
            "vocab_size": 26,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 26031,
        "commit_id": "85681143d185863ae1a54af03f0690d11af04563",
        "repo": "saleor",
        "path": "saleor/graphql/page/tests/mutations/test_page_update.py",
        "file_name": "test_page_update.py",
        "fun_name": "test_paginate_pages",
        "commit_message": "Update files structure of page tests (#9182)",
        "code": "def test_paginate_pages(user_api_client, page, page_type):\n    page.is_published = True\n    data_02 = {\n        \"slug\": \"test02-url\",\n        \"title\": \"Test page\",\n        \"content\": dummy_editorjs(\"Content for page 1\"),\n        \"is_published\": True,\n        \"page_type\": page_type,\n    }\n    data_03 = {\n        \"slug\": \"test03-url\",\n        \"title\": \"Test page\",\n        \"content\": dummy_editorjs(\"Content for page 1\"),\n        \"is_published\": True,\n        \"page_type\": page_type,\n    }\n\n    Page.objects.create(**data_02)\n    Page.objects.create(**data_03)\n    query = \n    response = user_api_client.post_graphql(query)\n    content = get_graphql_content(response)\n    pages_data = content[\"data\"][\"pages\"]\n    assert len(pages_data[\"edges\"]) == 2\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "vocab_size": 39,
        "complexity": 1,
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        "token_counts": 122,
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        "d_id": 4929,
        "documentation": {
            "docstring": "\n        query PagesQuery {\n            pages(first: 2) {\n                edges {\n                    node {\n                        id\n                        title\n                    }\n                }\n            }\n        }\n        ",
            "n_words": 16,
            "vocab_size": 10,
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            "language": "en"
        }
    },
    {
        "id": 19700,
        "commit_id": "9a3b3ce70621af6f9adaa9eeac9cf83fa149319c",
        "repo": "pipenv",
        "path": "pipenv/exceptions.py",
        "file_name": "exceptions.py",
        "fun_name": "prettify_exc",
        "commit_message": "Issue 4993 Add standard pre commit hooks and apply linting. (#4994)\n\n* Add .pre-commit-config.yaml to the project and exclude tests (for now).  This does not include the MyPy linting that pip does but does include everything else.",
        "code": "def prettify_exc(error):\n    \n    errors = []\n    for exc in KNOWN_EXCEPTIONS:\n        search_string = exc.match_string if exc.match_string else exc.exception_name\n        split_string = (\n            exc.show_from_string if exc.show_from_string else exc.exception_name\n        )\n        if search_string in error:\n            # for known exceptions with no display rules and no prefix\n            # we should simply show nothing\n            if not exc.show_from_string and not exc.prefix:\n                errors.append(\"\")\n                continue\n            elif exc.prefix and exc.prefix in error:\n                _, error, info = error.rpartition(exc.prefix)\n            else:\n                _, error, info = error.rpartition(split_string)\n            errors.append(f\"{error} {info}\")\n    if not errors:\n        return f\"{vistir.misc.decode_for_output(error)}\"\n\n    return \"\\n\".join(errors)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 3069,
        "documentation": {
            "docstring": "Catch known errors and prettify them instead of showing the\n    entire traceback, for better UX",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 203451,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/options.py",
        "file_name": "options.py",
        "fun_name": "log_deletion",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def log_deletion(self, request, obj, object_repr):\n        \n        from django.contrib.admin.models import DELETION, LogEntry\n\n        return LogEntry.objects.log_action(\n            user_id=request.user.pk,\n            content_type_id=get_content_type_for_model(obj).pk,\n            object_id=obj.pk,\n            object_repr=object_repr,\n            action_flag=DELETION,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "nloc": 9,
        "token_counts": 63,
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        "n_identifiers": 20,
        "d_id": 50382,
        "documentation": {
            "docstring": "\n        Log that an object will be deleted. Note that this method must be\n        called before the deletion.\n\n        The default implementation creates an admin LogEntry object.\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 113817,
        "commit_id": "bc3b53170ee1bc542682366ed93bc362cf26e152",
        "repo": "mindsdb",
        "path": "mindsdb/api/mysql/mysql_proxy/classes/sql_query.py",
        "file_name": "sql_query.py",
        "fun_name": "_parse_query",
        "commit_message": "fix selecting from files",
        "code": "def _parse_query(self, sql):\n        mindsdb_sql_struct = parse_sql(sql, dialect='mindsdb')\n\n        # is it query to 'predictors'?\n        if (\n            isinstance(mindsdb_sql_struct.from_table, Identifier)\n            and mindsdb_sql_struct.from_table.parts[-1].lower() == 'predictors'\n            and (\n                self.database == 'mindsdb'\n                or mindsdb_sql_struct.from_table.parts[0].lower() == 'mindsdb'\n            )\n        ):\n            dn = self.datahub.get(self.mindsdb_database_name)\n            data, columns = dn.get_predictors(mindsdb_sql_struct)\n            table_name = ('mindsdb', 'predictors', 'predictors')\n            data = [{(key, key): value for key, value in row.items()} for row in data]\n            data = [{table_name: x} for x in data]\n            self.columns_list = [\n                (table_name + (column_name, column_name))\n                for column_name in columns\n            ]\n\n            columns = [(column_name, column_name) for column_name in columns]\n\n            self.fetched_data = {\n                'values': data,\n                'columns': {table_name: columns},\n                'tables': [table_name]\n            }\n            return\n\n        # is it query to 'commands'?\n        if (\n            isinstance(mindsdb_sql_struct.from_table, Identifier)\n            and mindsdb_sql_struct.from_table.parts[-1].lower() == 'commands'\n            and (\n                self.database == 'mindsdb'\n                or mindsdb_sql_struct.from_table.parts[0].lower() == 'mindsdb'\n            )\n        ):\n            self.fetched_data = {\n                'values': [],\n                'columns': {('mindsdb', 'commands', 'commands'): [('command', 'command')]},\n                'tables': [('mindsdb', 'commands', 'commands')]\n            }\n            self.columns_list = [('mindsdb', 'commands', 'commands', 'command', 'command')]\n            return\n\n        # is it query to 'datasources'?\n        if (\n            isinstance(mindsdb_sql_struct.from_table, Identifier)\n            and mindsdb_sql_struct.from_table.parts[-1].lower() == 'datasources'\n            and (\n                self.database == 'mindsdb'\n                or mindsdb_sql_struct.from_table.parts[0].lower() == 'mindsdb'\n            )\n        ):\n            dn = self.datahub.get(self.mindsdb_database_name)\n            data, columns = dn.get_datasources(mindsdb_sql_struct)\n            table_name = ('mindsdb', 'datasources', 'datasources')\n            data = [{(key, key): value for key, value in row.items()} for row in data]\n            data = [{table_name: x} for x in data]\n\n            self.columns_list = [\n                (table_name + (column_name, column_name))\n                for column_name in columns\n            ]\n\n            columns = [(column_name, column_name) for column_name in columns]\n\n            self.fetched_data = {\n                'values': data,\n                'columns': {table_name: columns},\n                'tables': [table_name]\n            }\n            return\n\n        integrations_names = self.datahub.get_datasources_names()\n        integrations_names.append('information_schema')\n        integrations_names.append('file')\n\n        all_tables = get_all_tables(mindsdb_sql_struct)\n\n        predictor_metadata = {}\n        predictors = db.session.query(db.Predictor).filter_by(company_id=self.session.company_id)\n        for model_name in set(all_tables):\n            for p in predictors:\n                if p.name == model_name:\n                    if isinstance(p.data, dict) and 'error' not in p.data:\n                        ts_settings = p.learn_args.get('timeseries_settings', {})\n                        if ts_settings.get('is_timeseries') is True:\n                            window = ts_settings.get('window')\n                            order_by = ts_settings.get('order_by')[0]\n                            group_by = ts_settings.get('group_by')\n                            if isinstance(group_by, list):\n                                group_by = ts_settings.get('group_by')[0]\n                            predictor_metadata[model_name] = {\n                                'timeseries': True,\n                                'window': window,\n                                'order_by_column': order_by,\n                                'group_by_column': group_by\n                            }\n                        else:\n                            predictor_metadata[model_name] = {\n                                'timeseries': False\n                            }\n                        self.model_types.update(p.data.get('dtypes', {}))\n\n        plan = plan_query(\n            mindsdb_sql_struct,\n            integrations=integrations_names,\n            predictor_namespace=self.mindsdb_database_name,\n            predictor_metadata=predictor_metadata,\n            default_namespace=self.database\n        )\n\n        steps_data = []\n        for step in plan.steps:\n            data = []\n            if type(step) == GetPredictorColumns:\n                predictor_name = step.predictor.parts[-1]\n                dn = self.datahub.get(self.mindsdb_database_name)\n                columns = dn.get_table_columns(predictor_name)\n                columns = [\n                    (column_name, column_name) for column_name in columns\n                ]\n                data = {\n                    'values': [],\n                    'columns': {\n                        (self.mindsdb_database_name, predictor_name, predictor_name): columns\n                    },\n                    'tables': [(self.mindsdb_database_name, predictor_name, predictor_name)]\n                }\n            elif type(step) == FetchDataframeStep:\n                data = self._fetch_dataframe_step(step)\n            elif type(step) == UnionStep:\n                raise Exception('Union step is not implemented')\n                # TODO add union support\n                # left_data = steps_data[step.left.step_num]\n                # right_data = steps_data[step.right.step_num]\n                # data = left_data + right_data\n            elif type(step) == MapReduceStep:\n                if step.reduce != 'union':\n                    raise Exception(f'Unknown MapReduceStep type: {step.reduce}')\n\n                step_data = steps_data[step.values.step_num]\n                values = []\n                step_data_values = step_data['values']\n                for row in step_data_values:\n                    for row_data in row.values():\n                        for name, value in row_data.items():\n                            if name[0] != '__mindsdb_row_id':\n                                values.append(value)\n\n                data = {\n                    'values': [],\n                    'columns': {},\n                    'tables': []\n                }\n                substep = step.step\n                if type(substep) == FetchDataframeStep:\n                    query = substep.query\n                    markQueryVar(query.where)\n                    for value in values:\n                        replaceQueryVar(query.where, value)\n                        sub_data = self._fetch_dataframe_step(substep)\n                        if len(data['columns']) == 0:\n                            data['columns'] = sub_data['columns']\n                        if len(data['tables']) == 0:\n                            data['tables'] = sub_data['tables']\n                        data['values'].extend(sub_data['values'])\n                elif type(substep) == MultipleSteps:\n                    data = self._multiple_steps_reduce(substep, values)\n                else:\n                    raise Exception(f'Unknown step type: {step.step}')\n            elif type(step) == ApplyPredictorRowStep:\n                predictor = '.'.join(step.predictor.parts)\n                dn = self.datahub.get(self.mindsdb_database_name)\n                where_data = step.row_dict\n\n                data = dn.select(\n                    table=predictor,\n                    columns=None,\n                    where_data=where_data,\n                    integration_name=self.session.integration,\n                    integration_type=self.session.integration_type\n                )\n\n                data = [{(key, key): value for key, value in row.items()} for row in data]\n\n                table_name = get_preditor_alias(step, self.database)\n                values = [{table_name: x} for x in data]\n                columns = {table_name: []}\n                if len(data) > 0:\n                    row = data[0]\n                    columns[table_name] = list(row.keys())\n                # TODO else\n\n                data = {\n                    'values': values,\n                    'columns': columns,\n                    'tables': [table_name]\n                }\n            elif type(step) == ApplyPredictorStep or type(step) == ApplyTimeseriesPredictorStep:\n                dn = self.datahub.get(self.mindsdb_database_name)\n                predictor = '.'.join(step.predictor.parts)\n                where_data = []\n                for row in steps_data[step.dataframe.step_num]['values']:\n                    new_row = {}\n                    for table_name in row:\n                        keys_intersection = set(new_row) & set(row[table_name])\n                        if len(keys_intersection) > 0:\n                            raise Exception(\n                                f'The predictor got two identical keys from different datasources: {keys_intersection}'\n                            )\n                        new_row.update(row[table_name])\n                    where_data.append(new_row)\n\n                where_data = [{key[1]: value for key, value in row.items()} for row in where_data]\n\n                is_timeseries = predictor_metadata[predictor]['timeseries']\n                _mdb_make_predictions = None\n                if is_timeseries:\n                    if 'LATEST' in self.raw:\n                        _mdb_make_predictions = False\n                    else:\n                        _mdb_make_predictions = True\n                    for row in where_data:\n                        if '__mdb_make_predictions' not in row:\n                            row['__mdb_make_predictions'] = _mdb_make_predictions\n\n                for row in where_data:\n                    for key in row:\n                        if isinstance(row[key], datetime.date):\n                            row[key] = str(row[key])\n\n                data = dn.select(\n                    table=predictor,\n                    columns=None,\n                    where_data=where_data,\n                    integration_name=self.session.integration,\n                    integration_type=self.session.integration_type\n                )\n\n                data = [{(key, key): value for key, value in row.items()} for row in data]\n\n                table_name = get_preditor_alias(step, self.database)\n                values = [{table_name: x} for x in data]\n                columns = {table_name: []}\n                if len(data) > 0:\n                    row = data[0]\n                    columns[table_name] = list(row.keys())\n                # TODO else\n\n                data = {\n                    'values': values,\n                    'columns': columns,\n                    'tables': [table_name]\n                }\n            elif type(step) == JoinStep:\n                left_data = steps_data[step.left.step_num]\n                right_data = steps_data[step.right.step_num]\n\n                # FIXME https://github.com/mindsdb/mindsdb_sql/issues/136\n                if True in [type(step) == ApplyTimeseriesPredictorStep for step in plan.steps]:\n                    right_data = steps_data[step.left.step_num]\n                    left_data = steps_data[step.right.step_num]\n\n                if step.query.condition is not None:\n                    raise Exception('At this moment supported only JOIN without condition')\n                if step.query.join_type.upper() not in ('LEFT JOIN', 'JOIN'):\n                    raise Exception('At this moment supported only JOIN and LEFT JOIN')\n                if (\n                    len(left_data['tables']) != 1 or len(right_data['tables']) != 1\n                    or left_data['tables'][0] == right_data['tables'][0]\n                ):\n                    raise Exception('At this moment supported only JOIN of two different tables')\n\n                data = {\n                    'values': [],\n                    'columns': {},\n                    'tables': list(set(left_data['tables'] + right_data['tables']))\n                }\n\n                for data_part in [left_data, right_data]:\n                    for table_name in data_part['columns']:\n                        if table_name not in data['columns']:\n                            data['columns'][table_name] = data_part['columns'][table_name]\n                        else:\n                            data['columns'][table_name].extend(data_part['columns'][table_name])\n                for table_name in data['columns']:\n                    data['columns'][table_name] = list(set(data['columns'][table_name]))\n\n                left_key = left_data['tables'][0]\n                right_key = right_data['tables'][0]\n\n                left_columns_map = {}\n                left_columns_map_reverse = {}\n                for i, column_name in enumerate(left_data['columns'][left_key]):\n                    left_columns_map[f'a{i}'] = column_name\n                    left_columns_map_reverse[column_name] = f'a{i}'\n\n                right_columns_map = {}\n                right_columns_map_reverse = {}\n                for i, column_name in enumerate(right_data['columns'][right_key]):\n                    right_columns_map[f'b{i}'] = column_name\n                    right_columns_map_reverse[column_name] = f'b{i}'\n\n                left_df_data = []\n                for row in left_data['values']:\n                    row = row[left_key]\n                    left_df_data.append({left_columns_map_reverse[key]: value for key, value in row.items()})\n\n                right_df_data = []\n                for row in right_data['values']:\n                    row = row[right_key]\n                    right_df_data.append({right_columns_map_reverse[key]: value for key, value in row.items()})\n\n                df_a = pd.DataFrame(left_df_data)\n                df_b = pd.DataFrame(right_df_data)\n\n                a_name = f'a{round(time.time()*1000)}'\n                b_name = f'b{round(time.time()*1000)}'\n                con = duckdb.connect(database=':memory:')\n                con.register(a_name, df_a)\n                con.register(b_name, df_b)\n                resp_df = con.execute(f).fetchdf()\n                con.unregister(a_name)\n                con.unregister(b_name)\n                con.close()\n                resp_df = resp_df.where(pd.notnull(resp_df), None)\n                resp_dict = resp_df.to_dict(orient='records')\n\n                for row in resp_dict:\n                    new_row = {left_key: {}, right_key: {}}\n                    for key, value in row.items():\n                        if key.startswith('a'):\n                            new_row[left_key][left_columns_map[key]] = value\n                        else:\n                            new_row[right_key][right_columns_map[key]] = value\n                    data['values'].append(new_row)\n            elif type(step) == FilterStep:\n                raise Exception('FilterStep is not implemented')\n            # elif type(step) == ApplyTimeseriesPredictorStep:\n            #     raise Exception('ApplyTimeseriesPredictorStep is not implemented')\n            elif type(step) == ProjectStep:\n                step_data = steps_data[step.dataframe.step_num]\n                columns_list = []\n                for column_full_name in step.columns:\n                    table_name = None\n                    if type(column_full_name) == Star:\n                        for table_name, table_columns_list in step_data['columns'].items():\n                            for column in table_columns_list:\n                                columns_list.append(table_name + column)\n                    elif type(column_full_name) == Identifier:\n                        column_name_parts = column_full_name.parts\n                        column_alias = None if column_full_name.alias is None else '.'.join(column_full_name.alias.parts)\n                        if len(column_name_parts) > 2:\n                            raise Exception(f'Column name must contain no more than 2 parts. Got name: {\".\".join(column_full_name)}')\n                        elif len(column_name_parts) == 1:\n                            column_name = column_name_parts[0]\n\n                            appropriate_table = None\n                            if len(step_data['tables']) == 1:\n                                appropriate_table = step_data['tables'][0]\n                            else:\n                                for table_name, table_columns in step_data['columns'].items():\n                                    if (column_name, column_name) in table_columns:\n                                        if appropriate_table is not None:\n                                            raise Exception('Found multiple appropriate tables for column {column_name}')\n                                        else:\n                                            appropriate_table = table_name\n                            if appropriate_table is None:\n                                # it is probably constaint\n                                # FIXME https://github.com/mindsdb/mindsdb_sql/issues/133\n                                # column_name = column_name.strip(\"'\")\n                                # name_or_alias = column_alias or column_name\n                                # column_alias = name_or_alias\n                                # for row in step_data['values']:\n                                #     for table in row:\n                                #         row[table][(column_name, name_or_alias)] = row[table][(column_name, column_name)]\n                                # appropriate_table = step_data['tables'][0]\n                                columns_list.append(appropriate_table + (column_alias, column_alias))\n                            else:\n                                columns_list.append(appropriate_table + (column_name, column_alias or column_name))  # column_name\n                        elif len(column_name_parts) == 2:\n                            table_name_or_alias = column_name_parts[0]\n                            column_name = column_name_parts[1]\n\n                            appropriate_table = None\n                            for table_name, table_columns in step_data['columns'].items():\n                                checkig_table_name_or_alias = table_name[2] or table_name[1]\n                                if table_name_or_alias == checkig_table_name_or_alias:\n                                    for table_column_name in table_columns:\n                                        if (\n                                            table_column_name[1] == column_name\n                                            or table_column_name[1] is None and table_column_name[0] == column_name\n                                        ):\n                                            break\n                                    else:\n                                        raise Exception(f'Can not find column \"{column_name}\" in table \"{table_name}\"')\n                                    appropriate_table = table_name\n                                    break\n                            if appropriate_table is None:\n                                raise Exception(f'Can not find approproate table for column {column_name}')\n\n                            columns_to_copy = None\n                            for column in step_data['columns'][appropriate_table]:\n                                if column[0] == column_name and (column[1] is None or column[1] == column_name):\n                                    columns_to_copy = column\n                                    break\n                            else:\n                                raise Exception(f'Can not find approproate column in data: {(column_name, column_alias)}')\n\n                            for row in step_data['values']:\n                                row[appropriate_table][(column_name, column_alias)] = row[appropriate_table][columns_to_copy]\n\n                            columns_list.append(appropriate_table + (column_name, column_alias))\n                        else:\n                            raise Exception('Undefined column name')\n                    else:\n                        raise Exception(f'Unexpected column name type: {column_full_name}')\n\n                self.columns_list = columns_list\n                data = step_data\n            else:\n                raise Exception(F'Unknown planner step: {step}')\n            steps_data.append(data)\n\n        if self.outer_query is not None:\n            data = []\n            # +++\n            result = []\n            for row in steps_data[-1]:\n                data_row = {}\n                for column_record in self.columns_list:\n                    table_name = column_record[:3]\n                    column_name = column_record[3]\n                    data_row[column_record[4] or column_record[3]] = row[table_name][column_name]\n                result.append(data_row)\n            # ---\n            data = self._make_list_result_view(result)\n            df = pd.DataFrame(data)\n            result = query_df(df, self.outer_query)\n\n            try:\n                self.columns_list = [\n                    ('', '', '', x, x) for x in result.columns\n                ]\n            except Exception:\n                self.columns_list = [\n                    ('', '', '', result.name, result.name)\n                ]\n\n            # +++ make list result view\n            new_result = []\n            for row in result.to_dict(orient='records'):\n                data_row = []\n                for column_record in self.columns_list:\n                    column_name = column_record[4] or column_record[3]\n                    data_row.append(row.get(column_name))\n                new_result.append(data_row)\n            result = new_result\n            # ---\n\n            self.fetched_data = result\n        else:\n            self.fetched_data = steps_data[-1]\n\n        if hasattr(self, 'columns_list') is False:\n            self.columns_list = []\n            for row in self.fetched_data:\n                for table_key in row:\n                    for column_name in row[table_key]:\n                        if (table_key + (column_name, column_name)) not in self.columns_list:\n                            self.columns_list.append((table_key + (column_name, column_name)))\n\n        # if there was no 'ProjectStep', then get columns list from last step:\n        if self.columns_list is None:\n            self.columns_list = []\n            for table_name in self.fetched_data['columns']:\n                self.columns_list.extend([\n                    table_name + column for column in self.fetched_data['columns'][table_name]\n                ])\n\n        self.columns_list = [x for x in self.columns_list if x[3] != '__mindsdb_row_id']\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 30,
        "n_whitespaces": 9407,
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        "vocab_size": 531,
        "complexity": 139,
        "nloc": 413,
        "token_counts": 3055,
        "n_ast_nodes": 5091,
        "n_identifiers": 176,
        "d_id": 25033,
        "documentation": {
            "docstring": "\n                    SELECT * FROM {a_name} as ta full join {b_name} as tb\n                    ON ta.{left_columns_map_reverse[('__mindsdb_row_id', '__mindsdb_row_id')]}\n                     = tb.{right_columns_map_reverse[('__mindsdb_row_id', '__mindsdb_row_id')]}\n                ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 26687,
        "commit_id": "0881beec1ac02dfa97525c5173687defb356d85c",
        "repo": "saleor",
        "path": "saleor/payment/tests/test_gateway.py",
        "file_name": "test_gateway.py",
        "fun_name": "test_payment_refund_or_void_refund_called_txn_exist",
        "commit_message": "Fix payment flow (#9504)\n\n* Do not capture payment again when it should be refunded or voided\r\n\r\n* Do not create order when then is ongoing refund",
        "code": "def test_payment_refund_or_void_refund_called_txn_exist(refund_mock, payment):\n    \n    # given\n    payment.charge_status = ChargeStatus.FULLY_CHARGED\n    payment.save(update_fields=[\"charge_status\"])\n    assert payment.can_refund() is True\n    payment.captured_amount = payment.total\n    payment.save(update_fields=[\"captured_amount\"])\n    txn = payment.transactions.create(\n        is_success=True,\n        action_required=False,\n        kind=TransactionKind.REFUND_ONGOING,\n        amount=payment.captured_amount / 2,\n        currency=payment.currency,\n        token=\"test\",\n        gateway_response={},\n    )\n\n    # when\n    gateway.payment_refund_or_void(\n        payment, get_plugins_manager(), None, transaction_id=txn.token\n    )\n\n    # then\n    assert refund_mock.called_once()\n\n\n@patch(\"saleor.payment.gateway.refund\")",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "@patch(\"saleor.payment.gateway.refund\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 140,
        "n_words": 43,
        "vocab_size": 37,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 120,
        "n_ast_nodes": 202,
        "n_identifiers": 29,
        "d_id": 5046,
        "documentation": {
            "docstring": "Ensure that the refund method is called when the refund process\n    is already ongoing but not covered full payment captured amount.",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 67838,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/get_item_details.py",
        "file_name": "get_item_details.py",
        "fun_name": "get_item_price",
        "commit_message": "style: format code with black",
        "code": "def get_item_price(args, item_code, ignore_party=False):\n\t\n\n\targs[\"item_code\"] = item_code\n\n\tconditions = \n\n\tconditions += \"and ifnull(batch_no, '') in ('', %(batch_no)s)\"\n\n\tif not ignore_party:\n\t\tif args.get(\"customer\"):\n\t\t\tconditions += \" and customer=%(customer)s\"\n\t\telif args.get(\"supplier\"):\n\t\t\tconditions += \" and supplier=%(supplier)s\"\n\t\telse:\n\t\t\tconditions += \"and (customer is null or customer = '') and (supplier is null or supplier = '')\"\n\n\tif args.get(\"transaction_date\"):\n\t\tconditions += \n\n\tif args.get(\"posting_date\"):\n\t\tconditions += \n\n\treturn frappe.db.sql(\n\t\t.format(\n\t\t\tconditions=conditions\n\t\t),\n\t\targs,\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 50,
        "n_words": 68,
        "vocab_size": 43,
        "complexity": 6,
        "nloc": 27,
        "token_counts": 96,
        "n_ast_nodes": 181,
        "n_identifiers": 10,
        "d_id": 14635,
        "documentation": {
            "docstring": "\n\tGet name, price_list_rate from Item Price based on conditions\n\t        Check if the desired qty is within the increment of the packing list.\n\t:param args: dict (or frappe._dict) with mandatory fields price_list, uom\n\t        optional fields transaction_date, customer, supplier\n\t:param item_code: str, Item Doctype field item_code\n\twhere item_code=%(item_code)s\n\t\tand price_list=%(price_list)s\n\t\tand ifnull(uom, '') in ('', %(uom)s) and %(transaction_date)s between\n\t\t\tifnull(valid_from, '2000-01-01') and ifnull(valid_upto, '2500-12-31') and %(posting_date)s between\n\t\t\tifnull(valid_from, '2000-01-01') and ifnull(valid_upto, '2500-12-31') select name, price_list_rate, uom\n\t\tfrom `tabItem Price` {conditions}\n\t\torder by valid_from desc, batch_no desc, uom desc ",
            "n_words": 86,
            "vocab_size": 66,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 109822,
        "commit_id": "b26040884de54145ae857a37a6737e110b2607c4",
        "repo": "matplotlib",
        "path": "lib/matplotlib/path.py",
        "file_name": "path.py",
        "fun_name": "make_compound_path_from_polys",
        "commit_message": "Cleanup make_compound_path_from_poly doc, example.",
        "code": "def make_compound_path_from_polys(cls, XY):\n        \n        # for each poly: 1 for the MOVETO, (numsides-1) for the LINETO, 1 for\n        # the CLOSEPOLY; the vert for the closepoly is ignored but we still\n        # need it to keep the codes aligned with the vertices\n        numpolys, numsides, two = XY.shape\n        if two != 2:\n            raise ValueError(\"The third dimension of 'XY' must be 2\")\n        stride = numsides + 1\n        nverts = numpolys * stride\n        verts = np.zeros((nverts, 2))\n        codes = np.full(nverts, cls.LINETO, dtype=cls.code_type)\n        codes[0::stride] = cls.MOVETO\n        codes[numsides::stride] = cls.CLOSEPOLY\n        for i in range(numsides):\n            verts[i::stride] = XY[:, i]\n        return cls(verts, codes)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 215,
        "n_words": 95,
        "vocab_size": 70,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 115,
        "n_ast_nodes": 183,
        "n_identifiers": 22,
        "d_id": 23762,
        "documentation": {
            "docstring": "\n        Make a compound `Path` object to draw a number of polygons with equal\n        numbers of sides.\n\n        .. plot:: gallery/misc/histogram_path.py\n\n        Parameters\n        ----------\n        XY : (numpolys, numsides, 2) array\n        ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 218550,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ipaddress.py",
        "file_name": "ipaddress.py",
        "fun_name": "_ip_int_from_string",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _ip_int_from_string(cls, ip_str):\n        \n        if not ip_str:\n            raise AddressValueError('Address cannot be empty')\n\n        octets = ip_str.split('.')\n        if len(octets) != 4:\n            raise AddressValueError(\"Expected 4 octets in %r\" % ip_str)\n\n        try:\n            return int.from_bytes(map(cls._parse_octet, octets), 'big')\n        except ValueError as exc:\n            raise AddressValueError(\"%s in %r\" % (exc, ip_str)) from None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 130,
        "n_words": 44,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 76,
        "n_ast_nodes": 131,
        "n_identifiers": 13,
        "d_id": 55382,
        "documentation": {
            "docstring": "Turn the given IP string into an integer for comparison.\n\n        Args:\n            ip_str: A string, the IP ip_str.\n\n        Returns:\n            The IP ip_str as an integer.\n\n        Raises:\n            AddressValueError: if ip_str isn't a valid IPv4 Address.\n\n        ",
            "n_words": 33,
            "vocab_size": 28,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 203605,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/auth/backends.py",
        "file_name": "backends.py",
        "fun_name": "user_can_authenticate",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def user_can_authenticate(self, user):\n        \n        is_active = getattr(user, \"is_active\", None)\n        return is_active or is_active is None\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 40,
        "n_identifiers": 5,
        "d_id": 50472,
        "documentation": {
            "docstring": "\n        Reject users with is_active=False. Custom user models that don't have\n        that attribute are allowed.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 20440,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/lexer.py",
        "file_name": "lexer.py",
        "fun_name": "get_tokens_unprocessed",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def get_tokens_unprocessed(self, text=None, context=None):\n        \n        tokendefs = self._tokens\n        if not context:\n            ctx = LexerContext(text, 0)\n            statetokens = tokendefs['root']\n        else:\n            ctx = context\n            statetokens = tokendefs[ctx.stack[-1]]\n            text = ctx.text\n        while 1:\n            for rexmatch, action, new_state in statetokens:\n                m = rexmatch(text, ctx.pos, ctx.end)\n                if m:\n                    if action is not None:\n                        if type(action) is _TokenType:\n                            yield ctx.pos, action, m.group()\n                            ctx.pos = m.end()\n                        else:\n                            yield from action(self, m, ctx)\n                            if not new_state:\n                                # altered the state stack?\n                                statetokens = tokendefs[ctx.stack[-1]]\n                    # CAUTION: callback must set ctx.pos!\n                    if new_state is not None:\n                        # state transition\n                        if isinstance(new_state, tuple):\n                            for state in new_state:\n                                if state == '#pop':\n                                    if len(ctx.stack) > 1:\n                                        ctx.stack.pop()\n                                elif state == '#push':\n                                    ctx.stack.append(ctx.stack[-1])\n                                else:\n                                    ctx.stack.append(state)\n                        elif isinstance(new_state, int):\n                            # see RegexLexer for why this check is made\n                            if abs(new_state) >= len(ctx.stack):\n                                del ctx.state[1:]\n                            else:\n                                del ctx.stack[new_state:]\n                        elif new_state == '#push':\n                            ctx.stack.append(ctx.stack[-1])\n                        else:\n                            assert False, \"wrong state def: %r\" % new_state\n                        statetokens = tokendefs[ctx.stack[-1]]\n                    break\n            else:\n                try:\n                    if ctx.pos >= ctx.end:\n                        break\n                    if text[ctx.pos] == '\\n':\n                        # at EOL, reset state to \"root\"\n                        ctx.stack = ['root']\n                        statetokens = tokendefs['root']\n                        yield ctx.pos, Text, '\\n'\n                        ctx.pos += 1\n                        continue\n                    yield ctx.pos, Error, text[ctx.pos]\n                    ctx.pos += 1\n                except IndexError:\n                    break\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 24,
        "n_whitespaces": 1512,
        "n_words": 193,
        "vocab_size": 108,
        "complexity": 20,
        "nloc": 56,
        "token_counts": 373,
        "n_ast_nodes": 609,
        "n_identifiers": 30,
        "d_id": 3369,
        "documentation": {
            "docstring": "\n        Split ``text`` into (tokentype, text) pairs.\n        If ``context`` is given, use this lexer context instead.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 9864,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/peapods/peas/helper.py",
        "file_name": "helper.py",
        "fun_name": "update_runtime_cls",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def update_runtime_cls(args, copy=False) -> 'Namespace':\n    \n    _args = deepcopy(args) if copy else args\n    gateway_runtime_dict = {\n        GatewayProtocolType.GRPC: 'GRPCGatewayRuntime',\n        GatewayProtocolType.WEBSOCKET: 'WebSocketGatewayRuntime',\n        GatewayProtocolType.HTTP: 'HTTPGatewayRuntime',\n    }\n    if _args.runtime_cls == 'WorkerRuntime' and is_valid_huburi(_args.uses):\n        _hub_args = deepcopy(_args)\n        _hub_args.uri = _args.uses\n        _hub_args.no_usage = True\n        _args.uses = HubIO(_hub_args).pull()\n\n    if hasattr(_args, 'protocol'):\n        _args.runtime_cls = gateway_runtime_dict[_args.protocol]\n    if _args.pea_role == PeaRoleType.HEAD:\n        _args.runtime_cls = 'HeadRuntime'\n\n    return _args\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 142,
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        "n_identifiers": 23,
        "d_id": 1737,
        "documentation": {
            "docstring": "Get runtime_cls as a string from args\n\n    :param args: pea/pod namespace args\n    :param copy: True if args shouldn't be modified in-place\n    :return: runtime class as a string\n    ",
            "n_words": 27,
            "vocab_size": 21,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 107297,
        "commit_id": "162bd59f50a9c59a51574aee5dc9e932133bb971",
        "repo": "matplotlib",
        "path": "lib/matplotlib/projections/polar.py",
        "file_name": "polar.py",
        "fun_name": "set_thetalim",
        "commit_message": "DOC: More capitalization of Axes\n\nIn line with #18726.\n\nTriggered by #22242.",
        "code": "def set_thetalim(self, *args, **kwargs):\n        r\n        orig_lim = self.get_xlim()  # in radians\n        if 'thetamin' in kwargs:\n            kwargs['xmin'] = np.deg2rad(kwargs.pop('thetamin'))\n        if 'thetamax' in kwargs:\n            kwargs['xmax'] = np.deg2rad(kwargs.pop('thetamax'))\n        new_min, new_max = self.set_xlim(*args, **kwargs)\n        # Parsing all permutations of *args, **kwargs is tricky; it is simpler\n        # to let set_xlim() do it and then validate the limits.\n        if abs(new_max - new_min) > 2 * np.pi:\n            self.set_xlim(orig_lim)  # un-accept the change\n            raise ValueError(\"The angle range must be less than a full circle\")\n        return tuple(np.rad2deg((new_min, new_max)))\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 188,
        "n_words": 80,
        "vocab_size": 65,
        "complexity": 4,
        "nloc": 26,
        "token_counts": 115,
        "n_ast_nodes": 200,
        "n_identifiers": 17,
        "d_id": 22680,
        "documentation": {
            "docstring": "\n        Set the minimum and maximum theta values.\n\n        Can take the following signatures:\n\n        - ``set_thetalim(minval, maxval)``: Set the limits in radians.\n        - ``set_thetalim(thetamin=minval, thetamax=maxval)``: Set the limits\n          in degrees.\n\n        where minval and maxval are the minimum and maximum limits. Values are\n        wrapped in to the range :math:`[0, 2\\pi]` (in radians), so for example\n        it is possible to do ``set_thetalim(-np.pi / 2, np.pi / 2)`` to have\n        an axis symmetric around 0. A ValueError is raised if the absolute\n        angle difference is larger than a full circle.\n        ",
            "n_words": 85,
            "vocab_size": 63,
            "n_whitespaces": 165,
            "language": "en"
        }
    },
    {
        "id": 116815,
        "commit_id": "eb78c9016971609746d063b135e76dc01898d821",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/solr_handler/solr_handler.py",
        "file_name": "solr_handler.py",
        "fun_name": "get_tables",
        "commit_message": "Added Solr Handler #2740",
        "code": "def get_tables(self) -> Response:\n        \n        result = {}\n        result['data_frame'] = pd.DataFrame([self.connection_data.get('collection')])\n        df = result.data_frame\n        result.data_frame = df.rename(columns={df.columns[0]: 'table_name'})\n        return result\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 61,
        "n_words": 19,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 60,
        "n_ast_nodes": 103,
        "n_identifiers": 12,
        "d_id": 25838,
        "documentation": {
            "docstring": "\n        Get a list with all of the tables in Solr\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 204574,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/mail/message.py",
        "file_name": "message.py",
        "fun_name": "attach",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def attach(self, filename=None, content=None, mimetype=None):\n        \n        if isinstance(filename, MIMEBase):\n            if content is not None or mimetype is not None:\n                raise ValueError(\n                    \"content and mimetype must not be given when a MIMEBase \"\n                    \"instance is provided.\"\n                )\n            self.attachments.append(filename)\n        elif content is None:\n            raise ValueError(\"content must be provided.\")\n        else:\n            mimetype = (\n                mimetype\n                or mimetypes.guess_type(filename)[0]\n                or DEFAULT_ATTACHMENT_MIME_TYPE\n            )\n            basetype, subtype = mimetype.split(\"/\", 1)\n\n            if basetype == \"text\":\n                if isinstance(content, bytes):\n                    try:\n                        content = content.decode()\n                    except UnicodeDecodeError:\n                        # If mimetype suggests the file is text but it's\n                        # actually binary, read() raises a UnicodeDecodeError.\n                        mimetype = DEFAULT_ATTACHMENT_MIME_TYPE\n\n            self.attachments.append((filename, content, mimetype))\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 470,
        "n_words": 96,
        "vocab_size": 67,
        "complexity": 10,
        "nloc": 24,
        "token_counts": 134,
        "n_ast_nodes": 221,
        "n_identifiers": 19,
        "d_id": 50791,
        "documentation": {
            "docstring": "\n        Attach a file with the given filename and content. The filename can\n        be omitted and the mimetype is guessed, if not provided.\n\n        If the first parameter is a MIMEBase subclass, insert it directly\n        into the resulting message attachments.\n\n        For a text/* mimetype (guessed or specified), when a bytes object is\n        specified as content, decode it as UTF-8. If that fails, set the\n        mimetype to DEFAULT_ATTACHMENT_MIME_TYPE and don't decode the content.\n        ",
            "n_words": 70,
            "vocab_size": 50,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 203167,
        "commit_id": "c5c7a15b09368a58340d3a65ba9d1f1441e92dc8",
        "repo": "django",
        "path": "tests/view_tests/views.py",
        "file_name": "views.py",
        "fun_name": "safestring_in_template_exception",
        "commit_message": "Fixed #33461 -- Escaped template errors in the technical 500 debug page.",
        "code": "def safestring_in_template_exception(request):\n    \n    template = Template('{% extends \"<script>alert(1);</script>\" %}')\n    try:\n        template.render(Context())\n    except Exception:\n        return technical_500_response(request, *sys.exc_info())\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 41,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 37,
        "n_ast_nodes": 67,
        "n_identifiers": 10,
        "d_id": 50242,
        "documentation": {
            "docstring": "\n    Trigger an exception in the template machinery which causes a SafeString\n    to be inserted as args[0] of the Exception.\n    ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 165750,
        "commit_id": "24652cf178c12562585639cba39c46d62b95f107",
        "repo": "pandas",
        "path": "pandas/tests/extension/json/test_json.py",
        "file_name": "test_json.py",
        "fun_name": "test_fillna_frame",
        "commit_message": "TST: Convert skip -> xfail (#46427)",
        "code": "def test_fillna_frame(self):\n        \n        super().test_fillna_frame()\n\n\nunhashable = pytest.mark.xfail(reason=\"Unhashable\")\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 19,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 13,
        "n_ast_nodes": 47,
        "n_identifiers": 8,
        "d_id": 39706,
        "documentation": {
            "docstring": "We treat dictionaries as a mapping in fillna, not a scalar.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 266134,
        "commit_id": "23c0ca456f2753dc35aa2717f69cdc62b405a233",
        "repo": "netbox",
        "path": "netbox/extras/tests/test_customfields.py",
        "file_name": "test_customfields.py",
        "fun_name": "test_import_missing_required",
        "commit_message": "#4347: Rename NetBoxModelCSVForm to NetBoxModelImportForm",
        "code": "def test_import_missing_required(self):\n        \n        # Set one of our CustomFields to required\n        CustomField.objects.filter(name='text').update(required=True)\n\n        form_data = {\n            'name': 'Site 1',\n            'slug': 'site-1',\n        }\n\n        form = SiteImportForm(data=form_data)\n        self.assertFalse(form.is_valid())\n        self.assertIn('cf_text', form.errors)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 104,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 63,
        "n_ast_nodes": 115,
        "n_identifiers": 16,
        "d_id": 78301,
        "documentation": {
            "docstring": "\n        Attempt to import an object missing a required custom field.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 204952,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/mysql/base.py",
        "file_name": "base.py",
        "fun_name": "disable_constraint_checking",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def disable_constraint_checking(self):\n        \n        with self.cursor() as cursor:\n            cursor.execute(\"SET foreign_key_checks=0\")\n        return True\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
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        "token_counts": 23,
        "n_ast_nodes": 46,
        "n_identifiers": 4,
        "d_id": 50989,
        "documentation": {
            "docstring": "\n        Disable foreign key checks, primarily for use in adding rows with\n        forward references. Always return True to indicate constraint checks\n        need to be re-enabled.\n        ",
            "n_words": 24,
            "vocab_size": 23,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 101575,
        "commit_id": "7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5",
        "repo": "faceswap",
        "path": "lib/training/preview_tk.py",
        "file_name": "preview_tk.py",
        "fun_name": "_set_mouse_bindings",
        "commit_message": "Training - Use custom preview pop-out",
        "code": "def _set_mouse_bindings(self) -> None:\n        \n        logger.debug(\"Binding mouse events\")\n        if system() == \"Linux\":\n            self._canvas.tag_bind(self._canvas.image_id, \"<Button-4>\", self._on_bound_zoom)\n            self._canvas.tag_bind(self._canvas.image_id, \"<Button-5>\", self._on_bound_zoom)\n        else:\n            self._canvas.tag_bind(self._canvas.image_id, \"<MouseWheel>\", self._on_bound_zoom)\n\n        self._canvas.tag_bind(self._canvas.image_id, \"<Button-1>\", self._on_mouse_click)\n        self._canvas.tag_bind(self._canvas.image_id, \"<B1-Motion>\", self._on_mouse_drag)\n        logger.debug(\"Bound mouse events\")\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 112,
        "n_words": 30,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 119,
        "n_ast_nodes": 198,
        "n_identifiers": 11,
        "d_id": 20985,
        "documentation": {
            "docstring": " Set the mouse bindings for interacting with the preview image\n\n        Mousewheel: Zoom in and out\n        Mouse click: Move image\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 101443,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "sections",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def sections(self) -> List[str]:\n        \n        return sorted(set(plugin.split(\".\")[0] for plugin in self._config.config.sections()\n                          if plugin.split(\".\")[0] != \"writer\"))\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 53,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 51,
        "n_ast_nodes": 87,
        "n_identifiers": 10,
        "d_id": 20856,
        "documentation": {
            "docstring": " list: The sorted section names that exist within the convert Configuration options. ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 5043,
        "commit_id": "fa22d32e146dff62a4be881c12e2f611e556abca",
        "repo": "airbyte",
        "path": "tools/bin/build_report.py",
        "file_name": "build_report.py",
        "fun_name": "test_parse_dockerfile_label",
        "commit_message": "Filter daily build report to only GA & Beta connectors (#12684)",
        "code": "def test_parse_dockerfile_label(self):\n            mock_dockerfile = \n            assert \"airbyte/source-salesforce\" == parse_dockerfile_repository_label(mock_dockerfile)\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 15,
        "n_ast_nodes": 29,
        "n_identifiers": 4,
        "d_id": 711,
        "documentation": {
            "docstring": "\nENTRYPOINT [\"python\", \"/airbyte/integration_code/main.py\"]\n\nLABEL io.airbyte.version=1.0.8\nLABEL io.airbyte.name=airbyte/source-salesforce",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 132035,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/train/trainer.py",
        "file_name": "trainer.py",
        "fun_name": "_fetch_next_result",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _fetch_next_result(self) -> Optional[List[Dict]]:\n        \n\n        while True:\n            results = ray.get(self._backend_executor_actor.get_next_results.remote())\n            if results is None:\n                return None\n            first_result = results[0]\n            result_type = first_result.type\n            if result_type is TrainingResultType.REPORT:\n                result_data = [self._backend.decode_data(r.data) for r in results]\n                return result_data\n            elif result_type is TrainingResultType.CHECKPOINT:\n                self._checkpoint_manager._process_checkpoint(\n                    results, decode_checkpoint_fn=self._backend.decode_data\n                )\n                # Iterate until next REPORT call or training has finished.\n            else:\n                raise TrainBackendError(\n                    f\"Unexpected result type: \"\n                    f\"{result_type}. \"\n                    f\"Expected one of \"\n                    f\"{[type in TrainingResultType]}\"\n                )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 375,
        "n_words": 69,
        "vocab_size": 54,
        "complexity": 6,
        "nloc": 31,
        "token_counts": 115,
        "n_ast_nodes": 198,
        "n_identifiers": 26,
        "d_id": 29641,
        "documentation": {
            "docstring": "Fetch next results produced by ``train.report()`` from each worker.\n\n        Assumes ``start_training`` has already been called.\n\n        Returns:\n            A list of dictionaries of values passed to ``train.report()`` from\n                each worker. Each item corresponds to an intermediate result\n                a single worker. If there are no more items to fetch,\n                returns None.\n        ",
            "n_words": 48,
            "vocab_size": 40,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 63049,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "requires",
        "commit_message": "upd; format",
        "code": "def requires(self, extras=()):\n        \n        dm = self._dep_map\n        deps = []\n        deps.extend(dm.get(None, ()))\n        for ext in extras:\n            try:\n                deps.extend(dm[safe_extra(ext)])\n            except KeyError:\n                raise UnknownExtra(\n                    \"%s has no such extra feature %r\" % (self, ext)\n                )\n        return deps\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 162,
        "n_words": 34,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 69,
        "n_ast_nodes": 113,
        "n_identifiers": 12,
        "d_id": 13115,
        "documentation": {
            "docstring": "List of Requirements needed for this distro if `extras` are used",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 56199,
        "commit_id": "b5b3d808bf059294a7adf17156e4ccdb5a3799da",
        "repo": "prefect",
        "path": "src/prefect/orion/database/migrations/versions/postgresql/2022_06_04_133535_d60c18774a5d_add_indexes_for_partial_name_matches.py",
        "file_name": "2022_06_04_133535_d60c18774a5d_add_indexes_for_partial_name_matches.py",
        "fun_name": "upgrade",
        "commit_message": "Add index migrations",
        "code": "def upgrade():\n    with op.get_context().autocommit_block():\n        op.execute(\n            \n        )\n        op.execute(\n            \n        )\n        op.execute(\n            \n        )\n        op.execute(\n            \n        )\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 118,
        "n_words": 12,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 30,
        "token_counts": 39,
        "n_ast_nodes": 77,
        "n_identifiers": 5,
        "d_id": 11462,
        "documentation": {
            "docstring": "\n            CREATE INDEX CONCURRENTLY \n            trgm_ix_flow_name \n            ON flow USING gin (name gin_trgm_ops);\n            \n            CREATE INDEX CONCURRENTLY \n            trgm_ix_flow_run_name \n            ON flow_run USING gin (name gin_trgm_ops);\n            \n            CREATE INDEX CONCURRENTLY \n            trgm_ix_task_run_name \n            ON task_run USING gin (name gin_trgm_ops);\n            \n            CREATE INDEX CONCURRENTLY \n            trgm_ix_deployment_name \n            ON deployment USING gin (name gin_trgm_ops);\n            ",
            "n_words": 40,
            "vocab_size": 16,
            "n_whitespaces": 228,
            "language": "en"
        }
    },
    {
        "id": 258990,
        "commit_id": "6a16763c008446953ed9380e084ed70a285a9f7e",
        "repo": "scikit-learn",
        "path": "sklearn/utils/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_in_unstable_openblas_configuration",
        "commit_message": "ENH Introduce `PairwiseDistancesReduction` and `PairwiseDistancesArgKmin` (feature branch) (#22134)\n\n* MAINT Introduce Pairwise Distances Reductions private submodule  (#22064)\r\n\r\n* MAINT Introduce FastEuclideanPairwiseArgKmin  (#22065)\r\n\r\n* fixup! Merge branch 'main' into pairwise-distances-argkmin\r\n\r\nRemove duplicated Bunch\r\n\r\n* MAINT Plug `PairwiseDistancesArgKmin` as a back-end (#22288)\r\n\r\n* Forward pairwise_dist_chunk_size in the configuration\r\n\r\n* Flip finalized results for PairwiseDistancesArgKmin\r\n\r\nThe previous would have made the code more complex\r\nby introducing some boilerplate for the interface plugs.\r\n\r\nHaving it this way actually simplifies the code.\r\n\r\nThis also removes the haversine branch for\r\ntest_pairwise_distances_argkmin\r\n\r\n* Plug PairwiseDistancesArgKmin as a back-end\r\n\r\n* Adapt test accordingly\r\n\r\n* Add whats_new entry\r\n\r\n* Change input validation order for kneighbors\r\n\r\n* Remove duplicated test_neighbors_distance_metric_deprecation\r\n\r\n* Adapt the documentation\r\n\r\n* Add mahalanobis case to test fixtures\r\n\r\n* Correct whats_new entry\r\n\r\n* CLN Remove unneeded private metric attribute\r\n\r\nThis was needed when 'fast_sqeuclidean' and 'fast_euclidean'\r\nwere present to choose the best implementation based on the user\r\nspecification.\r\n\r\nThose metric have been removed since then, making this attribute\r\nuseless.\r\n\r\n* TST Assert FutureWarning instead of DeprecationWarning in\r\ntest_neighbors_metrics\r\n\r\n* MAINT Add use_pairwise_dist_activate to scikit-learn config\r\n\r\n* TST Add a test for the 'brute' backends' results' consistency\r\n\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\n\r\n* fixup! MAINT Add use_pairwise_dist_activate to scikit-learn config\r\n\r\n* fixup! fixup! MAINT Add use_pairwise_dist_activate to scikit-learn config\r\n\r\n* TST Filter FutureWarning for WMinkowskiDistance\r\n\r\n* MAINT pin numpydoc in arm for now (#22292)\r\n\r\n* fixup! TST Filter FutureWarning for WMinkowskiDistance\r\n\r\n* Revert keywords arguments removal for the GEMM trick for 'euclidean'\r\n\r\n* MAINT pin max numpydoc for now (#22286)\r\n\r\n* Add 'haversine' to CDIST_PAIRWISE_DISTANCES_REDUCTION_COMMON_METRICS\r\n\r\n* fixup! Add 'haversine' to CDIST_PAIRWISE_DISTANCES_REDUCTION_COMMON_METRICS\r\n\r\n* Apply suggestions from code review\r\n\r\n* MAINT Document some config parameters for maintenance\r\n\r\nAlso rename one of them.\r\n\r\n* FIX Support and test one of 'sqeuclidean' specification\r\n\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\n\r\n* FIX Various typos fix and correct haversine\r\n\r\n'haversine' is not supported by cdist.\r\n\r\n* Directly use get_config\r\n\r\n* CLN Apply comments from review\r\n\r\n* Motivate swapped returned values\r\n\r\n* TST Remove mahalanobis from test fixtures\r\n\r\n* MNT Add comment regaduction functions' signatures\r\n\r\n* TST Complete test for `pairwise_distance_{argmin,argmin_min}` (#22371)\r\n\r\n* DOC Add sub-pull requests to the whats_new entry\r\n\r\n* DOC place comment inside functions\r\n\r\n* DOC move up whatsnew entry\r\n\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com>\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Jérémie du Boisberranger <jeremiedbb@users.noreply.github.com>",
        "code": "def _in_unstable_openblas_configuration():\n    \n\n    # Import libraries which might load OpenBLAS.\n    import numpy  # noqa\n    import scipy  # noqa\n\n    modules_info = threadpool_info()\n\n    open_blas_used = any(info[\"internal_api\"] == \"openblas\" for info in modules_info)\n    if not open_blas_used:\n        return False\n\n    # OpenBLAS 0.3.16 fixed unstability for arm64, see:\n    # https://github.com/xianyi/OpenBLAS/blob/1b6db3dbba672b4f8af935bd43a1ff6cff4d20b7/Changelog.txt#L56-L58 # noqa\n    openblas_arm64_stable_version = parse_version(\"0.3.16\")\n    for info in modules_info:\n        if info[\"internal_api\"] != \"openblas\":\n            continue\n        openblas_version = info.get(\"version\")\n        openblas_architecture = info.get(\"architecture\")\n        if openblas_version is None or openblas_architecture is None:\n            # Cannot be sure that OpenBLAS is good enough. Assume unstable:\n            return True\n        if (\n            openblas_architecture == \"neoversen1\"\n            and parse_version(openblas_version) < openblas_arm64_stable_version\n        ):\n            # See discussions in https://github.com/numpy/numpy/issues/19411\n            return True\n    return False\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 268,
        "n_words": 104,
        "vocab_size": 69,
        "complexity": 9,
        "nloc": 21,
        "token_counts": 100,
        "n_ast_nodes": 186,
        "n_identifiers": 13,
        "d_id": 75509,
        "documentation": {
            "docstring": "Return True if in an unstable configuration for OpenBLAS",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 206964,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_changelist/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_result_list_set_empty_value_display_in_model_admin",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_result_list_set_empty_value_display_in_model_admin(self):\n        \n        new_child = Child.objects.create(name=\"name\", parent=None)\n        request = self.factory.get(\"/child/\")\n        request.user = self.superuser\n        m = EmptyValueChildAdmin(Child, admin.site)\n        cl = m.get_changelist_instance(request)\n        cl.formset = None\n        template = Template(\n            \"{% load admin_list %}{% spaceless %}{% result_list cl %}{% endspaceless %}\"\n        )\n        context = Context({\"cl\": cl, \"opts\": Child._meta})\n        table_output = template.render(context)\n        link = reverse(\"admin:admin_changelist_child_change\", args=(new_child.id,))\n        row_html = build_tbody_html(\n            new_child.id,\n            link,\n            '<td class=\"field-age_display\">&amp;dagger;</td>'\n            '<td class=\"field-age\">-empty-</td>',\n        )\n        self.assertNotEqual(\n            table_output.find(row_html),\n            -1,\n            \"Failed to find expected row element: %s\" % table_output,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 273,
        "n_words": 73,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 140,
        "n_ast_nodes": 235,
        "n_identifiers": 35,
        "d_id": 51813,
        "documentation": {
            "docstring": "\n        Empty value display can be set in ModelAdmin or individual fields.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 86534,
        "commit_id": "286bf2ae7ecfdd6698d8fb1cd4753f107159d4d2",
        "repo": "sentry",
        "path": "src/sentry/stacktraces/processing.py",
        "file_name": "processing.py",
        "fun_name": "get_stacktrace_processing_task",
        "commit_message": "ref: use dict instead of OrderedDict since sentry is >python3.6 (#39695)\n\npartially automated (especially the fixtures) also via `\\(([^]+),\r\n(.*)\\),$` -> `\\1: \\2,`",
        "code": "def get_stacktrace_processing_task(infos, processors):\n    \n    by_processor = {}\n    to_lookup = {}\n\n    # by_stacktrace_info requires stable sorting as it is used in\n    # StacktraceProcessingTask.iter_processable_stacktraces. This is important\n    # to guarantee reproducible symbolicator requests.\n    by_stacktrace_info = {}\n\n    for info in infos:\n        processable_frames = get_processable_frames(info, processors)\n        for processable_frame in processable_frames:\n            processable_frame.processor.preprocess_frame(processable_frame)\n            by_processor.setdefault(processable_frame.processor, []).append(processable_frame)\n            by_stacktrace_info.setdefault(processable_frame.stacktrace_info, []).append(\n                processable_frame\n            )\n            if processable_frame.cache_key is not None:\n                to_lookup[processable_frame.cache_key] = processable_frame\n\n    frame_cache = lookup_frame_cache(to_lookup)\n    for cache_key, processable_frame in to_lookup.items():\n        processable_frame.cache_value = frame_cache.get(cache_key)\n\n    return StacktraceProcessingTask(\n        processable_stacktraces=by_stacktrace_info, processors=by_processor\n    )\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 225,
        "n_words": 76,
        "vocab_size": 54,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 132,
        "n_ast_nodes": 211,
        "n_identifiers": 23,
        "d_id": 18122,
        "documentation": {
            "docstring": "Returns a list of all tasks for the processors.  This can skip over\n    processors that seem to not handle any frames.\n    ",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 199717,
        "commit_id": "3d30d00c37371f142e6a0e9dc5058752d8c9d401",
        "repo": "sympy",
        "path": "sympy/polys/orthopolys.py",
        "file_name": "orthopolys.py",
        "fun_name": "dup_chebyshevu",
        "commit_message": "Restore domain elements in dup_* functions",
        "code": "def dup_chebyshevu(n, K):\n    \n    if n < 1:\n        return [K.one]\n    m2, m1 = [K.one], [K(2), K.zero]\n    for i in range(2, n+1):\n        m2, m1 = m1, dup_sub(dup_mul_ground(dup_lshift(m1, 1, K), K(2), K), m2, K)\n    return m1\n\n@public",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "@public",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 62,
        "n_words": 34,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 84,
        "n_ast_nodes": 129,
        "n_identifiers": 13,
        "d_id": 49373,
        "documentation": {
            "docstring": "Low-level implementation of Chebyshev polynomials of the second kind.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 207487,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/test_actions.py",
        "file_name": "test_actions.py",
        "fun_name": "test_media_from_actions_form",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_media_from_actions_form(self):\n        \n        response = self.client.get(reverse(\"admin:admin_views_subscriber_changelist\"))\n        media_path = MediaActionForm.Media.js[0]\n        self.assertIsInstance(response.context[\"action_form\"], MediaActionForm)\n        self.assertIn(\"media\", response.context)\n        self.assertIn(media_path, response.context[\"media\"]._js)\n        self.assertContains(response, media_path)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 65,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 75,
        "n_ast_nodes": 125,
        "n_identifiers": 15,
        "d_id": 51978,
        "documentation": {
            "docstring": "\n        The action form's media is included in the changelist view's media.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 46269,
        "commit_id": "68aa01936c37f9b03468cc83e3f32766ae0ba5cb",
        "repo": "airflow",
        "path": "airflow/_vendor/cgroupspy/nodes.py",
        "file_name": "nodes.py",
        "fun_name": "create_cgroup",
        "commit_message": "Add cgroupspy to _vendor folder (#22206)\n\nThis is just importing existing cgroupspy library without\r\ncode modifications. In the next step we will modify the cgroupspy\r\ncode to work from the new location, then we will fix it to\r\nimplement Python 3.10 compatibility and finally we will change\r\nairflow to use the vendored package instead of the original\r\npackage.\r\n\r\nThis is part of the effort needed to implement Python 3.10\r\ncompatibility: #22050",
        "code": "def create_cgroup(self, name):\n        \n        if isinstance(name, str):\n            name = name.encode()\n\n        node = Node(name, parent=self)\n        if node in self.children:\n            raise RuntimeError('Node {} already exists under {}'.format(name, self.path))\n\n        fp = os.path.join(self.full_path, name)\n        os.mkdir(fp)\n        self.children.append(node)\n        return node\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 111,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 84,
        "n_ast_nodes": 135,
        "n_identifiers": 19,
        "d_id": 8836,
        "documentation": {
            "docstring": "\n        Create a cgroup by name and attach it under this node.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 144569,
        "commit_id": "54a71e6c4f430f210685e3b1bccef8051dd1260c",
        "repo": "ray",
        "path": "python/ray/experimental/dag/dag_node.py",
        "file_name": "dag_node.py",
        "fun_name": "_get_all_child_nodes",
        "commit_message": "[Ray DAG] Add `execute()` interface to take user inputs with ENTRY_POINT tag. (#22196)\n\n## Diff Summary\r\n\r\nCurrent implementation of DAGNode pre-bind inputs and the signature of `def execute(self)` doesn't take user input yet. This PR extends the interface to take user input, mark DAG entrypoint methods as first stop of all user requests in a DAG. It's needed to unblock next step serve pipeline implementation to serve user requests.\r\n\r\nCloses #22196 #22197\r\n\r\nNotable changes:\r\n- Added a `DAG_ENTRY_POINT` flag in ray dag API to annotate DAG entrypoint functions. Function or class method only. All marked functions will receive identical input from user as first layer of DAG. \r\n- Changed implementations of ClassNode and FunctionNode accordingly to handle different execution for a node marked as entrypoint or not.\r\n- Added a `kwargs_to_resolve` kwarg in the interface of `DAGNode` to handle args that sub-classes need to use to resolve it's implementation without exposing all terms to parent class level.\r\n  - This is particularly important for ClassMethodNode binding, so we can have implementations to track method name, parent ClassNode as well as previous class method call without existiting \r\n  - Changed implementation of `_copy()` to handle execution of `kwargs_to_resolve`.\r\n  - Changed implementation of `_apply_and_replace_all_child_nodes()` to fetch DAGNode type in `kwargs_to_resolve`.\r\n- Added pretty printed lines for `kwargs_to_resolve`",
        "code": "def _get_all_child_nodes(self) -> Set[\"DAGNode\"]:\n        \n\n        scanner = _PyObjScanner()\n        children = set()\n        for n in scanner.find_nodes(\n            [\n                self._bound_args,\n                self._bound_kwargs,\n                self._bound_other_args_to_resolve,\n            ]\n        ):\n            children.add(n)\n        return children\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 143,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 19,
        "token_counts": 52,
        "n_ast_nodes": 85,
        "n_identifiers": 13,
        "d_id": 33256,
        "documentation": {
            "docstring": "Return the set of nodes referenced by the args, kwargs, and\n        args_to_resolve in current node, even they're deeply nested.\n\n        Examples:\n            f.remote(a, [b]) -> set(a, b)\n            f.remote(a, [b], key={\"nested\": [c]}) -> set(a, b, c)\n        ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 259117,
        "commit_id": "279388d9ed2ea83194dd45a2d78161be30b43aa7",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/_discretization.py",
        "file_name": "_discretization.py",
        "fun_name": "get_feature_names_out",
        "commit_message": "DOC Improve get_feature_names_out docstrings (#22718)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def get_feature_names_out(self, input_features=None):\n        \n        input_features = _check_feature_names_in(self, input_features)\n        return self._encoder.get_feature_names_out(input_features)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 75576,
        "documentation": {
            "docstring": "Get output feature names.\n\n        Parameters\n        ----------\n        input_features : array-like of str or None, default=None\n            Input features.\n\n            - If `input_features` is `None`, then `feature_names_in_` is\n              used as feature names in. If `feature_names_in_` is not defined,\n              then the following input feature names are generated:\n              `[\"x0\", \"x1\", ..., \"x(n_features_in_ - 1)\"]`.\n            - If `input_features` is an array-like, then `input_features` must\n              match `feature_names_in_` if `feature_names_in_` is defined.\n\n        Returns\n        -------\n        feature_names_out : ndarray of str objects\n            Transformed feature names.\n        ",
            "n_words": 74,
            "vocab_size": 51,
            "n_whitespaces": 219,
            "language": "en"
        }
    },
    {
        "id": 29670,
        "commit_id": "9effd5aec81acbdd2a1076c1d72bbee1afcc65a1",
        "repo": "saleor",
        "path": "saleor/graphql/order/tests/queries/test_order.py",
        "file_name": "test_order.py",
        "fun_name": "test_orders_without_channel",
        "commit_message": "restructure order app tests (#11226)",
        "code": "def test_orders_without_channel(staff_api_client, permission_manage_orders, orders):\n    query = \n\n    staff_api_client.user.user_permissions.add(permission_manage_orders)\n    response = staff_api_client.post_graphql(query)\n    edges = get_graphql_content(response)[\"data\"][\"orders\"][\"edges\"]\n\n    assert len(edges) == Order.objects.non_draft().count()\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 62,
        "n_ast_nodes": 105,
        "n_identifiers": 17,
        "d_id": 5253,
        "documentation": {
            "docstring": "\n    query OrdersQuery {\n        orders(first: 10) {\n            edges {\n                node {\n                    id\n                }\n            }\n        }\n    }\n    ",
            "n_words": 15,
            "vocab_size": 9,
            "n_whitespaces": 110,
            "language": "en"
        }
    },
    {
        "id": 207064,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_custom_urls/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_basic_add_GET",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_basic_add_GET(self):\n        \n        add_url = reverse(\"admin_custom_urls:admin_custom_urls_action_add\")\n        self.assertTrue(add_url.endswith(\"/!add/\"))\n        response = self.client.get(add_url)\n        self.assertIsInstance(response, TemplateResponse)\n        self.assertEqual(response.status_code, 200)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 55,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 51,
        "n_ast_nodes": 88,
        "n_identifiers": 13,
        "d_id": 51855,
        "documentation": {
            "docstring": "\n        Ensure GET on the add_view works.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 144664,
        "commit_id": "48adb6f7bb335b28fb0fb0d1190bd6c5dfc8ddfa",
        "repo": "ray",
        "path": "python/ray/serve/deployment_state.py",
        "file_name": "deployment_state.py",
        "fun_name": "shutdown",
        "commit_message": "[serve] Introduce DeploymentStatus, poll for statuses instead of using async goals (#22121)",
        "code": "def shutdown(self):\n        \n\n        for deployment_state in self._deployment_states.values():\n            deployment_state.delete()\n\n        # TODO(jiaodong): This might not be 100% safe since we deleted\n        # everything without ensuring all shutdown goals are completed\n        # yet. Need to address in follow-up PRs.\n        self._kv_store.delete(CHECKPOINT_KEY)\n\n        # TODO(jiaodong): Need to add some logic to prevent new replicas\n        # from being created once shutdown signal is sent.\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 123,
        "n_words": 56,
        "vocab_size": 46,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 30,
        "n_ast_nodes": 57,
        "n_identifiers": 8,
        "d_id": 33278,
        "documentation": {
            "docstring": "\n        Shutdown all running replicas by notifying the controller, and leave\n        it to the controller event loop to take actions afterwards.\n\n        Once shutdown signal is received, it will also prevent any new\n        deployments or replicas from being created.\n\n        One can send multiple shutdown signals but won't effectively make any\n        difference compare to calling it once.\n        ",
            "n_words": 54,
            "vocab_size": 46,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 167731,
        "commit_id": "f65417656ba8c59438d832b6e2a431f78d40c21c",
        "repo": "pandas",
        "path": "pandas/core/arrays/sparse/accessor.py",
        "file_name": "accessor.py",
        "fun_name": "from_spmatrix",
        "commit_message": "TYP: more return annotations in core/ (#47618)\n\n* TYP: more return annotations in core/\r\n\r\n* from __future__ import annotations\r\n\r\n* more __future__",
        "code": "def from_spmatrix(cls, data, index=None, columns=None) -> DataFrame:\n        \n        from pandas._libs.sparse import IntIndex\n\n        from pandas import DataFrame\n\n        data = data.tocsc()\n        index, columns = cls._prep_index(data, index, columns)\n        n_rows, n_columns = data.shape\n        # We need to make sure indices are sorted, as we create\n        # IntIndex with no input validation (i.e. check_integrity=False ).\n        # Indices may already be sorted in scipy in which case this adds\n        # a small overhead.\n        data.sort_indices()\n        indices = data.indices\n        indptr = data.indptr\n        array_data = data.data\n        dtype = SparseDtype(array_data.dtype, 0)\n        arrays = []\n        for i in range(n_columns):\n            sl = slice(indptr[i], indptr[i + 1])\n            idx = IntIndex(n_rows, indices[sl], check_integrity=False)\n            arr = SparseArray._simple_new(array_data[sl], idx, dtype)\n            arrays.append(arr)\n        return DataFrame._from_arrays(\n            arrays, columns=columns, index=index, verify_integrity=False\n        )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 299,
        "n_words": 111,
        "vocab_size": 91,
        "complexity": 2,
        "nloc": 49,
        "token_counts": 171,
        "n_ast_nodes": 261,
        "n_identifiers": 34,
        "d_id": 40093,
        "documentation": {
            "docstring": "\n        Create a new DataFrame from a scipy sparse matrix.\n\n        .. versionadded:: 0.25.0\n\n        Parameters\n        ----------\n        data : scipy.sparse.spmatrix\n            Must be convertible to csc format.\n        index, columns : Index, optional\n            Row and column labels to use for the resulting DataFrame.\n            Defaults to a RangeIndex.\n\n        Returns\n        -------\n        DataFrame\n            Each column of the DataFrame is stored as a\n            :class:`arrays.SparseArray`.\n\n        Examples\n        --------\n        >>> import scipy.sparse\n        >>> mat = scipy.sparse.eye(3)\n        >>> pd.DataFrame.sparse.from_spmatrix(mat)\n             0    1    2\n        0  1.0  0.0  0.0\n        1  0.0  1.0  0.0\n        2  0.0  0.0  1.0\n        ",
            "n_words": 81,
            "vocab_size": 59,
            "n_whitespaces": 290,
            "language": "en"
        }
    },
    {
        "id": 149719,
        "commit_id": "b58e811b1486ae62e835cbea3e40cf88128243a0",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/trade_model.py",
        "file_name": "trade_model.py",
        "fun_name": "has_no_leverage",
        "commit_message": "Move trade/order Models to their own class",
        "code": "def has_no_leverage(self) -> bool:\n        \n        return ((self.leverage == 1.0 or self.leverage is None) and not self.is_short)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 29,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 48,
        "n_identifiers": 5,
        "d_id": 34502,
        "documentation": {
            "docstring": "Returns true if this is a non-leverage, non-short trade",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 207583,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_limited_filter",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_limited_filter(self):\n        \n        response = self.client.get(reverse(\"admin:admin_views_thing_changelist\"))\n        self.assertContains(\n            response,\n            '<div id=\"changelist-filter\">',\n            msg_prefix=\"Expected filter not found in changelist view\",\n        )\n        self.assertNotContains(\n            response,\n            '<a href=\"?color__id__exact=3\">Blue</a>',\n            msg_prefix=\"Changelist filter not correctly limited by limit_choices_to\",\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 137,
        "n_words": 29,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 45,
        "n_ast_nodes": 80,
        "n_identifiers": 9,
        "d_id": 52009,
        "documentation": {
            "docstring": "Ensure admin changelist filters do not contain objects excluded via limit_choices_to.\n        This also tests relation-spanning filters (e.g. 'color__value').\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 109880,
        "commit_id": "df6f95703b60348e01603f98a439b133da2938a0",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/axes_grid1/axes_divider.py",
        "file_name": "axes_divider.py",
        "fun_name": "new_locator",
        "commit_message": "Improve mpl_toolkit documentation",
        "code": "def new_locator(self, nx, ny, nx1=None, ny1=None):\n        \n        return AxesLocator(\n            self, nx, ny,\n            nx1 if nx1 is not None else nx + 1,\n            ny1 if ny1 is not None else ny + 1)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 78,
        "n_words": 31,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 49,
        "n_ast_nodes": 67,
        "n_identifiers": 7,
        "d_id": 23789,
        "documentation": {
            "docstring": "\n        Return a new `.AxesLocator` for the specified cell.\n\n        Parameters\n        ----------\n        nx, nx1 : int\n            Integers specifying the column-position of the\n            cell. When *nx1* is None, a single *nx*-th column is\n            specified. Otherwise, location of columns spanning between *nx*\n            to *nx1* (but excluding *nx1*-th column) is specified.\n        ny, ny1 : int\n            Same as *nx* and *nx1*, but for row positions.\n        ",
            "n_words": 59,
            "vocab_size": 46,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 9827,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/helper.py",
        "file_name": "helper.py",
        "fun_name": "random_port",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def random_port() -> Optional[int]:\n    \n\n    import threading\n    import multiprocessing\n    from contextlib import closing\n    import socket\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 29,
        "n_words": 14,
        "vocab_size": 11,
        "complexity": 5,
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        "token_counts": 131,
        "n_ast_nodes": 38,
        "n_identifiers": 8,
        "d_id": 1713,
        "documentation": {
            "docstring": "\n    Get a random available port number from '49153' to '65535'.\n\n    :return: A random port.\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 303763,
        "commit_id": "ebbff7b60e43f17d65ead811d314602b9daddfc4",
        "repo": "core",
        "path": "tests/components/awair/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "local_devices_fixture",
        "commit_message": "Add Awair Local API support (#75535)",
        "code": "def local_devices_fixture():\n    \n    return json.loads(load_fixture(\"awair/local_devices.json\"))\n\n\n@pytest.fixture(name=\"gen1_data\", scope=\"session\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(name=\"gen1_data\", scope=\"session\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 11,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 15,
        "n_ast_nodes": 54,
        "n_identifiers": 8,
        "d_id": 102572,
        "documentation": {
            "docstring": "Fixture representing devices returned by Awair local API.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 269534,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "in_test_phase",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def in_test_phase(x, alt, training=None):\n    \n    return in_train_phase(alt, x, training=training)\n\n\n# NN OPERATIONS\n\n\n@keras_export(\"keras.backend.relu\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.relu\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
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        "n_whitespaces": 16,
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        "complexity": 1,
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        "token_counts": 23,
        "n_ast_nodes": 65,
        "n_identifiers": 12,
        "d_id": 80162,
        "documentation": {
            "docstring": "Selects `x` in test phase, and `alt` otherwise.\n\n    Note that `alt` should have the *same shape* as `x`.\n\n    Args:\n        x: What to return in test phase\n            (tensor or callable that returns a tensor).\n        alt: What to return otherwise\n            (tensor or callable that returns a tensor).\n        training: Optional scalar tensor\n            (or Python boolean, or Python integer)\n            specifying the learning phase.\n\n    Returns:\n        Either `x` or `alt` based on `K.learning_phase`.\n    ",
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        "id": 62541,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/html5lib/html5parser.py",
        "file_name": "html5parser.py",
        "fun_name": "parse",
        "commit_message": "upd; format",
        "code": "def parse(self, stream, *args, **kwargs):\n        \n        self._parse(stream, False, None, *args, **kwargs)\n        return self.tree.getDocument()\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "documentation": {
            "docstring": "Parse a HTML document into a well-formed tree\n\n        :arg stream: a file-like object or string containing the HTML to be parsed\n\n            The optional encoding parameter must be a string that indicates\n            the encoding.  If specified, that encoding will be used,\n            regardless of any BOM or later declaration (such as in a meta\n            element).\n\n        :arg scripting: treat noscript elements as if JavaScript was turned on\n\n        :returns: parsed tree\n\n        Example:\n\n        >>> from html5lib.html5parser import HTMLParser\n        >>> parser = HTMLParser()\n        >>> parser.parse('<html><body><p>This is a doc</p></body></html>')\n        <Element u'{http://www.w3.org/1999/xhtml}html' at 0x7feac4909db0>\n\n        ",
            "n_words": 86,
            "vocab_size": 67,
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            "language": "en"
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    {
        "id": 176320,
        "commit_id": "34d9d630bb02426d297d3e20fedb7da8c3ced03a",
        "repo": "networkx",
        "path": "networkx/algorithms/assortativity/correlation.py",
        "file_name": "correlation.py",
        "fun_name": "numeric_assortativity_coefficient",
        "commit_message": "MAINT: Cleanup assortativity module, remove unused variables (#5301)\n\nRemove unused variables, sort imports,\r\nraise errors instead of accepting invalid arguments silently\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def numeric_assortativity_coefficient(G, attribute, nodes=None):\n    \n    if nodes is None:\n        nodes = G.nodes\n    vals = {G.nodes[n][attribute] for n in nodes}\n    mapping = {d: i for i, d, in enumerate(vals)}\n    M = attribute_mixing_matrix(G, attribute, nodes, mapping)\n    return _numeric_ac(M, mapping)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 10,
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        "token_counts": 75,
        "n_ast_nodes": 111,
        "n_identifiers": 13,
        "d_id": 41834,
        "documentation": {
            "docstring": "Compute assortativity for numerical node attributes.\n\n    Assortativity measures the similarity of connections\n    in the graph with respect to the given numeric attribute.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n\n    attribute : string\n        Node attribute key.\n\n    nodes: list or iterable (optional)\n        Compute numeric assortativity only for attributes of nodes in\n        container. The default is all nodes.\n\n    Returns\n    -------\n    r: float\n       Assortativity of graph for given attribute\n\n    Examples\n    --------\n    >>> G = nx.Graph()\n    >>> G.add_nodes_from([0, 1], size=2)\n    >>> G.add_nodes_from([2, 3], size=3)\n    >>> G.add_edges_from([(0, 1), (2, 3)])\n    >>> print(nx.numeric_assortativity_coefficient(G, \"size\"))\n    1.0\n\n    Notes\n    -----\n    This computes Eq. (21) in Ref. [1]_ , which is the Pearson correlation\n    coefficient of the specified (scalar valued) attribute across edges.\n\n    References\n    ----------\n    .. [1] M. E. J. Newman, Mixing patterns in networks\n           Physical Review E, 67 026126, 2003\n    ",
            "n_words": 129,
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        "id": 296854,
        "commit_id": "73a368c24246b081cdb98923ca3180937d436c3b",
        "repo": "core",
        "path": "homeassistant/components/history_stats/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "pretty_duration",
        "commit_message": "Refactor history_stats to minimize database access (part 2) (#70255)",
        "code": "def pretty_duration(hours):\n        \n        seconds = int(3600 * hours)\n        days, seconds = divmod(seconds, 86400)\n        hours, seconds = divmod(seconds, 3600)\n        minutes, seconds = divmod(seconds, 60)\n        if days > 0:\n            return \"%dd %dh %dm\" % (days, hours, minutes)\n        if hours > 0:\n            return \"%dh %dm\" % (hours, minutes)\n        return \"%dm\" % minutes\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 95828,
        "documentation": {
            "docstring": "Format a duration in days, hours, minutes, seconds.",
            "n_words": 8,
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            "language": "en"
        }
    },
    {
        "id": 130281,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/_private/thirdparty/pathspec/util.py",
        "file_name": "util.py",
        "fun_name": "_normalize_entries",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _normalize_entries(entries, separators=None):\n    \n    norm_files = {}\n    for entry in entries:\n        norm_files[normalize_file(entry.path, separators=separators)] = entry\n    return norm_files\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 29206,
        "documentation": {
            "docstring": "\n    Normalizes the entry paths to use the POSIX path separator.\n\n    *entries* (:class:`~collections.abc.Iterable` of :class:`.TreeEntry`)\n    contains the entries to be normalized.\n\n    *separators* (:class:`~collections.abc.Collection` of :class:`str`; or\n    :data:`None`) optionally contains the path separators to normalize.\n    See :func:`normalize_file` for more information.\n\n    Returns a :class:`dict` mapping the each normalized file path (:class:`str`)\n    to the entry (:class:`.TreeEntry`)\n    ",
            "n_words": 52,
            "vocab_size": 39,
            "n_whitespaces": 80,
            "language": "en"
        }
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    {
        "id": 107727,
        "commit_id": "4caa5ba85c11cc499eb1a45372eb249173e6b1fd",
        "repo": "matplotlib",
        "path": "lib/matplotlib/cbook/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_connect_picklable",
        "commit_message": "Simplify the internal API to connect picklable callbacks.\n\nThe API may be made public in the future, but right now the point is\nonly to make its internal use more ergonomic as it can be helpful in\nsome other internal places too (to be updated in a separate patch).",
        "code": "def _connect_picklable(self, signal, func):\n        \n        cid = self.connect(signal, func)\n        self._pickled_cids.add(cid)\n        return cid\n\n    # Keep a reference to sys.is_finalizing, as sys may have been cleared out\n    # at that point.",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "token_counts": 30,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 22893,
        "documentation": {
            "docstring": "\n        Like `.connect`, but the callback is kept when pickling/unpickling.\n\n        Currently internal-use only.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
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    {
        "id": 40277,
        "commit_id": "47b5c8af57f0f927d50fe94f3474b09a54292553",
        "repo": "seaborn",
        "path": "seaborn/external/appdirs.py",
        "file_name": "appdirs.py",
        "fun_name": "_get_win_folder_from_registry",
        "commit_message": "Standardize cache directory",
        "code": "def _get_win_folder_from_registry(csidl_name):\n    \n    import winreg as _winreg\n\n    shell_folder_name = {\n        \"CSIDL_APPDATA\": \"AppData\",\n        \"CSIDL_COMMON_APPDATA\": \"Common AppData\",\n        \"CSIDL_LOCAL_APPDATA\": \"Local AppData\",\n    }[csidl_name]\n\n    key = _winreg.OpenKey(\n        _winreg.HKEY_CURRENT_USER,\n        r\"Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\Shell Folders\"\n    )\n    dir, type = _winreg.QueryValueEx(key, shell_folder_name)\n    return dir\n\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "token_counts": 56,
        "n_ast_nodes": 99,
        "n_identifiers": 11,
        "d_id": 7372,
        "documentation": {
            "docstring": "This is a fallback technique at best. I'm not sure if using the\n    registry for this guarantees us the correct answer for all CSIDL_*\n    names.\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 22751,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "primelib/primelib.py",
        "file_name": "primelib.py",
        "fun_name": "getPrimeNumbers",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def getPrimeNumbers(N):\n    \n\n    # precondition\n    assert isinstance(N, int) and (N > 2), \"'N' must been an int and > 2\"\n\n    ans = []\n\n    # iterates over all numbers between 2 up to N+1\n    # if a number is prime then appends to list 'ans'\n    for number in range(2, N + 1):\n\n        if isPrime(number):\n            ans.append(number)\n\n    # precondition\n    assert isinstance(ans, list), \"'ans' must been from type list\"\n\n    return ans\n\n\n# -----------------------------------------\n\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "complexity": 4,
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        "token_counts": 60,
        "n_ast_nodes": 102,
        "n_identifiers": 10,
        "d_id": 4442,
        "documentation": {
            "docstring": "\n    input: positive integer 'N' > 2\n    returns a list of prime numbers from 2 up to N (inclusive)\n    This function is more efficient as function 'sieveEr(...)'\n    ",
            "n_words": 26,
            "vocab_size": 24,
            "n_whitespaces": 39,
            "language": "en"
        }
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    {
        "id": 178479,
        "commit_id": "68e62e62d6d1c92209dcc1c7b60c3b5e09bcf308",
        "repo": "Nuitka",
        "path": "nuitka/plugins/PluginBase.py",
        "file_name": "PluginBase.py",
        "fun_name": "onBootstrapBinary",
        "commit_message": "Plugins: Add support for upx compression of onefile tempdir Linux\n\n* This also avoids the padding done for Windows signing tool to\n  be applied to other platforms, not needed there.\n\n* For UPX not preserving payload outside of Windows, we need to\n  apply it before the payload gets attached on Linux with temp\n  file mode.\n\n* Also do not do it AppImage, it hates that to happen, probably\n  that is also a payload attachment problem.",
        "code": "def onBootstrapBinary(self, filename):\n        \n        # Virtual method, pylint: disable=no-self-use,unused-argument\n        return None\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
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        "n_identifiers": 3,
        "d_id": 42707,
        "documentation": {
            "docstring": "Called after successfully creating a bootstrap binary, but without payload.\n\n        Args:\n            filename: the created bootstrap binary, will be modified later\n\n        Returns:\n            None\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 196680,
        "commit_id": "9ad8ab9fe58051cf11626ba6654852fcfec60147",
        "repo": "sympy",
        "path": "sympy/stats/crv_types.py",
        "file_name": "crv_types.py",
        "fun_name": "FDistribution",
        "commit_message": "Documentation cleanup 5",
        "code": "def FDistribution(name, d1, d2):\n    r\n\n    return rv(name, FDistributionDistribution, (d1, d2))\n\n#-------------------------------------------------------------------------------\n# Fisher Z distribution --------------------------------------------------------\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "documentation": {
            "docstring": "\n    Create a continuous random variable with a F distribution.\n\n    Explanation\n    ===========\n\n    The density of the F distribution is given by\n\n    .. math::\n        f(x) := \\frac{\\sqrt{\\frac{(d_1 x)^{d_1} d_2^{d_2}}\n                {(d_1 x + d_2)^{d_1 + d_2}}}}\n                {x \\mathrm{B} \\left(\\frac{d_1}{2}, \\frac{d_2}{2}\\right)}\n\n    with :math:`x > 0`.\n\n    Parameters\n    ==========\n\n    d1 : `d_1 > 0`, where `d_1` is the degrees of freedom (`n_1 - 1`)\n    d2 : `d_2 > 0`, where `d_2` is the degrees of freedom (`n_2 - 1`)\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    Examples\n    ========\n\n    >>> from sympy.stats import FDistribution, density\n    >>> from sympy import Symbol, pprint\n\n    >>> d1 = Symbol(\"d1\", positive=True)\n    >>> d2 = Symbol(\"d2\", positive=True)\n    >>> z = Symbol(\"z\")\n\n    >>> X = FDistribution(\"x\", d1, d2)\n\n    >>> D = density(X)(z)\n    >>> pprint(D, use_unicode=False)\n      d2\n      --    ______________________________\n      2    /       d1            -d1 - d2\n    d2  *\\/  (d1*z)  *(d1*z + d2)\n    --------------------------------------\n                    /d1  d2\\\n                 z*B|--, --|\n                    \\2   2 /\n\n    References\n    ==========\n\n    .. [1] https://en.wikipedia.org/wiki/F-distribution\n    .. [2] http://mathworld.wolfram.com/F-Distribution.html\n\n    ",
            "n_words": 148,
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        "id": 221275,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/cgi.py",
        "file_name": "cgi.py",
        "fun_name": "read_lines_to_outerboundary",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def read_lines_to_outerboundary(self):\n        \n        next_boundary = b\"--\" + self.outerboundary\n        last_boundary = next_boundary + b\"--\"\n        delim = b\"\"\n        last_line_lfend = True\n        _read = 0\n        while 1:\n\n            if self.limit is not None and 0 <= self.limit <= _read:\n                break\n            line = self.fp.readline(1<<16) # bytes\n            self.bytes_read += len(line)\n            _read += len(line)\n            if not line:\n                self.done = -1\n                break\n            if delim == b\"\\r\":\n                line = delim + line\n                delim = b\"\"\n            if line.startswith(b\"--\") and last_line_lfend:\n                strippedline = line.rstrip()\n                if strippedline == next_boundary:\n                    break\n                if strippedline == last_boundary:\n                    self.done = 1\n                    break\n            odelim = delim\n            if line.endswith(b\"\\r\\n\"):\n                delim = b\"\\r\\n\"\n                line = line[:-2]\n                last_line_lfend = True\n            elif line.endswith(b\"\\n\"):\n                delim = b\"\\n\"\n                line = line[:-1]\n                last_line_lfend = True\n            elif line.endswith(b\"\\r\"):\n                # We may interrupt \\r\\n sequences if they span the 2**16\n                # byte boundary\n                delim = b\"\\r\"\n                line = line[:-1]\n                last_line_lfend = False\n            else:\n                delim = b\"\"\n                last_line_lfend = False\n            self.__write(odelim + line)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
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            "docstring": "Internal: read lines until outerboundary.\n        Data is read as bytes: boundaries and line ends must be converted\n        to bytes for comparisons.\n        ",
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    {
        "id": 289746,
        "commit_id": "6979cd95b0fe85c3ee8eca3dbc9881b8d05591e8",
        "repo": "core",
        "path": "homeassistant/components/sensor/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "suggested_unit_of_measurement",
        "commit_message": "Add suggested_unit_of_measurement attribute to sensors (#80638)\n\n* Add suggested_unit_of_measurement attribute to sensors\r\n\r\n* Lazy calculation of initial entity options\r\n\r\n* Add type alias for entity options\r\n\r\n* Small tweak\r\n\r\n* Add tests\r\n\r\n* Store suggested_unit_of_measurement in its own option key\r\n\r\n* Adapt to renaming of IMPERIAL_SYSTEM\r\n\r\n* Fix rebase mistakes\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "def suggested_unit_of_measurement(self) -> str | None:\n        \n        if hasattr(self, \"_attr_suggested_unit_of_measurement\"):\n            return self._attr_suggested_unit_of_measurement\n        if hasattr(self, \"entity_description\"):\n            return self.entity_description.suggested_unit_of_measurement\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 88882,
        "documentation": {
            "docstring": "Return the unit which should be used for the sensor's state.\n\n        This can be used by integrations to override automatic unit conversion rules,\n        for example to make a temperature sensor display in °C even if the configured\n        unit system prefers °F.\n\n        For sensors without a `unique_id`, this takes precedence over legacy\n        temperature conversion rules only.\n\n        For sensors with a `unique_id`, this is applied only if the unit is not set by the user,\n        and takes precedence over automatic device-class conversion rules.\n\n        Note:\n            suggested_unit_of_measurement is stored in the entity registry the first time\n            the entity is seen, and then never updated.\n        ",
            "n_words": 100,
            "vocab_size": 65,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 104693,
        "commit_id": "eab78694e17f10c200bceb60c6f21a2f70eadf68",
        "repo": "datasets",
        "path": "datasets/medical_dialog/medical_dialog.py",
        "file_name": "medical_dialog.py",
        "fun_name": "manual_download_instructions",
        "commit_message": "Add configs with processed data to medical_dialog dataset (#4127)\n\n* Add configs with processed data in medical_dialog dataset\r\n\r\n* Update metadata JSON\r\n\r\n* Update dataset card\r\n\r\n* Rename dummy data dirs\r\n\r\n* Fix script",
        "code": "def manual_download_instructions(self):\n        *processed, _ = self.config.name.split(\".\")\n        return (\n            None\n            if processed\n            else \n        )\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 21934,
        "documentation": {
            "docstring": "\\\n    \\n  For English:\\nYou need to go to https://drive.google.com/drive/folders/1g29ssimdZ6JzTST6Y8g6h-ogUNReBtJD?usp=sharing,\\\n    and manually download the dataset from Google Drive. Once it is completed,\n    a file named Medical-Dialogue-Dataset-English-<timestamp-info>.zip will appear in your Downloads folder(\n    or whichever folder your browser chooses to save files to). Unzip the folder to obtain\n    a folder named \"Medical-Dialogue-Dataset-English\" several text files.\n\n    Now, you can specify the path to this folder for the data_dir argument in the\n    datasets.load_dataset(...) option.\n    The <path/to/folder> can e.g. be \"/Downloads/Medical-Dialogue-Dataset-English\".\n    The data can then be loaded using the below command:\\\n         `datasets.load_dataset(\"medical_dialog\", name=\"en\", data_dir=\"/Downloads/Medical-Dialogue-Dataset-English\")`.\n\n    \\n  For Chinese:\\nFollow the above process. Change the 'name' to 'zh'.The download link is https://drive.google.com/drive/folders/1r09_i8nJ9c1nliXVGXwSqRYqklcHd9e2\n\n    **NOTE**\n    - A caution while downloading from drive. It is better to download single files since creating a zip might not include files <500 MB. This has been observed mutiple times.\n    - After downloading the files and adding them to the appropriate folder, the path of the folder can be given as input tu the data_dir path.\n    ",
            "n_words": 161,
            "vocab_size": 112,
            "n_whitespaces": 213,
            "language": "en"
        }
    },
    {
        "id": 108010,
        "commit_id": "075ff0952896f44d7d0b0b3318f0978ae53f84d7",
        "repo": "matplotlib",
        "path": "lib/matplotlib/offsetbox.py",
        "file_name": "offsetbox.py",
        "fun_name": "set_bbox_to_anchor",
        "commit_message": "Small style fixes.",
        "code": "def set_bbox_to_anchor(self, bbox, transform=None):\n        \n        if bbox is None or isinstance(bbox, BboxBase):\n            self._bbox_to_anchor = bbox\n        else:\n            try:\n                l = len(bbox)\n            except TypeError as err:\n                raise ValueError(f\"Invalid bbox: {bbox}\") from err\n\n            if l == 2:\n                bbox = [bbox[0], bbox[1], 0, 0]\n\n            self._bbox_to_anchor = Bbox.from_bounds(*bbox)\n\n        self._bbox_to_anchor_transform = transform\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 183,
        "n_words": 48,
        "vocab_size": 38,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 95,
        "n_ast_nodes": 153,
        "n_identifiers": 16,
        "d_id": 23014,
        "documentation": {
            "docstring": "\n        Set the bbox that the box is anchored to.\n\n        *bbox* can be a Bbox instance, a list of [left, bottom, width,\n        height], or a list of [left, bottom] where the width and\n        height will be assumed to be zero. The bbox will be\n        transformed to display coordinate by the given transform.\n        ",
            "n_words": 51,
            "vocab_size": 37,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 47750,
        "commit_id": "c3d883a971a8e4e65ccc774891928daaaa0f4442",
        "repo": "airflow",
        "path": "tests/providers/cncf/kubernetes/operators/test_kubernetes_pod.py",
        "file_name": "test_kubernetes_pod.py",
        "fun_name": "test_mark_checked_unexpected_exception",
        "commit_message": "KubernetesPodOperator should patch \"already checked\" always (#22734)\n\nWhen not configured to delete pods, at end of task execution the current behavior is to patch the pod as \"already checked\", but only if pod not successful.  We should also patch when successful so it isn't \"reattached\" to after a task clear.",
        "code": "def test_mark_checked_unexpected_exception(self, mock_patch_already_checked, mock_delete_pod):\n        \n        k = KubernetesPodOperator(\n            namespace=\"default\",\n            image=\"ubuntu:16.04\",\n            name=\"test\",\n            task_id=\"task\",\n            is_delete_operator_pod=False,\n        )\n        self.await_pod_mock.side_effect = AirflowException(\"oops\")\n        context = create_context(k)\n        with pytest.raises(AirflowException):\n            k.execute(context=context)\n        mock_patch_already_checked.assert_called_once()\n        mock_delete_pod.assert_not_called()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 146,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 77,
        "n_ast_nodes": 133,
        "n_identifiers": 21,
        "d_id": 9243,
        "documentation": {
            "docstring": "If we aren't deleting pods and have an exception, mark it so we don't reattach to it",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 61420,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "is_immutable_rev_checkout",
        "commit_message": "upd; format",
        "code": "def is_immutable_rev_checkout(self, url, dest):\n        # type: (str, str) -> bool\n        \n        return False\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 21,
        "n_identifiers": 4,
        "d_id": 12563,
        "documentation": {
            "docstring": "\n        Return true if the commit hash checked out at dest matches\n        the revision in url.\n\n        Always return False, if the VCS does not support immutable commit\n        hashes.\n\n        This method does not check if there are local uncommitted changes\n        in dest after checkout, as pip currently has no use case for that.\n        ",
            "n_words": 51,
            "vocab_size": 42,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 295372,
        "commit_id": "d7375f1a9c4a69858a65a56bd524f5a78ecab23c",
        "repo": "core",
        "path": "tests/components/telegram_bot/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "unauthorized_update_message_text",
        "commit_message": "Refactor telegram_bot polling/webhooks platforms and add tests (#66433)\n\nCo-authored-by: Pär Berge <paer.berge@gmail.com>",
        "code": "def unauthorized_update_message_text(update_message_text):\n    \n    update_message_text[\"message\"][\"from\"][\"id\"] = 1234\n    update_message_text[\"message\"][\"chat\"][\"id\"] = 1234\n    return update_message_text\n\n\n@pytest.fixture",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 22,
        "n_words": 11,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 69,
        "n_identifiers": 4,
        "d_id": 94390,
        "documentation": {
            "docstring": "Fixture for mocking an incoming update of type message/text that is not in our `allowed_chat_ids`.",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 216011,
        "commit_id": "52c922760e8447f0c9efd23b12481ba1a7509dcd",
        "repo": "salt",
        "path": "salt/states/win_wua.py",
        "file_name": "win_wua.py",
        "fun_name": "installed",
        "commit_message": "Remove 40 character limit to update Title",
        "code": "def installed(name, updates=None):\n    \n    if isinstance(updates, str):\n        updates = [updates]\n\n    if not updates:\n        updates = name\n\n    ret = {\"name\": name, \"changes\": {}, \"result\": True, \"comment\": \"\"}\n\n    wua = salt.utils.win_update.WindowsUpdateAgent()\n\n    # Search for updates\n    install_list = wua.search(updates)\n\n    # No updates found\n    if install_list.count() == 0:\n        ret[\"comment\"] = \"No updates found\"\n        return ret\n\n    # List of updates to download\n    download = salt.utils.win_update.Updates()\n    for item in install_list.updates:\n        if not salt.utils.data.is_true(item.IsDownloaded):\n            download.updates.Add(item)\n\n    # List of updates to install\n    install = salt.utils.win_update.Updates()\n    installed_updates = []\n    for item in install_list.updates:\n        if not salt.utils.data.is_true(item.IsInstalled):\n            install.updates.Add(item)\n        else:\n            installed_updates.extend(\"KB\" + kb for kb in item.KBArticleIDs)\n\n    if install.count() == 0:\n        ret[\"comment\"] = \"Updates already installed: \"\n        ret[\"comment\"] += \"\\n - \".join(installed_updates)\n        return ret\n\n    # Return comment of changes if test.\n    if __opts__[\"test\"]:\n        ret[\"result\"] = None\n        ret[\"comment\"] = \"Updates will be installed:\"\n        for update in install.updates:\n            ret[\"comment\"] += \"\\n\"\n            ret[\"comment\"] += \": \".join([update.Identity.UpdateID, update.Title])\n        return ret\n\n    # Download updates\n    wua.download(download)\n\n    # Install updates\n    wua.install(install)\n\n    # Refresh windows update info\n    wua.refresh()\n    post_info = wua.updates().list()\n\n    # Verify the installation\n    for item in install.list():\n        if not salt.utils.data.is_true(post_info[item][\"Installed\"]):\n            ret[\"changes\"][\"failed\"] = {\n                item: {\n                    \"Title\": post_info[item][\"Title\"],\n                    \"KBs\": post_info[item][\"KBs\"],\n                }\n            }\n            ret[\"result\"] = False\n        else:\n            ret[\"changes\"][\"installed\"] = {\n                item: {\n                    \"Title\": post_info[item][\"Title\"],\n                    \"NeedsReboot\": post_info[item][\"NeedsReboot\"],\n                    \"KBs\": post_info[item][\"KBs\"],\n                }\n            }\n\n    if ret[\"changes\"].get(\"failed\", False):\n        ret[\"comment\"] = \"Updates failed\"\n    else:\n        ret[\"comment\"] = \"Updates installed successfully\"\n\n    return ret\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 699,
        "n_words": 215,
        "vocab_size": 114,
        "complexity": 15,
        "nloc": 59,
        "token_counts": 441,
        "n_ast_nodes": 772,
        "n_identifiers": 37,
        "d_id": 54320,
        "documentation": {
            "docstring": "\n    Ensure Microsoft Updates are installed. Updates will be downloaded if\n    needed.\n\n    Args:\n\n        name (str):\n            The identifier of a single update to install.\n\n        updates (list):\n            A list of identifiers for updates to be installed. Overrides\n            ``name``. Default is None.\n\n    .. note:: Identifiers can be the GUID, the KB number, or any part of the\n       Title of the Microsoft update. GUIDs and KBs are the preferred method\n       to ensure you're installing the correct update.\n\n    .. warning:: Using a partial KB number or a partial Title could result in\n       more than one update being installed.\n\n    Returns:\n        dict: A dictionary containing the results of the update\n\n    CLI Example:\n\n    .. code-block:: yaml\n\n        # using a GUID\n        install_update:\n          wua.installed:\n            - name: 28cf1b09-2b1a-458c-9bd1-971d1b26b211\n\n        # using a KB\n        install_update:\n          wua.installed:\n            - name: KB3194343\n\n        # using the full Title\n        install_update:\n          wua.installed:\n            - name: Security Update for Adobe Flash Player for Windows 10 Version 1607 (for x64-based Systems) (KB3194343)\n\n        # Install multiple updates\n        install_updates:\n          wua.installed:\n            - updates:\n              - KB3194343\n              - 28cf1b09-2b1a-458c-9bd1-971d1b26b211\n    ",
            "n_words": 161,
            "vocab_size": 101,
            "n_whitespaces": 423,
            "language": "en"
        }
    },
    {
        "id": 22160,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/requests/utils.py",
        "file_name": "utils.py",
        "fun_name": "unquote_header_value",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def unquote_header_value(value, is_filename=False):\n    r\n    if value and value[0] == value[-1] == '\"':\n        # this is not the real unquoting, but fixing this so that the\n        # RFC is met will result in bugs with internet explorer and\n        # probably some other browsers as well.  IE for example is\n        # uploading files with \"C:\\foo\\bar.txt\" as filename\n        value = value[1:-1]\n\n        # if this is a filename and the starting characters look like\n        # a UNC path, then just return the value without quotes.  Using the\n        # replace sequence below on a UNC path has the effect of turning\n        # the leading double slash into a single slash and then\n        # _fix_ie_filename() doesn't work correctly.  See #458.\n        if not is_filename or value[:2] != \"\\\\\\\\\":\n            return value.replace(\"\\\\\\\\\", \"\\\\\").replace('\\\\\"', '\"')\n    return value\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 226,
        "n_words": 127,
        "vocab_size": 87,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 66,
        "n_ast_nodes": 127,
        "n_identifiers": 4,
        "d_id": 4230,
        "documentation": {
            "docstring": "Unquotes a header value.  (Reversal of :func:`quote_header_value`).\n    This does not use the real unquoting but what browsers are actually\n    using for quoting.\n\n    :param value: the header value to unquote.\n    :rtype: str\n    ",
            "n_words": 31,
            "vocab_size": 29,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 138636,
        "commit_id": "fc1cd89020ca1362951a9af301547b4890fb93ae",
        "repo": "ray",
        "path": "python/ray/tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "create_ray_logs_for_failed_test",
        "commit_message": "[ci] Add short failing test summary for pytests (#24104)\n\nIt is sometimes hard to find all failing tests in buildkite output logs - even filtering for \"FAILED\" is cumbersome as the output can be overloaded. This PR adds a small utility to add a short summary log in a separate output section at the end of the buildkite job.\r\n\r\nThe only shared directory between the Buildkite host machine and the test docker container is `/tmp/artifacts:/artifact-mount`. Thus, we write the summary file to this directory, and delete it before actually uploading it as an artifact in the `post-commands` hook.",
        "code": "def create_ray_logs_for_failed_test(rep):\n    \n\n    # We temporarily restrict to Linux until we have artifact dirs\n    # for Windows and Mac\n    if platform.system() != \"Linux\":\n        return\n\n    # Only archive failed tests after the \"call\" phase of the test\n    if rep.when != \"call\" or not rep.failed:\n        return\n\n    # Get dir to write zipped logs to\n    archive_dir = os.environ.get(\"RAY_TEST_FAILURE_LOGS_ARCHIVE_DIR\")\n\n    if not archive_dir:\n        return\n\n    if not os.path.exists(archive_dir):\n        os.makedirs(archive_dir)\n\n    # Get logs dir from the latest ray session\n    tmp_dir = gettempdir()\n    logs_dir = os.path.join(tmp_dir, \"ray\", \"session_latest\", \"logs\")\n\n    if not os.path.exists(logs_dir):\n        return\n\n    # Write zipped logs to logs archive dir\n    test_name = rep.nodeid.replace(os.sep, \"::\")\n    output_file = os.path.join(archive_dir, f\"{test_name}_{time.time():.4f}\")\n    shutil.make_archive(output_file, \"zip\", logs_dir)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 192,
        "n_words": 103,
        "vocab_size": 69,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 131,
        "n_ast_nodes": 249,
        "n_identifiers": 25,
        "d_id": 31492,
        "documentation": {
            "docstring": "Creates artifact zip of /tmp/ray/session_latest/logs for failed tests",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 69113,
        "commit_id": "9baa2229761c5415f29646a1a5bed4a3f4981e05",
        "repo": "erpnext",
        "path": "erpnext/controllers/queries.py",
        "file_name": "queries.py",
        "fun_name": "get_batch_no",
        "commit_message": "fix: specify allowed doctype in queries (#31761)",
        "code": "def get_batch_no(doctype, txt, searchfield, start, page_len, filters):\n\tdoctype = \"Batch\"\n\tcond = \"\"\n\tif filters.get(\"posting_date\"):\n\t\tcond = \"and (batch.expiry_date is null or batch.expiry_date >= %(posting_date)s)\"\n\n\tbatch_nos = None\n\targs = {\n\t\t\"item_code\": filters.get(\"item_code\"),\n\t\t\"warehouse\": filters.get(\"warehouse\"),\n\t\t\"posting_date\": filters.get(\"posting_date\"),\n\t\t\"txt\": \"%{0}%\".format(txt),\n\t\t\"start\": start,\n\t\t\"page_len\": page_len,\n\t}\n\n\thaving_clause = \"having sum(sle.actual_qty) > 0\"\n\tif filters.get(\"is_return\"):\n\t\thaving_clause = \"\"\n\n\tmeta = frappe.get_meta(doctype, cached=True)\n\tsearchfields = meta.get_search_fields()\n\n\tsearch_columns = \"\"\n\tsearch_cond = \"\"\n\n\tif searchfields:\n\t\tsearch_columns = \", \" + \", \".join(searchfields)\n\t\tsearch_cond = \" or \" + \" or \".join([field + \" like %(txt)s\" for field in searchfields])\n\n\tif args.get(\"warehouse\"):\n\t\tsearchfields = [\"batch.\" + field for field in searchfields]\n\t\tif searchfields:\n\t\t\tsearch_columns = \", \" + \", \".join(searchfields)\n\t\t\tsearch_cond = \" or \" + \" or \".join([field + \" like %(txt)s\" for field in searchfields])\n\n\t\tbatch_nos = frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tsearch_columns=search_columns,\n\t\t\t\tcond=cond,\n\t\t\t\tmatch_conditions=get_match_cond(doctype),\n\t\t\t\thaving_clause=having_clause,\n\t\t\t\tsearch_cond=search_cond,\n\t\t\t),\n\t\t\targs,\n\t\t)\n\n\t\treturn batch_nos\n\telse:\n\t\treturn frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tcond,\n\t\t\t\tsearch_columns=search_columns,\n\t\t\t\tsearch_cond=search_cond,\n\t\t\t\tmatch_conditions=get_match_cond(doctype),\n\t\t\t),\n\t\t\targs,\n\t\t)\n\n\n@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 106,
        "n_words": 158,
        "vocab_size": 80,
        "complexity": 9,
        "nloc": 83,
        "token_counts": 280,
        "n_ast_nodes": 501,
        "n_identifiers": 29,
        "d_id": 14981,
        "documentation": {
            "docstring": "select sle.batch_no, round(sum(sle.actual_qty),2), sle.stock_uom,\n\t\t\t\tconcat('MFG-',batch.manufacturing_date), concat('EXP-',batch.expiry_date)\n\t\t\t\t{search_columns}\n\t\t\tfrom `tabStock Ledger Entry` sle\n\t\t\t\tINNER JOIN `tabBatch` batch on sle.batch_no = batch.name\n\t\t\twhere\n\t\t\t\tbatch.disabled = 0\n\t\t\t\tand sle.is_cancelled = 0\n\t\t\t\tand sle.item_code = %(item_code)s\n\t\t\t\tand sle.warehouse = %(warehouse)s\n\t\t\t\tand (sle.batch_no like %(txt)s\n\t\t\t\tor batch.expiry_date like %(txt)s\n\t\t\t\tor batch.manufacturing_date like %(txt)s\n\t\t\t\t{search_cond})\n\t\t\t\tand batch.docstatus < 2\n\t\t\t\t{cond}\n\t\t\t\t{match_conditions}\n\t\t\tgroup by batch_no {having_clause}\n\t\t\torder by batch.expiry_date, sle.batch_no desc\n\t\t\tlimit %(page_len)s offset %(start)sselect name, concat('MFG-', manufacturing_date), concat('EXP-',expiry_date)\n\t\t\t{search_columns}\n\t\t\tfrom `tabBatch` batch\n\t\t\twhere batch.disabled = 0\n\t\t\tand item = %(item_code)s\n\t\t\tand (name like %(txt)s\n\t\t\tor expiry_date like %(txt)s\n\t\t\tor manufacturing_date like %(txt)s\n\t\t\t{search_cond})\n\t\t\tand docstatus < 2\n\t\t\t{0}\n\t\t\t{match_conditions}\n\n\t\t\torder by expiry_date, name desc\n\t\t\tlimit %(page_len)s offset %(start)s",
            "n_words": 112,
            "vocab_size": 65,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 67735,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/doctype/serial_no/serial_no.py",
        "file_name": "serial_no.py",
        "fun_name": "allow_serial_nos_with_different_item",
        "commit_message": "style: format code with black",
        "code": "def allow_serial_nos_with_different_item(sle_serial_no, sle):\n\t\n\tallow_serial_nos = False\n\tif sle.voucher_type == \"Stock Entry\" and cint(sle.actual_qty) > 0:\n\t\tstock_entry = frappe.get_cached_doc(\"Stock Entry\", sle.voucher_no)\n\t\tif stock_entry.purpose in (\"Repack\", \"Manufacture\"):\n\t\t\tfor d in stock_entry.get(\"items\"):\n\t\t\t\tif d.serial_no and (d.s_warehouse if not sle.is_cancelled else d.t_warehouse):\n\t\t\t\t\tserial_nos = get_serial_nos(d.serial_no)\n\t\t\t\t\tif sle_serial_no in serial_nos:\n\t\t\t\t\t\tallow_serial_nos = True\n\n\treturn allow_serial_nos\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 39,
        "n_words": 50,
        "vocab_size": 38,
        "complexity": 9,
        "nloc": 11,
        "token_counts": 98,
        "n_ast_nodes": 163,
        "n_identifiers": 20,
        "d_id": 14610,
        "documentation": {
            "docstring": "\n\tAllows same serial nos for raw materials and finished goods\n\tin Manufacture / Repack type Stock Entry\n\t",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 268629,
        "commit_id": "9545f2e0deae73d142047f02b499940b07b700aa",
        "repo": "ansible",
        "path": "hacking/build_library/build_ansible/command_plugins/docs_build.py",
        "file_name": "docs_build.py",
        "fun_name": "find_latest_deps_file",
        "commit_message": "stable docs build: do not use YAML parsing/serialization for .deps files (#79233)\n\n* Do not use YAML parsing/serialization for .deps files.\r\n\r\n* Prevent crash.",
        "code": "def find_latest_deps_file(build_data_working, ansible_version):\n    \n    # imports here so that they don't cause unnecessary deps for all of the plugins\n    from packaging.version import Version\n\n    data_dir = os.path.join(build_data_working, ansible_version)\n    deps_files = glob.glob(os.path.join(data_dir, '*.deps'))\n    if not deps_files:\n        raise Exception('No deps files exist for version {0}'.format(ansible_version))\n\n    # Find the latest version of the deps file for this major version\n    latest = None\n    latest_ver = Version('0')\n    for filename in deps_files:\n        deps_data = parse_deps_file(filename)\n        new_version = Version(deps_data['_ansible_version'])\n        if new_version > latest_ver:\n            latest_ver = new_version\n            latest = filename\n\n    if latest is None:\n        raise NoSuchFile('Could not find an ansible deps file in {0}'.format(data_dir))\n\n    return latest\n\n\n#\n# Subcommand core\n#\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 191,
        "n_words": 101,
        "vocab_size": 64,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 114,
        "n_ast_nodes": 197,
        "n_identifiers": 21,
        "d_id": 79570,
        "documentation": {
            "docstring": "Find the most recent ansible deps file for the given ansible major version.",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 225577,
        "commit_id": "43201769f044e2f1bcd594a6e5c251903cf14c49",
        "repo": "albumentations",
        "path": "albumentations/augmentations/functional.py",
        "file_name": "functional.py",
        "fun_name": "move_tone_curve",
        "commit_message": "Upgrade black to 22.3.0 (#1181)\n\n* Upgrade black to 22.3.0\r\n\r\n* Remove sphinx docs build",
        "code": "def move_tone_curve(img, low_y, high_y):\n    \n    input_dtype = img.dtype\n\n    if low_y < 0 or low_y > 1:\n        raise ValueError(\"low_shift must be in range [0, 1]\")\n    if high_y < 0 or high_y > 1:\n        raise ValueError(\"high_shift must be in range [0, 1]\")\n\n    if input_dtype != np.uint8:\n        raise ValueError(\"Unsupported image type {}\".format(input_dtype))\n\n    t = np.linspace(0.0, 1.0, 256)\n\n    # Defines responze of a four-point bezier curve",
        "url": "https://github.com/albumentations-team/albumentations.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 103,
        "n_words": 61,
        "vocab_size": 42,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 126,
        "n_ast_nodes": 120,
        "n_identifiers": 12,
        "d_id": 57473,
        "documentation": {
            "docstring": "Rescales the relationship between bright and dark areas of the image by manipulating its tone curve.\n\n    Args:\n        img (numpy.ndarray): RGB or grayscale image.\n        low_y (float): y-position of a Bezier control point used\n            to adjust the tone curve, must be in range [0, 1]\n        high_y (float): y-position of a Bezier control point used\n            to adjust image tone curve, must be in range [0, 1]\n    ",
            "n_words": 63,
            "vocab_size": 40,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 169112,
        "commit_id": "d1485e76b7c48316c0d54f1a4df26c4467792670",
        "repo": "pandas",
        "path": "pandas/core/apply.py",
        "file_name": "apply.py",
        "fun_name": "apply_str",
        "commit_message": "CLN: Refactor groupby._make_wrapper (#48400)\n\n* CLN: Refactor groupby._make_wrapper\r\n\r\n* Remove type: ignore\r\n\r\n* Revert behavior change for corrwith; fix skew and mad\r\n\r\n* Add docstring",
        "code": "def apply_str(self) -> DataFrame | Series:\n        \n        # Caller is responsible for checking isinstance(self.f, str)\n        f = cast(str, self.f)\n\n        obj = self.obj\n\n        # Support for `frame.transform('method')`\n        # Some methods (shift, etc.) require the axis argument, others\n        # don't, so inspect and insert if necessary.\n        func = getattr(obj, f, None)\n        if callable(func):\n            sig = inspect.getfullargspec(func)\n            if self.axis != 0 and (\n                \"axis\" not in sig.args or f in (\"corrwith\", \"mad\", \"skew\")\n            ):\n                raise ValueError(f\"Operation {f} does not support axis=1\")\n            elif \"axis\" in sig.args:\n                self.kwargs[\"axis\"] = self.axis\n        return self._try_aggregate_string_function(obj, f, *self.args, **self.kwargs)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 248,
        "n_words": 89,
        "vocab_size": 71,
        "complexity": 6,
        "nloc": 20,
        "token_counts": 117,
        "n_ast_nodes": 199,
        "n_identifiers": 19,
        "d_id": 40394,
        "documentation": {
            "docstring": "\n        Compute apply in case of a string.\n\n        Returns\n        -------\n        result: Series or DataFrame\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 177600,
        "commit_id": "074af782e6f351c711f18d8ad6a05aa4f632339c",
        "repo": "label-studio",
        "path": "label_studio/tasks/models.py",
        "file_name": "models.py",
        "fun_name": "completed_annotations",
        "commit_message": "feat: DEV-469: Skip queue (#1693)\n\n* DEV-469 Skip queue project setting\r\n\r\n* DEV-469 review fixes\r\n\r\n* Merge migrations (DEV-469)\r\n\r\n* Update requirements-test.txt\r\n\r\n* Update requirements-test.txt\r\n\r\n* Update test_exception.py\r\n\r\n* Revert \"Update test_exception.py\"\r\n\r\nThis reverts commit b9c686c9bacaf298bafe3a207352cc5260fef737.\r\n\r\n* Revert \"Update requirements-test.txt\"\r\n\r\nThis reverts commit 3704d29978761089bcd008506f9e1c30a162bb3a.\r\n\r\n* Revert \"Update requirements-test.txt\"\r\n\r\nThis reverts commit 50273847ae2872b31bccc376d04a3afff0efcf21.\r\n\r\n* Recalc is_labeled after skip_queue change (DEV-469)\r\n\r\n* Fix migrations (DEV-469)\r\n\r\nCo-authored-by: Max Tkachenko <makseq@gmail.com>\r\nCo-authored-by: niklub <lubimov.nicolas@gmail.com>\r\nCo-authored-by: nik <nik@heartex.net>",
        "code": "def completed_annotations(self):\n        \n        if self.project.skip_queue == self.project.SkipQueue.IGNORE_SKIPPED:\n            return self.annotations.filter(Q(ground_truth=False))\n        else:\n            return self.annotations.filter(Q_finished_annotations)\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 54,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 76,
        "n_identifiers": 11,
        "d_id": 42458,
        "documentation": {
            "docstring": "Annotations that we take into account when set completed status to the task",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 127348,
        "commit_id": "4c970cc88247f7cfa7351297b8b5050f2372742e",
        "repo": "ray",
        "path": "python/ray/serve/tests/test_gradio_visualization.py",
        "file_name": "test_gradio_visualization.py",
        "fun_name": "test_get_result_correctness",
        "commit_message": "[serve] Visualize Deployment Graph with Gradio (#27897)",
        "code": "async def test_get_result_correctness(graph1):\n    \n    (_, _, _, dag) = graph1\n\n    handle = serve.run(DAGDriver.bind(dag))\n    visualizer = GraphVisualizer()\n    visualizer.visualize_with_gradio(handle, _launch=False)\n\n    await visualizer._send_request(random.randint(0, 100), 1, 2)\n    values = await asyncio.gather(\n        *[\n            (visualizer._get_result(node.get_stable_uuid()))\n            for node in visualizer.node_to_block\n        ]\n    )\n    assert {1, 2} <= set(values)\n\n\n@pytest.mark.asyncio",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.asyncio",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 102,
        "n_words": 40,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 103,
        "n_ast_nodes": 171,
        "n_identifiers": 26,
        "d_id": 28422,
        "documentation": {
            "docstring": "Tests correctness: that after running _send_request(), _get_result() in\n    GraphVisualizer correctly returns object refs to the submitted tasks.\n    ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 249543,
        "commit_id": "ac1a31740b6d0dfda4d57a25762aaddfde981caf",
        "repo": "synapse",
        "path": "tests/storage/test_event_federation.py",
        "file_name": "test_event_federation.py",
        "fun_name": "test_get_backfill_points_in_room",
        "commit_message": "Only try to backfill event if we haven't tried before recently (#13635)\n\nOnly try to backfill event if we haven't tried before recently (exponential backoff). No need to keep trying the same backfill point that fails over and over.\r\n\r\nFix https://github.com/matrix-org/synapse/issues/13622\r\nFix https://github.com/matrix-org/synapse/issues/8451\r\n\r\nFollow-up to https://github.com/matrix-org/synapse/pull/13589\r\n\r\nPart of https://github.com/matrix-org/synapse/issues/13356",
        "code": "def test_get_backfill_points_in_room(self):\n        \n        setup_info = self._setup_room_for_backfill_tests()\n        room_id = setup_info.room_id\n\n        backfill_points = self.get_success(\n            self.store.get_backfill_points_in_room(room_id)\n        )\n        backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points]\n        self.assertListEqual(\n            backfill_event_ids, [\"b6\", \"b5\", \"b4\", \"2\", \"b3\", \"b2\", \"b1\"]\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 108,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 67,
        "n_ast_nodes": 115,
        "n_identifiers": 12,
        "d_id": 72983,
        "documentation": {
            "docstring": "\n        Test to make sure we get some backfill points\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 243959,
        "commit_id": "c9e1906f00505621b0247ab364feb0ca862fa98c",
        "repo": "mmdetection",
        "path": "mmdet/datasets/pipelines/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "_mixup_transform",
        "commit_message": "[Fix] Fix MixUp transform filter boxes failing case. Added test case (#7080)",
        "code": "def _mixup_transform(self, results):\n        \n\n        assert 'mix_results' in results\n        assert len(\n            results['mix_results']) == 1, 'MixUp only support 2 images now !'\n\n        if results['mix_results'][0]['gt_bboxes'].shape[0] == 0:\n            # empty bbox\n            return results\n\n        retrieve_results = results['mix_results'][0]\n        retrieve_img = retrieve_results['img']\n\n        jit_factor = random.uniform(*self.ratio_range)\n        is_filp = random.uniform(0, 1) > self.flip_ratio\n\n        if len(retrieve_img.shape) == 3:\n            out_img = np.ones(\n                (self.dynamic_scale[0], self.dynamic_scale[1], 3),\n                dtype=retrieve_img.dtype) * self.pad_val\n        else:\n            out_img = np.ones(\n                self.dynamic_scale, dtype=retrieve_img.dtype) * self.pad_val\n\n        # 1. keep_ratio resize\n        scale_ratio = min(self.dynamic_scale[0] / retrieve_img.shape[0],\n                          self.dynamic_scale[1] / retrieve_img.shape[1])\n        retrieve_img = mmcv.imresize(\n            retrieve_img, (int(retrieve_img.shape[1] * scale_ratio),\n                           int(retrieve_img.shape[0] * scale_ratio)))\n\n        # 2. paste\n        out_img[:retrieve_img.shape[0], :retrieve_img.shape[1]] = retrieve_img\n\n        # 3. scale jit\n        scale_ratio *= jit_factor\n        out_img = mmcv.imresize(out_img, (int(out_img.shape[1] * jit_factor),\n                                          int(out_img.shape[0] * jit_factor)))\n\n        # 4. flip\n        if is_filp:\n            out_img = out_img[:, ::-1, :]\n\n        # 5. random crop\n        ori_img = results['img']\n        origin_h, origin_w = out_img.shape[:2]\n        target_h, target_w = ori_img.shape[:2]\n        padded_img = np.zeros(\n            (max(origin_h, target_h), max(origin_w,\n                                          target_w), 3)).astype(np.uint8)\n        padded_img[:origin_h, :origin_w] = out_img\n\n        x_offset, y_offset = 0, 0\n        if padded_img.shape[0] > target_h:\n            y_offset = random.randint(0, padded_img.shape[0] - target_h)\n        if padded_img.shape[1] > target_w:\n            x_offset = random.randint(0, padded_img.shape[1] - target_w)\n        padded_cropped_img = padded_img[y_offset:y_offset + target_h,\n                                        x_offset:x_offset + target_w]\n\n        # 6. adjust bbox\n        retrieve_gt_bboxes = retrieve_results['gt_bboxes']\n        retrieve_gt_bboxes[:, 0::2] = retrieve_gt_bboxes[:, 0::2] * scale_ratio\n        retrieve_gt_bboxes[:, 1::2] = retrieve_gt_bboxes[:, 1::2] * scale_ratio\n        if self.bbox_clip_border:\n            retrieve_gt_bboxes[:, 0::2] = np.clip(retrieve_gt_bboxes[:, 0::2],\n                                                  0, origin_w)\n            retrieve_gt_bboxes[:, 1::2] = np.clip(retrieve_gt_bboxes[:, 1::2],\n                                                  0, origin_h)\n\n        if is_filp:\n            retrieve_gt_bboxes[:, 0::2] = (\n                origin_w - retrieve_gt_bboxes[:, 0::2][:, ::-1])\n\n        # 7. filter\n        cp_retrieve_gt_bboxes = retrieve_gt_bboxes.copy()\n        cp_retrieve_gt_bboxes[:, 0::2] = \\\n            cp_retrieve_gt_bboxes[:, 0::2] - x_offset\n        cp_retrieve_gt_bboxes[:, 1::2] = \\\n            cp_retrieve_gt_bboxes[:, 1::2] - y_offset\n        if self.bbox_clip_border:\n            cp_retrieve_gt_bboxes[:, 0::2] = np.clip(\n                cp_retrieve_gt_bboxes[:, 0::2], 0, target_w)\n            cp_retrieve_gt_bboxes[:, 1::2] = np.clip(\n                cp_retrieve_gt_bboxes[:, 1::2], 0, target_h)\n\n        # 8. mix up\n        ori_img = ori_img.astype(np.float32)\n        mixup_img = 0.5 * ori_img + 0.5 * padded_cropped_img.astype(np.float32)\n\n        retrieve_gt_labels = retrieve_results['gt_labels']\n        if not self.skip_filter:\n            keep_list = self._filter_box_candidates(retrieve_gt_bboxes.T,\n                                                    cp_retrieve_gt_bboxes.T)\n\n            retrieve_gt_labels = retrieve_gt_labels[keep_list]\n            cp_retrieve_gt_bboxes = cp_retrieve_gt_bboxes[keep_list]\n\n        mixup_gt_bboxes = np.concatenate(\n            (results['gt_bboxes'], cp_retrieve_gt_bboxes), axis=0)\n        mixup_gt_labels = np.concatenate(\n            (results['gt_labels'], retrieve_gt_labels), axis=0)\n\n        # remove outside bbox\n        inside_inds = find_inside_bboxes(mixup_gt_bboxes, target_h, target_w)\n        mixup_gt_bboxes = mixup_gt_bboxes[inside_inds]\n        mixup_gt_labels = mixup_gt_labels[inside_inds]\n\n        results['img'] = mixup_img.astype(np.uint8)\n        results['img_shape'] = mixup_img.shape\n        results['gt_bboxes'] = mixup_gt_bboxes\n        results['gt_labels'] = mixup_gt_labels\n\n        return results\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1392,
        "n_words": 340,
        "vocab_size": 179,
        "complexity": 10,
        "nloc": 83,
        "token_counts": 835,
        "n_ast_nodes": 1292,
        "n_identifiers": 56,
        "d_id": 70162,
        "documentation": {
            "docstring": "MixUp transform function.\n\n        Args:\n            results (dict): Result dict.\n\n        Returns:\n            dict: Updated result dict.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 215547,
        "commit_id": "70972c8016ff5d6fbdd7f83776077b0936f60dea",
        "repo": "salt",
        "path": "salt/crypt.py",
        "file_name": "crypt.py",
        "fun_name": "authenticate",
        "commit_message": "Use salt.channel.client instead of salt.transport.client",
        "code": "def authenticate(self, _=None):  # TODO: remove unused var\n        \n        acceptance_wait_time = self.opts[\"acceptance_wait_time\"]\n        acceptance_wait_time_max = self.opts[\"acceptance_wait_time_max\"]\n        if not acceptance_wait_time_max:\n            acceptance_wait_time_max = acceptance_wait_time\n        with salt.channel.client.ReqChannel.factory(\n            self.opts, crypt=\"clear\"\n        ) as channel:\n            while True:\n                creds = self.sign_in(channel=channel)\n                if creds == \"retry\":\n                    if self.opts.get(\"caller\"):\n                        # We have a list of masters, so we should break\n                        # and try the next one in the list.\n                        if self.opts.get(\"local_masters\", None):\n                            error = SaltClientError(\n                                \"Minion failed to authenticate\"\n                                \" with the master, has the \"\n                                \"minion key been accepted?\"\n                            )\n                            break\n                        else:\n                            print(\n                                \"Minion failed to authenticate with the master, \"\n                                \"has the minion key been accepted?\"\n                            )\n                            sys.exit(2)\n                    if acceptance_wait_time:\n                        log.info(\n                            \"Waiting %s seconds before retry.\", acceptance_wait_time\n                        )\n                        time.sleep(acceptance_wait_time)\n                    if acceptance_wait_time < acceptance_wait_time_max:\n                        acceptance_wait_time += acceptance_wait_time\n                        log.debug(\n                            \"Authentication wait time is %s\", acceptance_wait_time\n                        )\n                    continue\n                break\n            self._creds = creds\n            self._crypticle = Crypticle(self.opts, creds[\"aes\"])\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 954,
        "n_words": 134,
        "vocab_size": 89,
        "complexity": 8,
        "nloc": 39,
        "token_counts": 172,
        "n_ast_nodes": 308,
        "n_identifiers": 28,
        "d_id": 54016,
        "documentation": {
            "docstring": "\n        Authenticate with the master, this method breaks the functional\n        paradigm, it will update the master information from a fresh sign\n        in, signing in can occur as often as needed to keep up with the\n        revolving master AES key.\n\n        :rtype: Crypticle\n        :returns: A crypticle used for encryption operations\n        ",
            "n_words": 47,
            "vocab_size": 41,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 70730,
        "commit_id": "18c4d7c81356dbd5c4503db2ea24b21492512317",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_menu.py",
        "file_name": "test_menu.py",
        "fun_name": "test_not_collapsed_with_legacy",
        "commit_message": "Update Wagtail test cases to match slim sidebar capabilities and implementation details",
        "code": "def test_not_collapsed_with_legacy(self):\n        \n        # Sidebar should not be collapsed because the feature flag is not enabled\n        self.client.cookies['wagtail_sidebar_collapsed'] = '1'\n        response = self.client.get(reverse('wagtailadmin_home'))\n        self.assertNotContains(response, 'sidebar-collapsed')\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 58,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 37,
        "n_ast_nodes": 70,
        "n_identifiers": 8,
        "d_id": 15545,
        "documentation": {
            "docstring": "Sidebar should only remember its collapsed state with the slim implementation.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 276832,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/generic_utils.py",
        "file_name": "generic_utils.py",
        "fun_name": "default",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def default(method):\n    \n    method._is_default = True  # pylint: disable=protected-access\n    return method\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 20,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 13,
        "n_ast_nodes": 25,
        "n_identifiers": 3,
        "d_id": 81746,
        "documentation": {
            "docstring": "Decorates a method to detect overrides in subclasses.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 218759,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/lib2to3/patcomp.py",
        "file_name": "patcomp.py",
        "fun_name": "tokenize_wrapper",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def tokenize_wrapper(input):\n    \n    skip = {token.NEWLINE, token.INDENT, token.DEDENT}\n    tokens = tokenize.generate_tokens(io.StringIO(input).readline)\n    for quintuple in tokens:\n        type, value, start, end, line_text = quintuple\n        if type not in skip:\n            yield quintuple\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 65,
        "n_words": 28,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 60,
        "n_ast_nodes": 92,
        "n_identifiers": 19,
        "d_id": 55459,
        "documentation": {
            "docstring": "Tokenizes a string suppressing significant whitespace.",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 5,
            "language": "en"
        }
    },
    {
        "id": 215928,
        "commit_id": "a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857",
        "repo": "salt",
        "path": "tests/pytests/unit/modules/test_win_certutil.py",
        "file_name": "test_win_certutil.py",
        "fun_name": "test_get_serials",
        "commit_message": "Add tests, fix state module",
        "code": "def test_get_serials():\n    \n    expected = [\n        \"180720d39cd2db3244ba037417241e90\",\n        \"1768ac4e5b72bf1d0df0df118b34b959\",\n    ]\n    mock = MagicMock(\n        return_value=(\n            \"CertInfo\\r\\n\"\n            \"================ Certificate 0 ================\\r\\n\"\n            \"Serial Number: 180720d39cd2db3244ba037417241e90\\r\\n\"\n            \"OtherStuff\\r\\n\"\n            \"\\r\\n\"\n            \"================ Certificate 1 ================\\r\\n\"\n            \"Serial Number: 1768ac4e5b72bf1d0df0df118b34b959\\r\\n\"\n            \"OtherStuff\"\n        )\n    )\n    with patch.dict(certutil.__salt__, {\"cmd.run\": mock}):\n        out = certutil.get_stored_cert_serials(\"TrustedPublisher\")\n        mock.assert_called_once_with('certutil.exe -store \"TrustedPublisher\"')\n        assert expected == out\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 201,
        "n_words": 46,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 64,
        "n_ast_nodes": 142,
        "n_identifiers": 12,
        "d_id": 54255,
        "documentation": {
            "docstring": "\n    Test getting all the serial numbers from a store\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 154121,
        "commit_id": "8864bc197974da6d8cda2de2f35ca31d561be1cc",
        "repo": "modin",
        "path": "modin/core/io/column_stores/parquet_dispatcher.py",
        "file_name": "parquet_dispatcher.py",
        "fun_name": "build_partition",
        "commit_message": "PERF-#4305: Parallelize `read_parquet` over row groups (#4700)\n\nCo-authored-by: mvashishtha <mahesh@ponder.io>",
        "code": "def build_partition(cls, partition_ids, column_widths):\n        \n        return np.array(\n            [\n                [\n                    cls.frame_partition_cls(\n                        part_id[0],\n                        length=part_id[2],\n                        width=col_width,\n                    )\n                    for part_id, col_width in zip(part_ids, column_widths)\n                ]\n                for part_ids in partition_ids\n            ]\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 240,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 56,
        "n_ast_nodes": 81,
        "n_identifiers": 13,
        "d_id": 35794,
        "documentation": {
            "docstring": "\n        Build array with partitions of `cls.frame_partition_cls` class.\n\n        Parameters\n        ----------\n        partition_ids : list\n            Array with references to the partitions data.\n        column_widths : list\n            Number of columns in each partition.\n\n        Returns\n        -------\n        np.ndarray\n            array with shape equals to the shape of `partition_ids` and\n            filed with partition objects.\n\n        Notes\n        -----\n        The second level of partitions_ids contains a list of object references\n        for each read call:\n        partition_ids[i][j] -> [ObjectRef(df), ObjectRef(df.index), ObjectRef(len(df))].\n        ",
            "n_words": 67,
            "vocab_size": 50,
            "n_whitespaces": 210,
            "language": "en"
        }
    },
    {
        "id": 108011,
        "commit_id": "075ff0952896f44d7d0b0b3318f0978ae53f84d7",
        "repo": "matplotlib",
        "path": "lib/matplotlib/patches.py",
        "file_name": "patches.py",
        "fun_name": "__new__",
        "commit_message": "Small style fixes.",
        "code": "def __new__(cls, stylename, **kwargs):\n        \n        # The \"class\" should have the _style_list attribute, which is a mapping\n        # of style names to style classes.\n        _list = stylename.replace(\" \", \"\").split(\",\")\n        _name = _list[0].lower()\n        try:\n            _cls = cls._style_list[_name]\n        except KeyError as err:\n            raise ValueError(f\"Unknown style: {stylename}\") from err\n        try:\n            _args_pair = [cs.split(\"=\") for cs in _list[1:]]\n            _args = {k: float(v) for k, v in _args_pair}\n        except ValueError as err:\n            raise ValueError(f\"Incorrect style argument: {stylename}\") from err\n        return _cls(**{**_args, **kwargs})\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 201,
        "n_words": 76,
        "vocab_size": 59,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 120,
        "n_ast_nodes": 208,
        "n_identifiers": 20,
        "d_id": 23015,
        "documentation": {
            "docstring": "Return the instance of the subclass with the given style name.",
            "n_words": 11,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 244083,
        "commit_id": "c576e5d570bf64a99e2c6817ed7b5c0084a44a55",
        "repo": "mmdetection",
        "path": "mmdet/models/roi_heads/mask_heads/mask_point_head.py",
        "file_name": "mask_point_head.py",
        "fun_name": "get_roi_rel_points_train",
        "commit_message": "[Enhance] Take point sample related functions out of mask_point_head (#7353)\n\nadd point sample\r\n\r\nreplace function in mask_point_head",
        "code": "def get_roi_rel_points_train(self, mask_pred, labels, cfg):\n        \n        point_coords = get_uncertain_point_coords_with_randomness(\n            mask_pred, labels, cfg.num_points, cfg.oversample_ratio,\n            cfg.importance_sample_ratio)\n        return point_coords\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 58,
        "n_words": 15,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 34,
        "n_ast_nodes": 49,
        "n_identifiers": 10,
        "d_id": 70231,
        "documentation": {
            "docstring": "Get ``num_points`` most uncertain points with random points during\n        train.\n\n        Sample points in [0, 1] x [0, 1] coordinate space based on their\n        uncertainty. The uncertainties are calculated for each point using\n        '_get_uncertainty()' function that takes point's logit prediction as\n        input.\n\n        Args:\n            mask_pred (Tensor): A tensor of shape (num_rois, num_classes,\n                mask_height, mask_width) for class-specific or class-agnostic\n                prediction.\n            labels (list): The ground truth class for each instance.\n            cfg (dict): Training config of point head.\n\n        Returns:\n            point_coords (Tensor): A tensor of shape (num_rois, num_points, 2)\n                that contains the coordinates sampled points.\n        ",
            "n_words": 89,
            "vocab_size": 72,
            "n_whitespaces": 234,
            "language": "en"
        }
    },
    {
        "id": 20001,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/utils/temp_dir.py",
        "file_name": "temp_dir.py",
        "fun_name": "tempdir_registry",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def tempdir_registry() -> Iterator[TempDirectoryTypeRegistry]:\n    \n    global _tempdir_registry\n    old_tempdir_registry = _tempdir_registry\n    _tempdir_registry = TempDirectoryTypeRegistry()\n    try:\n        yield _tempdir_registry\n    finally:\n        _tempdir_registry = old_tempdir_registry\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 51,
        "n_words": 19,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 29,
        "n_ast_nodes": 53,
        "n_identifiers": 5,
        "d_id": 3170,
        "documentation": {
            "docstring": "Provides a scoped global tempdir registry that can be used to dictate\n    whether directories should be deleted.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 39443,
        "commit_id": "1d7341e93d1f03387699fb3c6ae0b6c0e464296f",
        "repo": "recommenders",
        "path": "recommenders/utils/python_utils.py",
        "file_name": "python_utils.py",
        "fun_name": "lexicographers_mutual_information",
        "commit_message": "Add new item similarity metrics for SAR (#1754)\n\n* Add mutual information similarity in SAR\r\n\r\n* Add lexicographers mutual information similarity for SAR\r\n\r\n* Add cosine similarity for SAR\r\n\r\n* Add inclusion index for SAR\r\n\r\n* Typos\r\n\r\n* Change SARSingleNode to SAR\r\n\r\n* Convert item similarity matrix to np.array\r\n\r\n* Update\r\n\r\n* Update SAR tests\r\n\r\n* Remove unused imports\r\n\r\n* Add explanations for new similarity metrics",
        "code": "def lexicographers_mutual_information(cooccurrence):\n    \n\n    with np.errstate(invalid=\"ignore\", divide=\"ignore\"):\n        result = cooccurrence * mutual_information(cooccurrence)\n\n    return np.array(result)\n\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 28,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 7235,
        "documentation": {
            "docstring": "Helper method to calculate the Lexicographers Mutual Information of\n    a matrix of co-occurrences.\n\n    Due to the bias of mutual information for low frequency items,\n    lexicographers mutual information corrects the formula by\n    multiplying it by the co-occurrence frequency.\n\n    Args:\n        cooccurrence (numpy.ndarray): The symmetric matrix of co-occurrences of items.\n\n    Returns:\n        numpy.ndarray: The matrix of lexicographers mutual information between any two items.\n\n    ",
            "n_words": 59,
            "vocab_size": 40,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 109064,
        "commit_id": "b9cdf3e2a68bd3d30ad7233b223f88d37044dab3",
        "repo": "matplotlib",
        "path": "lib/matplotlib/legend.py",
        "file_name": "legend.py",
        "fun_name": "set_title",
        "commit_message": "ENH: add the ability to control label alignment in legends\n\nCo-authored-by: Tim Hoffmann <2836374+timhoffm@users.noreply.github.com>",
        "code": "def set_title(self, title, prop=None):\n        \n        self._legend_title_box._text.set_text(title)\n        if title:\n            self._legend_title_box._text.set_visible(True)\n            self._legend_title_box.set_visible(True)\n        else:\n            self._legend_title_box._text.set_visible(False)\n            self._legend_title_box.set_visible(False)\n\n        if prop is not None:\n            self._legend_title_box._text.set_fontproperties(prop)\n\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 118,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 84,
        "n_ast_nodes": 136,
        "n_identifiers": 10,
        "d_id": 23426,
        "documentation": {
            "docstring": "\n        Set legend title and title style.\n\n        Parameters\n        ----------\n        title : str\n            The legend title.\n\n        prop : `.font_manager.FontProperties` or `str` or `pathlib.Path`\n            The font properties of the legend title.\n            If a `str`, it is interpreted as a fontconfig pattern parsed by\n            `.FontProperties`.  If a `pathlib.Path`, it is interpreted as the\n            absolute path to a font file.\n\n        ",
            "n_words": 55,
            "vocab_size": 37,
            "n_whitespaces": 154,
            "language": "en"
        }
    },
    {
        "id": 150503,
        "commit_id": "87a3115073562e9abc7efd792569020435a01f6e",
        "repo": "freqtrade",
        "path": "freqtrade/freqtradebot.py",
        "file_name": "freqtradebot.py",
        "fun_name": "get_free_open_trades",
        "commit_message": "Add get_open_trade_count() to simplify getting open trade count.",
        "code": "def get_free_open_trades(self) -> int:\n        \n        open_trades = Trade.get_open_trade_count()\n        return max(0, self.config['max_open_trades'] - open_trades)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 29,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 34774,
        "documentation": {
            "docstring": "\n        Return the number of free open trades slots or 0 if\n        max number of open trades reached\n        ",
            "n_words": 17,
            "vocab_size": 13,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 297698,
        "commit_id": "a6ddac9004b7f73633f2019f3b5267e1486756c1",
        "repo": "core",
        "path": "homeassistant/components/isy994/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "native_unit_of_measurement",
        "commit_message": "Use UnitOfTemperature in integrations (i-m) (#84307)",
        "code": "def native_unit_of_measurement(self) -> str | None:\n        \n        raw_units = self.raw_unit_of_measurement\n        # Check if this is a known index pair UOM\n        if isinstance(raw_units, dict) or raw_units in (UOM_ON_OFF, UOM_INDEX):\n            return None\n        if raw_units in (\n            UnitOfTemperature.FAHRENHEIT,\n            UnitOfTemperature.CELSIUS,\n            UOM_DOUBLE_TEMP,\n        ):\n            return self.hass.config.units.temperature_unit\n        return raw_units\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 145,
        "n_words": 41,
        "vocab_size": 33,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 61,
        "n_ast_nodes": 94,
        "n_identifiers": 17,
        "d_id": 96664,
        "documentation": {
            "docstring": "Get the Home Assistant unit of measurement for the device.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 267383,
        "commit_id": "86779cc90376ea70bafa7044b12ce5132409fd63",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/target.py",
        "file_name": "target.py",
        "fun_name": "find_target_completion",
        "commit_message": "ansible-test - Code cleanup.\n\nThis helps prepare for a future pylint upgrade.",
        "code": "def find_target_completion(target_func, prefix, short):  # type: (t.Callable[[], t.Iterable[CompletionTarget]], str, bool) -> t.List[str]\n    \n    try:\n        targets = target_func()\n        matches = list(walk_completion_targets(targets, prefix, short))\n        return matches\n    except Exception as ex:  # pylint: disable=locally-disabled, broad-except\n        return ['%s' % ex]\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 74,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 43,
        "n_ast_nodes": 74,
        "n_identifiers": 10,
        "d_id": 78873,
        "documentation": {
            "docstring": "Return a list of targets from the given target function which match the given prefix.",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 153784,
        "commit_id": "3d4404e9d9a9b2a3327f8aee664a8e71ac1f18b8",
        "repo": "modin",
        "path": "modin/experimental/batch/test/test_pipeline.py",
        "file_name": "test_pipeline.py",
        "fun_name": "test_pipeline_simple",
        "commit_message": "FEAT-#4412: Add Batch Pipeline API to Modin (#4452)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>\r\nSigned-off-by: Rehan Durrani <rehan@ponder.io>",
        "code": "def test_pipeline_simple(self):\n        \n        arr = np.random.randint(0, 1000, (1000, 1000))\n        df = pd.DataFrame(arr)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 6,
        "nloc": 35,
        "token_counts": 257,
        "n_ast_nodes": 51,
        "n_identifiers": 9,
        "d_id": 35608,
        "documentation": {
            "docstring": "Create a simple pipeline and ensure that it runs end to end correctly.",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 196275,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/geometry/point.py",
        "file_name": "point.py",
        "fun_name": "__mul__",
        "commit_message": "Updated import locations",
        "code": "def __mul__(self, factor):\n        \n        factor = sympify(factor)\n        coords = [simplify(x*factor) for x in self.args]\n        return Point(coords, evaluate=False)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 44,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 62,
        "n_identifiers": 10,
        "d_id": 47775,
        "documentation": {
            "docstring": "Multiply point's coordinates by a factor.\n\n        Notes\n        =====\n\n        >>> from sympy import Point\n\n        When multiplying a Point by a floating point number,\n        the coordinates of the Point will be changed to Floats:\n\n        >>> Point(1, 2)*0.1\n        Point2D(0.1, 0.2)\n\n        If this is not desired, the `scale` method can be used or\n        else only multiply or divide by integers:\n\n        >>> Point(1, 2).scale(1.1, 1.1)\n        Point2D(11/10, 11/5)\n        >>> Point(1, 2)*11/10\n        Point2D(11/10, 11/5)\n\n        See Also\n        ========\n\n        sympy.geometry.point.Point.scale\n        ",
            "n_words": 71,
            "vocab_size": 53,
            "n_whitespaces": 190,
            "language": "en"
        }
    },
    {
        "id": 252418,
        "commit_id": "002f919dda5f01d067c2e786426c68751551d15c",
        "repo": "mitmproxy",
        "path": "mitmproxy/contrib/kaitaistruct/vlq_base128_le.py",
        "file_name": "vlq_base128_le.py",
        "fun_name": "value",
        "commit_message": "update kaitai definitions",
        "code": "def value(self):\n            \n            if hasattr(self, '_m_value'):\n                return self._m_value\n\n            self._m_value = (self.b & 127)\n            return getattr(self, '_m_value', None)\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 75,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 38,
        "n_ast_nodes": 64,
        "n_identifiers": 6,
        "d_id": 73952,
        "documentation": {
            "docstring": "The 7-bit (base128) numeric value chunk of this group.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 96559,
        "commit_id": "542484c0cd71625e62e086f3f7c5aaf85360f724",
        "repo": "sentry",
        "path": "src/sentry/plugins/bases/notify.py",
        "file_name": "notify.py",
        "fun_name": "notify",
        "commit_message": "fix(plugins): Silence error (#32042)",
        "code": "def notify(self, notification, raise_exception=False):\n        \n        event = notification.event\n        try:\n            return self.notify_users(\n                event.group, event, triggering_rules=[r.label for r in notification.rules]\n            )\n        except (\n            ApiError,\n            HTTPError,\n            InvalidIdentity,\n            PluginError,\n            SSLError,\n            UrllibHTTPError,\n        ) as err:\n            self.logger.info(\n                \"notification-plugin.notify-failed\",\n                extra={\n                    \"error\": str(err),\n                    \"plugin\": self.slug,\n                    \"project_id\": event.group.project_id,\n                    \"organization_id\": event.group.project.organization_id,\n                },\n            )\n            if raise_exception:\n                raise err\n            return False\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 366,
        "n_words": 48,
        "vocab_size": 45,
        "complexity": 4,
        "nloc": 26,
        "token_counts": 114,
        "n_ast_nodes": 175,
        "n_identifiers": 26,
        "d_id": 19326,
        "documentation": {
            "docstring": "\n        This calls the notify_users method of the plugin.\n        Normally this method eats the error and logs it but if we\n        set raise_exception=True like we do for the test plugin button,\n        the exception is raised\n        ",
            "n_words": 34,
            "vocab_size": 28,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 266782,
        "commit_id": "a06fa496d3f837cca3c437ab6e9858525633d147",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/host_profiles.py",
        "file_name": "host_profiles.py",
        "fun_name": "create_single_host",
        "commit_message": "ansible-test - Code cleanup and refactoring. (#77169)\n\n* Remove unnecessary PyCharm ignores.\r\n* Ignore intentional undefined attribute usage.\r\n* Add missing type hints. Fix existing type hints.\r\n* Fix docstrings and comments.\r\n* Use function to register completion handler.\r\n* Pass strings to display functions.\r\n* Fix CompositeAction handling of dest argument.\r\n* Use consistent types in expressions/assignments.\r\n* Use custom function to keep linters happy.\r\n* Add missing raise for custom exception.\r\n* Clean up key/value type handling in cloud plugins.\r\n* Use dataclass instead of dict for results.\r\n* Add custom type_guard function to check lists.\r\n* Ignore return type that can't be checked (yet).\r\n* Avoid changing types on local variables.",
        "code": "def create_single_host(name, variables):  # type: (str, t.Dict[str, t.Union[str, int]]) -> Inventory\n        \n        return Inventory(host_groups=dict(all={name: variables}))\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 29,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 78585,
        "documentation": {
            "docstring": "Return an inventory instance created from the given hostname and variables.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 137248,
        "commit_id": "ed5b9e5439811becd062ef7734b1afceca2c7d07",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_syncer.py",
        "file_name": "test_syncer.py",
        "fun_name": "test_syncer_hanging_sync_with_timeout",
        "commit_message": "[Tune] Add timeout for experiment checkpoint syncing to cloud (#30855)\n\n#28155 introduced a sync timeout for trainable checkpoint syncing to the cloud, in the case that the sync operation (default is with pyarrow) hangs. This PR adds a similar timeout for experiment checkpoint cloud syncing.\r\n\r\nSigned-off-by: Justin Yu <justinvyu@berkeley.edu>",
        "code": "def test_syncer_hanging_sync_with_timeout(temp_data_dirs):\n    \n    tmp_source, tmp_target = temp_data_dirs\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 12,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 86,
        "n_ast_nodes": 21,
        "n_identifiers": 4,
        "d_id": 31110,
        "documentation": {
            "docstring": "Check that syncing times out when the sync process is hanging.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 109729,
        "commit_id": "8387676bc049d7b3e071846730c632e6ced137ed",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_secondary_axes.py",
        "file_name": "_secondary_axes.py",
        "fun_name": "draw",
        "commit_message": "Clean up code in SecondaryAxis",
        "code": "def draw(self, renderer):\n        \n        self._set_lims()\n        # this sets the scale in case the parent has set its scale.\n        self._set_scale()\n        super().draw(renderer)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 54,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 48,
        "n_identifiers": 6,
        "d_id": 23725,
        "documentation": {
            "docstring": "\n        Draw the secondary axes.\n\n        Consults the parent axes for its limits and converts them\n        using the converter specified by\n        `~.axes._secondary_axes.set_functions` (or *functions*\n        parameter when axes initialized.)\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 245713,
        "commit_id": "d915740fa8228cf57741b27d9e5d66e358456b8e",
        "repo": "mmdetection",
        "path": "mmdet/models/task_modules/coders/bucketing_bbox_coder.py",
        "file_name": "bucketing_bbox_coder.py",
        "fun_name": "decode",
        "commit_message": "[Refactor] Refactor anchor head and base head with boxlist (#8625)\n\n* Refactor anchor head\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Add a series of boxes tools\r\n\r\n* Fix box type to support n x box_dim boxes\r\n\r\n* revert box type changes\r\n\r\n* Add docstring\r\n\r\n* refactor retina_head\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Fix comments\r\n\r\n* modify docstring of coder and ioucalculator\r\n\r\n* Replace with_boxlist with use_box_type",
        "code": "def decode(self, bboxes, pred_bboxes, max_shape=None):\n        \n        bboxes = get_box_tensor(bboxes)\n        assert len(pred_bboxes) == 2\n        cls_preds, offset_preds = pred_bboxes\n        assert cls_preds.size(0) == bboxes.size(0) and offset_preds.size(\n            0) == bboxes.size(0)\n        bboxes, loc_confidence = bucket2bbox(bboxes, cls_preds, offset_preds,\n                                             self.num_buckets,\n                                             self.scale_factor, max_shape,\n                                             self.clip_border)\n        if self.use_box_type:\n            bboxes = HorizontalBoxes(bboxes, clone=False)\n        return bboxes, loc_confidence\n\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 254,
        "n_words": 44,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 105,
        "n_ast_nodes": 158,
        "n_identifiers": 18,
        "d_id": 70859,
        "documentation": {
            "docstring": "Apply transformation `pred_bboxes` to `boxes`.\n        Args:\n            boxes (torch.Tensor or :obj:`BaseBoxes`): Basic boxes.\n            pred_bboxes (torch.Tensor): Predictions for bucketing estimation\n                and fine regression\n            max_shape (tuple[int], optional): Maximum shape of boxes.\n                Defaults to None.\n\n        Returns:\n            Union[torch.Tensor, :obj:`BaseBoxes`]: Decoded boxes.\n        ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 131,
            "language": "en"
        }
    },
    {
        "id": 74116,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_blocks.py",
        "file_name": "test_blocks.py",
        "fun_name": "test_include_block_tag_with_plain_value",
        "commit_message": "Reformat with black",
        "code": "def test_include_block_tag_with_plain_value(self):\n        \n        result = render_to_string(\n            \"tests/blocks/include_block_test.html\",\n            {\n                \"test_block\": 42,\n            },\n        )\n\n        self.assertIn(\"<body>42</body>\", result)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 89,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 28,
        "n_ast_nodes": 51,
        "n_identifiers": 5,
        "d_id": 16220,
        "documentation": {
            "docstring": "\n        The include_block tag should be able to render a value without a render_as_block method\n        by just rendering it as a string\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 156257,
        "commit_id": "7471eb3d1e9ccf085b70b219413aa891c8c2c167",
        "repo": "dask",
        "path": "dask/array/utils.py",
        "file_name": "utils.py",
        "fun_name": "meta_from_array",
        "commit_message": "masked scalars input to da.from_array (#8895)",
        "code": "def meta_from_array(x, ndim=None, dtype=None):\n    \n    # If using x._meta, x must be a Dask Array, some libraries (e.g. zarr)\n    # implement a _meta attribute that are incompatible with Dask Array._meta\n    if hasattr(x, \"_meta\") and isinstance(x, Array):\n        x = x._meta\n\n    if dtype is None and x is None:\n        raise ValueError(\"You must specify the meta or dtype of the array\")\n\n    if np.isscalar(x):\n        x = np.array(x)\n\n    if x is None:\n        x = np.ndarray\n    elif dtype is None and hasattr(x, \"dtype\"):\n        dtype = x.dtype\n\n    if isinstance(x, type):\n        x = x(shape=(0,) * (ndim or 0), dtype=dtype)\n\n    if isinstance(x, list) or isinstance(x, tuple):\n        ndims = [\n            0\n            if isinstance(a, numbers.Number)\n            else a.ndim\n            if hasattr(a, \"ndim\")\n            else len(a)\n            for a in x\n        ]\n        a = [a if nd == 0 else meta_from_array(a, nd) for a, nd in zip(x, ndims)]\n        return a if isinstance(x, list) else tuple(x)\n\n    if (\n        not hasattr(x, \"shape\")\n        or not hasattr(x, \"dtype\")\n        or not isinstance(x.shape, tuple)\n    ):\n        return x\n\n    if ndim is None:\n        ndim = x.ndim\n\n    try:\n        meta = x[tuple(slice(0, 0, None) for _ in range(x.ndim))]\n        if meta.ndim != ndim:\n            if ndim > x.ndim:\n                meta = meta[(Ellipsis,) + tuple(None for _ in range(ndim - meta.ndim))]\n                meta = meta[tuple(slice(0, 0, None) for _ in range(meta.ndim))]\n            elif ndim == 0:\n                meta = meta.sum()\n            else:\n                meta = meta.reshape((0,) * ndim)\n        if meta is np.ma.masked:\n            meta = np.ma.array(np.empty((0,) * ndim, dtype=dtype or x.dtype), mask=True)\n    except Exception:\n        meta = np.empty((0,) * ndim, dtype=dtype or x.dtype)\n\n    if np.isscalar(meta):\n        meta = np.array(meta)\n\n    if dtype and meta.dtype != dtype:\n        try:\n            meta = meta.astype(dtype)\n        except ValueError as e:\n            if (\n                any(\n                    s in str(e)\n                    for s in [\n                        \"invalid literal\",\n                        \"could not convert string to float\",\n                    ]\n                )\n                and meta.dtype.kind in \"SU\"\n            ):\n                meta = np.array([]).astype(dtype)\n            else:\n                raise e\n\n    return meta\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 887,
        "n_words": 287,
        "vocab_size": 149,
        "complexity": 40,
        "nloc": 66,
        "token_counts": 524,
        "n_ast_nodes": 816,
        "n_identifiers": 42,
        "d_id": 36621,
        "documentation": {
            "docstring": "Normalize an array to appropriate meta object\n\n    Parameters\n    ----------\n    x: array-like, callable\n        Either an object that looks sufficiently like a Numpy array,\n        or a callable that accepts shape and dtype keywords\n    ndim: int\n        Number of dimensions of the array\n    dtype: Numpy dtype\n        A valid input for ``np.dtype``\n\n    Returns\n    -------\n    array-like with zero elements of the correct dtype\n    ",
            "n_words": 57,
            "vocab_size": 45,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 289313,
        "commit_id": "62690759d483b03932939d28bbf87ce3b293c486",
        "repo": "core",
        "path": "homeassistant/components/yandex_transport/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "async_update",
        "commit_message": "Move attribution to standalone attribute [t-z] (#80521)",
        "code": "async def async_update(self, *, tries=0):\n        \n        attrs = {}\n        closer_time = None\n        try:\n            yandex_reply = await self.requester.get_stop_info(self._stop_id)\n        except CaptchaError as ex:\n            _LOGGER.error(\n                \"%s. You may need to disable the integration for some time\",\n                ex,\n            )\n            return\n        try:\n            data = yandex_reply[\"data\"]\n        except KeyError as key_error:\n            _LOGGER.warning(\n                \"Exception KeyError was captured, missing key is %s. Yandex returned: %s\",\n                key_error,\n                yandex_reply,\n            )\n            if tries > 0:\n                return\n            await self.requester.set_new_session()\n            await self.async_update(tries=tries + 1)\n            return\n\n        stop_name = data[\"name\"]\n        transport_list = data[\"transports\"]\n        for transport in transport_list:\n            for thread in transport[\"threads\"]:\n                if \"Events\" not in thread[\"BriefSchedule\"]:\n                    continue\n                if thread.get(\"noBoarding\") is True:\n                    continue\n                for event in thread[\"BriefSchedule\"][\"Events\"]:\n                    # Railway route depends on the essential stops and\n                    # can vary over time.\n                    # City transport has the fixed name for the route\n                    if \"railway\" in transport[\"Types\"]:\n                        route = \" - \".join(\n                            [x[\"name\"] for x in thread[\"EssentialStops\"]]\n                        )\n                    else:\n                        route = transport[\"name\"]\n\n                    if self._routes and route not in self._routes:\n                        # skip unnecessary route info\n                        continue\n                    if \"Estimated\" not in event and \"Scheduled\" not in event:\n                        continue\n\n                    departure = event.get(\"Estimated\") or event[\"Scheduled\"]\n                    posix_time_next = int(departure[\"value\"])\n                    if closer_time is None or closer_time > posix_time_next:\n                        closer_time = posix_time_next\n                    if route not in attrs:\n                        attrs[route] = []\n                    attrs[route].append(departure[\"text\"])\n        attrs[STOP_NAME] = stop_name\n\n        if closer_time is None:\n            self._state = None\n        else:\n            self._state = dt_util.utc_from_timestamp(closer_time).replace(microsecond=0)\n        self._attrs = attrs\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1075,
        "n_words": 211,
        "vocab_size": 125,
        "complexity": 20,
        "nloc": 56,
        "token_counts": 316,
        "n_ast_nodes": 545,
        "n_identifiers": 39,
        "d_id": 88455,
        "documentation": {
            "docstring": "Get the latest data from maps.yandex.ru and update the states.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 259442,
        "commit_id": "75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_glm/glm.py",
        "file_name": "glm.py",
        "fun_name": "_linear_predictor",
        "commit_message": "ENH migrate GLMs / TweedieRegressor to linear loss (#22548)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def _linear_predictor(self, X):\n        \n        check_is_fitted(self)\n        X = self._validate_data(\n            X,\n            accept_sparse=[\"csr\", \"csc\", \"coo\"],\n            dtype=[np.float64, np.float32],\n            ensure_2d=True,\n            allow_nd=False,\n            reset=False,\n        )\n        return X @ self.coef_ + self.intercept_\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 124,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 65,
        "n_ast_nodes": 100,
        "n_identifiers": 15,
        "d_id": 75775,
        "documentation": {
            "docstring": "Compute the linear_predictor = `X @ coef_ + intercept_`.\n\n        Note that we often use the term raw_prediction instead of linear predictor.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix} of shape (n_samples, n_features)\n            Samples.\n\n        Returns\n        -------\n        y_pred : array of shape (n_samples,)\n            Returns predicted values of linear predictor.\n        ",
            "n_words": 47,
            "vocab_size": 38,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 299235,
        "commit_id": "29a2df3dfcf3b5d1fb6cf20b413e024eb0ebf597",
        "repo": "core",
        "path": "homeassistant/components/onvif/binary_sensor.py",
        "file_name": "binary_sensor.py",
        "fun_name": "async_added_to_hass",
        "commit_message": "Restore ONVIF sensors (#70393)\n\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>",
        "code": "async def async_added_to_hass(self):\n        \n        self.async_on_remove(\n            self.device.events.async_add_listener(self.async_write_ha_state)\n        )\n        if (last_state := await self.async_get_last_state()) is not None:\n            self._attr_is_on = last_state.state == STATE_ON\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 69,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 47,
        "n_ast_nodes": 79,
        "n_identifiers": 12,
        "d_id": 98171,
        "documentation": {
            "docstring": "Connect to dispatcher listening for entity data notifications.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 251164,
        "commit_id": "e83ec8390ad6be6a86cfcfc57bce14cb8861bf32",
        "repo": "mitmproxy",
        "path": "mitmproxy/tls.py",
        "file_name": "tls.py",
        "fun_name": "extensions",
        "commit_message": "`pyupgrade --py39-plus **/*.py`",
        "code": "def extensions(self) -> list[tuple[int, bytes]]:\n        \n        ret = []\n        if self._client_hello.extensions:\n            for extension in self._client_hello.extensions.extensions:\n                body = getattr(extension, \"_raw_body\", extension.body)\n                ret.append((extension.type, body))\n        return ret\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 92,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 64,
        "n_ast_nodes": 100,
        "n_identifiers": 13,
        "d_id": 73616,
        "documentation": {
            "docstring": "The raw list of extensions in the form of `(extension_type, raw_bytes)` tuples.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 132932,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/client/runtime_context.py",
        "file_name": "runtime_context.py",
        "fun_name": "build_runtime_context",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def build_runtime_context(self) -> \"RuntimeContext\":\n        \n        # Defer the import of RuntimeContext until needed to avoid cycles\n        from ray.runtime_context import RuntimeContext\n\n        return RuntimeContext(self)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 49,
        "n_words": 21,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 19,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 29871,
        "documentation": {
            "docstring": "Creates a RuntimeContext backed by the properites of this API",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 223045,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/tests/test_archive_util.py",
        "file_name": "test_archive_util.py",
        "fun_name": "test_make_tarball_latin1",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def test_make_tarball_latin1(self):\n        \n        self.test_make_tarball('årchiv') # note this isn't a real word\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 26,
        "n_identifiers": 3,
        "d_id": 56856,
        "documentation": {
            "docstring": "\n        Mirror test_make_tarball, except filename contains latin characters.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 130602,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/data/impl/block_list.py",
        "file_name": "block_list.py",
        "fun_name": "ensure_schema_for_first_block",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def ensure_schema_for_first_block(self) -> Optional[Union[\"pyarrow.Schema\", type]]:\n        \n        get_schema = cached_remote_fn(_get_schema)\n        try:\n            block = next(self.iter_blocks())\n        except (StopIteration, ValueError):\n            # Dataset is empty (no blocks) or was manually cleared.\n            return None\n        schema = ray.get(get_schema.remote(block))\n        # Set the schema.\n        self._metadata[0].schema = schema\n        return schema\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 128,
        "n_words": 39,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 68,
        "n_ast_nodes": 113,
        "n_identifiers": 18,
        "d_id": 29328,
        "documentation": {
            "docstring": "Ensure that the schema is set for the first block.\n\n        Returns None if the block list is empty.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 217445,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ftplib.py",
        "file_name": "ftplib.py",
        "fun_name": "parse257",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parse257(resp):\n    \n    if resp[:3] != '257':\n        raise error_reply(resp)\n    if resp[3:5] != ' \"':\n        return '' # Not compliant to RFC 959, but UNIX ftpd does this\n    dirname = ''\n    i = 5\n    n = len(resp)\n    while i < n:\n        c = resp[i]\n        i = i+1\n        if c == '\"':\n            if i >= n or resp[i] != '\"':\n                break\n            i = i+1\n        dirname = dirname + c\n    return dirname\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 171,
        "n_words": 68,
        "vocab_size": 42,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 90,
        "n_ast_nodes": 158,
        "n_identifiers": 8,
        "d_id": 54790,
        "documentation": {
            "docstring": "Parse the '257' response for a MKD or PWD request.\n    This is a response to a MKD or PWD request: a directory name.\n    Returns the directoryname in the 257 reply.",
            "n_words": 30,
            "vocab_size": 21,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 155996,
        "commit_id": "8a6f6a7b95762df4e44bc4d82ce33a7c388a0676",
        "repo": "dask",
        "path": "dask/dataframe/io/io.py",
        "file_name": "io.py",
        "fun_name": "to_bag",
        "commit_message": "Move Bag.map_partitions to Blockwise (#8646)\n\n1. Adds `format=\"frame\"` option to `dataframe.io.to_bag` (effectively returning a zero-copy view of the same dask graph, that no-longer tracks meta/divisions)\r\n2. Revises `Bag.map_partitions` to use `blockwise` (and to support the `token=` option)\r\n3. Modifies the ACA code path to use a `Bag.map_partitions` for any blockwise operations where partitions may loose \"dataframe-like\" properties.\r\n\r\nThis represents an alternative to using `map_partitions` incorrectly in ACA. It is also an alternative to the low-level `blockwise` API.",
        "code": "def to_bag(df, index=False, format=\"tuple\"):\n    \n    from ...bag.core import Bag\n\n    if not isinstance(df, (DataFrame, Series)):\n        raise TypeError(\"df must be either DataFrame or Series\")\n    name = \"to_bag-\" + tokenize(df, index, format)\n    if format == \"frame\":\n        # Use existing graph and name of df, but\n        # drop meta to produce a Bag collection\n        dsk = df.dask\n        name = df._name\n    else:\n        dsk = {\n            (name, i): (_df_to_bag, block, index, format)\n            for (i, block) in enumerate(df.__dask_keys__())\n        }\n        dsk.update(df.__dask_optimize__(df.__dask_graph__(), df.__dask_keys__()))\n    return Bag(dsk, name, df.npartitions)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 176,
        "n_words": 77,
        "vocab_size": 66,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 134,
        "n_ast_nodes": 215,
        "n_identifiers": 25,
        "d_id": 36501,
        "documentation": {
            "docstring": "Create Dask Bag from a Dask DataFrame\n\n    Parameters\n    ----------\n    index : bool, optional\n        If True, the elements are tuples of ``(index, value)``, otherwise\n        they're just the ``value``.  Default is False.\n    format : {\"tuple\", \"dict\", \"frame\"}, optional\n        Whether to return a bag of tuples, dictionaries, or\n        dataframe-like objects. Default is \"tuple\". If \"frame\",\n        the original partitions of ``df`` will not be transformed\n        in any way.\n\n\n    Examples\n    --------\n    >>> bag = df.to_bag()  # doctest: +SKIP\n    ",
            "n_words": 73,
            "vocab_size": 61,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 101662,
        "commit_id": "892d8626ed4e7f834ac5607af59f14f5476d5997",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_get_no_faces",
        "commit_message": "Bugfix: Alignments tool - don't error on from-faces job",
        "code": "def _get_no_faces(self):\n        \n        self.output_message = \"Frames with no faces\"\n        for frame in tqdm(self._items, desc=self.output_message):\n            logger.trace(frame)  # type:ignore\n            frame_name = frame[\"frame_fullname\"]\n            if not self._alignments.frame_has_faces(frame_name):\n                logger.debug(\"Returning: '%s'\", frame_name)\n                yield frame_name\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 112,
        "n_words": 27,
        "vocab_size": 25,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 60,
        "n_ast_nodes": 104,
        "n_identifiers": 13,
        "d_id": 21067,
        "documentation": {
            "docstring": " yield each frame that has no face match in alignments file ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 201962,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/cache/tests.py",
        "file_name": "tests.py",
        "fun_name": "_perform_invalid_key_test",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _perform_invalid_key_test(self, key, expected_warning):\n        \n        msg = expected_warning.replace(key, cache.make_key(key))\n        tests = [\n            (\"add\", [key, 1]),\n            (\"get\", [key]),\n            (\"set\", [key, 1]),\n            (\"incr\", [key]),\n            (\"decr\", [key]),\n            (\"touch\", [key]),\n            (\"delete\", [key]),\n            (\"get_many\", [[key, \"b\"]]),\n            (\"set_many\", [{key: 1, \"b\": 2}]),\n            (\"delete_many\", [[key, \"b\"]]),\n        ]\n        for operation, args in tests:\n            with self.subTest(operation=operation):\n                with self.assertRaises(InvalidCacheKey) as cm:\n                    getattr(cache, operation)(*args)\n                self.assertEqual(str(cm.exception), msg)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 259,
        "n_words": 54,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 19,
        "token_counts": 179,
        "n_ast_nodes": 281,
        "n_identifiers": 19,
        "d_id": 50027,
        "documentation": {
            "docstring": "\n        While other backends merely warn, memcached should raise for an invalid\n        key.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 90884,
        "commit_id": "b9f5a910dc841b85f58d46266ec049ae5a7fd305",
        "repo": "sentry",
        "path": "tests/sentry/integrations/slack/notifications/test_deploy.py",
        "file_name": "test_deploy.py",
        "fun_name": "test_deploy",
        "commit_message": "ref(models): `ActivityType` (#34978)\n\n## Objective:\r\nWe want to separate enum logic from Model logic. This breaks a lot of circular dependencies.",
        "code": "def test_deploy(self, mock_func):\n        \n        release = Release.objects.create(\n            version=\"meow\" * 10,\n            organization_id=self.project.organization_id,\n            date_released=timezone.now(),\n        )\n\n        # The projects can appear out of order.\n        projects = (self.project, self.create_project(name=\"battlesnake\"))\n        SLUGS_TO_PROJECT = {project.slug: project for project in projects}\n\n        for project in projects:\n            release.add_project(project)\n\n        deploy = Deploy.objects.create(\n            release=release,\n            organization_id=self.organization.id,\n            environment_id=self.environment.id,\n        )\n        notification = ReleaseActivityNotification(\n            Activity(\n                project=self.project,\n                user=self.user,\n                type=ActivityType.RELEASE.value,\n                data={\"version\": release.version, \"deploy_id\": deploy.id},\n            )\n        )\n        with self.tasks():\n            notification.send()\n\n        attachment, text = get_attachment()\n        assert (\n            text\n            == f\"Release {release.version} was deployed to {self.environment.name} for these projects\"\n        )\n\n        first_project = None\n        for i in range(len(projects)):\n            project = SLUGS_TO_PROJECT[attachment[\"actions\"][i][\"text\"]]\n            if not first_project:\n                first_project = project\n            assert (\n                attachment[\"actions\"][i][\"url\"]\n                == f\"http://testserver/organizations/{self.organization.slug}/releases/\"\n                f\"{release.version}/?project={project.id}&unselectedSeries=Healthy/\"\n            )\n\n        assert (\n            attachment[\"footer\"]\n            == f\"{first_project.slug} | <http://testserver/settings/account/notifications/\"\n            f\"deploy/?referrer=release_activity-slack-user|Notification Settings>\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 573,
        "n_words": 111,
        "vocab_size": 79,
        "complexity": 5,
        "nloc": 45,
        "token_counts": 244,
        "n_ast_nodes": 440,
        "n_identifiers": 43,
        "d_id": 18703,
        "documentation": {
            "docstring": "\n        Test that a Slack message is sent with the expected payload when a deploy happens.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 207338,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_scripts/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_option_then_setting",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_option_then_setting(self):\n        \n        args = [\n            \"base_command\",\n            \"testlabel\",\n            \"--option_a=x\",\n            \"--settings=alternate_settings\",\n        ]\n        self._test(args)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 83,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 24,
        "n_ast_nodes": 46,
        "n_identifiers": 4,
        "d_id": 51933,
        "documentation": {
            "docstring": "Options passed before settings are correctly handled.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 259327,
        "commit_id": "ee5a1b69d1dfa99635a10f0a5b54ec263cedf866",
        "repo": "scikit-learn",
        "path": "sklearn/utils/validation.py",
        "file_name": "validation.py",
        "fun_name": "_pandas_dtype_needs_early_conversion",
        "commit_message": "DOC, MNT Typos found by codespell (#22906)",
        "code": "def _pandas_dtype_needs_early_conversion(pd_dtype):\n    \n    try:\n        from pandas.api.types import (\n            is_extension_array_dtype,\n            is_float_dtype,\n            is_integer_dtype,\n            is_sparse,\n        )\n    except ImportError:\n        return False\n\n    if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype):\n        # Sparse arrays will be converted later in `check_array`\n        # Only handle extension arrays for integer and floats\n        return False\n    elif is_float_dtype(pd_dtype):\n        # Float ndarrays can normally support nans. They need to be converted\n        # first to map pd.NA to np.nan\n        return True\n    elif is_integer_dtype(pd_dtype):\n        # XXX: Warn when converting from a high integer to a float\n        return True\n\n    return False\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 224,
        "n_words": 82,
        "vocab_size": 61,
        "complexity": 6,
        "nloc": 17,
        "token_counts": 62,
        "n_ast_nodes": 105,
        "n_identifiers": 10,
        "d_id": 75712,
        "documentation": {
            "docstring": "Return True if pandas extension pd_dtype need to be converted early.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 194458,
        "commit_id": "1830123ba3edf7290b7c6cb1c6f406ccf1d0e5d4",
        "repo": "kivy",
        "path": "kivy/uix/widget.py",
        "file_name": "widget.py",
        "fun_name": "on_motion",
        "commit_message": "Feature: EventManagerBase (#7658)\n\n* Added EventManagerBase class and event_managers attribute to WindowBase class.\r\n* Added on_motion event to Widget class.\r\n* Updated post_dispatch_input in EventLoopBase to skip non-touch events.\r\n* Using type ids in MouseMotionEventProvider.\r\n* Added on_motion method to Widget subclasses.\r\n* Updated Widget.on_motion method to dispatch to filtered widgets if 'pos' is not in me.profile.\r\n* Changed motion_filter property in Widget to store key to list values.\r\n* Updated Widget.on_motion to not dispatch event to children if widget is disabled.\r\n* Widget: Using flags to control dispatching in on_motion method.\r\n* Widget: Don't dispatch on_motion to children if only self is registered.\r\n* Widget: Removed collision on disabled check from on_motion method.\r\n* Widget: Added docstrings for motion_filter and related methods.\r\n* EventManager: Moved motion event flags to eventmanager/__init__.py module.\r\n* ScreenManager: Overrode the on_motion method.\r\n* WindowBase: Using attributes event_managers and event_managers_dict.\r\n* WindowBase: Added doc for register_event_manager and unregister_event_manager methods.\r\n* Widget: Improved default dispatch to stop after the last registered widgets.\r\n* EventManagerBase: Added initial docs class and module.\r\n* Widget: Added experimental warnings to motion_filter property and to on_motion and (un)register_for_motion_event methods.\r\n* WindowBase: Added docs for event_managers and event_managers_dict attributes.\r\n* MotionEvent: Added type_id and flags to push_attrs list.\r\n* EventManagerBase: Added versionadded tag on all flags.\r\n* EventManagerBase: Use dispatch modes instead of flags.",
        "code": "def on_motion(self, etype, me):\n        \n        if self.disabled or me.dispatch_mode == MODE_DONT_DISPATCH:\n            return\n        if me.type_id not in self.motion_filter:\n            return\n        filtered = self.motion_filter[me.type_id]\n        if filtered[0] is self and len(filtered) == 1:\n            return\n        if me.dispatch_mode == MODE_DEFAULT_DISPATCH:\n            last_filtered = filtered[-1]\n            for widget in self.children[:]:\n                if widget.dispatch('on_motion', etype, me):\n                    return True\n                if widget is last_filtered:\n                    return\n        if me.dispatch_mode == MODE_FILTERED_DISPATCH:\n            widgets = filtered[1:] if filtered[0] is self else filtered[:]\n            for widget in widgets:\n                if widget.dispatch('on_motion', etype, me):\n                    return True\n\n    #\n    # Default event handlers\n    #",
        "url": "https://github.com/kivy/kivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 317,
        "n_words": 80,
        "vocab_size": 43,
        "complexity": 14,
        "nloc": 20,
        "token_counts": 148,
        "n_ast_nodes": 233,
        "n_identifiers": 18,
        "d_id": 46982,
        "documentation": {
            "docstring": "Called when a motion event is received.\n\n        :Parameters:\n            `etype`: `str`\n                Event type, one of \"begin\", \"update\" or \"end\"\n            `me`: :class:`~kivy.input.motionevent.MotionEvent`\n                Received motion event\n        :Returns: `bool`\n            `True` to stop event dispatching\n\n        .. versionadded:: 2.1.0\n\n        .. warning::\n            This is an experimental method and it remains so while this warning\n            is present as it can be changed or removed in the next versions of\n            Kivy.\n        ",
            "n_words": 62,
            "vocab_size": 53,
            "n_whitespaces": 193,
            "language": "en"
        }
    },
    {
        "id": 285988,
        "commit_id": "83377868b25b91b608f04cbda9383f838dff74cd",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/portfolio/portfolio_optimization/po_controller.py",
        "file_name": "po_controller.py",
        "fun_name": "call_ef",
        "commit_message": "PO_controller refactoring and tests (#2725)\n\n* Adding tests\n\n* Added tests to po_controller\n\n* Refactored po controller\n\n* fix custom_resets\n\n* fix load\n\n* add disable timeout\n\n* pylint\n\nCo-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt>\nCo-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>\nCo-authored-by: montezdesousa <montezdesousa@gmail.com>",
        "code": "def call_ef(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            prog=\"ef\",\n            description=,\n        )\n        parser.add_argument(\n            \"-vs\",\n            \"--value-short\",\n            dest=\"short_allocation\",\n            help=\"Amount to allocate to portfolio in short positions\",\n            type=float,\n            default=self.params[\"short_allocation\"]\n            if \"short_allocation\" in self.params\n            else 0.0,\n        )\n        if other_args and \"-\" not in other_args[0][0]:\n            other_args.insert(0, \"-n\")\n        parser.add_argument(\n            \"-n\",\n            \"--number-portfolios\",\n            default=self.params[\"amount_portfolios\"]\n            if \"amount_portfolios\" in self.params\n            else 100,\n            type=check_non_negative,\n            dest=\"amount_portfolios\",\n            help=\"Number of portfolios to simulate\",\n        )\n        parser.add_argument(\n            \"-se\",\n            \"--seed\",\n            default=self.params[\"random_seed\"] if \"random_seed\" in self.params else 123,\n            type=check_non_negative,\n            dest=\"random_seed\",\n            help=\"Seed used to generate random portfolios\",\n        )\n        parser.add_argument(\n            \"-t\",\n            \"--tangency\",\n            action=\"store_true\",\n            dest=\"tangency\",\n            default=self.params[\"tangency\"] if \"tangency\" in self.params else False,\n            help=\"Adds the optimal line with the risk-free asset\",\n        )\n        parser.add_argument(\n            \"--no_plot\",\n            action=\"store_false\",\n            dest=\"plot_tickers\",\n            default=True,\n            help=\"Whether or not to plot the tickers for the assets provided\",\n        )\n        parser = self.po_parser(\n            parser,\n            rm=True,\n            mt=True,\n            p=True,\n            s=True,\n            e=True,\n            lr=True,\n            freq=True,\n            mn=True,\n            th=True,\n            r=True,\n            a=True,\n            v=True,\n        )\n        ns_parser = self.parse_known_args_and_warn(parser, other_args)\n\n        if ns_parser:\n            if len(self.tickers) < 2:\n                console.print(\n                    \"Please have at least 2 loaded tickers to calculate weights.\\n\"\n                )\n                return\n\n            optimizer_view.display_ef(\n                symbols=self.tickers,\n                interval=ns_parser.historic_period,\n                start_date=ns_parser.start_period,\n                end_date=ns_parser.end_period,\n                log_returns=ns_parser.log_returns,\n                freq=ns_parser.return_frequency,\n                maxnan=ns_parser.max_nan,\n                threshold=ns_parser.threshold_value,\n                method=ns_parser.nan_fill_method,\n                risk_measure=ns_parser.risk_measure.lower(),\n                risk_free_rate=ns_parser.risk_free,\n                alpha=ns_parser.significance_level,\n                value=ns_parser.long_allocation,\n                value_short=ns_parser.short_allocation,\n                n_portfolios=ns_parser.amount_portfolios,\n                seed=ns_parser.random_seed,\n                tangency=ns_parser.tangency,\n                plot_tickers=ns_parser.plot_tickers,\n            )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 1230,
        "n_words": 176,
        "vocab_size": 133,
        "complexity": 9,
        "nloc": 95,
        "token_counts": 436,
        "n_ast_nodes": 668,
        "n_identifiers": 73,
        "d_id": 85488,
        "documentation": {
            "docstring": "Process ef commandThis function plots random portfolios based on their\n                risk and returns and shows the efficient frontier.",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 19953,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/req/req_install.py",
        "file_name": "req_install.py",
        "fun_name": "is_pinned",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def is_pinned(self) -> bool:\n        \n        specifiers = self.specifier\n        return len(specifiers) == 1 and next(iter(specifiers)).operator in {\"==\", \"===\"}\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 37,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 63,
        "n_identifiers": 9,
        "d_id": 3159,
        "documentation": {
            "docstring": "Return whether I am pinned to an exact version.\n\n        For example, some-package==1.2 is pinned; some-package>1.2 is not.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 300319,
        "commit_id": "26177bd080b4eb6d11cfd9fbdd158be36f4983d4",
        "repo": "core",
        "path": "homeassistant/components/logbook/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_generate_legacy_events_context_id_query",
        "commit_message": "Convert logbook to use lambda_stmt (#71624)",
        "code": "def _generate_legacy_events_context_id_query() -> Select:\n    \n    # This can be removed once we no longer have event_ids in the states table\n    return (\n        select(\n            *EVENT_COLUMNS,\n            literal(value=None, type_=sqlalchemy.String).label(\"shared_data\"),\n            States.state,\n            States.entity_id,\n            States.attributes,\n            StateAttributes.shared_attrs,\n        )\n        .outerjoin(States, (Events.event_id == States.event_id))\n        .where(States.last_updated == States.last_changed)\n        .where(_not_continuous_entity_matcher())\n        .outerjoin(\n            StateAttributes, (States.attributes_id == StateAttributes.attributes_id)\n        )\n    )\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 183,
        "n_words": 45,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 98,
        "n_ast_nodes": 151,
        "n_identifiers": 24,
        "d_id": 99183,
        "documentation": {
            "docstring": "Generate a legacy events context id query that also joins states.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 259457,
        "commit_id": "75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_glm/tests/test_glm.py",
        "file_name": "test_glm.py",
        "fun_name": "test_poisson_glmnet",
        "commit_message": "ENH migrate GLMs / TweedieRegressor to linear loss (#22548)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def test_poisson_glmnet():\n    \n    # library(\"glmnet\")\n    # options(digits=10)\n    # df <- data.frame(a=c(-2,-1,1,2), b=c(0,0,1,1), y=c(0,1,1,2))\n    # x <- data.matrix(df[,c(\"a\", \"b\")])\n    # y <- df$y\n    # fit <- glmnet(x=x, y=y, alpha=0, intercept=T, family=\"poisson\",\n    #               standardize=F, thresh=1e-10, nlambda=10000)\n    # coef(fit, s=1)\n    # (Intercept) -0.12889386979\n    # a            0.29019207995\n    # b            0.03741173122\n    X = np.array([[-2, -1, 1, 2], [0, 0, 1, 1]]).T\n    y = np.array([0, 1, 1, 2])\n    glm = PoissonRegressor(\n        alpha=1,\n        fit_intercept=True,\n        tol=1e-7,\n        max_iter=300,\n    )\n    glm.fit(X, y)\n    assert_allclose(glm.intercept_, -0.12889386979, rtol=1e-5)\n    assert_allclose(glm.coef_, [0.29019207995, 0.03741173122], rtol=1e-5)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 199,
        "n_words": 78,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 123,
        "n_ast_nodes": 170,
        "n_identifiers": 17,
        "d_id": 75787,
        "documentation": {
            "docstring": "Compare Poisson regression with L2 regularization and LogLink to glmnet",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 126228,
        "commit_id": "eb69c1ca286a2eec594f02ddaf546657a8127afd",
        "repo": "ray",
        "path": "python/ray/tune/progress_reporter.py",
        "file_name": "progress_reporter.py",
        "fun_name": "detect_reporter",
        "commit_message": "[air] Add annotation for Tune module. (#27060)\n\nCo-authored-by: Kai Fricke <kai@anyscale.com>",
        "code": "def _detect_reporter(**kwargs) -> TuneReporterBase:\n    \n    if IS_NOTEBOOK:\n        kwargs.setdefault(\"overwrite\", not has_verbosity(Verbosity.V2_TRIAL_NORM))\n        progress_reporter = JupyterNotebookReporter(**kwargs)\n    else:\n        progress_reporter = CLIReporter(**kwargs)\n    return progress_reporter\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 51,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 44,
        "n_ast_nodes": 78,
        "n_identifiers": 11,
        "d_id": 28098,
        "documentation": {
            "docstring": "Detect progress reporter class.\n\n    Will return a :class:`JupyterNotebookReporter` if a IPython/Jupyter-like\n    session was detected, and a :class:`CLIReporter` otherwise.\n\n    Keyword arguments are passed on to the reporter class.\n    ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 258777,
        "commit_id": "d8d5637cfe372dd353dfc9f79dbb63c3189a9ecc",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_linear_loss.py",
        "file_name": "_linear_loss.py",
        "fun_name": "_w_intercept_raw",
        "commit_message": "ENH Loss module LogisticRegression (#21808)\n\n* ENH replace loss in linear logistic regression\r\n\r\n* MNT remove logistic regression's own loss functions\r\n\r\n* CLN remove comment\r\n\r\n* DOC add whatsnew\r\n\r\n* DOC more precise whatsnew\r\n\r\n* CLN restore improvements of #19571\r\n\r\n* ENH improve fit time by separating mat-vec in multiclass\r\n\r\n* DOC update whatsnew\r\n\r\n* not only a bit ;-)\r\n\r\n* DOC note memory benefit for multiclass case\r\n\r\n* trigger CI\r\n\r\n* trigger CI\r\n\r\n* CLN rename variable to hess_prod\r\n\r\n* DOC address reviewer comments\r\n\r\n* CLN remove C/F for 1d arrays\r\n\r\n* CLN rename to gradient_per_sample\r\n\r\n* CLN rename alpha to l2_reg_strength\r\n\r\n* ENH respect F-contiguity\r\n\r\n* TST fix sag tests\r\n\r\n* CLN rename to LinearModelLoss\r\n\r\n* CLN improve comments according to review\r\n\r\n* CLN liblinear comment\r\n\r\n* TST add / move test to test_linear_loss.py\r\n\r\n* CLN comment placement\r\n\r\n* trigger CI\r\n\r\n* CLN add comment about contiguity of raw_prediction\r\n\r\n* DEBUG debian-32\r\n\r\n* DEBUG test only linear_model module\r\n\r\n* Revert \"DEBUG test only linear_model module\"\r\n\r\nThis reverts commit 9d6e6987ff4fbcd32fc9a07944b260688162e14b.\r\n\r\n* DEBUG test -k LogisticRegression\r\n\r\n* Revert \"DEBUG test -k LogisticRegression\"\r\n\r\nThis reverts commit c20316704185da400857b0a3f32935ee1b56c8d9.\r\n\r\n* Revert \"DEBUG debian-32\"\r\n\r\nThis reverts commit ef0b98f23251d1b2b0bd8801e456f258392a8d18.\r\n\r\n* DEBUG set n_jobs=1\r\n\r\n* Revert \"DEBUG set n_jobs=1\"\r\n\r\nThis reverts commit c7f6f72a8c1ee21299786130e097df248fc1a0fb.\r\n\r\n* CLN always use n_threads=1\r\n\r\n* CLN address review\r\n\r\n* ENH avoid array copy\r\n\r\n* CLN simplify L2 norm\r\n\r\n* CLN rename w to weights\r\n\r\n* CLN rename to hessian_sum and hx_sum\r\n\r\n* CLN address review\r\n\r\n* CLN rename to init arg and attribute to base_loss\r\n\r\n* CLN apply review suggestion\r\n\r\nCo-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>\r\n\r\n* CLN base_loss instead of _loss attribute\r\n\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Alexandre Gramfort <alexandre.gramfort@m4x.org>",
        "code": "def _w_intercept_raw(self, coef, X):\n        \n        if not self.base_loss.is_multiclass:\n            if self.fit_intercept:\n                intercept = coef[-1]\n                weights = coef[:-1]\n            else:\n                intercept = 0.0\n                weights = coef\n            raw_prediction = X @ weights + intercept\n        else:\n            # reshape to (n_classes, n_dof)\n            if coef.ndim == 1:\n                weights = coef.reshape((self.base_loss.n_classes, -1), order=\"F\")\n            else:\n                weights = coef\n            if self.fit_intercept:\n                intercept = weights[:, -1]\n                weights = weights[:, :-1]\n            else:\n                intercept = 0.0\n            raw_prediction = X @ weights.T + intercept  # ndarray, likely C-contiguous\n\n        return weights, intercept, raw_prediction\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 340,
        "n_words": 77,
        "vocab_size": 41,
        "complexity": 5,
        "nloc": 21,
        "token_counts": 136,
        "n_ast_nodes": 216,
        "n_identifiers": 15,
        "d_id": 75421,
        "documentation": {
            "docstring": "Helper function to get coefficients, intercept and raw_prediction.\n\n        Parameters\n        ----------\n        coef : ndarray of shape (n_dof,), (n_classes, n_dof) or (n_classes * n_dof,)\n            Coefficients of a linear model.\n            If shape (n_classes * n_dof,), the classes of one feature are contiguous,\n            i.e. one reconstructs the 2d-array via\n            coef.reshape((n_classes, -1), order=\"F\").\n        X : {array-like, sparse matrix} of shape (n_samples, n_features)\n            Training data.\n\n        Returns\n        -------\n        weights : ndarray of shape (n_features,) or (n_classes, n_features)\n            Coefficients without intercept term.\n        intercept : float or ndarray of shape (n_classes,)\n            Intercept terms.\n        raw_prediction : ndarray of shape (n_samples,) or \\\n            (n_samples, n_classes)\n        ",
            "n_words": 94,
            "vocab_size": 63,
            "n_whitespaces": 252,
            "language": "en"
        }
    },
    {
        "id": 271103,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/data_adapter.py",
        "file_name": "data_adapter.py",
        "fun_name": "_make_class_weight_map_fn",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _make_class_weight_map_fn(class_weight):\n    \n    class_ids = list(sorted(class_weight.keys()))\n    expected_class_ids = list(range(len(class_ids)))\n    if class_ids != expected_class_ids:\n        error_msg = (\n            \"Expected `class_weight` to be a dict with keys from 0 to one less \"\n            \"than the number of classes, found {}\"\n        ).format(class_weight)\n        raise ValueError(error_msg)\n\n    class_weight_tensor = tf.convert_to_tensor(\n        [class_weight[int(c)] for c in class_ids]\n    )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 116,
        "n_words": 48,
        "vocab_size": 43,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 76,
        "n_ast_nodes": 123,
        "n_identifiers": 17,
        "d_id": 80688,
        "documentation": {
            "docstring": "Applies class weighting to a `Dataset`.\n\n    The `Dataset` is assumed to be in format `(x, y)` or `(x, y, sw)`, where\n    `y` must be a single `Tensor`.\n\n    Args:\n      class_weight: A map where the keys are integer class ids and values are\n        the class weights, e.g. `{0: 0.2, 1: 0.6, 2: 0.3}`\n\n    Returns:\n      A function that can be used with `tf.data.Dataset.map` to apply class\n      weighting.\n    ",
            "n_words": 64,
            "vocab_size": 51,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 52497,
        "commit_id": "7eef3bfde63d03acbd1fc9a15a5e56bef47c0ef7",
        "repo": "PaddleHub",
        "path": "modules/audio/svs/diffsinger/utils/cwt.py",
        "file_name": "cwt.py",
        "fun_name": "convert_continuos_f0",
        "commit_message": "Add Diffsinger Module (#2120)\n\n* add diffsinger\r\n\r\n* update README\r\n\r\n* update README",
        "code": "def convert_continuos_f0(f0):\n    \n    # get uv information as binary\n    f0 = np.copy(f0)\n    uv = np.float32(f0 != 0)\n\n    # get start and end of f0\n    if (f0 == 0).all():\n        print(\"| all of the f0 values are 0.\")\n        return uv, f0\n    start_f0 = f0[f0 != 0][0]\n    end_f0 = f0[f0 != 0][-1]\n\n    # padding start and end of f0 sequence\n    start_idx = np.where(f0 == start_f0)[0][0]\n    end_idx = np.where(f0 == end_f0)[0][-1]\n    f0[:start_idx] = start_f0\n    f0[end_idx:] = end_f0\n\n    # get non-zero frame index\n    nz_frames = np.where(f0 != 0)[0]\n\n    # perform linear interpolation\n    f = interp1d(nz_frames, f0[nz_frames])\n    cont_f0 = f(np.arange(0, f0.shape[0]))\n\n    return uv, cont_f0\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 168,
        "n_words": 97,
        "vocab_size": 58,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 159,
        "n_ast_nodes": 255,
        "n_identifiers": 19,
        "d_id": 10585,
        "documentation": {
            "docstring": "CONVERT F0 TO CONTINUOUS F0\n    Args:\n        f0 (ndarray): original f0 sequence with the shape (T)\n    Return:\n        (ndarray): continuous f0 with the shape (T)\n    ",
            "n_words": 23,
            "vocab_size": 15,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 116198,
        "commit_id": "5b1cd41a6202873e49c9ec43c770cf7d1f700adb",
        "repo": "mindsdb",
        "path": "tests/unit/test_executor.py",
        "file_name": "test_executor.py",
        "fun_name": "test_dates",
        "commit_message": "keep datetype from predictor",
        "code": "def test_dates(self, mock_handler):\n        df = pd.DataFrame([\n            {'a': 1, 'b': dt.datetime(2020, 1, 1)},\n            {'a': 2, 'b': dt.datetime(2020, 1, 2)},\n            {'a': 1, 'b': dt.datetime(2020, 1, 3)},\n        ])\n        self.set_handler(mock_handler, name='pg', tables={'tasks': df})\n\n        # --- use predictor ---\n        predictor = {\n            'name': 'task_model',\n            'predict': 'p',\n            'dtypes': {\n                'p': dtype.float,\n                'a': dtype.integer,\n                'b': dtype.categorical\n            },\n            'predicted_value': 3.14\n        }\n        self.set_predictor(predictor)\n        ret = self.command_executor.execute_command(parse_sql(f, dialect='mindsdb'))\n        assert ret.error_code is None\n\n        assert len(ret.data) == 2\n        # is last datetime value of a = 1\n        assert ret.data[0][1].isoformat() == dt.datetime(2020, 1, 3).isoformat()\n\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 297,
        "n_words": 81,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 198,
        "n_ast_nodes": 320,
        "n_identifiers": 26,
        "d_id": 25689,
        "documentation": {
            "docstring": "\n            SELECT a, last(b)\n            FROM (\n               SELECT res.a, res.b \n               FROM pg.tasks as source\n               JOIN mindsdb.task_model as res\n            ) \n            group by 1\n            order by a\n           ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 133,
            "language": "en"
        }
    },
    {
        "id": 220370,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/base_futures.py",
        "file_name": "base_futures.py",
        "fun_name": "isfuture",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def isfuture(obj):\n    \n    return (hasattr(obj.__class__, '_asyncio_future_blocking') and\n            obj._asyncio_future_blocking is not None)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 27,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 5,
        "d_id": 55982,
        "documentation": {
            "docstring": "Check for a Future.\n\n    This returns True when obj is a Future instance or is advertising\n    itself as duck-type compatible by setting _asyncio_future_blocking.\n    See comment in Future for more details.\n    ",
            "n_words": 30,
            "vocab_size": 26,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 261230,
        "commit_id": "5d8a1994620713c2e4226fb8e40fef7e81af1103",
        "repo": "scikit-learn",
        "path": "sklearn/utils/extmath.py",
        "file_name": "extmath.py",
        "fun_name": "density",
        "commit_message": "API Deprecate the extra keyword arguments of utils.extmath.density (#24523)\n\nCo-authored-by: Meekail Zain <34613774+Micky774@users.noreply.github.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def density(w, **kwargs):\n    \n    if kwargs:\n        warnings.warn(\n            \"Additional keyword arguments are deprecated in version 1.2 and will be\"\n            \" removed in version 1.4.\",\n            FutureWarning,\n        )\n\n    if hasattr(w, \"toarray\"):\n        d = float(w.nnz) / (w.shape[0] * w.shape[1])\n    else:\n        d = 0 if w is None else float((w != 0).sum()) / w.size\n    return d\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 126,
        "n_words": 50,
        "vocab_size": 42,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 82,
        "n_ast_nodes": 135,
        "n_identifiers": 13,
        "d_id": 76700,
        "documentation": {
            "docstring": "Compute density of a sparse vector.\n\n    Parameters\n    ----------\n    w : array-like\n        The sparse vector.\n    **kwargs : keyword arguments\n        Ignored.\n\n        .. deprecated:: 1.2\n            ``**kwargs`` were deprecated in version 1.2 and will be removed in\n            1.4.\n\n    Returns\n    -------\n    float\n        The density of w, between 0 and 1.\n    ",
            "n_words": 45,
            "vocab_size": 36,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 101219,
        "commit_id": "5e73437be47f2410439a3c6716de96354e6a0c94",
        "repo": "faceswap",
        "path": "lib/align/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "get_faces_in_frame",
        "commit_message": "lib.align updates:\n  - alignments.py\n    - Add typed dicts for imported alignments\n    - Explicitly check for presence of thumb value in alignments dict\n    - linting\n  - detected_face.py\n    - Typing\n    - Linting\n    - Legacy support for pre-aligned face\n    - Update dependencies to new property names",
        "code": "def get_faces_in_frame(self, frame_name):\n        \n        logger.trace(\"Getting faces for frame_name: '%s'\", frame_name)\n        return self._data.get(frame_name, {}).get(\"faces\", [])\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 36,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 20639,
        "documentation": {
            "docstring": " Obtain the faces from :attr:`data` associated with a given frame_name.\n\n        Parameters\n        ----------\n        frame_name: str\n            The frame name to return faces for. This should be the base name of the frame, not the\n            full path\n\n        Returns\n        -------\n        list\n            The list of face dictionaries that appear within the requested frame_name\n        ",
            "n_words": 48,
            "vocab_size": 39,
            "n_whitespaces": 131,
            "language": "en"
        }
    },
    {
        "id": 311446,
        "commit_id": "58b8c30221a6f6e5acbbe98b7e3298b03fb741f5",
        "repo": "core",
        "path": "tests/components/homekit_controller/test_alarm_control_panel.py",
        "file_name": "test_alarm_control_panel.py",
        "fun_name": "test_switch_change_alarm_state",
        "commit_message": "Improve homekit_controller tests (#65266)",
        "code": "async def test_switch_change_alarm_state(hass, utcnow):\n    \n    helper = await setup_test_component(hass, create_security_system_service)\n\n    await hass.services.async_call(\n        \"alarm_control_panel\",\n        \"alarm_arm_home\",\n        {\"entity_id\": \"alarm_control_panel.testdevice\"},\n        blocking=True,\n    )\n    helper.async_assert_service_values(\n        ServicesTypes.SECURITY_SYSTEM,\n        {\n            CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 0,\n        },\n    )\n\n    await hass.services.async_call(\n        \"alarm_control_panel\",\n        \"alarm_arm_away\",\n        {\"entity_id\": \"alarm_control_panel.testdevice\"},\n        blocking=True,\n    )\n    helper.async_assert_service_values(\n        ServicesTypes.SECURITY_SYSTEM,\n        {\n            CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 1,\n        },\n    )\n\n    await hass.services.async_call(\n        \"alarm_control_panel\",\n        \"alarm_arm_night\",\n        {\"entity_id\": \"alarm_control_panel.testdevice\"},\n        blocking=True,\n    )\n    helper.async_assert_service_values(\n        ServicesTypes.SECURITY_SYSTEM,\n        {\n            CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 2,\n        },\n    )\n\n    await hass.services.async_call(\n        \"alarm_control_panel\",\n        \"alarm_disarm\",\n        {\"entity_id\": \"alarm_control_panel.testdevice\"},\n        blocking=True,\n    )\n    helper.async_assert_service_values(\n        ServicesTypes.SECURITY_SYSTEM,\n        {\n            CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 3,\n        },\n    )\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 363,
        "n_words": 69,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 50,
        "token_counts": 177,
        "n_ast_nodes": 290,
        "n_identifiers": 14,
        "d_id": 110111,
        "documentation": {
            "docstring": "Test that we can turn a HomeKit alarm on and off again.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 265901,
        "commit_id": "9628dead07ccef9608b32906aa8194bc948e5a09",
        "repo": "netbox",
        "path": "netbox/netbox/tests/test_search.py",
        "file_name": "test_search.py",
        "fun_name": "test_cache_multiple_objects",
        "commit_message": "Closes #10560: New global search (#10676)\n\n* Initial work on new search backend\r\n\r\n* Clean up search backends\r\n\r\n* Return only the most relevant result per object\r\n\r\n* Clear any pre-existing cached entries on cache()\r\n\r\n* #6003: Implement global search functionality for custom field values\r\n\r\n* Tweak field weights & document guidance\r\n\r\n* Extend search() to accept a lookup type\r\n\r\n* Move get_registry() out of SearchBackend\r\n\r\n* Enforce object permissions when returning search results\r\n\r\n* Add indexers for remaining models\r\n\r\n* Avoid calling remove() on non-cacheable objects\r\n\r\n* Use new search backend by default\r\n\r\n* Extend search backend to filter by object type\r\n\r\n* Clean up search view form\r\n\r\n* Enable specifying lookup logic\r\n\r\n* Add indexes for value field\r\n\r\n* Remove object type selector from search bar\r\n\r\n* Introduce SearchTable and enable HTMX for results\r\n\r\n* Enable pagination\r\n\r\n* Remove legacy search backend\r\n\r\n* Cleanup\r\n\r\n* Use a UUID for CachedValue primary key\r\n\r\n* Refactoring search methods\r\n\r\n* Define max search results limit\r\n\r\n* Extend reindex command to support specifying particular models\r\n\r\n* Add clear() and size to SearchBackend\r\n\r\n* Optimize bulk caching performance\r\n\r\n* Highlight matched portion of field value\r\n\r\n* Performance improvements for reindexing\r\n\r\n* Started on search tests\r\n\r\n* Cleanup & docs\r\n\r\n* Documentation updates\r\n\r\n* Clean up SearchIndex\r\n\r\n* Flatten search registry to register by app_label.model_name\r\n\r\n* Clean up search backend classes\r\n\r\n* Clean up RestrictedGenericForeignKey and RestrictedPrefetch\r\n\r\n* Resolve migrations conflict",
        "code": "def test_cache_multiple_objects(self):\n        \n        sites = Site.objects.all()\n        search_backend.cache(sites)\n\n        content_type = ContentType.objects.get_for_model(Site)\n        self.assertEqual(\n            CachedValue.objects.filter(object_type=content_type).count(),\n            len(SiteIndex.fields) * sites.count()\n        )\n        for site in sites:\n            for field_name, weight in SiteIndex.fields:\n                self.assertTrue(\n                    CachedValue.objects.filter(\n                        object_type=content_type,\n                        object_id=site.pk,\n                        field=field_name,\n                        value=getattr(site, field_name),\n                        weight=weight\n                    ),\n                )\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 299,
        "n_words": 34,
        "vocab_size": 30,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 116,
        "n_ast_nodes": 180,
        "n_identifiers": 28,
        "d_id": 78238,
        "documentation": {
            "docstring": "\n        Test that multiples objects are cached appropriately\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 218844,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/lib2to3/pytree.py",
        "file_name": "pytree.py",
        "fun_name": "convert",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def convert(gr, raw_node):\n    \n    type, value, context, children = raw_node\n    if children or type in gr.number2symbol:\n        # If there's exactly one child, return that child instead of\n        # creating a new node.\n        if len(children) == 1:\n            return children[0]\n        return Node(type, children, context=context)\n    else:\n        return Leaf(type, value, context=context)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 104,
        "n_words": 46,
        "vocab_size": 38,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 63,
        "n_ast_nodes": 97,
        "n_identifiers": 11,
        "d_id": 55497,
        "documentation": {
            "docstring": "\n    Convert raw node information to a Node or Leaf instance.\n\n    This is passed to the parser driver which calls it whenever a reduction of a\n    grammar rule produces a new complete node, so that the tree is build\n    strictly bottom-up.\n    ",
            "n_words": 40,
            "vocab_size": 34,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 222741,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/command/install.py",
        "file_name": "install.py",
        "fun_name": "has_lib",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def has_lib(self):\n        \n        return (self.distribution.has_pure_modules() or\n                self.distribution.has_ext_modules())\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 42,
        "n_identifiers": 5,
        "d_id": 56722,
        "documentation": {
            "docstring": "Returns true if the current distribution has any Python\n        modules to install.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 48147,
        "commit_id": "3ed07474649b1e202f9b106105fef21f7b2cfddc",
        "repo": "airflow",
        "path": "scripts/in_container/verify_providers.py",
        "file_name": "verify_providers.py",
        "fun_name": "get_all_providers",
        "commit_message": "Seperate provider verification as standalone breeze command (#23454)\n\nThis is another step in simplifying and converting to Python all of\r\nthe CI/local development tooling.\r\n\r\nThis PR separates out verification of providers as a separate\r\nbreeze command `verify-provider-packages`. It was previously part of\r\n\"prepare_provider_packages.py\" but it has been now\r\nextracted to a separate in-container python file and it was\r\nwrapped with breeze's `verify-provider-packages` command.\r\n\r\nNo longer provider verification is run with \"preparing provider docs\"\r\nnor \"preparing provider packages\" - it's a standaline command.\r\n\r\nThis command is also used in CI now to run the tests:\r\n\r\n* all provider packages are built and created on CI together with\r\n  airflow version\r\n* the packages are installed inside the CI image and providers are\r\n  verified\r\n* the 2.1 version of Airflow is installed together with all 2.1\r\n  - compatible providers and provider verification is run there too.\r\n\r\nThis all is much simpler now - we got rediof some 500 lines of bash\r\ncode again in favour of breeze python code.\r\n\r\nFixes: #23430",
        "code": "def get_all_providers() -> List[str]:\n    \n    from setup import PROVIDERS_REQUIREMENTS\n\n    return list(PROVIDERS_REQUIREMENTS.keys())\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 9376,
        "documentation": {
            "docstring": "\n    Returns all providers for regular packages.\n    :return: list of providers that are considered for provider packages\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 95663,
        "commit_id": "9af098891a8243d08ee5ab6e51925a082135e3f2",
        "repo": "sentry",
        "path": "tests/sentry/api/endpoints/test_organization_metrics.py",
        "file_name": "test_organization_metrics.py",
        "fun_name": "test_orderby_percentile_with_many_fields_transactions_unsupported_fields",
        "commit_message": "feat(metrics): Support multi-field orderby for performance [INGEST-805] (#31162)\n\n* feat(metrics): Support metrics multi-field orderby queries\r\n\r\nAdds support for the performance table to the\r\nmetrics organization data endpoint",
        "code": "def test_orderby_percentile_with_many_fields_transactions_unsupported_fields(self):\n        \n        response = self.get_response(\n            self.organization.slug,\n            field=[\n                \"p50(sentry.transactions.measurements.lcp)\",\n                \"sum(user_misery)\",\n            ],\n            statsPeriod=\"1h\",\n            interval=\"1h\",\n            datasource=\"snuba\",\n            groupBy=[\"project_id\", \"transaction\"],\n            orderBy=\"p50(sentry.transactions.measurements.lcp)\",\n        )\n        assert response.status_code == 400\n        assert (\n            response.json()[\"detail\"]\n            == \"Multi-field select order by queries is not supported for metric user_misery\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 219,
        "n_words": 37,
        "vocab_size": 34,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 71,
        "n_ast_nodes": 123,
        "n_identifiers": 14,
        "d_id": 19226,
        "documentation": {
            "docstring": "\n        Test that contains a field in the `select` that is performance related but currently\n        not supported should return a 400\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 101502,
        "commit_id": "dc18c74eea0c7837a820d27628cb12b0824fa30e",
        "repo": "faceswap",
        "path": "lib/gui/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_result",
        "commit_message": "Bugfix: Preview for extract in batch mode",
        "code": "def get_result(self) -> Any:\n        \n        if not self._complete.is_set():\n            logger.warning(\"Aborting attempt to retrieve result from a LongRunningTask that is \"\n                           \"still running\")\n            return None\n        if self.err:\n            logger.debug(\"Error caught in thread\")\n            self._config.set_cursor_default(widget=self._widget)\n            raise self.err[1].with_traceback(self.err[2])\n\n        logger.debug(\"Getting result from thread\")\n        retval = self._queue.get()\n        logger.debug(\"Got result from thread\")\n        self._config.set_cursor_default(widget=self._widget)\n        return retval\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 182,
        "n_words": 45,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 23,
        "token_counts": 102,
        "n_ast_nodes": 177,
        "n_identifiers": 17,
        "d_id": 20914,
        "documentation": {
            "docstring": " Return the result from the given task.\n\n        Returns\n        -------\n        varies:\n            The result of the thread will depend on the given task. If a call is made to\n            :func:`get_result` prior to the thread completing its task then ``None`` will be\n            returned\n        ",
            "n_words": 40,
            "vocab_size": 30,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 186893,
        "commit_id": "39e8d14e1b221bf37526cc05ecc83beee30a3c57",
        "repo": "certbot",
        "path": "tools/finish_release.py",
        "file_name": "finish_release.py",
        "fun_name": "get_snap_revisions",
        "commit_message": "Set up 2.0 pre-releases (#9400)\n\n* update credential info\r\n\r\n* update release tooling to use candidate channel\r\n\r\n* split deploy jobs\r\n\r\n* pass parameter through\r\n\r\n* add 2.0 pipeline prerelease\r\n\r\n* add comments\r\n\r\n* quote file path",
        "code": "def get_snap_revisions(snap, version):\n    \n    print('Getting revision numbers for', snap, version)\n    cmd = ['snapcraft', 'status', snap]\n    process = subprocess.run(cmd, check=True, stdout=subprocess.PIPE, universal_newlines=True)\n    pattern = f'^\\s+candidate\\s+{version}\\s+(\\d+)\\s*'\n    revisions = re.findall(pattern, process.stdout, re.MULTILINE)\n    assert len(revisions) == SNAP_ARCH_COUNT, f'Unexpected number of snaps found for {snap} {version} (expected {SNAP_ARCH_COUNT}, found {len(revisions)})'\n    return revisions\n\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 70,
        "n_words": 46,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 79,
        "n_ast_nodes": 148,
        "n_identifiers": 19,
        "d_id": 45646,
        "documentation": {
            "docstring": "Finds the revisions for the snap and version in the candidate channel.\n\n    If you call this function without being logged in with snapcraft, it\n    will hang with no output.\n\n    :param str snap: the name of the snap on the snap store\n    :param str version: snap version number, e.g. 1.7.0\n\n    :returns: list of revision numbers\n    :rtype: `list` of `str`\n\n    :raises subprocess.CalledProcessError: if the snapcraft command\n        fails\n\n    :raises AssertionError: if the expected snaps are not found\n\n    ",
            "n_words": 74,
            "vocab_size": 55,
            "n_whitespaces": 108,
            "language": "en"
        }
    },
    {
        "id": 197054,
        "commit_id": "e0dc14eca132f37c5f49369eb4051eae37c9b119",
        "repo": "sympy",
        "path": "sympy/polys/factortools.py",
        "file_name": "factortools.py",
        "fun_name": "dup_zz_mignotte_bound",
        "commit_message": "Refactored import ordering in functions",
        "code": "def dup_zz_mignotte_bound(f, K):\n    \n    from sympy.functions.combinatorial.factorials import binomial\n    d = dup_degree(f)\n    delta = _ceil(d / 2)\n    delta2 = _ceil(delta / 2)\n\n    # euclidean-norm\n    eucl_norm = K.sqrt( sum( [cf**2 for cf in f] ) )\n\n    # biggest values of binomial coefficients (p. 538 of reference)\n    t1 = binomial(delta - 1, delta2)\n    t2 = binomial(delta - 1, delta2 - 1)\n\n    lc = K.abs(dup_LC(f, K))   # leading coefficient\n    bound = t1 * eucl_norm + t2 * lc   # (p. 538 of reference)\n    bound += dup_max_norm(f, K) # add max coeff for irreducible polys\n    bound = _ceil(bound / 2) * 2   # round up to even integer\n\n    return bound\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 155,
        "n_words": 104,
        "vocab_size": 65,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 123,
        "n_ast_nodes": 197,
        "n_identifiers": 24,
        "d_id": 48311,
        "documentation": {
            "docstring": "\n    The Knuth-Cohen variant of Mignotte bound for\n    univariate polynomials in `K[x]`.\n\n    Examples\n    ========\n\n    >>> from sympy.polys import ring, ZZ\n    >>> R, x = ring(\"x\", ZZ)\n\n    >>> f = x**3 + 14*x**2 + 56*x + 64\n    >>> R.dup_zz_mignotte_bound(f)\n    152\n\n    By checking `factor(f)` we can see that max coeff is 8\n\n    Also consider a case that `f` is irreducible for example `f = 2*x**2 + 3*x + 4`\n    To avoid a bug for these cases, we return the bound plus the max coefficient of `f`\n\n    >>> f = 2*x**2 + 3*x + 4\n    >>> R.dup_zz_mignotte_bound(f)\n    6\n\n    Lastly,To see the difference between the new and the old Mignotte bound\n    consider the irreducible polynomial::\n\n    >>> f = 87*x**7 + 4*x**6 + 80*x**5 + 17*x**4 + 9*x**3 + 12*x**2 + 49*x + 26\n    >>> R.dup_zz_mignotte_bound(f)\n    744\n\n    The new Mignotte bound is 744 whereas the old one (SymPy 1.5.1) is 1937664.\n\n\n    References\n    ==========\n\n    ..[1] [Abbott2013]_\n\n    ",
            "n_words": 149,
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            "language": "en"
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        "id": 37824,
        "commit_id": "2fbb237967f5d1b2eb65c2131954f23a24bd29ef",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_accelerate",
        "commit_message": "Add the auto_find_batch_size capability from Accelerate into Trainer (#17068)\n\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n- Adds auto_batch_size finder \r\n- Moves training loop to an inner training loop",
        "code": "def require_accelerate(test_case):\n    \n    return unittest.skipUnless(is_accelerate_available(), \"test requires accelerate\")(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 6873,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires accelerate. These tests are skipped when accelerate isn't installed.\n    ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 148500,
        "commit_id": "16861db653ec8166f73fc8480894f186a137e7bd",
        "repo": "freqtrade",
        "path": "freqtrade/misc.py",
        "file_name": "misc.py",
        "fun_name": "get_strategy_run_id",
        "commit_message": "Implement previous backtest result reuse when config and strategy did not change.",
        "code": "def get_strategy_run_id(strategy) -> str:\n    \n    digest = hashlib.sha1()\n    config = deepcopy(strategy.config)\n\n    # Options that have no impact on results of individual backtest.\n    not_important_keys = ('strategy_list', 'original_config', 'telegram', 'api_server')\n    for k in not_important_keys:\n        if k in config:\n            del config[k]\n\n    digest.update(rapidjson.dumps(config, default=str,\n                                  number_mode=rapidjson.NM_NATIVE).encode('utf-8'))\n    with open(strategy.__file__, 'rb') as fp:\n        digest.update(fp.read())\n    return digest.hexdigest().lower()\n\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 133,
        "n_words": 48,
        "vocab_size": 44,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 107,
        "n_ast_nodes": 184,
        "n_identifiers": 23,
        "d_id": 34273,
        "documentation": {
            "docstring": "\n    Generate unique identification hash for a backtest run. Identical config and strategy file will\n    always return an identical hash.\n    :param strategy: strategy object.\n    :return: hex string id.\n    ",
            "n_words": 27,
            "vocab_size": 26,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 260794,
        "commit_id": "ed3172b6c5c733906ce3aa2316c4ad60b5c26d10",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/_optics.py",
        "file_name": "_optics.py",
        "fun_name": "fit",
        "commit_message": "MAINT Parameters validation for OPTICS (#24326)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def fit(self, X, y=None):\n        \n        self._validate_params()\n\n        dtype = bool if self.metric in PAIRWISE_BOOLEAN_FUNCTIONS else float\n        if dtype == bool and X.dtype != bool:\n            msg = (\n                \"Data will be converted to boolean for\"\n                f\" metric {self.metric}, to avoid this warning,\"\n                \" you may convert the data prior to calling fit.\"\n            )\n            warnings.warn(msg, DataConversionWarning)\n\n        X = self._validate_data(X, dtype=dtype, accept_sparse=\"csr\")\n        if self.metric == \"precomputed\" and issparse(X):\n            with warnings.catch_warnings():\n                warnings.simplefilter(\"ignore\", SparseEfficiencyWarning)\n                # Set each diagonal to an explicit value so each point is its\n                # own neighbor\n                X.setdiag(X.diagonal())\n        memory = check_memory(self.memory)\n\n        (\n            self.ordering_,\n            self.core_distances_,\n            self.reachability_,\n            self.predecessor_,\n        ) = memory.cache(compute_optics_graph)(\n            X=X,\n            min_samples=self.min_samples,\n            algorithm=self.algorithm,\n            leaf_size=self.leaf_size,\n            metric=self.metric,\n            metric_params=self.metric_params,\n            p=self.p,\n            n_jobs=self.n_jobs,\n            max_eps=self.max_eps,\n        )\n\n        # Extract clusters from the calculated orders and reachability\n        if self.cluster_method == \"xi\":\n            labels_, clusters_ = cluster_optics_xi(\n                reachability=self.reachability_,\n                predecessor=self.predecessor_,\n                ordering=self.ordering_,\n                min_samples=self.min_samples,\n                min_cluster_size=self.min_cluster_size,\n                xi=self.xi,\n                predecessor_correction=self.predecessor_correction,\n            )\n            self.cluster_hierarchy_ = clusters_\n        elif self.cluster_method == \"dbscan\":\n            if self.eps is None:\n                eps = self.max_eps\n            else:\n                eps = self.eps\n\n            if eps > self.max_eps:\n                raise ValueError(\n                    \"Specify an epsilon smaller than %s. Got %s.\" % (self.max_eps, eps)\n                )\n\n            labels_ = cluster_optics_dbscan(\n                reachability=self.reachability_,\n                core_distances=self.core_distances_,\n                ordering=self.ordering_,\n                eps=eps,\n            )\n\n        self.labels_ = labels_\n        return self\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 908,
        "n_words": 179,
        "vocab_size": 132,
        "complexity": 10,
        "nloc": 60,
        "token_counts": 336,
        "n_ast_nodes": 528,
        "n_identifiers": 52,
        "d_id": 76498,
        "documentation": {
            "docstring": "Perform OPTICS clustering.\n\n        Extracts an ordered list of points and reachability distances, and\n        performs initial clustering using ``max_eps`` distance specified at\n        OPTICS object instantiation.\n\n        Parameters\n        ----------\n        X : {ndarray, sparse matrix} of shape (n_samples, n_features), or \\\n                (n_samples, n_samples) if metric='precomputed'\n            A feature array, or array of distances between samples if\n            metric='precomputed'. If a sparse matrix is provided, it will be\n            converted into CSR format.\n\n        y : Ignored\n            Not used, present for API consistency by convention.\n\n        Returns\n        -------\n        self : object\n            Returns a fitted instance of self.\n        ",
            "n_words": 87,
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            "language": "en"
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    },
    {
        "id": 245502,
        "commit_id": "af063a6f25ddae4de90646f86b2db824f3d00138",
        "repo": "mmdetection",
        "path": "mmdet/datasets/transforms/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "_filter_boxes",
        "commit_message": "[Refactor] Refactor pipelines with boxlist. (#8562)\n\n* Refactor pipelines and data_preprocesser by boxlist\r\n\r\n* Refactor browse_dataset.py\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* update\r\n\r\n* Update\r\n\r\n* Change with_box_wrapped to with_boxlist\r\n\r\n* Fix comments\r\n\r\n* Fix commits\r\n\r\n* Update  UT",
        "code": "def _filter_boxes(self, patch, boxes):\n        \n        center = boxes.centers.numpy()\n        mask = (center[:, 0] > patch[0]) * (center[:, 1] > patch[1]) * (\n            center[:, 0] < patch[2]) * (\n                center[:, 1] < patch[3])\n        return mask\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "d_id": 70808,
        "documentation": {
            "docstring": "Check whether the center of each box is in the patch.\n\n        Args:\n            patch (list[int]): The cropped area, [left, top, right, bottom].\n            boxes (numpy array, (N x 4)): Ground truth boxes.\n\n        Returns:\n            mask (numpy array, (N,)): Each box is inside or outside the patch.\n        ",
            "n_words": 43,
            "vocab_size": 36,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 120261,
        "commit_id": "92ca76a0395ad32423e681b6d6ce6d84c361852b",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "_normalize_index",
        "commit_message": "Skip normalization of unsigned indices",
        "code": "def _normalize_index(index, axis_size):\n  \n  if issubdtype(_dtype(index), np.unsignedinteger):\n    return index\n  if core.is_constant_dim(axis_size):\n    axis_size_val = _lax_const(index, axis_size)\n  else:\n    axis_size_val = lax.convert_element_type(core.dimension_as_value(axis_size),\n                                             _dtype(index))\n  return lax.select(\n    lax.lt(index, _lax_const(index, 0)),\n    lax.add(index, axis_size_val),\n    index)\n\n\nTAKE_ALONG_AXIS_DOC = \n\n@_wraps(np.take_along_axis, update_doc=False,\n        lax_description=TAKE_ALONG_AXIS_DOC)\n@partial(jit, static_argnames=('axis', 'mode'))",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.take_along_axis, update_doc=False,\n        lax_description=TAKE_ALONG_AXIS_DOC)\n@partial(jit, static_argnames=('axis', 'mode'))",
        "n_ast_errors": 1,
        "ast_levels": 13,
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        "vocab_size": 29,
        "complexity": 3,
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        "n_identifiers": 25,
        "d_id": 26806,
        "documentation": {
            "docstring": "Normalizes an index value in the range [-N, N) to the range [0, N).\nUnlike :func:`numpy.take_along_axis`, :func:`jax.numpy.take_along_axis` takes\nan optional ``mode`` parameter controlling how out-of-bounds indices should be\nhandled. By default, out-of-bounds indices are clamped into range. In a future\nchange, out-of-bounds indices will return invalid (e.g., ``NaN``) values\ninstead. See :attr:`jax.numpy.ndarray.at` for more discussion\nof out-of-bounds indexing in JAX.\n",
            "n_words": 60,
            "vocab_size": 51,
            "n_whitespaces": 53,
            "language": "en"
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    },
    {
        "id": 3604,
        "commit_id": "27b5ba338656b9adbfc8ebd90960a200a14d5935",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-looker/source_looker/streams.py",
        "file_name": "streams.py",
        "fun_name": "state_checkpoint_interval",
        "commit_message": ":tada: Source Looker: Migrate to native CDK (#9609)",
        "code": "def state_checkpoint_interval(self) -> Optional[int]:\n        \n        if self._is_finished:\n            return 1\n        return 100\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
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        "token_counts": 20,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 494,
        "documentation": {
            "docstring": "this is a workaround: the Airbyte CDK forces for save the latest state after reading of all records",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 206336,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/templatetags/tz.py",
        "file_name": "tz.py",
        "fun_name": "timezone_tag",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def timezone_tag(parser, token):\n    \n    bits = token.split_contents()\n    if len(bits) != 2:\n        raise TemplateSyntaxError(\"'%s' takes one argument (timezone)\" % bits[0])\n    tz = parser.compile_filter(bits[1])\n    nodelist = parser.parse((\"endtimezone\",))\n    parser.delete_first_token()\n    return TimezoneNode(nodelist, tz)\n\n\n@register.tag(\"get_current_timezone\")",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag(\"get_current_timezone\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 56,
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        "vocab_size": 27,
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        "token_counts": 67,
        "n_ast_nodes": 126,
        "n_identifiers": 15,
        "d_id": 51491,
        "documentation": {
            "docstring": "\n    Enable a given time zone just for this block.\n\n    The ``timezone`` argument must be an instance of a ``tzinfo`` subclass, a\n    time zone name, or ``None``. If it is ``None``, the default time zone is\n    used within the block.\n\n    Sample usage::\n\n        {% timezone \"Europe/Paris\" %}\n            It is {{ now }} in Paris.\n        {% endtimezone %}\n    ",
            "n_words": 55,
            "vocab_size": 43,
            "n_whitespaces": 99,
            "language": "en"
        }
    },
    {
        "id": 289281,
        "commit_id": "c717fd19de01fc822d146cc5e353959dfa86d5f7",
        "repo": "core",
        "path": "homeassistant/components/gtfs/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "update",
        "commit_message": "Move attribution to standalone attribute [e-g] (#80513)",
        "code": "def update(self) -> None:\n        \n        with self.lock:\n            # Fetch valid stop information once\n            if not self._origin:\n                stops = self._pygtfs.stops_by_id(self.origin)\n                if not stops:\n                    self._available = False\n                    _LOGGER.warning(\"Origin stop ID %s not found\", self.origin)\n                    return\n                self._origin = stops[0]\n\n            if not self._destination:\n                stops = self._pygtfs.stops_by_id(self.destination)\n                if not stops:\n                    self._available = False\n                    _LOGGER.warning(\n                        \"Destination stop ID %s not found\", self.destination\n                    )\n                    return\n                self._destination = stops[0]\n\n            self._available = True\n\n            # Fetch next departure\n            self._departure = get_next_departure(\n                self._pygtfs,\n                self.origin,\n                self.destination,\n                self._offset,\n                self._include_tomorrow,\n            )\n\n            # Define the state as a UTC timestamp with ISO 8601 format\n            if not self._departure:\n                self._state = None\n            else:\n                self._state = self._departure[\"departure_time\"].replace(\n                    tzinfo=dt_util.UTC\n                )\n\n            # Fetch trip and route details once, unless updated\n            if not self._departure:\n                self._trip = None\n            else:\n                trip_id = self._departure[\"trip_id\"]\n                if not self._trip or self._trip.trip_id != trip_id:\n                    _LOGGER.debug(\"Fetching trip details for %s\", trip_id)\n                    self._trip = self._pygtfs.trips_by_id(trip_id)[0]\n\n                route_id = self._departure[\"route_id\"]\n                if not self._route or self._route.route_id != route_id:\n                    _LOGGER.debug(\"Fetching route details for %s\", route_id)\n                    self._route = self._pygtfs.routes_by_id(route_id)[0]\n\n            # Fetch agency details exactly once\n            if self._agency is None and self._route:\n                _LOGGER.debug(\"Fetching agency details for %s\", self._route.agency_id)\n                try:\n                    self._agency = self._pygtfs.agencies_by_id(self._route.agency_id)[0]\n                except IndexError:\n                    _LOGGER.warning(\n                        \"Agency ID '%s' was not found in agency table, \"\n                        \"you may want to update the routes database table \"\n                        \"to fix this missing reference\",\n                        self._route.agency_id,\n                    )\n                    self._agency = False\n\n            # Assign attributes, icon and name\n            self.update_attributes()\n\n            if self._agency:\n                self._attr_attribution = self._agency.agency_name\n            else:\n                self._attr_attribution = None\n\n            if self._route:\n                self._icon = ICONS.get(self._route.route_type, ICON)\n            else:\n                self._icon = ICON\n\n            name = (\n                f\"{getattr(self._agency, 'agency_name', DEFAULT_NAME)} \"\n                f\"{self.origin} to {self.destination} next departure\"\n            )\n            if not self._departure:\n                name = f\"{DEFAULT_NAME}\"\n            self._name = self._custom_name or name\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 17,
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        "d_id": 88424,
        "documentation": {
            "docstring": "Get the latest data from GTFS and update the states.",
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    },
    {
        "id": 293677,
        "commit_id": "aa57907c1878b5d7bdaf258e0b135c189abb8f27",
        "repo": "core",
        "path": "homeassistant/components/discord/notify.py",
        "file_name": "notify.py",
        "fun_name": "file_exists",
        "commit_message": "Improve logging for Discord integration (#68160)",
        "code": "def file_exists(self, filename):\n        \n        if not self.hass.config.is_allowed_path(filename):\n            _LOGGER.warning(\"Path not allowed: %s\", filename)\n            return False\n        if not os.path.isfile(filename):\n            _LOGGER.warning(\"Not a file: %s\", filename)\n            return False\n        return True\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "d_id": 92734,
        "documentation": {
            "docstring": "Check if a file exists on disk and is in authorized path.",
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            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 114397,
        "commit_id": "44d7ef0e08e5144870ad2831ce6e221f9044c47c",
        "repo": "mindsdb",
        "path": "mindsdb/api/http/namespaces/util.py",
        "file_name": "util.py",
        "fun_name": "get",
        "commit_message": "'files' route",
        "code": "def get(self):\n        \n        response = {\n            'learn': False,\n            'predict': False,\n            'analyse': False\n        }\n\n        if os.name != 'posix':\n            return response\n\n        for process_type in response:\n            processes_dir = Path(tempfile.gettempdir()).joinpath(f'mindsdb/processes/{process_type}/')\n            if not processes_dir.is_dir():\n                continue\n            process_marks = [x.name for x in processes_dir.iterdir()]\n            for p_mark in process_marks:\n                pid = int(p_mark.split('-')[0])\n                try:\n                    psutil.Process(pid)\n                except Exception:\n                    processes_dir.joinpath(p_mark).unlink()\n                else:\n                    response[process_type] = True\n\n        return response\n\n\n@ns_conf.route('/telemetry')",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "@ns_conf.route('/telemetry')",
        "n_ast_errors": 1,
        "ast_levels": 16,
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        "n_identifiers": 25,
        "d_id": 25182,
        "documentation": {
            "docstring": " Checks server use native for learn or analyse.\n            Will return right result only on Linux.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 70612,
        "commit_id": "284380672da91b5f1d5ea35e01b5b86d7a534dbb",
        "repo": "wagtail",
        "path": "wagtail/admin/views/workflows.py",
        "file_name": "workflows.py",
        "fun_name": "get_task_type_filter_choices",
        "commit_message": "add another helper method get_task_type_filter_choices",
        "code": "def get_task_type_filter_choices(self):\n        \n        task_type_choices = [\n            (model, model.get_verbose_name())\n            for model in self.task_models\n        ]\n        task_type_choices.sort(key=lambda task_type: task_type[1].lower())\n        return task_type_choices\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 74,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 45,
        "n_ast_nodes": 73,
        "n_identifiers": 10,
        "d_id": 15532,
        "documentation": {
            "docstring": "\n        To be called after dispatch(); returns the list of task type choices for filter on \"existing task\" tab\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 72248,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_workflows.py",
        "file_name": "test_workflows.py",
        "fun_name": "test_workflow_action_via_edit_view",
        "commit_message": "Reformat with black",
        "code": "def test_workflow_action_via_edit_view(self):\n        \n        # Post\n        self.client.post(\n            reverse(\"wagtailadmin_pages:edit\", args=(self.page.id,)),\n            {\n                \"title\": \"This title was edited while approving\",\n                \"slug\": str(self.page.slug),\n                \"content\": str(self.page.content),\n                \"action-workflow-action\": \"True\",\n                \"workflow-action-name\": \"approve\",\n                \"workflow-action-extra-data\": '{\"comment\": \"my comment\"}',\n            },\n        )\n\n        # Check that the workflow was approved\n\n        workflow_state = WorkflowState.objects.get(\n            page=self.page, requested_by=self.submitter\n        )\n\n        self.assertEqual(workflow_state.status, workflow_state.STATUS_APPROVED)\n\n        # Check that the task was approved\n\n        task_state = workflow_state.current_task_state\n\n        self.assertEqual(task_state.status, task_state.STATUS_APPROVED)\n\n        # Check that the comment was added to the task state correctly\n\n        self.assertEqual(task_state.comment, \"my comment\")\n\n        # Check that page edits made at the same time as the action have been saved\n        page = Page.objects.get(id=self.page.id)\n        self.assertEqual(\n            page.get_latest_revision_as_page().title,\n            \"This title was edited while approving\",\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 374,
        "n_words": 99,
        "vocab_size": 67,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 160,
        "n_ast_nodes": 271,
        "n_identifiers": 26,
        "d_id": 15861,
        "documentation": {
            "docstring": "\n        Posting to the 'edit' view with 'action-workflow-action' set should perform the given workflow action in addition to updating page content\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 22685,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "linear-algebra-python/src/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_zeroVector",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def test_zeroVector(self):\n        \n        self.assertTrue(zeroVector(10).__str__().count(\"0\") == 10)\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 26,
        "n_ast_nodes": 48,
        "n_identifiers": 6,
        "d_id": 4413,
        "documentation": {
            "docstring": "\n        test for the global function zeroVector(...)\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 57498,
        "commit_id": "daddc2985f0cba6c6e0ae3903232cbca155e7e91",
        "repo": "prefect",
        "path": "tests/infrastructure/test_kubernetes_job.py",
        "file_name": "test_kubernetes_job.py",
        "fun_name": "test_user_can_supply_a_sidecar_container_and_volume",
        "commit_message": "Port KubernetesFlowRunner tests to KubernetesJob tests",
        "code": "def test_user_can_supply_a_sidecar_container_and_volume(self):\n        \n        manifest = KubernetesJob(\n            command=[\"echo\", \"hello\"],\n            job={\n                \"apiVersion\": \"batch/v1\",\n                \"kind\": \"Job\",\n                \"metadata\": {\"labels\": {}},\n                \"spec\": {\n                    \"template\": {\n                        \"spec\": {\n                            \"parallelism\": 1,\n                            \"completions\": 1,\n                            \"restartPolicy\": \"Never\",\n                            \"containers\": [\n                                {\n                                    \"name\": \"prefect-job\",\n                                    \"env\": [],\n                                },\n                                {\n                                    \"name\": \"my-sidecar\",\n                                    \"image\": \"cool-peeps/cool-code:latest\",\n                                    \"volumeMounts\": [\n                                        {\"name\": \"data-volume\", \"mountPath\": \"/data/\"}\n                                    ],\n                                },\n                            ],\n                            \"volumes\": [\n                                {\"name\": \"data-volume\", \"hostPath\": \"/all/the/data/\"}\n                            ],\n                        }\n                    }\n                },\n            },\n        ).build_job()\n\n        pod = manifest[\"spec\"][\"template\"][\"spec\"]\n\n        assert pod[\"volumes\"] == [{\"name\": \"data-volume\", \"hostPath\": \"/all/the/data/\"}]\n\n        # the prefect-job container is still populated\n        assert pod[\"containers\"][0][\"name\"] == \"prefect-job\"\n        assert pod[\"containers\"][0][\"command\"] == [\"echo\", \"hello\"]\n\n        assert pod[\"containers\"][1] == {\n            \"name\": \"my-sidecar\",\n            \"image\": \"cool-peeps/cool-code:latest\",\n            \"volumeMounts\": [{\"name\": \"data-volume\", \"mountPath\": \"/data/\"}],\n        }\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 26,
        "n_whitespaces": 989,
        "n_words": 101,
        "vocab_size": 65,
        "complexity": 1,
        "nloc": 43,
        "token_counts": 218,
        "n_ast_nodes": 422,
        "n_identifiers": 8,
        "d_id": 11673,
        "documentation": {
            "docstring": "The user can supply a custom base job that includes more complex\n        modifications, like a sidecar container and volumes",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 63420,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "addCondition",
        "commit_message": "upd; format",
        "code": "def addCondition(self, *fns, **kwargs):\n        \n        for fn in fns:\n            self.parseAction.append(conditionAsParseAction(fn, message=kwargs.get('message'),\n                                                           fatal=kwargs.get('fatal', False)))\n\n        self.callDuringTry = self.callDuringTry or kwargs.get(\"callDuringTry\", False)\n        return self\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 117,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 66,
        "n_ast_nodes": 107,
        "n_identifiers": 12,
        "d_id": 13297,
        "documentation": {
            "docstring": "Add a boolean predicate function to expression's list of parse actions. See\n        :class:`setParseAction` for function call signatures. Unlike ``setParseAction``,\n        functions passed to ``addCondition`` need to return boolean success/fail of the condition.\n\n        Optional keyword arguments:\n        - message = define a custom message to be used in the raised exception\n        - fatal   = if True, will raise ParseFatalException to stop parsing immediately; otherwise will raise ParseException\n\n        Example::\n\n            integer = Word(nums).setParseAction(lambda toks: int(toks[0]))\n            year_int = integer.copy()\n            year_int.addCondition(lambda toks: toks[0] >= 2000, message=\"Only support years 2000 and later\")\n            date_str = year_int + '/' + integer + '/' + integer\n\n            result = date_str.parseString(\"1999/12/31\")  # -> Exception: Only support years 2000 and later (at char 0), (line:1, col:1)\n        ",
            "n_words": 112,
            "vocab_size": 82,
            "n_whitespaces": 219,
            "language": "en"
        }
    },
    {
        "id": 281416,
        "commit_id": "42b1acf5c3d2f9e9922ac8c4e956fffc08a5d7ae",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/stocks/due_diligence/dd_controller.py",
        "file_name": "dd_controller.py",
        "fun_name": "call_arktrades",
        "commit_message": "Add an API wrapper for terminal functions to be used in python (#1170)\n\n* Initial implementation of the API wrapper for stocks/disc\r\n\r\n* Create a file for helper classes\r\n\r\n* Move models namespace class where it belongs... TO THE HELPER_CLASSES🚀\r\n\r\n* Add backtesting api wrapper\r\n\r\n* Add ba api wrapper\r\n\r\n* Add dps api wrapper\r\n\r\n* Fix flake8 warnings in command help strings\r\n\r\n* Add comparison analysis models\r\n\r\n* Add dd api wrapper\r\n\r\n* Add fa api wrapper\r\n\r\n* Add gov api wrapper\r\n\r\n* Add ins api wrapper *note the note\r\n\r\n* Add options api wrapper *note the note\r\n\r\n* Add prediction api wrapper\r\n\r\n* Add api support for importing models from both local and common contexts\r\n\r\n* Add qa api wrapper\r\n\r\n* Add screener api wrapper *note the note\r\n\r\n* Fix typos in sia controller\r\n\r\n* Add sia api wrapper\r\n\r\n* Add ta api wrapper\r\n\r\n* Disable linting for specific lines that fail in CI\r\n\r\n* Remove deprecated parameter\r\n\r\n* Add exception handling when prediction packages are not installed",
        "code": "def call_arktrades(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            add_help=False,\n            prog=\"arktrades\",\n            description=,\n        )\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            help=\"Limit of rows to show\",\n            dest=\"limit\",\n            default=10,\n            type=check_positive,\n        )\n        parser.add_argument(\n            \"-s\",\n            \"--show_ticker\",\n            action=\"store_true\",\n            default=False,\n            help=\"Flag to show ticker in table\",\n            dest=\"show_ticker\",\n        )\n        if other_args and \"-\" not in other_args[0][0]:\n            other_args.insert(0, \"-l\")\n        ns_parser = parse_known_args_and_warn(\n            parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n        if ns_parser:\n            ark_view.display_ark_trades(\n                ticker=self.ticker,\n                num=ns_parser.limit,\n                export=ns_parser.export,\n                show_ticker=ns_parser.show_ticker,\n            )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 405,
        "n_words": 59,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 36,
        "token_counts": 143,
        "n_ast_nodes": 229,
        "n_identifiers": 28,
        "d_id": 83747,
        "documentation": {
            "docstring": "Process arktrades command\n                Get trades for ticker across all ARK funds.\n            ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 258898,
        "commit_id": "1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_ridge.py",
        "file_name": "_ridge.py",
        "fun_name": "_solve_svd_design_matrix",
        "commit_message": "MNT Update black to stable version (#22474)",
        "code": "def _solve_svd_design_matrix(self, alpha, y, sqrt_sw, X_mean, singvals_sq, U, UT_y):\n        \n        w = ((singvals_sq + alpha) ** -1) - (alpha**-1)\n        if self.fit_intercept:\n            # detect intercept column\n            normalized_sw = sqrt_sw / np.linalg.norm(sqrt_sw)\n            intercept_dim = _find_smallest_angle(normalized_sw, U)\n            # cancel the regularization for the intercept\n            w[intercept_dim] = -(alpha**-1)\n        c = np.dot(U, self._diag_dot(w, UT_y)) + (alpha**-1) * y\n        G_inverse_diag = self._decomp_diag(w, U) + (alpha**-1)\n        if len(y.shape) != 1:\n            # handle case where y is 2-d\n            G_inverse_diag = G_inverse_diag[:, np.newaxis]\n        return G_inverse_diag, c\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 202,
        "n_words": 76,
        "vocab_size": 57,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 143,
        "n_ast_nodes": 220,
        "n_identifiers": 25,
        "d_id": 75474,
        "documentation": {
            "docstring": "Compute dual coefficients and diagonal of G^-1.\n\n        Used when we have an SVD decomposition of X\n        (n_samples > n_features and X is dense).\n        ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 215988,
        "commit_id": "f2a783643de61cac1ff3288b40241e5ce6e1ddc8",
        "repo": "salt",
        "path": "tests/pytests/functional/modules/state/test_state.py",
        "file_name": "test_state.py",
        "fun_name": "test_parallel_state_with_long_tag",
        "commit_message": "Update to latest ``pyupgrade`` hook. Stop skipping it on CI.\n\nSigned-off-by: Pedro Algarvio <palgarvio@vmware.com>",
        "code": "def test_parallel_state_with_long_tag(state, state_tree):\n    \n    short_command = \"helloworld\"\n    long_command = short_command * 25\n    sls_contents = .format(\n        short_command, long_command\n    )\n    with pytest.helpers.temp_file(\"issue-49738.sls\", sls_contents, state_tree):\n        ret = state.sls(\n            \"issue-49738\",\n            __pub_jid=\"1\",  # Because these run in parallel we need a fake JID\n        )\n\n    comments = sorted(x.comment for x in ret)\n    expected = sorted(\n        'Command \"{}\" run'.format(x) for x in (short_command, long_command)\n    )\n    assert comments == expected, \"{} != {}\".format(comments, expected)\n\n\n@pytest.mark.skip_on_darwin(reason=\"Test is broken on macosx\")\n@pytest.mark.skip_on_windows(\n    reason=(\n        \"Functional testing this on windows raises unicode errors. \"\n        \"Tested in tests/pytests/integration/modules/state/test_state.py\"\n    )\n)",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.skip_on_darwin(reason=\"Test is broken on macosx\")\n@pytest.mark.skip_on_windows(\n    reason=(\n        \"Functional testing this on windows raises unicode errors. \"\n        \"Tested in tests/pytests/integration/modules/state/test_state.py\"\n    )\n)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 184,
        "n_words": 86,
        "vocab_size": 67,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 97,
        "n_ast_nodes": 209,
        "n_identifiers": 22,
        "d_id": 54306,
        "documentation": {
            "docstring": "\n    This tests the case where the state being executed has a long ID dec or\n    name and states are being run in parallel. The filenames used for the\n    parallel state cache were previously based on the tag for each chunk,\n    and longer ID decs or name params can cause the cache file to be longer\n    than the operating system's max file name length. To counter this we\n    instead generate a SHA1 hash of the chunk's tag to use as the cache\n    filename. This test will ensure that long tags don't cause caching\n    failures.\n\n    See https://github.com/saltstack/salt/issues/49738 for more info.\n    \n    test_cmd_short:\n      cmd.run:\n        - name: {}\n        - parallel: True\n\n    test_cmd_long:\n      cmd.run:\n        - name: {}\n        - parallel: True\n    ",
            "n_words": 114,
            "vocab_size": 80,
            "n_whitespaces": 193,
            "language": "en"
        }
    },
    {
        "id": 5992,
        "commit_id": "89d18365c41c4ded68edd2095349ce4a6caf5d18",
        "repo": "ludwig",
        "path": "ludwig/datasets/mnist/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "process_downloaded_dataset",
        "commit_message": "Removes skimage and imageio dependencies replacing imsave with torchvision.utils.save_image (#1694)",
        "code": "def process_downloaded_dataset(self):\n        \n        makedirs(self.processed_temp_path, exist_ok=True)\n        for dataset in [\"training\", \"testing\"]:\n            print(f\">>> create ludwig formatted {dataset} data\")\n            labels, images = self.read_source_dataset(dataset, self.raw_dataset_path)\n            self.write_output_dataset(labels, images, os.path.join(self.processed_temp_path, dataset))\n        self.output_training_and_test_data()\n        rename(self.processed_temp_path, self.processed_dataset_path)\n        print(\">>> completed data preparation\")\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 106,
        "n_words": 31,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 84,
        "n_ast_nodes": 141,
        "n_identifiers": 18,
        "d_id": 901,
        "documentation": {
            "docstring": "Read the training and test directories and write out a csv containing the training path and the\n        label.",
            "n_words": 18,
            "vocab_size": 13,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 155483,
        "commit_id": "b541b6c18e6fb4515e998b9b4f88528490cf69c6",
        "repo": "modin",
        "path": "modin/pandas/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "stack",
        "commit_message": "REFACTOR-#3948: Use `__constructor__` in `DataFrame` and `Series` classes (#5485)\n\nSigned-off-by: Anatoly Myachev <anatoly.myachev@intel.com>",
        "code": "def stack(self, level=-1, dropna=True):  # noqa: PR01, RT01, D200\n        \n        if not isinstance(self.columns, pandas.MultiIndex) or (\n            isinstance(self.columns, pandas.MultiIndex)\n            and is_list_like(level)\n            and len(level) == self.columns.nlevels\n        ):\n            return self._reduce_dimension(\n                query_compiler=self._query_compiler.stack(level, dropna)\n            )\n        else:\n            return self.__constructor__(\n                query_compiler=self._query_compiler.stack(level, dropna)\n            )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 171,
        "n_words": 35,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 95,
        "n_ast_nodes": 148,
        "n_identifiers": 15,
        "d_id": 36398,
        "documentation": {
            "docstring": "\n        Stack the prescribed level(s) from columns to index.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 38629,
        "commit_id": "5fdb54ece78b5d277fe26a3865beca8da0430495",
        "repo": "transformers",
        "path": "examples/research_projects/information-gain-filtration/igf/igf.py",
        "file_name": "igf.py",
        "fun_name": "set_seed",
        "commit_message": "Add Information Gain Filtration algorithm (#16953)\n\n* Add information gain filtration algorithm\r\n\r\n* Complying with black requirements\r\n\r\n* Added author\r\n\r\n* Fixed import order\r\n\r\n* flake8 corrections\r\n\r\nCo-authored-by: Javier Turek <javier.turek@intel.com>",
        "code": "def set_seed(seed):\n    \n    random.seed(seed)\n    np.random.seed(seed)\n    torch.manual_seed(seed)\n    torch.cuda.manual_seed_all(seed)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 34,
        "n_ast_nodes": 59,
        "n_identifiers": 8,
        "d_id": 6997,
        "documentation": {
            "docstring": "\n    For reproducible training\n\n    Args:\n        seed: A seed for reproducible training\n\n    ",
            "n_words": 10,
            "vocab_size": 8,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 34046,
        "commit_id": "44eaa2b3036c5c9a83ed781e08e3dc50aae193a9",
        "repo": "transformers",
        "path": "src/transformers/modeling_tf_utils.py",
        "file_name": "modeling_tf_utils.py",
        "fun_name": "test_step",
        "commit_message": "Update TF test_step to match train_step (#15111)\n\n* Update TF test_step to match train_step\r\n\r\n* Update compile() warning to be clearer about what to pass",
        "code": "def test_step(self, data):\n        \n        data = data_adapter.expand_1d(data)\n        x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data)\n        # These next two lines differ from the base method - they avoid issues when the labels are in\n        # the input dict (and loss is computed internally)\n        if y is None and \"labels\" in x:\n            y = x[\"labels\"]  # Stops confusion with metric computations\n        elif y is None and \"input_ids\" in x:\n            # Just make any kind of dummy array to make loss work\n            y = tf.zeros(tf.shape(x[\"input_ids\"])[0], dtype=tf.int64)\n        y_pred = self(x, training=False)\n        self.compiled_loss(y, y_pred, sample_weight, regularization_losses=self.losses)\n        # Updates stateful loss metrics.\n        if isinstance(y_pred, TFSeq2SeqLMOutput) and isinstance(y, tf.Tensor):\n            y_pred = y_pred[\"logits\"]\n        self.compiled_metrics.update_state(y, y_pred, sample_weight)\n        # Collect metrics to return\n        return_metrics = {}\n        for metric in self.metrics:\n            result = metric.result()\n            if isinstance(result, dict):\n                return_metrics.update(result)\n            else:\n                return_metrics[metric.name] = result\n        # These next two lines are also not in the base method - they correct the displayed metrics\n        # when we're using a dummy loss, to avoid a bogus \"loss_loss\" value being shown.\n        if \"loss\" in return_metrics and \"loss_loss\" in return_metrics:\n            del return_metrics[\"loss_loss\"]\n        return return_metrics\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_whitespaces": 425,
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        "complexity": 11,
        "nloc": 22,
        "token_counts": 196,
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        "n_identifiers": 31,
        "d_id": 6190,
        "documentation": {
            "docstring": "\n        A modification of Keras's default test_step that cleans up the printed metrics when we use a dummy loss.\n        ",
            "n_words": 18,
            "vocab_size": 18,
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            "language": "en"
        }
    },
    {
        "id": 132330,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/sync_client.py",
        "file_name": "sync_client.py",
        "fun_name": "get_cloud_sync_client",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def get_cloud_sync_client(remote_path):\n    \n    if remote_path.startswith(S3_PREFIX):\n        if not distutils.spawn.find_executable(\"aws\"):\n            raise ValueError(\n                \"Upload uri starting with '{}' requires awscli tool\"\n                \" to be installed\".format(S3_PREFIX)\n            )\n        sync_up_template = (\n            \"aws s3 sync {source} {target} \" \"--only-show-errors {options}\"\n        )\n        sync_down_template = sync_up_template\n        delete_template = (\n            \"aws s3 rm {target} --recursive \" \"--only-show-errors {options}\"\n        )\n        exclude_template = \"--exclude '{pattern}'\"\n    elif remote_path.startswith(GS_PREFIX):\n        if not distutils.spawn.find_executable(\"gsutil\"):\n            raise ValueError(\n                \"Upload uri starting with '{}' requires gsutil tool\"\n                \" to be installed\".format(GS_PREFIX)\n            )\n        sync_up_template = \"gsutil rsync -r {options} {source} {target}\"\n        sync_down_template = sync_up_template\n        delete_template = \"gsutil rm -r {options} {target}\"\n        exclude_template = \"-x '{regex_pattern}'\"\n    elif remote_path.startswith(HDFS_PREFIX):\n        if not distutils.spawn.find_executable(\"hdfs\"):\n            raise ValueError(\n                \"Upload uri starting with '{}' requires hdfs tool\"\n                \" to be installed\".format(HDFS_PREFIX)\n            )\n        sync_up_template = \"hdfs dfs -put -f {source} {target}\"\n        sync_down_template = \"hdfs dfs -get -f {source} {target}\"\n        delete_template = \"hdfs dfs -rm -r {target}\"\n        exclude_template = None\n    else:\n        raise ValueError(\n            f\"Upload uri must start with one of: {ALLOWED_REMOTE_PREFIXES} \"\n            f\"(is: `{remote_path}`)\"\n        )\n    return CommandBasedClient(\n        sync_up_template, sync_down_template, delete_template, exclude_template\n    )\n\n\n@PublicAPI(stability=\"beta\")",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@PublicAPI(stability=\"beta\")",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 524,
        "n_words": 164,
        "vocab_size": 76,
        "complexity": 7,
        "nloc": 43,
        "token_counts": 159,
        "n_ast_nodes": 324,
        "n_identifiers": 19,
        "d_id": 29740,
        "documentation": {
            "docstring": "Returns a CommandBasedClient that can sync to/from remote storage.\n\n    Args:\n        remote_path (str): Path to remote storage (S3, GS or HDFS).\n\n    Raises:\n        ValueError if malformed remote_dir.\n    ",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 288758,
        "commit_id": "117c12d135039797e5c00e9f1c87ece7f4be13e0",
        "repo": "core",
        "path": "tests/components/homekit_controller/test_climate.py",
        "file_name": "test_climate.py",
        "fun_name": "test_hvac_mode_vs_hvac_action_current_mode_wrong",
        "commit_message": "Fix Eve Thermo always showing as heating in homekit_controller even when off (#80019)",
        "code": "async def test_hvac_mode_vs_hvac_action_current_mode_wrong(hass, utcnow):\n    \n    helper = await setup_test_component(hass, create_thermostat_service)\n\n    await helper.async_update(\n        ServicesTypes.THERMOSTAT,\n        {\n            CharacteristicsTypes.TEMPERATURE_CURRENT: 22,\n            CharacteristicsTypes.TEMPERATURE_TARGET: 21,\n            CharacteristicsTypes.HEATING_COOLING_CURRENT: 1,\n            CharacteristicsTypes.HEATING_COOLING_TARGET: 0,\n            CharacteristicsTypes.RELATIVE_HUMIDITY_CURRENT: 50,\n            CharacteristicsTypes.RELATIVE_HUMIDITY_TARGET: 45,\n        },\n    )\n\n    state = await helper.poll_and_get_state()\n    assert state.state == \"off\"\n    assert state.attributes[\"hvac_action\"] == \"idle\"\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 147,
        "n_words": 39,
        "vocab_size": 34,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 89,
        "n_ast_nodes": 140,
        "n_identifiers": 19,
        "d_id": 87911,
        "documentation": {
            "docstring": "Check that we cope with buggy HEATING_COOLING_CURRENT.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 203569,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "url_params_from_lookup_dict",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def url_params_from_lookup_dict(lookups):\n    \n    params = {}\n    if lookups and hasattr(lookups, \"items\"):\n        for k, v in lookups.items():\n            if callable(v):\n                v = v()\n            if isinstance(v, (tuple, list)):\n                v = \",\".join(str(x) for x in v)\n            elif isinstance(v, bool):\n                v = (\"0\", \"1\")[v]\n            else:\n                v = str(v)\n            params[k] = v\n    return params\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 181,
        "n_words": 47,
        "vocab_size": 31,
        "complexity": 8,
        "nloc": 14,
        "token_counts": 103,
        "n_ast_nodes": 171,
        "n_identifiers": 15,
        "d_id": 50449,
        "documentation": {
            "docstring": "\n    Convert the type of lookups specified in a ForeignKey limit_choices_to\n    attribute to a dictionary of query parameters\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 177315,
        "commit_id": "8a325d26aa7fdd3a72580c4720fa97f971bbefcb",
        "repo": "networkx",
        "path": "networkx/algorithms/bipartite/matrix.py",
        "file_name": "matrix.py",
        "fun_name": "from_biadjacency_matrix",
        "commit_message": "Use scipy.sparse array datastructure (#6037)\n\n* Use scipy.sparse array datastructure\r\n\r\n* Add reminder to rm wrapper when scipy adds creation fns.\r\n\r\n* Rm mention of np matrix from code comment.\r\n\r\n* Update networkx/algorithms/bipartite/matrix.py\r\n\r\nCo-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>\r\nCo-authored-by: Stefan van der Walt <sjvdwalt@gmail.com>",
        "code": "def from_biadjacency_matrix(A, create_using=None, edge_attribute=\"weight\"):\n    r\n    G = nx.empty_graph(0, create_using)\n    n, m = A.shape\n    # Make sure we get even the isolated nodes of the graph.\n    G.add_nodes_from(range(n), bipartite=0)\n    G.add_nodes_from(range(n, n + m), bipartite=1)\n    # Create an iterable over (u, v, w) triples and for each triple, add an\n    # edge from u to v with weight w.\n    triples = ((u, n + v, d) for (u, v, d) in _generate_weighted_edges(A))\n    # If the entries in the adjacency matrix are integers and the graph is a\n    # multigraph, then create parallel edges, each with weight 1, for each\n    # entry in the adjacency matrix. Otherwise, create one edge for each\n    # positive entry in the adjacency matrix and set the weight of that edge to\n    # be the entry in the matrix.\n    if A.dtype.kind in (\"i\", \"u\") and G.is_multigraph():\n        chain = itertools.chain.from_iterable\n        triples = chain(((u, v, 1) for d in range(w)) for (u, v, w) in triples)\n    G.add_weighted_edges_from(triples, weight=edge_attribute)\n    return G\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 223,
        "n_words": 159,
        "vocab_size": 93,
        "complexity": 6,
        "nloc": 46,
        "token_counts": 157,
        "n_ast_nodes": 243,
        "n_identifiers": 27,
        "d_id": 42335,
        "documentation": {
            "docstring": "Creates a new bipartite graph from a biadjacency matrix given as a\n    SciPy sparse array.\n\n    Parameters\n    ----------\n    A: scipy sparse array\n      A biadjacency matrix representation of a graph\n\n    create_using: NetworkX graph\n       Use specified graph for result.  The default is Graph()\n\n    edge_attribute: string\n       Name of edge attribute to store matrix numeric value. The data will\n       have the same type as the matrix entry (int, float, (real,imag)).\n\n    Notes\n    -----\n    The nodes are labeled with the attribute `bipartite` set to an integer\n    0 or 1 representing membership in part 0 or part 1 of the bipartite graph.\n\n    If `create_using` is an instance of :class:`networkx.MultiGraph` or\n    :class:`networkx.MultiDiGraph` and the entries of `A` are of\n    type :class:`int`, then this function returns a multigraph (of the same\n    type as `create_using`) with parallel edges. In this case, `edge_attribute`\n    will be ignored.\n\n    See Also\n    --------\n    biadjacency_matrix\n    from_numpy_array\n\n    References\n    ----------\n    [1] https://en.wikipedia.org/wiki/Adjacency_matrix#Adjacency_matrix_of_a_bipartite_graph\n    ",
            "n_words": 143,
            "vocab_size": 99,
            "n_whitespaces": 236,
            "language": "en"
        }
    },
    {
        "id": 189522,
        "commit_id": "daf23c9d1031b12d9c119b8f6b7e60727d7f9242",
        "repo": "manim",
        "path": "manim/mobject/coordinate_systems.py",
        "file_name": "coordinate_systems.py",
        "fun_name": "_get_default_coordinate_values",
        "commit_message": "Upgraded typehints (#2429)\n\n* Future Annotations\r\n\r\n* Delete template_twitter_post.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Apply suggestions from code review\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fixed broken RTD\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def _get_default_coordinate_values(self) -> list[float | complex]:\n        \n        x_numbers = self.get_x_axis().get_tick_range()\n        y_numbers = self.get_y_axis().get_tick_range()\n        y_numbers = [complex(0, y) for y in y_numbers if y != 0]\n        return [*x_numbers, *y_numbers]\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 62,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 61,
        "n_ast_nodes": 99,
        "n_identifiers": 11,
        "d_id": 46112,
        "documentation": {
            "docstring": "Generate a list containing the numerical values of the plane's labels.\n\n        Returns\n        -------\n        List[Union[float, complex]]\n            A list of floats representing the x-axis and complex numbers representing the y-axis.\n        ",
            "n_words": 28,
            "vocab_size": 22,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 109454,
        "commit_id": "c73f4c455514cf5422d27bf38c93250de8316b21",
        "repo": "matplotlib",
        "path": "lib/matplotlib/gridspec.py",
        "file_name": "gridspec.py",
        "fun_name": "update",
        "commit_message": "Merge SubplotBase into AxesBase.",
        "code": "def update(self, **kwargs):\n        \n        for k, v in kwargs.items():\n            if k in self._AllowedKeys:\n                setattr(self, k, v)\n            else:\n                raise AttributeError(f\"{k} is an unknown keyword\")\n        for figmanager in _pylab_helpers.Gcf.figs.values():\n            for ax in figmanager.canvas.figure.axes:\n                if ax.get_subplotspec() is not None:\n                    ss = ax.get_subplotspec().get_topmost_subplotspec()\n                    if ss.get_gridspec() == self:\n                        ax._set_position(\n                            ax.get_subplotspec().get_position(ax.figure))\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 231,
        "n_words": 44,
        "vocab_size": 35,
        "complexity": 7,
        "nloc": 13,
        "token_counts": 114,
        "n_ast_nodes": 188,
        "n_identifiers": 24,
        "d_id": 23597,
        "documentation": {
            "docstring": "\n        Update the subplot parameters of the grid.\n\n        Parameters that are not explicitly given are not changed. Setting a\n        parameter to *None* resets it to :rc:`figure.subplot.*`.\n\n        Parameters\n        ----------\n        left, right, top, bottom : float or None, optional\n            Extent of the subplots as a fraction of figure width or height.\n        wspace, hspace : float, optional\n            Spacing between the subplots as a fraction of the average subplot\n            width / height.\n        ",
            "n_words": 67,
            "vocab_size": 45,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 102178,
        "commit_id": "bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d",
        "repo": "pytorch",
        "path": "tools/test/test_gen_backend_stubs.py",
        "file_name": "test_gen_backend_stubs.py",
        "fun_name": "test_valid_multiple_ops",
        "commit_message": "Revert \"Revert D32498569: allow external backend codegen to toggle whether to generate out= and inplace kernels\" (#69950)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/69950\n\nThis reverts commit f6cad53443704dfe5a20cc62bee14d91e3bffcaa.\n\nTest Plan: Imported from OSS\n\nReviewed By: albanD\n\nDifferential Revision: D33113545\n\nPulled By: bdhirsh\n\nfbshipit-source-id: d6590294662588d36c09662dea65919ad4e1e288",
        "code": "def test_valid_multiple_ops(self) -> None:\n        yaml_str = \n        self.assert_success_from_gen_backend_stubs(yaml_str)\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 16,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 21493,
        "documentation": {
            "docstring": "\\\nbackend: XLA\ncpp_namespace: torch_xla\nsupported:\n- add.Tensor\n- abs",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 140528,
        "commit_id": "905258dbc19753c81039f993477e7ab027960729",
        "repo": "ray",
        "path": "python/ray/util/collective/collective_group/gloo_collective_group.py",
        "file_name": "gloo_collective_group.py",
        "fun_name": "meet",
        "commit_message": "Clean up docstyle in python modules and add LINT rule (#25272)",
        "code": "def meet(self, timeout_s=180):\n        \n        if timeout_s <= 0:\n            raise ValueError(\n                \"The 'timeout' argument must be positive. \"\n                \"Got '{}'.\".format(timeout_s)\n            )\n\n        timeout_delta = datetime.timedelta(seconds=timeout_s)\n        elapsed = datetime.timedelta(seconds=0)\n        start_time = datetime.datetime.now()\n        q, s = None, None\n\n        if self._store_type == \"redis\" or self._store_type == \"ray_internal_kv\":\n            while elapsed < timeout_delta:\n                try:\n                    # I don't quite understand why we need gloo queue actor.\n                    q = ray.get_actor(\"gloo_queue\")\n                    s = ray.get_actor(f\"gloo_{self._group_name}_signal\")\n                    break\n                except ValueError:\n                    if self._context.rank == 0:\n                        if not q:\n                            ray.remote(gloo_util.glooQueue).options(\n                                name=\"gloo_queue\", lifetime=\"detached\"\n                            ).remote(1000)\n                        if not s:\n                            gloo_util.SignalActor.options(\n                                name=f\"gloo_{self._group_name}_signal\",\n                                lifetime=\"detached\",\n                            ).remote(self._context.size)\n                    else:\n                        time.sleep(0.1)\n                elapsed = datetime.datetime.now() - start_time\n            if not q:\n                raise RuntimeError(\"Unable to get gloo_queue.\")\n            if self._context.rank == 0:\n                ray.get(q.put_nowait.remote(self._group_name))\n            while ray.get(q.index.remote(self._group_name)):\n                time.sleep(0.1)\n\n            self._context.connectFullMesh(self._store, self._device)\n            ray.get(s.send.remote(self._context.rank))\n            if self._context.rank == 0:\n                ray.get(s.wait.remote())\n                keys = []\n                keys += [f\"rank_{i}\" for i in range(self._context.size)]\n                keys += [f\"{i}\" for i in range(self._context.size)]\n                self._store.delKeys(keys)\n                group_name = ray.get(q.get_nowait.remote())\n                assert group_name == self._group_name\n                ray.kill(s)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 24,
        "n_whitespaces": 913,
        "n_words": 141,
        "vocab_size": 96,
        "complexity": 15,
        "nloc": 47,
        "token_counts": 372,
        "n_ast_nodes": 631,
        "n_identifiers": 46,
        "d_id": 31999,
        "documentation": {
            "docstring": "Meet at the named actor store.\n\n        Args:\n            timeout_s: timeout in seconds.\n\n        Return:\n            None\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 288886,
        "commit_id": "f23b1750e85f07091eb896a0b12b8f95e5646338",
        "repo": "core",
        "path": "tests/components/homekit_controller/specific_devices/test_vocolinc_vp3.py",
        "file_name": "test_vocolinc_vp3.py",
        "fun_name": "test_vocolinc_vp3_setup",
        "commit_message": "Migrate HomeKit Controller to use stable identifiers (#80064)",
        "code": "async def test_vocolinc_vp3_setup(hass):\n    \n\n    entity_registry = er.async_get(hass)\n    outlet = entity_registry.async_get_or_create(\n        \"switch\",\n        \"homekit_controller\",\n        \"homekit-EU0121203xxxxx07-48\",\n        suggested_object_id=\"original_vocolinc_vp3_outlet\",\n    )\n    sensor = entity_registry.async_get_or_create(\n        \"sensor\",\n        \"homekit_controller\",\n        \"homekit-EU0121203xxxxx07-aid:1-sid:48-cid:97\",\n        suggested_object_id=\"original_vocolinc_vp3_power\",\n    )\n\n    accessories = await setup_accessories_from_file(hass, \"vocolinc_vp3.json\")\n    await setup_test_accessories(hass, accessories)\n\n    await assert_devices_and_entities_created(\n        hass,\n        DeviceTestInfo(\n            unique_id=HUB_TEST_ACCESSORY_ID,\n            name=\"VOCOlinc-VP3-123456\",\n            model=\"VP3\",\n            manufacturer=\"VOCOlinc\",\n            sw_version=\"1.101.2\",\n            hw_version=\"1.0.3\",\n            serial_number=\"EU0121203xxxxx07\",\n            devices=[],\n            entities=[\n                EntityTestInfo(\n                    entity_id=\"switch.original_vocolinc_vp3_outlet\",\n                    friendly_name=\"VOCOlinc-VP3-123456 Outlet\",\n                    unique_id=\"00:00:00:00:00:00_1_48\",\n                    state=\"on\",\n                ),\n                EntityTestInfo(\n                    entity_id=\"sensor.original_vocolinc_vp3_power\",\n                    friendly_name=\"VOCOlinc-VP3-123456 Power\",\n                    unique_id=\"00:00:00:00:00:00_1_48_97\",\n                    unit_of_measurement=POWER_WATT,\n                    capabilities={\"state_class\": SensorStateClass.MEASUREMENT},\n                    state=\"0\",\n                ),\n            ],\n        ),\n    )\n\n    assert (\n        entity_registry.async_get(outlet.entity_id).unique_id\n        == \"00:00:00:00:00:00_1_48\"\n    )\n    assert (\n        entity_registry.async_get(sensor.entity_id).unique_id\n        == \"00:00:00:00:00:00_1_48_97\"\n    )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 582,
        "n_words": 75,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 53,
        "token_counts": 196,
        "n_ast_nodes": 332,
        "n_identifiers": 33,
        "d_id": 88035,
        "documentation": {
            "docstring": "Test that a VOCOlinc VP3 can be correctly setup in HA.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 96980,
        "commit_id": "654c6627307359956c6d44f83791d6b177841363",
        "repo": "sentry",
        "path": "src/sentry/rules/conditions/event_frequency.py",
        "file_name": "event_frequency.py",
        "fun_name": "is_guessed_to_be_created_on_project_creation",
        "commit_message": "ref(types): Add types to conditions and filters (#32393)",
        "code": "def is_guessed_to_be_created_on_project_creation(self) -> bool:\n        \n        # TODO(mgaeta): Bug: Rule is optional.\n        delta = abs(self.rule.date_added - self.project.date_added)\n        guess: bool = delta.total_seconds() < 30 and self.rule.label == DEFAULT_RULE_LABEL\n        return guess\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 62,
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        "d_id": 19359,
        "documentation": {
            "docstring": "\n        Best effort approximation on whether a rule with this condition was\n        created on project creation based on how closely the rule and project\n        are created; and if the label matches the default name used on project\n        creation.\n\n        :return:\n            bool: True if rule is approximated to be created on project creation, False otherwise.\n        ",
            "n_words": 52,
            "vocab_size": 38,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 259234,
        "commit_id": "7f0006c8aad1a09621ad19c3db19c3ff0555a183",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/tests/test_encoders.py",
        "file_name": "test_encoders.py",
        "fun_name": "test_ohe_drop_first_explicit_categories",
        "commit_message": "ENH Adds infrequent categories to OneHotEncoder (#16018)\n\n* ENH Completely adds infrequent categories\r\n\r\n* STY Linting\r\n\r\n* STY Linting\r\n\r\n* DOC Improves wording\r\n\r\n* DOC Lint\r\n\r\n* BUG Fixes\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* DOC Uses math to description float min_frequency\r\n\r\n* DOC Adds comment regarding drop\r\n\r\n* BUG Fixes method name\r\n\r\n* DOC Clearer docstring\r\n\r\n* TST Adds more tests\r\n\r\n* FIX Fixes mege\r\n\r\n* CLN More pythonic\r\n\r\n* CLN Address comments\r\n\r\n* STY Flake8\r\n\r\n* CLN Address comments\r\n\r\n* DOC Fix\r\n\r\n* MRG\r\n\r\n* WIP\r\n\r\n* ENH Address comments\r\n\r\n* STY Fix\r\n\r\n* ENH Use functiion call instead of property\r\n\r\n* ENH Adds counts feature\r\n\r\n* CLN Rename variables\r\n\r\n* DOC More details\r\n\r\n* CLN Remove unneeded line\r\n\r\n* CLN Less lines is less complicated\r\n\r\n* CLN Less diffs\r\n\r\n* CLN Improves readiabilty\r\n\r\n* BUG Fix\r\n\r\n* CLN Address comments\r\n\r\n* TST Fix\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* CLN Move docstring to userguide\r\n\r\n* DOC Better wrapping\r\n\r\n* TST Adds test to handle_unknown='error'\r\n\r\n* ENH Spelling error in docstring\r\n\r\n* BUG Fixes counter with nan values\r\n\r\n* BUG Removes unneeded test\r\n\r\n* BUG Fixes issue\r\n\r\n* ENH Sync with main\r\n\r\n* DOC Correct settings\r\n\r\n* DOC Adds docstring\r\n\r\n* DOC Immprove user guide\r\n\r\n* DOC Move to 1.0\r\n\r\n* DOC Update docs\r\n\r\n* TST Remove test\r\n\r\n* DOC Update docstring\r\n\r\n* STY Linting\r\n\r\n* DOC Address comments\r\n\r\n* ENH Neater code\r\n\r\n* DOC Update explaination for auto\r\n\r\n* Update sklearn/preprocessing/_encoders.py\r\n\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\n\r\n* TST Uses docstring instead of comments\r\n\r\n* TST Remove call to fit\r\n\r\n* TST Spelling error\r\n\r\n* ENH Adds support for drop + infrequent categories\r\n\r\n* ENH Adds infrequent_if_exist option\r\n\r\n* DOC Address comments for user guide\r\n\r\n* DOC Address comments for whats_new\r\n\r\n* DOC Update docstring based on comments\r\n\r\n* CLN Update test with suggestions\r\n\r\n* ENH Adds computed property infrequent_categories_\r\n\r\n* DOC Adds where the infrequent column is located\r\n\r\n* TST Adds more test for infrequent_categories_\r\n\r\n* DOC Adds docstring for _compute_drop_idx\r\n\r\n* CLN Moves _convert_to_infrequent_idx into its own method\r\n\r\n* TST Increases test coverage\r\n\r\n* TST Adds failing test\r\n\r\n* CLN Careful consideration of dropped and inverse_transform\r\n\r\n* STY Linting\r\n\r\n* DOC Adds docstrinb about dropping infrequent\r\n\r\n* DOC Uses only\r\n\r\n* DOC Numpydoc\r\n\r\n* TST Includes test for get_feature_names_out\r\n\r\n* DOC Move whats new\r\n\r\n* DOC Address docstring comments\r\n\r\n* DOC Docstring changes\r\n\r\n* TST Better comments\r\n\r\n* TST Adds check for handle_unknown='ignore' for infrequent\r\n\r\n* CLN Make _infrequent_indices private\r\n\r\n* CLN Change min_frequency default to None\r\n\r\n* DOC Adds comments\r\n\r\n* ENH adds support for max_categories=1\r\n\r\n* ENH Describe lexicon ordering for ties\r\n\r\n* DOC Better docstring\r\n\r\n* STY Fix\r\n\r\n* CLN Error when explicity dropping an infrequent category\r\n\r\n* STY Grammar\r\n\r\nCo-authored-by: Joel Nothman <joel.nothman@gmail.com>\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_ohe_drop_first_explicit_categories(handle_unknown):\n    \n\n    X = [[\"a\", 0], [\"b\", 2], [\"b\", 1]]\n\n    ohe = OneHotEncoder(\n        drop=\"first\",\n        sparse=False,\n        handle_unknown=handle_unknown,\n        categories=[[\"b\", \"a\"], [1, 2]],\n    )\n    ohe.fit(X)\n\n    X_test = [[\"c\", 1]]\n    X_expected = np.array([[0, 0]])\n\n    warn_msg = (\n        r\"Found unknown categories in columns \\[0\\] during transform. \"\n        r\"These unknown categories will be encoded as all zeros\"\n    )\n    with pytest.warns(UserWarning, match=warn_msg):\n        X_trans = ohe.transform(X_test)\n    assert_allclose(X_trans, X_expected)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 142,
        "n_words": 60,
        "vocab_size": 50,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 123,
        "n_ast_nodes": 198,
        "n_identifiers": 21,
        "d_id": 75666,
        "documentation": {
            "docstring": "Check drop='first' and handle_unknown='ignore'/'infrequent_if_exist'\n    during fit with categories passed in.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 216260,
        "commit_id": "75c0cb7181d14f780b24ee5dd126f2836730053b",
        "repo": "salt",
        "path": "salt/grains/core.py",
        "file_name": "core.py",
        "fun_name": "ip6_interfaces",
        "commit_message": "Filter secondary IP address by type (#61434)\n\n* Add filter for secondary ip addresses\r\n\r\nShould improve #61370\r\n\r\n* Remove unnecessary space\r\n\r\n* Add test case for secondary IP address\r\n\r\nTest data for IPv6 secondary IP looks wrong but this is what _interfaces_ip() could return looking at the current code\r\n\r\n* Change order of tests because of caching issues\r\n\r\nChange order of test_network_grains_secondary_ip and test_network_grains_cache because of caching issues when running after test_network_grains_cache\r\n\r\n* Unify style in _interfaces_ip\r\n\r\nUnify coding style in _interfaces_ip for secondary ip addresses with the style for regular addresses. Also align the attributes for IPv6 secondary ip addresses with regular ipv6 addresses\r\n\r\n* Align IPv6 secondary IP attributes with changes to _interfaces_ip\r\n\r\n* Add changelog for fix of issue 61370\r\n\r\n* Use salt.loader.grain_funcs for secondary ip test\r\n\r\nTo work around caching issues when changing order of test_network_grains_cache and test_network_grains_secondary_ip use use salt.loader.grain_funcs in both functions. Also we hope this solves the issue, that this test worked in my local dev environment but not on the saltstack jenkins instances.\r\n\r\n* Use side_effect to simulate test data\r\n\r\nI don't understand what is different when these tests are run on the Jenkins infrastructure. Hope copying this from test_network_grains_cache make the tests work on them.\r\n\r\n* Changed checking for secondaryip address type\r\n\r\n* Add filter for secondary ip addresses\r\n\r\nShould improve #61370\r\n\r\n* Remove unnecessary space\r\n\r\n* Add test case for secondary IP address\r\n\r\nTest data for IPv6 secondary IP looks wrong but this is what _interfaces_ip() could return looking at the current code\r\n\r\n* Change order of tests because of caching issues\r\n\r\nChange order of test_network_grains_secondary_ip and test_network_grains_cache because of caching issues when running after test_network_grains_cache\r\n\r\n* Unify style in _interfaces_ip\r\n\r\nUnify coding style in _interfaces_ip for secondary ip addresses with the style for regular addresses. Also align the attributes for IPv6 secondary ip addresses with regular ipv6 addresses\r\n\r\n* Align IPv6 secondary IP attributes with changes to _interfaces_ip\r\n\r\n* Add changelog for fix of issue 61370\r\n\r\n* Use salt.loader.grain_funcs for secondary ip test\r\n\r\nTo work around caching issues when changing order of test_network_grains_cache and test_network_grains_secondary_ip use use salt.loader.grain_funcs in both functions. Also we hope this solves the issue, that this test worked in my local dev environment but not on the saltstack jenkins instances.\r\n\r\n* Use side_effect to simulate test data\r\n\r\nI don't understand what is different when these tests are run on the Jenkins infrastructure. Hope copying this from test_network_grains_cache make the tests work on them.\r\n\r\n* Changed checking for secondaryip address type\r\n\r\n* Satisfy black code formatting\r\n\r\nCo-authored-by: Shane Lee <leesh@vmware.com>\r\nCo-authored-by: mayrstefan <stefan+github@mayr-stefan.de>",
        "code": "def ip6_interfaces():\n    \n    # Provides:\n    #   ip_interfaces\n\n    if salt.utils.platform.is_proxy():\n        return {}\n\n    ret = {}\n    ifaces = _get_interfaces()\n    for face in ifaces:\n        iface_ips = []\n        for inet in ifaces[face].get(\"inet6\", []):\n            if \"address\" in inet:\n                iface_ips.append(inet[\"address\"])\n        for secondary in ifaces[face].get(\"secondary\", []):\n            if \"address\" in secondary and secondary.get(\"type\") == \"inet6\":\n                iface_ips.append(secondary[\"address\"])\n        ret[face] = iface_ips\n    return {\"ip6_interfaces\": ret}\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 166,
        "n_words": 53,
        "vocab_size": 35,
        "complexity": 8,
        "nloc": 15,
        "token_counts": 118,
        "n_ast_nodes": 207,
        "n_identifiers": 14,
        "d_id": 54487,
        "documentation": {
            "docstring": "\n    Provide a dict of the connected interfaces and their ip6 addresses\n    The addresses will be passed as a list for each interface\n    ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 218860,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/lib2to3/pytree.py",
        "file_name": "pytree.py",
        "fun_name": "match",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def match(self, node, results=None):\n        \n        if self.type is not None and node.type != self.type:\n            return False\n        if self.content is not None:\n            r = None\n            if results is not None:\n                r = {}\n            if not self._submatch(node, r):\n                return False\n            if r:\n                results.update(r)\n        if results is not None and self.name:\n            results[self.name] = node\n        return True\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 198,
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        "nloc": 14,
        "token_counts": 93,
        "n_ast_nodes": 145,
        "n_identifiers": 10,
        "d_id": 55510,
        "documentation": {
            "docstring": "\n        Does this pattern exactly match a node?\n\n        Returns True if it matches, False if not.\n\n        If results is not None, it must be a dict which will be\n        updated with the nodes matching named subpatterns.\n\n        Default implementation for non-wildcard patterns.\n        ",
            "n_words": 40,
            "vocab_size": 36,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 299152,
        "commit_id": "f073f170402bd02e6d6c7597ce5d842a016e97be",
        "repo": "core",
        "path": "homeassistant/components/recorder/run_history.py",
        "file_name": "run_history.py",
        "fun_name": "reset",
        "commit_message": "Refactor tracking of the recorder run history (#70456)\n\nCo-authored-by: Erik Montnemery <erik@montnemery.com>",
        "code": "def reset(self) -> None:\n        \n        self._recording_start = dt_util.utcnow()\n        self._current_run_info = None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 22,
        "n_ast_nodes": 39,
        "n_identifiers": 6,
        "d_id": 98089,
        "documentation": {
            "docstring": "Reset the run when the database is changed or fails.\n\n        Must run in the recorder thread.\n        ",
            "n_words": 16,
            "vocab_size": 13,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 20773,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/rich/live_render.py",
        "file_name": "live_render.py",
        "fun_name": "position_cursor",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def position_cursor(self) -> Control:\n        \n        if self._shape is not None:\n            _, height = self._shape\n            return Control(\n                ControlType.CARRIAGE_RETURN,\n                (ControlType.ERASE_IN_LINE, 2),\n                *(\n                    (\n                        (ControlType.CURSOR_UP, 1),\n                        (ControlType.ERASE_IN_LINE, 2),\n                    )\n                    * (height - 1)\n                )\n            )\n        return Control()\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 250,
        "n_words": 33,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 70,
        "n_ast_nodes": 105,
        "n_identifiers": 10,
        "d_id": 3537,
        "documentation": {
            "docstring": "Get control codes to move cursor to beginning of live render.\n\n        Returns:\n            Control: A control instance that may be printed.\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 215982,
        "commit_id": "f2a783643de61cac1ff3288b40241e5ce6e1ddc8",
        "repo": "salt",
        "path": "salt/utils/platform.py",
        "file_name": "platform.py",
        "fun_name": "is_fedora",
        "commit_message": "Update to latest ``pyupgrade`` hook. Stop skipping it on CI.\n\nSigned-off-by: Pedro Algarvio <palgarvio@vmware.com>",
        "code": "def is_fedora():\n    \n    (osname, osrelease, oscodename) = (\n        x.strip('\"').strip(\"'\") for x in linux_distribution()\n    )\n    return osname == \"Fedora\"\n\n\n@real_memoize",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "@real_memoize",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 36,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 36,
        "n_ast_nodes": 68,
        "n_identifiers": 8,
        "d_id": 54302,
        "documentation": {
            "docstring": "\n    Simple function to return if host is Fedora or not\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 119074,
        "commit_id": "026b91b85db17bb60d49309da7698d33122f751f",
        "repo": "jax",
        "path": "jax/_src/random.py",
        "file_name": "random.py",
        "fun_name": "default_prng_impl",
        "commit_message": "add `random.default_prng_impl` to retrieve the default PRNG implementation",
        "code": "def default_prng_impl():\n  \n  impl_name = config.jax_default_prng_impl\n  assert impl_name in PRNG_IMPLS, impl_name\n  return PRNG_IMPLS[impl_name]\n\n\n### key operations\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 18,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 26542,
        "documentation": {
            "docstring": "Get the default PRNG implementation.\n\n  The default implementation is determined by ``config.jax_default_prng_impl``,\n  which specifies it by name. This function returns the corresponding\n  ``jax.prng.PRNGImpl`` instance.\n  ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 187143,
        "commit_id": "3d44da082b3ba202b9d0557bfd8ce747a1d7960c",
        "repo": "streamlink",
        "path": "tests/test_api_validate.py",
        "file_name": "test_api_validate.py",
        "fun_name": "test_all",
        "commit_message": "plugin.api.validate: implement ValidationError\n\n- Implement `ValidationError`\n  - Inherit from `ValueError` to preserve backwards compatiblity\n  - Allow collecting multiple errors (AnySchema)\n  - Keep an error stack of parent `ValidationError`s or other exceptions\n  - Format error stack when converting error to string\n- Raise `ValidationError` instead of `ValueError`\n  - Add error contexts where it makes sense\n  - Add schema names to error instances\n- Add and update tests",
        "code": "def test_all(self):\n        assert validate(all(int, lambda n: 0 < n < 5), 3) == 3\n\n        assert validate(all(transform(int), lambda n: 0 < n < 5), 3.33) == 3\n\n        with self.assertRaises(ValueError) as cm:\n            validate(all(int, float), 123)\n        assert_validationerror(cm.exception, )\n",
        "url": "https://github.com/streamlink/streamlink.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 73,
        "n_words": 35,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 81,
        "n_ast_nodes": 123,
        "n_identifiers": 13,
        "d_id": 45704,
        "documentation": {
            "docstring": "\n            ValidationError(type):\n              Type of 123 should be 'float', but is 'int'\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 269618,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "temporal_padding",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def temporal_padding(x, padding=(1, 1)):\n    \n    assert len(padding) == 2\n    pattern = [[0, 0], [padding[0], padding[1]], [0, 0]]\n    return tf.compat.v1.pad(x, pattern)\n\n\n@keras_export(\"keras.backend.spatial_2d_padding\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.spatial_2d_padding\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 22,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 61,
        "n_ast_nodes": 117,
        "n_identifiers": 15,
        "d_id": 80237,
        "documentation": {
            "docstring": "Pads the middle dimension of a 3D tensor.\n\n    Args:\n        x: Tensor or variable.\n        padding: Tuple of 2 integers, how many zeros to\n            add at the start and end of dim 1.\n\n    Returns:\n        A padded 3D tensor.\n    ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 59848,
        "commit_id": "1a6dee5e9eb71e6e6d1d3492002e9cd674ab9f9b",
        "repo": "prefect",
        "path": "src/prefect/cli/cloud.py",
        "file_name": "cloud.py",
        "fun_name": "set_login_api_ready_event",
        "commit_message": "Add login with a browser to `prefect cloud login` (#7334)",
        "code": "def set_login_api_ready_event():\n    login_api.extra[\"ready-event\"].set()\n\n\nlogin_api = FastAPI(on_startup=[set_login_api_ready_event])\n\n\nlogin_api.add_middleware(\n    CORSMiddleware,\n    allow_origins=[\"*\"],\n    allow_methods=[\"*\"],\n    allow_headers=[\"*\"],\n)\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "complexity": 1,
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        "d_id": 11953,
        "documentation": {
            "docstring": "\nThis small API server is used for data transmission for browser-based log in.\n",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 283232,
        "commit_id": "ab4de1dd70fba866930150e440a03e461a6ca6a8",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/terminal_helper.py",
        "file_name": "terminal_helper.py",
        "fun_name": "hide_splashscreen",
        "commit_message": "Create a packaged app bundle with Pyinstaller (#1525)\n\n* Add dashboard widget assets\r\n\r\n* Add ipywidgets and ipyflex to project\r\n\r\n* Add currencies dashboard notebook\r\n\r\n* Update docs and docstrings\r\n\r\n* Add pyinstaller to project deps\r\n\r\n* Add pyinstaller artifacts to gitignore\r\n\r\n* Fix linter errors in terminal.py\r\n\r\n* Update cspell hook and action with a pyinstaller specific word\r\n\r\n* Add pyinstaller specfile and artifacts\r\n\r\n* Add splashscreen image\r\n\r\n* Add app icon\r\n\r\n* adding splash screen support to terminal.spec and terminal.py\r\n\r\n* Restore the conda env build files\r\n\r\n* Sync deps\r\n\r\n* Add border to the splashscreen image\r\n\r\n* Clean up terminal launcher\r\n\r\n* Add support for default feature flags in packages apps\r\n\r\n* Fix types and linting\r\n\r\n* Add splashscreen management to app bootup\r\n\r\n* Check prediction feature flag when entering crypto/pred\r\n\r\n* Update pyinstaller spec file\r\n\r\n* fix .spec file to work for splash and icon - removed the \"..\"\r\n\r\n* Allows to export when using installer (#1568)\r\n\r\n* fix export for packaged apps\r\n\r\n* fix filename\r\n\r\n* Git : replace commit_hash when it is set in config_terminal\r\n\r\n* Add update of the git commit hash in gtff default during build\r\n\r\n* Add packaged app name and feature flag to logs\r\n\r\n* Add platform specific icon assignment\r\n\r\n* Add macOS build assets\r\n\r\n* Add tensorflow to hidden imports\r\n\r\n* Move LOGGING_COMMIT_HASH to gtff\r\n\r\n* Adding files/folders needed to .spec  and pyinstaller folder. This will make certain commands work again.\r\n\r\n* Linting\r\n\r\n* Workflow : ignore ./build/pyinstaller from codespell\r\n\r\n* Workflow : exclude ./build/pyinstaller from flake8\r\n\r\n* Poetry + Workflow : add types-six\r\n\r\n* Pyinstaller : remove property_cached, user_agent and vaderSentiment\r\n\r\n* Revert \"Pyinstaller : remove property_cached, user_agent and vaderSentiment\"\r\n\r\nThis reverts commit dbb3e2b81086f97819ebd21457148c7160a4d703.\r\n\r\n* Clean up local paths in specfile\r\n\r\n* Validate deps have correct Jinja version (they do)\r\n\r\n* Fix logging commit hash to be set correctly for the logger to see it\r\n\r\nCo-authored-by: Andrew <andrew.kenreich@gmail.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>",
        "code": "def hide_splashscreen():\n    \n    try:\n        import pyi_splash  # type: ignore  # pylint: disable=import-outside-toplevel\n\n        pyi_splash.update_text(\"Terminal Loaded!\")\n        pyi_splash.close()\n    except Exception as e:\n        logger.info(e)\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 31,
        "n_ast_nodes": 61,
        "n_identifiers": 8,
        "d_id": 84482,
        "documentation": {
            "docstring": "Hide the splashscreen on Windows bundles.\n\n    `pyi_splash` is a PyInstaller \"fake-package\" that's used to communicate\n    with the splashscreen on Windows.\n    Sending the `close` signal to the splash screen is required.\n    The splash screen remains open until this function is called or the Python\n    program is terminated.\n    ",
            "n_words": 46,
            "vocab_size": 34,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 322298,
        "commit_id": "4a1b98b9390aa0ec9c16530b28ba8d311787867b",
        "repo": "PaddleNLP",
        "path": "applications/neural_search/recall/milvus/feature_extract.py",
        "file_name": "feature_extract.py",
        "fun_name": "predict",
        "commit_message": "Update Readme and Update Mivus feature extraction module (#1699)\n\n* add recall inference similarity\r\n\r\n* update examples\r\n\r\n* updatea readme\r\n\r\n* update dir name\r\n\r\n* update neural search readme\r\n\r\n* update milvus readme\r\n\r\n* update domain adaptive pretraining readme\r\n\r\n* fix the mistakes\r\n\r\n* update readme\r\n\r\n* add recall Paddle Serving Support\r\n\r\n* update readme\r\n\r\n* update readme and format the code\r\n\r\n* reformat the files\r\n\r\n* move the files\r\n\r\n* reformat the code\r\n\r\n* remove redundant code\r\n\r\n* update changes\r\n\r\n* Add C++ Paddle Serving\r\n\r\n* Update Readme and Update Mivus feature extraction module\r\n\r\n* check formats\r\n\r\n* update serving config\r\n\r\n* deleted redundant code\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>\r\nCo-authored-by: tianxin <tianxin04@baidu.com>",
        "code": "def predict(self, data, tokenizer):\n        \n\n        batchify_fn = lambda samples, fn=Tuple(\n            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # input\n            Pad(axis=0, pad_val=tokenizer.pad_token_id),  # segment\n        ): fn(samples)\n\n        all_embeddings = []\n        examples = []\n        for idx, text in enumerate(tqdm(data)):\n            input_ids, segment_ids = convert_example(\n                text,\n                tokenizer,\n                max_seq_length=self.max_seq_length,\n                pad_to_max_seq_len=True)\n            examples.append((input_ids, segment_ids))\n            if (len(examples) > 100):\n                input_ids, segment_ids = batchify_fn(examples)\n                self.input_handles[0].copy_from_cpu(input_ids)\n                self.input_handles[1].copy_from_cpu(segment_ids)\n                self.predictor.run()\n                logits = self.output_handle.copy_to_cpu()\n                all_embeddings.append(logits)\n                examples = []\n\n        all_embeddings = np.concatenate(all_embeddings, axis=0)\n        np.save('corpus_embedding', all_embeddings)\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 342,
        "n_words": 64,
        "vocab_size": 48,
        "complexity": 3,
        "nloc": 24,
        "token_counts": 188,
        "n_ast_nodes": 295,
        "n_identifiers": 35,
        "d_id": 118117,
        "documentation": {
            "docstring": "\n        Predicts the data labels.\n\n        Args:\n            data (obj:`List(str)`): The batch data whose each element is a raw text.\n            tokenizer(obj:`PretrainedTokenizer`): This tokenizer inherits from :class:`~paddlenlp.transformers.PretrainedTokenizer` \n                which contains most of the methods. Users should refer to the superclass for more information regarding methods.\n\n        Returns:\n            results(obj:`dict`): All the predictions labels.\n        ",
            "n_words": 46,
            "vocab_size": 39,
            "n_whitespaces": 124,
            "language": "en"
        }
    },
    {
        "id": 115816,
        "commit_id": "b4b66f241b6b2905e1dba81c42c2edd095c257bc",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/vertica_handler/vertica_handler.py",
        "file_name": "vertica_handler.py",
        "fun_name": "get_tables",
        "commit_message": "ALMOST Completed But Dialect not working",
        "code": "def get_tables(self) -> Response:\n        \n        q = f\n\n         \n        return self.native_query(q)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 39,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 19,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 25565,
        "documentation": {
            "docstring": "\n        Get a list with all of the tabels in VERTICA\n        SELECT \n        TABLE_NAME,\n        TABLE_SCHEMA\n        from v_catalog.tables \n        WHERE table_schema='{self.schema_name}' \n        order by\n        table_name;",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 9405,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/external/stylegan2/dnnlib/tflib/ops/upfirdn_2d.py",
        "file_name": "upfirdn_2d.py",
        "fun_name": "upsample_2d",
        "commit_message": "initialize ostec",
        "code": "def upsample_2d(x, k=None, factor=2, gain=1, data_format='NCHW', impl='cuda'):\n    r\n\n    assert isinstance(factor, int) and factor >= 1\n    if k is None:\n        k = [1] * factor\n    k = _setup_kernel(k) * (gain * (factor ** 2))\n    p = k.shape[0] - factor\n    return _simple_upfirdn_2d(x, k, up=factor, pad0=(p+1)//2+factor-1, pad1=p//2, data_format=data_format, impl=impl)\n\n#----------------------------------------------------------------------------\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 70,
        "n_words": 47,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 29,
        "token_counts": 95,
        "n_ast_nodes": 171,
        "n_identifiers": 16,
        "d_id": 1605,
        "documentation": {
            "docstring": "Upsample a batch of 2D images with the given filter.\n\n    Accepts a batch of 2D images of the shape `[N, C, H, W]` or `[N, H, W, C]`\n    and upsamples each image with the given filter. The filter is normalized so that\n    if the input pixels are constant, they will be scaled by the specified `gain`.\n    Pixels outside the image are assumed to be zero, and the filter is padded with\n    zeros so that its shape is a multiple of the upsampling factor.\n\n    Args:\n        x:            Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.\n        k:            FIR filter of the shape `[firH, firW]` or `[firN]` (separable).\n                      The default is `[1] * factor`, which corresponds to nearest-neighbor\n                      upsampling.\n        factor:       Integer upsampling factor (default: 2).\n        gain:         Scaling factor for signal magnitude (default: 1.0).\n        data_format:  `'NCHW'` or `'NHWC'` (default: `'NCHW'`).\n        impl:         Name of the implementation to use. Can be `\"ref\"` or `\"cuda\"` (default).\n\n    Returns:\n        Tensor of the shape `[N, C, H * factor, W * factor]` or\n        `[N, H * factor, W * factor, C]`, and same datatype as `x`.\n    ",
            "n_words": 181,
            "vocab_size": 105,
            "n_whitespaces": 348,
            "language": "en"
        }
    },
    {
        "id": 217918,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/imaplib.py",
        "file_name": "imaplib.py",
        "fun_name": "copy",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def copy(self, message_set, new_mailbox):\n        \n        return self._simple_command('COPY', message_set, new_mailbox)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 55013,
        "documentation": {
            "docstring": "Copy 'message_set' messages onto end of 'new_mailbox'.\n\n        (typ, [data]) = <instance>.copy(message_set, new_mailbox)\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 162160,
        "commit_id": "f0d785d3ed59e879a69f69f3c9334754f11747e0",
        "repo": "yt-dlp",
        "path": "yt_dlp/extractor/youtube.py",
        "file_name": "youtube.py",
        "fun_name": "extract_relative_time",
        "commit_message": "[youtube:tab] Extract more playlist metadata (#2069)\n\n* Add fields modified_date, modified_timestamp\r\n* Add field playlist_count\r\n* [youtube:tab] Extract view_count, playlist_count, modified_date\r\n\r\nAuthored by: coletdjnz, pukkandan",
        "code": "def extract_relative_time(relative_time_text):\n        \n        mobj = re.search(r'(?P<start>today|yesterday|now)|(?P<time>\\d+)\\s*(?P<unit>microsecond|second|minute|hour|day|week|month|year)s?\\s*ago', relative_time_text)\n        if mobj:\n            start = mobj.group('start')\n            if start:\n                return datetime_from_str(start)\n            try:\n                return datetime_from_str('now-%s%s' % (mobj.group('time'), mobj.group('unit')))\n            except ValueError:\n                return None\n",
        "url": "https://github.com/yt-dlp/yt-dlp.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 135,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 64,
        "n_ast_nodes": 113,
        "n_identifiers": 9,
        "d_id": 39169,
        "documentation": {
            "docstring": "\n        Extracts a relative time from string and converts to dt object\n        e.g. 'streamed 6 days ago', '5 seconds ago (edited)', 'updated today'\n        ",
            "n_words": 22,
            "vocab_size": 22,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 251210,
        "commit_id": "fdde9ba3b3caaa2654048cec0af07bfcc3a6a3f8",
        "repo": "mitmproxy",
        "path": "mitmproxy/optmanager.py",
        "file_name": "optmanager.py",
        "fun_name": "make_parser",
        "commit_message": "use Python 3.9+ typing",
        "code": "def make_parser(self, parser, optname, metavar=None, short=None):\n        \n        if optname not in self._options:\n            return\n\n        o = self._options[optname]\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 47,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 8,
        "nloc": 58,
        "token_counts": 308,
        "n_ast_nodes": 53,
        "n_identifiers": 8,
        "d_id": 73636,
        "documentation": {
            "docstring": "\n            Auto-Create a command-line parser entry for a named option. If the\n            option does not exist, it is ignored.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 212837,
        "commit_id": "e575a0b8dc72561ce6565edaf804dc8c6b5053e5",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "update",
        "commit_message": "Fixed problem with making elements invisible causing the pack settings to be lost.  Converted Text, Input, Multiline, StatusBar, Frame, Combo to see if this is the right approach",
        "code": "def update(self, value=None, background_color=None, text_color=None, font=None, visible=None):\n        \n\n        if not self._widget_was_created():  # if widget hasn't been created yet, then don't allow\n            return\n        if value is not None:\n            self.DisplayText = str(value)\n            self.TKStringVar.set(str(value))\n        if background_color not in (None, COLOR_SYSTEM_DEFAULT):\n            self.TKText.configure(background=background_color)\n        if text_color not in (None, COLOR_SYSTEM_DEFAULT):\n            self.TKText.configure(fg=text_color)\n        if font is not None:\n            self.TKText.configure(font=font)\n        if visible is False:\n            element._pack_forget_save_settings()\n            # self.TKText.pack_forget()\n        elif visible is True:\n            self._pack_restore_settings()\n            # self.TKText.pack(padx=self.pad_used[0], pady=self.pad_used[1])\n        if visible is not None:\n            self._visible = visible\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 258,
        "n_words": 73,
        "vocab_size": 46,
        "complexity": 9,
        "nloc": 18,
        "token_counts": 147,
        "n_ast_nodes": 233,
        "n_identifiers": 21,
        "d_id": 53445,
        "documentation": {
            "docstring": "\n        Changes some of the settings for the Text Element. Must call `Window.Read` or `Window.Finalize` prior\n\n        Changes will not be visible in your window until you call window.read or window.refresh.\n\n        If you change visibility, your element may MOVE. If you want it to remain stationary, use the \"layout helper\"\n        function \"pin\" to ensure your element is \"pinned\" to that location in your layout so that it returns there\n        when made visible.\n\n        :param value:            new text to show\n        :type value:             (str)\n        :param background_color: color of background\n        :type background_color:  (str)\n        :param text_color:       color of the text\n        :type text_color:        (str)\n        :param font:             specifies the  font family, size, etc. Tuple or Single string format 'name size styles'. Styles: italic * roman bold normal underline overstrike\n        :type font:              (str or (str, int[, str]) or None)\n        :param visible:          set visibility state of the element\n        :type visible:           (bool)\n        ",
            "n_words": 140,
            "vocab_size": 95,
            "n_whitespaces": 335,
            "language": "en"
        }
    },
    {
        "id": 264304,
        "commit_id": "54834c47f8870e7faabcd847c3270da0bd3d2884",
        "repo": "netbox",
        "path": "netbox/netbox/views/generic/object_views.py",
        "file_name": "object_views.py",
        "fun_name": "get_template_name",
        "commit_message": "Refactor generic views; add plugins dev documentation",
        "code": "def get_template_name(self):\n        \n        if self.template_name is not None:\n            return self.template_name\n        model_opts = self.queryset.model._meta\n        return f'{model_opts.app_label}/{model_opts.model_name}.html'\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 53,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 77675,
        "documentation": {
            "docstring": "\n        Return self.template_name if defined. Otherwise, dynamically resolve the template name using the queryset\n        model's `app_label` and `model_name`.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 249821,
        "commit_id": "d8cc86eff484b6f570f55a5badb337080c6e4dcd",
        "repo": "synapse",
        "path": "tests/replication/slave/storage/test_events.py",
        "file_name": "test_events.py",
        "fun_name": "persist",
        "commit_message": "Remove redundant types from comments. (#14412)\n\nRemove type hints from comments which have been added\r\nas Python type hints. This helps avoid drift between comments\r\nand reality, as well as removing redundant information.\r\n\r\nAlso adds some missing type hints which were simple to fill in.",
        "code": "def persist(self, backfill=False, **kwargs) -> FrozenEvent:\n        \n        event, context = self.build_event(**kwargs)\n\n        if backfill:\n            self.get_success(\n                self._storage_controllers.persistence.persist_events(\n                    [(event, context)], backfilled=True\n                )\n            )\n        else:\n            self.get_success(\n                self._storage_controllers.persistence.persist_event(event, context)\n            )\n\n        return event\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 169,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 75,
        "n_ast_nodes": 118,
        "n_identifiers": 14,
        "d_id": 73153,
        "documentation": {
            "docstring": "\n        Returns:\n            The event that was persisted.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 53410,
        "commit_id": "1d4218a287ef343f32f1e32482592b471be5df1d",
        "repo": "prefect",
        "path": "src/prefect/settings.py",
        "file_name": "settings.py",
        "fun_name": "from_env",
        "commit_message": "Move `prefect.settings` to `prefect.settings.from_env()`",
        "code": "def from_env() -> Settings:\n    \n    # Since os.environ is a Dict[str, str] we can safely hash it by contents, but we\n    # must be careful to avoid hashing a generator instead of a tuple\n    cache_key = hash(tuple((key, value) for key, value in os.environ.items()))\n\n    if cache_key not in _FROM_ENV_CACHE:\n        _FROM_ENV_CACHE[cache_key] = Settings()\n    \n    return _FROM_ENV_CACHE[cache_key]\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 81,
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        "vocab_size": 44,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 51,
        "n_ast_nodes": 84,
        "n_identifiers": 11,
        "d_id": 10794,
        "documentation": {
            "docstring": "\n    Returns a settings object populated with default values and overrides from\n    environment variables.\n\n    Calls with the same environment return a cached object instead of reconstructing.\n    ",
            "n_words": 25,
            "vocab_size": 21,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 148484,
        "commit_id": "813a2cd23b0d9fa9f384c8c1f0b558ca5c4363e2",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/models.py",
        "file_name": "models.py",
        "fun_name": "nr_of_successful_buys",
        "commit_message": "Add useful helper methods for adjust_trade_position implementation",
        "code": "def nr_of_successful_buys(self) -> int:\n        \n        return len([o for o in self.orders if o.ft_order_side == 'buy' and\n                    o.status in NON_OPEN_EXCHANGE_STATES and\n                    o.filled > 0])\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 74,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 5,
        "nloc": 8,
        "token_counts": 39,
        "n_ast_nodes": 64,
        "n_identifiers": 10,
        "d_id": 34265,
        "documentation": {
            "docstring": "\n        Helper function to count the number of buy orders that have been filled.\n        :return: int count of buy orders that have been filled for this trade.\n        ",
            "n_words": 26,
            "vocab_size": 19,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 109392,
        "commit_id": "a17f4f3bd63e3ca3754f96d7db4ce5197720589b",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_colorbar.py",
        "file_name": "test_colorbar.py",
        "fun_name": "_get_cmap_norms",
        "commit_message": "MNT: convert tests and internal usage way from using mpl.cm.get_cmap",
        "code": "def _get_cmap_norms():\n    \n    # Create a colormap and specify the levels it represents.\n    cmap = mpl.colormaps[\"RdBu\"].resampled(5)\n    clevs = [-5., -2.5, -.5, .5, 1.5, 3.5]\n    # Define norms for the colormaps.\n    norms = dict()\n    norms['neither'] = BoundaryNorm(clevs, len(clevs) - 1)\n    norms['min'] = BoundaryNorm([-10] + clevs[1:], len(clevs) - 1)\n    norms['max'] = BoundaryNorm(clevs[:-1] + [10], len(clevs) - 1)\n    norms['both'] = BoundaryNorm([-10] + clevs[1:-1] + [10], len(clevs) - 1)\n    return cmap, norms\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 100,
        "n_words": 67,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 151,
        "n_ast_nodes": 230,
        "n_identifiers": 10,
        "d_id": 23565,
        "documentation": {
            "docstring": "\n    Define a colormap and appropriate norms for each of the four\n    possible settings of the extend keyword.\n\n    Helper function for _colorbar_extension_shape and\n    colorbar_extension_length.\n    ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 249545,
        "commit_id": "2fae1a3f7862bf38cd0b52dfd3ea3ae76794d2b7",
        "repo": "synapse",
        "path": "tests/storage/test_event_push_actions.py",
        "file_name": "test_event_push_actions.py",
        "fun_name": "test_get_unread_push_actions_for_user_in_range",
        "commit_message": "Improve tests for get_unread_push_actions_for_user_in_range_*. (#13893)\n\n* Adds a docstring.\r\n* Reduces a small amount of duplicated code.\r\n* Improves tests.",
        "code": "def test_get_unread_push_actions_for_user_in_range(self) -> None:\n        \n        user_id, token, _, other_token, room_id = self._create_users_and_room()\n\n        # Create two events, one of which is a highlight.\n        self.helper.send_event(\n            room_id,\n            type=\"m.room.message\",\n            content={\"msgtype\": \"m.text\", \"body\": \"msg\"},\n            tok=other_token,\n        )\n        event_id = self.helper.send_event(\n            room_id,\n            type=\"m.room.message\",\n            content={\"msgtype\": \"m.text\", \"body\": user_id},\n            tok=other_token,\n        )[\"event_id\"]\n\n        # Fetch unread actions for HTTP pushers.\n        http_actions = self.get_success(\n            self.store.get_unread_push_actions_for_user_in_range_for_http(\n                user_id, 0, 1000, 20\n            )\n        )\n        self.assertEqual(2, len(http_actions))\n\n        # Fetch unread actions for email pushers.\n        email_actions = self.get_success(\n            self.store.get_unread_push_actions_for_user_in_range_for_email(\n                user_id, 0, 1000, 20\n            )\n        )\n        self.assertEqual(2, len(email_actions))\n\n        # Send a receipt, which should clear any actions.\n        self.get_success(\n            self.store.insert_receipt(\n                room_id,\n                \"m.read\",\n                user_id=user_id,\n                event_ids=[event_id],\n                thread_id=None,\n                data={},\n            )\n        )\n        http_actions = self.get_success(\n            self.store.get_unread_push_actions_for_user_in_range_for_http(\n                user_id, 0, 1000, 20\n            )\n        )\n        self.assertEqual([], http_actions)\n        email_actions = self.get_success(\n            self.store.get_unread_push_actions_for_user_in_range_for_email(\n                user_id, 0, 1000, 20\n            )\n        )\n        self.assertEqual([], email_actions)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 638,
        "n_words": 122,
        "vocab_size": 66,
        "complexity": 1,
        "nloc": 49,
        "token_counts": 245,
        "n_ast_nodes": 381,
        "n_identifiers": 26,
        "d_id": 72985,
        "documentation": {
            "docstring": "Test getting unread push actions for HTTP and email pushers.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 184433,
        "commit_id": "6a22c96a9e1831a7ac5889738bec8d5386fd111f",
        "repo": "textual",
        "path": "src/textual/dom.py",
        "file_name": "dom.py",
        "fun_name": "screen",
        "commit_message": "screen fix",
        "code": "def screen(self) -> \"Screen\":\n        \n        # Get the node by looking up a chain of parents\n        # Note that self.screen may not be the same as self.app.screen\n        from .screen import Screen\n\n        node = self\n        while node and not isinstance(node, Screen):\n            node = node._parent\n        if not isinstance(node, Screen):\n            raise NoScreen(\"{self} has no screen\")\n        return node\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 131,
        "n_words": 53,
        "vocab_size": 42,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 48,
        "n_ast_nodes": 87,
        "n_identifiers": 7,
        "d_id": 44581,
        "documentation": {
            "docstring": "Get the screen that this node is contained within. Note that this may not be the currently active screen within the app.",
            "n_words": 22,
            "vocab_size": 17,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 258976,
        "commit_id": "abbee570f31a91243c22b1892e42056bb915c056",
        "repo": "scikit-learn",
        "path": "sklearn/covariance/tests/test_graphical_lasso.py",
        "file_name": "test_graphical_lasso.py",
        "fun_name": "test_graphical_lasso_cv_alphas_iterable",
        "commit_message": "FIX accept NumPy arrays for alphas in GraphicalLassoCV (#22493)",
        "code": "def test_graphical_lasso_cv_alphas_iterable(alphas_container_type):\n    \n    true_cov = np.array(\n        [\n            [0.8, 0.0, 0.2, 0.0],\n            [0.0, 0.4, 0.0, 0.0],\n            [0.2, 0.0, 0.3, 0.1],\n            [0.0, 0.0, 0.1, 0.7],\n        ]\n    )\n    rng = np.random.RandomState(0)\n    X = rng.multivariate_normal(mean=[0, 0, 0, 0], cov=true_cov, size=200)\n    alphas = _convert_container([0.02, 0.03], alphas_container_type)\n    GraphicalLassoCV(alphas=alphas, tol=1e-1, n_jobs=1).fit(X)\n\n\n# TODO: Remove `score` and `test_score` suffix in 1.2\n@pytest.mark.parametrize(\"suffix\", [\"score\", \"test_score\"])\n@pytest.mark.filterwarnings(\"ignore:Key*:FutureWarning:sklearn\")",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"suffix\", [\"score\", \"test_score\"])\n@pytest.mark.filterwarnings(\"ignore:Key*:FutureWarning:sklearn\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 132,
        "n_words": 56,
        "vocab_size": 47,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 160,
        "n_ast_nodes": 213,
        "n_identifiers": 23,
        "d_id": 75504,
        "documentation": {
            "docstring": "Check that we can pass an array-like to `alphas`.\n\n    Non-regression test for:\n    https://github.com/scikit-learn/scikit-learn/issues/22489\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 207867,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_change_view_with_show_delete_extra_context",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_change_view_with_show_delete_extra_context(self):\n        \n        instance = UndeletableObject.objects.create(name=\"foo\")\n        response = self.client.get(\n            reverse(\"admin:admin_views_undeletableobject_change\", args=(instance.pk,))\n        )\n        self.assertNotContains(response, \"deletelink\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 59,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 48,
        "n_ast_nodes": 83,
        "n_identifiers": 14,
        "d_id": 52138,
        "documentation": {
            "docstring": "\n        The 'show_delete' context variable in the admin's change view controls\n        the display of the delete button.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 247396,
        "commit_id": "7e91107be1a4287873266e588a3c5b415279f4c8",
        "repo": "synapse",
        "path": "tests/rest/media/v1/test_html_preview.py",
        "file_name": "test_html_preview.py",
        "fun_name": "test_meta_charset",
        "commit_message": "Add type hints to `tests/rest` (#12146)\n\n* Add type hints to `tests/rest`\r\n\r\n* newsfile\r\n\r\n* change import from `SigningKey`",
        "code": "def test_meta_charset(self) -> None:\n        \n        encodings = _get_html_media_encodings(\n            b,\n            \"text/html\",\n        )\n        self.assertEqual(list(encodings), [\"ascii\", \"utf-8\", \"cp1252\"])\n\n        # A less well-formed version.\n        encodings = _get_html_media_encodings(\n            b,\n            \"text/html\",\n        )\n        self.assertEqual(list(encodings), [\"ascii\", \"utf-8\", \"cp1252\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 129,
        "n_words": 29,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 62,
        "n_ast_nodes": 111,
        "n_identifiers": 6,
        "d_id": 71652,
        "documentation": {
            "docstring": "A character encoding is found via the meta tag.\n        <html>\n        <head><meta charset=\"ascii\">\n        </head>\n        </html>\n        \n        <html>\n        <head>< meta charset = ascii>\n        </head>\n        </html>\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 55038,
        "commit_id": "95b47e807fa5ccc626a06efc2cced0d8ff8eadfa",
        "repo": "prefect",
        "path": "src/prefect/settings.py",
        "file_name": "settings.py",
        "fun_name": "get_current_settings",
        "commit_message": "Rewrite temporary settings to use copy_with_update",
        "code": "def get_current_settings() -> Settings:\n    \n    from prefect.context import ProfileContext\n\n    profile = ProfileContext.get()\n    if profile is not None:\n        return profile.settings\n\n    return get_settings_from_env()\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 42,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 34,
        "n_ast_nodes": 58,
        "n_identifiers": 9,
        "d_id": 11185,
        "documentation": {
            "docstring": "\n    Returns a settings object populated with values from the current profile or, if no\n    profile is active, the environment.\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 64834,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/chart_of_accounts_importer/chart_of_accounts_importer.py",
        "file_name": "chart_of_accounts_importer.py",
        "fun_name": "unset_existing_data",
        "commit_message": "style: format code with black",
        "code": "def unset_existing_data(company):\n\tlinked = frappe.db.sql(\n\t\t,\n\t\tas_dict=True,\n\t)\n\n\t# remove accounts data from company\n\tupdate_values = {d.fieldname: \"\" for d in linked}\n\tfrappe.db.set_value(\"Company\", company, update_values, update_values)\n\n\t# remove accounts data from various doctypes\n\tfor doctype in [\n\t\t\"Account\",\n\t\t\"Party Account\",\n\t\t\"Mode of Payment Account\",\n\t\t\"Tax Withholding Account\",\n\t\t\"Sales Taxes and Charges Template\",\n\t\t\"Purchase Taxes and Charges Template\",\n\t]:\n\t\tfrappe.db.sql(\n\t\t\t.format(doctype) % (company)  # nosec\n\t\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 46,
        "n_words": 65,
        "vocab_size": 48,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 82,
        "n_ast_nodes": 140,
        "n_identifiers": 13,
        "d_id": 13733,
        "documentation": {
            "docstring": "select fieldname from tabDocField\n\t\twhere fieldtype=\"Link\" and options=\"Account\" and parent=\"Company\"delete from `tab{0}` where `company`=\"%s\"",
            "n_words": 14,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 163265,
        "commit_id": "d603d43df2057ecdf74010d9dadc735e37f8f7b5",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "__getitem__",
        "commit_message": "TYP: Ignore numpy related issues (#45244)",
        "code": "def __getitem__(self, key):\n        \n        getitem = self._data.__getitem__\n\n        if is_integer(key) or is_float(key):\n            # GH#44051 exclude bool, which would return a 2d ndarray\n            key = com.cast_scalar_indexer(key, warn_float=True)\n            return getitem(key)\n\n        if isinstance(key, slice):\n            # This case is separated from the conditional above to avoid\n            # pessimization com.is_bool_indexer and ndim checks.\n            result = getitem(key)\n            # Going through simple_new for performance.\n            return type(self)._simple_new(result, name=self._name)\n\n        if com.is_bool_indexer(key):\n            # if we have list[bools, length=1e5] then doing this check+convert\n            #  takes 166 µs + 2.1 ms and cuts the ndarray.__getitem__\n            #  time below from 3.8 ms to 496 µs\n            # if we already have ndarray[bool], the overhead is 1.4 µs or .25%\n            key = np.asarray(key, dtype=bool)\n\n        result = getitem(key)\n        # Because we ruled out integer above, we always get an arraylike here\n        if result.ndim > 1:\n            deprecate_ndim_indexing(result)\n            if hasattr(result, \"_ndarray\"):\n                # error: Item \"ndarray[Any, Any]\" of \"Union[ExtensionArray,\n                # ndarray[Any, Any]]\" has no attribute \"_ndarray\"  [union-attr]\n                # i.e. NDArrayBackedExtensionArray\n                # Unpack to ndarray for MPL compat\n                return result._ndarray  # type: ignore[union-attr]\n            return result\n\n        # NB: Using _constructor._simple_new would break if MultiIndex\n        #  didn't override __getitem__\n        return self._constructor._simple_new(result, name=self._name)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 511,
        "n_words": 178,
        "vocab_size": 123,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 139,
        "n_ast_nodes": 236,
        "n_identifiers": 27,
        "d_id": 39411,
        "documentation": {
            "docstring": "\n        Override numpy.ndarray's __getitem__ method to work as desired.\n\n        This function adds lists and Series as valid boolean indexers\n        (ndarrays only supports ndarray with dtype=bool).\n\n        If resulting ndim != 1, plain ndarray is returned instead of\n        corresponding `Index` subclass.\n\n        ",
            "n_words": 38,
            "vocab_size": 36,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 223782,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/message.py",
        "file_name": "message.py",
        "fun_name": "del_param",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def del_param(self, param, header='content-type', requote=True):\n        \n        if header not in self:\n            return\n        new_ctype = ''\n        for p, v in self.get_params(header=header, unquote=requote):\n            if p.lower() != param.lower():\n                if not new_ctype:\n                    new_ctype = _formatparam(p, v, requote)\n                else:\n                    new_ctype = SEMISPACE.join([new_ctype,\n                                                _formatparam(p, v, requote)])\n        if new_ctype != self.get(header):\n            del self[header]\n            self[header] = new_ctype\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 242,
        "n_words": 48,
        "vocab_size": 32,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 113,
        "n_ast_nodes": 177,
        "n_identifiers": 15,
        "d_id": 57063,
        "documentation": {
            "docstring": "Remove the given parameter completely from the Content-Type header.\n\n        The header will be re-written in place without the parameter or its\n        value. All values will be quoted as necessary unless requote is\n        False.  Optional header specifies an alternative to the Content-Type\n        header.\n        ",
            "n_words": 42,
            "vocab_size": 33,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 110304,
        "commit_id": "03a0b5ea238014ba87f74ef766928287726aa00a",
        "repo": "matplotlib",
        "path": "lib/matplotlib/patches.py",
        "file_name": "patches.py",
        "fun_name": "set_positions",
        "commit_message": "Doc: Fix grammar and spelling",
        "code": "def set_positions(self, posA, posB):\n        \n        if posA is not None:\n            self._posA_posB[0] = posA\n        if posB is not None:\n            self._posA_posB[1] = posB\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 73,
        "n_words": 23,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 67,
        "n_identifiers": 6,
        "d_id": 24044,
        "documentation": {
            "docstring": "\n        Set the start and end positions of the connecting path.\n\n        Parameters\n        ----------\n        posA, posB : None, tuple\n            (x, y) coordinates of arrow tail and arrow head respectively. If\n            `None` use current value.\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 215599,
        "commit_id": "43277294a3454e5dcd9079e005f747bf880801f6",
        "repo": "salt",
        "path": "salt/transport/tcp.py",
        "file_name": "tcp.py",
        "fun_name": "send",
        "commit_message": "Test fix",
        "code": "def send(self, msg, timeout=None, callback=None, raw=False, future=None, tries=3):\n        \n        message_id = self._message_id()\n        header = {\"mid\": message_id}\n\n        if future is None:\n            future = salt.ext.tornado.concurrent.Future()\n            future.tries = tries\n            future.attempts = 0\n            future.timeout = timeout\n\n        if callback is not None:\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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            "docstring": "\n        Send given message, and return a future\n        ",
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    {
        "id": 160494,
        "commit_id": "2215054472616df563faa4613734426c790d4217",
        "repo": "numpy",
        "path": "numpy/lib/histograms.py",
        "file_name": "histograms.py",
        "fun_name": "histogramdd",
        "commit_message": "DEP: Remove `normed=` keyword argument from histogroms\n\nThe normed keyword argument has been deprecated for a long time.\nThis removes it, replacing its position with the new density\nargument.",
        "code": "def histogramdd(sample, bins=10, range=None, density=None, weights=None):\n    \n\n    try:\n        # Sample is an ND-array.\n        N, D = sample.shape\n    except (AttributeError, ValueError):\n        # Sample is a sequence of 1D arrays.\n        sample = np.atleast_2d(sample).T\n        N, D = sample.shape\n\n    nbin = np.empty(D, int)\n    edges = D*[None]\n    dedges = D*[None]\n    if weights is not None:\n        weights = np.asarray(weights)\n\n    try:\n        M = len(bins)\n        if M != D:\n            raise ValueError(\n                'The dimension of bins must be equal to the dimension of the '\n                ' sample x.')\n    except TypeError:\n        # bins is an integer\n        bins = D*[bins]\n\n    # normalize the range argument\n    if range is None:\n        range = (None,) * D\n    elif len(range) != D:\n        raise ValueError('range argument must have one entry per dimension')\n\n    # Create edge arrays\n    for i in _range(D):\n        if np.ndim(bins[i]) == 0:\n            if bins[i] < 1:\n                raise ValueError(\n                    '`bins[{}]` must be positive, when an integer'.format(i))\n            smin, smax = _get_outer_edges(sample[:,i], range[i])\n            try:\n                n = operator.index(bins[i])\n\n            except TypeError as e:\n                raise TypeError(\n                \t\"`bins[{}]` must be an integer, when a scalar\".format(i)\n                ) from e\n\n            edges[i] = np.linspace(smin, smax, n + 1)\n        elif np.ndim(bins[i]) == 1:\n            edges[i] = np.asarray(bins[i])\n            if np.any(edges[i][:-1] > edges[i][1:]):\n                raise ValueError(\n                    '`bins[{}]` must be monotonically increasing, when an array'\n                    .format(i))\n        else:\n            raise ValueError(\n                '`bins[{}]` must be a scalar or 1d array'.format(i))\n\n        nbin[i] = len(edges[i]) + 1  # includes an outlier on each end\n        dedges[i] = np.diff(edges[i])\n\n    # Compute the bin number each sample falls into.\n    Ncount = tuple(\n        # avoid np.digitize to work around gh-11022\n        np.searchsorted(edges[i], sample[:, i], side='right')\n        for i in _range(D)\n    )\n\n    # Using digitize, values that fall on an edge are put in the right bin.\n    # For the rightmost bin, we want values equal to the right edge to be\n    # counted in the last bin, and not as an outlier.\n    for i in _range(D):\n        # Find which points are on the rightmost edge.\n        on_edge = (sample[:, i] == edges[i][-1])\n        # Shift these points one bin to the left.\n        Ncount[i][on_edge] -= 1\n\n    # Compute the sample indices in the flattened histogram matrix.\n    # This raises an error if the array is too large.\n    xy = np.ravel_multi_index(Ncount, nbin)\n\n    # Compute the number of repetitions in xy and assign it to the\n    # flattened histmat.\n    hist = np.bincount(xy, weights, minlength=nbin.prod())\n\n    # Shape into a proper matrix\n    hist = hist.reshape(nbin)\n\n    # This preserves the (bad) behavior observed in gh-7845, for now.\n    hist = hist.astype(float, casting='safe')\n\n    # Remove outliers (indices 0 and -1 for each dimension).\n    core = D*(slice(1, -1),)\n    hist = hist[core]\n\n    if density:\n        # calculate the probability density function\n        s = hist.sum()\n        for i in _range(D):\n            shape = np.ones(D, int)\n            shape[i] = nbin[i] - 2\n            hist = hist / dedges[i].reshape(shape)\n        hist /= s\n\n    if (hist.shape != nbin - 2).any():\n        raise RuntimeError(\n            \"Internal Shape Error\")\n    return hist, edges\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "documentation": {
            "docstring": "\n    Compute the multidimensional histogram of some data.\n\n    Parameters\n    ----------\n    sample : (N, D) array, or (D, N) array_like\n        The data to be histogrammed.\n\n        Note the unusual interpretation of sample when an array_like:\n\n        * When an array, each row is a coordinate in a D-dimensional space -\n          such as ``histogramdd(np.array([p1, p2, p3]))``.\n        * When an array_like, each element is the list of values for single\n          coordinate - such as ``histogramdd((X, Y, Z))``.\n\n        The first form should be preferred.\n\n    bins : sequence or int, optional\n        The bin specification:\n\n        * A sequence of arrays describing the monotonically increasing bin\n          edges along each dimension.\n        * The number of bins for each dimension (nx, ny, ... =bins)\n        * The number of bins for all dimensions (nx=ny=...=bins).\n\n    range : sequence, optional\n        A sequence of length D, each an optional (lower, upper) tuple giving\n        the outer bin edges to be used if the edges are not given explicitly in\n        `bins`.\n        An entry of None in the sequence results in the minimum and maximum\n        values being used for the corresponding dimension.\n        The default, None, is equivalent to passing a tuple of D None values.\n    density : bool, optional\n        If False, the default, returns the number of samples in each bin.\n        If True, returns the probability *density* function at the bin,\n        ``bin_count / sample_count / bin_volume``.\n    weights : (N,) array_like, optional\n        An array of values `w_i` weighing each sample `(x_i, y_i, z_i, ...)`.\n        Weights are normalized to 1 if density is True. If density is False,\n        the values of the returned histogram are equal to the sum of the\n        weights belonging to the samples falling into each bin.\n\n    Returns\n    -------\n    H : ndarray\n        The multidimensional histogram of sample x. See density and weights\n        for the different possible semantics.\n    edges : list\n        A list of D arrays describing the bin edges for each dimension.\n\n    See Also\n    --------\n    histogram: 1-D histogram\n    histogram2d: 2-D histogram\n\n    Examples\n    --------\n    >>> r = np.random.randn(100,3)\n    >>> H, edges = np.histogramdd(r, bins = (5, 8, 4))\n    >>> H.shape, edges[0].size, edges[1].size, edges[2].size\n    ((5, 8, 4), 6, 9, 5)\n\n    ",
            "n_words": 340,
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    {
        "id": 203351,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/checks.py",
        "file_name": "checks.py",
        "fun_name": "_check_list_display_links",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _check_list_display_links(self, obj):\n        \n        from django.contrib.admin.options import ModelAdmin\n\n        if obj.list_display_links is None:\n            return []\n        elif not isinstance(obj.list_display_links, (list, tuple)):\n            return must_be(\n                \"a list, a tuple, or None\",\n                option=\"list_display_links\",\n                obj=obj,\n                id=\"admin.E110\",\n            )\n        # Check only if ModelAdmin.get_list_display() isn't overridden.\n        elif obj.get_list_display.__func__ is ModelAdmin.get_list_display:\n            return list(\n                chain.from_iterable(\n                    self._check_list_display_links_item(\n                        obj, field_name, \"list_display_links[%d]\" % index\n                    )\n                    for index, field_name in enumerate(obj.list_display_links)\n                )\n            )\n        return []\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 50325,
        "documentation": {
            "docstring": "Check that list_display_links is a unique subset of list_display.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 113472,
        "commit_id": "bcc640c4e5e687a03fe21503692dad96e0b97fa7",
        "repo": "nni",
        "path": "nni/algorithms/hpo/bohb_advisor/bohb_advisor.py",
        "file_name": "bohb_advisor.py",
        "fun_name": "handle_trial_end",
        "commit_message": "[nas] fix issue introduced by the trial recovery feature (#5109)",
        "code": "def handle_trial_end(self, data):\n        \n        hyper_params = nni.load(data['hyper_params'])\n        if self.is_created_in_previous_exp(hyper_params['parameter_id']):\n            # The end of the recovered trial is ignored\n            return\n        logger.debug('Tuner handle trial end, result is %s', data)\n        self._handle_trial_end(hyper_params['parameter_id'])\n        if data['trial_job_id'] in self.job_id_para_id_map:\n            del self.job_id_para_id_map[data['trial_job_id']]\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "complexity": 3,
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        "token_counts": 68,
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        "d_id": 24917,
        "documentation": {
            "docstring": "receive the information of trial end and generate next configuaration.\n\n        Parameters\n        ----------\n        data: dict()\n            it has three keys: trial_job_id, event, hyper_params\n            trial_job_id: the id generated by training service\n            event: the job's state\n            hyper_params: the hyperparameters (a string) generated and returned by tuner\n        ",
            "n_words": 42,
            "vocab_size": 36,
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            "language": "en"
        }
    },
    {
        "id": 202901,
        "commit_id": "0ab58c120939093fea90822f376e1866fc714d1f",
        "repo": "django",
        "path": "django/core/management/commands/makemigrations.py",
        "file_name": "makemigrations.py",
        "fun_name": "handle_merge",
        "commit_message": "Refs #29026 -- Allowed customizing InteractiveMigrationQuestioner's prompt destination.\n\nPreviously, the questioner did not obey the value of stdout provided\nto the command.",
        "code": "def handle_merge(self, loader, conflicts):\n        \n        if self.interactive:\n            questioner = InteractiveMigrationQuestioner(prompt_output=self.stdout)\n        else:\n            questioner = MigrationQuestioner(defaults={'ask_merge': True})\n\n        for app_label, migration_names in conflicts.items():\n            # Grab out the migrations in question, and work out their\n            # common ancestor.\n            merge_migrations = []\n            for migration_name in migration_names:\n                migration = loader.get_migration(app_label, migration_name)\n                migration.ancestry = [\n                    mig for mig in loader.graph.forwards_plan((app_label, migration_name))\n                    if mig[0] == migration.app_label\n                ]\n                merge_migrations.append(migration)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
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        "d_id": 50163,
        "documentation": {
            "docstring": "\n        Handles merging together conflicted migrations interactively,\n        if it's safe; otherwise, advises on how to fix it.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 38,
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        }
    },
    {
        "id": 261382,
        "commit_id": "ff9344f3d8d11d38fa3a2497199113e5bac9537c",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_glm/_newton_solver.py",
        "file_name": "_newton_solver.py",
        "fun_name": "line_search",
        "commit_message": "FEA add (single) Cholesky Newton solver to GLMs (#24637)\n\n* FEA add NewtonSolver, CholeskyNewtonSolver and QRCholeskyNewtonSolver\n\n* ENH better singular hessian special solve\n\n* CLN fix some typos found by reviewer\n\n* TST assert ConvergenceWarning is raised\n\n* MNT add BaseCholeskyNewtonSolver\n\n* WIP colinear design in GLMs\n\n* FIX _solve_singular\n\n* FIX false unpacking in\n\n* TST add tests for unpenalized GLMs\n\n* TST fix solutions of glm_dataset\n\n* ENH add SVDFallbackSolver\n\n* CLN remove SVDFallbackSolver\n\n* ENH use gradient step for singular hessians\n\n* ENH print iteration number in warnings\n\n* TST improve test_linalg_warning_with_newton_solver\n\n* CLN LinAlgWarning fron scipy.linalg\n\n* ENH more robust hessian\n\n* ENH increase maxls for lbfgs to make it more robust\n\n* ENH add hessian_warning for too many negative hessian values\n\n* CLN some warning messages\n\n* ENH add lbfgs_step\n\n* ENH use lbfgs_step for hessian_warning\n\n* TST make them pass\n\n* TST tweek rtol for lbfgs\n\n* TST add rigoros test for GLMs\n\n* TST improve test_warm_start\n\n* ENH improve lbfgs options for better convergence\n\n* CLN fix test_warm_start\n\n* TST fix assert singular values in datasets\n\n* CLN address most review comments\n\n* ENH enable more vebosity levels for lbfgs\n\n* DOC add whatsnew\n\n* CLN remove xfail and clean a bit\n\n* CLN docstring about minimum norm\n\n* More informative repr for the glm_dataset fixture cases\n\n* Forgot to run black\n\n* CLN remove unnecessary filterwarnings\n\n* CLN address review comments\n\n* Trigger [all random seeds] on the following tests:\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* CLN add comment for lbfgs ftol=64 * machine precision\n\n* CLN XXX code comment\n\n* Trigger [all random seeds] on the following tests:\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* CLN link issue and remove code snippet in comment\n\n* Trigger [all random seeds] on the following tests:\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* CLN add catch_warnings\n\n* Trigger [all random seeds] on the following tests:\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* Trigger [all random seeds] on the following tests:\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* [all random seeds]\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* Trigger with -Werror [all random seeds]\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* ENH increase maxls to 50\n\n* [all random seeds]\n\ntest_glm_regression\ntest_glm_regression_hstacked_X\ntest_glm_regression_vstacked_X\ntest_glm_regression_unpenalized\ntest_glm_regression_unpenalized_hstacked_X\ntest_glm_regression_unpenalized_vstacked_X\ntest_warm_start\n\n* Revert \"Trigger with -Werror [all random seeds]\"\n\nThis reverts commit 99f4cf99ca41b4ad2bdad537ad60f936970e3a88.\n\n* TST add catch_warnings to filterwarnings\n\n* TST adapt tests for newton solvers\n\n* CLN cleaner gradient step with gradient_times_newton\n\n* DOC add whatsnew\n\n* ENH always use lbfgs as fallback\n\n* TST adapt rtol\n\n* TST fix test_linalg_warning_with_newton_solver\n\n* CLN address some review comments\n\n* Improve tests related to convergence warning on collinear data\n\n* overfit -> fit\n\n* Typo in comment\n\n* Apply suggestions from code review\n\n* ENH fallback_lbfgs_solve\n- Do not use lbfgs steps, fall back complete to lbfgs\n\n* ENH adapt rtol\n\n* Improve test_linalg_warning_with_newton_solver\n\n* Better comments\n\n* Fixed Hessian casing and improved warning messages\n\n* [all random seeds]\n\ntest_linalg_warning_with_newton_solver\n\n* Ignore ConvergenceWarnings for now if convergence is good\n\n* CLN remove counting of warnings\n\n* ENH fall back to lbfgs if line search did not converge\n\n* DOC better comment on performance bottleneck\n\n* Update GLM related examples to use the new solver\n\n* CLN address reviewer comments\n\n* EXA improve some wordings\n\n* CLN do not pop \"solver in parameter constraints\n\n* CLN fix typos\n\n* DOC fix docstring\n\n* CLN remove solver newton-qr-cholesky\n\n* DOC update PR number in whatsnew\n\n* CLN address review comments\n\n* CLN remove unnecessary catch_warnings\n\n* CLN address some review comments\n\n* DOC more precise whatsnew\n\n* CLN use init_zero_coef\n\n* CLN use and test init_zero_coef\n\n* CLN address some review comments\n\n* CLN mark NewtonSolver as private by leading underscore\n\n* CLN exact comments for inner_solve\n\n* TST add test_newton_solver_verbosity\n\n* TST extend test_newton_solver_verbosity\n\n* TST logic in test_glm_regression_unpenalized\n\n* TST use count_nonzero\n\n* CLN remove super rare line search checks\n\n* MNT move Newton solver to new file _newton_solver.py\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def line_search(self, X, y, sample_weight):\n        \n        # line search parameters\n        beta, sigma = 0.5, 0.00048828125  # 1/2, 1/2**11\n        eps = 16 * np.finfo(self.loss_value.dtype).eps\n        t = 1  # step size\n\n        # gradient_times_newton = self.gradient @ self.coef_newton\n        # was computed in inner_solve.\n        armijo_term = sigma * self.gradient_times_newton\n        _, _, raw_prediction_newton = self.linear_loss.weight_intercept_raw(\n            self.coef_newton, X\n        )\n\n        self.coef_old = self.coef\n        self.loss_value_old = self.loss_value\n        self.gradient_old = self.gradient\n\n        # np.sum(np.abs(self.gradient_old))\n        sum_abs_grad_old = -1\n\n        is_verbose = self.verbose >= 2\n        if is_verbose:\n            print(\"  Backtracking Line Search\")\n            print(f\"    eps=10 * finfo.eps={eps}\")\n\n        for i in range(21):  # until and including t = beta**20 ~ 1e-6\n            self.coef = self.coef_old + t * self.coef_newton\n            raw = self.raw_prediction + t * raw_prediction_newton\n            self.loss_value, self.gradient = self.linear_loss.loss_gradient(\n                coef=self.coef,\n                X=X,\n                y=y,\n                sample_weight=sample_weight,\n                l2_reg_strength=self.l2_reg_strength,\n                n_threads=self.n_threads,\n                raw_prediction=raw,\n            )\n            # Note: If coef_newton is too large, loss_gradient may produce inf values,\n            # potentially accompanied by a RuntimeWarning.\n            # This case will be captured by the Armijo condition.\n\n            # 1. Check Armijo / sufficient decrease condition.\n            # The smaller (more negative) the better.\n            loss_improvement = self.loss_value - self.loss_value_old\n            check = loss_improvement <= t * armijo_term\n            if is_verbose:\n                print(\n                    f\"    line search iteration={i+1}, step size={t}\\n\"\n                    f\"      check loss improvement <= armijo term: {loss_improvement} \"\n                    f\"<= {t * armijo_term} {check}\"\n                )\n            if check:\n                break\n            # 2. Deal with relative loss differences around machine precision.\n            tiny_loss = np.abs(self.loss_value_old * eps)\n            check = np.abs(loss_improvement) <= tiny_loss\n            if is_verbose:\n                print(\n                    \"      check loss |improvement| <= eps * |loss_old|:\"\n                    f\" {np.abs(loss_improvement)} <= {tiny_loss} {check}\"\n                )\n            if check:\n                if sum_abs_grad_old < 0:\n                    sum_abs_grad_old = scipy.linalg.norm(self.gradient_old, ord=1)\n                # 2.1 Check sum of absolute gradients as alternative condition.\n                sum_abs_grad = scipy.linalg.norm(self.gradient, ord=1)\n                check = sum_abs_grad < sum_abs_grad_old\n                if is_verbose:\n                    print(\n                        \"      check sum(|gradient|) < sum(|gradient_old|): \"\n                        f\"{sum_abs_grad} < {sum_abs_grad_old} {check}\"\n                    )\n                if check:\n                    break\n\n            t *= beta\n        else:\n            warnings.warn(\n                f\"Line search of Newton solver {self.__class__.__name__} at iteration \"\n                f\"#{self.iteration} did no converge after 21 line search refinement \"\n                \"iterations. It will now resort to lbfgs instead.\",\n                ConvergenceWarning,\n            )\n            if self.verbose:\n                print(\"  Line search did not converge and resorts to lbfgs instead.\")\n            self.use_fallback_lbfgs_solve = True\n            return\n\n        self.raw_prediction = raw\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
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        "nloc": 70,
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        "d_id": 76792,
        "documentation": {
            "docstring": "Backtracking line search.\n\n        Sets:\n            - self.coef_old\n            - self.coef\n            - self.loss_value_old\n            - self.loss_value\n            - self.gradient_old\n            - self.gradient\n            - self.raw_prediction\n        ",
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        }
    },
    {
        "id": 176440,
        "commit_id": "2ef5c096fb870638fd565c62c84999364c21beaf",
        "repo": "networkx",
        "path": "networkx/algorithms/distance_measures.py",
        "file_name": "distance_measures.py",
        "fun_name": "extrema_bounding",
        "commit_message": "Deprecate extrema bounding (#5422)\n\n* Add public wrapper and convert impl to private.\r\n\r\n* Add deprecation warning to public fn.\r\n\r\n* Add test for deprecation warning.\r\n\r\n* Add deprecation note.\r\n\r\n* Add release note.",
        "code": "def extrema_bounding(G, compute=\"diameter\"):\n    \n    import warnings\n\n    msg = \"extrema_bounding is deprecated and will be removed in networkx 3.0\\n\"\n    # NOTE: _extrema_bounding does input checking, so it is skipped here\n    if compute in {\"diameter\", \"radius\", \"periphery\", \"center\"}:\n        msg += f\"Use nx.{compute}(G, usebounds=True) instead.\"\n    if compute == \"eccentricities\":\n        msg += f\"Use nx.eccentricity(G) instead.\"\n    warnings.warn(msg, DeprecationWarning, stacklevel=2)\n\n    return _extrema_bounding(G, compute=compute)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 94,
        "n_words": 56,
        "vocab_size": 47,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 62,
        "n_ast_nodes": 116,
        "n_identifiers": 9,
        "d_id": 41903,
        "documentation": {
            "docstring": "Compute requested extreme distance metric of undirected graph G\n\n    .. deprecated:: 2.8\n\n       extrema_bounding is deprecated and will be removed in NetworkX 3.0.\n       Use the corresponding distance measure with the `usebounds=True` option\n       instead.\n\n    Computation is based on smart lower and upper bounds, and in practice\n    linear in the number of nodes, rather than quadratic (except for some\n    border cases such as complete graphs or circle shaped graphs).\n\n    Parameters\n    ----------\n    G : NetworkX graph\n       An undirected graph\n\n    compute : string denoting the requesting metric\n       \"diameter\" for the maximal eccentricity value,\n       \"radius\" for the minimal eccentricity value,\n       \"periphery\" for the set of nodes with eccentricity equal to the diameter,\n       \"center\" for the set of nodes with eccentricity equal to the radius,\n       \"eccentricities\" for the maximum distance from each node to all other nodes in G\n\n    Returns\n    -------\n    value : value of the requested metric\n       int for \"diameter\" and \"radius\" or\n       list of nodes for \"center\" and \"periphery\" or\n       dictionary of eccentricity values keyed by node for \"eccentricities\"\n\n    Raises\n    ------\n    NetworkXError\n        If the graph consists of multiple components\n    ValueError\n        If `compute` is not one of \"diameter\", \"radius\", \"periphery\", \"center\", or \"eccentricities\".\n    Notes\n    -----\n    This algorithm was proposed in the following papers:\n\n    F.W. Takes and W.A. Kosters, Determining the Diameter of Small World\n    Networks, in Proceedings of the 20th ACM International Conference on\n    Information and Knowledge Management (CIKM 2011), pp. 1191-1196, 2011.\n    doi: https://doi.org/10.1145/2063576.2063748\n\n    F.W. Takes and W.A. Kosters, Computing the Eccentricity Distribution of\n    Large Graphs, Algorithms 6(1): 100-118, 2013.\n    doi: https://doi.org/10.3390/a6010100\n\n    M. Borassi, P. Crescenzi, M. Habib, W.A. Kosters, A. Marino and F.W. Takes,\n    Fast Graph Diameter and Radius BFS-Based Computation in (Weakly Connected)\n    Real-World Graphs, Theoretical Computer Science 586: 59-80, 2015.\n    doi: https://doi.org/10.1016/j.tcs.2015.02.033\n    ",
            "n_words": 280,
            "vocab_size": 175,
            "n_whitespaces": 456,
            "language": "en"
        }
    },
    {
        "id": 60372,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/scripts/cpp_lint.py",
        "file_name": "cpp_lint.py",
        "fun_name": "_GetTextInside",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def _GetTextInside(text, start_pattern):\n  r\n  # TODO(sugawarayu): Audit cpplint.py to see what places could be profitably\n  # rewritten to use _GetTextInside (and use inferior regexp matching today).\n\n  # Give opening punctuations to get the matching close-punctuations.\n  matching_punctuation = {'(': ')', '{': '}', '[': ']'}\n  closing_punctuation = set(matching_punctuation.itervalues())\n\n  # Find the position to start extracting text.\n  match = re.search(start_pattern, text, re.M)\n  if not match:  # start_pattern not found in text.\n    return None\n  start_position = match.end(0)\n\n  assert start_position > 0, (\n      'start_pattern must ends with an opening punctuation.')\n  assert text[start_position - 1] in matching_punctuation, (\n      'start_pattern must ends with an opening punctuation.')\n  # Stack of closing punctuations we expect to have in text after position.\n  punctuation_stack = [matching_punctuation[text[start_position - 1]]]\n  position = start_position\n  while punctuation_stack and position < len(text):\n    if text[position] == punctuation_stack[-1]:\n      punctuation_stack.pop()\n    elif text[position] in closing_punctuation:\n      # A closing punctuation without matching opening punctuations.\n      return None\n    elif text[position] in matching_punctuation:\n      punctuation_stack.append(matching_punctuation[text[position]])\n    position += 1\n  if punctuation_stack:\n    # Opening punctuations left without matching close-punctuations.\n    return None\n  # punctuations match.\n  return text[start_position:position - 1]\n\n\n# Patterns for matching call-by-reference parameters.\n#\n# Supports nested templates up to 2 levels deep using this messy pattern:\n#   < (?: < (?: < [^<>]*\n#               >\n#           |   [^<>] )*\n#         >\n#     |   [^<>] )*\n#   >\n_RE_PATTERN_IDENT = r'[_a-zA-Z]\\w*'  # =~ [[:alpha:]][[:alnum:]]*\n_RE_PATTERN_TYPE = (\n    r'(?:const\\s+)?(?:typename\\s+|class\\s+|struct\\s+|union\\s+|enum\\s+)?'\n    r'(?:\\w|'\n    r'\\s*<(?:<(?:<[^<>]*>|[^<>])*>|[^<>])*>|'\n    r'::)+')\n# A call-by-reference parameter ends with '& identifier'.\n_RE_PATTERN_REF_PARAM = re.compile(\n    r'(' + _RE_PATTERN_TYPE + r'(?:\\s*(?:\\bconst\\b|[*]))*\\s*'\n    r'&\\s*' + _RE_PATTERN_IDENT + r')\\s*(?:=[^,()]+)?[,)]')\n# A call-by-const-reference parameter either ends with 'const& identifier'\n# or looks like 'const type& identifier' when 'type' is atomic.\n_RE_PATTERN_CONST_REF_PARAM = (\n    r'(?:.*\\s*\\bconst\\s*&\\s*' + _RE_PATTERN_IDENT +\n    r'|const\\s+' + _RE_PATTERN_TYPE + r'\\s*&\\s*' + _RE_PATTERN_IDENT + r')')\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 405,
        "n_words": 282,
        "vocab_size": 164,
        "complexity": 8,
        "nloc": 43,
        "token_counts": 173,
        "n_ast_nodes": 397,
        "n_identifiers": 23,
        "d_id": 12101,
        "documentation": {
            "docstring": "Retrieves all the text between matching open and close parentheses.\n\n  Given a string of lines and a regular expression string, retrieve all the text\n  following the expression and between opening punctuation symbols like\n  (, [, or {, and the matching close-punctuation symbol. This properly nested\n  occurrences of the punctuations, so for the text like\n    printf(a(), b(c()));\n  a call to _GetTextInside(text, r'printf\\(') will return 'a(), b(c())'.\n  start_pattern must match string having an open punctuation symbol at the end.\n\n  Args:\n    text: The lines to extract text. Its comments and strings must be elided.\n           It can be single line and can span multiple lines.\n    start_pattern: The regexp string indicating where to start extracting\n                   the text.\n  Returns:\n    The extracted text.\n    None if either the opening string or ending punctuation could not be found.\n  ",
            "n_words": 129,
            "vocab_size": 87,
            "n_whitespaces": 181,
            "language": "en"
        }
    },
    {
        "id": 186897,
        "commit_id": "212c2ba990758cb9acd2b200e55302534988089a",
        "repo": "certbot",
        "path": "certbot/certbot/_internal/storage.py",
        "file_name": "storage.py",
        "fun_name": "rsa_key_size",
        "commit_message": "error out when --reuse-key conflicts with other flags (#9262)\n\n* error out when --reuse-key conflicts with other flags\r\n\r\n* add unit test\r\n\r\n* add integration tests\r\n\r\n* lint",
        "code": "def rsa_key_size(self) -> Optional[int]:\n        \n        key = self._private_key()\n        if isinstance(key, RSAPrivateKey):\n            return key.key_size\n        return None\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 53,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 32,
        "n_ast_nodes": 53,
        "n_identifiers": 9,
        "d_id": 45648,
        "documentation": {
            "docstring": "\n        :returns: If the private key is an RSA key, its size.\n        :rtype: int\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 250114,
        "commit_id": "3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b",
        "repo": "synapse",
        "path": "tests/storage/test_client_ips.py",
        "file_name": "test_client_ips.py",
        "fun_name": "test_get_user_ip_and_agents_combined_data",
        "commit_message": "Require types in tests.storage. (#14646)\n\nAdds missing type hints to `tests.storage` package\r\nand does not allow untyped definitions.",
        "code": "def test_get_user_ip_and_agents_combined_data(self) -> None:\n        \n        self.reactor.advance(12345678)\n\n        user_id = \"@user:id\"\n        user = UserID.from_string(user_id)\n\n        # Insert user IPs\n        self.get_success(\n            self.store.insert_client_ip(\n                user_id, \"access_token\", \"ip_1\", \"user_agent_1\", \"MY_DEVICE_1\"\n            )\n        )\n        self.get_success(\n            self.store.insert_client_ip(\n                user_id, \"access_token\", \"ip_2\", \"user_agent_2\", \"MY_DEVICE_2\"\n            )\n        )\n\n        # Trigger the storage loop and wait for the rate limiting period to be over\n        self.reactor.advance(10 + LAST_SEEN_GRANULARITY / 1000)\n\n        # Update the user agent for the second device, without running the storage loop\n        self.get_success(\n            self.store.insert_client_ip(\n                user_id, \"access_token\", \"ip_2\", \"user_agent_3\", \"MY_DEVICE_2\"\n            )\n        )\n\n        # Check that the new IP and user agent has not been stored yet\n        db_result = self.get_success(\n            self.store.db_pool.simple_select_list(\n                table=\"user_ips\",\n                keyvalues={},\n                retcols=(\"access_token\", \"ip\", \"user_agent\", \"last_seen\"),\n            ),\n        )\n        self.assertEqual(\n            db_result,\n            [\n                {\n                    \"access_token\": \"access_token\",\n                    \"ip\": \"ip_1\",\n                    \"user_agent\": \"user_agent_1\",\n                    \"last_seen\": 12345678000,\n                },\n                {\n                    \"access_token\": \"access_token\",\n                    \"ip\": \"ip_2\",\n                    \"user_agent\": \"user_agent_2\",\n                    \"last_seen\": 12345678000,\n                },\n            ],\n        )\n\n        # Check that data from the database and memory are combined together correctly\n        self.assertCountEqual(\n            self.get_success(self.store.get_user_ip_and_agents(user)),\n            [\n                {\n                    \"access_token\": \"access_token\",\n                    \"ip\": \"ip_1\",\n                    \"user_agent\": \"user_agent_1\",\n                    \"last_seen\": 12345678000,\n                },\n                {\n                    \"access_token\": \"access_token\",\n                    \"ip\": \"ip_2\",\n                    \"user_agent\": \"user_agent_3\",\n                    \"last_seen\": 12345688000 + LAST_SEEN_GRANULARITY,\n                },\n            ],\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 989,
        "n_words": 167,
        "vocab_size": 90,
        "complexity": 1,
        "nloc": 64,
        "token_counts": 250,
        "n_ast_nodes": 451,
        "n_identifiers": 21,
        "d_id": 73278,
        "documentation": {
            "docstring": "Test that `get_user_ip_and_agents` combines persisted and unpersisted data\n        together correctly\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 189389,
        "commit_id": "c4217731e08470d5a56cf02cf76cae01c03fb78f",
        "repo": "manim",
        "path": "tests/utils/GraphicalUnitTester.py",
        "file_name": "GraphicalUnitTester.py",
        "fun_name": "_show_diff_helper",
        "commit_message": "Added MyPy Support (#1972)\n\n* MyPy Support\r\n\r\n* MyPy Hook\r\n\r\n* Removing MyPy Hook\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Delete __init__.pyi\r\n\r\n* Delete color.pyi\r\n\r\n* Update .mypy.ini\r\n\r\nCo-authored-by: Christopher Besch <christopher.besch@gmx.de>\r\n\r\n* changes\r\n\r\n* quick fix\r\n\r\n* MyPy Hook\r\n\r\n* MyPy Hook\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Christopher Besch <christopher.besch@gmx.de>",
        "code": "def _show_diff_helper(self, frame_data, expected_frame_data):\n        \n        import matplotlib.gridspec as gridspec  # type: ignore\n        import matplotlib.pyplot as plt\n\n        gs = gridspec.GridSpec(2, 2)\n        fig = plt.figure()\n        fig.suptitle(f\"Test for {str(self.scene).replace('Test', '')}\", fontsize=16)\n\n        ax = fig.add_subplot(gs[0, 0])\n        ax.imshow(frame_data)\n        ax.set_title(\"Generated :\")\n\n        ax = fig.add_subplot(gs[0, 1])\n        ax.imshow(expected_frame_data)\n        ax.set_title(\"Expected :\")\n\n        ax = fig.add_subplot(gs[1, :])\n        diff_im = expected_frame_data.copy()\n        diff_im = np.where(\n            frame_data != np.array([0, 0, 0, 255]),\n            np.array([0, 255, 0, 255], dtype=\"uint8\"),\n            np.array([0, 0, 0, 255], dtype=\"uint8\"),\n        )  # Set any non-black pixels to green\n        np.putmask(\n            diff_im,\n            expected_frame_data != frame_data,\n            np.array([255, 0, 0, 255], dtype=\"uint8\"),\n        )  # Set any different pixels to red\n        ax.imshow(diff_im, interpolation=\"nearest\")\n        ax.set_title(\"Differences summary : (green = same, red = different)\")\n\n        plt.show()\n        plt.savefig(f\"{self.scene}.png\")\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 329,
        "n_words": 106,
        "vocab_size": 69,
        "complexity": 1,
        "nloc": 28,
        "token_counts": 240,
        "n_ast_nodes": 407,
        "n_identifiers": 31,
        "d_id": 46030,
        "documentation": {
            "docstring": "Will visually display with matplotlib differences between frame generated and the one expected.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 141978,
        "commit_id": "6313ddc47cf9df4df8c8907997df559850a1b874",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_util_file_transfer.py",
        "file_name": "test_util_file_transfer.py",
        "fun_name": "test_multi_sync_same_node",
        "commit_message": "[tune] Refactor Syncer / deprecate Sync client (#25655)\n\nThis PR includes / depends on #25709\r\n\r\nThe two concepts of Syncer and SyncClient are confusing, as is the current API for passing custom sync functions.\r\n\r\nThis PR refactors Tune's syncing behavior. The Sync client concept is hard deprecated. Instead, we offer a well defined Syncer API that can be extended to provide own syncing functionality. However, the default will be to use Ray AIRs file transfer utilities.\r\n\r\nNew API:\r\n- Users can pass `syncer=CustomSyncer` which implements the `Syncer` API\r\n- Otherwise our off-the-shelf syncing is used\r\n- As before, syncing to cloud disables syncing to driver\r\n\r\nChanges:\r\n- Sync client is removed\r\n- Syncer interface introduced\r\n- _DefaultSyncer is a wrapper around the URI upload/download API from Ray AIR\r\n- SyncerCallback only uses remote tasks to synchronize data\r\n- Rsync syncing is fully depracated and removed\r\n- Docker and kubernetes-specific syncing is fully deprecated and removed\r\n- Testing is improved to use `file://` URIs instead of mock sync clients",
        "code": "def test_multi_sync_same_node(ray_start_2_cpus, temp_data_dirs, num_workers):\n    \n    tmp_source, tmp_target = temp_data_dirs\n\n    assert_file(True, tmp_source, \"level0.txt\")\n    assert_file(True, tmp_source, \"subdir/level1.txt\")\n\n    node_ip = ray.util.get_node_ip_address()\n    futures = [\n        _sync_dir_on_same_node(\n            ip=node_ip,\n            source_path=tmp_source,\n            target_path=tmp_target,\n            return_futures=True,\n        )\n        for _ in range(num_workers)\n    ]\n    ray.get(futures)\n\n    assert_file(True, tmp_target, \"level0.txt\")\n    assert_file(True, tmp_target, \"subdir/level1.txt\")\n\n\n@pytest.mark.parametrize(\"num_workers\", [1, 8])",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"num_workers\", [1, 8])",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 135,
        "n_words": 41,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 92,
        "n_ast_nodes": 168,
        "n_identifiers": 23,
        "d_id": 32557,
        "documentation": {
            "docstring": "Check that multiple competing syncs to the same node+dir don't interfere",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 97663,
        "commit_id": "09e1a361f3590dcf345ba7b2a1e35b74cba97ccb",
        "repo": "sentry",
        "path": "src/sentry/lint/engine.py",
        "file_name": "engine.py",
        "fun_name": "yarn_check",
        "commit_message": "fix(dx): Check for prettier verison in dependencies also (#33100)",
        "code": "def yarn_check(file_list):\n    \n\n    if file_list is None or os.environ.get(\"SKIP_YARN_CHECK\"):\n        return False\n\n    if \"package.json\" in file_list and \"yarn.lock\" not in file_list:\n        sys.stdout.write(\n            \"\\033[33m\"\n            + \n            + \"\\033[0m\"\n            + \"\\n\"\n        )\n        return True\n\n    return False\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 116,
        "n_words": 31,
        "vocab_size": 23,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 50,
        "n_ast_nodes": 98,
        "n_identifiers": 8,
        "d_id": 19455,
        "documentation": {
            "docstring": "\n    Checks if package.json was modified WITHOUT a corresponding change in the Yarn\n    lockfile. This can happen if a user manually edited package.json without running Yarn.\n\n    This is a user prompt right now because there ARE cases where you can touch package.json\n    without a Yarn lockfile change, e.g. Jest config changes, license changes, etc.\n    Warning: package.json modified without accompanying yarn.lock modifications.\n\nIf you updated a dependency/devDependencies in package.json, you must run `yarn install` to update the lockfile.\n\nTo skip this check, run `SKIP_YARN_CHECK=1 git commit [options]`",
            "n_words": 85,
            "vocab_size": 63,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 286572,
        "commit_id": "59d8b36bb0467a1a99513b10e8b8471afaa56fd6",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/due_diligence/pycoingecko_model.py",
        "file_name": "pycoingecko_model.py",
        "fun_name": "_get_base_market_data_info",
        "commit_message": "[IMPROVE] Fix Docstring formatting/Fix missing, incomplete type hints (#3412)\n\n* Fixes\r\n\r\n* Update stocks_helper.py\r\n\r\n* update git-actions set-output to new format\r\n\r\n* Update stocks_helper.py\r\n\r\n* Update terminal_helper.py\r\n\r\n* removed LineAnnotateDrawer from qa_view\r\n\r\n* lint\r\n\r\n* few changes\r\n\r\n* updates\r\n\r\n* sdk auto gen modules done\r\n\r\n* Update stocks_helper.py\r\n\r\n* updates to changed imports, and remove first sdk_modules\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* pylint\r\n\r\n* revert stocks_helper\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* full auto generation, added sdk.py/controllers creation\r\n\r\n* missed enable forecasting\r\n\r\n* added running black in subprocess after sdk files generation completes\r\n\r\n* removed deleted sdk_arg_logger\r\n\r\n* comment out tests\r\n\r\n* property doc fix\r\n\r\n* clean up\r\n\r\n* Update generate_sdk.py\r\n\r\n* make trailmap classes useable for doc generation\r\n\r\n* Update generate_sdk.py\r\n\r\n* added lineon to trailmap class for linking to func in markdown\r\n\r\n* changed lineon to dict\r\n\r\n* added full_path to trailmap for linking in docs\r\n\r\n* updated portfolio\r\n\r\n* feat: initial files\r\n\r\n* feat: added meta head\r\n\r\n* feat: added funcdef\r\n\r\n* added func_def to trailmap attributes for markdown in docs, added missing type hints to covid functions\r\n\r\n* feat: added view and merged with jaun\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* init\r\n\r\n* fix returns\r\n\r\n* fix: random stuff\r\n\r\n* fix: random\r\n\r\n* fixed encoding issue on windows\r\n\r\n* fix: generate tabs\r\n\r\n* update\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Create .pydocstyle.ini\r\n\r\n* added type hint classes for views\r\n\r\n* fixes\r\n\r\n* alt, ba\r\n\r\n* alt-economy\r\n\r\n* Update finviz_compare_model.py\r\n\r\n* fixs\r\n\r\n* Update substack_model.py\r\n\r\n* Update generate_sdk.py\r\n\r\n* last of my section\r\n\r\n* porfolio\r\n\r\n* po\r\n\r\n* Update optimizer_model.py\r\n\r\n* fixing more things\r\n\r\n* few more\r\n\r\n* keys done\r\n\r\n* update\r\n\r\n* fixes\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* mypy forecast fix\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\n* fixes\r\n\r\n* forecast fixes\r\n\r\n* one more fix\r\n\r\n* Update coinbase_model.py\r\n\r\n* Update generate_sdk_markdown.py\r\n\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>\r\nCo-authored-by: jose-donato <zmcdonato@gmail.com>\r\nCo-authored-by: andrewkenreich <andrew.kenreich@gmail.com>",
        "code": "def _get_base_market_data_info(self) -> Union[Dict[str, Any], Any]:\n        \n        market_dct = {}\n        market_data = self.coin.get(\"market_data\", {})\n        for stat in [\n            \"total_supply\",\n            \"max_supply\",\n            \"circulating_supply\",\n            \"price_change_percentage_24h\",\n            \"price_change_percentage_7d\",\n            \"price_change_percentage_30d\",\n        ]:\n            market_dct[stat] = market_data.get(stat)\n        prices = create_dictionary_with_prefixes(\n            [\"current_price\"], market_data, DENOMINATION\n        )\n        market_dct.update(prices)\n        return market_dct\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 188,
        "n_words": 37,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 84,
        "n_ast_nodes": 139,
        "n_identifiers": 15,
        "d_id": 85888,
        "documentation": {
            "docstring": "Helper method that fetches all the base market/price information about given coin. [Source: CoinGecko]\n\n        Returns\n        ----------\n        Dict[str, Any]\n            All market related information for given coin\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 124997,
        "commit_id": "569fe0109629048d08e1d9e023f7769f10bd2244",
        "repo": "ray",
        "path": "rllib/offline/tests/test_dataset_reader.py",
        "file_name": "test_dataset_reader.py",
        "fun_name": "test_dataset_shard_with_task_parallelization",
        "commit_message": "[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)",
        "code": "def test_dataset_shard_with_task_parallelization(self):\n        \n        config = {\n            \"input\": \"dataset\",\n            \"input_config\": {\n                \"format\": \"json\",\n                \"paths\": self.dset_path,\n                \"parallelism\": 10,\n            },\n        }\n        NUM_WORKERS = 4\n\n        _, shards = get_dataset_and_shards(config, num_workers=NUM_WORKERS)\n\n        assert len(shards) == NUM_WORKERS + 1\n        assert shards[0] is None\n        assert all(\n            isinstance(remote_shard, ray.data.Dataset) for remote_shard in shards[1:]\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 196,
        "n_words": 44,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 86,
        "n_ast_nodes": 143,
        "n_identifiers": 16,
        "d_id": 27737,
        "documentation": {
            "docstring": "Tests whether the dataset_shard function works correctly with parallelism\n        for reading the dataset.",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 259555,
        "commit_id": "4253eace9893eb6aef36ca631e7978b6a8808fbc",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/cluster/_supervised.py",
        "file_name": "_supervised.py",
        "fun_name": "homogeneity_score",
        "commit_message": "DOC Ensures that homogeneity_score passes numpydoc validation (#23006)",
        "code": "def homogeneity_score(labels_true, labels_pred):\n    \n    return homogeneity_completeness_v_measure(labels_true, labels_pred)[0]\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 12,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 18,
        "n_ast_nodes": 29,
        "n_identifiers": 4,
        "d_id": 75819,
        "documentation": {
            "docstring": "Homogeneity metric of a cluster labeling given a ground truth.\n\n    A clustering result satisfies homogeneity if all of its clusters\n    contain only data points which are members of a single class.\n\n    This metric is independent of the absolute values of the labels:\n    a permutation of the class or cluster label values won't change the\n    score value in any way.\n\n    This metric is not symmetric: switching ``label_true`` with ``label_pred``\n    will return the :func:`completeness_score` which will be different in\n    general.\n\n    Read more in the :ref:`User Guide <homogeneity_completeness>`.\n\n    Parameters\n    ----------\n    labels_true : int array, shape = [n_samples]\n        Ground truth class labels to be used as a reference.\n\n    labels_pred : array-like of shape (n_samples,)\n        Cluster labels to evaluate.\n\n    Returns\n    -------\n    homogeneity : float\n       Score between 0.0 and 1.0. 1.0 stands for perfectly homogeneous labeling.\n\n    See Also\n    --------\n    completeness_score : Completeness metric of cluster labeling.\n    v_measure_score : V-Measure (NMI with arithmetic mean option).\n\n    References\n    ----------\n\n    .. [1] `Andrew Rosenberg and Julia Hirschberg, 2007. V-Measure: A\n       conditional entropy-based external cluster evaluation measure\n       <https://aclweb.org/anthology/D/D07/D07-1043.pdf>`_\n\n    Examples\n    --------\n\n    Perfect labelings are homogeneous::\n\n      >>> from sklearn.metrics.cluster import homogeneity_score\n      >>> homogeneity_score([0, 0, 1, 1], [1, 1, 0, 0])\n      1.0\n\n    Non-perfect labelings that further split classes into more clusters can be\n    perfectly homogeneous::\n\n      >>> print(\"%.6f\" % homogeneity_score([0, 0, 1, 1], [0, 0, 1, 2]))\n      1.000000\n      >>> print(\"%.6f\" % homogeneity_score([0, 0, 1, 1], [0, 1, 2, 3]))\n      1.000000\n\n    Clusters that include samples from different classes do not make for an\n    homogeneous labeling::\n\n      >>> print(\"%.6f\" % homogeneity_score([0, 0, 1, 1], [0, 1, 0, 1]))\n      0.0...\n      >>> print(\"%.6f\" % homogeneity_score([0, 0, 1, 1], [0, 0, 0, 0]))\n      0.0...\n    ",
            "n_words": 263,
            "vocab_size": 162,
            "n_whitespaces": 443,
            "language": "en"
        }
    },
    {
        "id": 208792,
        "commit_id": "93c8b4d5380d861bf77c590660b93e495bef893b",
        "repo": "ipython",
        "path": "IPython/core/magics/config.py",
        "file_name": "config.py",
        "fun_name": "config",
        "commit_message": "Update ipdoctest test",
        "code": "def config(self, s):\n        \n        from traitlets.config.loader import Config\n        # some IPython objects are Configurable, but do not yet have\n        # any configurable traits.  Exclude them from the effects of\n        # this magic, as their presence is just noise:\n        configurables = sorted(set([ c for c in self.shell.configurables\n                                     if c.__class__.class_traits(config=True)\n                                     ]), key=lambda x: x.__class__.__name__)\n        classnames = [ c.__class__.__name__ for c in configurables ]\n\n        line = s.strip()\n        if not line:\n            # print available configurable names\n            print(\"Available objects for config:\")\n            for name in classnames:\n                print(\"   \", name)\n            return\n        elif line in classnames:\n            # `%config TerminalInteractiveShell` will print trait info for\n            # TerminalInteractiveShell\n            c = configurables[classnames.index(line)]\n            cls = c.__class__\n            help = cls.class_get_help(c)\n            # strip leading '--' from cl-args:\n            help = re.sub(re.compile(r'^--', re.MULTILINE), '', help)\n            print(help)\n            return\n        elif reg.match(line):\n            cls, attr = line.split('.')\n            return getattr(configurables[classnames.index(cls)],attr)\n        elif '=' not in line:\n            msg = \"Invalid config statement: %r, \"\\\n                  \"should be `Class.trait = value`.\"\n            \n            ll = line.lower()\n            for classname in classnames:\n                if ll == classname.lower():\n                    msg = msg + '\\nDid you mean %s (note the case)?' % classname\n                    break\n\n            raise UsageError( msg % line)\n\n        # otherwise, assume we are setting configurables.\n        # leave quotes on args when splitting, because we want\n        # unquoted args to eval in user_ns\n        cfg = Config()\n        exec(\"cfg.\"+line, self.shell.user_ns, locals())\n\n        for configurable in configurables:\n            try:\n                configurable.update_config(cfg)\n            except Exception as e:\n                error(e)\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 775,
        "n_words": 216,
        "vocab_size": 148,
        "complexity": 13,
        "nloc": 38,
        "token_counts": 276,
        "n_ast_nodes": 463,
        "n_identifiers": 48,
        "d_id": 52525,
        "documentation": {
            "docstring": "configure IPython\n\n            %config Class[.trait=value]\n\n        This magic exposes most of the IPython config system. Any\n        Configurable class should be able to be configured with the simple\n        line::\n\n            %config Class.trait=value\n\n        Where `value` will be resolved in the user's namespace, if it is an\n        expression or variable name.\n\n        Examples\n        --------\n\n        To see what classes are available for config, pass no arguments::\n\n            In [1]: %config\n            Available objects for config:\n                AliasManager\n                DisplayFormatter\n                HistoryManager\n                IPCompleter\n                LoggingMagics\n                MagicsManager\n                OSMagics\n                PrefilterManager\n                ScriptMagics\n                TerminalInteractiveShell\n\n        To view what is configurable on a given class, just pass the class\n        name::\n\n            In [2]: %config IPCompleter\n            IPCompleter(Completer) options\n            ----------------------------\n            IPCompleter.backslash_combining_completions=<Bool>\n                Enable unicode completions, e.g. \\\\alpha<tab> . Includes completion of latex\n                commands, unicode names, and expanding unicode characters back to latex\n                commands.\n                Current: True\n            IPCompleter.debug=<Bool>\n                Enable debug for the Completer. Mostly print extra information for\n                experimental jedi integration.\n                Current: False\n            IPCompleter.disable_matchers=<list-item-1>...\n                List of matchers to disable.\n                Current: []\n            IPCompleter.greedy=<Bool>\n                Activate greedy completion\n                        PENDING DEPRECATION. this is now mostly taken care of with Jedi.\n                        This will enable completion on elements of lists, results of function calls, etc.,\n                        but can be unsafe because the code is actually evaluated on TAB.\n                Current: False\n            IPCompleter.jedi_compute_type_timeout=<Int>\n                Experimental: restrict time (in milliseconds) during which Jedi can compute types.\n                        Set to 0 to stop computing types. Non-zero value lower than 100ms may hurt\n                        performance by preventing jedi to build its cache.\n                Current: 400\n            IPCompleter.limit_to__all__=<Bool>\n                DEPRECATED as of version 5.0.\n                Instruct the completer to use __all__ for the completion\n                Specifically, when completing on ``object.<tab>``.\n                When True: only those names in obj.__all__ will be included.\n                When False [default]: the __all__ attribute is ignored\n                Current: False\n            IPCompleter.merge_completions=<Bool>\n                Whether to merge completion results into a single list\n                        If False, only the completion results from the first non-empty\n                        completer will be returned.\n                        As of version 8.5.0, setting the value to ``False`` is an alias for:\n                        ``IPCompleter.suppress_competing_matchers = True.``.\n                Current: True\n            IPCompleter.omit__names=<Enum>\n                Instruct the completer to omit private method names\n                        Specifically, when completing on ``object.<tab>``.\n                        When 2 [default]: all names that start with '_' will be excluded.\n                        When 1: all 'magic' names (``__foo__``) will be excluded.\n                        When 0: nothing will be excluded.\n                Choices: any of [0, 1, 2]\n                Current: 2\n            IPCompleter.profile_completions=<Bool>\n                If True, emit profiling data for completion subsystem using cProfile.\n                Current: False\n            IPCompleter.profiler_output_dir=<Unicode>\n                Template for path at which to output profile data for completions.\n                Current: '.completion_profiles'\n            IPCompleter.suppress_competing_matchers=<Union>\n                Whether to suppress completions from other `Matchers`_.\n                When set to ``None`` (default) the matchers will attempt to auto-detect\n                whether suppression of other matchers is desirable. For example, at the\n                beginning of a line followed by `%` we expect a magic completion to be the\n                only applicable option, and after ``my_dict['`` we usually expect a\n                completion with an existing dictionary key.\n                If you want to disable this heuristic and see completions from all matchers,\n                set ``IPCompleter.suppress_competing_matchers = False``. To disable the\n                heuristic for specific matchers provide a dictionary mapping:\n                ``IPCompleter.suppress_competing_matchers = {'IPCompleter.dict_key_matcher':\n                False}``.\n                Set ``IPCompleter.suppress_competing_matchers = True`` to limit completions\n                to the set of matchers with the highest priority; this is equivalent to\n                ``IPCompleter.merge_completions`` and         can be beneficial for\n                performance, but will sometimes omit relevant candidates from matchers\n                further down the priority list.\n                Current: False\n            IPCompleter.use_jedi=<Bool>\n                Experimental: Use Jedi to generate autocompletions. Default to True if jedi\n                is installed.\n                Current: True\n\n        but the real use is in setting values::\n\n            In [3]: %config IPCompleter.greedy = True\n\n        and these values are read from the user_ns if they are variables::\n\n            In [4]: feeling_greedy=False\n\n            In [5]: %config IPCompleter.greedy = feeling_greedy\n\n        ",
            "n_words": 566,
            "vocab_size": 324,
            "n_whitespaces": 2076,
            "language": "en"
        }
    },
    {
        "id": 258198,
        "commit_id": "4dfddf0d1039e134b1ce5aac748de853e2516735",
        "repo": "haystack",
        "path": "test/document_stores/test_weaviate.py",
        "file_name": "test_weaviate.py",
        "fun_name": "test_ne_filters",
        "commit_message": "refactor: Refactor Weaviate tests (#3541)\n\n* refactor tests\r\n\r\n* fix job\r\n\r\n* revert\r\n\r\n* revert\r\n\r\n* revert\r\n\r\n* use latest weaviate\r\n\r\n* fix abstract methods signatures\r\n\r\n* pass class_name to all the CRUD methods\r\n\r\n* finish moving all the tests\r\n\r\n* bump weaviate version\r\n\r\n* raise, don't pass",
        "code": "def test_ne_filters(self, ds, documents):\n        \n        ds.write_documents(documents)\n\n        result = ds.get_all_documents(filters={\"year\": {\"$ne\": \"2020\"}})\n        assert len(result) == 3\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 41,
        "n_ast_nodes": 72,
        "n_identifiers": 9,
        "d_id": 75197,
        "documentation": {
            "docstring": "\n        Weaviate doesn't include documents if the field is missing,\n        so we customize this test\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 101941,
        "commit_id": "dab823a3eb7a5257cb1e0818ee10ed234d3de97f",
        "repo": "faceswap",
        "path": "lib/gui/utils/image.py",
        "file_name": "image.py",
        "fun_name": "previewoutput",
        "commit_message": "Typing - lib.gui.display_command",
        "code": "def previewoutput(self) -> Tuple[Image.Image, ImageTk.PhotoImage]:\n        \n        assert self._previewoutput is not None\n        return self._previewoutput\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 28,
        "n_ast_nodes": 44,
        "n_identifiers": 7,
        "d_id": 21319,
        "documentation": {
            "docstring": " Tuple: First item in the tuple is the extract or convert preview image\n        (:class:`PIL.Image`), the second item is the image in a format that tkinter can display\n        (:class:`PIL.ImageTK.PhotoImage`).\n\n        The value of the property is ``None`` if no extract or convert task is running or there are\n        no files available in the output folder. ",
            "n_words": 53,
            "vocab_size": 36,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 39221,
        "commit_id": "2b98f1045321475f6537986af134fb53f8320268",
        "repo": "recommenders",
        "path": "contrib/sarplus/python/pysarplus/SARPlus.py",
        "file_name": "SARPlus.py",
        "fun_name": "fit",
        "commit_message": "Correct typos",
        "code": "def fit(self, df):\n        \n        # threshold - items below this number get set to zero in cooccurrence counts\n\n        df.createOrReplaceTempView(self.f(\"{prefix}df_train_input\"))\n\n        if self.timedecay_formula:\n            # WARNING: previously we would take the last value in training dataframe and set it\n            # as a matrix U element\n            # for each user-item pair. Now with time decay, we compute a sum over ratings given\n            # by a user in the case\n            # when T=np.inf, so user gets a cumulative sum of ratings for a particular item and\n            # not the last rating.\n            # Time Decay\n            # does a group by on user item pairs and apply the formula for time decay there\n            # Time T parameter is in days and input time is in seconds,\n            # so we do dt/60/(T*24*60)=dt/(T*24*3600)\n            # the following is the query which we want to run\n\n            query = self.f(\n                \n            )\n\n            # replace with timedecayed version\n            df = self.spark.sql(query)\n        else:\n            # since SQL is case-insensitive, this check needs to be performed similar\n            if self.header[\"col_timestamp\"].lower() in [\n                s.name.lower() for s in df.schema\n            ]:\n                # we need to de-duplicate items by using the latest item\n                query = self.f(\n                    \n                )\n\n                df = self.spark.sql(query)\n\n        df.createOrReplaceTempView(self.f(\"{prefix}df_train\"))\n\n        log.info(\"sarplus.fit 1/2: compute item cooccurrences...\")\n\n        # compute cooccurrence above minimum threshold\n        query = self.f(\n            \n        )\n\n        item_cooccurrence = self.spark.sql(query)\n        item_cooccurrence.write.mode(\"overwrite\").saveAsTable(\n            self.f(\"{prefix}item_cooccurrence\")\n        )\n\n        # compute the diagonal used later for Jaccard and Lift\n        if self.similarity_type == SIM_LIFT or self.similarity_type == SIM_JACCARD:\n            item_marginal = self.spark.sql(\n                self.f(\n                    \"SELECT i1 i, value AS margin FROM {prefix}item_cooccurrence WHERE i1 = i2\"\n                )\n            )\n            item_marginal.createOrReplaceTempView(self.f(\"{prefix}item_marginal\"))\n\n        if self.similarity_type == SIM_COOCCUR:\n            self.item_similarity = item_cooccurrence\n        elif self.similarity_type == SIM_JACCARD:\n            query = self.f(\n                \n            )\n            self.item_similarity = self.spark.sql(query)\n        elif self.similarity_type == SIM_LIFT:\n            query = self.f(\n                \n            )\n            self.item_similarity = self.spark.sql(query)\n        else:\n            raise ValueError(\n                \"Unknown similarity type: {0}\".format(self.similarity_type)\n            )\n\n        # store upper triangular\n        log.info(\n            \"sarplus.fit 2/2: compute similarity metric %s...\" % self.similarity_type\n        )\n        self.item_similarity.write.mode(\"overwrite\").saveAsTable(\n            self.f(\"{prefix}item_similarity_upper\")\n        )\n\n        # expand upper triangular to full matrix\n\n        query = self.f(\n            \n        )\n\n        self.item_similarity = self.spark.sql(query)\n        self.item_similarity.write.mode(\"overwrite\").saveAsTable(\n            self.f(\"{prefix}item_similarity\")\n        )\n\n        # free space\n        self.spark.sql(self.f(\"DROP TABLE {prefix}item_cooccurrence\"))\n        self.spark.sql(self.f(\"DROP TABLE {prefix}item_similarity_upper\"))\n\n        self.item_similarity = self.spark.table(self.f(\"{prefix}item_similarity\"))\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1172,
        "n_words": 329,
        "vocab_size": 175,
        "complexity": 9,
        "nloc": 109,
        "token_counts": 375,
        "n_ast_nodes": 669,
        "n_identifiers": 29,
        "d_id": 7143,
        "documentation": {
            "docstring": "Main fit method for SAR.\n\n        Expects the dataframes to have row_id, col_id columns which are indexes,\n        i.e. contain the sequential integer index of the original alphanumeric user and item IDs.\n        Dataframe also contains rating and timestamp as floats; timestamp is in seconds since Epoch by default.\n\n        Arguments:\n            df (pySpark.DataFrame): input dataframe which contains the index of users and items.\n        \n            SELECT\n                 {col_user}, {col_item}, \n                 SUM({col_rating} * EXP(-log(2) * (latest_timestamp - CAST({col_timestamp} AS long)) / ({time_decay_coefficient} * 3600 * 24))) as {col_rating}\n            FROM {prefix}df_train_input,\n                 (SELECT CAST(MAX({col_timestamp}) AS long) latest_timestamp FROM {prefix}df_train_input)\n            GROUP BY {col_user}, {col_item} \n            CLUSTER BY {col_user} \n            \n                SELECT {col_user}, {col_item}, {col_rating}\n                FROM\n                (\n                SELECT\n                    {col_user}, {col_item}, {col_rating}, \n                    ROW_NUMBER() OVER (PARTITION BY {col_user}, {col_item} ORDER BY {col_timestamp} DESC) latest\n                FROM {prefix}df_train_input\n                )\n                WHERE latest = 1\n                \n        SELECT A.{col_item} i1, B.{col_item} i2, COUNT(*) value\n        FROM   {prefix}df_train A INNER JOIN {prefix}df_train B\n               ON A.{col_user} = B.{col_user} AND A.{col_item} <= b.{col_item}  \n        GROUP  BY A.{col_item}, B.{col_item}\n        HAVING COUNT(*) >= {threshold}\n        CLUSTER BY i1, i2\n        \n            SELECT i1, i2, value / (M1.margin + M2.margin - value) AS value\n            FROM {prefix}item_cooccurrence A \n                INNER JOIN {prefix}item_marginal M1 ON A.i1 = M1.i \n                INNER JOIN {prefix}item_marginal M2 ON A.i2 = M2.i\n            CLUSTER BY i1, i2\n            \n            SELECT i1, i2, value / (M1.margin * M2.margin) AS value\n            FROM {prefix}item_cooccurrence A \n                INNER JOIN {prefix}item_marginal M1 ON A.i1 = M1.i \n                INNER JOIN {prefix}item_marginal M2 ON A.i2 = M2.i\n            CLUSTER BY i1, i2\n            \n        SELECT i1, i2, value\n        FROM\n        (\n          (SELECT i1, i2, value FROM {prefix}item_similarity_upper)\n          UNION ALL\n          (SELECT i2 i1, i1 i2, value FROM {prefix}item_similarity_upper WHERE i1 <> i2)\n        )\n        CLUSTER BY i1\n        ",
            "n_words": 255,
            "vocab_size": 133,
            "n_whitespaces": 854,
            "language": "en"
        }
    },
    {
        "id": 46787,
        "commit_id": "4ffd4f09532fceb67675fce4c1f5cd383eff992e",
        "repo": "airflow",
        "path": "dev/breeze/src/airflow_breeze/utils/docker_command_utils.py",
        "file_name": "docker_command_utils.py",
        "fun_name": "check_docker_permission",
        "commit_message": "Prepare Breeze2 for prime time :) (#22713)\n\nThis is a review and clean-up for all the parameters and\r\ncommands for Breeze2 in order to prepare it for being\r\nused by the contribugors.\r\n\r\nThere are various small fixes here and there, removal\r\nof duplicated code, refactoring and moving code around\r\nas well as cleanup and review all the parameters used\r\nfor all implemented commands.\r\n\r\nThe parameters, default values and their behaviours were\r\nupdated to match \"new\" life of Breeze rather than old\r\none.\r\n\r\nSome improvements are made to the autocomplete and\r\nclick help messages printed.  Full list of choices is\r\nalways displayed, parameters are groups according to\r\ntheir target audience, and they were sorted according\r\nto importance and frequency of use.\r\n\r\nVarious messages have been colourised according to their\r\nmeaning - warnings as yellow, errors as red and\r\ninformational messages as bright_blue.\r\n\r\nThe `dry-run` option has been added to just show what\r\nwould have been run without actually running some\r\npotentially \"write\" commands (read commands are still\r\nexecuted) so that you can easily verify and manually\r\ncopy and execute the commands with option to modify\r\nthem before. The `dry_run` and `verbose` options are\r\nnow used for all commands.\r\n\r\nThe \"main\" command now runs \"shell\" by default similarly\r\nas the original Breeze.\r\n\r\nAll \"shortcut\" parameters have been standardized - i.e\r\ncommon options (verbose/dry run/help) have one and all\r\ncommon flags that are likely to be used often have an\r\nassigned shortcute.\r\n\r\nThe \"stop\" and \"cleanup\" command have been added\r\nas they are necessary for average user to complete the\r\nregular usage cycle.\r\n\r\nDocumentation for all the important methods have been\r\nupdated.",
        "code": "def check_docker_permission(verbose) -> bool:\n    \n    permission_denied = False\n    docker_permission_command = [\"docker\", \"info\"]\n    try:\n        _ = run_command(\n            docker_permission_command,\n            verbose=verbose,\n            no_output_dump_on_exception=True,\n            capture_output=True,\n            text=True,\n            check=True,\n        )\n    except subprocess.CalledProcessError as ex:\n        permission_denied = True\n        if ex.stdout and 'Got permission denied while trying to connect' in ex.stdout:\n            console.print('ERROR: You have `permission denied` error when trying to communicate with docker.')\n            console.print(\n                'Most likely you need to add your user to `docker` group: \\\n                https://docs.docker.com/ engine/install/linux-postinstall/ .'\n            )\n    return permission_denied\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 247,
        "n_words": 72,
        "vocab_size": 62,
        "complexity": 4,
        "nloc": 29,
        "token_counts": 82,
        "n_ast_nodes": 139,
        "n_identifiers": 17,
        "d_id": 8991,
        "documentation": {
            "docstring": "\n    Checks if we have permission to write to docker socket. By default, on Linux you need to add your user\n    to docker group and some new users do not realize that. We help those users if we have\n    permission to run docker commands.\n\n    :param verbose: print commands when running\n    :return: True if permission is denied.\n    ",
            "n_words": 55,
            "vocab_size": 42,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 127982,
        "commit_id": "e50165492587556dac318418a0121e72bf93baa7",
        "repo": "ray",
        "path": "rllib/algorithms/ppo/tests/test_ppo.py",
        "file_name": "test_ppo.py",
        "fun_name": "test_ppo_legacy_config",
        "commit_message": "Revert \"[RLlib] @deprecate(error=True|False) escalation. (#28733)\" (#28795)\n\nSigned-off-by: Amog Kamsetty amogkamsetty@yahoo.com\r\n\r\nReverts #28733\r\n\r\nBreaks ray-air/examples:rl_offline_example and ray-air/examples:rl_online_example",
        "code": "def test_ppo_legacy_config(self):\n        \n        ppo_config = ppo.DEFAULT_CONFIG\n        # Expect warning.\n        print(f\"Accessing learning-rate from legacy config dict: {ppo_config['lr']}\")\n        # Build Algorithm.\n        ppo_trainer = ppo.PPO(config=ppo_config, env=\"CartPole-v1\")\n        print(ppo_trainer.train())\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 72,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 38,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 28577,
        "documentation": {
            "docstring": "Tests, whether the old PPO config dict is still functional.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 266732,
        "commit_id": "a06fa496d3f837cca3c437ab6e9858525633d147",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/commands/coverage/analyze/targets/missing.py",
        "file_name": "missing.py",
        "fun_name": "command_coverage_analyze_targets_missing",
        "commit_message": "ansible-test - Code cleanup and refactoring. (#77169)\n\n* Remove unnecessary PyCharm ignores.\r\n* Ignore intentional undefined attribute usage.\r\n* Add missing type hints. Fix existing type hints.\r\n* Fix docstrings and comments.\r\n* Use function to register completion handler.\r\n* Pass strings to display functions.\r\n* Fix CompositeAction handling of dest argument.\r\n* Use consistent types in expressions/assignments.\r\n* Use custom function to keep linters happy.\r\n* Add missing raise for custom exception.\r\n* Clean up key/value type handling in cloud plugins.\r\n* Use dataclass instead of dict for results.\r\n* Add custom type_guard function to check lists.\r\n* Ignore return type that can't be checked (yet).\r\n* Avoid changing types on local variables.",
        "code": "def command_coverage_analyze_targets_missing(args):  # type: (CoverageAnalyzeTargetsMissingConfig) -> None\n    \n    host_state = prepare_profiles(args)  # coverage analyze targets missing\n\n    if args.delegate:\n        raise Delegate(host_state=host_state)\n\n    from_targets, from_path_arcs, from_path_lines = read_report(args.from_file)\n    to_targets, to_path_arcs, to_path_lines = read_report(args.to_file)\n    target_indexes = {}  # type: TargetIndexes\n\n    if args.only_gaps:\n        arcs = find_gaps(from_path_arcs, from_targets, to_path_arcs, target_indexes, args.only_exists)\n        lines = find_gaps(from_path_lines, from_targets, to_path_lines, target_indexes, args.only_exists)\n    else:\n        arcs = find_missing(from_path_arcs, from_targets, to_path_arcs, to_targets, target_indexes, args.only_exists)\n        lines = find_missing(from_path_lines, from_targets, to_path_lines, to_targets, target_indexes, args.only_exists)\n\n    report = make_report(target_indexes, arcs, lines)\n    write_report(args, report, args.output_file)\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 144,
        "n_words": 76,
        "vocab_size": 47,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 147,
        "n_ast_nodes": 216,
        "n_identifiers": 26,
        "d_id": 78543,
        "documentation": {
            "docstring": "Identify aggregated coverage in one file missing from another.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 106355,
        "commit_id": "0700fde6403aa9eec1ff02bff7323696a205900c",
        "repo": "youtube-dl",
        "path": "youtube_dl/extractor/openload.py",
        "file_name": "openload.py",
        "fun_name": "get",
        "commit_message": "[utils, etc] Kill child processes when yt-dl is killed\n\n* derived from PR #26592, closes #26592\n\nAuthored by: Unrud",
        "code": "def get(self, url, html=None, video_id=None, note=None, note2='Executing JS on webpage', headers={}, jscode='saveAndExit();'):\n        \n        if 'saveAndExit();' not in jscode:\n            raise ExtractorError('`saveAndExit();` not found in `jscode`')\n        if not html:\n            html = self.extractor._download_webpage(url, video_id, note=note, headers=headers)\n        with open(self._TMP_FILES['html'].name, 'wb') as f:\n            f.write(html.encode('utf-8'))\n\n        self._save_cookies(url)\n\n        replaces = self.options\n        replaces['url'] = url\n        user_agent = headers.get('User-Agent') or std_headers['User-Agent']\n        replaces['ua'] = user_agent.replace('\"', '\\\\\"')\n        replaces['jscode'] = jscode\n\n        for x in self._TMP_FILE_NAMES:\n            replaces[x] = self._TMP_FILES[x].name.replace('\\\\', '\\\\\\\\').replace('\"', '\\\\\"')\n\n        with open(self._TMP_FILES['script'].name, 'wb') as f:\n            f.write(self._TEMPLATE.format(**replaces).encode('utf-8'))\n\n        if video_id is None:\n            self.extractor.to_screen('%s' % (note2,))\n        else:\n            self.extractor.to_screen('%s: %s' % (video_id, note2))\n\n        p = subprocess.Popen([\n            self.exe, '--ssl-protocol=any',\n            self._TMP_FILES['script'].name\n        ], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n        out, err = process_communicate_or_kill(p)\n        if p.returncode != 0:\n            raise ExtractorError(\n                'Executing JS failed\\n:' + encodeArgument(err))\n        with open(self._TMP_FILES['html'].name, 'rb') as f:\n            html = f.read().decode('utf-8')\n\n        self._load_cookies()\n\n        return (html, encodeArgument(out))\n",
        "url": "https://github.com/ytdl-org/youtube-dl.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 404,
        "n_words": 121,
        "vocab_size": 92,
        "complexity": 7,
        "nloc": 33,
        "token_counts": 352,
        "n_ast_nodes": 604,
        "n_identifiers": 44,
        "d_id": 22352,
        "documentation": {
            "docstring": "\n        Downloads webpage (if needed) and executes JS\n\n        Params:\n            url: website url\n            html: optional, html code of website\n            video_id: video id\n            note: optional, displayed when downloading webpage\n            note2: optional, displayed when executing JS\n            headers: custom http headers\n            jscode: code to be executed when page is loaded\n\n        Returns tuple with:\n            * downloaded website (after JS execution)\n            * anything you print with `console.log` (but not inside `page.execute`!)\n\n        In most cases you don't need to add any `jscode`.\n        It is executed in `page.onLoadFinished`.\n        `saveAndExit();` is mandatory, use it instead of `phantom.exit()`\n        It is possible to wait for some element on the webpage, for example:\n            var check = function() {\n              var elementFound = page.evaluate(function() {\n                return document.querySelector('#b.done') !== null;\n              });\n              if(elementFound)\n                saveAndExit();\n              else\n                window.setTimeout(check, 500);\n            }\n\n            page.evaluate(function(){\n              document.querySelector('#a').click();\n            });\n            check();\n        ",
            "n_words": 125,
            "vocab_size": 99,
            "n_whitespaces": 446,
            "language": "en"
        }
    },
    {
        "id": 269545,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "all",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def all(x, axis=None, keepdims=False):\n    \n    x = tf.cast(x, tf.bool)\n    return tf.reduce_all(x, axis, keepdims)\n\n\n@keras_export(\"keras.backend.argmax\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.argmax\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 21,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 37,
        "n_ast_nodes": 85,
        "n_identifiers": 14,
        "d_id": 80171,
        "documentation": {
            "docstring": "Bitwise reduction (logical AND).\n\n    Args:\n        x: Tensor or variable.\n        axis: axis along which to perform the reduction.\n        keepdims: whether the drop or broadcast the reduction axes.\n\n    Returns:\n        A uint8 tensor (0s and 1s).\n    ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 91722,
        "commit_id": "7f60db924ea37f34e0cfe6856777239e2a2ffe13",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_postgres_indexer.py",
        "file_name": "test_postgres_indexer.py",
        "fun_name": "test_get_db_records",
        "commit_message": "feat(metrics): make indexer more configurable (#35604)\n\nThis makes the sentry_metrics indexer more configurable in the following ways, to enable indexing on the ingest-performance-metrics topic:\r\n\r\n- configurable input Kafka topic\r\n- configurable output Kafka topic\r\n- configurable model from which to pull index results\r\n- tags for internal metrics to distinguish between the two modes operationally",
        "code": "def test_get_db_records(self):\n        \n        string = StringIndexer.objects.create(organization_id=123, string=\"oop\")\n        collection = KeyCollection({123: {\"oop\"}})\n        key = \"123:oop\"\n\n        assert indexer_cache.get(key) is None\n        assert indexer_cache.get(string.id) is None\n\n        self.indexer._get_db_records(self.use_case_id, collection)\n\n        assert indexer_cache.get(string.id) is None\n        assert indexer_cache.get(key) is None\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 94,
        "n_words": 31,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 89,
        "n_ast_nodes": 147,
        "n_identifiers": 16,
        "d_id": 18794,
        "documentation": {
            "docstring": "\n        Make sure that calling `_get_db_records` doesn't populate the cache\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 221226,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/calendar.py",
        "file_name": "calendar.py",
        "fun_name": "weekday",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def weekday(year, month, day):\n    \n    if not datetime.MINYEAR <= year <= datetime.MAXYEAR:\n        year = 2000 + year % 400\n    return datetime.date(year, month, day).weekday()\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 38,
        "n_words": 22,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 44,
        "n_ast_nodes": 68,
        "n_identifiers": 8,
        "d_id": 56278,
        "documentation": {
            "docstring": "Return weekday (0-6 ~ Mon-Sun) for year, month (1-12), day (1-31).",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 132255,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/schedulers/pb2.py",
        "file_name": "pb2.py",
        "fun_name": "select_config",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def select_config(Xraw, yraw, current, newpoint, bounds, num_f):\n    \n    length = select_length(Xraw, yraw, bounds, num_f)\n\n    Xraw = Xraw[-length:, :]\n    yraw = yraw[-length:]\n\n    base_vals = np.array(list(bounds.values())).T\n    oldpoints = Xraw[:, :num_f]\n    old_lims = np.concatenate(\n        (np.max(oldpoints, axis=0), np.min(oldpoints, axis=0))\n    ).reshape(2, oldpoints.shape[1])\n    limits = np.concatenate((old_lims, base_vals), axis=1)\n\n    X = normalize(Xraw, limits)\n    y = standardize(yraw).reshape(yraw.size, 1)\n\n    fixed = normalize(newpoint, oldpoints)\n\n    kernel = TV_SquaredExp(\n        input_dim=X.shape[1], variance=1.0, lengthscale=1.0, epsilon=0.1\n    )\n\n    try:\n        m = GPy.models.GPRegression(X, y, kernel)\n    except np.linalg.LinAlgError:\n        # add diagonal ** we would ideally make this something more robust...\n        X += np.eye(X.shape[0]) * 1e-3\n        m = GPy.models.GPRegression(X, y, kernel)\n\n    try:\n        m.optimize()\n    except np.linalg.LinAlgError:\n        # add diagonal ** we would ideally make this something more robust...\n        X += np.eye(X.shape[0]) * 1e-3\n        m = GPy.models.GPRegression(X, y, kernel)\n        m.optimize()\n\n    m.kern.lengthscale.fix(m.kern.lengthscale.clip(1e-5, 1))\n\n    if current is None:\n        m1 = deepcopy(m)\n    else:\n        # add the current trials to the dataset\n        padding = np.array([fixed for _ in range(current.shape[0])])\n        current = normalize(current, base_vals)\n        current = np.hstack((padding, current))\n\n        Xnew = np.vstack((X, current))\n        ypad = np.zeros(current.shape[0])\n        ypad = ypad.reshape(-1, 1)\n        ynew = np.vstack((y, ypad))\n\n        # kernel = GPy.kern.RBF(input_dim=X.shape[1], variance=1.,\n        # lengthscale=1.)\n        kernel = TV_SquaredExp(\n            input_dim=X.shape[1], variance=1.0, lengthscale=1.0, epsilon=0.1\n        )\n        m1 = GPy.models.GPRegression(Xnew, ynew, kernel)\n        m1.optimize()\n\n    xt = optimize_acq(UCB, m, m1, fixed, num_f)\n\n    # convert back...\n    xt = xt * (np.max(base_vals, axis=0) - np.min(base_vals, axis=0)) + np.min(\n        base_vals, axis=0\n    )\n\n    xt = xt.astype(np.float32)\n    return xt\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 497,
        "n_words": 216,
        "vocab_size": 127,
        "complexity": 5,
        "nloc": 49,
        "token_counts": 536,
        "n_ast_nodes": 783,
        "n_identifiers": 63,
        "d_id": 29714,
        "documentation": {
            "docstring": "Selects the next hyperparameter config to try.\n\n    This function takes the formatted data, fits the GP model and optimizes the\n    UCB acquisition function to select the next point.\n\n    Args:\n        Xraw (np.array): The un-normalized array of hyperparams, Time and\n            Reward\n        yraw (np.array): The un-normalized vector of reward changes.\n        current (list): The hyperparams of trials currently running. This is\n            important so we do not select the same config twice. If there is\n            data here then we fit a second GP including it\n            (with fake y labels). The GP variance doesn't depend on the y\n            labels so it is ok.\n        newpoint (np.array): The Reward and Time for the new point.\n            We cannot change these as they are based on the *new weights*.\n        bounds (dict): Bounds for the hyperparameters. Used to normalize.\n        num_f (int): The number of fixed params. Almost always 2 (reward+time)\n\n    Return:\n        xt (np.array): A vector of new hyperparameters.\n    ",
            "n_words": 147,
            "vocab_size": 100,
            "n_whitespaces": 277,
            "language": "en"
        }
    },
    {
        "id": 132977,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/collective/collective_group/gloo_collective_group.py",
        "file_name": "gloo_collective_group.py",
        "fun_name": "broadcast",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def broadcast(self, tensors, broadcast_options=BroadcastOptions()):\n        \n        root_rank = broadcast_options.root_rank\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 31,
        "n_ast_nodes": 32,
        "n_identifiers": 6,
        "d_id": 29889,
        "documentation": {
            "docstring": "Broadcast tensors to all other processes following options.\n\n        Args:\n            tensors (List): tensors to be broadcast or received.\n            broadcast_options: broadcast options.\n\n        Returns:\n            None\n        ",
            "n_words": 22,
            "vocab_size": 17,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 204769,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/serializers/xml_serializer.py",
        "file_name": "xml_serializer.py",
        "fun_name": "_handle_fk_field_node",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _handle_fk_field_node(self, node, field):\n        \n        # Check if there is a child node named 'None', returning None if so.\n        if node.getElementsByTagName(\"None\"):\n            return None\n        else:\n            model = field.remote_field.model\n            if hasattr(model._default_manager, \"get_by_natural_key\"):\n                keys = node.getElementsByTagName(\"natural\")\n                if keys:\n                    # If there are 'natural' subelements, it must be a natural key\n                    field_value = [getInnerText(k).strip() for k in keys]\n                    try:\n                        obj = model._default_manager.db_manager(\n                            self.db\n                        ).get_by_natural_key(*field_value)\n                    except ObjectDoesNotExist:\n                        if self.handle_forward_references:\n                            return base.DEFER_FIELD\n                        else:\n                            raise\n                    obj_pk = getattr(obj, field.remote_field.field_name)\n                    # If this is a natural foreign key to an object that\n                    # has a FK/O2O as the foreign key, use the FK value\n                    if field.remote_field.model._meta.pk.remote_field:\n                        obj_pk = obj_pk.pk\n                else:\n                    # Otherwise, treat like a normal PK\n                    field_value = getInnerText(node).strip()\n                    obj_pk = model._meta.get_field(\n                        field.remote_field.field_name\n                    ).to_python(field_value)\n                return obj_pk\n            else:\n                field_value = getInnerText(node).strip()\n                return model._meta.get_field(field.remote_field.field_name).to_python(\n                    field_value\n                )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 769,
        "n_words": 126,
        "vocab_size": 83,
        "complexity": 8,
        "nloc": 32,
        "token_counts": 194,
        "n_ast_nodes": 324,
        "n_identifiers": 29,
        "d_id": 50882,
        "documentation": {
            "docstring": "\n        Handle a <field> node for a ForeignKey\n        ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 70769,
        "commit_id": "29a7f701611d22ab9c7f12f1134aeac1d31b9438",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_get_relevant_site_root_paths",
        "commit_message": "Add Page._get_relevant_site_root_paths() for use in signal handlers",
        "code": "def _get_relevant_site_root_paths(self, cache_object=None):\n        \n        return tuple(\n            srp\n            for srp in self._get_site_root_paths(cache_object)\n            if self.url_path.startswith(srp.root_path)\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 67,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 35,
        "n_ast_nodes": 56,
        "n_identifiers": 9,
        "d_id": 15553,
        "documentation": {
            "docstring": "\n        .. versionadded::2.16\n\n        Returns a tuple of root paths for all sites this page belongs to.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 269271,
        "commit_id": "06f5ef7989db314ee210455b04fe6f71e8dc57a7",
        "repo": "keras",
        "path": "keras/utils/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "_get_data_iterator_from_dataset",
        "commit_message": "Export split_dataset utility.\n\nPiperOrigin-RevId: 447783753",
        "code": "def _get_data_iterator_from_dataset(dataset, dataset_type_spec):\n  \n  if dataset_type_spec == list:\n    if len(dataset) == 0:\n      raise ValueError('Received an empty list dataset. '\n                       'Please provide a non-empty list of arrays.')\n\n    if _get_type_spec(dataset[0]) is np.ndarray:\n      expected_shape = dataset[0].shape\n      for i, element in enumerate(dataset):\n        if np.array(element).shape[0] != expected_shape[0]:\n          raise ValueError('Received a list of NumPy arrays with different '\n                           f'lengths. Mismatch found at index {i}, '\n                           f'Expected shape={expected_shape} '\n                           f'Received shape={np.array(element).shape}.'\n                           f'Please provide a list of NumPy arrays with '\n                           f'the same length.')\n    else:\n      raise ValueError('Expected a list of `numpy.ndarray` objects,'\n                       f'Received: {type(dataset[0])}')\n\n    return iter(zip(*dataset))\n  elif dataset_type_spec == tuple:\n    if len(dataset) == 0:\n      raise ValueError('Received an empty list dataset.'\n                       'Please provide a non-empty tuple of arrays.')\n\n    if _get_type_spec(dataset[0]) is np.ndarray:\n      expected_shape = dataset[0].shape\n      for i, element in enumerate(dataset):\n        if np.array(element).shape[0] != expected_shape[0]:\n          raise ValueError('Received a tuple of NumPy arrays with different '\n                           f'lengths. Mismatch found at index {i}, '\n                           f'Expected shape={expected_shape} '\n                           f'Received shape={np.array(element).shape}.'\n                           f'Please provide a tuple of NumPy arrays with '\n                           'the same length.')\n    else:\n      raise ValueError('Expected a tuple of `numpy.ndarray` objects, '\n                       f'Received: {type(dataset[0])}')\n\n    return iter(zip(*dataset))\n  elif dataset_type_spec == tf.data.Dataset:\n    if is_batched(dataset):\n      dataset = dataset.unbatch()\n    return iter(dataset)\n  elif dataset_type_spec == np.ndarray:\n    return iter(dataset)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 651,
        "n_words": 188,
        "vocab_size": 73,
        "complexity": 14,
        "nloc": 43,
        "token_counts": 248,
        "n_ast_nodes": 486,
        "n_identifiers": 24,
        "d_id": 79995,
        "documentation": {
            "docstring": "Get the iterator from a dataset.\n\n  Args:\n      dataset :  A `tf.data.Dataset` object or a list/tuple of arrays.\n      dataset_type_spec : the type of the dataset\n\n  Raises:\n      ValueError:\n                - If the dataset is empty.\n                - If the dataset is not a `tf.data.Dataset` object\n                  or a list/tuple of arrays.\n                - If the dataset is a list/tuple of arrays and the\n                  length of the list/tuple is not equal to the number\n\n  Returns:\n      iterator: An `iterator` object.\n  ",
            "n_words": 72,
            "vocab_size": 36,
            "n_whitespaces": 176,
            "language": "en"
        }
    },
    {
        "id": 223429,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/doctest.py",
        "file_name": "doctest.py",
        "fun_name": "get",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get(self):\n        \n\n        return self.val\n\n__test__ = {\"_TestClass\": _TestClass,\n            \"string\": r,\n\n            \"bool-int equivalence\": r,\n\n            \"blank lines\": r,\n\n            \"ellipsis\": r,\n\n            \"whitespace normalization\": r,\n           }\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 100,
        "n_words": 22,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 78,
        "n_identifiers": 5,
        "d_id": 56895,
        "documentation": {
            "docstring": "get() -> return TestClass's associated value.\n\n        >>> x = _TestClass(-42)\n        >>> print(x.get())\n        -42\n        \n                      Example of a string object, searched as-is.\n                      >>> x = 1; y = 2\n                      >>> x + y, x * y\n                      (3, 2)\n                      \n                                    In 2.2, boolean expressions displayed\n                                    0 or 1.  By default, we still accept\n                                    them.  This can be disabled by passing\n                                    DONT_ACCEPT_TRUE_FOR_1 to the new\n                                    optionflags argument.\n                                    >>> 4 == 4\n                                    1\n                                    >>> 4 == 4\n                                    True\n                                    >>> 4 > 4\n                                    0\n                                    >>> 4 > 4\n                                    False\n                                    \n                Blank lines can be marked with <BLANKLINE>:\n                    >>> print('foo\\n\\nbar\\n')\n                    foo\n                    <BLANKLINE>\n                    bar\n                    <BLANKLINE>\n            \n                If the ellipsis flag is used, then '...' can be used to\n                elide substrings in the desired output:\n                    >>> print(list(range(1000))) #doctest: +ELLIPSIS\n                    [0, 1, 2, ..., 999]\n            \n                If the whitespace normalization flag is used, then\n                differences in whitespace are ignored.\n                    >>> print(list(range(30))) #doctest: +NORMALIZE_WHITESPACE\n                    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,\n                     15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26,\n                     27, 28, 29]\n            ",
            "n_words": 169,
            "vocab_size": 123,
            "n_whitespaces": 1118,
            "language": "en"
        }
    },
    {
        "id": 119182,
        "commit_id": "d9dcd1394aedf760272f14c3560cd5415495c28a",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "_where",
        "commit_message": "djax: let make_jaxpr build dyn shape jaxprs",
        "code": "def _where(condition, x=None, y=None):\n  if x is None or y is None:\n    raise ValueError(\"Either both or neither of the x and y arguments should \"\n                     \"be provided to jax.numpy.where, got {} and {}.\"\n                     .format(x, y))\n  if not issubdtype(_dtype(condition), bool_):\n    condition = lax.ne(condition, zeros_like(condition))\n  x, y = _promote_dtypes(x, y)\n  condition, x, y = broadcast_arrays(condition, x, y)\n  try: is_always_empty = core.is_empty_shape(np.shape(x))\n  except: is_always_empty = False  # can fail with dynamic shapes\n  return lax.select(condition, x, y) if not is_always_empty else x\n\n\n_WHERE_DOC = \n\n@_wraps(np.where, update_doc=False, lax_description=_WHERE_DOC)",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.where, update_doc=False, lax_description=_WHERE_DOC)",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 135,
        "n_words": 83,
        "vocab_size": 60,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 120,
        "n_ast_nodes": 217,
        "n_identifiers": 25,
        "d_id": 26551,
        "documentation": {
            "docstring": "\\\nAt present, JAX does not support JIT-compilation of the single-argument form\nof :py:func:`jax.numpy.where` because its output shape is data-dependent. The\nthree-argument form does not have a data-dependent shape and can be JIT-compiled\nsuccessfully. Alternatively, you can specify the optional ``size`` keyword:\nif specified, the first ``size`` True elements will be returned; if there\nare fewer True elements than ``size`` indicates, the index arrays will be\npadded with ``fill_value`` (default is 0.)\n",
            "n_words": 72,
            "vocab_size": 54,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 276217,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/saving/saved_model_experimental.py",
        "file_name": "saved_model_experimental.py",
        "fun_name": "_get_variables_path",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _get_variables_path(export_dir):\n    \n    return tf.io.gfile.join(\n        tf.compat.as_text(_get_variables_dir(export_dir)),\n        tf.compat.as_text(tf.saved_model.VARIABLES_FILENAME),\n    )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 30,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 41,
        "n_ast_nodes": 66,
        "n_identifiers": 11,
        "d_id": 81598,
        "documentation": {
            "docstring": "Return the variables path, used as the prefix for checkpoint files.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 95947,
        "commit_id": "51403cc4c85c9c595a3b2d0ab5c2c1c4e33a3a1e",
        "repo": "sentry",
        "path": "tests/sentry/utils/test_snuba.py",
        "file_name": "test_snuba.py",
        "fun_name": "test_quantize_time_jitter",
        "commit_message": "fix(sessions): Prevent query mutation behavior in `_prepare_query_params` (#31422)\n\n* fix(sessions): Prevent query mutation behavior in `_prepare_query_params`\r\n\r\nFixes the behavior of `_prepare_query_params`\r\nthat mutates the conditions passed from the query.\r\n\r\n* Add test that validates the change",
        "code": "def test_quantize_time_jitter(self):\n        \n        i = j = None\n        starting_key = quantize_time(self.now, 0, duration=10)\n        for i in range(11):\n            current_key = quantize_time(self.now + timedelta(seconds=i), 0, duration=10)\n            if current_key != starting_key:\n                break\n\n        other_key = quantize_time(self.now, 5, duration=10)\n        for j in range(11):\n            current_key = quantize_time(self.now + timedelta(seconds=j), 5, duration=10)\n            if current_key != other_key:\n                break\n\n        assert i != j\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 176,
        "n_words": 53,
        "vocab_size": 26,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 113,
        "n_ast_nodes": 173,
        "n_identifiers": 13,
        "d_id": 19259,
        "documentation": {
            "docstring": "Different key hashes should change keys at different times\n\n        While starting_key and other_key might begin as the same values they should change at different times\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 189806,
        "commit_id": "8841e39a20b501e38091df126a62bb7440931089",
        "repo": "manim",
        "path": "manim/utils/simple_functions.py",
        "file_name": "simple_functions.py",
        "fun_name": "clip",
        "commit_message": "Document and type `simple_functions.py` (#2674)\n\n* 🏷️ Add types to simple_functions.py\r\n\r\n* 💄 Neaten binary_search()\r\n\r\nAdd spacing between signature and code.\r\nRemove and expressions and address IDE warnings\r\n\r\n* 📝 Add docstrings for functions in simple_functions.py\r\n\r\n* 🎨 Reorder functions alphabetically\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* 🐛 Reformat code examples\r\n\r\nThese were causing checks to fail due to missing spaces after `>>>`\r\nI had wanted to change these to be more consistent with iterables.py anyway.\r\n\r\n* 🎨 Change single tics to double\r\n\r\nChange \\` to \\`` - this ensures that the variable names are actually\r\ndisplayed as code (and not italics)\r\n\r\n* improved docstrings, rewrote examples as doctests\r\n\r\n* fix (???) unrelated failing doctest\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fixed typo\r\n\r\n* Update manim/utils/simple_functions.py\r\n\r\nCo-authored-by: Luca <30503695+tameTNT@users.noreply.github.com>\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>",
        "code": "def clip(a, min_a, max_a):\n    \n    if a < min_a:\n        return min_a\n    elif a > max_a:\n        return max_a\n    return a\n\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 44,
        "n_words": 18,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 26,
        "n_ast_nodes": 42,
        "n_identifiers": 4,
        "d_id": 46218,
        "documentation": {
            "docstring": "Clips ``a`` to the interval [``min_a``, ``max_a``].\n\n    Accepts any comparable objects (i.e. those that support <, >).\n    Returns ``a`` if it is between ``min_a`` and ``max_a``.\n    Otherwise, whichever of ``min_a`` and ``max_a`` is closest.\n\n    Examples\n    --------\n    ::\n\n        >>> clip(15, 11, 20)\n        15\n        >>> clip('a', 'h', 'k')\n        'h'\n    ",
            "n_words": 47,
            "vocab_size": 42,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 119949,
        "commit_id": "fbfc3d8edfbf8dc5eb2f38c2bb315646a94ad399",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "fromiter",
        "commit_message": "Better error messages for jnp.fromiter and jnp.fromfile",
        "code": "def fromiter(*args, **kwargs):\n  \n  raise NotImplementedError(\n    \"jnp.fromiter() is not implemented because it may be non-pure and thus unsafe for use \"\n    \"with JIT and other JAX transformations. Consider using jnp.asarray(np.fromiter(...)) \"\n    \"instead, although care should be taken if np.fromiter is used within a jax transformations \"\n    \"because of its potential side-effect of consuming the iterable object; for more information see \"\n    \"https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#pure-functions\")\n\n\n@_wraps(np.fromfunction)",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.fromfunction)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 78,
        "n_words": 62,
        "vocab_size": 54,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 19,
        "n_ast_nodes": 54,
        "n_identifiers": 7,
        "d_id": 26720,
        "documentation": {
            "docstring": "Unimplemented JAX wrapper for jnp.fromiter.\n\n  This function is left deliberately unimplemented because it may be non-pure and thus\n  unsafe for use with JIT and other JAX transformations. Consider using\n  ``jnp.asarray(np.fromiter(...))`` instead, although care should be taken if ``np.fromiter``\n  is used within jax transformations because of its potential side-effect of consuming the\n  iterable object; for more information see `Common Gotchas: Pure Functions\n  <https://jax.readthedocs.io/en/latest/notebooks/Common_Gotchas_in_JAX.html#pure-functions>`_.\n  ",
            "n_words": 62,
            "vocab_size": 54,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 119978,
        "commit_id": "3184dd65a222354bffa2466d9a375162f5649132",
        "repo": "jax",
        "path": "jax/experimental/sparse/bcoo.py",
        "file_name": "bcoo.py",
        "fun_name": "bcoo_multiply_sparse",
        "commit_message": "[sparse] Update docstrings for bcoo primitives.\n\nPiperOrigin-RevId: 438685829",
        "code": "def bcoo_multiply_sparse(lhs, rhs):\n  \n  out_data, out_indices, out_shape = _bcoo_multiply_sparse(\n      lhs.data, lhs.indices, rhs.data, rhs.indices, lhs_spinfo=lhs._info,\n      rhs_spinfo=rhs._info)\n  return BCOO((out_data, out_indices), shape=out_shape)\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 31,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 57,
        "n_ast_nodes": 82,
        "n_identifiers": 14,
        "d_id": 26730,
        "documentation": {
            "docstring": "An element-wise multiplication of two sparse arrays.\n\n  Args:\n    lhs: A BCOO-format array.\n    rhs: A BCOO-format array.\n\n  Returns:\n    An BCOO-format array containing the result.\n  ",
            "n_words": 23,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 276983,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/metrics_utils.py",
        "file_name": "metrics_utils.py",
        "fun_name": "sparse_top_k_categorical_matches",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def sparse_top_k_categorical_matches(y_true, y_pred, k=5):\n    \n    reshape_matches = False\n    y_true = tf.convert_to_tensor(y_true)\n    y_pred = tf.convert_to_tensor(y_pred)\n    y_true_rank = y_true.shape.ndims\n    y_pred_rank = y_pred.shape.ndims\n    y_true_org_shape = tf.shape(y_true)\n\n    # Flatten y_pred to (batch_size, num_samples) and y_true to (num_samples,)\n    if (y_true_rank is not None) and (y_pred_rank is not None):\n        if y_pred_rank > 2:\n            y_pred = tf.reshape(y_pred, [-1, y_pred.shape[-1]])\n        if y_true_rank > 1:\n            reshape_matches = True\n            y_true = tf.reshape(y_true, [-1])\n\n    matches = tf.cast(\n        tf.math.in_top_k(\n            predictions=y_pred, targets=tf.cast(y_true, \"int32\"), k=k\n        ),\n        dtype=backend.floatx(),\n    )\n\n    # returned matches is expected to have same shape as y_true input\n    if reshape_matches:\n        return tf.reshape(matches, shape=y_true_org_shape)\n\n    return matches\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 220,
        "n_words": 92,
        "vocab_size": 61,
        "complexity": 6,
        "nloc": 22,
        "token_counts": 172,
        "n_ast_nodes": 268,
        "n_identifiers": 22,
        "d_id": 81815,
        "documentation": {
            "docstring": "Creates float Tensor, 1.0 for label-TopK_prediction match, 0.0 for mismatch.\n\n    Args:\n      y_true: tensor of true targets.\n      y_pred: tensor of predicted targets.\n      k: (Optional) Number of top elements to look at for computing accuracy.\n        Defaults to 5.\n\n    Returns:\n      Match tensor: 1.0 for label-prediction match, 0.0 for mismatch.\n    ",
            "n_words": 46,
            "vocab_size": 33,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 65856,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/doctype/academic_term/academic_term.py",
        "file_name": "academic_term.py",
        "fun_name": "validate_duplication",
        "commit_message": "style: format code with black",
        "code": "def validate_duplication(self):\n\tterm = frappe.db.sql(\n\t\t,\n\t\t(self.academic_year, self.term_name, self.name),\n\t)\n\tif term:\n\t\tfrappe.throw(\n\t\t\t_(\n\t\t\t\t\"An academic term with this 'Academic Year' {0} and 'Term Name' {1} already exists. Please modify these entries and try again.\"\n\t\t\t).format(self.academic_year, self.term_name)\n\t\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 27,
        "n_words": 38,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 53,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 14043,
        "documentation": {
            "docstring": "select name from `tabAcademic Term` where academic_year= %s and term_name= %s\n    and docstatus<2 and name != %s",
            "n_words": 17,
            "vocab_size": 12,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 86729,
        "commit_id": "d6bcead1be02914e9734ab23f5e476b3d6f3f2cb",
        "repo": "sentry",
        "path": "src/sentry/integrations/github/client.py",
        "file_name": "client.py",
        "fun_name": "get_repositories",
        "commit_message": "fix(github): Add pagination when fetching repositories (#39750)\n\nWe are not using pagination for Github's repositories endpoint. This means we were getting up to a maximum of 100 repositories.\r\n\r\nI do not know how no one hit any issues in the past.\r\n\r\nThis is work to support WOR-2234 and creating automatic code mappings.",
        "code": "def get_repositories(self) -> Sequence[JSONData]:\n        \n        # Explicitly typing to satisfy mypy.\n        repos: JSONData = self.get_with_pagination(\n            \"/installation/repositories\", response_key=\"repositories\"\n        )\n        return [repo for repo in repos if not repo.get(\"archived\")]\n\n    # XXX: Find alternative approach",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 80,
        "n_words": 31,
        "vocab_size": 30,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 41,
        "n_ast_nodes": 73,
        "n_identifiers": 9,
        "d_id": 18160,
        "documentation": {
            "docstring": "\n        This fetches all repositories accessible to the Github App\n        https://docs.github.com/en/rest/apps/installations#list-repositories-accessible-to-the-app-installation\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 222884,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/dist.py",
        "file_name": "dist.py",
        "fun_name": "handle_display_options",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def handle_display_options(self, option_order):\n        \n        from distutils.core import gen_usage\n\n        # User just wants a list of commands -- we'll print it out and stop\n        # processing now (ie. if they ran \"setup --help-commands foo bar\",\n        # we ignore \"foo bar\").\n        if self.help_commands:\n            self.print_commands()\n            print('')\n            print(gen_usage(self.script_name))\n            return 1\n\n        # If user supplied any of the \"display metadata\" options, then\n        # display that metadata in the order in which the user supplied the\n        # metadata options.\n        any_display_options = 0\n        is_display_option = {}\n        for option in self.display_options:\n            is_display_option[option[0]] = 1\n\n        for (opt, val) in option_order:\n            if val and is_display_option.get(opt):\n                opt = translate_longopt(opt)\n                value = getattr(self.metadata, \"get_\"+opt)()\n                if opt in ['keywords', 'platforms']:\n                    print(','.join(value))\n                elif opt in ('classifiers', 'provides', 'requires',\n                             'obsoletes'):\n                    print('\\n'.join(value))\n                else:\n                    print(value)\n                any_display_options = 1\n\n        return any_display_options\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 461,
        "n_words": 122,
        "vocab_size": 88,
        "complexity": 8,
        "nloc": 24,
        "token_counts": 152,
        "n_ast_nodes": 267,
        "n_identifiers": 22,
        "d_id": 56798,
        "documentation": {
            "docstring": "If there were any non-global \"display-only\" options\n        (--help-commands or the metadata display options) on the command\n        line, display the requested info and return true; else return\n        false.\n        ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 246345,
        "commit_id": "40771773909cb03d9296e3f0505e4e32372f10aa",
        "repo": "synapse",
        "path": "tests/push/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_push_unread_count_group_by_room",
        "commit_message": "Prevent duplicate push notifications for room reads (#11835)",
        "code": "def test_push_unread_count_group_by_room(self):\n        \n        # Carry out common push count tests and setup\n        self._test_push_unread_count()\n\n        # Carry out our option-value specific test\n        #\n        # This push should still only contain an unread count of 1 (for 1 unread room)\n        self._check_push_attempt(6, 1)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 87,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 71168,
        "documentation": {
            "docstring": "\n        The HTTP pusher will group unread count by number of unread rooms.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 202419,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/csrf_tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_https_good_referer",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_https_good_referer(self):\n        \n        req = self._get_POST_request_with_token()\n        req._is_secure_override = True\n        req.META[\"HTTP_HOST\"] = \"www.example.com\"\n        req.META[\"HTTP_REFERER\"] = \"https://www.example.com/somepage\"\n        mw = CsrfViewMiddleware(post_form_view)\n        mw.process_request(req)\n        resp = mw.process_view(req, post_form_view, (), {})\n        self.assertIsNone(resp)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 88,
        "n_words": 25,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 68,
        "n_ast_nodes": 118,
        "n_identifiers": 13,
        "d_id": 50121,
        "documentation": {
            "docstring": "\n        A POST HTTPS request with a good referer is accepted.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 199450,
        "commit_id": "0bed141b2d875829e5caf6923431185ba16c625a",
        "repo": "sympy",
        "path": "sympy/logic/boolalg.py",
        "file_name": "boolalg.py",
        "fun_name": "as_Boolean",
        "commit_message": "Cache replacement tuples, do not lookup true/false, new replacements",
        "code": "def as_Boolean(e):\n    \n    from sympy.core.symbol import Symbol\n    if e == True:\n        return true\n    if e == False:\n        return false\n    if isinstance(e, Symbol):\n        z = e.is_zero\n        if z is None:\n            return e\n        return false if z else true\n    if isinstance(e, Boolean):\n        return e\n    raise TypeError('expecting bool or Boolean, not `%s`.' % e)\n\n\n@sympify_method_args",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "@sympify_method_args",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 124,
        "n_words": 51,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 71,
        "n_ast_nodes": 117,
        "n_identifiers": 14,
        "d_id": 49274,
        "documentation": {
            "docstring": "Like ``bool``, return the Boolean value of an expression, e,\n    which can be any instance of :py:class:`~.Boolean` or ``bool``.\n\n    Examples\n    ========\n\n    >>> from sympy import true, false, nan\n    >>> from sympy.logic.boolalg import as_Boolean\n    >>> from sympy.abc import x\n    >>> as_Boolean(0) is false\n    True\n    >>> as_Boolean(1) is true\n    True\n    >>> as_Boolean(x)\n    x\n    >>> as_Boolean(2)\n    Traceback (most recent call last):\n    ...\n    TypeError: expecting bool or Boolean, not `2`.\n    >>> as_Boolean(nan)\n    Traceback (most recent call last):\n    ...\n    TypeError: expecting bool or Boolean, not `nan`.\n\n    ",
            "n_words": 81,
            "vocab_size": 53,
            "n_whitespaces": 144,
            "language": "en"
        }
    },
    {
        "id": 286532,
        "commit_id": "0ae89d6cc20be84bf49c31e437fda38a845ebc68",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/overview/overview_controller.py",
        "file_name": "overview_controller.py",
        "fun_name": "call_exchanges",
        "commit_message": "Style fixing: removing --ascend/--descend (#3395)\n\n* stocks candle to use reverse\r\n\r\n* qa raw to use reverse\r\n\r\n* etf candle to use reverse\r\n\r\n* oss rossix to use reverse\r\n\r\n* crypto/defi to use reverse\r\n\r\n* crypto/disc to use reverse\r\n\r\n* added test\r\n\r\n* crypto/dd to use reverse\r\n\r\n* crypto/onchain to use reverse\r\n\r\n* crypto/ov to use revert\r\n\r\n* forex candle to use revert\r\n\r\n* conibase controller to use revert\r\n\r\n* tests to use reverse\r\n\r\n* covid to use reverse\r\n\r\n* removing ascend\r\n\r\n* removing ascend from econ\r\n\r\n* more removing ascend\r\n\r\n* more removing ascend\r\n\r\n* more removing ascend\r\n\r\n* fixing stuff on .md files\r\n\r\n* fixed economy controller tests\r\n\r\n* fixed screener tests\r\n\r\n* fa controller to use comma separated when multiple inputs",
        "code": "def call_exchanges(self, other_args):\n        \n        filters = (\n            pycoingecko_model.EXCHANGES_FILTERS + coinpaprika_model.EXCHANGES_FILTERS\n        )\n        parser = argparse.ArgumentParser(\n            prog=\"exchanges\",\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            description=,\n        )\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            dest=\"limit\",\n            type=check_positive,\n            help=\"display N number records\",\n            default=15,\n        )\n        parser.add_argument(\n            \"-s\",\n            \"--sortby\",\n            dest=\"sortby\",\n            type=str,\n            help=\"Sort by given column. Default: Rank\",\n            default=\"Rank\",\n            choices=filters,\n        )\n        parser.add_argument(\n            \"-r\",\n            \"--reverse\",\n            action=\"store_true\",\n            dest=\"reverse\",\n            default=False,\n            help=(\n                \"Data is sorted in descending order by default. \"\n                \"Reverse flag will sort it in an ascending way. \"\n                \"Only works when raw data is displayed.\"\n            ),\n        )\n        parser.add_argument(\n            \"-u\",\n            \"--urls\",\n            dest=\"urls\",\n            action=\"store_true\",\n            help=\"Flag to add a url column. Works only with CoinGecko source\",\n            default=False,\n        )\n        parser.add_argument(\n            \"--vs\",\n            help=\"Quoted currency. Default: USD. Works only with CoinPaprika source\",\n            dest=\"vs\",\n            default=\"USD\",\n            type=str,\n            choices=CURRENCIES,\n        )\n        ns_parser = self.parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n        if ns_parser:\n            if ns_parser.source == \"CoinGecko\":\n                pycoingecko_view.display_exchanges(\n                    limit=ns_parser.limit,\n                    export=ns_parser.export,\n                    sortby=ns_parser.sortby,\n                    ascend=ns_parser.reverse,\n                    links=ns_parser.urls,\n                )\n            elif ns_parser.source == \"CoinPaprika\":\n                coinpaprika_view.display_all_exchanges(\n                    symbol=ns_parser.vs,\n                    limit=ns_parser.limit,\n                    ascend=ns_parser.reverse,\n                    sortby=ns_parser.sortby,\n                    export=ns_parser.export,\n                )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 1004,
        "n_words": 143,
        "vocab_size": 108,
        "complexity": 4,
        "nloc": 83,
        "token_counts": 278,
        "n_ast_nodes": 446,
        "n_identifiers": 42,
        "d_id": 85855,
        "documentation": {
            "docstring": "Process exchanges commandShows Top Crypto Exchanges\n                You can display only N number exchanges with --limit parameter.\n                You can sort data by Trust_Score, Id, Name, Country, Year_Established, Trade_Volume_24h_BTC with --sortby\n                Or you can sort data by 'name', 'currencies', 'markets', 'fiats', 'confidence',\n                'volume_24h', 'volume_7d', 'volume_30d', 'sessions_per_month'\n                if you are using the alternative source CoinPaprika\n                and also with --reverse flag to sort ascending.\n                Flag --urls will display urls.\n                Displays: Trust_Score, Id, Name, Country, Year_Established, Trade_Volume_24h_BTC",
            "n_words": 72,
            "vocab_size": 54,
            "n_whitespaces": 191,
            "language": "en"
        }
    },
    {
        "id": 75478,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/search/backends/database/mysql/mysql.py",
        "file_name": "mysql.py",
        "fun_name": "autocomplete",
        "commit_message": "Reformat with black",
        "code": "def autocomplete(self):\n        \n        texts = []\n        for field in self.search_fields:\n            for current_field, value in self.prepare_field(self.obj, field):\n                if isinstance(current_field, AutocompleteField):\n                    texts.append((value))\n\n        return \" \".join(texts)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 95,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 56,
        "n_ast_nodes": 91,
        "n_identifiers": 13,
        "d_id": 16409,
        "documentation": {
            "docstring": "\n        Returns all values to index as \"autocomplete\". This is the value of all AutocompleteFields\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 99575,
        "commit_id": "1730c481f1a8a71446326fa1ff72e10663016385",
        "repo": "sentry",
        "path": "tests/sentry/integrations/slack/notifications/test_issue_alert.py",
        "file_name": "test_issue_alert.py",
        "fun_name": "test_issue_alert_team",
        "commit_message": "fix(notifications): Use `metrics_key` (#34572)",
        "code": "def test_issue_alert_team(self, mock_func):\n        \n        # add a second organization\n        org = self.create_organization(owner=self.user)\n        OrganizationIntegration.objects.create(organization=org, integration=self.integration)\n\n        # add a second user to the team so we can be sure it's only\n        # sent once (to the team, and not to each individual user)\n        user2 = self.create_user(is_superuser=False)\n        self.create_member(teams=[self.team], user=user2, organization=self.organization)\n        self.idp = IdentityProvider.objects.create(type=\"slack\", external_id=\"TXXXXXXX2\", config={})\n        self.identity = Identity.objects.create(\n            external_id=\"UXXXXXXX2\",\n            idp=self.idp,\n            user=user2,\n            status=IdentityStatus.VALID,\n            scopes=[],\n        )\n        NotificationSetting.objects.update_settings(\n            ExternalProviders.SLACK,\n            NotificationSettingTypes.ISSUE_ALERTS,\n            NotificationSettingOptionValues.ALWAYS,\n            user=user2,\n        )\n        # update the team's notification settings\n        ExternalActor.objects.create(\n            actor=self.team.actor,\n            organization=self.organization,\n            integration=self.integration,\n            provider=ExternalProviders.SLACK.value,\n            external_name=\"goma\",\n            external_id=\"CXXXXXXX2\",\n        )\n        NotificationSetting.objects.update_settings(\n            ExternalProviders.SLACK,\n            NotificationSettingTypes.ISSUE_ALERTS,\n            NotificationSettingOptionValues.ALWAYS,\n            team=self.team,\n        )\n\n        event = self.store_event(\n            data={\"message\": \"Hello world\", \"level\": \"error\"}, project_id=self.project.id\n        )\n        action_data = {\n            \"id\": \"sentry.mail.actions.NotifyEmailAction\",\n            \"targetType\": \"Team\",\n            \"targetIdentifier\": str(self.team.id),\n        }\n        rule = Rule.objects.create(\n            project=self.project,\n            label=\"ja rule\",\n            data={\n                \"match\": \"all\",\n                \"actions\": [action_data],\n            },\n        )\n        notification = Notification(event=event, rule=rule)\n\n        with self.options({\"system.url-prefix\": \"http://example.com\"}), self.tasks():\n            self.adapter.notify(notification, ActionTargetType.TEAM, self.team.id)\n\n        # check that only one was sent out - more would mean each user is being notified\n        # rather than the team\n        assert len(responses.calls) == 1\n\n        # check that the team got a notification\n        data = parse_qs(responses.calls[0].request.body)\n        assert data[\"channel\"] == [\"CXXXXXXX2\"]\n        assert \"attachments\" in data\n        attachments = json.loads(data[\"attachments\"][0])\n        assert len(attachments) == 1\n        assert attachments[0][\"title\"] == \"Hello world\"\n        assert (\n            attachments[0][\"footer\"]\n            == f\"{self.project.slug} | <http://example.com/settings/{self.organization.slug}/teams/{self.team.slug}/notifications/?referrer=issue_alert-slack-team|Notification Settings>\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 822,
        "n_words": 196,
        "vocab_size": 138,
        "complexity": 1,
        "nloc": 63,
        "token_counts": 430,
        "n_ast_nodes": 724,
        "n_identifiers": 71,
        "d_id": 19653,
        "documentation": {
            "docstring": "Test that issue alerts are sent to a team in Slack.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 32231,
        "commit_id": "6561fbcc6e6d6e1a29fb848dc34710aa25feae78",
        "repo": "transformers",
        "path": "tests/models/encoder_decoder/test_modeling_tf_encoder_decoder.py",
        "file_name": "test_modeling_tf_encoder_decoder.py",
        "fun_name": "check_pt_to_tf_equivalence",
        "commit_message": "Update TF(Vision)EncoderDecoderModel PT/TF equivalence tests (#18073)\n\nCo-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>",
        "code": "def check_pt_to_tf_equivalence(self, config, decoder_config, tf_inputs_dict):\n        \n\n        encoder_decoder_config = EncoderDecoderConfig.from_encoder_decoder_configs(config, decoder_config)\n        # Output all for aggressive testing\n        encoder_decoder_config.output_hidden_states = True\n        # All models tested in this file have attentions\n        encoder_decoder_config.output_attentions = True\n\n        pt_model = EncoderDecoderModel(encoder_decoder_config)\n\n        with tempfile.TemporaryDirectory() as encoder_tmp_dirname, tempfile.TemporaryDirectory() as decoder_tmp_dirname:\n\n            pt_model.encoder.save_pretrained(encoder_tmp_dirname)\n            pt_model.decoder.save_pretrained(decoder_tmp_dirname)\n            tf_model = TFEncoderDecoderModel.from_encoder_decoder_pretrained(\n                encoder_tmp_dirname, decoder_tmp_dirname, encoder_from_pt=True, decoder_from_pt=True\n            )\n            # This is only for copying some specific attributes of this particular model.\n            tf_model.config = pt_model.config\n\n        self.check_pt_tf_equivalence(tf_model, pt_model, tf_inputs_dict)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 213,
        "n_words": 69,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 106,
        "n_ast_nodes": 171,
        "n_identifiers": 25,
        "d_id": 5885,
        "documentation": {
            "docstring": "EncoderDecoderModel requires special way to cross load (PT -> TF)",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 266685,
        "commit_id": "b61380827758f8357b6a2721e4a8f290f05c6eaa",
        "repo": "ansible",
        "path": "test/units/errors/test_errors.py",
        "file_name": "test_errors.py",
        "fun_name": "test_get_error_lines_error_empty_lines_around_error",
        "commit_message": "Remove obsolete unit test builtins compat.",
        "code": "def test_get_error_lines_error_empty_lines_around_error(self):\n        \n        m = mock_open()\n        m.return_value.readlines.return_value = ['this is line 1\\n', 'this is line 2\\n', 'this is line 3\\n', '  \\n', '   \\n', ' ']\n\n        with patch('builtins.open', m):\n            self.obj.ansible_pos = ('foo.yml', 5, 1)\n            e = AnsibleError(self.message, self.obj)\n            self.assertEqual(\n                e.message,\n                (\"This is the error message\\n\\nThe error appears to be in 'foo.yml': line 5, column 1, but may\\nbe elsewhere in the file depending on \"\n                 \"the exact syntax problem.\\n\\nThe offending line appears to be:\\n\\nthis is line 2\\nthis is line 3\\n^ here\\n\")\n            )\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 201,
        "n_words": 80,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 78,
        "n_ast_nodes": 154,
        "n_identifiers": 13,
        "d_id": 78515,
        "documentation": {
            "docstring": "Test that trailing whitespace after the error is removed",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 321172,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/webkit/network/webkitqutescheme.py",
        "file_name": "webkitqutescheme.py",
        "fun_name": "handler",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def handler(request, operation, current_url):\n    \n    if operation != QNetworkAccessManager.Operation.GetOperation:\n        return networkreply.ErrorNetworkReply(\n            request, \"Unsupported request type\",\n            QNetworkReply.NetworkError.ContentOperationNotPermittedError)\n\n    url = request.url()\n\n    if ((url.scheme(), url.host(), url.path()) ==\n            ('qute', 'settings', '/set')):\n        if current_url != QUrl('qute://settings/'):\n            log.network.warning(\"Blocking malicious request from {} to {}\"\n                                .format(current_url.toDisplayString(),\n                                        url.toDisplayString()))\n            return networkreply.ErrorNetworkReply(\n                request, \"Invalid qute://settings request\",\n                QNetworkReply.NetworkError.ContentAccessDenied)\n\n    try:\n        mimetype, data = qutescheme.data_for_url(url)\n    except qutescheme.Error as e:\n        errors = {\n            qutescheme.NotFoundError:\n                QNetworkReply.NetworkError.ContentNotFoundError,\n            qutescheme.UrlInvalidError:\n                QNetworkReply.NetworkError.ContentOperationNotPermittedError,\n            qutescheme.RequestDeniedError:\n                QNetworkReply.NetworkError.ContentAccessDenied,\n            qutescheme.SchemeOSError:\n                QNetworkReply.NetworkError.ContentNotFoundError,\n            qutescheme.Error:\n                QNetworkReply.NetworkError.InternalServerError,\n        }\n        exctype = type(e)\n        log.misc.error(\"{} while handling qute://* URL\".format(\n            exctype.__name__))\n        return networkreply.ErrorNetworkReply(request, str(e), errors[exctype])\n    except qutescheme.Redirect as e:\n        qtutils.ensure_valid(e.url)\n        return networkreply.RedirectNetworkReply(e.url)\n\n    return networkreply.FixedDataNetworkReply(request, data, mimetype)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 483,
        "n_words": 93,
        "vocab_size": 76,
        "complexity": 6,
        "nloc": 38,
        "token_counts": 264,
        "n_ast_nodes": 418,
        "n_identifiers": 47,
        "d_id": 117576,
        "documentation": {
            "docstring": "Scheme handler for qute:// URLs.\n\n    Args:\n        request: QNetworkRequest to answer to.\n        operation: The HTTP operation being done.\n        current_url: The page we're on currently.\n\n    Return:\n        A QNetworkReply.\n    ",
            "n_words": 26,
            "vocab_size": 25,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 21231,
        "commit_id": "4b996c0fa85824b323ad9eff3364dbe2213ebb4c",
        "repo": "pipenv",
        "path": "pipenv/project.py",
        "file_name": "project.py",
        "fun_name": "parsed_pipfile",
        "commit_message": "Convert type comments to type annotations",
        "code": "def parsed_pipfile(self) -> Union[tomlkit.toml_document.TOMLDocument, TPipfile]:\n        \n        contents = self.read_pipfile()\n        # use full contents to get around str/bytes 2/3 issues\n        cache_key = (self.pipfile_location, contents)\n        if cache_key not in _pipfile_cache:\n            parsed = self._parse_pipfile(contents)\n            _pipfile_cache[cache_key] = parsed\n        return _pipfile_cache[cache_key]\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 99,
        "n_words": 35,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 58,
        "n_ast_nodes": 92,
        "n_identifiers": 14,
        "d_id": 3731,
        "documentation": {
            "docstring": "Parse Pipfile into a TOMLFile and cache it\n\n        (call clear_pipfile_cache() afterwards if mutating)",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 100563,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/gpu_stats/amd.py",
        "file_name": "amd.py",
        "fun_name": "_get_free_vram",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def _get_free_vram(self) -> List[float]:\n        \n        vram = self._all_vram\n        self._log(\"debug\", f\"GPU VRAM free: {vram}\")\n        return vram\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 27,
        "n_ast_nodes": 51,
        "n_identifiers": 7,
        "d_id": 20027,
        "documentation": {
            "docstring": " Obtain the amount of VRAM that is available, in Megabytes, for each connected AMD\n        GPU.\n\n        Notes\n        -----\n        There is no useful way to get free VRAM on PlaidML. OpenCL loads and unloads VRAM as\n        required, so this returns the total memory available per card for AMD GPUs, which is\n        not particularly useful.\n\n        Returns\n        -------\n        list\n             List of `float`s containing the amount of VRAM available, in Megabytes, for each\n             connected GPU as corresponding to the values in :attr:`_handles\n        ",
            "n_words": 77,
            "vocab_size": 55,
            "n_whitespaces": 172,
            "language": "en"
        }
    },
    {
        "id": 177442,
        "commit_id": "0f91550007fd3a95261d858b1a6a623ef8bda38a",
        "repo": "networkx",
        "path": "networkx/classes/backends.py",
        "file_name": "backends.py",
        "fun_name": "_mark_tests",
        "commit_message": "plugin based backend infrastructure to use multiple computation backends (#6000)\n\n* Wrappers classes to dispatch to a backend\r\n\r\n* Rework the backend dispatching\r\n\r\n- Use __networkx_plugin__=name to find graph-like objects instead of\r\n  subclassing\r\n- Add PluginInfo to smooth over differences in importlib.metadata across\r\n  python versions\r\n- Add dispatch behavior override via environment variable to aid in\r\n  testing plugins\r\n\r\n* Dispatch more algorithms and improve auto-test capabilities\r\n\r\n* Allow dispatcher decorator without a name\r\n\r\n- Name is taken from the decorated function\r\n- Raise error if backend doesn't implement a decorated function which is called\r\n- Check for duplicate names for dispatching algorithms\r\n\r\n* Make sphinx pick up backend docs\r\n\r\n* make black happy\r\n\r\n* Rename decorator to _dispatch as it's experimental\r\n\r\n* A few more dispatched functions\r\n\r\n* Make convert to and from methods for auto-testing\r\n\r\n- Rename `convert` to `convert_from_nx`\r\n- Add `convert_to_nx` function\r\n\r\nThese will allow backends to return native objects when dispatching,\r\nbut provide a mechanism to convert the result to the type expected\r\nby NetworkX tests for the auto-test plugin mechanism.\r\n\r\n* More dispatching\r\n\r\n* Include name with `convert_**_nx` methods\r\n\r\n* Remove known plugin names\r\n\r\nThis check is not needed, as any plugin can register itself in the entry points section.\r\nThe dispatching and auto-testing explicitly specify the plugin to use, so there is no\r\nneed to hardcode the options.\r\nThese were originally included for security, but any malicious actor would simply use one\r\nof the valid names, so having a hardcoded list does not actually provide any meaningful\r\nsecurity.\r\n\r\n* Add `dispatchname` to dispatchable functions\r\n\r\nCo-authored-by: Jim Kitchen <jim22k@gmail.com>\r\nCo-authored-by: Erik Welch <erik.n.welch@gmail.com>",
        "code": "def _mark_tests(items):\n    \n    if os.environ.get(\"NETWORKX_GRAPH_CONVERT\"):\n        plugin_name = os.environ[\"NETWORKX_GRAPH_CONVERT\"]\n        backend = plugins[plugin_name].load()\n        if hasattr(backend, \"on_start_tests\"):\n            getattr(backend, \"on_start_tests\")(items)\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 53,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 51,
        "n_ast_nodes": 91,
        "n_identifiers": 11,
        "d_id": 42378,
        "documentation": {
            "docstring": "Allow backend to mark tests (skip or xfail) if they aren't able to correctly handle them",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 189440,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/numbers.py",
        "file_name": "numbers.py",
        "fun_name": "_get_formatter",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _get_formatter(self, **kwargs):\n        \n        config = {\n            attr: getattr(self, attr)\n            for attr in [\n                \"include_sign\",\n                \"group_with_commas\",\n                \"num_decimal_places\",\n            ]\n        }\n        config.update(kwargs)\n        return \"\".join(\n            [\n                \"{\",\n                config.get(\"field_name\", \"\"),\n                \":\",\n                \"+\" if config[\"include_sign\"] else \"\",\n                \",\" if config[\"group_with_commas\"] else \"\",\n                \".\",\n                str(config[\"num_decimal_places\"]),\n                \"f\",\n                \"}\",\n            ],\n        )\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 319,
        "n_words": 42,
        "vocab_size": 38,
        "complexity": 4,
        "nloc": 23,
        "token_counts": 92,
        "n_ast_nodes": 163,
        "n_identifiers": 10,
        "d_id": 46054,
        "documentation": {
            "docstring": "\n        Configuration is based first off instance attributes,\n        but overwritten by any kew word argument.  Relevant\n        key words:\n        - include_sign\n        - group_with_commas\n        - num_decimal_places\n        - field_name (e.g. 0 or 0.real)\n        ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 87,
            "language": "en"
        }
    },
    {
        "id": 93002,
        "commit_id": "cd803d173c72b64d06c0687170bf9a945d0b503c",
        "repo": "sentry",
        "path": "tests/snuba/sessions/test_sessions.py",
        "file_name": "test_sessions.py",
        "fun_name": "parametrize_backend",
        "commit_message": "fix(snuba): Add appropriate `UseCaseKey` for indexer [TET-146] (#36308)\n\n* fix(snuba): Add appropriate `UseCaseKey` for indexer\r\n\r\nUpdate indexer invocation call to have the appropriate\r\n`UseCaseKey` depending on use case.\r\n\r\nIn `src/sentry/sentry_metrics/indexer/base.py::StringIndexer`\r\nwhen using `resolve` and `reverse_resolve` callers should not\r\nrely on the default use_case_id.\r\n\r\nImportant changes:\r\n- Add required parameter `use_case_id: UseCaseKey` to `get_series` from `src/sentry/snuba/metrics/datasource.py#L612`;\r\n- Add required parameter  to `get_metrics` in `src/sentry/snuba/metrics/datasource.py`\r\n- Add required parameter  to `get_tags` in `src/sentry/snuba/metrics/datasource.py`\r\n- Add required parameter to `get_tag_values` in `src/sentry/snuba/metrics/datasource.py`",
        "code": "def parametrize_backend(cls):\n    \n\n    assert not hasattr(cls, \"backend\")\n    cls.backend = SessionsReleaseHealthBackend()\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 18,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 104,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 18965,
        "documentation": {
            "docstring": "\n    hack to parametrize test-classes by backend. Ideally we'd move\n    over to pytest-style tests so we can use `pytest.mark.parametrize`, but\n    hopefully we won't have more than one backend in the future.\n    ",
            "n_words": 30,
            "vocab_size": 28,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 282770,
        "commit_id": "401e4c739a6f9d18944e0ab49c782e97b56fda94",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/helper_funcs.py",
        "file_name": "helper_funcs.py",
        "fun_name": "handle_error_code",
        "commit_message": "Output Missing API Key Message to Console (#1357)\n\n* Decorator to output error msg to console of missing API Key\r\n\r\n* Refactor FMP & alpha advantage\r\n\r\n* Refactor FRED & QUANDL\r\n\r\n* Refactor Polygon\r\n\r\n* Refactor FRED\r\n\r\n* Refactor FRED\r\n\r\n* Refactor Finnhub & coinmarketcap & Newsapi\r\n\r\n* Allow disabling of check api\r\n\r\n* Updating tests : disable check api for tests\r\n\r\n* Refactor Finnhub & SI & Binance\r\n\r\n* Fix linting\r\n\r\n* Fix test & add black formatting\r\n\r\n* Fix test failing\r\n\r\n* Fix test failing\r\n\r\n* Refactor CryptoPanic & Whales alert & Glassnode & Coinglass\r\n\r\n* Refactor ETHexplorer & Smartstake & Alpha Advanage & Coinbase\r\n\r\n* Add decorators to controllers\r\n\r\n* Fix test & Refactor Coinbase, RH, Reddit\r\n\r\n* Add contributing guideline\r\n\r\n* Update CONTRIBUTING.md\r\n\r\n* Update CONTRIBUTING.md\r\n\r\n* fix tests\r\n\r\n* add decorator to snews cmd\r\n\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>",
        "code": "def handle_error_code(requests_obj, error_code_map):\n    \n    for error_code, error_msg in error_code_map.items():\n        if requests_obj.status_code == error_code:\n            console.print(error_msg)\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 37,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 53,
        "n_identifiers": 9,
        "d_id": 84294,
        "documentation": {
            "docstring": "\n    Helper function to handle error code of HTTP requests.\n\n    Parameters\n    ----------\n    requests_obj: Object\n        Request object\n    error_code_map: Dict\n        Dictionary mapping of HTTP error code and output message\n\n    ",
            "n_words": 26,
            "vocab_size": 22,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 72991,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/models.py",
        "file_name": "models.py",
        "fun_name": "render_landing_page",
        "commit_message": "Reformat with black",
        "code": "def render_landing_page(self, request, form_submission=None, *args, **kwargs):\n        \n        context = self.get_context(request)\n        context[\"form_submission\"] = form_submission\n        return TemplateResponse(\n            request, self.get_landing_page_template(request), context\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 64,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 46,
        "n_ast_nodes": 72,
        "n_identifiers": 10,
        "d_id": 15921,
        "documentation": {
            "docstring": "\n        Renders the landing page.\n\n        You can override this method to return a different HttpResponse as\n        landing page. E.g. you could return a redirect to a separate page.\n        ",
            "n_words": 27,
            "vocab_size": 20,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 6534,
        "commit_id": "23a33eef3bc7ea3ba33ec56dc9b56ba38462648a",
        "repo": "ludwig",
        "path": "ludwig/combiners/combiners.py",
        "file_name": "combiners.py",
        "fun_name": "get_combiner_conds",
        "commit_message": "feat: Modify Trainer to use marshmallow_dataclass syntax for handling hyperparameters. Add basic scripting for docstring extraction to marshmallow schema. Fix some existing marshmallow issues. (#1606)",
        "code": "def get_combiner_conds():\n    \n    combiner_types = sorted(list(combiner_registry.keys()))\n    conds = []\n    for combiner_type in combiner_types:\n        combiner_cls = combiner_registry[combiner_type]\n        schema_cls = combiner_cls.get_schema_cls()\n        combiner_schema = schema.get_custom_schema_from_marshmallow_class(schema_cls)\n        combiner_props = combiner_schema[\"properties\"]\n        combiner_cond = schema.create_cond({\"type\": combiner_type}, combiner_props)\n        conds.append(combiner_cond)\n    return conds\n\n\n# super class to house common properties",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 95,
        "n_words": 39,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 76,
        "n_ast_nodes": 130,
        "n_identifiers": 18,
        "d_id": 1011,
        "documentation": {
            "docstring": "Returns a list of if-then JSON clauses for each combiner type in `combiner_registry` and its properties'\n    constraints.",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 120708,
        "commit_id": "3ad08543a9d766d8e6b9d7272cebfe4f2c431980",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "ravel_multi_index",
        "commit_message": "[x64] make jnp.histogram and related functions work with strict promotion",
        "code": "def ravel_multi_index(multi_index, dims, mode='raise', order='C'):\n  assert len(multi_index) == len(dims), f\"len(multi_index)={len(multi_index)} != len(dims)={len(dims)}\"\n  dims = tuple(core.concrete_or_error(operator.index, d, \"in `dims` argument of ravel_multi_index().\") for d in dims)\n  _check_arraylike(\"ravel_multi_index\", *multi_index)\n  for index in multi_index:\n    if mode == 'raise':\n      core.concrete_or_error(array, index,\n        \"The error occurred because ravel_multi_index was jit-compiled\"\n        \" with mode='raise'. Use mode='wrap' or mode='clip' instead.\")\n    if not issubdtype(_dtype(index), integer):\n      raise TypeError(\"only int indices permitted\")\n  if mode == \"raise\":\n    if _any(any((i < 0) | (i >= d)) for i, d in zip(multi_index, dims)):\n      raise ValueError(\"invalid entry in coordinates array\")\n  elif mode == \"clip\":\n    multi_index = [clip(i, 0, d - 1) for i, d in zip(multi_index, dims)]\n  elif mode == \"wrap\":\n    multi_index = [i % d for i, d in zip(multi_index, dims)]\n  else:\n    raise ValueError(f\"invalid mode={mode!r}. Expected 'raise', 'wrap', or 'clip'\")\n\n  if order == \"F\":\n    strides = np.cumprod((1,) + dims[:-1])\n  elif order == \"C\":\n    strides = np.cumprod((1,) + dims[1:][::-1])[::-1]\n  else:\n    raise ValueError(f\"invalid order={order!r}. Expected 'C' or 'F'\")\n\n  result = array(0, dtype=multi_index[0].dtype)\n  for i, s in zip(multi_index, strides):\n    result = result + i * int(s)\n  return result\n\n\n_UNRAVEL_INDEX_DOC = \n\n@_wraps(np.unravel_index, lax_description=_UNRAVEL_INDEX_DOC)",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@_wraps(np.unravel_index, lax_description=_UNRAVEL_INDEX_DOC)",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 246,
        "n_words": 175,
        "vocab_size": 113,
        "complexity": 15,
        "nloc": 30,
        "token_counts": 297,
        "n_ast_nodes": 533,
        "n_identifiers": 35,
        "d_id": 26928,
        "documentation": {
            "docstring": "\\\nUnlike numpy's implementation of unravel_index, negative indices are accepted\nand out-of-bounds indices are clipped into the valid range.\n",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 101438,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "_build_ui",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _build_ui(self) -> None:\n        \n        container = ttk.PanedWindow(self,\n                                    orient=tk.VERTICAL)\n        container.pack(fill=tk.BOTH, expand=True)\n        setattr(container, \"preview_display\", self._display)  # TODO subclass not setattr\n        self._image_canvas = ImagesCanvas(container, self._tk_vars)\n        container.add(self._image_canvas, weight=3)\n\n        options_frame = ttk.Frame(container)\n        self._cli_frame = ActionFrame(\n            options_frame,\n            self._available_masks,\n            self._samples.predictor.has_predicted_mask,\n            self._patch.converter.cli_arguments.color_adjustment.replace(\"-\", \"_\"),\n            self._patch.converter.cli_arguments.mask_type.replace(\"-\", \"_\"),\n            self._config_tools,\n            self._refresh,\n            self._samples.generate,\n            self._tk_vars)\n        self._opts_book = OptionsBook(options_frame,\n                                      self._config_tools,\n                                      self._refresh)\n        container.add(options_frame, weight=1)\n        self.update_idletasks()\n        container.sashpos(0, int(400 * get_config().scaling_factor))\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 346,
        "n_words": 53,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 198,
        "n_ast_nodes": 306,
        "n_identifiers": 43,
        "d_id": 20851,
        "documentation": {
            "docstring": " Build the elements for displaying preview images and options panels. ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 101420,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "update_config",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def update_config(self) -> None:\n        \n        for section, items in self.tk_vars.items():\n            for item, value in items.items():\n                try:\n                    new_value = str(value.get())\n                except tk.TclError as err:\n                    # When manually filling in text fields, blank values will\n                    # raise an error on numeric data types so return 0\n                    logger.debug(\"Error getting value. Defaulting to 0. Error: %s\", str(err))\n                    new_value = str(0)\n                old_value = self._config.config[section][item]\n                if new_value != old_value:\n                    logger.trace(\"Updating config: %s, %s from %s to %s\",  # type: ignore\n                                 section, item, old_value, new_value)\n                    self._config.config[section][item] = new_value\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 331,
        "n_words": 80,
        "vocab_size": 63,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 113,
        "n_ast_nodes": 184,
        "n_identifiers": 19,
        "d_id": 20834,
        "documentation": {
            "docstring": " Update :attr:`config` with the currently selected values from the GUI. ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 219860,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pyio.py",
        "file_name": "_pyio.py",
        "fun_name": "readline",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def readline(self, size=-1):\n        r\n        # For backwards compatibility, a (slowish) readline().\n        if hasattr(self, \"peek\"):",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 34,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 8,
        "nloc": 32,
        "token_counts": 110,
        "n_ast_nodes": 35,
        "n_identifiers": 4,
        "d_id": 55865,
        "documentation": {
            "docstring": "Read and return a line of bytes from the stream.\n\n        If size is specified, at most size bytes will be read.\n        Size should be an int.\n\n        The line terminator is always b'\\n' for binary files; for text\n        files, the newlines argument to open can be used to select the line\n        terminator(s) recognized.\n        ",
            "n_words": 52,
            "vocab_size": 41,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 189494,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/svg/text_mobject.py",
        "file_name": "text_mobject.py",
        "fun_name": "_text2settings",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _text2settings(self):\n        \n        t2xs = [\n            (self.t2f, \"font\"),\n            (self.t2s, \"slant\"),\n            (self.t2w, \"weight\"),\n            (self.t2c, \"color\"),\n        ]\n        setting_args = {arg: getattr(self, arg) for _, arg in t2xs}\n\n        settings = self._get_settings_from_t2xs(t2xs)\n        settings.extend(self._get_settings_from_gradient(setting_args))\n\n        # Handle overlaps\n\n        settings.sort(key=lambda setting: setting.start)\n        for index, setting in enumerate(settings):\n            if index + 1 == len(settings):\n                break\n\n            next_setting = settings[index + 1]\n            if setting.end > next_setting.start:\n                new_setting = self._merge_settings(setting, next_setting, setting_args)\n                new_index = index + 1\n                while (\n                    new_index < len(settings)\n                    and settings[new_index].start < new_setting.start\n                ):\n                    new_index += 1\n                settings.insert(new_index, new_setting)\n\n        # Set all text settings (default font, slant, weight)\n        temp_settings = settings.copy()\n        start = 0\n        for setting in settings:\n            if setting.start != start:\n                temp_settings.append(TextSetting(start, setting.start, **setting_args))\n            start = setting.end\n        if start != len(self.text):\n            temp_settings.append(TextSetting(start, len(self.text), **setting_args))\n        settings = sorted(temp_settings, key=lambda setting: setting.start)\n\n        if re.search(r\"\\n\", self.text):\n            line_num = 0\n            for start, end in self._find_indexes(\"\\n\", self.text):\n                for setting in settings:\n                    if setting.line_num == -1:\n                        setting.line_num = line_num\n                    if start < setting.end:\n                        line_num += 1\n                        new_setting = copy.copy(setting)\n                        setting.end = end\n                        new_setting.start = end\n                        new_setting.line_num = line_num\n                        settings.append(new_setting)\n                        settings.sort(key=lambda setting: setting.start)\n                        break\n        for setting in settings:\n            if setting.line_num == -1:\n                setting.line_num = 0\n        return settings\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 888,
        "n_words": 182,
        "vocab_size": 99,
        "complexity": 17,
        "nloc": 52,
        "token_counts": 389,
        "n_ast_nodes": 612,
        "n_identifiers": 38,
        "d_id": 46094,
        "documentation": {
            "docstring": "Converts the texts and styles to a setting for parsing.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 176261,
        "commit_id": "290ebce534b84f9db20ec58b98cbb170e65a0ba1",
        "repo": "networkx",
        "path": "networkx/generators/social.py",
        "file_name": "social.py",
        "fun_name": "karate_club_graph",
        "commit_message": "Add weights to karate club graph (#5285)\n\nAdd weights to the karate_club_graph.\r\nModifies `non_randomness` and `naive_greedy_modularity_communities` to\r\naccept a `weight` parameter and modifies tests that use the kcg accordingly\r\n\r\nCo-authored-by: Kevin Berry <kevin.berry@worthix.com>\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def karate_club_graph():\n    \n    # Create the set of all members, and the members of each club.\n    all_members = set(range(34))\n    club1 = {0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 21}\n    # club2 = all_members - club1\n\n    G = nx.Graph()\n    G.add_nodes_from(all_members)\n    G.name = \"Zachary's Karate Club\"\n\n    zacharydat = \n\n    for row, line in enumerate(zacharydat.split(\"\\n\")):\n        thisrow = [int(b) for b in line.split()]\n        for col, entry in enumerate(thisrow):\n            if entry >= 1:\n                G.add_edge(row, col, weight=entry)\n\n    # Add the name of each member's club as a node attribute.\n    for v in G:\n        G.nodes[v][\"club\"] = \"Mr. Hi\" if v in club1 else \"Officer\"\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 193,
        "n_words": 106,
        "vocab_size": 77,
        "complexity": 7,
        "nloc": 49,
        "token_counts": 154,
        "n_ast_nodes": 241,
        "n_identifiers": 24,
        "d_id": 41796,
        "documentation": {
            "docstring": "Returns Zachary's Karate Club graph.\n\n    Each node in the returned graph has a node attribute 'club' that\n    indicates the name of the club to which the member represented by that node\n    belongs, either 'Mr. Hi' or 'Officer'. Each edge has a weight based on the\n    number of contexts in which that edge's incident node members interacted.\n\n    Examples\n    --------\n    To get the name of the club to which a node belongs::\n\n        >>> G = nx.karate_club_graph()\n        >>> G.nodes[5][\"club\"]\n        'Mr. Hi'\n        >>> G.nodes[9][\"club\"]\n        'Officer'\n\n    References\n    ----------\n    .. [1] Zachary, Wayne W.\n       \"An Information Flow Model for Conflict and Fission in Small Groups.\"\n       *Journal of Anthropological Research*, 33, 452--473, (1977).\n    \\\n0 4 5 3 3 3 3 2 2 0 2 3 2 3 0 0 0 2 0 2 0 2 0 0 0 0 0 0 0 0 0 2 0 0\n4 0 6 3 0 0 0 4 0 0 0 0 0 5 0 0 0 1 0 2 0 2 0 0 0 0 0 0 0 0 2 0 0 0\n5 6 0 3 0 0 0 4 5 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 3 0\n3 3 3 0 0 0 0 3 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n3 0 0 0 0 0 2 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n3 0 0 0 0 0 5 0 0 0 3 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n3 0 0 0 2 5 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n2 4 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n2 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 3\n0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2\n2 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n3 5 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 4\n0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2\n2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1\n2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 4 0 2 0 0 5 4\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 3 0 0 0 2 0 0\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 2 0 0 0 0 0 0 7 0 0\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 2\n0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0 0 0 0 0 0 4\n0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2\n0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 4 0 0 0 0 0 3 2\n0 2 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3\n2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 7 0 0 2 0 0 0 4 4\n0 0 2 0 0 0 0 0 3 0 0 0 0 0 3 3 0 0 1 0 3 0 2 5 0 0 0 0 0 4 3 4 0 5\n0 0 0 0 0 0 0 0 4 2 0 0 0 3 2 4 0 0 2 1 1 0 3 4 0 0 2 4 2 2 3 4 5 0",
            "n_words": 1263,
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            "language": "en"
        }
    },
    {
        "id": 269517,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "spatial_3d_padding",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def spatial_3d_padding(x, padding=((1, 1), (1, 1), (1, 1)), data_format=None):\n    \n    assert len(padding) == 3\n    assert len(padding[0]) == 2\n    assert len(padding[1]) == 2\n    assert len(padding[2]) == 2\n    if data_format is None:\n        data_format = image_data_format()\n    if data_format not in {\"channels_first\", \"channels_last\"}:\n        raise ValueError(\"Unknown data_format: \" + str(data_format))\n\n    if data_format == \"channels_first\":\n        pattern = [\n            [0, 0],\n            [0, 0],\n            [padding[0][0], padding[0][1]],\n            [padding[1][0], padding[1][1]],\n            [padding[2][0], padding[2][1]],\n        ]\n    else:\n        pattern = [\n            [0, 0],\n            [padding[0][0], padding[0][1]],\n            [padding[1][0], padding[1][1]],\n            [padding[2][0], padding[2][1]],\n            [0, 0],\n        ]\n    return tf.compat.v1.pad(x, pattern)\n\n\n@keras_export(\"keras.backend.stack\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.stack\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 262,
        "n_words": 83,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 49,
        "token_counts": 259,
        "n_ast_nodes": 396,
        "n_identifiers": 19,
        "d_id": 80148,
        "documentation": {
            "docstring": "Pads 5D tensor with zeros along the depth, height, width dimensions.\n\n    Pads these dimensions with respectively\n    \"padding[0]\", \"padding[1]\" and \"padding[2]\" zeros left and right.\n\n    For 'channels_last' data_format,\n    the 2nd, 3rd and 4th dimension will be padded.\n    For 'channels_first' data_format,\n    the 3rd, 4th and 5th dimension will be padded.\n\n    Args:\n        x: Tensor or variable.\n        padding: Tuple of 3 tuples, padding pattern.\n        data_format: One of `channels_last` or `channels_first`.\n\n    Returns:\n        A padded 5D tensor.\n\n    Raises:\n        ValueError: if `data_format` is neither\n            `channels_last` or `channels_first`.\n\n    ",
            "n_words": 80,
            "vocab_size": 59,
            "n_whitespaces": 156,
            "language": "en"
        }
    },
    {
        "id": 11454,
        "commit_id": "a5fd192b186c66aa983137ca3a179caac7f6b786",
        "repo": "jina",
        "path": "jina/hubble/hubapi.py",
        "file_name": "hubapi.py",
        "fun_name": "list_local",
        "commit_message": "feat: optimize create hub root (#4388)",
        "code": "def list_local():\n    \n    result = []\n    for dist_name in get_hub_packages_dir().glob(r'*/v*.dist-info'):\n        result.append(dist_name)\n\n    return result\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 53,
        "n_identifiers": 6,
        "d_id": 2043,
        "documentation": {
            "docstring": "List the locally-available executor packages.\n\n    :return: the list of local executors (if found)\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 84081,
        "commit_id": "a142fbff85302c5e3acb2e204eca2e9c75dbc74b",
        "repo": "zulip",
        "path": "zerver/tests/test_markdown.py",
        "file_name": "test_markdown.py",
        "fun_name": "test_render_mention_stream_api",
        "commit_message": "tests: Refactor away result.json() calls with helpers.\n\nSigned-off-by: Zixuan James Li <p359101898@gmail.com>",
        "code": "def test_render_mention_stream_api(self) -> None:\n        \n        content = \"This mentions #**Denmark** and @**King Hamlet**.\"\n        result = self.api_post(\n            self.example_user(\"othello\"),\n            \"/api/v1/messages/render\",\n            dict(content=content),\n        )\n        response_dict = self.assert_json_success(result)\n        user_id = self.example_user(\"hamlet\").id\n        stream_id = get_stream(\"Denmark\", get_realm(\"zulip\")).id\n        self.assertEqual(\n            response_dict[\"rendered\"],\n            f'<p>This mentions <a class=\"stream\" data-stream-id=\"{stream_id}\" href=\"/#narrow/stream/{stream_id}-Denmark\">#Denmark</a> and <span class=\"user-mention\" data-user-id=\"{user_id}\">@King Hamlet</span>.</p>',\n        )\n\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 161,
        "n_words": 43,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 78,
        "n_ast_nodes": 149,
        "n_identifiers": 15,
        "d_id": 17769,
        "documentation": {
            "docstring": "Determines whether we're correctly passing the realm context",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 260694,
        "commit_id": "c925b7e24c4b58e7191eec935d724e23d351c58b",
        "repo": "scikit-learn",
        "path": "sklearn/feature_extraction/text.py",
        "file_name": "text.py",
        "fun_name": "strip_accents_unicode",
        "commit_message": "DOC Ensures that strip_accents_unicode passes numpydoc (#24232)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def strip_accents_unicode(s):\n    \n    try:\n        # If `s` is ASCII-compatible, then it does not contain any accented\n        # characters and we can avoid an expensive list comprehension\n        s.encode(\"ASCII\", errors=\"strict\")\n        return s\n    except UnicodeEncodeError:\n        normalized = unicodedata.normalize(\"NFKD\", s)\n        return \"\".join([c for c in normalized if not unicodedata.combining(c)])\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 95,
        "n_words": 44,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 54,
        "n_ast_nodes": 97,
        "n_identifiers": 11,
        "d_id": 76422,
        "documentation": {
            "docstring": "Transform accentuated unicode symbols into their simple counterpart.\n\n    Warning: the python-level loop and join operations make this\n    implementation 20 times slower than the strip_accents_ascii basic\n    normalization.\n\n    Parameters\n    ----------\n    s : str\n        The string to strip.\n\n    Returns\n    -------\n    s : str\n        The stripped string.\n\n    See Also\n    --------\n    strip_accents_ascii : Remove accentuated char for any unicode symbol that\n        has a direct ASCII equivalent.\n    ",
            "n_words": 61,
            "vocab_size": 52,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 159748,
        "commit_id": "b8c82404855d317a9ac77b4743d3db39f009c6aa",
        "repo": "numpy",
        "path": "numpy/lib/tests/test_io.py",
        "file_name": "test_io.py",
        "fun_name": "test_default_float_converter_exception",
        "commit_message": "TST: Fixup current loadtxt tests for changes",
        "code": "def test_default_float_converter_exception(self):\n        \n        c = TextIO(\"qrs tuv\")  # Invalid values for default float converter\n        with pytest.raises(ValueError,\n                match=\"could not convert string 'qrs' to float64\"):\n            np.loadtxt(c)\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 71,
        "n_words": 23,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 58,
        "n_identifiers": 10,
        "d_id": 38416,
        "documentation": {
            "docstring": "\n        Ensure that the exception message raised during failed floating point\n        conversion is correct. Regression test related to gh-19598.\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 164926,
        "commit_id": "03fef5f0e35200aa5828975b62782bcf11faa0d2",
        "repo": "pandas",
        "path": "pandas/tests/plotting/common.py",
        "file_name": "common.py",
        "fun_name": "_check_axes_shape",
        "commit_message": "TST: Clean tests/plotting (#45992)",
        "code": "def _check_axes_shape(self, axes, axes_num=None, layout=None, figsize=None):\n        \n        from pandas.plotting._matplotlib.tools import flatten_axes\n\n        if figsize is None:\n            figsize = (6.4, 4.8)\n        visible_axes = self._flatten_visible(axes)\n\n        if axes_num is not None:\n            assert len(visible_axes) == axes_num\n            for ax in visible_axes:\n                # check something drawn on visible axes\n                assert len(ax.get_children()) > 0\n\n        if layout is not None:\n            result = self._get_axes_layout(flatten_axes(axes))\n            assert result == layout\n\n        tm.assert_numpy_array_equal(\n            visible_axes[0].figure.get_size_inches(),\n            np.array(figsize, dtype=np.float64),\n        )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 225,
        "n_words": 62,
        "vocab_size": 46,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 133,
        "n_ast_nodes": 196,
        "n_identifiers": 26,
        "d_id": 39622,
        "documentation": {
            "docstring": "\n        Check expected number of axes is drawn in expected layout\n\n        Parameters\n        ----------\n        axes : matplotlib Axes object, or its list-like\n        axes_num : number\n            expected number of axes. Unnecessary axes should be set to\n            invisible.\n        layout : tuple\n            expected layout, (expected number of rows , columns)\n        figsize : tuple\n            expected figsize. default is matplotlib default\n        ",
            "n_words": 54,
            "vocab_size": 35,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 281196,
        "commit_id": "f40ba0d256a78ab2b8461f0df3a9a52ca7dc5704",
        "repo": "OpenBBTerminal",
        "path": "discordbot/stocks/technical_analysis/cg.py",
        "file_name": "cg.py",
        "fun_name": "cg_command",
        "commit_message": "Bot logging fix (#1105)\n\n* Write bot logs to stdout instead of a file\r\nHeroku's logging uses the stdout and has problems with files\r\n\r\n* Send \"you snooze you lose\" only if debug flag is enabled\r\n\r\n* Replace print statements with logger entries in the economy menu\r\n\r\n* Add logging to bot menu command calls\r\n\r\n* Silence bandit warnings about the REPLACE_ME token\r\n\r\n* Organize imports and update logging in economy menu\r\n\r\n* Organize imports and update logging in dps menu\r\n\r\n* Organize imports and update logging in dd menu\r\n\r\n* Organize imports and update logging in gov menu\r\n\r\n* Organize imports and update logging in options menu\r\n\r\n* Organize imports and update logging in screener menu\r\n\r\n* Organize imports and update logging in ta menu\r\n\r\n* Revert automatic import sorting\r\n\r\n* Add logging to the options reaction helper",
        "code": "async def cg_command(ctx, ticker=\"\", length=\"14\", start=\"\", end=\"\"):\n    \n\n    try:\n\n        # Debug\n        if cfg.DEBUG:\n            logger.debug(\n                \"!stocks.ta.cg %s %s %s %s\",\n                ticker,\n                length,\n                start,\n                end,\n            )\n\n        # Check for argument\n        if ticker == \"\":\n            raise Exception(\"Stock ticker is required\")\n\n        if start == \"\":\n            start = datetime.now() - timedelta(days=365)\n        else:\n            start = datetime.strptime(start, cfg.DATE_FORMAT)\n\n        if end == \"\":\n            end = datetime.now()\n        else:\n            end = datetime.strptime(end, cfg.DATE_FORMAT)\n\n        if not length.lstrip(\"-\").isnumeric():\n            raise Exception(\"Number has to be an integer\")\n        length = float(length)\n\n        ticker = ticker.upper()\n        df_stock = discordbot.helpers.load(ticker, start)\n        if df_stock.empty:\n            raise Exception(\"Stock ticker is invalid\")\n\n        # Retrieve Data\n        df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]\n\n        df_ta = momentum_model.cg(\"1440min\", df_stock, length)\n\n        # Output Data\n        fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)\n        ax = axes[0]\n        ax.set_title(f\"{ticker} Centre of Gravity\")\n        ax.plot(df_stock.index, df_stock[\"Adj Close\"].values, \"k\", lw=1)\n        ax.set_xlim(df_stock.index[0], df_stock.index[-1])\n        ax.set_ylabel(\"Share Price ($)\")\n        ax.grid(b=True, which=\"major\", color=\"#666666\", linestyle=\"-\")\n\n        ax2 = axes[1]\n        ax2.plot(df_ta.index, df_ta.values, \"b\", lw=2, label=\"CG\")\n        # shift cg 1 bar forward for signal\n        signal = df_ta.values\n        signal = np.roll(signal, 1)\n        ax2.plot(df_ta.index, signal, \"g\", lw=1, label=\"Signal\")\n        ax2.set_xlim(df_stock.index[0], df_stock.index[-1])\n        ax2.grid(b=True, which=\"major\", color=\"#666666\", linestyle=\"-\")\n\n        plt.gcf().autofmt_xdate()\n        fig.tight_layout(pad=1)\n        plt.legend()\n\n        plt.savefig(\"ta_cg.png\")\n        uploaded_image = gst_imgur.upload_image(\"ta_cg.png\", title=\"something\")\n        image_link = uploaded_image.link\n        if cfg.DEBUG:\n            logger.debug(\"Image URL: %s\", image_link)\n        title = \"Stocks: Center-of-Gravity \" + ticker\n        embed = discord.Embed(title=title, colour=cfg.COLOR)\n        embed.set_author(\n            name=cfg.AUTHOR_NAME,\n            icon_url=cfg.AUTHOR_ICON_URL,\n        )\n        embed.set_image(url=image_link)\n        os.remove(\"ta_cg.png\")\n\n        await ctx.send(embed=embed)\n\n    except Exception as e:\n        embed = discord.Embed(\n            title=\"ERROR Stocks: Center-of-Gravity\",\n            colour=cfg.COLOR,\n            description=e,\n        )\n        embed.set_author(\n            name=cfg.AUTHOR_NAME,\n            icon_url=cfg.AUTHOR_ICON_URL,\n        )\n\n        await ctx.send(embed=embed)\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 854,
        "n_words": 226,
        "vocab_size": 155,
        "complexity": 9,
        "nloc": 71,
        "token_counts": 574,
        "n_ast_nodes": 948,
        "n_identifiers": 85,
        "d_id": 83602,
        "documentation": {
            "docstring": "Displays chart with centre of gravity [Yahoo Finance]",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 60934,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/operations/install/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "csv_io_kwargs",
        "commit_message": "upd; format",
        "code": "def csv_io_kwargs(mode):\n    # type: (str) -> Dict[str, Any]\n    \n    return {'mode': mode, 'newline': '', 'encoding': 'utf-8'}\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 43,
        "n_identifiers": 2,
        "d_id": 12349,
        "documentation": {
            "docstring": "Return keyword arguments to properly open a CSV file\n    in the given mode.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 198528,
        "commit_id": "99ede53223eafb56b2c2b4ab7b8a6764b628c9d9",
        "repo": "sympy",
        "path": "sympy/physics/continuum_mechanics/truss.py",
        "file_name": "truss.py",
        "fun_name": "change_node_label",
        "commit_message": "remove_load method added along with other changes",
        "code": "def change_node_label(self, label, new_label):\n        \n        if label not in self._node_labels:\n            raise ValueError(\"No such node exists for the Truss\")\n        else:\n            for node in self._nodes:\n                if node[0] == label:\n                    if self._supports[label] == 'pinned':\n                        if 'R_'+str(label)+'_x' in list(self._reaction_loads) and 'R_'+str(label)+'_y' in list(self._reaction_loads):\n                            self._reaction_loads['R_'+str(new_label)+'_x'] = self._reaction_loads['R_'+str(label)+'_x']\n                            self._reaction_loads['R_'+str(new_label)+'_y'] = self._reaction_loads['R_'+str(label)+'_y']\n                            self._reaction_loads.pop('R_'+str(label)+'_x')\n                            self._reaction_loads.pop('R_'+str(label)+'_y')\n                        self._loads['R_'+str(new_label)+'_x'] = self._loads['R_'+str(label)+'_x'] \n                        self._loads['R_'+str(new_label)+'_y'] = self._loads['R_'+str(label)+'_y']\n                        self._loads.pop('R_'+str(label)+'_x')\n                        self._loads.pop('R_'+str(label)+'_y')\n                    elif self._supports[label] == 'roller':\n                        if 'R_'+str(label)+'_y' in list(self._reaction_loads):\n                            self._reaction_loads['R_'+str(new_label)+'_y'] = self._reaction_loads['R_'+str(label)+'_y']\n                            self._reaction_loads.pop('R_'+str(label)+'_y')\n                        self._loads['R_'+str(new_label)+'_y'] = self._loads['R_'+str(label)+'_y']\n                        self._loads.pop('R_'+str(label)+'_y')\n                    for member in self._members:\n                        if member[1] == node[0]:\n                            member[1] = new_label\n                            self._member_nodes[member[0]] = [new_label, member[2]]\n                            self._nodes_occupied[(new_label, member[2])] = True\n                            self._nodes_occupied[(member[2], new_label)] = True\n                            self._nodes_occupied.pop(tuple([label, member[2]]))\n                            self._nodes_occupied.pop(tuple([member[2], label]))\n                        elif member[2] == node[0]:\n                            member[2] = new_label\n                            self._member_nodes[member[0]] = [member[1], new_label]\n                            self._nodes_occupied[(member[1], new_label)] = True\n                            self._nodes_occupied[(new_label, member[1])] = True\n                            self._nodes_occupied.pop(tuple([member[1], label]))\n                            self._nodes_occupied.pop(tuple([label, member[1]]))\n                    self._nodes[self._nodes.index((label, node[1], node[2]))] = (new_label, node[1], node[2])\n                    self._node_labels[self._node_labels.index(node[0])] = new_label\n                    self._loads[new_label] = self._loads[node[0]]\n                    self._loads.pop(node[0])\n                    self._supports[new_label] = self._supports[node[0]]\n                    self._supports.pop(node[0])\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 1084,
        "n_words": 138,
        "vocab_size": 80,
        "complexity": 12,
        "nloc": 43,
        "token_counts": 682,
        "n_ast_nodes": 1114,
        "n_identifiers": 20,
        "d_id": 48980,
        "documentation": {
            "docstring": "\n        This method changes the label of a node.\n\n        Parameters\n        ==========\n        label: String or Symbol\n            The label of the node for which the label has\n            to be changed.\n\n        new_label: String or Symbol\n            The new label of the node.\n\n        Examples\n        ========\n\n        >>> from sympy.physics.continuum_mechanics.truss import Truss\n        >>> t = Truss()\n        >>> t.add_node('A', 0, 0)\n        >>> t.add_node('B', 3, 0)\n        >>> t.nodes\n        [('A', 0, 0), ('B', 3, 0)]\n        >>> t.change_node_label('A', 'C')\n        >>> t.nodes\n        [('C', 0, 0), ('B', 3, 0)]\n        >>> t.add_member('BC', 'B', 'C')\n        >>> t.members\n        [['BC', 'B', 'C']]\n        >>> t.change_member_label('BC', 'BC_new')\n        >>> t.members\n        [['BC_new', 'B', 'C']]\n        ",
            "n_words": 92,
            "vocab_size": 55,
            "n_whitespaces": 287,
            "language": "en"
        }
    },
    {
        "id": 244226,
        "commit_id": "4aaaf4dccfe26ac2265f77069f09aa8204f23337",
        "repo": "mmdetection",
        "path": "mmdet/datasets/openimages.py",
        "file_name": "openimages.py",
        "fun_name": "get_cat_ids",
        "commit_message": "[Feature] Support Class Aware Sampler (#7436)\n\n* [Feature] Support Class Aware Sampler\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* rename get_label_dict to get_index_dict\r\n\r\n* fix cas logic\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix",
        "code": "def get_cat_ids(self, idx):\n        \n        return self.get_ann_info(idx)['labels'].astype(np.int).tolist()\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 29,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 70290,
        "documentation": {
            "docstring": "Get category ids by index.\n\n        Args:\n            idx (int): Index of data.\n\n        Returns:\n            list[int]: All categories in the image of specified index.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 220797,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/tasks.py",
        "file_name": "tasks.py",
        "fun_name": "print_stack",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def print_stack(self, *, limit=None, file=None):\n        \n        return base_tasks._task_print_stack(self, limit, file)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 23,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 27,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 56120,
        "documentation": {
            "docstring": "Print the stack or traceback for this task's coroutine.\n\n        This produces output similar to that of the traceback module,\n        for the frames retrieved by get_stack().  The limit argument\n        is passed to get_stack().  The file argument is an I/O stream\n        to which the output is written; by default output is written\n        to sys.stderr.\n        ",
            "n_words": 52,
            "vocab_size": 35,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 110473,
        "commit_id": "b51c471f0bea8ad2bd3e295ebf896cba0efbb5ef",
        "repo": "matplotlib",
        "path": "lib/matplotlib/offsetbox.py",
        "file_name": "offsetbox.py",
        "fun_name": "_get_aligned_offsets",
        "commit_message": "FIX: VPacker and HPacker bottom/top alignment\n\nThe bottom and top alignments were incorrectly defined before,\nthis updates them to have the expected alignment.",
        "code": "def _get_aligned_offsets(hd_list, height, align=\"baseline\"):\n    \n\n    if height is None:\n        height = max(h for h, d in hd_list)\n    _api.check_in_list(\n        [\"baseline\", \"left\", \"top\", \"right\", \"bottom\", \"center\"], align=align)\n\n    if align == \"baseline\":\n        height_descent = max(h - d for h, d in hd_list)\n        descent = max(d for h, d in hd_list)\n        height = height_descent + descent\n        offsets = [0. for h, d in hd_list]\n    elif align in [\"left\", \"bottom\"]:\n        descent = 0.\n        offsets = [d for h, d in hd_list]\n    elif align in [\"right\", \"top\"]:\n        descent = 0.\n        offsets = [height - h + d for h, d in hd_list]\n    elif align == \"center\":\n        descent = 0.\n        offsets = [(height - h) * .5 + d for h, d in hd_list]\n\n    return height, descent, offsets\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 228,
        "n_words": 120,
        "vocab_size": 50,
        "complexity": 13,
        "nloc": 20,
        "token_counts": 186,
        "n_ast_nodes": 294,
        "n_identifiers": 12,
        "d_id": 24176,
        "documentation": {
            "docstring": "\n    Align boxes each specified by their ``(height, descent)`` pair.\n\n    For simplicity of the description, the terminology used here assumes a\n    horizontal layout (i.e., vertical alignment), but the function works\n    equally for a vertical layout.\n\n    Parameters\n    ----------\n    hd_list\n        List of (height, xdescent) of boxes to be aligned.\n    height : float or None\n        Intended total height. If None, the maximum of the heights in *hd_list*\n        is used.\n    align : {'baseline', 'left', 'top', 'right', 'bottom', 'center'}\n        The alignment anchor of the boxes.\n\n    Returns\n    -------\n    height\n        The total height of the packing (if a value was originally passed in,\n        it is returned without checking that it is actually large enough).\n    descent\n        The descent of the packing.\n    offsets\n        The bottom offsets of the boxes.\n    ",
            "n_words": 119,
            "vocab_size": 87,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 31640,
        "commit_id": "d6b6fb9963e094216daa30ebf61224ca1c46921e",
        "repo": "transformers",
        "path": "src/transformers/models/codegen/modeling_codegen.py",
        "file_name": "modeling_codegen.py",
        "fun_name": "duplicate_interleave",
        "commit_message": "Add CodeGen model (#17443)\n\n* Add CodeGen model\r\n\r\n* Add missing key and switch order of super()\r\n\r\n* Fix torch.ones init with uint8 instead of bool\r\n\r\n* Address comments: copy statements and doc\r\n\r\n* update tests\r\n\r\n* remove old model parallel\r\n\r\n* fix batch gen tests\r\n\r\n* fix batch gen test\r\n\r\n* update test_gpt2_sample_max_time\r\n\r\n* fix codgen test and revert gpt2 test change\r\n\r\n* Fix incorrect tie_word_embedding value, typo, URL\r\n\r\n* Fix model order in README and styling\r\n\r\n* Reorder model list alphabetically\r\n\r\n* Set tie_word_embedding to False by default\r\n\r\n* Apply suggestions from code review\r\n\r\n* Better attn mask name & remove attn masked_bias\r\n\r\n* add tokenizer for codegen\r\n\r\n* quality\r\n\r\n* doc tokenizer\r\n\r\n* fix-copies\r\n\r\n* add CodeGenTokenizer in converter\r\n\r\n* make truncation optional\r\n\r\n* add test for truncation\r\n\r\n* add copyright\r\n\r\n* fix-copies\r\n\r\n* fix fast tokenizer decode\r\n\r\n* Update src/transformers/models/codegen/tokenization_codegen.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* increase vocab_size in tests\r\n\r\nCo-authored-by: patil-suraj <surajp815@gmail.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def duplicate_interleave(m):\n    \n    dim0 = m.shape[0]\n    m = m.view(-1, 1)  # flatten the matrix\n    m = m.repeat(1, 2)  # repeat all elements into the 2nd dimension\n    m = m.view(dim0, -1)  # reshape into a matrix, interleaving the copy\n    return m\n\n\n# Copied from transformers.models.gptj.modeling_gptj.apply_rotary_pos_emb",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 63,
        "n_words": 43,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 48,
        "n_ast_nodes": 81,
        "n_identifiers": 6,
        "d_id": 5777,
        "documentation": {
            "docstring": "\n    A simple version of `torch.repeat_interleave` for duplicating a matrix while interleaving the copy.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 282731,
        "commit_id": "f2ca215132de40804667feb4deaa0c6b8bfc3d25",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/econometrics/econometrics_model.py",
        "file_name": "econometrics_model.py",
        "fun_name": "get_granger_causality",
        "commit_message": "Econometrics Menu (#1403)\n\n* Add Statistics Menu\n\n* Add Granger Causality test\n\n* Apply Black formatting\n\n* Add Cointegration Tests\n\n* Adjust plotting for Cointegration test\n\n* Add Significant parameter to Cointegration tests\n\n* Move regression functions to seperate .py files\n\n* Progress on Panel Data\n\n* A lot of progress for Panel Data\n\n* Make functions robust and improve documentation\n\n* Re-enable Breusch-Godfrey\n\n* Add modify functionality\n\n* Improve modify functionality\n\n* Add Breusch-Pagan heteroscedasticity test\n\n* Capitalize a word\n\n* Include documentatin for the Statistics Menu\n\n* Update _index.md\n\n* Update _index.md\n\n* Update _index.md\n\n* Fix export statements and add Example datasets\n\n* Update example with Longley's dataset\n\n* Update documentation with a legit source\n\n* Compare the results from each regression models based on the wage_panel dataset\n\n* Updated with all relevant types of regression tables\n\n* Update with all relevant regression types for Panel data\n\n* Update _index.md\n\n* Add change column type, improve OLS, add time and entity effects for FE\n\n* Update documentation and fix a small bug\n\n* Add in Statistics menu, replacing Custom menu\n\n* Remove custom menu\n\n* Add in documentation\n\n* Add in gst files\n\n* Cointegration can be used on any amount of columns\n\n* Add Tests\n\n* Make tests time invariant\n\n* Update Poetry and Requirements\n\n* Change name of Statistics menu to Econometrics menu\n\n* Rename scripts\n\n* Add type in Documentation\n\n* Change names from Statistics to Econometrics\n\n* Add graph\n\n* Update tests with rounding and naming\n\n* Make minor adjustments to fix the tests\n\n* Updating tests : allow extra args for capture\n\n* Apply recorder formatting\n\n* Adding some minor formatting\n\n* Fix error with MyPy\n\n* Attempt to fix MyPy annoyance\n\n* super small style things\n\n* Fix small bugs and add plot command to dwat\n\n* Small description mistake\n\n* Update documentation with missing argument\n\n* Update styling\n\n* Add error handling and add improve show functionality\n\n* Fix merge issue\n\n* Allow import from custom_imports\n\nCo-authored-by: Jeroen Bouma <jeroenbouma@MacBook-Pro-van-Jeroen.local>\nCo-authored-by: jmaslek <jmaslek11@gmail.com>\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>",
        "code": "def get_granger_causality(time_series_y, time_series_x, lags):\n    \n    granger_set = pd.concat([time_series_y, time_series_x], axis=1)\n\n    granger = grangercausalitytests(granger_set, [lags], verbose=False)\n\n    return granger\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 42,
        "n_ast_nodes": 63,
        "n_identifiers": 11,
        "d_id": 84280,
        "documentation": {
            "docstring": "Calculate granger tests\n\n    Parameters\n    ----------\n    time_series_y : Series\n        The series you want to test Granger Causality for.\n    time_series_x : Series\n        The series that you want to test whether it Granger-causes time_series_y\n    lags : int\n        The amoiunt of lags for the Granger test. By default, this is set to 3.\n    ",
            "n_words": 49,
            "vocab_size": 35,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 244007,
        "commit_id": "1516986a616fee8bb741d0ab2be40683045efccd",
        "repo": "mmdetection",
        "path": "mmdet/datasets/pipelines/loading.py",
        "file_name": "loading.py",
        "fun_name": "_load_bboxes",
        "commit_message": "[Feature] Support OpenImages Dataset (#6331)\n\n* [Feature] support openimage group of eval\r\n\r\n* [Feature] support openimage group of eval\r\n\r\n* support openimage dataset\r\n\r\n* support openimage challenge dataset\r\n\r\n* fully support OpenImages-V6 and OpenImages Challenge 2019\r\n\r\n* Fix some logic error\r\n\r\n* update config file\r\n\r\n* fix get data_infos error\r\n\r\n* fully support OpenImages evaluation\r\n\r\n* update OpenImages config files\r\n\r\n* [Feature] support OpenImages datasets\r\n\r\n* fix bug\r\n\r\n* support load image metas from pipeline\r\n\r\n* fix bug\r\n\r\n* fix get classes logic error\r\n\r\n* update code\r\n\r\n* support get image metas\r\n\r\n* support openimags\r\n\r\n* support collect image metas\r\n\r\n* support Open Images\r\n\r\n* fix openimages logic\r\n\r\n* minor fix\r\n\r\n* add a new function to compute openimages tpfp\r\n\r\n* minor fix\r\n\r\n* fix ci error\r\n\r\n* minor fix\r\n\r\n* fix indication\r\n\r\n* minor fix\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* minor fix\r\n\r\n* update readme\r\n\r\n* support loading image level labels and fix some logic\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add class names\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add openimages test unit\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* fix logic error\r\n\r\n* minor fix\r\n\r\n* fully support openimages\r\n\r\n* minor fix\r\n\r\n* fix docstring\r\n\r\n* fix docstrings in readthedocs\r\n\r\n* update get image metas script\r\n\r\n* label_description_file -> label_file\r\n\r\n* update openimages readme\r\n\r\n* fix test unit\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* update readme file\r\n\r\n* Update get_image_metas.py",
        "code": "def _load_bboxes(self, results):\n        \n\n        ann_info = results['ann_info']\n        results['gt_bboxes'] = ann_info['bboxes'].copy()\n\n        if self.denorm_bbox:\n            h, w = results['img_shape'][:2]\n            bbox_num = results['gt_bboxes'].shape[0]\n            if bbox_num != 0:\n                results['gt_bboxes'][:, 0::2] *= w\n                results['gt_bboxes'][:, 1::2] *= h\n            results['gt_bboxes'] = results['gt_bboxes'].astype(np.float32)\n\n        gt_bboxes_ignore = ann_info.get('bboxes_ignore', None)\n        if gt_bboxes_ignore is not None:\n            results['gt_bboxes_ignore'] = gt_bboxes_ignore.copy()\n            results['bbox_fields'].append('gt_bboxes_ignore')\n        results['bbox_fields'].append('gt_bboxes')\n\n        gt_is_group_ofs = ann_info.get('gt_is_group_ofs', None)\n        if gt_is_group_ofs is not None:\n            results['gt_is_group_ofs'] = gt_is_group_ofs.copy()\n\n        return results\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 238,
        "n_words": 61,
        "vocab_size": 39,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 176,
        "n_ast_nodes": 303,
        "n_identifiers": 17,
        "d_id": 70196,
        "documentation": {
            "docstring": "Private function to load bounding box annotations.\n\n        Args:\n            results (dict): Result dict from :obj:`mmdet.CustomDataset`.\n\n        Returns:\n            dict: The dict contains loaded bounding box annotations.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 160598,
        "commit_id": "126046f84449fffeb0c75ae88657ce6b90236eee",
        "repo": "numpy",
        "path": "numpy/core/shape_base.py",
        "file_name": "shape_base.py",
        "fun_name": "hstack",
        "commit_message": "ENH: adding casting option to numpy.stack. (#21627)\n\nnp.concatenate and np.stack are similar methods, but only np.concatenate has the casting option.\r\n\r\nThis PR puts the casting option into the np.stack method to control what kind of data casting may occur\r\n\r\nCloses gh-20959\r\n\r\n* ENH: adding casting option to numpy.stack.\r\n\r\nSee #20959\r\n\r\n* ENH: adding dtype option to numpy.stack.\r\n\r\nSee #20959\r\n\r\n* REV: removing auto-generated file loops_modulo.dispatch.c\r\n\r\nSee numpy#20959\r\n\r\n* REV: removing auto-generated file loops_modulo.dispatch.c\r\n\r\nSee numpy#20959\r\n\r\n* REV: removing inserted newlines\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* DOC: inserting versionadded info in dtype and casting parameters.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* TST: writing tests to stack method with dtype and casting options\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* DOC: adding upcoming_change file for new options casting and dtype in method stack.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* REV: reverting lint errors.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* DOC: inserting hstack and vstack methods in upcoming changes\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* ENH: adding dtype and casting keyword arguments to numpy.vstack and numpy.hstack.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* TST: writing tests to vstack and hstack methods with dtype and casting keyword arguments.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* REV: reverting the 'out' option type in stack method.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* REV: Reverting out type changes in overload of shape_base.pyi file.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: jhonatancunha <jhonatancunha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\n* DOC: correcting some english erros in upcoming_changes file.\r\n\r\nSee numpy#20959\r\n\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>\r\n\r\nCo-authored-by: JessePires <jessepires2010@gmail.com>\r\nCo-authored-by: alescrocaro <alescrocaro@gmail.com>\r\nCo-authored-by: JessePires <jesserocha@alunos.utfpr.edu.br>\r\nCo-authored-by: patriarka <matheussantanapatriarca2019@outlook.com>",
        "code": "def hstack(tup, *, dtype=None, casting=\"same_kind\"):\n    \n    if not overrides.ARRAY_FUNCTION_ENABLED:\n        # raise warning if necessary\n        _arrays_for_stack_dispatcher(tup, stacklevel=2)\n\n    arrs = atleast_1d(*tup)\n    if not isinstance(arrs, list):\n        arrs = [arrs]\n    # As a special case, dimension 0 of 1-dimensional arrays is \"horizontal\"\n    if arrs and arrs[0].ndim == 1:\n        return _nx.concatenate(arrs, 0, dtype=dtype, casting=casting)\n    else:\n        return _nx.concatenate(arrs, 1, dtype=dtype, casting=casting)\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 110,
        "n_words": 54,
        "vocab_size": 42,
        "complexity": 5,
        "nloc": 10,
        "token_counts": 99,
        "n_ast_nodes": 154,
        "n_identifiers": 15,
        "d_id": 38661,
        "documentation": {
            "docstring": "\n    Stack arrays in sequence horizontally (column wise).\n\n    This is equivalent to concatenation along the second axis, except for 1-D\n    arrays where it concatenates along the first axis. Rebuilds arrays divided\n    by `hsplit`.\n\n    This function makes most sense for arrays with up to 3 dimensions. For\n    instance, for pixel-data with a height (first axis), width (second axis),\n    and r/g/b channels (third axis). The functions `concatenate`, `stack` and\n    `block` provide more general stacking and concatenation operations.\n\n    Parameters\n    ----------\n    tup : sequence of ndarrays\n        The arrays must have the same shape along all but the second axis,\n        except 1-D arrays which can be any length.\n\n    dtype : str or dtype\n        If provided, the destination array will have this dtype. Cannot be\n        provided together with `out`.\n\n    .. versionadded:: 1.24\n\n    casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n        Controls what kind of data casting may occur. Defaults to 'same_kind'.\n\n    .. versionadded:: 1.24\n\n    Returns\n    -------\n    stacked : ndarray\n        The array formed by stacking the given arrays.\n\n    See Also\n    --------\n    concatenate : Join a sequence of arrays along an existing axis.\n    stack : Join a sequence of arrays along a new axis.\n    block : Assemble an nd-array from nested lists of blocks.\n    vstack : Stack arrays in sequence vertically (row wise).\n    dstack : Stack arrays in sequence depth wise (along third axis).\n    column_stack : Stack 1-D arrays as columns into a 2-D array.\n    hsplit : Split an array into multiple sub-arrays horizontally (column-wise).\n\n    Examples\n    --------\n    >>> a = np.array((1,2,3))\n    >>> b = np.array((4,5,6))\n    >>> np.hstack((a,b))\n    array([1, 2, 3, 4, 5, 6])\n    >>> a = np.array([[1],[2],[3]])\n    >>> b = np.array([[4],[5],[6]])\n    >>> np.hstack((a,b))\n    array([[1, 4],\n           [2, 5],\n           [3, 6]])\n\n    ",
            "n_words": 270,
            "vocab_size": 172,
            "n_whitespaces": 447,
            "language": "en"
        }
    },
    {
        "id": 259460,
        "commit_id": "75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/_regression.py",
        "file_name": "_regression.py",
        "fun_name": "d2_tweedie_score",
        "commit_message": "ENH migrate GLMs / TweedieRegressor to linear loss (#22548)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def d2_tweedie_score(y_true, y_pred, *, sample_weight=None, power=0):\n    \n    y_type, y_true, y_pred, _ = _check_reg_targets(\n        y_true, y_pred, None, dtype=[np.float64, np.float32]\n    )\n    if y_type == \"continuous-multioutput\":\n        raise ValueError(\"Multioutput not supported in d2_tweedie_score\")\n\n    if _num_samples(y_pred) < 2:\n        msg = \"D^2 score is not well-defined with less than two samples.\"\n        warnings.warn(msg, UndefinedMetricWarning)\n        return float(\"nan\")\n\n    y_true, y_pred = np.squeeze(y_true), np.squeeze(y_pred)\n    numerator = mean_tweedie_deviance(\n        y_true, y_pred, sample_weight=sample_weight, power=power\n    )\n\n    y_avg = np.average(y_true, weights=sample_weight)\n    denominator = _mean_tweedie_deviance(\n        y_true, y_avg, sample_weight=sample_weight, power=power\n    )\n\n    return 1 - numerator / denominator\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 164,
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        "vocab_size": 58,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 147,
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        "d_id": 75790,
        "documentation": {
            "docstring": "D^2 regression score function, percentage of Tweedie deviance explained.\n\n    Best possible score is 1.0 and it can be negative (because the model can be\n    arbitrarily worse). A model that always uses the empirical mean of `y_true` as\n    constant prediction, disregarding the input features, gets a D^2 score of 0.0.\n\n    Read more in the :ref:`User Guide <d2_tweedie_score>`.\n\n    .. versionadded:: 1.0\n\n    Parameters\n    ----------\n    y_true : array-like of shape (n_samples,)\n        Ground truth (correct) target values.\n\n    y_pred : array-like of shape (n_samples,)\n        Estimated target values.\n\n    sample_weight : array-like of shape (n_samples,), optional\n        Sample weights.\n\n    power : float, default=0\n        Tweedie power parameter. Either power <= 0 or power >= 1.\n\n        The higher `p` the less weight is given to extreme\n        deviations between true and predicted targets.\n\n        - power < 0: Extreme stable distribution. Requires: y_pred > 0.\n        - power = 0 : Normal distribution, output corresponds to r2_score.\n          y_true and y_pred can be any real numbers.\n        - power = 1 : Poisson distribution. Requires: y_true >= 0 and\n          y_pred > 0.\n        - 1 < p < 2 : Compound Poisson distribution. Requires: y_true >= 0\n          and y_pred > 0.\n        - power = 2 : Gamma distribution. Requires: y_true > 0 and y_pred > 0.\n        - power = 3 : Inverse Gaussian distribution. Requires: y_true > 0\n          and y_pred > 0.\n        - otherwise : Positive stable distribution. Requires: y_true > 0\n          and y_pred > 0.\n\n    Returns\n    -------\n    z : float or ndarray of floats\n        The D^2 score.\n\n    Notes\n    -----\n    This is not a symmetric function.\n\n    Like R^2, D^2 score may be negative (it need not actually be the square of\n    a quantity D).\n\n    This metric is not well-defined for single samples and will return a NaN\n    value if n_samples is less than two.\n\n    References\n    ----------\n    .. [1] Eq. (3.11) of Hastie, Trevor J., Robert Tibshirani and Martin J.\n           Wainwright. \"Statistical Learning with Sparsity: The Lasso and\n           Generalizations.\" (2015). https://trevorhastie.github.io\n\n    Examples\n    --------\n    >>> from sklearn.metrics import d2_tweedie_score\n    >>> y_true = [0.5, 1, 2.5, 7]\n    >>> y_pred = [1, 1, 5, 3.5]\n    >>> d2_tweedie_score(y_true, y_pred)\n    0.285...\n    >>> d2_tweedie_score(y_true, y_pred, power=1)\n    0.487...\n    >>> d2_tweedie_score(y_true, y_pred, power=2)\n    0.630...\n    >>> d2_tweedie_score(y_true, y_true, power=2)\n    1.0\n    ",
            "n_words": 353,
            "vocab_size": 196,
            "n_whitespaces": 630,
            "language": "en"
        }
    },
    {
        "id": 60728,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/index/package_finder.py",
        "file_name": "package_finder.py",
        "fun_name": "find_requirement",
        "commit_message": "upd; format",
        "code": "def find_requirement(self, req, upgrade):\n        # type: (InstallRequirement, bool) -> Optional[InstallationCandidate]\n        \n        hashes = req.hashes(trust_internet=False)\n        best_candidate_result = self.find_best_candidate(\n            req.name, specifier=req.specifier, hashes=hashes,\n        )\n        best_candidate = best_candidate_result.best_candidate\n\n        installed_version = None    # type: Optional[_BaseVersion]\n        if req.satisfied_by is not None:\n            installed_version = parse_version(req.satisfied_by.version)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 118,
        "n_words": 37,
        "vocab_size": 30,
        "complexity": 11,
        "nloc": 55,
        "token_counts": 214,
        "n_ast_nodes": 106,
        "n_identifiers": 15,
        "d_id": 12265,
        "documentation": {
            "docstring": "Try to find a Link matching req\n\n        Expects req, an InstallRequirement and upgrade, a boolean\n        Returns a InstallationCandidate if found,\n        Raises DistributionNotFound or BestVersionAlreadyInstalled otherwise\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 196757,
        "commit_id": "ad766d1c02943e86f50559abfd0c72e582c9ca6a",
        "repo": "sympy",
        "path": "sympy/assumptions/assume.py",
        "file_name": "assume.py",
        "fun_name": "add_handler",
        "commit_message": "Update the AskHandler deprecation warnings\n\nn.b., the issue number in the original warning message was wrong. It should\nhave been #20837.",
        "code": "def add_handler(self, handler):\n        sympy_deprecation_warning(\n            ,\n            deprecated_since_version=\"1.8\",\n            active_deprecations_target='deprecated-askhandler',\n        )\n        self.handlers.append(handler)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 62,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 28,
        "n_ast_nodes": 48,
        "n_identifiers": 8,
        "d_id": 48153,
        "documentation": {
            "docstring": "\n            The AskHandler system is deprecated. Predicate.add_handler()\n            should be replaced with the multipledispatch handler of Predicate.\n            ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 61435,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "get_revision",
        "commit_message": "upd; format",
        "code": "def get_revision(cls, location):\n        # type: (str) -> str\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 19,
        "n_identifiers": 4,
        "d_id": 12574,
        "documentation": {
            "docstring": "\n        Return the current commit id of the files at the given location.\n        ",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 268017,
        "commit_id": "3eb0485dd92c88cc92152d3656d94492db44b183",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/host_profiles.py",
        "file_name": "host_profiles.py",
        "fun_name": "get_config_profile_type_map",
        "commit_message": "ansible-test - Use more native type hints. (#78435)\n\n* ansible-test - Use more native type hints.\r\n\r\nSimple search and replace to switch from comments to native type hints for return types of functions with no arguments.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of simple single-line function annotation type comments to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of single-line function annotation type comments with default values to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nManual conversion of type annotation comments for functions which have pylint directives.",
        "code": "def get_config_profile_type_map() -> t.Dict[t.Type[HostConfig], t.Type[HostProfile]]:\n    \n    return get_type_map(HostProfile, HostConfig)\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 14,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 48,
        "n_identifiers": 7,
        "d_id": 79291,
        "documentation": {
            "docstring": "Create and return a mapping of HostConfig types to HostProfile types.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 68806,
        "commit_id": "00ef499739959630cd7cf97419fbb6ca59be05f2",
        "repo": "erpnext",
        "path": "erpnext/projects/utils.py",
        "file_name": "utils.py",
        "fun_name": "query_task",
        "commit_message": "refactor: use db independent offset syntax (#31345)\n\n* chore: use db independent offset syntax\r\n\r\n* fix: typo\r\n\r\n* style: reformat code to black spec\r\n\r\nCo-authored-by: Ankush Menat <ankush@frappe.io>",
        "code": "def query_task(doctype, txt, searchfield, start, page_len, filters):\n\tfrom frappe.desk.reportview import build_match_conditions\n\n\tsearch_string = \"%%%s%%\" % txt\n\torder_by_string = \"%s%%\" % txt\n\tmatch_conditions = build_match_conditions(\"Task\")\n\tmatch_conditions = (\"and\" + match_conditions) if match_conditions else \"\"\n\n\treturn frappe.db.sql(\n\t\t\n\t\t% (searchfield, \"%s\", \"%s\", match_conditions, \"%s\", searchfield, \"%s\", searchfield, \"%s\", \"%s\"),\n\t\t(search_string, search_string, order_by_string, order_by_string, page_len, start),\n\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
        "n_words": 53,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 18,
        "token_counts": 96,
        "n_ast_nodes": 150,
        "n_identifiers": 16,
        "d_id": 14887,
        "documentation": {
            "docstring": "select name, subject from `tabTask`\n\t\twhere (`%s` like %s or `subject` like %s) %s\n\t\torder by\n\t\t\tcase when `subject` like %s then 0 else 1 end,\n\t\t\tcase when `%s` like %s then 0 else 1 end,\n\t\t\t`%s`,\n\t\t\tsubject\n\t\tlimit %s offset %s",
            "n_words": 42,
            "vocab_size": 25,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 121063,
        "commit_id": "76fcf63fb4e53fd82faece677ed46db8b0c71707",
        "repo": "jax",
        "path": "jax/experimental/sparse/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_project_out",
        "commit_message": "Add initial LOBPCG top-k eigenvalue solver (#3112)\n\nThis initial version is f32-only for accelerators, since it relies on an eigh call (which itself is f32 at most) in its inner loop.\n\nFor details, see jax.experimental.linalg.standard_lobpcg documentation.\n\nThis is a partial implementation of the similar [scipy lobpcg\nfunction](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.lobpcg.html).",
        "code": "def _project_out(basis, U):\n  \n\n  # See Sec. 6.9 of The Symmetric Eigenvalue Problem by Beresford Parlett [1]\n  # which motivates two loop iterations for basis subtraction. This\n  # \"twice is enough\" approach is due to Kahan. See also a practical note\n  # by SLEPc developers [2].\n  #\n  # Interspersing with orthonormalization isn't directly grounded in the\n  # original analysis, but taken from Algorithm 5 of [3]. In practice, due to\n  # normalization, I have noticed that that the orthonormalized basis\n  # does not always end up as a subspace of the starting basis in practice.\n  # There may be room to refine this procedure further, but the adjustment\n  # in the subsequent block handles this edge case well enough for now.\n  #\n  # [1]: https://epubs.siam.org/doi/abs/10.1137/1.9781611971163\n  # [2]: http://slepc.upv.es/documentation/reports/str1.pdf\n  # [3]: https://arxiv.org/abs/1704.07458\n  for _ in range(2):\n    U -= _mm(basis, _mm(basis.T, U))\n    U = _orthonormalize(U)\n\n  # It's crucial to end on a subtraction of the original basis.\n  # This seems to be a detail not present in [2], possibly because of\n  # of reliance on soft locking.\n  #\n  # Near convergence, if the residuals R are 0 and our last\n  # operation when projecting (X, P) out from R is the orthonormalization\n  # done above, then due to catastrophic cancellation we may re-introduce\n  # (X, P) subspace components into U, which can ruin the Rayleigh-Ritz\n  # conditioning.\n  #\n  # We zero out any columns that are even remotely suspicious, so the invariant\n  # that [basis, U] is zero-or-orthogonal is ensured.\n  for _ in range(2):\n    U -= _mm(basis, _mm(basis.T, U))\n  normU = jnp.linalg.norm(U, ord=2, axis=0, keepdims=True)\n  U *= (normU >= 0.99).astype(U.dtype)\n\n  return U\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 311,
        "n_words": 269,
        "vocab_size": 171,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 101,
        "n_ast_nodes": 176,
        "n_identifiers": 17,
        "d_id": 27026,
        "documentation": {
            "docstring": "Derives component of U in the orthogonal complement of basis.\n\n  This method iteratively subtracts out the basis component and orthonormalizes\n  the remainder. To an extent, these two operations can oppose each other\n  when the remainder norm is near-zero (since normalization enlarges a vector\n  which may possibly lie in the subspace `basis` to be subtracted).\n\n  We make sure to prioritize orthogonality between `basis` and `U`, favoring\n  to return a lower-rank space thank `rank(U)`, in this tradeoff.\n\n  Args:\n    basis : An `(n, m)` array which describes a linear subspace of R^n, this\n        is assumed to be orthonormal but zero columns are allowed.\n    U : An `(n, k)` array representing another subspace of R^n, whose `basis`\n        component is to be projected out.\n\n  Returns:\n    An `(n, k)` array, with some columns possibly zeroed out, representing\n    the component of `U` in the complement of `basis`. The nonzero columns\n    are mutually orthonormal.\n  ",
            "n_words": 146,
            "vocab_size": 96,
            "n_whitespaces": 184,
            "language": "en"
        }
    },
    {
        "id": 24246,
        "commit_id": "7a99588dd8b678233eff0391aac13ebd0f7000f6",
        "repo": "PaddleOCR",
        "path": "ppocr/data/imaug/label_ops.py",
        "file_name": "label_ops.py",
        "fun_name": "filter_empty_contents",
        "commit_message": "add more dataset yamls and fix re exceptions (#6791)\n\n* add more dataset yamls and fix re exceptions",
        "code": "def filter_empty_contents(self, ocr_info):\n        \n        new_ocr_info = []\n        empty_index = []\n        for idx, info in enumerate(ocr_info):\n            if len(info[\"transcription\"]) > 0:\n                new_ocr_info.append(copy.deepcopy(info))\n            else:\n                empty_index.append(info[\"id\"])\n\n        for idx, info in enumerate(new_ocr_info):\n            new_link = []\n            for link in info[\"linking\"]:\n                if link[0] in empty_index or link[1] in empty_index:\n                    continue\n                new_link.append(link)\n            new_ocr_info[idx][\"linking\"] = new_link\n        return new_ocr_info\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 224,
        "n_words": 48,
        "vocab_size": 31,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 114,
        "n_ast_nodes": 188,
        "n_identifiers": 14,
        "d_id": 4713,
        "documentation": {
            "docstring": "\n        find out the empty texts and remove the links\n        ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 87324,
        "commit_id": "495d45c6547e398a5d4d3c1fa8cb97e69b1751f8",
        "repo": "sentry",
        "path": "tests/sentry/integrations/slack/notifications/test_issue_alert.py",
        "file_name": "test_issue_alert.py",
        "fun_name": "test_performance_issue_alert_user",
        "commit_message": "ref(slack): Update workflow alerts for perf issues (#40463)\n\nSlack workflow alerts for performance issues are showing a text value of\r\n\"no value\". This PR adds feature parity with error issues for workflow\r\nalerts so that they are shown with the proper data.",
        "code": "def test_performance_issue_alert_user(self, mock_func):\n        \n\n        event = self.create_performance_issue()\n\n        action_data = {\n            \"id\": \"sentry.mail.actions.NotifyEmailAction\",\n            \"targetType\": \"Member\",\n            \"targetIdentifier\": str(self.user.id),\n        }\n        rule = Rule.objects.create(\n            project=self.project,\n            label=\"ja rule\",\n            data={\n                \"match\": \"all\",\n                \"actions\": [action_data],\n            },\n        )\n\n        notification = AlertRuleNotification(\n            Notification(event=event, rule=rule), ActionTargetType.MEMBER, self.user.id\n        )\n        with self.feature(\"organizations:performance-issues\"), self.tasks():\n            notification.send()\n\n        attachment, text = get_attachment()\n        assert attachment[\"title\"] == \"N+1 Query\"\n        assert (\n            attachment[\"text\"]\n            == \"db - SELECT `books_author`.`id`, `books_author`.`name` FROM `books_author` WHERE `books_author`.`id` = %s LIMIT 21\"\n        )\n        assert (\n            attachment[\"footer\"]\n            == f\"{self.project.slug} | production | <http://testserver/settings/account/notifications/alerts/?referrer=issue_alert-slack-user|Notification Settings>\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 357,
        "n_words": 79,
        "vocab_size": 65,
        "complexity": 1,
        "nloc": 30,
        "token_counts": 149,
        "n_ast_nodes": 268,
        "n_identifiers": 28,
        "d_id": 18279,
        "documentation": {
            "docstring": "Test that performance issue alerts are sent to a Slack user.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 34328,
        "commit_id": "ac227093e41cecb07c7e0f2fc9a504850907bd06",
        "repo": "transformers",
        "path": "src/transformers/models/vilt/processing_vilt.py",
        "file_name": "processing_vilt.py",
        "fun_name": "save_pretrained",
        "commit_message": "Add ViLT (#14895)\n\n* First commit\r\n\r\n* Add conversion script\r\n\r\n* Make conversion script work for base model\r\n\r\n* More improvements\r\n\r\n* Update conversion script, works for vqa\r\n\r\n* Add indexing argument to meshgrid\r\n\r\n* Make conversion script work for ViltForPreTraining\r\n\r\n* Add ViltForPreTraining to docs\r\n\r\n* Fix device issue\r\n\r\n* Add processor\r\n\r\n* Add MinMaxResize to feature extractor\r\n\r\n* Implement call method of ViltProcessor\r\n\r\n* Fix tests\r\n\r\n* Add integration test\r\n\r\n* Add loss calculation for VQA\r\n\r\n* Improve tests\r\n\r\n* Improve some more tests\r\n\r\n* Debug tests\r\n\r\n* Small improvements\r\n\r\n* Add support for attention_mask\r\n\r\n* Remove mask_it\r\n\r\n* Add pixel_mask\r\n\r\n* Add tests for ViltFeatureExtractor\r\n\r\n* Improve tests\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning to conversion script\r\n\r\n* Minor fixes\r\n\r\n* Add support for image_embeds, update docstrings to markdown\r\n\r\n* Update docs to markdown\r\n\r\n* Improve conversion script\r\n\r\n* Rename ViltForPreTraining to ViltForMaskedLM\r\n\r\n* Improve conversion script\r\n\r\n* Convert docstrings to markdown\r\n\r\n* Fix code example of retrieval model\r\n\r\n* Properly convert masked language model\r\n\r\n* Add integration test for nlvr\r\n\r\n* Fix code quality\r\n\r\n* Apply suggestions from code review\r\n\r\n* Add copied from statements\r\n\r\n* Fix pretrained_config_archive_map\r\n\r\n* Fix docs\r\n\r\n* Add model to README\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Apply more suggestions from code review\r\n\r\n* Make code more readable\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning to the tests\r\n\r\n* Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering\r\n\r\n* Replace pixel_values_2 by single tensor\r\n\r\n* Add hidden_states and attentions\r\n\r\n* Fix one more test\r\n\r\n* Fix all tests\r\n\r\n* Update year\r\n\r\n* Fix rebase issues\r\n\r\n* Fix another rebase issue\r\n\r\n* Remove ViltForPreTraining from auto mapping\r\n\r\n* Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval\r\n\r\n* Make it possible to use BertTokenizerFast in the processor\r\n\r\n* Use BertTokenizerFast by default\r\n\r\n* Rename ViltForNaturalLanguageVisualReasoning, define custom model output\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def save_pretrained(self, save_directory):\n        \n\n        self.feature_extractor.save_pretrained(save_directory)\n        self.tokenizer.save_pretrained(save_directory)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 26,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 5,
        "d_id": 6259,
        "documentation": {
            "docstring": "\n        Save a ViLT feature_extractor object and BERT tokenizer object to the directory `save_directory`, so that it\n        can be re-loaded using the [`~ViltProcessor.from_pretrained`] class method.\n\n        <Tip>\n\n        This class method is simply calling [`~feature_extraction_utils.FeatureExtractionMixin.save_pretrained`] and\n        [`~tokenization_utils_base.PreTrainedTokenizer.save_pretrained`]. Please refer to the docstrings of the methods\n        above for more information.\n\n        </Tip>\n\n        Args:\n            save_directory (`str` or `os.PathLike`):\n                Directory where the feature extractor JSON file and the tokenizer files will be saved (directory will\n                be created if it does not exist).\n        ",
            "n_words": 75,
            "vocab_size": 60,
            "n_whitespaces": 180,
            "language": "en"
        }
    },
    {
        "id": 310821,
        "commit_id": "eb487480381bff3aa87f4d80145b162863dc0a27",
        "repo": "core",
        "path": "tests/components/webostv/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "client_entity_removed_fixture",
        "commit_message": "Add webostv 100% tests coverage for init (#64801)",
        "code": "def client_entity_removed_fixture(hass):\n    \n    with patch(\n        \"homeassistant.components.webostv.WebOsClient\", autospec=True\n    ) as mock_client_class:\n        client = mock_client_class.return_value\n        client.hello_info = {\"deviceUUID\": \"some-fake-uuid\"}\n        client.connected = False\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 56,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 64,
        "n_ast_nodes": 70,
        "n_identifiers": 9,
        "d_id": 109493,
        "documentation": {
            "docstring": "Patch of client library, entity removed waiting for connect.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 128960,
        "commit_id": "8cc268096cb79ededff67b90806b4e4d996ca775",
        "repo": "ray",
        "path": "python/ray/tests/test_multi_node_3.py",
        "file_name": "test_multi_node_3.py",
        "fun_name": "test_calling_start_ray_head",
        "commit_message": "[GCS][Bootstrap 3/n] Refactor to support GCS bootstrap (#21295)\n\nThis PR refactors several components to support switching to GCS address bootstrapping later:\r\n- Treat address from `ray.init()` and `ray` CLI as bootstrap address instead of assuming it is Redis address.\r\n- Ray client servers support `--address` flag instead of `--redis-address`.\r\n- A few other miscellaneous cleanup.\r\n\r\nAlso, add a test for starting non-head node with `ray start`.",
        "code": "def test_calling_start_ray_head(call_ray_stop_only):\n\n    # Test that we can call ray start with various command line\n    # parameters.\n\n    # Test starting Ray with a redis port specified.\n    check_call_ray([\"start\", \"--head\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with a node IP address specified.\n    check_call_ray(\n        [\"start\", \"--head\", \"--node-ip-address\", \"127.0.0.1\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with a system config parameter set.\n    check_call_ray([\n        \"start\", \"--head\", \"--system-config\",\n        \"{\\\"metrics_report_interval_ms\\\":100}\", \"--port\", \"0\"\n    ])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with the object manager and node manager ports\n    # specified.\n    check_call_ray([\n        \"start\", \"--head\", \"--object-manager-port\", \"22345\",\n        \"--node-manager-port\", \"54321\", \"--port\", \"0\"\n    ])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with the worker port range specified.\n    check_call_ray([\n        \"start\", \"--head\", \"--min-worker-port\", \"51000\", \"--max-worker-port\",\n        \"51050\", \"--port\", \"0\"\n    ])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with a worker port list.\n    check_call_ray([\"start\", \"--head\", \"--worker-port-list\", \"10002,10003\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with a non-int in the worker port list.\n    with pytest.raises(subprocess.CalledProcessError):\n        check_call_ray([\"start\", \"--head\", \"--worker-port-list\", \"10002,a\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with an invalid port in the worker port list.\n    with pytest.raises(subprocess.CalledProcessError):\n        check_call_ray([\"start\", \"--head\", \"--worker-port-list\", \"100\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with the number of CPUs specified.\n    check_call_ray([\"start\", \"--head\", \"--num-cpus\", \"2\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with the number of GPUs specified.\n    check_call_ray([\"start\", \"--head\", \"--num-gpus\", \"100\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with redis shard ports specified.\n    check_call_ray([\n        \"start\", \"--head\", \"--redis-shard-ports\", \"6380,6381,6382\", \"--port\",\n        \"0\"\n    ])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with all arguments specified.\n    check_call_ray([\n        \"start\", \"--head\", \"--redis-shard-ports\", \"6380,6381,6382\",\n        \"--object-manager-port\", \"22345\", \"--num-cpus\", \"2\", \"--num-gpus\", \"0\",\n        \"--resources\", \"{\\\"Custom\\\": 1}\", \"--port\", \"0\"\n    ])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with invalid external address.\n    # It will fall back to creating a new one.\n    check_call_ray(\n        [\"start\", \"--head\", \"--address\", \"127.0.0.1:6379\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n\n    # Test starting Ray with RAY_REDIS_ADDRESS env.\n    os.environ[\"RAY_REDIS_ADDRESS\"] = \"127.0.0.1:6379\"\n    check_call_ray([\"start\", \"--head\", \"--port\", \"0\"])\n    check_call_ray([\"stop\"])\n    del os.environ[\"RAY_REDIS_ADDRESS\"]\n\n    # Test --block. Killing a child process should cause the command to exit.\n    blocked = subprocess.Popen(\n        [\"ray\", \"start\", \"--head\", \"--block\", \"--port\", \"0\"])\n\n    blocked.poll()\n    assert blocked.returncode is None\n    # Make sure ray cluster is up\n    run_string_as_driver()\n\n    # Make sure ray cluster is up\n    run_string_as_driver()\n\n    kill_process_by_name(\"raylet\", SIGKILL=True)\n    wait_for_children_of_pid_to_exit(blocked.pid, timeout=30)\n    blocked.wait()\n    assert blocked.returncode != 0, \"ray start shouldn't return 0 on bad exit\"\n\n    # Test --block. Killing the command should clean up all child processes.\n    blocked = subprocess.Popen(\n        [\"ray\", \"start\", \"--head\", \"--block\", \"--port\", \"0\"])\n    blocked.poll()\n    assert blocked.returncode is None\n\n    wait_for_children_of_pid(blocked.pid, num_children=7, timeout=30)\n\n    blocked.terminate()\n    wait_for_children_of_pid_to_exit(blocked.pid, timeout=30)\n    blocked.wait()\n    assert blocked.returncode != 0, \"ray start shouldn't return 0 on bad exit\"\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 732,
        "n_words": 392,
        "vocab_size": 143,
        "complexity": 1,
        "nloc": 88,
        "token_counts": 495,
        "n_ast_nodes": 970,
        "n_identifiers": 23,
        "d_id": 28858,
        "documentation": {
            "docstring": "\nimport ray\nfrom time import sleep\nfor i in range(0, 5):\n    try:\n        ray.init(address='auto')\n        break\n    except:\n        sleep(1)\n\nimport ray\nfrom time import sleep\nfor i in range(0, 5):\n    try:\n        ray.init(address='auto')\n        break\n    except:\n        sleep(1)\n",
            "n_words": 32,
            "vocab_size": 15,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 46402,
        "commit_id": "f06b3955b1d937138fb38021a6a373b94ae8f9e8",
        "repo": "airflow",
        "path": "airflow/utils/db.py",
        "file_name": "db.py",
        "fun_name": "check_task_fail_for_duplicates",
        "commit_message": "Add map_index and run_id to TaskFail (#22260)\n\nTaskFail entities always belong to a TaskInstance.  The PK for TaskInstance has changed, so we need to update TaskFail to have the new columns.",
        "code": "def check_task_fail_for_duplicates(session):\n    \n    metadata = reflect_tables([TaskFail], session)\n    task_fail = metadata.tables.get(TaskFail.__tablename__)  # type: ignore\n    if task_fail is None:  # table not there\n        return\n    if \"run_id\" in task_fail.columns:  # upgrade already applied\n        return\n    yield from check_table_for_duplicates(\n        table_name=task_fail.name,\n        uniqueness=['dag_id', 'task_id', 'execution_date'],\n        session=session,\n    )\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 98,
        "n_words": 39,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 67,
        "n_ast_nodes": 115,
        "n_identifiers": 14,
        "d_id": 8873,
        "documentation": {
            "docstring": "Check that there are no duplicates in the task_fail table before creating FK",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 154500,
        "commit_id": "d6d503ac7c3028d871c34d9e99e925ddb0746df6",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "add_to_apply_calls",
        "commit_message": "FIX-#4597: Refactor Partition handling of func, args, kwargs (#4715)\n\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Jonathan Shi <jhshi@ponder.io>",
        "code": "def add_to_apply_calls(self, func, length=None, width=None, *args, **kwargs):\n        \n        return cuDFOnRayDataframePartition(\n            self.gpu_manager,\n            self.apply(func, *args, **kwargs),\n            length=length,\n            width=width,\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 81,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 51,
        "n_ast_nodes": 73,
        "n_identifiers": 10,
        "d_id": 36023,
        "documentation": {
            "docstring": "\n        Apply `func` to this partition and create new.\n\n        Parameters\n        ----------\n        func : callable\n            A function to apply.\n        length : ray.ObjectRef or int, optional\n            Length, or reference to length, of wrapped ``pandas.DataFrame``.\n        width : ray.ObjectRef or int, optional\n            Width, or reference to width, of wrapped ``pandas.DataFrame``.\n        *args : tuple\n            Positional arguments to be passed in `func`.\n        **kwargs : dict\n            Additional keywords arguments to be passed in `func`.\n\n        Returns\n        -------\n        cuDFOnRayDataframePartition\n            New partition based on result of `func`.\n\n        Notes\n        -----\n        We eagerly schedule the apply `func` and produce a new ``cuDFOnRayDataframePartition``.\n        ",
            "n_words": 89,
            "vocab_size": 60,
            "n_whitespaces": 261,
            "language": "en"
        }
    },
    {
        "id": 259112,
        "commit_id": "279388d9ed2ea83194dd45a2d78161be30b43aa7",
        "repo": "scikit-learn",
        "path": "sklearn/compose/_column_transformer.py",
        "file_name": "_column_transformer.py",
        "fun_name": "get_feature_names_out",
        "commit_message": "DOC Improve get_feature_names_out docstrings (#22718)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def get_feature_names_out(self, input_features=None):\n        \n        check_is_fitted(self)\n        input_features = _check_feature_names_in(self, input_features)\n\n        # List of tuples (name, feature_names_out)\n        transformer_with_feature_names_out = []\n        for name, trans, column, _ in self._iter(fitted=True):\n            feature_names_out = self._get_feature_name_out_for_transformer(\n                name, trans, column, input_features\n            )\n            if feature_names_out is None:\n                continue\n            transformer_with_feature_names_out.append((name, feature_names_out))\n\n        if not transformer_with_feature_names_out:\n            # No feature names\n            return np.array([], dtype=object)\n\n        if self.verbose_feature_names_out:\n            # Prefix the feature names out with the transformers name\n            names = list(\n                chain.from_iterable(\n                    (f\"{name}__{i}\" for i in feature_names_out)\n                    for name, feature_names_out in transformer_with_feature_names_out\n                )\n            )\n            return np.asarray(names, dtype=object)\n\n        # verbose_feature_names_out is False\n        # Check that names are all unique without a prefix\n        feature_names_count = Counter(\n            chain.from_iterable(s for _, s in transformer_with_feature_names_out)\n        )\n        top_6_overlap = [\n            name for name, count in feature_names_count.most_common(6) if count > 1\n        ]\n        top_6_overlap.sort()\n        if top_6_overlap:\n            if len(top_6_overlap) == 6:\n                # There are more than 5 overlapping names, we only show the 5\n                # of the feature names\n                names_repr = str(top_6_overlap[:5])[:-1] + \", ...]\"\n            else:\n                names_repr = str(top_6_overlap)\n            raise ValueError(\n                f\"Output feature names: {names_repr} are not unique. Please set \"\n                \"verbose_feature_names_out=True to add prefixes to feature names\"\n            )\n\n        return np.concatenate(\n            [name for _, name in transformer_with_feature_names_out],\n        )\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 683,
        "n_words": 182,
        "vocab_size": 113,
        "complexity": 13,
        "nloc": 40,
        "token_counts": 231,
        "n_ast_nodes": 380,
        "n_identifiers": 38,
        "d_id": 75571,
        "documentation": {
            "docstring": "Get output feature names for transformation.\n\n        Parameters\n        ----------\n        input_features : array-like of str or None, default=None\n            Input features.\n\n            - If `input_features` is `None`, then `feature_names_in_` is\n              used as feature names in. If `feature_names_in_` is not defined,\n              then the following input feature names are generated:\n              `[\"x0\", \"x1\", ..., \"x(n_features_in_ - 1)\"]`.\n            - If `input_features` is an array-like, then `input_features` must\n              match `feature_names_in_` if `feature_names_in_` is defined.\n\n        Returns\n        -------\n        feature_names_out : ndarray of str objects\n            Transformed feature names.\n        ",
            "n_words": 76,
            "vocab_size": 53,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 75890,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/search/utils.py",
        "file_name": "utils.py",
        "fun_name": "parse_query_string",
        "commit_message": "Reformat with black",
        "code": "def parse_query_string(query_string, operator=None, zero_terms=MATCH_NONE):\n    \n    filters, query_string = separate_filters_from_query(query_string)\n\n    is_phrase = False\n    tokens = []\n    for part in query_string.split('\"'):\n        part = part.strip()\n\n        if part:\n            if is_phrase:\n                tokens.append(Phrase(part))\n            else:\n                tokens.append(\n                    PlainText(part, operator=operator or PlainText.DEFAULT_OPERATOR)\n                )\n\n        is_phrase = not is_phrase\n\n    if tokens:\n        if operator == \"or\":\n            search_query = OR(tokens)\n        else:\n            search_query = AND(tokens)\n    else:\n        search_query = zero_terms\n\n    return filters, search_query\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 231,
        "n_words": 57,
        "vocab_size": 38,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 115,
        "n_ast_nodes": 193,
        "n_identifiers": 19,
        "d_id": 16438,
        "documentation": {
            "docstring": "\n    This takes a query string typed in by a user and extracts the following:\n\n     - Quoted terms (for phrase search)\n     - Filters\n\n    For example, the following query:\n\n      `hello \"this is a phrase\" live:true` would be parsed into:\n\n    filters: {'live': 'true'}\n    tokens: And([PlainText('hello'), Phrase('this is a phrase')])\n    ",
            "n_words": 46,
            "vocab_size": 40,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 269080,
        "commit_id": "9c24fc4057303172ad977cebd626da2b7adb63d4",
        "repo": "keras",
        "path": "keras/applications/resnet_rs.py",
        "file_name": "resnet_rs.py",
        "fun_name": "preprocess_input",
        "commit_message": "Add ResNet-RS to keras.applications - code refactor",
        "code": "def preprocess_input(x, data_format=None):\n    \n    return x\n\n\n@keras_export(\"keras.applications.resnet_rs.decode_predictions\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.applications.resnet_rs.decode_predictions\")",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 11,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 32,
        "n_identifiers": 4,
        "d_id": 79882,
        "documentation": {
            "docstring": "A placeholder method for backward compatibility.\n\n    The preprocessing logic has been included in the ResnetRS model\n    implementation. Users are no longer required to call this method to normalize\n    the input data. This method does nothing and only kept as a placeholder to\n    align the API surface between old and new version of model.\n\n    Args:\n      x: A floating point `numpy.array` or a `tf.Tensor`.\n      data_format: Optional data format of the image tensor/array. Defaults to\n        None, in which case the global setting\n        `tf.keras.backend.image_data_format()` is used (unless you changed it, it\n        defaults to \"channels_last\").{mode}\n\n    Returns:\n      Unchanged `numpy.array` or `tf.Tensor`.\n    ",
            "n_words": 95,
            "vocab_size": 76,
            "n_whitespaces": 152,
            "language": "en"
        }
    },
    {
        "id": 67329,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/selling/doctype/customer/customer.py",
        "file_name": "customer.py",
        "fun_name": "check_credit_limit",
        "commit_message": "style: format code with black",
        "code": "def check_credit_limit(customer, company, ignore_outstanding_sales_order=False, extra_amount=0):\n\tcredit_limit = get_credit_limit(customer, company)\n\tif not credit_limit:\n\t\treturn\n\n\tcustomer_outstanding = get_customer_outstanding(customer, company, ignore_outstanding_sales_order)\n\tif extra_amount > 0:\n\t\tcustomer_outstanding += flt(extra_amount)\n\n\tif credit_limit > 0 and flt(customer_outstanding) > credit_limit:\n\t\tmsgprint(\n\t\t\t_(\"Credit limit has been crossed for customer {0} ({1}/{2})\").format(\n\t\t\t\tcustomer, customer_outstanding, credit_limit\n\t\t\t)\n\t\t)\n\n\t\t# If not authorized person raise exception\n\t\tcredit_controller_role = frappe.db.get_single_value(\"Accounts Settings\", \"credit_controller\")\n\t\tif not credit_controller_role or credit_controller_role not in frappe.get_roles():\n\t\t\t# form a list of emails for the credit controller users\n\t\t\tcredit_controller_users = get_users_with_role(credit_controller_role or \"Sales Master Manager\")\n\n\t\t\t# form a list of emails and names to show to the user\n\t\t\tcredit_controller_users_formatted = [\n\t\t\t\tget_formatted_email(user).replace(\"<\", \"(\").replace(\">\", \")\")\n\t\t\t\tfor user in credit_controller_users\n\t\t\t]\n\t\t\tif not credit_controller_users_formatted:\n\t\t\t\tfrappe.throw(\n\t\t\t\t\t_(\"Please contact your administrator to extend the credit limits for {0}.\").format(customer)\n\t\t\t\t)\n\n\t\t\tmessage = .format(\n\t\t\t\tcustomer, \"<li>\".join(credit_controller_users_formatted)\n\t\t\t)\n\n\t\t\t# if the current user does not have permissions to override credit limit,\n\t\t\t# prompt them to send out an email to the controller users\n\t\t\tfrappe.msgprint(\n\t\t\t\tmessage,\n\t\t\t\ttitle=\"Notify\",\n\t\t\t\traise_exception=1,\n\t\t\t\tprimary_action={\n\t\t\t\t\t\"label\": \"Send Email\",\n\t\t\t\t\t\"server_action\": \"erpnext.selling.doctype.customer.customer.send_emails\",\n\t\t\t\t\t\"args\": {\n\t\t\t\t\t\t\"customer\": customer,\n\t\t\t\t\t\t\"customer_outstanding\": customer_outstanding,\n\t\t\t\t\t\t\"credit_limit\": credit_limit,\n\t\t\t\t\t\t\"credit_controller_users_list\": credit_controller_users,\n\t\t\t\t\t},\n\t\t\t\t},\n\t\t\t)\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 18,
        "n_whitespaces": 133,
        "n_words": 181,
        "vocab_size": 118,
        "complexity": 10,
        "nloc": 43,
        "token_counts": 218,
        "n_ast_nodes": 383,
        "n_identifiers": 31,
        "d_id": 14497,
        "documentation": {
            "docstring": "Please contact any of the following users to extend the credit limits for {0}:\n\t\t\t\t<br><br><ul><li>{1}</li></ul>",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 215192,
        "commit_id": "637e74f0f2e80723fa30eb8f83a86af440c6ba4e",
        "repo": "salt",
        "path": "tests/unit/grains/test_lvm.py",
        "file_name": "test_lvm.py",
        "fun_name": "test__linux_lvm_no_logical_volumes",
        "commit_message": "Uses only command's stdout to populate lvm grain",
        "code": "def test__linux_lvm_no_logical_volumes(self):\n        \n\n        vgs_out = {\"pid\": 123, \"retcode\": 0, \"stdout\": \"  vg00\\n  vg01\", \"stderr\": \"\"}\n        lvs_out = {\"pid\": 456, \"retcode\": 0, \"stdout\": \"\", \"stderr\": \"\"}\n        cmd_out = MagicMock(autospec=True, side_effect=[vgs_out, lvs_out, lvs_out])\n\n        patch_which = patch(\n            \"salt.utils.path.which\", autospec=True, return_value=\"/usr/sbin/lvm\"\n        )\n        patch_cmd_lvm = patch.dict(lvm.__salt__, {\"cmd.run_all\": cmd_out})\n        with patch_which, patch_cmd_lvm:\n            ret = lvm._linux_lvm()\n\n        assert ret == {\"lvm\": {\"vg00\": [], \"vg01\": []}}, ret\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 144,
        "n_words": 57,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 124,
        "n_ast_nodes": 222,
        "n_identifiers": 17,
        "d_id": 53878,
        "documentation": {
            "docstring": "\n        Test grains._linux_lvm, lvm is installed, volume groups created but\n        no logical volumes present.\n        Should return a dictionary only with the header\n        ",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 120148,
        "commit_id": "4354f355a858e6e99a0853dde90812bf8e846ee5",
        "repo": "jax",
        "path": "jax/interpreters/xla.py",
        "file_name": "xla.py",
        "fun_name": "jaxpr_collectives",
        "commit_message": "prototyping dynamic shapes\n\nCo-authored-by: Dougal Maclaurin <dougalm@google.com>",
        "code": "def jaxpr_collectives(jaxpr):\n  \n  for eqn in jaxpr.eqns:\n    if eqn.primitive in _collective_primitives:\n      yield eqn.primitive\n  for subjaxpr in core.subjaxprs(jaxpr): yield from jaxpr_collectives(subjaxpr)\n\n\n### xla_call underlying jit\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 33,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 40,
        "n_ast_nodes": 67,
        "n_identifiers": 9,
        "d_id": 26784,
        "documentation": {
            "docstring": "Generates all the collective primitives anywhere inside a Jaxpr.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 102071,
        "commit_id": "48c886b3dce3d3117ad16edaf35c8abd28dc51f5",
        "repo": "faceswap",
        "path": "lib/sysinfo.py",
        "file_name": "sysinfo.py",
        "fun_name": "_conda_version",
        "commit_message": "Allow decoding errors",
        "code": "def _conda_version(self):\n        \n        if not self._is_conda:\n            return \"N/A\"\n        with Popen(\"conda --version\", shell=True, stdout=PIPE, stderr=PIPE) as conda:\n            stdout, stderr = conda.communicate()\n        if stderr:\n            return \"Conda is used, but version not found\"\n        version = stdout.decode(self._encoding, errors=\"replace\").splitlines()\n        return \"\\n\".join(version)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 110,
        "n_words": 35,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 73,
        "n_ast_nodes": 130,
        "n_identifiers": 16,
        "d_id": 21436,
        "documentation": {
            "docstring": " str: The installed version of Conda, or `N/A` if Conda is not installed. ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 122412,
        "commit_id": "2416d154355f19e77b5c1ddf1de1f8552e4a98ad",
        "repo": "jax",
        "path": "jax/_src/third_party/numpy/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_multi_dot",
        "commit_message": "Call _check_arraylike for jnp.linalg & jnp.fft functions",
        "code": "def _multi_dot(arrays, order, i, j, precision):\n  \n  if i == j:\n    return arrays[i]\n  else:\n    return jnp.dot(_multi_dot(arrays, order, i, order[i, j], precision),\n                   _multi_dot(arrays, order, order[i, j] + 1, j, precision),\n                   precision=precision)\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 74,
        "n_words": 29,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 73,
        "n_ast_nodes": 99,
        "n_identifiers": 8,
        "d_id": 27181,
        "documentation": {
            "docstring": "Actually do the multiplication with the given order.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 304497,
        "commit_id": "8b1713a691bd0c90824261be785f1998ad89f66f",
        "repo": "core",
        "path": "homeassistant/components/lutron_caseta/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "unique_id",
        "commit_message": "Add support for non-serialized devices (light, switch, cover, fan in RA3 Zones) (#75323)\n\nCo-authored-by: J. Nick Koston <nick@koston.org>",
        "code": "def unique_id(self):\n        \n        if self.serial is None:\n            return f\"{self._bridge_unique_id}_{self.device_id}\"\n        return super().unique_id\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 22,
        "n_ast_nodes": 53,
        "n_identifiers": 6,
        "d_id": 103304,
        "documentation": {
            "docstring": "Return a unique identifier if serial number is None.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 196758,
        "commit_id": "ad766d1c02943e86f50559abfd0c72e582c9ca6a",
        "repo": "sympy",
        "path": "sympy/assumptions/assume.py",
        "file_name": "assume.py",
        "fun_name": "eval",
        "commit_message": "Update the AskHandler deprecation warnings\n\nn.b., the issue number in the original warning message was wrong. It should\nhave been #20837.",
        "code": "def eval(self, args, assumptions=True):\n        # Support for deprecated design\n        # When old design is removed, this will always return None\n        sympy_deprecation_warning(\n            ,\n            deprecated_since_version=\"1.8\",\n            active_deprecations_target='deprecated-askhandler',\n            stacklevel=5,\n        )\n        expr, = args\n        res, _res = None, None\n        mro = inspect.getmro(type(expr))\n        for handler in self.handlers:\n            cls = get_class(handler)\n            for subclass in mro:\n                eval_ = getattr(cls, subclass.__name__, None)\n                if eval_ is None:\n                    continue\n                res = eval_(expr, assumptions)\n                # Do not stop if value returned is None\n                # Try to check for higher classes\n                if res is None:\n                    continue\n                if _res is None:\n                    _res = res\n                else:\n                    # only check consistency if both resolutors have concluded\n                    if _res != res:\n                        raise ValueError('incompatible resolutors')\n                break\n        return res\n\n\n@contextmanager",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "@contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 491,
        "n_words": 111,
        "vocab_size": 73,
        "complexity": 7,
        "nloc": 30,
        "token_counts": 123,
        "n_ast_nodes": 206,
        "n_identifiers": 25,
        "d_id": 48154,
        "documentation": {
            "docstring": "\n            The AskHandler system is deprecated. Evaluating UndefinedPredicate\n            objects should be replaced with the multipledispatch handler of\n            Predicate.\n            ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 109967,
        "commit_id": "6c88dd95935bcc5125ebaa81cd8202c347f3941c",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axis.py",
        "file_name": "axis.py",
        "fun_name": "_translate_tick_params",
        "commit_message": "Add translation from internal kw to ones in tick_params()",
        "code": "def _translate_tick_params(kw, reverse=False):\n        \n        kw_ = {**kw}\n\n        # The following lists may be moved to a more accessible location.\n        allowed_keys = [\n            'size', 'width', 'color', 'tickdir', 'pad',\n            'labelsize', 'labelcolor', 'zorder', 'gridOn',\n            'tick1On', 'tick2On', 'label1On', 'label2On',\n            'length', 'direction', 'left', 'bottom', 'right', 'top',\n            'labelleft', 'labelbottom', 'labelright', 'labeltop',\n            'labelrotation',\n            *_gridline_param_names]\n\n        keymap = {\n            # tick_params key -> axis key\n            'length': 'size',\n            'direction': 'tickdir',\n            'rotation': 'labelrotation',\n            'left': 'tick1On',\n            'bottom': 'tick1On',\n            'right': 'tick2On',\n            'top': 'tick2On',\n            'labelleft': 'label1On',\n            'labelbottom': 'label1On',\n            'labelright': 'label2On',\n            'labeltop': 'label2On',\n        }\n        if reverse:\n            kwtrans = {\n                oldkey: kw_.pop(newkey)\n                for oldkey, newkey in keymap.items() if newkey in kw_\n            }\n        else:\n            kwtrans = {\n                newkey: kw_.pop(oldkey)\n                for oldkey, newkey in keymap.items() if oldkey in kw_\n            }\n        if 'colors' in kw_:\n            c = kw_.pop('colors')\n            kwtrans['color'] = c\n            kwtrans['labelcolor'] = c\n        # Maybe move the checking up to the caller of this method.\n        for key in kw_:\n            if key not in allowed_keys:\n                raise ValueError(\n                    \"keyword %s is not recognized; valid keywords are %s\"\n                    % (key, allowed_keys))\n        kwtrans.update(kw_)\n        return kwtrans\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 663,
        "n_words": 162,
        "vocab_size": 109,
        "complexity": 9,
        "nloc": 44,
        "token_counts": 230,
        "n_ast_nodes": 426,
        "n_identifiers": 16,
        "d_id": 23860,
        "documentation": {
            "docstring": "\n        Translate the kwargs supported by `.Axis.set_tick_params` to kwargs\n        supported by `.Tick._apply_params`.\n\n        In particular, this maps axis specific names like 'top', 'left'\n        to the generic tick1, tick2 logic of the axis. Additionally, there\n        are some other name translations.\n\n        Returns a new dict of translated kwargs.\n\n        Note: Use reverse=True to translate from those supported by\n        `.Tick._apply_params` back to those supported by\n        `.Axis.set_tick_params`.\n        ",
            "n_words": 60,
            "vocab_size": 46,
            "n_whitespaces": 131,
            "language": "en"
        }
    },
    {
        "id": 205832,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/sql/compiler.py",
        "file_name": "compiler.py",
        "fun_name": "get_order_by",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_order_by(self):\n        \n        result = []\n        seen = set()\n\n        for expr, is_ref in self._order_by_pairs():\n            resolved = expr.resolve_expression(self.query, allow_joins=True, reuse=None)\n            if self.query.combinator and self.select:\n                src = resolved.get_source_expressions()[0]\n                expr_src = expr.get_source_expressions()[0]\n                # Relabel order by columns to raw numbers if this is a combined\n                # query; necessary since the columns can't be referenced by the\n                # fully qualified name and the simple column names may collide.\n                for idx, (sel_expr, _, col_alias) in enumerate(self.select):\n                    if is_ref and col_alias == src.refs:\n                        src = src.source\n                    elif col_alias and not (\n                        isinstance(expr_src, F) and col_alias == expr_src.name\n                    ):\n                        continue\n                    if src == sel_expr:\n                        resolved.set_source_expressions([RawSQL(\"%d\" % (idx + 1), ())])\n                        break\n                else:\n                    if col_alias:\n                        raise DatabaseError(\n                            \"ORDER BY term does not match any column in the result set.\"\n                        )\n                    # Add column used in ORDER BY clause to the selected\n                    # columns and to each combined query.\n                    order_by_idx = len(self.query.select) + 1\n                    col_name = f\"__orderbycol{order_by_idx}\"\n                    for q in self.query.combined_queries:\n                        q.add_annotation(expr_src, col_name)\n                    self.query.add_select_col(resolved, col_name)\n                    resolved.set_source_expressions([RawSQL(f\"{order_by_idx}\", ())])\n            sql, params = self.compile(resolved)\n            # Don't add the same column twice, but the order direction is\n            # not taken into account so we strip it. When this entire method\n            # is refactored into expressions, then we can check each part as we\n            # generate it.\n            without_ordering = self.ordering_parts.search(sql)[1]\n            params_hash = make_hashable(params)\n            if (without_ordering, params_hash) in seen:\n                continue\n            seen.add((without_ordering, params_hash))\n            result.append((resolved, (sql, params, is_ref)))\n        return result\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 948,
        "n_words": 222,
        "vocab_size": 147,
        "complexity": 14,
        "nloc": 37,
        "token_counts": 288,
        "n_ast_nodes": 469,
        "n_identifiers": 48,
        "d_id": 51231,
        "documentation": {
            "docstring": "\n        Return a list of 2-tuples of the form (expr, (sql, params, is_ref)) for\n        the ORDER BY clause.\n\n        The order_by clause can alter the select clause (for example it can add\n        aliases to clauses that do not yet have one, or it can add totally new\n        select clauses).\n        ",
            "n_words": 47,
            "vocab_size": 38,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 58817,
        "commit_id": "6ec2dcd6d424da1d069b2ecf378b4e4ddfdd43e3",
        "repo": "prefect",
        "path": "src/prefect/orion/database/configurations.py",
        "file_name": "configurations.py",
        "fun_name": "engine",
        "commit_message": "Resolve SQLite param ordering issue",
        "code": "async def engine(self) -> AsyncEngine:\n        \n\n        if sqlite3.sqlite_version_info < self.MIN_SQLITE_VERSION:\n            required = \".\".join(str(v) for v in self.MIN_SQLITE_VERSION)\n            raise RuntimeError(\n                f\"Orion requires sqlite >= {required} but we found version \"\n                f\"{sqlite3.sqlite_version}\"\n            )\n\n        kwargs = {}\n\n        loop = get_running_loop()\n\n        cache_key = (\n            loop,\n            self.connection_url,\n            self.echo,\n            self.timeout,\n        )\n        if cache_key not in self.ENGINES:\n\n            # apply database timeout\n            if self.timeout is not None:\n                kwargs[\"connect_args\"] = dict(timeout=self.timeout)\n\n            # use `named` paramstyle because of edge cases where `qmark`\n            # results in params being sent in the wrong positional order\n            # https://github.com/PrefectHQ/prefect/pull/6645\n            kwargs[\"paramstyle\"] = \"named\"\n\n            # ensure a long-lasting pool is used with in-memory databases\n            # because they disappear when the last connection closes\n            if \":memory:\" in self.connection_url:\n                kwargs.update(poolclass=sa.pool.SingletonThreadPool)\n\n            engine = create_async_engine(self.connection_url, echo=self.echo, **kwargs)\n            sa.event.listen(engine.sync_engine, \"engine_connect\", self.setup_sqlite)\n\n            self.ENGINES[cache_key] = engine\n            await self.schedule_engine_disposal(cache_key)\n        return self.ENGINES[cache_key]\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 462,
        "n_words": 126,
        "vocab_size": 99,
        "complexity": 6,
        "nloc": 39,
        "token_counts": 178,
        "n_ast_nodes": 305,
        "n_identifiers": 32,
        "d_id": 11816,
        "documentation": {
            "docstring": "Retrieves an async SQLAlchemy engine.\n\n        Args:\n            connection_url (str, optional): The database connection string.\n                Defaults to self.connection_url\n            echo (bool, optional): Whether to echo SQL sent\n                to the database. Defaults to self.echo\n            timeout (float, optional): The database statement timeout, in seconds.\n                Defaults to self.timeout\n\n        Returns:\n            AsyncEngine: a SQLAlchemy engine\n        ",
            "n_words": 47,
            "vocab_size": 35,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 321337,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/completion/test_completiondelegate.py",
        "file_name": "test_completiondelegate.py",
        "fun_name": "test_highlighted",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_highlighted(qtbot):\n    \n    doc = QTextDocument()\n    completiondelegate._Highlighter(doc, 'Hello', Qt.GlobalColor.red)\n    doc.setPlainText('Hello World')\n\n    # Needed so the highlighting actually works.\n    edit = QTextEdit()\n    qtbot.add_widget(edit)\n    edit.setDocument(doc)\n\n    colors = [f.foreground().color() for f in doc.allFormats()]\n    assert QColor('red') in colors\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 63,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 76,
        "n_ast_nodes": 133,
        "n_identifiers": 20,
        "d_id": 117670,
        "documentation": {
            "docstring": "Make sure highlighting works.\n\n    Note that with Qt > 5.12.1 we need to call setPlainText *after*\n    creating the highlighter for highlighting to work. Ideally, we'd test\n    whether CompletionItemDelegate._get_textdoc() works properly, but testing\n    that is kind of hard, so we just test it in isolation here.\n    ",
            "n_words": 45,
            "vocab_size": 40,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 197296,
        "commit_id": "65be461082dda54c8748922f9c29a19af1279fe1",
        "repo": "sympy",
        "path": "sympy/codegen/ast.py",
        "file_name": "ast.py",
        "fun_name": "topological_sort",
        "commit_message": "Remove abbreviations in documentation",
        "code": "def topological_sort(cls, assignments):\n        \n\n        if not all(isinstance(i, Assignment) for i in assignments):\n            # Will support more things later\n            raise NotImplementedError(\"CodeBlock.topological_sort only supports Assignments\")\n\n        if any(isinstance(i, AugmentedAssignment) for i in assignments):\n            raise NotImplementedError(\"CodeBlock.topological_sort does not yet work with AugmentedAssignments\")\n\n        # Create a graph where the nodes are assignments and there is a directed edge\n        # between nodes that use a variable and nodes that assign that\n        # variable, like\n\n        # [(x := 1, y := x + 1), (x := 1, z := y + z), (y := x + 1, z := y + z)]\n\n        # If we then topologically sort these nodes, they will be in\n        # assignment order, like\n\n        # x := 1\n        # y := x + 1\n        # z := y + z\n\n        # A = The nodes\n        #\n        # enumerate keeps nodes in the same order they are already in if\n        # possible. It will also allow us to handle duplicate assignments to\n        # the same variable when those are implemented.\n        A = list(enumerate(assignments))\n\n        # var_map = {variable: [nodes for which this variable is assigned to]}\n        # like {x: [(1, x := y + z), (4, x := 2 * w)], ...}\n        var_map = defaultdict(list)\n        for node in A:\n            i, a = node\n            var_map[a.lhs].append(node)\n\n        # E = Edges in the graph\n        E = []\n        for dst_node in A:\n            i, a = dst_node\n            for s in a.rhs.free_symbols:\n                for src_node in var_map[s]:\n                    E.append((src_node, dst_node))\n\n        ordered_assignments = topological_sort([A, E])\n\n        # De-enumerate the result\n        return cls(*[a for i, a in ordered_assignments])\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 558,
        "n_words": 251,
        "vocab_size": 130,
        "complexity": 10,
        "nloc": 18,
        "token_counts": 150,
        "n_ast_nodes": 254,
        "n_identifiers": 26,
        "d_id": 48439,
        "documentation": {
            "docstring": "\n        Return a CodeBlock with topologically sorted assignments so that\n        variables are assigned before they are used.\n\n        Examples\n        ========\n\n        The existing order of assignments is preserved as much as possible.\n\n        This function assumes that variables are assigned to only once.\n\n        This is a class constructor so that the default constructor for\n        CodeBlock can error when variables are used before they are assigned.\n\n        Examples\n        ========\n\n        >>> from sympy import symbols\n        >>> from sympy.codegen.ast import CodeBlock, Assignment\n        >>> x, y, z = symbols('x y z')\n\n        >>> assignments = [\n        ...     Assignment(x, y + z),\n        ...     Assignment(y, z + 1),\n        ...     Assignment(z, 2),\n        ... ]\n        >>> CodeBlock.topological_sort(assignments)\n        CodeBlock(\n            Assignment(z, 2),\n            Assignment(y, z + 1),\n            Assignment(x, y + z)\n        )\n\n        ",
            "n_words": 115,
            "vocab_size": 71,
            "n_whitespaces": 315,
            "language": "en"
        }
    },
    {
        "id": 272918,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/layers/preprocessing/discretization.py",
        "file_name": "discretization.py",
        "fun_name": "adapt",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def adapt(self, data, batch_size=None, steps=None):\n        \n        super().adapt(data, batch_size=batch_size, steps=steps)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 32,
        "n_ast_nodes": 49,
        "n_identifiers": 6,
        "d_id": 81075,
        "documentation": {
            "docstring": "Computes bin boundaries from quantiles in a input dataset.\n\n        Calling `adapt()` on a `Discretization` layer is an alternative to passing\n        in a `bin_boundaries` argument during construction. A `Discretization` layer\n        should always be either adapted over a dataset or passed `bin_boundaries`.\n\n        During `adapt()`, the layer will estimate the quantile boundaries of the\n        input dataset. The number of quantiles can be controlled via the `num_bins`\n        argument, and the error tolerance for quantile boundaries can be controlled\n        via the `epsilon` argument.\n\n        In order to make `Discretization` efficient in any distribution context, the\n        computed boundaries are kept static with respect to any compiled `tf.Graph`s\n        that call the layer. As a consequence, if the layer is adapted a second\n        time, any models using the layer should be re-compiled. For more information\n        see `tf.keras.layers.experimental.preprocessing.PreprocessingLayer.adapt`.\n\n        `adapt()` is meant only as a single machine utility to compute layer state.\n        To analyze a dataset that cannot fit on a single machine, see\n        [Tensorflow Transform](https://www.tensorflow.org/tfx/transform/get_started)\n        for a multi-machine, map-reduce solution.\n\n        Arguments:\n          data: The data to train on. It can be passed either as a\n              `tf.data.Dataset`, or as a numpy array.\n          batch_size: Integer or `None`.\n              Number of samples per state update.\n              If unspecified, `batch_size` will default to 32.\n              Do not specify the `batch_size` if your data is in the\n              form of datasets, generators, or `keras.utils.Sequence` instances\n              (since they generate batches).\n          steps: Integer or `None`.\n              Total number of steps (batches of samples)\n              When training with input tensors such as\n              TensorFlow data tensors, the default `None` is equal to\n              the number of samples in your dataset divided by\n              the batch size, or 1 if that cannot be determined. If x is a\n              `tf.data` dataset, and 'steps' is None, the epoch will run until\n              the input dataset is exhausted. When passing an infinitely\n              repeating dataset, you must specify the `steps` argument. This\n              argument is not supported with array inputs.\n        ",
            "n_words": 305,
            "vocab_size": 175,
            "n_whitespaces": 653,
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    },
    {
        "id": 206617,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/dateparse.py",
        "file_name": "dateparse.py",
        "fun_name": "parse_datetime",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def parse_datetime(value):\n    \n    try:\n        return datetime.datetime.fromisoformat(value)\n    except ValueError:\n        if match := datetime_re.match(value):\n            kw = match.groupdict()\n            kw[\"microsecond\"] = kw[\"microsecond\"] and kw[\"microsecond\"].ljust(6, \"0\")\n            tzinfo = kw.pop(\"tzinfo\")\n            if tzinfo == \"Z\":\n                tzinfo = utc\n            elif tzinfo is not None:\n                offset_mins = int(tzinfo[-2:]) if len(tzinfo) > 3 else 0\n                offset = 60 * int(tzinfo[1:3]) + offset_mins\n                if tzinfo[0] == \"-\":\n                    offset = -offset\n                tzinfo = get_fixed_timezone(offset)\n            kw = {k: int(v) for k, v in kw.items() if v is not None}\n            return datetime.datetime(**kw, tzinfo=tzinfo)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
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        "complexity": 10,
        "nloc": 18,
        "token_counts": 170,
        "n_ast_nodes": 282,
        "n_identifiers": 21,
        "d_id": 51588,
        "documentation": {
            "docstring": "Parse a string and return a datetime.datetime.\n\n    This function supports time zone offsets. When the input contains one,\n    the output uses a timezone with a fixed offset from UTC.\n\n    Raise ValueError if the input is well formatted but not a valid datetime.\n    Return None if the input isn't well formatted.\n    ",
            "n_words": 50,
            "vocab_size": 39,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 218022,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_abc.py",
        "file_name": "_abc.py",
        "fun_name": "create_module",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def create_module(self, spec):\n        \n        # By default, defer to default semantics for the new module.\n        return None\n\n    # We don't define exec_module() here since that would break\n    # hasattr checks we do to support backward compatibility.\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 62,
        "n_words": 35,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 21,
        "n_identifiers": 3,
        "d_id": 55084,
        "documentation": {
            "docstring": "Return a module to initialize and into which to load.\n\n        This method should raise ImportError if anything prevents it\n        from creating a new module.  It may return None to indicate\n        that the spec should create the new module.\n        ",
            "n_words": 38,
            "vocab_size": 31,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 163775,
        "commit_id": "c5ff649b11bd625ca36ad218539badb1c2057668",
        "repo": "pandas",
        "path": "pandas/tests/io/test_user_agent.py",
        "file_name": "test_user_agent.py",
        "fun_name": "responder",
        "commit_message": "CI/TST: Call join on server process test (#45628)",
        "code": "def responder(request):\n    \n    # Find an available port\n    with socket.socket() as sock:\n        sock.bind((\"localhost\", 0))\n        port = sock.getsockname()[1]\n\n    server_process = multiprocessing.Process(\n        target=process_server, args=(request.param, port)\n    )\n    server_process.start()\n    yield port\n    server_process.join(10)\n    server_process.terminate()\n    kill_time = 5\n    wait_time = 0\n    while server_process.is_alive():\n        if wait_time > kill_time:\n            server_process.kill()\n            break\n        else:\n            wait_time += 0.1\n            time.sleep(0.1)\n    server_process.close()\n\n\n@pytest.mark.parametrize(\n    \"responder, read_method, parquet_engine\",\n    [\n        (CSVUserAgentResponder, pd.read_csv, None),\n        (JSONUserAgentResponder, pd.read_json, None),\n        (ParquetPyArrowUserAgentResponder, pd.read_parquet, \"pyarrow\"),\n        pytest.param(\n            ParquetFastParquetUserAgentResponder,\n            pd.read_parquet,\n            \"fastparquet\",\n            # TODO(ArrayManager) fastparquet\n            marks=[\n                td.skip_array_manager_not_yet_implemented,\n                pytest.mark.xfail(PY310, reason=\"fastparquet failing on 3.10\"),\n            ],\n        ),\n        (PickleUserAgentResponder, pd.read_pickle, None),\n        (StataUserAgentResponder, pd.read_stata, None),\n        (GzippedCSVUserAgentResponder, pd.read_csv, None),\n        (GzippedJSONUserAgentResponder, pd.read_json, None),\n    ],\n    indirect=[\"responder\"],\n)",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"responder, read_method, parquet_engine\",\n    [\n        (CSVUserAgentResponder, pd.read_csv, None),\n        (JSONUserAgentResponder, pd.read_json, None),\n        (ParquetPyArrowUserAgentResponder, pd.read_parquet, \"pyarrow\"),\n        pytest.param(\n            ParquetFastParquetUserAgentResponder,\n            pd.read_parquet,\n            \"fastparquet\",\n            # TODO(ArrayManager) fastparquet\n            marks=[\n                td.skip_array_manager_not_yet_implemented,\n                pytest.mark.xfail(PY310, reason=\"fastparquet failing on 3.10\"),\n            ],\n        ),\n        (PickleUserAgentResponder, pd.read_pickle, None),\n        (StataUserAgentResponder, pd.read_stata, None),\n        (GzippedCSVUserAgentResponder, pd.read_csv, None),\n        (GzippedJSONUserAgentResponder, pd.read_json, None),\n    ],\n    indirect=[\"responder\"],\n)",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 380,
        "n_words": 93,
        "vocab_size": 75,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 117,
        "n_ast_nodes": 366,
        "n_identifiers": 48,
        "d_id": 39497,
        "documentation": {
            "docstring": "\n    Fixture that starts a local http server in a separate process on localhost\n    and returns the port.\n\n    Running in a separate process instead of a thread to allow termination/killing\n    of http server upon cleanup.\n    ",
            "n_words": 34,
            "vocab_size": 25,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 144928,
        "commit_id": "4c73560b313821fbfbb8c943e02c8b298b7c1731",
        "repo": "ray",
        "path": "python/ray/_private/runtime_env/_clonevirtualenv.py",
        "file_name": "_clonevirtualenv.py",
        "fun_name": "_dirmatch",
        "commit_message": "[runtime env] Support clone `virtualenv` from an existing `virtualenv` (#22309)\n\nBefore this PR, we can't run ray in virtualenv, cause `runtime_env` does not support create a new virtualenv  from an existing virtualenv.\r\n\r\nMore details:https://github.com/ray-project/ray/pull/21801#discussion_r796848499\r\n\r\nCo-authored-by: 捕牛 <hejialing.hjl@antgroup.com>",
        "code": "def _dirmatch(path, matchwith):\n    \n    matchlen = len(matchwith)\n    if (path.startswith(matchwith)\n        and path[matchlen:matchlen + 1] in [os.sep, '']):\n        return True\n    return False\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 45,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 73,
        "n_identifiers": 8,
        "d_id": 33344,
        "documentation": {
            "docstring": "Check if path is within matchwith's tree.\n    >>> _dirmatch('/home/foo/bar', '/home/foo/bar')\n    True\n    >>> _dirmatch('/home/foo/bar/', '/home/foo/bar')\n    True\n    >>> _dirmatch('/home/foo/bar/etc', '/home/foo/bar')\n    True\n    >>> _dirmatch('/home/foo/bar2', '/home/foo/bar')\n    False\n    >>> _dirmatch('/home/foo/bar2/etc', '/home/foo/bar')\n    False\n    ",
            "n_words": 27,
            "vocab_size": 16,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 297779,
        "commit_id": "10e796e9d5916ce214d23e6aeaf5d757638b07b1",
        "repo": "core",
        "path": "homeassistant/components/hue/v2/light.py",
        "file_name": "light.py",
        "fun_name": "max_mireds",
        "commit_message": "Fix issues with Color temperature conversions in Hue (#83982)",
        "code": "def max_mireds(self) -> int:\n        \n        if color_temp := self.resource.color_temperature:\n            return color_temp.mirek_schema.mirek_maximum\n        # return a fallback value to prevent issues with mired->kelvin conversions\n        return FALLBACK_MAX_MIREDS\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 62,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 25,
        "n_ast_nodes": 43,
        "n_identifiers": 9,
        "d_id": 96740,
        "documentation": {
            "docstring": "Return the warmest color_temp that this light supports.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 198413,
        "commit_id": "e94a7b45d7b033ccbd57395dca28b654f875c54c",
        "repo": "sympy",
        "path": "sympy/integrals/prde.py",
        "file_name": "prde.py",
        "fun_name": "prde_no_cancel_b_large",
        "commit_message": "Improve loop performance",
        "code": "def prde_no_cancel_b_large(b, Q, n, DE):\n    \n    db = b.degree(DE.t)\n    m = len(Q)\n    H = [Poly(0, DE.t)]*m\n\n    for N, i in itertools.product(range(n, -1, -1), range(m)):  # [n, ..., 0]\n        si = Q[i].nth(N + db)/b.LC()\n        sitn = Poly(si*DE.t**N, DE.t)\n        H[i] = H[i] + sitn\n        Q[i] = Q[i] - derivation(sitn, DE) - b*sitn\n\n    if all(qi.is_zero for qi in Q):\n        dc = -1\n        M = zeros(0, 2, DE.t)\n    else:\n        dc = max([qi.degree(DE.t) for qi in Q])\n        M = Matrix(dc + 1, m, lambda i, j: Q[j].nth(i), DE.t)\n    A, u = constant_system(M, zeros(dc + 1, 1, DE.t), DE)\n    c = eye(m, DE.t)\n    A = A.row_join(zeros(A.rows, m, DE.t)).col_join(c.row_join(-c))\n\n    return (H, A)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 194,
        "n_words": 104,
        "vocab_size": 70,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 281,
        "n_ast_nodes": 421,
        "n_identifiers": 39,
        "d_id": 48922,
        "documentation": {
            "docstring": "\n    Parametric Poly Risch Differential Equation - No cancellation: deg(b) large enough.\n\n    Explanation\n    ===========\n\n    Given a derivation D on k[t], n in ZZ, and b, q1, ..., qm in k[t] with\n    b != 0 and either D == d/dt or deg(b) > max(0, deg(D) - 1), returns\n    h1, ..., hr in k[t] and a matrix A with coefficients in Const(k) such that\n    if c1, ..., cm in Const(k) and q in k[t] satisfy deg(q) <= n and\n    Dq + b*q == Sum(ci*qi, (i, 1, m)), then q = Sum(dj*hj, (j, 1, r)), where\n    d1, ..., dr in Const(k) and A*Matrix([[c1, ..., cm, d1, ..., dr]]).T == 0.\n    ",
            "n_words": 106,
            "vocab_size": 75,
            "n_whitespaces": 137,
            "language": "en"
        }
    },
    {
        "id": 198500,
        "commit_id": "9d58006fc0a23afcba38f641c9472917c436428a",
        "repo": "sympy",
        "path": "sympy/ntheory/residue_ntheory.py",
        "file_name": "residue_ntheory.py",
        "fun_name": "_discrete_log_shanks_steps",
        "commit_message": "Code cleanup",
        "code": "def _discrete_log_shanks_steps(n, a, b, order=None):\n    \n    a %= n\n    b %= n\n    if order is None:\n        order = n_order(b, n)\n    m = isqrt(order) + 1\n    T = {}\n    x = 1\n    for i in range(m):\n        T[x] = i\n        x = x * b % n\n    z = mod_inverse(b, n)\n    z = pow(z, m, n)\n    x = a\n    for i in range(m):\n        if x in T:\n            return i * m + T[x]\n        x = x * z % n\n    raise ValueError(\"Log does not exist\")\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 167,
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        "nloc": 19,
        "token_counts": 126,
        "n_ast_nodes": 194,
        "n_identifiers": 16,
        "d_id": 48963,
        "documentation": {
            "docstring": "\n    Baby-step giant-step algorithm for computing the discrete logarithm of\n    ``a`` to the base ``b`` modulo ``n``.\n\n    The algorithm is a time-memory trade-off of the method of exhaustive\n    search. It uses `O(sqrt(m))` memory, where `m` is the group order.\n\n    Examples\n    ========\n\n    >>> from sympy.ntheory.residue_ntheory import _discrete_log_shanks_steps\n    >>> _discrete_log_shanks_steps(41, 15, 7)\n    3\n\n    See Also\n    ========\n\n    discrete_log\n\n    References\n    ==========\n\n    .. [1] \"Handbook of applied cryptography\", Menezes, A. J., Van, O. P. C., &\n        Vanstone, S. A. (1997).\n    ",
            "n_words": 74,
            "vocab_size": 63,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 65748,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/crm/report/campaign_efficiency/campaign_efficiency.py",
        "file_name": "campaign_efficiency.py",
        "fun_name": "get_lead_data",
        "commit_message": "style: format code with black",
        "code": "def get_lead_data(filters, based_on):\n\tbased_on_field = frappe.scrub(based_on)\n\tconditions = get_filter_conditions(filters)\n\n\tlead_details = frappe.db.sql(\n\t\t.format(\n\t\t\tbased_on_field=based_on_field, conditions=conditions\n\t\t),\n\t\tfilters,\n\t\tas_dict=1,\n\t)\n\n\tlead_map = frappe._dict()\n\tfor d in lead_details:\n\t\tlead_map.setdefault(d.get(based_on_field), []).append(d.name)\n\n\tdata = []\n\tfor based_on_value, leads in lead_map.items():\n\t\trow = {based_on_field: based_on_value, \"lead_count\": len(leads)}\n\t\trow[\"quot_count\"] = get_lead_quotation_count(leads)\n\t\trow[\"opp_count\"] = get_lead_opp_count(leads)\n\t\trow[\"order_count\"] = get_quotation_ordered_count(leads)\n\t\trow[\"order_value\"] = get_order_amount(leads) or 0\n\n\t\trow[\"opp_lead\"] = flt(row[\"opp_count\"]) / flt(row[\"lead_count\"] or 1.0) * 100.0\n\t\trow[\"quot_lead\"] = flt(row[\"quot_count\"]) / flt(row[\"lead_count\"] or 1.0) * 100.0\n\n\t\trow[\"order_quot\"] = flt(row[\"order_count\"]) / flt(row[\"quot_count\"] or 1.0) * 100.0\n\n\t\tdata.append(row)\n\n\treturn data\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 61,
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        "complexity": 7,
        "nloc": 29,
        "token_counts": 241,
        "n_ast_nodes": 381,
        "n_identifiers": 31,
        "d_id": 14000,
        "documentation": {
            "docstring": "\n\t\tselect {based_on_field}, name\n\t\tfrom `tabLead`\n\t\twhere {based_on_field} is not null and {based_on_field} != '' {conditions}\n\t",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 250874,
        "commit_id": "9d1e3107e851b3187c1270df189da74236e447f7",
        "repo": "mitmproxy",
        "path": "mitmproxy/contentviews/grpc.py",
        "file_name": "grpc.py",
        "fun_name": "gen_flat_decoded_field_dicts",
        "commit_message": "`pyupgrade --keep-runtime-typing --py38-plus`",
        "code": "def gen_flat_decoded_field_dicts(self) -> Generator[Dict, None, None]:\n            \n            selected_decoding, decoded_val = self.safe_decode_as(self.preferred_decoding, self.try_unpack)\n            field_desc_dict = {\n                \"tag\": self._gen_tag_str(),\n                \"wireType\": self._wire_type_str(),\n                \"decoding\": self._decoding_str(selected_decoding),\n                \"name\": self.name,\n            }\n            if isinstance(decoded_val, list):\n                if (\n                    selected_decoding == ProtoParser.DecodedTypes.message  # field is a message with subfields\n                    and not self.is_packed_parent  # field is a message, but replaced by packed fields\n                ):\n                    # Field is a message, not packed, thus include it as message header\n                    field_desc_dict[\"val\"] = \"\"\n                    yield field_desc_dict\n                # add sub-fields of messages or packed fields\n                for f in decoded_val:\n                    yield from f.gen_flat_decoded_field_dicts()\n            else:\n                field_desc_dict[\"val\"] = decoded_val\n                yield field_desc_dict\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 423,
        "n_words": 91,
        "vocab_size": 68,
        "complexity": 5,
        "nloc": 28,
        "token_counts": 120,
        "n_ast_nodes": 204,
        "n_identifiers": 21,
        "d_id": 73562,
        "documentation": {
            "docstring": "\n            Returns a generator which passes the field as a dict.\n\n            In order to return the field value it gets decoded (based on a failover strategy and\n            provided ParserRules).\n            If the field holds a nested message, the fields contained in the message are appended.\n            Ultimately this flattens all fields recursively.\n            ",
            "n_words": 49,
            "vocab_size": 39,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 207831,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_change_view",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_change_view(self):\n        \n        change_dict = {\n            \"title\": \"Ikke fordømt\",\n            \"content\": \"<p>edited article</p>\",\n            \"date_0\": \"2008-03-18\",\n            \"date_1\": \"10:54:39\",\n            \"section\": self.s1.pk,\n        }\n        article_change_url = reverse(\n            \"admin:admin_views_article_change\", args=(self.a1.pk,)\n        )\n        article_changelist_url = reverse(\"admin:admin_views_article_changelist\")\n\n        # add user should not be able to view the list of article or change any of them\n        self.client.force_login(self.adduser)\n        response = self.client.get(article_changelist_url)\n        self.assertEqual(response.status_code, 403)\n        response = self.client.get(article_change_url)\n        self.assertEqual(response.status_code, 403)\n        post = self.client.post(article_change_url, change_dict)\n        self.assertEqual(post.status_code, 403)\n        self.client.get(reverse(\"admin:logout\"))\n\n        # view user can view articles but not make changes.\n        self.client.force_login(self.viewuser)\n        response = self.client.get(article_changelist_url)\n        self.assertContains(\n            response,\n            \"<title>Select article to view | Django site admin</title>\",\n        )\n        self.assertContains(response, \"<h1>Select article to view</h1>\")\n        self.assertEqual(response.context[\"title\"], \"Select article to view\")\n        response = self.client.get(article_change_url)\n        self.assertContains(response, \"<title>View article | Django site admin</title>\")\n        self.assertContains(response, \"<h1>View article</h1>\")\n        self.assertContains(response, \"<label>Extra form field:</label>\")\n        self.assertContains(\n            response,\n            '<a href=\"/test_admin/admin/admin_views/article/\" class=\"closelink\">Close</a>',\n        )\n        self.assertEqual(response.context[\"title\"], \"View article\")\n        post = self.client.post(article_change_url, change_dict)\n        self.assertEqual(post.status_code, 403)\n        self.assertEqual(\n            Article.objects.get(pk=self.a1.pk).content, \"<p>Middle content</p>\"\n        )\n        self.client.get(reverse(\"admin:logout\"))\n\n        # change user can view all items and edit them\n        self.client.force_login(self.changeuser)\n        response = self.client.get(article_changelist_url)\n        self.assertEqual(response.context[\"title\"], \"Select article to change\")\n        self.assertContains(\n            response,\n            \"<title>Select article to change | Django site admin</title>\",\n        )\n        self.assertContains(response, \"<h1>Select article to change</h1>\")\n        response = self.client.get(article_change_url)\n        self.assertEqual(response.context[\"title\"], \"Change article\")\n        self.assertContains(\n            response,\n            \"<title>Change article | Django site admin</title>\",\n        )\n        self.assertContains(response, \"<h1>Change article</h1>\")\n        post = self.client.post(article_change_url, change_dict)\n        self.assertRedirects(post, article_changelist_url)\n        self.assertEqual(\n            Article.objects.get(pk=self.a1.pk).content, \"<p>edited article</p>\"\n        )\n\n        # one error in form should produce singular error message, multiple errors plural\n        change_dict[\"title\"] = \"\"\n        post = self.client.post(article_change_url, change_dict)\n        self.assertContains(\n            post,\n            \"Please correct the error below.\",\n            msg_prefix=\"Singular error message not found in response to post with one error\",\n        )\n\n        change_dict[\"content\"] = \"\"\n        post = self.client.post(article_change_url, change_dict)\n        self.assertContains(\n            post,\n            \"Please correct the errors below.\",\n            msg_prefix=\"Plural error message not found in response to post with multiple errors\",\n        )\n        self.client.get(reverse(\"admin:logout\"))\n\n        # Test redirection when using row-level change permissions. Refs #11513.\n        r1 = RowLevelChangePermissionModel.objects.create(id=1, name=\"odd id\")\n        r2 = RowLevelChangePermissionModel.objects.create(id=2, name=\"even id\")\n        r3 = RowLevelChangePermissionModel.objects.create(id=3, name=\"odd id mult 3\")\n        r6 = RowLevelChangePermissionModel.objects.create(id=6, name=\"even id mult 3\")\n        change_url_1 = reverse(\n            \"admin:admin_views_rowlevelchangepermissionmodel_change\", args=(r1.pk,)\n        )\n        change_url_2 = reverse(\n            \"admin:admin_views_rowlevelchangepermissionmodel_change\", args=(r2.pk,)\n        )\n        change_url_3 = reverse(\n            \"admin:admin_views_rowlevelchangepermissionmodel_change\", args=(r3.pk,)\n        )\n        change_url_6 = reverse(\n            \"admin:admin_views_rowlevelchangepermissionmodel_change\", args=(r6.pk,)\n        )\n        logins = [\n            self.superuser,\n            self.viewuser,\n            self.adduser,\n            self.changeuser,\n            self.deleteuser,\n        ]\n        for login_user in logins:\n            with self.subTest(login_user.username):\n                self.client.force_login(login_user)\n                response = self.client.get(change_url_1)\n                self.assertEqual(response.status_code, 403)\n                response = self.client.post(change_url_1, {\"name\": \"changed\"})\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=1).name, \"odd id\"\n                )\n                self.assertEqual(response.status_code, 403)\n                response = self.client.get(change_url_2)\n                self.assertEqual(response.status_code, 200)\n                response = self.client.post(change_url_2, {\"name\": \"changed\"})\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=2).name, \"changed\"\n                )\n                self.assertRedirects(response, self.index_url)\n                response = self.client.get(change_url_3)\n                self.assertEqual(response.status_code, 200)\n                response = self.client.post(change_url_3, {\"name\": \"changed\"})\n                self.assertEqual(response.status_code, 403)\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=3).name,\n                    \"odd id mult 3\",\n                )\n                response = self.client.get(change_url_6)\n                self.assertEqual(response.status_code, 200)\n                response = self.client.post(change_url_6, {\"name\": \"changed\"})\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=6).name, \"changed\"\n                )\n                self.assertRedirects(response, self.index_url)\n\n                self.client.get(reverse(\"admin:logout\"))\n\n        for login_user in [self.joepublicuser, self.nostaffuser]:\n            with self.subTest(login_user.username):\n                self.client.force_login(login_user)\n                response = self.client.get(change_url_1, follow=True)\n                self.assertContains(response, \"login-form\")\n                response = self.client.post(\n                    change_url_1, {\"name\": \"changed\"}, follow=True\n                )\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=1).name, \"odd id\"\n                )\n                self.assertContains(response, \"login-form\")\n                response = self.client.get(change_url_2, follow=True)\n                self.assertContains(response, \"login-form\")\n                response = self.client.post(\n                    change_url_2, {\"name\": \"changed again\"}, follow=True\n                )\n                self.assertEqual(\n                    RowLevelChangePermissionModel.objects.get(id=2).name, \"changed\"\n                )\n                self.assertContains(response, \"login-form\")\n                self.client.get(reverse(\"admin:logout\"))\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 2165,
        "n_words": 462,
        "vocab_size": 202,
        "complexity": 3,
        "nloc": 156,
        "token_counts": 1131,
        "n_ast_nodes": 1865,
        "n_identifiers": 49,
        "d_id": 52122,
        "documentation": {
            "docstring": "Change view should restrict access and allow users to edit items.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 323181,
        "commit_id": "44a290e94d1becd1f09fddc3d873f9e19c9d6919",
        "repo": "PaddleNLP",
        "path": "paddlenlp/trainer/utils/helper.py",
        "file_name": "helper.py",
        "fun_name": "nested_concat",
        "commit_message": "[Trainer] Add init version of paddlenlp trainer and apply  finetune for ernie-1.0 pretraining. (#1761)\n\n* add some datasets for finetune.\r\n\r\n* support fine tune for all tastks.\r\n\r\n* add trainer prototype.\r\n\r\n* init verison for paddlenlp trainer.\r\n\r\n* refine trainer.\r\n\r\n* update for some details.\r\n\r\n* support multi-cards training evaluation.\r\n\r\n* support load from ckpt.\r\n\r\n* support for export inference model.\r\n\r\n* first version of trainer.\r\n\r\n* seq cls support clue.\r\n\r\n* trainer support for token classification and question answersing tasks.\r\n\r\n* fix as reviews.\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>",
        "code": "def nested_concat(tensors, new_tensors, padding_index=-100):\n    \n    assert type(tensors) == type(\n        new_tensors\n    ), f\"Expected `tensors` and `new_tensors` to have the same type but found {type(tensors)} and {type(new_tensors)}.\"\n    if isinstance(tensors, (list, tuple)):\n        return type(tensors)(nested_concat(\n            t, n, padding_index=padding_index)\n                             for t, n in zip(tensors, new_tensors))\n    elif isinstance(tensors, paddle.Tensor):\n        return paddle_pad_and_concatenate(\n            tensors, new_tensors, padding_index=padding_index)\n    elif isinstance(tensors, np.ndarray):\n        return numpy_pad_and_concatenate(\n            tensors, new_tensors, padding_index=padding_index)\n    else:\n        raise TypeError(\n            f\"Unsupported type for concatenation: got {type(tensors)}\")\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 192,
        "n_words": 64,
        "vocab_size": 50,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 116,
        "n_ast_nodes": 200,
        "n_identifiers": 18,
        "d_id": 118400,
        "documentation": {
            "docstring": "\n    Concat the `new_tensors` to `tensors` on the first dim and pad them on the second if needed. Works for tensors or\n    nested list/tuples of tensors.\n    ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 299032,
        "commit_id": "fe0120b65a5e685b1aed06e8bd3cf10b561a710b",
        "repo": "core",
        "path": "tests/components/zwave_js/test_light.py",
        "file_name": "test_light.py",
        "fun_name": "test_light_none_color_value",
        "commit_message": "Use light enums in zwave_js (#70791)",
        "code": "async def test_light_none_color_value(hass, light_color_null_values, integration):\n    \n    entity_id = \"light.repeater\"\n    state = hass.states.get(entity_id)\n\n    assert state\n    assert state.state == STATE_ON\n    assert state.attributes[ATTR_SUPPORTED_FEATURES] == LightEntityFeature.TRANSITION\n    assert state.attributes[ATTR_SUPPORTED_COLOR_MODES] == [\"hs\"]\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 46,
        "n_words": 25,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 14,
        "d_id": 97970,
        "documentation": {
            "docstring": "Test the light entity can handle None value in current color Value.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 110307,
        "commit_id": "03a0b5ea238014ba87f74ef766928287726aa00a",
        "repo": "matplotlib",
        "path": "lib/matplotlib/path.py",
        "file_name": "path.py",
        "fun_name": "contains_points",
        "commit_message": "Doc: Fix grammar and spelling",
        "code": "def contains_points(self, points, transform=None, radius=0.0):\n        \n        if transform is not None:\n            transform = transform.frozen()\n        result = _path.points_in_path(points, radius, self, transform)\n        return result.astype('bool')\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 60,
        "n_words": 21,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 52,
        "n_ast_nodes": 78,
        "n_identifiers": 10,
        "d_id": 24047,
        "documentation": {
            "docstring": "\n        Return whether the area enclosed by the path contains the given points.\n\n        The path is always treated as closed; i.e. if the last code is not\n        CLOSEPOLY an implicit segment connecting the last vertex to the first\n        vertex is assumed.\n\n        Parameters\n        ----------\n        points : (N, 2) array\n            The points to check. Columns contain x and y values.\n        transform : `matplotlib.transforms.Transform`, optional\n            If not ``None``, *points* will be compared to ``self`` transformed\n            by *transform*; i.e. for a correct check, *transform* should\n            transform the path into the coordinate system of *points*.\n        radius : float, default: 0\n            Additional margin on the path in coordinates of *points*.\n            The path is extended tangentially by *radius/2*; i.e. if you would\n            draw the path with a linewidth of *radius*, all points on the line\n            would still be considered to be contained in the area. Conversely,\n            negative values shrink the area: Points on the imaginary line\n            will be considered outside the area.\n\n        Returns\n        -------\n        length-N bool array\n\n        Notes\n        -----\n        The current algorithm has some limitations:\n\n        - The result is undefined for points exactly at the boundary\n          (i.e. at the path shifted by *radius/2*).\n        - The result is undefined if there is no enclosed area, i.e. all\n          vertices are on a straight line.\n        - If bounding lines start to cross each other due to *radius* shift,\n          the result is not guaranteed to be correct.\n        ",
            "n_words": 225,
            "vocab_size": 137,
            "n_whitespaces": 496,
            "language": "en"
        }
    },
    {
        "id": 189420,
        "commit_id": "149479f9132daf2266c27caa7a3e11ce06be501d",
        "repo": "manim",
        "path": "tests/test_graphical_units/test_probability.py",
        "file_name": "test_probability.py",
        "fun_name": "test_advanced_customization",
        "commit_message": "Refactored :class:`~.BarChart` and made it inherit from :class:`~.Axes`. (#2387)\n\n* rebase\r\n\r\n* fixed None bar_names\r\n\r\n* fixed scale issues\r\n\r\n* fixed to accept negative bar values\r\n\r\n* fixed some bugs\r\n\r\n* Added docs for parameters (DRAFT)\r\n\r\n* clean up parameters\r\n\r\n* more clean up\r\n\r\n* clean up __init__\r\n\r\n* replace add_x_labels with built-in functionality\r\n\r\n* adjust default font_size for labels\r\n\r\n* Update docs descriptions\r\n\r\n* Add bar_width and adjust get_bar_labels\r\n\r\n* Add bar_width and adjust get_bar_labels\r\n\r\n* Add docs to class and methods\r\n\r\n* remove unecessary imports\r\n\r\n* remove getters\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Attempt to fix duplicated parameters section\r\n\r\n* adjust BarChart example to include title\r\n\r\n* switch order around\r\n\r\n* change_bar_values\r\n\r\n* back to get_bar_values\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* add docs for _update_default_config and fix method\r\n\r\n* remove print(dicts)\r\n\r\n* allow negative_numbers to work with bar chart\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* allow negative numbers to work with change_bar_values\r\n\r\n* add test_probability.py\r\n\r\n* add control data\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* change example\r\n\r\n* update examples again\r\n\r\n* rewrite test\r\n\r\n* rewrite other test\r\n\r\n* remove comma after list in example\r\n\r\n* improve wording in docs\r\n\r\n* add parameter/docs for label_constructor\r\n\r\n* change create_label_tex and update methods\r\n\r\n* update docs\r\n\r\n* use decimal number\r\n\r\n* switch default to Tex\r\n\r\n* update instances of create_label_tex in coordinate_systems.py\r\n\r\n* hardcode for add_labels\r\n\r\n* add TODO\r\n\r\n* use label_constructor\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix indentation in docs\r\n\r\n* Fix minor doc typo\r\n\r\nCo-authored-by: Led Me Explain <ledmeexplain@gmail.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def test_advanced_customization(scene):\n    \n    chart = BarChart(values=[10, 40, 10, 20], bar_names=[\"one\", \"two\", \"three\", \"four\"])\n\n    c_x_lbls = chart.x_axis.labels\n    c_x_lbls.set_color_by_gradient(GREEN, RED, YELLOW)\n\n    c_y_nums = chart.y_axis.numbers\n    c_y_nums.set_color_by_gradient(BLUE, WHITE).shift(LEFT)\n\n    c_y_axis = chart.y_axis\n    c_y_axis.ticks.set_color(YELLOW)\n\n    c_bar_lbls = chart.get_bar_labels()\n\n    scene.add(chart, c_bar_lbls)\n\n\n@frames_comparison",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "@frames_comparison",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 62,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 99,
        "n_ast_nodes": 162,
        "n_identifiers": 27,
        "d_id": 46049,
        "documentation": {
            "docstring": "Tests to make sure advanced customization can be done through :class:`~.BarChart`",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 242078,
        "commit_id": "f2ccee6761ddcdde2c6502146ca1b37730d46d6d",
        "repo": "scipy",
        "path": "scipy/linalg/_generate_pyx.py",
        "file_name": "_generate_pyx.py",
        "fun_name": "newer",
        "commit_message": "MAINT: Remove `distutils` usage and add `newer`",
        "code": "def newer(source, target):\n    \n    if not os.path.exists(source):\n        raise ValueError(\"file '%s' does not exist\" % os.path.abspath(source))\n    if not os.path.exists(target):\n        return 1\n\n    mtime1 = os.stat(source)[ST_MTIME]\n    mtime2 = os.stat(target)[ST_MTIME]\n\n    return mtime1 > mtime2\n\n",
        "url": "https://github.com/scipy/scipy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 61,
        "n_words": 29,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 72,
        "n_ast_nodes": 118,
        "n_identifiers": 12,
        "d_id": 69778,
        "documentation": {
            "docstring": "\n    Return true if 'source' exists and is more recently modified than\n    'target', or if 'source' exists and 'target' doesn't.  Return false if\n    both exist and 'target' is the same age or younger than 'source'.\n    ",
            "n_words": 34,
            "vocab_size": 23,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 249328,
        "commit_id": "2281427175e4c93a30c39607fb4ac23c2a1f399f",
        "repo": "synapse",
        "path": "tests/rest/admin/test_registration_tokens.py",
        "file_name": "test_registration_tokens.py",
        "fun_name": "test_list_invalid_query_parameter",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13488)\n\n* Use literals in place of `HTTPStatus` constants in tests\r\n\r\n* newsfile\r\n\r\n* code style\r\n\r\n* code style",
        "code": "def test_list_invalid_query_parameter(self) -> None:\n        \n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?valid=x\",\n            {},\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(400, channel.code, msg=channel.json_body)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 89,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 48,
        "n_ast_nodes": 77,
        "n_identifiers": 11,
        "d_id": 72831,
        "documentation": {
            "docstring": "Test with `valid` query parameter not `true` or `false`.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 320273,
        "commit_id": "00f39d8b581c358f2484680275222f6ad909758c",
        "repo": "paperless-ngx",
        "path": "src/paperless_mail/tests/test_parsers.py",
        "file_name": "test_parsers.py",
        "fun_name": "test_get_parsed_simple_text_mail",
        "commit_message": "add test comments",
        "code": "def test_get_parsed_simple_text_mail(self):\n        \n        # Parse Test file and check relevant content\n        parsed1 = self.parser.get_parsed(\n            os.path.join(self.SAMPLE_FILES, \"simple_text.eml\"),\n        )\n\n        self.assertEqual(parsed1.date.year, 2022)\n        self.assertEqual(parsed1.date.month, 10)\n        self.assertEqual(parsed1.date.day, 12)\n        self.assertEqual(parsed1.date.hour, 21)\n        self.assertEqual(parsed1.date.minute, 40)\n        self.assertEqual(parsed1.date.second, 43)\n        self.assertEqual(parsed1.date.tzname(), \"UTC+02:00\")\n        self.assertEqual(parsed1.from_, \"mail@someserver.de\")\n        self.assertEqual(parsed1.subject, \"Simple Text Mail\")\n        self.assertEqual(parsed1.text, \"This is just a simple Text Mail.\\n\")\n        self.assertEqual(parsed1.to, (\"some@one.de\",))\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 162,
        "n_words": 46,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 157,
        "n_ast_nodes": 254,
        "n_identifiers": 22,
        "d_id": 117103,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - Fresh parser\n        WHEN:\n            - A .eml file should be parsed\n        THEN:\n            - The content of the mail should be available in the parse result.\n        ",
            "n_words": 26,
            "vocab_size": 21,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 104393,
        "commit_id": "e35be138148333078284b942ccc9ed7b1d826f97",
        "repo": "datasets",
        "path": "src/datasets/table.py",
        "file_name": "table.py",
        "fun_name": "from_pydict",
        "commit_message": "Update docs to new frontend/UI (#3690)\n\n* WIP: update docs to new UI\r\n\r\n* make style\r\n\r\n* Rm unused\r\n\r\n* inject_arrow_table_documentation __annotations__\r\n\r\n* hasattr(arrow_table_method, \"__annotations__\")\r\n\r\n* Update task_template.rst\r\n\r\n* Codeblock PT-TF-SPLIT\r\n\r\n* Convert loading scripts\r\n\r\n* Convert docs to mdx\r\n\r\n* Fix mdx\r\n\r\n* Add <Tip>\r\n\r\n* Convert mdx tables\r\n\r\n* Fix codeblock\r\n\r\n* Rm unneded hashlinks\r\n\r\n* Update index.mdx\r\n\r\n* Redo dev change\r\n\r\n* Rm circle ci `build_doc` & `deploy_doc`\r\n\r\n* Rm unneeded files\r\n\r\n* Update docs reamde\r\n\r\n* Standardize to `Example::`\r\n\r\n* mdx logging levels doc\r\n\r\n* Table properties inject_arrow_table_documentation\r\n\r\n* ``` to ```py mdx\r\n\r\n* Add Tips mdx\r\n\r\n* important,None -> <Tip warning={true}>\r\n\r\n* More misc\r\n\r\n* Center imgs\r\n\r\n* Update instllation page\r\n\r\n* `setup.py` docs section\r\n\r\n* Rm imgs since they are in hf.co\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* Update index mdx\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* just `Dataset` obj\r\n\r\n* Addedversion just italics\r\n\r\n* Update ReadInstruction doc example syntax\r\n\r\n* Change docstring for `prepare_for_task`\r\n\r\n* Chore\r\n\r\n* Remove `code` syntax from headings\r\n\r\n* Rm `code` syntax from headings\r\n\r\n* Hashlink backward compatability\r\n\r\n* S3FileSystem doc\r\n\r\n* S3FileSystem doc updates\r\n\r\n* index.mdx updates\r\n\r\n* Add darkmode gifs\r\n\r\n* Index logo img css classes\r\n\r\n* Index mdx dataset logo img size\r\n\r\n* Docs for DownloadMode class\r\n\r\n* Doc DownloadMode table\r\n\r\n* format docstrings\r\n\r\n* style\r\n\r\n* Add doc builder scripts (#3790)\r\n\r\n* add doc builder scripts\r\n\r\n* fix docker image\r\n\r\n* Docs new UI actions no self hosted (#3793)\r\n\r\n* No self hosted\r\n\r\n* replace doc injection by actual docstrings\r\n\r\n* Docstring formatted\r\n\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\n* Rm notebooks from docs actions since they dont exi\r\n\r\n* Update tsting branch\r\n\r\n* More docstring\r\n\r\n* Chore\r\n\r\n* bump up node version\r\n\r\n* bump up node\r\n\r\n* ``` -> ```py for audio_process.mdx\r\n\r\n* Update .github/workflows/build_documentation.yml\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\n\r\n* Uodate dev doc build\r\n\r\n* remove run on PR\r\n\r\n* fix action\r\n\r\n* Fix gh doc workflow\r\n\r\n* forgot this change when merging master\r\n\r\n* Update build doc\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>",
        "code": "def from_pydict(cls, *args, **kwargs):\n        \n        return cls(pa.Table.from_pydict(*args, **kwargs))\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 28,
        "n_ast_nodes": 46,
        "n_identifiers": 6,
        "d_id": 21830,
        "documentation": {
            "docstring": "\n        Construct a Table from Arrow arrays or columns\n\n        Args:\n            mapping (:obj:`Union[dict, Mapping]`):\n                A mapping of strings to Arrays or Python lists.\n            schema (:obj:`Schema`, defaults to :obj:`None`):\n                If not passed, will be inferred from the Mapping values\n            metadata (:obj:`Union[dict, Mapping]`, default None):\n                Optional metadata for the schema (if inferred).\n\n        Returns:\n            :class:`datasets.table.Table`:\n        ",
            "n_words": 50,
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            "language": "en"
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    },
    {
        "id": 168224,
        "commit_id": "2f8d0a36703e81e4dca52ca9fe4f58c910c1b304",
        "repo": "pandas",
        "path": "pandas/core/groupby/grouper.py",
        "file_name": "grouper.py",
        "fun_name": "_check_deprecated_resample_kwargs",
        "commit_message": "PERF cache find_stack_level (#48023)\n\ncache stacklevel",
        "code": "def _check_deprecated_resample_kwargs(kwargs, origin):\n    \n    # Deprecation warning of `base` and `loffset` since v1.1.0:\n    # we are raising the warning here to be able to set the `stacklevel`\n    # properly since we need to raise the `base` and `loffset` deprecation\n    # warning from three different cases:\n    #   core/generic.py::NDFrame.resample\n    #   core/groupby/groupby.py::GroupBy.resample\n    #   core/groupby/grouper.py::Grouper\n    # raising these warnings from TimeGrouper directly would fail the test:\n    #   tests/resample/test_deprecated.py::test_deprecating_on_loffset_and_base\n\n    if kwargs.get(\"base\", None) is not None:\n        warnings.warn(\n            \"'base' in .resample() and in Grouper() is deprecated.\\n\"\n            \"The new arguments that you should use are 'offset' or 'origin'.\\n\"\n            '\\n>>> df.resample(freq=\"3s\", base=2)\\n'\n            \"\\nbecomes:\\n\"\n            '\\n>>> df.resample(freq=\"3s\", offset=\"2s\")\\n',\n            FutureWarning,\n            stacklevel=find_stack_level(inspect.currentframe()),\n        )\n    if kwargs.get(\"loffset\", None) is not None:\n        warnings.warn(\n            \"'loffset' in .resample() and in Grouper() is deprecated.\\n\"\n            '\\n>>> df.resample(freq=\"3s\", loffset=\"8H\")\\n'\n            \"\\nbecomes:\\n\"\n            \"\\n>>> from pandas.tseries.frequencies import to_offset\"\n            '\\n>>> df = df.resample(freq=\"3s\").mean()'\n            '\\n>>> df.index = df.index.to_timestamp() + to_offset(\"8H\")\\n',\n            FutureWarning,\n            stacklevel=find_stack_level(inspect.currentframe()),\n        )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 373,
        "n_words": 136,
        "vocab_size": 85,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 83,
        "n_ast_nodes": 176,
        "n_identifiers": 11,
        "d_id": 40239,
        "documentation": {
            "docstring": "\n    Check for use of deprecated parameters in ``resample`` and related functions.\n\n    Raises the appropriate warnings if these parameters are detected.\n    Only sets an approximate ``stacklevel`` for the warnings (see #37603, #36629).\n\n    Parameters\n    ----------\n    kwargs : dict\n        Dictionary of keyword arguments to check for deprecated parameters.\n    origin : object\n        From where this function is being called; either Grouper or TimeGrouper. Used\n        to determine an approximate stacklevel.\n    ",
            "n_words": 65,
            "vocab_size": 54,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 164509,
        "commit_id": "c7da9ea5b089ebd0a57a62309e63dff08d26b2c8",
        "repo": "pandas",
        "path": "pandas/compat/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "is_platform_arm",
        "commit_message": "TST: Create is_ci_environment helper (#45812)",
        "code": "def is_platform_arm() -> bool:\n    \n    return platform.machine() in (\"arm64\", \"aarch64\") or platform.machine().startswith(\n        \"armv\"\n    )\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 29,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 30,
        "n_ast_nodes": 57,
        "n_identifiers": 5,
        "d_id": 39565,
        "documentation": {
            "docstring": "\n    Checking if the running platform use ARM architecture.\n\n    Returns\n    -------\n    bool\n        True if the running platform uses ARM architecture.\n    ",
            "n_words": 19,
            "vocab_size": 13,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 122213,
        "commit_id": "78ed03c4c2970e5e0d11f14a8d4fc968a4efbca2",
        "repo": "jax",
        "path": "jax/_src/lax/lax.py",
        "file_name": "lax.py",
        "fun_name": "broadcast_shapes",
        "commit_message": "[typing] add annotations to jax.numpy.linalg",
        "code": "def broadcast_shapes(*shapes):\n  \n  # NOTE: We have both cached and uncached versions to handle Tracers in shapes.\n  try:\n    return _broadcast_shapes_cached(*shapes)\n  except:\n    return _broadcast_shapes_uncached(*shapes)\n\n@cache()",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@cache()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 23,
        "n_ast_nodes": 52,
        "n_identifiers": 5,
        "d_id": 27122,
        "documentation": {
            "docstring": "Returns the shape that results from NumPy broadcasting of `shapes`.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 26788,
        "commit_id": "e5d78c63edd2620e67671e713ef594e924b0e1c9",
        "repo": "saleor",
        "path": "saleor/plugins/webhook/tests/subscription_webhooks/fixtures.py",
        "file_name": "fixtures.py",
        "fun_name": "subscription_channel_updated_webhook",
        "commit_message": "New events for changes related to channels (#9570)\n\n* Channel webhooks events added\r\n\r\n* use isActive instead od channel status property\r\n\r\n* correct CHOICES value for channel_created event",
        "code": "def subscription_channel_updated_webhook(subscription_webhook):\n    return subscription_webhook(\n        CHANNEL_UPDATED_SUBSCRIPTION_QUERY, WebhookEventAsyncType.CHANNEL_UPDATED\n    )\n\n\nCHANNEL_DELETED_SUBSCRIPTION_QUERY = \n\n\n@pytest.fixture",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 21,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 14,
        "n_ast_nodes": 36,
        "n_identifiers": 8,
        "d_id": 5063,
        "documentation": {
            "docstring": "\n    subscription{\n      event{\n        ...on ChannelDeleted{\n          channel{\n            id\n          }\n        }\n      }\n    }\n",
            "n_words": 10,
            "vocab_size": 7,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 11824,
        "commit_id": "ceb51082b4ec6f31811945ffc67b734acbbebac2",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/runtimes/worker.py",
        "file_name": "worker.py",
        "fun_name": "mixin_worker_runtime_parser",
        "commit_message": "feat: convert embedding/tensor array type at executor level (#4484)",
        "code": "def mixin_worker_runtime_parser(parser):\n    \n\n    gp = add_arg_group(parser, title='WorkerRuntime')\n    from jina import __default_executor__\n\n    gp.add_argument(\n        '--uses',\n        type=str,\n        default=__default_executor__,\n        help=,\n    )\n    gp.add_argument(\n        '--uses-with',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n    gp.add_argument(\n        '--uses-metas',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n    gp.add_argument(\n        '--uses-requests',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n    gp.add_argument(\n        '--py-modules',\n        type=str,\n        nargs='*',\n        metavar='PATH',\n        help=,\n    )\n\n    gp.add_argument(\n        '--port-in',\n        type=int,\n        default=helper.random_port(),\n        dest='port',\n        help='The port for input data to bind to, default a random port between [49152, 65535]',\n    )\n    gp.add_argument(\n        '--host-in',\n        type=str,\n        default=__default_host__,\n        help=f'The host address for binding to, by default it is {__default_host__}',\n    )\n\n    gp.add_argument(\n        '--native',\n        action='store_true',\n        default=False,\n        help='If set, only native Executors is allowed, and the Executor is always run inside WorkerRuntime.',\n    )\n\n    gp.add_argument(\n        '--output-array-type',\n        type=str,\n        default=None,\n        help=,\n    )\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 460,
        "n_words": 110,
        "vocab_size": 71,
        "complexity": 1,
        "nloc": 92,
        "token_counts": 216,
        "n_ast_nodes": 363,
        "n_identifiers": 21,
        "d_id": 2127,
        "documentation": {
            "docstring": "Mixing in arguments required by :class:`WorkerRuntime` into the given parser.\n    :param parser: the parser instance to which we add arguments\n    \n        The config of the executor, it could be one of the followings:\n        * an Executor YAML file (.yml, .yaml, .jaml)\n        * a Jina Hub Executor (must start with `jinahub://` or `jinahub+docker://`)\n        * a docker image (must start with `docker://`)\n        * the string literal of a YAML config (must start with `!` or `jtype: `)\n        * the string literal of a JSON config\n\n        When use it under Python, one can use the following values additionally:\n        - a Python dict that represents the config\n        - a text file stream has `.read()` interface\n        \n    Dictionary of keyword arguments that will override the `with` configuration in `uses`\n    \n    Dictionary of keyword arguments that will override the `metas` configuration in `uses`\n    \n        Dictionary of keyword arguments that will override the `requests` configuration in `uses`\n        \nThe customized python modules need to be imported before loading the executor\n\nNote that the recommended way is to only import a single module - a simple python file, if your\nexecutor can be defined in a single file, or an ``__init__.py`` file if you have multiple files,\nwhich should be structured as a python package. For more details, please see the\n`Executor cookbook <https://docs.jina.ai/fundamentals/executor/repository-structure/>`__\n\nThe type of array `tensor` and `embedding` will be serialized to.\n\nSupports the same types as `docarray.to_protobuf(.., ndarray_type=...)`, which can be found \n`here <https://docarray.jina.ai/fundamentals/document/serialization/#from-to-protobuf>`.\nDefaults to retaining whatever type is returned by the Executor.\n",
            "n_words": 245,
            "vocab_size": 138,
            "n_whitespaces": 343,
            "language": "en"
        }
    },
    {
        "id": 6266,
        "commit_id": "20a8a6fdb516e543d4598c852063ba0fb407f3ba",
        "repo": "ludwig",
        "path": "ludwig/utils/entmax/activations.py",
        "file_name": "activations.py",
        "fun_name": "_sparsemax_threshold_and_support",
        "commit_message": "Removes dependency on entmax from PyPI, adds entmax source to utils (#1778)\n\n* Removes dependency on entmax from PyPi, add entmax source code into utils instead.\r\n\r\n* Removes build status and image from README\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fix python formatting in docs for pre-commit.\r\n\r\n* Removes __main__ from test_losses.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Update entmax imports.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\nCo-authored-by: Daniel Treiman <daniel@predibase.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def _sparsemax_threshold_and_support(X, dim=-1, k=None):\n    \n\n    if k is None or k >= X.shape[dim]:  # do full sort\n        topk, _ = torch.sort(X, dim=dim, descending=True)\n    else:\n        topk, _ = torch.topk(X, k=k, dim=dim)\n\n    topk_cumsum = topk.cumsum(dim) - 1\n    rhos = _make_ix_like(topk, dim)\n    support = rhos * topk > topk_cumsum\n\n    support_size = support.sum(dim=dim).unsqueeze(dim)\n    tau = topk_cumsum.gather(dim, support_size - 1)\n    tau /= support_size.to(X.dtype)\n\n    if k is not None and k < X.shape[dim]:\n        unsolved = (support_size == k).squeeze(dim)\n\n        if torch.any(unsolved):\n            in_ = _roll_last(X, dim)[unsolved]\n            tau_, ss_ = _sparsemax_threshold_and_support(in_, dim=-1, k=2 * k)\n            _roll_last(tau, dim)[unsolved] = tau_\n            _roll_last(support_size, dim)[unsolved] = ss_\n\n    return tau, support_size\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 202,
        "n_words": 96,
        "vocab_size": 64,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 221,
        "n_ast_nodes": 336,
        "n_identifiers": 29,
        "d_id": 947,
        "documentation": {
            "docstring": "Core computation for sparsemax: optimal threshold and support size.\n\n    Parameters\n    ----------\n    X : torch.Tensor\n        The input tensor to compute thresholds over.\n\n    dim : int\n        The dimension along which to apply sparsemax.\n\n    k : int or None\n        number of largest elements to partial-sort over. For optimal\n        performance, should be slightly bigger than the expected number of\n        nonzeros in the solution. If the solution is more than k-sparse,\n        this function is recursively called with a 2*k schedule.\n        If `None`, full sorting is performed from the beginning.\n\n    Returns\n    -------\n    tau : torch.Tensor like `X`, with all but the `dim` dimension intact\n        the threshold value for each vector\n    support_size : torch LongTensor, shape like `tau`\n        the number of nonzeros in each vector.\n    ",
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    },
    {
        "id": 203160,
        "commit_id": "0af9a5fc7d765aa05ea784e2c3237675f3bb4b49",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "bulk_update",
        "commit_message": "Fixed #33463 -- Fixed QuerySet.bulk_update() with F() expressions.",
        "code": "def bulk_update(self, objs, fields, batch_size=None):\n        \n        if batch_size is not None and batch_size < 0:\n            raise ValueError('Batch size must be a positive integer.')\n        if not fields:\n            raise ValueError('Field names must be given to bulk_update().')\n        objs = tuple(objs)\n        if any(obj.pk is None for obj in objs):\n            raise ValueError('All bulk_update() objects must have a primary key set.')\n        fields = [self.model._meta.get_field(name) for name in fields]\n        if any(not f.concrete or f.many_to_many for f in fields):\n            raise ValueError('bulk_update() can only be used with concrete fields.')\n        if any(f.primary_key for f in fields):\n            raise ValueError('bulk_update() cannot be used with primary key fields.')\n        if not objs:\n            return 0\n        for obj in objs:\n            obj._prepare_related_fields_for_save(operation_name='bulk_update', fields=fields)\n        # PK is used twice in the resulting update query, once in the filter\n        # and once in the WHEN. Each field will also have one CAST.\n        connection = connections[self.db]\n        max_batch_size = connection.ops.bulk_batch_size(['pk', 'pk'] + fields, objs)\n        batch_size = min(batch_size, max_batch_size) if batch_size else max_batch_size\n        requires_casting = connection.features.requires_casted_case_in_updates\n        batches = (objs[i:i + batch_size] for i in range(0, len(objs), batch_size))\n        updates = []\n        for batch_objs in batches:\n            update_kwargs = {}\n            for field in fields:\n                when_statements = []\n                for obj in batch_objs:\n                    attr = getattr(obj, field.attname)\n                    if not hasattr(attr, 'resolve_expression'):\n                        attr = Value(attr, output_field=field)\n                    when_statements.append(When(pk=obj.pk, then=attr))\n                case_statement = Case(*when_statements, output_field=field)\n                if requires_casting:\n                    case_statement = Cast(case_statement, output_field=field)\n                update_kwargs[field.attname] = case_statement\n            updates.append(([obj.pk for obj in batch_objs], update_kwargs))\n        rows_updated = 0\n        with transaction.atomic(using=self.db, savepoint=False):\n            for pks, update_kwargs in updates:\n                rows_updated += self.filter(pk__in=pks).update(**update_kwargs)\n        return rows_updated\n    bulk_update.alters_data = True\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "complexity": 23,
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        "token_counts": 381,
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        "n_identifiers": 61,
        "d_id": 50240,
        "documentation": {
            "docstring": "\n        Update the given fields in each of the given objects in the database.\n        ",
            "n_words": 13,
            "vocab_size": 9,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 282685,
        "commit_id": "a5848af9088466ae711ce403c9f344b964d581b8",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/cryptocurrency/overview/overview_controller.py",
        "file_name": "overview_controller.py",
        "fun_name": "call_hm",
        "commit_message": "Crypto heatmaps (#1416)\n\n* added hm feature\r\n\r\n* updated requirements\r\n\r\n* updated tests\r\n\r\n* updated tests\r\n\r\n* updated charts convention and removed duplicated autocompletion\r\n\r\n* added percentage\r\n\r\n* lint\r\n\r\nCo-authored-by: jmaslek <jmaslek11@gmail.com>",
        "code": "def call_hm(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            prog=\"hm\",\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            description=,\n        )\n\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            dest=\"limit\",\n            type=int,\n            help=\"Display N items\",\n            default=10,\n        )\n        parser.add_argument(\n            \"-c\",\n            \"--category\",\n            default=\"\",\n            dest=\"category\",\n            help=\"Category (e.g., stablecoins). Empty for no category\",\n        )\n        if other_args and not other_args[0][0] == \"-\":\n            other_args.insert(0, \"-c\")\n\n        ns_parser = parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_FIGURES_ALLOWED\n        )\n        if ns_parser:\n            pycoingecko_view.display_crypto_heatmap(\n                category=ns_parser.category,\n                top=ns_parser.limit,\n                export=ns_parser.export,\n            )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 388,
        "n_words": 57,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 37,
        "token_counts": 137,
        "n_ast_nodes": 222,
        "n_identifiers": 27,
        "d_id": 84248,
        "documentation": {
            "docstring": "Process hm commandDisplay cryptocurrencies heatmap [Source: https://coingecko.com]\n            Accepts --category or -c to display only coins of a certain category\n            (default no category to display all coins ranked by market cap).\n            You can look on only top N number of records with --limit.\n            ",
            "n_words": 42,
            "vocab_size": 36,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 223619,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_parseaddr.py",
        "file_name": "_parseaddr.py",
        "fun_name": "parsedate_tz",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parsedate_tz(data):\n    \n    res = _parsedate_tz(data)\n    if not res:\n        return\n    if res[9] is None:\n        res[9] = 0\n    return tuple(res)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 18,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 61,
        "n_identifiers": 5,
        "d_id": 57010,
        "documentation": {
            "docstring": "Convert a date string to a time tuple.\n\n    Accounts for military timezones.\n    ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 257868,
        "commit_id": "938e6fda5b686ec49c52cb23f786a74d9321e048",
        "repo": "haystack",
        "path": "haystack/pipelines/base.py",
        "file_name": "base.py",
        "fun_name": "get_type",
        "commit_message": "Classify pipeline's type based on its components (#3132)\n\n* Add pipeline get_type mehod\r\n\r\n* Add pipeline uptime\r\n\r\n* Add pipeline telemetry event sending\r\n\r\n* Send pipeline telemetry once a day (at most)\r\n\r\n* Add pipeline invocation counter, change invocation counter logic\r\n\r\n* Update allowed telemetry parameters - allow pipeline parameters\r\n\r\n* PR review: add unit test",
        "code": "def get_type(self) -> str:\n        \n        # values of the dict are functions evaluating whether components of this pipeline match the pipeline type\n        # specified by dict keys\n        pipeline_types = {\n            \"GenerativeQAPipeline\": lambda x: {\"Generator\", \"Retriever\"} <= set(x.keys()),\n            \"FAQPipeline\": lambda x: {\"Docs2Answers\"} <= set(x.keys()),\n            \"ExtractiveQAPipeline\": lambda x: {\"Reader\", \"Retriever\"} <= set(x.keys()),\n            \"SearchSummarizationPipeline\": lambda x: {\"Retriever\", \"Summarizer\"} <= set(x.keys()),\n            \"TranslationWrapperPipeline\": lambda x: {\"InputTranslator\", \"OutputTranslator\"} <= set(x.keys()),\n            \"RetrieverQuestionGenerationPipeline\": lambda x: {\"Retriever\", \"QuestionGenerator\"} <= set(x.keys()),\n            \"QuestionAnswerGenerationPipeline\": lambda x: {\"QuestionGenerator\", \"Reader\"} <= set(x.keys()),\n            \"DocumentSearchPipeline\": lambda x: {\"Retriever\"} <= set(x.keys()),\n            \"QuestionGenerationPipeline\": lambda x: {\"QuestionGenerator\"} <= set(x.keys()),\n            \"MostSimilarDocumentsPipeline\": lambda x: len(x.values()) == 1\n            and isinstance(list(x.values())[0], BaseDocumentStore),\n        }\n        retrievers = [type(comp).__name__ for comp in self.components.values() if isinstance(comp, BaseRetriever)]\n        doc_stores = [type(comp).__name__ for comp in self.components.values() if isinstance(comp, BaseDocumentStore)]\n\n        pipeline_type = next(\n            (p_type for p_type, eval_f in pipeline_types.items() if eval_f(self.components)), \"Unknown pipeline\"\n        )\n        retrievers_used = retrievers if retrievers else \"None\"\n        doc_stores_used = doc_stores if doc_stores else \"None\"\n        return f\"{pipeline_type} (retriever: {retrievers_used}, doc_store: {doc_stores_used})\"\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 369,
        "n_words": 153,
        "vocab_size": 89,
        "complexity": 10,
        "nloc": 25,
        "token_counts": 317,
        "n_ast_nodes": 556,
        "n_identifiers": 26,
        "d_id": 75161,
        "documentation": {
            "docstring": "\n        Returns the type of the pipeline.\n        ",
            "n_words": 6,
            "vocab_size": 5,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 299827,
        "commit_id": "29bda196b5e0a90a2bea7e1797742236114afc1c",
        "repo": "core",
        "path": "tests/components/history/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "record_states",
        "commit_message": "Break apart recorder into tasks and core modules (#71222)",
        "code": "def record_states(hass):\n    \n    mp = \"media_player.test\"\n    mp2 = \"media_player.test2\"\n    mp3 = \"media_player.test3\"\n    therm = \"thermostat.test\"\n    therm2 = \"thermostat.test2\"\n    zone = \"zone.home\"\n    script_c = \"script.can_cancel_this_one\"\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 47,
        "n_words": 23,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 60,
        "token_counts": 446,
        "n_ast_nodes": 62,
        "n_identifiers": 9,
        "d_id": 98729,
        "documentation": {
            "docstring": "Record some test states.\n\n    We inject a bunch of state updates from media player, zone and\n    thermostat.\n    ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 269098,
        "commit_id": "3073e00912838454359079a35f1638ccf06e855f",
        "repo": "keras",
        "path": "keras/preprocessing/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "labels_to_dataset",
        "commit_message": "Fix the issue in the other two places it occurs",
        "code": "def labels_to_dataset(labels, label_mode, num_classes):\n  \n  label_ds = tf.data.Dataset.from_tensor_slices(labels)\n  if label_mode == 'binary':\n    label_ds = label_ds.map(\n        lambda x: tf.expand_dims(tf.cast(x, 'float32'), axis=-1),\n        num_parallel_calls=tf.data.AUTOTUNE)\n  elif label_mode == 'categorical':\n    label_ds = label_ds.map(lambda x: tf.one_hot(x, num_classes),\n                            num_parallel_calls=tf.data.AUTOTUNE)\n  return label_ds\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 85,
        "n_words": 33,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 96,
        "n_ast_nodes": 154,
        "n_identifiers": 17,
        "d_id": 79896,
        "documentation": {
            "docstring": "Create a tf.data.Dataset from the list/tuple of labels.\n\n  Args:\n    labels: list/tuple of labels to be converted into a tf.data.Dataset.\n    label_mode: String describing the encoding of `labels`. Options are:\n    - 'binary' indicates that the labels (there can be only 2) are encoded as\n      `float32` scalars with values 0 or 1 (e.g. for `binary_crossentropy`).\n    - 'categorical' means that the labels are mapped into a categorical vector.\n      (e.g. for `categorical_crossentropy` loss).\n    num_classes: number of classes of labels.\n\n  Returns:\n    A `Dataset` instance.\n  ",
            "n_words": 78,
            "vocab_size": 58,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 207805,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_change_view_without_object_change_permission",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_change_view_without_object_change_permission(self):\n        \n        change_url = reverse(\"admin9:admin_views_article_change\", args=(self.a1.pk,))\n        self.client.force_login(self.viewuser)\n        response = self.client.get(change_url)\n        self.assertEqual(response.context[\"title\"], \"View article\")\n        self.assertContains(response, \"<title>View article | Django site admin</title>\")\n        self.assertContains(response, \"<h1>View article</h1>\")\n        self.assertContains(\n            response,\n            '<a href=\"/test_admin/admin9/admin_views/article/\" class=\"closelink\">Close</a>',\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 114,
        "n_words": 29,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 81,
        "n_ast_nodes": 138,
        "n_identifiers": 15,
        "d_id": 52110,
        "documentation": {
            "docstring": "\n        The object should be read-only if the user has permission to view it\n        and change objects of that type but not to change the current object.\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 67491,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/setup/doctype/party_type/party_type.py",
        "file_name": "party_type.py",
        "fun_name": "get_party_type",
        "commit_message": "style: format code with black",
        "code": "def get_party_type(doctype, txt, searchfield, start, page_len, filters):\n\tcond = \"\"\n\tif filters and filters.get(\"account\"):\n\t\taccount_type = frappe.db.get_value(\"Account\", filters.get(\"account\"), \"account_type\")\n\t\tcond = \"and account_type = '%s'\" % account_type\n\n\treturn frappe.db.sql(\n\t\t.format(\n\t\t\tkey=searchfield, cond=cond\n\t\t),\n\t\t{\"txt\": \"%\" + txt + \"%\", \"start\": start, \"page_len\": page_len},\n\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 33,
        "n_words": 44,
        "vocab_size": 36,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 91,
        "n_ast_nodes": 155,
        "n_identifiers": 16,
        "d_id": 14544,
        "documentation": {
            "docstring": "select name from `tabParty Type`\n\t\t\twhere `{key}` LIKE %(txt)s {cond}\n\t\t\torder by name limit %(start)s, %(page_len)s",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 267819,
        "commit_id": "3eb0485dd92c88cc92152d3656d94492db44b183",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/commands/coverage/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_collection_path_regexes",
        "commit_message": "ansible-test - Use more native type hints. (#78435)\n\n* ansible-test - Use more native type hints.\r\n\r\nSimple search and replace to switch from comments to native type hints for return types of functions with no arguments.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of simple single-line function annotation type comments to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of single-line function annotation type comments with default values to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nManual conversion of type annotation comments for functions which have pylint directives.",
        "code": "def get_collection_path_regexes() -> t.Tuple[t.Optional[t.Pattern], t.Optional[t.Pattern]]:\n    \n    if data_context().content.collection:\n        collection_search_re = re.compile(r'/%s/' % data_context().content.collection.directory)\n        collection_sub_re = re.compile(r'^.*?/%s/' % data_context().content.collection.directory)\n    else:\n        collection_search_re = None\n        collection_sub_re = None\n\n    return collection_search_re, collection_sub_re\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 67,
        "n_words": 27,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 87,
        "n_ast_nodes": 141,
        "n_identifiers": 13,
        "d_id": 79100,
        "documentation": {
            "docstring": "Return a pair of regexes used for identifying and manipulating collection paths.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 306592,
        "commit_id": "3798d28bec6dc257da8387a6751949d47fb29a29",
        "repo": "core",
        "path": "homeassistant/components/unifi/switch.py",
        "file_name": "switch.py",
        "fun_name": "available",
        "commit_message": "Improve entity type hints [u] (#77884)",
        "code": "def available(self) -> bool:\n        \n        return (\n            self.poe_mode is not None\n            and self.controller.available\n            and self.client.switch_port\n            and self.client.switch_mac\n            and self.client.switch_mac in self.controller.api.devices\n        )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 97,
        "n_words": 21,
        "vocab_size": 17,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 49,
        "n_ast_nodes": 77,
        "n_identifiers": 10,
        "d_id": 105376,
        "documentation": {
            "docstring": "Return if switch is available.\n\n        Poe_mode None means its POE state is unknown.\n        Sw_mac unavailable means restored client.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 289215,
        "commit_id": "551fb449752e1c3f55eb688d24509876020852d1",
        "repo": "core",
        "path": "homeassistant/components/nibe_heatpump/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "async_shutdown",
        "commit_message": "Stop coordinator before connection in nibe_heatpump (#80396)\n\nStop coordinator in nibe_heatpump",
        "code": "async def async_shutdown(self):\n        \n        if self.task:\n            self.task.cancel()\n            await asyncio.wait((self.task,))\n        self._unschedule_refresh()\n        await self.connection.stop()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 61,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 76,
        "n_identifiers": 9,
        "d_id": 88359,
        "documentation": {
            "docstring": "Make sure a coordinator is shut down as well as it's connection.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 209035,
        "commit_id": "b754f97d346e2db6e4a9e9cc6ff88010f502db89",
        "repo": "scapy",
        "path": "scapy/autorun.py",
        "file_name": "autorun.py",
        "fun_name": "autorun_get_interactive_session",
        "commit_message": "Update Mypy version",
        "code": "def autorun_get_interactive_session(cmds, **kargs):\n    # type: (str, **Any) -> Tuple[str, Any]\n    \n    sstdout, sstderr, sexcepthook = sys.stdout, sys.stderr, sys.excepthook\n    sw = StringWriter()\n    h_old = log_scapy.handlers[0]\n    log_scapy.removeHandler(h_old)\n    log_scapy.addHandler(logging.StreamHandler(stream=sw))\n    try:\n        try:\n            sys.stdout = sys.stderr = sw\n            sys.excepthook = sys.__excepthook__  # type: ignore\n            res = autorun_commands_timeout(cmds, **kargs)\n        except StopAutorun as e:\n            e.code_run = sw.s\n            raise\n    finally:\n        sys.stdout, sys.stderr, sys.excepthook = sstdout, sstderr, sexcepthook\n        log_scapy.removeHandler(log_scapy.handlers[0])\n        log_scapy.addHandler(h_old)\n    return sw.s, res\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 184,
        "n_words": 63,
        "vocab_size": 43,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 142,
        "n_ast_nodes": 228,
        "n_identifiers": 27,
        "d_id": 52584,
        "documentation": {
            "docstring": "Create an interactive session and execute the\n    commands passed as \"cmds\" and return all output\n\n    :param cmds: a list of commands to run\n    :param timeout: timeout in seconds\n    :returns: (output, returned) contains both sys.stdout and sys.stderr logs\n    ",
            "n_words": 37,
            "vocab_size": 33,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 176215,
        "commit_id": "54e36acb36c75e09bc53dfcb81c73386b82a20c9",
        "repo": "networkx",
        "path": "networkx/readwrite/gexf.py",
        "file_name": "gexf.py",
        "fun_name": "generate_gexf",
        "commit_message": "Update gexf website link in documentation (#5275)\n\nHi, we've recently put the GEXF website again into its own domain http://gexf.net/ so this documentation should be updated. Thanks!",
        "code": "def generate_gexf(G, encoding=\"utf-8\", prettyprint=True, version=\"1.2draft\"):\n    \n    writer = GEXFWriter(encoding=encoding, prettyprint=prettyprint, version=version)\n    writer.add_graph(G)\n    yield from str(writer).splitlines()\n\n\n@open_file(0, mode=\"rb\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@open_file(0, mode=\"rb\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 27,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 50,
        "n_ast_nodes": 99,
        "n_identifiers": 12,
        "d_id": 41768,
        "documentation": {
            "docstring": "Generate lines of GEXF format representation of G.\n\n    \"GEXF (Graph Exchange XML Format) is a language for describing\n    complex networks structures, their associated data and dynamics\" [1]_.\n\n    Parameters\n    ----------\n    G : graph\n    A NetworkX graph\n    encoding : string (optional, default: 'utf-8')\n    Encoding for text data.\n    prettyprint : bool (optional, default: True)\n    If True use line breaks and indenting in output XML.\n    version : string (default: 1.2draft)\n    Version of GEFX File Format (see http://gexf.net/schema.html)\n    Supported values: \"1.1draft\", \"1.2draft\"\n\n\n    Examples\n    --------\n    >>> G = nx.path_graph(4)\n    >>> linefeed = chr(10)  # linefeed=\\n\n    >>> s = linefeed.join(nx.generate_gexf(G))\n    >>> for line in nx.generate_gexf(G):  # doctest: +SKIP\n    ...     print(line)\n\n    Notes\n    -----\n    This implementation does not support mixed graphs (directed and undirected\n    edges together).\n\n    The node id attribute is set to be the string of the node label.\n    If you want to specify an id use set it as node data, e.g.\n    node['a']['id']=1 to set the id of node 'a' to 1.\n\n    References\n    ----------\n    .. [1] GEXF File Format, https://gephi.org/gexf/format/\n    ",
            "n_words": 163,
            "vocab_size": 120,
            "n_whitespaces": 262,
            "language": "en"
        }
    },
    {
        "id": 163773,
        "commit_id": "4248b23371a70b339a2c16b8e5caca9c2e5897f8",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "_can_use_libjoin",
        "commit_message": "ENH: ExtensionEngine (#45514)",
        "code": "def _can_use_libjoin(self) -> bool:\n        \n        if type(self) is Index:\n            # excludes EAs\n            return isinstance(self.dtype, np.dtype)\n        return not is_interval_dtype(self.dtype)\n\n    # --------------------------------------------------------------------\n    # Uncategorized Methods\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 71,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 35,
        "n_ast_nodes": 61,
        "n_identifiers": 9,
        "d_id": 39495,
        "documentation": {
            "docstring": "\n        Whether we can use the fastpaths implement in _libs.join\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 216005,
        "commit_id": "9354c15e0818715d055242d14b1308643a6918d7",
        "repo": "salt",
        "path": "salt/modules/mount.py",
        "file_name": "mount.py",
        "fun_name": "remount",
        "commit_message": "Convert Py 2'isms to Python 3, and add tests for set_filesystems on AIX",
        "code": "def remount(name, device, mkmnt=False, fstype=\"\", opts=\"defaults\", user=None):\n    \n    force_mount = False\n    if __grains__[\"os\"] in [\"MacOS\", \"Darwin\"]:\n        if opts == \"defaults\":\n            opts = \"noowners\"\n        if fstype == \"smbfs\":\n            force_mount = True\n\n    if \"AIX\" in __grains__[\"os\"]:\n        if opts == \"defaults\":\n            opts = []\n\n    if isinstance(opts, str):\n        opts = opts.split(\",\")\n    mnts = active()\n    if name in mnts:\n        # The mount point is mounted, attempt to remount it with the given data\n        if \"remount\" not in opts and __grains__[\"os\"] not in [\n            \"OpenBSD\",\n            \"MacOS\",\n            \"Darwin\",\n        ]:\n            opts.append(\"remount\")\n        if force_mount:\n            # We need to force the mount but first we should unmount\n            umount(name, device, user=user)\n        args = \"\"\n        if opts:\n            lopts = \",\".join(opts)\n            args = \"-o {}\".format(lopts)\n\n        if fstype:\n            # use of fstype on AIX differs from typical Linux use of\n            # -t functionality AIX uses -v vfsname, -t fstype mounts\n            # all with fstype in /etc/filesystems\n            if \"AIX\" in __grains__[\"os\"]:\n                args += \" -v {}\".format(fstype)\n            elif \"solaris\" in __grains__[\"os\"].lower():\n                args += \" -F {}\".format(fstype)\n            else:\n                args += \" -t {}\".format(fstype)\n\n        if __grains__[\"os\"] not in [\"OpenBSD\", \"MacOS\", \"Darwin\"] or force_mount:\n            cmd = \"mount {} {} {} \".format(args, device, name)\n        else:\n            cmd = \"mount -u {} {} {} \".format(args, device, name)\n        out = __salt__[\"cmd.run_all\"](cmd, runas=user, python_shell=False)\n        if out[\"retcode\"]:\n            return out[\"stderr\"]\n        return True\n    # Mount a filesystem that isn't already\n    return mount(name, device, mkmnt, fstype, opts, user=user)\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 623,
        "n_words": 219,
        "vocab_size": 124,
        "complexity": 18,
        "nloc": 42,
        "token_counts": 299,
        "n_ast_nodes": 529,
        "n_identifiers": 27,
        "d_id": 54317,
        "documentation": {
            "docstring": "\n    Attempt to remount a device, if the device is not already mounted, mount\n    is called\n\n    CLI Example:\n\n    .. code-block:: bash\n\n        salt '*' mount.remount /mnt/foo /dev/sdz1 True\n    ",
            "n_words": 26,
            "vocab_size": 25,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 13871,
        "commit_id": "46d7973043e2e599149812cc6fc7671b935c13f8",
        "repo": "jina",
        "path": "jina/serve/runtimes/worker/request_handling.py",
        "file_name": "request_handling.py",
        "fun_name": "close",
        "commit_message": "feat: dynamic batching (#5410)\n\nCo-authored-by: Johannes Messner <messnerjo@gmail.com>\r\nCo-authored-by: Alaeddine Abdessalem <alaeddine-13@live.fr>",
        "code": "async def close(self):\n        \n        if not self._is_closed:\n            await asyncio.gather(*[q.close() for q in self._all_batch_queues()])\n            self._executor.close()\n            self._is_closed = True\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 63,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 80,
        "n_identifiers": 8,
        "d_id": 2779,
        "documentation": {
            "docstring": "Close the data request handler, by closing the executor and the batch queues.",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 197287,
        "commit_id": "f3b08522003f40868afb20304fc0fa5b16d13f6a",
        "repo": "sympy",
        "path": "sympy/utilities/iterables.py",
        "file_name": "iterables.py",
        "fun_name": "filter_symbols",
        "commit_message": "Cleanup documentation",
        "code": "def filter_symbols(iterator, exclude):\n    \n    exclude = set(exclude)\n    for s in iterator:\n        if s not in exclude:\n            yield s\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 44,
        "n_words": 17,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 27,
        "n_ast_nodes": 45,
        "n_identifiers": 5,
        "d_id": 48434,
        "documentation": {
            "docstring": "\n    Only yield elements from `iterator` that do not occur in `exclude`.\n\n    Parameters\n    ==========\n\n    iterator : iterable\n        iterator to take elements from\n\n    exclude : iterable\n        elements to exclude\n\n    Returns\n    =======\n\n    iterator : iterator\n        filtered iterator\n    ",
            "n_words": 34,
            "vocab_size": 22,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 251073,
        "commit_id": "fab7016b318d7c37fc30cef9c0567b9b620b883e",
        "repo": "mitmproxy",
        "path": "mitmproxy/tools/console/consoleaddons.py",
        "file_name": "consoleaddons.py",
        "fun_name": "edit_focus_options",
        "commit_message": "beautify flowtable dns entries\n\nthis isn't perfect (the whole table needs to be refactored properly),\nbut good enough for now.",
        "code": "def edit_focus_options(self) -> typing.Sequence[str]:\n        \n        flow = self.master.view.focus.flow\n        focus_options = []\n\n        if isinstance(flow, tcp.TCPFlow):\n            focus_options = [\"tcp-message\"]\n        elif isinstance(flow, http.HTTPFlow):\n            focus_options = [\n                \"cookies\",\n                \"urlencoded form\",\n                \"multipart form\",\n                \"path\",\n                \"method\",\n                \"query\",\n                \"reason\",\n                \"request-headers\",\n                \"response-headers\",\n                \"request-body\",\n                \"response-body\",\n                \"status_code\",\n                \"set-cookies\",\n                \"url\",\n            ]\n        elif isinstance(flow, dns.DNSFlow):\n            raise exceptions.CommandError(\"Cannot edit DNS flows yet, please submit a patch.\")\n\n        return focus_options\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 357,
        "n_words": 54,
        "vocab_size": 44,
        "complexity": 4,
        "nloc": 28,
        "token_counts": 104,
        "n_ast_nodes": 181,
        "n_identifiers": 19,
        "d_id": 73587,
        "documentation": {
            "docstring": "\n            Possible components for console.edit.focus.\n        ",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 3743,
        "commit_id": "a3aae8017a0a40ff2006e2567f71dccb04c997a5",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/source_facebook_marketing/streams/async_job.py",
        "file_name": "async_job.py",
        "fun_name": "_check_status",
        "commit_message": "🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805)\n\n* Facebook Marketing performance improvement\r\n\r\n* add comments and little refactoring\r\n\r\n* fix integration tests with the new config\r\n\r\n* improve job status handling, limit concurrency to 10\r\n\r\n* fix campaign jobs, refactor manager\r\n\r\n* big refactoring of async jobs, support random order of slices\r\n\r\n* update source _read_incremental to hook new state logic\r\n\r\n* fix issues with timeout\r\n\r\n* remove debugging and clean up, improve retry logic\r\n\r\n* merge changes from #8234\r\n\r\n* fix call super _read_increment\r\n\r\n* generalize batch execution, add use_batch flag\r\n\r\n* improve coverage, do some refactoring of spec\r\n\r\n* update test, remove overrides of source\r\n\r\n* add split by AdSet\r\n\r\n* add smaller insights\r\n\r\n* fix end_date < start_date case\r\n\r\n* add account_id to PK\r\n\r\n* add notes\r\n\r\n* fix new streams\r\n\r\n* fix reversed incremental stream\r\n\r\n* update spec.json for SAT\r\n\r\n* upgrade CDK and bump version\r\n\r\nCo-authored-by: Dmytro Rezchykov <dmitry.rezchykov@zazmic.com>\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>",
        "code": "def _check_status(self) -> bool:\n        \n        job_status = self._job[\"async_status\"]\n        percent = self._job[\"async_percent_completion\"]\n        logger.info(f\"{self}: is {percent} complete ({job_status})\")\n\n        if self.elapsed_time > self.job_timeout:\n            logger.info(f\"{self}: run more than maximum allowed time {self.job_timeout}.\")\n            self._finish_time = pendulum.now()\n            self._failed = True\n            return True\n        elif job_status == Status.COMPLETED:\n            self._finish_time = pendulum.now()  # TODO: is not actual running time, but interval between check_status calls\n            return True\n        elif job_status in [Status.FAILED, Status.SKIPPED]:\n            self._finish_time = pendulum.now()\n            self._failed = True\n            logger.info(f\"{self}: has status {job_status} after {self.elapsed_time.in_seconds()} seconds.\")\n            return True\n\n        return False\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 245,
        "n_words": 78,
        "vocab_size": 54,
        "complexity": 4,
        "nloc": 22,
        "token_counts": 119,
        "n_ast_nodes": 243,
        "n_identifiers": 19,
        "d_id": 532,
        "documentation": {
            "docstring": "Perform status check\n\n        :return: True if the job is completed, False - if the job is still running\n        ",
            "n_words": 18,
            "vocab_size": 14,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 269147,
        "commit_id": "e61cbc52fd3b0170769c120e9b8dabc8c4205322",
        "repo": "keras",
        "path": "keras/saving/saved_model/save_impl.py",
        "file_name": "save_impl.py",
        "fun_name": "_reset_layer_losses",
        "commit_message": "Support Keras saving/loading for ShardedVariables with arbitrary partitions.\n\nPiperOrigin-RevId: 439837516",
        "code": "def _reset_layer_losses(parent_layer):\n  \n  losses_dict = {}\n  for layer in utils.list_all_layers_and_sublayers(parent_layer):\n    losses_dict[layer] = {\n        'losses': layer._losses[:],\n        'eager_losses': layer._eager_losses[:]\n    }\n    with utils.no_automatic_dependency_tracking_scope(layer):\n      layer._losses = []\n      layer._eager_losses = []\n  return losses_dict\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 64,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 66,
        "n_ast_nodes": 113,
        "n_identifiers": 9,
        "d_id": 79929,
        "documentation": {
            "docstring": "Resets losses of layer and its sublayers, and returns original losses.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 21440,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py",
        "file_name": "tarfile.py",
        "fun_name": "list",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def list(self, verbose=True):\n        \n        self._check()\n\n        for tarinfo in self:\n            if verbose:\n                print(filemode(tarinfo.mode), end=' ')\n                print(\"%s/%s\" % (tarinfo.uname or tarinfo.uid,\n                                 tarinfo.gname or tarinfo.gid), end=' ')\n                if tarinfo.ischr() or tarinfo.isblk():\n                    print(\"%10s\" % (\"%d,%d\" \\\n                                    % (tarinfo.devmajor, tarinfo.devminor)), end=' ')\n                else:\n                    print(\"%10d\" % tarinfo.size, end=' ')\n                print(\"%d-%02d-%02d %02d:%02d:%02d\" \\\n                      % time.localtime(tarinfo.mtime)[:6], end=' ')\n\n            print(tarinfo.name + (\"/\" if tarinfo.isdir() else \"\"), end=' ')\n\n            if verbose:\n                if tarinfo.issym():\n                    print(\"->\", tarinfo.linkname, end=' ')\n                if tarinfo.islnk():\n                    print(\"link to\", tarinfo.linkname, end=' ')\n            print()\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 408,
        "n_words": 74,
        "vocab_size": 46,
        "complexity": 11,
        "nloc": 21,
        "token_counts": 200,
        "n_ast_nodes": 341,
        "n_identifiers": 26,
        "d_id": 3836,
        "documentation": {
            "docstring": "Print a table of contents to sys.stdout. If `verbose' is False, only\n           the names of the members are printed. If it is True, an `ls -l'-like\n           output is produced.\n        ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 263901,
        "commit_id": "49abfa5498b1db83b8f1b2e859e461b1e8540c6f",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/qt.py",
        "file_name": "qt.py",
        "fun_name": "_find_all_or_none",
        "commit_message": "hookutils: qt: ensure ANGLE DLLs are collected from Anaconda Qt5\n\nAnaconda's Qt5 ships ANGLE DLLs (`libEGL.dll` and `libGLESv2.dll`)\nbut does not seem to provide the `d3dcompiler_XY.dll`. Therefore,\nwe need to adjust the extra Qt DLL collection to consider the\nlatter an optional dependency whose absence does not preclude\nthe collection of the ANGLE DLL group.\n\nRework the `get_qt_binaries` hook utility function and its\n`_find_all_or_none` helper to peform collection based on a list\nof mandatory and a list of optional patterns, instead of a single\nlist and number of expected matches (since up until now, all\nmatches were always expected to be found).",
        "code": "def _find_all_or_none(qt_library_info, mandatory_dll_patterns, optional_dll_patterns=None):\n    \n    optional_dll_patterns = optional_dll_patterns or []\n\n    # Resolve path to the the corresponding python package (actually, its parent directory). Used to preserve directory\n    # structure when DLLs are collected from the python package (e.g., PyPI wheels).\n    package_parent_path = pathlib.Path(qt_library_info.package_location).resolve().parent\n\n    # In PyQt5/PyQt6, the DLLs we are looking for are located in location['BinariesPath'], whereas in PySide2/PySide6,\n    # they are located in location['PrefixPath'].\n    dll_path = qt_library_info.location['BinariesPath' if qt_library_info.is_pyqt else 'PrefixPath']\n    dll_path = pathlib.Path(dll_path).resolve()\n\n    # Helper for processing single DLL pattern",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 111,
        "n_words": 81,
        "vocab_size": 58,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 100,
        "n_ast_nodes": 105,
        "n_identifiers": 13,
        "d_id": 77505,
        "documentation": {
            "docstring": "\n    Try to find Qt DLLs from the specified mandatory pattern list. If all mandatory patterns resolve to DLLs, collect\n    them all, as well as any DLLs from the optional pattern list. If a mandatory pattern fails to resolve to a DLL,\n    return an empty list.\n\n    This allows all-or-none collection of particular groups of Qt DLLs that may or may not be available.\n    ",
            "n_words": 62,
            "vocab_size": 42,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 208123,
        "commit_id": "1c4ff33bd22cf94e297bd6449a06b5a30c2c1fbc",
        "repo": "celery",
        "path": "t/unit/tasks/test_canvas.py",
        "file_name": "test_canvas.py",
        "fun_name": "test_double_stamping",
        "commit_message": "Canvas Header Stamping (#7384)\n\n* Strip down the header-stamping PR to the basics.\r\n\r\n* Serialize groups.\r\n\r\n* Add groups to result backend meta data.\r\n\r\n* Fix spelling mistake.\r\n\r\n* Revert changes to canvas.py\r\n\r\n* Revert changes to app/base.py\r\n\r\n* Add stamping implementation to canvas.py\r\n\r\n* Send task to AMQP with groups.\r\n\r\n* Successfully pass single group to result.\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* First draft of the visitor API.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fixed lint and elements\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* type -> isinstance\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Redo header stamping (#7341)\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fixed lint and elements\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* type -> isinstance\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* Added stamping mechanism\r\n\r\n* Manual stamping improved\r\n\r\n* flake8 fixed\r\n\r\n* Added subtests\r\n\r\n* Add comma.\r\n\r\n* Moved groups to stamps\r\n\r\n* Fixed chord and added test for that\r\n\r\n* Strip down the header-stamping PR to the basics.\r\n\r\n* Serialize groups.\r\n\r\n* Add groups to result backend meta data.\r\n\r\n* Fix spelling mistake.\r\n\r\n* Revert changes to canvas.py\r\n\r\n* Revert changes to app/base.py\r\n\r\n* Add stamping implementation to canvas.py\r\n\r\n* Send task to AMQP with groups.\r\n\r\n* Successfully pass single group to result.\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* First draft of the visitor API.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* Fixed lint and elements\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* type -> isinstance\r\n\r\n* Added stamping mechanism\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Manual stamping improved\r\n\r\n* fail_ci_if_error uncommented\r\n\r\n* flake8 fixed\r\n\r\n* Added subtests\r\n\r\n* Changes\r\n\r\n* Add comma.\r\n\r\n* Fixed chord and added test for that\r\n\r\n* canvas.py fixed\r\n\r\n* Test chord.py fixed\r\n\r\n* Fixed stamped_headers\r\n\r\n* collections import fixed\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* collections import fixed\r\n\r\n* Update celery/backends/base.py\r\n\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* ampq.py fixed\r\n\r\n* Refrain from using deprecated import path.\r\n\r\n* Fix test_complex_chain regression.\r\n\r\nWhenever we stamp a group we need to freeze it first if it wasn't already frozen.\r\nSomewhere along the line, the group id changed because we were freezing twice.\r\nThis commit places the stamping operation after preparing the chain's steps which fixes the problem somehow.\r\n\r\nWe don't know why yet.\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed issues with maybe_list. Add documentation\r\n\r\n* Fixed potential issue with integration tests\r\n\r\n* Fixed issues with _regen\r\n\r\n* Fixed issues with _regen\r\n\r\n* Fixed test_generator issues\r\n\r\n* Fixed _regen stamping\r\n\r\n* Fixed _regen stamping\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Update docs/userguide/canvas.rst\r\n\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* Fixed Couchbase\r\n\r\n* Better stamping intro\r\n\r\n* New GroupVisitor example\r\n\r\n* Adjust documentation.\r\n\r\nCo-authored-by: Naomi Elstein <naomi.els@omerkatz.com>\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Asif Saif Uddin <auvipy@gmail.com>\r\nCo-authored-by: Omer Katz <omer.katz@kcg.tech>",
        "code": "def test_double_stamping(self, subtests):\n        \n        self.app.conf.task_always_eager = True\n        self.app.conf.task_store_eager_result = True\n        self.app.conf.result_extended = True\n\n        sig_1 = self.add.s(2, 2)\n        sig_1.stamp(stamp1=\"stamp1\")\n        sig_1.stamp(stamp2=\"stamp2\")\n        sig_1_res = sig_1.freeze()\n        sig_1.apply()\n\n        with subtests.test(\"sig_1_res is stamped with stamp1\", stamp1=[\"stamp1\"]):\n            assert sig_1_res._get_task_meta()[\"stamp1\"] == [\"stamp1\"]\n\n        with subtests.test(\"sig_1_res is stamped with stamp2\", stamp2=[\"stamp2\"]):\n            assert sig_1_res._get_task_meta()[\"stamp2\"] == [\"stamp2\"]\n\n        with subtests.test(\"sig_1_res is stamped twice\", stamped_headers=[\"stamp2\", \"stamp1\"]):\n            assert sig_1_res._get_task_meta()[\"stamped_headers\"] == [\"stamp2\", \"stamp1\", \"groups\"]\n",
        "url": "https://github.com/celery/celery.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 12,
        "n_whitespaces": 174,
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        "complexity": 1,
        "nloc": 15,
        "token_counts": 162,
        "n_ast_nodes": 291,
        "n_identifiers": 20,
        "d_id": 52214,
        "documentation": {
            "docstring": "\n        Test manual signature stamping with two different stamps.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 60260,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/io.py",
        "file_name": "io.py",
        "fun_name": "arraylist_to_blobprotovector_str",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def arraylist_to_blobprotovector_str(arraylist):\n    \n    vec = caffe_pb2.BlobProtoVector()\n    vec.blobs.extend([array_to_blobproto(arr) for arr in arraylist])\n    return vec.SerializeToString()\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "d_id": 12051,
        "documentation": {
            "docstring": "Converts a list of arrays to a serialized blobprotovec, which could be\n    then passed to a network for processing.\n    ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 113714,
        "commit_id": "9c19236902c2c66238c75f149cf9cefa411494c9",
        "repo": "nni",
        "path": "nni/contrib/distillation/storage.py",
        "file_name": "storage.py",
        "fun_name": "cleanup",
        "commit_message": "[Compression] update distillation utils (#5215)",
        "code": "def cleanup(self):\n        \n        cleanup_filename = set(self._uid2filename.values())\n        if Path(self._cache_folder / SETTING_FILENAME).exists():\n            with Path(self._cache_folder / SETTING_FILENAME).open(mode='r') as f:\n                uid2filename: Dict[str, str] = json_tricks.load(f)\n                cleanup_filename = cleanup_filename.difference(uid2filename.values())\n        for filename in cleanup_filename:\n            filepath = self._data_folder / filename\n            if filepath.exists():\n                os.remove(str(filepath))\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
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        "n_identifiers": 24,
        "d_id": 25012,
        "documentation": {
            "docstring": "\n        Cleanup the saved files under `cache_folder`.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 104786,
        "commit_id": "1904d0c0a3a96330d9b870cdca3e9a3a137f2977",
        "repo": "datasets",
        "path": "src/datasets/dataset_dict.py",
        "file_name": "dataset_dict.py",
        "fun_name": "column_names",
        "commit_message": "Add code examples for DatasetDict (#4245)\n\n* 📝 add code examples for DatasetDict\r\n\r\n* 🖍 apply quentin review",
        "code": "def column_names(self) -> Dict[str, List[str]]:\n        \n        self._check_values_type()\n        return {k: dataset.column_names for k, dataset in self.items()}\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
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        "vocab_size": 14,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 39,
        "n_ast_nodes": 62,
        "n_identifiers": 9,
        "d_id": 21968,
        "documentation": {
            "docstring": "Names of the columns in each split of the dataset.\n\n        Example:\n\n        ```py\n        >>> from datasets import load_dataset\n        >>> ds = load_dataset(\"rotten_tomatoes\")\n        >>> ds.column_names\n        {'test': ['text', 'label'],\n         'train': ['text', 'label'],\n         'validation': ['text', 'label']}\n        ```\n        ",
            "n_words": 33,
            "vocab_size": 26,
            "n_whitespaces": 105,
            "language": "en"
        }
    },
    {
        "id": 153002,
        "commit_id": "be2716f393fddd2f669f26616f80e051fc7ceee6",
        "repo": "modin",
        "path": "modin/pandas/test/test_general.py",
        "file_name": "test_general.py",
        "fun_name": "test_merge_asof_on_variations",
        "commit_message": "TEST-#3655: Check that Modin is defaulting to Pandas. (#3656)\n\nCo-authored-by: Dmitry Chigarev <62142979+dchigarev@users.noreply.github.com>\r\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: mvashishtha <mahesh@ponder.io>",
        "code": "def test_merge_asof_on_variations():\n    \n    left = {\"a\": [1, 5, 10], \"left_val\": [\"a\", \"b\", \"c\"]}\n    left_index = [6, 8, 12]\n    right = {\"a\": [1, 2, 3, 6, 7], \"right_val\": [\"d\", \"e\", \"f\", \"g\", \"h\"]}\n    right_index = [6, 7, 8, 9, 15]\n    pandas_left, pandas_right = (\n        pandas.DataFrame(left, index=left_index),\n        pandas.DataFrame(right, index=right_index),\n    )\n    modin_left, modin_right = (\n        pd.DataFrame(left, index=left_index),\n        pd.DataFrame(right, index=right_index),\n    )\n    for on_arguments in [\n        {\"on\": \"a\"},\n        {\"left_on\": \"a\", \"right_on\": \"a\"},\n        {\"left_on\": \"a\", \"right_index\": True},\n        {\"left_index\": True, \"right_on\": \"a\"},\n        {\"left_index\": True, \"right_index\": True},\n    ]:\n        pandas_merged = pandas.merge_asof(pandas_left, pandas_right, **on_arguments)\n        with warns_that_defaulting_to_pandas():\n            modin_merged = pd.merge_asof(modin_left, modin_right, **on_arguments)\n        df_equals(pandas_merged, modin_merged)\n\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 221,
        "n_words": 93,
        "vocab_size": 68,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 226,
        "n_ast_nodes": 367,
        "n_identifiers": 19,
        "d_id": 35224,
        "documentation": {
            "docstring": "on=,left_on=,right_on=,right_index=,left_index= options match Pandas.",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 3,
            "language": "en"
        }
    },
    {
        "id": 5863,
        "commit_id": "4fb8f63181f5153b4f6778c6ef8dad61022c4f3f",
        "repo": "ludwig",
        "path": "tests/integration_tests/test_server.py",
        "file_name": "test_server.py",
        "fun_name": "train_and_predict_model",
        "commit_message": "Use tempfile to automatically garbage collect data and modeling artifacts in ludwig integration tests. (#1642)\n\n* Use tmpdir to automatically garbage collect data and modeling artifacts in ludwig integration tests.",
        "code": "def train_and_predict_model(input_features, output_features, data_csv, output_directory):\n    \n    config = {\n        \"input_features\": input_features,\n        \"output_features\": output_features,\n        \"combiner\": {\"type\": \"concat\", \"fc_size\": 14},\n        \"training\": {\"epochs\": 2},\n    }\n    model = LudwigModel(config, backend=LocalTestBackend())\n    model.train(\n        dataset=data_csv,\n        skip_save_processed_input=True,\n        skip_save_progress=True,\n        skip_save_unprocessed_output=True,\n        output_directory=output_directory,\n    )\n    model.predict(dataset=data_csv, output_directory=output_directory)\n    return model\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "token_counts": 95,
        "n_ast_nodes": 153,
        "n_identifiers": 16,
        "d_id": 859,
        "documentation": {
            "docstring": "Helper method to avoid code repetition for training a model and using it for prediction.\n\n    :param input_features: input schema\n    :param output_features: output schema\n    :param data_csv: path to data\n    :param output_directory: model output directory\n    :return: None\n    ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 19360,
        "commit_id": "def289b723e9216830c2a7b2577cb31b55710167",
        "repo": "PythonRobotics",
        "path": "PathPlanning/CubicSpline/cubic_spline_planner.py",
        "file_name": "cubic_spline_planner.py",
        "fun_name": "calc_second_derivative",
        "commit_message": "enhance cubic spline path doc (#698)\n\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cublic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc\r\n\r\n* enhance cubic spline path doc",
        "code": "def calc_second_derivative(self, x):\n        \n\n        if x < self.x[0]:\n            return None\n        elif x > self.x[-1]:\n            return None\n\n        i = self.__search_index(x)\n        dx = x - self.x[i]\n        ddy = 2.0 * self.c[i] + 6.0 * self.d[i] * dx\n        return ddy\n",
        "url": "https://github.com/AtsushiSakai/PythonRobotics.git",
        "language": "Python",
        "ast_errors": "",
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        "documentation": {
            "docstring": "\n        Calc second derivative at given x.\n\n        if x is outside the input x, return None\n\n        Returns\n        -------\n        ddy : float\n            second derivative for given x.\n        ",
            "n_words": 25,
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    },
    {
        "id": 176827,
        "commit_id": "c8fdab5d87235cbf5c2142531087fadfa653887a",
        "repo": "networkx",
        "path": "networkx/classes/multidigraph.py",
        "file_name": "multidigraph.py",
        "fun_name": "remove_edge",
        "commit_message": "Update multigraph docstrings to reflect `remove_edges_from` behavior. (#5699)\n\n* Update MG docstring to reflect rm_edges_from behavior.\r\n\r\nAlso adds example.\r\n\r\n* Update remove_edge docstring in MG and MDG.\r\n\r\n* Fix MDG examples.",
        "code": "def remove_edge(self, u, v, key=None):\n        \n        try:\n            d = self._adj[u][v]\n        except KeyError as err:\n            raise NetworkXError(f\"The edge {u}-{v} is not in the graph.\") from err\n        # remove the edge with specified data\n        if key is None:\n            d.popitem()\n        else:\n            try:\n                del d[key]\n            except KeyError as err:\n                msg = f\"The edge {u}-{v} with key {key} is not in the graph.\"\n                raise NetworkXError(msg) from err\n        if len(d) == 0:\n            # remove the key entries if last edge\n            del self._succ[u][v]\n            del self._pred[v][u]\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 259,
        "n_words": 77,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 103,
        "n_ast_nodes": 184,
        "n_identifiers": 15,
        "d_id": 42123,
        "documentation": {
            "docstring": "Remove an edge between u and v.\n\n        Parameters\n        ----------\n        u, v : nodes\n            Remove an edge between nodes u and v.\n        key : hashable identifier, optional (default=None)\n            Used to distinguish multiple edges between a pair of nodes.\n            If None, remove a single edge between u and v. If there are\n            multiple edges, removes the last edge added in terms of\n            insertion order.\n\n        Raises\n        ------\n        NetworkXError\n            If there is not an edge between u and v, or\n            if there is no edge with the specified key.\n\n        See Also\n        --------\n        remove_edges_from : remove a collection of edges\n\n        Examples\n        --------\n        >>> G = nx.MultiDiGraph()\n        >>> nx.add_path(G, [0, 1, 2, 3])\n        >>> G.remove_edge(0, 1)\n        >>> e = (1, 2)\n        >>> G.remove_edge(*e)  # unpacks e from an edge tuple\n\n        For multiple edges\n\n        >>> G = nx.MultiDiGraph()\n        >>> G.add_edges_from([(1, 2), (1, 2), (1, 2)])  # key_list returned\n        [0, 1, 2]\n\n        When ``key=None`` (the default), edges are removed in the opposite\n        order that they were added:\n\n        >>> G.remove_edge(1, 2)\n        >>> G.edges(keys=True)\n        OutMultiEdgeView([(1, 2, 0), (1, 2, 1)])\n\n        For edges with keys\n\n        >>> G = nx.MultiDiGraph()\n        >>> G.add_edge(1, 2, key=\"first\")\n        'first'\n        >>> G.add_edge(1, 2, key=\"second\")\n        'second'\n        >>> G.remove_edge(1, 2, key=\"first\")\n        >>> G.edges(keys=True)\n        OutMultiEdgeView([(1, 2, 'second')])\n\n        ",
            "n_words": 197,
            "vocab_size": 109,
            "n_whitespaces": 528,
            "language": "en"
        }
    },
    {
        "id": 216411,
        "commit_id": "5550d1823e9cb571740ae9e57b25424cfe6a919e",
        "repo": "salt",
        "path": "tests/pytests/functional/modules/win_file/test_check_perms.py",
        "file_name": "test_check_perms.py",
        "fun_name": "test_check_perms_set_owner_test_true",
        "commit_message": "Add changelong",
        "code": "def test_check_perms_set_owner_test_true(test_file):\n    \n    expected = {\n        \"comment\": \"\",\n        \"changes\": {\"owner\": \"Backup Operators\"},\n        \"name\": str(test_file),\n        \"result\": None,\n    }\n    with patch.dict(win_dacl.__opts__, {\"test\": True}):\n        result = win_file.check_perms(\n            path=str(test_file), owner=\"Backup Operators\", inheritance=None\n        )\n        assert result == expected\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 104,
        "n_words": 32,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 74,
        "n_ast_nodes": 132,
        "n_identifiers": 14,
        "d_id": 54577,
        "documentation": {
            "docstring": "\n    Test setting the owner of a file with test=True\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 133004,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/collective/collective_group/nccl_collective_group.py",
        "file_name": "nccl_collective_group.py",
        "fun_name": "_get_comm_key_send_recv",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _get_comm_key_send_recv(my_rank, my_gpu_idx, peer_rank, peer_gpu_idx):\n    \n    if my_rank < peer_rank:\n        lower_key = str(my_rank) + \"_\" + str(my_gpu_idx)\n        higher_key = str(peer_rank) + \"_\" + str(peer_gpu_idx)\n    elif my_rank > peer_rank:\n        lower_key = str(peer_rank) + \"_\" + str(peer_gpu_idx)\n        higher_key = str(my_rank) + \"_\" + str(my_gpu_idx)\n    else:\n        raise RuntimeError(\n            \"Send and recv happens on the same process. ray.util.collective \"\n            \"does not support this case as of now. Alternatively, consider \"\n            \"doing GPU to GPU memcpy?\"\n        )\n    comm_key = lower_key + \":\" + higher_key\n    return comm_key\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 173,
        "n_words": 80,
        "vocab_size": 51,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 92,
        "n_ast_nodes": 164,
        "n_identifiers": 10,
        "d_id": 29912,
        "documentation": {
            "docstring": "Return a key given source and destination ranks for p2p tasks.\n\n    The p2p key is in the following form:\n                [min_rank]_[gpu_index]:[max_rank]_[gpu_index].\n\n    Args:\n        my_rank (int): the rank of the source process.\n        my_gpu_idx (int): the source gpu index on the process.\n        peer_rank (int): the rank of the destination process.\n        peer_gpu_idx (int): the destination gpu index on the process.\n\n    Returns:\n        comm_key (str): a string key to query the communication cache.\n    ",
            "n_words": 66,
            "vocab_size": 38,
            "n_whitespaces": 128,
            "language": "en"
        }
    },
    {
        "id": 203684,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/auth/models.py",
        "file_name": "models.py",
        "fun_name": "update_last_login",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def update_last_login(sender, user, **kwargs):\n    \n    user.last_login = timezone.now()\n    user.save(update_fields=[\"last_login\"])\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 30,
        "n_ast_nodes": 52,
        "n_identifiers": 9,
        "d_id": 50509,
        "documentation": {
            "docstring": "\n    A signal receiver which updates the last_login date for\n    the user logging in.\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 257683,
        "commit_id": "e7627c3f8b241654b61f8523479c81f855102f0a",
        "repo": "haystack",
        "path": "test/document_stores/test_opensearch.py",
        "file_name": "test_opensearch.py",
        "fun_name": "test__create_document_index_wrong_mapping_raises",
        "commit_message": "Use opensearch-py in OpenSearchDocumentStore (#2691)\n\n* add Opensearch extras\r\n\r\n* let OpenSearchDocumentStore use opensearch-py\r\n\r\n* Update Documentation & Code Style\r\n\r\n* fix a bug found after adding tests\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>\r\nCo-authored-by: Sara Zan <sara.zanzottera@deepset.ai>",
        "code": "def test__create_document_index_wrong_mapping_raises(self, mocked_document_store, index):\n        \n        mocked_document_store.search_fields = [\"age\"]\n        mocked_document_store.client.indices.exists.return_value = True\n        mocked_document_store.client.indices.get.return_value = {self.index_name: index}\n        with pytest.raises(Exception, match=f\"The search_field 'age' of index '{self.index_name}' with type 'integer'\"):\n            mocked_document_store._create_document_index(self.index_name)\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 72,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 66,
        "n_ast_nodes": 115,
        "n_identifiers": 16,
        "d_id": 75113,
        "documentation": {
            "docstring": "\n        Ensure the method raises if we specify a field in `search_fields` that's not text\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 108228,
        "commit_id": "7c6c5f6215b40a27cfefb7bf21246299fd9b3a1e",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "plot",
        "commit_message": "Fix removed cross-references",
        "code": "def plot(self, *args, scalex=True, scaley=True, data=None, **kwargs):\n        \n        kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D)\n        lines = [*self._get_lines(*args, data=data, **kwargs)]\n        for line in lines:\n            self.add_line(line)\n        if scalex:\n            self._request_autoscale_view(\"x\")\n        if scaley:\n            self._request_autoscale_view(\"y\")\n        return lines\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 111,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 86,
        "n_ast_nodes": 137,
        "n_identifiers": 16,
        "d_id": 23109,
        "documentation": {
            "docstring": "\n        Plot y versus x as lines and/or markers.\n\n        Call signatures::\n\n            plot([x], y, [fmt], *, data=None, **kwargs)\n            plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n\n        The coordinates of the points or line nodes are given by *x*, *y*.\n\n        The optional parameter *fmt* is a convenient way for defining basic\n        formatting like color, marker and linestyle. It's a shortcut string\n        notation described in the *Notes* section below.\n\n        >>> plot(x, y)        # plot x and y using default line style and color\n        >>> plot(x, y, 'bo')  # plot x and y using blue circle markers\n        >>> plot(y)           # plot y using x as index array 0..N-1\n        >>> plot(y, 'r+')     # ditto, but with red plusses\n\n        You can use `.Line2D` properties as keyword arguments for more\n        control on the appearance. Line properties and *fmt* can be mixed.\n        The following two calls yield identical results:\n\n        >>> plot(x, y, 'go--', linewidth=2, markersize=12)\n        >>> plot(x, y, color='green', marker='o', linestyle='dashed',\n        ...      linewidth=2, markersize=12)\n\n        When conflicting with *fmt*, keyword arguments take precedence.\n\n\n        **Plotting labelled data**\n\n        There's a convenient way for plotting objects with labelled data (i.e.\n        data that can be accessed by index ``obj['y']``). Instead of giving\n        the data in *x* and *y*, you can provide the object in the *data*\n        parameter and just give the labels for *x* and *y*::\n\n        >>> plot('xlabel', 'ylabel', data=obj)\n\n        All indexable objects are supported. This could e.g. be a `dict`, a\n        `pandas.DataFrame` or a structured numpy array.\n\n\n        **Plotting multiple sets of data**\n\n        There are various ways to plot multiple sets of data.\n\n        - The most straight forward way is just to call `plot` multiple times.\n          Example:\n\n          >>> plot(x1, y1, 'bo')\n          >>> plot(x2, y2, 'go')\n\n        - If *x* and/or *y* are 2D arrays a separate data set will be drawn\n          for every column. If both *x* and *y* are 2D, they must have the\n          same shape. If only one of them is 2D with shape (N, m) the other\n          must have length N and will be used for every data set m.\n\n          Example:\n\n          >>> x = [1, 2, 3]\n          >>> y = np.array([[1, 2], [3, 4], [5, 6]])\n          >>> plot(x, y)\n\n          is equivalent to:\n\n          >>> for col in range(y.shape[1]):\n          ...     plot(x, y[:, col])\n\n        - The third way is to specify multiple sets of *[x]*, *y*, *[fmt]*\n          groups::\n\n          >>> plot(x1, y1, 'g^', x2, y2, 'g-')\n\n          In this case, any additional keyword argument applies to all\n          datasets. Also this syntax cannot be combined with the *data*\n          parameter.\n\n        By default, each line is assigned a different style specified by a\n        'style cycle'. The *fmt* and line property parameters are only\n        necessary if you want explicit deviations from these defaults.\n        Alternatively, you can also change the style cycle using\n        :rc:`axes.prop_cycle`.\n\n\n        Parameters\n        ----------\n        x, y : array-like or scalar\n            The horizontal / vertical coordinates of the data points.\n            *x* values are optional and default to ``range(len(y))``.\n\n            Commonly, these parameters are 1D arrays.\n\n            They can also be scalars, or two-dimensional (in that case, the\n            columns represent separate data sets).\n\n            These arguments cannot be passed as keywords.\n\n        fmt : str, optional\n            A format string, e.g. 'ro' for red circles. See the *Notes*\n            section for a full description of the format strings.\n\n            Format strings are just an abbreviation for quickly setting\n            basic line properties. All of these and more can also be\n            controlled by keyword arguments.\n\n            This argument cannot be passed as keyword.\n\n        data : indexable object, optional\n            An object with labelled data. If given, provide the label names to\n            plot in *x* and *y*.\n\n            .. note::\n                Technically there's a slight ambiguity in calls where the\n                second label is a valid *fmt*. ``plot('n', 'o', data=obj)``\n                could be ``plt(x, y)`` or ``plt(y, fmt)``. In such cases,\n                the former interpretation is chosen, but a warning is issued.\n                You may suppress the warning by adding an empty format string\n                ``plot('n', 'o', '', data=obj)``.\n\n        Returns\n        -------\n        list of `.Line2D`\n            A list of lines representing the plotted data.\n\n        Other Parameters\n        ----------------\n        scalex, scaley : bool, default: True\n            These parameters determine if the view limits are adapted to the\n            data limits. The values are passed on to\n            `~.axes.Axes.autoscale_view`.\n\n        **kwargs : `.Line2D` properties, optional\n            *kwargs* are used to specify properties like a line label (for\n            auto legends), linewidth, antialiasing, marker face color.\n            Example::\n\n            >>> plot([1, 2, 3], [1, 2, 3], 'go-', label='line 1', linewidth=2)\n            >>> plot([1, 2, 3], [1, 4, 9], 'rs', label='line 2')\n\n            If you specify multiple lines with one plot call, the kwargs apply\n            to all those lines. In case the label object is iterable, each\n            element is used as labels for each set of data.\n\n            Here is a list of available `.Line2D` properties:\n\n            %(Line2D:kwdoc)s\n\n        See Also\n        --------\n        scatter : XY scatter plot with markers of varying size and/or color (\n            sometimes also called bubble chart).\n\n        Notes\n        -----\n        **Format Strings**\n\n        A format string consists of a part for color, marker and line::\n\n            fmt = '[marker][line][color]'\n\n        Each of them is optional. If not provided, the value from the style\n        cycle is used. Exception: If ``line`` is given, but no ``marker``,\n        the data will be a line without markers.\n\n        Other combinations such as ``[color][marker][line]`` are also\n        supported, but note that their parsing may be ambiguous.\n\n        **Markers**\n\n        =============   ===============================\n        character       description\n        =============   ===============================\n        ``'.'``         point marker\n        ``','``         pixel marker\n        ``'o'``         circle marker\n        ``'v'``         triangle_down marker\n        ``'^'``         triangle_up marker\n        ``'<'``         triangle_left marker\n        ``'>'``         triangle_right marker\n        ``'1'``         tri_down marker\n        ``'2'``         tri_up marker\n        ``'3'``         tri_left marker\n        ``'4'``         tri_right marker\n        ``'8'``         octagon marker\n        ``'s'``         square marker\n        ``'p'``         pentagon marker\n        ``'P'``         plus (filled) marker\n        ``'*'``         star marker\n        ``'h'``         hexagon1 marker\n        ``'H'``         hexagon2 marker\n        ``'+'``         plus marker\n        ``'x'``         x marker\n        ``'X'``         x (filled) marker\n        ``'D'``         diamond marker\n        ``'d'``         thin_diamond marker\n        ``'|'``         vline marker\n        ``'_'``         hline marker\n        =============   ===============================\n\n        **Line Styles**\n\n        =============    ===============================\n        character        description\n        =============    ===============================\n        ``'-'``          solid line style\n        ``'--'``         dashed line style\n        ``'-.'``         dash-dot line style\n        ``':'``          dotted line style\n        =============    ===============================\n\n        Example format strings::\n\n            'b'    # blue markers with default shape\n            'or'   # red circles\n            '-g'   # green solid line\n            '--'   # dashed line with default color\n            '^k:'  # black triangle_up markers connected by a dotted line\n\n        **Colors**\n\n        The supported color abbreviations are the single letter codes\n\n        =============    ===============================\n        character        color\n        =============    ===============================\n        ``'b'``          blue\n        ``'g'``          green\n        ``'r'``          red\n        ``'c'``          cyan\n        ``'m'``          magenta\n        ``'y'``          yellow\n        ``'k'``          black\n        ``'w'``          white\n        =============    ===============================\n\n        and the ``'CN'`` colors that index into the default property cycle.\n\n        If the color is the only part of the format string, you can\n        additionally use any  `matplotlib.colors` spec, e.g. full names\n        (``'green'``) or hex strings (``'#008000'``).\n        ",
            "n_words": 1065,
            "vocab_size": 527,
            "n_whitespaces": 2954,
            "language": "en"
        }
    },
    {
        "id": 54410,
        "commit_id": "5c53517aee853a5262fd2373a4fae5a15ad72da4",
        "repo": "prefect",
        "path": "src/prefect/utilities/asyncio.py",
        "file_name": "asyncio.py",
        "fun_name": "start",
        "commit_message": "Wait for task run futures concurrently",
        "code": "async def start(self, fn, *args):\n        \n        raise RuntimeError(\"`GatherTaskGroup` does not support `start`.\")\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 16,
        "n_ast_nodes": 30,
        "n_identifiers": 5,
        "d_id": 11051,
        "documentation": {
            "docstring": "\n        Since `start` returns the result of `task_status.started()` but here we must\n        return the key instead, we just won't support this method for now.\n        ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 171781,
        "commit_id": "de6a5cc21e59e61733be1b7f8ae7d3d4e15374f2",
        "repo": "pandas",
        "path": "pandas/tests/io/pytables/test_errors.py",
        "file_name": "test_errors.py",
        "fun_name": "test_unimplemented_dtypes_table_columns",
        "commit_message": "REF: remove NDFrame._convert (#50026)",
        "code": "def test_unimplemented_dtypes_table_columns(setup_path):\n\n    with ensure_clean_store(setup_path) as store:\n\n        dtypes = [(\"date\", datetime.date(2001, 1, 2))]\n\n        # currently not supported dtypes ####\n        for n, f in dtypes:\n            df = tm.makeDataFrame()\n            df[n] = f\n            msg = re.escape(f\"[{n}] is not implemented as a table column\")\n            with pytest.raises(TypeError, match=msg):\n                store.append(f\"df1_{n}\", df)\n\n    # frame\n    df = tm.makeDataFrame()\n    df[\"obj1\"] = \"foo\"\n    df[\"obj2\"] = \"bar\"\n    df[\"datetime1\"] = datetime.date(2001, 1, 2)\n    df = df._consolidate()\n\n    with ensure_clean_store(setup_path) as store:\n        # this fails because we have a date in the object block......\n        msg = re.escape(\n            \n        )\n        with pytest.raises(TypeError, match=msg):\n            store.append(\"df_unimplemented\", df)\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 242,
        "n_words": 88,
        "vocab_size": 56,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 158,
        "n_ast_nodes": 281,
        "n_identifiers": 21,
        "d_id": 40719,
        "documentation": {
            "docstring": "Cannot serialize the column [datetime1]\nbecause its data contents are not [string] but [date] object dtype",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 161968,
        "commit_id": "0d41a799678a9ad7cd77f1e19201d570bc40fdf8",
        "repo": "numba",
        "path": "numba/np/arrayobj.py",
        "file_name": "arrayobj.py",
        "fun_name": "record_setattr",
        "commit_message": "ugly poc",
        "code": "def record_setattr(context, builder, sig, args, attr):\n    \n    typ, valty = sig.args\n    target, val = args\n\n    context.sentry_record_alignment(typ, attr)\n    offset = typ.offset(attr)\n    elemty = typ.typeof(attr)\n\n    if isinstance(elemty, types.NestedArray):\n        # TODO: assert both sides are arrays\n        dptr = cgutils.get_record_member(builder, target, offset,\n                                     context.get_data_type(elemty))\n\n        dataval_ptr = context.data_model_manager[elemty].get(builder, val, 'data')\n        dataval_ptr = builder.bitcast(dataval_ptr, context.get_data_type(elemty).as_pointer())\n        align = None if typ.aligned else 1\n        dataval = builder.load(dataval_ptr)\n        builder.store(dataval, dptr, align=align)\n    else:\n        dptr = cgutils.get_record_member(builder, target, offset,\n                                     context.get_data_type(elemty))\n        val = context.cast(builder, val, valty, elemty)\n        align = None if typ.aligned else 1\n        context.pack_value(builder, elemty, val, dptr, align=align)\n\n\n@lower_builtin('static_getitem', types.Record, types.StringLiteral)",
        "url": "https://github.com/numba/numba.git",
        "language": "Python",
        "ast_errors": "@lower_builtin('static_getitem', types.Record, types.StringLiteral)",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 260,
        "n_words": 88,
        "vocab_size": 58,
        "complexity": 4,
        "nloc": 20,
        "token_counts": 204,
        "n_ast_nodes": 325,
        "n_identifiers": 36,
        "d_id": 39113,
        "documentation": {
            "docstring": "\n    Generic setattr() implementation for records: set the given\n    record member, i.e. a scalar.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 204736,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/serializers/base.py",
        "file_name": "base.py",
        "fun_name": "getvalue",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def getvalue(self):\n        \n        if callable(getattr(self.stream, \"getvalue\", None)):\n            return self.stream.getvalue()\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 29,
        "n_ast_nodes": 50,
        "n_identifiers": 5,
        "d_id": 50864,
        "documentation": {
            "docstring": "\n        Return the fully serialized queryset (or None if the output stream is\n        not seekable).\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 221217,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/calendar.py",
        "file_name": "calendar.py",
        "fun_name": "itermonthdates",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def itermonthdates(self, year, month):\n        \n        for y, m, d in self.itermonthdays3(year, month):\n            yield datetime.date(y, m, d)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 37,
        "n_ast_nodes": 55,
        "n_identifiers": 10,
        "d_id": 56274,
        "documentation": {
            "docstring": "\n        Return an iterator for one month. The iterator will yield datetime.date\n        values and will always iterate through complete weeks, so it will yield\n        dates outside the specified month.\n        ",
            "n_words": 28,
            "vocab_size": 23,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 74545,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_streamfield.py",
        "file_name": "test_streamfield.py",
        "fun_name": "test_lazy_load",
        "commit_message": "Reformat with black",
        "code": "def test_lazy_load(self):\n        \n        with self.assertNumQueries(1):\n            # Get the instance. The StreamField should *not* load the image yet\n            instance = StreamModel.objects.get(pk=self.with_image.pk)\n\n        with self.assertNumQueries(0):\n            # Access the body. The StreamField should still not get the image.\n            body = instance.body\n\n        with self.assertNumQueries(1):\n            # Access the image item from the stream. The image is fetched now\n            body[0].value\n\n        with self.assertNumQueries(0):\n            # Everything has been fetched now, no further database queries.\n            self.assertEqual(body[0].value, self.image)\n            self.assertEqual(body[1].value, \"foo\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 202,
        "n_words": 68,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 93,
        "n_ast_nodes": 162,
        "n_identifiers": 13,
        "d_id": 16262,
        "documentation": {
            "docstring": "\n        Getting a single item should lazily load the StreamField, only\n        accessing the database once the StreamField is accessed\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 67308,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/regional/united_arab_emirates/setup.py",
        "file_name": "setup.py",
        "fun_name": "add_print_formats",
        "commit_message": "style: format code with black",
        "code": "def add_print_formats():\n\tfrappe.reload_doc(\"regional\", \"print_format\", \"detailed_tax_invoice\")\n\tfrappe.reload_doc(\"regional\", \"print_format\", \"simplified_tax_invoice\")\n\tfrappe.reload_doc(\"regional\", \"print_format\", \"tax_invoice\")\n\n\tfrappe.db.sql(\n\t\t\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 7,
        "n_words": 13,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 42,
        "n_ast_nodes": 83,
        "n_identifiers": 5,
        "d_id": 14487,
        "documentation": {
            "docstring": " update `tabPrint Format` set disabled = 0 where\n\t\tname in('Simplified Tax Invoice', 'Detailed Tax Invoice', 'Tax Invoice') ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 12206,
        "commit_id": "a3b71c7208b3cd48aa7bc978c3343a074947e3d9",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/base.py",
        "file_name": "base.py",
        "fun_name": "mixin_essential_parser",
        "commit_message": "fix(parsers): clearify flow args (#4701)",
        "code": "def mixin_essential_parser(parser):\n    \n    gp = add_arg_group(parser, title='Essential')\n    gp.add_argument(\n        '--name',\n        type=str,\n        help=,\n    )\n\n    gp.add_argument(\n        '--workspace',\n        type=str,\n        default=None,\n        help='The working directory for any IO operations in this object. '\n        'If not set, then derive from its parent `workspace`.',\n    )\n\n    from jina import __resources_path__\n\n    gp.add_argument(\n        '--log-config',\n        type=str,\n        default=os.path.join(__resources_path__, 'logging.default.yml'),\n        help='The YAML config of the logger used in this object.',\n    )\n\n    gp.add_argument(\n        '--quiet',\n        action='store_true',\n        default=False,\n        help='If set, then no log will be emitted from this object.',\n    )\n\n    gp.add_argument(\n        '--quiet-error',\n        action='store_true',\n        default=False,\n        help='If set, then exception stack information will not be added to the log',\n    )\n\n    gp.add_argument(\n        '--workspace-id',\n        type=str,\n        default=random_identity(),\n        help='the UUID for identifying the workspace. When not given a random id will be assigned.'\n        'Multiple Pod/Deployment/Flow will work under the same workspace if they share the same '\n        '`workspace-id`.'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 370,
        "n_words": 129,
        "vocab_size": 87,
        "complexity": 2,
        "nloc": 53,
        "token_counts": 150,
        "n_ast_nodes": 254,
        "n_identifiers": 20,
        "d_id": 2214,
        "documentation": {
            "docstring": "Mixing in arguments required by every module into the given parser.\n    :param parser: the parser instance to which we add arguments\n    \n    The name of this object.\n\n    This will be used in the following places:\n    - how you refer to this object in Python/YAML/CLI\n    - visualization\n    - log message header\n    - ...\n\n    When not given, then the default naming strategy will apply.\n                        ",
            "n_words": 61,
            "vocab_size": 49,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 73767,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/migrations/0027_fix_collection_path_collation.py",
        "file_name": "0027_fix_collection_path_collation.py",
        "fun_name": "set_collection_path_collation",
        "commit_message": "Reformat with black",
        "code": "def set_collection_path_collation(apps, schema_editor):\n    \n    if schema_editor.connection.vendor == \"postgresql\":\n        schema_editor.execute(\n            \n        )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 41,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 23,
        "n_ast_nodes": 43,
        "n_identifiers": 6,
        "d_id": 16099,
        "documentation": {
            "docstring": "\n    Treebeard's path comparison logic can fail on certain locales such as sk_SK, which\n    sort numbers after letters. To avoid this, we explicitly set the collation for the\n    'path' column to the (non-locale-specific) 'C' collation.\n\n    See: https://groups.google.com/d/msg/wagtail/q0leyuCnYWI/I9uDvVlyBAAJ\n    \n            ALTER TABLE wagtailcore_collection ALTER COLUMN path TYPE VARCHAR(255) COLLATE \"C\"\n        ",
            "n_words": 46,
            "vocab_size": 42,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 83125,
        "commit_id": "b729f00fc289a731c56d7f6b4afcca2878e9309e",
        "repo": "zulip",
        "path": "zerver/tests/test_upload.py",
        "file_name": "test_upload.py",
        "fun_name": "test_invalid_logo_upload",
        "commit_message": "test_upload: Uncomment subTest contexts.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def test_invalid_logo_upload(self) -> None:\n        \n        for fname in self.corrupt_files:\n            with self.subTest(fname=fname):\n                self.login(\"iago\")\n                with get_test_image_file(fname) as fp:\n                    result = self.client_post(\n                        \"/json/realm/logo\", {\"file\": fp, \"night\": orjson.dumps(self.night).decode()}\n                    )\n\n                self.assert_json_error(\n                    result, \"Could not decode image; did you upload an image file?\"\n                )\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 202,
        "n_words": 37,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 76,
        "n_ast_nodes": 136,
        "n_identifiers": 15,
        "d_id": 17597,
        "documentation": {
            "docstring": "\n        A PUT request to /json/realm/logo with an invalid file should fail.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 151925,
        "commit_id": "c2936d551b8ad6ccf7b57e2ac6cb55d8550622cf",
        "repo": "freqtrade",
        "path": "freqtrade/templates/FreqaiExampleStrategy.py",
        "file_name": "FreqaiExampleStrategy.py",
        "fun_name": "feature_engineering_standard",
        "commit_message": "improve doc, update test strats, change function names",
        "code": "def feature_engineering_standard(self, dataframe, **kwargs):\n        \n        dataframe[\"%-day_of_week\"] = dataframe[\"date\"].dt.dayofweek\n        dataframe[\"%-hour_of_day\"] = dataframe[\"date\"].dt.hour\n        return dataframe\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 68,
        "n_identifiers": 7,
        "d_id": 35167,
        "documentation": {
            "docstring": "\n        *Only functional with FreqAI enabled strategies*\n        This optional function will be called once with the dataframe of the base timeframe.\n        This is the final function to be called, which means that the dataframe entering this\n        function will contain all the features and columns created by all other\n        freqai_feature_engineering_* functions.\n\n        This function is a good place to do custom exotic feature extractions (e.g. tsfresh).\n        This function is a good place for any feature that should not be auto-expanded upon\n        (e.g. day of the week).\n\n        All features must be prepended with `%` to be recognized by FreqAI internals.\n\n        More details about feature engineering available:\n\n        https://www.freqtrade.io/en/latest/freqai-feature-engineering\n\n        :param df: strategy dataframe which will receive the features\n        usage example: dataframe[\"%-day_of_week\"] = (dataframe[\"date\"].dt.dayofweek + 1) / 7\n        ",
            "n_words": 121,
            "vocab_size": 80,
            "n_whitespaces": 220,
            "language": "en"
        }
    },
    {
        "id": 160369,
        "commit_id": "1134be2ca463d3f5d788c4c7b1dcf3ef1f9e3d33",
        "repo": "numpy",
        "path": "numpy/core/tests/test_simd.py",
        "file_name": "test_simd.py",
        "fun_name": "test_pack",
        "commit_message": "SIMD: Use universal intrinsics to implement comparison functions",
        "code": "def test_pack(self):\n        \n        if self.sfx not in (\"b16\", \"b32\", \"b64\"):\n            return\n\n        # create the vectors\n        data = self._data()\n        rdata = self._data(reverse=True)\n        vdata = self._load_b(data)\n        vrdata = self._load_b(rdata)\n\n        pack_simd = getattr(self.npyv, f\"pack_b8_{self.sfx}\")\n\n        # for scalar execution, concatenate the elements of the multiple lists\n        # into a single list (spack) and then iterate over the elements of\n        # the created list applying a mask to capture the first byte of them.\n        if self.sfx == \"b16\":\n            spack = [(i & 0xFF) for i in (list(rdata) + list(data))]\n            vpack = pack_simd(vrdata, vdata)\n        elif self.sfx == \"b32\":\n            spack = [(i & 0xFF) for i in (2*list(rdata) + 2*list(data))]\n            vpack = pack_simd(vrdata, vrdata, vdata, vdata)\n        elif self.sfx == \"b64\":\n            spack = [(i & 0xFF) for i in (4*list(rdata) + 4*list(data))]\n            vpack = pack_simd(vrdata, vrdata, vrdata, vrdata,\n                               vdata,  vdata,  vdata,  vdata)\n        assert vpack == spack\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 352,
        "n_words": 137,
        "vocab_size": 74,
        "complexity": 8,
        "nloc": 19,
        "token_counts": 207,
        "n_ast_nodes": 336,
        "n_identifiers": 17,
        "d_id": 38613,
        "documentation": {
            "docstring": "\n        Pack multiple vectors into one\n        Test intrinsics:\n            npyv_pack_b8_b16\n            npyv_pack_b8_b32\n            npyv_pack_b8_b64\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 303930,
        "commit_id": "73001e29ff22f7a5008a0b0a0e058aae22771d16",
        "repo": "core",
        "path": "homeassistant/components/mqtt/light/schema_json.py",
        "file_name": "schema_json.py",
        "fun_name": "valid_color_configuration",
        "commit_message": "Remove deprecated white_value support from MQTT light (#76848)\n\n* Remove deprecated white_value support from MQTT light\r\n\r\n* Remove deprecated white_value support from MQTT JSON light\r\n\r\n* Remove deprecated white_value support from MQTT template light",
        "code": "def valid_color_configuration(config):\n    \n    deprecated = {CONF_COLOR_TEMP, CONF_HS, CONF_RGB, CONF_XY}\n    if config[CONF_COLOR_MODE] and any(config.get(key) for key in deprecated):\n        raise vol.Invalid(f\"color_mode must not be combined with any of {deprecated}\")\n    return config\n\n\n_PLATFORM_SCHEMA_BASE = (\n    MQTT_RW_SCHEMA.extend(\n        {\n            vol.Optional(CONF_BRIGHTNESS, default=DEFAULT_BRIGHTNESS): cv.boolean,\n            vol.Optional(\n                CONF_BRIGHTNESS_SCALE, default=DEFAULT_BRIGHTNESS_SCALE\n            ): vol.All(vol.Coerce(int), vol.Range(min=1)),\n            vol.Inclusive(\n                CONF_COLOR_MODE, \"color_mode\", default=DEFAULT_COLOR_MODE\n            ): cv.boolean,\n            vol.Optional(CONF_COLOR_TEMP, default=DEFAULT_COLOR_TEMP): cv.boolean,\n            vol.Optional(CONF_EFFECT, default=DEFAULT_EFFECT): cv.boolean,\n            vol.Optional(CONF_EFFECT_LIST): vol.All(cv.ensure_list, [cv.string]),\n            vol.Optional(\n                CONF_FLASH_TIME_LONG, default=DEFAULT_FLASH_TIME_LONG\n            ): cv.positive_int,\n            vol.Optional(\n                CONF_FLASH_TIME_SHORT, default=DEFAULT_FLASH_TIME_SHORT\n            ): cv.positive_int,\n            vol.Optional(CONF_HS, default=DEFAULT_HS): cv.boolean,\n            vol.Optional(CONF_MAX_MIREDS): cv.positive_int,\n            vol.Optional(CONF_MIN_MIREDS): cv.positive_int,\n            vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string,\n            vol.Optional(CONF_OPTIMISTIC, default=DEFAULT_OPTIMISTIC): cv.boolean,\n            vol.Optional(CONF_QOS, default=DEFAULT_QOS): vol.All(\n                vol.Coerce(int), vol.In([0, 1, 2])\n            ),\n            vol.Optional(CONF_RETAIN, default=DEFAULT_RETAIN): cv.boolean,\n            vol.Optional(CONF_RGB, default=DEFAULT_RGB): cv.boolean,\n            vol.Optional(CONF_STATE_TOPIC): valid_subscribe_topic,\n            vol.Inclusive(CONF_SUPPORTED_COLOR_MODES, \"color_mode\"): vol.All(\n                cv.ensure_list,\n                [vol.In(VALID_COLOR_MODES)],\n                vol.Unique(),\n                valid_supported_color_modes,\n            ),\n            vol.Optional(CONF_XY, default=DEFAULT_XY): cv.boolean,\n        },\n    )\n    .extend(MQTT_ENTITY_COMMON_SCHEMA.schema)\n    .extend(MQTT_LIGHT_SCHEMA_SCHEMA.schema)\n)\n\n# Configuring MQTT Lights under the light platform key is deprecated in HA Core 2022.6\nPLATFORM_SCHEMA_JSON = vol.All(\n    cv.PLATFORM_SCHEMA.extend(_PLATFORM_SCHEMA_BASE.schema),\n    valid_color_configuration,\n)\n\nDISCOVERY_SCHEMA_JSON = vol.All(\n    # CONF_WHITE_VALUE is no longer supported, support was removed in 2022.9\n    cv.removed(CONF_WHITE_VALUE),\n    _PLATFORM_SCHEMA_BASE.extend({}, extra=vol.REMOVE_EXTRA),\n    valid_color_configuration,\n)\n\nPLATFORM_SCHEMA_MODERN_JSON = vol.All(\n    _PLATFORM_SCHEMA_BASE,\n    valid_color_configuration,\n)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 628,
        "n_words": 158,
        "vocab_size": 121,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 694,
        "n_identifiers": 73,
        "d_id": 102738,
        "documentation": {
            "docstring": "Test color_mode is not combined with deprecated config.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 216038,
        "commit_id": "b856d3225ef1003cbe94499dc8bd82efffabb661",
        "repo": "salt",
        "path": "tests/pytests/functional/pillar/test_gpg.py",
        "file_name": "test_gpg.py",
        "fun_name": "test_decrypt_pillar_invalid_renderer",
        "commit_message": "Add tests for gpg decryption failure option\n\nTest that:\n1. Pillar registers an error when `gpg_decrypt_must_succeed` is `True` and decryption fails\n2. The GPG renderer fails silently when `gpg_decrypt_must_succeed` is `False`\n\nAlso mock `__opts__[\"gpg_decrypt_must_succeed\"]` for gpg renderer unit pytests.",
        "code": "def test_decrypt_pillar_invalid_renderer(salt_master, grains, pillar_homedir):\n    \n    opts = salt_master.config.copy()\n    opts[\"decrypt_pillar\"] = [{\"secrets:vault\": \"gpg\"}]\n    opts[\"decrypt_pillar_default\"] = \"foo\"\n    opts[\"decrypt_pillar_renderers\"] = [\"foo\", \"bar\"]\n    pillar_obj = salt.pillar.Pillar(opts, grains, \"test\", \"base\")\n    ret = pillar_obj.compile_pillar()\n    expected = copy.deepcopy(GPG_PILLAR_ENCRYPTED)\n    expected[\"_errors\"] = [\n        \"Failed to decrypt pillar key 'secrets:vault': 'gpg' is not a valid decryption\"\n        \" renderer. Valid choices are: foo, bar\"\n    ]\n    assert ret[\"_errors\"] == expected[\"_errors\"]\n    assert ret[\"secrets\"][\"vault\"][\"foo\"] == expected[\"secrets\"][\"vault\"][\"foo\"]\n    assert ret[\"secrets\"][\"vault\"][\"bar\"] == expected[\"secrets\"][\"vault\"][\"bar\"]\n    assert ret[\"secrets\"][\"vault\"][\"baz\"] == expected[\"secrets\"][\"vault\"][\"baz\"]\n    assert ret[\"secrets\"][\"vault\"][\"qux\"] == expected[\"secrets\"][\"vault\"][\"qux\"]\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 132,
        "n_words": 73,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 185,
        "n_ast_nodes": 346,
        "n_identifiers": 16,
        "d_id": 54344,
        "documentation": {
            "docstring": "\n    Test decryption using a renderer which is not permitted. It should\n    fail, leaving the encrypted keys intact, and add an error to the pillar\n    dictionary.\n\n        decrypt_pillar_default: foo\n        decrypt_pillar_renderers:\n          - foo\n          - bar\n        decrypt_pillar:\n          - 'secrets:vault': gpg\n    ",
            "n_words": 36,
            "vocab_size": 32,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 321395,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/misc/test_editor.py",
        "file_name": "test_editor.py",
        "fun_name": "test_unreadable",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_unreadable(self, message_mock, editor, caplog, qtbot):\n        \n        editor.edit(\"\")\n        filename = pathlib.Path(editor._filename)\n        assert filename.exists()\n        filename.chmod(0o277)\n        if os.access(str(filename), os.R_OK):\n            # Docker container or similar\n            pytest.skip(\"File was still readable\")\n\n        with caplog.at_level(logging.ERROR):\n            editor._proc._proc.finished.emit(0, QProcess.ExitStatus.NormalExit)\n        assert not filename.exists()\n        msg = message_mock.getmsg(usertypes.MessageLevel.error)\n        assert msg.text.startswith(\"Failed to read back edited file: \")\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 146,
        "n_words": 43,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 119,
        "n_ast_nodes": 197,
        "n_identifiers": 35,
        "d_id": 117695,
        "documentation": {
            "docstring": "Test file handling when closing with an unreadable file.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 196325,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/holonomic/recurrence.py",
        "file_name": "recurrence.py",
        "fun_name": "RecurrenceOperators",
        "commit_message": "Updated import locations",
        "code": "def RecurrenceOperators(base, generator):\n    \n\n    ring = RecurrenceOperatorAlgebra(base, generator)\n    return (ring, ring.shift_operator)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 47825,
        "documentation": {
            "docstring": "\n    Returns an Algebra of Recurrence Operators and the operator for\n    shifting i.e. the `Sn` operator.\n    The first argument needs to be the base polynomial ring for the algebra\n    and the second argument must be a generator which can be either a\n    noncommutative Symbol or a string.\n\n    Examples\n    ========\n\n    >>> from sympy import ZZ\n    >>> from sympy import symbols\n    >>> from sympy.holonomic.recurrence import RecurrenceOperators\n    >>> n = symbols('n', integer=True)\n    >>> R, Sn = RecurrenceOperators(ZZ.old_poly_ring(n), 'Sn')\n    ",
            "n_words": 74,
            "vocab_size": 53,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 100506,
        "commit_id": "71c20252c2e747f692289cdefe80ad0d5a456ea6",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "_patch_faces",
        "commit_message": "bugfix: Preview Tool, ensure all config items are written",
        "code": "def _patch_faces(self, queue_in, queue_out, sample_size):\n        \n        logger.trace(\"Patching faces\")\n        self._converter.process(queue_in, queue_out)\n        swapped = []\n        idx = 0\n        while idx < sample_size:\n            logger.trace(\"Patching image %s of %s\", idx + 1, sample_size)\n            item = queue_out.get()\n            swapped.append(item[1])\n            logger.trace(\"Patched image %s of %s\", idx + 1, sample_size)\n            idx += 1\n        logger.trace(\"Patched faces\")\n        return swapped\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 159,
        "n_words": 48,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 91,
        "n_ast_nodes": 150,
        "n_identifiers": 14,
        "d_id": 19975,
        "documentation": {
            "docstring": " Patch faces.\n\n        Run the convert process on the swapped faces and return the patched faces.\n\n        patch_queue_in: :class:`queue.Queue`\n            The input queue for the patching process\n        queue_out: :class:`queue.Queue`\n            The output queue from the patching process\n        sample_size: int\n            The number of samples to be displayed\n\n        Returns\n        -------\n        list\n            The swapped faces patched with the selected convert settings\n        ",
            "n_words": 54,
            "vocab_size": 36,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 123121,
        "commit_id": "803b90729d25fda253011c505d0189e8e63cc039",
        "repo": "EasyOCR",
        "path": "easyocr/DBNet/DBNet.py",
        "file_name": "DBNet.py",
        "fun_name": "get_cv2_image",
        "commit_message": "add dbnet",
        "code": "def get_cv2_image(self, image):\n        \n        if isinstance(image, str):\n            if os.path.isfile(image):\n                image = cv2.imread(image, cv2.IMREAD_COLOR).astype('float32')\n            else:\n                raise FileNotFoundError(\"Cannot find {}\".format(image))\n        elif isinstance(image, np.ndarray):\n            image = image.astype('float32')\n        elif isinstance(image, PIL.Image.Image):\n            image = np.asarray(image)[:, :, ::-1]\n        else:\n            raise TypeError(\"Unsupport image format. Only path-to-file, opencv BGR image, and PIL image are supported.\")\n\n        return image\n",
        "url": "https://github.com/JaidedAI/EasyOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 175,
        "n_words": 48,
        "vocab_size": 35,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 111,
        "n_ast_nodes": 186,
        "n_identifiers": 20,
        "d_id": 27298,
        "documentation": {
            "docstring": "\n        Load or convert input to OpenCV BGR image numpy array.\n\n        Parameters\n        ----------\n        image : str, PIL.Image, or np.ndarray\n            Image to load or convert.\n\n        Raises\n        ------\n        FileNotFoundError\n            Raised when the input is a path to file (str), but the file is not found.\n        TypeError\n            Raised when the data type of the input is not supported.\n\n        Returns\n        -------\n        image : np.ndarray\n            OpenCV BGR image.\n        ",
            "n_words": 62,
            "vocab_size": 41,
            "n_whitespaces": 191,
            "language": "en"
        }
    },
    {
        "id": 279795,
        "commit_id": "2ed044d06d0ae552477672aa8b778f8edafb52f1",
        "repo": "keras",
        "path": "keras/saving/pickle_utils.py",
        "file_name": "pickle_utils.py",
        "fun_name": "serialize_model_as_bytecode",
        "commit_message": "Use new saving logic for pickling. This is somewhat cleaner since it restores the exact same model (no usage of traces). It may however be less convenient since it requires get_config() to be implemented and the use of a custom_object_scope.\n\nPiperOrigin-RevId: 474146108",
        "code": "def serialize_model_as_bytecode(model):\n    \n    # Note: we don't use a RAM path for this because zipfile cannot write\n    # to such paths.\n    temp_dir = tempfile.mkdtemp()\n    try:\n        filepath = os.path.join(temp_dir, \"model.keras\")\n        saving_lib.save_model(model, filepath)\n        with open(filepath, \"rb\") as f:\n            data = f.read()\n    except Exception as e:\n        raise e\n    else:\n        return data\n    finally:\n        tf.io.gfile.rmtree(temp_dir)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 126,
        "n_words": 49,
        "vocab_size": 44,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 75,
        "n_ast_nodes": 134,
        "n_identifiers": 21,
        "d_id": 83134,
        "documentation": {
            "docstring": "Convert a Keras Model into a bytecode representation for pickling.\n\n    Args:\n        model: Keras Model instance.\n\n    Returns:\n        Tuple that can be read by `deserialize_from_bytecode`.\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 108536,
        "commit_id": "032316bc6c7798fca6c82de24167c975f237687f",
        "repo": "matplotlib",
        "path": "tools/boilerplate.py",
        "file_name": "boilerplate.py",
        "fun_name": "boilerplate_gen",
        "commit_message": "Cleanup documentation generation for pyplot\n\n- remove the awkward `pyplot.plotting()` function, which only served\n  as a namespace to take up the docs for pyplot and output them via\n  `.. autofunction`\n- Instead generate the same information using `.. autosummary::`. We\n  have to list the desired methods here explicitly. I've added a test\n  that these are the same as previously auto-generated in the\n  `plotting()` docstring. If we change anything in pyplot, we'll be\n  notified through the test failure that we have to adapt the\n  autosummary list.\n- Removed the docstring generation logic\n  `_setup_pyplot_info_docstrings()`. Apart from generating the\n  `plotting()` docstring, this added docstrings to the pyplot colormap\n  setters. Instead, we now add these docstrings directly via\n  boilerplate.py\n\nCo-authored-by: Elliott Sales de Andrade <quantum.analyst@gmail.com>",
        "code": "def boilerplate_gen():\n    \n\n    _figure_commands = (\n        'figimage',\n        'figtext:text',\n        'gca',\n        'gci:_gci',\n        'ginput',\n        'subplots_adjust',\n        'suptitle',\n        'tight_layout',\n        'waitforbuttonpress',\n    )\n\n    # These methods are all simple wrappers of Axes methods by the same name.\n    _axes_commands = (\n        'acorr',\n        'angle_spectrum',\n        'annotate',\n        'arrow',\n        'autoscale',\n        'axhline',\n        'axhspan',\n        'axis',\n        'axline',\n        'axvline',\n        'axvspan',\n        'bar',\n        'barbs',\n        'barh',\n        'bar_label',\n        'boxplot',\n        'broken_barh',\n        'clabel',\n        'cohere',\n        'contour',\n        'contourf',\n        'csd',\n        'errorbar',\n        'eventplot',\n        'fill',\n        'fill_between',\n        'fill_betweenx',\n        'grid',\n        'hexbin',\n        'hist',\n        'stairs',\n        'hist2d',\n        'hlines',\n        'imshow',\n        'legend',\n        'locator_params',\n        'loglog',\n        'magnitude_spectrum',\n        'margins',\n        'minorticks_off',\n        'minorticks_on',\n        'pcolor',\n        'pcolormesh',\n        'phase_spectrum',\n        'pie',\n        'plot',\n        'plot_date',\n        'psd',\n        'quiver',\n        'quiverkey',\n        'scatter',\n        'semilogx',\n        'semilogy',\n        'specgram',\n        'spy',\n        'stackplot',\n        'stem',\n        'step',\n        'streamplot',\n        'table',\n        'text',\n        'tick_params',\n        'ticklabel_format',\n        'tricontour',\n        'tricontourf',\n        'tripcolor',\n        'triplot',\n        'violinplot',\n        'vlines',\n        'xcorr',\n        # pyplot name : real name\n        'sci:_sci',\n        'title:set_title',\n        'xlabel:set_xlabel',\n        'ylabel:set_ylabel',\n        'xscale:set_xscale',\n        'yscale:set_yscale',\n    )\n\n    cmappable = {\n        'contour': 'if __ret._A is not None: sci(__ret)  # noqa',\n        'contourf': 'if __ret._A is not None: sci(__ret)  # noqa',\n        'hexbin': 'sci(__ret)',\n        'scatter': 'sci(__ret)',\n        'pcolor': 'sci(__ret)',\n        'pcolormesh': 'sci(__ret)',\n        'hist2d': 'sci(__ret[-1])',\n        'imshow': 'sci(__ret)',\n        'spy': 'if isinstance(__ret, cm.ScalarMappable): sci(__ret)  # noqa',\n        'quiver': 'sci(__ret)',\n        'specgram': 'sci(__ret[-1])',\n        'streamplot': 'sci(__ret.lines)',\n        'tricontour': 'if __ret._A is not None: sci(__ret)  # noqa',\n        'tricontourf': 'if __ret._A is not None: sci(__ret)  # noqa',\n        'tripcolor': 'sci(__ret)',\n    }\n\n    for spec in _figure_commands:\n        if ':' in spec:\n            name, called_name = spec.split(':')\n        else:\n            name = called_name = spec\n        yield generate_function(name, f'Figure.{called_name}',\n                                FIGURE_METHOD_TEMPLATE)\n\n    for spec in _axes_commands:\n        if ':' in spec:\n            name, called_name = spec.split(':')\n        else:\n            name = called_name = spec\n\n        template = (AXES_CMAPPABLE_METHOD_TEMPLATE if name in cmappable else\n                    AXES_METHOD_TEMPLATE)\n        yield generate_function(name, f'Axes.{called_name}', template,\n                                sci_command=cmappable.get(name))\n\n    cmaps = (\n        'autumn',\n        'bone',\n        'cool',\n        'copper',\n        'flag',\n        'gray',\n        'hot',\n        'hsv',\n        'jet',\n        'pink',\n        'prism',\n        'spring',\n        'summer',\n        'winter',\n        'magma',\n        'inferno',\n        'plasma',\n        'viridis',\n        \"nipy_spectral\"\n    )\n    # add all the colormaps (autumn, hsv, ....)\n    for name in cmaps:\n        yield AUTOGEN_MSG\n        yield CMAP_TEMPLATE.format(name=name)\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 1350,
        "n_words": 275,
        "vocab_size": 190,
        "complexity": 7,
        "nloc": 147,
        "token_counts": 398,
        "n_ast_nodes": 780,
        "n_identifiers": 19,
        "d_id": 23247,
        "documentation": {
            "docstring": "Generator of lines for the automated part of pyplot.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 67398,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/selling/report/customer_acquisition_and_loyalty/customer_acquisition_and_loyalty.py",
        "file_name": "customer_acquisition_and_loyalty.py",
        "fun_name": "get_data_by_territory",
        "commit_message": "style: format code with black",
        "code": "def get_data_by_territory(filters, common_columns):\n\tcolumns = [\n\t\t{\n\t\t\t\"label\": \"Territory\",\n\t\t\t\"fieldname\": \"territory\",\n\t\t\t\"fieldtype\": \"Link\",\n\t\t\t\"options\": \"Territory\",\n\t\t\t\"width\": 150,\n\t\t}\n\t]\n\tcolumns += common_columns\n\n\tcustomers_in = get_customer_stats(filters, tree_view=True)\n\n\tterritory_dict = {}\n\tfor t in frappe.db.sql(\n\t\t, as_dict=1\n\t):\n\t\tterritory_dict.update({t.name: {\"parent\": t.parent_territory, \"is_group\": t.is_group}})\n\n\tdepth_map = frappe._dict()\n\tfor name, info in territory_dict.items():\n\t\tdefault = depth_map.get(info[\"parent\"]) + 1 if info[\"parent\"] else 0\n\t\tdepth_map.setdefault(name, default)\n\n\tdata = []\n\tfor name, indent in depth_map.items():\n\t\tcondition = customers_in.get(name)\n\t\tnew = customers_in[name][\"new\"] if condition else [0, 0.0]\n\t\trepeat = customers_in[name][\"repeat\"] if condition else [0, 0.0]\n\t\ttemp = {\n\t\t\t\"territory\": name,\n\t\t\t\"parent_territory\": territory_dict[name][\"parent\"],\n\t\t\t\"indent\": indent,\n\t\t\t\"new_customers\": new[0],\n\t\t\t\"repeat_customers\": repeat[0],\n\t\t\t\"total\": new[0] + repeat[0],\n\t\t\t\"new_customer_revenue\": new[1],\n\t\t\t\"repeat_customer_revenue\": repeat[1],\n\t\t\t\"total_revenue\": new[1] + repeat[1],\n\t\t\t\"bold\": 0 if indent else 1,\n\t\t}\n\t\tdata.append(temp)\n\n\tloop_data = sorted(data, key=lambda k: k[\"indent\"], reverse=True)\n\n\tfor ld in loop_data:\n\t\tif ld[\"parent_territory\"]:\n\t\t\tparent_data = [x for x in data if x[\"territory\"] == ld[\"parent_territory\"]][0]\n\t\t\tfor key in parent_data.keys():\n\t\t\t\tif key not in [\"indent\", \"territory\", \"parent_territory\", \"bold\"]:\n\t\t\t\t\tparent_data[key] += ld[key]\n\n\treturn columns, data, None, None, None, 1\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 119,
        "n_words": 166,
        "vocab_size": 112,
        "complexity": 14,
        "nloc": 47,
        "token_counts": 382,
        "n_ast_nodes": 608,
        "n_identifiers": 40,
        "d_id": 14514,
        "documentation": {
            "docstring": "SELECT name, lft, parent_territory, is_group FROM `tabTerritory` ORDER BY lft",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 176846,
        "commit_id": "23fc7568a5179c54dccd0c6f68760877f88aa4b6",
        "repo": "networkx",
        "path": "networkx/drawing/tests/test_layout.py",
        "file_name": "test_layout.py",
        "fun_name": "test_multipartite_layout_layer_order",
        "commit_message": "Recover order of layers in multipartite_layout when layers are sortable (#5705)\n\n* Add test for sorted layers.\r\n\r\n* Implement layer sorting when possible.\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\n\r\n* Add test case for non-sortable layers.\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def test_multipartite_layout_layer_order():\n    \n    G = nx.Graph()\n    for node, layer in zip((\"a\", \"b\", \"c\", \"d\", \"e\"), (2, 3, 1, 2, 4)):\n        G.add_node(node, subset=layer)\n\n    # Horizontal alignment, therefore y-coord determines layers\n    pos = nx.multipartite_layout(G, align=\"horizontal\")\n\n    # Nodes \"a\" and \"d\" are in the same layer\n    assert pos[\"a\"][-1] == pos[\"d\"][-1]\n    # positions should be sorted according to layer\n    assert pos[\"c\"][-1] < pos[\"a\"][-1] < pos[\"b\"][-1] < pos[\"e\"][-1]\n\n    # Make sure that multipartite_layout still works when layers are not sortable\n    G.nodes[\"a\"][\"subset\"] = \"layer_0\"  # Can't sort mixed strs/ints\n    pos_nosort = nx.multipartite_layout(G)  # smoke test: this should not raise\n    assert pos_nosort.keys() == pos.keys()\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 144,
        "n_words": 96,
        "vocab_size": 75,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 151,
        "n_ast_nodes": 257,
        "n_identifiers": 15,
        "d_id": 42138,
        "documentation": {
            "docstring": "Return the layers in sorted order if the layers of the multipartite\n    graph are sortable. See gh-5691",
            "n_words": 17,
            "vocab_size": 14,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 60561,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/cli/req_command.py",
        "file_name": "req_command.py",
        "fun_name": "trace_basic_info",
        "commit_message": "upd; format",
        "code": "def trace_basic_info(finder):\n        # type: (PackageFinder) -> None\n        \n        # Display where finder is looking for packages\n        search_scope = finder.search_scope\n        locations = search_scope.get_formatted_locations()\n        if locations:\n            logger.info(locations)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 77,
        "n_words": 24,
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        "d_id": 12210,
        "documentation": {
            "docstring": "\n        Trace basic information about the provided objects.\n        ",
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    },
    {
        "id": 200421,
        "commit_id": "24f1e7730119fe958cc8e28411f790c9a5ec04eb",
        "repo": "sympy",
        "path": "sympy/physics/continuum_mechanics/beam.py",
        "file_name": "beam.py",
        "fun_name": "draw",
        "commit_message": "Fix various typos\n\nFound via `codespell -q 3 -L aboves,aline,ans,aother,arithmetics,assum,atleast,braket,clen,declar,declars,dorder,dum,enew,fo,fro,inout,iself,ist,ket,lamda,lightyear,lightyears,nd,numer,numers,orderd,ot,pring,rcall,rever,ro,ser,siz,splitted,sring,supercedes,te,tht,unequality,upto,vas,versin,whet`",
        "code": "def draw(self, pictorial=True):\n        \n        if not numpy:\n            raise ImportError(\"To use this function numpy module is required\")\n\n        x = self.variable\n\n        # checking whether length is an expression in terms of any Symbol.\n        if isinstance(self.length, Expr):\n            l = list(self.length.atoms(Symbol))\n            # assigning every Symbol a default value of 10\n            l = {i:10 for i in l}\n            length = self.length.subs(l)\n        else:\n            l = {}\n            length = self.length\n        height = length/10\n\n        rectangles = []\n        rectangles.append({'xy':(0, 0), 'width':length, 'height': height, 'facecolor':\"brown\"})\n        annotations, markers, load_eq,load_eq1, fill = self._draw_load(pictorial, length, l)\n        support_markers, support_rectangles = self._draw_supports(length, l)\n\n        rectangles += support_rectangles\n        markers += support_markers\n\n        sing_plot = plot(height + load_eq, height + load_eq1, (x, 0, length),\n         xlim=(-height, length + height), ylim=(-length, 1.25*length), annotations=annotations,\n          markers=markers, rectangles=rectangles, line_color='brown', fill=fill, axis=False, show=False)\n\n        return sing_plot\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "n_words": 119,
        "vocab_size": 91,
        "complexity": 4,
        "nloc": 22,
        "token_counts": 226,
        "n_ast_nodes": 344,
        "n_identifiers": 35,
        "d_id": 49636,
        "documentation": {
            "docstring": "\n        Returns a plot object representing the beam diagram of the beam.\n\n        .. note::\n            The user must be careful while entering load values.\n            The draw function assumes a sign convention which is used\n            for plotting loads.\n            Given a right handed coordinate system with XYZ coordinates,\n            the beam's length is assumed to be along the positive X axis.\n            The draw function recognizes positive loads(with n>-2) as loads\n            acting along negative Y direction and positive moments acting\n            along positive Z direction.\n\n        Parameters\n        ==========\n\n        pictorial: Boolean (default=True)\n            Setting ``pictorial=True`` would simply create a pictorial (scaled) view\n            of the beam diagram not with the exact dimensions.\n            Although setting ``pictorial=False`` would create a beam diagram with\n            the exact dimensions on the plot\n\n        Examples\n        ========\n\n        .. plot::\n            :context: close-figs\n            :format: doctest\n            :include-source: True\n\n            >>> from sympy.physics.continuum_mechanics.beam import Beam\n            >>> from sympy import symbols\n            >>> R1, R2 = symbols('R1, R2')\n            >>> E, I = symbols('E, I')\n            >>> b = Beam(50, 20, 30)\n            >>> b.apply_load(10, 2, -1)\n            >>> b.apply_load(R1, 10, -1)\n            >>> b.apply_load(R2, 30, -1)\n            >>> b.apply_load(90, 5, 0, 23)\n            >>> b.apply_load(10, 30, 1, 50)\n            >>> b.apply_support(50, \"pin\")\n            >>> b.apply_support(0, \"fixed\")\n            >>> b.apply_support(20, \"roller\")\n            >>> p = b.draw()\n            >>> p\n            Plot object containing:\n            [0]: cartesian line: 25*SingularityFunction(x, 5, 0) - 25*SingularityFunction(x, 23, 0)\n            + SingularityFunction(x, 30, 1) - 20*SingularityFunction(x, 50, 0)\n            - SingularityFunction(x, 50, 1) + 5 for x over (0.0, 50.0)\n            [1]: cartesian line: 5 for x over (0.0, 50.0)\n            >>> p.show()\n\n        ",
            "n_words": 234,
            "vocab_size": 153,
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            "language": "en"
        }
    },
    {
        "id": 65905,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/doctype/student_leave_application/student_leave_application.py",
        "file_name": "student_leave_application.py",
        "fun_name": "get_number_of_leave_days",
        "commit_message": "style: format code with black",
        "code": "def get_number_of_leave_days(from_date, to_date, holiday_list):\n\tnumber_of_days = date_diff(to_date, from_date) + 1\n\n\tholidays = frappe.db.sql(\n\t\t,\n\t\t(from_date, to_date, holiday_list),\n\t)[0][0]\n\n\tnumber_of_days = flt(number_of_days) - flt(holidays)\n\n\treturn number_of_days\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
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        "token_counts": 57,
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        "n_identifiers": 11,
        "d_id": 14052,
        "documentation": {
            "docstring": "\n\t\tSELECT\n\t\t\tCOUNT(DISTINCT holiday_date)\n\t\tFROM `tabHoliday` h1,`tabHoliday List` h2\n\t\tWHERE\n\t\t\th1.parent = h2.name and\n\t\t\th1.holiday_date between %s and %s and\n\t\t\th2.name = %s",
            "n_words": 22,
            "vocab_size": 16,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 218447,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/inspect.py",
        "file_name": "inspect.py",
        "fun_name": "getgeneratorlocals",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getgeneratorlocals(generator):\n    \n\n    if not isgenerator(generator):\n        raise TypeError(\"{!r} is not a Python generator\".format(generator))\n\n    frame = getattr(generator, \"gi_frame\", None)\n    if frame is not None:\n        return generator.gi_frame.f_locals\n    else:\n        return {}\n\n\n# ------------------------------------------------ coroutine introspection\n\nCORO_CREATED = 'CORO_CREATED'\nCORO_RUNNING = 'CORO_RUNNING'\nCORO_SUSPENDED = 'CORO_SUSPENDED'\nCORO_CLOSED = 'CORO_CLOSED'\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
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        "d_id": 55315,
        "documentation": {
            "docstring": "\n    Get the mapping of generator local variables to their current values.\n\n    A dict is returned, with the keys the local variable names and values the\n    bound values.",
            "n_words": 27,
            "vocab_size": 22,
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            "language": "en"
        }
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    {
        "id": 203668,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/auth/middleware.py",
        "file_name": "middleware.py",
        "fun_name": "_remove_invalid_user",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _remove_invalid_user(self, request):\n        \n        try:\n            stored_backend = load_backend(\n                request.session.get(auth.BACKEND_SESSION_KEY, \"\")\n            )\n        except ImportError:\n            # backend failed to load\n            auth.logout(request)\n        else:\n            if isinstance(stored_backend, RemoteUserBackend):\n                auth.logout(request)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
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        "n_identifiers": 13,
        "d_id": 50501,
        "documentation": {
            "docstring": "\n        Remove the current authenticated user in the request which is invalid\n        but only if the user is authenticated via the RemoteUserBackend.\n        ",
            "n_words": 21,
            "vocab_size": 15,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 131087,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tests/aws/test_aws_batch_tag_update.py",
        "file_name": "test_aws_batch_tag_update.py",
        "fun_name": "batch_test",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def batch_test(num_threads, delay):\n    \n    with mock.patch(\n        \"ray.autoscaler._private.aws.node_provider.make_ec2_client\"\n    ), mock.patch.object(AWSNodeProvider, \"_create_tags\", mock_create_tags):\n        provider = AWSNodeProvider(\n            provider_config={\"region\": \"nowhere\"}, cluster_name=\"default\"\n        )\n        provider.batch_counter = 0\n        provider.tag_update_counter = 0\n        provider.tag_cache = {str(x): {} for x in range(num_threads)}\n\n        threads = []\n        for x in range(num_threads):\n            thread = threading.Thread(\n                target=provider.set_node_tags, args=(str(x), {\"foo\": \"bar\"})\n            )\n            threads.append(thread)\n\n        for thread in threads:\n            thread.start()\n            time.sleep(delay)\n        for thread in threads:\n            thread.join()\n\n        return provider.batch_counter, provider.tag_update_counter\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 239,
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        "complexity": 5,
        "nloc": 22,
        "token_counts": 154,
        "n_ast_nodes": 256,
        "n_identifiers": 29,
        "d_id": 29474,
        "documentation": {
            "docstring": "Run AWSNodeProvider.set_node_tags in several threads, with a\n    specified delay between thread launches.\n\n    Return the number of batches of tag updates and the number of tags\n    updated.\n    ",
            "n_words": 26,
            "vocab_size": 22,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 256204,
        "commit_id": "a59bca366174d9c692fa19750c24d65f47660ef7",
        "repo": "haystack",
        "path": "haystack/modeling/data_handler/input_features.py",
        "file_name": "input_features.py",
        "fun_name": "sample_to_features_text",
        "commit_message": "Apply black formatting (#2115)\n\n* Testing black on ui/\r\n\r\n* Applying black on docstores\r\n\r\n* Add latest docstring and tutorial changes\r\n\r\n* Create a single GH action for Black and docs to reduce commit noise to the minimum, slightly refactor the OpenAPI action too\r\n\r\n* Remove comments\r\n\r\n* Relax constraints on pydoc-markdown\r\n\r\n* Split temporary black from the docs. Pydoc-markdown was obsolete and needs a separate PR to upgrade\r\n\r\n* Fix a couple of bugs\r\n\r\n* Add a type: ignore that was missing somehow\r\n\r\n* Give path to black\r\n\r\n* Apply Black\r\n\r\n* Apply Black\r\n\r\n* Relocate a couple of type: ignore\r\n\r\n* Update documentation\r\n\r\n* Make Linux CI run after applying Black\r\n\r\n* Triggering Black\r\n\r\n* Apply Black\r\n\r\n* Remove dependency, does not work well\r\n\r\n* Remove manually double trailing commas\r\n\r\n* Update documentation\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def sample_to_features_text(sample, tasks, max_seq_len, tokenizer):\n    \n\n    if tokenizer.is_fast:\n        text = sample.clear_text[\"text\"]\n        # Here, we tokenize the sample for the second time to get all relevant ids\n        # This should change once we git rid of FARM's tokenize_with_metadata()\n        inputs = tokenizer(\n            text,\n            return_token_type_ids=True,\n            truncation=True,\n            truncation_strategy=\"longest_first\",\n            max_length=max_seq_len,\n            return_special_tokens_mask=True,\n        )\n\n        if (len(inputs[\"input_ids\"]) - inputs[\"special_tokens_mask\"].count(1)) != len(sample.tokenized[\"tokens\"]):\n            logger.error(\n                f\"FastTokenizer encoded sample {sample.clear_text['text']} to \"\n                f\"{len(inputs['input_ids']) - inputs['special_tokens_mask'].count(1)} tokens, which differs \"\n                f\"from number of tokens produced in tokenize_with_metadata(). \\n\"\n                f\"Further processing is likely to be wrong.\"\n            )\n    else:\n        # TODO It might be cleaner to adjust the data structure in sample.tokenized\n        tokens_a = sample.tokenized[\"tokens\"]\n        tokens_b = sample.tokenized.get(\"tokens_b\", None)\n\n        inputs = tokenizer.encode_plus(\n            tokens_a,\n            tokens_b,\n            add_special_tokens=True,\n            truncation=False,  # truncation_strategy is deprecated\n            return_token_type_ids=True,\n            is_split_into_words=False,\n        )\n\n    input_ids, segment_ids = inputs[\"input_ids\"], inputs[\"token_type_ids\"]\n\n    # The mask has 1 for real tokens and 0 for padding tokens. Only real\n    # tokens are attended to.\n    padding_mask = [1] * len(input_ids)\n\n    # Padding up to the sequence length.\n    # Normal case: adding multiple 0 to the right\n    # Special cases:\n    # a) xlnet pads on the left and uses  \"4\"  for padding token_type_ids\n    if tokenizer.__class__.__name__ == \"XLNetTokenizer\":\n        pad_on_left = True\n        segment_ids = pad(segment_ids, max_seq_len, 4, pad_on_left=pad_on_left)\n    else:\n        pad_on_left = False\n        segment_ids = pad(segment_ids, max_seq_len, 0, pad_on_left=pad_on_left)\n\n    input_ids = pad(input_ids, max_seq_len, tokenizer.pad_token_id, pad_on_left=pad_on_left)\n    padding_mask = pad(padding_mask, max_seq_len, 0, pad_on_left=pad_on_left)\n\n    assert len(input_ids) == max_seq_len\n    assert len(padding_mask) == max_seq_len\n    assert len(segment_ids) == max_seq_len\n\n    feat_dict = {\n        \"input_ids\": input_ids,\n        \"padding_mask\": padding_mask,\n        \"segment_ids\": segment_ids,\n    }\n\n    # Add Labels for different tasks\n    for task_name, task in tasks.items():\n        try:\n            label_name = task[\"label_name\"]\n            label_raw = sample.clear_text[label_name]\n            label_list = task[\"label_list\"]\n            if task[\"task_type\"] == \"classification\":\n                # id of label\n                try:\n                    label_ids = [label_list.index(label_raw)]\n                except ValueError as e:\n                    raise ValueError(f\"[Task: {task_name}] Observed label {label_raw} not in defined label_list\")\n            elif task[\"task_type\"] == \"multilabel_classification\":\n                # multi-hot-format\n                label_ids = [0] * len(label_list)\n                for l in label_raw.split(\",\"):\n                    if l != \"\":\n                        label_ids[label_list.index(l)] = 1\n            elif task[\"task_type\"] == \"regression\":\n                label_ids = [float(label_raw)]\n            else:\n                raise ValueError(task[\"task_type\"])\n        except KeyError:\n            # For inference mode we don't expect labels\n            label_ids = None\n        if label_ids is not None:\n            feat_dict[task[\"label_tensor_name\"]] = label_ids\n    return [feat_dict]\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 74800,
        "documentation": {
            "docstring": "\n    Generates a dictionary of features for a given input sample that is to be consumed by a text classification model.\n\n    :param sample: Sample object that contains human readable text and label fields from a single text classification data sample\n    :type sample: Sample\n    :param tasks: A dictionary where the keys are the names of the tasks and the values are the details of the task (e.g. label_list, metric, tensor name)\n    :type tasks: dict\n    :param max_seq_len: Sequences are truncated after this many tokens\n    :type max_seq_len: int\n    :param tokenizer: A tokenizer object that can turn string sentences into a list of tokens\n    :return: A list with one dictionary containing the keys \"input_ids\", \"padding_mask\" and \"segment_ids\" (also \"label_ids\" if not\n             in inference mode). The values are lists containing those features.\n    :rtype: list\n    ",
            "n_words": 128,
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            "language": "en"
        }
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    {
        "id": 305321,
        "commit_id": "105bb3e08264c753012f10fd35f8358c8683646d",
        "repo": "core",
        "path": "homeassistant/components/ecowitt/entity.py",
        "file_name": "entity.py",
        "fun_name": "available",
        "commit_message": "Ecowitt integration (#77441)\n\n* Add ecowitt integration\r\n\r\n* add tests\r\n\r\n* use total\r\n\r\n* use total\r\n\r\n* test coverage\r\n\r\n* Update homeassistant/components/ecowitt/__init__.py\r\n\r\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>\r\n\r\n* Update homeassistant/components/ecowitt/binary_sensor.py\r\n\r\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>\r\n\r\n* Update homeassistant/components/ecowitt/entity.py\r\n\r\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>\r\n\r\n* Update homeassistant/components/ecowitt/diagnostics.py\r\n\r\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>\r\n\r\n* add to async_on_unload\r\n\r\n* remove attr_name / unload callback\r\n\r\n* support unload platforms\r\n\r\n* using replace\r\n\r\n* address mapping\r\n\r\n* update type\r\n\r\n* mark final\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Fix bracket\r\n\r\n* Fix another bracket\r\n\r\n* Address comment\r\n\r\n* Add strings\r\n\r\n* update tests\r\n\r\n* Update homeassistant/components/ecowitt/strings.json\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* update text\r\n\r\n* Update homeassistant/components/ecowitt/strings.json\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\nCo-authored-by: Paulus Schoutsen <balloob@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "def available(self) -> bool:\n        \n        return (self.ecowitt.last_update_m + 5 * 60) > time.monotonic()\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 104111,
        "documentation": {
            "docstring": "Return whether the state is based on actual reading from device.",
            "n_words": 11,
            "vocab_size": 11,
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        }
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    {
        "id": 321077,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/commands.py",
        "file_name": "commands.py",
        "fun_name": "_get_selection_override",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def _get_selection_override(self, prev, next_, opposite):\n        \n        cmdutils.check_exclusive((prev, next_, opposite), 'pno')\n        if prev:\n            return QTabBar.SelectionBehavior.SelectLeftTab\n        elif next_:\n            return QTabBar.SelectionBehavior.SelectRightTab\n        elif opposite:\n            conf_selection = config.val.tabs.select_on_remove\n            if conf_selection == QTabBar.SelectionBehavior.SelectLeftTab:\n                return QTabBar.SelectionBehavior.SelectRightTab\n            elif conf_selection == QTabBar.SelectionBehavior.SelectRightTab:\n                return QTabBar.SelectionBehavior.SelectLeftTab\n            elif conf_selection == QTabBar.SelectionBehavior.SelectPreviousTab:\n                raise cmdutils.CommandError(\n                    \"-o is not supported with 'tabs.select_on_remove' set to \"\n                    \"'last-used'!\")\n            else:  # pragma: no cover\n                raise ValueError(\"Invalid select_on_remove value \"\n                                 \"{!r}!\".format(conf_selection))\n        return None\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 313,
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        "vocab_size": 45,
        "complexity": 7,
        "nloc": 20,
        "token_counts": 118,
        "n_ast_nodes": 194,
        "n_identifiers": 20,
        "d_id": 117512,
        "documentation": {
            "docstring": "Helper function for tab_close to get the tab to select.\n\n        Args:\n            prev: Force selecting the tab before the current tab.\n            next_: Force selecting the tab after the current tab.\n            opposite: Force selecting the tab in the opposite direction of\n                      what's configured in 'tabs.select_on_remove'.\n\n        Return:\n            QTabBar.SelectionBehavior.SelectLeftTab, QTabBar.SelectionBehavior.SelectRightTab, or None if no change\n            should be made.\n        ",
            "n_words": 54,
            "vocab_size": 37,
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        }
    },
    {
        "id": 86529,
        "commit_id": "286bf2ae7ecfdd6698d8fb1cd4753f107159d4d2",
        "repo": "sentry",
        "path": "src/sentry/apidocs/spectacular_ports.py",
        "file_name": "spectacular_ports.py",
        "fun_name": "resolve_type_hint",
        "commit_message": "ref: use dict instead of OrderedDict since sentry is >python3.6 (#39695)\n\npartially automated (especially the fixtures) also via `\\(([^]+),\r\n(.*)\\),$` -> `\\1: \\2,`",
        "code": "def resolve_type_hint(hint) -> Any:\n    \n    origin, args = _get_type_hint_origin(hint)\n    excluded_fields = get_override(hint, \"exclude_fields\", [])\n\n    if origin is None and is_basic_type(hint, allow_none=False):\n        return build_basic_type(hint)\n    elif origin is None and inspect.isclass(hint) and issubclass(hint, tuple):\n        # a convoluted way to catch NamedTuple. suggestions welcome.\n        if get_type_hints(hint):\n            properties = {k: resolve_type_hint(v) for k, v in get_type_hints(hint).items()}\n        else:\n            properties = {k: build_basic_type(OpenApiTypes.ANY) for k in hint._fields}\n        return build_object_type(properties=properties, required=properties.keys())\n    elif origin is list or hint is list:\n        return build_array_type(\n            resolve_type_hint(args[0]) if args else build_basic_type(OpenApiTypes.ANY)\n        )\n    elif origin is tuple:\n        return build_array_type(\n            schema=build_basic_type(args[0]),\n            max_length=len(args),\n            min_length=len(args),\n        )\n    elif origin is dict or origin is defaultdict:\n        schema = build_basic_type(OpenApiTypes.OBJECT)\n        if args and args[1] is not typing.Any:\n            schema[\"additionalProperties\"] = resolve_type_hint(args[1])\n        return schema\n    elif origin is set:\n        return build_array_type(resolve_type_hint(args[0]))\n    elif origin is frozenset:\n        return build_array_type(resolve_type_hint(args[0]))\n    elif origin is Literal:\n        # Literal only works for python >= 3.8 despite typing_extensions, because it\n        # behaves slightly different w.r.t. __origin__\n        schema = {\"enum\": list(args)}\n        if all(type(args[0]) is type(choice) for choice in args):\n            schema.update(build_basic_type(type(args[0])))\n        return schema\n    elif inspect.isclass(hint) and issubclass(hint, Enum):\n        schema = {\"enum\": [item.value for item in hint]}\n        mixin_base_types = [t for t in hint.__mro__ if is_basic_type(t)]\n        if mixin_base_types:\n            schema.update(build_basic_type(mixin_base_types[0]))\n        return schema\n    elif isinstance(hint, _TypedDictMeta):\n        return build_object_type(\n            properties={\n                k: resolve_type_hint(v)\n                for k, v in get_type_hints(hint).items()\n                if k not in excluded_fields\n            },\n            description=inspect.cleandoc(hint.__doc__ or \"\"),\n            required=[h for h in hint.__required_keys__ if h not in excluded_fields],\n        )\n    elif origin is Union:\n        type_args = [arg for arg in args if arg is not type(None)]  # noqa: E721\n        if len(type_args) > 1:\n            schema = {\"oneOf\": [resolve_type_hint(arg) for arg in type_args]}\n        else:\n            schema = resolve_type_hint(type_args[0])\n        if type(None) in args:\n            schema[\"nullable\"] = True\n        return schema\n    elif origin is collections.abc.Iterable:\n        return build_array_type(resolve_type_hint(args[0]))\n    elif isinstance(hint, typing._TypedDictMeta):\n        raise UnableToProceedError(\"Wrong TypedDict class, please use typing_extensions.TypedDict\")\n    else:\n        raise UnableToProceedError(hint)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 788,
        "n_words": 284,
        "vocab_size": 148,
        "complexity": 42,
        "nloc": 67,
        "token_counts": 569,
        "n_ast_nodes": 895,
        "n_identifiers": 63,
        "d_id": 18119,
        "documentation": {
            "docstring": "drf-spectacular library method modified as described above",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 107770,
        "commit_id": "1504c4d7d4ed3121c6aa0e8060325ddf1bd10d06",
        "repo": "matplotlib",
        "path": "lib/matplotlib/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "edge_centers",
        "commit_message": "DOC: fix various typos",
        "code": "def edge_centers(self):\n        \n        x0, y0, width, height = self._rect_bbox\n        w = width / 2.\n        h = height / 2.\n        xe = x0, x0 + w, x0 + width, x0 + w\n        ye = y0 + h, y0, y0 + h, y0 + height\n        transform = self._get_rotation_transform()\n        coords = transform.transform(np.array([xe, ye]).T).T\n        return coords[0], coords[1]\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 115,
        "n_words": 52,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 97,
        "n_ast_nodes": 144,
        "n_identifiers": 17,
        "d_id": 22906,
        "documentation": {
            "docstring": "\n        Midpoint of rectangle edges in data coordinates from left,\n        moving anti-clockwise.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 85390,
        "commit_id": "6aaaf5089b2c39757883179df5a8512db3b0c716",
        "repo": "sentry",
        "path": "src/sentry/eventstore/models.py",
        "file_name": "models.py",
        "fun_name": "get_event_type",
        "commit_message": "feat(perf_issues): Add `GroupEvent` and split some functionality in `Event` into a base class. (#38143)\n\nSince we can now have events with multiple groups, we can no longer rely on the `Event.group`\r\nproperty. This pr adds in a `GroupEvent` subclass that should be passed around wherever we expect an\r\nevent to have a single `Group` associated with it.\r\n\r\n`Event` has been split up into `BaseEvent` and `Event`. We will deprecate and remove uses of\r\n`group_id` and `group` in the `Event` class going forward. If we need an event with a `Group`, we\r\ncan use `build_group_events` to fetch all `GroupEvents` associated with the `Event`, or `for_group`\r\nif we just need a specific `Event`/`Group` pairing.\r\n\r\nGoing forward, the plan is to store all groups in the `groups` property. This means that error\r\nevents being sent via eventstream will have their group included in `groups` as well. We'll\r\nneed to update the errors processor in snuba to look there instead of `group_id`. This seems cleaner\r\nlong term, instead of having both `group_id` and `group_ids` passed through.\r\n\r\nTo figure out where we need to use `build_group_events` and `for_group` we can do a mix of searching\r\nthe codebase and commenting  out the `group_id` and `group` properties and see how CI goes.",
        "code": "def get_event_type(self) -> str:\n        \n        column = self._get_column_name(Columns.TYPE)\n        if column in self._snuba_data:\n            return cast(str, self._snuba_data[column])\n        return cast(str, self.data.get(\"type\", \"default\"))\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 11,
        "d_id": 17984,
        "documentation": {
            "docstring": "\n        Return the type of this event.\n\n        See ``sentry.eventtypes``.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 113659,
        "commit_id": "d68c786ff81bad19c04619d6a999ff34aaa724e7",
        "repo": "nni",
        "path": "nni/compression/pytorch/quantization/qat_quantizer.py",
        "file_name": "qat_quantizer.py",
        "fun_name": "_dequantize",
        "commit_message": "[Compression] remove pruning v1 & refactor directory (#5228)",
        "code": "def _dequantize(self, quantized_val, scale, zero_point):\n        \n        real_val = scale * (quantized_val - zero_point)\n        return real_val\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 36,
        "n_identifiers": 6,
        "d_id": 24993,
        "documentation": {
            "docstring": "\n        dequantize quantized value.\n        Because we simulate quantization in training process, all the computations still happen as float point computations, which means we\n        first quantize tensors then dequantize them. For more details, please refer to the paper.\n\n        Parameters\n        ----------\n        quantized_val : torch.Tensor\n            the quantized value to be de-quantized\n        scale : torch.Tensor\n            quantization scale\n        zero_point : torch.Tensor\n            quantization zero point\n\n        Returns\n        -------\n        Tensor\n        ",
            "n_words": 61,
            "vocab_size": 47,
            "n_whitespaces": 179,
            "language": "en"
        }
    },
    {
        "id": 266836,
        "commit_id": "871b2ca73adcba3a35551247cf839246cf121231",
        "repo": "ansible",
        "path": "lib/ansible/utils/_junit_xml.py",
        "file_name": "_junit_xml.py",
        "fun_name": "get_attributes",
        "commit_message": "Simplify existing type hints.",
        "code": "def get_attributes(self) -> dict[str, str]:\n        \n        return _attributes(\n            message=self.message,\n            type=self.type,\n        )\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 53,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 29,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 78616,
        "documentation": {
            "docstring": "Return a dictionary of attributes for this instance.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 176323,
        "commit_id": "34d9d630bb02426d297d3e20fedb7da8c3ced03a",
        "repo": "networkx",
        "path": "networkx/algorithms/assortativity/pairs.py",
        "file_name": "pairs.py",
        "fun_name": "node_attribute_xy",
        "commit_message": "MAINT: Cleanup assortativity module, remove unused variables (#5301)\n\nRemove unused variables, sort imports,\r\nraise errors instead of accepting invalid arguments silently\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def node_attribute_xy(G, attribute, nodes=None):\n    \n    if nodes is None:\n        nodes = set(G)\n    else:\n        nodes = set(nodes)\n    Gnodes = G.nodes\n    for u, nbrsdict in G.adjacency():\n        if u not in nodes:\n            continue\n        uattr = Gnodes[u].get(attribute, None)\n        if G.is_multigraph():\n            for v, keys in nbrsdict.items():\n                vattr = Gnodes[v].get(attribute, None)\n                for _ in keys:\n                    yield (uattr, vattr)\n        else:\n            for v in nbrsdict:\n                vattr = Gnodes[v].get(attribute, None)\n                yield (uattr, vattr)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 232,
        "n_words": 63,
        "vocab_size": 39,
        "complexity": 8,
        "nloc": 19,
        "token_counts": 135,
        "n_ast_nodes": 210,
        "n_identifiers": 17,
        "d_id": 41837,
        "documentation": {
            "docstring": "Returns iterator of node-attribute pairs for all edges in G.\n\n    Parameters\n    ----------\n    G: NetworkX graph\n\n    attribute: key\n       The node attribute key.\n\n    nodes: list or iterable (optional)\n        Use only edges that are incident to specified nodes.\n        The default is all nodes.\n\n    Returns\n    -------\n    (x, y): 2-tuple\n        Generates 2-tuple of (attribute, attribute) values.\n\n    Examples\n    --------\n    >>> G = nx.DiGraph()\n    >>> G.add_node(1, color=\"red\")\n    >>> G.add_node(2, color=\"blue\")\n    >>> G.add_edge(1, 2)\n    >>> list(nx.node_attribute_xy(G, \"color\"))\n    [('red', 'blue')]\n\n    Notes\n    -----\n    For undirected graphs each edge is produced twice, once for each edge\n    representation (u, v) and (v, u), with the exception of self-loop edges\n    which only appear once.\n    ",
            "n_words": 101,
            "vocab_size": 83,
            "n_whitespaces": 194,
            "language": "en"
        }
    },
    {
        "id": 248248,
        "commit_id": "d38d242411b8910dfacde1e61fd3a0ec5cbcaa66",
        "repo": "synapse",
        "path": "tests/config/test_cache.py",
        "file_name": "test_cache.py",
        "fun_name": "test_apply_cache_factor_from_config",
        "commit_message": "Reload cache factors from disk on SIGHUP (#12673)",
        "code": "def test_apply_cache_factor_from_config(self):\n        \n\n        config = {\"caches\": {\"event_cache_size\": \"10k\"}}\n        self.config.read_config(config, config_dir_path=\"\", data_dir_path=\"\")\n        self.config.resize_all_caches()\n\n        cache = LruCache(\n            max_size=self.config.event_cache_size,\n            apply_cache_factor_from_config=False,\n        )\n        add_resizable_cache(\"event_cache\", cache_resize_callback=cache.set_cache_factor)\n\n        self.assertEqual(cache.max_size, 10240)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 99,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 77,
        "n_ast_nodes": 132,
        "n_identifiers": 16,
        "d_id": 72179,
        "documentation": {
            "docstring": "Caches can disable applying cache factor updates, mainly used by\n        event cache size.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 185889,
        "commit_id": "f07684438f1d4f9f18022b1e0d21b908ca299a23",
        "repo": "textual",
        "path": "src/textual/widget.py",
        "file_name": "widget.py",
        "fun_name": "remove",
        "commit_message": "fix remove freeze",
        "code": "def remove(self) -> AwaitRemove:\n        \n\n        await_remove = self.app._remove_nodes([self])\n        return await_remove\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 22,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 45233,
        "documentation": {
            "docstring": "Remove the Widget from the DOM (effectively deleting it)\n\n        Returns:\n            AwaitRemove: An awaitable object that waits for the widget to be removed.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 318781,
        "commit_id": "fc695896dd8b0169001c438054a79e347053fac6",
        "repo": "paperless-ngx",
        "path": "src/paperless/checks.py",
        "file_name": "checks.py",
        "fun_name": "binaries_check",
        "commit_message": "Format Python code with black",
        "code": "def binaries_check(app_configs, **kwargs):\n    \n\n    error = \"Paperless can't find {}. Without it, consumption is impossible.\"\n    hint = \"Either it's not in your ${PATH} or it's not installed.\"\n\n    binaries = (settings.CONVERT_BINARY, settings.OPTIPNG_BINARY, \"tesseract\")\n\n    check_messages = []\n    for binary in binaries:\n        if shutil.which(binary) is None:\n            check_messages.append(Warning(error.format(binary), hint))\n\n    return check_messages\n\n\n@register()",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "@register()",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 85,
        "n_words": 47,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 65,
        "n_ast_nodes": 117,
        "n_identifiers": 17,
        "d_id": 116916,
        "documentation": {
            "docstring": "\n    Paperless requires the existence of a few binaries, so we do some checks\n    for those here.\n    ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 196100,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/graycode.py",
        "file_name": "graycode.py",
        "fun_name": "generate_gray",
        "commit_message": "Updated import locations",
        "code": "def generate_gray(self, **hints):\n        \n        bits = self.n\n        start = None\n        if \"start\" in hints:\n            start = hints[\"start\"]\n        elif \"rank\" in hints:\n            start = GrayCode.unrank(self.n, hints[\"rank\"])\n        if start is not None:\n            self._current = start\n        current = self.current\n        graycode_bin = gray_to_bin(current)\n        if len(graycode_bin) > self.n:\n            raise ValueError('Gray code start has length %i but should '\n            'not be greater than %i' % (len(graycode_bin), bits))\n        self._current = int(current, 2)\n        graycode_int = int(''.join(graycode_bin), 2)\n        for i in range(graycode_int, 1 << bits):\n            if self._skip:\n                self._skip = False\n            else:\n                yield self.current\n            bbtc = (i ^ (i + 1))\n            gbtc = (bbtc ^ (bbtc >> 1))\n            self._current = (self._current ^ gbtc)\n        self._current = 0\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 336,
        "n_words": 105,
        "vocab_size": 71,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 186,
        "n_ast_nodes": 303,
        "n_identifiers": 22,
        "d_id": 47600,
        "documentation": {
            "docstring": "\n        Generates the sequence of bit vectors of a Gray Code.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import GrayCode\n        >>> a = GrayCode(3)\n        >>> list(a.generate_gray())\n        ['000', '001', '011', '010', '110', '111', '101', '100']\n        >>> list(a.generate_gray(start='011'))\n        ['011', '010', '110', '111', '101', '100']\n        >>> list(a.generate_gray(rank=4))\n        ['110', '111', '101', '100']\n\n        See Also\n        ========\n\n        skip\n\n        References\n        ==========\n\n        .. [1] Knuth, D. (2011). The Art of Computer Programming,\n               Vol 4, Addison Wesley\n\n        ",
            "n_words": 65,
            "vocab_size": 49,
            "n_whitespaces": 206,
            "language": "en"
        }
    },
    {
        "id": 253415,
        "commit_id": "8c2428c9d355ca5fbc3dd90e9820ceb1cc795837",
        "repo": "mitmproxy",
        "path": "examples/contrib/webscanner_helper/watchdog.py",
        "file_name": "watchdog.py",
        "fun_name": "not_in_timeout",
        "commit_message": "[autofix.ci] apply automated fixes",
        "code": "def not_in_timeout(cls, last_triggered, timeout):\n        \n        return (\n            last_triggered is None\n            or timeout is None\n            or (time.time() - last_triggered > timeout)\n        )\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 74,
        "n_words": 20,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 32,
        "n_ast_nodes": 51,
        "n_identifiers": 5,
        "d_id": 74072,
        "documentation": {
            "docstring": "Checks if current error lies not in timeout after last trigger (potential reset of connection).",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 218115,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "_get_spec",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _get_spec(cls, fullname, path, target=None):\n        \n        # If this ends up being a namespace package, namespace_path is\n        #  the list of paths that will become its __path__\n        namespace_path = []\n        for entry in path:\n            if not isinstance(entry, (str, bytes)):\n                continue\n            finder = cls._path_importer_cache(entry)\n            if finder is not None:\n                if hasattr(finder, 'find_spec'):\n                    spec = finder.find_spec(fullname, target)\n                else:\n                    spec = cls._legacy_get_spec(fullname, finder)\n                if spec is None:\n                    continue\n                if spec.loader is not None:\n                    return spec\n                portions = spec.submodule_search_locations\n                if portions is None:\n                    raise ImportError('spec missing loader')\n                # This is possibly part of a namespace package.\n                #  Remember these path entries (if any) for when we\n                #  create a namespace package, and continue iterating\n                #  on path.\n                namespace_path.extend(portions)\n        else:\n            spec = _bootstrap.ModuleSpec(fullname, None)\n            spec.submodule_search_locations = namespace_path\n            return spec\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 510,
        "n_words": 123,
        "vocab_size": 76,
        "complexity": 8,
        "nloc": 23,
        "token_counts": 137,
        "n_ast_nodes": 224,
        "n_identifiers": 23,
        "d_id": 55141,
        "documentation": {
            "docstring": "Find the loader or namespace_path for this module/package name.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 249141,
        "commit_id": "c97042f7eef3748e17c90e48a4122389a89c4735",
        "repo": "synapse",
        "path": "tests/rest/admin/test_room.py",
        "file_name": "test_room.py",
        "fun_name": "test_list_rooms_pagination",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13469)",
        "code": "def test_list_rooms_pagination(self) -> None:\n        \n        # Create 5 test rooms\n        total_rooms = 5\n        room_ids = []\n        for _ in range(total_rooms):\n            room_id = self.helper.create_room_as(\n                self.admin_user, tok=self.admin_user_tok\n            )\n            room_ids.append(room_id)\n\n        # Set the name of the rooms so we get a consistent returned ordering\n        for idx, room_id in enumerate(room_ids):\n            self.helper.send_state(\n                room_id,\n                \"m.room.name\",\n                {\"name\": str(idx)},\n                tok=self.admin_user_tok,\n            )\n\n        # Request the list of rooms\n        returned_room_ids = []\n        start = 0\n        limit = 2\n\n        run_count = 0\n        should_repeat = True\n        while should_repeat:\n            run_count += 1\n\n            url = \"/_synapse/admin/v1/rooms?from=%d&limit=%d&order_by=%s\" % (\n                start,\n                limit,\n                \"name\",\n            )\n            channel = self.make_request(\n                \"GET\",\n                url.encode(\"ascii\"),\n                access_token=self.admin_user_tok,\n            )\n            self.assertEqual(200, channel.code, msg=channel.json_body)\n\n            self.assertTrue(\"rooms\" in channel.json_body)\n            for r in channel.json_body[\"rooms\"]:\n                returned_room_ids.append(r[\"room_id\"])\n\n            # Check that the correct number of total rooms was returned\n            self.assertEqual(channel.json_body[\"total_rooms\"], total_rooms)\n\n            # Check that the offset is correct\n            # We're only getting 2 rooms each page, so should be 2 * last run_count\n            self.assertEqual(channel.json_body[\"offset\"], 2 * (run_count - 1))\n\n            if run_count > 1:\n                # Check the value of prev_batch is correct\n                self.assertEqual(channel.json_body[\"prev_batch\"], 2 * (run_count - 2))\n\n            if \"next_batch\" not in channel.json_body:\n                # We have reached the end of the list\n                should_repeat = False\n            else:\n                # Make another query with an updated start value\n                start = channel.json_body[\"next_batch\"]\n\n        # We should've queried the endpoint 3 times\n        self.assertEqual(\n            run_count,\n            3,\n            msg=\"Should've queried 3 times for 5 rooms with limit 2 per query\",\n        )\n\n        # Check that we received all of the room ids\n        self.assertEqual(room_ids, returned_room_ids)\n\n        url = \"/_synapse/admin/v1/rooms?from=%d&limit=%d\" % (start, limit)\n        channel = self.make_request(\n            \"GET\",\n            url.encode(\"ascii\"),\n            access_token=self.admin_user_tok,\n        )\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 974,
        "n_words": 246,
        "vocab_size": 142,
        "complexity": 7,
        "nloc": 58,
        "token_counts": 329,
        "n_ast_nodes": 542,
        "n_identifiers": 33,
        "d_id": 72648,
        "documentation": {
            "docstring": "Test that we can get a full list of rooms through pagination",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 265101,
        "commit_id": "0c915f7de9612c7485da3713cc6d63f368698a5d",
        "repo": "netbox",
        "path": "netbox/dcim/svg.py",
        "file_name": "svg.py",
        "fun_name": "draw_background",
        "commit_message": "Clean up rack elevation rendering",
        "code": "def draw_background(self, face):\n        \n        x_offset = RACK_ELEVATION_BORDER_WIDTH + self.legend_width\n        url_string = '{}?{}&position={{}}'.format(\n            reverse('dcim:device_add'),\n            urlencode({\n                'site': self.rack.site.pk,\n                'location': self.rack.location.pk if self.rack.location else '',\n                'rack': self.rack.pk,\n                'face': face,\n            })\n        )\n\n        for ru in range(0, self.rack.u_height):\n            y_offset = RACK_ELEVATION_BORDER_WIDTH + ru * self.unit_height\n            text_coords = (\n                x_offset + self.unit_width / 2,\n                y_offset + self.unit_height / 2\n            )\n\n            link = Hyperlink(href=url_string.format(ru), target='_blank')\n            link.add(Rect((x_offset, y_offset), (self.unit_width, self.unit_height), class_='slot'))\n            link.add(self.drawing.text('add device', insert=text_coords, class_='add-device'))\n\n            self.drawing.add(link)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 302,
        "n_words": 67,
        "vocab_size": 53,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 187,
        "n_ast_nodes": 300,
        "n_identifiers": 31,
        "d_id": 77988,
        "documentation": {
            "docstring": "\n        Draw the rack unit placeholders which form the \"background\" of the rack elevation.\n        ",
            "n_words": 13,
            "vocab_size": 10,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 304350,
        "commit_id": "bf7239c25db06f1377a895244a906b43242c9963",
        "repo": "core",
        "path": "homeassistant/components/danfoss_air/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "update",
        "commit_message": "Improve entity type hints [d] (#77031)",
        "code": "def update(self) -> None:\n        \n        self._data.update()\n\n        self._attr_native_value = self._data.get_value(self._type)\n        if self._attr_native_value is None:\n            _LOGGER.debug(\"Could not get data for %s\", self._type)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 46,
        "n_ast_nodes": 78,
        "n_identifiers": 8,
        "d_id": 103157,
        "documentation": {
            "docstring": "Update the new state of the sensor.\n\n        This is done through the DanfossAir object that does the actual\n        communication with the Air CCM.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 63105,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "compatible_platforms",
        "commit_message": "upd; format",
        "code": "def compatible_platforms(provided, required):\n    \n    if provided is None or required is None or provided == required:\n        # easy case\n        return True\n\n    # Mac OS X special cases\n    reqMac = macosVersionString.match(required)\n    if reqMac:\n        provMac = macosVersionString.match(provided)\n\n        # is this a Mac package?\n        if not provMac:\n            # this is backwards compatibility for packages built before\n            # setuptools 0.6. All packages built after this point will\n            # use the new macosx designation.\n            provDarwin = darwinVersionString.match(provided)\n            if provDarwin:\n                dversion = int(provDarwin.group(1))\n                macosversion = \"%s.%s\" % (reqMac.group(1), reqMac.group(2))\n                if dversion == 7 and macosversion >= \"10.3\" or \\\n                        dversion == 8 and macosversion >= \"10.4\":\n                    return True\n            # egg isn't macosx or legacy darwin\n            return False\n\n        # are they the same major version and machine type?\n        if provMac.group(1) != reqMac.group(1) or \\\n                provMac.group(3) != reqMac.group(3):\n            return False\n\n        # is the required OS major update >= the provided one?\n        if int(provMac.group(2)) > int(reqMac.group(2)):\n            return False\n\n        return True\n\n    # XXX Linux and other platforms' special cases should go here\n    return False\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 455,
        "n_words": 163,
        "vocab_size": 95,
        "complexity": 14,
        "nloc": 22,
        "token_counts": 168,
        "n_ast_nodes": 281,
        "n_identifiers": 13,
        "d_id": 13149,
        "documentation": {
            "docstring": "Can code for the `provided` platform run on the `required` platform?\n\n    Returns true if either platform is ``None``, or the platforms are equal.\n\n    XXX Needs compatibility checks for Linux and other unixy OSes.\n    ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 60536,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/cli/parser.py",
        "file_name": "parser.py",
        "fun_name": "option_list_all",
        "commit_message": "upd; format",
        "code": "def option_list_all(self):\n        # type: () -> List[optparse.Option]\n        \n        res = self.option_list[:]\n        for i in self.option_groups:\n            res.extend(i.option_list)\n\n        return res\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 31,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 12198,
        "documentation": {
            "docstring": "Get a list of all options, including those in option groups.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 218544,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ipaddress.py",
        "file_name": "ipaddress.py",
        "fun_name": "is_private",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def is_private(self):\n        \n        return (self.network_address.is_private and\n                self.broadcast_address.is_private)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 20,
        "n_ast_nodes": 34,
        "n_identifiers": 4,
        "d_id": 55379,
        "documentation": {
            "docstring": "Test if this address is allocated for private networks.\n\n        Returns:\n            A boolean, True if the address is reserved per\n            iana-ipv4-special-registry or iana-ipv6-special-registry.\n\n        ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 124651,
        "commit_id": "b3878e26d765e28dd7c69abadbd856181037db97",
        "repo": "ray",
        "path": "python/ray/tune/impl/tuner_internal.py",
        "file_name": "tuner_internal.py",
        "fun_name": "_get_tune_run_arguments",
        "commit_message": "[AIR] Fix `ResourceChangingScheduler` not working with AIR (#26307)\n\nThis PR ensures that the new trial resources set by `ResourceChangingScheduler` are respected by the train loop logic by modifying the scaling config to match. Previously, even though trials had their resources updated, the scaling config was not modified which lead to eg. new workers not being spawned in the `DataParallelTrainer` even though resources were available.\r\n\r\nIn order to accomplish this, `ScalingConfigDataClass` is updated to allow equality comparisons with other `ScalingConfigDataClass`es (using the underlying PGF) and to create a `ScalingConfigDataClass` from a PGF.\r\n\r\nPlease note that this is an internal only change intended to actually make `ResourceChangingScheduler` work. In the future, `ResourceChangingScheduler` should be updated to operate on `ScalingConfigDataClass`es instead of PGFs as it is now. That will require a deprecation cycle.",
        "code": "def _get_tune_run_arguments(self) -> Dict[str, Any]:\n        \n        return dict(\n            mode=self._tune_config.mode,\n            metric=self._tune_config.metric,\n            callbacks=self._run_config.callbacks,\n            sync_config=self._run_config.sync_config,\n            stop=self._run_config.stop,\n            max_failures=(\n                self._run_config.failure_config.max_failures\n                if self._run_config.failure_config\n                else 0\n            ),\n            keep_checkpoints_num=(\n                self._run_config.checkpoint_config.num_to_keep\n                if self._run_config.checkpoint_config\n                else None\n            ),\n            checkpoint_score_attr=(\n                self._run_config.checkpoint_config._tune_legacy_checkpoint_score_attr\n                if self._run_config.checkpoint_config\n                else None\n            ),\n            _experiment_checkpoint_dir=self._experiment_checkpoint_dir,\n            raise_on_failed_trial=False,\n            fail_fast=(\n                self._run_config.failure_config.fail_fast\n                if self._run_config.failure_config\n                else False\n            ),\n            verbose=self._run_config.verbose,\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 421,
        "n_words": 44,
        "vocab_size": 32,
        "complexity": 5,
        "nloc": 32,
        "token_counts": 155,
        "n_ast_nodes": 220,
        "n_identifiers": 24,
        "d_id": 27646,
        "documentation": {
            "docstring": "Get tune.run arguments common for both new and resumed runs.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 331584,
        "commit_id": "cdcd0a92ca8a3dc120336a5dde1b7d6ecd5e9186",
        "repo": "pytorch-image-models",
        "path": "timm/optim/lars.py",
        "file_name": "lars.py",
        "fun_name": "step",
        "commit_message": "fix lars",
        "code": "def step(self, closure=None):\n        \n        loss = None\n        if closure is not None:\n            with torch.enable_grad():\n                loss = closure()\n\n        device = self.param_groups[0]['params'][0].device\n        one_tensor = torch.tensor(1.0, device=device)  # because torch.where doesn't handle scalars correctly\n\n        for group in self.param_groups:\n            weight_decay = group['weight_decay']\n            momentum = group['momentum']\n            dampening = group['dampening']\n            nesterov = group['nesterov']\n            trust_coeff = group['trust_coeff']\n            eps = group['eps']\n\n            for p in group['params']:\n                if p.grad is None:\n                    continue\n                grad = p.grad\n\n                # apply LARS LR adaptation, LARC clipping, weight decay\n                # ref: https://github.com/NVIDIA/apex/blob/master/apex/parallel/LARC.py\n                if weight_decay != 0 or group['always_adapt']:\n                    w_norm = p.norm(2.0)\n                    g_norm = grad.norm(2.0)\n                    trust_ratio = trust_coeff * w_norm / (g_norm + w_norm * weight_decay + eps)\n                    # FIXME nested where required since logical and/or not working in PT XLA\n                    trust_ratio = torch.where(\n                        w_norm > 0,\n                        torch.where(g_norm > 0, trust_ratio, one_tensor),\n                        one_tensor,\n                    )\n                    if group['trust_clip']:\n                        trust_ratio = torch.minimum(trust_ratio / group['lr'], one_tensor)\n                    grad.add_(p, alpha=weight_decay)\n                    grad.mul_(trust_ratio)\n\n                # apply SGD update https://github.com/pytorch/pytorch/blob/1.7/torch/optim/sgd.py#L100\n                if momentum != 0:\n                    param_state = self.state[p]\n                    if 'momentum_buffer' not in param_state:\n                        buf = param_state['momentum_buffer'] = torch.clone(grad).detach()\n                    else:\n                        buf = param_state['momentum_buffer']\n                        buf.mul_(momentum).add_(grad, alpha=1. - dampening)\n                    if nesterov:\n                        grad = grad.add(buf, alpha=momentum)\n                    else:\n                        grad = buf\n\n                p.add_(grad, alpha=-group['lr'])\n\n        return loss",
        "url": "https://github.com/huggingface/pytorch-image-models.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 947,
        "n_words": 182,
        "vocab_size": 118,
        "complexity": 11,
        "nloc": 44,
        "token_counts": 331,
        "n_ast_nodes": 534,
        "n_identifiers": 34,
        "d_id": 119869,
        "documentation": {
            "docstring": "Performs a single optimization step.\n\n        Args:\n            closure (callable, optional): A closure that reevaluates the model and returns the loss.\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 204183,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/messages/storage/session.py",
        "file_name": "session.py",
        "fun_name": "_get",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get(self, *args, **kwargs):\n        \n        return (\n            self.deserialize_messages(self.request.session.get(self.session_key)),\n            True,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 52,
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        "complexity": 1,
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        "token_counts": 35,
        "n_ast_nodes": 55,
        "n_identifiers": 9,
        "d_id": 50674,
        "documentation": {
            "docstring": "\n        Retrieve a list of messages from the request's session. This storage\n        always stores everything it is given, so return True for the\n        all_retrieved flag.\n        ",
            "n_words": 24,
            "vocab_size": 23,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 195034,
        "commit_id": "4291c8a63a3ae9e7107dda0f90fff8da3b31d29b",
        "repo": "ParlAI",
        "path": "parlai/core/params.py",
        "file_name": "params.py",
        "fun_name": "parse_known_args",
        "commit_message": "python 3.8 parser fix on args_that_override (#4507)\n\n* single dash\r\n\r\n* handle args during parsing",
        "code": "def parse_known_args(self, args=None, namespace=None, nohelp=False):\n        \n        if args is None:\n            # args default to the system args\n            args = _sys.argv[1:]\n\n        args = fix_underscores(args)\n        # handle the single dash stuff. See _handle_single_dash_addarg for info\n        actions = set()\n        for action in self._actions:\n            actions.update(action.option_strings)\n        args = self._handle_single_dash_parsearg(args, actions)\n        if nohelp:\n            # ignore help\n            args = [\n                a\n                for a in args\n                if a != '-h' and a != '--help' and a != '--helpall' and a != '--h'\n            ]\n        return super().parse_known_args(args, namespace)\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 251,
        "n_words": 77,
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        "complexity": 9,
        "nloc": 15,
        "token_counts": 107,
        "n_ast_nodes": 177,
        "n_identifiers": 17,
        "d_id": 47160,
        "documentation": {
            "docstring": "\n        Parse known args to ignore help flag.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 320852,
        "commit_id": "6c4e2810285af0698538aed9d46a99de085eb310",
        "repo": "qutebrowser",
        "path": "tests/unit/utils/test_version.py",
        "file_name": "test_version.py",
        "fun_name": "test_uptime",
        "commit_message": "pylint: Fix new unnecessary-lambda-assignment",
        "code": "def test_uptime(monkeypatch, qapp):\n    \n    monkeypatch.setattr(objects, 'qapp', qapp)\n\n    launch_time = datetime.datetime(1, 1, 1, 1, 1, 1, 1)\n    monkeypatch.setattr(qapp, \"launch_time\", launch_time, raising=False)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 1,
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        "token_counts": 90,
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        "n_identifiers": 8,
        "d_id": 117395,
        "documentation": {
            "docstring": "Test _uptime runs and check if microseconds are dropped.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 65820,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/e_commerce/shopping_cart/cart.py",
        "file_name": "cart.py",
        "fun_name": "get_address_territory",
        "commit_message": "style: format code with black",
        "code": "def get_address_territory(address_name):\n\t\n\tterritory = None\n\n\tif address_name:\n\t\taddress_fields = frappe.db.get_value(\"Address\", address_name, [\"city\", \"state\", \"country\"])\n\t\tfor value in address_fields:\n\t\t\tterritory = frappe.db.get_value(\"Territory\", value)\n\t\t\tif territory:\n\t\t\t\tbreak\n\n\treturn territory\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 18,
        "n_words": 27,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 55,
        "n_ast_nodes": 95,
        "n_identifiers": 8,
        "d_id": 14022,
        "documentation": {
            "docstring": "Tries to match city, state and country of address to existing territory",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 141204,
        "commit_id": "2a5d322e705df080e9254c9c9a3e187c1ea41c4e",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_trial_relative_logdir.py",
        "file_name": "test_trial_relative_logdir.py",
        "fun_name": "testDotsInLogdir",
        "commit_message": "[tune] Relative logdir paths in trials for ExperimentAnalysis in remote buckets (#25063)\n\nWhen running an experiment for example in the cloud and syncing to a bucket the logdir path in the trials will be changed when working with the checkpoints in the bucket. There are some workarounds, but the easier solution is to also add a rel_logdir containing the relative path to the trials/checkpoints that can handle any changes in the location of experiment results.\r\n\r\nAs discussed with @Yard1 and @krfricke\r\n\r\nCo-authored-by: Antoni Baum <antoni.baum@protonmail.com>\r\nCo-authored-by: Kai Fricke <kai@anyscale.com>",
        "code": "def testDotsInLogdir(self):\n        \n        local_dir_path = Path(\"/tmp/test_rel_dots\")\n        local_dir = str(local_dir_path)\n        if local_dir_path.exists():\n            local_dir = tempfile.mkdtemp(prefix=str(local_dir_path) + \"_\")\n        trial = Trial(trainable_name=\"rel_logdir\", local_dir=local_dir)\n\n        with self.assertRaises(ValueError):\n            trial.logdir = \"/tmp/test_rel/../dots\"\n        with self.assertRaises(ValueError):\n            trial.logdir = local_dir + \"/../\"\n\n        if shutil.rmtree.avoids_symlink_attacks:\n            if local_dir_path.exists():\n                shutil.rmtree(local_dir)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 151,
        "n_words": 36,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 100,
        "n_ast_nodes": 179,
        "n_identifiers": 19,
        "d_id": 32293,
        "documentation": {
            "docstring": "This should result in errors as dots in paths are not allowed.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 153048,
        "commit_id": "58bbcc37477866d19c8b092a0e1974a4f0baa586",
        "repo": "modin",
        "path": "modin/core/dataframe/pandas/dataframe/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "_compute_tree_reduce_metadata",
        "commit_message": "REFACTOR-#2656: Update modin to fit algebra (code only) (#3717)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>\r\nCo-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>\r\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: Rehan Durrani <rehan@ponder.io>",
        "code": "def _compute_tree_reduce_metadata(self, axis, new_parts):\n        \n        new_axes, new_axes_lengths = [0, 0], [0, 0]\n\n        new_axes[axis] = [\"__reduced__\"]\n        new_axes[axis ^ 1] = self.axes[axis ^ 1]\n\n        new_axes_lengths[axis] = [1]\n        new_axes_lengths[axis ^ 1] = self._axes_lengths[axis ^ 1]\n\n        new_dtypes = None\n        result = self.__constructor__(\n            new_parts,\n            *new_axes,\n            *new_axes_lengths,\n            new_dtypes,\n        )\n        return result\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 158,
        "n_words": 44,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 93,
        "n_ast_nodes": 140,
        "n_identifiers": 11,
        "d_id": 35232,
        "documentation": {
            "docstring": "\n        Compute the metadata for the result of reduce function.\n\n        Parameters\n        ----------\n        axis : int\n            The axis on which reduce function was applied.\n        new_parts : NumPy 2D array\n            Partitions with the result of applied function.\n\n        Returns\n        -------\n        PandasDataframe\n            Modin series (1xN frame) containing the reduced data.\n        ",
            "n_words": 45,
            "vocab_size": 36,
            "n_whitespaces": 142,
            "language": "en"
        }
    },
    {
        "id": 130722,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/exceptions.py",
        "file_name": "exceptions.py",
        "fun_name": "as_instanceof_cause",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def as_instanceof_cause(self):\n        \n\n        cause_cls = self.cause.__class__\n        if issubclass(RayTaskError, cause_cls):\n            return self  # already satisfied\n\n        if issubclass(cause_cls, RayError):\n            return self  # don't try to wrap ray internal errors\n\n        error_msg = str(self)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 88,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 74,
        "n_ast_nodes": 66,
        "n_identifiers": 10,
        "d_id": 29335,
        "documentation": {
            "docstring": "Returns an exception that is an instance of the cause's class.\n\n        The returned exception will inherit from both RayTaskError and the\n        cause class and will contain all of the attributes of the cause\n        exception.\n        ",
            "n_words": 34,
            "vocab_size": 24,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 177286,
        "commit_id": "a796f526c7ce6a7f182aee4b81b8499feabe1a45",
        "repo": "networkx",
        "path": "networkx/algorithms/isomorphism/vf2pp.py",
        "file_name": "vf2pp.py",
        "fun_name": "vf2pp_is_isomorphic",
        "commit_message": "VF2++ for Directed Graphs (#5972)\n\nModify vf2pp implementation to support directed graphs. Updates all helper\r\nfunctions and state/parameter objects to account for in/out degree.\r\n\r\nIncludes other changes such as renaming the keyword argument from\r\nnode_labels to node_label to better reflect the fact that the label kwarg expects\r\na single value.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def vf2pp_is_isomorphic(G1, G2, node_label=None, default_label=None):\n    \n    if vf2pp_isomorphism(G1, G2, node_label, default_label) is not None:\n        return True\n    return False\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 33,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 51,
        "n_identifiers": 6,
        "d_id": 42325,
        "documentation": {
            "docstring": "Examines whether G1 and G2 are isomorphic.\n\n    Parameters\n    ----------\n    G1, G2 : NetworkX Graph or MultiGraph instances.\n        The two graphs to check for isomorphism.\n\n    node_label : str, optional\n        The name of the node attribute to be used when comparing nodes.\n        The default is `None`, meaning node attributes are not considered\n        in the comparison. Any node that doesn't have the `node_label`\n        attribute uses `default_label` instead.\n\n    default_label : scalar\n        Default value to use when a node doesn't have an attribute\n        named `node_label`. Default is `None`.\n\n    Returns\n    -------\n    bool\n        True if the two graphs are isomorphic, False otherwise.\n    ",
            "n_words": 95,
            "vocab_size": 71,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 181580,
        "commit_id": "d39f3be7b3f49e6178f29fb03461a920103caa35",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_predict_proba_6",
        "commit_message": "added test to hasattr",
        "code": "def test_predict_proba_6():\n    \n\n    est = TPOTClassifier(generations=1,population_size=1, template='LogisticRegression')\n    est.fit(training_features, training_target)\n    assert hasattr(est, \"predict_proba\") #This model has predict_proba\n    est.predict_proba(training_features)\n\n    est = TPOTClassifier(generations=1,population_size=1, template='LinearSVC')\n    est.fit(training_features, training_target)\n    assert not hasattr(est, \"predict_proba\") #This model does not have predict_proba, but it hasattr shouldn't raise an error\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 39,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 74,
        "n_ast_nodes": 124,
        "n_identifiers": 11,
        "d_id": 43372,
        "documentation": {
            "docstring": "Assert that TPOT's predict_proba is exposed when available, and hidden when not.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 42540,
        "commit_id": "8a4cf5d94eb94b6427c5d1d7907ba07b119932c5",
        "repo": "nltk",
        "path": "nltk/corpus/reader/framenet.py",
        "file_name": "framenet.py",
        "fun_name": "lu",
        "commit_message": "Docstring tests (#3050)\n\n* fixed pytests\r\n\r\n* fixed more pytests\r\n\r\n* fixed more pytest and changed multiline pytest issues fixes for snowball.py and causal.py\r\n\r\n* fixed pytests (mainly multiline or rounding issues)\r\n\r\n* fixed treebank pytests, removed test for return_string=True (deprecated)\r\n\r\n* fixed destructive.py pytests, removed test for return_string=True (deprecated)\r\n\r\n* fixed pytest (rounding issues)\r\n\r\n* fixed pytest (initialised missing object)\r\n\r\n* fixed pytest (formatting issues)\r\n\r\n* fixed pytest (formatting issues)\r\n\r\n* fixed pytest (formatting issues)\r\n\r\n* added pytest +SKIP for deprecated module stanford\r\n\r\n* updated AUTHORS.md\r\n\r\n* changed docstring corrections by usage of ELLIPSIS and different roundings\r\n\r\n* fixed AUTHORS.md to be consistent\r\n\r\n* Fix framenet doctest formatting with pprint\r\n\r\n* Change docstring on MultiListBox.__init__\r\n\r\nI believe the original typo was misinterpreted and changed to something that was not originally intended.\r\n\r\nCo-authored-by: Jan Lennartz <jan.lennartz@ing.com>\r\nCo-authored-by: Tom Aarsen <37621491+tomaarsen@users.noreply.github.com>\r\nCo-authored-by: Tom Aarsen <Cubiegamedev@gmail.com>",
        "code": "def lu(self, fn_luid, ignorekeys=[], luName=None, frameID=None, frameName=None):\n        \n        # look for this LU in cache\n        if not self._lu_idx:\n            self._buildluindex()\n        OOV = object()\n        luinfo = self._lu_idx.get(fn_luid, OOV)\n        if luinfo is OOV:\n            # LU not in the index. We create a placeholder by falling back to\n            # luName, frameID, and frameName. However, this will not be listed\n            # among the LUs for its frame.\n            self._warn(\n                \"LU ID not found: {} ({}) in {} ({})\".format(\n                    luName, fn_luid, frameName, frameID\n                )\n            )\n            luinfo = AttrDict(\n                {\n                    \"_type\": \"lu\",\n                    \"ID\": fn_luid,\n                    \"name\": luName,\n                    \"frameID\": frameID,\n                    \"status\": \"Problem\",\n                }\n            )\n            f = self.frame_by_id(luinfo.frameID)\n            assert f.name == frameName, (f.name, frameName)\n            luinfo[\"frame\"] = f\n            self._lu_idx[fn_luid] = luinfo\n        elif \"_type\" not in luinfo:\n            # we only have an index entry for the LU. loading the frame will replace this.\n            f = self.frame_by_id(luinfo.frameID)\n            luinfo = self._lu_idx[fn_luid]\n        if ignorekeys:\n            return AttrDict({k: v for k, v in luinfo.items() if k not in ignorekeys})\n\n        return luinfo\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 565,
        "n_words": 152,
        "vocab_size": 99,
        "complexity": 7,
        "nloc": 30,
        "token_counts": 193,
        "n_ast_nodes": 314,
        "n_identifiers": 22,
        "d_id": 7602,
        "documentation": {
            "docstring": "\n        Access a lexical unit by its ID. luName, frameID, and frameName are used\n        only in the event that the LU does not have a file in the database\n        (which is the case for LUs with \"Problem\" status); in this case,\n        a placeholder LU is created which just contains its name, ID, and frame.\n\n\n        Usage examples:\n\n        >>> from nltk.corpus import framenet as fn\n        >>> fn.lu(256).name\n        'foresee.v'\n        >>> fn.lu(256).definition\n        'COD: be aware of beforehand; predict.'\n        >>> fn.lu(256).frame.name\n        'Expectation'\n        >>> list(map(PrettyDict, fn.lu(256).lexemes))\n        [{'POS': 'V', 'breakBefore': 'false', 'headword': 'false', 'name': 'foresee', 'order': 1}]\n\n        >>> fn.lu(227).exemplars[23] # doctest: +NORMALIZE_WHITESPACE\n        exemplar sentence (352962):\n        [sentNo] 0\n        [aPos] 59699508\n        <BLANKLINE>\n        [LU] (227) guess.v in Coming_to_believe\n        <BLANKLINE>\n        [frame] (23) Coming_to_believe\n        <BLANKLINE>\n        [annotationSet] 2 annotation sets\n        <BLANKLINE>\n        [POS] 18 tags\n        <BLANKLINE>\n        [POS_tagset] BNC\n        <BLANKLINE>\n        [GF] 3 relations\n        <BLANKLINE>\n        [PT] 3 phrases\n        <BLANKLINE>\n        [Other] 1 entry\n        <BLANKLINE>\n        [text] + [Target] + [FE]\n        <BLANKLINE>\n        When he was inside the house , Culley noticed the characteristic\n                                                      ------------------\n                                                      Content\n        <BLANKLINE>\n        he would n't have guessed at .\n        --                ******* --\n        Co                        C1 [Evidence:INI]\n         (Co=Cognizer, C1=Content)\n        <BLANKLINE>\n        <BLANKLINE>\n\n        The dict that is returned from this function will contain most of the\n        following information about the LU. Note that some LUs do not contain\n        all of these pieces of information - particularly 'totalAnnotated' and\n        'incorporatedFE' may be missing in some LUs:\n\n        - 'name'       : the name of the LU (e.g. 'merger.n')\n        - 'definition' : textual definition of the LU\n        - 'ID'         : the internal ID number of the LU\n        - '_type'      : 'lu'\n        - 'status'     : e.g. 'Created'\n        - 'frame'      : Frame that this LU belongs to\n        - 'POS'        : the part of speech of this LU (e.g. 'N')\n        - 'totalAnnotated' : total number of examples annotated with this LU\n        - 'incorporatedFE' : FE that incorporates this LU (e.g. 'Ailment')\n        - 'sentenceCount'  : a dict with the following two keys:\n                 - 'annotated': number of sentences annotated with this LU\n                 - 'total'    : total number of sentences with this LU\n\n        - 'lexemes'  : a list of dicts describing the lemma of this LU.\n           Each dict in the list contains these keys:\n\n           - 'POS'     : part of speech e.g. 'N'\n           - 'name'    : either single-lexeme e.g. 'merger' or\n                         multi-lexeme e.g. 'a little'\n           - 'order': the order of the lexeme in the lemma (starting from 1)\n           - 'headword': a boolean ('true' or 'false')\n           - 'breakBefore': Can this lexeme be separated from the previous lexeme?\n                Consider: \"take over.v\" as in::\n\n                         Germany took over the Netherlands in 2 days.\n                         Germany took the Netherlands over in 2 days.\n\n                In this case, 'breakBefore' would be \"true\" for the lexeme\n                \"over\". Contrast this with \"take after.v\" as in::\n\n                         Mary takes after her grandmother.\n                        *Mary takes her grandmother after.\n\n                In this case, 'breakBefore' would be \"false\" for the lexeme \"after\"\n\n        - 'lemmaID'    : Can be used to connect lemmas in different LUs\n        - 'semTypes'   : a list of semantic type objects for this LU\n        - 'subCorpus'  : a list of subcorpora\n           - Each item in the list is a dict containing the following keys:\n              - 'name' :\n              - 'sentence' : a list of sentences in the subcorpus\n                 - each item in the list is a dict with the following keys:\n                    - 'ID':\n                    - 'sentNo':\n                    - 'text': the text of the sentence\n                    - 'aPos':\n                    - 'annotationSet': a list of annotation sets\n                       - each item in the list is a dict with the following keys:\n                          - 'ID':\n                          - 'status':\n                          - 'layer': a list of layers\n                             - each layer is a dict containing the following keys:\n                                - 'name': layer name (e.g. 'BNC')\n                                - 'rank':\n                                - 'label': a list of labels for the layer\n                                   - each label is a dict containing the following keys:\n                                      - 'start': start pos of label in sentence 'text' (0-based)\n                                      - 'end': end pos of label in sentence 'text' (0-based)\n                                      - 'name': name of label (e.g. 'NN1')\n\n        Under the hood, this implementation looks up the lexical unit information\n        in the *frame* definition file. That file does not contain\n        corpus annotations, so the LU files will be accessed on demand if those are\n        needed. In principle, valence patterns could be loaded here too,\n        though these are not currently supported.\n\n        :param fn_luid: The id number of the lexical unit\n        :type fn_luid: int\n        :param ignorekeys: The keys to ignore. These keys will not be\n            included in the output. (optional)\n        :type ignorekeys: list(str)\n        :return: All information about the lexical unit\n        :rtype: dict\n        ",
            "n_words": 723,
            "vocab_size": 328,
            "n_whitespaces": 2239,
            "language": "en"
        }
    },
    {
        "id": 204879,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/operations.py",
        "file_name": "operations.py",
        "fun_name": "combine_expression",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def combine_expression(self, connector, sub_expressions):\n        \n        conn = \" %s \" % connector\n        return conn.join(sub_expressions)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 50952,
        "documentation": {
            "docstring": "\n        Combine a list of subexpressions into a single expression, using\n        the provided connecting operator. This is required because operators\n        can vary between backends (e.g., Oracle with %% and &) and between\n        subexpression types (e.g., date expressions).\n        ",
            "n_words": 36,
            "vocab_size": 32,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 259203,
        "commit_id": "7f0006c8aad1a09621ad19c3db19c3ff0555a183",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/_encoders.py",
        "file_name": "_encoders.py",
        "fun_name": "_map_infrequent_categories",
        "commit_message": "ENH Adds infrequent categories to OneHotEncoder (#16018)\n\n* ENH Completely adds infrequent categories\r\n\r\n* STY Linting\r\n\r\n* STY Linting\r\n\r\n* DOC Improves wording\r\n\r\n* DOC Lint\r\n\r\n* BUG Fixes\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* DOC Uses math to description float min_frequency\r\n\r\n* DOC Adds comment regarding drop\r\n\r\n* BUG Fixes method name\r\n\r\n* DOC Clearer docstring\r\n\r\n* TST Adds more tests\r\n\r\n* FIX Fixes mege\r\n\r\n* CLN More pythonic\r\n\r\n* CLN Address comments\r\n\r\n* STY Flake8\r\n\r\n* CLN Address comments\r\n\r\n* DOC Fix\r\n\r\n* MRG\r\n\r\n* WIP\r\n\r\n* ENH Address comments\r\n\r\n* STY Fix\r\n\r\n* ENH Use functiion call instead of property\r\n\r\n* ENH Adds counts feature\r\n\r\n* CLN Rename variables\r\n\r\n* DOC More details\r\n\r\n* CLN Remove unneeded line\r\n\r\n* CLN Less lines is less complicated\r\n\r\n* CLN Less diffs\r\n\r\n* CLN Improves readiabilty\r\n\r\n* BUG Fix\r\n\r\n* CLN Address comments\r\n\r\n* TST Fix\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* CLN Move docstring to userguide\r\n\r\n* DOC Better wrapping\r\n\r\n* TST Adds test to handle_unknown='error'\r\n\r\n* ENH Spelling error in docstring\r\n\r\n* BUG Fixes counter with nan values\r\n\r\n* BUG Removes unneeded test\r\n\r\n* BUG Fixes issue\r\n\r\n* ENH Sync with main\r\n\r\n* DOC Correct settings\r\n\r\n* DOC Adds docstring\r\n\r\n* DOC Immprove user guide\r\n\r\n* DOC Move to 1.0\r\n\r\n* DOC Update docs\r\n\r\n* TST Remove test\r\n\r\n* DOC Update docstring\r\n\r\n* STY Linting\r\n\r\n* DOC Address comments\r\n\r\n* ENH Neater code\r\n\r\n* DOC Update explaination for auto\r\n\r\n* Update sklearn/preprocessing/_encoders.py\r\n\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\n\r\n* TST Uses docstring instead of comments\r\n\r\n* TST Remove call to fit\r\n\r\n* TST Spelling error\r\n\r\n* ENH Adds support for drop + infrequent categories\r\n\r\n* ENH Adds infrequent_if_exist option\r\n\r\n* DOC Address comments for user guide\r\n\r\n* DOC Address comments for whats_new\r\n\r\n* DOC Update docstring based on comments\r\n\r\n* CLN Update test with suggestions\r\n\r\n* ENH Adds computed property infrequent_categories_\r\n\r\n* DOC Adds where the infrequent column is located\r\n\r\n* TST Adds more test for infrequent_categories_\r\n\r\n* DOC Adds docstring for _compute_drop_idx\r\n\r\n* CLN Moves _convert_to_infrequent_idx into its own method\r\n\r\n* TST Increases test coverage\r\n\r\n* TST Adds failing test\r\n\r\n* CLN Careful consideration of dropped and inverse_transform\r\n\r\n* STY Linting\r\n\r\n* DOC Adds docstrinb about dropping infrequent\r\n\r\n* DOC Uses only\r\n\r\n* DOC Numpydoc\r\n\r\n* TST Includes test for get_feature_names_out\r\n\r\n* DOC Move whats new\r\n\r\n* DOC Address docstring comments\r\n\r\n* DOC Docstring changes\r\n\r\n* TST Better comments\r\n\r\n* TST Adds check for handle_unknown='ignore' for infrequent\r\n\r\n* CLN Make _infrequent_indices private\r\n\r\n* CLN Change min_frequency default to None\r\n\r\n* DOC Adds comments\r\n\r\n* ENH adds support for max_categories=1\r\n\r\n* ENH Describe lexicon ordering for ties\r\n\r\n* DOC Better docstring\r\n\r\n* STY Fix\r\n\r\n* CLN Error when explicity dropping an infrequent category\r\n\r\n* STY Grammar\r\n\r\nCo-authored-by: Joel Nothman <joel.nothman@gmail.com>\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def _map_infrequent_categories(self, X_int, X_mask):\n        \n        if not self._infrequent_enabled:\n            return\n\n        for col_idx in range(X_int.shape[1]):\n            infrequent_idx = self._infrequent_indices[col_idx]\n            if infrequent_idx is None:\n                continue\n\n            X_int[~X_mask[:, col_idx], col_idx] = infrequent_idx[0]\n            if self.handle_unknown == \"infrequent_if_exist\":\n                # All the unknown values are now mapped to the\n                # infrequent_idx[0], which makes the unknown values valid\n                # This is needed in `transform` when the encoding is formed\n                # using `X_mask`.\n                X_mask[:, col_idx] = True\n\n        # Remaps encoding in `X_int` where the infrequent categories are\n        # grouped together.\n        for i, mapping in enumerate(self._default_to_infrequent_mappings):\n            if mapping is None:\n                continue\n            X_int[:, i] = np.take(mapping, X_int[:, i])\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 318,
        "n_words": 94,
        "vocab_size": 62,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 114,
        "n_ast_nodes": 182,
        "n_identifiers": 17,
        "d_id": 75641,
        "documentation": {
            "docstring": "Map infrequent categories to integer representing the infrequent category.\n\n        This modifies X_int in-place. Values that were invalid based on `X_mask`\n        are mapped to the infrequent category if there was an infrequent\n        category for that feature.\n\n        Parameters\n        ----------\n        X_int: ndarray of shape (n_samples, n_features)\n            Integer encoded categories.\n\n        X_mask: ndarray of shape (n_samples, n_features)\n            Bool mask for valid values in `X_int`.\n        ",
            "n_words": 59,
            "vocab_size": 46,
            "n_whitespaces": 137,
            "language": "en"
        }
    },
    {
        "id": 136429,
        "commit_id": "e368dd9b4e10026767df66d1811a92bd8ca2d8f9",
        "repo": "ray",
        "path": "rllib/offline/estimators/tests/test_ope.py",
        "file_name": "test_ope.py",
        "fun_name": "test_is_wis_on_estimate_on_dataset",
        "commit_message": "[RLlib] By-pass Evaluation workers when doing OPE (#30135)\n\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def test_is_wis_on_estimate_on_dataset(self):\n        \n        config = self.dqn_on_fake_ds.copy()\n        config = config.evaluation(\n            off_policy_estimation_methods={\n                \"is\": {\"type\": ImportanceSampling},\n                \"wis\": {\"type\": WeightedImportanceSampling},\n            },\n        )\n        num_actions = config.action_space.n\n        algo = config.build()\n\n        evaluated_results = algo.evaluate()\n        ope_results = evaluated_results[\"evaluation\"][\"off_policy_estimator\"]\n        policy = algo.get_policy()\n\n        wis_gain, wis_ste = compute_expected_is_or_wis_estimator(\n            self.train_df, policy, num_actions=num_actions, is_wis=True\n        )\n\n        is_gain, is_ste = compute_expected_is_or_wis_estimator(\n            self.train_df, policy, num_actions=num_actions, is_wis=False\n        )\n\n        check(wis_gain, ope_results[\"wis\"][\"v_gain_mean\"])\n        check(wis_ste, ope_results[\"wis\"][\"v_gain_ste\"])\n        check(is_gain, ope_results[\"is\"][\"v_gain_mean\"])\n        check(is_ste, ope_results[\"is\"][\"v_gain_ste\"])\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 251,
        "n_words": 58,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 168,
        "n_ast_nodes": 281,
        "n_identifiers": 27,
        "d_id": 30916,
        "documentation": {
            "docstring": "Test that the IS and WIS estimators work.\n\n        First we compute the estimates with RLlib's algorithm and then compare the\n        results to the estimates that are manually computed on raw data frame version\n        of the dataset to check correctness.\n        ",
            "n_words": 39,
            "vocab_size": 31,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 160521,
        "commit_id": "d4e11c7a2eb64861275facb076d47ccd135fa28c",
        "repo": "numpy",
        "path": "numpy/f2py/capi_maps.py",
        "file_name": "capi_maps.py",
        "fun_name": "f2cexpr",
        "commit_message": "ENH: Support character string arrays\n\nTST: added test for issue #18684\n\nENH: f2py opens files with correct encoding, fixes #635\n\nTST: added test for issue #6308\n\nTST: added test for issue #4519\n\nTST: added test for issue #3425\n\nENH: Implement user-defined hooks support for post-processing f2py data structure. Implement character BC hook.\n\nENH: Add support for detecting utf-16 and utf-32 encodings.",
        "code": "def f2cexpr(expr):\n    \n    # TODO: support Fortran `len` function with optional kind parameter\n    expr = re.sub(r'\\blen\\b', 'f2py_slen', expr)\n    return expr\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 38648,
        "documentation": {
            "docstring": "Rewrite Fortran expression as f2py supported C expression.\n\n    Due to the lack of a proper expression parser in f2py, this\n    function uses a heuristic approach that assumes that Fortran\n    arithmetic expressions are valid C arithmetic expressions when\n    mapping Fortran function calls to the corresponding C function/CPP\n    macros calls.\n\n    ",
            "n_words": 48,
            "vocab_size": 36,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 114363,
        "commit_id": "27a34a6a706a06e1241671d29c8cab93d77a19c1",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/libs/storage_handler.py",
        "file_name": "storage_handler.py",
        "fun_name": "_setup_connection",
        "commit_message": "feat: add docs, improve base class signatures",
        "code": "def _setup_connection(self):\n          # noqa\n        cur = self.connection.cursor()\n        if ('store',) not in list(cur.execute(\"SELECT name FROM sqlite_master WHERE type='table';\")):\n            cur.execute(\n                )\n            self.internal_registry.commit()\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 79,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 83,
        "n_identifiers": 9,
        "d_id": 25164,
        "documentation": {
            "docstring": " Checks that a key-value table exists, otherwise creates it. create table store (key text, value text)",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 264189,
        "commit_id": "1024adca72570f58ac899850c5ca66bf782ee528",
        "repo": "netbox",
        "path": "netbox/netbox/views/generic/object_views.py",
        "file_name": "object_views.py",
        "fun_name": "export_table",
        "commit_message": "Exclude actions column from export",
        "code": "def export_table(self, table, columns=None):\n        \n        exclude_columns = {'pk', 'actions'}\n        if columns:\n            all_columns = [col_name for col_name, _ in table.selected_columns + table.available_columns]\n            exclude_columns.update({\n                col for col in all_columns if col not in columns\n            })\n        exporter = TableExport(\n            export_format=TableExport.CSV,\n            table=table,\n            exclude_columns=exclude_columns\n        )\n        return exporter.response(\n            filename=f'netbox_{self.queryset.model._meta.verbose_name_plural}.csv'\n        )\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 184,
        "n_words": 43,
        "vocab_size": 33,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 84,
        "n_ast_nodes": 147,
        "n_identifiers": 22,
        "d_id": 77639,
        "documentation": {
            "docstring": "\n        Export all table data in CSV format.\n\n        :param table: The Table instance to export\n        :param columns: A list of specific columns to include. If not specified, all columns will be exported.\n        ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 199618,
        "commit_id": "e875bdb804b0285e4a9bd8de0158436e792c03cb",
        "repo": "sympy",
        "path": "sympy/polys/appellseqs.py",
        "file_name": "appellseqs.py",
        "fun_name": "euler_poly",
        "commit_message": "Initial definition of Appell sequences",
        "code": "def euler_poly(n, x=None, polys=False):\n    \n    return appell_poly(n, [[1], [1, QQ(-1,2)]], 1, lambda p, i: -p / 2, QQ, x, polys)\n\n\n@public",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "@public",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 25,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 55,
        "n_ast_nodes": 81,
        "n_identifiers": 9,
        "d_id": 49296,
        "documentation": {
            "docstring": "Generates the Euler polynomial of degree `n` in `x`.\n\n    Parameters\n    ==========\n\n    n : int\n        Degree of the polynomial.\n    x : optional\n    polys : bool, optional\n        If True, return a Poly, otherwise (default) return an expression.\n    ",
            "n_words": 35,
            "vocab_size": 29,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 247060,
        "commit_id": "1901cb1d4a8b7d9af64493fbd336e9aa2561c20c",
        "repo": "synapse",
        "path": "tests/rest/client/test_retention.py",
        "file_name": "test_retention.py",
        "fun_name": "test_retention_event_purged_without_state_event",
        "commit_message": "Add type hints to `tests/rest/client` (#12084)",
        "code": "def test_retention_event_purged_without_state_event(self) -> None:\n        \n        room_id = self.helper.create_room_as(self.user_id, tok=self.token)\n\n        self._test_retention_event_purged(room_id, one_day_ms * 2)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 36,
        "n_ast_nodes": 58,
        "n_identifiers": 10,
        "d_id": 71470,
        "documentation": {
            "docstring": "Tests that expired events are correctly purged when the room's retention policy\n        is defined by the server's configuration's default retention policy.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 294438,
        "commit_id": "d645e80ccd5acb92c5ee6bce30c20bc634fc3e77",
        "repo": "core",
        "path": "tests/components/androidtv/test_media_player.py",
        "file_name": "test_media_player.py",
        "fun_name": "test_reconnect",
        "commit_message": "Clean up async_update_entity helper usage (#68641)",
        "code": "async def test_reconnect(hass, caplog, config):\n    \n    patch_key, entity_id, config_entry = _setup(config)\n    config_entry.add_to_hass(hass)\n\n    with patchers.PATCH_ADB_DEVICE_TCP, patchers.patch_connect(True)[\n        patch_key\n    ], patchers.patch_shell(SHELL_RESPONSE_OFF)[\n        patch_key\n    ], patchers.PATCH_KEYGEN, patchers.PATCH_ANDROIDTV_OPEN, patchers.PATCH_SIGNER:\n        assert await hass.config_entries.async_setup(config_entry.entry_id)\n        await hass.async_block_till_done()\n\n        await async_update_entity(hass, entity_id)\n        state = hass.states.get(entity_id)\n        assert state is not None\n        assert state.state == STATE_OFF\n\n    caplog.clear()\n    caplog.set_level(logging.WARNING)\n\n    with patchers.patch_connect(False)[patch_key], patchers.patch_shell(error=True)[\n        patch_key\n    ], patchers.PATCH_ANDROIDTV_OPEN, patchers.PATCH_SIGNER:\n        for _ in range(5):\n            await async_update_entity(hass, entity_id)\n            state = hass.states.get(entity_id)\n            assert state is not None\n            assert state.state == STATE_UNAVAILABLE\n\n    assert len(caplog.record_tuples) == 2\n    assert caplog.record_tuples[0][1] == logging.ERROR\n    assert caplog.record_tuples[1][1] == logging.WARNING\n\n    caplog.set_level(logging.DEBUG)\n    with patchers.patch_connect(True)[patch_key], patchers.patch_shell(\n        SHELL_RESPONSE_STANDBY\n    )[patch_key], patchers.PATCH_ANDROIDTV_OPEN, patchers.PATCH_SIGNER:\n        await async_update_entity(hass, entity_id)\n\n        state = hass.states.get(entity_id)\n        assert state is not None\n        assert state.state == STATE_STANDBY\n\n    if patch_key == \"python\":\n        assert (\n            \"ADB connection to 127.0.0.1:5555 successfully established\"\n            in caplog.record_tuples[2]\n        )\n    else:\n        assert (\n            \"ADB connection to 127.0.0.1:5555 via ADB server 127.0.0.1:5037 successfully established\"\n            in caplog.record_tuples[2]\n        )\n\n\n@pytest.mark.parametrize(\n    \"config\",\n    [\n        CONFIG_ANDROIDTV_PYTHON_ADB,\n        CONFIG_FIRETV_PYTHON_ADB,\n        CONFIG_ANDROIDTV_ADB_SERVER,\n        CONFIG_FIRETV_ADB_SERVER,\n    ],\n)",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"config\",\n    [\n        CONFIG_ANDROIDTV_PYTHON_ADB,\n        CONFIG_FIRETV_PYTHON_ADB,\n        CONFIG_ANDROIDTV_ADB_SERVER,\n        CONFIG_FIRETV_ADB_SERVER,\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 455,
        "n_words": 145,
        "vocab_size": 78,
        "complexity": 3,
        "nloc": 45,
        "token_counts": 320,
        "n_ast_nodes": 536,
        "n_identifiers": 47,
        "d_id": 93474,
        "documentation": {
            "docstring": "Test that the error and reconnection attempts are logged correctly.\n\n    \"Handles device/service unavailable. Log a warning once when\n    unavailable, log once when reconnected.\"\n\n    https://developers.home-assistant.io/docs/en/integration_quality_scale_index.html\n    ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 266037,
        "commit_id": "ea6d86e6c4bb6037465410db6205a7471bc81a6c",
        "repo": "netbox",
        "path": "netbox/extras/tests/test_customfields.py",
        "file_name": "test_customfields.py",
        "fun_name": "test_missing_required_field",
        "commit_message": "Closes #10052: The cf attribute now returns deserialized custom field data",
        "code": "def test_missing_required_field(self):\n        \n        cf3 = CustomField(type=CustomFieldTypeChoices.TYPE_TEXT, name='baz', required=True)\n        cf3.save()\n        cf3.content_types.set([ContentType.objects.get_for_model(Site)])\n\n        site = Site(name='Test Site', slug='test-site')\n\n        # Set custom field data with a required field omitted\n        site.custom_field_data['foo'] = 'abc'\n        with self.assertRaises(ValidationError):\n            site.clean()\n\n        site.custom_field_data['baz'] = 'def'\n        site.clean()\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 115,
        "n_words": 34,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 92,
        "n_ast_nodes": 165,
        "n_identifiers": 22,
        "d_id": 78274,
        "documentation": {
            "docstring": "\n        Check that a ValidationError is raised if any required custom fields are not present.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 65186,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/cash_flow/cash_flow.py",
        "file_name": "cash_flow.py",
        "fun_name": "get_account_type_based_gl_data",
        "commit_message": "style: format code with black",
        "code": "def get_account_type_based_gl_data(company, start_date, end_date, account_type, filters=None):\n\tcond = \"\"\n\tfilters = frappe._dict(filters or {})\n\n\tif filters.include_default_book_entries:\n\t\tcompany_fb = frappe.db.get_value(\"Company\", company, \"default_finance_book\")\n\t\tcond =  % (\n\t\t\tfrappe.db.escape(filters.finance_book),\n\t\t\tfrappe.db.escape(company_fb),\n\t\t)\n\telse:\n\t\tcond = \" AND (finance_book in (%s, '') OR finance_book IS NULL)\" % (\n\t\t\tfrappe.db.escape(cstr(filters.finance_book))\n\t\t)\n\n\tgl_sum = frappe.db.sql_list(\n\t\t.format(\n\t\t\tcond=cond\n\t\t),\n\t\t(company, start_date, end_date, account_type),\n\t)\n\n\treturn gl_sum[0] if gl_sum and gl_sum[0] else 0\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 45,
        "n_words": 64,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 27,
        "token_counts": 137,
        "n_ast_nodes": 214,
        "n_identifiers": 19,
        "d_id": 13820,
        "documentation": {
            "docstring": " AND (finance_book in (%s, %s, '') OR finance_book IS NULL)\n\t\t\t\n\t\tselect sum(credit) - sum(debit)\n\t\tfrom `tabGL Entry`\n\t\twhere company=%s and posting_date >= %s and posting_date <= %s\n\t\t\tand voucher_type != 'Period Closing Voucher'\n\t\t\tand account in ( SELECT name FROM tabAccount WHERE account_type = %s) {cond}\n\t",
            "n_words": 46,
            "vocab_size": 40,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 67399,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/selling/report/customer_acquisition_and_loyalty/customer_acquisition_and_loyalty.py",
        "file_name": "customer_acquisition_and_loyalty.py",
        "fun_name": "get_customer_stats",
        "commit_message": "style: format code with black",
        "code": "def get_customer_stats(filters, tree_view=False):\n\t\n\tcompany_condition = \"\"\n\tif filters.get(\"company\"):\n\t\tcompany_condition = \" and company=%(company)s\"\n\n\tcustomers = []\n\tcustomers_in = {}\n\n\tfor si in frappe.db.sql(\n\t\t.format(\n\t\t\tcompany_condition=company_condition\n\t\t),\n\t\tfilters,\n\t\tas_dict=1,\n\t):\n\n\t\tkey = si.territory if tree_view else si.posting_date.strftime(\"%Y-%m\")\n\t\tnew_or_repeat = \"new\" if si.customer not in customers else \"repeat\"\n\t\tcustomers_in.setdefault(key, {\"new\": [0, 0.0], \"repeat\": [0, 0.0]})\n\n\t\t# if filters.from_date <= si.posting_date.strftime('%Y-%m-%d'):\n\t\tif getdate(filters.from_date) <= getdate(si.posting_date):\n\t\t\tcustomers_in[key][new_or_repeat][0] += 1\n\t\t\tcustomers_in[key][new_or_repeat][1] += si.base_grand_total\n\t\tif new_or_repeat == \"new\":\n\t\t\tcustomers.append(si.customer)\n\n\treturn customers_in\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 52,
        "n_words": 75,
        "vocab_size": 56,
        "complexity": 7,
        "nloc": 24,
        "token_counts": 170,
        "n_ast_nodes": 272,
        "n_identifiers": 24,
        "d_id": 14515,
        "documentation": {
            "docstring": "Calculates number of new and repeated customers and revenue.select territory, posting_date, customer, base_grand_total from `tabSales Invoice`\n\t\twhere docstatus=1 and posting_date <= %(to_date)s\n\t\t{company_condition} order by posting_date",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 217703,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/client.py",
        "file_name": "client.py",
        "fun_name": "_safe_read",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _safe_read(self, amt):\n        \n        data = self.fp.read(amt)\n        if len(data) < amt:\n            raise IncompleteRead(data, amt-len(data))\n        return data\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 40,
        "n_ast_nodes": 65,
        "n_identifiers": 8,
        "d_id": 54889,
        "documentation": {
            "docstring": "Read the number of bytes requested.\n\n        This function should be used when <amt> bytes \"should\" be present for\n        reading. If the bytes are truly not available (due to EOF), then the\n        IncompleteRead exception can be used to detect the problem.\n        ",
            "n_words": 40,
            "vocab_size": 31,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 186299,
        "commit_id": "6f82ad9c4a2e17812a68d3c76d7eae89aee3a515",
        "repo": "textual",
        "path": "src/textual/strip.py",
        "file_name": "strip.py",
        "fun_name": "cell_length",
        "commit_message": "adds Strip primitive",
        "code": "def cell_length(self) -> int:\n        \n        # Done on demand and cached, as this is an O(n) operation\n        if self._cell_length is None:\n            self._cell_length = Segment.get_line_length(self._segments)\n        return self._cell_length\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 64,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 31,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 45438,
        "documentation": {
            "docstring": "Get the number of cells required to render this object.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 257543,
        "commit_id": "4d8f40425bc4e7346359b7609720a50ac10b8af9",
        "repo": "haystack",
        "path": "test/nodes/test_summarizer.py",
        "file_name": "test_summarizer.py",
        "fun_name": "add_metadata_summerizer",
        "commit_message": "Passing the meta-data in the summerizer response (#2179)\n\n* Passing the all the meta-data in the summerizer\r\n\r\n* Disable metadata forwarding if `generate_single_summary` is `True`\r\n\r\n* Update Documentation & Code Style\r\n\r\n* simplify tests\r\n\r\n* Update Documentation & Code Style\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def add_metadata_summerizer():\n    docs = [\n        Document(\n            content=,\n            meta={\n                \"sub_content\": \"Pegasus Example\",\n                \"topic\": \"California's Electricity\",\n                \"context\": \"Dummy - PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires.\",\n            },\n        ),\n        Document(\n            content=,\n            meta={\"sub_content\": \"Paris best tour best tour\", \"topic\": \"Eiffel tower\"},\n        ),\n    ]\n    # Original input is overwrote after the \"predict\". So adding the same input as check_output to assess the output\n    check_output = deepcopy(docs)\n\n    summarizer = TransformersSummarizer(model_name_or_path=\"google/pegasus-xsum\")\n    summary = summarizer.predict(documents=docs)\n\n    assert len(summary[0].meta) == len(check_output[0].meta)\n    assert len(summary[1].meta) - 1 == len(check_output[1].meta)\n    assert (\n        summary[0].meta[\"context\"]\n        == \n    )\n\n    summary = summarizer.predict(documents=docs, generate_single_summary=True)\n\n    assert len(summary) == 1\n    assert not summary[0].meta  # Metadata is not returned in case of a single summary\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 304,
        "n_words": 122,
        "vocab_size": 88,
        "complexity": 1,
        "nloc": 27,
        "token_counts": 162,
        "n_ast_nodes": 273,
        "n_identifiers": 15,
        "d_id": 75094,
        "documentation": {
            "docstring": "PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct.PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow.",
            "n_words": 222,
            "vocab_size": 117,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 20345,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/formatters/img.py",
        "file_name": "img.py",
        "fun_name": "_draw_linenumber",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _draw_linenumber(self, posno, lineno):\n        \n        self._draw_text(\n            self._get_linenumber_pos(posno),\n            str(lineno).rjust(self.line_number_chars),\n            font=self.fonts.get_font(self.line_number_bold,\n                                     self.line_number_italic),\n            text_fg=self.line_number_fg,\n            text_bg=None,\n        )\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 124,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 61,
        "n_ast_nodes": 91,
        "n_identifiers": 17,
        "d_id": 3336,
        "documentation": {
            "docstring": "\n        Remember a line number drawable to paint later.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 160078,
        "commit_id": "7dd53bce20121b3818a5960371dfdd1f138296bd",
        "repo": "numpy",
        "path": "numpy/linalg/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "qr",
        "commit_message": "DOC: Update linalg.qr docstring with numerically stable example (#21149)\n\nCo-authored-by: Melissa Weber Mendonça <melissawm@gmail.com>",
        "code": "def qr(a, mode='reduced'):\n    \n    if mode not in ('reduced', 'complete', 'r', 'raw'):\n        if mode in ('f', 'full'):\n            # 2013-04-01, 1.8\n            msg = \"\".join((\n                    \"The 'full' option is deprecated in favor of 'reduced'.\\n\",\n                    \"For backward compatibility let mode default.\"))\n            warnings.warn(msg, DeprecationWarning, stacklevel=3)\n            mode = 'reduced'\n        elif mode in ('e', 'economic'):\n            # 2013-04-01, 1.8\n            msg = \"The 'economic' option is deprecated.\"\n            warnings.warn(msg, DeprecationWarning, stacklevel=3)\n            mode = 'economic'\n        else:\n            raise ValueError(f\"Unrecognized mode '{mode}'\")\n\n    a, wrap = _makearray(a)\n    _assert_stacked_2d(a)\n    m, n = a.shape[-2:]\n    t, result_t = _commonType(a)\n    a = a.astype(t, copy=True)\n    a = _to_native_byte_order(a)\n    mn = min(m, n)\n\n    if m <= n:\n        gufunc = _umath_linalg.qr_r_raw_m\n    else:\n        gufunc = _umath_linalg.qr_r_raw_n\n\n    signature = 'D->D' if isComplexType(t) else 'd->d'\n    extobj = get_linalg_error_extobj(_raise_linalgerror_qr)\n    tau = gufunc(a, signature=signature, extobj=extobj)\n\n    # handle modes that don't return q\n    if mode == 'r':\n        r = triu(a[..., :mn, :])\n        r = r.astype(result_t, copy=False)\n        return wrap(r)\n\n    if mode == 'raw':\n        q = transpose(a)\n        q = q.astype(result_t, copy=False)\n        tau = tau.astype(result_t, copy=False)\n        return wrap(q), tau\n\n    if mode == 'economic':\n        a = a.astype(result_t, copy=False)\n        return wrap(a)\n\n    # mc is the number of columns in the resulting q\n    # matrix. If the mode is complete then it is \n    # same as number of rows, and if the mode is reduced,\n    # then it is the minimum of number of rows and columns.\n    if mode == 'complete' and m > n:\n        mc = m\n        gufunc = _umath_linalg.qr_complete\n    else:\n        mc = mn\n        gufunc = _umath_linalg.qr_reduced\n\n    signature = 'DD->D' if isComplexType(t) else 'dd->d'\n    extobj = get_linalg_error_extobj(_raise_linalgerror_qr)\n    q = gufunc(a, tau, signature=signature, extobj=extobj)\n    r = triu(a[..., :mc, :])\n\n    q = q.astype(result_t, copy=False)\n    r = r.astype(result_t, copy=False)\n\n    return wrap(q), wrap(r)\n\n# Eigenvalues\n\n\n@array_function_dispatch(_unary_dispatcher)",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "@array_function_dispatch(_unary_dispatcher)",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 625,
        "n_words": 270,
        "vocab_size": 130,
        "complexity": 12,
        "nloc": 53,
        "token_counts": 407,
        "n_ast_nodes": 694,
        "n_identifiers": 43,
        "d_id": 38478,
        "documentation": {
            "docstring": "\n    Compute the qr factorization of a matrix.\n\n    Factor the matrix `a` as *qr*, where `q` is orthonormal and `r` is\n    upper-triangular.\n\n    Parameters\n    ----------\n    a : array_like, shape (..., M, N)\n        An array-like object with the dimensionality of at least 2.\n    mode : {'reduced', 'complete', 'r', 'raw'}, optional\n        If K = min(M, N), then\n\n        * 'reduced'  : returns q, r with dimensions\n                       (..., M, K), (..., K, N) (default)\n        * 'complete' : returns q, r with dimensions (..., M, M), (..., M, N)\n        * 'r'        : returns r only with dimensions (..., K, N)\n        * 'raw'      : returns h, tau with dimensions (..., N, M), (..., K,)\n\n        The options 'reduced', 'complete, and 'raw' are new in numpy 1.8,\n        see the notes for more information. The default is 'reduced', and to\n        maintain backward compatibility with earlier versions of numpy both\n        it and the old default 'full' can be omitted. Note that array h\n        returned in 'raw' mode is transposed for calling Fortran. The\n        'economic' mode is deprecated.  The modes 'full' and 'economic' may\n        be passed using only the first letter for backwards compatibility,\n        but all others must be spelled out. See the Notes for more\n        explanation.\n\n\n    Returns\n    -------\n    q : ndarray of float or complex, optional\n        A matrix with orthonormal columns. When mode = 'complete' the\n        result is an orthogonal/unitary matrix depending on whether or not\n        a is real/complex. The determinant may be either +/- 1 in that\n        case. In case the number of dimensions in the input array is\n        greater than 2 then a stack of the matrices with above properties\n        is returned.\n    r : ndarray of float or complex, optional\n        The upper-triangular matrix or a stack of upper-triangular\n        matrices if the number of dimensions in the input array is greater\n        than 2.\n    (h, tau) : ndarrays of np.double or np.cdouble, optional\n        The array h contains the Householder reflectors that generate q\n        along with r. The tau array contains scaling factors for the\n        reflectors. In the deprecated  'economic' mode only h is returned.\n\n    Raises\n    ------\n    LinAlgError\n        If factoring fails.\n\n    See Also\n    --------\n    scipy.linalg.qr : Similar function in SciPy.\n    scipy.linalg.rq : Compute RQ decomposition of a matrix.\n\n    Notes\n    -----\n    This is an interface to the LAPACK routines ``dgeqrf``, ``zgeqrf``,\n    ``dorgqr``, and ``zungqr``.\n\n    For more information on the qr factorization, see for example:\n    https://en.wikipedia.org/wiki/QR_factorization\n\n    Subclasses of `ndarray` are preserved except for the 'raw' mode. So if\n    `a` is of type `matrix`, all the return values will be matrices too.\n\n    New 'reduced', 'complete', and 'raw' options for mode were added in\n    NumPy 1.8.0 and the old option 'full' was made an alias of 'reduced'.  In\n    addition the options 'full' and 'economic' were deprecated.  Because\n    'full' was the previous default and 'reduced' is the new default,\n    backward compatibility can be maintained by letting `mode` default.\n    The 'raw' option was added so that LAPACK routines that can multiply\n    arrays by q using the Householder reflectors can be used. Note that in\n    this case the returned arrays are of type np.double or np.cdouble and\n    the h array is transposed to be FORTRAN compatible.  No routines using\n    the 'raw' return are currently exposed by numpy, but some are available\n    in lapack_lite and just await the necessary work.\n\n    Examples\n    --------\n    >>> a = np.random.randn(9, 6)\n    >>> q, r = np.linalg.qr(a)\n    >>> np.allclose(a, np.dot(q, r))  # a does equal qr\n    True\n    >>> r2 = np.linalg.qr(a, mode='r')\n    >>> np.allclose(r, r2)  # mode='r' returns the same r as mode='full'\n    True\n    >>> a = np.random.normal(size=(3, 2, 2)) # Stack of 2 x 2 matrices as input\n    >>> q, r = np.linalg.qr(a)\n    >>> q.shape\n    (3, 2, 2)\n    >>> r.shape\n    (3, 2, 2)\n    >>> np.allclose(a, np.matmul(q, r))\n    True\n\n    Example illustrating a common use of `qr`: solving of least squares\n    problems\n\n    What are the least-squares-best `m` and `y0` in ``y = y0 + mx`` for\n    the following data: {(0,1), (1,0), (1,2), (2,1)}. (Graph the points\n    and you'll see that it should be y0 = 0, m = 1.)  The answer is provided\n    by solving the over-determined matrix equation ``Ax = b``, where::\n\n      A = array([[0, 1], [1, 1], [1, 1], [2, 1]])\n      x = array([[y0], [m]])\n      b = array([[1], [0], [2], [1]])\n\n    If A = qr such that q is orthonormal (which is always possible via\n    Gram-Schmidt), then ``x = inv(r) * (q.T) * b``.  (In numpy practice,\n    however, we simply use `lstsq`.)\n\n    >>> A = np.array([[0, 1], [1, 1], [1, 1], [2, 1]])\n    >>> A\n    array([[0, 1],\n           [1, 1],\n           [1, 1],\n           [2, 1]])\n    >>> b = np.array([1, 2, 2, 3])\n    >>> q, r = np.linalg.qr(A)\n    >>> p = np.dot(q.T, b)\n    >>> np.dot(np.linalg.inv(r), p)\n    array([  1.,   1.])\n\n    ",
            "n_words": 761,
            "vocab_size": 356,
            "n_whitespaces": 1269,
            "language": "en"
        }
    },
    {
        "id": 314578,
        "commit_id": "fb108533580d5f4c326ca970d8e6fd4998cc5593",
        "repo": "core",
        "path": "homeassistant/components/zha/core/group.py",
        "file_name": "group.py",
        "fun_name": "members",
        "commit_message": "Fix mypy issues in zha core modules (#74028)\n\n* Fix mypy issues in zha gateway, group and helpers\r\n\r\n* Cleanup device\r\n\r\n* Apply suggestion\r\n\r\n* Raise ValueError\r\n\r\n* Use hass.config.path",
        "code": "def members(self) -> list[ZHAGroupMember]:\n        \n        return [\n            ZHAGroupMember(self, self._zha_gateway.devices[member_ieee], endpoint_id)\n            for (member_ieee, endpoint_id) in self._zigpy_group.members.keys()\n            if member_ieee in self._zha_gateway.devices\n        ]\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 53,
        "n_ast_nodes": 80,
        "n_identifiers": 10,
        "d_id": 113184,
        "documentation": {
            "docstring": "Return the ZHA devices that are members of this group.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 64929,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/payment_request/payment_request.py",
        "file_name": "payment_request.py",
        "fun_name": "get_dummy_message",
        "commit_message": "style: format code with black",
        "code": "def get_dummy_message(doc):\n\treturn frappe.render_template(\n\t\t,\n\t\tdict(doc=doc, payment_url=\"{{ payment_url }}\"),\n\t)\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 5,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 24,
        "n_ast_nodes": 51,
        "n_identifiers": 7,
        "d_id": 13757,
        "documentation": {
            "docstring": "{% if doc.contact_person -%}\n<p>Dear {{ doc.contact_person }},</p>\n{%- else %}<p>Hello,</p>{% endif %}\n\n<p>{{ _(\"Requesting payment against {0} {1} for amount {2}\").format(doc.doctype,\n\tdoc.name, doc.get_formatted(\"grand_total\")) }}</p>\n\n<a href=\"{{ payment_url }}\">{{ _(\"Make Payment\") }}</a>\n\n<p>{{ _(\"If you have any questions, please get back to us.\") }}</p>\n\n<p>{{ _(\"Thank you for your business!\") }}</p>\n",
            "n_words": 51,
            "vocab_size": 44,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 282059,
        "commit_id": "4501dfd442d371150b8785d379c5354095b6954b",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/cryptocurrency/crypto_controller.py",
        "file_name": "crypto_controller.py",
        "fun_name": "call_find",
        "commit_message": "Crypto features: Replace coingecko scrapping (#1156)\n\n* replaced cgcategories with api\r\n\r\n* added coingecko categories\r\n\r\n* refactoring commands to use api, added coins to cryptocontroller and merged find and coins\r\n\r\n* autocompletion for coins\r\n\r\n* removed unused vars\r\n\r\n* added dappradar features\r\n\r\n* refactoring commands position\r\n\r\n* refactoring commands position\r\n\r\n* adding visual commands and fixed report\r\n\r\n* skipped tests for now\r\n\r\n* lint notebook\r\n\r\n* correct report\r\n\r\n* black formatter keeps crying because notebook\r\n\r\n* removed unused imports\r\n\r\n* Fixed black\r\n\r\n* Keep kernel metadata 'cause it's required by papermill\r\n\r\n* Change jupyter cleanup hook to one based on nbconvert\r\n\r\n* Try fix the hook I just broke\r\n\r\n* Fix trailing commas in the crypto notebook\r\n\r\n* Change the jupyter hook to a one that's featured on pre-commit's page\r\n\r\n* Format report notebook and test new notebook hook\r\n\r\n* Black the notebook\r\n\r\n* Remove deleted functions from the crypto discovery API\r\n\r\n* Remove deleted functions from the crypto overview API\r\n\r\n* replaced print for console print and removed print from table\r\n\r\n* replaced print for console print and removed print from table\r\n\r\n* auto completion + sort for all discovery commands\r\n\r\n* replacing help messages\r\n\r\n* fix linting\r\n\r\n* added docs and removed unused commands\r\n\r\n* added todos and fixed help messages\r\n\r\n* lint\r\n\r\n* pr issues fixed\r\n\r\n* updated tests\r\n\r\n* tests merge\r\n\r\n* replaced with new rich table function\r\n\r\nCo-authored-by: Colin Delahunty <colin99delahunty@gmail.com>\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>",
        "code": "def call_find(self, other_args):\n        \n        parser = argparse.ArgumentParser(\n            prog=\"find\",\n            add_help=False,\n            formatter_class=argparse.ArgumentDefaultsHelpFormatter,\n            description=,\n        )\n\n        parser.add_argument(\n            \"-c\",\n            \"--coin\",\n            help=\"Symbol Name or Id of Coin\",\n            dest=\"coin\",\n            required=\"-h\" not in other_args,\n            type=str,\n        )\n\n        parser.add_argument(\n            \"-k\",\n            \"--key\",\n            dest=\"key\",\n            help=\"Specify by which column you would like to search: symbol, name, id\",\n            type=str,\n            choices=FIND_KEYS,\n            default=\"symbol\",\n        )\n\n        parser.add_argument(\n            \"-l\",\n            \"--limit\",\n            default=10,\n            dest=\"limit\",\n            help=\"Number of records to display\",\n            type=check_positive,\n        )\n\n        parser.add_argument(\n            \"--source\",\n            dest=\"source\",\n            choices=CRYPTO_SOURCES.keys(),\n            default=\"cg\",\n            help=\"Source of data.\",\n            type=str,\n        )\n\n        parser.add_argument(\n            \"-s\",\n            \"--skip\",\n            default=0,\n            dest=\"skip\",\n            help=\"Skip n of records\",\n            type=check_positive,\n        )\n\n        if other_args and not other_args[0][0] == \"-\":\n            other_args.insert(0, \"-c\")\n\n        ns_parser = parse_known_args_and_warn(\n            parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED\n        )\n        # TODO: merge find + display_all_coins\n        if ns_parser:\n            find(\n                coin=ns_parser.coin,\n                source=ns_parser.source,\n                key=ns_parser.key,\n                top=ns_parser.limit,\n                export=ns_parser.export,\n            )\n            display_all_coins(\n                coin=ns_parser.coin,\n                source=ns_parser.source,\n                top=ns_parser.limit,\n                skip=ns_parser.skip,\n                show_all=bool(\"ALL\" in other_args),\n                export=ns_parser.export,\n            )\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 863,
        "n_words": 121,
        "vocab_size": 93,
        "complexity": 4,
        "nloc": 86,
        "token_counts": 281,
        "n_ast_nodes": 446,
        "n_identifiers": 38,
        "d_id": 84022,
        "documentation": {
            "docstring": "Process find command\n            Find similar coin by coin name,symbol or id. If you don't remember exact name or id of the Coin at CoinGecko,\n            Binance, Coinbase or CoinPaprika you can use this command to display coins with similar name, symbol or id\n            to your search query.\n            Example of usage: coin name is something like \"polka\". So I can try: find -c polka -k name -t 25\n            It will search for coin that has similar name to polka and display top 25 matches.\n            -c, --coin stands for coin - you provide here your search query\n            -k, --key it's a searching key. You can search by symbol, id or name of coin\n            -l, --limit it displays top N number of records.\n            coins: Shows list of coins available on CoinGecko, CoinPaprika and Binance.If you provide name of\n            coin then in result you will see ids of coins with best match for all mentioned services.\n            If you provide ALL keyword in your search query, then all coins will be displayed. To move over coins you\n            can use pagination mechanism with skip, top params. E.g. coins ALL --skip 100 --limit 30 then all coins\n            from 100 to 130 will be displayed. By default skip = 0, limit = 10.\n            If you won't provide source of the data everything will be displayed (CoinGecko, CoinPaprika, Binance).\n            If you want to search only in given source then use --source flag. E.g. if you want to find coin with name\n            uniswap on CoinPaprika then use: coins uniswap --source cp --limit 10\n            ",
            "n_words": 252,
            "vocab_size": 140,
            "n_whitespaces": 439,
            "language": "en"
        }
    },
    {
        "id": 268500,
        "commit_id": "76b746655a36807fa9198064ca9fe7c6cc00083a",
        "repo": "ansible",
        "path": "test/support/network-integration/collections/ansible_collections/ansible/netcommon/plugins/connection/network_cli.py",
        "file_name": "network_cli.py",
        "fun_name": "_needs_cache_invalidation",
        "commit_message": "Add `use_rsa_sha2_algorithms` option for paramiko (#78789)\n\nFixes #76737\r\nFixes #77673\r\n\r\nCo-authored-by: Matt Clay <matt@mystile.com>",
        "code": "def _needs_cache_invalidation(self, command):\n        \n        invalidate = False\n        cfg_cmds = []\n        try:\n            # AnsiblePlugin base class in Ansible 2.9 does not have has_option() method.\n            # TO-DO: use has_option() when we drop 2.9 support.\n            cfg_cmds = self.cliconf.get_option(\"config_commands\")\n        except AttributeError:\n            cfg_cmds = []\n        if (self._is_in_config_mode()) or (to_text(command) in cfg_cmds):\n            invalidate = True\n        return invalidate\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 154,
        "n_words": 50,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 57,
        "n_ast_nodes": 100,
        "n_identifiers": 10,
        "d_id": 79529,
        "documentation": {
            "docstring": "\n        This method determines if it is necessary to invalidate\n        the existing cache based on whether the device has entered\n        configuration mode or if the last command sent to the device\n        is potentially capable of making configuration changes.\n\n        :param command: The last command sent to the target device.\n        :returns: A boolean indicating if cache invalidation is required or not.\n        ",
            "n_words": 58,
            "vocab_size": 41,
            "n_whitespaces": 108,
            "language": "en"
        }
    },
    {
        "id": 258522,
        "commit_id": "ab08e4dba5f1f87b8c3395f32469a6ddb5e34f89",
        "repo": "scikit-learn",
        "path": "sklearn/discriminant_analysis.py",
        "file_name": "discriminant_analysis.py",
        "fun_name": "transform",
        "commit_message": "DOC Add documentation on output shape of LDA.transform (#22238)",
        "code": "def transform(self, X):\n        \n        if self.solver == \"lsqr\":\n            raise NotImplementedError(\n                \"transform not implemented for 'lsqr' solver (use 'svd' or 'eigen').\"\n            )\n        check_is_fitted(self)\n\n        X = self._validate_data(X, reset=False)\n        if self.solver == \"svd\":\n            X_new = np.dot(X - self.xbar_, self.scalings_)\n        elif self.solver == \"eigen\":\n            X_new = np.dot(X, self.scalings_)\n\n        return X_new[:, : self._max_components]\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 155,
        "n_words": 47,
        "vocab_size": 38,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 88,
        "n_ast_nodes": 147,
        "n_identifiers": 14,
        "d_id": 75274,
        "documentation": {
            "docstring": "Project data to maximize class separation.\n\n        Parameters\n        ----------\n        X : array-like of shape (n_samples, n_features)\n            Input data.\n\n        Returns\n        -------\n        X_new : ndarray of shape (n_samples, n_components) or \\\n            (n_samples, min(rank, n_components))\n            Transformed data. In the case of the 'svd' solver, the shape\n            is (n_samples, min(rank, n_components)).\n        ",
            "n_words": 46,
            "vocab_size": 34,
            "n_whitespaces": 139,
            "language": "en"
        }
    },
    {
        "id": 264557,
        "commit_id": "efd5a73a187f1183a278595d7345046abee5800b",
        "repo": "netbox",
        "path": "netbox/netbox/api/viewsets/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_object_with_snapshot",
        "commit_message": "Refactor API views",
        "code": "def get_object_with_snapshot(self):\n        \n        obj = super().get_object()\n        if hasattr(obj, 'snapshot'):\n            obj.snapshot()\n        return obj\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 50,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 55,
        "n_identifiers": 7,
        "d_id": 77754,
        "documentation": {
            "docstring": "\n        Save a pre-change snapshot of the object immediately after retrieving it. This snapshot will be used to\n        record the \"before\" data in the changelog.\n        ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 283133,
        "commit_id": "9923c6974cdb659164d7aefd5523de4bfd563553",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/cryptocurrency/cryptocurrency_helpers.py",
        "file_name": "cryptocurrency_helpers.py",
        "fun_name": "prepare_all_coins_df",
        "commit_message": "Add YahooFinance to crypto load (#1533)\n\n* Add yf to crypto load\r\n\r\n* silence pylint too many branches\r\n\r\n* Add yf chart\r\n\r\n* Add exception handling when coins are not found\r\n\r\n* Fix tests failing\r\n\r\n* Address PR Comments\r\n\r\n* Change the backwards yf crypto chart and volume label\r\n\r\n* fix gst file\r\n\r\nCo-authored-by: jmaslek <jmaslek11@gmail.com>\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>",
        "code": "def prepare_all_coins_df() -> pd.DataFrame:\n    \n\n    gecko_coins_df = load_coins_list(\"coingecko_coins.json\")\n\n    paprika_coins_df = load_coins_list(\"coinpaprika_coins.json\")\n    paprika_coins_df = paprika_coins_df[paprika_coins_df[\"is_active\"]]\n    paprika_coins_df = paprika_coins_df[[\"rank\", \"id\", \"name\", \"symbol\", \"type\"]]\n    yahoofinance_coins_df = load_coins_list(\"yahoofinance_coins.json\")\n\n    # TODO: Think about scheduled job, that once a day will update data\n\n    binance_coins_df = load_binance_map().rename(columns={\"symbol\": \"Binance\"})\n    coinbase_coins_df = load_coinbase_map().rename(columns={\"symbol\": \"Coinbase\"})\n    gecko_paprika_coins_df = pd.merge(\n        gecko_coins_df, paprika_coins_df, on=\"name\", how=\"left\"\n    )\n    df_merged = pd.merge(\n        left=gecko_paprika_coins_df,\n        right=binance_coins_df,\n        left_on=\"id_x\",\n        right_on=\"id\",\n        how=\"left\",\n    )\n    df_merged.rename(\n        columns={\n            \"id_x\": \"CoinGecko\",\n            \"symbol_x\": \"Symbol\",\n            \"id_y\": \"CoinPaprika\",\n        },\n        inplace=True,\n    )\n\n    df_merged = pd.merge(\n        left=df_merged,\n        right=coinbase_coins_df,\n        left_on=\"CoinGecko\",\n        right_on=\"id\",\n        how=\"left\",\n    )\n\n    yahoofinance_coins_df.rename(\n        columns={\n            \"symbol\": \"Symbol\",\n        },\n        inplace=True,\n    )\n\n    df_merged = pd.merge(\n        left=df_merged,\n        right=yahoofinance_coins_df[[\"Symbol\", \"id\"]],\n        on=\"Symbol\",\n        how=\"left\",\n    )\n\n    df_merged.rename(\n        columns={\n            \"id\": \"YahooFinance\",\n        },\n        inplace=True,\n    )\n\n    return df_merged[\n        [\"CoinGecko\", \"CoinPaprika\", \"Binance\", \"Coinbase\", \"YahooFinance\", \"Symbol\"]\n    ]\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 418,
        "n_words": 113,
        "vocab_size": 76,
        "complexity": 1,
        "nloc": 71,
        "token_counts": 265,
        "n_ast_nodes": 464,
        "n_identifiers": 23,
        "d_id": 84446,
        "documentation": {
            "docstring": "Helper method which loads coins from all sources: CoinGecko, CoinPaprika,\n    Binance, Yahoo Finance and merge those coins on keys:\n\n        CoinGecko - > name < - CoinPaprika\n        CoinGecko - > id <- Binance\n\n    Returns\n    -------\n    pd.DataFrame\n        CoinGecko - id for coin in CoinGecko API: uniswap\n        CoinPaprika - id for coin in CoinPaprika API: uni-uniswap\n        Binance - symbol (baseAsset) for coin in Binance API: UNI\n        Coinbase - symbol for coin in Coinbase Pro API e.g UNI\n        Yahoo Finance - symbol for coin in Yahoo Finance e.g. UNI1-USD\n\n        Symbol: uni\n    ",
            "n_words": 87,
            "vocab_size": 47,
            "n_whitespaces": 158,
            "language": "en"
        }
    },
    {
        "id": 124153,
        "commit_id": "7d3ceb222c8af98a5c101b1c28ab37ffcb0a3793",
        "repo": "ray",
        "path": "python/ray/tests/kuberay/test_autoscaling_config.py",
        "file_name": "test_autoscaling_config.py",
        "fun_name": "_get_autoscaling_config_with_overrides",
        "commit_message": "[kuberay][autoscaler] Improve CPU, GPU, and memory detection. (#26219)\n\nThis PR improves the autoscaler's resource detection logic",
        "code": "def _get_autoscaling_config_with_overrides() -> dict:\n    \n    config = _get_basic_autoscaling_config()\n    config[\"available_node_types\"][\"small-group\"][\"resources\"][\"memory\"] = 300000000\n    config[\"available_node_types\"][\"small-group\"][\"resources\"][\"GPU\"] = 100\n    config[\"available_node_types\"][\"small-group\"][\"resources\"][\"CPU\"] = 100\n    config[\"available_node_types\"][\"gpu-group\"][\"resources\"][\"GPU\"] = 100\n    return config\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 42,
        "n_words": 21,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 74,
        "n_ast_nodes": 143,
        "n_identifiers": 4,
        "d_id": 27528,
        "documentation": {
            "docstring": "Autoscaling config with memory and gpu annotations.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 103727,
        "commit_id": "6604e0d015fbd7a3e5602a6f3831d786b4ed659d",
        "repo": "kitty",
        "path": "kitty_tests/check_build.py",
        "file_name": "check_build.py",
        "fun_name": "test_launcher_ensures_stdio",
        "commit_message": "Fix regression in 0.26.0 that caused launching kitty without working STDIO handles to result in high CPU usage and prewarming failing\n\nFixes #5444",
        "code": "def test_launcher_ensures_stdio(self):\n        from kitty.constants import kitty_exe\n        import subprocess\n        exe = kitty_exe()\n        cp = subprocess.run([exe, '+runpy', ])\n        self.assertEqual(cp.returncode, 0)\n\n",
        "url": "https://github.com/kovidgoyal/kitty.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 52,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 42,
        "n_ast_nodes": 71,
        "n_identifiers": 11,
        "d_id": 21711,
        "documentation": {
            "docstring": "\\\nimport os, sys\nif sys.stdin:\n    os.close(sys.stdin.fileno())\nif sys.stdout:\n    os.close(sys.stdout.fileno())\nif sys.stderr:\n    os.close(sys.stderr.fileno())\nos.execlp('kitty', 'kitty', '+runpy', 'import sys; raise SystemExit(1 if sys.stdout is None or sys.stdin is None or sys.stderr is None else 0)')\n",
            "n_words": 34,
            "vocab_size": 26,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 265105,
        "commit_id": "0c915f7de9612c7485da3713cc6d63f368698a5d",
        "repo": "netbox",
        "path": "netbox/dcim/svg.py",
        "file_name": "svg.py",
        "fun_name": "_get_device_coords",
        "commit_message": "Clean up rack elevation rendering",
        "code": "def _get_device_coords(self, position, height):\n        \n        x = self.legend_width + RACK_ELEVATION_BORDER_WIDTH\n        y = RACK_ELEVATION_BORDER_WIDTH\n        if self.rack.desc_units:\n            y += int((position - 1) * self.unit_height)\n        else:\n            y += int((self.rack.u_height - position + 1) * self.unit_height) - int(height * self.unit_height)\n\n        return x, y\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 102,
        "n_words": 38,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 76,
        "n_ast_nodes": 121,
        "n_identifiers": 13,
        "d_id": 77991,
        "documentation": {
            "docstring": "\n        Return the X, Y coordinates of the top left corner for a device in the specified rack unit.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 190662,
        "commit_id": "b21b008118fc8cf65b4bcd9b059f1cd704e05c68",
        "repo": "pytest",
        "path": "testing/python/metafunc.py",
        "file_name": "metafunc.py",
        "fun_name": "test_notset_idval",
        "commit_message": "Refactor idmaker functions into class IdMaker\n\nThis commit only refactors, it does not change or add functionality yet. Public\nAPI is retained. Reason or refactoring:\n\nUser provided parameter IDs (e.g. Metafunc.parametrize(ids=...)) had so far\nonly been used to calculate a unique test ID for each test invocation. That\ntest ID was a joined string where each parameter contributed some partial ID.\n\nWe're soon going to reuse functionality to generate parameter keys for\nreorder_items and FixtureDef cache. We will be interested in the partial\nIDs, and only if they originate from explicit user information. Refactoring\nmakes logic and data accessible for reuse, and increases cohesion in general.",
        "code": "def test_notset_idval(self) -> None:\n        \n        assert IdMaker([], [], None, None, None, None)._idval(NOTSET, \"a\", 0) == \"a0\"\n",
        "url": "https://github.com/pytest-dev/pytest.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 29,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 57,
        "n_identifiers": 5,
        "d_id": 46371,
        "documentation": {
            "docstring": "Test that a NOTSET value (used by an empty parameterset) generates\n        a proper ID.\n\n        Regression test for #7686.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 106852,
        "commit_id": "5b8b7f267cfaf76a2a39a727ef31a62b3909a093",
        "repo": "visdom",
        "path": "py/visdom/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "fork_env",
        "commit_message": "apply black py to all python files",
        "code": "def fork_env(self, prev_eid, eid):\n        \n        assert isstr(prev_eid), \"prev_eid should be a string\"\n        assert isstr(eid), \"eid should be a string\"\n\n        return self._send(msg={\"prev_eid\": prev_eid, \"eid\": eid}, endpoint=\"fork_env\")\n",
        "url": "https://github.com/fossasia/visdom.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 52,
        "n_words": 24,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 45,
        "n_ast_nodes": 77,
        "n_identifiers": 8,
        "d_id": 22475,
        "documentation": {
            "docstring": "This function allows the user to fork environments.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 130510,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/autoscaler/_private/monitor.py",
        "file_name": "monitor.py",
        "fun_name": "update_event_summary",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def update_event_summary(self):\n        \n        avail_resources = self.load_metrics.resources_avail_summary()\n        if not self.readonly_config and avail_resources != self.last_avail_resources:\n            self.event_summarizer.add(\n                \"Resized to {}.\",  # e.g., Resized to 100 CPUs, 4 GPUs.\n                quantity=avail_resources,\n                aggregate=lambda old, new: new,\n            )\n            self.last_avail_resources = avail_resources\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 133,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 54,
        "n_ast_nodes": 89,
        "n_identifiers": 13,
        "d_id": 29289,
        "documentation": {
            "docstring": "Report the current size of the cluster.\n\n        To avoid log spam, only cluster size changes (CPU or GPU count change)\n        are reported to the event summarizer. The event summarizer will report\n        only the latest cluster size per batch.\n        ",
            "n_words": 38,
            "vocab_size": 30,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 20288,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/formatters/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_formatter_for_filename",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def get_formatter_for_filename(fn, **options):\n    \n    fn = basename(fn)\n    for modname, name, _, filenames, _ in FORMATTERS.values():\n        for filename in filenames:\n            if _fn_matches(fn, filename):\n                if name not in _formatter_cache:\n                    _load_formatters(modname)\n                return _formatter_cache[name](**options)\n    for cls in find_plugin_formatters():\n        for filename in cls.filenames:\n            if _fn_matches(fn, filename):\n                return cls(**options)\n    raise ClassNotFound(\"no formatter found for file name %r\" % fn)\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 167,
        "n_words": 52,
        "vocab_size": 37,
        "complexity": 8,
        "nloc": 13,
        "token_counts": 99,
        "n_ast_nodes": 155,
        "n_identifiers": 17,
        "d_id": 3311,
        "documentation": {
            "docstring": "Lookup and instantiate a formatter by filename pattern.\n\n    Raises ClassNotFound if not found.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 58397,
        "commit_id": "ab657b5b3e2235e836ef017d9c58d580e1c254c6",
        "repo": "prefect",
        "path": "src/prefect/agent.py",
        "file_name": "agent.py",
        "fun_name": "get_work_queues",
        "commit_message": "Handle errors gracefully and yield queues",
        "code": "async def get_work_queues(self) -> Iterator[WorkQueue]:\n        \n        for name in self.work_queues:\n            try:\n                work_queue = await self.client.read_work_queue_by_name(name)\n            except ObjectNotFound:\n\n                # if the work queue wasn't found, create it\n                try:\n                    work_queue = await self.client.create_work_queue(name=name)\n\n                # if creating it raises an exception, it was probably just\n                # created by some other agent; rather than entering a re-read\n                # loop with new error handling, we log the exception and\n                # continue.\n                except Exception as exc:\n                    self.logger.exception(exc)\n                    continue\n\n            yield work_queue\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 297,
        "n_words": 73,
        "vocab_size": 59,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 65,
        "n_ast_nodes": 116,
        "n_identifiers": 15,
        "d_id": 11764,
        "documentation": {
            "docstring": "\n        Loads the work queue objects corresponding to the agent's target work\n        queues. If any of them don't exist, they are created.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 220529,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/futures.py",
        "file_name": "futures.py",
        "fun_name": "cancel",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def cancel(self, msg=None):\n        \n        self.__log_traceback = False\n        if self._state != _PENDING:\n            return False\n        self._state = _CANCELLED\n        self._cancel_message = msg\n        self.__schedule_callbacks()\n        return True\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 81,
        "n_words": 21,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 41,
        "n_ast_nodes": 68,
        "n_identifiers": 9,
        "d_id": 56036,
        "documentation": {
            "docstring": "Cancel the future and schedule callbacks.\n\n        If the future is already done or cancelled, return False.  Otherwise,\n        change the future's state to cancelled, schedule the callbacks and\n        return True.\n        ",
            "n_words": 29,
            "vocab_size": 21,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 246073,
        "commit_id": "af13a3be29dd2d84d9255f8e613ca70c16819436",
        "repo": "synapse",
        "path": "tests/handlers/test_room_summary.py",
        "file_name": "test_room_summary.py",
        "fun_name": "test_fed_caching",
        "commit_message": "Fix a bug that corrupted the cache of federated space hierarchies (#11775)\n\n`FederationClient.get_room_hierarchy()` caches its return values, so\r\nrefactor the code to avoid modifying the returned room summary.",
        "code": "def test_fed_caching(self):\n        \n        fed_hostname = self.hs.hostname + \"2\"\n        fed_subspace = \"#space:\" + fed_hostname\n        fed_room = \"#room:\" + fed_hostname\n\n        # Add a room to the space which is on another server.\n        self._add_child(self.space, fed_subspace, self.token, via=[fed_hostname])\n\n        federation_requests = 0\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 85,
        "n_words": 36,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 33,
        "token_counts": 238,
        "n_ast_nodes": 83,
        "n_identifiers": 12,
        "d_id": 70985,
        "documentation": {
            "docstring": "\n        Federation `/hierarchy` responses should be cached.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 11718,
        "commit_id": "bb8ab48d2008b6165a8d08cd9942c07e938f8dd5",
        "repo": "jina",
        "path": "tests/integration/graphql/test_graphql.py",
        "file_name": "test_graphql.py",
        "fun_name": "test_id_in_matches",
        "commit_message": "feat(gateway): add graphql support (#4403)",
        "code": "def test_id_in_matches(req_type):\n    response = graphql_query(\n        (\n            f'{req_type} {{'\n            \n        )\n    )\n    assert sorted(set(response['data']['docs'][0].keys())) == sorted(\n        {'id', 'text', 'matches'}\n    )\n    assert len(response['data']['docs'][0]['matches']) == 2\n    for match in response['data']['docs'][0]['matches']:\n        assert set(match.keys()) == {'id'}\n\n\n@pytest.mark.parametrize('req_type', ['mutation', 'query'])",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize('req_type', ['mutation', 'query'])",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 100,
        "n_words": 33,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 96,
        "n_ast_nodes": 203,
        "n_identifiers": 12,
        "d_id": 2085,
        "documentation": {
            "docstring": "docs(data: {text: \"abcd\"}) { \n                id \n                text\n                matches {\n                    id\n                }\n            } \n        }\n    ",
            "n_words": 12,
            "vocab_size": 8,
            "n_whitespaces": 115,
            "language": "en"
        }
    },
    {
        "id": 263828,
        "commit_id": "684bfac8adcf254fec5777f212c13eb62181f900",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/gi.py",
        "file_name": "gi.py",
        "fun_name": "collect_typelib_data",
        "commit_message": "hooks: refactor GObject introspection (gi) hooks\n\nThe modules imported from gi.repository are marked as runtime\nmodules by their corresponding pre-safe-import-module hooks.\nTherefore, their standard hooks are always loaded and executed,\nregardless of whether the modue is actually importable or not.\n\nIn PyInstaller v5, this behavior triggers errors in hooks for\nGI modules that are not importable, because the new `isolated`\nframework propagates the errors instead of swallowing them.\nWhile these errors could be caught and demoted to warnings\nto match the old behavior, it would be better hooks checked\nwhether module is importable before doing any processing\nat all.\n\nTo that end, we introduce new class, `GiModuleInfo` that,\nas part of its initialization, allows us to:\n - perform availability check\n - obtain data previously returned by `get_gi_typelibs`\n - obtain data previously returned by `get_gi_libdir`\nusing a single isolated import attempt (instead of one\nbeing performed in each of those steps).\n\nIn  addition, if passed `hook_api` as an optional argument,\nthe `GiModuleInfo` can use hook configuration API to override\nthe GI module version to be collected (which allows the\nstandard use pattern to be removed from the hook itself).\n\nThe old `get_gi_typelibs` and `get_gi_libdir` functions\nnow internally use `GiModuleInfo` to provide backward\ncompatible behavior to (potential) exetnal user.\n\nAll `gi` hooks are ported to the `GiModuleInfo` and now\nbecome no-op if the module is not available.\n\nIn addition, hooks are cleaned up/refactored so that all\nprocessing is performed either in the loading stage (\"simple\"\nhooks that do not require access to hook configuration API)\nor in the `hook()` function (hooks that require access to\nhook configuration API), but not in the mixture of the two.",
        "code": "def collect_typelib_data(self):\n        \n        datas = []\n        binaries = []\n        hiddenimports = []\n\n        logger.debug(\"Collecting module data for %s %s\", self.name, self.version)\n\n        # Module unavailable\n        if not self.available:\n            raise ValueError(f\"Module {self.name} {self.version} is unavailable!\")\n\n        # Find shared libraries\n        for lib in self.sharedlibs:\n            lib_path = findSystemLibrary(lib)\n            if lib_path:\n                logger.debug('Collecting shared library %s at %s', lib, lib_path)\n                binaries.append((lib_path, '.'))\n\n        # Find and collect .typelib file. Run it through the `gir_library_path_fix` to fix the library path, if\n        # necessary.\n        typelib_entry = gir_library_path_fix(self.typelib)\n        if typelib_entry:\n            logger.debug('Collecting gir typelib at %s', typelib_entry[0])\n            datas.append(typelib_entry)\n\n        # Overrides for the module\n        hiddenimports += collect_submodules('gi.overrides', lambda name: name.endswith('.' + self.name))\n\n        # Module dependencies\n        for dep in self.dependencies:\n            dep_module, _ = dep.rsplit('-', 1)\n            hiddenimports += [f'gi.repository.{dep_module}']\n\n        return binaries, datas, hiddenimports\n\n\n# The old function, provided for backwards compatibility in 3rd party hooks.",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 361,
        "n_words": 129,
        "vocab_size": 92,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 159,
        "n_ast_nodes": 288,
        "n_identifiers": 26,
        "d_id": 77453,
        "documentation": {
            "docstring": "\n        Return a tuple of (binaries, datas, hiddenimports) to be used by PyGObject related hooks.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 321106,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/pdfjs.py",
        "file_name": "pdfjs.py",
        "fun_name": "_generate_pdfjs_script",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def _generate_pdfjs_script(filename):\n    \n    url = QUrl('qute://pdfjs/file')\n    url_query = QUrlQuery()\n    url_query.addQueryItem('filename', filename)\n    url.setQuery(url_query)\n\n    js_url = javascript.to_js(\n        url.toString(QUrl.ComponentFormattingOption.FullyEncoded))  # type: ignore[arg-type]\n\n    return jinja.js_environment.from_string().render(url=js_url)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 49,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 64,
        "n_ast_nodes": 113,
        "n_identifiers": 18,
        "d_id": 117534,
        "documentation": {
            "docstring": "Generate the script that shows the pdf with pdf.js.\n\n    Args:\n        filename: The name of the file to open.\n    \n        document.addEventListener(\"DOMContentLoaded\", function() {\n          if (typeof window.PDFJS !== 'undefined') {\n              // v1.x\n              window.PDFJS.verbosity = window.PDFJS.VERBOSITY_LEVELS.info;\n          } else {\n              // v2.x\n              const options = window.PDFViewerApplicationOptions;\n              options.set('verbosity', pdfjsLib.VerbosityLevel.INFOS);\n          }\n\n          const viewer = window.PDFView || window.PDFViewerApplication;\n          viewer.open({{ url }});\n        });\n    ",
            "n_words": 54,
            "vocab_size": 45,
            "n_whitespaces": 195,
            "language": "en"
        }
    },
    {
        "id": 109500,
        "commit_id": "f57f30e14de5dfb59dfc22522a602084ba8c8081",
        "repo": "matplotlib",
        "path": "lib/matplotlib/cbook/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_auto_format_str",
        "commit_message": "Add cbook function for str formatting.",
        "code": "def _auto_format_str(fmt, value):\n    \n    try:\n        lbl = fmt % value\n        # when used in `Axes.bar_label()`` this doesn't always raise an error\n        # when the {}-style formatting should be used instead of %-style\n        if lbl == fmt:\n            raise TypeError\n        return lbl\n    except (TypeError, ValueError):\n        return fmt.format(value)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 106,
        "n_words": 44,
        "vocab_size": 37,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 38,
        "n_ast_nodes": 64,
        "n_identifiers": 7,
        "d_id": 23611,
        "documentation": {
            "docstring": "\n    Apply *value* to the format string *fmt*.\n\n    This works both with unnamed %-style formatting and\n    unnamed {}-style formatting. %-style formatting has priority.\n    If *fmt* is %-style formattable that will be used. Otherwise,\n    {}-formatting is applied. Strings without formatting placeholders\n    are passed through as is.\n\n    Examples\n    --------\n    >>> _auto_format_str('%.2f m', 0.2)\n    '0.20 m'\n    >>> _auto_format_str('{} m', 0.2)\n    '0.2 m'\n    >>> _auto_format_str('const', 0.2)\n    'const'\n    >>> _auto_format_str('%d or {}', 0.2)\n    '0 or {}'\n    ",
            "n_words": 70,
            "vocab_size": 55,
            "n_whitespaces": 122,
            "language": "en"
        }
    },
    {
        "id": 265414,
        "commit_id": "e07dd3ddcb2b8453d5a72ccb984e456297fb8296",
        "repo": "netbox",
        "path": "netbox/dcim/api/serializers.py",
        "file_name": "serializers.py",
        "fun_name": "get_destination",
        "commit_message": "Define NESTED_SERIALIZER_PREFIX constant",
        "code": "def get_destination(self, obj):\n        \n        if obj.destination_id is not None:\n            serializer = get_serializer_for_model(obj.destination, prefix=NESTED_SERIALIZER_PREFIX)\n            context = {'request': self.context['request']}\n            return serializer(obj.destination, context=context).data\n        return None\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 75,
        "n_words": 21,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 55,
        "n_ast_nodes": 89,
        "n_identifiers": 11,
        "d_id": 78093,
        "documentation": {
            "docstring": "\n        Return the appropriate serializer for the destination, if any.\n        ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 61936,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py",
        "file_name": "database.py",
        "fun_name": "exports",
        "commit_message": "upd; format",
        "code": "def exports(self):\n        \n        result = {}\n        r = self.get_distinfo_resource(EXPORTS_FILENAME)\n        if r:\n            result = self.read_exports()\n        return result\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 61,
        "n_words": 15,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 30,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 12760,
        "documentation": {
            "docstring": "\n        Return the information exported by this distribution.\n        :return: A dictionary of exports, mapping an export category to a dict\n                 of :class:`ExportEntry` instances describing the individual\n                 export entries, and keyed by name.\n        ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 321852,
        "commit_id": "ee4d6e0396a6b570f4d5592a9c4c1a9fee1027b6",
        "repo": "qutebrowser",
        "path": "qutebrowser/misc/sql.py",
        "file_name": "sql.py",
        "fun_name": "text",
        "commit_message": "sql: Add *all* primary sqlite result codes\n\nFor three reasons:\n\n- There are only 31 of them, and we don't really expect any more to\n  turn up (last happened in 2013, and we have a test for it happening)\n- It makes for nicer debug output\n- It always felt strange to only have a small subset in the enum",
        "code": "def text(self) -> str:\n        \n        if self.error is None:\n            return str(self)\n        return self.error.databaseText()\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 44,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 28,
        "n_ast_nodes": 48,
        "n_identifiers": 5,
        "d_id": 117945,
        "documentation": {
            "docstring": "Get a short text description of the error.\n\n        This is a string suitable to show to the user as error message.\n        ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 46739,
        "commit_id": "c758c76ac336c054fd17d4b878378aa893b7a979",
        "repo": "airflow",
        "path": "airflow/providers/arangodb/hooks/arangodb.py",
        "file_name": "arangodb.py",
        "fun_name": "query",
        "commit_message": "Adding ArangoDB Provider (#22548)\n\n* Adding ArangoDB Provider",
        "code": "def query(self, query, **kwargs) -> Result:\n        \n        try:\n            if self.db_conn:\n                result = self.db_conn.aql.execute(query, **kwargs)\n                return result\n            else:\n                raise AirflowException(\n                    f\"Failed to execute AQLQuery, error connecting to database: {self.database}\"\n                )\n        except AQLQueryExecuteError as error:\n            raise AirflowException(f\"Failed to execute AQLQuery, error: {str(error)}\")\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 172,
        "n_words": 39,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 56,
        "n_ast_nodes": 109,
        "n_identifiers": 13,
        "d_id": 8978,
        "documentation": {
            "docstring": "\n        Function to create a arangodb session\n        and execute the AQL query in the session.\n\n        :param query: AQL query\n        :return: Result\n        ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 149011,
        "commit_id": "bcfa73d492e3c150f0b909df58eb2c59ce6a15a6",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/models.py",
        "file_name": "models.py",
        "fun_name": "nr_of_successful_entries",
        "commit_message": "Add \"nr_of_successfull_entries\"",
        "code": "def nr_of_successful_entries(self) -> int:\n        \n\n        return len(self.select_filled_orders(self.enter_side))\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "d_id": 34357,
        "documentation": {
            "docstring": "\n        Helper function to count the number of entry orders that have been filled.\n        :return: int count of entry orders that have been filled for this trade.\n        ",
            "n_words": 26,
            "vocab_size": 19,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 155766,
        "commit_id": "20e924618999febeac706b20212104fe4f3ea61d",
        "repo": "dask",
        "path": "dask/array/chunk.py",
        "file_name": "chunk.py",
        "fun_name": "argtopk",
        "commit_message": "Type annotations, part 1 (#8295)",
        "code": "def argtopk(a_plus_idx, k, axis, keepdims):\n    \n    assert keepdims is True\n    axis = axis[0]\n\n    if isinstance(a_plus_idx, list):\n        a_plus_idx = list(flatten(a_plus_idx))\n        a = np.concatenate([ai for ai, _ in a_plus_idx], axis)\n        idx = np.concatenate(\n            [np.broadcast_to(idxi, ai.shape) for ai, idxi in a_plus_idx], axis\n        )\n    else:\n        a, idx = a_plus_idx\n\n    if abs(k) >= a.shape[axis]:\n        return a_plus_idx\n\n    idx2 = np.argpartition(a, -k, axis=axis)\n    k_slice = slice(-k, None) if k > 0 else slice(-k)\n    idx2 = idx2[tuple(k_slice if i == axis else slice(None) for i in range(a.ndim))]\n    return np.take_along_axis(a, idx2, axis), np.take_along_axis(idx, idx2, axis)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
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        "n_words": 85,
        "vocab_size": 58,
        "complexity": 8,
        "nloc": 17,
        "token_counts": 189,
        "n_ast_nodes": 282,
        "n_identifiers": 27,
        "d_id": 36460,
        "documentation": {
            "docstring": "Chunk and combine function of argtopk\n\n    Extract the indices of the k largest elements from a on the given axis.\n    If k is negative, extract the indices of the -k smallest elements instead.\n    Note that, unlike in the parent function, the returned elements\n    are not sorted internally.\n    ",
            "n_words": 47,
            "vocab_size": 35,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 62169,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/util.py",
        "file_name": "util.py",
        "fun_name": "split_filename",
        "commit_message": "upd; format",
        "code": "def split_filename(filename, project_name=None):\n    \n    result = None\n    pyver = None\n    filename = unquote(filename).replace(' ', '-')\n    m = PYTHON_VERSION.search(filename)\n    if m:\n        pyver = m.group(1)\n        filename = filename[:m.start()]\n    if project_name and len(filename) > len(project_name) + 1:\n        m = re.match(re.escape(project_name) + r'\\b', filename)\n        if m:\n            n = m.end()\n            result = filename[:n], filename[n + 1:], pyver\n    if result is None:\n        m = PROJECT_NAME_AND_VERSION.match(filename)\n        if m:\n            result = m.group(1), m.group(3), pyver\n    return result\n\n# Allow spaces in name because of legacy dists like \"Twisted Core\"\nNAME_VERSION_RE = re.compile(r'(?P<name>[\\w .-]+)\\s*'\n                             r'\\(\\s*(?P<ver>[^\\s)]+)\\)$')\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 212,
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        "vocab_size": 54,
        "complexity": 7,
        "nloc": 18,
        "token_counts": 154,
        "n_ast_nodes": 270,
        "n_identifiers": 21,
        "d_id": 12890,
        "documentation": {
            "docstring": "\n    Extract name, version, python version from a filename (no extension)\n\n    Return name, version, pyver or None\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 37910,
        "commit_id": "47412c7d434f6ddfc02a9b7ecd6182b86ae0a164",
        "repo": "transformers",
        "path": "src/transformers/trainer_pt_utils.py",
        "file_name": "trainer_pt_utils.py",
        "fun_name": "numpy_pad_and_concatenate",
        "commit_message": "Ensure tensors are at least 1d for pad and concat (#17179)\n\n* Ensure tensors are at least 1d for pad and concat\r\n\r\n* Compatibility\r\n\r\n* Fix\r\n\r\n* Fix\r\n\r\n* Add test\r\n\r\n* Retrigger CI\r\n\r\n* Consistency with master\r\n\r\n* Retrigger CI",
        "code": "def numpy_pad_and_concatenate(array1, array2, padding_index=-100):\n    \n    array1 = atleast_1d(array1)\n    array2 = atleast_1d(array2)\n\n    if len(array1.shape) == 1 or array1.shape[1] == array2.shape[1]:\n        return np.concatenate((array1, array2), axis=0)\n\n    # Let's figure out the new shape\n    new_shape = (array1.shape[0] + array2.shape[0], max(array1.shape[1], array2.shape[1])) + array1.shape[2:]\n\n    # Now let's fill the result tensor\n    result = np.full_like(array1, padding_index, shape=new_shape)\n    result[: array1.shape[0], : array1.shape[1]] = array1\n    result[array1.shape[0] :, : array2.shape[1]] = array2\n    return result\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 104,
        "n_words": 64,
        "vocab_size": 49,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 162,
        "n_ast_nodes": 242,
        "n_identifiers": 14,
        "d_id": 6885,
        "documentation": {
            "docstring": "Concatenates `array1` and `array2` on first axis, applying padding on the second if necessary.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 305683,
        "commit_id": "420733a064286cfe6fc5cf11483835d15ff83462",
        "repo": "core",
        "path": "homeassistant/components/noaa_tides/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "update",
        "commit_message": "Improve entity type hints [n] (#77824)",
        "code": "def update(self) -> None:\n        \n        begin = datetime.now()\n        delta = timedelta(days=2)\n        end = begin + delta\n        try:\n            df_predictions = self._station.get_data(\n                begin_date=begin.strftime(\"%Y%m%d %H:%M\"),\n                end_date=end.strftime(\"%Y%m%d %H:%M\"),\n                product=\"predictions\",\n                datum=\"MLLW\",\n                interval=\"hilo\",\n                units=self._unit_system,\n                time_zone=self._timezone,\n            )\n            self.data = df_predictions.head()\n            _LOGGER.debug(\"Data = %s\", self.data)\n            _LOGGER.debug(\n                \"Recent Tide data queried with start time set to %s\",\n                begin.strftime(\"%m-%d-%Y %H:%M\"),\n            )\n        except ValueError as err:\n            _LOGGER.error(\"Check NOAA Tides and Currents: %s\", err.args)\n            self.data = None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 329,
        "n_words": 64,
        "vocab_size": 50,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 134,
        "n_ast_nodes": 226,
        "n_identifiers": 30,
        "d_id": 104467,
        "documentation": {
            "docstring": "Get the latest data from NOAA Tides and Currents API.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 61926,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py",
        "file_name": "database.py",
        "fun_name": "source_url",
        "commit_message": "upd; format",
        "code": "def source_url(self):\n        \n        return self.metadata.source_url\n\n    download_url = source_url   # Backward compatibility\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 29,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 28,
        "n_identifiers": 4,
        "d_id": 12751,
        "documentation": {
            "docstring": "\n        The source archive download URL for this distribution.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 209792,
        "commit_id": "a2b7a28faff1db058dd22ce097a268e0ad5d1d33",
        "repo": "scapy",
        "path": "scapy/arch/windows/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "pcap_service_start",
        "commit_message": "[Hinty] Core typing: windows (#3684)\n\n* Core typing: windows\r\n\r\nCo-authored-by: Pierre <pierre@droids-corp.org>",
        "code": "def pcap_service_start(askadmin=True):\n    # type: (bool) -> bool\n    \n    return _pcap_service_control('sc start', askadmin=askadmin)\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 32,
        "n_identifiers": 3,
        "d_id": 52782,
        "documentation": {
            "docstring": "Starts the pcap adapter. Will ask for admin. Returns True if success",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 268734,
        "commit_id": "cda16cc5e9aa8703fb4e1ac0a0be6b631d9076cc",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/host_profiles.py",
        "file_name": "host_profiles.py",
        "fun_name": "create_systemd_cgroup_v1",
        "commit_message": "ansible-test - Improve container management. (#78550)\n\nSee changelogs/fragments/ansible-test-container-management.yml for details.",
        "code": "def create_systemd_cgroup_v1(self) -> str:\n        \n        self.cgroup_path = f'/sys/fs/cgroup/systemd/ansible-test-{self.label}'\n\n        # Privileged mode is required to create the cgroup directories on some hosts, such as Fedora 36 and RHEL 9.0.\n        # The mkdir command will fail with \"Permission denied\" otherwise.\n        options = ['--volume', '/sys/fs/cgroup/systemd:/sys/fs/cgroup/systemd:rw', '--privileged']\n        cmd = ['sh', '-c', f'>&2 echo {shlex.quote(self.MARKER)} && mkdir {shlex.quote(self.cgroup_path)}']\n\n        try:\n            run_utility_container(self.args, f'ansible-test-cgroup-create-{self.label}', cmd, options)\n        except SubprocessError as ex:\n            if error := self.extract_error(ex.stderr):\n                raise ControlGroupError(self.args, f'Unable to create a v1 cgroup within the systemd hierarchy.\\n'\n                                                   f'Reason: {error}') from ex  # cgroup create permission denied\n\n            raise\n\n        return self.cgroup_path\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 251,
        "n_words": 89,
        "vocab_size": 75,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 84,
        "n_ast_nodes": 193,
        "n_identifiers": 18,
        "d_id": 79634,
        "documentation": {
            "docstring": "Create a unique ansible-test cgroup in the v1 systemd hierarchy and return its path.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 215394,
        "commit_id": "ab4803984bce4a4de7cc10910e7310c4babf557e",
        "repo": "salt",
        "path": "salt/transport/base.py",
        "file_name": "base.py",
        "fun_name": "close",
        "commit_message": "Start to add base class defs",
        "code": "def close(self):\n        \n\n    # XXX:  Should have a connect too?\n    # def connect(self):\n    #    \n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
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        "token_counts": 6,
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        "n_identifiers": 2,
        "d_id": 53945,
        "documentation": {
            "docstring": "\n        Close the connection.\n        \n    #    Connect to the server / broker.\n    #    ",
            "n_words": 11,
            "vocab_size": 9,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 120507,
        "commit_id": "7ba36fc1784a7a286aa13ab7c098f84ff64336f1",
        "repo": "jax",
        "path": "jax/_src/scipy/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "polar",
        "commit_message": "Change implementation of jax.scipy.linalg.polar() and jax._src.scipy.eigh to use the QDWH decomposition from jax._src.lax.qdwh.\n\nRemove jax._src.lax.polar.\n\nPiperOrigin-RevId: 448241206",
        "code": "def polar(a, side='right', *, method='qdwh', eps=None, max_iterations=None):\n  r\n  a = jnp.asarray(a)\n  if a.ndim != 2:\n    raise ValueError(\"The input `a` must be a 2-D array.\")\n\n  if side not in [\"right\", \"left\"]:\n    raise ValueError(\"The argument `side` must be either 'right' or 'left'.\")\n\n  m, n = a.shape\n  if method == \"qdwh\":\n    # TODO(phawkins): return info also if the user opts in?\n    if m >= n and side == \"right\":\n      unitary, posdef, _, _ = qdwh.qdwh(a, is_hermitian=False, eps=eps)\n    elif m < n and side == \"left\":\n      a = a.T.conj()\n      unitary, posdef, _, _ = qdwh.qdwh(a, is_hermitian=False, eps=eps)\n      posdef = posdef.T.conj()\n      unitary = unitary.T.conj()\n    else:\n      raise NotImplementedError(\"method='qdwh' only supports mxn matrices \"\n                                \"where m < n where side='right' and m >= n \"\n                                f\"side='left', got {a.shape} with side={side}\")\n  elif method == \"svd\":\n    u_svd, s_svd, vh_svd = lax_linalg.svd(a, full_matrices=False)\n    unitary = u_svd @ vh_svd\n    if side == \"right\":\n      # a = u * p\n      posdef = (vh_svd.T.conj() * s_svd[None, :]) @ vh_svd\n    else:\n      # a = p * u\n      posdef = (u_svd * s_svd[None, :]) @ (u_svd.T.conj())\n  else:\n    raise ValueError(f\"Unknown polar decomposition method {method}.\")\n\n  return unitary, posdef\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
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        "complexity": 10,
        "nloc": 81,
        "token_counts": 258,
        "n_ast_nodes": 439,
        "n_identifiers": 27,
        "d_id": 26871,
        "documentation": {
            "docstring": "Computes the polar decomposition.\n\n  Given the :math:`m \\times n` matrix :math:`a`, returns the factors of the polar\n  decomposition :math:`u` (also :math:`m \\times n`) and :math:`p` such that\n  :math:`a = up` (if side is ``\"right\"``; :math:`p` is :math:`n \\times n`) or\n  :math:`a = pu` (if side is ``\"left\"``; :math:`p` is :math:`m \\times m`),\n  where :math:`p` is positive semidefinite.  If :math:`a` is nonsingular,\n  :math:`p` is positive definite and the\n  decomposition is unique. :math:`u` has orthonormal columns unless\n  :math:`n > m`, in which case it has orthonormal rows.\n\n  Writing the SVD of :math:`a` as\n  :math:`a = u_\\mathit{svd} \\cdot s_\\mathit{svd} \\cdot v^h_\\mathit{svd}`, we\n  have :math:`u = u_\\mathit{svd} \\cdot v^h_\\mathit{svd}`. Thus the unitary\n  factor :math:`u` can be constructed as the application of the sign function to\n  the singular values of :math:`a`; or, if :math:`a` is Hermitian, the\n  eigenvalues.\n\n  Several methods exist to compute the polar decomposition. Currently two\n  are supported:\n\n  * ``method=\"svd\"``:\n\n    Computes the SVD of :math:`a` and then forms\n    :math:`u = u_\\mathit{svd} \\cdot v^h_\\mathit{svd}`.\n\n  * ``method=\"qdwh\"``:\n\n    Applies the `QDWH`_ (QR-based Dynamically Weighted Halley) algorithm.\n\n  Args:\n    a: The :math:`m \\times n` input matrix.\n    side: Determines whether a right or left polar decomposition is computed.\n      If ``side`` is ``\"right\"`` then :math:`a = up`. If ``side`` is ``\"left\"``\n      then :math:`a = pu`. The default is ``\"right\"``.\n    method: Determines the algorithm used, as described above.\n    precision: :class:`~jax.lax.Precision` object specifying the matmul precision.\n    eps: The final result will satisfy\n      :math:`\\left|x_k - x_{k-1}\\right| < \\left|x_k\\right| (4\\epsilon)^{\\frac{1}{3}}`,\n      where :math:`x_k` are the QDWH iterates. Ignored if ``method`` is not\n      ``\"qdwh\"``.\n    max_iterations: Iterations will terminate after this many steps even if the\n      above is unsatisfied.  Ignored if ``method`` is not ``\"qdwh\"``.\n\n  Returns:\n    A ``(unitary, posdef)`` tuple, where ``unitary`` is the unitary factor\n    (:math:`m \\times n`), and ``posdef`` is the positive-semidefinite factor.\n    ``posdef`` is either :math:`n \\times n` or :math:`m \\times m` depending on\n    whether ``side`` is ``\"right\"`` or ``\"left\"``, respectively.\n\n  .. _QDWH: https://epubs.siam.org/doi/abs/10.1137/090774999\n  ",
            "n_words": 310,
            "vocab_size": 178,
            "n_whitespaces": 403,
            "language": "en"
        }
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    {
        "id": 271877,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_utils_v1.py",
        "file_name": "training_utils_v1.py",
        "fun_name": "aggregate",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def aggregate(self, batch_outs, batch_start=None, batch_end=None):\n        \n        raise NotImplementedError(\"Must be implemented in subclasses.\")\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
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        "complexity": 1,
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        "token_counts": 21,
        "n_ast_nodes": 35,
        "n_identifiers": 6,
        "d_id": 80886,
        "documentation": {
            "docstring": "Aggregates batch-level results into total results.\n\n        Args:\n          batch_outs: A list of batch-level outputs.\n          batch_start: The start index of this batch. Always `None` if `use_steps`\n            is `True`.\n          batch_end: The end index of this batch. Always `None` if `use_steps` is\n            `True`.\n        ",
            "n_words": 39,
            "vocab_size": 26,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 206274,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/engine.py",
        "file_name": "engine.py",
        "fun_name": "get_default",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_default():\n        \n        # Since Engine is imported in django.template and since\n        # DjangoTemplates is a wrapper around this Engine class,\n        # local imports are required to avoid import loops.\n        from django.template import engines\n        from django.template.backends.django import DjangoTemplates\n\n        for engine in engines.all():\n            if isinstance(engine, DjangoTemplates):\n                return engine.engine\n        raise ImproperlyConfigured(\"No DjangoTemplates backend is configured.\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 134,
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        "vocab_size": 40,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 79,
        "n_identifiers": 10,
        "d_id": 51461,
        "documentation": {
            "docstring": "\n        Return the first DjangoTemplates backend that's configured, or raise\n        ImproperlyConfigured if none are configured.\n\n        This is required for preserving historical APIs that rely on a\n        globally available, implicitly configured engine such as:\n\n        >>> from django.template import Context, Template\n        >>> template = Template(\"Hello {{ name }}!\")\n        >>> context = Context({'name': \"world\"})\n        >>> template.render(context)\n        'Hello world!'\n        ",
            "n_words": 54,
            "vocab_size": 50,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 181621,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/export_tests.py",
        "file_name": "export_tests.py",
        "fun_name": "test_get_by_name_3",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_get_by_name_3():\n    \n\n    # no duplicate\n    ret_op_class = get_by_name(\"SelectPercentile\", tpot_obj.operators)\n    # add a copy of TPOTSelectPercentile into operator list\n    tpot_obj.operators.append(TPOTSelectPercentile)\n    assert_raises(ValueError, get_by_name, \"SelectPercentile\", tpot_obj.operators)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 41,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 62,
        "n_identifiers": 9,
        "d_id": 43409,
        "documentation": {
            "docstring": "Assert that get_by_name raises ValueError with duplicate operators in operator dictionary.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 156035,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/array/core.py",
        "file_name": "core.py",
        "fun_name": "to_dask_dataframe",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def to_dask_dataframe(self, columns=None, index=None, meta=None):\n        \n        from dask.dataframe import from_dask_array\n\n        return from_dask_array(self, columns=columns, index=index, meta=meta)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 41,
        "n_ast_nodes": 60,
        "n_identifiers": 8,
        "d_id": 36513,
        "documentation": {
            "docstring": "Convert dask Array to dask Dataframe\n\n        Parameters\n        ----------\n        columns: list or string\n            list of column names if DataFrame, single string if Series\n        index : dask.dataframe.Index, optional\n            An optional *dask* Index to use for the output Series or DataFrame.\n\n            The default output index depends on whether the array has any unknown\n            chunks. If there are any unknown chunks, the output has ``None``\n            for all the divisions (one per chunk). If all the chunks are known,\n            a default index with known divsions is created.\n\n            Specifying ``index`` can be useful if you're conforming a Dask Array\n            to an existing dask Series or DataFrame, and you would like the\n            indices to match.\n        meta : object, optional\n            An optional `meta` parameter can be passed for dask\n            to specify the concrete dataframe type to use for partitions of\n            the Dask dataframe. By default, pandas DataFrame is used.\n\n        See Also\n        --------\n        dask.dataframe.from_dask_array\n        ",
            "n_words": 145,
            "vocab_size": 94,
            "n_whitespaces": 340,
            "language": "en"
        }
    },
    {
        "id": 49781,
        "commit_id": "f4d6e64cdc132ae868699a0ba442f4ab1d304a14",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/gaussian_diffusion.py",
        "file_name": "gaussian_diffusion.py",
        "fun_name": "condition_score_with_grad",
        "commit_message": "add disco_diffusion_cnclip_vitb16 module",
        "code": "def condition_score_with_grad(self, cond_fn, p_mean_var, x, t, model_kwargs=None):\n        \n        alpha_bar = _extract_into_tensor(self.alphas_cumprod, t, x.shape)\n\n        eps = self._predict_eps_from_xstart(x, t, p_mean_var[\"pred_xstart\"])\n        eps = eps - (1 - alpha_bar).sqrt() * cond_fn(x, t, p_mean_var, **model_kwargs)\n\n        out = p_mean_var.copy()\n        out[\"pred_xstart\"] = self._predict_xstart_from_eps(x, t, eps)\n        out[\"mean\"], _, _ = self.q_posterior_mean_variance(x_start=out[\"pred_xstart\"], x_t=x, t=t)\n        return out\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 102,
        "n_words": 46,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 124,
        "n_ast_nodes": 187,
        "n_identifiers": 21,
        "d_id": 9905,
        "documentation": {
            "docstring": "\n        Compute what the p_mean_variance output would have been, should the\n        model's score function be conditioned by cond_fn.\n\n        See condition_mean() for details on cond_fn.\n\n        Unlike condition_mean(), this instead uses the conditioning strategy\n        from Song et al (2020).\n        ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 91654,
        "commit_id": "0ad4aa9d9fe3beb3fd20aaedd961b3c2c800efb1",
        "repo": "sentry",
        "path": "src/django_picklefield/fields.py",
        "file_name": "fields.py",
        "fun_name": "get_db_prep_value",
        "commit_message": "ref(django-3.2): Vendor django picklefield (#35727)\n\n* ref(django-3.2): Vendor django picklefield\r\n\r\nDjango-picklefield hasn't been updated in 2 years, but we need it. We also need to upgrade to django 3.2 which means we need to update picklefield.\r\n\r\n* Remove reference to django-picklefield\r\n\r\n* Fix the module name to use underscore\r\n\r\n* style(lint): Auto commit lint changes\r\n\r\n* Remove versioning code\r\n\r\nCo-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>",
        "code": "def get_db_prep_value(self, value, connection=None, prepared=False):\n        \n        if value is not None and not isinstance(value, PickledObject):\n            # We call force_str here explicitly, so that the encoded string\n            # isn't rejected by the postgresql_psycopg2 backend. Alternatively,\n            # we could have just registered PickledObject with the psycopg\n            # marshaller (telling it to store it like it would a string), but\n            # since both of these methods result in the same value being stored,\n            # doing things this way is much easier.\n            value = force_str(dbsafe_encode(value, self.compress, self.protocol, self.copy))\n        return value\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 183,
        "n_words": 85,
        "vocab_size": 70,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 53,
        "n_ast_nodes": 85,
        "n_identifiers": 12,
        "d_id": 18774,
        "documentation": {
            "docstring": "\n        Pickle and b64encode the object, optionally compressing it.\n\n        The pickling protocol is specified explicitly (by default 2),\n        rather than as -1 or HIGHEST_PROTOCOL, because we don't want the\n        protocol to change over time. If it did, ``exact`` and ``in``\n        lookups would likely fail, since pickle would now be generating\n        a different string.\n\n        ",
            "n_words": 52,
            "vocab_size": 48,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 114643,
        "commit_id": "ce99adc96da2e6f98f722f9e3733af00204b26f3",
        "repo": "mindsdb",
        "path": "tests/integration_tests/flows/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_08_sql_create_predictor",
        "commit_message": "http test",
        "code": "def test_08_sql_create_predictor(self):\n        resp = self.sql_via_http('show predictors', RESPONSE_TYPE.TABLE)\n        self.assertTrue(len(resp['data']) == 0)\n\n        self.sql_via_http(, RESPONSE_TYPE.OK)\n        status = self.await_predictor('p_test_1', timeout=120)\n        self.assertTrue(status == 'complete')\n\n        resp = self.sql_via_http(, RESPONSE_TYPE.TABLE)\n        sqft_index = resp['column_names'].index('sqft')\n        rental_price_index = resp['column_names'].index('rental_price')\n        self.assertTrue(len(resp['data']) == 1)\n        self.assertTrue(resp['data'][0][sqft_index] == 1000)\n        self.assertTrue(resp['data'][0][rental_price_index] > 0)\n\n        resp = self.sql_via_http(, RESPONSE_TYPE.TABLE)\n        rental_price_index = resp['column_names'].index('rental_price')\n        self.assertTrue(len(resp['data']) == 5)\n        # FIXME rental price is str instead of float\n        # for row in resp['data']:\n        #     self.assertTrue(row[rental_price_index] > 0)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 188,
        "n_words": 66,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 180,
        "n_ast_nodes": 313,
        "n_identifiers": 15,
        "d_id": 25244,
        "documentation": {
            "docstring": "\n            create predictor p_test_1\n            from files (select sqft, location, rental_price from test_file limit 30)\n            predict rental_price\n        \n            select * from mindsdb.p_test_1 where sqft = 1000\n        \n            select * from files.small_test_file ta join mindsdb.p_test_1\n        ",
            "n_words": 30,
            "vocab_size": 23,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 260485,
        "commit_id": "912a71788eaca2a6b87aced510781cb88b38f14c",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/pairwise.py",
        "file_name": "pairwise.py",
        "fun_name": "paired_manhattan_distances",
        "commit_message": "DOC Update `paired_manhattan_distances` and make it pass numpydoc validation (#23900)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def paired_manhattan_distances(X, Y):\n    \n    X, Y = check_paired_arrays(X, Y)\n    diff = X - Y\n    if issparse(diff):\n        diff.data = np.abs(diff.data)\n        return np.squeeze(np.array(diff.sum(axis=1)))\n    else:\n        return np.abs(diff).sum(axis=-1)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 59,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 77,
        "n_ast_nodes": 125,
        "n_identifiers": 13,
        "d_id": 76281,
        "documentation": {
            "docstring": "Compute the paired L1 distances between X and Y.\n\n    Distances are calculated between (X[0], Y[0]), (X[1], Y[1]), ...,\n    (X[n_samples], Y[n_samples]).\n\n    Read more in the :ref:`User Guide <metrics>`.\n\n    Parameters\n    ----------\n    X : array-like of shape (n_samples, n_features)\n        An array-like where each row is a sample and each column is a feature.\n\n    Y : array-like of shape (n_samples, n_features)\n        An array-like where each row is a sample and each column is a feature.\n\n    Returns\n    -------\n    distances : ndarray of shape (n_samples,)\n        L1 paired distances between the row vectors of `X`\n        and the row vectors of `Y`.\n\n    Examples\n    --------\n    >>> from sklearn.metrics.pairwise import paired_manhattan_distances\n    >>> import numpy as np\n    >>> X = np.array([[1, 1, 0], [0, 1, 0], [0, 0, 1]])\n    >>> Y = np.array([[0, 1, 0], [0, 0, 1], [0, 0, 0]])\n    >>> paired_manhattan_distances(X, Y)\n    array([1., 2., 1.])\n    ",
            "n_words": 136,
            "vocab_size": 75,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 154350,
        "commit_id": "c5107e5be29089720528c6c0ec4f96bc2a6a1eb3",
        "repo": "modin",
        "path": "modin/core/io/file_dispatcher.py",
        "file_name": "file_dispatcher.py",
        "fun_name": "get_path",
        "commit_message": "FEAT-#4766: Support fsspec URLs in `read_csv` and `read_csv_glob` (#4898)\n\nSigned-off-by: Karthik Velayutham <vkarthik@ponder.io>",
        "code": "def get_path(cls, file_path):\n        \n        if is_fsspec_url(file_path) or is_url(file_path):\n            return file_path\n        else:\n            return os.path.abspath(file_path)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 55,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 32,
        "n_ast_nodes": 54,
        "n_identifiers": 8,
        "d_id": 35943,
        "documentation": {
            "docstring": "\n        Process `file_path` in accordance to it's type.\n\n        Parameters\n        ----------\n        file_path : str, os.PathLike[str] object or file-like object\n            The file, or a path to the file. Paths to S3 buckets are also\n            acceptable.\n\n        Returns\n        -------\n        str\n            Updated or verified `file_path` parameter.\n\n        Notes\n        -----\n        if `file_path` is a URL, parameter will be returned as is, otherwise\n        absolute path will be returned.\n        ",
            "n_words": 59,
            "vocab_size": 48,
            "n_whitespaces": 177,
            "language": "en"
        }
    },
    {
        "id": 109223,
        "commit_id": "a8c01a42c5bbe96fa6c536c72e6c26954c798908",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "broken_barh",
        "commit_message": "BUG: modified safe_first_element and added tests\n\nCo-authored-by: Thomas A Caswell <tcaswell@gmail.com>",
        "code": "def broken_barh(self, xranges, yrange, **kwargs):\n        \n        # process the unit information\n        if len(xranges):\n            xdata = cbook._safe_first_non_none(xranges)\n        else:\n            xdata = None\n        if len(yrange):\n            ydata = cbook._safe_first_non_none(yrange)\n        else:\n            ydata = None\n        self._process_unit_info(\n            [(\"x\", xdata), (\"y\", ydata)], kwargs, convert=False)\n        xranges_conv = []\n        for xr in xranges:\n            if len(xr) != 2:\n                raise ValueError('each range in xrange must be a sequence '\n                                 'with two elements (i.e. an Nx2 array)')\n            # convert the absolute values, not the x and dx...\n            x_conv = np.asarray(self.convert_xunits(xr[0]))\n            x1 = self._convert_dx(xr[1], xr[0], x_conv, self.convert_xunits)\n            xranges_conv.append((x_conv, x1))\n\n        yrange_conv = self.convert_yunits(yrange)\n\n        col = mcoll.BrokenBarHCollection(xranges_conv, yrange_conv, **kwargs)\n        self.add_collection(col, autolim=True)\n        self._request_autoscale_view()\n\n        return col\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 352,
        "n_words": 97,
        "vocab_size": 78,
        "complexity": 5,
        "nloc": 24,
        "token_counts": 184,
        "n_ast_nodes": 293,
        "n_identifiers": 30,
        "d_id": 23482,
        "documentation": {
            "docstring": "\n        Plot a horizontal sequence of rectangles.\n\n        A rectangle is drawn for each element of *xranges*. All rectangles\n        have the same vertical position and size defined by *yrange*.\n\n        This is a convenience function for instantiating a\n        `.BrokenBarHCollection`, adding it to the Axes and autoscaling the\n        view.\n\n        Parameters\n        ----------\n        xranges : sequence of tuples (*xmin*, *xwidth*)\n            The x-positions and extends of the rectangles. For each tuple\n            (*xmin*, *xwidth*) a rectangle is drawn from *xmin* to *xmin* +\n            *xwidth*.\n        yrange : (*ymin*, *yheight*)\n            The y-position and extend for all the rectangles.\n\n        Returns\n        -------\n        `~.collections.BrokenBarHCollection`\n\n        Other Parameters\n        ----------------\n        data : indexable object, optional\n            DATA_PARAMETER_PLACEHOLDER\n        **kwargs : `.BrokenBarHCollection` properties\n\n            Each *kwarg* can be either a single argument applying to all\n            rectangles, e.g.::\n\n                facecolors='black'\n\n            or a sequence of arguments over which is cycled, e.g.::\n\n                facecolors=('black', 'blue')\n\n            would create interleaving black and blue rectangles.\n\n            Supported keywords:\n\n            %(BrokenBarHCollection:kwdoc)s\n        ",
            "n_words": 140,
            "vocab_size": 98,
            "n_whitespaces": 418,
            "language": "en"
        }
    },
    {
        "id": 207004,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_changelist/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_custom_user_pk_not_named_id",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_custom_user_pk_not_named_id(self):\n        \n        context = Context({\"user\": CustomIdUser()})\n        template = Template(\n            \"{% load log %}{% get_admin_log 10 as admin_log for_user user %}\"\n        )\n        # This template tag just logs.\n        self.assertEqual(template.render(context), \"\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 82,
        "n_words": 29,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 37,
        "n_ast_nodes": 70,
        "n_identifiers": 9,
        "d_id": 51831,
        "documentation": {
            "docstring": "\n        {% get_admin_log %} works if the user model's primary key isn't named\n        'id'.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 19673,
        "commit_id": "9a3b3ce70621af6f9adaa9eeac9cf83fa149319c",
        "repo": "pipenv",
        "path": "pipenv/environment.py",
        "file_name": "environment.py",
        "fun_name": "dist_is_in_project",
        "commit_message": "Issue 4993 Add standard pre commit hooks and apply linting. (#4994)\n\n* Add .pre-commit-config.yaml to the project and exclude tests (for now).  This does not include the MyPy linting that pip does but does include everything else.",
        "code": "def dist_is_in_project(self, dist):\n        # type: (pkg_resources.Distribution) -> bool\n        \n        from .environments import normalize_pipfile_path as _normalized\n\n        prefixes = [\n            _normalized(prefix)\n            for prefix in self.base_paths[\"libdirs\"].split(os.pathsep)\n            if _normalized(prefix).startswith(_normalized(self.prefix.as_posix()))\n        ]\n        location = self.locate_dist(dist)\n        if not location:\n            return False\n        location = _normalized(make_posix(location))\n        return any(location.startswith(prefix) for prefix in prefixes)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 149,
        "n_words": 42,
        "vocab_size": 34,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 95,
        "n_ast_nodes": 157,
        "n_identifiers": 18,
        "d_id": 3056,
        "documentation": {
            "docstring": "Determine whether the supplied distribution is in the environment.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 94501,
        "commit_id": "7bbb85a0d95d23620228a02bb4401fc09658f5f1",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/test_all_indexers.py",
        "file_name": "test_all_indexers.py",
        "fun_name": "test_rate_limited",
        "commit_message": "ref(metrics): Split caching out of indexers, random test refactoring [sns-1606] (#37714)",
        "code": "def test_rate_limited(indexer):\n    \n    if isinstance(indexer, RawSimpleIndexer):\n        pytest.skip(\"mock indexer does not support rate limiting\")\n\n    org_strings = {1: {\"a\", \"b\", \"c\"}, 2: {\"e\", \"f\"}, 3: {\"g\"}}\n\n    with override_options(\n        {\n            \"sentry-metrics.writes-limiter.limits.releasehealth.per-org\": [\n                {\"window_seconds\": 10, \"granularity_seconds\": 10, \"limit\": 1}\n            ],\n        }\n    ):\n        results = indexer.bulk_record(use_case_id=use_case_id, org_strings=org_strings)\n\n    assert len(results[1]) == 3\n    assert len(results[2]) == 2\n    assert len(results[3]) == 1\n    assert results[3][\"g\"] is not None\n\n    rate_limited_strings = set()\n\n    for org_id in 1, 2, 3:\n        for k, v in results[org_id].items():\n            if v is None:\n                rate_limited_strings.add((org_id, k))\n\n    assert len(rate_limited_strings) == 3\n    assert (3, \"g\") not in rate_limited_strings\n\n    for org_id, string in rate_limited_strings:\n        assert results.get_fetch_metadata()[org_id][string] == Metadata(\n            id=None,\n            fetch_type=FetchType.RATE_LIMITED,\n            fetch_type_ext=FetchTypeExt(is_global=False),\n        )\n\n    org_strings = {1: {\"x\", \"y\", \"z\"}}\n\n    # attempt to index even more strings, and assert that we can't get any indexed\n    with override_options(\n        {\n            \"sentry-metrics.writes-limiter.limits.releasehealth.per-org\": [\n                {\"window_seconds\": 10, \"granularity_seconds\": 10, \"limit\": 1}\n            ],\n        }\n    ):\n        results = indexer.bulk_record(use_case_id=use_case_id, org_strings=org_strings)\n\n    assert results[1] == {\"x\": None, \"y\": None, \"z\": None}\n    for letter in \"xyz\":\n        assert results.get_fetch_metadata()[1][letter] == Metadata(\n            id=None,\n            fetch_type=FetchType.RATE_LIMITED,\n            fetch_type_ext=FetchTypeExt(is_global=False),\n        )\n\n    org_strings = {1: rate_limited_strings}\n\n    # assert that if we reconfigure limits, the quota resets\n    with override_options(\n        {\n            \"sentry-metrics.writes-limiter.limits.releasehealth.global\": [\n                {\"window_seconds\": 10, \"granularity_seconds\": 10, \"limit\": 2}\n            ],\n        }\n    ):\n        results = indexer.bulk_record(use_case_id=use_case_id, org_strings=org_strings)\n\n    rate_limited_strings2 = set()\n    for k, v in results[1].items():\n        if v is None:\n            rate_limited_strings2.add(k)\n\n    assert len(rate_limited_strings2) == 1\n    assert len(rate_limited_strings - rate_limited_strings2) == 2\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 626,
        "n_words": 216,
        "vocab_size": 116,
        "complexity": 9,
        "nloc": 60,
        "token_counts": 431,
        "n_ast_nodes": 701,
        "n_identifiers": 31,
        "d_id": 19098,
        "documentation": {
            "docstring": "\n    Assert that rate limits per-org and globally are applied at all.\n\n    Since we don't have control over ordering in sets/dicts, we have no\n    control over which string gets rate-limited. That makes assertions\n    quite awkward and imprecise.\n    ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 185332,
        "commit_id": "bd3a723d86f9c550b0324153975580b70509cb22",
        "repo": "textual",
        "path": "src/textual/events.py",
        "file_name": "events.py",
        "fun_name": "key_aliases",
        "commit_message": "Move aliasing/normalisation logic into Key",
        "code": "def key_aliases(self) -> Iterable[str]:\n        \n        for alias in _get_key_aliases(self.key):\n            yield _normalize_key(alias)\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 44,
        "n_identifiers": 8,
        "d_id": 44978,
        "documentation": {
            "docstring": "Get the aliases for the key, including the key itself",
            "n_words": 10,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 204855,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/introspection.py",
        "file_name": "introspection.py",
        "fun_name": "get_primary_key_column",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_primary_key_column(self, cursor, table_name):\n        \n        for constraint in self.get_constraints(cursor, table_name).values():\n            if constraint[\"primary_key\"]:\n                return constraint[\"columns\"][0]\n        return None\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 62,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 42,
        "n_ast_nodes": 68,
        "n_identifiers": 7,
        "d_id": 50933,
        "documentation": {
            "docstring": "\n        Return the name of the primary key column for the given table.\n        ",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 260499,
        "commit_id": "60c5d320e1478514e6bbe31fd0347692591cca9e",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/pairwise.py",
        "file_name": "pairwise.py",
        "fun_name": "cosine_similarity",
        "commit_message": "DOC Ensure `cosine_similarity` passes numpydoc validation (#23947)",
        "code": "def cosine_similarity(X, Y=None, dense_output=True):\n    \n    # to avoid recursive import\n\n    X, Y = check_pairwise_arrays(X, Y)\n\n    X_normalized = normalize(X, copy=True)\n    if X is Y:\n        Y_normalized = X_normalized\n    else:\n        Y_normalized = normalize(Y, copy=True)\n\n    K = safe_sparse_dot(X_normalized, Y_normalized.T, dense_output=dense_output)\n\n    return K\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 75,
        "n_words": 37,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 70,
        "n_ast_nodes": 110,
        "n_identifiers": 12,
        "d_id": 76294,
        "documentation": {
            "docstring": "Compute cosine similarity between samples in X and Y.\n\n    Cosine similarity, or the cosine kernel, computes similarity as the\n    normalized dot product of X and Y:\n\n        K(X, Y) = <X, Y> / (||X||*||Y||)\n\n    On L2-normalized data, this function is equivalent to linear_kernel.\n\n    Read more in the :ref:`User Guide <cosine_similarity>`.\n\n    Parameters\n    ----------\n    X : {ndarray, sparse matrix} of shape (n_samples_X, n_features)\n        Input data.\n\n    Y : {ndarray, sparse matrix} of shape (n_samples_Y, n_features), \\\n            default=None\n        Input data. If ``None``, the output will be the pairwise\n        similarities between all samples in ``X``.\n\n    dense_output : bool, default=True\n        Whether to return dense output even when the input is sparse. If\n        ``False``, the output is sparse if both input arrays are sparse.\n\n        .. versionadded:: 0.17\n           parameter ``dense_output`` for dense output.\n\n    Returns\n    -------\n    kernel matrix : ndarray of shape (n_samples_X, n_samples_Y)\n        Returns the cosine similarity between samples in X and Y.\n    ",
            "n_words": 144,
            "vocab_size": 95,
            "n_whitespaces": 260,
            "language": "en"
        }
    },
    {
        "id": 19689,
        "commit_id": "9a3b3ce70621af6f9adaa9eeac9cf83fa149319c",
        "repo": "pipenv",
        "path": "pipenv/environments.py",
        "file_name": "environments.py",
        "fun_name": "_is_env_truthy",
        "commit_message": "Issue 4993 Add standard pre commit hooks and apply linting. (#4994)\n\n* Add .pre-commit-config.yaml to the project and exclude tests (for now).  This does not include the MyPy linting that pip does but does include everything else.",
        "code": "def _is_env_truthy(name):\n    \n    if name not in os.environ:\n        return False\n    return os.environ.get(name).lower() not in _false_values\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 30,
        "n_words": 14,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 3067,
        "documentation": {
            "docstring": "An environment variable is truthy if it exists and isn't one of (0, false, no, off)",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 176369,
        "commit_id": "28b3014d68d2b4e40d3e02219770296a827bd55c",
        "repo": "networkx",
        "path": "networkx/algorithms/matching.py",
        "file_name": "matching.py",
        "fun_name": "min_weight_matching",
        "commit_message": "Update matching functions for error validation and speed (#4897)\n\n* First steps to update matching functions for #4644\r\n\r\nExpand tests\r\nChange API to raise NetworkXError when matching involves nodes not in G\r\nUpdate is_*_matching to 100+ times faster.\r\n\r\n* improve matching_dict_to_set and docs for min_weight_matching\r\n\r\n* fix sphinx error",
        "code": "def min_weight_matching(G, maxcardinality=False, weight=\"weight\"):\n    \n    if len(G.edges) == 0:\n        return max_weight_matching(G, maxcardinality, weight)\n    G_edges = G.edges(data=weight, default=1)\n    min_weight = min(w for _, _, w in G_edges)\n    InvG = nx.Graph()\n    edges = ((u, v, 1 / (1 + w - min_weight)) for u, v, w in G_edges)\n    InvG.add_weighted_edges_from(edges, weight=weight)\n    return max_weight_matching(InvG, maxcardinality, weight)\n\n\n@not_implemented_for(\"multigraph\")\n@not_implemented_for(\"directed\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"multigraph\")\n@not_implemented_for(\"directed\")",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 82,
        "n_words": 53,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 114,
        "n_ast_nodes": 191,
        "n_identifiers": 21,
        "d_id": 41855,
        "documentation": {
            "docstring": "Computing a minimum-weight maximal matching of G.\n\n    Use reciprocal edge weights with the maximum-weight algorithm.\n\n    A matching is a subset of edges in which no node occurs more than once.\n    The weight of a matching is the sum of the weights of its edges.\n    A maximal matching cannot add more edges and still be a matching.\n    The cardinality of a matching is the number of matched edges.\n\n    This method replaces the weights with their reciprocal and\n    then runs :func:`max_weight_matching`.\n    Read the documentation of max_weight_matching for more information.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n      Undirected graph\n\n    maxcardinality: bool, optional (default=False)\n       If maxcardinality is True, compute the maximum-cardinality matching\n       with minimum weight among all maximum-cardinality matchings.\n\n    weight: string, optional (default='weight')\n       Edge data key corresponding to the edge weight.\n       If key not found, uses 1 as weight.\n\n    Returns\n    -------\n    matching : set\n        A minimal weight matching of the graph.\n    ",
            "n_words": 146,
            "vocab_size": 92,
            "n_whitespaces": 233,
            "language": "en"
        }
    },
    {
        "id": 167667,
        "commit_id": "67e8c4c3761ab1da4b0a341a472c0fe2ea393e8b",
        "repo": "pandas",
        "path": "pandas/core/dtypes/common.py",
        "file_name": "common.py",
        "fun_name": "is_datetime64_ns_dtype",
        "commit_message": "ENH: DTI/DTA.astype support non-nano (#47579)\n\n* ENH: DTI/DTA.astype support non-nano\r\n\r\n* whatsnew\r\n\r\n* GH ref\r\n\r\n* pyright fixup",
        "code": "def is_datetime64_ns_dtype(arr_or_dtype) -> bool:\n    \n    if arr_or_dtype is None:\n        return False\n    try:\n        tipo = get_dtype(arr_or_dtype)\n    except TypeError:\n        if is_datetime64tz_dtype(arr_or_dtype):\n            tipo = get_dtype(arr_or_dtype.dtype)\n        else:\n            return False\n    return tipo == DT64NS_DTYPE or (\n        isinstance(tipo, DatetimeTZDtype) and tipo._unit == \"ns\"\n    )\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 112,
        "n_words": 37,
        "vocab_size": 29,
        "complexity": 6,
        "nloc": 47,
        "token_counts": 63,
        "n_ast_nodes": 106,
        "n_identifiers": 12,
        "d_id": 40074,
        "documentation": {
            "docstring": "\n    Check whether the provided array or dtype is of the datetime64[ns] dtype.\n\n    Parameters\n    ----------\n    arr_or_dtype : array-like or dtype\n        The array or dtype to check.\n\n    Returns\n    -------\n    bool\n        Whether or not the array or dtype is of the datetime64[ns] dtype.\n\n    Examples\n    --------\n    >>> is_datetime64_ns_dtype(str)\n    False\n    >>> is_datetime64_ns_dtype(int)\n    False\n    >>> is_datetime64_ns_dtype(np.datetime64)  # no unit\n    False\n    >>> is_datetime64_ns_dtype(DatetimeTZDtype(\"ns\", \"US/Eastern\"))\n    True\n    >>> is_datetime64_ns_dtype(np.array(['a', 'b']))\n    False\n    >>> is_datetime64_ns_dtype(np.array([1, 2]))\n    False\n    >>> is_datetime64_ns_dtype(np.array([], dtype=\"datetime64\"))  # no unit\n    False\n    >>> is_datetime64_ns_dtype(np.array([], dtype=\"datetime64[ps]\"))  # wrong unit\n    False\n    >>> is_datetime64_ns_dtype(pd.DatetimeIndex([1, 2, 3], dtype=\"datetime64[ns]\"))\n    True\n    ",
            "n_words": 86,
            "vocab_size": 49,
            "n_whitespaces": 188,
            "language": "en"
        }
    },
    {
        "id": 200290,
        "commit_id": "6d2bbf80752549276a968fd4af78231c569d55c5",
        "repo": "sympy",
        "path": "sympy/testing/runtests.py",
        "file_name": "runtests.py",
        "fun_name": "raise_on_deprecated",
        "commit_message": "runtests.py: Undo auto-formatting, re-add changes to blacklist for scipy, numpy",
        "code": "def raise_on_deprecated():\n    \n    with warnings.catch_warnings():\n        warnings.filterwarnings('error', '.*', DeprecationWarning, module='sympy.*')\n        yield\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 29,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 27,
        "n_ast_nodes": 54,
        "n_identifiers": 6,
        "d_id": 49585,
        "documentation": {
            "docstring": "Context manager to make DeprecationWarning raise an error\n\n    This is to catch SymPyDeprecationWarning from library code while running\n    tests and doctests. It is important to use this context manager around\n    each individual test/doctest in case some tests modify the warning\n    filters.\n    ",
            "n_words": 41,
            "vocab_size": 36,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 261829,
        "commit_id": "2cce02414d4a7161f0d105450c196d94b1182220",
        "repo": "scikit-learn",
        "path": "sklearn/naive_bayes.py",
        "file_name": "naive_bayes.py",
        "fun_name": "_update_mean_variance",
        "commit_message": "TST Add common tests for single class fitting induced by sample weights (#24140)\n\nCo-authored-by: johayon <johayon.math@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def _update_mean_variance(n_past, mu, var, X, sample_weight=None):\n        \n        if X.shape[0] == 0:\n            return mu, var\n\n        # Compute (potentially weighted) mean and variance of new datapoints\n        if sample_weight is not None:\n            n_new = float(sample_weight.sum())\n            if np.isclose(n_new, 0.0):\n                return mu, var\n            new_mu = np.average(X, axis=0, weights=sample_weight)\n            new_var = np.average((X - new_mu) ** 2, axis=0, weights=sample_weight)\n        else:\n            n_new = X.shape[0]\n            new_var = np.var(X, axis=0)\n            new_mu = np.mean(X, axis=0)\n\n        if n_past == 0:\n            return new_mu, new_var\n\n        n_total = float(n_past + n_new)\n\n        # Combine mean of old and new data, taking into consideration\n        # (weighted) number of observations\n        total_mu = (n_new * new_mu + n_past * mu) / n_total\n\n        # Combine variance of old and new data, taking into consideration\n        # (weighted) number of observations. This is achieved by combining\n        # the sum-of-squared-differences (ssd)\n        old_ssd = n_past * var\n        new_ssd = n_new * new_var\n        total_ssd = old_ssd + new_ssd + (n_new * n_past / n_total) * (mu - new_mu) ** 2\n        total_var = total_ssd / n_total\n\n        return total_mu, total_var\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 402,
        "n_words": 162,
        "vocab_size": 81,
        "complexity": 5,
        "nloc": 22,
        "token_counts": 204,
        "n_ast_nodes": 314,
        "n_identifiers": 24,
        "d_id": 77021,
        "documentation": {
            "docstring": "Compute online update of Gaussian mean and variance.\n\n        Given starting sample count, mean, and variance, a new set of\n        points X, and optionally sample weights, return the updated mean and\n        variance. (NB - each dimension (column) in X is treated as independent\n        -- you get variance, not covariance).\n\n        Can take scalar mean and variance, or vector mean and variance to\n        simultaneously update a number of independent Gaussians.\n\n        See Stanford CS tech report STAN-CS-79-773 by Chan, Golub, and LeVeque:\n\n        http://i.stanford.edu/pub/cstr/reports/cs/tr/79/773/CS-TR-79-773.pdf\n\n        Parameters\n        ----------\n        n_past : int\n            Number of samples represented in old mean and variance. If sample\n            weights were given, this should contain the sum of sample\n            weights represented in old mean and variance.\n\n        mu : array-like of shape (number of Gaussians,)\n            Means for Gaussians in original set.\n\n        var : array-like of shape (number of Gaussians,)\n            Variances for Gaussians in original set.\n\n        sample_weight : array-like of shape (n_samples,), default=None\n            Weights applied to individual samples (1. for unweighted).\n\n        Returns\n        -------\n        total_mu : array-like of shape (number of Gaussians,)\n            Updated mean for each Gaussian over the combined set.\n\n        total_var : array-like of shape (number of Gaussians,)\n            Updated variance for each Gaussian over the combined set.\n        ",
            "n_words": 191,
            "vocab_size": 105,
            "n_whitespaces": 412,
            "language": "en"
        }
    },
    {
        "id": 33107,
        "commit_id": "c72d7d91bf4899760725793421eff9da640c8527",
        "repo": "transformers",
        "path": "src/transformers/models/xglm/modeling_tf_xglm.py",
        "file_name": "modeling_tf_xglm.py",
        "fun_name": "serving_output",
        "commit_message": "Add TF implementation of `XGLMModel` (#16543)\n\n* Add TFXGLM models \r\n\r\n* Add todo: self.supports_xla_generation = False\r\n\r\nCo-authored-by: Daniel Stancl <stancld@Daniels-MacBook-Pro.local>\r\nCo-authored-by: Daniel Stancl <stancld@daniels-mbp.home>\r\nCo-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>\r\nCo-authored-by: Daniel <daniel.stancl@rossum.ai>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def serving_output(self, output):\n        pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None\n        hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None\n        attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None\n        cross_attns = (\n            tf.convert_to_tensor(output.cross_attentions)\n            if self.config.output_attentions and self.config.add_cross_attention\n            else None\n        )\n\n        return TFBaseModelOutputWithPastAndCrossAttentions(\n            last_hidden_state=output.hidden_states,\n            past_key_values=pkv,\n            hidden_states=hs,\n            attentions=attns,\n            cross_attentions=cross_attns,\n        )\n\n\n@add_start_docstrings(\n    ,\n    XGLM_START_DOCSTRING,\n)",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"\"\"\n    The XGLM Model transformer with a language modeling head on top (linear layer with weights tied to the input\n    embeddings).\n    \"\"\",\n    XGLM_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 187,
        "n_words": 47,
        "vocab_size": 32,
        "complexity": 6,
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        "d_id": 6060,
        "documentation": {
            "docstring": "\n    The XGLM Model transformer with a language modeling head on top (linear layer with weights tied to the input\n    embeddings).\n    ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 65688,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/controllers/trends.py",
        "file_name": "trends.py",
        "fun_name": "get_period_wise_query",
        "commit_message": "style: format code with black",
        "code": "def get_period_wise_query(bet_dates, trans_date, query_details):\n\tquery_details +=  % {\n\t\t\"trans_date\": trans_date,\n\t\t\"sd\": bet_dates[0],\n\t\t\"ed\": bet_dates[1],\n\t}\n\treturn query_details\n\n\n@frappe.whitelist(allow_guest=True)",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist(allow_guest=True)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 11,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 35,
        "n_ast_nodes": 72,
        "n_identifiers": 7,
        "d_id": 13987,
        "documentation": {
            "docstring": "SUM(IF(t1.%(trans_date)s BETWEEN '%(sd)s' AND '%(ed)s', t2.stock_qty, NULL)),\n\t\t\t\t\tSUM(IF(t1.%(trans_date)s BETWEEN '%(sd)s' AND '%(ed)s', t2.base_net_amount, NULL)),\n\t\t\t\t",
            "n_words": 14,
            "vocab_size": 8,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 132900,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/annotations.py",
        "file_name": "annotations.py",
        "fun_name": "DeveloperAPI",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def DeveloperAPI(obj):\n    \n\n    if not obj.__doc__:\n        obj.__doc__ = \"\"\n    obj.__doc__ += \"\\n    DeveloperAPI: This API may change across minor Ray releases.\"\n    return obj\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 44,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 24,
        "n_ast_nodes": 47,
        "n_identifiers": 3,
        "d_id": 29859,
        "documentation": {
            "docstring": "Annotation for documenting developer APIs.\n\n    Developer APIs are lower-level methods explicitly exposed to advanced Ray\n    users and library developers. Their interfaces may change across minor\n    Ray releases.\n\n    Examples:\n        >>> @DeveloperAPI\n        >>> def func(x):\n        >>>     return x\n    ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 37208,
        "commit_id": "8d3f952adb8c98cec2ea1f59bb7acfbc08232381",
        "repo": "transformers",
        "path": "src/transformers/models/data2vec/modeling_data2vec_vision.py",
        "file_name": "modeling_data2vec_vision.py",
        "fun_name": "_set_gradient_checkpointing",
        "commit_message": "[Data2Vec] Add data2vec vision (#16760)\n\n* save intermediate\r\n\r\n* add vision\r\n\r\n* add vision\r\n\r\n* save\r\n\r\n* finish models\r\n\r\n* finish models\r\n\r\n* continue\r\n\r\n* finish\r\n\r\n* up\r\n\r\n* up\r\n\r\n* up\r\n\r\n* tests all pass\r\n\r\n* clean up\r\n\r\n* up\r\n\r\n* up\r\n\r\n* fix bugs in beit\r\n\r\n* correct docs\r\n\r\n* finish\r\n\r\n* finish docs\r\n\r\n* make style\r\n\r\n* up\r\n\r\n* more fixes\r\n\r\n* fix type hint\r\n\r\n* make style\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update tests/data2vec/test_modeling_data2vec_vision.py\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\n\r\n* fix test\r\n\r\nCo-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def _set_gradient_checkpointing(self, module, value=False):\n        if isinstance(module, Data2VecVisionEncoder):\n            module.gradient_checkpointing = value\n\n\nDATA2VEC_VISION_START_DOCSTRING = r\n\nDATA2VEC_VISION_INPUTS_DOCSTRING = r\n\n\n@add_start_docstrings(\n    \"The bare Data2VecVision Model transformer outputting raw hidden-states without any specific head on top.\",\n    DATA2VEC_VISION_START_DOCSTRING,\n)\n# Copied from transformers.models.beit.modeling_beit.BeitModel with BEIT->DATA2VEC_VISION,Beit->Data2VecVision,True->False",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"The bare Data2VecVision Model transformer outputting raw hidden-states without any specific head on top.\",\n    DATA2VEC_VISION_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 57,
        "n_words": 39,
        "vocab_size": 36,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 65,
        "n_identifiers": 10,
        "d_id": 6754,
        "documentation": {
            "docstring": "\n    This model is a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass. Use it\n    as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and\n    behavior.\n\n    Parameters:\n        config ([`Data2VecVisionConfig`]): Model configuration class with all the parameters of the model.\n            Initializing with a config file does not load the weights associated with the model, only the\n            configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.\n\n    Args:\n        pixel_values (`torch.FloatTensor` of shape `(batch_size, num_channels, height, width)`):\n            Pixel values. Pixel values can be obtained using [`BeitFeatureExtractor`]. See\n            [`BeitFeatureExtractor.__call__`] for details.\n\n        head_mask (`torch.FloatTensor` of shape `(num_heads,)` or `(num_layers, num_heads)`, *optional*):\n            Mask to nullify selected heads of the self-attention modules. Mask values selected in `[0, 1]`:\n\n            - 1 indicates the head is **not masked**,\n            - 0 indicates the head is **masked**.\n\n        output_attentions (`bool`, *optional*):\n            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned\n            tensors for more detail.\n        output_hidden_states (`bool`, *optional*):\n            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for\n            more detail.\n        return_dict (`bool`, *optional*):\n            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n",
            "n_words": 190,
            "vocab_size": 113,
            "n_whitespaces": 379,
            "language": "en"
        }
    },
    {
        "id": 60887,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/network/lazy_wheel.py",
        "file_name": "lazy_wheel.py",
        "fun_name": "truncate",
        "commit_message": "upd; format",
        "code": "def truncate(self, size=None):\n        # type: (Optional[int]) -> int\n        \n        return self._file.truncate(size)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 19,
        "n_ast_nodes": 33,
        "n_identifiers": 4,
        "d_id": 12321,
        "documentation": {
            "docstring": "Resize the stream to the given size in bytes.\n\n        If size is unspecified resize to the current position.\n        The current stream position isn't changed.\n\n        Return the new file size.\n        ",
            "n_words": 29,
            "vocab_size": 22,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 96433,
        "commit_id": "146fba432a32568be7d0b884dae0c39a6c33a11f",
        "repo": "sentry",
        "path": "tests/sentry/incidents/test_subscription_processor.py",
        "file_name": "test_subscription_processor.py",
        "fun_name": "test_crash_rate_alert_for_sessions_with_critical_warning_then_resolved",
        "commit_message": "fix(metric_alerts): Make sure critical triggers resolve properly when no action is set on a warning trigger (#31883)\n\n### Problem\r\nIf we have an alert set up like:\r\n- Warning: 50. Action: None\r\n- Critical: 100. Action: Slack\r\n\r\nThen if we go from critical -> warning state the slack resolve action will fail to fire.\r\n\r\n### Cause\r\nThe reason this happens is related to a previous fix. For an alert like\r\n- Warning: 50. Action: Slack\r\n- Critical: 100. Action: Slack\r\n\r\nWhen going from critical -> warning the critical action would be marked as resolved. This would\r\ncause a slack notification with `Resolved` to be sent to the channel. This is misleading, because\r\nthe alert is still active, just in the warning state. What we want here is to fire a warning\r\nnotification instead.\r\n\r\nThe initial fix for this was that when we resolved a critical trigger, we’d check and see whether\r\nthere was an active warning trigger. If so, we’d send a warning trigger fire to our actions, rather\r\nthan a critical trigger resolve. This works ok for many cases, but fails when the actions on the\r\nwarning trigger are different to those on the critical trigger.\r\n\r\n### Fix\r\nSubstituting the warning trigger for the critical trigger causes us subtle bugs. So, instead of\r\nthis, when triggering fires/resolves on our action handlers we will also pass along the incident\r\nstate change that the trigger/resolve caused the incident to go into.\r\n\r\nSo if a critical trigger resolves, we check what state it would have put the incident in. If\r\nthere’s a warning trigger, then the state is warning. If no warning trigger, the state is closed.\r\nThis state is then used to appropriately generate the messages that we send to users via our\r\nvarious actions.\r\n\r\nSo now, If we have an alert set up like:\r\n- Warning: 50. Action: None\r\n- Critical: 100. Action: Slack\r\n\r\nIf this goes from\r\n- critical -> warning OR critical -> resolved we will send `IncidentStatus.WARNING` to any actions\r\nrelated to the critical trigger. \r\n- warning -> resolved We do nothing since there are no actions on the warning trigger\r\n\r\nIf we have an alert set up like:\r\n- Warning: 50. Action: Slack\r\n- Critical: 100. Action: Slack\r\n\r\nIf this goes from:\r\n- critical -> warning: critical trigger, `IncidentStatus.Warning`\r\n- warning -> resolved: warning trigger, `IncidentStatus.Closed`\r\n- critical -> resolved: Since we de-dupe triggers to avoid spamming the user, we will select the\r\nwarning trigger here, and send `IncidentStatus.closed`\r\n\r\nIf we have an alert set up like:\r\n- Warning: 50. Action: Slack\r\n- Critical: 100. Action: Pagerduty\r\n\r\nIf this goes from:\r\n- critical -> warning: critical trigger, `IncidentStatus.Warning` sent to Pagerduty. Nothing sent\r\nto Slack\r\n- warning -> resolved: warning trigger, `IncidentStatus.Closed` sent to Slack. Nothing sent to\r\nPagerduty\r\n- critical -> resolved: Critical trigger, `IncidentStatus.Warning` sent to Pagerduty. Warning\r\ntrigger, `IncidentStatus.Closed` sent to Slack. We don’t de-dupe here since the actions are\r\ndifferent.",
        "code": "def test_crash_rate_alert_for_sessions_with_critical_warning_then_resolved(self):\n        \n        rule = self.crash_rate_alert_rule\n\n        trigger = self.crash_rate_alert_critical_trigger\n        trigger_warning = self.crash_rate_alert_warning_trigger\n\n        action_critical = self.crash_rate_alert_critical_action\n        action_warning = self.crash_rate_alert_warning_action\n\n        # Send Critical Update\n        update_value = (1 - trigger.alert_threshold / 100) + 0.05\n        self.send_crash_rate_alert_update(\n            rule=rule,\n            value=update_value,\n            time_delta=timedelta(minutes=-10),\n            subscription=rule.snuba_query.subscriptions.filter(project=self.project).get(),\n        )\n        incident = self.assert_active_incident(rule)\n        self.assert_actions_fired_for_incident(\n            incident, [action_critical], [(75.0, IncidentStatus.CRITICAL)]\n        )\n        self.assert_trigger_exists_with_status(incident, trigger, TriggerStatus.ACTIVE)\n\n        # Send Warning Update\n        update_value = (1 - trigger_warning.alert_threshold / 100) + 0.05\n        self.send_crash_rate_alert_update(\n            rule=rule,\n            value=update_value,\n            time_delta=timedelta(minutes=-3),\n            subscription=rule.snuba_query.subscriptions.filter(project=self.project).get(),\n        )\n\n        incident = self.assert_active_incident(rule)\n        self.assert_actions_resolved_for_incident(\n            incident, [action_critical], [(85.0, IncidentStatus.WARNING)]\n        )\n        self.assert_trigger_exists_with_status(incident, trigger_warning, TriggerStatus.ACTIVE)\n\n        # Send update higher than warning threshold\n        update_value = (1 - trigger_warning.alert_threshold / 100) - 0.05\n        self.send_crash_rate_alert_update(\n            rule=rule,\n            value=update_value,\n            time_delta=timedelta(minutes=-1),\n            subscription=rule.snuba_query.subscriptions.filter(project=self.project).get(),\n        )\n        self.assert_actions_resolved_for_incident(\n            incident, [action_warning], [(95.0, IncidentStatus.CLOSED)]\n        )\n        self.assert_no_active_incident(rule)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 476,
        "n_words": 108,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 41,
        "token_counts": 320,
        "n_ast_nodes": 468,
        "n_identifiers": 37,
        "d_id": 19312,
        "documentation": {
            "docstring": "\n        Test that tests the behavior of going from Critical status to Warning status to Resolved\n        for Crash Rate Alerts\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 176719,
        "commit_id": "2a05ccdb07cff88e56661dee8a9271859354027f",
        "repo": "networkx",
        "path": "networkx/algorithms/link_analysis/tests/test_pagerank.py",
        "file_name": "test_pagerank.py",
        "fun_name": "test_dangling_matrix",
        "commit_message": "Remove redundant py2 numeric conversions (#5661)\n\n* Remove redundant float conversion\r\n\r\n* Remove redundant int conversion\r\n\r\n* Use integer division\r\n\r\nCo-authored-by: Miroslav Šedivý <6774676+eumiro@users.noreply.github.com>",
        "code": "def test_dangling_matrix(self):\n        \n        G = self.G\n        dangling = self.dangling_edges\n        dangling_sum = sum(dangling.values())\n        M1 = nx.google_matrix(G, personalization=dangling)\n        M2 = nx.google_matrix(G, personalization=dangling, dangling=dangling)\n        for i in range(len(G)):\n            for j in range(len(G)):\n                if i == self.dangling_node_index and (j + 1) in dangling:\n                    assert M2[i, j] == pytest.approx(\n                        dangling[j + 1] / dangling_sum, abs=1e-4\n                    )\n                else:\n                    assert M2[i, j] == pytest.approx(M1[i, j], abs=1e-4)\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 228,
        "n_words": 58,
        "vocab_size": 42,
        "complexity": 5,
        "nloc": 14,
        "token_counts": 145,
        "n_ast_nodes": 214,
        "n_identifiers": 21,
        "d_id": 42054,
        "documentation": {
            "docstring": "\n        Tests that the google_matrix doesn't change except for the dangling\n        nodes.\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 172886,
        "commit_id": "32a3c45ee0f7e13bd61075f32a4dcebc415585a1",
        "repo": "calibre-web",
        "path": "cps/db.py",
        "file_name": "db.py",
        "fun_name": "search_query",
        "commit_message": "Refactored load read status for web access and opds access\nRefactored and removed discover html page\nBugfix show author\nBugfix open dialog in author page\nFix for #2341 (advanced search with linked read column and read column having a higher number than number of available custom columns)",
        "code": "def search_query(self, term, config_read_column, *join):\n        term.strip().lower()\n        self.session.connection().connection.connection.create_function(\"lower\", 1, lcase)\n        q = list()\n        authorterms = re.split(\"[, ]+\", term)\n        for authorterm in authorterms:\n            q.append(Books.authors.any(func.lower(Authors.name).ilike(\"%\" + authorterm + \"%\")))\n        query = self.generate_linked_query(config_read_column, Books)\n        \n\n        if len(join) == 6:\n            query = query.outerjoin(join[0], join[1]).outerjoin(join[2]).outerjoin(join[3], join[4]).outerjoin(join[5])\n        if len(join) == 3:\n            query = query.outerjoin(join[0], join[1]).outerjoin(join[2])\n        elif len(join) == 2:\n            query = query.outerjoin(join[0], join[1])\n        elif len(join) == 1:\n            query = query.outerjoin(join[0])\n        return query.filter(self.common_filters(True)).filter(\n            or_(Books.tags.any(func.lower(Tags.name).ilike(\"%\" + term + \"%\")),\n                Books.series.any(func.lower(Series.name).ilike(\"%\" + term + \"%\")),\n                Books.authors.any(and_(*q)),\n                Books.publishers.any(func.lower(Publishers.name).ilike(\"%\" + term + \"%\")),\n                func.lower(Books.title).ilike(\"%\" + term + \"%\")\n                ))\n\n    # read search results from calibre-database and return it (function is used for feed and simple search",
        "url": "https://github.com/janeczku/calibre-web.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 331,
        "n_words": 103,
        "vocab_size": 64,
        "complexity": 6,
        "nloc": 39,
        "token_counts": 353,
        "n_ast_nodes": 567,
        "n_identifiers": 40,
        "d_id": 40821,
        "documentation": {
            "docstring": "if not config_read_column:\n            query = (self.session.query(Books, ub.ArchivedBook.is_archived, ub.ReadBook).select_from(Books)\n                     .outerjoin(ub.ReadBook, and_(Books.id == ub.ReadBook.book_id,\n                                                  int(current_user.id) == ub.ReadBook.user_id)))\n        else:\n            try:\n                read_column = cc_classes[config_read_column]\n                query = (self.session.query(Books, ub.ArchivedBook.is_archived, read_column.value)\n                         .select_from(Books)\n                         .outerjoin(read_column, read_column.book == Books.id))\n            except (KeyError, AttributeError, IndexError):\n                log.error(\"Custom Column No.{} is not existing in calibre database\".format(config_read_column))\n                # Skip linking read column\n                query = self.session.query(Books, ub.ArchivedBook.is_archived, None)\n        query = query.outerjoin(ub.ArchivedBook, and_(Books.id == ub.ArchivedBook.book_id,\n                                                      int(current_user.id) == ub.ArchivedBook.user_id))",
            "n_words": 62,
            "vocab_size": 45,
            "n_whitespaces": 353,
            "language": "en"
        }
    },
    {
        "id": 68515,
        "commit_id": "d99b4e29b95db9c3ae9a2852a9757977e4912096",
        "repo": "erpnext",
        "path": "erpnext/regional/report/hsn_wise_summary_of_outward_supplies/hsn_wise_summary_of_outward_supplies.py",
        "file_name": "hsn_wise_summary_of_outward_supplies.py",
        "fun_name": "get_items",
        "commit_message": "fix: HSN-wise-summary of outward supplies Updated Report\n\nReport changes done in order to meet the specification as per govt guideline - [GUIDELINE](https://taxguru.in/goods-and-service-tax/12-points-note-filing-gstr-1-01st-2021-onwards.html)\n\n(cherry picked from commit 363752510ead7d3b86693d3659b2157753f2762d)\n\n# Conflicts:\n#\terpnext/regional/report/hsn_wise_summary_of_outward_supplies/hsn_wise_summary_of_outward_supplies.py",
        "code": "def get_items(filters):\n\tconditions = get_conditions(filters)\n\tmatch_conditions = frappe.build_match_conditions(\"Sales Invoice\")\n\tif match_conditions:\n\t\tmatch_conditions = \" and {0} \".format(match_conditions)\n\n\titems = frappe.db.sql(\n\t\t\n\t\t% (conditions, match_conditions),\n\t\tfilters,\n\t\tas_dict=1,\n\t)\n=======\n\t\t\t`tabSales Invoice Item`.parent,\n\t\t\t`tabSales Invoice Item`.item_code\n\t\t",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "=======\n\t\t\t`tabSales Invoice Item`.`as_dict=1)\n>>>>>>> 363752510fix:summary of outward supplies Updated",
        "n_ast_errors": 5,
        "ast_levels": 11,
        "n_whitespaces": 20,
        "n_words": 33,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 38,
        "token_counts": 53,
        "n_ast_nodes": 158,
        "n_identifiers": 27,
        "d_id": 14805,
        "documentation": {
            "docstring": "\n\t\tselect\n\t\t\t`tabSales Invoice Item`.gst_hsn_code,\n\t\t\t`tabSales Invoice Item`.stock_uom,\n\t\t\tsum(`tabSales Invoice Item`.stock_qty) as stock_qty,\n\t\t\tsum(`tabSales Invoice Item`.base_net_amount) as base_net_amount,\n\t\t\tsum(`tabSales Invoice Item`.base_price_list_rate) as base_price_list_rate,\n\t\t\t`tabSales Invoice Item`.parent,\n\t\t\t`tabSales Invoice Item`.item_code,\n\t\t\t`tabGST HSN Code`.description,\n\t\t\tjson_extract(`tabSales Taxes and Charges`.item_wise_tax_detail,\n\t\t\tconcat('$.\"' , `tabSales Invoice Item`.item_code, '\"[0]')) * count(distinct `tabSales Taxes and Charges`.name) as tax_rate\n\t\tfrom\n\t\t\t`tabSales Invoice`,\n\t\t\t`tabSales Invoice Item`,\n\t\t\t`tabGST HSN Code`,\n\t\t\t`tabSales Taxes and Charges`\n\t\twhere\n\t\t\t`tabSales Invoice`.name = `tabSales Invoice Item`.parent\n\t\t\tand `tabSales Taxes and Charges`.parent = `tabSales Invoice`.name\n\t\t\tand `tabSales Invoice`.docstatus = 1\n\t\t\tand `tabSales Invoice Item`.gst_hsn_code is not NULL\n\t\t\tand `tabSales Invoice Item`.gst_hsn_code = `tabGST HSN Code`.name %s %s\n\t\tgroup by\n<<<<<<< HEAD\n\t\t\t`tabSales Invoice Item`.parent, `tabSales Invoice Item`.item_code\n\n\t\t % (conditions, match_conditions), filters, as_dict=1)\n>>>>>>> 363752510e (fix: HSN-wise-summary of outward supplies Updated Report)\n\n\treturn items\n\n",
            "n_words": 125,
            "vocab_size": 68,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 211859,
        "commit_id": "da0157cf64aef2b7bf54a46e9cd1fbdea8b38f3e",
        "repo": "PaddleDetection",
        "path": "ppdet/data/crop_utils/chip_box_utils.py",
        "file_name": "chip_box_utils.py",
        "fun_name": "intersection_over_box",
        "commit_message": "update numpy 1.24 (#7552)",
        "code": "def intersection_over_box(chips, boxes):\n    \n    M = chips.shape[0]\n    N = boxes.shape[0]\n    if M * N == 0:\n        return np.zeros([M, N], dtype='float32')\n\n    box_area = bbox_area(boxes)  # B\n\n    inter_x2y2 = np.minimum(np.expand_dims(chips, 1)[:, :, 2:],\n                            boxes[:, 2:])  # CxBX2\n    inter_x1y1 = np.maximum(np.expand_dims(chips, 1)[:, :, :2],\n                            boxes[:, :2])  # CxBx2\n    inter_wh = inter_x2y2 - inter_x1y1\n    inter_wh = np.clip(inter_wh, a_min=0, a_max=None)\n    inter_area = inter_wh[:, :, 0] * inter_wh[:, :, 1]  # CxB\n\n    iob = inter_area / np.expand_dims(box_area, 0)\n    return iob\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleDetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 174,
        "n_words": 73,
        "vocab_size": 47,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 168,
        "n_ast_nodes": 259,
        "n_identifiers": 22,
        "d_id": 53153,
        "documentation": {
            "docstring": "\n    intersection area over box area\n    :param chips:  C\n    :param boxes:  B\n    :return: iob, CxB\n    ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 217515,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/genericpath.py",
        "file_name": "genericpath.py",
        "fun_name": "samefile",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def samefile(f1, f2):\n    \n    s1 = os.stat(f1)\n    s2 = os.stat(f2)\n    return samestat(s1, s2)\n\n\n# Are two open files really referencing the same file?\n# (Not necessarily the same file descriptor!)",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 39,
        "n_words": 29,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 53,
        "n_identifiers": 8,
        "d_id": 54828,
        "documentation": {
            "docstring": "Test whether two pathnames reference the same actual file or directory\n\n    This is determined by the device number and i-node number and\n    raises an exception if an os.stat() call on either pathname fails.\n    ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 63386,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "line",
        "commit_message": "upd; format",
        "code": "def line(loc, strg):\n    \n    lastCR = strg.rfind(\"\\n\", 0, loc)\n    nextCR = strg.find(\"\\n\", loc)\n    if nextCR >= 0:\n        return strg[lastCR + 1:nextCR]\n    else:\n        return strg[lastCR + 1:]\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 54,
        "n_words": 25,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 54,
        "n_ast_nodes": 90,
        "n_identifiers": 7,
        "d_id": 13281,
        "documentation": {
            "docstring": "Returns the line of text containing loc within a string, counting newlines as line separators.\n       ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 89462,
        "commit_id": "5f5d69722ff6c28ce46ebc958eb9d44d36cbf75b",
        "repo": "sentry",
        "path": "src/sentry/ingest/transaction_clusterer/tree.py",
        "file_name": "tree.py",
        "fun_name": "_sort_rules",
        "commit_message": "feat(txcluster): Discard rules with all `*`s (#42076)\n\nRules consisting of all `*`s aren't helpful and provide a worse user\r\nexperience, so we want to get rid of them. All `*` rules are produced\r\nwhen the merge threshold is not high enough for the existing data, and\r\nthey look like the following:\r\n\r\n```json\r\n  \"rules\": [\r\n    \"/*/*/*/*/*/*/**\",\r\n    \"/*/*/*/*/*/**\",\r\n    \"/*/*/*/*/**\",\r\n    \"/*/*/*/**\",\r\n    \"/*/*/**\",\r\n    \"/*/**\"\r\n  ]\r\n```\r\n\r\nThis PR introduces a `RuleValidator` running when computing rules, so\r\nthat invalid rules are never produced. There's also a small refactor to\r\nseparate the concerns of each method. I've tried to build this in an\r\neasy-to-extend way since it's likely we will need to add new validation\r\nrequirements.",
        "code": "def _sort_rules(self) -> None:\n        \n        if not self._rules:\n            return\n        self._rules.sort(key=len, reverse=True)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 29,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 18542,
        "documentation": {
            "docstring": "Sorts the rules by path length, descending (most specific rule first).",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 133356,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/sgd/torch/torch_trainer.py",
        "file_name": "torch_trainer.py",
        "fun_name": "_resize_worker_group",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _resize_worker_group(self, state_dict, max_retries=10):\n        \n        old_workers = self.worker_group.num_workers\n        self.worker_group.reset()\n\n        time.sleep(1)\n        for i in range(max_retries):\n            new_workers = self.worker_group.new_workers_size()\n            if new_workers:\n                self._last_resize = time.time()\n                startup_success = self._start_workers(int(new_workers))\n                if not startup_success:\n                    logger.info(\n                        f\"Worker startup failed. Retrying \"\n                        f\"{max_retries-i-1} more times.\"\n                    )\n                    self.worker_group.reset()\n                    continue\n                self.load_state_dict(state_dict, blocking=True)\n                if self.use_local and new_workers == 1 and old_workers > 1:\n                    # Major hack. If we go from LocalDistributedRunner to a\n                    # standard TorchRunner we have to manually reset the\n                    # dummy actor handle global vars.\n                    # TODO(amog): Refactor LocalDistributedTorchRunner to\n                    #  not use global variables for resource reservation.\n                    ray.util.sgd.torch.distributed_torch_runner._dummy_cuda_actor = None\n                    ray.util.sgd.torch.distributed_torch_runner._dummy_cpu_actor = None\n                return\n            else:\n                delay = 2 ** i\n                logger.warning(\"No new workers found. Retrying in %d sec.\" % delay)\n                time.sleep(delay)\n        raise RuntimeError(\"Exceeded max_retries for relaunching workers.\")\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 585,
        "n_words": 119,
        "vocab_size": 92,
        "complexity": 7,
        "nloc": 26,
        "token_counts": 169,
        "n_ast_nodes": 294,
        "n_identifiers": 33,
        "d_id": 29987,
        "documentation": {
            "docstring": "Resizes the number of remote workers based on available resources.\n        Total number of workers will never exceed `num_workers` amount.\n\n        Args:\n            state_dict (dict): The state dict to load to all workers.\n            max_retries (int): How many times to attempt to resize workers\n                before failing.\n        ",
            "n_words": 42,
            "vocab_size": 35,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 160531,
        "commit_id": "d4e11c7a2eb64861275facb076d47ccd135fa28c",
        "repo": "numpy",
        "path": "numpy/f2py/crackfortran.py",
        "file_name": "crackfortran.py",
        "fun_name": "readfortrancode",
        "commit_message": "ENH: Support character string arrays\n\nTST: added test for issue #18684\n\nENH: f2py opens files with correct encoding, fixes #635\n\nTST: added test for issue #6308\n\nTST: added test for issue #4519\n\nTST: added test for issue #3425\n\nENH: Implement user-defined hooks support for post-processing f2py data structure. Implement character BC hook.\n\nENH: Add support for detecting utf-16 and utf-32 encodings.",
        "code": "def readfortrancode(ffile, dowithline=show, istop=1):\n    \n    global gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77\n    global beginpattern, quiet, verbose, dolowercase, include_paths\n\n    if not istop:\n        saveglobals = gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77,\\\n            beginpattern, quiet, verbose, dolowercase\n    if ffile == []:\n        return\n    localdolowercase = dolowercase\n    # cont: set to True when the content of the last line read\n    # indicates statement continuation\n    cont = False\n    finalline = ''\n    ll = ''\n    includeline = re.compile(\n        r'\\s*include\\s*(\\'|\")(?P<name>[^\\'\"]*)(\\'|\")', re.I)\n    cont1 = re.compile(r'(?P<line>.*)&\\s*\\Z')\n    cont2 = re.compile(r'(\\s*&|)(?P<line>.*)')\n    mline_mark = re.compile(r\".*?)(?P<this>.*?)(?P<after>",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 155,
        "n_words": 78,
        "vocab_size": 57,
        "complexity": 60,
        "nloc": 201,
        "token_counts": 1187,
        "n_ast_nodes": 3370,
        "n_identifiers": 119,
        "d_id": 38652,
        "documentation": {
            "docstring": "\n    Read fortran codes from files and\n     1) Get rid of comments, line continuations, and empty lines; lower cases.\n     2) Call dowithline(line) on every line.\n     3) Recursively call itself when statement \\\"include '<filename>'\\\" is met.\n    \")\n    if istop:\n        dowithline('', -1)\n    ll, l1 = '', ''\n    spacedigits = [' '] + [str(_m) for _m in range(10)]\n    filepositiontext = ''\n    fin = fileinput.FileInput(ffile, openhook=openhook)\n    while True:\n        try:\n            l = fin.readline()\n        except UnicodeDecodeError as msg:\n            raise Exception(\n                f'readfortrancode: reading {fin.filename()}#{fin.lineno()}'\n                f' failed with\\n{msg}.\\nIt is likely that installing chardet'\n                ' package will help f2py determine the input file encoding'\n                ' correctly.')\n        if not l:\n            break\n        if fin.isfirstline():\n            filepositiontext = ''\n            currentfilename = fin.filename()\n            gotnextfile = 1\n            l1 = l\n            strictf77 = 0\n            sourcecodeform = 'fix'\n            ext = os.path.splitext(currentfilename)[1]\n            if is_f_file(currentfilename) and \\\n                    not (_has_f90_header(l) or _has_fix_header(l)):\n                strictf77 = 1\n            elif is_free_format(currentfilename) and not _has_fix_header(l):\n                sourcecodeform = 'free'\n            if strictf77:\n                beginpattern = beginpattern77\n            else:\n                beginpattern = beginpattern90\n            outmess('\\tReading file %s (format:%s%s)\\n'\n                    % (repr(currentfilename), sourcecodeform,\n                       strictf77 and ',strict' or ''))\n\n        l = l.expandtabs().replace('\\xa0', ' ')\n        # Get rid of newline characters\n        while not l == '':\n            if l[-1] not in \"\\n\\r\\f\":\n                break\n            l = l[:-1]\n        if not strictf77:\n            (l, rl) = split_by_unquoted(l, '!')\n            l += ' '\n            if rl[:5].lower() == '!f2py':  # f2py directive\n                l, _ = split_by_unquoted(l + 4 * ' ' + rl[5:], '!')\n        if l.strip() == '':  # Skip empty line\n            if sourcecodeform == 'free':\n                # In free form, a statement continues in the next line\n                # that is not a comment line [3.3.2.4^1], lines with\n                # blanks are comment lines [3.3.2.3^1]. Hence, the\n                # line continuation flag must retain its state.\n                pass\n            else:\n                # In fixed form, statement continuation is determined\n                # by a non-blank character at the 6-th position. Empty\n                # line indicates a start of a new statement\n                # [3.3.3.3^1]. Hence, the line continuation flag must\n                # be reset.\n                cont = False\n            continue\n        if sourcecodeform == 'fix':\n            if l[0] in ['*', 'c', '!', 'C', '#']:\n                if l[1:5].lower() == 'f2py':  # f2py directive\n                    l = '     ' + l[5:]\n                else:  # Skip comment line\n                    cont = False\n                    continue\n            elif strictf77:\n                if len(l) > 72:\n                    l = l[:72]\n            if not (l[0] in spacedigits):\n                raise Exception('readfortrancode: Found non-(space,digit) char '\n                                'in the first column.\\n\\tAre you sure that '\n                                'this code is in fix form?\\n\\tline=%s' % repr(l))\n\n            if (not cont or strictf77) and (len(l) > 5 and not l[5] == ' '):\n                # Continuation of a previous line\n                ll = ll + l[6:]\n                finalline = ''\n                origfinalline = ''\n            else:\n                if not strictf77:\n                    # F90 continuation\n                    r = cont1.match(l)\n                    if r:\n                        l = r.group('line')  # Continuation follows ..\n                    if cont:\n                        ll = ll + cont2.match(l).group('line')\n                        finalline = ''\n                        origfinalline = ''\n                    else:\n                        # clean up line beginning from possible digits.\n                        l = '     ' + l[5:]\n                        if localdolowercase:\n                            finalline = ll.lower()\n                        else:\n                            finalline = ll\n                        origfinalline = ll\n                        ll = l\n                    cont = (r is not None)\n                else:\n                    # clean up line beginning from possible digits.\n                    l = '     ' + l[5:]\n                    if localdolowercase:\n                        finalline = ll.lower()\n                    else:\n                        finalline = ll\n                    origfinalline = ll\n                    ll = l\n\n        elif sourcecodeform == 'free':\n            if not cont and ext == '.pyf' and mline_mark.match(l):\n                l = l + '\\n'\n                while True:\n                    lc = fin.readline()\n                    if not lc:\n                        errmess(\n                            'Unexpected end of file when reading multiline\\n')\n                        break\n                    l = l + lc\n                    if mline_mark.match(lc):\n                        break\n                l = l.rstrip()\n            r = cont1.match(l)\n            if r:\n                l = r.group('line')  # Continuation follows ..\n            if cont:\n                ll = ll + cont2.match(l).group('line')\n                finalline = ''\n                origfinalline = ''\n            else:\n                if localdolowercase:\n                    finalline = ll.lower()\n                else:\n                    finalline = ll\n                origfinalline = ll\n                ll = l\n            cont = (r is not None)\n        else:\n            raise ValueError(\n                \"Flag sourcecodeform must be either 'fix' or 'free': %s\" % repr(sourcecodeform))\n        filepositiontext = 'Line #%d in %s:\"%s\"\\n\\t' % (\n            fin.filelineno() - 1, currentfilename, l1)\n        m = includeline.match(origfinalline)\n        if m:\n            fn = m.group('name')\n            if os.path.isfile(fn):\n                readfortrancode(fn, dowithline=dowithline, istop=0)\n            else:\n                include_dirs = [\n                    os.path.dirname(currentfilename)] + include_paths\n                foundfile = 0\n                for inc_dir in include_dirs:\n                    fn1 = os.path.join(inc_dir, fn)\n                    if os.path.isfile(fn1):\n                        foundfile = 1\n                        readfortrancode(fn1, dowithline=dowithline, istop=0)\n                        break\n                if not foundfile:\n                    outmess('readfortrancode: could not find include file %s in %s. Ignoring.\\n' % (\n                        repr(fn), os.pathsep.join(include_dirs)))\n        else:\n            dowithline(finalline)\n        l1 = ll\n    if localdolowercase:\n        finalline = ll.lower()\n    else:\n        finalline = ll\n    origfinalline = ll\n    filepositiontext = 'Line #%d in %s:\"%s\"\\n\\t' % (\n        fin.filelineno() - 1, currentfilename, l1)\n    m = includeline.match(origfinalline)\n    if m:\n        fn = m.group('name')\n        if os.path.isfile(fn):\n            readfortrancode(fn, dowithline=dowithline, istop=0)\n        else:\n            include_dirs = [os.path.dirname(currentfilename)] + include_paths\n            foundfile = 0\n            for inc_dir in include_dirs:\n                fn1 = os.path.join(inc_dir, fn)\n                if os.path.isfile(fn1):\n                    foundfile = 1\n                    readfortrancode(fn1, dowithline=dowithline, istop=0)\n                    break\n            if not foundfile:\n                outmess('readfortrancode: could not find include file %s in %s. Ignoring.\\n' % (\n                    repr(fn), os.pathsep.join(include_dirs)))\n    else:\n        dowithline(finalline)\n    filepositiontext = ''\n    fin.close()\n    if istop:\n        dowithline('', 1)\n    else:\n        gotnextfile, filepositiontext, currentfilename, sourcecodeform, strictf77,\\\n            beginpattern, quiet, verbose, dolowercase = saveglobals\n\n# Crack line\nbeforethisafter = r'\\s*(?P<before>%s(?=\\s*(\\b(%s)\\b)))' + \\\n    r'\\s*(?P<this>(\\b(%s)\\b))' + \\\n    r'\\s*(?P<after>%s)\\s*\\Z'\n##\nfortrantypes = r'character|logical|integer|real|complex|double\\s*(precision\\s*(complex|)|complex)|type(?=\\s*\\([\\w\\s,=(*)]*\\))|byte'\ntypespattern = re.compile(\n    beforethisafter % ('', fortrantypes, fortrantypes, '.*'), re.I), 'type'\ntypespattern4implicit = re.compile(beforethisafter % (\n    '', fortrantypes + '|static|automatic|undefined', fortrantypes + '|static|automatic|undefined', '.*'), re.I)\n#\nfunctionpattern = re.compile(beforethisafter % (\n    r'([a-z]+[\\w\\s(=*+-/)]*?|)', 'function', 'function', '.*'), re.I), 'begin'\nsubroutinepattern = re.compile(beforethisafter % (\n    r'[a-z\\s]*?', 'subroutine', 'subroutine', '.*'), re.I), 'begin'\n# modulepattern=re.compile(beforethisafter%('[a-z\\s]*?','module','module','.*'),re.I),'begin'\n#\ngroupbegins77 = r'program|block\\s*data'\nbeginpattern77 = re.compile(\n    beforethisafter % ('', groupbegins77, groupbegins77, '.*'), re.I), 'begin'\ngroupbegins90 = groupbegins77 + \\\n    r'|module(?!\\s*procedure)|python\\s*module|(abstract|)\\s*interface|' + \\\n    r'type(?!\\s*\\()'\nbeginpattern90 = re.compile(\n    beforethisafter % ('', groupbegins90, groupbegins90, '.*'), re.I), 'begin'\ngroupends = (r'end|endprogram|endblockdata|endmodule|endpythonmodule|'\n             r'endinterface|endsubroutine|endfunction')\nendpattern = re.compile(\n    beforethisafter % ('', groupends, groupends, r'.*'), re.I), 'end'\nendifs = r'end\\s*(if|do|where|select|while|forall|associate|block|' + \\\n         r'critical|enum|team)'\nendifpattern = re.compile(\n    beforethisafter % (r'[\\w]*?', endifs, endifs, r'[\\w\\s]*'), re.I), 'endif'\n#\nmoduleprocedures = r'module\\s*procedure'\nmoduleprocedurepattern = re.compile(\n    beforethisafter % ('', moduleprocedures, moduleprocedures, r'.*'), re.I), \\\n    'moduleprocedure'\nimplicitpattern = re.compile(\n    beforethisafter % ('', 'implicit', 'implicit', '.*'), re.I), 'implicit'\ndimensionpattern = re.compile(beforethisafter % (\n    '', 'dimension|virtual', 'dimension|virtual', '.*'), re.I), 'dimension'\nexternalpattern = re.compile(\n    beforethisafter % ('', 'external', 'external', '.*'), re.I), 'external'\noptionalpattern = re.compile(\n    beforethisafter % ('', 'optional', 'optional', '.*'), re.I), 'optional'\nrequiredpattern = re.compile(\n    beforethisafter % ('', 'required', 'required', '.*'), re.I), 'required'\npublicpattern = re.compile(\n    beforethisafter % ('', 'public', 'public', '.*'), re.I), 'public'\nprivatepattern = re.compile(\n    beforethisafter % ('', 'private', 'private', '.*'), re.I), 'private'\nintrinsicpattern = re.compile(\n    beforethisafter % ('', 'intrinsic', 'intrinsic', '.*'), re.I), 'intrinsic'\nintentpattern = re.compile(beforethisafter % (\n    '', 'intent|depend|note|check', 'intent|depend|note|check', r'\\s*\\(.*?\\).*'), re.I), 'intent'\nparameterpattern = re.compile(\n    beforethisafter % ('', 'parameter', 'parameter', r'\\s*\\(.*'), re.I), 'parameter'\ndatapattern = re.compile(\n    beforethisafter % ('', 'data', 'data', '.*'), re.I), 'data'\ncallpattern = re.compile(\n    beforethisafter % ('', 'call', 'call', '.*'), re.I), 'call'\nentrypattern = re.compile(\n    beforethisafter % ('', 'entry', 'entry', '.*'), re.I), 'entry'\ncallfunpattern = re.compile(\n    beforethisafter % ('', 'callfun', 'callfun', '.*'), re.I), 'callfun'\ncommonpattern = re.compile(\n    beforethisafter % ('', 'common', 'common', '.*'), re.I), 'common'\nusepattern = re.compile(\n    beforethisafter % ('', 'use', 'use', '.*'), re.I), 'use'\ncontainspattern = re.compile(\n    beforethisafter % ('', 'contains', 'contains', ''), re.I), 'contains'\nformatpattern = re.compile(\n    beforethisafter % ('', 'format', 'format', '.*'), re.I), 'format'\n# Non-fortran and f2py-specific statements\nf2pyenhancementspattern = re.compile(beforethisafter % ('', 'threadsafe|fortranname|callstatement|callprotoargument|usercode|pymethoddef',\n                                                        'threadsafe|fortranname|callstatement|callprotoargument|usercode|pymethoddef', '.*'), re.I | re.S), 'f2pyenhancements'\nmultilinepattern = re.compile(\n    r\"\\s*(?P<before>)\\s*\\Z\", re.S), 'multiline'\n##\n",
            "n_words": 1168,
            "vocab_size": 439,
            "n_whitespaces": 4055,
            "language": "en"
        }
    },
    {
        "id": 187554,
        "commit_id": "f7cbfae2621d6dd2f9f1189cf98a59ba64ff9721",
        "repo": "streamlink",
        "path": "src/streamlink/plugins/rtpplay.py",
        "file_name": "rtpplay.py",
        "fun_name": "_get_streams",
        "commit_message": "plugins: move and refactor validation schemas\n\nRefactor validation schemas of plugins where schemas are defined as\nclass attributes and where no major changes are needed:\n\n- Move validation schemas from class attributes to schema definitions\n- Apply minor validation schema adjustments (eg. union_get)\n- Use `validate.none_or_all(...)`\n- Replace `validate.transform(pattern.search)` with `pattern` and fix\n  schemas using `validate.regex(pattern)` where a regex has to match\n  - Move pattern definitions from class attributes to schema definitions\n  - Fix some patterns in regards to quotation matching\n- Fix minor style issues where it makes sense\n  - use double quotes\n  - use f-strings\n  - add trailing commas\n  - fix indentation",
        "code": "def _get_streams(self):\n        self.session.http.headers.update({\n            \"User-Agent\": useragents.CHROME,\n            \"Referer\": self.url,\n        })\n\n        re_m3u8 = re.compile(\n            r,\n            re.VERBOSE,\n        )\n\n        hls_url = self.session.http.get(self.url, schema=validate.Schema(\n            validate.transform(lambda text: next(reversed(list(re_m3u8.finditer(text))), None)),\n            validate.any(\n                None,\n                validate.all(\n                    validate.get(\"string\"),\n                    str,\n                    validate.any(\n                        \"\",\n                        validate.url(),\n                    ),\n                ),\n                validate.all(\n                    validate.get(\"obfuscated\"),\n                    str,\n                    validate.parse_json(),\n                    validate.transform(lambda arr: unquote(\"\".join(arr))),\n                    validate.url(),\n                ),\n                validate.all(\n                    validate.get(\"obfuscated_b64\"),\n                    str,\n                    validate.parse_json(),\n                    validate.transform(lambda arr: unquote(\"\".join(arr))),\n                    validate.transform(lambda b64: b64decode(b64).decode(\"utf-8\")),\n                    validate.url(),\n                ),\n            ),\n        ))\n        if hls_url:\n            return HLSStream.parse_variant_playlist(self.session, hls_url)\n\n\n__plugin__ = RTPPlay\n",
        "url": "https://github.com/streamlink/streamlink.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 634,
        "n_words": 63,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 48,
        "token_counts": 251,
        "n_ast_nodes": 399,
        "n_identifiers": 38,
        "d_id": 45806,
        "documentation": {
            "docstring": "\n                hls\\s*:\\s*(?:\n                    (?P<q>[\"'])(?P<string>.*?)(?P=q)\n                    |\n                    decodeURIComponent\\s*\\((?P<obfuscated>\\[.*?])\\.join\\(\n                    |\n                    atob\\s*\\(\\s*decodeURIComponent\\s*\\((?P<obfuscated_b64>\\[.*?])\\.join\\(\n                )\n            ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 144,
            "language": "en"
        }
    },
    {
        "id": 260299,
        "commit_id": "b7721135a0d3df30e5a1a1c34156421b55fe67ca",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_ridge.py",
        "file_name": "_ridge.py",
        "fun_name": "fit",
        "commit_message": "MAINT validate parameters in Ridge (#23563)\n\nCo-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def fit(self, X, y, sample_weight=None):\n        \n        self._validate_params()\n\n        _accept_sparse = _get_valid_accept_sparse(sparse.issparse(X), self.solver)\n        X, y = self._validate_data(\n            X,\n            y,\n            accept_sparse=_accept_sparse,\n            dtype=[np.float64, np.float32],\n            multi_output=True,\n            y_numeric=True,\n        )\n        return super().fit(X, y, sample_weight=sample_weight)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 134,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 86,
        "n_ast_nodes": 126,
        "n_identifiers": 20,
        "d_id": 76169,
        "documentation": {
            "docstring": "Fit Ridge regression model.\n\n        Parameters\n        ----------\n        X : {ndarray, sparse matrix} of shape (n_samples, n_features)\n            Training data.\n\n        y : ndarray of shape (n_samples,) or (n_samples, n_targets)\n            Target values.\n\n        sample_weight : float or ndarray of shape (n_samples,), default=None\n            Individual weights for each sample. If given a float, every sample\n            will have the same weight.\n\n        Returns\n        -------\n        self : object\n            Fitted estimator.\n        ",
            "n_words": 60,
            "vocab_size": 50,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 186667,
        "commit_id": "7d9e9a49005de7961e84d2a7c608db57dbab3046",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/override_fedora.py",
        "file_name": "override_fedora.py",
        "fun_name": "_prepare_options",
        "commit_message": "Add typing to certbot.apache (#9071)\n\n* Add typing to certbot.apache\r\n\r\nCo-authored-by: Adrien Ferrand <ferrand.ad@gmail.com>",
        "code": "def _prepare_options(self) -> None:\n        \n        super()._prepare_options()\n        self.options.restart_cmd[0] = 'apachectl'\n        if not self.options.restart_cmd_alt:  # pragma: no cover\n            raise ValueError(\"OS option restart_cmd_alt must be set for Fedora.\")\n        self.options.restart_cmd_alt[0] = 'apachectl'\n        self.options.conftest_cmd[0] = 'apachectl'\n\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 84,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 58,
        "n_ast_nodes": 104,
        "n_identifiers": 8,
        "d_id": 45574,
        "documentation": {
            "docstring": "\n        Override the options dictionary initialization to keep using apachectl\n        instead of httpd and so take advantages of this new bash script in newer versions\n        of Fedora to restart httpd.\n        ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 258948,
        "commit_id": "1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe",
        "repo": "scikit-learn",
        "path": "sklearn/random_projection.py",
        "file_name": "random_projection.py",
        "fun_name": "johnson_lindenstrauss_min_dim",
        "commit_message": "MNT Update black to stable version (#22474)",
        "code": "def johnson_lindenstrauss_min_dim(n_samples, *, eps=0.1):\n    \n    eps = np.asarray(eps)\n    n_samples = np.asarray(n_samples)\n\n    if np.any(eps <= 0.0) or np.any(eps >= 1):\n        raise ValueError(\"The JL bound is defined for eps in ]0, 1[, got %r\" % eps)\n\n    if np.any(n_samples) <= 0:\n        raise ValueError(\n            \"The JL bound is defined for n_samples greater than zero, got %r\"\n            % n_samples\n        )\n\n    denominator = (eps**2 / 2) - (eps**3 / 3)\n    return (4 * np.log(n_samples) / denominator).astype(np.int64)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 133,
        "n_words": 69,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 112,
        "n_ast_nodes": 177,
        "n_identifiers": 11,
        "d_id": 75490,
        "documentation": {
            "docstring": "Find a 'safe' number of components to randomly project to.\n\n    The distortion introduced by a random projection `p` only changes the\n    distance between two points by a factor (1 +- eps) in an euclidean space\n    with good probability. The projection `p` is an eps-embedding as defined\n    by:\n\n      (1 - eps) ||u - v||^2 < ||p(u) - p(v)||^2 < (1 + eps) ||u - v||^2\n\n    Where u and v are any rows taken from a dataset of shape (n_samples,\n    n_features), eps is in ]0, 1[ and p is a projection by a random Gaussian\n    N(0, 1) matrix of shape (n_components, n_features) (or a sparse\n    Achlioptas matrix).\n\n    The minimum number of components to guarantee the eps-embedding is\n    given by:\n\n      n_components >= 4 log(n_samples) / (eps^2 / 2 - eps^3 / 3)\n\n    Note that the number of dimensions is independent of the original\n    number of features but instead depends on the size of the dataset:\n    the larger the dataset, the higher is the minimal dimensionality of\n    an eps-embedding.\n\n    Read more in the :ref:`User Guide <johnson_lindenstrauss>`.\n\n    Parameters\n    ----------\n    n_samples : int or array-like of int\n        Number of samples that should be a integer greater than 0. If an array\n        is given, it will compute a safe number of components array-wise.\n\n    eps : float or ndarray of shape (n_components,), dtype=float, \\\n            default=0.1\n        Maximum distortion rate in the range (0,1 ) as defined by the\n        Johnson-Lindenstrauss lemma. If an array is given, it will compute a\n        safe number of components array-wise.\n\n    Returns\n    -------\n    n_components : int or ndarray of int\n        The minimal number of components to guarantee with good probability\n        an eps-embedding with n_samples.\n\n    Examples\n    --------\n    >>> from sklearn.random_projection import johnson_lindenstrauss_min_dim\n    >>> johnson_lindenstrauss_min_dim(1e6, eps=0.5)\n    663\n\n    >>> johnson_lindenstrauss_min_dim(1e6, eps=[0.5, 0.1, 0.01])\n    array([    663,   11841, 1112658])\n\n    >>> johnson_lindenstrauss_min_dim([1e4, 1e5, 1e6], eps=0.1)\n    array([ 7894,  9868, 11841])\n\n    References\n    ----------\n\n    .. [1] https://en.wikipedia.org/wiki/Johnson%E2%80%93Lindenstrauss_lemma\n\n    .. [2] Sanjoy Dasgupta and Anupam Gupta, 1999,\n           \"An elementary proof of the Johnson-Lindenstrauss Lemma.\"\n           http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.3654\n\n    ",
            "n_words": 318,
            "vocab_size": 187,
            "n_whitespaces": 522,
            "language": "en"
        }
    },
    {
        "id": 194950,
        "commit_id": "7e453008fde751aff0cfd752662e19fe2adc7410",
        "repo": "ParlAI",
        "path": "projects/seeker/scripts/generate_lm_data.py",
        "file_name": "generate_lm_data.py",
        "fun_name": "act",
        "commit_message": "SeeKeR (#4447)\n\n* seeker\r\n\r\n* todo\r\n\r\n* readme updates; add test\r\n\r\n* small config changes\r\n\r\n* various updates\r\n\r\n* readme fix\r\n\r\n* model card\r\n\r\n* add arxiv link\r\n\r\n* surround spacy with try catch\r\n\r\n* more protected\r\n\r\n* more protection of imports\r\n\r\n* lint",
        "code": "def act(self):\n        \n        obs = self.observation\n        reply = {'text': INVALID, 'id': self.getID(), 'episode_done': False}\n        if obs is None or obs['text'] == DO_NOT_RETRIEVE:\n            return Message(reply)\n\n        # construct the search query\n        labels = obs.get('labels', obs.get('eval_labels', None))\n        search_query = self.construct_search_query(labels)\n        if (\n            self.opt['min_num_search_words'] > 0\n            and len(search_query[0].split()) <= self.opt['min_num_search_words']\n        ):\n            return Message(reply)\n\n        # retrieve\n        self.search_engine.set_search_queries(search_query)\n        retrieved, _ = self.search_engine.retrieve_and_score(self.dummy)\n        all_docs = [d.get_tokenization_str() for d in retrieved[0]]  # batched\n\n        # Find the right doc\n        best_f1, best_doc, best_doc_idx = self.get_best_doc(all_docs, labels)\n        if best_doc:\n            assert best_doc_idx is not None\n            reply['knowledge'] = f'{TOKEN_KNOWLEDGE}{best_doc}{TOKEN_END_KNOWLEDGE}'\n            reply['f1_overlap'] = best_f1\n            reply['text'] = labels[0]\n            reply['retrieved_docs'] = all_docs\n            reply['gold_doc'] = all_docs[best_doc_idx]\n            reply['search_query'] = search_query[0]\n        return Message(reply)\n\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 343,
        "n_words": 102,
        "vocab_size": 74,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 219,
        "n_ast_nodes": 379,
        "n_identifiers": 31,
        "d_id": 47131,
        "documentation": {
            "docstring": "\n        Search for overlap with the observation label.\n\n        Return the best fitting document. A document is valid if the f1 is above the\n        threshold AND the f1 is less than 1.0 AND the target label is not in the\n        document.\n        ",
            "n_words": 39,
            "vocab_size": 27,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 248149,
        "commit_id": "75dff3dc980974960f55fa21fc8e672201f63045",
        "repo": "synapse",
        "path": "tests/rest/client/test_relations.py",
        "file_name": "test_relations.py",
        "fun_name": "test_thread_with_bundled_aggregations_for_latest",
        "commit_message": "Include bundled aggregations for the latest event in a thread. (#12273)\n\nThe `latest_event` field of the bundled aggregations for `m.thread` relations\r\ndid not include bundled aggregations itself. This resulted in clients needing to\r\nimmediately request the event from the server (and thus making it useless that\r\nthe latest event itself was serialized instead of just including an event ID).",
        "code": "def test_thread_with_bundled_aggregations_for_latest(self) -> None:\n        \n        self._send_relation(RelationTypes.THREAD, \"m.room.test\")\n        channel = self._send_relation(RelationTypes.THREAD, \"m.room.test\")\n        thread_2 = channel.json_body[\"event_id\"]\n\n        self._send_relation(\n            RelationTypes.ANNOTATION, \"m.reaction\", \"a\", parent_id=thread_2\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 72,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 68,
        "n_ast_nodes": 93,
        "n_identifiers": 10,
        "d_id": 72127,
        "documentation": {
            "docstring": "\n        Bundled aggregations should get applied to the latest thread event.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 163193,
        "commit_id": "521259299f7829da667ba39302ec77acedde9e5e",
        "repo": "pandas",
        "path": "pandas/core/series.py",
        "file_name": "series.py",
        "fun_name": "map",
        "commit_message": "DOC: Improve doc summaries in series.rst (#45237)",
        "code": "def map(self, arg, na_action=None) -> Series:\n        \n        new_values = self._map_values(arg, na_action=na_action)\n        return self._constructor(new_values, index=self.index).__finalize__(\n            self, method=\"map\"\n        )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 55,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 79,
        "token_counts": 48,
        "n_ast_nodes": 75,
        "n_identifiers": 11,
        "d_id": 39401,
        "documentation": {
            "docstring": "\n        Map values of Series according to an input mapping or function.\n\n        Used for substituting each value in a Series with another value,\n        that may be derived from a function, a ``dict`` or\n        a :class:`Series`.\n\n        Parameters\n        ----------\n        arg : function, collections.abc.Mapping subclass or Series\n            Mapping correspondence.\n        na_action : {None, 'ignore'}, default None\n            If 'ignore', propagate NaN values, without passing them to the\n            mapping correspondence.\n\n        Returns\n        -------\n        Series\n            Same index as caller.\n\n        See Also\n        --------\n        Series.apply : For applying more complex functions on a Series.\n        DataFrame.apply : Apply a function row-/column-wise.\n        DataFrame.applymap : Apply a function elementwise on a whole DataFrame.\n\n        Notes\n        -----\n        When ``arg`` is a dictionary, values in Series that are not in the\n        dictionary (as keys) are converted to ``NaN``. However, if the\n        dictionary is a ``dict`` subclass that defines ``__missing__`` (i.e.\n        provides a method for default values), then this default is used\n        rather than ``NaN``.\n\n        Examples\n        --------\n        >>> s = pd.Series(['cat', 'dog', np.nan, 'rabbit'])\n        >>> s\n        0      cat\n        1      dog\n        2      NaN\n        3   rabbit\n        dtype: object\n\n        ``map`` accepts a ``dict`` or a ``Series``. Values that are not found\n        in the ``dict`` are converted to ``NaN``, unless the dict has a default\n        value (e.g. ``defaultdict``):\n\n        >>> s.map({'cat': 'kitten', 'dog': 'puppy'})\n        0   kitten\n        1    puppy\n        2      NaN\n        3      NaN\n        dtype: object\n\n        It also accepts a function:\n\n        >>> s.map('I am a {}'.format)\n        0       I am a cat\n        1       I am a dog\n        2       I am a nan\n        3    I am a rabbit\n        dtype: object\n\n        To avoid applying the function to missing values (and keep them as\n        ``NaN``) ``na_action='ignore'`` can be used:\n\n        >>> s.map('I am a {}'.format, na_action='ignore')\n        0     I am a cat\n        1     I am a dog\n        2            NaN\n        3  I am a rabbit\n        dtype: object\n        ",
            "n_words": 285,
            "vocab_size": 155,
            "n_whitespaces": 802,
            "language": "en"
        }
    },
    {
        "id": 100467,
        "commit_id": "aa39234538a8f83e6aa2b60b8275a570e8876ac2",
        "repo": "faceswap",
        "path": "plugins/train/model/phaze_a.py",
        "file_name": "phaze_a.py",
        "fun_name": "_validate_encoder_architecture",
        "commit_message": "Update all Keras Imports to be conditional (#1214)\n\n* Remove custom keras importer\r\n\r\n* first round keras imports fix\r\n\r\n* launcher.py: Remove KerasFinder references\r\n\r\n* 2nd round keras imports update (lib and extract)\r\n\r\n* 3rd round keras imports update (train)\r\n\r\n* remove KerasFinder from tests\r\n\r\n* 4th round keras imports update (tests)",
        "code": "def _validate_encoder_architecture(self):\n        \n        arch = self.config[\"enc_architecture\"].lower()\n        model = _MODEL_MAPPING.get(arch)\n        if not model:\n            raise FaceswapError(f\"'{arch}' is not a valid choice for encoder architecture. Choose \"\n                                f\"one of {list(_MODEL_MAPPING.keys())}.\")\n\n        if get_backend() == \"amd\" and model.get(\"no_amd\"):\n            valid = [k for k, v in _MODEL_MAPPING.items() if not v.get('no_amd')]\n            raise FaceswapError(f\"'{arch}' is not compatible with the AMD backend. Choose one of \"\n                                f\"{valid}.\")\n\n        tf_ver = float(\".\".join(tf.__version__.split(\".\")[:2]))  # pylint:disable=no-member\n        tf_min = model.get(\"tf_min\", 2.0)\n        if get_backend() != \"amd\" and tf_ver < tf_min:\n            raise FaceswapError(f\"{arch}' is not compatible with your version of Tensorflow. The \"\n                                f\"minimum version required is {tf_min} whilst you have version \"\n                                f\"{tf_ver} installed.\")\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 323,
        "n_words": 98,
        "vocab_size": 65,
        "complexity": 8,
        "nloc": 16,
        "token_counts": 138,
        "n_ast_nodes": 281,
        "n_identifiers": 23,
        "d_id": 19941,
        "documentation": {
            "docstring": " Validate that the requested architecture is a valid choice for the running system\n        configuration.\n\n        If the selection is not valid, an error is logged and system exits.\n        ",
            "n_words": 27,
            "vocab_size": 22,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 109615,
        "commit_id": "1374e34d2f5cb9c424fc0ae4a9495f3e562e4b06",
        "repo": "matplotlib",
        "path": "doc/conf.py",
        "file_name": "conf.py",
        "fun_name": "gallery_image_warning_filter",
        "commit_message": "filter warnings",
        "code": "def gallery_image_warning_filter(record):\n        msg = record.msg\n        for gallery_dir in sphinx_gallery_conf['gallery_dirs']:\n            if msg.startswith(f'image file not readable: {gallery_dir}'):\n                return False\n\n        if msg == 'Could not obtain image size. :scale: option is ignored.':\n            return False\n\n        return True\n\n    logger = logging.getLogger('sphinx')\n    logger.addFilter(gallery_image_warning_filter)\n\n\nmathmpl_fontsize = 11.0\nmathmpl_srcset = ['2x']\n\n# Monkey-patching gallery header to include search keywords\ngen_rst.EXAMPLE_HEADER = \n\n# Add any paths that contain templates here, relative to this directory.\ntemplates_path = ['_templates']\n\n# The suffix of source filenames.\nsource_suffix = '.rst'\n\n# This is the default encoding, but it doesn't hurt to be explicit\nsource_encoding = \"utf-8\"\n\n# The toplevel toctree document (renamed to root_doc in Sphinx 4.0)\nroot_doc = master_doc = 'users/index'\n\n# General substitutions.\ntry:\n    SHA = subprocess.check_output(\n        ['git', 'describe', '--dirty']).decode('utf-8').strip()\n# Catch the case where git is not installed locally, and use the setuptools_scm\n# version number instead\nexcept (subprocess.CalledProcessError, FileNotFoundError):\n    SHA = matplotlib.__version__\n\nproject = 'Matplotlib'\ncopyright = (\n    '2002–2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom '\n    'and the Matplotlib development team; '\n    f'2012–{sourceyear} The Matplotlib development team'\n)\n\n\n# The default replacements for |version| and |release|, also used in various\n# other places throughout the built documents.\n#\n# The short X.Y version.\n\nversion = matplotlib.__version__\n# The full version, including alpha/beta/rc tags.\nrelease = version\n\n# There are two options for replacing |today|: either, you set today to some\n# non-false value, then it is used:\n# today = ''\n# Else, today_fmt is used as the format for a strftime call.\ntoday_fmt = '%B %d, %Y'\n\n# List of documents that shouldn't be included in the build.\nunused_docs = []\n\n# If true, '()' will be appended to :func: etc. cross-reference text.\n# add_function_parentheses = True\n\n# If true, the current module name will be prepended to all description\n# unit titles (such as .. function::).\n# add_module_names = True\n\n# If true, sectionauthor and moduleauthor directives will be shown in the\n# output. They are ignored by default.\n# show_authors = False\n\n# The name of the Pygments (syntax highlighting) style to use.\npygments_style = 'sphinx'\n\ndefault_role = 'obj'\n\n# Plot directive configuration\n# ----------------------------\n\n# For speedup, decide which plot_formats to build based on build targets:\n#     html only -> png\n#     latex only -> pdf\n#     all other cases, including html + latex -> png, pdf\n# For simplicity, we assume that the build targets appear in the command line.\n# We're falling back on using all formats in case that assumption fails.\nformats = {'html': ('png', 100), 'latex': ('pdf', 100)}\nplot_formats = [formats[target] for target in ['html', 'latex']\n                if target in sys.argv] or list(formats.values())\n\n\n# GitHub extension\n\ngithub_project_url = \"https://github.com/matplotlib/matplotlib/\"\n\n\n# Options for HTML output\n# -----------------------\n",
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            "docstring": "\n.. DO NOT EDIT.\n.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.\n.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:\n.. \"{0}\"\n.. LINE NUMBERS ARE GIVEN BELOW.\n\n.. only:: html\n\n    .. meta::\n        :keywords: codex\n\n    .. note::\n        :class: sphx-glr-download-link-note\n\n        Click :ref:`here <sphx_glr_download_{1}>`\n        to download the full example code{2}\n\n.. rst-class:: sphx-glr-example-title\n\n.. _sphx_glr_{1}:\n\n",
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    {
        "id": 127791,
        "commit_id": "42da4445e7a3cb358a1a02ae433a004e9fa836b5",
        "repo": "ray",
        "path": "dashboard/modules/metrics/metrics_head.py",
        "file_name": "metrics_head.py",
        "fun_name": "_create_default_prometheus_configs",
        "commit_message": "Export default configurations for grafana and prometheus (#28286)",
        "code": "def _create_default_prometheus_configs(self):\n        \n        prometheus_config_output_path = os.path.join(\n            self.metrics_root, \"prometheus\", \"prometheus.yml\"\n        )\n\n        # Copy default prometheus configurations\n        if os.path.exists(prometheus_config_output_path):\n            os.remove(prometheus_config_output_path)\n        os.makedirs(os.path.dirname(prometheus_config_output_path), exist_ok=True)\n        shutil.copy(PROMETHEUS_CONFIG_INPUT_PATH, prometheus_config_output_path)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 28527,
        "documentation": {
            "docstring": "\n        Creates the prometheus configurations that are by default provided by Ray.\n        This will completely replace the `/tmp/ray/metrics/prometheus` folder.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 40,
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        "id": 109425,
        "commit_id": "0dc472b4c7cdcc1e88228988fff17762c90f1cb9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/patches.py",
        "file_name": "patches.py",
        "fun_name": "set_connectionstyle",
        "commit_message": "Harmonize docstrings for boxstyle/connectionstyle/arrowstyle.\n\n- Rely on `__init_subclass__` to avoid the need for the out-of-order\n  `interpd.update`/`dedent_interpd`.\n- Use consistent wording for all setters, and add ACCEPTS list in all\n  cases.\n- Move get_boxstyle right next to set_boxstyle (consistently with the\n  other setters/getters).\n- Make the type check in the setters consistent in all cases (check for\n  str, not for forcing inheritance from the private _Base).\n- Support `set_connectionstyle()` as equivalent to\n  `set_connectionstyle(None)`, consistently with the other two setters.",
        "code": "def set_connectionstyle(self, connectionstyle=None, **kwargs):\n        \n        if connectionstyle is None:\n            return ConnectionStyle.pprint_styles()\n        self._connector = (\n            ConnectionStyle(connectionstyle, **kwargs)\n            if isinstance(connectionstyle, str) else connectionstyle)\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 23577,
        "documentation": {
            "docstring": "\n        Set the connection style, possibly with further attributes.\n\n        Attributes from the previous connection style are not reused.\n\n        Without argument (or with ``connectionstyle=None``), the available box\n        styles are returned as a human-readable string.\n\n        Parameters\n        ----------\n        connectionstyle : str or `matplotlib.patches.ConnectionStyle`\n            The style of the connection: either a `.ConnectionStyle` instance,\n            or a string, which is the style name and optionally comma separated\n            attributes (e.g. \"Arc,armA=30,rad=10\"). Such a string is used to\n            construct a `.ConnectionStyle` object, as documented in that class.\n\n            The following connection styles are available:\n\n            %(ConnectionStyle:table_and_accepts)s\n\n        **kwargs\n            Additional attributes for the connection style. See the table above\n            for supported parameters.\n\n        Examples\n        --------\n        ::\n\n            set_connectionstyle(\"Arc,armA=30,rad=10\")\n            set_connectionstyle(\"arc\", armA=30, rad=10)\n        ",
            "n_words": 106,
            "vocab_size": 80,
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            "language": "en"
        }
    },
    {
        "id": 153755,
        "commit_id": "49fc2cf3733f20ac6cf8a7c61e42ef7aa5cf4b03",
        "repo": "modin",
        "path": "modin/logging/config.py",
        "file_name": "config.py",
        "fun_name": "formatTime",
        "commit_message": "FEAT-#4371: Add logging to Modin (#4372)\n\nCo-authored-by: Devin Petersohn <devin.petersohn@gmail.com>\r\nCo-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>\r\nCo-authored-by: Anatoly Myachev <anatoliimyachev@mail.com>\r\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Naren Krishna <naren@ponder.io>",
        "code": "def formatTime(self, record, datefmt=None):\n        \n        ct = dt.datetime.fromtimestamp(record.created)\n        if datefmt:\n            s = ct.strftime(datefmt)\n        else:\n            # Format datetime object ct to microseconds\n            t = ct.strftime(\"%Y-%m-%d %H:%M:%S\")\n            s = f\"{t},{record.msecs:03}\"\n        return s\n\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 108,
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        "nloc": 8,
        "token_counts": 51,
        "n_ast_nodes": 100,
        "n_identifiers": 13,
        "d_id": 35586,
        "documentation": {
            "docstring": "\n        Return the creation time of the specified LogRecord as formatted text.\n\n        This custom logging formatter inherits from the logging module and\n        records timestamps at the microsecond level of granularity.\n\n        Parameters\n        ----------\n        record : LogRecord\n            The specified LogRecord object.\n        datefmt : str, default: None\n            Used with time.ststrftime() to format time record.\n\n        Returns\n        -------\n        datetime\n            Datetime object containing microsecond timestamp.\n        ",
            "n_words": 58,
            "vocab_size": 47,
            "n_whitespaces": 169,
            "language": "en"
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    {
        "id": 122219,
        "commit_id": "4da72cf3988b4918f65b1401e46c40b7c4504963",
        "repo": "jax",
        "path": "jax/experimental/pjit.py",
        "file_name": "pjit.py",
        "fun_name": "host_local_array_to_global_array",
        "commit_message": "Add `host_local_array_to_global_array` and `global_array_to_host_local_array` for enabling transition to jax.Array.\n\nAlso support `FROM_GDA` for `jax.Array` as a backwards compatible change so that users can continue to use that until they transition to jax.Array. Its currently required because of usage like `in_axis_resources = (FROM_GDA, FROM_GDA, P('data'), None)` and changing this on users side will require input from users so we as JAX can just support it as a temporary thing since GDA and Array act similarly in pjit.\n\nPiperOrigin-RevId: 479035326",
        "code": "def host_local_array_to_global_array(local_inputs, global_mesh, pspecs):\n  \n  def _convert(arr, pspec):\n    if isinstance(arr, array.ArrayImpl) and isinstance(arr.sharding, PmapSharding):\n      arr = np.array(arr)\n    local_sharding = MeshPspecSharding(global_mesh.local_mesh, pspec)\n    arrays = [\n        device_put(arr[index], d)\n        for d, index in local_sharding.devices_indices_map(arr.shape).items()\n    ]\n    global_aval = global_mesh._local_to_global(\n        pxla._get_array_mapping(pspec),\n        core.ShapedArray(arr.shape, arrays[0].dtype))\n    return array.ArrayImpl(global_aval, MeshPspecSharding(global_mesh, pspec),\n                           arrays, committed=True)\n\n  flattened_inps, in_tree = tree_flatten(local_inputs)\n  in_pspecs = flatten_axis_resources(\n      'input pspecs', in_tree, pspecs, tupled_args=True)\n  out = tree_map(_convert, tuple(flattened_inps), in_pspecs)\n  return tree_unflatten(in_tree, out)\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 151,
        "n_words": 63,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 54,
        "n_ast_nodes": 262,
        "n_identifiers": 41,
        "d_id": 27124,
        "documentation": {
            "docstring": "Converts a host local value to a globally sharded `jax.Array`.\n\n  You can use this function to transition to `jax.Array`. Using `jax.Array` with\n  `pjit` has the same semantics of using GDA with pjit i.e. all `jax.Array`\n  inputs to pjit should be globally shaped.\n\n  If you are currently passing host local values to pjit, you can use this\n  function to convert your host local values to global Arrays and then pass that\n  to pjit.\n\n  Example usage:\n\n  ```\n  global_inputs = jax.experimental.pjit.host_local_array_to_global_array(\n    host_local_inputs, global_mesh, in_pspecs)\n\n  with mesh:\n    global_out = pjitted_fun(global_inputs)\n\n  host_local_output = jax.experimental.pjit.global_array_to_host_local_array(\n    global_out, mesh, out_pspecs)\n  ```\n\n  Args:\n    local_inputs: A Pytree of host local values.\n    global_mesh: The global mesh.\n    pspecs: A Pytree of PartitionSpecs.\n  ",
            "n_words": 110,
            "vocab_size": 76,
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            "language": "en"
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    },
    {
        "id": 223783,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/message.py",
        "file_name": "message.py",
        "fun_name": "get_charsets",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_charsets(self, failobj=None):\n        \n        return [part.get_content_charset(failobj) for part in self.walk()]\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 23,
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        "vocab_size": 9,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 27,
        "n_ast_nodes": 44,
        "n_identifiers": 6,
        "d_id": 57064,
        "documentation": {
            "docstring": "Return a list containing the charset(s) used in this message.\n\n        The returned list of items describes the Content-Type headers'\n        charset parameter for this message and all the subparts in its\n        payload.\n\n        Each item will either be a string (the value of the charset parameter\n        in the Content-Type header of that part) or the value of the\n        'failobj' parameter (defaults to None), if the part does not have a\n        main MIME type of \"text\", or the charset is not defined.\n\n        The list will contain one string for each part of the message, plus\n        one for the container message (i.e. self), so that a non-multipart\n        message will still return a list of length 1.\n        ",
            "n_words": 112,
            "vocab_size": 67,
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            "language": "en"
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    {
        "id": 22022,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/pygments/lexers/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_all_lexers",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def get_all_lexers(plugins=True):\n    \n    for item in LEXERS.values():\n        yield item[1:]\n    if plugins:\n        for lexer in find_plugin_lexers():\n            yield lexer.name, lexer.aliases, lexer.filenames, lexer.mimetypes\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 53,
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        "token_counts": 49,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 4117,
        "documentation": {
            "docstring": "Return a generator of tuples in the form ``(name, aliases,\n    filenames, mimetypes)`` of all know lexers.\n\n    If *plugins* is true (the default), plugin lexers supplied by entrypoints\n    are also returned.  Otherwise, only builtin ones are considered.\n    ",
            "n_words": 36,
            "vocab_size": 34,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 138398,
        "commit_id": "30ab5458a7e4ba2351d5e1beef8c8797b5946493",
        "repo": "ray",
        "path": "dashboard/state_aggregator.py",
        "file_name": "state_aggregator.py",
        "fun_name": "get_placement_groups",
        "commit_message": "[State Observability] Tasks and Objects API (#23912)\n\nThis PR implements ray list tasks and ray list objects APIs.\r\n\r\nNOTE: You can ignore the merge conflict for now. It is because the first PR was reverted. There's a fix PR open now.",
        "code": "async def get_placement_groups(self) -> dict:\n        \n        reply = await self._client.get_all_placement_group_info(\n            timeout=DEFAULT_RPC_TIMEOUT\n        )\n        result = {}\n        for message in reply.placement_group_table_data:\n            data = self._message_to_dict(\n                message=message,\n                fields_to_decode=[\"placement_group_id\"],\n            )\n            data = filter_fields(data, PlacementGroupState)\n            result[data[\"placement_group_id\"]] = data\n        return result\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "nloc": 19,
        "token_counts": 68,
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        "d_id": 31406,
        "documentation": {
            "docstring": "List all placement group information from the cluster.\n\n        Returns:\n            {pg_id -> pg_data_in_dict}\n            pg_data_in_dict's schema is in PlacementGroupState\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 53,
            "language": "en"
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    },
    {
        "id": 258354,
        "commit_id": "9ebf164cfdfb320503b7161493420c1b0ec577a3",
        "repo": "haystack",
        "path": "haystack/nodes/prompt/prompt_node.py",
        "file_name": "prompt_node.py",
        "fun_name": "get_prompt_template_names",
        "commit_message": "feat: Expand LLM support with PromptModel, PromptNode, and PromptTemplate (#3667)\n\nCo-authored-by: ZanSara <sarazanzo94@gmail.com>",
        "code": "def get_prompt_template_names(cls) -> List[str]:\n        \n        return list(cls.prompt_templates.keys())\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "d_id": 75224,
        "documentation": {
            "docstring": "\n        Returns the list of supported prompt template names.\n        :return: List of supported prompt template names.\n        ",
            "n_words": 15,
            "vocab_size": 10,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 102547,
        "commit_id": "8d05174defd689cb1cb2346e0cde5b7fa572814a",
        "repo": "pytorch",
        "path": "torch/testing/_comparison.py",
        "file_name": "_comparison.py",
        "fun_name": "_handle_meta_tensor_data_access",
        "commit_message": "make meta tensor data access error message for expressive in assert_close (#68802)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/68802\n\nWithout this patch, the error message of comparing meta tensors looks like this after #68722 was merged:\n\n```python\n>>> t = torch.empty((), device=\"meta\")\n>>> assert_close(t, t)\nNotImplementedError: Could not run 'aten::abs.out' with arguments from the 'Meta' backend. [...]\n[...]\nThe above exception was the direct cause of the following exception:\n[...]\nRuntimeError: Comparing\n\nTensorLikePair(\n    id=(),\n    actual=tensor(..., device='meta', size=()),\n    expected=tensor(..., device='meta', size=()),\n    rtol=1.3e-06,\n    atol=1e-05,\n    equal_nan=False,\n    check_device=True,\n    check_dtype=True,\n    check_layout=True,\n    check_stride=False,\n    check_is_coalesced=True,\n)\n\nresulted in the unexpected exception above. If you are a user and see this message during normal operation please file an issue at https://github.com/pytorch/pytorch/issues. If you are a developer and working on the comparison functions, please except the previous error and raise an expressive `ErrorMeta` instead.\n```\n\nThus, we follow our own advice and turn it into an expected exception until #68592 is resolved:\n\n```python\n>>> t = torch.empty((), device=\"meta\")\n>>> assert_close(t, t)\nValueError: Comparing meta tensors is currently not supported\n```\n\nTest Plan: Imported from OSS\n\nReviewed By: ngimel\n\nDifferential Revision: D33542999\n\nPulled By: mruberry\n\nfbshipit-source-id: 0fe1ddee15b5decdbd4c5dd84f03804ca7eac95b",
        "code": "def _handle_meta_tensor_data_access(self):\n        \n        try:\n            yield\n        except NotImplementedError as error:\n            if \"meta\" not in str(error).lower():\n                raise error\n\n            # TODO: See https://github.com/pytorch/pytorch/issues/68592\n            raise self._make_error_meta(NotImplementedError, \"Comparing meta tensors is currently not supported.\")\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 108,
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        "complexity": 3,
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        "token_counts": 38,
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        "n_identifiers": 7,
        "d_id": 21545,
        "documentation": {
            "docstring": "Turns a vanilla :class:`NotImplementedError` stemming from data access on a meta tensor into an expressive\n        :class:`ErrorMeta`.\n\n        Although it looks like meta tensors could be handled upfront, we need to do it lazily: there are use cases\n        where a meta tensor wraps a data tensors and dispatches all operator calls to it. Thus, although the tensor is\n        a meta tensor, it behaves like a regular one.\n        ",
            "n_words": 65,
            "vocab_size": 49,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 117490,
        "commit_id": "fca34e2db1ab32fb348abb3b6e9d5feef80b6d23",
        "repo": "mindsdb",
        "path": "tests/unit/test_merlion_handler.py",
        "file_name": "test_merlion_handler.py",
        "fun_name": "exec_train_and_forecast",
        "commit_message": "Integration merlion issue2377 (#3435)\n\n* [issue2377] Merlion integrated, forecaster: default, sarima, prophet, mses, detector: default, isolation forest, windstats, prophet.\r\n\r\n* [issue2377] 1) Add ref to models; 2) Use url to fetch test data; 3) Set author.\r\n\r\n* [issue2377] 1) Replace print with mindsdb.log 2) Add lower and upper bound of merlin version in requirements.\r\n\r\n* [issue2377] 1) requirements.txt fixed. 2) test cases fixed. 3) Code refined.\r\n\r\n* [issue2377] Delete the redundant logic of expanding customized columns.\r\n\r\n* [issue2377] Some useless column processing code removed.\r\n\r\n* [issue2377] Truncate blank lines.\r\n\r\n* [issue2377] Fix\r\n\r\n* [issue2377] 1) Fix some bugs, 2) Modify testcase according to the modification of mindsdb (Add 'project' concept and use engine='xx' to specify handler)\r\n\r\n* [issue2377] 1) Using timeseries_settings.order_by/window/horizon in merlion 2) Fix importing problem caused by merging about mindsdb.utilities.log.\r\n\r\n* [issue2377] Fix the arg fetching problem causing by merging staging.",
        "code": "def exec_train_and_forecast(self, mock_handler, model_name, using):\n        # create predictor\n        create_sql = f\n        ret = self.run_mindsdb_sql(sql=create_sql)\n        assert ret.error_code is None, \"train failed: \" + model_name\n\n        self.wait_training(model_name=f'{model_name}_forecaster')\n\n        predict_sql = f\n        ret = self.run_mindsdb_sql(sql=predict_sql)\n        assert ret.error_code is None, \"forecast failed: \" + model_name\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 94,
        "n_words": 39,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 68,
        "n_ast_nodes": 125,
        "n_identifiers": 12,
        "d_id": 26018,
        "documentation": {
            "docstring": "\n                    CREATE PREDICTOR mindsdb.{model_name}_forecaster\n                    FROM pg\n                    (select t, H1 from m4 where train = 1) \n                    PREDICT H1\n                    USING engine='merlion'{using}\n                \n                    select p.t, p.H1 real, t.H1, t.H1__upper, t.H1__lower\n                    from mindsdb.{model_name}_forecaster t\n                    inner join pg.m4 p on t.t = p.t\n                    where p.train = 0\n                ",
            "n_words": 40,
            "vocab_size": 34,
            "n_whitespaces": 244,
            "language": "en"
        }
    },
    {
        "id": 63872,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/toml/decoder.py",
        "file_name": "decoder.py",
        "fun_name": "load",
        "commit_message": "upd; format",
        "code": "def load(f, _dict=dict, decoder=None):\n    \n\n    if _ispath(f):\n        with io.open(_getpath(f), encoding='utf-8') as ffile:\n            return loads(ffile.read(), _dict, decoder)\n    elif isinstance(f, list):\n        from os import path as op\n        from warnings import warn\n        if not [path for path in f if op.exists(path)]:\n            error_msg = \"Load expects a list to contain filenames only.\"\n            error_msg += linesep\n            error_msg += (\"The list needs to contain the path of at least one \"\n                          \"existing file.\")\n            raise FNFError(error_msg)\n        if decoder is None:\n            decoder = TomlDecoder(_dict)\n        d = decoder.get_empty_table()\n        for l in f:  # noqa: E741\n            if op.exists(l):\n                d.update(load(l, _dict, decoder))\n            else:\n                warn(\"Non-existent filename in list with at least one valid \"\n                     \"filename\")\n        return d\n    else:\n        try:\n            return loads(f.read(), _dict, decoder)\n        except AttributeError:\n            raise TypeError(\"You can only load a file descriptor, filename or \"\n                            \"list\")\n\n\n_groupname_re = re.compile(r'^[A-Za-z0-9_-]+$')\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 421,
        "n_words": 127,
        "vocab_size": 88,
        "complexity": 10,
        "nloc": 29,
        "token_counts": 181,
        "n_ast_nodes": 323,
        "n_identifiers": 34,
        "d_id": 13519,
        "documentation": {
            "docstring": "Parses named file or files as toml and returns a dictionary\n\n    Args:\n        f: Path to the file to open, array of files to read into single dict\n           or a file descriptor\n        _dict: (optional) Specifies the class of the returned toml dictionary\n        decoder: The decoder to use\n\n    Returns:\n        Parsed toml file represented as a dictionary\n\n    Raises:\n        TypeError -- When f is invalid type\n        TomlDecodeError: Error while decoding toml\n        IOError / FileNotFoundError -- When an array with no valid (existing)\n        (Python 2 / Python 3)          file paths is passed\n    ",
            "n_words": 87,
            "vocab_size": 62,
            "n_whitespaces": 174,
            "language": "en"
        }
    },
    {
        "id": 80110,
        "commit_id": "ec6229c23600ebae8ec0d5db6846b095a9468151",
        "repo": "wagtail",
        "path": "wagtail/blocks/migrations/utils.py",
        "file_name": "utils.py",
        "fun_name": "map_stream_block_value",
        "commit_message": "Add StreamField migration helpers from https://github.com/sandilsranasinghe/wagtail-streamfield-migration-toolkit/",
        "code": "def map_stream_block_value(stream_block_value, block_def, block_path, **kwargs):\n    \n\n    mapped_value = []\n    for child_block in stream_block_value:\n\n        if not should_alter_block(child_block[\"type\"], block_path):\n            mapped_value.append(child_block)\n\n        else:\n            try:\n                child_block_def = block_def.child_blocks[child_block[\"type\"]]\n            except KeyError:\n                raise InvalidBlockDefError(\n                    \"No current block def named {}\".format(child_block[\"type\"])\n                )\n            mapped_child_value = map_block_value(\n                child_block[\"value\"],\n                block_def=child_block_def,\n                block_path=block_path[1:],\n                **kwargs,\n            )\n            mapped_value.append({**child_block, \"value\": mapped_child_value})\n\n    return mapped_value\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 262,
        "n_words": 46,
        "vocab_size": 41,
        "complexity": 4,
        "nloc": 20,
        "token_counts": 111,
        "n_ast_nodes": 182,
        "n_identifiers": 16,
        "d_id": 17006,
        "documentation": {
            "docstring": "\n    Maps each child block in a StreamBlock value.\n\n    Args:\n        stream_block_value:\n            The value of the StreamBlock, a list of child blocks\n        block_def:\n            The definition of the StreamBlock\n        block_path:\n            A '.' separated list of names of the blocks from the current block (not included) to\n            the nested block of which the value will be passed to the operation.\n\n    Returns\n        mapped_value:\n            The value of the StreamBlock after mapping all the children.\n    ",
            "n_words": 68,
            "vocab_size": 41,
            "n_whitespaces": 164,
            "language": "en"
        }
    },
    {
        "id": 247727,
        "commit_id": "9e06e220649cc0139749c388a894bee0d65d5f4e",
        "repo": "synapse",
        "path": "tests/handlers/test_federation.py",
        "file_name": "test_federation.py",
        "fun_name": "test_invite_by_user_ratelimit",
        "commit_message": "Add type hints to more tests files. (#12240)",
        "code": "def test_invite_by_user_ratelimit(self) -> None:\n        \n        other_server = \"otherserver\"\n        other_user = \"@otheruser:\" + other_server\n\n        # create the room\n        user_id = self.register_user(\"kermit\", \"test\")\n        tok = self.login(\"kermit\", \"test\")\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 66,
        "n_words": 24,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 27,
        "token_counts": 101,
        "n_ast_nodes": 72,
        "n_identifiers": 8,
        "d_id": 71877,
        "documentation": {
            "docstring": "Tests that invites from federation to a particular user are\n        actually rate-limited.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 249401,
        "commit_id": "3dd175b628bab5638165f20de9eade36a4e88147",
        "repo": "synapse",
        "path": "synapse/http/site.py",
        "file_name": "site.py",
        "fun_name": "get_authenticated_entity",
        "commit_message": "`synapse.api.auth.Auth` cleanup: make permission-related methods use `Requester` instead of the `UserID` (#13024)\n\nPart of #13019\r\n\r\nThis changes all the permission-related methods to rely on the Requester instead of the UserID. This is a first step towards enabling scoped access tokens at some point, since I expect the Requester to have scope-related informations in it.\r\n\r\nIt also changes methods which figure out the user/device/appservice out of the access token to return a Requester instead of something else. This avoids having store-related objects in the methods signatures.",
        "code": "def get_authenticated_entity(self) -> Tuple[Optional[str], Optional[str]]:\n        \n        # Convert the requester into a string that we can log\n        if isinstance(self._requester, str):\n            return self._requester, None\n        elif isinstance(self._requester, Requester):\n            requester = self._requester.user.to_string()\n            authenticated_entity = self._requester.authenticated_entity\n\n            # If this is a request where the target user doesn't match the user who\n            # authenticated (e.g. and admin is puppetting a user) then we return both.\n            if requester != authenticated_entity:\n                return requester, authenticated_entity\n\n            return requester, None\n        elif self._requester is not None:\n            # This shouldn't happen, but we log it so we don't lose information\n            # and can see that we're doing something wrong.\n            return repr(self._requester), None  # type: ignore[unreachable]\n\n        return None, None\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 273,
        "n_words": 105,
        "vocab_size": 70,
        "complexity": 5,
        "nloc": 24,
        "token_counts": 97,
        "n_ast_nodes": 156,
        "n_identifiers": 13,
        "d_id": 72895,
        "documentation": {
            "docstring": "\n        Get the \"authenticated\" entity of the request, which might be the user\n        performing the action, or a user being puppeted by a server admin.\n\n        Returns:\n            A tuple:\n                The first item is a string representing the user making the request.\n\n                The second item is a string or None representing the user who\n                authenticated when making this request. See\n                Requester.authenticated_entity.\n        ",
            "n_words": 58,
            "vocab_size": 38,
            "n_whitespaces": 158,
            "language": "en"
        }
    },
    {
        "id": 245836,
        "commit_id": "9c1b26726eebe4a196d213249dc22e8017761fab",
        "repo": "mmdetection",
        "path": "mmdet/models/detectors/d2_wrapper.py",
        "file_name": "d2_wrapper.py",
        "fun_name": "_forward",
        "commit_message": "[Feature] Support training detection models in detectron2 (#8672)\n\n* [Feature]Support using mmengine to train detectron2\r\n\r\n* update\r\n\r\n* del unnecessary comments\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* Support mask rcnn and retinanet\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* chinese doc\r\n\r\n* update\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* update docs",
        "code": "def _forward(self, *args, **kwargs):\n        \n        raise NotImplementedError(\n            f'`_forward` is not implemented in {self.__class__.__name__}')\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 37,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 18,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 70906,
        "documentation": {
            "docstring": "Network forward process.\n\n        Usually includes backbone, neck and head forward without any post-\n        processing.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 286052,
        "commit_id": "4304a5c664700cf083f1432fa7523f051492754c",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/economy/wsj_model.py",
        "file_name": "wsj_model.py",
        "fun_name": "us_indices",
        "commit_message": "Enhances error handling in economy menu (#2819)\n\n* Lots of bug fixes\r\n\r\n* Fixed issue",
        "code": "def us_indices() -> pd.DataFrame:\n    \n    url = (\n        \"https://www.wsj.com/market-data/stocks?id=%7B%22application%22%3A%22WSJ%22%2C%22instruments%22%3A%5B%7B\"\n        \"%22symbol%22%3A%22INDEX%2FUS%2F%2FDJIA%22%2C%22name%22%3A%22DJIA%22%7D%2C%7B%22symbol%22%3A%22INDEX%2FUS%2F\"\n        \"%2FCOMP%22%2C%22name%22%3A%22Nasdaq%20Composite%22%7D%2C%7B%22symbol%22%3A%22INDEX%2FUS%2F%2FSPX%22%2C%22name\"\n        \"%22%3A%22S%26P%20500%22%7D%2C%7B%22symbol%22%3A%22INDEX%2FUS%2F%2FDWCF%22%2C%22name%22%3A%22DJ%20Total%20Stock\"\n        \"%20Market%22%7D%2C%7B%22symbol%22%3A%22INDEX%2FUS%2F%2FRUT%22%2C%22name%22%3A%22Russell%202000%22%7D%2C%7B\"\n        \"%22symbol%22%3A%22INDEX%2FUS%2F%2FNYA%22%2C%22name%22%3A%22NYSE%20Composite%22%7D%2C%7B%22symbol%22%3A%22INDEX\"\n        \"%2FUS%2F%2FB400%22%2C%22name%22%3A%22Barron%27s%20400%22%7D%2C%7B%22symbol%22%3A%22INDEX%2FUS%2F%2FVIX%22%2C%22\"\n        \"name%22%3A%22CBOE%20Volatility%22%7D%2C%7B%22symbol%22%3A%22FUTURE%2FUS%2F%2FDJIA%20FUTURES%22%2C%22name%22%3A%\"\n        \"22DJIA%20Futures%22%7D%2C%7B%22symbol%22%3A%22FUTURE%2FUS%2F%2FS%26P%20500%20FUTURES%22%2C%22name%22%3A%22S%26P\"\n        \"%20500%20Futures%22%7D%5D%7D&type=mdc_quotes\"\n    )\n    try:\n        response = requests.get(\n            url,\n            headers={\"User-Agent\": get_user_agent()},\n        )\n    except requests.exceptions.RequestException:\n        console.print(\"[red]Could not retrieve data from wsj.[/red]\\n\")\n        return pd.DataFrame()\n    data = response.json()\n\n    name, last_price, net_change, percent_change = [], [], [], []\n\n    for entry in data[\"data\"][\"instruments\"]:\n        name.append(entry[\"formattedName\"])\n        last_price.append(entry[\"lastPrice\"])\n        net_change.append(entry[\"priceChange\"])\n        percent_change.append(entry[\"percentChange\"])\n\n    indices = pd.DataFrame(\n        {\" \": name, \"Price\": last_price, \"Chg\": net_change, \"%Chg\": percent_change}\n    )\n\n    return indices\n\n\n@log_start_end(log=logger)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 259,
        "n_words": 72,
        "vocab_size": 58,
        "complexity": 3,
        "nloc": 39,
        "token_counts": 162,
        "n_ast_nodes": 304,
        "n_identifiers": 25,
        "d_id": 85525,
        "documentation": {
            "docstring": "Get the top US indices\n\n    Returns\n    -------\n    indices: pd.DataFrame\n        Dataframe containing name, price, net change and percent change\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 301790,
        "commit_id": "635d7085cf42dfaf8e60d1e262f096827d56e6e1",
        "repo": "core",
        "path": "homeassistant/components/mqtt/scene.py",
        "file_name": "scene.py",
        "fun_name": "async_activate",
        "commit_message": "Move MQTT config schemas and client to separate modules (#71995)\n\n* Move MQTT config schemas and client to separate modules\r\n\r\n* Update integrations depending on MQTT",
        "code": "async def async_activate(self, **kwargs):\n        \n        await async_publish(\n            self.hass,\n            self._config[CONF_COMMAND_TOPIC],\n            self._config[CONF_PAYLOAD_ON],\n            self._config[CONF_QOS],\n            self._config[CONF_RETAIN],\n            self._config[CONF_ENCODING],\n        )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 100,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 52,
        "n_ast_nodes": 76,
        "n_identifiers": 11,
        "d_id": 100629,
        "documentation": {
            "docstring": "Activate the scene.\n\n        This method is a coroutine.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 271578,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training.py",
        "file_name": "training.py",
        "fun_name": "state_updates",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def state_updates(self):\n        \n        warnings.warn(\n            \"`Model.state_updates` will be removed in a future version. \"\n            \"This property should not be used in TensorFlow 2.0, \"\n            \"as `updates` are applied automatically.\",\n            stacklevel=2,\n        )\n        state_updates = []\n        for layer in self.layers:\n            if getattr(layer, \"stateful\", False):\n                if hasattr(layer, \"updates\"):\n                    state_updates += layer.updates\n        return state_updates\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 179,
        "n_words": 48,
        "vocab_size": 41,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 55,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 80809,
        "documentation": {
            "docstring": "Deprecated, do NOT use!\n\n        Returns the `updates` from all layers that are stateful.\n\n        This is useful for separating training updates and\n        state updates, e.g. when we need to update a layer's internal state\n        during prediction.\n\n        Returns:\n            A list of update ops.\n        ",
            "n_words": 41,
            "vocab_size": 39,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 299731,
        "commit_id": "ea456893f94c7dc88b0cc28f92dadf240fbb1fe7",
        "repo": "core",
        "path": "tests/components/androidtv/test_media_player.py",
        "file_name": "test_media_player.py",
        "fun_name": "test_get_image_disabled",
        "commit_message": "Review AndroidTV tests for media player entity (#71168)",
        "code": "async def test_get_image_disabled(hass, hass_ws_client):\n    \n    patch_key, entity_id, config_entry = _setup(CONFIG_ANDROIDTV_DEFAULT)\n    config_entry.add_to_hass(hass)\n    hass.config_entries.async_update_entry(\n        config_entry, options={CONF_SCREENCAP: False}\n    )\n\n    with patchers.patch_connect(True)[patch_key], patchers.patch_shell(\n        SHELL_RESPONSE_OFF\n    )[patch_key]:\n        assert await hass.config_entries.async_setup(config_entry.entry_id)\n        await hass.async_block_till_done()\n\n    with patchers.patch_shell(\"11\")[patch_key]:\n        await async_update_entity(hass, entity_id)\n\n    client = await hass_ws_client(hass)\n\n    with patch(\n        \"androidtv.basetv.basetv_async.BaseTVAsync.adb_screencap\", return_value=b\"image\"\n    ) as screen_cap:\n        await client.send_json(\n            {\"id\": 5, \"type\": \"media_player_thumbnail\", \"entity_id\": entity_id}\n        )\n\n        await client.receive_json()\n        assert not screen_cap.called\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 169,
        "n_words": 55,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 147,
        "n_ast_nodes": 253,
        "n_identifiers": 28,
        "d_id": 98635,
        "documentation": {
            "docstring": "Test taking a screen capture with screencap option disabled.\n\n    This is based on `test_get_image` in tests/components/media_player/test_init.py.\n    ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 215721,
        "commit_id": "eb8bd12761fdad5abc682bf29c131231736f4616",
        "repo": "salt",
        "path": "tests/pytests/unit/log/handlers/test_sentry_mod.py",
        "file_name": "test_sentry_mod.py",
        "fun_name": "test___virtual___fail",
        "commit_message": "Test that sentry logger does not load grains/modules\n\nReinforce sentry log handler not wasting time reloading grains/execution\nmodules with unit tests.",
        "code": "def test___virtual___fail(sentry_handler):\n    \n    with patch(\"salt.log.handlers.sentry_mod.HAS_RAVEN\", False), patch(\n        \"salt.log.handlers.sentry_mod.__opts__\", sentry_handler\n    ):\n        ret = salt.log.handlers.sentry_mod.__virtual__()\n    assert ret[0] is False\n    assert ret[1] == \"Cannot find 'raven' python library\"\n\n    with patch(\"salt.log.handlers.sentry_mod.HAS_RAVEN\", True), patch(\n        \"salt.log.handlers.sentry_mod.__opts__\", {}\n    ):\n        ret = salt.log.handlers.sentry_mod.__virtual__()\n    assert ret[0] is False\n    assert ret[1] == \"'sentry_handler' config is empty or not defined\"\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 103,
        "n_words": 48,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 91,
        "n_ast_nodes": 157,
        "n_identifiers": 9,
        "d_id": 54121,
        "documentation": {
            "docstring": "\n    Test `__virtual__()` returns a reason for not loading.\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 287748,
        "commit_id": "1b144c0e4dd683e3b47668a89da5eb6da4ae5e08",
        "repo": "core",
        "path": "homeassistant/components/bluetooth/usage.py",
        "file_name": "usage.py",
        "fun_name": "install_multiple_bleak_catcher",
        "commit_message": "Update to bleak 0.18.0 (#79008)",
        "code": "def install_multiple_bleak_catcher() -> None:\n    \n    bleak.BleakScanner = HaBleakScannerWrapper  # type: ignore[misc, assignment]\n    bleak.BleakClient = HaBleakClientWrapper  # type: ignore[misc, assignment]\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 29,
        "n_words": 18,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 17,
        "n_ast_nodes": 33,
        "n_identifiers": 6,
        "d_id": 86936,
        "documentation": {
            "docstring": "Wrap the bleak classes to return the shared instance if multiple instances are detected.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 267172,
        "commit_id": "5c2d830dea986a8c7bd8c286b86bdce326cd7eb1",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/host_profiles.py",
        "file_name": "host_profiles.py",
        "fun_name": "configure",
        "commit_message": "ansible-test - Fix subprocess management. (#77641)\n\n* Run code-smell sanity tests in UTF-8 Mode.\r\n* Update subprocess use in sanity test programs.\r\n* Use raw_command instead of run_command with always=True set.\r\n* Add more capture=True usage.\r\n* Don't expose stdin to subprocesses.\r\n* Capture more output. Warn on retry.\r\n* Add more captures.\r\n* Capture coverage cli output.\r\n* Capture windows and network host checks.\r\n* Be explicit about interactive usage.\r\n* Use a shell for non-captured, non-interactive subprocesses.\r\n* Add integration test to assert no TTY.\r\n* Add unit test to assert no TTY.\r\n* Require blocking stdin/stdout/stderr.\r\n* Use subprocess.run in ansible-core sanity tests.\r\n* Remove unused arg.\r\n* Be explicit with subprocess.run check=False.\r\n* Add changelog.\r\n* Use a Python subprocess instead of a shell.\r\n* Use InternalError instead of Exception.\r\n* Require capture argument.\r\n* Check for invalid raw_command arguments.\r\n* Removed pointless communicate=True usage.\r\n* Relocate stdout w/o capture check.\r\n* Use threads instead of a subprocess for IO.",
        "code": "def configure(self):  # type: () -> None\n        \n        # a target uses a single python version, but a controller may include additional versions for targets running on the controller\n        python_versions = [self.python.version] + [target.python.version for target in self.targets if isinstance(target, ControllerConfig)]\n        python_versions = sorted_versions(list(set(python_versions)))\n\n        core_ci = self.wait_for_instance()\n        pwd = self.wait_until_ready()\n\n        display.info(f'Remote working directory: {pwd}', verbosity=1)\n\n        bootstrapper = BootstrapRemote(\n            controller=self.controller,\n            platform=self.config.platform,\n            platform_version=self.config.version,\n            python_versions=python_versions,\n            ssh_key=core_ci.ssh_key,\n        )\n\n        setup_sh = bootstrapper.get_script()\n        shell = setup_sh.splitlines()[0][2:]\n\n        ssh = self.get_origin_controller_connection()\n        ssh.run([shell], data=setup_sh, capture=False)\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 222,
        "n_words": 75,
        "vocab_size": 61,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 154,
        "n_ast_nodes": 245,
        "n_identifiers": 35,
        "d_id": 78777,
        "documentation": {
            "docstring": "Perform in-band configuration. Executed before delegation for the controller and after delegation for targets.",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 107162,
        "commit_id": "ec4dfbc3c83866f487ff0bc9c87b0d43a1c02b22",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_constrainedlayout.py",
        "file_name": "test_constrainedlayout.py",
        "fun_name": "test_align_labels",
        "commit_message": "ENH: implement and use base layout_engine for more flexible layout.",
        "code": "def test_align_labels():\n    \n    fig, (ax3, ax1, ax2) = plt.subplots(3, 1, layout=\"constrained\",\n                                        figsize=(6.4, 8),\n                                        gridspec_kw={\"height_ratios\": (1, 1,\n                                                                       0.7)})\n\n    ax1.set_ylim(0, 1)\n    ax1.set_ylabel(\"Label\")\n\n    ax2.set_ylim(-1.5, 1.5)\n    ax2.set_ylabel(\"Label\")\n\n    ax3.set_ylim(0, 1)\n    ax3.set_ylabel(\"Label\")\n\n    fig.align_ylabels(axs=(ax3, ax1, ax2))\n\n    fig.draw_without_rendering()\n    after_align = [ax1.yaxis.label.get_window_extent(),\n                   ax2.yaxis.label.get_window_extent(),\n                   ax3.yaxis.label.get_window_extent()]\n    # ensure labels are approximately aligned\n    np.testing.assert_allclose([after_align[0].x0, after_align[2].x0],\n                               after_align[1].x0, rtol=0, atol=1e-05)\n    # ensure labels do not go off the edge\n    assert after_align[0].x0 >= 1\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 317,
        "n_words": 58,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 200,
        "n_ast_nodes": 294,
        "n_identifiers": 25,
        "d_id": 22617,
        "documentation": {
            "docstring": "\n    Tests for a bug in which constrained layout and align_ylabels on\n    three unevenly sized subplots, one of whose y tick labels include\n    negative numbers, drives the non-negative subplots' y labels off\n    the edge of the plot\n    ",
            "n_words": 36,
            "vocab_size": 31,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 71901,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_contentstate.py",
        "file_name": "test_contentstate.py",
        "fun_name": "test_broken_document_link",
        "commit_message": "Reformat with black",
        "code": "def test_broken_document_link(self):\n        converter = ContentstateConverter(features=[\"document-link\"])\n        result = json.loads(\n            converter.from_database_format(\n                \n            )\n        )\n        self.assertContentStateEqual(\n            result,\n            {\n                \"entityMap\": {\n                    \"0\": {\n                        \"mutability\": \"MUTABLE\",\n                        \"type\": \"DOCUMENT\",\n                        \"data\": {\"id\": 9999},\n                    }\n                },\n                \"blocks\": [\n                    {\n                        \"inlineStyleRanges\": [],\n                        \"text\": \"a document link\",\n                        \"depth\": 0,\n                        \"type\": \"unstyled\",\n                        \"key\": \"00000\",\n                        \"entityRanges\": [{\"offset\": 2, \"length\": 8, \"key\": 0}],\n                    },\n                ],\n            },\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 501,
        "n_words": 53,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 110,
        "n_ast_nodes": 203,
        "n_identifiers": 10,
        "d_id": 15764,
        "documentation": {
            "docstring": "\n            <p>a <a linktype=\"document\" id=\"9999\">document</a> link</p>\n            ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 275284,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_experimental/optimizer.py",
        "file_name": "optimizer.py",
        "fun_name": "finalize_variable_values",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def finalize_variable_values(self, var_list):\n        \n        if self.use_ema:\n            # If the optimizer uses EMA, then when finalizing, we replace the model\n            # variable value with its moving average stored inside optimizer.\n            self._overwrite_model_variables_with_average_value(var_list)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 76,
        "n_words": 29,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 81369,
        "documentation": {
            "docstring": "Set the final value of model's trainable variables.\n\n        Sometimes there are some extra steps before ending the variable updates,\n        such as overriding the model variables with its average value.\n\n        Args:\n          var_list: list of model variables.\n        ",
            "n_words": 35,
            "vocab_size": 30,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 100575,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/gpu_stats/nvidia.py",
        "file_name": "nvidia.py",
        "fun_name": "_get_free_vram",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def _get_free_vram(self) -> List[float]:\n        \n        vram = [pynvml.nvmlDeviceGetMemoryInfo(handle).free / (1024 * 1024)\n                for handle in self._handles]\n        self._log(\"debug\", f\"GPU VRAM free: {vram}\")\n        return vram\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 65,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 46,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 20039,
        "documentation": {
            "docstring": " Obtain the amount of VRAM that is available, in Megabytes, for each connected Nvidia\n        GPU.\n\n        Returns\n        -------\n        list\n             List of `float`s containing the amount of VRAM available, in Megabytes, for each\n             connected GPU as corresponding to the values in :attr:`_handles\n        ",
            "n_words": 40,
            "vocab_size": 27,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 249309,
        "commit_id": "2281427175e4c93a30c39607fb4ac23c2a1f399f",
        "repo": "synapse",
        "path": "tests/rest/admin/test_event_reports.py",
        "file_name": "test_event_reports.py",
        "fun_name": "test_from_is_negative",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13488)\n\n* Use literals in place of `HTTPStatus` constants in tests\r\n\r\n* newsfile\r\n\r\n* code style\r\n\r\n* code style",
        "code": "def test_from_is_negative(self) -> None:\n        \n\n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?from=-5\",\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(400, channel.code, msg=channel.json_body)\n        self.assertEqual(Codes.INVALID_PARAM, channel.json_body[\"errcode\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 86,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 60,
        "n_ast_nodes": 97,
        "n_identifiers": 13,
        "d_id": 72812,
        "documentation": {
            "docstring": "\n        Testing that a negative from parameter returns a 400\n        ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 66639,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v12_0/remove_denied_leaves_from_leave_ledger.py",
        "file_name": "remove_denied_leaves_from_leave_ledger.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\t\n\tif not frappe.db.a_row_exists(\"Leave Ledger Entry\"):\n\t\treturn\n\n\tleave_application_list = get_denied_leave_application_list()\n\tif leave_application_list:\n\t\tdelete_denied_leaves_from_leave_ledger_entry(leave_application_list)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 8,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 29,
        "n_ast_nodes": 55,
        "n_identifiers": 7,
        "d_id": 14264,
        "documentation": {
            "docstring": "Delete leave ledger entry created\n\tvia leave applications with status != Approved",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 299149,
        "commit_id": "f073f170402bd02e6d6c7597ce5d842a016e97be",
        "repo": "core",
        "path": "homeassistant/components/recorder/run_history.py",
        "file_name": "run_history.py",
        "fun_name": "clear",
        "commit_message": "Refactor tracking of the recorder run history (#70456)\n\nCo-authored-by: Erik Montnemery <erik@montnemery.com>",
        "code": "def clear(self) -> None:\n        \n        assert self._current_run_info is not None\n        assert self._current_run_info.end is not None\n        self._current_run_info = None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 45,
        "n_words": 17,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 29,
        "n_ast_nodes": 47,
        "n_identifiers": 4,
        "d_id": 98086,
        "documentation": {
            "docstring": "Clear the current run after ending it.\n\n        Must run in the recorder thread.\n        ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 85163,
        "commit_id": "5346de91647f29ce9e24b520c8fb85a7fa0f72d5",
        "repo": "zulip",
        "path": "zerver/webhooks/circleci/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_github_tag_workflow_completed",
        "commit_message": "circleci: Rewrite integration to support the new webhook format.\n\nCircleCI has updated its webhook format[1] for CircleCI Cloud,\nServer version 3.x and 4.x. This commit rewrites the CircleCI\nintegration to parse the new webhook structure. The tests have also\nbeen rewritten for the new format.\n\nWith this commit, we support webhooks from projects that use GitHub,\nBitBucket and GitLab as VCS providers. The CircleCI integration doc\nhas been updated to mention the same. The doc has also been updated\nwith the latest instructions for configuring a webhook on the CircleCI\ninterface, and the new output screenshots.\n\nReferences:\n[1]: https://circleci.com/docs/webhooks",
        "code": "def test_github_tag_workflow_completed(self) -> None:\n        expected_topic = \"circleci-webhook-test\"\n        expected_message = .strip()\n        self.check_webhook(\"github_tag_workflow_completed\", expected_topic, expected_message)\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 33,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 27,
        "n_ast_nodes": 49,
        "n_identifiers": 6,
        "d_id": 17961,
        "documentation": {
            "docstring": "\nWorkflow [`sample`](https://app.circleci.com/pipelines/github/prah23/circleci-webhook-test/20/workflows/045c6271-78e2-4802-8a62-f4fa6d25d0c9) within Pipeline #20 has succeeded.\n\nTriggered on the latest tag on [0e6e66c14e6](https://github.com/prah23/circleci-webhook-test/commit/0e6e66c14e61fbcd95db716b0f30d67dbcce7814).\n",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 264829,
        "commit_id": "5667a9c456e0514a2d00d6475e7013748b4a7c1e",
        "repo": "netbox",
        "path": "netbox/circuits/signals.py",
        "file_name": "signals.py",
        "fun_name": "rebuild_cablepaths",
        "commit_message": "Refactor CablePath.from_origin()",
        "code": "def rebuild_cablepaths(instance, raw=False, **kwargs):\n    \n    if not raw:\n        peer_termination = instance.get_peer_termination()\n        # if peer_termination:\n        #     rebuild_paths(peer_termination)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 46,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 31,
        "n_ast_nodes": 43,
        "n_identifiers": 6,
        "d_id": 77847,
        "documentation": {
            "docstring": "\n    Rebuild any CablePaths which traverse the peer CircuitTermination.\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 107554,
        "commit_id": "3b3fb2afbe3264ea3fa39e7e6e547410b402bfa0",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/axes3d.py",
        "file_name": "axes3d.py",
        "fun_name": "tick_params",
        "commit_message": "Tweak Axes3D docstrings that refer to 2D plotting methods.\n\n... and minor edits to 2D Axes.margins docs as well.",
        "code": "def tick_params(self, axis='both', **kwargs):\n        \n        _api.check_in_list(['x', 'y', 'z', 'both'], axis=axis)\n        if axis in ['x', 'y', 'both']:\n            super().tick_params(axis, **kwargs)\n        if axis in ['z', 'both']:\n            zkw = dict(kwargs)\n            zkw.pop('top', None)\n            zkw.pop('bottom', None)\n            zkw.pop('labeltop', None)\n            zkw.pop('labelbottom', None)\n            self.zaxis.set_tick_params(**zkw)\n\n    # data limits, ticks, tick labels, and formatting\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 150,
        "n_words": 42,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 109,
        "n_ast_nodes": 194,
        "n_identifiers": 12,
        "d_id": 22810,
        "documentation": {
            "docstring": "\n        Convenience method for changing the appearance of ticks and\n        tick labels.\n\n        See `.Axes.tick_params` for full documentation.  Because this function\n        applies to 3D Axes, *axis* can also be set to 'z', and setting *axis*\n        to 'both' autoscales all three axes.\n\n        Also, because of how Axes3D objects are drawn very differently\n        from regular 2D axes, some of these settings may have\n        ambiguous meaning.  For simplicity, the 'z' axis will\n        accept settings as if it was like the 'y' axis.\n\n        .. note::\n           Axes3D currently ignores some of these settings.\n        ",
            "n_words": 86,
            "vocab_size": 72,
            "n_whitespaces": 176,
            "language": "en"
        }
    },
    {
        "id": 62078,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/metadata.py",
        "file_name": "metadata.py",
        "fun_name": "get_fullname",
        "commit_message": "upd; format",
        "code": "def get_fullname(self, filesafe=False):\n        \n        return _get_name_and_version(self['Name'], self['Version'], filesafe)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 21,
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        "d_id": 12863,
        "documentation": {
            "docstring": "Return the distribution name with version.\n\n        If filesafe is true, return a filename-escaped form.",
            "n_words": 14,
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            "language": "en"
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    {
        "id": 196067,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/free_groups.py",
        "file_name": "free_groups.py",
        "fun_name": "eliminate_word",
        "commit_message": "Updated import locations",
        "code": "def eliminate_word(self, gen, by=None, _all=False, inverse=True):\n        \n        if by is None:\n            by = self.group.identity\n        if self.is_independent(gen) or gen == by:\n            return self\n        if gen == self:\n            return by\n        if gen**-1 == by:\n            _all = False\n        word = self\n        l = len(gen)\n\n        try:\n            i = word.subword_index(gen)\n            k = 1\n        except ValueError:\n            if not inverse:\n                return word\n            try:\n                i = word.subword_index(gen**-1)\n                k = -1\n            except ValueError:\n                return word\n\n        word = word.subword(0, i)*by**k*word.subword(i+l, len(word)).eliminate_word(gen, by)\n\n        if _all:\n            return word.eliminate_word(gen, by, _all=True, inverse=inverse)\n        else:\n            return word\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 346,
        "n_words": 81,
        "vocab_size": 47,
        "complexity": 10,
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        "token_counts": 176,
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        "d_id": 47567,
        "documentation": {
            "docstring": "\n        For an associative word `self`, a subword `gen`, and an associative\n        word `by` (identity by default), return the associative word obtained by\n        replacing each occurrence of `gen` in `self` by `by`. If `_all = True`,\n        the occurrences of `gen` that may appear after the first substitution will\n        also be replaced and so on until no occurrences are found. This might not\n        always terminate (e.g. `(x).eliminate_word(x, x**2, _all=True)`).\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import free_group\n        >>> f, x, y = free_group(\"x y\")\n        >>> w = x**5*y*x**2*y**-4*x\n        >>> w.eliminate_word( x, x**2 )\n        x**10*y*x**4*y**-4*x**2\n        >>> w.eliminate_word( x, y**-1 )\n        y**-11\n        >>> w.eliminate_word(x**5)\n        y*x**2*y**-4*x\n        >>> w.eliminate_word(x*y, y)\n        x**4*y*x**2*y**-4*x\n\n        See Also\n        ========\n        substituted_word\n\n        ",
            "n_words": 108,
            "vocab_size": 82,
            "n_whitespaces": 270,
            "language": "en"
        }
    },
    {
        "id": 153859,
        "commit_id": "4ec7f6347903f9133c65ebc5b6e0e15553b98577",
        "repo": "modin",
        "path": "modin/core/execution/dask/implementations/pandas_on_dask/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "__copy__",
        "commit_message": "REFACTOR-#4530: Standardize access to physical data in partitions (#4563)\n\nSigned-off-by: Alexey Prutskov <lehaprutskov@gmail.com>",
        "code": "def __copy__(self):\n        \n        return PandasOnDaskDataframePartition(\n            self._data,\n            length=self._length_cache,\n            width=self._width_cache,\n            ip=self._ip_cache,\n            call_queue=self.call_queue,\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_identifiers": 11,
        "d_id": 35665,
        "documentation": {
            "docstring": "\n        Create a copy of this partition.\n\n        Returns\n        -------\n        PandasOnDaskDataframePartition\n            A copy of this partition.\n        ",
            "n_words": 14,
            "vocab_size": 10,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 196690,
        "commit_id": "9ad8ab9fe58051cf11626ba6654852fcfec60147",
        "repo": "sympy",
        "path": "sympy/stats/crv_types.py",
        "file_name": "crv_types.py",
        "fun_name": "Kumaraswamy",
        "commit_message": "Documentation cleanup 5",
        "code": "def Kumaraswamy(name, a, b):\n    r\n\n    return rv(name, KumaraswamyDistribution, (a, b))\n\n#-------------------------------------------------------------------------------\n# Laplace distribution ---------------------------------------------------------\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "token_counts": 24,
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        "n_identifiers": 6,
        "d_id": 48108,
        "documentation": {
            "docstring": "\n    Create a Continuous Random Variable with a Kumaraswamy distribution.\n\n    Explanation\n    ===========\n\n    The density of the Kumaraswamy distribution is given by\n\n    .. math::\n        f(x) := a b x^{a-1} (1-x^a)^{b-1}\n\n    with :math:`x \\in [0,1]`.\n\n    Parameters\n    ==========\n\n    a : Real number, `a > 0`, a shape\n    b : Real number, `b > 0`, a shape\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    Examples\n    ========\n\n    >>> from sympy.stats import Kumaraswamy, density, cdf\n    >>> from sympy import Symbol, pprint\n\n    >>> a = Symbol(\"a\", positive=True)\n    >>> b = Symbol(\"b\", positive=True)\n    >>> z = Symbol(\"z\")\n\n    >>> X = Kumaraswamy(\"x\", a, b)\n\n    >>> D = density(X)(z)\n    >>> pprint(D, use_unicode=False)\n                       b - 1\n         a - 1 /     a\\\n    a*b*z     *\\1 - z /\n\n    >>> cdf(X)(z)\n    Piecewise((0, z < 0), (1 - (1 - z**a)**b, z <= 1), (1, True))\n\n    References\n    ==========\n\n    .. [1] https://en.wikipedia.org/wiki/Kumaraswamy_distribution\n\n    ",
            "n_words": 131,
            "vocab_size": 86,
            "n_whitespaces": 267,
            "language": "en"
        }
    },
    {
        "id": 136001,
        "commit_id": "e707ce4fb3717e3c05118c57f503dfbd03552ca9",
        "repo": "ray",
        "path": "rllib/evaluation/worker_set.py",
        "file_name": "worker_set.py",
        "fun_name": "num_healthy_workers",
        "commit_message": "[RLlib] Refactor `WorkerSet` on top of `FaultTolerantActorManager`. (#29938)\n\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def num_healthy_workers(self) -> int:\n        \n        return (\n            int(bool(self._local_worker)) + self.__worker_manager.num_healthy_actors()\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 30792,
        "documentation": {
            "docstring": "Returns the number of healthy workers, including local and remote workers.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 24457,
        "commit_id": "ddaa2c2552e19635cd6cdf38619f1f176c358f89",
        "repo": "PaddleOCR",
        "path": "ppstructure/layout/picodet_postprocess.py",
        "file_name": "picodet_postprocess.py",
        "fun_name": "hard_nms",
        "commit_message": "add SLANet",
        "code": "def hard_nms(box_scores, iou_threshold, top_k=-1, candidate_size=200):\n    \n    scores = box_scores[:, -1]\n    boxes = box_scores[:, :-1]\n    picked = []\n    indexes = np.argsort(scores)\n    indexes = indexes[-candidate_size:]\n    while len(indexes) > 0:\n        current = indexes[-1]\n        picked.append(current)\n        if 0 < top_k == len(picked) or len(indexes) == 1:\n            break\n        current_box = boxes[current, :]\n        indexes = indexes[:-1]\n        rest_boxes = boxes[indexes, :]\n        iou = iou_of(\n            rest_boxes,\n            np.expand_dims(\n                current_box, axis=0), )\n        indexes = indexes[iou <= iou_threshold]\n\n    return box_scores[picked, :]\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 196,
        "n_words": 68,
        "vocab_size": 50,
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        "token_counts": 152,
        "n_ast_nodes": 237,
        "n_identifiers": 20,
        "d_id": 4737,
        "documentation": {
            "docstring": "\n    Args:\n        box_scores (N, 5): boxes in corner-form and probabilities.\n        iou_threshold: intersection over union threshold.\n        top_k: keep top_k results. If k <= 0, keep all the results.\n        candidate_size: only consider the candidates with the highest scores.\n    Returns:\n         picked: a list of indexes of the kept boxes\n    ",
            "n_words": 45,
            "vocab_size": 38,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 113688,
        "commit_id": "d68c786ff81bad19c04619d6a999ff34aaa724e7",
        "repo": "nni",
        "path": "nni/compression/pytorch/utils/pruning.py",
        "file_name": "pruning.py",
        "fun_name": "get_module_by_name",
        "commit_message": "[Compression] remove pruning v1 & refactor directory (#5228)",
        "code": "def get_module_by_name(model, module_name):\n    \n    name_list = module_name.split(\".\")\n    for name in name_list[:-1]:\n        if hasattr(model, name):\n            model = getattr(model, name)\n        else:\n            return None, None\n    if hasattr(model, name_list[-1]):\n        leaf_module = getattr(model, name_list[-1])\n        return model, leaf_module\n    else:\n        return None, None\n\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 107,
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        "token_counts": 82,
        "n_ast_nodes": 131,
        "n_identifiers": 9,
        "d_id": 25005,
        "documentation": {
            "docstring": "\n    Get a module specified by its module name\n    Parameters\n    ----------\n    model : pytorch model\n        the pytorch model from which to get its module\n    module_name : str\n        the name of the required module\n    Returns\n    -------\n    module, module\n        the parent module of the required module, the required module\n    ",
            "n_words": 46,
            "vocab_size": 25,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 167425,
        "commit_id": "734db4f1fde2566a02b3c7ff661a479b0a71633c",
        "repo": "pandas",
        "path": "pandas/io/json/_json.py",
        "file_name": "_json.py",
        "fun_name": "check_keys_split",
        "commit_message": "TYP: Return annotations for io/{formats,json} (#47516)\n\n* TYP: Return annotations for io/{formats,json}\r\n\r\n* flake8\r\n\r\n* explicitly check whether width is None",
        "code": "def check_keys_split(self, decoded) -> None:\n        \n        bad_keys = set(decoded.keys()).difference(set(self._split_keys))\n        if bad_keys:\n            bad_keys_joined = \", \".join(bad_keys)\n            raise ValueError(f\"JSON data had unexpected key(s): {bad_keys_joined}\")\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
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        "token_counts": 47,
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        "n_identifiers": 11,
        "d_id": 40008,
        "documentation": {
            "docstring": "\n        Checks that dict has only the appropriate keys for orient='split'.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 217460,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ftplib.py",
        "file_name": "ftplib.py",
        "fun_name": "connect",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def connect(self, host='', port=0, timeout=-999, source_address=None):\n        \n        if host != '':\n            self.host = host\n        if port > 0:\n            self.port = port\n        if timeout != -999:\n            self.timeout = timeout\n        if self.timeout is not None and not self.timeout:\n            raise ValueError('Non-blocking socket (timeout=0) is not supported')\n        if source_address is not None:\n            self.source_address = source_address\n        sys.audit(\"ftplib.connect\", self, self.host, self.port)\n        self.sock = socket.create_connection((self.host, self.port), self.timeout,\n                                             source_address=self.source_address)\n        self.af = self.sock.family\n        self.file = self.sock.makefile('r', encoding=self.encoding)\n        self.welcome = self.getresp()\n        return self.welcome\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 255,
        "n_words": 72,
        "vocab_size": 49,
        "complexity": 7,
        "nloc": 18,
        "token_counts": 167,
        "n_ast_nodes": 264,
        "n_identifiers": 19,
        "d_id": 54803,
        "documentation": {
            "docstring": "Connect to host.  Arguments are:\n         - host: hostname to connect to (string, default previous host)\n         - port: port to connect to (integer, default previous port)\n         - timeout: the timeout to set against the ftp socket(s)\n         - source_address: a 2-tuple (host, port) for the socket to bind\n           to as its source address before connecting.\n        ",
            "n_words": 53,
            "vocab_size": 37,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 79676,
        "commit_id": "c8689acb3724dc12fb09a0bfc14d7e4755a1ea0f",
        "repo": "wagtail",
        "path": "wagtail/models/reference_index.py",
        "file_name": "reference_index.py",
        "fun_name": "model_is_indexable",
        "commit_message": "Check field for .extract_references method instead of field type\n\nCo-authored-by: Matt Westcott <matthew@torchbox.com>",
        "code": "def model_is_indexable(cls, model, allow_child_models=False):\n        \n        if getattr(model, \"wagtail_reference_index_ignore\", False):\n            return False\n\n        # Don't check any models that have a parental key, references from these will be collected from the parent\n        if not allow_child_models and any(\n            [isinstance(field, ParentalKey) for field in model._meta.get_fields()]\n        ):\n            return False\n\n        for field in model._meta.get_fields():\n            if field.is_relation and field.many_to_one:\n                if getattr(field, \"wagtail_reference_index_ignore\", False):\n                    continue\n\n                if getattr(\n                    field.related_model, \"wagtail_reference_index_ignore\", False\n                ):\n                    continue\n\n                if isinstance(field, (ParentalKey, GenericRel)):\n                    continue\n\n                return True\n\n            if hasattr(field, \"extract_references\"):\n                return True\n\n        if issubclass(model, ClusterableModel):\n            for child_relation in get_all_child_relations(model):\n                if cls.model_is_indexable(\n                    child_relation.related_model,\n                    allow_child_models=True,\n                ):\n                    return True\n\n        return False\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 466,
        "n_words": 91,
        "vocab_size": 59,
        "complexity": 15,
        "nloc": 28,
        "token_counts": 156,
        "n_ast_nodes": 244,
        "n_identifiers": 20,
        "d_id": 16955,
        "documentation": {
            "docstring": "\n        Returns True if the given model may have outbound references that we would be interested in recording in the index.\n\n\n        Args:\n            model (type): a Django model class\n            allow_child_models (boolean): Child models are not indexable on their own. If you are looking at\n                                          a child model from the perspective of indexing it through its parent,\n                                          set this to True to disable checking for this. Default False.\n        ",
            "n_words": 65,
            "vocab_size": 55,
            "n_whitespaces": 191,
            "language": "en"
        }
    },
    {
        "id": 135586,
        "commit_id": "9fab504fe776f96fecf85e12ea006264cbe92f4a",
        "repo": "ray",
        "path": "python/ray/data/tests/test_dataset_tfrecords.py",
        "file_name": "test_dataset_tfrecords.py",
        "fun_name": "test_write_tfrecords",
        "commit_message": "[Datasets] Add writer for TFRecords. (#29448)\n\nThis PR enables users to write TFRecords from datasets.\r\n\r\nIn particular, the master branch already includes an API for reading TFRecords from datasets. Users have requested the ability to write these datasets back to TFRecords.",
        "code": "def test_write_tfrecords(ray_start_regular_shared, tmp_path):\n    \n\n    import tensorflow as tf\n\n    # The dataset we will write to a .tfrecords file.\n    ds = ray.data.from_items(\n        [\n            # Row one.\n            {\n                \"int_item\": 1,\n                \"int_list\": [2, 2, 3],\n                \"float_item\": 1.0,\n                \"float_list\": [2.0, 3.0, 4.0],\n                \"bytes_item\": b\"abc\",\n                \"bytes_list\": [b\"abc\", b\"1234\"],\n            },\n            # Row two.\n            {\n                \"int_item\": 2,\n                \"int_list\": [3, 3, 4],\n                \"float_item\": 2.0,\n                \"float_list\": [2.0, 2.0, 3.0],\n                \"bytes_item\": b\"def\",\n                \"bytes_list\": [b\"def\", b\"1234\"],\n            },\n        ]\n    )\n\n    # The corresponding tf.train.Example that we would expect to read\n    # from this dataset.\n\n    expected_records = [\n        # Record one (corresponding to row one).\n        tf.train.Example(\n            features=tf.train.Features(\n                feature={\n                    \"int_item\": tf.train.Feature(\n                        int64_list=tf.train.Int64List(value=[1])\n                    ),\n                    \"int_list\": tf.train.Feature(\n                        int64_list=tf.train.Int64List(value=[2, 2, 3])\n                    ),\n                    \"float_item\": tf.train.Feature(\n                        float_list=tf.train.FloatList(value=[1.0])\n                    ),\n                    \"float_list\": tf.train.Feature(\n                        float_list=tf.train.FloatList(value=[2.0, 3.0, 4.0])\n                    ),\n                    \"bytes_item\": tf.train.Feature(\n                        bytes_list=tf.train.BytesList(value=[b\"abc\"])\n                    ),\n                    \"bytes_list\": tf.train.Feature(\n                        bytes_list=tf.train.BytesList(value=[b\"abc\", b\"1234\"])\n                    ),\n                }\n            )\n        ),\n        # Record two (corresponding to row two).\n        tf.train.Example(\n            features=tf.train.Features(\n                feature={\n                    \"int_item\": tf.train.Feature(\n                        int64_list=tf.train.Int64List(value=[2])\n                    ),\n                    \"int_list\": tf.train.Feature(\n                        int64_list=tf.train.Int64List(value=[3, 3, 4])\n                    ),\n                    \"float_item\": tf.train.Feature(\n                        float_list=tf.train.FloatList(value=[2.0])\n                    ),\n                    \"float_list\": tf.train.Feature(\n                        float_list=tf.train.FloatList(value=[2.0, 2.0, 3.0])\n                    ),\n                    \"bytes_item\": tf.train.Feature(\n                        bytes_list=tf.train.BytesList(value=[b\"def\"])\n                    ),\n                    \"bytes_list\": tf.train.Feature(\n                        bytes_list=tf.train.BytesList(value=[b\"def\", b\"1234\"])\n                    ),\n                }\n            )\n        ),\n    ]\n\n    # Perform the test.\n    # Write the dataset to a .tfrecords file.\n    ds.write_tfrecords(tmp_path)\n\n    # Read the Examples back out from the .tfrecords file.\n    # This follows the offical TFRecords tutorial:\n    # https://www.tensorflow.org/tutorials/load_data/tfrecord#reading_a_tfrecord_file_2\n\n    filenames = sorted(os.listdir(tmp_path))\n    filepaths = [os.path.join(tmp_path, filename) for filename in filenames]\n    raw_dataset = tf.data.TFRecordDataset(filepaths)\n\n    tfrecords = []\n    for raw_record in raw_dataset:\n        example = tf.train.Example()\n        example.ParseFromString(raw_record.numpy())\n        tfrecords.append(example)\n\n    assert tfrecords == expected_records\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 1453,
        "n_words": 231,
        "vocab_size": 127,
        "complexity": 3,
        "nloc": 82,
        "token_counts": 590,
        "n_ast_nodes": 885,
        "n_identifiers": 40,
        "d_id": 30665,
        "documentation": {
            "docstring": "Test that write_tfrecords writes TFRecords correctly.\n\n    Test this by writing a Dataset to a TFRecord (function under test),\n    reading it back out into a tf.train.Example,\n    and checking that the result is analogous to the original Dataset.\n    ",
            "n_words": 36,
            "vocab_size": 30,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 60940,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/operations/install/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "fix_script",
        "commit_message": "upd; format",
        "code": "def fix_script(path):\n    # type: (str) -> bool\n    \n    # XXX RECORD hashes will need to be updated\n    assert os.path.isfile(path)\n\n    with open(path, 'rb') as script:\n        firstline = script.readline()\n        if not firstline.startswith(b'#!python'):\n            return False\n        exename = sys.executable.encode(sys.getfilesystemencoding())\n        firstline = b'#!' + exename + os.linesep.encode(\"ascii\")\n        rest = script.read()\n    with open(path, 'wb') as script:\n        script.write(firstline)\n        script.write(rest)\n    return True\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 12,
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        "nloc": 13,
        "token_counts": 104,
        "n_ast_nodes": 185,
        "n_identifiers": 18,
        "d_id": 12353,
        "documentation": {
            "docstring": "Replace #!python with #!/path/to/python\n    Return True if file was changed.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 54156,
        "commit_id": "40309ccbc3b8c8474ae15293fbbecb28eded6ef5",
        "repo": "prefect",
        "path": "src/prefect/orion/database/orm_models.py",
        "file_name": "orm_models.py",
        "fun_name": "decrypt_data",
        "commit_message": "Update Block API",
        "code": "async def decrypt_data(self, session):\n        \n        return await decrypt_fernet(session, self.data)\n\n\n@declarative_mixin",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "@declarative_mixin",
        "n_ast_errors": 1,
        "ast_levels": 9,
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        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
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        "n_ast_nodes": 35,
        "n_identifiers": 6,
        "d_id": 10992,
        "documentation": {
            "docstring": "\n        Retrieve decrypted data from the ORM model.\n\n        Note: will only succeed if the caller has sufficient permission.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 171745,
        "commit_id": "36dcf519c67a8098572447f7d5a896740fc9c464",
        "repo": "pandas",
        "path": "pandas/core/frame.py",
        "file_name": "frame.py",
        "fun_name": "assign",
        "commit_message": "ENH/TST: expand copy-on-write to assign() method (#50010)",
        "code": "def assign(self, **kwargs) -> DataFrame:\n        r\n        data = self.copy(deep=None)\n\n        for k, v in kwargs.items():\n            data[k] = com.apply_if_callable(v, data)\n        return data\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 66,
        "token_counts": 48,
        "n_ast_nodes": 75,
        "n_identifiers": 12,
        "d_id": 40716,
        "documentation": {
            "docstring": "\n        Assign new columns to a DataFrame.\n\n        Returns a new object with all original columns in addition to new ones.\n        Existing columns that are re-assigned will be overwritten.\n\n        Parameters\n        ----------\n        **kwargs : dict of {str: callable or Series}\n            The column names are keywords. If the values are\n            callable, they are computed on the DataFrame and\n            assigned to the new columns. The callable must not\n            change input DataFrame (though pandas doesn't check it).\n            If the values are not callable, (e.g. a Series, scalar, or array),\n            they are simply assigned.\n\n        Returns\n        -------\n        DataFrame\n            A new DataFrame with the new columns in addition to\n            all the existing columns.\n\n        Notes\n        -----\n        Assigning multiple columns within the same ``assign`` is possible.\n        Later items in '\\*\\*kwargs' may refer to newly created or modified\n        columns in 'df'; items are computed and assigned into 'df' in order.\n\n        Examples\n        --------\n        >>> df = pd.DataFrame({'temp_c': [17.0, 25.0]},\n        ...                   index=['Portland', 'Berkeley'])\n        >>> df\n                  temp_c\n        Portland    17.0\n        Berkeley    25.0\n\n        Where the value is a callable, evaluated on `df`:\n\n        >>> df.assign(temp_f=lambda x: x.temp_c * 9 / 5 + 32)\n                  temp_c  temp_f\n        Portland    17.0    62.6\n        Berkeley    25.0    77.0\n\n        Alternatively, the same behavior can be achieved by directly\n        referencing an existing Series or sequence:\n\n        >>> df.assign(temp_f=df['temp_c'] * 9 / 5 + 32)\n                  temp_c  temp_f\n        Portland    17.0    62.6\n        Berkeley    25.0    77.0\n\n        You can create multiple columns within the same assign where one\n        of the columns depends on another one defined within the same assign:\n\n        >>> df.assign(temp_f=lambda x: x['temp_c'] * 9 / 5 + 32,\n        ...           temp_k=lambda x: (x['temp_f'] +  459.67) * 5 / 9)\n                  temp_c  temp_f  temp_k\n        Portland    17.0    62.6  290.15\n        Berkeley    25.0    77.0  298.15\n        ",
            "n_words": 268,
            "vocab_size": 146,
            "n_whitespaces": 761,
            "language": "en"
        }
    },
    {
        "id": 209123,
        "commit_id": "20ac1d00389d0735e6d8cd1347f0a53f478144ba",
        "repo": "scapy",
        "path": "scapy/layers/inet.py",
        "file_name": "inet.py",
        "fun_name": "in4_chksum",
        "commit_message": "Support TCP-MD5 and TCP-AO (#3358)\n\nSupport TCP-MD5 and TCP-AO",
        "code": "def in4_chksum(proto, u, p):\n    # type: (int, IP, bytes) -> int\n    \n    if not isinstance(u, IP):\n        warning(\"No IP underlayer to compute checksum. Leaving null.\")\n        return 0\n    psdhdr = in4_pseudoheader(proto, u, len(p))\n    return checksum(psdhdr + p)\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 34,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 74,
        "n_identifiers": 11,
        "d_id": 52613,
        "documentation": {
            "docstring": "IPv4 Pseudo Header checksum as defined in RFC793\n\n    :param nh: value of upper layer protocol\n    :param u: upper layer instance\n    :param p: the payload of the upper layer provided as a string\n    ",
            "n_words": 32,
            "vocab_size": 23,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 69776,
        "commit_id": "408c89df030998fe36df135570c9edd90a522996",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/bank_reconciliation_tool/bank_reconciliation_tool.py",
        "file_name": "bank_reconciliation_tool.py",
        "fun_name": "get_pe_matching_query",
        "commit_message": "Feat:Filter on Payment Entries and Journal Entries\n\nApplying filters on Payement entries and Journal Entries as per reference  date and posting date",
        "code": "def get_pe_matching_query(amount_condition, account_from_to, transaction):\n\t# get matching payment entries query\n\tfrom_date = frappe.db.get_single_value(\"Bank Reconciliation Tool\", \"bank_statement_from_date\")\n\tto_date = frappe.db.get_single_value(\"Bank Reconciliation Tool\", \"bank_statement_to_date\")\n\tfrom_reference_date = frappe.db.get_single_value(\n\t\t\"Bank Reconciliation Tool\", \"from_reference_date\"\n\t)\n\tto_reference_date = frappe.db.get_single_value(\"Bank Reconciliation Tool\", \"to_reference_date\")\n\tfiltered_by_reference_date = frappe.db.get_single_value(\n\t\t\"Bank Reconciliation Tool\", \"filtered_by_reference_date\"\n\t)\n\tif transaction.deposit > 0:\n\t\tcurrency_field = \"paid_to_account_currency as currency\"\n\telse:\n\t\tcurrency_field = \"paid_from_account_currency as currency\"\n\tcond_filtered_from_ref_date = \"\"\n\tcond_filtered_to_ref_date = \"\"\n\tcond_filtered_from_posting_date = \"\"\n\tcond_filtered_to_posting_date = \"\"\n\tfrom_ref_date  =\"\"\n\tto_ref_date =\"\"\n\tfrom_post_date = \"\"\n\tto_post_date = \"\"\n\tif(filtered_by_reference_date):\n\t\tcond_filtered_from_ref_date = \" AND reference_date >=\"\n\t\tcond_filtered_to_ref_date = \" AND reference_date <=\"\n\t\tfrom_ref_date = from_reference_date\n\t\tto_ref_date = to_reference_date\n\telif(not filtered_by_reference_date):\n\t\tcond_filtered_from_posting_date = \" AND posting_date >=\"\n\t\tcond_filtered_to_posting_date = \" AND posting_date <=\"\n\t\tfrom_post_date = from_date\n\t\tto_post_date = to_date\n\t\t\n\tpe_data=  f\t\n\treturn pe_data\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 124,
        "vocab_size": 60,
        "complexity": 4,
        "nloc": 61,
        "token_counts": 149,
        "n_ast_nodes": 336,
        "n_identifiers": 24,
        "d_id": 15095,
        "documentation": {
            "docstring": "\n\t\tSELECT\n\t\t\t(CASE WHEN reference_no=%(reference_no)s THEN 1 ELSE 0 END\n\t\t\t+ CASE WHEN (party_type = %(party_type)s AND party = %(party)s ) THEN 1 ELSE 0  END\n\t\t\t+ 1 ) AS rank,\n\t\t\t'Payment Entry' as doctype,\n\t\t\tname,\n\t\t\tpaid_amount,\n\t\t\treference_no,\n\t\t\treference_date,\n\t\t\tparty,\n\t\t\tparty_type,\n\t\t\tposting_date,\n\t\t\t{currency_field}\n\t\tFROM\n\t\t\t`tabPayment Entry`\n\t\tWHERE\n\t\t\tpaid_amount {amount_condition} %(amount)s\n\t\t\tAND docstatus = 1\n\t\t\tAND payment_type IN (%(payment_type)s, 'Internal Transfer')\n\t\t\tAND ifnull(clearance_date, '') = \"\"\n\t\t\tAND {account_from_to} = %(bank_account)s\n\t\t\tAND reference_no = '{transaction.reference_number}'\n\t\t\t{cond_filtered_from_ref_date} \"{from_ref_date}\"\n\t\t\t{cond_filtered_to_ref_date} \"{to_ref_date}\"\n\t\t\t{cond_filtered_from_posting_date} \"{from_post_date}\"\n\t\t\t{cond_filtered_to_posting_date} \"{to_post_date}\"\n\t\t",
            "n_words": 80,
            "vocab_size": 60,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 104200,
        "commit_id": "21bfd0d3f5ff3fbfd691600e2c7071a167816cdf",
        "repo": "datasets",
        "path": "templates/new_metric_script.py",
        "file_name": "new_metric_script.py",
        "fun_name": "_download_and_prepare",
        "commit_message": "Run pyupgrade for Python 3.6+ (#3560)\n\n* Run pyupgrade for Python 3.6+\r\n\r\n* Fix lint issues\r\n\r\n* Revert changes for the datasets code\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>",
        "code": "def _download_and_prepare(self, dl_manager):\n        \n        # TODO: Download external resources if needed\n        bad_words_path = dl_manager.download_and_extract(BAD_WORDS_URL)\n        self.bad_words = {w.strip() for w in open(bad_words_path, encoding=\"utf-8\")}\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 49,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 38,
        "n_ast_nodes": 64,
        "n_identifiers": 11,
        "d_id": 21781,
        "documentation": {
            "docstring": "Optional: download external resources useful to compute the scores",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 218142,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "_cache_bytecode",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _cache_bytecode(self, source_path, cache_path, data):\n        \n        # For backwards compatibility, we delegate to set_data()\n        return self.set_data(cache_path, data)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 37,
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        "n_identifiers": 6,
        "d_id": 55160,
        "documentation": {
            "docstring": "Optional method which writes data (bytes) to a file path (a str).\n\n        Implementing this method allows for the writing of bytecode files.\n\n        The source path is needed in order to correctly transfer permissions\n        ",
            "n_words": 33,
            "vocab_size": 30,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 189648,
        "commit_id": "e040bcacd38378386749db18aeba575b93f4ebca",
        "repo": "manim",
        "path": "manim/mobject/geometry/arc.py",
        "file_name": "arc.py",
        "fun_name": "add_tip",
        "commit_message": "Improved structure of the :mod:`.mobject` module (#2476)\n\n* group graphing and update its references\r\n\r\n* group text and update its references\r\n\r\n* group opengl and update its references\r\n\r\n* group three_d and update its references\r\n\r\n* group geometry and update (most) references\r\n\r\n* move some chaning.py + updater files  into animation\r\n\r\n* refactor arc.py\r\n\r\n* refactor line.py\r\n\r\n* refactor polygram.py\r\n\r\n* refactor tips.py\r\n\r\n* black + isort\r\n\r\n* import new files in __init__.py\r\n\r\n* refactor places where geometry was used\r\n\r\n* black + isort again\r\n\r\n* remove unused imports\r\n\r\n* update reference.rst\r\n\r\n* add descriptions to files\r\n\r\n* fix circular imports\r\n\r\n* forgot ArrowTip\r\n\r\n* fix tests\r\n\r\n* fix doctests\r\n\r\n* satisfy mypy?\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix ALL merge conflicts\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* one VMobject import slipped through\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* re-add imports to `manim/opengl/__init__.py`\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix reference manual\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* ignore unknown directive type\r\n\r\n* fix arrow tip imports in docstrings\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>",
        "code": "def add_tip(self, tip=None, tip_shape=None, tip_length=None, at_start=False):\n        \n        if tip is None:\n            tip = self.create_tip(tip_shape, tip_length, at_start)\n        else:\n            self.position_tip(tip, at_start)\n        self.reset_endpoints_based_on_tip(tip, at_start)\n        self.asign_tip_attr(tip, at_start)\n        self.add(tip)\n        return self\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 96,
        "n_words": 25,
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        "complexity": 2,
        "nloc": 9,
        "token_counts": 73,
        "n_ast_nodes": 111,
        "n_identifiers": 11,
        "d_id": 46154,
        "documentation": {
            "docstring": "\n        Adds a tip to the TipableVMobject instance, recognising\n        that the endpoints might need to be switched if it's\n        a 'starting tip' or not.\n        ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 277267,
        "commit_id": "fa6d9107a498f7c2403ff28c7b389a1a0c5cc083",
        "repo": "keras",
        "path": "keras/engine/base_layer_utils.py",
        "file_name": "base_layer_utils.py",
        "fun_name": "check_graph_consistency",
        "commit_message": "reduct too long lines",
        "code": "def check_graph_consistency(tensor=None, method=\"add_loss\", force_raise=False):\n    \n    if force_raise or (\n        tf1.executing_eagerly_outside_functions()\n        and hasattr(tensor, \"graph\")\n        and tensor.graph.is_control_flow_graph\n    ):\n        if method == \"activity_regularizer\":\n            bad_example = ",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "bad_example = \"\"\"",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 70,
        "n_words": 21,
        "vocab_size": 19,
        "complexity": 8,
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        "token_counts": 130,
        "n_ast_nodes": 96,
        "n_identifiers": 14,
        "d_id": 81922,
        "documentation": {
            "docstring": "Checks that tensors passed to `add_*` method match the Keras graph.\n\n    When one of the `add_*` method is called inside a V2 conditional branch, the\n    underlying tensor gets created in a FuncGraph managed by control_flow_v2.\n    We need to raise clear error messages in such cases.\n\n    Args:\n      tensor: Tensor to check, or `False` if it is known that an error\n        should be raised.\n      method: Caller method, one of {'add_metric', 'add_loss', 'add_update'}.\n      force_raise: If an error should be raised regardless of `tensor`.\n\n    Raises:\n      RuntimeError: In case of an out-of-graph tensor.\n    \n      class TestModel(tf.keras.Model):\n",
            "n_words": 90,
            "vocab_size": 70,
            "n_whitespaces": 140,
            "language": "en"
        }
    },
    {
        "id": 135341,
        "commit_id": "136c8d5e4d2fab6106f007f4ce5d5c321922ae17",
        "repo": "ray",
        "path": "rllib/algorithms/bandit/bandit_tf_model.py",
        "file_name": "bandit_tf_model.py",
        "fun_name": "_make_dist",
        "commit_message": "[RLlib] Tests for bandit convergence and solving cov matrix problem (#29666)\n\nSigned-off-by: Avnish <avnishnarayan@gmail.com>\r\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>\r\nCo-authored-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def _make_dist(self):\n        \n        dist = tfp.distributions.MultivariateNormalTriL(\n            self.theta, scale_tril=tf.linalg.cholesky(self.covariance)\n        )\n        return dist\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 49,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 33,
        "n_ast_nodes": 54,
        "n_identifiers": 12,
        "d_id": 30601,
        "documentation": {
            "docstring": "Create a multivariate normal distribution with the current parameters",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 119998,
        "commit_id": "df1ceaeeb11efc7c5af1ad2dd102857128c23b26",
        "repo": "jax",
        "path": "jax/_src/scipy/sparse/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "_kth_arnoldi_iteration",
        "commit_message": "Deprecate jax.tree_util.tree_multimap",
        "code": "def _kth_arnoldi_iteration(k, A, M, V, H):\n  \n  eps = jnp.finfo(jnp.result_type(*tree_leaves(V))).eps\n\n  v = tree_map(lambda x: x[..., k], V)  # Gets V[:, k]\n  v = M(A(v))\n  _, v_norm_0 = _safe_normalize(v)\n  v, h = _iterative_classical_gram_schmidt(V, v, v_norm_0, max_iterations=2)\n\n  tol = eps * v_norm_0\n  unit_v, v_norm_1 = _safe_normalize(v, thresh=tol)\n  V = tree_map(lambda X, y: X.at[..., k + 1].set(y), V, unit_v)\n\n  h = h.at[k + 1].set(v_norm_1)\n  H = H.at[k, :].set(h)\n  breakdown = v_norm_1 == 0.\n  return V, H, breakdown\n\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 87,
        "n_words": 73,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 170,
        "n_ast_nodes": 255,
        "n_identifiers": 29,
        "d_id": 26741,
        "documentation": {
            "docstring": "\n  Performs a single (the k'th) step of the Arnoldi process. Thus,\n  adds a new orthonormalized Krylov vector A(M(V[:, k])) to V[:, k+1],\n  and that vectors overlaps with the existing Krylov vectors to\n  H[k, :]. The tolerance 'tol' sets the threshold at which an invariant\n  subspace is declared to have been found, in which case in which case the new\n  vector is taken to be the zero vector.\n  ",
            "n_words": 67,
            "vocab_size": 50,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 189455,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/svg/code_mobject.py",
        "file_name": "code_mobject.py",
        "fun_name": "correct_non_span",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _correct_non_span(self, line_str):\n        \n        words = line_str.split(\"</span>\")\n        line_str = \"\"\n        for i in range(0, words.__len__()):\n            if i != words.__len__() - 1:\n                j = words[i].find(\"<span\")\n            else:\n                j = words[i].__len__()\n            temp = \"\"\n            starti = -1\n            for k in range(0, j):\n                if words[i][k] == \"\\t\" and starti == -1:\n                    continue\n                else:\n                    if starti == -1:\n                        starti = k\n                    temp = temp + words[i][k]\n            if temp != \"\":\n                if i != words.__len__() - 1:\n                    temp = (\n                        '<span style=\"color:'\n                        + self.default_color\n                        + '\">'\n                        + words[i][starti:j]\n                        + \"</span>\"\n                    )\n                else:\n                    temp = (\n                        '<span style=\"color:'\n                        + self.default_color\n                        + '\">'\n                        + words[i][starti:j]\n                    )\n                temp = temp + words[i][j:]\n                words[i] = temp\n            if words[i] != \"\":\n                line_str = line_str + words[i] + \"</span>\"\n        return line_str\n\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 728,
        "n_words": 118,
        "vocab_size": 46,
        "complexity": 10,
        "nloc": 38,
        "token_counts": 223,
        "n_ast_nodes": 375,
        "n_identifiers": 14,
        "d_id": 46063,
        "documentation": {
            "docstring": "Function put text color to those strings that don't have one according to background_color of displayed code.\n\n        Parameters\n        ---------\n        line_str : :class:`str`\n            Takes a html element's string to put color to it according to background_color of displayed code.\n\n        Returns\n        -------\n        :class:`str`\n            The generated html element's string with having color attributes.\n        ",
            "n_words": 50,
            "vocab_size": 34,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 49784,
        "commit_id": "f4d6e64cdc132ae868699a0ba442f4ab1d304a14",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/gaussian_diffusion.py",
        "file_name": "gaussian_diffusion.py",
        "fun_name": "get_named_beta_schedule",
        "commit_message": "add disco_diffusion_cnclip_vitb16 module",
        "code": "def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):\n    \n    if schedule_name == \"linear\":\n        # Linear schedule from Ho et al, extended to work for any number of\n        # diffusion steps.\n        scale = 1000 / num_diffusion_timesteps\n        beta_start = scale * 0.0001\n        beta_end = scale * 0.02\n        return np.linspace(beta_start, beta_end, num_diffusion_timesteps, dtype=np.float64)\n    elif schedule_name == \"cosine\":\n        return betas_for_alpha_bar(\n            num_diffusion_timesteps,\n            lambda t: math.cos((t + 0.008) / 1.008 * math.pi / 2)**2,\n        )\n    else:\n        raise NotImplementedError(f\"unknown beta schedule: {schedule_name}\")\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 166,
        "n_words": 69,
        "vocab_size": 56,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 96,
        "n_ast_nodes": 147,
        "n_identifiers": 16,
        "d_id": 9908,
        "documentation": {
            "docstring": "\n    Get a pre-defined beta schedule for the given name.\n\n    The beta schedule library consists of beta schedules which remain similar\n    in the limit of num_diffusion_timesteps.\n    Beta schedules may be added, but should not be removed or changed once\n    they are committed to maintain backwards compatibility.\n    ",
            "n_words": 45,
            "vocab_size": 38,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 278117,
        "commit_id": "6fafb567af4e4d9f42974d0b6c55b18bc03e17eb",
        "repo": "keras",
        "path": "keras/feature_column/sequence_feature_column.py",
        "file_name": "sequence_feature_column.py",
        "fun_name": "call",
        "commit_message": "resolve line-too-long in feature_column",
        "code": "def call(self, features, training=None):\n        \n        if not isinstance(features, dict):\n            raise ValueError(\n                \"We expected a dictionary here. Instead we got: \", features\n            )\n        if training is None:\n            training = backend.learning_phase()\n        transformation_cache = (\n            tf.__internal__.feature_column.FeatureTransformationCache(features)\n        )\n        output_tensors = []\n        sequence_lengths = []\n\n        for column in self._feature_columns:\n            with backend.name_scope(column.name):\n                try:\n                    (\n                        dense_tensor,\n                        sequence_length,\n                    ) = column.get_sequence_dense_tensor(\n                        transformation_cache,\n                        self._state_manager,\n                        training=training,\n                    )\n                except TypeError:\n                    (\n                        dense_tensor,\n                        sequence_length,\n                    ) = column.get_sequence_dense_tensor(\n                        transformation_cache, self._state_manager\n                    )\n                # Flattens the final dimension to produce a 3D Tensor.\n                output_tensors.append(\n                    self._process_dense_tensor(column, dense_tensor)\n                )\n                sequence_lengths.append(sequence_length)\n\n        # Check and process sequence lengths.\n        kfc._verify_static_batch_size_equality(\n            sequence_lengths, self._feature_columns\n        )\n        sequence_length = _assert_all_equal_and_return(sequence_lengths)\n\n        return self._verify_and_concat_tensors(output_tensors), sequence_length\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 677,
        "n_words": 98,
        "vocab_size": 73,
        "complexity": 5,
        "nloc": 39,
        "token_counts": 167,
        "n_ast_nodes": 264,
        "n_identifiers": 31,
        "d_id": 82375,
        "documentation": {
            "docstring": "Returns sequence input corresponding to the `feature_columns`.\n\n        Args:\n          features: A dict mapping keys to tensors.\n          training: Python boolean or None, indicating whether to the layer is\n            being run in training mode. This argument is passed to the call\n            method of any `FeatureColumn` that takes a `training` argument. For\n            example, if a `FeatureColumn` performed dropout, the column could\n            expose a `training` argument to control whether the dropout should\n            be applied. If `None`, defaults to\n            `tf.keras.backend.learning_phase()`.\n\n\n        Returns:\n          An `(input_layer, sequence_length)` tuple where:\n          - input_layer: A float `Tensor` of shape `[batch_size, T, D]`.\n              `T` is the maximum sequence length for this batch, which could\n              differ from batch to batch. `D` is the sum of `num_elements` for\n              all `feature_columns`.\n          - sequence_length: An int `Tensor` of shape `[batch_size]`. The\n            sequence length for each example.\n\n        Raises:\n          ValueError: If features are not a dictionary.\n        ",
            "n_words": 137,
            "vocab_size": 99,
            "n_whitespaces": 335,
            "language": "en"
        }
    },
    {
        "id": 21965,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/chardet/utf1632prober.py",
        "file_name": "utf1632prober.py",
        "fun_name": "validate_utf16_characters",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def validate_utf16_characters(self, pair):\n        \n        if not self.first_half_surrogate_pair_detected_16be:\n            if 0xD8 <= pair[0] <= 0xDB:\n                self.first_half_surrogate_pair_detected_16be = True\n            elif 0xDC <= pair[0] <= 0xDF:\n                self.invalid_utf16be = True\n        else:\n            if 0xDC <= pair[0] <= 0xDF:\n                self.first_half_surrogate_pair_detected_16be = False\n            else:\n                self.invalid_utf16be = True\n\n        if not self.first_half_surrogate_pair_detected_16le:\n            if 0xD8 <= pair[1] <= 0xDB:\n                self.first_half_surrogate_pair_detected_16le = True\n            elif 0xDC <= pair[1] <= 0xDF:\n                self.invalid_utf16le = True\n        else:\n            if 0xDC <= pair[1] <= 0xDF:\n                self.first_half_surrogate_pair_detected_16le = False\n            else:\n                self.invalid_utf16le = True\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 316,
        "n_words": 73,
        "vocab_size": 23,
        "complexity": 9,
        "nloc": 21,
        "token_counts": 128,
        "n_ast_nodes": 199,
        "n_identifiers": 7,
        "d_id": 4096,
        "documentation": {
            "docstring": "\n        Validate if the pair of bytes is  valid UTF-16.\n\n        UTF-16 is valid in the range 0x0000 - 0xFFFF excluding 0xD800 - 0xFFFF\n        with an exception for surrogate pairs, which must be in the range\n        0xD800-0xDBFF followed by 0xDC00-0xDFFF\n\n        https://en.wikipedia.org/wiki/UTF-16\n        ",
            "n_words": 39,
            "vocab_size": 31,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 67568,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/startup/leaderboard.py",
        "file_name": "leaderboard.py",
        "fun_name": "get_all_items",
        "commit_message": "style: format code with black",
        "code": "def get_all_items(date_range, company, field, limit=None):\n\tif field in (\"available_stock_qty\", \"available_stock_value\"):\n\t\tselect_field = \"sum(actual_qty)\" if field == \"available_stock_qty\" else \"sum(stock_value)\"\n\t\treturn frappe.db.get_all(\n\t\t\t\"Bin\",\n\t\t\tfields=[\"item_code as name\", \"{0} as value\".format(select_field)],\n\t\t\tgroup_by=\"item_code\",\n\t\t\torder_by=\"value desc\",\n\t\t\tlimit=limit,\n\t\t)\n\telse:\n\t\tif field == \"total_sales_amount\":\n\t\t\tselect_field = \"sum(order_item.base_net_amount)\"\n\t\t\tselect_doctype = \"Sales Order\"\n\t\telif field == \"total_purchase_amount\":\n\t\t\tselect_field = \"sum(order_item.base_net_amount)\"\n\t\t\tselect_doctype = \"Purchase Order\"\n\t\telif field == \"total_qty_sold\":\n\t\t\tselect_field = \"sum(order_item.stock_qty)\"\n\t\t\tselect_doctype = \"Sales Order\"\n\t\telif field == \"total_qty_purchased\":\n\t\t\tselect_field = \"sum(order_item.stock_qty)\"\n\t\t\tselect_doctype = \"Purchase Order\"\n\n\t\tdate_condition = get_date_condition(date_range, \"sales_order.transaction_date\")\n\n\t\treturn frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tselect_field, select_doctype, date_condition\n\t\t\t),\n\t\t\t(company, cint(limit)),\n\t\t\tas_dict=1,\n\t\t)  # nosec\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 65,
        "n_words": 96,
        "vocab_size": 56,
        "complexity": 7,
        "nloc": 40,
        "token_counts": 152,
        "n_ast_nodes": 284,
        "n_identifiers": 20,
        "d_id": 14559,
        "documentation": {
            "docstring": "\n\t\t\tselect order_item.item_code as name, {0} as value\n\t\t\tfrom `tab{1}` sales_order join `tab{1} Item` as order_item\n\t\t\t\ton sales_order.name = order_item.parent\n\t\t\twhere sales_order.docstatus = 1\n\t\t\t\tand sales_order.company = %s {2}\n\t\t\tgroup by order_item.item_code\n\t\t\torder by value desc\n\t\t\tlimit %s\n\t\t",
            "n_words": 37,
            "vocab_size": 29,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 262743,
        "commit_id": "57c520132b4d0ab7bfd5653383ec2602e40088af",
        "repo": "pyinstaller",
        "path": "PyInstaller/depend/bindepend.py",
        "file_name": "bindepend.py",
        "fun_name": "findLibrary",
        "commit_message": "Bindepend: Add Termux-specific libraries search path.\n\nAccording to termux/termux-app#1595, this is all we need to change to faclitate\nusing PyInstaller on Termux.",
        "code": "def findLibrary(name):\n    \n    assert compat.is_unix, \"Current implementation for Unix only (Linux, Solaris, AIX, FreeBSD)\"\n\n    # Look in the LD_LIBRARY_PATH according to platform.\n    if compat.is_aix:\n        lp = compat.getenv('LIBPATH', '')\n    elif compat.is_darwin:\n        lp = compat.getenv('DYLD_LIBRARY_PATH', '')\n    else:\n        lp = compat.getenv('LD_LIBRARY_PATH', '')\n    lib = _which_library(name, filter(None, lp.split(os.pathsep)))\n\n    # Look in /etc/ld.so.cache\n    # Solaris does not have /sbin/ldconfig. Just check if this file exists.\n    if lib is None:\n        utils.load_ldconfig_cache()\n        lib = utils.LDCONFIG_CACHE.get(name)\n        if lib:\n            assert os.path.isfile(lib)\n\n    # Look in the known safe paths.\n    if lib is None:\n        # Architecture independent locations.\n        paths = ['/lib', '/usr/lib']\n        # Architecture dependent locations.\n        if compat.architecture == '32bit':\n            paths.extend(['/lib32', '/usr/lib32'])\n        else:\n            paths.extend(['/lib64', '/usr/lib64'])\n        # Machine dependent locations.\n        if compat.machine == 'intel':\n            if compat.architecture == '32bit':\n                paths.extend(['/usr/lib/i386-linux-gnu'])\n            else:\n                paths.extend(['/usr/lib/x86_64-linux-gnu'])\n\n        # On Debian/Ubuntu /usr/bin/python is linked statically with libpython. Newer Debian/Ubuntu with multiarch\n        # support puts the libpythonX.Y.so in paths like /usr/lib/i386-linux-gnu/.\n        try:\n            # Module available only in Python 2.7+\n            import sysconfig\n\n            # 'multiarchsubdir' works on Debian/Ubuntu only in Python 2.7 and 3.3+.\n            arch_subdir = sysconfig.get_config_var('multiarchsubdir')\n            # Ignore if None is returned.\n            if arch_subdir:\n                arch_subdir = os.path.basename(arch_subdir)\n                paths.append(os.path.join('/usr/lib', arch_subdir))\n            else:\n                logger.debug('Multiarch directory not detected.')\n        except ImportError:\n            logger.debug('Multiarch directory not detected.')\n\n        # Termux (a Ubuntu like subsystem for Android) has an additional libraries directory.\n        if os.path.isdir('/data/data/com.termux/files/usr/lib'):\n            paths.append('/data/data/com.termux/files/usr/lib')\n\n        if compat.is_aix:\n            paths.append('/opt/freeware/lib')\n        elif compat.is_hpux:\n            if compat.architecture == '32bit':\n                paths.append('/usr/local/lib/hpux32')\n            else:\n                paths.append('/usr/local/lib/hpux64')\n        elif compat.is_freebsd or compat.is_openbsd:\n            paths.append('/usr/local/lib')\n        lib = _which_library(name, paths)\n\n    # Give up :(\n    if lib is None:\n        return None\n\n    # Resolve the file name into the soname\n    if compat.is_freebsd or compat.is_aix or compat.is_openbsd:\n        # On FreeBSD objdump does not show SONAME, and on AIX objdump does not exist, so we just return the lib we\n        # have found.\n        return lib\n    else:\n        dir = os.path.dirname(lib)\n        return os.path.join(dir, _get_so_name(lib))\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 840,
        "n_words": 283,
        "vocab_size": 160,
        "complexity": 21,
        "nloc": 54,
        "token_counts": 360,
        "n_ast_nodes": 650,
        "n_identifiers": 40,
        "d_id": 77342,
        "documentation": {
            "docstring": "\n    Look for a library in the system.\n\n    Emulate the algorithm used by dlopen. `name` must include the prefix, e.g., ``libpython2.4.so``.\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 246360,
        "commit_id": "eb609c65d0794dd49efcd924bdc8743fd4253a93",
        "repo": "synapse",
        "path": "tests/storage/test_state.py",
        "file_name": "test_state.py",
        "fun_name": "test_return_expanded",
        "commit_message": "Fix bug in `StateFilter.return_expanded()` and add some tests. (#12016)",
        "code": "def test_return_expanded(self):\n        \n\n        self.assertEqual(StateFilter.all().return_expanded(), StateFilter.all())\n\n        self.assertEqual(StateFilter.none().return_expanded(), StateFilter.none())\n\n        # Concrete-only state filters stay the same\n        # (Case: mixed filter)\n        self.assertEqual(\n            StateFilter.freeze(\n                {\n                    EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"},\n                    \"some.other.state.type\": {\"\"},\n                },\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze(\n                {\n                    EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"},\n                    \"some.other.state.type\": {\"\"},\n                },\n                include_others=False,\n            ),\n        )\n\n        # Concrete-only state filters stay the same\n        # (Case: non-member-only filter)\n        self.assertEqual(\n            StateFilter.freeze(\n                {\"some.other.state.type\": {\"\"}}, include_others=False\n            ).return_expanded(),\n            StateFilter.freeze({\"some.other.state.type\": {\"\"}}, include_others=False),\n        )\n\n        # Concrete-only state filters stay the same\n        # (Case: member-only filter)\n        self.assertEqual(\n            StateFilter.freeze(\n                {\n                    EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"},\n                },\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze(\n                {\n                    EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"},\n                },\n                include_others=False,\n            ),\n        )\n\n        # Wildcard member-only state filters stay the same\n        self.assertEqual(\n            StateFilter.freeze(\n                {EventTypes.Member: None},\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze(\n                {EventTypes.Member: None},\n                include_others=False,\n            ),\n        )\n\n        # If there is a wildcard in the non-member portion of the filter,\n        # it's expanded to include ALL non-member events.\n        # (Case: mixed filter)\n        self.assertEqual(\n            StateFilter.freeze(\n                {\n                    EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"},\n                    \"some.other.state.type\": None,\n                },\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze(\n                {EventTypes.Member: {\"@wombat:test\", \"@alicia:test\"}},\n                include_others=True,\n            ),\n        )\n\n        # If there is a wildcard in the non-member portion of the filter,\n        # it's expanded to include ALL non-member events.\n        # (Case: non-member-only filter)\n        self.assertEqual(\n            StateFilter.freeze(\n                {\n                    \"some.other.state.type\": None,\n                },\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze({EventTypes.Member: set()}, include_others=True),\n        )\n        self.assertEqual(\n            StateFilter.freeze(\n                {\n                    \"some.other.state.type\": None,\n                    \"yet.another.state.type\": {\"wombat\"},\n                },\n                include_others=False,\n            ).return_expanded(),\n            StateFilter.freeze({EventTypes.Member: set()}, include_others=True),\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 1317,
        "n_words": 203,
        "vocab_size": 63,
        "complexity": 1,
        "nloc": 81,
        "token_counts": 410,
        "n_ast_nodes": 668,
        "n_identifiers": 12,
        "d_id": 71177,
        "documentation": {
            "docstring": "\n        Tests the behaviour of the return_expanded() function that expands\n        StateFilters to include more state types (for the sake of cache hit rate).\n        ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 89155,
        "commit_id": "3bfb9420a7d80e395c250718d17419daaf021aa2",
        "repo": "sentry",
        "path": "src/sentry/silo/base.py",
        "file_name": "base.py",
        "fun_name": "exit_single_process_silo_context",
        "commit_message": "chore(hybrid-cloud): several endpoint tests e2e (#41691)\n\nThis a major break through PR that gets several acceptance and api unit\r\ntests passing e2e with hybrid cloud.\r\n\r\nI want to explain what's going on in greater detail and get this merged\r\nnext week, unfortunately I'm traveling for now.\r\n\r\nThis only brings up our hybrid cloud test coverage to 77/4096, but\r\nhere's the thing -- this is a break through, because its much much much\r\neasier now in general to add new endpoints. With these major issues out\r\nof the way, getting endpoint tests is some combination of:\r\n\r\n1. Swapping out `user=user` for `user_id=user.id`, or similar\r\n(`organization=organization` for `organization_id=...`) in situations\r\nwhere a relationship would span a silo boundary, but the id is the only\r\nthing that matters.\r\n2. Fixing serializers. Serializers LOVE to cross silo boundaries, but\r\nfixes don't have to be complicated.\r\n3.  Something else but I'm tired and I can't think straight.\r\n\r\nBut honestly, I think it will be much easier to start banging out way\r\nmore stable=True tests from this.\r\nLet's get this merged next week and figure out how to start smashing\r\nmore boundaries down.",
        "code": "def exit_single_process_silo_context(cls) -> Generator[None, None, None]:\n        \n        old = _single_process_silo_mode_state.mode\n        _single_process_silo_mode_state.mode = None\n        try:\n            yield\n        finally:\n            _single_process_silo_mode_state.mode = old\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 75,
        "n_words": 18,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 35,
        "n_ast_nodes": 59,
        "n_identifiers": 6,
        "d_id": 18506,
        "documentation": {
            "docstring": "\n        Used by silo endpoint decorators and other contexts to signal that a potential inter process interaction\n        is being simulated locally for acceptance tests that validate the behavior of multiple endpoints with\n        process boundaries in play.  Call this inside of any RPC interaction to ensure that such acceptance tests\n        can 'swap' the silo context on the fly.\n        ",
            "n_words": 56,
            "vocab_size": 45,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 206167,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/shortcuts.py",
        "file_name": "shortcuts.py",
        "fun_name": "redirect",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def redirect(to, *args, permanent=False, **kwargs):\n    \n    redirect_class = (\n        HttpResponsePermanentRedirect if permanent else HttpResponseRedirect\n    )\n    return redirect_class(resolve_url(to, *args, **kwargs))\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 37,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 39,
        "n_ast_nodes": 60,
        "n_identifiers": 9,
        "d_id": 51392,
        "documentation": {
            "docstring": "\n    Return an HttpResponseRedirect to the appropriate URL for the arguments\n    passed.\n\n    The arguments could be:\n\n        * A model: the model's `get_absolute_url()` function will be called.\n\n        * A view name, possibly with arguments: `urls.reverse()` will be used\n          to reverse-resolve the name.\n\n        * A URL, which will be used as-is for the redirect location.\n\n    Issues a temporary redirect by default; pass permanent=True to issue a\n    permanent redirect.\n    ",
            "n_words": 65,
            "vocab_size": 46,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 133802,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/agents/ppo/tests/test_ppo.py",
        "file_name": "test_ppo.py",
        "fun_name": "test_ppo_exploration_setup",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_ppo_exploration_setup(self):\n        \n        config = copy.deepcopy(ppo.DEFAULT_CONFIG)\n        config[\"num_workers\"] = 0  # Run locally.\n        config[\"env_config\"] = {\"is_slippery\": False, \"map_name\": \"4x4\"}\n        obs = np.array(0)\n\n        # Test against all frameworks.\n        for fw in framework_iterator(config):\n            # Default Agent should be setup with StochasticSampling.\n            trainer = ppo.PPOTrainer(config=config, env=\"FrozenLake-v1\")\n            # explore=False, always expect the same (deterministic) action.\n            a_ = trainer.compute_single_action(\n                obs, explore=False, prev_action=np.array(2), prev_reward=np.array(1.0)\n            )\n            # Test whether this is really the argmax action over the logits.\n            if fw != \"tf\":\n                last_out = trainer.get_policy().model.last_output()\n                if fw == \"torch\":\n                    check(a_, np.argmax(last_out.detach().cpu().numpy(), 1)[0])\n                else:\n                    check(a_, np.argmax(last_out.numpy(), 1)[0])\n            for _ in range(50):\n                a = trainer.compute_single_action(\n                    obs,\n                    explore=False,\n                    prev_action=np.array(2),\n                    prev_reward=np.array(1.0),\n                )\n                check(a, a_)\n\n            # With explore=True (default), expect stochastic actions.\n            actions = []\n            for _ in range(300):\n                actions.append(\n                    trainer.compute_single_action(\n                        obs, prev_action=np.array(2), prev_reward=np.array(1.0)\n                    )\n                )\n            check(np.mean(actions), 1.5, atol=0.2)\n            trainer.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 629,
        "n_words": 126,
        "vocab_size": 87,
        "complexity": 6,
        "nloc": 33,
        "token_counts": 285,
        "n_ast_nodes": 446,
        "n_identifiers": 37,
        "d_id": 30114,
        "documentation": {
            "docstring": "Tests, whether PPO runs with different exploration setups.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 203467,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/sites.py",
        "file_name": "sites.py",
        "fun_name": "logout",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def logout(self, request, extra_context=None):\n        \n        from django.contrib.auth.views import LogoutView\n\n        defaults = {\n            \"extra_context\": {\n                **self.each_context(request),\n                # Since the user isn't logged out at this point, the value of\n                # has_permission must be overridden.\n                \"has_permission\": False,\n                **(extra_context or {}),\n            },\n        }\n        if self.logout_template is not None:\n            defaults[\"template_name\"] = self.logout_template\n        request.current_app = self.name\n        return LogoutView.as_view(**defaults)(request)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 209,
        "n_words": 52,
        "vocab_size": 46,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 85,
        "n_ast_nodes": 137,
        "n_identifiers": 15,
        "d_id": 50391,
        "documentation": {
            "docstring": "\n        Log out the user for the given HttpRequest.\n\n        This should *not* assume the user is already logged in.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 250551,
        "commit_id": "ee4999e8e4380f7b67faef92f04c361deffba412",
        "repo": "mitmproxy",
        "path": "mitmproxy/addonmanager.py",
        "file_name": "addonmanager.py",
        "fun_name": "register",
        "commit_message": "Rename new async helper functions.\n\nasync_trigger -> trigger_event\ninvoke_addon -> invoke_addon_sync (API breakage)\nasync_invoke_addon -> invoke_addon",
        "code": "def register(self, addon):\n        \n        api_changes = {\n            # mitmproxy 6 -> mitmproxy 7\n            \"clientconnect\": \"client_connected\",\n            \"clientdisconnect\": \"client_disconnected\",\n            \"serverconnect\": \"server_connect and server_connected\",\n            \"serverdisconnect\": \"server_disconnected\",\n        }\n        for a in traverse([addon]):\n            for old, new in api_changes.items():\n                if hasattr(a, old):\n                    ctx.log.warn(f\"The {old} event has been removed, use {new} instead. \"\n                                 f\"For more details, see https://docs.mitmproxy.org/stable/addons-events/.\")\n            name = _get_name(a)\n            if name in self.lookup:\n                raise exceptions.AddonManagerError(\n                    \"An addon called '%s' already exists.\" % name\n                )\n        l = Loader(self.master)\n        self.invoke_addon_sync(addon, LoadHook(l))\n        for a in traverse([addon]):\n            name = _get_name(a)\n            self.lookup[name] = a\n        for a in traverse([addon]):\n            self.master.commands.collect_commands(a)\n        self.master.options.process_deferred()\n        return addon\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 397,
        "n_words": 91,
        "vocab_size": 68,
        "complexity": 7,
        "nloc": 26,
        "token_counts": 164,
        "n_ast_nodes": 283,
        "n_identifiers": 27,
        "d_id": 73504,
        "documentation": {
            "docstring": "\n            Register an addon, call its load event, and then register all its\n            sub-addons. This should be used by addons that dynamically manage\n            addons.\n\n            If the calling addon is already running, it should follow with\n            running and configure events. Must be called within a current\n            context.\n        ",
            "n_words": 45,
            "vocab_size": 41,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 117299,
        "commit_id": "13d267c409bf1cc65fca366d1aa4fc51438cbf71",
        "repo": "mindsdb",
        "path": "tests/integration_tests/flows/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_sql_create_database",
        "commit_message": "It http test refactoring (#3959)\n\n* HTTP and company independent tests refactoring",
        "code": "def test_sql_create_database(self, db, subtests, request):\n        \n        db_data = request.getfixturevalue(db)\n        db_type = db_data['type']\n        db_creds = db_data['connection_data']\n        queries = [\n            {\n                'create': 'CREATE DATABASE',\n                'drop': 'DROP DATABASE'\n            }, {\n                'create': 'CREATE DATABASE',\n                'drop': None\n            }\n        ]\n        created_db_names = []\n        for query in queries:\n            create_query = query['create']\n            drop_query = query['drop']\n            db_name = db_type.upper()\n            created_db_names.append(db_name)\n            with subtests.test(msg=f'{db_type}', create_query=create_query, drop_query=drop_query, db_name=db_name):\n                query = f\n                self.sql_via_http(query, RESPONSE_TYPE.OK)\n                assert db_name in self.show_databases()\n                if drop_query is not None:\n                    self.sql_via_http(f'{drop_query} {db_name}', RESPONSE_TYPE.OK)\n                    assert db_name.upper() not in self.show_databases()\n\n        resp = self.sql_via_http('show databases', RESPONSE_TYPE.TABLE)\n        db_names = [x[0] for x in resp['data']]\n        for name in created_db_names:\n            assert name in db_names\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 431,
        "n_words": 97,
        "vocab_size": 65,
        "complexity": 5,
        "nloc": 34,
        "token_counts": 200,
        "n_ast_nodes": 367,
        "n_identifiers": 30,
        "d_id": 25949,
        "documentation": {
            "docstring": " sql-via-http:\n            'create database' for each db\n            'drop database' for each db\n            'create database' for each db\n        \n                    {create_query} {db_name}\n                    WITH ENGINE = '{db_type}',\n                    PARAMETERS = {json.dumps(db_creds)};\n                ",
            "n_words": 25,
            "vocab_size": 15,
            "n_whitespaces": 139,
            "language": "en"
        }
    },
    {
        "id": 129592,
        "commit_id": "1971a08b7dadf98c337ed0067db5b59d805b31ae",
        "repo": "ray",
        "path": "python/ray/node.py",
        "file_name": "node.py",
        "fun_name": "get_log_file_handles",
        "commit_message": "[RFC] [Core] Support disabling log redirection via `RAY_LOG_TO_STDERR` environment variable. (#21767)",
        "code": "def get_log_file_handles(self, name, unique=False):\n        \n        if not self.should_redirect_logs():\n            return None, None\n\n        log_stdout, log_stderr = self._get_log_file_names(name, unique=unique)\n        return open_log(log_stdout), open_log(log_stderr)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 48,
        "n_ast_nodes": 77,
        "n_identifiers": 9,
        "d_id": 28982,
        "documentation": {
            "docstring": "Open log files with partially randomized filenames, returning the\n        file handles. If output redirection has been disabled, no files will\n        be opened and `(None, None)` will be returned.\n\n        Args:\n            name (str): descriptive string for this log file.\n            unique (bool): if true, a counter will be attached to `name` to\n                ensure the returned filename is not already used.\n\n        Returns:\n            A tuple of two file handles for redirecting (stdout, stderr), or\n            `(None, None)` if output redirection is disabled.\n        ",
            "n_words": 76,
            "vocab_size": 60,
            "n_whitespaces": 170,
            "language": "en"
        }
    },
    {
        "id": 8086,
        "commit_id": "e4fc06f986e03919d9aef3ab55c05fee5a6b9d3a",
        "repo": "ludwig",
        "path": "ludwig/datasets/loaders/dataset_loader.py",
        "file_name": "dataset_loader.py",
        "fun_name": "get_default_cache_location",
        "commit_message": "Config-first Datasets API (ludwig.datasets refactor) (#2479)\n\n* Adds README and stub for reading dataset configs.\r\n\r\n* Adds __init__.py for configs, moves circular import into function scope in ludwig/datasets/__init__.py\r\n\r\n* Print config files in datasets folder.\r\n\r\n* First pass at automatic archive extraction.\r\n\r\n* Implemented downloading and extract.\r\n\r\n* Refactor DatasetConfig into its own file.\r\n\r\n* Fixed bugs downloading kaggle dataset.\r\n\r\n* Makes registry store dataset instances, not classes. Also comments out import_submodules for testing.\r\n\r\n* Typo fix.\r\n\r\n* Only pass data files on to load_unprocessed_dataframe, symlink directories.\r\n\r\n* Downloading dataset files into existing directory if exists.\r\n\r\n* Refactor: make datasets fully config-first, lazy load dataset loaders.\r\n\r\n* Implemented agnews custom loader.\r\n\r\n* Implements train/validation/test split by files, and globbing support\r\n\r\n* Adds _glob_multiple\r\n\r\n* Adds adult_census_income, agnews, allstate_claims_severity.\r\n\r\n* Implements sha256 verification, adds more datasets up to creditcard_fraud.\r\n\r\n* Adds checksums, dbpedia, electricity\r\n\r\n* Fixes gzip file name returned as string not list, adds up to forest_cover dataset.\r\n\r\n* Adds datasets up to reuters_r8\r\n\r\n* Adds all datasets which don't require a custom class.\r\n\r\n* Restore dataset import behavior by implementing module __getattr__\r\n\r\n* Adds KDD datasets.\r\n\r\n* Adds ieee_fraud.\r\n\r\n* Adds imbalanced_insurance, insurance_lite.\r\n\r\n* Adds mnist.\r\n\r\n* Completes implementation of all of the built-in datasets.\r\n\r\n* Made cache_dir optional, read from environment variable if set.\r\n\r\n* Upgrades datasets tests.\r\n\r\n* Adds test for new dataset config API.  Also adds scripts for dataset link checking.\r\n\r\n* Fixes loading allstate claims severity dataset.\r\n\r\n* Use @lru_cache(1), @cache not supported in python < 3.9\r\n\r\n* Deletes dataset registry, updates automl test utils\r\n\r\n* Fix imports of datasets API.\r\n\r\n* Adds more detail to sha256: docstring and basic README\r\n\r\n* Copy-paste link oops.\r\n\r\n* Fixes handling of nested archive types like .tar.bz  Also adds a LUDWIG_CACHE and export to the README\r\n\r\n* Adds link for twitter bots.\r\n\r\n* Fix order of splits in README.md\r\n\r\n* typo\r\n\r\n* Adds verify as a phase in doc string.\r\n\r\n* Support .pqt, .pq extensions for parquet.\r\n\r\n* Handle nested archives with longer file extensions like .csv.zip\r\n\r\n* Handle nested .gz types properly too.  Check all extensions with .endswith\r\n\r\n* Handle all archive types with .endswith\r\n\r\n* Update ludwig/datasets/loaders/split_loaders.py\r\n\r\nCo-authored-by: Joppe Geluykens <joppe@rvrie.com>\r\n\r\n* Adds explanation for export, fixes preserve_paths (should be relative to processed_dataset_dir)\r\n\r\n* Resolve preserved paths relative to raw dataset dir before move.\r\n\r\n* Catch runtime exception from extracting sub-archives.\r\n\r\nCo-authored-by: Daniel Treiman <daniel@predibase.com>\r\nCo-authored-by: Joppe Geluykens <joppe@rvrie.com>",
        "code": "def get_default_cache_location() -> str:\n    \n    if \"LUDWIG_CACHE\" in os.environ and os.environ[\"LUDWIG_CACHE\"]:\n        return os.environ[\"LUDWIG_CACHE\"]\n    else:\n        return str(Path.home().joinpath(\".ludwig_cache\"))\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 38,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 44,
        "n_ast_nodes": 81,
        "n_identifiers": 7,
        "d_id": 1336,
        "documentation": {
            "docstring": "Returns a path to the default LUDWIG_CACHE location, or $HOME/.ludwig_cache.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 60915,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/network/utils.py",
        "file_name": "utils.py",
        "fun_name": "response_chunks",
        "commit_message": "upd; format",
        "code": "def response_chunks(response, chunk_size=CONTENT_CHUNK_SIZE):\n    # type: (Response, int) -> Iterator[bytes]\n    \n    try:\n        # Special case for urllib3.\n        for chunk in response.raw.stream(\n            chunk_size,\n            # We use decode_content=False here because we don't\n            # want urllib3 to mess with the raw bytes we get\n            # from the server. If we decompress inside of\n            # urllib3 then we cannot verify the checksum\n            # because the checksum will be of the compressed\n            # file. This breakage will only occur if the\n            # server adds a Content-Encoding header, which\n            # depends on how the server was configured:\n            # - Some servers will notice that the file isn't a\n            #   compressible file and will leave the file alone\n            #   and with an empty Content-Encoding\n            # - Some servers will notice that the file is\n            #   already compressed and will leave the file\n            #   alone and will add a Content-Encoding: gzip\n            #   header\n            # - Some servers won't notice anything at all and\n            #   will take a file that's already been compressed\n            #   and compress it again and set the\n            #   Content-Encoding: gzip header\n            #\n            # By setting this not to decode automatically we\n            # hope to eliminate problems with the second case.\n            decode_content=False,\n        ):\n            yield chunk\n    except AttributeError:\n        # Standard file-like object.\n        while True:\n            chunk = response.raw.read(chunk_size)\n            if not chunk:\n                break\n            yield chunk\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 600,
        "n_words": 214,
        "vocab_size": 119,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 54,
        "n_ast_nodes": 114,
        "n_identifiers": 10,
        "d_id": 12341,
        "documentation": {
            "docstring": "Given a requests Response, provide the data chunks.\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 203489,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/templatetags/admin_list.py",
        "file_name": "admin_list.py",
        "fun_name": "result_list",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def result_list(cl):\n    \n    headers = list(result_headers(cl))\n    num_sorted_fields = 0\n    for h in headers:\n        if h[\"sortable\"] and h[\"sorted\"]:\n            num_sorted_fields += 1\n    return {\n        \"cl\": cl,\n        \"result_hidden_fields\": list(result_hidden_fields(cl)),\n        \"result_headers\": headers,\n        \"num_sorted_fields\": num_sorted_fields,\n        \"results\": list(results(cl)),\n    }\n\n\n@register.tag(name=\"result_list\")",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.tag(name=\"result_list\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 103,
        "n_words": 33,
        "vocab_size": 31,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 72,
        "n_ast_nodes": 142,
        "n_identifiers": 12,
        "d_id": 50407,
        "documentation": {
            "docstring": "\n    Display the headers and data list together.\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 201109,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/apps/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_single_path",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_single_path(self):\n        \n        with extend_sys_path(self.base_location):\n            with self.settings(INSTALLED_APPS=[\"nsapp\"]):\n                app_config = apps.get_app_config(\"nsapp\")\n                self.assertEqual(app_config.path, self.app_path)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 66,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 49877,
        "documentation": {
            "docstring": "\n        A Py3.3+ namespace package can be an app if it has only one path.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 264909,
        "commit_id": "6ff2e55ce408f0f7f2fe99129048421c25ecafe6",
        "repo": "netbox",
        "path": "netbox/dcim/models/cables.py",
        "file_name": "cables.py",
        "fun_name": "origins",
        "commit_message": "Add origins, destinations properties on CablePath",
        "code": "def origins(self):\n        \n        if hasattr(self, '_path_objects'):\n            return self.path_objects[0]\n        return [\n            path_node_to_object(node) for node in self.path[0]\n        ]\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 65,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 37,
        "n_ast_nodes": 60,
        "n_identifiers": 7,
        "d_id": 77907,
        "documentation": {
            "docstring": "\n        Return the list of originating objects (from cache, if available).\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 128083,
        "commit_id": "51aa429f4c2db2f5bb35064cedaf70c8df2828a8",
        "repo": "ray",
        "path": "rllib/connectors/connector.py",
        "file_name": "connector.py",
        "fun_name": "to_state",
        "commit_message": "[RLlib] minor cleanup of connector to/from state APIs (#28884)\n\n* [RLlib] minor cleanup of connector to/from state APIs. Also better error messages.\r\n\r\nSigned-off-by: Jun Gong <jungong@anyscale.com>\r\n\r\n* wip\r\n\r\nSigned-off-by: Jun Gong <jungong@anyscale.com>\r\n\r\n* address review comments.\r\n\r\nSigned-off-by: Jun Gong <jungong@anyscale.com>\r\n\r\n* lint\r\n\r\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def to_state(self) -> Tuple[str, Any]:\n        \n        # Must implement by each connector.\n        return NotImplementedError\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 15,
        "n_ast_nodes": 26,
        "n_identifiers": 6,
        "d_id": 28611,
        "documentation": {
            "docstring": "Serialize a connector into a JSON serializable Tuple.\n\n        to_state is required, so that all Connectors are serializable.\n\n        Returns:\n            A tuple of connector's name and its serialized states.\n            String should match the name used to register the connector,\n            while state can be any single data structure that contains the\n            serialized state of the connector. If a connector is stateless,\n            state can simply be None.\n        ",
            "n_words": 63,
            "vocab_size": 48,
            "n_whitespaces": 139,
            "language": "en"
        }
    },
    {
        "id": 258521,
        "commit_id": "a5b70b3132467b5e3616178d9ecca6cb7316c400",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/pairwise.py",
        "file_name": "pairwise.py",
        "fun_name": "paired_cosine_distances",
        "commit_message": "DOC Ensures that sklearn.metrics.pairwise.paired_cosine_distances passes numpydoc validation (#22141)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def paired_cosine_distances(X, Y):\n    \n    X, Y = check_paired_arrays(X, Y)\n    return 0.5 * row_norms(normalize(X) - normalize(Y), squared=True)\n\n\nPAIRED_DISTANCES = {\n    \"cosine\": paired_cosine_distances,\n    \"euclidean\": paired_euclidean_distances,\n    \"l2\": paired_euclidean_distances,\n    \"l1\": paired_manhattan_distances,\n    \"manhattan\": paired_manhattan_distances,\n    \"cityblock\": paired_manhattan_distances,\n}\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 56,
        "n_words": 31,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 39,
        "n_ast_nodes": 108,
        "n_identifiers": 10,
        "d_id": 75273,
        "documentation": {
            "docstring": "\n    Compute the paired cosine distances between X and Y.\n\n    Read more in the :ref:`User Guide <metrics>`.\n\n    Parameters\n    ----------\n    X : array-like of shape (n_samples, n_features)\n        An array where each row is a sample and each column is a feature.\n\n    Y : array-like of shape (n_samples, n_features)\n        An array where each row is a sample and each column is a feature.\n\n    Returns\n    -------\n    distances : ndarray of shape (n_samples,)\n        Returns the distances between the row vectors of `X`\n        and the row vectors of `Y`, where `distances[i]` is the\n        distance between `X[i]` and `Y[i]`.\n\n    Notes\n    -----\n    The cosine distance is equivalent to the half the squared\n    euclidean distance if each sample is normalized to unit norm.\n    ",
            "n_words": 114,
            "vocab_size": 57,
            "n_whitespaces": 192,
            "language": "en"
        }
    },
    {
        "id": 71191,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/models.py",
        "file_name": "models.py",
        "fun_name": "popular_tags_for_model",
        "commit_message": "Reformat with black",
        "code": "def popular_tags_for_model(model, count=10):\n    \n    content_type = ContentType.objects.get_for_model(model)\n    return (\n        Tag.objects.filter(taggit_taggeditem_items__content_type=content_type)\n        .annotate(item_count=Count(\"taggit_taggeditem_items\"))\n        .order_by(\"-item_count\")[:count]\n    )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 45,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 52,
        "n_ast_nodes": 88,
        "n_identifiers": 14,
        "d_id": 15639,
        "documentation": {
            "docstring": "Return a queryset of the most frequently used tags used on this model class",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 133938,
        "commit_id": "297341e107daee1ea3aff991ae8ea8c90993c683",
        "repo": "ray",
        "path": "python/ray/tests/test_client.py",
        "file_name": "test_client.py",
        "fun_name": "test_create_remote_before_start",
        "commit_message": "[Test][Client] Only start ray once in client tests (#28835)\n\nIt looks like we're frequently starting and shutting down Ray in this test because `ray_start_client_server` isn't connecting to the Ray created by `ray_start_regular_shared`, and is instead starting a new Ray head process every time it launches.\r\n\r\nRay client tests are failing frequently with:\r\n\r\n```\r\n[2022-10-06 07:31:46,253 E 13235 13751] core_worker_process.cc:277: The core worker has already been shutdown. This happens when the language frontend accesses the Ray's worker after it is shutdown. The process will exit\r\n```\r\n\r\nWhich is probably caused by having multiple ray clusters running simultaneous, with some shutting down asynchronously. This refactor forces all of the tests in the module to use the same Ray cluster.\r\n\r\nAlso fixes two other sources of potential flakiness:\r\n* Joins the thread in test_client_thread_safe (seems like this has a bad interaction when the client server is cleaned up)\r\n* Calls ray.get in `test_stdout_log_stream`, to make sure that the remote function is done running before we try searching for its output\r\n\r\nShould also have the happy side effect of speeding up test_client.\r\n\r\nRan the `Small & Client` tests (regular and external redis) twice each, no flakes, and windows version of test_client.",
        "code": "def test_create_remote_before_start(call_ray_start_shared):\n    \n    from ray.util.client import ray\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 12,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 77,
        "n_ast_nodes": 24,
        "n_identifiers": 5,
        "d_id": 30157,
        "documentation": {
            "docstring": "Creates remote objects (as though in a library) before\n    starting the client.\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 130746,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/experimental/array/distributed/linalg.py",
        "file_name": "linalg.py",
        "fun_name": "tsqr",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def tsqr(a):\n    \n    if len(a.shape) != 2:\n        raise Exception(\n            \"tsqr requires len(a.shape) == 2, but a.shape is \" \"{}\".format(a.shape)\n        )\n    if a.num_blocks[1] != 1:\n        raise Exception(\n            \"tsqr requires a.num_blocks[1] == 1, but a.num_blocks \"\n            \"is {}\".format(a.num_blocks)\n        )\n\n    num_blocks = a.num_blocks[0]\n    K = int(np.ceil(np.log2(num_blocks))) + 1\n    q_tree = np.empty((num_blocks, K), dtype=object)\n    current_rs = []\n    for i in range(num_blocks):\n        block = a.object_refs[i, 0]\n        q, r = ra.linalg.qr.remote(block)\n        q_tree[i, 0] = q\n        current_rs.append(r)\n    for j in range(1, K):\n        new_rs = []\n        for i in range(int(np.ceil(1.0 * len(current_rs) / 2))):\n            stacked_rs = ra.vstack.remote(*current_rs[(2 * i) : (2 * i + 2)])\n            q, r = ra.linalg.qr.remote(stacked_rs)\n            q_tree[i, j] = q\n            new_rs.append(r)\n        current_rs = new_rs\n    assert len(current_rs) == 1, \"len(current_rs) = \" + str(len(current_rs))\n\n    # handle the special case in which the whole DistArray \"a\" fits in one\n    # block and has fewer rows than columns, this is a bit ugly so think about\n    # how to remove it\n    if a.shape[0] >= a.shape[1]:\n        q_shape = a.shape\n    else:\n        q_shape = [a.shape[0], a.shape[0]]\n    q_num_blocks = core.DistArray.compute_num_blocks(q_shape)\n    q_object_refs = np.empty(q_num_blocks, dtype=object)\n    q_result = core.DistArray(q_shape, q_object_refs)\n\n    # reconstruct output\n    for i in range(num_blocks):\n        q_block_current = q_tree[i, 0]\n        ith_index = i\n        for j in range(1, K):\n            if np.mod(ith_index, 2) == 0:\n                lower = [0, 0]\n                upper = [a.shape[1], core.BLOCK_SIZE]\n            else:\n                lower = [a.shape[1], 0]\n                upper = [2 * a.shape[1], core.BLOCK_SIZE]\n            ith_index //= 2\n            q_block_current = ra.dot.remote(\n                q_block_current, ra.subarray.remote(q_tree[ith_index, j], lower, upper)\n            )\n        q_result.object_refs[i] = q_block_current\n    r = current_rs[0]\n    return q_result, ray.get(r)\n\n\n# TODO(rkn): This is unoptimized, we really want a block version of this.\n# This is Algorithm 5 from\n# http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-175.pdf.\n@ray.remote(num_returns=3)",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@ray.remote(num_returns=3)",
        "n_ast_errors": 1,
        "ast_levels": 18,
        "n_whitespaces": 649,
        "n_words": 261,
        "vocab_size": 154,
        "complexity": 10,
        "nloc": 52,
        "token_counts": 473,
        "n_ast_nodes": 749,
        "n_identifiers": 51,
        "d_id": 29340,
        "documentation": {
            "docstring": "Perform a QR decomposition of a tall-skinny matrix.\n\n    Args:\n        a: A distributed matrix with shape MxN (suppose K = min(M, N)).\n\n    Returns:\n        A tuple of q (a DistArray) and r (a numpy array) satisfying the\n            following.\n            - If q_full = ray.get(DistArray, q).assemble(), then\n              q_full.shape == (M, K).\n            - np.allclose(np.dot(q_full.T, q_full), np.eye(K)) == True.\n            - If r_val = ray.get(np.ndarray, r), then r_val.shape == (K, N).\n            - np.allclose(r, np.triu(r)) == True.\n    ",
            "n_words": 69,
            "vocab_size": 54,
            "n_whitespaces": 160,
            "language": "en"
        }
    },
    {
        "id": 199088,
        "commit_id": "f5e24ed39a88b645ca27d15d60d5098895785773",
        "repo": "sympy",
        "path": "sympy/integrals/risch.py",
        "file_name": "risch.py",
        "fun_name": "recognize_log_derivative",
        "commit_message": "fix nits",
        "code": "def recognize_log_derivative(a, d, DE, z=None):\n    \n\n    z = z or Dummy('z')\n    a, d = a.cancel(d, include=True)\n    _, a = a.div(d)\n\n    pz = Poly(z, DE.t)\n    Dd = derivation(d, DE)\n    q = a - pz*Dd\n    r, _ = d.resultant(q, includePRS=True)\n    r = Poly(r, z)\n    Np, Sp = splitfactor_sqf(r, DE, coefficientD=True, z=z)\n\n    for s, _ in Sp:\n        # TODO also consider the complex roots which should\n        # turn the flag false\n        a = real_roots(s.as_poly(z))\n\n        if not all(j.is_Integer for j in a):\n            return False\n    return True\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 156,
        "n_words": 81,
        "vocab_size": 62,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 146,
        "n_ast_nodes": 226,
        "n_identifiers": 29,
        "d_id": 49138,
        "documentation": {
            "docstring": "\n    There exists a v in K(x)* such that f = dv/v\n    where f a rational function if and only if f can be written as f = A/D\n    where D is squarefree,deg(A) < deg(D), gcd(A, D) = 1,\n    and all the roots of the Rothstein-Trager resultant are integers. In that case,\n    any of the Rothstein-Trager, Lazard-Rioboo-Trager or Czichowski algorithm\n    produces u in K(x) such that du/dx = uf.\n    ",
            "n_words": 68,
            "vocab_size": 51,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 312712,
        "commit_id": "3c5a667d9784bb5f2fab426b133b5582706c6e68",
        "repo": "core",
        "path": "homeassistant/components/zwave_me/config_flow.py",
        "file_name": "config_flow.py",
        "fun_name": "async_step_zeroconf",
        "commit_message": "Add Z-Wave.Me integration (#65473)\n\n* Add support of Z-Wave.Me Z-Way and RaZberry server (#61182)\r\n\r\nCo-authored-by: Paulus Schoutsen <paulus@home-assistant.io>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\nCo-authored-by: LawfulChaos <kerbalspacema@gmail.com>\r\n\r\n* Add switch platform to Z-Wave.Me integration (#64957)\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\n\r\n* Add button platform to Z-Wave.Me integration (#65109)\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Fix button controller access (#65117)\r\n\r\n* Add lock platform to Z-Wave.Me integration #65109 (#65114)\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Add sensor platform to Z-Wave.Me integration (#65132)\r\n\r\n* Sensor Entity\r\n\r\n* Sensor fixes\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Inline descriotion according to review proposal\r\n\r\n* State Classes for sensor\r\n\r\n* Generic sensor\r\n\r\n* Generic sensor\r\n\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Add binary sensor platform to Z-Wave.Me integration (#65306)\r\n\r\n* Binary Sensor Entity\r\n\r\n* Update docstring\r\n\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Add Light Entity platform to Z-Wave.Me integration (#65331)\r\n\r\n* Light Entity\r\n\r\n* mypy fix\r\n\r\n* Fixes, ZWaveMePlatforms enum\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Fixes\r\n\r\n* Fixes\r\n\r\n* Fixes\r\n\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Add Thermostat platform to Z-Wave.Me integration #65331 (#65371)\r\n\r\n* Climate entity\r\n\r\n* Climate entity\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Climate entity fix\r\n\r\n* Clean up\r\n\r\n* cleanup\r\n\r\n* Import order fix\r\n\r\n* Correct naming\r\n\r\nCo-authored-by: Dmitry Vlasov <kerbalspacema@gmail.com>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Correct zwave_me .coveragerc (#65491)\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\nCo-authored-by: Paulus Schoutsen <paulus@home-assistant.io>\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\nCo-authored-by: LawfulChaos <kerbalspacema@gmail.com>\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "async def async_step_zeroconf(self, discovery_info):\n        \n        self.url = discovery_info.host\n        self.uuid = await helpers.get_uuid(self.url)\n        if self.uuid is None:\n            return self.async_abort(reason=\"no_valid_uuid_set\")\n\n        await self.async_set_unique_id(self.uuid)\n        self._abort_if_unique_id_configured()\n        return await self.async_step_user()\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 83,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 65,
        "n_ast_nodes": 111,
        "n_identifiers": 13,
        "d_id": 111351,
        "documentation": {
            "docstring": "\n        Handle a discovered Z-Wave accessory - get url to pass into user step.\n\n        This flow is triggered by the discovery component.\n        ",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 177180,
        "commit_id": "53f766aa94b5aa5d3f87178418e794c4cc5f77eb",
        "repo": "networkx",
        "path": "networkx/algorithms/simple_paths.py",
        "file_name": "simple_paths.py",
        "fun_name": "all_simple_paths",
        "commit_message": "Improved documentation for all_simple_paths (#5944)\n\n* Improved documentation for all_simple_paths\r\n\r\nImproved the documentation for all_simple_paths.\r\n\r\n* Update simple_paths.py\r\n\r\nBlack code style compliance edits.",
        "code": "def all_simple_paths(G, source, target, cutoff=None):\n    \n    if source not in G:\n        raise nx.NodeNotFound(f\"source node {source} not in graph\")\n    if target in G:\n        targets = {target}\n    else:\n        try:\n            targets = set(target)\n        except TypeError as err:\n            raise nx.NodeNotFound(f\"target node {target} not in graph\") from err\n    if source in targets:\n        return _empty_generator()\n    if cutoff is None:\n        cutoff = len(G) - 1\n    if cutoff < 1:\n        return _empty_generator()\n    if G.is_multigraph():\n        return _all_simple_paths_multigraph(G, source, targets, cutoff)\n    else:\n        return _all_simple_paths_graph(G, source, targets, cutoff)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 188,
        "n_words": 76,
        "vocab_size": 45,
        "complexity": 8,
        "nloc": 20,
        "token_counts": 125,
        "n_ast_nodes": 205,
        "n_identifiers": 16,
        "d_id": 42304,
        "documentation": {
            "docstring": "Generate all simple paths in the graph G from source to target.\n\n    A simple path is a path with no repeated nodes.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n\n    source : node\n       Starting node for path\n\n    target : nodes\n       Single node or iterable of nodes at which to end path\n\n    cutoff : integer, optional\n        Depth to stop the search. Only paths of length <= cutoff are returned.\n\n    Returns\n    -------\n    path_generator: generator\n       A generator that produces lists of simple paths.  If there are no paths\n       between the source and target within the given cutoff the generator\n       produces no output. If it is possible to traverse the same sequence of\n       nodes in multiple ways, namely through parallel edges, then it will be\n       returned multiple times (once for each viable edge combination).\n\n    Examples\n    --------\n    This iterator generates lists of nodes::\n\n        >>> G = nx.complete_graph(4)\n        >>> for path in nx.all_simple_paths(G, source=0, target=3):\n        ...     print(path)\n        ...\n        [0, 1, 2, 3]\n        [0, 1, 3]\n        [0, 2, 1, 3]\n        [0, 2, 3]\n        [0, 3]\n\n    You can generate only those paths that are shorter than a certain\n    length by using the `cutoff` keyword argument::\n\n        >>> paths = nx.all_simple_paths(G, source=0, target=3, cutoff=2)\n        >>> print(list(paths))\n        [[0, 1, 3], [0, 2, 3], [0, 3]]\n\n    To get each path as the corresponding list of edges, you can use the\n    :func:`networkx.utils.pairwise` helper function::\n\n        >>> paths = nx.all_simple_paths(G, source=0, target=3)\n        >>> for path in map(nx.utils.pairwise, paths):\n        ...     print(list(path))\n        [(0, 1), (1, 2), (2, 3)]\n        [(0, 1), (1, 3)]\n        [(0, 2), (2, 1), (1, 3)]\n        [(0, 2), (2, 3)]\n        [(0, 3)]\n\n    Pass an iterable of nodes as target to generate all paths ending in any of several nodes::\n\n        >>> G = nx.complete_graph(4)\n        >>> for path in nx.all_simple_paths(G, source=0, target=[3, 2]):\n        ...     print(path)\n        ...\n        [0, 1, 2]\n        [0, 1, 2, 3]\n        [0, 1, 3]\n        [0, 1, 3, 2]\n        [0, 2]\n        [0, 2, 1, 3]\n        [0, 2, 3]\n        [0, 3]\n        [0, 3, 1, 2]\n        [0, 3, 2]\n\n    Iterate over each path from the root nodes to the leaf nodes in a\n    directed acyclic graph using a functional programming approach::\n\n        >>> from itertools import chain\n        >>> from itertools import product\n        >>> from itertools import starmap\n        >>> from functools import partial\n        >>>\n        >>> chaini = chain.from_iterable\n        >>>\n        >>> G = nx.DiGraph([(0, 1), (1, 2), (0, 3), (3, 2)])\n        >>> roots = (v for v, d in G.in_degree() if d == 0)\n        >>> leaves = (v for v, d in G.out_degree() if d == 0)\n        >>> all_paths = partial(nx.all_simple_paths, G)\n        >>> list(chaini(starmap(all_paths, product(roots, leaves))))\n        [[0, 1, 2], [0, 3, 2]]\n\n    The same list computed using an iterative approach::\n\n        >>> G = nx.DiGraph([(0, 1), (1, 2), (0, 3), (3, 2)])\n        >>> roots = (v for v, d in G.in_degree() if d == 0)\n        >>> leaves = (v for v, d in G.out_degree() if d == 0)\n        >>> all_paths = []\n        >>> for root in roots:\n        ...     for leaf in leaves:\n        ...         paths = nx.all_simple_paths(G, root, leaf)\n        ...         all_paths.extend(paths)\n        >>> all_paths\n        [[0, 1, 2], [0, 3, 2]]\n\n    Iterate over each path from the root nodes to the leaf nodes in a\n    directed acyclic graph passing all leaves together to avoid unnecessary\n    compute::\n\n        >>> G = nx.DiGraph([(0, 1), (2, 1), (1, 3), (1, 4)])\n        >>> roots = (v for v, d in G.in_degree() if d == 0)\n        >>> leaves = [v for v, d in G.out_degree() if d == 0]\n        >>> all_paths = []\n        >>> for root in roots:\n        ...     paths = nx.all_simple_paths(G, root, leaves)\n        ...     all_paths.extend(paths)\n        >>> all_paths\n        [[0, 1, 3], [0, 1, 4], [2, 1, 3], [2, 1, 4]]\n\n    If parallel edges offer multiple ways to traverse a given sequence of\n    nodes, this sequence of nodes will be returned multiple times:\n\n        >>> G = nx.MultiDiGraph([(0, 1), (0, 1), (1, 2)])\n        >>> list(nx.all_simple_paths(G, 0, 2))\n        [[0, 1, 2], [0, 1, 2]]\n\n    Notes\n    -----\n    This algorithm uses a modified depth-first search to generate the\n    paths [1]_.  A single path can be found in $O(V+E)$ time but the\n    number of simple paths in a graph can be very large, e.g. $O(n!)$ in\n    the complete graph of order $n$.\n\n    This function does not check that a path exists between `source` and\n    `target`. For large graphs, this may result in very long runtimes.\n    Consider using `has_path` to check that a path exists between `source` and\n    `target` before calling this function on large graphs.\n\n    References\n    ----------\n    .. [1] R. Sedgewick, \"Algorithms in C, Part 5: Graph Algorithms\",\n       Addison Wesley Professional, 3rd ed., 2001.\n\n    See Also\n    --------\n    all_shortest_paths, shortest_path, has_path\n\n    ",
            "n_words": 741,
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            "n_whitespaces": 1450,
            "language": "en"
        }
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    {
        "id": 161988,
        "commit_id": "159f3667f4772680368cb7b0771c6d5e44416e3c",
        "repo": "numba",
        "path": "numba/tests/gdb_support.py",
        "file_name": "gdb_support.py",
        "fun_name": "supports_numpy",
        "commit_message": "Numba gdb-python extension for printing\n\nThis adds support for printing Numba types as their python\nequivalents from gdb by using its python extension.",
        "code": "def supports_numpy(self):\n        \n        if not self.supports_python():\n            return False\n        self.interpreter_exec('console', 'python import numpy; print numpy')\n        return \"module \\'numpy\\' from\" in self._captured.before.decode()\n",
        "url": "https://github.com/numba/numba.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 36,
        "n_ast_nodes": 69,
        "n_identifiers": 7,
        "d_id": 39119,
        "documentation": {
            "docstring": "Returns True if the underlying gdb implementation has NumPy support\n           (and by extension Python support) False otherwise",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 264062,
        "commit_id": "2b2559af1c7790596e7b2040f48e56baef608f9d",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/tcl_tk.py",
        "file_name": "tcl_tk.py",
        "fun_name": "_get_tcl_tk_info",
        "commit_message": "hookutils: tcl/tk: port to PyInstaller.isolated framework",
        "code": "def _get_tcl_tk_info():\n    \n    try:\n        import tkinter\n        from _tkinter import TCL_VERSION, TK_VERSION\n    except ImportError:\n        # tkinter unavailable\n        return None, None, None, False\n\n    tcl = tkinter.Tcl()\n\n    # Query the location of Tcl library/data directory.\n    tcl_dir = tcl.eval(\"info library\")\n\n    # Check if Tcl/Tk is built with multi-threaded support (built with --enable-threads), as indicated by the presence\n    # of optional `threaded` member in `tcl_platform` array.\n    try:\n        tcl.getvar(\"tcl_platform(threaded)\")  # Ignore the actual value.\n        tcl_threaded = True\n    except tkinter.TclError:\n        tcl_threaded = False\n\n    return tcl_dir, TCL_VERSION, TK_VERSION, tcl_threaded\n\n\n# Populate the variables. If `tkinter` is unavailable, the values are set to `None` or `False`.\n(\n    tcl_dir,\n    tcl_version,\n    tk_version,\n    tcl_threaded,\n) = _get_tcl_tk_info()\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 196,
        "n_words": 104,
        "vocab_size": 76,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 68,
        "n_ast_nodes": 141,
        "n_identifiers": 15,
        "d_id": 77583,
        "documentation": {
            "docstring": "\n    Isolated-subprocess helper to retrieve the basic Tcl/Tk information:\n     - tcl_dir = path to the Tcl library/data directory.\n     - tcl_version = Tcl version\n     - tk_version = Tk version\n     - tcl_theaded = boolean indicating whether Tcl/Tk is built with multi-threading support.\n    ",
            "n_words": 39,
            "vocab_size": 28,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 65646,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/controllers/queries.py",
        "file_name": "queries.py",
        "fun_name": "lead_query",
        "commit_message": "style: format code with black",
        "code": "def lead_query(doctype, txt, searchfield, start, page_len, filters):\n\tfields = get_fields(\"Lead\", [\"name\", \"lead_name\", \"company_name\"])\n\n\treturn frappe.db.sql(\n\t\t.format(\n\t\t\t**{\"fields\": \", \".join(fields), \"key\": searchfield, \"mcond\": get_match_cond(doctype)}\n\t\t),\n\t\t{\"txt\": \"%%%s%%\" % txt, \"_txt\": txt.replace(\"%\", \"\"), \"start\": start, \"page_len\": page_len},\n\t)\n\n\t# searches for customer\n\n\n@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 31,
        "n_words": 42,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 92,
        "n_ast_nodes": 178,
        "n_identifiers": 18,
        "d_id": 13968,
        "documentation": {
            "docstring": "select {fields} from `tabLead`\n\t\twhere docstatus < 2\n\t\t\tand ifnull(status, '') != 'Converted'\n\t\t\tand ({key} like %(txt)s\n\t\t\t\tor lead_name like %(txt)s\n\t\t\t\tor company_name like %(txt)s)\n\t\t\t{mcond}\n\t\torder by\n\t\t\tif(locate(%(_txt)s, name), locate(%(_txt)s, name), 99999),\n\t\t\tif(locate(%(_txt)s, lead_name), locate(%(_txt)s, lead_name), 99999),\n\t\t\tif(locate(%(_txt)s, company_name), locate(%(_txt)s, company_name), 99999),\n\t\t\tidx desc,\n\t\t\tname, lead_name\n\t\tlimit %(start)s, %(page_len)s",
            "n_words": 50,
            "vocab_size": 35,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 54421,
        "commit_id": "ca11b933b9187a0e1bf9008315eeec2155815ab3",
        "repo": "prefect",
        "path": "src/prefect/agent.py",
        "file_name": "agent.py",
        "fun_name": "update_work_queue_id_from_name",
        "commit_message": "Support work_queue_name for agent",
        "code": "async def update_work_queue_id_from_name(self) -> bool:\n        \n        if not self.work_queue_name:\n            raise ValueError(\"No work queue name provided.\")\n        try:\n            work_queue = await self.client.read_work_queue_by_name(self.work_queue_name)\n            self.work_queue_id = work_queue.id\n        except httpx.HTTPStatusError:\n            self.logger.warn(f'No work queue found named \"{self.work_queue_name}\"')\n            self.work_queue_id = None\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 116,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 60,
        "n_ast_nodes": 111,
        "n_identifiers": 14,
        "d_id": 11054,
        "documentation": {
            "docstring": "\n        For agents that were provided a work_queue_name, rather than a work_queue_id,\n        this function will retrieve the work queue ID corresponding to that name and assign\n        it to `work_queue_id`. If no matching queue is found, a warning is logged\n        and `work_queue_id = None`.\n        ",
            "n_words": 42,
            "vocab_size": 35,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 208066,
        "commit_id": "1c4ff33bd22cf94e297bd6449a06b5a30c2c1fbc",
        "repo": "celery",
        "path": "celery/canvas.py",
        "file_name": "canvas.py",
        "fun_name": "on_chord_header_start",
        "commit_message": "Canvas Header Stamping (#7384)\n\n* Strip down the header-stamping PR to the basics.\r\n\r\n* Serialize groups.\r\n\r\n* Add groups to result backend meta data.\r\n\r\n* Fix spelling mistake.\r\n\r\n* Revert changes to canvas.py\r\n\r\n* Revert changes to app/base.py\r\n\r\n* Add stamping implementation to canvas.py\r\n\r\n* Send task to AMQP with groups.\r\n\r\n* Successfully pass single group to result.\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* First draft of the visitor API.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fixed lint and elements\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* type -> isinstance\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Redo header stamping (#7341)\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Fixed lint and elements\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* type -> isinstance\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* Added stamping mechanism\r\n\r\n* Manual stamping improved\r\n\r\n* flake8 fixed\r\n\r\n* Added subtests\r\n\r\n* Add comma.\r\n\r\n* Moved groups to stamps\r\n\r\n* Fixed chord and added test for that\r\n\r\n* Strip down the header-stamping PR to the basics.\r\n\r\n* Serialize groups.\r\n\r\n* Add groups to result backend meta data.\r\n\r\n* Fix spelling mistake.\r\n\r\n* Revert changes to canvas.py\r\n\r\n* Revert changes to app/base.py\r\n\r\n* Add stamping implementation to canvas.py\r\n\r\n* Send task to AMQP with groups.\r\n\r\n* Successfully pass single group to result.\r\n\r\n* _freeze_gid dict merge fixed\r\n\r\n* First draft of the visitor API.\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* OptionsVisitor created\r\n\r\n* Fixed canvas.py\r\n\r\n* Added test for simple test for chord and fixed chord implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Changed _IMMUTABLE_OPTIONS\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed chord interface\r\n\r\n* Fixed list order\r\n\r\n* Fixed tests (stamp test and chord test), fixed order in groups\r\n\r\n* Fixed lint and elements\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Changed implementation of stamp API and fix lint\r\n\r\n* Added documentation to Stamping API. Added chord with groups test\r\n\r\n* Implemented stamping inside replace and added test for an implementation\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Added test additonal tests for chord, improved coverage\r\n\r\n* Splitted into subtests\r\n\r\n* Group stamping rollback\r\n\r\n* group.id is None fixed\r\n\r\n* Added integration test\r\n\r\n* Added integration test\r\n\r\n* apply_async fixed\r\n\r\n* Integration test and test_chord fixed\r\n\r\n* Lint fixed\r\n\r\n* chord freeze fixed\r\n\r\n* Minor fixes.\r\n\r\n* Chain apply_async fixed and tests fixed\r\n\r\n* lint fixed\r\n\r\n* Added integration test for chord\r\n\r\n* type -> isinstance\r\n\r\n* Added stamping mechanism\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Manual stamping improved\r\n\r\n* fail_ci_if_error uncommented\r\n\r\n* flake8 fixed\r\n\r\n* Added subtests\r\n\r\n* Changes\r\n\r\n* Add comma.\r\n\r\n* Fixed chord and added test for that\r\n\r\n* canvas.py fixed\r\n\r\n* Test chord.py fixed\r\n\r\n* Fixed stamped_headers\r\n\r\n* collections import fixed\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* collections import fixed\r\n\r\n* Update celery/backends/base.py\r\n\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* ampq.py fixed\r\n\r\n* Refrain from using deprecated import path.\r\n\r\n* Fix test_complex_chain regression.\r\n\r\nWhenever we stamp a group we need to freeze it first if it wasn't already frozen.\r\nSomewhere along the line, the group id changed because we were freezing twice.\r\nThis commit places the stamping operation after preparing the chain's steps which fixes the problem somehow.\r\n\r\nWe don't know why yet.\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed integration tests\r\n\r\n* Fixed issues with maybe_list. Add documentation\r\n\r\n* Fixed potential issue with integration tests\r\n\r\n* Fixed issues with _regen\r\n\r\n* Fixed issues with _regen\r\n\r\n* Fixed test_generator issues\r\n\r\n* Fixed _regen stamping\r\n\r\n* Fixed _regen stamping\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Fixed TimeOut issue\r\n\r\n* Update docs/userguide/canvas.rst\r\n\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\n\r\n* Fixed Couchbase\r\n\r\n* Better stamping intro\r\n\r\n* New GroupVisitor example\r\n\r\n* Adjust documentation.\r\n\r\nCo-authored-by: Naomi Elstein <naomi.els@omerkatz.com>\r\nCo-authored-by: Omer Katz <omer.katz@omerkatz.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Asif Saif Uddin <auvipy@gmail.com>\r\nCo-authored-by: Omer Katz <omer.katz@kcg.tech>",
        "code": "def on_chord_header_start(self, chord, **header) -> dict:\n        \n        if not isinstance(chord.tasks, group):\n            chord.tasks = group(chord.tasks)\n        return self.on_group_start(chord.tasks, **header)\n",
        "url": "https://github.com/celery/celery.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 48,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 46,
        "n_ast_nodes": 73,
        "n_identifiers": 9,
        "d_id": 52191,
        "documentation": {
            "docstring": "Method that is called on сhord header stamping start.\n\n         Arguments:\n             chord (chord): chord that is stamped.\n             headers (Dict): Partial headers that could be merged with existing headers.\n         Returns:\n             Dict: headers to update.\n         ",
            "n_words": 32,
            "vocab_size": 26,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 251966,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/test_command.py",
        "file_name": "test_command.py",
        "fun_name": "test_collect_commands",
        "commit_message": "make it black!",
        "code": "async def test_collect_commands():\n    \n    with taddons.context() as tctx:\n        c = command.CommandManager(tctx.master)\n        a = TCmds()\n        c.collect_commands(a)\n        assert \"empty\" in c.commands\n\n        a = TypeErrAddon()\n        c.collect_commands(a)\n        await tctx.master.await_log(\"Could not load\")\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 81,
        "n_words": 26,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 61,
        "n_ast_nodes": 113,
        "n_identifiers": 14,
        "d_id": 73904,
        "documentation": {
            "docstring": "\n    This tests for errors thrown by getattr() or __getattr__ implementations\n    that return an object for .command_name.\n    ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 155180,
        "commit_id": "193505fdf0c984743397ba3df56262f30aee13a8",
        "repo": "modin",
        "path": "modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "mask",
        "commit_message": "FEAT-#5053: Add pandas on unidist execution with MPI backend (#5059)\n\nSigned-off-by: Igoshev, Iaroslav <iaroslav.igoshev@intel.com>",
        "code": "def mask(self, row_labels, col_labels):\n        \n        logger = get_logger()\n        logger.debug(f\"ENTER::Partition.mask::{self._identity}\")\n        new_obj = super().mask(row_labels, col_labels)\n        if isinstance(row_labels, slice) and unidist.is_object_ref(self._length_cache):\n            if row_labels == slice(None):\n                # fast path - full axis take\n                new_obj._length_cache = self._length_cache\n            else:\n                new_obj._length_cache = compute_sliced_len.remote(\n                    row_labels, self._length_cache\n                )\n        if isinstance(col_labels, slice) and unidist.is_object_ref(self._width_cache):\n            if col_labels == slice(None):\n                # fast path - full axis take\n                new_obj._width_cache = self._width_cache\n            else:\n                new_obj._width_cache = compute_sliced_len.remote(\n                    col_labels, self._width_cache\n                )\n        logger.debug(f\"EXIT::Partition.mask::{self._identity}\")\n        return new_obj\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 325,
        "n_words": 67,
        "vocab_size": 39,
        "complexity": 7,
        "nloc": 20,
        "token_counts": 139,
        "n_ast_nodes": 238,
        "n_identifiers": 18,
        "d_id": 36272,
        "documentation": {
            "docstring": "\n        Lazily create a mask that extracts the indices provided.\n\n        Parameters\n        ----------\n        row_labels : list-like, slice or label\n            The row labels for the rows to extract.\n        col_labels : list-like, slice or label\n            The column labels for the columns to extract.\n\n        Returns\n        -------\n        PandasOnUnidistDataframePartition\n            A new ``PandasOnUnidistDataframePartition`` object.\n        ",
            "n_words": 46,
            "vocab_size": 34,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 13120,
        "commit_id": "cdaf7f87ececf9e13b517379ca183b17f0d7b007",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/runtimes/remote.py",
        "file_name": "remote.py",
        "fun_name": "mixin_gateway_parser",
        "commit_message": "feat: allow passing custom gateway in Flow (#5189)",
        "code": "def mixin_gateway_parser(parser):\n    \n    gp = add_arg_group(parser, title='Gateway')\n    _add_host(gp)\n    _add_proxy(gp)\n\n    gp.add_argument(\n        '--uses',\n        type=str,\n        default=None,\n        # TODO: add Jina Hub Gateway\n        help=,\n    )\n\n    gp.add_argument(\n        '--uses-with',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n\n    gp.add_argument(\n        '--py-modules',\n        type=str,\n        nargs='*',\n        metavar='PATH',\n        help=,\n    )\n\n    mixin_base_runtime_parser(gp)\n\n    gp.add_argument(\n        '--port-expose',\n        type=int,\n        dest='port',\n        default=helper.random_port(),\n        help='The port that the gateway exposes for clients for GRPC connections.',\n    )\n\n    parser.add_argument(\n        '--graph-description',\n        type=str,\n        help='Routing graph for the gateway',\n        default='{}',\n    )\n\n    parser.add_argument(\n        '--graph-conditions',\n        type=str,\n        help='Dictionary stating which filtering conditions each Executor in the graph requires to receive Documents.',\n        default='{}',\n    )\n\n    parser.add_argument(\n        '--deployments-addresses',\n        type=str,\n        help='dictionary JSON with the input addresses of each Deployment',\n        default='{}',\n    )\n\n    parser.add_argument(\n        '--deployments-disable-reduce',\n        type=str,\n        help='list JSON disabling the built-in merging mechanism for each Deployment listed',\n        default='[]',\n    )\n\n    gp.add_argument(\n        '--compression',\n        choices=['NoCompression', 'Deflate', 'Gzip'],\n        help='The compression mechanism used when sending requests from the Head to the WorkerRuntimes. For more details, '\n        'check https://grpc.github.io/grpc/python/grpc.html#compression.',\n    )\n\n    gp.add_argument(\n        '--timeout-send',\n        type=int,\n        default=None,\n        help='The timeout in milliseconds used when sending data requests to Executors, -1 means no timeout, disabled by default',\n    )\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 543,
        "n_words": 160,
        "vocab_size": 108,
        "complexity": 1,
        "nloc": 87,
        "token_counts": 237,
        "n_ast_nodes": 404,
        "n_identifiers": 22,
        "d_id": 2555,
        "documentation": {
            "docstring": "Add the options for remote expose at the Gateway\n    :param parser: the parser\n    \n        The config of the gateway, it could be one of the followings:\n        * the string literal of an Gateway class name\n        * a Gateway YAML file (.yml, .yaml, .jaml)\n        * a docker image (must start with `docker://`)\n        * the string literal of a YAML config (must start with `!` or `jtype: `)\n        * the string literal of a JSON config\n\n        When use it under Python, one can use the following values additionally:\n        - a Python dict that represents the config\n        - a text file stream has `.read()` interface\n        \n    Dictionary of keyword arguments that will override the `with` configuration in `uses`\n    \nThe customized python modules need to be imported before loading the gateway\n\nNote that the recommended way is to only import a single module - a simple python file, if your\ngateway can be defined in a single file, or an ``__init__.py`` file if you have multiple files,\nwhich should be structured as a python package.\n",
            "n_words": 169,
            "vocab_size": 102,
            "n_whitespaces": 249,
            "language": "en"
        }
    },
    {
        "id": 296832,
        "commit_id": "a2c74b978664b627bafc4a43b26aa2be7b15b229",
        "repo": "core",
        "path": "tests/components/calendar/test_trigger.py",
        "file_name": "test_trigger.py",
        "fun_name": "test_update_next_event",
        "commit_message": "Add initial implementation of a calendar trigger (#68674)\n\n* Add initial implementation of calendar trigger\r\n\r\nThis is an initial implementation of a calendar trigger, that supports\r\ntriggering on calendar start time.\r\n\r\nSee architecture proposal in:\r\nhttps://github.com/home-assistant/architecture/discussions/700\r\n\r\n* Address reviewer feedback\r\n\r\n* Use f-strings for all tests\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Remove logging f-strings, and move to main code\r\n\r\n* Remove mypy ignore\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update calendar triggers to use new calendar data model\r\n\r\n* Update tests/components/calendar/test_trigger.py\r\n\r\nCo-authored-by: Franck Nijhof <frenck@frenck.nl>\r\n\r\n* Rewrite tests using freezegun\r\n\r\nRewrite tests using freezegun and improve edge case handling, and use utc consistently for all alarms.\r\n\r\n* Update homeassistant/components/calendar/trigger.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/calendar/trigger.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Increase test coverage based on pr feedback\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\nCo-authored-by: Franck Nijhof <frenck@frenck.nl>",
        "code": "async def test_update_next_event(hass, calls, fake_schedule):\n    \n\n    event_data1 = fake_schedule.create_event(\n        start=datetime.datetime.fromisoformat(\"2022-04-19 11:00:00+00:00\"),\n        end=datetime.datetime.fromisoformat(\"2022-04-19 11:15:00+00:00\"),\n    )\n    await create_automation(hass, EVENT_START)\n\n    # No calls before event start\n    await fake_schedule.fire_until(\n        datetime.datetime.fromisoformat(\"2022-04-19 10:45:00+00:00\")\n    )\n    assert len(calls()) == 0\n\n    # Create a new event between now and when the event fires\n    event_data2 = fake_schedule.create_event(\n        start=datetime.datetime.fromisoformat(\"2022-04-19 10:55:00+00:00\"),\n        end=datetime.datetime.fromisoformat(\"2022-04-19 11:05:00+00:00\"),\n    )\n\n    # Advance past the end of the events\n    await fake_schedule.fire_until(\n        datetime.datetime.fromisoformat(\"2022-04-19 11:30:00+00:00\")\n    )\n    assert calls() == [\n        {\n            \"platform\": \"calendar\",\n            \"event\": EVENT_START,\n            \"calendar_event\": event_data2,\n        },\n        {\n            \"platform\": \"calendar\",\n            \"event\": EVENT_START,\n            \"calendar_event\": event_data1,\n        },\n    ]\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 269,
        "n_words": 85,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 149,
        "n_ast_nodes": 259,
        "n_identifiers": 15,
        "d_id": 95806,
        "documentation": {
            "docstring": "Test detection of a new event after initial trigger is setup.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 245715,
        "commit_id": "d915740fa8228cf57741b27d9e5d66e358456b8e",
        "repo": "mmdetection",
        "path": "mmdet/models/task_modules/coders/delta_xywh_bbox_coder.py",
        "file_name": "delta_xywh_bbox_coder.py",
        "fun_name": "encode",
        "commit_message": "[Refactor] Refactor anchor head and base head with boxlist (#8625)\n\n* Refactor anchor head\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Add a series of boxes tools\r\n\r\n* Fix box type to support n x box_dim boxes\r\n\r\n* revert box type changes\r\n\r\n* Add docstring\r\n\r\n* refactor retina_head\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Fix comments\r\n\r\n* modify docstring of coder and ioucalculator\r\n\r\n* Replace with_boxlist with use_box_type",
        "code": "def encode(self, bboxes, gt_bboxes):\n        \n        bboxes = get_box_tensor(bboxes)\n        gt_bboxes = get_box_tensor(gt_bboxes)\n        assert bboxes.size(0) == gt_bboxes.size(0)\n        assert bboxes.size(-1) == gt_bboxes.size(-1) == 4\n        encoded_bboxes = bbox2delta(bboxes, gt_bboxes, self.means, self.stds)\n        return encoded_bboxes\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 77,
        "n_words": 28,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 72,
        "n_ast_nodes": 112,
        "n_identifiers": 10,
        "d_id": 70861,
        "documentation": {
            "docstring": "Get box regression transformation deltas that can be used to\n        transform the ``bboxes`` into the ``gt_bboxes``.\n\n        Args:\n            bboxes (torch.Tensor or :obj:`BaseBoxes`): Source boxes,\n                e.g., object proposals.\n            gt_bboxes (torch.Tensor or :obj:`BaseBoxes`): Target of the\n                transformation, e.g., ground-truth boxes.\n\n        Returns:\n            torch.Tensor: Box transformation deltas\n        ",
            "n_words": 42,
            "vocab_size": 34,
            "n_whitespaces": 133,
            "language": "en"
        }
    },
    {
        "id": 9551,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/utils/align2stylegan.py",
        "file_name": "align2stylegan.py",
        "fun_name": "create_perspective_transform",
        "commit_message": "initialize ostec",
        "code": "def create_perspective_transform(src, dst, round=False, splat_args=False):\n    \n    try:\n        transform_matrix = create_perspective_transform_matrix(src, dst)\n        error = None\n    except np.linalg.LinAlgError as e:\n        transform_matrix = np.identity(3, dtype=np.float)\n        error = \"invalid input quads (%s and %s): %s\" %(src, dst, e)\n        error = error.replace(\"\\n\", \"\")\n\n    to_eval = \"def perspective_transform(%s):\\n\" %(\n        splat_args and \"*pt\" or \"pt\",\n    )\n    to_eval += \"  res = np.dot(transform_matrix, ((pt[0], ), (pt[1], ), (1, )))\\n\"\n    to_eval += \"  res = res / res[2]\\n\"\n    if round:\n        to_eval += \"  return (int(round(res[0][0])), int(round(res[1][0])))\\n\"\n    else:\n        to_eval += \"  return (res[0][0], res[1][0])\\n\"\n    locals = {\n        \"transform_matrix\": transform_matrix,\n    }\n    locals.update(globals())\n    exec(to_eval,locals,locals)\n    res = locals[\"perspective_transform\"]\n    res.matrix = transform_matrix\n    res.error = error\n    return res\n\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 220,
        "n_words": 102,
        "vocab_size": 67,
        "complexity": 5,
        "nloc": 26,
        "token_counts": 144,
        "n_ast_nodes": 254,
        "n_identifiers": 23,
        "d_id": 1631,
        "documentation": {
            "docstring": " Returns a function which will transform points in quadrilateral\n        ``src`` to the corresponding points on quadrilateral ``dst``::\n\n            >>> transform = create_perspective_transform(\n            ...     [(0, 0), (10, 0), (10, 10), (0, 10)],\n            ...     [(50, 50), (100, 50), (100, 100), (50, 100)],\n            ... )\n            >>> transform((5, 5))\n            (74.99999999999639, 74.999999999999957)\n\n        If ``round`` is ``True`` then points will be rounded to the nearest\n        integer and integer values will be returned.\n\n            >>> transform = create_perspective_transform(\n            ...     [(0, 0), (10, 0), (10, 10), (0, 10)],\n            ...     [(50, 50), (100, 50), (100, 100), (50, 100)],\n            ...     round=True,\n            ... )\n            >>> transform((5, 5))\n            (75, 75)\n\n        If ``splat_args`` is ``True`` the function will accept two arguments\n        instead of a tuple.\n\n            >>> transform = create_perspective_transform(\n            ...     [(0, 0), (10, 0), (10, 10), (0, 10)],\n            ...     [(50, 50), (100, 50), (100, 100), (50, 100)],\n            ...     splat_args=True,\n            ... )\n            >>> transform(5, 5)\n            (74.99999999999639, 74.999999999999957)\n\n        If the input values yield an invalid transformation matrix an identity\n        function will be returned and the ``error`` attribute will be set to a\n        description of the error::\n\n            >>> tranform = create_perspective_transform(\n            ...     np.zeros((4, 2)),\n            ...     np.zeros((4, 2)),\n            ... )\n            >>> transform((5, 5))\n            (5.0, 5.0)\n            >>> transform.error\n            'invalid input quads (...): Singular matrix\n        ",
            "n_words": 194,
            "vocab_size": 84,
            "n_whitespaces": 606,
            "language": "en"
        }
    },
    {
        "id": 196391,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/matrices/matrices.py",
        "file_name": "matrices.py",
        "fun_name": "limit",
        "commit_message": "Moved imports to higher level",
        "code": "def limit(self, *args):\n        \n        return self.applyfunc(lambda x: x.limit(*args))\n\n\n# https://github.com/sympy/sympy/pull/12854",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 22,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 47891,
        "documentation": {
            "docstring": "Calculate the limit of each element in the matrix.\n        ``args`` will be passed to the ``limit`` function.\n\n        Examples\n        ========\n\n        >>> from sympy import Matrix\n        >>> from sympy.abc import x, y\n        >>> M = Matrix([[x, y], [1, 0]])\n        >>> M.limit(x, 2)\n        Matrix([\n        [2, y],\n        [1, 0]])\n\n        See Also\n        ========\n\n        integrate\n        diff\n        ",
            "n_words": 50,
            "vocab_size": 39,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 163521,
        "commit_id": "4e034ec0006b6c05160ce67ea1420ce28f295c91",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "difference",
        "commit_message": "DEPR: DatetimeIndex.intersection with mixed timezones cast to UTC, not object (#45357)\n\n* DEPR: DatetimeIndex.intersection with mixed timezones cast to UTC instead of object\r\n\r\n* GH ref\r\n\r\n* mypy fixup\r\n\r\nCo-authored-by: Jeff Reback <jeff@reback.net>",
        "code": "def difference(self, other, sort=None):\n        \n        self._validate_sort_keyword(sort)\n        self._assert_can_do_setop(other)\n        other, result_name = self._convert_can_do_setop(other)\n\n        # Note: we do NOT call _deprecate_dti_setop here, as there\n        #  is no requirement that .difference be commutative, so it does\n        #  not cast to object.\n\n        if self.equals(other):\n            # Note: we do not (yet) sort even if sort=None GH#24959\n            return self[:0].rename(result_name)\n\n        if len(other) == 0:\n            # Note: we do not (yet) sort even if sort=None GH#24959\n            return self.rename(result_name)\n\n        if not self._should_compare(other):\n            # Nothing matches -> difference is everything\n            return self.rename(result_name)\n\n        result = self._difference(other, sort=sort)\n        return self._wrap_difference_result(other, result)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 239,
        "n_words": 87,
        "vocab_size": 57,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 105,
        "n_ast_nodes": 173,
        "n_identifiers": 15,
        "d_id": 39453,
        "documentation": {
            "docstring": "\n        Return a new Index with elements of index not in `other`.\n\n        This is the set difference of two Index objects.\n\n        Parameters\n        ----------\n        other : Index or array-like\n        sort : False or None, default None\n            Whether to sort the resulting index. By default, the\n            values are attempted to be sorted, but any TypeError from\n            incomparable elements is caught by pandas.\n\n            * None : Attempt to sort the result, but catch any TypeErrors\n              from comparing incomparable elements.\n            * False : Do not sort the result.\n\n        Returns\n        -------\n        difference : Index\n\n        Examples\n        --------\n        >>> idx1 = pd.Index([2, 1, 3, 4])\n        >>> idx2 = pd.Index([3, 4, 5, 6])\n        >>> idx1.difference(idx2)\n        Int64Index([1, 2], dtype='int64')\n        >>> idx1.difference(idx2, sort=False)\n        Int64Index([2, 1], dtype='int64')\n        ",
            "n_words": 115,
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        }
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    {
        "id": 320759,
        "commit_id": "a20bb67a878b2e68abf8268c1b0a27f018d01352",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/webkit/webkittab.py",
        "file_name": "webkittab.py",
        "fun_name": "_on_frame_load_finished",
        "commit_message": "mypy: Upgrade to PyQt5-stubs 5.15.6.0\n\nFor some unknown reason, those new stubs cause a *lot* of things now to be\nchecked by mypy which formerly probably got skipped due to Any being implied\nsomewhere.\n\nThe stubs themselves mainly improved, with a couple of regressions too.\n\nIn total, there were some 337 (!) new mypy errors. This commit fixes almost all\nof them, and the next commit improves a fix to get things down to 0 errors\nagain.\n\nOverview of the changes:\n\n==== qutebrowser/app.py\n\n- Drop type ignore due to improved stubs.\n\n==== qutebrowser/browser/browsertab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  This is debatable: I suppose the abstract stuff shouldn't need to know\n  anything about the concrete backends at all. But it seems like we cut some\n  corners when initially implementing things, and put some code in browsertab.py\n  just because the APIs of both backends happened to be compatible. Perhaps\n  something to reconsider once we drop QtWebKit and hopefully implement a dummy\n  backend.\n\n- Add an additional assertion in AbstractAction.run_string. This is already\n  covered by the isinstance(member, self.action_base) above it, but that's too\n  dynamic for mypy to understand.\n\n- Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x\n  and y components), not a single int.\n\n- Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x\n  and y components), not a single int.\n\n- Fix the argument types of AbstractScroller.to_perc, as it's possible to pass\n  fractional percentages too.\n\n- Specify the type for AbstractHistoryPrivate._history. See above (_widget) re\n  this being debatable.\n\n- Fix the return type of AbstractTabPrivate.event_target(), which can be None\n  (see #3888).\n\n- Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS\n  return value), not None.\n\n- Fix the argument type for AbstractTabPrivate.toggle_inspector: position can\n  be None to use the last used position.\n\n- Declare the type of sub-objects of AbstractTab.\n\n- Fix the return value of AbstractTab.icon(), which is the QIcon, not None.\n\n==== qutebrowser/browser/commands.py\n\n- Make sure the active window is a MainWindow (with a .win_id attribute).\n\n==== qutebrowser/browser/downloadview.py\n\n- Add _model() which makes sure that self.model() is a DownloadModel, not None\n  or any other model. This is needed because other methods access a variety of\n  custom attributes on it, e.g. last_index().\n\n==== qutebrowser/browser/greasemonkey.py\n\n- Add an ignore for AbstractDownload.requested_url which we patch onto the\n  downloads. Probably would be nicer to add it as a proper attribute which always\n  gets set by the DownloadManager.\n\n==== qutebrowser/browser/hints.py\n\n- Remove type ignores for QUrl.toString().\n- Add a new type ignore for combining different URL flags (which works, but is\n  not exactly type safe... still probably a regression in the stubs).\n- Make sure the things we get back from self._get_keyparser are what we actually\n  expect. Probably should introduce a TypedDict (and/or overloads for\n  _get_keyparser with typing.Literal) to teach mypy about the exact return value.\n  See #7098.\n  This is needed because we access Hint/NormalKeyParser-specific attributes such\n  as .set_inhibited_timout() or .update_bindings().\n\n==== qutebrowser/browser/inspector.py\n\n- Similar changes than in browsertab.py to make some types where we share API\n  (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next\n  commit.\n\n==== qutebrowser/browser/network/pac.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/qtnetworkdownloads.py\n\n- Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an\n  AbstractDownload), so that we can call ._uses_nam() on it.\n\n==== qutebrowser/browser/qutescheme.py\n\n- Remove now unneeded type ignore for QUrl flags.\n\n==== qutebrowser/browser/urlmarks.py\n\n- Specify the type of UrlMarkManager._lineparser, as those only get initialized\n  in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist.\n\n==== qutebrowser/browser/webelem.py\n\n- New casts to turn single KeyboardModifier (enum) entries into\n  KeyboardModifiers (flags). Might not be needed anymore with Qt 6.\n- With that, casting the final value is now unneeded.\n\n==== qutebrowser/browser/webengine/notification.py\n\n- Remove now unneeded type ignore for signal.\n- Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished()\n  is a QProcess, not just any QObject.\n\n==== qutebrowser/browser/webengine/webenginedownloads.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webengine/webengineelem.py\n\n- Specify the type of WebEngineElement._tab.\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webengineinspector.py\n\n- See changes to inspector.py and next commit.\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/webengine/webenginequtescheme.py\n\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webenginesettings.py\n\n- Ignore access of .setter attribute which we patch onto QWebEngineProfile.\n  Would be nice to have a subclass or wrapper-class instead.\n\n==== qutebrowser/browser/webengine/webenginetab.py\n\n- Specified the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Remove some now-unneeded type ignores for creating FindFlags.\n- Specify more concrete types for WebEngineTab members where we actually need to\n  access WebEngine-specific attributes.\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webengine/webview.py\n\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webkit/network/networkreply.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webkit/webkitinspector.py\n\n- See changes to inspector.py and next commit.\n\n==== qutebrowser/browser/webkit/webkittab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Add a type ignore for WebKitAction because our workaround needs to\n  treat them as ints (which is allowed by PyQt, even if not type-safe).\n- Add new ignores for findText calls: The text is a QString and can be None; the\n  flags are valid despite mypy thinking they aren't (stubs regression?).\n- Specify the type for WebKitHistoryPrivate._history, because we access\n  WebKit-specific attributes. See above (_widget) re this being debatable.\n- Make mypy aware that .currentFrame() and .frameAt() can return None (stubs\n  regression?).\n- Make sure the .page() and .page().networkAccessManager() are our subclasses\n  rather than the more generic QtWebKit objects, as we use custom attributes.\n- Add new type ignores for signals (stubs regression!)\n\n==== qutebrowser/browser/webkit/webpage.py\n\n- Make sure the .networkAccessManager() is our subclass rather than the more\n  generic QtWebKit object, as we use custom attributes.\n- Replace a cast by a type ignore. The cast didn't work anymore.\n\n==== qutebrowser/browser/webkit/webview.py\n\n- Make sure the .page() is our subclass rather than the more generic QtWebKit\n  object, as we use custom attributes.\n\n==== qutebrowser/commands/userscripts.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/completion/completer.py\n\n- Add a new _completion() getter (which ensures it actually gets the completion\n  view) rather than accessing the .parent() directly (which could be any QObject).\n\n==== qutebrowser/completion/completiondelegate.py\n\n- Make sure self.parent() is a CompletionView (no helper method as there is only\n  one instance).\n- Remove a now-unneeded type ignore for adding QSizes.\n\n==== qutebrowser/completion/completionwidget.py\n\n- Add a ._model() getter which ensures that we get a CompletionModel (with\n  custom attributes) rather than Qt's .model() which can be any QAbstractItemModel\n  (or None).\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/completion/models/completionmodel.py\n\n- Remove now unneeded type ignores for signals.\n- Ignore a complaint about .set_pattern() not being defined. Completion\n  categories don't share any common parent class, so it would be good to introduce\n  a typing.Protocol for this. See #7098.\n\n==== qutebrowser/components/misccommands.py\n\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/components/readlinecommands.py\n\n- Make sure QApplication.instance() is a QApplication (and not just a\n  QCoreApplication). This includes the former \"not None\" check.\n\n==== qutebrowser/components/scrollcommands.py\n\n- Add basic annotation for \"funcs\" dict. Could have a callable protocol to\n  specify it needs a count kwarg, see #7098.\n\n==== qutebrowser/config/stylesheet.py\n\n- Correctly specify that stylesheet apply to QWidgets, not any QObject.\n- Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy\n  about this with overloads and protocols (stylesheet for set_register being None\n  => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not\n  worth the troble. See #7098.\n\n==== qutebrowser/keyinput/keyutils.py\n\n- Remove some now-unneeded type ignores and add a cast for using a single enum\n  value as flags. Might need to look at this again with Qt 6 support.\n\n==== qutebrowser/keyinput/modeman.py\n\n- Add a FIXME for using a TypedDict, see comments for hints.py above.\n\n==== qutebrowser/mainwindow/mainwindow.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n- Improve where we cast from WindowType to WindowFlags, no int needed\n- Use new .tab_bar() getter, see below.\n\n==== qutebrowser/mainwindow/prompt.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n\n==== qutebrowser/mainwindow/statusbar/bar.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/statusbar/command.py\n\n- Fix type for setText() override (from QLineEdit): text can be None\n  (QString in C++).\n\n==== qutebrowser/mainwindow/statusbar/url.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/tabbedbrowser.py\n\n- Specify that TabDeque manages browser tabs, not any QWidgets. It accesses\n  AbstractTab-specific attributes.\n- Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access\n  .maybe_hide.\n- Fix the annotations for stored marks: Scroll positions are a QPoint, not int.\n- Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and\n  .widget(), which ensures that the return values are valid AbstractTabs (or None\n  for _tab_by_idx). This is needed because we access AbstractTab-specific\n  attributes.\n- For some places, where the tab can be None, continue using .currentTab() but\n  add asserts.\n- Remove some now-unneeded [unreachable] ignores, as mypy knows about the None\n  possibility now.\n\n==== qutebrowser/mainwindow/tabwidget.py\n\n- Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and\n  .widget() are of type TabBar and AbstractTab, respectively.\n- Add additional assertions where we expect ._tab_by_idx() to never be None.\n- Remove dead code in get_tab_fields for handling a None y scroll position. I\n  was unable to find any place in the code where this could be set to None.\n- Remove some now-unneeded type ignores and casts, as mypy now knows that\n  _type_by_idx() could be None.\n- Work around a strange instance where mypy complains about not being able to\n  find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility,\n  despite it clearly being shown as a bool *inside* that class without any\n  annotation.\n- Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in\n  fact a TabWidget.\n\n==== qutebrowser/misc/crashsignal.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/editor.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/ipc.py\n\n- Remove now unneeded type ignores for signals.\n- Add new type ignores for .error() which is both a signal and a getter\n  (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was\n  renamed to errorOccurred in 5.15.\n\n==== qutebrowser/misc/objects.py\n\n- Make sure mypy knows that objects.app is our custom Application (with custom\n  attributes) rather than any QApplication.\n\n==== qutebrowser/utils/objreg.py\n\n- Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol,\n  but ideally, the whole objreg stuff should die one day anyways.\n\n==== tests/unit/completion/test_completer.py\n\n- Make CompletionWidgetStub inherit from CompletionView so that it passes the\n  new isinstance() asserts in completer.py (see above).",
        "code": "def _on_frame_load_finished(self):\n        \n        page = self._widget.page()\n        assert isinstance(page, webpage.BrowserPage), page\n        self._on_load_finished(not page.error_occurred)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
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        "documentation": {
            "docstring": "Make sure we emit an appropriate status when loading finished.\n\n        While Qt has a bool \"ok\" attribute for loadFinished, it always is True\n        when using error pages... See\n        https://github.com/qutebrowser/qutebrowser/issues/84\n        ",
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            "language": "en"
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    },
    {
        "id": 218182,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_common.py",
        "file_name": "_common.py",
        "fun_name": "get_package",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_package(package):\n    # type: (Package) -> types.ModuleType\n    \n    resolved = resolve(package)\n    if wrap_spec(resolved).submodule_search_locations is None:\n        raise TypeError(f'{package!r} is not a package')\n    return resolved\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
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        "d_id": 55184,
        "documentation": {
            "docstring": "Take a package name or module object and return the module.\n\n    Raise an exception if the resolved module is not a package.\n    ",
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    },
    {
        "id": 223835,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/message.py",
        "file_name": "message.py",
        "fun_name": "get_content_charset",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_content_charset(self, failobj=None):\n        \n        missing = object()\n        charset = self.get_param('charset', missing)\n        if charset is missing:\n            return failobj\n        if isinstance(charset, tuple):\n            # RFC 2231 encoded, so decode it, and it better end up as ascii.\n            pcharset = charset[0] or 'us-ascii'\n            try:\n                # LookupError will be raised if the charset isn't known to\n                # Python.  UnicodeError will be raised if the encoded text\n                # contains a character not in the charset.\n                as_bytes = charset[2].encode('raw-unicode-escape')\n                charset = str(as_bytes, pcharset)\n            except (LookupError, UnicodeError):\n                charset = charset[2]\n        # charset characters must be in us-ascii range\n        try:\n            charset.encode('us-ascii')\n        except UnicodeError:\n            return failobj\n        # RFC 2046, $4.1.2 says charsets are not case sensitive\n        return charset.lower()\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
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            "docstring": "Return the charset parameter of the Content-Type header.\n\n        The returned string is always coerced to lower case.  If there is no\n        Content-Type header, or if that header has no charset parameter,\n        failobj is returned.\n        ",
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        "path": "python3.10.4/Lib/email/_header_value_parser.py",
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        "commit_message": "add python 3.10.4 for windows",
        "code": "def get_fws(value):\n    \n    newvalue = value.lstrip()\n    fws = WhiteSpaceTerminal(value[:len(value)-len(newvalue)], 'fws')\n    return fws, newvalue\n",
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            "docstring": "FWS = 1*WSP\n\n    This isn't the RFC definition.  We're using fws to represent tokens where\n    folding can be done, but when we are parsing the *un*folding has already\n    been done so we don't need to watch out for CRLF.\n\n    ",
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        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/index/collector.py",
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        "commit_message": "upd; format",
        "code": "def _determine_base_url(document, page_url):\n    # type: (HTMLElement, str) -> str\n    \n    for base in document.findall(\".//base\"):\n        href = base.get(\"href\")\n        if href is not None:\n            return href\n    return page_url\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
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        "documentation": {
            "docstring": "Determine the HTML document's base URL.\n\n    This looks for a ``<base>`` tag in the HTML document. If present, its href\n    attribute denotes the base URL of anchor tags in the document. If there is\n    no such tag (or if it does not have a valid href attribute), the HTML\n    file's URL is used as the base URL.\n\n    :param document: An HTML document representation. The current\n        implementation expects the result of ``html5lib.parse()``.\n    :param page_url: The URL of the HTML document.\n    ",
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        "commit_id": "8bb1b365ca6bb21b32a1ee1654eecb02570970ac",
        "repo": "keras",
        "path": "keras/metrics/metrics.py",
        "file_name": "metrics.py",
        "fun_name": "binary_accuracy",
        "commit_message": "reverting binary accuracy to original",
        "code": "def binary_accuracy(y_true, y_pred, threshold=0.5):\n  \n  y_pred = tf.convert_to_tensor(y_pred)\n  threshold = tf.cast(threshold, y_pred.dtype)\n  y_pred = tf.cast(y_pred > threshold, y_pred.dtype)\n  return backend.mean(tf.equal(y_true, y_pred), axis=-1)\n\n\n@keras_export('keras.metrics.categorical_accuracy')\n@tf.__internal__.dispatch.add_dispatch_support",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export('keras.metrics.categorical_accuracy')\n@tf.__internal__.dispatch.add_dispatch_support",
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        "d_id": 79764,
        "documentation": {
            "docstring": "Calculates how often predictions match binary labels.\n\n  Standalone usage:\n  >>> y_true = [[1], [1], [0], [0]]\n  >>> y_pred = [[1], [1], [0], [0]]\n  >>> m = tf.keras.metrics.binary_accuracy(y_true, y_pred)\n  >>> assert m.shape == (4,)\n  >>> m.numpy()\n  array([1., 1., 1., 1.], dtype=float32)\n\n  Args:\n    y_true: Ground truth values. shape = `[batch_size, d0, .. dN]`.\n    y_pred: The predicted values. shape = `[batch_size, d0, .. dN]`.\n    threshold: (Optional) Float representing the threshold for deciding whether\n      prediction values are 1 or 0.\n\n  Returns:\n    Binary accuracy values. shape = `[batch_size, d0, .. dN-1]`\n  ",
            "n_words": 86,
            "vocab_size": 61,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 56999,
        "commit_id": "8f3ffd09dc47bfd2af6a635cc04c640febffd519",
        "repo": "prefect",
        "path": "src/prefect/blocks/kubernetes.py",
        "file_name": "kubernetes.py",
        "fun_name": "activate",
        "commit_message": "add test coerage for get_api_client and activate",
        "code": "def activate(self) -> str:\n        \n        load_kube_config_from_dict(\n            config_dict=self.config,\n            context=self.context,\n        )\n\n        return self.current_context()\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 60,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 29,
        "n_ast_nodes": 48,
        "n_identifiers": 8,
        "d_id": 11603,
        "documentation": {
            "docstring": "\n        Convenience method for activating the k8s config stored in an instance of this block\n\n        Returns current_context for sanity check\n        ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 337312,
        "commit_id": "fb5ed62c102c0323486b89805e1888495de3db15",
        "repo": "accelerate",
        "path": "utils/style_doc.py",
        "file_name": "style_doc.py",
        "fun_name": "style_doc_files",
        "commit_message": "Convert documentation to the new front (#271)\n\n* Main conversion\r\n\r\n* Doc styling\r\n\r\n* Style\r\n\r\n* New front deploy\r\n\r\n* Fixes\r\n\r\n* Fixes\r\n\r\n* Fix new docstrings\r\n\r\n* Style",
        "code": "def style_doc_files(*files, max_len=119, check_only=False):\n    \n    changed = []\n    black_errors = []\n    for file in files:\n        # Treat folders\n        if os.path.isdir(file):\n            files = [os.path.join(file, f) for f in os.listdir(file)]\n            files = [f for f in files if os.path.isdir(f) or f.endswith(\".mdx\") or f.endswith(\".py\")]\n            changed += style_doc_files(*files, max_len=max_len, check_only=check_only)\n        # Treat mdx\n        elif file.endswith(\".mdx\"):\n            try:\n                diff, black_error = style_mdx_file(file, max_len=max_len, check_only=check_only)\n                if diff:\n                    changed.append(file)\n                if len(black_error) > 0:\n                    black_errors.append(\n                        f\"There was a problem while formatting an example in {file} with black:\\m{black_error}\"\n                    )\n            except Exception:\n                print(f\"There is a problem in {file}.\")\n                raise\n        # Treat python files\n        elif file.endswith(\".py\"):\n            try:\n                diff, black_error = style_file_docstrings(file, max_len=max_len, check_only=check_only)\n                if diff:\n                    changed.append(file)\n                if len(black_error) > 0:\n                    black_errors.append(\n                        f\"There was a problem while formatting an example in {file} with black:\\m{black_error}\"\n                    )\n            except Exception:\n                print(f\"There is a problem in {file}.\")\n                raise\n        else:\n            warnings.warn(f\"Ignoring {file} because it's not a py or an mdx file or a folder.\")\n    if len(black_errors) > 0:\n        black_message = \"\\n\\n\".join(black_errors)\n        raise ValueError(\n            \"Some code examples can't be interpreted by black, which means they aren't regular python:\\n\\n\"\n            + black_message\n            + \"\\n\\nMake sure to fix the corresponding docstring or doc file, or remove the py/python after ``` if it \"\n            + \"was not supposed to be a Python code sample.\"\n        )\n    return changed\n\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 733,
        "n_words": 203,
        "vocab_size": 110,
        "complexity": 17,
        "nloc": 43,
        "token_counts": 264,
        "n_ast_nodes": 474,
        "n_identifiers": 26,
        "d_id": 121025,
        "documentation": {
            "docstring": "\n    Applies doc styling or checks everything is correct in a list of files.\n\n    Args:\n        files (several `str` or `os.PathLike`): The files to treat.\n        max_len (`int`): The maximum number of characters per line.\n        check_only (`bool`, *optional*, defaults to `False`):\n            Whether to restyle file or just check if they should be restyled.\n\n    Returns:\n        List[`str`]: The list of files changed or that should be restyled.\n    ",
            "n_words": 62,
            "vocab_size": 47,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 196027,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/assumptions/assume.py",
        "file_name": "assume.py",
        "fun_name": "assuming",
        "commit_message": "Updated import locations",
        "code": "def assuming(*assumptions):\n    \n    old_global_assumptions = global_assumptions.copy()\n    global_assumptions.update(assumptions)\n    try:\n        yield\n    finally:\n        global_assumptions.clear()\n        global_assumptions.update(old_global_assumptions)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 47,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 36,
        "n_ast_nodes": 67,
        "n_identifiers": 7,
        "d_id": 47527,
        "documentation": {
            "docstring": "\n    Context manager for assumptions.\n\n    Examples\n    ========\n\n    >>> from sympy import assuming, Q, ask\n    >>> from sympy.abc import x, y\n    >>> print(ask(Q.integer(x + y)))\n    None\n    >>> with assuming(Q.integer(x), Q.integer(y)):\n    ...     print(ask(Q.integer(x + y)))\n    True\n    ",
            "n_words": 33,
            "vocab_size": 25,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 22585,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "brickout-game/brickout-game.py",
        "file_name": "brickout-game.py",
        "fun_name": "update",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def update(self, paddle, brickwall):\n        \n        self._xLoc += self.__xVel\n        self._yLoc += self.__yVel\n        # left screen wall bounce\n        if self._xLoc <= self._radius:\n            self.__xVel *= -1\n        # right screen wall bounce\n        elif self._xLoc >= self.__width - self._radius:\n            self.__xVel *= -1\n        # top wall bounce\n        if self._yLoc <= self._radius:\n            self.__yVel *= -1\n        # bottom drop out\n        elif self._yLoc >= self.__width - self._radius:\n            return True\n\n        # for bouncing off the bricks.\n        if brickwall.collide(self):\n            self.__yVel *= -1\n\n        # collision detection between ball and paddle\n        paddleY = paddle._yLoc\n        paddleW = paddle._width\n        paddleH = paddle._height\n        paddleX = paddle._xLoc\n        ballX = self._xLoc\n        ballY = self._yLoc\n\n        if ((ballX + self._radius) >= paddleX and ballX <= (paddleX + paddleW)) and (\n            (ballY + self._radius) >= paddleY and ballY <= (paddleY + paddleH)\n        ):\n            self.__yVel *= -1\n\n        return False\n\n\n\n\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 364,
        "n_words": 126,
        "vocab_size": 64,
        "complexity": 10,
        "nloc": 24,
        "token_counts": 186,
        "n_ast_nodes": 296,
        "n_identifiers": 19,
        "d_id": 4365,
        "documentation": {
            "docstring": "\n        moves the ball at the screen.\n        contains some collision detection.\n        \n    Simple class for representing a paddle\n",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 19880,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/distributions/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "get_metadata_distribution",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def get_metadata_distribution(self) -> BaseDistribution:\n        \n        assert self.req.local_file_path, \"Set as part of preparation during download\"\n        assert self.req.name, \"Wheels are never unnamed\"\n        wheel = FilesystemWheel(self.req.local_file_path)\n        return get_wheel_distribution(wheel, canonicalize_name(self.req.name))\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 60,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 48,
        "n_ast_nodes": 79,
        "n_identifiers": 10,
        "d_id": 3125,
        "documentation": {
            "docstring": "Loads the metadata from the wheel file into memory and returns a\n        Distribution that uses it, not relying on the wheel file or\n        requirement.\n        ",
            "n_words": 24,
            "vocab_size": 20,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 102398,
        "commit_id": "6eba936082a641be8ece156f70c0f5c435f7a7aa",
        "repo": "pytorch",
        "path": "torch/testing/_internal/common_modules.py",
        "file_name": "common_modules.py",
        "fun_name": "no_batch_dim_reference_rnn_gru",
        "commit_message": "[rnn/gru] no batch dim (#70442)\n\nSummary:\nFixes https://github.com/pytorch/pytorch/issues/60585\n\nTODO:\n* [x] Doc updates\n\nPull Request resolved: https://github.com/pytorch/pytorch/pull/70442\n\nReviewed By: zou3519\n\nDifferential Revision: D33460427\n\nPulled By: jbschlosser\n\nfbshipit-source-id: c64d9624c305d90570c79d11a28557f9ec667b27",
        "code": "def no_batch_dim_reference_rnn_gru(m, p, *args, **kwargs):\n    \n    if len(args) == 1:\n        inp, = args\n        h = None\n    elif len(args) == 2:\n        inp, h = args\n        h = h.unsqueeze(1)\n\n    batch_dim = 0 if kwargs['batch_first'] else 1\n    kwargs.pop('batch_first')\n    inp = inp.unsqueeze(batch_dim)\n    single_batch_input_args = (inp, h)\n    with freeze_rng_state():\n        output = m(*single_batch_input_args, **kwargs)\n        return (output[0].squeeze(batch_dim), output[1].squeeze(1))\n\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 116,
        "n_words": 50,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 118,
        "n_ast_nodes": 192,
        "n_identifiers": 15,
        "d_id": 21518,
        "documentation": {
            "docstring": "Reference function for RNN and GRU supporting no batch dimensions.\n\n    Unbatched inputs are unsqueezed to form a\n    single batch input before passing them to the module.\n    The output is squeezed to compare with the\n    output of unbatched input to the module.\n    ",
            "n_words": 41,
            "vocab_size": 32,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 67257,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/regional/report/provident_fund_deductions/provident_fund_deductions.py",
        "file_name": "provident_fund_deductions.py",
        "fun_name": "get_years",
        "commit_message": "style: format code with black",
        "code": "def get_years():\n\tyear_list = frappe.db.sql_list(\n\t\t\n\t)\n\tif not year_list:\n\t\tyear_list = [getdate().year]\n\n\treturn \"\\n\".join(str(year) for year in year_list)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 12,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 41,
        "n_ast_nodes": 72,
        "n_identifiers": 9,
        "d_id": 14458,
        "documentation": {
            "docstring": "select distinct YEAR(end_date) from `tabSalary Slip` ORDER BY YEAR(end_date) DESC",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 196159,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/permutations.py",
        "file_name": "permutations.py",
        "fun_name": "rmul",
        "commit_message": "Updated import locations",
        "code": "def rmul(*args):\n        \n        rv = args[0]\n        for i in range(1, len(args)):\n            rv = args[i]*rv\n        return rv\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 36,
        "n_ast_nodes": 58,
        "n_identifiers": 6,
        "d_id": 47659,
        "documentation": {
            "docstring": "\n        Return product of Permutations [a, b, c, ...] as the Permutation whose\n        ith value is a(b(c(i))).\n\n        a, b, c, ... can be Permutation objects or tuples.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation\n\n        >>> a, b = [1, 0, 2], [0, 2, 1]\n        >>> a = Permutation(a); b = Permutation(b)\n        >>> list(Permutation.rmul(a, b))\n        [1, 2, 0]\n        >>> [a(b(i)) for i in range(3)]\n        [1, 2, 0]\n\n        This handles the operands in reverse order compared to the ``*`` operator:\n\n        >>> a = Permutation(a); b = Permutation(b)\n        >>> list(a*b)\n        [2, 0, 1]\n        >>> [b(a(i)) for i in range(3)]\n        [2, 0, 1]\n\n        Notes\n        =====\n\n        All items in the sequence will be parsed by Permutation as\n        necessary as long as the first item is a Permutation:\n\n        >>> Permutation.rmul(a, [0, 2, 1]) == Permutation.rmul(a, b)\n        True\n\n        The reverse order of arguments will raise a TypeError.\n\n        ",
            "n_words": 139,
            "vocab_size": 82,
            "n_whitespaces": 322,
            "language": "en"
        }
    },
    {
        "id": 184099,
        "commit_id": "49764a3ec7e9525530e25465be0e1b0c7bffaf6c",
        "repo": "textual",
        "path": "src/textual/design.py",
        "file_name": "design.py",
        "fun_name": "generate",
        "commit_message": "improved color harmony",
        "code": "def generate(self) -> dict[str, str]:\n        \n\n        primary = self.primary\n        secondary = self.secondary or primary\n        warning = self.warning or primary\n        error = self.error or secondary\n        success = self.success or secondary\n        accent = self.accent or primary\n\n        dark = self._dark\n        luminosity_spread = self._luminosity_spread\n        text_alpha = self._text_alpha\n\n        if dark:\n            background = self.background or Color.parse(DEFAULT_DARK_BACKGROUND)\n            surface = self.surface or Color.parse(DEFAULT_DARK_SURFACE)\n        else:\n            background = self.background or Color.parse(DEFAULT_LIGHT_BACKGROUND)\n            surface = self.surface or Color.parse(DEFAULT_LIGHT_SURFACE)\n\n        if self.panel is None:\n            panel = surface.blend(primary, luminosity_spread)\n        else:\n            panel = self.panel\n\n        colors: dict[str, str] = {}\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 253,
        "n_words": 82,
        "vocab_size": 45,
        "complexity": 19,
        "nloc": 72,
        "token_counts": 387,
        "n_ast_nodes": 248,
        "n_identifiers": 27,
        "d_id": 44480,
        "documentation": {
            "docstring": "Generate a mapping of color name on to a CSS color.\n\n        Args:\n            dark (bool, optional): Enable dark mode. Defaults to False.\n            luminosity_spread (float, optional): Amount of luminosity to subtract and add to generate\n                shades. Defaults to 0.2.\n            text_alpha (float, optional): Alpha value for text. Defaults to 0.9.\n\n        Returns:\n            dict[str, str]: A mapping of color name on to a CSS-style encoded color\n\n        ",
            "n_words": 61,
            "vocab_size": 40,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 31490,
        "commit_id": "3eed5530ec74bb60ad9f8f612717d0f6ccf820f2",
        "repo": "transformers",
        "path": "src/transformers/tokenization_utils_base.py",
        "file_name": "tokenization_utils_base.py",
        "fun_name": "cls_token",
        "commit_message": "Fix properties of unset special tokens in non verbose mode (#17797)\n\nCo-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>",
        "code": "def cls_token(self) -> str:\n        \n        if self._cls_token is None:\n            if self.verbose:\n                logger.error(\"Using cls_token, but it is not set yet.\")\n            return None\n        return str(self._cls_token)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 80,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 35,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 5765,
        "documentation": {
            "docstring": "\n        `str`: Classification token, to extract a summary of an input sequence leveraging self-attention along the full\n        depth of the model. Log an error if used while not having been set.\n        ",
            "n_words": 30,
            "vocab_size": 27,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 155800,
        "commit_id": "e25284dced9749f02bd5d8c80b6225153aa282d8",
        "repo": "dask",
        "path": "dask/array/creation.py",
        "file_name": "creation.py",
        "fun_name": "eye",
        "commit_message": "Fix eye inconsistency with NumPy for dtype=None (#8669) (#8685)",
        "code": "def eye(N, chunks=\"auto\", M=None, k=0, dtype=float):\n    \n    eye = {}\n    if M is None:\n        M = N\n    if dtype is None:\n        dtype = float\n\n    if not isinstance(chunks, (int, str)):\n        raise ValueError(\"chunks must be an int or string\")\n\n    vchunks, hchunks = normalize_chunks(chunks, shape=(N, M), dtype=dtype)\n    chunks = vchunks[0]\n\n    token = tokenize(N, chunks, M, k, dtype)\n    name_eye = \"eye-\" + token\n\n    for i, vchunk in enumerate(vchunks):\n        for j, hchunk in enumerate(hchunks):\n            if (j - i - 1) * chunks <= k <= (j - i + 1) * chunks:\n                eye[name_eye, i, j] = (\n                    np.eye,\n                    vchunk,\n                    hchunk,\n                    k - (j - i) * chunks,\n                    dtype,\n                )\n            else:\n                eye[name_eye, i, j] = (np.zeros, (vchunk, hchunk), dtype)\n    return Array(eye, name_eye, shape=(N, M), chunks=(chunks, chunks), dtype=dtype)\n\n\n@derived_from(np)",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "@derived_from(np)",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 343,
        "n_words": 121,
        "vocab_size": 80,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 230,
        "n_ast_nodes": 342,
        "n_identifiers": 27,
        "d_id": 36471,
        "documentation": {
            "docstring": "\n    Return a 2-D Array with ones on the diagonal and zeros elsewhere.\n\n    Parameters\n    ----------\n    N : int\n      Number of rows in the output.\n    chunks : int, str\n        How to chunk the array. Must be one of the following forms:\n\n        -   A blocksize like 1000.\n        -   A size in bytes, like \"100 MiB\" which will choose a uniform\n            block-like shape\n        -   The word \"auto\" which acts like the above, but uses a configuration\n            value ``array.chunk-size`` for the chunk size\n    M : int, optional\n      Number of columns in the output. If None, defaults to `N`.\n    k : int, optional\n      Index of the diagonal: 0 (the default) refers to the main diagonal,\n      a positive value refers to an upper diagonal, and a negative value\n      to a lower diagonal.\n    dtype : data-type, optional\n      Data-type of the returned array.\n\n    Returns\n    -------\n    I : Array of shape (N,M)\n      An array where all elements are equal to zero, except for the `k`-th\n      diagonal, whose values are equal to one.\n    ",
            "n_words": 162,
            "vocab_size": 103,
            "n_whitespaces": 295,
            "language": "en"
        }
    },
    {
        "id": 200995,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/annotations/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_null_annotation",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_null_annotation(self):\n        \n        book = Book.objects.annotate(\n            no_value=Value(None, output_field=IntegerField())\n        ).first()\n        self.assertIsNone(book.no_value)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 48,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 39,
        "n_ast_nodes": 66,
        "n_identifiers": 12,
        "d_id": 49839,
        "documentation": {
            "docstring": "\n        Annotating None onto a model round-trips\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 100680,
        "commit_id": "6437cd7ab0d6f18cdca0172ba281fd71967b86ac",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "process",
        "commit_message": "alignments tool - Add from-faces job\n  - Allows user to regenerate alignments file(s) from a folder of extracted faces",
        "code": "def process(self) -> None:\n        \n        logger.info(\"[CREATE ALIGNMENTS FROM FACES]\")  # Tidy up cli output\n        skip_count = 0\n        d_align = {}\n        for filename, meta in tqdm(read_image_meta_batch(self._filelist),\n                                   desc=\"Generating Alignments\",\n                                   total=len(self._filelist),\n                                   leave=False):\n\n            if \"itxt\" not in meta or \"alignments\" not in meta[\"itxt\"]:\n                logger.verbose(\"skipping invalid file: '%s'\", filename)\n                skip_count += 1\n                continue\n\n            align_fname = self._get_alignments_filename(meta[\"itxt\"][\"source\"])\n            source_name, f_idx, alignment = self._extract_alignment(meta)\n            full_info = (f_idx, alignment, filename, meta[\"itxt\"][\"source\"])\n\n            d_align.setdefault(align_fname, {}).setdefault(source_name, []).append(full_info)\n\n        alignments = self._sort_alignments(d_align)\n        self._save_alignments(alignments)\n        if skip_count > 1:\n            logger.warning(\"%s of %s files skipped that do not contain valid alignment data\",\n                           skip_count, len(self._filelist))\n            logger.warning(\"Run the process in verbose mode to see which files were skipped\")\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 405,
        "n_words": 98,
        "vocab_size": 81,
        "complexity": 5,
        "nloc": 23,
        "token_counts": 184,
        "n_ast_nodes": 306,
        "n_identifiers": 29,
        "d_id": 20138,
        "documentation": {
            "docstring": " Run the job to read faces from a folder to create alignments file(s). ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 267516,
        "commit_id": "24d91f552cad2a485f286f3c34cbba2005599ab4",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/become.py",
        "file_name": "become.py",
        "fun_name": "method",
        "commit_message": "ansible-test - Add support for more remotes.",
        "code": "def method(self):  # type: () -> str\n        \n        raise NotImplementedError('Ansible has no built-in doas become plugin.')\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 11,
        "n_ast_nodes": 24,
        "n_identifiers": 3,
        "d_id": 78936,
        "documentation": {
            "docstring": "The name of the Ansible become plugin that is equivalent to this.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 247516,
        "commit_id": "32c828d0f760492711a98b11376e229d795fd1b3",
        "repo": "synapse",
        "path": "tests/rest/media/v1/test_media_storage.py",
        "file_name": "test_media_storage.py",
        "fun_name": "test_disposition_none",
        "commit_message": "Add type hints to `tests/rest`. (#12208)\n\nCo-authored-by: Patrick Cloke <clokep@users.noreply.github.com>",
        "code": "def test_disposition_none(self) -> None:\n        \n        channel = self._req(None)\n\n        headers = channel.headers\n        self.assertEqual(\n            headers.getRawHeaders(b\"Content-Type\"), [self.test_image.content_type]\n        )\n        self.assertEqual(headers.getRawHeaders(b\"Content-Disposition\"), None)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 69,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 55,
        "n_ast_nodes": 90,
        "n_identifiers": 9,
        "d_id": 71709,
        "documentation": {
            "docstring": "\n        If there is no filename, one isn't passed on in the Content-Disposition\n        of the request.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 301193,
        "commit_id": "cf5e21a996818d4273cb107f1de5c91ac69ab4e9",
        "repo": "core",
        "path": "homeassistant/components/wemo/binary_sensor.py",
        "file_name": "binary_sensor.py",
        "fun_name": "is_on",
        "commit_message": "Use properties of wemo Insight device (#72316)",
        "code": "def is_on(self) -> bool:\n        \n        # Note: wemo.get_standby_state is a @property.\n        return super().is_on and self.wemo.get_standby_state == StandbyState.ON\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 37,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 42,
        "n_identifiers": 8,
        "d_id": 100041,
        "documentation": {
            "docstring": "Return true device connected to the Insight Switch is on.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 200451,
        "commit_id": "24f1e7730119fe958cc8e28411f790c9a5ec04eb",
        "repo": "sympy",
        "path": "sympy/stats/random_matrix_models.py",
        "file_name": "random_matrix_models.py",
        "fun_name": "CircularUnitaryEnsemble",
        "commit_message": "Fix various typos\n\nFound via `codespell -q 3 -L aboves,aline,ans,aother,arithmetics,assum,atleast,braket,clen,declar,declars,dorder,dum,enew,fo,fro,inout,iself,ist,ket,lamda,lightyear,lightyears,nd,numer,numers,orderd,ot,pring,rcall,rever,ro,ser,siz,splitted,sring,supercedes,te,tht,unequality,upto,vas,versin,whet`",
        "code": "def CircularUnitaryEnsemble(sym, dim):\n    \n    sym, dim = _symbol_converter(sym), _sympify(dim)\n    model = CircularUnitaryEnsembleModel(sym, dim)\n    rmp = RandomMatrixPSpace(sym, model=model)\n    return RandomMatrixSymbol(sym, dim, dim, pspace=rmp)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 36,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 52,
        "n_ast_nodes": 80,
        "n_identifiers": 11,
        "d_id": 49657,
        "documentation": {
            "docstring": "\n    Represents Circular Unitary Ensembles.\n\n    Examples\n    ========\n\n    >>> from sympy.stats import CircularUnitaryEnsemble as CUE\n    >>> from sympy.stats import joint_eigen_distribution\n    >>> C = CUE('U', 1)\n    >>> joint_eigen_distribution(C)\n    Lambda(t[1], Product(Abs(exp(I*t[_j]) - exp(I*t[_k]))**2, (_j, _k + 1, 1), (_k, 1, 0))/(2*pi))\n\n    Note\n    ====\n\n    As can be seen above in the example, density of CiruclarUnitaryEnsemble\n    is not evaluated because the exact definition is based on haar measure of\n    unitary group which is not unique.\n    ",
            "n_words": 69,
            "vocab_size": 57,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 260151,
        "commit_id": "02cbe01e67165d7d38e5e441cfccd6b57b2207b6",
        "repo": "scikit-learn",
        "path": "sklearn/utils/_param_validation.py",
        "file_name": "_param_validation.py",
        "fun_name": "generate_invalid_param_val",
        "commit_message": "FIX Param validation: fix generating invalid param when 2 interval constraints (#23513)\n\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def generate_invalid_param_val(constraint, constraints=None):\n    \n    if isinstance(constraint, StrOptions):\n        return f\"not {' or '.join(constraint.options)}\"\n\n    if not isinstance(constraint, Interval):\n        raise NotImplementedError\n\n    # constraint is an interval\n    constraints = [constraint] if constraints is None else constraints\n    return _generate_invalid_param_val_interval(constraint, constraints)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 66,
        "n_words": 34,
        "vocab_size": 27,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 50,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 76092,
        "documentation": {
            "docstring": "Return a value that does not satisfy the constraint.\n\n    Raises a NotImplementedError if there exists no invalid value for this constraint.\n\n    This is only useful for testing purpose.\n\n    Parameters\n    ----------\n    constraint : _Constraint instance\n        The constraint to generate a value for.\n\n    constraints : list of _Constraint instances or None, default=None\n        The list of all constraints for this parameter. If None, the list only\n        containing `constraint` is used.\n\n    Returns\n    -------\n    val : object\n        A value that does not satisfy the constraint.\n    ",
            "n_words": 80,
            "vocab_size": 52,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 249552,
        "commit_id": "29269d9d3f3419a3d92cdd80dae4a37e2d99a395",
        "repo": "synapse",
        "path": "tests/storage/databases/main/test_events_worker.py",
        "file_name": "test_events_worker.py",
        "fun_name": "test_invalidate_cache_by_room_id",
        "commit_message": "Fix `have_seen_event` cache not being invalidated (#13863)\n\nFix https://github.com/matrix-org/synapse/issues/13856\r\nFix https://github.com/matrix-org/synapse/issues/13865\r\n\r\n> Discovered while trying to make Synapse fast enough for [this MSC2716 test for importing many batches](https://github.com/matrix-org/complement/pull/214#discussion_r741678240). As an example, disabling the `have_seen_event` cache saves 10 seconds for each `/messages` request in that MSC2716 Complement test because we're not making as many federation requests for `/state` (speeding up `have_seen_event` itself is related to https://github.com/matrix-org/synapse/issues/13625) \r\n> \r\n> But this will also make `/messages` faster in general so we can include it in the [faster `/messages` milestone](https://github.com/matrix-org/synapse/milestone/11).\r\n> \r\n> *-- https://github.com/matrix-org/synapse/issues/13856*\r\n\r\n\r\n### The problem\r\n\r\n`_invalidate_caches_for_event` doesn't run in monolith mode which means we never even tried to clear the `have_seen_event` and other caches. And even in worker mode, it only runs on the workers, not the master (AFAICT).\r\n\r\nAdditionally there was bug with the key being wrong so `_invalidate_caches_for_event` never invalidates the `have_seen_event` cache even when it does run.\r\n\r\nBecause we were using the `@cachedList` wrong, it was putting items in the cache under keys like `((room_id, event_id),)` with a `set` in a `set` (ex. `(('!TnCIJPKzdQdUlIyXdQ:test', '$Iu0eqEBN7qcyF1S9B3oNB3I91v2o5YOgRNPwi_78s-k'),)`) and we we're trying to invalidate with just `(room_id, event_id)` which did nothing.",
        "code": "def test_invalidate_cache_by_room_id(self):\n        \n        with LoggingContext(name=\"test\") as ctx:\n            # Prime the cache with some values\n            res = self.get_success(\n                self.store.have_seen_events(self.room_id, self.event_ids)\n            )\n            self.assertEqual(res, set(self.event_ids))\n\n            # That should result in a single db query to lookup\n            self.assertEqual(ctx.get_resource_usage().db_txn_count, 1)\n\n        # Clear the cache with any events associated with the `room_id`\n        self.store.have_seen_event.invalidate((self.room_id,))\n\n        with LoggingContext(name=\"test\") as ctx:\n            res = self.get_success(\n                self.store.have_seen_events(self.room_id, self.event_ids)\n            )\n            self.assertEqual(res, set(self.event_ids))\n\n            # Since we cleared the cache, it should result in another db query to lookup\n            self.assertEqual(ctx.get_resource_usage().db_txn_count, 1)\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 261,
        "n_words": 75,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 137,
        "n_ast_nodes": 230,
        "n_identifiers": 17,
        "d_id": 72989,
        "documentation": {
            "docstring": "\n        Test to make sure that all events associated with the given `(room_id,)`\n        are invalidated in the `have_seen_event` cache.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 101635,
        "commit_id": "2d312a9db228c025d0bd2ea7a4f747a2c644b5d8",
        "repo": "faceswap",
        "path": "tools/alignments/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "_find_alignments",
        "commit_message": "Minor updates and fixups\n  - Mask Tool - Typing + BiSeNet mask update fix\n  - Alignments Tool - Auto search for alignments file",
        "code": "def _find_alignments(self) -> str:\n        \n        fname = self._args.alignments_file\n        frames = self._args.frames_dir\n        if fname and os.path.isfile(fname) and os.path.splitext(fname)[-1].lower() == \".fsa\":\n            return fname\n        if fname:\n            logger.error(\"Not a valid alignments file: '%s'\", fname)\n            sys.exit(1)\n\n        if not frames or not os.path.exists(frames):\n            logger.error(\"Not a valid frames folder: '%s'. Can't scan for alignments.\", frames)\n            sys.exit(1)\n\n        fname = \"alignments.fsa\"\n        if os.path.isdir(frames) and os.path.exists(os.path.join(frames, fname)):\n            return fname\n\n        if os.path.isdir(frames) or os.path.splitext(frames)[-1] not in _video_extensions:\n            logger.error(\"Can't find a valid alignments file in location: %s\", frames)\n            sys.exit(1)\n\n        fname = f\"{os.path.splitext(frames)[0]}_{fname}\"\n        if not os.path.exists(fname):\n            logger.error(\"Can't find a valid alignments file for video: %s\", frames)\n            sys.exit(1)\n\n        return fname\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 289,
        "n_words": 95,
        "vocab_size": 50,
        "complexity": 12,
        "nloc": 32,
        "token_counts": 204,
        "n_ast_nodes": 360,
        "n_identifiers": 21,
        "d_id": 21043,
        "documentation": {
            "docstring": " If an alignments folder is required and hasn't been provided, scan for a file based on\n        the video folder.\n\n        Exits if an alignments file cannot be located\n\n        Returns\n        -------\n        str\n            The full path to an alignments file\n        ",
            "n_words": 37,
            "vocab_size": 31,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 154793,
        "commit_id": "027f92a7655ae5b473839b7956ff52bf7879f3cc",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "_has_arrow_table",
        "commit_message": "FIX-#4022: Fixed empty data frame with index (#4910)\n\nSigned-off-by: Andrey Pavlenko <andrey.a.pavlenko@gmail.com>",
        "code": "def _has_arrow_table(self):\n        \n        if not isinstance(self._op, FrameNode):\n            return False\n        return all(p.arrow_table is not None for p in self._partitions.flatten())\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 49,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 63,
        "n_identifiers": 10,
        "d_id": 36150,
        "documentation": {
            "docstring": "\n        Return True for materialized frame with Arrow table.\n\n        Returns\n        -------\n        bool\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 76338,
        "commit_id": "1838fbfb1a720e0a286c989dbdea03dfde6af4a5",
        "repo": "wagtail",
        "path": "wagtail/admin/templatetags/wagtailadmin_tags.py",
        "file_name": "wagtailadmin_tags.py",
        "fun_name": "message_level_tag",
        "commit_message": "Prevent custom MESSAGE_TAGS settings from leaking into admin styles\n\nFixes a test failure against Django main.\n\nIn #2552, a fix was applied to ensure that the project-level MESSAGE_TAGS setting was ignored, allowing end-users to customise that setting for their own projects without it leaking into Wagtail admin styles.\n\nUnfortunately, the test was flawed (or was broken in a Django regression at some point): in Django <=4.0, MESSAGE_TAGS was not affected by override_settings after the first request, which meant that unless the test was run in isolation, the custom classname that was supposed to flag up the problem never got applied, and the test always succeeded.\n\nThe change to SVG icons broke the intent of #2552, since it used message.level_tag for the icon's classname (and this picks up MESSAGE_TAGS customisations), but due to the broken test this went unnoticed.\n\nhttps://github.com/django/django/commit/24b316536a7ee4c54a54f632de1852aecb4038c0 fixed the override_settings behaviour, making the test fail as it should have done long ago.\n\nHere we adjust the test to not rely on override_settings (so that it does what it's supposed to do on all Django versions), fix a test that gets broken as a side effect (because it's unnecessarily checking message.level_tag), and fixes our SVG-icon-powered message include to bypass the MESSAGE_TAGS setting like the old implementation did.\n\nConfusing? Yes.",
        "code": "def message_level_tag(message):\n    \n    return MESSAGE_TAGS.get(message.level)\n\n\n@register.simple_tag",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@register.simple_tag",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 10,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 15,
        "n_ast_nodes": 34,
        "n_identifiers": 7,
        "d_id": 16502,
        "documentation": {
            "docstring": "\n    Return the tag for this message's level as defined in\n    django.contrib.messages.constants.DEFAULT_TAGS, ignoring the project-level\n    MESSAGE_TAGS setting (which end-users might customise).\n    ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 269606,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "_has_nchw_support",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _has_nchw_support():\n    \n    explicitly_on_cpu = _is_current_explicit_device(\"CPU\")\n    gpus_available = bool(_get_available_gpus())\n    return not explicitly_on_cpu and gpus_available\n\n\n# VARIABLE MANIPULATION\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 27,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 47,
        "n_identifiers": 6,
        "d_id": 80226,
        "documentation": {
            "docstring": "Check whether the current scope supports NCHW ops.\n\n    TensorFlow does not support NCHW on CPU. Therefore we check if we are not\n    explicitly put on\n    CPU, and have GPUs available. In this case there will be soft-placing on the\n    GPU device.\n\n    Returns:\n        bool: if the current scope device placement would support nchw\n    ",
            "n_words": 52,
            "vocab_size": 41,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 221659,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/configparser.py",
        "file_name": "configparser.py",
        "fun_name": "write",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def write(self, fp, space_around_delimiters=True):\n        \n        if space_around_delimiters:\n            d = \" {} \".format(self._delimiters[0])\n        else:\n            d = self._delimiters[0]\n        if self._defaults:\n            self._write_section(fp, self.default_section,\n                                    self._defaults.items(), d)\n        for section in self._sections:\n            self._write_section(fp, section,\n                                self._sections[section].items(), d)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 174,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 91,
        "n_ast_nodes": 140,
        "n_identifiers": 13,
        "d_id": 56462,
        "documentation": {
            "docstring": "Write an .ini-format representation of the configuration state.\n\n        If `space_around_delimiters' is True (the default), delimiters\n        between keys and values are surrounded by spaces.\n\n        Please note that comments in the original configuration file are not\n        preserved when writing the configuration back.\n        ",
            "n_words": 40,
            "vocab_size": 35,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 215733,
        "commit_id": "3bb43882e727b1d36abe2e501759c9c5e9048ecf",
        "repo": "salt",
        "path": "tests/pytests/unit/utils/win_dacl/test_get_name.py",
        "file_name": "test_get_name.py",
        "fun_name": "test_get_name_mixed_case",
        "commit_message": "Add tests, migrate some tests to pytest",
        "code": "def test_get_name_mixed_case():\n    \n    result = salt.utils.win_dacl.get_name(\"adMiniStrAtorS\")\n    expected = \"Administrators\"\n    assert result == expected\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 24,
        "n_words": 12,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 46,
        "n_identifiers": 7,
        "d_id": 54127,
        "documentation": {
            "docstring": "\n    Test get_name when passing an account name with mixed case characters\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 169679,
        "commit_id": "b48a73ff53a2c3414e38f5adf11f661dd7883cd1",
        "repo": "pandas",
        "path": "pandas/tests/io/test_stata.py",
        "file_name": "test_stata.py",
        "fun_name": "test_non_categorical_value_label_convert_categoricals_error",
        "commit_message": "TST: use `with` where possible instead of manual `close` (#48931)\n\nCoincidentally fixes some StataReaders being left open in tests.",
        "code": "def test_non_categorical_value_label_convert_categoricals_error():\n    # Mapping more than one value to the same label is valid for Stata\n    # labels, but can't be read with convert_categoricals=True\n    value_labels = {\n        \"repeated_labels\": {10: \"Ten\", 20: \"More than ten\", 40: \"More than ten\"}\n    }\n\n    data = DataFrame(\n        {\n            \"repeated_labels\": [10, 10, 20, 20, 40, 40],\n        }\n    )\n\n    with tm.ensure_clean() as path:\n        data.to_stata(path, value_labels=value_labels)\n\n        with StataReader(path, convert_categoricals=False) as reader:\n            reader_value_labels = reader.value_labels()\n        assert reader_value_labels == value_labels\n\n        col = \"repeated_labels\"\n        repeats = \"-\" * 80 + \"\\n\" + \"\\n\".join([\"More than ten\"])\n\n        msg = f\n        with pytest.raises(ValueError, match=msg):\n            read_stata(path, convert_categoricals=True)\n\n\n@pytest.mark.parametrize(\"version\", [114, 117, 118, 119, None])\n@pytest.mark.parametrize(\n    \"dtype\",\n    [\n        pd.BooleanDtype,\n        pd.Int8Dtype,\n        pd.Int16Dtype,\n        pd.Int32Dtype,\n        pd.Int64Dtype,\n        pd.UInt8Dtype,\n        pd.UInt16Dtype,\n        pd.UInt32Dtype,\n        pd.UInt64Dtype,\n    ],\n)",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"version\", [114, 117, 118, 119, None])\n@pytest.mark.parametrize(\n    \"dtype\",\n    [\n        pd.BooleanDtype,\n        pd.Int8Dtype,\n        pd.Int16Dtype,\n        pd.Int32Dtype,\n        pd.Int64Dtype,\n        pd.UInt8Dtype,\n        pd.UInt16Dtype,\n        pd.UInt32Dtype,\n        pd.UInt64Dtype,\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 304,
        "n_words": 112,
        "vocab_size": 90,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 131,
        "n_ast_nodes": 334,
        "n_identifiers": 33,
        "d_id": 40445,
        "documentation": {
            "docstring": "\nValue labels for column {col} are not unique. These cannot be converted to\npandas categoricals.\n\nEither read the file with `convert_categoricals` set to False or use the\nlow level interface in `StataReader` to separately read the values and the\nvalue_labels.\n\nThe repeated labels are:\n{repeats}\n",
            "n_words": 45,
            "vocab_size": 38,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 82019,
        "commit_id": "cfce31419d6fa5155e87f0d3faddd713e12210a2",
        "repo": "awx",
        "path": "awx/main/utils/common.py",
        "file_name": "common.py",
        "fun_name": "memoize",
        "commit_message": "Move the IS_TESTING method out of settings",
        "code": "def memoize(ttl=60, cache_key=None, track_function=False, cache=None):\n    \n    if cache_key and track_function:\n        raise IllegalArgumentError(\"Can not specify cache_key when track_function is True\")\n    cache = cache or get_memoize_cache()\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 39,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 41,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 17296,
        "documentation": {
            "docstring": "\n    Decorator to wrap a function and cache its result.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 10921,
        "commit_id": "13edc16d806fb5d77a6849551178ccc75937f25f",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/base.py",
        "file_name": "base.py",
        "fun_name": "mixin_base_ppr_parser",
        "commit_message": "refactor: rename pod to deployment (#4230)\n\n* refactor: rename pod to deployment\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: undo daemon mistake\r\n\r\n* refactor: leftover cleanup\r\n\r\n* fix: more test fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more tests\r\n\r\n* fix: fix more tests\r\n\r\n* refactor: fix more tests\r\n\r\n* refactor: more tests fixes\r\n\r\n* refactor: rename pea to pod\r\n\r\n* refactor: adjust docs\r\n\r\n* refactor: complete pea renaming\r\n\r\n* refactor: more fixes\r\n\r\n* fix: pea_type in k8s yamls\r\n\r\n* fix: adjust pod args name\r\n\r\n* refactor: rename peapods parser folder\r\n\r\n* fix: da init\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>",
        "code": "def mixin_base_ppr_parser(parser):\n    \n\n    gp = add_arg_group(parser, title='Essential')\n    gp.add_argument(\n        '--name',\n        type=str,\n        help=,\n    )\n\n    gp.add_argument(\n        '--workspace',\n        type=str,\n        help='The working directory for any IO operations in this object. '\n        'If not set, then derive from its parent `workspace`.',\n    )\n\n    from jina import __resources_path__\n\n    gp.add_argument(\n        '--log-config',\n        type=str,\n        default=os.path.join(__resources_path__, 'logging.default.yml'),\n        help='The YAML config of the logger used in this object.',\n    )\n\n    gp.add_argument(\n        '--quiet',\n        action='store_true',\n        default=False,\n        help='If set, then no log will be emitted from this object.',\n    )\n\n    gp.add_argument(\n        '--quiet-error',\n        action='store_true',\n        default=False,\n        help='If set, then exception stack information will not be added to the log',\n    )\n\n    gp.add_argument(\n        '--workspace-id',\n        type=str,\n        default=random_identity(),\n        help='the UUID for identifying the workspace. When not given a random id will be assigned.'\n        'Multiple Pod/Deployment/Flow will work under the same workspace if they share the same '\n        '`workspace-id`.'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    parser.add_argument(\n        '--extra-search-paths',\n        type=str,\n        default=[],\n        nargs='*',\n        help='Extra search paths to be used when loading modules and finding YAML config files.'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    gp.add_argument(\n        '--timeout-ctrl',\n        type=int,\n        default=int(os.getenv('JINA_DEFAULT_TIMEOUT_CTRL', '60')),\n        help='The timeout in milliseconds of the control request, -1 for waiting forever',\n    )\n\n    parser.add_argument(\n        '--k8s-namespace',\n        type=str,\n        help='Name of the namespace where Kubernetes deployment should be deployed, to be filled by flow name'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    gp.add_argument(\n        '--k8s-disable-connection-pool',\n        action='store_false',\n        dest='k8s_connection_pool',\n        default=True,\n        help='Defines if connection pooling for replicas should be disabled in K8s. This mechanism implements load balancing between replicas of the same executor. This should be disabled if a service mesh (like istio) is used for load balancing.'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    gp.add_argument(\n        '--polling',\n        type=str,\n        default=PollingType.ANY.name,\n        help=,\n    )\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 700,
        "n_words": 247,
        "vocab_size": 147,
        "complexity": 5,
        "nloc": 99,
        "token_counts": 278,
        "n_ast_nodes": 461,
        "n_identifiers": 27,
        "d_id": 1996,
        "documentation": {
            "docstring": "Mixing in arguments required by pod/deployment/runtime module into the given parser.\n    :param parser: the parser instance to which we add arguments\n    \nThe name of this object.\n\nThis will be used in the following places:\n- how you refer to this object in Python/YAML/CLI\n- visualization\n- log message header\n- ...\n\nWhen not given, then the default naming strategy will apply.\n                    \n    The polling strategy of the Deployment and its endpoints (when `shards>1`).\n    Can be defined for all endpoints of a Deployment or by endpoint.\n    Define per Deployment:\n    - ANY: only one (whoever is idle) Pod polls the message\n    - ALL: all Pods poll the message (like a broadcast)\n    Define per Endpoint:\n    JSON dict, {endpoint: PollingType}\n    {'/custom': 'ALL', '/search': 'ANY', '*': 'ANY'}\n    \n    ",
            "n_words": 121,
            "vocab_size": 90,
            "n_whitespaces": 172,
            "language": "en"
        }
    },
    {
        "id": 259424,
        "commit_id": "d14fd82cf423c21ab6d01f7d0430083f9d7026be",
        "repo": "scikit-learn",
        "path": "sklearn/decomposition/_fastica.py",
        "file_name": "_fastica.py",
        "fun_name": "transform",
        "commit_message": "ENH Preserving dtypes for ICA (#22806)\n\n\r\n\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def transform(self, X, copy=True):\n        \n        check_is_fitted(self)\n\n        X = self._validate_data(\n            X, copy=(copy and self._whiten), dtype=[np.float64, np.float32], reset=False\n        )\n        if self._whiten:\n            X -= self.mean_\n\n        return np.dot(X, self.components_.T)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 88,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 73,
        "n_ast_nodes": 110,
        "n_identifiers": 16,
        "d_id": 75763,
        "documentation": {
            "docstring": "Recover the sources from X (apply the unmixing matrix).\n\n        Parameters\n        ----------\n        X : array-like of shape (n_samples, n_features)\n            Data to transform, where `n_samples` is the number of samples\n            and `n_features` is the number of features.\n\n        copy : bool, default=True\n            If False, data passed to fit can be overwritten. Defaults to True.\n\n        Returns\n        -------\n        X_new : ndarray of shape (n_samples, n_components)\n            Estimated sources obtained by transforming the data with the\n            estimated unmixing matrix.\n        ",
            "n_words": 72,
            "vocab_size": 52,
            "n_whitespaces": 183,
            "language": "en"
        }
    },
    {
        "id": 166591,
        "commit_id": "e9350a4affbb424aaecad279f638a0dd1584df68",
        "repo": "pandas",
        "path": "pandas/tseries/frequencies.py",
        "file_name": "frequencies.py",
        "fun_name": "get_freq",
        "commit_message": "infer_freq handle non-nano (#47126)\n\n* infer_freq handle non-nano\r\n\r\n* remove unused import",
        "code": "def get_freq(self) -> str | None:\n        \n        if not self.is_monotonic or not self.index._is_unique:\n            return None\n\n        delta = self.deltas[0]\n        ppd = periods_per_day(self._reso)\n        if delta and _is_multiple(delta, ppd):\n            return self._infer_daily_rule()\n\n        # Business hourly, maybe. 17: one day / 65: one weekend\n        if self.hour_deltas in ([1, 17], [1, 65], [1, 17, 65]):\n            return \"BH\"\n\n        # Possibly intraday frequency.  Here we use the\n        # original .asi8 values as the modified values\n        # will not work around DST transitions.  See #8772\n        if not self.is_unique_asi8:\n            return None\n\n        delta = self.deltas_asi8[0]\n        pph = ppd // 24\n        ppm = pph // 60\n        pps = ppm // 60\n        if _is_multiple(delta, pph):\n            # Hours\n            return _maybe_add_count(\"H\", delta / pph)\n        elif _is_multiple(delta, ppm):\n            # Minutes\n            return _maybe_add_count(\"T\", delta / ppm)\n        elif _is_multiple(delta, pps):\n            # Seconds\n            return _maybe_add_count(\"S\", delta / pps)\n        elif _is_multiple(delta, (pps // 1000)):\n            # Milliseconds\n            return _maybe_add_count(\"L\", delta / (pps // 1000))\n        elif _is_multiple(delta, (pps // 1_000_000)):\n            # Microseconds\n            return _maybe_add_count(\"U\", delta / (pps // 1_000_000))\n        else:\n            # Nanoseconds\n            return _maybe_add_count(\"N\", delta)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 487,
        "n_words": 162,
        "vocab_size": 94,
        "complexity": 12,
        "nloc": 35,
        "token_counts": 210,
        "n_ast_nodes": 367,
        "n_identifiers": 20,
        "d_id": 39834,
        "documentation": {
            "docstring": "\n        Find the appropriate frequency string to describe the inferred\n        frequency of self.i8values\n\n        Returns\n        -------\n        str or None\n        ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 126641,
        "commit_id": "f6d19ac7c03b12bbf839824381376e228d0fffad",
        "repo": "ray",
        "path": "python/ray/serve/_private/utils.py",
        "file_name": "utils.py",
        "fun_name": "guarded_deprecation_warning",
        "commit_message": "[Serve] Gate the deprecation warnings behind envvar (#27479)",
        "code": "def guarded_deprecation_warning(*args, **kwargs):\n    \n    if os.environ.get(\"SERVE_WARN_V1_DEPRECATIONS\", \"0\") == \"1\":\n        from ray._private.utils import deprecated\n\n        return deprecated(*args, **kwargs)\n    else:\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 39,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 75,
        "n_identifiers": 10,
        "d_id": 28208,
        "documentation": {
            "docstring": "Wrapper for deprecation warnings, guarded by a flag.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 188798,
        "commit_id": "9a95d8b0c26bdaea17ea9264ab45e8a81b6422f0",
        "repo": "calibre",
        "path": "src/calibre/gui2/preferences/create_custom_column.py",
        "file_name": "create_custom_column.py",
        "fun_name": "current_headings",
        "commit_message": "More CreateNewCustomColumn stuff.\n- Improved documentation\n- Check column headings for duplicates\n- Method to return the current column headings as a dict\n- Improved exception handling",
        "code": "def current_headings(self):\n        \n        return {v['name']:('#' + v['label']) for v in self.custcols.values()}\n",
        "url": "https://github.com/kovidgoyal/calibre.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 32,
        "n_ast_nodes": 57,
        "n_identifiers": 5,
        "d_id": 45934,
        "documentation": {
            "docstring": "\n        Return the currently defined column headings\n\n        Return the column headings including the ones that haven't yet been\n        created. It is a dict. The key is the heading, the value is the lookup\n        name having that heading.\n        ",
            "n_words": 36,
            "vocab_size": 25,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 181829,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/base.py",
        "file_name": "base.py",
        "fun_name": "_generate",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def _generate(self, pset, min_, max_, condition, type_=None):\n        \n        if type_ is None:\n            type_ = pset.ret\n        expr = []\n        height = np.random.randint(min_, max_)\n        stack = [(0, type_)]\n        while len(stack) != 0:\n            depth, type_ = stack.pop()\n\n            # We've added a type_ parameter to the condition function\n            if condition(height, depth, type_):\n                try:\n                    term = np.random.choice(pset.terminals[type_])\n                except IndexError:\n                    _, _, traceback = sys.exc_info()\n                    raise IndexError(\n                        \"The gp.generate function tried to add \"\n                        \"a terminal of type {}, but there is\"\n                        \"none available. {}\".format(type_, traceback)\n                    )\n                if inspect.isclass(term):\n                    term = term()\n                expr.append(term)\n            else:\n                try:\n                    prim = np.random.choice(pset.primitives[type_])\n                except IndexError:\n                    _, _, traceback = sys.exc_info()\n                    raise IndexError(\n                        \"The gp.generate function tried to add \"\n                        \"a primitive of type {}, but there is\"\n                        \"none available. {}\".format(type_, traceback)\n                    )\n                expr.append(prim)\n                for arg in reversed(prim.args):\n                    stack.append((depth + 1, arg))\n        return expr\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 683,
        "n_words": 131,
        "vocab_size": 83,
        "complexity": 8,
        "nloc": 35,
        "token_counts": 221,
        "n_ast_nodes": 357,
        "n_identifiers": 34,
        "d_id": 43607,
        "documentation": {
            "docstring": "Generate a Tree as a list of lists.\n\n        The tree is build from the root to the leaves, and it stop growing when\n        the condition is fulfilled.\n\n        Parameters\n        ----------\n        pset: PrimitiveSetTyped\n            Primitive set from which primitives are selected.\n        min_: int\n            Minimum height of the produced trees.\n        max_: int\n            Maximum height of the produced trees.\n        condition: function\n            The condition is a function that takes two arguments,\n            the height of the tree to build and the current\n            depth in the tree.\n        type_: class\n            The type that should return the tree when called, when\n            :obj:None (default) no return type is enforced.\n\n        Returns\n        -------\n        individual: list\n            A grown tree with leaves at possibly different depths\n            depending on the condition function.\n        ",
            "n_words": 116,
            "vocab_size": 75,
            "n_whitespaces": 317,
            "language": "en"
        }
    },
    {
        "id": 19917,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/metadata/base.py",
        "file_name": "base.py",
        "fun_name": "installed_by_distutils",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def installed_by_distutils(self) -> bool:\n        \n        info_location = self.info_location\n        if not info_location:\n            return False\n        return pathlib.Path(info_location).is_file()\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 53,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 30,
        "n_ast_nodes": 52,
        "n_identifiers": 7,
        "d_id": 3148,
        "documentation": {
            "docstring": "Whether this distribution is installed with legacy distutils format.\n\n        A distribution installed with \"raw\" distutils not patched by setuptools\n        uses one single file at ``info_location`` to store metadata. We need to\n        treat this specially on uninstallation.\n        ",
            "n_words": 36,
            "vocab_size": 30,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 119709,
        "commit_id": "e262c72b195d4f6b31d9b45c18a23a53d22be85c",
        "repo": "jax",
        "path": "jax/_src/numpy/lax_numpy.py",
        "file_name": "lax_numpy.py",
        "fun_name": "_view",
        "commit_message": "remove `_check_user_dtype_supported` from public `jax.lax` module",
        "code": "def _view(arr, dtype=None, type=None):\n  lax_internal._check_user_dtype_supported(dtype, \"view\")\n  if type is not None:\n    raise NotImplementedError(\"`type` argument of array.view()\")\n  if dtype is None:\n    return arr\n  arr_dtype = _dtype(arr)\n  if arr_dtype == dtype:\n    return arr\n  # bool is implemented as lax:PRED, which is not compatible with lax.bitcast_convert_type.\n  # We work around this by casting bool to uint8.\n  if arr_dtype == bool_:\n    arr = arr.astype(uint8)\n  nbits_in = 8 * arr_dtype.itemsize\n  nbits_out = 8 * np.dtype(dtype).itemsize\n  if nbits_in == nbits_out:\n    if dtype == bool_:\n      return lax.bitcast_convert_type(arr, uint8).astype(dtype)\n    return lax.bitcast_convert_type(arr, dtype)\n  if nbits_out > nbits_in and (shape(arr)[-1] * nbits_in) % nbits_out != 0:\n    raise ValueError(\"When changing to a larger dtype, its size must be a divisor \"\n                     \"of the total size in bytes of the last axis of the array.\")\n  byte_dtypes = {8: uint8, 16: uint16, 32: uint32, 64: uint64}\n  if nbits_in not in byte_dtypes:\n    raise NotImplementedError(f\"arr.view() for arr.dtype={arr_dtype}\")\n  if nbits_out not in byte_dtypes:\n    raise NotImplementedError(f\"arr.view(dtype) for dtype={dtype}\")\n  dt_in = byte_dtypes[nbits_in]\n  dt_out = byte_dtypes[nbits_out]\n  arr_bytes = lax.bitcast_convert_type(arr, dt_in)\n  if nbits_in < nbits_out:\n    arr_bytes = arr_bytes.reshape(arr.shape[:-1] + (-1, nbits_out // nbits_in)).astype(dt_out)\n    shifts = expand_dims(arange(0, nbits_out, nbits_in, dtype=dt_out), tuple(range(arr_bytes.ndim - 1)))\n    arr_bytes = (arr_bytes << shifts).sum(-1).astype(dt_out)\n  else:\n    shifts = lax.expand_dims(arange(0, nbits_in, nbits_out, dtype=dt_in), tuple(range(arr_bytes.ndim)))\n    arr_bytes = ((arr_bytes[..., newaxis] >> shifts) & iinfo(dt_out).max).astype(dt_out)\n    arr_bytes = arr_bytes.reshape(arr_bytes.shape[:-2] + (-1,))\n  if dtype == bool_:\n    return lax.bitcast_convert_type(arr_bytes, uint8).astype(dtype)\n  return lax.bitcast_convert_type(arr_bytes, dtype)\n\n### track unimplemented functions\n\n_NOT_IMPLEMENTED_DESC = \n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 317,
        "n_words": 224,
        "vocab_size": 135,
        "complexity": 13,
        "nloc": 39,
        "token_counts": 391,
        "n_ast_nodes": 632,
        "n_identifiers": 39,
        "d_id": 26669,
        "documentation": {
            "docstring": "\n*** This function is not yet implemented by jax.numpy, and will raise NotImplementedError ***\n",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 101189,
        "commit_id": "a2de4a97985dc62db3b140a924aeac2be733abf8",
        "repo": "faceswap",
        "path": "lib/align/aligned_face.py",
        "file_name": "aligned_face.py",
        "fun_name": "_get_offset",
        "commit_message": "lib.align.aligned_face updates\n  - Typing\n  - Legacy support for pre-aligned faces\n  - Coverage support for pre-aligned faces\n  - Standardized retrieval of sub-crops",
        "code": "def _get_offset(self) -> Dict[CenteringType, np.ndarray]:\n        \n        offset: Dict[CenteringType, np.ndarray] = dict(legacy=np.array([0.0, 0.0]))\n        points: Dict[Literal[\"face\", \"head\"], Tuple[float, ...]] = dict(head=(0.0, 0.0, -2.3),\n                                                                        face=(0.0, -1.5, 4.2))\n\n        for key, pnts in points.items():\n            center = cv2.projectPoints(np.array([pnts]).astype(\"float32\"),\n                                       self._rotation,\n                                       self._translation,\n                                       self._camera_matrix,\n                                       self._distortion_coefficients)[0].squeeze()\n            logger.trace(\"center %s: %s\", key, center)  # type: ignore\n            offset[key] = center - (0.5, 0.5)\n        logger.trace(\"offset: %s\", offset)  # type: ignore\n        return offset\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 357,
        "n_words": 57,
        "vocab_size": 47,
        "complexity": 2,
        "nloc": 22,
        "token_counts": 190,
        "n_ast_nodes": 258,
        "n_identifiers": 30,
        "d_id": 20610,
        "documentation": {
            "docstring": " Obtain the offset between the original center of the extracted face to the new center\n        of the head in 2D space.\n\n        Returns\n        -------\n        :class:`numpy.ndarray`\n            The x, y offset of the new center from the old center.\n        ",
            "n_words": 36,
            "vocab_size": 24,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 108279,
        "commit_id": "e8006163923564ea04f745a289e079b80afc6db8",
        "repo": "matplotlib",
        "path": "lib/matplotlib/font_manager.py",
        "file_name": "font_manager.py",
        "fun_name": "list_fonts",
        "commit_message": "skip sub directories when finding fonts on windows\n\nCloses #22859\n\nCo-authored-by: Tim Hoffmann <2836374+timhoffm@users.noreply.github.com>",
        "code": "def list_fonts(directory, extensions):\n    \n    extensions = [\".\" + ext for ext in extensions]\n    if sys.platform == 'win32' and directory == win32FontDirectory():\n        return [os.path.join(directory, filename)\n                for filename in os.listdir(directory)\n                if os.path.isfile(filename)]\n    else:\n        return [os.path.join(dirpath, filename)\n                # os.walk ignores access errors, unlike Path.glob.\n                for dirpath, _, filenames in os.walk(directory)\n                for filename in filenames\n                if Path(filename).suffix.lower() in extensions]\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 170,
        "n_words": 54,
        "vocab_size": 38,
        "complexity": 9,
        "nloc": 11,
        "token_counts": 108,
        "n_ast_nodes": 170,
        "n_identifiers": 20,
        "d_id": 23132,
        "documentation": {
            "docstring": "\n    Return a list of all fonts matching any of the extensions, found\n    recursively under the directory.\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 142091,
        "commit_id": "5fb61abba3f583a1aa080623623af0b79de9e3f3",
        "repo": "ray",
        "path": "python/ray/tests/test_usage_stats.py",
        "file_name": "test_usage_stats.py",
        "fun_name": "test_usage_lib_get_cluster_config_to_report",
        "commit_message": "[Usage Stats][Hotfix] Import usage reported from workers. (#25785)\n\n## Why are these changes needed?\r\n\r\nWe currently only record usage stats from drivers. This can lose some of information when libraries are imported from workers (e.g., doing some rllib import from trainable).\r\n\r\n@jjyao just for the future reference.",
        "code": "def test_usage_lib_get_cluster_config_to_report(monkeypatch, tmp_path, reset_lib_usage):\n    cluster_config_file_path = tmp_path / \"ray_bootstrap_config.yaml\"\n    \n    cluster_config_file_path.write_text(\n        \n    )\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        cluster_config_file_path\n    )\n    assert cluster_config_to_report.cloud_provider == \"aws\"\n    assert cluster_config_to_report.min_workers is None\n    assert cluster_config_to_report.max_workers == 1\n    assert cluster_config_to_report.head_node_instance_type is None\n    assert cluster_config_to_report.worker_node_instance_types is None\n\n    cluster_config_file_path.write_text(\n        \n    )\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        cluster_config_file_path\n    )\n    assert cluster_config_to_report.cloud_provider == \"gcp\"\n    assert cluster_config_to_report.min_workers == 1\n    assert cluster_config_to_report.max_workers is None\n    assert cluster_config_to_report.head_node_instance_type == \"m5.large\"\n    assert cluster_config_to_report.worker_node_instance_types == list(\n        {\"m3.large\", \"Standard_D2s_v3\", \"n1-standard-2\"}\n    )\n\n    cluster_config_file_path.write_text(\n        \n    )\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        cluster_config_file_path\n    )\n    assert cluster_config_to_report.cloud_provider is None\n    assert cluster_config_to_report.min_workers is None\n    assert cluster_config_to_report.max_workers is None\n    assert cluster_config_to_report.head_node_instance_type is None\n    assert cluster_config_to_report.worker_node_instance_types == [\"m5.large\"]\n\n    cluster_config_file_path.write_text(\"[invalid\")\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        cluster_config_file_path\n    )\n    assert cluster_config_to_report == ClusterConfigToReport()\n\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        tmp_path / \"does_not_exist.yaml\"\n    )\n    assert cluster_config_to_report == ClusterConfigToReport()\n\n    monkeypatch.setenv(\"KUBERNETES_SERVICE_HOST\", \"localhost\")\n    cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(\n        tmp_path / \"does_not_exist.yaml\"\n    )\n    assert cluster_config_to_report.cloud_provider == \"kubernetes\"\n    assert cluster_config_to_report.min_workers is None\n    assert cluster_config_to_report.max_workers is None\n    assert cluster_config_to_report.head_node_instance_type is None\n    assert cluster_config_to_report.worker_node_instance_types is None\n\n\n@pytest.mark.skipif(\n    sys.platform == \"win32\",\n    reason=\"Test depends on runtime env feature not supported on Windows.\",\n)",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.skipif(\n    sys.platform == \"win32\",\n    reason=\"Test depends on runtime env feature not supported on Windows.\",\n)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 371,
        "n_words": 159,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 99,
        "token_counts": 242,
        "n_ast_nodes": 441,
        "n_identifiers": 23,
        "d_id": 32589,
        "documentation": {
            "docstring": " Test minimal cluster config\ncluster_name: minimal\nmax_workers: 1\nprovider:\n    type: aws\n    region: us-west-2\n    availability_zone: us-west-2a\n\ncluster_name: full\nmin_workers: 1\nprovider:\n    type: gcp\nhead_node_type: head_node\navailable_node_types:\n    head_node:\n        node_config:\n            InstanceType: m5.large\n        min_workers: 0\n        max_workers: 0\n    aws_worker_node:\n        node_config:\n            InstanceType: m3.large\n        min_workers: 0\n        max_workers: 0\n    azure_worker_node:\n        node_config:\n            azure_arm_parameters:\n                vmSize: Standard_D2s_v3\n    gcp_worker_node:\n        node_config:\n            machineType: n1-standard-2\n\ncluster_name: full\nhead_node_type: head_node\navailable_node_types:\n    worker_node_1:\n        node_config:\n            ImageId: xyz\n    worker_node_2:\n        resources: {}\n    worker_node_3:\n        node_config:\n            InstanceType: m5.large\n",
            "n_words": 66,
            "vocab_size": 41,
            "n_whitespaces": 246,
            "language": "en"
        }
    },
    {
        "id": 110019,
        "commit_id": "1068a6faa19767724437461bcfb88c6852ec435c",
        "repo": "matplotlib",
        "path": "lib/matplotlib/contour.py",
        "file_name": "contour.py",
        "fun_name": "_process_contour_level_args",
        "commit_message": "Remove unnecessary np.{,as}array / astype calls.\n\nQuite often numpy will call asarray for us, saving us the need to call\nasarray explicitly.\n\nWhen we do call asarray (or array) ourselves, a dtype can directly be\npassed in, rather than immediately calling astype immediately after.\nPassing the dtype makes it unnecessary for asarray to infer the dtype\nof the passed-in container, and can also save an extra array allocation\nif asarray first has to allocate an array of a type and astype\nimmediately has to allocate an array of another type.",
        "code": "def _process_contour_level_args(self, args):\n        \n        if self.levels is None:\n            if len(args) == 0:\n                levels_arg = 7  # Default, hard-wired.\n            else:\n                levels_arg = args[0]\n        else:\n            levels_arg = self.levels\n        if isinstance(levels_arg, Integral):\n            self.levels = self._autolev(levels_arg)\n        else:\n            self.levels = np.asarray(levels_arg, np.float64)\n\n        if not self.filled:\n            inside = (self.levels > self.zmin) & (self.levels < self.zmax)\n            levels_in = self.levels[inside]\n            if len(levels_in) == 0:\n                self.levels = [self.zmin]\n                _api.warn_external(\n                    \"No contour levels were found within the data range.\")\n\n        if self.filled and len(self.levels) < 2:\n            raise ValueError(\"Filled contours require at least 2 levels.\")\n\n        if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0:\n            raise ValueError(\"Contour levels must be increasing\")\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 342,
        "n_words": 96,
        "vocab_size": 66,
        "complexity": 10,
        "nloc": 23,
        "token_counts": 185,
        "n_ast_nodes": 299,
        "n_identifiers": 22,
        "d_id": 23889,
        "documentation": {
            "docstring": "\n        Determine the contour levels and store in self.levels.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 75124,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/tests/test_admin_views.py",
        "file_name": "test_admin_views.py",
        "fun_name": "test_delete_post",
        "commit_message": "Reformat with black",
        "code": "def test_delete_post(self):\n        \n        # Send request\n        response = self.client.post(\n            reverse(\"wagtailimages:delete_multiple\", args=(self.image.id,))\n        )\n\n        # Check response\n        self.assertEqual(response.status_code, 200)\n        self.assertEqual(response[\"Content-Type\"], \"application/json\")\n\n        # Make sure the image is deleted\n        self.assertFalse(Image.objects.filter(id=self.image.id).exists())\n\n        # Check JSON\n        response_json = json.loads(response.content.decode())\n        self.assertIn(\"image_id\", response_json)\n        self.assertIn(\"success\", response_json)\n        self.assertEqual(response_json[\"image_id\"], self.image.id)\n        self.assertTrue(response_json[\"success\"])\n\n\n@override_settings(WAGTAILIMAGES_IMAGE_MODEL=\"tests.CustomImage\")",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@override_settings(WAGTAILIMAGES_IMAGE_MODEL=\"tests.CustomImage\")",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 155,
        "n_words": 40,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 128,
        "n_ast_nodes": 232,
        "n_identifiers": 25,
        "d_id": 16361,
        "documentation": {
            "docstring": "\n        This tests that a POST request to the delete view deletes the image\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 224016,
        "commit_id": "e7f07cc82ab2be920ab426ba07456d8b2592714d",
        "repo": "mkdocs",
        "path": "mkdocs/structure/files.py",
        "file_name": "files.py",
        "fun_name": "is_media_file",
        "commit_message": "Remove spaces at the ends of docstrings, normalize quotes",
        "code": "def is_media_file(self):\n        \n        return not (self.is_documentation_page() or self.is_static_page())\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 57163,
        "documentation": {
            "docstring": "Return True if file is not a documentation or static page.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 284457,
        "commit_id": "33a041e5bf93ce93ab1a19adbc5ed74c2f1eb337",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/stocks/tradinghours/bursa_model.py",
        "file_name": "bursa_model.py",
        "fun_name": "get_all",
        "commit_message": "Trading hours stock feature (#1697)",
        "code": "def get_all() -> pd.DataFrame:\n    \n    bursa = all_bursa()\n    is_open_list = []\n    for exchange in bursa.index:\n        is_open = check_if_open(bursa, exchange)\n        is_open_list.append(is_open)\n    bursa[\"open\"] = is_open_list\n    return bursa[[\"name\", \"short_name\", \"open\"]]\n\n\n@log_start_end(log=logger)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 27,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 18,
        "token_counts": 56,
        "n_ast_nodes": 109,
        "n_identifiers": 14,
        "d_id": 84727,
        "documentation": {
            "docstring": "Get all exchanges.\n\n    Parameters\n    ----------\n\n    Returns\n    -------\n    pd.DataFrame\n        All available exchanges\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 20048,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distro.py",
        "file_name": "distro.py",
        "fun_name": "distro_release_info",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def distro_release_info(self):\n        # type: () -> Dict[str, str]\n        \n        return self._distro_release_info\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 20,
        "n_identifiers": 3,
        "d_id": 3197,
        "documentation": {
            "docstring": "\n        Return a dictionary containing key-value pairs for the information\n        items from the distro release file data source of the OS\n        distribution.\n\n        For details, see :func:`distro.distro_release_info`.\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 107135,
        "commit_id": "ec4dfbc3c83866f487ff0bc9c87b0d43a1c02b22",
        "repo": "matplotlib",
        "path": "lib/matplotlib/figure.py",
        "file_name": "figure.py",
        "fun_name": "set_constrained_layout",
        "commit_message": "ENH: implement and use base layout_engine for more flexible layout.",
        "code": "def set_constrained_layout(self, constrained):\n        \n        if constrained is None:\n            constrained = mpl.rcParams['figure.constrained_layout.use']\n        _constrained = bool(constrained)\n        _parameters = constrained if isinstance(constrained, dict) else {}\n        if _constrained:\n            self.set_layout_engine(ConstrainedLayoutEngine(**_parameters))\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 91,
        "n_words": 27,
        "vocab_size": 20,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 58,
        "n_ast_nodes": 96,
        "n_identifiers": 13,
        "d_id": 22600,
        "documentation": {
            "docstring": "\n        Set whether ``constrained_layout`` is used upon drawing. If None,\n        :rc:`figure.constrained_layout.use` value will be used.\n\n        When providing a dict containing the keys ``w_pad``, ``h_pad``\n        the default ``constrained_layout`` paddings will be\n        overridden.  These pads are in inches and default to 3.0/72.0.\n        ``w_pad`` is the width padding and ``h_pad`` is the height padding.\n\n        See :doc:`/tutorials/intermediate/constrainedlayout_guide`.\n\n        Parameters\n        ----------\n        constrained : bool or dict or None\n        ",
            "n_words": 61,
            "vocab_size": 48,
            "n_whitespaces": 140,
            "language": "en"
        }
    },
    {
        "id": 43172,
        "commit_id": "451a6f4d9ff8b744075e2f25099046c77f28179e",
        "repo": "airflow",
        "path": "airflow/utils/json.py",
        "file_name": "json.py",
        "fun_name": "_default",
        "commit_message": "Speed up grid_data endpoint by 10x (#24284)\n\n* Speed up grid_data endpoint by 10x\r\n\r\nThese changes make the endpoint go from almost 20s down to 1.5s and the\r\nchanges are two fold:\r\n\r\n1. Keep datetimes as objects for as long as possible\r\n\r\n   Previously we were converting start/end dates for a task group to a\r\n   string, and then in the parent parsing it back to a datetime to find\r\n   the min and max of all the child nodes.\r\n\r\n   The fix for that was to leave it as a datetime (or a\r\n   pendulum.DateTime technically) and use the existing\r\n   `AirflowJsonEncoder` class to \"correctly\" encode these objects on\r\n   output.\r\n\r\n2. Reduce the number of DB queries from 1 per task to 1.\r\n\r\n   The removed `get_task_summaries` function was called for each task,\r\n   and was making a query to the database to find info for the given\r\n   DagRuns.\r\n\r\n   The helper function now makes just a single DB query for all\r\n   tasks/runs and constructs a dict to efficiently look up the ti by\r\n   run_id.\r\n\r\n* Add support for mapped tasks in the grid data\r\n\r\n* Don't fail when not all tasks have a finish date.\r\n\r\nNote that this possibly has incorrect behaviour, in that the end_date of\r\na TaskGroup is set to the max of all the children's end dates, even if\r\nsome are still running. (This is the existing behaviour and is not\r\nchanged or altered by this change - limiting it to just performance\r\nfixes)",
        "code": "def _default(obj):\n        \n        if isinstance(obj, datetime):\n            if is_naive(obj):\n                obj = convert_to_utc(obj)\n            return obj.isoformat()\n        elif isinstance(obj, date):\n            return obj.strftime('%Y-%m-%d')\n        elif isinstance(obj, Decimal):\n            _, _, exponent = obj.as_tuple()\n            if exponent >= 0:  # No digits after the decimal point.\n                return int(obj)\n            # Technically lossy due to floating point errors, but the best we\n            # can do without implementing a custom encode function.\n            return float(obj)\n        elif np is not None and isinstance(\n            obj,\n            (\n                np.int_,\n                np.intc,\n                np.intp,\n                np.int8,\n                np.int16,\n                np.int32,\n                np.int64,\n                np.uint8,\n                np.uint16,\n                np.uint32,\n                np.uint64,\n            ),\n        ):\n            return int(obj)\n        elif np is not None and isinstance(obj, np.bool_):\n            return bool(obj)\n        elif np is not None and isinstance(\n            obj, (np.float_, np.float16, np.float32, np.float64, np.complex_, np.complex64, np.complex128)\n        ):\n            return float(obj)\n        elif k8s is not None and isinstance(obj, (k8s.V1Pod, k8s.V1ResourceRequirements)):\n            from airflow.kubernetes.pod_generator import PodGenerator\n\n            return PodGenerator.serialize_pod(obj)\n\n        raise TypeError(f\"Object of type '{obj.__class__.__name__}' is not JSON serializable\")\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 597,
        "n_words": 137,
        "vocab_size": 92,
        "complexity": 14,
        "nloc": 39,
        "token_counts": 253,
        "n_ast_nodes": 386,
        "n_identifiers": 47,
        "d_id": 7849,
        "documentation": {
            "docstring": "Convert dates and numpy objects in a json serializable format.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 269546,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "repeat_elements",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def repeat_elements(x, rep, axis):\n    \n    x_shape = x.shape.as_list()\n    # For static axis\n    if x_shape[axis] is not None:\n        # slices along the repeat axis\n        splits = tf.split(value=x, num_or_size_splits=x_shape[axis], axis=axis)\n        # repeat each slice the given number of reps\n        x_rep = [s for s in splits for _ in range(rep)]\n        return concatenate(x_rep, axis)\n\n    # Here we use tf.tile to mimic behavior of np.repeat so that\n    # we can handle dynamic shapes (that include None).\n    # To do that, we need an auxiliary axis to repeat elements along\n    # it and then merge them along the desired axis.\n\n    # Repeating\n    auxiliary_axis = axis + 1\n    x_shape = tf.shape(x)\n    x_rep = tf.expand_dims(x, axis=auxiliary_axis)\n    reps = np.ones(len(x.shape) + 1)\n    reps[auxiliary_axis] = rep\n    x_rep = tf.tile(x_rep, reps)\n\n    # Merging\n    reps = np.delete(reps, auxiliary_axis)\n    reps[axis] = rep\n    reps = tf.constant(reps, dtype=\"int32\")\n    x_shape *= reps\n    x_rep = tf.reshape(x_rep, x_shape)\n\n    # Fix shape representation\n    x_shape = x.shape.as_list()\n    x_rep.set_shape(x_shape)\n    x_rep._keras_shape = tuple(x_shape)\n    return x_rep\n\n\n@keras_export(\"keras.backend.repeat\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.repeat\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 266,
        "n_words": 156,
        "vocab_size": 102,
        "complexity": 4,
        "nloc": 21,
        "token_counts": 195,
        "n_ast_nodes": 339,
        "n_identifiers": 37,
        "d_id": 80172,
        "documentation": {
            "docstring": "Repeats the elements of a tensor along an axis, like `np.repeat`.\n\n    If `x` has shape `(s1, s2, s3)` and `axis` is `1`, the output\n    will have shape `(s1, s2 * rep, s3)`.\n\n    Args:\n        x: Tensor or variable.\n        rep: Python integer, number of times to repeat.\n        axis: Axis along which to repeat.\n\n    Returns:\n        A tensor.\n\n    Example:\n\n        >>> b = tf.constant([1, 2, 3])\n        >>> tf.keras.backend.repeat_elements(b, rep=2, axis=0)\n        <tf.Tensor: shape=(6,), dtype=int32,\n            numpy=array([1, 1, 2, 2, 3, 3], dtype=int32)>\n\n    ",
            "n_words": 75,
            "vocab_size": 65,
            "n_whitespaces": 153,
            "language": "en"
        }
    },
    {
        "id": 107549,
        "commit_id": "c4116bb841f6d2c0911c87c89817998342d67c5c",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_axes.py",
        "file_name": "test_axes.py",
        "fun_name": "test_annotate_signature",
        "commit_message": "Make signature of Axes.annotate() more explicit.\n\nThe signature is identical to Annotation. This makes the parameters\nexplicit instead of `*args`, which improves usability. On the downside,\nthis introduces redundancy. But we can bear that. The signature will\nnot change often and I've added a test that ensures the signatures\nstay synchronized.",
        "code": "def test_annotate_signature():\n    \n    fig, ax = plt.subplots()\n    annotate_params = inspect.signature(ax.annotate).parameters\n    annotation_params = inspect.signature(mtext.Annotation).parameters\n    assert list(annotate_params.keys()) == list(annotation_params.keys())\n    for p1, p2 in zip(annotate_params.values(), annotation_params.values()):\n        assert p1 == p2\n\n\n@image_comparison(['fill_units.png'], savefig_kwarg={'dpi': 60})",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "@image_comparison(['fill_units.png'], savefig_kwarg={'dpi': 60})",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 53,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 80,
        "n_ast_nodes": 159,
        "n_identifiers": 21,
        "d_id": 22805,
        "documentation": {
            "docstring": "Check that the signature of Axes.annotate() matches Annotation.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 220346,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/base_events.py",
        "file_name": "base_events.py",
        "fun_name": "_check_thread",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _check_thread(self):\n        \n        if self._thread_id is None:\n            return\n        thread_id = threading.get_ident()\n        if thread_id != self._thread_id:\n            raise RuntimeError(\n                \"Non-thread-safe operation invoked on an event loop other \"\n                \"than the current one\")\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 109,
        "n_words": 29,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 34,
        "n_ast_nodes": 63,
        "n_identifiers": 7,
        "d_id": 55970,
        "documentation": {
            "docstring": "Check that the current thread is the thread running the event loop.\n\n        Non-thread-safe methods of this class make this assumption and will\n        likely behave incorrectly when the assumption is violated.\n\n        Should only be called when (self._debug == True).  The caller is\n        responsible for checking this condition for performance reasons.\n        ",
            "n_words": 49,
            "vocab_size": 38,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 110276,
        "commit_id": "9b6abd0b4933811e0a45c2535ab8fd107db65dd9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/figure.py",
        "file_name": "figure.py",
        "fun_name": "add_gridspec",
        "commit_message": "DOC: improve grammar and consistency",
        "code": "def add_gridspec(self, nrows=1, ncols=1, **kwargs):\n        \n\n        _ = kwargs.pop('figure', None)  # pop in case user has added this...\n        gs = GridSpec(nrows=nrows, ncols=ncols, figure=self, **kwargs)\n        return gs\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 54,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 48,
        "n_ast_nodes": 75,
        "n_identifiers": 10,
        "d_id": 24018,
        "documentation": {
            "docstring": "\n        Return a `.GridSpec` that has this figure as a parent.  This allows\n        complex layout of Axes in the figure.\n\n        Parameters\n        ----------\n        nrows : int, default: 1\n            Number of rows in grid.\n\n        ncols : int, default: 1\n            Number of columns in grid.\n\n        Returns\n        -------\n        `.GridSpec`\n\n        Other Parameters\n        ----------------\n        **kwargs\n            Keyword arguments are passed to `.GridSpec`.\n\n        See Also\n        --------\n        matplotlib.pyplot.subplots\n\n        Examples\n        --------\n        Adding a subplot that spans two rows::\n\n            fig = plt.figure()\n            gs = fig.add_gridspec(2, 2)\n            ax1 = fig.add_subplot(gs[0, 0])\n            ax2 = fig.add_subplot(gs[1, 0])\n            # spans two rows:\n            ax3 = fig.add_subplot(gs[:, 1])\n\n        ",
            "n_words": 90,
            "vocab_size": 67,
            "n_whitespaces": 324,
            "language": "en"
        }
    },
    {
        "id": 128560,
        "commit_id": "c1d62d46495f0157faf3168aa87eed350802e10f",
        "repo": "ray",
        "path": "python/ray/data/_internal/arrow_serialization.py",
        "file_name": "arrow_serialization.py",
        "fun_name": "_register_arrow_data_serializer",
        "commit_message": "[Datasets] Arrow 7.0.0+ Support: Use Arrow IPC format for pickling Arrow data to circumvent slice view buffer truncation bug. (#29055)\n\nThis PR registers a custom serializer for Array arrays, chunked arrays, record batches, and tables that works around an Arrow serialization bug that serializes the entire underlying data buffer when serializing zero-copy slice views. The custom serializer uses the Arrow IPC format as the underlying pickled representation.",
        "code": "def _register_arrow_data_serializer(serialization_context):\n    \n    import pyarrow as pa\n\n    if os.environ.get(RAY_DISABLE_CUSTOM_ARROW_DATA_SERIALIZATION, \"0\") == \"1\":\n        return\n\n    # Register custom reducer for Arrow Arrays.\n    array_types = _get_arrow_array_types()\n    for array_type in array_types:\n        serialization_context._register_cloudpickle_reducer(\n            array_type, _arrow_array_reduce\n        )\n    # Register custom reducer for Arrow ChunkedArrays.\n    serialization_context._register_cloudpickle_reducer(\n        pa.ChunkedArray, _arrow_chunkedarray_reduce\n    )\n    # Register custom reducer for Arrow RecordBatches.\n    serialization_context._register_cloudpickle_reducer(\n        pa.RecordBatch, _arrow_recordbatch_reduce\n    )\n    # Register custom reducer for Arrow Tables.\n    serialization_context._register_cloudpickle_reducer(pa.Table, _arrow_table_reduce)\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 149,
        "n_words": 61,
        "vocab_size": 38,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 73,
        "n_ast_nodes": 124,
        "n_identifiers": 19,
        "d_id": 28745,
        "documentation": {
            "docstring": "Custom reducer for Arrow data that works around a zero-copy slicing pickling\n    bug by using the Arrow IPC format for the underlying serialization.\n\n    Background:\n        Arrow has both array-level slicing and buffer-level slicing; both are zero-copy,\n        but the former has a serialization bug where the entire buffer is serialized\n        instead of just the slice, while the latter's serialization works as expected\n        and only serializes the slice of the buffer. I.e., array-level slicing doesn't\n        propagate the slice down to the buffer when serializing the array.\n\n        All that these copy methods do is, at serialization time, take the array-level\n        slicing and translate them to buffer-level slicing, so only the buffer slice is\n        sent over the wire instead of the entire buffer.\n\n    See https://issues.apache.org/jira/browse/ARROW-10739.\n    ",
            "n_words": 120,
            "vocab_size": 75,
            "n_whitespaces": 188,
            "language": "en"
        }
    },
    {
        "id": 303714,
        "commit_id": "2bab6447a924d63d253b210f9a6ab3ea3ca67e7d",
        "repo": "core",
        "path": "homeassistant/components/swisscom/device_tracker.py",
        "file_name": "device_tracker.py",
        "fun_name": "get_swisscom_data",
        "commit_message": "Replaces aiohttp.hdrs CONTENT_TYPE with plain string for the Swisscom integration (#76568)",
        "code": "def get_swisscom_data(self):\n        \n        url = f\"http://{self.host}/ws\"\n        headers = {\"Content-Type\": \"application/x-sah-ws-4-call+json\"}\n        data = \n\n        devices = {}\n\n        try:\n            request = requests.post(url, headers=headers, data=data, timeout=10)\n        except (\n            requests.exceptions.ConnectionError,\n            requests.exceptions.Timeout,\n            requests.exceptions.ConnectTimeout,\n        ):\n            _LOGGER.info(\"No response from Swisscom Internet Box\")\n            return devices\n\n        if \"status\" not in request.json():\n            _LOGGER.info(\"No status in response from Swisscom Internet Box\")\n            return devices\n\n        for device in request.json()[\"status\"]:\n            with suppress(KeyError, requests.exceptions.RequestException):\n                devices[device[\"Key\"]] = {\n                    \"ip\": device[\"IPAddress\"],\n                    \"mac\": device[\"PhysAddress\"],\n                    \"host\": device[\"Name\"],\n                    \"status\": device[\"Active\"],\n                }\n        return devices\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 354,
        "n_words": 71,
        "vocab_size": 53,
        "complexity": 4,
        "nloc": 28,
        "token_counts": 158,
        "n_ast_nodes": 279,
        "n_identifiers": 22,
        "d_id": 102529,
        "documentation": {
            "docstring": "Retrieve data from Swisscom and return parsed result.\n        {\"service\":\"Devices\", \"method\":\"get\",\n        \"parameters\":{\"expression\":\"lan and not self\"}}",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 179183,
        "commit_id": "85b0d2df3458236b5e8c343febc507f94c1e60ad",
        "repo": "gradio",
        "path": "gradio/interpretation.py",
        "file_name": "interpretation.py",
        "fun_name": "run_interpret",
        "commit_message": "brought back sessions for TF 1.x",
        "code": "def run_interpret(interface, raw_input):\n    \n    if isinstance(interface.interpretation, list):  # Either \"default\" or \"shap\"\n        processed_input = [input_component.preprocess(raw_input[i])\n                            for i, input_component in enumerate(interface.input_components)]\n        original_output = interface.run_prediction(processed_input)\n        scores, alternative_outputs = [], []\n        for i, (x, interp) in enumerate(zip(raw_input, interface.interpretation)):\n            if interp == \"default\":\n                input_component = interface.input_components[i]\n                neighbor_raw_input = list(raw_input)\n                if input_component.interpret_by_tokens:\n                    tokens, neighbor_values, masks = input_component.tokenize(\n                        x)\n                    interface_scores = []\n                    alternative_output = []\n                    for neighbor_input in neighbor_values:\n                        neighbor_raw_input[i] = neighbor_input\n                        processed_neighbor_input = [input_component.preprocess(neighbor_raw_input[i])\n                                                    for i, input_component in enumerate(interface.input_components)]\n                        neighbor_output = interface.run_prediction(\n                            processed_neighbor_input)\n                        processed_neighbor_output = [output_component.postprocess(\n                            neighbor_output[i]) for i, output_component in enumerate(interface.output_components)]\n\n                        alternative_output.append(\n                            processed_neighbor_output)\n                        interface_scores.append(quantify_difference_in_label(\n                            interface, original_output, neighbor_output))\n                    alternative_outputs.append(alternative_output)\n                    scores.append(\n                        input_component.get_interpretation_scores(\n                            raw_input[i], neighbor_values, interface_scores, masks=masks, tokens=tokens))\n                else:\n                    neighbor_values, interpret_kwargs = input_component.get_interpretation_neighbors(\n                        x)\n                    interface_scores = []\n                    alternative_output = []\n                    for neighbor_input in neighbor_values:\n                        neighbor_raw_input[i] = neighbor_input\n                        processed_neighbor_input = [input_component.preprocess(neighbor_raw_input[i])\n                                                    for i, input_component in enumerate(interface.input_components)]\n                        neighbor_output = interface.run_prediction(\n                            processed_neighbor_input)\n                        processed_neighbor_output = [output_component.postprocess(\n                            neighbor_output[i]) for i, output_component in enumerate(interface.output_components)]\n\n                        alternative_output.append(\n                            processed_neighbor_output)\n                        interface_scores.append(quantify_difference_in_label(\n                            interface, original_output, neighbor_output))\n                    alternative_outputs.append(alternative_output)\n                    interface_scores = [-score for score in interface_scores]\n                    scores.append(\n                        input_component.get_interpretation_scores(\n                            raw_input[i], neighbor_values, interface_scores, **interpret_kwargs))\n            elif interp == \"shap\" or interp == \"shapley\":\n                try:\n                    import shap  # type: ignore\n                except (ImportError, ModuleNotFoundError):\n                    raise ValueError(\n                        \"The package `shap` is required for this interpretation method. Try: `pip install shap`\")\n                input_component = interface.input_components[i]\n                if not (input_component.interpret_by_tokens):\n                    raise ValueError(\n                        \"Input component {} does not support `shap` interpretation\".format(input_component))\n\n                tokens, _, masks = input_component.tokenize(x)\n\n                # construct a masked version of the input",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 1546,
        "n_words": 221,
        "vocab_size": 117,
        "complexity": 22,
        "nloc": 93,
        "token_counts": 674,
        "n_ast_nodes": 701,
        "n_identifiers": 46,
        "d_id": 42917,
        "documentation": {
            "docstring": "\n    Runs the interpretation command for the machine learning model. Handles both the \"default\" out-of-the-box\n    interpretation for a certain set of UI component types, as well as the custom interpretation case.\n    Parameters:\n    raw_input: a list of raw inputs to apply the interpretation(s) on.\n    ",
            "n_words": 42,
            "vocab_size": 32,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 186787,
        "commit_id": "6e1696ba32ef8c1162bb0cd85df5a22113952828",
        "repo": "certbot",
        "path": "tools/finish_release.py",
        "file_name": "finish_release.py",
        "fun_name": "parse_args",
        "commit_message": "Add Signed Windows Installer Workflow (#9076)\n\n* Add Code Signing action for Windows Installer\r\n\r\n* Clean up variable names and input\r\n\r\n* Amend and add to documentation per PR guidelines\r\n\r\n* Update tools/finish_release.py\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\n\r\n* Update tools/finish_release.py\r\n\r\nAmend typo\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\n\r\n* Amend release script for better work flow\r\n\r\n- SCP commands to upload and download unsigned & signed installers from CSS\r\n\r\n* Collapse spaces\r\n\r\n* Update tools/finish_release.py\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\n\r\n* Create new windows signer function\r\n\r\n* Update Windows Installer Script\r\n\r\n- Update change log\r\n- add new function for signing and document\r\n- @TODO Streammline SSH session\r\n\r\n* Remove Azure and Github release methods\r\n\r\n- Methods moved to CSS\r\n- Reduced to a ssh function that triggers the process on a CSS\r\n\r\n* Amend Chnagelog and Remove Unneeded Deps\r\n\r\n* Update tools/finish_release.py\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\n\r\n* Add Verison Fetch Function\r\n\r\n- For the purpose of snap releases\r\n- Add back package to dev extras for function\r\n\r\n* Chaneg path in ssh command\r\n\r\n* Amend release script\r\n\r\n* Amend the ssh command for CSS\r\n\r\n* Update tools/finish_release.py\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\n\r\n* Update script with proper path and subprocess call\r\n\r\n* Update ssh command\r\n\r\n* Correct typo in path\r\n\r\n* Fix typo in path\r\n\r\n* Update certbot/CHANGELOG.md\r\n\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>\r\n\r\n* Remove missed conflict text\r\n\r\nCo-authored-by: Brad Warren <bmw@users.noreply.github.com>\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>",
        "code": "def parse_args(args):\n    \n    # Use the file's docstring for the help text and don't let argparse reformat it.\n    parser = argparse.ArgumentParser(description=__doc__,\n                                     formatter_class=argparse.RawDescriptionHelpFormatter)\n    parser.add_argument('--css', type=str, required=True, help='hostname of code signing server')\n    group = parser.add_mutually_exclusive_group()\n    # We use 'store_false' and a destination related to the other type of\n    # artifact to cause the flag being set to disable publishing of the other\n    # artifact. This makes using the parsed arguments later on a little simpler\n    # and cleaner.\n    group.add_argument('--snaps-only', action='store_false', dest='publish_windows',\n                        help='Skip publishing other artifacts and only publish the snaps')\n    group.add_argument('--windows-only', action='store_false', dest='publish_snaps',\n                        help='Skip publishing other artifacts and only publish the Windows installer')\n    return parser.parse_args(args)\n\n    ",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 224,
        "n_words": 102,
        "vocab_size": 71,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 90,
        "n_ast_nodes": 160,
        "n_identifiers": 18,
        "d_id": 45621,
        "documentation": {
            "docstring": "Parse command line arguments.\n\n    :param args: command line arguments with the program name removed. This is\n        usually taken from sys.argv[1:].\n    :type args: `list` of `str`\n\n    :returns: parsed arguments\n    :rtype: argparse.Namespace\n\n    ",
            "n_words": 30,
            "vocab_size": 26,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 70549,
        "commit_id": "e9183a95c88fe2eaf4c1d3aff9833633509713f3",
        "repo": "wagtail",
        "path": "wagtail/admin/action_menu.py",
        "file_name": "action_menu.py",
        "fun_name": "get_context_data",
        "commit_message": "Update docs links to reference new domain",
        "code": "def get_context_data(self, parent_context):\n        \n        context = parent_context.copy()\n\n        if requires_request_arg(self.get_url):\n            warn(\n                \"%s.get_url should no longer take a 'request' argument. \"\n                \"See https://docs.wagtail.org/en/stable/releases/2.15.html#template-components-2-15\" % type(self).__name__,\n                category=RemovedInWagtail217Warning\n            )\n            url = self.get_url(parent_context['request'], parent_context)\n        else:\n            url = self.get_url(parent_context)\n\n        context.update({\n            'label': self.label,\n            'url': url,\n            'name': self.name,\n            'classname': self.classname,\n            'icon_name': self.icon_name,\n            'request': parent_context['request'],\n        })\n        return context\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 252,
        "n_words": 48,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 106,
        "n_ast_nodes": 182,
        "n_identifiers": 18,
        "d_id": 15517,
        "documentation": {
            "docstring": "Defines context for the template, overridable to use more data",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 209070,
        "commit_id": "402677d50cc007cb5b39dc0fdb8934dae36cf6ac",
        "repo": "scapy",
        "path": "scapy/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_parse_tag",
        "commit_message": "Update git format",
        "code": "def _parse_tag(tag):\n    # type: (str) -> str\n    \n    match = re.match('^v?(.+?)-(\\\\d+)-g[a-f0-9]+$', tag)\n    if match:\n        # remove the 'v' prefix and add a '.devN' suffix\n        return '%s.dev%s' % (match.group(1), match.group(2))\n    else:\n        # just remove the 'v' prefix\n        return re.sub('^v', '', tag)\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 82,
        "n_words": 39,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 50,
        "n_ast_nodes": 91,
        "n_identifiers": 6,
        "d_id": 52591,
        "documentation": {
            "docstring": "\n    Parse a tag from ``git describe`` into a version.\n\n    Example::\n\n        v2.3.2-346-g164a52c075c8 -> '2.3.2.dev346'\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 82002,
        "commit_id": "d3eb2c197595c29c4a3f7b38cd609ce953009623",
        "repo": "awx",
        "path": "awx/main/management/commands/bottleneck.py",
        "file_name": "bottleneck.py",
        "fun_name": "handle",
        "commit_message": "Add new flak8 rules to do some meaningful corrections",
        "code": "def handle(self, *args, **options):\n        jt = options['jt']\n        threshold = options['threshold']\n        history = options['history']\n        ignore = options['ignore']\n\n        print('## ' + JobTemplate.objects.get(pk=jt).name + f' (last {history} runs)\\n')\n        with connection.cursor() as cursor:\n            cursor.execute(\n                f\n            )\n            slowest_events = cursor.fetchall()\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 124,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 14,
        "nloc": 67,
        "token_counts": 398,
        "n_ast_nodes": 150,
        "n_identifiers": 19,
        "d_id": 17294,
        "documentation": {
            "docstring": "\n                SELECT\n                    b.id, b.job_id, b.host_name, b.created - a.created delta,\n                    b.task task,\n                    b.event_data::json->'task_action' task_action,\n                    b.event_data::json->'task_path' task_path\n                FROM main_jobevent a JOIN main_jobevent b\n                ON b.parent_uuid = a.parent_uuid  AND a.host_name = b.host_name\n                WHERE\n                    a.event = 'runner_on_start' AND\n                    b.event != 'runner_on_start' AND\n                    b.event != 'runner_on_skipped' AND\n                    b.failed = false AND\n                    a.job_id IN (\n                        SELECT unifiedjob_ptr_id FROM main_job\n                        WHERE job_template_id={jt}\n                        ORDER BY unifiedjob_ptr_id DESC\n                        LIMIT {history}\n                    )\n                ORDER BY delta DESC;\n                ",
            "n_words": 65,
            "vocab_size": 48,
            "n_whitespaces": 439,
            "language": "en"
        }
    },
    {
        "id": 191685,
        "commit_id": "8d0869c6d3ed63b2b15d4f75ea664e089dcc569d",
        "repo": "langchain",
        "path": "tests/unit_tests/chains/test_base.py",
        "file_name": "test_base.py",
        "fun_name": "test_multiple_output_keys_error",
        "commit_message": "change run to use args and kwargs (#367)\n\nBefore, `run` was not able to be called with multiple arguments. This\r\nexpands the functionality.",
        "code": "def test_multiple_output_keys_error() -> None:\n    \n    chain = FakeChain(the_output_keys=[\"foo\", \"bar\"])\n    with pytest.raises(ValueError):\n        chain.run(\"bar\")\n",
        "url": "https://github.com/hwchase17/langchain.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 27,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 33,
        "n_ast_nodes": 64,
        "n_identifiers": 8,
        "d_id": 46799,
        "documentation": {
            "docstring": "Test run with multiple output keys errors as expected.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 146296,
        "commit_id": "4b28bc3f09ebcc9c0d6262355b394452a11667fc",
        "repo": "ray",
        "path": "python/ray/tune/result_grid.py",
        "file_name": "result_grid.py",
        "fun_name": "get_best_result",
        "commit_message": "[Tuner part1] Add Tuner interface. (#22975)",
        "code": "def get_best_result(self) -> Result:\n        \n        return self._trial_to_result(self._experiment_analysis.best_trial)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 19,
        "n_ast_nodes": 33,
        "n_identifiers": 6,
        "d_id": 33655,
        "documentation": {
            "docstring": "Get the best result from all the trials run.\n\n        Note, \"best\" here is determined by \"metric\" and \"mode\" specified in your Tuner's\n        TuneConfig.\n\n        Trials are compared using their \"last\" results. In a similar notion, the last\n        checkpoint of the best trial is returned as part of the result.",
            "n_words": 48,
            "vocab_size": 41,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 91646,
        "commit_id": "0ad4aa9d9fe3beb3fd20aaedd961b3c2c800efb1",
        "repo": "sentry",
        "path": "src/django_picklefield/fields.py",
        "file_name": "fields.py",
        "fun_name": "get_lookup",
        "commit_message": "ref(django-3.2): Vendor django picklefield (#35727)\n\n* ref(django-3.2): Vendor django picklefield\r\n\r\nDjango-picklefield hasn't been updated in 2 years, but we need it. We also need to upgrade to django 3.2 which means we need to update picklefield.\r\n\r\n* Remove reference to django-picklefield\r\n\r\n* Fix the module name to use underscore\r\n\r\n* style(lint): Auto commit lint changes\r\n\r\n* Remove versioning code\r\n\r\nCo-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>",
        "code": "def get_lookup(self, lookup_name):\n        \n        if lookup_name not in [\"exact\", \"in\", \"isnull\"]:\n            raise TypeError(\"Lookup type %s is not supported.\" % lookup_name)\n        return super().get_lookup(lookup_name)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 53,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 36,
        "n_ast_nodes": 65,
        "n_identifiers": 5,
        "d_id": 18772,
        "documentation": {
            "docstring": "\n        We need to limit the lookup types.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 107585,
        "commit_id": "8573a52853df59579236a6096abbecd409c26982",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_legend.py",
        "file_name": "test_legend.py",
        "fun_name": "test_legend_label_with_leading_underscore",
        "commit_message": "Clarify warning about labels with leading underscores.\n\nReplaces and closes #17488.\n\nCo-authored-by: Clement Walter <clement0walter@gmail.com>",
        "code": "def test_legend_label_with_leading_underscore():\n    \n    fig, ax = plt.subplots()\n    line, = ax.plot([0, 1], label='_foo')\n    with pytest.warns(UserWarning,\n                      match=r\"starts with '_'.*excluded from the legend.\"):\n        legend = ax.legend(handles=[line])\n    assert len(legend.legendHandles) == 0\n\n\n@image_comparison(['legend_labels_first.png'], remove_text=True)",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "@image_comparison(['legend_labels_first.png'], remove_text=True)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 70,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 65,
        "n_ast_nodes": 128,
        "n_identifiers": 18,
        "d_id": 22829,
        "documentation": {
            "docstring": "\n    Test that artists with labels starting with an underscore are not added to\n    the legend, and that a warning is issued if one tries to add them\n    explicitly.\n    ",
            "n_words": 28,
            "vocab_size": 25,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 314885,
        "commit_id": "00810235c92b492a966c6021021d49360ffb3cdd",
        "repo": "core",
        "path": "homeassistant/config_entries.py",
        "file_name": "config_entries.py",
        "fun_name": "_async_process_on_unload",
        "commit_message": "Track tasks adding entities (#73828)\n\n* Track tasks adding entities\r\n\r\n* Update homeassistant/config_entries.py\r\n\r\n* fix cast tests\r\n\r\nCo-authored-by: J. Nick Koston <nick@koston.org>",
        "code": "async def _async_process_on_unload(self) -> None:\n        \n        if self._on_unload is not None:\n            while self._on_unload:\n                self._on_unload.pop()()\n\n        while self._pending_tasks:\n            pending = [task for task in self._pending_tasks if not task.done()]\n            self._pending_tasks.clear()\n            if pending:\n                await asyncio.gather(*pending)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 125,
        "n_words": 30,
        "vocab_size": 25,
        "complexity": 7,
        "nloc": 10,
        "token_counts": 71,
        "n_ast_nodes": 120,
        "n_identifiers": 11,
        "d_id": 113486,
        "documentation": {
            "docstring": "Process the on_unload callbacks and wait for pending tasks.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 183431,
        "commit_id": "dd18ecbdbe744812509630935a877424202f2a70",
        "repo": "textual",
        "path": "src/textual/_text_backend.py",
        "file_name": "_text_backend.py",
        "fun_name": "cursor_text_start",
        "commit_message": "Docstring improvements",
        "code": "def cursor_text_start(self) -> bool:\n        \n        if self.cursor_index == 0:\n            return False\n\n        self.cursor_index = 0\n        return True\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 4,
        "d_id": 44183,
        "documentation": {
            "docstring": "Move the cursor to the start of the text\n\n        Returns:\n            bool: True if the cursor moved. False otherwise.\n        ",
            "n_words": 18,
            "vocab_size": 14,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 291944,
        "commit_id": "af4e37339a39badd5596e8bc9ba86d6c1994aa1b",
        "repo": "core",
        "path": "homeassistant/components/sia/sia_entity_base.py",
        "file_name": "sia_entity_base.py",
        "fun_name": "async_create_post_interval_update_cb",
        "commit_message": "Add Connectivity sensor to SIA (#64305)\n\n* implemented connectivity sensor\r\n\r\n* further cleanup off update code\r\n\r\n* cleanup and tighter behaviour for attributes\r\n\r\n* added seperate connectivity class to binary sensor\r\n\r\n* callbacks and keys\r\n\r\n* redid name and unique_id logic, non-breaking result\r\n\r\n* using entry more in inits\r\n\r\n* Fix import\r\n\r\n* fix ping_interval in sia_entity_base\r\n\r\n* added ping_interval default to next\r\n\r\n* fixed next\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "def async_create_post_interval_update_cb(self) -> None:\n        \n        self._post_interval_update_cb_canceller = async_call_later(\n            self.hass,\n            get_unavailability_interval(self.ping_interval),\n            self.async_post_interval_update,\n        )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 65,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 30,
        "n_ast_nodes": 48,
        "n_identifiers": 8,
        "d_id": 91047,
        "documentation": {
            "docstring": "Create a port interval update cb and store the callback.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 309149,
        "commit_id": "ea5b18c1ef16b64cd7916f2540692ab5de2d2edf",
        "repo": "core",
        "path": "tests/components/august/test_binary_sensor.py",
        "file_name": "test_binary_sensor.py",
        "fun_name": "test_doorbell_update_via_pubnub",
        "commit_message": "Split august motion and image capture binary sensors (#62154)",
        "code": "async def test_doorbell_update_via_pubnub(hass):\n    \n    doorbell_one = await _mock_doorbell_from_fixture(hass, \"get_doorbell.json\")\n    pubnub = AugustPubNub()\n\n    await _create_august_with_devices(hass, [doorbell_one], pubnub=pubnub)\n    assert doorbell_one.pubsub_channel == \"7c7a6672-59c8-3333-ffff-dcd98705cccc\"\n\n    binary_sensor_k98gidt45gul_name_motion = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_motion\"\n    )\n    assert binary_sensor_k98gidt45gul_name_motion.state == STATE_OFF\n    binary_sensor_k98gidt45gul_name_ding = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_ding\"\n    )\n    assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF\n\n    pubnub.message(\n        pubnub,\n        Mock(\n            channel=doorbell_one.pubsub_channel,\n            timetoken=_timetoken(),\n            message={\n                \"status\": \"imagecapture\",\n                \"data\": {\n                    \"result\": {\n                        \"created_at\": \"2021-03-16T01:07:08.817Z\",\n                        \"secure_url\": \"https://dyu7azbnaoi74.cloudfront.net/zip/images/zip.jpeg\",\n                    },\n                },\n            },\n        ),\n    )\n\n    await hass.async_block_till_done()\n\n    binary_sensor_k98gidt45gul_name_image_capture = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_image_capture\"\n    )\n    assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_ON\n\n    pubnub.message(\n        pubnub,\n        Mock(\n            channel=doorbell_one.pubsub_channel,\n            timetoken=_timetoken(),\n            message={\n                \"status\": \"doorbell_motion_detected\",\n                \"data\": {\n                    \"event\": \"doorbell_motion_detected\",\n                    \"image\": {\n                        \"height\": 640,\n                        \"width\": 480,\n                        \"format\": \"jpg\",\n                        \"created_at\": \"2021-03-16T02:36:26.886Z\",\n                        \"bytes\": 14061,\n                        \"secure_url\": \"https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg\",\n                        \"url\": \"https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg\",\n                        \"etag\": \"09e839331c4ea59eef28081f2caa0e90\",\n                    },\n                    \"doorbellName\": \"Front Door\",\n                    \"callID\": None,\n                    \"origin\": \"mars-api\",\n                    \"mutableContent\": True,\n                },\n            },\n        ),\n    )\n\n    await hass.async_block_till_done()\n\n    binary_sensor_k98gidt45gul_name_motion = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_motion\"\n    )\n    assert binary_sensor_k98gidt45gul_name_motion.state == STATE_ON\n\n    binary_sensor_k98gidt45gul_name_ding = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_ding\"\n    )\n    assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF\n\n    new_time = dt_util.utcnow() + datetime.timedelta(seconds=40)\n    native_time = datetime.datetime.now() + datetime.timedelta(seconds=40)\n    with patch(\n        \"homeassistant.components.august.binary_sensor._native_datetime\",\n        return_value=native_time,\n    ):\n        async_fire_time_changed(hass, new_time)\n        await hass.async_block_till_done()\n\n    binary_sensor_k98gidt45gul_name_image_capture = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_image_capture\"\n    )\n    assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_OFF\n\n    pubnub.message(\n        pubnub,\n        Mock(\n            channel=doorbell_one.pubsub_channel,\n            timetoken=_timetoken(),\n            message={\n                \"status\": \"buttonpush\",\n            },\n        ),\n    )\n    await hass.async_block_till_done()\n\n    binary_sensor_k98gidt45gul_name_ding = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_ding\"\n    )\n    assert binary_sensor_k98gidt45gul_name_ding.state == STATE_ON\n    new_time = dt_util.utcnow() + datetime.timedelta(seconds=40)\n    native_time = datetime.datetime.now() + datetime.timedelta(seconds=40)\n    with patch(\n        \"homeassistant.components.august.binary_sensor._native_datetime\",\n        return_value=native_time,\n    ):\n        async_fire_time_changed(hass, new_time)\n        await hass.async_block_till_done()\n\n    binary_sensor_k98gidt45gul_name_ding = hass.states.get(\n        \"binary_sensor.k98gidt45gul_name_ding\"\n    )\n    assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 1162,
        "n_words": 211,
        "vocab_size": 87,
        "complexity": 1,
        "nloc": 109,
        "token_counts": 475,
        "n_ast_nodes": 819,
        "n_identifiers": 33,
        "d_id": 107857,
        "documentation": {
            "docstring": "Test creation of a doorbell that can be updated via pubnub.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 47930,
        "commit_id": "1dfae80412377eef0a38637535d6a1d3393cc4fe",
        "repo": "airflow",
        "path": "tests/www/views/test_views_connection.py",
        "file_name": "test_views_connection.py",
        "fun_name": "test_prefill_form_backcompat",
        "commit_message": "Enable use of custom conn extra fields without prefix (#22607)\n\nPreviously, connection \"extra\" fields which were added as custom fields in the\r\nwebserver connection form had to be named with prefix `extra__<conn_type>__`.\r\nThis was because custom fields are registered globally on the connection view model,\r\nso the prefix was necessary to prevent collisions.\r\n\r\nBut the prefix is ugly and cumbersome in the `extra` field.  So now what we do is\r\nadd this prefix when defining the field internally in the model, and strip it when\r\nsaving the connection.\r\n\r\nThis doesn't change any providers -- each of those will have to be updated in order to use no-prefix custom fields, with special care to handle backcompat.",
        "code": "def test_prefill_form_backcompat(extras, expected):\n    \n    mock_form = mock.Mock()\n    mock_form.data = {\"conn_id\": \"test\", \"extra\": json.dumps(extras), \"conn_type\": \"test\"}\n    cmv = ConnectionModelView()\n    cmv.extra_fields = ['extra__test__my_param']\n\n    # this is set by `lazy_add_provider_discovered_options_to_connection_form`\n    cmv.extra_field_name_mapping['extra__test__my_param'] = 'my_param'\n\n    cmv.prefill_form(form=mock_form, pk=1)\n    assert mock_form.extra__test__my_param.data == expected\n\n\n@pytest.mark.parametrize('field_name', ['extra__test__custom_field', 'custom_field'])\n@mock.patch('airflow.utils.module_loading.import_string')\n@mock.patch('airflow.providers_manager.ProvidersManager.hooks', new_callable=PropertyMock)",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize('field_name', ['extra__test__custom_field', 'custom_field'])\n@mock.patch('airflow.utils.module_loading.import_string')\n@mock.patch('airflow.providers_manager.ProvidersManager.hooks', new_callable=PropertyMock)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 65,
        "n_words": 41,
        "vocab_size": 37,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 77,
        "n_ast_nodes": 197,
        "n_identifiers": 23,
        "d_id": 9302,
        "documentation": {
            "docstring": "\n    When populating custom fields in the connection form we should first check for the non-prefixed\n    value (since prefixes in extra are deprecated) and then fallback to the prefixed value.\n\n    Either way, the field is known internally to the model view as the prefixed value.\n    ",
            "n_words": 44,
            "vocab_size": 35,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 266525,
        "commit_id": "fbb5d56bd274c44b193cb95f0230b9352f62aab2",
        "repo": "ansible",
        "path": "lib/ansible/plugins/callback/junit.py",
        "file_name": "junit.py",
        "fun_name": "_build_test_case",
        "commit_message": "ansible-test - Use relative paths in junit output. (#76871)\n\n* ansible-test - Use relative paths in junit output.\r\n\r\nAlso fix a traceback in the junit callback during automatic fact gathering.\r\n\r\n* ansible-test - Handle out-of-tree JUnit paths.",
        "code": "def _build_test_case(self, task_data, host_data):\n        \n\n        name = '[%s] %s: %s' % (host_data.name, task_data.play, task_data.name)\n        duration = host_data.finish - task_data.start\n\n        if self._task_relative_path and task_data.path:\n            junit_classname = os.path.relpath(task_data.path, self._task_relative_path)\n        else:\n            junit_classname = task_data.path\n\n        if self._replace_out_of_tree_path is not None and junit_classname.startswith('../'):\n            junit_classname = self._replace_out_of_tree_path + os.path.basename(junit_classname)\n\n        if self._task_class == 'true':\n            junit_classname = re.sub(r'\\.yml:[0-9]+$', '', junit_classname)\n\n        if host_data.status == 'included':\n            return TestCase(name=name, classname=junit_classname, time=duration, system_out=str(host_data.result))\n\n        res = host_data.result._result\n        rc = res.get('rc', 0)\n        dump = self._dump_results(res, indent=0)\n        dump = self._cleanse_string(dump)\n\n        if host_data.status == 'ok':\n            return TestCase(name=name, classname=junit_classname, time=duration, system_out=dump)\n\n        test_case = TestCase(name=name, classname=junit_classname, time=duration)\n\n        if host_data.status == 'failed':\n            if 'exception' in res:\n                message = res['exception'].strip().split('\\n')[-1]\n                output = res['exception']\n                test_case.errors.append(TestError(message=message, output=output))\n            elif 'msg' in res:\n                message = res['msg']\n                test_case.failures.append(TestFailure(message=message, output=dump))\n            else:\n                test_case.failures.append(TestFailure(message='rc=%s' % rc, output=dump))\n        elif host_data.status == 'skipped':\n            if 'skip_reason' in res:\n                message = res['skip_reason']\n            else:\n                message = 'skipped'\n            test_case.skipped = message\n\n        return test_case\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 509,
        "n_words": 138,
        "vocab_size": 81,
        "complexity": 13,
        "nloc": 37,
        "token_counts": 360,
        "n_ast_nodes": 589,
        "n_identifiers": 46,
        "d_id": 78457,
        "documentation": {
            "docstring": " build a TestCase from the given TaskData and HostData ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 204433,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/checks/model_checks.py",
        "file_name": "model_checks.py",
        "fun_name": "_check_lazy_references",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _check_lazy_references(apps, ignore=None):\n    \n    pending_models = set(apps._pending_operations) - (ignore or set())\n\n    # Short circuit if there aren't any errors.\n    if not pending_models:\n        return []\n\n    from django.db.models import signals\n\n    model_signals = {\n        signal: name\n        for name, signal in vars(signals).items()\n        if isinstance(signal, signals.ModelSignal)\n    }\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 90,
        "n_words": 41,
        "vocab_size": 38,
        "complexity": 7,
        "nloc": 32,
        "token_counts": 155,
        "n_ast_nodes": 112,
        "n_identifiers": 17,
        "d_id": 50730,
        "documentation": {
            "docstring": "\n    Ensure all lazy (i.e. string) model references have been resolved.\n\n    Lazy references are used in various places throughout Django, primarily in\n    related fields and model signals. Identify those common cases and provide\n    more helpful error messages for them.\n\n    The ignore parameter is used by StateApps to exclude swappable models from\n    this check.\n    ",
            "n_words": 52,
            "vocab_size": 47,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 19684,
        "commit_id": "9a3b3ce70621af6f9adaa9eeac9cf83fa149319c",
        "repo": "pipenv",
        "path": "pipenv/environment.py",
        "file_name": "environment.py",
        "fun_name": "activated",
        "commit_message": "Issue 4993 Add standard pre commit hooks and apply linting. (#4994)\n\n* Add .pre-commit-config.yaml to the project and exclude tests (for now).  This does not include the MyPy linting that pip does but does include everything else.",
        "code": "def activated(self, include_extras=True, extra_dists=None):\n        \n\n        if not extra_dists:\n            extra_dists = []\n        original_path = sys.path\n        original_prefix = sys.prefix\n        parent_path = Path(__file__).absolute().parent\n        vendor_dir = parent_path.joinpath(\"vendor\").as_posix()\n        patched_dir = parent_path.joinpath(\"patched\").as_posix()\n        parent_path = parent_path.as_posix()\n        self.add_dist(\"pip\")\n        prefix = self.prefix.as_posix()\n        with vistir.contextmanagers.temp_environ(), vistir.contextmanagers.temp_path():\n            os.environ[\"PATH\"] = os.pathsep.join(\n                [\n                    vistir.compat.fs_str(self.script_basedir),\n                    vistir.compat.fs_str(self.prefix.as_posix()),\n                    os.environ.get(\"PATH\", \"\"),\n                ]\n            )\n            os.environ[\"PYTHONIOENCODING\"] = vistir.compat.fs_str(\"utf-8\")\n            os.environ[\"PYTHONDONTWRITEBYTECODE\"] = vistir.compat.fs_str(\"1\")\n            if self.is_venv:\n                os.environ[\"PYTHONPATH\"] = self.base_paths[\"PYTHONPATH\"]\n                os.environ[\"VIRTUAL_ENV\"] = vistir.compat.fs_str(prefix)\n            else:\n                if not self.project.s.PIPENV_USE_SYSTEM and not os.environ.get(\n                    \"VIRTUAL_ENV\"\n                ):\n                    os.environ[\"PYTHONPATH\"] = self.base_paths[\"PYTHONPATH\"]\n                    os.environ.pop(\"PYTHONHOME\", None)\n            sys.path = self.sys_path\n            sys.prefix = self.sys_prefix\n            site.addsitedir(self.base_paths[\"purelib\"])\n            pip = self.safe_import(\"pip\")  # noqa\n            pip_vendor = self.safe_import(\"pip._vendor\")\n            pep517_dir = os.path.join(os.path.dirname(pip_vendor.__file__), \"pep517\")\n            site.addsitedir(pep517_dir)\n            os.environ[\"PYTHONPATH\"] = os.pathsep.join(\n                [os.environ.get(\"PYTHONPATH\", self.base_paths[\"PYTHONPATH\"]), pep517_dir]\n            )\n            if include_extras:\n                site.addsitedir(parent_path)\n                sys.path.extend([parent_path, patched_dir, vendor_dir])\n                extra_dists = list(self.extra_dists) + extra_dists\n                for extra_dist in extra_dists:\n                    if extra_dist not in self.get_working_set():\n                        extra_dist.activate(self.sys_path)\n            try:\n                yield\n            finally:\n                sys.path = original_path\n                sys.prefix = original_prefix\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 783,
        "n_words": 130,
        "vocab_size": 84,
        "complexity": 9,
        "nloc": 52,
        "token_counts": 440,
        "n_ast_nodes": 743,
        "n_identifiers": 51,
        "d_id": 3062,
        "documentation": {
            "docstring": "Helper context manager to activate the environment.\n\n        This context manager will set the following variables for the duration\n        of its activation:\n\n            * sys.prefix\n            * sys.path\n            * os.environ[\"VIRTUAL_ENV\"]\n            * os.environ[\"PATH\"]\n\n        In addition, it will make any distributions passed into `extra_dists` available\n        on `sys.path` while inside the context manager, as well as making `passa` itself\n        available.\n\n        The environment's `prefix` as well as `scripts_dir` properties are both prepended\n        to `os.environ[\"PATH\"]` to ensure that calls to `~Environment.run()` use the\n        environment's path preferentially.\n        ",
            "n_words": 78,
            "vocab_size": 59,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 177572,
        "commit_id": "85152f2c8c7f8b301b28fcd771f13b5c166c59eb",
        "repo": "label-studio",
        "path": "label_studio/data_manager/actions/basic.py",
        "file_name": "basic.py",
        "fun_name": "delete_tasks_annotations",
        "commit_message": "fix: DEV-1486: fix dm action when deleting all annotations, finished state is not updated (#1923)\n\nCo-authored-by: Max Tkachenko <makseq@gmail.com>",
        "code": "def delete_tasks_annotations(project, queryset, **kwargs):\n    \n    task_ids = queryset.values_list('id', flat=True)\n    annotations = Annotation.objects.filter(task__id__in=task_ids)\n    count = annotations.count()\n    annotations_ids = list(annotations.values('id'))\n    annotations.delete()\n    emit_webhooks_for_instance(project.organization, project, WebhookAction.ANNOTATIONS_DELETED, annotations_ids)\n    bulk_update_stats_project_tasks(queryset)\n    return {'processed_items': count,\n            'detail': 'Deleted ' + str(count) + ' annotations'}\n\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 72,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 93,
        "n_ast_nodes": 158,
        "n_identifiers": 23,
        "d_id": 42445,
        "documentation": {
            "docstring": " Delete all annotations by tasks ids\n\n    :param project: project instance\n    :param queryset: filtered tasks db queryset\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 217834,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/cookies.py",
        "file_name": "cookies.py",
        "fun_name": "load",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def load(self, rawdata):\n        \n        if isinstance(rawdata, str):\n            self.__parse_string(rawdata)\n        else:\n            # self.update() wouldn't call our custom __setitem__\n            for key, value in rawdata.items():\n                self[key] = value\n        return\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 100,
        "n_words": 24,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 70,
        "n_identifiers": 9,
        "d_id": 54959,
        "documentation": {
            "docstring": "Load cookies from a string (presumably HTTP_COOKIE) or\n        from a dictionary.  Loading cookies from a dictionary 'd'\n        is equivalent to calling:\n            map(Cookie.__setitem__, d.keys(), d.values())\n        ",
            "n_words": 24,
            "vocab_size": 19,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 269497,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "_assert_same_graph",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _assert_same_graph(original_item, item):\n    \n    original_graph = getattr(original_item, \"graph\", None)\n    graph = getattr(item, \"graph\", None)\n    if original_graph and graph and original_graph is not graph:\n        raise ValueError(\n            \"%s must be from the same graph as %s (graphs are %s and %s).\"\n            % (item, original_item, graph, original_graph)\n        )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 92,
        "n_words": 44,
        "vocab_size": 34,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 53,
        "n_ast_nodes": 84,
        "n_identifiers": 7,
        "d_id": 80129,
        "documentation": {
            "docstring": "Fail if the 2 items are from different graphs.\n\n    Args:\n      original_item: Original item to check against.\n      item: Item to check.\n\n    Raises:\n      ValueError: if graphs do not match.\n    ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 196055,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/fp_groups.py",
        "file_name": "fp_groups.py",
        "fun_name": "rewrite",
        "commit_message": "Updated import locations",
        "code": "def rewrite(C, alpha, w):\n    \n    v = C._schreier_free_group.identity\n    for i in range(len(w)):\n        x_i = w[i]\n        v = v*C.P[alpha][C.A_dict[x_i]]\n        alpha = C.table[alpha][C.A_dict[x_i]]\n    return v\n\n# Pg 350, section 2.5.2 from [2]",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 61,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 70,
        "n_ast_nodes": 107,
        "n_identifiers": 14,
        "d_id": 47555,
        "documentation": {
            "docstring": "\n    Parameters\n    ==========\n\n    C: CosetTable\n    alpha: A live coset\n    w: A word in `A*`\n\n    Returns\n    =======\n\n    rho(tau(alpha), w)\n\n    Examples\n    ========\n\n    >>> from sympy.combinatorics.fp_groups import FpGroup, CosetTable, define_schreier_generators, rewrite\n    >>> from sympy.combinatorics import free_group\n    >>> F, x, y = free_group(\"x, y\")\n    >>> f = FpGroup(F, [x**2, y**3, (x*y)**6])\n    >>> C = CosetTable(f, [])\n    >>> C.table = [[1, 1, 2, 3], [0, 0, 4, 5], [4, 4, 3, 0], [5, 5, 0, 2], [2, 2, 5, 1], [3, 3, 1, 4]]\n    >>> C.p = [0, 1, 2, 3, 4, 5]\n    >>> define_schreier_generators(C)\n    >>> rewrite(C, 0, (x*y)**6)\n    x_4*y_2*x_3*x_1*x_2*y_4*x_5\n\n    ",
            "n_words": 94,
            "vocab_size": 67,
            "n_whitespaces": 158,
            "language": "en"
        }
    },
    {
        "id": 203036,
        "commit_id": "0a4a5e5bacc354df3132d0fcf706839c21afb89d",
        "repo": "django",
        "path": "django/contrib/admin/sites.py",
        "file_name": "sites.py",
        "fun_name": "login",
        "commit_message": "Refs #32681 -- Fixed VariableDoesNotExist when rendering some admin template.\n\nRegression in 84609b3205905097d7d3038d32e6101f012c0619.\r\n\r\nFollow up to 4e5bbb6ef2287126badd32842b239f4a8a7394ca.\r\n\r\nThanks Sourav Kumar for the report.",
        "code": "def login(self, request, extra_context=None):\n        \n        if request.method == 'GET' and self.has_permission(request):\n            # Already logged-in, redirect to admin index\n            index_path = reverse('admin:index', current_app=self.name)\n            return HttpResponseRedirect(index_path)\n\n        # Since this module gets imported in the application's root package,\n        # it cannot import models from other applications at the module level,\n        # and django.contrib.admin.forms eventually imports User.\n        from django.contrib.admin.forms import AdminAuthenticationForm\n        from django.contrib.auth.views import LoginView\n        context = {\n            **self.each_context(request),\n            'title': _('Log in'),\n            'subtitle': None,\n            'app_path': request.get_full_path(),\n            'username': request.user.get_username(),\n        }\n        if (REDIRECT_FIELD_NAME not in request.GET and\n                REDIRECT_FIELD_NAME not in request.POST):\n            context[REDIRECT_FIELD_NAME] = reverse('admin:index', current_app=self.name)\n        context.update(extra_context or {})\n\n        defaults = {\n            'extra_context': context,\n            'authentication_form': self.login_form or AdminAuthenticationForm,\n            'template_name': self.login_template or 'admin/login.html',\n        }\n        request.current_app = self.name\n        return LoginView.as_view(**defaults)(request)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 362,
        "n_words": 110,
        "vocab_size": 83,
        "complexity": 8,
        "nloc": 24,
        "token_counts": 187,
        "n_ast_nodes": 308,
        "n_identifiers": 33,
        "d_id": 50220,
        "documentation": {
            "docstring": "\n        Display the login form for the given HttpRequest.\n        ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 108020,
        "commit_id": "13147992b317c29c6e832ca7f6d05bf48aeb0718",
        "repo": "matplotlib",
        "path": "lib/matplotlib/texmanager.py",
        "file_name": "texmanager.py",
        "fun_name": "get_font_preamble",
        "commit_message": "Move towards making texmanager stateless.\n\nPreviously, TexManager needed to call get_font_config at a specific\nplace in the middle of processing to update some internal attributes\nbefore proceeding with TeX source generation.  Instead, move towards\nmaking TexManager stateless (except for caching), i.e. the user facing\nAPI should be thought of as a bunch of independently callable functions\n`make_tex()`, `make_dvi()`, etc. (they will probably stay as methods on\na \"empty\" TexManager object for a long time for backcompat, in fact).",
        "code": "def get_font_preamble(cls):\n        \n        font_preamble, command = cls._get_font_preamble_and_command()\n        return font_preamble\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 29,
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        "vocab_size": 8,
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        "token_counts": 17,
        "n_ast_nodes": 31,
        "n_identifiers": 5,
        "d_id": 23019,
        "documentation": {
            "docstring": "\n        Return a string containing font configuration for the tex preamble.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 178915,
        "commit_id": "abfb99b0a05dd76d2ecc6ebc20732a271857c6c8",
        "repo": "Nuitka",
        "path": "nuitka/freezer/IncludedDataFiles.py",
        "file_name": "IncludedDataFiles.py",
        "fun_name": "addIncludedDataFilesFromPackageOptions",
        "commit_message": "Plugins: Massive cleanup of data file handling\n\n* Move data file handling out of standalone only, allowing support\n  for other modes as well.\n\n* Attach logger and tags to data file objects.",
        "code": "def addIncludedDataFilesFromPackageOptions():\n    \n    # Cyclic dependency\n    from nuitka import ModuleRegistry\n\n    for module in ModuleRegistry.getDoneModules():\n        if module.isCompiledPythonPackage() or module.isUncompiledPythonPackage():\n            package_name = module.getFullName()\n\n            match, reason = package_name.matchesToShellPatterns(\n                patterns=getShallIncludePackageData()\n            )\n\n            if match:\n                package_directory = module.getCompileTimeDirectory()\n\n                pkg_filenames = getFileList(\n                    package_directory,\n                    ignore_dirs=(\"__pycache__\",),\n                    ignore_suffixes=(\".py\", \".pyw\", \".pyc\", \".pyo\", \".dll\")\n                    + getSharedLibrarySuffixes(),\n                )\n\n                if pkg_filenames:\n                    file_reason = \"package '%s' %s\" % (package_name, reason)\n\n                    for pkg_filename in pkg_filenames:\n                        rel_path = os.path.join(\n                            package_name.asPath(),\n                            os.path.relpath(pkg_filename, package_directory),\n                        )\n\n                        addIncludedDataFile(\n                            makeIncludedDataFile(\n                                source_path=pkg_filename,\n                                dest_path=rel_path,\n                                reason=file_reason,\n                                tracer=options_logger,\n                                tags=\"user,package_data\",\n                            )\n                        )\n\n    # Circular dependency\n    from nuitka.plugins.Plugins import Plugins\n\n    # Plugins provide per module through this.\n    for module in ModuleRegistry.getDoneModules():\n        for included_datafile in Plugins.considerDataFiles(module=module):\n            addIncludedDataFile(included_datafile)\n\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 734,
        "n_words": 97,
        "vocab_size": 70,
        "complexity": 9,
        "nloc": 36,
        "token_counts": 196,
        "n_ast_nodes": 319,
        "n_identifiers": 40,
        "d_id": 42860,
        "documentation": {
            "docstring": "Late data files, from plugins and user options that work with packages",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 206133,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/middleware/clickjacking.py",
        "file_name": "clickjacking.py",
        "fun_name": "get_xframe_options_value",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_xframe_options_value(self, request, response):\n        \n        return getattr(settings, \"X_FRAME_OPTIONS\", \"DENY\").upper()\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 23,
        "n_ast_nodes": 40,
        "n_identifiers": 7,
        "d_id": 51375,
        "documentation": {
            "docstring": "\n        Get the value to set for the X_FRAME_OPTIONS header. Use the value from\n        the X_FRAME_OPTIONS setting, or 'DENY' if not set.\n\n        This method can be overridden if needed, allowing it to vary based on\n        the request or response.\n        ",
            "n_words": 38,
            "vocab_size": 29,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 224047,
        "commit_id": "e7f07cc82ab2be920ab426ba07456d8b2592714d",
        "repo": "mkdocs",
        "path": "mkdocs/tests/config/config_options_tests.py",
        "file_name": "config_options_tests.py",
        "fun_name": "validate_config",
        "commit_message": "Remove spaces at the ends of docstrings, normalize quotes",
        "code": "def validate_config(self, config):\n        \n        site_dir = config_options.SiteDir()\n        docs_dir = config_options.Dir()\n\n        fname = os.path.join(os.path.abspath('..'), 'mkdocs.yml')\n\n        config['docs_dir'] = docs_dir.validate(config['docs_dir'])\n        config['site_dir'] = site_dir.validate(config['site_dir'])\n\n        schema = [\n            ('site_dir', site_dir),\n            ('docs_dir', docs_dir),\n        ]\n        cfg = Config(schema, fname)\n        cfg.load_dict(config)\n        failed, warned = cfg.validate()\n\n        if failed:\n            raise config_options.ValidationError(failed)\n\n        return True\n",
        "url": "https://github.com/mkdocs/mkdocs.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 166,
        "n_words": 42,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 120,
        "n_ast_nodes": 203,
        "n_identifiers": 21,
        "d_id": 57194,
        "documentation": {
            "docstring": "Given a config with values for site_dir and doc_dir, run site_dir post_validation.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 196621,
        "commit_id": "72a2eb0cd1dda000a1fe56bb0fc8ff1f3c119bd9",
        "repo": "sympy",
        "path": "sympy/algebras/quaternion.py",
        "file_name": "quaternion.py",
        "fun_name": "axis",
        "commit_message": "made changes",
        "code": "def axis(self):\n        \n        axis = self.vector_part().normalize()\n\n        return Quaternion(0, axis.b, axis.c, axis.d)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 55,
        "n_identifiers": 8,
        "d_id": 48054,
        "documentation": {
            "docstring": "\n        Returns the axis($\\mathbf{Ax}(q)$) of the quaternion.\n\n        Explanation\n        ===========\n\n        Given a quaternion $q = a + bi + cj + dk$ and returns $\\mathbf{Ax}(q)$ ie normalized versor (vector part) of that quaternion.\n        The axis is always an imaginary unit with square equal to $-1 + 0i + 0j + 0k$.\n\n        Examples\n        ========\n\n        >>> from sympy.algebras.quaternion import Quaternion\n        >>> q = Quaternion(1, 1, 1, 1)\n        >>> q.axis()\n        0 + sqrt(3)/3*i + sqrt(3)/3*j + sqrt(3)/3*k\n\n        See Also\n        ========\n\n        vector_part\n\n        ",
            "n_words": 76,
            "vocab_size": 59,
            "n_whitespaces": 182,
            "language": "en"
        }
    },
    {
        "id": 75039,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/formats.py",
        "file_name": "formats.py",
        "fun_name": "editor_attributes",
        "commit_message": "Reformat with black",
        "code": "def editor_attributes(self, image, alt_text):\n        \n        return {\n            \"data-embedtype\": \"image\",\n            \"data-id\": image.id,\n            \"data-format\": self.name,\n            \"data-alt\": escape(alt_text),\n        }\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 80,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 63,
        "n_identifiers": 7,
        "d_id": 16343,
        "documentation": {
            "docstring": "\n        Return additional attributes to go on the HTML element\n        when outputting this image within a rich text editor field\n        ",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 23181,
        "commit_id": "9f62b610dea6161627200ed85d92e19b1923279a",
        "repo": "PaddleOCR",
        "path": "ppocr/data/imaug/fce_targets.py",
        "file_name": "fce_targets.py",
        "fun_name": "find_head_tail",
        "commit_message": "add fcenet",
        "code": "def find_head_tail(self, points, orientation_thr):\n        \n\n        assert points.ndim == 2\n        assert points.shape[0] >= 4\n        assert points.shape[1] == 2\n        assert isinstance(orientation_thr, float)\n\n        if len(points) > 4:\n            pad_points = np.vstack([points, points[0]])\n            edge_vec = pad_points[1:] - pad_points[:-1]\n\n            theta_sum = []\n            adjacent_vec_theta = []\n            for i, edge_vec1 in enumerate(edge_vec):\n                adjacent_ind = [x % len(edge_vec) for x in [i - 1, i + 1]]\n                adjacent_edge_vec = edge_vec[adjacent_ind]\n                temp_theta_sum = np.sum(\n                    self.vector_angle(edge_vec1, adjacent_edge_vec))\n                temp_adjacent_theta = self.vector_angle(adjacent_edge_vec[0],\n                                                        adjacent_edge_vec[1])\n                theta_sum.append(temp_theta_sum)\n                adjacent_vec_theta.append(temp_adjacent_theta)\n            theta_sum_score = np.array(theta_sum) / np.pi\n            adjacent_theta_score = np.array(adjacent_vec_theta) / np.pi\n            poly_center = np.mean(points, axis=0)\n            edge_dist = np.maximum(\n                norm(\n                    pad_points[1:] - poly_center, axis=-1),\n                norm(\n                    pad_points[:-1] - poly_center, axis=-1))\n            dist_score = edge_dist / np.max(edge_dist)\n            position_score = np.zeros(len(edge_vec))\n            score = 0.5 * theta_sum_score + 0.15 * adjacent_theta_score\n            score += 0.35 * dist_score\n            if len(points) % 2 == 0:\n                position_score[(len(score) // 2 - 1)] += 1\n                position_score[-1] += 1\n            score += 0.1 * position_score\n            pad_score = np.concatenate([score, score])\n            score_matrix = np.zeros((len(score), len(score) - 3))\n            x = np.arange(len(score) - 3) / float(len(score) - 4)\n            gaussian = 1. / (np.sqrt(2. * np.pi) * 0.5) * np.exp(-np.power(\n                (x - 0.5) / 0.5, 2.) / 2)\n            gaussian = gaussian / np.max(gaussian)\n            for i in range(len(score)):\n                score_matrix[i, :] = score[i] + pad_score[(i + 2):(i + len(\n                    score) - 1)] * gaussian * 0.3\n\n            head_start, tail_increment = np.unravel_index(score_matrix.argmax(),\n                                                          score_matrix.shape)\n            tail_start = (head_start + tail_increment + 2) % len(points)\n            head_end = (head_start + 1) % len(points)\n            tail_end = (tail_start + 1) % len(points)\n\n            if head_end > tail_end:\n                head_start, tail_start = tail_start, head_start\n                head_end, tail_end = tail_end, head_end\n            head_inds = [head_start, head_end]\n            tail_inds = [tail_start, tail_end]\n        else:\n            if self.vector_slope(points[1] - points[0]) + self.vector_slope(\n                    points[3] - points[2]) < self.vector_slope(points[\n                        2] - points[1]) + self.vector_slope(points[0] - points[\n                            3]):\n                horizontal_edge_inds = [[0, 1], [2, 3]]\n                vertical_edge_inds = [[3, 0], [1, 2]]\n            else:\n                horizontal_edge_inds = [[3, 0], [1, 2]]\n                vertical_edge_inds = [[0, 1], [2, 3]]\n\n            vertical_len_sum = norm(points[vertical_edge_inds[0][0]] - points[\n                vertical_edge_inds[0][1]]) + norm(points[vertical_edge_inds[1][\n                    0]] - points[vertical_edge_inds[1][1]])\n            horizontal_len_sum = norm(points[horizontal_edge_inds[0][\n                0]] - points[horizontal_edge_inds[0][1]]) + norm(points[\n                    horizontal_edge_inds[1][0]] - points[horizontal_edge_inds[1]\n                                                         [1]])\n\n            if vertical_len_sum > horizontal_len_sum * orientation_thr:\n                head_inds = horizontal_edge_inds[0]\n                tail_inds = horizontal_edge_inds[1]\n            else:\n                head_inds = vertical_edge_inds[0]\n                tail_inds = vertical_edge_inds[1]\n\n        return head_inds, tail_inds\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1486,
        "n_words": 345,
        "vocab_size": 182,
        "complexity": 9,
        "nloc": 78,
        "token_counts": 831,
        "n_ast_nodes": 1235,
        "n_identifiers": 64,
        "d_id": 4527,
        "documentation": {
            "docstring": "Find the head edge and tail edge of a text polygon.\n\n        Args:\n            points (ndarray): The points composing a text polygon.\n            orientation_thr (float): The threshold for distinguishing between\n                head edge and tail edge among the horizontal and vertical edges\n                of a quadrangle.\n\n        Returns:\n            head_inds (list): The indexes of two points composing head edge.\n            tail_inds (list): The indexes of two points composing tail edge.\n        ",
            "n_words": 62,
            "vocab_size": 33,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 155342,
        "commit_id": "2ebc9cf51bfc773e3d4c898f5a33c0f60ad7ebc5",
        "repo": "modin",
        "path": "modin/pandas/base.py",
        "file_name": "base.py",
        "fun_name": "_is_dataframe",
        "commit_message": "REFACTOR-#5310: Remove some hasattr('columns') checks. (#5311)\n\nSigned-off-by: mvashishtha <mahesh@ponder.io>",
        "code": "def _is_dataframe(self) -> bool:\n        \n        return issubclass(self._pandas_class, pandas.DataFrame)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
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        "complexity": 1,
        "nloc": 14,
        "token_counts": 19,
        "n_ast_nodes": 32,
        "n_identifiers": 7,
        "d_id": 36344,
        "documentation": {
            "docstring": "\n        Tell whether this is a dataframe.\n\n        Ideally, other methods of BasePandasDataset shouldn't care whether this\n        is a dataframe or a series, but sometimes we need to know. This method\n        is better than hasattr(self, \"columns\"), which for series will call\n        self.__getattr__(\"columns\"), which requires materializing the index.\n\n        Returns\n        -------\n        bool : Whether this is a dataframe.\n        ",
            "n_words": 54,
            "vocab_size": 43,
            "n_whitespaces": 118,
            "language": "en"
        }
    },
    {
        "id": 31420,
        "commit_id": "b681e12d5963490d29c2a77ba7346ee050e46def",
        "repo": "transformers",
        "path": "src/transformers/models/vit_mae/modeling_tf_vit_mae.py",
        "file_name": "modeling_tf_vit_mae.py",
        "fun_name": "forward_loss",
        "commit_message": "[ViTMAE] Fix docstrings and variable names (#17710)\n\n* Fix docstrings and variable names\r\n\r\n* Rename x to something better\r\n\r\n* Improve messages\r\n\r\n* Fix docstrings and add test for greyscale images\r\n\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def forward_loss(self, pixel_values, pred, mask):\n        \n        target = self.patchify(pixel_values)\n        if self.config.norm_pix_loss:\n            mean = tf.reduce_mean(target, axis=-1, keepdims=True)\n            var = tf.math.reduce_variance(target, axis=-1, keepdims=True)\n            target = (target - mean) / (var + 1.0e-6) ** 0.5\n\n        loss = (pred - target) ** 2\n        loss = tf.reduce_mean(loss, axis=-1)  # [batch_size, num_patches], mean loss per patch\n\n        loss = tf.reduce_sum(loss * mask) / tf.reduce_sum(mask)  # mean loss on removed patches\n        return loss\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 148,
        "n_words": 64,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 125,
        "n_ast_nodes": 185,
        "n_identifiers": 19,
        "d_id": 5737,
        "documentation": {
            "docstring": "\n        Args:\n            pixel_values (`tf.Tensor` of shape `(batch_size, height, width, num_channels)`):\n                Pixel values.\n            pred (`tf.Tensor` of shape `(batch_size, num_patches, patch_size**2 * num_channels)`:\n                Predicted pixel values.\n            mask (`tf.Tensor` of shape `(batch_size, sequence_length)`):\n                Tensor indicating which patches are masked (1) and which are not (0).\n\n        Returns:\n            `tf.Tensor`: Pixel reconstruction loss.\n        ",
            "n_words": 46,
            "vocab_size": 34,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 208924,
        "commit_id": "adaa923db82be88e5bd84b4046faa23f2b69d0ed",
        "repo": "scapy",
        "path": "scapy/arch/bpf/supersocket.py",
        "file_name": "supersocket.py",
        "fun_name": "extract_frames",
        "commit_message": "Major BPF improvements\n\nThis adds:\n- timestamps support\n- structures of bpf_hdr\n- nanosecond precision on FREEBSD\n- cleanups",
        "code": "def extract_frames(self, bpf_buffer):\n        \n\n        # Ensure that the BPF buffer contains at least the header\n        len_bb = len(bpf_buffer)\n        if len_bb < _bpf_hdr_len:\n            return\n\n        # Extract useful information from the BPF header\n        bh_hdr = bpf_hdr.from_buffer_copy(bpf_buffer)\n        if bh_hdr.bh_datalen == 0:\n            return\n\n        # Get and store the Scapy object\n        frame_str = bpf_buffer[\n            bh_hdr.bh_hdrlen:bh_hdr.bh_hdrlen + bh_hdr.bh_caplen\n        ]\n        if _NANOTIME:\n            ts = bh_hdr.bh_tstamp.tv_sec + 1e-9 * bh_hdr.bh_tstamp.tv_nsec\n        else:\n            ts = bh_hdr.bh_tstamp.tv_sec + 1e-6 * bh_hdr.bh_tstamp.tv_usec\n        self.received_frames.append(\n            (self.guessed_cls, frame_str, ts)\n        )\n\n        # Extract the next frame\n        end = self.bpf_align(bh_hdr.bh_hdrlen, bh_hdr.bh_caplen)\n        if (len_bb - end) >= 20:\n            self.extract_frames(bpf_buffer[end:])\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 286,
        "n_words": 90,
        "vocab_size": 65,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 140,
        "n_ast_nodes": 218,
        "n_identifiers": 24,
        "d_id": 52575,
        "documentation": {
            "docstring": "\n        Extract all frames from the buffer and stored them in the received list\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 198655,
        "commit_id": "19114acf6514bc87f5c8cfde35e0fcab88965be7",
        "repo": "sympy",
        "path": "sympy/core/add.py",
        "file_name": "add.py",
        "fun_name": "as_content_primitive",
        "commit_message": "Code optimizations",
        "code": "def as_content_primitive(self, radical=False, clear=True):\n        \n        con, prim = self.func(*[_keep_coeff(*a.as_content_primitive(\n            radical=radical, clear=clear)) for a in self.args]).primitive()\n        if not clear and not con.is_Integer and prim.is_Add:\n            con, d = con.as_numer_denom()\n            _p = prim/d\n            if any(a.as_coeff_Mul()[0].is_Integer for a in _p.args):\n                prim = _p\n            else:\n                con /= d\n        if radical and prim.is_Add:\n            # look for common radicals that can be removed\n            args = prim.args\n            rads = []\n            common_q = None\n            for m in args:\n                term_rads = defaultdict(list)\n                for ai in Mul.make_args(m):\n                    if ai.is_Pow:\n                        b, e = ai.as_base_exp()\n                        if e.is_Rational and b.is_Integer:\n                            term_rads[e.q].append(abs(int(b))**e.p)\n                if not term_rads:\n                    break\n                if common_q is None:\n                    common_q = set(term_rads.keys())\n                else:\n                    common_q = common_q & set(term_rads.keys())\n                    if not common_q:\n                        break\n                rads.append(term_rads)\n            else:\n                # process rads\n                # keep only those in common_q\n                for r in rads:\n                    for q in list(r.keys()):\n                        if q not in common_q:\n                            r.pop(q)\n                    for q in r:\n                        r[q] = Mul(*r[q])\n                # find the gcd of bases for each q\n                G = []\n                for q in common_q:\n                    g = reduce(igcd, [r[q] for r in rads], 0)\n                    if g != 1:\n                        G.append(g**Rational(1, q))\n                if G:\n                    G = Mul(*G)\n                    args = [ai/G for ai in args]\n                    prim = G*prim.func(*args)\n\n        return con, prim\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 989,
        "n_words": 188,
        "vocab_size": 99,
        "complexity": 26,
        "nloc": 47,
        "token_counts": 369,
        "n_ast_nodes": 587,
        "n_identifiers": 46,
        "d_id": 49018,
        "documentation": {
            "docstring": "Return the tuple (R, self/R) where R is the positive Rational\n        extracted from self. If radical is True (default is False) then\n        common radicals will be removed and included as a factor of the\n        primitive expression.\n\n        Examples\n        ========\n\n        >>> from sympy import sqrt\n        >>> (3 + 3*sqrt(2)).as_content_primitive()\n        (3, 1 + sqrt(2))\n\n        Radical content can also be factored out of the primitive:\n\n        >>> (2*sqrt(2) + 4*sqrt(10)).as_content_primitive(radical=True)\n        (2, sqrt(2)*(1 + 2*sqrt(5)))\n\n        See docstring of Expr.as_content_primitive for more examples.\n        ",
            "n_words": 76,
            "vocab_size": 62,
            "n_whitespaces": 167,
            "language": "en"
        }
    },
    {
        "id": 154552,
        "commit_id": "e5b1888cd932909e49194d58035da34b210b91c4",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/hdk_on_native/calcite_builder.py",
        "file_name": "calcite_builder.py",
        "fun_name": "_add_projection",
        "commit_message": "FEAT-#4946: Replace OmniSci with HDK (#4947)\n\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Andrey Pavlenko <andrey.a.pavlenko@gmail.com>",
        "code": "def _add_projection(self, frame):\n        \n        proj = CalciteProjectionNode(\n            frame._table_cols, [self._ref(frame, col) for col in frame._table_cols]\n        )\n        self._push(proj)\n        return proj\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 63,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 41,
        "n_ast_nodes": 64,
        "n_identifiers": 9,
        "d_id": 36062,
        "documentation": {
            "docstring": "\n        Add a projection node to the resulting sequence.\n\n        Added node simply selects all frame's columns. This method can be used\n        to discard a virtual 'rowid' column provided by all scan nodes.\n\n        Parameters\n        ----------\n        frame : HdkOnNativeDataframe\n            An input frame for a projection.\n\n        Returns\n        -------\n        CalciteProjectionNode\n            Created projection node.\n        ",
            "n_words": 48,
            "vocab_size": 41,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 61288,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/parallel.py",
        "file_name": "parallel.py",
        "fun_name": "closing",
        "commit_message": "upd; format",
        "code": "def closing(pool):\n    # type: (Pool) -> Iterator[Pool]\n    \n    try:\n        yield pool\n    finally:\n        # For Pool.imap*, close and join are needed\n        # for the returned iterator to begin yielding.\n        pool.close()\n        pool.join()\n        pool.terminate()\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 84,
        "n_words": 30,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 27,
        "n_ast_nodes": 55,
        "n_identifiers": 5,
        "d_id": 12490,
        "documentation": {
            "docstring": "Return a context manager making sure the pool closes properly.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 154972,
        "commit_id": "7871c7bc5adeeaca9b6fc4b88482be8b18333faa",
        "repo": "modin",
        "path": "modin/pandas/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "_cov",
        "commit_message": "FEAT-#4989: Switch pandas version to 1.5 (#5037)\n\nCo-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>\r\nCo-authored-by: Anatoly Myachev <anatoliimyachev@mail.com>\r\nCo-authored-by: Jonathan Shi <jhshi07@gmail.com>\r\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Vasily Litvinov <fam1ly.n4me@yandex.ru>",
        "code": "def _cov(self, min_periods, ddof, numeric_only):  # noqa: PR01, RT01, D200\n        \n        if not numeric_only:\n            return self._default_to_pandas(\n                pandas.DataFrame.cov,\n                min_periods=min_periods,\n                ddof=ddof,\n                numeric_only=numeric_only,\n            )\n        numeric_df = self.drop(\n            columns=[\n                i for i in self.dtypes.index if not is_numeric_dtype(self.dtypes[i])\n            ]\n        )\n\n        is_notna = True\n\n        if all(numeric_df.notna().all()):\n            if min_periods is not None and min_periods > len(numeric_df):\n                result = np.empty((numeric_df.shape[1], numeric_df.shape[1]))\n                result.fill(np.nan)\n                return numeric_df.__constructor__(result)\n            else:\n                cols = numeric_df.columns\n                idx = cols.copy()\n                numeric_df = numeric_df.astype(dtype=\"float64\")\n                denom = 1.0 / (len(numeric_df) - ddof)\n                means = numeric_df.mean(axis=0)\n                result = numeric_df - means\n                result = result.T._query_compiler.conj().dot(result._query_compiler)\n        else:\n            result = numeric_df._query_compiler.cov(min_periods=min_periods)\n            is_notna = False\n\n        if is_notna:\n            result = numeric_df.__constructor__(\n                query_compiler=result, index=idx, columns=cols\n            )\n            result *= denom\n        else:\n            result = numeric_df.__constructor__(query_compiler=result)\n        return result\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 551,
        "n_words": 108,
        "vocab_size": 68,
        "complexity": 8,
        "nloc": 38,
        "token_counts": 265,
        "n_ast_nodes": 413,
        "n_identifiers": 41,
        "d_id": 36194,
        "documentation": {
            "docstring": "\n        Compute pairwise covariance of columns, excluding NA/null values.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 2529,
        "commit_id": "54c0a2f6738090252dc2b2863eb3c13b1bcb9e6a",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/node/common/node_service/oblv/oblv_messages.py",
        "file_name": "oblv_messages.py",
        "fun_name": "_object2proto",
        "commit_message": "Changes for publishing dataset and passing actions to enclave",
        "code": "def _object2proto(self) -> PublishDatasetMessage_PB:\n        \n        return PublishDatasetMessage_PB(\n            msg_id=serialize(self.id),\n            address=serialize(self.address),\n            reply_to=serialize(self.reply_to),\n            dataset_id=self.dataset_id,\n            deployment_id=self.deployment_id,\n            host_or_ip = self.host_or_ip,\n            protocol = self.protocol,\n            port = self.port,\n            client=serialize(self.client),\n        )\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 142,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 78,
        "n_ast_nodes": 115,
        "n_identifiers": 14,
        "d_id": 310,
        "documentation": {
            "docstring": "Returns a protobuf serialization of self.\n        As a requirement of all objects which inherit from Serializable,\n        this method transforms the current object into the corresponding\n        Protobuf object so that it can be further serialized.\n        :return: returns a protobuf object\n        :rtype: PublishDatasetMessage_PB\n        .. note::\n            This method is purely an internal method. Please use serialize(object) or one of\n            the other public serialization methods if you wish to serialize an\n            object.\n        ",
            "n_words": 68,
            "vocab_size": 56,
            "n_whitespaces": 150,
            "language": "en"
        }
    },
    {
        "id": 304852,
        "commit_id": "b043053aadab57435c768d1e0fe3892367686999",
        "repo": "core",
        "path": "homeassistant/components/gdacs/sensor.py",
        "file_name": "sensor.py",
        "fun_name": "async_update",
        "commit_message": "Improve entity type hints [g] (#77145)",
        "code": "async def async_update(self) -> None:\n        \n        _LOGGER.debug(\"Updating %s\", self._config_entry_id)\n        if self._manager:\n            status_info = self._manager.status_info()\n            if status_info:\n                self._update_from_status_info(status_info)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 74,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 41,
        "n_ast_nodes": 72,
        "n_identifiers": 8,
        "d_id": 103647,
        "documentation": {
            "docstring": "Update this entity from the data held in the feed manager.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 321330,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/browser/webengine/test_webenginetab.py",
        "file_name": "test_webenginetab.py",
        "fun_name": "test_notification_permission_workaround",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_notification_permission_workaround():\n    \n    try:\n        notifications = QWebEnginePage.Feature.Notifications\n    except AttributeError:\n        pytest.skip(\"No Notifications member\")\n\n    permissions = webenginetab._WebEnginePermissions\n    assert permissions._options[notifications] == 'content.notifications.enabled'\n    assert permissions._messages[notifications] == 'show notifications'\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 55,
        "n_words": 23,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 46,
        "n_ast_nodes": 82,
        "n_identifiers": 13,
        "d_id": 117667,
        "documentation": {
            "docstring": "Make sure the value for QWebEnginePage::Notifications is correct.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 108475,
        "commit_id": "686c9e5a413e31c46bb049407d5eca285bcab76d",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_preprocess_data.py",
        "file_name": "test_preprocess_data.py",
        "fun_name": "test_data_parameter_replacement",
        "commit_message": "Fix spelling errors",
        "code": "def test_data_parameter_replacement():\n    \n    program = (\n        \"import logging; \"\n        \"logging.basicConfig(level=logging.DEBUG); \"\n        \"import matplotlib.pyplot as plt\"\n    )\n    cmd = [sys.executable, \"-c\", program]\n    completed_proc = subprocess.run(cmd, text=True, capture_output=True)\n    assert 'data parameter docstring error' not in completed_proc.stderr\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 72,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 46,
        "n_ast_nodes": 81,
        "n_identifiers": 11,
        "d_id": 23206,
        "documentation": {
            "docstring": "\n    Test that the docstring contains the correct *data* parameter stub\n    for all methods that we run _preprocess_data() on.\n    ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 45435,
        "commit_id": "4ad21f5f7c2d416cf813a860564bc2bf3e161d46",
        "repo": "airflow",
        "path": "airflow/models/trigger.py",
        "file_name": "trigger.py",
        "fun_name": "submit_failure",
        "commit_message": "Log traceback in trigger excs (#21213)",
        "code": "def submit_failure(cls, trigger_id, exc=None, session=None):\n        \n        for task_instance in session.query(TaskInstance).filter(\n            TaskInstance.trigger_id == trigger_id, TaskInstance.state == State.DEFERRED\n        ):\n            # Add the error and set the next_method to the fail state\n            traceback = format_exception(type(exc), exc, exc.__traceback__) if exc else None\n            task_instance.next_method = \"__fail__\"\n            task_instance.next_kwargs = {\"error\": \"Trigger failure\", \"traceback\": traceback}\n            # Remove ourselves as its trigger\n            task_instance.trigger_id = None\n            # Finally, mark it as scheduled so it gets re-queued\n            task_instance.state = State.SCHEDULED\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 189,
        "n_words": 69,
        "vocab_size": 56,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 92,
        "n_ast_nodes": 149,
        "n_identifiers": 19,
        "d_id": 8565,
        "documentation": {
            "docstring": "\n        Called when a trigger has failed unexpectedly, and we need to mark\n        everything that depended on it as failed. Notably, we have to actually\n        run the failure code from a worker as it may have linked callbacks, so\n        hilariously we have to re-schedule the task instances to a worker just\n        so they can then fail.\n\n        We use a special __fail__ value for next_method to achieve this that\n        the runtime code understands as immediate-fail, and pack the error into\n        next_kwargs.\n\n        TODO: Once we have shifted callback (and email) handling to run on\n        workers as first-class concepts, we can run the failure code here\n        in-process, but we can't do that right now.\n        ",
            "n_words": 110,
            "vocab_size": 74,
            "n_whitespaces": 195,
            "language": "en"
        }
    },
    {
        "id": 20088,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distro.py",
        "file_name": "distro.py",
        "fun_name": "uname_attr",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def uname_attr(self, attribute):\n        # type: (str) -> str\n        \n        return self._uname_info.get(attribute, \"\")\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 3231,
        "documentation": {
            "docstring": "\n        Return a single named information item from the uname command\n        output data source of the OS distribution.\n\n        For details, see :func:`distro.uname_attr`.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 155050,
        "commit_id": "11ba4811e6db11740e11fd33d3cdfba8ce5bec54",
        "repo": "modin",
        "path": "modin/pandas/indexing.py",
        "file_name": "indexing.py",
        "fun_name": "_set_item_existing_loc",
        "commit_message": "FIX-#3764: Ensure df.loc with a scalar out of bounds appends to df (#3765)\n\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nCo-authored-by: Bill Wang <billiam@ponder.io>\r\nCo-authored-by: Vasily Litvinov <fam1ly.n4me@yandex.ru>",
        "code": "def _set_item_existing_loc(self, row_loc, col_loc, item):\n        \n        row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)\n        self._setitem_positional(\n            row_lookup,\n            col_lookup,\n            item,\n            axis=self._determine_setitem_axis(\n                row_lookup, col_lookup, is_scalar(row_loc), is_scalar(col_loc)\n            ),\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 119,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 56,
        "n_ast_nodes": 81,
        "n_identifiers": 12,
        "d_id": 36224,
        "documentation": {
            "docstring": "\n        Assign `item` value to dataset located by `row_loc` and `col_loc` with existing rows and columns.\n\n        Parameters\n        ----------\n        row_loc : scalar, slice, list, array or tuple\n            Row locator.\n        col_loc : scalar, slice, list, array or tuple\n            Columns locator.\n        item : modin.pandas.DataFrame, modin.pandas.Series or scalar\n            Value that should be assigned to located dataset.\n        ",
            "n_words": 51,
            "vocab_size": 38,
            "n_whitespaces": 134,
            "language": "en"
        }
    },
    {
        "id": 314748,
        "commit_id": "a8349a4866d22cddbca9ac9367d4affae39a8325",
        "repo": "core",
        "path": "tests/helpers/test_entityfilter.py",
        "file_name": "test_entityfilter.py",
        "fun_name": "test_exclude_glob_case5_include_strong",
        "commit_message": "Adjust entity filters to make includes stronger than excludes (#74080)\n\n* Adjust entity filters to make includes stronger than excludes\r\n\r\nFixes #59080\r\n\r\n* adjust test for stronger entity glob includes\r\n\r\n* sync with docs",
        "code": "def test_exclude_glob_case5_include_strong():\n    \n    incl_dom = {}\n    incl_glob = {}\n    incl_ent = {\"binary_sensor.working\"}\n    excl_dom = {\"binary_sensor\"}\n    excl_glob = {\"binary_sensor.*\"}\n    excl_ent = {\"light.ignoreme\", \"sensor.notworking\"}\n    testfilter = generate_filter(\n        incl_dom, incl_ent, excl_dom, excl_ent, incl_glob, excl_glob\n    )\n\n    assert testfilter(\"sensor.test\")\n    assert testfilter(\"sensor.notworking\") is False\n    assert testfilter(\"light.test\")\n    assert testfilter(\"light.ignoreme\") is False\n    assert testfilter(\"binary_sensor.working\")\n    assert testfilter(\"binary_sensor.another\") is False\n    assert testfilter(\"sun.sun\") is True\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 108,
        "n_words": 53,
        "vocab_size": 34,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 94,
        "n_ast_nodes": 172,
        "n_identifiers": 9,
        "d_id": 113352,
        "documentation": {
            "docstring": "Test case 5 - include and exclude specified, with excluded glob, and a specifically included entity.",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 168434,
        "commit_id": "e94faa23e24c0abf9db74d79cfebe06676577867",
        "repo": "pandas",
        "path": "pandas/core/computation/expressions.py",
        "file_name": "expressions.py",
        "fun_name": "_bool_arith_fallback",
        "commit_message": "WARN,TST check stacklevel for all warnings  (#47998)\n\n* use find_stack_level everywhere\n\n* fixup\n\n* pyx fixups\n\n* fixup test_optional_dependency\n\n* fixup api\n\n* set check_stacklevel=False for some tests\n\n* use lru_cache for currentframe\n\n* fixup import in __init__\n\n* add missing imports to pyx files\n\n* add missing import\n\n* fixup import in conversion\n\n* revert some __init__ changes\n\n* start n=1\n\n* temporarily dont check stacklevel in _check_plot_works\n\n* catch some more warnings\n\n* dont check stacklevel in check_plot_works\n\n* fixup\n\n* ignore stacklevel in check_plot_works",
        "code": "def _bool_arith_fallback(op_str, a, b):\n    \n    if _has_bool_dtype(a) and _has_bool_dtype(b):\n        if op_str in _BOOL_OP_UNSUPPORTED:\n            warnings.warn(\n                f\"evaluating in Python space because the {repr(op_str)} \"\n                \"operator is not supported by numexpr for the bool dtype, \"\n                f\"use {repr(_BOOL_OP_UNSUPPORTED[op_str])} instead.\",\n                stacklevel=find_stack_level(inspect.currentframe()),\n            )\n            return True\n    return False\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 150,
        "n_words": 41,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 52,
        "n_ast_nodes": 108,
        "n_identifiers": 13,
        "d_id": 40296,
        "documentation": {
            "docstring": "\n    Check if we should fallback to the python `_evaluate_standard` in case\n    of an unsupported operation by numexpr, which is the case for some\n    boolean ops.\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 270719,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/base_layer.py",
        "file_name": "base_layer.py",
        "fun_name": "compute_output_shape",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def compute_output_shape(self, input_shape):\n        \n        if tf.executing_eagerly():\n            # In this case we build the model first in order to do shape inference.\n            # This is acceptable because the framework only calls\n            # `compute_output_shape` on shape values that the layer would later be\n            # built for. It would however cause issues in case a user attempts to\n            # use `compute_output_shape` manually with shapes that are incompatible\n            # with the shape the Layer will be called on (these users will have to\n            # implement `compute_output_shape` themselves).\n            self._maybe_build(input_shape)\n            graph_name = str(self.name) + \"_scratch_graph\"\n            with tf.__internal__.FuncGraph(graph_name).as_default():\n                input_shape = tf_utils.convert_shapes(\n                    input_shape, to_tuples=False\n                )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 269,
        "n_words": 96,
        "vocab_size": 70,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 131,
        "n_ast_nodes": 105,
        "n_identifiers": 15,
        "d_id": 80542,
        "documentation": {
            "docstring": "Computes the output shape of the layer.\n\n        This method will cause the layer's state to be built, if that has not\n        happened before. This requires that the layer will later be used with\n        inputs that match the input shape provided here.\n\n        Args:\n            input_shape: Shape tuple (tuple of integers)\n                or list of shape tuples (one per output tensor of the layer).\n                Shape tuples can include None for free dimensions,\n                instead of an integer.\n\n        Returns:\n            An input shape tuple.\n        ",
            "n_words": 77,
            "vocab_size": 56,
            "n_whitespaces": 186,
            "language": "en"
        }
    },
    {
        "id": 255401,
        "commit_id": "83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd",
        "repo": "onnx",
        "path": "onnx/test/compose_test.py",
        "file_name": "compose_test.py",
        "fun_name": "test_error_wrong_input_output_name",
        "commit_message": "Use Python type annotations rather than comments (#3962)\n\n* These have been supported since Python 3.5.\r\n\r\nONNX doesn't support Python < 3.6, so we can use the annotations.\r\n\r\nDiffs generated by https://pypi.org/project/com2ann/.\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* Remove MYPY conditional logic in gen_proto.py\r\n\r\nIt breaks the type annotations and shouldn't be needed.\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* Get rid of MYPY bool from more scripts\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* move Descriptors class above where its referenced in type annotation\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fixes\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* remove extra blank line\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fix type annotations\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fix type annotation in gen_docs\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fix Operators.md\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fix TestCoverage.md\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>\r\n\r\n* fix protoc-gen-mypy.py\r\n\r\nSigned-off-by: Gary Miguel <garymiguel@microsoft.com>",
        "code": "def test_error_wrong_input_output_name(self) -> None:\n        \n        m1, m2 = _load_model(m1_def), _load_model(m2_def)\n\n        self.assertRaises(ValueError,\n                          compose.merge_models, m1, m2,\n                          io_map=[(\"wrong_outname\", \"B01\"), (\"B10\", \"B11\"), (\"B20\", \"B21\")])\n\n        # Wrong output name\n        self.assertRaises(ValueError,\n                          compose.merge_models, m1, m2,\n                          io_map=[(\"B00\", \"wrong_input\"), (\"B10\", \"B11\"), (\"B20\", \"B21\")])\n",
        "url": "https://github.com/onnx/onnx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 168,
        "n_words": 33,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 93,
        "n_ast_nodes": 154,
        "n_identifiers": 12,
        "d_id": 74741,
        "documentation": {
            "docstring": "\n        Tests that providing a non existing output/input name in the io_map argument produces an error.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 168984,
        "commit_id": "ae6dc976d334e791b3e215cf6e63a267675cccbe",
        "repo": "pandas",
        "path": "pandas/tests/io/formats/test_format.py",
        "file_name": "test_format.py",
        "fun_name": "get_local_am_pm",
        "commit_message": "BUG: Fixed Unicode decoding error in `Period.strftime` when a locale-specific directive is used (#46405)\n\n* Added test representative of #46319. Should fail on CI\r\n\r\n* Added a gha worker with non utf 8 zh_CN encoding\r\n\r\n* Attempt to fix the encoding so that locale works\r\n\r\n* Added the fix, but not using it for now, until CI is able to reproduce the issue.\r\n\r\n* Crazy idea: maybe simply removing the .utf8 modifier will use the right encoding !\r\n\r\n* Hopefully fixing the locale not available error\r\n\r\n* Now simply generating the locale, not updating the ubuntu one\r\n\r\n* Trying to install the locale without enabling it\r\n\r\n* Stupid mistake\r\n\r\n* Testing the optional locale generator condition\r\n\r\n* Put back all runners\r\n\r\n* Added whatsnew\r\n\r\n* Now using the fix\r\n\r\n* As per code review: moved locale-switching fixture `overridden_locale` to conftest\r\n\r\n* Flake8\r\n\r\n* Added comments on the runner\r\n\r\n* Added a non-utf8 locale in the `it_IT` runner. Added the zh_CN.utf8 locale in the tests\r\n\r\n* Improved readability of fixture `overridden_locale` as per code review\r\n\r\n* Added two comments on default encoding\r\n\r\n* Fixed #46319 by adding a new `char_to_string_locale` function in the `tslibs.util` module, able to decode char* using the current locale.\r\n\r\n* As per code review: modified the test to contain non-utf8 chars. Fixed the resulting issue.\r\n\r\n* Split the test in two for clarity\r\n\r\n* Fixed test and flake8 error.\r\n\r\n* Updated whatsnew to ref #46468 . Updated test name\r\n\r\n* Removing wrong whatsnew bullet\r\n\r\n* Nitpick on whatsnew as per code review\r\n\r\n* Fixed build error rst directive\r\n\r\n* Names incorrectly reverted in last merge commit\r\n\r\n* Fixed test_localization so that #46595 can be demonstrated on windows targets (even if today these do not run on windows targets, see #46597)\r\n\r\n* Fixed `tm.set_locale` context manager, it could error and leak when category LC_ALL was used. Fixed #46595\r\n\r\n* Removed the fixture as per code review, and added corresponding parametrization in tests.\r\n\r\n* Dummy mod to trigger CI again\r\n\r\n* reverted dummy mod\r\n\r\n* Attempt to fix the remaining error on the numpy worker\r\n\r\n* Fixed issue in `_from_ordinal`\r\n\r\n* Added asserts to try to understand\r\n\r\n* Reverted debugging asserts and applied fix for numpy repeat from #47670.\r\n\r\n* Fixed the last issue on numpy dev: a TypeError message had changed\r\n\r\n* Code review: Removed `EXTRA_LOC`\r\n\r\n* Code review: removed commented line\r\n\r\n* Code review: reverted out of scope change\r\n\r\n* Code review: reverted out of scope change\r\n\r\n* Fixed unused import\r\n\r\n* Fixed revert mistake\r\n\r\n* Moved whatsnew to 1.6.0\r\n\r\n* Update pandas/tests/io/parser/test_quoting.py\r\n\r\nCo-authored-by: Sylvain MARIE <sylvain.marie@se.com>",
        "code": "def get_local_am_pm():\n    \n    am_local = time(1).strftime(\"%p\")\n    pm_local = time(13).strftime(\"%p\")\n    return am_local, pm_local\n\n\n@pytest.fixture(params=[\"string\", \"pathlike\", \"buffer\"])",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(params=[\"string\", \"pathlike\", \"buffer\"])",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 25,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 86,
        "n_identifiers": 8,
        "d_id": 40362,
        "documentation": {
            "docstring": "Return the AM and PM strings returned by strftime in current locale.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 61043,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/req/req_uninstall.py",
        "file_name": "req_uninstall.py",
        "fun_name": "_get_directory_stash",
        "commit_message": "upd; format",
        "code": "def _get_directory_stash(self, path):\n        # type: (str) -> str\n        \n\n        try:\n            save_dir = AdjacentTempDirectory(path)  # type: TempDirectory\n        except OSError:\n            save_dir = TempDirectory(kind=\"uninstall\")\n        self._save_dirs[os.path.normcase(path)] = save_dir\n\n        return save_dir.path\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 90,
        "n_words": 25,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 46,
        "n_ast_nodes": 80,
        "n_identifiers": 11,
        "d_id": 12394,
        "documentation": {
            "docstring": "Stashes a directory.\n\n        Directories are stashed adjacent to their original location if\n        possible, or else moved/copied into the user's temp dir.",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 269628,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "sqrt",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def sqrt(x):\n    \n    zero = _constant_to_tensor(0.0, x.dtype.base_dtype)\n    x = tf.maximum(x, zero)\n    return tf.sqrt(x)\n\n\n@keras_export(\"keras.backend.exp\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.exp\")\n@tf.__internal__.dispatch.add_dispatch_support\n@doc_controls.do_not_generate_docs",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 24,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
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        "n_ast_nodes": 86,
        "n_identifiers": 14,
        "d_id": 80245,
        "documentation": {
            "docstring": "Element-wise square root.\n\n       This function clips negative tensor values to 0 before computing the\n       square root.\n\n    Args:\n        x: Tensor or variable.\n\n    Returns:\n        A tensor.\n    ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 42023,
        "commit_id": "5910d6ef50196c8bd1f4ed40a5da202a39d7f62c",
        "repo": "seaborn",
        "path": "seaborn/algorithms.py",
        "file_name": "algorithms.py",
        "fun_name": "_handle_random_seed",
        "commit_message": "docs: fix typos (#2899)\n\n* Small typo fixes\r\n\r\n* Catch an additional typo\r\n\r\nCo-authored-by: Michael Waskom <mwaskom@users.noreply.github.com>",
        "code": "def _handle_random_seed(seed=None):\n    \n    if isinstance(seed, np.random.RandomState):\n        rng = seed\n    else:\n        try:\n            # General interface for seeding on numpy >= 1.17\n            rng = np.random.default_rng(seed)\n        except AttributeError:\n            # We are on numpy < 1.17, handle options ourselves\n            if isinstance(seed, (numbers.Integral, np.integer)):\n                rng = np.random.RandomState(seed)\n            elif seed is None:\n                rng = np.random.RandomState()\n            else:\n                err = \"{} cannot be used to seed the random number generator\"\n                raise ValueError(err.format(seed))\n    return rng\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 224,
        "n_words": 65,
        "vocab_size": 49,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 97,
        "n_ast_nodes": 162,
        "n_identifiers": 15,
        "d_id": 7462,
        "documentation": {
            "docstring": "Given a seed in one of many formats, return a random number generator.\n\n    Generalizes across the numpy 1.17 changes, preferring newer functionality.\n\n    ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 207732,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "get_admin_form_fields",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_admin_form_fields(self, response):\n        \n        fields = []\n        for fieldset in response.context[\"adminform\"]:\n            for field_line in fieldset:\n                fields.extend(field_line)\n        return fields\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 71,
        "n_words": 17,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 35,
        "n_ast_nodes": 58,
        "n_identifiers": 8,
        "d_id": 52074,
        "documentation": {
            "docstring": "\n        Return a list of AdminFields for the AdminForm in the response.\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 259163,
        "commit_id": "1c094728a33f05bb6c83d7b856b87254964e0e8c",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_least_angle.py",
        "file_name": "_least_angle.py",
        "fun_name": "_fit",
        "commit_message": "CLN clean _preprocess_data in linear_model (#22762)",
        "code": "def _fit(self, X, y, max_iter, alpha, fit_path, normalize, Xy=None):\n        \n        n_features = X.shape[1]\n\n        X, y, X_offset, y_offset, X_scale = _preprocess_data(\n            X, y, self.fit_intercept, normalize, self.copy_X\n        )\n\n        if y.ndim == 1:\n            y = y[:, np.newaxis]\n\n        n_targets = y.shape[1]\n\n        Gram = self._get_gram(self.precompute, X, y)\n\n        self.alphas_ = []\n        self.n_iter_ = []\n        self.coef_ = np.empty((n_targets, n_features), dtype=X.dtype)\n\n        if fit_path:\n            self.active_ = []\n            self.coef_path_ = []\n            for k in range(n_targets):\n                this_Xy = None if Xy is None else Xy[:, k]\n                alphas, active, coef_path, n_iter_ = lars_path(\n                    X,\n                    y[:, k],\n                    Gram=Gram,\n                    Xy=this_Xy,\n                    copy_X=self.copy_X,\n                    copy_Gram=True,\n                    alpha_min=alpha,\n                    method=self.method,\n                    verbose=max(0, self.verbose - 1),\n                    max_iter=max_iter,\n                    eps=self.eps,\n                    return_path=True,\n                    return_n_iter=True,\n                    positive=self.positive,\n                )\n                self.alphas_.append(alphas)\n                self.active_.append(active)\n                self.n_iter_.append(n_iter_)\n                self.coef_path_.append(coef_path)\n                self.coef_[k] = coef_path[:, -1]\n\n            if n_targets == 1:\n                self.alphas_, self.active_, self.coef_path_, self.coef_ = [\n                    a[0]\n                    for a in (self.alphas_, self.active_, self.coef_path_, self.coef_)\n                ]\n                self.n_iter_ = self.n_iter_[0]\n        else:\n            for k in range(n_targets):\n                this_Xy = None if Xy is None else Xy[:, k]\n                alphas, _, self.coef_[k], n_iter_ = lars_path(\n                    X,\n                    y[:, k],\n                    Gram=Gram,\n                    Xy=this_Xy,\n                    copy_X=self.copy_X,\n                    copy_Gram=True,\n                    alpha_min=alpha,\n                    method=self.method,\n                    verbose=max(0, self.verbose - 1),\n                    max_iter=max_iter,\n                    eps=self.eps,\n                    return_path=False,\n                    return_n_iter=True,\n                    positive=self.positive,\n                )\n                self.alphas_.append(alphas)\n                self.n_iter_.append(n_iter_)\n            if n_targets == 1:\n                self.alphas_ = self.alphas_[0]\n                self.n_iter_ = self.n_iter_[0]\n\n        self._set_intercept(X_offset, y_offset, X_scale)\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1212,
        "n_words": 186,
        "vocab_size": 99,
        "complexity": 10,
        "nloc": 70,
        "token_counts": 519,
        "n_ast_nodes": 740,
        "n_identifiers": 51,
        "d_id": 75616,
        "documentation": {
            "docstring": "Auxiliary method to fit the model using X, y as training data",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 130362,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/autoscaler/_private/aliyun/utils.py",
        "file_name": "utils.py",
        "fun_name": "delete_instance",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def delete_instance(self, instance_id):\n        \n        request = DeleteInstanceRequest()\n        request.set_InstanceId(instance_id)\n        request.set_Force(True)\n        logging.info(\"Delete %s command submit successfully\", instance_id)\n        self._send_request(request)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 57,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 68,
        "n_identifiers": 10,
        "d_id": 29248,
        "documentation": {
            "docstring": "Release a pay-as-you-go instance or\n            an expired subscription instance.\n\n        :param instance_id: The ID of the instance that you want to release.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 59729,
        "commit_id": "e935e13e0f2abf2be02b548bbd7e874d131162b0",
        "repo": "prefect",
        "path": "src/prefect/orion/orchestration/rules.py",
        "file_name": "rules.py",
        "fun_name": "__aenter__",
        "commit_message": "Push nullified transition logic into GlobalTransforms\n\n- we may choose to run some bookkeeping even if a transition is aborted",
        "code": "async def __aenter__(self):\n        \n\n        await self.before_transition(self.context)\n        self.context.rule_signature.append(str(self.__class__))\n        return self.context\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 36,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 59,
        "n_identifiers": 8,
        "d_id": 11937,
        "documentation": {
            "docstring": "\n        Enter an async runtime context governed by this transform.\n\n        The `with` statement will bind a governed `OrchestrationContext` to the target\n        specified by the `as` clause. If the transition proposed by the\n        `OrchestrationContext` has been nullified on entry and `context.proposed_state`\n        is `None`, entering this context will do nothing. Otherwise\n        `self.before_transition` will fire.\n        ",
            "n_words": 51,
            "vocab_size": 40,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 87430,
        "commit_id": "9738a416a27cd77a3d9a2e506c31d8280e0bf1af",
        "repo": "sentry",
        "path": "src/sentry/runner/commands/spans.py",
        "file_name": "spans.py",
        "fun_name": "write_hashes",
        "commit_message": "feat(suspect-spans): Add CLI script for testing hashing output (#40668)\n\nAdds a CLI script for testing our spans hashes. Given a file, runs\r\ngrouping, and writes the result to a new JSON file.",
        "code": "def write_hashes(filename):\n    \n\n    [head, tail] = os.path.split(filename)\n    new_filename = f\"{head}/hashed-{tail}\"\n\n    shutil.copy(filename, new_filename)\n\n    with open(filename) as in_file:\n        data = json.loads(in_file.read())\n\n    click.echo(f\"Event ID: {data['event_id']}\")\n    click.echo(\"Writing span hashes\")\n\n    config = load_span_grouping_config({\"id\": DEFAULT_CONFIG_ID})\n    results = config.execute_strategy(data)\n\n    with open(new_filename, \"w\") as out_file:\n        results.write_to_event(data)\n        out_file.write(json.dumps(data, indent=4))\n\n    click.echo(\"Done\")\n    click.echo(\"\\n\")\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 98,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 126,
        "n_ast_nodes": 240,
        "n_identifiers": 28,
        "d_id": 18307,
        "documentation": {
            "docstring": "\n    Runs span hash grouping on event data in the supplied filename using the\n    default grouping strategy. Write the results to a copy of the file.\n    Filename should be a path to a JSON event data file.\n    ",
            "n_words": 36,
            "vocab_size": 26,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 200424,
        "commit_id": "24f1e7730119fe958cc8e28411f790c9a5ec04eb",
        "repo": "sympy",
        "path": "sympy/physics/secondquant.py",
        "file_name": "secondquant.py",
        "fun_name": "_get_ordered_dummies",
        "commit_message": "Fix various typos\n\nFound via `codespell -q 3 -L aboves,aline,ans,aother,arithmetics,assum,atleast,braket,clen,declar,declars,dorder,dum,enew,fo,fro,inout,iself,ist,ket,lamda,lightyear,lightyears,nd,numer,numers,orderd,ot,pring,rcall,rever,ro,ser,siz,splitted,sring,supercedes,te,tht,unequality,upto,vas,versin,whet`",
        "code": "def _get_ordered_dummies(mul, verbose=False):\n    \n    # setup dicts to avoid repeated calculations in key()\n    args = Mul.make_args(mul)\n    fac_dum = { fac: fac.atoms(Dummy) for fac in args }\n    fac_repr = { fac: __kprint(fac) for fac in args }\n    all_dums = set().union(*fac_dum.values())\n    mask = {}\n    for d in all_dums:\n        if d.assumptions0.get('below_fermi'):\n            mask[d] = '0'\n        elif d.assumptions0.get('above_fermi'):\n            mask[d] = '1'\n        else:\n            mask[d] = '2'\n    dum_repr = {d: __kprint(d) for d in all_dums}\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 148,
        "n_words": 67,
        "vocab_size": 43,
        "complexity": 13,
        "nloc": 26,
        "token_counts": 258,
        "n_ast_nodes": 211,
        "n_identifiers": 21,
        "d_id": 49638,
        "documentation": {
            "docstring": "Returns all dummies in the mul sorted in canonical order.\n\n    Explanation\n    ===========\n\n    The purpose of the canonical ordering is that dummies can be substituted\n    consistently across terms with the result that equivalent terms can be\n    simplified.\n\n    It is not possible to determine if two terms are equivalent based solely on\n    the dummy order.  However, a consistent substitution guided by the ordered\n    dummies should lead to trivially (non-)equivalent terms, thereby revealing\n    the equivalence.  This also means that if two terms have identical sequences of\n    dummies, the (non-)equivalence should already be apparent.\n\n    Strategy\n    --------\n\n    The canonical order is given by an arbitrary sorting rule.  A sort key\n    is determined for each dummy as a tuple that depends on all factors where\n    the index is present.  The dummies are thereby sorted according to the\n    contraction structure of the term, instead of sorting based solely on the\n    dummy symbol itself.\n\n    After all dummies in the term has been assigned a key, we check for identical\n    keys, i.e. unorderable dummies.  If any are found, we call a specialized\n    method, _determine_ambiguous(), that will determine a unique order based\n    on recursive calls to _get_ordered_dummies().\n\n    Key description\n    ---------------\n\n    A high level description of the sort key:\n\n        1. Range of the dummy index\n        2. Relation to external (non-dummy) indices\n        3. Position of the index in the first factor\n        4. Position of the index in the second factor\n\n    The sort key is a tuple with the following components:\n\n        1. A single character indicating the range of the dummy (above, below\n           or general.)\n        2. A list of strings with fully masked string representations of all\n           factors where the dummy is present.  By masked, we mean that dummies\n           are represented by a symbol to indicate either below fermi, above or\n           general.  No other information is displayed about the dummies at\n           this point.  The list is sorted stringwise.\n        3. An integer number indicating the position of the index, in the first\n           factor as sorted in 2.\n        4. An integer number indicating the position of the index, in the second\n           factor as sorted in 2.\n\n    If a factor is either of type AntiSymmetricTensor or SqOperator, the index\n    position in items 3 and 4 is indicated as 'upper' or 'lower' only.\n    (Creation operators are considered upper and annihilation operators lower.)\n\n    If the masked factors are identical, the two factors cannot be ordered\n    unambiguously in item 2.  In this case, items 3, 4 are left out.  If several\n    indices are contracted between the unorderable factors, it will be handled by\n    _determine_ambiguous()\n\n\n    ",
            "n_words": 415,
            "vocab_size": 207,
            "n_whitespaces": 650,
            "language": "en"
        }
    },
    {
        "id": 42525,
        "commit_id": "8b43b49b0cd8c12cae1d48df27edfdd98cf859fd",
        "repo": "nltk",
        "path": "nltk/corpus/reader/verbnet.py",
        "file_name": "verbnet.py",
        "fun_name": "_pprint_semantics_within_frame",
        "commit_message": "Read 'bool' field from VerbNet",
        "code": "def _pprint_semantics_within_frame(self, vnframe, indent=\"\"):\n        \n        pieces = []\n        for predicate in vnframe[\"semantics\"]:\n            arguments = [argument[\"value\"] for argument in predicate[\"arguments\"]]\n            pieces.append(\n                f\"{'¬' if predicate['negated'] else ''}{predicate['predicate_value']}({', '.join(arguments)})\"\n            )\n        return \"\\n\".join(f\"{indent}* {piece}\" for piece in pieces)\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 109,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 58,
        "n_ast_nodes": 151,
        "n_identifiers": 11,
        "d_id": 7592,
        "documentation": {
            "docstring": "Returns a pretty printed version of semantics within frame in a VerbNet class\n\n        Return a string containing a pretty-printed representation of\n        the given VerbNet frame semantics.\n\n        :param vnframe: An ElementTree containing the xml contents of\n            a VerbNet frame.\n        ",
            "n_words": 38,
            "vocab_size": 27,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 213595,
        "commit_id": "d743336b1f3654cd0315f380f43eed4116997c1d",
        "repo": "ivy",
        "path": "ivy/core/device.py",
        "file_name": "device.py",
        "fun_name": "dev_clone_iter",
        "commit_message": "renamed dev_str arg to dev for all methods.",
        "code": "def dev_clone_iter(xs, devs):\n    \n    if isinstance(devs, str):\n        devs = [devs]\n    return DevClonedIter([dev_clone(x, devs) for x in xs], devs)\n\n",
        "url": "https://github.com/unifyai/ivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 60,
        "n_identifiers": 8,
        "d_id": 53667,
        "documentation": {
            "docstring": "\n    Clone elements of the iterbale xs to each of the specified devices.\n\n    :param xs: The iterable of items to clone.\n    :type xs: iterable of any\n    :param devs: The devices to clone each of the iterable elements to.\n    :type devs: sequence of strs\n    :return: iterable with each element cloned to each of the target devices\n    ",
            "n_words": 54,
            "vocab_size": 29,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 117468,
        "commit_id": "9ce5a21dd6359fd7e8ebf78051ce9e97bd195ec9",
        "repo": "mindsdb",
        "path": "tests/unit/ml_handlers/test_lightwood.py",
        "file_name": "test_lightwood.py",
        "fun_name": "test_ts",
        "commit_message": "ML handler supbrocess (#3377)\n\n* log -> logger\r\n\r\ndividing components:\r\n\r\napp initialize\r\n    parse args\r\n    set env.MINDSDB_CONFIG_PATH\r\n\r\nconfig\r\n    requiers env.MINDSDB_CONFIG_PATH\r\n    sets\r\n        env.MINDSDB_DB_CON\r\n    Config() - makes initialization\r\n\r\nlog\r\n    uses config\r\n    initialize_log - makes initialization\r\n\r\ndatabase\r\n    uses env.MINDSDB_DB_CON\r\n    have init() method\r\n\r\nfile storage\r\n    uses config\r\n\r\n* partial sync for model storage interfaces\r\n\r\n* ml handler in subprocess interface\r\n\r\n* fix delete model\r\n\r\n* fix: model with error in success status\r\n\r\n* fix: remove hf predictor\r\n\r\n* fix pg handler\r\n\r\n* MLHandlerPersistWrapper keeps wrapper process opened\r\n\r\n* predictor with error keeps 'success' status\r\n\r\n#3362\r\n\r\n* lock for sending tasks to subprocess one by one\r\n\r\n* check target of predictor before run learn in subproccess\r\n\r\n* fix check target\r\n\r\n* fix: json_ai override and problem definition generation\r\n\r\n* fix None case\r\n\r\n* folder for ml handler tests\r\n\r\n* fix: add timeseries_settings key to learn_args\r\n\r\n* fixes in lw_handler\r\n\r\n* fix: del join_learn_process\r\n\r\n* tests for LW handler\r\n\r\n* finish unit test for LW\r\n\r\n* changes in tests:\r\n- set-project -> to base class\r\n- return of ml handler is dataframe\r\n- draft for project structure test\r\n\r\n* merge from staging\r\n\r\n* create_validation method to check learn params before send to subprocess\r\nfixes of HF\r\nfixed version of transformers in HF requirements\r\n\r\nCo-authored-by: Patricio Cerda Mardini <pcerdam@live.com>",
        "code": "def test_ts(self, mock_handler):\n        # TS\n        df2 = pd.DataFrame(pd.date_range(start='1/1/2018', end='1/31/2018'), columns=['t'])\n        df3 = df2.copy()\n\n        df2['a'] = 'a'\n        df2['x'] = range(1, 32)\n\n        df3['a'] = 'b'\n        df3['x'] = range(11, 42)\n\n        df = pd.concat([df2, df3])\n        self.set_handler(mock_handler, name='pg', tables={'df': df})\n\n        # create project\n        self.run_sql('create database proj')\n\n        # TS predictor\n        # create predictor\n        self.run_sql()\n        self.wait_predictor('proj', 'modelx')\n\n        # run predict\n        ret = self.run_sql()\n        # LW can predict\n        assert list(ret.x) == [42, 43, 44]\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 198,
        "n_words": 66,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 27,
        "token_counts": 146,
        "n_ast_nodes": 258,
        "n_identifiers": 23,
        "d_id": 26011,
        "documentation": {
            "docstring": "\n           create model proj.modelx\n           from pg (select * from df)\n           predict x\n           order by t\n           group by a\n           window 5\n           horizon 3\n        \n           SELECT p.*\n           FROM pg.df as t \n           JOIN proj.modelx as p\n           where t.a='b' and t.t > latest\n        ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 164,
            "language": "en"
        }
    },
    {
        "id": 62899,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/packaging/tags.py",
        "file_name": "tags.py",
        "fun_name": "sys_tags",
        "commit_message": "upd; format",
        "code": "def sys_tags(**kwargs):\n    # type: (bool) -> Iterator[Tag]\n    \n    warn = _warn_keyword_parameter(\"sys_tags\", kwargs)\n\n    interp_name = interpreter_name()\n    if interp_name == \"cp\":\n        for tag in cpython_tags(warn=warn):\n            yield tag\n    else:\n        for tag in generic_tags():\n            yield tag\n\n    for tag in compatible_tags():\n        yield tag\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 101,
        "n_words": 37,
        "vocab_size": 24,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 57,
        "n_ast_nodes": 102,
        "n_identifiers": 10,
        "d_id": 13065,
        "documentation": {
            "docstring": "\n    Returns the sequence of tag triples for the running interpreter.\n\n    The order of the sequence corresponds to priority order for the\n    interpreter, from most to least important.\n    ",
            "n_words": 27,
            "vocab_size": 19,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 11938,
        "commit_id": "dd5f08e9d0c535de2f0e6b106db3b21c597752cd",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/runtimes/remote.py",
        "file_name": "remote.py",
        "fun_name": "mixin_http_gateway_parser",
        "commit_message": "feat: add grpc tls support on gateway (#4522)",
        "code": "def mixin_http_gateway_parser(parser=None):\n    \n    gp = add_arg_group(parser, title='HTTP Gateway')\n\n    gp.add_argument(\n        '--title',\n        type=str,\n        help='The title of this HTTP server. It will be used in automatics docs such as Swagger UI.',\n    )\n\n    gp.add_argument(\n        '--description',\n        type=str,\n        help='The description of this HTTP server. It will be used in automatics docs such as Swagger UI.',\n    )\n\n    gp.add_argument(\n        '--cors',\n        action='store_true',\n        default=False,\n        help=,\n    )\n\n    gp.add_argument(\n        '--default-swagger-ui',\n        action='store_true',\n        default=False,\n        help='If set, the default swagger ui is used for `/docs` endpoint. ',\n    )\n\n    gp.add_argument(\n        '--no-debug-endpoints',\n        action='store_true',\n        default=False,\n        help='If set, /status /post endpoints are removed from HTTP interface. ',\n    )\n\n    gp.add_argument(\n        '--no-crud-endpoints',\n        action='store_true',\n        default=False,\n        help=,\n    )\n\n    gp.add_argument(\n        '--expose-endpoints',\n        type=str,\n        help=,\n    )\n\n    gp.add_argument(\n        '--uvicorn-kwargs',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n\n    gp.add_argument(\n        '--grpc-server-kwargs',\n        action=KVAppendAction,\n        metavar='KEY: VALUE',\n        nargs='*',\n        help=,\n    )\n\n    gp.add_argument(\n        '--ssl-certfile',\n        type=str,\n        help=,\n        dest='ssl_certfile',\n    )\n\n    gp.add_argument(\n        '--ssl-keyfile',\n        type=str,\n        help=,\n        dest='ssl_keyfile',\n    )\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 500,
        "n_words": 127,
        "vocab_size": 66,
        "complexity": 1,
        "nloc": 86,
        "token_counts": 223,
        "n_ast_nodes": 378,
        "n_identifiers": 15,
        "d_id": 2141,
        "documentation": {
            "docstring": "Add the options to rest server\n\n    :param parser: the parser\n    \n        If set, a CORS middleware is added to FastAPI frontend to allow cross-origin access.\n        \n        If set, /index, /search, /update, /delete endpoints are removed from HTTP interface.\n\n        Any executor that has `@requests(on=...)` bind with those values will receive data requests.\n        \n        A JSON string that represents a map from executor endpoints (`@requests(on=...)`) to HTTP endpoints.\n        \nDictionary of kwargs arguments that will be passed to Uvicorn server when starting the server\n\nMore details can be found in Uvicorn docs: https://www.uvicorn.org/settings/\n\n\n    Dictionary of kwargs arguments that will be passed to the grpc server when starting the server # todo update\n    \n        the path to the certificate file\n        \n        the path to the key file\n        ",
            "n_words": 118,
            "vocab_size": 75,
            "n_whitespaces": 211,
            "language": "en"
        }
    },
    {
        "id": 21454,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py",
        "file_name": "tarfile.py",
        "fun_name": "next",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def next(self):\n        \n        self._check(\"ra\")\n        if self.firstmember is not None:\n            m = self.firstmember\n            self.firstmember = None\n            return m\n\n        # Read the next block.\n        self.fileobj.seek(self.offset)\n        tarinfo = None\n        while True:\n            try:\n                tarinfo = self.tarinfo.fromtarfile(self)\n            except EOFHeaderError as e:\n                if self.ignore_zeros:\n                    self._dbg(2, \"0x%X: %s\" % (self.offset, e))\n                    self.offset += BLOCKSIZE\n                    continue\n            except InvalidHeaderError as e:\n                if self.ignore_zeros:\n                    self._dbg(2, \"0x%X: %s\" % (self.offset, e))\n                    self.offset += BLOCKSIZE\n                    continue\n                elif self.offset == 0:\n                    raise ReadError(str(e))\n            except EmptyHeaderError:\n                if self.offset == 0:\n                    raise ReadError(\"empty file\")\n            except TruncatedHeaderError as e:\n                if self.offset == 0:\n                    raise ReadError(str(e))\n            except SubsequentHeaderError as e:\n                raise ReadError(str(e))\n            break\n\n        if tarinfo is not None:\n            self.members.append(tarinfo)\n        else:\n            self._loaded = True\n\n        return tarinfo\n\n    #--------------------------------------------------------------------------\n    # Little helper methods:\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 596,
        "n_words": 112,
        "vocab_size": 58,
        "complexity": 14,
        "nloc": 37,
        "token_counts": 211,
        "n_ast_nodes": 353,
        "n_identifiers": 24,
        "d_id": 3847,
        "documentation": {
            "docstring": "Return the next member of the archive as a TarInfo object, when\n           TarFile is opened for reading. Return None if there is no more\n           available.\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 189989,
        "commit_id": "309c9d41eb734ca85a7aea5533f88a6d4ee7c944",
        "repo": "manim",
        "path": "manim/mobject/svg/svg_mobject.py",
        "file_name": "svg_mobject.py",
        "fun_name": "generate_config_style_dict",
        "commit_message": "Ported improved implementation of :class:`.SVGMobject` from 3b1b/manim (#2898)\n\n* port SVGMobject from 3b1b/manim\r\n\r\n* added svgelements as dependency\r\n\r\n* revert change of default values\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* set default stroke_width of svg elements to 0 if not set\r\n\r\n* fix handling of circles with different rx/ry\r\n\r\n* turn more methods into staticmethods\r\n\r\n* removed duplicated method\r\n\r\n* set/adapt stroke-width of some test SVGs\r\n\r\n* updated control data\r\n\r\n* forgot some control data\r\n\r\n* fixed init_colors in tex_mobject and text_mobject\r\n\r\n* minor changes, added docstrings\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* module docstring, removed import\r\n\r\n* vector_to_coords changed again\r\n\r\n* nail sphinx version to below 5.1 to fix rtd (?)\r\n\r\n* update test_text control data for science\r\n\r\n* changed Brace to use VMobjectFromSVGPath\r\n\r\n* remove unused classes and methods depending on old SVG path implementation\r\n\r\n* remove style_utils and svg_path modules\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* change test_text to use monospace font\r\n\r\n* restore geometry.polygram\r\n\r\n* added get_mobject_type_class auxiliary method; changed polyline implementation to ad-hoc approach\r\n\r\n* restore test_text to previous version\r\n\r\n* skip Use tags as svgelements already populates them\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def generate_config_style_dict(self) -> dict[str, str]:\n        \n        keys_converting_dict = {\n            \"fill\": (\"color\", \"fill_color\"),\n            \"fill-opacity\": (\"opacity\", \"fill_opacity\"),\n            \"stroke\": (\"color\", \"stroke_color\"),\n            \"stroke-opacity\": (\"opacity\", \"stroke_opacity\"),\n            \"stroke-width\": (\"stroke_width\",),\n        }\n        svg_default_dict = self.svg_default\n        result = {}\n        for svg_key, style_keys in keys_converting_dict.items():\n            for style_key in style_keys:\n                if svg_default_dict[style_key] is None:\n                    continue\n                result[svg_key] = str(svg_default_dict[style_key])\n        return result\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 212,
        "n_words": 48,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 104,
        "n_ast_nodes": 180,
        "n_identifiers": 12,
        "d_id": 46283,
        "documentation": {
            "docstring": "Generate a dictionary holding the default style information.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 116615,
        "commit_id": "0dadd5cecec68f252a08637f695b0e4b573b316f",
        "repo": "mindsdb",
        "path": "tests/unit/test_executor.py",
        "file_name": "test_executor.py",
        "fun_name": "test_update_from_select",
        "commit_message": "support of update command\n#2454",
        "code": "def test_update_from_select(self, mock_handler):\n        self.set_handler(mock_handler, name='pg', tables={'tasks': self.df})\n\n        # --- use predictor ---\n        predictor = {\n            'name': 'task_model',\n            'predict': 'p',\n            'dtypes': {\n                'p': dtype.float,\n                'a': dtype.integer,\n                'b': dtype.categorical,\n                'c': dtype.datetime\n            },\n            'predicted_value': 'ccc'\n        }\n        self.set_predictor(predictor)\n        sql = \n\n        ret = self.command_executor.execute_command(\n            parse_sql(sql, dialect='mindsdb'))\n        assert ret.error_code is None\n\n        # 1 select and 2 updates\n        assert mock_handler().query.call_count == 3\n\n        # second is update\n        assert mock_handler().query.call_args_list[1][0][0].to_string() == \"update table2 set a1=1, c1='ccc' where (a1 = 1) AND (b1 = 'ccc')\"\n\n\n    # @patch('mindsdb.integrations.handlers.postgres_handler.Handler')\n    # def test_union_type_mismatch(self, mock_handler):\n    #     self.set_handler(mock_handler, name='pg', tables={'tasks': self.df})\n    #\n    #     sql = \n    #     from mindsdb.api.mysql.mysql_proxy.utilities import ErSqlWrongArguments\n    #     with pytest.raises(ErSqlWrongArguments):\n    #         self.command_executor.execute_command(parse_sql(sql, dialect='mindsdb'))\n\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 360,
        "n_words": 101,
        "vocab_size": 71,
        "complexity": 1,
        "nloc": 37,
        "token_counts": 135,
        "n_ast_nodes": 247,
        "n_identifiers": 25,
        "d_id": 25796,
        "documentation": {
            "docstring": "\n            update \n                pg.table2                   \n            set\n                a1 = df.a,\n                c1 = df.c\n            from                            \n                (\n                    SELECT model.a as a, model.b as b, model.p as c\n                      FROM pg.tasks as t\n                     JOIN mindsdb.task_model as model\n                     WHERE t.a=1 \n                )\n                as df\n            where  \n                table2.a1 = df.a \n                and table2.b1 = df.b     \n        \n    #          SELECT a, b  FROM pg.tasks\n    #        UNION\n    #          SELECT b, a  FROM pg.tasks\n    #     ",
            "n_words": 57,
            "vocab_size": 38,
            "n_whitespaces": 410,
            "language": "en"
        }
    },
    {
        "id": 192761,
        "commit_id": "e556640badaa3d565e8a1238154265eaccf9f49c",
        "repo": "vision",
        "path": "references/segmentation/utils.py",
        "file_name": "utils.py",
        "fun_name": "synchronize_between_processes",
        "commit_message": "Reduce variance of evaluation in reference (#5819)\n\n* Change code to reduce variance in eval\r\n\r\n* Remove unnecessary new line\r\n\r\n* Fix missing import warnings\r\n\r\n* Fix the warning on video_classification\r\n\r\n* Fix bug to get len of UniformClipSampler",
        "code": "def synchronize_between_processes(self):\n        \n        t = reduce_across_processes([self.count, self.total])\n        t = t.tolist()\n        self.count = int(t[0])\n        self.total = t[1]\n",
        "url": "https://github.com/pytorch/vision.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 50,
        "n_words": 15,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 75,
        "n_identifiers": 8,
        "d_id": 46906,
        "documentation": {
            "docstring": "\n        Warning: does not synchronize the deque!\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 48187,
        "commit_id": "766726f2e3a282fcd2662f5dc6e9926dc38a6540",
        "repo": "airflow",
        "path": "airflow/providers/google/cloud/transfers/sql_to_gcs.py",
        "file_name": "sql_to_gcs.py",
        "fun_name": "convert_types",
        "commit_message": "Fix `PostgresToGCSOperator` does not allow nested JSON (#23063)\n\n* Avoid double json.dumps for json data export in PostgresToGCSOperator.\r\n\r\n* Fix CI",
        "code": "def convert_types(self, schema, col_type_dict, row, stringify_dict=False) -> list:\n        \n        return [\n            self.convert_type(value, col_type_dict.get(name), stringify_dict=stringify_dict)\n            for name, value in zip(schema, row)\n        ]\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 49,
        "n_ast_nodes": 71,
        "n_identifiers": 12,
        "d_id": 9394,
        "documentation": {
            "docstring": "Convert values from DBAPI to output-friendly formats.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 132303,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/suggest/basic_variant.py",
        "file_name": "basic_variant.py",
        "fun_name": "__next__",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def __next__(self):\n        \n\n        if \"run\" not in self.unresolved_spec:\n            raise TuneError(\"Must specify `run` in {}\".format(self.unresolved_spec))\n\n        if self.variants and self.variants.has_next():\n            # This block will be skipped upon instantiation.\n            # `variants` will be set later after the first loop.\n            resolved_vars, spec = next(self.variants)\n            return self.create_trial(resolved_vars, spec)\n\n        if self.points_to_evaluate:\n            config = self.points_to_evaluate.pop(0)\n            self.num_samples_left -= 1\n            self.variants = _VariantIterator(\n                get_preset_variants(\n                    self.unresolved_spec,\n                    config,\n                    constant_grid_search=self.constant_grid_search,\n                    random_state=self.random_state,\n                ),\n                lazy_eval=self.lazy_eval,\n            )\n            resolved_vars, spec = next(self.variants)\n            return self.create_trial(resolved_vars, spec)\n        elif self.num_samples_left > 0:\n            self.variants = _VariantIterator(\n                generate_variants(\n                    self.unresolved_spec,\n                    constant_grid_search=self.constant_grid_search,\n                    random_state=self.random_state,\n                ),\n                lazy_eval=self.lazy_eval,\n            )\n            self.num_samples_left -= 1\n            resolved_vars, spec = next(self.variants)\n            return self.create_trial(resolved_vars, spec)\n        else:\n            raise StopIteration\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 547,
        "n_words": 95,
        "vocab_size": 58,
        "complexity": 6,
        "nloc": 34,
        "token_counts": 200,
        "n_ast_nodes": 312,
        "n_identifiers": 22,
        "d_id": 29734,
        "documentation": {
            "docstring": "Generates Trial objects with the variant generation process.\n\n        Uses a fixed point iteration to resolve variants. All trials\n        should be able to be generated at once.\n\n        See also: `ray.tune.suggest.variant_generator`.\n\n        Returns:\n            Trial object\n        ",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 259453,
        "commit_id": "75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_glm/tests/test_glm.py",
        "file_name": "test_glm.py",
        "fun_name": "test_tweedie_link_auto",
        "commit_message": "ENH migrate GLMs / TweedieRegressor to linear loss (#22548)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def test_tweedie_link_auto(power, expected_link_class):\n    \n    y = np.array([0.1, 0.5])  # in range of all distributions\n    X = np.array([[1], [2]])\n    glm = TweedieRegressor(link=\"auto\", power=power).fit(X, y)\n    assert isinstance(glm._linear_loss.base_loss.link, expected_link_class)\n\n\n@pytest.mark.parametrize(\"power\", [0, 1, 1.5, 2, 3])\n@pytest.mark.parametrize(\"link\", [\"log\", \"identity\"])",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"power\", [0, 1, 1.5, 2, 3])\n@pytest.mark.parametrize(\"link\", [\"log\", \"identity\"])",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 48,
        "n_words": 34,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 72,
        "n_ast_nodes": 164,
        "n_identifiers": 17,
        "d_id": 75784,
        "documentation": {
            "docstring": "Test that link='auto' delivers the expected link function",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 242047,
        "commit_id": "56869131c8e0a0d6e1af86cc1a000c61e83efcf6",
        "repo": "scipy",
        "path": "scipy/stats/_stats_py.py",
        "file_name": "_stats_py.py",
        "fun_name": "gmean",
        "commit_message": "DOC: stats: correct doc display",
        "code": "def gmean(a, axis=0, dtype=None, weights=None):\n    r\n    if not isinstance(a, np.ndarray):\n        # if not an ndarray object attempt to convert it\n        log_a = np.log(np.array(a, dtype=dtype))\n    elif dtype:\n        # Must change the default dtype allowing array type\n        if isinstance(a, np.ma.MaskedArray):\n            log_a = np.log(np.ma.asarray(a, dtype=dtype))\n        else:\n            log_a = np.log(np.asarray(a, dtype=dtype))\n    else:\n        log_a = np.log(a)\n\n    if weights is not None:\n        weights = np.asanyarray(weights, dtype=dtype)\n\n    return np.exp(np.average(log_a, axis=axis, weights=weights))\n\n\n@_axis_nan_policy_factory(\n        lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True,\n        result_unpacker=lambda x: (x,), kwd_samples=['weights'])",
        "url": "https://github.com/scipy/scipy.git",
        "language": "Python",
        "ast_errors": "@_axis_nan_policy_factory(\n        lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True,\n        result_unpacker=lambda x: (x,), kwd_samples=['weights'])",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 177,
        "n_words": 76,
        "vocab_size": 57,
        "complexity": 5,
        "nloc": 79,
        "token_counts": 148,
        "n_ast_nodes": 286,
        "n_identifiers": 25,
        "d_id": 69761,
        "documentation": {
            "docstring": "Compute the weighted geometric mean along the specified axis.\n\n    The weighted geometric mean of the array :math:`a_i` associated to weights\n    :math:`w_i` is:\n\n    .. math::\n\n        \\exp \\left( \\frac{ \\sum_{i=1}^n w_i \\log a_i }{ \\sum_{i=1}^n w_i }\n                   \\right) \\, ,\n\n    and, with equal weights, it falls backs to:\n\n    .. math::\n\n        \\sqrt[n]{ \\prod_{i=1}^n a_i } \\, .\n\n    Parameters\n    ----------\n    a : array_like\n        Input array or object that can be converted to an array.\n    axis : int or None, optional\n        Axis along which the geometric mean is computed. Default is 0.\n        If None, compute over the whole array `a`.\n    dtype : dtype, optional\n        Type of the returned array and of the accumulator in which the\n        elements are summed. If dtype is not specified, it defaults to the\n        dtype of a, unless a has an integer dtype with a precision less than\n        that of the default platform integer. In that case, the default\n        platform integer is used.\n    weights : array_like, optional\n        The `weights` array must be broadcastable to the same shape as `a`.\n        Default is None, which gives each value a weight of 1.0.\n\n    Returns\n    -------\n    gmean : ndarray\n        See `dtype` parameter above.\n\n    See Also\n    --------\n    numpy.mean : Arithmetic average\n    numpy.average : Weighted average\n    hmean : Harmonic mean\n\n    Notes\n    -----\n    The geometric average is computed over a single dimension of the input\n    array, axis=0 by default, or all values in the array if axis=None.\n    float64 intermediate and return values are used for integer inputs.\n\n    References\n    ----------\n    .. [1] \"Weighted Geometric Mean\", *Wikipedia*,\n           https://en.wikipedia.org/wiki/Weighted_geometric_mean.\n\n    Examples\n    --------\n    >>> from scipy.stats import gmean\n    >>> gmean([1, 4])\n    2.0\n    >>> gmean([1, 2, 3, 4, 5, 6, 7])\n    3.3800151591412964\n    >>> gmean([1, 4, 7], weights=[3, 1, 3])\n    2.80668351922014\n\n    ",
            "n_words": 276,
            "vocab_size": 173,
            "n_whitespaces": 506,
            "language": "en"
        }
    },
    {
        "id": 112049,
        "commit_id": "2566badb06095b9e3ea16eb6f00fd58da65a95fd",
        "repo": "nni",
        "path": "nni/algorithms/compression/v2/pytorch/base/pruner.py",
        "file_name": "pruner.py",
        "fun_name": "_wrap_model",
        "commit_message": "[Model Compression] Pruning Wrapper Refactor (#4488)",
        "code": "def _wrap_model(self):\n        \n        if not self.is_wrapped:\n            for _, wrapper in reversed(self.get_modules_wrapper().items()):\n                _setattr(self.bound_model, wrapper.name, wrapper)\n                wrapper._weight2buffer()\n            self.is_wrapped = True\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 83,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 52,
        "n_ast_nodes": 86,
        "n_identifiers": 12,
        "d_id": 24562,
        "documentation": {
            "docstring": "\n        Wrap all modules that needed to be compressed.\n        Different from the parent function, call `wrapper._weight2buffer()` after replace the origin module to wrapper.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 286830,
        "commit_id": "faca7ab67d1ce5d0ae0e5c862332bcfc37f72ea9",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/portfolio/portfolio_optimization/parameters/params_helpers.py",
        "file_name": "params_helpers.py",
        "fun_name": "check_convert_parameter",
        "commit_message": "Portfolio optimization bug fixes (#3675)\n\n* remove hcp\n\n* add prams dict to statics\n\n* little controller bug\n\n* fix view bug\n\n* avoid crash if one stock\n\n* check params on setup\n\n* create parameter class\n\n* check and convert parameters using class\n\n* change params name to avoid confusion\n\n* create a parameter statics dict\n\n* change some funcs names\n\n* remove unused imports\n\n* remove default dict\n\n* optional type\n\n* add multi choices\n\n* cast only int and float\n\n* fix completer\n\n* fix bugs with parameter validation\n\n* fix bugs with parameter validation\n\n* add excel formatting\n\n* sdk needs mapping as well, controller takes care of this in terminal\n\n* small formating\n\n* add some safe guard try except\n\n* controller bugs\n\n* oops\n\n* change export path of parameters to portfolio folder\n\n* add more commands to scripts\n\n* catch optimization exception\n\n* log errors\n\n* black and exceptions\n\n* add flag to test\n\n* black\n\n* flake8\n\n* forgot this\n\n* pylint\n\n* change defaults\n\n* fix ef default\n\n* fix bl\n\n* sync sdk defaults\n\n* sync last defaults\n\n* fix plot heat and add more choices to controller autocomplete\n\n* patch weights\n\n* fix wrong bool parsing\n\nCo-authored-by: James Maslek <jmaslek11@gmail.com>",
        "code": "def check_convert_parameter(name, value, parameter):\n    \n\n    try:\n        # Try to cast the value to the correct type if int or float\n        if parameter.type_ is int:\n            new_value = parameter.type_(float(value))\n        elif parameter.type_ is float:\n            new_value = parameter.type_(value)\n        elif parameter.type_ is bool:\n            new_value = strtobool(value)\n        else:\n            new_value = value\n    except ValueError:\n        new_value = parameter.default\n        console.print(\n            f\"[red]'{name}' format should be '{parameter.type_.__name__}' type[/red]\",\n            f\"[red]and could not be converted. Setting default '{new_value}'.\\n[/red]\",\n        )\n\n    return new_value\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 201,
        "n_words": 67,
        "vocab_size": 48,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 84,
        "n_ast_nodes": 157,
        "n_identifiers": 15,
        "d_id": 86053,
        "documentation": {
            "docstring": "Converts a parameter to the correct type\n\n    Parameters\n    ----------\n    name: str\n        The name of the received parameter\n    value: str\n        The value of the received parameter\n    parameter: Parameter\n        The parameter object\n\n    Returns\n    -------\n    The converted parameter\n    ",
            "n_words": 35,
            "vocab_size": 23,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 72022,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_menu.py",
        "file_name": "test_menu.py",
        "fun_name": "test_remember_collapsed",
        "commit_message": "Reformat with black",
        "code": "def test_remember_collapsed(self):\n        \n        # Sidebar should not be collapsed\n        self.client.cookies[\"wagtail_sidebar_collapsed\"] = \"0\"\n        response = self.client.get(reverse(\"wagtailadmin_home\"))\n        self.assertNotContains(response, \"sidebar-collapsed\")\n\n        # Sidebar should be collapsed\n        self.client.cookies[\"wagtail_sidebar_collapsed\"] = \"1\"\n        response = self.client.get(reverse(\"wagtailadmin_home\"))\n        self.assertContains(response, \"sidebar-collapsed\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 92,
        "n_words": 29,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 68,
        "n_ast_nodes": 127,
        "n_identifiers": 9,
        "d_id": 15818,
        "documentation": {
            "docstring": "Sidebar should render with collapsed class applied.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 260317,
        "commit_id": "06834fc8e197f1f308f5ab690ec73a66b6b0b10b",
        "repo": "scikit-learn",
        "path": "sklearn/decomposition/tests/test_dict_learning.py",
        "file_name": "test_dict_learning.py",
        "fun_name": "test_minibatch_dictionary_learning_warns_and_ignore_n_iter",
        "commit_message": "DEPR deprecate n_iter in MiniBatchSparsePCA (#23726)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>\r\nCo-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>",
        "code": "def test_minibatch_dictionary_learning_warns_and_ignore_n_iter():\n    \n    warn_msg = \"'n_iter' is deprecated in version 1.1\"\n    with pytest.warns(FutureWarning, match=warn_msg):\n        model = MiniBatchDictionaryLearning(batch_size=256, n_iter=2, max_iter=2).fit(X)\n    assert model.n_iter_ == 2\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 41,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 79,
        "n_identifiers": 14,
        "d_id": 76179,
        "documentation": {
            "docstring": "Check that we always raise a warning when `n_iter` is set even if it is\n    ignored if `max_iter` is set.\n    ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 19906,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/metadata/base.py",
        "file_name": "base.py",
        "fun_name": "installed_with_setuptools_egg_info",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def installed_with_setuptools_egg_info(self) -> bool:\n        \n        info_location = self.info_location\n        if not info_location:\n            return False\n        if not info_location.endswith(\".egg-info\"):\n            return False\n        return pathlib.Path(info_location).is_dir()\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 76,
        "n_words": 19,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 41,
        "n_ast_nodes": 72,
        "n_identifiers": 8,
        "d_id": 3143,
        "documentation": {
            "docstring": "Whether this distribution is installed with the ``.egg-info`` format.\n\n        This usually indicates the distribution was installed with setuptools\n        with an old pip version or with ``single-version-externally-managed``.\n\n        Note that this ensure the metadata store is a directory. distutils can\n        also installs an ``.egg-info``, but as a file, not a directory. This\n        property is *False* for that case. Also see ``installed_by_distutils``.\n        ",
            "n_words": 59,
            "vocab_size": 43,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 179292,
        "commit_id": "cc0cff893f9d7d472788adc2510c123967b384fe",
        "repo": "gradio",
        "path": "gradio/queueing.py",
        "file_name": "queueing.py",
        "fun_name": "generate_hash",
        "commit_message": "Format The Codebase\n- black formatting\n- isort formatting",
        "code": "def generate_hash():\n    generate = True\n    conn = sqlite3.connect(DB_FILE)\n    c = conn.cursor()\n    while generate:\n        hash = uuid.uuid4().hex\n        c.execute(\n            ,\n            (hash,),\n        )\n        generate = c.fetchone() is not None\n    conn.commit()\n    return hash\n\n",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 96,
        "n_words": 29,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 63,
        "n_ast_nodes": 105,
        "n_identifiers": 15,
        "d_id": 42942,
        "documentation": {
            "docstring": "\n            SELECT hash FROM queue\n            WHERE hash = ?;\n        ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 196203,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/subsets.py",
        "file_name": "subsets.py",
        "fun_name": "unrank_gray",
        "commit_message": "Updated import locations",
        "code": "def unrank_gray(self, rank, superset):\n        \n        graycode_bitlist = GrayCode.unrank(len(superset), rank)\n        return Subset.subset_from_bitlist(superset, graycode_bitlist)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 32,
        "n_ast_nodes": 50,
        "n_identifiers": 10,
        "d_id": 47703,
        "documentation": {
            "docstring": "\n        Gets the Gray code ordered subset of the specified rank.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Subset\n        >>> Subset.unrank_gray(4, ['a', 'b', 'c']).subset\n        ['a', 'b']\n        >>> Subset.unrank_gray(0, ['a', 'b', 'c']).subset\n        []\n\n        See Also\n        ========\n\n        iterate_graycode, rank_gray\n        ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 120,
            "language": "en"
        }
    },
    {
        "id": 23193,
        "commit_id": "9f62b610dea6161627200ed85d92e19b1923279a",
        "repo": "PaddleOCR",
        "path": "ppocr/data/imaug/fce_targets.py",
        "file_name": "fce_targets.py",
        "fun_name": "resample_sidelines",
        "commit_message": "add fcenet",
        "code": "def resample_sidelines(self, sideline1, sideline2, resample_step):\n        \n\n        assert sideline1.ndim == sideline2.ndim == 2\n        assert sideline1.shape[1] == sideline2.shape[1] == 2\n        assert sideline1.shape[0] >= 2\n        assert sideline2.shape[0] >= 2\n        assert isinstance(resample_step, float)\n\n        length1 = sum([\n            norm(sideline1[i + 1] - sideline1[i])\n            for i in range(len(sideline1) - 1)\n        ])\n        length2 = sum([\n            norm(sideline2[i + 1] - sideline2[i])\n            for i in range(len(sideline2) - 1)\n        ])\n\n        total_length = (length1 + length2) / 2\n        resample_point_num = max(int(float(total_length) / resample_step), 1)\n\n        resampled_line1 = self.resample_line(sideline1, resample_point_num)\n        resampled_line2 = self.resample_line(sideline2, resample_point_num)\n\n        return resampled_line1, resampled_line2\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 231,
        "n_words": 82,
        "vocab_size": 49,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 178,
        "n_ast_nodes": 266,
        "n_identifiers": 23,
        "d_id": 4537,
        "documentation": {
            "docstring": "Resample two sidelines to be of the same points number according to\n        step size.\n\n        Args:\n            sideline1 (ndarray): The points composing a sideline of a text\n                polygon.\n            sideline2 (ndarray): The points composing another sideline of a\n                text polygon.\n            resample_step (float): The resampled step size.\n\n        Returns:\n            resampled_line1 (ndarray): The resampled line 1.\n            resampled_line2 (ndarray): The resampled line 2.\n        ",
            "n_words": 56,
            "vocab_size": 33,
            "n_whitespaces": 169,
            "language": "en"
        }
    },
    {
        "id": 39793,
        "commit_id": "b3bb96da2002383625b7ff595d9862a4f0085c17",
        "repo": "dash",
        "path": "dash/_utils.py",
        "file_name": "_utils.py",
        "fun_name": "set_read_only",
        "commit_message": "Make AttributeDict additive\n\n._read_only attribute is now a dict of name -> msgs\n\nOverrides .update() method to use __setitem__ implementation\n\nIncludes updates to unit tests",
        "code": "def set_read_only(self, names, msg=\"Attribute is read-only\"):\n        \n        new_read_only = {name: msg for name in names}\n        if getattr(self, \"_read_only\", False):\n            self._read_only.update(new_read_only)\n        else:\n            object.__setattr__(self, \"_read_only\", new_read_only)\n",
        "url": "https://github.com/plotly/dash.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 11,
        "d_id": 7256,
        "documentation": {
            "docstring": "\n        Designate named attributes as read-only with the corresponding msg\n\n        Method is additive. Making additional calls to this method will update\n        existing messages and add to the current set of _read_only names.\n        ",
            "n_words": 31,
            "vocab_size": 29,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 183062,
        "commit_id": "91783b7c1e06a45e93fd89dbdb6aa3d1a9c2e990",
        "repo": "textual",
        "path": "tests/css/test_help_text.py",
        "file_name": "test_help_text.py",
        "fun_name": "test_help_text_examples_are_contextualized",
        "commit_message": "Testing for help text",
        "code": "def test_help_text_examples_are_contextualized():\n    \n    rendered_inline = render(spacing_invalid_value(\"padding\", \"inline\"))\n    assert \"widget.styles.padding\" in rendered_inline\n\n    rendered_css = render(spacing_invalid_value(\"padding\", \"css\"))\n    assert \"padding:\" in rendered_css\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 33,
        "n_words": 18,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 35,
        "n_ast_nodes": 70,
        "n_identifiers": 5,
        "d_id": 44041,
        "documentation": {
            "docstring": "Ensure that if the user is using CSS, they see CSS-specific examples\n    and if they're using inline styles they see inline-specific examples.",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 80230,
        "commit_id": "10dbbddaf35607e4257f50dd960520a1268dd225",
        "repo": "wagtail",
        "path": "wagtail/snippets/tests/test_locking.py",
        "file_name": "test_locking.py",
        "fun_name": "test_unlock_post_own_snippet_with_bad_permissions",
        "commit_message": "Add tests for locking snippets",
        "code": "def test_unlock_post_own_snippet_with_bad_permissions(self):\n        \n\n        # Remove privileges from user\n        self.user.is_superuser = False\n        self.user.groups.add(Group.objects.get(name=\"Editors\"))\n        self.user.save()\n\n        # Lock the snippet\n        self.lock_snippet(self.user)\n\n        next_url = reverse(\"wagtailadmin_home\")\n        response = self.client.post(self.get_url(\"unlock\"), {\"next\": next_url})\n        self.refresh_snippet()\n\n        # Check response\n        self.assertRedirects(response, next_url)\n\n        # Check that the snippet is not locked\n        self.assertFalse(self.snippet.locked)\n        self.assertIsNone(self.snippet.locked_by)\n        self.assertIsNone(self.snippet.locked_at)\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 154,
        "n_words": 42,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 117,
        "n_ast_nodes": 202,
        "n_identifiers": 26,
        "d_id": 17036,
        "documentation": {
            "docstring": "User can unlock a snippet they have locked without the unlock permission.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 219818,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "to_integral_value",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def to_integral_value(self, rounding=None, context=None):\n        \n        if context is None:\n            context = getcontext()\n        if rounding is None:\n            rounding = context.rounding\n        if self._is_special:\n            ans = self._check_nans(context=context)\n            if ans:\n                return ans\n            return Decimal(self)\n        if self._exp >= 0:\n            return Decimal(self)\n        else:\n            return self._rescale(0, rounding)\n\n    # the method name changed, but we provide also the old one, for compatibility\n    to_integral = to_integral_value\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 196,
        "n_words": 56,
        "vocab_size": 39,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 82,
        "n_ast_nodes": 138,
        "n_identifiers": 12,
        "d_id": 55831,
        "documentation": {
            "docstring": "Rounds to the nearest integer, without raising inexact, rounded.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 132072,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/automlboard/backend/collector.py",
        "file_name": "collector.py",
        "fun_name": "_update_trial_info",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _update_trial_info(self, expr_dir):\n        \n        trial_id = expr_dir[-8:]\n\n        meta_file = os.path.join(expr_dir, EXPR_META_FILE)\n        meta = parse_json(meta_file)\n\n        result_file = os.path.join(expr_dir, EXPR_RESULT_FILE)\n        offset = self._result_offsets.get(trial_id, 0)\n        results, new_offset = parse_multiple_json(result_file, offset)\n        self._add_results(results, trial_id)\n        self._result_offsets[trial_id] = new_offset\n\n        if meta:\n            TrialRecord.objects.filter(trial_id=trial_id).update(\n                trial_status=meta[\"status\"],\n                end_time=timestamp2date(meta.get(\"end_time\", None)),\n            )\n        elif len(results) > 0:\n            metrics = {\n                \"episode_reward\": results[-1].get(\"episode_reward_mean\", None),\n                \"accuracy\": results[-1].get(\"mean_accuracy\", None),\n                \"loss\": results[-1].get(\"loss\", None),\n            }\n            if results[-1].get(\"done\"):\n                TrialRecord.objects.filter(trial_id=trial_id).update(\n                    trial_status=\"TERMINATED\",\n                    end_time=results[-1].get(\"date\", None),\n                    metrics=str(metrics),\n                )\n            else:\n                TrialRecord.objects.filter(trial_id=trial_id).update(\n                    metrics=str(metrics)\n                )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 421,
        "n_words": 67,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 30,
        "token_counts": 253,
        "n_ast_nodes": 407,
        "n_identifiers": 30,
        "d_id": 29665,
        "documentation": {
            "docstring": "Update information for given trial.\n\n        Meta file will be loaded if exists, and the trial information\n        in db backend will be updated.\n\n        Args:\n            expr_dir(str)\n        ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 246133,
        "commit_id": "bf60da1a60096fac5fb778b732ff2214862ac808",
        "repo": "synapse",
        "path": "tests/rest/client/test_profile.py",
        "file_name": "test_profile.py",
        "fun_name": "test_avatar_allowed_mime_type_per_room",
        "commit_message": "Configurable limits on avatars (#11846)\n\nOnly allow files which file size and content types match configured\r\nlimits to be set as avatar.\r\n\r\nMost of the inspiration from the non-test code comes from matrix-org/synapse-dinsic#19",
        "code": "def test_avatar_allowed_mime_type_per_room(self):\n        \n        self._setup_local_files(\n            {\n                \"good\": {\"mimetype\": \"image/png\"},\n                \"bad\": {\"mimetype\": \"application/octet-stream\"},\n            }\n        )\n\n        room_id = self.helper.create_room_as(tok=self.owner_tok)\n\n        channel = self.make_request(\n            \"PUT\",\n            f\"/rooms/{room_id}/state/m.room.member/{self.owner}\",\n            content={\"membership\": \"join\", \"avatar_url\": \"mxc://test/bad\"},\n            access_token=self.owner_tok,\n        )\n        self.assertEqual(channel.code, 403, channel.result)\n        self.assertEqual(\n            channel.json_body[\"errcode\"], Codes.FORBIDDEN, channel.json_body\n        )\n\n        channel = self.make_request(\n            \"PUT\",\n            f\"/rooms/{room_id}/state/m.room.member/{self.owner}\",\n            content={\"membership\": \"join\", \"avatar_url\": \"mxc://test/good\"},\n            access_token=self.owner_tok,\n        )\n        self.assertEqual(channel.code, 200, channel.result)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 283,
        "n_words": 48,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 150,
        "n_ast_nodes": 276,
        "n_identifiers": 19,
        "d_id": 71034,
        "documentation": {
            "docstring": "Tests that the MIME type whitelist for avatars is enforced when updating a\n        per-room profile.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 246320,
        "commit_id": "c3db7a0b59d48b8872bc24096f9a2467ef35f703",
        "repo": "synapse",
        "path": "tests/federation/transport/test_server.py",
        "file_name": "test_server.py",
        "fun_name": "test_blocked_public_room_list_over_federation",
        "commit_message": "Tests: replace mocked Authenticator with the real thing (#11913)\n\nIf we prepopulate the test homeserver with a key for a remote homeserver, we\r\ncan make federation requests to it without having to stub out the\r\nauthenticator. This has two advantages:\r\n\r\n * means that what we are testing is closer to reality (ie, we now have\r\n   complete tests for the incoming-request-authorisation flow)\r\n\r\n * some tests require that other objects be signed by the remote server (eg,\r\n   the event in `/send_join`), and doing that would require a whole separate\r\n   set of mocking out. It's much simpler just to use real keys.",
        "code": "def test_blocked_public_room_list_over_federation(self):\n        \n        channel = self.make_signed_federation_request(\n            \"GET\",\n            \"/_matrix/federation/v1/publicRooms\",\n        )\n        self.assertEquals(403, channel.code)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 60,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 27,
        "n_ast_nodes": 48,
        "n_identifiers": 6,
        "d_id": 71153,
        "documentation": {
            "docstring": "Test that unauthenticated requests to the public rooms directory 403 when\n        allow_public_rooms_over_federation is False.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 250085,
        "commit_id": "3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b",
        "repo": "synapse",
        "path": "tests/storage/databases/main/test_room.py",
        "file_name": "test_room.py",
        "fun_name": "test_background_populate_rooms_creator_column",
        "commit_message": "Require types in tests.storage. (#14646)\n\nAdds missing type hints to `tests.storage` package\r\nand does not allow untyped definitions.",
        "code": "def test_background_populate_rooms_creator_column(self) -> None:\n        \n\n        # Insert a room without the creator\n        room_id = self._generate_room()\n        self.get_success(\n            self.store.db_pool.simple_update(\n                table=\"rooms\",\n                keyvalues={\"room_id\": room_id},\n                updatevalues={\"creator\": None},\n                desc=\"test\",\n            )\n        )\n\n        # Make sure the test is starting out with a room without a creator\n        room_creator_before = self.get_success(\n            self.store.db_pool.simple_select_one_onecol(\n                table=\"rooms\",\n                keyvalues={\"room_id\": room_id},\n                retcol=\"creator\",\n                allow_none=True,\n            )\n        )\n        self.assertEqual(room_creator_before, None)\n\n        # Insert and run the background update.\n        self.get_success(\n            self.store.db_pool.simple_insert(\n                \"background_updates\",\n                {\n                    \"update_name\": _BackgroundUpdates.POPULATE_ROOMS_CREATOR_COLUMN,\n                    \"progress_json\": \"{}\",\n                },\n            )\n        )\n\n        # ... and tell the DataStore that it hasn't finished all updates yet\n        self.store.db_pool.updates._all_done = False\n\n        # Now let's actually drive the updates to completion\n        self.wait_for_background_updates()\n\n        # Make sure the background update filled in the room creator\n        room_creator_after = self.get_success(\n            self.store.db_pool.simple_select_one_onecol(\n                table=\"rooms\",\n                keyvalues={\"room_id\": room_id},\n                retcol=\"creator\",\n                allow_none=True,\n            )\n        )\n        self.assertEqual(room_creator_after, self.user_id)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 610,
        "n_words": 119,
        "vocab_size": 73,
        "complexity": 1,
        "nloc": 42,
        "token_counts": 188,
        "n_ast_nodes": 316,
        "n_identifiers": 25,
        "d_id": 73263,
        "documentation": {
            "docstring": "Test that the background update to populate the rooms creator column\n        works properly.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 5031,
        "commit_id": "73c7fad7fce952a8c3ba827ca858e4280bd846f3",
        "repo": "airbyte",
        "path": "airbyte-cdk/python/airbyte_cdk/utils/traced_exception.py",
        "file_name": "traced_exception.py",
        "fun_name": "as_airbyte_message",
        "commit_message": "CDK: emit `AirbyteTraceMessage` with exception trace information (#12593)",
        "code": "def as_airbyte_message(self) -> AirbyteMessage:\n        \n        now_millis = datetime.now().timestamp() * 1000.0\n\n        trace_exc = self._exception or self\n        stack_trace_str = \"\".join(traceback.TracebackException.from_exception(trace_exc).format())\n\n        trace_message = AirbyteTraceMessage(\n            type=TraceType.ERROR,\n            emitted_at=now_millis,\n            error=AirbyteErrorTraceMessage(\n                message=self.message or \"Something went wrong in the connector. See the logs for more details.\",\n                internal_message=self.internal_message,\n                failure_type=self.failure_type,\n                stack_trace=stack_trace_str,\n            ),\n        )\n\n        return AirbyteMessage(type=MessageType.TRACE, trace=trace_message)\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 198,
        "n_words": 45,
        "vocab_size": 40,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 107,
        "n_ast_nodes": 166,
        "n_identifiers": 30,
        "d_id": 710,
        "documentation": {
            "docstring": "\n        Builds an AirbyteTraceMessage from the exception\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 114440,
        "commit_id": "4b49bf89ad95fcc645a249983efd764c1a73e3bb",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/lightwood_handler/lightwood_handler/lightwood_handler.py",
        "file_name": "lightwood_handler.py",
        "fun_name": "_get_model_info",
        "commit_message": "copy from /lightwood_handler branch: added generic serializer for dill support, lw integration functional",
        "code": "def _get_model_info(self, model_name):\n          # noqa\n        return self.storage.get('models')[model_name]\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 22,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 25193,
        "documentation": {
            "docstring": " Returns a dictionary with three keys: 'jsonai', 'predictor' (serialized), and 'code'. ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 114587,
        "commit_id": "7e3da9157508a5eb38dbfabbd7f08ba8fa6c5a88",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/postgres_handler/postgres_handler.py",
        "file_name": "postgres_handler.py",
        "fun_name": "get_views",
        "commit_message": "Get tables, views, describe",
        "code": "def get_views(self):\n        \n        query = f\"SELECT * FROM information_schema.views WHERE table_schema NOT IN ('information_schema', 'pg_catalog')\"\n        result = self.run_native_query(query)\n        return result\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 47,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 20,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 25222,
        "documentation": {
            "docstring": "\n        List all views in PostgreSQL without the system views information_schema and pg_catalog\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 197274,
        "commit_id": "f3b08522003f40868afb20304fc0fa5b16d13f6a",
        "repo": "sympy",
        "path": "sympy/core/numbers.py",
        "file_name": "numbers.py",
        "fun_name": "mod_inverse",
        "commit_message": "Cleanup documentation",
        "code": "def mod_inverse(a, m):\n    r\n    c = None\n    try:\n        a, m = as_int(a), as_int(m)\n        if m != 1 and m != -1:\n            x, _, g = igcdex(a, m)\n            if g == 1:\n                c = x % m\n    except ValueError:\n        a, m = sympify(a), sympify(m)\n        if not (a.is_number and m.is_number):\n            raise TypeError(filldedent())\n        big = (m > 1)\n        if big not in (S.true, S.false):\n            raise ValueError('m > 1 did not evaluate; try to simplify %s' % m)\n        elif big:\n            c = 1/a\n    if c is None:\n        raise ValueError('inverse of %s (mod %s) does not exist' % (a, m))\n    return c\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 240,
        "n_words": 97,
        "vocab_size": 64,
        "complexity": 10,
        "nloc": 63,
        "token_counts": 149,
        "n_ast_nodes": 240,
        "n_identifiers": 18,
        "d_id": 48421,
        "documentation": {
            "docstring": "\n    Return the number $c$ such that, $a \\times c = 1 \\pmod{m}$\n    where $c$ has the same sign as $m$. If no such value exists,\n    a ValueError is raised.\n\n    Examples\n    ========\n\n    >>> from sympy import mod_inverse, S\n\n    Suppose we wish to find multiplicative inverse $x$ of\n    3 modulo 11. This is the same as finding $x$ such\n    that $3x = 1 \\pmod{11}$. One value of x that satisfies\n    this congruence is 4. Because $3 \\times 4 = 12$ and $12 = 1 \\pmod{11}$.\n    This is the value returned by ``mod_inverse``:\n\n    >>> mod_inverse(3, 11)\n    4\n    >>> mod_inverse(-3, 11)\n    7\n\n    When there is a common factor between the numerators of\n    `a` and `m` the inverse does not exist:\n\n    >>> mod_inverse(2, 4)\n    Traceback (most recent call last):\n    ...\n    ValueError: inverse of 2 mod 4 does not exist\n\n    >>> mod_inverse(S(2)/7, S(5)/2)\n    7/2\n\n    References\n    ==========\n\n    .. [1] https://en.wikipedia.org/wiki/Modular_multiplicative_inverse\n    .. [2] https://en.wikipedia.org/wiki/Extended_Euclidean_algorithm\n    \n                Expected numbers for arguments; symbolic `mod_inverse`\n                is not implemented\n                but symbolic expressions can be handled with the\n                similar function,\n                sympy.polys.polytools.invert",
            "n_words": 166,
            "vocab_size": 119,
            "n_whitespaces": 326,
            "language": "en"
        }
    },
    {
        "id": 271566,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training.py",
        "file_name": "training.py",
        "fun_name": "potentially_ragged_concat",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def potentially_ragged_concat(tensors):\n    \n    if len(tensors) == 1:\n        return tensors[0]\n    if isinstance(tensors[0], tf.SparseTensor):\n        return tf.sparse.concat(axis=0, sp_inputs=tensors)\n    elif isinstance(tensors[0], tf.RaggedTensor):\n        return tf.concat(tensors, axis=0)\n    elif not tf.__internal__.tf2.enabled():\n        return tf.concat(tensors, axis=0)\n\n    non_batch_shapes = tf.stack([tf.shape(tensor)[1:] for tensor in tensors])\n    constant_dims = tf.math.reduce_all(\n        non_batch_shapes == non_batch_shapes[:1], axis=0\n    )\n    if tf.math.reduce_all(constant_dims).numpy().item():\n        # All non-batch dims are constant\n        return tf.concat(tensors, axis=0)\n\n    # First, identify constant inner dimensions by finding the\n    # rightmost dimension that is not constant\n    constant_inner_dimensions = (\n        constant_dims.numpy().tolist()[::-1].index(False)\n    )\n    # If there are constant inner dimensions, define a constant inner shape\n    if constant_inner_dimensions == 0:\n        constant_inner_shape = None\n    else:\n        constant_inner_shape = tensors[0].shape[-constant_inner_dimensions:]\n    return tf.ragged.constant(\n        [tensor.numpy() for tensor in tensors], inner_shape=constant_inner_shape\n    ).merge_dims(0, 1)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 237,
        "n_words": 106,
        "vocab_size": 68,
        "complexity": 9,
        "nloc": 25,
        "token_counts": 242,
        "n_ast_nodes": 380,
        "n_identifiers": 31,
        "d_id": 80801,
        "documentation": {
            "docstring": "Concats `Tensor`s along their first dimension.\n\n    Args:\n      tensors: List of `Tensor`s.\n\n    Returns:\n      Concatenation of the inputs along the first dimension -- of type `Tensor`\n      if all input shapes are compatible, or `RaggedTensor` if not.\n    ",
            "n_words": 34,
            "vocab_size": 28,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 176856,
        "commit_id": "304682fd71ba3bae9c456b004bbabafb96022add",
        "repo": "networkx",
        "path": "networkx/algorithms/dag.py",
        "file_name": "dag.py",
        "fun_name": "dag_longest_path",
        "commit_message": "Add example of topo_order kwarg to dag_longest_path (#5728)",
        "code": "def dag_longest_path(G, weight=\"weight\", default_weight=1, topo_order=None):\n    \n    if not G:\n        return []\n\n    if topo_order is None:\n        topo_order = nx.topological_sort(G)\n\n    dist = {}  # stores {v : (length, u)}\n    for v in topo_order:\n        us = [\n            (dist[u][0] + data.get(weight, default_weight), u)\n            for u, data in G.pred[v].items()\n        ]\n\n        # Use the best predecessor if there is one and its distance is\n        # non-negative, otherwise terminate.\n        maxu = max(us, key=lambda x: x[0]) if us else (0, v)\n        dist[v] = maxu if maxu[0] >= 0 else (0, v)\n\n    u = None\n    v = max(dist, key=lambda x: dist[x][0])\n    path = []\n    while u != v:\n        path.append(v)\n        u = v\n        v = dist[v][1]\n\n    path.reverse()\n    return path\n\n\n@not_implemented_for(\"undirected\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"undirected\")",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 241,
        "n_words": 109,
        "vocab_size": 74,
        "complexity": 8,
        "nloc": 22,
        "token_counts": 185,
        "n_ast_nodes": 295,
        "n_identifiers": 23,
        "d_id": 42147,
        "documentation": {
            "docstring": "Returns the longest path in a directed acyclic graph (DAG).\n\n    If `G` has edges with `weight` attribute the edge data are used as\n    weight values.\n\n    Parameters\n    ----------\n    G : NetworkX DiGraph\n        A directed acyclic graph (DAG)\n\n    weight : str, optional\n        Edge data key to use for weight\n\n    default_weight : int, optional\n        The weight of edges that do not have a weight attribute\n\n    topo_order: list or tuple, optional\n        A topological order for `G` (if None, the function will compute one)\n\n    Returns\n    -------\n    list\n        Longest path\n\n    Raises\n    ------\n    NetworkXNotImplemented\n        If `G` is not directed\n\n    Examples\n    --------\n    >>> DG = nx.DiGraph([(0, 1, {'cost':1}), (1, 2, {'cost':1}), (0, 2, {'cost':42})])\n    >>> list(nx.all_simple_paths(DG, 0, 2))\n    [[0, 1, 2], [0, 2]]\n    >>> nx.dag_longest_path(DG)\n    [0, 1, 2]\n    >>> nx.dag_longest_path(DG, weight=\"cost\")\n    [0, 2]\n\n    In the case where multiple valid topological orderings exist, `topo_order`\n    can be used to specify a specific ordering:\n\n    >>> DG = nx.DiGraph([(0, 1), (0, 2)])\n    >>> sorted(nx.all_topological_sorts(DG))  # Valid topological orderings\n    [[0, 1, 2], [0, 2, 1]]\n    >>> nx.dag_longest_path(DG, topo_order=[0, 1, 2])\n    [0, 1]\n    >>> nx.dag_longest_path(DG, topo_order=[0, 2, 1])\n    [0, 2]\n\n    See also\n    --------\n    dag_longest_path_length\n\n    ",
            "n_words": 180,
            "vocab_size": 114,
            "n_whitespaces": 331,
            "language": "en"
        }
    },
    {
        "id": 4928,
        "commit_id": "1642630461c25e447ede67bb42ba6ea6ec700e52",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-intercom/unit_tests/unit_test.py",
        "file_name": "unit_test.py",
        "fun_name": "test_conversation_part_filtering_based_on_conversation",
        "commit_message": "🐛 Source Intercom: Fixed filtering of conversation_parts (#12374)",
        "code": "def test_conversation_part_filtering_based_on_conversation(requests_mock, conversation_parts_responses):\n    \n    updated_at = 1650988200\n    state = {\"updated_at\": updated_at}\n    expected_record_ids = set()\n    for response_tuple in conversation_parts_responses:\n        requests_mock.register_uri('GET', response_tuple[0], json=response_tuple[1])\n        if \"conversation_parts\" in response_tuple[1]:\n            expected_record_ids.update([cp[\"id\"] for cp in response_tuple[1][\"conversation_parts\"][\"conversation_parts\"]])\n\n    records = []\n    conversation_parts = ConversationParts(authenticator=NoAuth())\n    for slice in conversation_parts.stream_slices(sync_mode=SyncMode.incremental, stream_state=state):\n        records.extend(list(conversation_parts.read_records(sync_mode=SyncMode.incremental, stream_slice=slice, stream_state=state)))\n\n    assert expected_record_ids == {r[\"id\"] for r in records}\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 110,
        "n_words": 51,
        "vocab_size": 39,
        "complexity": 6,
        "nloc": 13,
        "token_counts": 149,
        "n_ast_nodes": 239,
        "n_identifiers": 28,
        "d_id": 690,
        "documentation": {
            "docstring": "\n    Test shows that conversation_parts filters conversations (from parent stream) correctly\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 20452,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/lexers/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_lexer_for_mimetype",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def get_lexer_for_mimetype(_mime, **options):\n    \n    for modname, name, _, _, mimetypes in LEXERS.values():\n        if _mime in mimetypes:\n            if name not in _lexer_cache:\n                _load_lexers(modname)\n            return _lexer_cache[name](**options)\n    for cls in find_plugin_lexers():\n        if _mime in cls.mimetypes:\n            return cls(**options)\n    raise ClassNotFound('no lexer for mimetype %r found' % _mime)\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 116,
        "n_words": 42,
        "vocab_size": 31,
        "complexity": 6,
        "nloc": 10,
        "token_counts": 77,
        "n_ast_nodes": 123,
        "n_identifiers": 14,
        "d_id": 3380,
        "documentation": {
            "docstring": "Get a lexer for a mimetype.\n\n    Raises ClassNotFound if not found.\n    ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 189496,
        "commit_id": "902e7eb4f0147b5882a613b67467e38a1d47f01e",
        "repo": "manim",
        "path": "manim/mobject/svg/text_mobject.py",
        "file_name": "text_mobject.py",
        "fun_name": "_extract_gradient_tags",
        "commit_message": "Hide more private methods from the docs. (#2468)\n\n* hide privs from text_mobject.py\r\n\r\n* hide privs from tex_mobject.py\r\n\r\n* hide privs from code_mobject.py\r\n\r\n* hide privs from svg_mobject.py\r\n\r\n* remove SVGPath and utils from __init__.py\r\n\r\n* don't import string_to_numbers\r\n\r\n* hide privs from geometry.py\r\n\r\n* hide privs from matrix.py\r\n\r\n* hide privs from numbers.py\r\n\r\n* hide privs from three_dimensions.py\r\n\r\n* forgot underscore under set_stroke_width_from_length\r\n\r\n* there were more i missed\r\n\r\n* unhidea method that was used in docs\r\n\r\n* forgot other text2hash\r\n\r\n* remove svg_path from docs",
        "code": "def _extract_gradient_tags(self):\n        \n        tags = re.finditer(\n            r'<gradient\\s+from=\"([^\"]+)\"\\s+to=\"([^\"]+)\"(\\s+offset=\"([^\"]+)\")?>(.+?)</gradient>',\n            self.original_text,\n            re.S,\n        )\n        gradientmap = []\n        for tag in tags:\n            start = self._count_real_chars(self.original_text[: tag.start(0)])\n            end = start + self._count_real_chars(tag.group(5))\n            offsets = tag.group(4).split(\",\") if tag.group(4) else [0]\n            start_offset = int(offsets[0]) if offsets[0] else 0\n            end_offset = int(offsets[1]) if len(offsets) == 2 and offsets[1] else 0\n\n            gradientmap.append(\n                {\n                    \"start\": start,\n                    \"end\": end,\n                    \"from\": tag.group(1),\n                    \"to\": tag.group(2),\n                    \"start_offset\": start_offset,\n                    \"end_offset\": end_offset,\n                },\n            )\n        self.text = re.sub(\"<gradient[^>]+>(.+?)</gradient>\", r\"\\1\", self.text, 0, re.S)\n        return gradientmap\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 378,
        "n_words": 75,
        "vocab_size": 60,
        "complexity": 6,
        "nloc": 25,
        "token_counts": 197,
        "n_ast_nodes": 311,
        "n_identifiers": 22,
        "d_id": 46096,
        "documentation": {
            "docstring": "Used to determine which parts (if any) of the string should be formatted\n        with a gradient.\n\n        Removes the ``<gradient>`` tag, as it is not part of Pango's markup and would cause an error.\n        ",
            "n_words": 33,
            "vocab_size": 31,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 259125,
        "commit_id": "67a3feed2fe4e82c1cc129c34b9e223b94a8d531",
        "repo": "scikit-learn",
        "path": "sklearn/kernel_approximation.py",
        "file_name": "kernel_approximation.py",
        "fun_name": "get_feature_names_out",
        "commit_message": "ENH Adds get_feature_names_out for AdditiveChi2Sampler (#22137)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@gmail.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def get_feature_names_out(self, input_features=None):\n        \n        input_features = _check_feature_names_in(\n            self, input_features, generate_names=True\n        )\n        est_name = self.__class__.__name__.lower()\n\n        names_list = [f\"{est_name}_{name}_sqrt\" for name in input_features]\n\n        for j in range(1, self.sample_steps):\n            cos_names = [f\"{est_name}_{name}_cos{j}\" for name in input_features]\n            sin_names = [f\"{est_name}_{name}_sin{j}\" for name in input_features]\n            names_list.extend(cos_names + sin_names)\n\n        return np.asarray(names_list, dtype=object)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 138,
        "n_words": 45,
        "vocab_size": 31,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 94,
        "n_ast_nodes": 176,
        "n_identifiers": 21,
        "d_id": 75584,
        "documentation": {
            "docstring": "Get output feature names for transformation.\n\n        Parameters\n        ----------\n        input_features : array-like of str or None, default=None\n            Only used to validate feature names with the names seen in :meth:`fit`.\n\n        Returns\n        -------\n        feature_names_out : ndarray of str objects\n            Transformed feature names.\n        ",
            "n_words": 39,
            "vocab_size": 32,
            "n_whitespaces": 110,
            "language": "en"
        }
    },
    {
        "id": 197433,
        "commit_id": "9a3ffc6781bd44c47cf49e128ef154389c32876a",
        "repo": "sympy",
        "path": "sympy/physics/vector/fieldfunctions.py",
        "file_name": "fieldfunctions.py",
        "fun_name": "scalar_potential_difference",
        "commit_message": "Some pep8 cleanup of sympy.physics.vector.",
        "code": "def scalar_potential_difference(field, frame, point1, point2, origin):\n    \n\n    _check_frame(frame)\n    if isinstance(field, Vector):\n        # Get the scalar potential function\n        scalar_fn = scalar_potential(field, frame)\n    else:\n        # Field is a scalar\n        scalar_fn = field\n    # Express positions in required frame\n    position1 = express(point1.pos_from(origin), frame, variables=True)\n    position2 = express(point2.pos_from(origin), frame, variables=True)\n    # Get the two positions as substitution dicts for coordinate variables\n    subs_dict1 = {}\n    subs_dict2 = {}\n    for i, x in enumerate(frame):\n        subs_dict1[frame[i]] = x.dot(position1)\n        subs_dict2[frame[i]] = x.dot(position2)\n    return scalar_fn.subs(subs_dict2) - scalar_fn.subs(subs_dict1)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 155,
        "n_words": 77,
        "vocab_size": 56,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 133,
        "n_ast_nodes": 208,
        "n_identifiers": 23,
        "d_id": 48541,
        "documentation": {
            "docstring": "\n    Returns the scalar potential difference between two points in a\n    certain frame, wrt a given field.\n\n    If a scalar field is provided, its values at the two points are\n    considered. If a conservative vector field is provided, the values\n    of its scalar potential function at the two points are used.\n\n    Returns (potential at position 2) - (potential at position 1)\n\n    Parameters\n    ==========\n\n    field : Vector/sympyfiable\n        The field to calculate wrt\n\n    frame : ReferenceFrame\n        The frame to do the calculations in\n\n    point1 : Point\n        The initial Point in given frame\n\n    position2 : Point\n        The second Point in the given frame\n\n    origin : Point\n        The Point to use as reference point for position vector\n        calculation\n\n    Examples\n    ========\n\n    >>> from sympy.physics.vector import ReferenceFrame, Point\n    >>> from sympy.physics.vector import scalar_potential_difference\n    >>> R = ReferenceFrame('R')\n    >>> O = Point('O')\n    >>> P = O.locatenew('P', R[0]*R.x + R[1]*R.y + R[2]*R.z)\n    >>> vectfield = 4*R[0]*R[1]*R.x + 2*R[0]**2*R.y\n    >>> scalar_potential_difference(vectfield, R, O, P, O)\n    2*R_x**2*R_y\n    >>> Q = O.locatenew('O', 3*R.x + R.y + 2*R.z)\n    >>> scalar_potential_difference(vectfield, R, P, Q, O)\n    -2*R_x**2*R_y + 18\n\n    ",
            "n_words": 174,
            "vocab_size": 93,
            "n_whitespaces": 298,
            "language": "en"
        }
    },
    {
        "id": 196219,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/subsets.py",
        "file_name": "subsets.py",
        "fun_name": "prev_lexicographic",
        "commit_message": "Updated import locations",
        "code": "def prev_lexicographic(self):\n        \n        i = self.superset_size - 1\n        indices = Subset.subset_indices(self.subset, self.superset)\n\n        while i >= 0 and i not in indices:\n            i = i - 1\n\n        if i == 0 or i - 1 in indices:\n            indices.remove(i)\n        else:\n            if i >= 0:\n                indices.remove(i)\n                indices.append(i - 1)\n            indices.append(self.superset_size - 1)\n\n        ret_set = []\n        super_set = self.superset\n        for i in indices:\n            ret_set.append(super_set[i])\n        return Subset(ret_set, super_set)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 217,
        "n_words": 62,
        "vocab_size": 35,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 120,
        "n_ast_nodes": 192,
        "n_identifiers": 13,
        "d_id": 47719,
        "documentation": {
            "docstring": "\n        Generates the previous lexicographically ordered subset.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Subset\n        >>> a = Subset([], ['a', 'b', 'c', 'd'])\n        >>> a.prev_lexicographic().subset\n        ['d']\n        >>> a = Subset(['c','d'], ['a', 'b', 'c', 'd'])\n        >>> a.prev_lexicographic().subset\n        ['c']\n\n        See Also\n        ========\n\n        next_lexicographic\n        ",
            "n_words": 39,
            "vocab_size": 27,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 204596,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/management/base.py",
        "file_name": "base.py",
        "fun_name": "add_base_argument",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def add_base_argument(self, parser, *args, **kwargs):\n        \n        for arg in args:\n            if arg in self.suppressed_base_arguments:\n                kwargs[\"help\"] = argparse.SUPPRESS\n                break\n        parser.add_argument(*args, **kwargs)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 81,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 73,
        "n_identifiers": 10,
        "d_id": 50806,
        "documentation": {
            "docstring": "\n        Call the parser's add_argument() method, suppressing the help text\n        according to BaseCommand.suppressed_base_arguments.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 66259,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/hr/report/monthly_attendance_sheet/monthly_attendance_sheet.py",
        "file_name": "monthly_attendance_sheet.py",
        "fun_name": "get_holiday",
        "commit_message": "style: format code with black",
        "code": "def get_holiday(holiday_list, month):\n\tholiday_map = frappe._dict()\n\tfor d in holiday_list:\n\t\tif d:\n\t\t\tholiday_map.setdefault(\n\t\t\t\td,\n\t\t\t\tfrappe.db.sql(\n\t\t\t\t\t,\n\t\t\t\t\t(d, month),\n\t\t\t\t),\n\t\t\t)\n\n\treturn holiday_map\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 10,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 47,
        "n_ast_nodes": 83,
        "n_identifiers": 11,
        "d_id": 14150,
        "documentation": {
            "docstring": "select day(holiday_date), weekly_off from `tabHoliday`\n\t\t\t\twhere parent=%s and month(holiday_date)=%s",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 284498,
        "commit_id": "54a1b6f545a0016c576e9e00eef5c003d229dacf",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/stocks/options/hedge/hedge_model.py",
        "file_name": "hedge_model.py",
        "fun_name": "add_hedge_option",
        "commit_message": "Feature/hedge (#1768)\n\n* [Bug] Incorrect log for reddit keys. #1733 fix\r\n\r\n* Create new feature-hedge\r\n\r\n* Significantly improve code of hedge menu\r\n\r\n* More robust\r\n\r\n* Robustness\r\n\r\n* Fix tests\r\n\r\n* Fix can't multiply sequence by non-int of type 'numpy.float64' error\r\n\r\n* Temporary fix of singular matrix error. Return first feasible solution\r\n\r\n* Update Hugo Documentation\r\n\r\n* Combining menus and cleaning up code\r\n\r\n* Tidy up call_exp\r\n\r\n* Update tests Round 1\r\n\r\n* Update tests Round 2\r\n\r\n* Fix linting error\r\n\r\n* Fix linting?\r\n\r\n* Fixed glitch\r\n\r\nCo-authored-by: JerBouma <jer.bouma@gmail.com>\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: colin99d <colin99delahunty@gmail.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>",
        "code": "def add_hedge_option(price, implied_volatility, strike, days, side):\n    \n    # Determine delta position given the option\n    delta = calc_delta(price, implied_volatility, strike, days, 0, side)\n\n    # Determine gamma position given the option\n    gamma = calc_gamma(price, implied_volatility, strike, days, 0)\n\n    # Determine vega position given the option\n    vega = calc_vega(price, implied_volatility, strike, days, 0)\n\n    return delta, gamma, vega\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 77,
        "n_words": 53,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 64,
        "n_ast_nodes": 88,
        "n_identifiers": 12,
        "d_id": 84764,
        "documentation": {
            "docstring": "Determine the delta, gamma and vega value of the portfolio and/or options.\n\n    Parameters\n    ----------\n    price: int\n        The price.\n    implied_volatility: float\n        The implied volatility.\n    strike: float\n        The strike price.\n    days: float\n        The amount of days until expiration. Use annual notation thus a month would be 30 / 360.\n    sign: int\n        Whether you have a long (1) or short (-1) position\n\n    Returns\n    -------\n    delta: float\n    gamma: float\n    portfolio: float\n    ",
            "n_words": 67,
            "vocab_size": 54,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 160889,
        "commit_id": "6d77c591c59b5678f14ae5af2127eebb7d2415bc",
        "repo": "numpy",
        "path": "numpy/ma/core.py",
        "file_name": "core.py",
        "fun_name": "__radd__",
        "commit_message": "ENH: Adding __array_ufunc__ capability to MaskedArrays.\n\nThis enables any ufunc numpy operations that are called on a\nMaskedArray to use the masked version of that function automatically\nwithout needing to resort to np.ma.func() calls.",
        "code": "def __radd__(self, other):\n        \n        # In analogy with __rsub__ and __rdiv__, use original order:\n        # we get here from `other + self`.\n        return np.add(other, self)\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 52,
        "n_words": 24,
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        "complexity": 1,
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        "token_counts": 17,
        "n_ast_nodes": 30,
        "n_identifiers": 5,
        "d_id": 38785,
        "documentation": {
            "docstring": "\n        Add other to self, and return a new masked array.\n\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 218361,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/util.py",
        "file_name": "util.py",
        "fun_name": "__getattribute__",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def __getattribute__(self, attr):\n        \n        # All module metadata must be garnered from __spec__ in order to avoid\n        # using mutated values.\n        # Stop triggering this method.\n        self.__class__ = types.ModuleType\n        # Get the original name to make sure no object substitution occurred\n        # in sys.modules.\n        original_name = self.__spec__.name\n        # Figure out exactly what attributes were mutated between the creation\n        # of the module and now.\n        attrs_then = self.__spec__.loader_state['__dict__']\n        attrs_now = self.__dict__\n        attrs_updated = {}\n        for key, value in attrs_now.items():\n            # Code that set the attribute may have kept a reference to the\n            # assigned object, making identity more important than equality.\n            if key not in attrs_then:\n                attrs_updated[key] = value\n            elif id(attrs_now[key]) != id(attrs_then[key]):\n                attrs_updated[key] = value\n        self.__spec__.loader.exec_module(self)\n        # If exec_module() was used directly there is no guarantee the module\n        # object was put into sys.modules.\n        if original_name in sys.modules:\n            if id(self) != id(sys.modules[original_name]):\n                raise ValueError(f\"module object for {original_name!r} \"\n                                  \"substituted in sys.modules during a lazy \"\n                                  \"load\")\n        # Update after loading since that's what would happen in an eager\n        # loading situation.\n        self.__dict__.update(attrs_updated)\n        return getattr(self, attr)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 494,
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        "complexity": 6,
        "nloc": 19,
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        "n_identifiers": 25,
        "d_id": 55258,
        "documentation": {
            "docstring": "Trigger the load of the module and return the attribute.",
            "n_words": 10,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 275169,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/models/cloning.py",
        "file_name": "cloning.py",
        "fun_name": "_reset_build_compile_trackers",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _reset_build_compile_trackers(model):\n    \n    # Reset build state\n    model.built = False\n    model.inputs = None\n    model.outputs = None\n    # Reset compile state\n    model._is_compiled = False  # pylint:disable=protected-access\n    if not tf.compat.v1.executing_eagerly_outside_functions():\n        model._v1_compile_was_called = False\n    model.optimizer = None\n\n\n@keras_export(\n    \"keras.__internal__.models.in_place_subclassed_model_state_restoration\",\n    v1=[],\n)",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\n    \"keras.__internal__.models.in_place_subclassed_model_state_restoration\",\n    v1=[],\n)",
        "n_ast_errors": 1,
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        "n_whitespaces": 76,
        "n_words": 37,
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        "d_id": 81325,
        "documentation": {
            "docstring": "Reset state trackers for model.\n\n    Note that we do not actually zero out attributes such as optimizer,\n    but instead rely on the expectation that all of the attrs will be\n    over-written on calling build/compile/etc. This is somewhat fragile,\n    insofar as we check elsewhere for the presence of these attributes as\n    evidence of having been built/compiled/etc. Pending a better way to do this,\n    we reset key attributes here to allow building and compiling.\n\n    Args:\n      model: the model that is being reset\n    ",
            "n_words": 80,
            "vocab_size": 61,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 113648,
        "commit_id": "d68c786ff81bad19c04619d6a999ff34aaa724e7",
        "repo": "nni",
        "path": "nni/compression/pytorch/quantization/observer_quantizer.py",
        "file_name": "observer_quantizer.py",
        "fun_name": "compress",
        "commit_message": "[Compression] remove pruning v1 & refactor directory (#5228)",
        "code": "def compress(self):\n        \n        modules_to_compress = self.get_modules_to_compress()\n        for layer, config in modules_to_compress:\n            module = layer.module\n            if \"weight\" in config.get(\"quant_types\", []):\n                scale, zero_point = self.calculate_qparams(layer.name, 'weight')\n                module.register_buffer('weight_scale', scale.to(self.device))\n                module.register_buffer('weight_zero_point', zero_point.to(self.device))\n                weight = module.weight\n                quantized_weight = self._quantize(weight,\n                                            module.weight_scale,\n                                            module.weight_zero_point,\n                                            module.weight_qmin,\n                                            module.weight_qmax)\n                delattr(module, 'weight')\n                module.register_buffer('weight', quantized_weight)\n            if \"input\" in config.get(\"quant_types\", []):\n                scale, zero_point = self.calculate_qparams(layer.name, 'input')\n                module.register_buffer('input_scale', scale.to(self.device))\n                module.register_buffer('input_zero_point', zero_point.to(self.device))\n            if \"output\" in config.get(\"quant_types\", []):\n                scale, zero_point = self.calculate_qparams(layer.name, 'output')\n                module.register_buffer('output_scale', scale.to(self.device))\n                module.register_buffer('output_zero_point', zero_point.to(self.device))\n        self.compressed = True\n        super().compress()\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 519,
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        "vocab_size": 46,
        "complexity": 5,
        "nloc": 26,
        "token_counts": 251,
        "n_ast_nodes": 421,
        "n_identifiers": 25,
        "d_id": 24988,
        "documentation": {
            "docstring": "\n        Calculate quantization information of each tensor. Note that the inference of\n        the compressed model will no longer update the corresponding. Instead, the quantization\n        process will be simulated, which is used to test the accuracy of the quantization.\n        ",
            "n_words": 37,
            "vocab_size": 28,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 266089,
        "commit_id": "cd8943144bec52ff608ddad3db5d0155832a4a23",
        "repo": "netbox",
        "path": "netbox/extras/context_managers.py",
        "file_name": "context_managers.py",
        "fun_name": "change_logging",
        "commit_message": "Use context vars instead of thread-local storage for change logging",
        "code": "def change_logging(request):\n    \n    current_request.set(request)\n    webhooks_queue.set([])\n\n    # Connect our receivers to the post_save and post_delete signals.\n    post_save.connect(handle_changed_object, dispatch_uid='handle_changed_object')\n    m2m_changed.connect(handle_changed_object, dispatch_uid='handle_changed_object')\n    pre_delete.connect(handle_deleted_object, dispatch_uid='handle_deleted_object')\n    clear_webhooks.connect(clear_webhook_queue, dispatch_uid='clear_webhook_queue')\n\n    yield\n\n    # Disconnect change logging signals. This is necessary to avoid recording any errant\n    # changes during test cleanup.\n    post_save.disconnect(handle_changed_object, dispatch_uid='handle_changed_object')\n    m2m_changed.disconnect(handle_changed_object, dispatch_uid='handle_changed_object')\n    pre_delete.disconnect(handle_deleted_object, dispatch_uid='handle_deleted_object')\n    clear_webhooks.disconnect(clear_webhook_queue, dispatch_uid='clear_webhook_queue')\n\n    # Flush queued webhooks to RQ\n    flush_webhooks(webhooks_queue.get())\n\n    # Clear context vars\n    current_request.set(None)\n    webhooks_queue.set([])\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 122,
        "n_words": 62,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 121,
        "n_ast_nodes": 215,
        "n_identifiers": 17,
        "d_id": 78284,
        "documentation": {
            "docstring": "\n    Enable change logging by connecting the appropriate signals to their receivers before code is run, and\n    disconnecting them afterward.\n\n    :param request: WSGIRequest object with a unique `id` set\n    ",
            "n_words": 28,
            "vocab_size": 28,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 45007,
        "commit_id": "66c342d033bd3cb959b4dc4e7e4b8aad597aab63",
        "repo": "airflow",
        "path": "airflow/migrations/versions/8646922c8a04_change_default_pool_slots_to_1.py",
        "file_name": "8646922c8a04_change_default_pool_slots_to_1.py",
        "fun_name": "upgrade",
        "commit_message": "Support generating SQL script for upgrades (#20962)\n\nThis PR attempts to add support for generating sql scripts for upgrade.\r\nExample command:\r\n`airflow db upgrade --revision-range e8d98d8ss99:78daisdu38d`\r\n`airflow db upgrade --range 2.0.0:2.2.3`",
        "code": "def upgrade():\n    \n    with op.batch_alter_table(\"task_instance\", schema=None) as batch_op:\n        batch_op.alter_column(\"pool_slots\", existing_type=sa.Integer, nullable=False, server_default='1')\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 24,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 39,
        "n_ast_nodes": 70,
        "n_identifiers": 11,
        "d_id": 8439,
        "documentation": {
            "docstring": "Change default pool_slots to 1 and make pool_slots not nullable",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 107009,
        "commit_id": "8669c4636ce3b6ac6f4905c365ab41685186da56",
        "repo": "matplotlib",
        "path": "lib/matplotlib/figure.py",
        "file_name": "figure.py",
        "fun_name": "gca",
        "commit_message": "Rewrite AxesStack independently of cbook.Stack.\n\nAxesStack is fairly independent from cbook.Stack: cbook.Stack handles\nthe forward/back/home buttons of the navbar, and therefore additionally\nmaintains a movable \"cursor\" in the stack; AxesStack, on the other hand,\nneeds to keep track both of \"original\" order and of \"gca\" order.\nRewriting it from scratch, and using \"original\" order as main storage\norder (the \"gca\" stack being tracked using indices) shortens the\nimplementation and simplifies it (as there's no more need to figure out\nwhat the super()calls do).",
        "code": "def gca(self, **kwargs):\n        \n        if kwargs:\n            _api.warn_deprecated(\n                \"3.4\",\n                message=\"Calling gca() with keyword arguments was deprecated \"\n                \"in Matplotlib %(since)s. Starting %(removal)s, gca() will \"\n                \"take no keyword arguments. The gca() function should only be \"\n                \"used to get the current axes, or if no axes exist, create \"\n                \"new axes with default keyword arguments. To create a new \"\n                \"axes with non-default arguments, use plt.axes() or \"\n                \"plt.subplot().\")\n        ax = self._axstack.current()\n        return ax if ax is not None else self.add_subplot(**kwargs)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 238,
        "n_words": 79,
        "vocab_size": 59,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 52,
        "n_ast_nodes": 97,
        "n_identifiers": 10,
        "d_id": 22547,
        "documentation": {
            "docstring": "\n        Get the current Axes.\n\n        If there is currently no Axes on this Figure, a new one is created\n        using `.Figure.add_subplot`.  (To test whether there is currently an\n        Axes on a Figure, check whether ``figure.axes`` is empty.  To test\n        whether there is currently a Figure on the pyplot figure stack, check\n        whether `.pyplot.get_fignums()` is empty.)\n\n        The following kwargs are supported for ensuring the returned Axes\n        adheres to the given projection etc., and for Axes creation if\n        the active Axes does not exist:\n\n        %(Axes:kwdoc)s\n        ",
            "n_words": 82,
            "vocab_size": 54,
            "n_whitespaces": 162,
            "language": "en"
        }
    },
    {
        "id": 264668,
        "commit_id": "f13a00b2dd33bffc3048c861b494096df457f212",
        "repo": "netbox",
        "path": "netbox/extras/reports.py",
        "file_name": "reports.py",
        "fun_name": "run_report",
        "commit_message": "Save old JobResults",
        "code": "def run_report(job_result, *args, **kwargs):\n    \n    module_name, report_name = job_result.name.split('.', 1)\n    report = get_report(module_name, report_name)\n\n    try:\n        report.run(job_result)\n    except Exception as e:\n        print(e)\n        job_result.set_status(JobResultStatusChoices.STATUS_ERRORED)\n        job_result.save()\n        logging.error(f\"Error during execution of report {job_result.name}\")\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 78,
        "n_words": 28,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 108,
        "n_ast_nodes": 127,
        "n_identifiers": 20,
        "d_id": 77780,
        "documentation": {
            "docstring": "\n    Helper function to call the run method on a report. This is needed to get around the inability to pickle an instance\n    method for queueing into the background processor.\n    ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 58708,
        "commit_id": "0a59ec9279d929fe6a7199ff7ff7c0b58cffa100",
        "repo": "prefect",
        "path": "src/prefect/deployments.py",
        "file_name": "deployments.py",
        "fun_name": "location",
        "commit_message": "Add location as a computed property of deployments",
        "code": "def location(self) -> str:\n        \n        location = \"\"\n        if self.storage:\n            location = (\n                self.storage.basepath + \"/\"\n                if not self.storage.basepath.endswith(\"/\")\n                else \"\"\n            )\n        if self.path:\n            location += self.path\n        return location\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 141,
        "n_words": 28,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 53,
        "n_ast_nodes": 94,
        "n_identifiers": 7,
        "d_id": 11802,
        "documentation": {
            "docstring": "\n        The 'location' that this deployment points to is given by `path` alone\n        in the case of no remote storage, and otherwise by `storage.basepath / path`.\n\n        The underlying flow entrypoint is interpreted relative to this location.\n        ",
            "n_words": 35,
            "vocab_size": 30,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 185308,
        "commit_id": "17bc375e080c30d8754dfeccf44f9a607e041e1b",
        "repo": "textual",
        "path": "tests/test_message_pump.py",
        "file_name": "test_message_pump.py",
        "fun_name": "test_dispatch_key_raises_when_public_and_private_handlers",
        "commit_message": "Support for key aliases, key handling tests",
        "code": "async def test_dispatch_key_raises_when_public_and_private_handlers():\n    \n    widget = DuplicateHandlersWidget()\n    with pytest.raises(DuplicateKeyHandlers):\n        await widget.dispatch_key(Key(widget, key=\"x\", char=\"x\"))\n    assert widget.called_by is None\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 35,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 42,
        "n_ast_nodes": 77,
        "n_identifiers": 11,
        "d_id": 44966,
        "documentation": {
            "docstring": "When both a public and private handler exists for one key, we fail fast via exception.",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 71728,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/pages/test_revisions.py",
        "file_name": "test_revisions.py",
        "fun_name": "test_unschedule_view_post",
        "commit_message": "Reformat with black",
        "code": "def test_unschedule_view_post(self):\n        \n\n        # Post to the unschedule page\n        response = self.client.post(\n            reverse(\n                \"wagtailadmin_pages:revisions_unschedule\",\n                args=(self.christmas_event.id, self.this_christmas_revision.id),\n            )\n        )\n\n        # Should be redirected to page history\n        self.assertRedirects(\n            response,\n            reverse(\"wagtailadmin_pages:history\", args=(self.christmas_event.id,)),\n        )\n\n        # Check that the page has no approved_schedule\n        self.assertFalse(\n            EventPage.objects.get(id=self.christmas_event.id).approved_schedule\n        )\n\n        # Check that the approved_go_live_at has been cleared from the revision\n        self.assertIsNone(\n            self.christmas_event.revisions.get(\n                id=self.this_christmas_revision.id\n            ).approved_go_live_at\n        )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 269,
        "n_words": 56,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 103,
        "n_ast_nodes": 167,
        "n_identifiers": 19,
        "d_id": 15720,
        "documentation": {
            "docstring": "\n        This posts to the unschedule view and checks that the revision was unscheduled\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 276118,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/saving/saved_model/save_impl.py",
        "file_name": "save_impl.py",
        "fun_name": "_wrap_call_and_conditional_losses",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _wrap_call_and_conditional_losses(layer):\n    \n    # Create function that generates both outputs and losses\n    layer_call = _get_layer_call_method(layer)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 23,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 24,
        "n_identifiers": 4,
        "d_id": 81567,
        "documentation": {
            "docstring": "Wraps call function that returns a tuple of (outputs, losses).\n\n    The losses returned are conditional on the inputs passed to the call function.\n    Unconditional losses (e.g. weight regularizeration) are wrapped separately.\n\n    Args:\n      layer: a Keras layer object\n\n    Returns:\n      python call function that returns outputs and conditional losses -- excludes\n      activity regularizer\n    ",
            "n_words": 51,
            "vocab_size": 40,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 205087,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/oracle/operations.py",
        "file_name": "operations.py",
        "fun_name": "_get_no_autofield_sequence_name",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get_no_autofield_sequence_name(self, table):\n        \n        name_length = self.max_name_length() - 3\n        return \"%s_SQ\" % truncate_name(strip_quotes(table), name_length).upper()\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 8,
        "d_id": 51012,
        "documentation": {
            "docstring": "\n        Manually created sequence name to keep backward compatibility for\n        AutoFields that aren't Oracle identity columns.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 221655,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/configparser.py",
        "file_name": "configparser.py",
        "fun_name": "_unify_values",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _unify_values(self, section, vars):\n        \n        sectiondict = {}\n        try:\n            sectiondict = self._sections[section]\n        except KeyError:\n            if section != self.default_section:\n                raise NoSectionError(section) from None\n        # Update with the entry specific variables\n        vardict = {}\n        if vars:\n            for key, value in vars.items():\n                if value is not None:\n                    value = str(value)\n                vardict[self.optionxform(key)] = value\n        return _ChainMap(vardict, sectiondict, self._defaults)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 206,
        "n_words": 53,
        "vocab_size": 42,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 93,
        "n_ast_nodes": 147,
        "n_identifiers": 17,
        "d_id": 56460,
        "documentation": {
            "docstring": "Create a sequence of lookups with 'vars' taking priority over\n        the 'section' which takes priority over the DEFAULTSECT.\n\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 42996,
        "commit_id": "b1ad017cee66f5e042144cc7baa2d44b23b47c4f",
        "repo": "airflow",
        "path": "airflow/cli/commands/dag_command.py",
        "file_name": "dag_command.py",
        "fun_name": "dag_state",
        "commit_message": "pydocstyle D202 added (#24221)",
        "code": "def dag_state(args, session=NEW_SESSION):\n    \n    dag = DagModel.get_dagmodel(args.dag_id, session=session)\n\n    if not dag:\n        raise SystemExit(f\"DAG: {args.dag_id} does not exist in 'dag' table\")\n    dr = session.query(DagRun).filter_by(dag_id=args.dag_id, execution_date=args.execution_date).one_or_none()\n    out = dr.state if dr else None\n    conf_out = ''\n    if out and dr.conf:\n        conf_out = ', ' + json.dumps(dr.conf)\n    print(str(out) + conf_out)\n\n\n@cli_utils.action_cli",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "@cli_utils.action_cli",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 84,
        "n_words": 47,
        "vocab_size": 36,
        "complexity": 5,
        "nloc": 10,
        "token_counts": 101,
        "n_ast_nodes": 179,
        "n_identifiers": 25,
        "d_id": 7780,
        "documentation": {
            "docstring": "\n    Returns the state (and conf if exists) of a DagRun at the command line.\n    >>> airflow dags state tutorial 2015-01-01T00:00:00.000000\n    running\n    >>> airflow dags state a_dag_with_conf_passed 2015-01-01T00:00:00.000000\n    failed, {\"name\": \"bob\", \"age\": \"42\"}\n    ",
            "n_words": 32,
            "vocab_size": 25,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 4247,
        "commit_id": "56bf982cb96f831fe04f5e44a92ee4a669b9e16a",
        "repo": "airbyte",
        "path": "octavia-cli/octavia_cli/apply/resources.py",
        "file_name": "resources.py",
        "fun_name": "_search",
        "commit_message": "🐙 octavia-cli: `apply` connections (#10881)",
        "code": "def _search(self, check_return_type=True) -> Union[SourceReadList, DestinationReadList, ConnectionReadList]:\n        \n        return self._search_fn(self.api_instance, self.search_payload, _check_return_type=check_return_type)\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 36,
        "n_ast_nodes": 53,
        "n_identifiers": 11,
        "d_id": 641,
        "documentation": {
            "docstring": "Run search of a resources on the remote Airbyte instance.\n\n        Returns:\n            Union[SourceReadList, DestinationReadList, ConnectionReadList]: Search results\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 34302,
        "commit_id": "ac227093e41cecb07c7e0f2fc9a504850907bd06",
        "repo": "transformers",
        "path": "src/transformers/models/vilt/feature_extraction_vilt.py",
        "file_name": "feature_extraction_vilt.py",
        "fun_name": "_resize",
        "commit_message": "Add ViLT (#14895)\n\n* First commit\r\n\r\n* Add conversion script\r\n\r\n* Make conversion script work for base model\r\n\r\n* More improvements\r\n\r\n* Update conversion script, works for vqa\r\n\r\n* Add indexing argument to meshgrid\r\n\r\n* Make conversion script work for ViltForPreTraining\r\n\r\n* Add ViltForPreTraining to docs\r\n\r\n* Fix device issue\r\n\r\n* Add processor\r\n\r\n* Add MinMaxResize to feature extractor\r\n\r\n* Implement call method of ViltProcessor\r\n\r\n* Fix tests\r\n\r\n* Add integration test\r\n\r\n* Add loss calculation for VQA\r\n\r\n* Improve tests\r\n\r\n* Improve some more tests\r\n\r\n* Debug tests\r\n\r\n* Small improvements\r\n\r\n* Add support for attention_mask\r\n\r\n* Remove mask_it\r\n\r\n* Add pixel_mask\r\n\r\n* Add tests for ViltFeatureExtractor\r\n\r\n* Improve tests\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning to conversion script\r\n\r\n* Minor fixes\r\n\r\n* Add support for image_embeds, update docstrings to markdown\r\n\r\n* Update docs to markdown\r\n\r\n* Improve conversion script\r\n\r\n* Rename ViltForPreTraining to ViltForMaskedLM\r\n\r\n* Improve conversion script\r\n\r\n* Convert docstrings to markdown\r\n\r\n* Fix code example of retrieval model\r\n\r\n* Properly convert masked language model\r\n\r\n* Add integration test for nlvr\r\n\r\n* Fix code quality\r\n\r\n* Apply suggestions from code review\r\n\r\n* Add copied from statements\r\n\r\n* Fix pretrained_config_archive_map\r\n\r\n* Fix docs\r\n\r\n* Add model to README\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Apply more suggestions from code review\r\n\r\n* Make code more readable\r\n\r\n* Add ViltForNaturalLanguageVisualReasoning to the tests\r\n\r\n* Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering\r\n\r\n* Replace pixel_values_2 by single tensor\r\n\r\n* Add hidden_states and attentions\r\n\r\n* Fix one more test\r\n\r\n* Fix all tests\r\n\r\n* Update year\r\n\r\n* Fix rebase issues\r\n\r\n* Fix another rebase issue\r\n\r\n* Remove ViltForPreTraining from auto mapping\r\n\r\n* Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval\r\n\r\n* Make it possible to use BertTokenizerFast in the processor\r\n\r\n* Use BertTokenizerFast by default\r\n\r\n* Rename ViltForNaturalLanguageVisualReasoning, define custom model output\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def _resize(self, image, shorter=800, longer=1333, size_divisor=32, resample=Image.BICUBIC):\n        \n        if not isinstance(image, Image.Image):\n            image = self.to_pil_image(image)\n\n        w, h = image.size\n        min_size = shorter\n        max_size = longer\n        scale = min_size / min(w, h)\n        if h < w:\n            newh, neww = min_size, scale * w\n        else:\n            newh, neww = scale * h, min_size\n\n        if max(newh, neww) > max_size:\n            scale = max_size / max(newh, neww)\n            newh = newh * scale\n            neww = neww * scale\n\n        newh, neww = int(newh + 0.5), int(neww + 0.5)\n        newh, neww = newh // size_divisor * size_divisor, neww // size_divisor * size_divisor\n\n        return self.resize(image, size=(neww, newh), resample=resample)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 247,
        "n_words": 97,
        "vocab_size": 52,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 169,
        "n_ast_nodes": 266,
        "n_identifiers": 23,
        "d_id": 6252,
        "documentation": {
            "docstring": "\n        Resizes the shorter edge of `image` to `shorter` and limits the longer edge to under `longer`, while preserving\n        the aspect ratio. Also makes sure that both the height and width can be divided by `size_divisor`.\n\n        Based on original implementation:\n        https://github.com/dandelin/ViLT/blob/3db8b5035464afee84d951bf6322e1b27f1d072d/vilt/transforms/utils.py#L5\n\n        Args:\n            image (`PIL.Image`):\n                The image to resize.\n            shorter (`int`, *optional*, defaults to `800`):\n                The size to which to resize the shorter side of the image.\n            longer (`int`, *optional*, defaults to `1333`):\n                The size by which to limit the longer side of the image, while preserving the aspect ratio.\n            size_divisor (`int`, *optional*, defaults to `32`):\n                The size by which both the height and the width must be divisible.\n            resample (`int`, *optional*, defaults to `PIL.Image.BICUBIC`):\n                An optional resampling filter.\n        ",
            "n_words": 117,
            "vocab_size": 61,
            "n_whitespaces": 290,
            "language": "en"
        }
    },
    {
        "id": 94414,
        "commit_id": "f5e5a3b1ed97383e0699aff9eb0363e9eb5db479",
        "repo": "sentry",
        "path": "tests/sentry/integrations/jira/test_integration.py",
        "file_name": "test_integration.py",
        "fun_name": "test_instance_url_mismatch",
        "commit_message": "feat(Jira): Plugin issue migration endpoint (#37577)\n\n* feat(jira): Plugin issue migration endpoint",
        "code": "def test_instance_url_mismatch(self):\n        \n        self.plugin.set_option(\"instance_url\", \"https://hellboy.atlassian.net\", self.project)\n        group = self.create_group(message=\"Hello world\", culprit=\"foo.bar\")\n        plugin_issue = GroupMeta.objects.create(\n            key=f\"{self.plugin.slug}:tid\", group_id=group.id, value=\"SEN-1\"\n        )\n        with self.tasks():\n            self.installation.migrate_issues()\n\n        assert not ExternalIssue.objects.filter(\n            organization_id=self.organization.id,\n            integration_id=self.integration.id,\n            key=plugin_issue.value,\n        ).exists()\n        assert GroupMeta.objects.filter(\n            key=f\"{self.plugin.slug}:tid\", group_id=group.id, value=\"SEN-1\"\n        ).exists()\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 169,
        "n_words": 33,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 132,
        "n_ast_nodes": 237,
        "n_identifiers": 28,
        "d_id": 19082,
        "documentation": {
            "docstring": "Test that if the plugin's instance URL does not match the integration's base URL, we don't migrate the issues",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 39219,
        "commit_id": "f1b06e2f758b5b4a965f7bf428d006621d19c0b0",
        "repo": "recommenders",
        "path": "tests/ci/aml_tests_old/submit_azureml_pytest.py",
        "file_name": "submit_azureml_pytest.py",
        "fun_name": "create_experiment",
        "commit_message": "changed folder structure for aml tests",
        "code": "def create_experiment(workspace, experiment_name):\n    \n\n    logger.debug(\"create: experiment_name {}\".format(experiment_name))\n    exp = Experiment(workspace=workspace, name=experiment_name)\n    return exp\n\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 24,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 33,
        "n_ast_nodes": 56,
        "n_identifiers": 9,
        "d_id": 7141,
        "documentation": {
            "docstring": "\n    AzureML requires an experiment as a container of trials.\n    This will either create a new experiment or use an\n    existing one.\n\n    Args:\n        workspace (str) : name of AzureML workspace\n        experiment_name (str) : AzureML experiment name\n    Return:\n        exp - AzureML experiment\n    ",
            "n_words": 40,
            "vocab_size": 27,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 47474,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/jobs/test_local_task_job.py",
        "file_name": "test_local_task_job.py",
        "fun_name": "test_localtaskjob_essential_attr",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def test_localtaskjob_essential_attr(self, dag_maker):\n        \n        with dag_maker('test_localtaskjob_essential_attr'):\n            op1 = EmptyOperator(task_id='op1')\n\n        dr = dag_maker.create_dagrun()\n\n        ti = dr.get_task_instance(task_id=op1.task_id)\n\n        job1 = LocalTaskJob(task_instance=ti, ignore_ti_state=True, executor=SequentialExecutor())\n\n        essential_attr = [\"dag_id\", \"job_type\", \"start_date\", \"hostname\"]\n\n        check_result_1 = [hasattr(job1, attr) for attr in essential_attr]\n        assert all(check_result_1)\n\n        check_result_2 = [getattr(job1, attr) is not None for attr in essential_attr]\n        assert all(check_result_2)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 129,
        "n_words": 48,
        "vocab_size": 36,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 111,
        "n_ast_nodes": 184,
        "n_identifiers": 23,
        "d_id": 9123,
        "documentation": {
            "docstring": "\n        Check whether essential attributes\n        of LocalTaskJob can be assigned with\n        proper values without intervention\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 251414,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "mitmproxy/net/http/url.py",
        "file_name": "url.py",
        "fun_name": "decode",
        "commit_message": "make it black!",
        "code": "def decode(s):\n    \n    return urllib.parse.parse_qsl(s, keep_blank_values=True, errors=\"surrogateescape\")\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 12,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 23,
        "n_ast_nodes": 39,
        "n_identifiers": 7,
        "d_id": 73725,
        "documentation": {
            "docstring": "\n    Takes a urlencoded string and returns a list of surrogate-escaped (key, value) tuples.\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 83239,
        "commit_id": "b0ce4f1bce8031881addecb1e86073483517f392",
        "repo": "zulip",
        "path": "zerver/tests/test_event_queue.py",
        "file_name": "test_event_queue.py",
        "fun_name": "test_collapse_event",
        "commit_message": "docs: Fix many spelling mistakes.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def test_collapse_event(self) -> None:\n        \n        client = self.get_client_descriptor()\n        queue = client.event_queue\n        queue.push({\"type\": \"restart\", \"server_generation\": 1, \"timestamp\": \"1\"})\n        # Verify the server_generation event is stored as a virtual event\n        self.assertEqual(\n            queue.virtual_events,\n            {\"restart\": {\"id\": 0, \"type\": \"restart\", \"server_generation\": 1, \"timestamp\": \"1\"}},\n        )\n        # And we can reconstruct newest_pruned_id etc.\n        self.verify_to_dict_end_to_end(client)\n\n        queue.push({\"type\": \"unknown\", \"timestamp\": \"1\"})\n        self.assertEqual(list(queue.queue), [{\"id\": 1, \"type\": \"unknown\", \"timestamp\": \"1\"}])\n        self.assertEqual(\n            queue.virtual_events,\n            {\"restart\": {\"id\": 0, \"type\": \"restart\", \"server_generation\": 1, \"timestamp\": \"1\"}},\n        )\n        # And we can still reconstruct newest_pruned_id etc. correctly\n        self.verify_to_dict_end_to_end(client)\n\n        # Verify virtual events are converted to real events by .contents()\n        self.assertEqual(\n            queue.contents(),\n            [\n                {\"id\": 0, \"type\": \"restart\", \"server_generation\": 1, \"timestamp\": \"1\"},\n                {\"id\": 1, \"type\": \"unknown\", \"timestamp\": \"1\"},\n            ],\n        )\n\n        # And now verify to_dict after pruning\n        queue.prune(0)\n        self.verify_to_dict_end_to_end(client)\n\n        queue.prune(1)\n        self.verify_to_dict_end_to_end(client)\n\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 389,
        "n_words": 121,
        "vocab_size": 64,
        "complexity": 1,
        "nloc": 34,
        "token_counts": 223,
        "n_ast_nodes": 414,
        "n_identifiers": 13,
        "d_id": 17634,
        "documentation": {
            "docstring": "\n        This mostly focuses on the internals of\n        how we store \"virtual_events\" that we\n        can collapse if subsequent events are\n        of the same form.  See the code in\n        EventQueue.push for more context.\n        ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 201772,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/backends/sqlite/test_introspection.py",
        "file_name": "test_introspection.py",
        "fun_name": "test_get_primary_key_column",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_get_primary_key_column(self):\n        \n        testable_column_strings = (\n            (\"id\", \"id\"),\n            (\"[id]\", \"id\"),\n            (\"`id`\", \"id\"),\n            ('\"id\"', \"id\"),\n            (\"[id col]\", \"id col\"),\n            (\"`id col`\", \"id col\"),\n            ('\"id col\"', \"id col\"),\n        )\n        with connection.cursor() as cursor:\n            for column, expected_string in testable_column_strings:\n                sql = \"CREATE TABLE test_primary (%s int PRIMARY KEY NOT NULL)\" % column\n                with self.subTest(column=column):\n                    try:\n                        cursor.execute(sql)\n                        field = connection.introspection.get_primary_key_column(\n                            cursor, \"test_primary\"\n                        )\n                        self.assertEqual(field, expected_string)\n                    finally:\n                        cursor.execute(\"DROP TABLE test_primary\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 390,
        "n_words": 64,
        "vocab_size": 52,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 119,
        "n_ast_nodes": 215,
        "n_identifiers": 14,
        "d_id": 49992,
        "documentation": {
            "docstring": "\n        Get the primary key column regardless of whether or not it has\n        quotation.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 281411,
        "commit_id": "5a5c7193db3cf15ee7bb881ba912b8289aa83a80",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/stocks/options/options_controller.py",
        "file_name": "options_controller.py",
        "fun_name": "print_help",
        "commit_message": "Volatility surface (#1176)\n\n* Add a 3D volatility surface from yfinance data\r\n\r\n* Update _index.md\r\n\r\n* other tests",
        "code": "def print_help(self):\n        \n        colored = self.ticker and self.selected_date\n        help_text = f\n        print(help_text)\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 39,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 30,
        "token_counts": 23,
        "n_ast_nodes": 140,
        "n_identifiers": 10,
        "d_id": 83744,
        "documentation": {
            "docstring": "Print help.\n    unu           show unusual options activity [fdscanner.com]\n    calc          basic call/put PnL calculator\n\n    load          load new ticker\n    exp           see and set expiration dates\n\nTicker: {self.ticker or None}\nExpiry: {self.selected_date or None}\n{\"\" if self.ticker else Style.DIM}\n    pcr           display put call ratio for ticker [AlphaQuery.com]{Style.DIM if not colored else ''}\n    info          display option information (volatility, IV rank etc) [Barchart.com]\n    chains        display option chains with greeks [Tradier]\n    oi            plot open interest [Tradier/YF]\n    vol           plot volume [Tradier/YF]\n    voi           plot volume and open interest [Tradier/YF]\n    hist          plot option history [Tradier]\n    vsurf         show 3D volatility surface [Yfinance]\n    grhist        plot option greek history [Syncretism.io]\n    plot          plot variables provided by the user [Yfinance]\n    parity        shows whether options are above or below expected price [Yfinance]\n    binom         shows the value of an option using binomial options pricing [Yfinance]\n{Style.RESET_ALL if not colored else ''}\n>   screen        screens tickers based on preset [Syncretism.io]{\"\" if colored else Style.DIM}\n>   payoff        shows payoff diagram for a selection of options [Yfinance]\n>   pricing       shows options pricing and risk neutral valuation [Yfinance]\n{Style.RESET_ALL if not colored else ''}",
            "n_words": 174,
            "vocab_size": 109,
            "n_whitespaces": 382,
            "language": "en"
        }
    },
    {
        "id": 61930,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py",
        "file_name": "database.py",
        "fun_name": "list_installed_files",
        "commit_message": "upd; format",
        "code": "def list_installed_files(self):\n        \n        for result in self._get_records():\n            yield result\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 17,
        "n_ast_nodes": 31,
        "n_identifiers": 4,
        "d_id": 12755,
        "documentation": {
            "docstring": "\n        Iterates over the ``RECORD`` entries and returns a tuple\n        ``(path, hash, size)`` for each line.\n\n        :returns: iterator of (path, hash, size)\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 133242,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/sgd/tests/test_torch_2.py",
        "file_name": "test_torch_2.py",
        "fun_name": "test_dataset",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_dataset(ray_start_4_cpus, use_local):\n    \n\n    model_creator = mlp_identity.model_creator\n    optimizer_creator = mlp_identity.optimizer_creator\n    dataset_creator = mlp_identity.dataset_creator\n\n    DatasetOperator = TrainingOperator.from_creators(\n        model_creator=model_creator,\n        optimizer_creator=optimizer_creator,\n        loss_creator=nn.MSELoss,\n    )\n\n    trainer = TorchTrainer(\n        training_operator_cls=DatasetOperator,\n        use_local=use_local,\n        num_workers=2,\n    )\n\n    dataset = dataset_creator()\n    for i in range(5):\n        trainer.train(dataset=dataset, num_steps=100)\n\n    x = mlp_identity.to_mat(0.5)\n    prediction = float(trainer.get_model()(x)[0][0])\n    assert 0.4 <= prediction <= 0.6\n    trainer.shutdown()\n\n\n@pytest.mark.parametrize(\"use_local\", [True, False])",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"use_local\", [True, False])",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 141,
        "n_words": 51,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 130,
        "n_ast_nodes": 216,
        "n_identifiers": 31,
        "d_id": 29963,
        "documentation": {
            "docstring": "\n    This test tries training the mlp_identity example. We check the accuracy of\n    the model as an all inclusive way of ensuring that we are properly sharding\n    and iterating over the entire dataset (instead of repeating the first set\n    of points for example).\n    ",
            "n_words": 42,
            "vocab_size": 35,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 63102,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_is_current",
        "commit_message": "upd; format",
        "code": "def _is_current(self, file_path, zip_path):\n        \n        timestamp, size = self._get_date_and_size(self.zipinfo[zip_path])\n        if not os.path.isfile(file_path):\n            return False\n        stat = os.stat(file_path)\n        if stat.st_size != size or stat.st_mtime != timestamp:\n            return False\n        # check that the contents match\n        zip_contents = self.loader.get_data(zip_path)\n        with open(file_path, 'rb') as f:\n            file_contents = f.read()\n        return zip_contents == file_contents\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 143,
        "n_words": 47,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 92,
        "n_ast_nodes": 152,
        "n_identifiers": 21,
        "d_id": 13147,
        "documentation": {
            "docstring": "\n        Return True if the file_path is current for this zip_path\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 160998,
        "commit_id": "0536874dec68e68969502ce1774168552727fa17",
        "repo": "MockingBird",
        "path": "synthesizer/inference.py",
        "file_name": "inference.py",
        "fun_name": "load",
        "commit_message": "Add config file for pretrained",
        "code": "def load(self):\n        # Try to scan config file\n        model_config_fpaths = list(self.model_fpath.parent.rglob(\"*.json\"))\n        if len(model_config_fpaths)>0 and model_config_fpaths[0].exists():\n            with model_config_fpaths[0].open(\"r\", encoding=\"utf-8\") as f:\n                hparams.loadJson(json.load(f))\n        \n        self._model = Tacotron(embed_dims=hparams.tts_embed_dims,\n                               num_chars=len(symbols),\n                               encoder_dims=hparams.tts_encoder_dims,\n                               decoder_dims=hparams.tts_decoder_dims,\n                               n_mels=hparams.num_mels,\n                               fft_bins=hparams.num_mels,\n                               postnet_dims=hparams.tts_postnet_dims,\n                               encoder_K=hparams.tts_encoder_K,\n                               lstm_dims=hparams.tts_lstm_dims,\n                               postnet_K=hparams.tts_postnet_K,\n                               num_highways=hparams.tts_num_highways,\n                               dropout=hparams.tts_dropout,\n                               stop_threshold=hparams.tts_stop_threshold,\n                               speaker_embedding_size=hparams.speaker_embedding_size).to(self.device)\n\n        self._model.load(self.model_fpath, self.device)\n        self._model.eval()\n\n        if self.verbose:\n            print(\"Loaded synthesizer \\\"%s\\\" trained to step %d\" % (self.model_fpath.name, self._model.state_dict()[\"step\"]))\n",
        "url": "https://github.com/babysor/MockingBird.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 535,
        "n_words": 52,
        "vocab_size": 49,
        "complexity": 4,
        "nloc": 26,
        "token_counts": 213,
        "n_ast_nodes": 335,
        "n_identifiers": 50,
        "d_id": 38850,
        "documentation": {
            "docstring": "\n        Instantiates and loads the model given the weights file that was passed in the constructor.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 242703,
        "commit_id": "a724be66bef4b692994e5defa22ba3f1b2a1f771",
        "repo": "Pillow",
        "path": "src/PIL/ImageTk.py",
        "file_name": "ImageTk.py",
        "fun_name": "paste",
        "commit_message": "Deprecated PhotoImage.paste() box parameter",
        "code": "def paste(self, im, box=None):\n        \n\n        if box is not None:\n            warnings.warn(\n                \"The box parameter is deprecated and will be removed in Pillow 10 \"\n                \"(2023-07-01).\",\n                DeprecationWarning,\n            )\n\n        # convert to blittable\n        im.load()\n        image = im.im\n        if image.isblock() and im.mode == self.__mode:\n            block = image\n        else:\n            block = image.new_block(self.__mode, im.size)\n            image.convert2(block, image)  # convert directly between buffers\n\n        _pyimagingtkcall(\"PyImagingPhoto\", self.__photo, block.id)\n\n\n# --------------------------------------------------------------------\n# BitmapImage\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 217,
        "n_words": 62,
        "vocab_size": 50,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 92,
        "n_ast_nodes": 154,
        "n_identifiers": 19,
        "d_id": 69895,
        "documentation": {
            "docstring": "\n        Paste a PIL image into the photo image.  Note that this can\n        be very slow if the photo image is displayed.\n\n        :param im: A PIL image. The size must match the target region.  If the\n                   mode does not match, the image is converted to the mode of\n                   the bitmap image.\n        ",
            "n_words": 50,
            "vocab_size": 36,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 292234,
        "commit_id": "beb30a1ff199596163c655e8ae745a0f1649b78a",
        "repo": "core",
        "path": "tests/components/google_travel_time/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_sensor_arrival_time_custom_timestamp",
        "commit_message": "Add google_travel_time sensor tests (#66568)\n\nCo-authored-by: Paulus Schoutsen <paulus@home-assistant.io>",
        "code": "async def test_sensor_arrival_time_custom_timestamp(hass):\n    \n    assert hass.states.get(\"sensor.google_travel_time\").state == \"27\"\n\n\n@pytest.mark.usefixtures(\"mock_update\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.usefixtures(\"mock_update\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 13,
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        "n_ast_nodes": 55,
        "n_identifiers": 8,
        "d_id": 91334,
        "documentation": {
            "docstring": "Test that sensor works for arrival time with a custom timestamp.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 63273,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "col",
        "commit_message": "upd; format",
        "code": "def col (loc, strg):\n    \n    s = strg\n    return 1 if 0 < loc < len(s) and s[loc-1] == '\\n' else loc - s.rfind(\"\\n\", 0, loc)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 34,
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        "d_id": 13225,
        "documentation": {
            "docstring": "Returns current column within a string, counting newlines as line separators.\n   The first column is number 1.\n\n   Note: the default parsing behavior is to expand tabs in the input string\n   before starting the parsing process.  See\n   :class:`ParserElement.parseString` for more\n   information on parsing strings containing ``<TAB>`` s, and suggested\n   methods to maintain a consistent view of the parsed string, the parse\n   location, and line and column positions within the parsed string.\n   ",
            "n_words": 70,
            "vocab_size": 52,
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            "language": "en"
        }
    },
    {
        "id": 220829,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/tasks.py",
        "file_name": "tasks.py",
        "fun_name": "ensure_future",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def ensure_future(coro_or_future, *, loop=None):\n    \n    return _ensure_future(coro_or_future, loop=loop)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
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        "n_identifiers": 4,
        "d_id": 56137,
        "documentation": {
            "docstring": "Wrap a coroutine or an awaitable in a future.\n\n    If the argument is a Future, it is returned directly.\n    ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 46604,
        "commit_id": "b5a786b38148295c492da8ab731d5e2f6f86ccf7",
        "repo": "airflow",
        "path": "airflow/providers_manager.py",
        "file_name": "providers_manager.py",
        "fun_name": "_discover_secrets_backends",
        "commit_message": "Suppress import errors for providers from sources (#22579)\n\nWhen we are running airflow locally with providers installed from sources, often many providers will be discovered which we haven't installed the deps for.  This generally results in a very large amount of traceback logging, which has a very negative effect on usefulness of terminal output.  Here we suppress this error logging for providers that are installed from sources.",
        "code": "def _discover_secrets_backends(self) -> None:\n        \n        for provider_package, provider in self._provider_dict.items():\n            if provider.data.get(\"secrets-backends\"):\n                for secrets_backends_class_name in provider.data[\"secrets-backends\"]:\n                    if _sanity_check(provider_package, secrets_backends_class_name, provider):\n                        self._secrets_backend_class_name_set.add(secrets_backends_class_name)\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 102,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 59,
        "n_ast_nodes": 97,
        "n_identifiers": 12,
        "d_id": 8932,
        "documentation": {
            "docstring": "Retrieves all secrets backends defined in the providers",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 99595,
        "commit_id": "1730c481f1a8a71446326fa1ff72e10663016385",
        "repo": "sentry",
        "path": "tests/sentry/notifications/test_notifications.py",
        "file_name": "test_notifications.py",
        "fun_name": "test_sends_note_notification",
        "commit_message": "fix(notifications): Use `metrics_key` (#34572)",
        "code": "def test_sends_note_notification(self):\n        \n\n        # leave a comment\n        url = f\"/api/0/issues/{self.group.id}/comments/\"\n        with self.tasks():\n            response = self.client.post(url, format=\"json\", data={\"text\": \"blah blah\"})\n        assert response.status_code == 201, response.content\n\n        msg = mail.outbox[0]\n        # check the txt version\n        assert \"blah blah\" in msg.body\n        # check the html version\n        assert \"blah blah</p></div>\" in msg.alternatives[0][0]\n\n        attachment, text = get_attachment()\n        # check the Slack version\n        assert text == f\"New comment by {self.name}\"\n        assert attachment[\"title\"] == f\"{self.group.title}\"\n        assert (\n            attachment[\"title_link\"]\n            == f\"http://testserver/organizations/{self.organization.slug}/issues/{self.group.id}/?referrer=note_activity-slack\"\n        )\n        assert attachment[\"text\"] == \"blah blah\"\n        assert (\n            attachment[\"footer\"]\n            == f\"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=note_activity-slack-user|Notification Settings>\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 274,
        "n_words": 86,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 122,
        "n_ast_nodes": 271,
        "n_identifiers": 26,
        "d_id": 19673,
        "documentation": {
            "docstring": "\n        Test that an email AND Slack notification are sent with\n        the expected values when a comment is created on an issue.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 115450,
        "commit_id": "75686f43be1d82794e50277acefda517eced0b6c",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/ckan_handler/ckan_handler.py",
        "file_name": "ckan_handler.py",
        "fun_name": "connect",
        "commit_message": "Add CKAN Handler for MindsDB",
        "code": "def connect(self) -> HandlerStatusResponse:\n        \n        url = self.connection_args.get('url')\n        try:\n            ckan = rc(url)\n            self.is_connected = True\n            self.ckan = ckan\n        except Exception as e:\n            return HandlerStatusResponse(False, f'Failed to connect to CKAN: {e}')\n        self.connection = ckan\n        return HandlerStatusResponse(True)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 120,
        "n_words": 34,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 59,
        "n_ast_nodes": 105,
        "n_identifiers": 12,
        "d_id": 25464,
        "documentation": {
            "docstring": "\n        Handles the connection to a CKAN remote portal instance.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 144060,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/utils/spaces/space_utils.py",
        "file_name": "space_utils.py",
        "fun_name": "unbatch",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def unbatch(batches_struct):\n    \n    flat_batches = tree.flatten(batches_struct)\n\n    out = []\n    for batch_pos in range(len(flat_batches[0])):\n        out.append(\n            tree.unflatten_as(\n                batches_struct,\n                [flat_batches[i][batch_pos] for i in range(len(flat_batches))],\n            )\n        )\n    return out\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 105,
        "n_words": 24,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 66,
        "n_ast_nodes": 104,
        "n_identifiers": 12,
        "d_id": 33102,
        "documentation": {
            "docstring": "Converts input from (nested) struct of batches to batch of structs.\n\n    Input: Struct of different batches (each batch has size=3):\n        {\"a\": [1, 2, 3], \"b\": ([4, 5, 6], [7.0, 8.0, 9.0])}\n    Output: Batch (list) of structs (each of these structs representing a\n        single action):\n        [\n            {\"a\": 1, \"b\": (4, 7.0)},  <- action 1\n            {\"a\": 2, \"b\": (5, 8.0)},  <- action 2\n            {\"a\": 3, \"b\": (6, 9.0)},  <- action 3\n        ]\n\n    Args:\n        batches_struct (any): The struct of component batches. Each leaf item\n            in this struct represents the batch for a single component\n            (in case struct is tuple/dict).\n            Alternatively, `batches_struct` may also simply be a batch of\n            primitives (non tuple/dict).\n\n    Returns:\n        List[struct[components]]: The list of rows. Each item\n            in the returned list represents a single (maybe complex) struct.\n    ",
            "n_words": 126,
            "vocab_size": 85,
            "n_whitespaces": 274,
            "language": "en"
        }
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    {
        "id": 258624,
        "commit_id": "254ea8c453cd2100ade07644648f1f00392611a6",
        "repo": "scikit-learn",
        "path": "sklearn/mixture/_base.py",
        "file_name": "_base.py",
        "fun_name": "sample",
        "commit_message": "ENH Replaced RandomState with Generator compatible calls (#22271)",
        "code": "def sample(self, n_samples=1):\n        \n        check_is_fitted(self)\n\n        if n_samples < 1:\n            raise ValueError(\n                \"Invalid value for 'n_samples': %d . The sampling requires at \"\n                \"least one sample.\" % (self.n_components)\n            )\n\n        _, n_features = self.means_.shape\n        rng = check_random_state(self.random_state)\n        n_samples_comp = rng.multinomial(n_samples, self.weights_)\n\n        if self.covariance_type == \"full\":\n            X = np.vstack(\n                [\n                    rng.multivariate_normal(mean, covariance, int(sample))\n                    for (mean, covariance, sample) in zip(\n                        self.means_, self.covariances_, n_samples_comp\n                    )\n                ]\n            )\n        elif self.covariance_type == \"tied\":\n            X = np.vstack(\n                [\n                    rng.multivariate_normal(mean, self.covariances_, int(sample))\n                    for (mean, sample) in zip(self.means_, n_samples_comp)\n                ]\n            )\n        else:\n            X = np.vstack(\n                [\n                    mean\n                    + rng.standard_normal(size=(sample, n_features))\n                    * np.sqrt(covariance)\n                    for (mean, covariance, sample) in zip(\n                        self.means_, self.covariances_, n_samples_comp\n                    )\n                ]\n            )\n\n        y = np.concatenate(\n            [np.full(sample, j, dtype=int) for j, sample in enumerate(n_samples_comp)]\n        )\n\n        return (X, y)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 657,
        "n_words": 118,
        "vocab_size": 73,
        "complexity": 8,
        "nloc": 41,
        "token_counts": 245,
        "n_ast_nodes": 372,
        "n_identifiers": 35,
        "d_id": 75335,
        "documentation": {
            "docstring": "Generate random samples from the fitted Gaussian distribution.\n\n        Parameters\n        ----------\n        n_samples : int, default=1\n            Number of samples to generate.\n\n        Returns\n        -------\n        X : array, shape (n_samples, n_features)\n            Randomly generated sample.\n\n        y : array, shape (nsamples,)\n            Component labels.\n        ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 297466,
        "commit_id": "0e2ebfe5c45716250280186234123f170e3bd08c",
        "repo": "core",
        "path": "tests/components/bluetooth/test_scanner.py",
        "file_name": "test_scanner.py",
        "fun_name": "test_adapter_recovery",
        "commit_message": "Move bluetooth watchdog into the scanner base class (#83888)",
        "code": "async def test_adapter_recovery(hass, one_adapter):\n    \n\n    called_start = 0\n    called_stop = 0\n    _callback = None\n    mock_discovered = []\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 31,
        "n_words": 16,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 50,
        "token_counts": 221,
        "n_ast_nodes": 38,
        "n_identifiers": 7,
        "d_id": 96435,
        "documentation": {
            "docstring": "Test we can recover when the adapter stops responding.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 259229,
        "commit_id": "7f0006c8aad1a09621ad19c3db19c3ff0555a183",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/tests/test_encoders.py",
        "file_name": "test_encoders.py",
        "fun_name": "test_ohe_infrequent_two_levels_user_cats_one_frequent",
        "commit_message": "ENH Adds infrequent categories to OneHotEncoder (#16018)\n\n* ENH Completely adds infrequent categories\r\n\r\n* STY Linting\r\n\r\n* STY Linting\r\n\r\n* DOC Improves wording\r\n\r\n* DOC Lint\r\n\r\n* BUG Fixes\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* DOC Uses math to description float min_frequency\r\n\r\n* DOC Adds comment regarding drop\r\n\r\n* BUG Fixes method name\r\n\r\n* DOC Clearer docstring\r\n\r\n* TST Adds more tests\r\n\r\n* FIX Fixes mege\r\n\r\n* CLN More pythonic\r\n\r\n* CLN Address comments\r\n\r\n* STY Flake8\r\n\r\n* CLN Address comments\r\n\r\n* DOC Fix\r\n\r\n* MRG\r\n\r\n* WIP\r\n\r\n* ENH Address comments\r\n\r\n* STY Fix\r\n\r\n* ENH Use functiion call instead of property\r\n\r\n* ENH Adds counts feature\r\n\r\n* CLN Rename variables\r\n\r\n* DOC More details\r\n\r\n* CLN Remove unneeded line\r\n\r\n* CLN Less lines is less complicated\r\n\r\n* CLN Less diffs\r\n\r\n* CLN Improves readiabilty\r\n\r\n* BUG Fix\r\n\r\n* CLN Address comments\r\n\r\n* TST Fix\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* CLN Move docstring to userguide\r\n\r\n* DOC Better wrapping\r\n\r\n* TST Adds test to handle_unknown='error'\r\n\r\n* ENH Spelling error in docstring\r\n\r\n* BUG Fixes counter with nan values\r\n\r\n* BUG Removes unneeded test\r\n\r\n* BUG Fixes issue\r\n\r\n* ENH Sync with main\r\n\r\n* DOC Correct settings\r\n\r\n* DOC Adds docstring\r\n\r\n* DOC Immprove user guide\r\n\r\n* DOC Move to 1.0\r\n\r\n* DOC Update docs\r\n\r\n* TST Remove test\r\n\r\n* DOC Update docstring\r\n\r\n* STY Linting\r\n\r\n* DOC Address comments\r\n\r\n* ENH Neater code\r\n\r\n* DOC Update explaination for auto\r\n\r\n* Update sklearn/preprocessing/_encoders.py\r\n\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\n\r\n* TST Uses docstring instead of comments\r\n\r\n* TST Remove call to fit\r\n\r\n* TST Spelling error\r\n\r\n* ENH Adds support for drop + infrequent categories\r\n\r\n* ENH Adds infrequent_if_exist option\r\n\r\n* DOC Address comments for user guide\r\n\r\n* DOC Address comments for whats_new\r\n\r\n* DOC Update docstring based on comments\r\n\r\n* CLN Update test with suggestions\r\n\r\n* ENH Adds computed property infrequent_categories_\r\n\r\n* DOC Adds where the infrequent column is located\r\n\r\n* TST Adds more test for infrequent_categories_\r\n\r\n* DOC Adds docstring for _compute_drop_idx\r\n\r\n* CLN Moves _convert_to_infrequent_idx into its own method\r\n\r\n* TST Increases test coverage\r\n\r\n* TST Adds failing test\r\n\r\n* CLN Careful consideration of dropped and inverse_transform\r\n\r\n* STY Linting\r\n\r\n* DOC Adds docstrinb about dropping infrequent\r\n\r\n* DOC Uses only\r\n\r\n* DOC Numpydoc\r\n\r\n* TST Includes test for get_feature_names_out\r\n\r\n* DOC Move whats new\r\n\r\n* DOC Address docstring comments\r\n\r\n* DOC Docstring changes\r\n\r\n* TST Better comments\r\n\r\n* TST Adds check for handle_unknown='ignore' for infrequent\r\n\r\n* CLN Make _infrequent_indices private\r\n\r\n* CLN Change min_frequency default to None\r\n\r\n* DOC Adds comments\r\n\r\n* ENH adds support for max_categories=1\r\n\r\n* ENH Describe lexicon ordering for ties\r\n\r\n* DOC Better docstring\r\n\r\n* STY Fix\r\n\r\n* CLN Error when explicity dropping an infrequent category\r\n\r\n* STY Grammar\r\n\r\nCo-authored-by: Joel Nothman <joel.nothman@gmail.com>\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_ohe_infrequent_two_levels_user_cats_one_frequent(kwargs):\n    \n\n    X_train = np.array([[\"a\"] * 5 + [\"e\"] * 30], dtype=object).T\n    ohe = OneHotEncoder(\n        categories=[[\"c\", \"d\", \"a\", \"b\"]],\n        sparse=False,\n        handle_unknown=\"infrequent_if_exist\",\n        **kwargs,\n    ).fit(X_train)\n\n    X_test = [[\"a\"], [\"b\"], [\"c\"], [\"d\"], [\"e\"]]\n    expected = np.array([[1, 0], [0, 1], [0, 1], [0, 1], [0, 1]])\n\n    X_trans = ohe.transform(X_test)\n    assert_allclose(expected, X_trans)\n\n    # 'a' is dropped\n    drops = [\"first\", \"if_binary\", [\"a\"]]\n    X_test = [[\"a\"], [\"c\"]]\n    for drop in drops:\n        ohe.set_params(drop=drop).fit(X_train)\n        assert_allclose([[0], [1]], ohe.transform(X_test))\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 146,
        "n_words": 68,
        "vocab_size": 54,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 201,
        "n_ast_nodes": 324,
        "n_identifiers": 22,
        "d_id": 75663,
        "documentation": {
            "docstring": "'a' is the only frequent category, all other categories are infrequent.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 25599,
        "commit_id": "c052f59016d82568a675e2c202ea1363f9e355ff",
        "repo": "saleor",
        "path": "saleor/warehouse/tests/test_stock_management.py",
        "file_name": "test_stock_management.py",
        "fun_name": "test_decrease_stock_multiple_lines_deallocate_stock_raises_error",
        "commit_message": "Fix incorrect stock allocation (#8963)\n\n* Fix incorrect stock allocation\r\n\r\n* Drop unused restock_order_lines order utils",
        "code": "def test_decrease_stock_multiple_lines_deallocate_stock_raises_error(order_with_lines):\n    \n\n    # given\n    order_line_1 = order_with_lines.lines.first()\n    order_line_2 = order_with_lines.lines.last()\n\n    allocation_1 = order_line_1.allocations.first()\n    allocation_2 = order_line_2.allocations.first()\n\n    stock_quantity = 100\n    allocation_1_qty_allocated = 10\n    allocation_2_qty_allocated = 80\n\n    stock_1 = allocation_1.stock\n    stock_2 = allocation_2.stock\n    stock_1.quantity = stock_quantity\n    stock_2.quantity = stock_quantity\n    Stock.objects.bulk_update([stock_1, stock_2], [\"quantity\"])\n\n    allocation_1.quantity_allocated = allocation_1_qty_allocated\n    allocation_1.order_line = order_line_1\n    warehouse_pk_1 = stock_1.warehouse.pk\n\n    allocation_2.quantity_allocated = allocation_2_qty_allocated\n    allocation_2.order_line = order_line_2\n    warehouse_pk_2 = stock_2.warehouse.pk\n\n    Allocation.objects.bulk_update(\n        [allocation_1, allocation_2], [\"quantity_allocated\", \"order_line\"]\n    )\n\n    line_1_qty = 50\n    line_2_qty = 20\n\n    # when\n    decrease_stock(\n        [\n            OrderLineInfo(\n                line=order_line_1,\n                quantity=line_1_qty,\n                variant=order_line_1.variant,\n                warehouse_pk=warehouse_pk_1,\n            ),\n            OrderLineInfo(\n                line=order_line_2,\n                quantity=line_2_qty,\n                variant=order_line_2.variant,\n                warehouse_pk=warehouse_pk_2,\n            ),\n        ],\n        manager=get_plugins_manager(),\n    )\n\n    # then\n    stock_1.refresh_from_db()\n    assert stock_1.quantity == stock_quantity - line_1_qty\n\n    stock_2.refresh_from_db()\n    assert stock_2.quantity == stock_quantity - line_2_qty\n\n    allocation_1.refresh_from_db()\n    assert allocation_1.quantity_allocated == 0\n\n    allocation_2.refresh_from_db()\n    assert allocation_2.quantity_allocated == allocation_2_qty_allocated - line_2_qty\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 417,
        "n_words": 117,
        "vocab_size": 70,
        "complexity": 1,
        "nloc": 49,
        "token_counts": 251,
        "n_ast_nodes": 399,
        "n_identifiers": 37,
        "d_id": 4910,
        "documentation": {
            "docstring": "Ensure that when some of the lines raise an error during the deallocation\n    quantity allocated value for all allocation will be updated.",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 267135,
        "commit_id": "b439e41a915ccec0ccbabecc966919ea406db74e",
        "repo": "ansible",
        "path": "lib/ansible/galaxy/collection/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "verify_local_collection",
        "commit_message": "expand ansible-doc coverage (#74963)\n\n* Expand ansible-doc to tests/filters and fix existing issues\r\n\r\n  enable filter/test docs if in single file or companion yaml\r\n  add docs for several filters/tests plugins\r\n  allow .yml companion for docs for other plugins, must be colocated\r\n  verify plugins are valid (not modules, cannot)\r\n  fix 'per collection' filtering\r\n  limit old style deprecation (_ prefix) to builtin/legacy\r\n  start move to pathlib for saner path handling\r\n  moved some funcitons, kept backwards compat shims with deprecation notice\r\n\r\n  Co-authored-by: Abhijeet Kasurde <akasurde@redhat.com>\r\n  Co-authored-by: Felix Fontein <felix@fontein.de>\r\n  Co-authored-by: Sandra McCann <samccann@redhat.com>",
        "code": "def verify_local_collection(local_collection, remote_collection, artifacts_manager):\n    # type: (Candidate, Candidate | None, ConcreteArtifactsManager) -> CollectionVerifyResult\n    \n    result = CollectionVerifyResult(local_collection.fqcn)\n\n    b_collection_path = to_bytes(local_collection.src, errors='surrogate_or_strict')\n\n    display.display(\"Verifying '{coll!s}'.\".format(coll=local_collection))\n    display.display(\n        u\"Installed collection found at '{path!s}'\".\n        format(path=to_text(local_collection.src)),\n    )\n\n    modified_content = []  # type: list[ModifiedContent]\n\n    verify_local_only = remote_collection is None\n\n    # partial away the local FS detail so we can just ask generically during validation\n    get_json_from_validation_source = functools.partial(_get_json_from_installed_dir, b_collection_path)\n    get_hash_from_validation_source = functools.partial(_get_file_hash, b_collection_path)\n\n    if not verify_local_only:\n        # Compare installed version versus requirement version\n        if local_collection.ver != remote_collection.ver:\n            err = (\n                \"{local_fqcn!s} has the version '{local_ver!s}' but \"\n                \"is being compared to '{remote_ver!s}'\".format(\n                    local_fqcn=local_collection.fqcn,\n                    local_ver=local_collection.ver,\n                    remote_ver=remote_collection.ver,\n                )\n            )\n            display.display(err)\n            result.success = False\n            return result\n\n    manifest_file = os.path.join(to_text(b_collection_path, errors='surrogate_or_strict'), MANIFEST_FILENAME)\n    signatures = list(local_collection.signatures)\n    if verify_local_only and local_collection.source_info is not None:\n        signatures = [info[\"signature\"] for info in local_collection.source_info[\"signatures\"]] + signatures\n    elif not verify_local_only and remote_collection.signatures:\n        signatures = list(remote_collection.signatures) + signatures\n\n    keyring_configured = artifacts_manager.keyring is not None\n    if not keyring_configured and signatures:\n        display.warning(\n            \"The GnuPG keyring used for collection signature \"\n            \"verification was not configured but signatures were \"\n            \"provided by the Galaxy server. \"\n            \"Configure a keyring for ansible-galaxy to verify \"\n            \"the origin of the collection. \"\n            \"Skipping signature verification.\"\n        )\n    elif keyring_configured:\n        if not verify_file_signatures(\n            local_collection.fqcn,\n            manifest_file,\n            signatures,\n            artifacts_manager.keyring,\n            artifacts_manager.required_successful_signature_count,\n            artifacts_manager.ignore_signature_errors,\n        ):\n            result.success = False\n            return result\n        display.vvvv(f\"GnuPG signature verification succeeded, verifying contents of {local_collection}\")\n\n    if verify_local_only:\n        # since we're not downloading this, just seed it with the value from disk\n        manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME)\n    elif keyring_configured and remote_collection.signatures:\n        manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME)\n    else:\n        # fetch remote\n        b_temp_tar_path = (  # NOTE: AnsibleError is raised on URLError\n            artifacts_manager.get_artifact_path\n            if remote_collection.is_concrete_artifact\n            else artifacts_manager.get_galaxy_artifact_path\n        )(remote_collection)\n\n        display.vvv(\n            u\"Remote collection cached as '{path!s}'\".format(path=to_text(b_temp_tar_path))\n        )\n\n        # partial away the tarball details so we can just ask generically during validation\n        get_json_from_validation_source = functools.partial(_get_json_from_tar_file, b_temp_tar_path)\n        get_hash_from_validation_source = functools.partial(_get_tar_file_hash, b_temp_tar_path)\n\n        # Verify the downloaded manifest hash matches the installed copy before verifying the file manifest\n        manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME)\n        _verify_file_hash(b_collection_path, MANIFEST_FILENAME, manifest_hash, modified_content)\n\n    display.display('MANIFEST.json hash: {manifest_hash}'.format(manifest_hash=manifest_hash))\n\n    manifest = get_json_from_validation_source(MANIFEST_FILENAME)\n\n    # Use the manifest to verify the file manifest checksum\n    file_manifest_data = manifest['file_manifest_file']\n    file_manifest_filename = file_manifest_data['name']\n    expected_hash = file_manifest_data['chksum_%s' % file_manifest_data['chksum_type']]\n\n    # Verify the file manifest before using it to verify individual files\n    _verify_file_hash(b_collection_path, file_manifest_filename, expected_hash, modified_content)\n    file_manifest = get_json_from_validation_source(file_manifest_filename)\n\n    collection_dirs = set()\n    collection_files = {\n        os.path.join(b_collection_path, b'MANIFEST.json'),\n        os.path.join(b_collection_path, b'FILES.json'),\n    }\n\n    # Use the file manifest to verify individual file checksums\n    for manifest_data in file_manifest['files']:\n        name = manifest_data['name']\n\n        if manifest_data['ftype'] == 'file':\n            collection_files.add(\n                os.path.join(b_collection_path, to_bytes(name, errors='surrogate_or_strict'))\n            )\n            expected_hash = manifest_data['chksum_%s' % manifest_data['chksum_type']]\n            _verify_file_hash(b_collection_path, name, expected_hash, modified_content)\n\n        if manifest_data['ftype'] == 'dir':\n            collection_dirs.add(\n                os.path.join(b_collection_path, to_bytes(name, errors='surrogate_or_strict'))\n            )\n\n    # Find any paths not in the FILES.json\n    for root, dirs, files in os.walk(b_collection_path):\n        for name in files:\n            full_path = os.path.join(root, name)\n            path = to_text(full_path[len(b_collection_path) + 1::], errors='surrogate_or_strict')\n\n            if full_path not in collection_files:\n                modified_content.append(\n                    ModifiedContent(filename=path, expected='the file does not exist', installed='the file exists')\n                )\n        for name in dirs:\n            full_path = os.path.join(root, name)\n            path = to_text(full_path[len(b_collection_path) + 1::], errors='surrogate_or_strict')\n\n            if full_path not in collection_dirs:\n                modified_content.append(\n                    ModifiedContent(filename=path, expected='the directory does not exist', installed='the directory exists')\n                )\n\n    if modified_content:\n        result.success = False\n        display.display(\n            'Collection {fqcn!s} contains modified content '\n            'in the following files:'.\n            format(fqcn=to_text(local_collection.fqcn)),\n        )\n        for content_change in modified_content:\n            display.display('    %s' % content_change.filename)\n            display.v(\"    Expected: %s\\n    Found: %s\" % (content_change.expected, content_change.installed))\n    else:\n        what = \"are internally consistent with its manifest\" if verify_local_only else \"match the remote collection\"\n        display.display(\n            \"Successfully verified that checksums for '{coll!s}' {what!s}.\".\n            format(coll=local_collection, what=what),\n        )\n\n    return result\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 1652,
        "n_words": 550,
        "vocab_size": 300,
        "complexity": 27,
        "nloc": 126,
        "token_counts": 793,
        "n_ast_nodes": 1307,
        "n_identifiers": 79,
        "d_id": 78753,
        "documentation": {
            "docstring": "Verify integrity of the locally installed collection.\n\n    :param local_collection: Collection being checked.\n    :param remote_collection: Upstream collection (optional, if None, only verify local artifact)\n    :param artifacts_manager: Artifacts manager.\n    :return: a collection verify result object.\n    ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 218888,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/lib2to3/refactor.py",
        "file_name": "refactor.py",
        "fun_name": "traverse_by",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def traverse_by(self, fixers, traversal):\n        \n        if not fixers:\n            return\n        for node in traversal:\n            for fixer in fixers[node.type]:\n                results = fixer.match(node)\n                if results:\n                    new = fixer.transform(node, results)\n                    if new is not None:\n                        node.replace(new)\n                        node = new\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 191,
        "n_words": 34,
        "vocab_size": 24,
        "complexity": 6,
        "nloc": 11,
        "token_counts": 66,
        "n_ast_nodes": 104,
        "n_identifiers": 12,
        "d_id": 55531,
        "documentation": {
            "docstring": "Traverse an AST, applying a set of fixers to each node.\n\n        This is a helper method for refactor_tree().\n\n        Args:\n            fixers: a list of fixer instances.\n            traversal: a generator that yields AST nodes.\n\n        Returns:\n            None\n        ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 129737,
        "commit_id": "8ebc50f844f42e283f125792d630ea6d0a2a7000",
        "repo": "ray",
        "path": "rllib/agents/ppo/tests/test_appo.py",
        "file_name": "test_appo.py",
        "fun_name": "test_appo_compilation_use_kl_loss",
        "commit_message": "[RLlib] Issue 21334: Fix APPO when kl_loss is enabled. (#21855)",
        "code": "def test_appo_compilation_use_kl_loss(self):\n        \n        config = ppo.appo.DEFAULT_CONFIG.copy()\n        config[\"num_workers\"] = 1\n        config[\"use_kl_loss\"] = True\n        num_iterations = 2\n\n        for _ in framework_iterator(config, with_eager_tracing=True):\n            trainer = ppo.APPOTrainer(config=config, env=\"CartPole-v0\")\n            for i in range(num_iterations):\n                results = trainer.train()\n                check_train_results(results)\n                print(results)\n            check_compute_single_action(trainer)\n            trainer.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 165,
        "n_words": 34,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 90,
        "n_ast_nodes": 152,
        "n_identifiers": 22,
        "d_id": 29010,
        "documentation": {
            "docstring": "Test whether an APPOTrainer can be built with kl_loss enabled.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 13243,
        "commit_id": "107631e955b21db8a4ddb3bee02130de3650d032",
        "repo": "jina",
        "path": "jina/serve/instrumentation/_aio_client.py",
        "file_name": "_aio_client.py",
        "fun_name": "intercept_unary_unary",
        "commit_message": "feat(instrumentation): add OpenTelemetry tracing and metrics with basic configurations (#5175)",
        "code": "async def intercept_unary_unary(self, continuation, client_call_details, request):\n        \n\n        if context.get_value(_SUPPRESS_INSTRUMENTATION_KEY):\n            return await continuation(client_call_details, request)\n\n        method = client_call_details.method.decode(\"utf-8\")\n        with self._start_span(\n            method,\n            end_on_exit=False,\n            record_exception=False,\n            set_status_on_exception=False,\n        ) as span:\n            new_details = self.propagate_trace_in_details(client_call_details)\n\n            continuation_with_args = functools.partial(\n                continuation, new_details, request\n            )\n            return await self._wrap_unary_response(continuation_with_args, span)\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 187,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 91,
        "n_ast_nodes": 143,
        "n_identifiers": 21,
        "d_id": 2579,
        "documentation": {
            "docstring": "Intercepts a unary-unary invocation asynchronously.\n\n        :param continuation: A coroutine that proceeds with the invocation by executing\n            the next interceptor in the chain or invoking the actual RPC on the\n            underlying Channel. It is the interceptor's responsibility to call it if\n            it decides to move the RPC forward.  The interceptor can use\n            `call = await continuation(client_call_details, request)` to continue with\n            the RPC. `continuation` returns the call to the RPC.\n        :param client_call_details: A ClientCallDetails object describing the outgoing RPC.\n        :param request: The request value for the RPC.\n\n        :returns: An object with the RPC response.\n\n        :raises: AioRpcError: Indicating that the RPC terminated with non-OK status.\n        :raises: asyncio.CancelledError: Indicating that the RPC was canceled.\n        ",
            "n_words": 110,
            "vocab_size": 70,
            "n_whitespaces": 215,
            "language": "en"
        }
    },
    {
        "id": 206016,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/utils.py",
        "file_name": "utils.py",
        "fun_name": "from_current_timezone",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def from_current_timezone(value):\n    \n    if settings.USE_TZ and value is not None and timezone.is_naive(value):\n        current_timezone = timezone.get_current_timezone()\n        try:\n            if not timezone._is_pytz_zone(\n                current_timezone\n            ) and timezone._datetime_ambiguous_or_imaginary(value, current_timezone):\n                raise ValueError(\"Ambiguous or non-existent time.\")\n            return timezone.make_aware(value, current_timezone)\n        except Exception as exc:\n            raise ValidationError(\n                _(\n                    \"%(datetime)s couldn’t be interpreted \"\n                    \"in time zone %(current_timezone)s; it \"\n                    \"may be ambiguous or it may not exist.\"\n                ),\n                code=\"ambiguous_timezone\",\n                params={\"datetime\": value, \"current_timezone\": current_timezone},\n            ) from exc\n    return value\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 300,
        "n_words": 68,
        "vocab_size": 54,
        "complexity": 7,
        "nloc": 20,
        "token_counts": 100,
        "n_ast_nodes": 170,
        "n_identifiers": 18,
        "d_id": 51326,
        "documentation": {
            "docstring": "\n    When time zone support is enabled, convert naive datetimes\n    entered in the current time zone to aware datetimes.\n    ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 248680,
        "commit_id": "6ad012ef89c966cbb3616c1be63d964db48d49ca",
        "repo": "synapse",
        "path": "synapse/logging/scopecontextmanager.py",
        "file_name": "scopecontextmanager.py",
        "fun_name": "active",
        "commit_message": "More type hints for `synapse.logging` (#13103)\n\nCompletes type hints for synapse.logging.scopecontextmanager and (partially)\r\nfor synapse.logging.opentracing.",
        "code": "def active(self) -> Optional[Scope]:\n        \n        ctx = current_context()\n        return ctx.scope\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 20,
        "n_ast_nodes": 35,
        "n_identifiers": 7,
        "d_id": 72415,
        "documentation": {
            "docstring": "\n        Returns the currently active Scope which can be used to access the\n        currently active Scope.span.\n        If there is a non-null Scope, its wrapped Span\n        becomes an implicit parent of any newly-created Span at\n        Tracer.start_active_span() time.\n\n        Return:\n            The Scope that is active, or None if not available.\n        ",
            "n_words": 46,
            "vocab_size": 40,
            "n_whitespaces": 107,
            "language": "en"
        }
    },
    {
        "id": 165949,
        "commit_id": "5531195f6f0d87817a704b288008809a3c98a304",
        "repo": "pandas",
        "path": "pandas/core/indexes/accessors.py",
        "file_name": "accessors.py",
        "fun_name": "isocalendar",
        "commit_message": "fix-ci-isocalendar (#46690)",
        "code": "def isocalendar(self):\n        \n        return self._get_values().isocalendar().set_index(self._parent.index)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 18,
        "n_words": 4,
        "vocab_size": 4,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 44,
        "n_identifiers": 6,
        "d_id": 39746,
        "documentation": {
            "docstring": "\n        Calculate year, week, and day according to the ISO 8601 standard.\n\n        .. versionadded:: 1.1.0\n\n        Returns\n        -------\n        DataFrame\n            With columns year, week and day.\n\n        See Also\n        --------\n        Timestamp.isocalendar : Function return a 3-tuple containing ISO year,\n            week number, and weekday for the given Timestamp object.\n        datetime.date.isocalendar : Return a named tuple object with\n            three components: year, week and weekday.\n\n        Examples\n        --------\n        >>> ser = pd.to_datetime(pd.Series([\"2010-01-01\", pd.NaT]))\n        >>> ser.dt.isocalendar()\n           year  week  day\n        0  2009    53     5\n        1  <NA>  <NA>  <NA>\n        >>> ser.dt.isocalendar().week\n        0      53\n        1    <NA>\n        Name: week, dtype: UInt32\n        ",
            "n_words": 88,
            "vocab_size": 64,
            "n_whitespaces": 293,
            "language": "en"
        }
    },
    {
        "id": 73874,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "update",
        "commit_message": "Reformat with black",
        "code": "def update(self, user=None, next_task=None):\n        \n        if self.status != self.STATUS_IN_PROGRESS:\n            # Updating a completed or cancelled workflow should have no effect\n            return\n        try:\n            current_status = self.current_task_state.status\n        except AttributeError:\n            current_status = None\n        if current_status == TaskState.STATUS_REJECTED:\n            self.status = self.STATUS_NEEDS_CHANGES\n            self.save()\n            workflow_rejected.send(sender=self.__class__, instance=self, user=user)\n        else:\n            if not next_task:\n                next_task = self.get_next_task()\n            if next_task:\n                if (\n                    (not self.current_task_state)\n                    or self.current_task_state.status\n                    != self.current_task_state.STATUS_IN_PROGRESS\n                ):\n                    # if not on a task, or the next task to move to is not the current task (ie current task's status is\n                    # not STATUS_IN_PROGRESS), move to the next task\n                    self.current_task_state = next_task.specific.start(self, user=user)\n                    self.save()\n                    # if task has auto-approved, update the workflow again\n                    if (\n                        self.current_task_state.status\n                        != self.current_task_state.STATUS_IN_PROGRESS\n                    ):\n                        self.update(user=user)\n                # otherwise, continue on the current task\n            else:\n                # if there is no uncompleted task, finish the workflow.\n                self.finish(user=user)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 630,
        "n_words": 129,
        "vocab_size": 71,
        "complexity": 9,
        "nloc": 29,
        "token_counts": 168,
        "n_ast_nodes": 275,
        "n_identifiers": 22,
        "d_id": 16154,
        "documentation": {
            "docstring": "Checks the status of the current task, and progresses (or ends) the workflow if appropriate. If the workflow progresses,\n        next_task will be used to start a specific task next if provided.",
            "n_words": 31,
            "vocab_size": 26,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 218598,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/lib2to3/fixer_base.py",
        "file_name": "fixer_base.py",
        "fun_name": "new_name",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def new_name(self, template=\"xxx_todo_changeme\"):\n        \n        name = template\n        while name in self.used_names:\n            name = template + str(next(self.numbers))\n        self.used_names.add(name)\n        return name\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 64,
        "n_words": 18,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 73,
        "n_identifiers": 9,
        "d_id": 55411,
        "documentation": {
            "docstring": "Return a string suitable for use as an identifier\n\n        The new name is guaranteed not to conflict with other identifiers.\n        ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 242323,
        "commit_id": "601c9d8515dba996af3f0b96d1a671619de37f10",
        "repo": "Pillow",
        "path": "src/PIL/JpegImagePlugin.py",
        "file_name": "JpegImagePlugin.py",
        "fun_name": "getxmp",
        "commit_message": "Fix return in docs",
        "code": "def getxmp(self):\n        \n\n        for segment, content in self.applist:\n            if segment == \"APP1\":\n                marker, xmp_tags = content.rsplit(b\"\\x00\", 1)\n                if marker == b\"http://ns.adobe.com/xap/1.0/\":\n                    return self._getxmp(xmp_tags)\n        return {}\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 105,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 49,
        "n_ast_nodes": 83,
        "n_identifiers": 9,
        "d_id": 69830,
        "documentation": {
            "docstring": "\n        Returns a dictionary containing the XMP tags.\n        Requires defusedxml to be installed.\n\n        :returns: XMP tags in a dictionary.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 205739,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "alias",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def alias(self, *args, **kwargs):\n        \n        self._not_support_combined_queries(\"alias\")\n        return self._annotate(args, kwargs, select=False)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 51,
        "n_identifiers": 7,
        "d_id": 51184,
        "documentation": {
            "docstring": "\n        Return a query set with added aliases for extra data or aggregations.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 154575,
        "commit_id": "e5b1888cd932909e49194d58035da34b210b91c4",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py",
        "file_name": "dataframe.py",
        "fun_name": "agg",
        "commit_message": "FEAT-#4946: Replace OmniSci with HDK (#4947)\n\nCo-authored-by: Iaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Andrey Pavlenko <andrey.a.pavlenko@gmail.com>",
        "code": "def agg(self, agg):\n        \n        assert isinstance(agg, str)\n\n        agg_exprs = OrderedDict()\n        for col in self.columns:\n            agg_exprs[col] = AggregateExpr(agg, self.ref(col))\n\n        return self.__constructor__(\n            columns=self.columns,\n            dtypes=self._dtypes_for_exprs(agg_exprs),\n            op=GroupbyAggNode(self, [], agg_exprs, {\"sort\": False}),\n            index_cols=None,\n            force_execution_mode=self._force_execution_mode,\n        )\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 137,
        "n_words": 29,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 92,
        "n_ast_nodes": 138,
        "n_identifiers": 18,
        "d_id": 36085,
        "documentation": {
            "docstring": "\n        Perform specified aggregation along columns.\n\n        Parameters\n        ----------\n        agg : str\n            Name of the aggregation function to perform.\n\n        Returns\n        -------\n        HdkOnNativeDataframe\n            New frame containing the result of aggregation.\n        ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 259120,
        "commit_id": "279388d9ed2ea83194dd45a2d78161be30b43aa7",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/_polynomial.py",
        "file_name": "_polynomial.py",
        "fun_name": "get_feature_names_out",
        "commit_message": "DOC Improve get_feature_names_out docstrings (#22718)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def get_feature_names_out(self, input_features=None):\n        \n        powers = self.powers_\n        input_features = _check_feature_names_in(self, input_features)\n        feature_names = []\n        for row in powers:\n            inds = np.where(row)[0]\n            if len(inds):\n                name = \" \".join(\n                    \"%s^%d\" % (input_features[ind], exp)\n                    if exp != 1\n                    else input_features[ind]\n                    for ind, exp in zip(inds, row[inds])\n                )\n            else:\n                name = \"1\"\n            feature_names.append(name)\n        return np.asarray(feature_names, dtype=object)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 258,
        "n_words": 51,
        "vocab_size": 41,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 111,
        "n_ast_nodes": 176,
        "n_identifiers": 21,
        "d_id": 75579,
        "documentation": {
            "docstring": "Get output feature names for transformation.\n\n        Parameters\n        ----------\n        input_features : array-like of str or None, default=None\n            Input features.\n\n            - If `input_features is None`, then `feature_names_in_` is\n              used as feature names in. If `feature_names_in_` is not defined,\n              then the following input feature names are generated:\n              `[\"x0\", \"x1\", ..., \"x(n_features_in_ - 1)\"]`.\n            - If `input_features` is an array-like, then `input_features` must\n              match `feature_names_in_` if `feature_names_in_` is defined.\n\n        Returns\n        -------\n        feature_names_out : ndarray of str objects\n            Transformed feature names.\n        ",
            "n_words": 76,
            "vocab_size": 54,
            "n_whitespaces": 221,
            "language": "en"
        }
    },
    {
        "id": 186581,
        "commit_id": "16aad35d31a887dab157f9d4f5e0fe9218d06064",
        "repo": "certbot",
        "path": "certbot-nginx/certbot_nginx/_internal/configurator.py",
        "file_name": "configurator.py",
        "fun_name": "revert_challenge_config",
        "commit_message": "Fully type certbot-nginx module (#9124)\n\n* Work in progress\r\n\r\n* Fix type\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Oups.\r\n\r\n* Fix typing in UnspacedList\r\n\r\n* Fix logic\r\n\r\n* Finish typing\r\n\r\n* List certbot-nginx as fully typed in tox\r\n\r\n* Fix lint\r\n\r\n* Fix checks\r\n\r\n* Organize imports\r\n\r\n* Fix typing for Python 3.6\r\n\r\n* Fix checks\r\n\r\n* Fix lint\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/configurator.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/configurator.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Fix signature of deploy_cert regarding the installer interface\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/obj.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Fix types\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/parser.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Precise type\r\n\r\n* Precise _coerce possible inputs/outputs\r\n\r\n* Fix type\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/http_01.py\r\n\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>\r\n\r\n* Fix type\r\n\r\n* Remove an undesirable implementation.\r\n\r\n* Fix type\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>",
        "code": "def revert_challenge_config(self) -> None:\n        \n        self.revert_temporary_config()\n        self.new_vhost = None\n        self.parser.load()\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 37,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 25,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 45497,
        "documentation": {
            "docstring": "Used to cleanup challenge configurations.\n\n        :raises .errors.PluginError: If unable to revert the challenge config.\n\n        ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 66842,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v13_0/updates_for_multi_currency_payroll.py",
        "file_name": "updates_for_multi_currency_payroll.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\n\tfrappe.reload_doc(\"Accounts\", \"doctype\", \"Salary Component Account\")\n\tif frappe.db.has_column(\"Salary Component Account\", \"default_account\"):\n\t\trename_field(\"Salary Component Account\", \"default_account\", \"account\")\n\n\tdoctype_list = [\n\t\t{\"module\": \"HR\", \"doctype\": \"Employee Advance\"},\n\t\t{\"module\": \"HR\", \"doctype\": \"Leave Encashment\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Additional Salary\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Employee Benefit Application\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Employee Benefit Claim\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Employee Incentive\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Employee Tax Exemption Declaration\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Employee Tax Exemption Proof Submission\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Income Tax Slab\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Payroll Entry\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Retention Bonus\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Salary Structure\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Salary Structure Assignment\"},\n\t\t{\"module\": \"Payroll\", \"doctype\": \"Salary Slip\"},\n\t]\n\n\tfor item in doctype_list:\n\t\tfrappe.reload_doc(item[\"module\"], \"doctype\", item[\"doctype\"])\n\n\t# update company in employee advance based on employee company\n\tfor dt in [\n\t\t\"Employee Incentive\",\n\t\t\"Leave Encashment\",\n\t\t\"Employee Benefit Application\",\n\t\t\"Employee Benefit Claim\",\n\t]:\n\t\tfrappe.db.sql(\n\t\t\t.format(\n\t\t\t\tdoctype=dt\n\t\t\t)\n\t\t)\n\n\t# update exchange rate for employee advance\n\tfrappe.db.sql(\"update `tabEmployee Advance` set exchange_rate=1\")\n\n\t# get all companies and it's currency\n\tall_companies = frappe.db.get_all(\n\t\t\"Company\", fields=[\"name\", \"default_currency\", \"default_payroll_payable_account\"]\n\t)\n\tfor d in all_companies:\n\t\tcompany = d.name\n\t\tcompany_currency = d.default_currency\n\t\tdefault_payroll_payable_account = d.default_payroll_payable_account\n\n\t\tif not default_payroll_payable_account:\n\t\t\tdefault_payroll_payable_account = frappe.db.get_value(\n\t\t\t\t\"Account\",\n\t\t\t\t{\n\t\t\t\t\t\"account_name\": _(\"Payroll Payable\"),\n\t\t\t\t\t\"company\": company,\n\t\t\t\t\t\"account_currency\": company_currency,\n\t\t\t\t\t\"is_group\": 0,\n\t\t\t\t},\n\t\t\t)\n\n\t\t# update currency in following doctypes based on company currency\n\t\tdoctypes_for_currency = [\n\t\t\t\"Employee Advance\",\n\t\t\t\"Leave Encashment\",\n\t\t\t\"Employee Benefit Application\",\n\t\t\t\"Employee Benefit Claim\",\n\t\t\t\"Employee Incentive\",\n\t\t\t\"Additional Salary\",\n\t\t\t\"Employee Tax Exemption Declaration\",\n\t\t\t\"Employee Tax Exemption Proof Submission\",\n\t\t\t\"Income Tax Slab\",\n\t\t\t\"Retention Bonus\",\n\t\t\t\"Salary Structure\",\n\t\t]\n\n\t\tfor dt in doctypes_for_currency:\n\t\t\tfrappe.db.sql(\n\t\t\t\t.format(doctype=dt),\n\t\t\t\t(company_currency, company),\n\t\t\t)\n\n\t\t# update fields in payroll entry\n\t\tfrappe.db.sql(\n\t\t\t,\n\t\t\t(company_currency, default_payroll_payable_account, company),\n\t\t)\n\n\t\t# update fields in Salary Structure Assignment\n\t\tfrappe.db.sql(\n\t\t\t,\n\t\t\t(company_currency, default_payroll_payable_account, company),\n\t\t)\n\n\t\t# update fields in Salary Slip\n\t\tfrappe.db.sql(\n\t\t\t,\n\t\t\t(company_currency, company),\n\t\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 197,
        "n_words": 285,
        "vocab_size": 133,
        "complexity": 7,
        "nloc": 106,
        "token_counts": 415,
        "n_ast_nodes": 773,
        "n_identifiers": 24,
        "d_id": 14360,
        "documentation": {
            "docstring": "\n\t\t\tupdate `tab{doctype}`\n\t\t\tset company = (select company from tabEmployee where name=`tab{doctype}`.employee)\n\t\tupdate `tab{doctype}` set currency = %s where company=%s\n\t\t\tupdate `tabPayroll Entry`\n\t\t\tset currency = %s,\n\t\t\t\texchange_rate = 1,\n\t\t\t\tpayroll_payable_account=%s\n\t\t\twhere company=%s\n\t\t\n\t\t\tupdate `tabSalary Structure Assignment`\n\t\t\tset currency = %s,\n\t\t\t\tpayroll_payable_account=%s\n\t\t\twhere company=%s\n\t\t\n\t\t\tupdate `tabSalary Slip`\n\t\t\tset currency = %s,\n\t\t\t\texchange_rate = 1,\n\t\t\t\tbase_hour_rate = hour_rate,\n\t\t\t\tbase_gross_pay = gross_pay,\n\t\t\t\tbase_total_deduction = total_deduction,\n\t\t\t\tbase_net_pay = net_pay,\n\t\t\t\tbase_rounded_total = rounded_total,\n\t\t\t\tbase_total_in_words = total_in_words\n\t\t\twhere company=%s\n\t\t",
            "n_words": 73,
            "vocab_size": 35,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 263831,
        "commit_id": "684bfac8adcf254fec5777f212c13eb62181f900",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/gi.py",
        "file_name": "gi.py",
        "fun_name": "get_libdir",
        "commit_message": "hooks: refactor GObject introspection (gi) hooks\n\nThe modules imported from gi.repository are marked as runtime\nmodules by their corresponding pre-safe-import-module hooks.\nTherefore, their standard hooks are always loaded and executed,\nregardless of whether the modue is actually importable or not.\n\nIn PyInstaller v5, this behavior triggers errors in hooks for\nGI modules that are not importable, because the new `isolated`\nframework propagates the errors instead of swallowing them.\nWhile these errors could be caught and demoted to warnings\nto match the old behavior, it would be better hooks checked\nwhether module is importable before doing any processing\nat all.\n\nTo that end, we introduce new class, `GiModuleInfo` that,\nas part of its initialization, allows us to:\n - perform availability check\n - obtain data previously returned by `get_gi_typelibs`\n - obtain data previously returned by `get_gi_libdir`\nusing a single isolated import attempt (instead of one\nbeing performed in each of those steps).\n\nIn  addition, if passed `hook_api` as an optional argument,\nthe `GiModuleInfo` can use hook configuration API to override\nthe GI module version to be collected (which allows the\nstandard use pattern to be removed from the hook itself).\n\nThe old `get_gi_typelibs` and `get_gi_libdir` functions\nnow internally use `GiModuleInfo` to provide backward\ncompatible behavior to (potential) exetnal user.\n\nAll `gi` hooks are ported to the `GiModuleInfo` and now\nbecome no-op if the module is not available.\n\nIn addition, hooks are cleaned up/refactored so that all\nprocessing is performed either in the loading stage (\"simple\"\nhooks that do not require access to hook configuration API)\nor in the `hook()` function (hooks that require access to\nhook configuration API), but not in the mixture of the two.",
        "code": "def get_libdir(self):\n        \n        # Module unavailable\n        if not self.available:\n            raise ValueError(f\"Module {self.name} {self.version} is unavailable!\")\n        # Module has no associated shared libraries\n        if not self.sharedlibs:\n            return None\n        for lib in self.sharedlibs:\n            path = findSystemLibrary(lib)\n            if path:\n                return os.path.normpath(os.path.dirname(path))\n        raise ValueError(f\"Could not resolve any shared library of {self.name} {self.version}: {self.sharedlibs}!\")\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 156,
        "n_words": 48,
        "vocab_size": 37,
        "complexity": 5,
        "nloc": 10,
        "token_counts": 64,
        "n_ast_nodes": 143,
        "n_identifiers": 13,
        "d_id": 77455,
        "documentation": {
            "docstring": "\n        Return the path to shared library used by the module. If no libraries are associated with the typelib, None is\n        returned. If multiple library names are associated with the typelib, the path to the first resolved shared\n        library is returned. Raises exception if module is unavailable or none of the shared libraries could be\n        resolved.\n        ",
            "n_words": 55,
            "vocab_size": 34,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 222511,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/difflib.py",
        "file_name": "difflib.py",
        "fun_name": "ratio",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def ratio(self):\n        \n\n        matches = sum(triple[-1] for triple in self.get_matching_blocks())\n        return _calculate_ratio(matches, len(self.a) + len(self.b))\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 43,
        "n_ast_nodes": 70,
        "n_identifiers": 10,
        "d_id": 56607,
        "documentation": {
            "docstring": "Return a measure of the sequences' similarity (float in [0,1]).\n\n        Where T is the total number of elements in both sequences, and\n        M is the number of matches, this is 2.0*M / T.\n        Note that this is 1 if the sequences are identical, and 0 if\n        they have nothing in common.\n\n        .ratio() is expensive to compute if you haven't already computed\n        .get_matching_blocks() or .get_opcodes(), in which case you may\n        want to try .quick_ratio() or .real_quick_ratio() first to get an\n        upper bound.\n\n        >>> s = SequenceMatcher(None, \"abcd\", \"bcde\")\n        >>> s.ratio()\n        0.75\n        >>> s.quick_ratio()\n        0.75\n        >>> s.real_quick_ratio()\n        1.0\n        ",
            "n_words": 96,
            "vocab_size": 71,
            "n_whitespaces": 208,
            "language": "en"
        }
    },
    {
        "id": 198995,
        "commit_id": "041eeb41b6a083dd106a0e6316d6f07e2248cd61",
        "repo": "sympy",
        "path": "sympy/polys/matrices/linsolve.py",
        "file_name": "linsolve.py",
        "fun_name": "_linear_eq_to_dict_inner",
        "commit_message": "linear_coeffs has nonstrict option",
        "code": "def _linear_eq_to_dict_inner(eqs, syms):\n    \n    syms = set(syms)\n    eqsdict, ind = [], []\n    for eq in eqs:\n        c, eqdict = _lin_eq2dict(eq, syms)\n        eqsdict.append(eqdict)\n        ind.append(c)\n    return eqsdict, ind\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 61,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 54,
        "n_ast_nodes": 88,
        "n_identifiers": 11,
        "d_id": 49076,
        "documentation": {
            "docstring": "Convert a system Expr/Eq equations into dict form, returning\n    the coefficient dictionaries and a list of syms-independent terms\n    from each expression in ``eqs```.\n\n    Examples\n    ========\n\n    >>> from sympy.polys.matrices.linsolve import _linear_eq_to_dict_inner as F\n    >>> from sympy.abc import x\n    >>> F([2*x + 3], {x})\n    ([{x: 2}], [3])\n    ",
            "n_words": 45,
            "vocab_size": 39,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 129861,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "dashboard/modules/actor/actor_utils.py",
        "file_name": "actor_utils.py",
        "fun_name": "construct_actor_groups",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def construct_actor_groups(actors):\n    \n    actor_groups = _group_actors_by_python_class(actors)\n    stats_by_group = {\n        name: _get_actor_group_stats(group) for name, group in actor_groups.items()\n    }\n\n    summarized_actor_groups = {}\n    for name, group in actor_groups.items():\n        summarized_actor_groups[name] = {\n            \"entries\": group,\n            \"summary\": stats_by_group[name],\n        }\n    return summarized_actor_groups\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 98,
        "n_words": 34,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 67,
        "n_ast_nodes": 110,
        "n_identifiers": 10,
        "d_id": 29041,
        "documentation": {
            "docstring": "actors is a dict from actor id to an actor or an\n    actor creation task The shared fields currently are\n    \"actorClass\", \"actorId\", and \"state\" ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 207753,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_change_view_history_link",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_change_view_history_link(self):\n        \n        url = reverse(\n            \"admin:%s_modelwithstringprimarykey_change\"\n            % ModelWithStringPrimaryKey._meta.app_label,\n            args=(quote(self.pk),),\n        )\n        response = self.client.get(url)\n        self.assertEqual(response.status_code, 200)\n        expected_link = reverse(\n            \"admin:%s_modelwithstringprimarykey_history\"\n            % ModelWithStringPrimaryKey._meta.app_label,\n            args=(quote(self.pk),),\n        )\n        self.assertContains(\n            response, '<a href=\"%s\" class=\"historylink\"' % escape(expected_link)\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 171,
        "n_words": 31,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 89,
        "n_ast_nodes": 144,
        "n_identifiers": 18,
        "d_id": 52085,
        "documentation": {
            "docstring": "Object history button link should work and contain the pk value quoted.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 196147,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/perm_groups.py",
        "file_name": "perm_groups.py",
        "fun_name": "generate_dimino",
        "commit_message": "Updated import locations",
        "code": "def generate_dimino(self, af=False):\n        \n        idn = list(range(self.degree))\n        order = 0\n        element_list = [idn]\n        set_element_list = {tuple(idn)}\n        if af:\n            yield idn\n        else:\n            yield _af_new(idn)\n        gens = [p._array_form for p in self.generators]\n\n        for i in range(len(gens)):\n            # D elements of the subgroup G_i generated by gens[:i]\n            D = element_list[:]\n            N = [idn]\n            while N:\n                A = N\n                N = []\n                for a in A:\n                    for g in gens[:i + 1]:\n                        ag = _af_rmul(a, g)\n                        if tuple(ag) not in set_element_list:\n                            # produce G_i*g\n                            for d in D:\n                                order += 1\n                                ap = _af_rmul(d, ag)\n                                if af:\n                                    yield ap\n                                else:\n                                    p = _af_new(ap)\n                                    yield p\n                                element_list.append(ap)\n                                set_element_list.add(tuple(ap))\n                                N.append(ap)\n        self._order = len(element_list)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 728,
        "n_words": 106,
        "vocab_size": 68,
        "complexity": 10,
        "nloc": 32,
        "token_counts": 187,
        "n_ast_nodes": 305,
        "n_identifiers": 30,
        "d_id": 47647,
        "documentation": {
            "docstring": "Yield group elements using Dimino's algorithm.\n\n        If ``af == True`` it yields the array form of the permutations.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation, PermutationGroup\n        >>> a = Permutation([0, 2, 1, 3])\n        >>> b = Permutation([0, 2, 3, 1])\n        >>> g = PermutationGroup([a, b])\n        >>> list(g.generate_dimino(af=True))\n        [[0, 1, 2, 3], [0, 2, 1, 3], [0, 2, 3, 1],\n         [0, 1, 3, 2], [0, 3, 2, 1], [0, 3, 1, 2]]\n\n        References\n        ==========\n\n        .. [1] The Implementation of Various Algorithms for Permutation Groups in\n               the Computer Algebra System: AXIOM, N.J. Doye, M.Sc. Thesis\n\n        ",
            "n_words": 93,
            "vocab_size": 64,
            "n_whitespaces": 206,
            "language": "en"
        }
    },
    {
        "id": 164913,
        "commit_id": "15a06d3d9e7656afff239da7a295a7b684456680",
        "repo": "pandas",
        "path": "pandas/core/groupby/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "size",
        "commit_message": "BUG: groupby.size and groupby.transform('size') incorrect for axis=1 (#45987)",
        "code": "def size(self) -> DataFrame | Series:\n        \n        result = self.grouper.size()\n\n        if self.axis == 1:\n            return DataFrame(\n                data=np.tile(result.values, (self.obj.shape[0], 1)),\n                columns=result.index,\n                index=self.obj.index,\n            )\n\n        # GH28330 preserve subclassed Series/DataFrames through calls\n        if issubclass(self.obj._constructor, Series):\n            result = self._obj_1d_constructor(result, name=self.obj.name)\n        else:\n            result = self._obj_1d_constructor(result)\n\n        if not self.as_index:\n            # Item \"None\" of \"Optional[Series]\" has no attribute \"reset_index\"\n            result = result.rename(\"size\").reset_index()  # type: ignore[union-attr]\n\n        return self._reindex_output(result, fill_value=0)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 228,
        "n_words": 60,
        "vocab_size": 49,
        "complexity": 4,
        "nloc": 24,
        "token_counts": 135,
        "n_ast_nodes": 214,
        "n_identifiers": 24,
        "d_id": 39620,
        "documentation": {
            "docstring": "\n        Compute group sizes.\n\n        Returns\n        -------\n        DataFrame or Series\n            Number of rows in each group as a Series if as_index is True\n            or a DataFrame if as_index is False.\n        ",
            "n_words": 28,
            "vocab_size": 20,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 21283,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/metadata/importlib/_dists.py",
        "file_name": "_dists.py",
        "fun_name": "_iter_requires_txt_entries",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def _iter_requires_txt_entries(self) -> Iterator[RequiresEntry]:\n        \n        content = self._dist.read_text(\"requires.txt\")\n        if content is None:\n            return\n        extra = marker = \"\"  # Section-less entries don't have markers.\n        for line in content.splitlines():\n            line = line.strip()\n            if not line or line.startswith(\"#\"):  # Comment; ignored.\n                continue\n            if line.startswith(\"[\") and line.endswith(\"]\"):  # A section header.\n                extra, _, marker = line.strip(\"[]\").partition(\":\")\n                continue\n            yield RequiresEntry(requirement=line, extra=extra, marker=marker)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 195,
        "n_words": 57,
        "vocab_size": 44,
        "complexity": 7,
        "nloc": 23,
        "token_counts": 108,
        "n_ast_nodes": 191,
        "n_identifiers": 17,
        "d_id": 3750,
        "documentation": {
            "docstring": "Parse a ``requires.txt`` in an egg-info directory.\n\n        This is an INI-ish format where an egg-info stores dependencies. A\n        section name describes extra other environment markers, while each entry\n        is an arbitrary string (not a key-value pair) representing a dependency\n        as a requirement string (no markers).\n\n        There is a construct in ``importlib.metadata`` called ``Sectioned`` that\n        does mostly the same, but the format is currently considered private.\n        ",
            "n_words": 65,
            "vocab_size": 50,
            "n_whitespaces": 114,
            "language": "en"
        }
    },
    {
        "id": 112161,
        "commit_id": "14d2966b9e91ae16dcc39de8f41017a75cec8ff9",
        "repo": "nni",
        "path": "nni/retiarii/oneshot/pytorch/supermodule/differentiable.py",
        "file_name": "differentiable.py",
        "fun_name": "named_parameters",
        "commit_message": "Valuechoice oneshot lightning (#4602)",
        "code": "def named_parameters(self, *args, **kwargs):\n        \n        arch = kwargs.pop('arch', False)\n        for name, p in super().named_parameters(*args, **kwargs):\n            if any(name == par_name for par_name in self._arch_parameter_names):\n                if arch:\n                    yield name, p\n            else:\n                if not arch:\n                    yield name, p\n\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 145,
        "n_words": 34,
        "vocab_size": 22,
        "complexity": 6,
        "nloc": 9,
        "token_counts": 71,
        "n_ast_nodes": 117,
        "n_identifiers": 12,
        "d_id": 24602,
        "documentation": {
            "docstring": "Named parameters excluding architecture parameters.",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 216799,
        "commit_id": "ef3a35ff9c9da7aab45e6f40103f32558f861e9b",
        "repo": "Open-Assistant",
        "path": "backend/oasst_backend/prompt_repository.py",
        "file_name": "prompt_repository.py",
        "fun_name": "get_stats",
        "commit_message": "fixes",
        "code": "def get_stats(self) -> SystemStats:\n        \n        deleted = self.db.query(Message.deleted, func.count()).group_by(Message.deleted)\n        nthreads = self.db.query(None, func.count(Message.id)).filter(Message.parent_id.is_(None))\n        query = deleted.union_all(nthreads)\n        result = {k: v for k, v in query.all()}\n\n        return SystemStats(\n            all=result.get(True, 0) + result.get(False, 0),\n            active=result.get(False, 0),\n            deleted=result.get(True, 0),\n            message_trees=result.get(None, 0),\n        )\n",
        "url": "https://github.com/LAION-AI/Open-Assistant.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 131,
        "n_words": 38,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 146,
        "n_ast_nodes": 222,
        "n_identifiers": 23,
        "d_id": 54687,
        "documentation": {
            "docstring": "\n        Get data stats such as number of all messages in the system,\n        number of deleted and active messages and number of message trees.\n        ",
            "n_words": 23,
            "vocab_size": 17,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 268874,
        "commit_id": "f1aa8b7d2a0c89591c5c42eca5b6f013114a7bbd",
        "repo": "keras",
        "path": "keras/preprocessing/sequence.py",
        "file_name": "sequence.py",
        "fun_name": "make_sampling_table",
        "commit_message": "Copy sequence utils from keras_preprocessing directly into core keras\n\nPiperOrigin-RevId: 424915569",
        "code": "def make_sampling_table(size, sampling_factor=1e-5):\n  \n  gamma = 0.577\n  rank = np.arange(size)\n  rank[0] = 1\n  inv_fq = rank * (np.log(rank) + gamma) + 0.5 - 1. / (12. * rank)\n  f = sampling_factor * inv_fq\n\n  return np.minimum(1., f / np.sqrt(f))\n\n\n@keras_export('keras.preprocessing.sequence.skipgrams')",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export('keras.preprocessing.sequence.skipgrams')",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 44,
        "n_words": 38,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 81,
        "n_ast_nodes": 125,
        "n_identifiers": 13,
        "d_id": 79742,
        "documentation": {
            "docstring": "Generates a word rank-based probabilistic sampling table.\n\n  Used for generating the `sampling_table` argument for `skipgrams`.\n  `sampling_table[i]` is the probability of sampling\n  the word i-th most common word in a dataset\n  (more common words should be sampled less frequently, for balance).\n\n  The sampling probabilities are generated according\n  to the sampling distribution used in word2vec:\n\n  ```\n  p(word) = (min(1, sqrt(word_frequency / sampling_factor) /\n      (word_frequency / sampling_factor)))\n  ```\n\n  We assume that the word frequencies follow Zipf's law (s=1) to derive\n  a numerical approximation of frequency(rank):\n\n  `frequency(rank) ~ 1/(rank * (log(rank) + gamma) + 1/2 - 1/(12*rank))`\n  where `gamma` is the Euler-Mascheroni constant.\n\n  Args:\n      size: Int, number of possible words to sample.\n      sampling_factor: The sampling factor in the word2vec formula.\n\n  Returns:\n      A 1D Numpy array of length `size` where the ith entry\n      is the probability that a word of rank i should be sampled.\n  ",
            "n_words": 140,
            "vocab_size": 97,
            "n_whitespaces": 181,
            "language": "en"
        }
    },
    {
        "id": 66869,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v8_7/sync_india_custom_fields.py",
        "file_name": "sync_india_custom_fields.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\tcompany = frappe.get_all(\"Company\", filters={\"country\": \"India\"})\n\tif not company:\n\t\treturn\n\n\tfrappe.reload_doc(\"Payroll\", \"doctype\", \"payroll_period\")\n\tfrappe.reload_doc(\"Payroll\", \"doctype\", \"employee_tax_exemption_declaration\")\n\tfrappe.reload_doc(\"Payroll\", \"doctype\", \"employee_tax_exemption_proof_submission\")\n\tfrappe.reload_doc(\"Payroll\", \"doctype\", \"employee_tax_exemption_declaration_category\")\n\tfrappe.reload_doc(\"Payroll\", \"doctype\", \"employee_tax_exemption_proof_submission_detail\")\n\n\tfrappe.reload_doc(\"accounts\", \"doctype\", \"tax_category\")\n\n\tfor doctype in [\"Sales Invoice\", \"Delivery Note\", \"Purchase Invoice\"]:\n\t\tfrappe.db.sql(\n\t\t\t,\n\t\t\tdoctype,\n\t\t)\n\n\tmake_custom_fields()\n\n\tfrappe.db.sql(\n\t\t\n\t)\n\n\tfrappe.db.sql(\n\t\t\n\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 27,
        "n_words": 47,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 31,
        "token_counts": 126,
        "n_ast_nodes": 241,
        "n_identifiers": 10,
        "d_id": 14367,
        "documentation": {
            "docstring": "delete from `tabCustom Field` where dt = %s\n\t\t\tand fieldname in ('port_code', 'shipping_bill_number', 'shipping_bill_date')\n\t\tupdate `tabCustom Field`\n\t\tset reqd = 0, `default` = ''\n\t\twhere fieldname = 'reason_for_issuing_document'\n\t\n\t\tupdate tabAddress\n\t\tset gst_state_number=concat(\"0\", gst_state_number)\n\t\twhere ifnull(gst_state_number, '') != '' and gst_state_number<10\n\t",
            "n_words": 40,
            "vocab_size": 28,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 264636,
        "commit_id": "36d6ae33d15e93cc552827cdea363a9c00c7f823",
        "repo": "netbox",
        "path": "netbox/extras/api/views.py",
        "file_name": "views.py",
        "fun_name": "run",
        "commit_message": "Allow setting individual timeouts on scripts and reports",
        "code": "def run(self, request, pk):\n        \n        # Check that the user has permission to run reports.\n        if not request.user.has_perm('extras.run_report'):\n            raise PermissionDenied(\"This user does not have permission to run reports.\")\n\n        # Check that at least one RQ worker is running\n        if not Worker.count(get_connection('default')):\n            raise RQWorkerNotRunningException()\n\n        # Retrieve and run the Report. This will create a new JobResult.\n        report = self._retrieve_report(pk)\n        report_content_type = ContentType.objects.get(app_label='extras', model='report')\n        job_result = JobResult.enqueue_job(\n            run_report,\n            report.full_name,\n            report_content_type,\n            request.user,\n            job_timeout=report.job_timeout\n        )\n        report.result = job_result\n\n        serializer = serializers.ReportDetailSerializer(report, context={'request': request})\n\n        return Response(serializer.data)\n\n\n#\n# Scripts\n#\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 249,
        "n_words": 84,
        "vocab_size": 62,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 118,
        "n_ast_nodes": 201,
        "n_identifiers": 32,
        "d_id": 77772,
        "documentation": {
            "docstring": "\n        Run a Report identified as \"<module>.<script>\" and return the pending JobResult as the result\n        ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 249135,
        "commit_id": "c97042f7eef3748e17c90e48a4122389a89c4735",
        "repo": "synapse",
        "path": "tests/rest/admin/test_room.py",
        "file_name": "test_room.py",
        "fun_name": "test_purge_room_and_not_block",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13469)",
        "code": "def test_purge_room_and_not_block(self) -> None:\n        \n        # Test that room is not purged\n        with self.assertRaises(AssertionError):\n            self._is_purged(self.room_id)\n\n        # Test that room is not blocked\n        self._is_blocked(self.room_id, expect=False)\n\n        # Assert one user in room\n        self._is_member(room_id=self.room_id, user_id=self.other_user)\n\n        channel = self.make_request(\n            \"DELETE\",\n            self.url.encode(\"ascii\"),\n            content={\"block\": False, \"purge\": True},\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n        self.assertEqual(None, channel.json_body[\"new_room_id\"])\n        self.assertEqual(self.other_user, channel.json_body[\"kicked_users\"][0])\n        self.assertIn(\"failed_to_kick_users\", channel.json_body)\n        self.assertIn(\"local_aliases\", channel.json_body)\n\n        self._is_purged(self.room_id)\n        self._is_blocked(self.room_id, expect=False)\n        self._has_no_members(self.room_id)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 231,
        "n_words": 57,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 183,
        "n_ast_nodes": 298,
        "n_identifiers": 24,
        "d_id": 72642,
        "documentation": {
            "docstring": "Test to purge a room and do not block it.\n        Members will not be moved to a new room and will not receive a message.\n        ",
            "n_words": 25,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 12659,
        "commit_id": "d21870ac47fc1594b45a5f01ee48cddf5c18b2ff",
        "repo": "jina",
        "path": "jina/serve/networking.py",
        "file_name": "networking.py",
        "fun_name": "get_next_connection",
        "commit_message": "fix: fix reconnect issues (#4941)",
        "code": "async def get_next_connection(self):\n        \n        return await self._get_next_connection(num_retries=3)\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 16,
        "n_ast_nodes": 30,
        "n_identifiers": 4,
        "d_id": 2365,
        "documentation": {
            "docstring": "\n        Returns a connection from the list. Strategy is round robin\n        :returns: A connection from the pool\n        ",
            "n_words": 16,
            "vocab_size": 13,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 8364,
        "commit_id": "4f40ffec8e81eb3f6385243498babe1409a675be",
        "repo": "ludwig",
        "path": "ludwig/visualize.py",
        "file_name": "visualize.py",
        "fun_name": "load_data_for_viz",
        "commit_message": "Changes learning_curves to use \"step\" or \"epoch\" as x-axis label. (#2578)\n\n* Started building dataclasses for model training output.\r\n\r\n* Adds EvaluationFrequency to training stats, dataclasses for training results.\r\n\r\n* Adds x_label, x_step to learning_curves.\r\n\r\n* fix x axis when using checkpoints_per_epoch.\r\n\r\n* Fixes CLI test by making dataclass JSON-serializable and implementing __contains__.\r\n\r\n* Adds default value for EvaluationFrequency, maybe fixes test_learning_curves with only training metrics.\r\n\r\n* Fixes kfold CV.\r\n\r\n* Fixes viz tests, restoring original functionality of load_data_for_viz\r\n\r\n* Adds todos to deprecate.",
        "code": "def load_data_for_viz(load_type, model_file_statistics, dtype=int, ground_truth_split=2) -> Dict[str, Any]:\n    \n    supported_load_types = dict(\n        load_json=load_json,\n        load_from_file=partial(load_from_file, dtype=dtype, ground_truth_split=ground_truth_split),\n    )\n    loader = supported_load_types[load_type]\n    # Loads training stats from JSON file(s).\n    try:\n        stats_per_model = [loader(stats_f) for stats_f in model_file_statistics]\n    except (TypeError, AttributeError):\n        logger.exception(f\"Unable to open model statistics file {model_file_statistics}!\")\n        raise\n    return stats_per_model\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 106,
        "n_words": 47,
        "vocab_size": 44,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 84,
        "n_ast_nodes": 131,
        "n_identifiers": 21,
        "d_id": 1405,
        "documentation": {
            "docstring": "Load JSON files (training stats, evaluation stats...) for a list of models.\n\n    :param load_type: type of the data loader to be used.\n    :param model_file_statistics: JSON file or list of json files containing any\n           model experiment stats.\n    :return List of training statistics loaded as json objects.\n    ",
            "n_words": 45,
            "vocab_size": 37,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 101744,
        "commit_id": "e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1",
        "repo": "faceswap",
        "path": "tools/alignments/media.py",
        "file_name": "media.py",
        "fun_name": "check_input_folder",
        "commit_message": "Alignments Tool - Typing, Documentation + Re-org",
        "code": "def check_input_folder(self) -> Optional[cv2.VideoCapture]:\n        \n        err = None\n        loadtype = self.__class__.__name__\n        if not self.folder:\n            err = f\"ERROR: A {loadtype} folder must be specified\"\n        elif not os.path.exists(self.folder):\n            err = f\"ERROR: The {loadtype} location {self.folder} could not be found\"\n        if err:\n            logger.error(err)\n            sys.exit(0)\n\n        if (loadtype == \"Frames\" and\n                os.path.isfile(self.folder) and\n                os.path.splitext(self.folder)[1].lower() in _video_extensions):\n            logger.verbose(\"Video exists at: '%s'\", self.folder)  # type: ignore\n            retval = cv2.VideoCapture(self.folder)  # pylint: disable=no-member\n            # TODO ImageIO single frame seek seems slow. Look into this\n            # retval = imageio.get_reader(self.folder, \"ffmpeg\")\n        else:\n            logger.verbose(\"Folder exists at '%s'\", self.folder)  # type: ignore\n            retval = None\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 300,
        "n_words": 94,
        "vocab_size": 65,
        "complexity": 7,
        "nloc": 27,
        "token_counts": 140,
        "n_ast_nodes": 252,
        "n_identifiers": 23,
        "d_id": 21148,
        "documentation": {
            "docstring": " makes sure that the frames or faces folder exists\n            If frames folder contains a video file return imageio reader object\n\n        Returns\n        -------\n        :class:`cv2.VideoCapture`\n            Object for reading a video stream\n        ",
            "n_words": 29,
            "vocab_size": 25,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 9335,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/external/landmark_detector/utils.py",
        "file_name": "utils.py",
        "fun_name": "generate_heatmap",
        "commit_message": "initialize ostec",
        "code": "def generate_heatmap(logits, num_classes):\n    \n\n    keypoint_colours = np.array([plt.cm.spectral(x) for x in np.linspace(0, 1, num_classes + 1)])[\n        ..., :3].astype(np.float32)\n\n    prediction = tf.nn.softmax(logits)\n    heatmap = tf.matmul(tf.reshape(prediction, (-1, num_classes + 1)), keypoint_colours)\n    heatmap = tf.reshape(heatmap, (tf.shape(prediction)[0],\n                                   tf.shape(prediction)[1],\n                                   tf.shape(prediction)[2], 3))\n    return heatmap\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 129,
        "n_words": 36,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 131,
        "n_ast_nodes": 195,
        "n_identifiers": 21,
        "d_id": 1586,
        "documentation": {
            "docstring": "Generates a coloured heatmap from the keypoint logits.\n\n    Args:\n        features: A `Tensor` of dimensions [num_batch, height, width, FLAGS.n_landmarks + 1].\n    ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 9894,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/peapods/pods/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "update_worker_pea_args",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def update_worker_pea_args(self):\n        \n        self.peas_args['peas'] = self._set_peas_args(self.args)\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 1761,
        "documentation": {
            "docstring": " Update args of all its worker peas based on Pod args. Does not touch head and tail",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 803,
        "commit_id": "a90188ecc017971b64778aa0ff41127a9d5d9d44",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/tensor/autodp/single_entity_phi.py",
        "file_name": "single_entity_phi.py",
        "fun_name": "to_local_object_without_private_data_child",
        "commit_message": "working fpt for SMPC+DP",
        "code": "def to_local_object_without_private_data_child(self) -> SingleEntityPhiTensor:\n        \n\n        public_shape = getattr(self, \"public_shape\", None)\n        public_dtype = getattr(self, \"public_dtype\", None)\n        return Tensor(\n            child=SingleEntityPhiTensor(\n                child=FixedPrecisionTensor(value=None),\n                entity=self.entity,\n                min_vals=self.min_vals,  # type: ignore\n                max_vals=self.max_vals,  # type: ignore\n                scalar_manager=self.scalar_manager,\n            ),\n            public_shape=public_shape,\n            public_dtype=public_dtype,\n        )\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 188,
        "n_words": 32,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 79,
        "n_ast_nodes": 121,
        "n_identifiers": 14,
        "d_id": 125,
        "documentation": {
            "docstring": "Convert this pointer into a partial version of the SingleEntityPhiTensor but without\n        any of the private data therein.",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 197501,
        "commit_id": "55c2eba0fc6eefa30c07e2e76795c1df89488b11",
        "repo": "sympy",
        "path": "sympy/physics/quantum/circuitplot.py",
        "file_name": "circuitplot.py",
        "fun_name": "_measurements",
        "commit_message": "Update documentation",
        "code": "def _measurements(self):\n        \n        ismeasured = {}\n        for i,g in enumerate(self._gates()):\n            if getattr(g,'measurement',False):\n                for target in g.targets:\n                    if target in ismeasured:\n                        if ismeasured[target] > i:\n                            ismeasured[target] = i\n                    else:\n                        ismeasured[target] = i\n        return ismeasured\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 197,
        "n_words": 32,
        "vocab_size": 20,
        "complexity": 6,
        "nloc": 11,
        "token_counts": 70,
        "n_ast_nodes": 113,
        "n_identifiers": 10,
        "d_id": 48582,
        "documentation": {
            "docstring": "Return a dict ``{i:j}`` where i is the index of the wire that has\n        been measured, and j is the gate where the wire is measured.\n        ",
            "n_words": 26,
            "vocab_size": 19,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 134154,
        "commit_id": "02f911ce78137cb63ecb685a8ef8e56dcb60062c",
        "repo": "ray",
        "path": "release/air_tests/air_benchmarks/mlperf-train/tf_utils.py",
        "file_name": "tf_utils.py",
        "fun_name": "parse_example_proto_and_decode",
        "commit_message": "Benchmarking Ray Data bulk ingest as input file size changes. (#29296)\n\nThis PR adds a benchmark which takes work from https://github.com/anyscale/air-benchmarks and makes it run as a release test.\r\n\r\nFull metrics are stored in Databricks.\r\n\r\nSigned-off-by: Cade Daniel <cade@anyscale.com>",
        "code": "def parse_example_proto_and_decode(example_serialized):\n    \n    image_buffer, label = _parse_example_proto(example_serialized)\n    image_buffer = tf.reshape(image_buffer, shape=[])\n    image_buffer = tf.io.decode_jpeg(image_buffer, channels=NUM_CHANNELS)\n    return image_buffer, label\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 32,
        "n_words": 17,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 45,
        "n_ast_nodes": 73,
        "n_identifiers": 12,
        "d_id": 30205,
        "documentation": {
            "docstring": "Parses an example and decodes the image to prepare for caching.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 65389,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_currency",
        "commit_message": "style: format code with black",
        "code": "def get_currency(filters):\n\t\n\tcompany = get_appropriate_company(filters)\n\tcompany_currency = get_company_currency(company)\n\tpresentation_currency = (\n\t\tfilters[\"presentation_currency\"] if filters.get(\"presentation_currency\") else company_currency\n\t)\n\n\treport_date = filters.get(\"to_date\")\n\n\tif not report_date:\n\t\tfiscal_year_to_date = get_from_and_to_date(filters.get(\"to_fiscal_year\"))[\"to_date\"]\n\t\treport_date = formatdate(get_datetime_str(fiscal_year_to_date), \"dd-MM-yyyy\")\n\n\tcurrency_map = dict(\n\t\tcompany=company,\n\t\tcompany_currency=company_currency,\n\t\tpresentation_currency=presentation_currency,\n\t\treport_date=report_date,\n\t)\n\n\treturn currency_map\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 23,
        "n_words": 40,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 95,
        "n_ast_nodes": 161,
        "n_identifiers": 15,
        "d_id": 13877,
        "documentation": {
            "docstring": "\n\tReturns a dictionary containing currency information. The keys of the dict are\n\t- company: The company for which we are fetching currency information. if no\n\tcompany is specified, it will fallback to the default company.\n\t- company currency: The functional currency of the said company.\n\t- presentation currency: The presentation currency to use. Only currencies that\n\thave been used for transactions will be allowed.\n\t- report date: The report date.\n\t:param filters: Report filters\n\t:type filters: dict\n\n\t:return: str - Currency\n\t",
            "n_words": 81,
            "vocab_size": 54,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 27234,
        "commit_id": "71c19c951bcfba66fa9a9ee5809a46ad3af8f11f",
        "repo": "saleor",
        "path": "saleor/graphql/order/tests/test_order.py",
        "file_name": "test_order.py",
        "fun_name": "test_query_order_fields_order_with_new_id_by_anonymous_user",
        "commit_message": "Allow fetching by id all order data for new orders (#9728)",
        "code": "def test_query_order_fields_order_with_new_id_by_anonymous_user(order, api_client):\n    \n    # given\n    variables = {\"id\": graphene.Node.to_global_id(\"Order\", order.pk)}\n\n    # when\n    response = api_client.post_graphql(QUERY_ORDER_FIELDS_BY_ID, variables)\n\n    # then\n    content = get_graphql_content(response)\n    assert content[\"data\"][\"order\"]\n    assert (\n        content[\"data\"][\"order\"][\"billingAddress\"][\"streetAddress1\"]\n        == order.billing_address.street_address_1\n    )\n    assert (\n        content[\"data\"][\"order\"][\"shippingAddress\"][\"streetAddress1\"]\n        == order.shipping_address.street_address_1\n    )\n    assert content[\"data\"][\"order\"][\"userEmail\"] == order.user_email\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 106,
        "n_words": 39,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 109,
        "n_ast_nodes": 194,
        "n_identifiers": 17,
        "d_id": 5103,
        "documentation": {
            "docstring": "Ensure that all fields that are available for order owner can be fetched with\n    use of new id by the customer user.",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 223013,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/tests/support.py",
        "file_name": "support.py",
        "fun_name": "mkdtemp",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def mkdtemp(self):\n        \n        d = tempfile.mkdtemp()\n        self.tempdirs.append(d)\n        return d\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 36,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 56849,
        "documentation": {
            "docstring": "Create a temporary directory that will be cleaned up.\n\n        Returns the path of the directory.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 115416,
        "commit_id": "d5b6d8cf5bd69a1f3427bac153fa09159dfe96d0",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/mongodb_handler/utils/mongodb_query.py",
        "file_name": "mongodb_query.py",
        "fun_name": "__str__",
        "commit_message": "added converters:\n- mongo to str\n- str to mongo\ncreating predictor from sql using mongo data\ntests",
        "code": "def __str__(self):\n        \n\n        call_str = f'db.{self.collection}'\n        for step in self.pipeline:\n            args_str = []\n            for arg in step['args']:\n                args_str.append(MongoJSONEncoder().encode(arg))\n            call_str += f'.{step[\"method\"]}({\",\".join(args_str)})'\n        return call_str\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 98,
        "n_words": 22,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 48,
        "n_ast_nodes": 113,
        "n_identifiers": 12,
        "d_id": 25455,
        "documentation": {
            "docstring": "\n        converts call to string\n\n        {\n            'collection': 'fish',\n            'call': [   // call is sequence of methods\n                {\n                    'method': 'find',\n                    'args': [{a:1}, {b:2}]\n                },\n                {\n                    'method': 'sort',\n                    'args': [{c:3}]\n                },\n            ]\n        }\n\n        to:\n\n         \"db_test.fish.find({a:1}, {b:2}).sort({c:3})\"\n        ",
            "n_words": 33,
            "vocab_size": 27,
            "n_whitespaces": 248,
            "language": "en"
        }
    },
    {
        "id": 61223,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/misc.py",
        "file_name": "misc.py",
        "fun_name": "pairwise",
        "commit_message": "upd; format",
        "code": "def pairwise(iterable):\n    # type: (Iterable[Any]) -> Iterator[Tuple[Any, Any]]\n    \n    iterable = iter(iterable)\n    return zip_longest(iterable, iterable)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 26,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 4,
        "d_id": 12448,
        "documentation": {
            "docstring": "\n    Return paired elements.\n\n    For example:\n        s -> (s0, s1), (s2, s3), (s4, s5), ...\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 37029,
        "commit_id": "4868a830db5f19f56712f540979d637368221d50",
        "repo": "transformers",
        "path": "examples/research_projects/codeparrot/scripts/human_eval.py",
        "file_name": "human_eval.py",
        "fun_name": "complete_code",
        "commit_message": "Jia multi gpu eval (#16428)\n\n* add simple multi gpu complet\r\n\r\n* add human_eval_multi_gpu\r\n\r\n* use copy strategy to distribute across gpu, to avoid padding\r\n\r\n* add doc string\r\n\r\n* update code style\r\n\r\n* use task id to arrange output\r\n\r\n* truncate input to avoid zero pad\r\n\r\n* Stop the copy mechanism\r\n\r\n* update style\r\n\r\n* restore copies to scale better in distributed mode\r\n\r\n* update style\r\n\r\n* replace human eval\r\n\r\n* Apply suggestions from code review\r\n\r\n1. Tokenize all input at the same time\r\n2. use attention_mask to get the input length\r\n3. other small fixes\r\n\r\nCo-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>\r\n\r\n* correct typo and update docstring\r\n\r\n* update code style\r\n\r\n* remove num sample division constraint\r\n\r\n* remove max len calculation\r\n\r\n* use accelerator.gather once to speed up\r\n\r\n* use accelerate set_seed; update accelerate version\r\n\r\n* correct gather bug\r\n\r\nCo-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>",
        "code": "def complete_code(accelerator, model, tokenizer, dataloader, n_tasks, batch_size=20, **gen_kwargs):\n    \n    gen_token_dict = defaultdict(list)  # dict of list of generated tokens\n    for step, batch in tqdm(enumerate(dataloader)):\n        with torch.no_grad():\n            gen_kwargs[\"stopping_criteria\"][0].start_length = batch[\"ids\"].shape[-1]\n            generated_tokens = accelerator.unwrap_model(model).generate(\n                input_ids=batch[\"ids\"][:, : batch[\"input_len\"]], num_return_sequences=batch_size, **gen_kwargs\n            )\n            # each task is generated batch_size times\n            generated_tasks = batch[\"task_id\"].repeat(batch_size)\n            generated_tokens = accelerator.pad_across_processes(\n                generated_tokens, dim=1, pad_index=tokenizer.pad_token_id\n            )\n\n            generated_tokens, generated_tasks = accelerator.gather((generated_tokens, generated_tasks))\n            generated_tokens = generated_tokens.cpu().numpy()\n            generated_tasks = generated_tasks.cpu().numpy()\n\n            for task, generated_tokens in zip(generated_tasks, generated_tokens):\n                gen_token_dict[task].append(generated_tokens)\n\n    code_gens = [[] for _ in range(n_tasks)]\n    for task, generated_tokens in gen_token_dict.items():\n        for s in generated_tokens:\n            gen_code = tokenizer.decode(s, skip_special_tokens=True, clean_up_tokenization_spaces=True)\n            code_gens[task].append(remove_last_block(gen_code))\n    return code_gens\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 317,
        "n_words": 96,
        "vocab_size": 66,
        "complexity": 6,
        "nloc": 23,
        "token_counts": 246,
        "n_ast_nodes": 387,
        "n_identifiers": 46,
        "d_id": 6716,
        "documentation": {
            "docstring": "Generate multiple codes for each task in the dataset. This function leverage accelerator to distribute\n    the processing to multiple GPUs.\n    dataloader, a wrapper around a TokenizeDataset objectm is supposed to send all the prompts from\n    the evalution dataset to the modelm as the following:\n    [p_0_0, p_0_1, ..., p_0_nc-1, p_1_0, ..., p_nt-1_nc-1]\n    where nc is the number of copies of the prompt, and nt is the number of tasks.\n    nc is such that num_sample = nc * batch_size\n\n    Parameters\n    ----------\n    accelerator: Accelerator\n\n    model: transformers.PreTrainedModel\n        Code generation model. AutoTokenizer.from_pretrained(model_ckpt), ex model_ckpt = \"lvwerra/codeparrot\"\n\n    tokenizer: transformers.AutoTokenizer\n        The tokenizer used to train model\n\n    dataloader: DataLoader\n        The dataloader is a wrapper around a TokenizeDataset object. It is designed to be used with multiple GPUs.\n\n    n_tasks: int\n        The number of tasks in the dataset. It is used to determine the length of the output.\n        Should be aligned with the number of tasks in the TokenizeDataset.\n\n    batch_size: int\n        num_return_sequences per copy of the prompt such that num_sample = batch_size * n_copies\n\n    gen_kwargs: dict\n        Keyword arguments for the generation function of the model.\n\n    Returns\n    -------\n    code_gens: list of list of str, of length n_tasks\n        List of generated codes for each task.\n        Each element is a list of generated codes for each task, with length num_samples\n    ",
            "n_words": 207,
            "vocab_size": 115,
            "n_whitespaces": 327,
            "language": "en"
        }
    },
    {
        "id": 266772,
        "commit_id": "a06fa496d3f837cca3c437ab6e9858525633d147",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/delegation.py",
        "file_name": "delegation.py",
        "fun_name": "delegate_command",
        "commit_message": "ansible-test - Code cleanup and refactoring. (#77169)\n\n* Remove unnecessary PyCharm ignores.\r\n* Ignore intentional undefined attribute usage.\r\n* Add missing type hints. Fix existing type hints.\r\n* Fix docstrings and comments.\r\n* Use function to register completion handler.\r\n* Pass strings to display functions.\r\n* Fix CompositeAction handling of dest argument.\r\n* Use consistent types in expressions/assignments.\r\n* Use custom function to keep linters happy.\r\n* Add missing raise for custom exception.\r\n* Clean up key/value type handling in cloud plugins.\r\n* Use dataclass instead of dict for results.\r\n* Add custom type_guard function to check lists.\r\n* Ignore return type that can't be checked (yet).\r\n* Avoid changing types on local variables.",
        "code": "def delegate_command(args, host_state, exclude, require):  # type: (EnvironmentConfig, HostState, t.List[str], t.List[str]) -> None\n    \n    con = host_state.controller_profile.get_origin_controller_connection()\n    working_directory = host_state.controller_profile.get_working_directory()\n    host_delegation = not isinstance(args.controller, OriginConfig)\n\n    if host_delegation:\n        if data_context().content.collection:\n            content_root = os.path.join(working_directory, data_context().content.collection.directory)\n        else:\n            content_root = os.path.join(working_directory, 'ansible')\n\n        ansible_bin_path = os.path.join(working_directory, 'ansible', 'bin')\n\n        with tempfile.NamedTemporaryFile(prefix='ansible-source-', suffix='.tgz') as payload_file:\n            create_payload(args, payload_file.name)\n            con.extract_archive(chdir=working_directory, src=payload_file)\n    else:\n        content_root = working_directory\n        ansible_bin_path = ANSIBLE_BIN_PATH\n\n    command = generate_command(args, host_state.controller_profile.python, ansible_bin_path, content_root, exclude, require)\n\n    if isinstance(con, SshConnection):\n        ssh = con.settings\n    else:\n        ssh = None\n\n    options = []\n\n    if isinstance(args, IntegrationConfig) and args.controller.is_managed and all(target.is_managed for target in args.targets):\n        if not args.allow_destructive:\n            options.append('--allow-destructive')\n\n    with support_container_context(args, ssh) as containers:  # type: t.Optional[ContainerDatabase]\n        if containers:\n            options.extend(['--containers', json.dumps(containers.to_dict())])\n\n        # Run unit tests unprivileged to prevent stray writes to the source tree.\n        # Also disconnect from the network once requirements have been installed.\n        if isinstance(args, UnitsConfig) and isinstance(con, DockerConnection):\n            pytest_user = 'pytest'\n\n            writable_dirs = [\n                os.path.join(content_root, ResultType.JUNIT.relative_path),\n                os.path.join(content_root, ResultType.COVERAGE.relative_path),\n            ]\n\n            con.run(['mkdir', '-p'] + writable_dirs)\n            con.run(['chmod', '777'] + writable_dirs)\n            con.run(['chmod', '755', working_directory])\n            con.run(['chmod', '644', os.path.join(content_root, args.metadata_path)])\n            con.run(['useradd', pytest_user, '--create-home'])\n            con.run(insert_options(command, options + ['--requirements-mode', 'only']))\n\n            container = con.inspect()\n            networks = container.get_network_names()\n\n            if networks is not None:\n                for network in networks:\n                    con.disconnect_network(network)\n            else:\n                display.warning('Network disconnection is not supported (this is normal under podman). '\n                                'Tests will not be isolated from the network. Network-related tests may misbehave.')\n\n            options.extend(['--requirements-mode', 'skip'])\n\n            con.user = pytest_user\n\n        success = False\n\n        try:\n            con.run(insert_options(command, options))\n            success = True\n        finally:\n            if host_delegation:\n                download_results(args, con, content_root, success)\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 770,
        "n_words": 231,
        "vocab_size": 154,
        "complexity": 16,
        "nloc": 57,
        "token_counts": 487,
        "n_ast_nodes": 803,
        "n_identifiers": 76,
        "d_id": 78575,
        "documentation": {
            "docstring": "Delegate execution based on the provided host state.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 22544,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "XORcipher/XOR_cipher.py",
        "file_name": "XOR_cipher.py",
        "fun_name": "decrypt_string",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def decrypt_string(self, content, key=0):\n        \n\n        # precondition\n        assert isinstance(key, int) and isinstance(content, str)\n\n        key = key or self.__key or 1\n\n        # make sure key can be any size\n        while key > 255:\n            key -= 255\n\n        # This will be returned\n        ans = \"\"\n\n        for ch in content:\n            ans += chr(ord(ch) ^ key)\n\n        return ans\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 145,
        "n_words": 53,
        "vocab_size": 42,
        "complexity": 6,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 105,
        "n_identifiers": 12,
        "d_id": 4360,
        "documentation": {
            "docstring": "\n        input: 'content' of type string and 'key' of type int\n        output: decrypted string 'content'\n        if key not passed the method uses the key by the constructor.\n        otherwise key = 1\n        ",
            "n_words": 30,
            "vocab_size": 22,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 3384,
        "commit_id": "6b502d8c326bcde791128f5711a21cc03bde19f3",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-square/source_square/source.py",
        "file_name": "source.py",
        "fun_name": "refresh_access_token",
        "commit_message": "🎉 square: added oauth support (#6842)\n\n* fixed test which check incorrect cred config\r\n\r\n* Added oauth2 authentication\r\n\r\n* Added oauth creds\r\n\r\n* fixed formatting\r\n\r\n* added oauth2 spec section, added missing type hints\r\n\r\n* Added java part of Square OAuth\r\n\r\n* fixed checkstyle\r\n\r\n* removed commented code\r\n\r\n* added support for old format of spec.json files, updated change logs docs\r\n\r\n* renamed spec property 'authentication' to default 'credentials'. fixed changes in java part\r\n\r\n* recovered empty files\r\n\r\n* updated OAuthImplementationFactory.java\r\n\r\n* fixed issue with autheticator for sub streams, added config catalog with all streams, updated docs\r\n\r\n* use advanced_auth\r\n\r\n* added advanced_auth\r\n\r\n* moved scopes to private property\r\n\r\n* updated source version\r\n\r\n* Revert \"updated source version\"\r\n\r\nThis reverts commit ce3d06165c4bbbe1592e22203d6b6c545deec9a9.\r\n\r\n* updated source version\r\n\r\n* added new version for airbyte index\r\n\r\nCo-authored-by: ievgeniit <etsybaev@gmail.com>",
        "code": "def refresh_access_token(self) -> Tuple[str, int]:\n        \n        token, expires_at = super().refresh_access_token()\n        expires_in = pendulum.parse(expires_at) - pendulum.now()\n        return token, expires_in.seconds\n\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 45,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 44,
        "n_ast_nodes": 73,
        "n_identifiers": 13,
        "d_id": 466,
        "documentation": {
            "docstring": "Handle differences in expiration attr:\n        from API: \"expires_at\": \"2021-11-05T14:26:57Z\"\n        expected: \"expires_in\": number of seconds\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 204767,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/serializers/xml_serializer.py",
        "file_name": "xml_serializer.py",
        "fun_name": "start_object",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def start_object(self, obj):\n        \n        if not hasattr(obj, \"_meta\"):\n            raise base.SerializationError(\n                \"Non-model object (%s) encountered during serialization\" % type(obj)\n            )\n\n        self.indent(1)\n        attrs = {\"model\": str(obj._meta)}\n        if not self.use_natural_primary_keys or not hasattr(obj, \"natural_key\"):\n            obj_pk = obj.pk\n            if obj_pk is not None:\n                attrs[\"pk\"] = str(obj_pk)\n\n        self.xml.startElement(\"object\", attrs)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 159,
        "n_words": 43,
        "vocab_size": 34,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 91,
        "n_ast_nodes": 157,
        "n_identifiers": 16,
        "d_id": 50880,
        "documentation": {
            "docstring": "\n        Called as each object is handled.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 134124,
        "commit_id": "fc9f8e458c4dad7a51e0d781917b1a003cb55cd7",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_syncer_callback.py",
        "file_name": "test_syncer_callback.py",
        "fun_name": "test_syncer_callback_dead_node_log_error",
        "commit_message": "[Tune] Catch SyncerCallback failure with dead node (#29438)\n\n### Context\r\nThis issue was uncovered by this long running test: `long_running_distributed_pytorch_pbt_failure`. This test randomly kills nodes via `FailureInjectorCallback`, and the test failure happens when:\r\n\r\n1. A trial result comes in and is processed\r\n2. The node this trial is running on is requested to be killed by the failure injector\r\n3. The driver's syncer callback runs on the on_trial_result event\r\n4. The node dies\r\n5. The driver is in the middle of syncing, trying to access the node ip, which errors\r\n\r\n### What's in this PR?\r\n1. Gracefully handle this race condition by catching the error thrown by the sync operation on a dead node\r\n2. Log an error to the user\r\n3. Adds a test for this sync with dead node scenario\r\n\r\nSigned-off-by: Justin Yu <justinvyu@berkeley.edu>",
        "code": "def test_syncer_callback_dead_node_log_error(caplog, ray_start_2_cpus, temp_data_dirs):\n    \n    caplog.set_level(logging.ERROR, logger=\"ray.tune.syncer\")\n\n    tmp_source, tmp_target = temp_data_dirs\n\n    syncer_callback = TestSyncerCallback(\n        sync_period=0,\n        local_logdir_override=tmp_target,\n    )\n\n    trial1 = MockTrial(trial_id=\"a\", logdir=tmp_source, on_dead_node=True)\n\n    syncer_callback.on_trial_result(iteration=1, trials=[], trial=trial1, result={})\n\n    assert (\n        \"An error occurred when trying to get the node ip where this trial is running\"\n        in caplog.text\n    )\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 100,
        "n_words": 45,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 86,
        "n_ast_nodes": 135,
        "n_identifiers": 25,
        "d_id": 30200,
        "documentation": {
            "docstring": "Check that we catch + log errors when trying syncing with a dead remote node.",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 160836,
        "commit_id": "cafec60a5e28af98fb8798049edd7942720d2d74",
        "repo": "numpy",
        "path": "numpy/testing/tests/test_utils.py",
        "file_name": "test_utils.py",
        "fun_name": "test_array_vs_scalar_strict",
        "commit_message": "ENH: Add strict parameter to assert_array_equal. (#21595)\n\nFixes #9542\r\n\r\nCo-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>",
        "code": "def test_array_vs_scalar_strict(self):\n        \n        a = np.array([1., 1., 1.])\n        b = 1.\n\n        with pytest.raises(AssertionError):\n            assert_array_equal(a, b, strict=True)\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 45,
        "n_ast_nodes": 67,
        "n_identifiers": 11,
        "d_id": 38755,
        "documentation": {
            "docstring": "Test comparing an array with a scalar with strict option.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 161110,
        "commit_id": "b617a87ee40ab384767a27335313c2c65ee094ec",
        "repo": "MockingBird",
        "path": "ppg_extractor/encoder/subsampling.py",
        "file_name": "subsampling.py",
        "fun_name": "__getitem__",
        "commit_message": "Init  ppg extractor and ppg2mel (#375)\n\n* Init  ppg extractor and ppg2mel\r\n\r\n* add preprocess and training\r\n\r\n* FIx known issues\r\n\r\n* Update __init__.py\r\n\r\nAllow to gen audio\r\n\r\n* Fix length issue\r\n\r\n* Fix bug of preparing fid\r\n\r\n* Fix sample issues\r\n\r\n* Add UI usage of PPG-vc",
        "code": "def __getitem__(self, key):\n        \n        if key != -1:\n            raise NotImplementedError(\"Support only `-1` (for `reset_parameters`).\")\n        return self.out[key]\n\n",
        "url": "https://github.com/babysor/MockingBird.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 47,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 5,
        "d_id": 38921,
        "documentation": {
            "docstring": "Subsample x.\n\n        When reset_parameters() is called, if use_scaled_pos_enc is used,\n            return the positioning encoding.\n\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 63347,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "__mul__",
        "commit_message": "upd; format",
        "code": "def __mul__(self, other):\n        \n        if other is Ellipsis:\n            other = (0, None)\n        elif isinstance(other, tuple) and other[:1] == (Ellipsis,):\n            other = ((0, ) + other[1:] + (None,))[:2]\n\n        if isinstance(other, int):\n            minElements, optElements = other, 0\n        elif isinstance(other, tuple):\n            other = tuple(o if o is not Ellipsis else None for o in other)\n            other = (other + (None, None))[:2]\n            if other[0] is None:\n                other = (0, other[1])\n            if isinstance(other[0], int) and other[1] is None:\n                if other[0] == 0:\n                    return ZeroOrMore(self)\n                if other[0] == 1:\n                    return OneOrMore(self)\n                else:\n                    return self * other[0] + ZeroOrMore(self)\n            elif isinstance(other[0], int) and isinstance(other[1], int):\n                minElements, optElements = other\n                optElements -= minElements\n            else:\n                raise TypeError(\"cannot multiply 'ParserElement' and ('%s', '%s') objects\", type(other[0]), type(other[1]))\n        else:\n            raise TypeError(\"cannot multiply 'ParserElement' and '%s' objects\", type(other))\n\n        if minElements < 0:\n            raise ValueError(\"cannot multiply ParserElement by negative value\")\n        if optElements < 0:\n            raise ValueError(\"second tuple value must be greater or equal to first tuple value\")\n        if minElements == optElements == 0:\n            raise ValueError(\"cannot multiply ParserElement by 0 or (0, 0)\")\n\n        if optElements:",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 544,
        "n_words": 169,
        "vocab_size": 86,
        "complexity": 22,
        "nloc": 47,
        "token_counts": 359,
        "n_ast_nodes": 451,
        "n_identifiers": 15,
        "d_id": 13262,
        "documentation": {
            "docstring": "\n        Implementation of * operator, allows use of ``expr * 3`` in place of\n        ``expr + expr + expr``.  Expressions may also me multiplied by a 2-integer\n        tuple, similar to ``{min, max}`` multipliers in regular expressions.  Tuples\n        may also include ``None`` as in:\n         - ``expr*(n, None)`` or ``expr*(n, )`` is equivalent\n              to ``expr*n + ZeroOrMore(expr)``\n              (read as \"at least n instances of ``expr``\")\n         - ``expr*(None, n)`` is equivalent to ``expr*(0, n)``\n              (read as \"0 to n instances of ``expr``\")\n         - ``expr*(None, None)`` is equivalent to ``ZeroOrMore(expr)``\n         - ``expr*(1, None)`` is equivalent to ``OneOrMore(expr)``\n\n        Note that ``expr*(None, n)`` does not raise an exception if\n        more than n exprs exist in the input stream; that is,\n        ``expr*(None, n)`` does not enforce a maximum number of expr\n        occurrences.  If this behavior is desired, then write\n        ``expr*(None, n) + ~expr``\n        ",
            "n_words": 135,
            "vocab_size": 84,
            "n_whitespaces": 280,
            "language": "en"
        }
    },
    {
        "id": 259779,
        "commit_id": "2e3abc2e32eefbfea78f15bcc767ca9bb4911568",
        "repo": "scikit-learn",
        "path": "sklearn/impute/_knn.py",
        "file_name": "_knn.py",
        "fun_name": "_calc_impute",
        "commit_message": "MAINT Fix some typos (#23251)",
        "code": "def _calc_impute(self, dist_pot_donors, n_neighbors, fit_X_col, mask_fit_X_col):\n        \n        # Get donors\n        donors_idx = np.argpartition(dist_pot_donors, n_neighbors - 1, axis=1)[\n            :, :n_neighbors\n        ]\n\n        # Get weight matrix from distance matrix\n        donors_dist = dist_pot_donors[\n            np.arange(donors_idx.shape[0])[:, None], donors_idx\n        ]\n\n        weight_matrix = _get_weights(donors_dist, self.weights)\n\n        # fill nans with zeros\n        if weight_matrix is not None:\n            weight_matrix[np.isnan(weight_matrix)] = 0.0\n\n        # Retrieve donor values and calculate kNN average\n        donors = fit_X_col.take(donors_idx)\n        donors_mask = mask_fit_X_col.take(donors_idx)\n        donors = np.ma.array(donors, mask=donors_mask)\n\n        return np.ma.average(donors, axis=1, weights=weight_matrix).data\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 210,
        "n_words": 72,
        "vocab_size": 56,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 137,
        "n_ast_nodes": 205,
        "n_identifiers": 25,
        "d_id": 75917,
        "documentation": {
            "docstring": "Helper function to impute a single column.\n\n        Parameters\n        ----------\n        dist_pot_donors : ndarray of shape (n_receivers, n_potential_donors)\n            Distance matrix between the receivers and potential donors from\n            training set. There must be at least one non-nan distance between\n            a receiver and a potential donor.\n\n        n_neighbors : int\n            Number of neighbors to consider.\n\n        fit_X_col : ndarray of shape (n_potential_donors,)\n            Column of potential donors from training set.\n\n        mask_fit_X_col : ndarray of shape (n_potential_donors,)\n            Missing mask for fit_X_col.\n\n        Returns\n        -------\n        imputed_values: ndarray of shape (n_receivers,)\n            Imputed values for receiver.\n        ",
            "n_words": 84,
            "vocab_size": 57,
            "n_whitespaces": 231,
            "language": "en"
        }
    },
    {
        "id": 212951,
        "commit_id": "85d664925ad7042896b76b32b518d778aae024e1",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "add_row",
        "commit_message": "Changed all Tab errors to the nicer traceback error popup.  Removed Output Element from the Pack function (that makes the change as real as it gets)",
        "code": "def add_row(self, *args):\n        \n        NumRows = len(self.Rows)  # number of existing rows is our row number\n        CurrentRowNumber = NumRows  # this row's number\n        CurrentRow = []  # start with a blank row and build up\n        # -------------------------  Add the elements to a row  ------------------------- #\n        for i, element in enumerate(args):  # Loop through list of elements and add them to the row\n            if type(element) == list:\n                popup_error_with_traceback('Error creating Tab layout',\n                           'Layout has a LIST instead of an ELEMENT',\n                           'This means you have a badly placed ]',\n                           'The offensive list is:',\n                           element,\n                           'This list will be stripped from your layout')\n                continue\n            elif callable(element) and not isinstance(element, Element):\n                popup_error_with_traceback('Error creating Tab layout',\n                           'Layout has a FUNCTION instead of an ELEMENT',\n                           'This likely means you are missing () from your layout',\n                           'The offensive list is:',\n                           element,\n                           'This item will be stripped from your layout')\n                continue\n            if element.ParentContainer is not None:\n                warnings.warn(\n                    '*** YOU ARE ATTEMPTING TO RESUSE AN ELEMENT IN YOUR LAYOUT! Once placed in a layout, an element cannot be used in another layout. ***',\n                    UserWarning)\n                popup_error_with_traceback('Error creating Tab layout',\n                           'The layout specified has already been used',\n                           'You MUST start witha \"clean\", unused layout every time you create a window',\n                           'The offensive Element = ',\n                           element,\n                           'and has a key = ', element.Key,\n                           'This item will be stripped from your layout',\n                           'Hint - try printing your layout and matching the IDs \"print(layout)\"')\n                continue\n            element.Position = (CurrentRowNumber, i)\n            element.ParentContainer = self\n            CurrentRow.append(element)\n            if element.Key is not None:\n                self.UseDictionary = True\n        # -------------------------  Append the row to list of Rows  ------------------------- #\n        self.Rows.append(CurrentRow)\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 999,
        "n_words": 258,
        "vocab_size": 143,
        "complexity": 7,
        "nloc": 40,
        "token_counts": 166,
        "n_ast_nodes": 288,
        "n_identifiers": 25,
        "d_id": 53532,
        "documentation": {
            "docstring": "\n        Not recommended use call.  Used to add rows of Elements to the Frame Element.\n\n        :param *args: The list of elements for this row\n        :type *args:  List[Element]\n        ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 283202,
        "commit_id": "ab4de1dd70fba866930150e440a03e461a6ca6a8",
        "repo": "OpenBBTerminal",
        "path": "build/pyinstaller/user_agent/base.py",
        "file_name": "base.py",
        "fun_name": "build_system_components",
        "commit_message": "Create a packaged app bundle with Pyinstaller (#1525)\n\n* Add dashboard widget assets\r\n\r\n* Add ipywidgets and ipyflex to project\r\n\r\n* Add currencies dashboard notebook\r\n\r\n* Update docs and docstrings\r\n\r\n* Add pyinstaller to project deps\r\n\r\n* Add pyinstaller artifacts to gitignore\r\n\r\n* Fix linter errors in terminal.py\r\n\r\n* Update cspell hook and action with a pyinstaller specific word\r\n\r\n* Add pyinstaller specfile and artifacts\r\n\r\n* Add splashscreen image\r\n\r\n* Add app icon\r\n\r\n* adding splash screen support to terminal.spec and terminal.py\r\n\r\n* Restore the conda env build files\r\n\r\n* Sync deps\r\n\r\n* Add border to the splashscreen image\r\n\r\n* Clean up terminal launcher\r\n\r\n* Add support for default feature flags in packages apps\r\n\r\n* Fix types and linting\r\n\r\n* Add splashscreen management to app bootup\r\n\r\n* Check prediction feature flag when entering crypto/pred\r\n\r\n* Update pyinstaller spec file\r\n\r\n* fix .spec file to work for splash and icon - removed the \"..\"\r\n\r\n* Allows to export when using installer (#1568)\r\n\r\n* fix export for packaged apps\r\n\r\n* fix filename\r\n\r\n* Git : replace commit_hash when it is set in config_terminal\r\n\r\n* Add update of the git commit hash in gtff default during build\r\n\r\n* Add packaged app name and feature flag to logs\r\n\r\n* Add platform specific icon assignment\r\n\r\n* Add macOS build assets\r\n\r\n* Add tensorflow to hidden imports\r\n\r\n* Move LOGGING_COMMIT_HASH to gtff\r\n\r\n* Adding files/folders needed to .spec  and pyinstaller folder. This will make certain commands work again.\r\n\r\n* Linting\r\n\r\n* Workflow : ignore ./build/pyinstaller from codespell\r\n\r\n* Workflow : exclude ./build/pyinstaller from flake8\r\n\r\n* Poetry + Workflow : add types-six\r\n\r\n* Pyinstaller : remove property_cached, user_agent and vaderSentiment\r\n\r\n* Revert \"Pyinstaller : remove property_cached, user_agent and vaderSentiment\"\r\n\r\nThis reverts commit dbb3e2b81086f97819ebd21457148c7160a4d703.\r\n\r\n* Clean up local paths in specfile\r\n\r\n* Validate deps have correct Jinja version (they do)\r\n\r\n* Fix logging commit hash to be set correctly for the logger to see it\r\n\r\nCo-authored-by: Andrew <andrew.kenreich@gmail.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>",
        "code": "def build_system_components(device_type, os_id, navigator_id):\n    \n\n    if os_id == \"win\":\n        platform_version = randomizer.choice(OS_PLATFORM[\"win\"])\n        cpu = randomizer.choice(OS_CPU[\"win\"])\n        if cpu:\n            platform = f\"{platform_version}; {cpu}\"\n        else:\n            platform = platform_version\n        res = {\n            \"platform_version\": platform_version,\n            \"platform\": platform,\n            \"ua_platform\": platform,\n            \"oscpu\": platform,\n        }\n    elif os_id == \"linux\":\n        cpu = randomizer.choice(OS_CPU[\"linux\"])\n        platform_version = randomizer.choice(OS_PLATFORM[\"linux\"])\n        platform = f\"{platform_version} {cpu}\"\n        res = {\n            \"platform_version\": platform_version,\n            \"platform\": platform,\n            \"ua_platform\": platform,\n            \"oscpu\": \"Linux %s\" % cpu,\n        }\n    elif os_id == \"mac\":\n        cpu = randomizer.choice(OS_CPU[\"mac\"])\n        platform_version = randomizer.choice(OS_PLATFORM[\"mac\"])\n        platform = platform_version\n        if navigator_id == \"chrome\":\n            platform = fix_chrome_mac_platform(platform)\n        res = {\n            \"platform_version\": platform_version,\n            \"platform\": \"MacIntel\",\n            \"ua_platform\": platform,\n            \"oscpu\": \"Intel Mac OS X %s\" % platform.split(\" \")[-1],\n        }\n    elif os_id == \"android\":\n        assert navigator_id in (\"firefox\", \"chrome\")\n        assert device_type in (\"smartphone\", \"tablet\")\n        platform_version = randomizer.choice(OS_PLATFORM[\"android\"])\n        if navigator_id == \"firefox\":\n            if device_type == \"smartphone\":\n                ua_platform = \"%s; Mobile\" % platform_version\n            elif device_type == \"tablet\":\n                ua_platform = \"%s; Tablet\" % platform_version\n        elif navigator_id == \"chrome\":\n            device_id = randomizer.choice(SMARTPHONE_DEV_IDS)\n            ua_platform = f\"Linux; {platform_version}; {device_id}\"\n        oscpu = \"Linux %s\" % randomizer.choice(OS_CPU[\"android\"])\n        res = {\n            \"platform_version\": platform_version,\n            \"ua_platform\": ua_platform,\n            \"platform\": oscpu,\n            \"oscpu\": oscpu,\n        }\n    return res\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 653,
        "n_words": 177,
        "vocab_size": 75,
        "complexity": 11,
        "nloc": 56,
        "token_counts": 303,
        "n_ast_nodes": 572,
        "n_identifiers": 18,
        "d_id": 84466,
        "documentation": {
            "docstring": "\n    For given os_id build random platform and oscpu\n    components\n\n    Returns dict {platform_version, platform, ua_platform, oscpu}\n\n    platform_version is OS name used in different places\n    ua_platform goes to navigator.platform\n    platform is used in building navigator.userAgent\n    oscpu goes to navigator.oscpu\n    ",
            "n_words": 37,
            "vocab_size": 30,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 10637,
        "commit_id": "eea04c36350e86b3b0f16217cd37e630bfb81b57",
        "repo": "jina",
        "path": "jina/peapods/pods/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "update_pea_args",
        "commit_message": "feat: support jinahub+sandbox (#4130)",
        "code": "def update_pea_args(self):\n        \n        if isinstance(self.args, Dict):\n            # This is used when a Pod is created in a remote context, where peas & their connections are already given.\n            self.peas_args = self.args\n        else:\n            self.peas_args = self._parse_args(self.args)\n\n        if self.is_sandbox:\n            host, port = HubIO.deploy_public_sandbox(getattr(self.args, 'uses', ''))\n            self.first_pea_args.host = host\n            self.first_pea_args.port_in = port\n            self.peas_args['head'].host = host\n            self.peas_args['head'].port_in = port\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 169,
        "n_words": 53,
        "vocab_size": 40,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 95,
        "n_ast_nodes": 159,
        "n_identifiers": 15,
        "d_id": 1886,
        "documentation": {
            "docstring": " Update args of all its peas based on Pod args. Including head/tail",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 262333,
        "commit_id": "dbe9da7f15544b83043f481a99e5bcb23e002dc9",
        "repo": "TTS",
        "path": "TTS/tts/models/vits.py",
        "file_name": "vits.py",
        "fun_name": "voice_conversion",
        "commit_message": "Add Voice conversion inference support (#1337)\n\n* Add support for voice conversion inference\r\n\r\n* Cache d_vectors_by_speaker for fast inference using a bigger speakers.json\r\n\r\n* Rebase bug fix\r\n\r\n* Use the average d-vector for inference",
        "code": "def voice_conversion(self, y, y_lengths, speaker_cond_src, speaker_cond_tgt):\n        \n        assert self.num_speakers > 0, \"num_speakers have to be larger than 0.\"\n        # speaker embedding\n        if self.args.use_speaker_embedding and not self.args.use_d_vector_file:\n            g_src = self.emb_g(speaker_cond_src).unsqueeze(-1)\n            g_tgt = self.emb_g(speaker_cond_tgt).unsqueeze(-1)\n        elif not self.args.use_speaker_embedding and self.args.use_d_vector_file:\n            g_src = F.normalize(speaker_cond_src).unsqueeze(-1)\n            g_tgt = F.normalize(speaker_cond_tgt).unsqueeze(-1)\n        else:\n            raise RuntimeError(\" [!] Voice conversion is only supported on multi-speaker models.\")\n\n        z, _, _, y_mask = self.posterior_encoder(y.transpose(1, 2), y_lengths, g=g_src)\n        z_p = self.flow(z, y_mask, g=g_src)\n        z_hat = self.flow(z_p, y_mask, g=g_tgt, reverse=True)\n        o_hat = self.waveform_decoder(z_hat * y_mask, g=g_tgt)\n        return o_hat, y_mask, (z, z_p, z_hat)\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 218,
        "n_words": 86,
        "vocab_size": 67,
        "complexity": 5,
        "nloc": 15,
        "token_counts": 198,
        "n_ast_nodes": 303,
        "n_identifiers": 29,
        "d_id": 77189,
        "documentation": {
            "docstring": "Forward pass for voice conversion\n\n        TODO: create an end-point for voice conversion\n\n        Args:\n            y (Tensor): Reference spectrograms. Tensor of shape [B, T, C]\n            y_lengths (Tensor): Length of each reference spectrogram. Tensor of shape [B]\n            speaker_cond_src (Tensor): Reference speaker ID. Tensor of shape [B,]\n            speaker_cond_tgt (Tensor): Target speaker ID. Tensor of shape [B,]\n        ",
            "n_words": 52,
            "vocab_size": 32,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 46541,
        "commit_id": "2f5a567977e1219cab16c2548825a1b9eba07ab3",
        "repo": "airflow",
        "path": "airflow/migrations/versions/0106_909884dea523_update_migration_for_fab_tables_to_add_missing_constraints.py",
        "file_name": "0106_909884dea523_update_migration_for_fab_tables_to_add_missing_constraints.py",
        "fun_name": "upgrade",
        "commit_message": "Use Airflow.Base.metadata in FAB models (#22353)\n\nSince FAB models are now in airflow, it makes sense to monitor changes\r\nin them. Therefore we use Airflow.models.base.Base.metadata for FAB models",
        "code": "def upgrade():\n    \n    conn = op.get_bind()\n    if conn.dialect.name == 'sqlite':\n        op.execute('PRAGMA foreign_keys=OFF')\n        with op.batch_alter_table('ab_view_menu', schema=None) as batch_op:\n            batch_op.create_unique_constraint(batch_op.f('ab_view_menu_name_uq'), ['name'])\n        op.execute('PRAGMA foreign_keys=ON')\n    elif conn.dialect.name == 'mysql':\n        with op.batch_alter_table('ab_register_user', schema=None) as batch_op:\n            batch_op.alter_column('username', existing_type=sa.String(256), nullable=False)\n            batch_op.alter_column('email', existing_type=sa.String(256), nullable=False)\n        with op.batch_alter_table('ab_user', schema=None) as batch_op:\n            batch_op.alter_column('username', existing_type=sa.String(256), nullable=False)\n            batch_op.alter_column('email', existing_type=sa.String(256), nullable=False)\n    elif conn.dialect.name == 'mssql':\n        with op.batch_alter_table('ab_register_user') as batch_op:\n            # Drop the unique constraint on username and email\n            constraints = get_mssql_table_constraints(conn, 'ab_register_user')\n            for k, _ in constraints.get('UNIQUE').items():\n                batch_op.drop_constraint(k, type_='unique')\n            batch_op.alter_column('username', existing_type=sa.String(256), nullable=False)\n            batch_op.create_unique_constraint(None, ['username'])\n            batch_op.alter_column('email', existing_type=sa.String(256), nullable=False)\n        with op.batch_alter_table('ab_user') as batch_op:\n            # Drop the unique constraint on username and email\n            constraints = get_mssql_table_constraints(conn, 'ab_user')\n            for k, _ in constraints.get('UNIQUE').items():\n                batch_op.drop_constraint(k, type_='unique')\n            batch_op.alter_column('username', existing_type=sa.String(256), nullable=False)\n            batch_op.create_unique_constraint(None, ['username'])\n            batch_op.alter_column('email', existing_type=sa.String(256), nullable=False)\n            batch_op.create_unique_constraint(None, ['email'])\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 408,
        "n_words": 116,
        "vocab_size": 53,
        "complexity": 6,
        "nloc": 30,
        "token_counts": 378,
        "n_ast_nodes": 652,
        "n_identifiers": 25,
        "d_id": 8919,
        "documentation": {
            "docstring": "Apply Update migration for FAB tables to add missing constraints",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 47758,
        "commit_id": "197cff3194e855b9207c3c0da8ae093a0d5dda55",
        "repo": "airflow",
        "path": "airflow/models/taskmixin.py",
        "file_name": "taskmixin.py",
        "fun_name": "_iter_all_mapped_downstreams",
        "commit_message": "Ensure TaskMap only checks \"relevant\" dependencies (#23053)\n\nWhen looking for \"mapped dependants\" of a task, we only want a task if\r\nit not only is a direct downstream of the task, but also it actually\r\n\"uses\" the task's pushed XCom for task mapping. So we need to peek into\r\nthe mapped downstream task's expansion kwargs, and only count it as a\r\nmapped dependant if the upstream is referenced there.",
        "code": "def _iter_all_mapped_downstreams(self) -> Iterator[\"MappedOperator\"]:\n        \n        from airflow.models.mappedoperator import MappedOperator\n        from airflow.utils.task_group import TaskGroup\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 10,
        "complexity": 6,
        "nloc": 28,
        "token_counts": 82,
        "n_ast_nodes": 44,
        "n_identifiers": 10,
        "d_id": 9247,
        "documentation": {
            "docstring": "Return mapped nodes that are direct dependencies of the current task.\n\n        For now, this walks the entire DAG to find mapped nodes that has this\n        current task as an upstream. We cannot use ``downstream_list`` since it\n        only contains operators, not task groups. In the future, we should\n        provide a way to record an DAG node's all downstream nodes instead.\n\n        Note that this does not guarantee the returned tasks actually use the\n        current task for task mapping, but only checks those task are mapped\n        operators, and are downstreams of the current task.\n\n        To get a list of tasks that uses the current task for task mapping, use\n        :meth:`iter_mapped_dependants` instead.\n        ",
            "n_words": 108,
            "vocab_size": 65,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 269225,
        "commit_id": "56b75d030cd9c3e3fde0ddf1f908436e6a5be3d6",
        "repo": "keras",
        "path": "keras/utils/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "_rescale_dataset_split_sizes",
        "commit_message": "adds test case for fractional size with tuple of numpy arrays in different shape",
        "code": "def _rescale_dataset_split_sizes(left_size,right_size,total_length):\n  \n\n  left_size_type = type(left_size)\n  right_size_type = type(right_size)\n\n  if ((left_size is not None and left_size_type not in [int,float]) and\n      (right_size is not None and right_size_type not in [int,float])):\n    raise TypeError('Invalid `left_size` and `right_size` Types. '\n                     'Expected: integer or float or None. '\n                     f' Received: {left_size_type} and {right_size_type}')\n\n  if left_size is not None and left_size_type not in [int,float]:\n    raise TypeError(f'Invalid `left_size` Type. Received: {left_size_type}.  '\n                     ' Expected: int or float or None')\n\n  if right_size is not None and right_size_type not in [int,float]:\n    raise TypeError(f'Invalid `right_size` Type. Received: {right_size_type}.'\n                    ' Expected: int or float or None')\n\n  if left_size == 0 and right_size == 0:\n    raise ValueError('Invalid `left_size` and `right_size` values. '\n                     'You must specify either `left_size` or `right_size` with '\n                     f'value greater than 0 and less than {total_length} '\n                      'or a float within range [0,1] to split the dataset'\n                      f'Received: `left_size`={left_size}, '\n                      f'`right_size`={right_size}')\n\n  if (left_size_type == int\n      and (left_size <= 0 or left_size>= total_length)\n      or left_size_type == float\n      and (left_size <= 0 or left_size>= 1) ):\n    raise ValueError('`left_size` should be either a positive integer '\n                     f'and smaller than {total_length} or a float '\n                     'within the range `[0, 1]`. Received: left_size='\n                     f'{left_size}')\n\n  if (right_size_type == int\n      and (right_size <= 0 or right_size>= total_length)\n      or right_size_type == float\n      and (right_size <= 0 or right_size>= 1)):\n    raise ValueError('`right_size` should be either a positive integer '\n                     f'and smaller than {total_length} or '\n                     'a float within the range `[0, 1]`. Received: right_size='\n                     f'{right_size}')\n\n  if right_size_type == left_size_type == float and right_size + left_size > 1:\n    raise ValueError('sum of `left_size` and `right_size`'\n                     ' should be within `[0,1]`.'\n                    f'Received: {right_size + left_size} ,'\n                    'reduce the `left_size` or `right_size`')\n\n  if left_size_type == float:\n    left_size = round(left_size*total_length)\n  elif left_size_type == int:\n    left_size = float(left_size)\n\n  if right_size_type == float:\n    right_size = round(right_size*total_length)\n  elif right_size_type == int:\n    right_size = float(right_size)\n\n\n  if left_size is None:\n    left_size = total_length - right_size\n  elif right_size is None:\n    right_size = total_length - left_size\n\n  if left_size + right_size > total_length:\n    raise ValueError('The sum of `left_size` and `right_size`'\n                     f' should be smaller than the samples {total_length} '\n                     ' reduce `left_size` or `right_size` ' )\n\n\n  for split,side in [(left_size,'left'),(right_size,'right')]:\n    if split == 0:\n      raise ValueError(f'with dataset of length={total_length} '\n                      '`left_size`={left_size} and `right_size`={right_size}, '\n                      f'resulting {side} dataset split will be empty. '\n                      'Adjust any of the aforementioned parameters')\n\n  left_size,right_size = int(left_size) ,int(right_size)\n  return left_size,right_size\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 951,
        "n_words": 382,
        "vocab_size": 142,
        "complexity": 34,
        "nloc": 66,
        "token_counts": 369,
        "n_ast_nodes": 671,
        "n_identifiers": 14,
        "d_id": 79956,
        "documentation": {
            "docstring": "Helper function to rescale  left_size/right_size args relative\n  to dataset's size\n  ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 143364,
        "commit_id": "dc7ed086a5038775e378b32cb31fb4a79f418dd9",
        "repo": "ray",
        "path": "python/ray/train/trainer.py",
        "file_name": "trainer.py",
        "fun_name": "best_checkpoint_path",
        "commit_message": "[AIR] More checkpoint configurability, `Result` extension (#25943)\n\nThis PR:\r\n* Allows the user to set `keep_checkpoints_num` and `checkpoint_score_attr` in `RunConfig` using the `CheckpointStrategy` dataclass\r\n* Adds two new fields to the `Result` object - `best_checkpoints` - a list of saved best checkpoints as determined by `CheckpointingConfig`.",
        "code": "def best_checkpoint_path(self) -> Optional[Path]:\n        \n        return self.checkpoint_manager.best_checkpoint_path\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 17,
        "n_ast_nodes": 29,
        "n_identifiers": 5,
        "d_id": 32968,
        "documentation": {
            "docstring": "Path to the best persisted checkpoint from the latest run.\n\n        \"Best\" is defined by the input ``CheckpointConfig``.\n        Default behavior is to return the most recent checkpoint.\n\n        Returns ``None`` if ``run()`` has not been called or if\n        ``train.save_checkpoint()`` has not been called from ``train_func``\n        within the most recent call to ``run``.\n        ",
            "n_words": 50,
            "vocab_size": 35,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 223628,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_policybase.py",
        "file_name": "_policybase.py",
        "fun_name": "clone",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def clone(self, **kw):\n        \n        newpolicy = self.__class__.__new__(self.__class__)\n        for attr, value in self.__dict__.items():\n            object.__setattr__(newpolicy, attr, value)\n        for attr, value in kw.items():\n            if not hasattr(self, attr):\n                raise TypeError(\n                    \"{!r} is an invalid keyword argument for {}\".format(\n                        attr, self.__class__.__name__))\n            object.__setattr__(newpolicy, attr, value)\n        return newpolicy\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 165,
        "n_words": 40,
        "vocab_size": 29,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 92,
        "n_ast_nodes": 144,
        "n_identifiers": 16,
        "d_id": 57018,
        "documentation": {
            "docstring": "Return a new instance with specified attributes changed.\n\n        The new instance has the same attribute values as the current object,\n        except for the changes passed in as keyword arguments.\n\n        ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 153543,
        "commit_id": "97769988a6f19e4b76f34238c97bf159ee7626a5",
        "repo": "modin",
        "path": "modin/core/io/column_stores/column_store_dispatcher.py",
        "file_name": "column_store_dispatcher.py",
        "fun_name": "call_deploy",
        "commit_message": "REFACTOR-#3853: interacting with Dask interface through 'DaskWrapper' class (#3854)\n\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nCo-authored-by: Dmitry Chigarev <dchigarev@users.noreply.github.com>\r\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Anatoly Myachev <anatoly.myachev@intel.com>",
        "code": "def call_deploy(cls, fname, col_partitions, **kwargs):\n        \n        return np.array(\n            [\n                cls.deploy(\n                    cls.parse,\n                    num_returns=NPartitions.get() + 2,\n                    fname=fname,\n                    columns=cols,\n                    num_splits=NPartitions.get(),\n                    **kwargs,\n                )\n                for cols in col_partitions\n            ]\n        ).T\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 226,
        "n_words": 24,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 65,
        "n_ast_nodes": 96,
        "n_identifiers": 16,
        "d_id": 35432,
        "documentation": {
            "docstring": "\n        Deploy remote tasks to the workers with passed parameters.\n\n        Parameters\n        ----------\n        fname : str, path object or file-like object\n            Name of the file to read.\n        col_partitions : list\n            List of arrays with columns names that should be read\n            by each partition.\n        **kwargs : dict\n            Parameters of deploying read_* function.\n\n        Returns\n        -------\n        np.ndarray\n            Array with references to the task deploy result for each partition.\n        ",
            "n_words": 63,
            "vocab_size": 49,
            "n_whitespaces": 189,
            "language": "en"
        }
    },
    {
        "id": 160136,
        "commit_id": "729ad4f92420231e2a7009b3223c6c7620b8b808",
        "repo": "numpy",
        "path": "numpy/f2py/tests/test_f2py2e.py",
        "file_name": "test_f2py2e.py",
        "fun_name": "test_nowrapfunc",
        "commit_message": "TST: Initialize f2py2e tests of the F2PY CLI (#20668)\n\nIncreases F2PY coverage by around 15 percent. For the CLI itself it covers the major features (around 70 percent), with the exception of mostly numpy.distutils stuff.\r\n\r\nMore importantly, sets the groundwork for #20056, in that passing the same testsuite should indicate feature parity.",
        "code": "def test_nowrapfunc(capfd, hello_world_f90, monkeypatch):\n    \n    ipath = Path(hello_world_f90)\n    mname = \"blah\"\n    monkeypatch.setattr(sys, \"argv\",\n                        f'f2py -m {mname} {ipath} --no-wrap-functions'.split())\n\n    with util.switchdir(ipath.parent):\n        f2pycli()\n        out, _ = capfd.readouterr()\n        assert r\"Fortran 77 wrappers are saved to\" not in out\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 93,
        "n_words": 34,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 62,
        "n_ast_nodes": 115,
        "n_identifiers": 17,
        "d_id": 38508,
        "documentation": {
            "docstring": "Ensures that fortran subroutine wrappers for F77 can be disabled\n\n    CLI :: --no-wrap-functions\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 265983,
        "commit_id": "484efdaf75f267a43f9321b938fda1bc967b9e53",
        "repo": "netbox",
        "path": "netbox/extras/views.py",
        "file_name": "views.py",
        "fun_name": "get_queryset",
        "commit_message": "Closes #9623: Implement saved filters (#10801)\n\n* Initial work on saved filters\r\n\r\n* Return only enabled/shared filters\r\n\r\n* Add tests\r\n\r\n* Clean up filtering of usable SavedFilters",
        "code": "def get_queryset(self, request):\n        \n        queryset = SavedFilter.objects.all()\n        user = request.user\n        if user.is_superuser:\n            return queryset\n        if user.is_anonymous:\n            return queryset.filter(shared=True)\n        return queryset.filter(\n            Q(shared=True) | Q(user=user)\n        )\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 105,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 62,
        "n_ast_nodes": 101,
        "n_identifiers": 13,
        "d_id": 78254,
        "documentation": {
            "docstring": "\n        Return only shared SavedFilters, or those owned by the current user, unless\n        this is a superuser.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 155995,
        "commit_id": "8a6f6a7b95762df4e44bc4d82ce33a7c388a0676",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "to_bag",
        "commit_message": "Move Bag.map_partitions to Blockwise (#8646)\n\n1. Adds `format=\"frame\"` option to `dataframe.io.to_bag` (effectively returning a zero-copy view of the same dask graph, that no-longer tracks meta/divisions)\r\n2. Revises `Bag.map_partitions` to use `blockwise` (and to support the `token=` option)\r\n3. Modifies the ACA code path to use a `Bag.map_partitions` for any blockwise operations where partitions may loose \"dataframe-like\" properties.\r\n\r\nThis represents an alternative to using `map_partitions` incorrectly in ACA. It is also an alternative to the low-level `blockwise` API.",
        "code": "def to_bag(self, index=False, format=\"tuple\"):\n        \n        from .io import to_bag\n\n        return to_bag(self, index, format)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 33,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 47,
        "n_identifiers": 5,
        "d_id": 36500,
        "documentation": {
            "docstring": "Convert to a dask Bag of tuples of each row.\n\n        Parameters\n        ----------\n        index : bool, optional\n            If True, the index is included as the first element of each tuple.\n            Default is False.\n        format : {\"tuple\", \"dict\", \"frame\"}, optional\n            Whether to return a bag of tuples, dictionaries, or\n            dataframe-like objects. Default is \"tuple\". If \"frame\",\n            the original partitions of ``df`` will not be transformed\n            in any way.\n        ",
            "n_words": 66,
            "vocab_size": 50,
            "n_whitespaces": 167,
            "language": "en"
        }
    },
    {
        "id": 253602,
        "commit_id": "19aba1f059efad45e1466d47954b2cf54d45b106",
        "repo": "d2l-en",
        "path": "d2l/mxnet.py",
        "file_name": "mxnet.py",
        "fun_name": "accuracy",
        "commit_message": "simplify d2l lib",
        "code": "def accuracy(self, Y_hat, Y, averaged=True):\n        \n        Y_hat = d2l.reshape(Y_hat, (-1, Y_hat.shape[-1]))\n        preds = d2l.astype(d2l.argmax(Y_hat, axis=1), Y.dtype)\n        compare = d2l.astype(preds == d2l.reshape(Y, -1), d2l.float32)\n        return d2l.reduce_mean(compare) if averaged else compare\n",
        "url": "https://github.com/d2l-ai/d2l-en.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 63,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 89,
        "n_ast_nodes": 133,
        "n_identifiers": 16,
        "d_id": 74149,
        "documentation": {
            "docstring": "Compute the number of correct predictions.\n\n        Defined in :numref:`sec_classification`",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 126370,
        "commit_id": "545c51609f0f55b41cf99cec95a9c21bee6846de",
        "repo": "ray",
        "path": "python/ray/serve/_private/router.py",
        "file_name": "router.py",
        "fun_name": "_reset_replica_iterator",
        "commit_message": "[Serve] ServeHandle detects ActorError and drop replicas from target group (#26685)",
        "code": "def _reset_replica_iterator(self):\n        \n        replicas = list(self.in_flight_queries.keys())\n        random.shuffle(replicas)\n        self.replica_iterator = itertools.cycle(replicas)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 37,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 59,
        "n_identifiers": 11,
        "d_id": 28152,
        "documentation": {
            "docstring": "Reset the iterator used to load balance replicas.\n\n        This call is expected to be called after the replica membership has\n        been updated. It will shuffle the replicas randomly to avoid multiple\n        handle sending requests in the same order.\n        ",
            "n_words": 38,
            "vocab_size": 33,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 45285,
        "commit_id": "900bad1c67654252196bb095a2a150a23ae5fc9a",
        "repo": "airflow",
        "path": "airflow/providers/oracle/hooks/oracle.py",
        "file_name": "oracle.py",
        "fun_name": "test_connection",
        "commit_message": "Fix oracle test connection (#21699)",
        "code": "def test_connection(self):\n        \n        status, message = False, ''\n        try:\n            if self.get_first(\"select 1 from dual\"):\n                status = True\n                message = 'Connection successfully tested'\n        except Exception as e:\n            status = False\n            message = str(e)\n\n        return status, message\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 132,
        "n_words": 34,
        "vocab_size": 25,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 47,
        "n_ast_nodes": 87,
        "n_identifiers": 8,
        "d_id": 8538,
        "documentation": {
            "docstring": "Tests the connection by executing a select 1 from dual query",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 46296,
        "commit_id": "3182ba2f402656bfc7d7777f1678161ec5a9cf79",
        "repo": "airflow",
        "path": "airflow/www/utils.py",
        "file_name": "utils.py",
        "fun_name": "task_instance_link",
        "commit_message": "Add map_index support to all task instance-related views (#22272)\n\nCo-authored-by: Ash Berlin-Taylor <ash@apache.org>\r\nCo-authored-by: Brent Bovenzi <brent.bovenzi@gmail.com>",
        "code": "def task_instance_link(attr):\n    \n    dag_id = attr.get('dag_id')\n    task_id = attr.get('task_id')\n    execution_date = attr.get('dag_run.execution_date') or attr.get('execution_date') or timezone.utcnow()\n    url = url_for(\n        'Airflow.task',\n        dag_id=dag_id,\n        task_id=task_id,\n        execution_date=execution_date.isoformat(),\n        map_index=attr.get('map_index', -1),\n    )\n    url_root = url_for(\n        'Airflow.graph', dag_id=dag_id, root=task_id, execution_date=execution_date.isoformat()\n    )\n    return Markup(\n        \n    ).format(url=url, task_id=task_id, url_root=url_root)\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 118,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 25,
        "token_counts": 120,
        "n_ast_nodes": 200,
        "n_identifiers": 16,
        "d_id": 8847,
        "documentation": {
            "docstring": "Generates a URL to the Graph view for a TaskInstance.\n        <span style=\"white-space: nowrap;\">\n        <a href=\"{url}\">{task_id}</a>\n        <a href=\"{url_root}\" title=\"Filter on this task and upstream\">\n        <span class=\"material-icons\" style=\"margin-left:0;\"\n            aria-hidden=\"true\">filter_alt</span>\n        </a>\n        </span>\n        ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 89,
            "language": "en"
        }
    },
    {
        "id": 44969,
        "commit_id": "0ebd6428e6b484790bfbbe1b8687ef4e6cae10e9",
        "repo": "airflow",
        "path": "airflow/migrations/versions/c306b5b5ae4a_switch_xcom_table_to_use_run_id.py",
        "file_name": "c306b5b5ae4a_switch_xcom_table_to_use_run_id.py",
        "fun_name": "downgrade",
        "commit_message": "Switch XCom implementation to use run_id (#20975)",
        "code": "def downgrade():\n    \n    op.create_table(\"__airflow_tmp_xcom\", *_get_old_xcom_columns())\n\n    xcom = Table(\"xcom\", metadata, *_get_new_xcom_columns())\n    query = select(\n        [\n            xcom.c.key,\n            xcom.c.value,\n            xcom.c.timestamp,\n            xcom.c.task_id,\n            xcom.c.dag_id,\n            dagrun.c.execution_date,\n        ],\n    ).select_from(\n        xcom.join(\n            dagrun,\n            xcom.c.dag_id == dagrun.c.dag_id,\n            xcom.c.run_id == dagrun.c.run_id,\n        ),\n    )\n    op.execute(f\"INSERT INTO __airflow_tmp_xcom {query.selectable.compile(op.get_bind())}\")\n\n    op.drop_table(\"xcom\")\n    op.rename_table(\"__airflow_tmp_xcom\", \"xcom\")\n    op.create_primary_key(\"xcom_pkey\", \"xcom\", [\"dag_id\", \"task_id\", \"execution_date\", \"key\"])\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 201,
        "n_words": 44,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 148,
        "n_ast_nodes": 264,
        "n_identifiers": 28,
        "d_id": 8429,
        "documentation": {
            "docstring": "Switch XCom table back to use execution_date.\n\n    Basically an inverse operation.\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 242978,
        "commit_id": "46a80d144a16836af304a7aaa8e620962d91ac23",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "remap_palette",
        "commit_message": "Update transparency when remapping the palette",
        "code": "def remap_palette(self, dest_map, source_palette=None):\n        \n        from . import ImagePalette\n\n        if self.mode not in (\"L\", \"P\"):\n            raise ValueError(\"illegal image mode\")\n\n        if source_palette is None:\n            if self.mode == \"P\":\n                self.load()\n                source_palette = self.im.getpalette(\"RGB\")[:768]\n            else:  # L-mode\n                source_palette = bytearray(i // 3 for i in range(768))\n\n        palette_bytes = b\"\"\n        new_positions = [0] * 256\n\n        # pick only the used colors from the palette\n        for i, oldPosition in enumerate(dest_map):\n            palette_bytes += source_palette[oldPosition * 3 : oldPosition * 3 + 3]\n            new_positions[oldPosition] = i\n\n        # replace the palette color id of all pixel with the new id\n\n        # Palette images are [0..255], mapped through a 1 or 3\n        # byte/color map.  We need to remap the whole image\n        # from palette 1 to palette 2. New_positions is\n        # an array of indexes into palette 1.  Palette 2 is\n        # palette 1 with any holes removed.\n\n        # We're going to leverage the convert mechanism to use the\n        # C code to remap the image from palette 1 to palette 2,\n        # by forcing the source image into 'L' mode and adding a\n        # mapping 'L' mode palette, then converting back to 'L'\n        # sans palette thus converting the image bytes, then\n        # assigning the optimized RGB palette.\n\n        # perf reference, 9500x4000 gif, w/~135 colors\n        # 14 sec prepatch, 1 sec postpatch with optimization forced.\n\n        mapping_palette = bytearray(new_positions)\n\n        m_im = self.copy()\n        m_im.mode = \"P\"\n\n        m_im.palette = ImagePalette.ImagePalette(\"RGB\", palette=mapping_palette * 3)\n        # possibly set palette dirty, then\n        # m_im.putpalette(mapping_palette, 'L')  # converts to 'P'\n        # or just force it.\n        # UNDONE -- this is part of the general issue with palettes\n        m_im.im.putpalette(\"RGB;L\", m_im.palette.tobytes())\n\n        m_im = m_im.convert(\"L\")\n\n        # Internally, we require 768 bytes for a palette.\n        new_palette_bytes = palette_bytes + (768 - len(palette_bytes)) * b\"\\x00\"\n        m_im.putpalette(new_palette_bytes)\n        m_im.palette = ImagePalette.ImagePalette(\"RGB\", palette=palette_bytes)\n\n        if \"transparency\" in self.info:\n            m_im.info[\"transparency\"] = new_positions[self.info[\"transparency\"]]\n\n        return m_im\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 680,
        "n_words": 299,
        "vocab_size": 177,
        "complexity": 6,
        "nloc": 27,
        "token_counts": 231,
        "n_ast_nodes": 425,
        "n_identifiers": 27,
        "d_id": 69947,
        "documentation": {
            "docstring": "\n        Rewrites the image to reorder the palette.\n\n        :param dest_map: A list of indexes into the original palette.\n           e.g. ``[1,0]`` would swap a two item palette, and ``list(range(256))``\n           is the identity transform.\n        :param source_palette: Bytes or None.\n        :returns:  An :py:class:`~PIL.Image.Image` object.\n\n        ",
            "n_words": 40,
            "vocab_size": 35,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 178264,
        "commit_id": "aa36f4f70f7a6290f74059a6e13fd89dfd3e6ef8",
        "repo": "label-studio",
        "path": "label_studio/projects/models.py",
        "file_name": "models.py",
        "fun_name": "_update_tasks_counters_and_is_labeled",
        "commit_message": "fix: DEV-3798: Improve performance for _rearrange_overlap_cohort (#3271)\n\n* fix: DEV-3798: Improve performance for _rearrange_overlap_cohort",
        "code": "def _update_tasks_counters_and_is_labeled(self, queryset, from_scratch=True):\n        \n        queryset = make_queryset_from_iterable(queryset)\n        objs = self._update_tasks_counters(queryset, from_scratch)\n        bulk_update_stats_project_tasks(queryset, self)\n        return objs\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 50,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 36,
        "n_ast_nodes": 57,
        "n_identifiers": 8,
        "d_id": 42640,
        "documentation": {
            "docstring": "\n        Update tasks counters and is_labeled in a single operation\n        :param queryset: Tasks to update queryset\n        :param from_scratch: Skip calculated tasks\n        :return: Count of updated tasks\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 307672,
        "commit_id": "5e338d21665cb04f66fcebd9376cdda389c30c01",
        "repo": "core",
        "path": "homeassistant/components/automation/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "async_enable",
        "commit_message": "Improve type hints in automation (#78368)\n\n* Improve type hints in automation\r\n\r\n* Apply suggestion\r\n\r\n* Apply suggestion\r\n\r\n* Apply suggestion\r\n\r\n* Add Protocol for IfAction\r\n\r\n* Use ConfigType for IfAction\r\n\r\n* Rename variable",
        "code": "async def async_enable(self) -> None:\n        \n        if self._is_enabled:\n            return\n\n        self._is_enabled = True\n\n        # HomeAssistant is starting up\n        if self.hass.state != CoreState.not_running:\n            self._async_detach_triggers = await self._async_attach_triggers(False)\n            self.async_write_ha_state()\n            return\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 105,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 67,
        "n_ast_nodes": 82,
        "n_identifiers": 10,
        "d_id": 106440,
        "documentation": {
            "docstring": "Enable this automation entity.\n\n        This method is a coroutine.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 260080,
        "commit_id": "effdd6e215c67f2ae8ed1e378ea1661e936059a4",
        "repo": "scikit-learn",
        "path": "sklearn/tests/test_calibration.py",
        "file_name": "test_calibration.py",
        "fun_name": "test_calibration_without_sample_weight_base_estimator",
        "commit_message": "API Rename base_estimator in CalibratedClassifierCV (#22054)\n\nCo-authored-by: Kevin Roice <kevinroice@Kevins-Air.broadband>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def test_calibration_without_sample_weight_base_estimator(data):\n    \n    X, y = data\n    sample_weight = np.ones_like(y)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 18,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 58,
        "n_ast_nodes": 34,
        "n_identifiers": 7,
        "d_id": 76059,
        "documentation": {
            "docstring": "Check that even if the estimator doesn't support\n    sample_weight, fitting with sample_weight still works.\n\n    There should be a warning, since the sample_weight is not passed\n    on to the estimator.\n    ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 268761,
        "commit_id": "1998521e2d5b89bc53d00639bad178330ebb98df",
        "repo": "ansible",
        "path": "lib/ansible/playbook/role/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_load_dependencies",
        "commit_message": "Always create new role (#78661)\n\nDon't use role cache for determining whether to create a new instance of role",
        "code": "def _load_dependencies(self):\n        \n\n        deps = []\n        for role_include in self._metadata.dependencies:\n            r = Role.load(role_include, play=self._play, parent_role=self)\n            deps.append(r)\n\n        return deps\n\n    # other functions\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 73,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 73,
        "n_identifiers": 13,
        "d_id": 79654,
        "documentation": {
            "docstring": "\n        Recursively loads role dependencies from the metadata list of\n        dependencies, if it exists\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 148107,
        "commit_id": "e57ce7efd6ea1d0e4f6942fcf6f526287340e63d",
        "repo": "ray",
        "path": "rllib/utils/replay_buffers/tests/test_replay_buffer.py",
        "file_name": "test_replay_buffer.py",
        "fun_name": "test_timesteps_unit",
        "commit_message": "[RLlib] Replay Buffer API and Training Iteration Fn for DQN. (#23420)",
        "code": "def test_timesteps_unit(self):\n        \n        self.batch_id = 0\n\n        batch_size = 5\n        buffer_size = 15\n\n        buffer = ReplayBuffer(capacity=buffer_size)\n\n        # Test add/sample\n        self._add_data_to_buffer(buffer, batch_size=batch_size, num_batches=1)\n\n        self._add_data_to_buffer(buffer, batch_size=batch_size, num_batches=2)\n\n        # Sampling from it now should yield our first batch 1/3 of the time\n        num_sampled_dict = {_id: 0 for _id in range(self.batch_id)}\n        num_samples = 200\n        for i in range(num_samples):\n            _id = buffer.sample(1)[\"batch_id\"][0]\n            num_sampled_dict[_id] += 1\n        assert np.allclose(\n            np.array(list(num_sampled_dict.values())) / num_samples,\n            len(num_sampled_dict) * [1 / 3],\n            atol=0.1,\n        )\n\n        # Test set/get state\n        state = buffer.get_state()\n        other_buffer = ReplayBuffer(capacity=buffer_size)\n        self._add_data_to_buffer(other_buffer, 1)\n        other_buffer.set_state(state)\n\n        assert other_buffer._storage == buffer._storage\n        assert other_buffer._next_idx == buffer._next_idx\n        assert other_buffer._num_timesteps_added == buffer._num_timesteps_added\n        assert (\n            other_buffer._num_timesteps_added_wrap == buffer._num_timesteps_added_wrap\n        )\n        assert other_buffer._num_timesteps_sampled == buffer._num_timesteps_sampled\n        assert other_buffer._eviction_started == buffer._eviction_started\n        assert other_buffer._est_size_bytes == buffer._est_size_bytes\n        assert len(other_buffer) == len(other_buffer)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 379,
        "n_words": 117,
        "vocab_size": 80,
        "complexity": 3,
        "nloc": 31,
        "token_counts": 236,
        "n_ast_nodes": 366,
        "n_identifiers": 34,
        "d_id": 34174,
        "documentation": {
            "docstring": "Tests adding, sampling, get-/set state, and eviction with\n        experiences stored by timesteps.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 303211,
        "commit_id": "8910d265d6cf15fed4e6e98b4344031019c1016d",
        "repo": "core",
        "path": "homeassistant/helpers/update_coordinator.py",
        "file_name": "update_coordinator.py",
        "fun_name": "_unschedule_refresh",
        "commit_message": "Keep track of a context for each listener (#72702)\n\n* Remove async_remove_listener\r\n\r\nThis avoids the ambuigity as to what happens if same callback is added multiple times.\r\n\r\n* Keep track of a context for each listener\r\n\r\nThis allow a update coordinator to adapt what data to request on update from the backing service based on which entities are enabled.\r\n\r\n* Clone list before calling callbacks\r\n\r\nThe callbacks can end up unregistering and modifying the dict while iterating.\r\n\r\n* Only yield actual values\r\n\r\n* Add a test for update context\r\n\r\n* Factor out iteration of _listeners to helper\r\n\r\n* Verify context is passed to coordinator\r\n\r\n* Switch to Any as type instead of object\r\n\r\n* Remove function which use was dropped earliers\r\n\r\nThe use was removed in 8bee25c938a123f0da7569b4e2753598d478b900",
        "code": "def _unschedule_refresh(self) -> None:\n        \n        if self._unsub_refresh:\n            self._unsub_refresh()\n            self._unsub_refresh = None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 46,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 3,
        "d_id": 102039,
        "documentation": {
            "docstring": "Unschedule any pending refresh since there is no longer any listeners.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 63142,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "split_sections",
        "commit_message": "upd; format",
        "code": "def split_sections(s):\n    \n    section = None\n    content = []\n    for line in yield_lines(s):\n        if line.startswith(\"[\"):\n            if line.endswith(\"]\"):\n                if section or content:\n                    yield section, content\n                section = line[1:-1].strip()\n                content = []\n            else:\n                raise ValueError(\"Invalid section heading\", line)\n        else:\n            content.append(line)\n\n    # wrap up last segment\n    yield section, content\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 189,
        "n_words": 45,
        "vocab_size": 30,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 84,
        "n_ast_nodes": 148,
        "n_identifiers": 11,
        "d_id": 13164,
        "documentation": {
            "docstring": "Split a string or iterable thereof into (section, content) pairs\n\n    Each ``section`` is a stripped version of the section header (\"[section]\")\n    and each ``content`` is a list of stripped lines excluding blank lines and\n    comment-only lines.  If there are any such lines before the first section\n    header, they're returned in a first ``section`` of ``None``.\n    ",
            "n_words": 55,
            "vocab_size": 41,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 166849,
        "commit_id": "96ba36ddcbedda4bfe4e70ea0261a3194724f768",
        "repo": "pandas",
        "path": "pandas/io/common.py",
        "file_name": "common.py",
        "fun_name": "close",
        "commit_message": "BUG: do not suppress errors when closing file handles (#47165)",
        "code": "def close(self) -> None:\n        \n        if self.is_wrapped:\n            assert isinstance(self.handle, TextIOWrapper)\n            self.handle.flush()\n            self.handle.detach()\n            self.created_handles.remove(self.handle)\n        for handle in self.created_handles:\n            handle.close()\n        self.created_handles = []\n        self.is_wrapped = False\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 113,
        "n_words": 23,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 69,
        "n_ast_nodes": 114,
        "n_identifiers": 10,
        "d_id": 39862,
        "documentation": {
            "docstring": "\n        Close all created buffers.\n\n        Note: If a TextIOWrapper was inserted, it is flushed and detached to\n        avoid closing the potentially user-created buffer.\n        ",
            "n_words": 22,
            "vocab_size": 22,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 43388,
        "commit_id": "e2f19505bf3622935480e80bee55bf5b6d80097b",
        "repo": "airflow",
        "path": "airflow/www/views.py",
        "file_name": "views.py",
        "fun_name": "robots",
        "commit_message": "Upgrade FAB to 4.1.1 (#24399)\n\n* Upgrade FAB to 4.1.1\r\n\r\nThe Flask Application Builder have been updated recently to\r\nsupport a number of newer dependencies. This PR is the\r\nattempt to migrate FAB to newer version.\r\n\r\nThis includes:\r\n\r\n* update setup.py and setup.cfg upper and lower bounds to\r\n  account for proper version of dependencies that\r\n  FAB < 4.0.0 was blocking from upgrade\r\n* added typed Flask application retrieval with a custom\r\n  application fields available for MyPy typing checks.\r\n* fix typing to account for typing hints added in multiple\r\n  upgraded libraries optional values and content of request\r\n  returned as Mapping\r\n* switch to PyJWT 2.* by using non-deprecated \"required\" claim as\r\n  list rather than separate fields\r\n* add possibiliyt to install providers without constraints\r\n  so that we could avoid errors on conflicting constraints when\r\n  upgrade-to-newer-dependencies is used\r\n* add pre-commit to check that 2.4+ only get_airflow_app is not\r\n  used in providers\r\n* avoid Bad Request in case the request sent to Flask 2.0 is not\r\n  JSon content type\r\n* switch imports of internal classes to direct packages\r\n  where classes are available rather than from \"airflow.models\" to\r\n  satisfy MyPY\r\n* synchronize changes of FAB Security Manager 4.1.1 with our copy\r\n  of the Security Manager.\r\n* add error handling for a few \"None\" cases detected by MyPY\r\n* corrected test cases that were broken by immutability of\r\n  Flask 2 objects and better escaping done by Flask 2\r\n* updated test cases to account for redirection to \"path\" rather\r\n  than full URL by Flask2\r\n\r\nFixes: #22397\r\n\r\n* fixup! Upgrade FAB to 4.1.1",
        "code": "def robots(self):\n        \n        return send_from_directory(get_airflow_app().static_folder, 'robots.txt')\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 32,
        "n_identifiers": 5,
        "d_id": 7945,
        "documentation": {
            "docstring": "\n        Returns a robots.txt file for blocking certain search engine crawlers. This mitigates some\n        of the risk associated with exposing Airflow to the public internet, however it does not\n        address the real security risks associated with such a deployment.\n        ",
            "n_words": 38,
            "vocab_size": 33,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 203997,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/gdal/prototypes/generation.py",
        "file_name": "generation.py",
        "fun_name": "geom_output",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def geom_output(func, argtypes, offset=None):\n    \n    # Setting the argument types\n    func.argtypes = argtypes\n\n    if not offset:\n        # When a geometry pointer is directly returned.\n        func.restype = c_void_p\n        func.errcheck = check_geom\n    else:\n        # Error code returned, geometry is returned by-reference.\n        func.restype = c_int\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 41,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 47,
        "n_ast_nodes": 66,
        "n_identifiers": 9,
        "d_id": 50602,
        "documentation": {
            "docstring": "\n    Generate a function that returns a Geometry either by reference\n    or directly (if the return_geom keyword is set to True).\n    ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 156252,
        "commit_id": "e30471041ab9be7126a14f412fd17a1e2df8a7f5",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "query",
        "commit_message": "Update `DataFrame.query` docstring (#8890)",
        "code": "def query(self, expr, **kwargs):\n        \n        return self.map_partitions(M.query, expr, **kwargs)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 39,
        "n_identifiers": 6,
        "d_id": 36619,
        "documentation": {
            "docstring": "Filter dataframe with complex expression\n\n        Blocked version of pd.DataFrame.query\n\n        Parameters\n        ----------\n        expr: str\n            The query string to evaluate.\n            You can refer to column names that are not valid Python variable names\n            by surrounding them in backticks.\n            Dask does not fully support referring to variables using the '@' character,\n            use f-strings or the ``local_dict`` keyword argument instead.\n\n        Notes\n        -----\n        This is like the sequential version except that this will also happen\n        in many threads.  This may conflict with ``numexpr`` which will use\n        multiple threads itself.  We recommend that you set ``numexpr`` to use a\n        single thread:\n\n        .. code-block:: python\n\n            import numexpr\n            numexpr.set_num_threads(1)\n\n        See also\n        --------\n        pandas.DataFrame.query\n        pandas.eval\n\n        Examples\n        --------\n        >>> import pandas as pd\n        >>> import dask.dataframe as dd\n        >>> df = pd.DataFrame({'x': [1, 2, 1, 2],\n        ...                    'y': [1, 2, 3, 4],\n        ...                    'z z': [4, 3, 2, 1]})\n        >>> ddf = dd.from_pandas(df, npartitions=2)\n\n        Refer to column names directly:\n\n        >>> ddf.query('y > x').compute()\n           x  y  z z\n        2  1  3    2\n        3  2  4    1\n\n        Refer to column name using backticks:\n\n        >>> ddf.query('`z z` > x').compute()\n           x  y  z z\n        0  1  1    4\n        1  2  2    3\n        2  1  3    2\n\n        Refer to variable name using f-strings:\n\n        >>> value = 1\n        >>> ddf.query(f'x == {value}').compute()\n           x  y  z z\n        0  1  1    4\n        2  1  3    2\n\n        Refer to variable name using ``local_dict``:\n\n        >>> ddf.query('x == @value', local_dict={\"value\": value}).compute()\n           x  y  z z\n        0  1  1    4\n        2  1  3    2\n        ",
            "n_words": 242,
            "vocab_size": 140,
            "n_whitespaces": 746,
            "language": "en"
        }
    },
    {
        "id": 132999,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/collective/collective_group/nccl_collective_group.py",
        "file_name": "nccl_collective_group.py",
        "fun_name": "_check_gpu_tensors",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _check_gpu_tensors(tensors):\n    \n    if not tensors or not isinstance(tensors, list):\n        raise RuntimeError(\"'tensors' must be a nonempty list.\")\n    if len(tensors) > nccl_util.get_num_gpus():\n        raise RuntimeError(\n            \"Tensor list cannot be larger than the number\"\n            \"of available GPUs. Got {} > {}.\".format(\n                len(tensors), nccl_util.get_num_gpus()\n            )\n        )\n    t0 = tensors[0]\n    dt = nccl_util.get_nccl_tensor_dtype(t0)\n    s = nccl_util.get_tensor_shape(t0)\n    d = nccl_util.get_tensor_device(t0)\n    for i, t in enumerate(tensors):\n        if i == 0:\n            continue\n        # We need to check the following:\n        # (1) tensor is cuda (already checked during API)\n        # (2) tensor dtype\n        # (3) tensor shape match\n        # (4) each tensor is on a different GPU\n        dtype = nccl_util.get_nccl_tensor_dtype(t)\n        if dt != dtype:\n            raise RuntimeError(\n                \"Tensors must have identical dtype. Got: '{}'.\".format(dtype)\n            )\n        shape = nccl_util.get_tensor_shape(t)\n        if s != shape:\n            raise RuntimeError(\n                \"Tensor must have identical shape. Got: '{}'.\".format(shape)\n            )\n        device = nccl_util.get_tensor_device(t)\n        if device == d:\n            raise RuntimeError(\"Tensor must be on distinct GPUs.\")\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 418,
        "n_words": 145,
        "vocab_size": 96,
        "complexity": 9,
        "nloc": 30,
        "token_counts": 165,
        "n_ast_nodes": 285,
        "n_identifiers": 22,
        "d_id": 29907,
        "documentation": {
            "docstring": "Check all tensors are distributed on different GPUs.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 42678,
        "commit_id": "70b41e46b46e65c0446a40ab91624cb2291a5039",
        "repo": "airflow",
        "path": "tests/models/test_mappedoperator.py",
        "file_name": "test_mappedoperator.py",
        "fun_name": "test_map_xcom_arg",
        "commit_message": "Move MappedOperator tests to mirror code location (#23884)\n\nAt some point during the development of AIP-42 we moved the code for\r\nMappedOperator out of baseoperator.py to mappedoperator.py, but we\r\ndidn't move the tests at the same time",
        "code": "def test_map_xcom_arg():\n    \n    with DAG(\"test-dag\", start_date=DEFAULT_DATE):\n        task1 = BaseOperator(task_id=\"op1\")\n        mapped = MockOperator.partial(task_id='task_2').expand(arg2=XComArg(task1))\n        finish = MockOperator(task_id=\"finish\")\n\n        mapped >> finish\n\n    assert task1.downstream_list == [mapped]\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 58,
        "n_words": 21,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 63,
        "n_ast_nodes": 112,
        "n_identifiers": 15,
        "d_id": 7687,
        "documentation": {
            "docstring": "Test that dependencies are correct when mapping with an XComArg",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 127553,
        "commit_id": "57cdbb1769a9c32972ba0ec9e7e857eeea961869",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_multinode_sync.py",
        "file_name": "test_multinode_sync.py",
        "fun_name": "testClusterAutoscaling",
        "commit_message": "Migrate the deprecated placement_group option to PlacementGroupSchedulingStrategy (#28437)\n\nplacement_group option is deprecated, use PlacementGroupSchedulingStrategy instead.",
        "code": "def testClusterAutoscaling(self):\n        \n        self.cluster.update_config(\n            {\n                \"provider\": {\"head_resources\": {\"CPU\": 4, \"GPU\": 0}},\n            }\n        )\n        self.cluster.start()\n        self.cluster.connect(client=True, timeout=120)\n\n        self.assertGreater(ray.cluster_resources().get(\"CPU\", 0), 0)\n\n        # Trigger autoscaling\n        pg = ray.util.placement_group([{\"CPU\": 1, \"GPU\": 1}] * 2)\n        timeout = time.monotonic() + 120\n        while ray.cluster_resources().get(\"GPU\", 0) < 2:\n            if time.monotonic() > timeout:\n                raise RuntimeError(\"Autoscaling failed or too slow.\")\n            time.sleep(1)\n\n        # Schedule task with resources\n        self.assertEquals(\n            5,\n            ray.get(\n                remote_task.options(\n                    num_cpus=1,\n                    num_gpus=1,\n                    scheduling_strategy=PlacementGroupSchedulingStrategy(\n                        placement_group=pg\n                    ),\n                ).remote(5)\n            ),\n        )\n\n        print(\"Autoscaling worked\")\n        ray.util.remove_placement_group(pg)\n\n        time.sleep(2)  # Give some time so nodes.json is updated\n\n        self.cluster.kill_node(num=2)\n        print(\"Killed GPU node.\")\n        pg = ray.util.placement_group([{\"CPU\": 1, \"GPU\": 1}] * 2)\n\n        table = ray.util.placement_group_table(pg)\n        assert table[\"state\"] == \"PENDING\"\n\n        timeout = time.monotonic() + 180\n        while table[\"state\"] != \"CREATED\":\n            if time.monotonic() > timeout:\n                raise RuntimeError(\"Re-starting killed node failed or too slow.\")\n            time.sleep(1)\n            table = ray.util.placement_group_table(pg)\n\n        print(\"Node was restarted.\")\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 579,
        "n_words": 126,
        "vocab_size": 90,
        "complexity": 5,
        "nloc": 42,
        "token_counts": 300,
        "n_ast_nodes": 513,
        "n_identifiers": 33,
        "d_id": 28467,
        "documentation": {
            "docstring": "Sanity check that multinode tests with autoscaling are working",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 212643,
        "commit_id": "acaae54a1ade24b2e55f7274ae4db747160a38db",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "string_width_in_pixels",
        "commit_message": "Enable Text class methods to be called prior to any windows being created: string_width_in_pixels, char_height_in_pixels, char_width_in_pixels.  Removed destruction of hidden master root from popup_get_file & popup_get_folder (was old code)",
        "code": "def string_width_in_pixels(cls, font, string):\n        \n\n        # if no windows have been created (there is no hidden master root to rely on) then temporarily make a window so the measurement can happen\n        if Window.NumOpenWindows == 0:\n            root = tk.Tk()\n        else:\n            root = None\n\n        size = 0\n        try:\n            size = tkinter.font.Font(font=font).measure(string)  # string's  width\n        except Exception as e:\n            _error_popup_with_traceback('Exception retrieving string width in pixels', e)\n\n        if root is not None:\n            root.destroy()\n\n        return size\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 190,
        "n_words": 70,
        "vocab_size": 56,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 75,
        "n_ast_nodes": 128,
        "n_identifiers": 17,
        "d_id": 53306,
        "documentation": {
            "docstring": "\n        Get the with of the supplied string in pixels for the font being passed in.\n        If an error occurs, 0 will be returned\n        :param font:   specifies the  font family, size, etc. Tuple or Single string format 'name size styles'. Styles: italic * roman bold normal underline overstrike, to be measured\n        :type font:    (str or (str, int[, str]) or None)\n        :param string: the string to measure\n        :type string:  str\n        :return:       Width in pixels of string\n        :rtype:        (int)\n        ",
            "n_words": 76,
            "vocab_size": 57,
            "n_whitespaces": 160,
            "language": "en"
        }
    },
    {
        "id": 19471,
        "commit_id": "7e33fcae4384563b4c927fd44318c29dd524a097",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/locations/_sysconfig.py",
        "file_name": "_sysconfig.py",
        "fun_name": "_should_use_osx_framework_prefix",
        "commit_message": "Vendor in pip 21.2.4 release (from pip 21.2.2 prior). (#5009)\n\n* Vendor in pip 21.2.4 release (from pip 21.2.2 prior).\r\n\r\n* Add news fragment for pip 21.2.4 vendor update.\r\n\r\n* Add potentially missing LICENSE files",
        "code": "def _should_use_osx_framework_prefix() -> bool:\n    \n    return (\n        \"osx_framework_library\" in _AVAILABLE_SCHEMES\n        and not running_under_virtualenv()\n        and is_osx_framework()\n    )\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 45,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 24,
        "token_counts": 22,
        "n_ast_nodes": 42,
        "n_identifiers": 5,
        "d_id": 2987,
        "documentation": {
            "docstring": "Check for Apple's ``osx_framework_library`` scheme.\n\n    Python distributed by Apple's Command Line Tools has this special scheme\n    that's used when:\n\n    * This is a framework build.\n    * We are installing into the system prefix.\n\n    This does not account for ``pip install --prefix`` (also means we're not\n    installing to the system prefix), which should use ``posix_prefix``, but\n    logic here means ``_infer_prefix()`` outputs ``osx_framework_library``. But\n    since ``prefix`` is not available for ``sysconfig.get_default_scheme()``,\n    which is the stdlib replacement for ``_infer_prefix()``, presumably Apple\n    wouldn't be able to magically switch between ``osx_framework_library`` and\n    ``posix_prefix``. ``_infer_prefix()`` returning ``osx_framework_library``\n    means its behavior is consistent whether we use the stdlib implementation\n    or our own, and we deal with this special case in ``get_scheme()`` instead.\n    ",
            "n_words": 115,
            "vocab_size": 86,
            "n_whitespaces": 157,
            "language": "en"
        }
    },
    {
        "id": 212817,
        "commit_id": "9b814f003b0685757d76ce56ee9c98eae114d346",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "set_focus",
        "commit_message": "Added key and widget Element properties, new focus methods Element.get_next_focus, Element.get_previous_focus. New Window method Window.widget_to_element",
        "code": "def set_focus(self, force=False):\n        \n        if not self._widget_was_created():  # if widget hasn't been created yet, then don't allow\n            return\n        try:\n            if force:\n                self.Widget.focus_force()\n            else:\n                self.Widget.focus_set()\n        except Exception as e:\n            _error_popup_with_traceback(\"Exception blocking focus. Check your element's Widget\", e)\n\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 138,
        "n_words": 35,
        "vocab_size": 33,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 51,
        "n_ast_nodes": 92,
        "n_identifiers": 10,
        "d_id": 53427,
        "documentation": {
            "docstring": "\n        Sets the current focus to be on this element\n\n        :param force: if True will call focus_force otherwise calls focus_set\n        :type force:  bool\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 247751,
        "commit_id": "12d1f82db213603972d60be3f46f6a36c3c2330f",
        "repo": "synapse",
        "path": "scripts-dev/release.py",
        "file_name": "release.py",
        "fun_name": "announce",
        "commit_message": "Generate announcement links in release script (#12242)",
        "code": "def announce():\n    \n\n    current_version, _, _ = parse_version_from_module()\n    tag_name = f\"v{current_version}\"\n\n    click.echo(\n        f\n    )\n\n    if \"rc\" in tag_name:\n        click.echo(\n            \n        )\n    else:\n        click.echo(\n            \n        )\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 102,
        "n_words": 22,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 28,
        "token_counts": 44,
        "n_ast_nodes": 106,
        "n_identifiers": 7,
        "d_id": 71896,
        "documentation": {
            "docstring": "Generate markdown to announce the release.\nHi everyone. Synapse {current_version} has just been released.\n\n[notes](https://github.com/matrix-org/synapse/releases/tag/{tag_name}) |\\\n[docker](https://hub.docker.com/r/matrixdotorg/synapse/tags?name={tag_name}) | \\\n[debs](https://packages.matrix.org/debian/) | \\\n[pypi](https://pypi.org/project/matrix-synapse/{current_version}/)\nAnnounce the RC in\n- #homeowners:matrix.org (Synapse Announcements)\n- #synapse-dev:matrix.org\nAnnounce the release in\n- #homeowners:matrix.org (Synapse Announcements), bumping the version in the topic\n- #synapse:matrix.org (Synapse Admins), bumping the version in the topic\n- #synapse-dev:matrix.org\n- #synapse-package-maintainers:matrix.org",
            "n_words": 61,
            "vocab_size": 37,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 73819,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "workflow_in_progress",
        "commit_message": "Reformat with black",
        "code": "def workflow_in_progress(self):\n        \n        if not getattr(settings, \"WAGTAIL_WORKFLOW_ENABLED\", True):\n            return False\n\n        # `_current_workflow_states` may be populated by `prefetch_workflow_states` on `PageQuerySet` as a\n        # performance optimisation\n        if hasattr(self, \"_current_workflow_states\"):\n            for state in self._current_workflow_states:\n                if state.status == WorkflowState.STATUS_IN_PROGRESS:\n                    return True\n            return False\n\n        return WorkflowState.objects.filter(\n            page=self, status=WorkflowState.STATUS_IN_PROGRESS\n        ).exists()\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 170,
        "n_words": 43,
        "vocab_size": 36,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 68,
        "n_ast_nodes": 112,
        "n_identifiers": 14,
        "d_id": 16127,
        "documentation": {
            "docstring": "Returns True if a workflow is in progress on the current page, otherwise False",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 336164,
        "commit_id": "1b42732ced07861b810f77ecf3fc8ce63ce465e8",
        "repo": "diffusers",
        "path": "src/diffusers/pipeline_utils.py",
        "file_name": "pipeline_utils.py",
        "fun_name": "numpy_to_pil",
        "commit_message": "PIL-ify the pipeline outputs (#111)",
        "code": "def numpy_to_pil(images):\n        \n        if images.ndim == 3:\n            images = images[None, ...]\n        images = (images * 255).round().astype(\"uint8\")\n        pil_images = [Image.fromarray(image) for image in images]\n\n        return pil_images\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 70,
        "n_words": 24,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 9,
        "d_id": 120858,
        "documentation": {
            "docstring": "\n        Convert a numpy image or a batch of images to a PIL image.\n        ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 199311,
        "commit_id": "e8bf22b0eb76ecb6aec12dd45549649c490e1354",
        "repo": "sympy",
        "path": "bin/mailmap_check.py",
        "file_name": "mailmap_check.py",
        "fun_name": "make_authors_file_lines",
        "commit_message": "mailmap documents python2\n\nI believe this to be useful for at least two reasons.\n\nCurrent documentation either state to use `python bin/mailmap_check.py` or just\n`bin/mailmap_check.py` which itself calles `python`. In both case, on ubuntu\nthis will run python2.\n\nWorse, instead of printing \"This script requires Python 3.8 or newer\" it prints\nan error message that python don't know what to do with the f-string. If the\nf-string is removed, that it does not know pathlib. So, I ensure that the script\nstill work as before on 3.8 and prints a more useful message on python2.  I\nadmit I'm not fan of removing a f-string, however, since there was a single\nf-string, I assume it was relatively acceptable.\n\nI suppose most sympy contributor are at ease with those subtilities of\npython2/3. However, this will at least be useful for people, like me, who only\nwanted to contribute to improving documentation and not have to deal with\ncomplexity of system administration.",
        "code": "def make_authors_file_lines(git_people):\n    # define new lines for the file\n    header = filldedent().lstrip()\n    header_extra = \"There are a total of %d authors.\"  % len(git_people)\n    lines = header.splitlines()\n    lines.append('')\n    lines.append(header_extra)\n    lines.append('')\n    lines.extend(git_people)\n    return lines\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 59,
        "n_words": 32,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 56,
        "n_ast_nodes": 103,
        "n_identifiers": 11,
        "d_id": 49232,
        "documentation": {
            "docstring": "\n        All people who contributed to SymPy by sending at least a patch or\n        more (in the order of the date of their first contribution), except\n        those who explicitly didn't want to be mentioned. People with a * next\n        to their names are not found in the metadata of the git history. This\n        file is generated automatically by running `./bin/authors_update.py`.\n        ",
            "n_words": 59,
            "vocab_size": 48,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 71246,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/templatetags/wagtailadmin_tags.py",
        "file_name": "wagtailadmin_tags.py",
        "fun_name": "avatar_url",
        "commit_message": "Reformat with black",
        "code": "def avatar_url(user, size=50, gravatar_only=False):\n    \n\n    if (\n        not gravatar_only\n        and hasattr(user, \"wagtail_userprofile\")\n        and user.wagtail_userprofile.avatar\n    ):\n        return user.wagtail_userprofile.avatar.url\n\n    if hasattr(user, \"email\"):\n        gravatar_url = get_gravatar_url(user.email, size=size)\n        if gravatar_url is not None:\n            return gravatar_url\n\n    return versioned_static_func(\"wagtailadmin/images/default-user-avatar.png\")\n\n\n@register.simple_tag",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@register.simple_tag",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 100,
        "n_words": 33,
        "vocab_size": 24,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 74,
        "n_ast_nodes": 127,
        "n_identifiers": 14,
        "d_id": 15646,
        "documentation": {
            "docstring": "\n    A template tag that receives a user and size and return\n    the appropriate avatar url for that user.\n    Example usage: {% avatar_url request.user 50 %}\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 321446,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "tests/unit/utils/test_qtutils.py",
        "file_name": "test_qtutils.py",
        "fun_name": "test_failing_open",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def test_failing_open(self, tmp_path):\n        \n        qf = QFile(str(tmp_path))\n        dev = qtutils.PyQIODevice(qf)\n        with pytest.raises(qtutils.QtOSError) as excinfo:\n            dev.open(QIODevice.OpenModeFlag.WriteOnly)\n        assert excinfo.value.qt_errno == QFileDevice.FileError.OpenError\n        assert dev.closed\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 63,
        "n_ast_nodes": 105,
        "n_identifiers": 23,
        "d_id": 117728,
        "documentation": {
            "docstring": "Test open() which fails (because it's an existent directory).",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 205257,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/migrations/autodetector.py",
        "file_name": "autodetector.py",
        "fun_name": "deep_deconstruct",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def deep_deconstruct(self, obj):\n        \n        if isinstance(obj, list):\n            return [self.deep_deconstruct(value) for value in obj]\n        elif isinstance(obj, tuple):\n            return tuple(self.deep_deconstruct(value) for value in obj)\n        elif isinstance(obj, dict):\n            return {key: self.deep_deconstruct(value) for key, value in obj.items()}\n        elif isinstance(obj, functools.partial):\n            return (\n                obj.func,\n                self.deep_deconstruct(obj.args),\n                self.deep_deconstruct(obj.keywords),\n            )\n        elif isinstance(obj, COMPILED_REGEX_TYPE):\n            return RegexObject(obj)\n        elif isinstance(obj, type):\n            # If this is a type that implements 'deconstruct' as an instance method,\n            # avoid treating this as being deconstructible itself - see #22951\n            return obj\n        elif hasattr(obj, \"deconstruct\"):\n            deconstructed = obj.deconstruct()\n            if isinstance(obj, models.Field):\n                # we have a field which also returns a name\n                deconstructed = deconstructed[1:]\n            path, args, kwargs = deconstructed\n            return (\n                path,\n                [self.deep_deconstruct(value) for value in args],\n                {key: self.deep_deconstruct(value) for key, value in kwargs.items()},\n            )\n        else:\n            return obj\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 469,
        "n_words": 121,
        "vocab_size": 72,
        "complexity": 14,
        "nloc": 29,
        "token_counts": 220,
        "n_ast_nodes": 337,
        "n_identifiers": 25,
        "d_id": 51047,
        "documentation": {
            "docstring": "\n        Recursive deconstruction for a field and its arguments.\n        Used for full comparison for rename/alter; sometimes a single-level\n        deconstruction will not compare correctly.\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 28584,
        "commit_id": "9e2ea5b2f647f7d19c3a54347ccdcbf787f2ca0b",
        "repo": "saleor",
        "path": "saleor/graphql/core/tests/test_core_reordering.py",
        "file_name": "test_core_reordering.py",
        "fun_name": "test_reordering_concurrently",
        "commit_message": "Upgrade Saleor to Django version 4.0 (#10518)\n\nLots of typing fixes uncovered while I attempted to upgrade to the\r\nlatest version of django-stubs. Didn't pull it here as it has a bug that\r\ncauses it to report problems related to its own type cloning code.",
        "code": "def test_reordering_concurrently(dummy_attribute, assert_num_queries):\n    \n\n    qs = SortedModel.objects\n    attribute = dummy_attribute\n\n    entries = list(\n        qs.bulk_create(\n            [\n                SortedModel(attribute=attribute, slug=\"1\", name=\"1\", sort_order=0),\n                SortedModel(attribute=attribute, slug=\"2\", name=\"2\", sort_order=1),\n            ]\n        )\n    )\n\n    operations = {entries[0].pk: +1}\n\n    with assert_num_queries(2) as ctx:\n        perform_reordering(qs, operations)\n\n    assert ctx[0][\"sql\"] == (\n        'SELECT \"attribute_attributevalue\".\"id\", '\n        '\"attribute_attributevalue\".\"sort_order\" '\n        'FROM \"attribute_attributevalue\" '\n        \"ORDER BY \"\n        '\"attribute_attributevalue\".\"sort_order\" ASC NULLS LAST, '\n        '\"attribute_attributevalue\".\"id\" ASC FOR UPDATE'\n    )\n    assert ctx[1][\"sql\"] == (\n        'UPDATE \"attribute_attributevalue\" '\n        'SET \"sort_order\" = '\n        f'(CASE WHEN (\"attribute_attributevalue\".\"id\" = {entries[0].pk}) '\n        f'THEN 1 WHEN (\"attribute_attributevalue\".\"id\" = {entries[1].pk}) '\n        \"THEN 0 ELSE NULL END)::integer \"\n        'WHERE \"attribute_attributevalue\".\"id\" '\n        f\"IN ({entries[0].pk}, {entries[1].pk})\"\n    )\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 294,
        "n_words": 97,
        "vocab_size": 70,
        "complexity": 1,
        "nloc": 31,
        "token_counts": 131,
        "n_ast_nodes": 272,
        "n_identifiers": 17,
        "d_id": 5174,
        "documentation": {
            "docstring": "\n    Ensures users cannot concurrently reorder, they need to wait for the other one\n    to achieve.\n\n    This must be the first thing done before doing anything. For that, we ensure\n    the first SQL query is acquiring the lock.\n    ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 317500,
        "commit_id": "04c6b9c51963418ffebddc7753939700fbea7e42",
        "repo": "core",
        "path": "homeassistant/components/zha/core/channels/lighting.py",
        "file_name": "lighting.py",
        "fun_name": "enhanced_current_hue",
        "commit_message": "ZHA light entity cleanup  (#75573)\n\n* use base class attributes\r\n\r\n* initial hue and saturation support\r\n\r\n* spec is 65536 not 65535\r\n\r\n* fixes\r\n\r\n* enhanced current hue\r\n\r\n* fix comparison\r\n\r\n* clean up\r\n\r\n* fix channel test\r\n\r\n* oops\r\n\r\n* report enhanced current hue",
        "code": "def enhanced_current_hue(self) -> int | None:\n        \n        return self.cluster.get(\"enhanced_current_hue\")\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 116067,
        "documentation": {
            "docstring": "Return cached value of the enhanced_current_hue attribute.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 3835,
        "commit_id": "a3aae8017a0a40ff2006e2567f71dccb04c997a5",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/unit_tests/test_base_insight_streams.py",
        "file_name": "test_base_insight_streams.py",
        "fun_name": "test_stream_slices_with_state",
        "commit_message": "🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805)\n\n* Facebook Marketing performance improvement\r\n\r\n* add comments and little refactoring\r\n\r\n* fix integration tests with the new config\r\n\r\n* improve job status handling, limit concurrency to 10\r\n\r\n* fix campaign jobs, refactor manager\r\n\r\n* big refactoring of async jobs, support random order of slices\r\n\r\n* update source _read_incremental to hook new state logic\r\n\r\n* fix issues with timeout\r\n\r\n* remove debugging and clean up, improve retry logic\r\n\r\n* merge changes from #8234\r\n\r\n* fix call super _read_increment\r\n\r\n* generalize batch execution, add use_batch flag\r\n\r\n* improve coverage, do some refactoring of spec\r\n\r\n* update test, remove overrides of source\r\n\r\n* add split by AdSet\r\n\r\n* add smaller insights\r\n\r\n* fix end_date < start_date case\r\n\r\n* add account_id to PK\r\n\r\n* add notes\r\n\r\n* fix new streams\r\n\r\n* fix reversed incremental stream\r\n\r\n* update spec.json for SAT\r\n\r\n* upgrade CDK and bump version\r\n\r\nCo-authored-by: Dmytro Rezchykov <dmitry.rezchykov@zazmic.com>\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>",
        "code": "def test_stream_slices_with_state(self, api, async_manager_mock, start_date):\n        \n        end_date = start_date + duration(days=10)\n        cursor_value = start_date + duration(days=5)\n        state = {AdsInsights.cursor_field: cursor_value.date().isoformat()}\n        stream = AdsInsights(api=api, start_date=start_date, end_date=end_date)\n        async_manager_mock.completed_jobs.return_value = [1, 2, 3]\n\n        slices = list(stream.stream_slices(stream_state=state, sync_mode=SyncMode.incremental))\n\n        assert slices == [{\"insight_job\": 1}, {\"insight_job\": 2}, {\"insight_job\": 3}]\n        async_manager_mock.assert_called_once()\n        args, kwargs = async_manager_mock.call_args\n        generated_jobs = list(kwargs[\"jobs\"])\n        assert len(generated_jobs) == (end_date - cursor_value).days\n        assert generated_jobs[0].interval.start == cursor_value.date() + duration(days=1)\n        assert generated_jobs[1].interval.start == cursor_value.date() + duration(days=2)\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 166,
        "n_words": 68,
        "vocab_size": 48,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 197,
        "n_ast_nodes": 310,
        "n_identifiers": 32,
        "d_id": 575,
        "documentation": {
            "docstring": "Stream will use cursor_value from state when there is state",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 100441,
        "commit_id": "aa39234538a8f83e6aa2b60b8275a570e8876ac2",
        "repo": "faceswap",
        "path": "plugins/extract/detect/mtcnn.py",
        "file_name": "mtcnn.py",
        "fun_name": "detect_rnet",
        "commit_message": "Update all Keras Imports to be conditional (#1214)\n\n* Remove custom keras importer\r\n\r\n* first round keras imports fix\r\n\r\n* launcher.py: Remove KerasFinder references\r\n\r\n* 2nd round keras imports update (lib and extract)\r\n\r\n* 3rd round keras imports update (train)\r\n\r\n* remove KerasFinder from tests\r\n\r\n* 4th round keras imports update (tests)",
        "code": "def detect_rnet(self, images, rectangle_batch, height, width):\n        \n        ret = []\n        # TODO: batching\n        for idx, rectangles in enumerate(rectangle_batch):\n            if not rectangles:\n                ret.append([])\n                continue\n            image = images[idx]\n            crop_number = 0\n            predict_24_batch = []\n            for rect in rectangles:\n                crop_img = image[int(rect[1]):int(rect[3]), int(rect[0]):int(rect[2])]\n                scale_img = cv2.resize(crop_img, (24, 24))\n                predict_24_batch.append(scale_img)\n                crop_number += 1\n            predict_24_batch = np.array(predict_24_batch)\n            output = self.rnet.predict(predict_24_batch, batch_size=128)\n            cls_prob = output[0]\n            cls_prob = np.array(cls_prob)\n            roi_prob = output[1]\n            roi_prob = np.array(roi_prob)\n            ret.append(filter_face_24net(\n                cls_prob, roi_prob, rectangles, width, height, self.threshold[1]\n            ))\n        return ret\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 360,
        "n_words": 77,
        "vocab_size": 56,
        "complexity": 4,
        "nloc": 24,
        "token_counts": 193,
        "n_ast_nodes": 294,
        "n_identifiers": 30,
        "d_id": 19919,
        "documentation": {
            "docstring": " second stage - refinement of face candidates with r-net ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 108380,
        "commit_id": "bed236261a74045a0e4a85fc930bc0ad0da786bb",
        "repo": "matplotlib",
        "path": "lib/matplotlib/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "_update_selection_poly",
        "commit_message": "Fix RangeSlider for same init values\n\nCloses #22686.\r\n\r\n\r\nCo-authored-by: Nickolaos Giannatos <t8190025@aueb.gr>",
        "code": "def _update_selection_poly(self, vmin, vmax):\n        \n        # The vertices are positioned\n        #  1 ------ 2\n        #  |        |\n        # 0, 4 ---- 3\n        verts = self.poly.xy\n        if self.orientation == \"vertical\":\n            verts[0] = verts[4] = .25, vmin\n            verts[1] = .25, vmax\n            verts[2] = .75, vmax\n            verts[3] = .75, vmin\n        else:\n            verts[0] = verts[4] = vmin, .25\n            verts[1] = vmin, .75\n            verts[2] = vmax, .75\n            verts[3] = vmax, .25\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 218,
        "n_words": 65,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 108,
        "n_ast_nodes": 159,
        "n_identifiers": 8,
        "d_id": 23167,
        "documentation": {
            "docstring": "\n        Update the vertices of the *self.poly* slider in-place\n        to cover the data range *vmin*, *vmax*.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 86877,
        "commit_id": "941184cd24186324fd9f7f304b7f713041834726",
        "repo": "sentry",
        "path": "src/sentry/region_to_control/producer.py",
        "file_name": "producer.py",
        "fun_name": "clear_region_to_control_producer",
        "commit_message": "chore(hybrid-cloud): AuditLogEntry is a control silo model now (#39890)\n\nIn the control silo, creating an audit log entry writes to the db\r\ndirectly, whilst in region silo mode creating an audit log entry will\r\ninstead push to a new kafka producer that consumes into the control silo\r\nasynchronously.",
        "code": "def clear_region_to_control_producer():\n    \n    global _publisher\n    if _publisher:\n        _publisher.close()\n        _publisher = None\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 33,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 18,
        "n_ast_nodes": 34,
        "n_identifiers": 3,
        "d_id": 18180,
        "documentation": {
            "docstring": "\n    In tests, it is necessary to close the publisher after test failures or success for the pytest runner to continue.\n    The atexit handler does not handle this case gracefully, so instead we use a test fixture and call this method to\n    ensure, that the producer is always closed.\n    ",
            "n_words": 48,
            "vocab_size": 41,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 218187,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/abc.py",
        "file_name": "abc.py",
        "fun_name": "find_loader",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def find_loader(self, fullname):\n        \n        warnings.warn(\"PathEntryFinder.find_loader() is deprecated since Python \"\n                      \"3.4 in favor of PathEntryFinder.find_spec() \"\n                      \"(available since 3.4)\",\n                      DeprecationWarning,\n                      stacklevel=2)\n        if not hasattr(self, 'find_spec'):\n            return None, []\n        found = self.find_spec(fullname)\n        if found is not None:\n            if not found.submodule_search_locations:\n                portions = []\n            else:\n                portions = found.submodule_search_locations\n            return found.loader, portions\n        else:\n            return None, []\n\n    find_module = _bootstrap_external._find_module_shim\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 269,
        "n_words": 55,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 80,
        "n_ast_nodes": 145,
        "n_identifiers": 16,
        "d_id": 55187,
        "documentation": {
            "docstring": "Return (loader, namespace portion) for the path entry.\n\n        The fullname is a str.  The namespace portion is a sequence of\n        path entries contributing to part of a namespace package. The\n        sequence may be empty.  If loader is not None, the portion will\n        be ignored.\n\n        The portion will be discarded if another path entry finder\n        locates the module as a normal module or package.\n\n        This method is deprecated since Python 3.4 in favor of\n        finder.find_spec(). If find_spec() is provided than backwards-compatible\n        functionality is provided.\n        ",
            "n_words": 83,
            "vocab_size": 55,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 70258,
        "commit_id": "a9ee2aa09c00b6adc396c666d6e970e2b58918e6",
        "repo": "glances",
        "path": "glances/outputs/glances_bottle.py",
        "file_name": "glances_bottle.py",
        "fun_name": "_api_all",
        "commit_message": "Replace json by ujson #2201",
        "code": "def _api_all(self):\n        \n        response.content_type = 'application/json; charset=utf-8'\n\n        if self.args.debug:\n            fname = os.path.join(tempfile.gettempdir(), 'glances-debug.json')\n            try:\n                with open(fname) as f:\n                    return f.read()\n            except IOError:\n                logger.debug(\"Debug file (%s) not found\" % fname)\n\n        # Update the stat\n        self.__update__()\n\n        try:\n            # Get the JSON value of the stat ID\n            statval = json_dumps(self.stats.getAllAsDict())\n        except Exception as e:\n            abort(404, \"Cannot get stats (%s)\" % str(e))\n\n        return statval\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 230,
        "n_words": 59,
        "vocab_size": 47,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 98,
        "n_ast_nodes": 177,
        "n_identifiers": 26,
        "d_id": 15471,
        "documentation": {
            "docstring": "Glances API RESTful implementation.\n\n        Return the JSON representation of all the plugins\n        HTTP/200 if OK\n        HTTP/400 if plugin is not found\n        HTTP/404 if others error\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 331622,
        "commit_id": "abc9ba254430ef971ea3dbd12f2b4f1969da55be",
        "repo": "pytorch-image-models",
        "path": "timm/models/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "pretrained_cfg_for_features",
        "commit_message": "Transitioning default_cfg -> pretrained_cfg. Improving handling of pretrained_cfg source (HF-Hub, files, timm config, etc). Checkpoint handling tweaks.",
        "code": "def pretrained_cfg_for_features(pretrained_cfg):\n    pretrained_cfg = deepcopy(pretrained_cfg)\n    # remove default pretrained cfg fields that don't have much relevance for feature backbone\n    to_remove = ('num_classes', 'crop_pct', 'classifier', 'global_pool')  # add default final pool size?\n    for tr in to_remove:\n        pretrained_cfg.pop(tr, None)\n    return pretrained_cfg\n\n\n# def overlay_external_pretrained_cfg(pretrained_cfg, kwargs):\n#     \n#     external_pretrained_cfg = kwargs.pop('external_pretrained_cfg', None)\n#     if external_pretrained_cfg:\n#         pretrained_cfg.pop('url', None)  # url should come from external cfg\n#         pretrained_cfg.pop('hf_hub', None)  # hf hub id should come from external cfg\n#         pretrained_cfg.update(external_pretrained_cfg)\n\n",
        "url": "https://github.com/huggingface/pytorch-image-models.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 130,
        "n_words": 76,
        "vocab_size": 51,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 37,
        "n_ast_nodes": 73,
        "n_identifiers": 6,
        "d_id": 119875,
        "documentation": {
            "docstring": " Overlay 'external_pretrained_cfg' in kwargs on top of pretrained_cfg arg.\n#     ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 215903,
        "commit_id": "a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857",
        "repo": "salt",
        "path": "tests/pytests/functional/modules/test_win_certutil.py",
        "file_name": "test_win_certutil.py",
        "fun_name": "test_get_cert_serial_valid",
        "commit_message": "Add tests, fix state module",
        "code": "def test_get_cert_serial_valid(certutil, cert_file):\n    \n    serial = certutil.get_cert_serial(str(cert_file))\n    assert serial == \"5be1cc5d51b78dbd49a0b7c00d44806d\"\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 54237,
        "documentation": {
            "docstring": "\n    Test get_cert_serial with a known valid certificate\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 204095,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/geos/prototypes/errcheck.py",
        "file_name": "errcheck.py",
        "fun_name": "check_string",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def check_string(result, func, cargs):\n    \n    if not result:\n        raise GEOSException(\n            'Error encountered checking string return value in GEOS C function \"%s\".'\n            % func.__name__\n        )\n    # Getting the string value at the pointer address.\n    s = string_at(result)\n    # Freeing the memory allocated within GEOS\n    free(result)\n    return s\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 102,
        "n_words": 45,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 35,
        "n_ast_nodes": 62,
        "n_identifiers": 9,
        "d_id": 50633,
        "documentation": {
            "docstring": "\n    Error checking for routines that return strings.\n\n    This frees the memory allocated by GEOS at the result pointer.\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 110847,
        "commit_id": "f16da868d016363c4cd734b2abd6535230b094df",
        "repo": "matplotlib",
        "path": "lib/matplotlib/image.py",
        "file_name": "image.py",
        "fun_name": "set_data",
        "commit_message": "[Doc] Fix ndarray-links for arguments",
        "code": "def set_data(self, x, y, A):\n        \n        x = np.array(x, np.float32)\n        y = np.array(y, np.float32)\n        A = cbook.safe_masked_invalid(A, copy=True)\n        if not (x.ndim == y.ndim == 1 and A.shape[0:2] == y.shape + x.shape):\n            raise TypeError(\"Axes don't match array shape\")\n        if A.ndim not in [2, 3]:\n            raise TypeError(\"Can only plot 2D or 3D data\")\n        if A.ndim == 3 and A.shape[2] not in [1, 3, 4]:\n            raise TypeError(\"3D arrays must have three (RGB) \"\n                            \"or four (RGBA) color components\")\n        if A.ndim == 3 and A.shape[2] == 1:\n            A = A.squeeze(axis=-1)\n        self._A = A\n        self._Ax = x\n        self._Ay = y\n        self._imcache = None\n\n        self.stale = True\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 262,
        "n_words": 100,
        "vocab_size": 68,
        "complexity": 8,
        "nloc": 18,
        "token_counts": 182,
        "n_ast_nodes": 284,
        "n_identifiers": 21,
        "d_id": 24326,
        "documentation": {
            "docstring": "\n        Set the grid for the pixel centers, and the pixel values.\n\n        Parameters\n        ----------\n        x, y : 1D array-like\n            Monotonic arrays of shapes (N,) and (M,), respectively, specifying\n            pixel centers.\n        A : array-like\n            (M, N) `~numpy.ndarray` or masked array of values to be\n            colormapped, or (M, N, 3) RGB array, or (M, N, 4) RGBA array.\n        ",
            "n_words": 55,
            "vocab_size": 42,
            "n_whitespaces": 142,
            "language": "en"
        }
    },
    {
        "id": 31457,
        "commit_id": "7cced021fa8ddc59f0f77384300760d34545394e",
        "repo": "transformers",
        "path": "src/transformers/modeling_tf_utils.py",
        "file_name": "modeling_tf_utils.py",
        "fun_name": "tf_shard_checkpoint",
        "commit_message": "TF Sharded (#17713)\n\n* initial commit\r\n\r\n* update modeeling tf utils\r\n\r\n* quality\r\n\r\n* clean and update args\r\n\r\n* update\r\n\r\n* remove potential bug\r\n\r\n* code quality\r\n\r\n* update\r\n\r\n* update max shard\r\n\r\n* update tests for sharding from pretrained\r\n\r\n* fix remaining test\r\n\r\n* make style\r\n\r\n* h5py if tf available\r\n\r\n* update and fix test\r\n\r\n* fix test\r\n\r\n* style\r\n\r\n* modified push to hub to support shard for TF\r\n\r\n* quick fix\r\n\r\n* update code\r\n\r\n* merge branch main and style\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* update based on reviews\r\n\r\n* update doc\r\n\r\n* update and style\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update based on reviews\r\n\r\n* fix typo\r\n\r\n* style\r\n\r\nCo-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def tf_shard_checkpoint(weights, max_shard_size=\"10GB\"):\n    \n    max_shard_size = convert_file_size_to_int(max_shard_size)\n\n    sharded_state_dicts = []\n    current_block = []\n    current_block_size = 0\n    total_size = 0\n\n    for item in weights:\n        weight_size = item.numpy().size * dtype_byte_size(item.dtype)\n\n        # If this weight is going to tip up over the maximal size, we split.\n        if current_block_size + weight_size > max_shard_size:\n            sharded_state_dicts.append(current_block)\n            current_block = []\n            current_block_size = 0\n\n        current_block.append(item)\n        current_block_size += weight_size\n        total_size += weight_size\n\n    # Add the last block\n    sharded_state_dicts.append(current_block)\n\n    # If we only have one shard, we return it\n    if len(sharded_state_dicts) == 1:\n        return {TF2_WEIGHTS_NAME: sharded_state_dicts[0]}, None\n\n    # Otherwise, let's build the index\n    weight_map = {}\n    shards = {}\n    for idx, shard in enumerate(sharded_state_dicts):\n        shard_file = TF2_WEIGHTS_NAME.replace(\".h5\", f\"-{idx+1:05d}-of-{len(sharded_state_dicts):05d}.h5\")\n        shards[shard_file] = shard\n        for weight in shard:\n            weight_name = weight.name\n            weight_map[weight_name] = shard_file\n\n    # Add the metadata\n    metadata = {\"total_size\": total_size}\n    index = {\"metadata\": metadata, \"weight_map\": weight_map}\n    return shards, index\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 319,
        "n_words": 137,
        "vocab_size": 83,
        "complexity": 6,
        "nloc": 29,
        "token_counts": 181,
        "n_ast_nodes": 324,
        "n_identifiers": 29,
        "d_id": 5748,
        "documentation": {
            "docstring": "\n    Splits a model state dictionary in sub-checkpoints so that the final size of each sub-checkpoint does not exceed a\n    given size.\n\n    The sub-checkpoints are determined by iterating through the `state_dict` in the order of its keys, so there is no\n    optimization made to make each sub-checkpoint as close as possible to the maximum size passed. For example, if the\n    limit is 10GB and we have weights of sizes [6GB, 6GB, 2GB, 6GB, 2GB, 2GB] they will get sharded as [6GB], [6+2GB],\n    [6+2+2GB] and not [6+2+2GB], [6+2GB], [6GB].\n\n    <Tip warning={true}>\n\n    If one of the model's weight is bigger that `max_shard_size`, it will end up in its own sub-checkpoint which will\n    have a size greater than `max_shard_size`.\n\n    </Tip>\n\n    Args:\n        weights (`Dict[str, tf.RessourceVariable]`): The list of tf.RessourceVariable of a model to save.\n        max_shard_size (`int` or `str`, *optional*, defaults to `\"10GB\"`):\n            The maximum size of each sub-checkpoint. If expressed as a string, needs to be digits followed by a unit\n            (like `\"5MB\"`).\n    ",
            "n_words": 158,
            "vocab_size": 105,
            "n_whitespaces": 231,
            "language": "en"
        }
    },
    {
        "id": 10879,
        "commit_id": "13edc16d806fb5d77a6849551178ccc75937f25f",
        "repo": "jina",
        "path": "jina/orchestrate/flow/base.py",
        "file_name": "base.py",
        "fun_name": "start",
        "commit_message": "refactor: rename pod to deployment (#4230)\n\n* refactor: rename pod to deployment\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: undo daemon mistake\r\n\r\n* refactor: leftover cleanup\r\n\r\n* fix: more test fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more tests\r\n\r\n* fix: fix more tests\r\n\r\n* refactor: fix more tests\r\n\r\n* refactor: more tests fixes\r\n\r\n* refactor: rename pea to pod\r\n\r\n* refactor: adjust docs\r\n\r\n* refactor: complete pea renaming\r\n\r\n* refactor: more fixes\r\n\r\n* fix: pea_type in k8s yamls\r\n\r\n* fix: adjust pod args name\r\n\r\n* refactor: rename peapods parser folder\r\n\r\n* fix: da init\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>",
        "code": "def start(self):\n        \n        if self._build_level.value < FlowBuildLevel.GRAPH.value:\n            self.build(copy_flow=False)\n\n        # set env only before the Deployment get started\n        if self.args.env:\n            for k, v in self.args.env.items():\n                os.environ[k] = str(v)\n\n        for k, v in self:\n            if not v.external:\n                self.enter_context(v)\n\n        self._wait_until_all_ready()\n\n        self._build_level = FlowBuildLevel.RUNNING\n\n        return self\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 160,
        "n_words": 41,
        "vocab_size": 34,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 93,
        "n_ast_nodes": 151,
        "n_identifiers": 20,
        "d_id": 1964,
        "documentation": {
            "docstring": "Start to run all Deployments in this Flow.\n\n        Remember to close the Flow with :meth:`close`.\n\n        Note that this method has a timeout of ``timeout_ready`` set in CLI,\n        which is inherited all the way from :class:`jina.orchestrate.pods.Pod`\n\n\n        .. # noqa: DAR401\n\n        :return: this instance\n        ",
            "n_words": 42,
            "vocab_size": 36,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 66913,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/payroll/doctype/payroll_entry/payroll_entry.py",
        "file_name": "payroll_entry.py",
        "fun_name": "get_sal_struct",
        "commit_message": "style: format code with black",
        "code": "def get_sal_struct(company, currency, salary_slip_based_on_timesheet, condition):\n\treturn frappe.db.sql_list(\n\t\t.format(\n\t\t\tcondition=condition\n\t\t),\n\t\t{\n\t\t\t\"company\": company,\n\t\t\t\"currency\": currency,\n\t\t\t\"salary_slip_based_on_timesheet\": salary_slip_based_on_timesheet,\n\t\t},\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 8,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 43,
        "n_ast_nodes": 68,
        "n_identifiers": 9,
        "d_id": 14378,
        "documentation": {
            "docstring": "\n\t\tselect\n\t\t\tname from `tabSalary Structure`\n\t\twhere\n\t\t\tdocstatus = 1 and\n\t\t\tis_active = 'Yes'\n\t\t\tand company = %(company)s\n\t\t\tand currency = %(currency)s and\n\t\t\tifnull(salary_slip_based_on_timesheet,0) = %(salary_slip_based_on_timesheet)s\n\t\t\t{condition}",
            "n_words": 26,
            "vocab_size": 19,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 291738,
        "commit_id": "c576a68d336bc91fd82c299d9b3e5dfdc1c14960",
        "repo": "core",
        "path": "tests/test_core.py",
        "file_name": "test_core.py",
        "fun_name": "test_track_task_functions",
        "commit_message": "Upgrade pytest-aiohttp (#82475)\n\n* Upgrade pytest-aiohttp\r\n\r\n* Make sure executors, tasks and timers are closed\r\n\r\nSome test will trigger warnings on garbage collect, these warnings\r\nspills over into next test.\r\n\r\nSome test trigger tasks that raise errors on shutdown, these spill\r\nover into next test.\r\n\r\nThis is to mimic older pytest-aiohttp and it's behaviour on test\r\ncleanup.\r\n\r\nDiscussions on similar changes for pytest-aiohttp are here:\r\nhttps://github.com/pytest-dev/pytest-asyncio/pull/309\r\n\r\n* Replace loop with event_loop\r\n\r\n* Make sure time is frozen for tests\r\n\r\n* Make sure the ConditionType is not async\r\n\r\n  /home-assistant/homeassistant/helpers/template.py:2082: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\r\n    def wrapper(*args, **kwargs):\r\n  Enable tracemalloc to get traceback where the object was allocated.\r\n  See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.\r\n\r\n* Increase litejet press tests with a factor 10\r\n\r\nThe times are simulated anyway, and we can't stop the normal\r\nevent from occuring.\r\n\r\n* Use async handlers for aiohttp\r\n\r\ntests/components/motioneye/test_camera.py::test_get_still_image_from_camera\r\ntests/components/motioneye/test_camera.py::test_get_still_image_from_camera\r\ntests/components/motioneye/test_camera.py::test_get_stream_from_camera\r\ntests/components/motioneye/test_camera.py::test_get_stream_from_camera\r\ntests/components/motioneye/test_camera.py::test_camera_option_stream_url_template\r\ntests/components/motioneye/test_camera.py::test_camera_option_stream_url_template\r\n  /Users/joakim/src/hass/home-assistant/venv/lib/python3.9/site-packages/aiohttp/web_urldispatcher.py:189: DeprecationWarning: Bare functions are deprecated, use async ones\r\n    warnings.warn(\r\n\r\n* Switch to freezegun in modbus tests\r\n\r\nThe tests allowed clock to tick in between steps\r\n\r\n* Make sure skybell object are fully mocked\r\n\r\nOld tests would trigger attempts to post to could services:\r\n\r\n```\r\nDEBUG:aioskybell:HTTP post https://cloud.myskybell.com/api/v3/login/ Request with headers: {'content-type': 'application/json', 'accept': '*/*', 'x-skybell-app-id': 'd2b542c7-a7e4-4e1e-b77d-2b76911c7c46', 'x-skybell-client-id': '1f36a3c0-6dee-4997-a6db-4e1c67338e57'}\r\n```\r\n\r\n* Fix sorting that broke after rebase",
        "code": "async def test_track_task_functions(event_loop):\n    \n    hass = ha.HomeAssistant()\n    try:\n        assert hass._track_task\n\n        hass.async_stop_track_tasks()\n        assert not hass._track_task\n\n        hass.async_track_tasks()\n        assert hass._track_task\n    finally:\n        await hass.async_stop()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 46,
        "n_ast_nodes": 83,
        "n_identifiers": 9,
        "d_id": 90842,
        "documentation": {
            "docstring": "Test function to start/stop track task and initial state.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 294616,
        "commit_id": "c1a2be72fc8b76b55cfde1823c5688100e397369",
        "repo": "core",
        "path": "homeassistant/components/generic/config_flow.py",
        "file_name": "config_flow.py",
        "fun_name": "async_test_still",
        "commit_message": "Generic IP Camera configflow 2 (#52360)\n\nCo-authored-by: J. Nick Koston <nick@koston.org>",
        "code": "async def async_test_still(hass, info) -> tuple[dict[str, str], str | None]:\n    \n    fmt = None\n    if not (url := info.get(CONF_STILL_IMAGE_URL)):\n        return {}, None\n    if not isinstance(url, template_helper.Template) and url:\n        url = cv.template(url)\n        url.hass = hass\n    try:\n        url = url.async_render(parse_result=False)\n    except TemplateError as err:\n        _LOGGER.error(\"Error parsing template %s: %s\", url, err)\n        return {CONF_STILL_IMAGE_URL: \"template_error\"}, None\n    verify_ssl = info.get(CONF_VERIFY_SSL)\n    auth = generate_auth(info)\n    try:\n        async_client = get_async_client(hass, verify_ssl=verify_ssl)",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "async def async_test_still(hass, info) -> tuple[dict[str, str], str | None]:\n    \"\"\"Verify that the still image is valid before we create an entity.\"\"\"\n    fmt = None\n    if not (url := info.get(CONF_STILL_IMAGE_URL)):\n        return {}, None\n    if not isinstance(url, template_helper.Template) and url:\n        url = cv.template(url)\n        url.hass = hass\n    try:\n        url = url.async_render(parse_result=False)\n    except TemplateError as err:\n        _LOGGER.error(\"Error parsing template %s: %s\", url, err)\n        return {CONF_STILL_IMAGE_URL: \"template_error\"}, None\n    verify_ssl = info.get(CONF_VERIFY_SSL)\n    auth = generate_auth(info)\n    try:\n        async_client = get_async_client(hass, verify_ssl=verify_ssl)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 139,
        "n_words": 63,
        "vocab_size": 50,
        "complexity": 8,
        "nloc": 40,
        "token_counts": 253,
        "n_ast_nodes": 208,
        "n_identifiers": 27,
        "d_id": 93650,
        "documentation": {
            "docstring": "Verify that the still image is valid before we create an entity.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 8560,
        "commit_id": "f60f0e8fc697d98d9f3a4b9ea851329321e64be9",
        "repo": "ludwig",
        "path": "ludwig/explain/captum_ray.py",
        "file_name": "captum_ray.py",
        "fun_name": "split_list",
        "commit_message": "Adds Ray implementation of IntegratedGradientsExplainer that distributes across cluster resources (#2697)",
        "code": "def split_list(v, n):\n    \n    k, m = divmod(len(v), n)\n    return (v[i * k + min(i, m) : (i + 1) * k + min(i + 1, m)] for i in range(n))\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 39,
        "n_words": 30,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 61,
        "n_ast_nodes": 93,
        "n_identifiers": 10,
        "d_id": 1457,
        "documentation": {
            "docstring": "Splits a list into n roughly equal sub-lists.\n\n    Source: https://stackoverflow.com/a/2135920\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 191349,
        "commit_id": "18aeb720126a68201c7e3b5a617139c27c779496",
        "repo": "langchain",
        "path": "tests/unit_tests/chains/test_base.py",
        "file_name": "test_base.py",
        "fun_name": "test_bad_inputs",
        "commit_message": "initial commit",
        "code": "def test_bad_inputs() -> None:\n    \n    chain = FakeChain()\n    with pytest.raises(ValueError):\n        chain({\"foobar\": \"baz\"})\n\n",
        "url": "https://github.com/hwchase17/langchain.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 27,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 28,
        "n_ast_nodes": 56,
        "n_identifiers": 6,
        "d_id": 46487,
        "documentation": {
            "docstring": "Test errors are raised if input keys are not found.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 268031,
        "commit_id": "3eb0485dd92c88cc92152d3656d94492db44b183",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/provider/layout/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "prefix",
        "commit_message": "ansible-test - Use more native type hints. (#78435)\n\n* ansible-test - Use more native type hints.\r\n\r\nSimple search and replace to switch from comments to native type hints for return types of functions with no arguments.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of simple single-line function annotation type comments to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nConversion of single-line function annotation type comments with default values to native type hints.\r\n\r\n* ansible-test - Use more native type hints.\r\n\r\nManual conversion of type annotation comments for functions which have pylint directives.",
        "code": "def prefix(self) -> str:\n        \n        if self.collection:\n            return self.collection.prefix\n\n        return ''\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 79305,
        "documentation": {
            "docstring": "Return the collection prefix or an empty string if not a collection.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 208476,
        "commit_id": "d55a692f46402f397ab38e6c4c9fb6423a85b54f",
        "repo": "ipython",
        "path": "IPython/core/interactiveshell.py",
        "file_name": "interactiveshell.py",
        "fun_name": "object_inspect_mime",
        "commit_message": "Update sphinxify usage",
        "code": "def object_inspect_mime(self, oname, detail_level=0, omit_sections=()):\n        \n        with self.builtin_trap:\n            info = self._object_find(oname)\n            if info.found:\n                docformat = sphinxify(self.object_inspect(oname)) if self.sphinxify_docstring else None\n                return self.inspector._get_info(\n                    info.obj,\n                    oname,\n                    info=info,\n                    detail_level=detail_level,\n                    formatter=docformat,\n                    omit_sections=omit_sections,\n                )\n            else:\n                raise KeyError(oname)\n\n    #-------------------------------------------------------------------------\n    # Things related to history management\n    #-------------------------------------------------------------------------\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 269,
        "n_words": 39,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 20,
        "token_counts": 89,
        "n_ast_nodes": 139,
        "n_identifiers": 18,
        "d_id": 52340,
        "documentation": {
            "docstring": "Get object info as a mimebundle of formatted representations.\n\n        A mimebundle is a dictionary, keyed by mime-type.\n        It must always have the key `'text/plain'`.\n        ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 73172,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/options.py",
        "file_name": "options.py",
        "fun_name": "get_admin_urls_for_registration",
        "commit_message": "Reformat with black",
        "code": "def get_admin_urls_for_registration(self):\n        \n        urls = (\n            re_path(\n                self.url_helper.get_action_url_pattern(\"index\"),\n                self.index_view,\n                name=self.url_helper.get_action_url_name(\"index\"),\n            ),\n            re_path(\n                self.url_helper.get_action_url_pattern(\"create\"),\n                self.create_view,\n                name=self.url_helper.get_action_url_name(\"create\"),\n            ),\n            re_path(\n                self.url_helper.get_action_url_pattern(\"edit\"),\n                self.edit_view,\n                name=self.url_helper.get_action_url_name(\"edit\"),\n            ),\n            re_path(\n                self.url_helper.get_action_url_pattern(\"delete\"),\n                self.delete_view,\n                name=self.url_helper.get_action_url_name(\"delete\"),\n            ),\n        )\n        if self.inspect_view_enabled:\n            urls = urls + (\n                re_path(\n                    self.url_helper.get_action_url_pattern(\"inspect\"),\n                    self.inspect_view,\n                    name=self.url_helper.get_action_url_name(\"inspect\"),\n                ),\n            )\n        if self.history_view_enabled:\n            urls = urls + (\n                re_path(\n                    self.url_helper.get_action_url_pattern(\"history\"),\n                    self.history_view,\n                    name=self.url_helper.get_action_url_name(\"history\"),\n                ),\n            )\n        if self.is_pagemodel:\n            urls = urls + (\n                re_path(\n                    self.url_helper.get_action_url_pattern(\"choose_parent\"),\n                    self.choose_parent_view,\n                    name=self.url_helper.get_action_url_name(\"choose_parent\"),\n                ),\n            )\n        return urls\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 711,
        "n_words": 67,
        "vocab_size": 35,
        "complexity": 4,
        "nloc": 48,
        "token_counts": 241,
        "n_ast_nodes": 385,
        "n_identifiers": 18,
        "d_id": 15969,
        "documentation": {
            "docstring": "\n        Utilised by Wagtail's 'register_admin_urls' hook to register urls for\n        our the views that class offers.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 306478,
        "commit_id": "0c767bd0d37a41af37728b1d8b4eae8dceb7e188",
        "repo": "core",
        "path": "homeassistant/components/sisyphus/media_player.py",
        "file_name": "media_player.py",
        "fun_name": "async_added_to_hass",
        "commit_message": "Improve entity type hints [s] (part 1/2) (#77881)",
        "code": "async def async_added_to_hass(self) -> None:\n        \n        self._table.add_listener(self.async_write_ha_state)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 18,
        "n_ast_nodes": 33,
        "n_identifiers": 5,
        "d_id": 105262,
        "documentation": {
            "docstring": "Add listeners after this object has been initialized.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 80703,
        "commit_id": "17756f0e725fb3a87862ac8234a5974c67b0f6e2",
        "repo": "awx",
        "path": "awx/main/analytics/collectors.py",
        "file_name": "collectors.py",
        "fun_name": "unified_job_template_table",
        "commit_message": "Add job execution environment image to analytics data (#11835)\n\n* Add job execution environment image to analytics data\r\n\r\n* Add EE image to UJT analytics data\r\n\r\n* Bump the unified job templates table",
        "code": "def unified_job_template_table(since, full_path, **kwargs):\n    unified_job_template_query = \n    return _copy_table(table='unified_job_template', query=unified_job_template_query, path=full_path)\n\n\n@register('workflow_job_node_table', '1.0', format='csv', description=_('Data on workflow runs'), expensive=four_hour_slicing)",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "@register('workflow_job_node_table', '1.0', format='csv', description=_('Data on workflow runs'), expensive=four_hour_slicing)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 23,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 28,
        "n_ast_nodes": 84,
        "n_identifiers": 15,
        "d_id": 17093,
        "documentation": {
            "docstring": "COPY (SELECT main_unifiedjobtemplate.id,\n                                 main_unifiedjobtemplate.polymorphic_ctype_id,\n                                 django_content_type.model,\n                                 main_executionenvironment.image as execution_environment_image,\n                                 main_unifiedjobtemplate.created,\n                                 main_unifiedjobtemplate.modified,\n                                 main_unifiedjobtemplate.created_by_id,\n                                 main_unifiedjobtemplate.modified_by_id,\n                                 main_unifiedjobtemplate.name,\n                                 main_unifiedjobtemplate.current_job_id,\n                                 main_unifiedjobtemplate.last_job_id,\n                                 main_unifiedjobtemplate.last_job_failed,\n                                 main_unifiedjobtemplate.last_job_run,\n                                 main_unifiedjobtemplate.next_job_run,\n                                 main_unifiedjobtemplate.next_schedule_id,\n                                 main_unifiedjobtemplate.status\n                                 FROM main_unifiedjobtemplate\n                                 LEFT JOIN main_executionenvironment ON main_executionenvironment.id = main_unifiedjobtemplate.execution_environment_id, django_content_type\n                                 WHERE main_unifiedjobtemplate.polymorphic_ctype_id = django_content_type.id\n                                 ORDER BY main_unifiedjobtemplate.id ASC) TO STDOUT WITH CSV HEADER",
            "n_words": 43,
            "vocab_size": 42,
            "n_whitespaces": 650,
            "language": "en"
        }
    },
    {
        "id": 61433,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "get_base_rev_args",
        "commit_message": "upd; format",
        "code": "def get_base_rev_args(rev):\n        # type: (str) -> List[str]\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 8,
        "n_ast_nodes": 17,
        "n_identifiers": 3,
        "d_id": 12572,
        "documentation": {
            "docstring": "\n        Return the base revision arguments for a vcs command.\n\n        Args:\n          rev: the name of a revision to install.  Cannot be None.\n        ",
            "n_words": 21,
            "vocab_size": 18,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 101237,
        "commit_id": "5e73437be47f2410439a3c6716de96354e6a0c94",
        "repo": "faceswap",
        "path": "lib/align/detected_face.py",
        "file_name": "detected_face.py",
        "fun_name": "stored_mask",
        "commit_message": "lib.align updates:\n  - alignments.py\n    - Add typed dicts for imported alignments\n    - Explicitly check for presence of thumb value in alignments dict\n    - linting\n  - detected_face.py\n    - Typing\n    - Linting\n    - Legacy support for pre-aligned face\n    - Update dependencies to new property names",
        "code": "def stored_mask(self) -> np.ndarray:\n        \n        assert self._mask is not None\n        dims = (self.stored_size, self.stored_size, 1)\n        mask = np.frombuffer(decompress(self._mask), dtype=\"uint8\").reshape(dims)\n        logger.trace(\"stored mask shape: %s\", mask.shape)  # type: ignore\n        return mask\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 71,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 64,
        "n_ast_nodes": 104,
        "n_identifiers": 15,
        "d_id": 20657,
        "documentation": {
            "docstring": " :class:`numpy.ndarray`: The mask at the size of :attr:`stored_size` as it is stored\n        (i.e. with no blurring/centering applied). ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 246367,
        "commit_id": "546b9c9e648f5e2b25bb7c8350570787ff9befae",
        "repo": "synapse",
        "path": "tests/storage/databases/test_state_store.py",
        "file_name": "test_state_store.py",
        "fun_name": "test_smaller_request_deduplicated",
        "commit_message": "Add more tests for in-flight state query duplication. (#12033)",
        "code": "def test_smaller_request_deduplicated(self) -> None:\n        \n        req1 = ensureDeferred(\n            self.state_datastore._get_state_for_group_using_inflight_cache(\n                42, StateFilter.from_types(((\"test.type\", None),))\n            )\n        )\n        self.pump(by=0.1)\n\n        # This should have gone to the database\n        self.assertEqual(len(self.get_state_group_calls), 1)\n        self.assertFalse(req1.called)\n\n        req2 = ensureDeferred(\n            self.state_datastore._get_state_for_group_using_inflight_cache(\n                42, StateFilter.from_types(((\"test.type\", \"b\"),))\n            )\n        )\n        self.pump(by=0.1)\n\n        # No more calls should have gone to the database, because the second\n        # request was already in the in-flight cache!\n        self.assertEqual(len(self.get_state_group_calls), 1)\n        self.assertFalse(req1.called)\n        self.assertFalse(req2.called)\n\n        groups, sf, d = self.get_state_group_calls[0]\n        self.assertEqual(groups, (42,))\n        # The state filter is expanded internally for increased cache hit rate,\n        # so we the database sees a wider state filter than requested.\n        self.assertEqual(sf, ALL_NON_MEMBERS_STATE_FILTER)\n\n        # Now we can complete the request\n        self._complete_request_fake(groups, sf, d)\n\n        self.assertEqual(\n            self.get_success(req1),\n            {(\"test.type\", \"a\"): \"AAA\", (\"test.type\", \"b\"): \"BBB\"},\n        )\n        self.assertEqual(self.get_success(req2), {(\"test.type\", \"b\"): \"BBB\"})\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 387,
        "n_words": 116,
        "vocab_size": 80,
        "complexity": 1,
        "nloc": 37,
        "token_counts": 224,
        "n_ast_nodes": 363,
        "n_identifiers": 22,
        "d_id": 71179,
        "documentation": {
            "docstring": "\n        Tests that duplicate requests for state are deduplicated.\n\n        This test:\n        - requests some state (state group 42, 'all' state filter)\n        - requests a subset of that state, before the first request finishes\n        - checks to see that only one database query was made\n        - completes the database query\n        - checks that both requests see the correct retrieved state\n        ",
            "n_words": 58,
            "vocab_size": 39,
            "n_whitespaces": 115,
            "language": "en"
        }
    },
    {
        "id": 132749,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_trial_scheduler.py",
        "file_name": "test_trial_scheduler.py",
        "fun_name": "testSuccessiveHalving",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def testSuccessiveHalving(self):\n        \n\n        stats = self.default_statistics()\n        sched, mock_runner = self.schedulerSetup(stats[\"max_trials\"])\n        big_bracket = sched._state[\"bracket\"]\n        cur_units = stats[str(stats[\"s_max\"])][\"r\"]\n        # The last bracket will downscale 4 times\n        for x in range(stats[\"brack_count\"] - 1):\n            trials = big_bracket.current_trials()\n            current_length = len(trials)\n            for trl in trials:\n                mock_runner._launch_trial(trl)\n\n            # Provides results from 0 to 8 in order, keeping last one running\n            for i, trl in enumerate(trials):\n                action = sched.on_trial_result(mock_runner, trl, result(cur_units, i))\n                if i < current_length - 1:\n                    self.assertEqual(action, TrialScheduler.PAUSE)\n                mock_runner.process_action(trl, action)\n\n            self.assertEqual(action, TrialScheduler.CONTINUE)\n            new_length = len(big_bracket.current_trials())\n            self.assertEqual(new_length, self.downscale(current_length, sched))\n            cur_units = int(cur_units * sched._eta)\n        self.assertEqual(len(big_bracket.current_trials()), 1)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 323,
        "n_words": 89,
        "vocab_size": 69,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 198,
        "n_ast_nodes": 320,
        "n_identifiers": 33,
        "d_id": 29800,
        "documentation": {
            "docstring": "Setup full band, then iterate through last bracket (n=81)\n        to make sure successive halving is correct.",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 248327,
        "commit_id": "8afb7b55d0527f8c6af7690b162ebaabe9b5d9f5",
        "repo": "synapse",
        "path": "tests/federation/transport/server/test__base.py",
        "file_name": "test__base.py",
        "fun_name": "test_authorization_header",
        "commit_message": "Make handling of federation Authorization header (more) compliant with RFC7230 (#12774)\n\nThe main differences are:\r\n- values with delimiters (such as colons) should be quoted, so always\r\n  quote the origin, since it could contain a colon followed by a port\r\n  number\r\n- should allow more than one space after \"X-Matrix\"\r\n- quoted values with backslash-escaped characters should be unescaped\r\n- names should be case insensitive",
        "code": "def test_authorization_header(self) -> None:\n        \n\n        # test a \"normal\" Authorization header\n        self.assertEqual(\n            _parse_auth_header(\n                b'X-Matrix origin=foo,key=\"ed25519:1\",sig=\"sig\",destination=\"bar\"'\n            ),\n            (\"foo\", \"ed25519:1\", \"sig\", \"bar\"),\n        )\n        # test an Authorization with extra spaces, upper-case names, and escaped\n        # characters\n        self.assertEqual(\n            _parse_auth_header(\n                b'X-Matrix  ORIGIN=foo,KEY=\"ed25\\\\519:1\",SIG=\"sig\",destination=\"bar\"'\n            ),\n            (\"foo\", \"ed25519:1\", \"sig\", \"bar\"),\n        )\n        self.assertEqual(\n            _parse_auth_header(\n                b'X-Matrix origin=foo,key=\"ed25519:1\",sig=\"sig\",destination=\"bar\",extra_field=ignored'\n            ),\n            (\"foo\", \"ed25519:1\", \"sig\", \"bar\"),\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 268,
        "n_words": 53,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 71,
        "n_ast_nodes": 131,
        "n_identifiers": 4,
        "d_id": 72218,
        "documentation": {
            "docstring": "Tests that the Authorization header is parsed correctly.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 126028,
        "commit_id": "862d10c162421706f77f73428429379a8b22fc38",
        "repo": "ray",
        "path": "rllib/evaluation/rollout_worker.py",
        "file_name": "rollout_worker.py",
        "fun_name": "find_free_port",
        "commit_message": "[AIR] Remove ML code from `ray.util` (#27005)\n\nRemoves all ML related code from `ray.util`\r\n\r\nRemoves:\r\n- `ray.util.xgboost`\r\n- `ray.util.lightgbm`\r\n- `ray.util.horovod`\r\n- `ray.util.ray_lightning`\r\n\r\nMoves `ray.util.ml_utils` to other locations\r\n\r\nCloses #23900\r\n\r\nSigned-off-by: Amog Kamsetty <amogkamsetty@yahoo.com>\r\nSigned-off-by: Kai Fricke <kai@anyscale.com>\r\nCo-authored-by: Kai Fricke <kai@anyscale.com>",
        "code": "def find_free_port(self) -> int:\n        \n        from ray.air._internal.util import find_free_port\n\n        return find_free_port()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 22,
        "n_ast_nodes": 36,
        "n_identifiers": 7,
        "d_id": 28045,
        "documentation": {
            "docstring": "Finds a free port on the node that this worker runs on.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 125000,
        "commit_id": "569fe0109629048d08e1d9e023f7769f10bd2244",
        "repo": "ray",
        "path": "rllib/offline/tests/test_dataset_reader.py",
        "file_name": "test_dataset_reader.py",
        "fun_name": "test_relative_json",
        "commit_message": "[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)",
        "code": "def test_relative_json(self):\n        \n        # this should work regardless of where th current working directory is.\n        with tempfile.TemporaryDirectory() as tmp_dir:\n            cwdir = os.getcwd()\n            os.chdir(tmp_dir)\n            unzipped_paths = _unzip_if_needed(\n                [str(Path(self.relative_path) / \"large.json\")], \"json\"\n            )\n            self.assertEqual(\n                os.path.realpath(str(Path(unzipped_paths[0]).absolute())),\n                os.path.realpath(\n                    str(\n                        Path(__file__).parent.parent.parent\n                        / self.relative_path\n                        / \"large.json\"\n                    )\n                ),\n            )\n\n            assert all([Path(fpath).exists() for fpath in unzipped_paths])\n            os.chdir(cwdir)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 325,
        "n_words": 49,
        "vocab_size": 44,
        "complexity": 2,
        "nloc": 19,
        "token_counts": 126,
        "n_ast_nodes": 213,
        "n_identifiers": 23,
        "d_id": 27740,
        "documentation": {
            "docstring": "Tests whether the unzip_if_needed function works correctly on relative json\n        files",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 215281,
        "commit_id": "d4e6111086ff713eb6609dc6c98cec98aded2564",
        "repo": "salt",
        "path": "salt/transport/zeromq.py",
        "file_name": "zeromq.py",
        "fun_name": "pub_connect",
        "commit_message": "Refactor into transports and channels",
        "code": "def pub_connect(self):\n        \n        if self.pub_sock:\n            self.pub_close()\n        ctx = zmq.Context.instance()\n        self._sock_data.sock = ctx.socket(zmq.PUSH)\n        self.pub_sock.setsockopt(zmq.LINGER, -1)\n        if self.opts.get(\"ipc_mode\", \"\") == \"tcp\":\n            pull_uri = \"tcp://127.0.0.1:{}\".format(\n                self.opts.get(\"tcp_master_publish_pull\", 4514)\n            )\n        else:\n            pull_uri = \"ipc://{}\".format(\n                os.path.join(self.opts[\"sock_dir\"], \"publish_pull.ipc\")\n            )\n        log.debug(\"Connecting to pub server: %s\", pull_uri)\n        self.pub_sock.connect(pull_uri)\n        return self._sock_data.sock\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 195,
        "n_words": 40,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 129,
        "n_ast_nodes": 223,
        "n_identifiers": 24,
        "d_id": 53906,
        "documentation": {
            "docstring": "\n        Create and connect this thread's zmq socket. If a publisher socket\n        already exists \"pub_close\" is called before creating and connecting a\n        new socket.\n        ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 82330,
        "commit_id": "9e8eb17497edf8f40d68f7dcb53b1b2c3576313c",
        "repo": "django-cms",
        "path": "cms/utils/request_ip_resolvers.py",
        "file_name": "request_ip_resolvers.py",
        "fun_name": "x_forwarded_ip",
        "commit_message": "Feat/django4 support (#7268)\n\n* feat: update requirements for the deps to install for django 4\r\n\r\n* fix: django utils http deprecations\r\n\r\n* fix: signals deprecation from Django\r\n\r\n* fix: lang key deprecation for session\r\n\r\n* wip: middleware deprecation fixes\r\n\r\n* feat: add django 4 to the ci mix\r\n\r\n* fix: 3.6 is deprecated\r\n\r\n* fix: use the same name as existing convention\r\n\r\n* wip: fix the toolbar\r\n\r\n* fix: more tests\r\n\r\n* fix: issue with thread local in Django\r\n\r\nDjango uses thread-locals internally to track the currently active language for the request.\r\n\r\nPython implements thread-local data through the threading.local class, but as of Django 3.x, multiple requests can be handled in a single thread and so thread-locals will no longer be unique to a single request. Django therefore provides asgiref.Local as a drop-in replacement.\r\n\r\nAuthored-by: Vinit Kumar <vinit.kumar@kidskonnect.nl>\r\nSigned-off-by: Vinit Kumar <vinit.kumar@kidskonnect.nl>\r\n\r\n* fix: add correct version of package deps\r\n\r\n* revert: old style middlewares\r\n\r\n* fix: current user middleware issues\r\n\r\n* fix: django 4.0 is 3.8+ only\r\n\r\n* fix: issue with middlewares upgrade to the new convention\r\n\r\n* fix: port the middleware to new convention\r\n\r\nAuthored-by: Vinit Kumar <vinit.kumar@kidskonnect.nl>\r\nSigned-off-by: Vinit Kumar <vinit.kumar@kidskonnect.nl>\r\nCo-authored-by: Mark Walker <theshow@gmail.com>\r\n\r\n* fix: isort linting issues\r\n\r\n* feat: port the middleware to the new format\r\n\r\n* Move django upper limit from 4 to 5\r\n\r\nCo-authored-by: Mark Walker <theshow@gmail.com>\r\nCo-authored-by: Mark Walker <mark.walker@realbuzz.com>",
        "code": "def x_forwarded_ip(request):\n    \n    ip_address_list = request.headers.get('X-Forwarded-For')\n    if ip_address_list:\n        ip_address_list = ip_address_list.split(',')\n        return ip_address_list[0]\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 35,
        "n_words": 12,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 32,
        "n_ast_nodes": 58,
        "n_identifiers": 6,
        "d_id": 17350,
        "documentation": {
            "docstring": "\n    Returns the IP Address contained in the 'HTTP_X_FORWARDED_FOR' header, if\n    present. Otherwise, `None`.\n\n    Should handle properly configured proxy servers.\n    ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 128822,
        "commit_id": "fe3c2294f08fd27867d77d0e3dc3ebfeba0d6d05",
        "repo": "ray",
        "path": "python/ray/data/tests/test_dataset_image.py",
        "file_name": "test_dataset_image.py",
        "fun_name": "test_basic",
        "commit_message": "[AIR - Datasets] Add experimental `read_images` (#29177)\n\nUsers can't discover ImageFolderDatasource. This PR adds a more-discoverable way to read images.\r\n\r\nSigned-off-by: Balaji Veeramani <bveeramani@berkeley.edu>\r\nCo-authored-by: Balaji Veeramani <bveeramani@berkeley.edu>",
        "code": "def test_basic(self, ray_start_regular_shared):\n        \n        # \"simple\" contains three 32x32 RGB images.\n        ds = ray.data.read_images(\"example://image-datasets/simple\")\n        assert ds.schema().names == [TENSOR_COLUMN_NAME]\n        column_type = ds.schema().types[0]\n        assert isinstance(column_type, ArrowTensorType)\n        assert all(array.shape == (32, 32, 3) for array in ds.take())\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 82,
        "n_words": 33,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 72,
        "n_ast_nodes": 115,
        "n_identifiers": 18,
        "d_id": 28818,
        "documentation": {
            "docstring": "Test basic `read_images` functionality.\n        The folder \"simple\" contains three 32x32 RGB images.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 213228,
        "commit_id": "ec8341197ccdd240a346a95c2a434e5ef9f9ef72",
        "repo": "ivy",
        "path": "ivy/core/general.py",
        "file_name": "general.py",
        "fun_name": "inplace_increment",
        "commit_message": "moved all inplace methods from gradients submodule to general submodule, as inplace ops are also relevant for non-Variable tensors.",
        "code": "def inplace_increment(x, val, f=None):\n    \n    return _cur_framework(x, f=f).inplace_increment(x, val)\n",
        "url": "https://github.com/unifyai/ivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 14,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 28,
        "n_ast_nodes": 43,
        "n_identifiers": 5,
        "d_id": 53647,
        "documentation": {
            "docstring": "\n    Perform in-place increment for the input variable.\n\n    :param x: The variable to increment.\n    :type x: variable\n    :param val: The array to increment the variable with.\n    :type val: array\n    :param f: Machine learning framework. Inferred from inputs if None.\n    :type f: ml_framework, optional\n    :return: The variable following the in-place increment.\n    ",
            "n_words": 49,
            "vocab_size": 30,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 276840,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/generic_utils.py",
        "file_name": "generic_utils.py",
        "fun_name": "func_dump",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def func_dump(func):\n    \n    if os.name == \"nt\":\n        raw_code = marshal.dumps(func.__code__).replace(b\"\\\\\", b\"/\")\n        code = codecs.encode(raw_code, \"base64\").decode(\"ascii\")\n    else:\n        raw_code = marshal.dumps(func.__code__)\n        code = codecs.encode(raw_code, \"base64\").decode(\"ascii\")\n    defaults = func.__defaults__\n    if func.__closure__:\n        closure = tuple(c.cell_contents for c in func.__closure__)\n    else:\n        closure = None\n    return code, defaults, closure\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 105,
        "n_words": 42,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 109,
        "n_ast_nodes": 185,
        "n_identifiers": 20,
        "d_id": 81751,
        "documentation": {
            "docstring": "Serializes a user defined function.\n\n    Args:\n        func: the function to serialize.\n\n    Returns:\n        A tuple `(code, defaults, closure)`.\n    ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 279673,
        "commit_id": "ba5086fa31d24a9f61b46d4a844311b58dea7ff1",
        "repo": "keras",
        "path": "keras/engine/base_layer.py",
        "file_name": "base_layer.py",
        "fun_name": "_set_state",
        "commit_message": "Keras saving: A prototype of config-based (idempotent) saving and loading, with simple model state restoration added. It's done via the archive provided by `zipfile` package.\n\nPreliminary for review and the APIs and implementation are subject to changes.\n\nPiperOrigin-RevId: 470784761",
        "code": "def _set_state(self, state):\n        \n        for child_attr, child_obj in self.__dict__.items():\n            # TODO(rchao): Retrieve non-variable states from the dict as well.\n            # TODO(rchao): Give a warning for mismatches.\n            if isinstance(child_obj, tf.Variable):\n                child_obj.assign(state[child_attr])\n            elif saving_lib.is_container(child_obj):\n                for k, contained_obj in enumerate(child_obj):\n                    if isinstance(contained_obj, tf.Variable):\n                        # Handling the case where `child_obj` is a list/tuple.\n                        contained_obj.assign(state[f\"{child_attr}-{k}\"])\n                    elif isinstance(child_obj, dict) and isinstance(\n                        child_obj[contained_obj], tf.Variable\n                    ):\n                        # Handling the case where `child_obj` is a dict.\n                        child_obj[contained_obj].assign(\n                            state[f\"{child_attr}-{contained_obj}\"]\n                        )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 379,
        "n_words": 69,
        "vocab_size": 49,
        "complexity": 8,
        "nloc": 14,
        "token_counts": 111,
        "n_ast_nodes": 192,
        "n_identifiers": 17,
        "d_id": 83088,
        "documentation": {
            "docstring": "Experimental method for setting the state of this layer object.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 241567,
        "commit_id": "650c710efacd633fa283955145342bb64063c883",
        "repo": "lightning",
        "path": "tests/strategies/test_deepspeed_strategy.py",
        "file_name": "test_deepspeed_strategy.py",
        "fun_name": "test_deepspeed_multigpu_single_file",
        "commit_message": "Rename training plugin test files & names to strategy (#11303)",
        "code": "def test_deepspeed_multigpu_single_file(tmpdir):\n    \n    model = BoringModel()\n    checkpoint_path = os.path.join(tmpdir, \"model.pt\")\n    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True)\n    trainer.fit(model)\n    trainer.save_checkpoint(checkpoint_path)\n\n    trainer = Trainer(\n        default_root_dir=tmpdir, strategy=DeepSpeedStrategy(stage=3), gpus=1, fast_dev_run=True, precision=16\n    )\n    strategy = trainer.strategy\n    assert isinstance(strategy, DeepSpeedStrategy)\n    assert not strategy.load_full_weights\n    with pytest.raises(MisconfigurationException, match=\"DeepSpeed was unable to load the checkpoint.\"):\n        trainer.test(model, ckpt_path=checkpoint_path)\n\n    trainer = Trainer(\n        default_root_dir=tmpdir,\n        strategy=DeepSpeedStrategy(stage=3, load_full_weights=True),\n        gpus=1,\n        fast_dev_run=True,\n        precision=16,\n    )\n    strategy = trainer.strategy\n    assert isinstance(strategy, DeepSpeedStrategy)\n    assert strategy.load_full_weights\n    trainer.test(model, ckpt_path=checkpoint_path)\n\n",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 167,
        "n_words": 64,
        "vocab_size": 41,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 175,
        "n_ast_nodes": 270,
        "n_identifiers": 27,
        "d_id": 69594,
        "documentation": {
            "docstring": "Test to ensure that DeepSpeed loads from a single file checkpoint.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 33995,
        "commit_id": "b67fd797bec56b59e1cd3ad54fa2783f7d7b7cbc",
        "repo": "transformers",
        "path": "utils/check_repo.py",
        "file_name": "check_repo.py",
        "fun_name": "get_model_modules",
        "commit_message": "Add TFVisionEncoderDecoderModel (#14148)\n\n* Start the work on TFVisionEncoderDecoderModel\r\n\r\n* Expose TFVisionEncoderDecoderModel\r\n\r\n* fix import\r\n\r\n* Add modeling_tf_vision_encoder_decoder to _ignore_modules in get_model_modules()\r\n\r\n* reorder\r\n\r\n* Apply the fix for checkpoint loading as in #14016\r\n\r\n* remove attention_mask + fix VISION_DUMMY_INPUTS\r\n\r\n* A minimal change to make TF generate() work for vision models as encoder in encoder-decoder setting\r\n\r\n* fix wrong condition: shape_list(input_ids) == 2\r\n\r\n* add tests\r\n\r\n* use personal TFViTModel checkpoint (for now)\r\n\r\n* Add equivalence tests + projection layer\r\n\r\n* style\r\n\r\n* make sure projection layer can run\r\n\r\n* Add examples\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Clean comments (need to work on TODOs for PyTorch models)\r\n\r\n* Remove TF -> PT in check_pt_tf_equivalence for TFVisionEncoderDecoderModel\r\n\r\n* fixes\r\n\r\n* Revert changes in PT code.\r\n\r\n* Update tests/test_modeling_tf_vision_encoder_decoder.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Add test_inference_coco_en for TF test\r\n\r\n* fix quality\r\n\r\n* fix name\r\n\r\n* build doc\r\n\r\n* add main_input_name\r\n\r\n* Fix ckpt name in test\r\n\r\n* fix diff between master and this PR\r\n\r\n* fix doc\r\n\r\n* fix style and quality\r\n\r\n* fix missing doc\r\n\r\n* fix labels handling\r\n\r\n* Delete auto.rst\r\n\r\n* Add the changes done in #14016\r\n\r\n* fix prefix\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* make style\r\n\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def get_model_modules():\n    \n    _ignore_modules = [\n        \"modeling_auto\",\n        \"modeling_encoder_decoder\",\n        \"modeling_marian\",\n        \"modeling_mmbt\",\n        \"modeling_outputs\",\n        \"modeling_retribert\",\n        \"modeling_utils\",\n        \"modeling_flax_auto\",\n        \"modeling_flax_encoder_decoder\",\n        \"modeling_flax_utils\",\n        \"modeling_speech_encoder_decoder\",\n        \"modeling_flax_vision_encoder_decoder\",\n        \"modeling_transfo_xl_utilities\",\n        \"modeling_tf_auto\",\n        \"modeling_tf_encoder_decoder\",\n        \"modeling_tf_outputs\",\n        \"modeling_tf_pytorch_utils\",\n        \"modeling_tf_utils\",\n        \"modeling_tf_transfo_xl_utilities\",\n        \"modeling_tf_vision_encoder_decoder\",\n        \"modeling_vision_encoder_decoder\",\n    ]\n    modules = []\n    for model in dir(transformers.models):\n        # There are some magic dunder attributes in the dir, we ignore them\n        if not model.startswith(\"__\"):\n            model_module = getattr(transformers.models, model)\n            for submodule in dir(model_module):\n                if submodule.startswith(\"modeling\") and submodule not in _ignore_modules:\n                    modeling_module = getattr(model_module, submodule)\n                    if inspect.ismodule(modeling_module):\n                        modules.append(modeling_module)\n    return modules\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 351,
        "n_words": 74,
        "vocab_size": 62,
        "complexity": 7,
        "nloc": 34,
        "token_counts": 129,
        "n_ast_nodes": 230,
        "n_identifiers": 15,
        "d_id": 6182,
        "documentation": {
            "docstring": "Get the model modules inside the transformers library.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 102613,
        "commit_id": "89f15f591cc3cc3e8ae40e95ffc802f7f2561ece",
        "repo": "chia-blockchain",
        "path": "chia/rpc/wallet_rpc_api.py",
        "file_name": "wallet_rpc_api.py",
        "fun_name": "_stop_wallet",
        "commit_message": "Merge standalone wallet into main (#9793)\n\n* wallet changes from pac\r\n\r\n* cat changes\r\n\r\n* pool tests\r\n\r\n* pooling tests passing\r\n\r\n* offers\r\n\r\n* lint\r\n\r\n* mempool_mode\r\n\r\n* black\r\n\r\n* linting\r\n\r\n* workflow files\r\n\r\n* flake8\r\n\r\n* more cleanup\r\n\r\n* renamed\r\n\r\n* remove obsolete test, don't cast announcement\r\n\r\n* memos are not only bytes32\r\n\r\n* trade renames\r\n\r\n* fix rpcs, block_record\r\n\r\n* wallet rpc, recompile settlement clvm\r\n\r\n* key derivation\r\n\r\n* clvm tests\r\n\r\n* lgtm issues and wallet peers\r\n\r\n* stash\r\n\r\n* rename\r\n\r\n* mypy linting\r\n\r\n* flake8\r\n\r\n* bad initializer\r\n\r\n* flaky tests\r\n\r\n* Make CAT wallets only create on verified hints (#9651)\r\n\r\n* fix clvm tests\r\n\r\n* return to log lvl warn\r\n\r\n* check puzzle unhardened\r\n\r\n* public key, not bytes. api caching change\r\n\r\n* precommit changes\r\n\r\n* remove unused import\r\n\r\n* mypy ci file, tests\r\n\r\n* ensure balance before creating a tx\r\n\r\n* Remove CAT logic from full node test (#9741)\r\n\r\n* Add confirmations and sleeps for wallet (#9742)\r\n\r\n* use pool executor\r\n\r\n* rever merge mistakes/cleanup\r\n\r\n* Fix trade test flakiness (#9751)\r\n\r\n* remove precommit\r\n\r\n* older version of black\r\n\r\n* lint only in super linter\r\n\r\n* Make announcements in RPC be objects instead of bytes (#9752)\r\n\r\n* Make announcements in RPC be objects instead of bytes\r\n\r\n* Lint\r\n\r\n* misc hint'ish cleanup (#9753)\r\n\r\n* misc hint'ish cleanup\r\n\r\n* unremove some ci bits\r\n\r\n* Use main cached_bls.py\r\n\r\n* Fix bad merge in main_pac (#9774)\r\n\r\n* Fix bad merge at 71da0487b9cd5564453ec24b76f1ac773c272b75\r\n\r\n* Remove unused ignores\r\n\r\n* more unused ignores\r\n\r\n* Fix bad merge at 3b143e705057d6c14e2fb3e00078aceff0552d7e\r\n\r\n* One more byte32.from_hexstr\r\n\r\n* Remove obsolete test\r\n\r\n* remove commented out\r\n\r\n* remove duplicate payment object\r\n\r\n* remove long sync\r\n\r\n* remove unused test, noise\r\n\r\n* memos type\r\n\r\n* bytes32\r\n\r\n* make it clear it's a single state at a time\r\n\r\n* copy over asset ids from pacr\r\n\r\n* file endl linter\r\n\r\n* Update chia/server/ws_connection.py\r\n\r\nCo-authored-by: dustinface <35775977+xdustinface@users.noreply.github.com>\r\n\r\nCo-authored-by: Matt Hauff <quexington@gmail.com>\r\nCo-authored-by: Kyle Altendorf <sda@fstab.net>\r\nCo-authored-by: dustinface <35775977+xdustinface@users.noreply.github.com>",
        "code": "async def _stop_wallet(self):\n        \n        if self.service is not None:\n            self.service._close()\n            peers_close_task: Optional[asyncio.Task] = await self.service._await_closed()\n            if peers_close_task is not None:\n                await peers_close_task\n\n    ##########################################################################################\n    # Key management\n    ##########################################################################################\n",
        "url": "https://github.com/Chia-Network/chia-blockchain.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 97,
        "n_words": 26,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 46,
        "n_ast_nodes": 81,
        "n_identifiers": 9,
        "d_id": 21556,
        "documentation": {
            "docstring": "\n        Stops a currently running wallet/key, which allows starting the wallet with a new key.\n        Each key has it's own wallet database.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 125454,
        "commit_id": "1fd2913abdcf376edd148692bfeb5962a6e1c478",
        "repo": "ray",
        "path": "python/ray/serve/deployment_state.py",
        "file_name": "deployment_state.py",
        "fun_name": "should_autoscale",
        "commit_message": "[serve] Refactor checkpointing to write ahead target state (#26797)",
        "code": "def should_autoscale(self) -> bool:\n        \n        return self._target_state.info.autoscaling_policy is not None\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 23,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 19,
        "n_ast_nodes": 32,
        "n_identifiers": 6,
        "d_id": 27880,
        "documentation": {
            "docstring": "\n        Check if the deployment is under autoscaling\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 60271,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/net_spec.py",
        "file_name": "net_spec.py",
        "fun_name": "assign_proto",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def assign_proto(proto, name, val):\n    \n\n    is_repeated_field = hasattr(getattr(proto, name), 'extend')\n    if is_repeated_field and not isinstance(val, list):\n        val = [val]\n    if isinstance(val, list):\n        if isinstance(val[0], dict):\n            for item in val:\n                proto_item = getattr(proto, name).add()\n                for k, v in six.iteritems(item):\n                    assign_proto(proto_item, k, v)\n        else:\n            getattr(proto, name).extend(val)\n    elif isinstance(val, dict):\n        for k, v in six.iteritems(val):\n            assign_proto(getattr(proto, name), k, v)\n    else:\n        setattr(proto, name, val)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 194,
        "n_words": 59,
        "vocab_size": 37,
        "complexity": 9,
        "nloc": 17,
        "token_counts": 151,
        "n_ast_nodes": 230,
        "n_identifiers": 19,
        "d_id": 12059,
        "documentation": {
            "docstring": "Assign a Python object to a protobuf message, based on the Python\n    type (in recursive fashion). Lists become repeated fields/messages, dicts\n    become messages, and other types are assigned directly. For convenience,\n    repeated fields whose values are not lists are converted to single-element\n    lists; e.g., `my_repeated_int_field=3` is converted to\n    `my_repeated_int_field=[3]`.",
            "n_words": 49,
            "vocab_size": 40,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 221366,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/codecs.py",
        "file_name": "codecs.py",
        "fun_name": "readlines",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def readlines(self, sizehint=None, keepends=True):\n\n        \n        data = self.read()\n        return data.splitlines(keepends)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 46,
        "n_identifiers": 7,
        "d_id": 56380,
        "documentation": {
            "docstring": " Read all lines available on the input stream\n            and return them as a list.\n\n            Line breaks are implemented using the codec's decoder\n            method and are included in the list entries.\n\n            sizehint, if given, is ignored since there is no efficient\n            way to finding the true end-of-line.\n\n        ",
            "n_words": 46,
            "vocab_size": 40,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 300608,
        "commit_id": "4885331509eeffe50f42d76b234996467b06170f",
        "repo": "core",
        "path": "homeassistant/helpers/template.py",
        "file_name": "template.py",
        "fun_name": "arc_cosine",
        "commit_message": "Fail template functions when no default specified (#71687)",
        "code": "def arc_cosine(value, default=_SENTINEL):\n    \n    try:\n        return math.acos(float(value))\n    except (ValueError, TypeError):\n        if default is _SENTINEL:\n            raise_no_default(\"acos\", value)\n        return default\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 58,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 70,
        "n_identifiers": 10,
        "d_id": 99468,
        "documentation": {
            "docstring": "Filter and function to get arc cosine of the value.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 176158,
        "commit_id": "dec723f072eb997a497a159dbe8674cd39999ee9",
        "repo": "networkx",
        "path": "networkx/generators/small.py",
        "file_name": "small.py",
        "fun_name": "heawood_graph",
        "commit_message": "Docstrings for the small.py module (#5240)\n\n* added description for the first 5 small graphs\r\n\r\n* modified descriptions based on comment and added description for two more functions\r\n\r\n* added doctrings to all the functions\r\n\r\n* Minor touchups.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def heawood_graph(create_using=None):\n    \n    G = LCF_graph(14, [5, -5], 7, create_using)\n    G.name = \"Heawood Graph\"\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 27,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 52,
        "n_identifiers": 5,
        "d_id": 41728,
        "documentation": {
            "docstring": "\n    Returns the Heawood Graph, a (3,6) cage.\n\n    The Heawood Graph is an undirected graph with 14 nodes and 21 edges,\n    named after Percy John Heawood [1]_.\n    It is cubic symmetric, nonplanar, Hamiltonian, and can be represented\n    in LCF notation as ``[5,-5]^7`` [2]_.\n    It is the unique (3,6)-cage: the regular cubic graph of girth 6 with\n    minimal number of vertices [3]_.\n\n    Parameters\n    ----------\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Returns\n    -------\n    G : networkx Graph\n        Heawood Graph with 14 nodes and 21 edges\n\n    References\n    ----------\n    .. [1] https://en.wikipedia.org/wiki/Heawood_graph\n    .. [2] https://mathworld.wolfram.com/HeawoodGraph.html\n    .. [3] https://www.win.tue.nl/~aeb/graphs/Heawood.html\n\n    ",
            "n_words": 105,
            "vocab_size": 77,
            "n_whitespaces": 176,
            "language": "en"
        }
    },
    {
        "id": 141206,
        "commit_id": "2a5d322e705df080e9254c9c9a3e187c1ea41c4e",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_trial_relative_logdir.py",
        "file_name": "test_trial_relative_logdir.py",
        "fun_name": "testRelativeLogdirWithNestedDir",
        "commit_message": "[tune] Relative logdir paths in trials for ExperimentAnalysis in remote buckets (#25063)\n\nWhen running an experiment for example in the cloud and syncing to a bucket the logdir path in the trials will be changed when working with the checkpoints in the bucket. There are some workarounds, but the easier solution is to also add a rel_logdir containing the relative path to the trials/checkpoints that can handle any changes in the location of experiment results.\r\n\r\nAs discussed with @Yard1 and @krfricke\r\n\r\nCo-authored-by: Antoni Baum <antoni.baum@protonmail.com>\r\nCo-authored-by: Kai Fricke <kai@anyscale.com>",
        "code": "def testRelativeLogdirWithNestedDir(self):\n        \n        local_dir_path = Path(\"/tmp/test_rel\")\n        if local_dir_path.exists():\n            local_dir = tempfile.mkdtemp(prefix=str(local_dir_path) + \"_\")\n        else:\n            local_dir = str(local_dir_path)\n\n        tune.run(\n            \"rel_logdir\",\n            config={\"a\": tune.randint(0, 10)},\n            local_dir=local_dir,\n            # Create a nested experiment directory.\n            name=\"exp_dir/deep_exp_dir\",\n        )\n\n        # Copy the folder\n        local_dir_moved = local_dir + \"_moved\"\n        shutil.copytree(local_dir + \"/exp_dir\", local_dir_moved)\n\n        # Load the trials.\n        with self.assertRaises(ValueError):\n            analysis = tune.ExperimentAnalysis(local_dir)\n\n        # Using the subdir should work, however.\n        analysis = tune.ExperimentAnalysis(local_dir + \"/exp_dir\")\n        analysis_moved = tune.ExperimentAnalysis(local_dir_moved)\n\n        configs = analysis.get_all_configs()\n        configs_moved = analysis_moved.get_all_configs()\n        config = configs[next(iter(configs))]\n        config_moved = configs_moved[next(iter(configs_moved))]\n\n        # Check, if the trial attributes can be loaded.\n        self.assertEqual(len(configs), 1)\n        self.assertEqual(len(configs_moved), 1)\n\n        # Check, if the two configs are equal.\n        self.assertDictEqual(config, config_moved)\n\n        metric = \"metric1\"\n        mode = \"max\"\n        analysis_df = analysis.dataframe(metric, mode)\n        analysis_moved_df = analysis_moved.dataframe(metric, mode)\n\n        self.assertEqual(analysis_df.shape[0], 1)\n        self.assertEqual(analysis_moved_df.shape[0], 1)\n\n        # Drop the `logdir` column as this should be different\n        # between the two trials.\n        analysis_df.drop(columns=\"logdir\", inplace=True)\n        analysis_moved_df.drop(columns=\"logdir\", inplace=True)\n        self.assertEqual(analysis_df, analysis_moved_df)\n\n        # Remove the files and directories.\n        if shutil.rmtree.avoids_symlink_attacks:\n            if local_dir_path.exists():\n                shutil.rmtree(local_dir)\n            shutil.rmtree(local_dir_moved)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 530,
        "n_words": 153,
        "vocab_size": 102,
        "complexity": 4,
        "nloc": 38,
        "token_counts": 299,
        "n_ast_nodes": 505,
        "n_identifiers": 43,
        "d_id": 32294,
        "documentation": {
            "docstring": "Using a nested directory for experiment name.\"\n\n        This should raise an error as nested structures are not\n        supported. It should work, however, to provide a nested\n        path to the `ExperimentAnalysis` class or relocate the\n        folder out of the nested structure.\n        ",
            "n_words": 40,
            "vocab_size": 32,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 140302,
        "commit_id": "eaed256d6863c529b8ada42514f7fba12d146f22",
        "repo": "ray",
        "path": "rllib/execution/tests/test_async_requests_manager.py",
        "file_name": "test_async_requests_manager.py",
        "fun_name": "test_add_remove_actors",
        "commit_message": "[RLlib] Async parallel execution manager. (#24423)",
        "code": "def test_add_remove_actors(self):\n        \n\n        workers = []\n        manager = AsyncRequestsManager(\n            workers, max_remote_requests_in_flight_per_worker=2\n        )\n        if not (\n            (\n                len(manager._all_workers)\n                == len(manager._remote_requests_in_flight)\n                == len(manager._pending_to_actor)\n                == len(manager._pending_remotes)\n                == 0\n            )\n        ):\n            raise ValueError(\"We should have no workers in this case.\")\n\n        assert not manager.call(lambda w: w.task()), (\n            \"Task shouldn't have been \"\n            \"launched since there are no \"\n            \"workers in the manager.\"\n        )\n        worker = RemoteRLlibActor.remote(sleep_time=0.1)\n        manager.add_workers(worker)\n        manager.call(lambda w: w.task())\n        if not (\n            len(manager._remote_requests_in_flight[worker])\n            == len(manager._pending_to_actor)\n            == len(manager._all_workers)\n            == len(manager._pending_remotes)\n            == 1\n        ):\n            raise ValueError(\"We should have 1 worker and 1 pending request\")\n        time.sleep(3)\n        manager.get_ready()\n        # test worker removal\n        for i in range(2):\n            manager.call(lambda w: w.task())\n            assert len(manager._pending_remotes) == i + 1\n        manager.remove_workers(worker)\n        if not ((len(manager._all_workers) == 0)):\n            raise ValueError(\"We should have no workers that we can schedule tasks to\")\n        if not (\n            (len(manager._pending_remotes) == 2 and len(manager._pending_to_actor) == 2)\n        ):\n            raise ValueError(\n                \"We should still have 2 pending requests in flight from the worker\"\n            )\n        time.sleep(3)\n        result = manager.get_ready()\n        if not (\n            len(result) == 1\n            and len(result[worker]) == 2\n            and len(manager._pending_remotes) == 0\n            and len(manager._pending_to_actor) == 0\n        ):\n            raise ValueError(\n                \"We should have 2 ready results from the worker and no pending requests\"\n            )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 744,
        "n_words": 189,
        "vocab_size": 86,
        "complexity": 11,
        "nloc": 56,
        "token_counts": 310,
        "n_ast_nodes": 507,
        "n_identifiers": 27,
        "d_id": 31921,
        "documentation": {
            "docstring": "Tests that the async manager can properly add and remove actors",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 275783,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/preprocessing/text.py",
        "file_name": "text.py",
        "fun_name": "get_config",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_config(self):\n        \n        json_word_counts = json.dumps(self.word_counts)\n        json_word_docs = json.dumps(self.word_docs)\n        json_index_docs = json.dumps(self.index_docs)\n        json_word_index = json.dumps(self.word_index)\n        json_index_word = json.dumps(self.index_word)\n\n        return {\n            \"num_words\": self.num_words,\n            \"filters\": self.filters,\n            \"lower\": self.lower,\n            \"split\": self.split,\n            \"char_level\": self.char_level,\n            \"oov_token\": self.oov_token,\n            \"document_count\": self.document_count,\n            \"word_counts\": json_word_counts,\n            \"word_docs\": json_word_docs,\n            \"index_docs\": json_index_docs,\n            \"index_word\": json_index_word,\n            \"word_index\": json_word_index,\n        }\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 232,
        "n_words": 44,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 121,
        "n_ast_nodes": 203,
        "n_identifiers": 21,
        "d_id": 81462,
        "documentation": {
            "docstring": "Returns the tokenizer configuration as Python dictionary.\n\n        The word count dictionaries used by the tokenizer get serialized\n        into plain JSON, so that the configuration can be read by other\n        projects.\n\n        Returns:\n            A Python dictionary with the tokenizer configuration.\n        ",
            "n_words": 38,
            "vocab_size": 30,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 150520,
        "commit_id": "6f5478cc029bc146e3980affa61dd7956c5cb416",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/replicate/channel.py",
        "file_name": "channel.py",
        "fun_name": "send_direct",
        "commit_message": "DataFrame transmission, strategy follower logic",
        "code": "async def send_direct(self, channel, data):\n        \n        # We iterate over the channels to get reference to the websocket object\n        # so we can disconnect incase of failure\n        await channel.send(data)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 56,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 32,
        "n_identifiers": 5,
        "d_id": 34784,
        "documentation": {
            "docstring": "\n        Send data directly through direct_channel only\n\n        :param direct_channel: The WebSocketChannel object to send data through\n        :param data: The data to send\n        ",
            "n_words": 21,
            "vocab_size": 14,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 9219,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/core/arcface_handler.py",
        "file_name": "arcface_handler.py",
        "fun_name": "align_arcface",
        "commit_message": "initialize ostec",
        "code": "def align_arcface(image, landmarks):\n    \n\n    image_size = (112, 112)\n    dst = np.array([\n        [30.2946, 51.6963],\n        [65.5318, 51.5014],\n        [48.0252, 71.7366],\n        [33.5493, 92.3655],\n        [62.7299, 92.2041]], dtype=np.float32)\n    if image_size[1] == 112:\n        dst[:, 0] += 8.0\n    # dst = dst[:, ::-1]\n    landmark5 = tf.stack([(landmarks[:, 36] + landmarks[:, 39]) / 2,\n                          (landmarks[:, 42] + landmarks[:, 45]) / 2,\n                          landmarks[:, 30],\n                          landmarks[:, 48],\n                          landmarks[:, 54]], 1)\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 217,
        "n_words": 57,
        "vocab_size": 45,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 284,
        "n_ast_nodes": 200,
        "n_identifiers": 12,
        "d_id": 1576,
        "documentation": {
            "docstring": "\n    Aligns 'image' with its corresponding 'landmarks' to a predefined template\n    with similarity transformation. This is the tensorflow implementation of\n    the default alignment procedure of ArcFace\n    Args:\n        image: a 4D float32 numpy array with shape [batch_size, image_height,\n        image_width, 3].\n        landmarks: 68 iBug landmark points of 'image'. [batch_size, 68, 2]\n\n    Returns:\n        4-D float32 numpy array with shape [batch_size, 112, 112, 3]. Contains\n        aligned version of 'image'\n\n    ",
            "n_words": 64,
            "vocab_size": 47,
            "n_whitespaces": 118,
            "language": "en"
        }
    },
    {
        "id": 84571,
        "commit_id": "a1f40ccda5d9bbf91122d755f88e8f03f426fc9a",
        "repo": "zulip",
        "path": "zerver/tests/test_realm.py",
        "file_name": "test_realm.py",
        "fun_name": "test_update_realm_allow_message_editing",
        "commit_message": "message_edit: Make zero invalid value for message_content_edit_time_limit_seconds.\n\nThis commit changes the code to consider zero as an invalid value for\nmessage_content_edit_time_limit_seconds. Now to represent the setting that\nuser can edit the message anytime, the setting value will be \"None\" in\ndatabase and \"unlimited\" will be passed to API from clients.",
        "code": "def test_update_realm_allow_message_editing(self) -> None:\n        \n        self.set_up_db(\"allow_message_editing\", False)\n        self.set_up_db(\"message_content_edit_limit_seconds\", None)\n        self.set_up_db(\"edit_topic_policy\", Realm.POLICY_ADMINS_ONLY)\n        realm = self.update_with_api(\"allow_message_editing\", True)\n        realm = self.update_with_api(\"message_content_edit_limit_seconds\", 100)\n        realm = self.update_with_api(\"edit_topic_policy\", Realm.POLICY_EVERYONE)\n        self.assertEqual(realm.allow_message_editing, True)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 100)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)\n        realm = self.update_with_api(\"allow_message_editing\", False)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 100)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)\n        realm = self.update_with_api(\"message_content_edit_limit_seconds\", 200)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 200)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_EVERYONE)\n        realm = self.update_with_api(\"edit_topic_policy\", Realm.POLICY_ADMINS_ONLY)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 200)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_ADMINS_ONLY)\n\n        realm = self.update_with_api(\"edit_topic_policy\", Realm.POLICY_MODERATORS_ONLY)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 200)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_MODERATORS_ONLY)\n\n        realm = self.update_with_api(\"edit_topic_policy\", Realm.POLICY_FULL_MEMBERS_ONLY)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 200)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_FULL_MEMBERS_ONLY)\n\n        realm = self.update_with_api(\"edit_topic_policy\", Realm.POLICY_MEMBERS_ONLY)\n        self.assertEqual(realm.allow_message_editing, False)\n        self.assertEqual(realm.message_content_edit_limit_seconds, 200)\n        self.assertEqual(realm.edit_topic_policy, Realm.POLICY_MEMBERS_ONLY)\n\n        # Test an invalid value for edit_topic_policy\n        invalid_edit_topic_policy_value = 10\n        req = {\"edit_topic_policy\": orjson.dumps(invalid_edit_topic_policy_value).decode()}\n        result = self.client_patch(\"/json/realm\", req)\n        self.assert_json_error(result, \"Invalid edit_topic_policy\")\n\n        # Test 0 is invalid value of message_content_edit_limit_seconds\n        invalid_message_content_edit_limit_seconds_value = 0\n        req = {\n            \"message_content_edit_limit_seconds\": orjson.dumps(\n                invalid_message_content_edit_limit_seconds_value\n            ).decode()\n        }\n        result = self.client_patch(\"/json/realm\", req)\n        self.assert_json_error(result, \"Bad value for 'message_content_edit_limit_seconds': 0\")\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 490,
        "n_words": 138,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 47,
        "token_counts": 432,
        "n_ast_nodes": 695,
        "n_identifiers": 24,
        "d_id": 17846,
        "documentation": {
            "docstring": "Tests updating the realm property 'allow_message_editing'.",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 5,
            "language": "en"
        }
    },
    {
        "id": 154270,
        "commit_id": "b240370bf83c88589d293b76b4a2409294e06f90",
        "repo": "modin",
        "path": "modin/core/io/column_stores/parquet_dispatcher.py",
        "file_name": "parquet_dispatcher.py",
        "fun_name": "engine",
        "commit_message": "FEAT-#4733: Support fastparquet as engine for `read_parquet` (#4807)\n\nSigned-off-by: Karthik Velayutham <vkarthik@ponder.io>",
        "code": "def engine(self):\n        \n        raise NotImplementedError\n\n    # TODO: make this cache_readonly after docstring inheritance is fixed.",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 31,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 8,
        "n_ast_nodes": 17,
        "n_identifiers": 3,
        "d_id": 35890,
        "documentation": {
            "docstring": "Return string representing what engine is being used.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 160869,
        "commit_id": "6d77c591c59b5678f14ae5af2127eebb7d2415bc",
        "repo": "numpy",
        "path": "numpy/ma/core.py",
        "file_name": "core.py",
        "fun_name": "__truediv__",
        "commit_message": "ENH: Adding __array_ufunc__ capability to MaskedArrays.\n\nThis enables any ufunc numpy operations that are called on a\nMaskedArray to use the masked version of that function automatically\nwithout needing to resort to np.ma.func() calls.",
        "code": "def __truediv__(self, other):\n        \n        if self._delegate_binop(other):\n            return NotImplemented\n        return np.true_divide(self, other)\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 42,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 27,
        "n_ast_nodes": 44,
        "n_identifiers": 7,
        "d_id": 38769,
        "documentation": {
            "docstring": "\n        Divide other into self, and return a new masked array.\n\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 274533,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/losses.py",
        "file_name": "losses.py",
        "fun_name": "__call__",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def __call__(self, y_true, y_pred, sample_weight=None):\n        \n        # If we are wrapping a lambda function strip '<>' from the name as it is not\n        # accepted in scope name.\n        graph_ctx = tf_utils.graph_context_for_symbolic_tensors(\n            y_true, y_pred, sample_weight\n        )\n        with backend.name_scope(self._name_scope), graph_ctx:\n            if tf.executing_eagerly():\n                call_fn = self.call\n            else:\n                call_fn = tf.__internal__.autograph.tf_convert(\n                    self.call, tf.__internal__.autograph.control_status_ctx()\n                )\n            losses = call_fn(y_true, y_pred)\n            return losses_utils.compute_weighted_loss(\n                losses, sample_weight, reduction=self._get_reduction()\n            )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 246,
        "n_words": 59,
        "vocab_size": 50,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 101,
        "n_ast_nodes": 160,
        "n_identifiers": 24,
        "d_id": 81211,
        "documentation": {
            "docstring": "Invokes the `Loss` instance.\n\n        Args:\n          y_true: Ground truth values. shape = `[batch_size, d0, .. dN]`, except\n            sparse loss functions such as sparse categorical crossentropy where\n            shape = `[batch_size, d0, .. dN-1]`\n          y_pred: The predicted values. shape = `[batch_size, d0, .. dN]`\n          sample_weight: Optional `sample_weight` acts as a coefficient for the\n            loss. If a scalar is provided, then the loss is simply scaled by the\n            given value. If `sample_weight` is a tensor of size `[batch_size]`, then\n            the total loss for each sample of the batch is rescaled by the\n            corresponding element in the `sample_weight` vector. If the shape of\n            `sample_weight` is `[batch_size, d0, .. dN-1]` (or can be broadcasted to\n            this shape), then each loss element of `y_pred` is scaled\n            by the corresponding value of `sample_weight`. (Note on`dN-1`: all loss\n              functions reduce by 1 dimension, usually axis=-1.)\n\n        Returns:\n          Weighted loss float `Tensor`. If `reduction` is `NONE`, this has\n            shape `[batch_size, d0, .. dN-1]`; otherwise, it is scalar. (Note `dN-1`\n            because all loss functions reduce by 1 dimension, usually axis=-1.)\n\n        Raises:\n          ValueError: If the shape of `sample_weight` is invalid.\n        ",
            "n_words": 177,
            "vocab_size": 94,
            "n_whitespaces": 384,
            "language": "en"
        }
    },
    {
        "id": 74199,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_jinja2.py",
        "file_name": "test_jinja2.py",
        "fun_name": "test_block_render_result_is_safe",
        "commit_message": "Reformat with black",
        "code": "def test_block_render_result_is_safe(self):\n        \n        stream_block = blocks.StreamBlock(\n            [(\"paragraph\", blocks.CharBlock(template=\"tests/jinja2/paragraph.html\"))]\n        )\n\n        stream_value = stream_block.to_python(\n            [\n                {\"type\": \"paragraph\", \"value\": \"hello world\"},\n            ]\n        )\n\n        result = render_to_string(\n            \"tests/jinja2/stream.html\",\n            {\n                \"value\": stream_value,\n            },\n        )\n\n        self.assertIn(\"<p>hello world</p>\", result)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 183,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 68,
        "n_ast_nodes": 123,
        "n_identifiers": 12,
        "d_id": 16230,
        "documentation": {
            "docstring": "\n        Ensure that any results of template rendering in block.render are marked safe\n        so that they don't get double-escaped when inserted into a parent template (#2541)\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 85913,
        "commit_id": "686675f81bf9402bc9b671e61ea0481b0c5c3468",
        "repo": "sentry",
        "path": "src/sentry/grouping/enhancer/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_matching_frame_actions",
        "commit_message": "fix(grouping): Exception matcher with no frames (#38994)\n\nWe used to pass `-1` as a frame index for exception matchers, which\r\nworked by accident because `-1` is a valid list index in Python, except\r\nwhen the list of frames was empty.\r\n\r\nReplace `-1` by `None` and make sure we do not attempt to access the\r\nlist of frames in the exception matcher, by giving it its own\r\n`matches_frame` override.\r\n\r\nFixes SENTRY-VWW",
        "code": "def get_matching_frame_actions(self, frames, platform, exception_data=None, cache=None):\n        \n        if not self.matchers:\n            return []\n\n        # 1 - Check if exception matchers match\n        for m in self._exception_matchers:\n            if not m.matches_frame(frames, None, platform, exception_data, cache):\n                return []\n\n        rv = []\n\n        # 2 - Check if frame matchers match\n        for idx, frame in enumerate(frames):\n            if all(\n                m.matches_frame(frames, idx, platform, exception_data, cache)\n                for m in self._other_matchers\n            ):\n                for action in self.actions:\n                    rv.append((idx, action))\n\n        return rv\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 247,
        "n_words": 68,
        "vocab_size": 40,
        "complexity": 8,
        "nloc": 15,
        "token_counts": 112,
        "n_ast_nodes": 166,
        "n_identifiers": 19,
        "d_id": 18062,
        "documentation": {
            "docstring": "Given a frame returns all the matching actions based on this rule.\n        If the rule does not match `None` is returned.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 22589,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "brickout-game/brickout-game.py",
        "file_name": "brickout-game.py",
        "fun_name": "update",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def update(self):\n        \n        x, y = pygame.mouse.get_pos()\n        if x >= 0 and x <= (self.__W - self._width):\n            self._xLoc = x\n\n\n\n\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 51,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 69,
        "n_identifiers": 10,
        "d_id": 4369,
        "documentation": {
            "docstring": "\n        moves the paddle at the screen via mouse\n        \n    This class represents a simple Brick class.\n    For representing bricks onto screen.\n",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 133393,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/sgd/torch/worker_group.py",
        "file_name": "worker_group.py",
        "fun_name": "_create_placement_group",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _create_placement_group(self, num_workers):\n        \n        pg = get_current_placement_group()\n        if pg is None:\n            bundle = {\"CPU\": self._num_cpus_per_worker, \"GPU\": int(self._use_gpu)}\n            bundles = [bundle] * num_workers\n            pg = ray.util.placement_group(bundles, strategy=\"SPREAD\")\n            logger.debug(\"Waiting for placement group to start.\")\n            ready, _ = ray.wait([pg.ready()], timeout=SGD_PLACEMENT_GROUP_TIMEOUT_S)\n            if ready:\n                logger.debug(\"Placement group has started.\")\n            else:\n                raise TimeoutError(\n                    \"Placement group creation timed out. Make sure \"\n                    \"your cluster either has enough resources or use \"\n                    \"an autoscaling cluster. Current resources \"\n                    \"available: {}, resources requested by the \"\n                    \"placement group: {}\".format(\n                        ray.available_resources(), pg.bundle_specs\n                    )\n                )\n            self._worker_placement_group = pg\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 376,
        "n_words": 85,
        "vocab_size": 67,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 121,
        "n_ast_nodes": 212,
        "n_identifiers": 26,
        "d_id": 30006,
        "documentation": {
            "docstring": "Creates a placement group for the workers.\n\n        If this worker is already in a placement group then a new one will\n        not be created. This is primarily for when Tune is the upstream and\n        will allocate resources for SGD workers.\n\n        If this worker is not in a placement group, a new one will be created\n        and set. The placement group will have a single bundle for each worker\n        and use the SPREAD strategy for an even distribution.\n        ",
            "n_words": 77,
            "vocab_size": 43,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 281474,
        "commit_id": "82747072c511beb1b2672846ae2ee4aec53eb562",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/economy/fred/fred_controller.py",
        "file_name": "fred_controller.py",
        "fun_name": "print_help",
        "commit_message": "Terminal Wide Rich (#1161)\n\n* My idea for how we handle Rich moving forward\r\n\r\n* remove independent consoles\r\n\r\n* FIxed pylint issues\r\n\r\n* add a few vars\r\n\r\n* Switched print to console\r\n\r\n* More transitions\r\n\r\n* Changed more prints\r\n\r\n* Replaced all prints\r\n\r\n* Fixing tabulate\r\n\r\n* Finished replace tabulate\r\n\r\n* Finished removing rich from Tabulate\r\n\r\n* add Panel around menu\r\n\r\n* add GST watermark under feature flag\r\n\r\n* Fixed 46 tests\r\n\r\n* Delete test_screener[False].yaml\r\n\r\n* Delete test_screener[True].yaml\r\n\r\n* Fixed the rest of the tests\r\n\r\n* add help and source color vars and use rgb\r\n\r\n* rich on stocks/options\r\n\r\n* update rich on disc, dps, sia\r\n\r\n* rich in gov, ins and scr menus\r\n\r\n* ba and ca menus with rich\r\n\r\n* Fixed import issue\r\n\r\n* Fixed some tests\r\n\r\n* removed termcolor\r\n\r\n* Removed prettytable\r\n\r\n* add rich to remaining stocks menus\r\n\r\n* FIxed linting issue\r\n\r\n* Added James' changes\r\n\r\n* Updated dependencies\r\n\r\n* Add rich to cryptocurrency menu\r\n\r\n* refactor economy and forex\r\n\r\n* refactor etf with rich\r\n\r\n* refactor mfunds\r\n\r\n* refactor rich rest\r\n\r\n* not specify style so default color works well on any background\r\n\r\n* Fixing mypy issues\r\n\r\n* Updated tests\r\n\r\n* More test fixes\r\n\r\n* James' test fixes\r\n\r\n* Updating tests : stocks/screener - fix cassettes using BR\r\n\r\n* Updating tests : crypto\r\n\r\n* Updating tests : disable DEBUG_MODE\r\n\r\n* Updating tests : stocks/fa/yfinance\r\n\r\n* minor fixes that escape\r\n\r\n* Improve the rich table function (that replaces tabulate :D )\r\n\r\n* Fixed bad code\r\n\r\n* delete rogue file + dcf fix + NoConsole\r\n\r\n* sia mypy\r\n\r\n* fuck you linter\r\n\r\n* fuck you linter pt 2\r\n\r\n* skip hehe\r\n\r\n* i hate the black linter\r\n\r\n* ubuntu mypy attempt\r\n\r\n* Update : rich_config + gtff\r\n\r\n* Updating tests : conftest\r\n\r\n* Updating tests : stocks\r\n\r\n* Update : rich_config\r\n\r\n* Updating : rich_config\r\n\r\n* make panel configurable for Theodore :b\r\n\r\n* colors update\r\n\r\n* Merged\r\n\r\n* Updating : rich_config + feature_flags\r\n\r\n* Updating : rich_config\r\n\r\n* Updating tests : stocks\r\n\r\n* Updating : feature_flags\r\n\r\nCo-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt>\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>\r\nCo-authored-by: james <jmaslek11@gmail.com>\r\nCo-authored-by: jose-donato <zmcdonato@gmail.com>",
        "code": "def print_help(self):\n        \n        id_string = \"\"\n        for s_id, sub_dict in self.current_series.items():\n            id_string += (\n                f\"    {s_id.upper()}{(self.long_id-len(s_id)) * ' '} :\"\n                f\" [italic]{sub_dict['title']}[/italic]\\n\"\n            )\n        if not id_string:\n            id_string += \"    [bold][red]None[/red][/bold]\\n\"\n        help_text = f\n        console.print(text=help_text, menu=\"Economy - Federal Reserve Economic Data\")\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 150,
        "n_words": 39,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 53,
        "n_ast_nodes": 243,
        "n_identifiers": 16,
        "d_id": 83791,
        "documentation": {
            "docstring": "Print help[cmds]\n    search        search FRED series notes\n    add           add series ID to list\n    rmv           remove series ID from list[/cmds]\n\n[param]Current Series IDs:[/param]\n{id_string}{'[dim]'if not self.current_series else \"\"}[cmds]\n    plot          plot selected series [/cmds]{'[/dim]'if not self.current_series else \"\"}\n{'[dim]'if len(self.current_series.keys())!=1 else \"\"}[menu]\n>   pred          prediction techniques (single SeriesID)[/menu]{'[/dim]'if len(self.current_series.keys())!=1 else \"\"}\n        ",
            "n_words": 49,
            "vocab_size": 35,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 153841,
        "commit_id": "b22b93df20ad25ae7a11f0c89d32fb2f234d4641",
        "repo": "modin",
        "path": "modin/core/execution/ray/common/utils.py",
        "file_name": "utils.py",
        "fun_name": "deserialize",
        "commit_message": "FIX-#4464: Refactor Ray utils and quick fix groupby.count failing on virtual partitions (#4490)\n\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: jeffreykennethli <jkli@ponder.io>",
        "code": "def deserialize(obj):\n    \n    if isinstance(obj, ObjectIDType):\n        return ray.get(obj)\n    elif isinstance(obj, (tuple, list)) and any(\n        isinstance(o, ObjectIDType) for o in obj\n    ):\n        return ray.get(list(obj))\n    elif isinstance(obj, dict) and any(\n        isinstance(val, ObjectIDType) for val in obj.values()\n    ):\n        return dict(zip(obj.keys(), ray.get(list(obj.values()))))\n    else:\n        return obj\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 103,
        "n_words": 40,
        "vocab_size": 27,
        "complexity": 8,
        "nloc": 13,
        "token_counts": 113,
        "n_ast_nodes": 177,
        "n_identifiers": 15,
        "d_id": 35654,
        "documentation": {
            "docstring": "\n    Deserialize a Ray object.\n\n    Parameters\n    ----------\n    obj : ObjectIDType, iterable of ObjectIDType, or mapping of keys to ObjectIDTypes\n        Object(s) to deserialize.\n\n    Returns\n    -------\n    obj\n        The deserialized object.\n    ",
            "n_words": 27,
            "vocab_size": 22,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 141909,
        "commit_id": "cc53a1e28bdb0dc7121f4378c651e6290b7bc84d",
        "repo": "ray",
        "path": "python/ray/air/tests/test_checkpoints.py",
        "file_name": "test_checkpoints.py",
        "fun_name": "test_metadata",
        "commit_message": "[air] update checkpoint.py to deal with metadata in conversion. (#25727)\n\nThis is carved out from https://github.com/ray-project/ray/pull/25558. \r\ntlrd: checkpoint.py current doesn't support the following\r\n```\r\na. from fs to dict checkpoint;\r\nb. drop some marker to dict checkpoint;\r\nc. convert back to fs checkpoint;\r\nd. convert back to dict checkpoint.\r\nAssert that the marker should still be there\r\n```",
        "code": "def test_metadata(self):\n        \n        checkpoint = self._prepare_fs_checkpoint()\n\n        # Convert into dict checkpoint\n        data_dict = checkpoint.to_dict()\n        self.assertIsInstance(data_dict, dict)\n\n        data_dict[\"my_marker\"] = \"marked\"\n\n        # Create from dict\n        checkpoint = Checkpoint.from_dict(data_dict)\n        self.assertTrue(checkpoint._data_dict)\n\n        self._assert_fs_checkpoint(checkpoint)\n\n        # Convert back to dict\n        data_dict_2 = Checkpoint.from_directory(checkpoint.to_directory()).to_dict()\n        assert data_dict_2[\"my_marker\"] == \"marked\"\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 130,
        "n_words": 39,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 79,
        "n_ast_nodes": 142,
        "n_identifiers": 16,
        "d_id": 32525,
        "documentation": {
            "docstring": "Test conversion with metadata involved.\n\n        a. from fs to dict checkpoint;\n        b. drop some marker to dict checkpoint;\n        c. convert back to fs checkpoint;\n        d. convert back to dict checkpoint.\n\n        Assert that the marker should still be there.",
            "n_words": 38,
            "vocab_size": 27,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 203544,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/views/autocomplete.py",
        "file_name": "autocomplete.py",
        "fun_name": "get",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get(self, request, *args, **kwargs):\n        \n        (\n            self.term,\n            self.model_admin,\n            self.source_field,\n            to_field_name,\n        ) = self.process_request(request)\n\n        if not self.has_perm(request):\n            raise PermissionDenied\n\n        self.object_list = self.get_queryset()\n        context = self.get_context_data()\n        return JsonResponse(\n            {\n                \"results\": [\n                    self.serialize_result(obj, to_field_name)\n                    for obj in context[\"object_list\"]\n                ],\n                \"pagination\": {\"more\": context[\"page_obj\"].has_next()},\n            }\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 257,
        "n_words": 41,
        "vocab_size": 38,
        "complexity": 3,
        "nloc": 20,
        "token_counts": 105,
        "n_ast_nodes": 169,
        "n_identifiers": 20,
        "d_id": 50440,
        "documentation": {
            "docstring": "\n        Return a JsonResponse with search results as defined in\n        serialize_result(), by default:\n        {\n            results: [{id: \"123\" text: \"foo\"}],\n            pagination: {more: true}\n        }\n        ",
            "n_words": 22,
            "vocab_size": 22,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 5824,
        "commit_id": "2a157d452611d37cf50ccb7d56ff1a06e9790ecb",
        "repo": "InstaPy",
        "path": "instapy/util.py",
        "file_name": "util.py",
        "fun_name": "get_users_from_dialog",
        "commit_message": "PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438)\n\n* Updated getUserData() and find_element*\r\nSigned-off-by: elulcao <elulcao@icloud.com>\r\n\r\nThanks @breuerfelix for reviewing, 🚀 \r\nPeople in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her",
        "code": "def get_users_from_dialog(old_data, dialog, logger):\n    \n\n    try:\n        user_blocks = dialog.find_elements(By.TAG_NAME, \"a\")\n        loaded_users = [\n            extract_text_from_element(u)\n            for u in user_blocks\n            if extract_text_from_element(u)\n        ]\n        new_data = old_data + loaded_users\n        new_data = remove_duplicates(new_data, True, None)\n\n        return new_data\n\n    except (NoSuchElementException, StaleElementReferenceException) as exc:\n        # Catch stale elements if any\n        logger.error(\n            \"Error occurred while retrieving data.\\n\\t{}\".format(\n                str(exc).encode(\"utf-8\")\n            )\n        )\n\n        return old_data\n\n",
        "url": "https://github.com/InstaPy/InstaPy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 203,
        "n_words": 54,
        "vocab_size": 42,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 88,
        "n_ast_nodes": 147,
        "n_identifiers": 20,
        "d_id": 846,
        "documentation": {
            "docstring": "\n    Prepared to work specially with the dynamic data load in the 'Likes'\n    dialog box\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 142603,
        "commit_id": "43aa2299e6623c8f8c7c4a1b80133459d0aa68b0",
        "repo": "ray",
        "path": "python/ray/tests/test_logging.py",
        "file_name": "test_logging.py",
        "fun_name": "test_log_redirect_to_stderr",
        "commit_message": "[api] Annotate as public / move ray-core APIs to _private and add enforcement rule (#25695)\n\nEnable checking of the ray core module, excluding serve, workflows, and tune, in ./ci/lint/check_api_annotations.py. This required moving many files to ray._private and associated fixes.",
        "code": "def test_log_redirect_to_stderr(shutdown_only, capfd):\n\n    log_components = {\n        ray_constants.PROCESS_TYPE_DASHBOARD: \"Dashboard head grpc address\",\n        ray_constants.PROCESS_TYPE_DASHBOARD_AGENT: \"Dashboard agent grpc address\",\n        ray_constants.PROCESS_TYPE_GCS_SERVER: \"Loading job table data\",\n        # No log monitor output if all components are writing to stderr.\n        ray_constants.PROCESS_TYPE_LOG_MONITOR: \"\",\n        ray_constants.PROCESS_TYPE_MONITOR: \"Starting monitor using ray installation\",\n        ray_constants.PROCESS_TYPE_PYTHON_CORE_WORKER: \"worker server started\",\n        ray_constants.PROCESS_TYPE_PYTHON_CORE_WORKER_DRIVER: \"driver server started\",\n        # TODO(Clark): Add coverage for Ray Client.\n        # ray_constants.PROCESS_TYPE_RAY_CLIENT_SERVER: \"Starting Ray Client server\",\n        ray_constants.PROCESS_TYPE_RAY_CLIENT_SERVER: \"\",\n        ray_constants.PROCESS_TYPE_RAYLET: \"Starting object store with directory\",\n        # No reaper process run (kernel fate-sharing).\n        ray_constants.PROCESS_TYPE_REAPER: \"\",\n        # No reporter process run.\n        ray_constants.PROCESS_TYPE_REPORTER: \"\",\n        # No web UI process run.\n        ray_constants.PROCESS_TYPE_WEB_UI: \"\",\n        # Unused.\n        ray_constants.PROCESS_TYPE_WORKER: \"\",\n    }\n\n    script = ",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "script = \"\"\"\nimport os\nfrom pathlib import Path\n\nimport ray\n\nos.environ[\"RAY_LOG_TO_STDERR\"] = \"1\"\nray.init()\n\nsession_dir = ray._private.worker.global_worker.node.address_info[\"session_dir\"]\nsession_path = Path(session_dir)\nlog_dir_path = session_path / \"logs\"@ray.remote",
        "n_ast_errors": 2,
        "ast_levels": 9,
        "n_whitespaces": 250,
        "n_words": 101,
        "vocab_size": 73,
        "complexity": 4,
        "nloc": 53,
        "token_counts": 150,
        "n_ast_nodes": 167,
        "n_identifiers": 21,
        "d_id": 32740,
        "documentation": {
            "docstring": "\nimport os\nfrom pathlib import Path\n\nimport ray\n\nos.environ[\"RAY_LOG_TO_STDERR\"] = \"1\"\nray.init()\n\nsession_dir = ray._private.worker.global_worker.node.address_info[\"session_dir\"]\nsession_path = Path(session_dir)\nlog_dir_path = session_path / \"logs\"\n\n# Run the basic workload.\n@ray.remote",
            "n_words": 29,
            "vocab_size": 23,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 219692,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "_set_rounding",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _set_rounding(self, type):\n        \n        rounding = self.rounding\n        self.rounding = type\n        return rounding\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 39,
        "n_words": 11,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 20,
        "n_ast_nodes": 34,
        "n_identifiers": 4,
        "d_id": 55717,
        "documentation": {
            "docstring": "Sets the rounding type.\n\n        Sets the rounding type, and returns the current (previous)\n        rounding type.  Often used like:\n\n        context = context.copy()\n        # so you don't change the calling context\n        # if an error occurs in the middle.\n        rounding = context._set_rounding(ROUND_UP)\n        val = self.__sub__(other, context=context)\n        context._set_rounding(rounding)\n\n        This will make it round up for that operation.\n        ",
            "n_words": 54,
            "vocab_size": 41,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 176411,
        "commit_id": "8f4c99debc9440728c5e85f8bffa5d26b232eb6f",
        "repo": "networkx",
        "path": "networkx/classes/multigraph.py",
        "file_name": "multigraph.py",
        "fun_name": "add_edge",
        "commit_message": "Multigraph docs update (#5389)\n\n* Updated MultiDiGraph documentation to include more examples of actually\r\nusing parallel edges, and fixed references to things like G[u, v] where\r\nG[u, v, k] is required for a MultiDigraph. Have not made parallel\r\nchanges in MultiGraph which should maybe also be made?\r\n\r\nDocs tests pass on my end; no code outside of comments was changed.\r\n\r\n-Peter Mawhorter\r\n\r\n* Updated docs for MultiGraph to add more multigraph-specific examples and\r\nfix a few places where untested examples were wrong.\r\n\r\n-Peter Mawhorter\r\n\r\n* [DOC] fix typo\r\n\r\n* add the right amount of separators\r\n\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>",
        "code": "def add_edge(self, u_for_edge, v_for_edge, key=None, **attr):\n        \n        u, v = u_for_edge, v_for_edge\n        # add nodes\n        if u not in self._adj:\n            if u is None:\n                raise ValueError(\"None cannot be a node\")\n            self._adj[u] = self.adjlist_inner_dict_factory()\n            self._node[u] = self.node_attr_dict_factory()\n        if v not in self._adj:\n            if v is None:\n                raise ValueError(\"None cannot be a node\")\n            self._adj[v] = self.adjlist_inner_dict_factory()\n            self._node[v] = self.node_attr_dict_factory()\n        if key is None:\n            key = self.new_edge_key(u, v)\n        if v in self._adj[u]:\n            keydict = self._adj[u][v]\n            datadict = keydict.get(key, self.edge_attr_dict_factory())\n            datadict.update(attr)\n            keydict[key] = datadict\n        else:\n            # selfloops work this way without special treatment\n            datadict = self.edge_attr_dict_factory()\n            datadict.update(attr)\n            keydict = self.edge_key_dict_factory()\n            keydict[key] = datadict\n            self._adj[u][v] = keydict\n            self._adj[v][u] = keydict\n        return key\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 397,
        "n_words": 106,
        "vocab_size": 55,
        "complexity": 7,
        "nloc": 27,
        "token_counts": 222,
        "n_ast_nodes": 352,
        "n_identifiers": 20,
        "d_id": 41876,
        "documentation": {
            "docstring": "Add an edge between u and v.\n\n        The nodes u and v will be automatically added if they are\n        not already in the graph.\n\n        Edge attributes can be specified with keywords or by directly\n        accessing the edge's attribute dictionary. See examples below.\n\n        Parameters\n        ----------\n        u_for_edge, v_for_edge : nodes\n            Nodes can be, for example, strings or numbers.\n            Nodes must be hashable (and not None) Python objects.\n        key : hashable identifier, optional (default=lowest unused integer)\n            Used to distinguish multiedges between a pair of nodes.\n        attr : keyword arguments, optional\n            Edge data (or labels or objects) can be assigned using\n            keyword arguments.\n\n        Returns\n        -------\n        The edge key assigned to the edge.\n\n        See Also\n        --------\n        add_edges_from : add a collection of edges\n\n        Notes\n        -----\n        To replace/update edge data, use the optional key argument\n        to identify a unique edge.  Otherwise a new edge will be created.\n\n        NetworkX algorithms designed for weighted graphs cannot use\n        multigraphs directly because it is not clear how to handle\n        multiedge weights.  Convert to Graph using edge attribute\n        'weight' to enable weighted graph algorithms.\n\n        Default keys are generated using the method `new_edge_key()`.\n        This method can be overridden by subclassing the base class and\n        providing a custom `new_edge_key()` method.\n\n        Examples\n        --------\n        The following each add an additional edge e=(1, 2) to graph G:\n\n        >>> G = nx.MultiGraph()\n        >>> e = (1, 2)\n        >>> ekey = G.add_edge(1, 2)  # explicit two-node form\n        >>> G.add_edge(*e)  # single edge as tuple of two nodes\n        1\n        >>> G.add_edges_from([(1, 2)])  # add edges from iterable container\n        [2]\n\n        Associate data to edges using keywords:\n\n        >>> ekey = G.add_edge(1, 2, weight=3)\n        >>> ekey = G.add_edge(1, 2, key=0, weight=4)  # update data for key=0\n        >>> ekey = G.add_edge(1, 3, weight=7, capacity=15, length=342.7)\n\n        For non-string attribute keys, use subscript notation.\n\n        >>> ekey = G.add_edge(1, 2)\n        >>> G[1][2][0].update({0: 5})\n        >>> G.edges[1, 2, 0].update({0: 5})\n        ",
            "n_words": 302,
            "vocab_size": 187,
            "n_whitespaces": 678,
            "language": "en"
        }
    },
    {
        "id": 132332,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/sync_client.py",
        "file_name": "sync_client.py",
        "fun_name": "set_logdir",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def set_logdir(self, logdir):\n        \n        self.logfile = tempfile.NamedTemporaryFile(\n            prefix=\"log_sync_out\", dir=logdir, suffix=\".log\", delete=False\n        )\n        self._closed = False\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 53,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 37,
        "n_ast_nodes": 61,
        "n_identifiers": 11,
        "d_id": 29741,
        "documentation": {
            "docstring": "Sets the directory to log sync execution output in.\n\n        Args:\n            logdir (str): Log directory.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 244450,
        "commit_id": "2cc631f7656258dec0d12bcce459f5fe3f781b68",
        "repo": "mmdetection",
        "path": "tests/test_datasets/test_pipelines/test_formatting.py",
        "file_name": "test_formatting.py",
        "fun_name": "setUp",
        "commit_message": "Add Transforms",
        "code": "def setUp(self):\n        \n        data_prefix = osp.join(osp.dirname(__file__), '../../data')\n        img_path = osp.join(data_prefix, 'color.jpg')\n        rng = np.random.RandomState(0)\n        self.results1 = {\n            'img_id': 1,\n            'img_path': img_path,\n            'ori_height': 300,\n            'ori_width': 400,\n            'height': 600,\n            'width': 800,\n            'scale_factor': 2.0,\n            'flip': False,\n            'img': rng.rand(300, 400),\n            'gt_seg_map': rng.rand(300, 400),\n            'gt_masks':\n            BitmapMasks(rng.rand(3, 300, 400), height=300, width=400),\n            'gt_bboxes_labels': rng.rand(3, ),\n            'gt_ignore_flags': np.array([0, 0, 1], dtype=np.bool)\n        }\n        self.results2 = {\n            'img_id': 1,\n            'img_path': img_path,\n            'ori_height': 300,\n            'ori_width': 400,\n            'height': 600,\n            'width': 800,\n            'scale_factor': 2.0,\n            'flip': False,\n            'img': rng.rand(300, 400),\n            'gt_seg_map': rng.rand(300, 400),\n            'gt_masks':\n            BitmapMasks(rng.rand(3, 300, 400), height=300, width=400),\n            'gt_bboxes_labels': rng.rand(3, )\n        }\n        self.meta_keys = ('img_id', 'img_path', 'ori_shape', 'img_shape',\n                          'scale_factor', 'flip')\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 481,
        "n_words": 96,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 37,
        "token_counts": 269,
        "n_ast_nodes": 432,
        "n_identifiers": 22,
        "d_id": 70384,
        "documentation": {
            "docstring": "Setup the model and optimizer which are used in every test method.\n\n        TestCase calls functions in this order: setUp() -> testMethod() ->\n        tearDown() -> cleanUp()\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 20009,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_internal/utils/virtualenv.py",
        "file_name": "virtualenv.py",
        "fun_name": "_no_global_under_venv",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _no_global_under_venv() -> bool:\n    \n    cfg_lines = _get_pyvenv_cfg_lines()\n    if cfg_lines is None:\n        # We're not in a \"sane\" venv, so assume there is no system\n        # site-packages access (since that's PEP 405's default state).\n        logger.warning(\n            \"Could not access 'pyvenv.cfg' despite a virtual environment \"\n            \"being active. Assuming global site-packages is not accessible \"\n            \"in this environment.\"\n        )\n        return True\n\n    for line in cfg_lines:\n        match = _INCLUDE_SYSTEM_SITE_PACKAGES_REGEX.match(line)\n        if match is not None and match.group(\"value\") == \"false\":\n            return True\n    return False\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 186,
        "n_words": 78,
        "vocab_size": 59,
        "complexity": 5,
        "nloc": 24,
        "token_counts": 59,
        "n_ast_nodes": 109,
        "n_identifiers": 10,
        "d_id": 3177,
        "documentation": {
            "docstring": "Check `{sys.prefix}/pyvenv.cfg` for system site-packages inclusion\n\n    PEP 405 specifies that when system site-packages are not supposed to be\n    visible from a virtual environment, `pyvenv.cfg` must contain the following\n    line:\n\n        include-system-site-packages = false\n\n    Additionally, log a warning if accessing the file fails.\n    ",
            "n_words": 41,
            "vocab_size": 37,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 167423,
        "commit_id": "734db4f1fde2566a02b3c7ff661a479b0a71633c",
        "repo": "pandas",
        "path": "pandas/io/json/_json.py",
        "file_name": "_json.py",
        "fun_name": "close",
        "commit_message": "TYP: Return annotations for io/{formats,json} (#47516)\n\n* TYP: Return annotations for io/{formats,json}\r\n\r\n* flake8\r\n\r\n* explicitly check whether width is None",
        "code": "def close(self) -> None:\n        \n        if self.handles is not None:\n            self.handles.close()\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 23,
        "n_ast_nodes": 40,
        "n_identifiers": 3,
        "d_id": 40007,
        "documentation": {
            "docstring": "\n        If we opened a stream earlier, in _get_data_from_filepath, we should\n        close it.\n\n        If an open stream or file was passed, we leave it open.\n        ",
            "n_words": 24,
            "vocab_size": 20,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 198387,
        "commit_id": "7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c",
        "repo": "sympy",
        "path": "sympy/integrals/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "_laplace_deep_collect",
        "commit_message": "Cleanup loops and ranges",
        "code": "def _laplace_deep_collect(f, t):\n    \n    func = f.func\n    args = list(f.args)\n    if len(f.args) == 0:\n        return f\n    else:\n        args = [_laplace_deep_collect(arg, t) for arg in args]\n        if func.is_Add:\n            return func(*args).collect(t)\n        else:\n            return func(*args)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 96,
        "n_words": 31,
        "vocab_size": 24,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 73,
        "n_ast_nodes": 119,
        "n_identifiers": 10,
        "d_id": 48899,
        "documentation": {
            "docstring": "\n    This is an internal helper function that traverses through the epression\n    tree of `f(t)` and collects arguments. The purpose of it is that\n    anything like `f(w*t-1*t-c)` will be written as `f((w-1)*t-c)` such that\n    it can match `f(a*t+b)`.\n    ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 105744,
        "commit_id": "67e65c90e9490810b89ee140da11fdd13c356c9c",
        "repo": "datasets",
        "path": "tests/test_metadata_util.py",
        "file_name": "test_metadata_util.py",
        "fun_name": "test_from_yaml_string",
        "commit_message": "Dataset infos in yaml (#4926)\n\n* wip\r\n\r\n* fix Features yaml\r\n\r\n* splits to yaml\r\n\r\n* add _to_yaml_list\r\n\r\n* style\r\n\r\n* example: conll2000\r\n\r\n* example: crime_and_punish\r\n\r\n* add pyyaml dependency\r\n\r\n* remove unused imports\r\n\r\n* remove validation tests\r\n\r\n* style\r\n\r\n* allow dataset_infos to be struct or list in YAML\r\n\r\n* fix test\r\n\r\n* style\r\n\r\n* update \"datasets-cli test\" + remove \"version\"\r\n\r\n* remove config definitions in conll2000 and crime_and_punish\r\n\r\n* remove versions for conll2000 and crime_and_punish\r\n\r\n* move conll2000 and cap dummy data\r\n\r\n* fix test\r\n\r\n* add tests\r\n\r\n* comments and tests\r\n\r\n* more test\r\n\r\n* don't mention the dataset_infos.json file in docs\r\n\r\n* nit in docs\r\n\r\n* docs\r\n\r\n* dataset_infos -> dataset_info\r\n\r\n* again\r\n\r\n* use id2label in class_label\r\n\r\n* update conll2000\r\n\r\n* fix utf-8 yaml dump\r\n\r\n* --save_infos -> --save_info\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Polina Kazakova <polina@huggingface.co>\r\n\r\n* style\r\n\r\n* fix reloading a single dataset_info\r\n\r\n* push info to README.md in push_to_hub\r\n\r\n* update test\r\n\r\nCo-authored-by: Polina Kazakova <polina@huggingface.co>",
        "code": "def test_from_yaml_string(self):\n\n        valid_yaml_string = _dedent(\n            \n        )\n        assert DatasetMetadata.from_yaml_string(valid_yaml_string)\n\n        duplicate_yaml_keys = _dedent(\n            \n        )\n        with self.assertRaises(TypeError):\n            DatasetMetadata.from_yaml_string(duplicate_yaml_keys)\n\n        valid_yaml_with_optional_keys = _dedent(\n            \n        )\n        assert DatasetMetadata.from_yaml_string(valid_yaml_with_optional_keys)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 130,
        "n_words": 21,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 99,
        "token_counts": 51,
        "n_ast_nodes": 95,
        "n_identifiers": 10,
        "d_id": 22202,
        "documentation": {
            "docstring": "\\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            \\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            \\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            ",
            "n_words": 201,
            "vocab_size": 107,
            "n_whitespaces": 1184,
            "language": "en"
        }
    },
    {
        "id": 30466,
        "commit_id": "57ce5c09ee1ac101f79962e59bd44a0396dfb76c",
        "repo": "spotify-downloader",
        "path": "tests/types/test_playlist.py",
        "file_name": "test_playlist.py",
        "fun_name": "test_playlist_from_string",
        "commit_message": "Search album by string enhancement (#1663)",
        "code": "def test_playlist_from_string():\n    \n\n    playlist = Playlist.from_search_term(\"playlist:this is gorillaz\")\n\n    assert playlist.name == \"This Is Gorillaz\"\n    assert playlist.url == \"http://open.spotify.com/playlist/37i9dQZF1DZ06evO25rXbO\"\n    assert len(playlist.urls) > 1\n\n\n@pytest.mark.vcr()",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.vcr()",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 36,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 34,
        "n_ast_nodes": 77,
        "n_identifiers": 11,
        "d_id": 5605,
        "documentation": {
            "docstring": "\n    Test if Playlist class can be initialized from string.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 61319,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/unpacking.py",
        "file_name": "unpacking.py",
        "fun_name": "untar_file",
        "commit_message": "upd; format",
        "code": "def untar_file(filename, location):\n    # type: (str, str) -> None\n    \n    ensure_dir(location)\n    if filename.lower().endswith(\".gz\") or filename.lower().endswith(\".tgz\"):\n        mode = \"r:gz\"\n    elif filename.lower().endswith(BZ2_EXTENSIONS):\n        mode = \"r:bz2\"\n    elif filename.lower().endswith(XZ_EXTENSIONS):\n        mode = \"r:xz\"\n    elif filename.lower().endswith(\".tar\"):\n        mode = \"r\"\n    else:\n        logger.warning(\n            \"Cannot determine compression type for file %s\",\n            filename,\n        )\n        mode = \"r:*\"\n    tar = tarfile.open(filename, mode)\n    try:\n        leading = has_leading_dir([member.name for member in tar.getmembers()])\n        for member in tar.getmembers():\n            fn = member.name\n            if leading:\n                fn = split_leading_dir(fn)[1]\n            path = os.path.join(location, fn)\n            if not is_within_directory(location, path):\n                message = (\n                    \"The tar file ({}) has a file ({}) trying to install \"\n                    \"outside target directory ({})\"\n                )\n                raise InstallationError(message.format(filename, path, location))\n            if member.isdir():\n                ensure_dir(path)\n            elif member.issym():\n                try:\n                    # https://github.com/python/typeshed/issues/2673\n                    tar._extract_member(member, path)  # type: ignore\n                except Exception as exc:\n                    # Some corrupt tar files seem to produce this\n                    # (specifically bad symlinks)\n                    logger.warning(\n                        \"In the tar file %s the member %s is invalid: %s\",\n                        filename,\n                        member.name,\n                        exc,\n                    )\n                    continue\n            else:\n                try:\n                    fp = tar.extractfile(member)\n                except (KeyError, AttributeError) as exc:\n                    # Some corrupt tar files seem to produce this\n                    # (specifically bad symlinks)\n                    logger.warning(\n                        \"In the tar file %s the member %s is invalid: %s\",\n                        filename,\n                        member.name,\n                        exc,\n                    )\n                    continue\n                ensure_dir(os.path.dirname(path))\n                assert fp is not None\n                with open(path, \"wb\") as destfp:\n                    shutil.copyfileobj(fp, destfp)\n                fp.close()\n                # Update the timestamp (useful for cython compiled files)\n                tar.utime(member, path)\n                # member have any execute permissions for user/group/world?\n                if member.mode & 0o111:\n                    set_extracted_file_to_default_mode_plus_executable(path)\n    finally:\n        tar.close()\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1194,
        "n_words": 229,
        "vocab_size": 133,
        "complexity": 16,
        "nloc": 64,
        "token_counts": 345,
        "n_ast_nodes": 591,
        "n_identifiers": 44,
        "d_id": 12505,
        "documentation": {
            "docstring": "\n    Untar the file (with path `filename`) to the destination `location`.\n    All files are written based on system defaults and umask (i.e. permissions\n    are not preserved), except that regular file members with any execute\n    permissions (user, group, or world) have \"chmod +x\" applied after being\n    written.  Note that for windows, any execute changes using os.chmod are\n    no-ops per the python docs.\n    ",
            "n_words": 60,
            "vocab_size": 51,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 181946,
        "commit_id": "2635f58e7c3d10b161ee69a15ebfe6499ac26daa",
        "repo": "textual",
        "path": "src/textual/dom.py",
        "file_name": "dom.py",
        "fun_name": "parent",
        "commit_message": "docstrings and tidy",
        "code": "def parent(self) -> DOMNode:\n        \n        if self._parent is None:\n            raise NoParent(f\"{self} has no parent\")\n        assert isinstance(self._parent, DOMNode)\n        return self._parent\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 34,
        "n_ast_nodes": 60,
        "n_identifiers": 6,
        "d_id": 43685,
        "documentation": {
            "docstring": "Get the parent node.\n\n        Raises:\n            NoParent: If this is the root node.\n\n        Returns:\n            DOMNode: The node which is the direct parent of this node.\n        ",
            "n_words": 24,
            "vocab_size": 17,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 258813,
        "commit_id": "1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/_birch.py",
        "file_name": "_birch.py",
        "fun_name": "merge_subcluster",
        "commit_message": "MNT Update black to stable version (#22474)",
        "code": "def merge_subcluster(self, nominee_cluster, threshold):\n        \n        new_ss = self.squared_sum_ + nominee_cluster.squared_sum_\n        new_ls = self.linear_sum_ + nominee_cluster.linear_sum_\n        new_n = self.n_samples_ + nominee_cluster.n_samples_\n        new_centroid = (1 / new_n) * new_ls\n        new_sq_norm = np.dot(new_centroid, new_centroid)\n\n        # The squared radius of the cluster is defined:\n        #   r^2  = sum_i ||x_i - c||^2 / n\n        # with x_i the n points assigned to the cluster and c its centroid:\n        #   c = sum_i x_i / n\n        # This can be expanded to:\n        #   r^2 = sum_i ||x_i||^2 / n - 2 < sum_i x_i / n, c> + n ||c||^2 / n\n        # and therefore simplifies to:\n        #   r^2 = sum_i ||x_i||^2 / n - ||c||^2\n        sq_radius = new_ss / new_n - new_sq_norm\n\n        if sq_radius <= threshold**2:\n            (\n                self.n_samples_,\n                self.linear_sum_,\n                self.squared_sum_,\n                self.centroid_,\n                self.sq_norm_,\n            ) = (new_n, new_ls, new_ss, new_centroid, new_sq_norm)\n            return True\n        return False\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 373,
        "n_words": 137,
        "vocab_size": 79,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 108,
        "n_ast_nodes": 167,
        "n_identifiers": 17,
        "d_id": 75440,
        "documentation": {
            "docstring": "Check if a cluster is worthy enough to be merged. If\n        yes then merge.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 261187,
        "commit_id": "703bee65e2122ad273cf0b42460c5c28ca638af8",
        "repo": "scikit-learn",
        "path": "sklearn/decomposition/tests/test_online_lda.py",
        "file_name": "test_online_lda.py",
        "fun_name": "test_lda_numerical_consistency",
        "commit_message": "ENH Preserving dtype for np.float32 in LatentDirichletAllocation (#24528)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>\r\nCo-authored-by: takoika <>\r\nCo-authored-by: Takeshi Oura <limit_cycle_underground@yahoo.co.jp>",
        "code": "def test_lda_numerical_consistency(learning_method, global_random_seed):\n    \n    rng = np.random.RandomState(global_random_seed)\n    X64 = rng.uniform(size=(20, 10))\n    X32 = X64.astype(np.float32)\n\n    lda_64 = LatentDirichletAllocation(\n        n_components=5, random_state=global_random_seed, learning_method=learning_method\n    ).fit(X64)\n    lda_32 = LatentDirichletAllocation(\n        n_components=5, random_state=global_random_seed, learning_method=learning_method\n    ).fit(X32)\n\n    assert_allclose(lda_32.components_, lda_64.components_)\n    assert_allclose(lda_32.transform(X32), lda_64.transform(X64))\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 75,
        "n_words": 31,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 110,
        "n_ast_nodes": 170,
        "n_identifiers": 22,
        "d_id": 76684,
        "documentation": {
            "docstring": "Check numerical consistency between np.float32 and np.float64.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 188795,
        "commit_id": "7b9bb6e62424e4b3c960e9e25c45a6946988959c",
        "repo": "calibre",
        "path": "src/calibre/gui2/preferences/create_custom_column.py",
        "file_name": "create_custom_column.py",
        "fun_name": "current_columns",
        "commit_message": "Yet another version of CreateNewCustomColumn.\n\nMy apologies for the multiple commits. I have been working with @davidfor and we cycled a few times. I hope this is the last, barring bugs.",
        "code": "def current_columns(self):\n        \n        return copy.deepcopy(self.custcols) #deepcopy to prevent users from changing it\n",
        "url": "https://github.com/kovidgoyal/calibre.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 15,
        "n_ast_nodes": 28,
        "n_identifiers": 5,
        "d_id": 45933,
        "documentation": {
            "docstring": "\n        Return the currently defined custom columns\n\n        Return the currently defined custom columns including the ones that haven't\n        yet been created. It is a dict of dicts defined as follows:\n            custcols[lookup_name] = {\n                    'label': lookup_name,\n                    'name': column_heading,\n                    'datatype': datatype,\n                    'display': display,\n                    'normalized': None,\n                    'colnum': an integer used internally,\n                    'is_multiple': is_multiple,\n                }\n        Columns that already exist will have additional attributes that this class\n        doesn't use. See calibre.library.field_metadata.add_custom_field() for the\n        complete list.\n        ",
            "n_words": 69,
            "vocab_size": 58,
            "n_whitespaces": 278,
            "language": "en"
        }
    },
    {
        "id": 116966,
        "commit_id": "257dfe6bac18d28088c7bfc79ca22cde682f9cd6",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/tdengine_handler/tdengine_handler.py",
        "file_name": "tdengine_handler.py",
        "fun_name": "get_tables",
        "commit_message": "Added TDENgine Handler",
        "code": "def get_tables(self) -> Response:\n        \n        q = 'SHOW TABLES;'\n\n         \n        return self.native_query(q)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 40,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 18,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 25874,
        "documentation": {
            "docstring": "\n        Get a list with all of the tabels in TDEngine\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 208353,
        "commit_id": "577eee60d51bdd75d3658699effdf6f78a3e604d",
        "repo": "celery",
        "path": "celery/canvas.py",
        "file_name": "canvas.py",
        "fun_name": "set_immutable",
        "commit_message": "Canvas.py doc enhancement (#7907)\n\n* Enhanced doc for canvas._chord.set_immutable()\r\n\r\n* Enhanced doc for canvas._chord.link()\r\n\r\n* Enhanced doc for canvas._chord.link_error()\r\n\r\n* Enhanced doc for canvas._chord.__length_hint__()\r\n\r\n* Enhanced doc for canvas._chord._descend()\r\n\r\n* Enhanced doc for canvas._chord.from_dict()\r\n\r\n* Enhanced doc for canvas._chord.run()",
        "code": "def set_immutable(self, immutable):\n        \n        for task in self.tasks:\n            task.set_immutable(immutable)\n",
        "url": "https://github.com/celery/celery.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 21,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 52289,
        "documentation": {
            "docstring": "Sets the immutable flag on the chord header only.\n\n        Note:\n            Does not affect the chord body.\n\n        Arguments:\n            immutable (bool): The new mutability value for chord header.\n        ",
            "n_words": 26,
            "vocab_size": 21,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 207497,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/test_actions.py",
        "file_name": "test_actions.py",
        "fun_name": "test_model_admin_no_delete_permission_externalsubscriber",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_model_admin_no_delete_permission_externalsubscriber(self):\n        \n        permission = Permission.objects.get(codename=\"delete_subscriber\")\n        self.user.user_permissions.add(permission)\n        delete_confirmation_data = {\n            ACTION_CHECKBOX_NAME: [self.s1.pk, self.s2.pk],\n            \"action\": \"delete_selected\",\n            \"post\": \"yes\",\n        }\n        response = self.client.post(\n            reverse(\"admin:admin_views_subscriber_changelist\"), delete_confirmation_data\n        )\n        self.assertEqual(response.status_code, 403)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 125,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 81,
        "n_ast_nodes": 137,
        "n_identifiers": 21,
        "d_id": 51987,
        "documentation": {
            "docstring": "\n        Permission is denied if the user doesn't have delete permission for a\n        related model (ExternalSubscriber).\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 174533,
        "commit_id": "c6baa7514ab87426780a004e34386c3b104a7f56",
        "repo": "pip",
        "path": "tests/unit/test_req.py",
        "file_name": "test_req.py",
        "fun_name": "test_download_info_vcs",
        "commit_message": "Add download_info to InstallRequirement",
        "code": "def test_download_info_vcs(self) -> None:\n        \n        finder = make_test_finder()\n        with self._basic_resolver(finder) as resolver:\n            ireq = get_processed_req_from_line(\n                \"pip-test-package @ git+https://github.com/pypa/pip-test-package\"\n            )\n            reqset = resolver.resolve([ireq], True)\n            assert len(reqset.all_requirements) == 1\n            req = reqset.all_requirements[0]\n            assert req.download_info\n            assert isinstance(req.download_info.info, VcsInfo)\n            assert req.download_info.url == \"https://github.com/pypa/pip-test-package\"\n            assert req.download_info.info.vcs == \"git\"\n\n",
        "url": "https://github.com/pypa/pip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 177,
        "n_words": 42,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 91,
        "n_ast_nodes": 153,
        "n_identifiers": 19,
        "d_id": 41327,
        "documentation": {
            "docstring": "Test that download_info is set for requirements from git.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 76983,
        "commit_id": "134bd19bef529f0c205a48cedb8574ee0c52d436",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/forms.py",
        "file_name": "forms.py",
        "fun_name": "get_formatted_field_choices",
        "commit_message": "add ability for form builder to split choices by newline\n\n- fixes #3001\n- keep support for comma separated lists if supplied",
        "code": "def get_formatted_field_choices(self, field):\n        \n\n        if \"\\n\" in field.choices:\n            choices = map(\n                lambda x: (\n                    x.strip().rstrip(\",\").strip(),\n                    x.strip().rstrip(\",\").strip(),\n                ),\n                field.choices.split(\"\\r\\n\"),\n            )\n        else:\n            choices = map(lambda x: (x.strip(), x.strip()), field.choices.split(\",\"))\n\n        return choices\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 172,
        "n_words": 28,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 99,
        "n_ast_nodes": 172,
        "n_identifiers": 9,
        "d_id": 16608,
        "documentation": {
            "docstring": "\n        Returns a list of choices [(string, string),] for the field.\n        Split the provided choices into a list, separated by new lines.\n        If no new lines in the provided choices, split by commas.\n        ",
            "n_words": 32,
            "vocab_size": 25,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 249435,
        "commit_id": "84ddcd7bbfe4100101741a408a91f283a8f742c7",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "test_400_missing_param_without_id_access_token",
        "commit_message": "Drop support for calling `/_matrix/client/v3/rooms/{roomId}/invite` without an `id_access_token` (#13241)\n\nFixes #13206\r\n\r\nSigned-off-by: Jacek Kusnierz jacek.kusnierz@tum.de",
        "code": "def test_400_missing_param_without_id_access_token(self) -> None:\n        \n        channel = self.make_request(\n            method=\"POST\",\n            path=\"/rooms/\" + self.room_id + \"/invite\",\n            content={\n                \"id_server\": \"example.com\",\n                \"medium\": \"email\",\n                \"address\": \"teresa@example.com\",\n            },\n            access_token=self.tok,\n        )\n        self.assertEqual(channel.code, 400)\n        self.assertEqual(channel.json_body[\"errcode\"], \"M_MISSING_PARAM\")\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 162,
        "n_words": 27,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 75,
        "n_ast_nodes": 133,
        "n_identifiers": 13,
        "d_id": 72915,
        "documentation": {
            "docstring": "\n        Test that a 3pid invite request returns 400 M_MISSING_PARAM\n        if we do not include id_access_token.\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 251831,
        "commit_id": "b3587b52b25077f68116b9852b041d33e7fc6601",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_multiple_server_connections",
        "commit_message": "make it black!",
        "code": "def test_multiple_server_connections(tctx):\n    \n    server1 = Placeholder(Server)\n    server2 = Placeholder(Server)\n    playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular), hooks=False)\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 25,
        "n_words": 13,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 35,
        "token_counts": 219,
        "n_ast_nodes": 61,
        "n_identifiers": 13,
        "d_id": 73835,
        "documentation": {
            "docstring": "Test multiple requests being rewritten to different targets.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 62933,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/packaging/version.py",
        "file_name": "version.py",
        "fun_name": "parse",
        "commit_message": "upd; format",
        "code": "def parse(version):\n    # type: (str) -> Union[LegacyVersion, Version]\n    \n    try:\n        return Version(version)\n    except InvalidVersion:\n        return LegacyVersion(version)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 41,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 21,
        "n_ast_nodes": 39,
        "n_identifiers": 5,
        "d_id": 13074,
        "documentation": {
            "docstring": "\n    Parse the given version string and return either a :class:`Version` object\n    or a :class:`LegacyVersion` object depending on if the given version is\n    a valid PEP 440 version or a legacy version.\n    ",
            "n_words": 31,
            "vocab_size": 22,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 160301,
        "commit_id": "1b9a98af861441899b882e2ceb40770b4a96b584",
        "repo": "numpy",
        "path": "numpy/core/tests/test_numeric.py",
        "file_name": "test_numeric.py",
        "fun_name": "test_promote_types_metadata",
        "commit_message": "TST: Fixup slow metadata promotion tests to match new behaviour",
        "code": "def test_promote_types_metadata(self, dtype1, dtype2):\n        \n        metadata1 = {1: 1}\n        metadata2 = {2: 2}\n        dtype1 = np.dtype(dtype1, metadata=metadata1)\n        dtype2 = np.dtype(dtype2, metadata=metadata2)\n\n        try:\n            res = np.promote_types(dtype1, dtype2)\n        except TypeError:\n            # Promotion failed, this test only checks metadata\n            return\n\n        if res.char not in \"USV\" or res.names is not None or res.shape != ():\n            # All except string dtypes (and unstructured void) lose metadata\n            # on promotion (unless both dtypes are identical).\n            # At some point structured ones did not, but were restrictive.\n            assert res.metadata is None\n        elif res == dtype1:\n            # If one result is the result, it is usually returned unchanged:\n            assert res is dtype1\n        elif res == dtype2:\n            # dtype1 may have been cast to the same type/kind as dtype2.\n            # If the resulting dtype is identical we currently pick the cast\n            # version of dtype1, which lost the metadata:\n            if np.promote_types(dtype1, dtype2.kind) == dtype2:\n                res.metadata is None\n            else:\n                res.metadata == metadata2\n        else:\n            assert res.metadata is None\n\n        # Try again for byteswapped version\n        dtype1 = dtype1.newbyteorder()\n        assert dtype1.metadata == metadata1\n        res_bs = np.promote_types(dtype1, dtype2)\n        assert res_bs == res\n        assert res_bs.metadata == res.metadata\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 495,
        "n_words": 181,
        "vocab_size": 112,
        "complexity": 8,
        "nloc": 25,
        "token_counts": 175,
        "n_ast_nodes": 284,
        "n_identifiers": 18,
        "d_id": 38594,
        "documentation": {
            "docstring": "Metadata handling in promotion does not appear formalized\n        right now in NumPy. This test should thus be considered to\n        document behaviour, rather than test the correct definition of it.\n\n        This test is very ugly, it was useful for rewriting part of the\n        promotion, but probably should eventually be replaced/deleted\n        (i.e. when metadata handling in promotion is better defined).\n        ",
            "n_words": 58,
            "vocab_size": 46,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 196343,
        "commit_id": "3e167a67bde4b4817666de48bf98d247bed86e2d",
        "repo": "sympy",
        "path": "sympy/combinatorics/perm_groups.py",
        "file_name": "perm_groups.py",
        "fun_name": "equals",
        "commit_message": "Update sympy/combinatorics/perm_groups.py",
        "code": "def equals(self, other):\n        \n        if not isinstance(other, PermutationGroup):\n            return False\n\n        set_self_gens = set(self.generators)\n        set_other_gens = set(other.generators)\n\n        # before reaching the general case there are also certain\n        # optimisation and obvious cases requiring less or no actual\n        # computation.\n        if set_self_gens == set_other_gens:\n            return True\n\n        # in the most general case it will check that each generator of\n        # one group belongs to the other PermutationGroup and vice-versa\n        for gen1 in set_self_gens:\n            if not other.contains(gen1):\n                return False\n        for gen2 in set_other_gens:\n            if not self.contains(gen2):\n                return False\n        return True\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 251,
        "n_words": 86,
        "vocab_size": 59,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 76,
        "n_ast_nodes": 127,
        "n_identifiers": 12,
        "d_id": 47843,
        "documentation": {
            "docstring": "Return ``True`` if PermutationGroup generated by elements in the\n        group are same i.e they represent the same PermutationGroup.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation, PermutationGroup\n        >>> p = Permutation(0, 1, 2, 3, 4, 5)\n        >>> G = PermutationGroup([p, p**2])\n        >>> H = PermutationGroup([p**2, p])\n        >>> G.generators == H.generators\n        False\n        >>> G.equals(H)\n        True\n\n        ",
            "n_words": 53,
            "vocab_size": 43,
            "n_whitespaces": 137,
            "language": "en"
        }
    },
    {
        "id": 320692,
        "commit_id": "cd4429db25746acbec3ef434935959d0f5f66224",
        "repo": "qutebrowser",
        "path": "qutebrowser/misc/earlyinit.py",
        "file_name": "earlyinit.py",
        "fun_name": "check_libraries",
        "commit_message": "Remove 3.6 pins from requirements files.\n\nThen regenerate the relevant files.\nAlso drop dataclasses from requirements files.\nTODO: should we drop the dataclasses-types requirement for mypy too?",
        "code": "def check_libraries():\n    \n    modules = {\n        'jinja2': _missing_str(\"jinja2\"),\n        'yaml': _missing_str(\"PyYAML\"),\n        'PyQt5.QtQml': _missing_str(\"PyQt5.QtQml\"),\n        'PyQt5.QtSql': _missing_str(\"PyQt5.QtSql\"),\n        'PyQt5.QtOpenGL': _missing_str(\"PyQt5.QtOpenGL\"),\n        'PyQt5.QtDBus': _missing_str(\"PyQt5.QtDBus\"),\n    }\n    if sys.version_info < (3, 9):\n        # Backport required\n        modules['importlib_resources'] = _missing_str(\"importlib_resources\")\n    _check_modules(modules)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 101,
        "n_words": 30,
        "vocab_size": 29,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 82,
        "n_ast_nodes": 145,
        "n_identifiers": 6,
        "d_id": 117285,
        "documentation": {
            "docstring": "Check if all needed Python libraries are installed.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 243723,
        "commit_id": "2ae55ccbdad9c842929fb238ea1eb81d1f999024",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "alpha_composite",
        "commit_message": "Improve exception traceback readability",
        "code": "def alpha_composite(self, im, dest=(0, 0), source=(0, 0)):\n        \n\n        if not isinstance(source, (list, tuple)):\n            msg = \"Source must be a tuple\"\n            raise ValueError(msg)\n        if not isinstance(dest, (list, tuple)):\n            msg = \"Destination must be a tuple\"\n            raise ValueError(msg)\n        if not len(source) in (2, 4):\n            msg = \"Source must be a 2 or 4-tuple\"\n            raise ValueError(msg)\n        if not len(dest) == 2:\n            msg = \"Destination must be a 2-tuple\"\n            raise ValueError(msg)\n        if min(source) < 0:\n            msg = \"Source must be non-negative\"\n            raise ValueError(msg)\n\n        if len(source) == 2:\n            source = source + im.size\n\n        # over image, crop if it's not the whole thing.\n        if source == (0, 0) + im.size:\n            overlay = im\n        else:\n            overlay = im.crop(source)\n\n        # target for the paste\n        box = dest + (dest[0] + overlay.width, dest[1] + overlay.height)\n\n        # destination image. don't copy if we're using the whole image.\n        if box == (0, 0) + self.size:\n            background = self\n        else:\n            background = self.crop(box)\n\n        result = alpha_composite(background, overlay)\n        self.paste(result, box)\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 441,
        "n_words": 157,
        "vocab_size": 80,
        "complexity": 9,
        "nloc": 41,
        "token_counts": 226,
        "n_ast_nodes": 362,
        "n_identifiers": 21,
        "d_id": 70092,
        "documentation": {
            "docstring": "'In-place' analog of Image.alpha_composite. Composites an image\n        onto this image.\n\n        :param im: image to composite over this one\n        :param dest: Optional 2 tuple (left, top) specifying the upper\n          left corner in this (destination) image.\n        :param source: Optional 2 (left, top) tuple for the upper left\n          corner in the overlay source image, or 4 tuple (left, top, right,\n          bottom) for the bounds of the source rectangle\n\n        Performance Note: Not currently implemented in-place in the core layer.\n        ",
            "n_words": 75,
            "vocab_size": 49,
            "n_whitespaces": 144,
            "language": "en"
        }
    },
    {
        "id": 117084,
        "commit_id": "ae4fa77a2c0a9fa57cc9c8bc7e8961dd01e4067e",
        "repo": "mindsdb",
        "path": "tests/integration_tests/flows/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "override_recursive",
        "commit_message": "It mysql api test pytest (#3694)\n\n* migration to pytest\r\n\r\n* Tests start passing\r\n\r\n* Fully working tests\r\n\r\n* Increase timeout for mindsdb start\r\n\r\n* reduce amount of logs\r\n\r\n* show logs only for failed tests",
        "code": "def override_recursive(a, b):\n    \n    for key in b:\n        if isinstance(b[key], dict) is False:\n            a[key] = b[key]\n        elif key not in a or isinstance(a[key], dict) is False:\n            a[key] = b[key]\n        # make config section empty by demand\n        elif isinstance(b[key], dict) is True and b[key] == {}:\n            a[key] = b[key]\n        else:\n            override_recursive(a[key], b[key])\n\n@pytest.fixture(scope=\"module\")",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(scope=\"module\")",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 135,
        "n_words": 51,
        "vocab_size": 35,
        "complexity": 7,
        "nloc": 10,
        "token_counts": 106,
        "n_ast_nodes": 176,
        "n_identifiers": 9,
        "d_id": 25896,
        "documentation": {
            "docstring": "Overrides some elements in json 'a' by elements in json 'b'",
            "n_words": 11,
            "vocab_size": 8,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 2395,
        "commit_id": "58da94aae4e66576a7f40b55f2de2d69693bfe20",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/node/common/node_manager/user_manager.py",
        "file_name": "user_manager.py",
        "fun_name": "get_all_applicant",
        "commit_message": "added user application manager,\nreverted default signup on user creation",
        "code": "def get_all_applicant(self) -> List[NoSQLUserApplication]:\n        \n        return self.user_application_manager.all()\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 19,
        "n_ast_nodes": 33,
        "n_identifiers": 6,
        "d_id": 286,
        "documentation": {
            "docstring": "Returns the application data of all the applicants in the database.\n\n        Returns:\n            List[NoSQLUserApplication]: All user applications.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 135117,
        "commit_id": "432f023642731bf53aac9b6c778f9dd7b1d82a57",
        "repo": "ray",
        "path": "rllib/models/tests/test_distributions.py",
        "file_name": "test_distributions.py",
        "fun_name": "test_gumbel_softmax",
        "commit_message": "[RLlib] Deprecate `AlgorithmConfig.framework(\"tfe\")`: Use `tf2` instead. (#29755)",
        "code": "def test_gumbel_softmax(self):\n        \n        for fw, sess in framework_iterator(frameworks=(\"tf2\", \"tf\"), session=True):\n            batch_size = 1000\n            num_categories = 5\n            input_space = Box(-1.0, 1.0, shape=(batch_size, num_categories))\n            input_space.seed(42)\n\n            # Batch of size=n and deterministic.\n            inputs = input_space.sample()\n            gumbel_softmax = GumbelSoftmax(inputs, {}, temperature=1.0)\n\n            expected = softmax(inputs)\n            # Sample n times, expect always mean value (deterministic draw).\n            out = gumbel_softmax.deterministic_sample()\n            check(out, expected)\n\n            # Batch of size=n and non-deterministic -> expect roughly that\n            # the max-likelihood (argmax) ints are output (most of the time).\n            inputs = input_space.sample()\n            gumbel_softmax = GumbelSoftmax(inputs, {}, temperature=1.0)\n            expected_mean = np.mean(np.argmax(inputs, -1)).astype(np.float32)\n            outs = gumbel_softmax.sample()\n            if sess:\n                outs = sess.run(outs)\n            check(np.mean(np.argmax(outs, -1)), expected_mean, rtol=0.08)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 337,
        "n_words": 99,
        "vocab_size": 71,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 188,
        "n_ast_nodes": 286,
        "n_identifiers": 32,
        "d_id": 30547,
        "documentation": {
            "docstring": "Tests the GumbelSoftmax ActionDistribution (tf + eager only).",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 216231,
        "commit_id": "21d3f4bc9eb7b9fb1118c59073595a9e9ee836bd",
        "repo": "salt",
        "path": "salt/modules/cmdmod.py",
        "file_name": "cmdmod.py",
        "fun_name": "_render_cmd",
        "commit_message": "fixes salt bug 61507",
        "code": "def _render_cmd(cmd, cwd, template, saltenv=None, pillarenv=None, pillar_override=None):\n    \n    if saltenv is None:\n        saltenv = __opts__.get(\"saltenv\", \"base\")\n    if not template:\n        return (cmd, cwd)\n\n    # render the path as a template using path_template_engine as the engine\n    if template not in salt.utils.templates.TEMPLATE_REGISTRY:\n        raise CommandExecutionError(\n            \"Attempted to render file paths with unavailable engine {}\".format(template)\n        )\n\n    kwargs = {}\n    kwargs[\"salt\"] = __salt__\n    if pillarenv is not None or pillar_override is not None:\n        pillarenv = pillarenv or __opts__[\"pillarenv\"]\n        kwargs[\"pillar\"] = _gather_pillar(pillarenv, pillar_override)\n    else:\n        kwargs[\"pillar\"] = __pillar__\n    kwargs[\"grains\"] = __grains__\n    kwargs[\"opts\"] = __opts__\n    kwargs[\"saltenv\"] = saltenv\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "nloc": 23,
        "token_counts": 155,
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        "n_identifiers": 20,
        "d_id": 54474,
        "documentation": {
            "docstring": "\n    If template is a valid template engine, process the cmd and cwd through\n    that engine.\n    ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 101714,
        "commit_id": "e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_compile_output",
        "commit_message": "Alignments Tool - Typing, Documentation + Re-org",
        "code": "def _compile_output(self) -> Union[List[str], List[Tuple[str, int]]]:\n        \n        action = self._job.replace(\"-\", \"_\")\n        processor = getattr(self, f\"_get_{action}\")\n        logger.debug(\"Processor: %s\", processor)\n        return [item for item in processor()]  # pylint:disable=unnecessary-comprehension\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 61,
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        "token_counts": 63,
        "n_ast_nodes": 106,
        "n_identifiers": 15,
        "d_id": 21118,
        "documentation": {
            "docstring": " Compile list of frames that meet criteria\n\n        Returns\n        -------\n        list\n            List of filenames or filenames and face indices for the selected criteria\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 110522,
        "commit_id": "94397f4949511881dfc35fbab76cb237f6911424",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_figure.py",
        "file_name": "test_figure.py",
        "fun_name": "test_layout_change_warning",
        "commit_message": "BUG: Warn when an existing layout manager changes to tight layout",
        "code": "def test_layout_change_warning(layout):\n    \n    fig, ax = plt.subplots(layout=layout)\n    with pytest.warns(UserWarning, match='The figure layout has changed to'):\n        plt.tight_layout()\n\n\n@check_figures_equal(extensions=[\"png\", \"pdf\"])",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "@check_figures_equal(extensions=[\"png\", \"pdf\"])",
        "n_ast_errors": 1,
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        "d_id": 24198,
        "documentation": {
            "docstring": "\n    Raise a warning when a previously assigned layout changes to tight using\n    plt.tight_layout().\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 21553,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/rich/_win32_console.py",
        "file_name": "_win32_console.py",
        "fun_name": "move_cursor_forward",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def move_cursor_forward(self) -> None:\n        \n        row, col = self.cursor_position\n        if col == self.screen_size.col - 1:\n            row += 1\n            col = 0\n        else:\n            col += 1\n        SetConsoleCursorPosition(\n            self._handle, coords=WindowsCoordinates(row=row, col=col)\n        )\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_identifiers": 10,
        "d_id": 3923,
        "documentation": {
            "docstring": "Move the cursor forward a single cell. Wrap to the next line if required.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 67893,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/report/itemwise_recommended_reorder_level/itemwise_recommended_reorder_level.py",
        "file_name": "itemwise_recommended_reorder_level.py",
        "fun_name": "get_item_info",
        "commit_message": "style: format code with black",
        "code": "def get_item_info(filters):\n\tfrom erpnext.stock.report.stock_ledger.stock_ledger import get_item_group_condition\n\n\tconditions = [get_item_group_condition(filters.get(\"item_group\"))]\n\tif filters.get(\"brand\"):\n\t\tconditions.append(\"item.brand=%(brand)s\")\n\tconditions.append(\"is_stock_item = 1\")\n\n\treturn frappe.db.sql(\n\t\t.format(\n\t\t\t\" and \".join(conditions)\n\t\t),\n\t\tfilters,\n\t\tas_dict=1,\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 12,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 76,
        "n_ast_nodes": 128,
        "n_identifiers": 16,
        "d_id": 14656,
        "documentation": {
            "docstring": "select name, item_name, description, brand, item_group,\n\t\tsafety_stock, lead_time_days from `tabItem` item where {}",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 320685,
        "commit_id": "bd8c940320b7d8476b422edd9c417703db64f603",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/webkit/http.py",
        "file_name": "http.py",
        "fun_name": "parse_content_disposition",
        "commit_message": "Simplify some syntax\n\nFound via pyupgrade",
        "code": "def parse_content_disposition(reply):\n    \n    is_inline = True\n    filename = None\n    content_disposition_header = b'Content-Disposition'\n    # First check if the Content-Disposition header has a filename\n    # attribute.\n    if reply.hasRawHeader(content_disposition_header):\n        # We use the unsafe variant of the filename as we sanitize it via\n        # os.path.basename later.\n        try:\n            value = bytes(reply.rawHeader(content_disposition_header))\n            log.network.debug(\"Parsing Content-Disposition: {value!r}\")\n            content_disposition = ContentDisposition.parse(value)\n            filename = content_disposition.filename()\n        except ContentDispositionError as e:\n            log.network.error(f\"Error while parsing filename: {e}\")\n        else:\n            is_inline = content_disposition.is_inline()\n    # Then try to get filename from url\n    if not filename:\n        filename = reply.url().path().rstrip('/')\n    # If that fails as well, use a fallback\n    if not filename:\n        filename = 'qutebrowser-download'\n    return is_inline, os.path.basename(filename)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 251,
        "n_words": 100,
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        "complexity": 5,
        "nloc": 19,
        "token_counts": 121,
        "n_ast_nodes": 222,
        "n_identifiers": 23,
        "d_id": 117279,
        "documentation": {
            "docstring": "Parse a content_disposition header.\n\n    Args:\n        reply: The QNetworkReply to get a filename for.\n\n    Return:\n        A (is_inline, filename) tuple.\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 20,
        "commit_id": "05edf746cf5742b562996cf1a319b404152960e5",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/node/common/node_service/object_request/object_request_messages.py",
        "file_name": "object_request_messages.py",
        "fun_name": "get_protobuf_schema",
        "commit_message": "MOVE GetAllRequestsMessage and GetAllRequestsResponseMessage to the proper message file",
        "code": "def get_protobuf_schema() -> GeneratedProtocolMessageType:\n        \n\n        return GetAllRequestsMessage_PB\n\n\n@serializable()",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "@serializable()",
        "n_ast_errors": 1,
        "ast_levels": 6,
        "n_whitespaces": 20,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
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        "token_counts": 9,
        "n_ast_nodes": 26,
        "n_identifiers": 4,
        "d_id": 12,
        "documentation": {
            "docstring": "Return the type of protobuf object which stores a class of this type\n\n        As a part of serialization and deserialization, we need the ability to\n        lookup the protobuf object type directly from the object type. This\n        static method allows us to do this.\n\n        Importantly, this method is also used to create the reverse lookup ability within\n        the metaclass of Serializable. In the metaclass, it calls this method and then\n        it takes whatever type is returned from this method and adds an attribute to it\n        with the type of this class attached to it. See the MetaSerializable class for details.\n\n        :return: the type of protobuf object which corresponds to this class.\n        :rtype: GeneratedProtocolMessageType\n\n        ",
            "n_words": 112,
            "vocab_size": 63,
            "n_whitespaces": 182,
            "language": "en"
        }
    },
    {
        "id": 194984,
        "commit_id": "c946fb395d52e0f7ad67646a1c01b8327c232027",
        "repo": "ParlAI",
        "path": "parlai/crowdsourcing/utils/tests.py",
        "file_name": "tests.py",
        "fun_name": "_get_server",
        "commit_message": "Updating to Mephisto 1.0 (#4426)\n\n* Version bumps\r\n\r\n* Correct version\r\n\r\n* Correct beta release\r\n\r\n* Tests should _run_, but fail\r\n\r\n* Temporarily force run all crowdsourcing tests\r\n\r\n* Forcerun crowdsourcing checks\r\n\r\n* Typo\r\n\r\n* Update config.yml\r\n\r\n* Minor\r\n\r\n* Update acute_eval_runner.py\r\n\r\n* Simple fix, more tests run\r\n\r\n* Force cleanup of the server.\r\n\r\n* Correct AcuteEvalRunner.run_unit\r\n\r\n* using v1.0.0 from Mephisto github\r\n\r\n* Rolling back temp solution\r\n\r\n* Fix model chat test?\r\n\r\n* chat demo fix\r\n\r\n* QA fix\r\n\r\n* model image chat\r\n\r\n* Only add sleep time to model image chat\r\n\r\n* Remove agent retry loop\r\n\r\n* Remove 2 lines\r\n\r\n* Lengthen time\r\n\r\n* Fixing model chat onboarding and task frontend\r\n\r\n* fix acute eval test\r\n\r\n* Remove TODOs\r\n\r\nCo-authored-by: Eric Smith <EricMichaelSmith@users.noreply.github.com>\r\nCo-authored-by: Stephen Roller <roller@fb.com>\r\nCo-authored-by: EricMichaelSmith <ems@fb.com>\r\nCo-authored-by: Dexter Ju <da.ju.fr@gmail.com>",
        "code": "def _get_server(self):\n        \n        live_run = self._get_live_run()\n        return live_run.architect.server\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 6,
        "d_id": 47139,
        "documentation": {
            "docstring": "\n        Return the MockArchitect's server associated with this run\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 102070,
        "commit_id": "48c886b3dce3d3117ad16edaf35c8abd28dc51f5",
        "repo": "faceswap",
        "path": "lib/sysinfo.py",
        "file_name": "sysinfo.py",
        "fun_name": "_installed_pip",
        "commit_message": "Allow decoding errors",
        "code": "def _installed_pip(self):\n        \n        with Popen(f\"{sys.executable} -m pip freeze\", shell=True, stdout=PIPE) as pip:\n            installed = pip.communicate()[0].decode(self._encoding, errors=\"replace\").splitlines()\n        return \"\\n\".join(installed)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 49,
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        "vocab_size": 17,
        "complexity": 1,
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        "token_counts": 55,
        "n_ast_nodes": 103,
        "n_identifiers": 16,
        "d_id": 21435,
        "documentation": {
            "docstring": " str: The list of installed pip packages within Faceswap's scope. ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 21340,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/shutil.py",
        "file_name": "shutil.py",
        "fun_name": "copy2",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def copy2(src, dst):\n    \n    if os.path.isdir(dst):\n        dst = os.path.join(dst, os.path.basename(src))\n    copyfile(src, dst)\n    copystat(src, dst)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "documentation": {
            "docstring": "Copy data and all stat info (\"cp -p src dst\").\n\n    The destination may be a directory.\n\n    ",
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            "language": "en"
        }
    },
    {
        "id": 50183,
        "commit_id": "ffcde21305c61d950a9f93e57e6180c9a9665b87",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/beam.py",
        "file_name": "beam.py",
        "fun_name": "_merge_batch_beams",
        "commit_message": "add disco_diffusion_ernievil_base",
        "code": "def _merge_batch_beams(self, x):\n        r\n        check_type(x, 'x', (Variable), 'BeamSearchDecoder._merge_batch_beams')\n        # TODO: avoid fake shape in compile-time like tile_beam_merge_with_batch\n        return nn.reshape(x, shape=[-1] + list(x.shape[2:]))\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "token_counts": 46,
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        "n_identifiers": 9,
        "d_id": 10041,
        "documentation": {
            "docstring": "\n        Reshape a tensor with shape `[batch_size, beam_size, ...]` to a new\n        tensor with shape `[batch_size * beam_size, ...]`.\n\n        Parameters:\n            x(Variable): A tensor with shape `[batch_size, beam_size, ...]`. The\n                data type should be float32, float64, int32, int64 or bool.\n\n        Returns:\n            Variable: A tensor with shape `[batch_size * beam_size, ...]`, whose \\\n                data type is same as `x`.\n        ",
            "n_words": 56,
            "vocab_size": 36,
            "n_whitespaces": 144,
            "language": "en"
        }
    },
    {
        "id": 119313,
        "commit_id": "e085370ec4137cf0f73c5163cb664bc4e1c46082",
        "repo": "jax",
        "path": "jax/_src/third_party/scipy/signal_helper.py",
        "file_name": "signal_helper.py",
        "fun_name": "_median_bias",
        "commit_message": "Add some functions for spectral analysis.\n\nThis commit adds \"stft\", \"csd\", and \"welch\" functions in scipy.signal.",
        "code": "def _median_bias(n):\n  \n  ii_2 = jnp.arange(2., n, 2)\n  return 1 + jnp.sum(1. / (ii_2 + 1) - 1. / ii_2)\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "token_counts": 40,
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        "n_identifiers": 6,
        "d_id": 26584,
        "documentation": {
            "docstring": "\n  Returns the bias of the median of a set of periodograms relative to\n  the mean.\n  See Appendix B from [1]_ for details.\n  Parameters\n  ----------\n  n : int\n      Numbers of periodograms being averaged.\n  Returns\n  -------\n  bias : float\n      Calculated bias.\n  References\n  ----------\n  .. [1] B. Allen, W.G. Anderson, P.R. Brady, D.A. Brown, J.D.E. Creighton.\n          \"FINDCHIRP: an algorithm for detection of gravitational waves from\n          inspiraling compact binaries\", Physical Review D 85, 2012,\n          :arxiv:`gr-qc/0509116`\n  ",
            "n_words": 71,
            "vocab_size": 58,
            "n_whitespaces": 122,
            "language": "en"
        }
    },
    {
        "id": 223882,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/utils.py",
        "file_name": "utils.py",
        "fun_name": "parseaddr",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parseaddr(addr):\n    \n    addrs = _AddressList(addr).addresslist\n    if not addrs:\n        return '', ''\n    return addrs[0]\n\n\n# rfc822.unquote() doesn't properly de-backslash-ify in Python pre-2.3.",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 39,
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        "token_counts": 27,
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        "n_identifiers": 5,
        "d_id": 57132,
        "documentation": {
            "docstring": "\n    Parse addr into its constituent realname and email address parts.\n\n    Return a tuple of realname and email address, unless the parse fails, in\n    which case return a 2-tuple of ('', '').\n    ",
            "n_words": 31,
            "vocab_size": 26,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
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        "id": 223636,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_policybase.py",
        "file_name": "_policybase.py",
        "fun_name": "handle_defect",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def handle_defect(self, obj, defect):\n        \n        if self.raise_on_defect:\n            raise defect\n        self.register_defect(obj, defect)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_whitespaces": 42,
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        "token_counts": 25,
        "n_ast_nodes": 40,
        "n_identifiers": 6,
        "d_id": 57022,
        "documentation": {
            "docstring": "Based on policy, either raise defect or call register_defect.\n\n            handle_defect(obj, defect)\n\n        defect should be a Defect subclass, but in any case must be an\n        Exception subclass.  obj is the object on which the defect should be\n        registered if it is not raised.  If the raise_on_defect is True, the\n        defect is raised as an error, otherwise the object and the defect are\n        passed to register_defect.\n\n        This method is intended to be called by parsers that discover defects.\n        The email package parsers always call it with Defect instances.\n\n        ",
            "n_words": 86,
            "vocab_size": 60,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 223462,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/doctest.py",
        "file_name": "doctest.py",
        "fun_name": "output_difference",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def output_difference(self, example, got, optionflags):\n        \n        want = example.want\n        # If <BLANKLINE>s are being used, then replace blank lines\n        # with <BLANKLINE> in the actual output string.\n        if not (optionflags & DONT_ACCEPT_BLANKLINE):\n            got = re.sub('(?m)^[ ]*(?=\\n)', BLANKLINE_MARKER, got)\n\n        # Check if we should use diff.\n        if self._do_a_fancy_diff(want, got, optionflags):\n            # Split want & got into lines.\n            want_lines = want.splitlines(keepends=True)\n            got_lines = got.splitlines(keepends=True)\n            # Use difflib to find their differences.\n            if optionflags & REPORT_UDIFF:\n                diff = difflib.unified_diff(want_lines, got_lines, n=2)\n                diff = list(diff)[2:] # strip the diff header\n                kind = 'unified diff with -expected +actual'\n            elif optionflags & REPORT_CDIFF:\n                diff = difflib.context_diff(want_lines, got_lines, n=2)\n                diff = list(diff)[2:] # strip the diff header\n                kind = 'context diff with expected followed by actual'\n            elif optionflags & REPORT_NDIFF:\n                engine = difflib.Differ(charjunk=difflib.IS_CHARACTER_JUNK)\n                diff = list(engine.compare(want_lines, got_lines))\n                kind = 'ndiff with -expected +actual'\n            else:\n                assert 0, 'Bad diff option'\n            return 'Differences (%s):\\n' % kind + _indent(''.join(diff))\n\n        # If we're not using diff, then simply list the expected\n        # output followed by the actual output.\n        if want and got:\n            return 'Expected:\\n%sGot:\\n%s' % (_indent(want), _indent(got))\n        elif want:\n            return 'Expected:\\n%sGot nothing\\n' % _indent(want)\n        elif got:\n            return 'Expected nothing\\nGot:\\n%s' % _indent(got)\n        else:\n            return 'Expected nothing\\nGot nothing\\n'\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 589,
        "n_words": 194,
        "vocab_size": 111,
        "complexity": 10,
        "nloc": 30,
        "token_counts": 229,
        "n_ast_nodes": 396,
        "n_identifiers": 32,
        "d_id": 56917,
        "documentation": {
            "docstring": "\n        Return a string describing the differences between the\n        expected output for a given example (`example`) and the actual\n        output (`got`).  `optionflags` is the set of option flags used\n        to compare `want` and `got`.\n        ",
            "n_words": 33,
            "vocab_size": 27,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 205408,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/base.py",
        "file_name": "base.py",
        "fun_name": "subclass_exception",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def subclass_exception(name, bases, module, attached_to):\n    \n    return type(\n        name,\n        bases,\n        {\n            \"__module__\": module,\n            \"__qualname__\": \"%s.%s\" % (attached_to.__qualname__, name),\n        },\n    )\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 78,
        "n_words": 19,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 39,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 51117,
        "documentation": {
            "docstring": "\n    Create exception subclass. Used by ModelBase below.\n\n    The exception is created in a way that allows it to be pickled, assuming\n    that the returned exception class will be added as an attribute to the\n    'attached_to' class.\n    ",
            "n_words": 36,
            "vocab_size": 30,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 21352,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distlib/_backport/shutil.py",
        "file_name": "shutil.py",
        "fun_name": "_make_zipfile",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def _make_zipfile(base_name, base_dir, verbose=0, dry_run=0, logger=None):\n    \n    zip_filename = base_name + \".zip\"\n    archive_dir = os.path.dirname(base_name)\n\n    if not os.path.exists(archive_dir):\n        if logger is not None:\n            logger.info(\"creating %s\", archive_dir)\n        if not dry_run:\n            os.makedirs(archive_dir)\n\n    # If zipfile module is not available, try spawning an external 'zip'\n    # command.\n    try:\n        import zipfile\n    except ImportError:\n        zipfile = None\n\n    if zipfile is None:\n        _call_external_zip(base_dir, zip_filename, verbose, dry_run)\n    else:\n        if logger is not None:\n            logger.info(\"creating '%s' and adding '%s' to it\",\n                        zip_filename, base_dir)\n\n        if not dry_run:\n            zip = zipfile.ZipFile(zip_filename, \"w\",\n                                  compression=zipfile.ZIP_DEFLATED)\n\n            for dirpath, dirnames, filenames in os.walk(base_dir):\n                for name in filenames:\n                    path = os.path.normpath(os.path.join(dirpath, name))\n                    if os.path.isfile(path):\n                        zip.write(path, path)\n                        if logger is not None:\n                            logger.info(\"adding '%s'\", path)\n            zip.close()\n\n    return zip_filename\n\n_ARCHIVE_FORMATS = {\n    'gztar': (_make_tarball, [('compress', 'gzip')], \"gzip'ed tar-file\"),\n    'bztar': (_make_tarball, [('compress', 'bzip2')], \"bzip2'ed tar-file\"),\n    'tar':   (_make_tarball, [('compress', None)], \"uncompressed tar file\"),\n    'zip':   (_make_zipfile, [], \"ZIP file\"),\n    }\n\nif _BZ2_SUPPORTED:\n    _ARCHIVE_FORMATS['bztar'] = (_make_tarball, [('compress', 'bzip2')],\n                                \"bzip2'ed tar-file\")\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 529,
        "n_words": 148,
        "vocab_size": 97,
        "complexity": 12,
        "nloc": 30,
        "token_counts": 210,
        "n_ast_nodes": 479,
        "n_identifiers": 34,
        "d_id": 3780,
        "documentation": {
            "docstring": "Create a zip file from all the files under 'base_dir'.\n\n    The output zip file will be named 'base_name' + \".zip\".  Uses either the\n    \"zipfile\" Python module (if available) or the InfoZIP \"zip\" utility\n    (if installed and found on the default search path).  If neither tool is\n    available, raises ExecError.  Returns the name of the output zip\n    file.\n    ",
            "n_words": 57,
            "vocab_size": 47,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 321601,
        "commit_id": "c5a51eb0bcbab0b68cdfbf3eba2e681cff2adf7a",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/greasemonkey.py",
        "file_name": "greasemonkey.py",
        "fun_name": "needs_document_end_workaround",
        "commit_message": "Drop Qt < 5.15\n\nFixes #7091\n\nTODO: Add changelog",
        "code": "def needs_document_end_workaround(self):\n        \n        if objects.backend == usertypes.Backend.QtWebKit:\n            return False\n\n        assert objects.backend == usertypes.Backend.QtWebEngine, objects.backend\n\n        broken_scripts = [\n            ('http://userstyles.org', None),\n            ('https://github.com/ParticleCore', 'Iridium'),\n        ]\n        return any(self._matches_id(namespace=namespace, name=name)\n                   for namespace, name in broken_scripts)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 122,
        "n_words": 29,
        "vocab_size": 25,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 71,
        "n_ast_nodes": 112,
        "n_identifiers": 13,
        "d_id": 117818,
        "documentation": {
            "docstring": "Check whether to force @run-at document-end.\n\n        This needs to be done on QtWebEngine for known-broken scripts.\n\n        On Qt 5.12, accessing the DOM isn't possible with \"@run-at\n        document-start\". It was documented to be impossible before, but seems\n        to work fine.\n\n        However, some scripts do DOM access with \"@run-at document-start\". Fix\n        those by forcing them to use document-end instead.\n        ",
            "n_words": 57,
            "vocab_size": 48,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 72114,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_privacy.py",
        "file_name": "test_privacy.py",
        "fun_name": "test_explorer_list_private",
        "commit_message": "Reformat with black",
        "code": "def test_explorer_list_private(self):\n        \n        response = self.client.get(\n            reverse(\"wagtailadmin_explore\", args=(self.private_page.id,))\n        )\n\n        # Check the response\n        self.assertEqual(response.status_code, 200)\n\n        # Must have one privacy icon (next to the private child page)\n        self.assertContains(\n            response,\n            '<span class=\"indicator privacy-indicator icon icon-no-view\"',\n            count=1,\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 135,
        "n_words": 35,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 53,
        "n_ast_nodes": 88,
        "n_identifiers": 13,
        "d_id": 15840,
        "documentation": {
            "docstring": "\n        This tests that there is a padlock displayed\n        next to the private child page in the private pages explorer listing\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 29667,
        "commit_id": "9effd5aec81acbdd2a1076c1d72bbee1afcc65a1",
        "repo": "saleor",
        "path": "saleor/graphql/order/tests/queries/test_order.py",
        "file_name": "test_order.py",
        "fun_name": "test_order_query_customer",
        "commit_message": "restructure order app tests (#11226)",
        "code": "def test_order_query_customer(api_client):\n    query = \n\n    response = api_client.post_graphql(query)\n    assert_no_permission(response)\n\n\n@pytest.mark.parametrize(\n    \"total_authorized, total_charged, expected_status\",\n    [\n        (Decimal(\"98.40\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"0\"), Decimal(\"98.40\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"10\"), Decimal(\"88.40\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"0\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.NONE.name),\n        (Decimal(\"11\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n        (Decimal(\"0\"), Decimal(\"50.00\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n        (Decimal(\"10\"), Decimal(\"40.40\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n    ],\n)",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"total_authorized, total_charged, expected_status\",\n    [\n        (Decimal(\"98.40\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"0\"), Decimal(\"98.40\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"10\"), Decimal(\"88.40\"), OrderAuthorizeStatusEnum.FULL.name),\n        (Decimal(\"0\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.NONE.name),\n        (Decimal(\"11\"), Decimal(\"0\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n        (Decimal(\"0\"), Decimal(\"50.00\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n        (Decimal(\"10\"), Decimal(\"40.40\"), OrderAuthorizeStatusEnum.PARTIAL.name),\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 101,
        "n_words": 36,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 20,
        "n_ast_nodes": 261,
        "n_identifiers": 15,
        "d_id": 5251,
        "documentation": {
            "docstring": "\n        query OrdersQuery {\n            orders(first: 1) {\n                edges {\n                    node {\n                        id\n                    }\n                }\n            }\n        }\n    ",
            "n_words": 15,
            "vocab_size": 9,
            "n_whitespaces": 146,
            "language": "en"
        }
    },
    {
        "id": 215808,
        "commit_id": "a35b29b2651bf33c5d5b45e64bc7765ffde4aff4",
        "repo": "salt",
        "path": "tests/pytests/functional/modules/file/test_replace.py",
        "file_name": "test_replace.py",
        "fun_name": "test_numeric_repl",
        "commit_message": "Add some funtional tests\n\nAdd functional tests for the following:\n- file.readlink\n- file.replace\n- file.symlink\n\nRemove unit tests for file.replace as they are duplicated in the added\nfunctional test",
        "code": "def test_numeric_repl(file, multiline_file):\n    \n    file.replace(multiline_file, r\"Etiam\", 123)\n    assert \"123\" in multiline_file.read_text()\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 46,
        "n_identifiers": 5,
        "d_id": 54182,
        "documentation": {
            "docstring": "\n    This test covers cases where the replacement string is numeric. The CLI\n    parser yaml-fies it into a numeric type. If not converted back to a string\n    type in file.replace, a TypeError occurs when the replace is attempted. See\n    https://github.com/saltstack/salt/issues/9097 for more information.\n    ",
            "n_words": 42,
            "vocab_size": 37,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 269281,
        "commit_id": "2d1086447a25d281f9428832d046c473d80ad761",
        "repo": "keras",
        "path": "keras/applications/convnext.py",
        "file_name": "convnext.py",
        "fun_name": "PreStem",
        "commit_message": "Corrected preprocess_input docstring in regnet.py and convnext.py",
        "code": "def PreStem(name=None):\n    \n    if name is None:\n        name = \"prestem\" + str(backend.get_uid(\"prestem\"))\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 24,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 30,
        "n_ast_nodes": 49,
        "n_identifiers": 5,
        "d_id": 80000,
        "documentation": {
            "docstring": "Normalizes inputs with ImageNet-1k mean and std.\n\n  Args:\n    name (str): Name prefix.\n\n  Returns:\n    A presemt function.\n  ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 173538,
        "commit_id": "f73ff0c91f0159a925fb6547612199bb7c915248",
        "repo": "magenta",
        "path": "magenta/models/onsets_frames_transcription/model.py",
        "file_name": "model.py",
        "fun_name": "model_fn",
        "commit_message": "Explicitly import estimator from tensorflow as a separate import instead of accessing it via tf.estimator and depend on the tensorflow estimator target.\n\nPiperOrigin-RevId: 436568278",
        "code": "def model_fn(features, labels, mode, params, config):\n  \n  del config\n  hparams = params\n\n  length = features.length\n  spec = features.spec\n\n  is_training = mode == tf_estimator.ModeKeys.TRAIN\n\n  if is_training:\n    onset_labels = labels.onsets\n    offset_labels = labels.offsets\n    velocity_labels = labels.velocities\n    frame_labels = labels.labels\n    frame_label_weights = labels.label_weights\n\n  if hparams.stop_activation_gradient and not hparams.activation_loss:\n    raise ValueError(\n        'If stop_activation_gradient is true, activation_loss must be true.')\n\n  losses = {}\n  with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=is_training):\n    with tf.variable_scope('onsets'):\n      onset_outputs = acoustic_model(\n          spec,\n          hparams,\n          lstm_units=hparams.onset_lstm_units,\n          lengths=length)\n      onset_probs = slim.fully_connected(\n          onset_outputs,\n          constants.MIDI_PITCHES,\n          activation_fn=tf.sigmoid,\n          scope='onset_probs')\n\n      # onset_probs_flat is used during inference.\n      onset_probs_flat = flatten_maybe_padded_sequences(onset_probs, length)\n      if is_training:\n        onset_labels_flat = flatten_maybe_padded_sequences(onset_labels, length)\n        onset_losses = tf_utils.log_loss(onset_labels_flat, onset_probs_flat)\n        tf.losses.add_loss(tf.reduce_mean(onset_losses))\n        losses['onset'] = onset_losses\n    with tf.variable_scope('offsets'):\n      offset_outputs = acoustic_model(\n          spec,\n          hparams,\n          lstm_units=hparams.offset_lstm_units,\n          lengths=length)\n      offset_probs = slim.fully_connected(\n          offset_outputs,\n          constants.MIDI_PITCHES,\n          activation_fn=tf.sigmoid,\n          scope='offset_probs')\n\n      # offset_probs_flat is used during inference.\n      offset_probs_flat = flatten_maybe_padded_sequences(offset_probs, length)\n      if is_training:\n        offset_labels_flat = flatten_maybe_padded_sequences(\n            offset_labels, length)\n        offset_losses = tf_utils.log_loss(offset_labels_flat, offset_probs_flat)\n        tf.losses.add_loss(tf.reduce_mean(offset_losses))\n        losses['offset'] = offset_losses\n    with tf.variable_scope('velocity'):\n      velocity_outputs = acoustic_model(\n          spec,\n          hparams,\n          lstm_units=hparams.velocity_lstm_units,\n          lengths=length)\n      velocity_values = slim.fully_connected(\n          velocity_outputs,\n          constants.MIDI_PITCHES,\n          activation_fn=None,\n          scope='onset_velocities')\n\n      velocity_values_flat = flatten_maybe_padded_sequences(\n          velocity_values, length)\n      if is_training:\n        velocity_labels_flat = flatten_maybe_padded_sequences(\n            velocity_labels, length)\n        velocity_loss = tf.reduce_sum(\n            onset_labels_flat *\n            tf.square(velocity_labels_flat - velocity_values_flat),\n            axis=1)\n        tf.losses.add_loss(tf.reduce_mean(velocity_loss))\n        losses['velocity'] = velocity_loss\n\n    with tf.variable_scope('frame'):\n      if not hparams.share_conv_features:\n        # TODO(eriche): this is broken when hparams.frame_lstm_units > 0\n        activation_outputs = acoustic_model(\n            spec,\n            hparams,\n            lstm_units=hparams.frame_lstm_units,\n            lengths=length)\n        activation_probs = slim.fully_connected(\n            activation_outputs,\n            constants.MIDI_PITCHES,\n            activation_fn=tf.sigmoid,\n            scope='activation_probs')\n      else:\n        activation_probs = slim.fully_connected(\n            onset_outputs,\n            constants.MIDI_PITCHES,\n            activation_fn=tf.sigmoid,\n            scope='activation_probs')\n\n      probs = []\n      if hparams.stop_onset_gradient:\n        probs.append(tf.stop_gradient(onset_probs))\n      else:\n        probs.append(onset_probs)\n\n      if hparams.stop_activation_gradient:\n        probs.append(tf.stop_gradient(activation_probs))\n      else:\n        probs.append(activation_probs)\n\n      if hparams.stop_offset_gradient:\n        probs.append(tf.stop_gradient(offset_probs))\n      else:\n        probs.append(offset_probs)\n\n      combined_probs = tf.concat(probs, 2)\n\n      if hparams.combined_lstm_units > 0:\n        outputs = lstm_layer(\n            combined_probs,\n            hparams.combined_lstm_units,\n            lengths=length if hparams.use_lengths else None,\n            stack_size=hparams.combined_rnn_stack_size,\n            use_cudnn=hparams.use_cudnn,\n            bidirectional=hparams.bidirectional)\n      else:\n        outputs = combined_probs\n\n      frame_probs = slim.fully_connected(\n          outputs,\n          constants.MIDI_PITCHES,\n          activation_fn=tf.sigmoid,\n          scope='frame_probs')\n\n    frame_probs_flat = flatten_maybe_padded_sequences(frame_probs, length)\n\n    if is_training:\n      frame_labels_flat = flatten_maybe_padded_sequences(frame_labels, length)\n      frame_label_weights_flat = flatten_maybe_padded_sequences(\n          frame_label_weights, length)\n      if hparams.weight_frame_and_activation_loss:\n        frame_loss_weights = frame_label_weights_flat\n      else:\n        frame_loss_weights = None\n      frame_losses = tf_utils.log_loss(\n          frame_labels_flat, frame_probs_flat, weights=frame_loss_weights)\n      tf.losses.add_loss(tf.reduce_mean(frame_losses))\n      losses['frame'] = frame_losses\n\n      if hparams.activation_loss:\n        if hparams.weight_frame_and_activation_loss:\n          activation_loss_weights = frame_label_weights\n        else:\n          activation_loss_weights = None\n        activation_losses = tf_utils.log_loss(\n            frame_labels_flat,\n            flatten_maybe_padded_sequences(activation_probs, length),\n            weights=activation_loss_weights)\n        tf.losses.add_loss(tf.reduce_mean(activation_losses))\n        losses['activation'] = activation_losses\n\n  frame_predictions = frame_probs_flat > hparams.predict_frame_threshold\n  onset_predictions = onset_probs_flat > hparams.predict_onset_threshold\n  offset_predictions = offset_probs_flat > hparams.predict_offset_threshold\n\n  frame_predictions = tf.expand_dims(frame_predictions, axis=0)\n  onset_predictions = tf.expand_dims(onset_predictions, axis=0)\n  offset_predictions = tf.expand_dims(offset_predictions, axis=0)\n  velocity_values = tf.expand_dims(velocity_values_flat, axis=0)\n\n  metrics_values = metrics.define_metrics(\n      frame_probs=frame_probs,\n      onset_probs=onset_probs,\n      frame_predictions=frame_predictions,\n      onset_predictions=onset_predictions,\n      offset_predictions=offset_predictions,\n      velocity_values=velocity_values,\n      length=features.length,\n      sequence_label=labels.note_sequence,\n      frame_labels=labels.labels,\n      sequence_id=features.sequence_id,\n      hparams=hparams)\n\n  for label, loss_collection in losses.items():\n    loss_label = 'losses/' + label\n    metrics_values[loss_label] = loss_collection\n\n  def predict_sequence():\n    \n",
        "url": "https://github.com/magenta/magenta.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 1488,
        "n_words": 385,
        "vocab_size": 217,
        "complexity": 23,
        "nloc": 228,
        "token_counts": 1401,
        "n_ast_nodes": 1442,
        "n_identifiers": 114,
        "d_id": 40851,
        "documentation": {
            "docstring": "Builds the acoustic model.Convert frame predictions into a sequence (TF).",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 73217,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/tests/test_page_modeladmin.py",
        "file_name": "test_page_modeladmin.py",
        "fun_name": "test_title_present",
        "commit_message": "Reformat with black",
        "code": "def test_title_present(self):\n        \n        response = self.get(4)\n        self.assertContains(response, \"Christmas\", 3)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 29,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 42,
        "n_identifiers": 5,
        "d_id": 15993,
        "documentation": {
            "docstring": "\n        The page title should appear three times. Once in the header, and two times\n        in the field listing (as the actual title and as the draft title)\n        ",
            "n_words": 27,
            "vocab_size": 21,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 176981,
        "commit_id": "db35812af218482b0ddf9ca47e4792e47e4d4666",
        "repo": "networkx",
        "path": "networkx/algorithms/triads.py",
        "file_name": "triads.py",
        "fun_name": "all_triads",
        "commit_message": "Add docstring examples for triads functions (#5522)\n\nAdds docstring examples to the functions in the triads module as well as\r\nsome additional explanatory text + links to other examples.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>",
        "code": "def all_triads(G):\n    \n    triplets = combinations(G.nodes(), 3)\n    for triplet in triplets:\n        yield G.subgraph(triplet).copy()\n\n\n@not_implemented_for(\"undirected\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"undirected\")",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 28,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 69,
        "n_identifiers": 9,
        "d_id": 42209,
        "documentation": {
            "docstring": "A generator of all possible triads in G.\n\n    Parameters\n    ----------\n    G : digraph\n       A NetworkX DiGraph\n\n    Returns\n    -------\n    all_triads : generator of DiGraphs\n       Generator of triads (order-3 DiGraphs)\n\n    Examples\n    --------\n    >>> G = nx.DiGraph([(1, 2), (2, 3), (3, 1), (3, 4), (4, 1), (4, 2)])\n    >>> for triad in nx.all_triads(G):\n    ...     print(triad.edges)\n    [(1, 2), (2, 3), (3, 1)]\n    [(1, 2), (4, 1), (4, 2)]\n    [(3, 1), (3, 4), (4, 1)]\n    [(2, 3), (3, 4), (4, 2)]\n\n    ",
            "n_words": 76,
            "vocab_size": 45,
            "n_whitespaces": 140,
            "language": "en"
        }
    },
    {
        "id": 197041,
        "commit_id": "e0dc14eca132f37c5f49369eb4051eae37c9b119",
        "repo": "sympy",
        "path": "sympy/ntheory/generate.py",
        "file_name": "generate.py",
        "fun_name": "totientrange",
        "commit_message": "Refactored import ordering in functions",
        "code": "def totientrange(self, a, b):\n        \n        a = max(1, _as_int_ceiling(a))\n        b = _as_int_ceiling(b)\n        n = len(self._tlist)\n        if a >= b:\n            return\n        elif b <= n:\n            for i in range(a, b):\n                yield self._tlist[i]\n        else:\n            self._tlist += _arange(n, b)\n            for i in range(1, n):\n                ti = self._tlist[i]\n                startindex = (n + i - 1) // i * i\n                for j in range(startindex, b, i):\n                    self._tlist[j] -= ti\n                if i >= a:\n                    yield ti\n\n            for i in range(n, b):\n                ti = self._tlist[i]\n                for j in range(2 * i, b, i):\n                    self._tlist[j] -= ti\n                if i >= a:\n                    yield ti\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 394,
        "n_words": 94,
        "vocab_size": 50,
        "complexity": 10,
        "nloc": 24,
        "token_counts": 177,
        "n_ast_nodes": 274,
        "n_identifiers": 15,
        "d_id": 48298,
        "documentation": {
            "docstring": "Generate all totient numbers for the range [a, b).\n\n        Examples\n        ========\n\n        >>> from sympy import sieve\n        >>> print([i for i in sieve.totientrange(7, 18)])\n        [6, 4, 6, 4, 10, 4, 12, 6, 8, 8, 16]\n        ",
            "n_words": 34,
            "vocab_size": 28,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 22228,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/dependencies.py",
        "file_name": "dependencies.py",
        "fun_name": "get_deps",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def get_deps(self, candidate):\n        \n\n        key = format_requirement(candidate)\n        if key not in self.dep_dict:\n            from .requirements import Requirement\n\n            req = Requirement.from_line(key)\n            req = req.merge_markers(self.markers)\n            self.dep_dict[key] = req.get_abstract_dependencies()\n        return self.dep_dict[key]\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 98,
        "n_words": 26,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 64,
        "n_ast_nodes": 105,
        "n_identifiers": 13,
        "d_id": 4272,
        "documentation": {
            "docstring": "Get the dependencies of the supplied candidate.\n\n        :param candidate: An installrequirement\n        :type candidate: :class:`~pipenv.patched.pip._internal.req.req_install.InstallRequirement`\n        :return: A list of abstract dependencies\n        :rtype: list[:class:`~requirementslib.models.dependency.AbstractDependency`]\n        ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 207354,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_scripts/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_all",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_all(self):\n        \n        self.write_settings(\"settings_to_diff.py\", sdict={\"STATIC_URL\": \"None\"})\n        args = [\"diffsettings\", \"--settings=settings_to_diff\", \"--all\"]\n        out, err = self.run_manage(args)\n        self.assertNoOutput(err)\n        self.assertOutput(out, \"### STATIC_URL = None\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 62,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 53,
        "n_ast_nodes": 98,
        "n_identifiers": 10,
        "d_id": 51934,
        "documentation": {
            "docstring": "The all option also shows settings with the default value.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 101376,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "scripts/convert.py",
        "file_name": "convert.py",
        "fun_name": "_validate",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _validate(self) -> None:\n        \n        if (self._args.writer == \"ffmpeg\" and\n                not self._images.is_video and\n                self._args.reference_video is None):\n            raise FaceswapError(\"Output as video selected, but using frames as input. You must \"\n                                \"provide a reference video ('-ref', '--reference-video').\")\n\n        if (self._args.on_the_fly and\n                self._args.mask_type not in (\"none\", \"extended\", \"components\")):\n            logger.warning(\"You have selected an incompatible mask type ('%s') for On-The-Fly \"\n                           \"conversion. Switching to 'extended'\", self._args.mask_type)\n            self._args.mask_type = \"extended\"\n\n        if (not self._args.on_the_fly and\n                self._args.mask_type not in (\"none\", \"predicted\") and\n                not self._alignments.mask_is_valid(self._args.mask_type)):\n            msg = (f\"You have selected the Mask Type `{self._args.mask_type}` but at least one \"\n                   \"face does not have this mask stored in the Alignments File.\\nYou should \"\n                   \"generate the required masks with the Mask Tool or set the Mask Type option to \"\n                   \"an existing Mask Type.\\nA summary of existing masks is as follows:\\nTotal \"\n                   f\"faces: {self._alignments.faces_count}, \"\n                   f\"Masks: {self._alignments.mask_summary}\")\n            raise FaceswapError(msg)\n\n        if self._args.mask_type == \"predicted\" and not self._predictor.has_predicted_mask:\n            available_masks = [k for k, v in self._alignments.mask_summary.items()\n                               if k != \"none\" and v == self._alignments.faces_count]\n            if not available_masks:\n                msg = (\"Predicted Mask selected, but the model was not trained with a mask and no \"\n                       \"masks are stored in the Alignments File.\\nYou should generate the \"\n                       \"required masks with the Mask Tool or set the Mask Type to `none`.\")\n                raise FaceswapError(msg)\n            mask_type = available_masks[0]\n            logger.warning(\"Predicted Mask selected, but the model was not trained with a \"\n                           \"mask. Selecting first available mask: '%s'\", mask_type)\n            self._args.mask_type = mask_type\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 727,
        "n_words": 230,
        "vocab_size": 125,
        "complexity": 15,
        "nloc": 49,
        "token_counts": 224,
        "n_ast_nodes": 423,
        "n_identifiers": 23,
        "d_id": 20791,
        "documentation": {
            "docstring": " Validate the Command Line Options.\n\n        Ensure that certain cli selections are valid and won't result in an error. Checks:\n            * If frames have been passed in with video output, ensure user supplies reference\n            video.\n            * If \"on-the-fly\" and a Neural Network mask is selected, warn and switch to 'extended'\n            * If a mask-type is selected, ensure it exists in the alignments file.\n            * If a predicted mask-type is selected, ensure model has been trained with a mask\n            otherwise attempt to select first available masks, otherwise raise error.\n\n        Raises\n        ------\n        FaceswapError\n            If an invalid selection has been found.\n\n        ",
            "n_words": 97,
            "vocab_size": 66,
            "n_whitespaces": 210,
            "language": "en"
        }
    },
    {
        "id": 246592,
        "commit_id": "64c73c6ac88a740ee480a0ad1f9afc8596bccfa4",
        "repo": "synapse",
        "path": "tests/rest/client/test_login.py",
        "file_name": "test_login.py",
        "fun_name": "test_cas_redirect_confirm",
        "commit_message": "Add type hints to `tests/rest/client` (#12066)",
        "code": "def test_cas_redirect_confirm(self) -> None:\n        \n        base_url = \"/_matrix/client/r0/login/cas/ticket?redirectUrl\"\n        redirect_url = \"https://dodgy-site.com/\"\n\n        url_parts = list(urllib.parse.urlparse(base_url))\n        query = dict(urllib.parse.parse_qsl(url_parts[4]))\n        query.update({\"redirectUrl\": redirect_url})\n        query.update({\"ticket\": \"ticket\"})\n        url_parts[4] = urllib.parse.urlencode(query)\n        cas_ticket_url = urllib.parse.urlunparse(url_parts)\n\n        # Get Synapse to call the fake CAS and serve the template.\n        channel = self.make_request(\"GET\", cas_ticket_url)\n\n        # Test that the response is HTML.\n        self.assertEqual(channel.code, 200, channel.result)\n        content_type_header_value = \"\"\n        for header in channel.result.get(\"headers\", []):\n            if header[0] == b\"Content-Type\":\n                content_type_header_value = header[1].decode(\"utf8\")\n\n        self.assertTrue(content_type_header_value.startswith(\"text/html\"))\n\n        # Test that the body isn't empty.\n        self.assertTrue(len(channel.result[\"body\"]) > 0)\n\n        # And that it contains our redirect link\n        self.assertIn(redirect_url, channel.result[\"body\"].decode(\"UTF-8\"))\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 254,
        "n_words": 88,
        "vocab_size": 70,
        "complexity": 3,
        "nloc": 21,
        "token_counts": 193,
        "n_ast_nodes": 333,
        "n_identifiers": 29,
        "d_id": 71284,
        "documentation": {
            "docstring": "Tests that the SSO login flow serves a confirmation page before redirecting a\n        user to the redirect URL.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 248549,
        "commit_id": "2959184a42398277ff916206235b844a8f7be5d7",
        "repo": "synapse",
        "path": "tests/test_event_auth.py",
        "file_name": "test_event_auth.py",
        "fun_name": "test_state_default_level",
        "commit_message": "EventAuthTestCase: build events for the right room version\n\nIn practice, when we run the auth rules, all of the events have the right room\nversion. Let's stop building Room V1 events for these tests and use the right\nversion.",
        "code": "def test_state_default_level(self):\n        \n        creator = \"@creator:example.com\"\n        pleb = \"@joiner:example.com\"\n        king = \"@joiner2:example.com\"\n\n        auth_events = [\n            _create_event(RoomVersions.V1, creator),\n            _join_event(RoomVersions.V1, creator),\n            _power_levels_event(\n                RoomVersions.V1,\n                creator,\n                {\"state_default\": \"30\", \"users\": {pleb: \"29\", king: \"30\"}},\n            ),\n            _join_event(RoomVersions.V1, pleb),\n            _join_event(RoomVersions.V1, king),\n        ]\n\n        # pleb should not be able to send state\n        self.assertRaises(\n            AuthError,\n            event_auth.check_auth_rules_for_event,\n            RoomVersions.V1,\n            _random_state_event(RoomVersions.V1, pleb),\n            auth_events,\n        ),\n\n        # king should be able to send state\n        event_auth.check_auth_rules_for_event(\n            RoomVersions.V1,\n            _random_state_event(RoomVersions.V1, king),\n            auth_events,\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 348,
        "n_words": 65,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 27,
        "token_counts": 130,
        "n_ast_nodes": 202,
        "n_identifiers": 16,
        "d_id": 72341,
        "documentation": {
            "docstring": "\n        Check that users above the state_default level can send state and\n        those below cannot\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 206599,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/dateformat.py",
        "file_name": "dateformat.py",
        "fun_name": "P",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def P(self):\n        \n        if self.data.minute == 0 and self.data.hour == 0:\n            return _(\"midnight\")\n        if self.data.minute == 0 and self.data.hour == 12:\n            return _(\"noon\")\n        return \"%s %s\" % (self.f(), self.a())\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 78,
        "n_words": 28,
        "vocab_size": 18,
        "complexity": 5,
        "nloc": 6,
        "token_counts": 66,
        "n_ast_nodes": 112,
        "n_identifiers": 8,
        "d_id": 51583,
        "documentation": {
            "docstring": "\n        Time, in 12-hour hours, minutes and 'a.m.'/'p.m.', with minutes left off\n        if they're zero and the strings 'midnight' and 'noon' if appropriate.\n        Examples: '1 a.m.', '1:30 p.m.', 'midnight', 'noon', '12:30 p.m.'\n        Proprietary extension.\n        ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 124505,
        "commit_id": "1243ed62bf4121c83881c3ddc095bc6a873a09f3",
        "repo": "ray",
        "path": "rllib/evaluation/rollout_worker.py",
        "file_name": "rollout_worker.py",
        "fun_name": "sample",
        "commit_message": "[RLlib] Make Dataset reader default reader and enable CRR to use dataset (#26304)\n\nCo-authored-by: avnish <avnish@avnishs-MBP.local.meter>",
        "code": "def sample(self) -> SampleBatchType:\n        \n        if self.fake_sampler and self.last_batch is not None:\n            return self.last_batch\n        elif self.input_reader is None:\n            raise ValueError(\n                \"RolloutWorker has no `input_reader` object! \"\n                \"Cannot call `sample()`. You can try setting \"\n                \"`create_env_on_driver` to True.\"\n            )\n\n        if log_once(\"sample_start\"):\n            logger.info(\n                \"Generating sample batch of size {}\".format(\n                    self.rollout_fragment_length\n                )\n            )\n\n        batches = [self.input_reader.next()]\n        steps_so_far = (\n            batches[0].count\n            if self.count_steps_by == \"env_steps\"\n            else batches[0].agent_steps()\n        )\n\n        # In truncate_episodes mode, never pull more than 1 batch per env.\n        # This avoids over-running the target batch size.\n        if self.batch_mode == \"truncate_episodes\":\n            max_batches = self.num_envs\n        else:\n            max_batches = float(\"inf\")\n        while steps_so_far < self.rollout_fragment_length and (\n            len(batches) < max_batches or self.policy_config.get(\"offline_sampling\")\n        ):\n            batch = self.input_reader.next()\n            steps_so_far += (\n                batch.count\n                if self.count_steps_by == \"env_steps\"\n                else batch.agent_steps()\n            )\n            batches.append(batch)\n        batch = batches[0].concat_samples(batches) if len(batches) > 1 else batches[0]\n\n        self.callbacks.on_sample_end(worker=self, samples=batch)\n\n        # Always do writes prior to compression for consistency and to allow\n        # for better compression inside the writer.\n        self.output_writer.write(batch)\n\n        # Do off-policy estimation, if needed.\n        if self.reward_estimators:\n            for estimator in self.reward_estimators:\n                estimator.process(batch)\n\n        if log_once(\"sample_end\"):\n            logger.info(\"Completed sample batch:\\n\\n{}\\n\".format(summarize(batch)))\n\n        if self.compress_observations:\n            batch.compress(bulk=self.compress_observations == \"bulk\")\n\n        if self.fake_sampler:\n            self.last_batch = batch\n        return batch\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 713,
        "n_words": 182,
        "vocab_size": 119,
        "complexity": 17,
        "nloc": 65,
        "token_counts": 284,
        "n_ast_nodes": 483,
        "n_identifiers": 41,
        "d_id": 27618,
        "documentation": {
            "docstring": "Returns a batch of experience sampled from this worker.\n\n        This method must be implemented by subclasses.\n\n        Returns:\n            A columnar batch of experiences (e.g., tensors).\n\n        Examples:\n            >>> import gym\n            >>> from ray.rllib.evaluation.rollout_worker import RolloutWorker\n            >>> from ray.rllib.algorithms.pg.pg_tf_policy import PGStaticGraphTFPolicy\n            >>> worker = RolloutWorker( # doctest: +SKIP\n            ...   env_creator=lambda _: gym.make(\"CartPole-v0\"), # doctest: +SKIP\n            ...   policy_spec=PGStaticGraphTFPolicy) # doctest: +SKIP\n            >>> print(worker.sample()) # doctest: +SKIP\n            SampleBatch({\"obs\": [...], \"action\": [...], ...})\n        ",
            "n_words": 67,
            "vocab_size": 46,
            "n_whitespaces": 198,
            "language": "en"
        }
    },
    {
        "id": 288486,
        "commit_id": "dd1463da287f591652e47b00eee0c5b77f5f5b7c",
        "repo": "core",
        "path": "homeassistant/components/bayesian/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "to_dict",
        "commit_message": "Refactor bayesian observations using dataclass (#79590)\n\n* refactor\r\n\r\n* remove some changes\r\n\r\n* remove typehint\r\n\r\n* improve codestyle\r\n\r\n* move docstring to comment\r\n\r\n* < 88 chars\r\n\r\n* avoid short var names\r\n\r\n* more readable\r\n\r\n* fix rename\r\n\r\n* Update homeassistant/components/bayesian/helpers.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* no intermediate\r\n\r\n* comment why set before list\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "def to_dict(self) -> dict[str, str | float | bool | None]:\n        \n\n        # Needed because dataclasses asdict() can't serialize Templates and ignores Properties.\n        dic = {\n            CONF_PLATFORM: self.platform,\n            CONF_ENTITY_ID: self.entity_id,\n            CONF_VALUE_TEMPLATE: self.template,\n            CONF_TO_STATE: self.to_state,\n            CONF_ABOVE: self.above,\n            CONF_BELOW: self.below,\n            CONF_P_GIVEN_T: self.prob_given_true,\n            CONF_P_GIVEN_F: self.prob_given_false,\n            \"observed\": self.observed,\n        }\n\n        for key, value in dic.copy().items():\n            if value is None:\n                del dic[key]\n\n        return dic\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 224,
        "n_words": 57,
        "vocab_size": 53,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 104,
        "n_ast_nodes": 155,
        "n_identifiers": 28,
        "d_id": 87643,
        "documentation": {
            "docstring": "Represent Class as a Dict for easier serialization.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 143840,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/policy/tests/test_sample_batch.py",
        "file_name": "test_sample_batch.py",
        "fun_name": "test_slicing",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def test_slicing(self):\n        \n        s1 = SampleBatch(\n            {\n                \"a\": np.array([1, 2, 3, 2, 3, 4]),\n                \"b\": {\"c\": np.array([4, 5, 6, 5, 6, 7])},\n            }\n        )\n        check(\n            s1[:3],\n            {\n                \"a\": [1, 2, 3],\n                \"b\": {\"c\": [4, 5, 6]},\n            },\n        )\n        check(\n            s1[0:3],\n            {\n                \"a\": [1, 2, 3],\n                \"b\": {\"c\": [4, 5, 6]},\n            },\n        )\n        check(\n            s1[1:4],\n            {\n                \"a\": [2, 3, 2],\n                \"b\": {\"c\": [5, 6, 5]},\n            },\n        )\n        check(\n            s1[1:],\n            {\n                \"a\": [2, 3, 2, 3, 4],\n                \"b\": {\"c\": [5, 6, 5, 6, 7]},\n            },\n        )\n        check(\n            s1[3:4],\n            {\n                \"a\": [2],\n                \"b\": {\"c\": [5]},\n            },\n        )\n\n        # When we change the slice, the original SampleBatch should also\n        # change (shared underlying data).\n        s1[:3][\"a\"][0] = 100\n        s1[1:2][\"a\"][0] = 200\n        check(s1[\"a\"][0], 100)\n        check(s1[\"a\"][1], 200)\n\n        # Seq-len batches should be auto-sliced along sequences,\n        # no matter what.\n        s2 = SampleBatch(\n            {\n                \"a\": np.array([1, 2, 3, 2, 3, 4]),\n                \"b\": {\"c\": np.array([4, 5, 6, 5, 6, 7])},\n                SampleBatch.SEQ_LENS: [2, 3, 1],\n                \"state_in_0\": [1.0, 3.0, 4.0],\n            }\n        )\n        # We would expect a=[1, 2, 3] now, but due to the sequence\n        # boundary, we stop earlier.\n        check(\n            s2[:3],\n            {\n                \"a\": [1, 2],\n                \"b\": {\"c\": [4, 5]},\n                SampleBatch.SEQ_LENS: [2],\n                \"state_in_0\": [1.0],\n            },\n        )\n        # Split exactly at a seq-len boundary.\n        check(\n            s2[:5],\n            {\n                \"a\": [1, 2, 3, 2, 3],\n                \"b\": {\"c\": [4, 5, 6, 5, 6]},\n                SampleBatch.SEQ_LENS: [2, 3],\n                \"state_in_0\": [1.0, 3.0],\n            },\n        )\n        # Split above seq-len boundary.\n        check(\n            s2[:50],\n            {\n                \"a\": [1, 2, 3, 2, 3, 4],\n                \"b\": {\"c\": [4, 5, 6, 5, 6, 7]},\n                SampleBatch.SEQ_LENS: [2, 3, 1],\n                \"state_in_0\": [1.0, 3.0, 4.0],\n            },\n        )\n        check(\n            s2[:],\n            {\n                \"a\": [1, 2, 3, 2, 3, 4],\n                \"b\": {\"c\": [4, 5, 6, 5, 6, 7]},\n                SampleBatch.SEQ_LENS: [2, 3, 1],\n                \"state_in_0\": [1.0, 3.0, 4.0],\n            },\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 1352,
        "n_words": 286,
        "vocab_size": 101,
        "complexity": 1,
        "nloc": 90,
        "token_counts": 639,
        "n_ast_nodes": 903,
        "n_identifiers": 9,
        "d_id": 33076,
        "documentation": {
            "docstring": "Tests, whether slicing can be done on SampleBatches.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 289373,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/components/history/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_list_statistic_ids",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "async def test_list_statistic_ids(recorder_mock, hass, hass_ws_client, caplog):\n    \n    await async_setup_component(hass, \"history\", {})\n    client = await hass_ws_client()\n\n    # Test the WS API works and issues a warning\n    await client.send_json({\"id\": 1, \"type\": \"history/list_statistic_ids\"})\n    response = await client.receive_json()\n    assert response[\"success\"]\n    assert response[\"result\"] == []\n\n    assert (\n        \"WS API 'history/list_statistic_ids' is deprecated and will be removed in \"\n        \"Home Assistant Core 2022.12. Use 'recorder/list_statistic_ids' instead\"\n    ) in caplog.text\n\n    with patch(\n        \"homeassistant.components.history.recorder_ws.ws_handle_list_statistic_ids\",\n        wraps=ws_handle_list_statistic_ids,\n    ) as ws_mock:\n        await client.send_json({\"id\": 2, \"type\": \"history/list_statistic_ids\"})\n        await client.receive_json()\n        ws_mock.assert_called_once()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 162,
        "n_words": 77,
        "vocab_size": 61,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 112,
        "n_ast_nodes": 206,
        "n_identifiers": 16,
        "d_id": 88515,
        "documentation": {
            "docstring": "Test history/list_statistic_ids forwards to recorder.",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 268182,
        "commit_id": "650befed37eadcaea735673638d5475fa957ca7e",
        "repo": "ansible",
        "path": "lib/ansible/modules/copy.py",
        "file_name": "copy.py",
        "fun_name": "copy_left_only",
        "commit_message": "Add missing space after keywords. (#78480)\n\nAlso remove unnecessary parenthesis.",
        "code": "def copy_left_only(src, dest, module):\n    \n\n    changed = False\n    owner = module.params['owner']\n    group = module.params['group']\n    local_follow = module.params['local_follow']\n    left_only = filecmp.dircmp(src, dest).left_only\n    if len(left_only):\n        changed = True\n    if not module.check_mode:\n        for item in left_only:\n            src_item_path = os.path.join(src, item)\n            dest_item_path = os.path.join(dest, item)\n            b_src_item_path = to_bytes(src_item_path, errors='surrogate_or_strict')\n            b_dest_item_path = to_bytes(dest_item_path, errors='surrogate_or_strict')\n\n            if os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path) and local_follow is True:\n                shutil.copytree(b_src_item_path, b_dest_item_path, symlinks=not local_follow)\n                chown_recursive(b_dest_item_path, module)\n\n            if os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path) and local_follow is False:\n                linkto = os.readlink(b_src_item_path)\n                os.symlink(linkto, b_dest_item_path)\n\n            if os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path) and local_follow is True:\n                shutil.copyfile(b_src_item_path, b_dest_item_path)\n                if owner is not None:\n                    module.set_owner_if_different(b_dest_item_path, owner, False)\n                if group is not None:\n                    module.set_group_if_different(b_dest_item_path, group, False)\n\n            if os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path) and local_follow is False:\n                linkto = os.readlink(b_src_item_path)\n                os.symlink(linkto, b_dest_item_path)\n\n            if not os.path.islink(b_src_item_path) and os.path.isfile(b_src_item_path):\n                shutil.copyfile(b_src_item_path, b_dest_item_path)\n                shutil.copymode(b_src_item_path, b_dest_item_path)\n\n                if owner is not None:\n                    module.set_owner_if_different(b_dest_item_path, owner, False)\n                if group is not None:\n                    module.set_group_if_different(b_dest_item_path, group, False)\n\n            if not os.path.islink(b_src_item_path) and os.path.isdir(b_src_item_path):\n                shutil.copytree(b_src_item_path, b_dest_item_path, symlinks=not local_follow)\n                chown_recursive(b_dest_item_path, module)\n\n            changed = True\n    return changed\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 618,
        "n_words": 155,
        "vocab_size": 63,
        "complexity": 24,
        "nloc": 41,
        "token_counts": 408,
        "n_ast_nodes": 634,
        "n_identifiers": 38,
        "d_id": 79439,
        "documentation": {
            "docstring": "Copy files that exist in `src` directory only to the `dest` directory.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 154404,
        "commit_id": "1c0935c1bc0856d43f69c1e32498636ee24ebc85",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/omnisci_on_native/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "__del__",
        "commit_message": "FEAT-#4913: Enabling pyhdk (#4900)\n\nCo-authored-by: ienkovich <ilya.enkovich@intel.com>\r\nSigned-off-by: izamyati <igor.zamyatin@intel.com>",
        "code": "def __del__(self):\n        \n        if self.frame_id is not None:\n            self._server.dropTable(self.frame_id)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 5,
        "d_id": 35961,
        "documentation": {
            "docstring": "Deallocate OmniSci resources related to the partition.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 196673,
        "commit_id": "9ad8ab9fe58051cf11626ba6654852fcfec60147",
        "repo": "sympy",
        "path": "sympy/stats/crv_types.py",
        "file_name": "crv_types.py",
        "fun_name": "PowerFunction",
        "commit_message": "Documentation cleanup 5",
        "code": "def PowerFunction(name, alpha, a, b):\n    r\n    return rv(name, PowerFunctionDistribution, (alpha, a, b))\n\n#-------------------------------------------------------------------------------\n# QuadraticU distribution ------------------------------------------------------\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 63,
        "token_counts": 28,
        "n_ast_nodes": 40,
        "n_identifiers": 7,
        "d_id": 48091,
        "documentation": {
            "docstring": "\n    Creates a continuous random variable with a Power Function Distribution.\n\n    Explanation\n    ===========\n\n    The density of PowerFunction distribution is given by\n\n    .. math::\n        f(x) := \\frac{{\\alpha}(x - a)^{\\alpha - 1}}{(b - a)^{\\alpha}}\n\n    with :math:`x \\in [a,b]`.\n\n    Parameters\n    ==========\n\n    alpha: Positive number, `0 < alpha`, the shape paramater\n    a : Real number, :math:`-\\infty < a`, the left boundary\n    b : Real number, :math:`a < b < \\infty`, the right boundary\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    Examples\n    ========\n\n    >>> from sympy.stats import PowerFunction, density, cdf, E, variance\n    >>> from sympy import Symbol\n    >>> alpha = Symbol(\"alpha\", positive=True)\n    >>> a = Symbol(\"a\", real=True)\n    >>> b = Symbol(\"b\", real=True)\n    >>> z = Symbol(\"z\")\n\n    >>> X = PowerFunction(\"X\", 2, a, b)\n\n    >>> density(X)(z)\n    (-2*a + 2*z)/(-a + b)**2\n\n    >>> cdf(X)(z)\n    Piecewise((a**2/(a**2 - 2*a*b + b**2) - 2*a*z/(a**2 - 2*a*b + b**2) +\n    z**2/(a**2 - 2*a*b + b**2), a <= z), (0, True))\n\n    >>> alpha = 2\n    >>> a = 0\n    >>> b = 1\n    >>> Y = PowerFunction(\"Y\", alpha, a, b)\n\n    >>> E(Y)\n    2/3\n\n    >>> variance(Y)\n    1/18\n\n    References\n    ==========\n\n    .. [1] http://www.mathwave.com/help/easyfit/html/analyses/distributions/power_func.html\n\n    ",
            "n_words": 174,
            "vocab_size": 111,
            "n_whitespaces": 302,
            "language": "en"
        }
    },
    {
        "id": 66234,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/hr/report/employee_analytics/employee_analytics.py",
        "file_name": "employee_analytics.py",
        "fun_name": "get_employees",
        "commit_message": "style: format code with black",
        "code": "def get_employees(filters):\n\tconditions = get_conditions(filters)\n\treturn frappe.db.sql(\n\t\t\n\t\t% conditions,\n\t\tas_list=1,\n\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 5,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 27,
        "n_ast_nodes": 44,
        "n_identifiers": 8,
        "d_id": 14144,
        "documentation": {
            "docstring": "select name, employee_name, date_of_birth,\n\tbranch, department, designation,\n\tgender, company from `tabEmployee` where status = 'Active' %s",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 113425,
        "commit_id": "4cf680090f8a07fdffaebca2e0c2a4f41a9e4315",
        "repo": "nni",
        "path": "nni/compression/pytorch/utils/shape_dependency.py",
        "file_name": "shape_dependency.py",
        "fun_name": "build_dependency",
        "commit_message": "Add Group Norm support for Pruning model (#5069)",
        "code": "def build_dependency(self):\n        \n        self.groups = {}\n        for node in self.graph.nodes_py.nodes_op:\n            if node.op_type in ['Conv2d', 'ConvTranspose2d', \"GroupNorm\"]:\n                if node.op_type in ['Conv2d', 'ConvTranspose2d']:\n                    group = self._get_conv_groups(node)\n                elif node.op_type == \"GroupNorm\":\n                    group = self._get_group_norm_condition(node)\n                if node.name in self.groups:\n                    # the conv layer whose group is larger than 1 will require that\n                    # it's number of output channel to be divisible by the number of group.\n                    self.groups[node.name].append(group)\n                else:\n                    self.groups[node.name] = [group]\n                if group > 1:\n                    # for the conv layer whose group is larger than 1, it will require the number\n                    # of output channels of their parent conv layer to be divisible by group.\n                    parent_convs = self._get_parent_convs(node)\n                    for parent in parent_convs:\n                        if parent in self.groups:\n                            self.groups[parent].append(group)\n                        else:\n                            self.groups[parent] = [group]\n\n        for name in self.groups:\n            self.dependency[name] = lcm_list(self.groups[name])\n            if min(self.groups[name]) == gcd_list(self.groups[name]):\n                self.min_groups[name] = min(self.groups[name])\n            else:\n                self.min_groups[name] = 1\n\n        return self.dependency\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 610,
        "n_words": 136,
        "vocab_size": 69,
        "complexity": 11,
        "nloc": 26,
        "token_counts": 228,
        "n_ast_nodes": 369,
        "n_identifiers": 21,
        "d_id": 24906,
        "documentation": {
            "docstring": "\n        Build the channel dependency for the conv layers\n        in the model. This function return the group number\n        of each conv layers. Note that, here, the group count\n        of conv layers may be larger than their originl groups.\n        This is because that the input channel will also be grouped\n        for the group conv layers. To make this clear, assume we\n        have two group conv layers: conv1(group=2), conv2(group=4).\n        conv2 takes the output features of conv1 as input.\n        Then we have to the filters of conv1 can still be\n        divided into 4 groups after filter pruning, because\n        the input channels of conv2 should be divided into\n        4 groups.\n\n        Returns\n        -------\n        self.dependency : dict\n            key: the name of conv layers, value: the minimum value that the number of\n            filters should be divisible to.\n        ",
            "n_words": 129,
            "vocab_size": 80,
            "n_whitespaces": 264,
            "language": "en"
        }
    },
    {
        "id": 154218,
        "commit_id": "3f985ed6864cc1b5b587094d75ca5b2695e4139f",
        "repo": "modin",
        "path": "modin/utils.py",
        "file_name": "utils.py",
        "fun_name": "try_cast_to_pandas",
        "commit_message": "REFACTOR-#4796: Introduce constant for __reduced__ column name (#4799)\n\nCo-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com>\r\nCo-authored-by: Alexey Prutskov <lehaprutskov@gmail.com>\r\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Jonathan Shi <jhshi@ponder.io>",
        "code": "def try_cast_to_pandas(obj, squeeze=False):\n    \n    if hasattr(obj, \"_to_pandas\"):\n        result = obj._to_pandas()\n        if squeeze:\n            result = result.squeeze(axis=1)\n        return result\n    if hasattr(obj, \"to_pandas\"):\n        result = obj.to_pandas()\n        if squeeze:\n            result = result.squeeze(axis=1)\n        # Query compiler case, it doesn't have logic about convertion to Series\n        if (\n            isinstance(getattr(result, \"name\", None), str)\n            and result.name == MODIN_UNNAMED_SERIES_LABEL\n        ):\n            result.name = None\n        return result\n    if isinstance(obj, (list, tuple)):\n        return type(obj)([try_cast_to_pandas(o, squeeze=squeeze) for o in obj])\n    if isinstance(obj, dict):\n        return {k: try_cast_to_pandas(v, squeeze=squeeze) for k, v in obj.items()}\n    if callable(obj):\n        module_hierarchy = getattr(obj, \"__module__\", \"\").split(\".\")\n        fn_name = getattr(obj, \"__name__\", None)\n        if fn_name and module_hierarchy[0] == \"modin\":\n            return (\n                getattr(pandas.DataFrame, fn_name, obj)\n                if module_hierarchy[-1] == \"dataframe\"\n                else getattr(pandas.Series, fn_name, obj)\n            )\n    return obj\n\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 353,
        "n_words": 112,
        "vocab_size": 71,
        "complexity": 15,
        "nloc": 30,
        "token_counts": 237,
        "n_ast_nodes": 376,
        "n_identifiers": 28,
        "d_id": 35865,
        "documentation": {
            "docstring": "\n    Convert `obj` and all nested objects from Modin to pandas if it is possible.\n\n    If no convertion possible return `obj`.\n\n    Parameters\n    ----------\n    obj : object\n        Object to convert from Modin to pandas.\n    squeeze : bool, default: False\n        Squeeze the converted object(s) before returning them.\n\n    Returns\n    -------\n    object\n        Converted object.\n    ",
            "n_words": 49,
            "vocab_size": 43,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 246021,
        "commit_id": "0fb3dd0830e476c0e0b89c3bf6c7855a4129ff11",
        "repo": "synapse",
        "path": "tests/handlers/test_federation.py",
        "file_name": "test_federation.py",
        "fun_name": "test_backfill_floating_outlier_membership_auth",
        "commit_message": "Refactor the way we set `outlier` (#11634)\n\n* `_auth_and_persist_outliers`: mark persisted events as outliers\r\n\r\nMark any events that get persisted via `_auth_and_persist_outliers` as, well,\r\noutliers.\r\n\r\nCurrently this will be a no-op as everything will already be flagged as an\r\noutlier, but I'm going to change that.\r\n\r\n* `process_remote_join`: stop flagging as outlier\r\n\r\nThe events are now flagged as outliers later on, by `_auth_and_persist_outliers`.\r\n\r\n* `send_join`: remove `outlier=True`\r\n\r\nThe events created here are returned in the result of `send_join` to\r\n`FederationHandler.do_invite_join`. From there they are passed into\r\n`FederationEventHandler.process_remote_join`, which passes them to\r\n`_auth_and_persist_outliers`... which sets the `outlier` flag.\r\n\r\n* `get_event_auth`: remove `outlier=True`\r\n\r\nstop flagging the events returned by `get_event_auth` as outliers. This method\r\nis only called by `_get_remote_auth_chain_for_event`, which passes the results\r\ninto `_auth_and_persist_outliers`, which will flag them as outliers.\r\n\r\n* `_get_remote_auth_chain_for_event`: remove `outlier=True`\r\n\r\nwe pass all the events into `_auth_and_persist_outliers`, which will now flag\r\nthe events as outliers.\r\n\r\n* `_check_sigs_and_hash_and_fetch`: remove unused `outlier` parameter\r\n\r\nThis param is now never set to True, so we can remove it.\r\n\r\n* `_check_sigs_and_hash_and_fetch_one`: remove unused `outlier` param\r\n\r\nThis is no longer set anywhere, so we can remove it.\r\n\r\n* `get_pdu`: remove unused `outlier` parameter\r\n\r\n... and chase it down into `get_pdu_from_destination_raw`.\r\n\r\n* `event_from_pdu_json`: remove redundant `outlier` param\r\n\r\nThis is never set to `True`, so can be removed.\r\n\r\n* changelog\r\n\r\n* update docstring",
        "code": "def test_backfill_floating_outlier_membership_auth(self):\n        \n        OTHER_SERVER = \"otherserver\"\n        OTHER_USER = \"@otheruser:\" + OTHER_SERVER\n\n        # create the room\n        user_id = self.register_user(\"kermit\", \"test\")\n        tok = self.login(\"kermit\", \"test\")\n        room_id = self.helper.create_room_as(\n            room_creator=user_id,\n            is_public=True,\n            tok=tok,\n            extra_content={\n                \"preset\": \"public_chat\",\n            },\n        )\n        room_version = self.get_success(self.store.get_room_version(room_id))\n\n        prev_event_ids = self.get_success(self.store.get_prev_events_for_room(room_id))\n        (\n            most_recent_prev_event_id,\n            most_recent_prev_event_depth,\n        ) = self.get_success(self.store.get_max_depth_of(prev_event_ids))\n        # mapping from (type, state_key) -> state_event_id\n        prev_state_map = self.get_success(\n            self.state_store.get_state_ids_for_event(most_recent_prev_event_id)\n        )\n        # List of state event ID's\n        prev_state_ids = list(prev_state_map.values())\n        auth_event_ids = prev_state_ids\n        auth_events = list(\n            self.get_success(self.store.get_events(auth_event_ids)).values()\n        )\n\n        # build a floating outlier member state event\n        fake_prev_event_id = \"$\" + random_string(43)\n        member_event_dict = {\n            \"type\": EventTypes.Member,\n            \"content\": {\n                \"membership\": \"join\",\n            },\n            \"state_key\": OTHER_USER,\n            \"room_id\": room_id,\n            \"sender\": OTHER_USER,\n            \"depth\": most_recent_prev_event_depth,\n            \"prev_events\": [fake_prev_event_id],\n            \"origin_server_ts\": self.clock.time_msec(),\n            \"signatures\": {OTHER_SERVER: {\"ed25519:key_version\": \"SomeSignatureHere\"}},\n        }\n        builder = self.hs.get_event_builder_factory().for_room_version(\n            room_version, member_event_dict\n        )\n        member_event = self.get_success(\n            builder.build(\n                prev_event_ids=member_event_dict[\"prev_events\"],\n                auth_event_ids=self._event_auth_handler.compute_auth_events(\n                    builder,\n                    prev_state_map,\n                    for_verification=False,\n                ),\n                depth=member_event_dict[\"depth\"],\n            )\n        )\n        # Override the signature added from \"test\" homeserver that we created the event with\n        member_event.signatures = member_event_dict[\"signatures\"]\n\n        # Add the new member_event to the StateMap\n        prev_state_map[\n            (member_event.type, member_event.state_key)\n        ] = member_event.event_id\n        auth_events.append(member_event)\n\n        # build and send an event authed based on the member event\n        message_event_dict = {\n            \"type\": EventTypes.Message,\n            \"content\": {},\n            \"room_id\": room_id,\n            \"sender\": OTHER_USER,\n            \"depth\": most_recent_prev_event_depth,\n            \"prev_events\": prev_event_ids.copy(),\n            \"origin_server_ts\": self.clock.time_msec(),\n            \"signatures\": {OTHER_SERVER: {\"ed25519:key_version\": \"SomeSignatureHere\"}},\n        }\n        builder = self.hs.get_event_builder_factory().for_room_version(\n            room_version, message_event_dict\n        )\n        message_event = self.get_success(\n            builder.build(\n                prev_event_ids=message_event_dict[\"prev_events\"],\n                auth_event_ids=self._event_auth_handler.compute_auth_events(\n                    builder,\n                    prev_state_map,\n                    for_verification=False,\n                ),\n                depth=message_event_dict[\"depth\"],\n            )\n        )\n        # Override the signature added from \"test\" homeserver that we created the event with\n        message_event.signatures = message_event_dict[\"signatures\"]\n\n        # Stub the /event_auth response from the OTHER_SERVER",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 1189,
        "n_words": 243,
        "vocab_size": 136,
        "complexity": 1,
        "nloc": 98,
        "token_counts": 523,
        "n_ast_nodes": 755,
        "n_identifiers": 58,
        "d_id": 70950,
        "documentation": {
            "docstring": "\n        As the local homeserver, check that we can properly process a federated\n        event from the OTHER_SERVER with auth_events that include a floating\n        membership event from the OTHER_SERVER.\n\n        Regression test, see #10439.\n        ",
            "n_words": 31,
            "vocab_size": 25,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 61197,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/hashes.py",
        "file_name": "hashes.py",
        "fun_name": "check_against_chunks",
        "commit_message": "upd; format",
        "code": "def check_against_chunks(self, chunks):\n        # type: (Iterator[bytes]) -> None\n        \n        gots = {}\n        for hash_name in self._allowed.keys():\n            try:\n                gots[hash_name] = hashlib.new(hash_name)\n            except (ValueError, TypeError):\n                raise InstallationError(f\"Unknown hash name: {hash_name}\")\n\n        for chunk in chunks:\n            for hash in gots.values():\n                hash.update(chunk)\n\n        for hash_name, got in gots.items():\n            if got.hexdigest() in self._allowed[hash_name]:\n                return\n        self._raise(gots)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 200,
        "n_words": 47,
        "vocab_size": 38,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 101,
        "n_ast_nodes": 167,
        "n_identifiers": 20,
        "d_id": 12436,
        "documentation": {
            "docstring": "Check good hashes against ones built from iterable of chunks of\n        data.\n\n        Raise HashMismatch if none match.\n\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 241623,
        "commit_id": "dbf1acd5a553ffc1546734be164cc89cef2b741d",
        "repo": "lightning",
        "path": "pytorch_lightning/plugins/environments/lsf_environment.py",
        "file_name": "lsf_environment.py",
        "fun_name": "world_size",
        "commit_message": "Modify LSFEnvironment to use more reliable environment variable (#10825)\n\n\r\nCo-authored-by: thomas chaton <thomas@grid.ai>\r\nCo-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>\r\nCo-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>\r\nCo-authored-by: Jirka Borovec <Borda@users.noreply.github.com>",
        "code": "def world_size(self) -> int:\n        \n        world_size = os.environ.get(\"JSM_NAMESPACE_SIZE\")\n        if world_size is None:\n            raise ValueError(\n                \"Cannot determine world size. Environment variable `JSM_NAMESPACE_SIZE` not found.\"\n                \"Make sure you run your executable with `jsrun`.\"\n            )\n        return int(world_size)\n",
        "url": "https://github.com/Lightning-AI/lightning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 113,
        "n_words": 33,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 34,
        "n_ast_nodes": 64,
        "n_identifiers": 7,
        "d_id": 69627,
        "documentation": {
            "docstring": "The world size is read from the environment variable ``JSM_NAMESPACE_SIZE``.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 105576,
        "commit_id": "139d210b05f0ca9e9bbe29fdd628a3339d1fa813",
        "repo": "datasets",
        "path": "src/datasets/info.py",
        "file_name": "info.py",
        "fun_name": "write_to_directory",
        "commit_message": "Download and prepare as Parquet for cloud storage (#4724)\n\n* use fsspec for caching\r\n\r\n* add parquet writer\r\n\r\n* add file_format argument\r\n\r\n* style\r\n\r\n* use \"gs\" instead of \"gcs\" for apache beam + use is_remote_filesystem\r\n\r\n* typo\r\n\r\n* fix test\r\n\r\n* test ArrowWriter with filesystem\r\n\r\n* test parquet writer\r\n\r\n* more tests\r\n\r\n* more tests\r\n\r\n* fix nullcontext on 3.6\r\n\r\n* parquet_writer.write_batch is not available in pyarrow 6\r\n\r\n* remove reference to open file\r\n\r\n* fix test\r\n\r\n* docs\r\n\r\n* docs: dask from parquet files\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Mario Šaško <mariosasko777@gmail.com>\r\n\r\n* use contextlib.nullcontext\r\n\r\n* fix missing import\r\n\r\n* Use unstrip_protocol to merge protocol and path\r\n\r\n* remove bad \"raise\" and add TODOs\r\n\r\n* add output_dir arg to download_and_prepare\r\n\r\n* update tests\r\n\r\n* update docs\r\n\r\n* fix tests\r\n\r\n* fix tests\r\n\r\n* fix output parent dir creattion\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Albert Villanova del Moral <8515462+albertvillanova@users.noreply.github.com>\r\n\r\n* revert changes for remote cache_dir\r\n\r\n* fix wording in the docs: load -> download and prepare\r\n\r\n* style\r\n\r\n* fix\r\n\r\n* simplify incomplete_dir\r\n\r\n* fix tests\r\n\r\n* albert's comments\r\n\r\nCo-authored-by: Mario Šaško <mariosasko777@gmail.com>\r\nCo-authored-by: Albert Villanova del Moral <8515462+albertvillanova@users.noreply.github.com>",
        "code": "def write_to_directory(self, dataset_info_dir, pretty_print=False, fs=None):\n        \n        fs = fs or LocalFileSystem()\n        is_local = not is_remote_filesystem(fs)\n        path_join = os.path.join if is_local else posixpath.join\n\n        with fs.open(path_join(dataset_info_dir, config.DATASET_INFO_FILENAME), \"wb\") as f:\n            self._dump_info(f, pretty_print=pretty_print)\n        if self.license:\n            with fs.open(path_join(dataset_info_dir, config.LICENSE_FILENAME), \"wb\") as f:\n                self._dump_license(f)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 117,
        "n_words": 38,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 102,
        "n_ast_nodes": 167,
        "n_identifiers": 21,
        "d_id": 22165,
        "documentation": {
            "docstring": "Write `DatasetInfo` and license (if present) as JSON files to `dataset_info_dir`.\n\n        Args:\n            dataset_info_dir (str): Destination directory.\n            pretty_print (bool, default ``False``): If True, the JSON will be pretty-printed with the indent level of 4.\n            fs (``fsspec.spec.AbstractFileSystem``, optional, defaults ``None``):\n                Instance of the remote filesystem used to download the files from.\n\n                <Added version=\"2.5.0\"/>\n\n        Example:\n\n        ```py\n        >>> from datasets import load_dataset\n        >>> ds = load_dataset(\"rotten_tomatoes\", split=\"validation\")\n        >>> ds.info.write_to_directory(\"/path/to/directory/\")\n        ```\n        ",
            "n_words": 66,
            "vocab_size": 57,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 107064,
        "commit_id": "e4dadb672ac01525f7f41ddabd844cb99e871502",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_widgets.py",
        "file_name": "test_widgets.py",
        "fun_name": "test_span_selector_animated_artists_callback",
        "commit_message": "Fix getting tuple of animated artists; add comments and test",
        "code": "def test_span_selector_animated_artists_callback():\n    \n    x = np.linspace(0, 2 * np.pi, 100)\n    values = np.sin(x)\n\n    fig, ax = plt.subplots()\n    (ln,) = ax.plot(x, values, animated=True)\n    (ln2, ) = ax.plot([], animated=True)\n\n    plt.pause(0.1)\n    ax.draw_artist(ln)\n    fig.canvas.blit(fig.bbox)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 56,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 36,
        "token_counts": 352,
        "n_ast_nodes": 147,
        "n_identifiers": 20,
        "d_id": 22578,
        "documentation": {
            "docstring": "Check that the animated artists changed in callbacks are updated.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 314235,
        "commit_id": "90e1fb6ce2faadb9a35fdbe1774fce7b4456364f",
        "repo": "core",
        "path": "homeassistant/components/weather/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_visibility_unit",
        "commit_message": "Weather unit conversion (#73441)\n\nCo-authored-by: Erik <erik@montnemery.com>",
        "code": "def _visibility_unit(self) -> str:\n        \n        if (\n            weather_option_visibility_unit := self._weather_option_visibility_unit\n        ) is not None:\n            return weather_option_visibility_unit\n\n        return self._default_visibility_unit\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 67,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 26,
        "n_ast_nodes": 43,
        "n_identifiers": 6,
        "d_id": 112843,
        "documentation": {
            "docstring": "Return the converted unit of measurement for visibility.\n\n        Should not be set by integrations.\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 246185,
        "commit_id": "901b264c0c88f39cbfb8b2229e0dc57968882658",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_consent",
        "commit_message": "Add type hints to `tests/rest/admin` (#11851)",
        "code": "def test_consent(self) -> None:\n        \n        # Have the admin user accept the terms.\n        self.get_success(self.store.user_set_consent_version(self.admin_user, \"1.0\"))\n\n        # First, cheekily accept the terms and create a room\n        self.get_success(self.store.user_set_consent_version(self.other_user, \"1.0\"))\n        room_id = self.helper.create_room_as(self.other_user, tok=self.other_user_tok)\n        self.helper.send_event(room_id, \"com.example.test\", tok=self.other_user_tok)\n\n        # Now unaccept it and check that we can't send an event\n        self.get_success(self.store.user_set_consent_version(self.other_user, \"0.0\"))\n        self.helper.send_event(\n            room_id,\n            \"com.example.test\",\n            tok=self.other_user_tok,\n            expect_code=HTTPStatus.FORBIDDEN,\n        )\n\n        # Login in as the user\n        puppet_token = self._get_token()\n\n        # Sending an event on their behalf should work fine\n        self.helper.send_event(room_id, \"com.example.test\", tok=puppet_token)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 224,
        "n_words": 75,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 137,
        "n_ast_nodes": 225,
        "n_identifiers": 18,
        "d_id": 71079,
        "documentation": {
            "docstring": "Test that sending a message is not subject to the privacy policies.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 177995,
        "commit_id": "71a9ada93224ed6433fb5b45bfcd60d5fe3edd4c",
        "repo": "label-studio",
        "path": "label_studio/tasks/api.py",
        "file_name": "api.py",
        "fun_name": "perform_create",
        "commit_message": "feat: DEV-2896: Comment List API (#2704)\n\n* feat: DEV-2896: Comment List API\r\n\r\n* Fix\r\n\r\n* Fix tests\r\n\r\n* Fix more tests\r\n\r\n* Fixes\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* Fix feature flags\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* Add fixes\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* Add user id to base.html\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/dm2\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\n* [submodules] Build static heartexlabs/label-studio-frontend\r\n\r\nCo-authored-by: Brandon Martel <brandonmartel@gmail.com>",
        "code": "def perform_create(self, serializer):\n        project_id = self.request.data.get('project')\n        project = generics.get_object_or_404(Project, pk=project_id)\n        instance = serializer.save(project=project)\n        emit_webhooks_for_instance(self.request.user.active_organization, project, WebhookAction.TASKS_CREATED, [instance])\n\n\n@method_decorator(name='get', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Get task',\n        operation_description=,\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ]))\n@method_decorator(name='patch', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Update task',\n        operation_description='Update the attributes of an existing labeling task.',\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ],\n        request_body=TaskSimpleSerializer))\n@method_decorator(name='delete', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Delete task',\n        operation_description='Delete a task in Label Studio. This action cannot be undone!',\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ],\n        ))",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "@method_decorator(name='get', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Get task',\n        operation_description=\"\"\"\n        Get task data, metadata, annotations and other attributes for a specific labeling task by task ID.\n        \"\"\",\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ]))\n@method_decorator(name='patch', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Update task',\n        operation_description='Update the attributes of an existing labeling task.',\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ],\n        request_body=TaskSimpleSerializer))\n@method_decorator(name='delete', decorator=swagger_auto_schema(\n        tags=['Tasks'],\n        operation_summary='Delete task',\n        operation_description='Delete a task in Label Studio. This action cannot be undone!',\n        manual_parameters=[\n            openapi.Parameter(\n                name='id',\n                type=openapi.TYPE_STRING,\n                in_=openapi.IN_PATH,\n                description='Task ID'\n            ),\n        ],\n        ))",
        "n_ast_errors": 1,
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        "documentation": {
            "docstring": "\n        Get task data, metadata, annotations and other attributes for a specific labeling task by task ID.\n        ",
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            "language": "en"
        }
    },
    {
        "id": 205912,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/utils.py",
        "file_name": "utils.py",
        "fun_name": "prepare_test_settings",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def prepare_test_settings(self, alias):\n        \n        try:\n            conn = self.databases[alias]\n        except KeyError:\n            raise self.exception_class(f\"The connection '{alias}' doesn't exist.\")\n\n        test_settings = conn.setdefault(\"TEST\", {})\n        default_test_settings = [\n            (\"CHARSET\", None),\n            (\"COLLATION\", None),\n            (\"MIGRATE\", True),\n            (\"MIRROR\", None),\n            (\"NAME\", None),\n        ]\n        for key, value in default_test_settings:\n            test_settings.setdefault(key, value)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "vocab_size": 35,
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        "token_counts": 89,
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        "n_identifiers": 12,
        "d_id": 51278,
        "documentation": {
            "docstring": "\n        Make sure the test settings are available in the 'TEST' sub-dictionary.\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 66700,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v12_0/update_owner_fields_in_acc_dimension_custom_fields.py",
        "file_name": "update_owner_fields_in_acc_dimension_custom_fields.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\taccounting_dimensions = frappe.db.sql(\n\t\t,\n\t\tas_dict=1,\n\t)\n\n\tdoclist = get_doctypes_with_dimensions()\n\n\tfor dimension in accounting_dimensions:\n\t\tfrappe.db.sql(\n\t\t\t\n\t\t\t% (\"%s\", \", \".join([\"%s\"] * len(doclist))),  # nosec\n\t\t\ttuple([dimension.fieldname] + doclist),\n\t\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 18,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 67,
        "n_ast_nodes": 114,
        "n_identifiers": 13,
        "d_id": 14300,
        "documentation": {
            "docstring": "select fieldname from\n\t\t`tabAccounting Dimension`\n\t\t\tUPDATE `tabCustom Field`\n\t\t\tSET owner = 'Administrator'\n\t\t\tWHERE fieldname = %s\n\t\t\tAND dt IN (%s)",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 297147,
        "commit_id": "923fa473e171fcdf396556ea200612e378f9b0a5",
        "repo": "core",
        "path": "tests/components/blebox/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "async_setup_entity",
        "commit_message": "Blebox add thermoBox to climate (#81090)\n\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "async def async_setup_entity(hass, entity_id):\n    \n\n    return (await async_setup_entities(hass, [entity_id]))[0]\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 14,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 23,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 96116,
        "documentation": {
            "docstring": "Return a configured entry with the given entity_id.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 36021,
        "commit_id": "50dd314d939a86f3a81e19af01459f449fbaeeca",
        "repo": "transformers",
        "path": "src/transformers/onnx/config.py",
        "file_name": "config.py",
        "fun_name": "outputs",
        "commit_message": "Add ONNX export for ViT (#15658)\n\n* Add ONNX support for ViT\r\n\r\n* Refactor to use generic preprocessor\r\n\r\n* Add vision dep to tests\r\n\r\n* Extend ONNX slow tests to ViT\r\n\r\n* Add dummy image generator\r\n\r\n* Use model_type to determine modality\r\n\r\n* Add deprecation warnings for tokenizer argument\r\n\r\n* Add warning when overwriting the preprocessor\r\n\r\n* Add optional args to docstrings\r\n\r\n* Add minimum PyTorch version to OnnxConfig\r\n\r\n* Refactor OnnxConfig class variables from CONSTANT_NAME to snake_case\r\n\r\n* Add reasonable value for default atol\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def outputs(self) -> Mapping[str, Mapping[int, str]]:\n        \n        common_outputs = self._tasks_to_common_outputs[self.task]\n        return copy.deepcopy(common_outputs)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 35,
        "n_ast_nodes": 54,
        "n_identifiers": 10,
        "d_id": 6563,
        "documentation": {
            "docstring": "\n        Mapping containing the axis definition of the output tensors to provide to the model\n\n        Returns:\n            For each output: its name associated to the axes symbolic name and the axis position within the tensor\n        ",
            "n_words": 33,
            "vocab_size": 24,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 249088,
        "commit_id": "c97042f7eef3748e17c90e48a4122389a89c4735",
        "repo": "synapse",
        "path": "tests/rest/admin/test_event_reports.py",
        "file_name": "test_event_reports.py",
        "fun_name": "test_valid_search_order",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13469)",
        "code": "def test_valid_search_order(self) -> None:\n        \n\n        # fetch the most recent first, largest timestamp\n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?dir=b\",\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n        self.assertEqual(channel.json_body[\"total\"], 20)\n        self.assertEqual(len(channel.json_body[\"event_reports\"]), 20)\n        report = 1\n        while report < len(channel.json_body[\"event_reports\"]):\n            self.assertGreaterEqual(\n                channel.json_body[\"event_reports\"][report - 1][\"received_ts\"],\n                channel.json_body[\"event_reports\"][report][\"received_ts\"],\n            )\n            report += 1\n\n        # fetch the oldest first, smallest timestamp\n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?dir=f\",\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n        self.assertEqual(channel.json_body[\"total\"], 20)\n        self.assertEqual(len(channel.json_body[\"event_reports\"]), 20)\n        report = 1\n        while report < len(channel.json_body[\"event_reports\"]):\n            self.assertLessEqual(\n                channel.json_body[\"event_reports\"][report - 1][\"received_ts\"],\n                channel.json_body[\"event_reports\"][report][\"received_ts\"],\n            )\n            report += 1\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 394,
        "n_words": 83,
        "vocab_size": 42,
        "complexity": 3,
        "nloc": 34,
        "token_counts": 244,
        "n_ast_nodes": 398,
        "n_identifiers": 15,
        "d_id": 72595,
        "documentation": {
            "docstring": "\n        Testing search order. Order by timestamps.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 223450,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/doctest.py",
        "file_name": "doctest.py",
        "fun_name": "report_failure",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def report_failure(self, out, test, example, got):\n        \n        out(self._failure_header(test, example) +\n            self._checker.output_difference(example, got, self.optionflags))\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 37,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 40,
        "n_ast_nodes": 59,
        "n_identifiers": 10,
        "d_id": 56908,
        "documentation": {
            "docstring": "\n        Report that the given example failed.\n        ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 156915,
        "commit_id": "bf66221722cce8f09a9b09895bdb4596f14a5430",
        "repo": "dask",
        "path": "dask/utils.py",
        "file_name": "utils.py",
        "fun_name": "tmpfile",
        "commit_message": "`tmpfile` does not end files with period on empty extension (#9429)",
        "code": "def tmpfile(extension=\"\", dir=None):\n    \n    extension = extension.lstrip(\".\")\n    if extension:\n        extension = \".\" + extension\n    handle, filename = tempfile.mkstemp(extension, dir=dir)\n    os.close(handle)\n    os.remove(filename)\n\n    try:\n        yield filename\n    finally:\n        if os.path.exists(filename):\n            with suppress(OSError):  # sometimes we can't remove a generated temp file\n                if os.path.isdir(filename):\n                    shutil.rmtree(filename)\n                else:\n                    os.remove(filename)\n\n\n@contextmanager",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "@contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 167,
        "n_words": 43,
        "vocab_size": 35,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 100,
        "n_ast_nodes": 179,
        "n_identifiers": 19,
        "d_id": 36805,
        "documentation": {
            "docstring": "\n    Function to create and return a unique temporary file with the given extension, if provided.\n\n    Parameters\n    ----------\n    extension : str\n        The extension of the temporary file to be created\n    dir : str\n        If ``dir`` is not None, the file will be created in that directory; otherwise,\n        Python's default temporary directory is used.\n\n    Returns\n    -------\n    out : str\n        Path to the temporary file\n\n    See Also\n    --------\n    NamedTemporaryFile : Built-in alternative for creating temporary files\n    tmp_path : pytest fixture for creating a temporary directory unique to the test invocation\n\n    Notes\n    -----\n    This context manager is particularly useful on Windows for opening temporary files multiple times.\n    ",
            "n_words": 103,
            "vocab_size": 69,
            "n_whitespaces": 180,
            "language": "en"
        }
    },
    {
        "id": 178303,
        "commit_id": "56eb59d93f13815e66d0dea07e7669dfe275fa10",
        "repo": "Nuitka",
        "path": "nuitka/plugins/PluginBase.py",
        "file_name": "PluginBase.py",
        "fun_name": "makeDllEntryPoint",
        "commit_message": "Plugins: Massive cleanup and API improvements and Kivy support\n\n* Added method to locate a DLL and to create a DLL entry point\n  as expected, removing need for imports and making it more\n  clear as an API.\n\n* The location of modules had already an API, but it wasn'\n  used where it could be.\n\n* Moved implicit imports and DLL usage for Gi to its plugin,\n  solving a TODO for it.\n\n* Make sure sure to only yield, and not return, that is just\n  more error prone.\n\n* Also allow generators for implicit dependencies, such that\n  generators work in a yield from fashion.\n\n* With this, Kivy apps work on at least Linux.",
        "code": "def makeDllEntryPoint(cls, source_path, dest_path, package_name):\n        \n        return makeDllEntryPoint(\n            source_path=source_path, dest_path=dest_path, package_name=package_name\n        )\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 43,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 27,
        "n_ast_nodes": 40,
        "n_identifiers": 5,
        "d_id": 42655,
        "documentation": {
            "docstring": "Create an entry point, as expected to be provided by getExtraDlls.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 107479,
        "commit_id": "f156db08eee54d285ab0fb4e031e48d078ba6aa3",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_base.py",
        "file_name": "_base.py",
        "fun_name": "contains_point",
        "commit_message": "DOC: More cleanup axes -> Axes",
        "code": "def contains_point(self, point):\n        \n        return self.patch.contains_point(point, radius=1.0)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 23,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 22768,
        "documentation": {
            "docstring": "\n        Return whether *point* (pair of pixel coordinates) is inside the Axes\n        patch.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 127998,
        "commit_id": "5034544d5df5d7d9596b261d7bdffdd28e76fe2b",
        "repo": "ray",
        "path": "python/ray/air/checkpoint.py",
        "file_name": "checkpoint.py",
        "fun_name": "to_dict",
        "commit_message": "[AIR] Maintain checkpoint type information during serialization  (#28387)\n\nThese changes are needed to fix the errors described in #28134.\r\n\r\nSigned-off-by: Balaji Veeramani <bveeramani@berkeley.edu>\r\nCo-authored-by: Amog Kamsetty <amogkam@users.noreply.github.com>",
        "code": "def to_dict(self) -> dict:\n        \n        if self._data_dict:\n            # If the checkpoint data is already a dict, return\n            checkpoint_data = self._data_dict\n        elif self._obj_ref:\n            # If the checkpoint data is an object reference, resolve\n            checkpoint_data = ray.get(self._obj_ref)\n        elif self._local_path or self._uri:\n            # Else, checkpoint is either on FS or external storage\n            with self.as_directory() as local_path:\n                checkpoint_data_path = os.path.join(\n                    local_path, _DICT_CHECKPOINT_FILE_NAME\n                )\n                if os.path.exists(checkpoint_data_path):\n                    # If we are restoring a dict checkpoint, load the dict\n                    # from the checkpoint file.\n                    with open(checkpoint_data_path, \"rb\") as f:\n                        checkpoint_data = pickle.load(f)\n\n                    # If there are additional files in the directory, add them as\n                    # _DICT_CHECKPOINT_ADDITIONAL_FILE_KEY\n                    additional_files = {}\n                    for file_or_dir in os.listdir(local_path):\n                        if file_or_dir in [\n                            \".\",\n                            \"..\",\n                            _DICT_CHECKPOINT_FILE_NAME,\n                            _CHECKPOINT_METADATA_FILE_NAME,\n                        ]:\n                            continue\n\n                        additional_files[file_or_dir] = _pack(\n                            os.path.join(local_path, file_or_dir)\n                        )\n\n                    if additional_files:\n                        checkpoint_data[\n                            _DICT_CHECKPOINT_ADDITIONAL_FILE_KEY\n                        ] = additional_files\n\n                else:\n                    files = [\n                        f\n                        for f in os.listdir(local_path)\n                        if os.path.isfile(os.path.join(local_path, f))\n                        and f.endswith(_METADATA_CHECKPOINT_SUFFIX)\n                    ]\n                    metadata = {}\n                    for file in files:\n                        with open(os.path.join(local_path, file), \"rb\") as f:\n                            key = file[: -len(_METADATA_CHECKPOINT_SUFFIX)]\n                            value = pickle.load(f)\n                            metadata[key] = value\n\n                    data = _pack(local_path)\n\n                    checkpoint_data = {\n                        _FS_CHECKPOINT_KEY: data,\n                    }\n                    checkpoint_data.update(metadata)\n        else:\n            raise RuntimeError(f\"Empty data for checkpoint {self}\")\n\n        return _CheckpointDict(checkpoint_data, metadata=self._metadata)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 1257,
        "n_words": 186,
        "vocab_size": 112,
        "complexity": 13,
        "nloc": 60,
        "token_counts": 280,
        "n_ast_nodes": 465,
        "n_identifiers": 43,
        "d_id": 28585,
        "documentation": {
            "docstring": "Return checkpoint data as dictionary.\n\n        .. note::\n            :meth:`~Checkpoint.to_dict` returns a ``dict`` subclass that contains\n            information about the checkpoint type. This ``dict`` subclass is\n            functionally identical to the built-in ``dict``.\n\n        Returns:\n            dict: Dictionary containing checkpoint data.\n        ",
            "n_words": 35,
            "vocab_size": 30,
            "n_whitespaces": 100,
            "language": "en"
        }
    },
    {
        "id": 299558,
        "commit_id": "781ec87dff674b5f47f4138552d818cc490b5201",
        "repo": "core",
        "path": "tests/components/insteon/mock_devices.py",
        "file_name": "mock_devices.py",
        "fun_name": "fill_properties",
        "commit_message": "Fix Insteon tests (#71092)",
        "code": "def fill_properties(self, address, props_dict):\n        \n\n        device = self._devices[Address(address)]\n        operating_flags = props_dict.get(\"operating_flags\", {})\n        properties = props_dict.get(\"properties\", {})\n\n        with patch(\"pyinsteon.subscriber_base.publish_topic\", MagicMock()):\n            for flag in operating_flags:\n                value = operating_flags[flag]\n                if device.operating_flags.get(flag):\n                    device.operating_flags[flag].load(value)\n            for flag in properties:\n                value = properties[flag]\n                if device.properties.get(flag):\n                    device.properties[flag].load(value)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 193,
        "n_words": 38,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 117,
        "n_ast_nodes": 190,
        "n_identifiers": 15,
        "d_id": 98486,
        "documentation": {
            "docstring": "Fill the operating flags and extended properties of a device.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 151922,
        "commit_id": "c2936d551b8ad6ccf7b57e2ac6cb55d8550622cf",
        "repo": "freqtrade",
        "path": "freqtrade/strategy/interface.py",
        "file_name": "interface.py",
        "fun_name": "set_freqai_targets",
        "commit_message": "improve doc, update test strats, change function names",
        "code": "def set_freqai_targets(self, dataframe, **kwargs):\n        \n        return dataframe\n\n###\n# END - Intended to be overridden by strategy\n###\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 28,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 13,
        "n_ast_nodes": 25,
        "n_identifiers": 4,
        "d_id": 35164,
        "documentation": {
            "docstring": "\n        *Only functional with FreqAI enabled strategies*\n        Required function to set the targets for the model.\n        All targets must be prepended with `&` to be recognized by the FreqAI internals.\n\n        More details about feature engineering available:\n\n        https://www.freqtrade.io/en/latest/freqai-feature-engineering\n\n        :param df: strategy dataframe which will receive the targets\n        usage example: dataframe[\"&-target\"] = dataframe[\"close\"].shift(-1) / dataframe[\"close\"]\n        ",
            "n_words": 52,
            "vocab_size": 43,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 323211,
        "commit_id": "c541f4ba1fcab8304c7ac4efdce3d63a2e478176",
        "repo": "PaddleNLP",
        "path": "paddlenlp/utils/file_lock.py",
        "file_name": "file_lock.py",
        "fun_name": "__exit__",
        "commit_message": "Add model parallel for FasterGPT. (#1755)\n\n* Add model parallel for FasterGPT.\r\n\r\n* Make GPT model parallel runable\r\n\r\n* Make FT model parallel optional.\r\n\r\n* Fix _write_setup_file when kwargs is not empty.\r\n\r\n* Fix ext_utils.load\r\n\r\n* Add file lock for model parallel.\r\n\r\n* Fix model_parallel.flag in CMakeLists.txt.\r\n\r\n* Use a separated lib for model parallel.\r\n\r\n* Make from_pretrained get partial model.\r\n\r\n* Make model parallel support layer group in python.\r\n\r\n* Fix fit_partial_model when model having keys state not including.\r\n\r\nAdd api docs for model parallel.\r\n\r\n* Fix the default world_size when mpi is not available.\r\n\r\n* Add demo for GPT model parallel.\r\n\r\n* Fix default global ft_para_conf.\r\n\r\n* Fix GPTModel state_dict wrapper for layer parallel.\r\n\r\n* Set seed for tensor parallel.\r\n\r\n* Fix location of gpt.h in cmake.\r\n\r\n* Fix seed in gpt.h\r\n\r\n* Fix NV FT GPT embedding.\r\n\r\n* Add more cases in gpt_mp_sample.py\r\n\r\n* Fix seed in ker_curand_setupLauncher.\r\nPut build dir of FG in PPNLP_HOME with digest of current path.\r\n\r\n* Refine gpt_mp_sample.py",
        "code": "def __exit__(self, type, value, traceback):\n        \n        if self.is_locked:\n            self.release()\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 33,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 22,
        "n_ast_nodes": 36,
        "n_identifiers": 7,
        "d_id": 118415,
        "documentation": {
            "docstring": " Activated at the end of the with statement.\n            It automatically releases the lock if it isn't locked.\n        ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 60461,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/_distutils_hack/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "pip_imported_during_build",
        "commit_message": "upd; format",
        "code": "def pip_imported_during_build():\n        \n        import traceback\n        return any(\n            frame.f_globals['__file__'].endswith('setup.py')\n            for frame, line in traceback.walk_stack(None)\n        )\n\n\nDISTUTILS_FINDER = DistutilsMetaFinder()\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 65,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 33,
        "n_ast_nodes": 68,
        "n_identifiers": 10,
        "d_id": 12171,
        "documentation": {
            "docstring": "\n        Detect if pip is being imported in a build script. Ref #2355.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 195534,
        "commit_id": "05ff60935043cf39192535eac38e2730212057c7",
        "repo": "ParlAI",
        "path": "parlai/core/torch_generator_agent.py",
        "file_name": "torch_generator_agent.py",
        "fun_name": "compute_loss",
        "commit_message": "Add Metric.from_mask helper method (#3411) (#4894)\n\n* Add Metric.from_mask helper method (#3411)\r\n\r\n* Use cls directly instead of passing in MyMetric",
        "code": "def compute_loss(self, batch, return_output=False):\n        \n        if batch.label_vec is None:\n            raise ValueError('Cannot compute loss without a label.')\n        model_output = self.model(*self._model_input(batch), ys=batch.label_vec)\n        scores, preds, *_ = model_output\n        score_view = scores.reshape(-1, scores.size(-1))\n        loss_flattened = self.criterion(score_view, batch.label_vec.view(-1))\n        loss_per_token = loss_flattened.view(scores.shape[:-1])\n        notnull = batch.label_vec.ne(self.NULL_IDX)\n\n        # save loss to metrics\n        # cross entropy loss\n        self.record_local_metric(\n            'loss', AverageMetric.from_mask(loss_per_token, notnull)\n        )\n        # perplexity\n        self.record_local_metric('ppl', PPLMetric.from_mask(loss_per_token, notnull))\n        # token-wise accuracy\n        self.record_local_metric(\n            'token_acc', AverageMetric.from_mask(batch.label_vec == preds, notnull)\n        )\n        # utterance-wise exact match\n        num_target_tokens = notnull.long().sum(dim=-1)\n        num_tokens_correct = ((batch.label_vec == preds) * notnull).sum(dim=-1)\n        self.record_local_metric(\n            'token_em', AverageMetric.many(num_tokens_correct == num_target_tokens)\n        )\n\n        # actually do backwards loss\n        loss = loss_per_token.sum(dim=1)\n        loss = loss.sum()\n        loss /= num_target_tokens.sum()  # average loss per token\n        if return_output:\n            return (loss, model_output)\n        else:\n            return loss\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 377,
        "n_words": 114,
        "vocab_size": 80,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 252,
        "n_ast_nodes": 410,
        "n_identifiers": 35,
        "d_id": 47269,
        "documentation": {
            "docstring": "\n        Compute and return the loss for the given batch.\n\n        Easily overridable for customized loss functions.\n\n        If return_output is True, the full output from the call to self.model()\n        is also returned, via a (loss, model_output) pair.\n        ",
            "n_words": 35,
            "vocab_size": 29,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 31289,
        "commit_id": "a72f1c9f5b907f96cbb7de3bbb02a1d431d34071",
        "repo": "transformers",
        "path": "src/transformers/models/longt5/modeling_longt5.py",
        "file_name": "modeling_longt5.py",
        "fun_name": "_relative_position_bucket",
        "commit_message": "Add `LongT5` model (#16792)\n\n* Initial commit\r\n\r\n* Make some fixes\r\n\r\n* Make PT model full forward pass\r\n\r\n* Drop TF & Flax implementation, fix copies etc\r\n\r\n* Add Flax model and update some corresponding stuff\r\n\r\n* Drop some TF things\r\n\r\n* Update config and flax local attn\r\n\r\n* Add encoder_attention_type to config\r\n\r\n* .\r\n\r\n* Update docs\r\n\r\n* Do some cleansing\r\n\r\n* Fix some issues -> make style; add some docs\r\n\r\n* Fix position_bias + mask addition + Update tests\r\n\r\n* Fix repo consistency\r\n\r\n* Fix model consistency by removing flax operation over attn_mask\r\n\r\n* [WIP] Add PT TGlobal LongT5\r\n\r\n* .\r\n\r\n* [WIP] Add flax tglobal model\r\n\r\n* [WIP] Update flax model to use the right attention type in the encoder\r\n\r\n* Fix flax tglobal model forward pass\r\n\r\n* Make the use of global_relative_attention_bias\r\n\r\n* Add test suites for TGlobal model\r\n\r\n* Fix minor bugs, clean code\r\n\r\n* Fix pt-flax equivalence though not convinced with correctness\r\n\r\n* Fix LocalAttn implementation to match the original impl. + update READMEs\r\n\r\n* Few updates\r\n\r\n* Update: [Flax] improve large model init and loading #16148\r\n\r\n* Add ckpt conversion script accoring to #16853 + handle torch device placement\r\n\r\n* Minor updates to conversion script.\r\n\r\n* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM\r\n\r\n* gpu support + dtype fix\r\n\r\n* Apply some suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* * Remove (de)parallelize stuff\r\n* Edit shape comments\r\n* Update README.md\r\n* make fix-copies\r\n\r\n* Remove caching logic for local & tglobal attention\r\n\r\n* Apply another batch of suggestions from code review\r\n\r\n* Add missing checkpoints\r\n* Format converting scripts\r\n* Drop (de)parallelize links from longT5 mdx\r\n\r\n* Fix converting script + revert config file change\r\n\r\n* Revert \"Remove caching logic for local & tglobal attention\"\r\n\r\nThis reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.\r\n\r\n* Stash caching logic in Flax model\r\n\r\n* Make side relative bias used always\r\n\r\n* Drop caching logic in PT model\r\n\r\n* Return side bias as it was\r\n\r\n* Drop all remaining model parallel logic\r\n\r\n* Remove clamp statements\r\n\r\n* Move test files to the proper place\r\n\r\n* Update docs with new version of hf-doc-builder\r\n\r\n* Fix test imports\r\n\r\n* Make some minor improvements\r\n\r\n* Add missing checkpoints to docs\r\n* Make TGlobal model compatible with torch.onnx.export\r\n* Replace some np.ndarray with jnp.ndarray\r\n\r\n* Fix TGlobal for ONNX conversion + update docs\r\n\r\n* fix _make_global_fixed_block_ids and masked neg  value\r\n\r\n* update flax model\r\n\r\n* style and quality\r\n\r\n* fix imports\r\n\r\n* remove load_tf_weights_in_longt5 from init and fix copies\r\n\r\n* add slow test for TGlobal model\r\n\r\n* typo fix\r\n\r\n* Drop obsolete is_parallelizable and one warning\r\n\r\n* Update __init__ files to fix repo-consistency\r\n\r\n* fix pipeline test\r\n\r\n* Fix some device placements\r\n\r\n* [wip]: Update tests -- need to generate summaries to update expected_summary\r\n\r\n* Fix quality\r\n\r\n* Update LongT5 model card\r\n\r\n* Update (slow) summarization tests\r\n\r\n* make style\r\n\r\n* rename checkpoitns\r\n\r\n* finish\r\n\r\n* fix flax tests\r\n\r\nCo-authored-by: phungvanduy <pvduy23@gmail.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\nCo-authored-by: patil-suraj <surajp815@gmail.com>",
        "code": "def _relative_position_bucket(relative_position, bidirectional=True, num_buckets=32, max_distance=128):\n        \n        relative_buckets = 0\n        if bidirectional:\n            num_buckets //= 2\n            relative_buckets += (relative_position > 0).to(torch.long) * num_buckets\n            relative_position = torch.abs(relative_position)\n        else:\n            relative_position = -torch.min(relative_position, torch.zeros_like(relative_position))\n        # now relative_position is in the range [0, inf)\n\n        # half of the buckets are for exact increments in positions\n        max_exact = num_buckets // 2\n        is_small = relative_position < max_exact\n\n        # The other half of the buckets are for logarithmically bigger bins in positions up to max_distance\n        relative_position_if_large = max_exact + (\n            torch.log(relative_position.float() / max_exact)\n            / math.log(max_distance / max_exact)\n            * (num_buckets - max_exact)\n        ).to(torch.long)\n        relative_position_if_large = torch.min(\n            relative_position_if_large, torch.full_like(relative_position_if_large, num_buckets - 1)\n        )\n\n        relative_buckets += torch.where(is_small, relative_position, relative_position_if_large)\n        return relative_buckets\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 301,
        "n_words": 108,
        "vocab_size": 70,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 150,
        "n_ast_nodes": 240,
        "n_identifiers": 20,
        "d_id": 5721,
        "documentation": {
            "docstring": "\n        Adapted from Mesh Tensorflow:\n        https://github.com/tensorflow/mesh/blob/0cb87fe07da627bf0b7e60475d59f95ed6b5be3d/mesh_tensorflow/transformer/transformer_layers.py#L593\n\n        Translate relative position to a bucket number for relative attention. The relative position is defined as\n        memory_position - query_position, i.e. the distance in tokens from the attending position to the attended-to\n        position. If bidirectional=False, then positive relative positions are invalid. We use smaller buckets for\n        small absolute relative_position and larger buckets for larger absolute relative_positions. All relative\n        positions >=max_distance map to the same bucket. All relative positions <=-max_distance map to the same bucket.\n        This should allow for more graceful generalization to longer sequences than the model has been trained on\n\n        Args:\n            relative_position: an int32 Tensor\n            bidirectional: a boolean - whether the attention is bidirectional\n            num_buckets: an integer\n            max_distance: an integer\n\n        Returns:\n            a Tensor with the same shape as relative_position, containing int32 values in the range [0, num_buckets)\n        ",
            "n_words": 132,
            "vocab_size": 88,
            "n_whitespaces": 265,
            "language": "en"
        }
    },
    {
        "id": 216493,
        "commit_id": "52e1d0b8116c86777c85cb6c3d940e2c04a518c4",
        "repo": "salt",
        "path": "salt/fileserver/roots.py",
        "file_name": "roots.py",
        "fun_name": "_file_lists",
        "commit_message": "add __env__ substitution inside file and pillar root paths",
        "code": "def _file_lists(load, form):\n    \n    if \"env\" in load:\n        # \"env\" is not supported; Use \"saltenv\".\n        load.pop(\"env\")\n\n    saltenv = load[\"saltenv\"]\n    actual_saltenv = saltenv\n    if saltenv not in __opts__[\"file_roots\"]:\n        if \"__env__\" in __opts__[\"file_roots\"]:\n            log.debug(\n                \"salt environment '%s' maps to __env__ file_roots directory\", saltenv\n            )\n            saltenv = \"__env__\"\n        else:\n            return []\n\n    list_cachedir = os.path.join(__opts__[\"cachedir\"], \"file_lists\", \"roots\")\n    if not os.path.isdir(list_cachedir):\n        try:\n            os.makedirs(list_cachedir)\n        except OSError:\n            log.critical(\"Unable to make cachedir %s\", list_cachedir)\n            return []\n    list_cache = os.path.join(\n        list_cachedir, \"{}.p\".format(salt.utils.files.safe_filename_leaf(saltenv))\n    )\n    w_lock = os.path.join(\n        list_cachedir, \".{}.w\".format(salt.utils.files.safe_filename_leaf(saltenv))\n    )\n    cache_match, refresh_cache, save_cache = salt.fileserver.check_file_list_cache(\n        __opts__, form, list_cache, w_lock\n    )\n    if cache_match is not None:\n        return cache_match\n    if refresh_cache:\n        ret = {\"files\": set(), \"dirs\": set(), \"empty_dirs\": set(), \"links\": {}}\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 322,
        "n_words": 108,
        "vocab_size": 70,
        "complexity": 12,
        "nloc": 51,
        "token_counts": 366,
        "n_ast_nodes": 377,
        "n_identifiers": 31,
        "d_id": 54610,
        "documentation": {
            "docstring": "\n    Return a dict containing the file lists for files, dirs, emtydirs and symlinks\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 269467,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "_preprocess_conv2d_input",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _preprocess_conv2d_input(x, data_format, force_transpose=False):\n    \n    tf_data_format = \"NHWC\"\n    if data_format == \"channels_first\":\n        if not _has_nchw_support() or force_transpose:\n            x = tf.compat.v1.transpose(x, (0, 2, 3, 1))  # NCHW -> NHWC\n        else:\n            tf_data_format = \"NCHW\"\n    return x, tf_data_format\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 83,
        "n_words": 34,
        "vocab_size": 29,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 59,
        "n_ast_nodes": 99,
        "n_identifiers": 10,
        "d_id": 80102,
        "documentation": {
            "docstring": "Transpose and cast the input before the conv2d.\n\n    Args:\n        x: input tensor.\n        data_format: string, `\"channels_last\"` or `\"channels_first\"`.\n        force_transpose: Boolean. If True, the input will always be transposed\n            from NCHW to NHWC if `data_format` is `\"channels_first\"`.\n            If False, the transposition only occurs on CPU (GPU ops are\n            assumed to support NCHW).\n\n    Returns:\n        A tensor.\n    ",
            "n_words": 53,
            "vocab_size": 44,
            "n_whitespaces": 123,
            "language": "en"
        }
    },
    {
        "id": 207636,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_changelist_field_classes",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_changelist_field_classes(self):\n        \n        Podcast.objects.create(name=\"Django Dose\", release_date=datetime.date.today())\n        response = self.client.get(reverse(\"admin:admin_views_podcast_changelist\"))\n        self.assertContains(response, '<th class=\"field-name\">')\n        self.assertContains(response, '<td class=\"field-release_date nowrap\">')\n        self.assertContains(response, '<td class=\"action-checkbox\">')\n\n\ntry:\n    import docutils\nexcept ImportError:\n    docutils = None\n\n\n@unittest.skipUnless(docutils, \"no docutils installed.\")\n@override_settings(ROOT_URLCONF=\"admin_views.urls\")\n@modify_settings(\n    INSTALLED_APPS={\"append\": [\"django.contrib.admindocs\", \"django.contrib.flatpages\"]}\n)",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@unittest.skipUnless(docutils, \"no docutils installed.\")\n@override_settings(ROOT_URLCONF=\"admin_views.urls\")\n@modify_settings(\n    INSTALLED_APPS={\"append\": [\"django.contrib.admindocs\", \"django.contrib.flatpages\"]}\n)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 81,
        "n_words": 36,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 63,
        "n_ast_nodes": 186,
        "n_identifiers": 23,
        "d_id": 52031,
        "documentation": {
            "docstring": "\n        Cells of the change list table should contain the field name in their class attribute\n        Refs #11195.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 163188,
        "commit_id": "521259299f7829da667ba39302ec77acedde9e5e",
        "repo": "pandas",
        "path": "pandas/core/arrays/datetimes.py",
        "file_name": "datetimes.py",
        "fun_name": "time",
        "commit_message": "DOC: Improve doc summaries in series.rst (#45237)",
        "code": "def time(self) -> npt.NDArray[np.object_]:\n        \n        # If the Timestamps have a timezone that is not UTC,\n        # convert them into their i8 representation while\n        # keeping their timezone and not using UTC\n        timestamps = self._local_timestamps()\n\n        return ints_to_pydatetime(timestamps, box=\"time\")\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 79,
        "n_words": 37,
        "vocab_size": 32,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 31,
        "n_ast_nodes": 56,
        "n_identifiers": 10,
        "d_id": 39396,
        "documentation": {
            "docstring": "\n        Returns numpy array of :class:`datetime.time` objects.\n\n        The time part of the Timestamps.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 243706,
        "commit_id": "2ae55ccbdad9c842929fb238ea1eb81d1f999024",
        "repo": "Pillow",
        "path": "src/PIL/Image.py",
        "file_name": "Image.py",
        "fun_name": "putalpha",
        "commit_message": "Improve exception traceback readability",
        "code": "def putalpha(self, alpha):\n        \n\n        self._ensure_mutable()\n\n        if self.mode not in (\"LA\", \"PA\", \"RGBA\"):\n            # attempt to promote self to a matching alpha mode\n            try:\n                mode = getmodebase(self.mode) + \"A\"\n                try:\n                    self.im.setmode(mode)\n                except (AttributeError, ValueError) as e:\n                    # do things the hard way\n                    im = self.im.convert(mode)\n                    if im.mode not in (\"LA\", \"PA\", \"RGBA\"):\n                        raise ValueError from e  # sanity check\n                    self.im = im\n                self.pyaccess = None\n                self.mode = self.im.mode\n            except KeyError as e:\n                msg = \"illegal image mode\"\n                raise ValueError(msg) from e\n\n        if self.mode in (\"LA\", \"PA\"):\n            band = 1\n        else:\n            band = 3\n\n        if isImageType(alpha):\n            # alpha layer\n            if alpha.mode not in (\"1\", \"L\"):\n                msg = \"illegal image mode\"\n                raise ValueError(msg)\n            alpha.load()\n            if alpha.mode == \"1\":\n                alpha = alpha.convert(\"L\")\n        else:\n            # constant alpha\n            try:\n                self.im.fillband(band, alpha)\n            except (AttributeError, ValueError):\n                # do things the hard way\n                alpha = new(\"L\", self.size, alpha)\n            else:\n                return\n\n        self.im.putband(alpha.im, band)\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 670,
        "n_words": 142,
        "vocab_size": 78,
        "complexity": 10,
        "nloc": 36,
        "token_counts": 233,
        "n_ast_nodes": 403,
        "n_identifiers": 22,
        "d_id": 70078,
        "documentation": {
            "docstring": "\n        Adds or replaces the alpha layer in this image.  If the image\n        does not have an alpha layer, it's converted to \"LA\" or \"RGBA\".\n        The new layer must be either \"L\" or \"1\".\n\n        :param alpha: The new alpha layer.  This can either be an \"L\" or \"1\"\n           image having the same size as this image, or an integer or\n           other color value.\n        ",
            "n_words": 62,
            "vocab_size": 43,
            "n_whitespaces": 120,
            "language": "en"
        }
    },
    {
        "id": 64293,
        "commit_id": "363ed9ccba3f848908113e6d728735a1c894aec8",
        "repo": "erpnext",
        "path": "erpnext/regional/report/datev/datev.py",
        "file_name": "datev.py",
        "fun_name": "run_query",
        "commit_message": "revert: BU Schlüssel (a21f76f)",
        "code": "def run_query(filters, extra_fields, extra_joins, extra_filters, as_dict=1):\n\t\n\tquery = .format(\n\t\t\textra_fields=extra_fields,\n\t\t\textra_joins=extra_joins,\n\t\t\textra_filters=extra_filters\n\t\t)\n\n\tgl_entries = frappe.db.sql(query, filters, as_dict=as_dict)\n\n\treturn gl_entries\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 12,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 58,
        "token_counts": 52,
        "n_ast_nodes": 79,
        "n_identifiers": 12,
        "d_id": 13598,
        "documentation": {
            "docstring": "\n\tGet a list of accounting entries.\n\n\tSelect GL Entries joined with Account and Party Account in order to get the\n\taccount numbers. Returns a list of accounting entries.\n\n\tArguments:\n\tfilters -- dict of filters to be passed to the sql query\n\tas_dict -- return as list of dicts [0,1]\n\t\n\t\tSELECT\n\n\t\t\t/* either debit or credit amount; always positive */\n\t\t\tcase gl.debit when 0 then gl.credit else gl.debit end as 'Umsatz (ohne Soll/Haben-Kz)',\n\n\t\t\t/* 'H' when credit, 'S' when debit */\n\t\t\tcase gl.debit when 0 then 'H' else 'S' end as 'Soll/Haben-Kennzeichen',\n\n\t\t\t/* account number or, if empty, party account number */\n\t\t\tacc.account_number as 'Konto',\n\n\t\t\t/* against number or, if empty, party against number */\n\t\t\t%(temporary_against_account_number)s as 'Gegenkonto (ohne BU-Schlüssel)',\n\n\t\t\t'' as 'BU-Schlüssel',\n\n\t\t\tgl.posting_date as 'Belegdatum',\n\t\t\tgl.voucher_no as 'Belegfeld 1',\n\t\t\tREPLACE(LEFT(gl.remarks, 60), '\\n', ' ') as 'Buchungstext',\n\t\t\tgl.voucher_type as 'Beleginfo - Art 1',\n\t\t\tgl.voucher_no as 'Beleginfo - Inhalt 1',\n\t\t\tgl.against_voucher_type as 'Beleginfo - Art 2',\n\t\t\tgl.against_voucher as 'Beleginfo - Inhalt 2',\n\t\t\tgl.party_type as 'Beleginfo - Art 3',\n\t\t\tgl.party as 'Beleginfo - Inhalt 3',\n\t\t\tcase gl.party_type when 'Customer' then 'Debitorennummer' when 'Supplier' then 'Kreditorennummer' else NULL end as 'Beleginfo - Art 4',\n\t\t\tpar.debtor_creditor_number as 'Beleginfo - Inhalt 4'\n\n\t\t\t{extra_fields}\n\n\t\tFROM `tabGL Entry` gl\n\n\t\t\t/* Kontonummer */\n\t\t\tLEFT JOIN `tabAccount` acc\n\t\t\tON gl.account = acc.name\n\n\t\t\tLEFT JOIN `tabParty Account` par\n\t\t\tON par.parent = gl.party\n\t\t\tAND par.parenttype = gl.party_type\n\t\t\tAND par.company = %(company)s\n\n\t\t\t{extra_joins}\n\n\t\tWHERE gl.company = %(company)s\n\t\tAND DATE(gl.posting_date) >= %(from_date)s\n\t\tAND DATE(gl.posting_date) <= %(to_date)s\n\n\t\t{extra_filters}\n\n\t\tORDER BY 'Belegdatum', gl.voucher_no",
            "n_words": 247,
            "vocab_size": 136,
            "n_whitespaces": 205,
            "language": "en"
        }
    },
    {
        "id": 285809,
        "commit_id": "3780cffeced904d41e04e2adfe8c1f2a34337099",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/etf/screener/screener_model.py",
        "file_name": "screener_model.py",
        "fun_name": "get_preset_choices",
        "commit_message": "New path for presets (#2634)\n\n* modify path for etf, options, insider\r\n\r\n* fix small\r\n\r\n* change path for stocks screener\r\n\r\n* fix flake 8\r\n\r\n* remove preset_path\r\n\r\n* black\r\n\r\n* fix\r\n\r\n* fix tests\r\n\r\n* fix tests\r\n\r\n* fix flake8\r\n\r\n* change paths_helper load\r\n\r\n* put ns parser back\r\n\r\nCo-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com>",
        "code": "def get_preset_choices() -> Dict:\n    \n\n    PRESETS_PATH = PRESETS_DIRECTORY / \"etf\" / \"screener\"\n    PRESETS_PATH_DEFAULT = Path(__file__).parent / \"presets\"\n    preset_choices = {\n        filepath.name: filepath\n        for filepath in PRESETS_PATH.iterdir()\n        if filepath.suffix == \".ini\"\n    }\n    preset_choices.update(\n        {\n            filepath.name: filepath\n            for filepath in PRESETS_PATH_DEFAULT.iterdir()\n            if filepath.suffix == \".ini\"\n        }\n    )\n\n    return preset_choices\n\n\n@log_start_end(log=logger)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 138,
        "n_words": 47,
        "vocab_size": 30,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 75,
        "n_ast_nodes": 142,
        "n_identifiers": 17,
        "d_id": 85436,
        "documentation": {
            "docstring": "\n    Return a dict containing keys as name of preset and\n    filepath as value\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 260068,
        "commit_id": "6ff214c46bacaf0385125bb47b4d8cb4a305fa3a",
        "repo": "scikit-learn",
        "path": "examples/text/plot_hashing_vs_dict_vectorizer.py",
        "file_name": "plot_hashing_vs_dict_vectorizer.py",
        "fun_name": "tokenize",
        "commit_message": "DOC Rework plot_hashing_vs_dict_vectorizer.py example (#23266)\n\n\r\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def tokenize(doc):\n    \n    return (tok.lower() for tok in re.findall(r\"\\w+\", doc))\n\n\nlist(tokenize(\"This is a simple example, isn't it?\"))\n\n# %%\n# We define an additional function that counts the (frequency of) occurrence of\n# each token in a given document. It returns a frequency dictionary to be used\n# by the vectorizers.\n\nfrom collections import defaultdict\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 54,
        "n_words": 54,
        "vocab_size": 47,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 26,
        "n_ast_nodes": 68,
        "n_identifiers": 9,
        "d_id": 76052,
        "documentation": {
            "docstring": "Extract tokens from doc.\n\n    This uses a simple regex that matches word characters to break strings\n    into tokens. For a more principled approach, see CountVectorizer or\n    TfidfVectorizer.\n    ",
            "n_words": 27,
            "vocab_size": 26,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 55479,
        "commit_id": "11638691240b7595c0d02542af506a96d344ae8b",
        "repo": "prefect",
        "path": "tests/cli/test_storage_cli.py",
        "file_name": "test_storage_cli.py",
        "fun_name": "get_first_menu_and_fail",
        "commit_message": "Update tests",
        "code": "def get_first_menu_and_fail() -> click.testing.Result:\n    \n    command = [\"storage\", \"create\"]\n    runner = CliRunner()\n    result = runner.invoke(app, command, input=INVALID_OPTION, catch_exceptions=False)\n\n    return result\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 34,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 43,
        "n_ast_nodes": 72,
        "n_identifiers": 13,
        "d_id": 11330,
        "documentation": {
            "docstring": "\n    Utility function to get output of first step of `prefect storage create` and exit\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 245154,
        "commit_id": "36c1f477b273cb2fb0dea3c921ec267db877c039",
        "repo": "mmdetection",
        "path": "mmdet/datasets/samplers/class_aware_sampler.py",
        "file_name": "class_aware_sampler.py",
        "fun_name": "get_cat2imgs",
        "commit_message": "Refactor OpenImages.",
        "code": "def get_cat2imgs(self) -> Dict[int, list]:\n        \n        classes = self.dataset.metainfo.get('CLASSES', None)\n        if classes is None:\n            raise ValueError('dataset metainfo must contain CLASSES')\n        # sort the label index\n        cat2imgs = {i: [] for i in range(len(classes))}\n        for i in range(len(self.dataset)):\n            cat_ids = set(self.dataset.get_cat_ids(i))\n            for cat in cat_ids:\n                cat2imgs[cat].append(i)\n        return cat2imgs\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 143,
        "n_words": 46,
        "vocab_size": 37,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 97,
        "n_ast_nodes": 157,
        "n_identifiers": 19,
        "d_id": 70678,
        "documentation": {
            "docstring": "Get a dict with class as key and img_ids as values.\n\n        Returns:\n            dict[int, list]: A dict of per-label image list,\n            the item of the dict indicates a label index,\n            corresponds to the image index that contains the label.\n        ",
            "n_words": 38,
            "vocab_size": 29,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 256957,
        "commit_id": "ac5617e757e9ace6f30b7291686d9dbbc339f433",
        "repo": "haystack",
        "path": "haystack/telemetry.py",
        "file_name": "telemetry.py",
        "fun_name": "print_telemetry_report",
        "commit_message": "Add basic telemetry features (#2314)\n\n* add basic telemetry features\r\n\r\n* change pipeline_config to _component_config\r\n\r\n* Update Documentation & Code Style\r\n\r\n* add super().__init__() calls to error classes\r\n\r\n* make posthog mock work with python 3.7\r\n\r\n* Update Documentation & Code Style\r\n\r\n* update link to docs web page\r\n\r\n* log exceptions, send event for raised HaystackErrors, refactor Path(CONFIG_PATH)\r\n\r\n* add comment on send_event in BaseComponent.init() and fix mypy\r\n\r\n* mock NonPrivateParameters and fix pylint undefined-variable\r\n\r\n* Update Documentation & Code Style\r\n\r\n* check model path contains multiple /\r\n\r\n* add test for writing to file\r\n\r\n* add test for en-/disable telemetry\r\n\r\n* Update Documentation & Code Style\r\n\r\n* merge file deletion methods and ignore pylint global statement\r\n\r\n* Update Documentation & Code Style\r\n\r\n* set env variable in demo to activate telemetry\r\n\r\n* fix mock of HAYSTACK_TELEMETRY_ENABLED\r\n\r\n* fix mypy and linter\r\n\r\n* add CI as env variable to execution contexts\r\n\r\n* remove threading, add test for custom error event\r\n\r\n* Update Documentation & Code Style\r\n\r\n* simplify config/log file deletion\r\n\r\n* add test for final event being sent\r\n\r\n* force writing config file in test\r\n\r\n* make test compatible with python 3.7\r\n\r\n* switch to posthog production server\r\n\r\n* Update Documentation & Code Style\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def print_telemetry_report():\n    \n    if is_telemetry_enabled():\n        user_id = _get_or_create_user_id()\n        meta_data = _get_or_create_telemetry_meta_data()\n        print({**{\"user_id\": user_id}, **meta_data})\n    else:\n        print(\"Telemetry is disabled.\")\n\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 54,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 40,
        "n_ast_nodes": 76,
        "n_identifiers": 7,
        "d_id": 74974,
        "documentation": {
            "docstring": "\n    Prints the user id and the meta data that are sent in events\n    ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 176083,
        "commit_id": "26be7d28bdb4eb96c888e373e08f46e6b85711e3",
        "repo": "edgedb",
        "path": "tests/test_edgeql_for.py",
        "file_name": "test_edgeql_for.py",
        "fun_name": "test_edgeql_for_in_computable_05",
        "commit_message": "Add a `bag` type that tells assert_query_result to ignore order (#3314)\n\nassert_query_result currently supports using sets to ignore order,\r\nbut that doesn't work for objects, which can't be hashed or sorted.\r\n\r\nThere is a system for specifying a sort key for internal data, but it\r\nis way clunkier than just saying we don't care about the order.\r\n\r\nI converted some places that were using sort= to use this.",
        "code": "async def test_edgeql_for_in_computable_05(self):\n        await self.assert_query_result(\n            r,\n            [{\"select_deck\":\n              tb.bag([\"Bog monster\", \"Dragon\", \"Giant turtle\", \"Imp\"])}],\n        )\n\n        # This one caused a totally nonsense type error.\n        await self.assert_query_result(\n            r,\n            [{\"select_deck\":\n              tb.bag([\"Bog monster\", \"Dragon\", \"Giant turtle\", \"Imp\"])}],\n        )\n",
        "url": "https://github.com/edgedb/edgedb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 138,
        "n_words": 34,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 65,
        "n_ast_nodes": 117,
        "n_identifiers": 5,
        "d_id": 41673,
        "documentation": {
            "docstring": "\n                SELECT User {\n                    select_deck := (\n                        FOR letter IN {'X'}\n                        UNION (\n                            (SELECT .deck.name)\n                        )\n                    )\n                } FILTER .name = 'Alice';\n            \n                SELECT User {\n                    select_deck := (\n                        FOR letter IN 'X'\n                        UNION (\n                            ((SELECT .deck).name)\n                        )\n                    )\n                } FILTER .name = 'Alice';\n            ",
            "n_words": 42,
            "vocab_size": 22,
            "n_whitespaces": 394,
            "language": "en"
        }
    },
    {
        "id": 58181,
        "commit_id": "b7d5fc52e4235370e368e96da218ca49bd32edcc",
        "repo": "prefect",
        "path": "src/prefect/orion/services/loop_service.py",
        "file_name": "loop_service.py",
        "fun_name": "stop",
        "commit_message": "Change default behavior to block=false",
        "code": "async def stop(self, block=False) -> None:\n        \n        self._stop()\n\n        if block:\n            while self._is_running:\n                await asyncio.sleep(0.1)\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 60,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 34,
        "n_ast_nodes": 56,
        "n_identifiers": 7,
        "d_id": 11739,
        "documentation": {
            "docstring": "\n        Gracefully stops a running LoopService and optionally blocks until the\n        service stops.\n\n        Args:\n            block (bool): if True, blocks until the service is\n                finished running. Otherwise it requests a stop and returns but\n                the service may still be running a final loop.\n\n        ",
            "n_words": 41,
            "vocab_size": 31,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 267014,
        "commit_id": "a0dede545864b9835f84315b4b3ea17dd1eafe04",
        "repo": "ansible",
        "path": "lib/ansible/executor/task_executor.py",
        "file_name": "task_executor.py",
        "fun_name": "run",
        "commit_message": "ansible-connection verboistery (#77509)\n\n* ansible-connection verboistery\r\n\r\n  for cli, just use normal parser creation\r\n this also adds --help, but that seems fine\r\n also some error cleanup\r\n\r\nCo-authored-by: Nathaniel Case <this.is@nathanielca.se>",
        "code": "def run(self):\n        \n\n        display.debug(\"in run() - task %s\" % self._task._uuid)\n\n        try:\n            try:\n                items = self._get_loop_items()\n            except AnsibleUndefinedVariable as e:\n                # save the error raised here for use later\n                items = None\n                self._loop_eval_error = e\n\n            if items is not None:\n                if len(items) > 0:\n                    item_results = self._run_loop(items)\n\n                    # create the overall result item\n                    res = dict(results=item_results)\n\n                    # loop through the item results and set the global changed/failed/skipped result flags based on any item.\n                    res['skipped'] = True\n                    for item in item_results:\n                        if 'changed' in item and item['changed'] and not res.get('changed'):\n                            res['changed'] = True\n                        if res['skipped'] and ('skipped' not in item or ('skipped' in item and not item['skipped'])):\n                            res['skipped'] = False\n                        if 'failed' in item and item['failed']:\n                            item_ignore = item.pop('_ansible_ignore_errors')\n                            if not res.get('failed'):\n                                res['failed'] = True\n                                res['msg'] = 'One or more items failed'\n                                self._task.ignore_errors = item_ignore\n                            elif self._task.ignore_errors and not item_ignore:\n                                self._task.ignore_errors = item_ignore\n\n                        # ensure to accumulate these\n                        for array in ['warnings', 'deprecations']:\n                            if array in item and item[array]:\n                                if array not in res:\n                                    res[array] = []\n                                if not isinstance(item[array], list):\n                                    item[array] = [item[array]]\n                                res[array] = res[array] + item[array]\n                                del item[array]\n\n                    if not res.get('failed', False):\n                        res['msg'] = 'All items completed'\n                    if res['skipped']:\n                        res['msg'] = 'All items skipped'\n                else:\n                    res = dict(changed=False, skipped=True, skipped_reason='No items in the list', results=[])\n            else:\n                display.debug(\"calling self._execute()\")\n                res = self._execute()\n                display.debug(\"_execute() done\")\n\n            # make sure changed is set in the result, if it's not present\n            if 'changed' not in res:\n                res['changed'] = False\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "def run(self):\n        '''\n        The main executor entrypoint, where we determine if the specified\n        task requires looping and either runs the task with self._run_loop()\n        or self._execute(). After that, the returned results are parsed and\n        returned as a dict.\n        '''\n\n        display.debug(\"in run() - task %s\" % self._task._uuid)\n\n        try:\n            try:\n                items = self._get_loop_items()\n            except AnsibleUndefinedVariable as e:\n                # save the error raised here for use later\n                items = None\n                self._loop_eval_error = e\n\n            if items is not None:\n                if len(items) > 0:\n                    item_results = self._run_loop(items)\n\n                    # create the overall result item\n                    res = dict(results=item_results)\n\n                    # loop through the item results and set the global changed/failed/skipped result flags based on any item.\n                    res['skipped'] = True\n                    for item in item_results:\n                        if 'changed' in item and item['changed'] and not res.get('changed'):\n                            res['changed'] = True\n                        if res['skipped'] and ('skipped' not in item or ('skipped' in item and not item['skipped'])):\n                            res['skipped'] = False\n                        if 'failed' in item and item['failed']:\n                            item_ignore = item.pop('_ansible_ignore_errors')\n                            if not res.get('failed'):\n                                res['failed'] = True\n                                res['msg'] = 'One or more items failed'\n                                self._task.ignore_errors = item_ignore\n                            elif self._task.ignore_errors and not item_ignore:\n                                self._task.ignore_errors = item_ignore\n\n                        # ensure to accumulate these\n                        for array in ['warnings', 'deprecations']:\n                            if array in item and item[array]:\n                                if array not in res:\n                                    res[array] = []\n                                if not isinstance(item[array], list):\n                                    item[array] = [item[array]]\n                                res[array] = res[array] + item[array]\n                                del item[array]\n\n                    if not res.get('failed', False):\n                        res['msg'] = 'All items completed'\n                    if res['skipped']:\n                        res['msg'] = 'All items skipped'\n                else:\n                    res = dict(changed=False, skipped=True, skipped_reason='No items in the list', results=[])\n            else:\n                display.debug(\"calling self._execute()\")\n                res = self._execute()\n                display.debug(\"_execute() done\")\n\n            # make sure changed is set in the result, if it's not present\n            if 'changed' not in res:\n                res['changed'] = False",
        "n_ast_errors": 1,
        "ast_levels": 20,
        "n_whitespaces": 1283,
        "n_words": 234,
        "vocab_size": 121,
        "complexity": 30,
        "nloc": 63,
        "token_counts": 501,
        "n_ast_nodes": 625,
        "n_identifiers": 29,
        "d_id": 78689,
        "documentation": {
            "docstring": "\n        The main executor entrypoint, where we determine if the specified\n        task requires looping and either runs the task with self._run_loop()\n        or self._execute(). After that, the returned results are parsed and\n        returned as a dict.\n        ",
            "n_words": 34,
            "vocab_size": 29,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 53285,
        "commit_id": "36e7e0838aeaffc9492b330297e4905f3ab4b11f",
        "repo": "prefect",
        "path": "tests/orion/database/test_migrations.py",
        "file_name": "test_migrations.py",
        "fun_name": "test_orion_full_migration_works_with_data_in_db",
        "commit_message": "code review revisions pt3",
        "code": "async def test_orion_full_migration_works_with_data_in_db(sample_db_data):\n    \n    try:\n        await run_sync_in_worker_thread(alembic_downgrade)\n    finally:\n        await run_sync_in_worker_thread(alembic_upgrade)\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 32,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 20,
        "n_ast_nodes": 40,
        "n_identifiers": 5,
        "d_id": 10770,
        "documentation": {
            "docstring": "\n    Tests that downgrade migrations work when the database has data in it.\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 3985,
        "commit_id": "6cd20e6879a42053692c18a16906eb410aad85db",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/unit_tests/test_base_streams.py",
        "file_name": "test_base_streams.py",
        "fun_name": "test_execute_in_batch_with_few_requests",
        "commit_message": "🐛 Source FB Marketing: fix `execute_in_batch` when batch is bigger than 50 (#10588)\n\n* fix execute_in_batch\r\n\r\n* add tests\r\n\r\n* fix pre-commit config\r\n\r\nCo-authored-by: Sherif A. Nada <snadalive@gmail.com>\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>\r\nCo-authored-by: Sherif A. Nada <snadalive@gmail.com>",
        "code": "def test_execute_in_batch_with_few_requests(self, api, batch, mock_batch_responses):\n        \n        mock_batch_responses(\n            [\n                {\n                    \"json\": [{\"body\": json.dumps({\"name\": \"creative 1\"}), \"code\": 200, \"headers\": {}}] * 3,\n                }\n            ]\n        )\n\n        stream = SomeTestStream(api=api)\n        requests = [FacebookRequest(\"node\", \"GET\", \"endpoint\") for _ in range(5)]\n\n        result = list(stream.execute_in_batch(requests))\n\n        assert batch.add_request.call_count == len(requests)\n        batch.execute.assert_called_once()\n        assert len(result) == 3\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 180,
        "n_words": 46,
        "vocab_size": 42,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 112,
        "n_ast_nodes": 190,
        "n_identifiers": 21,
        "d_id": 600,
        "documentation": {
            "docstring": "Should execute single batch if number of requests less than MAX_BATCH_SIZE.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 268931,
        "commit_id": "b96518a22bfd92a29811e507dec0b34248a8a3f5",
        "repo": "keras",
        "path": "keras/tests/model_subclassing_test_util.py",
        "file_name": "model_subclassing_test_util.py",
        "fun_name": "get_multi_io_subclass_model",
        "commit_message": "- Consolidate disparate test-related files into a single testing_infra folder.\n- Cleanup TODO related to removing testing infra as a dependency of the Keras target.\n- Standardize import naming: there is now only \"test_combinations\" for test combinations, and \"test_utils\" for utilities. The TF utilities module \"test_util\" is now always imported as \"tf_test_utils\" to avoid confusion.\n\nPiperOrigin-RevId: 426773173",
        "code": "def get_multi_io_subclass_model(use_bn=False, use_dp=False, num_classes=(2, 3)):\n  \n  shared_layer = keras.layers.Dense(32, activation='relu')\n  branch_a = [shared_layer]\n  if use_dp:\n    branch_a.append(keras.layers.Dropout(0.5))\n  branch_a.append(keras.layers.Dense(num_classes[0], activation='softmax'))\n\n  branch_b = [shared_layer]\n  if use_bn:\n    branch_b.append(keras.layers.BatchNormalization())\n  branch_b.append(keras.layers.Dense(num_classes[1], activation='softmax'))\n\n  model = (\n      test_utils._MultiIOSubclassModel(   # pylint: disable=protected-access\n          branch_a, branch_b, name='test_model'))\n  return model\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 69,
        "n_words": 37,
        "vocab_size": 30,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 135,
        "n_ast_nodes": 214,
        "n_identifiers": 18,
        "d_id": 79770,
        "documentation": {
            "docstring": "Creates MultiIOModel for the tests of subclass model.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 197335,
        "commit_id": "65be461082dda54c8748922f9c29a19af1279fe1",
        "repo": "sympy",
        "path": "sympy/physics/mechanics/functions.py",
        "file_name": "functions.py",
        "fun_name": "inertia",
        "commit_message": "Remove abbreviations in documentation",
        "code": "def inertia(frame, ixx, iyy, izz, ixy=0, iyz=0, izx=0):\n    \n\n    if not isinstance(frame, ReferenceFrame):\n        raise TypeError('Need to define the inertia in a frame')\n    ol = sympify(ixx) * (frame.x | frame.x)\n    ol += sympify(ixy) * (frame.x | frame.y)\n    ol += sympify(izx) * (frame.x | frame.z)\n    ol += sympify(ixy) * (frame.y | frame.x)\n    ol += sympify(iyy) * (frame.y | frame.y)\n    ol += sympify(iyz) * (frame.y | frame.z)\n    ol += sympify(izx) * (frame.z | frame.x)\n    ol += sympify(iyz) * (frame.z | frame.y)\n    ol += sympify(izz) * (frame.z | frame.z)\n    return ol\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 129,
        "n_words": 86,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 184,
        "n_ast_nodes": 286,
        "n_identifiers": 16,
        "d_id": 48478,
        "documentation": {
            "docstring": "Simple way to create inertia Dyadic object.\n\n    Explanation\n    ===========\n\n    If you do not know what a Dyadic is, just treat this like the inertia\n    tensor. Then, do the easy thing and define it in a body-fixed frame.\n\n    Parameters\n    ==========\n\n    frame : ReferenceFrame\n        The frame the inertia is defined in\n    ixx : Sympifyable\n        the xx element in the inertia dyadic\n    iyy : Sympifyable\n        the yy element in the inertia dyadic\n    izz : Sympifyable\n        the zz element in the inertia dyadic\n    ixy : Sympifyable\n        the xy element in the inertia dyadic\n    iyz : Sympifyable\n        the yz element in the inertia dyadic\n    izx : Sympifyable\n        the zx element in the inertia dyadic\n\n    Examples\n    ========\n\n    >>> from sympy.physics.mechanics import ReferenceFrame, inertia\n    >>> N = ReferenceFrame('N')\n    >>> inertia(N, 1, 2, 3)\n    (N.x|N.x) + 2*(N.y|N.y) + 3*(N.z|N.z)\n\n    ",
            "n_words": 131,
            "vocab_size": 73,
            "n_whitespaces": 240,
            "language": "en"
        }
    },
    {
        "id": 101689,
        "commit_id": "e5356a417e7c2124e75c4a2994ed604fc0a3cc74",
        "repo": "faceswap",
        "path": "lib/align/alignments.py",
        "file_name": "alignments.py",
        "fun_name": "hashes_to_frame",
        "commit_message": "Alignments update:\n  - Store face embeddings in PNG header when sorting\n  - typing + refactor\n  - Update alignments keys for 'identity' and 'video_meta' + bump to v2.3\n  - General typing fixes",
        "code": "def hashes_to_frame(self) -> Dict[str, Dict[str, int]]:\n        \n        return self._legacy.hashes_to_frame\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 24,
        "n_ast_nodes": 37,
        "n_identifiers": 6,
        "d_id": 21093,
        "documentation": {
            "docstring": " dict: The SHA1 hash of the face mapped to the frame(s) and face index within the frame\n        that the hash corresponds to.\n\n        Notes\n        -----\n        This method is depractated and exists purely for updating legacy hash based alignments\n        to new png header storage in :class:`lib.align.update_legacy_png_header`.\n        ",
            "n_words": 44,
            "vocab_size": 36,
            "n_whitespaces": 87,
            "language": "en"
        }
    },
    {
        "id": 12595,
        "commit_id": "65d6873500f008dafba193340f8731bca39bc7dc",
        "repo": "jina",
        "path": "jina/clients/base/helper.py",
        "file_name": "helper.py",
        "fun_name": "start",
        "commit_message": "feat: expose kwargs to Clients (#4947)",
        "code": "async def start(self):\n        \n        with ImportExtensions(required=True):\n            import aiohttp\n\n        self.session = aiohttp.ClientSession(**self._session_kwargs)\n        await self.session.__aenter__()\n        return self\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 60,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 71,
        "n_identifiers": 9,
        "d_id": 2350,
        "documentation": {
            "docstring": "Create ClientSession and enter context\n\n        :return: self\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 254229,
        "commit_id": "2b1acfbfe84b6c9c4756a615620f9b376d48085a",
        "repo": "d2l-en",
        "path": "d2l/torch.py",
        "file_name": "torch.py",
        "fun_name": "evaluate_accuracy_gpu",
        "commit_message": "JAX: Fix CI bug; enable build all sections",
        "code": "def evaluate_accuracy_gpu(net, data_iter, device=None):\n    \n    if isinstance(net, nn.Module):\n        net.eval()  # Set the model to evaluation mode\n        if not device:\n            device = next(iter(net.parameters())).device\n    # No. of correct predictions, no. of predictions\n    metric = d2l.Accumulator(2)\n\n    with torch.no_grad():\n        for X, y in data_iter:\n            if isinstance(X, list):\n                # Required for BERT Fine-tuning (to be covered later)\n                X = [x.to(device) for x in X]\n            else:\n                X = X.to(device)\n            y = y.to(device)\n            metric.add(d2l.accuracy(net(X), y), d2l.size(y))\n    return metric[0] / metric[1]\n\n",
        "url": "https://github.com/d2l-ai/d2l-en.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 212,
        "n_words": 72,
        "vocab_size": 58,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 141,
        "n_ast_nodes": 228,
        "n_identifiers": 24,
        "d_id": 74503,
        "documentation": {
            "docstring": "Compute the accuracy for a model on a dataset using a GPU.\n\n    Defined in :numref:`sec_utils`",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 243994,
        "commit_id": "1516986a616fee8bb741d0ab2be40683045efccd",
        "repo": "mmdetection",
        "path": "mmdet/datasets/openimages.py",
        "file_name": "openimages.py",
        "fun_name": "get_classes_from_csv",
        "commit_message": "[Feature] Support OpenImages Dataset (#6331)\n\n* [Feature] support openimage group of eval\r\n\r\n* [Feature] support openimage group of eval\r\n\r\n* support openimage dataset\r\n\r\n* support openimage challenge dataset\r\n\r\n* fully support OpenImages-V6 and OpenImages Challenge 2019\r\n\r\n* Fix some logic error\r\n\r\n* update config file\r\n\r\n* fix get data_infos error\r\n\r\n* fully support OpenImages evaluation\r\n\r\n* update OpenImages config files\r\n\r\n* [Feature] support OpenImages datasets\r\n\r\n* fix bug\r\n\r\n* support load image metas from pipeline\r\n\r\n* fix bug\r\n\r\n* fix get classes logic error\r\n\r\n* update code\r\n\r\n* support get image metas\r\n\r\n* support openimags\r\n\r\n* support collect image metas\r\n\r\n* support Open Images\r\n\r\n* fix openimages logic\r\n\r\n* minor fix\r\n\r\n* add a new function to compute openimages tpfp\r\n\r\n* minor fix\r\n\r\n* fix ci error\r\n\r\n* minor fix\r\n\r\n* fix indication\r\n\r\n* minor fix\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* minor fix\r\n\r\n* update readme\r\n\r\n* support loading image level labels and fix some logic\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add class names\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add openimages test unit\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* fix logic error\r\n\r\n* minor fix\r\n\r\n* fully support openimages\r\n\r\n* minor fix\r\n\r\n* fix docstring\r\n\r\n* fix docstrings in readthedocs\r\n\r\n* update get image metas script\r\n\r\n* label_description_file -> label_file\r\n\r\n* update openimages readme\r\n\r\n* fix test unit\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* update readme file\r\n\r\n* Update get_image_metas.py",
        "code": "def get_classes_from_csv(self, label_file):\n        \n\n        index_list = []\n        classes_names = []\n        with open(label_file, 'r') as f:\n            reader = csv.reader(f)\n            for line in reader:\n                self.cat2label[line[0]] = line[1]\n                classes_names.append(line[1])\n                index_list.append(line[0])\n        self.index_dict = {index: i for i, index in enumerate(index_list)}\n        return classes_names\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 146,
        "n_words": 37,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 91,
        "n_ast_nodes": 147,
        "n_identifiers": 16,
        "d_id": 70184,
        "documentation": {
            "docstring": "Get classes name from file.\n\n        Args:\n            label_file (str): File path of the label description file that\n                maps the classes names in MID format to their short\n                descriptions.\n\n        Returns:\n            list[str]: Class name of OpenImages.\n        ",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 206862,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/generic/dates.py",
        "file_name": "dates.py",
        "fun_name": "_get_dated_items",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get_dated_items(self, date):\n        \n        lookup_kwargs = self._make_single_date_lookup(date)\n        qs = self.get_dated_queryset(**lookup_kwargs)\n\n        return (\n            None,\n            qs,\n            {\n                \"day\": date,\n                \"previous_day\": self.get_previous_day(date),\n                \"next_day\": self.get_next_day(date),\n                \"previous_month\": self.get_previous_month(date),\n                \"next_month\": self.get_next_month(date),\n            },\n        )\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 180,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 75,
        "n_ast_nodes": 123,
        "n_identifiers": 11,
        "d_id": 51763,
        "documentation": {
            "docstring": "\n        Do the actual heavy lifting of getting the dated items; this accepts a\n        date object so that TodayArchiveView can be trivial.\n        ",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 177606,
        "commit_id": "1c4328c5a8b10ee20ac4328ce30612d106350699",
        "repo": "label-studio",
        "path": "label_studio/data_manager/actions/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "perform_action",
        "commit_message": "feat: DEV-1205: Add task.updated_at column (#1784)\n\n* Update task.updated_at on annotation update (DEV-1205)\r\n\r\n* Fix set updated_at on annotation delete (DEV-1205)\r\n\r\n* Set update_at for every dm action (DEV-1205)\r\n\r\n* Stop changing updated_at on actions (DEV-1205)\r\n\r\n* Update experimental.py\r\n\r\nCo-authored-by: Max Tkachenko <makseq@gmail.com>\r\nCo-authored-by: niklub <lubimov.nicolas@gmail.com>",
        "code": "def perform_action(action_id, project, queryset, user, **kwargs):\n    \n    if action_id not in settings.DATA_MANAGER_ACTIONS:\n        raise DataManagerException(\"Can't find '\" + action_id + \"' in registered actions\")\n\n    action = settings.DATA_MANAGER_ACTIONS[action_id]\n\n    # check user permissions for this action\n    if not check_permissions(user, action):\n        raise DRFPermissionDenied(f'Action is not allowed for the current user: {action[\"id\"]}')\n\n\n    try:\n        result = action['entry_point'](project, queryset, **kwargs)\n    except Exception as e:\n        text = 'Error while perform action: ' + action_id + '\\n' + tb.format_exc()\n        logger.error(text, extra={'sentry_skip': True})\n        raise e\n\n    return result\n\n\nregister_actions_from_dir('data_manager.actions', os.path.dirname(__file__))\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 143,
        "n_words": 78,
        "vocab_size": 60,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 107,
        "n_ast_nodes": 212,
        "n_identifiers": 26,
        "d_id": 42459,
        "documentation": {
            "docstring": " Perform action using entry point from actions\n    ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 127486,
        "commit_id": "5c500f6308dce526c50a5230029fb4909b492a35",
        "repo": "ray",
        "path": "python/ray/tune/tuner.py",
        "file_name": "tuner.py",
        "fun_name": "fit",
        "commit_message": "[docs/air] Fix up some minor docstrings (#28361)",
        "code": "def fit(self) -> ResultGrid:\n        \n\n        if not self._is_ray_client:\n            try:\n                return self._local_tuner.fit()\n            except Exception as e:\n                raise TuneError(\n                    f\"Tune run failed. \"\n                    f'Please use tuner = Tuner.restore(\"'\n                    f'{self._local_tuner.get_experiment_checkpoint_dir()}\") to resume.'\n                ) from e\n        else:\n            experiment_checkpoint_dir = ray.get(\n                self._remote_tuner.get_experiment_checkpoint_dir.remote()\n            )\n            try:\n                return ray.get(self._remote_tuner.fit.remote())\n            except Exception as e:\n                raise TuneError(\n                    f\"Tune run failed. \"\n                    f'Please use tuner = Tuner.restore(\"'\n                    f'{experiment_checkpoint_dir}\") to resume.'\n                ) from e\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 367,
        "n_words": 61,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 41,
        "token_counts": 93,
        "n_ast_nodes": 175,
        "n_identifiers": 14,
        "d_id": 28451,
        "documentation": {
            "docstring": "Executes hyperparameter tuning job as configured and returns result.\n\n        Failure handling:\n        For the kind of exception that happens during the execution of a trial,\n        one may inspect it together with stacktrace through the returned result grid.\n        See ``ResultGrid`` for reference. Each trial may fail up to a certain number.\n        This is configured by ``RunConfig.FailureConfig.max_failures``.\n\n        Exception that happens beyond trials will be thrown by this method as well.\n        In such cases, there will be instruction like the following printed out\n        at the end of console output to inform users on how to resume.\n\n        Please use tuner = Tuner.restore(\"~/ray_results/tuner_resume\")\n        to resume.\n\n        Raises:\n            RayTaskError: If user-provided trainable raises an exception\n            TuneError: General Ray Tune error.\n        ",
            "n_words": 112,
            "vocab_size": 92,
            "n_whitespaces": 218,
            "language": "en"
        }
    },
    {
        "id": 42640,
        "commit_id": "f352ee63a5d09546a7997ba8f2f8702a1ddb4af7",
        "repo": "airflow",
        "path": "tests/cli/commands/test_task_command.py",
        "file_name": "test_task_command.py",
        "fun_name": "test_task_states_for_dag_run_when_dag_run_not_exists",
        "commit_message": "Replaced all days_ago functions with datetime functions (#23237)\n\nCo-authored-by: Dev232001 <thedevhooda@gmail.com>",
        "code": "def test_task_states_for_dag_run_when_dag_run_not_exists(self):\n        \n        with pytest.raises(DagRunNotFound):\n            default_date2 = timezone.datetime(2016, 1, 9)\n            task_command.task_states_for_dag_run(\n                self.parser.parse_args(\n                    [\n                        'tasks',\n                        'states-for-dag-run',\n                        'not_exists_dag',\n                        default_date2.isoformat(),\n                        '--output',\n                        \"json\",\n                    ]\n                )\n            )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 274,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 56,
        "n_ast_nodes": 97,
        "n_identifiers": 13,
        "d_id": 7671,
        "documentation": {
            "docstring": "\n        task_states_for_dag_run should return an AirflowException when invalid dag id is passed\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 221242,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/calendar.py",
        "file_name": "calendar.py",
        "fun_name": "yeardatescalendar",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def yeardatescalendar(self, year, width=3):\n        \n        months = [\n            self.monthdatescalendar(year, i)\n            for i in range(January, January+12)\n        ]\n        return [months[i:i+width] for i in range(0, len(months), width) ]\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 74,
        "n_words": 24,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 60,
        "n_ast_nodes": 88,
        "n_identifiers": 10,
        "d_id": 56289,
        "documentation": {
            "docstring": "\n        Return the data for the specified year ready for formatting. The return\n        value is a list of month rows. Each month row contains up to width months.\n        Each month contains between 4 and 6 weeks and each week contains 1-7\n        days. Days are datetime.date objects.\n        ",
            "n_words": 45,
            "vocab_size": 37,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 7853,
        "commit_id": "c13bc2cf1443ce9339cde0eb5e0d2b568af341f7",
        "repo": "ludwig",
        "path": "ludwig/datasets/noshow_appointments/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "process_downloaded_dataset",
        "commit_message": "Add medical no-show appointments dataset (#2387)\n\nCo-authored-by: Daniel Treiman <dan.treiman@gmail.com>",
        "code": "def process_downloaded_dataset(self):\n        \n        df = pd.read_csv(os.path.join(self.raw_dataset_path, self.csv_filename))\n        df[SPLIT] = np.random.choice(3, len(df), p=(0.7, 0.1, 0.2)).astype(np.int8)\n\n        makedirs(self.processed_temp_path, exist_ok=True)\n        df.to_csv(os.path.join(self.processed_temp_path, self.csv_filename), index=False)\n        rename(self.processed_temp_path, self.processed_dataset_path)\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 62,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 111,
        "n_ast_nodes": 159,
        "n_identifiers": 25,
        "d_id": 1281,
        "documentation": {
            "docstring": "The final method where we create a concatenated CSV file with both training and test data.",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 288487,
        "commit_id": "dd1463da287f591652e47b00eee0c5b77f5f5b7c",
        "repo": "core",
        "path": "homeassistant/components/bayesian/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "template",
        "commit_message": "Refactor bayesian observations using dataclass (#79590)\n\n* refactor\r\n\r\n* remove some changes\r\n\r\n* remove typehint\r\n\r\n* improve codestyle\r\n\r\n* move docstring to comment\r\n\r\n* < 88 chars\r\n\r\n* avoid short var names\r\n\r\n* more readable\r\n\r\n* fix rename\r\n\r\n* Update homeassistant/components/bayesian/helpers.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* no intermediate\r\n\r\n* comment why set before list\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "def template(self) -> str | None:\n        \n        if self.value_template is not None:\n            return self.value_template.template\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 26,
        "n_ast_nodes": 43,
        "n_identifiers": 4,
        "d_id": 87644,
        "documentation": {
            "docstring": "Not all observations have templates and we want to get template strings.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 82225,
        "commit_id": "e403c603d68def3b4cc6e4b253092343d646da1a",
        "repo": "awx",
        "path": "awx/main/scheduler/task_manager_models.py",
        "file_name": "task_manager_models.py",
        "fun_name": "get_capacity",
        "commit_message": "use task manager models more consistently in serializer",
        "code": "def get_capacity(self):\n        \n        if self.is_container_group:\n            return self.max_forks\n        return self.get_instance_capacity()\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 40,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 17333,
        "documentation": {
            "docstring": "This reports any type of capacity, including that of container group jobs.\n\n        Container groups don't really have capacity, but if they have max_forks set,\n        we can interperet that as how much capacity the user has defined them to have.\n        ",
            "n_words": 39,
            "vocab_size": 35,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 132094,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/config_parser.py",
        "file_name": "config_parser.py",
        "fun_name": "create_trial_from_spec",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def create_trial_from_spec(spec, output_path, parser, **trial_kwargs):\n    \n    global _cached_pgf\n\n    spec = spec.copy()\n    resources = spec.pop(\"resources_per_trial\", None)\n\n    try:\n        args, _ = parser.parse_known_args(to_argv(spec))\n    except SystemExit:\n        raise TuneError(\"Error parsing args, see above message\", spec)\n\n    if resources:\n        if isinstance(resources, PlacementGroupFactory):\n            trial_kwargs[\"placement_group_factory\"] = resources\n        else:\n            # This will be converted to a placement group factory in the\n            # Trial object constructor\n            try:\n                trial_kwargs[\"resources\"] = json_to_resources(resources)\n            except (TuneError, ValueError) as exc:\n                raise TuneError(\"Error parsing resources_per_trial\", resources) from exc\n\n    remote_checkpoint_dir = spec.get(\"remote_checkpoint_dir\")\n\n    sync_config = spec.get(\"sync_config\", SyncConfig())\n    if sync_config.syncer is None or isinstance(sync_config.syncer, str):\n        sync_function_tpl = sync_config.syncer\n    elif not isinstance(sync_config.syncer, str):\n        # If a syncer was specified, but not a template, it is a function.\n        # Functions cannot be used for trial checkpointing on remote nodes,\n        # so we set the remote checkpoint dir to None to disable this.\n        sync_function_tpl = None\n        remote_checkpoint_dir = None\n    else:\n        sync_function_tpl = None  # Auto-detect\n\n    return Trial(\n        # Submitting trial via server in py2.7 creates Unicode, which does not\n        # convert to string in a straightforward manner.\n        trainable_name=spec[\"run\"],\n        # json.load leads to str -> unicode in py2.7\n        config=spec.get(\"config\", {}),\n        local_dir=os.path.join(spec[\"local_dir\"], output_path),\n        # json.load leads to str -> unicode in py2.7\n        stopping_criterion=spec.get(\"stop\", {}),\n        remote_checkpoint_dir=remote_checkpoint_dir,\n        sync_function_tpl=sync_function_tpl,\n        checkpoint_freq=args.checkpoint_freq,\n        checkpoint_at_end=args.checkpoint_at_end,\n        sync_on_checkpoint=sync_config.sync_on_checkpoint,\n        keep_checkpoints_num=args.keep_checkpoints_num,\n        checkpoint_score_attr=args.checkpoint_score_attr,\n        export_formats=spec.get(\"export_formats\", []),\n        # str(None) doesn't create None\n        restore_path=spec.get(\"restore\"),\n        trial_name_creator=spec.get(\"trial_name_creator\"),\n        trial_dirname_creator=spec.get(\"trial_dirname_creator\"),\n        log_to_file=spec.get(\"log_to_file\"),\n        # str(None) doesn't create None\n        max_failures=args.max_failures,\n        **trial_kwargs\n    )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 587,
        "n_words": 214,
        "vocab_size": 140,
        "complexity": 8,
        "nloc": 45,
        "token_counts": 313,
        "n_ast_nodes": 511,
        "n_identifiers": 46,
        "d_id": 29682,
        "documentation": {
            "docstring": "Creates a Trial object from parsing the spec.\n\n    Args:\n        spec (dict): A resolved experiment specification. Arguments should\n            The args here should correspond to the command line flags\n            in ray.tune.config_parser.\n        output_path (str); A specific output path within the local_dir.\n            Typically the name of the experiment.\n        parser (ArgumentParser): An argument parser object from\n            make_parser.\n        trial_kwargs: Extra keyword arguments used in instantiating the Trial.\n\n    Returns:\n        A trial object with corresponding parameters to the specification.\n    ",
            "n_words": 71,
            "vocab_size": 55,
            "n_whitespaces": 159,
            "language": "en"
        }
    },
    {
        "id": 258639,
        "commit_id": "604bc5c605b9587526794de2653624b19c6a8031",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/tests/test_bicluster.py",
        "file_name": "test_bicluster.py",
        "fun_name": "test_spectralbiclustering_parameter_validation",
        "commit_message": "MNT use check_scalar in SpectralBiClustering and SpectralCoClustering (#20817)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_spectralbiclustering_parameter_validation(params, type_err, err_msg):\n    \n    data = np.arange(25).reshape((5, 5))\n    model = SpectralBiclustering(**params)\n    with pytest.raises(type_err, match=err_msg):\n        model.fit(data)\n\n\n@pytest.mark.parametrize(\"est\", (SpectralBiclustering(), SpectralCoclustering()))",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"est\", (SpectralBiclustering(), SpectralCoclustering()))",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 36,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 52,
        "n_ast_nodes": 117,
        "n_identifiers": 17,
        "d_id": 75345,
        "documentation": {
            "docstring": "Check parameters validation in `SpectralBiClustering`",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 4,
            "language": "en"
        }
    },
    {
        "id": 41880,
        "commit_id": "563e96d3be1eaee8db8dfbccf7eed1f1c66dfd31",
        "repo": "seaborn",
        "path": "seaborn/_oldcore.py",
        "file_name": "_oldcore.py",
        "fun_name": "categorical_mapping",
        "commit_message": "Downgrade exception on mapping list length mismatch to warning (#2856)\n\n* Downgrade exception on mapping list length mismatch to warning\r\n\r\n* Lint\r\n\r\n* Fix pairplot test\r\n\r\n* Set stacklevel to report warning in user code",
        "code": "def categorical_mapping(self, data, palette, order):\n        \n        # -- Identify the order and name of the levels\n\n        levels = categorical_order(data, order)\n        n_colors = len(levels)\n\n        # -- Identify the set of colors to use\n\n        if isinstance(palette, dict):\n\n            missing = set(levels) - set(palette)\n            if any(missing):\n                err = \"The palette dictionary is missing keys: {}\"\n                raise ValueError(err.format(missing))\n\n            lookup_table = palette\n\n        else:\n\n            if palette is None:\n                if n_colors <= len(get_color_cycle()):\n                    colors = color_palette(None, n_colors)\n                else:\n                    colors = color_palette(\"husl\", n_colors)\n            elif isinstance(palette, list):\n                colors = self._check_list_length(levels, palette, \"palette\")\n            else:\n                colors = color_palette(palette, n_colors)\n\n            lookup_table = dict(zip(levels, colors))\n\n        return levels, lookup_table\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 354,
        "n_words": 93,
        "vocab_size": 57,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 147,
        "n_ast_nodes": 240,
        "n_identifiers": 24,
        "d_id": 7453,
        "documentation": {
            "docstring": "Determine colors when the hue mapping is categorical.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 44454,
        "commit_id": "3e9828022b03b60d9e112f1f64340a528c8407e3",
        "repo": "airflow",
        "path": "airflow/www/security.py",
        "file_name": "security.py",
        "fun_name": "has_all_dags_access",
        "commit_message": "Simplify fab has access lookup (#19294)\n\n* Use FAB models.\r\n\r\n* Remove incorrect conversions to new permission naming scheme.\r\n\r\n* Fix missing FAB renames.\r\n\r\n* Remove unused FAB compatibility fixes in models.py.\r\n\r\n* Set perms directly on user objects.\r\n\r\n* Set perms properties on User model.\r\n\r\n* Rename missed old naming scheme conversion.\r\n\r\n* Remove unused imports.\r\n\r\n* Remove unused imports.\r\n\r\n* Remeve get_user_roles() method.\r\n\r\n* Make permissions eagerload.\r\n\r\n* Remove unused imports.\r\n\r\n* Clarify query params.\r\n\r\n* Modify sort logic so MSSQL passes.\r\n\r\n* Add text modifier to order_by values.\r\n\r\n* Remove calls to get_*_dags.\r\n\r\n* Add back execution_date\r\n\r\n* Add back comma to match rest of file.\r\n\r\n* Remove unused permission functions.\r\n\r\n* Fix failing tests.\r\n\r\n* Pass user object to current_app.appbuilder.sm.has_all_dags_access.\r\n\r\n* Remove attempts to fix query.\r\n\r\n* Update the api_connexion query builders.\r\n\r\n* Add typing.\r\n\r\n* Apply sorts directly to model objects.\r\n\r\n* Apply sorts directly to model objects.\r\n\r\n* Standardize custom sort code.\r\n\r\n* Code review\r\n\r\n* Augment xcom docs (#20755)\r\n\r\n* Fix relationship join bug in FAB/SecurityManager with SQLA 1.4 (#21296)\r\n\r\nThis is fixed in SQLA 1.4.19, but the fix makes the intent clearer here\r\nanyway.\r\n\r\n* Docs: Fix task order in overview example (#21282)\r\n\r\n* Update stat_name_handler documentation (#21298)\r\n\r\nPreviously stat_name_handler was under the scheduler section of the\r\nconfiguration but it was moved to the metrics section since 2.0.0.\r\n\r\n* Update recipe for Google Cloud SDK (#21268)\r\n\r\n* Use FAB models.\r\n\r\n* Remove incorrect conversions to new permission naming scheme.\r\n\r\n* Fix missing FAB renames.\r\n\r\n* Remove unused FAB compatibility fixes in models.py.\r\n\r\n* Set perms directly on user objects.\r\n\r\n* Set perms properties on User model.\r\n\r\n* Rename missed old naming scheme conversion.\r\n\r\n* Remove unused imports.\r\n\r\n* Remove unused imports.\r\n\r\n* Remeve get_user_roles() method.\r\n\r\n* Make permissions eagerload.\r\n\r\n* Remove unused imports.\r\n\r\n* Clarify query params.\r\n\r\n* Modify sort logic so MSSQL passes.\r\n\r\n* Add text modifier to order_by values.\r\n\r\n* Remove calls to get_*_dags.\r\n\r\n* Add back execution_date\r\n\r\n* Add back comma to match rest of file.\r\n\r\n* Remove unused permission functions.\r\n\r\n* Fix failing tests.\r\n\r\n* Pass user object to current_app.appbuilder.sm.has_all_dags_access.\r\n\r\n* Remove attempts to fix query.\r\n\r\n* Update the api_connexion query builders.\r\n\r\n* Add typing.\r\n\r\n* Apply sorts directly to model objects.\r\n\r\n* Apply sorts directly to model objects.\r\n\r\n* Standardize custom sort code.\r\n\r\n* Make sure joined fields prefetch.\r\n\r\n* Dont use cached_property, since its only on > 3.8.\r\n\r\nCo-authored-by: Ash Berlin-Taylor <ash@apache.org>\r\nCo-authored-by: Lewis John McGibbney <lewis.mcgibbney@gmail.com>\r\nCo-authored-by: Ash Berlin-Taylor <ash_github@firemirror.com>\r\nCo-authored-by: Lucia Kasman <38845383+luciakasman@users.noreply.github.com>\r\nCo-authored-by: Fran Sánchez <fj-sanchez@users.noreply.github.com>\r\nCo-authored-by: Kamil Breguła <mik-laj@users.noreply.github.com>",
        "code": "def has_all_dags_access(self, user):\n        \n        if not user:\n            user = g.user\n        return (\n            self._has_role(['Admin', 'Viewer', 'Op', 'User'], user)\n            or self.has_access(permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG, user)\n            or self.has_access(permissions.ACTION_CAN_EDIT, permissions.RESOURCE_DAG, user)\n        )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 97,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 8,
        "token_counts": 66,
        "n_ast_nodes": 105,
        "n_identifiers": 10,
        "d_id": 8272,
        "documentation": {
            "docstring": "\n        Has all the dag access in any of the 3 cases:\n        1. Role needs to be in (Admin, Viewer, User, Op).\n        2. Has can_read action on dags resource.\n        3. Has can_edit action on dags resource.\n        ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 266665,
        "commit_id": "68fb3bf90efa3a722ba5ab7d66b1b22adc73198c",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_util/target/setup/requirements.py",
        "file_name": "requirements.py",
        "fun_name": "bootstrap",
        "commit_message": "ansible-test - Fix consistency of managed venvs. (#77028)",
        "code": "def bootstrap(pip, options):  # type: (str, t.Dict[str, t.Any]) -> None\n    \n    pip_version = options['pip_version']\n    packages = options['packages']\n\n    url = 'https://ci-files.testing.ansible.com/ansible-test/get-pip-%s.py' % pip_version\n    cache_path = os.path.expanduser('~/.ansible/test/cache/get_pip_%s.py' % pip_version.replace(\".\", \"_\"))\n    temp_path = cache_path + '.download'\n\n    if os.path.exists(cache_path):\n        log('Using cached pip %s bootstrap script: %s' % (pip_version, cache_path))\n    else:\n        log('Downloading pip %s bootstrap script: %s' % (pip_version, url))\n\n        make_dirs(os.path.dirname(cache_path))\n        download_file(url, temp_path)\n        shutil.move(temp_path, cache_path)\n\n        log('Cached pip %s bootstrap script: %s' % (pip_version, cache_path))\n\n    env = common_pip_environment()\n    env.update(GET_PIP=cache_path)\n\n    options = common_pip_options()\n    options.extend(packages)\n\n    command = [sys.executable, pip] + options\n\n    execute_command(command, env=env)\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 169,
        "n_words": 84,
        "vocab_size": 56,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 159,
        "n_ast_nodes": 272,
        "n_identifiers": 29,
        "d_id": 78507,
        "documentation": {
            "docstring": "Bootstrap pip and related packages in an empty virtual environment.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 45314,
        "commit_id": "27d19e7626ef80687997a6799762fa00162c1328",
        "repo": "airflow",
        "path": "airflow/providers/databricks/operators/databricks_sql.py",
        "file_name": "databricks_sql.py",
        "fun_name": "_create_sql_query",
        "commit_message": "Databricks SQL operators (#21363)",
        "code": "def _create_sql_query(self) -> str:\n        escaper = ParamEscaper()\n        location = escaper.escape_item(self._file_location)\n        if self._expression_list is not None:\n            location = f\"(SELECT {self._expression_list} FROM {location})\"\n        files_or_pattern = \"\"\n        if self._pattern is not None:\n            files_or_pattern = f\"PATTERN = {escaper.escape_item(self._pattern)}\\n\"\n        elif self._files is not None:\n            files_or_pattern = f\"FILES = {escaper.escape_item(self._files)}\\n\"\n        format_options = self._generate_options(\"FORMAT_OPTIONS\", escaper, self._format_options)\n        copy_options = self._generate_options(\"COPY_OPTIONS\", escaper, self._copy_options)\n        # TODO: think on how to make sure that table_name and expression_list aren't used for SQL injection\n        sql = f\n        return sql.strip()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 185,
        "n_words": 76,
        "vocab_size": 55,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 99,
        "n_ast_nodes": 236,
        "n_identifiers": 21,
        "d_id": 8546,
        "documentation": {
            "docstring": "COPY INTO {self._table_name}\nFROM {location}\nFILEFORMAT = {self._file_format}\n{files_or_pattern}{format_options}{copy_options}\n",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 5,
            "language": "en"
        }
    },
    {
        "id": 163191,
        "commit_id": "521259299f7829da667ba39302ec77acedde9e5e",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "map",
        "commit_message": "DOC: Improve doc summaries in series.rst (#45237)",
        "code": "def map(self, mapper, na_action=None):\n        \n        from pandas.core.indexes.multi import MultiIndex\n\n        new_values = self._map_values(mapper, na_action=na_action)\n\n        # we can return a MultiIndex\n        if new_values.size and isinstance(new_values[0], tuple):\n            if isinstance(self, MultiIndex):\n                names = self.names\n            elif self.name:\n                names = [self.name] * len(new_values[0])\n            else:\n                names = None\n            return MultiIndex.from_tuples(new_values, names=names)\n\n        dtype = None\n        if not new_values.size:\n            # empty\n            dtype = self.dtype\n\n        # e.g. if we are floating and new_values is all ints, then we\n        #  don't want to cast back to floating.  But if we are UInt64\n        #  and new_values is all ints, we want to try.\n        same_dtype = lib.infer_dtype(new_values, skipna=False) == self.inferred_type\n        if same_dtype:\n            new_values = maybe_cast_pointwise_result(\n                new_values, self.dtype, same_dtype=same_dtype\n            )\n\n        if self._is_backward_compat_public_numeric_index and is_numeric_dtype(\n            new_values.dtype\n        ):\n            return self._constructor(\n                new_values, dtype=dtype, copy=False, name=self.name\n            )\n\n        return Index._with_infer(new_values, dtype=dtype, copy=False, name=self.name)\n\n    # TODO: De-duplicate with map, xref GH#32349",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 437,
        "n_words": 130,
        "vocab_size": 83,
        "complexity": 9,
        "nloc": 26,
        "token_counts": 199,
        "n_ast_nodes": 304,
        "n_identifiers": 31,
        "d_id": 39399,
        "documentation": {
            "docstring": "\n        Map values using an input mapping or function.\n\n        Parameters\n        ----------\n        mapper : function, dict, or Series\n            Mapping correspondence.\n        na_action : {None, 'ignore'}\n            If 'ignore', propagate NA values, without passing them to the\n            mapping correspondence.\n\n        Returns\n        -------\n        applied : Union[Index, MultiIndex], inferred\n            The output of the mapping function applied to the index.\n            If the function returns a tuple with more than one element\n            a MultiIndex will be returned.\n        ",
            "n_words": 67,
            "vocab_size": 53,
            "n_whitespaces": 197,
            "language": "en"
        }
    },
    {
        "id": 101076,
        "commit_id": "2ea05623bd684b2d1dd75679ad00441a5c751e7e",
        "repo": "faceswap",
        "path": "scripts/train.py",
        "file_name": "train.py",
        "fun_name": "_handle_deprecations",
        "commit_message": "Update Distibution Strategies:\n  - Add Central Storage Stategy\n  - Deprecate 'distributed' cli argument",
        "code": "def _handle_deprecations(self) -> None:\n        \n        if self._args.distributed:\n            deprecation_warning(\"`-d`, `--distributed`\",\n                                \"Please use `-D`, `--distribution-strategy`\")\n            logger.warning(\"Setting 'distribution-strategy' to 'mirrored'\")\n            setattr(self._args, \"distribution_strategy\", \"mirrored\")\n            del self._args.distributed\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 110,
        "n_words": 21,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 43,
        "n_ast_nodes": 79,
        "n_identifiers": 8,
        "d_id": 20513,
        "documentation": {
            "docstring": " Handle the update of deprecated arguments and output warnings. ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 268905,
        "commit_id": "b96518a22bfd92a29811e507dec0b34248a8a3f5",
        "repo": "keras",
        "path": "keras/engine/correctness_test.py",
        "file_name": "correctness_test.py",
        "fun_name": "multi_input_functional",
        "commit_message": "- Consolidate disparate test-related files into a single testing_infra folder.\n- Cleanup TODO related to removing testing infra as a dependency of the Keras target.\n- Standardize import naming: there is now only \"test_combinations\" for test combinations, and \"test_utils\" for utilities. The TF utilities module \"test_util\" is now always imported as \"tf_test_utils\" to avoid confusion.\n\nPiperOrigin-RevId: 426773173",
        "code": "def multi_input_functional():\n  \n  input_1 = keras.Input(shape=(1,))\n  input_2 = keras.Input(shape=(1,))\n  input_3 = keras.Input(shape=(1,))\n  added = keras.layers.Add()([input_1, input_2, input_3])\n  output = test_utils.Bias()(added)\n  return keras.Model([input_1, input_2, input_3], output)\n\n\n@test_combinations.run_with_all_model_types\n@test_combinations.run_all_keras_modes",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@test_combinations.run_with_all_model_types\n@test_combinations.run_all_keras_modes",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 31,
        "n_words": 26,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 87,
        "n_ast_nodes": 149,
        "n_identifiers": 17,
        "d_id": 79765,
        "documentation": {
            "docstring": "Functional Model that adds its inputs and then adds a bias.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 264753,
        "commit_id": "4bb9b6ee2639db683b70d6ddbee055497e0a3647",
        "repo": "netbox",
        "path": "netbox/dcim/signals.py",
        "file_name": "signals.py",
        "fun_name": "nullify_connected_endpoints",
        "commit_message": "Extend Cable model to support multiple A/B terminations",
        "code": "def nullify_connected_endpoints(instance, **kwargs):\n    \n    logger = logging.getLogger('netbox.dcim.cable')\n\n    # Disassociate the Cable from its termination points\n    if instance.termination_a:\n        logger.debug(f\"Nullifying termination A for cable {instance}\")\n        model = instance.termination_a_type.model_class()\n        model.objects.filter(pk__in=instance.termination_a_ids).update(_link_peer_type=None, _link_peer_id=None)\n    if instance.termination_b:\n        logger.debug(f\"Nullifying termination B for cable {instance}\")\n        model = instance.termination_b_type.model_class()\n        model.objects.filter(pk__in=instance.termination_b_ids).update(_link_peer_type=None, _link_peer_id=None)\n\n    # Delete and retrace any dependent cable paths\n    for cablepath in CablePath.objects.filter(path__contains=instance):\n        cp = CablePath.from_origin(cablepath.origin)\n        if cp:\n            CablePath.objects.filter(pk=cablepath.pk).update(\n                path=cp.path,\n                destination_type=ContentType.objects.get_for_model(cp.destination) if cp.destination else None,\n                destination_id=cp.destination.pk if cp.destination else None,\n                is_active=cp.is_active,\n                is_split=cp.is_split\n            )\n        else:\n            cablepath.delete()\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 266,
        "n_words": 74,
        "vocab_size": 53,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 205,
        "n_ast_nodes": 332,
        "n_identifiers": 37,
        "d_id": 77796,
        "documentation": {
            "docstring": "\n    When a Cable is deleted, check for and update its two connected endpoints\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 298235,
        "commit_id": "df2d0cd3e3ade2339a18415f92c85810308a9926",
        "repo": "core",
        "path": "homeassistant/components/mysensors/device_tracker.py",
        "file_name": "device_tracker.py",
        "fun_name": "_async_update",
        "commit_message": "Refactor mysensors device tracker (#84747)",
        "code": "def _async_update(self) -> None:\n        \n        super()._async_update()\n        node = self.gateway.sensors[self.node_id]\n        child = node.children[self.child_id]\n        position: str = child.values[self.value_type]\n        latitude, longitude, _ = position.split(\",\")\n        self._latitude = float(latitude)\n        self._longitude = float(longitude)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 82,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 77,
        "n_ast_nodes": 126,
        "n_identifiers": 21,
        "d_id": 97180,
        "documentation": {
            "docstring": "Update the controller with the latest value from a device.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 269284,
        "commit_id": "2d1086447a25d281f9428832d046c473d80ad761",
        "repo": "keras",
        "path": "keras/applications/convnext.py",
        "file_name": "convnext.py",
        "fun_name": "preprocess_input",
        "commit_message": "Corrected preprocess_input docstring in regnet.py and convnext.py",
        "code": "def preprocess_input(x, data_format=None):  # pylint: disable=unused-argument\n    \n    return x\n\n\n@keras_export(\"keras.applications.convnext.decode_predictions\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.applications.convnext.decode_predictions\")",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 15,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 33,
        "n_identifiers": 4,
        "d_id": 80001,
        "documentation": {
            "docstring": "A placeholder method for backward compatibility.\n\n  The preprocessing logic has been included in the convnext model\n  implementation. Users are no longer required to call this method to normalize\n  the input data. This method does nothing and only kept as a placeholder to\n  align the API surface between old and new version of model.\n\n  Args:\n    x: A floating point `numpy.array` or a `tf.Tensor`.\n    data_format: Optional data format of the image tensor/array. Defaults to\n      None, in which case the global setting\n      `tf.keras.backend.image_data_format()` is used (unless you changed it, it\n      defaults to \"channels_last\").{mode}\n\n  Returns:\n    Unchanged `numpy.array` or `tf.Tensor`.\n  ",
            "n_words": 95,
            "vocab_size": 76,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 69105,
        "commit_id": "9baa2229761c5415f29646a1a5bed4a3f4981e05",
        "repo": "erpnext",
        "path": "erpnext/controllers/queries.py",
        "file_name": "queries.py",
        "fun_name": "get_delivery_notes_to_be_billed",
        "commit_message": "fix: specify allowed doctype in queries (#31761)",
        "code": "def get_delivery_notes_to_be_billed(doctype, txt, searchfield, start, page_len, filters, as_dict):\n\tdoctype = \"Delivery Note\"\n\tfields = get_fields(doctype, [\"name\", \"customer\", \"posting_date\"])\n\n\treturn frappe.db.sql(\n\t\t\n\t\t% {\n\t\t\t\"fields\": \", \".join([\"`tabDelivery Note`.{0}\".format(f) for f in fields]),\n\t\t\t\"key\": searchfield,\n\t\t\t\"fcond\": get_filters_cond(doctype, filters, []),\n\t\t\t\"mcond\": get_match_cond(doctype),\n\t\t\t\"start\": start,\n\t\t\t\"page_len\": page_len,\n\t\t\t\"txt\": \"%(txt)s\",\n\t\t},\n\t\t{\"txt\": (\"%%%s%%\" % txt)},\n\t\tas_dict=as_dict,\n\t)\n\n\n@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 35,
        "n_words": 53,
        "vocab_size": 47,
        "complexity": 2,
        "nloc": 32,
        "token_counts": 116,
        "n_ast_nodes": 210,
        "n_identifiers": 20,
        "d_id": 14974,
        "documentation": {
            "docstring": "\n\t\tselect %(fields)s\n\t\tfrom `tabDelivery Note`\n\t\twhere `tabDelivery Note`.`%(key)s` like %(txt)s and\n\t\t\t`tabDelivery Note`.docstatus = 1\n\t\t\tand status not in ('Stopped', 'Closed') %(fcond)s\n\t\t\tand (\n\t\t\t\t(`tabDelivery Note`.is_return = 0 and `tabDelivery Note`.per_billed < 100)\n\t\t\t\tor (`tabDelivery Note`.grand_total = 0 and `tabDelivery Note`.per_billed < 100)\n\t\t\t\tor (\n\t\t\t\t\t`tabDelivery Note`.is_return = 1\n\t\t\t\t\tand return_against in (select name from `tabDelivery Note` where per_billed < 100)\n\t\t\t\t)\n\t\t\t)\n\t\t\t%(mcond)s order by `tabDelivery Note`.`%(key)s` asc limit %(page_len)s offset %(start)s\n\t",
            "n_words": 73,
            "vocab_size": 41,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 272394,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/layers/attention/multi_head_attention.py",
        "file_name": "multi_head_attention.py",
        "fun_name": "_build_attention_equation",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _build_attention_equation(rank, attn_axes):\n    \n    target_notation = _CHR_IDX[:rank]\n    # `batch_dims` includes the head dim.\n    batch_dims = tuple(np.delete(range(rank), attn_axes + (rank - 1,)))\n    letter_offset = rank\n    source_notation = \"\"\n    for i in range(rank):\n        if i in batch_dims or i == rank - 1:\n            source_notation += target_notation[i]\n        else:\n            source_notation += _CHR_IDX[letter_offset]\n            letter_offset += 1\n\n    product_notation = \"\".join(\n        [target_notation[i] for i in batch_dims]\n        + [target_notation[i] for i in attn_axes]\n        + [source_notation[i] for i in attn_axes]\n    )\n    dot_product_equation = \"%s,%s->%s\" % (\n        source_notation,\n        target_notation,\n        product_notation,\n    )\n    attn_scores_rank = len(product_notation)\n    combine_equation = \"%s,%s->%s\" % (\n        product_notation,\n        source_notation,\n        target_notation,\n    )\n    return dot_product_equation, combine_equation, attn_scores_rank\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 251,
        "n_words": 96,
        "vocab_size": 56,
        "complexity": 7,
        "nloc": 28,
        "token_counts": 155,
        "n_ast_nodes": 241,
        "n_identifiers": 19,
        "d_id": 81007,
        "documentation": {
            "docstring": "Builds einsum equations for the attention computation.\n\n    Query, key, value inputs after projection are expected to have the shape as:\n    `(bs, <non-attention dims>, <attention dims>, num_heads, channels)`.\n    `bs` and `<non-attention dims>` are treated as `<batch dims>`.\n\n    The attention operations can be generalized:\n    (1) Query-key dot product:\n    `(<batch dims>, <query attention dims>, num_heads, channels), (<batch dims>,\n    <key attention dims>, num_heads, channels) -> (<batch dims>,\n    num_heads, <query attention dims>, <key attention dims>)`\n    (2) Combination:\n    `(<batch dims>, num_heads, <query attention dims>, <key attention dims>),\n    (<batch dims>, <value attention dims>, num_heads, channels) -> (<batch dims>,\n    <query attention dims>, num_heads, channels)`\n\n    Args:\n      rank: Rank of query, key, value tensors.\n      attn_axes: List/tuple of axes, `[-1, rank)`,\n        that attention will be applied to.\n\n    Returns:\n      Einsum equations.\n    ",
            "n_words": 119,
            "vocab_size": 73,
            "n_whitespaces": 186,
            "language": "en"
        }
    },
    {
        "id": 211275,
        "commit_id": "0f75cb6c640203bc5c2670f6cbd9ac89ad53ecf4",
        "repo": "PaddleDetection",
        "path": "deploy/python/utils.py",
        "file_name": "utils.py",
        "fun_name": "nms",
        "commit_message": "[smalldet] add SAHI slice train eval infer deploy (#6465)\n\n* add slice infer for smalldet\r\n\r\n* add slice infer for smalldet\r\n\r\n* fix slice infer\r\n\r\n* fix doc, test=document_fix\r\n\r\n* fix eval and configs\r\n\r\n* add slice dataset loader\r\n\r\n* fix deploy\r\n\r\n* fix docs, test=document_fix\r\n\r\n* update docs, test=document_fix",
        "code": "def nms(dets, match_threshold=0.6, match_metric='iou'):\n    \n    if dets.shape[0] == 0:\n        return dets[[], :]\n    scores = dets[:, 0]\n    x1 = dets[:, 1]\n    y1 = dets[:, 2]\n    x2 = dets[:, 3]\n    y2 = dets[:, 4]\n    areas = (x2 - x1 + 1) * (y2 - y1 + 1)\n    order = scores.argsort()[::-1]\n\n    ndets = dets.shape[0]\n    suppressed = np.zeros((ndets), dtype=np.int)\n\n    for _i in range(ndets):\n        i = order[_i]\n        if suppressed[i] == 1:\n            continue\n        ix1 = x1[i]\n        iy1 = y1[i]\n        ix2 = x2[i]\n        iy2 = y2[i]\n        iarea = areas[i]\n        for _j in range(_i + 1, ndets):\n            j = order[_j]\n            if suppressed[j] == 1:\n                continue\n            xx1 = max(ix1, x1[j])\n            yy1 = max(iy1, y1[j])\n            xx2 = min(ix2, x2[j])\n            yy2 = min(iy2, y2[j])\n            w = max(0.0, xx2 - xx1 + 1)\n            h = max(0.0, yy2 - yy1 + 1)\n            inter = w * h\n            if match_metric == 'iou':\n                union = iarea + areas[j] - inter\n                match_value = inter / union\n            elif match_metric == 'ios':\n                smaller = min(iarea, areas[j])\n                match_value = inter / smaller\n            else:\n                raise ValueError()\n            if match_value >= match_threshold:\n                suppressed[j] = 1\n    keep = np.where(suppressed == 0)[0]\n    dets = dets[keep, :]\n    return dets\n",
        "url": "https://github.com/PaddlePaddle/PaddleDetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 550,
        "n_words": 183,
        "vocab_size": 100,
        "complexity": 9,
        "nloc": 45,
        "token_counts": 365,
        "n_ast_nodes": 553,
        "n_identifiers": 44,
        "d_id": 53054,
        "documentation": {
            "docstring": " Apply NMS to avoid detecting too many overlapping bounding boxes.\n        Args:\n            dets: shape [N, 5], [score, x1, y1, x2, y2]\n            match_metric: 'iou' or 'ios'\n            match_threshold: overlap thresh for match metric.\n    ",
            "n_words": 30,
            "vocab_size": 30,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 289374,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/components/history/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_fetch_period_api_with_minimal_response",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "async def test_fetch_period_api_with_minimal_response(recorder_mock, hass, hass_client):\n    \n    now = dt_util.utcnow()\n    await async_setup_component(hass, \"history\", {})\n\n    hass.states.async_set(\"sensor.power\", 0, {\"attr\": \"any\"})\n    await async_wait_recording_done(hass)\n    hass.states.async_set(\"sensor.power\", 50, {\"attr\": \"any\"})\n    await async_wait_recording_done(hass)\n    hass.states.async_set(\"sensor.power\", 23, {\"attr\": \"any\"})\n    last_changed = hass.states.get(\"sensor.power\").last_changed\n    await async_wait_recording_done(hass)\n    hass.states.async_set(\"sensor.power\", 23, {\"attr\": \"any\"})\n    await async_wait_recording_done(hass)\n    client = await hass_client()\n    response = await client.get(\n        f\"/api/history/period/{now.isoformat()}?filter_entity_id=sensor.power&minimal_response&no_attributes\"\n    )\n    assert response.status == HTTPStatus.OK\n    response_json = await response.json()\n    assert len(response_json[0]) == 3\n    state_list = response_json[0]\n\n    assert state_list[0][\"entity_id\"] == \"sensor.power\"\n    assert state_list[0][\"attributes\"] == {}\n    assert state_list[0][\"state\"] == \"0\"\n\n    assert \"attributes\" not in state_list[1]\n    assert \"entity_id\" not in state_list[1]\n    assert state_list[1][\"state\"] == \"50\"\n\n    assert \"attributes\" not in state_list[2]\n    assert \"entity_id\" not in state_list[2]\n    assert state_list[2][\"state\"] == \"23\"\n    assert state_list[2][\"last_changed\"] == json.dumps(\n        process_timestamp(last_changed),\n        cls=JSONEncoder,\n    ).replace('\"', \"\")\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "complexity": 1,
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        "token_counts": 284,
        "n_ast_nodes": 500,
        "n_identifiers": 28,
        "d_id": 88516,
        "documentation": {
            "docstring": "Test the fetch period view for history with minimal_response.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 204670,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/management/commands/migrate.py",
        "file_name": "migrate.py",
        "fun_name": "describe_operation",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def describe_operation(operation, backwards):\n        \n        prefix = \"\"\n        is_error = False\n        if hasattr(operation, \"code\"):\n            code = operation.reverse_code if backwards else operation.code\n            action = (code.__doc__ or \"\") if code else None\n        elif hasattr(operation, \"sql\"):\n            action = operation.reverse_sql if backwards else operation.sql\n        else:\n            action = \"\"\n            if backwards:\n                prefix = \"Undo \"\n        if action is not None:\n            action = str(action).replace(\"\\n\", \"\")\n        elif backwards:\n            action = \"IRREVERSIBLE\"\n            is_error = True\n        if action:\n            action = \" -> \" + action\n        truncated = Truncator(action)\n        return prefix + operation.describe() + truncated.chars(40), is_error\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "n_identifiers": 18,
        "d_id": 50839,
        "documentation": {
            "docstring": "Return a string that describes a migration operation for --plan.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 282485,
        "commit_id": "e1b6022b9cf156ffc0697d0d25a5ed2772ea8d68",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/cryptocurrency/due_diligence/binance_model.py",
        "file_name": "binance_model.py",
        "fun_name": "get_binance_available_quotes_for_each_coin",
        "commit_message": "Global plot styles (#1228)\n\n* Add default stylesheets\r\n\r\n* Add terminal style helper class and global style initialization in cfg\r\n\r\n* Style comments and docstrings\r\n\r\n* Load rich terminal theme from config file\r\n\r\n* Add application chart styles to candle charts\r\n\r\n* Add todos\r\n\r\n* Remove explicit color setting for some ta charts\r\n\r\n* Add user styles folder to gitignore\r\n\r\n* Update default stylesheets\r\n\r\n* Add matplotlib font manager support\r\n\r\n* Add matplotlib font manager support\r\n\r\n* Update docstrings and default style\r\n\r\n* Update stocks candle chart formatting (return fig to style title)\r\n\r\n* Style common ta overlap view\r\n\r\n* Make up and down market colors a part of the style helper\r\n\r\n* Update stylesheets\r\n\r\n* Style common ta volume view\r\n\r\n* Style common ta momentum view\r\n\r\n* Style common ta trend indicators view\r\n\r\n* Style common ta volatility view\r\n\r\n* Style common ta volume view\r\n\r\n* Style common ta custom indicators view\r\n\r\n* Fix styling bugs and remove the obvious time x lablel\r\n\r\n* Style charts in the covid menu\r\n\r\n* Set legend position to upper left in the mpl stylesheet\r\n\r\n* Add mpl_rcparams configs for parameters not covered by stylesheets\r\n\r\n* Remove font configuration files\r\n\r\n* Update style class utility functions\r\n\r\n* Implement passing external axes and style utility usage in ema & stoch\r\n\r\n* Add theme watermark and output helpers\r\n\r\n* Rename style to theme\r\n\r\n* Update helper usage in ta/ma and ta/stoch\r\n\r\n* Update style to theme in sample menus\r\n\r\n* Style forex (#1305)\r\n\r\n* Make tight layout optional 'cause mplfinance doesn't support it\r\n\r\n* Apply global style to the forex menu\r\n\r\n* Update code layout in oanda view and black\r\n\r\n* Style common TA (#1315)\r\n\r\n* Make tight layout optional 'cause mplfinance doesn't support it\r\n\r\n* Apply global style to the forex menu\r\n\r\n* Add linewidth to theme for use in mpf's addplots\r\n\r\n* Add vwap to the stocks notebook api\r\n\r\n* Update common/ta overlap to follow charting style\r\n\r\n* Apply style on TerminalStyle init\r\n\r\n* Enable infrastructure for excluding non-trading days from plots\r\n\r\n* Update notebook api to include there and resolve bandit warning\r\n\r\n* Update ta/common/overlap to exclude non-trading days\r\n\r\n* Enable external ax, style and non-trading days in common/ta/momentum\r\n\r\n* Enable external ax, style and non-trading days in common/ta/trend\r\n\r\n* Update vwap to the argument naming convention\r\n\r\n* Enable external ax, style and non-trading days in common/ta/volatility\r\n\r\n* Enable external ax, style and non-trading days in common/ta/volume\r\n\r\n* Enable external ax, style and non-trading days in common/ta/custom\r\n\r\n* Fix controller tests\r\n\r\n* Forgot to disable rewriting of the cassettes ...\r\n\r\n* Fix controller errors that came up because a merge conflict\r\n\r\n* Fix price label position on fib\r\n\r\n* Fix line having wrong x values in fib\r\n\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\n\r\n* Style economy (#1308)\r\n\r\n* Began converting\r\n\r\n* Added alphavan_view\r\n\r\n* Added CNN View\r\n\r\n* Updated nasdaq view, fixed glitch\r\n\r\n* Added fred\r\n\r\n* Refactored URL\r\n\r\n* Theo's requested changes\r\n\r\n* Updated docstrings\r\n\r\n* Updated tests\r\n\r\n* Fixed pylint\r\n\r\n* Fixed tests\r\n\r\n* Theo changes\r\n\r\n* Econ Fix\r\n\r\n* Refactor chart style for Crypto context (#1306)\r\n\r\n* Remove mock for gff\r\n\r\n* Mock visualize_output helper function\r\n\r\n* Refactor\r\n\r\n* Fix plot helper\r\n\r\n* Update legend loc\r\n\r\n* Refactor mplfinance candle plot\r\n\r\n* Fix errors in the helper function\r\n\r\n* Fix binbook having the wrong call_ function name\r\n\r\n* Remove hardcoded style params\r\n\r\n* Resolve kwargs future warning from pandas\r\n\r\n* Remove warnings import\r\n\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\n\r\n* funds + custom (#1311)\r\n\r\n* funds + custom\r\n\r\n* cleanup cleanup everybody everywhere\r\n\r\n* Fix external axes conditional and a typo\r\n\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\n\r\n* Add external axes mode to covid charts (#1328)\r\n\r\n* Add portfolio menu plots (#1318)\r\n\r\n* Portfolio view plots (commenting out report stuff)\r\n\r\n* PA Menu broken.  Commenting out and fix tests\r\n\r\n* portfolio optimization\r\n\r\n* comment out commented api line\r\n\r\n* Add notes on disabling the pa submenu\r\n\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\n\r\n* Plot updates in common BA (#1335)\r\n\r\n* Add external axes support to common/ba/finbrain\r\n\r\n* Add external axes support to common/ba/twitter\r\n\r\n* Add external axes support to common/ba/google\r\n\r\n* Add external axes support to common/ba/sentimentinvestor\r\n\r\n* Add sentimentinvestor to the notebooks API\r\n\r\n* Fix tests\r\n\r\n* Etf refactor (#1323)\r\n\r\n* Refactored no ETF\r\n\r\n* Fixed gtff import\r\n\r\n* Fixed tests\r\n\r\n* Fix pie chart style\r\n\r\n* Refactored etf/candle\r\n\r\n* Added pylint fix\r\n\r\n* Fixed tests\r\n\r\n* Update candle chart layout\r\n\r\n* Update etf controller test\r\n\r\n* Remove strange binary file\r\n\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\n\r\n* Expose ETF candle function in the notebooks API\r\n\r\n* Common BA and Common QA charts update (#1342)\r\n\r\n* Add external axes support to common/ba/finbrain\r\n\r\n* Add external axes support to common/ba/twitter\r\n\r\n* Add external axes support to common/ba/google\r\n\r\n* Add external axes support to common/ba/sentimentinvestor\r\n\r\n* Add sentimentinvestor to the notebooks API\r\n\r\n* Fix tests\r\n\r\n* Update stylesheet files\r\n\r\n* Refactor charts for common/qa\r\n\r\n* Update the forgotten line plot\r\n\r\n* Update tests\r\n\r\n* Add missing arg to a docstring\r\n\r\n* Remove scientific notation\r\n\r\n* Black imports\r\n\r\nCo-authored-by: Minh Hoang <nminh.hoang1023@gmail.com>\r\n\r\n* Options refactor (#1324)\r\n\r\n* Fixed alphaquery_view\r\n\r\n* finished options\r\n\r\n* Fixed pylint\r\n\r\n* Fixed tests\r\n\r\n* Fixed tests\r\n\r\n* Fixed tests\r\n\r\n* update yfinance\r\n\r\n* Tradier + Chartexchange\r\n\r\n* change mocks from gtff to theme.visualize output\r\n\r\n* tests\r\n\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\nCo-authored-by: james <jmaslek11@gmail.com>\r\n\r\n* Refactor Stocks menu (#1325)\r\n\r\n* Fix backtesting menu\r\n\r\n* Refactor comparison analysis\r\n\r\n* Refactor Dark pool shorts\r\n\r\n* Refactor rest of menu\r\n\r\n* Fix test\r\n\r\n* Fix tests failing\r\n\r\n* Fix tests fail\r\n\r\n* Fix test failing\r\n\r\n* Remove record mode=none to record new output\r\n\r\n* Rewrite test output\r\n\r\n* Rewrite test outputs\r\n\r\n* Adding more rewritten test output\r\n\r\n* Mock plt.show\r\n\r\n* Mock missing plt.show\r\n\r\n* Missing @pytest.mark.vcr\r\n\r\n* Updating tests : common/behavioural_analysis/finbrain\r\n\r\n* Improve notebooks API coverage for CA and DPS\r\n\r\n* Silence annoying flake8 warning\r\n\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\n\r\n* Charts update for common/pred (#1344)\r\n\r\n* Add external axes support to common/ba/finbrain\r\n\r\n* Add external axes support to common/ba/twitter\r\n\r\n* Add external axes support to common/ba/google\r\n\r\n* Add external axes support to common/ba/sentimentinvestor\r\n\r\n* Add sentimentinvestor to the notebooks API\r\n\r\n* Fix tests\r\n\r\n* Update stylesheet files\r\n\r\n* Refactor charts for common/qa\r\n\r\n* Update the forgotten line plot\r\n\r\n* Update tests\r\n\r\n* Add missing arg to a docstring\r\n\r\n* Style pred helper and controllers\r\n\r\n* Update ETS plot\r\n\r\n* Update plots in KNN and pred helper\r\n\r\n* Update plot and pretty table for arima\r\n\r\n* Update plot for common/pred/regression\r\n\r\n* Refactor mc_view\r\n\r\n* Fix linting\r\n\r\n* Fix mypy\r\n\r\n* Move plot title to the axis level to make more vertical space\r\n\r\nCo-authored-by: Minh Hoang <nminh.hoang1023@gmail.com>\r\nCo-authored-by: jmaslek <jmaslek11@gmail.com>\r\n\r\n* linter\r\n\r\n* Update common/ba test data\r\n\r\n* Change etf candle to match stock candle\r\n\r\n* try updating sia test\r\n\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: jmaslek <jmaslek11@gmail.com>\r\nCo-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com>\r\nCo-authored-by: Minh Hoang <nminh.hoang1023@gmail.com>\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>",
        "code": "def get_binance_available_quotes_for_each_coin() -> dict:\n    \n    trading_pairs = _get_trading_pairs()\n    results = defaultdict(list)\n    for pair in trading_pairs:\n        results[pair[\"baseAsset\"]].append(pair[\"quoteAsset\"])\n    return results\n\n\n@log_start_end(log=logger)",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "@log_start_end(log=logger)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 39,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 40,
        "n_ast_nodes": 82,
        "n_identifiers": 12,
        "d_id": 84165,
        "documentation": {
            "docstring": "Helper methods that for every coin available on Binance add all quote assets. [Source: Binance]\n\n    Returns\n    -------\n    dict:\n        All quote assets for given coin\n        {'ETH' : ['BTC', 'USDT' ...], 'UNI' : ['ETH', 'BTC','BUSD', ...]\n\n    ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 75853,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/search/tests/test_postgres_backend.py",
        "file_name": "test_postgres_backend.py",
        "fun_name": "test_search_tsquery_chars",
        "commit_message": "Reformat with black",
        "code": "def test_search_tsquery_chars(self):\n        \n\n        # Simple quote should be escaped inside each tsquery term.\n        results = self.backend.search(\"L'amour piqué par une abeille\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"'starting quote\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"ending quote'\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"double quo''te\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"triple quo",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 140,
        "n_words": 63,
        "vocab_size": 34,
        "complexity": 13,
        "nloc": 25,
        "token_counts": 378,
        "n_ast_nodes": 595,
        "n_identifiers": 10,
        "d_id": 16435,
        "documentation": {
            "docstring": "\n        Checks that tsquery characters are correctly escaped\n        and do not generate a PostgreSQL syntax error.\n        te\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n\n        # Now suffixes.\n        results = self.backend.search(\"Something:B\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"Something:*\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n        results = self.backend.search(\"Something:A*BCD\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n\n        # Now the AND operator.\n        results = self.backend.search(\"first & second\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n\n        # Now the OR operator.\n        results = self.backend.search(\"first | second\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n\n        # Now the NOT operator.\n        results = self.backend.search(\"first & !second\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n\n        # Now the phrase operator.\n        results = self.backend.search(\"first <-> second\", models.Book)\n        self.assertUnsortedListEqual([r.title for r in results], [])\n",
            "n_words": 124,
            "vocab_size": 43,
            "n_whitespaces": 285,
            "language": "en"
        }
    },
    {
        "id": 271957,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_v1.py",
        "file_name": "training_v1.py",
        "fun_name": "sample_weights_mismatch",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def sample_weights_mismatch(self):\n        \n        # If there is a mismatch between sample weight mode and the placeholders\n        # created, then recompile the sub-graphs that depend on sample weights.\n        return (\n            self.sample_weight_mode is not None and self.sample_weight is None\n        ) or (\n            self.sample_weight_mode is None and self.sample_weight is not None\n        )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 112,
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        "vocab_size": 31,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 36,
        "n_ast_nodes": 59,
        "n_identifiers": 4,
        "d_id": 80913,
        "documentation": {
            "docstring": "Check if the sample weight and the mode match or not.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 222614,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/cmd.py",
        "file_name": "cmd.py",
        "fun_name": "set_undefined_options",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def set_undefined_options(self, src_cmd, *option_pairs):\n        \n        # Option_pairs: list of (src_option, dst_option) tuples\n        src_cmd_obj = self.distribution.get_command_obj(src_cmd)\n        src_cmd_obj.ensure_finalized()\n        for (src_option, dst_option) in option_pairs:\n            if getattr(self, dst_option) is None:\n                setattr(self, dst_option, getattr(src_cmd_obj, src_option))\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 90,
        "n_words": 29,
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        "complexity": 3,
        "nloc": 6,
        "token_counts": 58,
        "n_ast_nodes": 90,
        "n_identifiers": 12,
        "d_id": 56675,
        "documentation": {
            "docstring": "Set the values of any \"undefined\" options from corresponding\n        option values in some other command object.  \"Undefined\" here means\n        \"is None\", which is the convention used to indicate that an option\n        has not been changed between 'initialize_options()' and\n        'finalize_options()'.  Usually called from 'finalize_options()' for\n        options that depend on some other command rather than another\n        option of the same command.  'src_cmd' is the other command from\n        which option values will be taken (a command object will be created\n        for it if necessary); the remaining arguments are\n        '(src_option,dst_option)' tuples which mean \"take the value of\n        'src_option' in the 'src_cmd' command object, and copy it to\n        'dst_option' in the current command object\".\n        ",
            "n_words": 109,
            "vocab_size": 71,
            "n_whitespaces": 196,
            "language": "en"
        }
    },
    {
        "id": 206140,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/middleware/csrf.py",
        "file_name": "csrf.py",
        "fun_name": "get_token",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_token(request):\n    \n    if \"CSRF_COOKIE\" in request.META:\n        csrf_secret = request.META[\"CSRF_COOKIE\"]\n        # Since the cookie is being used, flag to send the cookie in\n        # process_response() (even if the client already has it) in order to\n        # renew the expiry timer.\n        request.META[\"CSRF_COOKIE_NEEDS_UPDATE\"] = True\n    else:\n        csrf_secret = _add_new_csrf_cookie(request)\n    return _mask_cipher_secret(csrf_secret)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 102,
        "n_words": 48,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 42,
        "n_ast_nodes": 79,
        "n_identifiers": 6,
        "d_id": 51381,
        "documentation": {
            "docstring": "\n    Return the CSRF token required for a POST form. The token is an\n    alphanumeric value. A new token is created if one is not already set.\n\n    A side effect of calling this function is to make the csrf_protect\n    decorator and the CsrfViewMiddleware add a CSRF cookie and a 'Vary: Cookie'\n    header to the outgoing response.  For this reason, you may need to use this\n    function lazily, as is done by the csrf context processor.\n    ",
            "n_words": 74,
            "vocab_size": 54,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 205905,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/sql/where.py",
        "file_name": "where.py",
        "fun_name": "as_sql",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def as_sql(self, compiler, connection):\n        \n        result = []\n        result_params = []\n        if self.connector == AND:\n            full_needed, empty_needed = len(self.children), 1\n        else:\n            full_needed, empty_needed = 1, len(self.children)\n\n        for child in self.children:\n            try:\n                sql, params = compiler.compile(child)\n            except EmptyResultSet:\n                empty_needed -= 1\n            else:\n                if sql:\n                    result.append(sql)\n                    result_params.extend(params)\n                else:\n                    full_needed -= 1\n            # Check if this node matches nothing or everything.\n            # First check the amount of full nodes and empty nodes\n            # to make this node empty/full.\n            # Now, check if this node is full/empty using the\n            # counts.\n            if empty_needed == 0:\n                if self.negated:\n                    return \"\", []\n                else:\n                    raise EmptyResultSet\n            if full_needed == 0:\n                if self.negated:\n                    raise EmptyResultSet\n                else:\n                    return \"\", []\n        conn = \" %s \" % self.connector\n        sql_string = conn.join(result)\n        if sql_string:\n            if self.negated:\n                # Some backends (Oracle at least) need parentheses\n                # around the inner SQL in the negated case, even if the\n                # inner SQL contains just a single expression.\n                sql_string = \"NOT (%s)\" % sql_string\n            elif len(result) > 1 or self.resolved:\n                sql_string = \"(%s)\" % sql_string\n        return sql_string, result_params\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 724,
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        "vocab_size": 98,
        "complexity": 13,
        "nloc": 36,
        "token_counts": 185,
        "n_ast_nodes": 320,
        "n_identifiers": 24,
        "d_id": 51276,
        "documentation": {
            "docstring": "\n        Return the SQL version of the where clause and the value to be\n        substituted in. Return '', [] if this node matches everything,\n        None, [] if this node is empty, and raise EmptyResultSet if this\n        node can't match anything.\n        ",
            "n_words": 39,
            "vocab_size": 28,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 74670,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_pageurl_with_unknown_site",
        "commit_message": "Reformat with black",
        "code": "def test_pageurl_with_unknown_site(self):\n        page = Page.objects.get(url_path=\"/home/events/\")\n        tpl = template.Template(\n            \n        )\n\n        # 'request' object in context, but site is None\n        request = HttpRequest()\n        request.META[\"HTTP_HOST\"] = \"unknown.example.com\"\n        request.META[\"SERVER_PORT\"] = 80\n        result = tpl.render(template.Context({\"page\": page, \"request\": request}))\n        self.assertIn('<a href=\"/events/\">Events</a>', result)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 110,
        "n_words": 36,
        "vocab_size": 31,
        "complexity": 1,
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        "token_counts": 75,
        "n_ast_nodes": 135,
        "n_identifiers": 17,
        "d_id": 16286,
        "documentation": {
            "docstring": "{% load wagtailcore_tags %}<a href=\"{% pageurl page %}\">{{ page.title }}</a>",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 322232,
        "commit_id": "7b455cce47204d4d664deea9661670a838ec8d35",
        "repo": "PaddleNLP",
        "path": "paddlenlp/datasets/conll2002.py",
        "file_name": "conll2002.py",
        "fun_name": "get_labels",
        "commit_message": "feat: add conll2002 dataset (#1561)\n\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>",
        "code": "def get_labels(self):\n        \n        return [\"O\", \"B-PER\", \"I-PER\", \"B-ORG\", \"I-ORG\", \"B-LOC\", \"I-LOC\", \"B-MISC\", \"I-MISC\"], \\\n               self.BUILDER_CONFIGS[self.name]['pos_tags']\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 14,
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        "token_counts": 39,
        "n_ast_nodes": 72,
        "n_identifiers": 4,
        "d_id": 118099,
        "documentation": {
            "docstring": "\n        Returns labels of ner tags and pos tags.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 206022,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/widgets.py",
        "file_name": "widgets.py",
        "fun_name": "format_value",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def format_value(self, value):\n        \n        if value == \"\" or value is None:\n            return None\n        if self.is_localized:\n            return formats.localize_input(value)\n        return str(value)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 69,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 36,
        "n_ast_nodes": 61,
        "n_identifiers": 7,
        "d_id": 51328,
        "documentation": {
            "docstring": "\n        Return a value as it should appear when rendered in a template.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 182658,
        "commit_id": "1a20b9de7d4cef7f93e4500757d3fb42e680f40c",
        "repo": "textual",
        "path": "src/textual/_compositor.py",
        "file_name": "_compositor.py",
        "fun_name": "__iter__",
        "commit_message": "docstring",
        "code": "def __iter__(self) -> Iterator[tuple[Widget, Region, Region, Size, Size]]:\n        \n        layers = sorted(self.map.items(), key=lambda item: item[1].order, reverse=True)\n        intersection = Region.intersection\n        for widget, (region, _order, clip, virtual_size, container_size) in layers:\n            yield (\n                widget,\n                intersection(region, clip),\n                region,\n                virtual_size,\n                container_size,\n            )\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 161,
        "n_words": 36,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 90,
        "n_ast_nodes": 126,
        "n_identifiers": 22,
        "d_id": 43896,
        "documentation": {
            "docstring": "Iterate map with information regarding each widget and is position\n\n        Yields:\n            Iterator[tuple[Widget, Region, Region, Size, Size]]: Iterates a tuple of\n                Widget, clip region, region, virtual size, and container size.\n        ",
            "n_words": 29,
            "vocab_size": 26,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 199355,
        "commit_id": "7c199e306648513c13c9b5c5b5fad06e5f1c3020",
        "repo": "sympy",
        "path": "sympy/physics/mechanics/joint.py",
        "file_name": "joint.py",
        "fun_name": "_express_axis",
        "commit_message": "Fix failing test and simplify joint orient methods",
        "code": "def _express_axis(self, axis, frame):\n        \n        try:\n            ax_mat = axis.to_matrix(self.parent_interframe)\n        except ValueError:\n            ax_mat = axis.to_matrix(self.child_interframe)\n        try:\n            self.parent_interframe.dcm(frame)  # Check if connected\n            int_frame = self.parent_interframe\n        except ValueError:\n            int_frame = self.child_interframe\n        return self._to_vector(ax_mat, int_frame).express(frame)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 128,
        "n_words": 30,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 72,
        "n_ast_nodes": 118,
        "n_identifiers": 13,
        "d_id": 49253,
        "documentation": {
            "docstring": "Helper function to get an axis expressed in a specified frame.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 5940,
        "commit_id": "69604268c2ddc06a4ee0b3dce0e05a8fb73b5d16",
        "repo": "ludwig",
        "path": "tests/integration_tests/test_visualization_api.py",
        "file_name": "test_visualization_api.py",
        "fun_name": "run_api_experiment",
        "commit_message": "Rename fc_size to output_size (#1641)\n\n* Rename fc_size to output_size\r\n\r\n* Responding to comments",
        "code": "def run_api_experiment(input_features, output_features):\n    \n    config = {\n        \"input_features\": input_features,\n        \"output_features\": output_features,\n        \"combiner\": {\"type\": \"concat\", \"output_size\": 14},\n        \"training\": {\"epochs\": 2},\n    }\n\n    model = LudwigModel(config)\n    return model\n\n\n@pytest.fixture(scope=\"module\")",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(scope=\"module\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 67,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 48,
        "n_ast_nodes": 105,
        "n_identifiers": 9,
        "d_id": 894,
        "documentation": {
            "docstring": "Helper method to avoid code repetition in running an experiment.\n\n    :param input_features: input schema\n    :param output_features: output schema\n    :return: None\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 107291,
        "commit_id": "162bd59f50a9c59a51574aee5dc9e932133bb971",
        "repo": "matplotlib",
        "path": "examples/axes_grid1/simple_axes_divider1.py",
        "file_name": "simple_axes_divider1.py",
        "fun_name": "label_axes",
        "commit_message": "DOC: More capitalization of Axes\n\nIn line with #18726.\n\nTriggered by #22242.",
        "code": "def label_axes(ax, text):\n    \n    ax.text(.5, .5, text, transform=ax.transAxes,\n            horizontalalignment=\"center\", verticalalignment=\"center\")\n    ax.tick_params(bottom=False, labelbottom=False,\n                   left=False, labelleft=False)\n\n\n##############################################################################\n# Fixed axes sizes; fixed paddings.\n\nfig = plt.figure(figsize=(6, 6))\nfig.suptitle(\"Fixed axes sizes, fixed paddings\")\n\n# Sizes are in inches.\nhoriz = [Size.Fixed(1.), Size.Fixed(.5), Size.Fixed(1.5), Size.Fixed(.5)]\nvert = [Size.Fixed(1.5), Size.Fixed(.5), Size.Fixed(1.)]\n\nrect = (0.1, 0.1, 0.8, 0.8)\n# Divide the axes rectangle into a grid with sizes specified by horiz * vert.\ndiv = Divider(fig, rect, horiz, vert, aspect=False)\n\n# The rect parameter will actually be ignored and overridden by axes_locator.\nax1 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=0))\nlabel_axes(ax1, \"nx=0, ny=0\")\nax2 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=2))\nlabel_axes(ax2, \"nx=0, ny=2\")\nax3 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, ny=2))\nlabel_axes(ax3, \"nx=2, ny=2\")\nax4 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, nx1=4, ny=0))\nlabel_axes(ax4, \"nx=2, nx1=4, ny=0\")\n\n##############################################################################\n# Axes sizes that scale with the figure size; fixed paddings.\n\nfig = plt.figure(figsize=(6, 6))\nfig.suptitle(\"Scalable axes sizes, fixed paddings\")\n\nhoriz = [Size.Scaled(1.5), Size.Fixed(.5), Size.Scaled(1.), Size.Scaled(.5)]\nvert = [Size.Scaled(1.), Size.Fixed(.5), Size.Scaled(1.5)]\n\nrect = (0.1, 0.1, 0.8, 0.8)\n# Divide the axes rectangle into a grid with sizes specified by horiz * vert.\ndiv = Divider(fig, rect, horiz, vert, aspect=False)\n\n# The rect parameter will actually be ignored and overridden by axes_locator.\nax1 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=0))\nlabel_axes(ax1, \"nx=0, ny=0\")\nax2 = fig.add_axes(rect, axes_locator=div.new_locator(nx=0, ny=2))\nlabel_axes(ax2, \"nx=0, ny=2\")\nax3 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, ny=2))\nlabel_axes(ax3, \"nx=2, ny=2\")\nax4 = fig.add_axes(rect, axes_locator=div.new_locator(nx=2, nx1=4, ny=0))\nlabel_axes(ax4, \"nx=2, nx1=4, ny=0\")\n\nplt.show()\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 226,
        "n_words": 226,
        "vocab_size": 101,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 54,
        "n_ast_nodes": 767,
        "n_identifiers": 37,
        "d_id": 22676,
        "documentation": {
            "docstring": "Place a label at the center of an Axes, and remove the axis ticks.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 290234,
        "commit_id": "83c6a7e18b1b0e4d5a302e304f117dee11d3aa51",
        "repo": "core",
        "path": "homeassistant/components/zha/core/channels/lighting.py",
        "file_name": "lighting.py",
        "fun_name": "max_mireds",
        "commit_message": "Fix invalid min and max color temp in bad ZHA light devices (#81604)\n\n* Fix ZHA default color temps\n\n* update test",
        "code": "def max_mireds(self) -> int:\n        \n        max_mireds = self.cluster.get(\"color_temp_physical_max\", self.MAX_MIREDS)\n        if max_mireds == 0:\n            self.warning(\n                \"[Max mireds is 0, setting to %s] Please open an issue on the quirks repo to have this device corrected\",\n                self.MAX_MIREDS,\n            )\n            max_mireds = self.MAX_MIREDS\n        return max_mireds\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 131,
        "n_words": 40,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 45,
        "n_ast_nodes": 76,
        "n_identifiers": 7,
        "d_id": 89352,
        "documentation": {
            "docstring": "Return the warmest color_temp that this channel supports.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 160357,
        "commit_id": "569fc6a40ea53054409e00c7d1c0e7f5f53cb0ce",
        "repo": "numpy",
        "path": "numpy/lib/recfunctions.py",
        "file_name": "recfunctions.py",
        "fun_name": "get_names",
        "commit_message": "Fix docstring and examples for rfn.get_names*",
        "code": "def get_names(adtype):\n    \n    listnames = []\n    names = adtype.names\n    for name in names:\n        current = adtype[name]\n        if current.names is not None:\n            listnames.append((name, tuple(get_names(current))))\n        else:\n            listnames.append(name)\n    return tuple(listnames)\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 84,
        "n_words": 26,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 63,
        "n_ast_nodes": 103,
        "n_identifiers": 8,
        "d_id": 38607,
        "documentation": {
            "docstring": "\n    Returns the field names of the input datatype as a tuple. Input datatype\n    has to have fields otherwise error is raised.\n\n    Parameters\n    ----------\n    adtype : dtype\n        Input datatype\n\n    Examples\n    --------\n    >>> from numpy.lib import recfunctions as rfn\n    >>> rfn.get_names(np.empty((1,), dtype=[('A', int)]).dtype)\n    ('A',)\n    >>> rfn.get_names(np.empty((1,), dtype=[('A',int), ('B', float)]).dtype)\n    ('A', 'B')\n    >>> adtype = np.dtype([('a', int), ('b', [('ba', int), ('bb', int)])])\n    >>> rfn.get_names(adtype)\n    ('a', ('b', ('ba', 'bb')))\n    ",
            "n_words": 65,
            "vocab_size": 52,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 221015,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/windows_utils.py",
        "file_name": "windows_utils.py",
        "fun_name": "pipe",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def pipe(*, duplex=False, overlapped=(True, True), bufsize=BUFSIZE):\n    \n    address = tempfile.mktemp(\n        prefix=r'\\\\.\\pipe\\python-pipe-{:d}-{:d}-'.format(\n            os.getpid(), next(_mmap_counter)))\n\n    if duplex:\n        openmode = _winapi.PIPE_ACCESS_DUPLEX\n        access = _winapi.GENERIC_READ | _winapi.GENERIC_WRITE\n        obsize, ibsize = bufsize, bufsize\n    else:\n        openmode = _winapi.PIPE_ACCESS_INBOUND\n        access = _winapi.GENERIC_WRITE\n        obsize, ibsize = 0, bufsize\n\n    openmode |= _winapi.FILE_FLAG_FIRST_PIPE_INSTANCE\n\n    if overlapped[0]:\n        openmode |= _winapi.FILE_FLAG_OVERLAPPED\n\n    if overlapped[1]:\n        flags_and_attribs = _winapi.FILE_FLAG_OVERLAPPED\n    else:\n        flags_and_attribs = 0\n\n    h1 = h2 = None\n    try:\n        h1 = _winapi.CreateNamedPipe(\n            address, openmode, _winapi.PIPE_WAIT,\n            1, obsize, ibsize, _winapi.NMPWAIT_WAIT_FOREVER, _winapi.NULL)\n\n        h2 = _winapi.CreateFile(\n            address, access, 0, _winapi.NULL, _winapi.OPEN_EXISTING,\n            flags_and_attribs, _winapi.NULL)\n\n        ov = _winapi.ConnectNamedPipe(h1, overlapped=True)\n        ov.GetOverlappedResult(True)\n        return h1, h2\n    except:\n        if h1 is not None:\n            _winapi.CloseHandle(h1)\n        if h2 is not None:\n            _winapi.CloseHandle(h2)\n        raise\n\n\n# Wrapper for a pipe handle\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 346,
        "n_words": 111,
        "vocab_size": 70,
        "complexity": 7,
        "nloc": 37,
        "token_counts": 232,
        "n_ast_nodes": 355,
        "n_identifiers": 38,
        "d_id": 56180,
        "documentation": {
            "docstring": "Like os.pipe() but with overlapped support and using handles not fds.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 310731,
        "commit_id": "d5ec2fe842411aea086333889c4357d8cd6cc394",
        "repo": "core",
        "path": "tests/components/lcn/test_light.py",
        "file_name": "test_light.py",
        "fun_name": "test_unload_config_entry",
        "commit_message": "Add tests for LCN light platform (#64741)",
        "code": "async def test_unload_config_entry(hass, entry, lcn_connection):\n    \n    await hass.config_entries.async_unload(entry.entry_id)\n    assert hass.states.get(\"light.light_output1\").state == STATE_UNAVAILABLE\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 20,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 58,
        "n_identifiers": 11,
        "d_id": 109403,
        "documentation": {
            "docstring": "Test the light is removed when the config entry is unloaded.",
            "n_words": 11,
            "vocab_size": 9,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 39818,
        "commit_id": "cd13276a2df1c33b5daabdd3a07f57e3128e471c",
        "repo": "dash",
        "path": "dash/_get_paths.py",
        "file_name": "_get_paths.py",
        "fun_name": "real_get_relative_path",
        "commit_message": "Added dash.get_relative_path, dash.strip_relative_path, dash.get_asset_url",
        "code": "def real_get_relative_path(config, path):\n    requests_pathname = config.requests_pathname_prefix\n    if requests_pathname == \"/\" and path == \"\":\n        return \"/\"\n    if requests_pathname != \"/\" and path == \"\":\n        return requests_pathname\n    if not path.startswith(\"/\"):\n        raise exceptions.UnsupportedRelativePath(\n            .format(\n                path\n            )\n        )\n    return \"/\".join([requests_pathname.rstrip(\"/\"), path.lstrip(\"/\")])\n\n",
        "url": "https://github.com/plotly/dash.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 117,
        "n_words": 38,
        "vocab_size": 22,
        "complexity": 6,
        "nloc": 16,
        "token_counts": 76,
        "n_ast_nodes": 139,
        "n_identifiers": 12,
        "d_id": 7266,
        "documentation": {
            "docstring": "\n            Paths that aren't prefixed with a leading / are not supported.\n            You supplied: {}\n            ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 280315,
        "commit_id": "c9068087d9142bab573e0c300bf9874a957accff",
        "repo": "keras",
        "path": "keras/saving/saving_api.py",
        "file_name": "saving_api.py",
        "fun_name": "load_model",
        "commit_message": "Prepare public API surface for v3 saving.\n\nPiperOrigin-RevId: 484397600",
        "code": "def load_model(filepath, custom_objects=None, compile=True, **kwargs):\n    \n    if str(filepath).endswith(\".keras\") and zipfile.is_zipfile(filepath):\n        if kwargs:\n            raise ValueError(\n                \"The following argument(s) are not supported \"\n                f\"with the native Keras format: {list(kwargs.keys())}\"\n            )\n        return saving_lib.load_model(\n            filepath, custom_objects=custom_objects, compile=compile\n        )\n\n    # Legacy case.\n    return legacy_sm_saving_lib.load_model(\n        filepath, custom_objects=custom_objects, compile=compile, **kwargs\n    )\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 149,
        "n_words": 43,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 78,
        "n_ast_nodes": 140,
        "n_identifiers": 14,
        "d_id": 83345,
        "documentation": {
            "docstring": "Loads a model saved via `model.save()`.\n\n    Args:\n        filepath: `str` or `pathlib.Path` object, path to the saved model file.\n        custom_objects: Optional dictionary mapping names\n            (strings) to custom classes or functions to be\n            considered during deserialization.\n        compile: Boolean, whether to compile the model after loading.\n\n    SavedModel format arguments:\n        options: Only applies to SavedModel format.\n            Optional `tf.saved_model.LoadOptions` object that specifies\n            SavedModel loading options.\n\n    Returns:\n        A Keras model instance. If the original model was compiled,\n        and the argument `compile=True` is set, then the returned model\n        will be compiled. Otherwise, the model will be left uncompiled.\n\n    Example:\n\n    ```python\n    model = tf.keras.Sequential([\n        tf.keras.layers.Dense(5, input_shape=(3,)),\n        tf.keras.layers.Softmax()])\n    model.save(\"model.keras\")\n    loaded_model = tf.keras.models.load_model(\"model.keras\")\n    x = tf.random.uniform((10, 3))\n    assert np.allclose(model.predict(x), loaded_model.predict(x))\n    ```\n\n    Note that the model variables may have different name values\n    (`var.name` property, e.g. `\"dense_1/kernel:0\"`) after being reloaded.\n    It is recommended that you use layer attributes to\n    access specific variables, e.g. `model.get_layer(\"dense_1\").kernel`.\n    ",
            "n_words": 142,
            "vocab_size": 108,
            "n_whitespaces": 297,
            "language": "en"
        }
    },
    {
        "id": 3243,
        "commit_id": "61f4138eeb028287425f6007d692bf7faa808e75",
        "repo": "PySyft",
        "path": "packages/syft/tests/syft/core/adp/data_subject_ledger_test.py",
        "file_name": "data_subject_ledger_test.py",
        "fun_name": "test_cache_invalidation",
        "commit_message": "Add tests for ledger and cache",
        "code": "def test_cache_invalidation() -> None:\n    \n    ledger_store = DictLedgerStore()\n    user_key = b\"1483\"\n    ledger = DataSubjectLedger.get_or_create(store=ledger_store, user_key=user_key)\n\n    assert ledger.delta == 1e-6, \"The cache has been changed or is invalid.\"\n    assert (\n        ledger._cache_constant2epsilon.all()\n    ), \"There is a zero epsilon value in the cache- major security flaw.\"\n    assert (\n        ledger._cache_constant2epsilon > 0\n    ).all(), \"Negative epsilon value in the cache- major security flaw.\"\n\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 98,
        "n_words": 57,
        "vocab_size": 43,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 66,
        "n_ast_nodes": 108,
        "n_identifiers": 11,
        "d_id": 411,
        "documentation": {
            "docstring": "The cache was built assuming a particular value of delta (1e-6), and shouldn't contain any zero values.",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 247147,
        "commit_id": "91bc15c772d22fbe814170ab2e0fdbfa50f9c372",
        "repo": "synapse",
        "path": "tests/util/test_async_helpers.py",
        "file_name": "test_async_helpers.py",
        "fun_name": "test_cancellation",
        "commit_message": "Add `stop_cancellation` utility function (#12106)",
        "code": "def test_cancellation(self):\n        \n        deferred: \"Deferred[str]\" = Deferred()\n        wrapper_deferred = stop_cancellation(deferred)\n\n        # Cancel the new `Deferred`.\n        wrapper_deferred.cancel()\n        self.assertTrue(wrapper_deferred.called)\n        self.failureResultOf(wrapper_deferred, CancelledError)\n        self.assertFalse(\n            deferred.called, \"Original `Deferred` was unexpectedly cancelled.\"\n        )\n\n        # Now make the inner `Deferred` fail.\n        # The `Failure` must be consumed, otherwise unwanted tracebacks will be printed\n        # in logs.\n        deferred.errback(ValueError(\"abc\"))\n        self.assertIsNone(deferred.result, \"`Failure` was not consumed\")\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 163,
        "n_words": 54,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 69,
        "n_ast_nodes": 126,
        "n_identifiers": 16,
        "d_id": 71509,
        "documentation": {
            "docstring": "Test that cancellation of the new `Deferred` leaves the original running.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 249167,
        "commit_id": "c97042f7eef3748e17c90e48a4122389a89c4735",
        "repo": "synapse",
        "path": "tests/rest/admin/test_statistics.py",
        "file_name": "test_statistics.py",
        "fun_name": "test_from",
        "commit_message": "Use literals in place of `HTTPStatus` constants in tests (#13469)",
        "code": "def test_from(self) -> None:\n        \n        self._create_users_with_media(20, 2)\n\n        channel = self.make_request(\n            \"GET\",\n            self.url + \"?from=5\",\n            access_token=self.admin_user_tok,\n        )\n\n        self.assertEqual(200, channel.code, msg=channel.json_body)\n        self.assertEqual(channel.json_body[\"total\"], 20)\n        self.assertEqual(len(channel.json_body[\"users\"]), 15)\n        self.assertNotIn(\"next_token\", channel.json_body)\n        self._check_fields(channel.json_body[\"users\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 121,
        "n_words": 25,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 103,
        "n_ast_nodes": 168,
        "n_identifiers": 15,
        "d_id": 72674,
        "documentation": {
            "docstring": "\n        Testing list of media with a defined starting point (from)\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 144867,
        "commit_id": "35a157948efa7ba1adf1d1507c2af1d6d84a7db7",
        "repo": "ray",
        "path": "python/ray/data/dataset.py",
        "file_name": "dataset.py",
        "fun_name": "get_internal_block_refs",
        "commit_message": "Lay the groundwork for lazy dataset optimization (no behavior changes) (#22233)\n\nThis PR refactors Dataset execution to enable lazy mode in the future, which can reduce memory usage in large-scale ingest pipelines. There should be no behavior changes in this PR. Many of the optimizations are also punted for future work.",
        "code": "def get_internal_block_refs(self) -> List[ObjectRef[Block]]:\n        \n        return self._plan.execute().get_blocks()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 26,
        "n_ast_nodes": 44,
        "n_identifiers": 8,
        "d_id": 33326,
        "documentation": {
            "docstring": "Get a list of references to the underlying blocks of this dataset.\n\n        This function can be used for zero-copy access to the data. It blocks\n        until the underlying blocks are computed.\n\n        Time complexity: O(1)\n\n        Returns:\n            A list of references to this dataset's blocks.\n        ",
            "n_words": 43,
            "vocab_size": 31,
            "n_whitespaces": 89,
            "language": "en"
        }
    },
    {
        "id": 85773,
        "commit_id": "72e351082168f68cbaa5700a51e8ed577222e887",
        "repo": "sentry",
        "path": "src/sentry/tagstore/base.py",
        "file_name": "base.py",
        "fun_name": "get_group_tag_value_count",
        "commit_message": "feat(perf_issues): Fix `GroupTagKeyDetailsEndpoint` to work for performance issues (#38860)\n\nThis allows this endpoint to return results for performance issues.",
        "code": "def get_group_tag_value_count(self, group, environment_id, key):\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 14,
        "n_ast_nodes": 22,
        "n_identifiers": 6,
        "d_id": 18042,
        "documentation": {
            "docstring": "\n        >>> get_group_tag_value_count(group, 3, 'key1')\n        ",
            "n_words": 4,
            "vocab_size": 4,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 141415,
        "commit_id": "80ae651f259e1ea13c21b285d6bfcc7fd834ef9c",
        "repo": "ray",
        "path": "python/ray/train/_internal/backend_executor.py",
        "file_name": "backend_executor.py",
        "fun_name": "_create_local_rank_map",
        "commit_message": "[Train] Clean up `ray.train` package (#25566)",
        "code": "def _create_local_rank_map(self) -> Dict:\n        \n        rank_mapping = {}\n        ip_dict = defaultdict(int)\n        for world_rank in range(len(self.worker_group)):\n            worker = self.worker_group.workers[world_rank]\n            node_ip = worker.metadata.node_ip\n            rank_mapping[world_rank] = ip_dict[node_ip]\n            ip_dict[node_ip] += 1\n        return rank_mapping\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 107,
        "n_words": 28,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 30,
        "token_counts": 65,
        "n_ast_nodes": 104,
        "n_identifiers": 15,
        "d_id": 32355,
        "documentation": {
            "docstring": "Create mapping from worker world_rank to local_rank.\n\n        Example:\n            Worker 0: 0.0.0.0\n            Worker 1: 0.0.0.0\n            Worker 2: 0.0.0.1\n            Worker 3: 0.0.0.0\n            Worker 4: 0.0.0.1\n\n            Workers 0, 1, 3 are on 0.0.0.0.\n            Workers 2, 4 are on 0.0.0.1.\n\n            Expected Output:\n            {\n                0 -> 0,\n                1 -> 1,\n                2 -> 0,\n                3 -> 2,\n                4 -> 1\n            }\n        ",
            "n_words": 55,
            "vocab_size": 34,
            "n_whitespaces": 254,
            "language": "en"
        }
    },
    {
        "id": 156093,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "iloc",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def iloc(self):\n        \n        from dask.dataframe.indexing import _iLocIndexer\n\n        # For dataframes with unique column names, this will be transformed into a __getitem__ call\n        return _iLocIndexer(self)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 51,
        "n_words": 23,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 33,
        "n_identifiers": 6,
        "d_id": 36552,
        "documentation": {
            "docstring": "Purely integer-location based indexing for selection by position.\n\n        Only indexing the column positions is supported. Trying to select\n        row positions will raise a ValueError.\n\n        See :ref:`dataframe.indexing` for more.\n\n        Examples\n        --------\n        >>> df.iloc[:, [2, 0, 1]]  # doctest: +SKIP\n        ",
            "n_words": 38,
            "vocab_size": 35,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 83261,
        "commit_id": "b0ce4f1bce8031881addecb1e86073483517f392",
        "repo": "zulip",
        "path": "zerver/tests/test_openapi.py",
        "file_name": "test_openapi.py",
        "fun_name": "check_for_non_existent_openapi_endpoints",
        "commit_message": "docs: Fix many spelling mistakes.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def check_for_non_existent_openapi_endpoints(self) -> None:\n        \n        openapi_paths = set(get_openapi_paths())\n        undocumented_paths = openapi_paths - self.checked_endpoints\n        undocumented_paths -= self.buggy_documentation_endpoints\n        undocumented_paths -= self.pending_endpoints\n        try:\n            self.assert_length(undocumented_paths, 0)\n        except AssertionError:  # nocoverage\n            msg = \"The following endpoints have been documented but can't be found in urls.py:\"\n            for undocumented_path in undocumented_paths:\n                msg += f\"\\n + {undocumented_path}\"\n            raise AssertionError(msg)\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 159,
        "n_words": 50,
        "vocab_size": 42,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 63,
        "n_ast_nodes": 113,
        "n_identifiers": 13,
        "d_id": 17642,
        "documentation": {
            "docstring": "Here, we check to see if every endpoint documented in the OpenAPI\n        documentation actually exists in urls.py and thus in actual code.\n        Note: We define this as a helper called at the end of\n        test_openapi_arguments instead of as a separate test to ensure that\n        this test is only executed after test_openapi_arguments so that it's\n        results can be used here in the set operations.",
            "n_words": 63,
            "vocab_size": 50,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 209600,
        "commit_id": "495b21f2867e48286767085c8cf2918e4092e9dc",
        "repo": "scapy",
        "path": "scapy/contrib/automotive/xcp/scanner.py",
        "file_name": "scanner.py",
        "fun_name": "_send_connect",
        "commit_message": "Add Automotive Logger for all debug outputs of the automotive layer",
        "code": "def _send_connect(self, identifier):\n        # type: (int) -> List[XCPScannerResult]\n        \n        all_slaves = []\n        body = Connect(connection_mode=0x00)\n        xcp_req_and_res_list = self._scan(identifier, body, 0xFF,\n                                          ConnectPositiveResponse)\n\n        for req_and_res in xcp_req_and_res_list:\n            result = XCPScannerResult(response_id=req_and_res[1].identifier,\n                                      request_id=identifier)\n            all_slaves.append(result)\n            log_automotive.info(\n                \"Detected XCP slave for broadcast identifier: \" + str(\n                    identifier) + \"\\nResponse: \" + str(result))\n\n        if len(all_slaves) == 0:\n            log_automotive.info(\n                \"No XCP slave detected for identifier: \" + str(identifier))\n        return all_slaves\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 288,
        "n_words": 61,
        "vocab_size": 46,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 101,
        "n_ast_nodes": 167,
        "n_identifiers": 20,
        "d_id": 52743,
        "documentation": {
            "docstring": "\n        Sends CONNECT Message on the Control Area Network\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 218170,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap_external.py",
        "file_name": "_bootstrap_external.py",
        "fun_name": "_calc_mode",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _calc_mode(path):\n    \n    try:\n        mode = _path_stat(path).st_mode\n    except OSError:\n        mode = 0o666\n    # We always ensure write access so we can update cached files\n    # later even when the source files are read-only on Windows (#6074)\n    mode |= 0o200\n    return mode\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 75,
        "n_words": 40,
        "vocab_size": 34,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 27,
        "n_ast_nodes": 50,
        "n_identifiers": 6,
        "d_id": 55174,
        "documentation": {
            "docstring": "Calculate the mode permissions for a bytecode file.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 105462,
        "commit_id": "a5e05ccffa49051cbad84c007f31725ad4b2e7f7",
        "repo": "datasets",
        "path": "src/datasets/download/download_manager.py",
        "file_name": "download_manager.py",
        "fun_name": "download",
        "commit_message": "Fix multiprocessing in map_nested  (#4740)\n\n* Do multiprocessing in map_nested when num_proc >= len(iterable)\r\n\r\n* Add missing type hint\r\n\r\n* Update docstring\r\n\r\n* Fix tests\r\n\r\n* Document download default and fix docstring\r\n\r\n* Fix docstring syntax\r\n\r\n* Add tests\r\n\r\n* Fix test for Python<3.8\r\n\r\n* Download with multiprocessing only if at least 16 files\r\n\r\n* Revert test fix\r\n\r\n* Rename multiprocessing_min_length to parallel_min_length",
        "code": "def download(self, url_or_urls):\n        \n        download_config = self.download_config.copy()\n        download_config.extract_compressed_file = False\n        # Default to using 16 parallel thread for downloading\n        # Note that if we have less than or equal to 16 files, multi-processing is not activated\n        if download_config.num_proc is None:\n            download_config.num_proc = 16\n        if download_config.download_desc is None:\n            download_config.download_desc = \"Downloading data\"\n\n        download_func = partial(self._download, download_config=download_config)\n\n        start_time = datetime.now()\n        downloaded_path_or_paths = map_nested(\n            download_func,\n            url_or_urls,\n            map_tuple=True,\n            num_proc=download_config.num_proc,\n            parallel_min_length=16,\n            disable_tqdm=not is_progress_bar_enabled(),\n            desc=\"Downloading data files\",\n        )\n        duration = datetime.now() - start_time\n        logger.info(f\"Downloading took {duration.total_seconds() // 60} min\")\n        url_or_urls = NestedDataStructure(url_or_urls)\n        downloaded_path_or_paths = NestedDataStructure(downloaded_path_or_paths)\n        self.downloaded_paths.update(dict(zip(url_or_urls.flatten(), downloaded_path_or_paths.flatten())))\n\n        start_time = datetime.now()\n        self._record_sizes_checksums(url_or_urls, downloaded_path_or_paths)\n        duration = datetime.now() - start_time\n        logger.info(f\"Checksum Computation took {duration.total_seconds() // 60} min\")\n\n        return downloaded_path_or_paths.data\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 355,
        "n_words": 109,
        "vocab_size": 73,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 186,
        "n_ast_nodes": 330,
        "n_identifiers": 33,
        "d_id": 22123,
        "documentation": {
            "docstring": "Download given URL(s).\n\n        By default, if there is more than one URL to download, multiprocessing is used with maximum `num_proc = 16`.\n        Pass customized `download_config.num_proc` to change this behavior.\n\n        Args:\n            url_or_urls (`str` or `list` or `dict`): URL or list/dict of URLs to download. Each URL is a `str`.\n\n        Returns:\n            `str` or `list` or `dict`: The downloaded paths matching the given input `url_or_urls`.\n\n        Example:\n\n        ```py\n        >>> downloaded_files = dl_manager.download('https://storage.googleapis.com/seldon-datasets/sentence_polarity_v1/rt-polaritydata.tar.gz')\n        ```\n        ",
            "n_words": 69,
            "vocab_size": 56,
            "n_whitespaces": 154,
            "language": "en"
        }
    },
    {
        "id": 209211,
        "commit_id": "f549b66f3f523c1c1a4a21aadc40c6153c5ad77e",
        "repo": "scapy",
        "path": "scapy/contrib/automotive/scanner/executor.py",
        "file_name": "executor.py",
        "fun_name": "execute_test_case",
        "commit_message": "Stabilize UDS_Scanner unit tests for appveyor (#3615)\n\n* Different approach\n\n* add event\n\n* fix test\n\n* cleanup\n\n* cleanup\n\n* lower timeout of GMLAN Scanner\n\n* apply feedback",
        "code": "def execute_test_case(self, test_case):\n        # type: (AutomotiveTestCaseABC) -> None\n        \n        test_case.pre_execute(\n            self.socket, self.target_state, self.configuration)\n\n        try:\n            test_case_kwargs = self.configuration[test_case.__class__.__name__]\n        except KeyError:\n            test_case_kwargs = dict()\n\n        log_interactive.debug(\"[i] Execute test_case %s with args %s\",\n                              test_case.__class__.__name__, test_case_kwargs)\n\n        test_case.execute(self.socket, self.target_state, **test_case_kwargs)\n        test_case.post_execute(\n            self.socket, self.target_state, self.configuration)\n\n        self.check_new_states(test_case)\n        self.check_new_testcases(test_case)\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 182,
        "n_words": 39,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 103,
        "n_ast_nodes": 162,
        "n_identifiers": 18,
        "d_id": 52642,
        "documentation": {
            "docstring": "\n        This function ensures the correct execution of a testcase, including\n        the pre_execute, execute and post_execute.\n        Finally the testcase is asked if a new edge or a new testcase was\n        generated.\n        :param test_case: A test case to be executed\n        :return: None\n        ",
            "n_words": 40,
            "vocab_size": 34,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 169282,
        "commit_id": "709f274245dc2f3fe2d91ad53a4cfa57f9d41d59",
        "repo": "pandas",
        "path": "pandas/core/groupby/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "backfill",
        "commit_message": "DOC: Add deprecation infos to deprecated functions (#48599)\n\n* DOC: Add deprecation infos to deprecated functions\r\n\r\n* Add sections\r\n\r\n* Fix",
        "code": "def backfill(self, limit=None):\n        \n        warnings.warn(\n            \"backfill is deprecated and will be removed in a future version. \"\n            \"Use bfill instead.\",\n            FutureWarning,\n            stacklevel=find_stack_level(inspect.currentframe()),\n        )\n        return self.bfill(limit=limit)\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 96,
        "n_words": 24,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 40,
        "n_ast_nodes": 68,
        "n_identifiers": 11,
        "d_id": 40410,
        "documentation": {
            "docstring": "\n        Backward fill the values.\n\n        .. deprecated:: 1.4\n            Use bfill instead.\n\n        Parameters\n        ----------\n        limit : int, optional\n            Limit of how many values to fill.\n\n        Returns\n        -------\n        Series or DataFrame\n            Object with missing values filled.\n        ",
            "n_words": 33,
            "vocab_size": 32,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 269510,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "disable_tf_random_generator",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def disable_tf_random_generator():\n    \n    global _USE_GENERATOR_FOR_RNG\n    _USE_GENERATOR_FOR_RNG = False\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 16,
        "n_words": 7,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 10,
        "n_ast_nodes": 20,
        "n_identifiers": 2,
        "d_id": 80141,
        "documentation": {
            "docstring": "Disable the `tf.random.Generator` as the RNG for Keras.\n\n    See `tf.keras.backend.experimental.is_tf_random_generator_enabled` for more\n    details.\n    ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 263836,
        "commit_id": "f4a8368fb0d1f4e0a902cccfabccde3c8c0d93d1",
        "repo": "pyinstaller",
        "path": "tests/unit/test_isolation.py",
        "file_name": "test_isolation.py",
        "fun_name": "test_exception_handling",
        "commit_message": "Allow sources to be formatted using yapf 0.32.0\n\nAllow sources to be formatted using yapf 0.32.0 in addition to\ncurrently pinned 0.31.0.\n\nVersion 0.32.0 enables `blank_line_before_nested_class_or_def` by\ndefault. As this was disabled by default in earlier versions, we\nnow need to explicitly turn it off in configuration.\n\nThe two versions also seem to disagree about alignment of split\nstring fragments (same line in 0.31, vertically aligned in 0.32).\nIn our code, some cases look better vertically aligned (disable\nyapf on those via comment to prevent changes on older version),\nwhile the remaining cases should have been merged into a single\nstring in the first place; so do that now.",
        "code": "def test_exception_handling():\n    \n    # Raising an error in a subprocess should propagate to a runtime error in the master process.\n    with pytest.raises(RuntimeError) as ex_info:\n        isolated.call(fail)\n    # The exception should include the offending function's name and the child's traceback which itself includes the\n    # breaking line of code and the exception type and message (in that order). Unfortunately, there seems to be a bug\n    # in pytest's exception rewriting which makes the exception type and message unverifiable when ran under pytest.\n    assert ex_info.match(r)\n    # It should have removed the following line.\n    assert \"Traceback (most recent call last)\" not in str(ex_info.value)\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 132,
        "n_words": 98,
        "vocab_size": 69,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 39,
        "n_ast_nodes": 76,
        "n_identifiers": 11,
        "d_id": 77458,
        "documentation": {
            "docstring": "\n    Test the behaviour which an error is raised in the child process.\n    (?s) call to fail\\(\\) failed .* assert 0, \"It's broken!\".*",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 38500,
        "commit_id": "5a9957358cebd616e58b2d1ab3b887c2f2793b45",
        "repo": "transformers",
        "path": "src/transformers/models/wav2vec2_conformer/modeling_wav2vec2_conformer.py",
        "file_name": "modeling_wav2vec2_conformer.py",
        "fun_name": "_set_gradient_checkpointing",
        "commit_message": "Add Wav2Vec2Conformer (#16812)\n\n* save intermediate\r\n\r\n* add wav2vec2 conformer\r\n\r\n* add more code\r\n\r\n* more\r\n\r\n* first test passes\r\n\r\n* make all checkpoints work\r\n\r\n* update\r\n\r\n* up\r\n\r\n* more clean ups\r\n\r\n* save clean-up\r\n\r\n* save clean-up\r\n\r\n* save more\r\n\r\n* remove bogus\r\n\r\n* finalize design conformer\r\n\r\n* remove vision\r\n\r\n* finish all tests\r\n\r\n* more changes\r\n\r\n* finish code\r\n\r\n* add doc tests\r\n\r\n* add slow tests\r\n\r\n* fix autoconfig test\r\n\r\n* up\r\n\r\n* correct docstring\r\n\r\n* up\r\n\r\n* update\r\n\r\n* fix\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Anton Lozhkov <aglozhkov@gmail.com>\r\n\r\n* Update docs/source/en/model_doc/wav2vec2-conformer.mdx\r\n\r\n* upload\r\n\r\n* save copied from\r\n\r\n* correct configs\r\n\r\n* fix model outputs\r\n\r\n* add to docs\r\n\r\n* fix imports\r\n\r\n* finish\r\n\r\n* finish code\r\n\r\n* correct copied from\r\n\r\n* correct again\r\n\r\n* correct make fix\r\n\r\n* improve make fix copies\r\n\r\n* save\r\n\r\n* correct fix copy from\r\n\r\n* correct init structure\r\n\r\n* correct\r\n\r\n* fix import\r\n\r\n* apply suggestions\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\nCo-authored-by: Anton Lozhkov <aglozhkov@gmail.com>",
        "code": "def _set_gradient_checkpointing(self, module, value=False):\n        if isinstance(module, (Wav2Vec2ConformerEncoder, Wav2Vec2ConformerFeatureEncoder)):\n            module.gradient_checkpointing = value\n\n\nWAV2VEC2_CONFORMER_START_DOCSTRING = r\n\n\nWAV2VEC2_CONFORMER_INPUTS_DOCSTRING = r\n\n\n@add_start_docstrings(\n    \"The bare Wav2Vec2Conformer Model transformer outputting raw hidden-states without any specific head on top.\",\n    WAV2VEC2_CONFORMER_START_DOCSTRING,\n)",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"The bare Wav2Vec2Conformer Model transformer outputting raw hidden-states without any specific head on top.\",\n    WAV2VEC2_CONFORMER_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 53,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 69,
        "n_identifiers": 11,
        "d_id": 6985,
        "documentation": {
            "docstring": "\n    Wav2Vec2Conformer was proposed in [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech\n    Representations](https://arxiv.org/abs/2006.11477) by Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, Michael\n    Auli.\n\n    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the\n    library implements for all its model (such as downloading or saving etc.).\n\n    This model is a PyTorch [nn.Module](https://pytorch.org/docs/stable/nn.html#nn.Module) sub-class. Use it as a\n    regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and behavior.\n\n    Parameters:\n        config ([`Wav2Vec2ConformerConfig`]): Model configuration class with all the parameters of the model.\n            Initializing with a config file does not load the weights associated with the model, only the\n            configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.\n\n    Args:\n        input_values (`torch.FloatTensor` of shape `(batch_size, sequence_length)`):\n            Float values of input raw speech waveform. Values can be obtained by loading a *.flac* or *.wav* audio file\n            into an array of type *List[float]* or a *numpy.ndarray*, *e.g.* via the soundfile library (*pip install\n            soundfile*). To prepare the array into *input_values*, the [`Wav2Vec2Processor`] should be used for padding\n            and conversion into a tensor of type *torch.FloatTensor*. See [`Wav2Vec2Processor.__call__`] for details.\n        attention_mask (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\n            Mask to avoid performing convolution and attention on padding token indices. Mask values selected in `[0,\n            1]`:\n\n            - 1 for tokens that are **not masked**,\n            - 0 for tokens that are **masked**.\n\n            [What are attention masks?](../glossary#attention-mask)\n\n            <Tip warning={true}>\n\n            `attention_mask` should only be passed if the corresponding processor has `config.return_attention_mask ==\n            True`. For all models whose processor has `config.return_attention_mask == False`, such as\n            [wav2vec2_conformer-base](https://huggingface.co/facebook/wav2vec2-conformer-large-rel-pos),\n            `attention_mask` should **not** be passed to avoid degraded performance when doing batched inference. For\n            such models `input_values` should simply be padded with 0 and passed without `attention_mask`. Be aware\n            that these models also yield slightly different results depending on whether `input_values` is padded or\n            not.\n\n            </Tip>\n\n        output_attentions (`bool`, *optional*):\n            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned\n            tensors for more detail.\n        output_hidden_states (`bool`, *optional*):\n            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for\n            more detail.\n        return_dict (`bool`, *optional*):\n            Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple.\n",
            "n_words": 362,
            "vocab_size": 217,
            "n_whitespaces": 706,
            "language": "en"
        }
    },
    {
        "id": 244549,
        "commit_id": "c71a160c5193b92f6a4f56c113e96b63decf8354",
        "repo": "mmdetection",
        "path": "mmdet/datasets/pipelines/loading.py",
        "file_name": "loading.py",
        "fun_name": "__call__",
        "commit_message": "Refacter Visualization",
        "code": "def __call__(self, results):\n        \n\n        img = results['img']\n        if self.to_float32:\n            img = img.astype(np.float32)\n\n        results['img_path'] = None\n        results['img'] = img\n        height, width = img.shape[:2]\n        results['height'] = height\n        results['width'] = width\n        results['ori_height'] = height\n        results['ori_width'] = width\n        return results\n\n\n@TRANSFORMS.register_module()",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "@TRANSFORMS.register_module()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 123,
        "n_words": 36,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 78,
        "n_ast_nodes": 147,
        "n_identifiers": 13,
        "d_id": 70426,
        "documentation": {
            "docstring": "Call functions to add image meta information.\n\n        Args:\n            results (dict): Result dict with Webcam read image in\n                ``results['img']``.\n\n        Returns:\n            dict: The dict contains loaded image and meta information.\n        ",
            "n_words": 28,
            "vocab_size": 23,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 110880,
        "commit_id": "511232b14b6fca586ac92bc5f8e0b0924f23172f",
        "repo": "matplotlib",
        "path": "lib/matplotlib/collections.py",
        "file_name": "collections.py",
        "fun_name": "set_linestyle",
        "commit_message": "remove redundant string handling",
        "code": "def set_linestyle(self, ls):\n        \n        try:\n            dashes = [mlines._get_dash_pattern(ls)]\n        except ValueError:\n            try:\n                dashes = [mlines._get_dash_pattern(x) for x in ls]\n            except ValueError as err:\n                raise ValueError('Do not know how to convert {!r} to '\n                                 'dashes'.format(ls)) from err\n\n        # get the list of raw 'unscaled' dash patterns\n        self._us_linestyles = dashes\n\n        # broadcast and scale the lw and dash patterns\n        self._linewidths, self._linestyles = self._bcast_lwls(\n            self._us_lw, self._us_linestyles)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 216,
        "n_words": 61,
        "vocab_size": 48,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 82,
        "n_ast_nodes": 138,
        "n_identifiers": 15,
        "d_id": 24344,
        "documentation": {
            "docstring": "\n        Set the linestyle(s) for the collection.\n\n        ===========================   =================\n        linestyle                     description\n        ===========================   =================\n        ``'-'`` or ``'solid'``        solid line\n        ``'--'`` or  ``'dashed'``     dashed line\n        ``'-.'`` or  ``'dashdot'``    dash-dotted line\n        ``':'`` or ``'dotted'``       dotted line\n        ===========================   =================\n\n        Alternatively a dash tuple of the following form can be provided::\n\n            (offset, onoffseq),\n\n        where ``onoffseq`` is an even length tuple of on and off ink in points.\n\n        Parameters\n        ----------\n        ls : str or tuple or list thereof\n            Valid values for individual linestyles include {'-', '--', '-.',\n            ':', '', (offset, on-off-seq)}. See `.Line2D.set_linestyle` for a\n            complete description.\n        ",
            "n_words": 90,
            "vocab_size": 69,
            "n_whitespaces": 288,
            "language": "en"
        }
    },
    {
        "id": 3353,
        "commit_id": "f83eca58eaf2129d21b5796a301732ab22675130",
        "repo": "airbyte",
        "path": "airbyte-cdk/python/unit_tests/sources/test_abstract_source.py",
        "file_name": "test_abstract_source.py",
        "fun_name": "test_valid_incremental_read_with_slices",
        "commit_message": "CDK: Fix typing errors (#9037)\n\n* fix typing, drop AirbyteLogger\r\n\r\n* format\r\n\r\n* bump the version\r\n\r\n* use logger instead of fixture logger\r\n\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>\r\nCo-authored-by: auganbay <auganenu@gmail.com>",
        "code": "def test_valid_incremental_read_with_slices(mocker):\n    \n    slices = [{\"1\": \"1\"}, {\"2\": \"2\"}]\n    stream_output = [{\"k1\": \"v1\"}, {\"k2\": \"v2\"}, {\"k3\": \"v3\"}]\n    s1 = MockStream(\n        [({\"sync_mode\": SyncMode.incremental, \"stream_slice\": s, \"stream_state\": mocker.ANY}, stream_output) for s in slices], name=\"s1\"\n    )\n    s2 = MockStream(\n        [({\"sync_mode\": SyncMode.incremental, \"stream_slice\": s, \"stream_state\": mocker.ANY}, stream_output) for s in slices], name=\"s2\"\n    )\n    state = {\"cursor\": \"value\"}\n    mocker.patch.object(MockStream, \"get_updated_state\", return_value=state)\n    mocker.patch.object(MockStream, \"supports_incremental\", return_value=True)\n    mocker.patch.object(MockStream, \"get_json_schema\", return_value={})\n    mocker.patch.object(MockStream, \"stream_slices\", return_value=slices)\n\n    src = MockSource(streams=[s1, s2])\n    catalog = ConfiguredAirbyteCatalog(streams=[_configured_stream(s1, SyncMode.incremental), _configured_stream(s2, SyncMode.incremental)])\n\n    expected = [\n        # stream 1 slice 1\n        *_as_records(\"s1\", stream_output),\n        _state({\"s1\": state}),\n        # stream 1 slice 2\n        *_as_records(\"s1\", stream_output),\n        _state({\"s1\": state}),\n        # stream 2 slice 1\n        *_as_records(\"s2\", stream_output),\n        _state({\"s1\": state, \"s2\": state}),\n        # stream 2 slice 2\n        *_as_records(\"s2\", stream_output),\n        _state({\"s1\": state, \"s2\": state}),\n    ]\n\n    messages = _fix_emitted_at(list(src.read(logger, {}, catalog, state=defaultdict(dict))))\n\n    assert expected == messages\n\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 280,
        "n_words": 128,
        "vocab_size": 74,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 326,
        "n_ast_nodes": 544,
        "n_identifiers": 32,
        "d_id": 455,
        "documentation": {
            "docstring": "Tests that an incremental read which uses slices outputs each record in the slice followed by a STATE message, for each slice",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 13058,
        "commit_id": "243639dd2b953fab8654747cbfdf6a0953b95578",
        "repo": "jina",
        "path": "jina/serve/runtimes/gateway/http/gateway.py",
        "file_name": "gateway.py",
        "fun_name": "setup_server",
        "commit_message": "refactor: extract gateway app logic into custom gateway class (#5153)",
        "code": "async def setup_server(self):\n        \n        from jina.helper import extend_rest_interface\n\n        self.app = extend_rest_interface(\n            get_fastapi_app(\n                streamer=self.streamer,\n                title=self.title,\n                description=self.description,\n                no_debug_endpoints=self.no_debug_endpoints,\n                no_crud_endpoints=self.no_crud_endpoints,\n                expose_endpoints=self.expose_endpoints,\n                expose_graphql_endpoint=self.expose_graphql_endpoint,\n                cors=self.cors,\n                logger=self.logger,\n            )\n        )\n\n        with ImportExtensions(required=True):\n            from uvicorn import Config, Server\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 232,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 7,
        "nloc": 40,
        "token_counts": 239,
        "n_ast_nodes": 137,
        "n_identifiers": 21,
        "d_id": 2529,
        "documentation": {
            "docstring": "\n        Initialize and return GRPC server\n        ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 203420,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/options.py",
        "file_name": "options.py",
        "fun_name": "get_sortable_by",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_sortable_by(self, request):\n        \n        return (\n            self.sortable_by\n            if self.sortable_by is not None\n            else self.get_list_display(request)\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 68,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 28,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 50365,
        "documentation": {
            "docstring": "Hook for specifying which fields can be sorted in the changelist.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 259103,
        "commit_id": "3605c140af992b6ac52f04f1689c58509cc0b5b2",
        "repo": "scikit-learn",
        "path": "sklearn/utils/tests/test_class_weight.py",
        "file_name": "test_class_weight.py",
        "fun_name": "test_class_weight_does_not_contains_more_classses",
        "commit_message": "FIX Support extra class_weights in compute_class_weight (#22595)",
        "code": "def test_class_weight_does_not_contains_more_classses():\n    \n    tree = DecisionTreeClassifier(class_weight={0: 1, 1: 10, 2: 20})\n\n    # Does not raise\n    tree.fit([[0, 0, 1], [1, 0, 1], [1, 2, 0]], [0, 0, 1])\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 38,
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        "vocab_size": 22,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 63,
        "n_ast_nodes": 89,
        "n_identifiers": 5,
        "d_id": 75568,
        "documentation": {
            "docstring": "Check that class_weight can contain more labels than in y.\n\n    Non-regression test for #22413\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 270367,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/distribute/distributed_training_utils_v1.py",
        "file_name": "distributed_training_utils_v1.py",
        "fun_name": "_make_replica_execution_function",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _make_replica_execution_function(model, mode):\n    \n    if mode == ModeKeys.TRAIN:\n        func = model.train_on_batch\n    elif mode == ModeKeys.TEST:\n        func = model.test_on_batch\n    else:\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 44,
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        "vocab_size": 14,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 60,
        "n_ast_nodes": 57,
        "n_identifiers": 9,
        "d_id": 80457,
        "documentation": {
            "docstring": "A single step of the distributed execution on a replica.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 212715,
        "commit_id": "992c5db3bcde5d735b0d00af66d9accfa25a1da7",
        "repo": "PySimpleGUI",
        "path": "PySimpleGUI.py",
        "file_name": "PySimpleGUI.py",
        "fun_name": "perform_long_operation",
        "commit_message": "Updated Window.perform_long_operation docstring to warn that Threads are used",
        "code": "def perform_long_operation(self, func, end_key):\n        \n\n        thread = threading.Thread(target=_long_func_thread, args=(self, end_key, func), daemon=True)\n        thread.start()\n        return thread\n",
        "url": "https://github.com/PySimpleGUI/PySimpleGUI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 41,
        "n_ast_nodes": 62,
        "n_identifiers": 12,
        "d_id": 53360,
        "documentation": {
            "docstring": "\n        Call your function that will take a long time to execute.  When it's complete, send an event\n        specified by the end_key.\n        This is a way for you to \"ease into\" threading without learning the details of threading.\n        Your function will run, and when it returns 2 things will happen:\n        1. The value you provide for end_key will be returned to you when you call window.read()\n        2. If your function returns a value, then the value returned will also be included in your windows.read call in the values dictionary\n\n        IMPORTANT - This method uses THREADS... this means you CANNOT make any PySimpleGUI calls from\n        the function you provide with the exception of one function, Window.write_event_value.\n\n\n        :param func:    A lambda or a function name with no parms\n        :type func:     Any\n        :param end_key: The key that will be generated when the function returns\n        :type end_key:  (Any)\n        :return:        The id of the thread\n        :rtype:         threading.Thread\n        ",
            "n_words": 151,
            "vocab_size": 99,
            "n_whitespaces": 281,
            "language": "en"
        }
    },
    {
        "id": 10586,
        "commit_id": "6f22e6824cbe9e95528e53e0613d5b1babd4af8e",
        "repo": "jina",
        "path": "jina/parsers/peapods/pod.py",
        "file_name": "pod.py",
        "fun_name": "mixin_base_pod_parser",
        "commit_message": "refactor: take out peas hosts from cli (#4171)",
        "code": "def mixin_base_pod_parser(parser):\n    \n    gp = add_arg_group(parser, title='Pod')\n\n    gp.add_argument(\n        '--uses-before',\n        type=str,\n        help='The executor attached after the Peas described by --uses, typically before sending to all '\n        'shards, accepted type follows `--uses`',\n    )\n    gp.add_argument(\n        '--uses-after',\n        type=str,\n        help='The executor attached after the Peas described by --uses, typically used for receiving from '\n        'all shards, accepted type follows `--uses`',\n    )\n\n    gp.add_argument(\n        '--external',\n        action='store_true',\n        default=False,\n        help='The Pod will be considered an external Pod that has been started independently from the Flow.'\n        'This Pod will not be context managed by the Flow.',\n    )\n\n    # hidden CLI used for internal only\n\n    gp.add_argument(\n        '--pod-role',\n        type=PodRoleType.from_string,\n        choices=list(PodRoleType),\n        help='The role of this pod in the flow'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 276,
        "n_words": 110,
        "vocab_size": 75,
        "complexity": 2,
        "nloc": 37,
        "token_counts": 117,
        "n_ast_nodes": 171,
        "n_identifiers": 18,
        "d_id": 1871,
        "documentation": {
            "docstring": "Add mixin arguments required by :class:`BasePod` into the given parser.\n\n    :param parser: the parser instance to which we add arguments\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 207849,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_cyclic",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_cyclic(self):\n        \n        one = '<li>Cyclic one: <a href=\"%s\">I am recursive</a>' % (\n            reverse(\"admin:admin_views_cyclicone_change\", args=(self.cy1.pk,)),\n        )\n        two = '<li>Cyclic two: <a href=\"%s\">I am recursive too</a>' % (\n            reverse(\"admin:admin_views_cyclictwo_change\", args=(self.cy2.pk,)),\n        )\n        response = self.client.get(\n            reverse(\"admin:admin_views_cyclicone_delete\", args=(self.cy1.pk,))\n        )\n\n        self.assertContains(response, one, 1)\n        self.assertContains(response, two, 1)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 137,
        "n_words": 41,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 94,
        "n_ast_nodes": 151,
        "n_identifiers": 13,
        "d_id": 52132,
        "documentation": {
            "docstring": "\n        Cyclic relationships should still cause each object to only be\n        listed once.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 244739,
        "commit_id": "96aa909c19dbe753852ac6dba13bbbc35329b99f",
        "repo": "mmdetection",
        "path": "tests/test_models/test_dense_heads/test_centernet_head.py",
        "file_name": "test_centernet_head.py",
        "fun_name": "test_center_head_loss",
        "commit_message": "[Refactor] CenterNet",
        "code": "def test_center_head_loss(self):\n        \n        s = 256\n        img_metas = [{'batch_input_shape': (s, s, 3)}]\n        test_cfg = dict(topK=100, max_per_img=100)\n        centernet_head = CenterNetHead(\n            num_classes=4, in_channels=1, feat_channels=4, test_cfg=test_cfg)\n\n        feat = [torch.rand(1, 1, s, s)]\n        center_out, wh_out, offset_out = centernet_head.forward(feat)\n        # Test that empty ground truth encourages the network to\n        # predict background\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.empty((0, 4))\n        gt_instances.labels = torch.LongTensor([])\n        empty_gt_losses = centernet_head.loss(center_out, wh_out, offset_out,\n                                              [gt_instances], img_metas)\n        loss_center = empty_gt_losses['loss_center_heatmap']\n        loss_wh = empty_gt_losses['loss_wh']\n        loss_offset = empty_gt_losses['loss_offset']\n        assert loss_center.item() > 0, 'loss_center should be non-zero'\n        assert loss_wh.item() == 0, (\n            'there should be no loss_wh when there are no true boxes')\n        assert loss_offset.item() == 0, (\n            'there should be no loss_offset when there are no true boxes')\n\n        # When truth is non-empty then both cls and box loss\n        # should be nonzero for random inputs\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.Tensor(\n            [[23.6667, 23.8757, 238.6326, 151.8874]])\n        gt_instances.labels = torch.LongTensor([2])\n        one_gt_losses = centernet_head.loss(center_out, wh_out, offset_out,\n                                            [gt_instances], img_metas)\n        loss_center = one_gt_losses['loss_center_heatmap']\n        loss_wh = one_gt_losses['loss_wh']\n        loss_offset = one_gt_losses['loss_offset']\n        assert loss_center.item() > 0, 'loss_center should be non-zero'\n        assert loss_wh.item() > 0, 'loss_wh should be non-zero'\n        assert loss_offset.item() > 0, 'loss_offset should be non-zero'\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 532,
        "n_words": 183,
        "vocab_size": 101,
        "complexity": 1,
        "nloc": 33,
        "token_counts": 295,
        "n_ast_nodes": 457,
        "n_identifiers": 34,
        "d_id": 70506,
        "documentation": {
            "docstring": "Tests center head loss when truth is empty and non-empty.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 223843,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/parser.py",
        "file_name": "parser.py",
        "fun_name": "parsebytes",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def parsebytes(self, text, headersonly=False):\n        \n        text = text.decode('ASCII', errors='surrogateescape')\n        return self.parser.parsestr(text, headersonly)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 35,
        "n_ast_nodes": 58,
        "n_identifiers": 8,
        "d_id": 57101,
        "documentation": {
            "docstring": "Create a message structure from a byte string.\n\n        Returns the root of the message structure.  Optional headersonly is a\n        flag specifying whether to stop parsing after reading the headers or\n        not.  The default is False, meaning it parses the entire contents of\n        the file.\n        ",
            "n_words": 44,
            "vocab_size": 35,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 148185,
        "commit_id": "de9e143938d2e551e973496e167297dcd166b3c8",
        "repo": "ray",
        "path": "rllib/policy/sample_batch.py",
        "file_name": "sample_batch.py",
        "fun_name": "shuffle",
        "commit_message": "[RLlib] Issue 23907: SampleBatch.shuffle does not flush intercepted_values dict (which it should). (#24005)",
        "code": "def shuffle(self) -> \"SampleBatch\":\n        \n\n        # Shuffling the data when we have `seq_lens` defined is probably\n        # a bad idea!\n        if self.get(SampleBatch.SEQ_LENS) is not None:\n            raise ValueError(\n                \"SampleBatch.shuffle not possible when your data has \"\n                \"`seq_lens` defined!\"\n            )\n\n        # Get a permutation over the single items once and use the same\n        # permutation for all the data (otherwise, data would become\n        # meaningless).\n        permutation = np.random.permutation(self.count)\n\n        self_as_dict = {k: v for k, v in self.items()}\n        shuffled = tree.map_structure(lambda v: v[permutation], self_as_dict)\n        self.update(shuffled)\n        # Flush cache such that intercepted values are recalculated after the\n        # shuffling.\n        self.intercepted_values = {}\n        return self\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 256,
        "n_words": 99,
        "vocab_size": 75,
        "complexity": 3,
        "nloc": 26,
        "token_counts": 86,
        "n_ast_nodes": 151,
        "n_identifiers": 19,
        "d_id": 34200,
        "documentation": {
            "docstring": "Shuffles the rows of this batch in-place.\n\n        Returns:\n            This very (now shuffled) SampleBatch.\n\n        Raises:\n            ValueError: If self[SampleBatch.SEQ_LENS] is defined.\n\n        Examples:\n            >>> from ray.rllib.policy.sample_batch import SampleBatch\n            >>> batch = SampleBatch({\"a\": [1, 2, 3, 4]})  # doctest: +SKIP\n            >>> print(batch.shuffle()) # doctest: +SKIP\n            {\"a\": [4, 1, 3, 2]}\n        ",
            "n_words": 46,
            "vocab_size": 39,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 176173,
        "commit_id": "dec723f072eb997a497a159dbe8674cd39999ee9",
        "repo": "networkx",
        "path": "networkx/generators/small.py",
        "file_name": "small.py",
        "fun_name": "frucht_graph",
        "commit_message": "Docstrings for the small.py module (#5240)\n\n* added description for the first 5 small graphs\r\n\r\n* modified descriptions based on comment and added description for two more functions\r\n\r\n* added doctrings to all the functions\r\n\r\n* Minor touchups.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def frucht_graph(create_using=None):\n    \n    G = cycle_graph(7, create_using)\n    G.add_edges_from(\n        [\n            [0, 7],\n            [1, 7],\n            [2, 8],\n            [3, 9],\n            [4, 9],\n            [5, 10],\n            [6, 10],\n            [7, 11],\n            [8, 11],\n            [8, 9],\n            [10, 11],\n        ]\n    )\n\n    G.name = \"Frucht Graph\"\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 191,
        "n_words": 38,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 96,
        "n_ast_nodes": 130,
        "n_identifiers": 6,
        "d_id": 41743,
        "documentation": {
            "docstring": "\n    Returns the Frucht Graph.\n\n    The Frucht Graph is the smallest cubical graph whose\n    automorphism group consists only of the identity element [1]_.\n    It has 12 nodes and 18 edges and no nontrivial symmetries.\n    It is planar and Hamiltonian [2]_.\n\n    Parameters\n    ----------\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Returns\n    -------\n    G : networkx Graph\n        Frucht Graph with 12 nodes and 18 edges\n\n    References\n    ----------\n    .. [1] https://en.wikipedia.org/wiki/Frucht_graph\n    .. [2] https://mathworld.wolfram.com/FruchtGraph.html\n\n    ",
            "n_words": 81,
            "vocab_size": 59,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 266742,
        "commit_id": "a06fa496d3f837cca3c437ab6e9858525633d147",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/commands/integration/cloud/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "managed",
        "commit_message": "ansible-test - Code cleanup and refactoring. (#77169)\n\n* Remove unnecessary PyCharm ignores.\r\n* Ignore intentional undefined attribute usage.\r\n* Add missing type hints. Fix existing type hints.\r\n* Fix docstrings and comments.\r\n* Use function to register completion handler.\r\n* Pass strings to display functions.\r\n* Fix CompositeAction handling of dest argument.\r\n* Use consistent types in expressions/assignments.\r\n* Use custom function to keep linters happy.\r\n* Add missing raise for custom exception.\r\n* Clean up key/value type handling in cloud plugins.\r\n* Use dataclass instead of dict for results.\r\n* Add custom type_guard function to check lists.\r\n* Ignore return type that can't be checked (yet).\r\n* Avoid changing types on local variables.",
        "code": "def managed(self):  # type: () -> bool\n        \n        return t.cast(bool, self._get_cloud_config(self._MANAGED))\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 25,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 22,
        "n_ast_nodes": 38,
        "n_identifiers": 7,
        "d_id": 78553,
        "documentation": {
            "docstring": "True if resources are managed by ansible-test, otherwise False.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 181816,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/base.py",
        "file_name": "base.py",
        "fun_name": "_combine_individual_stats",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def _combine_individual_stats(self, operator_count, cv_score, individual_stats):\n        \n        stats = deepcopy(\n            individual_stats\n        )  # Deepcopy, since the string reference to predecessor should be cloned\n        stats[\"operator_count\"] = operator_count\n        stats[\"internal_cv_score\"] = cv_score\n        return stats\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 83,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 32,
        "n_ast_nodes": 55,
        "n_identifiers": 7,
        "d_id": 43600,
        "documentation": {
            "docstring": "Combine the stats with operator count and cv score and preprare to be written to _evaluated_individuals\n\n        Parameters\n        ----------\n        operator_count: int\n            number of components in the pipeline\n        cv_score: float\n            internal cross validation score\n        individual_stats: dictionary\n            dict containing statistics about the individual. currently:\n            'generation': generation in which the individual was evaluated\n            'mutation_count': number of mutation operations applied to the individual and its predecessor cumulatively\n            'crossover_count': number of crossover operations applied to the individual and its predecessor cumulatively\n            'predecessor': string representation of the individual\n\n        Returns\n        -------\n        stats: dictionary\n            dict containing the combined statistics:\n            'operator_count': number of operators in the pipeline\n            'internal_cv_score': internal cross validation score\n            and all the statistics contained in the 'individual_stats' parameter\n        ",
            "n_words": 111,
            "vocab_size": 66,
            "n_whitespaces": 295,
            "language": "en"
        }
    },
    {
        "id": 165894,
        "commit_id": "41e423fd09df5817dcfa11f3aea111a5b1a2f98a",
        "repo": "pandas",
        "path": "pandas/core/arrays/interval.py",
        "file_name": "interval.py",
        "fun_name": "__arrow_array__",
        "commit_message": "REF: Create pandas/core/arrays/arrow (#46591)",
        "code": "def __arrow_array__(self, type=None):\n        \n        import pyarrow\n\n        from pandas.core.arrays.arrow._arrow_utils import ArrowIntervalType\n\n        try:\n            subtype = pyarrow.from_numpy_dtype(self.dtype.subtype)\n        except TypeError as err:\n            raise TypeError(\n                f\"Conversion to arrow with subtype '{self.dtype.subtype}' \"\n                \"is not supported\"\n            ) from err\n        interval_type = ArrowIntervalType(subtype, self.closed)\n        storage_array = pyarrow.StructArray.from_arrays(\n            [\n                pyarrow.array(self._left, type=subtype, from_pandas=True),\n                pyarrow.array(self._right, type=subtype, from_pandas=True),\n            ],\n            names=[\"left\", \"right\"],\n        )\n        mask = self.isna()\n        if mask.any():\n            # if there are missing values, set validity bitmap also on the array level\n            null_bitmap = pyarrow.array(~mask).buffers()[1]\n            storage_array = pyarrow.StructArray.from_buffers(\n                storage_array.type,\n                len(storage_array),\n                [null_bitmap],\n                children=[storage_array.field(0), storage_array.field(1)],\n            )\n\n        if type is not None:\n            if type.equals(interval_type.storage_type):\n                return storage_array\n            elif isinstance(type, ArrowIntervalType):\n                # ensure we have the same subtype and closed attributes\n                if not type.equals(interval_type):\n                    raise TypeError(\n                        \"Not supported to convert IntervalArray to type with \"\n                        f\"different 'subtype' ({self.dtype.subtype} vs {type.subtype}) \"\n                        f\"and 'closed' ({self.closed} vs {type.closed}) attributes\"\n                    )\n            else:\n                raise TypeError(\n                    f\"Not supported to convert IntervalArray to '{type}' type\"\n                )\n\n        return pyarrow.ExtensionArray.from_storage(interval_type, storage_array)\n\n    _interval_shared_docs[\n        \"to_tuples\"\n    ] = \n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 711,
        "n_words": 149,
        "vocab_size": 106,
        "complexity": 7,
        "nloc": 42,
        "token_counts": 249,
        "n_ast_nodes": 450,
        "n_identifiers": 40,
        "d_id": 39734,
        "documentation": {
            "docstring": "\n        Convert myself into a pyarrow Array.\n        \n        Return an %(return_type)s of tuples of the form (left, right).\n\n        Parameters\n        ----------\n        na_tuple : bool, default True\n            Returns NA as a tuple if True, ``(nan, nan)``, or just as the NA\n            value itself if False, ``nan``.\n\n        Returns\n        -------\n        tuples: %(return_type)s\n        %(examples)s\\\n        ",
            "n_words": 47,
            "vocab_size": 39,
            "n_whitespaces": 148,
            "language": "en"
        }
    },
    {
        "id": 222919,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/fancy_getopt.py",
        "file_name": "fancy_getopt.py",
        "fun_name": "getopt",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getopt(self, args=None, object=None):\n        \n        if args is None:\n            args = sys.argv[1:]\n        if object is None:\n            object = OptionDummy()\n            created_object = True\n        else:\n            created_object = False\n\n        self._grok_option_table()\n\n        short_opts = ' '.join(self.short_opts)\n        try:\n            opts, args = getopt.getopt(args, short_opts, self.long_opts)\n        except getopt.error as msg:\n            raise DistutilsArgError(msg)\n\n        for opt, val in opts:\n            if len(opt) == 2 and opt[0] == '-': # it's a short option\n                opt = self.short2long[opt[1]]\n            else:\n                assert len(opt) > 2 and opt[:2] == '--'\n                opt = opt[2:]\n\n            alias = self.alias.get(opt)\n            if alias:\n                opt = alias\n\n            if not self.takes_arg[opt]:     # boolean option?\n                assert val == '', \"boolean option can't have value\"\n                alias = self.negative_alias.get(opt)\n                if alias:\n                    opt = alias\n                    val = 0\n                else:\n                    val = 1\n\n            attr = self.attr_name[opt]\n            # The only repeating option at the moment is 'verbose'.\n            # It has a negative option -q quiet, which should set verbose = 0.\n            if val and self.repeat.get(attr) is not None:\n                val = getattr(object, attr, 0) + 1\n            setattr(object, attr, val)\n            self.option_order.append((opt, val))\n\n        # for opts\n        if created_object:\n            return args, object\n        else:\n            return args\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 660,
        "n_words": 171,
        "vocab_size": 101,
        "complexity": 14,
        "nloc": 40,
        "token_counts": 269,
        "n_ast_nodes": 437,
        "n_identifiers": 31,
        "d_id": 56808,
        "documentation": {
            "docstring": "Parse command-line options in args. Store as attributes on object.\n\n        If 'args' is None or not supplied, uses 'sys.argv[1:]'.  If\n        'object' is None or not supplied, creates a new OptionDummy\n        object, stores option values there, and returns a tuple (args,\n        object).  If 'object' is supplied, it is modified in place and\n        'getopt()' just returns 'args'; in both cases, the returned\n        'args' is a modified copy of the passed-in 'args' list, which\n        is left untouched.\n        ",
            "n_words": 74,
            "vocab_size": 51,
            "n_whitespaces": 132,
            "language": "en"
        }
    },
    {
        "id": 335484,
        "commit_id": "4261c3aadfc23ee5b123b80ab7d8680a013acb66",
        "repo": "diffusers",
        "path": "utils/custom_init_isort.py",
        "file_name": "custom_init_isort.py",
        "fun_name": "split_code_in_indented_blocks",
        "commit_message": "Make style",
        "code": "def split_code_in_indented_blocks(code, indent_level=\"\", start_prompt=None, end_prompt=None):\n    \n    # Let's split the code into lines and move to start_index.\n    index = 0\n    lines = code.split(\"\\n\")\n    if start_prompt is not None:\n        while not lines[index].startswith(start_prompt):\n            index += 1\n        blocks = [\"\\n\".join(lines[:index])]\n    else:\n        blocks = []\n\n    # We split into blocks until we get to the `end_prompt` (or the end of the block).\n    current_block = [lines[index]]\n    index += 1\n    while index < len(lines) and (end_prompt is None or not lines[index].startswith(end_prompt)):\n        if len(lines[index]) > 0 and get_indent(lines[index]) == indent_level:\n            if len(current_block) > 0 and get_indent(current_block[-1]).startswith(indent_level + \" \"):\n                current_block.append(lines[index])\n                blocks.append(\"\\n\".join(current_block))\n                if index < len(lines) - 1:\n                    current_block = [lines[index + 1]]\n                    index += 1\n                else:\n                    current_block = []\n            else:\n                blocks.append(\"\\n\".join(current_block))\n                current_block = [lines[index]]\n        else:\n            current_block.append(lines[index])\n        index += 1\n\n    # Adds current block if it's nonempty.\n    if len(current_block) > 0:\n        blocks.append(\"\\n\".join(current_block))\n\n    # Add final block after end_prompt if provided.\n    if end_prompt is not None and index < len(lines):\n        blocks.append(\"\\n\".join(lines[index:]))\n\n    return blocks\n\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 445,
        "n_words": 153,
        "vocab_size": 80,
        "complexity": 14,
        "nloc": 32,
        "token_counts": 284,
        "n_ast_nodes": 478,
        "n_identifiers": 15,
        "d_id": 120784,
        "documentation": {
            "docstring": "\n    Split `code` into its indented blocks, starting at `indent_level`. If provided, begins splitting after\n    `start_prompt` and stops at `end_prompt` (but returns what's before `start_prompt` as a first block and what's\n    after `end_prompt` as a last block, so `code` is always the same as joining the result of this function).\n    ",
            "n_words": 49,
            "vocab_size": 38,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 300692,
        "commit_id": "4e9bc9eaffd464f192d187a01771a86699b2f932",
        "repo": "core",
        "path": "tests/util/test_dt.py",
        "file_name": "test_dt.py",
        "fun_name": "test_find_next_time_expression_tenth_second_pattern_does_not_drift_entering_dst",
        "commit_message": "Small cleanups to find_next_time_expression and addition of tests (#71845)",
        "code": "def test_find_next_time_expression_tenth_second_pattern_does_not_drift_entering_dst():\n    \n    tz = dt_util.get_time_zone(\"America/Chicago\")\n    dt_util.set_default_time_zone(tz)\n    tenth_second_pattern = (None, None, \"10\")\n    # Entering DST, clocks go forward\n    test_time = datetime(2021, 3, 15, 2, 30, 0, tzinfo=tz, fold=0)\n    matching_hours, matching_minutes, matching_seconds = _get_matches(\n        *tenth_second_pattern\n    )\n    next_time = dt_util.find_next_time_expression_time(\n        test_time, matching_seconds, matching_minutes, matching_hours\n    )\n    assert next_time == datetime(2021, 3, 15, 2, 30, 10, tzinfo=tz)\n    prev_target = next_time\n    for i in range(1000):\n        next_target = dt_util.find_next_time_expression_time(\n            prev_target.replace(microsecond=999999) + timedelta(seconds=1),\n            matching_seconds,\n            matching_minutes,\n            matching_hours,\n        )\n        assert (next_target - prev_target).total_seconds() == 60\n        assert next_target.second == 10\n        prev_target = next_target\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 214,
        "n_words": 82,
        "vocab_size": 55,
        "complexity": 2,
        "nloc": 23,
        "token_counts": 159,
        "n_ast_nodes": 236,
        "n_identifiers": 26,
        "d_id": 99552,
        "documentation": {
            "docstring": "Test finding next time expression tenth second pattern does not drift entering dst.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 9954,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/types/request/data.py",
        "file_name": "data.py",
        "fun_name": "groundtruths",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def groundtruths(self) -> 'DocumentArray':\n            \n            return DocumentArray(self._content.groundtruths)\n\n    \n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 1803,
        "documentation": {
            "docstring": "Get the :class: `DocumentArray` with sequence `data.docs` as content.\n\n            .. # noqa: DAR201\n    :class:`DataRequest` is one of the **primitive data type** in Jina.\n\n    It offers a Pythonic interface to allow users access and manipulate\n    :class:`jina.jina_pb2.DataRequestProto` object without working with Protobuf itself.\n\n    A container for serialized :class:`jina_pb2.DataRequestProto` that only triggers deserialization\n    and decompression when receives the first read access to its member.\n\n    It overrides :meth:`__getattr__` to provide the same get/set interface as an\n    :class:`jina_pb2.DataRequestProto` object.\n\n    :param request: The request.\n    ",
            "n_words": 78,
            "vocab_size": 66,
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            "language": "en"
        }
    },
    {
        "id": 107477,
        "commit_id": "f156db08eee54d285ab0fb4e031e48d078ba6aa3",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_base.py",
        "file_name": "_base.py",
        "fun_name": "sharey",
        "commit_message": "DOC: More cleanup axes -> Axes",
        "code": "def sharey(self, other):\n        \n        _api.check_isinstance(_AxesBase, other=other)\n        if self._sharey is not None and other is not self._sharey:\n            raise ValueError(\"y-axis is already shared\")\n        self._shared_axes[\"y\"].join(self, other)\n        self._sharey = other\n        self.yaxis.major = other.yaxis.major  # Ticker instances holding\n        self.yaxis.minor = other.yaxis.minor  # locator and formatter.\n        y0, y1 = other.get_ylim()\n        self.set_ylim(y0, y1, emit=False, auto=other.get_autoscaley_on())\n        self.yaxis._scale = other.yaxis._scale\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 133,
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        "nloc": 11,
        "token_counts": 118,
        "n_ast_nodes": 188,
        "n_identifiers": 21,
        "d_id": 22766,
        "documentation": {
            "docstring": "\n        Share the y-axis with *other*.\n\n        This is equivalent to passing ``sharey=other`` when constructing the\n        Axes, and cannot be used if the y-axis is already being shared with\n        another Axes.\n        ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 256314,
        "commit_id": "a59bca366174d9c692fa19750c24d65f47660ef7",
        "repo": "haystack",
        "path": "test/benchmarks/nq_to_squad.py",
        "file_name": "nq_to_squad.py",
        "fun_name": "clean_text",
        "commit_message": "Apply black formatting (#2115)\n\n* Testing black on ui/\r\n\r\n* Applying black on docstores\r\n\r\n* Add latest docstring and tutorial changes\r\n\r\n* Create a single GH action for Black and docs to reduce commit noise to the minimum, slightly refactor the OpenAPI action too\r\n\r\n* Remove comments\r\n\r\n* Relax constraints on pydoc-markdown\r\n\r\n* Split temporary black from the docs. Pydoc-markdown was obsolete and needs a separate PR to upgrade\r\n\r\n* Fix a couple of bugs\r\n\r\n* Add a type: ignore that was missing somehow\r\n\r\n* Give path to black\r\n\r\n* Apply Black\r\n\r\n* Apply Black\r\n\r\n* Relocate a couple of type: ignore\r\n\r\n* Update documentation\r\n\r\n* Make Linux CI run after applying Black\r\n\r\n* Triggering Black\r\n\r\n* Apply Black\r\n\r\n* Remove dependency, does not work well\r\n\r\n* Remove manually double trailing commas\r\n\r\n* Update documentation\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def clean_text(start_token, end_token, doc_tokens, doc_bytes, ignore_final_whitespace=True):\n    \n    text = \"\"\n    for index in range(start_token, end_token):\n        token = doc_tokens[index]\n        if token[\"html_token\"]:\n            continue\n        text += token[\"token\"]\n        # Add a single space between two tokens iff there is at least one\n        # whitespace character between them (outside of an HTML tag). For example:\n        #\n        #   token1 token2                           ==> Add space.\n        #   token1</B> <B>token2                    ==> Add space.\n        #   token1</A>token2                        ==> No space.\n        #   token1<A href=\"...\" title=\"...\">token2  ==> No space.\n        #   token1<SUP>2</SUP>token2                ==> No space.\n        next_token = token\n        last_index = end_token if ignore_final_whitespace else end_token + 1\n        for next_token in doc_tokens[index + 1 : last_index]:\n            if not next_token[\"html_token\"]:\n                break\n        chars = doc_bytes[token[\"end_byte\"] : next_token[\"start_byte\"]].decode(\"utf-8\")\n        # Since some HTML tags are missing from the token list, we count '<' and\n        # '>' to detect if we're inside a tag.\n        unclosed_brackets = 0\n        for char in chars:\n            if char == \"<\":\n                unclosed_brackets += 1\n            elif char == \">\":\n                unclosed_brackets -= 1\n            elif unclosed_brackets == 0 and re.match(r\"\\s\", char):\n                # Add a single space after this token.\n                text += \" \"\n                break\n    return text\n\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 559,
        "n_words": 175,
        "vocab_size": 107,
        "complexity": 11,
        "nloc": 23,
        "token_counts": 144,
        "n_ast_nodes": 250,
        "n_identifiers": 18,
        "d_id": 74866,
        "documentation": {
            "docstring": "Remove HTML tags from a text span and reconstruct proper spacing.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 126972,
        "commit_id": "0dceddb912ed92286032b5563dd2e541a8a7031f",
        "repo": "ray",
        "path": "rllib/algorithms/simple_q/tests/test_simple_q.py",
        "file_name": "test_simple_q.py",
        "fun_name": "test_simple_q_compilation",
        "commit_message": "[RLlib] Move learning_starts logic from buffers into `training_step()`. (#26032)",
        "code": "def test_simple_q_compilation(self):\n        \n        # Run locally and with compression\n        config = (\n            simple_q.SimpleQConfig()\n            .rollouts(num_rollout_workers=0, compress_observations=True)\n            .training(num_steps_sampled_before_learning_starts=0)\n        )\n\n        num_iterations = 2\n\n        for _ in framework_iterator(config, with_eager_tracing=True):\n            trainer = config.build(env=\"CartPole-v0\")\n            rw = trainer.workers.local_worker()\n            for i in range(num_iterations):\n                sb = rw.sample()\n                assert sb.count == config.rollout_fragment_length\n                results = trainer.train()\n                check_train_results(results)\n                print(results)\n\n            check_compute_single_action(trainer)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 241,
        "n_words": 47,
        "vocab_size": 40,
        "complexity": 3,
        "nloc": 17,
        "token_counts": 109,
        "n_ast_nodes": 180,
        "n_identifiers": 31,
        "d_id": 28323,
        "documentation": {
            "docstring": "Test whether SimpleQ can be built on all frameworks.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 22954,
        "commit_id": "a323fce66dd68a881cf599526185b52ab5df356b",
        "repo": "PaddleOCR",
        "path": "tools/program.py",
        "file_name": "program.py",
        "fun_name": "load_config",
        "commit_message": "vqa code integrated into ppocr training system",
        "code": "def load_config(file_path):\n    \n    _, ext = os.path.splitext(file_path)\n    assert ext in ['.yml', '.yaml'], \"only support yaml files for now\"\n    config = yaml.load(open(file_path, 'rb'), Loader=yaml.Loader)\n    return config\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 39,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 49,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 4491,
        "documentation": {
            "docstring": "\n    Load config from yml/yaml file.\n    Args:\n        file_path (str): Path of the config file to be loaded.\n    Returns: global config\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 136000,
        "commit_id": "e707ce4fb3717e3c05118c57f503dfbd03552ca9",
        "repo": "ray",
        "path": "rllib/evaluation/worker_set.py",
        "file_name": "worker_set.py",
        "fun_name": "_get_spaces_from_remote_worker",
        "commit_message": "[RLlib] Refactor `WorkerSet` on top of `FaultTolerantActorManager`. (#29938)\n\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def _get_spaces_from_remote_worker(self):\n        \n        # Get ID of the first remote worker.\n        worker_id = next(iter(self.__worker_manager.actors().keys()))\n\n        # Try to figure out spaces from the first remote worker.\n        remote_spaces = self.foreach_worker(\n            lambda worker: worker.foreach_policy(\n                lambda p, pid: (pid, p.observation_space, p.action_space)\n            ),\n            remote_worker_indices=[worker_id],\n            local_worker=False,\n        )\n        if not remote_spaces:\n            raise ValueError(\n                \"Could not get observation and action spaces from remote \"\n                \"worker. Maybe specify them manually in the config?\"\n            )\n        spaces = {\n            e[0]: (getattr(e[1], \"original_space\", e[1]), e[2])\n            for e in remote_spaces[0]\n        }\n\n        # Try to add the actual env's obs/action spaces.\n        env_spaces = self.foreach_worker(\n            lambda worker: worker.foreach_env(\n                lambda env: (env.observation_space, env.action_space)\n            ),\n            remote_worker_indices=[worker_id],\n            local_worker=False,\n        )\n        if env_spaces:\n            # env_spaces group spaces by environment then worker.\n            # So need to unpack thing twice.\n            spaces[\"__env__\"] = env_spaces[0][0]\n\n        logger.info(\n            \"Inferred observation/action spaces from remote \"\n            f\"worker (local worker has no env): {spaces}\"\n        )\n\n        return spaces\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 496,
        "n_words": 137,
        "vocab_size": 94,
        "complexity": 4,
        "nloc": 32,
        "token_counts": 177,
        "n_ast_nodes": 286,
        "n_identifiers": 27,
        "d_id": 30791,
        "documentation": {
            "docstring": "Infer observation and action spaces from a remote worker.\n\n        Returns:\n            A dict mapping from policy ids to spaces.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 247931,
        "commit_id": "d666fc02fab7421efb39a33800a83791f88bf9b2",
        "repo": "synapse",
        "path": "tests/test_phone_home.py",
        "file_name": "test_phone_home.py",
        "fun_name": "test_performance_frozen_clock",
        "commit_message": "Add type hints to some tests files (#12371)",
        "code": "def test_performance_frozen_clock(self) -> None:\n        \n        past_stats = [\n            (self.hs.get_clock().time(), resource.getrusage(resource.RUSAGE_SELF))\n        ]\n        stats: JsonDict = {}\n        self.get_success(phone_stats_home(self.hs, stats, past_stats))\n        self.assertEqual(stats[\"cpu_average\"], 0)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 72,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 66,
        "n_ast_nodes": 107,
        "n_identifiers": 14,
        "d_id": 71999,
        "documentation": {
            "docstring": "\n        If time doesn't move, don't error out.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 149690,
        "commit_id": "b58e811b1486ae62e835cbea3e40cf88128243a0",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/trade_model.py",
        "file_name": "trade_model.py",
        "fun_name": "get_trades",
        "commit_message": "Move trade/order Models to their own class",
        "code": "def get_trades(trade_filter=None) -> Query:\n        \n        if not Trade.use_db:\n            raise NotImplementedError('`Trade.get_trades()` not supported in backtesting mode.')\n        if trade_filter is not None:\n            if not isinstance(trade_filter, list):\n                trade_filter = [trade_filter]\n            return Trade.query.filter(*trade_filter)\n        else:\n            return Trade.query\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 118,
        "n_words": 31,
        "vocab_size": 24,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 57,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 34484,
        "documentation": {
            "docstring": "\n        Helper function to query Trades using filters.\n        NOTE: Not supported in Backtesting.\n        :param trade_filter: Optional filter to apply to trades\n                             Can be either a Filter object, or a List of filters\n                             e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`\n                             e.g. `(trade_filter=Trade.id == trade_id)`\n        :return: unsorted query object\n        ",
            "n_words": 44,
            "vocab_size": 38,
            "n_whitespaces": 164,
            "language": "en"
        }
    },
    {
        "id": 279394,
        "commit_id": "be73ac1a1e25d9abd4d793cba9707098d7adf231",
        "repo": "keras",
        "path": "keras/datasets/boston_housing.py",
        "file_name": "boston_housing.py",
        "fun_name": "load_data",
        "commit_message": "Add f-string format and lint with flynt on the whole codebase",
        "code": "def load_data(path=\"boston_housing.npz\", test_split=0.2, seed=113):\n    \n    assert 0 <= test_split < 1\n    origin_folder = (\n        \"https://storage.googleapis.com/tensorflow/tf-keras-datasets/\"\n    )\n    path = get_file(\n        path,\n        origin=origin_folder + \"boston_housing.npz\",\n        file_hash=(  # noqa: E501\n            \"f553886a1f8d56431e820c5b82552d9d95cfcb96d1e678153f8839538947dff5\"\n        ),\n    )\n    with np.load(path, allow_pickle=True) as f:\n        x = f[\"x\"]\n        y = f[\"y\"]\n\n    rng = np.random.RandomState(seed)\n    indices = np.arange(len(x))\n    rng.shuffle(indices)\n    x = x[indices]\n    y = y[indices]\n\n    x_train = np.array(x[: int(len(x) * (1 - test_split))])\n    y_train = np.array(y[: int(len(x) * (1 - test_split))])\n    x_test = np.array(x[int(len(x) * (1 - test_split)) :])\n    y_test = np.array(y[int(len(x) * (1 - test_split)) :])\n    return (x_train, y_train), (x_test, y_test)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 202,
        "n_words": 90,
        "vocab_size": 63,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 221,
        "n_ast_nodes": 354,
        "n_identifiers": 27,
        "d_id": 82968,
        "documentation": {
            "docstring": "Loads the Boston Housing dataset.\n\n    This is a dataset taken from the StatLib library which is maintained at\n    Carnegie Mellon University.\n\n    **WARNING:** This dataset has an ethical problem: the authors of this\n    dataset included a variable, \"B\", that may appear to assume that racial\n    self-segregation influences house prices. As such, we strongly discourage\n    the use of this dataset, unless in the context of illustrating ethical\n    issues in data science and machine learning.\n\n    Samples contain 13 attributes of houses at different locations around the\n    Boston suburbs in the late 1970s. Targets are the median values of\n    the houses at a location (in k$).\n\n    The attributes themselves are defined in the\n    [StatLib website](http://lib.stat.cmu.edu/datasets/boston).\n\n    Args:\n      path: path where to cache the dataset locally\n          (relative to `~/.keras/datasets`).\n      test_split: fraction of the data to reserve as test set.\n      seed: Random seed for shuffling the data\n          before computing the test split.\n\n    Returns:\n      Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.\n\n    **x_train, x_test**: numpy arrays with shape `(num_samples, 13)`\n      containing either the training samples (for x_train),\n      or test samples (for y_train).\n\n    **y_train, y_test**: numpy arrays of shape `(num_samples,)` containing the\n      target scalars. The targets are float scalars typically between 10 and\n      50 that represent the home prices in k$.\n    ",
            "n_words": 202,
            "vocab_size": 142,
            "n_whitespaces": 311,
            "language": "en"
        }
    },
    {
        "id": 299745,
        "commit_id": "ea456893f94c7dc88b0cc28f92dadf240fbb1fe7",
        "repo": "core",
        "path": "tests/components/androidtv/test_media_player.py",
        "file_name": "test_media_player.py",
        "fun_name": "test_androidtv_select_source_overridden_app_name",
        "commit_message": "Review AndroidTV tests for media player entity (#71168)",
        "code": "async def test_androidtv_select_source_overridden_app_name(hass):\n    \n    # Evidence that the default YouTube app ID will be overridden\n    conf_apps = {\n        \"com.youtube.test\": \"YouTube\",\n    }\n    assert \"YouTube\" in ANDROIDTV_APPS.values()\n    assert \"com.youtube.test\" not in ANDROIDTV_APPS\n    await _test_select_source(\n        hass,\n        CONFIG_ANDROIDTV_PYTHON_ADB,\n        conf_apps,\n        \"YouTube\",\n        \"com.youtube.test\",\n        patchers.PATCH_LAUNCH_APP,\n    )\n\n\n@pytest.mark.parametrize(\n    [\"source\", \"expected_arg\", \"method_patch\"],\n    [\n        (\"com.app.test1\", \"com.app.test1\", patchers.PATCH_LAUNCH_APP),\n        (\"TEST 1\", \"com.app.test1\", patchers.PATCH_LAUNCH_APP),\n        (\"com.app.test2\", \"com.app.test2\", patchers.PATCH_LAUNCH_APP),\n        (\"com.app.test3\", \"com.app.test3\", patchers.PATCH_LAUNCH_APP),\n        (\"!com.app.test1\", \"com.app.test1\", patchers.PATCH_STOP_APP),\n        (\"!TEST 1\", \"com.app.test1\", patchers.PATCH_STOP_APP),\n        (\"!com.app.test2\", \"com.app.test2\", patchers.PATCH_STOP_APP),\n        (\"!com.app.test3\", \"com.app.test3\", patchers.PATCH_STOP_APP),\n    ],\n)",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    [\"source\", \"expected_arg\", \"method_patch\"],\n    [\n        (\"com.app.test1\", \"com.app.test1\", patchers.PATCH_LAUNCH_APP),\n        (\"TEST 1\", \"com.app.test1\", patchers.PATCH_LAUNCH_APP),\n        (\"com.app.test2\", \"com.app.test2\", patchers.PATCH_LAUNCH_APP),\n        (\"com.app.test3\", \"com.app.test3\", patchers.PATCH_LAUNCH_APP),\n        (\"!com.app.test1\", \"com.app.test1\", patchers.PATCH_STOP_APP),\n        (\"!TEST 1\", \"com.app.test1\", patchers.PATCH_STOP_APP),\n        (\"!com.app.test2\", \"com.app.test2\", patchers.PATCH_STOP_APP),\n        (\"!com.app.test3\", \"com.app.test3\", patchers.PATCH_STOP_APP),\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 207,
        "n_words": 71,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 45,
        "n_ast_nodes": 243,
        "n_identifiers": 13,
        "d_id": 98649,
        "documentation": {
            "docstring": "Test that when an app name is overridden via the `apps` configuration parameter, the app is launched correctly.",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 73068,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/forms/views.py",
        "file_name": "views.py",
        "fun_name": "to_row_dict",
        "commit_message": "Reformat with black",
        "code": "def to_row_dict(self, item):\n        \n        row_dict = OrderedDict(\n            (field, item.get_data().get(field)) for field in self.list_export\n        )\n        return row_dict\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 35,
        "n_ast_nodes": 56,
        "n_identifiers": 9,
        "d_id": 15939,
        "documentation": {
            "docstring": "Orders the submission dictionary for spreadsheet writing",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 101721,
        "commit_id": "e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1",
        "repo": "faceswap",
        "path": "tools/alignments/jobs.py",
        "file_name": "jobs.py",
        "fun_name": "_get_multi_faces",
        "commit_message": "Alignments Tool - Typing, Documentation + Re-org",
        "code": "def _get_multi_faces(self) -> Union[Generator[str, None, None],\n                                        Generator[Tuple[str, int], None, None]]:\n        \n        process_type = getattr(self, f\"_get_multi_faces_{self._type}\")\n        for item in process_type():\n            yield item\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 91,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 31,
        "n_ast_nodes": 80,
        "n_identifiers": 11,
        "d_id": 21125,
        "documentation": {
            "docstring": " yield each frame or face that has multiple faces matched in alignments file\n\n        Yields\n        ------\n        str or tuple\n            The frame name of any frames which have multiple faces and potentially the face id\n        ",
            "n_words": 33,
            "vocab_size": 28,
            "n_whitespaces": 73,
            "language": "en"
        }
    },
    {
        "id": 299337,
        "commit_id": "6151306e3d8f0bc774145280276a1801613f8aa7",
        "repo": "core",
        "path": "homeassistant/components/sonos/media_player.py",
        "file_name": "media_player.py",
        "fun_name": "group_members",
        "commit_message": "Use standard attribute for Sonos group members (#70924)",
        "code": "def group_members(self) -> list[str] | None:\n        \n        return self.speaker.sonos_group_entities\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 32,
        "n_identifiers": 6,
        "d_id": 98271,
        "documentation": {
            "docstring": "List of entity_ids which are currently grouped together.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 39033,
        "commit_id": "dbf7ed08d36b4c77e5455c2c3ba165d6308aeaaf",
        "repo": "recommenders",
        "path": "recommenders/models/rbm/rbm.py",
        "file_name": "rbm.py",
        "fun_name": "losses",
        "commit_message": "update loss function documentation",
        "code": "def losses(self, vv):\n        \n\n        with tf.compat.v1.variable_scope(\"losses\"):\n            obj = self.free_energy(vv) - self.free_energy(self.v_k)\n\n        return obj\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 44,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 68,
        "n_identifiers": 10,
        "d_id": 7088,
        "documentation": {
            "docstring": "Calculate contrastive divergence, which is the difference between\n        the free energy clamped on the data (v) and the model Free energy (v_k).\n\n        Args:\n            vv (tf.Tensor, float32): empirical input\n\n        Returns:\n            obj: contrastive divergence\n        ",
            "n_words": 32,
            "vocab_size": 27,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 107623,
        "commit_id": "924d7c7f9900d8839e66616791121237101e7b57",
        "repo": "matplotlib",
        "path": "lib/matplotlib/offsetbox.py",
        "file_name": "offsetbox.py",
        "fun_name": "update_positions",
        "commit_message": "Cleanup AnnotationBbox.\n\nInline _update_position_xybox into update_positions.  Avoid unpacking\nx,y pairs where unnecessary.  Don't bother copying arrowprops, as we\ndon't actually modify it.  Reuse mutation scale for both patch and\narrow.  Clarify the doc for frameon.  Various small extra cleanups.",
        "code": "def update_positions(self, renderer):\n        \n\n        x, y = self.xybox\n        if isinstance(self.boxcoords, tuple):\n            xcoord, ycoord = self.boxcoords\n            x1, y1 = self._get_xy(renderer, x, y, xcoord)\n            x2, y2 = self._get_xy(renderer, x, y, ycoord)\n            ox0, oy0 = x1, y2\n        else:\n            ox0, oy0 = self._get_xy(renderer, x, y, self.boxcoords)\n\n        w, h, xd, yd = self.offsetbox.get_extent(renderer)\n        fw, fh = self._box_alignment\n        self.offsetbox.set_offset((ox0 - fw * w + xd, oy0 - fh * h + yd))\n\n        bbox = self.offsetbox.get_window_extent(renderer)\n        self.patch.set_bounds(bbox.bounds)\n\n        mutation_scale = renderer.points_to_pixels(self.get_fontsize())\n        self.patch.set_mutation_scale(mutation_scale)\n\n        if self.arrowprops:\n            # Use FancyArrowPatch if self.arrowprops has \"arrowstyle\" key.\n\n            # Adjust the starting point of the arrow relative to the textbox.\n            # TODO: Rotation needs to be accounted.\n            arrow_begin = bbox.p0 + bbox.size * self._arrow_relpos\n            arrow_end = self._get_position_xy(renderer)\n            # The arrow (from arrow_begin to arrow_end) will be first clipped\n            # by patchA and patchB, then shrunk by shrinkA and shrinkB (in\n            # points).  If patch A is not set, self.bbox_patch is used.\n            self.arrow_patch.set_positions(arrow_begin, arrow_end)\n\n            if \"mutation_scale\" in self.arrowprops:\n                mutation_scale = renderer.points_to_pixels(\n                    self.arrowprops[\"mutation_scale\"])\n                # Else, use fontsize-based mutation_scale defined above.\n            self.arrow_patch.set_mutation_scale(mutation_scale)\n\n            patchA = self.arrowprops.get(\"patchA\", self.patch)\n            self.arrow_patch.set_patchA(patchA)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 501,
        "n_words": 169,
        "vocab_size": 113,
        "complexity": 4,
        "nloc": 26,
        "token_counts": 264,
        "n_ast_nodes": 418,
        "n_identifiers": 49,
        "d_id": 22838,
        "documentation": {
            "docstring": "\n        Update pixel positions for the annotated point, the text and the arrow.\n        ",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 289810,
        "commit_id": "dbfca8def81b6aac9b4bd0a494c96a0b15f1a82c",
        "repo": "core",
        "path": "tests/components/aws/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_events_service_call",
        "commit_message": "Add support for EventBridge to aws integration (#77573)\n\n* Added EventBridge support to aws integration\r\n\r\n* Added type hints for all aws notification services + Added unit tests for EventBridge AWS integration\r\n\r\n* Increase line coverage for unit tests for aws integration.",
        "code": "async def test_events_service_call(hass):\n    \n    mock_session = MockAioSession()\n    with async_patch(\n        \"homeassistant.components.aws.AioSession\", return_value=mock_session\n    ):\n        await async_setup_component(\n            hass,\n            \"aws\",\n            {\n                \"aws\": {\n                    \"notify\": [\n                        {\n                            \"service\": \"events\",\n                            \"name\": \"Events Test\",\n                            \"region_name\": \"us-east-1\",\n                        }\n                    ]\n                }\n            },\n        )\n        await hass.async_block_till_done()\n\n    assert hass.services.has_service(\"notify\", \"events_test\") is True\n\n    mock_session.put_events.return_value = {\n        \"Entries\": [{\"EventId\": \"\", \"ErrorCode\": 0, \"ErrorMessage\": \"test-error\"}]\n    }\n\n    await hass.services.async_call(\n        \"notify\",\n        \"events_test\",\n        {\n            \"message\": \"test\",\n            \"target\": \"ARN\",\n            \"data\": {},\n        },\n        blocking=True,\n    )\n\n    mock_session.put_events.assert_called_once_with(\n        Entries=[\n            {\n                \"EventBusName\": \"ARN\",\n                \"Detail\": json.dumps({\"message\": \"test\"}),\n                \"DetailType\": \"\",\n                \"Source\": \"homeassistant\",\n                \"Resources\": [],\n            }\n        ]\n    )\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 568,
        "n_words": 82,
        "vocab_size": 65,
        "complexity": 1,
        "nloc": 46,
        "token_counts": 173,
        "n_ast_nodes": 328,
        "n_identifiers": 17,
        "d_id": 88945,
        "documentation": {
            "docstring": "Test events service (EventBridge) call works as expected.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 182900,
        "commit_id": "a72e347ed99333a090377ee438eaf63477cbf98b",
        "repo": "textual",
        "path": "src/textual/devtools/service.py",
        "file_name": "service.py",
        "fun_name": "_consume_incoming",
        "commit_message": "Seperate server and client handling logic into classes for devtools",
        "code": "async def _consume_incoming(self) -> None:\n        \n        while True:\n            message_json = await self.incoming_queue.get()\n            if message_json is None:\n                self.incoming_queue.task_done()\n                break\n\n            type = message_json[\"type\"]\n            if type == \"client_log\":\n                path = message_json[\"payload\"][\"path\"]\n                line_number = message_json[\"payload\"][\"line_number\"]\n                timestamp = message_json[\"payload\"][\"timestamp\"]\n                encoded_segments = message_json[\"payload\"][\"encoded_segments\"]\n                decoded_segments = base64.b64decode(encoded_segments)\n                segments = pickle.loads(decoded_segments)\n                self.service.console.print(\n                    DevtoolsLogMessage(\n                        segments=segments,\n                        path=path,\n                        line_number=line_number,\n                        unix_timestamp=timestamp,\n                    )\n                )\n            elif type == \"client_spillover\":\n                spillover = int(message_json[\"payload\"][\"spillover\"])\n                info_renderable = DevtoolsInternalMessage(\n                    f\"Discarded {spillover} messages\", level=\"warning\"\n                )\n                self.service.console.print(info_renderable)\n            self.incoming_queue.task_done()\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 506,
        "n_words": 67,
        "vocab_size": 49,
        "complexity": 5,
        "nloc": 32,
        "token_counts": 170,
        "n_ast_nodes": 299,
        "n_identifiers": 27,
        "d_id": 44000,
        "documentation": {
            "docstring": "Consume messages from the incoming (client -> server) Queue, and print\n        the corresponding renderables to the console for each message.\n        ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 61064,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/resolution/legacy/resolver.py",
        "file_name": "resolver.py",
        "fun_name": "resolve",
        "commit_message": "upd; format",
        "code": "def resolve(self, root_reqs, check_supported_wheels):\n        # type: (List[InstallRequirement], bool) -> RequirementSet\n        \n        requirement_set = RequirementSet(check_supported_wheels=check_supported_wheels)\n        for req in root_reqs:\n            if req.constraint:\n                check_invalid_constraint_type(req)\n            requirement_set.add_requirement(req)\n\n        # Actually prepare the files, and collect any exceptions. Most hash\n        # exceptions cannot be checked ahead of time, because\n        # _populate_link() needs to be called before we can make decisions\n        # based on link type.\n        discovered_reqs = []  # type: List[InstallRequirement]\n        hash_errors = HashErrors()\n        for req in chain(requirement_set.all_requirements, discovered_reqs):\n            try:\n                discovered_reqs.extend(self._resolve_one(requirement_set, req))\n            except HashError as exc:\n                exc.req = req\n                hash_errors.append(exc)\n\n        if hash_errors:\n            raise hash_errors\n\n        return requirement_set\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 295,
        "n_words": 88,
        "vocab_size": 71,
        "complexity": 6,
        "nloc": 17,
        "token_counts": 97,
        "n_ast_nodes": 163,
        "n_identifiers": 20,
        "d_id": 12406,
        "documentation": {
            "docstring": "Resolve what operations need to be done\n\n        As a side-effect of this method, the packages (and their dependencies)\n        are downloaded, unpacked and prepared for installation. This\n        preparation is done by ``pip.operations.prepare``.\n\n        Once PyPI has static dependency metadata available, it would be\n        possible to move the preparation to become a step separated from\n        dependency resolution.\n        ",
            "n_words": 54,
            "vocab_size": 46,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 308485,
        "commit_id": "457ce195dd9758cc7916d0cf1786948a10ef8135",
        "repo": "core",
        "path": "tests/components/mqtt/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "test_convert_outgoing_payload",
        "commit_message": "Add mqtt entity attributes command templates (#61937)\n\n* Add entity variables to MqttCommandTemplate\r\n\r\n* missing command template update\r\n\r\n* make hass and entity conditional parameters\r\n\r\n* Add encoding support for publishing\r\n\r\n* Revert \"Add encoding support for publishing\"\r\n\r\nThis reverts commit b69b9c60ececdab1d35621bdd7ffe5b8b9d59c44.",
        "code": "async def test_convert_outgoing_payload(hass):\n    \n    command_template = mqtt.MqttCommandTemplate(None, hass=hass)\n    assert command_template.async_render(b\"\\xde\\xad\\xbe\\xef\") == b\"\\xde\\xad\\xbe\\xef\"\n\n    assert (\n        command_template.async_render(\"b'\\\\xde\\\\xad\\\\xbe\\\\xef'\")\n        == \"b'\\\\xde\\\\xad\\\\xbe\\\\xef'\"\n    )\n\n    assert command_template.async_render(1234) == 1234\n\n    assert command_template.async_render(1234.56) == 1234.56\n\n    assert command_template.async_render(None) is None\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 67,
        "n_words": 29,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 71,
        "n_ast_nodes": 129,
        "n_identifiers": 6,
        "d_id": 107239,
        "documentation": {
            "docstring": "Test the converting of outgoing MQTT payloads without template.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 86663,
        "commit_id": "4d9743df1cadba2b3dd8055f05c76e6e5fae3c4d",
        "repo": "sentry",
        "path": "tests/sentry/release_health/test_metrics_sessions_v2.py",
        "file_name": "test_metrics_sessions_v2.py",
        "fun_name": "test_sessions_metrics_equal_num_keys",
        "commit_message": "fix(metrics): Fix flaky test [TET-387] (#39742)\n\nThis PR aims at fixing the flakiness reproduced\r\n[here](https://sentry.io/organizations/sentry/issues/3070580114/?project=2423079&query=is:unresolved+test_sessions_metrics_equal_num_keys&statsPeriod=14d).",
        "code": "def test_sessions_metrics_equal_num_keys(self):\n        \n        interval_days_int = 1\n        interval_days = f\"{interval_days_int}d\"\n\n        groupbyes = _session_groupby_powerset()\n\n        for groupby in groupbyes:\n            with patch(\n                \"sentry.api.endpoints.organization_sessions.release_health\",\n                SessionsReleaseHealthBackend(),\n            ):\n                sessions_data = result_sorted(self.get_sessions_data(groupby, interval_days))\n\n            with patch(\n                \"sentry.api.endpoints.organization_sessions.release_health\",\n                MetricsReleaseHealthBackend(),\n            ):\n                metrics_data = result_sorted(self.get_sessions_data(groupby, interval_days))\n\n            errors = compare_results(\n                sessions=sessions_data,\n                metrics=metrics_data,\n                rollup=interval_days_int * 24 * 60 * 60,  # days to seconds\n            )\n            assert len(errors) == 0\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 302,
        "n_words": 54,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 21,
        "token_counts": 101,
        "n_ast_nodes": 172,
        "n_identifiers": 20,
        "d_id": 18144,
        "documentation": {
            "docstring": "\n        Tests whether the number of keys in the metrics implementation of\n        sessions data is the same as in the sessions implementation.\n\n        ",
            "n_words": 21,
            "vocab_size": 15,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 269479,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "stop_gradient",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def stop_gradient(variables):\n    \n    if isinstance(variables, (list, tuple)):\n        return map(tf.stop_gradient, variables)\n    return tf.stop_gradient(variables)\n\n\n# CONTROL FLOW\n\n\n@keras_export(\"keras.backend.rnn\")\n@tf.__internal__.dispatch.add_dispatch_support",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.rnn\")\n@tf.__internal__.dispatch.add_dispatch_support",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 29,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 78,
        "n_identifiers": 11,
        "d_id": 80112,
        "documentation": {
            "docstring": "Returns `variables` but with zero gradient w.r.t. every other variable.\n\n    Args:\n        variables: Tensor or list of tensors to consider constant with respect\n          to any other variable.\n\n\n    Returns:\n        A single tensor or a list of tensors (depending on the passed argument)\n        that has no gradient with respect to any other variable.\n    ",
            "n_words": 50,
            "vocab_size": 35,
            "n_whitespaces": 89,
            "language": "en"
        }
    },
    {
        "id": 250016,
        "commit_id": "acea4d7a2ff61b5beda420b54a8451088060a8cd",
        "repo": "synapse",
        "path": "tests/util/test_stream_change_cache.py",
        "file_name": "test_stream_change_cache.py",
        "fun_name": "test_max_pos",
        "commit_message": "Add missing types to tests.util. (#14597)\n\nRemoves files under tests.util from the ignored by list, then\r\nfully types all tests/util/*.py files.",
        "code": "def test_max_pos(self) -> None:\n        \n        cache = StreamChangeCache(\"#test\", 1)\n\n        cache.entity_has_changed(\"user@foo.com\", 2)\n        cache.entity_has_changed(\"bar@baz.net\", 3)\n        cache.entity_has_changed(\"user@elsewhere.org\", 4)\n\n        # Known entities will return the point where they were changed.\n        self.assertEqual(cache.get_max_pos_of_last_change(\"user@foo.com\"), 2)\n        self.assertEqual(cache.get_max_pos_of_last_change(\"bar@baz.net\"), 3)\n        self.assertEqual(cache.get_max_pos_of_last_change(\"user@elsewhere.org\"), 4)\n\n        # Unknown entities will return the stream start position.\n        self.assertEqual(cache.get_max_pos_of_last_change(\"not@here.website\"), 1)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 119,
        "n_words": 42,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 92,
        "n_ast_nodes": 162,
        "n_identifiers": 7,
        "d_id": 73230,
        "documentation": {
            "docstring": "\n        StreamChangeCache.get_max_pos_of_last_change will return the most\n        recent point where the entity could have changed.  If the entity is not\n        known, the stream start is provided instead.\n        ",
            "n_words": 25,
            "vocab_size": 20,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 182371,
        "commit_id": "8be6ea91f6e8a8d24d385975f1a5a7714cf27894",
        "repo": "textual",
        "path": "tests/test_animator.py",
        "file_name": "test_animator.py",
        "fun_name": "test_simple_animation_reverse",
        "commit_message": "fix and test for animator",
        "code": "def test_simple_animation_reverse():\n    \n\n    # Thing that may be animated\n    animatable = AnimateTest()\n\n    # Fake wall-clock time\n    time = 100.0\n\n    # Object that does the animation\n    animation = SimpleAnimation(\n        animatable,\n        \"foo\",\n        time,\n        3.0,\n        start_value=50.0,\n        end_value=20.0,\n        final_value=20.0,\n        easing=lambda x: x,\n    )\n\n    assert animation(time) is False\n    assert animatable.foo == 50.0\n\n    assert animation(time + 1.0) is False\n    assert animatable.foo == 40.0\n\n    assert animation(time + 2.0) is False\n    assert animatable.foo == 30.0\n\n    assert animation(time + 3.0) is True\n    assert animatable.foo == 20.0\n\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 180,
        "n_words": 76,
        "vocab_size": 47,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 127,
        "n_ast_nodes": 162,
        "n_identifiers": 12,
        "d_id": 43809,
        "documentation": {
            "docstring": "Test an animation from one float to another, where the end value is less than the start.",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 320534,
        "commit_id": "97d6503fefc5737028637c39a2c1f33dd1e12904",
        "repo": "paperless-ngx",
        "path": "src/documents/signals/handlers.py",
        "file_name": "handlers.py",
        "fun_name": "before_task_publish_handler",
        "commit_message": "Switches task serialization over to pickle format",
        "code": "def before_task_publish_handler(sender=None, headers=None, body=None, **kwargs):\n    \n    if \"task\" not in headers or headers[\"task\"] != \"documents.tasks.consume_file\":\n        # Assumption: this is only ever a v2 message\n        return\n\n    try:\n        task_args = body[0]\n        task_kwargs = body[1]\n\n        task_file_name = \"\"\n        if \"override_filename\" in task_kwargs:\n            task_file_name = task_kwargs[\"override_filename\"]\n\n        # Nothing was found, report the task first argument\n        if not len(task_file_name):\n            # There are always some arguments to the consume, first is always filename\n            filepath = Path(task_args[0])\n            task_file_name = filepath.name\n\n        PaperlessTask.objects.create(\n            task_id=headers[\"id\"],\n            status=states.PENDING,\n            task_file_name=task_file_name,\n            task_name=headers[\"task\"],\n            result=None,\n            date_created=timezone.now(),\n            date_started=None,\n            date_done=None,\n        )\n    except Exception as e:  # pragma: no cover\n        # Don't let an exception in the signal handlers prevent\n        # a document from being consumed.\n        logger.error(f\"Creating PaperlessTask failed: {e}\", exc_info=True)\n\n\n@task_prerun.connect",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "@task_prerun.connect",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 347,
        "n_words": 112,
        "vocab_size": 89,
        "complexity": 6,
        "nloc": 24,
        "token_counts": 149,
        "n_ast_nodes": 258,
        "n_identifiers": 33,
        "d_id": 117208,
        "documentation": {
            "docstring": "\n    Creates the PaperlessTask object in a pending state.  This is sent before\n    the task reaches the broker, but before it begins executing on a worker.\n\n    https://docs.celeryq.dev/en/stable/userguide/signals.html#before-task-publish\n\n    https://docs.celeryq.dev/en/stable/internals/protocol.html#version-2\n\n    ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 156780,
        "commit_id": "ddcb841903f8f180aa359bd8db0054aa3b5964e3",
        "repo": "dask",
        "path": "dask/dataframe/tests/test_format.py",
        "file_name": "test_format.py",
        "fun_name": "test_dataframe_format_with_index",
        "commit_message": "Change repr methods to avoid Layer materialization (#9289)\n\n* change task count to layer count in DataFrame and Array reprs\r\n\r\n* add test\r\n\r\n* address doctest failure\r\n\r\n* simplify test\r\n\r\n* support pluralization\r\n\r\n* use 'graph layers' instead of 'layers' to be more explicit",
        "code": "def test_dataframe_format_with_index():\n    pytest.importorskip(\"jinja2\")\n    df = pd.DataFrame(\n        {\n            \"A\": [1, 2, 3, 4, 5, 6, 7, 8],\n            \"B\": list(\"ABCDEFGH\"),\n            \"C\": pd.Categorical(list(\"AAABBBCC\")),\n        },\n        index=list(\"ABCDEFGH\"),\n    )\n    ddf = dd.from_pandas(df, 3)\n    exp = (\n        \"Dask DataFrame Structure:\\n\"\n        \"                   A       B                C\\n\"\n        \"npartitions=3                                \\n\"\n        \"A              int64  object  category[known]\\n\"\n        \"D                ...     ...              ...\\n\"\n        \"G                ...     ...              ...\\n\"\n        \"H                ...     ...              ...\\n\"\n        \"Dask Name: from_pandas, 1 graph layer\"\n    )\n    assert repr(ddf) == exp\n    assert str(ddf) == exp\n\n    exp_table = \n\n    exp = .format(\n        exp_table=exp_table\n    )\n    assert ddf.to_html() == exp\n\n    # table is boxed with div and has style\n    exp = .format(\n        style=style, exp_table=exp_table\n    )\n    assert ddf._repr_html_() == exp\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 453,
        "n_words": 100,
        "vocab_size": 70,
        "complexity": 1,
        "nloc": 79,
        "token_counts": 145,
        "n_ast_nodes": 259,
        "n_identifiers": 20,
        "d_id": 36771,
        "documentation": {
            "docstring": "<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>A</th>\n      <th>B</th>\n      <th>C</th>\n    </tr>\n    <tr>\n      <th>npartitions=3</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>A</th>\n      <td>int64</td>\n      <td>object</td>\n      <td>category[known]</td>\n    </tr>\n    <tr>\n      <th>D</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>G</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>H</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n  </tbody>\n</table><div><strong>Dask DataFrame Structure:</strong></div>\n{exp_table}\n<div>Dask Name: from_pandas, 1 graph layer</div><div><strong>Dask DataFrame Structure:</strong></div>\n<div>\n{style}{exp_table}\n</div>\n<div>Dask Name: from_pandas, 1 graph layer</div>",
            "n_words": 66,
            "vocab_size": 38,
            "n_whitespaces": 218,
            "language": "en"
        }
    },
    {
        "id": 177249,
        "commit_id": "d8b07498dfcd9fb2ce1c83ccf190ab24209234e8",
        "repo": "networkx",
        "path": "networkx/classes/function.py",
        "file_name": "function.py",
        "fun_name": "is_path",
        "commit_message": "Minor docstring touchups and test refactor for `is_path` (#5967)\n\n* Touch up docstring.\r\n\r\n* Condense conditional.\r\n\r\n* Minor refactor of ispath test - parametrize and rm redundant.\r\n\r\n* Add release note.\r\n\r\n* Update networkx/classes/function.py\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>",
        "code": "def is_path(G, path):\n    \n    for node, nbr in nx.utils.pairwise(path):\n        if (node not in G) or (nbr not in G[node]):\n            return False\n    return True\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 49,
        "n_words": 22,
        "vocab_size": 18,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 44,
        "n_ast_nodes": 68,
        "n_identifiers": 8,
        "d_id": 42315,
        "documentation": {
            "docstring": "Returns whether or not the specified path exists.\n\n    For it to return True, every node on the path must exist and\n    each consecutive pair must be connected via one or more edges.\n\n    Parameters\n    ----------\n    G : graph\n        A NetworkX graph.\n\n    path : list\n        A list of nodes which defines the path to traverse\n\n    Returns\n    -------\n    bool\n        True if `path` is a valid path in `G`\n\n    ",
            "n_words": 65,
            "vocab_size": 52,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 9466,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/external/stylegan2/metrics/precision_recall.py",
        "file_name": "precision_recall.py",
        "fun_name": "evaluate",
        "commit_message": "initialize ostec",
        "code": "def evaluate(self, eval_features, return_realism=False, return_neighbors=False):\n        \n        num_eval_images = eval_features.shape[0]\n        num_ref_images = self.D.shape[0]\n        distance_batch = np.zeros([self.row_batch_size, num_ref_images], dtype=np.float16)\n        batch_predictions = np.zeros([num_eval_images, self.num_nhoods], dtype=np.int32)\n        #max_realism_score = np.zeros([num_eval_images,], dtype=np.float32)\n        realism_score = np.zeros([num_eval_images,], dtype=np.float32)\n        nearest_indices = np.zeros([num_eval_images,], dtype=np.int32)\n\n        for begin1 in range(0, num_eval_images, self.row_batch_size):\n            end1 = min(begin1 + self.row_batch_size, num_eval_images)\n            feature_batch = eval_features[begin1:end1]\n\n            for begin2 in range(0, num_ref_images, self.col_batch_size):\n                end2 = min(begin2 + self.col_batch_size, num_ref_images)\n                ref_batch = self._ref_features[begin2:end2]\n\n                distance_batch[0:end1-begin1, begin2:end2] = self._distance_block.pairwise_distances(feature_batch, ref_batch)\n\n            # From the minibatch of new feature vectors, determine if they are in the estimated manifold.\n            # If a feature vector is inside a hypersphere of some reference sample, then the new sample lies on the estimated manifold.\n            # The radii of the hyperspheres are determined from distances of neighborhood size k.\n            samples_in_manifold = distance_batch[0:end1-begin1, :, None] <= self.D\n            batch_predictions[begin1:end1] = np.any(samples_in_manifold, axis=1).astype(np.int32)\n\n            #max_realism_score[begin1:end1] = np.max(self.D[:, 0] / (distance_batch[0:end1-begin1, :] + 1e-18), axis=1)\n            #nearest_indices[begin1:end1] = np.argmax(self.D[:, 0] / (distance_batch[0:end1-begin1, :] + 1e-18), axis=1)\n            nearest_indices[begin1:end1] = np.argmin(distance_batch[0:end1-begin1, :], axis=1)\n            realism_score[begin1:end1] = self.D[nearest_indices[begin1:end1], 0] / np.min(distance_batch[0:end1-begin1, :], axis=1)\n\n        if return_realism and return_neighbors:\n            return batch_predictions, realism_score, nearest_indices\n        elif return_realism:\n            return batch_predictions, realism_score\n        elif return_neighbors:\n            return batch_predictions, nearest_indices\n\n        return batch_predictions\n\n#----------------------------------------------------------------------------\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 485,
        "n_words": 185,
        "vocab_size": 118,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 336,
        "n_ast_nodes": 499,
        "n_identifiers": 38,
        "d_id": 1623,
        "documentation": {
            "docstring": "Evaluate if new feature vectors are in the estimated manifold.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 82298,
        "commit_id": "a3110e1ff24085373898c7d2a85f628abeb8518d",
        "repo": "django-cms",
        "path": "cms/tests/test_rendering.py",
        "file_name": "test_rendering.py",
        "fun_name": "test_processors",
        "commit_message": "Enabled isort workflow (#7200)\n\n* Ran isort\r\n\r\n* Enabled isort workflow\r\n\r\nCo-authored-by: Vinit Kumar <mail@vinitkumar.me>",
        "code": "def test_processors(self):\n        \n        from djangocms_text_ckeditor.cms_plugins import TextPlugin\n\n        from cms.plugin_pool import plugin_pool\n\n        instance = CMSPlugin.objects.all()[0].get_plugin_instance()[0]\n\n        load_from_string = self.load_template_from_string\n",
        "url": "https://github.com/django-cms/django-cms.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 51,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 27,
        "token_counts": 169,
        "n_ast_nodes": 69,
        "n_identifiers": 14,
        "d_id": 17345,
        "documentation": {
            "docstring": "\n        Tests that plugin processors and plugin context processors can be defined\n        in settings and are working and that extra plugin context processors can be\n        passed to PluginContext.\n        ",
            "n_words": 27,
            "vocab_size": 17,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 54803,
        "commit_id": "05b92d7c7f6cf21c5d6033df7242c331fc66b92e",
        "repo": "prefect",
        "path": "src/prefect/client.py",
        "file_name": "client.py",
        "fun_name": "__aenter__",
        "commit_message": "Disable lifespan management during logging",
        "code": "async def __aenter__(self):\n        \n        if self._closed:\n            # httpx.AsyncClient does not allow reuse so we will not either.\n            raise RuntimeError(\n                \"The client cannot be started again after closing. \"\n                \"Retrieve a new client with `get_client()` instead.\"\n            )\n\n        if self._started:\n            # httpx.AsyncClient does not allow reentrancy so we will not either.\n            raise RuntimeError(\"The client cannot be started more than once.\")\n\n        await self._exit_stack.__aenter__()\n\n        # Enter a lifespan context if using an ephemeral application.\n        # See https://github.com/encode/httpx/issues/350\n        if self._ephemeral_app and self.manage_lifespan:\n            self._ephemeral_lifespan = await self._exit_stack.enter_async_context(\n                app_lifespan_context(self._ephemeral_app)\n            )\n\n        # Enter the httpx client's context\n        await self._exit_stack.enter_async_context(self._client)\n\n        self._started = True\n\n        return self\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 294,
        "n_words": 95,
        "vocab_size": 65,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 80,
        "n_ast_nodes": 145,
        "n_identifiers": 12,
        "d_id": 11152,
        "documentation": {
            "docstring": "\n        Start the client.\n\n        If the client is already started, this will raise an exception.\n\n        If the client is already closed, this will raise an exception. Use a new client\n        instance instead.\n        ",
            "n_words": 31,
            "vocab_size": 19,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 269967,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/callbacks.py",
        "file_name": "callbacks.py",
        "fun_name": "_start_profiler",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _start_profiler(self, logdir):\n        \n        if self._profiler_started:\n            return\n        try:\n            tf.profiler.experimental.start(logdir=logdir)\n            self._profiler_started = True\n        except tf.errors.AlreadyExistsError as e:\n            # Profiler errors should not be fatal.\n            logging.error(\"Failed to start profiler: %s\", e.message)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 111,
        "n_words": 28,
        "vocab_size": 28,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 52,
        "n_ast_nodes": 89,
        "n_identifiers": 14,
        "d_id": 80363,
        "documentation": {
            "docstring": "Starts the profiler if currently inactive.\n\n        Args:\n          logdir: Directory where profiler results will be saved.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 181617,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/export_tests.py",
        "file_name": "export_tests.py",
        "fun_name": "test_export_pipeline_3",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_export_pipeline_3():\n    \n\n    pipeline_string = (\n        'DecisionTreeClassifier(SelectPercentile(input_matrix, SelectPercentile__percentile=20),'\n        'DecisionTreeClassifier__criterion=gini, DecisionTreeClassifier__max_depth=8,'\n        'DecisionTreeClassifier__min_samples_leaf=5, DecisionTreeClassifier__min_samples_split=5)'\n    )\n    pipeline = creator.Individual.from_string(pipeline_string, tpot_obj._pset)\n\n    expected_code = \n    assert expected_code == export_pipeline(pipeline, tpot_obj.operators, tpot_obj._pset)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 64,
        "n_words": 24,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 44,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 43405,
        "documentation": {
            "docstring": "Assert that exported_pipeline() generated a compile source file as expected given a fixed simple pipeline with a preprocessor.import numpy as np\nimport pandas as pd\nfrom sklearn.feature_selection import SelectPercentile, f_classif\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.tree import DecisionTreeClassifier\n\n# NOTE: Make sure that the outcome column is labeled 'target' in the data file\ntpot_data = pd.read_csv('PATH/TO/DATA/FILE', sep='COLUMN_SEPARATOR', dtype=np.float64)\nfeatures = tpot_data.drop('target', axis=1)\ntraining_features, testing_features, training_target, testing_target = \\\\\n            train_test_split(features, tpot_data['target'], random_state=None)\n\nexported_pipeline = make_pipeline(\n    SelectPercentile(score_func=f_classif, percentile=20),\n    DecisionTreeClassifier(criterion=\"gini\", max_depth=8, min_samples_leaf=5, min_samples_split=5)\n)\n\nexported_pipeline.fit(training_features, training_target)\nresults = exported_pipeline.predict(testing_features)\n",
            "n_words": 90,
            "vocab_size": 72,
            "n_whitespaces": 93,
            "language": "en"
        }
    },
    {
        "id": 100547,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/gpu_stats/amd.py",
        "file_name": "amd.py",
        "fun_name": "_experimental_indices",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def _experimental_indices(self) -> List[int]:\n        \n        retval = [idx for idx, device in enumerate(self._all_devices)\n                  if device not in self._supported_indices]\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 57,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 36,
        "n_ast_nodes": 57,
        "n_identifiers": 10,
        "d_id": 20011,
        "documentation": {
            "docstring": " list: The indices corresponding to :attr:`_ids` of GPU devices marked as\n        \"experimental\". ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 110319,
        "commit_id": "383de519505964ed879c40b23ef36e90c17ebe0d",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_axes.py",
        "file_name": "_axes.py",
        "fun_name": "loglog",
        "commit_message": "[Doc] fix more spelling and grammar",
        "code": "def loglog(self, *args, **kwargs):\n        \n        dx = {k: v for k, v in kwargs.items()\n              if k in ['base', 'subs', 'nonpositive',\n                       'basex', 'subsx', 'nonposx']}\n        self.set_xscale('log', **dx)\n        dy = {k: v for k, v in kwargs.items()\n              if k in ['base', 'subs', 'nonpositive',\n                       'basey', 'subsy', 'nonposy']}\n        self.set_yscale('log', **dy)\n        return self.plot(\n            *args, **{k: v for k, v in kwargs.items() if k not in {*dx, *dy}})\n\n    # @_preprocess_data() # let 'plot' do the unpacking..",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 194,
        "n_words": 68,
        "vocab_size": 41,
        "complexity": 7,
        "nloc": 11,
        "token_counts": 132,
        "n_ast_nodes": 222,
        "n_identifiers": 12,
        "d_id": 24058,
        "documentation": {
            "docstring": "\n        Make a plot with log scaling on both the x- and y-axis.\n\n        Call signatures::\n\n            loglog([x], y, [fmt], data=None, **kwargs)\n            loglog([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n\n        This is just a thin wrapper around `.plot` which additionally changes\n        both the x-axis and the y-axis to log scaling. All the concepts and\n        parameters of plot can be used here as well.\n\n        The additional parameters *base*, *subs* and *nonpositive* control the\n        x/y-axis properties. They are just forwarded to `.Axes.set_xscale` and\n        `.Axes.set_yscale`. To use different properties on the x-axis and the\n        y-axis, use e.g.\n        ``ax.set_xscale(\"log\", base=10); ax.set_yscale(\"log\", base=2)``.\n\n        Parameters\n        ----------\n        base : float, default: 10\n            Base of the logarithm.\n\n        subs : sequence, optional\n            The location of the minor ticks. If *None*, reasonable locations\n            are automatically chosen depending on the number of decades in the\n            plot. See `.Axes.set_xscale`/`.Axes.set_yscale` for details.\n\n        nonpositive : {'mask', 'clip'}, default: 'mask'\n            Non-positive values can be masked as invalid, or clipped to a very\n            small positive number.\n\n        **kwargs\n            All parameters supported by `.plot`.\n\n        Returns\n        -------\n        list of `.Line2D`\n            Objects representing the plotted data.\n        ",
            "n_words": 173,
            "vocab_size": 126,
            "n_whitespaces": 424,
            "language": "en"
        }
    },
    {
        "id": 176165,
        "commit_id": "dec723f072eb997a497a159dbe8674cd39999ee9",
        "repo": "networkx",
        "path": "networkx/generators/small.py",
        "file_name": "small.py",
        "fun_name": "moebius_kantor_graph",
        "commit_message": "Docstrings for the small.py module (#5240)\n\n* added description for the first 5 small graphs\r\n\r\n* modified descriptions based on comment and added description for two more functions\r\n\r\n* added doctrings to all the functions\r\n\r\n* Minor touchups.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def moebius_kantor_graph(create_using=None):\n    \n    G = LCF_graph(16, [5, -5], 8, create_using)\n    G.name = \"Moebius-Kantor Graph\"\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 27,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 52,
        "n_identifiers": 5,
        "d_id": 41735,
        "documentation": {
            "docstring": "\n    Returns the Moebius-Kantor graph.\n\n    The Möbius-Kantor graph is the cubic symmetric graph on 16 nodes.\n    Its LCF notation is [5,-5]^8, and it is isomorphic to the generalized\n    Petersen graph [1]_.\n\n    Parameters\n    ----------\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Returns\n    -------\n    G : networkx Graph\n        Moebius-Kantor graph\n\n    References\n    ----------\n    .. [1] https://en.wikipedia.org/wiki/M%C3%B6bius%E2%80%93Kantor_graph\n\n    ",
            "n_words": 63,
            "vocab_size": 48,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 26365,
        "commit_id": "6e1f00a685069da8d0704216ceca1fc2c2177840",
        "repo": "saleor",
        "path": "saleor/graphql/core/tests/test_graphql.py",
        "file_name": "test_graphql.py",
        "fun_name": "test_real_query",
        "commit_message": "Make GraphQL list items non-nullable (#9391)\n\n* Add NonNullList type\r\n\r\n* Fix types.common imports\r\n\r\n* Adjust tests\r\n\r\n* Explicit types.common imports\r\n\r\n* Fix tests\r\n\r\n* Use NonNullList in filter inputs",
        "code": "def test_real_query(user_api_client, product, channel_USD):\n    product_attr = product.product_type.product_attributes.first()\n    category = product.category\n    attr_value = product_attr.values.first()\n    query = \n    variables = {\n        \"categoryId\": graphene.Node.to_global_id(\"Category\", category.id),\n        \"sortBy\": {\"field\": \"NAME\", \"direction\": \"ASC\"},\n        \"first\": 1,\n        \"attributesFilter\": [\n            {\"slug\": f\"{product_attr.slug}\", \"values\": [f\"{attr_value.slug}\"]}\n        ],\n        \"channel\": channel_USD.slug,\n    }\n    response = user_api_client.post_graphql(query, variables)\n    get_graphql_content(response)\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 120,
        "n_words": 43,
        "vocab_size": 38,
        "complexity": 1,
        "nloc": 146,
        "token_counts": 110,
        "n_ast_nodes": 204,
        "n_identifiers": 21,
        "d_id": 4970,
        "documentation": {
            "docstring": "\n    query Root($categoryId: ID!, $sortBy: ProductOrder, $first: Int,\n            $attributesFilter: [AttributeInput!], $channel: String) {\n\n        category(id: $categoryId) {\n            ...CategoryPageFragmentQuery\n            __typename\n        }\n        products(first: $first, sortBy: $sortBy, filter: {categories: [$categoryId],\n            attributes: $attributesFilter}, channel: $channel) {\n\n            ...ProductListFragmentQuery\n            __typename\n        }\n        attributes(first: 20, filter: {inCategory: $categoryId}, channel: $channel) {\n            edges {\n                node {\n                    ...ProductFiltersFragmentQuery\n                    __typename\n                }\n            }\n        }\n    }\n\n    fragment CategoryPageFragmentQuery on Category {\n        id\n        name\n        ancestors(first: 20) {\n            edges {\n                node {\n                    name\n                    id\n                    __typename\n                }\n            }\n        }\n        children(first: 20) {\n            edges {\n                node {\n                    name\n                    id\n                    slug\n                    __typename\n                }\n            }\n        }\n        __typename\n    }\n\n    fragment ProductListFragmentQuery on ProductCountableConnection {\n        edges {\n            node {\n                ...ProductFragmentQuery\n                __typename\n            }\n            __typename\n        }\n        pageInfo {\n            hasNextPage\n            __typename\n        }\n        __typename\n    }\n\n    fragment ProductFragmentQuery on Product {\n        id\n        isAvailable\n        name\n        pricing {\n            ...ProductPriceFragmentQuery\n            __typename\n        }\n        thumbnailUrl1x: thumbnail(size: 255){\n            url\n        }\n        thumbnailUrl2x:     thumbnail(size: 510){\n            url\n        }\n        __typename\n    }\n\n    fragment ProductPriceFragmentQuery on ProductPricingInfo {\n        discount {\n            gross {\n                amount\n                currency\n                __typename\n            }\n            __typename\n        }\n        priceRange {\n            stop {\n                gross {\n                    amount\n                    currency\n                    __typename\n                }\n                currency\n                __typename\n            }\n            start {\n                gross {\n                    amount\n                    currency\n                    __typename\n                }\n                currency\n                __typename\n            }\n            __typename\n        }\n        __typename\n    }\n\n    fragment ProductFiltersFragmentQuery on Attribute {\n        id\n        name\n        slug\n        choices(first: 10) {\n            edges {\n                node {\n                    id\n                    name\n                    slug\n                    __typename\n                }\n            }\n        }\n        __typename\n    }\n    ",
            "n_words": 200,
            "vocab_size": 75,
            "n_whitespaces": 1534,
            "language": "en"
        }
    },
    {
        "id": 20286,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/formatter.py",
        "file_name": "formatter.py",
        "fun_name": "format",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def format(self, tokensource, outfile):\n        \n        if self.encoding:\n            # wrap the outfile in a StreamWriter\n            outfile = codecs.lookup(self.encoding)[3](outfile)\n        return self.format_unencoded(tokensource, outfile)\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 62,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 40,
        "n_ast_nodes": 64,
        "n_identifiers": 8,
        "d_id": 3310,
        "documentation": {
            "docstring": "\n        Format ``tokensource``, an iterable of ``(tokentype, tokenstring)``\n        tuples and write it into ``outfile``.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 276121,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/saving/saved_model/save_impl.py",
        "file_name": "save_impl.py",
        "fun_name": "_get_layer_inputs",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _get_layer_inputs(self, layer):\n        \n        if (\n            isinstance(layer.call, tf.__internal__.function.Function)\n            and layer.call.input_signature is not None\n        ):\n            return layer.call.input_signature, {}\n        elif isinstance(layer, training_lib.Model):\n            return saving_utils.model_call_inputs(layer)\n        elif (\n            layer.input_spec is not None\n            and layer._use_input_spec_as_call_signature\n        ):  # pylint: disable=protected-access\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 142,
        "n_words": 33,
        "vocab_size": 25,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 104,
        "n_ast_nodes": 117,
        "n_identifiers": 16,
        "d_id": 81569,
        "documentation": {
            "docstring": "Inspects layer object and returns the inferred input signature.\n\n        Args:\n          layer: Layer object.\n\n        Returns:\n          List of possibly nested TensorSpecs of the layer call function inputs in\n          the form of `(args, kwargs)`\n        ",
            "n_words": 31,
            "vocab_size": 26,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 202324,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/contenttypes_tests/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_lookup_cache",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_lookup_cache(self):\n        \n        # At this point, a lookup for a ContentType should hit the DB\n        with self.assertNumQueries(1):\n            ContentType.objects.get_for_model(ContentType)\n\n        # A second hit, though, won't hit the DB, nor will a lookup by ID\n        # or natural key\n        with self.assertNumQueries(0):\n            ct = ContentType.objects.get_for_model(ContentType)\n        with self.assertNumQueries(0):\n            ContentType.objects.get_for_id(ct.id)\n        with self.assertNumQueries(0):\n            ContentType.objects.get_by_natural_key(\"contenttypes\", \"contenttype\")\n\n        # Once we clear the cache, another lookup will again hit the DB\n        ContentType.objects.clear_cache()\n        with self.assertNumQueries(1):\n            ContentType.objects.get_for_model(ContentType)\n\n        # The same should happen with a lookup by natural key\n        ContentType.objects.clear_cache()\n        with self.assertNumQueries(1):\n            ContentType.objects.get_by_natural_key(\"contenttypes\", \"contenttype\")\n        # And a second hit shouldn't hit the DB\n        with self.assertNumQueries(0):\n            ContentType.objects.get_by_natural_key(\"contenttypes\", \"contenttype\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 284,
        "n_words": 95,
        "vocab_size": 48,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 142,
        "n_ast_nodes": 263,
        "n_identifiers": 11,
        "d_id": 50069,
        "documentation": {
            "docstring": "\n        The content type cache (see ContentTypeManager) works correctly.\n        Lookups for a particular content type -- by model, ID, or natural key\n        -- should hit the database only on the first lookup.\n        ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 215494,
        "commit_id": "25c2ae356bcf684cbe20f776e1ffcab0f8aeb80c",
        "repo": "salt",
        "path": "salt/cli/daemons.py",
        "file_name": "daemons.py",
        "fun_name": "prepare",
        "commit_message": "Address docs and hard coded strings",
        "code": "def prepare(self):\n        \n        super().prepare()\n\n        try:\n            if self.config[\"verify_env\"]:\n                confd = self.config.get(\"default_include\")\n                if confd:\n                    # If 'default_include' is specified in config, then use it\n                    if \"*\" in confd:\n                        # Value is of the form \"minion.d/*.conf\"\n                        confd = os.path.dirname(confd)\n                    if not os.path.isabs(confd):\n                        # If configured 'default_include' is not an absolute\n                        # path, consider it relative to folder of 'conf_file'\n                        # (/etc/salt by default)\n                        confd = os.path.join(\n                            os.path.dirname(self.config[\"conf_file\"]), confd\n                        )\n                else:\n                    confd = os.path.join(\n                        os.path.dirname(self.config[\"conf_file\"]), \"minion.d\"\n                    )\n\n                v_dirs = [\n                    self.config[\"pki_dir\"],\n                    self.config[\"cachedir\"],\n                    self.config[\"sock_dir\"],\n                    self.config[\"extension_modules\"],\n                    confd,\n                ]\n\n                verify_env(\n                    v_dirs,\n                    self.config[\"user\"],\n                    permissive=self.config[\"permissive_pki_access\"],\n                    root_dir=self.config[\"root_dir\"],\n                    pki_dir=self.config[\"pki_dir\"],\n                )\n        except OSError as error:\n            self.environment_failure(error)\n\n        self.setup_logfile_logger()\n        verify_log(self.config)\n        log.info('Setting up the Salt Minion \"%s\"', self.config[\"id\"])\n        migrations.migrate_paths(self.config)\n\n        # Bail out if we find a process running and it matches out pidfile\n        if (HAS_PSUTIL and not self.claim_process_responsibility()) or (\n            not HAS_PSUTIL and self.check_running()\n        ):\n            self.action_log_info(\"An instance is already running. Exiting\")\n            self.shutdown(1)\n\n        transport = self.config.get(\"transport\").lower()\n\n        try:\n            # Late import so logging works correctly\n            import salt.minion\n\n            # If the minion key has not been accepted, then Salt enters a loop\n            # waiting for it, if we daemonize later then the minion could halt\n            # the boot process waiting for a key to be accepted on the master.\n            # This is the latest safe place to daemonize\n            self.daemonize_if_required()\n            self.set_pidfile()\n            if self.config.get(\"master_type\") == \"func\":\n                salt.minion.eval_master_func(self.config)\n            self.minion = salt.minion.MinionManager(self.config)\n        except Exception:  # pylint: disable=broad-except\n            log.error(\n                \"An error occured while setting up the minion manager\", exc_info=True\n            )\n            self.shutdown(1)\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 1155,
        "n_words": 227,
        "vocab_size": 148,
        "complexity": 12,
        "nloc": 54,
        "token_counts": 348,
        "n_ast_nodes": 599,
        "n_identifiers": 40,
        "d_id": 53991,
        "documentation": {
            "docstring": "\n        Run the preparation sequence required to start a salt minion.\n\n        If sub-classed, don't **ever** forget to run:\n\n            super(YourSubClass, self).prepare()\n        ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 292210,
        "commit_id": "ba6d1976dff8df2aa32726ff2acbf0ba61e5c550",
        "repo": "core",
        "path": "tests/components/mqtt/test_discovery.py",
        "file_name": "test_discovery.py",
        "fun_name": "test_cleanup_device_mqtt",
        "commit_message": "Improve MQTT device removal (#66766)\n\n* Improve MQTT device removal\r\n\r\n* Update homeassistant/components/mqtt/mixins.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Adjust tests\r\n\r\n* Improve test coverage\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "async def test_cleanup_device_mqtt(hass, device_reg, entity_reg, mqtt_mock):\n    \n    data = (\n        '{ \"device\":{\"identifiers\":[\"0AFFD2\"]},'\n        '  \"state_topic\": \"foobar/sensor\",'\n        '  \"unique_id\": \"unique\" }'\n    )\n\n    async_fire_mqtt_message(hass, \"homeassistant/sensor/bla/config\", data)\n    await hass.async_block_till_done()\n\n    # Verify device and registry entries are created\n    device_entry = device_reg.async_get_device({(\"mqtt\", \"0AFFD2\")})\n    assert device_entry is not None\n    entity_entry = entity_reg.async_get(\"sensor.mqtt_sensor\")\n    assert entity_entry is not None\n\n    state = hass.states.get(\"sensor.mqtt_sensor\")\n    assert state is not None\n\n    async_fire_mqtt_message(hass, \"homeassistant/sensor/bla/config\", \"\")\n    await hass.async_block_till_done()\n    await hass.async_block_till_done()\n\n    # Verify device and registry entries are cleared\n    device_entry = device_reg.async_get_device({(\"mqtt\", \"0AFFD2\")})\n    assert device_entry is None\n    entity_entry = entity_reg.async_get(\"sensor.mqtt_sensor\")\n    assert entity_entry is None\n\n    # Verify state is removed\n    state = hass.states.get(\"sensor.mqtt_sensor\")\n    assert state is None\n    await hass.async_block_till_done()\n\n    # Verify retained discovery topics have not been cleared again\n    mqtt_mock.async_publish.assert_not_called()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 213,
        "n_words": 112,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 157,
        "n_ast_nodes": 280,
        "n_identifiers": 17,
        "d_id": 91310,
        "documentation": {
            "docstring": "Test discvered device is cleaned up when removed through MQTT.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 261378,
        "commit_id": "b849ce8d17fce0ff7569a9d49b7264d0f54d37d3",
        "repo": "scikit-learn",
        "path": "sklearn/pipeline.py",
        "file_name": "pipeline.py",
        "fun_name": "set_params",
        "commit_message": "DOC fix typo inside Pipeline docstring (#24730)",
        "code": "def set_params(self, **kwargs):\n        \n        self._set_params(\"transformer_list\", **kwargs)\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 28,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 20,
        "n_ast_nodes": 36,
        "n_identifiers": 4,
        "d_id": 76788,
        "documentation": {
            "docstring": "Set the parameters of this estimator.\n\n        Valid parameter keys can be listed with ``get_params()``. Note that\n        you can directly set the parameters of the estimators contained in\n        `transformer_list`.\n\n        Parameters\n        ----------\n        **kwargs : dict\n            Parameters of this estimator or parameters of estimators contained\n            in `transform_list`. Parameters of the transformers may be set\n            using its name and the parameter name separated by a '__'.\n\n        Returns\n        -------\n        self : object\n            FeatureUnion class instance.\n        ",
            "n_words": 70,
            "vocab_size": 48,
            "n_whitespaces": 184,
            "language": "en"
        }
    },
    {
        "id": 221663,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/configparser.py",
        "file_name": "configparser.py",
        "fun_name": "_convert_to_boolean",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _convert_to_boolean(self, value):\n        \n        if value.lower() not in self.BOOLEAN_STATES:\n            raise ValueError('Not a boolean: %s' % value)\n        return self.BOOLEAN_STATES[value.lower()]\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 49,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 38,
        "n_ast_nodes": 64,
        "n_identifiers": 6,
        "d_id": 56464,
        "documentation": {
            "docstring": "Return a boolean value translating from other types if necessary.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 316449,
        "commit_id": "7cd68381f1d4f58930ffd631dfbfc7159d459832",
        "repo": "core",
        "path": "tests/test_config_entries.py",
        "file_name": "test_config_entries.py",
        "fun_name": "test_unignore_create_entry",
        "commit_message": "Search/replace RESULT_TYPE_* by FlowResultType enum (#74642)",
        "code": "async def test_unignore_create_entry(hass, manager):\n    \n    async_setup_entry = AsyncMock(return_value=True)\n    mock_integration(hass, MockModule(\"comp\", async_setup_entry=async_setup_entry))\n    mock_entity_platform(hass, \"config_flow.comp\", None)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 25,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 29,
        "token_counts": 244,
        "n_ast_nodes": 63,
        "n_identifiers": 9,
        "d_id": 115027,
        "documentation": {
            "docstring": "Test that we can ignore flows that are in progress and have a unique ID, then rediscover them.",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 253303,
        "commit_id": "f23a1887bb76501f6dbb57573847767e7c1538f1",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http3.py",
        "file_name": "test_http3.py",
        "fun_name": "test_rst_then_close",
        "commit_message": "[quic] fix h3 double-close issue",
        "code": "def test_rst_then_close(tctx):\n    \n    playbook, cff = start_h3_client(tctx)\n    flow = tutils.Placeholder(HTTPFlow)\n    server = tutils.Placeholder(connection.Server)\n    err = tutils.Placeholder(str)\n\n    assert (\n        playbook\n        # request client\n        >> cff.receive_headers(example_request_headers, end_stream=True)\n        << (request := http.HttpRequestHeadersHook(flow))\n        << cff.send_decoder()  # for receive_headers\n        >> tutils.reply(to=request)\n        << http.HttpRequestHook(flow)\n        >> tutils.reply()\n        # request server\n        << (open := commands.OpenConnection(server))\n        >> cff.receive_data(b\"unexpected data frame\")\n        << quic.CloseQuicConnection(\n            tctx.client,\n            error_code=quic.QuicErrorCode.PROTOCOL_VIOLATION,\n            frame_type=None,\n            reason_phrase=err,\n        )\n        >> quic.QuicConnectionClosed(\n            tctx.client,\n            error_code=quic.QuicErrorCode.PROTOCOL_VIOLATION,\n            frame_type=None,\n            reason_phrase=err,\n        )\n        >> tutils.reply(\"connection cancelled\", to=open)\n        << http.HttpErrorHook(flow)\n        >> tutils.reply()\n    )\n    assert flow().error.msg == \"connection cancelled\"\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 317,
        "n_words": 78,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 32,
        "token_counts": 212,
        "n_ast_nodes": 314,
        "n_identifiers": 40,
        "d_id": 74056,
        "documentation": {
            "docstring": "\n    Test that we properly handle the case of a client that first causes protocol errors and then disconnects.\n\n    This is slightly different to H2, as QUIC will close the connection immediately.\n    ",
            "n_words": 31,
            "vocab_size": 29,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 95412,
        "commit_id": "5efa5eeb57ae6ddf740256e08ce3b9ff4ec98eaa",
        "repo": "sentry",
        "path": "tests/sentry/api/endpoints/test_organization_codeowners_associations.py",
        "file_name": "test_organization_codeowners_associations.py",
        "fun_name": "test_simple",
        "commit_message": "feat(codeowners): Add endpoint to view code owner associations per organization (#31030)\n\nSee API-2186\r\n\r\nSo the earlier version of this PR just had the endpoint return the entire serialized ProjectCodeOwners for an organization. While that works, the intention behind this feature is to read and use the associations, so sending the raw codeowners file, and timestamps are unnecessary and increase the latency with such large payloads, especially for larger orgs.\r\n\r\n@NisanthanNanthakumar suggested limiting what the endpoint returns to just what the feature will need on the frontend, and making the endpoint name a bit more specific. OrganizationCodeOwners -> OrganizationCodeOwnersAssocations.\r\n\r\nAlong with this refactor, tests have been updated.",
        "code": "def test_simple(self):\n        \n        code_owner_1 = self.create_codeowners(\n            self.project_1, self.code_mapping_1, raw=self.data_1[\"raw\"]\n        )\n        code_owner_2 = self.create_codeowners(\n            self.project_2, self.code_mapping_2, raw=self.data_2[\"raw\"]\n        )\n        response = self.get_success_response(self.organization.slug, status=status.HTTP_200_OK)\n        for code_owner in [code_owner_1, code_owner_2]:\n            assert code_owner.project.slug in response.data.keys()\n            associations, errors = ProjectCodeOwners.validate_codeowners_associations(\n                code_owner.raw, code_owner.project\n            )\n            assert \"associations\" in response.data[code_owner.project.slug].keys()\n            assert response.data[code_owner.project.slug][\"associations\"] == associations\n            assert \"errors\" in response.data[code_owner.project.slug].keys()\n            assert response.data[code_owner.project.slug][\"errors\"] == errors\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 215,
        "n_words": 52,
        "vocab_size": 36,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 175,
        "n_ast_nodes": 274,
        "n_identifiers": 26,
        "d_id": 19207,
        "documentation": {
            "docstring": "\n        Tests that all the ProjectCodeOwners are serialized in the response\n        ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 181716,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_memory_2",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_memory_2():\n    \n    cachedir = mkdtemp()\n    tpot_obj = TPOTClassifier(\n        random_state=42,\n        population_size=1,\n        offspring_size=2,\n        generations=1,\n        config_dict='TPOT light',\n        memory=cachedir,\n        verbosity=0\n    )\n    tpot_obj._setup_memory()\n    rmtree(cachedir)\n\n    assert tpot_obj._cachedir == cachedir\n    assert isinstance(tpot_obj._memory, Memory)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 99,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 66,
        "n_ast_nodes": 104,
        "n_identifiers": 18,
        "d_id": 43503,
        "documentation": {
            "docstring": "Assert that the TPOT _setup_memory function runs normally with a valid path.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 44661,
        "commit_id": "05a883b35e34853ec9326bd579551a8e161d6cdc",
        "repo": "airflow",
        "path": "airflow/providers/google/cloud/hooks/cloud_composer.py",
        "file_name": "cloud_composer.py",
        "fun_name": "get_environment_client",
        "commit_message": "Google Cloud Composer opearators (#21251)",
        "code": "def get_environment_client(self) -> EnvironmentsClient:\n        \n        return EnvironmentsClient(\n            credentials=self._get_credentials(),\n            client_info=self.client_info,\n            client_options=self.client_options,\n        )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 64,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 32,
        "n_ast_nodes": 51,
        "n_identifiers": 7,
        "d_id": 8337,
        "documentation": {
            "docstring": "Retrieves client library object that allow access Environments service.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 7165,
        "commit_id": "aa0c63bf2ed825eb3ca8eff8a002d5ccbe395173",
        "repo": "ludwig",
        "path": "ludwig/models/base.py",
        "file_name": "base.py",
        "fun_name": "update_metrics",
        "commit_message": "feat: Added model type GBM (LightGBM tree learner), as an alternative to ECD (#2027)",
        "code": "def update_metrics(self, targets, predictions):\n        \n        for of_name, of_obj in self.output_features.items():\n            of_obj.update_metrics(targets[of_name], predictions[of_name])\n\n        eval_loss, additional_losses = self.eval_loss(targets, predictions)\n        self.eval_loss_metric.update(eval_loss)\n        self.eval_additional_losses_metrics.update(additional_losses)\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 64,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 65,
        "n_ast_nodes": 101,
        "n_identifiers": 13,
        "d_id": 1143,
        "documentation": {
            "docstring": "Updates the model's metrics given targets and predictions.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 189657,
        "commit_id": "e040bcacd38378386749db18aeba575b93f4ebca",
        "repo": "manim",
        "path": "manim/mobject/geometry/arc.py",
        "file_name": "arc.py",
        "fun_name": "get_arc_center",
        "commit_message": "Improved structure of the :mod:`.mobject` module (#2476)\n\n* group graphing and update its references\r\n\r\n* group text and update its references\r\n\r\n* group opengl and update its references\r\n\r\n* group three_d and update its references\r\n\r\n* group geometry and update (most) references\r\n\r\n* move some chaning.py + updater files  into animation\r\n\r\n* refactor arc.py\r\n\r\n* refactor line.py\r\n\r\n* refactor polygram.py\r\n\r\n* refactor tips.py\r\n\r\n* black + isort\r\n\r\n* import new files in __init__.py\r\n\r\n* refactor places where geometry was used\r\n\r\n* black + isort again\r\n\r\n* remove unused imports\r\n\r\n* update reference.rst\r\n\r\n* add descriptions to files\r\n\r\n* fix circular imports\r\n\r\n* forgot ArrowTip\r\n\r\n* fix tests\r\n\r\n* fix doctests\r\n\r\n* satisfy mypy?\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix ALL merge conflicts\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* one VMobject import slipped through\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* re-add imports to `manim/opengl/__init__.py`\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix reference manual\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* ignore unknown directive type\r\n\r\n* fix arrow tip imports in docstrings\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>",
        "code": "def get_arc_center(self, warning=True):\n        \n        # First two anchors and handles\n        a1, h1, h2, a2 = self.points[:4]\n\n        if np.all(a1 == a2):\n            # For a1 and a2 to lie at the same point arc radius\n            # must be zero. Thus arc_center will also lie at\n            # that point.\n            return a1\n        # Tangent vectors\n        t1 = h1 - a1\n        t2 = h2 - a2\n        # Normals\n        n1 = rotate_vector(t1, TAU / 4)\n        n2 = rotate_vector(t2, TAU / 4)\n        try:\n            return line_intersection(line1=(a1, a1 + n1), line2=(a2, a2 + n2))\n        except Exception:\n            if warning:\n                warnings.warn(\"Can't find Arc center, using ORIGIN instead\")\n            self._failed_to_get_center = True\n            return np.array(ORIGIN)\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 287,
        "n_words": 100,
        "vocab_size": 73,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 116,
        "n_ast_nodes": 187,
        "n_identifiers": 25,
        "d_id": 46157,
        "documentation": {
            "docstring": "\n        Looks at the normals to the first two\n        anchors, and finds their intersection points\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 37643,
        "commit_id": "1ac698744c4dbdf1495d303246d08ffacdf4f5b8",
        "repo": "transformers",
        "path": "src/transformers/models/yolos/modeling_yolos.py",
        "file_name": "modeling_yolos.py",
        "fun_name": "forward",
        "commit_message": "Add YOLOS (#16848)\n\n* First draft\r\n\r\n* Add YolosForObjectDetection\r\n\r\n* Make forward pass work\r\n\r\n* Add mid position embeddings\r\n\r\n* Add interpolation of position encodings\r\n\r\n* Add expected values\r\n\r\n* Add YOLOS to tests\r\n\r\n* Add integration test\r\n\r\n* Support tiny model as well\r\n\r\n* Support all models in conversion script\r\n\r\n* Remove mid_pe_size attribute\r\n\r\n* Make more tests pass\r\n\r\n* Add model to README and fix config\r\n\r\n* Add copied from statements\r\n\r\n* Rename base_model_prefix to vit\r\n\r\n* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP\r\n\r\n* Apply suggestions from code review\r\n\r\n* Apply more suggestions from code review\r\n\r\n* Convert remaining checkpoints\r\n\r\n* Improve docstrings\r\n\r\n* Add YolosFeatureExtractor\r\n\r\n* Add feature extractor to docs\r\n\r\n* Add corresponding tests\r\n\r\n* Fix style\r\n\r\n* Fix docs\r\n\r\n* Apply suggestion from code review\r\n\r\n* Fix bad rebase\r\n\r\n* Fix some more bad rebase\r\n\r\n* Fix missing character\r\n\r\n* Improve docs and variable names\r\n\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def forward(self, hidden_states):\n        # We \"pool\" the model by simply taking the hidden state corresponding\n        # to the first token.\n        first_token_tensor = hidden_states[:, 0]\n        pooled_output = self.dense(first_token_tensor)\n        pooled_output = self.activation(pooled_output)\n        return pooled_output\n\n\n@add_start_docstrings(\n    ,\n    YOLOS_START_DOCSTRING,\n)",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"\"\"\n    YOLOS Model (consisting of a ViT encoder) with object detection heads on top, for tasks such as COCO detection.\n    \"\"\",\n    YOLOS_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 81,
        "n_words": 36,
        "vocab_size": 29,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 33,
        "n_ast_nodes": 68,
        "n_identifiers": 9,
        "d_id": 6846,
        "documentation": {
            "docstring": "\n    YOLOS Model (consisting of a ViT encoder) with object detection heads on top, for tasks such as COCO detection.\n    ",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 309493,
        "commit_id": "537dfbca18830a90a7f89d291f519948a3d977e8",
        "repo": "core",
        "path": "tests/components/cloud/test_alexa_config.py",
        "file_name": "test_alexa_config.py",
        "fun_name": "test_enabled_requires_valid_sub",
        "commit_message": "Rename cloud's AlexaConfig to CloudAlexaConfig (#64065)\n\n* Rename cloud's AlexaConfig to CloudAlexaConfig\r\n\r\n* Tweak",
        "code": "def test_enabled_requires_valid_sub(hass, mock_expired_cloud_login, cloud_prefs):\n    \n    assert cloud_prefs.alexa_enabled\n    assert hass.data[\"cloud\"].is_logged_in\n    assert hass.data[\"cloud\"].subscription_expired\n\n    config = alexa_config.CloudAlexaConfig(\n        hass, ALEXA_SCHEMA({}), \"mock-user-id\", cloud_prefs, hass.data[\"cloud\"]\n    )\n\n    assert not config.enabled\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 50,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 62,
        "n_ast_nodes": 100,
        "n_identifiers": 13,
        "d_id": 108191,
        "documentation": {
            "docstring": "Test that alexa config enabled requires a valid Cloud sub.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 158223,
        "commit_id": "b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2",
        "repo": "d2l-zh",
        "path": "d2l/mxnet.py",
        "file_name": "mxnet.py",
        "fun_name": "predict_snli",
        "commit_message": "[PaddlePaddle] Merge master into Paddle branch (#1186)\n\n* change 15.2 title in chinese version (#1109)\r\n\r\nchange title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘\r\n\r\n* 修改部分语义表述 (#1105)\r\n\r\n* Update r0.17.5 (#1120)\r\n\r\n* Bump versions in installation\r\n\r\n* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)\r\n\r\n* line 313: \"bert.mall\" -> \"bert.small\" (#1130)\r\n\r\n* fix: update language as native reader (#1114)\r\n\r\n* Fix the translation of \"stride\" (#1115)\r\n\r\n* Update index.md (#1118)\r\n\r\n修改部分语义表述\r\n\r\n* Update self-attention-and-positional-encoding.md (#1133)\r\n\r\n依照本书的翻译习惯，将pooling翻译成汇聚\r\n\r\n* maybe a comment false (#1149)\r\n\r\n* maybe a little false\r\n\r\n* maybe a little false\r\n\r\n* A minor bug in the rcnn section (Chinese edition) (#1148)\r\n\r\n* Update bert.md (#1137)\r\n\r\n一个笔误\r\n# 假设batch_size=2，num_pred_positions=3\r\n# 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1]\r\n\r\n* Update calculus.md (#1135)\r\n\r\n* fix typo in git documentation (#1106)\r\n\r\n* fix: Update the Chinese translation in lr-scheduler.md (#1136)\r\n\r\n* Update lr-scheduler.md\r\n\r\n* Update chapter_optimization/lr-scheduler.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* fix translation for kaggle-house-price.md (#1107)\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\n\r\n* Update weight-decay.md (#1150)\r\n\r\n* Update weight-decay.md\r\n\r\n关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解\r\n关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。\r\n并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释\r\n解释为何会增加复杂性以及为何需要细粒度工具。\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Fix a spelling error (#1161)\r\n\r\n* Update gru.md (#1152)\r\n\r\nThe key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state.\r\n翻译错误\r\n\r\n* Unify the function naming (#1113)\r\n\r\nUnify naming of the function 'init_xavier()'.\r\n\r\n* Update mlp-concise.md (#1166)\r\n\r\n* Update mlp-concise.md\r\n\r\n语句不通顺\r\n\r\n* Update environment.md\r\n\r\n语序异常\r\n\r\n* Update config.ini\r\n\r\n* fix the imprecise description (#1168)\r\n\r\nCo-authored-by: yuande <yuande>\r\n\r\n* fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175)\r\n\r\n* Fix some typos. (#1163)\r\n\r\n* Update batch-norm.md (#1170)\r\n\r\nfixing typos u->x in article\r\n\r\n* Update linear-regression.md (#1090)\r\n\r\nWe invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that\r\n\r\n原译文把who也直接翻译出来了。\r\n\r\n* Update mlp.md (#1117)\r\n\r\n* Update mlp.md\r\n\r\n修改部分语义表述\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Correct a translation error. (#1091)\r\n\r\n* Correct a translation error.\r\n\r\n* Update chapter_computer-vision/image-augmentation.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update aws.md (#1121)\r\n\r\n* Update aws.md\r\n\r\n* Update chapter_appendix-tools-for-deep-learning/aws.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update image-augmentation.md (#1093)\r\n\r\n* Update anchor.md (#1088)\r\n\r\nfix a minor issue in  code\r\n\r\n* Update anchor.md\r\n\r\n* Update image-augmentation.md\r\n\r\n* fix typo and improve translation in chapter_linear-networks\\softmax-regression.md (#1087)\r\n\r\n* Avoid `torch.meshgrid` user warning (#1174)\r\n\r\nAvoids the following user warning:\r\n```python\r\n~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2228.)\r\n  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\r\n```\r\n\r\n* bump to 2.0.0-beta1\r\n\r\n* Update sequence.md\r\n\r\n* bump beta1 on readme\r\n\r\n* Add latex code block background to config\r\n\r\n* BLD: Bump python support version 3.9 (#1183)\r\n\r\n* BLD: Bump python support version 3.9\r\n\r\n* Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4\r\n\r\n* BLD: Bump torch and tensorflow\r\n\r\n* Update Jenkinsfile\r\n\r\n* Update chapter_installation/index.md\r\n\r\n* Update chapter_installation/index.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update config.ini\r\n\r\n* Update INFO.md\r\n\r\n* Update INFO.md\r\n\r\n* Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187)\r\n\r\n* resolve the conflicts\r\n\r\n* revise from publisher (#1089)\r\n\r\n* revise from publisher\r\n\r\n* d2l api\r\n\r\n* post_latex\r\n\r\n* revise from publisher\r\n\r\n* revise ch11\r\n\r\n* Delete d2l-Copy1.bib\r\n\r\n* clear cache\r\n\r\n* rm d2lbook clear\r\n\r\n* debug anchor\r\n\r\n* keep original d2l doc\r\n\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\n\r\n* 重复语句 (#1188)\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improve expression for chapter_preliminaries/pandas.md (#1184)\r\n\r\n* Update pandas.md\r\n\r\n* Improve expression\r\n\r\n* Improve expression\r\n\r\n* Update chapter_preliminaries/pandas.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improce expression for chapter_preliminaries/linear-algebra.md (#1185)\r\n\r\n* Improce expression\r\n\r\n* Improve code comments\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Fix multibox_detection bugs\r\n\r\n* Update d2l to 0.17.5 version\r\n\r\n* restore older version\r\n\r\n* Upgrade pandas\r\n\r\n* change to python3.8\r\n\r\n* Test warning log\r\n\r\n* relocate  warning log\r\n\r\n* test logs filtering\r\n\r\n* Update gru.md\r\n\r\n* Add DeprecationWarning filter\r\n\r\n* Test warning log\r\n\r\n* Update attention mechanisms & computational performance\r\n\r\n* Update multilayer perceptron& linear & convolution networks & computer vision\r\n\r\n* Update recurrent&optimition&nlp pretraining & nlp applications\r\n\r\n* ignore warnings\r\n\r\n* Update index.md\r\n\r\n* Update linear networks\r\n\r\n* Update multilayer perceptrons&deep learning computation\r\n\r\n* Update preliminaries\r\n\r\n* Check and Add warning filter\r\n\r\n* Update kaggle-cifar10.md\r\n\r\n* Update object-detection-dataset.md\r\n\r\n* Update ssd.md fcn.md\r\n\r\n* Update hybridize.md\r\n\r\n* Update hybridize.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\nCo-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com>\r\nCo-authored-by: Xinwei Liu <xinzone@outlook.com>\r\nCo-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com>\r\nCo-authored-by: gyro永不抽风 <1247006353@qq.com>\r\nCo-authored-by: CanChengZheng <zcc550169544@163.com>\r\nCo-authored-by: linlin <jajupmochi@gmail.com>\r\nCo-authored-by: iuk <liukun0104@gmail.com>\r\nCo-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com>\r\nCo-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com>\r\nCo-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com>\r\nCo-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com>\r\nCo-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com>\r\nCo-authored-by: Ming Liu <akira.liu@njnu.edu.cn>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\nCo-authored-by: silenceZheng66 <13754430639@163.com>\r\nCo-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com>\r\nCo-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com>\r\nCo-authored-by: Krahets <krahets@163.com>\r\nCo-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com>\r\nCo-authored-by: Jameson <miraclecome@gmail.com>\r\nCo-authored-by: P. Yao <12227516+YaoPengCN@users.noreply.github.com>\r\nCo-authored-by: Yulv-git <34329208+Yulv-git@users.noreply.github.com>\r\nCo-authored-by: Liu,Xiao <45966993+liuxiao916@users.noreply.github.com>\r\nCo-authored-by: YIN, Gang <1246410+yingang@users.noreply.github.com>\r\nCo-authored-by: Joe-HZ <58297431+Joe-HZ@users.noreply.github.com>\r\nCo-authored-by: lybloveyou <102609904+lybloveyou@users.noreply.github.com>\r\nCo-authored-by: VigourJiang <jiangfuqiang154@163.com>\r\nCo-authored-by: zxhd863943427 <74853597+zxhd863943427@users.noreply.github.com>\r\nCo-authored-by: LYF <27893441+liyufan@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\nCo-authored-by: xiaotinghe <xiaotih@amazon.com>\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Holly-Max <60691735+Holly-Max@users.noreply.github.com>\r\nCo-authored-by: HinGwenWoong <peterhuang0323@qq.com>\r\nCo-authored-by: Shuai Zhang <cheungdaven@gmail.com>",
        "code": "def predict_snli(net, vocab, premise, hypothesis):\n    \n    premise = np.array(vocab[premise], ctx=d2l.try_gpu())\n    hypothesis = np.array(vocab[hypothesis], ctx=d2l.try_gpu())\n    label = np.argmax(net([premise.reshape((1, -1)),\n                           hypothesis.reshape((1, -1))]), axis=1)\n    return 'entailment' if label == 0 else 'contradiction' if label == 1 \\\n            else 'neutral'\n\nd2l.DATA_HUB['ml-100k'] = (\n    'https://files.grouplens.org/datasets/movielens/ml-100k.zip',\n    'cd4dcac4241c8a4ad7badc7ca635da8a69dddb83')\n",
        "url": "https://github.com/d2l-ai/d2l-zh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 97,
        "n_words": 40,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 104,
        "n_ast_nodes": 183,
        "n_identifiers": 15,
        "d_id": 37391,
        "documentation": {
            "docstring": "Predict the logical relationship between the premise and hypothesis.\n\n    Defined in :numref:`sec_natural-language-inference-attention`",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 260545,
        "commit_id": "ceeda362402bfc978bcc93d02481fe28e21a07ad",
        "repo": "scikit-learn",
        "path": "sklearn/manifold/_locally_linear.py",
        "file_name": "_locally_linear.py",
        "fun_name": "fit",
        "commit_message": "MAINT Use _validate_params in LocallyLinearEmbedding (#23938)\n\nCo-authored-by: jeremiedbb <jeremiedbb@yahoo.fr>",
        "code": "def fit(self, X, y=None):\n        \n        self._validate_params()\n        self._fit_transform(X)\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 36,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 25,
        "n_ast_nodes": 42,
        "n_identifiers": 6,
        "d_id": 76332,
        "documentation": {
            "docstring": "Compute the embedding vectors for data X.\n\n        Parameters\n        ----------\n        X : array-like of shape (n_samples, n_features)\n            Training set.\n\n        y : Ignored\n            Not used, present here for API consistency by convention.\n\n        Returns\n        -------\n        self : object\n            Fitted `LocallyLinearEmbedding` class instance.\n        ",
            "n_words": 39,
            "vocab_size": 36,
            "n_whitespaces": 128,
            "language": "en"
        }
    },
    {
        "id": 175018,
        "commit_id": "83c85e94b70aa5b3211ef3cc592d8cd8619beb15",
        "repo": "pip",
        "path": "tests/lib/venv.py",
        "file_name": "venv.py",
        "fun_name": "_customize_site",
        "commit_message": "Fix legacy virtualenv setup in tests",
        "code": "def _customize_site(self) -> None:\n        if not LEGACY_VIRTUALENV or self._venv_type == \"venv\":\n            # Enable user site (before system).\n            contents = textwrap.dedent(\n                f\n            ).strip()\n        else:\n            contents = \"\"\n        if self._sitecustomize is not None:\n            contents += \"\\n\" + self._sitecustomize\n        sitecustomize = self.site / \"sitecustomize.py\"\n        sitecustomize.write_text(contents)\n        # Make sure bytecode is up-to-date too.\n        assert compileall.compile_file(str(sitecustomize), quiet=1, force=True)\n",
        "url": "https://github.com/pypa/pip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 171,
        "n_words": 53,
        "vocab_size": 43,
        "complexity": 4,
        "nloc": 32,
        "token_counts": 81,
        "n_ast_nodes": 154,
        "n_identifiers": 18,
        "d_id": 41545,
        "documentation": {
            "docstring": "\n                import os, site, sys\n                if not os.environ.get('PYTHONNOUSERSITE', False):\n                    site.ENABLE_USER_SITE = {self._user_site_packages}\n                    # First, drop system-sites related paths.\n                    original_sys_path = sys.path[:]\n                    known_paths = set()\n                    for path in site.getsitepackages():\n                        site.addsitedir(path, known_paths=known_paths)\n                    system_paths = sys.path[len(original_sys_path):]\n                    for path in system_paths:\n                        if path in original_sys_path:\n                            original_sys_path.remove(path)\n                    sys.path = original_sys_path\n                    # Second, add user-site.\n                    if {self._user_site_packages}:\n                        site.addsitedir(site.getusersitepackages())\n                    # Third, add back system-sites related paths.\n                    for path in site.getsitepackages():\n                        site.addsitedir(path)\n                ",
            "n_words": 63,
            "vocab_size": 41,
            "n_whitespaces": 456,
            "language": "en"
        }
    },
    {
        "id": 85091,
        "commit_id": "4e4689949438735622bdf669f05d218c671e7e01",
        "repo": "zulip",
        "path": "zerver/webhooks/bitbucket2/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_bitbucket2_on_push_commits_multiple_committers_with_others",
        "commit_message": "webhooks: Pick a more reasonable length for short sha.\n\n7 characters are not enough for large projects, so we change\nit to reasonably longer. As an example, The Linux kernel needs\nat least 11 characters of sha in its shortened form to identify\na revision. We pick 11 so it should work for most of the projects.\n\nSigned-off-by: Zixuan James Li <p359101898@gmail.com>",
        "code": "def test_bitbucket2_on_push_commits_multiple_committers_with_others(self) -> None:\n        commit_info = \"* first commit ([84b96adc644](https://bitbucket.org/kolaszek/repository-name/commits/84b96adc644a30fd6465b3d196369d880762afed))\\n\"\n        expected_message = f\n        self.check_webhook(\n            \"push_multiple_committers_with_others\", TOPIC_BRANCH_EVENTS, expected_message\n        )\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 56,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 24,
        "n_ast_nodes": 52,
        "n_identifiers": 6,
        "d_id": 17927,
        "documentation": {
            "docstring": "Tomasz [pushed](https://bitbucket.org/kolaszek/repository-name/branch/master) 10 commits to branch master. Commits by Tomasz (4), James (3), Brendon (2) and others (1).\\n\\n{commit_info*9}* first commit ([84b96adc644](https://bitbucket.org/kolaszek/repository-name/commits/84b96adc644a30fd6465b3d196369d880762afed))",
            "n_words": 21,
            "vocab_size": 20,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 109916,
        "commit_id": "df6f95703b60348e01603f98a439b133da2938a0",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/art3d.py",
        "file_name": "art3d.py",
        "fun_name": "line_collection_2d_to_3d",
        "commit_message": "Improve mpl_toolkit documentation",
        "code": "def line_collection_2d_to_3d(col, zs=0, zdir='z'):\n    \n    segments3d = _paths_to_3d_segments(col.get_paths(), zs, zdir)\n    col.__class__ = Line3DCollection\n    col.set_segments(segments3d)\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 25,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 39,
        "n_ast_nodes": 64,
        "n_identifiers": 10,
        "d_id": 23823,
        "documentation": {
            "docstring": "Convert a `.LineCollection` to a `.Line3DCollection` object.",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 204735,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/serializers/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "register_serializer",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def register_serializer(format, serializer_module, serializers=None):\n    \n    if serializers is None and not _serializers:\n        _load_serializers()\n\n    try:\n        module = importlib.import_module(serializer_module)\n    except ImportError as exc:\n        bad_serializer = BadSerializer(exc)\n\n        module = type(\n            \"BadSerializerModule\",\n            (),\n            {\n                \"Deserializer\": bad_serializer,\n                \"Serializer\": bad_serializer,\n            },\n        )\n\n    if serializers is None:\n        _serializers[format] = module\n    else:\n        serializers[format] = module\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 187,
        "n_words": 46,
        "vocab_size": 35,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 84,
        "n_ast_nodes": 140,
        "n_identifiers": 14,
        "d_id": 50863,
        "documentation": {
            "docstring": "Register a new serializer.\n\n    ``serializer_module`` should be the fully qualified module name\n    for the serializer.\n\n    If ``serializers`` is provided, the registration will be added\n    to the provided dictionary.\n\n    If ``serializers`` is not provided, the registration will be made\n    directly into the global register of serializers. Adding serializers\n    directly is not a thread-safe operation.\n    ",
            "n_words": 53,
            "vocab_size": 35,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 103211,
        "commit_id": "fd0262413e84c02f93d15eca1f87e1ba74cbe34e",
        "repo": "kitty",
        "path": "kitty/shm.py",
        "file_name": "shm.py",
        "fun_name": "close",
        "commit_message": "Access to POSIX shared memory from Python",
        "code": "def close(self) -> None:\n        \n        if self._buf is not None:\n            self._buf.release()\n            self._buf = None\n        if self._mmap is not None:\n            self._mmap.close()\n        if self._fd >= 0:\n            os.close(self._fd)\n            self._fd = -1\n",
        "url": "https://github.com/kovidgoyal/kitty.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 110,
        "n_words": 27,
        "vocab_size": 18,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 64,
        "n_ast_nodes": 106,
        "n_identifiers": 7,
        "d_id": 21617,
        "documentation": {
            "docstring": "Closes access to the shared memory from this instance but does\n        not destroy the shared memory block.",
            "n_words": 17,
            "vocab_size": 14,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 104318,
        "commit_id": "b55c590809381d7822ad76c2bebbb06e895393fa",
        "repo": "datasets",
        "path": "tests/utils.py",
        "file_name": "utils.py",
        "fun_name": "require_libsndfile_with_opus",
        "commit_message": "process .opus files (for Multilingual Spoken Words) (#3666)\n\n* check version of libsndfile explicitly (instead of catching an error)\r\n\r\n* fix version of libsndfile\r\n\r\n* add test for opus decoding\r\n\r\n* add decorator to pass tests that require libsndfile>=1.0.30",
        "code": "def require_libsndfile_with_opus(test_case):\n    \n    if (sys.platform != \"linux\" and find_spec(\"soundfile\")) or (sys.platform == \"linux\" and find_library(\"sndfile\")):\n        import soundfile\n\n        # soundfile library is needed to be installed to check libsndfile version\n\n        if version.parse(soundfile.__libsndfile_version__) < version.parse(\"1.0.30\"):\n            test_case = unittest.skip(\n                \"test requires libsndfile>=1.0.30: `conda install -c conda-forge libsndfile>=1.0.30`\"\n            )(test_case)\n    else:\n        test_case = require_sndfile(test_case)\n\n    return test_case\n\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 127,
        "n_words": 50,
        "vocab_size": 41,
        "complexity": 6,
        "nloc": 10,
        "token_counts": 73,
        "n_ast_nodes": 134,
        "n_identifiers": 13,
        "d_id": 21816,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires libsndfile>=1.0.30 (version that is required for opus decoding).\n\n    These tests are skipped when libsndfile is <1.0.30.\n\n    ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 276127,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/saving/saved_model/save_impl.py",
        "file_name": "save_impl.py",
        "fun_name": "_replace_child_layer_functions",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _replace_child_layer_functions(layer, serialization_cache):\n    \n    # pylint: disable=protected-access\n    original_fns = {}\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 18,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 6,
        "nloc": 22,
        "token_counts": 106,
        "n_ast_nodes": 23,
        "n_identifiers": 4,
        "d_id": 81571,
        "documentation": {
            "docstring": "Replaces functions in the children layers with wrapped tf.functions.\n\n    This step allows functions from parent layers to reference the wrapped\n    functions from their children layers instead of retracing the ops.\n\n    This function also resets all losses stored in the layer. These are stored in\n    the returned dictionary. Use `_restore_child_layer_functions` to restore\n    the original attributes.\n\n    Args:\n      layer: Keras Layer object.\n      serialization_cache: Dictionary shared between all objects during\n        serialization.\n\n    Returns:\n      Dictionary mapping layer objects -> original functions and losses:\n        { Child layer 1: {\n            'losses': Original losses,\n            'call': Original call function\n            '_activity_regularizer': Original activity regularizer},\n          Child layer 2: ...\n        }\n    ",
            "n_words": 98,
            "vocab_size": 69,
            "n_whitespaces": 200,
            "language": "en"
        }
    },
    {
        "id": 101458,
        "commit_id": "13cfb3f39e72e9ca181f173b7b3db2a048db0d08",
        "repo": "faceswap",
        "path": "plugins/extract/pipeline.py",
        "file_name": "pipeline.py",
        "fun_name": "_parallel_scaling",
        "commit_message": "extract: Add batch processing mode",
        "code": "def _parallel_scaling(self) -> Dict[int, float]:\n        \n        retval = {0: 1.0,\n                  1: 1.0,\n                  2: 0.7,\n                  3: 0.55,\n                  4: 0.5,\n                  5: 0.4}\n        logger.trace(retval)  # type: ignore\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 139,
        "n_words": 25,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 22,
        "token_counts": 60,
        "n_ast_nodes": 72,
        "n_identifiers": 8,
        "d_id": 20871,
        "documentation": {
            "docstring": " dict: key is number of parallel plugins being loaded, value is the scaling factor that\n        the total base vram for those plugins should be scaled by\n\n        Notes\n        -----\n        VRAM for parallel plugins does not stack in a linear manner. Calculating the precise\n        scaling for any given plugin combination is non trivial, however the following are\n        calculations based on running 2-5 plugins in parallel using s3fd, fan, unet, vgg-clear\n        and vgg-obstructed. The worst ratio is selected for each combination, plus a little extra\n        to ensure that vram is not used up.\n\n        If OOM errors are being reported, then these ratios should be relaxed some more\n        ",
            "n_words": 104,
            "vocab_size": 79,
            "n_whitespaces": 175,
            "language": "en"
        }
    },
    {
        "id": 289490,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "hass",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "def hass(hass_fixture_setup, loop, load_registries, hass_storage, request):\n    \n\n    hass_fixture_setup.append(True)\n\n    orig_tz = dt_util.DEFAULT_TIME_ZONE\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 19,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 111,
        "n_ast_nodes": 39,
        "n_identifiers": 10,
        "d_id": 88632,
        "documentation": {
            "docstring": "Fixture to provide a test instance of Home Assistant.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 205875,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/sql/query.py",
        "file_name": "query.py",
        "fun_name": "change_aliases",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def change_aliases(self, change_map):\n        \n        # If keys and values of change_map were to intersect, an alias might be\n        # updated twice (e.g. T4 -> T5, T5 -> T6, so also T4 -> T6) depending\n        # on their order in change_map.\n        assert set(change_map).isdisjoint(change_map.values())\n\n        # 1. Update references in \"select\" (normal columns plus aliases),\n        # \"group by\" and \"where\".\n        self.where.relabel_aliases(change_map)\n        if isinstance(self.group_by, tuple):\n            self.group_by = tuple(\n                [col.relabeled_clone(change_map) for col in self.group_by]\n            )\n        self.select = tuple([col.relabeled_clone(change_map) for col in self.select])\n        self.annotations = self.annotations and {\n            key: col.relabeled_clone(change_map)\n            for key, col in self.annotations.items()\n        }\n\n        # 2. Rename the alias in the internal table/alias datastructures.\n        for old_alias, new_alias in change_map.items():\n            if old_alias not in self.alias_map:\n                continue\n            alias_data = self.alias_map[old_alias].relabeled_clone(change_map)\n            self.alias_map[new_alias] = alias_data\n            self.alias_refcount[new_alias] = self.alias_refcount[old_alias]\n            del self.alias_refcount[old_alias]\n            del self.alias_map[old_alias]\n\n            table_aliases = self.table_map[alias_data.table_name]\n            for pos, alias in enumerate(table_aliases):\n                if alias == old_alias:\n                    table_aliases[pos] = new_alias\n                    break\n        self.external_aliases = {\n            # Table is aliased or it's being changed and thus is aliased.\n            change_map.get(alias, alias): (aliased or alias in change_map)\n            for alias, aliased in self.external_aliases.items()\n        }\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 527,
        "n_words": 167,
        "vocab_size": 113,
        "complexity": 12,
        "nloc": 29,
        "token_counts": 246,
        "n_ast_nodes": 385,
        "n_identifiers": 31,
        "d_id": 51257,
        "documentation": {
            "docstring": "\n        Change the aliases in change_map (which maps old-alias -> new-alias),\n        relabelling any references to them in select columns and the where\n        clause.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 116874,
        "commit_id": "8f9cbb01af1f68c55227cebf4e749b86a2c525ca",
        "repo": "mindsdb",
        "path": "tests/unit/test_executor.py",
        "file_name": "test_executor.py",
        "fun_name": "test_update_from_select",
        "commit_message": "unit tests for:\n- create table\n- insert into",
        "code": "def test_update_from_select(self, mock_handler):\n        self.set_handler(mock_handler, name='pg', tables={'tasks': self.df})\n\n        # --- use predictor ---\n        self.set_predictor(self.task_predictor)\n        sql = \n\n        ret = self.command_executor.execute_command(\n            parse_sql(sql, dialect='mindsdb'))\n        assert ret.error_code is None\n\n        # 1 select and 2 updates\n        assert mock_handler().query.call_count == 3\n\n        # second is update\n        assert mock_handler().query.call_args_list[1][0][0].to_string() == \"update table2 set a1=1, c1='ccc' where (a1 = 1) AND (b1 = 'ccc')\"\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 135,
        "n_words": 54,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 26,
        "token_counts": 94,
        "n_ast_nodes": 157,
        "n_identifiers": 20,
        "d_id": 25858,
        "documentation": {
            "docstring": "\n            update \n                pg.table2                   \n            set\n                a1 = df.a,\n                c1 = df.c\n            from                            \n                (\n                    SELECT model.a as a, model.b as b, model.p as c\n                      FROM pg.tasks as t\n                     JOIN mindsdb.task_model as model\n                     WHERE t.a=1 \n                )\n                as df\n            where  \n                table2.a1 = df.a \n                and table2.b1 = df.b     \n        ",
            "n_words": 42,
            "vocab_size": 34,
            "n_whitespaces": 351,
            "language": "en"
        }
    },
    {
        "id": 271987,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/training_v1.py",
        "file_name": "training_v1.py",
        "fun_name": "_compile_weights_loss_and_weighted_metrics",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _compile_weights_loss_and_weighted_metrics(self, sample_weights=None):\n        \n        with backend.get_graph().as_default():\n            if sample_weights is not None:\n                self._update_sample_weight_modes(sample_weights)\n            self._prepare_sample_weights(sample_weights)\n\n            masks = self._prepare_output_masks()\n\n            # Compute weighted metrics.\n            self._handle_metrics(\n                self.outputs,\n                targets=self._targets,\n                skip_target_masks=self._prepare_skip_target_masks(),\n                sample_weights=self.sample_weights,\n                masks=masks,\n                return_weighted_metrics=True,\n            )\n\n            # Compute total loss.\n            # Used to keep track of the total loss value (stateless).\n            # eg., total_loss = loss_weight_1 * output_1_loss_fn(...) +\n            #                   loss_weight_2 * output_2_loss_fn(...) +\n            #                   layer losses.\n            self.total_loss = self._prepare_total_loss(masks)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 348,
        "n_words": 61,
        "vocab_size": 50,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 93,
        "n_ast_nodes": 154,
        "n_identifiers": 19,
        "d_id": 80923,
        "documentation": {
            "docstring": "Compiles the model loss and weighted metric sub-graphs.\n\n        This may be used to set graph tensors as sample weights (instead of creating\n        placeholders). This functionality is necessary for\n        `tf.keras.estimator.model_to_estimator`, which calls Keras models in a v1\n        graph, and creates iterator tensors for inputs, targets, and sample weights.\n\n        Args:\n          sample_weights: List of tensors to use as the sample weights. Must be the\n            same length as the number of outputs. If left as `None`, placeholders\n            are used instead.\n        ",
            "n_words": 76,
            "vocab_size": 56,
            "n_whitespaces": 149,
            "language": "en"
        }
    },
    {
        "id": 64915,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/payment_order/payment_order.py",
        "file_name": "payment_order.py",
        "fun_name": "get_mop_query",
        "commit_message": "style: format code with black",
        "code": "def get_mop_query(doctype, txt, searchfield, start, page_len, filters):\n\treturn frappe.db.sql(\n\t\t,\n\t\t{\"parent\": filters.get(\"parent\"), \"start\": start, \"page_len\": page_len, \"txt\": \"%%%s%%\" % txt},\n\t)\n\n\n@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()\n@frappe.validate_and_sanitize_search_inputs",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 16,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 50,
        "n_ast_nodes": 99,
        "n_identifiers": 13,
        "d_id": 13751,
        "documentation": {
            "docstring": " select mode_of_payment from `tabPayment Order Reference`\n\t\twhere parent = %(parent)s and mode_of_payment like %(txt)s\n\t\tlimit %(start)s, %(page_len)s",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 71107,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/edit_handlers.py",
        "file_name": "edit_handlers.py",
        "fun_name": "reset_page_edit_handler_cache",
        "commit_message": "Reformat with black",
        "code": "def reset_page_edit_handler_cache(**kwargs):\n    \n    if kwargs[\"setting\"] == \"WAGTAILADMIN_COMMENTS_ENABLED\":\n        set_default_page_edit_handlers(Page)\n        for model in apps.get_models():\n            if issubclass(model, Page):\n                model.get_edit_handler.cache_clear()\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 61,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 76,
        "n_identifiers": 10,
        "d_id": 15624,
        "documentation": {
            "docstring": "\n    Clear page edit handler cache when global WAGTAILADMIN_COMMENTS_ENABLED settings are changed\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 247381,
        "commit_id": "7e91107be1a4287873266e588a3c5b415279f4c8",
        "repo": "synapse",
        "path": "tests/rest/media/v1/test_html_preview.py",
        "file_name": "test_html_preview.py",
        "fun_name": "test_comment",
        "commit_message": "Add type hints to `tests/rest` (#12146)\n\n* Add type hints to `tests/rest`\r\n\r\n* newsfile\r\n\r\n* change import from `SigningKey`",
        "code": "def test_comment(self) -> None:\n        html = b\n\n        tree = decode_body(html, \"http://example.com/test.html\")\n        og = parse_html_to_open_graph(tree, \"http://example.com/test.html\")\n\n        self.assertEqual(og, {\"og:title\": \"Foo\", \"og:description\": \"Some text.\"})\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 48,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 43,
        "n_ast_nodes": 78,
        "n_identifiers": 8,
        "d_id": 71639,
        "documentation": {
            "docstring": "\n        <html>\n        <head><title>Foo</title></head>\n        <body>\n        <!-- HTML comment -->\n        Some text.\n        </body>\n        </html>\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 209763,
        "commit_id": "ca10c5cf00425d0178998ec0b006cbb65ddbfb54",
        "repo": "scapy",
        "path": "scapy/sessions.py",
        "file_name": "sessions.py",
        "fun_name": "_process_packet",
        "commit_message": "[MS-RPCE] and [MS-SMB] major update (#3683)\n\n* Various fixes regarding DCE/RPC build\r\n\r\n* DCE/RPC sessions\r\n\r\n* Cleanup unused code\r\n\r\n* Add missing GSS_WRAP algo names\r\n\r\n* Add find_dcerpc_interface\r\n\r\n* Split SMB client and server\r\n\r\n* Missing StrFixedLenFieldUtf16\r\n\r\n* Remove unfinished smbserver feature\r\n\r\n* Friendlier getter for SMB2\r\n\r\n* DceRpcNak\r\n\r\n* Improve NDR parsing (a lot)\r\n\r\n* Minor SMB2 improvements\r\n\r\n* BIG NDR refactor + Dissect pointer deferal\r\n\r\n* Build with pointer deferral\r\n\r\n* Small build bugs\r\n\r\n* SMB2 logoff, fix rawToken in SMB standalone\r\n\r\n* Add security providers from MS-RPCE to DCERPC\r\n\r\n* Cleanup ptr_pack of NDRPacketListField\r\n\r\n* Clearer exception in find_dcerpc_interface\r\n\r\n* Add minor_version attribute\r\n\r\n* Fix computation of auth_pad in sec_trailer\r\n\r\n* Fix a WTF bug\r\n\r\n* Compute length for NDR arrays\r\n\r\n* Pass enum to EnumField\r\n\r\n* Match union attributes from response with request\r\n\r\n* Improve SMB server\r\n\r\n* Small bug in pointer deferal dissection\r\n\r\n* Add user-friendly utils\r\n\r\n* Add a few NDR tests\r\n\r\n* More user-friendly improvements\r\n\r\n* Bug: parent not copied in clone_with\r\n\r\n* Build: propagate NDR64 and bug fix\r\n\r\n* Default close response parameters\r\n\r\n* Fix Python 2.7\r\n\r\n* Fix SMB2_Create_Context offset\r\n\r\n* Fix SMB2 create context\r\n\r\n* SMB2: support chain, improvements\r\n\r\n* Fix ioctl error\r\n\r\n* SMB: check computeNTProofStr\r\n\r\n* Fix UTCField default\r\n\r\n* Improve FileId capabilities\r\n\r\n* SMB2: contexts\r\n\r\n* Typos\r\n\r\n* Minor NDRUnion fixes\r\n\r\n* Py2 fixes",
        "code": "def _process_packet(self, pkt):\n        # type: (Packet) -> Optional[Packet]\n        \n        if self.app:\n            # Special mode: Application layer. Use on top of TCP\n            pay_class = pkt.__class__\n            if not hasattr(pay_class, \"tcp_reassemble\"):\n                # Being on top of TCP, we have no way of knowing\n                # when a packet ends.\n                return pkt\n            self.data += bytes(pkt)\n            pkt = pay_class.tcp_reassemble(self.data, self.metadata, self.session)\n            if pkt:\n                self.data = b\"\"\n                self.metadata = {}\n                return pkt\n            return None\n\n        from scapy.layers.inet import IP, TCP\n        if not pkt or TCP not in pkt:\n            return pkt\n        pay = pkt[TCP].payload\n        if isinstance(pay, (NoPayload, conf.padding_layer)):\n            return pkt\n        new_data = pay.original\n        # Match packets by a unique TCP identifier\n        seq = pkt[TCP].seq\n        ident = self._get_ident(pkt)\n        data, metadata = self.tcp_frags[ident]\n        tcp_session = self.tcp_sessions[self._get_ident(pkt, True)]\n        # Let's guess which class is going to be used\n        if \"pay_class\" not in metadata:\n            pay_class = pay.__class__\n            if hasattr(pay_class, \"tcp_reassemble\"):\n                tcp_reassemble = pay_class.tcp_reassemble\n            else:\n                # We can't know for sure when a packet ends.\n                # Ignore.\n                return pkt\n            metadata[\"pay_class\"] = pay_class\n            metadata[\"tcp_reassemble\"] = tcp_reassemble\n        else:\n            tcp_reassemble = metadata[\"tcp_reassemble\"]\n        if \"seq\" not in metadata:\n            metadata[\"seq\"] = seq\n        # Get a relative sequence number for a storage purpose\n        relative_seq = metadata.get(\"relative_seq\", None)\n        if relative_seq is None:\n            relative_seq = metadata[\"relative_seq\"] = seq - 1\n        seq = seq - relative_seq\n        # Add the data to the buffer\n        # Note that this take care of retransmission packets.\n        data.append(new_data, seq)\n        # Check TCP FIN or TCP RESET\n        if pkt[TCP].flags.F or pkt[TCP].flags.R:\n            metadata[\"tcp_end\"] = True\n\n        # In case any app layer protocol requires it,\n        # allow the parser to inspect TCP PSH flag\n        if pkt[TCP].flags.P:\n            metadata[\"tcp_psh\"] = True\n        # XXX TODO: check that no empty space is missing in the buffer.\n        # XXX Currently, if a TCP fragment was missing, we won't notice it.\n        packet = None  # type: Optional[Packet]\n        if data.full():\n            # Reassemble using all previous packets\n            packet = tcp_reassemble(bytes(data), metadata, tcp_session)\n        # Stack the result on top of the previous frames\n        if packet:\n            if \"seq\" in metadata:\n                pkt[TCP].seq = metadata[\"seq\"]\n            # Clear buffer\n            data.clear()\n            # Clear TCP reassembly metadata\n            metadata.clear()\n            del self.tcp_frags[ident]\n            # Rebuild resulting packet\n            pay.underlayer.remove_payload()\n            if IP in pkt:\n                pkt[IP].len = None\n                pkt[IP].chksum = None\n            pkt = pkt / packet\n            pkt.wirelen = None\n            return pkt\n        return None\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 1171,
        "n_words": 360,
        "vocab_size": 189,
        "complexity": 18,
        "nloc": 61,
        "token_counts": 405,
        "n_ast_nodes": 675,
        "n_identifiers": 46,
        "d_id": 52769,
        "documentation": {
            "docstring": "Process each packet: matches the TCP seq/ack numbers\n        to follow the TCP streams, and orders the fragments.\n        ",
            "n_words": 17,
            "vocab_size": 14,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 191532,
        "commit_id": "4a4dfbfbed5ca271fc74f61a0b3387314dda8703",
        "repo": "langchain",
        "path": "tests/unit_tests/chains/test_sequential.py",
        "file_name": "test_sequential.py",
        "fun_name": "test_sequential_bad_outputs",
        "commit_message": "Harrison/sequential chains (#168)\n\nadd support for basic sequential chains",
        "code": "def test_sequential_bad_outputs() -> None:\n    \n    chain_1 = FakeChain(input_variables=[\"foo\"], output_variables=[\"bar\"])\n    chain_2 = FakeChain(input_variables=[\"bar\"], output_variables=[\"baz\"])\n    with pytest.raises(ValueError):\n        # \"test\" is not present as an output variable.\n        SequentialChain(\n            chains=[chain_1, chain_2],\n            input_variables=[\"foo\"],\n            output_variables=[\"test\"],\n        )\n\n",
        "url": "https://github.com/hwchase17/langchain.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 95,
        "n_words": 29,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 70,
        "n_ast_nodes": 123,
        "n_identifiers": 11,
        "d_id": 46657,
        "documentation": {
            "docstring": "Test error is raised when bad outputs are specified.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 43210,
        "commit_id": "95bd6b71cc9f5da377e272707f7b68000d980939",
        "repo": "airflow",
        "path": "tests/utils/test_db_cleanup.py",
        "file_name": "test_db_cleanup.py",
        "fun_name": "test_run_cleanup_skip_archive",
        "commit_message": "Don't rely on current ORM structure for db clean command (#23574)\n\nFor command DB clean, by not relying on the ORM models, we will be able to use the command even when the metadatabase is not yet upgraded to the version of Airflow you have installed.\r\n\r\nAdditionally we archive all rows before deletion.",
        "code": "def test_run_cleanup_skip_archive(self, cleanup_table_mock, kwargs, should_skip):\n        \n        run_cleanup(\n            clean_before_timestamp=None,\n            table_names=['log'],\n            dry_run=None,\n            verbose=None,\n            confirm=False,\n            **kwargs,\n        )\n        assert cleanup_table_mock.call_args[1]['skip_archive'] is should_skip\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 111,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 52,
        "n_ast_nodes": 78,
        "n_identifiers": 12,
        "d_id": 7871,
        "documentation": {
            "docstring": "test that delete confirmation input is called when appropriate",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 226741,
        "commit_id": "43e3a4011080911901176aab919c0ecf5046ddd3",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/graph_objs/_figure.py",
        "file_name": "_figure.py",
        "fun_name": "for_each_shape",
        "commit_message": "switch to black .22",
        "code": "def for_each_shape(self, fn, selector=None, row=None, col=None, secondary_y=None):\n        \n        for obj in self._select_annotations_like(\n            prop=\"shapes\",\n            selector=selector,\n            row=row,\n            col=col,\n            secondary_y=secondary_y,\n        ):\n            fn(obj)\n\n        return self\n",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 114,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 59,
        "n_ast_nodes": 86,
        "n_identifiers": 10,
        "d_id": 58414,
        "documentation": {
            "docstring": "\n        Apply a function to all shapes that satisfy the specified selection\n        criteria\n\n        Parameters\n        ----------\n        fn:\n            Function that inputs a single shape object.\n        selector: dict, function, int, str or None (default None)\n            Dict to use as selection criteria.\n            Traces will be selected if they contain properties corresponding\n            to all of the dictionary's keys, with values that exactly match\n            the supplied values. If None (the default), all shapes are\n            selected. If a function, it must be a function accepting a single\n            argument and returning a boolean. The function will be called on\n            each shape and those for which the function returned True\n            will be in the selection. If an int N, the Nth shape matching row\n            and col will be selected (N can be negative). If a string S, the selector\n            is equivalent to dict(type=S).\n        row, col: int or None (default None)\n            Subplot row and column index of shapes to select.\n            To select shapes by row and column, the Figure must have been\n            created using plotly.subplots.make_subplots.  To select only those\n            shapes that are in paper coordinates, set row and col to the\n            string 'paper'.  If None (the default), all shapes are selected.\n        secondary_y: boolean or None (default None)\n            * If True, only select shapes associated with the secondary\n              y-axis of the subplot.\n            * If False, only select shapes associated with the primary\n              y-axis of the subplot.\n            * If None (the default), do not filter shapes based on secondary\n              y-axis.\n\n            To select shapes by secondary y-axis, the Figure must have been\n            created using plotly.subplots.make_subplots. See the docstring\n            for the specs argument to make_subplots for more info on\n            creating subplots with secondary y-axes.\n        Returns\n        -------\n        self\n            Returns the Figure object that the method was called on\n        ",
            "n_words": 282,
            "vocab_size": 142,
            "n_whitespaces": 672,
            "language": "en"
        }
    },
    {
        "id": 151471,
        "commit_id": "76b33359a939e8db89b55f268e9d650f78c51bf3",
        "repo": "freqtrade",
        "path": "freqtrade/freqai/data_drawer.py",
        "file_name": "data_drawer.py",
        "fun_name": "load_drawer_from_disk",
        "commit_message": "add an optional metric tracker to collect train timings, inference timings, and cpu load data",
        "code": "def load_drawer_from_disk(self):\n        \n        exists = self.pair_dictionary_path.is_file()\n        if exists:\n            with open(self.pair_dictionary_path, \"r\") as fp:\n                self.pair_dict = json.load(fp)\n        elif not self.follow_mode:\n            logger.info(\"Could not find existing datadrawer, starting from scratch\")\n        else:\n            logger.warning(\n                f\"Follower could not find pair_dictionary at {self.full_path} \"\n                \"sending null values back to strategy\"\n            )\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 167,
        "n_words": 43,
        "vocab_size": 39,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 62,
        "n_ast_nodes": 121,
        "n_identifiers": 15,
        "d_id": 35018,
        "documentation": {
            "docstring": "\n        Locate and load a previously saved data drawer full of all pair model metadata in\n        present model folder.\n        Load any existing metric tracker that may be present.\n        ",
            "n_words": 27,
            "vocab_size": 26,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 269013,
        "commit_id": "75d70a610dffe927d89ceb400d79bb7f9027b26e",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_v2/optimizer_v2.py",
        "file_name": "optimizer_v2.py",
        "fun_name": "_var_key",
        "commit_message": "Support checkpointing ShardedVariables in optimizer slot variables.\n\nPiperOrigin-RevId: 429577423",
        "code": "def _var_key(var):\n  \n\n  # pylint: disable=protected-access\n  # Get the distributed variable if it exists.\n  if hasattr(var, \"_distributed_container\"):\n    var = var._distributed_container()\n  if getattr(var, \"_in_graph_mode\", False):\n    return var._shared_name\n  return var._unique_id\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 39,
        "n_words": 27,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 69,
        "n_identifiers": 7,
        "d_id": 79831,
        "documentation": {
            "docstring": "Key for representing a primary variable, for looking up slots.\n\n  In graph mode the name is derived from the var shared name.\n  In eager mode the name is derived from the var unique id.\n  If distribution strategy exists, get the primary variable first.\n\n  Args:\n    var: the variable.\n\n  Returns:\n    the unique name of the variable.\n  ",
            "n_words": 54,
            "vocab_size": 35,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 163017,
        "commit_id": "9dfb454dbe5f183b1508a9571ee97938c9cb0db9",
        "repo": "pandas",
        "path": "pandas/io/formats/xml.py",
        "file_name": "xml.py",
        "fun_name": "process_dataframe",
        "commit_message": "REF: Deduplicate to_xml code (#45132)",
        "code": "def process_dataframe(self) -> dict[int | str, dict[str, Any]]:\n        \n\n        df = self.frame\n\n        if self.index:\n            df = df.reset_index()\n\n        if self.na_rep is not None:\n            df = df.fillna(self.na_rep)\n\n        return df.to_dict(orient=\"index\")\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 83,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 64,
        "n_ast_nodes": 103,
        "n_identifiers": 14,
        "d_id": 39359,
        "documentation": {
            "docstring": "\n        Adjust Data Frame to fit xml output.\n\n        This method will adjust underlying data frame for xml output,\n        including optionally replacing missing values and including indexes.\n        ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 190597,
        "commit_id": "4fc3616712edb19179b17dd270ad6cf63abf99c2",
        "repo": "DeOldify",
        "path": "fastai/vision/models/xresnet2.py",
        "file_name": "xresnet2.py",
        "fun_name": "xresnet101",
        "commit_message": "Upgrading to support latest Pytorch version",
        "code": "def xresnet101(pretrained=False, **kwargs):\n    \n    model = XResNet(Bottleneck, [3, 4, 23, 3], **kwargs)\n    if pretrained: model.load_state_dict(model_zoo.load_url(model_urls['xresnet101']))\n    return model\n\n",
        "url": "https://github.com/jantic/DeOldify.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 49,
        "n_ast_nodes": 77,
        "n_identifiers": 10,
        "d_id": 46356,
        "documentation": {
            "docstring": "Constructs a XResNet-101 model.\n\n    Args:\n        pretrained (bool): If True, returns a model pre-trained on ImageNet\n    ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 208444,
        "commit_id": "cb6563dcd85783ea0a687fbe227c4782a8a7cadf",
        "repo": "ipython",
        "path": "IPython/core/tests/test_inputtransformer2.py",
        "file_name": "test_inputtransformer2.py",
        "fun_name": "test_check_complete_II",
        "commit_message": "Fix and test for \"async with does not allow new lines\".\n\nUse the opportunity to add a test, and parametrise a few other, plus set\nthe correct stacklevel.\n\nCloses #12975",
        "code": "def test_check_complete_II(value, expected):\n    \n    cc = ipt2.TransformerManager().check_complete\n    assert cc(value) == expected\n\n\n@pytest.mark.parametrize(\n    \"value, expected\",\n    [\n        (\")\", (\"invalid\", None)),\n        (\"]\", (\"invalid\", None)),\n        (\"}\", (\"invalid\", None)),\n        (\")(\", (\"invalid\", None)),\n        (\"][\", (\"invalid\", None)),\n        (\"}{\", (\"invalid\", None)),\n        (\"]()(\", (\"invalid\", None)),\n        (\"())(\", (\"invalid\", None)),\n        (\")[](\", (\"invalid\", None)),\n        (\"()](\", (\"invalid\", None)),\n    ],\n)",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"value, expected\",\n    [\n        (\")\", (\"invalid\", None)),\n        (\"]\", (\"invalid\", None)),\n        (\"}\", (\"invalid\", None)),\n        (\")(\", (\"invalid\", None)),\n        (\"][\", (\"invalid\", None)),\n        (\"}{\", (\"invalid\", None)),\n        (\"]()(\", (\"invalid\", None)),\n        (\"())(\", (\"invalid\", None)),\n        (\")[](\", (\"invalid\", None)),\n        (\"()](\", (\"invalid\", None)),\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 132,
        "n_words": 46,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 223,
        "n_identifiers": 10,
        "d_id": 52326,
        "documentation": {
            "docstring": "\n    Test that multiple line strings are properly handled.\n\n    Separate test function for convenience\n\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 244324,
        "commit_id": "2631e2879acf0bd20a64dfdd7039f37a8e6afbf6",
        "repo": "mmdetection",
        "path": "mmdet/apis/inference.py",
        "file_name": "inference.py",
        "fun_name": "async_inference_detector",
        "commit_message": "Support Datasampler",
        "code": "async def async_inference_detector(model, imgs):\n    \n    if not isinstance(imgs, (list, tuple)):\n        imgs = [imgs]\n\n    cfg = model.cfg\n\n    if isinstance(imgs[0], np.ndarray):\n        cfg = cfg.copy()\n        # set loading pipeline type\n        cfg.data.test.pipeline[0].type = 'LoadImageFromWebcam'\n\n    cfg.data.test.pipeline = replace_ImageToTensor(cfg.data.test.pipeline)\n    test_pipeline = Compose(cfg.data.test.pipeline)\n\n    datas = []\n    for img in imgs:\n        # prepare data\n        if isinstance(img, np.ndarray):\n            # directly add img\n            data = dict(img=img)\n        else:\n            # add information into dict\n            data = dict(img_info=dict(filename=img), img_prefix=None)\n        # build the data pipeline\n        data = test_pipeline(data)\n        datas.append(data)\n\n    for m in model.modules():\n        assert not isinstance(\n            m,\n            RoIPool), 'CPU inference with RoIPool is not supported currently.'\n\n    # We don't restore `torch.is_grad_enabled()` value during concurrent\n    # inference since execution can overlap\n    torch.set_grad_enabled(False)\n    results = await model.aforward_test(data, rescale=True)\n    return results\n\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 298,
        "n_words": 113,
        "vocab_size": 80,
        "complexity": 6,
        "nloc": 24,
        "token_counts": 193,
        "n_ast_nodes": 314,
        "n_identifiers": 32,
        "d_id": 70325,
        "documentation": {
            "docstring": "Async inference image(s) with the detector.\n\n    Args:\n        model (nn.Module): The loaded detector.\n        img (str | ndarray): Either image files or loaded images.\n\n    Returns:\n        Awaitable detection results.\n    ",
            "n_words": 26,
            "vocab_size": 24,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 54788,
        "commit_id": "fc9f253912945e088e48cc723af383e6a9f46faf",
        "repo": "prefect",
        "path": "src/prefect/orion/database/migrations/versions/postgresql/2022_04_21_095519_14dc68cc5853_backfill_state_name.py",
        "file_name": "2022_04_21_095519_14dc68cc5853_backfill_state_name.py",
        "fun_name": "upgrade",
        "commit_message": "Add run.state_name columns",
        "code": "def upgrade():\n    \n    conn = op.get_bind()\n\n    update_flow_run_state_name_in_batches = \n\n    result = conn.execute(sa.text(update_flow_run_state_name_in_batches))\n    while True:\n        if result.rowcount <= 0:\n            break\n\n    update_task_run_state_name_in_batches = \n\n    result = conn.execute(sa.text(update_task_run_state_name_in_batches))\n    while True:\n        if result.rowcount <= 0:\n            break\n\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 29,
        "vocab_size": 17,
        "complexity": 5,
        "nloc": 26,
        "token_counts": 66,
        "n_ast_nodes": 116,
        "n_identifiers": 11,
        "d_id": 11142,
        "documentation": {
            "docstring": "\n    Backfills state_name column for task_run and flow_run tables.\n\n    This is a data only migration that can be run as many\n    times as desired.\n    \n        WITH null_flow_run_state_name_cte as (SELECT id from flow_run where state_name is null limit 500)\n        UPDATE flow_run\n        SET state_name = flow_run_state.name\n        FROM flow_run_state, null_flow_run_state_name_cte\n        WHERE flow_run.state_id = flow_run_state.id\n        AND flow_run.id = null_flow_run_state_name_cte.id;\n    \n        WITH null_task_run_state_name_cte as (SELECT id from task_run where state_name is null limit 500)\n        UPDATE task_run\n        SET state_name = task_run_state.name\n        FROM task_run_state, null_task_run_state_name_cte\n        WHERE task_run.state_id = task_run_state.id\n        AND task_run.id = null_task_run_state_name_cte.id;\n    ",
            "n_words": 83,
            "vocab_size": 50,
            "n_whitespaces": 188,
            "language": "en"
        }
    },
    {
        "id": 137403,
        "commit_id": "f9ec2d1ae2e14e1f1ed38d315dfd643f600dc397",
        "repo": "ray",
        "path": "rllib/algorithms/algorithm_config.py",
        "file_name": "algorithm_config.py",
        "fun_name": "get_default_rl_module_class",
        "commit_message": "[RLlib] Make RLModule initialization easy (#31069)\n\n1. Moved the `_enable_rl_module_api` signature into `rl_module()` api of the algorithmConfig.\r\n2. Added the ability for the user to override the entire RLModule from algorithmConfig by\r\nsimply changing the class.\r\n3. updated marl_module: we now have only one MARLModule base-class that can be used stand-alone, users can override it completely if they want.\r\n4. Removed test_torch_marl_module (Will add it back in a framework agnostic way)\r\n5. Updated TorchMARL and RL modules to use the new constructor format.\r\n6. Core tests now works independent of failures of PPORLModule.\r\n7. Core tests is now based on factory methods of RLModule.\r\n8. created a new isolated unittest for marl_module\r\n9. update ppo torch RL module to adhere to the new API changes.\r\n10. get_rl_module_class is now a instance method instead of classmethod\r\n11. made enabling the api more explicit from algo_config()\r\n\r\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def get_default_rl_module_class(self) -> Union[Type[\"RLModule\"], str]:\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 18,
        "n_ast_nodes": 31,
        "n_identifiers": 6,
        "d_id": 31158,
        "documentation": {
            "docstring": "Returns the RLModule class to use for this algorithm.\n\n        Override this method in the sub-class to return the RLModule class type given\n        the input framework.\n\n        Returns:\n            The RLModule class to use for this algorithm either as a class type or as\n            a string (e.g. x.y.z).\n        ",
            "n_words": 45,
            "vocab_size": 28,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 311067,
        "commit_id": "a371f8f7882bd1c7de5e344aa23f7d6b1967ce66",
        "repo": "core",
        "path": "homeassistant/components/spotify/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "is_spotify_media_type",
        "commit_message": "Allow browsing the Spotify media player in Sonos (#64921)",
        "code": "def is_spotify_media_type(media_content_type):\n    \n    return media_content_type.startswith(MEDIA_PLAYER_PREFIX)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 10,
        "n_words": 4,
        "vocab_size": 4,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 13,
        "n_ast_nodes": 24,
        "n_identifiers": 4,
        "d_id": 109737,
        "documentation": {
            "docstring": "Return whether the media_content_type is a valid Spotify media_id.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 101545,
        "commit_id": "7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5",
        "repo": "faceswap",
        "path": "lib/training/preview_cv.py",
        "file_name": "preview_cv.py",
        "fun_name": "_window_closed",
        "commit_message": "Training - Use custom preview pop-out",
        "code": "def _window_closed(self) -> bool:\n        \n        retval = any(cv2.getWindowProperty(win, cv2.WND_PROP_VISIBLE) < 1 for win in self._windows)\n        if retval:\n            logger.debug(\"Window closed detected\")\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 60,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 42,
        "n_ast_nodes": 70,
        "n_identifiers": 12,
        "d_id": 20955,
        "documentation": {
            "docstring": " bool: ``True`` if any window has been closed otherwise ``False`` ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 199448,
        "commit_id": "fc7b460a21e340d4104e67c86d973765c9b4071b",
        "repo": "sympy",
        "path": "sympy/functions/elementary/piecewise.py",
        "file_name": "piecewise.py",
        "fun_name": "eval",
        "commit_message": "Refactor Piecewise simplifcation/evaluation",
        "code": "def eval(cls, *_args):\n        \n        if not _args:\n            return Undefined\n\n        if len(_args) == 1 and _args[0][-1] == True:\n            return _args[0][0]\n\n        newargs = _piecewise_collapse_arguments(_args)\n\n        # some conditions may have been redundant\n        missing = len(newargs) != len(_args)\n        # some conditions may have changed\n        same = all(a == b for a, b in zip(newargs, _args))\n        # if either change happened we return the expr with the\n        # updated args\n        if not newargs:\n            raise ValueError(filldedent())\n        if missing or not same:\n            return cls(*newargs)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 204,
        "n_words": 76,
        "vocab_size": 52,
        "complexity": 8,
        "nloc": 15,
        "token_counts": 102,
        "n_ast_nodes": 169,
        "n_identifiers": 15,
        "d_id": 49272,
        "documentation": {
            "docstring": "Either return a modified version of the args or, if no\n        modifications were made, return None.\n\n        Modifications that are made here:\n\n        1. relationals are made canonical\n        2. any False conditions are dropped\n        3. any repeat of a previous condition is ignored\n        4. any args past one with a true condition are dropped\n\n        If there are no args left, nan will be returned.\n        If there is a single arg with a True condition, its\n        corresponding expression will be returned.\n\n        EXAMPLES\n        ========\n\n        >>> from sympy import Piecewise\n        >>> from sympy.abc import x\n        >>> cond = -x < -1\n        >>> args = [(1, cond), (4, cond), (3, False), (2, True), (5, x < 1)]\n        >>> Piecewise(*args, evaluate=False)\n        Piecewise((1, -x < -1), (4, -x < -1), (2, True))\n        >>> Piecewise(*args)\n        Piecewise((1, x > 1), (2, True))\n        \n                There are no conditions (or none that\n                are not trivially false) to define an\n                expression.",
            "n_words": 147,
            "vocab_size": 94,
            "n_whitespaces": 332,
            "language": "en"
        }
    },
    {
        "id": 186378,
        "commit_id": "eeca208c8f57304590ac1af80b496e61021aaa45",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/configurator.py",
        "file_name": "configurator.py",
        "fun_name": "_populate_vhost_names_v2",
        "commit_message": "Various clean-ups in certbot-apache. Use f-strings. (#9132)\n\n* Various clean-ups in certbot-apache. Use f-strings.\r\n\r\n* Smaller tweaks",
        "code": "def _populate_vhost_names_v2(self, vhost):\n        \n\n        servername_match = vhost.node.find_directives(\"ServerName\", exclude=False)\n        serveralias_match = vhost.node.find_directives(\"ServerAlias\", exclude=False)\n\n        servername = None\n        if servername_match:\n            servername = servername_match[-1].parameters[-1]\n\n        if not vhost.modmacro:\n            for alias in serveralias_match:\n                for serveralias in alias.parameters:\n                    vhost.aliases.add(serveralias)\n            vhost.name = servername\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 143,
        "n_words": 34,
        "vocab_size": 24,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 86,
        "n_ast_nodes": 139,
        "n_identifiers": 16,
        "d_id": 45474,
        "documentation": {
            "docstring": "Helper function that populates the VirtualHost names.\n        :param host: In progress vhost whose names will be added\n        :type host: :class:`~certbot_apache.obj.VirtualHost`\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 61975,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py",
        "file_name": "database.py",
        "fun_name": "get_resource_path",
        "commit_message": "upd; format",
        "code": "def get_resource_path(self, relative_path):\n        \n        r = self.get_distinfo_resource('RESOURCES')\n        with contextlib.closing(r.as_stream()) as stream:\n            with CSVReader(stream=stream) as resources_reader:\n                for relative, destination in resources_reader:\n                    if relative == relative_path:\n                        return destination\n        raise KeyError('no resource file with relative path %r '\n                       'is installed' % relative_path)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 156,
        "n_words": 38,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 62,
        "n_ast_nodes": 113,
        "n_identifiers": 14,
        "d_id": 12790,
        "documentation": {
            "docstring": "\n        NOTE: This API may change in the future.\n\n        Return the absolute path to a resource file with the given relative\n        path.\n\n        :param relative_path: The path, relative to .dist-info, of the resource\n                              of interest.\n        :return: The absolute path where the resource is to be found.\n        ",
            "n_words": 44,
            "vocab_size": 31,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 276811,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "get_training_or_validation_split",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_training_or_validation_split(samples, labels, validation_split, subset):\n    \n    if not validation_split:\n        return samples, labels\n\n    num_val_samples = int(validation_split * len(samples))\n    if subset == \"training\":\n        print(f\"Using {len(samples) - num_val_samples} files for training.\")\n        samples = samples[:-num_val_samples]\n        labels = labels[:-num_val_samples]\n    elif subset == \"validation\":\n        print(f\"Using {num_val_samples} files for validation.\")\n        samples = samples[-num_val_samples:]\n        labels = labels[-num_val_samples:]\n    else:\n        raise ValueError(\n            '`subset` must be either \"training\" '\n            f'or \"validation\", received: {subset}'\n        )\n    return samples, labels\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 171,
        "n_words": 65,
        "vocab_size": 49,
        "complexity": 4,
        "nloc": 18,
        "token_counts": 96,
        "n_ast_nodes": 184,
        "n_identifiers": 10,
        "d_id": 81744,
        "documentation": {
            "docstring": "Potentially restict samples & labels to a training or validation split.\n\n    Args:\n      samples: List of elements.\n      labels: List of corresponding labels.\n      validation_split: Float, fraction of data to reserve for validation.\n      subset: Subset of the data to return.\n        Either \"training\", \"validation\", or None. If None, we return all of the\n        data.\n\n    Returns:\n      tuple (samples, labels), potentially restricted to the specified subset.\n    ",
            "n_words": 60,
            "vocab_size": 48,
            "n_whitespaces": 108,
            "language": "en"
        }
    },
    {
        "id": 66253,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/hr/report/employees_working_on_a_holiday/employees_working_on_a_holiday.py",
        "file_name": "employees_working_on_a_holiday.py",
        "fun_name": "get_employees",
        "commit_message": "style: format code with black",
        "code": "def get_employees(filters):\n\tholiday_filter = [\n\t\t[\"holiday_date\", \">=\", filters.from_date],\n\t\t[\"holiday_date\", \"<=\", filters.to_date],\n\t]\n\tif filters.holiday_list:\n\t\tholiday_filter.append([\"parent\", \"=\", filters.holiday_list])\n\n\tholidays = frappe.get_all(\n\t\t\"Holiday\", fields=[\"holiday_date\", \"description\"], filters=holiday_filter\n\t)\n\n\tholiday_names = {}\n\tholidays_list = []\n\n\tfor holiday in holidays:\n\t\tholidays_list.append(holiday.holiday_date)\n\t\tholiday_names[holiday.holiday_date] = holiday.description\n\n\tif holidays_list:\n\t\tcond = \" attendance_date in %(holidays_list)s\"\n\n\t\tif filters.holiday_list:\n\t\t\tcond += (\n\t\t\t\t\n\t\t\t)\n\n\t\temployee_list = frappe.db.sql(\n\t\t\t\n\t\t\t% cond.format(\", \".join([\"%s\"] * len(holidays_list))),\n\t\t\t{\"holidays_list\": holidays_list, \"holidays\": filters.holiday_list},\n\t\t\tas_list=True,\n\t\t)\n\n\t\tfor employee_data in employee_list:\n\t\t\temployee_data.append(holiday_names[employee_data[2]])\n\n\t\treturn employee_list\n\telse:\n\t\treturn []\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 47,
        "n_words": 77,
        "vocab_size": 58,
        "complexity": 6,
        "nloc": 35,
        "token_counts": 185,
        "n_ast_nodes": 308,
        "n_identifiers": 25,
        "d_id": 14147,
        "documentation": {
            "docstring": " and (employee in (select employee from tabEmployee where holiday_list = %(holidays)s))select\n\t\t\t\temployee, employee_name, attendance_date, status\n\t\t\tfrom tabAttendance\n\t\t\twhere %s",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 201823,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/backends/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_django_date_trunc",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_django_date_trunc(self):\n        \n        updated = datetime.datetime(2010, 2, 20)\n        SchoolClass.objects.create(year=2009, last_updated=updated)\n        years = SchoolClass.objects.dates(\"last_updated\", \"year\")\n        self.assertEqual(list(years), [datetime.date(2010, 1, 1)])\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 52,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 66,
        "n_ast_nodes": 105,
        "n_identifiers": 14,
        "d_id": 50004,
        "documentation": {
            "docstring": "\n        Test the custom ``django_date_trunc method``, in particular against\n        fields which clash with strings passed to it (e.g. 'year') (#12818).\n        ",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 35453,
        "commit_id": "29c10a41d04f855c433a6cde7797b325651417d2",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "get_tests_dir",
        "commit_message": "[Test refactor 1/5] Per-folder tests reorganization (#15725)\n\n* Per-folder tests reorganization\r\n\r\nCo-authored-by: sgugger <sylvain.gugger@gmail.com>\r\nCo-authored-by: Stas Bekman <stas@stason.org>",
        "code": "def get_tests_dir(append_path=None):\n    \n    # this function caller's __file__\n    caller__file__ = inspect.stack()[1][1]\n    tests_dir = os.path.abspath(os.path.dirname(caller__file__))\n\n    while not tests_dir.endswith(\"tests\"):\n        tests_dir = os.path.dirname(tests_dir)\n\n    if append_path:\n        return os.path.join(tests_dir, append_path)\n    else:\n        return tests_dir\n\n\n#\n# Helper functions for dealing with testing text outputs\n# The original code came from:\n# https://github.com/fastai/fastai/blob/master/tests/utils/text.py\n\n# When any function contains print() calls that get overwritten, like progress bars,\n# a special care needs to be applied, since under pytest -s captured output (capsys\n# or contextlib.redirect_stdout) contains any temporary printed strings, followed by\n# \\r's. This helper function ensures that the buffer will contain the same output\n# with and without -s in pytest, by turning:\n# foo bar\\r tar mar\\r final message\n# into:\n# final message\n# it can handle a single string or a multiline buffer",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 158,
        "n_words": 129,
        "vocab_size": 95,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 75,
        "n_ast_nodes": 138,
        "n_identifiers": 12,
        "d_id": 6452,
        "documentation": {
            "docstring": "\n    Args:\n        append_path: optional path to append to the tests dir path\n\n    Return:\n        The full path to the `tests` dir, so that the tests can be invoked from anywhere. Optionally `append_path` is\n        joined after the `tests` dir the former is provided.\n\n    ",
            "n_words": 40,
            "vocab_size": 28,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 53272,
        "commit_id": "36e7e0838aeaffc9492b330297e4905f3ab4b11f",
        "repo": "prefect",
        "path": "src/prefect/orion/database/alembic_commands.py",
        "file_name": "alembic_commands.py",
        "fun_name": "alembic_stamp",
        "commit_message": "code review revisions pt3",
        "code": "def alembic_stamp(revision):\n    \n    # lazy import for performance\n    import alembic.command\n\n    alembic.command.stamp(alembic_config(), revision=revision)\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 23,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 42,
        "n_identifiers": 6,
        "d_id": 10767,
        "documentation": {
            "docstring": "\n    Stamp the revision table with the given revision; don’t run any migrations\n\n    Args:\n        revision: The revision passed to `alembic stamp`.\n    ",
            "n_words": 20,
            "vocab_size": 18,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 62961,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pep517/build.py",
        "file_name": "build.py",
        "fun_name": "compat_system",
        "commit_message": "upd; format",
        "code": "def compat_system(source_dir):\n    \n    try:\n        system = load_system(source_dir)\n    except (FileNotFoundError, KeyError):\n        system = {}\n    system.setdefault(\n        'build-backend',\n        'setuptools.build_meta:__legacy__',\n    )\n    system.setdefault('requires', ['setuptools', 'wheel'])\n    return system\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 70,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 48,
        "n_ast_nodes": 87,
        "n_identifiers": 7,
        "d_id": 13077,
        "documentation": {
            "docstring": "\n    Given a source dir, attempt to get a build system backend\n    and requirements from pyproject.toml. Fallback to\n    setuptools but only if the file was not found or a build\n    system was not indicated.\n    ",
            "n_words": 33,
            "vocab_size": 26,
            "n_whitespaces": 49,
            "language": "en"
        }
    },
    {
        "id": 42431,
        "commit_id": "b0e85694107992e00a2f9fb48e6410c50fe1f1f6",
        "repo": "nltk",
        "path": "nltk/app/wordnet_app.py",
        "file_name": "wordnet_app.py",
        "fun_name": "get_static_upper_page",
        "commit_message": "Updated Copyright year to 2022 (#2928)",
        "code": "def get_static_upper_page(with_shutdown):\n    \n    template = \n    if with_shutdown:\n        shutdown_link = '<a href=\"SHUTDOWN THE SERVER\">Shutdown</a>'\n    else:\n        shutdown_link = \"\"\n\n    return template % shutdown_link\n\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 50,
        "n_words": 20,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 30,
        "token_counts": 24,
        "n_ast_nodes": 49,
        "n_identifiers": 4,
        "d_id": 7529,
        "documentation": {
            "docstring": "\n    Return the upper frame page,\n\n    If with_shutdown is True then a 'shutdown' button is also provided\n    to shutdown the server.\n    \n<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.01//EN\" \"http://www.w3.org/TR/html4/strict.dtd\">\n<html>\n    <!-- Natural Language Toolkit: Wordnet Interface: Graphical Wordnet Browser\n        Copyright (C) 2001-2022 NLTK Project\n        Author: Jussi Salmela <jtsalmela@users.sourceforge.net>\n        URL: <https://www.nltk.org/>\n        For license information, see LICENSE.TXT -->\n    <head>\n                <meta http-equiv=\"Content-Type\" content=\"text/html; charset=iso-8859-1\" />\n        <title>Untitled Document</title>\n    </head>\n    <body>\n    <form method=\"GET\" action=\"search\" target=\"body\">\n            Current Word:&nbsp;<input type=\"text\" id=\"currentWord\" size=\"10\" disabled>\n            Next Word:&nbsp;<input type=\"text\" id=\"nextWord\" name=\"nextWord\" size=\"10\">\n            <input name=\"searchButton\" type=\"submit\" value=\"Search\">\n    </form>\n        <a target=\"body\" href=\"web_help.html\">Help</a>\n        %s\n\n</body>\n</html>\n",
            "n_words": 91,
            "vocab_size": 85,
            "n_whitespaces": 215,
            "language": "en"
        }
    },
    {
        "id": 305307,
        "commit_id": "61ff52c93acd2f274d24469494b51356c88bb66f",
        "repo": "core",
        "path": "tests/components/deconz/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_add_battery_later",
        "commit_message": "Normalize deCONZ sensor unique IDs (#76357)\n\n* Normalize deCONZ sensor unique IDs\r\n\r\n* Handle battery sensors properly\r\n\r\n* Fix daylight sensor unique ID",
        "code": "async def test_add_battery_later(hass, aioclient_mock, mock_deconz_websocket):\n    \n    data = {\n        \"sensors\": {\n            \"1\": {\n                \"name\": \"Switch 1\",\n                \"type\": \"ZHASwitch\",\n                \"state\": {\"buttonevent\": 1000},\n                \"config\": {},\n                \"uniqueid\": \"00:00:00:00:00:00:00:00-00-0000\",\n            },\n            \"2\": {\n                \"name\": \"Switch 2\",\n                \"type\": \"ZHASwitch\",\n                \"state\": {\"buttonevent\": 1000},\n                \"config\": {},\n                \"uniqueid\": \"00:00:00:00:00:00:00:00-00-0001\",\n            },\n        }\n    }\n    with patch.dict(DECONZ_WEB_REQUEST, data):\n        await setup_deconz_integration(hass, aioclient_mock)\n\n    assert len(hass.states.async_all()) == 0\n\n    event_changed_sensor = {\n        \"t\": \"event\",\n        \"e\": \"changed\",\n        \"r\": \"sensors\",\n        \"id\": \"2\",\n        \"config\": {\"battery\": 50},\n    }\n    await mock_deconz_websocket(data=event_changed_sensor)\n    await hass.async_block_till_done()\n\n    assert len(hass.states.async_all()) == 0\n\n    event_changed_sensor = {\n        \"t\": \"event\",\n        \"e\": \"changed\",\n        \"r\": \"sensors\",\n        \"id\": \"1\",\n        \"config\": {\"battery\": 50},\n    }\n    await mock_deconz_websocket(data=event_changed_sensor)\n    await hass.async_block_till_done()\n\n    assert len(hass.states.async_all()) == 1\n\n    assert hass.states.get(\"sensor.switch_1_battery\").state == \"50\"\n\n\n@pytest.mark.parametrize(\"model_id\", [\"0x8030\", \"0x8031\", \"0x8034\", \"0x8035\"])",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"model_id\", [\"0x8030\", \"0x8031\", \"0x8034\", \"0x8035\"])",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 439,
        "n_words": 107,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 43,
        "token_counts": 229,
        "n_ast_nodes": 466,
        "n_identifiers": 19,
        "d_id": 104097,
        "documentation": {
            "docstring": "Test that a battery sensor can be created later on.\n\n    Without an initial battery state a battery sensor\n    can be created once a value is reported.\n    ",
            "n_words": 26,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 195032,
        "commit_id": "4f7e4b60975ff73be4227d7c8c428319366e1fe9",
        "repo": "ParlAI",
        "path": "parlai/tasks/huggingface/agents.py",
        "file_name": "agents.py",
        "fun_name": "_get_text_value",
        "commit_message": "[tasks/huggingface] Way to add to message but not \"text\" (#4516)\n\nI want to be able to add my own mutators to grab information from other fields out of a huggingface dataset. Since I don't want it to show up in the text itself, I do it in a new attribute.\r\n\r\nI also delete some code that was written at some point but isn't used anywhere while I'm here.\r\n\r\nTest Plan:\r\nRun `parlai dd -t` with a new dataset that I'm working on that uses this.\r\n\r\nAlso run `parlai dd -t glue; parlai dd -t superglue` to validate that I don't break anything that already exists. (Former dies, but it's cause of a dataset issues on the HF side where the size of the datasets have changed, so not worrying about it)",
        "code": "def _get_text_value(self, row) -> Tuple[str, Dict[str, str]]:\n        \n        # construct text query from the hf_text_fields specified\n        text_dict = {}\n        for col in self.hf_text_fields:\n            text_part = row.get(col)\n            if text_part is None:\n                raise KeyError(f'Feature \"{col}\" not found in data.')\n            text_dict[col] = text_part\n        query = '\\n'.join(text_dict.values())\n        if hasattr(self, \"hf_message_fields\"):\n            for col in self.hf_message_fields:\n                text_part = row.get(col)\n                if text_part is None:\n                    raise KeyError(f'Feature \"{col}\" not found in data.')\n                text_dict[col] = text_part\n        return query, text_dict\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 241,
        "n_words": 69,
        "vocab_size": 40,
        "complexity": 6,
        "nloc": 18,
        "token_counts": 112,
        "n_ast_nodes": 189,
        "n_identifiers": 17,
        "d_id": 47158,
        "documentation": {
            "docstring": "\n        return the constructed text query and dict mapping text field names to values.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 322212,
        "commit_id": "621357338437ee420eabbbf5ab19065bc85e73a5",
        "repo": "PaddleNLP",
        "path": "paddlenlp/taskflow/text_similarity.py",
        "file_name": "text_similarity.py",
        "fun_name": "_postprocess",
        "commit_message": "Update neural search readme and Add Paddle Serving Support (#1558)\n\n* add recall inference similarity\r\n\r\n* update examples\r\n\r\n* updatea readme\r\n\r\n* update dir name\r\n\r\n* update neural search readme\r\n\r\n* update milvus readme\r\n\r\n* update domain adaptive pretraining readme\r\n\r\n* fix the mistakes\r\n\r\n* update readme\r\n\r\n* add recall Paddle Serving Support\r\n\r\n* update readme\r\n\r\n* update readme and format the code\r\n\r\n* reformat the files\r\n\r\n* move the files\r\n\r\n* reformat the code\r\n\r\n* remove redundant code\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>\r\nCo-authored-by: tianxin <tianxin04@baidu.com>",
        "code": "def _postprocess(self, inputs):\n        \n        final_results = []\n        for text, similarity in zip(inputs['text'], inputs['result']):\n            result = {}\n            result['text1'] = text[0]\n            result['text2'] = text[1]\n            result['similarity'] = similarity\n            final_results.append(result)\n        return final_results\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 110,
        "n_words": 27,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 66,
        "n_ast_nodes": 112,
        "n_identifiers": 9,
        "d_id": 118095,
        "documentation": {
            "docstring": "\n        The model output is tag ids, this function will convert the model output to raw text.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 260662,
        "commit_id": "02a4b342181e5ff0226081691308414e53c3107b",
        "repo": "scikit-learn",
        "path": "sklearn/impute/_base.py",
        "file_name": "_base.py",
        "fun_name": "_most_frequent",
        "commit_message": "MAINT fix the way to call stats.mode (#23633)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Meekail Zain <34613774+Micky774@users.noreply.github.com>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def _most_frequent(array, extra_value, n_repeat):\n    \n    # Compute the most frequent value in array only\n    if array.size > 0:\n        if array.dtype == object:\n            # scipy.stats.mode is slow with object dtype array.\n            # Python Counter is more efficient\n            counter = Counter(array)\n            most_frequent_count = counter.most_common(1)[0][1]\n            # tie breaking similarly to scipy.stats.mode\n            most_frequent_value = min(\n                value\n                for value, count in counter.items()\n                if count == most_frequent_count\n            )\n        else:\n            mode = _mode(array)\n            most_frequent_value = mode[0][0]\n            most_frequent_count = mode[1][0]\n    else:\n        most_frequent_value = 0\n        most_frequent_count = 0\n\n    # Compare to array + [extra_value] * n_repeat\n    if most_frequent_count == 0 and n_repeat == 0:\n        return np.nan\n    elif most_frequent_count < n_repeat:\n        return extra_value\n    elif most_frequent_count > n_repeat:\n        return most_frequent_value\n    elif most_frequent_count == n_repeat:\n        # tie breaking similarly to scipy.stats.mode\n        return min(most_frequent_value, extra_value)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 366,
        "n_words": 121,
        "vocab_size": 67,
        "complexity": 10,
        "nloc": 25,
        "token_counts": 137,
        "n_ast_nodes": 221,
        "n_identifiers": 20,
        "d_id": 76401,
        "documentation": {
            "docstring": "Compute the most frequent value in a 1d array extended with\n    [extra_value] * n_repeat, where extra_value is assumed to be not part\n    of the array.",
            "n_words": 25,
            "vocab_size": 24,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 196158,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/permutations.py",
        "file_name": "permutations.py",
        "fun_name": "order",
        "commit_message": "Updated import locations",
        "code": "def order(self):\n        \n\n        return reduce(lcm, [len(cycle) for cycle in self.cyclic_form], 1)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 24,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 26,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 47658,
        "documentation": {
            "docstring": "\n        Computes the order of a permutation.\n\n        When the permutation is raised to the power of its\n        order it equals the identity permutation.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation\n        >>> from sympy import init_printing\n        >>> init_printing(perm_cyclic=False, pretty_print=False)\n        >>> p = Permutation([3, 1, 5, 2, 4, 0])\n        >>> p.order()\n        4\n        >>> (p**(p.order()))\n        Permutation([], size=6)\n\n        See Also\n        ========\n\n        identity, cardinality, length, rank, size\n        ",
            "n_words": 61,
            "vocab_size": 47,
            "n_whitespaces": 181,
            "language": "en"
        }
    },
    {
        "id": 319512,
        "commit_id": "8a6aaf4e2d05021a14adc681c66dff6a815aa2a0",
        "repo": "paperless-ngx",
        "path": "src/documents/tests/test_date_parsing.py",
        "file_name": "test_date_parsing.py",
        "fun_name": "test_filename_date_parse_valid_ymd",
        "commit_message": "Adds additional testing for both date parsing and consumed document created date",
        "code": "def test_filename_date_parse_valid_ymd(self, *args):\n        \n        self.assertEqual(\n            parse_date(\"/tmp/Scan-2022-04-01.pdf\", \"No date in here\"),\n            datetime.datetime(2022, 4, 1, 0, 0, tzinfo=tz.gettz(settings.TIME_ZONE)),\n        )\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 59,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 47,
        "n_ast_nodes": 73,
        "n_identifiers": 11,
        "d_id": 116952,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - Date parsing from the filename is enabled\n            - Filename date format is with Year Month Day (YMD)\n            - Filename contains date matching the format\n\n        THEN:\n            - Should parse the date from the filename\n        ",
            "n_words": 35,
            "vocab_size": 22,
            "n_whitespaces": 101,
            "language": "en"
        }
    },
    {
        "id": 266590,
        "commit_id": "43e55db20821a1341d21ffa1e4e7e6185b244105",
        "repo": "ansible",
        "path": "lib/ansible/galaxy/collection/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "install_artifact",
        "commit_message": "ansible-galaxy - add signature verification of the MANIFEST.json (#76681)\n\n* ansible-galaxy collection install|verify:\r\n\r\n  - Support verifying the origin of the MANIFEST.json when the Galaxy server has provided signatures.\r\n  - Allow supplemental signatures to use during verification on the CLI/requirements file.\r\n\r\n* ansible-galaxy collection install:\r\n\r\n  - Support disabling signature verification. This silences the warning provided by ansible-galaxy if the Galaxy server provided signatures it cannot use because no keyring is configured.\r\n  - Store Galaxy server metadata alongside installed collections for provenance. This is used by 'ansible-galaxy collection verify --offline'.\r\n\r\n* Add unit tests for method that gets signatures from a Galaxy server\r\n\r\n* Add integration tests for user-provided signature sources\r\n\r\n- Test CLI option combinations\r\n- Test installing collections with valid/invalid signature sources\r\n- Test disabling GPG verification when installing collections\r\n- Test verifying collections with valid/invalid signature sources\r\n\r\n* Make signature verification advisory-by-default if signatures are provided by the Galaxy server\r\n\r\n- Make the default keyring None\r\n- Warn if the keyring is None but the Galaxy server provided signatures\r\n- Error if the keyring is None but the user supplied signatures\r\n- Error if the keyring is not None but is invalid\r\n\r\n* changelog\r\n\r\n* add ansible-galaxy user documentation for new options\r\n\r\nCo-authored-by: Matt Martz <matt@sivel.net>\r\nCo-authored-by: Sviatoslav Sydorenko <wk.cvs.github@sydorenko.org.ua>\r\nCo-authored-by: Martin Krizek <martin.krizek@gmail.com>\r\nCo-authored-by: Sandra McCann <samccann@redhat.com>\r\nCo-authored-by: Andy Mott <amott@redhat.com>\r\nCo-authored-by: John R Barker <john@johnrbarker.com>",
        "code": "def install_artifact(b_coll_targz_path, b_collection_path, b_temp_path, signatures, keyring):\n    \n    try:\n        with tarfile.open(b_coll_targz_path, mode='r') as collection_tar:\n            # Verify the signature on the MANIFEST.json before extracting anything else\n            _extract_tar_file(collection_tar, MANIFEST_FILENAME, b_collection_path, b_temp_path)\n\n            if signatures and keyring is not None:\n                manifest_file = os.path.join(to_text(b_collection_path, errors='surrogate_or_strict'), MANIFEST_FILENAME)\n                verify_artifact_manifest(manifest_file, signatures, keyring)\n\n            files_member_obj = collection_tar.getmember('FILES.json')\n            with _tarfile_extract(collection_tar, files_member_obj) as (dummy, files_obj):\n                files = json.loads(to_text(files_obj.read(), errors='surrogate_or_strict'))\n\n            _extract_tar_file(collection_tar, 'FILES.json', b_collection_path, b_temp_path)\n\n            for file_info in files['files']:\n                file_name = file_info['name']\n                if file_name == '.':\n                    continue\n\n                if file_info['ftype'] == 'file':\n                    _extract_tar_file(collection_tar, file_name, b_collection_path, b_temp_path,\n                                      expected_hash=file_info['chksum_sha256'])\n\n                else:\n                    _extract_tar_dir(collection_tar, file_name, b_collection_path)\n\n    except Exception:\n        # Ensure we don't leave the dir behind in case of a failure.\n        shutil.rmtree(b_collection_path)\n\n        b_namespace_path = os.path.dirname(b_collection_path)\n        if not os.listdir(b_namespace_path):\n            os.rmdir(b_namespace_path)\n\n        raise\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 446,
        "n_words": 108,
        "vocab_size": 83,
        "complexity": 8,
        "nloc": 26,
        "token_counts": 216,
        "n_ast_nodes": 353,
        "n_identifiers": 39,
        "d_id": 78488,
        "documentation": {
            "docstring": "Install a collection from tarball under a given path.\n\n    :param b_coll_targz_path: Collection tarball to be installed.\n    :param b_collection_path: Collection dirs layout path.\n    :param b_temp_path: Temporary dir path.\n    :param signatures: frozenset of signatures to verify the MANIFEST.json\n    :param keyring: The keyring used during GPG verification\n    ",
            "n_words": 44,
            "vocab_size": 34,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 250292,
        "commit_id": "652d1669c5a103b1c20478770c4aaf18849c09a3",
        "repo": "synapse",
        "path": "tests/handlers/test_e2e_room_keys.py",
        "file_name": "test_e2e_room_keys.py",
        "fun_name": "test_create_version",
        "commit_message": "Add missing type hints to tests.handlers. (#14680)\n\nAnd do not allow untyped defs in tests.handlers.",
        "code": "def test_create_version(self) -> None:\n        \n        version = self.get_success(\n            self.handler.create_version(\n                self.local_user,\n                {\n                    \"algorithm\": \"m.megolm_backup.v1\",\n                    \"auth_data\": \"first_version_auth_data\",\n                },\n            )\n        )\n        self.assertEqual(version, \"1\")\n\n        # check we can retrieve it as the current version\n        res = self.get_success(self.handler.get_version_info(self.local_user))\n        version_etag = res[\"etag\"]\n        self.assertIsInstance(version_etag, str)\n        del res[\"etag\"]\n        self.assertDictEqual(\n            res,\n            {\n                \"version\": \"1\",\n                \"algorithm\": \"m.megolm_backup.v1\",\n                \"auth_data\": \"first_version_auth_data\",\n                \"count\": 0,\n            },\n        )\n\n        # check we can retrieve it as a specific version\n        res = self.get_success(self.handler.get_version_info(self.local_user, \"1\"))\n        self.assertEqual(res[\"etag\"], version_etag)\n        del res[\"etag\"]\n        self.assertDictEqual(\n            res,\n            {\n                \"version\": \"1\",\n                \"algorithm\": \"m.megolm_backup.v1\",\n                \"auth_data\": \"first_version_auth_data\",\n                \"count\": 0,\n            },\n        )\n\n        # upload a new one...\n        version = self.get_success(\n            self.handler.create_version(\n                self.local_user,\n                {\n                    \"algorithm\": \"m.megolm_backup.v1\",\n                    \"auth_data\": \"second_version_auth_data\",\n                },\n            )\n        )\n        self.assertEqual(version, \"2\")\n\n        # check we can retrieve it as the current version\n        res = self.get_success(self.handler.get_version_info(self.local_user))\n        del res[\"etag\"]\n        self.assertDictEqual(\n            res,\n            {\n                \"version\": \"2\",\n                \"algorithm\": \"m.megolm_backup.v1\",\n                \"auth_data\": \"second_version_auth_data\",\n                \"count\": 0,\n            },\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 802,
        "n_words": 131,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 58,
        "token_counts": 253,
        "n_ast_nodes": 448,
        "n_identifiers": 14,
        "d_id": 73370,
        "documentation": {
            "docstring": "Check that we can create and then retrieve versions.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 160332,
        "commit_id": "7332a698c8194c6e680510da086678fe07d9cf9d",
        "repo": "numpy",
        "path": "numpy/core/tests/test_array_coercion.py",
        "file_name": "test_array_coercion.py",
        "fun_name": "is_parametric_dtype",
        "commit_message": "Fix some typos.",
        "code": "def is_parametric_dtype(dtype):\n    \n    if dtype.itemsize == 0:\n        return True\n    if issubclass(dtype.type, (np.datetime64, np.timedelta64)):\n        if dtype.name.endswith(\"64\"):\n            # Generic time units\n            return True\n    return False\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 70,
        "n_words": 22,
        "vocab_size": 17,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 78,
        "n_identifiers": 10,
        "d_id": 38598,
        "documentation": {
            "docstring": "Returns True if the dtype is a parametric legacy dtype (itemsize\n    is 0, or a datetime without units)\n    ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 150868,
        "commit_id": "2b5f0678772bea0abaf4abe93efc55de43ea3e0e",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/rpc.py",
        "file_name": "rpc.py",
        "fun_name": "_handle_default_message",
        "commit_message": "Refactoring, minor improvements, data provider improvements",
        "code": "def _handle_default_message(self, type, data):\n        \n        logger.debug(f\"Received message from Leader of type {type}: {data}\")\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 26,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 37,
        "n_identifiers": 6,
        "d_id": 34858,
        "documentation": {
            "docstring": "\n        Default leader message handler, just logs it. We should never have to\n        run this unless the leader sends us some weird message.\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 149544,
        "commit_id": "baefda80d19e3eaf14e2ec6a600dcb8c456a3ccf",
        "repo": "freqtrade",
        "path": "freqtrade/persistence/models.py",
        "file_name": "models.py",
        "fun_name": "borrowed",
        "commit_message": "Enable flake8 E226 rule",
        "code": "def borrowed(self) -> float:\n        \n        if self.has_no_leverage:\n            return 0.0\n        elif not self.is_short:\n            return (self.amount * self.open_rate) * ((self.leverage - 1) / self.leverage)\n        else:\n            return self.amount\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 85,
        "n_words": 24,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 53,
        "n_ast_nodes": 83,
        "n_identifiers": 8,
        "d_id": 34448,
        "documentation": {
            "docstring": "\n            The amount of currency borrowed from the exchange for leverage trades\n            If a long trade, the amount is in base currency\n            If a short trade, the amount is in the other currency being traded\n        ",
            "n_words": 34,
            "vocab_size": 22,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 260432,
        "commit_id": "fd60379f95f5c0d3791b2f54c4d070c0aa2ac576",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/_label.py",
        "file_name": "_label.py",
        "fun_name": "fit_transform",
        "commit_message": "MAINT parameter validation for Multilabel Binarizer (#23802)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def fit_transform(self, y):\n        \n        if self.classes is not None:\n            return self.fit(y).transform(y)\n\n        self._validate_params()\n        self._cached_dict = None\n\n        # Automatically increment on new class\n        class_mapping = defaultdict(int)\n        class_mapping.default_factory = class_mapping.__len__\n        yt = self._transform(y, class_mapping)\n\n        # sort classes and reorder columns\n        tmp = sorted(class_mapping, key=class_mapping.get)\n\n        # (make safe for tuples)\n        dtype = int if all(isinstance(c, int) for c in tmp) else object\n        class_mapping = np.empty(len(tmp), dtype=dtype)\n        class_mapping[:] = tmp\n        self.classes_, inverse = np.unique(class_mapping, return_inverse=True)\n        # ensure yt.indices keeps its current dtype\n        yt.indices = np.array(inverse[yt.indices], dtype=yt.indices.dtype, copy=False)\n\n        if not self.sparse_output:\n            yt = yt.toarray()\n\n        return yt\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 244,
        "n_words": 89,
        "vocab_size": 65,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 171,
        "n_ast_nodes": 269,
        "n_identifiers": 36,
        "d_id": 76245,
        "documentation": {
            "docstring": "Fit the label sets binarizer and transform the given label sets.\n\n        Parameters\n        ----------\n        y : iterable of iterables\n            A set of labels (any orderable and hashable object) for each\n            sample. If the `classes` parameter is set, `y` will not be\n            iterated.\n\n        Returns\n        -------\n        y_indicator : {ndarray, sparse matrix} of shape (n_samples, n_classes)\n            A matrix such that `y_indicator[i, j] = 1` iff `classes_[j]`\n            is in `y[i]`, and 0 otherwise. Sparse matrix will be of CSR\n            format.\n        ",
            "n_words": 75,
            "vocab_size": 61,
            "n_whitespaces": 190,
            "language": "en"
        }
    },
    {
        "id": 114701,
        "commit_id": "e00014335bbda3623ee1ccac02c9427ae324141d",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/mysql_handler/mysql_handler.py",
        "file_name": "mysql_handler.py",
        "fun_name": "select_query",
        "commit_message": "Update mysql handler",
        "code": "def select_query(self, query):\n        \n        renderer = SqlalchemyRender('mysql')\n        query_str = renderer.get_string(query, with_failback=True)\n        return self.native_query(query_str)\n  ",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 42,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 33,
        "n_ast_nodes": 56,
        "n_identifiers": 9,
        "d_id": 25255,
        "documentation": {
            "docstring": "\n        Retrieve the data from the SQL statement.\n        ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 177027,
        "commit_id": "15614a4e2736752b0200d3a770d83f2be2d130b9",
        "repo": "networkx",
        "path": "networkx/classes/tests/test_multigraph.py",
        "file_name": "test_multigraph.py",
        "fun_name": "test_multigraph_add_edges_from_four_tuple_misordered",
        "commit_message": "Update tests in base class and simple rename in convert.py (#5848)",
        "code": "def test_multigraph_add_edges_from_four_tuple_misordered(self):\n        \n        G = nx.MultiGraph()\n        with pytest.raises(TypeError):\n            # key/data values flipped in 4-tuple\n            G.add_edges_from([(0, 1, {\"color\": \"red\"}, 0)])\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 61,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 41,
        "n_ast_nodes": 73,
        "n_identifiers": 9,
        "d_id": 42237,
        "documentation": {
            "docstring": "add_edges_from expects 4-tuples of the format (u, v, key, data_dict).\n\n        Ensure 4-tuples of form (u, v, data_dict, key) raise exception.\n        ",
            "n_words": 20,
            "vocab_size": 16,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 47625,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/models/test_taskinstance.py",
        "file_name": "test_taskinstance.py",
        "fun_name": "test_get_previous_start_date_none",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def test_get_previous_start_date_none(self, dag_maker):\n        \n        with dag_maker(\"test_get_previous_start_date_none\", schedule_interval=None) as dag:\n            task = EmptyOperator(task_id=\"op\")\n\n        day_1 = DEFAULT_DATE\n        day_2 = DEFAULT_DATE + datetime.timedelta(days=1)\n\n        # Create a DagRun for day_1 and day_2. Calling ti_2.get_previous_start_date()\n        # should return the start_date of ti_1 (which is None because ti_1 was not run).\n        # It should not raise an error.\n        dagrun_1 = dag_maker.create_dagrun(\n            execution_date=day_1,\n            state=State.RUNNING,\n            run_type=DagRunType.MANUAL,\n        )\n\n        dagrun_2 = dag.create_dagrun(\n            execution_date=day_2,\n            state=State.RUNNING,\n            run_type=DagRunType.MANUAL,\n        )\n\n        ti_1 = dagrun_1.get_task_instance(task.task_id)\n        ti_2 = dagrun_2.get_task_instance(task.task_id)\n        ti_1.task = task\n        ti_2.task = task\n\n        assert ti_2.get_previous_start_date() == ti_1.start_date\n        assert ti_1.start_date is None\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 281,
        "n_words": 85,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 135,
        "n_ast_nodes": 219,
        "n_identifiers": 29,
        "d_id": 9179,
        "documentation": {
            "docstring": "\n        Test that get_previous_start_date() can handle TaskInstance with no start_date.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 196414,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/printing/mathml.py",
        "file_name": "mathml.py",
        "fun_name": "print_mathml",
        "commit_message": "Moved imports to higher level",
        "code": "def print_mathml(expr, printer='content', **settings):\n    \n    if printer == 'presentation':\n        s = MathMLPresentationPrinter(settings)\n    else:\n        s = MathMLContentPrinter(settings)\n    xml = s._print(sympify(expr))\n    s.apply_patch()\n    pretty_xml = xml.toprettyxml()\n    s.restore_patch()\n\n    print(pretty_xml)\n\n\n# For backward compatibility\nMathMLPrinter = MathMLContentPrinter\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 67,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 64,
        "n_ast_nodes": 119,
        "n_identifiers": 16,
        "d_id": 47914,
        "documentation": {
            "docstring": "\n    Prints a pretty representation of the MathML code for expr. If printer is\n    presentation then prints Presentation MathML else prints content MathML.\n\n    Examples\n    ========\n\n    >>> ##\n    >>> from sympy import print_mathml\n    >>> from sympy.abc import x\n    >>> print_mathml(x+1) #doctest: +NORMALIZE_WHITESPACE\n    <apply>\n        <plus/>\n        <ci>x</ci>\n        <cn>1</cn>\n    </apply>\n    >>> print_mathml(x+1, printer='presentation')\n    <mrow>\n        <mi>x</mi>\n        <mo>+</mo>\n        <mn>1</mn>\n    </mrow>\n\n    ",
            "n_words": 53,
            "vocab_size": 45,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 277101,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/tf_utils.py",
        "file_name": "tf_utils.py",
        "fun_name": "sync_to_numpy_or_python_type",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def sync_to_numpy_or_python_type(tensors):\n    \n    if isinstance(tensors, tf.distribute.experimental.coordinator.RemoteValue):\n        tensors = tensors.fetch()\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 21,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 42,
        "n_ast_nodes": 49,
        "n_identifiers": 9,
        "d_id": 81872,
        "documentation": {
            "docstring": "Syncs and converts a structure of `Tensor`s to `NumPy` arrays or Python scalar types.\n\n    For each tensor, it calls `tensor.numpy()`. If the result is a scalar value,\n    it converts it to a Python type, such as a float or int, by calling\n    `result.item()`.\n\n    Numpy scalars are converted, as Python types are often more convenient to deal\n    with. This is especially useful for bfloat16 Numpy scalars, which don't\n    support as many operations as other Numpy values.\n\n    Async strategies (such as `TPUStrategy` and `ParameterServerStrategy`) are\n    forced to\n    sync during this process.\n\n    Args:\n      tensors: A structure of tensors.\n\n    Returns:\n      `tensors`, but scalar tensors are converted to Python types and non-scalar\n      tensors are converted to Numpy arrays.\n    ",
            "n_words": 113,
            "vocab_size": 77,
            "n_whitespaces": 164,
            "language": "en"
        }
    },
    {
        "id": 304818,
        "commit_id": "8896229ea641a558161d8caed796895e9a78f457",
        "repo": "core",
        "path": "tests/components/foobot/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_setup_permanent_error",
        "commit_message": "Improve type hint in foobot sensor entity (#77164)",
        "code": "async def test_setup_permanent_error(hass, aioclient_mock):\n    \n    fake_async_add_entities = MagicMock()\n\n    errors = [HTTPStatus.BAD_REQUEST, HTTPStatus.UNAUTHORIZED, HTTPStatus.FORBIDDEN]\n    for error in errors:\n        aioclient_mock.get(re.compile(\"api.foobot.io/v2/owner/.*\"), status=error)\n        result = await foobot.async_setup_platform(\n            hass, VALID_CONFIG, fake_async_add_entities\n        )\n        assert result is None\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 81,
        "n_words": 30,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 65,
        "n_ast_nodes": 103,
        "n_identifiers": 19,
        "d_id": 103613,
        "documentation": {
            "docstring": "Expected failures caused by permanent errors in API response.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 179258,
        "commit_id": "cc0cff893f9d7d472788adc2510c123967b384fe",
        "repo": "gradio",
        "path": "gradio/interface.py",
        "file_name": "interface.py",
        "fun_name": "integrate",
        "commit_message": "Format The Codebase\n- black formatting\n- isort formatting",
        "code": "def integrate(self, comet_ml=None, wandb=None, mlflow=None) -> None:\n        \n        analytics_integration = \"\"\n        if comet_ml is not None:\n            analytics_integration = \"CometML\"\n            comet_ml.log_other(\"Created from\", \"Gradio\")\n            if self.share_url is not None:\n                comet_ml.log_text(\"gradio: \" + self.share_url)\n                comet_ml.end()\n            else:\n                comet_ml.log_text(\"gradio: \" + self.local_url)\n                comet_ml.end()\n        if wandb is not None:\n            analytics_integration = \"WandB\"\n            if self.share_url is not None:\n                wandb.log(\n                    {\n                        \"Gradio panel\": wandb.Html(\n                            '<iframe src=\"'\n                            + self.share_url\n                            + '\" width=\"'\n                            + str(self.width)\n                            + '\" height=\"'\n                            + str(self.height)\n                            + '\" frameBorder=\"0\"></iframe>'\n                        )\n                    }\n                )\n            else:\n                print(\n                    \"The WandB integration requires you to \"\n                    \"`launch(share=True)` first.\"\n                )\n        if mlflow is not None:\n            analytics_integration = \"MLFlow\"\n            if self.share_url is not None:\n                mlflow.log_param(\"Gradio Interface Share Link\", self.share_url)\n            else:\n                mlflow.log_param(\"Gradio Interface Local Link\", self.local_url)\n        if self.analytics_enabled and analytics_integration:\n            data = {\"integration\": analytics_integration}\n            utils.integration_analytics(data)\n\n",
        "url": "https://github.com/gradio-app/gradio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 755,
        "n_words": 120,
        "vocab_size": 66,
        "complexity": 9,
        "nloc": 52,
        "token_counts": 202,
        "n_ast_nodes": 356,
        "n_identifiers": 22,
        "d_id": 42929,
        "documentation": {
            "docstring": "\n        A catch-all method for integrating with other libraries.\n        Should be run after launch()\n        Parameters:\n            comet_ml (Experiment): If a comet_ml Experiment object is provided,\n            will integrate with the experiment and appear on Comet dashboard\n            wandb (module): If the wandb module is provided, will integrate\n            with it and appear on WandB dashboard\n            mlflow (module): If the mlflow module  is provided, will integrate\n            with the experiment and appear on ML Flow dashboard\n        ",
            "n_words": 69,
            "vocab_size": 39,
            "n_whitespaces": 165,
            "language": "en"
        }
    },
    {
        "id": 338046,
        "commit_id": "8944975a3c8db55f57774e9e566e7a791be766cb",
        "repo": "accelerate",
        "path": "src/accelerate/test_utils/testing.py",
        "file_name": "testing.py",
        "fun_name": "require_huggingface_suite",
        "commit_message": "Reenable Gather for Metrics (#590)\n\n* Clean and finish\r\n\r\nCo-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>",
        "code": "def require_huggingface_suite(test_case):\n    \n    return unittest.skipUnless(\n        is_transformers_available() and is_datasets_available(), \"test requires the Hugging Face suite\"\n    )(test_case)\n\n",
        "url": "https://github.com/huggingface/accelerate.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 30,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 44,
        "n_identifiers": 6,
        "d_id": 121157,
        "documentation": {
            "docstring": "\n    Decorator marking a test that requires transformers and datasets. These tests are skipped when they are not.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 125175,
        "commit_id": "adf24bfa9723b0621183bb27f0c889b813c06e8a",
        "repo": "ray",
        "path": "python/ray/_private/thirdparty/tabulate/tabulate.py",
        "file_name": "tabulate.py",
        "fun_name": "_type",
        "commit_message": "[State Observability] Use a table format by default (#26159)\n\nNOTE: tabulate is copied/pasted to the codebase for table formatting.\r\n\r\nThis PR changes the default layout to be the table format for both summary and list APIs.",
        "code": "def _type(string, has_invisible=True, numparse=True):\n    \n\n    if has_invisible and (\n        isinstance(string, _text_type) or isinstance(string, _binary_type)\n    ):\n        string = _strip_invisible(string)\n\n    if string is None:\n        return _none_type\n    elif hasattr(string, \"isoformat\"):  # datetime.datetime, date, and time\n        return _text_type\n    elif _isbool(string):\n        return _bool_type\n    elif _isint(string) and numparse:\n        return int\n    elif _isint(string, _long_type) and numparse:\n        return int\n    elif _isnumber(string) and numparse:\n        return float\n    elif isinstance(string, _binary_type):\n        return _binary_type\n    else:\n        return _text_type\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 168,
        "n_words": 64,
        "vocab_size": 40,
        "complexity": 14,
        "nloc": 21,
        "token_counts": 110,
        "n_ast_nodes": 179,
        "n_identifiers": 17,
        "d_id": 27792,
        "documentation": {
            "docstring": "The least generic type (type(None), int, float, str, unicode).\n\n    >>> _type(None) is type(None)\n    True\n    >>> _type(\"foo\") is type(\"\")\n    True\n    >>> _type(\"1\") is type(1)\n    True\n    >>> _type('\\x1b[31m42\\x1b[0m') is type(42)\n    True\n    >>> _type('\\x1b[31m42\\x1b[0m') is type(42)\n    True\n\n    ",
            "n_words": 34,
            "vocab_size": 20,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 125012,
        "commit_id": "38c9e1d52aeada536a0460fba01b2633973bc989",
        "repo": "ray",
        "path": "rllib/execution/train_ops.py",
        "file_name": "train_ops.py",
        "fun_name": "multi_gpu_train_one_step",
        "commit_message": "[RLlib]: Fix OPE trainables (#26279)\n\nCo-authored-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def multi_gpu_train_one_step(algorithm, train_batch) -> Dict:\n    \n    config = algorithm.config\n    workers = algorithm.workers\n    local_worker = workers.local_worker()\n    num_sgd_iter = config.get(\"num_sgd_iter\", 1)\n    sgd_minibatch_size = config.get(\"sgd_minibatch_size\", config[\"train_batch_size\"])\n\n    # Determine the number of devices (GPUs or 1 CPU) we use.\n    num_devices = int(math.ceil(config[\"num_gpus\"] or 1))\n\n    # Make sure total batch size is dividable by the number of devices.\n    # Batch size per tower.\n    per_device_batch_size = sgd_minibatch_size // num_devices\n    # Total batch size.\n    batch_size = per_device_batch_size * num_devices\n    assert batch_size % num_devices == 0\n    assert batch_size >= num_devices, \"Batch size too small!\"\n\n    # Handle everything as if multi-agent.\n    train_batch = train_batch.as_multi_agent()\n\n    # Load data into GPUs.\n    load_timer = algorithm._timers[LOAD_BATCH_TIMER]\n    with load_timer:\n        num_loaded_samples = {}\n        for policy_id, batch in train_batch.policy_batches.items():\n            # Not a policy-to-train.\n            if not local_worker.is_policy_to_train(policy_id, train_batch):\n                continue\n\n            # Decompress SampleBatch, in case some columns are compressed.\n            batch.decompress_if_needed()\n\n            # Load the entire train batch into the Policy's only buffer\n            # (idx=0). Policies only have >1 buffers, if we are training\n            # asynchronously.\n            num_loaded_samples[policy_id] = local_worker.policy_map[\n                policy_id\n            ].load_batch_into_buffer(batch, buffer_index=0)\n\n    # Execute minibatch SGD on loaded data.\n    learn_timer = algorithm._timers[LEARN_ON_BATCH_TIMER]\n    with learn_timer:\n        # Use LearnerInfoBuilder as a unified way to build the final\n        # results dict from `learn_on_loaded_batch` call(s).\n        # This makes sure results dicts always have the same structure\n        # no matter the setup (multi-GPU, multi-agent, minibatch SGD,\n        # tf vs torch).\n        learner_info_builder = LearnerInfoBuilder(num_devices=num_devices)\n\n        for policy_id, samples_per_device in num_loaded_samples.items():\n            policy = local_worker.policy_map[policy_id]\n            num_batches = max(1, int(samples_per_device) // int(per_device_batch_size))\n            logger.debug(\"== sgd epochs for {} ==\".format(policy_id))\n            for _ in range(num_sgd_iter):\n                permutation = np.random.permutation(num_batches)\n                for batch_index in range(num_batches):\n                    # Learn on the pre-loaded data in the buffer.\n                    # Note: For minibatch SGD, the data is an offset into\n                    # the pre-loaded entire train batch.\n                    results = policy.learn_on_loaded_batch(\n                        permutation[batch_index] * per_device_batch_size, buffer_index=0\n                    )\n\n                    learner_info_builder.add_learn_on_batch_results(results, policy_id)\n\n        # Tower reduce and finalize results.\n        learner_info = learner_info_builder.finalize()\n\n    load_timer.push_units_processed(train_batch.count)\n    learn_timer.push_units_processed(train_batch.count)\n\n    # TODO: Move this into Trainer's `training_iteration` method for\n    #  better transparency.\n    algorithm._counters[NUM_ENV_STEPS_TRAINED] += train_batch.count\n    algorithm._counters[NUM_AGENT_STEPS_TRAINED] += train_batch.agent_steps()\n\n    if algorithm.reward_estimators:\n        learner_info[DEFAULT_POLICY_ID][\"off_policy_estimation\"] = {}\n        for name, estimator in algorithm.reward_estimators.items():\n            learner_info[DEFAULT_POLICY_ID][\"off_policy_estimation\"][\n                name\n            ] = estimator.train(train_batch)\n\n    return learner_info\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 892,
        "n_words": 330,
        "vocab_size": 216,
        "complexity": 9,
        "nloc": 66,
        "token_counts": 362,
        "n_ast_nodes": 616,
        "n_identifiers": 63,
        "d_id": 27750,
        "documentation": {
            "docstring": "Multi-GPU version of train_one_step.\n\n    Uses the policies' `load_batch_into_buffer` and `learn_on_loaded_batch` methods\n    to be more efficient wrt CPU/GPU data transfers. For example, when doing multiple\n    passes through a train batch (e.g. for PPO) using `config.num_sgd_iter`, the\n    actual train batch is only split once and loaded once into the GPU(s).\n\n    Examples:\n        >>> from ray.rllib.execution.rollout_ops import synchronous_parallel_sample\n        >>> algo = [...] # doctest: +SKIP\n        >>> train_batch = synchronous_parallel_sample(algo.workers) # doctest: +SKIP\n        >>> # This trains the policy on one batch.\n        >>> results = multi_gpu_train_one_step(algo, train_batch)) # doctest: +SKIP\n        {\"default_policy\": ...}\n\n    Updates the NUM_ENV_STEPS_TRAINED and NUM_AGENT_STEPS_TRAINED counters as well as\n    the LOAD_BATCH_TIMER and LEARN_ON_BATCH_TIMER timers of the Algorithm instance.\n    ",
            "n_words": 105,
            "vocab_size": 78,
            "n_whitespaces": 171,
            "language": "en"
        }
    },
    {
        "id": 48644,
        "commit_id": "df584350b4f77143d84615f05000f71408aec9c0",
        "repo": "django-rest-framework",
        "path": "rest_framework/schemas/coreapi.py",
        "file_name": "coreapi.py",
        "fun_name": "get_keys",
        "commit_message": "Prevent head method mapping to coerce action name (#7729)",
        "code": "def get_keys(self, subpath, method, view):\n        \n        if hasattr(view, 'action'):\n            # Viewsets have explicitly named actions.\n            action = view.action\n        else:\n            # Views have no associated action, so we determine one from the method.\n            if is_list_view(subpath, method, view):\n                action = 'list'\n            else:\n                action = self.default_mapping[method.lower()]\n\n        named_path_components = [\n            component for component\n            in subpath.strip('/').split('/')\n            if '{' not in component\n        ]\n\n        if is_custom_action(action):\n            # Custom action, eg \"/users/{pk}/activate/\", \"/users/active/\"\n            mapped_methods = {\n                # Don't count head mapping, e.g. not part of the schema\n                method for method in view.action_map if method != 'head'\n            }\n            if len(mapped_methods) > 1:\n                action = self.default_mapping[method.lower()]\n                if action in self.coerce_method_names:\n                    action = self.coerce_method_names[action]\n                return named_path_components + [action]\n            else:\n                return named_path_components[:-1] + [action]\n\n        if action in self.coerce_method_names:\n            action = self.coerce_method_names[action]\n\n        # Default action, eg \"/users/\", \"/users/{pk}/\"\n        return named_path_components + [action]\n",
        "url": "https://github.com/encode/django-rest-framework.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 484,
        "n_words": 128,
        "vocab_size": 73,
        "complexity": 11,
        "nloc": 27,
        "token_counts": 174,
        "n_ast_nodes": 287,
        "n_identifiers": 19,
        "d_id": 9553,
        "documentation": {
            "docstring": "\n        Return a list of keys that should be used to layout a link within\n        the schema document.\n\n        /users/                   (\"users\", \"list\"), (\"users\", \"create\")\n        /users/{pk}/              (\"users\", \"read\"), (\"users\", \"update\"), (\"users\", \"delete\")\n        /users/enabled/           (\"users\", \"enabled\")  # custom viewset list action\n        /users/{pk}/star/         (\"users\", \"star\")     # custom viewset detail action\n        /users/{pk}/groups/       (\"users\", \"groups\", \"list\"), (\"users\", \"groups\", \"create\")\n        /users/{pk}/groups/{pk}/  (\"users\", \"groups\", \"read\"), (\"users\", \"groups\", \"update\"), (\"users\", \"groups\", \"delete\")\n        ",
            "n_words": 62,
            "vocab_size": 36,
            "n_whitespaces": 187,
            "language": "en"
        }
    },
    {
        "id": 109136,
        "commit_id": "91f47d6eff63187f582c395c007d0152980be6b3",
        "repo": "matplotlib",
        "path": "lib/matplotlib/lines.py",
        "file_name": "lines.py",
        "fun_name": "set_pickradius",
        "commit_message": "Unify set_pickradius argument",
        "code": "def set_pickradius(self, pickradius):\n        \n        if not isinstance(pickradius, Number) or pickradius < 0:\n            raise ValueError(\"pick radius should be a distance\")\n        self._pickradius = pickradius\n\n    pickradius = property(get_pickradius, set_pickradius)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 60,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 65,
        "n_identifiers": 9,
        "d_id": 23452,
        "documentation": {
            "docstring": "\n        Set the pick radius used for containment tests.\n\n        See `.contains` for more details.\n\n        Parameters\n        ----------\n        pickradius : float\n            Pick radius, in points.\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 118685,
        "commit_id": "dd9084523e365e637443ea351eaaaa25f52d8412",
        "repo": "streamlit",
        "path": "lib/tests/streamlit/config_test.py",
        "file_name": "config_test.py",
        "fun_name": "test_missing_config",
        "commit_message": "Report sharing removal (#4260)\n\nThe report sharing feature is a substantial but completely unused portion of the code in Streamlit's underlying machinery. The feature was created early on, used by just a few groups, and has not been used by anyone for a while, as indicated by no activity in the associated S3 buckets. This commit removes that code to make the remaining code easier to navigate and understand.",
        "code": "def test_missing_config(self):\n        \n        with patch(\"streamlit.config.os.path.exists\") as path_exists:\n            path_exists.return_value = False\n            config.get_config_options()\n\n            self.assertEqual(True, config.get_option(\"client.caching\"))\n            self.assertIsNone(config.get_option(\"theme.font\"))\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 48,
        "n_ast_nodes": 90,
        "n_identifiers": 10,
        "d_id": 26360,
        "documentation": {
            "docstring": "Test that we can initialize our config even if the file is missing.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 42816,
        "commit_id": "1507ca48d7c211799129ce7956c11f4c45fee5bc",
        "repo": "airflow",
        "path": "airflow/dag_processing/manager.py",
        "file_name": "manager.py",
        "fun_name": "get_last_runtime",
        "commit_message": "Fix StatD timing metric units (#21106)\n\nCo-authored-by: Tzu-ping Chung <uranusjr@gmail.com>\r\nCo-authored-by: Tzu-ping Chung <tp@astronomer.io>",
        "code": "def get_last_runtime(self, file_path):\n        \n        stat = self._file_stats.get(file_path)\n        return stat.last_duration.total_seconds() if stat and stat.last_duration else None\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 55,
        "n_identifiers": 8,
        "d_id": 7740,
        "documentation": {
            "docstring": "\n        :param file_path: the path to the file that was processed\n        :return: the runtime (in seconds) of the process of the last run, or\n            None if the file was never processed.\n        :rtype: float\n        ",
            "n_words": 32,
            "vocab_size": 24,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 298805,
        "commit_id": "e688f6b315a2edcab6c7e6bd1dfe8a77bf715fed",
        "repo": "core",
        "path": "homeassistant/components/tuya/climate.py",
        "file_name": "climate.py",
        "fun_name": "turn_on",
        "commit_message": "Use climate enums in tuya (#70747)",
        "code": "def turn_on(self) -> None:\n        \n        if DPCode.SWITCH in self.device.function:\n            self._send_command([{\"code\": DPCode.SWITCH, \"value\": True}])\n            return\n\n        # Fake turn on\n        for mode in (HVACMode.HEAT_COOL, HVACMode.HEAT, HVACMode.COOL):\n            if mode not in self.hvac_modes:\n                continue\n            self.set_hvac_mode(mode)\n            break\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 129,
        "n_words": 31,
        "vocab_size": 27,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 71,
        "n_ast_nodes": 116,
        "n_identifiers": 14,
        "d_id": 97746,
        "documentation": {
            "docstring": "Turn the device on, retaining current HVAC (if supported).",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 127235,
        "commit_id": "d0678b80edf7ab50ffde93c13f4a8cdbd7dbba99",
        "repo": "ray",
        "path": "python/ray/tune/trainable/trainable.py",
        "file_name": "trainable.py",
        "fun_name": "train",
        "commit_message": "[rfc] [air/tune/train] Improve trial/training failure error printing (#27946)\n\nWhen training fails, the console output is currently cluttered with tracebacks which are hard to digest. This problem is exacerbated when running multiple trials in a tuning run.\r\n\r\nThe main problems here are:\r\n\r\n1. Tracebacks are printed multiple times: In the remote worker and on the driver\r\n2. Tracebacks include many internal wrappers\r\n\r\nThe proposed solution for 1 is to only print tracebacks once (on the driver) or never (if configured).\r\n\r\nThe proposed solution for 2 is to shorten the tracebacks to include mostly user-provided code.\r\n\r\n### Deduplicating traceback printing\r\n\r\nThe solution here is to use `logger.error` instead of `logger.exception` in the `function_trainable.py` to avoid printing a traceback in the trainable. \r\n\r\nAdditionally, we introduce an environment variable `TUNE_PRINT_ALL_TRIAL_ERRORS` which defaults to 1. If set to 0, trial errors will not be printed at all in the console (only the error.txt files will exist).\r\n\r\nTo be discussed: We could also default this to 0, but I think the expectation is to see at least some failure output in the console logs per default.\r\n\r\n### Removing internal wrappers from tracebacks\r\n\r\nThe solution here is to introcude a magic local variable `_ray_start_tb`. In two places, we use this magic local variable to reduce the stacktrace. A utility `shorten_tb` looks for the last occurence of `_ray_start_tb` in the stacktrace and starts the traceback from there. This takes only linear time. If the magic variable is not present, the full traceback is returned - this means that if the error does not come up in user code, the full traceback is returned, giving visibility in possible internal bugs. Additionally there is an env variable `RAY_AIR_FULL_TRACEBACKS` which disables traceback shortening.\r\n\r\nSigned-off-by: Kai Fricke <kai@anyscale.com>",
        "code": "def train(self):\n        \n        if self._warmup_time is None:\n            self._warmup_time = time.time() - self._start_time\n        start = time.time()\n        try:\n            result = self.step()\n        except Exception as e:\n            raise skip_exceptions(e) from None\n\n        assert isinstance(result, dict), \"step() needs to return a dict.\"\n\n        # We do not modify internal state nor update this result if duplicate.\n        if RESULT_DUPLICATE in result:\n            return result\n\n        result = result.copy()\n\n        self._iteration += 1\n        self._iterations_since_restore += 1\n\n        if result.get(TIME_THIS_ITER_S) is not None:\n            time_this_iter = result[TIME_THIS_ITER_S]\n        else:\n            time_this_iter = time.time() - start\n        self._time_total += time_this_iter\n        self._time_since_restore += time_this_iter\n\n        result.setdefault(DONE, False)\n\n        # self._timesteps_total should only be tracked if increments provided\n        if result.get(TIMESTEPS_THIS_ITER) is not None:\n            if self._timesteps_total is None:\n                self._timesteps_total = 0\n            self._timesteps_total += result[TIMESTEPS_THIS_ITER]\n            self._timesteps_since_restore += result[TIMESTEPS_THIS_ITER]\n\n        # self._episodes_total should only be tracked if increments provided\n        if result.get(EPISODES_THIS_ITER) is not None:\n            if self._episodes_total is None:\n                self._episodes_total = 0\n            self._episodes_total += result[EPISODES_THIS_ITER]\n\n        # self._timesteps_total should not override user-provided total\n        result.setdefault(TIMESTEPS_TOTAL, self._timesteps_total)\n        result.setdefault(EPISODES_TOTAL, self._episodes_total)\n        result.setdefault(TRAINING_ITERATION, self._iteration)\n\n        # Provides auto-filled neg_mean_loss for avoiding regressions\n        if result.get(\"mean_loss\"):\n            result.setdefault(\"neg_mean_loss\", -result[\"mean_loss\"])\n\n        now = datetime.today()\n        result.update(self.get_auto_filled_metrics(now, time_this_iter))\n\n        monitor_data = self._monitor.get_data()\n        if monitor_data:\n            result.update(monitor_data)\n\n        self.log_result(result)\n\n        if self._stdout_context:\n            self._stdout_stream.flush()\n        if self._stderr_context:\n            self._stderr_stream.flush()\n\n        self._last_result = result\n\n        return result\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 623,
        "n_words": 183,
        "vocab_size": 104,
        "complexity": 13,
        "nloc": 47,
        "token_counts": 328,
        "n_ast_nodes": 536,
        "n_identifiers": 47,
        "d_id": 28398,
        "documentation": {
            "docstring": "Runs one logical iteration of training.\n\n        Calls ``step()`` internally. Subclasses should override ``step()``\n        instead to return results.\n        This method automatically fills the following fields in the result:\n\n            `done` (bool): training is terminated. Filled only if not provided.\n\n            `time_this_iter_s` (float): Time in seconds this iteration\n            took to run. This may be overridden in order to override the\n            system-computed time difference.\n\n            `time_total_s` (float): Accumulated time in seconds for this\n            entire experiment.\n\n            `experiment_id` (str): Unique string identifier\n            for this experiment. This id is preserved\n            across checkpoint / restore calls.\n\n            `training_iteration` (int): The index of this\n            training iteration, e.g. call to train(). This is incremented\n            after `step()` is called.\n\n            `pid` (str): The pid of the training process.\n\n            `date` (str): A formatted date of when the result was processed.\n\n            `timestamp` (str): A UNIX timestamp of when the result\n            was processed.\n\n            `hostname` (str): Hostname of the machine hosting the training\n            process.\n\n            `node_ip` (str): Node ip of the machine hosting the training\n            process.\n\n        Returns:\n            A dict that describes training progress.\n        ",
            "n_words": 163,
            "vocab_size": 104,
            "n_whitespaces": 429,
            "language": "en"
        }
    },
    {
        "id": 267700,
        "commit_id": "884244f1b2da3c3f367e064ef4ac0123fcb12675",
        "repo": "ansible",
        "path": "lib/ansible/utils/collection_loader/_collection_finder.py",
        "file_name": "_collection_finder.py",
        "fun_name": "legacy_plugin_dir_to_plugin_type",
        "commit_message": "Python 3.9 min for controller (#77566)",
        "code": "def legacy_plugin_dir_to_plugin_type(legacy_plugin_dir_name):\n        \n        legacy_plugin_dir_name = to_text(legacy_plugin_dir_name)\n\n        plugin_type = legacy_plugin_dir_name.removesuffix(u'_plugins')\n\n        if plugin_type == u'library':\n            plugin_type = u'modules'\n\n        if plugin_type not in AnsibleCollectionRef.VALID_REF_TYPES:\n            raise ValueError('{0} cannot be mapped to a valid collection ref type'.format(to_native(legacy_plugin_dir_name)))\n\n        return plugin_type\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 97,
        "n_words": 33,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 54,
        "n_ast_nodes": 93,
        "n_identifiers": 10,
        "d_id": 79008,
        "documentation": {
            "docstring": "\n        Utility method to convert from a PluginLoader dir name to a plugin ref_type\n        :param legacy_plugin_dir_name: PluginLoader dir name (eg, 'action_plugins', 'library')\n        :return: the corresponding plugin ref_type (eg, 'action', 'role')\n        ",
            "n_words": 29,
            "vocab_size": 21,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 146015,
        "commit_id": "b267be475863a66e9feedb2be5f0a30a2ed8c493",
        "repo": "ray",
        "path": "python/ray/ml/tests/test_checkpoints.py",
        "file_name": "test_checkpoints.py",
        "fun_name": "test_fs_checkpoint_dict",
        "commit_message": "[ml] Add Ray ML / AIR checkpoint implementation (#22691)\n\nThis PR splits up the changes in #22393 and introduces an implementation of the ML Checkpoint interface used by Ray Tune.\r\n\r\nThis means, the TuneCheckpoint class implements the to/from_[bytes|dict|directory|object_ref|uri] conversion functions, as well as more high-level functions to transition between the different TuneCheckpoint classes. It also includes test cases for Tune's main conversion modes, i.e. dict - intermediate - dict and fs - intermediate - fs.\r\n\r\nThese changes will be the basis for refactoring the tune interface to use TuneCheckpoint objects instead of TrialCheckpoints (externally) and instead of paths/objects (internally).",
        "code": "def test_fs_checkpoint_dict(self):\n        \n        checkpoint = self._prepare_fs_checkpoint()\n\n        # Convert into dict checkpoint\n        data_dict = checkpoint.to_dict()\n        self.assertIsInstance(data_dict, dict)\n\n        # Create from dict\n        checkpoint = Checkpoint.from_dict(data_dict)\n        self.assertTrue(checkpoint._data_dict)\n\n        self._assert_fs_checkpoint(checkpoint)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
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        "n_words": 24,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 50,
        "n_ast_nodes": 87,
        "n_identifiers": 13,
        "d_id": 33588,
        "documentation": {
            "docstring": "Test conversion from fs to dict checkpoint and back.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 170932,
        "commit_id": "d13c9e034ce8a1d738766c4b1cec80c76f5523be",
        "repo": "pandas",
        "path": "pandas/core/indexes/base.py",
        "file_name": "base.py",
        "fun_name": "_validate_index_level",
        "commit_message": "STYLE: fix pylint: no-else-raise (#49520)\n\n* fix pylint: no-else-raise\r\n\r\n* fix possible imbalanced tuple unpacking warning\r\n\r\nCo-authored-by: carlotta <c.fabian@turbit.de>",
        "code": "def _validate_index_level(self, level) -> None:\n        \n        if isinstance(level, int):\n            if level < 0 and level != -1:\n                raise IndexError(\n                    \"Too many levels: Index has only 1 level, \"\n                    f\"{level} is not a valid level number\"\n                )\n            if level > 0:\n                raise IndexError(\n                    f\"Too many levels: Index has only 1 level, not {level + 1}\"\n                )\n        elif level != self.name:\n            raise KeyError(\n                f\"Requested level ({level}) does not match index name ({self.name})\"\n            )\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 267,
        "n_words": 70,
        "vocab_size": 48,
        "complexity": 6,
        "nloc": 22,
        "token_counts": 59,
        "n_ast_nodes": 121,
        "n_identifiers": 8,
        "d_id": 40622,
        "documentation": {
            "docstring": "\n        Validate index level.\n\n        For single-level Index getting level number is a no-op, but some\n        verification must be done like in MultiIndex.\n\n        ",
            "n_words": 21,
            "vocab_size": 21,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 67967,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/stock_ledger.py",
        "file_name": "stock_ledger.py",
        "fun_name": "make_sl_entries",
        "commit_message": "style: format code with black",
        "code": "def make_sl_entries(sl_entries, allow_negative_stock=False, via_landed_cost_voucher=False):\n\t\n\tfrom erpnext.controllers.stock_controller import future_sle_exists\n\n\tif sl_entries:\n\t\tcancel = sl_entries[0].get(\"is_cancelled\")\n\t\tif cancel:\n\t\t\tvalidate_cancellation(sl_entries)\n\t\t\tset_as_cancel(sl_entries[0].get(\"voucher_type\"), sl_entries[0].get(\"voucher_no\"))\n\n\t\targs = get_args_for_future_sle(sl_entries[0])\n\t\tfuture_sle_exists(args, sl_entries)\n\n\t\tfor sle in sl_entries:\n\t\t\tif sle.serial_no and not via_landed_cost_voucher:\n\t\t\t\tvalidate_serial_no(sle)\n\n\t\t\tif cancel:\n\t\t\t\tsle[\"actual_qty\"] = -flt(sle.get(\"actual_qty\"))\n\n\t\t\t\tif sle[\"actual_qty\"] < 0 and not sle.get(\"outgoing_rate\"):\n\t\t\t\t\tsle[\"outgoing_rate\"] = get_incoming_outgoing_rate_for_cancel(\n\t\t\t\t\t\tsle.item_code, sle.voucher_type, sle.voucher_no, sle.voucher_detail_no\n\t\t\t\t\t)\n\t\t\t\t\tsle[\"incoming_rate\"] = 0.0\n\n\t\t\t\tif sle[\"actual_qty\"] > 0 and not sle.get(\"incoming_rate\"):\n\t\t\t\t\tsle[\"incoming_rate\"] = get_incoming_outgoing_rate_for_cancel(\n\t\t\t\t\t\tsle.item_code, sle.voucher_type, sle.voucher_no, sle.voucher_detail_no\n\t\t\t\t\t)\n\t\t\t\t\tsle[\"outgoing_rate\"] = 0.0\n\n\t\t\tif sle.get(\"actual_qty\") or sle.get(\"voucher_type\") == \"Stock Reconciliation\":\n\t\t\t\tsle_doc = make_entry(sle, allow_negative_stock, via_landed_cost_voucher)\n\n\t\t\targs = sle_doc.as_dict()\n\n\t\t\tif sle.get(\"voucher_type\") == \"Stock Reconciliation\":\n\t\t\t\t# preserve previous_qty_after_transaction for qty reposting\n\t\t\t\targs.previous_qty_after_transaction = sle.get(\"previous_qty_after_transaction\")\n\n\t\t\tis_stock_item = frappe.get_cached_value(\"Item\", args.get(\"item_code\"), \"is_stock_item\")\n\t\t\tif is_stock_item:\n\t\t\t\tbin_name = get_or_make_bin(args.get(\"item_code\"), args.get(\"warehouse\"))\n\t\t\t\trepost_current_voucher(args, allow_negative_stock, via_landed_cost_voucher)\n\t\t\t\tupdate_bin_qty(bin_name, args)\n\t\t\telse:\n\t\t\t\tfrappe.msgprint(\n\t\t\t\t\t_(\"Item {0} ignored since it is not a stock item\").format(args.get(\"item_code\"))\n\t\t\t\t)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 93,
        "n_words": 132,
        "vocab_size": 85,
        "complexity": 15,
        "nloc": 38,
        "token_counts": 336,
        "n_ast_nodes": 563,
        "n_identifiers": 37,
        "d_id": 14689,
        "documentation": {
            "docstring": "Create SL entries from SL entry dicts\n\n\targs:\n\t        - allow_negative_stock: disable negative stock valiations if true\n\t        - via_landed_cost_voucher: landed cost voucher cancels and reposts\n\t        entries of purchase document. This flag is used to identify if\n\t        cancellation and repost is happening via landed cost voucher, in\n\t        such cases certain validations need to be ignored (like negative\n\t                        stock)\n\t",
            "n_words": 56,
            "vocab_size": 46,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 258647,
        "commit_id": "8991c3d7870df692fe01510e0fe6de62ea550cad",
        "repo": "scikit-learn",
        "path": "sklearn/isotonic.py",
        "file_name": "isotonic.py",
        "fun_name": "get_feature_names_out",
        "commit_message": "ENH Adds get_feature_names to isotonic module (#22249)",
        "code": "def get_feature_names_out(self, input_features=None):\n        \n        class_name = self.__class__.__name__.lower()\n        return np.asarray([f\"{class_name}0\"], dtype=object)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 35,
        "n_ast_nodes": 61,
        "n_identifiers": 11,
        "d_id": 75349,
        "documentation": {
            "docstring": "Get output feature names for transformation.\n\n        Parameters\n        ----------\n        input_features : array-like of str or None, default=None\n            Ignored.\n\n        Returns\n        -------\n        feature_names_out : ndarray of str objects\n            An ndarray with one string i.e. [\"isotonicregression0\"].\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 103,
            "language": "en"
        }
    },
    {
        "id": 186582,
        "commit_id": "16aad35d31a887dab157f9d4f5e0fe9218d06064",
        "repo": "certbot",
        "path": "certbot-nginx/certbot_nginx/_internal/configurator.py",
        "file_name": "configurator.py",
        "fun_name": "config_test",
        "commit_message": "Fully type certbot-nginx module (#9124)\n\n* Work in progress\r\n\r\n* Fix type\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Work in progress\r\n\r\n* Oups.\r\n\r\n* Fix typing in UnspacedList\r\n\r\n* Fix logic\r\n\r\n* Finish typing\r\n\r\n* List certbot-nginx as fully typed in tox\r\n\r\n* Fix lint\r\n\r\n* Fix checks\r\n\r\n* Organize imports\r\n\r\n* Fix typing for Python 3.6\r\n\r\n* Fix checks\r\n\r\n* Fix lint\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/configurator.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/configurator.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Fix signature of deploy_cert regarding the installer interface\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/obj.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Fix types\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/parser.py\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\n\r\n* Precise type\r\n\r\n* Precise _coerce possible inputs/outputs\r\n\r\n* Fix type\r\n\r\n* Update certbot-nginx/certbot_nginx/_internal/http_01.py\r\n\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>\r\n\r\n* Fix type\r\n\r\n* Remove an undesirable implementation.\r\n\r\n* Fix type\r\n\r\nCo-authored-by: alexzorin <alex@zor.io>\r\nCo-authored-by: ohemorange <ebportnoy@gmail.com>",
        "code": "def config_test(self) -> None:\n        \n        try:\n            util.run_script([self.conf('ctl'), \"-c\", self.nginx_conf, \"-t\"])\n        except errors.SubprocessError as err:\n            raise errors.MisconfigurationError(str(err))\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 58,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 48,
        "n_ast_nodes": 84,
        "n_identifiers": 11,
        "d_id": 45498,
        "documentation": {
            "docstring": "Check the configuration of Nginx for errors.\n\n        :raises .errors.MisconfigurationError: If config_test fails\n\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 258972,
        "commit_id": "5d1571db5c1f5b65b1dfc47c21d08050238a60f7",
        "repo": "scikit-learn",
        "path": "sklearn/utils/validation.py",
        "file_name": "validation.py",
        "fun_name": "_is_arraylike_not_scalar",
        "commit_message": "FIX Supports numpy strings and array-like in KMean.init (#22154)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def _is_arraylike_not_scalar(array):\n    \n    return _is_arraylike(array) and not np.isscalar(array)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 19,
        "n_ast_nodes": 34,
        "n_identifiers": 5,
        "d_id": 75501,
        "documentation": {
            "docstring": "Return True if array is array-like and not a scalar",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 127398,
        "commit_id": "203253321d34543aa25483803ebc21e3903679b6",
        "repo": "ray",
        "path": "python/ray/dag/input_node.py",
        "file_name": "input_node.py",
        "fun_name": "get_result_type",
        "commit_message": "[serve] Add additional features to DAG visualization with Gradio (#28246)",
        "code": "def get_result_type(self) -> str:\n        \n        if \"result_type_string\" in self._bound_other_args_to_resolve:\n            return self._bound_other_args_to_resolve[\"result_type_string\"]\n\n\n@DeveloperAPI",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@DeveloperAPI",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 35,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 22,
        "n_ast_nodes": 45,
        "n_identifiers": 5,
        "d_id": 28431,
        "documentation": {
            "docstring": "Get type of the output of this DAGNode.\n\n        Generated by ray.experimental.gradio_utils.type_to_string().\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 30131,
        "commit_id": "fa2ad657482aca9dc628e6d7062b8badf2706bb6",
        "repo": "spotify-downloader",
        "path": "tests/types/test_album.py",
        "file_name": "test_album.py",
        "fun_name": "test_album_from_url",
        "commit_message": "v4 init",
        "code": "def test_album_from_url():\n    \n\n    album = Album.from_url(\"https://open.spotify.com/album/4MQnUDGXmHOvnsWCpzeqWT\")\n\n    assert album.name == \"NCS: The Best of 2017\"\n    assert album.url == \"https://open.spotify.com/album/4MQnUDGXmHOvnsWCpzeqWT\"\n    assert album.artist[\"name\"] == \"Various Artists\"\n    assert len(album.tracks) == 16\n\n\n@pytest.mark.vcr()",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.vcr()",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 44,
        "n_words": 27,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 94,
        "n_identifiers": 12,
        "d_id": 5332,
        "documentation": {
            "docstring": "\n    Test if Album class can be initialized from url.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 321744,
        "commit_id": "9212ba94d651e4bed5724dea28e90ca2e190b007",
        "repo": "qutebrowser",
        "path": "scripts/link_pyqt.py",
        "file_name": "link_pyqt.py",
        "fun_name": "link_pyqt",
        "commit_message": "scripts: Allow linking/installing pyqt-5 or pyqt-6",
        "code": "def link_pyqt(executable, venv_path, *, version='5'):\n    \n    if version not in [\"5\", \"6\"]:\n        raise ValueError(f\"Invalid version {version}\")\n\n    try:\n        get_lib_path(executable, f'PyQt{version}.sip')\n    except Error:\n        # There is no PyQt5.sip, so we need to copy the toplevel sip.\n        sip_file = get_lib_path(executable, 'sip')\n    else:\n        # There is a PyQt5.sip, it'll get copied with the PyQt5 dir.\n        sip_file = None\n\n    sipconfig_file = get_lib_path(executable, 'sipconfig', required=False)\n    pyqt_dir = os.path.dirname(get_lib_path(executable, f'PyQt{version}.QtCore'))\n\n    for path in [sip_file, sipconfig_file, pyqt_dir]:\n        if path is None:\n            continue\n\n        fn = os.path.basename(path)\n        dest = os.path.join(venv_path, fn)\n\n        if os.path.exists(dest):\n            if needs_update(path, dest):\n                remove(dest)\n            else:\n                continue\n\n        copy_or_link(path, dest)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 254,
        "n_words": 90,
        "vocab_size": 68,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 153,
        "n_ast_nodes": 262,
        "n_identifiers": 22,
        "d_id": 117879,
        "documentation": {
            "docstring": "Symlink the systemwide PyQt/sip into the venv.\n\n    Args:\n        executable: The python executable where the source files are present.\n        venv_path: The path to the virtualenv site-packages.\n        version: The PyQt version to use.\n    ",
            "n_words": 31,
            "vocab_size": 25,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 132898,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/actor_pool.py",
        "file_name": "actor_pool.py",
        "fun_name": "get_next_unordered",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def get_next_unordered(self, timeout=None):\n        \n        if not self.has_next():\n            raise StopIteration(\"No more results to get\")\n        # TODO(ekl) bulk wait for performance\n        res, _ = ray.wait(list(self._future_to_actor), num_returns=1, timeout=timeout)\n        if res:\n            [future] = res\n        else:\n            raise TimeoutError(\"Timed out waiting for result\")\n        i, a = self._future_to_actor.pop(future)\n        self._return_actor(a)\n        del self._index_to_future[i]\n        self._next_return_index = max(self._next_return_index, i + 1)\n        return ray.get(future)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 161,
        "n_words": 51,
        "vocab_size": 45,
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        "nloc": 13,
        "token_counts": 107,
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        "n_identifiers": 22,
        "d_id": 29857,
        "documentation": {
            "docstring": "Returns any of the next pending results.\n\n        This returns some result produced by submit(), blocking for up to\n        the specified timeout until it is available. Unlike get_next(), the\n        results are not always returned in same order as submitted, which can\n        improve performance.\n\n        Returns:\n            The next result.\n\n        Raises:\n            TimeoutError if the timeout is reached.\n\n        Examples:\n            >>> pool = ActorPool(...)\n            >>> pool.submit(lambda a, v: a.double.remote(v), 1)\n            >>> pool.submit(lambda a, v: a.double.remote(v), 2)\n            >>> print(pool.get_next_unordered())\n            4\n            >>> print(pool.get_next_unordered())\n            2\n        ",
            "n_words": 76,
            "vocab_size": 61,
            "n_whitespaces": 231,
            "language": "en"
        }
    },
    {
        "id": 204660,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/core/management/commands/makemessages.py",
        "file_name": "makemessages.py",
        "fun_name": "normalize_eols",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def normalize_eols(raw_contents):\n    \n    lines_list = raw_contents.splitlines()\n    # Ensure last line has its EOL\n    if lines_list and lines_list[-1]:\n        lines_list.append(\"\")\n    return \"\\n\".join(lines_list)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
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        "n_identifiers": 6,
        "d_id": 50833,
        "documentation": {
            "docstring": "\n    Take a block of raw text that will be passed through str.splitlines() to\n    get universal newlines treatment.\n\n    Return the resulting block of text with normalized `\\n` EOL sequences ready\n    to be written to disk using current platform's native EOLs.\n    ",
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    },
    {
        "id": 176891,
        "commit_id": "5b7d549bf1369440151708fa6b988eb36e1a1bde",
        "repo": "networkx",
        "path": "networkx/readwrite/json_graph/tree.py",
        "file_name": "tree.py",
        "fun_name": "tree_data",
        "commit_message": "remove old attr keyword from json_graph/tree (#5785)",
        "code": "def tree_data(G, root, ident=\"id\", children=\"children\"):\n    \n    if G.number_of_nodes() != G.number_of_edges() + 1:\n        raise TypeError(\"G is not a tree.\")\n    if not G.is_directed():\n        raise TypeError(\"G is not directed.\")\n    if not nx.is_weakly_connected(G):\n        raise TypeError(\"G is not weakly connected.\")\n\n    if ident == children:\n        raise nx.NetworkXError(\"The values for `id` and `children` must be different.\")\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 48,
        "vocab_size": 34,
        "complexity": 5,
        "nloc": 13,
        "token_counts": 116,
        "n_ast_nodes": 134,
        "n_identifiers": 12,
        "d_id": 42160,
        "documentation": {
            "docstring": "Returns data in tree format that is suitable for JSON serialization\n    and use in Javascript documents.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n       G must be an oriented tree\n\n    root : node\n       The root of the tree\n\n    ident : string\n        Attribute name for storing NetworkX-internal graph data. `ident` must\n        have a different value than `children`. The default is 'id'.\n\n    children : string\n        Attribute name for storing NetworkX-internal graph data. `children`\n        must have a different value than `ident`. The default is 'children'.\n\n    Returns\n    -------\n    data : dict\n       A dictionary with node-link formatted data.\n\n    Raises\n    ------\n    NetworkXError\n        If `children` and `ident` attributes are identical.\n\n    Examples\n    --------\n    >>> from networkx.readwrite import json_graph\n    >>> G = nx.DiGraph([(1, 2)])\n    >>> data = json_graph.tree_data(G, root=1)\n\n    To serialize with json\n\n    >>> import json\n    >>> s = json.dumps(data)\n\n    Notes\n    -----\n    Node attributes are stored in this format but keys\n    for attributes must be strings if you want to serialize with JSON.\n\n    Graph and edge attributes are not stored.\n\n    See Also\n    --------\n    tree_graph, node_link_data, adjacency_data\n    ",
            "n_words": 165,
            "vocab_size": 103,
            "n_whitespaces": 308,
            "language": "en"
        }
    },
    {
        "id": 198289,
        "commit_id": "2a1afca9477eb781f16d5d6b63fa37abed7740a3",
        "repo": "sympy",
        "path": "sympy/physics/quantum/cg.py",
        "file_name": "cg.py",
        "fun_name": "_check_cg_simp",
        "commit_message": "Use sympify less",
        "code": "def _check_cg_simp(expr, simp, sign, lt, term_list, variables, dep_variables, build_index_expr, index_expr):\n    \n    other_part = 0\n    i = 0\n    while i < len(term_list):\n        sub_1 = _check_cg(term_list[i], expr, len(variables))\n        if sub_1 is None:\n            i += 1\n            continue\n        if not build_index_expr.subs(sub_1).is_number:\n            i += 1\n            continue\n        sub_dep = [(x, sub_1[x]) for x in dep_variables]\n        cg_index = [None]*build_index_expr.subs(sub_1)\n        for j in range(i, len(term_list)):\n            sub_2 = _check_cg(term_list[j], expr.subs(sub_dep), len(variables) - len(dep_variables), sign=(sign.subs(sub_1), sign.subs(sub_dep)))\n            if sub_2 is None:\n                continue\n            if not index_expr.subs(sub_dep).subs(sub_2).is_number:\n                continue\n            cg_index[index_expr.subs(sub_dep).subs(sub_2)] = j, expr.subs(lt, 1).subs(sub_dep).subs(sub_2), lt.subs(sub_2), sign.subs(sub_dep).subs(sub_2)\n        if not any(i is None for i in cg_index):\n            min_lt = min(*[ abs(term[2]) for term in cg_index ])\n            indices = [ term[0] for term in cg_index]\n            indices.sort()\n            indices.reverse()\n            [ term_list.pop(j) for j in indices ]\n            for term in cg_index:\n                if abs(term[2]) > min_lt:\n                    term_list.append( (term[2] - min_lt*term[3])*term[1] )\n            other_part += min_lt*(sign*simp).subs(sub_1)\n        else:\n            i += 1\n    return term_list, other_part\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 450,
        "n_words": 139,
        "vocab_size": 82,
        "complexity": 15,
        "nloc": 33,
        "token_counts": 366,
        "n_ast_nodes": 557,
        "n_identifiers": 33,
        "d_id": 48858,
        "documentation": {
            "docstring": " Checks for simplifications that can be made, returning a tuple of the\n    simplified list of terms and any terms generated by simplification.\n\n    Parameters\n    ==========\n\n    expr: expression\n        The expression with Wild terms that will be matched to the terms in\n        the sum\n\n    simp: expression\n        The expression with Wild terms that is substituted in place of the CG\n        terms in the case of simplification\n\n    sign: expression\n        The expression with Wild terms denoting the sign that is on expr that\n        must match\n\n    lt: expression\n        The expression with Wild terms that gives the leading term of the\n        matched expr\n\n    term_list: list\n        A list of all of the terms is the sum to be simplified\n\n    variables: list\n        A list of all the variables that appears in expr\n\n    dep_variables: list\n        A list of the variables that must match for all the terms in the sum,\n        i.e. the dependent variables\n\n    build_index_expr: expression\n        Expression with Wild terms giving the number of elements in cg_index\n\n    index_expr: expression\n        Expression with Wild terms giving the index terms have when storing\n        them to cg_index\n\n    ",
            "n_words": 172,
            "vocab_size": 72,
            "n_whitespaces": 317,
            "language": "en"
        }
    },
    {
        "id": 202491,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/custom_managers/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_filtering",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_filtering(self):\n        \n        self.assertQuerysetEqual(\n            Book.published_objects.all(),\n            [\n                \"How to program\",\n            ],\n            lambda b: b.title,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 93,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 31,
        "n_ast_nodes": 52,
        "n_identifiers": 8,
        "d_id": 50134,
        "documentation": {
            "docstring": "\n        Custom managers respond to usual filtering methods\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 300467,
        "commit_id": "1d9fb4bca871f97109684419f0f9526a0c151f2d",
        "repo": "core",
        "path": "tests/components/recorder/test_models.py",
        "file_name": "test_models.py",
        "fun_name": "test_process_datetime_to_timestamp_freeze_time",
        "commit_message": "Fix process_datetime_to_timestamp and add test coverage (#71755)",
        "code": "def test_process_datetime_to_timestamp_freeze_time(time_zone, hass):\n    \n    hass.config.set_time_zone(time_zone)\n    utc_now = dt_util.utcnow()\n    with freeze_time(utc_now):\n        epoch = utc_now.timestamp()\n        assert process_datetime_to_timestamp(dt_util.utcnow()) == epoch\n        now = dt_util.now()\n        assert process_datetime_to_timestamp(now) == epoch\n\n\n@pytest.mark.parametrize(\n    \"time_zone\", [\"Europe/Berlin\", \"America/Chicago\", \"US/Hawaii\", \"UTC\"]\n)",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"time_zone\", [\"Europe/Berlin\", \"America/Chicago\", \"US/Hawaii\", \"UTC\"]\n)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 30,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 61,
        "n_ast_nodes": 141,
        "n_identifiers": 16,
        "d_id": 99327,
        "documentation": {
            "docstring": "Test we can handle processing database datatimes to timestamps.\n\n    This test freezes time to make sure everything matches.\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 247630,
        "commit_id": "5dd949bee6158a8b651db9f2ae417a62c8184bfd",
        "repo": "synapse",
        "path": "tests/handlers/test_oidc.py",
        "file_name": "test_oidc.py",
        "fun_name": "test_null_localpart",
        "commit_message": "Add type hints to some tests/handlers files. (#12224)",
        "code": "def test_null_localpart(self) -> None:\n        \n        userinfo = {\n            \"sub\": \"tester\",\n            \"username\": None,\n        }\n        self.get_success(_make_callback_with_userinfo(self.hs, userinfo))\n        self.assertRenderedError(\"mapping_error\", \"localpart is invalid: \")\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 76,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 41,
        "n_ast_nodes": 75,
        "n_identifiers": 7,
        "d_id": 71794,
        "documentation": {
            "docstring": "Mapping onto a null localpart via an empty OIDC attribute should be rejected",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 23234,
        "commit_id": "9f62b610dea6161627200ed85d92e19b1923279a",
        "repo": "PaddleOCR",
        "path": "ppocr/postprocess/fce_postprocess.py",
        "file_name": "fce_postprocess.py",
        "fun_name": "points2polygon",
        "commit_message": "add fcenet",
        "code": "def points2polygon(points):\n    \n    if isinstance(points, list):\n        points = np.array(points)\n\n    assert isinstance(points, np.ndarray)\n    assert (points.size % 2 == 0) and (points.size >= 8)\n\n    point_mat = points.reshape([-1, 2])\n    return plg.Polygon(point_mat)\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 52,
        "n_words": 27,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 69,
        "n_ast_nodes": 109,
        "n_identifiers": 12,
        "d_id": 4551,
        "documentation": {
            "docstring": "Convert k points to 1 polygon.\n\n    Args:\n        points (ndarray or list): A ndarray or a list of shape (2k)\n            that indicates k points.\n\n    Returns:\n        polygon (Polygon): A polygon object.\n    ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 154398,
        "commit_id": "1c0935c1bc0856d43f69c1e32498636ee24ebc85",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/omnisci_on_native/base_worker.py",
        "file_name": "base_worker.py",
        "fun_name": "import_pandas_dataframe",
        "commit_message": "FEAT-#4913: Enabling pyhdk (#4900)\n\nCo-authored-by: ienkovich <ilya.enkovich@intel.com>\r\nSigned-off-by: izamyati <igor.zamyatin@intel.com>",
        "code": "def import_pandas_dataframe(cls, df, name=None):\n        \n        return cls.import_arrow_table(pa.Table.from_pandas(df))\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 20,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 26,
        "n_ast_nodes": 42,
        "n_identifiers": 8,
        "d_id": 35959,
        "documentation": {
            "docstring": "\n        Import ``pandas.DataFrame`` to the worker.\n\n        Parameters\n        ----------\n        df : pandas.DataFrame\n            A frame to import.\n        name : str, optional\n            A table name to use. None to generate a unique name.\n\n        Returns\n        -------\n        str\n            Imported table name.\n        ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 132,
            "language": "en"
        }
    },
    {
        "id": 48712,
        "commit_id": "9e328a9549b8cc5fbeff7b70cf2523fa3d97518f",
        "repo": "django-rest-framework",
        "path": "rest_framework/schemas/openapi.py",
        "file_name": "openapi.py",
        "fun_name": "get_operation_id_base",
        "commit_message": "Fix OpenAPI operation name plural appropriately (#8017)",
        "code": "def get_operation_id_base(self, path, method, action):\n        \n        model = getattr(getattr(self.view, 'queryset', None), 'model', None)\n\n        if self.operation_id_base is not None:\n            name = self.operation_id_base\n\n        # Try to deduce the ID from the view's model\n        elif model is not None:\n            name = model.__name__\n\n        # Try with the serializer class name\n        elif self.get_serializer(path, method) is not None:\n            name = self.get_serializer(path, method).__class__.__name__\n            if name.endswith('Serializer'):\n                name = name[:-10]\n\n        # Fallback to the view name\n        else:\n            name = self.view.__class__.__name__\n            if name.endswith('APIView'):\n                name = name[:-7]\n            elif name.endswith('View'):\n                name = name[:-4]\n\n            # Due to camel-casing of classes and `action` being lowercase, apply title in order to find if action truly\n            # comes at the end of the name\n            if name.endswith(action.title()):  # ListView, UpdateAPIView, ThingDelete ...\n                name = name[:-len(action)]\n\n        if action == 'list':\n            name = pluralize(name)\n\n        return name\n",
        "url": "https://github.com/encode/django-rest-framework.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 385,
        "n_words": 126,
        "vocab_size": 72,
        "complexity": 9,
        "nloc": 21,
        "token_counts": 177,
        "n_ast_nodes": 295,
        "n_identifiers": 17,
        "d_id": 9574,
        "documentation": {
            "docstring": "\n        Compute the base part for operation ID from the model, serializer or view name.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 139165,
        "commit_id": "e8fc66af348f2afd2b578fe1c6776cc88ea82499",
        "repo": "ray",
        "path": "python/ray/workflow/workflow_context.py",
        "file_name": "workflow_context.py",
        "fun_name": "workflow_logging_context",
        "commit_message": "[Workflow]Make workflow logs publish to the correct driver. (#24089)\n\nAll workflow tasks are executed as remote functions that submitted from WorkflowManagmentActor. WorkflowManagmentActor is a detached long-running actor whose owner is the first driver in the cluster that runs the very first workflow execution. Therefore, for new drivers that run workflows, the loggings won't be properly published back to the driver because loggings are saved and published based on job_id and the job_id is always the first driver's job_id as the ownership goes like: first_driver -> WorkflowManagmentActor -> workflow executions using remote functions.\r\n\r\nTo solve this, during workflow execution, we pass the actual driver's job_id along with execution, and re-configure the logging files on each worker that runs the remote functions. Notice that we need to do this in multiple places as a workflow task is executed with more than one remote functions that are running in different workers.",
        "code": "def workflow_logging_context(job_id) -> None:\n    \n    node = ray.worker._global_node\n    original_out_file, original_err_file = node.get_log_file_handles(\n        get_worker_log_file_name(\"WORKER\")\n    )\n    out_file, err_file = node.get_log_file_handles(\n        get_worker_log_file_name(\"WORKER\", job_id)\n    )\n    try:\n        configure_log_file(out_file, err_file)\n        yield\n    finally:\n        configure_log_file(original_out_file, original_err_file)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 86,
        "n_words": 27,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 27,
        "token_counts": 60,
        "n_ast_nodes": 104,
        "n_identifiers": 13,
        "d_id": 31619,
        "documentation": {
            "docstring": "Initialize the workflow logging context.\n\n    Workflow executions are running as remote functions from\n    WorkflowManagementActor. Without logging redirection, workflow\n    inner execution logs will be pushed to the driver that initially\n    created WorkflowManagementActor rather than the driver that\n    actually submits the current workflow execution.\n    We use this conext manager to re-configure the log files to send\n    the logs to the correct driver, and to restore the log files once\n    the execution is done.\n\n    Args:\n        job_id: The ID of the job that submits the workflow execution.\n    ",
            "n_words": 83,
            "vocab_size": 56,
            "n_whitespaces": 120,
            "language": "en"
        }
    },
    {
        "id": 91851,
        "commit_id": "8c83731694d352c5832ef6dd26ec57333bc8d5b5",
        "repo": "sentry",
        "path": "src/sentry/tasks/base.py",
        "file_name": "base.py",
        "fun_name": "load_model_from_db",
        "commit_message": "feat(celery): Disallow complex pickle for new tasks (#35811)",
        "code": "def load_model_from_db(cls, instance_or_id, allow_cache=True):\n    \n    if isinstance(instance_or_id, int):\n        if hasattr(cls.objects, \"get_from_cache\") and allow_cache:\n            return cls.objects.get_from_cache(pk=instance_or_id)\n        return cls.objects.get(pk=instance_or_id)\n    return instance_or_id\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 52,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 56,
        "n_ast_nodes": 89,
        "n_identifiers": 11,
        "d_id": 18819,
        "documentation": {
            "docstring": "Utility function to allow a task to transition to passing ids rather than model instances.",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 260239,
        "commit_id": "9bb209817a978d6da0fec392ed212685efe08694",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/_ranking.py",
        "file_name": "_ranking.py",
        "fun_name": "ndcg_score",
        "commit_message": "ENH Added warning for `ndcg_score` when used w/ negative `y_true` values (#23461)\n\nCo-authored-by: trinhcon <conroy.trinh@mail.utoronto.ca>\r\nCo-authored-by: Victor Ko <vk07275@gmail.com>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def ndcg_score(y_true, y_score, *, k=None, sample_weight=None, ignore_ties=False):\n    \n    y_true = check_array(y_true, ensure_2d=False)\n    y_score = check_array(y_score, ensure_2d=False)\n    check_consistent_length(y_true, y_score, sample_weight)\n\n    if y_true.min() < 0:\n        # TODO(1.4): Replace warning w/ ValueError\n        warnings.warn(\n            \"ndcg_score should not be used on negative y_true values. ndcg_score will\"\n            \" raise a ValueError on negative y_true values starting from version 1.4.\",\n            FutureWarning,\n        )\n    _check_dcg_target_type(y_true)\n    gain = _ndcg_sample_scores(y_true, y_score, k=k, ignore_ties=ignore_ties)\n    return np.average(gain, weights=sample_weight)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 142,
        "n_words": 64,
        "vocab_size": 54,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 100,
        "n_ast_nodes": 154,
        "n_identifiers": 19,
        "d_id": 76130,
        "documentation": {
            "docstring": "Compute Normalized Discounted Cumulative Gain.\n\n    Sum the true scores ranked in the order induced by the predicted scores,\n    after applying a logarithmic discount. Then divide by the best possible\n    score (Ideal DCG, obtained for a perfect ranking) to obtain a score between\n    0 and 1.\n\n    This ranking metric returns a high value if true labels are ranked high by\n    ``y_score``.\n\n    Parameters\n    ----------\n    y_true : ndarray of shape (n_samples, n_labels)\n        True targets of multilabel classification, or true scores of entities\n        to be ranked. Negative values in `y_true` may result in an output\n        that is not between 0 and 1.\n\n        .. versionchanged:: 1.2\n            These negative values are deprecated, and will raise an error in v1.4.\n\n    y_score : ndarray of shape (n_samples, n_labels)\n        Target scores, can either be probability estimates, confidence values,\n        or non-thresholded measure of decisions (as returned by\n        \"decision_function\" on some classifiers).\n\n    k : int, default=None\n        Only consider the highest k scores in the ranking. If `None`, use all\n        outputs.\n\n    sample_weight : ndarray of shape (n_samples,), default=None\n        Sample weights. If `None`, all samples are given the same weight.\n\n    ignore_ties : bool, default=False\n        Assume that there are no ties in y_score (which is likely to be the\n        case if y_score is continuous) for efficiency gains.\n\n    Returns\n    -------\n    normalized_discounted_cumulative_gain : float in [0., 1.]\n        The averaged NDCG scores for all samples.\n\n    See Also\n    --------\n    dcg_score : Discounted Cumulative Gain (not normalized).\n\n    References\n    ----------\n    `Wikipedia entry for Discounted Cumulative Gain\n    <https://en.wikipedia.org/wiki/Discounted_cumulative_gain>`_\n\n    Jarvelin, K., & Kekalainen, J. (2002).\n    Cumulated gain-based evaluation of IR techniques. ACM Transactions on\n    Information Systems (TOIS), 20(4), 422-446.\n\n    Wang, Y., Wang, L., Li, Y., He, D., Chen, W., & Liu, T. Y. (2013, May).\n    A theoretical analysis of NDCG ranking measures. In Proceedings of the 26th\n    Annual Conference on Learning Theory (COLT 2013)\n\n    McSherry, F., & Najork, M. (2008, March). Computing information retrieval\n    performance measures efficiently in the presence of tied scores. In\n    European conference on information retrieval (pp. 414-421). Springer,\n    Berlin, Heidelberg.\n\n    Examples\n    --------\n    >>> import numpy as np\n    >>> from sklearn.metrics import ndcg_score\n    >>> # we have groud-truth relevance of some answers to a query:\n    >>> true_relevance = np.asarray([[10, 0, 0, 1, 5]])\n    >>> # we predict some scores (relevance) for the answers\n    >>> scores = np.asarray([[.1, .2, .3, 4, 70]])\n    >>> ndcg_score(true_relevance, scores)\n    0.69...\n    >>> scores = np.asarray([[.05, 1.1, 1., .5, .0]])\n    >>> ndcg_score(true_relevance, scores)\n    0.49...\n    >>> # we can set k to truncate the sum; only top k answers contribute.\n    >>> ndcg_score(true_relevance, scores, k=4)\n    0.35...\n    >>> # the normalization takes k into account so a perfect answer\n    >>> # would still get 1.0\n    >>> ndcg_score(true_relevance, true_relevance, k=4)\n    1.0\n    >>> # now we have some ties in our prediction\n    >>> scores = np.asarray([[1, 0, 0, 0, 1]])\n    >>> # by default ties are averaged, so here we get the average (normalized)\n    >>> # true relevance of our top predictions: (10 / 10 + 5 / 10) / 2 = .75\n    >>> ndcg_score(true_relevance, scores, k=1)\n    0.75\n    >>> # we can choose to ignore ties for faster results, but only\n    >>> # if we know there aren't ties in our scores, otherwise we get\n    >>> # wrong results:\n    >>> ndcg_score(true_relevance,\n    ...           scores, k=1, ignore_ties=True)\n    0.5\n    ",
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        "id": 65623,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/controllers/accounts_controller.py",
        "file_name": "accounts_controller.py",
        "fun_name": "get_supplier_block_status",
        "commit_message": "style: format code with black",
        "code": "def get_supplier_block_status(party_name):\n\t\n\tsupplier = frappe.get_doc(\"Supplier\", party_name)\n\tinfo = {\n\t\t\"on_hold\": supplier.on_hold,\n\t\t\"release_date\": supplier.release_date,\n\t\t\"hold_type\": supplier.hold_type,\n\t}\n\treturn info\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
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            "docstring": "\n\tReturns a dict containing the values of `on_hold`, `release_date` and `hold_type` of\n\ta `Supplier`\n\t",
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    },
    {
        "id": 219780,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "compare_total",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def compare_total(self, a, b):\n        \n        a = _convert_other(a, raiseit=True)\n        return a.compare_total(b)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
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        "nloc": 3,
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        "n_identifiers": 6,
        "d_id": 55795,
        "documentation": {
            "docstring": "Compares two operands using their abstract representation.\n\n        This is not like the standard compare, which use their numerical\n        value. Note that a total ordering is defined for all possible abstract\n        representations.\n\n        >>> ExtendedContext.compare_total(Decimal('12.73'), Decimal('127.9'))\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(Decimal('-127'),  Decimal('12'))\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.3'))\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(Decimal('12.30'), Decimal('12.30'))\n        Decimal('0')\n        >>> ExtendedContext.compare_total(Decimal('12.3'),  Decimal('12.300'))\n        Decimal('1')\n        >>> ExtendedContext.compare_total(Decimal('12.3'),  Decimal('NaN'))\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(1, 2)\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(Decimal(1), 2)\n        Decimal('-1')\n        >>> ExtendedContext.compare_total(1, Decimal(2))\n        Decimal('-1')\n        ",
            "n_words": 67,
            "vocab_size": 46,
            "n_whitespaces": 224,
            "language": "en"
        }
    },
    {
        "id": 336027,
        "commit_id": "63c68d979a8e4a9c9fea306bdf63e73812843453",
        "repo": "diffusers",
        "path": "src/diffusers/schedulers/scheduling_sde_ve.py",
        "file_name": "scheduling_sde_ve.py",
        "fun_name": "step_pred",
        "commit_message": "VE/VP SDE updates (#90)\n\n* improve comments for sde_ve scheduler, init tests\r\n\r\n* more comments, tweaking pipelines\r\n\r\n* timesteps --> num_training_timesteps, some comments\r\n\r\n* merge cpu test, add m1 data\r\n\r\n* fix scheduler tests with num_train_timesteps\r\n\r\n* make np compatible, add tests for sde ve\r\n\r\n* minor default variable fixes\r\n\r\n* make style and fix-copies\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def step_pred(self, score, x, t):\n        \n        # TODO(Patrick) better comments + non-PyTorch\n        t = self.repeat_scalar(t, x.shape[0])\n        timesteps = self.long((t * (len(self.timesteps) - 1)))\n\n        sigma = self.discrete_sigmas[timesteps]\n        adjacent_sigma = self.get_adjacent_sigma(timesteps, t)\n        drift = self.zeros_like(x)\n        diffusion = (sigma**2 - adjacent_sigma**2) ** 0.5\n\n        # equation 6 in the paper: the score modeled by the network is grad_x log pt(x)\n        # also equation 47 shows the analog from SDE models to ancestral sampling methods\n        drift = drift - diffusion[:, None, None, None] ** 2 * score\n\n        #  equation 6: sample noise for the diffusion term of\n        noise = self.randn_like(x)\n        x_mean = x - drift  # subtract because `dt` is a small negative timestep\n        # TODO is the variable diffusion the correct scaling term for the noise?\n        x = x_mean + diffusion[:, None, None, None] * noise  # add impact of diffusion field g\n        return x, x_mean\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
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        "token_counts": 140,
        "n_ast_nodes": 215,
        "n_identifiers": 20,
        "d_id": 120850,
        "documentation": {
            "docstring": "\n        Predict the sample at the previous timestep by reversing the SDE.\n        ",
            "n_words": 11,
            "vocab_size": 9,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 75173,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/images/tests/test_admin_views.py",
        "file_name": "test_admin_views.py",
        "fun_name": "test_get_bad_image",
        "commit_message": "Reformat with black",
        "code": "def test_get_bad_image(self):\n        \n        # Get\n        response = self.client.get(\n            reverse(\n                \"wagtailimages:generate_url\", args=(self.image.id + 1, \"fill-800x600\")\n            )\n        )\n\n        # Check response\n        self.assertEqual(response.status_code, 404)\n        self.assertEqual(response[\"Content-Type\"], \"application/json\")\n\n        # Check JSON\n        self.assertJSONEqual(\n            response.content.decode(),\n            json.dumps(\n                {\n                    \"error\": \"Cannot find image.\",\n                }\n            ),\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 225,
        "n_words": 36,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 79,
        "n_ast_nodes": 137,
        "n_identifiers": 16,
        "d_id": 16373,
        "documentation": {
            "docstring": "\n        This tests that the view gives a 404 response if a user attempts to use it with an image which doesn't exist\n        ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 321111,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/qtnetworkdownloads.py",
        "file_name": "qtnetworkdownloads.py",
        "fun_name": "get",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def get(self, url, cache=True, **kwargs):\n        \n        if not url.isValid():\n            urlutils.invalid_url_error(url, \"start download\")\n            return None\n\n        req = QNetworkRequest(url)\n        user_agent = websettings.user_agent(url)\n        req.setHeader(QNetworkRequest.KnownHeaders.UserAgentHeader, user_agent)\n\n        if not cache:\n            req.setAttribute(QNetworkRequest.Attribute.CacheSaveControlAttribute, False)\n\n        return self.get_request(req, **kwargs)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 111,
        "n_words": 29,
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        "complexity": 3,
        "nloc": 10,
        "token_counts": 85,
        "n_ast_nodes": 136,
        "n_identifiers": 19,
        "d_id": 117539,
        "documentation": {
            "docstring": "Start a download with a link URL.\n\n        Args:\n            url: The URL to get, as QUrl\n            cache: If set to False, don't cache the response.\n            **kwargs: passed to get_request().\n\n        Return:\n            The created DownloadItem.\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 97,
            "language": "en"
        }
    },
    {
        "id": 218471,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/inspect.py",
        "file_name": "inspect.py",
        "fun_name": "getcomments",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getcomments(object):\n    \n    try:\n        lines, lnum = findsource(object)\n    except (OSError, TypeError):\n        return None\n\n    if ismodule(object):\n        # Look for a comment block at the top of the file.\n        start = 0\n        if lines and lines[0][:2] == '#!': start = 1\n        while start < len(lines) and lines[start].strip() in ('', '#'):\n            start = start + 1\n        if start < len(lines) and lines[start][:1] == '#':\n            comments = []\n            end = start\n            while end < len(lines) and lines[end][:1] == '#':\n                comments.append(lines[end].expandtabs())\n                end = end + 1\n            return ''.join(comments)\n\n    # Look for a preceding block of comments at the same indentation.\n    elif lnum > 0:\n        indent = indentsize(lines[lnum])\n        end = lnum - 1\n        if end >= 0 and lines[end].lstrip()[:1] == '#' and \\\n            indentsize(lines[end]) == indent:\n            comments = [lines[end].expandtabs().lstrip()]\n            if end > 0:\n                end = end - 1\n                comment = lines[end].expandtabs().lstrip()\n                while comment[:1] == '#' and indentsize(lines[end]) == indent:\n                    comments[:0] = [comment]\n                    end = end - 1\n                    if end < 0: break\n                    comment = lines[end].expandtabs().lstrip()\n            while comments and comments[0].strip() == '#':\n                comments[:1] = []\n            while comments and comments[-1].strip() == '#':\n                comments[-1:] = []\n            return ''.join(comments)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
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        "n_identifiers": 20,
        "d_id": 55330,
        "documentation": {
            "docstring": "Get lines of comments immediately preceding an object's source code.\n\n    Returns None when source can't be found.\n    ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 253331,
        "commit_id": "8c2428c9d355ca5fbc3dd90e9820ceb1cc795837",
        "repo": "mitmproxy",
        "path": "examples/contrib/jsondump.py",
        "file_name": "jsondump.py",
        "fun_name": "convert_to_strings",
        "commit_message": "[autofix.ci] apply automated fixes",
        "code": "def convert_to_strings(cls, obj):\n        \n        if isinstance(obj, dict):\n            return {\n                cls.convert_to_strings(key): cls.convert_to_strings(value)\n                for key, value in obj.items()\n            }\n        elif isinstance(obj, list) or isinstance(obj, tuple):\n            return [cls.convert_to_strings(element) for element in obj]\n        elif isinstance(obj, bytes):\n            return str(obj)[2:-1]\n        return obj\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "token_counts": 91,
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        "n_identifiers": 13,
        "d_id": 74068,
        "documentation": {
            "docstring": "\n        Recursively convert all list/dict elements of type `bytes` into strings.\n        ",
            "n_words": 10,
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            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 202906,
        "commit_id": "0ab58c120939093fea90822f376e1866fc714d1f",
        "repo": "django",
        "path": "tests/migrations/test_commands.py",
        "file_name": "test_commands.py",
        "fun_name": "test_makemigrations_interactive_reject",
        "commit_message": "Refs #29026 -- Allowed customizing InteractiveMigrationQuestioner's prompt destination.\n\nPreviously, the questioner did not obey the value of stdout provided\nto the command.",
        "code": "def test_makemigrations_interactive_reject(self):\n        \n        # Monkeypatch interactive questioner to auto reject\n        with mock.patch('builtins.input', mock.Mock(return_value='N')):\n            with self.temporary_migration_module(module=\"migrations.test_migrations_conflict\") as migration_dir:\n                with captured_stdout():\n                    call_command(\n                        'makemigrations',\n                        'migrations',\n                        name='merge',\n                        merge=True,\n                        interactive=True,\n                        verbosity=0,\n                    )\n                merge_file = os.path.join(migration_dir, '0003_merge.py')\n                self.assertFalse(os.path.exists(merge_file))\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
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        "complexity": 1,
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        "n_identifiers": 21,
        "d_id": 50165,
        "documentation": {
            "docstring": "\n        makemigrations enters and exits interactive mode properly.\n        ",
            "n_words": 7,
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            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 223004,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/sysconfig.py",
        "file_name": "sysconfig.py",
        "fun_name": "customize_compiler",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def customize_compiler(compiler):\n    \n    if compiler.compiler_type == \"unix\":\n        if sys.platform == \"darwin\":\n            # Perform first-time customization of compiler-related\n            # config vars on OS X now that we know we need a compiler.\n            # This is primarily to support Pythons from binary\n            # installers.  The kind and paths to build tools on\n            # the user system may vary significantly from the system\n            # that Python itself was built on.  Also the user OS\n            # version and build tools may not support the same set\n            # of CPU architectures for universal builds.\n            if not _config_vars.get('CUSTOMIZED_OSX_COMPILER'):\n                import _osx_support\n                _osx_support.customize_compiler(_config_vars)\n                _config_vars['CUSTOMIZED_OSX_COMPILER'] = 'True'\n\n        (cc, cxx, cflags, ccshared, ldshared, shlib_suffix, ar, ar_flags) = \\\n            get_config_vars('CC', 'CXX', 'CFLAGS',\n                            'CCSHARED', 'LDSHARED', 'SHLIB_SUFFIX', 'AR', 'ARFLAGS')\n\n        if 'CC' in os.environ:\n            newcc = os.environ['CC']\n            if (sys.platform == 'darwin'\n                    and 'LDSHARED' not in os.environ\n                    and ldshared.startswith(cc)):\n                # On OS X, if CC is overridden, use that as the default\n                #       command for LDSHARED as well\n                ldshared = newcc + ldshared[len(cc):]\n            cc = newcc\n        if 'CXX' in os.environ:\n            cxx = os.environ['CXX']\n        if 'LDSHARED' in os.environ:\n            ldshared = os.environ['LDSHARED']\n        if 'CPP' in os.environ:\n            cpp = os.environ['CPP']\n        else:\n            cpp = cc + \" -E\"           # not always\n        if 'LDFLAGS' in os.environ:\n            ldshared = ldshared + ' ' + os.environ['LDFLAGS']\n        if 'CFLAGS' in os.environ:\n            cflags = cflags + ' ' + os.environ['CFLAGS']\n            ldshared = ldshared + ' ' + os.environ['CFLAGS']\n        if 'CPPFLAGS' in os.environ:\n            cpp = cpp + ' ' + os.environ['CPPFLAGS']\n            cflags = cflags + ' ' + os.environ['CPPFLAGS']\n            ldshared = ldshared + ' ' + os.environ['CPPFLAGS']\n        if 'AR' in os.environ:\n            ar = os.environ['AR']\n        if 'ARFLAGS' in os.environ:\n            archiver = ar + ' ' + os.environ['ARFLAGS']\n        else:\n            archiver = ar + ' ' + ar_flags\n\n        cc_cmd = cc + ' ' + cflags\n        compiler.set_executables(\n            preprocessor=cpp,\n            compiler=cc_cmd,\n            compiler_so=cc_cmd + ' ' + ccshared,\n            compiler_cxx=cxx,\n            linker_so=ldshared,\n            linker_exe=cc,\n            archiver=archiver)\n\n        compiler.shared_lib_extension = shlib_suffix\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
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        "documentation": {
            "docstring": "Do any platform-specific customization of a CCompiler instance.\n\n    Mainly needed on Unix, so we can plug in the information that\n    varies across Unices and is stored in Python's Makefile.\n    ",
            "n_words": 29,
            "vocab_size": 28,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 203361,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/checks.py",
        "file_name": "checks.py",
        "fun_name": "_check_list_filter_item",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _check_list_filter_item(self, obj, item, label):\n        \n        from django.contrib.admin import FieldListFilter, ListFilter\n\n        if callable(item) and not isinstance(item, models.Field):\n            # If item is option 3, it should be a ListFilter...\n            if not _issubclass(item, ListFilter):\n                return must_inherit_from(\n                    parent=\"ListFilter\", option=label, obj=obj, id=\"admin.E113\"\n                )\n            # ...  but not a FieldListFilter.\n            elif issubclass(item, FieldListFilter):\n                return [\n                    checks.Error(\n                        \"The value of '%s' must not inherit from 'FieldListFilter'.\"\n                        % label,\n                        obj=obj.__class__,\n                        id=\"admin.E114\",\n                    )\n                ]\n            else:\n                return []\n        elif isinstance(item, (tuple, list)):\n            # item is option #2\n            field, list_filter_class = item\n            if not _issubclass(list_filter_class, FieldListFilter):\n                return must_inherit_from(\n                    parent=\"FieldListFilter\",\n                    option=\"%s[1]\" % label,\n                    obj=obj,\n                    id=\"admin.E115\",\n                )\n            else:\n                return []\n        else:\n            # item is option #1\n            field = item\n\n            # Validate the field string\n            try:\n                get_fields_from_path(obj.model, field)\n            except (NotRelationField, FieldDoesNotExist):\n                return [\n                    checks.Error(\n                        \"The value of '%s' refers to '%s', which does not refer to a Field.\"\n                        % (label, field),\n                        obj=obj.__class__,\n                        id=\"admin.E116\",\n                    )\n                ]\n            else:\n                return []\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 880,
        "n_words": 144,
        "vocab_size": 89,
        "complexity": 8,
        "nloc": 44,
        "token_counts": 207,
        "n_ast_nodes": 331,
        "n_identifiers": 31,
        "d_id": 50332,
        "documentation": {
            "docstring": "\n        Check one item of `list_filter`, i.e. check if it is one of three options:\n        1. 'field' -- a basic field filter, possibly w/ relationships (e.g.\n           'field__rel')\n        2. ('field', SomeFieldListFilter) - a field-based list filter class\n        3. SomeListFilter - a non-field list filter class\n        ",
            "n_words": 43,
            "vocab_size": 35,
            "n_whitespaces": 89,
            "language": "en"
        }
    },
    {
        "id": 64880,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/loyalty_point_entry/loyalty_point_entry.py",
        "file_name": "loyalty_point_entry.py",
        "fun_name": "get_redemption_details",
        "commit_message": "style: format code with black",
        "code": "def get_redemption_details(customer, loyalty_program, company):\n\treturn frappe._dict(\n\t\tfrappe.db.sql(\n\t\t\t,\n\t\t\t(customer, loyalty_program, company),\n\t\t)\n\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 6,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 32,
        "n_ast_nodes": 47,
        "n_identifiers": 8,
        "d_id": 13746,
        "documentation": {
            "docstring": "\n\t\tselect redeem_against, sum(loyalty_points)\n\t\tfrom `tabLoyalty Point Entry`\n\t\twhere customer=%s and loyalty_program=%s and loyalty_points<0 and company=%s\n\t\tgroup by redeem_against\n\t",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 38418,
        "commit_id": "38043d8453b82a9c712f8d5c98323150fbee7503",
        "repo": "transformers",
        "path": "utils/tests_fetcher.py",
        "file_name": "tests_fetcher.py",
        "fun_name": "get_all_tests",
        "commit_message": "Update self-push workflow (#17177)\n\n* update push ci\r\n\r\n* install git-python\r\n\r\n* update comment\r\n\r\n* update deepspeed jobs\r\n\r\n* fix report\r\n\r\n* skip 2 more tests that require fairscale\r\n\r\n* Fix changes in test_fetcher.py (to deal with `setup.py` is changed)\r\n\r\n* set RUN_PT_TF_CROSS_TESTS=1 and final clean-up\r\n\r\n* remove SIGOPT_API_TOKEN\r\n\r\n* remove echo \"$matrix_folders\"\r\n\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>",
        "code": "def get_all_tests():\n    \n    test_root_dir = os.path.join(PATH_TO_TRANFORMERS, \"tests\")\n\n    # test folders/files directly under `tests` folder\n    tests = os.listdir(test_root_dir)\n    tests = sorted(\n        list(filter(lambda x: os.path.isdir(x) or x.startswith(\"tests/test_\"), [f\"tests/{x}\" for x in tests]))\n    )\n\n    # model specific test folders\n    model_tests_folders = os.listdir(os.path.join(test_root_dir, \"models\"))\n    model_test_folders = sorted(list(filter(os.path.isdir, [f\"tests/models/{x}\" for x in model_tests_folders])))\n\n    tests.remove(\"tests/models\")\n    tests = model_test_folders + tests\n\n    return tests\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 98,
        "n_words": 55,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 118,
        "n_ast_nodes": 205,
        "n_identifiers": 17,
        "d_id": 6971,
        "documentation": {
            "docstring": "\n    Return a list of paths to all test folders and files under `tests`. All paths are rooted at `tests`.\n\n    - folders under `tests`: `tokenization`, `pipelines`, etc. The folder `models` is excluded.\n    - folders under `tests/models`: `bert`, `gpt2`, etc.\n    - test files under `tests`: `test_modeling_common.py`, `test_tokenization_common.py`, etc.\n    ",
            "n_words": 46,
            "vocab_size": 32,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 186894,
        "commit_id": "39e8d14e1b221bf37526cc05ecc83beee30a3c57",
        "repo": "certbot",
        "path": "tools/finish_release.py",
        "file_name": "finish_release.py",
        "fun_name": "promote_snaps",
        "commit_message": "Set up 2.0 pre-releases (#9400)\n\n* update credential info\r\n\r\n* update release tooling to use candidate channel\r\n\r\n* split deploy jobs\r\n\r\n* pass parameter through\r\n\r\n* add 2.0 pipeline prerelease\r\n\r\n* add comments\r\n\r\n* quote file path",
        "code": "def promote_snaps(version):\n    \n    assert_logged_into_snapcraft()\n    for snap in SNAPS:\n        revisions = get_snap_revisions(snap, version)\n        # The loop below is kind of slow, so let's print some output about what\n        # it is doing.\n        print('Releasing', snap, 'snaps to the stable channel')\n        for revision in revisions:\n            cmd = ['snapcraft', 'release', snap, revision, 'stable']\n            try:\n                subprocess.run(cmd, check=True, stdout=subprocess.PIPE, universal_newlines=True)\n            except subprocess.CalledProcessError as e:\n                print(\"The command\", f\"'{' '.join(cmd)}'\", \"failed.\")\n                print(\"The output printed to stdout was:\")\n                print(e.stdout)\n                raise\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 222,
        "n_words": 70,
        "vocab_size": 61,
        "complexity": 4,
        "nloc": 14,
        "token_counts": 97,
        "n_ast_nodes": 180,
        "n_identifiers": 19,
        "d_id": 45647,
        "documentation": {
            "docstring": "Promotes all Certbot snaps from the candidate to stable channel.\n\n    If the snaps have already been released to the stable channel, this\n    function will try to release them again which has no effect.\n\n    :param str version: the version number that should be found in the\n        candidate channel, e.g. 1.7.0\n\n    :raises SystemExit: if the command snapcraft is unavailable or it\n        isn't logged into an account\n\n    :raises subprocess.CalledProcessError: if a snapcraft command fails\n        for another reason\n\n    ",
            "n_words": 74,
            "vocab_size": 59,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 66963,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/payroll/report/salary_register/salary_register.py",
        "file_name": "salary_register.py",
        "fun_name": "get_ss_earning_map",
        "commit_message": "style: format code with black",
        "code": "def get_ss_earning_map(salary_slips, currency, company_currency):\n\tss_earnings = frappe.db.sql(\n\t\t\n\t\t% (\", \".join([\"%s\"] * len(salary_slips))),\n\t\ttuple([d.name for d in salary_slips]),\n\t\tas_dict=1,\n\t)\n\n\tss_earning_map = {}\n\tfor d in ss_earnings:\n\t\tss_earning_map.setdefault(d.parent, frappe._dict()).setdefault(d.salary_component, 0.0)\n\t\tif currency == company_currency:\n\t\t\tss_earning_map[d.parent][d.salary_component] += flt(d.amount) * flt(\n\t\t\t\td.exchange_rate if d.exchange_rate else 1\n\t\t\t)\n\t\telse:\n\t\t\tss_earning_map[d.parent][d.salary_component] += flt(d.amount)\n\n\treturn ss_earning_map\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 34,
        "n_words": 50,
        "vocab_size": 38,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 145,
        "n_ast_nodes": 221,
        "n_identifiers": 22,
        "d_id": 14391,
        "documentation": {
            "docstring": "select sd.parent, sd.salary_component, sd.amount, ss.exchange_rate, ss.name\n\t\tfrom `tabSalary Detail` sd, `tabSalary Slip` ss where sd.parent=ss.name and sd.parent in (%s)",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 101070,
        "commit_id": "049314429f71a21e6595e9d27e9e36f6a3479c42",
        "repo": "faceswap",
        "path": "plugins/convert/writer/pillow.py",
        "file_name": "pillow.py",
        "fun_name": "_get_save_kwargs",
        "commit_message": "Convert: Add option to output mask separately for draw-transparent",
        "code": "def _get_save_kwargs(self) -> Dict[str, Union[bool, int, str]]:\n        \n        filetype = self.config[\"format\"]\n        kwargs = {}\n        if filetype in (\"gif\", \"jpg\", \"png\"):\n            kwargs[\"optimize\"] = self.config[\"optimize\"]\n        if filetype == \"gif\":\n            kwargs[\"interlace\"] = self.config[\"gif_interlace\"]\n        if filetype == \"png\":\n            kwargs[\"compress_level\"] = self.config[\"png_compress_level\"]\n        if filetype == \"tif\":\n            kwargs[\"compression\"] = self.config[\"tif_compression\"]\n        logger.debug(kwargs)\n        return kwargs\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 153,
        "n_words": 46,
        "vocab_size": 31,
        "complexity": 5,
        "nloc": 20,
        "token_counts": 110,
        "n_ast_nodes": 195,
        "n_identifiers": 12,
        "d_id": 20507,
        "documentation": {
            "docstring": " Return the save parameters for the file format\n\n        Returns\n        -------\n        dict\n            The specific keyword arguments for the selected file format\n        ",
            "n_words": 20,
            "vocab_size": 15,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 60302,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/test/test_coord_map.py",
        "file_name": "test_coord_map.py",
        "fun_name": "test_multi_conv",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def test_multi_conv(self):\n        \n        n = coord_net_spec()\n        # multi bottom/top\n        n.conv_data, n.conv_aux = L.Convolution(\n            n.data, n.aux, ntop=2, num_output=10, kernel_size=5, stride=2,\n            pad=0)\n        ax1, a1, b1 = coord_map_from_to(n.conv_data, n.data)\n        ax2, a2, b2 = coord_map_from_to(n.conv_aux, n.aux)\n        self.assertEquals(ax1, ax2)\n        self.assertEquals(a1, a2)\n        self.assertEquals(b1, b2)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 122,
        "n_words": 37,
        "vocab_size": 34,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 107,
        "n_ast_nodes": 160,
        "n_identifiers": 23,
        "d_id": 12080,
        "documentation": {
            "docstring": "\n        Multiple bottoms/tops of a layer are identically mapped.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 198503,
        "commit_id": "9d58006fc0a23afcba38f641c9472917c436428a",
        "repo": "sympy",
        "path": "sympy/polys/multivariate_resultants.py",
        "file_name": "multivariate_resultants.py",
        "fun_name": "get_submatrix",
        "commit_message": "Code cleanup",
        "code": "def get_submatrix(self, matrix):\n        r\n        reduced, non_reduced = self.get_reduced_nonreduced()\n\n        # if reduced == [], then det(matrix) should be 1\n        if reduced == []:\n            return diag([1])\n\n        # reduced != []\n        reduction_set = [v ** self.degrees[i] for i, v\n                         in enumerate(self.variables)]\n\n        ais = [self.polynomials[i].coeff(reduction_set[i])\n               for i in range(self.n)]\n\n        reduced_matrix = matrix[:, reduced]\n        keep = []\n        for row in range(reduced_matrix.rows):\n            check = [ai in reduced_matrix[row, :] for ai in ais]\n            if True not in check:\n                keep.append(row)\n\n        return matrix[keep, non_reduced]\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 237,
        "n_words": 75,
        "vocab_size": 54,
        "complexity": 7,
        "nloc": 24,
        "token_counts": 138,
        "n_ast_nodes": 212,
        "n_identifiers": 25,
        "d_id": 48966,
        "documentation": {
            "docstring": "\n        Returns\n        =======\n\n        macaulay_submatrix: Matrix\n            The Macaulay denominator matrix. Columns that are non reduced are kept.\n            The row which contains one of the a_{i}s is dropped. a_{i}s\n            are the coefficients of x_i ^ {d_i}.\n        ",
            "n_words": 33,
            "vocab_size": 27,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 131456,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tests/test_component_failures_2.py",
        "file_name": "test_component_failures_2.py",
        "fun_name": "check_components_alive",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def check_components_alive(cluster, component_type, check_component_alive):\n    \n    worker_nodes = get_other_nodes(cluster)\n    assert len(worker_nodes) > 0\n    for node in worker_nodes:\n        process = node.all_processes[component_type][0].process\n        if check_component_alive:\n            assert process.poll() is None\n        else:\n            print(\n                \"waiting for \"\n                + component_type\n                + \" with PID \"\n                + str(process.pid)\n                + \"to terminate\"\n            )\n            process.wait()\n            print(\n                \"done waiting for \"\n                + component_type\n                + \" with PID \"\n                + str(process.pid)\n                + \"to terminate\"\n            )\n            assert not process.poll() is None\n\n\n@pytest.mark.parametrize(\n    \"ray_start_cluster\",\n    [\n        {\n            \"num_cpus\": 8,\n            \"num_nodes\": 4,\n            \"_system_config\": {\"num_heartbeats_timeout\": 10},\n        }\n    ],\n    indirect=True,\n)",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"ray_start_cluster\",\n    [\n        {\n            \"num_cpus\": 8,\n            \"num_nodes\": 4,\n            \"_system_config\": {\"num_heartbeats_timeout\": 10},\n        }\n    ],\n    indirect=True,\n)",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 398,
        "n_words": 81,
        "vocab_size": 52,
        "complexity": 3,
        "nloc": 24,
        "token_counts": 102,
        "n_ast_nodes": 235,
        "n_identifiers": 19,
        "d_id": 29534,
        "documentation": {
            "docstring": "Check that a given component type is alive on all worker nodes.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 156105,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "compute_current_divisions",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def compute_current_divisions(self, col=None):\n        \n        if col is None and self.known_divisions:\n            return self.divisions\n\n        from dask.dataframe.shuffle import compute_divisions\n\n        return compute_divisions(self, col=col)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 40,
        "n_ast_nodes": 62,
        "n_identifiers": 9,
        "d_id": 36561,
        "documentation": {
            "docstring": "Compute the current divisions of the DataFrame.\n\n        This method triggers immediate computation. If you find yourself running this command\n        repeatedly for the same dataframe, we recommend storing the result\n        so you don't have to rerun it.\n\n        If the column or index values overlap between partitions, raises ``ValueError``.\n        To prevent this, make sure the data are sorted by the column or index.\n\n        Parameters\n        ----------\n        col : string, optional\n            Calculate the divisions for a non-index column by passing in the name of the column.\n            If col is not specified, the index will be used to calculate divisions.\n            In this case, if the divisions are already known, they will be returned\n            immediately without computing.\n\n        Examples\n        --------\n        >>> import dask\n        >>> ddf = dask.datasets.timeseries(start=\"2021-01-01\", end=\"2021-01-07\", freq=\"1H\").clear_divisions()\n        >>> divisions = ddf.compute_current_divisions()\n        >>> print(divisions)  # doctest: +NORMALIZE_WHITESPACE\n        (Timestamp('2021-01-01 00:00:00'),\n         Timestamp('2021-01-02 00:00:00'),\n         Timestamp('2021-01-03 00:00:00'),\n         Timestamp('2021-01-04 00:00:00'),\n         Timestamp('2021-01-05 00:00:00'),\n         Timestamp('2021-01-06 00:00:00'),\n         Timestamp('2021-01-06 23:00:00'))\n\n        >>> ddf.divisions = divisions\n        >>> ddf.known_divisions\n        True\n\n        >>> ddf = ddf.reset_index().clear_divisions()\n        >>> divisions = ddf.compute_current_divisions(\"timestamp\")\n        >>> print(divisions)  # doctest: +NORMALIZE_WHITESPACE\n        (Timestamp('2021-01-01 00:00:00'),\n         Timestamp('2021-01-02 00:00:00'),\n         Timestamp('2021-01-03 00:00:00'),\n         Timestamp('2021-01-04 00:00:00'),\n         Timestamp('2021-01-05 00:00:00'),\n         Timestamp('2021-01-06 00:00:00'),\n         Timestamp('2021-01-06 23:00:00'))\n\n        >>> ddf = ddf.set_index(\"timestamp\", divisions=divisions, sorted=True)\n        ",
            "n_words": 185,
            "vocab_size": 113,
            "n_whitespaces": 495,
            "language": "en"
        }
    },
    {
        "id": 61340,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/utils/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "parse_wheel",
        "commit_message": "upd; format",
        "code": "def parse_wheel(wheel_zip, name):\n    # type: (ZipFile, str) -> Tuple[str, Message]\n    \n    try:\n        info_dir = wheel_dist_info_dir(wheel_zip, name)\n        metadata = wheel_metadata(wheel_zip, info_dir)\n        version = wheel_version(metadata)\n    except UnsupportedWheel as e:\n        raise UnsupportedWheel(\"{} has an invalid wheel, {}\".format(name, str(e)))\n\n    check_compatibility(version, name)\n\n    return info_dir, metadata\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 85,
        "n_words": 39,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 62,
        "n_ast_nodes": 103,
        "n_identifiers": 14,
        "d_id": 12522,
        "documentation": {
            "docstring": "Extract information from the provided wheel, ensuring it meets basic\n    standards.\n\n    Returns the name of the .dist-info directory and the parsed WHEEL metadata.\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 31378,
        "commit_id": "a2d34b7c040723b92823310e3b8fd66874c9d667",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_torch_bf16_cpu",
        "commit_message": "deprecate is_torch_bf16_available (#17738)\n\n* deprecate is_torch_bf16_available\r\n\r\n* address suggestions",
        "code": "def require_torch_bf16_cpu(test_case):\n    \n    return unittest.skipUnless(\n        is_torch_bf16_cpu_available(),\n        \"test requires torch>=1.10, using CPU\",\n    )(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 34,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 5726,
        "documentation": {
            "docstring": "Decorator marking a test that requires torch>=1.10, using CPU.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 69969,
        "commit_id": "4d50e8cb5756755cf019cef1f45cd569bef708fc",
        "repo": "glances",
        "path": "glances/plugins/glances_plugin.py",
        "file_name": "glances_plugin.py",
        "fun_name": "is_show",
        "commit_message": "Create a Show option in the configuration file to only show some stats #2052",
        "code": "def is_show(self, value, header=\"\"):\n        \n        # @TODO: possible optimisation: create a re.compile list\n        return any(j for j in [re.match(i, value) for i in self.get_conf_value('show', header=header)])\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 45,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 2,
        "token_counts": 43,
        "n_ast_nodes": 69,
        "n_identifiers": 10,
        "d_id": 15210,
        "documentation": {
            "docstring": "Return True if the value is in the show configuration list.\n\n        If the show value is empty, return True (show by default)\n\n        The show configuration list is defined in the glances.conf file.\n        It is a comma separated list of regexp.\n        Example for diskio:\n        show=sda.*\n        ",
            "n_words": 44,
            "vocab_size": 31,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 258673,
        "commit_id": "9f85c9d44965b764f40169ef2917e5f7a798684f",
        "repo": "scikit-learn",
        "path": "sklearn/feature_selection/tests/test_from_model.py",
        "file_name": "test_from_model.py",
        "fun_name": "test_estimator_does_not_support_feature_names",
        "commit_message": "TST Better info when checking for no warnings in tests (#22362)",
        "code": "def test_estimator_does_not_support_feature_names():\n    \n    pytest.importorskip(\"pandas\")\n    X, y = datasets.load_iris(as_frame=True, return_X_y=True)\n    all_feature_names = set(X.columns)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 23,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 114,
        "n_ast_nodes": 61,
        "n_identifiers": 12,
        "d_id": 75364,
        "documentation": {
            "docstring": "SelectFromModel works with estimators that do not support feature_names_in_.\n\n    Non-regression test for #21949.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 246901,
        "commit_id": "02d708568b476f2f7716000b35c0adfa4cbd31b3",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "test_get_member_list_no_permission_former_member",
        "commit_message": "Replace assertEquals and friends with non-deprecated versions. (#12092)",
        "code": "def test_get_member_list_no_permission_former_member(self):\n        \n        # create a room, invite the user and the user joins\n        room_id = self.helper.create_room_as(\"@alice:red\")\n        self.helper.invite(room_id, \"@alice:red\", self.user_id)\n        self.helper.join(room_id, self.user_id)\n\n        # check that the user can see the member list to start with\n        channel = self.make_request(\"GET\", \"/rooms/%s/members\" % room_id)\n        self.assertEqual(200, channel.code, msg=channel.result[\"body\"])\n\n        # ban the user\n        self.helper.change_membership(room_id, \"@alice:red\", self.user_id, \"ban\")\n\n        # check the user can no longer see the member list\n        channel = self.make_request(\"GET\", \"/rooms/%s/members\" % room_id)\n        self.assertEqual(403, channel.code, msg=channel.result[\"body\"])\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 162,
        "n_words": 71,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 120,
        "n_ast_nodes": 203,
        "n_identifiers": 15,
        "d_id": 71395,
        "documentation": {
            "docstring": "\n        Tests that a former member of the room can not get the member list.\n        ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 206855,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/generic/dates.py",
        "file_name": "dates.py",
        "fun_name": "get_dated_queryset",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_dated_queryset(self, **lookup):\n        \n        qs = self.get_queryset().filter(**lookup)\n        date_field = self.get_date_field()\n        allow_future = self.get_allow_future()\n        allow_empty = self.get_allow_empty()\n        paginate_by = self.get_paginate_by(qs)\n\n        if not allow_future:\n            now = timezone.now() if self.uses_datetime_field else timezone_today()\n            qs = qs.filter(**{\"%s__lte\" % date_field: now})\n\n        if not allow_empty:\n            # When pagination is enabled, it's better to do a cheap query\n            # than to load the unpaginated queryset in memory.\n            is_empty = not qs if paginate_by is None else not qs.exists()\n            if is_empty:\n                raise Http404(\n                    _(\"No %(verbose_name_plural)s available\")\n                    % {\n                        \"verbose_name_plural\": qs.model._meta.verbose_name_plural,\n                    }\n                )\n\n        return qs\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 323,
        "n_words": 84,
        "vocab_size": 61,
        "complexity": 6,
        "nloc": 19,
        "token_counts": 130,
        "n_ast_nodes": 222,
        "n_identifiers": 25,
        "d_id": 51756,
        "documentation": {
            "docstring": "\n        Get a queryset properly filtered according to `allow_future` and any\n        extra lookup kwargs.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 4171,
        "commit_id": "63af98e3b999d4b223237b51472a819915c5a558",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-recurly/source_recurly/streams.py",
        "file_name": "streams.py",
        "fun_name": "default_params",
        "commit_message": "🎉 Recurly Schema Revamp (#9866)\n\n* Cleanup Recurly connector schemas\r\n\r\n* Add more Recurly schemas to the connector\r\n\r\n- `billing_infos`\r\n- `shipping_addresses`\r\n- `shipping_methods`\r\n- `subscription_changes`\r\n\r\n* Add Recurly `add-on` resouce\r\n\r\n* Add Recurly's account notes resource schema\r\n\r\n* Add unique coupons to Recurly source\r\n\r\n* Add credit payments to Recurly connector\r\n\r\n* Add Recurly resources to integration tests configurations\r\n\r\n* Bump Recurly source version to `0.4.0`\r\n\r\n* Add `line_items` Recurly resource\r\n\r\n* Add `line_items` to Recurly documentation\r\n\r\n* Add missing `line_items` JSON schema\r\n\r\n* Replace Subscription Change Recurly API call with Subscription `pending_changes` field\r\n\r\n* Replace Recurly unique coupon codes API call with coupons `unique_coupon` field\r\n\r\nTo avoid the extra API call to import unique coupon calls\r\n\r\n* Revert \"Replace Recurly unique coupon codes API call with coupons `unique_coupon` field\"\r\n\r\nThis reverts commit 1c4592d82da3c5e5e0026dda8eb2ed7a896ac5b8.\r\n\r\n* Add `end_time` parameter to Recurly connector\r\n\r\n* Order Recurly specs\r\n\r\n* Set the Recurly `begin_time` and `end_time` to be optional\r\n\r\n* Add `order` to Recurly `source_spec.yaml`\r\n\r\n* Add `maxLength` to Recurly source schemas\r\n\r\n* Set `maxLength` for Recurly Subscription and Transaction `uuid`\r\n\r\n* Fix Recurly `export_dates` acceptance tests",
        "code": "def default_params(self) -> dict:\n        \n        return {\"order\": \"asc\", \"sort\": self.sort_key, \"limit\": self.limit}\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 25,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 26,
        "n_ast_nodes": 49,
        "n_identifiers": 5,
        "d_id": 628,
        "documentation": {
            "docstring": "\n        Returns the parameters to be sent together with the API call to Recurly\n        ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 268868,
        "commit_id": "a449efe29b092e658a29cd847e0494979a47d252",
        "repo": "keras",
        "path": "keras/tests/keras_doctest.py",
        "file_name": "keras_doctest.py",
        "fun_name": "filter_on_submodules",
        "commit_message": "Add a keras doctest modeled on tensorflow doctest\n\nPiperOrigin-RevId: 424672415",
        "code": "def filter_on_submodules(all_modules, submodule):\n  \n\n  filtered_modules = [\n      mod for mod in all_modules if PACKAGE + submodule in mod.__name__\n  ]\n  return filtered_modules\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 29,
        "n_words": 20,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 27,
        "n_ast_nodes": 43,
        "n_identifiers": 7,
        "d_id": 79737,
        "documentation": {
            "docstring": "Filters all the modules based on the module flag.\n\n  The module flag has to be relative to the core package imported.\n  For example, if `submodule=keras.layers` then, this function will return\n  all the modules in the submodule.\n\n  Args:\n    all_modules: All the modules in the core package.\n    submodule: Submodule to filter from all the modules.\n\n  Returns:\n    All the modules in the submodule.\n  ",
            "n_words": 60,
            "vocab_size": 38,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 62100,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/resources.py",
        "file_name": "resources.py",
        "fun_name": "is_stale",
        "commit_message": "upd; format",
        "code": "def is_stale(self, resource, path):\n        \n        # Cache invalidation is a hard problem :-)\n        return True\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 35,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 21,
        "n_identifiers": 4,
        "d_id": 12869,
        "documentation": {
            "docstring": "\n        Is the cache stale for the given resource?\n\n        :param resource: The :class:`Resource` being cached.\n        :param path: The path of the resource in the cache.\n        :return: True if the cache is stale.\n        ",
            "n_words": 31,
            "vocab_size": 24,
            "n_whitespaces": 67,
            "language": "en"
        }
    },
    {
        "id": 221566,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/concurrent/futures/_base.py",
        "file_name": "_base.py",
        "fun_name": "set_result",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def set_result(self, result):\n        \n        with self._condition:\n            if self._state in {CANCELLED, CANCELLED_AND_NOTIFIED, FINISHED}:\n                raise InvalidStateError('{}: {!r}'.format(self._state, self))\n            self._result = result\n            self._state = FINISHED\n            for waiter in self._waiters:\n                waiter.add_result(self)\n            self._condition.notify_all()\n        self._invoke_callbacks()\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 134,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 75,
        "n_ast_nodes": 123,
        "n_identifiers": 16,
        "d_id": 56431,
        "documentation": {
            "docstring": "Sets the return value of work associated with the future.\n\n        Should only be used by Executor implementations and unit tests.\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 100307,
        "commit_id": "c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf",
        "repo": "faceswap",
        "path": "lib/gui/analysis/event_reader.py",
        "file_name": "event_reader.py",
        "fun_name": "get_data",
        "commit_message": "Update code to support Tensorflow versions up to 2.8 (#1213)\n\n* Update maximum tf version in setup + requirements\r\n\r\n* - bump max version of tf version in launcher\r\n- standardise tf version check\r\n\r\n* update keras get_custom_objects  for tf>2.6\r\n\r\n* bugfix: force black text in GUI file dialogs (linux)\r\n\r\n* dssim loss - Move to stock tf.ssim function\r\n\r\n* Update optimizer imports for compatibility\r\n\r\n* fix logging for tf2.8\r\n\r\n* Fix GUI graphing for TF2.8\r\n\r\n* update tests\r\n\r\n* bump requirements.txt versions\r\n\r\n* Remove limit on nvidia-ml-py\r\n\r\n* Graphing bugfixes\r\n  - Prevent live graph from displaying if data not yet available\r\n\r\n* bugfix: Live graph. Collect loss labels correctly\r\n\r\n* fix: live graph - swallow inconsistent loss errors\r\n\r\n* Bugfix: Prevent live graph from clearing during training\r\n\r\n* Fix graphing for AMD",
        "code": "def get_data(self, session_id, metric):\n        \n        if session_id is None:\n            raw = self._data\n        else:\n            data = self._data.get(session_id)\n            if not data:\n                return None\n            raw = {session_id: data}\n\n        dtype = \"float32\" if metric == \"loss\" else \"float64\"\n\n        retval = {}\n        for idx, data in raw.items():\n            val = {metric: np.frombuffer(zlib.decompress(data[metric]),\n                                         dtype=dtype).reshape(data[f\"{metric}_shape\"])}\n            if metric == \"loss\":\n                val[\"labels\"] = data[\"labels\"]\n            retval[idx] = val\n\n        logger.debug(\"Obtained cached data: %s\",\n                     {session_id: {k: v.shape if isinstance(v, np.ndarray) else v\n                                   for k, v in data.items()}\n                      for session_id, data in retval.items()})\n        return retval\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 358,
        "n_words": 80,
        "vocab_size": 52,
        "complexity": 9,
        "nloc": 21,
        "token_counts": 173,
        "n_ast_nodes": 284,
        "n_identifiers": 25,
        "d_id": 19804,
        "documentation": {
            "docstring": " Retrieve the decompressed cached data from the cache for the given session id.\n\n        Parameters\n        ----------\n        session_id: int or ``None``\n            If session_id is provided, then the cached data for that session is returned. If\n            session_id is ``None`` then the cached data for all sessions is returned\n        metric: ['loss', 'timestamps']\n            The metric to return the data for.\n\n        Returns\n        -------\n        dict\n            The `session_id` (s) as key, the values are a dictionary containing the requested\n            metric information for each session returned\n        ",
            "n_words": 77,
            "vocab_size": 50,
            "n_whitespaces": 189,
            "language": "en"
        }
    },
    {
        "id": 22233,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/requirements.py",
        "file_name": "requirements.py",
        "fun_name": "find_all_matches",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def find_all_matches(self, sources=None, finder=None):\n        # type: (Optional[List[Dict[S, Union[S, bool]]]], Optional[PackageFinder]) -> List[InstallationCandidate]\n        \n\n        from .dependencies import find_all_matches, get_finder\n\n        if not finder:\n            _, finder = get_finder(sources=sources)\n        return find_all_matches(finder, self.as_ireq())\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 73,
        "n_words": 27,
        "vocab_size": 27,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 77,
        "n_identifiers": 8,
        "d_id": 4277,
        "documentation": {
            "docstring": "Find all matching candidates for the current requirement.\n\n        Consults a finder to find all matching candidates.\n\n        :param sources: Pipfile-formatted sources, defaults to None\n        :param sources: list[dict], optional\n        :param PackageFinder finder: A **PackageFinder** instance from pip's repository implementation\n        :return: A list of Installation Candidates\n        :rtype: list[ :class:`~pipenv.patched.pip._internal.index.InstallationCandidate` ]\n        ",
            "n_words": 47,
            "vocab_size": 40,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 126954,
        "commit_id": "0dceddb912ed92286032b5563dd2e541a8a7031f",
        "repo": "ray",
        "path": "rllib/algorithms/ddpg/tests/test_ddpg.py",
        "file_name": "test_ddpg.py",
        "fun_name": "test_ddpg_compilation",
        "commit_message": "[RLlib] Move learning_starts logic from buffers into `training_step()`. (#26032)",
        "code": "def test_ddpg_compilation(self):\n        \n        config = (\n            ddpg.DDPGConfig()\n            .training(num_steps_sampled_before_learning_starts=0)\n            .rollouts(num_rollout_workers=0, num_envs_per_worker=2)\n        )\n        explore = config.exploration_config.update({\"random_timesteps\": 100})\n        config.exploration(exploration_config=explore)\n\n        num_iterations = 1\n\n        # Test against all frameworks.\n        for _ in framework_iterator(config, with_eager_tracing=True):\n            algo = config.build(env=\"Pendulum-v1\")\n            for i in range(num_iterations):\n                results = algo.train()\n                check_train_results(results)\n                print(results)\n            check_compute_single_action(algo)\n            # Ensure apply_gradient_fn is being called and updating global_step\n            pol = algo.get_policy()\n            if config.framework_str == \"tf\":\n                a = pol.get_session().run(pol.global_step)\n            else:\n                a = pol.global_step\n            check(a, 500)\n            algo.stop()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 330,
        "n_words": 67,
        "vocab_size": 56,
        "complexity": 4,
        "nloc": 23,
        "token_counts": 153,
        "n_ast_nodes": 257,
        "n_identifiers": 37,
        "d_id": 28309,
        "documentation": {
            "docstring": "Test whether DDPG can be built with both frameworks.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 100841,
        "commit_id": "ff6b0209dd5ad57b81b0aca570df7f39a7119bfb",
        "repo": "faceswap",
        "path": "plugins/train/model/_base/model.py",
        "file_name": "model.py",
        "fun_name": "increment_iterations",
        "commit_message": "Refactoring and TravisCI to Github Actions (#1239)\n\n* refactor training\r\n\r\n* travis to actions",
        "code": "def increment_iterations(self) -> None:\n        \n        self._iterations += 1\n        self._sessions[self._session_id][\"iterations\"] += 1\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 5,
        "d_id": 20292,
        "documentation": {
            "docstring": " Increment :attr:`iterations` and session iterations by 1. ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 12474,
        "commit_id": "16b16b07a66cd5a8fc7cca1d3f1c378a9c63d38c",
        "repo": "jina",
        "path": "jina/exporter.py",
        "file_name": "exporter.py",
        "fun_name": "export_docker_compose",
        "commit_message": "refactor: rename cli to jina_cli (#4890)\n\n* chore: fix readme\r\n\r\n* chore: fix readme\r\n\r\n* chore: fix dockerignore\r\n\r\n* fix: #4845\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: cicd export cli\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>",
        "code": "def export_docker_compose(args):\n    \n\n    Flow.load_config(args.flowpath).to_docker_compose_yaml(\n        output_path=args.outpath, network_name=args.network_name\n    )\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 22,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 29,
        "n_ast_nodes": 48,
        "n_identifiers": 9,
        "d_id": 2301,
        "documentation": {
            "docstring": "Export to Docker compose yaml files\n\n    :param args: args from CLI\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 4306,
        "commit_id": "710543a9abacc7578238cb5edaa47f43ed7c0431",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-hubspot/unit_tests/test_source.py",
        "file_name": "test_source.py",
        "fun_name": "test_search_based_stream_should_not_attempt_to_get_more_than_10k_records",
        "commit_message": "🐛 Source Hubspot: Handled 10K+ search-endpoint queries (#10700)\n\n* Handled search queries that would output more than 10K records\r\n\r\n* Getting CRM search objects in ascending chronological ortder\r\n\r\n* Fixed stream\r\n\r\n* Fixed rebase\r\n\r\n* Fixed condition\r\n\r\n* Added unit test\r\n\r\n* Removed unused import\r\n\r\n* Started a new query when reached 10K records\r\n\r\n* Moved comment",
        "code": "def test_search_based_stream_should_not_attempt_to_get_more_than_10k_records(requests_mock, common_params, fake_properties_list):\n    \n\n    responses = [\n        {\n            \"json\": {\n                \"results\": [{\"id\": f\"{y}\", \"updatedAt\": \"2022-02-25T16:43:11Z\"} for y in range(100)],\n                \"paging\": {\"next\": {\"after\": f\"{x*100}\",}}\n            },\n            \"status_code\": 200,\n        }\n        for x in range(1, 101)\n    ]\n    # After reaching 10K records, it performs a new search query. \n    responses.extend([\n        {\n            \"json\": {\n                \"results\": [{\"id\": f\"{y}\", \"updatedAt\": \"2022-03-01T00:00:00Z\"} for y in range(100)],\n                \"paging\": {\"next\": {\"after\": f\"{x*100}\",}}\n            },\n            \"status_code\": 200,\n        }\n        for x in range(1, 10)\n    ])\n    # Last page... it does not have paging->next->after\n    responses.append({\n            \"json\": {\n                \"results\": [{\"id\": f\"{y}\", \"updatedAt\": \"2022-03-01T00:00:00Z\"} for y in range(100)],\n                \"paging\": {}\n            },\n            \"status_code\": 200,\n        })\n\n    properties_response = [{\n        \"json\": [\n            {\"name\": property_name, \"type\": \"string\", \"updatedAt\": 1571085954360, \"createdAt\": 1565059306048}\n            for property_name in fake_properties_list\n        ],\n        \"status_code\": 200\n    }]\n\n    # Create test_stream instance with some state\n    test_stream = Companies(**common_params)\n    test_stream.state = {\"updatedAt\": \"2022-02-24T16:43:11Z\"}\n\n    # Mocking Request\n    requests_mock.register_uri(\"POST\", test_stream.url, responses)\n    requests_mock.register_uri(\"GET\", \"/properties/v2/company/properties\", properties_response)\n    records = list(test_stream.read_records(sync_mode=SyncMode.incremental))\n    # The stream should not attempt to get more than 10K records. \n    # Instead, it should use the new state to start a new search query.\n    assert len(records) == 11000\n    assert test_stream.state['updatedAt'] == '2022-03-01T00:00:00+00:00'\n\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 524,
        "n_words": 178,
        "vocab_size": 107,
        "complexity": 7,
        "nloc": 42,
        "token_counts": 277,
        "n_ast_nodes": 514,
        "n_identifiers": 24,
        "d_id": 652,
        "documentation": {
            "docstring": "\n    If there are more than 10,000 records that would be returned by the Hubspot search endpoint,\n    the CRMSearchStream instance should stop at the 10Kth record\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 68837,
        "commit_id": "74a782d81d8f8c4a4d9214a9c06377e5e6e464dd",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/sales_payment_summary/sales_payment_summary.py",
        "file_name": "sales_payment_summary.py",
        "fun_name": "get_mode_of_payments",
        "commit_message": "refactor: DB independent quoting and truthy/falsy values (#31358)\n\n* refactor: DB independent quoting and truthy/falsy values\r\n\r\n* style: reformat to black spec\r\n\r\n* fix: ifnull -> coalesce\r\n\r\n* fix: coalesce -> Coalesce\r\n\r\n* fix: revert pypika comparison\r\n\r\n* refactor: convert queries to QB\r\n\r\n* fix: incorrect value types for query\r\n\r\n`=` query makes no sense with list of values\r\n\r\n* fix: remove warehouse docstatus condition\r\n\r\n* fix: keep using base rate as rate\r\n\r\nCo-authored-by: Ankush Menat <ankush@frappe.io>",
        "code": "def get_mode_of_payments(filters):\n\tmode_of_payments = {}\n\tinvoice_list = get_invoices(filters)\n\tinvoice_list_names = \",\".join(\"'\" + invoice[\"name\"] + \"'\" for invoice in invoice_list)\n\tif invoice_list:\n\t\tinv_mop = frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tinvoice_list_names=invoice_list_names\n\t\t\t),\n\t\t\tas_dict=1,\n\t\t)\n\t\tfor d in inv_mop:\n\t\t\tmode_of_payments.setdefault(d[\"owner\"] + cstr(d[\"posting_date\"]), []).append(d.mode_of_payment)\n\treturn mode_of_payments\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 25,
        "n_words": 39,
        "vocab_size": 31,
        "complexity": 4,
        "nloc": 34,
        "token_counts": 93,
        "n_ast_nodes": 157,
        "n_identifiers": 19,
        "d_id": 14908,
        "documentation": {
            "docstring": "select a.owner,a.posting_date, ifnull(b.mode_of_payment, '') as mode_of_payment\n\t\t\tfrom `tabSales Invoice` a, `tabSales Invoice Payment` b\n\t\t\twhere a.name = b.parent\n\t\t\tand a.docstatus = 1\n\t\t\tand a.name in ({invoice_list_names})\n\t\t\tunion\n\t\t\tselect a.owner,a.posting_date, ifnull(b.mode_of_payment, '') as mode_of_payment\n\t\t\tfrom `tabSales Invoice` a, `tabPayment Entry` b,`tabPayment Entry Reference` c\n\t\t\twhere a.name = c.reference_name\n\t\t\tand b.name = c.parent\n\t\t\tand b.docstatus = 1\n\t\t\tand a.name in ({invoice_list_names})\n\t\t\tunion\n\t\t\tselect a.owner, a.posting_date,\n\t\t\tifnull(a.voucher_type,'') as mode_of_payment\n\t\t\tfrom `tabJournal Entry` a, `tabJournal Entry Account` b\n\t\t\twhere a.name = b.parent\n\t\t\tand a.docstatus = 1\n\t\t\tand b.reference_type = 'Sales Invoice'\n\t\t\tand b.reference_name in ({invoice_list_names})\n\t\t\t",
            "n_words": 91,
            "vocab_size": 42,
            "n_whitespaces": 71,
            "language": "en"
        }
    },
    {
        "id": 80146,
        "commit_id": "ad65741b94f36fbe793cf15f0ab002482070cdb6",
        "repo": "wagtail",
        "path": "wagtail/tests/streamfield_migrations/test_simple_structures.py",
        "file_name": "test_simple_structures.py",
        "fun_name": "test_alter_value",
        "commit_message": "Add tests for streamfield migration helpers\n\nCurrently failing due to wagtail-factories being broken on Wagtail 4.1: https://github.com/wagtail/wagtail-factories/issues/65",
        "code": "def test_alter_value(self):\n        \n\n        altered_raw_data = apply_changes_to_raw_data(\n            raw_data=self.raw_data,\n            block_path_str=\"char1\",\n            operation=AlterBlockValueOperation(new_value=\"foo\"),\n            streamfield=models.SampleModel.content,\n        )\n\n        self.assertEqual(altered_raw_data[0][\"value\"], \"foo\")\n        self.assertEqual(altered_raw_data[1][\"value\"], self.raw_data[1][\"value\"])\n        self.assertEqual(altered_raw_data[2][\"value\"], \"foo\")\n        self.assertEqual(altered_raw_data[3][\"value\"], self.raw_data[3][\"value\"])\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 111,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 110,
        "n_ast_nodes": 181,
        "n_identifiers": 14,
        "d_id": 17024,
        "documentation": {
            "docstring": "Change the value of each `char1` block to `foo`\n\n        Check whether the value of each `char1` block has changed to `foo`.\n        Check whether the values of other blocks are intact.\n        ",
            "n_words": 30,
            "vocab_size": 19,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 39476,
        "commit_id": "99b46f65e08a67f3b11cbaf80edeffe6dd5d6b2e",
        "repo": "recommenders",
        "path": "contrib/sarplus/python/pysarplus/SARPlus.py",
        "file_name": "SARPlus.py",
        "fun_name": "get_popularity_based_topk",
        "commit_message": "Implemented get_popularity_based_topk",
        "code": "def get_popularity_based_topk(self, top_k=10, items=True):\n        \n\n        # TODO: get most frequent users\n        if not items:\n            raise ValueError(\"Not implemented\")\n\n        return self.item_frequencies.orderBy(\"frequency\", ascending=False).limit(top_k)\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 58,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 41,
        "n_ast_nodes": 70,
        "n_identifiers": 9,
        "d_id": 7242,
        "documentation": {
            "docstring": "Get top K most frequently occurring items across all users.\n\n        Args:\n            top_k (int): number of top items to recommend.\n            items (bool): if false, return most frequent users instead.\n\n        Returns:\n            pyspark.sql.DataFrame: Spark dataframe with top k most popular items\n            and their frequencies in descending order.\n        ",
            "n_words": 44,
            "vocab_size": 37,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 65988,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/erpnext_integrations/doctype/mpesa_settings/mpesa_settings.py",
        "file_name": "mpesa_settings.py",
        "fun_name": "format_string_to_json",
        "commit_message": "style: format code with black",
        "code": "def format_string_to_json(balance_info):\n\tWorking Account|KES|481000.00|481000.00|0.00|0.00\n\tbalance_dict = frappe._dict()\n\tfor account_info in balance_info.split(\"&\"):\n\t\taccount_info = account_info.split(\"|\")\n\t\tbalance_dict[account_info[0]] = dict(\n\t\t\tcurrent_balance=fmt_money(account_info[2], currency=\"KES\"),\n\t\t\tavailable_balance=fmt_money(account_info[3], currency=\"KES\"),\n\t\t\treserved_balance=fmt_money(account_info[4], currency=\"KES\"),\n\t\t\tuncleared_balance=fmt_money(account_info[5], currency=\"KES\"),\n\t\t)\n\treturn dumps(balance_dict)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 16,
        "n_words": 28,
        "vocab_size": 22,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 103,
        "n_ast_nodes": 166,
        "n_identifiers": 15,
        "d_id": 14080,
        "documentation": {
            "docstring": "\n\tFormat string to json.\n\n\te.g: \n\t=> {'Working Account': {'current_balance': '481000.00',\n\t        'available_balance': '481000.00',\n\t        'reserved_balance': '0.00',\n\t        'uncleared_balance': '0.00'}}\n\t",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 242434,
        "commit_id": "a0e1fde1eddf45f26653e2ff6080d31e177adbec",
        "repo": "Pillow",
        "path": "src/PIL/ImageFile.py",
        "file_name": "ImageFile.py",
        "fun_name": "setimage",
        "commit_message": "Added PyEncoder",
        "code": "def setimage(self, im, extents=None):\n        \n\n        # following c code\n        self.im = im\n\n        if extents:\n            (x0, y0, x1, y1) = extents\n        else:\n            (x0, y0, x1, y1) = (0, 0, 0, 0)\n\n        if x0 == 0 and x1 == 0:\n            self.state.xsize, self.state.ysize = self.im.size\n        else:\n            self.state.xoff = x0\n            self.state.yoff = y0\n            self.state.xsize = x1 - x0\n            self.state.ysize = y1 - y0\n\n        if self.state.xsize <= 0 or self.state.ysize <= 0:\n            raise ValueError(\"Size cannot be negative\")\n\n        if (\n            self.state.xsize + self.state.xoff > self.im.size[0]\n            or self.state.ysize + self.state.yoff > self.im.size[1]\n        ):\n            raise ValueError(\"Tile cannot extend outside image\")\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 282,
        "n_words": 91,
        "vocab_size": 54,
        "complexity": 8,
        "nloc": 20,
        "token_counts": 184,
        "n_ast_nodes": 282,
        "n_identifiers": 15,
        "d_id": 69856,
        "documentation": {
            "docstring": "\n        Called from ImageFile to set the core output image for the codec\n\n        :param im: A core image object\n        :param extents: a 4 tuple of (x0, y0, x1, y1) defining the rectangle\n            for this tile\n        :returns: None\n        ",
            "n_words": 36,
            "vocab_size": 30,
            "n_whitespaces": 83,
            "language": "en"
        }
    },
    {
        "id": 73478,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/settings/models.py",
        "file_name": "models.py",
        "fun_name": "get_cache_attr_name",
        "commit_message": "Reformat with black",
        "code": "def get_cache_attr_name(cls):\n        \n        return \"_{}.{}\".format(cls._meta.app_label, cls._meta.model_name).lower()\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 27,
        "n_ast_nodes": 47,
        "n_identifiers": 7,
        "d_id": 16023,
        "documentation": {
            "docstring": "\n        Returns the name of the attribute that should be used to store\n        a reference to the fetched/created object on a request.\n        ",
            "n_words": 21,
            "vocab_size": 17,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 267581,
        "commit_id": "43153c58310d02223f2cb0964f4255ba1ac4ed53",
        "repo": "ansible",
        "path": "lib/ansible/playbook/block.py",
        "file_name": "block.py",
        "fun_name": "serialize",
        "commit_message": "`FieldAttribute`s as descriptors (#73908)",
        "code": "def serialize(self):\n        \n\n        data = dict()\n        for attr in self.fattributes:\n            if attr not in ('block', 'rescue', 'always'):\n                data[attr] = getattr(self, attr)\n\n        data['dep_chain'] = self.get_dep_chain()\n\n        if self._role is not None:\n            data['role'] = self._role.serialize()\n        if self._parent is not None:\n            data['parent'] = self._parent.copy(exclude_tasks=True).serialize()\n            data['parent_type'] = self._parent.__class__.__name__\n\n        return data\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 152,
        "n_words": 44,
        "vocab_size": 30,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 112,
        "n_ast_nodes": 188,
        "n_identifiers": 14,
        "d_id": 78962,
        "documentation": {
            "docstring": "\n        Override of the default serialize method, since when we're serializing\n        a task we don't want to include the attribute list of tasks.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 277507,
        "commit_id": "8401e08334d4b1f102a6ee9479738bacfee0600c",
        "repo": "keras",
        "path": "keras/layers/attention/base_dense_attention.py",
        "file_name": "base_dense_attention.py",
        "fun_name": "_apply_scores",
        "commit_message": "reduce layers line-too-long",
        "code": "def _apply_scores(self, scores, value, scores_mask=None, training=None):\n        \n        if scores_mask is not None:\n            padding_mask = tf.logical_not(scores_mask)\n            # Bias so padding positions do not contribute to attention\n            # distribution.  Note 65504. is the max float16 value.\n            if scores.dtype is tf.float16:\n                scores -= 65504.0 * tf.cast(padding_mask, dtype=scores.dtype)\n            else:\n                scores -= 1.0e9 * tf.cast(padding_mask, dtype=scores.dtype)\n        if training is None:\n            training = backend.learning_phase()\n        weights = tf.nn.softmax(scores)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 185,
        "n_words": 60,
        "vocab_size": 44,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 133,
        "n_ast_nodes": 153,
        "n_identifiers": 17,
        "d_id": 82075,
        "documentation": {
            "docstring": "Applies attention scores to the given value tensor.\n\n        To use this method in your attention layer, follow the steps:\n\n        * Use `query` tensor of shape `[batch_size, Tq]` and `key` tensor of\n          shape `[batch_size, Tv]` to calculate the attention `scores`.\n        * Pass `scores` and `value` tensors to this method. The method applies\n          `scores_mask`, calculates `attention_distribution = softmax(scores)`,\n          then returns `matmul(attention_distribution, value).\n        * Apply `query_mask` and return the result.\n\n        Args:\n          scores: Scores float tensor of shape `[batch_size, Tq, Tv]`.\n          value: Value tensor of shape `[batch_size, Tv, dim]`.\n          scores_mask: A boolean mask `Tensor` of shape `[batch_size, 1, Tv]` or\n            `[batch_size, Tq, Tv]`. If given, scores at positions where\n            `scores_mask==False` do not contribute to the result. It must\n            contain at least one `True` value in each line along the last\n            dimension.\n          training: Python boolean indicating whether the layer should behave in\n            training mode (adding dropout) or in inference mode (no dropout).\n\n        Returns:\n          Tensor of shape `[batch_size, Tq, dim]`.\n          Attention scores after masking and softmax with shape\n            `[batch_size, Tq, Tv]`.\n        ",
            "n_words": 165,
            "vocab_size": 108,
            "n_whitespaces": 361,
            "language": "en"
        }
    },
    {
        "id": 101433,
        "commit_id": "1022651eb8a7741014f5d2ec7cbfe882120dfa5f",
        "repo": "faceswap",
        "path": "tools/preview/preview.py",
        "file_name": "preview.py",
        "fun_name": "_build_sub_tabs",
        "commit_message": "Bugfix: convert - Gif Writer\n  - Fix non-launch error on Gif Writer\n  - convert plugins - linting\n  - convert/fs_media/preview/queue_manager - typing\n  - Change convert items from dict to Dataclass",
        "code": "def _build_sub_tabs(self) -> None:\n        \n        for section, plugins in self.config_tools.plugins_dict.items():\n            for plugin in plugins:\n                config_key = \".\".join((section, plugin))\n                config_dict = self.config_tools.config_dicts[config_key]\n                tab = ConfigFrame(self, config_key, config_dict)\n                self._tabs[section][plugin] = tab\n                text = plugin.replace(\"_\", \" \").title()\n                cast(ttk.Notebook, self._tabs[section][\"tab\"]).add(tab, text=text)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 151,
        "n_words": 36,
        "vocab_size": 29,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 110,
        "n_ast_nodes": 175,
        "n_identifiers": 22,
        "d_id": 20846,
        "documentation": {
            "docstring": " Build the notebook sub tabs for each convert section's plugin. ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 84150,
        "commit_id": "a142fbff85302c5e3acb2e204eca2e9c75dbc74b",
        "repo": "zulip",
        "path": "zerver/tests/test_upload.py",
        "file_name": "test_upload.py",
        "fun_name": "test_realm_quota",
        "commit_message": "tests: Refactor away result.json() calls with helpers.\n\nSigned-off-by: Zixuan James Li <p359101898@gmail.com>",
        "code": "def test_realm_quota(self) -> None:\n        \n        self.login(\"hamlet\")\n\n        d1 = StringIO(\"zulip!\")\n        d1.name = \"dummy_1.txt\"\n        result = self.client_post(\"/json/user_uploads\", {\"file\": d1})\n        response_dict = self.assert_json_success(result)\n        d1_path_id = re.sub(\"/user_uploads/\", \"\", response_dict[\"uri\"])\n        d1_attachment = Attachment.objects.get(path_id=d1_path_id)\n\n        realm = get_realm(\"zulip\")\n        realm.upload_quota_gb = 1\n        realm.save(update_fields=[\"upload_quota_gb\"])\n\n        # The size of StringIO(\"zulip!\") is 6 bytes. Setting the size of\n        # d1_attachment to realm.upload_quota_bytes() - 11 should allow\n        # us to upload only one more attachment.\n        quota = realm.upload_quota_bytes()\n        assert quota is not None\n        d1_attachment.size = quota - 11\n        d1_attachment.save(update_fields=[\"size\"])\n\n        d2 = StringIO(\"zulip!\")\n        d2.name = \"dummy_2.txt\"\n        result = self.client_post(\"/json/user_uploads\", {\"file\": d2})\n        self.assert_json_success(result)\n\n        d3 = StringIO(\"zulip!\")\n        d3.name = \"dummy_3.txt\"\n        result = self.client_post(\"/json/user_uploads\", {\"file\": d3})\n        self.assert_json_error(result, \"Upload would exceed your organization's upload quota.\")\n\n        realm.upload_quota_gb = None\n        realm.save(update_fields=[\"upload_quota_gb\"])\n        result = self.client_post(\"/json/user_uploads\", {\"file\": d3})\n        self.assert_json_success(result)\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 327,
        "n_words": 117,
        "vocab_size": 69,
        "complexity": 1,
        "nloc": 30,
        "token_counts": 223,
        "n_ast_nodes": 402,
        "n_identifiers": 29,
        "d_id": 17789,
        "documentation": {
            "docstring": "\n        Realm quota for uploading should not be exceeded.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 244047,
        "commit_id": "cac356380d505bf15587f07c0529218cc36b9652",
        "repo": "mmdetection",
        "path": "mmdet/models/detectors/maskformer.py",
        "file_name": "maskformer.py",
        "fun_name": "forward_dummy",
        "commit_message": "[Feature] Add Maskformer to mmdet (#7212)\n\n* first commit\r\n\r\n* add README\r\n\r\n* move model description from config to readme\r\n\r\nadd description for binary_input\r\n\r\nadd description for dice loss\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nremove compatibility of pretrain in maskformer\r\n\r\n* update comments in maskformer_head\r\n\r\n* update docs format",
        "code": "def forward_dummy(self, img, img_metas):\n        \n        super(SingleStageDetector, self).forward_train(img, img_metas)\n        x = self.extract_feat(img)\n        outs = self.panoptic_head(x, img_metas)\n        return outs\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 51,
        "n_words": 16,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 67,
        "n_identifiers": 11,
        "d_id": 70214,
        "documentation": {
            "docstring": "Used for computing network flops. See\n        `mmdetection/tools/analysis_tools/get_flops.py`\n\n        Args:\n            img (Tensor): of shape (N, C, H, W) encoding input images.\n                Typically these should be mean centered and std scaled.\n            img_metas (list[Dict]): list of image info dict where each dict\n                has: 'img_shape', 'scale_factor', 'flip', and may also contain\n                'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.\n                For details on the values of these keys see\n                `mmdet/datasets/pipelines/formatting.py:Collect`.\n        ",
            "n_words": 61,
            "vocab_size": 55,
            "n_whitespaces": 179,
            "language": "en"
        }
    },
    {
        "id": 101758,
        "commit_id": "c79175cbde5600bebd65785f3821fc74b3a80cbe",
        "repo": "faceswap",
        "path": "tools/alignments/media.py",
        "file_name": "media.py",
        "fun_name": "sorted_items",
        "commit_message": "Alignments Tool updates\n  - Copy info back to alignments file from faces",
        "code": "def sorted_items(self) -> List[Tuple[str, \"PNGHeaderDict\"]]:\n        \n        items = sorted(self.process_folder(), key=itemgetter(0))\n        logger.trace(items)  # type: ignore\n        return items\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 44,
        "n_words": 15,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 41,
        "n_ast_nodes": 69,
        "n_identifiers": 12,
        "d_id": 21162,
        "documentation": {
            "docstring": " Return the items sorted by the saved file name.\n\n        Returns\n        --------\n        list\n            List of `dict` objects for each face found, sorted by the face's current filename\n        ",
            "n_words": 26,
            "vocab_size": 22,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 22543,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "XORcipher/XOR_cipher.py",
        "file_name": "XOR_cipher.py",
        "fun_name": "encrypt_file",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def encrypt_file(self, file, key=0):\n        \n\n        # precondition\n        assert isinstance(file, str) and isinstance(key, int)\n\n        try:\n            with open(file, \"r\") as fin:\n                with open(\"encrypt.out\", \"w+\") as fout:\n                    # actual encrypt-process\n                    for line in fin:\n                        fout.write(self.encrypt_string(line, key))\n\n        except:\n            return False\n\n        return True\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 177,
        "n_words": 37,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 72,
        "n_ast_nodes": 125,
        "n_identifiers": 13,
        "d_id": 4359,
        "documentation": {
            "docstring": "\n        input: filename (str) and a key (int)\n        output: returns true if encrypt process was\n        successful otherwise false\n        if key not passed the method uses the key by the constructor.\n        otherwise key = 1\n        ",
            "n_words": 33,
            "vocab_size": 26,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 206861,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/views/generic/dates.py",
        "file_name": "dates.py",
        "fun_name": "_get_next_prev",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get_next_prev(generic_view, date, is_previous, period):\n    \n    date_field = generic_view.get_date_field()\n    allow_empty = generic_view.get_allow_empty()\n    allow_future = generic_view.get_allow_future()\n\n    get_current = getattr(generic_view, \"_get_current_%s\" % period)\n    get_next = getattr(generic_view, \"_get_next_%s\" % period)\n\n    # Bounds of the current interval\n    start, end = get_current(date), get_next(date)\n\n    # If allow_empty is True, the naive result will be valid\n    if allow_empty:\n        if is_previous:\n            result = get_current(start - datetime.timedelta(days=1))\n        else:\n            result = end\n\n        if allow_future or result <= timezone_today():\n            return result\n        else:\n            return None\n\n    # Otherwise, we'll need to go to the database to look for an object\n    # whose date_field is at least (greater than/less than) the given\n    # naive result\n    else:\n        # Construct a lookup and an ordering depending on whether we're doing\n        # a previous date or a next date lookup.\n        if is_previous:\n            lookup = {\"%s__lt\" % date_field: generic_view._make_date_lookup_arg(start)}\n            ordering = \"-%s\" % date_field\n        else:\n            lookup = {\"%s__gte\" % date_field: generic_view._make_date_lookup_arg(end)}\n            ordering = date_field\n\n        # Filter out objects in the future if appropriate.\n        if not allow_future:\n            # Fortunately, to match the implementation of allow_future,\n            # we need __lte, which doesn't conflict with __lt above.\n            if generic_view.uses_datetime_field:\n                now = timezone.now()\n            else:\n                now = timezone_today()\n            lookup[\"%s__lte\" % date_field] = now\n\n        qs = generic_view.get_queryset().filter(**lookup).order_by(ordering)\n\n        # Snag the first object from the queryset; if it doesn't exist that\n        # means there's no next/previous link available.\n        try:\n            result = getattr(qs[0], date_field)\n        except IndexError:\n            return None\n\n        # Convert datetimes to dates in the current time zone.\n        if generic_view.uses_datetime_field:\n            if settings.USE_TZ:\n                result = timezone.localtime(result)\n            result = result.date()\n\n        # Return the first day of the period.\n        return get_current(result)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 658,
        "n_words": 251,
        "vocab_size": 144,
        "complexity": 11,
        "nloc": 39,
        "token_counts": 247,
        "n_ast_nodes": 429,
        "n_identifiers": 35,
        "d_id": 51762,
        "documentation": {
            "docstring": "\n    Get the next or the previous valid date. The idea is to allow links on\n    month/day views to never be 404s by never providing a date that'll be\n    invalid for the given view.\n\n    This is a bit complicated since it handles different intervals of time,\n    hence the coupling to generic_view.\n\n    However in essence the logic comes down to:\n\n        * If allow_empty and allow_future are both true, this is easy: just\n          return the naive result (just the next/previous day/week/month,\n          regardless of object existence.)\n\n        * If allow_empty is true, allow_future is false, and the naive result\n          isn't in the future, then return it; otherwise return None.\n\n        * If allow_empty is false and allow_future is true, return the next\n          date *that contains a valid object*, even if it's in the future. If\n          there are no next objects, return None.\n\n        * If allow_empty is false and allow_future is false, return the next\n          date that contains a valid object. If that date is in the future, or\n          if there are no next objects, return None.\n    ",
            "n_words": 170,
            "vocab_size": 88,
            "n_whitespaces": 283,
            "language": "en"
        }
    },
    {
        "id": 22042,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/requests/adapters.py",
        "file_name": "adapters.py",
        "fun_name": "request_url",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def request_url(self, request, proxies):\n        \n        proxy = select_proxy(request.url, proxies)\n        scheme = urlparse(request.url).scheme\n\n        is_proxied_http_request = proxy and scheme != \"https\"\n        using_socks_proxy = False\n        if proxy:\n            proxy_scheme = urlparse(proxy).scheme.lower()\n            using_socks_proxy = proxy_scheme.startswith(\"socks\")\n\n        url = request.path_url\n        if is_proxied_http_request and not using_socks_proxy:\n            url = urldefragauth(request.url)\n\n        return url\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 138,
        "n_words": 42,
        "vocab_size": 27,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 84,
        "n_ast_nodes": 140,
        "n_identifiers": 16,
        "d_id": 4131,
        "documentation": {
            "docstring": "Obtain the url to use when making the final request.\n\n        If the message is being sent through a HTTP proxy, the full URL has to\n        be used. Otherwise, we should only use the path portion of the URL.\n\n        This should not be called from user code, and is only exposed for use\n        when subclassing the\n        :class:`HTTPAdapter <requests.adapters.HTTPAdapter>`.\n\n        :param request: The :class:`PreparedRequest <PreparedRequest>` being sent.\n        :param proxies: A dictionary of schemes or schemes and hosts to proxy URLs.\n        :rtype: str\n        ",
            "n_words": 79,
            "vocab_size": 59,
            "n_whitespaces": 142,
            "language": "en"
        }
    },
    {
        "id": 269607,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "cast_to_floatx",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def cast_to_floatx(x):\n    \n    if isinstance(x, (tf.Tensor, tf.Variable, tf.SparseTensor)):\n        return tf.cast(x, dtype=floatx())\n    return np.asarray(x, dtype=floatx())\n\n\n@keras_export(\"keras.backend.get_uid\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.backend.get_uid\")",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 29,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 52,
        "n_ast_nodes": 92,
        "n_identifiers": 13,
        "d_id": 80227,
        "documentation": {
            "docstring": "Cast a Numpy array to the default Keras float type.\n\n    Args:\n        x: Numpy array or TensorFlow tensor.\n\n    Returns:\n        The same array (Numpy array if `x` was a Numpy array, or TensorFlow tensor\n        if `x` was a tensor), cast to its new type.\n\n    Example:\n\n    >>> tf.keras.backend.floatx()\n    'float32'\n    >>> arr = np.array([1.0, 2.0], dtype='float64')\n    >>> arr.dtype\n    dtype('float64')\n    >>> new_arr = cast_to_floatx(arr)\n    >>> new_arr\n    array([1.,  2.], dtype=float32)\n    >>> new_arr.dtype\n    dtype('float32')\n\n    ",
            "n_words": 67,
            "vocab_size": 46,
            "n_whitespaces": 131,
            "language": "en"
        }
    },
    {
        "id": 115746,
        "commit_id": "b9ee4a5930e20a09350a3e0774283ba658a42da7",
        "repo": "mindsdb",
        "path": "mindsdb/api/mysql/mysql_proxy/datahub/datanodes/mindsdb_datanode.py",
        "file_name": "mindsdb_datanode.py",
        "fun_name": "query",
        "commit_message": "del code",
        "code": "def query(self, table, columns=None, where=None, where_data=None, order_by=None, group_by=None, integration_name=None, integration_type=None):\n        \n        if table == 'predictors':\n            return self._select_predictors()\n        if table == 'datasources':\n            return self._select_datasources()\n\n        new_where = {}\n        if where_data is None:\n            for key, value in where_data.items():\n                if isinstance(value, dict) is False or len(value.keys()) != 1 or list(value.keys())[0] != '$eq':\n                    # TODO value should be just string or number\n                    raise Exception()\n                new_where[key] = value['$eq']\n\n            if len(new_where) == 0:\n                return []\n\n            where_data = [new_where]\n\n        if isinstance(where_data, dict):\n            where_data = [where_data]\n\n        result = self.handler.predict(table, where_data)\n        return result\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 287,
        "n_words": 82,
        "vocab_size": 59,
        "complexity": 10,
        "nloc": 18,
        "token_counts": 169,
        "n_ast_nodes": 269,
        "n_identifiers": 25,
        "d_id": 25538,
        "documentation": {
            "docstring": " NOTE WHERE statements can be just $eq joined with 'and'\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 256915,
        "commit_id": "11cf94a9652a577732941f27ad59eb7c8bc5063e",
        "repo": "haystack",
        "path": "test/test_pipeline_yaml.py",
        "file_name": "test_pipeline_yaml.py",
        "fun_name": "mock_json_schema",
        "commit_message": "Pipeline's YAML: syntax validation (#2226)\n\n* Add BasePipeline.validate_config, BasePipeline.validate_yaml, and some new custom exception classes\r\n\r\n* Make error composition work properly\r\n\r\n* Clarify typing\r\n\r\n* Help mypy a bit more\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Enable autogenerated docs for Milvus1 and 2 separately\r\n\r\n* Revert \"Enable autogenerated docs for Milvus1 and 2 separately\"\r\n\r\nThis reverts commit 282be4a78a6e95862a9b4c924fc3dea5ca71e28d.\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Re-enable 'additionalProperties: False'\r\n\r\n* Add pipeline.type to JSON Schema, was somehow forgotten\r\n\r\n* Disable additionalProperties on the pipeline properties too\r\n\r\n* Fix json-schemas for 1.1.0 and 1.2.0 (should not do it again in the future)\r\n\r\n* Cal super in PipelineValidationError\r\n\r\n* Improve _read_pipeline_config_from_yaml's error handling\r\n\r\n* Fix generate_json_schema.py to include document stores\r\n\r\n* Fix json schemas (retro-fix 1.1.0 again)\r\n\r\n* Improve custom errors printing, add link to docs\r\n\r\n* Add function in BaseComponent to list its subclasses in a module\r\n\r\n* Make some document stores base classes abstract\r\n\r\n* Add marker 'integration' in pytest flags\r\n\r\n* Slighly improve validation of pipelines at load\r\n\r\n* Adding tests for YAML loading and validation\r\n\r\n* Make custom_query Optional for validation issues\r\n\r\n* Fix bug in _read_pipeline_config_from_yaml\r\n\r\n* Improve error handling in BasePipeline and Pipeline and add DAG check\r\n\r\n* Move json schema generation into haystack/nodes/_json_schema.py (useful for tests)\r\n\r\n* Simplify errors slightly\r\n\r\n* Add some YAML validation tests\r\n\r\n* Remove load_from_config from BasePipeline, it was never used anyway\r\n\r\n* Improve tests\r\n\r\n* Include json-schemas in package\r\n\r\n* Fix conftest imports\r\n\r\n* Make BasePipeline abstract\r\n\r\n* Improve mocking by making the test independent from the YAML version\r\n\r\n* Add exportable_to_yaml decorator to forget about set_config on mock nodes\r\n\r\n* Fix mypy errors\r\n\r\n* Comment out one monkeypatch\r\n\r\n* Fix typing again\r\n\r\n* Improve error message for validation\r\n\r\n* Add required properties to pipelines\r\n\r\n* Fix YAML version for REST API YAMLs to 1.2.0\r\n\r\n* Fix load_from_yaml call in load_from_deepset_cloud\r\n\r\n* fix HaystackError.__getattr__\r\n\r\n* Add super().__init__()in most nodes and docstore, comment set_config\r\n\r\n* Remove type from REST API pipelines\r\n\r\n* Remove useless init from doc2answers\r\n\r\n* Call super in Seq3SeqGenerator\r\n\r\n* Typo in deepsetcloud.py\r\n\r\n* Fix rest api indexing error mismatch and mock version of JSON schema in all tests\r\n\r\n* Working on pipeline tests\r\n\r\n* Improve errors printing slightly\r\n\r\n* Add back test_pipeline.yaml\r\n\r\n* _json_schema.py supports different versions with identical schemas\r\n\r\n* Add type to 0.7 schema for backwards compatibility\r\n\r\n* Fix small bug in _json_schema.py\r\n\r\n* Try alternative to generate json schemas on the CI\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Make linux CI match autoformat CI\r\n\r\n* Fix super-init-not-called\r\n\r\n* Accidentally committed file\r\n\r\n* Update Documentation & Code Style\r\n\r\n* fix test_summarizer_translation.py's import\r\n\r\n* Mock YAML in a few suites, split and simplify test_pipeline_debug_and_validation.py::test_invalid_run_args\r\n\r\n* Fix json schema for ray tests too\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Reintroduce validation\r\n\r\n* Usa unstable version in tests and rest api\r\n\r\n* Make unstable support the latest versions\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Remove needless fixture\r\n\r\n* Make type in pipeline optional in the strings validation\r\n\r\n* Fix schemas\r\n\r\n* Fix string validation for pipeline type\r\n\r\n* Improve validate_config_strings\r\n\r\n* Remove type from test p[ipelines\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix test_pipeline\r\n\r\n* Removing more type from pipelines\r\n\r\n* Temporary CI patc\r\n\r\n* Fix issue with exportable_to_yaml never invoking the wrapped init\r\n\r\n* rm stray file\r\n\r\n* pipeline tests are green again\r\n\r\n* Linux CI now needs .[all] to generate the schema\r\n\r\n* Bugfixes, pipeline tests seems to be green\r\n\r\n* Typo in version after merge\r\n\r\n* Implement missing methods in Weaviate\r\n\r\n* Trying to avoid FAISS tests from running in the Milvus1 test suite\r\n\r\n* Fix some stray test paths and faiss index dumping\r\n\r\n* Fix pytest markers list\r\n\r\n* Temporarily disable cache to be able to see tests failures\r\n\r\n* Fix pyproject.toml syntax\r\n\r\n* Use only tmp_path\r\n\r\n* Fix preprocessor signature after merge\r\n\r\n* Fix faiss bug\r\n\r\n* Fix Ray test\r\n\r\n* Fix documentation issue by removing quotes from faiss type\r\n\r\n* Update Documentation & Code Style\r\n\r\n* use document properly in preprocessor tests\r\n\r\n* Update Documentation & Code Style\r\n\r\n* make preprocessor capable of handling documents\r\n\r\n* import document\r\n\r\n* Revert support for documents in preprocessor, do later\r\n\r\n* Fix bug in _json_schema.py that was breaking validation\r\n\r\n* re-enable cache\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Simplify calling _json_schema.py from the CI\r\n\r\n* Remove redundant ABC inheritance\r\n\r\n* Ensure exportable_to_yaml works only on implementations\r\n\r\n* Rename subclass to class_ in Meta\r\n\r\n* Make run() and get_config() abstract in BasePipeline\r\n\r\n* Revert unintended change in preprocessor\r\n\r\n* Move outgoing_edges_input_node check inside try block\r\n\r\n* Rename VALID_CODE_GEN_INPUT_REGEX into VALID_INPUT_REGEX\r\n\r\n* Add check for a RecursionError on validate_config_strings\r\n\r\n* Address usages of _pipeline_config in data silo and elasticsearch\r\n\r\n* Rename _pipeline_config into _init_parameters\r\n\r\n* Fix pytest marker and remove unused imports\r\n\r\n* Remove most redundant ABCs\r\n\r\n* Rename _init_parameters into _component_configuration\r\n\r\n* Remove set_config and type from _component_configuration's dict\r\n\r\n* Remove last instances of set_config and replace with super().__init__()\r\n\r\n* Implement __init_subclass__ approach\r\n\r\n* Simplify checks on the existence of _component_configuration\r\n\r\n* Fix faiss issue\r\n\r\n* Dynamic generation of node schemas & weed out old schemas\r\n\r\n* Add debatable test\r\n\r\n* Add docstring to debatable test\r\n\r\n* Positive diff between schemas implemented\r\n\r\n* Improve diff printing\r\n\r\n* Rename REST API YAML files to trigger IDE validation\r\n\r\n* Fix typing issues\r\n\r\n* Fix more typing\r\n\r\n* Typo in YAML filename\r\n\r\n* Remove needless type:ignore\r\n\r\n* Add tests\r\n\r\n* Fix tests & validation feedback for accessory classes in custom nodes\r\n\r\n* Refactor RAGeneratorType out\r\n\r\n* Fix broken import in conftest\r\n\r\n* Improve source error handling\r\n\r\n* Remove unused import in test_eval.py breaking tests\r\n\r\n* Fix changed error message in tests matches too\r\n\r\n* Normalize generate_openapi_specs.py and generate_json_schema.py in the actions\r\n\r\n* Fix path to generate_openapi_specs.py in autoformat.yml\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Add test for FAISSDocumentStore-like situations (superclass with init params)\r\n\r\n* Update Documentation & Code Style\r\n\r\n* Fix indentation\r\n\r\n* Remove commented set_config\r\n\r\n* Store model_name_or_path in FARMReader to use in DistillationDataSilo\r\n\r\n* Rename _component_configuration into _component_config\r\n\r\n* Update Documentation & Code Style\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def mock_json_schema(request, monkeypatch, tmp_path):\n    \n    # Do not patch integration tests\n    if \"integration\" in request.keywords:\n        return\n\n    # Mock the subclasses list to make it very small, containing only mock nodes\n    monkeypatch.setattr(\n        haystack.nodes._json_schema,\n        \"find_subclasses_in_modules\",\n        lambda *a, **k: [(conftest, MockDocumentStore), (conftest, MockReader), (conftest, MockRetriever)],\n    )\n    # Point the JSON schema path to tmp_path\n    monkeypatch.setattr(haystack.pipelines.config, \"JSON_SCHEMAS_PATH\", tmp_path)\n\n    # Generate mock schema in tmp_path\n    filename = f\"haystack-pipeline-unstable.schema.json\"\n    test_schema = _json_schema.get_json_schema(filename=filename, compatible_versions=[\"unstable\"])\n\n    with open(tmp_path / filename, \"w\") as schema_file:\n        json.dump(test_schema, schema_file, indent=4)\n\n\n#\n# Integration\n#\n\n\n@pytest.mark.integration\n@pytest.mark.elasticsearch",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.integration\n@pytest.mark.elasticsearch",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 148,
        "n_words": 82,
        "vocab_size": 68,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 116,
        "n_ast_nodes": 209,
        "n_identifiers": 30,
        "d_id": 74961,
        "documentation": {
            "docstring": "\n    JSON schema with the unstable version and only mocked nodes.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 269264,
        "commit_id": "e70d21c144503f560d8659fec0e08267e686a431",
        "repo": "keras",
        "path": "keras/saving/experimental/saving_lib.py",
        "file_name": "saving_lib.py",
        "fun_name": "_get_object_config",
        "commit_message": "Keras saving: A prototype of config-based (idempotent) saving and loading. This shows an example of custom Model, Layer, Optimizer, and Loss, and adds test to confirm that the basic aforementioned elements work across this new saving and loading scheme.\n\nPiperOrigin-RevId: 447193044",
        "code": "def _get_object_config(obj):\n  \n  if isinstance(obj, str):\n    # Use the content of the string as the config for string.\n    return obj\n  elif isinstance(obj, types.FunctionType):\n    # Keep track of the function's module and name in a dict as the config.\n    return {\n        'module': obj.__module__,\n        'function_name': obj.__name__,\n    }\n  if not hasattr(obj, 'get_config'):\n    raise TypeError(f'Unable to recognize the config of {obj}.')\n  return obj.get_config()\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 95,
        "n_words": 58,
        "vocab_size": 44,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 62,
        "n_ast_nodes": 110,
        "n_identifiers": 11,
        "d_id": 79990,
        "documentation": {
            "docstring": "Return the object's config depending on string, function, or others.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 114374,
        "commit_id": "0fd3b436c38f38bcae6fed9e14dc4d2a12e90793",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/libs/storage_handler.py",
        "file_name": "storage_handler.py",
        "fun_name": "_get",
        "commit_message": "fix tests and reformat",
        "code": "def _get(self, serialized_key):\n        cur = self.connection.cursor()\n        # should always be a single match, hence the [0]\n        return list(cur.execute(f))[0][0]\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 38,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 8,
        "d_id": 25171,
        "documentation": {
            "docstring": "select value from store where key='{serialized_key}'",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 5,
            "language": "en"
        }
    },
    {
        "id": 24496,
        "commit_id": "ddaa2c2552e19635cd6cdf38619f1f176c358f89",
        "repo": "PaddleOCR",
        "path": "ppstructure/table/table_master_match.py",
        "file_name": "table_master_match.py",
        "fun_name": "deal_duplicate_bb",
        "commit_message": "add SLANet",
        "code": "def deal_duplicate_bb(thead_part):\n    \n    # 1. find out <td></td> in <thead></thead>.\n    td_pattern = \"<td rowspan=\\\"(\\d)+\\\" colspan=\\\"(\\d)+\\\">(.+?)</td>|\" \\\n                 \"<td colspan=\\\"(\\d)+\\\" rowspan=\\\"(\\d)+\\\">(.+?)</td>|\" \\\n                 \"<td rowspan=\\\"(\\d)+\\\">(.+?)</td>|\" \\\n                 \"<td colspan=\\\"(\\d)+\\\">(.+?)</td>|\" \\\n                 \"<td>(.*?)</td>\"\n    td_iter = re.finditer(td_pattern, thead_part)\n    td_list = [t.group() for t in td_iter]\n\n    # 2. is multiply <b></b> in <td></td> or not?\n    new_td_list = []\n    for td_item in td_list:\n        if td_item.count('<b>') > 1 or td_item.count('</b>') > 1:\n            # multiply <b></b> in <td></td> case.\n            # 1. remove all <b></b>\n            td_item = td_item.replace('<b>', '').replace('</b>', '')\n            # 2. replace <tb> -> <tb><b>, </tb> -> </b></tb>.\n            td_item = td_item.replace('<td>', '<td><b>').replace('</td>',\n                                                                 '</b></td>')\n            new_td_list.append(td_item)\n        else:\n            new_td_list.append(td_item)\n\n    # 3. replace original thead part.\n    for td_item, new_td_item in zip(td_list, new_td_list):\n        thead_part = thead_part.replace(td_item, new_td_item)\n    return thead_part\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 371,
        "n_words": 112,
        "vocab_size": 71,
        "complexity": 6,
        "nloc": 20,
        "token_counts": 140,
        "n_ast_nodes": 259,
        "n_identifiers": 16,
        "d_id": 4744,
        "documentation": {
            "docstring": "\n    Deal duplicate <b> or </b> after replace.\n    Keep one <b></b> in a <td></td> token.\n    :param thead_part:\n    :return:\n    ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 135585,
        "commit_id": "9fab504fe776f96fecf85e12ea006264cbe92f4a",
        "repo": "ray",
        "path": "python/ray/data/tests/test_dataset_tfrecords.py",
        "file_name": "test_dataset_tfrecords.py",
        "fun_name": "test_readback_tfrecords",
        "commit_message": "[Datasets] Add writer for TFRecords. (#29448)\n\nThis PR enables users to write TFRecords from datasets.\r\n\r\nIn particular, the master branch already includes an API for reading TFRecords from datasets. Users have requested the ability to write these datasets back to TFRecords.",
        "code": "def test_readback_tfrecords(ray_start_regular_shared, tmp_path):\n    \n\n    # The dataset we will write to a .tfrecords file.\n    ds = ray.data.from_items(\n        [\n            # Row one.\n            {\n                \"int_item\": 1,\n                \"int_list\": [2, 2, 3],\n                \"float_item\": 1.0,\n                \"float_list\": [2.0, 3.0, 4.0],\n                \"bytes_item\": b\"abc\",\n                \"bytes_list\": [b\"abc\", b\"1234\"],\n            },\n            # Row two.\n            {\n                \"int_item\": 2,\n                \"int_list\": [3, 3, 4],\n                \"float_item\": 2.0,\n                \"float_list\": [2.0, 2.0, 3.0],\n                \"bytes_item\": b\"def\",\n                \"bytes_list\": [b\"def\", b\"1234\"],\n            },\n        ]\n    )\n\n    # Write the TFRecords.\n    ds.write_tfrecords(tmp_path)\n\n    # Read the TFRecords.\n    readback_ds = ray.data.read_tfrecords(tmp_path)\n    assert ds.take() == readback_ds.take()\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 366,
        "n_words": 79,
        "vocab_size": 59,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 155,
        "n_ast_nodes": 226,
        "n_identifiers": 11,
        "d_id": 30664,
        "documentation": {
            "docstring": "\n    Test reading back TFRecords written using datasets.\n    The dataset we read back should be the same that we wrote.\n    ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 92186,
        "commit_id": "8201e74ec3d81e89354905c946e62436f0247602",
        "repo": "sentry",
        "path": "tests/sentry/integrations/vercel/test_uninstall.py",
        "file_name": "test_uninstall.py",
        "fun_name": "test_uninstall_from_sentry",
        "commit_message": "ref(integrations): Update Vercel endpoints  (#36150)\n\nThis PR updates the endpoints we reach to in the Vercel integration. It seems to work just fine without changes as the payloads returned from vercel haven't updated, but we'll need to specify API Scopes so they don't receive 403s.\r\n\r\nThis also refactored the pagination code to loop 100 at a time, indefinitely\r\n\r\nI had previously tried to consolidate the project webhooks in this PR, but I'll be doing that separately.",
        "code": "def test_uninstall_from_sentry(self):\n        \n        self.login_as(self.user)\n        with self.tasks():\n            config_id = \"my_config_id\"\n            responses.add(\n                responses.DELETE,\n                f\"{VercelClient.base_url}{VercelClient.UNINSTALL % config_id}\",\n                json={},\n            )\n            path = (\n                f\"/api/0/organizations/{self.organization.slug}/integrations/{self.integration.id}/\"\n            )\n            response = self.client.delete(path, format=\"json\")\n            assert response.status_code == 204\n\n        assert (\n            len(\n                OrganizationIntegration.objects.filter(\n                    integration=self.integration,\n                    status=ObjectStatus.VISIBLE,\n                )\n            )\n            == 1\n        )\n\n        response = self.client.delete(\n            path=self.url,\n            data=PRIMARY_UNINSTALL_RESPONSE,\n            content_type=\"application/json\",\n        )\n        assert response.status_code == 204\n\n        integration = Integration.objects.get(id=self.integration.id)\n        assert integration.metadata == {\n            \"access_token\": \"my_access_token2\",\n            \"installation_id\": \"my_config_id2\",\n            \"installation_type\": \"team\",\n            \"webhook_id\": \"my_webhook_id2\",\n            \"configurations\": {\n                \"my_config_id2\": {\n                    \"access_token\": \"my_access_token2\",\n                    \"webhook_id\": \"my_webhook_id2\",\n                    \"organization_id\": self.second_org.id,\n                }\n            },\n        }\n\n        with self.tasks():\n            config_id = \"my_config_id2\"\n            responses.add(\n                responses.DELETE,\n                f\"{VercelClient.base_url}{VercelClient.UNINSTALL % config_id}\",\n                json={},\n            )\n            path = (\n                f\"/api/0/organizations/{self.second_org.slug}/integrations/{self.integration.id}/\"\n            )\n            response = self.client.delete(path, format=\"json\")\n            assert response.status_code == 204\n\n        assert (\n            len(\n                OrganizationIntegration.objects.filter(\n                    integration=self.integration,\n                    status=ObjectStatus.VISIBLE,\n                )\n            )\n            == 0\n        )\n\n        response = self.client.delete(\n            path=self.url,\n            data=NONPRIMARY_UNINSTALL_RESPONSE,\n            content_type=\"application/json\",\n        )\n        assert response.status_code == 204\n        assert not Integration.objects.filter(id=self.integration.id).exists()\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 949,
        "n_words": 128,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 71,
        "token_counts": 316,
        "n_ast_nodes": 596,
        "n_identifiers": 40,
        "d_id": 18884,
        "documentation": {
            "docstring": "\n        Test flows of uninstalling from sentry first to make sure\n        that uninstall webhook is valid even if the OrganizationIntegration\n        was deleted prior.\n          1. Uninstall the primary configuration\n          2. Check that integration metadata still updated\n          3. Uninstall remaining configuration\n          4. Check that integration is removed\n        ",
            "n_words": 44,
            "vocab_size": 36,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 115631,
        "commit_id": "f1fb699f88f8644d46afa9a2786a934510b05b79",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/scylla_handler/scylla_handler.py",
        "file_name": "scylla_handler.py",
        "fun_name": "check_connection",
        "commit_message": "Impl handler",
        "code": "def check_connection(self) -> StatusResponse:\n        \n        response = StatusResponse(False)\n\n        try:\n            session = self.connect()\n            # TODO: change the healthcheck\n            session.execute('SELECT release_version FROM system.local').one()\n            response.success = True\n        except Exception as e:\n            log.error(f'Error connecting to Scylla {self.connection_args[\"keyspace\"]}, {e}!')\n            response.error_message = e\n\n        if response.success is False and self.is_connected is True:\n            self.is_connected = False\n\n        return response\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 168,
        "n_words": 49,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 75,
        "n_ast_nodes": 147,
        "n_identifiers": 16,
        "d_id": 25506,
        "documentation": {
            "docstring": "\n        Check the connection of the Scylla database\n        :return: success status and error message if error occurs\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 45487,
        "commit_id": "69f6f9e01b6df76c3c8fa266d460324163957887",
        "repo": "airflow",
        "path": "airflow/migrations/versions/a66efa278eea_add_precision_to_execution_date_in_mysql.py",
        "file_name": "a66efa278eea_add_precision_to_execution_date_in_mysql.py",
        "fun_name": "downgrade",
        "commit_message": "Autogenerate migration reference doc (#21601)\n\n* document airflow version in each alembic migration module and use this to autogen the doc\r\n* update each migration module to have the same description used in migration ref (so it can be used in autogen)",
        "code": "def downgrade():\n    \n    conn = op.get_bind()\n    if conn.dialect.name == \"mysql\":\n        op.alter_column(\n            table_name=TABLE_NAME, column_name=COLUMN_NAME, type_=mysql.TIMESTAMP(), nullable=False\n        )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 49,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 45,
        "n_ast_nodes": 75,
        "n_identifiers": 15,
        "d_id": 8614,
        "documentation": {
            "docstring": "Unapply Add Precision to ``execution_date`` in ``RenderedTaskInstanceFields`` table",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 267602,
        "commit_id": "5797d06aecb1ff620483f6c3ff4bd6d30356332f",
        "repo": "ansible",
        "path": "lib/ansible/plugins/action/pause.py",
        "file_name": "pause.py",
        "fun_name": "setraw",
        "commit_message": "Use customized setraw to prevent output issues (#78060)",
        "code": "def setraw(fd, when=termios.TCSAFLUSH):\n    \n    mode = termios.tcgetattr(fd)\n    mode[tty.IFLAG] = mode[tty.IFLAG] & ~(termios.BRKINT | termios.ICRNL | termios.INPCK | termios.ISTRIP | termios.IXON)\n    # mode[tty.OFLAG] = mode[tty.OFLAG] & ~(termios.OPOST)\n    mode[tty.CFLAG] = mode[tty.CFLAG] & ~(termios.CSIZE | termios.PARENB)\n    mode[tty.CFLAG] = mode[tty.CFLAG] | termios.CS8\n    mode[tty.LFLAG] = mode[tty.LFLAG] & ~(termios.ECHO | termios.ICANON | termios.IEXTEN | termios.ISIG)\n    mode[tty.CC][termios.VMIN] = 1\n    mode[tty.CC][termios.VTIME] = 0\n    termios.tcsetattr(fd, when, mode)\n\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 87,
        "n_words": 57,
        "vocab_size": 33,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 165,
        "n_ast_nodes": 250,
        "n_identifiers": 27,
        "d_id": 78971,
        "documentation": {
            "docstring": "Put terminal into a raw mode.\n\n    Copied from ``tty`` from CPython 3.11.0, and modified to not remove OPOST from OFLAG\n\n    OPOST is kept to prevent an issue with multi line prompts from being corrupted now that display\n    is proxied via the queue from forks. The problem is a race condition, in that we proxy the display\n    over the fork, but before it can be displayed, this plugin will have continued executing, potentially\n    setting stdout and stdin to raw which remove output post processing that commonly converts NL to CRLF\n    ",
            "n_words": 89,
            "vocab_size": 70,
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            "language": "en"
        }
    },
    {
        "id": 65941,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/report/student_batch_wise_attendance/student_batch_wise_attendance.py",
        "file_name": "student_batch_wise_attendance.py",
        "fun_name": "get_student_attendance",
        "commit_message": "style: format code with black",
        "code": "def get_student_attendance(student_group, date):\n\tstudent_attendance = frappe.db.sql(\n\t\t,\n\t\t(student_group, date),\n\t\tas_dict=1,\n\t)\n\treturn student_attendance\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 6,
        "n_words": 13,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 30,
        "n_ast_nodes": 45,
        "n_identifiers": 8,
        "d_id": 14062,
        "documentation": {
            "docstring": "select count(*) as count, status from `tabStudent Attendance` where\n\t\t\t\tstudent_group= %s and date= %s and docstatus = 1 and\n\t\t\t\t(course_schedule is Null or course_schedule='') group by status",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 110587,
        "commit_id": "d8bb1a52316c38434e526412c27d9c4b01960084",
        "repo": "matplotlib",
        "path": "lib/matplotlib/tests/test_legend.py",
        "file_name": "test_legend.py",
        "fun_name": "test_legend_auto5",
        "commit_message": "ENH: rely on non-rectangular patch paths rather than bboxes for legend auto-placing (fix #9580) (#9598)\n\n* use path rather than bbox for non rectangular patches\r\n\r\n* Add tests\r\n\r\n* Add a short breadcrumb note in api_changes",
        "code": "def test_legend_auto5():\n    \n    fig, axs = plt.subplots(ncols=2, figsize=(9.6, 4.8))\n\n    leg_bboxes = []\n    for ax, loc in zip(axs.flat, (\"center\", \"best\")):\n        # An Ellipse patch at the top, a U-shaped Polygon patch at the\n        # bottom and a ring-like Wedge patch: the correct placement of\n        # the legend should be in the center.\n        for _patch in [\n                mpatches.Ellipse(\n                    xy=(0.5, 0.9), width=0.8, height=0.2, fc=\"C1\"),\n                mpatches.Polygon(np.array([\n                    [0, 1], [0, 0], [1, 0], [1, 1], [0.9, 1.0], [0.9, 0.1],\n                    [0.1, 0.1], [0.1, 1.0], [0.1, 1.0]]), fc=\"C1\"),\n                mpatches.Wedge((0.5, 0.5), 0.5, 0, 360, width=0.05, fc=\"C0\")\n                ]:\n            ax.add_patch(_patch)\n\n        ax.plot([0.1, 0.9], [0.9, 0.9], label=\"A segment\")  # sthg to label\n\n        leg = ax.legend(loc=loc)\n        fig.canvas.draw()\n        leg_bboxes.append(\n            leg.get_window_extent().transformed(ax.transAxes.inverted()))\n\n    assert_allclose(leg_bboxes[1].bounds, leg_bboxes[0].bounds)\n\n\n@image_comparison(['legend_various_labels'], remove_text=True)",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "@image_comparison(['legend_various_labels'], remove_text=True)",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 319,
        "n_words": 109,
        "vocab_size": 82,
        "complexity": 3,
        "nloc": 19,
        "token_counts": 300,
        "n_ast_nodes": 390,
        "n_identifiers": 39,
        "d_id": 24225,
        "documentation": {
            "docstring": "\n    Check that the automatic placement handle a rather complex\n    case with non rectangular patch. Related to issue #9580.\n    ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 65230,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/financial_statements.py",
        "file_name": "financial_statements.py",
        "fun_name": "sort_accounts",
        "commit_message": "style: format code with black",
        "code": "def sort_accounts(accounts, is_root=False, key=\"name\"):\n\t\n\n\tdef compare_accounts(a, b):\n\t\tif re.split(r\"\\W+\", a[key])[0].isdigit():\n\t\t\t# if chart of accounts is numbered, then sort by number\n\t\t\treturn int(a[key] > b[key]) - int(a[key] < b[key])\n\t\telif is_root:\n\t\t\tif a.report_type != b.report_type and a.report_type == \"Balance Sheet\":\n\t\t\t\treturn -1\n\t\t\tif a.root_type != b.root_type and a.root_type == \"Asset\":\n\t\t\t\treturn -1\n\t\t\tif a.root_type == \"Liability\" and b.root_type == \"Equity\":\n\t\t\t\treturn -1\n\t\t\tif a.root_type == \"Income\" and b.root_type == \"Expense\":\n\t\t\t\treturn -1\n\t\telse:\n\t\t\t# sort by key (number) or name\n\t\t\treturn int(a[key] > b[key]) - int(a[key] < b[key])\n\t\treturn 1\n\n\taccounts.sort(key=functools.cmp_to_key(compare_accounts))\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 72,
        "n_words": 91,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 29,
        "n_ast_nodes": 297,
        "n_identifiers": 16,
        "d_id": 13828,
        "documentation": {
            "docstring": "Sort root types as Asset, Liability, Equity, Income, Expense",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 9563,
        "commit_id": "7375ee364e0df2a417f92593e09557f1b2a3575a",
        "repo": "insightface",
        "path": "reconstruction/ostec/utils/ganfit_camera.py",
        "file_name": "ganfit_camera.py",
        "fun_name": "look_at",
        "commit_message": "initialize ostec",
        "code": "def look_at(eye, center, world_up):\n    \n    batch_size = center.shape[0]\n    vector_degeneracy_cutoff = 1e-6\n    forward = center - eye\n    forward_norm = np.linalg.norm(forward, axis=1, keepdims=True)\n    forward = np.divide(forward, forward_norm)\n\n    to_side = np.cross(forward, world_up)\n    to_side_norm = np.linalg.norm(to_side, axis=1, keepdims=True)\n    to_side = np.divide(to_side, to_side_norm)\n    cam_up = np.cross(to_side, forward)\n\n    w_column = np.array(\n        batch_size * [[0., 0., 0., 1.]], dtype=np.float32)  # [batch_size, 4]\n    w_column = np.reshape(w_column, [batch_size, 4, 1])\n    view_rotation = np.stack(\n        [to_side, cam_up, -forward,\n         np.zeros_like(to_side, dtype=np.float32)],\n        axis=1)  # [batch_size, 4, 3] matrix\n    view_rotation = np.concatenate(\n        [view_rotation, w_column], axis=2)  # [batch_size, 4, 4]\n\n    identity_batch = np.tile(np.expand_dims(np.eye(3), 0), [batch_size, 1, 1])\n    view_translation = np.concatenate([identity_batch, np.expand_dims(-eye, 2)], 2)\n    view_translation = np.concatenate(\n        [view_translation,\n         np.reshape(w_column, [batch_size, 1, 4])], 1)\n    camera_matrices = np.matmul(view_rotation, view_translation)\n    return camera_matrices\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 223,
        "n_words": 112,
        "vocab_size": 72,
        "complexity": 1,
        "nloc": 26,
        "token_counts": 287,
        "n_ast_nodes": 410,
        "n_identifiers": 34,
        "d_id": 1638,
        "documentation": {
            "docstring": "Computes camera viewing matrices.\n    Functionality mimes gluLookAt (third_party/GL/glu/include/GLU/glu.h).\n    Args:\n    eye: 2-D float32 tensor with shape [batch_size, 3] containing the XYZ world\n        space position of the camera.\n    center: 2-D float32 tensor with shape [batch_size, 3] containing a position\n        along the center of the camera's gaze.\n    world_up: 2-D float32 tensor with shape [batch_size, 3] specifying the\n        world's up direction; the output camera will have no tilt with respect\n        to this direction.\n    Returns:\n    A [batch_size, 4, 4] float tensor containing a right-handed camera\n    extrinsics matrix that maps points from world space to points in eye space.\n    ",
            "n_words": 93,
            "vocab_size": 60,
            "n_whitespaces": 148,
            "language": "en"
        }
    },
    {
        "id": 277786,
        "commit_id": "f3cafc77c269f7ecbf80bb4cf4b54e28c153f4e6",
        "repo": "keras",
        "path": "keras/callbacks.py",
        "file_name": "callbacks.py",
        "fun_name": "on_train_batch_end",
        "commit_message": "resolve line-too-long in root directory",
        "code": "def on_train_batch_end(self, batch, logs=None):\n        \n        # For backwards compatibility.\n        self.on_batch_end(batch, logs=logs)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 22,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 82206,
        "documentation": {
            "docstring": "Called at the end of a training batch in `fit` methods.\n\n        Subclasses should override for any actions to run.\n\n        Note that if the `steps_per_execution` argument to `compile` in\n        `tf.keras.Model` is set to `N`, this method will only be called every\n        `N` batches.\n\n        Args:\n            batch: Integer, index of batch within the current epoch.\n            logs: Dict. Aggregated metric results up until this batch.\n        ",
            "n_words": 61,
            "vocab_size": 53,
            "n_whitespaces": 125,
            "language": "en"
        }
    },
    {
        "id": 181545,
        "commit_id": "0c377fc2588ad0f57b3060c26f2d4f891c68276f",
        "repo": "labelImg",
        "path": "libs/labelDialog.py",
        "file_name": "labelDialog.py",
        "fun_name": "pop_up",
        "commit_message": "move \"OK\" button below cursor when opening label dialog (#893)\n\nThe intent for this change is to allow faster labeling when there\r\nare streaks of the same label occasionally, but not consistently\r\nenough to enable \"default label\" mode. With this PR the user can\r\nsimply click again to confirm the previous selection, without\r\nhaving to aim for the OK button, or move either hand to the\r\nENTER button.\r\n\r\nThe alignment and position change of the buttons is for two reasons:\r\n- it covers less of the drawn shape, easing verification of the\r\n  label to be selected\r\n- the alignment wasn't taken into account for offset calculation.\r\n  It works if the dialog is shown, but that causes the dialog to\r\n  briefly flicker in the old position. Presumably an `adjustSize`\r\n  or similar is needed on more widgets, but I was unable to\r\n  figure out which.",
        "code": "def pop_up(self, text='', move=True):\n        \n        self.edit.setText(text)\n        self.edit.setSelection(0, len(text))\n        self.edit.setFocus(Qt.PopupFocusReason)\n        if move:\n            cursor_pos = QCursor.pos()\n\n            # move OK button below cursor\n            btn = self.button_box.buttons()[0]\n            self.adjustSize()\n            btn.adjustSize()\n            offset = btn.mapToGlobal(btn.pos()) - self.pos()\n            offset += QPoint(btn.size().width()/4, btn.size().height()/2)\n            cursor_pos.setX(max(0, cursor_pos.x() - offset.x()))\n            cursor_pos.setY(max(0, cursor_pos.y() - offset.y()))\n\n            parent_bottom_right = self.parentWidget().geometry()\n            max_x = parent_bottom_right.x() + parent_bottom_right.width() - self.sizeHint().width()\n            max_y = parent_bottom_right.y() + parent_bottom_right.height() - self.sizeHint().height()\n            max_global = self.parentWidget().mapToGlobal(QPoint(max_x, max_y))\n            if cursor_pos.x() > max_global.x():\n                cursor_pos.setX(max_global.x())\n            if cursor_pos.y() > max_global.y():\n                cursor_pos.setY(max_global.y())\n            self.move(cursor_pos)\n        return trimmed(self.edit.text()) if self.exec_() else None\n",
        "url": "https://github.com/heartexlabs/labelImg.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 327,
        "n_words": 79,
        "vocab_size": 61,
        "complexity": 5,
        "nloc": 23,
        "token_counts": 310,
        "n_ast_nodes": 515,
        "n_identifiers": 38,
        "d_id": 43352,
        "documentation": {
            "docstring": "\n        Shows the dialog, setting the current text to `text`, and blocks the caller until the user has made a choice.\n        If the user entered a label, that label is returned, otherwise (i.e. if the user cancelled the action)\n        `None` is returned.\n        ",
            "n_words": 41,
            "vocab_size": 31,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 37117,
        "commit_id": "34ef029dc04bb94b4e280e02ef3e82dacf1b9dfc",
        "repo": "transformers",
        "path": "examples/research_projects/self-training-text-classification/selftraining.py",
        "file_name": "selftraining.py",
        "fun_name": "create_pseudo_labeled_data",
        "commit_message": "Add self training code for text classification (#16738)\n\n* Add self-training code for text-classification\r\n\r\n* Add self-training code for text-classification\r\n\r\n* Add self-training code for text-classification\r\n\r\n* Add self-training code for text-classification\r\n\r\n* Add self-training code for text-classification\r\n\r\n* Delete strata",
        "code": "def create_pseudo_labeled_data(args, infer_input, infer_output, eval_result, id2label, next_data_dir):\n    \n\n    dataset = datasets.concatenate_datasets([infer_input, infer_output], axis=1)\n\n    if args.do_filter_by_confidence:\n        dataset = dataset.filter(lambda example: example[\"probability\"] > args.confidence_threshold)\n\n    if args.do_filter_by_val_performance:\n        assert eval_result >= 0.0 and eval_result <= 1.0\n        num_selected_rows = int(eval_result * len(dataset))\n        print(num_selected_rows)\n        dataset = dataset.sort(\"probability\", reverse=True)\n        dataset = dataset.select(range(num_selected_rows))\n\n    dataset = dataset.remove_columns([\"label\", \"probability\"])\n    dataset = dataset.rename_column(\"prediction\", \"label\")\n    dataset = dataset.map(lambda example: {\"label\": id2label[example[\"label\"]]})\n    dataset = dataset.shuffle(seed=args.seed)\n\n    pseudo_labeled_data_file = os.path.join(next_data_dir, f\"train_pseudo.{args.data_file_extension}\")\n    if args.data_file_extension == \"csv\":\n        dataset.to_csv(pseudo_labeled_data_file, index=False)\n    else:\n        dataset.to_json(pseudo_labeled_data_file)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 162,
        "n_words": 73,
        "vocab_size": 53,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 203,
        "n_ast_nodes": 332,
        "n_identifiers": 37,
        "d_id": 6736,
        "documentation": {
            "docstring": "Create pseudeo labeled data for the next self-training iteration.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 197883,
        "commit_id": "d7614cda8f6b341df8515c65244a415b0bf2fc6f",
        "repo": "sympy",
        "path": "sympy/ntheory/residue_ntheory.py",
        "file_name": "residue_ntheory.py",
        "fun_name": "jacobi_symbol",
        "commit_message": "jacobi_symbol: remove dead code paths\n\nFixes #23443\r\n\r\nThe first part of the code was never reached `m %= n`\r\n\r\nThe later `n != 1` condition never matched either since the gcd calculation prevented that from ever happening.\r\n```python\r\n    if igcd(m, n) != 1:\r\n        return 0\r\n```\r\n\r\nhttps://en.wikipedia.org/wiki/Jacobi_symbol#Implementation_in_Lua",
        "code": "def jacobi_symbol(m, n):\n    r\n    m, n = as_int(m), as_int(n)\n    if n < 0 or not n % 2:\n        raise ValueError(\"n should be an odd positive integer\")\n    if m < 0 or m > n:\n        m %= n\n    if not m:\n        return int(n == 1)\n    if n == 1 or m == 1:\n        return 1\n    if igcd(m, n) != 1:\n        return 0\n\n    j = 1\n    while m != 0:\n        while m % 2 == 0 and m > 0:\n            m >>= 1\n            if n % 8 in [3, 5]:\n                j = -j\n        m, n = n, m\n        if m % 4 == n % 4 == 3:\n            j = -j\n        m %= n\n    return j\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 254,
        "n_words": 114,
        "vocab_size": 52,
        "complexity": 17,
        "nloc": 85,
        "token_counts": 177,
        "n_ast_nodes": 234,
        "n_identifiers": 8,
        "d_id": 48735,
        "documentation": {
            "docstring": "\n    Returns the Jacobi symbol `(m / n)`.\n\n    For any integer ``m`` and any positive odd integer ``n`` the Jacobi symbol\n    is defined as the product of the Legendre symbols corresponding to the\n    prime factors of ``n``:\n\n    .. math ::\n        \\genfrac(){}{}{m}{n} =\n            \\genfrac(){}{}{m}{p^{1}}^{\\alpha_1}\n            \\genfrac(){}{}{m}{p^{2}}^{\\alpha_2}\n            ...\n            \\genfrac(){}{}{m}{p^{k}}^{\\alpha_k}\n            \\text{ where } n =\n                p_1^{\\alpha_1}\n                p_2^{\\alpha_2}\n                ...\n                p_k^{\\alpha_k}\n\n    Like the Legendre symbol, if the Jacobi symbol `\\genfrac(){}{}{m}{n} = -1`\n    then ``m`` is a quadratic nonresidue modulo ``n``.\n\n    But, unlike the Legendre symbol, if the Jacobi symbol\n    `\\genfrac(){}{}{m}{n} = 1` then ``m`` may or may not be a quadratic residue\n    modulo ``n``.\n\n    Parameters\n    ==========\n\n    m : integer\n    n : odd positive integer\n\n    Examples\n    ========\n\n    >>> from sympy.ntheory import jacobi_symbol, legendre_symbol\n    >>> from sympy import S\n    >>> jacobi_symbol(45, 77)\n    -1\n    >>> jacobi_symbol(60, 121)\n    1\n\n    The relationship between the ``jacobi_symbol`` and ``legendre_symbol`` can\n    be demonstrated as follows:\n\n    >>> L = legendre_symbol\n    >>> S(45).factors()\n    {3: 2, 5: 1}\n    >>> jacobi_symbol(7, 45) == L(7, 3)**2 * L(7, 5)**1\n    True\n\n    See Also\n    ========\n\n    is_quad_residue, legendre_symbol\n    ",
            "n_words": 165,
            "vocab_size": 107,
            "n_whitespaces": 387,
            "language": "en"
        }
    },
    {
        "id": 211087,
        "commit_id": "5e02a81af77a9a4ecd1e394430c4396b48bc76fd",
        "repo": "PaddleDetection",
        "path": "ppdet/modeling/layers.py",
        "file_name": "layers.py",
        "fun_name": "_topk",
        "commit_message": "remove one line redundant code (#6424)",
        "code": "def _topk(self, scores):\n        \n        k = self.max_per_img\n        shape_fm = paddle.shape(scores)\n        shape_fm.stop_gradient = True\n        cat, height, width = shape_fm[1], shape_fm[2], shape_fm[3]\n        # batch size is 1\n        scores_r = paddle.reshape(scores, [cat, -1])\n        topk_scores, topk_inds = paddle.topk(scores_r, k)\n        topk_ys = topk_inds // width\n        topk_xs = topk_inds % width\n\n        topk_score_r = paddle.reshape(topk_scores, [-1])\n        topk_score, topk_ind = paddle.topk(topk_score_r, k)\n        k_t = paddle.full(paddle.shape(topk_ind), k, dtype='int64')\n        topk_clses = paddle.cast(paddle.floor_divide(topk_ind, k_t), 'float32')\n\n        topk_inds = paddle.reshape(topk_inds, [-1])\n        topk_ys = paddle.reshape(topk_ys, [-1, 1])\n        topk_xs = paddle.reshape(topk_xs, [-1, 1])\n        topk_inds = paddle.gather(topk_inds, topk_ind)\n        topk_ys = paddle.gather(topk_ys, topk_ind)\n        topk_xs = paddle.gather(topk_xs, topk_ind)\n\n        return topk_score, topk_inds, topk_clses, topk_ys, topk_xs\n",
        "url": "https://github.com/PaddlePaddle/PaddleDetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 242,
        "n_words": 95,
        "vocab_size": 60,
        "complexity": 1,
        "nloc": 21,
        "token_counts": 238,
        "n_ast_nodes": 344,
        "n_identifiers": 29,
        "d_id": 53025,
        "documentation": {
            "docstring": "\n        Select top k scores and decode to get xy coordinates.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 289958,
        "commit_id": "bcae6d604e2967c7475f0caa4b1b5e4e76ab88bf",
        "repo": "core",
        "path": "homeassistant/components/mqtt/device_tracker/schema_discovery.py",
        "file_name": "schema_discovery.py",
        "fun_name": "latitude",
        "commit_message": "Improve MQTT type hints part 8 (#81034)\n\n* Improve typing device_tracker discovery\r\n\r\n* Improve typing device_tracker yaml\r\n\r\n* Add test source_type attribute\r\n\r\n* Follow up comment\r\n\r\n* Initialize at `__init__` not at class level.\r\n\r\n* Use full name for return variable\r\n\r\n* Correct import, remove assert\r\n\r\n* Use AsyncSeeCallback",
        "code": "def latitude(self) -> float | None:\n        \n        if (\n            self.extra_state_attributes is not None\n            and ATTR_LATITUDE in self.extra_state_attributes\n        ):\n            latitude: float = self.extra_state_attributes[ATTR_LATITUDE]\n            return latitude\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 97,
        "n_words": 25,
        "vocab_size": 21,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 40,
        "n_ast_nodes": 64,
        "n_identifiers": 5,
        "d_id": 89084,
        "documentation": {
            "docstring": "Return latitude if provided in extra_state_attributes or None.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 73222,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/tests/test_page_modeladmin.py",
        "file_name": "test_page_modeladmin.py",
        "fun_name": "test_false_values_displayed",
        "commit_message": "Reformat with black",
        "code": "def test_false_values_displayed(self):\n        \n        response = self.get(4)\n        self.assertContains(response, \"<dd>False</dd>\", count=3, html=True)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 30,
        "n_ast_nodes": 50,
        "n_identifiers": 7,
        "d_id": 15994,
        "documentation": {
            "docstring": "\n        Boolean fields with False values should display False, rather than the\n        value of `get_empty_value_display()`. For this page, those should be\n        `locked`, `expired` and `has_unpublished_changes`\n        ",
            "n_words": 24,
            "vocab_size": 23,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 100359,
        "commit_id": "c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf",
        "repo": "faceswap",
        "path": "lib/model/normalization/normalization_tf.py",
        "file_name": "normalization_tf.py",
        "fun_name": "call",
        "commit_message": "Update code to support Tensorflow versions up to 2.8 (#1213)\n\n* Update maximum tf version in setup + requirements\r\n\r\n* - bump max version of tf version in launcher\r\n- standardise tf version check\r\n\r\n* update keras get_custom_objects  for tf>2.6\r\n\r\n* bugfix: force black text in GUI file dialogs (linux)\r\n\r\n* dssim loss - Move to stock tf.ssim function\r\n\r\n* Update optimizer imports for compatibility\r\n\r\n* fix logging for tf2.8\r\n\r\n* Fix GUI graphing for TF2.8\r\n\r\n* update tests\r\n\r\n* bump requirements.txt versions\r\n\r\n* Remove limit on nvidia-ml-py\r\n\r\n* Graphing bugfixes\r\n  - Prevent live graph from displaying if data not yet available\r\n\r\n* bugfix: Live graph. Collect loss labels correctly\r\n\r\n* fix: live graph - swallow inconsistent loss errors\r\n\r\n* Bugfix: Prevent live graph from clearing during training\r\n\r\n* Fix graphing for AMD",
        "code": "def call(self, inputs, **kwargs):  # pylint:disable=unused-argument\n        \n        # Compute the axes along which to reduce the mean / variance\n        input_shape = K.int_shape(inputs)\n        layer_size = input_shape[self.axis]\n\n        if self.partial in (0.0, 1.0):\n            mean_square = K.mean(K.square(inputs), axis=self.axis, keepdims=True)\n        else:\n            partial_size = int(layer_size * self.partial)\n            partial_x, _ = tf.split(  # pylint:disable=redundant-keyword-arg,no-value-for-parameter\n                inputs,\n                [partial_size, layer_size - partial_size],\n                axis=self.axis)\n            mean_square = K.mean(K.square(partial_x), axis=self.axis, keepdims=True)\n\n        recip_square_root = tf.math.rsqrt(mean_square + self.epsilon)\n        output = self.scale * inputs * recip_square_root + self.offset\n        return output\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 227,
        "n_words": 73,
        "vocab_size": 53,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 153,
        "n_ast_nodes": 230,
        "n_identifiers": 27,
        "d_id": 19848,
        "documentation": {
            "docstring": " Call Root Mean Square Layer Normalization\n\n        Parameters\n        ----------\n        inputs: tensor\n            Input tensor, or list/tuple of input tensors\n\n        Returns\n        -------\n        tensor\n            A tensor or list/tuple of tensors\n        ",
            "n_words": 26,
            "vocab_size": 20,
            "n_whitespaces": 98,
            "language": "en"
        }
    },
    {
        "id": 73622,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/typed_table_block/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_to_python",
        "commit_message": "Reformat with black",
        "code": "def test_to_python(self):\n        \n        table = self.block.to_python(self.db_data)\n        self.assertIsInstance(table, TypedTable)\n        self.assertEqual(len(table.columns), 2)\n        self.assertEqual(table.columns[0][\"heading\"], \"Country\")\n        self.assertEqual(table.columns[1][\"heading\"], \"Description\")\n        rows = list(table.rows)\n        self.assertEqual(len(rows), 2)\n        self.assertEqual(\n            [block.value for block in rows[0]],\n            [\"nl\", \"A small country with stroopwafels\"],\n        )\n        self.assertEqual(\n            [block.value for block in rows[1]], [\"fr\", \"A large country with baguettes\"]\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 161,
        "n_words": 44,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 137,
        "n_ast_nodes": 221,
        "n_identifiers": 14,
        "d_id": 16073,
        "documentation": {
            "docstring": "\n        Test that we can turn JSONish data from the database into a TypedTable instance\n        ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 107535,
        "commit_id": "88cb4c9d0aa1e790fc4689ca7e68725bf851bf63",
        "repo": "matplotlib",
        "path": "lib/matplotlib/ticker.py",
        "file_name": "ticker.py",
        "fun_name": "_format_maybe_minus_and_locale",
        "commit_message": "Properly capitalize \"Unicode\".\n\nSee e.g. https://en.wikipedia.org/wiki/Unicode,\nhttps://docs.python.org/3/howto/unicode.html.\n\nAlso associated minor doc cleanups.",
        "code": "def _format_maybe_minus_and_locale(self, fmt, arg):\n        \n        return self.fix_minus(locale.format_string(fmt, (arg,), True)\n                              if self._useLocale else fmt % arg)\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 57,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 37,
        "n_ast_nodes": 55,
        "n_identifiers": 8,
        "d_id": 22797,
        "documentation": {
            "docstring": "\n        Format *arg* with *fmt*, applying Unicode minus and locale if desired.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 317039,
        "commit_id": "da027fa3905d36b91beefd456cb546f891617eab",
        "repo": "core",
        "path": "tests/test_util/aiohttp.py",
        "file_name": "aiohttp.py",
        "fun_name": "create_session",
        "commit_message": "JSON serialize NamedTuple subclasses with aiohttp (#74971)",
        "code": "def create_session(self, loop):\n        \n        session = ClientSession(loop=loop, json_serialize=json_dumps)\n        # Setting directly on `session` will raise deprecation warning\n        object.__setattr__(session, \"_request\", self.match_request)\n        return session\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 56,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 56,
        "n_identifiers": 10,
        "d_id": 115615,
        "documentation": {
            "docstring": "Create a ClientSession that is bound to this mocker.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 205791,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "last",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def last(self):\n        \n        for obj in (self.reverse() if self.ordered else self.order_by(\"-pk\"))[:1]:\n            return obj\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 37,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 57,
        "n_identifiers": 6,
        "d_id": 51217,
        "documentation": {
            "docstring": "Return the last object of a query or None if no match is found.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 73170,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/options.py",
        "file_name": "options.py",
        "fun_name": "create_view",
        "commit_message": "Reformat with black",
        "code": "def create_view(self, request):\n        \n        kwargs = {\"model_admin\": self}\n        view_class = self.create_view_class\n        return view_class.as_view(**kwargs)(request)\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 40,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 54,
        "n_identifiers": 7,
        "d_id": 15968,
        "documentation": {
            "docstring": "\n        Instantiates a class-based view to provide 'creation' functionality for\n        the assigned model, or redirect to Wagtail's create view if the\n        assigned model extends 'Page'. The view class used can be overridden by\n        changing the 'create_view_class' attribute.\n        ",
            "n_words": 36,
            "vocab_size": 30,
            "n_whitespaces": 72,
            "language": "en"
        }
    },
    {
        "id": 312340,
        "commit_id": "41ab12cb88741807a246bb296762d7c683a30b58",
        "repo": "core",
        "path": "homeassistant/components/recorder/migration.py",
        "file_name": "migration.py",
        "fun_name": "_create_index",
        "commit_message": "Don't use shared session during recorder migration (#65672)",
        "code": "def _create_index(instance, table_name, index_name):\n    \n    table = Table(table_name, Base.metadata)\n    _LOGGER.debug(\"Looking up index %s for table %s\", index_name, table_name)\n    # Look up the index object by name from the table is the models\n    index_list = [idx for idx in table.indexes if idx.name == index_name]\n    if not index_list:\n        _LOGGER.debug(\"The index %s no longer exists\", index_name)\n        return\n    index = index_list[0]\n    _LOGGER.debug(\"Creating %s index\", index_name)\n    _LOGGER.warning(\n        \"Adding index `%s` to database. Note: this can take several \"\n        \"minutes on large databases and slow computers. Please \"\n        \"be patient!\",\n        index_name,\n    )\n    try:\n        with session_scope(session=instance.get_session()) as session:\n            connection = session.connection()\n            index.create(connection)\n    except (InternalError, ProgrammingError, OperationalError) as err:\n        raise_if_exception_missing_str(err, [\"already exists\", \"duplicate\"])\n        _LOGGER.warning(\n            \"Index %s already exists on %s, continuing\", index_name, table_name\n        )\n\n    _LOGGER.debug(\"Finished creating %s\", index_name)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 261,
        "n_words": 119,
        "vocab_size": 91,
        "complexity": 5,
        "nloc": 25,
        "token_counts": 153,
        "n_ast_nodes": 258,
        "n_identifiers": 26,
        "d_id": 110990,
        "documentation": {
            "docstring": "Create an index for the specified table.\n\n    The index name should match the name given for the index\n    within the table definition described in the models\n    ",
            "n_words": 26,
            "vocab_size": 18,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 166611,
        "commit_id": "244f747bb63f45c1c439193f0672c6162853b168",
        "repo": "pandas",
        "path": "pandas/core/generic.py",
        "file_name": "generic.py",
        "fun_name": "squeeze",
        "commit_message": "make series axis parameter docs consistent (#47109)\n\n* make series docs consistent\r\n\r\nadd series unused param info to DF docs\r\n\r\n* fix trailing whitespace\r\n\r\n* fix docs build\r\n\r\n* add unused\r\n\r\n* add or update docs for all series methods\r\n\r\n* small fix\r\n\r\n* fix line length\r\n\r\n* fix param order\r\n\r\n* fix param order\r\n\r\n* add\r\n\r\n* add backticks to None and fix space\r\n\r\nCo-authored-by: uncjackg <jackg@live.unc.edu>",
        "code": "def squeeze(self, axis=None):\n        \n        axis = range(self._AXIS_LEN) if axis is None else (self._get_axis_number(axis),)\n        return self.iloc[\n            tuple(\n                0 if i in axis and len(a) == 1 else slice(None)\n                for i, a in enumerate(self.axes)\n            )\n        ]\n\n    # ----------------------------------------------------------------------\n    # Rename\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 123,
        "n_words": 37,
        "vocab_size": 31,
        "complexity": 5,
        "nloc": 8,
        "token_counts": 69,
        "n_ast_nodes": 108,
        "n_identifiers": 14,
        "d_id": 39840,
        "documentation": {
            "docstring": "\n        Squeeze 1 dimensional axis objects into scalars.\n\n        Series or DataFrames with a single element are squeezed to a scalar.\n        DataFrames with a single column or a single row are squeezed to a\n        Series. Otherwise the object is unchanged.\n\n        This method is most useful when you don't know if your\n        object is a Series or DataFrame, but you do know it has just a single\n        column. In that case you can safely call `squeeze` to ensure you have a\n        Series.\n\n        Parameters\n        ----------\n        axis : {0 or 'index', 1 or 'columns', None}, default None\n            A specific axis to squeeze. By default, all length-1 axes are\n            squeezed. For `Series` this parameter is unused and defaults to `None`.\n\n        Returns\n        -------\n        DataFrame, Series, or scalar\n            The projection after squeezing `axis` or all the axes.\n\n        See Also\n        --------\n        Series.iloc : Integer-location based indexing for selecting scalars.\n        DataFrame.iloc : Integer-location based indexing for selecting Series.\n        Series.to_frame : Inverse of DataFrame.squeeze for a\n            single-column DataFrame.\n\n        Examples\n        --------\n        >>> primes = pd.Series([2, 3, 5, 7])\n\n        Slicing might produce a Series with a single value:\n\n        >>> even_primes = primes[primes % 2 == 0]\n        >>> even_primes\n        0    2\n        dtype: int64\n\n        >>> even_primes.squeeze()\n        2\n\n        Squeezing objects with more than one value in every axis does nothing:\n\n        >>> odd_primes = primes[primes % 2 == 1]\n        >>> odd_primes\n        1    3\n        2    5\n        3    7\n        dtype: int64\n\n        >>> odd_primes.squeeze()\n        1    3\n        2    5\n        3    7\n        dtype: int64\n\n        Squeezing is even more effective when used with DataFrames.\n\n        >>> df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])\n        >>> df\n           a  b\n        0  1  2\n        1  3  4\n\n        Slicing a single column will produce a DataFrame with the columns\n        having only one value:\n\n        >>> df_a = df[['a']]\n        >>> df_a\n           a\n        0  1\n        1  3\n\n        So the columns can be squeezed down, resulting in a Series:\n\n        >>> df_a.squeeze('columns')\n        0    1\n        1    3\n        Name: a, dtype: int64\n\n        Slicing a single row from a single column will produce a single\n        scalar DataFrame:\n\n        >>> df_0a = df.loc[df.index < 1, ['a']]\n        >>> df_0a\n           a\n        0  1\n\n        Squeezing the rows produces a single scalar Series:\n\n        >>> df_0a.squeeze('rows')\n        a    1\n        Name: 0, dtype: int64\n\n        Squeezing all axes will project directly into a scalar:\n\n        >>> df_0a.squeeze()\n        1\n        ",
            "n_words": 361,
            "vocab_size": 184,
            "n_whitespaces": 964,
            "language": "en"
        }
    },
    {
        "id": 62287,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/wheel.py",
        "file_name": "wheel.py",
        "fun_name": "filename",
        "commit_message": "upd; format",
        "code": "def filename(self):\n        \n        if self.buildver:\n            buildver = '-' + self.buildver\n        else:\n            buildver = ''\n        pyver = '.'.join(self.pyver)\n        abi = '.'.join(self.abi)\n        arch = '.'.join(self.arch)\n        # replace - with _ as a local version separator\n        version = self.version.replace('-', '_')\n        return '%s-%s%s-%s-%s-%s.whl' % (self.name, version, buildver,\n                                         pyver, abi, arch)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 170,
        "n_words": 45,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 83,
        "n_ast_nodes": 146,
        "n_identifiers": 10,
        "d_id": 12910,
        "documentation": {
            "docstring": "\n        Build and return a filename from the various components.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 293995,
        "commit_id": "073fb40b79cf8aa06790fdceb23b6857db888c99",
        "repo": "core",
        "path": "homeassistant/components/update/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "async_internal_added_to_hass",
        "commit_message": "Add update entity platform (#68248)\n\nCo-authored-by: Glenn Waters <glenn@watrs.ca>",
        "code": "async def async_internal_added_to_hass(self) -> None:\n        \n        await super().async_internal_added_to_hass()\n        state = await self.async_get_last_state()\n        if state is not None and state.attributes.get(ATTR_SKIPPED_VERSION) is not None:\n            self.__skipped_version = state.attributes[ATTR_SKIPPED_VERSION]\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 63,
        "n_words": 24,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 52,
        "n_ast_nodes": 88,
        "n_identifiers": 9,
        "d_id": 93040,
        "documentation": {
            "docstring": "Call when the update entity is added to hass.\n\n        It is used to restore the skipped version, if any.\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 181898,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/export_utils.py",
        "file_name": "export_utils.py",
        "fun_name": "generate_export_pipeline_code",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def generate_export_pipeline_code(pipeline_tree, operators):\n    \n    steps = _process_operator(pipeline_tree, operators)\n    # number of steps in a pipeline\n    num_step = len(steps)\n    if num_step > 1:\n        pipeline_text = \"make_pipeline(\\n{STEPS}\\n)\".format(\n            STEPS=_indent(\",\\n\".join(steps), 4)\n        )\n    # only one operator (root = True)\n    else:\n        pipeline_text = \"{STEPS}\".format(STEPS=_indent(\",\\n\".join(steps), 0))\n\n    return pipeline_text\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 97,
        "n_words": 41,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 71,
        "n_ast_nodes": 128,
        "n_identifiers": 12,
        "d_id": 43653,
        "documentation": {
            "docstring": "Generate code specific to the construction of the sklearn Pipeline for export_pipeline.\n\n    Parameters\n    ----------\n    pipeline_tree: list\n        List of operators in the current optimized pipeline\n\n    Returns\n    -------\n    Source code for the sklearn pipeline\n\n    ",
            "n_words": 32,
            "vocab_size": 24,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 217838,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/cookies.py",
        "file_name": "cookies.py",
        "fun_name": "OutputString",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def OutputString(self, attrs=None):\n        # Build up our result\n        #\n        result = []\n        append = result.append\n\n        # First, the key=value pair\n        append(\"%s=%s\" % (self.key, self.coded_value))\n\n        # Now add any defined attributes\n        if attrs is None:\n            attrs = self._reserved\n        items = sorted(self.items())\n        for key, value in items:\n            if value == \"\":\n                continue\n            if key not in attrs:\n                continue\n            if key == \"expires\" and isinstance(value, int):\n                append(\"%s=%s\" % (self._reserved[key], _getdate(value)))\n            elif key == \"max-age\" and isinstance(value, int):\n                append(\"%s=%d\" % (self._reserved[key], value))\n            elif key == \"comment\" and isinstance(value, str):\n                append(\"%s=%s\" % (self._reserved[key], _quote(value)))\n            elif key in self._flags:\n                if value:\n                    append(str(self._reserved[key]))\n            else:\n                append(\"%s=%s\" % (self._reserved[key], value))\n\n        # Return the result\n        return _semispacejoin(result)\n\n    __class_getitem__ = classmethod(types.GenericAlias)\n\n\n#\n# Pattern for finding cookie\n#\n# This used to be strict parsing based on the RFC2109 and RFC2068\n# specifications.  I have since discovered that MSIE 3.0x doesn't\n# follow the character rules outlined in those specs.  As a\n# result, the parsing rules here are less strict.\n#\n\n_LegalKeyChars  = r\"\\w\\d!#%&'~_`><@,:/\\$\\*\\+\\-\\.\\^\\|\\)\\(\\?\\}\\{\\=\"\n_LegalValueChars = _LegalKeyChars + r'\\[\\]'\n_CookiePattern = re.compile(r + _LegalKeyChars + r + _LegalValueChars + r, re.ASCII | re.VERBOSE)    # re.ASCII may be removed if safe.\n\n\n# At long last, here is the cookie class.  Using this class is almost just like\n# using a dictionary.  See this module's docstring for example usage.\n#",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 510,
        "n_words": 218,
        "vocab_size": 132,
        "complexity": 13,
        "nloc": 24,
        "token_counts": 203,
        "n_ast_nodes": 420,
        "n_identifiers": 29,
        "d_id": 54962,
        "documentation": {
            "docstring": "\n    \\s*                            # Optional whitespace at start of cookie\n    (?P<key>                       # Start of group 'key'\n    []+?   # Any word of at least one letter\n    )                              # End of group 'key'\n    (                              # Optional group: there may not be a value.\n    \\s*=\\s*                          # Equal Sign\n    (?P<val>                         # Start of group 'val'\n    \"(?:[^\\\\\"]|\\\\.)*\"                  # Any doublequoted string\n    |                                  # or\n    \\w{3},\\s[\\w\\d\\s-]{9,11}\\s[\\d:]{8}\\sGMT  # Special case for \"expires\" attr\n    |                                  # or\n    []*      # Any word or empty string\n    )                                # End of group 'val'\n    )?                             # End of optional value group\n    \\s*                            # Any number of spaces.\n    (\\s+|;|$)                      # Ending either at space, semicolon, or EOS.\n    ",
            "n_words": 102,
            "vocab_size": 57,
            "n_whitespaces": 508,
            "language": "en"
        }
    },
    {
        "id": 108079,
        "commit_id": "22a44db48c1b7659837092c5b01a59eb1d004fc6",
        "repo": "matplotlib",
        "path": "lib/matplotlib/rcsetup.py",
        "file_name": "rcsetup.py",
        "fun_name": "validate_cycler",
        "commit_message": "Use repr in error messages",
        "code": "def validate_cycler(s):\n    \n    if isinstance(s, str):\n        # TODO: We might want to rethink this...\n        # While I think I have it quite locked down, it is execution of\n        # arbitrary code without sanitation.\n        # Combine this with the possibility that rcparams might come from the\n        # internet (future plans), this could be downright dangerous.\n        # I locked it down by only having the 'cycler()' function available.\n        # UPDATE: Partly plugging a security hole.\n        # I really should have read this:\n        # https://nedbatchelder.com/blog/201206/eval_really_is_dangerous.html\n        # We should replace this eval with a combo of PyParsing and\n        # ast.literal_eval()\n        try:\n            _DunderChecker().visit(ast.parse(s))\n            s = eval(s, {'cycler': cycler, '__builtins__': {}})\n        except BaseException as e:\n            raise ValueError(f\"{s!r} is not a valid cycler construction: {e}\"\n                             ) from e\n    # Should make sure what comes from the above eval()\n    # is a Cycler object.\n    if isinstance(s, Cycler):\n        cycler_inst = s\n    else:\n        raise ValueError(f\"Object is not a string or Cycler instance: {s!r}\")\n\n    unknowns = cycler_inst.keys - (set(_prop_validators) | set(_prop_aliases))\n    if unknowns:\n        raise ValueError(\"Unknown artist properties: %s\" % unknowns)\n\n    # Not a full validation, but it'll at least normalize property names\n    # A fuller validation would require v0.10 of cycler.\n    checker = set()\n    for prop in cycler_inst.keys:\n        norm_prop = _prop_aliases.get(prop, prop)\n        if norm_prop != prop and norm_prop in cycler_inst.keys:\n            raise ValueError(f\"Cannot specify both {norm_prop!r} and alias \"\n                             f\"{prop!r} in the same prop_cycle\")\n        if norm_prop in checker:\n            raise ValueError(f\"Another property was already aliased to \"\n                             f\"{norm_prop!r}. Collision normalizing {prop!r}.\")\n        checker.update([norm_prop])\n\n    # This is just an extra-careful check, just in case there is some\n    # edge-case I haven't thought of.\n    assert len(checker) == len(cycler_inst.keys)\n\n    # Now, it should be safe to mutate this cycler\n    for prop in cycler_inst.keys:\n        norm_prop = _prop_aliases.get(prop, prop)\n        cycler_inst.change_key(prop, norm_prop)\n\n    for key, vals in cycler_inst.by_key().items():\n        _prop_validators[key](vals)\n\n    return cycler_inst\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 646,
        "n_words": 289,
        "vocab_size": 192,
        "complexity": 11,
        "nloc": 32,
        "token_counts": 228,
        "n_ast_nodes": 423,
        "n_identifiers": 31,
        "d_id": 23050,
        "documentation": {
            "docstring": "Return a Cycler object from a string repr or the object itself.",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 206236,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/defaultfilters.py",
        "file_name": "defaultfilters.py",
        "fun_name": "addslashes",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def addslashes(value):\n    \n    return value.replace(\"\\\\\", \"\\\\\\\\\").replace('\"', '\\\\\"').replace(\"'\", \"\\\\'\")\n\n\n@register.filter(is_safe=True)\n@stringfilter",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.filter(is_safe=True)\n@stringfilter",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 13,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 29,
        "n_ast_nodes": 81,
        "n_identifiers": 7,
        "d_id": 51427,
        "documentation": {
            "docstring": "\n    Add slashes before quotes. Useful for escaping strings in CSV, for\n    example. Less useful for escaping JavaScript; use the ``escapejs``\n    filter instead.\n    ",
            "n_words": 22,
            "vocab_size": 19,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 65767,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/crm/report/prospects_engaged_but_not_converted/prospects_engaged_but_not_converted.py",
        "file_name": "prospects_engaged_but_not_converted.py",
        "fun_name": "get_data",
        "commit_message": "style: format code with black",
        "code": "def get_data(filters):\n\tlead_details = []\n\tlead_filters = get_lead_filters(filters)\n\n\tfor lead in frappe.get_all(\n\t\t\"Lead\", fields=[\"name\", \"lead_name\", \"company_name\"], filters=lead_filters\n\t):\n\t\tdata = frappe.db.sql(\n\t\t\t,\n\t\t\t{\"lead\": lead.name, \"limit\": filters.get(\"no_of_interaction\")},\n\t\t)\n\n\t\tfor lead_info in data:\n\t\t\tlead_data = [lead.name, lead.lead_name, lead.company_name] + list(lead_info)\n\t\t\tlead_details.append(lead_data)\n\n\treturn lead_details\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 27,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 3,
        "nloc": 33,
        "token_counts": 100,
        "n_ast_nodes": 164,
        "n_identifiers": 20,
        "d_id": 14009,
        "documentation": {
            "docstring": "\n\t\t\tselect\n\t\t\t\t`tabCommunication`.reference_doctype, `tabCommunication`.reference_name,\n\t\t\t\t`tabCommunication`.content, `tabCommunication`.communication_date\n\t\t\tfrom\n\t\t\t\t(\n\t\t\t\t\t(select name, party_name as lead from `tabOpportunity` where opportunity_from='Lead' and party_name = %(lead)s)\n\t\t\t\tunion\n\t\t\t\t\t(select name, party_name as lead from `tabQuotation` where quotation_to = 'Lead' and party_name = %(lead)s)\n\t\t\t\tunion\n\t\t\t\t\t(select name, lead from `tabIssue` where lead = %(lead)s and status!='Closed')\n\t\t\t\tunion\n\t\t\t\t\t(select %(lead)s, %(lead)s)\n\t\t\t\t)\n\t\t\t\tas ref_document, `tabCommunication`\n\t\t\twhere\n\t\t\t\t`tabCommunication`.reference_name = ref_document.name and\n\t\t\t\t`tabCommunication`.sent_or_received = 'Received'\n\t\t\torder by\n\t\t\t\tref_document.lead, `tabCommunication`.creation desc limit %(limit)s",
            "n_words": 71,
            "vocab_size": 40,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 156727,
        "commit_id": "2820bae493a49cb1d0a6e376985c5473b8f04fa8",
        "repo": "dask",
        "path": "dask/array/core.py",
        "file_name": "core.py",
        "fun_name": "choose",
        "commit_message": "Don't include docs in ``Array`` methods, just refer to module docs (#9244)\n\nCo-authored-by: James Bourbeau <jrbourbeau@users.noreply.github.com>",
        "code": "def choose(self, choices):\n        \n        from dask.array.routines import choose\n\n        return choose(self, choices)\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 23,
        "n_ast_nodes": 36,
        "n_identifiers": 6,
        "d_id": 36737,
        "documentation": {
            "docstring": "Use an index array to construct a new array from a set of choices.\n\n        Refer to :func:`dask.array.choose` for full documentation.\n\n        See Also\n        --------\n        dask.array.choose : equivalent function\n        ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 62218,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/util.py",
        "file_name": "util.py",
        "fun_name": "newer",
        "commit_message": "upd; format",
        "code": "def newer(self, source, target):\n        \n        if not os.path.exists(source):\n            raise DistlibException(\"file '%r' does not exist\" %\n                                   os.path.abspath(source))\n        if not os.path.exists(target):\n            return True\n\n        return os.stat(source).st_mtime > os.stat(target).st_mtime\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 108,
        "n_words": 24,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 66,
        "n_ast_nodes": 108,
        "n_identifiers": 11,
        "d_id": 12901,
        "documentation": {
            "docstring": "Tell if the target is newer than the source.\n\n        Returns true if 'source' exists and is more recently modified than\n        'target', or if 'source' exists and 'target' doesn't.\n\n        Returns false if both exist and 'target' is the same age or younger\n        than 'source'. Raise PackagingFileError if 'source' does not exist.\n\n        Note that this test is not very accurate: files created in the same\n        second will have the same \"age\".\n        ",
            "n_words": 69,
            "vocab_size": 45,
            "n_whitespaces": 118,
            "language": "en"
        }
    },
    {
        "id": 197470,
        "commit_id": "2047f4855577845b1b99e0926b887d313725a6e7",
        "repo": "sympy",
        "path": "sympy/utilities/misc.py",
        "file_name": "misc.py",
        "fun_name": "filldedent",
        "commit_message": "Pass keyword arguments to filldedent() through to fill()",
        "code": "def filldedent(s, w=70, **kwargs):\n    \n    return '\\n' + fill(dedent(str(s)).strip('\\n'), width=w, **kwargs)\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 16,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 38,
        "n_ast_nodes": 66,
        "n_identifiers": 9,
        "d_id": 48569,
        "documentation": {
            "docstring": "\n    Strips leading and trailing empty lines from a copy of ``s``, then dedents,\n    fills and returns it.\n\n    Empty line stripping serves to deal with docstrings like this one that\n    start with a newline after the initial triple quote, inserting an empty\n    line at the beginning of the string.\n\n    Additional keyword arguments will be passed to ``textwrap.fill()``.\n\n    See Also\n    ========\n    strlines, rawlines\n\n    ",
            "n_words": 61,
            "vocab_size": 52,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 83259,
        "commit_id": "b0ce4f1bce8031881addecb1e86073483517f392",
        "repo": "zulip",
        "path": "zerver/tests/test_openapi.py",
        "file_name": "test_openapi.py",
        "fun_name": "test_regex",
        "commit_message": "docs: Fix many spelling mistakes.\n\nSigned-off-by: Anders Kaseorg <anders@zulip.com>",
        "code": "def test_regex(self) -> None:\n        \n        # Some of the undocumented endpoints which are very similar to\n        # some of the documented endpoints.\n        assert find_openapi_endpoint(\"/users/me/presence\") is None\n        assert find_openapi_endpoint(\"/users/me/subscriptions/23\") is None\n        assert find_openapi_endpoint(\"/users/iago/subscriptions/23\") is None\n        assert find_openapi_endpoint(\"/messages/matches_narrow\") is None\n        # Making sure documented endpoints are matched correctly.\n        assert (\n            find_openapi_endpoint(\"/users/23/subscriptions/21\")\n            == \"/users/{user_id}/subscriptions/{stream_id}\"\n        )\n        assert (\n            find_openapi_endpoint(\"/users/iago@zulip.com/presence\")\n            == \"/users/{user_id_or_email}/presence\"\n        )\n        assert find_openapi_endpoint(\"/users/iago@zulip.com\") == \"/users/{email}\"\n        assert find_openapi_endpoint(\"/messages/23\") == \"/messages/{message_id}\"\n        assert find_openapi_endpoint(\"/realm/emoji/realm_emoji_1\") == \"/realm/emoji/{emoji_name}\"\n\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 218,
        "n_words": 69,
        "vocab_size": 42,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 75,
        "n_ast_nodes": 152,
        "n_identifiers": 3,
        "d_id": 17641,
        "documentation": {
            "docstring": "\n        Calls a few documented  and undocumented endpoints and checks whether they\n        find a match or not.\n        ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 219816,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "compare_total",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def compare_total(self, other, context=None):\n        \n        other = _convert_other(other, raiseit=True)\n\n        # if one is negative and the other is positive, it's easy\n        if self._sign and not other._sign:\n            return _NegativeOne\n        if not self._sign and other._sign:\n            return _One\n        sign = self._sign\n\n        # let's handle both NaN types\n        self_nan = self._isnan()\n        other_nan = other._isnan()\n        if self_nan or other_nan:\n            if self_nan == other_nan:\n                # compare payloads as though they're integers\n                self_key = len(self._int), self._int\n                other_key = len(other._int), other._int\n                if self_key < other_key:\n                    if sign:\n                        return _One\n                    else:\n                        return _NegativeOne\n                if self_key > other_key:\n                    if sign:\n                        return _NegativeOne\n                    else:\n                        return _One\n                return _Zero\n\n            if sign:\n                if self_nan == 1:\n                    return _NegativeOne\n                if other_nan == 1:\n                    return _One\n                if self_nan == 2:\n                    return _NegativeOne\n                if other_nan == 2:\n                    return _One\n            else:\n                if self_nan == 1:\n                    return _One\n                if other_nan == 1:\n                    return _NegativeOne\n                if self_nan == 2:\n                    return _One\n                if other_nan == 2:\n                    return _NegativeOne\n\n        if self < other:\n            return _NegativeOne\n        if self > other:\n            return _One\n\n        if self._exp < other._exp:\n            if sign:\n                return _One\n            else:\n                return _NegativeOne\n        if self._exp > other._exp:\n            if sign:\n                return _NegativeOne\n            else:\n                return _One\n        return _Zero\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 999,
        "n_words": 183,
        "vocab_size": 61,
        "complexity": 27,
        "nloc": 57,
        "token_counts": 242,
        "n_ast_nodes": 391,
        "n_identifiers": 19,
        "d_id": 55829,
        "documentation": {
            "docstring": "Compares self to other using the abstract representations.\n\n        This is not like the standard compare, which use their numerical\n        value. Note that a total ordering is defined for all possible abstract\n        representations.\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 186917,
        "commit_id": "eed1afb8082518a5212a6d8016a4ccf44c5ad99e",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/configurator.py",
        "file_name": "configurator.py",
        "fun_name": "_override_cmds",
        "commit_message": "certbot-apache: use httpd by default for CentOS/RHEL (#9402)\n\n* certbot-apache: use httpd for newer RHEL derived distros\r\n\r\nA change in RHEL 9 is causing apachectl to error out when used\r\nwith additional arguments, resulting in certbot errors. The CentOS\r\nconfigurator now uses httpd instead for RHEL 9 (and later) derived\r\ndistros.\r\n\r\n* Single CentOS class which uses the apache_bin option\r\n\r\n* soothe mypy\r\n\r\n* Always call super()._override_cmds()",
        "code": "def _override_cmds(self) -> None:\n        \n        self.options.version_cmd[0] = self.options.ctl\n        self.options.restart_cmd[0] = self.options.ctl\n        self.options.conftest_cmd[0] = self.options.ctl\n        self.options.get_modules_cmd[0] = self.options.ctl\n        self.options.get_includes_cmd[0] = self.options.ctl\n        self.options.get_defines_cmd[0] = self.options.ctl\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 71,
        "n_words": 22,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 92,
        "n_ast_nodes": 142,
        "n_identifiers": 10,
        "d_id": 45657,
        "documentation": {
            "docstring": "\n        Set our various command binaries to whatever the user has overridden for apachectl\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 154259,
        "commit_id": "b240370bf83c88589d293b76b4a2409294e06f90",
        "repo": "modin",
        "path": "modin/core/io/column_stores/parquet_dispatcher.py",
        "file_name": "parquet_dispatcher.py",
        "fun_name": "_get_files",
        "commit_message": "FEAT-#4733: Support fastparquet as engine for `read_parquet` (#4807)\n\nSigned-off-by: Karthik Velayutham <vkarthik@ponder.io>",
        "code": "def _get_files(self, files):\n        \n        # Older versions of fsspec doesn't support unstrip_protocol(). It\n        # was only added relatively recently:\n        # https://github.com/fsspec/filesystem_spec/pull/828",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 48,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 5,
        "nloc": 9,
        "token_counts": 81,
        "n_ast_nodes": 18,
        "n_identifiers": 3,
        "d_id": 35881,
        "documentation": {
            "docstring": "\n        Retrieve list of formatted file names in dataset path.\n\n        Parameters\n        ----------\n        files : list\n            List of files from path.\n\n        Returns\n        -------\n        fs_files : list\n            List of files from path with fs-protocol prepended.\n        ",
            "n_words": 32,
            "vocab_size": 22,
            "n_whitespaces": 111,
            "language": "en"
        }
    },
    {
        "id": 61110,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/factory.py",
        "file_name": "factory.py",
        "fun_name": "get_wheel_cache_entry",
        "commit_message": "upd; format",
        "code": "def get_wheel_cache_entry(self, link, name):\n        # type: (Link, Optional[str]) -> Optional[CacheEntry]\n        \n        if self._wheel_cache is None or self.preparer.require_hashes:\n            return None\n        return self._wheel_cache.get_cache_entry(\n            link=link,\n            package_name=name,\n            supported_tags=get_supported(),\n        )\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 103,
        "n_words": 24,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 47,
        "n_ast_nodes": 73,
        "n_identifiers": 11,
        "d_id": 12412,
        "documentation": {
            "docstring": "Look up the link in the wheel cache.\n\n        If ``preparer.require_hashes`` is True, don't use the wheel cache,\n        because cached wheels, always built locally, have different hashes\n        than the files downloaded from the index server and thus throw false\n        hash mismatches. Furthermore, cached wheels at present have\n        nondeterministic contents due to file modification times.\n        ",
            "n_words": 53,
            "vocab_size": 46,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 150418,
        "commit_id": "9f6bba40af1a407f190a89f5c0c8b4e3f528ba46",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/replicate/channel.py",
        "file_name": "channel.py",
        "fun_name": "broadcast",
        "commit_message": "initial concept for replicate, basic leader and follower logic",
        "code": "async def broadcast(self, data):\n        \n        for channel in self.channels.values():\n            await channel.send(data)\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 35,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 34740,
        "documentation": {
            "docstring": "\n        Broadcast data on all Channels\n\n        :param data: The data to send\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 220522,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/futures.py",
        "file_name": "futures.py",
        "fun_name": "_set_concurrent_future_state",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _set_concurrent_future_state(concurrent, source):\n    \n    assert source.done()\n    if source.cancelled():\n        concurrent.cancel()\n    if not concurrent.set_running_or_notify_cancel():\n        return\n    exception = source.exception()\n    if exception is not None:\n        concurrent.set_exception(_convert_future_exc(exception))\n    else:\n        result = source.result()\n        concurrent.set_result(result)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 82,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 72,
        "n_ast_nodes": 124,
        "n_identifiers": 12,
        "d_id": 56029,
        "documentation": {
            "docstring": "Copy state from a future to a concurrent.futures.Future.",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 246308,
        "commit_id": "df36945ff0e4a293a9dac0da07e2c94256835b32",
        "repo": "synapse",
        "path": "tests/rest/client/test_relations.py",
        "file_name": "test_relations.py",
        "fun_name": "test_repeated_paginate_relations",
        "commit_message": "Support pagination tokens from /sync and /messages in the relations API. (#11952)",
        "code": "def test_repeated_paginate_relations(self):\n        \n\n        expected_event_ids = []\n        for idx in range(10):\n            channel = self._send_relation(\n                RelationTypes.ANNOTATION, \"m.reaction\", chr(ord(\"a\") + idx)\n            )\n            self.assertEquals(200, channel.code, channel.json_body)\n            expected_event_ids.append(channel.json_body[\"event_id\"])\n\n        prev_token = \"\"\n        found_event_ids: List[str] = []\n        for _ in range(20):\n            from_token = \"\"\n            if prev_token:\n                from_token = \"&from=\" + prev_token\n\n            channel = self.make_request(\n                \"GET\",\n                f\"/_matrix/client/unstable/rooms/{self.room}/relations/{self.parent_id}?limit=1{from_token}\",\n                access_token=self.user_token,\n            )\n            self.assertEquals(200, channel.code, channel.json_body)\n\n            found_event_ids.extend(e[\"event_id\"] for e in channel.json_body[\"chunk\"])\n            next_batch = channel.json_body.get(\"next_batch\")\n\n            self.assertNotEquals(prev_token, next_batch)\n            prev_token = next_batch\n\n            if not prev_token:\n                break\n\n        # We paginated backwards, so reverse\n        found_event_ids.reverse()\n        self.assertEquals(found_event_ids, expected_event_ids)\n\n        # Reset and try again, but convert the tokens to the legacy format.\n        prev_token = \"\"\n        found_event_ids = []\n        for _ in range(20):\n            from_token = \"\"\n            if prev_token:\n                from_token = \"&from=\" + self._stream_token_to_relation_token(prev_token)\n\n            channel = self.make_request(\n                \"GET\",\n                f\"/_matrix/client/unstable/rooms/{self.room}/relations/{self.parent_id}?limit=1{from_token}\",\n                access_token=self.user_token,\n            )\n            self.assertEquals(200, channel.code, channel.json_body)\n\n            found_event_ids.extend(e[\"event_id\"] for e in channel.json_body[\"chunk\"])\n            next_batch = channel.json_body.get(\"next_batch\")\n\n            self.assertNotEquals(prev_token, next_batch)\n            prev_token = next_batch\n\n            if not prev_token:\n                break\n\n        # We paginated backwards, so reverse\n        found_event_ids.reverse()\n        self.assertEquals(found_event_ids, expected_event_ids)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 689,
        "n_words": 148,
        "vocab_size": 66,
        "complexity": 10,
        "nloc": 48,
        "token_counts": 305,
        "n_ast_nodes": 544,
        "n_identifiers": 33,
        "d_id": 71143,
        "documentation": {
            "docstring": "Test that if we paginate using a limit and tokens then we get the\n        expected events.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 205011,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/mysql/schema.py",
        "file_name": "schema.py",
        "fun_name": "_delete_composed_index",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _delete_composed_index(self, model, fields, *args):\n        \n        first_field = model._meta.get_field(fields[0])\n        if first_field.get_internal_type() == \"ForeignKey\":\n            constraint_names = self._constraint_names(\n                model, [first_field.column], index=True\n            )\n            if not constraint_names:\n                self.execute(\n                    self._create_index_sql(model, fields=[first_field], suffix=\"\")\n                )\n        return super()._delete_composed_index(model, fields, *args)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 156,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 92,
        "n_ast_nodes": 145,
        "n_identifiers": 17,
        "d_id": 50995,
        "documentation": {
            "docstring": "\n        MySQL can remove an implicit FK index on a field when that field is\n        covered by another index like a unique_together. \"covered\" here means\n        that the more complex index starts like the simpler one.\n        https://bugs.mysql.com/bug.php?id=37910 / Django ticket #24757\n        We check here before removing the [unique|index]_together if we have to\n        recreate a FK index.\n        ",
            "n_words": 54,
            "vocab_size": 43,
            "n_whitespaces": 104,
            "language": "en"
        }
    },
    {
        "id": 293667,
        "commit_id": "21aa07e3e58268d6ca1425cd05abcfd847b9872c",
        "repo": "core",
        "path": "tests/components/zwave_js/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "climate_adc_t3000_missing_fan_mode_states_fixture",
        "commit_message": "Add Z-Wave thermostat fan entity (#65865)\n\n* Add Z-Wave thermostat fan entity\r\n\r\n* Fix failing test, increase number of entities to 27\r\n\r\n* Add tests to improve coverage\r\n\r\n* Take back unrelated changes to climate.py\r\n\r\n* Clean up guard clauses, use info.primary_value, and make entity disabled by default\r\n\r\n* Fix tests\r\n\r\n* Add more tests for code coverage\r\n\r\n* Remove unused const\r\n\r\n* Remove speed parameter from overridden method since it was removed from entity\r\n\r\n* Address PR comments",
        "code": "def climate_adc_t3000_missing_fan_mode_states_fixture(client, climate_adc_t3000_state):\n    \n    data = copy.deepcopy(climate_adc_t3000_state)\n    data[\"name\"] = f\"{data['name']} missing fan mode states\"\n    for value in data[\"values\"]:\n        if (\n            value[\"commandClassName\"] == \"Thermostat Fan Mode\"\n            and value[\"property\"] == \"mode\"\n        ):\n            del value[\"metadata\"][\"states\"]\n    node = Node(client, data)\n    client.driver.controller.nodes[node.node_id] = node\n    return node\n\n\n@pytest.fixture(name=\"climate_danfoss_lc_13\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(name=\"climate_danfoss_lc_13\")",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 108,
        "n_words": 41,
        "vocab_size": 35,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 80,
        "n_ast_nodes": 165,
        "n_identifiers": 16,
        "d_id": 92724,
        "documentation": {
            "docstring": "Mock a climate ADC-T3000 node with missing 'states' metadata on Thermostat Fan Mode.",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 107997,
        "commit_id": "4ea309aac5b6b638967d19107db297b5c7bde551",
        "repo": "matplotlib",
        "path": "lib/matplotlib/texmanager.py",
        "file_name": "texmanager.py",
        "fun_name": "get_basefile",
        "commit_message": "Pick TeX cache name based on entire TeX source.\n\nThis allows invalidating the cache when the source generation algorithm\nchanges.",
        "code": "def get_basefile(self, tex, fontsize, dpi=None):\n        \n        src = self._get_tex_source(tex, fontsize) + str(dpi)\n        return os.path.join(\n            self.texcache, hashlib.md5(src.encode('utf-8')).hexdigest())\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 47,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 56,
        "n_ast_nodes": 89,
        "n_identifiers": 16,
        "d_id": 23006,
        "documentation": {
            "docstring": "\n        Return a filename based on a hash of the string, fontsize, and dpi.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 73300,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/views.py",
        "file_name": "views.py",
        "fun_name": "get_dict_for_field",
        "commit_message": "Reformat with black",
        "code": "def get_dict_for_field(self, field_name):\n        \n        try:\n            field = self.model._meta.get_field(field_name)\n        except FieldDoesNotExist:\n            field = None\n        return {\n            \"label\": self.get_field_label(field_name, field),\n            \"value\": self.get_field_display_value(field_name, field),\n        }\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 100,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 53,
        "n_ast_nodes": 87,
        "n_identifiers": 10,
        "d_id": 16009,
        "documentation": {
            "docstring": "\n        Return a dictionary containing `label` and `value` values to display\n        for a field.\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 337070,
        "commit_id": "a73f8b725105b12a60a9b22918bda68f8b6d26c3",
        "repo": "diffusers",
        "path": "src/diffusers/models/resnet.py",
        "file_name": "resnet.py",
        "fun_name": "_upsample_2d",
        "commit_message": "Clean up resnet.py file (#780)\n\n* clean up resnet.py\r\n\r\n* make style and quality\r\n\r\n* minor formatting",
        "code": "def _upsample_2d(self, hidden_states, weight=None, kernel=None, factor=2, gain=1):\n        \n\n        assert isinstance(factor, int) and factor >= 1\n\n        # Setup filter kernel.\n        if kernel is None:\n            kernel = [1] * factor\n\n        # setup kernel\n        kernel = torch.tensor(kernel, dtype=torch.float32)\n        if kernel.ndim == 1:\n            kernel = torch.outer(kernel, kernel)\n        kernel /= torch.sum(kernel)\n\n        kernel = kernel * (gain * (factor**2))\n\n        if self.use_conv:\n            convH = weight.shape[2]\n            convW = weight.shape[3]\n            inC = weight.shape[1]\n\n            pad_value = (kernel.shape[0] - factor) - (convW - 1)\n\n            stride = (factor, factor)\n            # Determine data dimensions.\n            output_shape = (\n                (hidden_states.shape[2] - 1) * factor + convH,\n                (hidden_states.shape[3] - 1) * factor + convW,\n            )\n            output_padding = (\n                output_shape[0] - (hidden_states.shape[2] - 1) * stride[0] - convH,\n                output_shape[1] - (hidden_states.shape[3] - 1) * stride[1] - convW,\n            )\n            assert output_padding[0] >= 0 and output_padding[1] >= 0\n            num_groups = hidden_states.shape[1] // inC\n\n            # Transpose weights.\n            weight = torch.reshape(weight, (num_groups, -1, inC, convH, convW))\n            weight = torch.flip(weight, dims=[3, 4]).permute(0, 2, 1, 3, 4)\n            weight = torch.reshape(weight, (num_groups * inC, -1, convH, convW))\n\n            inverse_conv = F.conv_transpose2d(\n                hidden_states, weight, stride=stride, output_padding=output_padding, padding=0\n            )\n\n            output = upfirdn2d_native(\n                inverse_conv,\n                torch.tensor(kernel, device=inverse_conv.device),\n                pad=((pad_value + 1) // 2 + factor - 1, pad_value // 2 + 1),\n            )\n        else:\n            pad_value = kernel.shape[0] - factor\n            output = upfirdn2d_native(\n                hidden_states,\n                torch.tensor(kernel, device=hidden_states.device),\n                up=factor,\n                pad=((pad_value + 1) // 2 + factor - 1, pad_value // 2),\n            )\n\n        return output\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 759,
        "n_words": 220,
        "vocab_size": 109,
        "complexity": 6,
        "nloc": 45,
        "token_counts": 430,
        "n_ast_nodes": 660,
        "n_identifiers": 39,
        "d_id": 120955,
        "documentation": {
            "docstring": "Fused `upsample_2d()` followed by `Conv2d()`.\n\n        Padding is performed only once at the beginning, not between the operations. The fused op is considerably more\n        efficient than performing the same calculation using standard TensorFlow ops. It supports gradients of\n        arbitrary order.\n\n        Args:\n            hidden_states: Input tensor of the shape `[N, C, H, W]` or `[N, H, W, C]`.\n            weight: Weight tensor of the shape `[filterH, filterW, inChannels,\n                outChannels]`. Grouped convolution can be performed by `inChannels = x.shape[0] // numGroups`.\n            kernel: FIR filter of the shape `[firH, firW]` or `[firN]`\n                (separable). The default is `[1] * factor`, which corresponds to nearest-neighbor upsampling.\n            factor: Integer upsampling factor (default: 2).\n            gain: Scaling factor for signal magnitude (default: 1.0).\n\n        Returns:\n            output: Tensor of the shape `[N, C, H * factor, W * factor]` or `[N, H * factor, W * factor, C]`, and same\n            datatype as `hidden_states`.\n        ",
            "n_words": 140,
            "vocab_size": 103,
            "n_whitespaces": 289,
            "language": "en"
        }
    },
    {
        "id": 125203,
        "commit_id": "adf24bfa9723b0621183bb27f0c889b813c06e8a",
        "repo": "ray",
        "path": "python/ray/_private/thirdparty/tabulate/tabulate.py",
        "file_name": "tabulate.py",
        "fun_name": "_update_lines",
        "commit_message": "[State Observability] Use a table format by default (#26159)\n\nNOTE: tabulate is copied/pasted to the codebase for table formatting.\r\n\r\nThis PR changes the default layout to be the table format for both summary and list APIs.",
        "code": "def _update_lines(self, lines, new_line):\n        \n        code_matches = [x for x in re.finditer(_invisible_codes, new_line)]\n        color_codes = [\n            code.string[code.span()[0] : code.span()[1]] for code in code_matches\n        ]\n\n        # Add color codes from earlier in the unwrapped line, and then track any new ones we add.\n        new_line = \"\".join(self._active_codes) + new_line\n\n        for code in color_codes:\n            if code != _ansi_color_reset_code:\n                self._active_codes.append(code)\n            else:  # A single reset code resets everything\n                self._active_codes = []\n\n        # Always ensure each line is color terminted if any colors are\n        # still active, otherwise colors will bleed into other cells on the console\n        if len(self._active_codes) > 0:\n            new_line = new_line + _ansi_color_reset_code\n\n        lines.append(new_line)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 253,
        "n_words": 101,
        "vocab_size": 75,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 115,
        "n_ast_nodes": 186,
        "n_identifiers": 18,
        "d_id": 27807,
        "documentation": {
            "docstring": "Adds a new line to the list of lines the text is being wrapped into\n        This function will also track any ANSI color codes in this string as well\n        as add any colors from previous lines order to preserve the same formatting\n        as a single unwrapped string.\n        ",
            "n_words": 47,
            "vocab_size": 39,
            "n_whitespaces": 75,
            "language": "en"
        }
    },
    {
        "id": 260641,
        "commit_id": "6e5ef2e9b8c64e6788428610ae884b9bf3d298a2",
        "repo": "scikit-learn",
        "path": "sklearn/feature_selection/_rfe.py",
        "file_name": "_rfe.py",
        "fun_name": "score",
        "commit_message": "MAINT solve long line reported by flake8 (#24065)",
        "code": "def score(self, X, y, **fit_params):\n        \n        check_is_fitted(self)\n        return self.estimator_.score(self.transform(X), y, **fit_params)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 36,
        "n_ast_nodes": 56,
        "n_identifiers": 8,
        "d_id": 76391,
        "documentation": {
            "docstring": "Reduce X to the selected features and return the score of the estimator.\n\n        Parameters\n        ----------\n        X : array of shape [n_samples, n_features]\n            The input samples.\n\n        y : array of shape [n_samples]\n            The target values.\n\n        **fit_params : dict\n            Parameters to pass to the `score` method of the underlying\n            estimator.\n\n            .. versionadded:: 1.0\n\n        Returns\n        -------\n        score : float\n            Score of the underlying base estimator computed with the selected\n            features returned by `rfe.transform(X)` and `y`.\n        ",
            "n_words": 72,
            "vocab_size": 46,
            "n_whitespaces": 212,
            "language": "en"
        }
    },
    {
        "id": 177986,
        "commit_id": "53f6308186aa131946e196b0409f3d732ec9e007",
        "repo": "label-studio",
        "path": "label_studio/data_import/uploader.py",
        "file_name": "uploader.py",
        "fun_name": "allowlist_svg",
        "commit_message": "fix: DEV-2236: Stored XSS via SVG file (#2273)\n\n* user uploaded content rendered as plain text or known image only\r\n\r\n* allow list for svg in progress\r\n\r\n* allow list for svg basic pass\r\n\r\n* add error handling\r\n\r\n* add to file processing re: code review\r\n\r\n* rm uneeded code\r\n\r\n* add env var to disable svg cleaning\r\n\r\n* add test\r\n\r\n* update env setting\r\n\r\n* rm lxml string methods\r\n\r\n* Update uploader.py\r\n\r\n* Update base.py\r\n\r\nCo-authored-by: Max Tkachenko <makseq@gmail.com>",
        "code": "def allowlist_svg(dirty_xml):\n    \n    from lxml.html import clean\n\n    allow_tags = [\n            'xml',\n            'svg',\n            'circle',\n            'ellipse',\n            'line',\n            'path',\n            'polygon',\n            'polyline',\n            'rect'\n    ]\n\n    cleaner = clean.Cleaner(\n            allow_tags=allow_tags,\n            style=True,\n            links=True,\n            add_nofollow=False,\n            page_structure=True,\n            safe_attrs_only=False,\n            remove_unknown_tags=False)\n\n    clean_xml = cleaner.clean_html(dirty_xml)\n    return clean_xml\n\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 231,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 77,
        "n_ast_nodes": 126,
        "n_identifiers": 16,
        "d_id": 42555,
        "documentation": {
            "docstring": "Filter out malicious/harmful content from SVG files\n    by defining allowed tags\n    ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 181731,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/tpot_tests.py",
        "file_name": "tpot_tests.py",
        "fun_name": "test_save_periodic_pipeline",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_save_periodic_pipeline():\n    \n    tpot_obj = TPOTClassifier(\n        random_state=42,\n        population_size=1,\n        offspring_size=2,\n        generations=1,\n        verbosity=0,\n        config_dict='TPOT light'\n    )\n    tpot_obj.fit(training_features, training_target)\n    with closing(StringIO()) as our_file:\n        tpot_obj.log_file_ = our_file\n        tpot_obj.verbosity = 3\n        tpot_obj._last_pipeline_write = datetime.now()\n        sleep(0.11)\n        tpot_obj._output_best_pipeline_period_seconds = 0.1\n        tmpdir = mkdtemp() + '/'\n        tpot_obj.periodic_checkpoint_folder = tmpdir\n        # reset _pareto_front to rasie exception\n        tpot_obj._pareto_front = None\n\n        tpot_obj._save_periodic_pipeline(1)\n        our_file.seek(0)\n\n        assert_in('Failed saving periodic pipeline, exception', our_file.read())\n        #clean up\n        rmtree(tmpdir)\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 215,
        "n_words": 60,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 126,
        "n_ast_nodes": 207,
        "n_identifiers": 30,
        "d_id": 43518,
        "documentation": {
            "docstring": "Assert that the _save_periodic_pipeline does not export periodic pipeline if exception happened",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 222361,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/datetime.py",
        "file_name": "datetime.py",
        "fun_name": "tzname",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def tzname(self):\n        \n        if self._tzinfo is None:\n            return None\n        name = self._tzinfo.tzname(None)\n        _check_tzname(name)\n        return name\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 60,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 31,
        "n_ast_nodes": 53,
        "n_identifiers": 5,
        "d_id": 56547,
        "documentation": {
            "docstring": "Return the timezone name.\n\n        Note that the name is 100% informational -- there's no requirement that\n        it mean anything in particular. For example, \"GMT\", \"UTC\", \"-500\",\n        \"-5:00\", \"EDT\", \"US/Eastern\", \"America/New York\" are all valid replies.\n        ",
            "n_words": 35,
            "vocab_size": 33,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 25192,
        "commit_id": "1f9400dd7374ce9cc47981372e324ff412e53ba3",
        "repo": "PaddleOCR",
        "path": "ppocr/losses/det_drrg_loss.py",
        "file_name": "det_drrg_loss.py",
        "fun_name": "gcn_loss",
        "commit_message": "add drrg",
        "code": "def gcn_loss(self, gcn_data):\n        \n        gcn_pred, gt_labels = gcn_data\n        gt_labels = gt_labels.reshape([-1])\n        loss = F.cross_entropy(gcn_pred, gt_labels)\n\n        return loss\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 51,
        "n_words": 16,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 36,
        "n_ast_nodes": 59,
        "n_identifiers": 9,
        "d_id": 4861,
        "documentation": {
            "docstring": "CrossEntropy Loss from gcn module.\n\n        Args:\n            gcn_data (tuple(Tensor, Tensor)): The first is the\n                prediction with shape :math:`(N, 2)` and the\n                second is the gt label with shape :math:`(m, n)`\n                where :math:`m * n = N`.\n\n        Returns:\n            Tensor: CrossEntropy loss.\n        ",
            "n_words": 39,
            "vocab_size": 33,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 206572,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/cache.py",
        "file_name": "cache.py",
        "fun_name": "add_never_cache_headers",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def add_never_cache_headers(response):\n    \n    patch_response_headers(response, cache_timeout=-1)\n    patch_cache_control(\n        response, no_cache=True, no_store=True, must_revalidate=True, private=True\n    )\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 30,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 35,
        "n_ast_nodes": 54,
        "n_identifiers": 9,
        "d_id": 51571,
        "documentation": {
            "docstring": "\n    Add headers to a response to indicate that a page should never be cached.\n    ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 137797,
        "commit_id": "8e680c483ce326cefc62e44f68ab1a6948b1c3d2",
        "repo": "ray",
        "path": "rllib/evaluation/tests/test_postprocessing.py",
        "file_name": "test_postprocessing.py",
        "fun_name": "test_n_step_very_short_trajectory",
        "commit_message": "[RLlib] gymnasium support (new `Env.reset()/step()/seed()/render()` APIs). (#28369)",
        "code": "def test_n_step_very_short_trajectory(self):\n        \n        gamma = 1.0\n        obs = np.arange(0, 2)\n        actions = np.random.randint(-100, 300, size=(2,))\n        check_actions = actions.copy()\n        rewards = [10.0, 100.0]\n        next_obs = np.arange(1, 3)\n        batch = SampleBatch(\n            {\n                SampleBatch.OBS: obs,\n                SampleBatch.ACTIONS: actions,\n                SampleBatch.REWARDS: rewards,\n                SampleBatch.TERMINATEDS: [False, False],\n                SampleBatch.TRUNCATEDS: [False, False],\n                SampleBatch.NEXT_OBS: next_obs,\n            }\n        )\n        adjust_nstep(3, gamma, batch)\n        check(batch[SampleBatch.OBS], [0, 1])\n        check(batch[SampleBatch.ACTIONS], check_actions)\n        check(batch[SampleBatch.TERMINATEDS], [False, False])\n        check(batch[SampleBatch.TRUNCATEDS], [False, False])\n        check(batch[SampleBatch.REWARDS], [10.0 + gamma * 100.0, 100.0])\n        check(batch[SampleBatch.NEXT_OBS], [2, 2])\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 293,
        "n_words": 69,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 224,
        "n_ast_nodes": 307,
        "n_identifiers": 24,
        "d_id": 31248,
        "documentation": {
            "docstring": "Tests, whether n-step also works for very small trajectories.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 204926,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/schema.py",
        "file_name": "schema.py",
        "fun_name": "_create_index_name",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _create_index_name(self, table_name, column_names, suffix=\"\"):\n        \n        _, table_name = split_identifier(table_name)\n        hash_suffix_part = \"%s%s\" % (\n            names_digest(table_name, *column_names, length=8),\n            suffix,\n        )\n        max_length = self.connection.ops.max_name_length() or 200\n        # If everything fits into max_length, use that name.\n        index_name = \"%s_%s_%s\" % (table_name, \"_\".join(column_names), hash_suffix_part)\n        if len(index_name) <= max_length:\n            return index_name\n        # Shorten a long suffix.\n        if len(hash_suffix_part) > max_length / 3:\n            hash_suffix_part = hash_suffix_part[: max_length // 3]\n        other_length = (max_length - len(hash_suffix_part)) // 2 - 1\n        index_name = \"%s_%s_%s\" % (\n            table_name[:other_length],\n            \"_\".join(column_names)[:other_length],\n            hash_suffix_part,\n        )\n        # Prepend D if needed to prevent the name from starting with an\n        # underscore or a number (not permitted on Oracle).\n        if index_name[0] == \"_\" or index_name[0].isdigit():\n            index_name = \"D%s\" % index_name[:-1]\n        return index_name\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 323,
        "n_words": 116,
        "vocab_size": 84,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 163,
        "n_ast_nodes": 276,
        "n_identifiers": 19,
        "d_id": 50980,
        "documentation": {
            "docstring": "\n        Generate a unique name for an index/unique constraint.\n\n        The name is divided into 3 parts: the table name, the column names,\n        and a unique digest and suffix.\n        ",
            "n_words": 27,
            "vocab_size": 22,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 73800,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "approve",
        "commit_message": "Reformat with black",
        "code": "def approve(self, user=None, update=True, comment=\"\"):\n        \n        if self.status != self.STATUS_IN_PROGRESS:\n            raise PermissionDenied\n        self.status = self.STATUS_APPROVED\n        self.finished_at = timezone.now()\n        self.finished_by = user\n        self.comment = comment\n        self.save()\n\n        self.log_state_change_action(user, \"approve\")\n        if update:\n            self.workflow_state.update(user=user)\n        task_approved.send(\n            sender=self.specific.__class__, instance=self.specific, user=user\n        )\n        return self\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 153,
        "n_words": 36,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 105,
        "n_ast_nodes": 168,
        "n_identifiers": 22,
        "d_id": 16117,
        "documentation": {
            "docstring": "Approve the task state and update the workflow state",
            "n_words": 9,
            "vocab_size": 7,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 275527,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_v2/optimizer_v2.py",
        "file_name": "optimizer_v2.py",
        "fun_name": "minimize",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def minimize(self, loss, var_list, grad_loss=None, name=None, tape=None):\n        \n        grads_and_vars = self._compute_gradients(\n            loss, var_list=var_list, grad_loss=grad_loss, tape=tape\n        )\n        return self.apply_gradients(grads_and_vars, name=name)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 53,
        "n_ast_nodes": 76,
        "n_identifiers": 10,
        "d_id": 81417,
        "documentation": {
            "docstring": "Minimize `loss` by updating `var_list`.\n\n        This method simply computes gradient using `tf.GradientTape` and calls\n        `apply_gradients()`. If you want to process the gradient before applying\n        then call `tf.GradientTape` and `apply_gradients()` explicitly instead\n        of using this function.\n\n        Args:\n          loss: `Tensor` or callable. If a callable, `loss` should take no arguments\n            and return the value to minimize. If a `Tensor`, the `tape` argument\n            must be passed.\n          var_list: list or tuple of `Variable` objects to update to minimize\n            `loss`, or a callable returning the list or tuple of `Variable` objects.\n            Use callable when the variable list would otherwise be incomplete before\n            `minimize` since the variables are created at the first time `loss` is\n            called.\n          grad_loss: (Optional). A `Tensor` holding the gradient computed for\n            `loss`.\n          name: (Optional) str. Name for the returned operation.\n          tape: (Optional) `tf.GradientTape`. If `loss` is provided as a `Tensor`,\n            the tape that computed the `loss` must be provided.\n\n        Returns:\n          An `Operation` that updates the variables in `var_list`. The `iterations`\n          will be automatically increased by 1.\n\n        Raises:\n          ValueError: If some of the variables are not `Variable` objects.\n\n        ",
            "n_words": 175,
            "vocab_size": 113,
            "n_whitespaces": 391,
            "language": "en"
        }
    },
    {
        "id": 8165,
        "commit_id": "5a25d1f2a914c849cf978573c5993411151bc447",
        "repo": "ludwig",
        "path": "tests/integration_tests/test_cli.py",
        "file_name": "test_cli.py",
        "fun_name": "test_render_config",
        "commit_message": "Added tests for init_config and render_config CLI commands (#2551)",
        "code": "def test_render_config(tmpdir):\n    \n    user_config_path = os.path.join(tmpdir, \"config.yaml\")\n    input_features = [\n        number_feature(),\n        number_feature(),\n        category_feature(encoder={\"vocab_size\": 3}),\n        category_feature(encoder={\"vocab_size\": 3}),\n    ]\n    output_features = [category_feature(decoder={\"vocab_size\": 3})]\n\n    user_config = {\n        INPUT_FEATURES: input_features,\n        OUTPUT_FEATURES: output_features,\n    }\n\n    with open(user_config_path, \"w\") as f:\n        yaml.dump(user_config, f)\n\n    output_config_path = os.path.join(tmpdir, \"rendered.yaml\")\n    _run_ludwig(\"render_config\", config=user_config_path, output=output_config_path)\n\n    rendered_config = load_yaml(output_config_path)\n    assert len(rendered_config[INPUT_FEATURES]) == len(user_config[INPUT_FEATURES])\n    assert len(rendered_config[OUTPUT_FEATURES]) == len(user_config[OUTPUT_FEATURES])\n    assert TRAINER in rendered_config\n    assert COMBINER in rendered_config\n    assert PREPROCESSING in rendered_config\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 162,
        "n_words": 65,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 170,
        "n_ast_nodes": 276,
        "n_identifiers": 29,
        "d_id": 1363,
        "documentation": {
            "docstring": "Test rendering a full config from a partial user config.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 167373,
        "commit_id": "7d2f9b8d59908fbf57c6453bc41891efbfe981a6",
        "repo": "pandas",
        "path": "pandas/io/pytables.py",
        "file_name": "pytables.py",
        "fun_name": "update_info",
        "commit_message": "TYP: some return annotations in pytables.py (#47512)",
        "code": "def update_info(self, info) -> None:\n        \n        for key in self._info_fields:\n\n            value = getattr(self, key, None)\n            idx = info.setdefault(self.name, {})\n\n            existing_value = idx.get(key)\n            if key in idx and value is not None and existing_value != value:\n                # frequency/name just warn\n                if key in [\"freq\", \"index_name\"]:\n                    ws = attribute_conflict_doc % (key, existing_value, value)\n                    warnings.warn(\n                        ws, AttributeConflictWarning, stacklevel=find_stack_level()\n                    )\n\n                    # reset\n                    idx[key] = None\n                    setattr(self, key, None)\n\n                else:\n                    raise ValueError(\n                        f\"invalid info for [{self.name}] for [{key}], \"\n                        f\"existing_value [{existing_value}] conflicts with \"\n                        f\"new value [{value}]\"\n                    )\n            else:\n                if value is not None or existing_value is not None:\n                    idx[key] = value\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 488,
        "n_words": 96,
        "vocab_size": 61,
        "complexity": 8,
        "nloc": 26,
        "token_counts": 141,
        "n_ast_nodes": 240,
        "n_identifiers": 21,
        "d_id": 39980,
        "documentation": {
            "docstring": "\n        set/update the info for this indexable with the key/value\n        if there is a conflict raise/warn as needed\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 262317,
        "commit_id": "1425a023fe4bc6bda8578295aeeeb02af78cc082",
        "repo": "TTS",
        "path": "TTS/tts/datasets/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "split_dataset",
        "commit_message": "Make style and lint",
        "code": "def split_dataset(items, eval_split_max_size=None, eval_split_size=0.01):\n    \n    speakers = [item[\"speaker_name\"] for item in items]\n    is_multi_speaker = len(set(speakers)) > 1\n    if eval_split_size > 1:\n        eval_split_size = int(eval_split_size)\n    else:\n        if eval_split_max_size:\n            eval_split_size = min(eval_split_max_size, int(len(items) * eval_split_size))\n        else:\n            eval_split_size = int(len(items) * eval_split_size)\n\n    assert (\n        eval_split_size > 0\n    ), \" [!] You do not have enough samples for the evaluation set. You can work around this setting the 'eval_split_size' parameter to a minimum of {}\".format(\n        1 / len(items)\n    )\n    np.random.seed(0)\n    np.random.shuffle(items)\n    if is_multi_speaker:\n        items_eval = []\n        speakers = [item[\"speaker_name\"] for item in items]\n        speaker_counter = Counter(speakers)\n        while len(items_eval) < eval_split_size:\n            item_idx = np.random.randint(0, len(items))\n            speaker_to_be_removed = items[item_idx][\"speaker_name\"]\n            if speaker_counter[speaker_to_be_removed] > 1:\n                items_eval.append(items[item_idx])\n                speaker_counter[speaker_to_be_removed] -= 1\n                del items[item_idx]\n        return items_eval, items\n    return items[:eval_split_size], items[eval_split_size:]\n\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 324,
        "n_words": 118,
        "vocab_size": 82,
        "complexity": 8,
        "nloc": 30,
        "token_counts": 219,
        "n_ast_nodes": 347,
        "n_identifiers": 23,
        "d_id": 77180,
        "documentation": {
            "docstring": "Split a dataset into train and eval. Consider speaker distribution in multi-speaker training.\n\n        Args:\n    <<<<<<< HEAD\n            items (List[List]):\n                A list of samples. Each sample is a list of `[audio_path, text, speaker_id]`.\n\n            eval_split_max_size (int):\n                Number maximum of samples to be used for evaluation in proportion split. Defaults to None (Disabled).\n\n            eval_split_size (float):\n                If between 0.0 and 1.0 represents the proportion of the dataset to include in the evaluation set.\n                If > 1, represents the absolute number of evaluation samples. Defaults to 0.01 (1%).\n    =======\n            items (List[List]): A list of samples. Each sample is a list of `[text, audio_path, speaker_id]`.\n    >>>>>>> Fix docstring\n    ",
            "n_words": 101,
            "vocab_size": 65,
            "n_whitespaces": 224,
            "language": "en"
        }
    },
    {
        "id": 177081,
        "commit_id": "28f78cfa9a386620ee1179582fda1db5ffc59f84",
        "repo": "networkx",
        "path": "networkx/algorithms/distance_measures.py",
        "file_name": "distance_measures.py",
        "fun_name": "center",
        "commit_message": "Add weight distance metrics (#5305)\n\nAdds the weight keyword argument to allow users to compute weighted distance metrics\r\ne.g. diameter, eccentricity, periphery, etc. The kwarg works in the same fashion as the\r\nweight param for shortest paths - i.e. if a string, look up with edge attr by key, if callable,\r\ncompute the weight via the function. Default is None, meaning return unweighted result\r\nwhich is the current behavior.\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def center(G, e=None, usebounds=False, weight=None):\n    \n    if usebounds is True and e is None and not G.is_directed():\n        return _extrema_bounding(G, compute=\"center\", weight=weight)\n    if e is None:\n        e = eccentricity(G, weight=weight)\n    radius = min(e.values())\n    p = [v for v in e if e[v] == radius]\n    return p\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 76,
        "n_words": 44,
        "vocab_size": 31,
        "complexity": 7,
        "nloc": 8,
        "token_counts": 90,
        "n_ast_nodes": 140,
        "n_identifiers": 14,
        "d_id": 42268,
        "documentation": {
            "docstring": "Returns the center of the graph G.\n\n    The center is the set of nodes with eccentricity equal to radius.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n       A graph\n\n    e : eccentricity dictionary, optional\n      A precomputed dictionary of eccentricities.\n\n    weight : string, function, or None\n        If this is a string, then edge weights will be accessed via the\n        edge attribute with this key (that is, the weight of the edge\n        joining `u` to `v` will be ``G.edges[u, v][weight]``). If no\n        such edge attribute exists, the weight of the edge is assumed to\n        be one.\n\n        If this is a function, the weight of an edge is the value\n        returned by the function. The function must accept exactly three\n        positional arguments: the two endpoints of an edge and the\n        dictionary of edge attributes for that edge. The function must\n        return a number.\n\n        If this is None, every edge has weight/distance/cost 1.\n\n        Weights stored as floating point values can lead to small round-off\n        errors in distances. Use integer weights to avoid this.\n\n        Weights should be positive, since they are distances.\n\n    Returns\n    -------\n    c : list\n       List of nodes in center\n\n    Examples\n    --------\n    >>> G = nx.Graph([(1, 2), (1, 3), (1, 4), (3, 4), (3, 5), (4, 5)])\n    >>> list(nx.center(G))\n    [1, 3, 4]\n\n    See Also\n    --------\n    barycenter\n    periphery\n    ",
            "n_words": 212,
            "vocab_size": 129,
            "n_whitespaces": 384,
            "language": "en"
        }
    },
    {
        "id": 102252,
        "commit_id": "8e6d1738a41cb28c36db3dc5e10fd812417673de",
        "repo": "pytorch",
        "path": "torch/jit/_recursive.py",
        "file_name": "_recursive.py",
        "fun_name": "infer_concrete_type_builder",
        "commit_message": "Per-overload torch.ops API (#67254)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/67254\n\nFixes https://github.com/pytorch/pytorch/issues/65997\n\nTODO: disallow `default` as an overload name for aten operators.\n\nBC breaking:\n`output = torch.ops._test.leaky_relu(self=torch.tensor(-1.0))` now fails with the error `TypeError: __call__() got multiple values for argument 'self'` since we call into `OpOverloadBundle`'s `__call__` method that has `self` bound to it as its first argument.\n\ncc ezyang gchanan\n\nTest Plan: Imported from OSS\n\nReviewed By: albanD\n\nDifferential Revision: D33262228\n\nPulled By: anjali411\n\nfbshipit-source-id: 600dbf511514ea9b41aea3e6b1bc1102dab08909",
        "code": "def infer_concrete_type_builder(nn_module, share_types=True):\n    \n    concrete_type_builder = torch._C.ConcreteModuleTypeBuilder(type(nn_module))\n    if isinstance(nn_module, (torch.nn.ModuleDict)):\n        concrete_type_builder.set_module_dict()\n    if isinstance(nn_module, (torch.nn.ModuleList, torch.nn.Sequential)):\n        concrete_type_builder.set_module_list()\n\n    class_annotations = getattr(nn_module, '__annotations__', {})\n    if isinstance(nn_module, (torch.ao.quantization.QuantWrapper)):\n        class_annotations = {}\n\n    # Get user-annotated ignored attributes.\n    user_annotated_ignored_attributes = getattr(nn_module, \"__jit_ignored_attributes__\", list())\n    concrete_type_builder.add_ignored_attributes(user_annotated_ignored_attributes)\n    ignored_properties = jit_ignored_properties(nn_module)\n\n    # try to infer the type from type annotation or from the object itself",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "vocab_size": 40,
        "complexity": 37,
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        "token_counts": 846,
        "n_ast_nodes": 198,
        "n_identifiers": 25,
        "d_id": 21503,
        "documentation": {
            "docstring": "\n    Build a ConcreteModuleTypeBuilder from an nn.Module. This\n    ConcreteModuleType doesn't have a JIT type associated with it yet, it\n    must be filled in by the caller.\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 176415,
        "commit_id": "8f4c99debc9440728c5e85f8bffa5d26b232eb6f",
        "repo": "networkx",
        "path": "networkx/classes/multigraph.py",
        "file_name": "multigraph.py",
        "fun_name": "to_undirected",
        "commit_message": "Multigraph docs update (#5389)\n\n* Updated MultiDiGraph documentation to include more examples of actually\r\nusing parallel edges, and fixed references to things like G[u, v] where\r\nG[u, v, k] is required for a MultiDigraph. Have not made parallel\r\nchanges in MultiGraph which should maybe also be made?\r\n\r\nDocs tests pass on my end; no code outside of comments was changed.\r\n\r\n-Peter Mawhorter\r\n\r\n* Updated docs for MultiGraph to add more multigraph-specific examples and\r\nfix a few places where untested examples were wrong.\r\n\r\n-Peter Mawhorter\r\n\r\n* [DOC] fix typo\r\n\r\n* add the right amount of separators\r\n\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>",
        "code": "def to_undirected(self, as_view=False):\n        \n        graph_class = self.to_undirected_class()\n        if as_view is True:\n            return nx.graphviews.generic_graph_view(self, graph_class)\n        # deepcopy when not a view\n        G = graph_class()\n        G.graph.update(deepcopy(self.graph))\n        G.add_nodes_from((n, deepcopy(d)) for n, d in self._node.items())\n        G.add_edges_from(\n            (u, v, key, deepcopy(datadict))\n            for u, nbrs in self._adj.items()\n            for v, keydict in nbrs.items()\n            for key, datadict in keydict.items()\n        )\n        return G\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 178,
        "n_words": 53,
        "vocab_size": 42,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 127,
        "n_ast_nodes": 198,
        "n_identifiers": 25,
        "d_id": 41880,
        "documentation": {
            "docstring": "Returns an undirected copy of the graph.\n\n        Returns\n        -------\n        G : Graph/MultiGraph\n            A deepcopy of the graph.\n\n        See Also\n        --------\n        copy, add_edge, add_edges_from\n\n        Notes\n        -----\n        This returns a \"deepcopy\" of the edge, node, and\n        graph attributes which attempts to completely copy\n        all of the data and references.\n\n        This is in contrast to the similar `G = nx.MultiGraph(D)`\n        which returns a shallow copy of the data.\n\n        See the Python copy module for more information on shallow\n        and deep copies, https://docs.python.org/3/library/copy.html.\n\n        Warning: If you have subclassed MultiGraph to use dict-like\n        objects in the data structure, those changes do not transfer\n        to the MultiGraph created by this method.\n\n        Examples\n        --------\n        >>> G = nx.MultiGraph([(0, 1), (0, 1), (1, 2)])\n        >>> H = G.to_directed()\n        >>> list(H.edges)\n        [(0, 1, 0), (0, 1, 1), (1, 0, 0), (1, 0, 1), (1, 2, 0), (2, 1, 0)]\n        >>> G2 = H.to_undirected()\n        >>> list(G2.edges)\n        [(0, 1, 0), (0, 1, 1), (1, 2, 0)]\n        ",
            "n_words": 155,
            "vocab_size": 94,
            "n_whitespaces": 362,
            "language": "en"
        }
    },
    {
        "id": 110265,
        "commit_id": "9b6abd0b4933811e0a45c2535ab8fd107db65dd9",
        "repo": "matplotlib",
        "path": "lib/matplotlib/colors.py",
        "file_name": "colors.py",
        "fun_name": "rgb_to_hsv",
        "commit_message": "DOC: improve grammar and consistency",
        "code": "def rgb_to_hsv(arr):\n    \n    arr = np.asarray(arr)\n\n    # check length of the last dimension, should be _some_ sort of rgb\n    if arr.shape[-1] != 3:\n        raise ValueError(\"Last dimension of input array must be 3; \"\n                         \"shape {} was found.\".format(arr.shape))\n\n    in_shape = arr.shape\n    arr = np.array(\n        arr, copy=False,\n        dtype=np.promote_types(arr.dtype, np.float32),  # Don't work on ints.\n        ndmin=2,  # In case input was 1D.\n    )\n    out = np.zeros_like(arr)\n    arr_max = arr.max(-1)\n    ipos = arr_max > 0\n    delta = arr.ptp(-1)\n    s = np.zeros_like(delta)\n    s[ipos] = delta[ipos] / arr_max[ipos]\n    ipos = delta > 0\n    # red is max\n    idx = (arr[..., 0] == arr_max) & ipos\n    out[idx, 0] = (arr[idx, 1] - arr[idx, 2]) / delta[idx]\n    # green is max\n    idx = (arr[..., 1] == arr_max) & ipos\n    out[idx, 0] = 2. + (arr[idx, 2] - arr[idx, 0]) / delta[idx]\n    # blue is max\n    idx = (arr[..., 2] == arr_max) & ipos\n    out[idx, 0] = 4. + (arr[idx, 0] - arr[idx, 1]) / delta[idx]\n\n    out[..., 0] = (out[..., 0] / 6.0) % 1.0\n    out[..., 1] = s\n    out[..., 2] = arr_max\n\n    return out.reshape(in_shape)\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 310,
        "n_words": 175,
        "vocab_size": 95,
        "complexity": 2,
        "nloc": 28,
        "token_counts": 308,
        "n_ast_nodes": 452,
        "n_identifiers": 24,
        "d_id": 24007,
        "documentation": {
            "docstring": "\n    Convert float RGB values (in the range [0, 1]), in a numpy array to HSV\n    values.\n\n    Parameters\n    ----------\n    arr : (..., 3) array-like\n       All values must be in the range [0, 1]\n\n    Returns\n    -------\n    (..., 3) ndarray\n       Colors converted to HSV values in range [0, 1]\n    ",
            "n_words": 46,
            "vocab_size": 32,
            "n_whitespaces": 86,
            "language": "en"
        }
    },
    {
        "id": 128493,
        "commit_id": "c8dbbf374661d89e620b472a8c62aa3ce3c6ce98",
        "repo": "ray",
        "path": "rllib/utils/nested_dict.py",
        "file_name": "nested_dict.py",
        "fun_name": "__len__",
        "commit_message": "[RLlib] Introduction of Nested dict for RLModule construction (#29027)\n\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def __len__(self) -> int:\n        \n\n        # do a DFS to count the number of leaf nodes\n        count = 0\n        stack = [self._data]\n        while stack:\n            node = stack.pop()\n            if isinstance(node, NestedDict):\n                node = node._data\n            if isinstance(node, Mapping):\n                stack.extend(node.values())\n            else:\n                count += 1\n\n        return count\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 173,
        "n_words": 42,
        "vocab_size": 33,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 66,
        "n_ast_nodes": 111,
        "n_identifiers": 13,
        "d_id": 28718,
        "documentation": {
            "docstring": "Returns the number of leaf nodes in the `NestedDict` that\n        are not of type Mappings.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 152620,
        "commit_id": "8deae077004f0332ca607fc3a5d568b1a4705bec",
        "repo": "stable-diffusion-webui",
        "path": "modules/scunet_model_arch.py",
        "file_name": "scunet_model_arch.py",
        "fun_name": "generate_mask",
        "commit_message": "Add ScuNET DeNoiser/Upscaler\n\nQ&D Implementation of ScuNET, thanks to our handy model loader. :P\n\nhttps://github.com/cszn/SCUNet",
        "code": "def generate_mask(self, h, w, p, shift):\n        \n        # supporting sqaure.\n        attn_mask = torch.zeros(h, w, p, p, p, p, dtype=torch.bool, device=self.relative_position_params.device)\n        if self.type == 'W':\n            return attn_mask\n\n        s = p - shift\n        attn_mask[-1, :, :s, :, s:, :] = True\n        attn_mask[-1, :, s:, :, :s, :] = True\n        attn_mask[:, -1, :, :s, :, s:] = True\n        attn_mask[:, -1, :, s:, :, :s] = True\n        attn_mask = rearrange(attn_mask, 'w1 w2 p1 p2 p3 p4 -> 1 1 (w1 w2) (p1 p2) (p3 p4)')\n        return attn_mask\n",
        "url": "https://github.com/AUTOMATIC1111/stable-diffusion-webui.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 170,
        "n_words": 82,
        "vocab_size": 48,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 146,
        "n_ast_nodes": 217,
        "n_identifiers": 16,
        "d_id": 35189,
        "documentation": {
            "docstring": " generating the mask of SW-MSA\n        Args:\n            shift: shift parameters in CyclicShift.\n        Returns:\n            attn_mask: should be (1 1 w p p),\n        ",
            "n_words": 20,
            "vocab_size": 20,
            "n_whitespaces": 64,
            "language": "en"
        }
    },
    {
        "id": 122164,
        "commit_id": "0cc4066bb7bf758a5ba8c5def9c2c32a1c98fb89",
        "repo": "jax",
        "path": "jax/tools/colab_tpu.py",
        "file_name": "colab_tpu.py",
        "fun_name": "setup_tpu",
        "commit_message": "Pin default jax.tools.colab_tpu.setup_tpu driver version.\n\nPrior to this change, we were defaulting to the TPU nightly driver\nversion. We should instead pin to the version associated with the\ndefault jaxlib version that Colab uses.",
        "code": "def setup_tpu(tpu_driver_version='tpu_driver-0.2'):\n  \n  global TPU_DRIVER_MODE\n\n  if not TPU_DRIVER_MODE:\n    colab_tpu_addr = os.environ['COLAB_TPU_ADDR'].split(':')[0]\n    url = f'http://{colab_tpu_addr}:8475/requestversion/{tpu_driver_version}'\n    requests.post(url)\n    TPU_DRIVER_MODE = 1\n\n  # The following is required to use TPU Driver as JAX's backend.\n  config.FLAGS.jax_xla_backend = \"tpu_driver\"\n  config.FLAGS.jax_backend_target = \"grpc://\" + os.environ['COLAB_TPU_ADDR']\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 55,
        "n_words": 37,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 64,
        "n_ast_nodes": 125,
        "n_identifiers": 14,
        "d_id": 27112,
        "documentation": {
            "docstring": "Sets up Colab to run on TPU.\n\n  Note: make sure the Colab Runtime is set to Accelerator: TPU.\n\n  Args\n  ----\n  tpu_driver_version : (str) specify the version identifier for the tpu driver.\n    Defaults to \"tpu_driver-0.2\", which can be used with jaxlib 0.3.20. Set to\n    \"tpu_driver_nightly\" to use the nightly tpu driver build.\n  ",
            "n_words": 51,
            "vocab_size": 41,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 5421,
        "commit_id": "d6d52c5d99dd7ebbd966da79c1d890699a947f39",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-rki-covid/source_rki_covid/source.py",
        "file_name": "source.py",
        "fun_name": "check_connection",
        "commit_message": ":tada: New Source: RKI (Robert Koch-Institut) Covid Public API  (#11732)\n\n* Added source for RKI-covid-germany, updated spec.json, implemented source with check and discover method added germany.json.\r\n\r\n* implemented incremental method for germany history cases with date as parameters, updated streams, added cursor field for incremental streams.\r\n\r\n* main file added.\r\n\r\n* added Incidence source with date as parameter. Incremental stream. spec, source, schemas updated, added class GermanHistoryIncidence added.\r\n\r\n* Added a full-refresh stream for germany/age-group .Added incremental streams for deaths/:days, recovered/:days, frozen-incidence/:days, hospitalization/:days. Updated source.py methods. Updated sepc.json properties key. Updated configured_catalogue.json with required streams. Updated config.json\r\n\r\n* writting test unit test cases for incremental streams: german history cases and german history incidence.\r\n\r\n* Incremental streams for germanhistorydeaths, germanhistoryfrozenIncidence, germanhistoryhospitalization, germanhistoryrecovered. Fixing other test cases.\r\n\r\n* Added test stream for age group and germany.\r\n\r\n* changes in Readme and source.py.\r\n\r\n* IncrementalMixin added to class GermanyHistoryCases. AFter review IncrementalMixin will be implemented to all incremental classes.\r\n\r\n* Implemented Incremental mixin or GermanHistory Cases connector.\r\n\r\n* corrected changes.\r\n\r\n* adding integration test\r\n\r\n* comment acceptence test.\r\n\r\n* On path with master\r\n\r\n* updated the changes for PR request.\r\n\r\n* changed file source-rki-covid/integration_tests/configured_catalog.json\r\n\r\n* corrected flake and blackformatting. Build gradel.\r\n\r\n* Worked on the suggestions.\r\n\r\n* source_rki_covid/schemas/germany_age_groups.json\r\n\r\n* uodated abnormal_state.json\r\n\r\n* updated the schemas for german age groups and history hospitalization.\r\n\r\n* correct dockerfile and update airbyte_cdk version\r\n\r\n* run format\r\n\r\n* update python version\r\n\r\n* correct dockerfile build\r\n\r\n* add source in seed\r\n\r\n* update uuid for rki-covid source\r\n\r\n* change docker\r\n\r\n* add bash\r\n\r\n* auto-bump connector version\r\n\r\n* run seed file\r\n\r\n* correct doc\r\n\r\n* auto-bump connector version\r\n\r\nCo-authored-by: Marcos Marx Millnitz <marcosmarxm@gmail.com>\r\nCo-authored-by: Octavia Squidington III <octavia-squidington-iii@users.noreply.github.com>",
        "code": "def check_connection(self, logger, config) -> Tuple[bool, any]:\n        \n        try:\n            req = requests.get(RkiCovidStream.url_base + \"germany\")\n            if req.status_code == 200:\n                return True, None\n            return False, req.reason\n        except Exception:\n            return False, \"There is a problem in source check connection.\"\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 115,
        "n_words": 35,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 55,
        "n_ast_nodes": 90,
        "n_identifiers": 15,
        "d_id": 770,
        "documentation": {
            "docstring": "\n        Testing connection availability for the connector.\n\n        :param config:  the user-input config object conforming to the connector's spec.json\n        :param logger:  logger object\n        :return Tuple[bool, any]: (True, None) if the input config can be used to connect to the API successfully, (False, error) otherwise.\n        ",
            "n_words": 42,
            "vocab_size": 33,
            "n_whitespaces": 80,
            "language": "en"
        }
    },
    {
        "id": 73294,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/contrib/modeladmin/views.py",
        "file_name": "views.py",
        "fun_name": "get_heading",
        "commit_message": "Reformat with black",
        "code": "def get_heading(self, queryset, field):\n        \n        heading_override = self.export_headings.get(field)\n        if heading_override:\n            return force_str(heading_override)\n        return force_str(\n            label_for_field(\n                field, model=self.model, model_admin=self.model_admin\n            ).title()\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 102,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 52,
        "n_ast_nodes": 82,
        "n_identifiers": 12,
        "d_id": 16007,
        "documentation": {
            "docstring": "Get headings for exported spreadsheet column for the relevant field",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 156874,
        "commit_id": "8b95f983c232c1bd628e9cba0695d3ef229d290b",
        "repo": "dask",
        "path": "dask/array/backends.py",
        "file_name": "backends.py",
        "fun_name": "_nannumel_sparse",
        "commit_message": "Sparse array reductions (#9342)",
        "code": "def _nannumel_sparse(x, **kwargs):\n    \n    n = _nannumel(x, **kwargs)\n    # If all dimensions are contracted, this will just be a number, otherwise we\n    # want to densify it.\n    return n.todense() if hasattr(n, \"todense\") else n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 48,
        "n_words": 33,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 7,
        "d_id": 36793,
        "documentation": {
            "docstring": "\n    A reduction to count the number of elements in a sparse array, excluding nans.\n    This will in general result in a dense matrix with an unpredictable fill value.\n    So make it official and convert it to dense.\n\n    https://github.com/dask/dask/issues/7169\n    ",
            "n_words": 38,
            "vocab_size": 33,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 323153,
        "commit_id": "44a290e94d1becd1f09fddc3d873f9e19c9d6919",
        "repo": "PaddleNLP",
        "path": "paddlenlp/trainer/trainer_callback.py",
        "file_name": "trainer_callback.py",
        "fun_name": "_new_step",
        "commit_message": "[Trainer] Add init version of paddlenlp trainer and apply  finetune for ernie-1.0 pretraining. (#1761)\n\n* add some datasets for finetune.\r\n\r\n* support fine tune for all tastks.\r\n\r\n* add trainer prototype.\r\n\r\n* init verison for paddlenlp trainer.\r\n\r\n* refine trainer.\r\n\r\n* update for some details.\r\n\r\n* support multi-cards training evaluation.\r\n\r\n* support load from ckpt.\r\n\r\n* support for export inference model.\r\n\r\n* first version of trainer.\r\n\r\n* seq cls support clue.\r\n\r\n* trainer support for token classification and question answersing tasks.\r\n\r\n* fix as reviews.\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>",
        "code": "def _new_step(self):\n        \n        self.should_save = False\n        self.should_evaluate = False\n        self.should_log = False\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 39,
        "n_words": 11,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 21,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 118389,
        "documentation": {
            "docstring": "Internal method that resets the variable for a new step.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 155752,
        "commit_id": "510bbc380531cbf56a409f1ae68e6fd84a9599e6",
        "repo": "dask",
        "path": "dask/dataframe/shuffle.py",
        "file_name": "shuffle.py",
        "fun_name": "shuffle_group",
        "commit_message": "Update `pre-commit` version  (#8691)",
        "code": "def shuffle_group(df, cols, stage, k, npartitions, ignore_index, nfinal):\n    \n    if isinstance(cols, str):\n        cols = [cols]\n\n    if cols and cols[0] == \"_partitions\":\n        ind = df[cols[0]]\n    else:\n        ind = hash_object_dispatch(df[cols] if cols else df, index=False)\n        if nfinal and nfinal != npartitions:\n            ind = ind % int(nfinal)\n\n    c = ind.values\n    typ = np.min_scalar_type(npartitions * 2)\n\n    c = np.mod(c, npartitions).astype(typ, copy=False)\n    np.floor_divide(c, k**stage, out=c)\n    np.mod(c, k, out=c)\n\n    return group_split_dispatch(df, c, k, ignore_index=ignore_index)\n\n\n@contextlib.contextmanager",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "@contextlib.contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 136,
        "n_words": 68,
        "vocab_size": 47,
        "complexity": 7,
        "nloc": 15,
        "token_counts": 157,
        "n_ast_nodes": 240,
        "n_identifiers": 27,
        "d_id": 36457,
        "documentation": {
            "docstring": "Splits dataframe into groups\n\n    The group is determined by their final partition, and which stage we are in\n    in the shuffle\n\n    Parameters\n    ----------\n    df: DataFrame\n    cols: str or list\n        Column name(s) on which to split the dataframe. If ``cols`` is not\n        \"_partitions\", hashing will be used to determine target partition\n    stage: int\n        We shuffle dataframes with many partitions we in a few stages to avoid\n        a quadratic number of tasks.  This number corresponds to which stage\n        we're in, starting from zero up to some small integer\n    k: int\n        Desired number of splits from this dataframe\n    npartition: int\n        Total number of output partitions for the full dataframe\n    nfinal: int\n        Total number of output partitions after repartitioning\n\n    Returns\n    -------\n    out: Dict[int, DataFrame]\n        A dictionary mapping integers in {0..k} to dataframes such that the\n        hash values of ``df[col]`` are well partitioned.\n    ",
            "n_words": 138,
            "vocab_size": 100,
            "n_whitespaces": 251,
            "language": "en"
        }
    },
    {
        "id": 301147,
        "commit_id": "654c59c19414c52f95f56603c460f63edeb60959",
        "repo": "core",
        "path": "tests/components/unifiprotect/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "unifi_dict",
        "commit_message": "Add diagnostics for UniFi Protect (#72280)",
        "code": "def unifi_dict(self) -> dict[str, Any]:\n        \n        return {\n            \"nvr\": self.nvr.unifi_dict(),\n            \"cameras\": [c.unifi_dict() for c in self.cameras.values()],\n            \"lights\": [c.unifi_dict() for c in self.lights.values()],\n            \"sensors\": [c.unifi_dict() for c in self.sensors.values()],\n            \"viewers\": [c.unifi_dict() for c in self.viewers.values()],\n            \"liveviews\": [c.unifi_dict() for c in self.liveviews.values()],\n            \"doorlocks\": [c.unifi_dict() for c in self.doorlocks.values()],\n            \"chimes\": [c.unifi_dict() for c in self.chimes.values()],\n        }\n\n\n@dataclass",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@dataclass",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 161,
        "n_words": 53,
        "vocab_size": 29,
        "complexity": 8,
        "nloc": 12,
        "token_counts": 166,
        "n_ast_nodes": 272,
        "n_identifiers": 16,
        "d_id": 99995,
        "documentation": {
            "docstring": "Return UniFi formatted dict representation of the NVR.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 65948,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/report/student_monthly_attendance_sheet/student_monthly_attendance_sheet.py",
        "file_name": "student_monthly_attendance_sheet.py",
        "fun_name": "get_attendance_list",
        "commit_message": "style: format code with black",
        "code": "def get_attendance_list(from_date, to_date, student_group, students_list):\n\tattendance_list = frappe.db.sql(\n\t\t,\n\t\t(student_group, from_date, to_date),\n\t\tas_dict=1,\n\t)\n\n\tatt_map = {}\n\tstudents_with_leave_application = get_students_with_leave_application(\n\t\tfrom_date, to_date, students_list\n\t)\n\tfor d in attendance_list:\n\t\tatt_map.setdefault(d.student, frappe._dict()).setdefault(d.date, \"\")\n\n\t\tif students_with_leave_application.get(\n\t\t\td.date\n\t\t) and d.student in students_with_leave_application.get(d.date):\n\t\t\tatt_map[d.student][d.date] = \"Present\"\n\t\telse:\n\t\t\tatt_map[d.student][d.date] = d.status\n\n\tatt_map = mark_holidays(att_map, from_date, to_date, students_list)\n\n\treturn att_map\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 34,
        "n_words": 54,
        "vocab_size": 39,
        "complexity": 4,
        "nloc": 24,
        "token_counts": 143,
        "n_ast_nodes": 215,
        "n_identifiers": 21,
        "d_id": 14067,
        "documentation": {
            "docstring": "select student, date, status\n\t\tfrom `tabStudent Attendance` where student_group = %s\n\t\tand docstatus = 1\n\t\tand date between %s and %s\n\t\torder by student, date",
            "n_words": 25,
            "vocab_size": 18,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 117309,
        "commit_id": "9ce5a21dd6359fd7e8ebf78051ce9e97bd195ec9",
        "repo": "mindsdb",
        "path": "mindsdb/api/http/initialize.py",
        "file_name": "initialize.py",
        "fun_name": "update_static",
        "commit_message": "ML handler supbrocess (#3377)\n\n* log -> logger\r\n\r\ndividing components:\r\n\r\napp initialize\r\n    parse args\r\n    set env.MINDSDB_CONFIG_PATH\r\n\r\nconfig\r\n    requiers env.MINDSDB_CONFIG_PATH\r\n    sets\r\n        env.MINDSDB_DB_CON\r\n    Config() - makes initialization\r\n\r\nlog\r\n    uses config\r\n    initialize_log - makes initialization\r\n\r\ndatabase\r\n    uses env.MINDSDB_DB_CON\r\n    have init() method\r\n\r\nfile storage\r\n    uses config\r\n\r\n* partial sync for model storage interfaces\r\n\r\n* ml handler in subprocess interface\r\n\r\n* fix delete model\r\n\r\n* fix: model with error in success status\r\n\r\n* fix: remove hf predictor\r\n\r\n* fix pg handler\r\n\r\n* MLHandlerPersistWrapper keeps wrapper process opened\r\n\r\n* predictor with error keeps 'success' status\r\n\r\n#3362\r\n\r\n* lock for sending tasks to subprocess one by one\r\n\r\n* check target of predictor before run learn in subproccess\r\n\r\n* fix check target\r\n\r\n* fix: json_ai override and problem definition generation\r\n\r\n* fix None case\r\n\r\n* folder for ml handler tests\r\n\r\n* fix: add timeseries_settings key to learn_args\r\n\r\n* fixes in lw_handler\r\n\r\n* fix: del join_learn_process\r\n\r\n* tests for LW handler\r\n\r\n* finish unit test for LW\r\n\r\n* changes in tests:\r\n- set-project -> to base class\r\n- return of ml handler is dataframe\r\n- draft for project structure test\r\n\r\n* merge from staging\r\n\r\n* create_validation method to check learn params before send to subprocess\r\nfixes of HF\r\nfixed version of transformers in HF requirements\r\n\r\nCo-authored-by: Patricio Cerda Mardini <pcerdam@live.com>",
        "code": "def update_static():\n    \n    config = Config()\n    logger = get_log('http')\n    static_path = Path(config['paths']['static'])\n\n    last_gui_version_lv = get_last_compatible_gui_version()\n    current_gui_version_lv = get_current_gui_version()\n\n    if last_gui_version_lv is False:\n        return False\n\n    if current_gui_version_lv is not None:\n        if current_gui_version_lv >= last_gui_version_lv:\n            return True\n\n    logger.info(f'New version of GUI available ({last_gui_version_lv.vstring}). Downloading...')\n\n    temp_dir = tempfile.mkdtemp(prefix='mindsdb_gui_files_')\n    success = download_gui(temp_dir, last_gui_version_lv.vstring)\n    if success is False:\n        shutil.rmtree(temp_dir)\n        return False\n\n    temp_dir_for_rm = tempfile.mkdtemp(prefix='mindsdb_gui_files_')\n    shutil.rmtree(temp_dir_for_rm)\n    shutil.copytree(str(static_path), temp_dir_for_rm)\n    shutil.rmtree(str(static_path))\n    shutil.copytree(temp_dir, str(static_path))\n    shutil.rmtree(temp_dir_for_rm)\n\n    logger.info(f'GUI version updated to {last_gui_version_lv.vstring}')\n    return True\n\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 171,
        "n_words": 72,
        "vocab_size": 47,
        "complexity": 5,
        "nloc": 25,
        "token_counts": 160,
        "n_ast_nodes": 286,
        "n_identifiers": 24,
        "d_id": 25952,
        "documentation": {
            "docstring": " Update Scout files basing on compatible-config.json content.\n        Files will be downloaded and updated if new version of GUI > current.\n        Current GUI version stored in static/version.txt.\n    ",
            "n_words": 26,
            "vocab_size": 24,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 83840,
        "commit_id": "803982e87254e3b1ebcb16ed795e224afceea3a3",
        "repo": "zulip",
        "path": "zerver/tests/test_subs.py",
        "file_name": "test_subs.py",
        "fun_name": "test_stream_admin_remove_others_from_public_stream",
        "commit_message": "message_flags: Short-circuit if no messages changed.\n\nOmit sending an event, and updating the database, if there are no\nmatching messages.",
        "code": "def test_stream_admin_remove_others_from_public_stream(self) -> None:\n        \n        result = self.attempt_unsubscribe_of_principal(\n            query_count=15,\n            target_users=[self.example_user(\"cordelia\")],\n            is_realm_admin=False,\n            is_stream_admin=True,\n            is_subbed=True,\n            invite_only=False,\n            target_users_subbed=True,\n        )\n        json = self.assert_json_success(result)\n        self.assert_length(json[\"removed\"], 1)\n        self.assert_length(json[\"not_removed\"], 0)\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 141,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 80,
        "n_ast_nodes": 125,
        "n_identifiers": 15,
        "d_id": 17733,
        "documentation": {
            "docstring": "\n        You can remove others from public streams you're a stream administrator of.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 4470,
        "commit_id": "787daa9961b6b103e8d520c544277fc77c191dfb",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-intercom/unit_tests/unit_test.py",
        "file_name": "unit_test.py",
        "fun_name": "test_conversation_part_has_conversation_id",
        "commit_message": "🎉 Source Intercom: Added conversation_id field to conversation_part records (#11206)",
        "code": "def test_conversation_part_has_conversation_id(requests_mock):\n    \n\n    response_body = {\n        \"type\": \"conversation\",\n        \"id\": \"151272900024304\",\n        \"created_at\": 1647365706,\n        \"updated_at\": 1647366443,\n        \"conversation_parts\": {\n            \"type\": \"conversation_part.list\",\n            \"conversation_parts\": [\n                {\"type\": \"conversation_part\", \"id\": \"13740311965\"},\n                {\"type\": \"conversation_part\", \"id\": \"13740312024\"},\n            ],\n            \"total_count\": 2,\n        },\n    }\n    url = \"https://api.intercom.io/conversations/151272900024304\"\n    requests_mock.get(url, json=response_body)\n\n    stream1 = ConversationParts(authenticator=NoAuth())\n\n    record_count = 0\n    for record in stream1.read_records(sync_mode=SyncMode.incremental, stream_slice={\"id\": \"151272900024304\"}):\n        assert record[\"conversation_id\"] == \"151272900024304\"\n        record_count += 1\n\n    assert record_count == 2\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 217,
        "n_words": 60,
        "vocab_size": 46,
        "complexity": 2,
        "nloc": 23,
        "token_counts": 126,
        "n_ast_nodes": 233,
        "n_identifiers": 17,
        "d_id": 666,
        "documentation": {
            "docstring": "\n    Test shows that conversation_part records include the `conversation_id` field.\n    ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 216076,
        "commit_id": "ec41b56baee98ade5e6e21083645da1ec21c4b86",
        "repo": "salt",
        "path": "salt/utils/data.py",
        "file_name": "data.py",
        "fun_name": "flatten",
        "commit_message": "detect reference cycles in flatten function",
        "code": "def flatten(data, levels=None, preserve_nulls=False, _ids=None):\n    \n    if _ids is None:\n        _ids = set()\n    if id(data) in _ids:\n        raise RecursionError(\"Reference cycle detected. Check input list.\")\n    _ids.add(id(data))\n\n    ret = []\n\n    for element in data:\n        if not preserve_nulls and element in (None, \"None\", \"null\"):\n            # ignore null items\n            continue\n        elif is_iter(element):\n            if levels is None:\n                ret.extend(flatten(element, preserve_nulls=preserve_nulls, _ids=_ids))\n            elif levels >= 1:\n                # decrement as we go down the stack\n                ret.extend(\n                    flatten(\n                        element,\n                        levels=(int(levels) - 1),\n                        preserve_nulls=preserve_nulls,\n                        _ids=_ids,\n                    )\n                )\n            else:\n                ret.append(element)\n        else:\n            ret.append(element)\n\n    return ret\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 409,
        "n_words": 82,
        "vocab_size": 64,
        "complexity": 9,
        "nloc": 27,
        "token_counts": 154,
        "n_ast_nodes": 249,
        "n_identifiers": 15,
        "d_id": 54379,
        "documentation": {
            "docstring": "\n    .. versionadded:: 3005\n\n    Flatten a list.\n\n    :param data: A list to flatten\n\n    :param levels: The number of levels in sub-lists to descend\n\n    :param preserve_nulls: Preserve nulls in a list, by default flatten removes\n                           them\n\n    :param _ids: Parameter used internally within the function to detect\n                 reference cycles.\n\n    :returns: A flat(ter) list of values\n\n    .. code-block:: jinja\n\n        {{ [3, [4, 2] ] | flatten }}\n        # => [3, 4, 2]\n\n    Flatten only the first level of a list:\n\n    .. code-block:: jinja\n\n        {{ [3, [4, [2]] ] | flatten(levels=1) }}\n        # => [3, 4, [2]]\n\n    Preserve nulls in a list, by default flatten removes them.\n\n    .. code-block:: jinja\n\n        {{ [3, None, [4, [2]] ] | flatten(levels=1, preserve_nulls=True) }}\n        # => [3, None, 4, [2]]\n    ",
            "n_words": 121,
            "vocab_size": 63,
            "n_whitespaces": 245,
            "language": "en"
        }
    },
    {
        "id": 129027,
        "commit_id": "853d10871c55cb741cb15212ef4ab42f158f968c",
        "repo": "ray",
        "path": "rllib/agents/trainer.py",
        "file_name": "trainer.py",
        "fun_name": "training_iteration",
        "commit_message": "[RLlib] Issue 18499: PGTrainer with training_iteration fn does not support multi-GPU. (#21376)",
        "code": "def training_iteration(self) -> ResultDict:\n        \n        # Some shortcuts.\n        batch_size = self.config[\"train_batch_size\"]\n\n        # Collects SampleBatches in parallel and synchronously\n        # from the Trainer's RolloutWorkers until we hit the\n        # configured `train_batch_size`.\n        sample_batches = []\n        num_env_steps = 0\n        num_agent_steps = 0\n        while (not self._by_agent_steps and num_env_steps < batch_size) or \\\n                (self._by_agent_steps and num_agent_steps < batch_size):\n            new_sample_batches = synchronous_parallel_sample(self.workers)\n            sample_batches.extend(new_sample_batches)\n            num_env_steps += sum(len(s) for s in new_sample_batches)\n            num_agent_steps += sum(\n                len(s) if isinstance(s, SampleBatch) else s.agent_steps()\n                for s in new_sample_batches)\n        self._counters[NUM_ENV_STEPS_SAMPLED] += num_env_steps\n        self._counters[NUM_AGENT_STEPS_SAMPLED] += num_agent_steps\n\n        # Combine all batches at once\n        train_batch = SampleBatch.concat_samples(sample_batches)\n\n        # Use simple optimizer (only for multi-agent or tf-eager; all other\n        # cases should use the multi-GPU optimizer, even if only using 1 GPU).\n        # TODO: (sven) rename MultiGPUOptimizer into something more\n        #  meaningful.\n        if self.config.get(\"simple_optimizer\") is True:\n            train_results = train_one_step(self, train_batch)\n        else:\n            train_results = multi_gpu_train_one_step(self, train_batch)\n\n        return train_results\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 399,
        "n_words": 140,
        "vocab_size": 97,
        "complexity": 9,
        "nloc": 35,
        "token_counts": 158,
        "n_ast_nodes": 261,
        "n_identifiers": 28,
        "d_id": 28878,
        "documentation": {
            "docstring": "Default single iteration logic of an algorithm.\n\n        - Collect on-policy samples (SampleBatches) in parallel using the\n          Trainer's RolloutWorkers (@ray.remote).\n        - Concatenate collected SampleBatches into one train batch.\n        - Note that we may have more than one policy in the multi-agent case:\n          Call the different policies' `learn_on_batch` (simple optimizer) OR\n          `load_batch_into_buffer` + `learn_on_loaded_batch` (multi-GPU\n          optimizer) methods to calculate loss and update the model(s).\n        - Return all collected metrics for the iteration.\n\n        Returns:\n            The results dict from executing the training iteration.\n        ",
            "n_words": 79,
            "vocab_size": 66,
            "n_whitespaces": 168,
            "language": "en"
        }
    },
    {
        "id": 203306,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/apps/registry.py",
        "file_name": "registry.py",
        "fun_name": "get_model",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def get_model(self, app_label, model_name=None, require_ready=True):\n        \n        if require_ready:\n            self.check_models_ready()\n        else:\n            self.check_apps_ready()\n\n        if model_name is None:\n            app_label, model_name = app_label.split(\".\")\n\n        app_config = self.get_app_config(app_label)\n\n        if not require_ready and app_config.models is None:\n            app_config.import_models()\n\n        return app_config.get_model(model_name, require_ready=require_ready)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 125,
        "n_words": 32,
        "vocab_size": 25,
        "complexity": 5,
        "nloc": 11,
        "token_counts": 80,
        "n_ast_nodes": 132,
        "n_identifiers": 12,
        "d_id": 50292,
        "documentation": {
            "docstring": "\n        Return the model matching the given app_label and model_name.\n\n        As a shortcut, app_label may be in the form <app_label>.<model_name>.\n\n        model_name is case-insensitive.\n\n        Raise LookupError if no application exists with this label, or no\n        model exists with this name in the application. Raise ValueError if\n        called with a single argument that doesn't contain exactly one dot.\n        ",
            "n_words": 55,
            "vocab_size": 41,
            "n_whitespaces": 105,
            "language": "en"
        }
    },
    {
        "id": 282723,
        "commit_id": "b8b3b49896b7553c8ad57e0f3fbb4464ecf24179",
        "repo": "OpenBBTerminal",
        "path": "bots/groupme/run_groupme.py",
        "file_name": "run_groupme.py",
        "fun_name": "handle_groupme",
        "commit_message": "Groupme Bot (#1418)\n\n* Added groupme helpers\r\n\r\n* Began handling of user input\r\n\r\n* Expanded commands, improved bot\r\n\r\n* Completed dictionary\r\n\r\n* Eliminated redundancies\r\n\r\n* Added more\r\n\r\n* Added debuggers for server\r\n\r\n* Fixed bugs\r\n\r\n* Improved input handling and image sending\r\n\r\n* Fixed dd-est\r\n\r\n* Fixed dd commands\r\n\r\n* Added dps fix\r\n\r\n* Fixed feargreed\r\n\r\n* Fixed econ commands\r\n\r\n* Fixed gov commands\r\n\r\n* Fixed ta\r\n\r\n* Added docstrings\r\n\r\n* Added docstrings\r\n\r\n* black\r\n\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>",
        "code": "def handle_groupme(request) -> bool:\n    \n\n    req = json.loads(request.decode(\"utf-8\"))\n    text = req.get(\"text\").strip().lower()\n    group_id = req.get(\"group_id\").strip()\n\n    if text[0] == \"!\":\n        cmd = text[1:]\n        full_cmd = cmd.split(\"/\")\n        group = full_cmd[0].split(\"-\")[0]\n        parents = {x.split(\"-\")[0] for x in commands}\n        if group in parents:\n            if full_cmd[0] in commands:\n                selected = commands[full_cmd[0]]\n                if len(full_cmd) != len(selected.get(\"required\", [])) + 1:\n                    syntax = get_syntax(selected, full_cmd[0])\n                    send_message(f\"Required syntax: {syntax}\", group_id)\n                    return False\n                other_args = {}\n                for i, val in enumerate(full_cmd[1:]):\n                    req_name = list(selected.get(\"required\", {}).keys())[i]\n                    required = selected.get(\"required\", [])[req_name]\n                    if isinstance(required, List) and required != [True, False]:\n                        required = [str(x) for x in required]\n                    if isinstance(val, str) and req_name in [\"ticker\"]:\n                        val = val.upper()\n                    elif isinstance(val, str) and req_name == \"raw\":\n                        val = bool(val)\n                    if (isinstance(required, List) and val not in required) or (\n                        isinstance(required, Pattern) and not required.match(val)\n                    ):\n                        syntax = get_syntax(selected, full_cmd[0])\n                        send_message(\n                            f\"{syntax}\\nInvalid argument for: {req_name}\", group_id\n                        )\n                        get_arguments(selected, req_name, group_id)\n                        return False\n                    other_args[req_name] = val\n                func = selected[\"function\"]\n                ShowView().groupme(func, group_id, cmd, **other_args)\n                return True\n            else:\n                show_cmds = []\n                for command in commands:\n                    if group == command[: len(group)]:\n                        show_cmds.append(command)\n                send_options(\"Valid commands: \", show_cmds, group_id)\n                return False\n        else:\n            send_options(\"Valid categories: \", parents, group_id)\n            return False\n    return False\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 941,
        "n_words": 187,
        "vocab_size": 108,
        "complexity": 20,
        "nloc": 62,
        "token_counts": 428,
        "n_ast_nodes": 703,
        "n_identifiers": 46,
        "d_id": 84275,
        "documentation": {
            "docstring": "Handles groupme bot inputs\n\n    Parameters\n    ----------\n    request : Request\n        The request object provided by FASTAPI\n\n    Returns\n    ----------\n    success : bool\n        Whether the response was sent successfully\n    ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 108136,
        "commit_id": "ec410abbb3a721e31f3aaa61e9e4f941467e35e1",
        "repo": "matplotlib",
        "path": "lib/matplotlib/backends/backend_pdf.py",
        "file_name": "backend_pdf.py",
        "fun_name": "_fill",
        "commit_message": "Deprecate functions in backends",
        "code": "def _fill(strings, linelen=75):\n    \n    currpos = 0\n    lasti = 0\n    result = []\n    for i, s in enumerate(strings):\n        length = len(s)\n        if currpos + length < linelen:\n            currpos += length + 1\n        else:\n            result.append(b' '.join(strings[lasti:i]))\n            lasti = i\n            currpos = length\n    result.append(b' '.join(strings[lasti:]))\n    return b'\\n'.join(result)\n\n# PDF strings are supposed to be able to include any eight-bit data,\n# except that unbalanced parens and backslashes must be escaped by a\n# backslash. However, sf bug #2708559 shows that the carriage return\n# character may get read as a newline; these characters correspond to\n# \\gamma and \\Omega in TeX's math font encoding. Escaping them fixes\n# the bug.\n_string_escape_regex = re.compile(br'([\\\\()\\r\\n])')\n\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 189,
        "n_words": 110,
        "vocab_size": 80,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 97,
        "n_ast_nodes": 181,
        "n_identifiers": 16,
        "d_id": 23073,
        "documentation": {
            "docstring": "\n    Make one string from sequence of strings, with whitespace in between.\n\n    The whitespace is chosen to form lines of at most *linelen* characters,\n    if possible.\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 308799,
        "commit_id": "10195dc700770cdfdeaff79c53cf5d1d763f20c6",
        "repo": "core",
        "path": "tests/components/plex/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "plextv_resources_fixture",
        "commit_message": "Improve server selection for Plex config flows (#63408)",
        "code": "def plextv_resources_fixture():\n    \n    return load_fixture(\"plex/plextv_resources_one_server.xml\")\n\n\n@pytest.fixture(name=\"plextv_resources_two_servers\", scope=\"session\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(name=\"plextv_resources_two_servers\", scope=\"session\")",
        "n_ast_errors": 1,
        "ast_levels": 8,
        "n_whitespaces": 11,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 46,
        "n_identifiers": 6,
        "d_id": 107537,
        "documentation": {
            "docstring": "Load single-server payload for plex.tv resources and return it.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 59586,
        "commit_id": "a7bd9cadd5038383449b0e75a87bb23a73b278d8",
        "repo": "prefect",
        "path": "tests/test_flows.py",
        "file_name": "test_flows.py",
        "fun_name": "test_timeout_does_not_wait_for_completion_for_sync_flows",
        "commit_message": "Add support for Python 3.11 (#7304)\n\nCo-authored-by: Chris Guidry <chris.g@prefect.io>",
        "code": "def test_timeout_does_not_wait_for_completion_for_sync_flows(self, tmp_path):\n        \n        if sys.version_info[1] == 11:\n            pytest.xfail(\"The engine returns _after_ sleep finishes in Python 3.11\")\n\n        canary_file = tmp_path / \"canary\"\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 53,
        "n_words": 21,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 14,
        "token_counts": 96,
        "n_ast_nodes": 52,
        "n_identifiers": 8,
        "d_id": 11913,
        "documentation": {
            "docstring": "\n        Sync flows are cancelled when they change instructions. The flow will return\n        immediately when the timeout is reached, but the thread it executes in will\n        continue until the next instruction is reached. `time.sleep` will return then\n        the thread will be interrupted.\n        ",
            "n_words": 41,
            "vocab_size": 31,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 199560,
        "commit_id": "f0ccc88c86f77f1c3e13d590d4506e49c8cb2a12",
        "repo": "sympy",
        "path": "sympy/physics/mechanics/body.py",
        "file_name": "body.py",
        "fun_name": "inertia",
        "commit_message": "Add property docstrings",
        "code": "def inertia(self):\n        \n        if self.is_rigidbody:\n            return RigidBody.inertia.fget(self)\n        return (self.central_inertia, self.masscenter)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 41,
        "n_words": 9,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 30,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 49282,
        "documentation": {
            "docstring": "The body's inertia about a point; stored as (Dyadic, Point).",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 248311,
        "commit_id": "fcf951d5dc7ca8c4cb18aa9c1f5ccb005df3610a",
        "repo": "synapse",
        "path": "tests/storage/databases/main/test_events_worker.py",
        "file_name": "test_events_worker.py",
        "fun_name": "test_event_ref",
        "commit_message": "Track in memory events using weakrefs (#10533)",
        "code": "def test_event_ref(self):\n        \n\n        # Reset the event cache\n        self.store._get_event_cache.clear()\n\n        with LoggingContext(\"test\") as ctx:\n            # We keep hold of the event event though we never use it.\n            event = self.get_success(self.store.get_event(self.event_id))  # noqa: F841\n\n            # We should have fetched the event from the DB\n            self.assertEqual(ctx.get_resource_usage().evt_db_fetch_count, 1)\n\n        # Reset the event cache\n        self.store._get_event_cache.clear()\n\n        with LoggingContext(\"test\") as ctx:\n            self.get_success(self.store.get_event(self.event_id))\n\n            # Since the event is still in memory we shouldn't have fetched it\n            # from the DB\n            self.assertEqual(ctx.get_resource_usage().evt_db_fetch_count, 0)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 211,
        "n_words": 73,
        "vocab_size": 40,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 100,
        "n_ast_nodes": 181,
        "n_identifiers": 14,
        "d_id": 72209,
        "documentation": {
            "docstring": "Test that we reuse events that are still in memory but have fallen\n        out of the cache, rather than requesting them from the DB.\n        ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 9736,
        "commit_id": "766b9e19585968d011649b53057fba3663eff551",
        "repo": "gensim",
        "path": "gensim/models/keyedvectors.py",
        "file_name": "keyedvectors.py",
        "fun_name": "_load_specials",
        "commit_message": "Ensure next_index available when loading old stored KeyedVectors models (#3117)\n\n* fix #3114: ensure next_index available\r\n\r\n* rm trailing whitespace",
        "code": "def _load_specials(self, *args, **kwargs):\n        \n        super(KeyedVectors, self)._load_specials(*args, **kwargs)\n        if hasattr(self, 'doctags'):\n            self._upconvert_old_d2vkv()\n        # fixup rename/consolidation into index_to_key of older index2word, index2entity\n        if not hasattr(self, 'index_to_key'):\n            self.index_to_key = self.__dict__.pop('index2word', self.__dict__.pop('index2entity', None))\n        # fixup rename into vectors of older syn0\n        if not hasattr(self, 'vectors'):\n            self.vectors = self.__dict__.pop('syn0', None)\n            self.vector_size = self.vectors.shape[1]\n        # ensure at least a 'None' in 'norms' to force recalc\n        if not hasattr(self, 'norms'):\n            self.norms = None\n        # ensure at least an empty 'expandos'\n        if not hasattr(self, 'expandos'):\n            self.expandos = {}\n        # fixup rename of vocab into map\n        if 'key_to_index' not in self.__dict__:\n            self._upconvert_old_vocab()\n        # ensure older instances have next_index\n        if not hasattr(self, 'next_index'):\n            self.next_index = len(self)\n",
        "url": "https://github.com/RaRe-Technologies/gensim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 299,
        "n_words": 106,
        "vocab_size": 66,
        "complexity": 8,
        "nloc": 17,
        "token_counts": 166,
        "n_ast_nodes": 286,
        "n_identifiers": 19,
        "d_id": 1665,
        "documentation": {
            "docstring": "Handle special requirements of `.load()` protocol, usually up-converting older versions.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 244361,
        "commit_id": "9c5b3331ac8edbfa328922fbab45c382380da540",
        "repo": "mmdetection",
        "path": "mmdet/models/dense_heads/base_dense_head.py",
        "file_name": "base_dense_head.py",
        "fun_name": "simple_test",
        "commit_message": "Simplify api of one-stage detector",
        "code": "def simple_test(self, feats, img_metas, rescale=False):\n        \n        outs = self.forward(feats)\n        results_list = self.get_results(\n            *outs, img_metas=img_metas, rescale=rescale)\n        return results_list\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 55,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 41,
        "n_ast_nodes": 63,
        "n_identifiers": 9,
        "d_id": 70350,
        "documentation": {
            "docstring": "Test function without test-time augmentation.\n\n        Args:\n            feats (tuple[torch.Tensor]): Multi-level features from the\n                upstream network, each is a 4D-tensor.\n            img_metas (list[dict]): List of image information.\n            rescale (bool, optional): Whether to rescale the results.\n                Defaults to False.\n\n        Returns:\n            list[obj:`InstanceData`]: Detection results of each image\n            after the post process.\n            Each item usually contains following keys.\n\n            - scores (Tensor): Classification scores, has a shape\n              (num_instance,)\n            - labels (Tensor): Labels of bboxes, has a shape\n              (num_instances,).\n            - bboxes (Tensor): Has a shape (num_instances, 4),\n              the last dimension 4 arrange as (x1, y1, x2, y2).\n        ",
            "n_words": 89,
            "vocab_size": 70,
            "n_whitespaces": 278,
            "language": "en"
        }
    },
    {
        "id": 250618,
        "commit_id": "372a632161dee642d81542069507826e34466ba1",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_http_server_aborts",
        "commit_message": "reintroduce `Flow.live`\n\nWe previously relied on the state of `Flow.reply` to check if a flow can be killed,\nbut this doesn't work anymore with `Flow.reply` being removed. Instead, we now\nreintroduce the `Flow.live` attribute, which signals if we are on a live connection.\nKilling still is not ideal (see comment in `Flow.killable`), but this paves the way.",
        "code": "def test_http_server_aborts(tctx, stream):\n    \n    server = Placeholder(Server)\n    flow = Placeholder(HTTPFlow)\n    playbook = Playbook(http.HttpLayer(tctx, HTTPMode.regular))\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 25,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 3,
        "nloc": 58,
        "token_counts": 277,
        "n_ast_nodes": 58,
        "n_identifiers": 14,
        "d_id": 73522,
        "documentation": {
            "docstring": "Test handling of the case where a server aborts during response transmission.",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 270139,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/datasets/reuters.py",
        "file_name": "reuters.py",
        "fun_name": "get_word_index",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get_word_index(path=\"reuters_word_index.json\"):\n    \n    origin_folder = (\n        \"https://storage.googleapis.com/tensorflow/tf-keras-datasets/\"\n    )\n    path = get_file(\n        path,\n        origin=origin_folder + \"reuters_word_index.json\",\n        file_hash=\"4d44cc38712099c9e383dc6e5f11a921\",\n    )\n    with open(path) as f:\n        return json.load(f)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 75,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 45,
        "n_ast_nodes": 83,
        "n_identifiers": 10,
        "d_id": 80402,
        "documentation": {
            "docstring": "Retrieves a dict mapping words to their index in the Reuters dataset.\n\n    Args:\n        path: where to cache the data (relative to `~/.keras/dataset`).\n\n    Returns:\n        The word index dictionary. Keys are word strings, values are their index.\n    ",
            "n_words": 35,
            "vocab_size": 28,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 53099,
        "commit_id": "b110baccdbfde300f410b069c873e8b2a2c98e00",
        "repo": "prefect",
        "path": "tests/test_logging.py",
        "file_name": "test_logging.py",
        "fun_name": "test_flow_run_respects_extra_loggers",
        "commit_message": "Add test",
        "code": "async def test_flow_run_respects_extra_loggers(orion_client, logger_test_deployment):\n    \n    flow_run = await orion_client.create_flow_run_from_deployment(\n        logger_test_deployment\n    )\n\n    await SubprocessFlowRunner(\n        env={\"PREFECT_LOGGING_EXTRA_LOGGERS\": \"foo\"}\n    ).submit_flow_run(flow_run, MagicMock(spec=anyio.abc.TaskStatus))\n\n    state = (await orion_client.read_flow_run(flow_run.id)).state\n    settings = await orion_client.resolve_datadoc(state.result())\n    api_logs = await orion_client.read_logs()\n    api_log_messages = [log.message for log in api_logs]\n\n    prefect_logger = logging.getLogger(\"prefect\")\n\n    # Configures 'foo' to match 'prefect'\n    assert settings[\"foo\"][\"handlers\"] == [\n        handler.name for handler in prefect_logger.handlers\n    ]\n    assert settings[\"foo\"][\"level\"] == prefect_logger.level\n    assert \"Hello from foo\" in api_log_messages\n\n    # Does not configure 'bar'\n    assert settings[\"bar\"][\"handlers\"] == []\n    assert settings[\"bar\"][\"level\"] == logging.NOTSET\n    assert \"Hello from bar\" not in api_log_messages\n\n\n@pytest.mark.parametrize(\"name\", [\"default\", None, \"\"])",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"name\", [\"default\", None, \"\"])",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 165,
        "n_words": 88,
        "vocab_size": 62,
        "complexity": 3,
        "nloc": 20,
        "token_counts": 163,
        "n_ast_nodes": 311,
        "n_identifiers": 35,
        "d_id": 10716,
        "documentation": {
            "docstring": "\n    Runs a flow in a subprocess to check that PREFECT_LOGGING_EXTRA_LOGGERS works as\n    intended. This avoids side-effects of modifying the loggers in this test run without\n    confusing mocking.\n    ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 40,
            "language": "en"
        }
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    {
        "id": 173342,
        "commit_id": "4ea80e9810a14ca3617f08a4ae5cfa6b50482e9a",
        "repo": "calibre-web",
        "path": "cps/config_sql.py",
        "file_name": "config_sql.py",
        "fun_name": "save",
        "commit_message": "Code cosmetics",
        "code": "def save(self):\n        \n        s = self._read_from_storage()  # type: _Settings\n\n        for k, v in self.__dict__.items():\n            if k[0] == '_':\n                continue\n            if hasattr(s, k):\n                setattr(s, k, v)\n\n        log.debug(\"_ConfigSQL updating storage\")\n        self._session.merge(s)\n        try:\n            self._session.commit()\n        except OperationalError as e:\n            log.error('Database error: %s', e)\n            self._session.rollback()\n        self.load()\n",
        "url": "https://github.com/janeczku/calibre-web.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
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        "nloc": 15,
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        "d_id": 40839,
        "documentation": {
            "docstring": "Apply all configuration values to the underlying storage.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 158288,
        "commit_id": "b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2",
        "repo": "d2l-zh",
        "path": "d2l/tensorflow.py",
        "file_name": "tensorflow.py",
        "fun_name": "try_all_gpus",
        "commit_message": "[PaddlePaddle] Merge master into Paddle branch (#1186)\n\n* change 15.2 title in chinese version (#1109)\r\n\r\nchange title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘\r\n\r\n* 修改部分语义表述 (#1105)\r\n\r\n* Update r0.17.5 (#1120)\r\n\r\n* Bump versions in installation\r\n\r\n* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)\r\n\r\n* line 313: \"bert.mall\" -> \"bert.small\" (#1130)\r\n\r\n* fix: update language as native reader (#1114)\r\n\r\n* Fix the translation of \"stride\" (#1115)\r\n\r\n* Update index.md (#1118)\r\n\r\n修改部分语义表述\r\n\r\n* Update self-attention-and-positional-encoding.md (#1133)\r\n\r\n依照本书的翻译习惯，将pooling翻译成汇聚\r\n\r\n* maybe a comment false (#1149)\r\n\r\n* maybe a little false\r\n\r\n* maybe a little false\r\n\r\n* A minor bug in the rcnn section (Chinese edition) (#1148)\r\n\r\n* Update bert.md (#1137)\r\n\r\n一个笔误\r\n# 假设batch_size=2，num_pred_positions=3\r\n# 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1]\r\n\r\n* Update calculus.md (#1135)\r\n\r\n* fix typo in git documentation (#1106)\r\n\r\n* fix: Update the Chinese translation in lr-scheduler.md (#1136)\r\n\r\n* Update lr-scheduler.md\r\n\r\n* Update chapter_optimization/lr-scheduler.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* fix translation for kaggle-house-price.md (#1107)\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\n\r\n* Update weight-decay.md (#1150)\r\n\r\n* Update weight-decay.md\r\n\r\n关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解\r\n关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。\r\n并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释\r\n解释为何会增加复杂性以及为何需要细粒度工具。\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Fix a spelling error (#1161)\r\n\r\n* Update gru.md (#1152)\r\n\r\nThe key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state.\r\n翻译错误\r\n\r\n* Unify the function naming (#1113)\r\n\r\nUnify naming of the function 'init_xavier()'.\r\n\r\n* Update mlp-concise.md (#1166)\r\n\r\n* Update mlp-concise.md\r\n\r\n语句不通顺\r\n\r\n* Update environment.md\r\n\r\n语序异常\r\n\r\n* Update config.ini\r\n\r\n* fix the imprecise description (#1168)\r\n\r\nCo-authored-by: yuande <yuande>\r\n\r\n* fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175)\r\n\r\n* Fix some typos. (#1163)\r\n\r\n* Update batch-norm.md (#1170)\r\n\r\nfixing typos u->x in article\r\n\r\n* Update linear-regression.md (#1090)\r\n\r\nWe invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that\r\n\r\n原译文把who也直接翻译出来了。\r\n\r\n* Update mlp.md (#1117)\r\n\r\n* Update mlp.md\r\n\r\n修改部分语义表述\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Correct a translation error. (#1091)\r\n\r\n* Correct a translation error.\r\n\r\n* Update chapter_computer-vision/image-augmentation.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update aws.md (#1121)\r\n\r\n* Update aws.md\r\n\r\n* Update chapter_appendix-tools-for-deep-learning/aws.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update image-augmentation.md (#1093)\r\n\r\n* Update anchor.md (#1088)\r\n\r\nfix a minor issue in  code\r\n\r\n* Update anchor.md\r\n\r\n* Update image-augmentation.md\r\n\r\n* fix typo and improve translation in chapter_linear-networks\\softmax-regression.md (#1087)\r\n\r\n* Avoid `torch.meshgrid` user warning (#1174)\r\n\r\nAvoids the following user warning:\r\n```python\r\n~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2228.)\r\n  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\r\n```\r\n\r\n* bump to 2.0.0-beta1\r\n\r\n* Update sequence.md\r\n\r\n* bump beta1 on readme\r\n\r\n* Add latex code block background to config\r\n\r\n* BLD: Bump python support version 3.9 (#1183)\r\n\r\n* BLD: Bump python support version 3.9\r\n\r\n* Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4\r\n\r\n* BLD: Bump torch and tensorflow\r\n\r\n* Update Jenkinsfile\r\n\r\n* Update chapter_installation/index.md\r\n\r\n* Update chapter_installation/index.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update config.ini\r\n\r\n* Update INFO.md\r\n\r\n* Update INFO.md\r\n\r\n* Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187)\r\n\r\n* resolve the conflicts\r\n\r\n* revise from publisher (#1089)\r\n\r\n* revise from publisher\r\n\r\n* d2l api\r\n\r\n* post_latex\r\n\r\n* revise from publisher\r\n\r\n* revise ch11\r\n\r\n* Delete d2l-Copy1.bib\r\n\r\n* clear cache\r\n\r\n* rm d2lbook clear\r\n\r\n* debug anchor\r\n\r\n* keep original d2l doc\r\n\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\n\r\n* 重复语句 (#1188)\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improve expression for chapter_preliminaries/pandas.md (#1184)\r\n\r\n* Update pandas.md\r\n\r\n* Improve expression\r\n\r\n* Improve expression\r\n\r\n* Update chapter_preliminaries/pandas.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improce expression for chapter_preliminaries/linear-algebra.md (#1185)\r\n\r\n* Improce expression\r\n\r\n* Improve code comments\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Fix multibox_detection bugs\r\n\r\n* Update d2l to 0.17.5 version\r\n\r\n* restore older version\r\n\r\n* Upgrade pandas\r\n\r\n* change to python3.8\r\n\r\n* Test warning log\r\n\r\n* relocate  warning log\r\n\r\n* test logs filtering\r\n\r\n* Update gru.md\r\n\r\n* Add DeprecationWarning filter\r\n\r\n* Test warning log\r\n\r\n* Update attention mechanisms & computational performance\r\n\r\n* Update multilayer perceptron& linear & convolution networks & computer vision\r\n\r\n* Update recurrent&optimition&nlp pretraining & nlp applications\r\n\r\n* ignore warnings\r\n\r\n* Update index.md\r\n\r\n* Update linear networks\r\n\r\n* Update multilayer perceptrons&deep learning computation\r\n\r\n* Update preliminaries\r\n\r\n* Check and Add warning filter\r\n\r\n* Update kaggle-cifar10.md\r\n\r\n* Update object-detection-dataset.md\r\n\r\n* Update ssd.md fcn.md\r\n\r\n* Update hybridize.md\r\n\r\n* Update hybridize.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\nCo-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com>\r\nCo-authored-by: Xinwei Liu <xinzone@outlook.com>\r\nCo-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com>\r\nCo-authored-by: gyro永不抽风 <1247006353@qq.com>\r\nCo-authored-by: CanChengZheng <zcc550169544@163.com>\r\nCo-authored-by: linlin <jajupmochi@gmail.com>\r\nCo-authored-by: iuk <liukun0104@gmail.com>\r\nCo-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com>\r\nCo-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com>\r\nCo-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com>\r\nCo-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com>\r\nCo-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com>\r\nCo-authored-by: Ming Liu <akira.liu@njnu.edu.cn>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\nCo-authored-by: silenceZheng66 <13754430639@163.com>\r\nCo-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com>\r\nCo-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com>\r\nCo-authored-by: Krahets <krahets@163.com>\r\nCo-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com>\r\nCo-authored-by: Jameson <miraclecome@gmail.com>\r\nCo-authored-by: P. 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        "code": "def try_all_gpus():\n    \n    num_gpus = len(tf.config.experimental.list_physical_devices('GPU'))\n    devices = [tf.device(f'/GPU:{i}') for i in range(num_gpus)]\n    return devices if devices else [tf.device('/CPU:0')]\n",
        "url": "https://github.com/d2l-ai/d2l-zh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 30,
        "n_words": 18,
        "vocab_size": 15,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 51,
        "n_ast_nodes": 91,
        "n_identifiers": 11,
        "d_id": 37441,
        "documentation": {
            "docstring": "Return all available GPUs, or [cpu(),] if no GPU exists.\n\n    Defined in :numref:`sec_use_gpu`",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 148314,
        "commit_id": "732175e2458ec671c80484bcd35150dcdc7e600b",
        "repo": "ray",
        "path": "python/ray/ml/examples/pytorch_geometric/distributed_sage_example.py",
        "file_name": "distributed_sage_example.py",
        "fun_name": "gen_fake_dataset",
        "commit_message": "[AIR] Add distributed `torch_geometric` example (#23580)\n\nAdd example for distributed pytorch geometric (graph learning) with Ray AIR\r\n\r\nThis only showcases distributed training, but with data small enough that it can be loaded in by each training worker individually. Distributed data ingest is out of scope for this PR.\r\n\r\nCo-authored-by: matthewdeng <matthew.j.deng@gmail.com>",
        "code": "def gen_fake_dataset():\n    \n\n    # For fake dataset, since the dataset is randomized, we create it once on the\n    # driver, and then send the same dataset to all the training workers.\n    # Use 10% of nodes for validation and 10% for testing.\n    fake_dataset = FakeDataset(transform=RandomNodeSplit(num_val=0.1, num_test=0.1))\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 60,
        "n_words": 45,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 30,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 34236,
        "documentation": {
            "docstring": "Returns a function to be called on each worker that returns a Fake Dataset.",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 221674,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/configparser.py",
        "file_name": "configparser.py",
        "fun_name": "read_dict",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def read_dict(self, dictionary, source='<dict>'):\n        \n        elements_added = set()\n        for section, keys in dictionary.items():\n            section = str(section)\n            try:\n                self.add_section(section)\n            except (DuplicateSectionError, ValueError):\n                if self._strict and section in elements_added:\n                    raise\n            elements_added.add(section)\n            for key, value in keys.items():\n                key = self.optionxform(str(key))\n                if value is not None:\n                    value = str(value)\n                if self._strict and (section, key) in elements_added:\n                    raise DuplicateOptionError(section, key, source)\n                elements_added.add((section, key))\n                self.set(section, key, value)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 298,
        "n_words": 60,
        "vocab_size": 42,
        "complexity": 9,
        "nloc": 18,
        "token_counts": 141,
        "n_ast_nodes": 222,
        "n_identifiers": 19,
        "d_id": 56469,
        "documentation": {
            "docstring": "Read configuration from a dictionary.\n\n        Keys are section names, values are dictionaries with keys and values\n        that should be present in the section. If the used dictionary type\n        preserves order, sections and their keys will be added in order.\n\n        All types held in the dictionary are converted to strings during\n        reading, including section names, option names and keys.\n\n        Optional second argument is the `source' specifying the name of the\n        dictionary being read.\n        ",
            "n_words": 72,
            "vocab_size": 54,
            "n_whitespaces": 128,
            "language": "en"
        }
    },
    {
        "id": 146198,
        "commit_id": "1100c982223757f697a410a0d0c3d8bf3ff9c805",
        "repo": "ray",
        "path": "python/ray/serve/api.py",
        "file_name": "api.py",
        "fun_name": "get_deployment_statuses",
        "commit_message": "[serve] Implement Serve Application object (#22917)\n\nThe concept of a Serve Application, a data structure containing all information needed to deploy Serve on a Ray cluster, has surfaced during recent design discussions. This change introduces a formal Application data structure and refactors existing code to use it.",
        "code": "def get_deployment_statuses() -> Dict[str, DeploymentStatusInfo]:\n    \n\n    return internal_get_global_client().get_deployment_statuses()\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 13,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 20,
        "n_ast_nodes": 35,
        "n_identifiers": 5,
        "d_id": 33628,
        "documentation": {
            "docstring": "Returns a dictionary of deployment statuses.\n\n    A deployment's status is one of {UPDATING, UNHEALTHY, and HEALTHY}.\n\n    Example:\n\n    >>> statuses = get_deployment_statuses()\n    >>> status_info = statuses[\"deployment_name\"]\n    >>> status = status_info.status\n    >>> message = status_info.message\n\n    Returns:\n            Dict[str, DeploymentStatus]: This dictionary maps the running\n                deployment's name to a DeploymentStatus object containing its\n                status and a message explaining the status.\n    ",
            "n_words": 56,
            "vocab_size": 40,
            "n_whitespaces": 121,
            "language": "en"
        }
    },
    {
        "id": 292362,
        "commit_id": "c496748125b811ef5437ad666d21c09025e0967f",
        "repo": "core",
        "path": "tests/components/config/test_device_registry.py",
        "file_name": "test_device_registry.py",
        "fun_name": "test_remove_config_entry_from_device_fails",
        "commit_message": "Add WS API for removing a config entry from a device (#66188)\n\n* Add WS API for removing a config entry from a device\r\n\r\n* Address review comments\r\n\r\n* Address review comments\r\n\r\n* Remove entity cleanup from ConfigEntries\r\n\r\n* Update + add tests\r\n\r\n* Improve comments in test\r\n\r\n* Add negative test\r\n\r\n* Refactor according to review comments\r\n\r\n* Add back async_remove_config_entry_device\r\n\r\n* Remove unnecessary error handling\r\n\r\n* Simplify error handling",
        "code": "async def test_remove_config_entry_from_device_fails(hass, hass_ws_client):\n    \n    assert await async_setup_component(hass, \"config\", {})\n    ws_client = await hass_ws_client(hass)\n    device_registry = mock_device_registry(hass)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 28,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 132,
        "token_counts": 617,
        "n_ast_nodes": 56,
        "n_identifiers": 7,
        "d_id": 91454,
        "documentation": {
            "docstring": "Test removing config entry from device failing cases.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 176826,
        "commit_id": "ad99a5862264355d5eaaa309136475bfb9a66c12",
        "repo": "networkx",
        "path": "networkx/generators/geometric.py",
        "file_name": "geometric.py",
        "fun_name": "geometric_edges",
        "commit_message": "Add default value p=2 for minkowski distance metric. (#5700)",
        "code": "def geometric_edges(G, radius, p=2):\n    \n    nodes_pos = G.nodes(data=\"pos\")\n    try:\n        import scipy as sp\n        import scipy.spatial  # call as sp.spatial\n    except ImportError:\n        # no scipy KDTree so compute by for-loop\n        radius_p = radius**p\n        edges = [\n            (u, v)\n            for (u, pu), (v, pv) in combinations(nodes_pos, 2)\n            if sum(abs(a - b) ** p for a, b in zip(pu, pv)) <= radius_p\n        ]\n        return edges\n    # scipy KDTree is available\n    nodes, coords = list(zip(*nodes_pos))\n    kdtree = sp.spatial.cKDTree(coords)  # Cannot provide generator.\n    edge_indexes = kdtree.query_pairs(radius, p)\n    edges = [(nodes[u], nodes[v]) for u, v in sorted(edge_indexes)]\n    return edges\n\n\n@py_random_state(5)",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@py_random_state(5)",
        "n_ast_errors": 1,
        "ast_levels": 18,
        "n_whitespaces": 206,
        "n_words": 93,
        "vocab_size": 69,
        "complexity": 6,
        "nloc": 18,
        "token_counts": 153,
        "n_ast_nodes": 247,
        "n_identifiers": 31,
        "d_id": 42122,
        "documentation": {
            "docstring": "Returns edge list of node pairs within `radius` of each other.\n\n    Parameters\n    ----------\n    G : networkx graph\n        The graph from which to generate the edge list. The nodes in `G` should\n        have an attribute ``pos`` corresponding to the node position, which is\n        used to compute the distance to other nodes.\n    radius : scalar\n        The distance threshold. Edges are included in the edge list if the\n        distance between the two nodes is less than `radius`.\n    p : scalar, default=2\n        The `Minkowski distance metric\n        <https://en.wikipedia.org/wiki/Minkowski_distance>`_ used to compute\n        distances. The default value is 2, i.e. Euclidean distance.\n\n    Returns\n    -------\n    edges : list\n        List of edges whose distances are less than `radius`\n\n    Notes\n    -----\n    Radius uses Minkowski distance metric `p`.\n    If scipy is available, `scipy.spatial.cKDTree` is used to speed computation.\n\n    Examples\n    --------\n    Create a graph with nodes that have a \"pos\" attribute representing 2D\n    coordinates.\n\n    >>> G = nx.Graph()\n    >>> G.add_nodes_from([\n    ...     (0, {\"pos\": (0, 0)}),\n    ...     (1, {\"pos\": (3, 0)}),\n    ...     (2, {\"pos\": (8, 0)}),\n    ... ])\n    >>> nx.geometric_edges(G, radius=1)\n    []\n    >>> nx.geometric_edges(G, radius=4)\n    [(0, 1)]\n    >>> nx.geometric_edges(G, radius=6)\n    [(0, 1), (1, 2)]\n    >>> nx.geometric_edges(G, radius=9)\n    [(0, 1), (0, 2), (1, 2)]\n    ",
            "n_words": 190,
            "vocab_size": 115,
            "n_whitespaces": 358,
            "language": "en"
        }
    },
    {
        "id": 222330,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/dataclasses.py",
        "file_name": "dataclasses.py",
        "fun_name": "fields",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def fields(class_or_instance):\n    \n\n    # Might it be worth caching this, per class?\n    try:\n        fields = getattr(class_or_instance, _FIELDS)\n    except AttributeError:\n        raise TypeError('must be called with a dataclass type or instance')\n\n    # Exclude pseudo-fields.  Note that fields is sorted by insertion\n    # order, so the order of the tuple is as the fields were defined.\n    return tuple(f for f in fields.values() if f._field_type is _FIELD)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 98,
        "n_words": 62,
        "vocab_size": 53,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 76,
        "n_identifiers": 11,
        "d_id": 56538,
        "documentation": {
            "docstring": "Return a tuple describing the fields of this dataclass.\n\n    Accepts a dataclass or an instance of one. Tuple elements are of\n    type Field.\n    ",
            "n_words": 23,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 198397,
        "commit_id": "7d773eb18daaef3c54f34d1ac6cbc5b83a5bb16c",
        "repo": "sympy",
        "path": "sympy/polys/ring_series.py",
        "file_name": "ring_series.py",
        "fun_name": "_invert_monoms",
        "commit_message": "Cleanup loops and ranges",
        "code": "def _invert_monoms(p1):\n    \n    terms = list(p1.items())\n    terms.sort()\n    deg = p1.degree()\n    R = p1.ring\n    p = R.zero\n    cv = p1.listcoeffs()\n    mv = p1.listmonoms()\n    for mvi, cvi in zip(mv, cv):\n        p[(deg - mvi[0],)] = cvi\n    return p\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 34,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 80,
        "n_ast_nodes": 131,
        "n_identifiers": 19,
        "d_id": 48908,
        "documentation": {
            "docstring": "\n    Compute ``x**n * p1(1/x)`` for a univariate polynomial ``p1`` in ``x``.\n\n    Examples\n    ========\n\n    >>> from sympy.polys.domains import ZZ\n    >>> from sympy.polys.rings import ring\n    >>> from sympy.polys.ring_series import _invert_monoms\n    >>> R, x = ring('x', ZZ)\n    >>> p = x**2 + 2*x + 3\n    >>> _invert_monoms(p)\n    3*x**2 + 2*x + 1\n\n    See Also\n    ========\n\n    sympy.polys.densebasic.dup_reverse\n    ",
            "n_words": 53,
            "vocab_size": 38,
            "n_whitespaces": 96,
            "language": "en"
        }
    },
    {
        "id": 205955,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/fields.py",
        "file_name": "fields.py",
        "fun_name": "to_python",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def to_python(self, value):\n        \n        value = super().to_python(value)\n        if value in self.empty_values:\n            return None\n        if self.localize:\n            value = formats.sanitize_separators(value)\n        # Strip trailing decimal and zeros.\n        try:\n            value = int(self.re_decimal.sub(\"\", str(value)))\n        except (ValueError, TypeError):\n            raise ValidationError(self.error_messages[\"invalid\"], code=\"invalid\")\n        return value\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 136,
        "n_words": 36,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 83,
        "n_ast_nodes": 139,
        "n_identifiers": 17,
        "d_id": 51297,
        "documentation": {
            "docstring": "\n        Validate that int() can be called on the input. Return the result\n        of int() or None for empty values.\n        ",
            "n_words": 19,
            "vocab_size": 17,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 109746,
        "commit_id": "4896ec1a2cfb8c454e385632d8df213c915ced52",
        "repo": "matplotlib",
        "path": "lib/mpl_toolkits/mplot3d/axes3d.py",
        "file_name": "axes3d.py",
        "fun_name": "_zoom_data_limits",
        "commit_message": "Add pan and zoom toolbar handling to 3D Axes (Replaces PR#22614) (#23449)\n\n* ENH: Add pan and zoom toolbar handling to 3D Axes\r\n\r\n1) This moves the pan logic that was already in the mouse move handler\r\ninto the \"drag_pan\" method to make it available from the toolbar.\r\n\r\n2) This expands upon the panning logic to enable a zoom-to-box feature.\r\nThe zoom-to-box is done relative to the Axes, so it shrinks/expands\r\nthe box as a fraction of each delta, from lower-left Axes to lower-left\r\nzoom-box. Thus, it tries to handle non-centered zooms, which adds more\r\ncases to handle versus the current right-click zoom only scaling from\r\nthe center of the projection.\r\n\r\n* Rewrite zooming with bounding box\r\n\r\n* Rewrite 3d panning to work with a roll angle\r\n\r\n* Whats new for zoom and pan buttons\r\n\r\n* Make pan button configurable\r\n\r\n* Do not jump when zooming and mouse goes over other subplot\r\n\r\n* Rework zooming for 3d plots\r\n\r\n* Handle x/y lock when zooming and panning\r\n\r\n* Update tests\r\n\r\n* Docstrings\r\n\r\n* Dont assume a scale_z\r\n\r\n* Limit zoom box\r\n\r\n* Test zoom pan key modifiers\r\n\r\n* Save some calculation by saving view axes\r\n\r\n* Deprecation warnings for Axes3D.eye, .vvec\r\n\r\n* Remove Axes3D._prepare_view_from_bbox for now\r\n\r\n* Comments and docstrings\r\n\r\n* Switch from uvn to uvw\r\n\r\n* Save aspect to axes\r\n\r\n* Constrain zooming with mouse when one of the equal aspect ratios is set\r\n\r\n* Cleanup\r\n\r\n* Cleanup\r\n\r\n* Consolidate finding equal aspect axis indices\r\n\r\n* linting\r\n\r\n* More intuitive scaling\r\n\r\n* Box zoom keeps existing aspect ratios\r\n\r\n* Linting\r\n\r\n* Code review comments\r\n\r\n* Revert parameters for view_transformation\r\n\r\n* Fix new 3d pan/zoom view going on view stack twice\r\n\r\n* Better clipping\r\n\r\n* Test 3d toolbar navigation\r\n\r\n* Privatize helper functions\r\n\r\n* Deprecations\r\n\r\n* Code review changes\r\n\r\n* Deprecation note\r\n\r\n* Undeprecate proj3d.view_transformation\r\n\r\n* Undeprecate proj3d.view_transformation\r\n\r\n* Update doc/api/next_api_changes/deprecations/23449-SS.rst\r\n\r\n\r\nCo-authored-by: Greg Lucas <greg.m.lucas@gmail.com>\r\nCo-authored-by: Scott Shambaugh <scottshambaugh@users.noreply.github.com>\r\nCo-authored-by: Oscar Gustafsson <oscar.gustafsson@gmail.com>",
        "code": "def _zoom_data_limits(self, scale_u, scale_v, scale_w):\n        \n        scale = np.array([scale_u, scale_v, scale_w])\n\n        # Only perform frame conversion if unequal scale factors\n        if not np.allclose(scale, scale_u):\n            # Convert the scale factors from the view frame to the data frame\n            R = np.array([self._view_u, self._view_v, self._view_w])\n            S = scale * np.eye(3)\n            scale = np.linalg.norm(R.T @ S, axis=1)\n\n            # Set the constrained scale factors to the factor closest to 1\n            if self._aspect in ('equal', 'equalxy', 'equalxz', 'equalyz'):\n                ax_idxs = self._equal_aspect_axis_indices(self._aspect)\n                min_ax_idxs = np.argmin(np.abs(scale[ax_idxs] - 1))\n                scale[ax_idxs] = scale[ax_idxs][min_ax_idxs]\n\n        self._scale_axis_limits(scale[0], scale[1], scale[2])\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 231,
        "n_words": 85,
        "vocab_size": 59,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 159,
        "n_ast_nodes": 246,
        "n_identifiers": 26,
        "d_id": 23730,
        "documentation": {
            "docstring": "\n        Zoom in or out of a 3D plot.\n        Will scale the data limits by the scale factors. These will be\n        transformed to the x, y, z data axes based on the current view angles.\n        A scale factor > 1 zooms out and a scale factor < 1 zooms in.\n\n        For an axes that has had its aspect ratio set to 'equal', 'equalxy',\n        'equalyz', or 'equalxz', the relevant axes are constrained to zoom\n        equally.\n\n        Parameters\n        ----------\n        scale_u : float\n            Scale factor for the u view axis (view screen horizontal).\n        scale_v : float\n            Scale factor for the v view axis (view screen vertical).\n        scale_w : float\n            Scale factor for the w view axis (view screen depth).\n        ",
            "n_words": 114,
            "vocab_size": 73,
            "n_whitespaces": 239,
            "language": "en"
        }
    },
    {
        "id": 9859,
        "commit_id": "933415bfa1f9eb89f935037014dfed816eb9815d",
        "repo": "jina",
        "path": "jina/peapods/peas/container.py",
        "file_name": "container.py",
        "fun_name": "start",
        "commit_message": "feat: star routing (#3900)\n\n* feat(proto): adjust proto for star routing (#3844)\r\n\r\n* feat(proto): adjust proto for star routing\r\n\r\n* feat(proto): generate proto files\r\n\r\n* feat(grpc): refactor grpclet interface (#3846)\r\n\r\n* feat: refactor connection pool for star routing (#3872)\r\n\r\n* feat(k8s): add more labels to k8s deployments\r\n\r\n* feat(network): refactor connection pool\r\n\r\n* feat(network): refactor k8s pool\r\n\r\n* feat: star routing graph gateway (#3877)\r\n\r\n* feat: star routing - refactor grpc data runtime (#3887)\r\n\r\n* feat(runtimes): refactor grpc dataruntime\r\n\r\n* fix(tests): adapt worker runtime tests\r\n\r\n* fix(import): fix import\r\n\r\n* feat(proto): enable sending multiple lists (#3891)\r\n\r\n* feat: star routing gateway (#3893)\r\n\r\n* feat: star routing gateway all protocols (#3897)\r\n\r\n* test: add streaming and prefetch tests (#3901)\r\n\r\n* feat(head): new head runtime for star routing (#3899)\r\n\r\n* feat(head): new head runtime\r\n\r\n* feat(head): new head runtime\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(network): improve proto comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(worker): merge docs in worker runtime (#3905)\r\n\r\n* feat(worker): merge docs in worker runtime\r\n\r\n* feat(tests): assert after clean up\r\n\r\n* feat(tests): star routing runtime integration tests (#3908)\r\n\r\n* fix(tests): fix integration tests\r\n\r\n* test: test runtimes fast slow request (#3910)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table (#3915)\r\n\r\n* feat(zmq): purge zmq, zed, routing_table\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(zmq): adapt comment in dependency list\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix type tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: add test gateway to worker connection (#3921)\r\n\r\n* feat(pea): adapt peas for star routing (#3918)\r\n\r\n* feat(pea): adapt peas for star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(pea): add tests\r\n\r\n* feat(tests): add failing head pea test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(tests): integration tests for peas (#3923)\r\n\r\n* feat(tests): integration tests for peas\r\n\r\n* feat(pea): remove _inner_pea function\r\n\r\n* feat: star routing container pea (#3922)\r\n\r\n* test: rescue tests (#3942)\r\n\r\n* fix: fix streaming tests (#3945)\r\n\r\n* refactor: move docker run to run (#3948)\r\n\r\n* feat: star routing pods (#3940)\r\n\r\n* feat(pod): adapt pods for star routing\r\n\r\n* feat(pods): adapt basepod to star routing\r\n\r\n* feat(pod): merge pod and compound pod\r\n\r\n* feat(tests): fix tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(test): add container pea int test\r\n\r\n* feat(ci): remove more unnecessary tests\r\n\r\n* fix(tests): remove jinad runtime\r\n\r\n* feat(ci): remove latency tracking\r\n\r\n* fix(ci): fix ci def\r\n\r\n* fix(runtime): enable runtime to be exited\r\n\r\n* fix(tests): wrap runtime test in process\r\n\r\n* fix(runtimes): remove unused runtimes\r\n\r\n* feat(runtimes): improve cancel wait\r\n\r\n* fix(ci): build test pip again in ci\r\n\r\n* fix(tests): fix a test\r\n\r\n* fix(test): run async in its own process\r\n\r\n* feat(pod): include shard in activate msg\r\n\r\n* fix(pea): dont join\r\n\r\n* feat(pod): more debug out\r\n\r\n* feat(grpc): manage channels properly\r\n\r\n* feat(pods): remove exitfifo\r\n\r\n* feat(network): add simple send retry mechanism\r\n\r\n* fix(network): await pool close\r\n\r\n* fix(test): always close grpc server in worker\r\n\r\n* fix(tests): remove container pea from tests\r\n\r\n* fix(tests): reorder tests\r\n\r\n* fix(ci): split tests\r\n\r\n* fix(ci): allow alias setting\r\n\r\n* fix(test): skip a test\r\n\r\n* feat(pods): address comments\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* test: unblock skipped test (#3957)\r\n\r\n* feat: jinad pea (#3949)\r\n\r\n* feat: jinad pea\r\n\r\n* feat: jinad pea\r\n\r\n* test: remote peas\r\n\r\n* test: toplogy tests with jinad\r\n\r\n* ci: parallel jobs\r\n\r\n* feat(tests): add pod integration tests (#3958)\r\n\r\n* feat(tests): add pod integration tests\r\n\r\n* fix(tests): make tests less flaky\r\n\r\n* fix(test): fix test\r\n\r\n* test(pea): remote pea topologies (#3961)\r\n\r\n* test(pea): remote pea simple topology\r\n\r\n* test: remote pea topologies\r\n\r\n* refactor: refactor streamer result handling (#3960)\r\n\r\n* feat(k8s): adapt K8s Pod for StarRouting (#3964)\r\n\r\n* test: optimize k8s test\r\n\r\n* test: increase timeout and use different namespace\r\n\r\n* test: optimize k8s test\r\n\r\n* test: build and load image when needed\r\n\r\n* test: refactor k8s test\r\n\r\n* test: fix image name error\r\n\r\n* test: fix k8s image load\r\n\r\n* test: fix typoe port expose\r\n\r\n* test: update tests in connection pool and handling\r\n\r\n* test: remove unused fixture\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* test: parameterize docker images\r\n\r\n* feat(k8s): adapt k8s pod for star routing\r\n\r\n* fix(k8s): dont overwrite add/remove function in pool\r\n\r\n* fix(k8s): some fixes\r\n\r\n* fix(k8s): some more fixes\r\n\r\n* fix(k8s): linting\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix k8s unit tests\r\n\r\n* feat(k8s): complete k8s integration test\r\n\r\n* feat(k8s): finish k8s tests\r\n\r\n* feat(k8s): fix test\r\n\r\n* fix(tests): fix test with no name\r\n\r\n* feat(k8s): unify create/replace interface\r\n\r\n* feat(k8s): extract k8s port constants\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): wait for runtime being ready in tests\r\n\r\n* feat(k8s): address comments\r\n\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\n\r\n* feat(flow): adapt Flow for StarRouting (#3986)\r\n\r\n* feat(flow): add routes\r\n\r\n* feat(flow): adapt flow to star routing\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(flow): handle empty topologies\r\n\r\n* feat(k8s): allow k8s pool disabling\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(test): fix test with mock\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(flow): clean up tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat: add plot function (#3994)\r\n\r\n* fix(tests): avoid hanging tests\r\n\r\n* feat(flow): add type hinting\r\n\r\n* fix(test): fix duplicate exec name in test\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): enable jinad test again\r\n\r\n* fix(tests): random port fixture\r\n\r\n* fix(style): replace quotes\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(ci): bring back ci (#3997)\r\n\r\n* feat(ci): enable ci again\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat(ci): add latency tracking\r\n\r\n* feat(ci): bring back some tests\r\n\r\n* fix(tests): remove invalid port test\r\n\r\n* feat(ci): disable daemon and distributed tests\r\n\r\n* fix(tests): fix entrypoint in hub test\r\n\r\n* fix(tests): wait for gateway to be ready\r\n\r\n* fix(test): fix more tests\r\n\r\n* feat(flow): do rolling update and scale sequentially\r\n\r\n* fix(tests): fix more tests\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* feat: star routing hanging pods (#4011)\r\n\r\n* fix: try to handle hanging pods better\r\n\r\n* test: hanging pods test work\r\n\r\n* fix: fix topology graph problem\r\n\r\n* test: add unit test to graph\r\n\r\n* fix(tests): fix k8s tests\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s pool test\r\n\r\n* fix(test): fix k8s test\r\n\r\n* fix(test): fix k8s connection pool setting\r\n\r\n* fix(tests): make runtime test more reliable\r\n\r\n* fix(test): fix routes test\r\n\r\n* fix(tests): make rolling update test less flaky\r\n\r\n* feat(network): gurantee unique ports\r\n\r\n* feat(network): do round robin for shards\r\n\r\n* fix(ci): increase pytest timeout to 10 min\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix(ci): fix ci file\r\n\r\n* feat(daemon): jinad pod for star routing\r\n\r\n* Revert \"feat(daemon): jinad pod for star routing\"\r\n\r\nThis reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92.\r\n\r\n* feat(daemon): remote jinad pod support (#4042)\r\n\r\n* feat(daemon): add pod tests for star routing\r\n\r\n* feat(daemon): add remote pod test\r\n\r\n* test(daemon): add remote pod arguments test\r\n\r\n* test(daemon): add async scale test\r\n\r\n* test(daemon): add rolling update test\r\n\r\n* test(daemon): fix host\r\n\r\n* feat(proto): remove message proto (#4051)\r\n\r\n* feat(proto): remove message proto\r\n\r\n* fix(tests): fix tests\r\n\r\n* fix(tests): fix some more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* fix(tests): fix more tests\r\n\r\n* feat(proto): put docs back in data\r\n\r\n* fix(proto): clean up\r\n\r\n* feat(proto): clean up\r\n\r\n* fix(tests): skip latency tracking\r\n\r\n* fix(test): fix hub test\r\n\r\n* fix(tests): fix k8s test\r\n\r\n* fix(test): some test clean up\r\n\r\n* fix(style): clean up style issues\r\n\r\n* feat(proto): adjust for rebase\r\n\r\n* fix(tests): bring back latency tracking\r\n\r\n* fix(tests): fix merge accident\r\n\r\n* feat(proto): skip request serialization (#4074)\r\n\r\n* feat: add reduce to star routing (#4070)\r\n\r\n* feat: add reduce on shards to head runtime\r\n\r\n* test: add reduce integration tests with fixed order\r\n\r\n* feat: add reduce on needs\r\n\r\n* chore: get_docs_matrix_from_request becomes public\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* docs: remove undeterministic results warning\r\n\r\n* fix: fix uses_after\r\n\r\n* test: assert correct num docs after reducing in test_external_pod\r\n\r\n* test: correct asserts after reduce in test_rolling_update\r\n\r\n* fix: no reduce if uses_after_address is set\r\n\r\n* fix: get_docs_from_request only if needed\r\n\r\n* fix: fix tests after merge\r\n\r\n* refactor: move reduce from data_request_handler to head\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* chore: apply suggestions\r\n\r\n* fix: fix asserts\r\n\r\n* chore: minor test fix\r\n\r\n* chore: apply suggestions\r\n\r\n* test: remove flow tests with external executor (pea)\r\n\r\n* fix: fix test_expected_messages_routing\r\n\r\n* fix: fix test_func_joiner\r\n\r\n* test:  adapt k8s test\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix(k8s): fix static pool config\r\n\r\n* fix: use custom protoc doc generator image (#4088)\r\n\r\n* fix: use custom protoc doc generator image\r\n\r\n* fix(docs): minor doc improvement\r\n\r\n* fix(docs): use custom image\r\n\r\n* fix(docs): copy docarray\r\n\r\n* fix: doc building local only\r\n\r\n* fix: timeout doc building\r\n\r\n* fix: use updated args when building ContainerPea\r\n\r\n* test: add container PeaFactory test\r\n\r\n* fix: force pea close on windows (#4098)\r\n\r\n* fix: dont reduce if uses exist (#4099)\r\n\r\n* fix: dont use reduce if uses exist\r\n\r\n* fix: adjust reduce tests\r\n\r\n* fix: adjust more reduce tests\r\n\r\n* fix: fix more tests\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: ignore non jina resources (#4101)\r\n\r\n* feat(executor): enable async executors (#4102)\r\n\r\n* feat(daemon): daemon flow on star routing (#4096)\r\n\r\n* test(daemon): add remote flow test\r\n\r\n* feat(daemon): call scale in daemon\r\n\r\n* feat(daemon): remove tail args and identity\r\n\r\n* test(daemon): rename scalable executor\r\n\r\n* test(daemon): add a small delay in async test\r\n\r\n* feat(daemon): scale partial flow only\r\n\r\n* feat(daemon): call scale directly in partial flow store\r\n\r\n* test(daemon): use asyncio sleep\r\n\r\n* feat(daemon): enable flow level distributed tests\r\n\r\n* test(daemon): fix jinad env workspace config\r\n\r\n* test(daemon): fix pod test use new port rolling update\r\n\r\n* feat(daemon): enable distribuetd tests\r\n\r\n* test(daemon): remove duplicate tests and zed runtime test\r\n\r\n* test(daemon): fix stores unit test\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* feat(daemon): enable part of distributed tests\r\n\r\n* test: correct test paths\r\n\r\n* test(daemon): add client test for remote flows\r\n\r\n* test(daemon): send a request with jina client\r\n\r\n* test(daemon): assert async generator\r\n\r\n* test(daemon): small interval between tests\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): add flow test for container runtime\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): fix executor name\r\n\r\n* test(daemon): use async client fetch result\r\n\r\n* test(daemon): finish container flow test\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): enable distributed in ci\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): debug ci if else\r\n\r\n* test(daemon): decare flows and pods\r\n\r\n* test(daemon): correct test paths\r\n\r\n* test(daemon): add small delay for async tests\r\n\r\n* fix: star routing fixes (#4100)\r\n\r\n* docs: update docs\r\n\r\n* fix: fix Request.__repr__\r\n\r\n* docs: update flow remarks\r\n\r\n* docs: fix typo\r\n\r\n* test: add non_empty_fields test\r\n\r\n* chore: remove non_empty_fields test\r\n\r\n* feat: polling per endpoint (#4111)\r\n\r\n* feat(polling): polling per endpoint configurable\r\n\r\n* fix: adjust tests\r\n\r\n* feat(polling): extend documentation\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: clean up\r\n\r\n* fix: adjust more tests\r\n\r\n* fix: remove repeat from flaky test\r\n\r\n* fix: k8s test\r\n\r\n* feat(polling): address pr feedback\r\n\r\n* feat: improve docs\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* feat(grpc): support connect grpc server via ssl tunnel (#4092)\r\n\r\n* feat(grpc): support ssl grpc connect if port is 443\r\n\r\n* fix(grpc): use https option instead of detect port automatically\r\n\r\n* chore: fix typo\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* fix: update jina/peapods/networking.py\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* test(networking): add test for peapods networking\r\n\r\n* fix: address comments\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\n\r\n* feat(polling): unify polling args (#4113)\r\n\r\n* fix: several issues for jinad pods (#4119)\r\n\r\n* fix: activate for jinad pods\r\n\r\n* fix: dont expose worker pod in partial daemon\r\n\r\n* fix: workspace setting\r\n\r\n* fix: containerized flows\r\n\r\n* fix: hub test\r\n\r\n* feat(daemon): remote peas on star routing (#4112)\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix request in peas\r\n\r\n* test(daemon): fix sync async client test\r\n\r\n* test(daemon): enable remote peas test\r\n\r\n* test(daemon): replace send message to send request\r\n\r\n* test(daemon): declare pea tests in ci\r\n\r\n* test(daemon): use pea args fixture\r\n\r\n* test(daemon): head pea use default host\r\n\r\n* test(daemon): fix peas topologies\r\n\r\n* test(daemon): fix pseudo naming\r\n\r\n* test(daemon): use default host as host\r\n\r\n* test(daemon): fix executor path\r\n\r\n* test(daemon): add remote worker back\r\n\r\n* test(daemon): skip local remote remote topology\r\n\r\n* fix: jinad pea test setup\r\n\r\n* fix: jinad pea tests\r\n\r\n* fix: remove invalid assertion\r\n\r\nCo-authored-by: jacobowitz <tobias.jacobowitz@posteo.de>\r\n\r\n* feat: enable daemon tests again (#4132)\r\n\r\n* feat: enable daemon tests again\r\n\r\n* fix: remove bogy empty script file\r\n\r\n* fix: more jinad test fixes\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: scale and ru in jinad\r\n\r\n* fix: fix more jinad tests\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\n\r\n* fix: fix flow test\r\n\r\n* fix: improve pea tests reliability (#4136)\r\n\r\nCo-authored-by: Joan Fontanals <joan.martinez@jina.ai>\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>\r\nCo-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai>\r\nCo-authored-by: bwanglzu <bo.wang@jina.ai>\r\nCo-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr>\r\nCo-authored-by: Zhaofeng Miao <522856232@qq.com>",
        "code": "def start(self):\n        \n        self.worker = _get_worker(\n            args=self.args,\n            target=run,\n            kwargs={\n                'args': self.args,\n                'name': self.name,\n                'container_name': self.container_name,\n                'net_mode': self.net_mode,\n                'runtime_ctrl_address': self.runtime_ctrl_address,\n                'envs': self._envs,\n                'is_started': self.is_started,\n                'is_shutdown': self.is_shutdown,\n                'is_ready': self.is_ready,\n            },\n        )\n        self.worker.start()\n        if not self.args.noblock_on_start:\n            self.wait_start_success()\n        return self\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
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        "documentation": {
            "docstring": "Start the ContainerPea.\n        This method calls :meth:`start` in :class:`threading.Thread` or :class:`multiprocesssing.Process`.\n        .. #noqa: DAR201\n        ",
            "n_words": 14,
            "vocab_size": 14,
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    },
    {
        "id": 20079,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/distro.py",
        "file_name": "distro.py",
        "fun_name": "info",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def info(self, pretty=False, best=False):\n        # type: (bool, bool) -> InfoDict\n        \n        return dict(\n            id=self.id(),\n            version=self.version(pretty, best),\n            version_parts=dict(\n                major=self.major_version(best),\n                minor=self.minor_version(best),\n                build_number=self.build_number(best),\n            ),\n            like=self.like(),\n            codename=self.codename(),\n        )\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
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        "n_identifiers": 15,
        "d_id": 3224,
        "documentation": {
            "docstring": "\n        Return certain machine-readable information about the OS\n        distribution.\n\n        For details, see :func:`distro.info`.\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 12698,
        "commit_id": "c3849c6fee4a65a77a82b2cfda9670d727ff0f53",
        "repo": "jina",
        "path": "jina/types/request/data.py",
        "file_name": "data.py",
        "fun_name": "data",
        "commit_message": "feat: allow to access parameters of data request wo loading data  (#4991)",
        "code": "def data(self) -> 'DataRequest._DataContent':\n        \n        return DataRequest._DataContent(self.proto_with_data.data)\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
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        "complexity": 1,
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        "token_counts": 19,
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        "n_identifiers": 5,
        "d_id": 2384,
        "documentation": {
            "docstring": "Get the data contained in this data request\n\n        :return: the data content as an instance of _DataContent wrapping docs\n        ",
            "n_words": 19,
            "vocab_size": 16,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 247330,
        "commit_id": "2ffaf30803f93273a4d8a65c9e6c3110c8433488",
        "repo": "synapse",
        "path": "tests/rest/client/test_third_party_rules.py",
        "file_name": "test_third_party_rules.py",
        "fun_name": "test_modify_event",
        "commit_message": "Add type hints to `tests/rest/client` (#12108)\n\n* Add type hints to `tests/rest/client`\r\n\r\n* newsfile\r\n\r\n* fix imports\r\n\r\n* add `test_account.py`\r\n\r\n* Remove one type hint in `test_report_event.py`\r\n\r\n* change `on_create_room` to `async`\r\n\r\n* update new functions in `test_third_party_rules.py`\r\n\r\n* Add `test_filter.py`\r\n\r\n* add `test_rooms.py`\r\n\r\n* change to `assertEquals` to `assertEqual`\r\n\r\n* lint",
        "code": "def test_modify_event(self) -> None:\n        \n        # first patch the event checker so that it will modify the event",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 71596,
        "documentation": {
            "docstring": "The module can return a modified version of the event",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 196682,
        "commit_id": "9ad8ab9fe58051cf11626ba6654852fcfec60147",
        "repo": "sympy",
        "path": "sympy/stats/crv_types.py",
        "file_name": "crv_types.py",
        "fun_name": "Dagum",
        "commit_message": "Documentation cleanup 5",
        "code": "def Dagum(name, p, a, b):\n    r\n\n    return rv(name, DagumDistribution, (p, a, b))\n\n#-------------------------------------------------------------------------------\n# Erlang distribution ----------------------------------------------------------\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 20,
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        "token_counts": 28,
        "n_ast_nodes": 40,
        "n_identifiers": 7,
        "d_id": 48100,
        "documentation": {
            "docstring": "\n    Create a continuous random variable with a Dagum distribution.\n\n    Explanation\n    ===========\n\n    The density of the Dagum distribution is given by\n\n    .. math::\n        f(x) := \\frac{a p}{x} \\left( \\frac{\\left(\\tfrac{x}{b}\\right)^{a p}}\n                {\\left(\\left(\\tfrac{x}{b}\\right)^a + 1 \\right)^{p+1}} \\right)\n\n    with :math:`x > 0`.\n\n    Parameters\n    ==========\n\n    p : Real number\n        `p > 0`, a shape.\n    a : Real number\n        `a > 0`, a shape.\n    b : Real number\n        `b > 0`, a scale.\n\n    Returns\n    =======\n\n    RandomSymbol\n\n    Examples\n    ========\n\n    >>> from sympy.stats import Dagum, density, cdf\n    >>> from sympy import Symbol\n\n    >>> p = Symbol(\"p\", positive=True)\n    >>> a = Symbol(\"a\", positive=True)\n    >>> b = Symbol(\"b\", positive=True)\n    >>> z = Symbol(\"z\")\n\n    >>> X = Dagum(\"x\", p, a, b)\n\n    >>> density(X)(z)\n    a*p*(z/b)**(a*p)*((z/b)**a + 1)**(-p - 1)/z\n\n    >>> cdf(X)(z)\n    Piecewise(((1 + (z/b)**(-a))**(-p), z >= 0), (0, True))\n\n\n    References\n    ==========\n\n    .. [1] https://en.wikipedia.org/wiki/Dagum_distribution\n\n    ",
            "n_words": 132,
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            "language": "en"
        }
    },
    {
        "id": 49840,
        "commit_id": "f4d6e64cdc132ae868699a0ba442f4ab1d304a14",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/script_util.py",
        "file_name": "script_util.py",
        "fun_name": "diffusion_defaults",
        "commit_message": "add disco_diffusion_cnclip_vitb16 module",
        "code": "def diffusion_defaults():\n    \n    return dict(\n        learn_sigma=False,\n        diffusion_steps=1000,\n        noise_schedule=\"linear\",\n        timestep_respacing=\"\",\n        use_kl=False,\n        predict_xstart=False,\n        rescale_timesteps=False,\n        rescale_learned_sigmas=False,\n    )\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 9936,
        "documentation": {
            "docstring": "\n    Defaults for image and classifier training.\n    ",
            "n_words": 6,
            "vocab_size": 6,
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        }
    },
    {
        "id": 196168,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/permutations.py",
        "file_name": "permutations.py",
        "fun_name": "resize",
        "commit_message": "Updated import locations",
        "code": "def resize(self, n):\n        \n        aform = self.array_form\n        l = len(aform)\n        if n > l:\n            aform += list(range(l, n))\n            return Permutation._af_new(aform)\n\n        elif n < l:\n            cyclic_form = self.full_cyclic_form\n            new_cyclic_form = []\n            for cycle in cyclic_form:\n                cycle_min = min(cycle)\n                cycle_max = max(cycle)\n                if cycle_min <= n-1:\n                    if cycle_max > n-1:\n                        raise ValueError(\n                            \"The permutation cannot be resized to {} \"\n                            \"because the cycle {} may break.\"\n                            .format(n, tuple(cycle)))\n\n                    new_cyclic_form.append(cycle)\n            return Permutation(new_cyclic_form)\n\n        return self\n\n    # XXX Deprecated flag\n    print_cyclic = None\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 378,
        "n_words": 77,
        "vocab_size": 58,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 116,
        "n_ast_nodes": 197,
        "n_identifiers": 24,
        "d_id": 47668,
        "documentation": {
            "docstring": "Resize the permutation to the new size ``n``.\n\n        Parameters\n        ==========\n\n        n : int\n            The new size of the permutation.\n\n        Raises\n        ======\n\n        ValueError\n            If the permutation cannot be resized to the given size.\n            This may only happen when resized to a smaller size than\n            the original.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation\n\n        Increasing the size of a permutation:\n\n        >>> p = Permutation(0, 1, 2)\n        >>> p = p.resize(5)\n        >>> p\n        (4)(0 1 2)\n\n        Decreasing the size of the permutation:\n\n        >>> p = p.resize(4)\n        >>> p\n        (3)(0 1 2)\n\n        If resizing to the specific size breaks the cycles:\n\n        >>> p.resize(2)\n        Traceback (most recent call last):\n        ...\n        ValueError: The permutation cannot be resized to 2 because the\n        cycle (0, 1, 2) may break.\n        ",
            "n_words": 121,
            "vocab_size": 70,
            "n_whitespaces": 340,
            "language": "en"
        }
    },
    {
        "id": 249367,
        "commit_id": "46bd7f4ed9020bbed459c03a11c26d7f7c3093b0",
        "repo": "synapse",
        "path": "synapse/storage/databases/main/event_push_actions.py",
        "file_name": "event_push_actions.py",
        "fun_name": "_remove_old_push_actions_that_have_rotated",
        "commit_message": "Clarifications for event push action processing. (#13485)\n\n* Clarifies comments.\r\n* Fixes an erroneous comment (about return type) added in #13455\r\n  (ec24813220f9d54108924dc04aecd24555277b99).\r\n* Clarifies the name of a variable.\r\n* Simplifies logic of pulling out the latest join for the requesting user.",
        "code": "async def _remove_old_push_actions_that_have_rotated(self) -> None:\n        \n\n        # We want to clear out anything that is older than a day that *has* already\n        # been rotated.\n        rotated_upto_stream_ordering = await self.db_pool.simple_select_one_onecol(\n            table=\"event_push_summary_stream_ordering\",\n            keyvalues={},\n            retcol=\"stream_ordering\",\n        )\n\n        max_stream_ordering_to_delete = min(\n            rotated_upto_stream_ordering, self.stream_ordering_day_ago\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 131,
        "n_words": 38,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 64,
        "n_ast_nodes": 72,
        "n_identifiers": 11,
        "d_id": 72870,
        "documentation": {
            "docstring": "Clear out old push actions that have been summarised.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 119743,
        "commit_id": "ddf23dead3a4214e6ef8a515d0a51648360ab797",
        "repo": "jax",
        "path": "jax/_src/numpy/util.py",
        "file_name": "util.py",
        "fun_name": "_asarray",
        "commit_message": "lax_numpy.py: factor out some common utilities\n\nRe-lands part of #9724\n\nPiperOrigin-RevId: 433838553",
        "code": "def _asarray(arr):\n  \n  _check_arraylike(\"_asarray\", arr)\n  dtype, weak_type = dtypes._lattice_result_type(arr)\n  return lax_internal._convert_element_type(arr, dtype, weak_type)\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 16,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 33,
        "n_ast_nodes": 55,
        "n_identifiers": 9,
        "d_id": 26678,
        "documentation": {
            "docstring": "\n  Pared-down utility to convert object to a DeviceArray.\n  Note this will not correctly handle lists or tuples.\n  ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 100564,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/gpu_stats/amd.py",
        "file_name": "amd.py",
        "fun_name": "_get_driver",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def _get_driver(self) -> str:\n        \n        drivers = [device.get(\"driverVersion\", \"No Driver Found\")\n                   for device in self._device_details]\n        self._log(\"debug\", f\"GPU Drivers: {drivers}\")\n        return drivers\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 66,
        "n_words": 20,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 37,
        "n_ast_nodes": 69,
        "n_identifiers": 8,
        "d_id": 20028,
        "documentation": {
            "docstring": " Obtain the AMD driver version currently in use.\n\n        Returns\n        -------\n        str\n            The current AMD GPU driver versions\n        ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 26685,
        "commit_id": "0881beec1ac02dfa97525c5173687defb356d85c",
        "repo": "saleor",
        "path": "saleor/payment/tests/test_gateway.py",
        "file_name": "test_gateway.py",
        "fun_name": "test_payment_refund_or_void_refund_called",
        "commit_message": "Fix payment flow (#9504)\n\n* Do not capture payment again when it should be refunded or voided\r\n\r\n* Do not create order when then is ongoing refund",
        "code": "def test_payment_refund_or_void_refund_called(refund_mock, payment):\n    \n    # given\n    payment.transactions.count() == 0\n    payment.charge_status = ChargeStatus.FULLY_CHARGED\n    payment.save(update_fields=[\"charge_status\"])\n\n    # when\n    gateway.payment_refund_or_void(payment, get_plugins_manager(), None)\n\n    # then\n    assert refund_mock.called_once()\n\n\n@patch(\"saleor.payment.gateway.refund\")",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "@patch(\"saleor.payment.gateway.refund\")",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 48,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 52,
        "n_ast_nodes": 101,
        "n_identifiers": 15,
        "d_id": 5044,
        "documentation": {
            "docstring": "Ensure that the refund method is called when payment can be refunded\n    and there is no refund transaction.",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 196771,
        "commit_id": "f757f3daae6e11ea0cfb7dadc133274d8d74315f",
        "repo": "sympy",
        "path": "sympy/concrete/summations.py",
        "file_name": "summations.py",
        "fun_name": "telescopic",
        "commit_message": "Reordered imports 2",
        "code": "def telescopic(L, R, limits):\n    \n    (i, a, b) = limits\n    if L.is_Add or R.is_Add:\n        return None\n\n    # We want to solve(L.subs(i, i + m) + R, m)\n    # First we try a simple match since this does things that\n    # solve doesn't do, e.g. solve(f(k+m)-f(k), m) fails\n\n    k = Wild(\"k\")\n    sol = (-R).match(L.subs(i, i + k))\n    s = None\n    if sol and k in sol:\n        s = sol[k]\n        if not (s.is_Integer and L.subs(i, i + s) == -R):\n            # sometimes match fail(f(x+2).match(-f(x+k))->{k: -2 - 2x}))\n            s = None\n\n    # But there are things that match doesn't do that solve\n    # can do, e.g. determine that 1/(x + m) = 1/(1 - x) when m = 1\n\n    if s is None:\n        m = Dummy('m')\n        try:\n            from sympy.solvers.solvers import solve\n            sol = solve(L.subs(i, i + m) + R, m) or []\n        except NotImplementedError:\n            return None\n        sol = [si for si in sol if si.is_Integer and\n               (L.subs(i, i + si) + R).expand().is_zero]\n        if len(sol) != 1:\n            return None\n        s = sol[0]\n\n    if s < 0:\n        return telescopic_direct(R, L, abs(s), (i, a, b))\n    elif s > 0:\n        return telescopic_direct(L, R, s, (i, a, b))\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 391,
        "n_words": 189,
        "vocab_size": 104,
        "complexity": 16,
        "nloc": 27,
        "token_counts": 242,
        "n_ast_nodes": 374,
        "n_identifiers": 27,
        "d_id": 48161,
        "documentation": {
            "docstring": "\n    Tries to perform the summation using the telescopic property.\n\n    Return None if not possible.\n    ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 5494,
        "commit_id": "76032e66dd2b75c611440bdccfc3d55863fb3e39",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/source_facebook_marketing/streams/base_insight_streams.py",
        "file_name": "base_insight_streams.py",
        "fun_name": "insights_lookback_period",
        "commit_message": "Source Facebook Marketing: Add lookback window to insights streams (#12402)",
        "code": "def insights_lookback_period(self):\n        \n        return pendulum.duration(days=self._insights_lookback_window)\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 18,
        "n_words": 4,
        "vocab_size": 4,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 17,
        "n_ast_nodes": 30,
        "n_identifiers": 6,
        "d_id": 773,
        "documentation": {
            "docstring": "\n        Facebook freezes insight data 28 days after it was generated, which means that all data\n        from the past 28 days may have changed since we last emitted it, so we retrieve it again.\n        But in some cases users my have define their own lookback window, thats\n        why the value for `insights_lookback_window` is set throught config.\n        ",
            "n_words": 55,
            "vocab_size": 48,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 26585,
        "commit_id": "620569b3a2466e8dda80df20a11b99ec0bec8c7c",
        "repo": "saleor",
        "path": "saleor/graphql/checkout/mutations/utils.py",
        "file_name": "utils.py",
        "fun_name": "check_permissions_for_custom_prices",
        "commit_message": "Custom prices (#9393)\n\n* Add price_override to CheckoutLine model\r\n\r\n* Allow to define custom price in checkout mutations\r\n\r\n* Apply code review suggestions\r\n\r\n* Use custom price when generating checkout payload\r\n\r\n* Use price override when calculating prices for checkout\r\n\r\n* Update populatedb - create checkout with custom prices\r\n\r\n* Fix schema.graphql file\r\n\r\n* Make quantity optional in `CheckoutLinesUpdate` mutation (#9430)\r\n\r\n* Make quantity optional in CheckoutLinesUpdate mutation\r\n\r\n* Refactor add_variants_to_checkout checkout utils\r\n\r\n* Update changelog\r\n\r\n* Update quantity field description in CheckoutLineUpdateInput",
        "code": "def check_permissions_for_custom_prices(app, lines):\n    \n    if any([\"price\" in line for line in lines]) and (\n        not app or not app.has_perm(CheckoutPermissions.HANDLE_CHECKOUTS)\n    ):\n        raise PermissionDenied(permissions=[CheckoutPermissions.HANDLE_CHECKOUTS])\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 44,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 5,
        "nloc": 5,
        "token_counts": 48,
        "n_ast_nodes": 79,
        "n_identifiers": 10,
        "d_id": 5029,
        "documentation": {
            "docstring": "Raise PermissionDenied when custom price is changed by user or app without perm.\n\n    Checkout line custom price can be changed only by app with\n    handle checkout permission.\n    ",
            "n_words": 27,
            "vocab_size": 22,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 202050,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/cache/tests.py",
        "file_name": "tests.py",
        "fun_name": "_perform_invalid_key_test",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _perform_invalid_key_test(self, key, expected_warning, key_func=None):\n        \n        # mimic custom ``make_key`` method being defined since the default will\n        # never show the below warnings",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 43,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 4,
        "nloc": 24,
        "token_counts": 191,
        "n_ast_nodes": 24,
        "n_identifiers": 5,
        "d_id": 50040,
        "documentation": {
            "docstring": "\n        All the builtin backends should warn (except memcached that should\n        error) on keys that would be refused by memcached. This encourages\n        portable caching code without making it too difficult to use production\n        backends with more liberal key rules. Refs #6447.\n        ",
            "n_words": 40,
            "vocab_size": 37,
            "n_whitespaces": 76,
            "language": "en"
        }
    },
    {
        "id": 222921,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/fancy_getopt.py",
        "file_name": "fancy_getopt.py",
        "fun_name": "set_negative_aliases",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def set_negative_aliases(self, negative_alias):\n        \n        self._check_alias_dict(negative_alias, \"negative alias\")\n        self.negative_alias = negative_alias\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 30,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 21,
        "n_ast_nodes": 37,
        "n_identifiers": 4,
        "d_id": 56809,
        "documentation": {
            "docstring": "Set the negative aliases for this option parser.\n        'negative_alias' should be a dictionary mapping option names to\n        option names, both the key and value must already be defined\n        in the option table.",
            "n_words": 32,
            "vocab_size": 26,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 244349,
        "commit_id": "9a3bf7660e6ced54672741095f96df07919f9ba7",
        "repo": "mmdetection",
        "path": "mmdet/models/dense_heads/dense_test_mixins.py",
        "file_name": "dense_test_mixins.py",
        "fun_name": "aug_test_bboxes",
        "commit_message": "[Refactor] Refactor dense head outputs to InstanceResults.",
        "code": "def aug_test_bboxes(self, feats, img_metas, rescale=False):\n        \n        # check with_nms argument\n        gb_sig = signature(self.get_results)\n        gb_args = [p.name for p in gb_sig.parameters.values()]\n        gbs_sig = signature(self._get_results_single)\n        gbs_args = [p.name for p in gbs_sig.parameters.values()]\n        assert ('with_nms' in gb_args) and ('with_nms' in gbs_args), \\\n            f'{self.__class__.__name__}' \\\n            ' does not support test-time augmentation'\n\n        aug_bboxes = []\n        aug_scores = []\n        aug_labels = []\n        for x, img_meta in zip(feats, img_metas):\n            # only one image in the batch\n            outs = self.forward(x)\n            bbox_outputs = self.get_results(\n                *outs,\n                img_metas=img_meta,\n                cfg=self.test_cfg,\n                rescale=False,\n                with_nms=False)[0]\n            aug_bboxes.append(bbox_outputs.bboxes)\n            aug_scores.append(bbox_outputs.scores)\n            if len(bbox_outputs) >= 3:\n                aug_labels.append(bbox_outputs.labels)\n\n        # after merging, bboxes will be rescaled to the original image size\n        merged_bboxes, merged_scores = self.merge_aug_bboxes(\n            aug_bboxes, aug_scores, img_metas)\n        merged_labels = torch.cat(aug_labels, dim=0) if aug_labels else None\n\n        if merged_bboxes.numel() == 0:\n            det_bboxes = torch.cat([merged_bboxes, merged_scores[:, None]], -1)\n            return [\n                (det_bboxes, merged_labels),\n            ]\n\n        det_bboxes, keep_idxs = batched_nms(merged_bboxes, merged_scores,\n                                            merged_labels, self.test_cfg.nms)\n        det_bboxes = det_bboxes[:self.test_cfg.max_per_img]\n        det_labels = merged_labels[keep_idxs][:self.test_cfg.max_per_img]\n\n        if rescale:\n            _det_bboxes = det_bboxes\n        else:\n            _det_bboxes = det_bboxes.clone()\n            _det_bboxes[:, :4] *= det_bboxes.new_tensor(\n                img_metas[0][0]['scale_factor'])\n\n        results = InstanceData()\n        results.bboxes = _det_bboxes[:, :4]\n        results.scores = _det_bboxes[:, 4]\n        results.labels = det_labels\n        return [results]\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 674,
        "n_words": 171,
        "vocab_size": 122,
        "complexity": 9,
        "nloc": 46,
        "token_counts": 361,
        "n_ast_nodes": 567,
        "n_identifiers": 54,
        "d_id": 70341,
        "documentation": {
            "docstring": "Test det bboxes with test time augmentation, can be applied in\n        DenseHead except for ``RPNHead`` and its variants, e.g., ``GARPNHead``,\n        etc.\n\n        Args:\n            feats (list[Tensor]): the outer list indicates test-time\n                augmentations and inner Tensor should have a shape NxCxHxW,\n                which contains features for all images in the batch.\n            img_metas (list[list[dict]]): the outer list indicates test-time\n                augs (multiscale, flip, etc.) and the inner list indicates\n                images in a batch. each dict has image information.\n            rescale (bool, optional): Whether to rescale the results.\n                Defaults to False.\n\n        Returns:\n            list[tuple[Tensor, Tensor]]: Each item in result_list is 2-tuple.\n                The first item is ``bboxes`` with shape (n, 5),\n                where 5 represent (tl_x, tl_y, br_x, br_y, score).\n                The shape of the second tensor in the tuple is ``labels``\n                with shape (n,). The length of list should always be 1.\n        ",
            "n_words": 131,
            "vocab_size": 92,
            "n_whitespaces": 345,
            "language": "en"
        }
    },
    {
        "id": 208205,
        "commit_id": "13d545b2155ebe9ee0ffad9e9d9ffc09a39185df",
        "repo": "celery",
        "path": "celery/platforms.py",
        "file_name": "platforms.py",
        "fun_name": "remove_if_stale",
        "commit_message": "Fix grammar typos on the whole project",
        "code": "def remove_if_stale(self):\n        \n        try:\n            pid = self.read_pid()\n        except ValueError:\n            print('Broken pidfile found - Removing it.', file=sys.stderr)\n            self.remove()\n            return True\n        if not pid:\n            self.remove()\n            return True\n\n        try:\n            os.kill(pid, 0)\n        except os.error as exc:\n            if exc.errno == errno.ESRCH or exc.errno == errno.EPERM:\n                print('Stale pidfile exists - Removing it.', file=sys.stderr)\n                self.remove()\n                return True\n        except SystemError:\n            print('Stale pidfile exists - Removing it.', file=sys.stderr)\n            self.remove()\n            return True\n        return False\n",
        "url": "https://github.com/celery/celery.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 285,
        "n_words": 63,
        "vocab_size": 35,
        "complexity": 7,
        "nloc": 22,
        "token_counts": 119,
        "n_ast_nodes": 202,
        "n_identifiers": 18,
        "d_id": 52237,
        "documentation": {
            "docstring": "Remove the lock if the process isn't running.\n\n        I.e. process does not respond to signal.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 34690,
        "commit_id": "e09473a817c5e5871e11cc81004355ef30250502",
        "repo": "transformers",
        "path": "src/transformers/models/xlm_roberta_xl/modeling_xlm_roberta_xl.py",
        "file_name": "modeling_xlm_roberta_xl.py",
        "fun_name": "_tie_weights",
        "commit_message": "Add support for XLM-R XL and XXL models by modeling_xlm_roberta_xl.py (#13727)\n\n* add xlm roberta xl\r\n\r\n* add convert xlm xl fairseq checkpoint to pytorch\r\n\r\n* fix init and documents for xlm-roberta-xl\r\n\r\n* fix indention\r\n\r\n* add test for XLM-R xl,xxl\r\n\r\n* fix model hub name\r\n\r\n* fix some stuff\r\n\r\n* up\r\n\r\n* correct init\r\n\r\n* fix more\r\n\r\n* fix as suggestions\r\n\r\n* add torch_device\r\n\r\n* fix default values of doc strings\r\n\r\n* fix leftovers\r\n\r\n* merge to master\r\n\r\n* up\r\n\r\n* correct hub names\r\n\r\n* fix docs\r\n\r\n* fix model\r\n\r\n* up\r\n\r\n* finalize\r\n\r\n* last fix\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* add copied from\r\n\r\n* make style\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def _tie_weights(self):\n        # To tie those two weights if they get disconnected (on TPU or when the bias is resized)\n        self.bias = self.decoder.bias\n\n\n@add_start_docstrings(\n    ,\n    XLM_ROBERTA_XL_START_DOCSTRING,\n)",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"\"\"\n    XLM-RoBERTa-xlarge Model transformer with a sequence classification/regression head on top (a linear layer on top\n    of the pooled output) e.g. for GLUE tasks.\n    \"\"\",\n    XLM_ROBERTA_XL_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
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        "documentation": {
            "docstring": "\n    XLM-RoBERTa-xlarge Model transformer with a sequence classification/regression head on top (a linear layer on top\n    of the pooled output) e.g. for GLUE tasks.\n    ",
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            "language": "en"
        }
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    {
        "id": 206644,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/encoding.py",
        "file_name": "encoding.py",
        "fun_name": "uri_to_iri",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def uri_to_iri(uri):\n    \n    if uri is None:\n        return uri\n    uri = force_bytes(uri)\n    # Fast selective unquote: First, split on '%' and then starting with the\n    # second block, decode the first 2 bytes if they represent a hex code to\n    # decode. The rest of the block is the part after '%AB', not containing\n    # any '%'. Add that to the output without further processing.\n    bits = uri.split(b\"%\")\n    if len(bits) == 1:\n        iri = uri\n    else:\n        parts = [bits[0]]\n        append = parts.append\n        hextobyte = _hextobyte\n        for item in bits[1:]:\n            hex = item[:2]\n            if hex in hextobyte:\n                append(hextobyte[item[:2]])\n                append(item[2:])\n            else:\n                append(b\"%\")\n                append(item)\n        iri = b\"\".join(parts)\n    return repercent_broken_unicode(iri).decode()\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
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        "d_id": 51602,
        "documentation": {
            "docstring": "\n    Convert a Uniform Resource Identifier(URI) into an Internationalized\n    Resource Identifier(IRI).\n\n    This is the algorithm from section 3.2 of RFC 3987, excluding step 4.\n\n    Take an URI in ASCII bytes (e.g. '/I%20%E2%99%A5%20Django/') and return\n    a string containing the encoded result (e.g. '/I%20♥%20Django/').\n    ",
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    {
        "id": 259232,
        "commit_id": "7f0006c8aad1a09621ad19c3db19c3ff0555a183",
        "repo": "scikit-learn",
        "path": "sklearn/preprocessing/tests/test_encoders.py",
        "file_name": "test_encoders.py",
        "fun_name": "test_ohe_drop_first_handle_unknown_ignore_warns",
        "commit_message": "ENH Adds infrequent categories to OneHotEncoder (#16018)\n\n* ENH Completely adds infrequent categories\r\n\r\n* STY Linting\r\n\r\n* STY Linting\r\n\r\n* DOC Improves wording\r\n\r\n* DOC Lint\r\n\r\n* BUG Fixes\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* DOC Uses math to description float min_frequency\r\n\r\n* DOC Adds comment regarding drop\r\n\r\n* BUG Fixes method name\r\n\r\n* DOC Clearer docstring\r\n\r\n* TST Adds more tests\r\n\r\n* FIX Fixes mege\r\n\r\n* CLN More pythonic\r\n\r\n* CLN Address comments\r\n\r\n* STY Flake8\r\n\r\n* CLN Address comments\r\n\r\n* DOC Fix\r\n\r\n* MRG\r\n\r\n* WIP\r\n\r\n* ENH Address comments\r\n\r\n* STY Fix\r\n\r\n* ENH Use functiion call instead of property\r\n\r\n* ENH Adds counts feature\r\n\r\n* CLN Rename variables\r\n\r\n* DOC More details\r\n\r\n* CLN Remove unneeded line\r\n\r\n* CLN Less lines is less complicated\r\n\r\n* CLN Less diffs\r\n\r\n* CLN Improves readiabilty\r\n\r\n* BUG Fix\r\n\r\n* CLN Address comments\r\n\r\n* TST Fix\r\n\r\n* CLN Address comments\r\n\r\n* CLN Address comments\r\n\r\n* CLN Move docstring to userguide\r\n\r\n* DOC Better wrapping\r\n\r\n* TST Adds test to handle_unknown='error'\r\n\r\n* ENH Spelling error in docstring\r\n\r\n* BUG Fixes counter with nan values\r\n\r\n* BUG Removes unneeded test\r\n\r\n* BUG Fixes issue\r\n\r\n* ENH Sync with main\r\n\r\n* DOC Correct settings\r\n\r\n* DOC Adds docstring\r\n\r\n* DOC Immprove user guide\r\n\r\n* DOC Move to 1.0\r\n\r\n* DOC Update docs\r\n\r\n* TST Remove test\r\n\r\n* DOC Update docstring\r\n\r\n* STY Linting\r\n\r\n* DOC Address comments\r\n\r\n* ENH Neater code\r\n\r\n* DOC Update explaination for auto\r\n\r\n* Update sklearn/preprocessing/_encoders.py\r\n\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\n\r\n* TST Uses docstring instead of comments\r\n\r\n* TST Remove call to fit\r\n\r\n* TST Spelling error\r\n\r\n* ENH Adds support for drop + infrequent categories\r\n\r\n* ENH Adds infrequent_if_exist option\r\n\r\n* DOC Address comments for user guide\r\n\r\n* DOC Address comments for whats_new\r\n\r\n* DOC Update docstring based on comments\r\n\r\n* CLN Update test with suggestions\r\n\r\n* ENH Adds computed property infrequent_categories_\r\n\r\n* DOC Adds where the infrequent column is located\r\n\r\n* TST Adds more test for infrequent_categories_\r\n\r\n* DOC Adds docstring for _compute_drop_idx\r\n\r\n* CLN Moves _convert_to_infrequent_idx into its own method\r\n\r\n* TST Increases test coverage\r\n\r\n* TST Adds failing test\r\n\r\n* CLN Careful consideration of dropped and inverse_transform\r\n\r\n* STY Linting\r\n\r\n* DOC Adds docstrinb about dropping infrequent\r\n\r\n* DOC Uses only\r\n\r\n* DOC Numpydoc\r\n\r\n* TST Includes test for get_feature_names_out\r\n\r\n* DOC Move whats new\r\n\r\n* DOC Address docstring comments\r\n\r\n* DOC Docstring changes\r\n\r\n* TST Better comments\r\n\r\n* TST Adds check for handle_unknown='ignore' for infrequent\r\n\r\n* CLN Make _infrequent_indices private\r\n\r\n* CLN Change min_frequency default to None\r\n\r\n* DOC Adds comments\r\n\r\n* ENH adds support for max_categories=1\r\n\r\n* ENH Describe lexicon ordering for ties\r\n\r\n* DOC Better docstring\r\n\r\n* STY Fix\r\n\r\n* CLN Error when explicity dropping an infrequent category\r\n\r\n* STY Grammar\r\n\r\nCo-authored-by: Joel Nothman <joel.nothman@gmail.com>\r\nCo-authored-by: Roman Yurchak <rth.yurchak@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def test_ohe_drop_first_handle_unknown_ignore_warns(handle_unknown):\n    \n    X = [[\"a\", 0], [\"b\", 2], [\"b\", 1]]\n\n    ohe = OneHotEncoder(drop=\"first\", sparse=False, handle_unknown=handle_unknown)\n    X_trans = ohe.fit_transform(X)\n\n    X_expected = np.array(\n        [\n            [0, 0, 0],\n            [1, 0, 1],\n            [1, 1, 0],\n        ]\n    )\n    assert_allclose(X_trans, X_expected)\n\n    # Both categories are unknown\n    X_test = [[\"c\", 3]]\n    X_expected = np.array([[0, 0, 0]])\n\n    warn_msg = (\n        r\"Found unknown categories in columns \\[0, 1\\] during \"\n        \"transform. These unknown categories will be encoded as all \"\n        \"zeros\"\n    )\n    with pytest.warns(UserWarning, match=warn_msg):\n        X_trans = ohe.transform(X_test)\n    assert_allclose(X_trans, X_expected)\n\n    # inverse_transform maps to None\n    X_inv = ohe.inverse_transform(X_expected)\n    assert_array_equal(X_inv, np.array([[\"a\", 0]], dtype=object))\n\n\n@pytest.mark.parametrize(\"handle_unknown\", [\"ignore\", \"infrequent_if_exist\"])",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"handle_unknown\", [\"ignore\", \"infrequent_if_exist\"])",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 221,
        "n_words": 96,
        "vocab_size": 71,
        "complexity": 1,
        "nloc": 24,
        "token_counts": 178,
        "n_ast_nodes": 307,
        "n_identifiers": 27,
        "d_id": 75665,
        "documentation": {
            "docstring": "Check drop='first' and handle_unknown='ignore'/'infrequent_if_exist'\n    during transform.",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 189413,
        "commit_id": "149479f9132daf2266c27caa7a3e11ce06be501d",
        "repo": "manim",
        "path": "manim/mobject/probability.py",
        "file_name": "probability.py",
        "fun_name": "_add_x_axis_labels",
        "commit_message": "Refactored :class:`~.BarChart` and made it inherit from :class:`~.Axes`. (#2387)\n\n* rebase\r\n\r\n* fixed None bar_names\r\n\r\n* fixed scale issues\r\n\r\n* fixed to accept negative bar values\r\n\r\n* fixed some bugs\r\n\r\n* Added docs for parameters (DRAFT)\r\n\r\n* clean up parameters\r\n\r\n* more clean up\r\n\r\n* clean up __init__\r\n\r\n* replace add_x_labels with built-in functionality\r\n\r\n* adjust default font_size for labels\r\n\r\n* Update docs descriptions\r\n\r\n* Add bar_width and adjust get_bar_labels\r\n\r\n* Add bar_width and adjust get_bar_labels\r\n\r\n* Add docs to class and methods\r\n\r\n* remove unecessary imports\r\n\r\n* remove getters\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* Attempt to fix duplicated parameters section\r\n\r\n* adjust BarChart example to include title\r\n\r\n* switch order around\r\n\r\n* change_bar_values\r\n\r\n* back to get_bar_values\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* add docs for _update_default_config and fix method\r\n\r\n* remove print(dicts)\r\n\r\n* allow negative_numbers to work with bar chart\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* allow negative numbers to work with change_bar_values\r\n\r\n* add test_probability.py\r\n\r\n* add control data\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* change example\r\n\r\n* update examples again\r\n\r\n* rewrite test\r\n\r\n* rewrite other test\r\n\r\n* remove comma after list in example\r\n\r\n* improve wording in docs\r\n\r\n* add parameter/docs for label_constructor\r\n\r\n* change create_label_tex and update methods\r\n\r\n* update docs\r\n\r\n* use decimal number\r\n\r\n* switch default to Tex\r\n\r\n* update instances of create_label_tex in coordinate_systems.py\r\n\r\n* hardcode for add_labels\r\n\r\n* add TODO\r\n\r\n* use label_constructor\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix indentation in docs\r\n\r\n* Fix minor doc typo\r\n\r\nCo-authored-by: Led Me Explain <ledmeexplain@gmail.com>\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>",
        "code": "def _add_x_axis_labels(self):\n        \n\n        val_range = np.arange(\n            0.5, len(self.bar_names), 1\n        )  # 0.5 shifted so that labels are centered, not on ticks\n\n        labels = VGroup()\n\n        for i, (value, bar_name) in enumerate(zip(val_range, self.bar_names)):\n            # to accommodate negative bars, the label may need to be\n            # below or above the x_axis depending on the value of the bar\n            if self.values[i] < 0:\n                direction = UP\n            else:\n                direction = DOWN\n            bar_name_label = self.x_axis.label_constructor(bar_name)\n\n            bar_name_label.font_size = self.x_axis.font_size\n            bar_name_label.next_to(\n                self.x_axis.number_to_point(value),\n                direction=direction,\n                buff=self.x_axis.line_to_number_buff,\n            )\n\n            labels.add(bar_name_label)\n\n        self.x_axis.labels = labels\n        self.x_axis.add(labels)\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 316,
        "n_words": 81,
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        "token_counts": 135,
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        "n_identifiers": 27,
        "d_id": 46048,
        "documentation": {
            "docstring": "Essentially ``:meth:~.NumberLine.add_labels``, but differs in that\n        the direction of the label with respect to the x_axis changes to UP or DOWN\n        depending on the value.\n\n        UP for negative values and DOWN for positive values.\n        ",
            "n_words": 34,
            "vocab_size": 27,
            "n_whitespaces": 62,
            "language": "en"
        }
    },
    {
        "id": 317880,
        "commit_id": "274584f2a47b7db9943168316122196a540080e5",
        "repo": "core",
        "path": "homeassistant/components/litterrobot/entity.py",
        "file_name": "entity.py",
        "fun_name": "async_cancel_refresh_callback",
        "commit_message": "Add strict typing for litterrobot (#75540)",
        "code": "def async_cancel_refresh_callback(self) -> None:\n        \n        if self._refresh_callback is not None:\n            self._refresh_callback()\n            self._refresh_callback = None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 49,
        "n_words": 13,
        "vocab_size": 11,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 26,
        "n_ast_nodes": 45,
        "n_identifiers": 3,
        "d_id": 116446,
        "documentation": {
            "docstring": "Clear the refresh callback if it has not already fired.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 261168,
        "commit_id": "b22f7fa552c03aa7f6b9b4d661470d0173f8db5d",
        "repo": "scikit-learn",
        "path": "sklearn/utils/discovery.py",
        "file_name": "discovery.py",
        "fun_name": "all_displays",
        "commit_message": "MNT numpydoc validation for Displays (#21469)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def all_displays():\n    \n    # lazy import to avoid circular imports from sklearn.base\n    from ._testing import ignore_warnings\n\n    all_classes = []\n    root = str(Path(__file__).parent.parent)  # sklearn package\n    # Ignore deprecation warnings triggered at import time and from walking\n    # packages\n    with ignore_warnings(category=FutureWarning):\n        for _, module_name, _ in pkgutil.walk_packages(path=[root], prefix=\"sklearn.\"):\n            module_parts = module_name.split(\".\")\n            if (\n                any(part in _MODULE_TO_IGNORE for part in module_parts)\n                or \"._\" in module_name\n            ):\n                continue\n            module = import_module(module_name)\n            classes = inspect.getmembers(module, inspect.isclass)\n            classes = [\n                (name, display_class)\n                for name, display_class in classes\n                if not name.startswith(\"_\") and name.endswith(\"Display\")\n            ]\n            all_classes.extend(classes)\n\n    return sorted(set(all_classes), key=itemgetter(0))\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 304,
        "n_words": 91,
        "vocab_size": 69,
        "complexity": 8,
        "nloc": 21,
        "token_counts": 153,
        "n_ast_nodes": 258,
        "n_identifiers": 37,
        "d_id": 76673,
        "documentation": {
            "docstring": "Get a list of all displays from `sklearn`.\n\n    Returns\n    -------\n    displays : list of tuples\n        List of (name, class), where ``name`` is the display class name as\n        string and ``class`` is the actual type of the class.\n    ",
            "n_words": 37,
            "vocab_size": 29,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 320800,
        "commit_id": "a20bb67a878b2e68abf8268c1b0a27f018d01352",
        "repo": "qutebrowser",
        "path": "qutebrowser/mainwindow/tabbedbrowser.py",
        "file_name": "tabbedbrowser.py",
        "fun_name": "on_mode_entered",
        "commit_message": "mypy: Upgrade to PyQt5-stubs 5.15.6.0\n\nFor some unknown reason, those new stubs cause a *lot* of things now to be\nchecked by mypy which formerly probably got skipped due to Any being implied\nsomewhere.\n\nThe stubs themselves mainly improved, with a couple of regressions too.\n\nIn total, there were some 337 (!) new mypy errors. This commit fixes almost all\nof them, and the next commit improves a fix to get things down to 0 errors\nagain.\n\nOverview of the changes:\n\n==== qutebrowser/app.py\n\n- Drop type ignore due to improved stubs.\n\n==== qutebrowser/browser/browsertab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  This is debatable: I suppose the abstract stuff shouldn't need to know\n  anything about the concrete backends at all. But it seems like we cut some\n  corners when initially implementing things, and put some code in browsertab.py\n  just because the APIs of both backends happened to be compatible. Perhaps\n  something to reconsider once we drop QtWebKit and hopefully implement a dummy\n  backend.\n\n- Add an additional assertion in AbstractAction.run_string. This is already\n  covered by the isinstance(member, self.action_base) above it, but that's too\n  dynamic for mypy to understand.\n\n- Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x\n  and y components), not a single int.\n\n- Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x\n  and y components), not a single int.\n\n- Fix the argument types of AbstractScroller.to_perc, as it's possible to pass\n  fractional percentages too.\n\n- Specify the type for AbstractHistoryPrivate._history. See above (_widget) re\n  this being debatable.\n\n- Fix the return type of AbstractTabPrivate.event_target(), which can be None\n  (see #3888).\n\n- Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS\n  return value), not None.\n\n- Fix the argument type for AbstractTabPrivate.toggle_inspector: position can\n  be None to use the last used position.\n\n- Declare the type of sub-objects of AbstractTab.\n\n- Fix the return value of AbstractTab.icon(), which is the QIcon, not None.\n\n==== qutebrowser/browser/commands.py\n\n- Make sure the active window is a MainWindow (with a .win_id attribute).\n\n==== qutebrowser/browser/downloadview.py\n\n- Add _model() which makes sure that self.model() is a DownloadModel, not None\n  or any other model. This is needed because other methods access a variety of\n  custom attributes on it, e.g. last_index().\n\n==== qutebrowser/browser/greasemonkey.py\n\n- Add an ignore for AbstractDownload.requested_url which we patch onto the\n  downloads. Probably would be nicer to add it as a proper attribute which always\n  gets set by the DownloadManager.\n\n==== qutebrowser/browser/hints.py\n\n- Remove type ignores for QUrl.toString().\n- Add a new type ignore for combining different URL flags (which works, but is\n  not exactly type safe... still probably a regression in the stubs).\n- Make sure the things we get back from self._get_keyparser are what we actually\n  expect. Probably should introduce a TypedDict (and/or overloads for\n  _get_keyparser with typing.Literal) to teach mypy about the exact return value.\n  See #7098.\n  This is needed because we access Hint/NormalKeyParser-specific attributes such\n  as .set_inhibited_timout() or .update_bindings().\n\n==== qutebrowser/browser/inspector.py\n\n- Similar changes than in browsertab.py to make some types where we share API\n  (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next\n  commit.\n\n==== qutebrowser/browser/network/pac.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/qtnetworkdownloads.py\n\n- Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an\n  AbstractDownload), so that we can call ._uses_nam() on it.\n\n==== qutebrowser/browser/qutescheme.py\n\n- Remove now unneeded type ignore for QUrl flags.\n\n==== qutebrowser/browser/urlmarks.py\n\n- Specify the type of UrlMarkManager._lineparser, as those only get initialized\n  in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist.\n\n==== qutebrowser/browser/webelem.py\n\n- New casts to turn single KeyboardModifier (enum) entries into\n  KeyboardModifiers (flags). Might not be needed anymore with Qt 6.\n- With that, casting the final value is now unneeded.\n\n==== qutebrowser/browser/webengine/notification.py\n\n- Remove now unneeded type ignore for signal.\n- Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished()\n  is a QProcess, not just any QObject.\n\n==== qutebrowser/browser/webengine/webenginedownloads.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webengine/webengineelem.py\n\n- Specify the type of WebEngineElement._tab.\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webengineinspector.py\n\n- See changes to inspector.py and next commit.\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/webengine/webenginequtescheme.py\n\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webenginesettings.py\n\n- Ignore access of .setter attribute which we patch onto QWebEngineProfile.\n  Would be nice to have a subclass or wrapper-class instead.\n\n==== qutebrowser/browser/webengine/webenginetab.py\n\n- Specified the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Remove some now-unneeded type ignores for creating FindFlags.\n- Specify more concrete types for WebEngineTab members where we actually need to\n  access WebEngine-specific attributes.\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webengine/webview.py\n\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webkit/network/networkreply.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webkit/webkitinspector.py\n\n- See changes to inspector.py and next commit.\n\n==== qutebrowser/browser/webkit/webkittab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Add a type ignore for WebKitAction because our workaround needs to\n  treat them as ints (which is allowed by PyQt, even if not type-safe).\n- Add new ignores for findText calls: The text is a QString and can be None; the\n  flags are valid despite mypy thinking they aren't (stubs regression?).\n- Specify the type for WebKitHistoryPrivate._history, because we access\n  WebKit-specific attributes. See above (_widget) re this being debatable.\n- Make mypy aware that .currentFrame() and .frameAt() can return None (stubs\n  regression?).\n- Make sure the .page() and .page().networkAccessManager() are our subclasses\n  rather than the more generic QtWebKit objects, as we use custom attributes.\n- Add new type ignores for signals (stubs regression!)\n\n==== qutebrowser/browser/webkit/webpage.py\n\n- Make sure the .networkAccessManager() is our subclass rather than the more\n  generic QtWebKit object, as we use custom attributes.\n- Replace a cast by a type ignore. The cast didn't work anymore.\n\n==== qutebrowser/browser/webkit/webview.py\n\n- Make sure the .page() is our subclass rather than the more generic QtWebKit\n  object, as we use custom attributes.\n\n==== qutebrowser/commands/userscripts.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/completion/completer.py\n\n- Add a new _completion() getter (which ensures it actually gets the completion\n  view) rather than accessing the .parent() directly (which could be any QObject).\n\n==== qutebrowser/completion/completiondelegate.py\n\n- Make sure self.parent() is a CompletionView (no helper method as there is only\n  one instance).\n- Remove a now-unneeded type ignore for adding QSizes.\n\n==== qutebrowser/completion/completionwidget.py\n\n- Add a ._model() getter which ensures that we get a CompletionModel (with\n  custom attributes) rather than Qt's .model() which can be any QAbstractItemModel\n  (or None).\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/completion/models/completionmodel.py\n\n- Remove now unneeded type ignores for signals.\n- Ignore a complaint about .set_pattern() not being defined. Completion\n  categories don't share any common parent class, so it would be good to introduce\n  a typing.Protocol for this. See #7098.\n\n==== qutebrowser/components/misccommands.py\n\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/components/readlinecommands.py\n\n- Make sure QApplication.instance() is a QApplication (and not just a\n  QCoreApplication). This includes the former \"not None\" check.\n\n==== qutebrowser/components/scrollcommands.py\n\n- Add basic annotation for \"funcs\" dict. Could have a callable protocol to\n  specify it needs a count kwarg, see #7098.\n\n==== qutebrowser/config/stylesheet.py\n\n- Correctly specify that stylesheet apply to QWidgets, not any QObject.\n- Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy\n  about this with overloads and protocols (stylesheet for set_register being None\n  => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not\n  worth the troble. See #7098.\n\n==== qutebrowser/keyinput/keyutils.py\n\n- Remove some now-unneeded type ignores and add a cast for using a single enum\n  value as flags. Might need to look at this again with Qt 6 support.\n\n==== qutebrowser/keyinput/modeman.py\n\n- Add a FIXME for using a TypedDict, see comments for hints.py above.\n\n==== qutebrowser/mainwindow/mainwindow.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n- Improve where we cast from WindowType to WindowFlags, no int needed\n- Use new .tab_bar() getter, see below.\n\n==== qutebrowser/mainwindow/prompt.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n\n==== qutebrowser/mainwindow/statusbar/bar.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/statusbar/command.py\n\n- Fix type for setText() override (from QLineEdit): text can be None\n  (QString in C++).\n\n==== qutebrowser/mainwindow/statusbar/url.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/tabbedbrowser.py\n\n- Specify that TabDeque manages browser tabs, not any QWidgets. It accesses\n  AbstractTab-specific attributes.\n- Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access\n  .maybe_hide.\n- Fix the annotations for stored marks: Scroll positions are a QPoint, not int.\n- Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and\n  .widget(), which ensures that the return values are valid AbstractTabs (or None\n  for _tab_by_idx). This is needed because we access AbstractTab-specific\n  attributes.\n- For some places, where the tab can be None, continue using .currentTab() but\n  add asserts.\n- Remove some now-unneeded [unreachable] ignores, as mypy knows about the None\n  possibility now.\n\n==== qutebrowser/mainwindow/tabwidget.py\n\n- Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and\n  .widget() are of type TabBar and AbstractTab, respectively.\n- Add additional assertions where we expect ._tab_by_idx() to never be None.\n- Remove dead code in get_tab_fields for handling a None y scroll position. I\n  was unable to find any place in the code where this could be set to None.\n- Remove some now-unneeded type ignores and casts, as mypy now knows that\n  _type_by_idx() could be None.\n- Work around a strange instance where mypy complains about not being able to\n  find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility,\n  despite it clearly being shown as a bool *inside* that class without any\n  annotation.\n- Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in\n  fact a TabWidget.\n\n==== qutebrowser/misc/crashsignal.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/editor.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/ipc.py\n\n- Remove now unneeded type ignores for signals.\n- Add new type ignores for .error() which is both a signal and a getter\n  (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was\n  renamed to errorOccurred in 5.15.\n\n==== qutebrowser/misc/objects.py\n\n- Make sure mypy knows that objects.app is our custom Application (with custom\n  attributes) rather than any QApplication.\n\n==== qutebrowser/utils/objreg.py\n\n- Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol,\n  but ideally, the whole objreg stuff should die one day anyways.\n\n==== tests/unit/completion/test_completer.py\n\n- Make CompletionWidgetStub inherit from CompletionView so that it passes the\n  new isinstance() asserts in completer.py (see above).",
        "code": "def on_mode_entered(self, mode):\n        \n        if (config.val.tabs.mode_on_change == 'restore' and\n                mode in modeman.INPUT_MODES):\n            tab = self.widget.currentWidget()\n            if tab is not None:\n                assert isinstance(tab, browsertab.AbstractTab), tab\n                tab.data.input_mode = mode\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 107,
        "n_words": 26,
        "vocab_size": 21,
        "complexity": 4,
        "nloc": 7,
        "token_counts": 60,
        "n_ast_nodes": 96,
        "n_identifiers": 17,
        "d_id": 117362,
        "documentation": {
            "docstring": "Save input mode when tabs.mode_on_change = restore.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 40266,
        "commit_id": "47b5c8af57f0f927d50fe94f3474b09a54292553",
        "repo": "seaborn",
        "path": "seaborn/external/appdirs.py",
        "file_name": "appdirs.py",
        "fun_name": "user_state_dir",
        "commit_message": "Standardize cache directory",
        "code": "def user_state_dir(appname=None, appauthor=None, version=None, roaming=False):\n    r\n    if system in [\"win32\", \"darwin\"]:\n        path = user_data_dir(appname, appauthor, None, roaming)\n    else:\n        path = os.getenv('XDG_STATE_HOME', os.path.expanduser(\"~/.local/state\"))\n        if appname:\n            path = os.path.join(path, appname)\n    if appname and version:\n        path = os.path.join(path, version)\n    return path\n\n",
        "url": "https://github.com/mwaskom/seaborn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 91,
        "n_words": 38,
        "vocab_size": 28,
        "complexity": 5,
        "nloc": 40,
        "token_counts": 95,
        "n_ast_nodes": 150,
        "n_identifiers": 12,
        "d_id": 7368,
        "documentation": {
            "docstring": "Return full path to the user-specific state dir for this application.\n\n        \"appname\" is the name of application.\n            If None, just the system directory is returned.\n        \"appauthor\" (only used on Windows) is the name of the\n            appauthor or distributing body for this application. Typically\n            it is the owning company name. This falls back to appname. You may\n            pass False to disable it.\n        \"version\" is an optional version path element to append to the\n            path. You might want to use this if you want multiple versions\n            of your app to be able to run independently. If used, this\n            would typically be \"<major>.<minor>\".\n            Only applied when appname is present.\n        \"roaming\" (boolean, default False) can be set True to use the Windows\n            roaming appdata directory. That means that for users on a Windows\n            network setup for roaming profiles, this user data will be\n            sync'd on login. See\n            <http://technet.microsoft.com/en-us/library/cc766489(WS.10).aspx>\n            for a discussion of issues.\n\n    Typical user state directories are:\n        Mac OS X:  same as user_data_dir\n        Unix:      ~/.local/state/<AppName>   # or in $XDG_STATE_HOME, if defined\n        Win *:     same as user_data_dir\n\n    For Unix, we follow this Debian proposal <https://wiki.debian.org/XDGBaseDirectorySpecification#state>\n    to extend the XDG spec and support $XDG_STATE_HOME.\n\n    That means, by default \"~/.local/state/<AppName>\".\n    ",
            "n_words": 194,
            "vocab_size": 135,
            "n_whitespaces": 413,
            "language": "en"
        }
    },
    {
        "id": 115838,
        "commit_id": "871793d4fbd99f454c0c1ff14db6ce3c385e656c",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/lightwood_handler/tests/test_lightwood_handler.py",
        "file_name": "test_lightwood_handler.py",
        "fun_name": "test_01_drop_predictor",
        "commit_message": "add more TS tests",
        "code": "def test_01_drop_predictor(self):\n        if self.test_model_1 not in self.handler.get_tables().data_frame.values:\n            # TODO: seems redundant because of test_02\n            query = f\n            self.handler.native_query(query)\n        response = self.handler.native_query(f\"DROP PREDICTOR {self.test_model_1}\")\n        self.assertTrue(response.type == RESPONSE_TYPE.OK)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 79,
        "n_words": 26,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 58,
        "n_ast_nodes": 120,
        "n_identifiers": 16,
        "d_id": 25578,
        "documentation": {
            "docstring": "\n                CREATE PREDICTOR {self.test_model_1}\n                FROM {PG_HANDLER_NAME} (SELECT * FROM {self.data_table_1} limit 50)\n                PREDICT rental_price\n            ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 176171,
        "commit_id": "dec723f072eb997a497a159dbe8674cd39999ee9",
        "repo": "networkx",
        "path": "networkx/generators/small.py",
        "file_name": "small.py",
        "fun_name": "truncated_cube_graph",
        "commit_message": "Docstrings for the small.py module (#5240)\n\n* added description for the first 5 small graphs\r\n\r\n* modified descriptions based on comment and added description for two more functions\r\n\r\n* added doctrings to all the functions\r\n\r\n* Minor touchups.\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def truncated_cube_graph(create_using=None):\n    \n    description = [\n        \"adjacencylist\",\n        \"Truncated Cube Graph\",\n        24,\n        [\n            [2, 3, 5],\n            [12, 15],\n            [4, 5],\n            [7, 9],\n            [6],\n            [17, 19],\n            [8, 9],\n            [11, 13],\n            [10],\n            [18, 21],\n            [12, 13],\n            [15],\n            [14],\n            [22, 23],\n            [16],\n            [20, 24],\n            [18, 19],\n            [21],\n            [20],\n            [24],\n            [22],\n            [23],\n            [24],\n            [],\n        ],\n    ]\n    G = make_small_undirected_graph(description, create_using)\n    return G\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 370,
        "n_words": 56,
        "vocab_size": 46,
        "complexity": 1,
        "nloc": 34,
        "token_counts": 152,
        "n_ast_nodes": 197,
        "n_identifiers": 5,
        "d_id": 41741,
        "documentation": {
            "docstring": "\n    Returns the skeleton of the truncated cube.\n\n    The truncated cube is an Archimedean solid with 14 regular\n    faces (6 octagonal and 8 triangular), 36 edges and 24 nodes [1]_.\n    The truncated cube is created by truncating (cutting off) the tips\n    of the cube one third of the way into each edge [2]_.\n\n    Parameters\n    ----------\n    create_using : NetworkX graph constructor, optional (default=nx.Graph)\n       Graph type to create. If graph instance, then cleared before populated.\n\n    Returns\n    -------\n    G : networkx Graph\n        Skeleton of the truncated cube\n\n    References\n    ----------\n    .. [1] https://en.wikipedia.org/wiki/Truncated_cube\n    .. [2] https://www.coolmath.com/reference/polyhedra-truncated-cube\n\n    ",
            "n_words": 91,
            "vocab_size": 68,
            "n_whitespaces": 153,
            "language": "en"
        }
    },
    {
        "id": 126210,
        "commit_id": "eb69c1ca286a2eec594f02ddaf546657a8127afd",
        "repo": "ray",
        "path": "python/ray/tune/execution/insufficient_resources_manager.py",
        "file_name": "insufficient_resources_manager.py",
        "fun_name": "on_no_available_trials",
        "commit_message": "[air] Add annotation for Tune module. (#27060)\n\nCo-authored-by: Kai Fricke <kai@anyscale.com>",
        "code": "def on_no_available_trials(self, all_trials):\n        \n        # This is approximately saying we are not making progress.\n        if len(all_trials) == self._last_trial_num:\n            if self._no_running_trials_since == -1:\n                self._no_running_trials_since = time.monotonic()\n            elif (\n                time.monotonic() - self._no_running_trials_since\n                > _get_insufficient_resources_warning_threshold()\n            ):\n                if not _is_ray_cluster():  # autoscaler not enabled\n                    # If any of the pending trial cannot be fulfilled,\n                    # that's a good enough hint of trial resources not enough.\n                    for trial in all_trials:\n                        if (\n                            trial.status is Trial.PENDING\n                            and not _can_fulfill_no_autoscaler(trial)\n                        ):\n                            # TODO(xwjiang):\n                            #  Raise an Error once #18608 is resolved.\n                            logger.warning(_get_insufficient_resources_error_msg(trial))\n                            break\n                else:\n                    # TODO(xwjiang): #17799.\n                    #  Output a more helpful msg for autoscaler.\n                    logger.warning(_get_insufficient_resources_warning_msg())\n                self._no_running_trials_since = time.monotonic()\n        else:\n            self._no_running_trials_since = -1\n        self._last_trial_num = len(all_trials)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 20,
        "n_whitespaces": 602,
        "n_words": 108,
        "vocab_size": 72,
        "complexity": 8,
        "nloc": 22,
        "token_counts": 125,
        "n_ast_nodes": 217,
        "n_identifiers": 19,
        "d_id": 28086,
        "documentation": {
            "docstring": "Tracks information across the life of Tune loop and makes guesses\n        about if Tune loop is stuck due to infeasible resources.\n        If so, outputs certain warning messages.\n        The logic should be conservative, non-intrusive and informative.\n        For example, rate limiting is applied so that the message is not\n        spammy.\n        ",
            "n_words": 48,
            "vocab_size": 42,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 289282,
        "commit_id": "d4c28e04e4793c328d1a1d096c2085ebbe7c5e7c",
        "repo": "core",
        "path": "tests/components/zwave_js/test_lock.py",
        "file_name": "test_lock.py",
        "fun_name": "test_door_lock_no_value",
        "commit_message": "Reduce missed coverage in zwave_js (#79571)\n\n* Reduce missed coverage in zwave_js.climate and cover\r\n\r\n* Add switch platform coverage\r\n\r\n* Add select platform\r\n\r\n* Add lock platform\r\n\r\n* Remove one line of coverage from number platform\r\n\r\n* update docstring",
        "code": "async def test_door_lock_no_value(hass, client, lock_schlage_be469_state, integration):\n    \n    node_state = replace_value_of_zwave_value(\n        lock_schlage_be469_state,\n        [\n            ZwaveValueMatcher(\n                property_=CURRENT_MODE_PROPERTY,\n                command_class=CommandClass.DOOR_LOCK,\n            )\n        ],\n        None,\n    )\n    node = Node(client, node_state)\n    client.driver.controller.emit(\"node added\", {\"node\": node})\n    await hass.async_block_till_done()\n    state = hass.states.get(SCHLAGE_BE469_LOCK_ENTITY)\n    assert state\n    assert state.state == STATE_UNKNOWN\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 144,
        "n_words": 37,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 85,
        "n_ast_nodes": 134,
        "n_identifiers": 24,
        "d_id": 88425,
        "documentation": {
            "docstring": "Test a lock entity with door lock command class that has no value for mode.",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 275572,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_v2/optimizer_v2_test.py",
        "file_name": "optimizer_v2_test.py",
        "fun_name": "make_model",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def make_model():\n    r\n    inputs = []\n    intermediates = []\n    for _ in range(_NUM_LEARNERS):\n        inp = keras.layers.Input(shape=(1,), dtype=tf.int32)\n        layer = keras.layers.Embedding(1, 4)(inp)\n        layer = keras.layers.Dense(1)(layer)\n\n        inputs.append(inp)\n        intermediates.append(layer)\n\n    layer = keras.layers.Concatenate(axis=-1)(intermediates)\n    layer = keras.layers.Dense(1)(layer)\n\n    return keras.models.Model(inputs, layer)\n\n\nCOEFFICIENT_PARAMS = (\n    (\"Adadelta\", adadelta.Adadelta, None),\n    (\"Adagrad\", adagrad.Adagrad, None),\n    (\"Adam\", adam.Adam, None),\n    (\"Adam_amdgrad\", adam.Adam, dict(amsgrad=True)),\n    (\"Adamax\", adamax.Adamax, None),\n    (\"Ftrl\", ftrl.Ftrl, None),\n    (\n        \"Ftrl_l2_shrinkage\",\n        ftrl.Ftrl,\n        dict(l2_shrinkage_regularization_strength=0.1),\n    ),\n    (\"SGD\", gradient_descent.SGD, None),\n    (\"SGD_momentum\", gradient_descent.SGD, dict(momentum=0.5)),\n    (\"Nadam\", nadam.Nadam, None),\n    (\"RMSprop\", rmsprop.RMSprop, None),\n    (\"RMSprop_centered\", rmsprop.RMSprop, dict(centered=True)),\n    (\"RMSprop_momentum\", rmsprop.RMSprop, dict(momentum=0.5)),\n    (\n        \"RMSprop_momentum_centered\",\n        rmsprop.RMSprop,\n        dict(momentum=0.5, centered=True),\n    ),\n)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 229,
        "n_words": 86,
        "vocab_size": 57,
        "complexity": 2,
        "nloc": 41,
        "token_counts": 123,
        "n_ast_nodes": 454,
        "n_identifiers": 44,
        "d_id": 81429,
        "documentation": {
            "docstring": "Constructs a simple ensemble of weak learners model.\n\n    ---------    ---------             ---------    ---------\n    | Input |    | Input |     ...     | Input |    | Input |\n    ---------    ---------             ---------    ---------\n        |            |                     |            |\n        V            V                     V            V\n    ---------    ---------             ---------    ---------\n    | Embed |    | Embed |     ...     | Embed |    | Embed |\n    ---------    ---------             ---------    ---------\n        |            |                     |            |\n        V            V                     V            V\n    ---------    ---------             ---------    ---------\n    | Dense |    | Dense |     ...     | Dense |    | Dense |\n    ---------    ---------             ---------    ---------\n        \\            |                     |            /\n         \\           |                     |           /\n          ---------------------------------------------\n                                |\n                            ---------\n                            | Dense |\n                            ---------\n\n    This topology is chosen because it exercises both dense and sparse update\n    paths.\n\n    Returns:\n      A model for testing optimizer coefficient reuse.\n    ",
            "n_words": 123,
            "vocab_size": 39,
            "n_whitespaces": 731,
            "language": "en"
        }
    },
    {
        "id": 66160,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/hr/doctype/leave_application/leave_application.py",
        "file_name": "leave_application.py",
        "fun_name": "add_department_leaves",
        "commit_message": "style: format code with black",
        "code": "def add_department_leaves(events, start, end, employee, company):\n\tdepartment = frappe.db.get_value(\"Employee\", employee, \"department\")\n\n\tif not department:\n\t\treturn\n\n\t# department leaves\n\tdepartment_employees = frappe.db.sql_list(\n\t\t,\n\t\t(department, company),\n\t)\n\n\tfilter_conditions = ' and employee in (\"%s\")' % '\", \"'.join(department_employees)\n\tadd_leaves(events, start, end, filter_conditions=filter_conditions)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 28,
        "n_words": 39,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 71,
        "n_ast_nodes": 113,
        "n_identifiers": 15,
        "d_id": 14117,
        "documentation": {
            "docstring": "select name from tabEmployee where department=%s\n\t\tand company=%s",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 129063,
        "commit_id": "e9068c45faf2928cd8e38f6d38c5260cb06130d2",
        "repo": "ray",
        "path": "python/ray/data/tests/test_stats.py",
        "file_name": "test_stats.py",
        "fun_name": "test_dataset_stats_read_parquet",
        "commit_message": "[data] Instrument most remaining dataset functions and add docs (#21412)\n\nThis PR finishes most of the stats todos for dataset. The main thing punted for future work is instrumentation of split(), which is particularly tricky since only certain blocks are transformed.\r\n\r\nCo-authored-by: Clark Zinzow <clarkzinzow@gmail.com>",
        "code": "def test_dataset_stats_read_parquet(ray_start_regular_shared, tmp_path):\n    ds = ray.data.range(1000, parallelism=10)\n    ds.write_parquet(str(tmp_path))\n    ds = ray.data.read_parquet(str(tmp_path)).map(lambda x: x)\n    stats = canonicalize(ds.stats())\n    print(stats)\n    assert stats == \n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 38,
        "n_words": 20,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 69,
        "n_ast_nodes": 113,
        "n_identifiers": 16,
        "d_id": 28886,
        "documentation": {
            "docstring": "Stage Z read: N/N blocks executed in T\n* Remote wall time: T min, T max, T mean, T total\n* Remote cpu time: T min, T max, T mean, T total\n* Output num rows: N min, N max, N mean, N total\n* Output size bytes: N min, N max, N mean, N total\n* Tasks per node: N min, N max, N mean; N nodes used\n\nStage N map: N/N blocks executed in T\n* Remote wall time: T min, T max, T mean, T total\n* Remote cpu time: T min, T max, T mean, T total\n* Output num rows: N min, N max, N mean, N total\n* Output size bytes: N min, N max, N mean, N total\n* Tasks per node: N min, N max, N mean; N nodes used\n",
            "n_words": 138,
            "vocab_size": 30,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 62468,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/html5lib/_tokenizer.py",
        "file_name": "_tokenizer.py",
        "fun_name": "emitCurrentToken",
        "commit_message": "upd; format",
        "code": "def emitCurrentToken(self):\n        \n        token = self.currentToken\n        # Add token to the queue to be yielded\n        if (token[\"type\"] in tagTokenTypes):\n            token[\"name\"] = token[\"name\"].translate(asciiUpper2Lower)\n            if token[\"type\"] == tokenTypes[\"StartTag\"]:\n                raw = token[\"data\"]\n                data = attributeMap(raw)\n                if len(raw) > len(data):\n                    # we had some duplicated attribute, fix so first wins\n                    data.update(raw[::-1])\n                token[\"data\"] = data\n\n            if token[\"type\"] == tokenTypes[\"EndTag\"]:\n                if token[\"data\"]:\n                    self.tokenQueue.append({\"type\": tokenTypes[\"ParseError\"],\n                                            \"data\": \"attributes-in-end-tag\"})\n                if token[\"selfClosing\"]:\n                    self.tokenQueue.append({\"type\": tokenTypes[\"ParseError\"],\n                                            \"data\": \"self-closing-flag-on-end-tag\"})\n        self.tokenQueue.append(token)\n        self.state = self.dataState\n\n    # Below are the various tokenizer states worked out.",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 408,
        "n_words": 78,
        "vocab_size": 56,
        "complexity": 7,
        "nloc": 19,
        "token_counts": 162,
        "n_ast_nodes": 293,
        "n_identifiers": 17,
        "d_id": 12978,
        "documentation": {
            "docstring": "This method is a generic handler for emitting the tags. It also sets\n        the state to \"data\" because that's what's needed after a token has been\n        emitted.\n        ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 215074,
        "commit_id": "fbcc707e76f11770712e6828155258ac61e00ff8",
        "repo": "salt",
        "path": "salt/modules/aixpkg.py",
        "file_name": "aixpkg.py",
        "fun_name": "remove",
        "commit_message": "work in progress while resolve issue of python3_32 usage by dnf and yum",
        "code": "def remove(name=None, pkgs=None, **kwargs):\n    \n    targets = salt.utils.args.split_input(pkgs) if pkgs else [name]\n    if not targets:\n        return {}\n\n    if pkgs:\n        log.debug(\"Removing these fileset(s)/rpm package(s) %s: %s\", name, targets)\n\n    errors = []\n\n    # Get a list of the currently installed pkgs.\n    old = list_pkgs()\n\n    # Remove the fileset or rpm package(s)\n    for target in targets:\n        try:\n            named, versionpkg, rpmpkg = _check_pkg(target)\n        except CommandExecutionError as exc:\n            if exc.info:\n                errors.append(exc.info[\"errors\"])\n            continue\n\n        if rpmpkg:\n\n            # assume use dnf or yum\n            cmdflags = \" -y remove \"\n            if pathlib.Path(\"/opt/freeware/bin/dnf\").is_file():\n                cmdexe = \"/opt/freeware/bin/dnf\"\n            elif pathlib.Path(\"/opt/freeware/bin/yum\").is_file():\n                cmdexe = \"/opt/freeware/bin/yum\"\n            elif pathlib.Path(\"/usr/bin/yum\").is_file():\n                cmdexe = \"/usr/bin/yum\"\n            else:\n                cmdexe = \"/usr/bin/rpm\"\n                cmdflags = \" -e \"\n\n            cmd = [cmdexe, cmdflags, named]\n            out = __salt__[\"cmd.run_all\"](cmd, python_shell=False)\n        else:\n            cmd = [\"/usr/sbin/installp\", \"-u\", named]\n            out = __salt__[\"cmd.run_all\"](cmd, python_shell=False)\n\n    # Get a list of the packages after the uninstall\n    __context__.pop(\"pkg.list_pkgs\", None)\n    new = list_pkgs()\n    ret = salt.utils.data.compare_dicts(old, new)\n\n    if errors:\n        raise CommandExecutionError(\n            \"Problems encountered removing filesets(s)/package(s)\",\n            info={\"changes\": ret, \"errors\": errors},\n        )\n\n    return ret\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 513,
        "n_words": 157,
        "vocab_size": 106,
        "complexity": 12,
        "nloc": 40,
        "token_counts": 256,
        "n_ast_nodes": 443,
        "n_identifiers": 38,
        "d_id": 53792,
        "documentation": {
            "docstring": "\n    Remove specified fileset(s)/rpm package(s).\n\n    name\n        The name of the fileset or rpm package to be deleted.\n\n    .. versionadded:: 3005\n\n        preference to install rpm packages are to use in the following order:\n            /opt/freeware/bin/dnf\n            /opt/freeware/bin/yum\n            /usr/bin/yum\n            /usr/bin/rpm\n\n    Multiple Package Options:\n\n    pkgs\n        A list of filesets and/or rpm packages to delete.\n        Must be passed as a python list. The ``name`` parameter will be\n        ignored if this option is passed.\n\n\n    Returns a list containing the removed packages.\n\n    CLI Example:\n\n    .. code-block:: bash\n\n        salt '*' pkg.remove <fileset/rpm package name>\n        salt '*' pkg.remove tcsh\n        salt '*' pkg.remove xlC.rte\n        salt '*' pkg.remove Firefox.base.adt\n        salt '*' pkg.remove pkgs='[\"foo\", \"bar\"]'\n    ",
            "n_words": 101,
            "vocab_size": 72,
            "n_whitespaces": 243,
            "language": "en"
        }
    },
    {
        "id": 293322,
        "commit_id": "2d4ccddd99bcc4bd314f813214be693788b1c0bf",
        "repo": "core",
        "path": "homeassistant/components/samsungtv/config_flow.py",
        "file_name": "config_flow.py",
        "fun_name": "_async_update_existing_host_entry",
        "commit_message": "Fix SSDP unique id in SamsungTV config flow (#67811)\n\nCo-authored-by: epenet <epenet@users.noreply.github.com>\r\nCo-authored-by: J. Nick Koston <nick@koston.org>",
        "code": "def _async_update_existing_host_entry(self) -> config_entries.ConfigEntry | None:\n        \n        for entry in self._async_current_entries(include_ignore=False):\n            mac = entry.data.get(CONF_MAC)\n            mac_match = mac and self._mac and mac == self._mac\n            upnp_udn_match = self._upnp_udn and self._upnp_udn == entry.unique_id\n            if (\n                entry.data[CONF_HOST] != self._host\n                and not mac_match\n                and not upnp_udn_match\n            ):\n                continue\n            entry_kw_args: dict = {}\n            if (self._udn and self._upnp_udn and self._upnp_udn != self._udn) or (\n                self.unique_id and entry.unique_id is None\n            ):\n                entry_kw_args[\"unique_id\"] = self.unique_id\n            if self._mac and not entry.data.get(CONF_MAC):\n                entry_kw_args[\"data\"] = {**entry.data, CONF_MAC: self._mac}\n            if entry_kw_args:\n                self.hass.config_entries.async_update_entry(entry, **entry_kw_args)\n                self.hass.async_create_task(\n                    self.hass.config_entries.async_reload(entry.entry_id)\n                )\n                return entry\n        return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 401,
        "n_words": 86,
        "vocab_size": 49,
        "complexity": 16,
        "nloc": 29,
        "token_counts": 197,
        "n_ast_nodes": 312,
        "n_identifiers": 26,
        "d_id": 92385,
        "documentation": {
            "docstring": "Check existing entries and update them.\n\n        Returns the existing entry if it was updated.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 60669,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/configuration.py",
        "file_name": "configuration.py",
        "fun_name": "_load_environment_vars",
        "commit_message": "upd; format",
        "code": "def _load_environment_vars(self):\n        # type: () -> None\n        \n        self._config[kinds.ENV_VAR].update(\n            self._normalized_keys(\":env:\", self.get_environ_vars())\n        )\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 50,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 30,
        "n_ast_nodes": 53,
        "n_identifiers": 8,
        "d_id": 12235,
        "documentation": {
            "docstring": "Loads configuration from environment variables\n        ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 217910,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/imaplib.py",
        "file_name": "imaplib.py",
        "fun_name": "open",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def open(self, host=None, port=None, timeout=None):\n        \n        self.host = None        # For compatibility with parent class\n        self.port = None\n        self.sock = None\n        self.file = None\n        self.process = subprocess.Popen(self.command,\n            bufsize=DEFAULT_BUFFER_SIZE,\n            stdin=subprocess.PIPE, stdout=subprocess.PIPE,\n            shell=True, close_fds=True)\n        self.writefile = self.process.stdin\n        self.readfile = self.process.stdout\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 133,
        "n_words": 37,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 92,
        "n_ast_nodes": 139,
        "n_identifiers": 20,
        "d_id": 55008,
        "documentation": {
            "docstring": "Setup a stream connection.\n        This connection will be used by the routines:\n            read, readline, send, shutdown.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 218488,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ipaddress.py",
        "file_name": "ipaddress.py",
        "fun_name": "collapse_addresses",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def collapse_addresses(addresses):\n    \n    addrs = []\n    ips = []\n    nets = []\n\n    # split IP addresses and networks\n    for ip in addresses:\n        if isinstance(ip, _BaseAddress):\n            if ips and ips[-1]._version != ip._version:\n                raise TypeError(\"%s and %s are not of the same version\" % (\n                                 ip, ips[-1]))\n            ips.append(ip)\n        elif ip._prefixlen == ip._max_prefixlen:\n            if ips and ips[-1]._version != ip._version:\n                raise TypeError(\"%s and %s are not of the same version\" % (\n                                 ip, ips[-1]))\n            try:\n                ips.append(ip.ip)\n            except AttributeError:\n                ips.append(ip.network_address)\n        else:\n            if nets and nets[-1]._version != ip._version:\n                raise TypeError(\"%s and %s are not of the same version\" % (\n                                 ip, nets[-1]))\n            nets.append(ip)\n\n    # sort and dedup\n    ips = sorted(set(ips))\n\n    # find consecutive address ranges in the sorted sequence and summarize them\n    if ips:\n        for first, last in _find_address_range(ips):\n            addrs.extend(summarize_address_range(first, last))\n\n    return _collapse_addresses_internal(addrs + nets)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 448,
        "n_words": 128,
        "vocab_size": 71,
        "complexity": 13,
        "nloc": 28,
        "token_counts": 205,
        "n_ast_nodes": 333,
        "n_identifiers": 23,
        "d_id": 55342,
        "documentation": {
            "docstring": "Collapse a list of IP objects.\n\n    Example:\n        collapse_addresses([IPv4Network('192.0.2.0/25'),\n                            IPv4Network('192.0.2.128/25')]) ->\n                           [IPv4Network('192.0.2.0/24')]\n\n    Args:\n        addresses: An iterator of IPv4Network or IPv6Network objects.\n\n    Returns:\n        An iterator of the collapsed IPv(4|6)Network objects.\n\n    Raises:\n        TypeError: If passed a list of mixed version objects.\n\n    ",
            "n_words": 38,
            "vocab_size": 28,
            "n_whitespaces": 134,
            "language": "en"
        }
    },
    {
        "id": 135275,
        "commit_id": "5af66e66cc6aa3859e2e15637c66f6decbec13b9",
        "repo": "ray",
        "path": "rllib/algorithms/tests/test_algorithm_config.py",
        "file_name": "test_algorithm_config.py",
        "fun_name": "test_creating_algo_config_from_legacy_dict",
        "commit_message": "[RLlib] AlgorithmConfigs: Broad rollout; Example scripts. (#29700)",
        "code": "def test_creating_algo_config_from_legacy_dict(self):\n        \n        config_dict = {\n            \"evaluation_config\": {\n                \"lr\": 0.1,\n            },\n            \"lr\": 0.2,\n            # Old-style multi-agent dict.\n            \"multiagent\": {\n                \"policies\": {\"pol1\", \"pol2\"},\n                \"policies_to_train\": [\"pol1\"],\n                \"policy_mapping_fn\": lambda aid, episode, worker, **kwargs: \"pol1\",\n            },\n        }\n        config = AlgorithmConfig.from_dict(config_dict)\n        self.assertFalse(config.in_evaluation)\n        self.assertTrue(config.lr == 0.2)\n        self.assertTrue(config.policies == {\"pol1\", \"pol2\"})\n        self.assertTrue(config.policy_mapping_fn(1, 2, 3) == \"pol1\")\n        eval_config = config.get_evaluation_config_object()\n        self.assertTrue(eval_config.in_evaluation)\n        self.assertTrue(eval_config.lr == 0.1)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 258,
        "n_words": 55,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 146,
        "n_ast_nodes": 238,
        "n_identifiers": 18,
        "d_id": 30578,
        "documentation": {
            "docstring": "Tests, whether translation from dict to AlgorithmConfig works as expected.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 157016,
        "commit_id": "72832d4bd685a25000ee646966a1aa5d0d8a1793",
        "repo": "dask",
        "path": "dask/dataframe/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "cov",
        "commit_message": "Groupby sort upstream compatibility (#9486)",
        "code": "def cov(self, ddof=1, split_every=None, split_out=1, std=False):\n        \n        if self.sort is None and split_out > 1:\n            warnings.warn(SORT_SPLIT_OUT_WARNING, FutureWarning)\n\n        levels = _determine_levels(self.by)\n\n        is_mask = any(is_series_like(s) for s in self.by)\n        if self._slice:\n            if is_mask:\n                self.obj = self.obj[self._slice]\n            else:\n                sliced_plus = list(self._slice) + list(self.by)\n                self.obj = self.obj[sliced_plus]\n\n        result = aca(\n            [self.obj, self.by]\n            if not isinstance(self.by, list)\n            else [self.obj] + self.by,\n            chunk=_cov_chunk,\n            aggregate=_cov_agg,\n            combine=_cov_combine,\n            token=self._token_prefix + \"cov\",\n            aggregate_kwargs={\"ddof\": ddof, \"levels\": levels, \"std\": std},\n            combine_kwargs={\"levels\": levels},\n            split_every=split_every,\n            split_out=split_out,\n            split_out_setup=split_out_on_index,\n            sort=self.sort,\n        )\n\n        if isinstance(self.obj, Series):\n            result = result[result.columns[0]]\n        if self._slice:\n            result = result[self._slice]\n        return result\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 400,
        "n_words": 87,
        "vocab_size": 68,
        "complexity": 9,
        "nloc": 31,
        "token_counts": 244,
        "n_ast_nodes": 368,
        "n_identifiers": 39,
        "d_id": 36829,
        "documentation": {
            "docstring": "Groupby covariance is accomplished by\n\n        1. Computing intermediate values for sum, count, and the product of\n           all columns: a b c -> a*a, a*b, b*b, b*c, c*c.\n\n        2. The values are then aggregated and the final covariance value is calculated:\n           cov(X, Y) = X*Y - Xbar * Ybar\n\n        When `std` is True calculate Correlation\n        ",
            "n_words": 54,
            "vocab_size": 48,
            "n_whitespaces": 102,
            "language": "en"
        }
    },
    {
        "id": 196399,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/matrices/repmatrix.py",
        "file_name": "repmatrix.py",
        "fun_name": "copyin_matrix",
        "commit_message": "Moved imports to higher level",
        "code": "def copyin_matrix(self, key, value):\n        \n        rlo, rhi, clo, chi = self.key2bounds(key)\n        shape = value.shape\n        dr, dc = rhi - rlo, chi - clo\n        if shape != (dr, dc):\n            raise ShapeError(filldedent(\"The Matrix `value` doesn't have the \"\n                                        \"same dimensions \"\n                                        \"as the in sub-Matrix given by `key`.\"))\n\n        for i in range(value.rows):\n            for j in range(value.cols):\n                self[i + rlo, j + clo] = value[i, j]\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 219,
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        "token_counts": 96,
        "n_ast_nodes": 150,
        "n_identifiers": 19,
        "d_id": 47899,
        "documentation": {
            "docstring": "Copy in values from a matrix into the given bounds.\n\n        Parameters\n        ==========\n\n        key : slice\n            The section of this matrix to replace.\n        value : Matrix\n            The matrix to copy values from.\n\n        Examples\n        ========\n\n        >>> from sympy import Matrix, eye\n        >>> M = Matrix([[0, 1], [2, 3], [4, 5]])\n        >>> I = eye(3)\n        >>> I[:3, :2] = M\n        >>> I\n        Matrix([\n        [0, 1, 0],\n        [2, 3, 0],\n        [4, 5, 1]])\n        >>> I[0, 1] = M\n        >>> I\n        Matrix([\n        [0, 0, 1],\n        [2, 2, 3],\n        [4, 4, 5]])\n\n        See Also\n        ========\n\n        copyin_list\n        ",
            "n_words": 90,
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            "language": "en"
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    },
    {
        "id": 133868,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "rllib/agents/trainer.py",
        "file_name": "trainer.py",
        "fun_name": "step",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def step(self) -> ResultDict:\n        \n        step_attempt_results = None\n\n        with self._step_context() as step_ctx:\n            while not step_ctx.should_stop(step_attempt_results):\n                # Try to train one step.\n                try:\n                    step_attempt_results = self.step_attempt()\n                # @ray.remote RolloutWorker failure.\n                except RayError as e:\n                    # Try to recover w/o the failed worker.\n                    if self.config[\"ignore_worker_failures\"]:\n                        logger.exception(\"Error in train call, attempting to recover\")\n                        self.try_recover_from_step_attempt()\n                    # Error out.\n                    else:\n                        logger.warning(\n                            \"Worker crashed during call to `step_attempt()`. \"\n                            \"To try to continue training without the failed \"\n                            \"worker, set `ignore_worker_failures=True`.\"\n                        )\n                        raise e\n                # Any other exception.\n                except Exception as e:\n                    # Allow logs messages to propagate.\n                    time.sleep(0.5)\n                    raise e\n\n        result = step_attempt_results\n\n        if hasattr(self, \"workers\") and isinstance(self.workers, WorkerSet):\n            # Sync filters on workers.\n            self._sync_filters_if_needed(self.workers)\n\n            # Collect worker metrics.\n            if self.config[\"_disable_execution_plan_api\"]:\n                result = self._compile_step_results(\n                    step_ctx=step_ctx,\n                    step_attempt_results=step_attempt_results,\n                )\n\n        return result\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 726,
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        "complexity": 8,
        "nloc": 43,
        "token_counts": 142,
        "n_ast_nodes": 254,
        "n_identifiers": 25,
        "d_id": 30128,
        "documentation": {
            "docstring": "Implements the main `Trainer.train()` logic.\n\n        Takes n attempts to perform a single training step. Thereby\n        catches RayErrors resulting from worker failures. After n attempts,\n        fails gracefully.\n\n        Override this method in your Trainer sub-classes if you would like to\n        handle worker failures yourself. Otherwise, override\n        `self.step_attempt()` to keep the n attempts (catch worker failures).\n\n        Returns:\n            The results dict with stats/infos on sampling, training,\n            and - if required - evaluation.\n        ",
            "n_words": 68,
            "vocab_size": 58,
            "n_whitespaces": 146,
            "language": "en"
        }
    },
    {
        "id": 196780,
        "commit_id": "f757f3daae6e11ea0cfb7dadc133274d8d74315f",
        "repo": "sympy",
        "path": "sympy/integrals/deltafunctions.py",
        "file_name": "deltafunctions.py",
        "fun_name": "deltaintegrate",
        "commit_message": "Reordered imports 2",
        "code": "def deltaintegrate(f, x):\n    \n    if not f.has(DiracDelta):\n        return None\n\n    # g(x) = DiracDelta(h(x))\n    if f.func == DiracDelta:\n        h = f.expand(diracdelta=True, wrt=x)\n        if h == f:  # can't simplify the expression\n            #FIXME: the second term tells whether is DeltaDirac or Derivative\n            #For integrating derivatives of DiracDelta we need the chain rule\n            if f.is_simple(x):\n                if (len(f.args) <= 1 or f.args[1] == 0):\n                    return Heaviside(f.args[0])\n                else:\n                    return (DiracDelta(f.args[0], f.args[1] - 1) /\n                        f.args[0].as_poly().LC())\n        else:  # let's try to integrate the simplified expression\n            fh = integrate(h, x)\n            return fh\n    elif f.is_Mul or f.is_Pow:  # g(x) = a*b*c*f(DiracDelta(h(x)))*d*e\n        g = f.expand()\n        if f != g:  # the expansion worked\n            fh = integrate(g, x)\n            if fh is not None and not isinstance(fh, Integral):\n                return fh\n        else:\n            # no expansion performed, try to extract a simple DiracDelta term\n            deltaterm, rest_mult = change_mul(f, x)\n\n            if not deltaterm:\n                if rest_mult:\n                    fh = integrate(rest_mult, x)\n                    return fh\n            else:\n                from sympy.solvers import solve\n                deltaterm = deltaterm.expand(diracdelta=True, wrt=x)\n                if deltaterm.is_Mul:  # Take out any extracted factors\n                    deltaterm, rest_mult_2 = change_mul(deltaterm, x)\n                    rest_mult = rest_mult*rest_mult_2\n                point = solve(deltaterm.args[0], x)[0]\n\n                # Return the largest hyperreal term left after\n                # repeated integration by parts.  For example,\n                #\n                #   integrate(y*DiracDelta(x, 1),x) == y*DiracDelta(x,0),  not 0\n                #\n                # This is so Integral(y*DiracDelta(x).diff(x),x).doit()\n                # will return y*DiracDelta(x) instead of 0 or DiracDelta(x),\n                # both of which are correct everywhere the value is defined\n                # but give wrong answers for nested integration.\n                n = (0 if len(deltaterm.args)==1 else deltaterm.args[1])\n                m = 0\n                while n >= 0:\n                    r = S.NegativeOne**n*rest_mult.diff(x, n).subs(x, point)\n                    if r.is_zero:\n                        n -= 1\n                        m += 1\n                    else:\n                        if m == 0:\n                            return r*Heaviside(x - point)\n                        else:\n                            return r*DiracDelta(x,m-1)\n                # In some very weak sense, x=0 is still a singularity,\n                # but we hope will not be of any practical consequence.\n                return S.Zero\n    return None\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 26,
        "n_whitespaces": 1179,
        "n_words": 297,
        "vocab_size": 173,
        "complexity": 19,
        "nloc": 48,
        "token_counts": 364,
        "n_ast_nodes": 585,
        "n_identifiers": 40,
        "d_id": 48168,
        "documentation": {
            "docstring": "\n    deltaintegrate(f, x)\n\n    Explanation\n    ===========\n\n    The idea for integration is the following:\n\n    - If we are dealing with a DiracDelta expression, i.e. DiracDelta(g(x)),\n      we try to simplify it.\n\n      If we could simplify it, then we integrate the resulting expression.\n      We already know we can integrate a simplified expression, because only\n      simple DiracDelta expressions are involved.\n\n      If we couldn't simplify it, there are two cases:\n\n      1) The expression is a simple expression: we return the integral,\n         taking care if we are dealing with a Derivative or with a proper\n         DiracDelta.\n\n      2) The expression is not simple (i.e. DiracDelta(cos(x))): we can do\n         nothing at all.\n\n    - If the node is a multiplication node having a DiracDelta term:\n\n      First we expand it.\n\n      If the expansion did work, then we try to integrate the expansion.\n\n      If not, we try to extract a simple DiracDelta term, then we have two\n      cases:\n\n      1) We have a simple DiracDelta term, so we return the integral.\n\n      2) We didn't have a simple term, but we do have an expression with\n         simplified DiracDelta terms, so we integrate this expression.\n\n    Examples\n    ========\n\n        >>> from sympy.abc import x, y, z\n        >>> from sympy.integrals.deltafunctions import deltaintegrate\n        >>> from sympy import sin, cos, DiracDelta\n        >>> deltaintegrate(x*sin(x)*cos(x)*DiracDelta(x - 1), x)\n        sin(1)*cos(1)*Heaviside(x - 1)\n        >>> deltaintegrate(y**2*DiracDelta(x - z)*DiracDelta(y - z), y)\n        z**2*DiracDelta(x - z)*Heaviside(y - z)\n\n    See Also\n    ========\n\n    sympy.functions.special.delta_functions.DiracDelta\n    sympy.integrals.integrals.Integral\n    ",
            "n_words": 225,
            "vocab_size": 115,
            "n_whitespaces": 411,
            "language": "en"
        }
    },
    {
        "id": 104394,
        "commit_id": "e35be138148333078284b942ccc9ed7b1d826f97",
        "repo": "datasets",
        "path": "src/datasets/table.py",
        "file_name": "table.py",
        "fun_name": "to_batches",
        "commit_message": "Update docs to new frontend/UI (#3690)\n\n* WIP: update docs to new UI\r\n\r\n* make style\r\n\r\n* Rm unused\r\n\r\n* inject_arrow_table_documentation __annotations__\r\n\r\n* hasattr(arrow_table_method, \"__annotations__\")\r\n\r\n* Update task_template.rst\r\n\r\n* Codeblock PT-TF-SPLIT\r\n\r\n* Convert loading scripts\r\n\r\n* Convert docs to mdx\r\n\r\n* Fix mdx\r\n\r\n* Add <Tip>\r\n\r\n* Convert mdx tables\r\n\r\n* Fix codeblock\r\n\r\n* Rm unneded hashlinks\r\n\r\n* Update index.mdx\r\n\r\n* Redo dev change\r\n\r\n* Rm circle ci `build_doc` & `deploy_doc`\r\n\r\n* Rm unneeded files\r\n\r\n* Update docs reamde\r\n\r\n* Standardize to `Example::`\r\n\r\n* mdx logging levels doc\r\n\r\n* Table properties inject_arrow_table_documentation\r\n\r\n* ``` to ```py mdx\r\n\r\n* Add Tips mdx\r\n\r\n* important,None -> <Tip warning={true}>\r\n\r\n* More misc\r\n\r\n* Center imgs\r\n\r\n* Update instllation page\r\n\r\n* `setup.py` docs section\r\n\r\n* Rm imgs since they are in hf.co\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* Update index mdx\r\n\r\n* Update docs/source/access.mdx\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\n\r\n* just `Dataset` obj\r\n\r\n* Addedversion just italics\r\n\r\n* Update ReadInstruction doc example syntax\r\n\r\n* Change docstring for `prepare_for_task`\r\n\r\n* Chore\r\n\r\n* Remove `code` syntax from headings\r\n\r\n* Rm `code` syntax from headings\r\n\r\n* Hashlink backward compatability\r\n\r\n* S3FileSystem doc\r\n\r\n* S3FileSystem doc updates\r\n\r\n* index.mdx updates\r\n\r\n* Add darkmode gifs\r\n\r\n* Index logo img css classes\r\n\r\n* Index mdx dataset logo img size\r\n\r\n* Docs for DownloadMode class\r\n\r\n* Doc DownloadMode table\r\n\r\n* format docstrings\r\n\r\n* style\r\n\r\n* Add doc builder scripts (#3790)\r\n\r\n* add doc builder scripts\r\n\r\n* fix docker image\r\n\r\n* Docs new UI actions no self hosted (#3793)\r\n\r\n* No self hosted\r\n\r\n* replace doc injection by actual docstrings\r\n\r\n* Docstring formatted\r\n\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>\r\nCo-authored-by: Mishig Davaadorj <dmishig@gmail.com>\r\n\r\n* Rm notebooks from docs actions since they dont exi\r\n\r\n* Update tsting branch\r\n\r\n* More docstring\r\n\r\n* Chore\r\n\r\n* bump up node version\r\n\r\n* bump up node\r\n\r\n* ``` -> ```py for audio_process.mdx\r\n\r\n* Update .github/workflows/build_documentation.yml\r\n\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\n\r\n* Uodate dev doc build\r\n\r\n* remove run on PR\r\n\r\n* fix action\r\n\r\n* Fix gh doc workflow\r\n\r\n* forgot this change when merging master\r\n\r\n* Update build doc\r\n\r\nCo-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>\r\nCo-authored-by: Quentin Lhoest <lhoest.q@gmail.com>\r\nCo-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>\r\nCo-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>",
        "code": "def to_batches(self, *args, **kwargs):\n        \n        return self.table.to_batches(*args, **kwargs)\n",
        "url": "https://github.com/huggingface/datasets.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
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        "n_identifiers": 5,
        "d_id": 21831,
        "documentation": {
            "docstring": "\n        Convert Table to list of (contiguous) RecordBatch objects.\n\n        Args:\n            max_chunksize (:obj:`int`, defaults to `None`):\n                Maximum size for RecordBatch chunks. Individual chunks may be\n                smaller depending on the chunk layout of individual columns.\n\n        Returns:\n            :obj:`List[pyarrow.RecordBatch]`:\n        ",
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    },
    {
        "id": 284534,
        "commit_id": "7b374b76629a963cef9a22b41bc8acbef70e876a",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/terminal_helper.py",
        "file_name": "terminal_helper.py",
        "fun_name": "check_for_updates",
        "commit_message": "Add check for updates at terminal startup (#1839)\n\n* Add check for updates at terminal startup\r\n\r\n* Fix ycrv missing from documentation\r\n\r\n* Add new line after update check message\r\n\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>",
        "code": "def check_for_updates() -> None:\n    \n    # The commit has was commented out because the terminal was crashing due to git import for multiple users\n    # ({str(git.Repo('.').head.commit)[:7]})\n    try:\n        r = requests.get(\n            \"https://api.github.com/repos/openbb-finance/openbbterminal/releases/latest\",\n            timeout=1,\n        )\n    except Exception:\n        r = None\n\n    if r is not None and r.status_code == 200:\n        release = r.json()[\"html_url\"].split(\"/\")[-1].replace(\"v\", \"\")\n        if obbff.VERSION == release:\n            console.print(\"[green]You are using the latest version[/green]\")\n        else:\n            console.print(\"[red]You are not using the latest version[/red]\")\n            console.print(\n                \"[yellow]Check for updates at https://openbb.co/products/terminal#get-started[/yellow]\"\n            )\n    else:\n        console.print(\n            \"[yellow]Unable to check for updates... \"\n            + \"Check your internet connection and try again...[/yellow]\"\n        )\n    console.print(\"\")\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "d_id": 84784,
        "documentation": {
            "docstring": "Check if the latest version is running.\n\n    Checks github for the latest release version and compares it to obbff.VERSION.\n    ",
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            "vocab_size": 16,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 158208,
        "commit_id": "b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2",
        "repo": "d2l-zh",
        "path": "d2l/mxnet.py",
        "file_name": "mxnet.py",
        "fun_name": "load_array",
        "commit_message": "[PaddlePaddle] Merge master into Paddle branch (#1186)\n\n* change 15.2 title in chinese version (#1109)\r\n\r\nchange title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘\r\n\r\n* 修改部分语义表述 (#1105)\r\n\r\n* Update r0.17.5 (#1120)\r\n\r\n* Bump versions in installation\r\n\r\n* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)\r\n\r\n* line 313: \"bert.mall\" -> \"bert.small\" (#1130)\r\n\r\n* fix: update language as native reader (#1114)\r\n\r\n* Fix the translation of \"stride\" (#1115)\r\n\r\n* Update index.md (#1118)\r\n\r\n修改部分语义表述\r\n\r\n* Update self-attention-and-positional-encoding.md (#1133)\r\n\r\n依照本书的翻译习惯，将pooling翻译成汇聚\r\n\r\n* maybe a comment false (#1149)\r\n\r\n* maybe a little false\r\n\r\n* maybe a little false\r\n\r\n* A minor bug in the rcnn section (Chinese edition) (#1148)\r\n\r\n* Update bert.md (#1137)\r\n\r\n一个笔误\r\n# 假设batch_size=2，num_pred_positions=3\r\n# 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1]\r\n\r\n* Update calculus.md (#1135)\r\n\r\n* fix typo in git documentation (#1106)\r\n\r\n* fix: Update the Chinese translation in lr-scheduler.md (#1136)\r\n\r\n* Update lr-scheduler.md\r\n\r\n* Update chapter_optimization/lr-scheduler.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* fix translation for kaggle-house-price.md (#1107)\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\n\r\n* Update weight-decay.md (#1150)\r\n\r\n* Update weight-decay.md\r\n\r\n关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解\r\n关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。\r\n并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释\r\n解释为何会增加复杂性以及为何需要细粒度工具。\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Fix a spelling error (#1161)\r\n\r\n* Update gru.md (#1152)\r\n\r\nThe key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state.\r\n翻译错误\r\n\r\n* Unify the function naming (#1113)\r\n\r\nUnify naming of the function 'init_xavier()'.\r\n\r\n* Update mlp-concise.md (#1166)\r\n\r\n* Update mlp-concise.md\r\n\r\n语句不通顺\r\n\r\n* Update environment.md\r\n\r\n语序异常\r\n\r\n* Update config.ini\r\n\r\n* fix the imprecise description (#1168)\r\n\r\nCo-authored-by: yuande <yuande>\r\n\r\n* fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175)\r\n\r\n* Fix some typos. (#1163)\r\n\r\n* Update batch-norm.md (#1170)\r\n\r\nfixing typos u->x in article\r\n\r\n* Update linear-regression.md (#1090)\r\n\r\nWe invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that\r\n\r\n原译文把who也直接翻译出来了。\r\n\r\n* Update mlp.md (#1117)\r\n\r\n* Update mlp.md\r\n\r\n修改部分语义表述\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Correct a translation error. (#1091)\r\n\r\n* Correct a translation error.\r\n\r\n* Update chapter_computer-vision/image-augmentation.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update aws.md (#1121)\r\n\r\n* Update aws.md\r\n\r\n* Update chapter_appendix-tools-for-deep-learning/aws.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update image-augmentation.md (#1093)\r\n\r\n* Update anchor.md (#1088)\r\n\r\nfix a minor issue in  code\r\n\r\n* Update anchor.md\r\n\r\n* Update image-augmentation.md\r\n\r\n* fix typo and improve translation in chapter_linear-networks\\softmax-regression.md (#1087)\r\n\r\n* Avoid `torch.meshgrid` user warning (#1174)\r\n\r\nAvoids the following user warning:\r\n```python\r\n~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2228.)\r\n  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\r\n```\r\n\r\n* bump to 2.0.0-beta1\r\n\r\n* Update sequence.md\r\n\r\n* bump beta1 on readme\r\n\r\n* Add latex code block background to config\r\n\r\n* BLD: Bump python support version 3.9 (#1183)\r\n\r\n* BLD: Bump python support version 3.9\r\n\r\n* Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4\r\n\r\n* BLD: Bump torch and tensorflow\r\n\r\n* Update Jenkinsfile\r\n\r\n* Update chapter_installation/index.md\r\n\r\n* Update chapter_installation/index.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update config.ini\r\n\r\n* Update INFO.md\r\n\r\n* Update INFO.md\r\n\r\n* Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187)\r\n\r\n* resolve the conflicts\r\n\r\n* revise from publisher (#1089)\r\n\r\n* revise from publisher\r\n\r\n* d2l api\r\n\r\n* post_latex\r\n\r\n* revise from publisher\r\n\r\n* revise ch11\r\n\r\n* Delete d2l-Copy1.bib\r\n\r\n* clear cache\r\n\r\n* rm d2lbook clear\r\n\r\n* debug anchor\r\n\r\n* keep original d2l doc\r\n\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\n\r\n* 重复语句 (#1188)\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improve expression for chapter_preliminaries/pandas.md (#1184)\r\n\r\n* Update pandas.md\r\n\r\n* Improve expression\r\n\r\n* Improve expression\r\n\r\n* Update chapter_preliminaries/pandas.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improce expression for chapter_preliminaries/linear-algebra.md (#1185)\r\n\r\n* Improce expression\r\n\r\n* Improve code comments\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Fix multibox_detection bugs\r\n\r\n* Update d2l to 0.17.5 version\r\n\r\n* restore older version\r\n\r\n* Upgrade pandas\r\n\r\n* change to python3.8\r\n\r\n* Test warning log\r\n\r\n* relocate  warning log\r\n\r\n* test logs filtering\r\n\r\n* Update gru.md\r\n\r\n* Add DeprecationWarning filter\r\n\r\n* Test warning log\r\n\r\n* Update attention mechanisms & computational performance\r\n\r\n* Update multilayer perceptron& linear & convolution networks & computer vision\r\n\r\n* Update recurrent&optimition&nlp pretraining & nlp applications\r\n\r\n* ignore warnings\r\n\r\n* Update index.md\r\n\r\n* Update linear networks\r\n\r\n* Update multilayer perceptrons&deep learning computation\r\n\r\n* Update preliminaries\r\n\r\n* Check and Add warning filter\r\n\r\n* Update kaggle-cifar10.md\r\n\r\n* Update object-detection-dataset.md\r\n\r\n* Update ssd.md fcn.md\r\n\r\n* Update hybridize.md\r\n\r\n* Update hybridize.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\nCo-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com>\r\nCo-authored-by: Xinwei Liu <xinzone@outlook.com>\r\nCo-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com>\r\nCo-authored-by: gyro永不抽风 <1247006353@qq.com>\r\nCo-authored-by: CanChengZheng <zcc550169544@163.com>\r\nCo-authored-by: linlin <jajupmochi@gmail.com>\r\nCo-authored-by: iuk <liukun0104@gmail.com>\r\nCo-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com>\r\nCo-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com>\r\nCo-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com>\r\nCo-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com>\r\nCo-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com>\r\nCo-authored-by: Ming Liu <akira.liu@njnu.edu.cn>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\nCo-authored-by: silenceZheng66 <13754430639@163.com>\r\nCo-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com>\r\nCo-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com>\r\nCo-authored-by: Krahets <krahets@163.com>\r\nCo-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com>\r\nCo-authored-by: Jameson <miraclecome@gmail.com>\r\nCo-authored-by: P. Yao <12227516+YaoPengCN@users.noreply.github.com>\r\nCo-authored-by: Yulv-git <34329208+Yulv-git@users.noreply.github.com>\r\nCo-authored-by: Liu,Xiao <45966993+liuxiao916@users.noreply.github.com>\r\nCo-authored-by: YIN, Gang <1246410+yingang@users.noreply.github.com>\r\nCo-authored-by: Joe-HZ <58297431+Joe-HZ@users.noreply.github.com>\r\nCo-authored-by: lybloveyou <102609904+lybloveyou@users.noreply.github.com>\r\nCo-authored-by: VigourJiang <jiangfuqiang154@163.com>\r\nCo-authored-by: zxhd863943427 <74853597+zxhd863943427@users.noreply.github.com>\r\nCo-authored-by: LYF <27893441+liyufan@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\nCo-authored-by: xiaotinghe <xiaotih@amazon.com>\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Holly-Max <60691735+Holly-Max@users.noreply.github.com>\r\nCo-authored-by: HinGwenWoong <peterhuang0323@qq.com>\r\nCo-authored-by: Shuai Zhang <cheungdaven@gmail.com>",
        "code": "def load_array(data_arrays, batch_size, is_train=True):\n    \n    dataset = gluon.data.ArrayDataset(*data_arrays)\n    return gluon.data.DataLoader(dataset, batch_size, shuffle=is_train)\n",
        "url": "https://github.com/d2l-ai/d2l-zh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 20,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 38,
        "n_ast_nodes": 59,
        "n_identifiers": 10,
        "d_id": 37377,
        "documentation": {
            "docstring": "Construct a Gluon data iterator.\n\n    Defined in :numref:`sec_linear_concise`",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 221085,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/base64.py",
        "file_name": "base64.py",
        "fun_name": "a85decode",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def a85decode(b, *, foldspaces=False, adobe=False, ignorechars=b' \\t\\n\\r\\v'):\n    \n    b = _bytes_from_decode_data(b)\n    if adobe:\n        if not b.endswith(_A85END):\n            raise ValueError(\n                \"Ascii85 encoded byte sequences must end \"\n                \"with {!r}\".format(_A85END)\n                )\n        if b.startswith(_A85START):\n            b = b[2:-2]  # Strip off start/end markers\n        else:\n            b = b[:-2]\n    #\n    # We have to go through this stepwise, so as to ignore spaces and handle\n    # special short sequences\n    #\n    packI = struct.Struct('!I').pack\n    decoded = []\n    decoded_append = decoded.append\n    curr = []\n    curr_append = curr.append\n    curr_clear = curr.clear\n    for x in b + b'u' * 4:\n        if b'!'[0] <= x <= b'u'[0]:\n            curr_append(x)\n            if len(curr) == 5:\n                acc = 0\n                for x in curr:\n                    acc = 85 * acc + (x - 33)\n                try:\n                    decoded_append(packI(acc))\n                except struct.error:\n                    raise ValueError('Ascii85 overflow') from None\n                curr_clear()\n        elif x == b'z'[0]:\n            if curr:\n                raise ValueError('z inside Ascii85 5-tuple')\n            decoded_append(b'\\0\\0\\0\\0')\n        elif foldspaces and x == b'y'[0]:\n            if curr:\n                raise ValueError('y inside Ascii85 5-tuple')\n            decoded_append(b'\\x20\\x20\\x20\\x20')\n        elif x in ignorechars:\n            # Skip whitespace\n            continue\n        else:\n            raise ValueError('Non-Ascii85 digit found: %c' % x)\n\n    result = b''.join(decoded)\n    padding = 4 - len(curr)\n    if padding:\n        # Throw away the extra padding\n        result = result[:-padding]\n    return result\n\n# The following code is originally taken (with permission) from Mercurial\n\n_b85alphabet = (b\"0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n                b\"abcdefghijklmnopqrstuvwxyz!#$%&()*+-;<=>?@^_`{|}~\")\n_b85chars = None\n_b85chars2 = None\n_b85dec = None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 686,
        "n_words": 212,
        "vocab_size": 138,
        "complexity": 16,
        "nloc": 47,
        "token_counts": 281,
        "n_ast_nodes": 513,
        "n_identifiers": 34,
        "d_id": 56193,
        "documentation": {
            "docstring": "Decode the Ascii85 encoded bytes-like object or ASCII string b.\n\n    foldspaces is a flag that specifies whether the 'y' short sequence should be\n    accepted as shorthand for 4 consecutive spaces (ASCII 0x20). This feature is\n    not supported by the \"standard\" Adobe encoding.\n\n    adobe controls whether the input sequence is in Adobe Ascii85 format (i.e.\n    is framed with <~ and ~>).\n\n    ignorechars should be a byte string containing characters to ignore from the\n    input. This should only contain whitespace characters, and by default\n    contains all whitespace characters in ASCII.\n\n    The result is returned as a bytes object.\n    ",
            "n_words": 96,
            "vocab_size": 71,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 20293,
        "commit_id": "f3166e673fe8d40277b804d35d77dcdb760fc3b3",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/pygments/formatters/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "_load_formatters",
        "commit_message": "check point progress on only bringing in pip==22.0.4 (#4966)\n\n* vendor in pip==22.0.4\r\n\r\n* updating vendor packaging version\r\n\r\n* update pipdeptree to fix pipenv graph with new version of pip.\r\n\r\n* Vendoring of pip-shims 0.7.0\r\n\r\n* Vendoring of requirementslib 1.6.3\r\n\r\n* Update pip index safety restrictions patch for pip==22.0.4\r\n\r\n* Update patches\r\n\r\n* exclude pyptoject.toml from black to see if that helps.\r\n\r\n* Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4",
        "code": "def _load_formatters(module_name):\n    \n    mod = __import__(module_name, None, None, ['__all__'])\n    for formatter_name in mod.__all__:\n        cls = getattr(mod, formatter_name)\n        _formatter_cache[cls.name] = cls\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 19,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 68,
        "n_identifiers": 10,
        "d_id": 3315,
        "documentation": {
            "docstring": "Load a formatter (and all others in the module too).",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 87329,
        "commit_id": "495d45c6547e398a5d4d3c1fa8cb97e69b1751f8",
        "repo": "sentry",
        "path": "tests/sentry/integrations/slack/notifications/test_resolved_in_release.py",
        "file_name": "test_resolved_in_release.py",
        "fun_name": "test_resolved_in_release_performance_issue",
        "commit_message": "ref(slack): Update workflow alerts for perf issues (#40463)\n\nSlack workflow alerts for performance issues are showing a text value of\r\n\"no value\". This PR adds feature parity with error issues for workflow\r\nalerts so that they are shown with the proper data.",
        "code": "def test_resolved_in_release_performance_issue(self, mock_func):\n        \n        event = self.create_performance_issue()\n        notification = ResolvedInReleaseActivityNotification(\n            Activity(\n                project=self.project,\n                group=event.group,\n                user=self.user,\n                type=ActivityType.SET_RESOLVED_IN_RELEASE,\n                data={\"version\": \"meow\"},\n            )\n        )\n        with self.feature(\"organizations:performance-issues\"), self.tasks():\n            notification.send()\n\n        attachment, text = get_attachment()\n        release_name = notification.activity.data[\"version\"]\n        assert text == f\"Issue marked as resolved in {release_name} by {self.name}\"\n        assert attachment[\"title\"] == \"N+1 Query\"\n        assert (\n            attachment[\"text\"]\n            == \"db - SELECT `books_author`.`id`, `books_author`.`name` FROM `books_author` WHERE `books_author`.`id` = %s LIMIT 21\"\n        )\n        assert (\n            attachment[\"footer\"]\n            == f\"{self.project.slug} | production | <http://testserver/settings/account/notifications/workflow/?referrer=resolved_in_release_activity-slack-user|Notification Settings>\"\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 317,
        "n_words": 74,
        "vocab_size": 58,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 122,
        "n_ast_nodes": 230,
        "n_identifiers": 25,
        "d_id": 18284,
        "documentation": {
            "docstring": "\n        Test that a Slack message is sent with the expected payload when a performance issue is resolved in a release\n        ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 108023,
        "commit_id": "13147992b317c29c6e832ca7f6d05bf48aeb0718",
        "repo": "matplotlib",
        "path": "lib/matplotlib/texmanager.py",
        "file_name": "texmanager.py",
        "fun_name": "make_png",
        "commit_message": "Move towards making texmanager stateless.\n\nPreviously, TexManager needed to call get_font_config at a specific\nplace in the middle of processing to update some internal attributes\nbefore proceeding with TeX source generation.  Instead, move towards\nmaking TexManager stateless (except for caching), i.e. the user facing\nAPI should be thought of as a bunch of independently callable functions\n`make_tex()`, `make_dvi()`, etc. (they will probably stay as methods on\na \"empty\" TexManager object for a long time for backcompat, in fact).",
        "code": "def make_png(cls, tex, fontsize, dpi):\n        \n        basefile = cls.get_basefile(tex, fontsize, dpi)\n        pngfile = '%s.png' % basefile\n        # see get_rgba for a discussion of the background\n        if not os.path.exists(pngfile):\n            dvifile = cls.make_dvi(tex, fontsize)\n            cmd = [\"dvipng\", \"-bg\", \"Transparent\", \"-D\", str(dpi),\n                   \"-T\", \"tight\", \"-o\", pngfile, dvifile]\n            # When testing, disable FreeType rendering for reproducibility; but\n            # dvipng 1.16 has a bug (fixed in f3ff241) that breaks --freetype0\n            # mode, so for it we keep FreeType enabled; the image will be\n            # slightly off.\n            if (getattr(mpl, \"_called_from_pytest\", False) and\n                    mpl._get_executable_info(\"dvipng\").raw_version != \"1.16\"):\n                cmd.insert(1, \"--freetype0\")\n            cls._run_checked_subprocess(cmd, tex)\n        return pngfile\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 276,
        "n_words": 94,
        "vocab_size": 78,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 117,
        "n_ast_nodes": 198,
        "n_identifiers": 21,
        "d_id": 23022,
        "documentation": {
            "docstring": "\n        Generate a png file containing latex's rendering of tex string.\n\n        Return the file name.\n        ",
            "n_words": 14,
            "vocab_size": 13,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 62036,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/locators.py",
        "file_name": "locators.py",
        "fun_name": "_wait_threads",
        "commit_message": "upd; format",
        "code": "def _wait_threads(self):\n        \n        # Note that you need two loops, since you can't say which\n        # thread will get each sentinel\n        for t in self._threads:\n            self._to_fetch.put(None)    # sentinel\n        for t in self._threads:\n            t.join()\n        self._threads = []\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 102,
        "n_words": 35,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 39,
        "n_ast_nodes": 68,
        "n_identifiers": 7,
        "d_id": 12843,
        "documentation": {
            "docstring": "\n        Tell all the threads to terminate (by sending a sentinel value) and\n        wait for them to do so.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 116090,
        "commit_id": "3d8422b16d8ad72005ffed2f7869eefe0b330c35",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/monetdb_handler/utils/monet_get_id.py",
        "file_name": "monet_get_id.py",
        "fun_name": "table_id",
        "commit_message": "utils used for getting schema_id and table_id",
        "code": "def table_id(connection, table_name, schema_name=None):\n    \n\n    schema_idm = schema_id(connection=connection,schema_name=schema_name)\n\n    q = f\n    \n    cur = connection.cursor()\n    cur.execute(q)\n\n    try:\n        table_id = cur.fetchall()[0][0] \n    except:\n        raise exc.NoSuchTableError(table_name)\n\n    \n\n    return table_id\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 70,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 67,
        "n_ast_nodes": 117,
        "n_identifiers": 13,
        "d_id": 25664,
        "documentation": {
            "docstring": "Fetch the id for schema.table_name, defaulting to current schema if\n       schema is None\n    \n        SELECT id\n        FROM sys.tables\n        WHERE name = '{table_name}'\n        AND schema_id = {schema_idm}\n        ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 70,
            "language": "en"
        }
    },
    {
        "id": 12995,
        "commit_id": "273fda5a86da0d6bf48f423fa50700e828b40be6",
        "repo": "jina",
        "path": "jina/clients/mixin.py",
        "file_name": "mixin.py",
        "fun_name": "is_flow_ready",
        "commit_message": "refactor: merge dryrun into ping (#5151)\n\n* refactor: merge dryrun into ping\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* refactor: merge dryrun into ping\r\n\r\n* refactor: merge dryrun into ping\r\n\r\n* refactor: merge dryrun into ping\r\n\r\n* refactor: merge dryrun into ping\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>",
        "code": "def is_flow_ready(self, **kwargs) -> bool:\n        \n        return run_async(self.client._is_flow_ready, **kwargs)\n\n    dry_run = deprecate_by(is_flow_ready)\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 28,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 23,
        "n_ast_nodes": 48,
        "n_identifiers": 9,
        "d_id": 2490,
        "documentation": {
            "docstring": "Check if the Flow is ready to receive requests\n\n        :param kwargs: potential kwargs received passed from the public interface\n        :return: boolean indicating the health/readiness of the Flow\n        ",
            "n_words": 27,
            "vocab_size": 23,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 12696,
        "commit_id": "c3849c6fee4a65a77a82b2cfda9670d727ff0f53",
        "repo": "jina",
        "path": "jina/types/request/data.py",
        "file_name": "data.py",
        "fun_name": "is_decompressed_wo_data",
        "commit_message": "feat: allow to access parameters of data request wo loading data  (#4991)",
        "code": "def is_decompressed_wo_data(self) -> bool:\n        \n        return type(self._pb_body) is jina_pb2.DataRequestProtoWoData\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 19,
        "n_ast_nodes": 33,
        "n_identifiers": 7,
        "d_id": 2382,
        "documentation": {
            "docstring": "\n        Checks if the underlying proto object was already deserialized into a :class:`jina.proto.jina_pb2.DataRequestProtoWoData`. It means that the proto is loaded without the data ( docs ).\n\n        :return: True if the proto was deserialized before into a DataRequest without docs\n        ",
            "n_words": 38,
            "vocab_size": 26,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 279734,
        "commit_id": "00524152437b957ca4e850a5db014e223d3c6826",
        "repo": "keras",
        "path": "keras/engine/base_layer.py",
        "file_name": "base_layer.py",
        "fun_name": "_update_trackables",
        "commit_message": "isort, black and flake8 checked",
        "code": "def _update_trackables(self):\n        \n        for trackable_obj in self._self_tracked_trackables:\n            if isinstance(\n                trackable_obj, tf.__internal__.tracking.TrackableDataStructure\n            ):\n                self._track_variables(trackable_obj)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 78,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 33,
        "n_ast_nodes": 54,
        "n_identifiers": 10,
        "d_id": 83115,
        "documentation": {
            "docstring": "Track variables added to lists/dicts after creation",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 189675,
        "commit_id": "e040bcacd38378386749db18aeba575b93f4ebca",
        "repo": "manim",
        "path": "manim/mobject/geometry/arc.py",
        "file_name": "arc.py",
        "fun_name": "get_unpositioned_tip",
        "commit_message": "Improved structure of the :mod:`.mobject` module (#2476)\n\n* group graphing and update its references\r\n\r\n* group text and update its references\r\n\r\n* group opengl and update its references\r\n\r\n* group three_d and update its references\r\n\r\n* group geometry and update (most) references\r\n\r\n* move some chaning.py + updater files  into animation\r\n\r\n* refactor arc.py\r\n\r\n* refactor line.py\r\n\r\n* refactor polygram.py\r\n\r\n* refactor tips.py\r\n\r\n* black + isort\r\n\r\n* import new files in __init__.py\r\n\r\n* refactor places where geometry was used\r\n\r\n* black + isort again\r\n\r\n* remove unused imports\r\n\r\n* update reference.rst\r\n\r\n* add descriptions to files\r\n\r\n* fix circular imports\r\n\r\n* forgot ArrowTip\r\n\r\n* fix tests\r\n\r\n* fix doctests\r\n\r\n* satisfy mypy?\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix ALL merge conflicts\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* one VMobject import slipped through\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* re-add imports to `manim/opengl/__init__.py`\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* fix reference manual\r\n\r\n* [pre-commit.ci] auto fixes from pre-commit.com hooks\r\n\r\nfor more information, see https://pre-commit.ci\r\n\r\n* ignore unknown directive type\r\n\r\n* fix arrow tip imports in docstrings\r\n\r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>\r\nCo-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>",
        "code": "def get_unpositioned_tip(self, tip_shape=None, tip_length=None):\n        \n        from manim.mobject.geometry.tips import ArrowTriangleFilledTip\n\n        if tip_shape is None:\n            tip_shape = ArrowTriangleFilledTip\n        if tip_length is None:\n            tip_length = self.get_default_tip_length()\n        color = self.get_color()\n        style = {\"fill_color\": color, \"stroke_color\": color}\n        style.update(self.tip_style)\n        tip = tip_shape(length=tip_length, **style)\n        return tip\n",
        "url": "https://github.com/ManimCommunity/manim.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 123,
        "n_words": 38,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 83,
        "n_ast_nodes": 134,
        "n_identifiers": 17,
        "d_id": 46162,
        "documentation": {
            "docstring": "\n        Returns a tip that has been stylistically configured,\n        but has not yet been given a position in space.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 258737,
        "commit_id": "5f75acdd12d77b973471961ad716367c6199d01c",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/_logistic.py",
        "file_name": "_logistic.py",
        "fun_name": "fit",
        "commit_message": "MNT Bump joblib version dependency to 1.0.0 (#22365)",
        "code": "def fit(self, X, y, sample_weight=None):\n        \n        solver = _check_solver(self.solver, self.penalty, self.dual)\n\n        if not isinstance(self.C, numbers.Number) or self.C < 0:\n            raise ValueError(\"Penalty term must be positive; got (C=%r)\" % self.C)\n        if self.penalty == \"elasticnet\":\n            if (\n                not isinstance(self.l1_ratio, numbers.Number)\n                or self.l1_ratio < 0\n                or self.l1_ratio > 1\n            ):\n                raise ValueError(\n                    \"l1_ratio must be between 0 and 1; got (l1_ratio=%r)\"\n                    % self.l1_ratio\n                )\n        elif self.l1_ratio is not None:\n            warnings.warn(\n                \"l1_ratio parameter is only used when penalty is \"\n                \"'elasticnet'. Got \"\n                \"(penalty={})\".format(self.penalty)\n            )\n        if self.penalty == \"none\":\n            if self.C != 1.0:  # default values\n                warnings.warn(\n                    \"Setting penalty='none' will ignore the C and l1_ratio parameters\"\n                )\n                # Note that check for l1_ratio is done right above\n            C_ = np.inf\n            penalty = \"l2\"\n        else:\n            C_ = self.C\n            penalty = self.penalty\n        if not isinstance(self.max_iter, numbers.Number) or self.max_iter < 0:\n            raise ValueError(\n                \"Maximum number of iteration must be positive; got (max_iter=%r)\"\n                % self.max_iter\n            )\n        if not isinstance(self.tol, numbers.Number) or self.tol < 0:\n            raise ValueError(\n                \"Tolerance for stopping criteria must be positive; got (tol=%r)\"\n                % self.tol\n            )\n\n        if solver == \"lbfgs\":\n            _dtype = np.float64\n        else:\n            _dtype = [np.float64, np.float32]\n\n        X, y = self._validate_data(\n            X,\n            y,\n            accept_sparse=\"csr\",\n            dtype=_dtype,\n            order=\"C\",\n            accept_large_sparse=solver not in [\"liblinear\", \"sag\", \"saga\"],\n        )\n        check_classification_targets(y)\n        self.classes_ = np.unique(y)\n\n        multi_class = _check_multi_class(self.multi_class, solver, len(self.classes_))\n\n        if solver == \"liblinear\":\n            if effective_n_jobs(self.n_jobs) != 1:\n                warnings.warn(\n                    \"'n_jobs' > 1 does not have any effect when\"\n                    \" 'solver' is set to 'liblinear'. Got 'n_jobs'\"\n                    \" = {}.\".format(effective_n_jobs(self.n_jobs))\n                )\n            self.coef_, self.intercept_, n_iter_ = _fit_liblinear(\n                X,\n                y,\n                self.C,\n                self.fit_intercept,\n                self.intercept_scaling,\n                self.class_weight,\n                self.penalty,\n                self.dual,\n                self.verbose,\n                self.max_iter,\n                self.tol,\n                self.random_state,\n                sample_weight=sample_weight,\n            )\n            self.n_iter_ = np.array([n_iter_])\n            return self\n\n        if solver in [\"sag\", \"saga\"]:\n            max_squared_sum = row_norms(X, squared=True).max()\n        else:\n            max_squared_sum = None\n\n        n_classes = len(self.classes_)\n        classes_ = self.classes_\n        if n_classes < 2:\n            raise ValueError(\n                \"This solver needs samples of at least 2 classes\"\n                \" in the data, but the data contains only one\"\n                \" class: %r\"\n                % classes_[0]\n            )\n\n        if len(self.classes_) == 2:\n            n_classes = 1\n            classes_ = classes_[1:]\n\n        if self.warm_start:\n            warm_start_coef = getattr(self, \"coef_\", None)\n        else:\n            warm_start_coef = None\n        if warm_start_coef is not None and self.fit_intercept:\n            warm_start_coef = np.append(\n                warm_start_coef, self.intercept_[:, np.newaxis], axis=1\n            )\n\n        # Hack so that we iterate only once for the multinomial case.\n        if multi_class == \"multinomial\":\n            classes_ = [None]\n            warm_start_coef = [warm_start_coef]\n        if warm_start_coef is None:\n            warm_start_coef = [None] * n_classes\n\n        path_func = delayed(_logistic_regression_path)\n\n        # The SAG solver releases the GIL so it's more efficient to use\n        # threads for this solver.\n        if solver in [\"sag\", \"saga\"]:\n            prefer = \"threads\"\n        else:\n            prefer = \"processes\"\n        fold_coefs_ = Parallel(n_jobs=self.n_jobs, verbose=self.verbose, prefer=prefer)(\n            path_func(\n                X,\n                y,\n                pos_class=class_,\n                Cs=[C_],\n                l1_ratio=self.l1_ratio,\n                fit_intercept=self.fit_intercept,\n                tol=self.tol,\n                verbose=self.verbose,\n                solver=solver,\n                multi_class=multi_class,\n                max_iter=self.max_iter,\n                class_weight=self.class_weight,\n                check_input=False,\n                random_state=self.random_state,\n                coef=warm_start_coef_,\n                penalty=penalty,\n                max_squared_sum=max_squared_sum,\n                sample_weight=sample_weight,\n            )\n            for class_, warm_start_coef_ in zip(classes_, warm_start_coef)\n        )\n\n        fold_coefs_, _, n_iter_ = zip(*fold_coefs_)\n        self.n_iter_ = np.asarray(n_iter_, dtype=np.int32)[:, 0]\n\n        n_features = X.shape[1]\n        if multi_class == \"multinomial\":\n            self.coef_ = fold_coefs_[0][0]\n        else:\n            self.coef_ = np.asarray(fold_coefs_)\n            self.coef_ = self.coef_.reshape(\n                n_classes, n_features + int(self.fit_intercept)\n            )\n\n        if self.fit_intercept:\n            self.intercept_ = self.coef_[:, -1]\n            self.coef_ = self.coef_[:, :-1]\n        else:\n            self.intercept_ = np.zeros(n_classes)\n\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 2295,
        "n_words": 490,
        "vocab_size": 258,
        "complexity": 29,
        "nloc": 152,
        "token_counts": 858,
        "n_ast_nodes": 1352,
        "n_identifiers": 81,
        "d_id": 75396,
        "documentation": {
            "docstring": "\n        Fit the model according to the given training data.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix} of shape (n_samples, n_features)\n            Training vector, where `n_samples` is the number of samples and\n            `n_features` is the number of features.\n\n        y : array-like of shape (n_samples,)\n            Target vector relative to X.\n\n        sample_weight : array-like of shape (n_samples,) default=None\n            Array of weights that are assigned to individual samples.\n            If not provided, then each sample is given unit weight.\n\n            .. versionadded:: 0.17\n               *sample_weight* support to LogisticRegression.\n\n        Returns\n        -------\n        self\n            Fitted estimator.\n\n        Notes\n        -----\n        The SAGA solver supports both float64 and float32 bit arrays.\n        ",
            "n_words": 97,
            "vocab_size": 75,
            "n_whitespaces": 280,
            "language": "en"
        }
    },
    {
        "id": 258161,
        "commit_id": "255072d8d548a19a1678ddc46b41d41cf5d09bc4",
        "repo": "haystack",
        "path": "test/document_stores/test_deepsetcloud.py",
        "file_name": "test_deepsetcloud.py",
        "fun_name": "ds",
        "commit_message": "refactor: move dC tests to their own module and job (#3529)\n\n* move dC tests to their own module and job\r\n\r\n* restore global var\r\n\r\n* revert",
        "code": "def ds(self):\n        \n        return DeepsetCloudDocumentStore(api_endpoint=DC_API_ENDPOINT, api_key=DC_API_KEY, index=DC_TEST_INDEX)\n\n    # Integration tests\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 26,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 21,
        "n_ast_nodes": 35,
        "n_identifiers": 9,
        "d_id": 75193,
        "documentation": {
            "docstring": "\n        We make this fixture depend on `dc_api_mock` so that passing the document store will\n        activate the mocking and we spare one function parameter.\n        ",
            "n_words": 23,
            "vocab_size": 22,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 322613,
        "commit_id": "1e2ee01dade0d4076ba98aa613c3eb150c615abb",
        "repo": "PaddleNLP",
        "path": "paddlenlp/taskflow/text_correction.py",
        "file_name": "text_correction.py",
        "fun_name": "_postprocess",
        "commit_message": "Update Taskflow word_segmentation and ner tasks (#1666)\n\n* Add AutoSplitter & AutoJoiner\r\n\r\n* codestyle fix\r\n\r\n* unify auto joiner\r\n\r\n* add comments\r\n\r\n* add sentence split mode\r\n\r\n* update params\r\n\r\n* add paddle version check\r\n\r\n* add wordtag for word_segmentation\r\n\r\n* add wordtag for word_segmentation\r\n\r\n* add ner-lac and word_segmentation-jieba\r\n\r\n* add return entities only for ner\r\n\r\n* fix ci\r\n\r\n* fix ci\r\n\r\n* fix ci\r\n\r\n* fix ci\r\n\r\n* fix ci\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* Update README.md\r\n\r\n* fix bugs of dataloader\r\n\r\n* remove guard\r\n\r\n* use fast mode for rnn example\r\n\r\n* Update README.md\r\n\r\n* Update README.md",
        "code": "def _postprocess(self, inputs):\n        \n        results = []\n\n        for examples, texts, temp_results in zip(inputs['batch_examples'],\n                                                 inputs['batch_texts'],\n                                                 inputs['batch_results']):\n            for i in range(len(examples)):\n                result = {}\n                det_pred, char_preds, length = temp_results[i]\n                pred_result = self._parse_decode(texts[i], char_preds, det_pred,\n                                                 length)\n                result['source'] = texts[i]\n                result['target'] = ''.join(pred_result)\n                results.append(result)\n        results = self._auto_joiner(results, self.input_mapping, is_dict=True)\n        for result in results:\n            errors_result = []\n            for i, (source_token, target_token\n                    ) in enumerate(zip(result['source'], result['target'])):\n                if source_token != target_token:\n                    errors_result.append({\n                        'position': i,\n                        'correction': {\n                            source_token: target_token\n                        }\n                    })\n            result['errors'] = errors_result\n        return results\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 565,
        "n_words": 77,
        "vocab_size": 54,
        "complexity": 6,
        "nloc": 27,
        "token_counts": 186,
        "n_ast_nodes": 297,
        "n_identifiers": 26,
        "d_id": 118205,
        "documentation": {
            "docstring": "\n        The model output is the logits and probs, this function will convert the model output to raw text.\n        ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 205927,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/forms/boundfield.py",
        "file_name": "boundfield.py",
        "fun_name": "label_tag",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def label_tag(self, contents=None, attrs=None, label_suffix=None, tag=None):\n        \n        contents = contents or self.label\n        if label_suffix is None:\n            label_suffix = (\n                self.field.label_suffix\n                if self.field.label_suffix is not None\n                else self.form.label_suffix\n            )\n        # Only add the suffix if the label does not end in punctuation.\n        # Translators: If found as last label character, these punctuation\n        # characters will prevent the default label_suffix to be appended to the label\n        if label_suffix and contents and contents[-1] not in _(\":?.!\"):\n            contents = format_html(\"{}{}\", contents, label_suffix)\n        widget = self.field.widget\n        id_ = widget.attrs.get(\"id\") or self.auto_id\n        if id_:\n            id_for_label = widget.id_for_label(id_)\n            if id_for_label:\n                attrs = {**(attrs or {}), \"for\": id_for_label}\n            if self.field.required and hasattr(self.form, \"required_css_class\"):\n                attrs = attrs or {}\n                if \"class\" in attrs:\n                    attrs[\"class\"] += \" \" + self.form.required_css_class\n                else:\n                    attrs[\"class\"] = self.form.required_css_class\n        context = {\n            \"field\": self,\n            \"label\": contents,\n            \"attrs\": attrs,\n            \"use_tag\": bool(id_),\n            \"tag\": tag or \"label\",\n        }\n        return self.form.render(self.form.template_name_label, context)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 497,
        "n_words": 142,
        "vocab_size": 94,
        "complexity": 16,
        "nloc": 30,
        "token_counts": 230,
        "n_ast_nodes": 380,
        "n_identifiers": 23,
        "d_id": 51286,
        "documentation": {
            "docstring": "\n        Wrap the given contents in a <label>, if the field has an ID attribute.\n        contents should be mark_safe'd to avoid HTML escaping. If contents\n        aren't given, use the field's HTML-escaped label.\n\n        If attrs are given, use them as HTML attributes on the <label> tag.\n\n        label_suffix overrides the form's label_suffix.\n        ",
            "n_words": 49,
            "vocab_size": 39,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 244027,
        "commit_id": "cac356380d505bf15587f07c0529218cc36b9652",
        "repo": "mmdetection",
        "path": "mmdet/core/bbox/match_costs/match_cost.py",
        "file_name": "match_cost.py",
        "fun_name": "__call__",
        "commit_message": "[Feature] Add Maskformer to mmdet (#7212)\n\n* first commit\r\n\r\n* add README\r\n\r\n* move model description from config to readme\r\n\r\nadd description for binary_input\r\n\r\nadd description for dice loss\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nadd a independent panoptic gt processing function\r\n\r\nremove compatibility of pretrain in maskformer\r\n\r\n* update comments in maskformer_head\r\n\r\n* update docs format",
        "code": "def __call__(self, bbox_pred, gt_bboxes):\n        \n        if self.box_format == 'xywh':\n            gt_bboxes = bbox_xyxy_to_cxcywh(gt_bboxes)\n        elif self.box_format == 'xyxy':\n            bbox_pred = bbox_cxcywh_to_xyxy(bbox_pred)\n        bbox_cost = torch.cdist(bbox_pred, gt_bboxes, p=1)\n        return bbox_cost * self.weight\n\n\n@MATCH_COST.register_module()",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "@MATCH_COST.register_module()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 84,
        "n_words": 28,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 56,
        "n_ast_nodes": 103,
        "n_identifiers": 14,
        "d_id": 70199,
        "documentation": {
            "docstring": "\n        Args:\n            bbox_pred (Tensor): Predicted boxes with normalized coordinates\n                (cx, cy, w, h), which are all in range [0, 1]. Shape\n                (num_query, 4).\n            gt_bboxes (Tensor): Ground truth boxes with normalized\n                coordinates (x1, y1, x2, y2). Shape (num_gt, 4).\n\n        Returns:\n            torch.Tensor: bbox_cost value with weight\n        ",
            "n_words": 43,
            "vocab_size": 35,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 206164,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/shortcuts.py",
        "file_name": "shortcuts.py",
        "fun_name": "_get_queryset",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _get_queryset(klass):\n    \n    # If it is a model class or anything else with ._default_manager\n    if hasattr(klass, \"_default_manager\"):\n        return klass._default_manager.all()\n    return klass\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 24,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 51389,
        "documentation": {
            "docstring": "\n    Return a QuerySet or a Manager.\n    Duck typing in action: any class with a `get()` method (for\n    get_object_or_404) or a `filter()` method (for get_list_or_404) might do\n    the job.\n    ",
            "n_words": 28,
            "vocab_size": 22,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 19198,
        "commit_id": "847eb6b22d03f0cffef945996cf835272870435a",
        "repo": "mlflow",
        "path": "mlflow/sklearn/utils.py",
        "file_name": "utils.py",
        "fun_name": "_get_classifier_artifacts",
        "commit_message": "Improve confusion matrix plot (#5273)\n\n* update\r\n\r\nSigned-off-by: Weichen Xu <weichen.xu@databricks.com>\r\n\r\n* fix\r\n\r\nSigned-off-by: Weichen Xu <weichen.xu@databricks.com>\r\n\r\n* update\r\n\r\nSigned-off-by: Weichen Xu <weichen.xu@databricks.com>",
        "code": "def _get_classifier_artifacts(fitted_estimator, prefix, X, y_true, sample_weight):\n    \n    import sklearn\n\n    if not _is_plotting_supported():\n        return []\n",
        "url": "https://github.com/mlflow/mlflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 29,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 3,
        "nloc": 48,
        "token_counts": 187,
        "n_ast_nodes": 41,
        "n_identifiers": 8,
        "d_id": 2909,
        "documentation": {
            "docstring": "\n    Draw and record various common artifacts for classifier\n\n    For all classifiers, we always log:\n    (1) confusion matrix:\n    https://scikit-learn.org/stable/modules/generated/sklearn.metrics.plot_confusion_matrix.html\n\n    For only binary classifiers, we will log:\n    (2) precision recall curve:\n    https://scikit-learn.org/stable/modules/generated/sklearn.metrics.plot_precision_recall_curve.html\n    (3) roc curve:\n    https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html\n\n    Steps:\n    1. Extract X and y_true from fit_args and fit_kwargs, and split into train & test datasets.\n    2. If the sample_weight argument exists in fit_func (accuracy_score by default\n    has sample_weight), extract it from fit_args or fit_kwargs as\n    (y_true, y_pred, sample_weight, multioutput), otherwise as (y_true, y_pred, multioutput)\n    3. return a list of artifacts path to be logged\n\n    :param fitted_estimator: The already fitted regressor\n    :param fit_args: Positional arguments given to fit_func.\n    :param fit_kwargs: Keyword arguments given to fit_func.\n    :return: List of artifacts to be logged\n    ",
            "n_words": 117,
            "vocab_size": 91,
            "n_whitespaces": 178,
            "language": "en"
        }
    },
    {
        "id": 289350,
        "commit_id": "31a787558fd312331b55e5c2c4b33341fc3601fc",
        "repo": "core",
        "path": "tests/components/demo/test_init.py",
        "file_name": "test_init.py",
        "fun_name": "mock_device_tracker_update_config",
        "commit_message": "Ensure recorder test fixture is setup before hass fixture (#80528)\n\n* Ensure recorder test fixture is setup before hass fixture\r\n\r\n* Adjust more tests",
        "code": "def mock_device_tracker_update_config():\n    \n    with patch(\"homeassistant.components.device_tracker.legacy.update_config\"):\n        yield\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 18,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 12,
        "n_ast_nodes": 29,
        "n_identifiers": 2,
        "d_id": 88492,
        "documentation": {
            "docstring": "Prevent device tracker from creating known devices file.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 196513,
        "commit_id": "e8c5f4fe692e863bf0a48573a1d0c7b92487c5c1",
        "repo": "sympy",
        "path": "sympy/algebras/quaternion.py",
        "file_name": "quaternion.py",
        "fun_name": "coplanar",
        "commit_message": "hamilton",
        "code": "def coplanar(self, other):\n        \n\n        aq = self.axis()\n        ar = other.axis()\n        return (aq == ar or aq == -ar)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 45,
        "n_words": 17,
        "vocab_size": 13,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 33,
        "n_ast_nodes": 56,
        "n_identifiers": 6,
        "d_id": 47953,
        "documentation": {
            "docstring": "\n        Returns if the two quaternions are coplanar or not.\n\n        Parameters\n        ==========\n\n        other : a quaternion\n\n        Examples\n        ========\n\n        >>> from sympy.algebras.quaternion import Quaternion\n        >>> q = Quaternion(1, 4, 4, 4)\n        >>> q1 = Quaternion(2, 8, 8, 8)\n        >>> q.coplanar(q1)\n        True\n\n        >>> q1 = Quaternion(2, 8, 13, 12)\n        >>> q.coplanar(q1)\n        False\n\n        ",
            "n_words": 49,
            "vocab_size": 36,
            "n_whitespaces": 155,
            "language": "en"
        }
    },
    {
        "id": 209767,
        "commit_id": "2001f35c7a9762d2d58f5ec402d93d10bbfd8e10",
        "repo": "scapy",
        "path": "scapy/layers/tls/extensions.py",
        "file_name": "extensions.py",
        "fun_name": "_TLS_Ext_CertTypeDispatcher",
        "commit_message": "Fix spellcheck",
        "code": "def _TLS_Ext_CertTypeDispatcher(m, *args, **kargs):\n    \n    tmp_len = struct.unpack(\"!H\", m[2:4])[0]\n    if tmp_len == 1:\n        cls = TLS_Ext_ServerCertType\n    else:\n        cls = TLS_Ext_ClientCertType\n    return cls(m, *args, **kargs)\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 52,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 54,
        "n_ast_nodes": 87,
        "n_identifiers": 10,
        "d_id": 52772,
        "documentation": {
            "docstring": "\n    We need to select the correct one on dissection. We use the length for\n    that, as 1 for client version would imply an empty list.\n    ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 35671,
        "commit_id": "df5a4094a6e3f98f2cb2058cdb688fcc3f453220",
        "repo": "transformers",
        "path": "src/transformers/models/data2vec/modeling_data2vec_audio.py",
        "file_name": "modeling_data2vec_audio.py",
        "fun_name": "_set_gradient_checkpointing",
        "commit_message": "Add Data2Vec (#15507)\n\n* Add data2vec model cloned from roberta\r\n\r\n* Add checkpoint conversion script\r\n\r\n* Fix copies\r\n\r\n* Update docs\r\n\r\n* Add checkpoint conversion script\r\n\r\n* Remove fairseq data2vec_text script and fix format\r\n\r\n* Add comment on where to get data2vec_text.py\r\n\r\n* Remove mock implementation cheat.py and fix style\r\n\r\n* Fix copies\r\n\r\n* Remove TF and Flax classes from init\r\n\r\n* Add back copy from fairseq data2vec_text.py and fix style\r\n\r\n* Update model name in docs/source/index.mdx to be CamelCase\r\n\r\n* Revert model name in table to lower-case to get check_table test to pass\r\n\r\n* Update src/transformers/models/data2vec/__init__.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/convert_data2vec_original_pytorch_checkpoint_to_pytorch.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update docs/source/model_doc/data2vec.mdx\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update docs/source/model_doc/data2vec.mdx\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/auto/configuration_auto.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/configuration_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update tests/test_modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/configuration_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update documentation\r\n\r\n* Copy-paste Data2VecConfig from BertConfig\r\n\r\n* Update config checkpoint to point to edugp/data2vec-nlp-base. Fix style and repo-consistency\r\n\r\n* Update config special tokens to match RoBERTa\r\n\r\n* Split multiple assertions and add individual error messages\r\n\r\n* Rename Data2VecModel to Data2VecForTextModel\r\n\r\n* Add Data2Vec to _toctree.yml\r\n\r\n* Rename Data2VecEmbeddings to Data2VecForTextEmbeddings\r\n\r\n* Add initial Data2VecForAudio model (unfinished). Only matching fairseq's implementation up to the feature encoder (before positional encoding).\r\n\r\n* finish audio model\r\n\r\n* finish audio file\r\n\r\n* Update names and fix style, quality and repo consistency\r\n\r\n* Remove Data2VecAudioForPretraining. Add tests for Data2VecAudio, mimicking the Wav2Vec2 test suite. Fix bias initilization in positional conv layers. Move back configurations for audio and text to separate files.\r\n\r\n* add inputs to logits to data2vec'\r\n\r\n* correct autio models\r\n\r\n* correct config auto\r\n\r\n* correct tok auto\r\n\r\n* Update utils/tests_fetcher.py\r\n\r\n* delete unnecessary files\r\n\r\n* delete unnecessary files\r\n\r\n* further renaming\r\n\r\n* make all tests pass\r\n\r\n* finish\r\n\r\n* remove useless test file\r\n\r\n* Update tests/test_modeling_common.py\r\n\r\n* Update utils/check_repo.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec_text.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Fix copies\r\n\r\n* Update docs\r\n\r\n* Remove fairseq data2vec_text script and fix format\r\n\r\n* Add comment on where to get data2vec_text.py\r\n\r\n* Remove mock implementation cheat.py and fix style\r\n\r\n* Fix copies\r\n\r\n* Remove TF and Flax classes from init\r\n\r\n* Add back copy from fairseq data2vec_text.py and fix style\r\n\r\n* Update model name in docs/source/index.mdx to be CamelCase\r\n\r\n* Revert model name in table to lower-case to get check_table test to pass\r\n\r\n* Update documentation\r\n\r\n* Update src/transformers/models/data2vec/__init__.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/convert_data2vec_original_pytorch_checkpoint_to_pytorch.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/auto/configuration_auto.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/configuration_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update tests/test_modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/configuration_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Copy-paste Data2VecConfig from BertConfig\r\n\r\n* Update config checkpoint to point to edugp/data2vec-nlp-base. Fix style and repo-consistency\r\n\r\n* Update config special tokens to match RoBERTa\r\n\r\n* Split multiple assertions and add individual error messages\r\n\r\n* Rename Data2VecModel to Data2VecForTextModel\r\n\r\n* Add Data2Vec to _toctree.yml\r\n\r\n* Rename Data2VecEmbeddings to Data2VecForTextEmbeddings\r\n\r\n* Add initial Data2VecForAudio model (unfinished). Only matching fairseq's implementation up to the feature encoder (before positional encoding).\r\n\r\n* finish audio model\r\n\r\n* finish audio file\r\n\r\n* add inputs to logits to data2vec'\r\n\r\n* Update names and fix style, quality and repo consistency\r\n\r\n* Remove Data2VecAudioForPretraining. Add tests for Data2VecAudio, mimicking the Wav2Vec2 test suite. Fix bias initilization in positional conv layers. Move back configurations for audio and text to separate files.\r\n\r\n* correct autio models\r\n\r\n* correct config auto\r\n\r\n* correct tok auto\r\n\r\n* delete unnecessary files\r\n\r\n* delete unnecessary files\r\n\r\n* Update utils/tests_fetcher.py\r\n\r\n* further renaming\r\n\r\n* make all tests pass\r\n\r\n* finish\r\n\r\n* remove useless test file\r\n\r\n* Update tests/test_modeling_common.py\r\n\r\n* Update utils/check_repo.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Update src/transformers/models/data2vec/modeling_data2vec_text.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\n\r\n* Move data2vec tests to new structure\r\n\r\n* Fix test imports for text tests\r\n\r\n* Remove fairseq files\r\n\r\n* Change paper link to arxiv\r\n\r\n* Modify Data2Vec documentation to reflect that the encoder is not shared across the audio and text models in the current implementation.\r\n\r\n* Update text model checkpoint to be facebook/data2vec-text-base\r\n\r\n* Add 'Copy from' statements and update paper links and docs\r\n\r\n* fix copy from statements\r\n\r\n* improve copied from\r\n\r\n* correct more copied from statements\r\n\r\n* finish copied from stuff\r\n\r\n* make style\r\n\r\n* add model to README\r\n\r\n* add to master\r\n\r\nCo-authored-by: Eduardo Gonzalez Ponferrada <eduardo@ferrumhealth.com>\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def _set_gradient_checkpointing(self, module, value=False):\n        if isinstance(module, (Data2VecAudioEncoder, Data2VecAudioFeatureEncoder)):\n            module.gradient_checkpointing = value\n\n\nDATA2VEC_AUDIO_START_DOCSTRING = r\n\n\nDATA2VEC_AUDIO_INPUTS_DOCSTRING = r\n\n\n@add_start_docstrings(\n    \"The bare Data2VecAudio Model transformer outputting raw hidden-states without any specific head on top.\",\n    DATA2VEC_AUDIO_START_DOCSTRING,\n)",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "@add_start_docstrings(\n    \"The bare Data2VecAudio Model transformer outputting raw hidden-states without any specific head on top.\",\n    DATA2VEC_AUDIO_START_DOCSTRING,\n)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 53,
        "n_words": 34,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 28,
        "n_ast_nodes": 69,
        "n_identifiers": 11,
        "d_id": 6521,
        "documentation": {
            "docstring": "\n    Data2VecAudio was proposed in [data2vec: A General Framework for Self-supervised Learning in Speech, Vision and\n    Language](https://arxiv.org/pdf/2202.03555) by Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu and\n    Michael Auli.\n\n    This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the\n    library implements for all its model (such as downloading or saving etc.).\n\n    This model is a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) sub-class. Use\n    it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and\n    behavior.\n\n    Parameters:\n        config ([`Data2VecAudioConfig`]): Model configuration class with all the parameters of the model.\n            Initializing with a config file does not load the weights associated with the model, only the\n            configuration. Check out the [`~PreTrainedModel.from_pretrained`] method to load the model weights.\n\n    Args:\n        input_values (`torch.FloatTensor` of shape `(batch_size, sequence_length)`):\n            Float values of input raw speech waveform. Values can be obtained by loading a *.flac* or *.wav* audio file\n            into an array of type *List[float]* or a *numpy.ndarray*, *e.g.* via the soundfile library (*pip install\n            soundfile*). To prepare the array into *input_values*, the [`Wav2Vec2Processor`] should be used for padding\n            and conversion into a tensor of type *torch.FloatTensor*. See [`Wav2Vec2Processor.__call__`] for details.\n        attention_mask (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*):\n            Mask to avoid performing convolution and attention on padding token indices. Mask values selected in `[0,\n            1]`:\n\n            - 1 for tokens that are **not masked**,\n            - 0 for tokens that are **masked**.\n\n            [What are attention masks?](../glossary#attention-mask)\n\n            <Tip warning={true}>\n\n            `attention_mask` should only be passed if the corresponding processor has `config.return_attention_mask ==\n            True`. For all models whose processor has `config.return_attention_mask == False`, such as\n            [data2vec-audio-base](https://huggingface.co/facebook/data2vec-audio-base-960h), `attention_mask` should\n            **not** be passed to avoid degraded performance when doing batched inference. For such models\n            `input_values` should simply be padded with 0 and passed without `attention_mask`. Be aware that these\n            models also yield slightly different results depending on whether `input_values` is padded or not.\n\n            </Tip>\n\n        output_attentions (`bool`, *optional*):\n            Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned\n            tensors for more detail.\n        output_hidden_states (`bool`, *optional*):\n            Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for\n            more detail.\n        return_dict (`bool`, *optional*):\n            Whether or not to return a [`~file_utils.ModelOutput`] instead of a plain tuple.\n",
            "n_words": 369,
            "vocab_size": 222,
            "n_whitespaces": 705,
            "language": "en"
        }
    },
    {
        "id": 282726,
        "commit_id": "f2ca215132de40804667feb4deaa0c6b8bfc3d25",
        "repo": "OpenBBTerminal",
        "path": "gamestonk_terminal/econometrics/econometrics_controller.py",
        "file_name": "econometrics_controller.py",
        "fun_name": "print_help",
        "commit_message": "Econometrics Menu (#1403)\n\n* Add Statistics Menu\n\n* Add Granger Causality test\n\n* Apply Black formatting\n\n* Add Cointegration Tests\n\n* Adjust plotting for Cointegration test\n\n* Add Significant parameter to Cointegration tests\n\n* Move regression functions to seperate .py files\n\n* Progress on Panel Data\n\n* A lot of progress for Panel Data\n\n* Make functions robust and improve documentation\n\n* Re-enable Breusch-Godfrey\n\n* Add modify functionality\n\n* Improve modify functionality\n\n* Add Breusch-Pagan heteroscedasticity test\n\n* Capitalize a word\n\n* Include documentatin for the Statistics Menu\n\n* Update _index.md\n\n* Update _index.md\n\n* Update _index.md\n\n* Fix export statements and add Example datasets\n\n* Update example with Longley's dataset\n\n* Update documentation with a legit source\n\n* Compare the results from each regression models based on the wage_panel dataset\n\n* Updated with all relevant types of regression tables\n\n* Update with all relevant regression types for Panel data\n\n* Update _index.md\n\n* Add change column type, improve OLS, add time and entity effects for FE\n\n* Update documentation and fix a small bug\n\n* Add in Statistics menu, replacing Custom menu\n\n* Remove custom menu\n\n* Add in documentation\n\n* Add in gst files\n\n* Cointegration can be used on any amount of columns\n\n* Add Tests\n\n* Make tests time invariant\n\n* Update Poetry and Requirements\n\n* Change name of Statistics menu to Econometrics menu\n\n* Rename scripts\n\n* Add type in Documentation\n\n* Change names from Statistics to Econometrics\n\n* Add graph\n\n* Update tests with rounding and naming\n\n* Make minor adjustments to fix the tests\n\n* Updating tests : allow extra args for capture\n\n* Apply recorder formatting\n\n* Adding some minor formatting\n\n* Fix error with MyPy\n\n* Attempt to fix MyPy annoyance\n\n* super small style things\n\n* Fix small bugs and add plot command to dwat\n\n* Small description mistake\n\n* Update documentation with missing argument\n\n* Update styling\n\n* Add error handling and add improve show functionality\n\n* Fix merge issue\n\n* Allow import from custom_imports\n\nCo-authored-by: Jeroen Bouma <jeroenbouma@MacBook-Pro-van-Jeroen.local>\nCo-authored-by: jmaslek <jmaslek11@gmail.com>\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>",
        "code": "def print_help(self):\n        \n        help_text = f\n        console.print(text=help_text, menu=\"Econometrics\")\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 28,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 35,
        "token_counts": 22,
        "n_ast_nodes": 60,
        "n_identifiers": 9,
        "d_id": 84276,
        "documentation": {
            "docstring": "Print help[cmds]\n    load            load in custom data sets\n    export          export a dataset\n    remove          remove a dataset\n    options         show available column-dataset options[/cmds]\n\n[param]Loaded files:[/param]    {\", \".join(self.files) or None}[cmds]\n\nExploration\n    show            show a portion of a loaded dataset\n    plot            plot data from a dataset\n    type            change types of the columns or display their types\n    desc            show descriptive statistics of a dataset\n    index           set (multi) index based on columns\n    clean           clean a dataset by filling or dropping NaNs\n    modify          combine columns of datasets and delete or rename columns\n\nTimeseries\n    ols             fit a (multi) linear regression model\n    norm            perform normality tests on a column of a dataset\n    root            perform unitroot tests (ADF & KPSS) on a column of a dataset\n\nPanel Data\n    panel           Estimate model based on various regression techniques\n    compare         Compare results of all estimated models\n\nTests\n    dwat            perform Durbin-Watson autocorrelation test on the residuals of the regression\n    bgod            perform Breusch-Godfrey autocorrelation tests with lags on the residuals of the regression\n    bpag            perform Breusch-Pagan heteroscedasticity test on the residuals of the regression\n    granger         perform Granger causality tests on two columns\n    coint           perform co-integration test on a multitude of columns[/cmds]\n        ",
            "n_words": 186,
            "vocab_size": 103,
            "n_whitespaces": 467,
            "language": "en"
        }
    },
    {
        "id": 23061,
        "commit_id": "11f6ff38dcc61348aa4aae8ad2fbbe42b0eab34d",
        "repo": "PaddleOCR",
        "path": "test_tipc/supplementary/utils.py",
        "file_name": "utils.py",
        "fun_name": "print_dict",
        "commit_message": "add supplementary",
        "code": "def print_dict(d, logger, delimiter=0):\n    \n    for k, v in sorted(d.items()):\n        if isinstance(v, dict):\n            logger.info(\"{}{} : \".format(delimiter * \" \", str(k)))\n            print_dict(v, logger, delimiter + 4)\n        elif isinstance(v, list) and len(v) >= 1 and isinstance(v[0], dict):\n            logger.info(\"{}{} : \".format(delimiter * \" \", str(k)))\n            for value in v:\n                print_dict(value, logger, delimiter + 4)\n        else:\n            logger.info(\"{}{} : {}\".format(delimiter * \" \", k, v))\n\n\n@functools.lru_cache()",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "@functools.lru_cache()",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 156,
        "n_words": 60,
        "vocab_size": 37,
        "complexity": 7,
        "nloc": 11,
        "token_counts": 139,
        "n_ast_nodes": 234,
        "n_identifiers": 18,
        "d_id": 4507,
        "documentation": {
            "docstring": "\n    Recursively visualize a dict and\n    indenting acrrording by the relationship of keys.\n    ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 150565,
        "commit_id": "8eeaab27467fa2e0bdc7314bdb888998bbb20af8",
        "repo": "freqtrade",
        "path": "freqtrade/freqai/prediction_models/RL/RLPrediction_env.py",
        "file_name": "RLPrediction_env.py",
        "fun_name": "is_tradesignal",
        "commit_message": "add reward function",
        "code": "def is_tradesignal(self, action):\n        # trade signal\n        \n        return not ((action == Actions.Neutral.value and self._position == Positions.Neutral)\n                    or (action == Actions.Short.value and self._position == Positions.Short)\n                    or (action == Actions.Long.value and self._position == Positions.Long))\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 90,
        "n_words": 31,
        "vocab_size": 20,
        "complexity": 6,
        "nloc": 4,
        "token_counts": 65,
        "n_ast_nodes": 102,
        "n_identifiers": 10,
        "d_id": 34793,
        "documentation": {
            "docstring": "\n        not trade signal is :\n        Action: Neutral, position: Neutral -> Nothing\n        Action: Long, position: Long -> Hold Long\n        Action: Short, position: Short -> Hold Short\n        ",
            "n_words": 25,
            "vocab_size": 16,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 132695,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_trial_runner_pg.py",
        "file_name": "test_trial_runner_pg.py",
        "fun_name": "testPlacementGroupDistributedTraining",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def testPlacementGroupDistributedTraining(self, reuse_actors=False):\n        \n\n        head_bundle = {\"CPU\": 1, \"GPU\": 0, \"custom\": 0}\n        child_bundle = {\"CPU\": 1}\n\n        placement_group_factory = PlacementGroupFactory(\n            [head_bundle, child_bundle, child_bundle, child_bundle]\n        )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 69,
        "n_words": 23,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 31,
        "token_counts": 213,
        "n_ast_nodes": 77,
        "n_identifiers": 7,
        "d_id": 29793,
        "documentation": {
            "docstring": "Run distributed training using placement groups.\n\n        Each trial requests 4 CPUs and starts 4 remote training workers.\n        ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 12429,
        "commit_id": "7c4c39a9d82c58ef2493c21a288c755901a9594e",
        "repo": "jina",
        "path": "jina/orchestrate/deployments/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "start",
        "commit_message": "fix: do not deploy sandbox on init (#4844)",
        "code": "def start(self) -> 'Deployment':\n        \n        if self.is_sandbox and not self._sandbox_deployed:\n            self.update_sandbox_args()\n\n        if self.pod_args['uses_before'] is not None:\n            _args = self.pod_args['uses_before']\n            if getattr(self.args, 'noblock_on_start', False):\n                _args.noblock_on_start = True\n            self.uses_before_pod = PodFactory.build_pod(_args)\n            self.enter_context(self.uses_before_pod)\n        if self.pod_args['uses_after'] is not None:\n            _args = self.pod_args['uses_after']\n            if getattr(self.args, 'noblock_on_start', False):\n                _args.noblock_on_start = True\n            self.uses_after_pod = PodFactory.build_pod(_args)\n            self.enter_context(self.uses_after_pod)\n        if self.pod_args['head'] is not None:\n            _args = self.pod_args['head']\n            if getattr(self.args, 'noblock_on_start', False):\n                _args.noblock_on_start = True\n            self.head_pod = PodFactory.build_pod(_args)\n            self.enter_context(self.head_pod)\n        for shard_id in self.pod_args['pods']:\n            self.shards[shard_id] = self._ReplicaSet(\n                self.args,\n                self.pod_args['pods'][shard_id],\n                self.head_pod,\n            )\n            self.enter_context(self.shards[shard_id])\n\n        if not getattr(self.args, 'noblock_on_start', False):\n            self.activate()\n        return self\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 420,
        "n_words": 87,
        "vocab_size": 43,
        "complexity": 11,
        "nloc": 40,
        "token_counts": 256,
        "n_ast_nodes": 417,
        "n_identifiers": 20,
        "d_id": 2287,
        "documentation": {
            "docstring": "\n        Start to run all :class:`Pod` in this BaseDeployment.\n\n        :return: started deployment\n\n        .. note::\n            If one of the :class:`Pod` fails to start, make sure that all of them\n            are properly closed.\n        ",
            "n_words": 30,
            "vocab_size": 26,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 47576,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/models/test_dag.py",
        "file_name": "test_dag.py",
        "fun_name": "test_roots",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def test_roots(self):\n        \n        with DAG(\"test_dag\", start_date=DEFAULT_DATE) as dag:\n            op1 = EmptyOperator(task_id=\"t1\")\n            op2 = EmptyOperator(task_id=\"t2\")\n            op3 = EmptyOperator(task_id=\"t3\")\n            op4 = EmptyOperator(task_id=\"t4\")\n            op5 = EmptyOperator(task_id=\"t5\")\n            [op1, op2] >> op3 >> [op4, op5]\n\n            assert set(dag.roots) == {op1, op2}\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 125,
        "n_words": 34,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 86,
        "n_ast_nodes": 148,
        "n_identifiers": 15,
        "d_id": 9164,
        "documentation": {
            "docstring": "Verify if dag.roots returns the root tasks of a DAG.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 267689,
        "commit_id": "884244f1b2da3c3f367e064ef4ac0123fcb12675",
        "repo": "ansible",
        "path": "lib/ansible/playbook/task.py",
        "file_name": "task.py",
        "fun_name": "_post_validate_environment",
        "commit_message": "Python 3.9 min for controller (#77566)",
        "code": "def _post_validate_environment(self, attr, value, templar):\n        \n        env = {}\n        if value is not None:\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 9,
        "nloc": 22,
        "token_counts": 137,
        "n_ast_nodes": 35,
        "n_identifiers": 6,
        "d_id": 79001,
        "documentation": {
            "docstring": "\n        Override post validation of vars on the play, as we don't want to\n        template these too early.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 176414,
        "commit_id": "8f4c99debc9440728c5e85f8bffa5d26b232eb6f",
        "repo": "networkx",
        "path": "networkx/classes/multigraph.py",
        "file_name": "multigraph.py",
        "fun_name": "get_edge_data",
        "commit_message": "Multigraph docs update (#5389)\n\n* Updated MultiDiGraph documentation to include more examples of actually\r\nusing parallel edges, and fixed references to things like G[u, v] where\r\nG[u, v, k] is required for a MultiDigraph. Have not made parallel\r\nchanges in MultiGraph which should maybe also be made?\r\n\r\nDocs tests pass on my end; no code outside of comments was changed.\r\n\r\n-Peter Mawhorter\r\n\r\n* Updated docs for MultiGraph to add more multigraph-specific examples and\r\nfix a few places where untested examples were wrong.\r\n\r\n-Peter Mawhorter\r\n\r\n* [DOC] fix typo\r\n\r\n* add the right amount of separators\r\n\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>",
        "code": "def get_edge_data(self, u, v, key=None, default=None):\n        \n        try:\n            if key is None:\n                return self._adj[u][v]\n            else:\n                return self._adj[u][v][key]\n        except KeyError:\n            return default\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 104,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 55,
        "n_ast_nodes": 83,
        "n_identifiers": 8,
        "d_id": 41879,
        "documentation": {
            "docstring": "Returns the attribute dictionary associated with edge (u, v,\n        key).\n\n        If a key is not provided, returns a dictionary mapping edge keys\n        to attribute dictionaries for each edge between u and v.\n\n        This is identical to `G[u][v][key]` except the default is returned\n        instead of an exception is the edge doesn't exist.\n\n        Parameters\n        ----------\n        u, v : nodes\n\n        default :  any Python object (default=None)\n            Value to return if the specific edge (u, v, key) is not\n            found, OR if there are no edges between u and v and no key\n            is specified.\n\n        key : hashable identifier, optional (default=None)\n            Return data only for the edge with specified key, as an\n            attribute dictionary (rather than a dictionary mapping keys\n            to attribute dictionaries).\n\n        Returns\n        -------\n        edge_dict : dictionary\n            The edge attribute dictionary, OR a dictionary mapping edge\n            keys to attribute dictionaries for each of those edges if no\n            specific key is provided (even if there's only one edge\n            between u and v).\n\n        Examples\n        --------\n        >>> G = nx.MultiGraph()  # or MultiDiGraph\n        >>> key = G.add_edge(0, 1, key=\"a\", weight=7)\n        >>> G[0][1][\"a\"]  # key='a'\n        {'weight': 7}\n        >>> G.edges[0, 1, \"a\"]  # key='a'\n        {'weight': 7}\n\n        Warning: we protect the graph data structure by making\n        `G.edges` and `G[1][2]` read-only dict-like structures.\n        However, you can assign values to attributes in e.g.\n        `G.edges[1, 2, 'a']` or `G[1][2]['a']` using an additional\n        bracket as shown next. You need to specify all edge info\n        to assign to the edge data associated with an edge.\n\n        >>> G[0][1][\"a\"][\"weight\"] = 10\n        >>> G.edges[0, 1, \"a\"][\"weight\"] = 10\n        >>> G[0][1][\"a\"][\"weight\"]\n        10\n        >>> G.edges[1, 0, \"a\"][\"weight\"]\n        10\n\n        >>> G = nx.MultiGraph()  # or MultiDiGraph\n        >>> nx.add_path(G, [0, 1, 2, 3])\n        >>> G.edges[0, 1, 0][\"weight\"] = 5\n        >>> G.get_edge_data(0, 1)\n        {0: {'weight': 5}}\n        >>> e = (0, 1)\n        >>> G.get_edge_data(*e)  # tuple form\n        {0: {'weight': 5}}\n        >>> G.get_edge_data(3, 0)  # edge not in graph, returns None\n        >>> G.get_edge_data(3, 0, default=0)  # edge not in graph, return default\n        0\n        >>> G.get_edge_data(1, 0, 0)  # specific key gives back\n        {'weight': 5}\n        ",
            "n_words": 330,
            "vocab_size": 166,
            "n_whitespaces": 778,
            "language": "en"
        }
    },
    {
        "id": 258126,
        "commit_id": "2bb81331b75aec68de0d45c4cb116170d265f1fe",
        "repo": "haystack",
        "path": "test/document_stores/test_base.py",
        "file_name": "test_base.py",
        "fun_name": "test_nested_condition_not_filters",
        "commit_message": "feat: add SQLDocumentStore tests (#3517)\n\n* port SQL tests\r\n\r\n* cleanup document_store_tests.py from sql tests\r\n\r\n* leftover\r\n\r\n* Update .github/workflows/tests.yml\r\n\r\nCo-authored-by: Sara Zan <sara.zanzottera@deepset.ai>\r\n\r\n* review comments\r\n\r\n* Update test/document_stores/test_base.py\r\n\r\nCo-authored-by: bogdankostic <bogdankostic@web.de>\r\n\r\nCo-authored-by: Sara Zan <sara.zanzottera@deepset.ai>\r\nCo-authored-by: bogdankostic <bogdankostic@web.de>",
        "code": "def test_nested_condition_not_filters(self, ds, documents):\n        \n        ds.write_documents(documents)\n        filters = {\n            \"$not\": {\n                \"$or\": {\n                    \"$and\": {\"numbers\": {\"$lt\": 5.0}, \"month\": {\"$ne\": \"01\"}},\n                    \"$not\": {\"year\": {\"$lte\": \"2021\", \"$gte\": \"2020\"}},\n                }\n            }\n        }\n        result = ds.get_all_documents(filters=filters)\n        assert len(result) == 3\n\n        docs_meta = result[0].meta[\"numbers\"]\n        assert [2, 4] == docs_meta\n\n        # Test same logical operator twice on same level\n\n        filters = {\n            \"$or\": [\n                {\"$and\": {\"name\": {\"$in\": [\"name_0\", \"name_1\"]}, \"year\": {\"$gte\": \"2020\"}}},\n                {\"$and\": {\"name\": {\"$in\": [\"name_0\", \"name_1\"]}, \"year\": {\"$lt\": \"2021\"}}},\n            ]\n        }\n        result = ds.get_all_documents(filters=filters)\n        docs_meta = [doc.meta[\"name\"] for doc in result]\n        assert len(result) == 4\n        assert \"name_0\" in docs_meta\n        assert \"name_2\" not in docs_meta\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 352,
        "n_words": 98,
        "vocab_size": 61,
        "complexity": 2,
        "nloc": 25,
        "token_counts": 202,
        "n_ast_nodes": 366,
        "n_identifiers": 12,
        "d_id": 75190,
        "documentation": {
            "docstring": "\n        Test nested logical operations within \"$not\", important as we apply De Morgan's laws in WeaviateDocumentstore\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 101924,
        "commit_id": "dab823a3eb7a5257cb1e0818ee10ed234d3de97f",
        "repo": "faceswap",
        "path": "lib/gui/project.py",
        "file_name": "project.py",
        "fun_name": "_project_modified",
        "commit_message": "Typing - lib.gui.display_command",
        "code": "def _project_modified(self):\n        \n        return any(var.get() for var in self._modified_vars.values())\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 2,
        "nloc": 2,
        "token_counts": 25,
        "n_ast_nodes": 43,
        "n_identifiers": 7,
        "d_id": 21303,
        "documentation": {
            "docstring": "bool: ``True`` if the project has been modified otherwise ``False``. ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 248918,
        "commit_id": "0f971ca68e808dd16f53f5594a6b33b7bddcc9a9",
        "repo": "synapse",
        "path": "tests/federation/test_federation_client.py",
        "file_name": "test_federation_client.py",
        "fun_name": "test_get_pdu_event_from_cache_is_pristine",
        "commit_message": "Update `get_pdu` to return the original, pristine `EventBase` (#13320)\n\nUpdate `get_pdu` to return the untouched, pristine `EventBase` as it was originally seen over federation (no metadata added). Previously, we returned the same `event` reference that we stored in the cache which downstream code modified in place and added metadata like setting it as an `outlier`  and essentially poisoned our cache. Now we always return a copy of the `event` so the original can stay pristine in our cache and re-used for the next cache call.\r\n\r\nSplit out from https://github.com/matrix-org/synapse/pull/13205\r\n\r\nAs discussed at:\r\n\r\n - https://github.com/matrix-org/synapse/pull/13205#discussion_r918365746\r\n - https://github.com/matrix-org/synapse/pull/13205#discussion_r918366125\r\n\r\nRelated to https://github.com/matrix-org/synapse/issues/12584. This PR doesn't fix that issue because it hits [`get_event` which exists from the local database before it tries to `get_pdu`](https://github.com/matrix-org/synapse/blob/7864f33e286dec22368dc0b11c06eebb1462a51e/synapse/federation/federation_client.py#L581-L594).",
        "code": "def test_get_pdu_event_from_cache_is_pristine(self):\n        \n\n        # Get the PDU in the cache\n        remote_pdu = self._get_pdu_once()\n\n        # Modify the the event reference.\n        # This change should not make it back to the `_get_pdu_cache`.\n        remote_pdu.internal_metadata.outlier = True\n\n        # Get the event again. This time it should read it from cache.\n        remote_pdu2 = self.get_success(\n            self.hs.get_federation_client().get_pdu(\n                [\"yet.another.server\"],\n                remote_pdu.event_id,\n                RoomVersions.V9,\n            )\n        )\n\n        # Sanity check that we are working against the same event\n        self.assertEqual(remote_pdu.event_id, remote_pdu2.event_id)\n\n        # Make sure the event does not include modification from earlier\n        self.assertIsNotNone(remote_pdu2)\n        self.assertEqual(remote_pdu2.internal_metadata.outlier, False)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 246,
        "n_words": 81,
        "vocab_size": 56,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 80,
        "n_ast_nodes": 135,
        "n_identifiers": 16,
        "d_id": 72509,
        "documentation": {
            "docstring": "Test that modifications made to events returned by `get_pdu()`\n        do not propagate back to to the internal cache (events returned should\n        be a copy).\n        ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 246084,
        "commit_id": "2aa37a4250675f6d9feb57ec0dce65b2a6a3cde6",
        "repo": "synapse",
        "path": "synapse/storage/databases/main/events.py",
        "file_name": "events.py",
        "fun_name": "_store_rejected_events_txn",
        "commit_message": "Add `state_key` and `rejection_reason` to `events` (#11792)\n\n... and start populating them for new events",
        "code": "def _store_rejected_events_txn(self, txn, events_and_contexts):\n        \n        # Remove the rejected events from the list now that we've added them\n        # to the events table and the events_json table.\n        to_remove = set()\n        for event, context in events_and_contexts:\n            if context.rejected:\n                # Insert the event_id into the rejections table\n                # (events.rejection_reason has already been done)\n                self._store_rejections_txn(txn, event.event_id, context.rejected)\n                to_remove.add(event)\n\n        return [ec for ec in events_and_contexts if ec[0] not in to_remove]\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 178,
        "n_words": 65,
        "vocab_size": 51,
        "complexity": 5,
        "nloc": 7,
        "token_counts": 63,
        "n_ast_nodes": 100,
        "n_identifiers": 13,
        "d_id": 70993,
        "documentation": {
            "docstring": "Add rows to the 'rejections' table for received events which were\n        rejected\n\n        Args:\n            txn (twisted.enterprise.adbapi.Connection): db connection\n            events_and_contexts (list[(EventBase, EventContext)]): events\n                we are persisting\n\n        Returns:\n            list[(EventBase, EventContext)] new list, without the rejected\n                events.\n        ",
            "n_words": 33,
            "vocab_size": 30,
            "n_whitespaces": 124,
            "language": "en"
        }
    },
    {
        "id": 222820,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/command/sdist.py",
        "file_name": "sdist.py",
        "fun_name": "read_template",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def read_template(self):\n        \n        log.info(\"reading manifest template '%s'\", self.template)\n        template = TextFile(self.template, strip_comments=1, skip_blanks=1,\n                            join_lines=1, lstrip_ws=1, rstrip_ws=1,\n                            collapse_join=1)\n\n        try:\n            while True:\n                line = template.readline()\n                if line is None:            # end of file\n                    break\n\n                try:\n                    self.filelist.process_template_line(line)\n                # the call above can raise a DistutilsTemplateError for\n                # malformed lines, or a ValueError from the lower-level\n                # convert_path function\n                except (DistutilsTemplateError, ValueError) as msg:\n                    self.warn(\"%s, line %d: %s\" % (template.filename,\n                                                   template.current_line,\n                                                   msg))\n        finally:\n            template.close()\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 453,
        "n_words": 69,
        "vocab_size": 59,
        "complexity": 5,
        "nloc": 18,
        "token_counts": 110,
        "n_ast_nodes": 180,
        "n_identifiers": 23,
        "d_id": 56758,
        "documentation": {
            "docstring": "Read and parse manifest template file named by self.template.\n\n        (usually \"MANIFEST.in\") The parsing and processing is done by\n        'self.filelist', which updates itself accordingly.\n        ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 212208,
        "commit_id": "b23a3b77447ede916b31756fca997cbb1b806de7",
        "repo": "bokeh",
        "path": "bokeh/core/has_props.py",
        "file_name": "has_props.py",
        "fun_name": "_clone",
        "commit_message": "Discover unstable defaults in `HasProps.__init__()` (#11959)\n\n* Discover unstable defaults in HasProps.__init__()\r\n\r\n* Make HasProps.__getattr__() fail properly\r\n\r\n* More sensible implementation of HasProps._clone()\r\n\r\n* Make InstanceDefault a generic class\r\n\r\n* Fix recursive model definition in tests\r\n\r\n* Fix default override in test_document\r\n\r\n* Add unit tests",
        "code": "def _clone(self) -> HasProps:\n        \n        attrs = self.properties_with_values(include_defaults=False, include_undefined=True)\n        return self.__class__(**{key: val for key, val in attrs.items() if val is not Undefined})\n\nKindRef = Any # TODO\n",
        "url": "https://github.com/bokeh/bokeh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 46,
        "n_words": 26,
        "vocab_size": 23,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 49,
        "n_ast_nodes": 84,
        "n_identifiers": 14,
        "d_id": 53205,
        "documentation": {
            "docstring": " Duplicate a HasProps object.\n\n        Values that are containers are shallow-copied.\n\n        ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 163187,
        "commit_id": "521259299f7829da667ba39302ec77acedde9e5e",
        "repo": "pandas",
        "path": "pandas/core/arrays/datetimes.py",
        "file_name": "datetimes.py",
        "fun_name": "timetz",
        "commit_message": "DOC: Improve doc summaries in series.rst (#45237)",
        "code": "def timetz(self) -> npt.NDArray[np.object_]:\n        \n        return ints_to_pydatetime(self.asi8, self.tz, box=\"time\")\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 30,
        "n_ast_nodes": 49,
        "n_identifiers": 10,
        "d_id": 39395,
        "documentation": {
            "docstring": "\n        Returns numpy array of :class:`datetime.time` objects with timezone\n        information.\n\n        The time part of the Timestamps.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 99254,
        "commit_id": "5ceb67a008be09eac939346e9882d2ec244b7e45",
        "repo": "sentry",
        "path": "src/sentry/models/release.py",
        "file_name": "release.py",
        "fun_name": "add_project",
        "commit_message": "fix(releases): Fix bug where project.has_releases would be false when there are releases associated with the project (#34205)\n\nWe increment `new_groups` in `ReleaseProject` in buffers. If `ReleaseProject` doesn't already exist,\r\nthen buffers will also create the row. The problem here is that we usually rely on\r\n`Release.add_project` to create a `ReleaseProject` row, which also makes sure we set the\r\n`has_releases` flag on the project.\r\n\r\nTo fix this, we add a receive on `buffer_incr_complete` and set the flag there if it is not already\r\nset. Also put some defensive code in `add_project`, although I don't think it will make a large\r\ndifference.\r\n\r\nThis should make it so that going forward we'll properly set this flag. Will follow up with a\r\nbackfill to correct the data.",
        "code": "def add_project(self, project):\n        \n        from sentry.models import Project\n\n        try:\n            with atomic_transaction(using=router.db_for_write(ReleaseProject)):\n                created = ReleaseProject.objects.get_or_create(project=project, release=self)[1]\n                if not project.flags.has_releases:\n                    project.flags.has_releases = True\n                    project.update(flags=F(\"flags\").bitor(Project.flags.has_releases))\n        except IntegrityError:\n            created = False\n\n        return created\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 153,
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        "vocab_size": 24,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 91,
        "n_ast_nodes": 150,
        "n_identifiers": 21,
        "d_id": 19630,
        "documentation": {
            "docstring": "\n        Add a project to this release.\n\n        Returns True if the project was added and did not already exist.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 275258,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_experimental/nadam.py",
        "file_name": "nadam.py",
        "fun_name": "build",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def build(self, var_list):\n        \n        super().build(var_list)\n        if getattr(self, \"_built\", False):\n            return\n        self._built = True\n        self._momentums = []\n        self._velocities = []\n        self._u_product = tf.Variable(1.0, dtype=var_list[0].dtype)\n        # Keep a counter on how many times of _u_product has been computed to\n        # avoid duplicated computations.\n        self._u_product_counter = 1\n\n        for var in var_list:\n            self._momentums.append(\n                self.add_variable_from_reference(\n                    model_variable=var, variable_name=\"m\"\n                )\n            )\n            self._velocities.append(\n                self.add_variable_from_reference(\n                    model_variable=var, variable_name=\"v\"\n                )\n            )\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 289,
        "n_words": 59,
        "vocab_size": 48,
        "complexity": 3,
        "nloc": 20,
        "token_counts": 113,
        "n_ast_nodes": 182,
        "n_identifiers": 18,
        "d_id": 81352,
        "documentation": {
            "docstring": "Initialize optimizer variables.\n\n        Nadam optimizer has 2 types of variables: momentums and velocities.\n\n        Args:\n          var_list: list of model variables to build Nadam variables on.\n        ",
            "n_words": 24,
            "vocab_size": 20,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 48734,
        "commit_id": "48a21aa0eb3a95d32456c2a927eff9552a04231e",
        "repo": "django-rest-framework",
        "path": "tests/test_routers.py",
        "file_name": "test_routers.py",
        "fun_name": "test_conflicting_autogenerated_basenames",
        "commit_message": "raise ImproperlyConfigured exception if `basename` is not unique (#8438)\n\n* raise ImproperlyConfigured if basename already exists\r\n\r\n* rename already_registered function; return True/False\r\n\r\n* additional basename tests\r\n\r\n* additional basename tests\r\n\r\n* Update rest_framework/routers.py\r\n\r\nCo-authored-by: David Graves <dgraves@lrtcapitalgroup.com>\r\nCo-authored-by: Asif Saif Uddin <auvipy@gmail.com>",
        "code": "def test_conflicting_autogenerated_basenames(self):\n        \n        self.router.register(r'notes', NoteViewSet)\n\n        with pytest.raises(ImproperlyConfigured):\n            self.router.register(r'notes_kwduplicate', KWargedNoteViewSet)\n\n        with pytest.raises(ImproperlyConfigured):\n            self.router.register(r'notes_duplicate', NoteViewSet)\n",
        "url": "https://github.com/encode/django-rest-framework.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 62,
        "n_words": 12,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 55,
        "n_ast_nodes": 94,
        "n_identifiers": 9,
        "d_id": 9585,
        "documentation": {
            "docstring": "\n        Ensure 2 routers with the same model, and no basename specified\n        throws an ImproperlyConfigured exception\n        ",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 37,
            "language": "en"
        }
    },
    {
        "id": 159925,
        "commit_id": "85a2a7776e8cc01ce3efdc92e262a7764f5fc061",
        "repo": "numpy",
        "path": "numpy/lib/function_base.py",
        "file_name": "function_base.py",
        "fun_name": "meshgrid",
        "commit_message": "DOC: Fix typo in meshgrid example\n\ncoordinate was misspelled in a comment in the example code\r\n\r\n[ci skip]",
        "code": "def meshgrid(*xi, copy=True, sparse=False, indexing='xy'):\n    \n    ndim = len(xi)\n\n    if indexing not in ['xy', 'ij']:\n        raise ValueError(\n            \"Valid values for `indexing` are 'xy' and 'ij'.\")\n\n    s0 = (1,) * ndim\n    output = [np.asanyarray(x).reshape(s0[:i] + (-1,) + s0[i + 1:])\n              for i, x in enumerate(xi)]\n\n    if indexing == 'xy' and ndim > 1:\n        # switch first and second axis\n        output[0].shape = (1, -1) + s0[2:]\n        output[1].shape = (-1, 1) + s0[2:]\n\n    if not sparse:\n        # Return the full N-D matrix (not only the 1-D vector)\n        output = np.broadcast_arrays(*output, subok=True)\n\n    if copy:\n        output = [x.copy() for x in output]\n\n    return output\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 198,
        "n_words": 98,
        "vocab_size": 67,
        "complexity": 8,
        "nloc": 16,
        "token_counts": 172,
        "n_ast_nodes": 275,
        "n_identifiers": 19,
        "d_id": 38447,
        "documentation": {
            "docstring": "\n    Return coordinate matrices from coordinate vectors.\n\n    Make N-D coordinate arrays for vectorized evaluations of\n    N-D scalar/vector fields over N-D grids, given\n    one-dimensional coordinate arrays x1, x2,..., xn.\n\n    .. versionchanged:: 1.9\n       1-D and 0-D cases are allowed.\n\n    Parameters\n    ----------\n    x1, x2,..., xn : array_like\n        1-D arrays representing the coordinates of a grid.\n    indexing : {'xy', 'ij'}, optional\n        Cartesian ('xy', default) or matrix ('ij') indexing of output.\n        See Notes for more details.\n\n        .. versionadded:: 1.7.0\n    sparse : bool, optional\n        If True the shape of the returned coordinate array for dimension *i*\n        is reduced from ``(N1, ..., Ni, ... Nn)`` to\n        ``(1, ..., 1, Ni, 1, ..., 1)``.  These sparse coordinate grids are\n        intended to be use with :ref:`basics.broadcasting`.  When all\n        coordinates are used in an expression, broadcasting still leads to a\n        fully-dimensonal result array.\n\n        Default is False.\n\n        .. versionadded:: 1.7.0\n    copy : bool, optional\n        If False, a view into the original arrays are returned in order to\n        conserve memory.  Default is True.  Please note that\n        ``sparse=False, copy=False`` will likely return non-contiguous\n        arrays.  Furthermore, more than one element of a broadcast array\n        may refer to a single memory location.  If you need to write to the\n        arrays, make copies first.\n\n        .. versionadded:: 1.7.0\n\n    Returns\n    -------\n    X1, X2,..., XN : ndarray\n        For vectors `x1`, `x2`,..., 'xn' with lengths ``Ni=len(xi)`` ,\n        return ``(N1, N2, N3,...Nn)`` shaped arrays if indexing='ij'\n        or ``(N2, N1, N3,...Nn)`` shaped arrays if indexing='xy'\n        with the elements of `xi` repeated to fill the matrix along\n        the first dimension for `x1`, the second for `x2` and so on.\n\n    Notes\n    -----\n    This function supports both indexing conventions through the indexing\n    keyword argument.  Giving the string 'ij' returns a meshgrid with\n    matrix indexing, while 'xy' returns a meshgrid with Cartesian indexing.\n    In the 2-D case with inputs of length M and N, the outputs are of shape\n    (N, M) for 'xy' indexing and (M, N) for 'ij' indexing.  In the 3-D case\n    with inputs of length M, N and P, outputs are of shape (N, M, P) for\n    'xy' indexing and (M, N, P) for 'ij' indexing.  The difference is\n    illustrated by the following code snippet::\n\n        xv, yv = np.meshgrid(x, y, indexing='ij')\n        for i in range(nx):\n            for j in range(ny):\n                # treat xv[i,j], yv[i,j]\n\n        xv, yv = np.meshgrid(x, y, indexing='xy')\n        for i in range(nx):\n            for j in range(ny):\n                # treat xv[j,i], yv[j,i]\n\n    In the 1-D and 0-D case, the indexing and sparse keywords have no effect.\n\n    See Also\n    --------\n    mgrid : Construct a multi-dimensional \"meshgrid\" using indexing notation.\n    ogrid : Construct an open multi-dimensional \"meshgrid\" using indexing\n            notation.\n\n    Examples\n    --------\n    >>> nx, ny = (3, 2)\n    >>> x = np.linspace(0, 1, nx)\n    >>> y = np.linspace(0, 1, ny)\n    >>> xv, yv = np.meshgrid(x, y)\n    >>> xv\n    array([[0. , 0.5, 1. ],\n           [0. , 0.5, 1. ]])\n    >>> yv\n    array([[0.,  0.,  0.],\n           [1.,  1.,  1.]])\n    >>> xv, yv = np.meshgrid(x, y, sparse=True)  # make sparse output arrays\n    >>> xv\n    array([[0. ,  0.5,  1. ]])\n    >>> yv\n    array([[0.],\n           [1.]])\n\n    `meshgrid` is very useful to evaluate functions on a grid.  If the\n    function depends on all coordinates, you can use the parameter\n    ``sparse=True`` to save memory and computation time.\n\n    >>> x = np.linspace(-5, 5, 101)\n    >>> y = np.linspace(-5, 5, 101)\n    >>> # full coordinate arrays\n    >>> xx, yy = np.meshgrid(x, y)\n    >>> zz = np.sqrt(xx**2 + yy**2)\n    >>> xx.shape, yy.shape, zz.shape\n    ((101, 101), (101, 101), (101, 101))\n    >>> # sparse coordinate arrays\n    >>> xs, ys = np.meshgrid(x, y, sparse=True)\n    >>> zs = np.sqrt(xs**2 + ys**2)\n    >>> xs.shape, ys.shape, zs.shape\n    ((1, 101), (101, 1), (101, 101))\n    >>> np.array_equal(zz, zs)\n    True\n\n    >>> import matplotlib.pyplot as plt\n    >>> h = plt.contourf(x, y, zs)\n    >>> plt.axis('scaled')\n    >>> plt.colorbar()\n    >>> plt.show()\n    ",
            "n_words": 609,
            "vocab_size": 321,
            "n_whitespaces": 1123,
            "language": "en"
        }
    },
    {
        "id": 89031,
        "commit_id": "1bcb129d69a6c4e481b950ebc5871e9c118db74f",
        "repo": "sentry",
        "path": "src/sentry/utils/snuba.py",
        "file_name": "snuba.py",
        "fun_name": "get_snuba_column_name",
        "commit_message": "perf(issue-search): optimize querying on perf issues by using hasAny on transaction.group_id  (#41685)\n\nSpecial optimization for searching on transactions for performance\r\nissues by doing a `hasAny` check instead of arrayJoining `group_ids`\r\ncolumn and applying a filter after.\r\n\r\nbefore query:\r\n```\r\n SELECT (arrayJoin((group_ids AS _snuba_group_ids)) AS _snuba_group_id), _snuba_group_id, (multiply(toUInt64(max((finish_ts AS _snuba_timestamp))), 1000) AS _snuba_last_seen), (ifNull(uniq(_snuba_group_id), 0) AS _snuba_total)\r\n  FROM transactions_local SAMPLE 1.0\r\n WHERE greaterOrEquals((finish_ts AS _snuba_finish_ts), toDateTime('2022-08-26T02:02:49', 'Universal'))\r\n   AND less(_snuba_finish_ts, toDateTime('2022-11-24T02:03:49', 'Universal'))\r\n   AND in((project_id AS _snuba_project_id), tuple(4550959674425346))\r\n   AND equals(('transaction' AS _snuba_type), 'transaction')\r\n   AND in(_snuba_project_id, tuple(4550959674425346))\r\n   AND in(_snuba_group_id, (1, 2))\r\n GROUP BY _snuba_group_id WITH TOTALS\r\n ORDER BY _snuba_last_seen DESC,\r\n          _snuba_group_id ASC\r\n LIMIT 150\r\nOFFSET 0\r\n```\r\n\r\nafter query:\r\n```\r\nSELECT (arrayJoin(arrayIntersect([1, 2], (group_ids AS _snuba_group_ids))) AS _snuba_group_id), (multiply(toUInt64(max((finish_ts AS _snuba_timestamp))), 1000) AS _snuba_last_seen), (ifNull(uniq(_snuba_group_id), 0) AS _snuba_total), _snuba_group_id\r\n  FROM transactions_local SAMPLE 1.0\r\n WHERE greaterOrEquals((finish_ts AS _snuba_finish_ts), toDateTime('2022-08-26T02:01:32', 'Universal'))\r\n   AND less(_snuba_finish_ts, toDateTime('2022-11-24T02:02:32', 'Universal'))\r\n   AND in((project_id AS _snuba_project_id), tuple(4550959669379074))\r\n   AND equals(hasAny(_snuba_group_ids, [1, 2]), 1)\r\n   AND equals(('transaction' AS _snuba_type), 'transaction')\r\n   AND in(_snuba_project_id, tuple(4550959669379074))\r\n GROUP BY _snuba_group_id WITH TOTALS\r\n ORDER BY _snuba_last_seen DESC,\r\n          _snuba_group_id ASC\r\n LIMIT 150\r\nOFFSET 0\r\n```",
        "code": "def get_snuba_column_name(name, dataset=Dataset.Events):\n    \n    no_conversion = {\"group_id\", \"group_ids\", \"project_id\", \"start\", \"end\"}\n\n    if name in no_conversion:\n        return name\n\n    if not name or name.startswith(\"tags[\") or QUOTED_LITERAL_RE.match(name):\n        return name\n\n    measurement_name = get_measurement_name(name)\n    span_op_breakdown_name = get_span_op_breakdown_name(name)\n    if \"measurements_key\" in DATASETS[dataset] and measurement_name:\n        default = f\"measurements[{measurement_name}]\"\n    elif \"span_op_breakdowns_key\" in DATASETS[dataset] and span_op_breakdown_name:\n        default = f\"span_op_breakdowns[{span_op_breakdown_name}]\"\n    else:\n        default = f\"tags[{name}]\"\n\n    return DATASETS[dataset].get(name, default)\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 121,
        "n_words": 56,
        "vocab_size": 37,
        "complexity": 9,
        "nloc": 15,
        "token_counts": 110,
        "n_ast_nodes": 200,
        "n_identifiers": 16,
        "d_id": 18492,
        "documentation": {
            "docstring": "\n    Get corresponding Snuba column name from Sentry snuba map, if not found\n    the column is assumed to be a tag. If name is falsy or name is a quoted literal\n    (e.g. \"'name'\"), leave unchanged.\n    ",
            "n_words": 34,
            "vocab_size": 28,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 319924,
        "commit_id": "b3b2519bf03185aa12028fa68d3b8f8860555e6e",
        "repo": "paperless-ngx",
        "path": "src/paperless_tesseract/tests/test_parser.py",
        "file_name": "test_parser.py",
        "fun_name": "test_skip_noarchive_withtext",
        "commit_message": "Fixes the creation of an archive file, even if noarchive was specified",
        "code": "def test_skip_noarchive_withtext(self):\n        \n        parser = RasterisedDocumentParser(None)\n        parser.parse(\n            os.path.join(self.SAMPLE_FILES, \"multi-page-digital.pdf\"),\n            \"application/pdf\",\n        )\n        self.assertIsNone(parser.archive_path)\n        self.assertContainsStrings(\n            parser.get_text().lower(),\n            [\"page 1\", \"page 2\", \"page 3\"],\n        )\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 113,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 63,
        "n_ast_nodes": 109,
        "n_identifiers": 14,
        "d_id": 117019,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - File with existing text layer\n            - OCR mode set to skip_noarchive\n        WHEN:\n            - Document is parsed\n        THEN:\n            - Text from images is extracted\n            - No archive file is created\n        ",
            "n_words": 31,
            "vocab_size": 25,
            "n_whitespaces": 115,
            "language": "en"
        }
    },
    {
        "id": 201975,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/cache/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_createcachetable_with_table_argument",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_createcachetable_with_table_argument(self):\n        \n        self.drop_table()\n        out = io.StringIO()\n        management.call_command(\n            \"createcachetable\",\n            \"test cache table\",\n            verbosity=2,\n            stdout=out,\n        )\n        self.assertEqual(out.getvalue(), \"Cache table 'test cache table' created.\\n\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 107,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 47,
        "n_ast_nodes": 83,
        "n_identifiers": 12,
        "d_id": 50030,
        "documentation": {
            "docstring": "\n        Delete and recreate cache table with legacy behavior (explicitly\n        specifying the table name).\n        ",
            "n_words": 13,
            "vocab_size": 12,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 285199,
        "commit_id": "9e1a58e2dbedec4e4a9f9c2e32ddf091776c606b",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/econometrics/econometrics_model.py",
        "file_name": "econometrics_model.py",
        "fun_name": "get_engle_granger_two_step_cointegration_test",
        "commit_message": "Here we merge all API Refactor related branches (#2236)\n\n* Update api.py\r\n\r\n* Updated forex menu\r\n\r\n* refactor ycrv command\r\n\r\n* refactor ycrv command black\r\n\r\n* refactor ecocal command\r\n\r\n* Minh changes\r\n\r\n* Adding space to test pushing\r\n\r\n* title fix ecocal df\r\n\r\n* get economic calendar annotation\r\n\r\n* fix investingcom tests\r\n\r\n* refactor index command\r\n\r\n* refactor overview command\r\n\r\n* give defaults to wsj view function args\r\n\r\n* rename date args investincom\r\n\r\n* refacto bigmac command\r\n\r\n* fix ecocal typo\r\n\r\n* refactor rtps command\r\n\r\n* alphavantage gdp\r\n\r\n* alphavantage gdp per capita\r\n\r\n* alphavantage cpi\r\n\r\n* alphavantage tyld\r\n\r\n* alphavantage inf\r\n\r\n* refactor macro command\r\n\r\n* refactor macro command w helpers\r\n\r\n* refactor treasury command\r\n\r\n* fix macro on terminal\r\n\r\n* treasury labels\r\n\r\n* refactor maturities\r\n\r\n* update treasury maturities doc strings\r\n\r\n* refactor get economic calendar finhub\r\n\r\n* refactor map command api\r\n\r\n* display map filter choices\r\n\r\n* route economy api to performance map\r\n\r\n* route economy api to performance map\r\n\r\n* display group choices on valuation command\r\n\r\n* refactor performance and valuation commands\r\n\r\n* refactor spectrum model and view\r\n\r\n* add choices to spectrum controller\r\n\r\n* delete image after view\r\n\r\n* fix model tests finviz\r\n\r\n* fix finciz view tests\r\n\r\n* refactor futures\r\n\r\n* fix some tests\r\n\r\n* fix more tests\r\n\r\n* fix controller test\r\n\r\n* refactor fred series notes\r\n\r\n* update fred notes docstring\r\n\r\n* refacto fred series ids\r\n\r\n* fix pred and qa when empty datasets\r\n\r\n* refactor fred\r\n\r\n* uncomment stuff\r\n\r\n* refacto get series data\r\n\r\n* fix some tests\r\n\r\n* set defaults on args\r\n\r\n* refactor fred yield curve\r\n\r\n* black\r\n\r\n* fix spell and remove ecocal names\r\n\r\n* fix linting\r\n\r\n* linting\r\n\r\n* pylint fix\r\n\r\n* change dangerous defaults\r\n\r\n* Working through crypto fixes (#2256)\r\n\r\n* Working through crypto fixes\r\n\r\n* Continued adding crypto stuff\r\n\r\n* Added crypto overview\r\n\r\n* Added test fixes\r\n\r\n* Added fixtures\r\n\r\n* Fixed tests\r\n\r\n* Fixed charting issue\r\n\r\n* Removed broken APIs\r\n\r\n* Final adjustments\r\n\r\n* Added test fixes\r\n\r\n* map get groups and get ycrv countries into old api\r\n\r\n* exposed econdb helper funcs\r\n\r\n* remove helpers\r\n\r\n* refactor search indices\r\n\r\n* linting\r\n\r\n* refactor arg currency\r\n\r\n* pylint from currency\r\n\r\n* Started switching crpyto ascending to ascend\r\n\r\n* Merging\r\n\r\n* Portfolio model arguements, params, and docstring\r\n\r\n* Refactored for etf commands (#2292)\r\n\r\n* Refactored for etf commands\r\n\r\n* Fixed tests\r\n\r\n* Added load command\r\n\r\n* Fixed menu\r\n\r\n* Portfolio logic fixes\r\n\r\n* Added econometrics (#2260)\r\n\r\n* Added econometrics\r\n\r\n* Fixed tests\r\n\r\n* Simplified API\r\n\r\n* Added test fixes\r\n\r\n* Added test csv\r\n\r\n* Allowed examples to be loaded\r\n\r\n* Fund refactor (#2291)\r\n\r\n* Fund refactor\r\n\r\n* Changed fund_name and fund to name\r\n\r\n* Changed ascending to ascend\r\n\r\n* Stock menu refactoring for easier API usage (#2194)\r\n\r\n* Stocks  refactoring for easier API usage\r\n\r\n* Linting\r\n\r\n* Refactor newly added features\r\n\r\n* Linting\r\n\r\n* Fixing tests\r\n\r\n* Refactor common files used by stocks menu\r\n\r\n* Fixing flake8\r\n\r\n* Fix linting and tests\r\n\r\n* Linting\r\n\r\n* Fix flake8\r\n\r\n* refactor insider_data\r\n\r\n* refactor mentions\r\n\r\n* refactor watchlist\r\n\r\n* refactor sentiment\r\n\r\n* refactor sentiment\r\n\r\n* fix yahoofinance tests\r\n\r\n* refactor load and candle\r\n\r\n* refactor get_news and display_news\r\n\r\n* refactor stocks.ins.act\r\n\r\n* candle default matplotlib\r\n\r\n* fix yahoofinance_view tests\r\n\r\n* fix ark model tests\r\n\r\n* fix ark view tests\r\n\r\n* fix business insider model\r\n\r\n* fix business insider view\r\n\r\n* refactor csimarket model\r\n\r\n* fix tests csi market model\r\n\r\n* update dd controller\r\n\r\n* fix get suppliers tests\r\n\r\n* fix dd controller tests\r\n\r\n* fix finhub tests\r\n\r\n* fix finviz tests\r\n\r\n* fix fmp tests\r\n\r\n* fix marketwatch tests\r\n\r\n* corrected argument keywords in test_bt_model\r\n\r\n* corrected argument keywords in test_bt_view\r\n\r\n* refactor fa controller\r\n\r\n* refactor marketwatch view\r\n\r\n* refactor gov controller\r\n\r\n* fix tests fa av\r\n\r\n* fix tests elect\r\n\r\n* fix dcf tests\r\n\r\n* fix polygon tests\r\n\r\n* fix fmp tests\r\n\r\n* fix quiverquant tests\r\n\r\n* fix yahoofinance fa tests\r\n\r\n* fix more fa tests\r\n\r\n* fix insider tests\r\n\r\n* fix more tests\r\n\r\n* fix more tests\r\n\r\n* fix options tests\r\n\r\n* fix stock gov tests\r\n\r\n* fix tests test_ba_controller\r\n\r\n* fix tests for test_finviz_compare_model.py\r\n\r\n* fixed 2 tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fix final tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* Fix tests\r\n\r\n* black\r\n\r\n* forgot to black tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* flakefix\r\n\r\n* Tests + code : Stocks / Discovery\r\n\r\n* fix tests\r\n\r\n* added recorder\r\n\r\n* fixed tests\r\n\r\n* fixed tests\r\n\r\n* black\r\n\r\n* black\r\n\r\n* remove unused imports\r\n\r\n* refactor display raw\r\n\r\n* sia dicts fix\r\n\r\n* pylint\r\n\r\n* linting\r\n\r\n* remove dangerous default\r\n\r\n* fix tests\r\n\r\n* fix beta model test\r\n\r\n* black\r\n\r\n* skip screener qa test\r\n\r\n* change sector path to sectors\r\n\r\n* update tests readme\r\n\r\n* fix metric defaults\r\n\r\n* black\r\n\r\n* substitute lost ticker\r\n\r\n* defaults cpic\r\n\r\n* another round on sia\r\n\r\n* refactor cramer\r\n\r\n* reduce default tweets on sentiment\r\n\r\n* refactor yf hist, corr, volume\r\n\r\n* arkorders default\r\n\r\n* refactor income, balance, cashflow\r\n\r\n* refacto scorr, screener, getfinnhub\r\n\r\n* refactor stockgrid\r\n\r\n* ibkr refactor\r\n\r\n* another round on stockgrid\r\n\r\n* add dividens end point\r\n\r\n* refactor discovery endpoints\r\n\r\n* update docstrings with similar input\r\n\r\n* refactor messages\r\n\r\n* refactor ba\r\n\r\n* refactor regioons\r\n\r\n* refactor twitter sentiment\r\n\r\n* refactor hist\r\n\r\n* refactor regions\r\n\r\n* give default to timeframe\r\n\r\n* refactor bunch of defaults and arg names\r\n\r\n* remove leftover imports\r\n\r\n* refactor vwap\r\n\r\n* let tests run\r\n\r\n* fix tests\r\n\r\n* fix stock tests\r\n\r\n* fix stockanalysis tests\r\n\r\n* flake\r\n\r\n* MYPY\r\n\r\n* Made important changes\r\n\r\n* added fixes\r\n\r\n* Fixed big issue\r\n\r\n* Added fixes to tests\r\n\r\n* fix qa tests\r\n\r\n* fix tests\r\n\r\n* fix 1 more test\r\n\r\n* last stocks failing\r\n\r\n* fix crypto test\r\n\r\nCo-authored-by: Chavithra PARANA <chavithra@gmail.com>\r\nCo-authored-by: montezdesousa <montezdesousa@gmail.com>\r\nCo-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>\r\nCo-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>\r\nCo-authored-by: colin99d <colin99delahunty@gmail.com>\r\n\r\n* fix portfolio tests\r\n\r\n* change period to window\r\n\r\n* update ca docstrings\r\n\r\n* refactor get_similar_companies func\r\n\r\n* Fixed\r\n\r\n* Update CI\r\n\r\n* Update CI 2\r\n\r\n* Update CI 3\r\n\r\n* Update dependencies\r\n\r\nCo-authored-by: colin99d <colin99delahunty@gmail.com>\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: montezdesousa <montezdesousa@gmail.com>\r\nCo-authored-by: James Simmons <simmonsj330@gmail.com>\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\nCo-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com>\r\nCo-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com>\r\nCo-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>\r\nCo-authored-by: northern-64bit <75195383+northern-64bit@users.noreply.github.com>\r\nCo-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>",
        "code": "def get_engle_granger_two_step_cointegration_test(dependent_series, independent_series):\n    \n    warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n    long_run_ols = sm.OLS(dependent_series, sm.add_constant(independent_series))\n    warnings.simplefilter(action=\"default\", category=FutureWarning)\n\n    long_run_ols_fit = long_run_ols.fit()\n\n    c, gamma = long_run_ols_fit.params\n    z = long_run_ols_fit.resid\n\n    short_run_ols = sm.OLS(dependent_series.diff().iloc[1:], (z.shift().iloc[1:]))\n    short_run_ols_fit = short_run_ols.fit()\n\n    alpha = short_run_ols_fit.params[0]\n\n    # NOTE: The p-value returned by the adfuller function assumes we do not estimate z\n    # first, but test stationarity of an unestimated series directly. This assumption\n    # should have limited effect for high N, however. Critical values taking this into\n    # account more accurately are provided in e.g. McKinnon (1990) and Engle & Yoo (1987).\n\n    adfstat, pvalue, _, _, _ = adfuller(z, maxlag=1, autolag=None)\n\n    return c, gamma, alpha, z, adfstat, pvalue\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
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        "d_id": 85239,
        "documentation": {
            "docstring": "Estimates long-run and short-run cointegration relationship for series y and x and apply\n    the two-step Engle & Granger test for cointegration.\n\n    Uses a 2-step process to first estimate coefficients for the long-run relationship\n        y_t = c + gamma * x_t + z_t\n\n    and then the short-term relationship,\n        y_t - y_(t-1) = alpha * z_(t-1) + epsilon_t,\n\n    with z the found residuals of the first equation.\n\n    Then tests cointegration by Dickey-Fuller phi=1 vs phi < 1 in\n        z_t = phi * z_(t-1) + eta_t\n\n    If this implies phi < 1, the z series is stationary is concluded to be\n    stationary, and thus the series y and x are concluded to be cointegrated.\n\n    Parameters\n    ----------\n    dependent_series : pd.Series\n        The first time series of the pair to analyse.\n\n    independent_series : pd.Series\n        The second time series of the pair to analyse.\n\n    Returns\n    -------\n    c : float\n        The constant term in the long-run relationship y_t = c + gamma * x_t + z_t. This\n        describes the static shift of y with respect to gamma * x.\n\n    gamma : float\n        The gamma term in the long-run relationship y_t = c + gamma * x_t + z_t. This\n        describes the ratio between the const-shifted y and x.\n\n    alpha : float\n        The alpha term in the short-run relationship y_t - y_(t-1) = alpha * z_(t-1) + epsilon. This\n        gives an indication of the strength of the error correction toward the long-run mean.\n\n    z : pd.Series\n        Series of residuals z_t from the long-run relationship y_t = c + gamma * x_t + z_t, representing\n        the value of the error correction term.\n\n    dfstat : float\n        The Dickey Fuller test-statistic for phi = 1 vs phi < 1 in the second equation. A more\n        negative value implies the existence of stronger cointegration.\n\n    pvalue : float\n        The p-value corresponding to the Dickey Fuller test-statistic. A lower value implies\n        stronger rejection of no-cointegration, thus stronger evidence of cointegration.\n\n    ",
            "n_words": 315,
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    },
    {
        "id": 177062,
        "commit_id": "8b6c25ec952b80539a38e7a884c0fdc3fd735b28",
        "repo": "networkx",
        "path": "networkx/algorithms/lowest_common_ancestors.py",
        "file_name": "lowest_common_ancestors.py",
        "fun_name": "naive_all_pairs_lowest_common_ancestor",
        "commit_message": "Improve LCA input validation (#5877)\n\n* Remove explicit checks for None nodes.\r\n\r\nThe graph objects already do not allow None nodes.\r\n\r\n* Change elif to if for raising branches.",
        "code": "def naive_all_pairs_lowest_common_ancestor(G, pairs=None):\n    \n    if not nx.is_directed_acyclic_graph(G):\n        raise nx.NetworkXError(\"LCA only defined on directed acyclic graphs.\")\n    if len(G) == 0:\n        raise nx.NetworkXPointlessConcept(\"LCA meaningless on null graphs.\")\n\n    ancestor_cache = {}\n\n    if pairs is None:\n\n        pairs = combinations_with_replacement(G, 2)\n\n    for v, w in pairs:\n        if v not in ancestor_cache:\n            ancestor_cache[v] = nx.ancestors(G, v)\n            ancestor_cache[v].add(v)\n        if w not in ancestor_cache:\n            ancestor_cache[w] = nx.ancestors(G, w)\n            ancestor_cache[w].add(w)\n\n        common_ancestors = ancestor_cache[v] & ancestor_cache[w]\n\n        if common_ancestors:\n            common_ancestor = next(iter(common_ancestors))\n            while True:\n                successor = None\n                for lower_ancestor in G.successors(common_ancestor):\n                    if lower_ancestor in common_ancestors:\n                        successor = lower_ancestor\n                        break\n                if successor is None:\n                    break\n                common_ancestor = successor\n            yield ((v, w), common_ancestor)\n\n\n@not_implemented_for(\"undirected\")\n@not_implemented_for(\"multigraph\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"undirected\")\n@not_implemented_for(\"multigraph\")",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 387,
        "n_words": 101,
        "vocab_size": 60,
        "complexity": 12,
        "nloc": 28,
        "token_counts": 188,
        "n_ast_nodes": 319,
        "n_identifiers": 22,
        "d_id": 42256,
        "documentation": {
            "docstring": "Return the lowest common ancestor of all pairs or the provided pairs\n\n    Parameters\n    ----------\n    G : NetworkX directed graph\n\n    pairs : iterable of pairs of nodes, optional (default: all pairs)\n        The pairs of nodes of interest.\n        If None, will find the LCA of all pairs of nodes.\n\n    Yields\n    ------\n    ((node1, node2), lca) : 2-tuple\n        Where lca is least common ancestor of node1 and node2.\n        Note that for the default case, the order of the node pair is not considered,\n        e.g. you will not get both ``(a, b)`` and ``(b, a)``\n\n    Raises\n    ------\n    NetworkXPointlessConcept\n        If `G` is null.\n    NetworkXError\n        If `G` is not a DAG.\n\n    Examples\n    --------\n    The default behavior is to yield the lowest common ancestor for all\n    possible combinations of nodes in `G`, including self-pairings:\n\n    >>> G = nx.DiGraph([(0, 1), (0, 3), (1, 2)])\n    >>> dict(nx.naive_all_pairs_lowest_common_ancestor(G))\n    {(0, 0): 0, (0, 1): 0, (0, 3): 0, (0, 2): 0, (1, 1): 1, (1, 3): 0, (1, 2): 1, (3, 3): 3, (3, 2): 0, (2, 2): 2}\n\n    The pairs argument can be used to limit the output to only the\n    specified node pairings:\n\n    >>> dict(nx.naive_all_pairs_lowest_common_ancestor(G, pairs=[(1, 2), (2, 3)]))\n    {(1, 2): 1, (2, 3): 0}\n\n    Notes\n    -----\n    Only defined on non-null directed acyclic graphs.\n\n    See Also\n    --------\n    naive_lowest_common_ancestor\n    ",
            "n_words": 208,
            "vocab_size": 126,
            "n_whitespaces": 344,
            "language": "en"
        }
    },
    {
        "id": 22163,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/requests/utils.py",
        "file_name": "utils.py",
        "fun_name": "unquote_unreserved",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def unquote_unreserved(uri):\n    \n    parts = uri.split(\"%\")\n    for i in range(1, len(parts)):\n        h = parts[i][0:2]\n        if len(h) == 2 and h.isalnum():\n            try:\n                c = chr(int(h, 16))\n            except ValueError:\n                raise InvalidURL(f\"Invalid percent-escape sequence: '{h}'\")\n\n            if c in UNRESERVED_SET:\n                parts[i] = c + parts[i][2:]\n            else:\n                parts[i] = f\"%{parts[i]}\"\n        else:\n            parts[i] = f\"%{parts[i]}\"\n    return \"\".join(parts)\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 198,
        "n_words": 50,
        "vocab_size": 37,
        "complexity": 6,
        "nloc": 16,
        "token_counts": 119,
        "n_ast_nodes": 215,
        "n_identifiers": 16,
        "d_id": 4233,
        "documentation": {
            "docstring": "Un-escape any percent-escape sequences in a URI that are unreserved\n    characters. This leaves all reserved, illegal and non-ASCII bytes encoded.\n\n    :rtype: str\n    ",
            "n_words": 22,
            "vocab_size": 22,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 172104,
        "commit_id": "bce995817caf00ab5e82cb4cf1b540f1530cf4ea",
        "repo": "pandas",
        "path": "pandas/core/dtypes/inference.py",
        "file_name": "inference.py",
        "fun_name": "is_named_tuple",
        "commit_message": "Fix some dosctring RT02 error (#50197)",
        "code": "def is_named_tuple(obj) -> bool:\n    \n    return isinstance(obj, abc.Sequence) and hasattr(obj, \"_fields\")\n\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 16,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 25,
        "token_counts": 24,
        "n_ast_nodes": 41,
        "n_identifiers": 7,
        "d_id": 40758,
        "documentation": {
            "docstring": "\n    Check if the object is a named tuple.\n\n    Parameters\n    ----------\n    obj : The object to check\n\n    Returns\n    -------\n    bool\n        Whether `obj` is a named tuple.\n\n    Examples\n    --------\n    >>> from collections import namedtuple\n    >>> Point = namedtuple(\"Point\", [\"x\", \"y\"])\n    >>> p = Point(1, 2)\n    >>>\n    >>> is_named_tuple(p)\n    True\n    >>> is_named_tuple((1, 2))\n    False\n    ",
            "n_words": 51,
            "vocab_size": 40,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 200509,
        "commit_id": "af443377dd48c2caf440d2b6dd76830dbe84712f",
        "repo": "sympy",
        "path": "sympy/integrals/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "_laplace_rule_timescale",
        "commit_message": "Moved all constant-factor calculations to `_laplace_apply_rules`",
        "code": "def _laplace_rule_timescale(f, t, s, doit=True, **hints):\n    r\n    _simplify = hints.pop('simplify', True)\n    b = Wild('b', exclude=[t])\n    g = WildFunction('g', nargs=1)\n    ma1 = f.match(g)\n    if ma1:\n        arg = ma1[g].args[0].collect(t)\n        ma2 = arg.match(b*t)\n        if ma2 and ma2[b]>0:\n            debug('_laplace_apply_rules match:')\n            debug('      f:    %s ( %s, %s )'%(f, ma1, ma2))\n            debug('      rule: amplitude and time scaling (1.1, 1.2)')\n            if ma2[b]==1:\n                if doit==True and not any(func.has(t) for func\n                                          in ma1[g].atoms(AppliedUndef)):\n                    return _laplace_transform(ma1[g].func(t), t, s,\n                                                simplify=_simplify)\n                else:\n                    return LaplaceTransform(ma1[g].func(t), t, s, **hints)\n            else:\n                L = _laplace_apply_rules(ma1[g].func(t), t, s/ma2[b],\n                                         doit=doit, **hints)\n                try:\n                    r, p, c = L\n                    return (1/ma2[b]*r, p, c)\n                except TypeError:\n                    return 1/ma2[b]*L\n    return None\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 506,
        "n_words": 99,
        "vocab_size": 71,
        "complexity": 9,
        "nloc": 37,
        "token_counts": 266,
        "n_ast_nodes": 407,
        "n_identifiers": 35,
        "d_id": 49677,
        "documentation": {
            "docstring": "\n    This internal helper function tries to apply the time-scaling rule of the\n    Laplace transform and returns `None` if it cannot do it.\n\n    Time-scaling means the following: if $F(s)$ is the Laplace transform of,\n    $f(t)$, then, for any $a>0$, the Laplace transform of $f(at)$ will be\n    $\\frac1a F(\\frac{s}{a})$. This scaling will also affect the transform's\n    convergence plane.\n    ",
            "n_words": 56,
            "vocab_size": 43,
            "n_whitespaces": 78,
            "language": "en"
        }
    },
    {
        "id": 153549,
        "commit_id": "97769988a6f19e4b76f34238c97bf159ee7626a5",
        "repo": "modin",
        "path": "modin/core/io/text/json_dispatcher.py",
        "file_name": "json_dispatcher.py",
        "fun_name": "_read",
        "commit_message": "REFACTOR-#3853: interacting with Dask interface through 'DaskWrapper' class (#3854)\n\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nCo-authored-by: Dmitry Chigarev <dchigarev@users.noreply.github.com>\r\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Anatoly Myachev <anatoly.myachev@intel.com>",
        "code": "def _read(cls, path_or_buf, **kwargs):\n        \n        path_or_buf = cls.get_path_or_buffer(path_or_buf)\n        if isinstance(path_or_buf, str):\n            if not cls.file_exists(path_or_buf):\n                return cls.single_worker_read(path_or_buf, **kwargs)\n            path_or_buf = cls.get_path(path_or_buf)\n        elif not cls.pathlib_or_pypath(path_or_buf):\n            return cls.single_worker_read(path_or_buf, **kwargs)\n        if not kwargs.get(\"lines\", False):\n            return cls.single_worker_read(path_or_buf, **kwargs)\n        with OpenFile(path_or_buf, \"rb\") as f:\n            columns = pandas.read_json(BytesIO(b\"\" + f.readline()), lines=True).columns\n        kwargs[\"columns\"] = columns\n        empty_pd_df = pandas.DataFrame(columns=columns)\n\n        with OpenFile(path_or_buf, \"rb\", kwargs.get(\"compression\", \"infer\")) as f:\n            partition_ids = []\n            index_ids = []\n            dtypes_ids = []\n\n            column_widths, num_splits = cls._define_metadata(empty_pd_df, columns)\n\n            args = {\"fname\": path_or_buf, \"num_splits\": num_splits, **kwargs}\n\n            splits = cls.partitioned_file(\n                f,\n                num_partitions=NPartitions.get(),\n            )\n            for start, end in splits:\n                args.update({\"start\": start, \"end\": end})\n                partition_id = cls.deploy(cls.parse, num_returns=num_splits + 3, **args)\n                partition_ids.append(partition_id[:-3])\n                index_ids.append(partition_id[-3])\n                dtypes_ids.append(partition_id[-2])\n\n        # partition_id[-1] contains the columns for each partition, which will be useful\n        # for implementing when `lines=False`.\n        row_lengths = cls.materialize(index_ids)\n        new_index = pandas.RangeIndex(sum(row_lengths))\n\n        dtypes = cls.get_dtypes(dtypes_ids)\n        partition_ids = cls.build_partition(partition_ids, row_lengths, column_widths)\n\n        if isinstance(dtypes, pandas.Series):\n            dtypes.index = columns\n        else:\n            dtypes = pandas.Series(dtypes, index=columns)\n\n        new_frame = cls.frame_cls(\n            np.array(partition_ids),\n            new_index,\n            columns,\n            row_lengths,\n            column_widths,\n            dtypes=dtypes,\n        )\n        new_frame.synchronize_labels(axis=0)\n        return cls.query_compiler_cls(new_frame)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 655,
        "n_words": 157,
        "vocab_size": 106,
        "complexity": 7,
        "nloc": 48,
        "token_counts": 398,
        "n_ast_nodes": 641,
        "n_identifiers": 58,
        "d_id": 35438,
        "documentation": {
            "docstring": "\n        Read data from `path_or_buf` according to the passed `read_json` `kwargs` parameters.\n\n        Parameters\n        ----------\n        path_or_buf : str, path object or file-like object\n            `path_or_buf` parameter of `read_json` function.\n        **kwargs : dict\n            Parameters of `read_json` function.\n\n        Returns\n        -------\n        BaseQueryCompiler\n            Query compiler with imported data for further processing.\n        ",
            "n_words": 44,
            "vocab_size": 35,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 204181,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/messages/storage/cookie.py",
        "file_name": "cookie.py",
        "fun_name": "_store",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _store(self, messages, response, remove_oldest=True, *args, **kwargs):\n        \n        unstored_messages = []\n        encoded_data = self._encode(messages)\n        if self.max_cookie_size:\n            # data is going to be stored eventually by SimpleCookie, which\n            # adds its own overhead, which we must account for.\n            cookie = SimpleCookie()  # create outside the loop\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 106,
        "n_words": 44,
        "vocab_size": 39,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 112,
        "n_ast_nodes": 70,
        "n_identifiers": 13,
        "d_id": 50673,
        "documentation": {
            "docstring": "\n        Store the messages to a cookie and return a list of any messages which\n        could not be stored.\n\n        If the encoded data is larger than ``max_cookie_size``, remove\n        messages until the data fits (these are the messages which are\n        returned), and add the not_finished sentinel value to indicate as much.\n        ",
            "n_words": 49,
            "vocab_size": 36,
            "n_whitespaces": 92,
            "language": "en"
        }
    },
    {
        "id": 156197,
        "commit_id": "bc43d692e8f5fc55e6d81c91053598bd89f79267",
        "repo": "dask",
        "path": "dask/dataframe/core.py",
        "file_name": "core.py",
        "fun_name": "handle_out",
        "commit_message": "Add sanity checks to divisions setter (#8806)\n\nAdds a few sanity checks to the divisions property setter\r\n\r\n- New divisions are compatible with the existing `npartitions`\r\n- New divisions don't mix None and non-None values\r\n- New divisions are sorted (except for ordered categorical dtypes, where\r\nthat's hard)",
        "code": "def handle_out(out, result):\n    \n    if isinstance(out, tuple):\n        if len(out) == 1:\n            out = out[0]\n        elif len(out) > 1:\n            raise NotImplementedError(\"The out parameter is not fully supported\")\n        else:\n            out = None\n\n    # Notice, we use .__class__ as opposed to type() in order to support\n    # object proxies see <https://github.com/dask/dask/pull/6981>\n    if out is not None and out.__class__ != result.__class__:\n        raise TypeError(\n            \"Mismatched types between result and out parameter. \"\n            \"out=%s, result=%s\" % (str(type(out)), str(type(result)))\n        )\n\n    if isinstance(out, DataFrame):\n        if len(out.columns) != len(result.columns):\n            raise ValueError(\n                \"Mismatched columns count between result and out parameter. \"\n                \"out=%s, result=%s\" % (str(len(out.columns)), str(len(result.columns)))\n            )\n\n    if isinstance(out, (Series, DataFrame, Scalar)):\n        out._meta = result._meta\n        out._name = result._name\n        out.dask = result.dask\n\n        if not isinstance(out, Scalar):\n            out._divisions = result.divisions\n    elif out is not None:\n        msg = (\n            \"The out parameter is not fully supported.\"\n            \" Received type %s, expected %s \"\n            % (typename(type(out)), typename(type(result)))\n        )\n        raise NotImplementedError(msg)\n    else:\n        return result\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 424,
        "n_words": 148,
        "vocab_size": 90,
        "complexity": 11,
        "nloc": 34,
        "token_counts": 227,
        "n_ast_nodes": 373,
        "n_identifiers": 23,
        "d_id": 36599,
        "documentation": {
            "docstring": "Handle out parameters\n\n    If out is a dask.DataFrame, dask.Series or dask.Scalar then\n    this overwrites the contents of it with the result\n    ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 259100,
        "commit_id": "742d39ca38f713027091324c4555f9b4e1b9da05",
        "repo": "scikit-learn",
        "path": "sklearn/neighbors/tests/test_neighbors.py",
        "file_name": "test_neighbors.py",
        "fun_name": "test_regressor_predict_on_arraylikes",
        "commit_message": "FIX Fixes KNeighborsRegressor.predict with array-likes (#22687)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>",
        "code": "def test_regressor_predict_on_arraylikes():\n    \n    X = [[5, 1], [3, 1], [4, 3], [0, 3]]\n    y = [2, 3, 5, 6]\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 27,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 90,
        "n_ast_nodes": 60,
        "n_identifiers": 3,
        "d_id": 75566,
        "documentation": {
            "docstring": "Ensures that `predict` works for array-likes when `weights` is a callable.\n\n    Non-regression test for #22687.\n    ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 149948,
        "commit_id": "45c47bda6000b2b57026fdedffaaa69f8fc1797e",
        "repo": "freqtrade",
        "path": "freqtrade/rpc/discord.py",
        "file_name": "discord.py",
        "fun_name": "_send_msg",
        "commit_message": "refactor into discord rpc module",
        "code": "def _send_msg(self, msg):\n        \n        self.logger.info(f\"Sending discord message: {msg}\")\n\n        # TODO: handle other message types\n        if msg['type'] == RPCMessageType.EXIT_FILL:\n            profit_ratio = msg.get('profit_ratio')\n            open_date = msg.get('open_date').strftime('%Y-%m-%d %H:%M:%S')\n            close_date = msg.get('close_date').strftime('%Y-%m-%d %H:%M:%S') if msg.get('close_date') else ''\n\n            embeds = [{\n                'title': '{} Trade: {}'.format(\n                    'Profit' if profit_ratio > 0 else 'Loss',\n                    msg.get('pair')),\n                'color': (0x00FF00 if profit_ratio > 0 else 0xFF0000),\n                'fields': [\n                    {'name': 'Trade ID', 'value': msg.get('id'), 'inline': True},\n                    {'name': 'Exchange', 'value': msg.get('exchange').capitalize(), 'inline': True},\n                    {'name': 'Pair', 'value': msg.get('pair'), 'inline': True},\n                    {'name': 'Direction', 'value': 'Short' if msg.get('is_short') else 'Long', 'inline': True},\n                    {'name': 'Open rate', 'value': msg.get('open_rate'), 'inline': True},\n                    {'name': 'Close rate', 'value': msg.get('close_rate'), 'inline': True},\n                    {'name': 'Amount', 'value': msg.get('amount'), 'inline': True},\n                    {'name': 'Open order', 'value': msg.get('open_order_id'), 'inline': True},\n                    {'name': 'Open date', 'value': open_date, 'inline': True},\n                    {'name': 'Close date', 'value': close_date, 'inline': True},\n                    {'name': 'Profit', 'value': msg.get('profit_amount'), 'inline': True},\n                    {'name': 'Profitability', 'value': '{:.2f}%'.format(profit_ratio * 100), 'inline': True},\n                    {'name': 'Stake currency', 'value': msg.get('stake_currency'), 'inline': True},\n                    {'name': 'Fiat currency', 'value': msg.get('fiat_display_currency'), 'inline': True},\n                    {'name': 'Buy Tag', 'value': msg.get('enter_tag'), 'inline': True},\n                    {'name': 'Sell Reason', 'value': msg.get('exit_reason'), 'inline': True},\n                    {'name': 'Strategy', 'value': self.strategy, 'inline': True},\n                    {'name': 'Timeframe', 'value': self.timeframe, 'inline': True},\n                ],\n            }]\n\n            # convert all value in fields to string for discord\n            for embed in embeds:\n                for field in embed['fields']:\n                    field['value'] = str(field['value'])\n\n            # Send the message to discord channel\n            payload = {\n                'embeds': embeds,\n            }\n            headers = {\n                'Content-Type': 'application/json',\n            }\n            try:\n                requests.post(self.config['discord']['webhook_url'], data=json.dumps(payload), headers=headers)\n            except Exception as e:\n                self.logger.error(f\"Failed to send discord message: {e}\")\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 953,
        "n_words": 237,
        "vocab_size": 130,
        "complexity": 9,
        "nloc": 45,
        "token_counts": 535,
        "n_ast_nodes": 994,
        "n_identifiers": 31,
        "d_id": 34602,
        "documentation": {
            "docstring": "\n        msg = {\n            'type': (RPCMessageType.EXIT_FILL if fill\n                     else RPCMessageType.EXIT),\n            'trade_id': trade.id,\n            'exchange': trade.exchange.capitalize(),\n            'pair': trade.pair,\n            'leverage': trade.leverage,\n            'direction': 'Short' if trade.is_short else 'Long',\n            'gain': gain,\n            'limit': profit_rate,\n            'order_type': order_type,\n            'amount': trade.amount,\n            'open_rate': trade.open_rate,\n            'close_rate': trade.close_rate,\n            'current_rate': current_rate,\n            'profit_amount': profit_trade,\n            'profit_ratio': profit_ratio,\n            'buy_tag': trade.enter_tag,\n            'enter_tag': trade.enter_tag,\n            'sell_reason': trade.exit_reason,  # Deprecated\n            'exit_reason': trade.exit_reason,\n            'open_date': trade.open_date,\n            'close_date': trade.close_date or datetime.utcnow(),\n            'stake_currency': self.config['stake_currency'],\n            'fiat_currency': self.config.get('fiat_display_currency', None),\n        }\n        ",
            "n_words": 63,
            "vocab_size": 59,
            "n_whitespaces": 359,
            "language": "en"
        }
    },
    {
        "id": 169366,
        "commit_id": "8f26ab7c184c7f6fc7337bfed47ac9d86ee4551f",
        "repo": "pandas",
        "path": "pandas/core/arrays/datetimelike.py",
        "file_name": "datetimelike.py",
        "fun_name": "_get_arithmetic_result_freq",
        "commit_message": "REF: helpers to de-duplicate datetimelike arithmetic (#48844)",
        "code": "def _get_arithmetic_result_freq(self, other) -> BaseOffset | None:\n        \n        # Adding or subtracting a Timedelta/Timestamp scalar is freq-preserving\n        #  whenever self.freq is a Tick\n        if is_period_dtype(self.dtype):\n            return self.freq\n        elif not lib.is_scalar(other):\n            return None\n        elif isinstance(self.freq, Tick):\n            # In these cases\n            return self.freq\n        return None\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 136,
        "n_words": 42,
        "vocab_size": 31,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 51,
        "n_ast_nodes": 85,
        "n_identifiers": 11,
        "d_id": 40423,
        "documentation": {
            "docstring": "\n        Check if we can preserve self.freq in addition or subtraction.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 95336,
        "commit_id": "524c8579d4d87954d993cd3fb7a29e0422058e6a",
        "repo": "sentry",
        "path": "src/sentry/incidents/subscription_processor.py",
        "file_name": "subscription_processor.py",
        "fun_name": "__reset_trigger_counts",
        "commit_message": "feat(alerts): Clear counters for null subscription updates (#30831)\n\nAdds logic that clears trigger count and resolve\r\ncount for crash rate alerts and metrics crash rate\r\nalerts in the case an empty subscription update is sent\r\nor if a min session count threshold is set and the count\r\nin the subscription update is lower than the min threshold",
        "code": "def __reset_trigger_counts(self):\n        \n        for trigger_id in self.trigger_alert_counts:\n            self.trigger_alert_counts[trigger_id] = 0\n        for trigger_id in self.trigger_resolve_counts:\n            self.trigger_resolve_counts[trigger_id] = 0\n        self.update_alert_rule_stats()\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 67,
        "n_words": 17,
        "vocab_size": 12,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 41,
        "n_ast_nodes": 66,
        "n_identifiers": 6,
        "d_id": 19202,
        "documentation": {
            "docstring": "\n        Helper method that clears both the trigger alert and the trigger resolve counts\n        ",
            "n_words": 13,
            "vocab_size": 11,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 50301,
        "commit_id": "ffcde21305c61d950a9f93e57e6180c9a9665b87",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/resnet.py",
        "file_name": "resnet.py",
        "fun_name": "wide_resnet50_2",
        "commit_message": "add disco_diffusion_ernievil_base",
        "code": "def wide_resnet50_2(pretrained=False, **kwargs):\n    \n    kwargs['width'] = 64 * 2\n    return _resnet('wide_resnet50_2', BottleneckBlock, 50, pretrained, **kwargs)\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 23,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 33,
        "n_ast_nodes": 54,
        "n_identifiers": 5,
        "d_id": 10081,
        "documentation": {
            "docstring": "Wide ResNet-50-2 model from\n    `\"Wide Residual Networks\" <https://arxiv.org/pdf/1605.07146.pdf>`_.\n\n    Args:\n        pretrained (bool): If True, returns a model pre-trained on ImageNet\n\n    Examples:\n        .. code-block:: python\n\n            import paddle\n            from paddle.vision.models import wide_resnet50_2\n\n            # build model\n            model = wide_resnet50_2()\n\n            # build model and load imagenet pretrained weight\n            # model = wide_resnet50_2(pretrained=True)\n\n            x = paddle.rand([1, 3, 224, 224])\n            out = model(x)\n\n            print(out.shape)\n    ",
            "n_words": 57,
            "vocab_size": 43,
            "n_whitespaces": 182,
            "language": "en"
        }
    },
    {
        "id": 3305,
        "commit_id": "8fbf8ba2a5bfcdb892e8ca596e338894614000b5",
        "repo": "prophet",
        "path": "python/prophet/forecaster.py",
        "file_name": "forecaster.py",
        "fun_name": "piecewise_linear",
        "commit_message": "Speed Up Uncertainty Predictions (#2186)",
        "code": "def piecewise_linear(t, deltas, k, m, changepoint_ts):\n        \n        deltas_t = (changepoint_ts[None, :] <= t[..., None]) * deltas\n        k_t = deltas_t.sum(axis=1) + k\n        m_t = (deltas_t * -changepoint_ts).sum(axis=1) + m\n        return k_t * t + m_t\n",
        "url": "https://github.com/facebook/prophet.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 68,
        "n_words": 33,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 68,
        "n_ast_nodes": 103,
        "n_identifiers": 11,
        "d_id": 440,
        "documentation": {
            "docstring": "Evaluate the piecewise linear function.\n\n        Parameters\n        ----------\n        t: np.array of times on which the function is evaluated.\n        deltas: np.array of rate changes at each changepoint.\n        k: Float initial rate.\n        m: Float initial offset.\n        changepoint_ts: np.array of changepoint times.\n\n        Returns\n        -------\n        Vector y(t).\n        ",
            "n_words": 42,
            "vocab_size": 35,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 249768,
        "commit_id": "2bb2c32e8ed5642a5bf3ba1e8c49e10cecc88905",
        "repo": "synapse",
        "path": "tests/metrics/test_metrics.py",
        "file_name": "test_metrics.py",
        "fun_name": "test_cache_metric",
        "commit_message": "Avoid incrementing bg process utime/stime counters by negative durations (#14323)",
        "code": "def test_cache_metric(self):\n        \n        CACHE_NAME = \"cache_metrics_test_fgjkbdfg\"\n        cache: DeferredCache[str, str] = DeferredCache(CACHE_NAME, max_entries=777)\n\n        items = {\n            x.split(b\"{\")[0].decode(\"ascii\"): x.split(b\" \")[1].decode(\"ascii\")\n            for x in filter(\n                lambda x: b\"cache_metrics_test_fgjkbdfg\" in x,\n                generate_latest(REGISTRY).split(b\"\\n\"),\n            )\n        }\n\n        self.assertEqual(items[\"synapse_util_caches_cache_size\"], \"0.0\")\n        self.assertEqual(items[\"synapse_util_caches_cache_max_size\"], \"777.0\")\n\n        cache.prefill(\"1\", \"hi\")\n\n        items = {\n            x.split(b\"{\")[0].decode(\"ascii\"): x.split(b\" \")[1].decode(\"ascii\")\n            for x in filter(\n                lambda x: b\"cache_metrics_test_fgjkbdfg\" in x,\n                generate_latest(REGISTRY).split(b\"\\n\"),\n            )\n        }\n\n        self.assertEqual(items[\"synapse_util_caches_cache_size\"], \"1.0\")\n        self.assertEqual(items[\"synapse_util_caches_cache_max_size\"], \"777.0\")\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 267,
        "n_words": 57,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 198,
        "n_ast_nodes": 336,
        "n_identifiers": 16,
        "d_id": 73114,
        "documentation": {
            "docstring": "\n        Caches produce metrics reflecting their state when scraped.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 260207,
        "commit_id": "2e3a0474a6195161e7e3ff02be9d1ff18591ca7b",
        "repo": "scikit-learn",
        "path": "sklearn/datasets/tests/test_svmlight_format.py",
        "file_name": "test_svmlight_format.py",
        "fun_name": "test_multilabel_y_explicit_zeros",
        "commit_message": "ENH Cythonize `dump_svmlight_file` (#23127)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def test_multilabel_y_explicit_zeros(tmp_path):\n    \n    save_path = str(tmp_path / \"svm_explicit_zero\")\n    rng = np.random.RandomState(42)\n    X = rng.randn(3, 5).astype(np.float64)\n    indptr = np.array([0, 2, 3, 6])\n    indices = np.array([0, 2, 2, 0, 1, 2])\n    # The first and last element are explicit zeros.\n    data = np.array([0, 1, 1, 1, 1, 0])\n    y = sp.csr_matrix((data, indices, indptr), shape=(3, 3))\n    # y as a dense array would look like\n    # [[0, 0, 1],\n    #  [0, 0, 1],\n    #  [1, 1, 0]]\n\n    dump_svmlight_file(X, y, save_path, multilabel=True)\n\n    _, y_load = load_svmlight_file(save_path, multilabel=True)\n    y_true = [(2.0,), (2.0,), (0.0, 1.0)]\n    assert y_load == y_true\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 145,
        "n_words": 92,
        "vocab_size": 64,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 174,
        "n_ast_nodes": 244,
        "n_identifiers": 26,
        "d_id": 76118,
        "documentation": {
            "docstring": "\n    Ensure that if y contains explicit zeros (i.e. elements of y.data equal to\n    0) then those explicit zeros are not encoded.\n    ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 185071,
        "commit_id": "1013f84ffc67bdce04bf13eaf401ab5ced572bb0",
        "repo": "textual",
        "path": "src/textual/message.py",
        "file_name": "message.py",
        "fun_name": "handler_name",
        "commit_message": "diagrams",
        "code": "def handler_name(self) -> str:\n        \n        # Property to make it read only\n        return self._handler_name\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 34,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 12,
        "n_ast_nodes": 23,
        "n_identifiers": 4,
        "d_id": 44890,
        "documentation": {
            "docstring": "The name of the handler associated with this message.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 259175,
        "commit_id": "9d7220b57ccac4ac12268a96281940667a4de1d8",
        "repo": "scikit-learn",
        "path": "sklearn/datasets/_base.py",
        "file_name": "_base.py",
        "fun_name": "load_sample_image",
        "commit_message": "DOC changed some typo of _shrunk_covariance.ledoit_wolf_shrinkage (#22798)\n\n* Changed from 3rd to 1st person the 1st word and remote blanck space.\r\n\r\n* Add two periods in the content",
        "code": "def load_sample_image(image_name):\n    \n    images = load_sample_images()\n    index = None\n    for i, filename in enumerate(images.filenames):\n        if filename.endswith(image_name):\n            index = i\n            break\n    if index is None:\n        raise AttributeError(\"Cannot find sample image: %s\" % image_name)\n    return images.images[index]\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 87,
        "n_words": 33,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 57,
        "n_ast_nodes": 96,
        "n_identifiers": 11,
        "d_id": 75626,
        "documentation": {
            "docstring": "Load the numpy array of a single sample image.\n\n    Read more in the :ref:`User Guide <sample_images>`.\n\n    Parameters\n    ----------\n    image_name : {`china.jpg`, `flower.jpg`}\n        The name of the sample image loaded\n\n    Returns\n    -------\n    img : 3D array\n        The image as a numpy array: height x width x color.\n\n    Examples\n    --------\n\n    >>> from sklearn.datasets import load_sample_image\n    >>> china = load_sample_image('china.jpg')   # doctest: +SKIP\n    >>> china.dtype                              # doctest: +SKIP\n    dtype('uint8')\n    >>> china.shape                              # doctest: +SKIP\n    (427, 640, 3)\n    >>> flower = load_sample_image('flower.jpg') # doctest: +SKIP\n    >>> flower.dtype                             # doctest: +SKIP\n    dtype('uint8')\n    >>> flower.shape                             # doctest: +SKIP\n    (427, 640, 3)\n    ",
            "n_words": 95,
            "vocab_size": 58,
            "n_whitespaces": 288,
            "language": "en"
        }
    },
    {
        "id": 127777,
        "commit_id": "5bf9d5084fe38d864c1b5075145d2e778c431a5b",
        "repo": "ray",
        "path": "rllib/connectors/tests/test_agent.py",
        "file_name": "test_agent.py",
        "fun_name": "test_vr_connector_with_multiple_buffers",
        "commit_message": "[RLlib] Pass input dict into action connectors, because sometimes input data is useful for adapting output actions. (#28588)\n\nBased on user feedback. Input data is sometimes useful for adapting outputs, for example action masks.\r\n\r\nSigned-off-by: Jun Gong <jungong@anyscale.com>",
        "code": "def test_vr_connector_with_multiple_buffers(self):\n        \n        context_len = 5\n        # This view requirement simulates the use-case of a decision transformer\n        # without reward-to-go.\n        view_rq_dict = {\n            # obs[t-context_len+1:t]\n            \"context_obs\": ViewRequirement(\"obs\", shift=f\"-{context_len-1}:0\"),\n            # next_obs[t-context_len+1:t]\n            \"context_next_obs\": ViewRequirement(\n                \"obs\", shift=f\"-{context_len}:1\", used_for_compute_actions=False\n            ),\n            # act[t-context_len+1:t]\n            \"context_act\": ViewRequirement(\n                SampleBatch.ACTIONS, shift=f\"-{context_len-1}:-1\"\n            ),\n        }\n\n        obs_arrs = np.arange(10)[:, None] + 1\n        act_arrs = (np.arange(10)[:, None] + 1) * 100\n        n_steps = obs_arrs.shape[0]\n        config = PPOConfig().to_dict()\n        ctx = ConnectorContext(\n            view_requirements=view_rq_dict, config=config, is_policy_recurrent=True\n        )\n        c = ViewRequirementAgentConnector(ctx)\n\n        # keep a queue of length ctx_len of observations\n        obs_list, act_list = [], []\n        for t in range(n_steps):\n            # next state and action at time t-1 are the following\n            timestep_data = {\n                SampleBatch.NEXT_OBS: obs_arrs[t],\n                SampleBatch.ACTIONS: (\n                    np.zeros_like(act_arrs[0]) if t == 0 else act_arrs[t - 1]\n                ),\n                SampleBatch.T: t - 1,\n            }\n            data = AgentConnectorDataType(0, 1, timestep_data)\n            processed = c([data])\n            sample_batch = processed[0].data.sample_batch\n\n            if t == 0:\n                obs_list.extend([obs_arrs[0] for _ in range(context_len)])\n                act_list.extend(\n                    [np.zeros_like(act_arrs[0]) for _ in range(context_len)]\n                )\n            else:\n                obs_list.pop(0)\n                act_list.pop(0)\n                obs_list.append(obs_arrs[t])\n                act_list.append(act_arrs[t - 1])\n\n            self.assertTrue(\"context_next_obs\" not in sample_batch)\n            check(sample_batch[\"context_obs\"], np.stack(obs_list)[None])\n            check(sample_batch[\"context_act\"], np.stack(act_list[:-1])[None])\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 731,
        "n_words": 166,
        "vocab_size": 122,
        "complexity": 6,
        "nloc": 44,
        "token_counts": 349,
        "n_ast_nodes": 572,
        "n_identifiers": 43,
        "d_id": 28520,
        "documentation": {
            "docstring": "Test that the ViewRequirementAgentConnector can handle slice shifts correctly\n        when it has multiple buffers to shift.",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 176452,
        "commit_id": "cc1db275efc709cb964ce88abbfa877798d58c10",
        "repo": "networkx",
        "path": "networkx/utils/contextmanagers.py",
        "file_name": "contextmanagers.py",
        "fun_name": "reversed",
        "commit_message": "Minor improvements from general code readthrough (#5414)\n\n* Add deprecated directive to reversed docstring.\r\n\r\n* Add missing dep directives to shpfiles.\r\n\r\n* Remove defn of INF sentinel.\r\n\r\n* typo.\r\n\r\n* str -> comment in forloop.\r\n\r\n* STY: appropriate casing for var name.",
        "code": "def reversed(G):\n    \n    msg = (\n        \"context manager reversed is deprecated and to be removed in 3.0.\"\n        \"Use G.reverse(copy=False) if G.is_directed() else G instead.\"\n    )\n    warnings.warn(msg, DeprecationWarning)\n\n    directed = G.is_directed()\n    if directed:\n        G._pred, G._succ = G._succ, G._pred\n        G._adj = G._succ\n\n    try:\n        yield\n    finally:\n        if directed:\n            # Reverse the reverse.\n            G._pred, G._succ = G._succ, G._pred\n            G._adj = G._succ\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 155,
        "n_words": 56,
        "vocab_size": 40,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 82,
        "n_ast_nodes": 141,
        "n_identifiers": 11,
        "d_id": 41913,
        "documentation": {
            "docstring": "A context manager for temporarily reversing a directed graph in place.\n\n    .. deprecated:: 2.6\n\n       This context manager is deprecated and will be removed in 3.0.\n       Use ``G.reverse(copy=False) if G.is_directed() else G`` instead.\n\n    This is a no-op for undirected graphs.\n\n    Parameters\n    ----------\n    G : graph\n        A NetworkX graph.\n\n    Warning\n    -------\n    The reversed context manager is deprecated in favor\n    of G.reverse(copy=False). The view allows multiple threads to use the\n    same graph without confusion while the context manager does not.\n    This context manager is scheduled to be removed in version 3.0.\n    ",
            "n_words": 88,
            "vocab_size": 60,
            "n_whitespaces": 143,
            "language": "en"
        }
    },
    {
        "id": 158287,
        "commit_id": "b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2",
        "repo": "d2l-zh",
        "path": "d2l/tensorflow.py",
        "file_name": "tensorflow.py",
        "fun_name": "train_epoch_ch3",
        "commit_message": "[PaddlePaddle] Merge master into Paddle branch (#1186)\n\n* change 15.2 title in chinese version (#1109)\r\n\r\nchange title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘\r\n\r\n* 修改部分语义表述 (#1105)\r\n\r\n* Update r0.17.5 (#1120)\r\n\r\n* Bump versions in installation\r\n\r\n* 94行typo: （“bert.mall”）->（“bert.small”） (#1129)\r\n\r\n* line 313: \"bert.mall\" -> \"bert.small\" (#1130)\r\n\r\n* fix: update language as native reader (#1114)\r\n\r\n* Fix the translation of \"stride\" (#1115)\r\n\r\n* Update index.md (#1118)\r\n\r\n修改部分语义表述\r\n\r\n* Update self-attention-and-positional-encoding.md (#1133)\r\n\r\n依照本书的翻译习惯，将pooling翻译成汇聚\r\n\r\n* maybe a comment false (#1149)\r\n\r\n* maybe a little false\r\n\r\n* maybe a little false\r\n\r\n* A minor bug in the rcnn section (Chinese edition) (#1148)\r\n\r\n* Update bert.md (#1137)\r\n\r\n一个笔误\r\n# 假设batch_size=2，num_pred_positions=3\r\n# 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1]\r\n\r\n* Update calculus.md (#1135)\r\n\r\n* fix typo in git documentation (#1106)\r\n\r\n* fix: Update the Chinese translation in lr-scheduler.md (#1136)\r\n\r\n* Update lr-scheduler.md\r\n\r\n* Update chapter_optimization/lr-scheduler.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* fix translation for kaggle-house-price.md (#1107)\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\n* fix translation for kaggle-house-price.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\n\r\n* Update weight-decay.md (#1150)\r\n\r\n* Update weight-decay.md\r\n\r\n关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解\r\n关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。\r\n并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释\r\n解释为何会增加复杂性以及为何需要细粒度工具。\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/weight-decay.md\r\n\r\nyep\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Fix a spelling error (#1161)\r\n\r\n* Update gru.md (#1152)\r\n\r\nThe key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state.\r\n翻译错误\r\n\r\n* Unify the function naming (#1113)\r\n\r\nUnify naming of the function 'init_xavier()'.\r\n\r\n* Update mlp-concise.md (#1166)\r\n\r\n* Update mlp-concise.md\r\n\r\n语句不通顺\r\n\r\n* Update environment.md\r\n\r\n语序异常\r\n\r\n* Update config.ini\r\n\r\n* fix the imprecise description (#1168)\r\n\r\nCo-authored-by: yuande <yuande>\r\n\r\n* fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175)\r\n\r\n* Fix some typos. (#1163)\r\n\r\n* Update batch-norm.md (#1170)\r\n\r\nfixing typos u->x in article\r\n\r\n* Update linear-regression.md (#1090)\r\n\r\nWe invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that\r\n\r\n原译文把who也直接翻译出来了。\r\n\r\n* Update mlp.md (#1117)\r\n\r\n* Update mlp.md\r\n\r\n修改部分语义表述\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Update chapter_multilayer-perceptrons/mlp.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\n\r\n* Correct a translation error. (#1091)\r\n\r\n* Correct a translation error.\r\n\r\n* Update chapter_computer-vision/image-augmentation.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update aws.md (#1121)\r\n\r\n* Update aws.md\r\n\r\n* Update chapter_appendix-tools-for-deep-learning/aws.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update image-augmentation.md (#1093)\r\n\r\n* Update anchor.md (#1088)\r\n\r\nfix a minor issue in  code\r\n\r\n* Update anchor.md\r\n\r\n* Update image-augmentation.md\r\n\r\n* fix typo and improve translation in chapter_linear-networks\\softmax-regression.md (#1087)\r\n\r\n* Avoid `torch.meshgrid` user warning (#1174)\r\n\r\nAvoids the following user warning:\r\n```python\r\n~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2228.)\r\n  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\r\n```\r\n\r\n* bump to 2.0.0-beta1\r\n\r\n* Update sequence.md\r\n\r\n* bump beta1 on readme\r\n\r\n* Add latex code block background to config\r\n\r\n* BLD: Bump python support version 3.9 (#1183)\r\n\r\n* BLD: Bump python support version 3.9\r\n\r\n* Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4\r\n\r\n* BLD: Bump torch and tensorflow\r\n\r\n* Update Jenkinsfile\r\n\r\n* Update chapter_installation/index.md\r\n\r\n* Update chapter_installation/index.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Update config.ini\r\n\r\n* Update INFO.md\r\n\r\n* Update INFO.md\r\n\r\n* Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187)\r\n\r\n* resolve the conflicts\r\n\r\n* revise from publisher (#1089)\r\n\r\n* revise from publisher\r\n\r\n* d2l api\r\n\r\n* post_latex\r\n\r\n* revise from publisher\r\n\r\n* revise ch11\r\n\r\n* Delete d2l-Copy1.bib\r\n\r\n* clear cache\r\n\r\n* rm d2lbook clear\r\n\r\n* debug anchor\r\n\r\n* keep original d2l doc\r\n\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\n\r\n* 重复语句 (#1188)\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improve expression for chapter_preliminaries/pandas.md (#1184)\r\n\r\n* Update pandas.md\r\n\r\n* Improve expression\r\n\r\n* Improve expression\r\n\r\n* Update chapter_preliminaries/pandas.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Improce expression for chapter_preliminaries/linear-algebra.md (#1185)\r\n\r\n* Improce expression\r\n\r\n* Improve code comments\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\n* Update chapter_preliminaries/linear-algebra.md\r\n\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\n\r\n* Fix multibox_detection bugs\r\n\r\n* Update d2l to 0.17.5 version\r\n\r\n* restore older version\r\n\r\n* Upgrade pandas\r\n\r\n* change to python3.8\r\n\r\n* Test warning log\r\n\r\n* relocate  warning log\r\n\r\n* test logs filtering\r\n\r\n* Update gru.md\r\n\r\n* Add DeprecationWarning filter\r\n\r\n* Test warning log\r\n\r\n* Update attention mechanisms & computational performance\r\n\r\n* Update multilayer perceptron& linear & convolution networks & computer vision\r\n\r\n* Update recurrent&optimition&nlp pretraining & nlp applications\r\n\r\n* ignore warnings\r\n\r\n* Update index.md\r\n\r\n* Update linear networks\r\n\r\n* Update multilayer perceptrons&deep learning computation\r\n\r\n* Update preliminaries\r\n\r\n* Check and Add warning filter\r\n\r\n* Update kaggle-cifar10.md\r\n\r\n* Update object-detection-dataset.md\r\n\r\n* Update ssd.md fcn.md\r\n\r\n* Update hybridize.md\r\n\r\n* Update hybridize.md\r\n\r\nSigned-off-by: sunhaizhou <haizhou.sun@smartmore.com>\r\nCo-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com>\r\nCo-authored-by: Xinwei Liu <xinzone@outlook.com>\r\nCo-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com>\r\nCo-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com>\r\nCo-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com>\r\nCo-authored-by: gyro永不抽风 <1247006353@qq.com>\r\nCo-authored-by: CanChengZheng <zcc550169544@163.com>\r\nCo-authored-by: linlin <jajupmochi@gmail.com>\r\nCo-authored-by: iuk <liukun0104@gmail.com>\r\nCo-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com>\r\nCo-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com>\r\nCo-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com>\r\nCo-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com>\r\nCo-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com>\r\nCo-authored-by: Ming Liu <akira.liu@njnu.edu.cn>\r\nCo-authored-by: goldmermaid <goldpiggy@berkeley.edu>\r\nCo-authored-by: silenceZheng66 <13754430639@163.com>\r\nCo-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com>\r\nCo-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com>\r\nCo-authored-by: Krahets <krahets@163.com>\r\nCo-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com>\r\nCo-authored-by: Jameson <miraclecome@gmail.com>\r\nCo-authored-by: P. Yao <12227516+YaoPengCN@users.noreply.github.com>\r\nCo-authored-by: Yulv-git <34329208+Yulv-git@users.noreply.github.com>\r\nCo-authored-by: Liu,Xiao <45966993+liuxiao916@users.noreply.github.com>\r\nCo-authored-by: YIN, Gang <1246410+yingang@users.noreply.github.com>\r\nCo-authored-by: Joe-HZ <58297431+Joe-HZ@users.noreply.github.com>\r\nCo-authored-by: lybloveyou <102609904+lybloveyou@users.noreply.github.com>\r\nCo-authored-by: VigourJiang <jiangfuqiang154@163.com>\r\nCo-authored-by: zxhd863943427 <74853597+zxhd863943427@users.noreply.github.com>\r\nCo-authored-by: LYF <27893441+liyufan@users.noreply.github.com>\r\nCo-authored-by: Aston Zhang <asv325@gmail.com>\r\nCo-authored-by: xiaotinghe <xiaotih@amazon.com>\r\nCo-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal>\r\nCo-authored-by: Holly-Max <60691735+Holly-Max@users.noreply.github.com>\r\nCo-authored-by: HinGwenWoong <peterhuang0323@qq.com>\r\nCo-authored-by: Shuai Zhang <cheungdaven@gmail.com>",
        "code": "def train_epoch_ch3(net, train_iter, loss, updater):\n    \n    # Sum of training loss, sum of training accuracy, no. of examples\n    metric = Accumulator(3)\n    for X, y in train_iter:\n        # Compute gradients and update parameters\n        with tf.GradientTape() as tape:\n            y_hat = net(X)\n            # Keras implementations for loss takes (labels, predictions)\n            # instead of (predictions, labels) that users might implement\n            # in this book, e.g. `cross_entropy` that we implemented above\n            if isinstance(loss, tf.keras.losses.Loss):\n                l = loss(y, y_hat)\n            else:\n                l = loss(y_hat, y)\n        if isinstance(updater, tf.keras.optimizers.Optimizer):\n            params = net.trainable_variables\n            grads = tape.gradient(l, params)\n            updater.apply_gradients(zip(grads, params))\n        else:\n            updater(X.shape[0], tape.gradient(l, updater.params))\n        # Keras loss by default returns the average loss in a batch\n        l_sum = l * float(tf.size(y)) if isinstance(\n            loss, tf.keras.losses.Loss) else tf.reduce_sum(l)\n        metric.add(l_sum, accuracy(y_hat, y), tf.size(y))\n    # Return training loss and training accuracy\n    return metric[0] / metric[2], metric[1] / metric[2]\n",
        "url": "https://github.com/d2l-ai/d2l-zh.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 352,
        "n_words": 134,
        "vocab_size": 98,
        "complexity": 5,
        "nloc": 19,
        "token_counts": 207,
        "n_ast_nodes": 324,
        "n_identifiers": 33,
        "d_id": 37440,
        "documentation": {
            "docstring": "The training loop defined in Chapter 3.\n\n    Defined in :numref:`sec_softmax_scratch`",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 200512,
        "commit_id": "af443377dd48c2caf440d2b6dd76830dbe84712f",
        "repo": "sympy",
        "path": "sympy/integrals/transforms.py",
        "file_name": "transforms.py",
        "fun_name": "_laplace_apply_rules",
        "commit_message": "Moved all constant-factor calculations to `_laplace_apply_rules`",
        "code": "def _laplace_apply_rules(f, t, s, doit=True, **hints):\n    \n\n    k, func = f.as_independent(t, as_Add=False)\n\n    simple_rules = _laplace_build_rules(t, s)\n    for t_dom, s_dom, check, plane, prep in simple_rules:\n        ma = prep(func).match(t_dom)\n        if ma:\n            debug('_laplace_apply_rules match:')\n            debug('      f:    %s'%(func,))\n            debug('      rule: %s o---o %s'%(t_dom, s_dom))\n            try:\n                debug('      try   %s'%(check,))\n                c = check.xreplace(ma)\n                debug('      check %s -> %s'%(check, c))\n                if c==True:\n                    return _laplace_cr(k*s_dom.xreplace(ma),\n                                plane.xreplace(ma), S.true, **hints)\n            except Exception:\n                debug('_laplace_apply_rules did not match.')\n    if f.has(DiracDelta):\n        return None\n\n    prog_rules = [_laplace_rule_timescale, _laplace_rule_heaviside,\n                  _laplace_rule_exp, _laplace_rule_trig, _laplace_rule_diff]\n    for p_rule in prog_rules:\n        LT = p_rule(func, t, s, doit=doit, **hints)\n        if LT is not None:\n            try:\n                r, p, c = LT\n                return (k*r, p, c)\n            except TypeError:\n                return k*LT\n            return LT\n    return None\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 469,
        "n_words": 110,
        "vocab_size": 77,
        "complexity": 9,
        "nloc": 32,
        "token_counts": 237,
        "n_ast_nodes": 365,
        "n_identifiers": 39,
        "d_id": 49680,
        "documentation": {
            "docstring": "\n    Helper function for the class LaplaceTransform.\n\n    This function does a Laplace transform based on rules and, after\n    applying the rules, hands the rest over to `_laplace_transform`, which\n    will attempt to integrate.\n\n    If it is called with `doit=False`, then it will instead return\n    `LaplaceTransform` objects.\n    ",
            "n_words": 44,
            "vocab_size": 38,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 2719,
        "commit_id": "e272ed2fa4c58e0a89e273a3e85da7d13a85e04c",
        "repo": "PySyft",
        "path": "packages/syft/src/syft/core/node/common/action/smpc_action_seq_batch_message.py",
        "file_name": "smpc_action_seq_batch_message.py",
        "fun_name": "_object2proto",
        "commit_message": "[syft.core.node.common.action] Change syft import absolute -> relative",
        "code": "def _object2proto(self) -> SMPCActionSeqBatchMessage_PB:\n        \n\n        return SMPCActionSeqBatchMessage_PB(\n            smpc_actions=list(map(lambda x: serialize(x), self.smpc_actions)),\n            address=serialize(self.address),\n            msg_id=serialize(self.id),\n        )\n",
        "url": "https://github.com/OpenMined/PySyft.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 67,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 50,
        "n_ast_nodes": 79,
        "n_identifiers": 11,
        "d_id": 349,
        "documentation": {
            "docstring": "Returns a protobuf serialization of self.\n\n        As a requirement of all objects which inherit from Serializable,\n        this method transforms the current object into the corresponding\n        Protobuf object so that it can be further serialized.\n\n        :return: returns a protobuf object\n        :rtype: SMPCActionSeqBatchMessage_PB\n\n        .. note::\n            This method is purely an internal method. Please use serialize(object) or one of\n            the other public serialization methods if you wish to serialize an\n            object.\n        ",
            "n_words": 68,
            "vocab_size": 56,
            "n_whitespaces": 150,
            "language": "en"
        }
    },
    {
        "id": 127405,
        "commit_id": "203253321d34543aa25483803ebc21e3903679b6",
        "repo": "ray",
        "path": "python/ray/serve/experimental/gradio_visualize_graph.py",
        "file_name": "gradio_visualize_graph.py",
        "fun_name": "postprocessing",
        "commit_message": "[serve] Add additional features to DAG visualization with Gradio (#28246)",
        "code": "def postprocessing(data):\n    \n\n    if type_to_string(type(data)) == \"torch.Tensor\":\n        try:\n            import torch\n            from torchvision import transforms\n\n            # By default Torch tensors are displayed as images. To display them as JSON,\n            # the user can simply convert them to numpy arrays.\n            transformer = transforms.ToPILImage()\n            return transformer(torch.squeeze(data))\n        except ModuleNotFoundError:\n            logger.warning(\n                \"Module `torchvision` isn't installed, unable to process torch tensor.\"\n            )\n            return data\n\n    return data\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 196,
        "n_words": 59,
        "vocab_size": 50,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 55,
        "n_ast_nodes": 101,
        "n_identifiers": 13,
        "d_id": 28435,
        "documentation": {
            "docstring": "Add support for types that are not supported by Gradio.\n\n    Some data types like PyTorch tensors, cannot be processed and displayed through\n    Gradio. Thus we extend support to these data types by transforming them into a form\n    that Gradio can process and display.\n    ",
            "n_words": 43,
            "vocab_size": 35,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 285679,
        "commit_id": "72b0a9f1ee8b91ad9fd9e76d80d2ccab51ee6d21",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/cryptocurrency/defi/terraengineer_model.py",
        "file_name": "terraengineer_model.py",
        "fun_name": "get_anchor_yield_reserve",
        "commit_message": "Next release : reports on steroids (#2349)\n\n* fix gov tests\r\n\r\n* refactor insider\r\n\r\n* new virtual path extraction\r\n\r\n* removed some symbol default params as they're considered critical\r\n\r\n* little adjustments\r\n\r\n* portfolio refactor\r\n\r\n* merge API factory\r\n\r\n* add helpers, stocks, crypto, forex\r\n\r\n* minor forex changes\r\n\r\n* include forex api paths\r\n\r\n* add 2 missing forex funcs\r\n\r\n* portfolio brokers refactor\r\n\r\n* display help on api func call\r\n\r\n* add econometrics virtual paths to api\r\n\r\n* add api unit test\r\n\r\n* fixed report for the new api\r\n\r\n* minor portfolio refactorings\r\n\r\n* added gdapps\r\n\r\n* anchor_yield path\r\n\r\n* some more crypto path fixes\r\n\r\n* small change\r\n\r\n* fixed wrong param\r\n\r\n* minor fixes\r\n\r\n* wip - inital commit for forex report\r\n\r\n* add bw as a model, we'll get better solution afterwards\r\n\r\n* added ema with dummy model as it adds great functionality to the report\r\n\r\n* minor fixes\r\n\r\n* wip - added functions to forex report\r\n\r\n* add feedparser news path\r\n\r\n* add new virtual paths to api\r\n\r\n* adding commands to equity report\r\n\r\n* revert to old paths, new ones were breaking\r\n\r\n* Add in very basic ETF report\r\n\r\n* Add candle chart to ETF report\r\n\r\n* add etf load\r\n\r\n* allow use of candle without data\r\n\r\n* add raw to candle\r\n\r\n* added forex report\r\n\r\n* ongoing equity report\r\n\r\n* equity report change\r\n\r\n* fix some portfolio bugs and add docstrings\r\n\r\n* include portfolio paths and coin class\r\n\r\n* add crypto paths\r\n\r\n* change event dates to str\r\n\r\n* starting economy report\r\n\r\n* window for limit\r\n\r\n* equity report and refactor newsapi\r\n\r\n* add helper to api\r\n\r\n* update on economy report\r\n\r\n* equity report\r\n\r\n* update economy report\r\n\r\n* refactor some docstrings\r\n\r\n* change maturities helper\r\n\r\n* refactor newsapi\r\n\r\n* refactor futures command\r\n\r\n* add some sauce to ycrv plot\r\n\r\n* black\r\n\r\n* update report\r\n\r\n* refactor alphavantage\r\n\r\n* refactor wsj\r\n\r\n* update economy report\r\n\r\n* ycrv tenor\r\n\r\n* map avaiable_indices\r\n\r\n* map economy helpers\r\n\r\n* fix econdb docstring\r\n\r\n* add plots on economy report\r\n\r\n* minor fixes\r\n\r\n* wip - crypto report\r\n\r\n* update economy report\r\n\r\n* added same default args as view\r\n\r\n* added view to explicity use chart=True when suing the api\r\n\r\n* adjustments - removed rich tables to use only df\r\n\r\n* final version economy report\r\n\r\n* change report name\r\n\r\n* equity report for review\r\n\r\n* linting\r\n\r\n* add etf symbols endpoint\r\n\r\n* incorporate feedback economy report\r\n\r\n* fix reports launch by adding tag to economy report\r\n\r\n* fix equity bug\r\n\r\n* remove analyst name\r\n\r\n* fix\r\n\r\n* fix news\r\n\r\n* make links hyperlinks for equity\r\n\r\n* click links\r\n\r\n* fixed arg name\r\n\r\n* improved news\r\n\r\n* small improves\r\n\r\n* Fix light terminal stylesheet that would prevent using it in notebooks (#2473)\r\n\r\n* improved report\r\n\r\n* run reports in installer\r\n\r\n* fix #2209\r\n\r\n* minor ycrv refactoring\r\n\r\n* refactor portfolio/holdv virtual path\r\n\r\n* refactor benchmark trades\r\n\r\n* fix events args\r\n\r\n* adapt economy report to changes\r\n\r\n* fix portfolio controller bug\r\n\r\n* holdv refactor\r\n\r\n* refactor perf command\r\n\r\n* start portfolio report\r\n\r\n* remove perf view\r\n\r\n* refactor holp\r\n\r\n* add textwrap3 to poetry (doesn't solve the error)\r\n\r\n* fix equity after merge\r\n\r\n* add some rolling commands\r\n\r\n* fix equity after save button\r\n\r\n* improved crypto report, plus minor fixes\r\n\r\n* minor fixes on the reports\r\n\r\n* add maxdd and distr\r\n\r\n* refactor qa\r\n\r\n* var command\r\n\r\n* refactor qa expected shortfall\r\n\r\n* add es command\r\n\r\n* add es command\r\n\r\n* fix qa percentile bug\r\n\r\n* fix economy rendering\r\n\r\n* refactor qa omega\r\n\r\n* add om command\r\n\r\n* add summary command\r\n\r\n* add dret command\r\n\r\n* add mret command\r\n\r\n* add yret command\r\n\r\n* add metrics\r\n\r\n* add allocs to report\r\n\r\n* remove bro and po commands, add later\r\n\r\n* fixed some tests\r\n\r\n* adjustments to crypto report\r\n\r\n* Fix docstring for VSCode\r\n\r\nAdded a note about installing Jupyter PowerToys extension for optimal API usage in Jupyter VSCode, in the API_README.md.\r\n\r\n* minor adjustment\r\n\r\n* remove nft calendar model virtual paths\r\n\r\n* Add in Portfolio report\r\n\r\n* fix external axes portfolio view\r\n\r\n* Update portfolio report with rolling plots\r\n\r\n* Details for ETF and Portfolio\r\n\r\n* fix economy report\r\n\r\n* change analyst to openbb\r\n\r\n* floppy\r\n\r\n* fixed unmatched axis in reports\r\n\r\n* Speed up tests\r\n\r\n* fix file and load on po\r\n\r\n* get_news output\r\n\r\n* add some po paths\r\n\r\n* Add integration tests for Reports menu\r\n\r\n* refactor maxsharpe\r\n\r\n* open maxsharpe\r\n\r\n* open minrisk\r\n\r\n* open maxutil\r\n\r\n* open maxret\r\n\r\n* Added fixes\r\n\r\n* black\r\n\r\n* remove useless views\r\n\r\n* Fixed small issue\r\n\r\n* refactor ef\r\n\r\n* open ef api\r\n\r\n* portfolio optimization report\r\n\r\n* Added fixes\r\n\r\n* unblock api loading\r\n\r\n* add more endpoints\r\n\r\n* update po report\r\n\r\n* unblock api loading\r\n\r\n* update po report\r\n\r\n* expose herc\r\n\r\n* expose property endpoint\r\n\r\n* Added fixes\r\n\r\n* More api fixes\r\n\r\n* flake8\r\n\r\n* Fixed some mypy\r\n\r\n* news api model\r\n\r\n* flake8\r\n\r\n* mypy fix\r\n\r\n* mypy\r\n\r\n* black\r\n\r\n* pylint\r\n\r\n* fix tests\r\n\r\n* markdown\r\n\r\n* markdown\r\n\r\n* Added fixes\r\n\r\n* fix economy report\r\n\r\n* merge\r\n\r\n* fix economy report\r\n\r\n* remove empty notebook\r\n\r\n* expose nco\r\n\r\n* remove jupyter notebook\r\n\r\n* expose plot endpoint\r\n\r\n* remove po report, just used for tests\r\n\r\n* api v paths plot\r\n\r\n* remove api_old\r\n\r\n* change loading msg\r\n\r\nCo-authored-by: montezdesousa <montezdesousa@gmail.com>\r\nCo-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>\r\nCo-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>\r\nCo-authored-by: Om Gupta <guptagom@gmail.com>\r\nCo-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com>\r\nCo-authored-by: JerBouma <jer.bouma@gmail.com>\r\nCo-authored-by: Theodore Aptekarev <aptekarev@gmail.com>\r\nCo-authored-by: Om Gupta <85685255+soggyomelette@users.noreply.github.com>\r\nCo-authored-by: Diogo Sousa <diogosousa@Diogos-MBP.lan>\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: northern-64bit <75195383+northern-64bit@users.noreply.github.com>\r\nCo-authored-by: colin99d <colin99delahunty@gmail.com>\r\nCo-authored-by: Minh Hoang <nminh.hoang1023@gmail.com>",
        "code": "def get_anchor_yield_reserve() -> pd.DataFrame:\n    \n\n    df = get_history_asset_from_terra_address(\n        address=\"terra1tmnqgvg567ypvsvk6rwsga3srp7e3lg6u0elp8\"\n    )\n    return df\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 30,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 19,
        "n_ast_nodes": 36,
        "n_identifiers": 6,
        "d_id": 85377,
        "documentation": {
            "docstring": "Displays the 30-day history of the Anchor Yield Reserve.\n    [Source: https://terra.engineer/]\n\n    Returns\n    ----------\n    pd.DataFrame\n        Dataframe containing historical data\n    ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 256958,
        "commit_id": "ac5617e757e9ace6f30b7291686d9dbbc339f433",
        "repo": "haystack",
        "path": "haystack/telemetry.py",
        "file_name": "telemetry.py",
        "fun_name": "disable_telemetry",
        "commit_message": "Add basic telemetry features (#2314)\n\n* add basic telemetry features\r\n\r\n* change pipeline_config to _component_config\r\n\r\n* Update Documentation & Code Style\r\n\r\n* add super().__init__() calls to error classes\r\n\r\n* make posthog mock work with python 3.7\r\n\r\n* Update Documentation & Code Style\r\n\r\n* update link to docs web page\r\n\r\n* log exceptions, send event for raised HaystackErrors, refactor Path(CONFIG_PATH)\r\n\r\n* add comment on send_event in BaseComponent.init() and fix mypy\r\n\r\n* mock NonPrivateParameters and fix pylint undefined-variable\r\n\r\n* Update Documentation & Code Style\r\n\r\n* check model path contains multiple /\r\n\r\n* add test for writing to file\r\n\r\n* add test for en-/disable telemetry\r\n\r\n* Update Documentation & Code Style\r\n\r\n* merge file deletion methods and ignore pylint global statement\r\n\r\n* Update Documentation & Code Style\r\n\r\n* set env variable in demo to activate telemetry\r\n\r\n* fix mock of HAYSTACK_TELEMETRY_ENABLED\r\n\r\n* fix mypy and linter\r\n\r\n* add CI as env variable to execution contexts\r\n\r\n* remove threading, add test for custom error event\r\n\r\n* Update Documentation & Code Style\r\n\r\n* simplify config/log file deletion\r\n\r\n* add test for final event being sent\r\n\r\n* force writing config file in test\r\n\r\n* make test compatible with python 3.7\r\n\r\n* switch to posthog production server\r\n\r\n* Update Documentation & Code Style\r\n\r\nCo-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>",
        "code": "def disable_telemetry():\n    \n    os.environ[HAYSTACK_TELEMETRY_ENABLED] = \"False\"\n    logger.info(\"Telemetry has been disabled.\")\n\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 18,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 19,
        "n_ast_nodes": 38,
        "n_identifiers": 6,
        "d_id": 74975,
        "documentation": {
            "docstring": "\n    Disables telemetry so that no events are sent anymore, except for one final event.\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 196069,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/free_groups.py",
        "file_name": "free_groups.py",
        "fun_name": "cyclic_reduction",
        "commit_message": "Updated import locations",
        "code": "def cyclic_reduction(self, removed=False):\n        \n        word = self.copy()\n        g = self.group.identity\n        while not word.is_cyclically_reduced():\n            exp1 = abs(word.exponent_syllable(0))\n            exp2 = abs(word.exponent_syllable(-1))\n            exp = min(exp1, exp2)\n            start = word[0]**abs(exp)\n            end = word[-1]**abs(exp)\n            word = start**-1*word*end**-1\n            g = g*start\n        if removed:\n            return word, g\n        return word\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 171,
        "n_words": 41,
        "vocab_size": 28,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 113,
        "n_ast_nodes": 184,
        "n_identifiers": 17,
        "d_id": 47569,
        "documentation": {
            "docstring": "Return a cyclically reduced version of the word. Unlike\n        `identity_cyclic_reduction`, this will not cyclically permute\n        the reduced word - just remove the \"unreduced\" bits on either\n        side of it. Compare the examples with those of\n        `identity_cyclic_reduction`.\n\n        When `removed` is `True`, return a tuple `(word, r)` where\n        self `r` is such that before the reduction the word was either\n        `r*word*r**-1`.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import free_group\n        >>> F, x, y = free_group(\"x, y\")\n        >>> (x**2*y**2*x**-1).cyclic_reduction()\n        x*y**2\n        >>> (x**-3*y**-1*x**5).cyclic_reduction()\n        y**-1*x**2\n        >>> (x**-3*y**-1*x**5).cyclic_reduction(removed=True)\n        (y**-1*x**2, x**-3)\n\n        ",
            "n_words": 83,
            "vocab_size": 66,
            "n_whitespaces": 209,
            "language": "en"
        }
    },
    {
        "id": 221122,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/bdb.py",
        "file_name": "bdb.py",
        "fun_name": "clear_bpbynumber",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def clear_bpbynumber(self, arg):\n        \n        try:\n            bp = self.get_bpbynumber(arg)\n        except ValueError as err:\n            return str(err)\n        bp.deleteMe()\n        self._prune_breaks(bp.file, bp.line)\n        return None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 82,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 47,
        "n_ast_nodes": 79,
        "n_identifiers": 12,
        "d_id": 56223,
        "documentation": {
            "docstring": "Delete a breakpoint by its index in Breakpoint.bpbynumber.\n\n        If arg is invalid, return an error message.\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 47369,
        "commit_id": "de3bf06863714c6c02ad0c7f5999c961b382bf4a",
        "repo": "airflow",
        "path": "tests/jobs/test_backfill_job.py",
        "file_name": "test_backfill_job.py",
        "fun_name": "test_mapped_dag_pre_existing_tis",
        "commit_message": "Ensure that BackfillJob re-runs existing mapped task instances (#22952)\n\n* Ensure that BackfillJob re-runs existing mapped task instances\r\n\r\n`expand_mapped_task` only returns _new_ TaskInstances, so if a backfill\r\njob was run for a dag that already existed the mapped task would never\r\nbe executed.\r\n\r\n* Fix tests for changed interface\r\n\r\nThis interface also isn't the best, and we could probably do with\r\nrefactoring it. Not now though",
        "code": "def test_mapped_dag_pre_existing_tis(self, dag_maker, session):\n        \n        from airflow.decorators import task\n        from airflow.operators.python import PythonOperator\n\n        list_result = [[1], [2], [{'a': 'b'}]]\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 46,
        "n_words": 18,
        "vocab_size": 16,
        "complexity": 3,
        "nloc": 61,
        "token_counts": 487,
        "n_ast_nodes": 68,
        "n_identifiers": 11,
        "d_id": 9086,
        "documentation": {
            "docstring": "If the DagRun already some mapped TIs, ensure that we re-run them successfully",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 151789,
        "commit_id": "5a4e99b413f84f818662cc3012819db76aec47c1",
        "repo": "freqtrade",
        "path": "freqtrade/optimize/backtesting.py",
        "file_name": "backtesting.py",
        "fun_name": "_collate_rejected",
        "commit_message": "Add support for collating and analysing rejected trades in backtest",
        "code": "def _collate_rejected(self, pair, row):\n        \n        # It could be fun to enable hyperopt mode to write\n        # a loss function to reduce rejected signals\n        if (self.config.get('export', 'none') == 'signals' and\n                self.dataprovider.runmode == RunMode.BACKTEST):\n            if pair not in self.rejected_dict:\n                self.rejected_dict[pair] = []\n            self.rejected_dict[pair].append([row[DATE_IDX], row[ENTER_TAG_IDX]])\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 122,
        "n_words": 42,
        "vocab_size": 37,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 74,
        "n_ast_nodes": 120,
        "n_identifiers": 14,
        "d_id": 35136,
        "documentation": {
            "docstring": "\n        Temporarily store rejected trade information for downstream use in backtesting_analysis\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 43181,
        "commit_id": "e29543ec00c0a3eae7a789cb49350499c3b584c2",
        "repo": "airflow",
        "path": "airflow/www/views.py",
        "file_name": "views.py",
        "fun_name": "not_found",
        "commit_message": "Use `get_hostname` instead of `socket.getfqdn` (#24260)\n\nWe allow users to configure a different function to determine the\r\nhostname, so we should use that consistently when we need the hostname.",
        "code": "def not_found(error):\n    \n    return (\n        render_template(\n            'airflow/not_found.html',\n            hostname=get_hostname()\n            if conf.getboolean('webserver', 'EXPOSE_HOSTNAME', fallback=True)\n            else 'redact',\n        ),\n        404,\n    )\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 90,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 38,
        "n_ast_nodes": 65,
        "n_identifiers": 8,
        "d_id": 7853,
        "documentation": {
            "docstring": "Show Not Found on screen for any error in the Webserver",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 251116,
        "commit_id": "56eea20f6389b751d38079fb09b29237a0d2b262",
        "repo": "mitmproxy",
        "path": "test/mitmproxy/proxy/layers/http/test_http.py",
        "file_name": "test_http.py",
        "fun_name": "test_http_proxy_relative_request_no_host_header",
        "commit_message": "tutils: add BytesMatching placeholder",
        "code": "def test_http_proxy_relative_request_no_host_header(tctx):\n    \n    assert (\n            Playbook(http.HttpLayer(tctx, HTTPMode.regular), hooks=False)\n            >> DataReceived(tctx.client, b\"GET / HTTP/1.1\\r\\n\\r\\n\")\n            << SendData(tctx.client, BytesMatching(b\"400 Bad Request.+\"\n                                                      b\"HTTP request has no host header, destination unknown.\"))\n            << CloseConnection(tctx.client)\n    )\n\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 134,
        "n_words": 28,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 61,
        "n_ast_nodes": 96,
        "n_identifiers": 13,
        "d_id": 73596,
        "documentation": {
            "docstring": "Test handling of a relative-form \"GET /\" in regular proxy mode, but without a host header.",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 214304,
        "commit_id": "04eb35c234de59d4a47848a4f85cb5be3c58c24e",
        "repo": "flair",
        "path": "flair/models/sandbox/prototypical_decoder/distance/hyperbolic.py",
        "file_name": "hyperbolic.py",
        "fun_name": "project",
        "commit_message": "Added prototypical decoder",
        "code": "def project(x):\n    \n    return torch.cat([torch.sqrt(1.0 + torch.sum(x * x, 1, keepdim=True)), x], 1)\n\n",
        "url": "https://github.com/flairNLP/flair.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 18,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 41,
        "n_ast_nodes": 60,
        "n_identifiers": 7,
        "d_id": 53731,
        "documentation": {
            "docstring": "Project onto the hyeprboloid embedded in in n+1 dimensions.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 130594,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/data/extensions/tensor_extension.py",
        "file_name": "tensor_extension.py",
        "fun_name": "_create_method",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _create_method(cls, op, coerce_to_dtype=True, result_dtype=None):\n        \n\n        # NOTE(Clark): This overrides, but coerce_to_dtype, result_dtype might\n        # not be needed\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 38,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 31,
        "n_ast_nodes": 27,
        "n_identifiers": 5,
        "d_id": 29321,
        "documentation": {
            "docstring": "\n        Add support for binary operators by unwrapping, applying, and\n        rewrapping.\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 264061,
        "commit_id": "2b2559af1c7790596e7b2040f48e56baef608f9d",
        "repo": "pyinstaller",
        "path": "PyInstaller/utils/hooks/tcl_tk.py",
        "file_name": "tcl_tk.py",
        "fun_name": "_collect_tcl_modules",
        "commit_message": "hookutils: tcl/tk: port to PyInstaller.isolated framework",
        "code": "def _collect_tcl_modules(tcl_root):\n    \n\n    # Obtain Tcl major version.\n    tcl_major_version = tcl_version.split('.')[0]\n\n    modules_dirname = f\"tcl{tcl_major_version}\"\n    modules_path = os.path.join(tcl_root, '..', modules_dirname)\n\n    if not os.path.isdir(modules_path):\n        logger.warning('Tcl modules directory %s does not exist.', modules_path)\n        return []\n\n    return Tree(modules_path, prefix=modules_dirname)\n\n",
        "url": "https://github.com/pyinstaller/pyinstaller.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 69,
        "n_words": 34,
        "vocab_size": 30,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 66,
        "n_ast_nodes": 116,
        "n_identifiers": 15,
        "d_id": 77582,
        "documentation": {
            "docstring": "\n    Get a list of TOC-style 3-tuples describing Tcl modules. The modules directory is separate from the library/data\n    one, and is located at $tcl_root/../tclX, where X is the major Tcl version.\n\n    Returns\n    -------\n    Tree\n        Such list, if the modules directory exists.\n    ",
            "n_words": 40,
            "vocab_size": 33,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 275141,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/mixed_precision/policy.py",
        "file_name": "policy.py",
        "fun_name": "policy_scope",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def policy_scope(policy):\n    \n    old_policy = _global_policy\n    try:\n        set_global_policy(policy)\n        yield\n    finally:\n        set_global_policy(old_policy)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 22,
        "n_ast_nodes": 43,
        "n_identifiers": 5,
        "d_id": 81316,
        "documentation": {
            "docstring": "A context manager that sets the global Policy under it.\n\n    Args:\n      policy: A Policy, or a string that will be converted to a Policy..\n\n    Yields:\n      Nothing.\n    ",
            "n_words": 26,
            "vocab_size": 23,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 177539,
        "commit_id": "247231f0154badc4a07b6a4ceb40148ea18f264b",
        "repo": "networkx",
        "path": "networkx/algorithms/swap.py",
        "file_name": "swap.py",
        "fun_name": "directed_edge_swap",
        "commit_message": "Bug fix in swap: directed_edge_swap and double_edge_swap  (#6149)\n\n* raise exception if graph has no edges and test for that\r\n\r\n* Simplify code: raise exception if G has less than 3 edges\r\n\r\n* add correction\r\n\r\n* Solved bug in double_edge_swap and added tests for that. Also updated the doc entry\r\n\r\n* Update networkx/algorithms/swap.py\r\n\r\n* Added some final suggestions\r\n\r\n* add merge suggestions\r\n\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def directed_edge_swap(G, *, nswap=1, max_tries=100, seed=None):\n    \n    if nswap > max_tries:\n        raise nx.NetworkXError(\"Number of swaps > number of tries allowed.\")\n    if len(G) < 4:\n        raise nx.NetworkXError(\"DiGraph has fewer than four nodes.\")\n    if len(G.edges) < 3:\n        raise nx.NetworkXError(\"DiGraph has fewer than 3 edges\")\n\n    # Instead of choosing uniformly at random from a generated edge list,\n    # this algorithm chooses nonuniformly from the set of nodes with\n    # probability weighted by degree.\n    tries = 0\n    swapcount = 0\n    keys, degrees = zip(*G.degree())  # keys, degree\n    cdf = nx.utils.cumulative_distribution(degrees)  # cdf of degree\n    discrete_sequence = nx.utils.discrete_sequence\n\n    while swapcount < nswap:\n        # choose source node index from discrete distribution\n        start_index = discrete_sequence(1, cdistribution=cdf, seed=seed)[0]\n        start = keys[start_index]\n        tries += 1\n\n        if tries > max_tries:\n            msg = f\"Maximum number of swap attempts ({tries}) exceeded before desired swaps achieved ({nswap}).\"\n            raise nx.NetworkXAlgorithmError(msg)\n\n        # If the given node doesn't have any out edges, then there isn't anything to swap\n        if G.out_degree(start) == 0:\n            continue\n        second = seed.choice(list(G.succ[start]))\n        if start == second:\n            continue\n\n        if G.out_degree(second) == 0:\n            continue\n        third = seed.choice(list(G.succ[second]))\n        if second == third:\n            continue\n\n        if G.out_degree(third) == 0:\n            continue\n        fourth = seed.choice(list(G.succ[third]))\n        if third == fourth:\n            continue\n\n        if (\n            third not in G.succ[start]\n            and fourth not in G.succ[second]\n            and second not in G.succ[third]\n        ):\n            # Swap nodes\n            G.add_edge(start, third)\n            G.add_edge(third, second)\n            G.add_edge(second, fourth)\n            G.remove_edge(start, second)\n            G.remove_edge(second, third)\n            G.remove_edge(third, fourth)\n            swapcount += 1\n\n    return G\n\n\n@py_random_state(3)",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@py_random_state(3)",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 620,
        "n_words": 228,
        "vocab_size": 139,
        "complexity": 15,
        "nloc": 47,
        "token_counts": 332,
        "n_ast_nodes": 549,
        "n_identifiers": 34,
        "d_id": 42431,
        "documentation": {
            "docstring": "Swap three edges in a directed graph while keeping the node degrees fixed.\n\n    A directed edge swap swaps three edges such that a -> b -> c -> d becomes\n    a -> c -> b -> d. This pattern of swapping allows all possible states with the\n    same in- and out-degree distribution in a directed graph to be reached.\n\n    If the swap would create parallel edges (e.g. if a -> c already existed in the\n    previous example), another attempt is made to find a suitable trio of edges.\n\n    Parameters\n    ----------\n    G : DiGraph\n       A directed graph\n\n    nswap : integer (optional, default=1)\n       Number of three-edge (directed) swaps to perform\n\n    max_tries : integer (optional, default=100)\n       Maximum number of attempts to swap edges\n\n    seed : integer, random_state, or None (default)\n        Indicator of random number generation state.\n        See :ref:`Randomness<randomness>`.\n\n    Returns\n    -------\n    G : DiGraph\n       The graph after the edges are swapped.\n\n    Raises\n    ------\n    NetworkXError\n        If `G` is not directed, or\n        If nswap > max_tries, or\n        If there are fewer than 4 nodes or 3 edges in `G`.\n    NetworkXAlgorithmError\n        If the number of swap attempts exceeds `max_tries` before `nswap` swaps are made\n\n    Notes\n    -----\n    Does not enforce any connectivity constraints.\n\n    The graph G is modified in place.\n\n    References\n    ----------\n    .. [1] Erdős, Péter L., et al. “A Simple Havel-Hakimi Type Algorithm to Realize\n           Graphical Degree Sequences of Directed Graphs.” ArXiv:0905.4913 [Math],\n           Jan. 2010. https://doi.org/10.48550/arXiv.0905.4913.\n           Published  2010 in Elec. J. Combinatorics (17(1)). R66.\n           http://www.combinatorics.org/Volume_17/PDF/v17i1r66.pdf\n    .. [2] “Combinatorics - Reaching All Possible Simple Directed Graphs with a given\n           Degree Sequence with 2-Edge Swaps.” Mathematics Stack Exchange,\n           https://math.stackexchange.com/questions/22272/. Accessed 30 May 2022.\n    ",
            "n_words": 264,
            "vocab_size": 176,
            "n_whitespaces": 472,
            "language": "en"
        }
    },
    {
        "id": 242760,
        "commit_id": "965df6df6f806887fca3f7b5c6dd6c70a20e803e",
        "repo": "Pillow",
        "path": "src/PIL/GdImageFile.py",
        "file_name": "GdImageFile.py",
        "fun_name": "open",
        "commit_message": "Add missing paramters to docstrings",
        "code": "def open(fp, mode=\"r\"):\n    \n    if mode != \"r\":\n        raise ValueError(\"bad mode\")\n\n    try:\n        return GdImageFile(fp)\n    except SyntaxError as e:\n        raise UnidentifiedImageError(\"cannot identify this image file\") from e\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 58,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 39,
        "n_ast_nodes": 73,
        "n_identifiers": 8,
        "d_id": 69912,
        "documentation": {
            "docstring": "\n    Load texture from a GD image file.\n\n    :param fp: GD file name, or an opened file handle.\n    :param mode: Optional mode.  In this version, if the mode argument\n        is given, it must be \"r\".\n    :returns: An image instance.\n    :raises OSError: If the image could not be read.\n    ",
            "n_words": 47,
            "vocab_size": 40,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 247439,
        "commit_id": "f63bedef07360216a8de71dc38f00f1aea503903",
        "repo": "synapse",
        "path": "tests/rest/client/test_relations.py",
        "file_name": "test_relations.py",
        "fun_name": "_make_relation_requests",
        "commit_message": "Invalidate caches when an event with a relation is redacted. (#12121)\n\nThe caches for the target of the relation must be cleared\r\nso that the bundled aggregations are re-calculated after\r\nthe redaction is processed.",
        "code": "def _make_relation_requests(self) -> Tuple[List[str], JsonDict]:\n        \n\n        # Request the relations of the event.\n        channel = self.make_request(\n            \"GET\",\n            f\"/_matrix/client/unstable/rooms/{self.room}/relations/{self.parent_id}\",\n            access_token=self.user_token,\n        )\n        self.assertEquals(200, channel.code, channel.json_body)\n        event_ids = [ev[\"event_id\"] for ev in channel.json_body[\"chunk\"]]\n\n        # Fetch the bundled aggregations of the event.\n        channel = self.make_request(\n            \"GET\",\n            f\"/_matrix/client/unstable/rooms/{self.room}/event/{self.parent_id}\",\n            access_token=self.user_token,\n        )\n        self.assertEquals(200, channel.code, channel.json_body)\n        bundled_relations = channel.json_body[\"unsigned\"].get(\"m.relations\", {})\n\n        return event_ids, bundled_relations\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 204,
        "n_words": 54,
        "vocab_size": 36,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 117,
        "n_ast_nodes": 214,
        "n_identifiers": 19,
        "d_id": 71671,
        "documentation": {
            "docstring": "\n        Makes requests and ensures they result in a 200 response, returns a\n        tuple of results:\n\n        1. `/relations` -> Returns a list of event IDs.\n        2. `/event` -> Returns the response's m.relations field (from unsigned),\n            if it exists.\n        ",
            "n_words": 37,
            "vocab_size": 32,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 153617,
        "commit_id": "605efa618e7994681f57b11d04d417f353ef8d50",
        "repo": "modin",
        "path": "modin/pandas/base.py",
        "file_name": "base.py",
        "fun_name": "at_time",
        "commit_message": "DOCS-#3099: Fix `BasePandasDataSet` docstrings warnings (#4333)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Alexander Myskov <alexander.myskov@intel.com>",
        "code": "def at_time(self, time, asof=False, axis=None):  # noqa: PR01, RT01, D200\n        \n        axis = self._get_axis_number(axis)\n        idx = self.index if axis == 0 else self.columns\n        indexer = pandas.Series(index=idx).at_time(time, asof=asof).index\n        return self.loc[indexer] if axis == 0 else self.loc[:, indexer]\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 35,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 78,
        "n_ast_nodes": 118,
        "n_identifiers": 13,
        "d_id": 35498,
        "documentation": {
            "docstring": "\n        Select values at particular time of day (e.g., 9:30AM).\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 203337,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/checks.py",
        "file_name": "checks.py",
        "fun_name": "_check_fields",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _check_fields(self, obj):\n        \n\n        if obj.fields is None:\n            return []\n        elif not isinstance(obj.fields, (list, tuple)):\n            return must_be(\"a list or tuple\", option=\"fields\", obj=obj, id=\"admin.E004\")\n        elif obj.fieldsets:\n            return [\n                checks.Error(\n                    \"Both 'fieldsets' and 'fields' are specified.\",\n                    obj=obj.__class__,\n                    id=\"admin.E005\",\n                )\n            ]\n        fields = flatten(obj.fields)\n        if len(fields) != len(set(fields)):\n            return [\n                checks.Error(\n                    \"The value of 'fields' contains duplicate field(s).\",\n                    obj=obj.__class__,\n                    id=\"admin.E006\",\n                )\n            ]\n\n        return list(\n            chain.from_iterable(\n                self._check_field_spec(obj, field_name, \"fields\")\n                for field_name in obj.fields\n            )\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 418,
        "n_words": 70,
        "vocab_size": 55,
        "complexity": 6,
        "nloc": 28,
        "token_counts": 142,
        "n_ast_nodes": 228,
        "n_identifiers": 21,
        "d_id": 50313,
        "documentation": {
            "docstring": "Check that `fields` only refer to existing fields, doesn't contain\n        duplicates. Check if at most one of `fields` and `fieldsets` is defined.\n        ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 36,
            "language": "en"
        }
    },
    {
        "id": 33222,
        "commit_id": "811c4c9f79758235762b4f70ffae00deae494fb1",
        "repo": "transformers",
        "path": "src/transformers/modeling_tf_utils.py",
        "file_name": "modeling_tf_utils.py",
        "fun_name": "register_for_auto_class",
        "commit_message": "fix bug: register_for_auto_class should be defined on TFPreTrainedModel instead of TFSequenceSummary (#18607)",
        "code": "def register_for_auto_class(cls, auto_class=\"TFAutoModel\"):\n        \n        if not isinstance(auto_class, str):\n            auto_class = auto_class.__name__\n\n        import transformers.models.auto as auto_module\n\n        if not hasattr(auto_module, auto_class):\n            raise ValueError(f\"{auto_class} is not a valid auto class.\")\n\n        cls._auto_class = auto_class\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 86,
        "n_words": 29,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 52,
        "n_ast_nodes": 89,
        "n_identifiers": 13,
        "d_id": 6074,
        "documentation": {
            "docstring": "\n        Register this class with a given auto class. This should only be used for custom models as the ones in the\n        library are already mapped with an auto class.\n\n        <Tip warning={true}>\n\n        This API is experimental and may have some slight breaking changes in the next releases.\n\n        </Tip>\n\n        Args:\n            auto_class (`str` or `type`, *optional*, defaults to `\"TFAutoModel\"`):\n                The auto class to register this new model with.\n        ",
            "n_words": 65,
            "vocab_size": 54,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 264296,
        "commit_id": "54834c47f8870e7faabcd847c3270da0bd3d2884",
        "repo": "netbox",
        "path": "netbox/netbox/views/generic/bulk_views.py",
        "file_name": "bulk_views.py",
        "fun_name": "get",
        "commit_message": "Refactor generic views; add plugins dev documentation",
        "code": "def get(self, request):\n        \n        model = self.queryset.model\n        content_type = ContentType.objects.get_for_model(model)\n\n        if self.filterset:\n            self.queryset = self.filterset(request.GET, self.queryset).qs\n\n        # Compile a dictionary indicating which permissions are available to the current user for this model\n        permissions = {}\n        for action in ('add', 'change', 'delete', 'view'):\n            perm_name = get_permission_for_model(model, action)\n            permissions[action] = request.user.has_perm(perm_name)\n\n        if 'export' in request.GET:\n\n            # Export the current table view\n            if request.GET['export'] == 'table':\n                table = self.get_table(request, permissions)\n                columns = [name for name, _ in table.selected_columns]\n                return self.export_table(table, columns)\n\n            # Render an ExportTemplate\n            elif request.GET['export']:\n                template = get_object_or_404(ExportTemplate, content_type=content_type, name=request.GET['export'])\n                return self.export_template(template, request)\n\n            # Check for YAML export support on the model\n            elif hasattr(model, 'to_yaml'):\n                response = HttpResponse(self.export_yaml(), content_type='text/yaml')\n                filename = 'netbox_{}.yaml'.format(self.queryset.model._meta.verbose_name_plural)\n                response['Content-Disposition'] = 'attachment; filename=\"{}\"'.format(filename)\n                return response\n\n            # Fall back to default table/YAML export\n            else:\n                table = self.get_table(request, permissions)\n                return self.export_table(table)\n\n        # Render the objects table\n        table = self.get_table(request, permissions)\n        configure_table(table, request)\n\n        # If this is an HTMX request, return only the rendered table HTML\n        if is_htmx(request):\n            return render(request, 'htmx/table.html', {\n                'table': table,\n            })\n\n        context = {\n            'content_type': content_type,\n            'table': table,\n            'permissions': permissions,\n            'action_buttons': self.action_buttons,\n            'filter_form': self.filterset_form(request.GET, label_suffix='') if self.filterset_form else None,\n        }\n        context.update(self.get_extra_context(request))\n\n        return render(request, self.template_name, context)\n\n    #\n    # Export methods\n    #\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 698,
        "n_words": 192,
        "vocab_size": 123,
        "complexity": 10,
        "nloc": 40,
        "token_counts": 342,
        "n_ast_nodes": 565,
        "n_identifiers": 47,
        "d_id": 77669,
        "documentation": {
            "docstring": "\n        GET request handler.\n\n        Args:\n            request: The current request\n        ",
            "n_words": 8,
            "vocab_size": 7,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 262249,
        "commit_id": "00c7600103ee34ac50506af88f1b34b713f849e7",
        "repo": "TTS",
        "path": "TTS/tts/models/vits.py",
        "file_name": "vits.py",
        "fun_name": "load_audio",
        "commit_message": "Update Vits model API",
        "code": "def load_audio(file_path):\n    \n    x, sr = torchaudio.load(file_path)\n    assert (x > 1).sum() + (x < -1).sum() == 0\n    return x, sr\n\n",
        "url": "https://github.com/coqui-ai/TTS.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 31,
        "n_words": 19,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 43,
        "n_ast_nodes": 72,
        "n_identifiers": 7,
        "d_id": 77159,
        "documentation": {
            "docstring": "Load the audio file normalized in [-1, 1]\n\n    Return Shapes:\n        - x: :math:`[1, T]`\n    ",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 3767,
        "commit_id": "a3aae8017a0a40ff2006e2567f71dccb04c997a5",
        "repo": "airbyte",
        "path": "airbyte-integrations/connectors/source-facebook-marketing/source_facebook_marketing/streams/base_streams.py",
        "file_name": "base_streams.py",
        "fun_name": "state",
        "commit_message": "🎉 🎉 Source FB Marketing: performance and reliability fixes (#9805)\n\n* Facebook Marketing performance improvement\r\n\r\n* add comments and little refactoring\r\n\r\n* fix integration tests with the new config\r\n\r\n* improve job status handling, limit concurrency to 10\r\n\r\n* fix campaign jobs, refactor manager\r\n\r\n* big refactoring of async jobs, support random order of slices\r\n\r\n* update source _read_incremental to hook new state logic\r\n\r\n* fix issues with timeout\r\n\r\n* remove debugging and clean up, improve retry logic\r\n\r\n* merge changes from #8234\r\n\r\n* fix call super _read_increment\r\n\r\n* generalize batch execution, add use_batch flag\r\n\r\n* improve coverage, do some refactoring of spec\r\n\r\n* update test, remove overrides of source\r\n\r\n* add split by AdSet\r\n\r\n* add smaller insights\r\n\r\n* fix end_date < start_date case\r\n\r\n* add account_id to PK\r\n\r\n* add notes\r\n\r\n* fix new streams\r\n\r\n* fix reversed incremental stream\r\n\r\n* update spec.json for SAT\r\n\r\n* upgrade CDK and bump version\r\n\r\nCo-authored-by: Dmytro Rezchykov <dmitry.rezchykov@zazmic.com>\r\nCo-authored-by: Eugene Kulak <kulak.eugene@gmail.com>",
        "code": "def state(self) -> Mapping[str, Any]:\n        \n        if self._cursor_value:\n            return {\n                self.cursor_field: self._cursor_value,\n                \"include_deleted\": self._include_deleted,\n            }\n\n        return {}\n",
        "url": "https://github.com/airbytehq/airbyte.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 89,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 38,
        "n_ast_nodes": 61,
        "n_identifiers": 8,
        "d_id": 553,
        "documentation": {
            "docstring": "State getter, get current state and serialize it to emmit Airbyte STATE message",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 64713,
        "commit_id": "8dff4d66a4a13def61276c2b46cbf0984c469819",
        "repo": "erpnext",
        "path": "erpnext/manufacturing/doctype/bom/test_bom.py",
        "file_name": "test_bom.py",
        "fun_name": "create_nested_bom",
        "commit_message": "fix: bom valuation - handle lack of LPP (#30454)",
        "code": "def create_nested_bom(tree, prefix=\"_Test bom \"):\n\t\n\n\tdef create_items(bom_tree):\n\t\tfor item_code, subtree in bom_tree.items():\n\t\t\tbom_item_code = prefix + item_code\n\t\t\tif not frappe.db.exists(\"Item\", bom_item_code):\n\t\t\t\tfrappe.get_doc(doctype=\"Item\", item_code=bom_item_code, item_group=\"_Test Item Group\").insert()\n\t\t\tcreate_items(subtree)\n\tcreate_items(tree)\n\n\tdef dfs(tree, node):\n\t\t\n\t\tfor node_name, subtree in tree.items():\n\t\t\tif node_name == node:\n\t\t\t\treturn subtree\n\t\t\telse:\n\t\t\t\tresult = dfs(subtree, node)\n\t\t\t\tif result is not None:\n\t\t\t\t\treturn result\n\n\torder_of_creating_bom = reversed(level_order_traversal(tree))\n\n\tfor item in order_of_creating_bom:\n\t\tchild_items = dfs(tree, item)\n\t\tif child_items:\n\t\t\tbom_item_code = prefix + item\n\t\t\tbom = frappe.get_doc(doctype=\"BOM\", item=bom_item_code)\n\t\t\tfor child_item in child_items.keys():\n\t\t\t\tbom.append(\"items\", {\"item_code\": prefix + child_item})\n\t\t\tbom.company = \"_Test Company\"\n\t\t\tbom.currency = \"INR\"\n\t\t\tbom.insert()\n\t\t\tbom.submit()\n\n\treturn bom  # parent bom is last bom\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 74,
        "n_words": 102,
        "vocab_size": 65,
        "complexity": 4,
        "nloc": 17,
        "token_counts": 107,
        "n_ast_nodes": 346,
        "n_identifiers": 32,
        "d_id": 13699,
        "documentation": {
            "docstring": " Helper function to create a simple nested bom from tree describing item names. (along with required items)\n\tnaive implementation for searching right subtree",
            "n_words": 23,
            "vocab_size": 23,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 3306,
        "commit_id": "8fbf8ba2a5bfcdb892e8ca596e338894614000b5",
        "repo": "prophet",
        "path": "python/prophet/forecaster.py",
        "file_name": "forecaster.py",
        "fun_name": "_make_historical_mat_time",
        "commit_message": "Speed Up Uncertainty Predictions (#2186)",
        "code": "def _make_historical_mat_time(deltas, changepoints_t, t_time, n_row=1, single_diff=None):\n        \n        if single_diff is None:\n            single_diff = np.diff(t_time).mean()\n        prev_time = np.arange(0, 1 + single_diff, single_diff)\n        idxs = []\n        for changepoint in changepoints_t:\n            idxs.append(np.where(prev_time > changepoint)[0][0])\n        prev_deltas = np.zeros(len(prev_time))\n        prev_deltas[idxs] = deltas\n        prev_deltas = np.repeat(prev_deltas.reshape(1, -1), n_row, axis=0)\n        return prev_deltas, prev_time\n",
        "url": "https://github.com/facebook/prophet.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 130,
        "n_words": 45,
        "vocab_size": 37,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 120,
        "n_ast_nodes": 183,
        "n_identifiers": 21,
        "d_id": 441,
        "documentation": {
            "docstring": "\n        Creates a matrix of slope-deltas where these changes occured in training data according to the trained prophet obj\n        ",
            "n_words": 18,
            "vocab_size": 18,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 36194,
        "commit_id": "cd4c5c90605b2e23879fcca484f7079b0fc0c361",
        "repo": "transformers",
        "path": "tests/gpt2/test_modeling_tf_gpt2.py",
        "file_name": "test_modeling_tf_gpt2.py",
        "fun_name": "test_lm_generate_gpt2_xla",
        "commit_message": "TF XLA greedy generation (#15786)\n\n* First attempt at TF XLA generation\r\n\r\n* Fix comments\r\n\r\n* Update XLA greedy generate with direct XLA calls\r\n\r\n* Support attention mask, prepare_inputs_for_generation no longer hardcoded for greedy\r\n\r\n* Handle position_ids correctly\r\n\r\n* make xla generate work for non xla case\r\n\r\n* force using xla generate\r\n\r\n* refactor\r\n\r\n* more fixes\r\n\r\n* finish cleaning\r\n\r\n* finish\r\n\r\n* finish\r\n\r\n* clean gpt2 tests\r\n\r\n* add gpt2 tests\r\n\r\n* correct more cases\r\n\r\n* up\r\n\r\n* finish\r\n\r\n* finish\r\n\r\n* more fixes\r\n\r\n* flake 8 stuff\r\n\r\n* final rag fix\r\n\r\n* Update src/transformers/models/rag/modeling_tf_rag.py\r\n\r\n* finish t5 as well\r\n\r\n* finish\r\n\r\n* Update src/transformers/generation_utils.py\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def test_lm_generate_gpt2_xla(self):\n        \n        model = TFGPT2LMHeadModel.from_pretrained(\"gpt2\")\n        input_ids = tf.convert_to_tensor([[464, 3290]], dtype=tf.int32)  # The dog\n\n        # The dog was found in a field near the intersection of West and West Streets.\\n\\nThe dog\n        # fmt: off\n        expected_output_ids = [464, 3290, 373, 1043, 287, 257, 2214, 1474, 262, 16246, 286, 2688, 290, 2688, 27262, 13, 198, 198, 464, 3290]\n        # fmt: on\n        xla_generate = tf.function(model.generate, jit_compile=True)\n\n        output_ids = xla_generate(input_ids, do_sample=False)\n        self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 139,
        "n_words": 68,
        "vocab_size": 54,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 120,
        "n_ast_nodes": 173,
        "n_identifiers": 20,
        "d_id": 6584,
        "documentation": {
            "docstring": "This test gives the exact same results as the non-xla test above",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 60411,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/scripts/cpp_lint.py",
        "file_name": "cpp_lint.py",
        "fun_name": "Error",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def Error(filename, linenum, category, confidence, message):\n  \n  if _ShouldPrintError(category, confidence, linenum):\n    _cpplint_state.IncrementErrorCount(category)\n    if _cpplint_state.output_format == 'vs7':\n      sys.stderr.write('%s(%s):  %s  [%s] [%d]\\n' % (\n          filename, linenum, message, category, confidence))\n    elif _cpplint_state.output_format == 'eclipse':\n      sys.stderr.write('%s:%s: warning: %s  [%s] [%d]\\n' % (\n          filename, linenum, message, category, confidence))\n    else:\n      sys.stderr.write('%s:%s:  %s  [%s] [%d]\\n' % (\n          filename, linenum, message, category, confidence))\n\n\n# Matches standard C++ escape sequences per 2.13.2.3 of the C++ standard.\n_RE_PATTERN_CLEANSE_LINE_ESCAPES = re.compile(\n    r'\\\\([abfnrtv?\"\\\\\\']|\\d+|x[0-9a-fA-F]+)')\n# Matches strings.  Escape codes should already be removed by ESCAPES.\n_RE_PATTERN_CLEANSE_LINE_DOUBLE_QUOTES = re.compile(r'\"[^\"]*\"')\n# Matches characters.  Escape codes should already be removed by ESCAPES.\n_RE_PATTERN_CLEANSE_LINE_SINGLE_QUOTES = re.compile(r\"'.'\")\n# Matches multi-line C++ comments.\n# This RE is a little bit more complicated than one might expect, because we\n# have to take care of space removals tools so we can handle comments inside\n# statements better.\n# The current rule is: We only clear spaces from both sides when we're at the\n# end of the line. Otherwise, we try to remove spaces from the right side,\n# if this doesn't work we try on left side but only if there's a non-character\n# on the right.\n_RE_PATTERN_CLEANSE_LINE_C_COMMENTS = re.compile(\n    r, re.VERBOSE)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 246,
        "n_words": 192,
        "vocab_size": 120,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 106,
        "n_ast_nodes": 241,
        "n_identifiers": 20,
        "d_id": 12139,
        "documentation": {
            "docstring": "Logs the fact we've found a lint error.\n\n  We log where the error was found, and also our confidence in the error,\n  that is, how certain we are this is a legitimate style regression, and\n  not a misidentification or a use that's sometimes justified.\n\n  False positives can be suppressed by the use of\n  \"cpplint(category)\"  comments on the offending line.  These are\n  parsed into _error_suppressions.\n\n  Args:\n    filename: The name of the file containing the error.\n    linenum: The number of the line containing the error.\n    category: A string used to describe the \"category\" this bug\n      falls under: \"whitespace\", say, or \"runtime\".  Categories\n      may have a hierarchy separated by slashes: \"whitespace/indent\".\n    confidence: A number from 1-5 representing a confidence score for\n      the error, with 5 meaning that we are certain of the problem,\n      and 1 meaning that it could be a legitimate construct.\n    message: The error message.\n  (\\s*/\\*.*\\*/\\s*$|\n            /\\*.*\\*/\\s+|\n         \\s+/\\*.*\\*/(?=\\W)|\n            /\\*.*\\*/)",
            "n_words": 148,
            "vocab_size": 103,
            "n_whitespaces": 223,
            "language": "en"
        }
    },
    {
        "id": 176216,
        "commit_id": "54e36acb36c75e09bc53dfcb81c73386b82a20c9",
        "repo": "networkx",
        "path": "networkx/readwrite/gexf.py",
        "file_name": "gexf.py",
        "fun_name": "write_gexf",
        "commit_message": "Update gexf website link in documentation (#5275)\n\nHi, we've recently put the GEXF website again into its own domain http://gexf.net/ so this documentation should be updated. Thanks!",
        "code": "def write_gexf(G, path, encoding=\"utf-8\", prettyprint=True, version=\"1.2draft\"):\n    \n    writer = GEXFWriter(encoding=encoding, prettyprint=prettyprint, version=version)\n    writer.add_graph(G)\n    writer.write(path)\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 25,
        "n_words": 13,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 48,
        "n_ast_nodes": 77,
        "n_identifiers": 10,
        "d_id": 41769,
        "documentation": {
            "docstring": "Write G in GEXF format to path.\n\n    \"GEXF (Graph Exchange XML Format) is a language for describing\n    complex networks structures, their associated data and dynamics\" [1]_.\n\n    Node attributes are checked according to the version of the GEXF\n    schemas used for parameters which are not user defined,\n    e.g. visualization 'viz' [2]_. See example for usage.\n\n    Parameters\n    ----------\n    G : graph\n       A NetworkX graph\n    path : file or string\n       File or file name to write.\n       File names ending in .gz or .bz2 will be compressed.\n    encoding : string (optional, default: 'utf-8')\n       Encoding for text data.\n    prettyprint : bool (optional, default: True)\n       If True use line breaks and indenting in output XML.\n    version: string (optional, default: '1.2draft')\n       The version of GEXF to be used for nodes attributes checking\n\n    Examples\n    --------\n    >>> G = nx.path_graph(4)\n    >>> nx.write_gexf(G, \"test.gexf\")\n\n    # visualization data\n    >>> G.nodes[0][\"viz\"] = {\"size\": 54}\n    >>> G.nodes[0][\"viz\"][\"position\"] = {\"x\": 0, \"y\": 1}\n    >>> G.nodes[0][\"viz\"][\"color\"] = {\"r\": 0, \"g\": 0, \"b\": 256}\n\n\n    Notes\n    -----\n    This implementation does not support mixed graphs (directed and undirected\n    edges together).\n\n    The node id attribute is set to be the string of the node label.\n    If you want to specify an id use set it as node data, e.g.\n    node['a']['id']=1 to set the id of node 'a' to 1.\n\n    References\n    ----------\n    .. [1] GEXF File Format, http://gexf.net/\n    .. [2] GEXF schema, http://gexf.net/schema.html\n    ",
            "n_words": 223,
            "vocab_size": 147,
            "n_whitespaces": 355,
            "language": "en"
        }
    },
    {
        "id": 57490,
        "commit_id": "daddc2985f0cba6c6e0ae3903232cbca155e7e91",
        "repo": "prefect",
        "path": "tests/infrastructure/test_kubernetes_job.py",
        "file_name": "test_kubernetes_job.py",
        "fun_name": "test_user_supplied_base_job_with_labels",
        "commit_message": "Port KubernetesFlowRunner tests to KubernetesJob tests",
        "code": "def test_user_supplied_base_job_with_labels(self):\n        \n        manifest = KubernetesJob(\n            command=[\"echo\", \"hello\"],\n            job={\n                \"apiVersion\": \"batch/v1\",\n                \"kind\": \"Job\",\n                \"metadata\": {\"labels\": {\"my-custom-label\": \"sweet\"}},\n                \"spec\": {\n                    \"template\": {\n                        \"spec\": {\n                            \"parallelism\": 1,\n                            \"completions\": 1,\n                            \"restartPolicy\": \"Never\",\n                            \"containers\": [\n                                {\n                                    \"name\": \"prefect-job\",\n                                    \"env\": [],\n                                }\n                            ],\n                        }\n                    }\n                },\n            },\n        ).build_job()\n\n        assert manifest[\"metadata\"][\"labels\"] == {\n            # the labels provided in the user's job base\n            \"my-custom-label\": \"sweet\",\n        }\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 574,
        "n_words": 58,
        "vocab_size": 47,
        "complexity": 1,
        "nloc": 27,
        "token_counts": 104,
        "n_ast_nodes": 201,
        "n_identifiers": 7,
        "d_id": 11669,
        "documentation": {
            "docstring": "The user can supply a custom base job with labels and they will be\n        included in the final manifest",
            "n_words": 19,
            "vocab_size": 19,
            "n_whitespaces": 25,
            "language": "en"
        }
    },
    {
        "id": 31379,
        "commit_id": "a2d34b7c040723b92823310e3b8fd66874c9d667",
        "repo": "transformers",
        "path": "src/transformers/testing_utils.py",
        "file_name": "testing_utils.py",
        "fun_name": "require_torch_bf16_gpu",
        "commit_message": "deprecate is_torch_bf16_available (#17738)\n\n* deprecate is_torch_bf16_available\r\n\r\n* address suggestions",
        "code": "def require_torch_bf16_gpu(test_case):\n    \n    return unittest.skipUnless(\n        is_torch_bf16_gpu_available(),\n        \"test requires torch>=1.10, using Ampere GPU or newer arch with cuda>=11.0\",\n    )(test_case)\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 40,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 21,
        "n_ast_nodes": 38,
        "n_identifiers": 5,
        "d_id": 5727,
        "documentation": {
            "docstring": "Decorator marking a test that requires torch>=1.10, using Ampere GPU or newer arch with cuda>=11.0",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 111556,
        "commit_id": "aea16719be04d4d6ab889cd20fe0e323b2c7ffee",
        "repo": "spaCy",
        "path": "spacy/tests/pipeline/test_pipe_methods.py",
        "file_name": "test_pipe_methods.py",
        "fun_name": "test_enable_disable_conflict_with_config",
        "commit_message": "Simplify and clarify enable/disable behavior of spacy.load() (#11459)\n\n* Change enable/disable behavior so that arguments take precedence over config options. Extend error message on conflict. Add warning message in case of overwriting config option with arguments.\r\n\r\n* Fix tests in test_serialize_pipeline.py to reflect changes to handling of enable/disable.\r\n\r\n* Fix type issue.\r\n\r\n* Move comment.\r\n\r\n* Move comment.\r\n\r\n* Issue UserWarning instead of printing wasabi message. Adjust test.\r\n\r\n* Added pytest.warns(UserWarning) for expected warning to fix tests.\r\n\r\n* Update warning message.\r\n\r\n* Move type handling out of fetch_pipes_status().\r\n\r\n* Add global variable for default value. Use id() to determine whether used values are default value.\r\n\r\n* Fix default value for disable.\r\n\r\n* Rename DEFAULT_PIPE_STATUS to _DEFAULT_EMPTY_PIPES.",
        "code": "def test_enable_disable_conflict_with_config():\n    \n    nlp = English()\n    nlp.add_pipe(\"tagger\")\n    nlp.add_pipe(\"senter\")\n    nlp.add_pipe(\"sentencizer\")\n\n    with make_tempdir() as tmp_dir:\n        nlp.to_disk(tmp_dir)\n        # Expected to fail, as config and arguments conflict.\n        with pytest.raises(ValueError):\n            spacy.load(\n                tmp_dir, enable=[\"tagger\"], config={\"nlp\": {\"disabled\": [\"senter\"]}}\n            )\n        # Expected to succeed without warning due to the lack of a conflicting config option.\n        spacy.load(tmp_dir, enable=[\"tagger\"])\n        # Expected to succeed with a warning, as disable=[] should override the config setting.\n        with pytest.warns(UserWarning):\n            spacy.load(\n                tmp_dir,\n                enable=[\"tagger\"],\n                disable=[],\n                config={\"nlp\": {\"disabled\": [\"senter\"]}},\n            )\n\n",
        "url": "https://github.com/explosion/spaCy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 258,
        "n_words": 72,
        "vocab_size": 49,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 127,
        "n_ast_nodes": 235,
        "n_identifiers": 17,
        "d_id": 24437,
        "documentation": {
            "docstring": "Test conflict between enable/disable w.r.t. `nlp.disabled` set in the config.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 102230,
        "commit_id": "e1e43c4e710389a3fcf54cd7f3537336e21d3ae5",
        "repo": "pytorch",
        "path": "torch/distributed/distributed_c10d.py",
        "file_name": "distributed_c10d.py",
        "fun_name": "broadcast_object_list",
        "commit_message": "Prevent sum overflow in broadcast_object_list (#70605)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/70605\n\nbroadcast_object_list casted the sum of all object lengths to int from long causing overflows.\n\nTest Plan:\nAdd a Tensor  with >2GB storage requirement (in distributed_test.py) to object broadcast.\n\nThis Tensor is only added if test are running at Meta as github tests will oom.\n\nWithout fix the length will overflow and the program will request a negative sized Tensor:\n```\nRuntimeError: Trying to create tensor with negative dimension -2147482417: [-2147482417]\n```\nWith fix it will pass the test.\n\nTest used on server with GPUs:\n\nbuck test  mode/dev-nosan //caffe2/test/distributed:distributed_nccl_spawn --local -- broadcast_object\nbuck test  mode/dev-nosan //caffe2/test/distributed:distributed_gloo_spawn --local -- broadcast_object\n\nReviewed By: r-barnes\n\nDifferential Revision: D33405741\n\nfbshipit-source-id: 972165f8297b3f5d475636e6127ed4a49adacab1",
        "code": "def broadcast_object_list(object_list, src=0, group=None, device=None):\n    \n    if _rank_not_in_group(group):\n        _warn_not_in_group(\"broadcast_object_list\")\n        return\n\n    my_rank = get_rank()\n    # Serialize object_list elements to tensors on src rank.\n    if my_rank == src:\n        tensor_list, size_list = zip(*[_object_to_tensor(obj) for obj in object_list])\n        object_sizes_tensor = torch.cat(size_list)\n    else:\n        object_sizes_tensor = torch.empty(len(object_list), dtype=torch.long)\n\n    # Current device selection.\n    # To preserve backwards compatibility, ``device`` is default to ``None``\n    # in which case we run current logic of device selection, i.e.\n    # ``current_device`` is CUDA if backend is NCCL otherwise CPU device. In the\n    # case it is not ``None`` we move the size and object tensors to be\n    # broadcasted to this device.\n    is_nccl_backend = _check_for_nccl_backend(group)\n    current_device = None\n    if device is not None:\n        if is_nccl_backend and device.type != \"cuda\":\n            raise ValueError(\"device type must be cuda for nccl backend\")\n        current_device = device\n    else:\n        current_device = torch.device(\"cpu\")\n        if is_nccl_backend:\n            # See note about using torch.cuda.current_device() here in\n            # docstring. We cannot simply use my_rank since rank == device is\n            # not necessarily true.\n            current_device = torch.device(\"cuda\", torch.cuda.current_device())\n    if is_nccl_backend:\n        object_sizes_tensor = object_sizes_tensor.to(current_device)\n\n    # Broadcast object sizes\n    broadcast(object_sizes_tensor, src=src, group=group)\n\n    # Concatenate and broadcast serialized object tensors\n    if my_rank == src:\n        object_tensor = torch.cat(tensor_list)\n    else:\n        object_tensor = torch.empty(\n            torch.sum(object_sizes_tensor).item(),  # type: ignore[arg-type]\n            dtype=torch.uint8,\n        )\n\n    if is_nccl_backend:\n        object_tensor = object_tensor.to(current_device)\n    broadcast(object_tensor, src=src, group=group)\n    # Deserialize objects using their stored sizes.\n    offset = 0\n    if my_rank != src:\n        for i, obj_size in enumerate(object_sizes_tensor):\n            obj_view = object_tensor[offset : offset + obj_size]\n            obj_view = obj_view.type(torch.uint8)\n            if obj_view.device != torch.device(\"cpu\"):\n                obj_view = obj_view.cpu()\n            offset += obj_size\n            object_list[i] = _tensor_to_object(obj_view, obj_size)\n\n",
        "url": "https://github.com/pytorch/pytorch.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 584,
        "n_words": 250,
        "vocab_size": 149,
        "complexity": 14,
        "nloc": 42,
        "token_counts": 301,
        "n_ast_nodes": 502,
        "n_identifiers": 40,
        "d_id": 21501,
        "documentation": {
            "docstring": "\n    Broadcasts picklable objects in ``object_list`` to the whole group. Similar\n    to :func:`broadcast`, but Python objects can be passed in.\n    Note that all objects in ``object_list`` must be picklable in order to be\n    broadcasted.\n\n    Args:\n        object_list (List[Any]): List of input objects to broadcast.\n            Each object must be picklable. Only objects on the ``src`` rank will\n            be broadcast, but each rank must provide lists of equal sizes.\n        src (int): Source rank from which to broadcast ``object_list``.\n        group: (ProcessGroup, optional): The process group to work on. If None,\n            the default process group will be used. Default is ``None``.\n        device (``torch.device``, optional): If not None, the objects are\n            serialized and converted to tensors which are moved to the\n            ``device`` before broadcasting. Default is ``None``.\n\n    Returns:\n        ``None``. If rank is part of the group, ``object_list`` will contain the\n        broadcasted objects from ``src`` rank.\n\n    .. note:: For NCCL-based processed groups, internal tensor representations\n        of objects must be moved to the GPU device before communication takes\n        place. In this case, the device used is given by\n        ``torch.cuda.current_device()`` and it is the user's responsiblity to\n        ensure that this is set so that each rank has an individual GPU, via\n        ``torch.cuda.set_device()``.\n\n    .. note:: Note that this API differs slightly from the :func:`all_gather`\n        collective since it does not provide an ``async_op`` handle and thus\n        will be a blocking call.\n\n    .. warning::\n        :func:`broadcast_object_list` uses ``pickle`` module implicitly, which\n        is known to be insecure. It is possible to construct malicious pickle\n        data which will execute arbitrary code during unpickling. Only call this\n        function with data you trust.\n\n    Example::\n        >>> # Note: Process group initialization omitted on each rank.\n        >>> import torch.distributed as dist\n        >>> if dist.get_rank() == 0:\n        >>>     # Assumes world_size of 3.\n        >>>     objects = [\"foo\", 12, {1: 2}] # any picklable object\n        >>> else:\n        >>>     objects = [None, None, None]\n        >>> # Assumes backend is not NCCL\n        >>> device = torch.device(\"cpu\")\n        >>> dist.broadcast_object_list(objects, src=0, device=device)\n        >>> objects\n        ['foo', 12, {1: 2}]\n    ",
            "n_words": 322,
            "vocab_size": 187,
            "n_whitespaces": 626,
            "language": "en"
        }
    },
    {
        "id": 244473,
        "commit_id": "924c381a78eb70cede198e042ef34e038e05c15a",
        "repo": "mmdetection",
        "path": "mmdet/models/detectors/base.py",
        "file_name": "base.py",
        "fun_name": "forward",
        "commit_message": "Modify RetinaNet model interface",
        "code": "def forward(self, data, optimizer=None, return_loss=False, **kwargs):\n        \n        batch_inputs, batch_data_samples = self.preprocss_data(data)\n\n        if torch.onnx.is_in_onnx_export():\n            # TODO: Delete\n            assert len(batch_inputs) == 1\n            return self.onnx_export(batch_inputs, batch_data_samples)\n\n        if return_loss:\n            losses = self.forward_train(batch_inputs, batch_data_samples,\n                                        **kwargs)\n            loss, log_vars = self._parse_losses(losses)\n\n            outputs = dict(\n                loss=loss,\n                log_vars=log_vars,\n                num_samples=len(batch_data_samples))\n            return outputs\n        else:\n            # TODO: refactor and support aug test later\n            assert isinstance(data[0]['inputs'], torch.Tensor), \\\n                'Only support simple test currently. Aug-test is ' \\\n                'not supported yet'\n            return self.forward_simple_test(batch_inputs, batch_data_samples,\n                                            **kwargs)\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 372,
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        "vocab_size": 55,
        "complexity": 3,
        "nloc": 20,
        "token_counts": 135,
        "n_ast_nodes": 209,
        "n_identifiers": 25,
        "d_id": 70395,
        "documentation": {
            "docstring": "The iteration step during training and testing. This method defines\n        an iteration step during training and testing, except for the back\n        propagation and optimizer updating during training, which are done in\n        an optimizer hook.\n\n        Args:\n            data (list[dict]): The output of dataloader.\n            optimizer (:obj:`torch.optim.Optimizer`, dict, Optional): The\n                optimizer of runner. This argument is unused and reserved.\n                Default to None.\n            return_loss (bool): Whether to return loss. In general,\n                it will be set to True during training and False\n                during testing. Default to False.\n\n        Returns:\n            during training\n                dict: It should contain at least 3 keys: ``loss``,\n                ``log_vars``, ``num_samples``.\n                    - ``loss`` is a tensor for back propagation, which can be a\n                      weighted sum of multiple losses.\n                    - ``log_vars`` contains all the variables to be sent to the\n                        logger.\n                    - ``num_samples`` indicates the batch size (when the model\n                        is DDP, it means the batch size on each GPU), which is\n                        used for averaging the logs.\n\n            during testing\n                list(obj:`DetDataSample`): Detection results of the\n                input images. Each DetDataSample usually contains\n                ``pred_instances`` or ``pred_panoptic_seg`` or\n                ``pred_sem_seg``.\n        ",
            "n_words": 168,
            "vocab_size": 111,
            "n_whitespaces": 562,
            "language": "en"
        }
    },
    {
        "id": 241885,
        "commit_id": "7438fe5edfb565ff341fa6ab054461fcdd504aa2",
        "repo": "scipy",
        "path": "scipy/stats/_stats_py.py",
        "file_name": "_stats_py.py",
        "fun_name": "mode",
        "commit_message": "MAINT: stats: mode: fix negative axis issue with np.moveaxis instead of custom code (#15421)",
        "code": "def mode(a, axis=0, nan_policy='propagate'):\n    \n    a, axis = _chk_asarray(a, axis)\n    if a.size == 0:\n        return ModeResult(np.array([]), np.array([]))\n\n    contains_nan, nan_policy = _contains_nan(a, nan_policy)\n\n    if contains_nan and nan_policy == 'omit':\n        a = ma.masked_invalid(a)\n        return mstats_basic.mode(a, axis)\n\n    if a.dtype == object and np.nan in set(a.ravel()):\n        # Fall back to a slower method since np.unique does not work with NaN\n        scores = set(np.ravel(a))  # get ALL unique values\n        testshape = list(a.shape)\n        testshape[axis] = 1\n        oldmostfreq = np.zeros(testshape, dtype=a.dtype)\n        oldcounts = np.zeros(testshape, dtype=int)\n\n        for score in scores:\n            template = (a == score)\n            counts = np.sum(template, axis, keepdims=True)\n            mostfrequent = np.where(counts > oldcounts, score, oldmostfreq)\n            oldcounts = np.maximum(counts, oldcounts)\n            oldmostfreq = mostfrequent\n\n        return ModeResult(mostfrequent, oldcounts)\n",
        "url": "https://github.com/scipy/scipy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 259,
        "n_words": 108,
        "vocab_size": 78,
        "complexity": 8,
        "nloc": 31,
        "token_counts": 340,
        "n_ast_nodes": 336,
        "n_identifiers": 35,
        "d_id": 69724,
        "documentation": {
            "docstring": "Return an array of the modal (most common) value in the passed array.\n\n    If there is more than one such value, only the smallest is returned.\n    The bin-count for the modal bins is also returned.\n\n    Parameters\n    ----------\n    a : array_like\n        n-dimensional array of which to find mode(s).\n    axis : int or None, optional\n        Axis along which to operate. Default is 0. If None, compute over\n        the whole array `a`.\n    nan_policy : {'propagate', 'raise', 'omit'}, optional\n        Defines how to handle when input contains nan.\n        The following options are available (default is 'propagate'):\n\n          * 'propagate': returns nan\n          * 'raise': throws an error\n          * 'omit': performs the calculations ignoring nan values\n\n    Returns\n    -------\n    mode : ndarray\n        Array of modal values.\n    count : ndarray\n        Array of counts for each mode.\n\n    Examples\n    --------\n    >>> a = np.array([[6, 8, 3, 0],\n    ...               [3, 2, 1, 7],\n    ...               [8, 1, 8, 4],\n    ...               [5, 3, 0, 5],\n    ...               [4, 7, 5, 9]])\n    >>> from scipy import stats\n    >>> stats.mode(a)\n    ModeResult(mode=array([[3, 1, 0, 0]]), count=array([[1, 1, 1, 1]]))\n\n    To get mode of whole array, specify ``axis=None``:\n\n    >>> stats.mode(a, axis=None)\n    ModeResult(mode=array([3]), count=array([3]))\n\n    ",
            "n_words": 183,
            "vocab_size": 131,
            "n_whitespaces": 390,
            "language": "en"
        }
    },
    {
        "id": 196164,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/permutations.py",
        "file_name": "permutations.py",
        "fun_name": "ascents",
        "commit_message": "Updated import locations",
        "code": "def ascents(self):\n        \n        a = self.array_form\n        pos = [i for i in range(len(a) - 1) if a[i] < a[i + 1]]\n        return pos\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 50,
        "n_words": 22,
        "vocab_size": 20,
        "complexity": 3,
        "nloc": 4,
        "token_counts": 42,
        "n_ast_nodes": 67,
        "n_identifiers": 8,
        "d_id": 47664,
        "documentation": {
            "docstring": "\n        Returns the positions of ascents in a permutation, ie, the location\n        where p[i] < p[i+1]\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Permutation\n        >>> p = Permutation([4, 0, 1, 3, 2])\n        >>> p.ascents()\n        [1, 2]\n\n        See Also\n        ========\n\n        descents, inversions, min, max\n        ",
            "n_words": 41,
            "vocab_size": 37,
            "n_whitespaces": 126,
            "language": "en"
        }
    },
    {
        "id": 196123,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/perm_groups.py",
        "file_name": "perm_groups.py",
        "fun_name": "_orbit",
        "commit_message": "Updated import locations",
        "code": "def _orbit(degree, generators, alpha, action='tuples'):\n    r\n    if not hasattr(alpha, '__getitem__'):\n        alpha = [alpha]\n\n    gens = [x._array_form for x in generators]\n    if len(alpha) == 1 or action == 'union':\n        orb = alpha\n        used = [False]*degree\n        for el in alpha:\n            used[el] = True\n        for b in orb:\n            for gen in gens:\n                temp = gen[b]\n                if used[temp] == False:\n                    orb.append(temp)\n                    used[temp] = True\n        return set(orb)\n    elif action == 'tuples':\n        alpha = tuple(alpha)\n        orb = [alpha]\n        used = {alpha}\n        for b in orb:\n            for gen in gens:\n                temp = tuple([gen[x] for x in b])\n                if temp not in used:\n                    orb.append(temp)\n                    used.add(temp)\n        return set(orb)\n    elif action == 'sets':\n        alpha = frozenset(alpha)\n        orb = [alpha]\n        used = {alpha}\n        for b in orb:\n            for gen in gens:\n                temp = frozenset([gen[x] for x in b])\n                if temp not in used:\n                    orb.append(temp)\n                    used.add(temp)\n        return {tuple(x) for x in orb}\n\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 517,
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        "d_id": 47623,
        "documentation": {
            "docstring": "Compute the orbit of alpha `\\{g(\\alpha) | g \\in G\\}` as a set.\n\n    Explanation\n    ===========\n\n    The time complexity of the algorithm used here is `O(|Orb|*r)` where\n    `|Orb|` is the size of the orbit and ``r`` is the number of generators of\n    the group. For a more detailed analysis, see [1], p.78, [2], pp. 19-21.\n    Here alpha can be a single point, or a list of points.\n\n    If alpha is a single point, the ordinary orbit is computed.\n    if alpha is a list of points, there are three available options:\n\n    'union' - computes the union of the orbits of the points in the list\n    'tuples' - computes the orbit of the list interpreted as an ordered\n    tuple under the group action ( i.e., g((1, 2, 3)) = (g(1), g(2), g(3)) )\n    'sets' - computes the orbit of the list interpreted as a sets\n\n    Examples\n    ========\n\n    >>> from sympy.combinatorics import Permutation, PermutationGroup\n    >>> from sympy.combinatorics.perm_groups import _orbit\n    >>> a = Permutation([1, 2, 0, 4, 5, 6, 3])\n    >>> G = PermutationGroup([a])\n    >>> _orbit(G.degree, G.generators, 0)\n    {0, 1, 2}\n    >>> _orbit(G.degree, G.generators, [0, 4], 'union')\n    {0, 1, 2, 3, 4, 5, 6}\n\n    See Also\n    ========\n\n    orbit, orbit_transversal\n\n    ",
            "n_words": 194,
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            "language": "en"
        }
    },
    {
        "id": 270708,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/engine/base_layer.py",
        "file_name": "base_layer.py",
        "fun_name": "_obj_reference_counts",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _obj_reference_counts(self):\n        \n        self._maybe_create_attribute(\n            \"_obj_reference_counts_dict\",\n            object_identity.ObjectIdentityDictionary(),\n        )\n        return self._obj_reference_counts_dict\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 58,
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        "nloc": 6,
        "token_counts": 23,
        "n_ast_nodes": 41,
        "n_identifiers": 6,
        "d_id": 80532,
        "documentation": {
            "docstring": "A dictionary counting the number of attributes referencing an object.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 182890,
        "commit_id": "ada31e68de9065d5d407b16868fe1a2ddb88c548",
        "repo": "textual",
        "path": "src/textual/app.py",
        "file_name": "app.py",
        "fun_name": "on_idle",
        "commit_message": "docstring",
        "code": "async def on_idle(self) -> None:\n        \n        if self._require_styles_update:\n            await self.post_message(messages.StylesUpdated(self))\n            self._require_styles_update = False\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "d_id": 43997,
        "documentation": {
            "docstring": "Perform actions when there are no messages in the queue.",
            "n_words": 10,
            "vocab_size": 10,
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    },
    {
        "id": 151174,
        "commit_id": "8aac644009dd7a8ab8f006594b547abddad5aca9",
        "repo": "freqtrade",
        "path": "freqtrade/freqai/RL/BaseReinforcementLearningModel.py",
        "file_name": "BaseReinforcementLearningModel.py",
        "fun_name": "unset_outlier_removal",
        "commit_message": "add tests. add guardrails.",
        "code": "def unset_outlier_removal(self):\n        \n        if self.ft_params.get('use_SVM_to_remove_outliers', False):\n            self.ft_params.update({'use_SVM_to_remove_outliers': False})\n            logger.warning('User tried to use SVM with RL. Deactivating SVM.')\n        if self.ft_params.get('use_DBSCAN_to_remove_outliers', False):\n            self.ft_params.update({'use_SVM_to_remove_outliers': False})\n            logger.warning('User tried to use DBSCAN with RL. Deactivating DBSCAN.')\n        if self.freqai_info['data_split_parameters'].get('shuffle', False):\n            self.freqai_info['data_split_parameters'].update('shuffle', False)\n            logger.warning('User tried to shuffle training data. Setting shuffle to False')\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "complexity": 4,
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        "token_counts": 100,
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        "n_identifiers": 8,
        "d_id": 34968,
        "documentation": {
            "docstring": "\n        If user has activated any function that may remove training points, this\n        function will set them to false and warn them\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 151131,
        "commit_id": "866a5649588c77ec686ba65e581d1306d8ea3751",
        "repo": "freqtrade",
        "path": "tests/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "log_has_when",
        "commit_message": "update emc start/shutdown, initial emc tests",
        "code": "def log_has_when(line, logs, when):\n    \n    return any(line == message.message for message in logs.get_records(when))\n\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 34960,
        "documentation": {
            "docstring": "Check if line is found in caplog's messages during a specified stage",
            "n_words": 12,
            "vocab_size": 12,
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            "language": "en"
        }
    },
    {
        "id": 119984,
        "commit_id": "3184dd65a222354bffa2466d9a375162f5649132",
        "repo": "jax",
        "path": "jax/experimental/sparse/bcoo.py",
        "file_name": "bcoo.py",
        "fun_name": "bcoo_dot_general_sampled",
        "commit_message": "[sparse] Update docstrings for bcoo primitives.\n\nPiperOrigin-RevId: 438685829",
        "code": "def bcoo_dot_general_sampled(A, B, indices, *, dimension_numbers):\n  \n  (lhs_contract, rhs_contract), (lhs_batch, rhs_batch) = dimension_numbers\n  cdims = (api_util._ensure_index_tuple(lhs_contract),\n           api_util._ensure_index_tuple(rhs_contract))\n  bdims = (api_util._ensure_index_tuple(lhs_batch),\n           api_util._ensure_index_tuple(rhs_batch))\n  return bcoo_dot_general_sampled_p.bind(A, B, indices,\n                                         dimension_numbers=(cdims, bdims))\n\n@bcoo_dot_general_sampled_p.def_impl",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "@bcoo_dot_general_sampled_p.def_impl",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 91,
        "n_words": 27,
        "vocab_size": 23,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 80,
        "n_ast_nodes": 124,
        "n_identifiers": 16,
        "d_id": 26736,
        "documentation": {
            "docstring": "A contraction operation with output computed at given sparse indices.\n\n  Args:\n    lhs: An ndarray.\n    rhs: An ndarray.\n    indices: BCOO indices.\n    dimension_numbers: a tuple of tuples of the form\n      `((lhs_contracting_dims, rhs_contracting_dims),\n      (lhs_batch_dims, rhs_batch_dims))`.\n\n  Returns:\n    BCOO data, an ndarray containing the result.\n  ",
            "n_words": 40,
            "vocab_size": 34,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 194794,
        "commit_id": "7c2b199d0b315c9016072897d849811cfc8a5073",
        "repo": "ParlAI",
        "path": "parlai/scripts/train_model.py",
        "file_name": "train_model.py",
        "fun_name": "setup_args",
        "commit_message": "Add WorldLogger to train_model script. (#4369)\n\n* Add WorldLogger to train_model ParlAI script.\r\n\r\n* Fix test_save_multiple_world_logs in test_train_model.py",
        "code": "def setup_args(parser=None) -> ParlaiParser:\n    \n    if parser is None:\n        parser = ParlaiParser(True, True, 'Train a model')\n    train = parser.add_argument_group('Training Loop Arguments')\n    train.add_argument(\n        '-et',\n        '--evaltask',\n        help='task to use for valid/test (defaults to the one used for training)',\n    )\n    train.add_argument(\n        '--final-extra-opt',\n        type=str,\n        default='',\n        help=\"A '.opt' file that is used for final eval. Useful for setting skip-generation to false. 'datatype' must be included as part of the opt.\",\n    )\n    train.add_argument(\n        '--eval-batchsize',\n        type=int,\n        hidden=True,\n        help='Eval time batch size (defaults to same as -bs)',\n    )\n    train.add_argument(\n        '--eval-dynamic-batching',  # FIXME: see https://github.com/facebookresearch/ParlAI/issues/3367\n        default=None,\n        type='nonestr',\n        choices={None, 'off', 'full', 'batchsort'},\n        help=(\n            'Set dynamic batching at evaluation time. Set to off for '\n            'train-only dynamic batching. Set to none (default) to use same '\n            'setting as --dynamic-batching.'\n        ),\n    )\n    train.add_argument(\n        '--num-workers',\n        default=0,\n        type=int,\n        help='Number of background workers (training only)',\n    )\n    train.add_argument('--display-examples', type='bool', default=False, hidden=True)\n    train.add_argument('-eps', '--num-epochs', type=float, default=-1)\n    train.add_argument('-ttim', '--max-train-time', type=float, default=-1)\n    train.add_argument(\n        '-tstep',\n        '--max-train-steps',\n        '--max-lr-steps',\n        type=int,\n        default=-1,\n        help='End training after n model updates',\n    )\n    train.add_argument('-ltim', '--log-every-n-secs', type=float, default=-1)\n    train.add_argument(\n        '-lstep',\n        '--log-every-n-steps',\n        type=int,\n        default=50,\n        help='Log every n training steps',\n    )\n    train.add_argument(\n        '-vtim',\n        '--validation-every-n-secs',\n        type=float,\n        default=-1,\n        help='Validate every n seconds. Saves model to model_file '\n        '(if set) whenever best val metric is found',\n    )\n    train.add_argument(\n        '-vstep',\n        '--validation-every-n-steps',\n        type=int,\n        default=-1,\n        help='Validate every n training steps. Saves model to model_file '\n        '(if set) whenever best val metric is found',\n    )\n    train.add_argument(\n        '-stim',\n        '--save-every-n-secs',\n        type=float,\n        default=-1,\n        help='Saves the model to model_file.checkpoint after '\n        'every n seconds (default -1, never).',\n    )\n    train.add_argument(\n        '-sval',\n        '--save-after-valid',\n        type='bool',\n        default=False,\n        help='Saves the model to model_file.checkpoint after '\n        'every validation (default %(default)s).',\n    )\n    train.add_argument(\n        '-veps',\n        '--validation-every-n-epochs',\n        type=float,\n        default=-1,\n        help='Validate every n epochs. Saves model to model_file '\n        '(if set) whenever best val metric is found',\n    )\n    train.add_argument(\n        '-vme',\n        '--validation-max-exs',\n        type=int,\n        default=-1,\n        hidden=True,\n        help='max examples to use during validation (default -1 uses all)',\n    )\n    train.add_argument(\n        '--short-final-eval',\n        default=False,\n        hidden=True,\n        type='bool',\n        help='If true, obeys --validation-max-exs in the final '\n        'validation and test evaluations.',\n    )\n    train.add_argument(\n        '-vp',\n        '--validation-patience',\n        type=int,\n        default=10,\n        help=(\n            'number of iterations of validation where result'\n            ' does not improve before we stop training'\n        ),\n    )\n    train.add_argument(\n        '-vmt',\n        '--validation-metric',\n        default='accuracy',\n        help='key into report table for selecting best validation',\n    )\n    train.add_argument(\n        '-vmm',\n        '--validation-metric-mode',\n        type=str,\n        choices=['max', 'min'],\n        help='the direction in which to optimize the validation metric, i.e. maximize or minimize',\n    )\n    train.add_argument(\n        '-vcut',\n        '--validation-cutoff',\n        type=float,\n        default=1.0,\n        hidden=True,\n        help='value at which training will stop if exceeded by metric',\n    )\n    train.add_argument(\n        '-lfc',\n        '--load-from-checkpoint',\n        type='bool',\n        default=True,\n        hidden=True,\n        help='load model from checkpoint if available',\n    )\n    train.add_argument(\n        '-vshare',\n        '--validation-share-agent',\n        default=False,\n        hidden=True,\n        help='use a shared copy of the agent for validation. '\n        'this will eventually default to True, but '\n        'currently defaults to False.',\n    )\n    train.add_argument(\n        '-mcs',\n        '--metrics',\n        type=str,\n        default='default',\n        help='list of metrics to show/compute, e.g. all, default,'\n        'or give a list split by , like '\n        'ppl,f1,accuracy,hits@1,rouge,bleu'\n        'the rouge metrics will be computed as rouge-1, rouge-2 and rouge-l',\n    )\n    train.add_argument(\n        '-micro',\n        '--aggregate-micro',\n        type='bool',\n        default=False,\n        help='Report micro-averaged metrics instead of macro averaged metrics.',\n        recommended=False,\n    )\n    train.add_argument(\n        '--world-logs',\n        type=str,\n        default='',\n        help='Saves a jsonl file of the world logs.'\n        'Set to the empty string to not save at all.',\n    )\n    train.add_argument(\n        '--save-format',\n        type=str,\n        default='conversations',\n        choices=['conversations', 'parlai'],\n    )\n    WorldLogger.add_cmdline_args(parser, partial_opt=None)\n    TensorboardLogger.add_cmdline_args(parser, partial_opt=None)\n    WandbLogger.add_cmdline_args(parser, partial_opt=None)\n\n    parser = setup_dict_args(parser)\n    return parser\n\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 1676,
        "n_words": 516,
        "vocab_size": 289,
        "complexity": 2,
        "nloc": 206,
        "token_counts": 687,
        "n_ast_nodes": 1162,
        "n_identifiers": 21,
        "d_id": 47086,
        "documentation": {
            "docstring": "\n    Build the ParlAI parser, adding command line args if necessary.\n\n    :param ParlaiParser parser:\n        Preexisting parser to append options to. Will be created if needed.\n\n    :returns:\n        the ParlaiParser with CLI options added.\n    ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 247290,
        "commit_id": "2ffaf30803f93273a4d8a65c9e6c3110c8433488",
        "repo": "synapse",
        "path": "tests/rest/client/test_rooms.py",
        "file_name": "test_rooms.py",
        "fun_name": "test_messages_filter_not_labels",
        "commit_message": "Add type hints to `tests/rest/client` (#12108)\n\n* Add type hints to `tests/rest/client`\r\n\r\n* newsfile\r\n\r\n* fix imports\r\n\r\n* add `test_account.py`\r\n\r\n* Remove one type hint in `test_report_event.py`\r\n\r\n* change `on_create_room` to `async`\r\n\r\n* update new functions in `test_third_party_rules.py`\r\n\r\n* Add `test_filter.py`\r\n\r\n* add `test_rooms.py`\r\n\r\n* change to `assertEquals` to `assertEqual`\r\n\r\n* lint",
        "code": "def test_messages_filter_not_labels(self) -> None:\n        \n        self._send_labelled_messages_in_room()\n\n        token = \"s0_0_0_0_0_0_0_0_0\"\n        channel = self.make_request(\n            \"GET\",\n            \"/rooms/%s/messages?access_token=%s&from=%s&filter=%s\"\n            % (self.room_id, self.tok, token, json.dumps(self.FILTER_NOT_LABELS)),\n        )\n\n        events = channel.json_body[\"chunk\"]\n\n        self.assertEqual(len(events), 4, [event[\"content\"] for event in events])\n        self.assertEqual(events[0][\"content\"][\"body\"], \"without label\", events[0])\n        self.assertEqual(events[1][\"content\"][\"body\"], \"without label\", events[1])\n        self.assertEqual(events[2][\"content\"][\"body\"], \"with wrong label\", events[2])\n        self.assertEqual(\n            events[3][\"content\"][\"body\"], \"with two wrong labels\", events[3]\n        )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 178,
        "n_words": 50,
        "vocab_size": 42,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 166,
        "n_ast_nodes": 272,
        "n_identifiers": 16,
        "d_id": 71573,
        "documentation": {
            "docstring": "Test that we can filter by the absence of a label on a /messages request.",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 118735,
        "commit_id": "72703b38029f9358a0ec7ca5ed875a6b438ece19",
        "repo": "streamlit",
        "path": "lib/streamlit/elements/json.py",
        "file_name": "json.py",
        "fun_name": "json",
        "commit_message": "Replace static apps with live Cloud apps (#4317)\n\nCo-authored-by: kajarenc <kajarenc@gmail.com>",
        "code": "def json(self, body):\n        \n        import streamlit as st\n\n        if isinstance(body, LazySessionState):\n            body = body.to_dict()\n\n        if not isinstance(body, str):\n            try:\n                body = json.dumps(body, default=repr)\n            except TypeError as err:\n                st.warning(\n                    \"Warning: this data structure was not fully serializable as \"\n                    \"JSON due to one or more unexpected keys.  (Error was: %s)\" % err\n                )\n                body = json.dumps(body, skipkeys=True, default=repr)\n\n        json_proto = JsonProto()\n        json_proto.body = body\n        return self.dg._enqueue(\"json\", json_proto)\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 246,
        "n_words": 65,
        "vocab_size": 51,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 101,
        "n_ast_nodes": 168,
        "n_identifiers": 20,
        "d_id": 26392,
        "documentation": {
            "docstring": "Display object or string as a pretty-printed JSON string.\n\n        Parameters\n        ----------\n        body : Object or str\n            The object to print as JSON. All referenced objects should be\n            serializable to JSON as well. If object is a string, we assume it\n            contains serialized JSON.\n\n        Example\n        -------\n        >>> st.json({\n        ...     'foo': 'bar',\n        ...     'baz': 'boz',\n        ...     'stuff': [\n        ...         'stuff 1',\n        ...         'stuff 2',\n        ...         'stuff 3',\n        ...         'stuff 5',\n        ...     ],\n        ... })\n\n        .. output::\n           https://share.streamlit.io/streamlit/docs/main/python/api-examples-source/data.json.py\n           height: 385px\n\n        ",
            "n_words": 77,
            "vocab_size": 57,
            "n_whitespaces": 297,
            "language": "en"
        }
    },
    {
        "id": 130302,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/_private/utils.py",
        "file_name": "utils.py",
        "fun_name": "set_kill_child_on_death_win32",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def set_kill_child_on_death_win32(child_proc):\n    \n\n    if isinstance(child_proc, subprocess.Popen):\n        child_proc = child_proc._handle\n    assert isinstance(child_proc, subprocess.Handle)\n\n    if detect_fate_sharing_support_win32():\n        if not win32_AssignProcessToJobObject(win32_job, int(child_proc)):\n            import ctypes\n\n            raise OSError(ctypes.get_last_error(), \"AssignProcessToJobObject() failed\")\n    else:\n        assert False, \"AssignProcessToJobObject used despite being unavailable\"\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 89,
        "n_words": 31,
        "vocab_size": 27,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 66,
        "n_ast_nodes": 111,
        "n_identifiers": 14,
        "d_id": 29222,
        "documentation": {
            "docstring": "Ensures the child process dies if this process dies (fate-sharing).\n\n    Windows-only. Must be called by the parent, after spawning the child.\n\n    Args:\n        child_proc: The subprocess.Popen or subprocess.Handle object.\n    ",
            "n_words": 28,
            "vocab_size": 24,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 122886,
        "commit_id": "4b587fa1f0049db5366fd04812ab940d80a71a22",
        "repo": "jax",
        "path": "jax/_src/pjit.py",
        "file_name": "pjit.py",
        "fun_name": "unflatten_superdims",
        "commit_message": "Move `pjit.py` to `jax/_src` in preparation for merging the `jit` and `pjit` frontend APIs\n\nPiperOrigin-RevId: 495944279",
        "code": "def unflatten_superdims(assignment):\n  \n  def check(cond):\n    if cond: return\n    raise NotImplementedError(\"Failed to convert OpSharding into a ShardingSpec. \"\n                              \"Please open a bug report!\")\n  flat_assignment = np.asarray(assignment, dtype=np.int64)\n  check(flat_assignment[0] == 0)\n  dims = []\n  while flat_assignment.size > 1:\n    stride = flat_assignment[1]\n    for i in range(len(flat_assignment)):\n      if flat_assignment[i] != i * stride: break\n    else:\n      # After this loop i should point to an \"element after the sequence\", so\n      # we have to increment it if the whole array is a strided sequence.\n      i += 1\n    size = i\n    dims.append((size, stride))\n    assert size > 1  # Ensure progress\n    flat_assignment = flat_assignment[::size]\n  return dims\n",
        "url": "https://github.com/google/jax.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 182,
        "n_words": 98,
        "vocab_size": 74,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 101,
        "n_ast_nodes": 192,
        "n_identifiers": 17,
        "d_id": 27261,
        "documentation": {
            "docstring": "Unflatten a list of dimension sizes and their strides that generates assignment.\n\n  If this function succeeds for a given ``assignment``, then the following property\n  should be satisfied::\n\n    dims_with_strides = unflatten_superdims(assignment)\n    base_array = np.arange(map(fst, sorted(dims_with_strides, key=snd, reverse=True)))\n    assignment == base_array.transpose(argsort(dims_with_strides, key=snd, reverse=True)).flatten()\n\n  That is, the returned dimensions list all sizes of the base array (with strides\n  indicating their initial order). The order of dimensions in the list corresponds\n  to the permutation that applied to the base array generates the assignment.\n  ",
            "n_words": 79,
            "vocab_size": 56,
            "n_whitespaces": 94,
            "language": "en"
        }
    },
    {
        "id": 177558,
        "commit_id": "6293c3226e3713bdae678603d6c1300e09c41448",
        "repo": "label-studio",
        "path": "label_studio/tasks/models.py",
        "file_name": "models.py",
        "fun_name": "_get_storage_by_url",
        "commit_message": "fix: DEV-1476: Resolving performance for project storages (#1910)\n\n* Fix: DEV-1476: Resolving performance for project storages\r\n\r\n* Rewrite cache\r\n\r\n* Remove cache completely",
        "code": "def _get_storage_by_url(self, url, storage_objects):\n        \n        from io_storages.models import get_storage_classes\n\n        for storage_object in storage_objects:\n            # check url is string because task can have int, float, dict, list\n            # and 'can_resolve_url' will fail\n            if isinstance(url, str) and storage_object.can_resolve_url(url):\n                return storage_object\n",
        "url": "https://github.com/heartexlabs/label-studio.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 106,
        "n_words": 37,
        "vocab_size": 34,
        "complexity": 4,
        "nloc": 5,
        "token_counts": 38,
        "n_ast_nodes": 61,
        "n_identifiers": 11,
        "d_id": 42439,
        "documentation": {
            "docstring": "Find the first compatible storage and returns pre-signed URL",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 188999,
        "commit_id": "471b19d2aa799cd73bded23379e864dd35bec2b6",
        "repo": "psutil",
        "path": "psutil/_pswindows.py",
        "file_name": "_pswindows.py",
        "fun_name": "swap_memory",
        "commit_message": "Fix typos",
        "code": "def swap_memory():\n    \n    mem = cext.virtual_mem()\n\n    total_phys = mem[0]\n    free_phys = mem[1]\n    total_system = mem[2]\n    free_system = mem[3]\n\n    # Despite the name PageFile refers to total system memory here\n    # thus physical memory values need to be subtracted to get swap values\n    total = total_system - total_phys\n    free = min(total, free_system - free_phys)\n    used = total - free\n    percent = usage_percent(used, total, round_=1)\n    return _common.sswap(total, used, free, percent, 0, 0)\n\n\n# =====================================================================\n# --- disk\n# =====================================================================\n\n\ndisk_io_counters = cext.disk_io_counters\n\n",
        "url": "https://github.com/giampaolo/psutil.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 114,
        "n_words": 79,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 85,
        "n_ast_nodes": 142,
        "n_identifiers": 18,
        "d_id": 45962,
        "documentation": {
            "docstring": "Swap system memory as a (total, used, free, sin, sout) tuple.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 300279,
        "commit_id": "539ce7ff0e9d9bc59cd8f028f245c09f802c89cb",
        "repo": "core",
        "path": "tests/components/mobile_app/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "test_default_disabling_entity",
        "commit_message": "Allow mobile app to disable entities by default (#71562)",
        "code": "async def test_default_disabling_entity(hass, create_registrations, webhook_client):\n    \n    webhook_id = create_registrations[1][\"webhook_id\"]\n    webhook_url = f\"/api/webhook/{webhook_id}\"\n\n    reg_resp = await webhook_client.post(\n        webhook_url,\n        json={\n            \"type\": \"register_sensor\",\n            \"data\": {\n                \"name\": \"Battery State\",\n                \"type\": \"sensor\",\n                \"unique_id\": \"battery_state\",\n                \"default_disabled\": True,\n            },\n        },\n    )\n\n    assert reg_resp.status == HTTPStatus.CREATED\n\n    json = await reg_resp.json()\n    assert json == {\"success\": True}\n    await hass.async_block_till_done()\n\n    entity = hass.states.get(\"sensor.test_1_battery_state\")\n    assert entity is None\n\n    assert (\n        er.async_get(hass).async_get(\"sensor.test_1_battery_state\").disabled_by\n        == er.RegistryEntryDisabler.INTEGRATION\n    )\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 228,
        "n_words": 61,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 129,
        "n_ast_nodes": 230,
        "n_identifiers": 21,
        "d_id": 99145,
        "documentation": {
            "docstring": "Test that sensors can be disabled by default upon registration.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 196106,
        "commit_id": "498015021131af4dbb07eb110e5badaba8250c7b",
        "repo": "sympy",
        "path": "sympy/combinatorics/partitions.py",
        "file_name": "partitions.py",
        "fun_name": "RGS",
        "commit_message": "Updated import locations",
        "code": "def RGS(self):\n        \n        rgs = {}\n        partition = self.partition\n        for i, part in enumerate(partition):\n            for j in part:\n                rgs[j] = i\n        return tuple([rgs[i] for i in sorted(\n            [i for p in partition for i in p], key=default_sort_key)])\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 108,
        "n_words": 36,
        "vocab_size": 23,
        "complexity": 6,
        "nloc": 8,
        "token_counts": 67,
        "n_ast_nodes": 102,
        "n_identifiers": 13,
        "d_id": 47606,
        "documentation": {
            "docstring": "\n        Returns the \"restricted growth string\" of the partition.\n\n        Explanation\n        ===========\n\n        The RGS is returned as a list of indices, L, where L[i] indicates\n        the block in which element i appears. For example, in a partition\n        of 3 elements (a, b, c) into 2 blocks ([c], [a, b]) the RGS is\n        [1, 1, 0]: \"a\" is in block 1, \"b\" is in block 1 and \"c\" is in block 0.\n\n        Examples\n        ========\n\n        >>> from sympy.combinatorics import Partition\n        >>> a = Partition([1, 2], [3], [4, 5])\n        >>> a.members\n        (1, 2, 3, 4, 5)\n        >>> a.RGS\n        (0, 0, 1, 2, 2)\n        >>> a + 1\n        Partition({3}, {4}, {5}, {1, 2})\n        >>> _.RGS\n        (0, 0, 1, 2, 3)\n        ",
            "n_words": 114,
            "vocab_size": 81,
            "n_whitespaces": 255,
            "language": "en"
        }
    },
    {
        "id": 303498,
        "commit_id": "34984a8af8efc5ef6d1d204404c517e7f7c2d1bb",
        "repo": "core",
        "path": "homeassistant/components/wilight/switch.py",
        "file_name": "switch.py",
        "fun_name": "pause_time",
        "commit_message": "Add switch to wilight (#62873)\n\n* Created switch.py and support\r\n\r\n* updated support.py\r\n\r\n* test for wilight switch\r\n\r\n* Update for Test\r\n\r\n* Updated test_switch.py\r\n\r\n* Trigger service with index\r\n\r\n* Updated support.py and switch.py\r\n\r\n* Updated support.py\r\n\r\n* Updated switch.py as PR#63614\r\n\r\n* Updated switch.py\r\n\r\n* add type hints\r\n\r\n* Updated support.py\r\n\r\n* Updated switch.py\r\n\r\n* Updated switch.py and services.yaml\r\n\r\n* Updated pywilight\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update ci.yaml\r\n\r\n* Update ci.yaml\r\n\r\n* Updated as pywilight\r\n\r\nRenamed Device as PyWiLightDevice in pywilight.\r\n\r\n* Updated as pywilight\r\n\r\nRenamed Device as PyWiLightDevice in pywilight.\r\n\r\n* Updated as pywilight\r\n\r\nRenamed Device as PyWiLightDevice in pywilight.\r\n\r\n* Updated as pywilight\r\n\r\nRenamed Device as PyWiLightDevice in pywilight.\r\n\r\n* Update switch.py\r\n\r\n* Update homeassistant/components/wilight/support.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update support.py\r\n\r\n* Update switch.py\r\n\r\n* Update support.py\r\n\r\n* Update support.py\r\n\r\n* Update switch.py\r\n\r\n* Update switch.py\r\n\r\n* Update services.yaml\r\n\r\n* Update switch.py\r\n\r\n* Update services.yaml\r\n\r\n* Update switch.py\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update homeassistant/components/wilight/switch.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update switch.py\r\n\r\n* Update switch.py\r\n\r\n* Update switch.py\r\n\r\n* Update test_switch.py\r\n\r\n* Update test_switch.py\r\n\r\n* Update test_switch.py\r\n\r\n* Decrease exception scope\r\n\r\n* Clean up\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "def pause_time(self) -> int | None:\n        \n        pause_time = self._status.get(\"timer_target\")\n        if pause_time is not None:\n            return wilight_to_hass_pause_time(pause_time)\n        return pause_time\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 57,
        "n_words": 18,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 33,
        "n_ast_nodes": 57,
        "n_identifiers": 6,
        "d_id": 102317,
        "documentation": {
            "docstring": "Return pause time of valve switch.\n\n        None is unknown, 1 is minimum, 24 is maximum.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 181902,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tpot/export_utils.py",
        "file_name": "export_utils.py",
        "fun_name": "set_param_recursive",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def set_param_recursive(pipeline_steps, parameter, value):\n    \n    for (_, obj) in pipeline_steps:\n        recursive_attrs = [\"steps\", \"transformer_list\", \"estimators\"]\n        for attr in recursive_attrs:\n            if hasattr(obj, attr):\n                set_param_recursive(getattr(obj, attr), parameter, value)\n        if hasattr(obj, \"estimator\"):  # nested estimator\n            est = getattr(obj, \"estimator\")\n            if hasattr(est, parameter):\n                setattr(est, parameter, value)\n        if hasattr(obj, parameter):\n            setattr(obj, parameter, value)\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 156,
        "n_words": 47,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 12,
        "token_counts": 102,
        "n_ast_nodes": 159,
        "n_identifiers": 12,
        "d_id": 43655,
        "documentation": {
            "docstring": "Recursively iterate through all objects in the pipeline and set a given parameter.\n\n    Parameters\n    ----------\n    pipeline_steps: array-like\n        List of (str, obj) tuples from a scikit-learn pipeline or related object\n    parameter: str\n        The parameter to assign a value for in each pipeline object\n    value: any\n        The value to assign the parameter to in each pipeline object\n    Returns\n    -------\n    None\n\n    ",
            "n_words": 58,
            "vocab_size": 41,
            "n_whitespaces": 106,
            "language": "en"
        }
    },
    {
        "id": 257944,
        "commit_id": "101d2bc86cab29f5e93cccd58730c5932acf8ca3",
        "repo": "haystack",
        "path": "haystack/modeling/model/multimodal/sentence_transformers.py",
        "file_name": "sentence_transformers.py",
        "fun_name": "embedding_dim",
        "commit_message": "feat: `MultiModalRetriever` (#2891)\n\n* Adding Data2VecVision and Data2VecText to the supported models and adapt Tokenizers accordingly\r\n\r\n* content_types\r\n\r\n* Splitting classes into respective folders\r\n\r\n* small changes\r\n\r\n* Fix EOF\r\n\r\n* eof\r\n\r\n* black\r\n\r\n* API\r\n\r\n* EOF\r\n\r\n* whitespace\r\n\r\n* api\r\n\r\n* improve multimodal similarity processor\r\n\r\n* tokenizer -> feature extractor\r\n\r\n* Making feature vectors come out of the feature extractor in the similarity head\r\n\r\n* embed_queries is now self-sufficient\r\n\r\n* couple trivial errors\r\n\r\n* Implemented separate language model classes for multimodal inference\r\n\r\n* Document embedding seems to work\r\n\r\n* removing batch_encode_plus, is deprecated anyway\r\n\r\n* Realized the base Data2Vec models are not trained on retrieval tasks\r\n\r\n* Issue with the generated embeddings\r\n\r\n* Add batching\r\n\r\n* Try to fit CLIP in\r\n\r\n* Stub of CLIP integration\r\n\r\n* Retrieval goes through but returns noise only\r\n\r\n* Still working on the scores\r\n\r\n* Introduce temporary adapter for CLIP models\r\n\r\n* Image retrieval now works with sentence-transformers\r\n\r\n* Tidying up the code\r\n\r\n* Refactoring is now functional\r\n\r\n* Add MPNet to the supported sentence transformers models\r\n\r\n* Remove unused classes\r\n\r\n* pylint\r\n\r\n* docs\r\n\r\n* docs\r\n\r\n* Remove the method renaming\r\n\r\n* mpyp first pass\r\n\r\n* docs\r\n\r\n* tutorial\r\n\r\n* schema\r\n\r\n* mypy\r\n\r\n* Move devices setup into get_model\r\n\r\n* more mypy\r\n\r\n* mypy\r\n\r\n* pylint\r\n\r\n* Move a few params in HaystackModel's init\r\n\r\n* make feature extractor work with squadprocessor\r\n\r\n* fix feature_extractor_kwargs forwarding\r\n\r\n* Forgotten part of the fix\r\n\r\n* Revert unrelated ES change\r\n\r\n* Revert unrelated memdocstore changes\r\n\r\n* comment\r\n\r\n* Small corrections\r\n\r\n* mypy and pylint\r\n\r\n* mypy\r\n\r\n* typo\r\n\r\n* mypy\r\n\r\n* Refactor the  call\r\n\r\n* mypy\r\n\r\n* Do not make FARMReader use the new FeatureExtractor\r\n\r\n* mypy\r\n\r\n* Detach DPR tests from FeatureExtractor too\r\n\r\n* Detach processor tests too\r\n\r\n* Add end2end marker\r\n\r\n* extract end2end feature extractor tests\r\n\r\n* temporary disable feature extraction tests\r\n\r\n* Introduce end2end tests for tokenizer tests\r\n\r\n* pylint\r\n\r\n* Fix model loading from folder in FeatureExtractor\r\n\r\n* working o n end2end\r\n\r\n* end2end keeps failing\r\n\r\n* Restructuring retriever tests\r\n\r\n* Restructuring retriever tests\r\n\r\n* remove covert_dataset_to_dataloader\r\n\r\n* remove comment\r\n\r\n* Better check sentence-transformers models\r\n\r\n* Use embed_meta_fields properly\r\n\r\n* rename passage into document\r\n\r\n* Embedding dims can't be found\r\n\r\n* Add check for models that support it\r\n\r\n* pylint\r\n\r\n* Split all retriever tests into suites, running mostly on InMemory only\r\n\r\n* fix mypy\r\n\r\n* fix tfidf test\r\n\r\n* fix weaviate tests\r\n\r\n* Parallelize on every docstore\r\n\r\n* Fix schema and specify modality in base retriever suite\r\n\r\n* tests\r\n\r\n* Add first image tests\r\n\r\n* remove comment\r\n\r\n* Revert to simpler tests\r\n\r\n* Update docs/_src/api/api/primitives.md\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Update haystack/modeling/model/multimodal/__init__.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* get_args\r\n\r\n* mypy\r\n\r\n* Update haystack/modeling/model/multimodal/__init__.py\r\n\r\n* Update haystack/modeling/model/multimodal/base.py\r\n\r\n* Update haystack/modeling/model/multimodal/base.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Update haystack/modeling/model/multimodal/sentence_transformers.py\r\n\r\n* Update haystack/modeling/model/multimodal/sentence_transformers.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Update haystack/modeling/model/multimodal/transformers.py\r\n\r\n* Update haystack/modeling/model/multimodal/transformers.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Update haystack/modeling/model/multimodal/transformers.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* Update haystack/nodes/retriever/multimodal/retriever.py\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\n\r\n* mypy\r\n\r\n* mypy\r\n\r\n* removing more ContentTypes\r\n\r\n* more contentypes\r\n\r\n* pylint\r\n\r\n* add to __init__\r\n\r\n* revert end2end workflow for now\r\n\r\n* missing integration markers\r\n\r\n* Update haystack/nodes/retriever/multimodal/embedder.py\r\n\r\nCo-authored-by: bogdankostic <bogdankostic@web.de>\r\n\r\n* review feedback, removing HaystackImageTransformerModel\r\n\r\n* review feedback part 2\r\n\r\n* mypy & pylint\r\n\r\n* mypy\r\n\r\n* mypy\r\n\r\n* fix multimodal docs also for Pinecone\r\n\r\n* add note on internal constants\r\n\r\n* Fix pinecone write_documents\r\n\r\n* schemas\r\n\r\n* keep support for sentence-transformers only\r\n\r\n* fix pinecone test\r\n\r\n* schemas\r\n\r\n* fix pinecone again\r\n\r\n* temporarily disable some tests, need to understand if they're still relevant\r\n\r\nCo-authored-by: Agnieszka Marzec <97166305+agnieszka-m@users.noreply.github.com>\r\nCo-authored-by: bogdankostic <bogdankostic@web.de>",
        "code": "def embedding_dim(self) -> int:\n        \n        emedding_dim = self.model.get_sentence_embedding_dimension()\n        if not emedding_dim:\n            logger.warning(\n                \"Can't find the output embedding dimensions for '%s'. Some checks will not run as intended.\",\n                self.model_name_or_path,\n            )\n        return emedding_dim\n",
        "url": "https://github.com/deepset-ai/haystack.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 110,
        "n_words": 30,
        "vocab_size": 28,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 34,
        "n_ast_nodes": 59,
        "n_identifiers": 9,
        "d_id": 75174,
        "documentation": {
            "docstring": "\n        Finds out the output embedding dim by running the model on a minimal amount of mock data.\n        ",
            "n_words": 17,
            "vocab_size": 16,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 60263,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/io.py",
        "file_name": "io.py",
        "fun_name": "blobprotovector_str_to_arraylist",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def blobprotovector_str_to_arraylist(str):\n    \n    vec = caffe_pb2.BlobProtoVector()\n    vec.ParseFromString(str)\n    return [blobproto_to_array(blob) for blob in vec.blobs]\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 24,
        "n_words": 12,
        "vocab_size": 12,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 32,
        "n_ast_nodes": 54,
        "n_identifiers": 9,
        "d_id": 12054,
        "documentation": {
            "docstring": "Converts a serialized blobprotovec to a list of arrays.\n    ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 47660,
        "commit_id": "49e336ae0302b386a2f47269a6d13988382d975f",
        "repo": "airflow",
        "path": "tests/sensors/test_external_task_sensor.py",
        "file_name": "test_external_task_sensor.py",
        "fun_name": "dag_bag_ext",
        "commit_message": "Replace usage of `DummyOperator` with `EmptyOperator` (#22974)\n\n* Replace usage of `DummyOperator` with `EmptyOperator`",
        "code": "def dag_bag_ext():\n    \n    clear_db_runs()\n\n    dag_bag = DagBag(dag_folder=DEV_NULL, include_examples=False)\n\n    dag_0 = DAG(\"dag_0\", start_date=DEFAULT_DATE, schedule_interval=None)\n    task_a_0 = EmptyOperator(task_id=\"task_a_0\", dag=dag_0)\n    task_b_0 = ExternalTaskMarker(\n        task_id=\"task_b_0\", external_dag_id=\"dag_1\", external_task_id=\"task_a_1\", recursion_depth=3, dag=dag_0\n    )\n    task_a_0 >> task_b_0\n\n    dag_1 = DAG(\"dag_1\", start_date=DEFAULT_DATE, schedule_interval=None)\n    task_a_1 = ExternalTaskSensor(\n        task_id=\"task_a_1\", external_dag_id=dag_0.dag_id, external_task_id=task_b_0.task_id, dag=dag_1\n    )\n    task_b_1 = ExternalTaskMarker(\n        task_id=\"task_b_1\", external_dag_id=\"dag_2\", external_task_id=\"task_a_2\", recursion_depth=2, dag=dag_1\n    )\n    task_a_1 >> task_b_1\n\n    dag_2 = DAG(\"dag_2\", start_date=DEFAULT_DATE, schedule_interval=None)\n    task_a_2 = ExternalTaskSensor(\n        task_id=\"task_a_2\", external_dag_id=dag_1.dag_id, external_task_id=task_b_1.task_id, dag=dag_2\n    )\n    task_b_2 = ExternalTaskMarker(\n        task_id=\"task_b_2\", external_dag_id=\"dag_3\", external_task_id=\"task_a_3\", recursion_depth=1, dag=dag_2\n    )\n    task_a_2 >> task_b_2\n\n    dag_3 = DAG(\"dag_3\", start_date=DEFAULT_DATE, schedule_interval=None)\n    task_a_3 = ExternalTaskSensor(\n        task_id=\"task_a_3\", external_dag_id=dag_2.dag_id, external_task_id=task_b_2.task_id, dag=dag_3\n    )\n    task_b_3 = EmptyOperator(task_id=\"task_b_3\", dag=dag_3)\n    task_a_3 >> task_b_3\n\n    for dag in [dag_0, dag_1, dag_2, dag_3]:\n        dag_bag.bag_dag(dag=dag, root_dag=dag)\n\n    yield dag_bag\n\n    clear_db_runs()\n\n\n@pytest.fixture",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 243,
        "n_words": 111,
        "vocab_size": 69,
        "complexity": 2,
        "nloc": 35,
        "token_counts": 290,
        "n_ast_nodes": 460,
        "n_identifiers": 36,
        "d_id": 9197,
        "documentation": {
            "docstring": "\n    Create a DagBag with DAGs looking like this. The dotted lines represent external dependencies\n    set up using ExternalTaskMarker and ExternalTaskSensor.\n\n    dag_0:   task_a_0 >> task_b_0\n                             |\n                             |\n    dag_1:                   ---> task_a_1 >> task_b_1\n                                                  |\n                                                  |\n    dag_2:                                        ---> task_a_2 >> task_b_2\n                                                                       |\n                                                                       |\n    dag_3:                                                             ---> task_a_3 >> task_b_3\n    ",
            "n_words": 45,
            "vocab_size": 35,
            "n_whitespaces": 480,
            "language": "en"
        }
    },
    {
        "id": 280071,
        "commit_id": "c269e3cd8fed713fb54d2971319df0bfe6e1bf10",
        "repo": "keras",
        "path": "keras/models/cloning.py",
        "file_name": "cloning.py",
        "fun_name": "clone_model",
        "commit_message": "Move serialization-related logic in utils/generic_utils.py to saving/legacy/serialization.py.\n\nPiperOrigin-RevId: 479688207",
        "code": "def clone_model(model, input_tensors=None, clone_function=None):\n    \n    with serialization.DisableSharedObjectScope():\n        if clone_function is None:\n            clone_function = _clone_layer\n\n        if isinstance(model, Sequential):\n            return _clone_sequential_model(\n                model, input_tensors=input_tensors, layer_fn=clone_function\n            )\n        else:\n            return _clone_functional_model(\n                model, input_tensors=input_tensors, layer_fn=clone_function\n            )\n\n\n# \"Clone\" a subclassed model by resetting all of the attributes.",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 151,
        "n_words": 40,
        "vocab_size": 33,
        "complexity": 3,
        "nloc": 12,
        "token_counts": 65,
        "n_ast_nodes": 103,
        "n_identifiers": 12,
        "d_id": 83239,
        "documentation": {
            "docstring": "Clone a Functional or Sequential `Model` instance.\n\n    Model cloning is similar to calling a model on new inputs,\n    except that it creates new layers (and thus new weights) instead\n    of sharing the weights of the existing layers.\n\n    Note that\n    `clone_model` will not preserve the uniqueness of shared objects within the\n    model (e.g. a single variable attached to two distinct layers will be\n    restored as two separate variables).\n\n    Args:\n        model: Instance of `Model`\n            (could be a Functional model or a Sequential model).\n        input_tensors: optional list of input tensors or InputLayer objects\n            to build the model upon. If not provided,\n            new `Input` objects will be created.\n        clone_function: Callable to be used to clone each layer in the target\n            model (except `InputLayer` instances). It takes as argument the\n            layer instance to be cloned, and returns the corresponding layer\n            instance to be used in the model copy. If unspecified, this callable\n            defaults to the following serialization/deserialization function:\n            `lambda layer: layer.__class__.from_config(layer.get_config())`.\n            By passing a custom callable, you can customize your copy of the\n            model, e.g. by wrapping certain layers of interest (you might want\n            to replace all `LSTM` instances with equivalent\n            `Bidirectional(LSTM(...))` instances, for example).\n\n    Returns:\n      An instance of `Model` reproducing the behavior\n      of the original model, on top of new inputs tensors,\n      using newly instantiated weights. The cloned model may behave\n      differently from the original model if a custom `clone_function`\n      modifies the layer.\n\n    Example:\n\n    ```python\n    # Create a test Sequential model.\n    model = keras.Sequential([\n        keras.Input(shape=(728,)),\n        keras.layers.Dense(32, activation='relu'),\n        keras.layers.Dense(1, activation='sigmoid'),\n    ])\n    # Create a copy of the test model (with freshly initialized weights).\n    new_model = clone_model(model)\n    ```\n\n    Note that subclassed models cannot be cloned, since their internal\n    layer structure is not known. To achieve equivalent functionality\n    as `clone_model` in the case of a subclassed model, simply make sure\n    that the model class implements `get_config()`\n    (and optionally `from_config()`), and call:\n\n    ```python\n    new_model = model.__class__.from_config(model.get_config())\n    ```\n    ",
            "n_words": 309,
            "vocab_size": 192,
            "n_whitespaces": 586,
            "language": "en"
        }
    },
    {
        "id": 64240,
        "commit_id": "b50036c04a116b2a3aa1784daf161a2f618765a8",
        "repo": "erpnext",
        "path": "erpnext/stock/doctype/delivery_note/delivery_note.py",
        "file_name": "delivery_note.py",
        "fun_name": "update_billed_amount_based_on_so",
        "commit_message": "fix: consider returned_qty while updating billed_amt\n\n(cherry picked from commit 63aaa1e357280b24c537a502a479f7bb7a6654e4)",
        "code": "def update_billed_amount_based_on_so(so_detail, update_modified=True):\n\t# Billed against Sales Order directly\n\tbilled_against_so = frappe.db.sql(, so_detail)\n\tbilled_against_so = billed_against_so and billed_against_so[0][0] or 0\n\n\t# Get all Delivery Note Item rows against the Sales Order Item row\n\tdn_details = frappe.db.sql(, so_detail, as_dict=1)\n\n\tupdated_dn = []\n\tfor dnd in dn_details:\n\t\tbilled_amt_agianst_dn = 0\n\n\t\t# If delivered against Sales Invoice\n\t\tif dnd.si_detail:\n\t\t\tbilled_amt_agianst_dn = flt(dnd.amount)\n\t\t\tbilled_against_so -= billed_amt_agianst_dn\n\t\telse:\n\t\t\t# Get billed amount directly against Delivery Note\n\t\t\tbilled_amt_agianst_dn = frappe.db.sql(, dnd.name)\n\t\t\tbilled_amt_agianst_dn = billed_amt_agianst_dn and billed_amt_agianst_dn[0][0] or 0\n\n\t\t# Distribute billed amount directly against SO between DNs based on FIFO\n\t\tif billed_against_so and billed_amt_agianst_dn < dnd.amount:\n\t\t\tif dnd.returned_qty:\n\t\t\t\tpending_to_bill = flt(dnd.amount) * (dnd.stock_qty - dnd.returned_qty) / dnd.stock_qty\n\t\t\telse:\n\t\t\t\tpending_to_bill = flt(dnd.amount)\n\t\t\tpending_to_bill -= billed_amt_agianst_dn\n\t\t\tif pending_to_bill <= billed_against_so:\n\t\t\t\tbilled_amt_agianst_dn += pending_to_bill\n\t\t\t\tbilled_against_so -= pending_to_bill\n\t\t\telse:\n\t\t\t\tbilled_amt_agianst_dn += billed_against_so\n\t\t\t\tbilled_against_so = 0\n\n\t\tfrappe.db.set_value(\"Delivery Note Item\", dnd.name, \"billed_amt\", billed_amt_agianst_dn, update_modified=update_modified)\n\n\t\tupdated_dn.append(dnd.parent)\n\n\treturn updated_dn\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 112,
        "n_words": 145,
        "vocab_size": 75,
        "complexity": 11,
        "nloc": 44,
        "token_counts": 205,
        "n_ast_nodes": 331,
        "n_identifiers": 22,
        "d_id": 13584,
        "documentation": {
            "docstring": "select sum(si_item.amount)\n\t\tfrom `tabSales Invoice Item` si_item, `tabSales Invoice` si\n\t\twhere\n\t\t\tsi_item.parent = si.name\n\t\t\tand si_item.so_detail=%s\n\t\t\tand (si_item.dn_detail is null or si_item.dn_detail = '')\n\t\t\tand si_item.docstatus=1\n\t\t\tand si.update_stock = 0\n\t\tselect dn_item.name, dn_item.amount, dn_item.si_detail, dn_item.parent, dn_item.stock_qty, dn_item.returned_qty\n\t\tfrom `tabDelivery Note Item` dn_item, `tabDelivery Note` dn\n\t\twhere\n\t\t\tdn.name = dn_item.parent\n\t\t\tand dn_item.so_detail=%s\n\t\t\tand dn.docstatus=1\n\t\t\tand dn.is_return = 0\n\t\torder by dn.posting_date asc, dn.posting_time asc, dn.name ascselect sum(amount) from `tabSales Invoice Item`\n\t\t\t\twhere dn_detail=%s and docstatus=1",
            "n_words": 74,
            "vocab_size": 49,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 176311,
        "commit_id": "930121ffb89d01077b9888abbd5e810a7e5e16a4",
        "repo": "networkx",
        "path": "networkx/algorithms/shortest_paths/dense.py",
        "file_name": "dense.py",
        "fun_name": "floyd_warshall_numpy",
        "commit_message": "More numpy.matrix cleanups for NX2.7 (#5319)\n\n* Fix return type in docstring of internal function.\r\n\r\n* Rm explicit mention of numpy matrix from class docstrings.\r\n\r\n* Fix return type of floyd_warshall_numpy docstring.\r\n\r\n* Remove mention of numpy matrix from code comment.\r\n\r\n* Fix simrank similarity internal docstring.\r\n\r\n* Rm explicit mention of matrix in favor of 2D array.\r\n\r\n* Update to_networkx_graph array exception wording.\r\n\r\n* Remove extraneous mention of numpy matrix.\r\n\r\n* Don't print array in exception message.",
        "code": "def floyd_warshall_numpy(G, nodelist=None, weight=\"weight\"):\n    \n    import numpy as np\n\n    if nodelist is not None:\n        if not (len(nodelist) == len(G) == len(set(nodelist))):\n            raise nx.NetworkXError(\n                \"nodelist must contain every node in G with no repeats.\"\n                \"If you wanted a subgraph of G use G.subgraph(nodelist)\"\n            )\n\n    # To handle cases when an edge has weight=0, we must make sure that\n    # nonedges are not given the value 0 as well.\n    A = nx.to_numpy_array(\n        G, nodelist, multigraph_weight=min, weight=weight, nonedge=np.inf\n    )\n    n, m = A.shape\n    np.fill_diagonal(A, 0)  # diagonal elements should be zero\n    for i in range(n):\n        # The second term has the same shape as A due to broadcasting\n        A = np.minimum(A, A[i, :][np.newaxis, :] + A[:, i][:, np.newaxis])\n    return A\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 230,
        "n_words": 116,
        "vocab_size": 96,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 139,
        "n_ast_nodes": 220,
        "n_identifiers": 24,
        "d_id": 41826,
        "documentation": {
            "docstring": "Find all-pairs shortest path lengths using Floyd's algorithm.\n\n    This algorithm for finding shortest paths takes advantage of\n    matrix representations of a graph and works well for dense\n    graphs where all-pairs shortest path lengths are desired.\n    The results are returned as a NumPy array, distance[i, j],\n    where i and j are the indexes of two nodes in nodelist.\n    The entry distance[i, j] is the distance along a shortest\n    path from i to j. If no path exists the distance is Inf.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n\n    nodelist : list, optional (default=G.nodes)\n       The rows and columns are ordered by the nodes in nodelist.\n       If nodelist is None then the ordering is produced by G.nodes.\n       Nodelist should include all nodes in G.\n\n    weight: string, optional (default='weight')\n       Edge data key corresponding to the edge weight.\n\n    Returns\n    -------\n    distance : 2D numpy.ndarray\n        A numpy array of shortest path distances between nodes.\n        If there is no path between two nodes the value is Inf.\n\n    Notes\n    -----\n    Floyd's algorithm is appropriate for finding shortest paths in\n    dense graphs or graphs with negative weights when Dijkstra's\n    algorithm fails. This algorithm can still fail if there are negative\n    cycles. It has running time $O(n^3)$ with running space of $O(n^2)$.\n\n    Raises\n    ------\n    NetworkXError\n        If nodelist is not a list of the nodes in G.\n    ",
            "n_words": 215,
            "vocab_size": 127,
            "n_whitespaces": 335,
            "language": "en"
        }
    },
    {
        "id": 217315,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/enum.py",
        "file_name": "enum.py",
        "fun_name": "__getattr__",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def __getattr__(cls, name):\n        \n        if _is_dunder(name):\n            raise AttributeError(name)\n        try:\n            return cls._member_map_[name]\n        except KeyError:\n            raise AttributeError(name) from None\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 77,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 38,
        "n_ast_nodes": 62,
        "n_identifiers": 7,
        "d_id": 54713,
        "documentation": {
            "docstring": "\n        Return the enum member matching `name`\n\n        We use __getattr__ instead of descriptors or inserting into the enum\n        class' __dict__ in order to support `name` and `value` being both\n        properties for enum members (which live in the class' __dict__) and\n        enum members themselves.\n        ",
            "n_words": 42,
            "vocab_size": 32,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 269045,
        "commit_id": "b3f1f645238c93ec3b283f64f73a02df3aea6b53",
        "repo": "keras",
        "path": "keras/preprocessing/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "index_subdirectory",
        "commit_message": "use tf.io.gfile instead of os.path to support cloud paths.\n\nPiperOrigin-RevId: 430975400",
        "code": "def index_subdirectory(directory, class_indices, follow_links, formats):\n  \n  dirname = os.path.basename(directory)\n  valid_files = iter_valid_files(directory, follow_links, formats)\n  labels = []\n  filenames = []\n  for root, fname in valid_files:\n    labels.append(class_indices[dirname])\n    absolute_path = tf.io.gfile.join(root, fname)\n    relative_path = tf.io.gfile.join(\n        dirname, os.path.relpath(absolute_path, directory))\n    filenames.append(relative_path)\n  return filenames, labels\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 65,
        "n_words": 39,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 103,
        "n_ast_nodes": 158,
        "n_identifiers": 23,
        "d_id": 79856,
        "documentation": {
            "docstring": "Recursively walks directory and list image paths and their class index.\n\n  Args:\n    directory: string, target directory.\n    class_indices: dict mapping class names to their index.\n    follow_links: boolean, whether to recursively follow subdirectories\n      (if False, we only list top-level images in `directory`).\n    formats: Allowlist of file extensions to index (e.g. \".jpg\", \".txt\").\n\n  Returns:\n    tuple `(filenames, labels)`. `filenames` is a list of relative file\n      paths, and `labels` is a list of integer labels corresponding to these\n      files.\n  ",
            "n_words": 74,
            "vocab_size": 58,
            "n_whitespaces": 107,
            "language": "en"
        }
    },
    {
        "id": 300810,
        "commit_id": "69cc6ab5f1d58adc586c3b300a4f7f0cde2cd0c2",
        "repo": "core",
        "path": "tests/auth/test_auth_store.py",
        "file_name": "test_auth_store.py",
        "fun_name": "test_loading_race_condition",
        "commit_message": "Clean up accessing entity_registry.async_get_registry helper via hass (#72005)",
        "code": "async def test_loading_race_condition(hass):\n    \n    store = auth_store.AuthStore(hass)\n    with patch(\n        \"homeassistant.helpers.entity_registry.async_get\"\n    ) as mock_ent_registry, patch(\n        \"homeassistant.helpers.device_registry.async_get\"\n    ) as mock_dev_registry, patch(\n        \"homeassistant.helpers.storage.Store.async_load\", return_value=None\n    ) as mock_load:\n        results = await asyncio.gather(store.async_get_users(), store.async_get_users())\n\n        mock_ent_registry.assert_called_once_with(hass)\n        mock_dev_registry.assert_called_once_with(hass)\n        mock_load.assert_called_once_with()\n        assert results[0] == results[1]\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 109,
        "n_words": 35,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 86,
        "n_ast_nodes": 152,
        "n_identifiers": 15,
        "d_id": 99666,
        "documentation": {
            "docstring": "Test only one storage load called when concurrent loading occurred .",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 244526,
        "commit_id": "015f8a9bafe808fbe3db673d629f126a804a9207",
        "repo": "mmdetection",
        "path": "tests/test_models/test_dense_heads/test_fcos_head.py",
        "file_name": "test_fcos_head.py",
        "fun_name": "test_fcos_head_loss",
        "commit_message": "Refactor interface of base dense free head and fcos head",
        "code": "def test_fcos_head_loss(self):\n        \n        s = 256\n        img_metas = [{\n            'img_shape': (s, s, 3),\n            'scale_factor': 1,\n        }]\n        fcos_head = FCOSHead(\n            num_classes=4,\n            in_channels=1,\n            feat_channels=1,\n            stacked_convs=1,\n            norm_cfg=None)\n\n        # Fcos head expects a multiple levels of features per image\n        feats = (\n            torch.rand(1, 1, s // stride[1], s // stride[0])\n            for stride in fcos_head.prior_generator.strides)\n        cls_scores, bbox_preds, centernesses = fcos_head.forward(feats)\n\n        # Test that empty ground truth encourages the network to\n        # predict background\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.empty((0, 4))\n        gt_instances.labels = torch.LongTensor([])\n\n        empty_gt_losses = fcos_head.loss(cls_scores, bbox_preds, centernesses,\n                                         [gt_instances], img_metas)\n        # When there is no truth, the cls loss should be nonzero but\n        # box loss and centerness loss should be zero\n        empty_cls_loss = empty_gt_losses['loss_cls'].item()\n        empty_box_loss = empty_gt_losses['loss_bbox'].item()\n        empty_ctr_loss = empty_gt_losses['loss_centerness'].item()\n        self.assertGreater(empty_cls_loss, 0, 'cls loss should be non-zero')\n        self.assertEqual(\n            empty_box_loss, 0,\n            'there should be no box loss when there are no true boxes')\n        self.assertEqual(\n            empty_ctr_loss, 0,\n            'there should be no centerness loss when there are no true boxes')\n\n        # When truth is non-empty then all cls, box loss and centerness loss\n        # should be nonzero for random inputs\n        gt_instances = InstanceData()\n        gt_instances.bboxes = torch.Tensor(\n            [[23.6667, 23.8757, 238.6326, 151.8874]])\n        gt_instances.labels = torch.LongTensor([2])\n\n        one_gt_losses = fcos_head.loss(cls_scores, bbox_preds, centernesses,\n                                       [gt_instances], img_metas)\n        onegt_cls_loss = one_gt_losses['loss_cls'].item()\n        onegt_box_loss = one_gt_losses['loss_bbox'].item()\n        onegt_ctr_loss = one_gt_losses['loss_centerness'].item()\n        self.assertGreater(onegt_cls_loss, 0, 'cls loss should be non-zero')\n        self.assertGreater(onegt_box_loss, 0, 'box loss should be non-zero')\n        self.assertGreater(onegt_ctr_loss, 0,\n                           'centerness loss should be non-zero')\n\n        # Test the `center_sampling` works fine.\n        fcos_head.center_sampling = True\n        ctrsamp_losses = fcos_head.loss(cls_scores, bbox_preds, centernesses,\n                                        [gt_instances], img_metas)\n        ctrsamp_cls_loss = ctrsamp_losses['loss_cls'].item()\n        ctrsamp_box_loss = ctrsamp_losses['loss_bbox'].item()\n        ctrsamp_ctr_loss = ctrsamp_losses['loss_centerness'].item()\n        self.assertGreater(ctrsamp_cls_loss, 0, 'cls loss should be non-zero')\n        self.assertGreater(ctrsamp_box_loss, 0, 'box loss should be non-zero')\n        self.assertGreater(ctrsamp_ctr_loss, 0,\n                           'centerness loss should be non-zero')\n\n        # Test the `norm_on_bbox` works fine.\n        fcos_head.norm_on_bbox = True\n        normbox_losses = fcos_head.loss(cls_scores, bbox_preds, centernesses,\n                                        [gt_instances], img_metas)\n        normbox_cls_loss = normbox_losses['loss_cls'].item()\n        normbox_box_loss = normbox_losses['loss_bbox'].item()\n        normbox_ctr_loss = normbox_losses['loss_centerness'].item()\n        self.assertGreater(normbox_cls_loss, 0, 'cls loss should be non-zero')\n        self.assertGreater(normbox_box_loss, 0, 'box loss should be non-zero')\n        self.assertGreater(normbox_ctr_loss, 0,\n                           'centerness loss should be non-zero')\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 1066,
        "n_words": 314,
        "vocab_size": 153,
        "complexity": 2,
        "nloc": 64,
        "token_counts": 484,
        "n_ast_nodes": 780,
        "n_identifiers": 50,
        "d_id": 70419,
        "documentation": {
            "docstring": "Tests fcos head loss when truth is empty and non-empty.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 247584,
        "commit_id": "605d161d7d585847fd1bb98d14d5281daeac8e86",
        "repo": "synapse",
        "path": "tests/util/test_rwlock.py",
        "file_name": "test_rwlock.py",
        "fun_name": "test_cancellation_while_holding_read_lock",
        "commit_message": "Add cancellation support to `ReadWriteLock` (#12120)\n\nAlso convert `ReadWriteLock` to use async context managers.\r\n\r\nSigned-off-by: Sean Quah <seanq@element.io>",
        "code": "def test_cancellation_while_holding_read_lock(self):\n        \n        rwlock = ReadWriteLock()\n        key = \"key\"\n\n        # 1. A reader takes the lock and blocks.\n        reader_d, _, _ = self._start_blocking_reader(rwlock, key, \"read completed\")\n\n        # 2. A writer waits for the reader to complete.\n        writer_d, _ = self._start_nonblocking_writer(rwlock, key, \"write completed\")\n        self.assertFalse(writer_d.called)\n\n        # 3. The reader is cancelled.\n        reader_d.cancel()\n        self.failureResultOf(reader_d, CancelledError)\n\n        # 4. The writer should take the lock and complete.\n        self.assertTrue(\n            writer_d.called, \"Writer is stuck waiting for a cancelled reader\"\n        )\n        self.assertEqual(\"write completed\", self.successResultOf(writer_d))\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 192,
        "n_words": 76,
        "vocab_size": 55,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 88,
        "n_ast_nodes": 152,
        "n_identifiers": 18,
        "d_id": 71759,
        "documentation": {
            "docstring": "Test cancellation while holding a read lock.\n\n        A waiting writer should be given the lock when the reader holding the lock is\n        cancelled.\n        ",
            "n_words": 23,
            "vocab_size": 19,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 21896,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/chardet/cli/chardetect.py",
        "file_name": "chardetect.py",
        "fun_name": "description_of",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def description_of(lines, name=\"stdin\"):\n    \n    u = UniversalDetector()\n    for line in lines:\n        line = bytearray(line)\n        u.feed(line)\n        # shortcut out of the loop to save reading further - particularly useful if we read a BOM.\n        if u.done:\n            break\n    u.close()\n    result = u.result\n    if result[\"encoding\"]:\n        return f'{name}: {result[\"encoding\"]} with confidence {result[\"confidence\"]}'\n    return f\"{name}: no result\"\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 118,
        "n_words": 51,
        "vocab_size": 45,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 60,
        "n_ast_nodes": 133,
        "n_identifiers": 11,
        "d_id": 4090,
        "documentation": {
            "docstring": "\n    Return a string describing the probable encoding of a file or\n    list of strings.\n\n    :param lines: The lines to get the encoding of.\n    :type lines: Iterable of bytes\n    :param name: Name of file or collection of lines\n    :type name: str\n    ",
            "n_words": 40,
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            "language": "en"
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    },
    {
        "id": 252727,
        "commit_id": "42ccc85b6f1881d92b55e411ba9719f26459b720",
        "repo": "mitmproxy",
        "path": "mitmproxy/addons/proxyserver.py",
        "file_name": "proxyserver.py",
        "fun_name": "load",
        "commit_message": "[quic] work on eventify layers",
        "code": "def load(self, loader):\n        loader.add_option(\n            \"connection_strategy\",\n            str,\n            \"eager\",\n            \"Determine when server connections should be established. When set to lazy, mitmproxy \"\n            \"tries to defer establishing an upstream connection as long as possible. This makes it possible to \"\n            \"use server replay while being offline. When set to eager, mitmproxy can detect protocols with \"\n            \"server-side greetings, as well as accurately mirror TLS ALPN negotiation.\",\n            choices=(\"eager\", \"lazy\"),\n        )\n        loader.add_option(\n            \"stream_large_bodies\",\n            Optional[str],\n            None,\n            ,\n        )\n        loader.add_option(\n            \"body_size_limit\",\n            Optional[str],\n            None,\n            ,\n        )\n        loader.add_option(\n            \"keep_host_header\",\n            bool,\n            False,\n            ,\n        )\n        loader.add_option(\n            \"proxy_debug\",\n            bool,\n            False,\n            \"Enable debug logs in the proxy core.\",\n        )\n        loader.add_option(\n            \"normalize_outbound_headers\",\n            bool,\n            True,\n            ,\n        )\n        loader.add_option(\n            \"validate_inbound_headers\",\n            bool,\n            True,\n            ,\n        )\n        loader.add_option(\n            \"connect_addr\",\n            Optional[str],\n            None,\n            ,\n        )\n",
        "url": "https://github.com/mitmproxy/mitmproxy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 621,
        "n_words": 114,
        "vocab_size": 74,
        "complexity": 1,
        "nloc": 76,
        "token_counts": 144,
        "n_ast_nodes": 217,
        "n_identifiers": 8,
        "d_id": 73982,
        "documentation": {
            "docstring": "\n            Stream data to the client if response body exceeds the given\n            threshold. If streamed, the body will not be stored in any way.\n            Understands k/m/g suffixes, i.e. 3m for 3 megabytes.\n            \n            Byte size limit of HTTP request and response bodies. Understands\n            k/m/g suffixes, i.e. 3m for 3 megabytes.\n            \n            Reverse Proxy: Keep the original host header instead of rewriting it\n            to the reverse proxy target.\n            \n            Normalize outgoing HTTP/2 header names, but emit a warning when doing so.\n            HTTP/2 does not allow uppercase header names. This option makes sure that HTTP/2 headers set\n            in custom scripts are lowercased before they are sent.\n            \n            Make sure that incoming HTTP requests are not malformed.\n            Disabling this option makes mitmproxy vulnerable to HTTP smuggling attacks.\n            Set the local IP address that mitmproxy should use when connecting to upstream servers.",
            "n_words": 133,
            "vocab_size": 96,
            "n_whitespaces": 324,
            "language": "en"
        }
    },
    {
        "id": 206695,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/http.py",
        "file_name": "http.py",
        "fun_name": "parse_etags",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def parse_etags(etag_str):\n    \n    if etag_str.strip() == \"*\":\n        return [\"*\"]\n    else:\n        # Parse each ETag individually, and return any that are valid.\n        etag_matches = (ETAG_MATCH.match(etag.strip()) for etag in etag_str.split(\",\"))\n        return [match[1] for match in etag_matches if match]\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 72,
        "n_words": 35,
        "vocab_size": 29,
        "complexity": 5,
        "nloc": 6,
        "token_counts": 57,
        "n_ast_nodes": 99,
        "n_identifiers": 8,
        "d_id": 51638,
        "documentation": {
            "docstring": "\n    Parse a string of ETags given in an If-None-Match or If-Match header as\n    defined by RFC 7232. Return a list of quoted ETags, or ['*'] if all ETags\n    should be matched.\n    ",
            "n_words": 31,
            "vocab_size": 27,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 63755,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/six.py",
        "file_name": "six.py",
        "fun_name": "print_",
        "commit_message": "upd; format",
        "code": "def print_(*args, **kwargs):\n        \n        fp = kwargs.pop(\"file\", sys.stdout)\n        if fp is None:\n            return\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 44,
        "n_words": 12,
        "vocab_size": 11,
        "complexity": 17,
        "nloc": 40,
        "token_counts": 208,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 13497,
        "documentation": {
            "docstring": "The new-style print function for Python 2.4 and 2.5.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 196406,
        "commit_id": "59d22b6bb7287613d598611027f640d068ca5748",
        "repo": "sympy",
        "path": "sympy/matrices/solvers.py",
        "file_name": "solvers.py",
        "fun_name": "_solve_least_squares",
        "commit_message": "Moved imports to higher level",
        "code": "def _solve_least_squares(M, rhs, method='CH'):\n    \n\n    if method == 'CH':\n        return M.cholesky_solve(rhs)\n    elif method == 'QR':\n        return M.QRsolve(rhs)\n    elif method == 'LDL':\n        return M.LDLsolve(rhs)\n    elif method == 'PINV':\n        return M.pinv_solve(rhs)\n    else:\n        t = M.H\n        return (t * M).solve(t * rhs, method=method)\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 99,
        "n_words": 39,
        "vocab_size": 25,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 84,
        "n_ast_nodes": 143,
        "n_identifiers": 11,
        "d_id": 47906,
        "documentation": {
            "docstring": "Return the least-square fit to the data.\n\n    Parameters\n    ==========\n\n    rhs : Matrix\n        Vector representing the right hand side of the linear equation.\n\n    method : string or boolean, optional\n        If set to ``'CH'``, ``cholesky_solve`` routine will be used.\n\n        If set to ``'LDL'``, ``LDLsolve`` routine will be used.\n\n        If set to ``'QR'``, ``QRsolve`` routine will be used.\n\n        If set to ``'PINV'``, ``pinv_solve`` routine will be used.\n\n        Otherwise, the conjugate of ``M`` will be used to create a system\n        of equations that is passed to ``solve`` along with the hint\n        defined by ``method``.\n\n    Returns\n    =======\n\n    solutions : Matrix\n        Vector representing the solution.\n\n    Examples\n    ========\n\n    >>> from sympy import Matrix, ones\n    >>> A = Matrix([1, 2, 3])\n    >>> B = Matrix([2, 3, 4])\n    >>> S = Matrix(A.row_join(B))\n    >>> S\n    Matrix([\n    [1, 2],\n    [2, 3],\n    [3, 4]])\n\n    If each line of S represent coefficients of Ax + By\n    and x and y are [2, 3] then S*xy is:\n\n    >>> r = S*Matrix([2, 3]); r\n    Matrix([\n    [ 8],\n    [13],\n    [18]])\n\n    But let's add 1 to the middle value and then solve for the\n    least-squares value of xy:\n\n    >>> xy = S.solve_least_squares(Matrix([8, 14, 18])); xy\n    Matrix([\n    [ 5/3],\n    [10/3]])\n\n    The error is given by S*xy - r:\n\n    >>> S*xy - r\n    Matrix([\n    [1/3],\n    [1/3],\n    [1/3]])\n    >>> _.norm().n(2)\n    0.58\n\n    If a different xy is used, the norm will be higher:\n\n    >>> xy += ones(2, 1)/10\n    >>> (S*xy - r).norm().n(2)\n    1.5\n\n    ",
            "n_words": 232,
            "vocab_size": 143,
            "n_whitespaces": 427,
            "language": "en"
        }
    },
    {
        "id": 77267,
        "commit_id": "37784643e9207380abaed3c5720dbbcaf69b473b",
        "repo": "wagtail",
        "path": "wagtail/admin/panels.py",
        "file_name": "panels.py",
        "fun_name": "get_bound_panel",
        "commit_message": "API docs for Panel",
        "code": "def get_bound_panel(self, instance=None, request=None, form=None):\n        \n        if self.model is None:\n            raise ImproperlyConfigured(\n                \"%s.bind_to_model(model) must be called before get_bound_panel\"\n                % type(self).__name__\n            )\n\n        if not issubclass(self.BoundPanel, EditHandler.BoundPanel):\n            raise ImproperlyConfigured(\n                \"%s.BoundPanel must be a subclass of EditHandler.BoundPanel\"\n                % type(self).__name__\n            )\n\n        return self.BoundPanel(\n            panel=self, instance=instance, request=request, form=form\n        )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 193,
        "n_words": 43,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 14,
        "token_counts": 83,
        "n_ast_nodes": 130,
        "n_identifiers": 13,
        "d_id": 16647,
        "documentation": {
            "docstring": "\n        Return a ``BoundPanel`` instance that can be rendered onto the template as a component. By default, this creates an instance\n        of the panel class's inner ``BoundPanel`` class, which must inherit from ``Panel.BoundPanel``.\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 259553,
        "commit_id": "6528e14085d059f9d0c94f93378e7e3c0b967f27",
        "repo": "scikit-learn",
        "path": "sklearn/linear_model/tests/test_ridge.py",
        "file_name": "test_ridge.py",
        "fun_name": "ols_ridge_dataset",
        "commit_message": "TST tight and clean tests for Ridge (#22910)\n\n* MNT replace pinvh by solve\r\n\r\n* DOC more info for svd solver\r\n\r\n* TST rewrite test_ridge\r\n\r\n* MNT remove test_ridge_singular\r\n\r\n* MNT restructure into several tests\r\n\r\n* MNT remove test_toy_ridge_object\r\n\r\n* MNT remove test_ridge_sparse_svd\r\n\r\nThis is tested in test_ridge_fit_intercept_sparse_error.\r\n\r\n* TST exclude cholesky from singular problem\r\n\r\n* CLN two fixes\r\n\r\n* MNT parametrize test_ridge_sample_weights\r\n\r\n* MNT restructure test_ridge_sample_weights\r\n\r\n* CLN tighten tolerance for sag solver\r\n\r\n* CLN try to fix saga tolerance\r\n\r\n* CLN make test_ridge_sample_weights nicer\r\n\r\n* MNT remove test_ridge_regression_sample_weights\r\n\r\n* MNT rename to test_ridge_regression_sample_weights\r\n\r\n* CLN make test_ridge_regression_unpenalized pass for all random seeds\r\n\r\n* CLN make tests pass for all random seeds\r\n\r\n* DOC fix typos\r\n\r\n* TST skip cholesky for singular problems\r\n\r\n* MNT move up test_ridge_regression_sample_weights\r\n\r\n* CLN set skip reason as comment",
        "code": "def ols_ridge_dataset(global_random_seed, request):\n    \n    # Make larger dim more than double as big as the smaller one.\n    # This helps when constructing singular matrices like (X, X).\n    if request.param == \"long\":\n        n_samples, n_features = 12, 4\n    else:\n        n_samples, n_features = 4, 12\n    k = min(n_samples, n_features)\n    rng = np.random.RandomState(global_random_seed)\n    X = make_low_rank_matrix(\n        n_samples=n_samples, n_features=n_features, effective_rank=k\n    )\n    X[:, -1] = 1  # last columns acts as intercept\n    U, s, Vt = linalg.svd(X)\n    assert np.all(s) > 1e-3  # to be sure\n    U1, U2 = U[:, :k], U[:, k:]\n    Vt1, _ = Vt[:k, :], Vt[k:, :]\n\n    if request.param == \"long\":\n        # Add a term that vanishes in the product X'y\n        coef_ols = rng.uniform(low=-10, high=10, size=n_features)\n        y = X @ coef_ols\n        y += U2 @ rng.normal(size=n_samples - n_features) ** 2\n    else:\n        y = rng.uniform(low=-10, high=10, size=n_samples)\n        # w = X'(XX')^-1 y = V s^-1 U' y\n        coef_ols = Vt1.T @ np.diag(1 / s) @ U1.T @ y\n\n    # Add penalty alpha * ||coef||_2^2 for alpha=1 and solve via normal equations.\n    # Note that the problem is well conditioned such that we get accurate results.\n    alpha = 1\n    d = alpha * np.identity(n_features)\n    d[-1, -1] = 0  # intercept gets no penalty\n    coef_ridge = linalg.solve(X.T @ X + d, X.T @ y)\n\n    # To be sure\n    R_OLS = y - X @ coef_ols\n    R_Ridge = y - X @ coef_ridge\n    assert np.linalg.norm(R_OLS) < np.linalg.norm(R_Ridge)\n\n    return X, y, coef_ols, coef_ridge\n\n\n@pytest.mark.parametrize(\"solver\", SOLVERS)\n@pytest.mark.parametrize(\"fit_intercept\", [True, False])",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"solver\", SOLVERS)\n@pytest.mark.parametrize(\"fit_intercept\", [True, False])",
        "n_ast_errors": 1,
        "ast_levels": 15,
        "n_whitespaces": 390,
        "n_words": 238,
        "vocab_size": 154,
        "complexity": 3,
        "nloc": 30,
        "token_counts": 306,
        "n_ast_nodes": 524,
        "n_identifiers": 46,
        "d_id": 75817,
        "documentation": {
            "docstring": "Dataset with OLS and Ridge solutions, well conditioned X.\n\n    The construction is based on the SVD decomposition of X = U S V'.\n\n    Parameters\n    ----------\n    type : {\"long\", \"wide\"}\n        If \"long\", then n_samples > n_features.\n        If \"wide\", then n_features > n_samples.\n\n    For \"wide\", we return the minimum norm solution w = X' (XX')^-1 y:\n\n        min ||w||_2 subject to X w = y\n\n    Returns\n    -------\n    X : ndarray\n        Last column of 1, i.e. intercept.\n    y : ndarray\n    coef_ols : ndarray of shape\n        Minimum norm OLS solutions, i.e. min ||X w - y||_2_2 (with mininum ||w||_2 in\n        case of ambiguity)\n        Last coefficient is intercept.\n    coef_ridge : ndarray of shape (5,)\n        Ridge solution with alpha=1, i.e. min ||X w - y||_2_2 + ||w||_2^2.\n        Last coefficient is intercept.\n    ",
            "n_words": 124,
            "vocab_size": 78,
            "n_whitespaces": 223,
            "language": "en"
        }
    },
    {
        "id": 65320,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/purchase_register/purchase_register.py",
        "file_name": "purchase_register.py",
        "fun_name": "get_supplier_details",
        "commit_message": "style: format code with black",
        "code": "def get_supplier_details(suppliers):\n\tsupplier_details = {}\n\tfor supp in frappe.db.sql(\n\t\t\n\t\t% \", \".join([\"%s\"] * len(suppliers)),\n\t\ttuple(suppliers),\n\t\tas_dict=1,\n\t):\n\t\tsupplier_details.setdefault(supp.name, supp.supplier_group)\n\n\treturn supplier_details\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 12,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 59,
        "n_ast_nodes": 96,
        "n_identifiers": 14,
        "d_id": 13854,
        "documentation": {
            "docstring": "select name, supplier_group from `tabSupplier`\n\t\twhere name in (%s)",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 246209,
        "commit_id": "901b264c0c88f39cbfb8b2229e0dc57968882658",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_get_whois_admin",
        "commit_message": "Add type hints to `tests/rest/admin` (#11851)",
        "code": "def test_get_whois_admin(self) -> None:\n        \n        channel = self.make_request(\n            \"GET\",\n            self.url,\n            access_token=self.admin_user_tok,\n        )\n        self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)\n        self.assertEqual(self.other_user, channel.json_body[\"user_id\"])\n        self.assertIn(\"devices\", channel.json_body)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 93,
        "n_words": 18,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 70,
        "n_ast_nodes": 112,
        "n_identifiers": 15,
        "d_id": 71103,
        "documentation": {
            "docstring": "\n        The lookup should succeed for an admin.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 92047,
        "commit_id": "d2fdbaf39e38bacf1fc5924b3feeb46f26de2171",
        "repo": "sentry",
        "path": "src/sentry/tasks/relay.py",
        "file_name": "relay.py",
        "fun_name": "compute_configs",
        "commit_message": "feat(relay): Eagerly recalculate project options in compute_configs (#36059)",
        "code": "def compute_configs(organization_id=None, project_id=None, public_key=None):\n    \n    from sentry.models import Project, ProjectKey\n\n    validate_args(organization_id, project_id, public_key)\n    configs = {}\n\n    if organization_id:\n        # We want to re-compute all projects in an organization, instead of simply\n        # removing the configs and rely on relay requests to lazily re-compute them.  This\n        # is done because we do want want to delete project configs in `invalidate_project_config`\n        # which might cause the key to disappear and trigger the task again.  Without this behavior\n        # it could be possible that refrequent invalidations cause the task to take excessive time\n        # to complete.\n        projects = list(Project.objects.filter(organization_id=organization_id))\n        for key in ProjectKey.objects.filter(project__in=projects):\n            # If we find the config in the cache it means it was active.  As such we want to\n            # recalculate it.  If the config was not there at all, we leave it and avoid the\n            # cost of re-computation.\n            if projectconfig_cache.get(key.public_key) is not None:\n                configs[key.public_key] = compute_projectkey_config(key)\n    elif project_id:\n        for key in ProjectKey.objects.filter(project_id=project_id):\n            configs[key.public_key] = compute_projectkey_config(key)\n    elif public_key:\n        try:\n            key = ProjectKey.objects.get(public_key=public_key)\n        except ProjectKey.DoesNotExist:\n            # The invalidation task was triggered for a deletion and the\n            # ProjectKey should be deleted from the cache.\n            #\n            # This used to delete the cache entry instead of disabling it. The\n            # reason for that was to work around a bug in our model signal\n            # handlers that sent off the invalidation tasks before the DB\n            # transaction was committed, causing us to write stale caches. That\n            # bug was fixed in https://github.com/getsentry/sentry/pull/35671\n            configs[public_key] = {\"disabled\": True}\n        else:\n            configs[public_key] = compute_projectkey_config(key)\n\n    else:\n        raise TypeError(\"One of the arguments must not be None\")\n\n    return configs\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 572,
        "n_words": 259,
        "vocab_size": 148,
        "complexity": 8,
        "nloc": 22,
        "token_counts": 172,
        "n_ast_nodes": 291,
        "n_identifiers": 21,
        "d_id": 18859,
        "documentation": {
            "docstring": "Computes all configs for the org, project or single public key.\n\n    You must only provide one single argument, not all.\n\n    :returns: A dict mapping all affected public keys to their config.  The dict will not\n       contain keys which should be retained in the cache unchanged.\n    ",
            "n_words": 45,
            "vocab_size": 38,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 218383,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/inspect.py",
        "file_name": "inspect.py",
        "fun_name": "_signature_get_bound_param",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _signature_get_bound_param(spec):\n    \n\n    assert spec.startswith('($')\n\n    pos = spec.find(',')\n    if pos == -1:\n        pos = spec.find(')')\n\n    cpos = spec.find(':')\n    assert cpos == -1 or cpos > pos\n\n    cpos = spec.find('=')\n    assert cpos == -1 or cpos > pos\n\n    return spec[2:pos]\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 72,
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        "complexity": 4,
        "nloc": 10,
        "token_counts": 76,
        "n_ast_nodes": 134,
        "n_identifiers": 6,
        "d_id": 55271,
        "documentation": {
            "docstring": " Private helper to get first parameter name from a\n    __text_signature__ of a builtin method, which should\n    be in the following format: '($param1, ...)'.\n    Assumptions are that the first argument won't have\n    a default value or an annotation.\n    ",
            "n_words": 37,
            "vocab_size": 33,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 67870,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/stock/report/incorrect_stock_value_report/incorrect_stock_value_report.py",
        "file_name": "incorrect_stock_value_report.py",
        "fun_name": "get_data",
        "commit_message": "style: format code with black",
        "code": "def get_data(report_filters):\n\tfrom_date = get_unsync_date(report_filters)\n\n\tif not from_date:\n\t\treturn []\n\n\tresult = []\n\n\tvoucher_wise_dict = {}\n\tdata = frappe.db.sql(\n\t\t,\n\t\t(from_date, report_filters.company),\n\t\tas_dict=1,\n\t)\n\n\tfor d in data:\n\t\tvoucher_wise_dict.setdefault((d.item_code, d.warehouse), []).append(d)\n\n\tclosing_date = add_days(from_date, -1)\n\tfor key, stock_data in voucher_wise_dict.items():\n\t\tprev_stock_value = get_stock_value_on(\n\t\t\tposting_date=closing_date, item_code=key[0], warehouse=key[1]\n\t\t)\n\t\tfor data in stock_data:\n\t\t\texpected_stock_value = prev_stock_value + data.stock_value_difference\n\t\t\tif abs(data.stock_value - expected_stock_value) > 0.1:\n\t\t\t\tdata.difference_value = abs(data.stock_value - expected_stock_value)\n\t\t\t\tdata.expected_stock_value = expected_stock_value\n\t\t\t\tresult.append(data)\n\n\treturn result\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 48,
        "n_words": 73,
        "vocab_size": 50,
        "complexity": 6,
        "nloc": 36,
        "token_counts": 169,
        "n_ast_nodes": 258,
        "n_identifiers": 30,
        "d_id": 14647,
        "documentation": {
            "docstring": "\n\t\t\tSELECT\n\t\t\t\tname, posting_date, posting_time, voucher_type, voucher_no,\n\t\t\t\tstock_value_difference, stock_value, warehouse, item_code\n\t\t\tFROM\n\t\t\t\t`tabStock Ledger Entry`\n\t\t\tWHERE\n\t\t\t\tposting_date\n\t\t\t\t= %s and company = %s\n\t\t\t\tand is_cancelled = 0\n\t\t\tORDER BY timestamp(posting_date, posting_time) asc, creation asc\n\t\t",
            "n_words": 33,
            "vocab_size": 29,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 278616,
        "commit_id": "3613c3defc39c236fb1592c4f7ba1a9cc887343a",
        "repo": "keras",
        "path": "keras/applications/efficientnet_v2.py",
        "file_name": "efficientnet_v2.py",
        "fun_name": "preprocess_input",
        "commit_message": "Remove pylint comments.\n\nPiperOrigin-RevId: 452353044",
        "code": "def preprocess_input(x, data_format=None):\n    \n    return x\n\n\n@keras_export(\"keras.applications.efficientnet_v2.decode_predictions\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.applications.efficientnet_v2.decode_predictions\")",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 11,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 12,
        "n_ast_nodes": 32,
        "n_identifiers": 4,
        "d_id": 82629,
        "documentation": {
            "docstring": "A placeholder method for backward compatibility.\n\n    The preprocessing logic has been included in the EfficientNetV2 model\n    implementation. Users are no longer required to call this method to\n    normalize the input data. This method does nothing and only kept as a\n    placeholder to align the API surface between old and new version of model.\n\n    Args:\n      x: A floating point `numpy.array` or a `tf.Tensor`.\n      data_format: Optional data format of the image tensor/array. Defaults to\n        None, in which case the global setting\n        `tf.keras.backend.image_data_format()` is used (unless you changed it,\n        it defaults to \"channels_last\").{mode}\n\n    Returns:\n      Unchanged `numpy.array` or `tf.Tensor`.\n    ",
            "n_words": 95,
            "vocab_size": 76,
            "n_whitespaces": 152,
            "language": "en"
        }
    },
    {
        "id": 226144,
        "commit_id": "43e3a4011080911901176aab919c0ecf5046ddd3",
        "repo": "plotly.py",
        "path": "packages/python/plotly/plotly/figure_factory/_ohlc.py",
        "file_name": "_ohlc.py",
        "fun_name": "make_increasing_ohlc",
        "commit_message": "switch to black .22",
        "code": "def make_increasing_ohlc(open, high, low, close, dates, **kwargs):\n    \n    (flat_increase_x, flat_increase_y, text_increase) = _OHLC(\n        open, high, low, close, dates\n    ).get_increase()\n\n    if \"name\" in kwargs:\n        showlegend = True\n    else:\n        kwargs.setdefault(\"name\", \"Increasing\")\n        showlegend = False\n\n    kwargs.setdefault(\"line\", dict(color=_DEFAULT_INCREASING_COLOR, width=1))\n    kwargs.setdefault(\"text\", text_increase)\n\n    ohlc_incr = dict(\n        type=\"scatter\",\n        x=flat_increase_x,\n        y=flat_increase_y,\n        mode=\"lines\",\n        showlegend=showlegend,\n        **kwargs,\n    )\n    return ohlc_incr\n\n",
        "url": "https://github.com/plotly/plotly.py.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 148,
        "n_words": 48,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 117,
        "n_ast_nodes": 183,
        "n_identifiers": 23,
        "d_id": 57818,
        "documentation": {
            "docstring": "\n    Makes increasing ohlc sticks\n\n    _make_increasing_ohlc() and _make_decreasing_ohlc separate the\n    increasing trace from the decreasing trace so kwargs (such as\n    color) can be passed separately to increasing or decreasing traces\n    when direction is set to 'increasing' or 'decreasing' in\n    FigureFactory.create_candlestick()\n\n    :param (list) open: opening values\n    :param (list) high: high values\n    :param (list) low: low values\n    :param (list) close: closing values\n    :param (list) dates: list of datetime objects. Default: None\n    :param kwargs: kwargs to be passed to increasing trace via\n        plotly.graph_objs.Scatter.\n\n    :rtype (trace) ohlc_incr_data: Scatter trace of all increasing ohlc\n        sticks.\n    ",
            "n_words": 89,
            "vocab_size": 59,
            "n_whitespaces": 146,
            "language": "en"
        }
    },
    {
        "id": 77079,
        "commit_id": "1822d7eee23cf5fceff8b1f58f3ca2f0a32c6e34",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_widgets.py",
        "file_name": "test_widgets.py",
        "fun_name": "test_tags_help_text_no_spaces_allowed",
        "commit_message": "display help text message for tag field\n\n- resolves #1874\n- ensure message is dynamic based on the setting TAG_SPACES_ALLOWED\n- Update wagtail/admin/templates/wagtailadmin/widgets/tag_widget.html",
        "code": "def test_tags_help_text_no_spaces_allowed(self):\n        \n        widget = widgets.AdminTagWidget()\n        help_text = widget.get_context(None, None, {})[\"widget\"][\"help_text\"]\n\n        html = widget.render(\"tags\", None, {})\n        help_text_html_element = self.get_help_text_html_element(html)\n\n        self.assertEqual(\n            help_text, \"Tags can only consist of a single word, no spaces allowed.\"\n        )\n\n        self.assertHTMLEqual(\n            help_text_html_element,\n             % help_text,\n        )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 134,
        "n_words": 37,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 72,
        "n_ast_nodes": 122,
        "n_identifiers": 13,
        "d_id": 16621,
        "documentation": {
            "docstring": "Checks that the tags help text html element content is correct when TAG_SPACES_ALLOWED is False<p class=\"help\">%s</p>",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 296853,
        "commit_id": "73a368c24246b081cdb98923ca3180937d436c3b",
        "repo": "core",
        "path": "homeassistant/components/history_stats/helpers.py",
        "file_name": "helpers.py",
        "fun_name": "handle_template_exception",
        "commit_message": "Refactor history_stats to minimize database access (part 2) (#70255)",
        "code": "def handle_template_exception(ex, field):\n        \n        if ex.args and ex.args[0].startswith(\"UndefinedError: 'None' has no attribute\"):\n            # Common during HA startup - so just a warning\n            _LOGGER.warning(ex)\n            return\n        _LOGGER.error(\"Error parsing template for field %s\", field, exc_info=ex)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 85,
        "n_words": 31,
        "vocab_size": 31,
        "complexity": 3,
        "nloc": 5,
        "token_counts": 44,
        "n_ast_nodes": 75,
        "n_identifiers": 9,
        "d_id": 95827,
        "documentation": {
            "docstring": "Log an error nicely if the template cannot be interpreted.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 208471,
        "commit_id": "1ec91ebf328bdf3450130de4b4604c79dc1e19d9",
        "repo": "ipython",
        "path": "IPython/core/profiledir.py",
        "file_name": "profiledir.py",
        "fun_name": "find_profile_dir_by_name",
        "commit_message": "FIX CVE-2022-21699\n\nSee https://github.com/ipython/ipython/security/advisories/GHSA-pq7m-3gw7-gq5x",
        "code": "def find_profile_dir_by_name(cls, ipython_dir, name=u'default', config=None):\n        \n        dirname = u'profile_' + name\n        paths = [ipython_dir]\n        for p in paths:\n            profile_dir = os.path.join(p, dirname)\n            if os.path.isdir(profile_dir):\n                return cls(location=profile_dir, config=config)\n        else:\n            raise ProfileDirError('Profile directory not found in paths: %s' % dirname)\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 120,
        "n_words": 37,
        "vocab_size": 32,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 75,
        "n_ast_nodes": 119,
        "n_identifiers": 15,
        "d_id": 52335,
        "documentation": {
            "docstring": "Find an existing profile dir by profile name, return its ProfileDir.\n\n        This searches through a sequence of paths for a profile dir.  If it\n        is not found, a :class:`ProfileDirError` exception will be raised.\n\n        The search path algorithm is:\n        1. ``os.getcwd()`` # removed for security reason.\n        2. ``ipython_dir``\n\n        Parameters\n        ----------\n        ipython_dir : unicode or str\n            The IPython directory to use.\n        name : unicode or str\n            The name of the profile.  The name of the profile directory\n            will be \"profile_<profile>\".\n        ",
            "n_words": 78,
            "vocab_size": 57,
            "n_whitespaces": 183,
            "language": "en"
        }
    },
    {
        "id": 194585,
        "commit_id": "e6c144b5423dada62fd13034c2d40bf48a2bc423",
        "repo": "kivy",
        "path": "kivy/tools/packaging/pyinstaller_hooks/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "add_dep_paths",
        "commit_message": "Replace deprecated logging.warn with logging.warning (#7906)",
        "code": "def add_dep_paths():\n    \n    paths = []\n    if old_deps is not None:\n        for importer, modname, ispkg in pkgutil.iter_modules(\n                old_deps.__path__):\n            if not ispkg:\n                continue\n            try:\n                mod = importer.find_module(modname).load_module(modname)\n            except ImportError as e:\n                logging.warning(f\"deps: Error importing dependency: {e}\")\n                continue\n\n            if hasattr(mod, 'dep_bins'):\n                paths.extend(mod.dep_bins)\n    sys.path.extend(paths)\n\n    if kivy_deps is None:\n        return\n\n    paths = []\n    for importer, modname, ispkg in pkgutil.iter_modules(kivy_deps.__path__):\n        if not ispkg:\n            continue\n        try:\n            mod = importer.find_module(modname).load_module(modname)\n        except ImportError as e:\n            logging.warning(f\"deps: Error importing dependency: {e}\")\n            continue\n\n        if hasattr(mod, 'dep_bins'):\n            paths.extend(mod.dep_bins)\n    sys.path.extend(paths)\n\n",
        "url": "https://github.com/kivy/kivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 332,
        "n_words": 77,
        "vocab_size": 38,
        "complexity": 11,
        "nloc": 29,
        "token_counts": 171,
        "n_ast_nodes": 293,
        "n_identifiers": 22,
        "d_id": 47008,
        "documentation": {
            "docstring": "Should be called by the hook. It adds the paths with the binary\n    dependencies to the system path so that pyinstaller can find the binaries\n    during its crawling stage.\n    ",
            "n_words": 29,
            "vocab_size": 25,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 219652,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_pydecimal.py",
        "file_name": "_pydecimal.py",
        "fun_name": "_ln_exp_bound",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _ln_exp_bound(self):\n        \n\n        # for 0.1 <= x <= 10 we use the inequalities 1-1/x <= ln(x) <= x-1\n        adj = self._exp + len(self._int) - 1\n        if adj >= 1:\n            # argument >= 10; we use 23/10 = 2.3 as a lower bound for ln(10)\n            return len(str(adj*23//10)) - 1\n        if adj <= -2:\n            # argument <= 0.1\n            return len(str((-1-adj)*23//10)) - 1\n        op = _WorkRep(self)\n        c, e = op.int, op.exp\n        if adj == 0:\n            # 1 < self < 10\n            num = str(c-10**-e)\n            den = str(c)\n            return len(num) - len(den) - (num < den)\n        # adj == -1, 0.1 <= self < 1\n        return e + len(str(10**-e - c)) - 1\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 267,
        "n_words": 109,
        "vocab_size": 59,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 126,
        "n_ast_nodes": 225,
        "n_identifiers": 15,
        "d_id": 55682,
        "documentation": {
            "docstring": "Compute a lower bound for the adjusted exponent of self.ln().\n        In other words, compute r such that self.ln() >= 10**r.  Assumes\n        that self is finite and positive and that self != 1.\n        ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 54,
            "language": "en"
        }
    },
    {
        "id": 27800,
        "commit_id": "a68553e1a55e3a1bd32826cdce294d27f74175e9",
        "repo": "saleor",
        "path": "saleor/graphql/order/tests/test_order.py",
        "file_name": "test_order.py",
        "fun_name": "test_orderline_query",
        "commit_message": "Metadata added to checkout and order lines (#10040)\n\n* Metadata added to checkout and order lines\r\n\r\n* CHANGELOG.md update\r\n\r\n* Missing tests added",
        "code": "def test_orderline_query(staff_api_client, permission_manage_orders, fulfilled_order):\n    order = fulfilled_order\n    query = \n    line = order.lines.first()\n\n    metadata_key = \"md key\"\n    metadata_value = \"md value\"\n\n    line.store_value_in_private_metadata({metadata_key: metadata_value})\n    line.store_value_in_metadata({metadata_key: metadata_value})\n    line.save()\n\n    staff_api_client.user.user_permissions.add(permission_manage_orders)\n    response = staff_api_client.post_graphql(query)\n    content = get_graphql_content(response)\n    order_data = content[\"data\"][\"orders\"][\"edges\"][0][\"node\"]\n    first_order_data_line = order_data[\"lines\"][0]\n    variant_id = graphene.Node.to_global_id(\"ProductVariant\", line.variant.pk)\n\n    assert first_order_data_line[\"thumbnail\"] is None\n    assert first_order_data_line[\"variant\"][\"id\"] == variant_id\n    assert first_order_data_line[\"quantity\"] == line.quantity\n    assert first_order_data_line[\"unitPrice\"][\"currency\"] == line.unit_price.currency\n    assert first_order_data_line[\"metadata\"] == [\n        {\"key\": metadata_key, \"value\": metadata_value}\n    ]\n    assert first_order_data_line[\"privateMetadata\"] == [\n        {\"key\": metadata_key, \"value\": metadata_value}\n    ]\n    expected_unit_price = Money(\n        amount=str(first_order_data_line[\"unitPrice\"][\"gross\"][\"amount\"]),\n        currency=\"USD\",\n    )\n    assert first_order_data_line[\"totalPrice\"][\"currency\"] == line.unit_price.currency\n    assert expected_unit_price == line.unit_price.gross\n\n    expected_total_price = Money(\n        amount=str(first_order_data_line[\"totalPrice\"][\"gross\"][\"amount\"]),\n        currency=\"USD\",\n    )\n    assert expected_total_price == line.unit_price.gross * line.quantity\n\n    allocation = line.allocations.first()\n    allocation_id = graphene.Node.to_global_id(\"Allocation\", allocation.pk)\n    warehouse_id = graphene.Node.to_global_id(\n        \"Warehouse\", allocation.stock.warehouse.pk\n    )\n    assert first_order_data_line[\"allocations\"] == [\n        {\n            \"id\": allocation_id,\n            \"quantity\": allocation.quantity_allocated,\n            \"warehouse\": {\"id\": warehouse_id},\n        }\n    ]\n\n",
        "url": "https://github.com/saleor/saleor.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 330,
        "n_words": 129,
        "vocab_size": 78,
        "complexity": 1,
        "nloc": 93,
        "token_counts": 349,
        "n_ast_nodes": 595,
        "n_identifiers": 45,
        "d_id": 5130,
        "documentation": {
            "docstring": "\n        query OrdersQuery {\n            orders(first: 1) {\n                edges {\n                    node {\n                        lines {\n                            thumbnail(size: 540) {\n                                url\n                            }\n                            variant {\n                                id\n                            }\n                            quantity\n                            allocations {\n                                id\n                                quantity\n                                warehouse {\n                                    id\n                                }\n                            }\n                            unitPrice {\n                                currency\n                                gross {\n                                    amount\n                                }\n                            }\n                            totalPrice {\n                                currency\n                                gross {\n                                    amount\n                                }\n                            }\n                            metadata {\n                                key\n                                value\n                            }\n                            privateMetadata {\n                                key\n                                value\n                            }\n                        }\n                    }\n                }\n            }\n        }\n    ",
            "n_words": 62,
            "vocab_size": 26,
            "n_whitespaces": 1222,
            "language": "en"
        }
    },
    {
        "id": 71769,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/tests/test_account_management.py",
        "file_name": "test_account_management.py",
        "fun_name": "test_login_view",
        "commit_message": "Reformat with black",
        "code": "def test_login_view(self):\n        \n        # Get login page\n        response = self.client.get(reverse(\"wagtailadmin_login\"))\n\n        # Check that the user received a login page\n        self.assertEqual(response.status_code, 200)\n        self.assertTemplateUsed(response, \"wagtailadmin/login.html\")\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 64,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 37,
        "n_ast_nodes": 67,
        "n_identifiers": 9,
        "d_id": 15736,
        "documentation": {
            "docstring": "\n        This tests that the login view responds with a login page\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 203539,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/admin/utils.py",
        "file_name": "utils.py",
        "fun_name": "construct_change_message",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def construct_change_message(form, formsets, add):\n    \n    # Evaluating `form.changed_data` prior to disabling translations is required\n    # to avoid fields affected by localization from being included incorrectly,\n    # e.g. where date formats differ such as MM/DD/YYYY vs DD/MM/YYYY.\n    changed_data = form.changed_data\n    with translation_override(None):\n        # Deactivate translations while fetching verbose_name for form\n        # field labels and using `field_name`, if verbose_name is not provided.\n        # Translations will happen later on LogEntry access.\n        changed_field_labels = _get_changed_field_labels_from_form(form, changed_data)\n\n    change_message = []\n    if add:\n        change_message.append({\"added\": {}})\n    elif form.changed_data:\n        change_message.append({\"changed\": {\"fields\": changed_field_labels}})\n    if formsets:\n        with translation_override(None):\n            for formset in formsets:\n                for added_object in formset.new_objects:\n                    change_message.append(\n                        {\n                            \"added\": {\n                                \"name\": str(added_object._meta.verbose_name),\n                                \"object\": str(added_object),\n                            }\n                        }\n                    )\n                for changed_object, changed_fields in formset.changed_objects:\n                    change_message.append(\n                        {\n                            \"changed\": {\n                                \"name\": str(changed_object._meta.verbose_name),\n                                \"object\": str(changed_object),\n                                \"fields\": _get_changed_field_labels_from_form(\n                                    formset.forms[0], changed_fields\n                                ),\n                            }\n                        }\n                    )\n                for deleted_object in formset.deleted_objects:\n                    change_message.append(\n                        {\n                            \"deleted\": {\n                                \"name\": str(deleted_object._meta.verbose_name),\n                                \"object\": str(deleted_object),\n                            }\n                        }\n                    )\n    return change_message\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 979,
        "n_words": 144,
        "vocab_size": 101,
        "complexity": 8,
        "nloc": 43,
        "token_counts": 206,
        "n_ast_nodes": 352,
        "n_identifiers": 22,
        "d_id": 50436,
        "documentation": {
            "docstring": "\n    Construct a JSON structure describing changes from a changed object.\n    Translations are deactivated so that strings are stored untranslated.\n    Translation happens later on LogEntry access.\n    ",
            "n_words": 25,
            "vocab_size": 23,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 217784,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/http/cookiejar.py",
        "file_name": "cookiejar.py",
        "fun_name": "split_header_words",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def split_header_words(header_values):\n    r\n    assert not isinstance(header_values, str)\n    result = []\n    for text in header_values:\n        orig_text = text\n        pairs = []\n        while text:\n            m = HEADER_TOKEN_RE.search(text)\n            if m:\n                text = unmatched(m)\n                name = m.group(1)\n                m = HEADER_QUOTED_VALUE_RE.search(text)\n                if m:  # quoted value\n                    text = unmatched(m)\n                    value = m.group(1)\n                    value = HEADER_ESCAPE_RE.sub(r\"\\1\", value)\n                else:\n                    m = HEADER_VALUE_RE.search(text)\n                    if m:  # unquoted value\n                        text = unmatched(m)\n                        value = m.group(1)\n                        value = value.rstrip()\n                    else:\n                        # no value, a lone token\n                        value = None\n                pairs.append((name, value))\n            elif text.lstrip().startswith(\",\"):\n                # concatenated headers, as per RFC 2616 section 4.2\n                text = text.lstrip()[1:]\n                if pairs: result.append(pairs)\n                pairs = []\n            else:\n                # skip junk\n                non_junk, nr_junk_chars = re.subn(r\"^[=\\s;]*\", \"\", text)\n                assert nr_junk_chars > 0, (\n                    \"split_header_words bug: '%s', '%s', %s\" %\n                    (orig_text, text, pairs))\n                text = non_junk\n        if pairs: result.append(pairs)\n    return result\n\nHEADER_JOIN_ESCAPE_RE = re.compile(r\"([\\\"\\\\])\")",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 700,
        "n_words": 136,
        "vocab_size": 78,
        "complexity": 9,
        "nloc": 81,
        "token_counts": 227,
        "n_ast_nodes": 392,
        "n_identifiers": 29,
        "d_id": 54932,
        "documentation": {
            "docstring": "Parse header values into a list of lists containing key,value pairs.\n\n    The function knows how to deal with \",\", \";\" and \"=\" as well as quoted\n    values after \"=\".  A list of space separated tokens are parsed as if they\n    were separated by \";\".\n\n    If the header_values passed as argument contains multiple values, then they\n    are treated as if they were a single value separated by comma \",\".\n\n    This means that this function is useful for parsing header fields that\n    follow this syntax (BNF as from the HTTP/1.1 specification, but we relax\n    the requirement for tokens).\n\n      headers           = #header\n      header            = (token | parameter) *( [\";\"] (token | parameter))\n\n      token             = 1*<any CHAR except CTLs or separators>\n      separators        = \"(\" | \")\" | \"<\" | \">\" | \"@\"\n                        | \",\" | \";\" | \":\" | \"\\\" | <\">\n                        | \"/\" | \"[\" | \"]\" | \"?\" | \"=\"\n                        | \"{\" | \"}\" | SP | HT\n\n      quoted-string     = ( <\"> *(qdtext | quoted-pair ) <\"> )\n      qdtext            = <any TEXT except <\">>\n      quoted-pair       = \"\\\" CHAR\n\n      parameter         = attribute \"=\" value\n      attribute         = token\n      value             = token | quoted-string\n\n    Each header is represented by a list of key/value pairs.  The value for a\n    simple token (not part of a parameter) is None.  Syntactically incorrect\n    headers will not necessarily be parsed as you would want.\n\n    This is easier to describe with some examples:\n\n    >>> split_header_words(['foo=\"bar\"; port=\"80,81\"; discard, bar=baz'])\n    [[('foo', 'bar'), ('port', '80,81'), ('discard', None)], [('bar', 'baz')]]\n    >>> split_header_words(['text/html; charset=\"iso-8859-1\"'])\n    [[('text/html', None), ('charset', 'iso-8859-1')]]\n    >>> split_header_words([r'Basic realm=\"\\\"foo\\bar\\\"\"'])\n    [[('Basic', None), ('realm', '\"foobar\"')]]\n\n    ",
            "n_words": 259,
            "vocab_size": 161,
            "n_whitespaces": 527,
            "language": "en"
        }
    },
    {
        "id": 182783,
        "commit_id": "e8636d0d86e596690647564b84a68d5e6d107dd0",
        "repo": "textual",
        "path": "src/textual/css/stylesheet.py",
        "file_name": "stylesheet.py",
        "fun_name": "reparse",
        "commit_message": "css reparse",
        "code": "def reparse(self) -> None:\n        \n        # Do this in a fresh Stylesheet so if there are errors we don't break self.\n        stylesheet = Stylesheet(variables=self.variables)\n        for css, path in self.source:\n            stylesheet.parse(css, path=path)\n        self._clone(stylesheet)\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 77,
        "n_words": 31,
        "vocab_size": 30,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 43,
        "n_ast_nodes": 71,
        "n_identifiers": 10,
        "d_id": 43963,
        "documentation": {
            "docstring": "Re-parse source, applying new variables.\n\n        Raises:\n            StylesheetError: If the CSS could not be read.\n            StylesheetParseError: If the CSS is invalid.\n\n        ",
            "n_words": 20,
            "vocab_size": 17,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 7812,
        "commit_id": "60197fe851aadfa51d18c16dd42b49f728ed7eaa",
        "repo": "ludwig",
        "path": "ludwig/data/dataset_synthesizer.py",
        "file_name": "dataset_synthesizer.py",
        "fun_name": "_get_feature_encoder_or_decoder",
        "commit_message": "Adds registry to organize backward compatibility updates around versions and config sections (#2335)\n\n* First pass implementation of VersionTransformation\r\n\r\n* Remove test main.\r\n\r\n* Refactors backward_compatibility.py to use version registration system\r\n\r\n* Changed sort order to process outer first.\r\n\r\n* Moves test_deprecated_field_aliases from test_defaults.py to test_backward_compatibility.py\r\n\r\n* s/prefix/prefixes in test_version_transformation.py\r\n\r\n* Removes comment, print statements.\r\n\r\n* Adds docstrings.\r\n\r\n* typo fix.\r\n\r\n* Removes unused import.\r\n\r\n* Small cleanup to backward_compatibility.py, removed redundant keys.\r\n\r\n* Assume version 0.4 if no version present in the config.\r\n\r\n* Updates dataset synthesis to work with nested encoder/decoders.\r\n\r\n* Fixes test_server.py\r\n\r\n* nesting image feature params in test_ray\r\n\r\n* _get_feature_encoder_or_decoder in generate_category.\r\n\r\n* oops, forgot random.choice.\r\n\r\nCo-authored-by: Daniel Treiman <daniel@predibase.com>",
        "code": "def _get_feature_encoder_or_decoder(feature):\n    \n    if DECODER in feature:\n        return feature[DECODER]\n    elif ENCODER in feature:\n        return feature[ENCODER]\n    else:\n        feature[ENCODER] = {}\n        return feature[ENCODER]\n\n",
        "url": "https://github.com/ludwig-ai/ludwig.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 60,
        "n_words": 20,
        "vocab_size": 14,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 40,
        "n_ast_nodes": 65,
        "n_identifiers": 4,
        "d_id": 1274,
        "documentation": {
            "docstring": "Returns the nested decoder or encoder dictionary for a feature.\n\n    If neither encoder nor decoder is present, creates an empty encoder dict and returns it.\n    ",
            "n_words": 25,
            "vocab_size": 22,
            "n_whitespaces": 31,
            "language": "en"
        }
    },
    {
        "id": 181642,
        "commit_id": "388616b6247ca4ea8de4e2f340d6206aee523541",
        "repo": "tpot",
        "path": "tests/feature_transformers_tests.py",
        "file_name": "feature_transformers_tests.py",
        "fun_name": "test_ContinuousSelector_4",
        "commit_message": "Revert \"Deployed 7ccda9a with MkDocs version: 1.3.0\"\n\nThis reverts commit bd9629c40e01241766197119b581a99409b07068.",
        "code": "def test_ContinuousSelector_4():\n    \n    cs = ContinuousSelector()\n\n    assert_raises(ValueError, cs.transform, iris_data[0:10,:])\n\n",
        "url": "https://github.com/EpistasisLab/tpot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 17,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 27,
        "n_ast_nodes": 45,
        "n_identifiers": 7,
        "d_id": 43430,
        "documentation": {
            "docstring": "Assert that ContinuousSelector rasies ValueError without categorical features.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 157369,
        "commit_id": "ca86da3a30c4e080d4db8c25fca73de843663cb4",
        "repo": "stablediffusion",
        "path": "ldm/models/diffusion/dpm_solver/dpm_solver.py",
        "file_name": "dpm_solver.py",
        "fun_name": "dpm_solver_first_update",
        "commit_message": "release more models",
        "code": "def dpm_solver_first_update(self, x, s, t, model_s=None, return_intermediate=False):\n        \n        ns = self.noise_schedule\n        dims = x.dim()\n        lambda_s, lambda_t = ns.marginal_lambda(s), ns.marginal_lambda(t)\n        h = lambda_t - lambda_s\n        log_alpha_s, log_alpha_t = ns.marginal_log_mean_coeff(s), ns.marginal_log_mean_coeff(t)\n        sigma_s, sigma_t = ns.marginal_std(s), ns.marginal_std(t)\n        alpha_t = torch.exp(log_alpha_t)\n\n        if self.predict_x0:\n            phi_1 = torch.expm1(-h)\n            if model_s is None:\n                model_s = self.model_fn(x, s)\n            x_t = (\n                    expand_dims(sigma_t / sigma_s, dims) * x\n                    - expand_dims(alpha_t * phi_1, dims) * model_s\n            )\n            if return_intermediate:\n                return x_t, {'model_s': model_s}\n            else:\n                return x_t\n        else:\n            phi_1 = torch.expm1(h)\n            if model_s is None:\n                model_s = self.model_fn(x, s)\n            x_t = (\n                    expand_dims(torch.exp(log_alpha_t - log_alpha_s), dims) * x\n                    - expand_dims(sigma_t * phi_1, dims) * model_s\n            )\n            if return_intermediate:\n                return x_t, {'model_s': model_s}\n            else:\n                return x_t\n",
        "url": "https://github.com/Stability-AI/stablediffusion.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 481,
        "n_words": 113,
        "vocab_size": 57,
        "complexity": 6,
        "nloc": 32,
        "token_counts": 235,
        "n_ast_nodes": 371,
        "n_identifiers": 30,
        "d_id": 36909,
        "documentation": {
            "docstring": "\n        DPM-Solver-1 (equivalent to DDIM) from time `s` to time `t`.\n        Args:\n            x: A pytorch tensor. The initial value at time `s`.\n            s: A pytorch tensor. The starting time, with the shape (x.shape[0],).\n            t: A pytorch tensor. The ending time, with the shape (x.shape[0],).\n            model_s: A pytorch tensor. The model function evaluated at time `s`.\n                If `model_s` is None, we evaluate the model by `x` and `s`; otherwise we directly use it.\n            return_intermediate: A `bool`. If true, also return the model value at time `s`.\n        Returns:\n            x_t: A pytorch tensor. The approximated solution at time `t`.\n        ",
            "n_words": 95,
            "vocab_size": 54,
            "n_whitespaces": 205,
            "language": "en"
        }
    },
    {
        "id": 261023,
        "commit_id": "2710a9e7eefd2088ce35fd2fb6651d5f97e5ef8b",
        "repo": "scikit-learn",
        "path": "sklearn/utils/_array_api.py",
        "file_name": "_array_api.py",
        "fun_name": "_asarray_with_order",
        "commit_message": "ENH Adds Array API support to LinearDiscriminantAnalysis (#22554)\n\nCo-authored-by: Olivier Grisel <olivier.grisel@ensta.org>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>",
        "code": "def _asarray_with_order(array, dtype=None, order=None, copy=None, xp=None):\n    \n    if xp is None:\n        xp, _ = get_namespace(array)\n    if xp.__name__ in {\"numpy\", \"numpy.array_api\"}:\n        # Use NumPy API to support order\n        array = numpy.asarray(array, order=order, dtype=dtype)\n        return xp.asarray(array, copy=copy)\n    else:\n        return xp.asarray(array, dtype=dtype, copy=copy)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 86,
        "n_words": 39,
        "vocab_size": 34,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 90,
        "n_ast_nodes": 139,
        "n_identifiers": 11,
        "d_id": 76628,
        "documentation": {
            "docstring": "Helper to support the order kwarg only for NumPy-backed arrays\n\n    Memory layout parameter `order` is not exposed in the Array API standard,\n    however some input validation code in scikit-learn needs to work both\n    for classes and functions that will leverage Array API only operations\n    and for code that inherently relies on NumPy backed data containers with\n    specific memory layout constraints (e.g. our own Cython code). The\n    purpose of this helper is to make it possible to share code for data\n    container validation without memory copies for both downstream use cases:\n    the `order` parameter is only enforced if the input array implementation\n    is NumPy based, otherwise `order` is just silently ignored.\n    ",
            "n_words": 110,
            "vocab_size": 77,
            "n_whitespaces": 140,
            "language": "en"
        }
    },
    {
        "id": 74164,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_blocks.py",
        "file_name": "test_blocks.py",
        "fun_name": "test_bound_blocks_are_available_on_template",
        "commit_message": "Reformat with black",
        "code": "def test_bound_blocks_are_available_on_template(self):\n        \n        block = SectionBlock()\n        value = block.to_python({\"title\": \"Hello\", \"body\": \"<i>italic</i> world\"})\n        result = block.render(value)\n        self.assertEqual(result, )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 52,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 43,
        "n_ast_nodes": 81,
        "n_identifiers": 9,
        "d_id": 16226,
        "documentation": {
            "docstring": "\n        Test that we are able to use value.bound_blocks within templates\n        to access a child block's own HTML rendering\n        <h1>Hello</h1><i>italic</i> world",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 154395,
        "commit_id": "1c0935c1bc0856d43f69c1e32498636ee24ebc85",
        "repo": "modin",
        "path": "modin/experimental/core/execution/native/implementations/omnisci_on_native/base_worker.py",
        "file_name": "base_worker.py",
        "fun_name": "_genName",
        "commit_message": "FEAT-#4913: Enabling pyhdk (#4900)\n\nCo-authored-by: ienkovich <ilya.enkovich@intel.com>\r\nSigned-off-by: izamyati <igor.zamyatin@intel.com>",
        "code": "def _genName(cls, name):\n        \n        if not name:\n            name = \"frame_\" + str(uuid.uuid4()).replace(\"-\", \"\")\n        # TODO: reword name in case of caller's mistake\n        return name\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 62,
        "n_words": 23,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 33,
        "n_ast_nodes": 62,
        "n_identifiers": 7,
        "d_id": 35956,
        "documentation": {
            "docstring": "\n        Generate or mangle a table name.\n\n        Parameters\n        ----------\n        name : str or None\n            Table name to mangle or None to generate a unique\n            table name.\n\n        Returns\n        -------\n        str\n            Table name.\n        ",
            "n_words": 30,
            "vocab_size": 18,
            "n_whitespaces": 120,
            "language": "en"
        }
    },
    {
        "id": 259865,
        "commit_id": "b94bc5ea6821607d1e9826ce2d084c76379820ba",
        "repo": "scikit-learn",
        "path": "sklearn/neighbors/_base.py",
        "file_name": "_base.py",
        "fun_name": "sort_graph_by_row_values",
        "commit_message": "ENH add new function sort_graph_by_row_values (#23139)\n\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>",
        "code": "def sort_graph_by_row_values(graph, copy=False, warn_when_not_sorted=True):\n    \n    if not issparse(graph):\n        raise TypeError(f\"Input graph must be a sparse matrix, got {graph!r} instead.\")\n\n    if graph.format == \"csr\" and _is_sorted_by_data(graph):\n        return graph\n\n    if warn_when_not_sorted:\n        warnings.warn(\n            \"Precomputed sparse input was not sorted by row values. Use the function\"\n            \" sklearn.neighbors.sort_graph_by_row_values to sort the input by row\"\n            \" values, with warn_when_not_sorted=False to remove this warning.\",\n            EfficiencyWarning,\n        )\n\n    if graph.format not in (\"csr\", \"csc\", \"coo\", \"lil\"):\n        raise TypeError(\n            f\"Sparse matrix in {graph.format!r} format is not supported due to \"\n            \"its handling of explicit zeros\"\n        )\n    elif graph.format != \"csr\":\n        if not copy:\n            raise ValueError(\n                \"The input graph is not in CSR format. Use copy=True to allow \"\n                \"the conversion to CSR format.\"\n            )\n        graph = graph.asformat(\"csr\")\n    elif copy:  # csr format with copy=True\n        graph = graph.copy()\n\n    row_nnz = np.diff(graph.indptr)\n    if row_nnz.max() == row_nnz.min():\n        # if each sample has the same number of provided neighbors\n        n_samples = graph.shape[0]\n        distances = graph.data.reshape(n_samples, -1)\n\n        order = np.argsort(distances, kind=\"mergesort\")\n        order += np.arange(n_samples)[:, None] * row_nnz[0]\n        order = order.ravel()\n        graph.data = graph.data[order]\n        graph.indices = graph.indices[order]\n\n    else:\n        for start, stop in zip(graph.indptr, graph.indptr[1:]):\n            order = np.argsort(graph.data[start:stop], kind=\"mergesort\")\n            graph.data[start:stop] = graph.data[start:stop][order]\n            graph.indices[start:stop] = graph.indices[start:stop][order]\n\n    return graph\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 501,
        "n_words": 190,
        "vocab_size": 125,
        "complexity": 11,
        "nloc": 41,
        "token_counts": 297,
        "n_ast_nodes": 503,
        "n_identifiers": 33,
        "d_id": 75959,
        "documentation": {
            "docstring": "Sort a sparse graph such that each row is stored with increasing values.\n\n    .. versionadded:: 1.2\n\n    Parameters\n    ----------\n    graph : sparse matrix of shape (n_samples, n_samples)\n        Distance matrix to other samples, where only non-zero elements are\n        considered neighbors. Matrix is converted to CSR format if not already.\n\n    copy : bool, default=False\n        If True, the graph is copied before sorting. If False, the sorting is\n        performed inplace. If the graph is not of CSR format, `copy` must be\n        True to allow the conversion to CSR format, otherwise an error is\n        raised.\n\n    warn_when_not_sorted : bool, default=True\n        If True, a :class:`~sklearn.exceptions.EfficiencyWarning` is raised\n        when the input graph is not sorted by row values.\n\n    Returns\n    -------\n    graph : sparse matrix of shape (n_samples, n_samples)\n        Distance matrix to other samples, where only non-zero elements are\n        considered neighbors. Matrix is in CSR format.\n    ",
            "n_words": 137,
            "vocab_size": 78,
            "n_whitespaces": 237,
            "language": "en"
        }
    },
    {
        "id": 284500,
        "commit_id": "54a1b6f545a0016c576e9e00eef5c003d229dacf",
        "repo": "OpenBBTerminal",
        "path": "openbb_terminal/stocks/options/hedge/hedge_view.py",
        "file_name": "hedge_view.py",
        "fun_name": "add_and_show_greeks",
        "commit_message": "Feature/hedge (#1768)\n\n* [Bug] Incorrect log for reddit keys. #1733 fix\r\n\r\n* Create new feature-hedge\r\n\r\n* Significantly improve code of hedge menu\r\n\r\n* More robust\r\n\r\n* Robustness\r\n\r\n* Fix tests\r\n\r\n* Fix can't multiply sequence by non-int of type 'numpy.float64' error\r\n\r\n* Temporary fix of singular matrix error. Return first feasible solution\r\n\r\n* Update Hugo Documentation\r\n\r\n* Combining menus and cleaning up code\r\n\r\n* Tidy up call_exp\r\n\r\n* Update tests Round 1\r\n\r\n* Update tests Round 2\r\n\r\n* Fix linting error\r\n\r\n* Fix linting?\r\n\r\n* Fixed glitch\r\n\r\nCo-authored-by: JerBouma <jer.bouma@gmail.com>\r\nCo-authored-by: James Maslek <jmaslek11@gmail.com>\r\nCo-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>\r\nCo-authored-by: colin99d <colin99delahunty@gmail.com>\r\nCo-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>",
        "code": "def add_and_show_greeks(price, implied_volatility, strike, days, side):\n    \n    # Add in hedge option\n    delta, gamma, vega = hedge_model.add_hedge_option(\n        price, implied_volatility, strike, days, side\n    )\n\n    # Show the added delta, gamma and vega positions. Next to that, also show the inputted\n    # implied volatility and strike\n    positions = pd.DataFrame(\n        [delta, gamma, vega, implied_volatility, strike],\n        index=[\"Delta\", \"Gamma\", \"Vega\", \"Implied Volatility\", \"Strike Price\"],\n        columns=[\"Positions\"],\n    )\n\n    # Show table\n    print_rich_table(positions, show_index=True, headers=list(positions.columns))\n\n    console.print()\n\n    return delta, gamma, vega\n\n",
        "url": "https://github.com/OpenBB-finance/OpenBBTerminal.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 135,
        "n_words": 71,
        "vocab_size": 53,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 101,
        "n_ast_nodes": 154,
        "n_identifiers": 22,
        "d_id": 84766,
        "documentation": {
            "docstring": "Determine the delta, gamma and vega value of the portfolio and/or options and show them.\n\n    Parameters\n    ----------\n    price: int\n        The price.\n    implied_volatility: float\n        The implied volatility.\n    strike: float\n        The strike price.\n    days: float\n        The amount of days until expiration. Use annual notation thus a month would be 30 / 360.\n    sign: int\n        Whether you have a long (1) or short (-1) position\n\n    Returns\n    -------\n    delta: float\n    gamma: float\n    vega: float\n    ",
            "n_words": 70,
            "vocab_size": 56,
            "n_whitespaces": 144,
            "language": "en"
        }
    },
    {
        "id": 84412,
        "commit_id": "bfd9fc86223c2446e8b38d2cdd5876caed50bfda",
        "repo": "zulip",
        "path": "zerver/webhooks/newrelic/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_acknowledged_new",
        "commit_message": "integration: Fix integration with newrelic.\n\nNewrelic updated the payload that's sent via the webhook incoming call\ncausing a bug in the newrelic webhook endpoint.\nThis fixes the bug by updating the endpoint to respect the new format\nof the payload as well as the old format. This should be updated once\nthe old format is EOLed.\n\nFixes #22338.",
        "code": "def test_acknowledged_new(self) -> None:\n        expected_topic = \"Test policy name (1234)\"\n        expected_message = .strip()\n\n        self.check_webhook(\n            \"incident_acknowledged_new\",\n            expected_topic,\n            expected_message,\n            content_type=\"application/json\",\n        )\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 90,
        "n_words": 19,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 32,
        "n_ast_nodes": 57,
        "n_identifiers": 7,
        "d_id": 17831,
        "documentation": {
            "docstring": "\n[Incident](https://alerts.newrelic.com/accounts/2941966/incidents/1234) **acknowledged** by **Alice** for condition: **Server Down**\n",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 186369,
        "commit_id": "eeca208c8f57304590ac1af80b496e61021aaa45",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/configurator.py",
        "file_name": "configurator.py",
        "fun_name": "_get_vhost_block",
        "commit_message": "Various clean-ups in certbot-apache. Use f-strings. (#9132)\n\n* Various clean-ups in certbot-apache. Use f-strings.\r\n\r\n* Smaller tweaks",
        "code": "def _get_vhost_block(self, vhost):\n        \n\n        try:\n            span_val = self.parser.aug.span(vhost.path)\n        except ValueError:\n            logger.critical(\"Error while reading the VirtualHost %s from \"\n                            \"file %s\", vhost.name, vhost.filep, exc_info=True)\n            raise errors.PluginError(\"Unable to read VirtualHost from file\")\n        span_filep = span_val[0]\n        span_start = span_val[5]\n        span_end = span_val[6]\n        with open(span_filep, 'r') as fh:\n            fh.seek(span_start)\n            vh_contents = fh.read(span_end-span_start).split(\"\\n\")\n        self._remove_closing_vhost_tag(vh_contents)\n        return vh_contents\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 195,
        "n_words": 50,
        "vocab_size": 43,
        "complexity": 2,
        "nloc": 15,
        "token_counts": 110,
        "n_ast_nodes": 187,
        "n_identifiers": 26,
        "d_id": 45465,
        "documentation": {
            "docstring": " Helper method to get VirtualHost contents from the original file.\n        This is done with help of augeas span, which returns the span start and\n        end positions\n\n        :returns: `list` of VirtualHost block content lines without closing tag\n        ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 276313,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/testing_infra/keras_doctest_lib.py",
        "file_name": "keras_doctest_lib.py",
        "fun_name": "__call__",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def __call__(self, string):\n        \n        texts = []\n        floats = []\n        for i, part in enumerate(self._FLOAT_RE.split(string)):\n            if i % 2 == 0:\n                texts.append(part)\n            else:\n                floats.append(float(part))\n\n        return texts, np.array(floats)\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 113,
        "n_words": 26,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 66,
        "n_ast_nodes": 109,
        "n_identifiers": 14,
        "d_id": 81626,
        "documentation": {
            "docstring": "Extracts floats from a string.\n\n        >>> text_parts, floats = _FloatExtractor()(\"Text 1.0 Text\")\n        >>> text_parts\n        ['Text ', ' Text']\n        >>> floats\n        array([1.])\n\n        Args:\n          string: the string to extract floats from.\n\n        Returns:\n          A (string, array) pair, where `string` has each float replaced by \"...\"\n          and `array` is a `float32` `numpy.array` containing the extracted floats.\n        ",
            "n_words": 52,
            "vocab_size": 45,
            "n_whitespaces": 135,
            "language": "en"
        }
    },
    {
        "id": 206065,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/http/multipartparser.py",
        "file_name": "multipartparser.py",
        "fun_name": "parse_boundary_stream",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def parse_boundary_stream(stream, max_header_size):\n    \n    # Stream at beginning of header, look for end of header\n    # and parse it if found. The header must fit within one\n    # chunk.\n    chunk = stream.read(max_header_size)\n\n    # 'find' returns the top of these four bytes, so we'll\n    # need to munch them later to prevent them from polluting\n    # the payload.\n    header_end = chunk.find(b\"\\r\\n\\r\\n\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 86,
        "n_words": 59,
        "vocab_size": 47,
        "complexity": 7,
        "nloc": 24,
        "token_counts": 149,
        "n_ast_nodes": 53,
        "n_identifiers": 7,
        "d_id": 51350,
        "documentation": {
            "docstring": "\n    Parse one and exactly one stream that encapsulates a boundary.\n    ",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 156059,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/array/slicing.py",
        "file_name": "slicing.py",
        "fun_name": "slice_with_int_dask_array",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def slice_with_int_dask_array(x, index):\n    \n    from dask.array.core import Array\n\n    assert len(index) == x.ndim\n    fancy_indexes = [\n        isinstance(idx, (tuple, list))\n        or (isinstance(idx, (np.ndarray, Array)) and idx.ndim > 0)\n        for idx in index\n    ]\n    if sum(fancy_indexes) > 1:\n        raise NotImplementedError(\"Don't yet support nd fancy indexing\")\n\n    out_index = []\n    dropped_axis_cnt = 0\n    for in_axis, idx in enumerate(index):\n        out_axis = in_axis - dropped_axis_cnt\n        if isinstance(idx, Array) and idx.dtype.kind in \"iu\":\n            if idx.ndim == 0:\n                idx = idx[np.newaxis]\n                x = slice_with_int_dask_array_on_axis(x, idx, out_axis)\n                x = x[tuple(0 if i == out_axis else slice(None) for i in range(x.ndim))]\n                dropped_axis_cnt += 1\n            elif idx.ndim == 1:\n                x = slice_with_int_dask_array_on_axis(x, idx, out_axis)\n                out_index.append(slice(None))\n            else:\n                raise NotImplementedError(\n                    \"Slicing with dask.array of ints only permitted when \"\n                    \"the indexer has zero or one dimensions\"\n                )\n        else:\n            out_index.append(idx)\n    return x, tuple(out_index)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 408,
        "n_words": 127,
        "vocab_size": 89,
        "complexity": 12,
        "nloc": 31,
        "token_counts": 219,
        "n_ast_nodes": 344,
        "n_identifiers": 31,
        "d_id": 36524,
        "documentation": {
            "docstring": "Slice x with at most one 1D dask arrays of ints.\n\n    This is a helper function of :meth:`Array.__getitem__`.\n\n    Parameters\n    ----------\n    x: Array\n    index: tuple with as many elements as x.ndim, among which there are\n           one or more Array's with dtype=int\n\n    Returns\n    -------\n    tuple of (sliced x, new index)\n\n    where the new index is the same as the input, but with slice(None)\n    replaced to the original slicer where a 1D filter has been applied and\n    one less element where a zero-dimensional filter has been applied.\n    ",
            "n_words": 84,
            "vocab_size": 61,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 72418,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/views/generic/multiple_upload.py",
        "file_name": "multiple_upload.py",
        "fun_name": "get_edit_upload_response_data",
        "commit_message": "Reformat with black",
        "code": "def get_edit_upload_response_data(self):\n        \n        return {\n            \"success\": True,\n            self.context_upload_id_name: self.upload_object.id,\n            \"form\": render_to_string(\n                self.edit_form_template_name,\n                self.get_edit_upload_form_context_data(),\n                request=self.request,\n            ),\n        }\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 125,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 45,
        "n_ast_nodes": 72,
        "n_identifiers": 9,
        "d_id": 15889,
        "documentation": {
            "docstring": "\n        Return the JSON response data for an object that has been uploaded to an\n        upload object and now needs extra metadata to become a final object\n        ",
            "n_words": 26,
            "vocab_size": 22,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 221193,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/bz2.py",
        "file_name": "bz2.py",
        "fun_name": "peek",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def peek(self, n=0):\n        \n        self._check_can_read()\n        # Relies on the undocumented fact that BufferedReader.peek()\n        # always returns at least one byte (except at EOF), independent\n        # of the value of n\n        return self._buffer.peek(n)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 73,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 24,
        "n_ast_nodes": 44,
        "n_identifiers": 5,
        "d_id": 56263,
        "documentation": {
            "docstring": "Return buffered data without advancing the file position.\n\n        Always returns at least one byte of data, unless at EOF.\n        The exact number of bytes returned is unspecified.\n        ",
            "n_words": 27,
            "vocab_size": 25,
            "n_whitespaces": 48,
            "language": "en"
        }
    },
    {
        "id": 216058,
        "commit_id": "7fabb22f3e361bfff3fdbca01c12659591d15109",
        "repo": "salt",
        "path": "salt/modules/status.py",
        "file_name": "status.py",
        "fun_name": "_get_boot_time_aix",
        "commit_message": "Fix uptime on AIX systems when less than 24 hours",
        "code": "def _get_boot_time_aix():\n    \n    res = __salt__[\"cmd.run_all\"](\"ps -o etime= -p 1\")\n    if res[\"retcode\"] > 0:\n        raise CommandExecutionError(\"Unable to find boot_time for pid 1.\")\n    bt_time = res[\"stdout\"]\n    match = re.match(r\"\\s*(?:(\\d+)-)?(?:(\\d\\d):)?(\\d\\d):(\\d\\d)\\s*\", bt_time)\n    if not match:\n        raise CommandExecutionError(\"Unexpected time format.\")\n\n    groups = match.groups(default=\"00\")\n    boot_secs = (\n        _number(groups[0]) * 86400\n        + _number(groups[1]) * 3600\n        + _number(groups[2]) * 60\n        + _number(groups[3])\n    )\n    return boot_secs\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 129,
        "n_words": 57,
        "vocab_size": 46,
        "complexity": 3,
        "nloc": 16,
        "token_counts": 106,
        "n_ast_nodes": 182,
        "n_identifiers": 11,
        "d_id": 54364,
        "documentation": {
            "docstring": "\n    Return the number of seconds since boot time on AIX\n\n    t=$(LC_ALL=POSIX ps -o etime= -p 1)\n    d=0 h=0\n    case $t in *-*) d=${t%%-*}; t=${t#*-};; esac\n    case $t in *:*:*) h=${t%%:*}; t=${t#*:};; esac\n    s=$((d*86400 + h*3600 + ${t%%:*}*60 + ${t#*:}))\n    ",
            "n_words": 39,
            "vocab_size": 33,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 198477,
        "commit_id": "9d58006fc0a23afcba38f641c9472917c436428a",
        "repo": "sympy",
        "path": "sympy/core/mul.py",
        "file_name": "mul.py",
        "fun_name": "_matches_get_other_nodes",
        "commit_message": "Code cleanup",
        "code": "def _matches_get_other_nodes(dictionary, nodes, node_ind):\n        \n        ind_node = nodes[node_ind]\n        return [ind for ind in dictionary if nodes[ind] == ind_node]\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 38,
        "n_words": 17,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 3,
        "token_counts": 31,
        "n_ast_nodes": 47,
        "n_identifiers": 6,
        "d_id": 48956,
        "documentation": {
            "docstring": "Find other wildcards that may have already been matched.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 248229,
        "commit_id": "dffecade7df8a88caced2a7707c51e2de3407c0d",
        "repo": "synapse",
        "path": "tests/test_server.py",
        "file_name": "test_server.py",
        "fun_name": "test_uncancellable_disconnect",
        "commit_message": "Respect the `@cancellable` flag for `DirectServe{Html,Json}Resource`s (#12698)\n\n`DirectServeHtmlResource` and `DirectServeJsonResource` both inherit\r\nfrom `_AsyncResource`. These classes expect to be subclassed with\r\n`_async_render_*` methods.\r\n\r\nThis commit has no effect on `JsonResource`, despite inheriting from\r\n`_AsyncResource`. `JsonResource` has its own `_async_render` override\r\nwhich will need to be updated separately.\r\n\r\nSigned-off-by: Sean Quah <seanq@element.io>",
        "code": "def test_uncancellable_disconnect(self) -> None:\n        \n        channel = make_request(\n            self.reactor, self.site, \"POST\", \"/sleep\", await_result=False\n        )\n        self._test_disconnect(\n            self.reactor,\n            channel,\n            expect_cancellation=False,\n            expected_body={\"result\": True},\n        )\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 110,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 51,
        "n_ast_nodes": 81,
        "n_identifiers": 10,
        "d_id": 72162,
        "documentation": {
            "docstring": "Test that handlers without the `@cancellable` flag cannot be cancelled.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 215899,
        "commit_id": "a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857",
        "repo": "salt",
        "path": "tests/pytests/functional/modules/test_win_certutil.py",
        "file_name": "test_win_certutil.py",
        "fun_name": "test_del_store_not_found",
        "commit_message": "Add tests, fix state module",
        "code": "def test_del_store_not_found(certutil, cert_file):\n    \n    with pytest.raises(salt.exceptions.CommandExecutionError) as exc:\n        certutil.del_store(\n            source=str(cert_file.parent / \"absent.cer\"),\n            store=\"TrustedPublisher\",\n        )\n    assert \"cert_file not found\" in exc.value.message\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 64,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 50,
        "n_ast_nodes": 88,
        "n_identifiers": 16,
        "d_id": 54234,
        "documentation": {
            "docstring": "\n    Test del_store with a missing certificate\n    ",
            "n_words": 6,
            "vocab_size": 6,
            "n_whitespaces": 13,
            "language": "en"
        }
    },
    {
        "id": 221360,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/codecs.py",
        "file_name": "codecs.py",
        "fun_name": "__next__",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def __next__(self):\n\n        \n        line = self.readline()\n        if line:\n            return line\n        raise StopIteration\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 50,
        "n_words": 11,
        "vocab_size": 10,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 20,
        "n_ast_nodes": 36,
        "n_identifiers": 5,
        "d_id": 56375,
        "documentation": {
            "docstring": " Return the next decoded line from the input stream.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 204876,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/backends/base/operations.py",
        "file_name": "operations.py",
        "fun_name": "datetime_cast_date_sql",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def datetime_cast_date_sql(self, field_name, tzname):\n        \n        raise NotImplementedError(\n            \"subclasses of BaseDatabaseOperations may require a \"\n            \"datetime_cast_date_sql() method.\"\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 59,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 16,
        "n_ast_nodes": 31,
        "n_identifiers": 5,
        "d_id": 50949,
        "documentation": {
            "docstring": "\n        Return the SQL to cast a datetime value to date value.\n        ",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 247800,
        "commit_id": "9d21ecf7ceab55bc19c4457b8b07401b0b1623a7",
        "repo": "synapse",
        "path": "tests/storage/test_id_generators.py",
        "file_name": "test_id_generators.py",
        "fun_name": "test_empty",
        "commit_message": "Add type hints to tests files. (#12256)",
        "code": "def test_empty(self) -> None:\n        \n\n        id_gen = self._create_id_generator()\n\n        # The table is empty so we expect an empty map for positions\n        self.assertEqual(id_gen.get_positions(), {})\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 50,
        "n_words": 22,
        "vocab_size": 21,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 28,
        "n_ast_nodes": 50,
        "n_identifiers": 6,
        "d_id": 71933,
        "documentation": {
            "docstring": "Test an ID generator against an empty database gives sensible\n        current positions.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 204001,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/gis/gdal/raster/band.py",
        "file_name": "band.py",
        "fun_name": "nodata_value",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def nodata_value(self, value):\n        \n        if value is None:\n            capi.delete_band_nodata_value(self._ptr)\n        elif not isinstance(value, (int, float)):\n            raise ValueError(\"Nodata value must be numeric or None.\")\n        else:\n            capi.set_band_nodata_value(self._ptr, value)\n        self._flush()\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 93,
        "n_words": 25,
        "vocab_size": 24,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 56,
        "n_ast_nodes": 93,
        "n_identifiers": 12,
        "d_id": 50605,
        "documentation": {
            "docstring": "\n        Set the nodata value for this band.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 207737,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_views/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_has_module_permission",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_has_module_permission(self):\n        \n        self.client.force_login(self.superuser)\n        response = self.client.get(self.index_url)\n        self.assertContains(response, \"admin_views\")\n        self.assertContains(response, \"Articles\")\n        self.client.logout()\n\n        self.client.force_login(self.viewuser)\n        response = self.client.get(self.index_url)\n        self.assertContains(response, \"admin_views\")\n        self.assertContains(response, \"Articles\")\n        self.client.logout()\n\n        self.client.force_login(self.adduser)\n        response = self.client.get(self.index_url)\n        self.assertContains(response, \"admin_views\")\n        self.assertContains(response, \"Articles\")\n        self.client.logout()\n\n        self.client.force_login(self.changeuser)\n        response = self.client.get(self.index_url)\n        self.assertContains(response, \"admin_views\")\n        self.assertContains(response, \"Articles\")\n        self.client.logout()\n\n        self.client.force_login(self.deleteuser)\n        response = self.client.get(self.index_url)\n        self.assertContains(response, \"admin_views\")\n        self.assertContains(response, \"Articles\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 221,
        "n_words": 46,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 25,
        "token_counts": 224,
        "n_ast_nodes": 376,
        "n_identifiers": 14,
        "d_id": 52077,
        "documentation": {
            "docstring": "\n        has_module_permission() returns True for all users who\n        have any permission for that module (add, change, or delete), so that\n        the module is displayed on the admin index page.\n        ",
            "n_words": 28,
            "vocab_size": 24,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 219598,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/_osx_support.py",
        "file_name": "_osx_support.py",
        "fun_name": "_supports_universal_builds",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def _supports_universal_builds():\n    \n    # As an approximation, we assume that if we are running on 10.4 or above,\n    # then we are running with an Xcode environment that supports universal\n    # builds, in particular -isysroot and -arch arguments to the compiler. This\n    # is in support of allowing 10.4 universal builds to run on 10.3.x systems.\n\n    osx_version = _get_system_version_tuple()\n    return bool(osx_version >= (10, 4)) if osx_version else False\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 88,
        "n_words": 67,
        "vocab_size": 51,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 25,
        "n_ast_nodes": 46,
        "n_identifiers": 4,
        "d_id": 55636,
        "documentation": {
            "docstring": "Returns True if universal builds are supported on this system",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 287952,
        "commit_id": "2667f0b792b1f936aeb5958cc40d5dee26350bf6",
        "repo": "core",
        "path": "tests/components/plugwise/conftest.py",
        "file_name": "conftest.py",
        "fun_name": "mock_smile_adam_2",
        "commit_message": "Bump plugwise to v0.21.3, add related new features (#76610)\n\nCo-authored-by: Franck Nijhof <frenck@frenck.nl>",
        "code": "def mock_smile_adam_2() -> Generator[None, MagicMock, None]:\n    \n    chosen_env = \"m_adam_heating\"\n\n    with patch(\n        \"homeassistant.components.plugwise.gateway.Smile\", autospec=True\n    ) as smile_mock:\n        smile = smile_mock.return_value\n\n        smile.gateway_id = \"da224107914542988a88561b4452b0f6\"\n        smile.heater_id = \"056ee145a816487eaa69243c3280f8bf\"\n        smile.smile_version = \"3.6.4\"\n        smile.smile_type = \"thermostat\"\n        smile.smile_hostname = \"smile98765\"\n        smile.smile_name = \"Adam\"\n\n        smile.connect.return_value = True\n\n        smile.notifications = _read_json(chosen_env, \"notifications\")\n        smile.async_update.return_value = _read_json(chosen_env, \"all_data\")\n\n        yield smile\n\n\n@pytest.fixture",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 146,
        "n_words": 51,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 95,
        "n_ast_nodes": 180,
        "n_identifiers": 21,
        "d_id": 87135,
        "documentation": {
            "docstring": "Create a 2nd Mock Adam environment for testing exceptions.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 116214,
        "commit_id": "9a0e918bba3439959112a7fd8e5210276b5ac255",
        "repo": "mindsdb",
        "path": "mindsdb/integrations/handlers/druid_handler/druid_handler.py",
        "file_name": "druid_handler.py",
        "fun_name": "get_tables",
        "commit_message": "implemented the get_tables() and get_columns() methods",
        "code": "def get_tables(self) -> StatusResponse:\n        \n\n        query = \n        result = self.native_query(query)\n        df = result.data_frame\n\n        df = df[['TABLE_NAME' 'TABLE_TYPE']]\n        result.data_frame = df.rename(columns={'TABLE_NAME': 'table_name', 'TABLE_TYPE': 'table_type'})\n\n        return result\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 74,
        "n_words": 24,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 55,
        "n_ast_nodes": 103,
        "n_identifiers": 10,
        "d_id": 25698,
        "documentation": {
            "docstring": "\n        Return list of entities that will be accessible as tables.\n        Returns:\n            HandlerResponse\n        \n            SELECT *\n            FROM INFORMATION_SCHEMA.TABLES\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 79,
            "language": "en"
        }
    },
    {
        "id": 277470,
        "commit_id": "fa6d9107a498f7c2403ff28c7b389a1a0c5cc083",
        "repo": "keras",
        "path": "keras/engine/training_v1.py",
        "file_name": "training_v1.py",
        "fun_name": "_add_unique_metric_name",
        "commit_message": "reduct too long lines",
        "code": "def _add_unique_metric_name(self, metric_name, metric_fn, output_index):\n        \n        # For multi-output models, prepend the output names to the metric name.\n        if len(self.output_names) > 1:\n            # If we're loading from an already-serialized model, we've already\n            # prepended the output name, and we don't want to do it again.\n            #\n            # Alternatively, we may be receiving a stateless metric (e.g. the\n            # string \"accuracy\") rather than a `Metric` object, in which case we\n            # want to prepend the output name even if we are loading a\n            # serialized model.\n            if not getattr(metric_fn, \"_from_serialized\", False):\n                metric_name = \"%s_%s\" % (\n                    self.output_names[output_index],\n                    metric_name,\n                )\n\n        j = 1\n        base_metric_name = metric_name\n        while metric_name in self.metrics_names:\n            metric_name = \"%s_%d\" % (base_metric_name, j)\n            j += 1\n\n        return metric_name\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 345,
        "n_words": 118,
        "vocab_size": 80,
        "complexity": 4,
        "nloc": 13,
        "token_counts": 75,
        "n_ast_nodes": 128,
        "n_identifiers": 11,
        "d_id": 82051,
        "documentation": {
            "docstring": "Makes the metric name unique.\n\n          If there are multiple outputs for which the metrics are calculated,\n          the metric names have to be made unique by appending an integer.\n\n        Args:\n          metric_name: Metric name that corresponds to the metric specified by\n            the user. For example: 'acc'.\n          metric_fn: The Metric object.\n          output_index: The index of the model output for which the metric name\n            is being added.\n\n        Returns:\n          string, name of the model's unique metric name\n        ",
            "n_words": 72,
            "vocab_size": 48,
            "n_whitespaces": 169,
            "language": "en"
        }
    },
    {
        "id": 298347,
        "commit_id": "3737b58e85d834728fe27fefa05e8a0526e66d12",
        "repo": "core",
        "path": "tests/components/recorder/test_statistics.py",
        "file_name": "test_statistics.py",
        "fun_name": "test_statistics_duplicated",
        "commit_message": "Avoid fetching metadata multiple times during stat compile (#70397)",
        "code": "def test_statistics_duplicated(hass_recorder, caplog):\n    \n    hass = hass_recorder()\n    recorder = hass.data[DATA_INSTANCE]\n    setup_component(hass, \"sensor\", {})\n    zero, four, states = record_states(hass)\n    hist = history.get_significant_states(hass, zero, four)\n    assert dict(states) == dict(hist)\n\n    wait_recording_done(hass)\n    assert \"Compiling statistics for\" not in caplog.text\n    assert \"Statistics already compiled\" not in caplog.text\n\n    with patch(\n        \"homeassistant.components.sensor.recorder.compile_statistics\",\n        return_value=statistics.PlatformCompiledStatistics([], {}),\n    ) as compile_statistics:\n        recorder.do_adhoc_statistics(start=zero)\n        wait_recording_done(hass)\n        assert compile_statistics.called\n        compile_statistics.reset_mock()\n        assert \"Compiling statistics for\" in caplog.text\n        assert \"Statistics already compiled\" not in caplog.text\n        caplog.clear()\n\n        recorder.do_adhoc_statistics(start=zero)\n        wait_recording_done(hass)\n        assert not compile_statistics.called\n        compile_statistics.reset_mock()\n        assert \"Compiling statistics for\" not in caplog.text\n        assert \"Statistics already compiled\" in caplog.text\n        caplog.clear()\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 236,
        "n_words": 88,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 28,
        "token_counts": 181,
        "n_ast_nodes": 304,
        "n_identifiers": 28,
        "d_id": 97291,
        "documentation": {
            "docstring": "Test statistics with same start time is not compiled.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 215571,
        "commit_id": "68ab9eeae6899b7ff14fb3489b012862d62653c6",
        "repo": "salt",
        "path": "tests/unit/modules/test_cp.py",
        "file_name": "test_cp.py",
        "fun_name": "test_push",
        "commit_message": "Fix more tests",
        "code": "def test_push(self):\n        \n        filename = \"/saltines/test.file\"\n        if salt.utils.platform.is_windows():\n            filename = \"C:\\\\saltines\\\\test.file\"\n        with patch(\n            \"salt.modules.cp.os.path\",\n            MagicMock(isfile=Mock(return_value=True), wraps=cp.os.path),\n        ), patch(\n            \"salt.modules.cp.os.path\",\n            MagicMock(getsize=MagicMock(return_value=10), wraps=cp.os.path),\n        ), patch.multiple(\n            \"salt.modules.cp\",\n            _auth=MagicMock(**{\"return_value.gen_token.return_value\": \"token\"}),\n            __opts__={\"id\": \"abc\", \"file_buffer_size\": 10},\n        ), patch(\n            \"salt.utils.files.fopen\", mock_open(read_data=b\"content\")\n        ) as m_open, patch(\n            \"salt.channel.client.ReqChannel.factory\", MagicMock()\n        ) as req_channel_factory_mock:\n            response = cp.push(filename)\n            assert response, response\n            num_opens = len(m_open.filehandles[filename])\n            assert num_opens == 1, num_opens\n            fh_ = m_open.filehandles[filename][0]\n            assert fh_.read.call_count == 2, fh_.read.call_count\n            req_channel_factory_mock().__enter__().send.assert_called_once_with(\n                dict(\n                    loc=fh_.tell(),  # pylint: disable=resource-leakage\n                    cmd=\"_file_recv\",\n                    tok=\"token\",\n                    path=[\"saltines\", \"test.file\"],\n                    size=10,\n                    data=b\"\",  # data is empty here because load['data'] is overwritten\n                    id=\"abc\",\n                )\n            )\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 514,
        "n_words": 88,
        "vocab_size": 63,
        "complexity": 2,
        "nloc": 36,
        "token_counts": 241,
        "n_ast_nodes": 403,
        "n_identifiers": 43,
        "d_id": 54034,
        "documentation": {
            "docstring": "\n        Test if push works with good posix path.\n        ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 160766,
        "commit_id": "cde60cee195660f2dafb2993e609d66559525fe8",
        "repo": "numpy",
        "path": "numpy/lib/arraysetops.py",
        "file_name": "arraysetops.py",
        "fun_name": "in1d",
        "commit_message": "MAINT: Switch parameter name to 'kind' over 'method'",
        "code": "def in1d(ar1, ar2, assume_unique=False, invert=False, kind=None):\n    \n    # Ravel both arrays, behavior for the first array could be different\n    ar1 = np.asarray(ar1).ravel()\n    ar2 = np.asarray(ar2).ravel()\n\n    # Ensure that iteration through object arrays yields size-1 arrays\n    if ar2.dtype == object:\n        ar2 = ar2.reshape(-1, 1)\n    # Convert booleans to uint8 so we can use the fast integer algorithm\n    if ar1.dtype == bool:\n        ar1 = ar1.view(np.uint8)\n    if ar2.dtype == bool:\n        ar2 = ar2.view(np.uint8)\n\n    # Check if we can use a fast integer algorithm:\n    integer_arrays = (np.issubdtype(ar1.dtype, np.integer) and\n                      np.issubdtype(ar2.dtype, np.integer))\n\n    if kind not in {None, 'sort', 'dictionary'}:\n        raise ValueError(\n            \"Invalid kind: {0}. \".format(kind)\n            + \"Please use None, 'sort' or 'dictionary'.\")\n\n    if integer_arrays and kind in {None, 'dictionary'}:\n        ar2_min = np.min(ar2)\n        ar2_max = np.max(ar2)\n        ar1_size = ar1.size\n        ar2_size = ar2.size\n\n        # Check for integer overflow\n        with np.errstate(over='raise'):\n            try:\n                ar2_range = ar2_max - ar2_min\n\n                # Optimal performance is for approximately\n                # log10(size) > (log10(range) - 2.27) / 0.927.\n                # However, here we set the requirement that\n                # the intermediate array can only be 6x\n                # the combined memory allocation of the original\n                # arrays.\n                # (see discussion on \n                # https://github.com/numpy/numpy/pull/12065)\n                below_memory_constraint = (\n                    ar2_range <= 6 * (ar1_size + ar2_size)\n                )\n            except FloatingPointError:\n                below_memory_constraint = False\n\n        # Use the fast integer algorithm\n        if below_memory_constraint or kind == 'dictionary':\n\n            if invert:\n                outgoing_array = np.ones_like(ar1, dtype=bool)\n            else:\n                outgoing_array = np.zeros_like(ar1, dtype=bool)\n\n            # Make elements 1 where the integer exists in ar2\n            if invert:\n                isin_helper_ar = np.ones(ar2_range + 1, dtype=bool)\n                isin_helper_ar[ar2 - ar2_min] = 0\n            else:\n                isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool)\n                isin_helper_ar[ar2 - ar2_min] = 1\n\n            # Mask out elements we know won't work\n            basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min)\n            outgoing_array[basic_mask] = isin_helper_ar[ar1[basic_mask] -\n                                                        ar2_min]\n\n            return outgoing_array\n    elif kind == 'dictionary':\n        raise ValueError(\n            \"The 'dictionary' method is only \"\n            \"supported for boolean or integer arrays. \"\n            \"Please select 'sort' or None for kind.\"\n        )\n\n\n    # Check if one of the arrays may contain arbitrary objects\n    contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject\n\n    # This code is run when\n    # a) the first condition is true, making the code significantly faster\n    # b) the second condition is true (i.e. `ar1` or `ar2` may contain\n    #    arbitrary objects), since then sorting is not guaranteed to work\n    if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object:\n        if invert:\n            mask = np.ones(len(ar1), dtype=bool)\n            for a in ar2:\n                mask &= (ar1 != a)\n        else:\n            mask = np.zeros(len(ar1), dtype=bool)\n            for a in ar2:\n                mask |= (ar1 == a)\n        return mask\n\n    # Otherwise use sorting\n    if not assume_unique:\n        ar1, rev_idx = np.unique(ar1, return_inverse=True)\n        ar2 = np.unique(ar2)\n\n    ar = np.concatenate((ar1, ar2))\n    # We need this to be a stable sort, so always use 'mergesort'\n    # here. The values from the first array should always come before\n    # the values from the second array.\n    order = ar.argsort(kind='mergesort')\n    sar = ar[order]\n    if invert:\n        bool_ar = (sar[1:] != sar[:-1])\n    else:\n        bool_ar = (sar[1:] == sar[:-1])\n    flag = np.concatenate((bool_ar, [invert]))\n    ret = np.empty(ar.shape, dtype=bool)\n    ret[order] = flag\n\n    if assume_unique:\n        return ret[:len(ar1)]\n    else:\n        return ret[rev_idx]\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 1384,
        "n_words": 496,
        "vocab_size": 258,
        "complexity": 23,
        "nloc": 77,
        "token_counts": 585,
        "n_ast_nodes": 955,
        "n_identifiers": 57,
        "d_id": 38719,
        "documentation": {
            "docstring": "\n    Test whether each element of a 1-D array is also present in a second array.\n\n    Returns a boolean array the same length as `ar1` that is True\n    where an element of `ar1` is in `ar2` and False otherwise.\n\n    We recommend using :func:`isin` instead of `in1d` for new code.\n\n    Parameters\n    ----------\n    ar1 : (M,) array_like\n        Input array.\n    ar2 : array_like\n        The values against which to test each value of `ar1`.\n    assume_unique : bool, optional\n        If True, the input arrays are both assumed to be unique, which\n        can speed up the calculation.  Default is False.\n    invert : bool, optional\n        If True, the values in the returned array are inverted (that is,\n        False where an element of `ar1` is in `ar2` and True otherwise).\n        Default is False. ``np.in1d(a, b, invert=True)`` is equivalent\n        to (but is faster than) ``np.invert(in1d(a, b))``.\n   kind : {None, 'sort', 'dictionary'}, optional\n        The algorithm to use. This will not affect the final result,\n        but will affect the speed. Default will select automatically\n        based on memory considerations.\n\n        - If 'sort', will use a mergesort-based approach. This will have\n          a memory usage of roughly 6 times the sum of the sizes of\n          `ar1` and `ar2`, not accounting for size of dtypes.\n        - If 'dictionary', will use a key-dictionary approach similar\n          to a counting sort. This is only available for boolean and\n          integer arrays. This will have a memory usage of the\n          size of `ar1` plus the max-min value of `ar2`. This tends\n          to be the faster method if the following formula is true:\n          `log10(len(ar2)) > (log10(max(ar2)-min(ar2)) - 2.27) / 0.927`,\n          but may use greater memory.\n        - If `None`, will automatically choose 'dictionary' if\n          the required memory allocation is less than or equal to\n          6 times the sum of the sizes of `ar1` and `ar2`,\n          otherwise will use 'sort'. This is done to not use\n          a large amount of memory by default, even though\n           'dictionary' may be faster in most cases.\n\n        .. versionadded:: 1.8.0\n\n    Returns\n    -------\n    in1d : (M,) ndarray, bool\n        The values `ar1[in1d]` are in `ar2`.\n\n    See Also\n    --------\n    isin                  : Version of this function that preserves the\n                            shape of ar1.\n    numpy.lib.arraysetops : Module with a number of other functions for\n                            performing set operations on arrays.\n\n    Notes\n    -----\n    `in1d` can be considered as an element-wise function version of the\n    python keyword `in`, for 1-D sequences. ``in1d(a, b)`` is roughly\n    equivalent to ``np.array([item in b for item in a])``.\n    However, this idea fails if `ar2` is a set, or similar (non-sequence)\n    container:  As ``ar2`` is converted to an array, in those cases\n    ``asarray(ar2)`` is an object array rather than the expected array of\n    contained values.\n\n    .. versionadded:: 1.4.0\n\n    Examples\n    --------\n    >>> test = np.array([0, 1, 2, 5, 0])\n    >>> states = [0, 2]\n    >>> mask = np.in1d(test, states)\n    >>> mask\n    array([ True, False,  True, False,  True])\n    >>> test[mask]\n    array([0, 2, 0])\n    >>> mask = np.in1d(test, states, invert=True)\n    >>> mask\n    array([False,  True, False,  True, False])\n    >>> test[mask]\n    array([1, 5])\n    ",
            "n_words": 485,
            "vocab_size": 256,
            "n_whitespaces": 921,
            "language": "en"
        }
    },
    {
        "id": 245290,
        "commit_id": "fa77be290460e84ce7da975831cb7e687a419177",
        "repo": "mmdetection",
        "path": "mmdet/models/utils/misc.py",
        "file_name": "misc.py",
        "fun_name": "center_of_mass",
        "commit_message": "Refactor package",
        "code": "def center_of_mass(mask, esp=1e-6):\n    \n    h, w = mask.shape\n    grid_h = torch.arange(h, device=mask.device)[:, None]\n    grid_w = torch.arange(w, device=mask.device)\n    normalizer = mask.sum().float().clamp(min=esp)\n    center_h = (mask * grid_h).sum() / normalizer\n    center_w = (mask * grid_w).sum() / normalizer\n    return center_h, center_w\n\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 60,
        "n_words": 36,
        "vocab_size": 25,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 100,
        "n_ast_nodes": 156,
        "n_identifiers": 18,
        "d_id": 70747,
        "documentation": {
            "docstring": "Calculate the centroid coordinates of the mask.\n\n    Args:\n        mask (Tensor): The mask to be calculated, shape (h, w).\n        esp (float): Avoid dividing by zero. Default: 1e-6.\n\n    Returns:\n        tuple[Tensor]: the coordinates of the center point of the mask.\n\n            - center_h (Tensor): the center point of the height.\n            - center_w (Tensor): the center point of the width.\n    ",
            "n_words": 55,
            "vocab_size": 33,
            "n_whitespaces": 107,
            "language": "en"
        }
    },
    {
        "id": 187036,
        "commit_id": "b72f23fd699de9730e9009ac319b84da68f15a73",
        "repo": "streamlink",
        "path": "src/streamlink/plugin/plugin.py",
        "file_name": "plugin.py",
        "fun_name": "streams",
        "commit_message": "docs: update API page, add type annotations",
        "code": "def streams(self, stream_types=None, sorting_excludes=None):\n        \n\n        try:\n            ostreams = self._get_streams()\n            if isinstance(ostreams, dict):\n                ostreams = ostreams.items()\n\n            # Flatten the iterator to a list so we can reuse it.\n            if ostreams:\n                ostreams = list(ostreams)\n        except NoStreamsError:\n            return {}\n        except (OSError, ValueError) as err:\n            raise PluginError(err)\n\n        if not ostreams:\n            return {}\n\n        if stream_types is None:\n            stream_types = self.default_stream_types(ostreams)\n\n        # Add streams depending on stream type and priorities\n        sorted_streams = sorted(iterate_streams(ostreams),\n                                key=partial(stream_type_priority,\n                                            stream_types))\n\n        streams = {}\n        for name, stream in sorted_streams:\n            stream_type = type(stream).shortname()\n\n            # Use * as wildcard to match other stream types\n            if \"*\" not in stream_types and stream_type not in stream_types:\n                continue\n\n            # drop _alt from any stream names\n            if name.endswith(\"_alt\"):\n                name = name[:-len(\"_alt\")]\n\n            existing = streams.get(name)\n            if existing:\n                existing_stream_type = type(existing).shortname()\n                if existing_stream_type != stream_type:\n                    name = \"{0}_{1}\".format(name, stream_type)\n\n                if name in streams:\n                    name = \"{0}_alt\".format(name)\n                    num_alts = len(list(filter(lambda n: n.startswith(name), streams.keys())))\n\n                    # We shouldn't need more than 2 alt streams\n                    if num_alts >= 2:\n                        continue\n                    elif num_alts > 0:\n                        name = \"{0}{1}\".format(name, num_alts + 1)\n\n            # Validate stream name and discard the stream if it's bad.\n            match = re.match(\"([A-z0-9_+]+)\", name)\n            if match:\n                name = match.group(1)\n            else:\n                self.logger.debug(f\"The stream '{name}' has been ignored since it is badly named.\")\n                continue\n\n            # Force lowercase name and replace space with underscore.\n            streams[name.lower()] = stream\n\n        # Create the best/worst synonyms",
        "url": "https://github.com/streamlink/streamlink.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 21,
        "n_whitespaces": 907,
        "n_words": 215,
        "vocab_size": 135,
        "complexity": 23,
        "nloc": 68,
        "token_counts": 482,
        "n_ast_nodes": 506,
        "n_identifiers": 44,
        "d_id": 45676,
        "documentation": {
            "docstring": "\n        Attempts to extract available streams.\n\n        Returns a :class:`dict` containing the streams, where the key is\n        the name of the stream (most commonly the quality name), with the value\n        being a :class:`Stream` instance.\n\n        The result can contain the synonyms **best** and **worst** which\n        point to the streams which are likely to be of highest and\n        lowest quality respectively.\n\n        If multiple streams with the same name are found, the order of\n        streams specified in *stream_types* will determine which stream\n        gets to keep the name while the rest will be renamed to\n        \"<name>_<stream type>\".\n\n        The synonyms can be fine-tuned with the *sorting_excludes*\n        parameter, which can be one of these types:\n\n            - A list of filter expressions in the format\n              ``[operator]<value>``. For example the filter \">480p\" will\n              exclude streams ranked higher than \"480p\" from the list\n              used in the synonyms ranking. Valid operators are ``>``, ``>=``, ``<``\n              and ``<=``. If no operator is specified then equality will be tested.\n\n            - A function that is passed to :meth:`filter` with a list of\n              stream names as input.\n\n\n        :param stream_types: A list of stream types to return\n        :param sorting_excludes: Specify which streams to exclude from the best/worst synonyms\n        :returns: A :class:`dict` of stream names and :class:`streamlink.stream.Stream` instances\n        ",
            "n_words": 200,
            "vocab_size": 112,
            "n_whitespaces": 407,
            "language": "en"
        }
    },
    {
        "id": 113876,
        "commit_id": "551205a18ac2ac19626f4e4ffb2ed88fcad705b9",
        "repo": "mindsdb",
        "path": "mindsdb/api/mysql/mysql_proxy/mysql_proxy.py",
        "file_name": "mysql_proxy.py",
        "fun_name": "insert_predictor_answer",
        "commit_message": "fix",
        "code": "def insert_predictor_answer(self, insert):\n        \n        model_interface = self.session.model_interface\n        data_store = self.session.data_store\n\n        select_data_query = insert.get('select_data_query')\n        if isinstance(select_data_query, str) is False or len(select_data_query) == 0:\n            self.packet(\n                ErrPacket,\n                err_code=ERR.ER_WRONG_ARGUMENTS,\n                msg=\"'select_data_query' should not be empty\"\n            ).send()\n            return\n\n        models = model_interface.get_models()\n        if insert['name'] in [x['name'] for x in models]:\n            self.packet(\n                ErrPacket,\n                err_code=ERR.ER_WRONG_ARGUMENTS,\n                msg=f\"predictor with name '{insert['name']}'' already exists\"\n            ).send()\n            return\n\n        kwargs = {}\n        if isinstance(insert.get('training_options'), str) \\\n                and len(insert['training_options']) > 0:\n            try:\n                kwargs = json.loads(insert['training_options'])\n            except Exception:\n                self.packet(\n                    ErrPacket,\n                    err_code=ERR.ER_WRONG_ARGUMENTS,\n                    msg='training_options should be in valid JSON string'\n                ).send()\n                return\n\n        integration = self.session.integration\n        if isinstance(integration, str) is False or len(integration) == 0:\n            self.packet(\n                ErrPacket,\n                err_code=ERR.ER_WRONG_ARGUMENTS,\n                msg='select_data_query can be used only in query from database'\n            ).send()\n            return\n        insert['select_data_query'] = insert['select_data_query'].replace(r\"\\'\", \"'\")\n        ds_name = data_store.get_vacant_name(insert['name'])\n        ds = data_store.save_datasource(ds_name, integration, {'query': insert['select_data_query']})\n\n        insert['predict'] = [x.strip() for x in insert['predict'].split(',')]\n\n        ds_data = data_store.get_datasource(ds_name)\n        if ds_data is None:\n            raise Exception(f\"DataSource '{ds_name}' does not exists\")\n        ds_columns = [x['name'] for x in ds_data['columns']]\n        for col in insert['predict']:\n            if col not in ds_columns:\n                data_store.delete_datasource(ds_name)\n                raise Exception(f\"Column '{col}' not exists\")\n\n        try:\n            insert['predict'] = self._check_predict_columns(insert['predict'], ds_columns)\n        except Exception:\n            data_store.delete_datasource(ds_name)\n            raise\n\n        model_interface.learn(\n            insert['name'], ds, insert['predict'], ds_data['id'], kwargs=kwargs, delete_ds_on_fail=True\n        )\n\n        self.packet(OkPacket).send()\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 833,
        "n_words": 181,
        "vocab_size": 109,
        "complexity": 18,
        "nloc": 63,
        "token_counts": 445,
        "n_ast_nodes": 713,
        "n_identifiers": 42,
        "d_id": 25051,
        "documentation": {
            "docstring": " Start learn new predictor.\n            Parameters:\n             - insert - dict with keys as columns of mindsb.predictors table.\n        ",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 268873,
        "commit_id": "f1aa8b7d2a0c89591c5c42eca5b6f013114a7bbd",
        "repo": "keras",
        "path": "keras/preprocessing/sequence.py",
        "file_name": "sequence.py",
        "fun_name": "_remove_long_seq",
        "commit_message": "Copy sequence utils from keras_preprocessing directly into core keras\n\nPiperOrigin-RevId: 424915569",
        "code": "def _remove_long_seq(maxlen, seq, label):\n  \n  new_seq, new_label = [], []\n  for x, y in zip(seq, label):\n    if len(x) < maxlen:\n      new_seq.append(x)\n      new_label.append(y)\n  return new_seq, new_label\n\n\n@keras_export('keras.preprocessing.sequence.TimeseriesGenerator')",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export('keras.preprocessing.sequence.TimeseriesGenerator')",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 41,
        "n_words": 25,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 55,
        "n_ast_nodes": 99,
        "n_identifiers": 12,
        "d_id": 79741,
        "documentation": {
            "docstring": "Removes sequences that exceed the maximum length.\n\n  Args:\n      maxlen: Int, maximum length of the output sequences.\n      seq: List of lists, where each sublist is a sequence.\n      label: List where each element is an integer.\n\n  Returns:\n      new_seq, new_label: shortened lists for `seq` and `label`.\n  ",
            "n_words": 43,
            "vocab_size": 36,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 21893,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/chardet/charsetprober.py",
        "file_name": "charsetprober.py",
        "fun_name": "remove_xml_tags",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def remove_xml_tags(buf):\n        \n        filtered = bytearray()\n        in_tag = False\n        prev = 0\n        buf = memoryview(buf).cast(\"c\")\n\n        for curr, buf_char in enumerate(buf):\n            # Check if we're coming out of or entering an XML tag\n            if buf_char == b\">\":\n                prev = curr + 1\n                in_tag = False\n            elif buf_char == b\"<\":\n                if curr > prev and not in_tag:\n                    # Keep everything after last non-extended-ASCII,\n                    # non-alphabetic character\n                    filtered.extend(buf[prev:curr])\n                    # Output a space to delimit stretch we kept\n                    filtered.extend(b\" \")\n                in_tag = True\n\n        # If we're not in a tag...\n        if not in_tag:\n            # Keep everything after last non-extended-ASCII, non-alphabetic\n            # character\n            filtered.extend(buf[prev:])\n\n        return filtered\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 384,
        "n_words": 100,
        "vocab_size": 62,
        "complexity": 7,
        "nloc": 17,
        "token_counts": 103,
        "n_ast_nodes": 180,
        "n_identifiers": 12,
        "d_id": 4089,
        "documentation": {
            "docstring": "\n        Returns a copy of ``buf`` that retains only the sequences of English\n        alphabet and high byte characters that are not between <> characters.\n        This filter can be applied to all scripts which contain both English\n        characters and extended ASCII characters, but is currently only used by\n        ``Latin1Prober``.\n        ",
            "n_words": 47,
            "vocab_size": 41,
            "n_whitespaces": 90,
            "language": "en"
        }
    },
    {
        "id": 74208,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/tests/test_jinja2.py",
        "file_name": "test_jinja2.py",
        "fun_name": "test_rich_text_is_safe",
        "commit_message": "Reformat with black",
        "code": "def test_rich_text_is_safe(self):\n        \n        stream_block = blocks.StreamBlock(\n            [\n                (\n                    \"paragraph\",\n                    blocks.RichTextBlock(template=\"tests/jinja2/rich_text.html\"),\n                )\n            ]\n        )\n        stream_value = stream_block.to_python(\n            [\n                {\n                    \"type\": \"paragraph\",\n                    \"value\": '<p>Merry <a linktype=\"page\" id=\"4\">Christmas</a>!</p>',\n                },\n            ]\n        )\n\n        result = render_to_string(\n            \"tests/jinja2/stream.html\",\n            {\n                \"value\": stream_value,\n            },\n        )\n\n        self.assertIn(\n            '<p>Merry <a href=\"/events/christmas/\">Christmas</a>!</p>', result\n        )\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 344,
        "n_words": 42,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 26,
        "token_counts": 70,
        "n_ast_nodes": 125,
        "n_identifiers": 12,
        "d_id": 16234,
        "documentation": {
            "docstring": "\n        Ensure that RichText values are marked safe\n        so that they don't get double-escaped when inserted into a parent template (#2542)\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 178629,
        "commit_id": "982929807fdc5838554cf302a2013a28e7707514",
        "repo": "Nuitka",
        "path": "nuitka/utils/SharedLibraries.py",
        "file_name": "SharedLibraries.py",
        "fun_name": "getWindowsDLLVersion",
        "commit_message": "macOS: Avoid references to original install paths as library ids",
        "code": "def getWindowsDLLVersion(filename):\n    \n    # Get size needed for buffer (0 if no info)\n    import ctypes.wintypes\n\n    if type(filename) is unicode:\n        GetFileVersionInfoSizeW = ctypes.windll.version.GetFileVersionInfoSizeW\n        GetFileVersionInfoSizeW.argtypes = [\n            ctypes.wintypes.LPCWSTR,\n            ctypes.wintypes.LPDWORD,\n        ]\n        GetFileVersionInfoSizeW.restype = ctypes.wintypes.HANDLE\n        size = GetFileVersionInfoSizeW(filename, None)\n    else:\n        size = ctypes.windll.version.GetFileVersionInfoSizeA(filename, None)\n\n    if not size:\n        return (0, 0, 0, 0)\n\n    # Create buffer\n    res = ctypes.create_string_buffer(size)\n    # Load file information into buffer res\n\n    if type(filename) is unicode:\n        # Python3 needs our help here.\n        GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoW\n        GetFileVersionInfo.argtypes = [\n            ctypes.wintypes.LPCWSTR,\n            ctypes.wintypes.DWORD,\n            ctypes.wintypes.DWORD,\n            ctypes.wintypes.LPVOID,\n        ]\n        GetFileVersionInfo.restype = ctypes.wintypes.BOOL\n\n    else:\n        # Python2 just works.\n        GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoA\n\n    success = GetFileVersionInfo(filename, 0, size, res)\n    # This cannot really fail anymore.\n    assert success\n\n    # Look for codepages\n    VerQueryValueA = ctypes.windll.version.VerQueryValueA\n    VerQueryValueA.argtypes = [\n        ctypes.wintypes.LPCVOID,\n        ctypes.wintypes.LPCSTR,\n        ctypes.wintypes.LPVOID,\n        ctypes.POINTER(ctypes.c_uint32),\n    ]\n    VerQueryValueA.restype = ctypes.wintypes.BOOL\n\n    file_info = ctypes.POINTER(VsFixedFileInfoStructure)()\n    uLen = ctypes.c_uint32(ctypes.sizeof(file_info))\n\n    b = VerQueryValueA(res, br\"\\\\\", ctypes.byref(file_info), ctypes.byref(uLen))\n    if not b:\n        return (0, 0, 0, 0)\n\n    if file_info.contents.dwSignature != 0xFEEF04BD:\n        return (0, 0, 0, 0)\n\n    ms = file_info.contents.dwFileVersionMS\n    ls = file_info.contents.dwFileVersionLS\n\n    return (ms >> 16) & 0xFFFF, ms & 0xFFFF, (ls >> 16) & 0xFFFF, ls & 0xFFFF\n\n\n_readelf_usage = \"The 'readelf' is used to analyse dependencies on ELF using systems and required to be found.\"\n\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 480,
        "n_words": 194,
        "vocab_size": 118,
        "complexity": 6,
        "nloc": 46,
        "token_counts": 351,
        "n_ast_nodes": 537,
        "n_identifiers": 43,
        "d_id": 42769,
        "documentation": {
            "docstring": "Return DLL version information from a file.\n\n    If not present, it will be (0, 0, 0, 0), otherwise it will be\n    a tuple of 4 numbers.\n    ",
            "n_words": 26,
            "vocab_size": 21,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 175168,
        "commit_id": "9d6a239a34a66e16188d76c23a3a770515ca44ca",
        "repo": "cpython",
        "path": "Lib/test/test_sqlite3/test_transactions.py",
        "file_name": "test_transactions.py",
        "fun_name": "test_rollback_cursor_consistency",
        "commit_message": "bpo-44092: Don't reset statements/cursors before rollback (GH-26026)\n\nIn SQLite versions pre 3.7.11, pending statements would block a rollback.  This is no longer the case, so remove the workaround.",
        "code": "def test_rollback_cursor_consistency(self):\n        \n        con = sqlite.connect(\":memory:\")\n        cur = con.cursor()\n        cur.execute(\"create table test(x)\")\n        cur.execute(\"insert into test(x) values (5)\")\n        cur.execute(\"select 1 union select 2 union select 3\")\n\n        con.rollback()\n        self.assertEqual(cur.fetchall(), [(1,), (2,), (3,)])\n\n",
        "url": "https://github.com/python/cpython.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 85,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 8,
        "token_counts": 71,
        "n_ast_nodes": 123,
        "n_identifiers": 11,
        "d_id": 41562,
        "documentation": {
            "docstring": "Check that cursors behave correctly after rollback.",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 6,
            "language": "en"
        }
    },
    {
        "id": 218049,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/importlib/_bootstrap.py",
        "file_name": "_bootstrap.py",
        "fun_name": "is_package",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def is_package(cls, fullname):\n        \n        return False\n\n    load_module = classmethod(_load_module_shim)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 25,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 28,
        "n_identifiers": 6,
        "d_id": 55099,
        "documentation": {
            "docstring": "Return False as built-in modules are never packages.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 110014,
        "commit_id": "1068a6faa19767724437461bcfb88c6852ec435c",
        "repo": "matplotlib",
        "path": "examples/event_handling/path_editor.py",
        "file_name": "path_editor.py",
        "fun_name": "get_ind_under_point",
        "commit_message": "Remove unnecessary np.{,as}array / astype calls.\n\nQuite often numpy will call asarray for us, saving us the need to call\nasarray explicitly.\n\nWhen we do call asarray (or array) ourselves, a dtype can directly be\npassed in, rather than immediately calling astype immediately after.\nPassing the dtype makes it unnecessary for asarray to infer the dtype\nof the passed-in container, and can also save an extra array allocation\nif asarray first has to allocate an array of a type and astype\nimmediately has to allocate an array of another type.",
        "code": "def get_ind_under_point(self, event):\n        \n        xy = self.pathpatch.get_path().vertices\n        xyt = self.pathpatch.get_transform().transform(xy)  # to display coords\n        xt, yt = xyt[:, 0], xyt[:, 1]\n        d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)\n        ind = d.argmin()\n        return ind if d[ind] < self.epsilon else None\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 90,
        "n_words": 40,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 96,
        "n_ast_nodes": 152,
        "n_identifiers": 20,
        "d_id": 23885,
        "documentation": {
            "docstring": "\n        Return the index of the point closest to the event position or *None*\n        if no point is within ``self.epsilon`` to the event position.\n        ",
            "n_words": 23,
            "vocab_size": 17,
            "n_whitespaces": 45,
            "language": "en"
        }
    },
    {
        "id": 23387,
        "commit_id": "6e607a0fa1cefbf0388dac86c84debf4781cec48",
        "repo": "PaddleOCR",
        "path": "ppocr/modeling/backbones/rec_efficientb3_pren.py",
        "file_name": "rec_efficientb3_pren.py",
        "fun_name": "round_filters",
        "commit_message": "[Feature] Add PREN Scene Text Recognition Model(Accepted in CVPR2021) (#5563)\n\n* [Feature] add PREN scene text recognition model\r\n\r\n* [Patch] Optimize yml File\r\n\r\n* [Patch] Save Label/Pred Preprocess Time Cost\r\n\r\n* [BugFix] Modify Shape Conversion to Fit for Inference Model Exportion\r\n\r\n* [Patch] ?\r\n\r\n* [Patch] ?\r\n\r\n* 啥情况...",
        "code": "def round_filters(filters, global_params):\n        \n        multiplier = global_params.width_coefficient\n        if not multiplier:\n            return filters\n        divisor = global_params.depth_divisor\n        filters *= multiplier\n        new_filters = int(filters + divisor / 2) // divisor * divisor\n        if new_filters < 0.9 * filters:\n            new_filters += divisor\n        return int(new_filters)\n",
        "url": "https://github.com/PaddlePaddle/PaddleOCR.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 117,
        "n_words": 39,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 10,
        "token_counts": 56,
        "n_ast_nodes": 92,
        "n_identifiers": 9,
        "d_id": 4587,
        "documentation": {
            "docstring": "Calculate and round number of filters based on depth multiplier.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 177015,
        "commit_id": "b2f91c34a23058dd70b41784af0d87890216026a",
        "repo": "networkx",
        "path": "networkx/algorithms/tests/test_lowest_common_ancestors.py",
        "file_name": "test_lowest_common_ancestors.py",
        "fun_name": "assert_lca_dicts_same",
        "commit_message": "Naive lowest common ancestor implementation (#5736)\n\n* Add naive lca methods\r\n\r\n* Naive algorithm implementation for LCA\r\n\r\n* Modify naive lca functions\r\n\r\n* Correct parameters of nx.ancestors\r\n\r\n* Update lowest_common_ancestors.py\r\n\r\n* Parametrize tests\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\n\r\n* Yield instead of append\r\n\r\n* Tests for naive lca\r\n\r\n* Correct test cases for naive lca algorithms\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>\r\n\r\n* Fix function name -when calling\r\n\r\n* Make requested changes\r\n\r\n* Inlining _get_a_lowest_common_ancestor\r\n\r\nCo-authored-by: dtuncturk <dilaramemis@sabanciuniv.edu>\r\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\nCo-authored-by: Mridul Seth <mail@mriduls.com>",
        "code": "def assert_lca_dicts_same(self, d1, d2, G=None):\n        \n        if G is None:\n            G = self.DG\n            root_distance = self.root_distance\n        else:\n            roots = [n for n, deg in G.in_degree if deg == 0]\n            assert len(roots) == 1\n            root_distance = nx.shortest_path_length(G, source=roots[0])\n\n        for a, b in ((min(pair), max(pair)) for pair in chain(d1, d2)):\n            assert (\n                root_distance[get_pair(d1, a, b)] == root_distance[get_pair(d2, a, b)]\n            )\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 177,
        "n_words": 57,
        "vocab_size": 40,
        "complexity": 6,
        "nloc": 12,
        "token_counts": 124,
        "n_ast_nodes": 183,
        "n_identifiers": 22,
        "d_id": 42227,
        "documentation": {
            "docstring": "Checks if d1 and d2 contain the same pairs and\n        have a node at the same distance from root for each.\n        If G is None use self.DG.",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 130803,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/node.py",
        "file_name": "node.py",
        "fun_name": "_prepare_socket_file",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def _prepare_socket_file(self, socket_path, default_prefix):\n        \n        result = socket_path\n        is_mac = sys.platform.startswith(\"darwin\")\n        if sys.platform == \"win32\":\n            if socket_path is None:\n                result = f\"tcp://{self._localhost}\" f\":{self._get_unused_port()}\"\n        else:\n            if socket_path is None:\n                result = self._make_inc_temp(\n                    prefix=default_prefix, directory_name=self._sockets_dir\n                )\n            else:\n                try_to_create_directory(os.path.dirname(socket_path))\n\n            # Check socket path length to make sure it's short enough\n            maxlen = (104 if is_mac else 108) - 1  # sockaddr_un->sun_path\n            if len(result.split(\"://\", 1)[-1].encode(\"utf-8\")) > maxlen:\n                raise OSError(\n                    \"AF_UNIX path length cannot exceed \"\n                    \"{} bytes: {!r}\".format(maxlen, result)\n                )\n        return result\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 333,
        "n_words": 77,
        "vocab_size": 56,
        "complexity": 6,
        "nloc": 20,
        "token_counts": 127,
        "n_ast_nodes": 234,
        "n_identifiers": 25,
        "d_id": 29375,
        "documentation": {
            "docstring": "Prepare the socket file for raylet and plasma.\n\n        This method helps to prepare a socket file.\n        1. Make the directory if the directory does not exist.\n        2. If the socket file exists, do nothing (this just means we aren't the\n           first worker on the node).\n\n        Args:\n            socket_path (string): the socket file to prepare.\n        ",
            "n_words": 53,
            "vocab_size": 40,
            "n_whitespaces": 109,
            "language": "en"
        }
    },
    {
        "id": 96313,
        "commit_id": "b7d894b56953153cf33008ae7d33e1e41b175eb7",
        "repo": "sentry",
        "path": "tests/sentry/integrations/slack/endpoints/events/test_message_im.py",
        "file_name": "test_message_im.py",
        "fun_name": "test_user_message_already_unlinked",
        "commit_message": "ref(tests): Split up large files (#31828)",
        "code": "def test_user_message_already_unlinked(self):\n        \n        IdentityProvider.objects.create(type=\"slack\", external_id=\"TXXXXXXX1\", config={})\n\n        responses.add(responses.POST, \"https://slack.com/api/chat.postMessage\", json={\"ok\": True})\n        resp = self.post_webhook(event_data=json.loads(MESSAGE_IM_EVENT_UNLINK))\n        assert resp.status_code == 200, resp.content\n        request = responses.calls[0].request\n        assert request.headers[\"Authorization\"] == \"Bearer xoxb-xxxxxxxxx-xxxxxxxxxx-xxxxxxxxxxxx\"\n        data = json.loads(request.body)\n        assert \"You do not have a linked identity to unlink\" in get_response_text(data)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 103,
        "n_words": 40,
        "vocab_size": 35,
        "complexity": 1,
        "nloc": 9,
        "token_counts": 104,
        "n_ast_nodes": 174,
        "n_identifiers": 25,
        "d_id": 19302,
        "documentation": {
            "docstring": "\n        Test that when a user without an Identity types in \"unlink\" to the DM we\n        reply with the correct response.\n        ",
            "n_words": 20,
            "vocab_size": 19,
            "n_whitespaces": 42,
            "language": "en"
        }
    },
    {
        "id": 83023,
        "commit_id": "c30458e1740c7878e436037f61431884e54b349d",
        "repo": "zulip",
        "path": "zerver/tests/test_subs.py",
        "file_name": "test_subs.py",
        "fun_name": "test_subscribe_to_stream_post_policy_moderators_stream",
        "commit_message": "streams: Add notifications for posting policy changes.\n\nAn explanatory note on the changes in zulip.yaml and\ncurl_param_value_generators is warranted here. In our automated\ntests for our curl examples, the test for the API endpoint that\nchanges the posting permissions of a stream comes before our\nexisting curl test for adding message reactions.\n\nSince there is an extra notification message due to the change in\nposting permissions, the message IDs used in tests that come after\nneed to be incremented by 1.\n\nThis is a part of #20289.",
        "code": "def test_subscribe_to_stream_post_policy_moderators_stream(self) -> None:\n        \n        member = self.example_user(\"AARON\")\n        stream = self.make_stream(\"stream1\")\n        # Make sure that we are testing this with full member which is just below the moderator\n        # in the role hierarchy.\n        self.assertFalse(member.is_provisional_member)\n        do_change_stream_post_policy(\n            stream, Stream.STREAM_POST_POLICY_MODERATORS, acting_user=member\n        )\n        result = self.common_subscribe_to_streams(member, [\"stream1\"])\n        self.assert_json_success(result)\n\n        json = result.json()\n        self.assertEqual(json[\"subscribed\"], {member.email: [\"stream1\"]})\n        self.assertEqual(json[\"already_subscribed\"], {})\n",
        "url": "https://github.com/zulip/zulip.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 153,
        "n_words": 51,
        "vocab_size": 45,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 100,
        "n_ast_nodes": 172,
        "n_identifiers": 18,
        "d_id": 17579,
        "documentation": {
            "docstring": "\n        Members can subscribe to streams where only admins and moderators can post\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 319934,
        "commit_id": "c8e838e3a0828e82efac1fd93ebb9aba6a000ff8",
        "repo": "paperless-ngx",
        "path": "src/documents/tests/test_management_retagger.py",
        "file_name": "test_management_retagger.py",
        "fun_name": "test_overwrite_storage_path",
        "commit_message": "Adds the storage paths to the re-tagger command",
        "code": "def test_overwrite_storage_path(self):\n        \n        call_command(\"document_retagger\", \"--storage_path\", \"--overwrite\")\n        d_first, d_second, d_unrelated, d_auto = self.get_updated_docs()\n\n        self.assertEqual(d_first.storage_path, self.sp2)\n        self.assertEqual(d_auto.storage_path, self.sp1)\n        self.assertIsNone(d_second.storage_path)\n        self.assertEqual(d_unrelated.storage_path, self.sp2)\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 67,
        "n_words": 18,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 71,
        "n_ast_nodes": 116,
        "n_identifiers": 13,
        "d_id": 117022,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - 2 storage paths with documents which match them\n            - 1 document which matches but has a storage path\n        WHEN:\n            - document retagger is called with overwrite\n        THEN:\n            - Matching document's storage paths updated\n            - Non-matching documents have no storage path\n            - Existing storage patch overwritten\n        ",
            "n_words": 47,
            "vocab_size": 32,
            "n_whitespaces": 142,
            "language": "en"
        }
    },
    {
        "id": 81176,
        "commit_id": "21972c91dd2b52cd206bf71ea038ab0e1f478b32",
        "repo": "awx",
        "path": "awx/conf/settings.py",
        "file_name": "settings.py",
        "fun_name": "hashkey",
        "commit_message": "add lock to cachetools usage\n\n* We observed daphne giving tracebacks when accessing logging settings.\n  Originally, configure tower in tower settings was no a suspect because\n  daphne is not multi-process. We've had issues with configure tower in\n  tower settings and multi-process before. We later learned that Daphne\n  is multi-threaded. Configure tower in tower was back to being a\n  suspect. We constructed a minimal reproducer to show that multiple\n  threads accessing settings can cause the same traceback that we saw in\n  daphne. See\n  https://gist.github.com/chrismeyersfsu/7aa4bdcf76e435efd617cb078c64d413\n  for that recreator. These fixes stop the recreation.",
        "code": "def hashkey(cls, *args, **kwargs):\n        \n        return cachetools.keys.hashkey(f\"<{cls.__name__}>\", *args, **kwargs)\n\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 22,
        "n_words": 8,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 28,
        "n_ast_nodes": 52,
        "n_identifiers": 7,
        "d_id": 17168,
        "documentation": {
            "docstring": "\n        Usage of @cachetools.cached has changed to @cachetools.cachedmethod\n        The previous cachetools decorator called the hash function and passed in (self, key).\n        The new cachtools decorator calls the hash function with just (key).\n        Ideally, we would continue to pass self, however, the cachetools decorator interface\n        does not allow us to.\n\n        This hashkey function is to maintain that the key generated looks like\n        ('<SettingsWrapper>', key). The thought is that maybe it is important to namespace\n        our cache to the SettingsWrapper scope in case some other usage of this cache exists.\n        I can not think of how any other system could and would use our private cache, but\n        for safety sake we are ensuring the key schema does not change.\n        ",
            "n_words": 116,
            "vocab_size": 82,
            "n_whitespaces": 194,
            "language": "en"
        }
    },
    {
        "id": 71201,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/admin/rich_text/converters/contentstate.py",
        "file_name": "contentstate.py",
        "fun_name": "link_entity",
        "commit_message": "Reformat with black",
        "code": "def link_entity(props):\n    \n    id_ = props.get(\"id\")\n    link_props = {}\n\n    if id_ is not None:\n        link_props[\"linktype\"] = \"page\"\n        link_props[\"id\"] = id_\n    else:\n        link_props[\"href\"] = check_url(props.get(\"url\"))\n\n    return DOM.create_element(\"a\", link_props, props[\"children\"])\n\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 66,
        "n_words": 27,
        "vocab_size": 21,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 66,
        "n_ast_nodes": 121,
        "n_identifiers": 8,
        "d_id": 15641,
        "documentation": {
            "docstring": "\n    <a linktype=\"page\" id=\"1\">internal page link</a>\n    ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 62242,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/distlib/version.py",
        "file_name": "version.py",
        "fun_name": "_suggest_semantic_version",
        "commit_message": "upd; format",
        "code": "def _suggest_semantic_version(s):\n    \n    result = s.strip().lower()\n    for pat, repl in _REPLACEMENTS:\n        result = pat.sub(repl, result)\n    if not result:\n        result = '0.0.0'\n\n    # Now look for numeric prefix, and separate it out from\n    # the rest.\n    #import pdb; pdb.set_trace()\n    m = _NUMERIC_PREFIX.match(result)\n    if not m:\n        prefix = '0.0.0'\n        suffix = result\n    else:\n        prefix = m.groups()[0].split('.')\n        prefix = [int(i) for i in prefix]\n        while len(prefix) < 3:\n            prefix.append(0)\n        if len(prefix) == 3:\n            suffix = result[m.end():]\n        else:\n            suffix = '.'.join([str(i) for i in prefix[3:]]) + result[m.end():]\n            prefix = prefix[:3]\n        prefix = '.'.join([str(i) for i in prefix])\n        suffix = suffix.strip()\n    if suffix:\n        #import pdb; pdb.set_trace()\n        # massage the suffix.\n        for pat, repl in _SUFFIX_REPLACEMENTS:\n            suffix = pat.sub(repl, suffix)\n\n    if not suffix:\n        result = prefix\n    else:\n        sep = '-' if 'dev' in suffix else '+'\n        result = prefix + sep + suffix\n    if not is_semver(result):\n        result = None\n    return result\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 370,
        "n_words": 144,
        "vocab_size": 67,
        "complexity": 14,
        "nloc": 33,
        "token_counts": 242,
        "n_ast_nodes": 411,
        "n_identifiers": 26,
        "d_id": 12903,
        "documentation": {
            "docstring": "\n    Try to suggest a semantic form for a version for which\n    _suggest_normalized_version couldn't come up with anything.\n    ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 56284,
        "commit_id": "5afded9fe6724d9e336f59792ee1d60656a2d94d",
        "repo": "prefect",
        "path": "tests/cli/test_deployment_preview.py",
        "file_name": "test_deployment_preview.py",
        "fun_name": "test_previewing_subprocess_deployment",
        "commit_message": "Add a CLI command to preview how a FlowRun will appear in any FlowRunner's execution environment (PrefectHQ/orion#1971)\n\nCo-authored-by: Terrence Dorsey <terrence@prefect.io>\r\nCo-authored-by: Michael Adkins <madkinszane@gmail.com>",
        "code": "def test_previewing_subprocess_deployment():\n    \n\n    result = invoke_and_assert(\n        [\n            \"deployment\",\n            \"preview\",\n            \"./tests/deployment_test_files/single_deployment.py\",\n        ],\n        expected_output_contains=\"prefect.engine\",\n    )\n    assert result.stdout.endswith(\"\\n\")\n\n    preview = result.stdout.strip()\n\n    # spot-check some variables and the command-line\n    assert \"\\nPREFECT_TEST_MODE=True \\\\\" in preview\n    assert \"\\nPREFECT_LOGGING_LEVEL=DEBUG \\\\\" in preview\n    assert preview.endswith(\" -m prefect.engine 00000000000000000000000000000000\")\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 120,
        "n_words": 39,
        "vocab_size": 31,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 56,
        "n_ast_nodes": 110,
        "n_identifiers": 8,
        "d_id": 11495,
        "documentation": {
            "docstring": "`prefect deployment preview my-flow-file.py` should render the\n    shell command that will be run for the subprocess",
            "n_words": 16,
            "vocab_size": 15,
            "n_whitespaces": 18,
            "language": "en"
        }
    },
    {
        "id": 320775,
        "commit_id": "a20bb67a878b2e68abf8268c1b0a27f018d01352",
        "repo": "qutebrowser",
        "path": "qutebrowser/completion/completionwidget.py",
        "file_name": "completionwidget.py",
        "fun_name": "completion_item_yank",
        "commit_message": "mypy: Upgrade to PyQt5-stubs 5.15.6.0\n\nFor some unknown reason, those new stubs cause a *lot* of things now to be\nchecked by mypy which formerly probably got skipped due to Any being implied\nsomewhere.\n\nThe stubs themselves mainly improved, with a couple of regressions too.\n\nIn total, there were some 337 (!) new mypy errors. This commit fixes almost all\nof them, and the next commit improves a fix to get things down to 0 errors\nagain.\n\nOverview of the changes:\n\n==== qutebrowser/app.py\n\n- Drop type ignore due to improved stubs.\n\n==== qutebrowser/browser/browsertab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  This is debatable: I suppose the abstract stuff shouldn't need to know\n  anything about the concrete backends at all. But it seems like we cut some\n  corners when initially implementing things, and put some code in browsertab.py\n  just because the APIs of both backends happened to be compatible. Perhaps\n  something to reconsider once we drop QtWebKit and hopefully implement a dummy\n  backend.\n\n- Add an additional assertion in AbstractAction.run_string. This is already\n  covered by the isinstance(member, self.action_base) above it, but that's too\n  dynamic for mypy to understand.\n\n- Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x\n  and y components), not a single int.\n\n- Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x\n  and y components), not a single int.\n\n- Fix the argument types of AbstractScroller.to_perc, as it's possible to pass\n  fractional percentages too.\n\n- Specify the type for AbstractHistoryPrivate._history. See above (_widget) re\n  this being debatable.\n\n- Fix the return type of AbstractTabPrivate.event_target(), which can be None\n  (see #3888).\n\n- Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS\n  return value), not None.\n\n- Fix the argument type for AbstractTabPrivate.toggle_inspector: position can\n  be None to use the last used position.\n\n- Declare the type of sub-objects of AbstractTab.\n\n- Fix the return value of AbstractTab.icon(), which is the QIcon, not None.\n\n==== qutebrowser/browser/commands.py\n\n- Make sure the active window is a MainWindow (with a .win_id attribute).\n\n==== qutebrowser/browser/downloadview.py\n\n- Add _model() which makes sure that self.model() is a DownloadModel, not None\n  or any other model. This is needed because other methods access a variety of\n  custom attributes on it, e.g. last_index().\n\n==== qutebrowser/browser/greasemonkey.py\n\n- Add an ignore for AbstractDownload.requested_url which we patch onto the\n  downloads. Probably would be nicer to add it as a proper attribute which always\n  gets set by the DownloadManager.\n\n==== qutebrowser/browser/hints.py\n\n- Remove type ignores for QUrl.toString().\n- Add a new type ignore for combining different URL flags (which works, but is\n  not exactly type safe... still probably a regression in the stubs).\n- Make sure the things we get back from self._get_keyparser are what we actually\n  expect. Probably should introduce a TypedDict (and/or overloads for\n  _get_keyparser with typing.Literal) to teach mypy about the exact return value.\n  See #7098.\n  This is needed because we access Hint/NormalKeyParser-specific attributes such\n  as .set_inhibited_timout() or .update_bindings().\n\n==== qutebrowser/browser/inspector.py\n\n- Similar changes than in browsertab.py to make some types where we share API\n  (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next\n  commit.\n\n==== qutebrowser/browser/network/pac.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/qtnetworkdownloads.py\n\n- Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an\n  AbstractDownload), so that we can call ._uses_nam() on it.\n\n==== qutebrowser/browser/qutescheme.py\n\n- Remove now unneeded type ignore for QUrl flags.\n\n==== qutebrowser/browser/urlmarks.py\n\n- Specify the type of UrlMarkManager._lineparser, as those only get initialized\n  in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist.\n\n==== qutebrowser/browser/webelem.py\n\n- New casts to turn single KeyboardModifier (enum) entries into\n  KeyboardModifiers (flags). Might not be needed anymore with Qt 6.\n- With that, casting the final value is now unneeded.\n\n==== qutebrowser/browser/webengine/notification.py\n\n- Remove now unneeded type ignore for signal.\n- Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished()\n  is a QProcess, not just any QObject.\n\n==== qutebrowser/browser/webengine/webenginedownloads.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webengine/webengineelem.py\n\n- Specify the type of WebEngineElement._tab.\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webengineinspector.py\n\n- See changes to inspector.py and next commit.\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/browser/webengine/webenginequtescheme.py\n\n- Remove now unneeded type ignore for mixed flags.\n\n==== qutebrowser/browser/webengine/webenginesettings.py\n\n- Ignore access of .setter attribute which we patch onto QWebEngineProfile.\n  Would be nice to have a subclass or wrapper-class instead.\n\n==== qutebrowser/browser/webengine/webenginetab.py\n\n- Specified the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Remove some now-unneeded type ignores for creating FindFlags.\n- Specify more concrete types for WebEngineTab members where we actually need to\n  access WebEngine-specific attributes.\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webengine/webview.py\n\n- Make sure the page we get is our custom WebEnginePage subclass, not just any\n  QWebEnginePage. This is needed because we access custom attributes on it.\n\n==== qutebrowser/browser/webkit/network/networkreply.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/browser/webkit/webkitinspector.py\n\n- See changes to inspector.py and next commit.\n\n==== qutebrowser/browser/webkit/webkittab.py\n\n- Specify the type of _widget members more closely than just QWidget.\n  See browsertab.py changes for details.\n- Add a type ignore for WebKitAction because our workaround needs to\n  treat them as ints (which is allowed by PyQt, even if not type-safe).\n- Add new ignores for findText calls: The text is a QString and can be None; the\n  flags are valid despite mypy thinking they aren't (stubs regression?).\n- Specify the type for WebKitHistoryPrivate._history, because we access\n  WebKit-specific attributes. See above (_widget) re this being debatable.\n- Make mypy aware that .currentFrame() and .frameAt() can return None (stubs\n  regression?).\n- Make sure the .page() and .page().networkAccessManager() are our subclasses\n  rather than the more generic QtWebKit objects, as we use custom attributes.\n- Add new type ignores for signals (stubs regression!)\n\n==== qutebrowser/browser/webkit/webpage.py\n\n- Make sure the .networkAccessManager() is our subclass rather than the more\n  generic QtWebKit object, as we use custom attributes.\n- Replace a cast by a type ignore. The cast didn't work anymore.\n\n==== qutebrowser/browser/webkit/webview.py\n\n- Make sure the .page() is our subclass rather than the more generic QtWebKit\n  object, as we use custom attributes.\n\n==== qutebrowser/commands/userscripts.py\n\n- Remove now unneeded type ignore for signal.\n\n==== qutebrowser/completion/completer.py\n\n- Add a new _completion() getter (which ensures it actually gets the completion\n  view) rather than accessing the .parent() directly (which could be any QObject).\n\n==== qutebrowser/completion/completiondelegate.py\n\n- Make sure self.parent() is a CompletionView (no helper method as there is only\n  one instance).\n- Remove a now-unneeded type ignore for adding QSizes.\n\n==== qutebrowser/completion/completionwidget.py\n\n- Add a ._model() getter which ensures that we get a CompletionModel (with\n  custom attributes) rather than Qt's .model() which can be any QAbstractItemModel\n  (or None).\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/completion/models/completionmodel.py\n\n- Remove now unneeded type ignores for signals.\n- Ignore a complaint about .set_pattern() not being defined. Completion\n  categories don't share any common parent class, so it would be good to introduce\n  a typing.Protocol for this. See #7098.\n\n==== qutebrowser/components/misccommands.py\n\n- Removed a now-unneeded type ignore for OR-ing flags.\n\n==== qutebrowser/components/readlinecommands.py\n\n- Make sure QApplication.instance() is a QApplication (and not just a\n  QCoreApplication). This includes the former \"not None\" check.\n\n==== qutebrowser/components/scrollcommands.py\n\n- Add basic annotation for \"funcs\" dict. Could have a callable protocol to\n  specify it needs a count kwarg, see #7098.\n\n==== qutebrowser/config/stylesheet.py\n\n- Correctly specify that stylesheet apply to QWidgets, not any QObject.\n- Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy\n  about this with overloads and protocols (stylesheet for set_register being None\n  => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not\n  worth the troble. See #7098.\n\n==== qutebrowser/keyinput/keyutils.py\n\n- Remove some now-unneeded type ignores and add a cast for using a single enum\n  value as flags. Might need to look at this again with Qt 6 support.\n\n==== qutebrowser/keyinput/modeman.py\n\n- Add a FIXME for using a TypedDict, see comments for hints.py above.\n\n==== qutebrowser/mainwindow/mainwindow.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n- Improve where we cast from WindowType to WindowFlags, no int needed\n- Use new .tab_bar() getter, see below.\n\n==== qutebrowser/mainwindow/prompt.py\n\n- Remove now-unneeded type ignores for calling with OR-ed flags.\n\n==== qutebrowser/mainwindow/statusbar/bar.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/statusbar/command.py\n\n- Fix type for setText() override (from QLineEdit): text can be None\n  (QString in C++).\n\n==== qutebrowser/mainwindow/statusbar/url.py\n\n- Adjust type ignores around @pyqtProperty. The fact one is still needed seems\n  like a stub regression.\n\n==== qutebrowser/mainwindow/tabbedbrowser.py\n\n- Specify that TabDeque manages browser tabs, not any QWidgets. It accesses\n  AbstractTab-specific attributes.\n- Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access\n  .maybe_hide.\n- Fix the annotations for stored marks: Scroll positions are a QPoint, not int.\n- Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and\n  .widget(), which ensures that the return values are valid AbstractTabs (or None\n  for _tab_by_idx). This is needed because we access AbstractTab-specific\n  attributes.\n- For some places, where the tab can be None, continue using .currentTab() but\n  add asserts.\n- Remove some now-unneeded [unreachable] ignores, as mypy knows about the None\n  possibility now.\n\n==== qutebrowser/mainwindow/tabwidget.py\n\n- Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and\n  .widget() are of type TabBar and AbstractTab, respectively.\n- Add additional assertions where we expect ._tab_by_idx() to never be None.\n- Remove dead code in get_tab_fields for handling a None y scroll position. I\n  was unable to find any place in the code where this could be set to None.\n- Remove some now-unneeded type ignores and casts, as mypy now knows that\n  _type_by_idx() could be None.\n- Work around a strange instance where mypy complains about not being able to\n  find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility,\n  despite it clearly being shown as a bool *inside* that class without any\n  annotation.\n- Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in\n  fact a TabWidget.\n\n==== qutebrowser/misc/crashsignal.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/editor.py\n\n- Remove now unneeded type ignores for signals.\n\n==== qutebrowser/misc/ipc.py\n\n- Remove now unneeded type ignores for signals.\n- Add new type ignores for .error() which is both a signal and a getter\n  (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was\n  renamed to errorOccurred in 5.15.\n\n==== qutebrowser/misc/objects.py\n\n- Make sure mypy knows that objects.app is our custom Application (with custom\n  attributes) rather than any QApplication.\n\n==== qutebrowser/utils/objreg.py\n\n- Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol,\n  but ideally, the whole objreg stuff should die one day anyways.\n\n==== tests/unit/completion/test_completer.py\n\n- Make CompletionWidgetStub inherit from CompletionView so that it passes the\n  new isinstance() asserts in completer.py (see above).",
        "code": "def completion_item_yank(self, sel=False):\n        \n        text = self._cmd.selectedText()\n        if not text:\n            index = self.currentIndex()\n            if not index.isValid():\n                raise cmdutils.CommandError(\"No item selected!\")\n            text = self._model().data(index)\n\n        if not utils.supports_selection():\n            sel = False\n\n        utils.set_clipboard(text, selection=sel)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 124,
        "n_words": 30,
        "vocab_size": 22,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 78,
        "n_ast_nodes": 133,
        "n_identifiers": 17,
        "d_id": 117342,
        "documentation": {
            "docstring": "Yank the current completion item into the clipboard.\n\n        Args:\n            sel: Use the primary selection instead of the clipboard.\n        ",
            "n_words": 18,
            "vocab_size": 14,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 153345,
        "commit_id": "e7cb2e82f8b9c7a68f82abdd3b6011d661230b7e",
        "repo": "modin",
        "path": "modin/core/execution/ray/implementations/pandas_on_ray/partitioning/partition.py",
        "file_name": "partition.py",
        "fun_name": "get_index_and_columns",
        "commit_message": "REFACTOR-#4251: define public interfaces in `modin.core.execution.ray` module (#3868)\n\nSigned-off-by: Anatoly Myachev <anatoly.myachev@intel.com>",
        "code": "def _get_index_and_columns(df):\n    \n    return len(df.index), len(df.columns)\n\n\n@ray.remote(num_returns=4)",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "@ray.remote(num_returns=4)",
        "n_ast_errors": 1,
        "ast_levels": 9,
        "n_whitespaces": 11,
        "n_words": 6,
        "vocab_size": 6,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 20,
        "n_ast_nodes": 50,
        "n_identifiers": 8,
        "d_id": 35381,
        "documentation": {
            "docstring": "\n    Get the number of rows and columns of a pandas DataFrame.\n\n    Parameters\n    ----------\n    df : pandas.DataFrame\n        A pandas DataFrame which dimensions are needed.\n\n    Returns\n    -------\n    int\n        The number of rows.\n    int\n        The number of columns.\n    ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 203144,
        "commit_id": "efb4478e484ae61c5fc23563d4e9df1f8f49df49",
        "repo": "django",
        "path": "tests/messages_tests/test_cookie.py",
        "file_name": "test_cookie.py",
        "fun_name": "test_extra_tags",
        "commit_message": "Fixed #33458 -- Fixed encoding of messages with empty string as extra_tags.",
        "code": "def test_extra_tags(self):\n        \n        for extra_tags in ['', None, 'some tags']:\n            with self.subTest(extra_tags=extra_tags):\n                self.assertEqual(\n                    self.encode_decode('message', extra_tags=extra_tags).extra_tags,\n                    extra_tags,\n                )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 109,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 47,
        "n_ast_nodes": 80,
        "n_identifiers": 6,
        "d_id": 50236,
        "documentation": {
            "docstring": "\n        A message's extra_tags attribute is correctly preserved when retrieved\n        from the message storage.\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 35,
            "language": "en"
        }
    },
    {
        "id": 322771,
        "commit_id": "1d930169e118c325c03343b6acd7d9c05eab1f85",
        "repo": "PaddleNLP",
        "path": "examples/language_model/data_tools/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "compile_helper",
        "commit_message": "[Pre-training]  Optional for nsp task, support multi-datasets in ERNIE-1.0 pre-training (#1621)\n\n* add no nsp training.\r\n\r\n* support for multi-dataset\r\n\r\n* fix test sample nums.",
        "code": "def compile_helper():\n    \n    import os\n    import subprocess\n    path = os.path.abspath(os.path.dirname(__file__))\n    ret = subprocess.run(['make', '-C', path])\n    if ret.returncode != 0:\n        print(\"Making C++ dataset helpers module failed, exiting.\")\n        import sys\n        sys.exit(1)\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 67,
        "n_words": 28,
        "vocab_size": 25,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 59,
        "n_ast_nodes": 105,
        "n_identifiers": 13,
        "d_id": 118235,
        "documentation": {
            "docstring": "Compile helper function ar runtime. Make sure this\n    is invoked on a single process.",
            "n_words": 14,
            "vocab_size": 14,
            "n_whitespaces": 16,
            "language": "en"
        }
    },
    {
        "id": 269521,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/backend.py",
        "file_name": "backend.py",
        "fun_name": "variable",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def variable(value, dtype=None, name=None, constraint=None):\n    \n    if dtype is None:\n        dtype = floatx()\n    if hasattr(value, \"tocoo\"):\n        sparse_coo = value.tocoo()\n        indices = np.concatenate(\n            (\n                np.expand_dims(sparse_coo.row, 1),\n                np.expand_dims(sparse_coo.col, 1),\n            ),\n            1,\n        )\n        v = tf.SparseTensor(\n            indices=indices,\n            values=sparse_coo.data,\n            dense_shape=sparse_coo.shape,\n        )\n        v._keras_shape = sparse_coo.shape\n        return v\n    v = tf.Variable(\n        value, dtype=tf.as_dtype(dtype), name=name, constraint=constraint\n    )\n    if isinstance(value, np.ndarray):\n        v._keras_shape = value.shape\n    elif hasattr(value, \"shape\"):\n        v._keras_shape = int_shape(value)\n    track_variable(v)\n    return v\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 264,
        "n_words": 64,
        "vocab_size": 44,
        "complexity": 5,
        "nloc": 28,
        "token_counts": 173,
        "n_ast_nodes": 265,
        "n_identifiers": 29,
        "d_id": 80150,
        "documentation": {
            "docstring": "Instantiates a variable and returns it.\n\n    Args:\n        value: Numpy array, initial value of the tensor.\n        dtype: Tensor type.\n        name: Optional name string for the tensor.\n        constraint: Optional projection function to be\n            applied to the variable after an optimizer update.\n\n    Returns:\n        A variable instance (with Keras metadata included).\n\n    Examples:\n\n    >>> val = np.array([[1, 2], [3, 4]])\n    >>> kvar = tf.keras.backend.variable(value=val, dtype='float64',\n    ...                                  name='example_var')\n    >>> tf.keras.backend.dtype(kvar)\n    'float64'\n    >>> print(kvar)\n    <tf.Variable 'example_var:...' shape=(2, 2) dtype=float64, numpy=\n      array([[1., 2.],\n             [3., 4.]])>\n\n    ",
            "n_words": 77,
            "vocab_size": 66,
            "n_whitespaces": 206,
            "language": "en"
        }
    },
    {
        "id": 191569,
        "commit_id": "a408ed3ea39dfa47e8b522a9e153b259f25df54e",
        "repo": "langchain",
        "path": "tests/unit_tests/chains/test_conversation.py",
        "file_name": "test_conversation.py",
        "fun_name": "test_conversation_chain_errors_bad_variable",
        "commit_message": "Samantha/add conversation chain (#166)\n\nAdd MemoryChain and ConversationChain as chains that take a docstore in\r\naddition to the prompt, and use the docstore to stuff context into the\r\nprompt. This can be used to have an ongoing conversation with a chatbot.\r\n\r\nProbably needs a bit of refactoring for code quality\r\n\r\nCo-authored-by: Harrison Chase <hw.chase.17@gmail.com>",
        "code": "def test_conversation_chain_errors_bad_variable() -> None:\n    \n    llm = FakeLLM()\n    prompt = PromptTemplate(input_variables=[\"foo\"], template=\"{foo}\")\n    memory = ConversationBufferMemory(dynamic_key=\"foo\")\n    with pytest.raises(ValueError):\n        ConversationChain(llm=llm, prompt=prompt, memory=memory, input_key=\"foo\")\n\n\n@pytest.mark.parametrize(\n    \"memory\",\n    [\n        ConversationBufferMemory(dynamic_key=\"baz\"),\n        ConversationSummaryMemory(llm=FakeLLM(), dynamic_key=\"baz\"),\n    ],\n)",
        "url": "https://github.com/hwchase17/langchain.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\n    \"memory\",\n    [\n        ConversationBufferMemory(dynamic_key=\"baz\"),\n        ConversationSummaryMemory(llm=FakeLLM(), dynamic_key=\"baz\"),\n    ],\n)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 28,
        "vocab_size": 26,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 60,
        "n_ast_nodes": 161,
        "n_identifiers": 18,
        "d_id": 46692,
        "documentation": {
            "docstring": "Test that conversation chain works in basic setting.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 56177,
        "commit_id": "1c74cd08aaa8eb7759490fc156abb18f916b0764",
        "repo": "prefect",
        "path": "src/prefect/blocks/core.py",
        "file_name": "core.py",
        "fun_name": "register",
        "commit_message": "Renames method from install to register",
        "code": "async def register(cls):\n        \n        for field in cls.__fields__.values():\n            if Block.is_block_class(field.type_):\n                await field.type_.register()\n            if get_origin(field.type_) is Union:\n                for type in get_args(field.type_):\n                    if Block.is_block_class(type):\n                        await type.register()\n",
        "url": "https://github.com/PrefectHQ/prefect.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 131,
        "n_words": 23,
        "vocab_size": 18,
        "complexity": 8,
        "nloc": 27,
        "token_counts": 178,
        "n_ast_nodes": 116,
        "n_identifiers": 12,
        "d_id": 11452,
        "documentation": {
            "docstring": "\n        Makes block available for configuration with current Orion server.\n        Recursively registers all nested blocks. Registration is idempotent.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 82077,
        "commit_id": "871175f97fb177ad3c6d6f150e2b685dc11893ce",
        "repo": "awx",
        "path": "awx/main/models/credential/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "get_input",
        "commit_message": "Sending field_name in AttributeError",
        "code": "def get_input(self, field_name, **kwargs):\n        \n        if self.credential_type.kind != 'external' and field_name in self.dynamic_input_fields:\n            return self._get_dynamic_input(field_name)\n        if field_name in self.credential_type.secret_fields:\n            try:\n                return decrypt_field(self, field_name)\n            except AttributeError:\n                for field in self.credential_type.inputs.get('fields', []):\n                    if field['id'] == field_name and 'default' in field:\n                        return field['default']\n                if 'default' in kwargs:\n                    return kwargs['default']\n                raise AttributeError(field_name)\n        if field_name in self.inputs:\n            return self.inputs[field_name]\n        if 'default' in kwargs:\n            return kwargs['default']\n        for field in self.credential_type.inputs.get('fields', []):\n            if field['id'] == field_name and 'default' in field:\n                return field['default']\n        raise AttributeError(field_name)\n",
        "url": "https://github.com/ansible/awx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 327,
        "n_words": 76,
        "vocab_size": 35,
        "complexity": 14,
        "nloc": 21,
        "token_counts": 166,
        "n_ast_nodes": 279,
        "n_identifiers": 14,
        "d_id": 17314,
        "documentation": {
            "docstring": "\n        Get an injectable and decrypted value for an input field.\n\n        Retrieves the value for a given credential input field name. Return\n        values for secret input fields are decrypted. If the credential doesn't\n        have an input value defined for the given field name, an AttributeError\n        is raised unless a default value is provided.\n\n        :param field_name(str):        The name of the input field.\n        :param default(optional[str]): A default return value to use.\n        ",
            "n_words": 68,
            "vocab_size": 43,
            "n_whitespaces": 132,
            "language": "en"
        }
    },
    {
        "id": 183562,
        "commit_id": "d14659c1a3760eade2dd3479b66eb8b2e7711db0",
        "repo": "textual",
        "path": "src/textual/_terminal_features.py",
        "file_name": "_terminal_features.py",
        "fun_name": "synchronized_update_sequences",
        "commit_message": "[terminal buffering] Add support for the \"mode 2026\"\n\nThat task is definitely way more complicated that it seemed to be 😅",
        "code": "def synchronized_update_sequences(self) -> tuple[str, str]:\n        \n        return (\n            self._synchronized_update_start_sequence(),\n            self._synchronized_update_end_sequence(),\n        )\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 53,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 14,
        "token_counts": 28,
        "n_ast_nodes": 45,
        "n_identifiers": 6,
        "d_id": 44251,
        "documentation": {
            "docstring": "\n        Returns the ANSI sequence that we should send to the terminal to tell it that\n        it should buffer the content we're about to send, as well as the ANIS sequence to end the buffering.\n        If the terminal doesn't seem to support synchronised updates both strings will be empty.\n\n        Returns:\n            tuple[str, str]: the start and end ANSI sequences, respectively. They will both be empty strings\n                if the terminal emulator doesn't seem to support the \"synchronised updates\" mode.\n        ",
            "n_words": 76,
            "vocab_size": 47,
            "n_whitespaces": 138,
            "language": "en"
        }
    },
    {
        "id": 203240,
        "commit_id": "c5cd8783825b5f6384417dac5f3889b4210b7d08",
        "repo": "django",
        "path": "django/template/defaulttags.py",
        "file_name": "defaulttags.py",
        "fun_name": "do_for",
        "commit_message": "Refs #33476 -- Refactored problematic code before reformatting by Black.\n\nIn these cases Black produces unexpected results, e.g.\r\n\r\ndef make_random_password(\r\n    self,\r\n    length=10,\r\n    allowed_chars='abcdefghjkmnpqrstuvwxyz' 'ABCDEFGHJKLMNPQRSTUVWXYZ' '23456789',\r\n):\r\n\r\nor\r\n\r\ncursor.execute(\"\"\"\r\nSELECT ...\r\n\"\"\",\r\n    [table name],\r\n)",
        "code": "def do_for(parser, token):\n    \n    bits = token.split_contents()\n    if len(bits) < 4:\n        raise TemplateSyntaxError(\n            \"'for' statements should have at least four words: %s\" % token.contents\n        )\n\n    is_reversed = bits[-1] == 'reversed'\n    in_index = -3 if is_reversed else -2\n    if bits[in_index] != 'in':\n        raise TemplateSyntaxError(\"'for' statements should use the format\"\n                                  \" 'for x in y': %s\" % token.contents)\n\n    invalid_chars = frozenset((' ', '\"', \"'\", FILTER_SEPARATOR))\n    loopvars = re.split(r' *, *', ' '.join(bits[1:in_index]))\n    for var in loopvars:\n        if not var or not invalid_chars.isdisjoint(var):\n            raise TemplateSyntaxError(\n                \"'for' tag received an invalid argument: %s\" % token.contents\n            )\n\n    sequence = parser.compile_filter(bits[in_index + 1])\n    nodelist_loop = parser.parse(('empty', 'endfor',))\n    token = parser.next_token()\n    if token.contents == 'empty':\n        nodelist_empty = parser.parse(('endfor',))\n        parser.delete_first_token()\n    else:\n        nodelist_empty = None\n    return ForNode(loopvars, sequence, is_reversed, nodelist_loop, nodelist_empty)\n\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 296,
        "n_words": 121,
        "vocab_size": 89,
        "complexity": 8,
        "nloc": 27,
        "token_counts": 203,
        "n_ast_nodes": 343,
        "n_identifiers": 27,
        "d_id": 50268,
        "documentation": {
            "docstring": "\n    Loop over each item in an array.\n\n    For example, to display a list of athletes given ``athlete_list``::\n\n        <ul>\n        {% for athlete in athlete_list %}\n            <li>{{ athlete.name }}</li>\n        {% endfor %}\n        </ul>\n\n    You can loop over a list in reverse by using\n    ``{% for obj in list reversed %}``.\n\n    You can also unpack multiple values from a two-dimensional array::\n\n        {% for key,value in dict.items %}\n            {{ key }}: {{ value }}\n        {% endfor %}\n\n    The ``for`` tag can take an optional ``{% empty %}`` clause that will\n    be displayed if the given array is empty or could not be found::\n\n        <ul>\n          {% for athlete in athlete_list %}\n            <li>{{ athlete.name }}</li>\n          {% empty %}\n            <li>Sorry, no athletes in this list.</li>\n          {% endfor %}\n        <ul>\n\n    The above is equivalent to -- but shorter, cleaner, and possibly faster\n    than -- the following::\n\n        <ul>\n          {% if athlete_list %}\n            {% for athlete in athlete_list %}\n              <li>{{ athlete.name }}</li>\n            {% endfor %}\n          {% else %}\n            <li>Sorry, no athletes in this list.</li>\n          {% endif %}\n        </ul>\n\n    The for loop sets a number of variables available within the loop:\n\n        ==========================  ================================================\n        Variable                    Description\n        ==========================  ================================================\n        ``forloop.counter``         The current iteration of the loop (1-indexed)\n        ``forloop.counter0``        The current iteration of the loop (0-indexed)\n        ``forloop.revcounter``      The number of iterations from the end of the\n                                    loop (1-indexed)\n        ``forloop.revcounter0``     The number of iterations from the end of the\n                                    loop (0-indexed)\n        ``forloop.first``           True if this is the first time through the loop\n        ``forloop.last``            True if this is the last time through the loop\n        ``forloop.parentloop``      For nested loops, this is the loop \"above\" the\n                                    current one\n        ==========================  ================================================\n    ",
            "n_words": 262,
            "vocab_size": 121,
            "n_whitespaces": 764,
            "language": "en"
        }
    },
    {
        "id": 197624,
        "commit_id": "40a89803dbe877edc8ab6672819715f959273e60",
        "repo": "sympy",
        "path": "sympy/physics/units/quantities.py",
        "file_name": "quantities.py",
        "fun_name": "set_global_relative_scale_factor",
        "commit_message": "feat(physics.units): add `is_prefixed` property to `Quantity`",
        "code": "def set_global_relative_scale_factor(self, scale_factor, reference_quantity):\n        \n        from sympy.physics.units import UnitSystem\n        scale_factor = sympify(scale_factor)\n        if isinstance(scale_factor, Prefix):\n            self._is_prefixed = True\n        # replace all prefixes by their ratio to canonical units:\n        scale_factor = scale_factor.replace(\n            lambda x: isinstance(x, Prefix),\n            lambda x: x.scale_factor\n        )\n        scale_factor = sympify(scale_factor)\n        UnitSystem._quantity_scale_factors_global[self] = (scale_factor, reference_quantity)\n        UnitSystem._quantity_dimensional_equivalence_map_global[self] = reference_quantity\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 151,
        "n_words": 48,
        "vocab_size": 38,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 86,
        "n_ast_nodes": 133,
        "n_identifiers": 16,
        "d_id": 48646,
        "documentation": {
            "docstring": "\n        Setting a scale factor that is valid across all unit system.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 64811,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/budget/budget.py",
        "file_name": "budget.py",
        "fun_name": "validate_expense_against_budget",
        "commit_message": "style: format code with black",
        "code": "def validate_expense_against_budget(args):\n\targs = frappe._dict(args)\n\n\tif args.get(\"company\") and not args.fiscal_year:\n\t\targs.fiscal_year = get_fiscal_year(args.get(\"posting_date\"), company=args.get(\"company\"))[0]\n\t\tfrappe.flags.exception_approver_role = frappe.get_cached_value(\n\t\t\t\"Company\", args.get(\"company\"), \"exception_budget_approver_role\"\n\t\t)\n\n\tif not args.account:\n\t\targs.account = args.get(\"expense_account\")\n\n\tif not (args.get(\"account\") and args.get(\"cost_center\")) and args.item_code:\n\t\targs.cost_center, args.account = get_item_details(args)\n\n\tif not args.account:\n\t\treturn\n\n\tfor budget_against in [\"project\", \"cost_center\"] + get_accounting_dimensions():\n\t\tif (\n\t\t\targs.get(budget_against)\n\t\t\tand args.account\n\t\t\tand frappe.db.get_value(\"Account\", {\"name\": args.account, \"root_type\": \"Expense\"})\n\t\t):\n\n\t\t\tdoctype = frappe.unscrub(budget_against)\n\n\t\t\tif frappe.get_cached_value(\"DocType\", doctype, \"is_tree\"):\n\t\t\t\tlft, rgt = frappe.db.get_value(doctype, args.get(budget_against), [\"lft\", \"rgt\"])\n\t\t\t\tcondition =  % (\n\t\t\t\t\tdoctype,\n\t\t\t\t\tlft,\n\t\t\t\t\trgt,\n\t\t\t\t\tbudget_against,\n\t\t\t\t)  # nosec\n\t\t\t\targs.is_tree = True\n\t\t\telse:\n\t\t\t\tcondition = \"and b.%s=%s\" % (budget_against, frappe.db.escape(args.get(budget_against)))\n\t\t\t\targs.is_tree = False\n\n\t\t\targs.budget_against_field = budget_against\n\t\t\targs.budget_against_doctype = doctype\n\n\t\t\tbudget_records = frappe.db.sql(\n\t\t\t\t.format(\n\t\t\t\t\tcondition=condition, budget_against_field=budget_against\n\t\t\t\t),\n\t\t\t\t(args.fiscal_year, args.account),\n\t\t\t\tas_dict=True,\n\t\t\t)  # nosec\n\n\t\t\tif budget_records:\n\t\t\t\tvalidate_budget_records(args, budget_records)\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 83,
        "n_words": 123,
        "vocab_size": 82,
        "complexity": 14,
        "nloc": 59,
        "token_counts": 324,
        "n_ast_nodes": 538,
        "n_identifiers": 33,
        "d_id": 13727,
        "documentation": {
            "docstring": "and exists(select name from `tab%s`\n\t\t\t\t\twhere lft<=%s and rgt>=%s and name=b.%s)\n\t\t\t\tselect\n\t\t\t\t\tb.{budget_against_field} as budget_against, ba.budget_amount, b.monthly_distribution,\n\t\t\t\t\tifnull(b.applicable_on_material_request, 0) as for_material_request,\n\t\t\t\t\tifnull(applicable_on_purchase_order, 0) as for_purchase_order,\n\t\t\t\t\tifnull(applicable_on_booking_actual_expenses,0) as for_actual_expenses,\n\t\t\t\t\tb.action_if_annual_budget_exceeded, b.action_if_accumulated_monthly_budget_exceeded,\n\t\t\t\t\tb.action_if_annual_budget_exceeded_on_mr, b.action_if_accumulated_monthly_budget_exceeded_on_mr,\n\t\t\t\t\tb.action_if_annual_budget_exceeded_on_po, b.action_if_accumulated_monthly_budget_exceeded_on_po\n\t\t\t\tfrom\n\t\t\t\t\t`tabBudget` b, `tabBudget Account` ba\n\t\t\t\twhere\n\t\t\t\t\tb.name=ba.parent and b.fiscal_year=%s\n\t\t\t\t\tand ba.account=%s and b.docstatus=1\n\t\t\t\t\t{condition}\n\t\t\t",
            "n_words": 49,
            "vocab_size": 38,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 222984,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/msvccompiler.py",
        "file_name": "msvccompiler.py",
        "fun_name": "load_macros",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def load_macros(self, version):\n        vsbase = r\"Software\\Microsoft\\VisualStudio\\%0.1f\" % version\n        self.set_macro(\"VCInstallDir\", vsbase + r\"\\Setup\\VC\", \"productdir\")\n        self.set_macro(\"VSInstallDir\", vsbase + r\"\\Setup\\VS\", \"productdir\")\n        net = r\"Software\\Microsoft\\.NETFramework\"\n        self.set_macro(\"FrameworkDir\", net, \"installroot\")\n        try:\n            if version > 7.0:\n                self.set_macro(\"FrameworkSDKDir\", net, \"sdkinstallrootv1.1\")\n            else:\n                self.set_macro(\"FrameworkSDKDir\", net, \"sdkinstallroot\")\n        except KeyError as exc: #\n            raise DistutilsPlatformError(\n            )\n\n        p = r\"Software\\Microsoft\\NET Framework Setup\\Product\"\n        for base in HKEYS:\n            try:\n                h = RegOpenKeyEx(base, p)\n            except RegError:\n                continue\n            key = RegEnumKey(h, 0)\n            d = read_values(base, r\"%s\\%s\" % (p, key))\n            self.macros[\"$(FrameworkVersion)\"] = d[\"version\"]\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 296,
        "n_words": 75,
        "vocab_size": 58,
        "complexity": 5,
        "nloc": 26,
        "token_counts": 151,
        "n_ast_nodes": 255,
        "n_identifiers": 20,
        "d_id": 56835,
        "documentation": {
            "docstring": "Python was built with Visual Studio 2003;\nextensions must be built with a compiler than can generate compatible binaries.\nVisual Studio 2003 was not found on this system. If you have Cygwin installed,\nyou can try compiling with MingW32, by passing \"-c mingw32\" to setup.py.",
            "n_words": 45,
            "vocab_size": 37,
            "n_whitespaces": 41,
            "language": "en"
        }
    },
    {
        "id": 217516,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/genericpath.py",
        "file_name": "genericpath.py",
        "fun_name": "samestat",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def samestat(s1, s2):\n    \n    return (s1.st_ino == s2.st_ino and\n            s1.st_dev == s2.st_dev)\n\n\n# Are two filenames really pointing to the same file?",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 37,
        "n_words": 21,
        "vocab_size": 20,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 26,
        "n_ast_nodes": 43,
        "n_identifiers": 5,
        "d_id": 54829,
        "documentation": {
            "docstring": "Test whether two stat buffers reference the same file",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 126078,
        "commit_id": "e5a8b1dd55817305ac85237cd99d8b6ed23df294",
        "repo": "ray",
        "path": "python/ray/serve/batching.py",
        "file_name": "batching.py",
        "fun_name": "batch",
        "commit_message": "[Serve] Add API Annotations And Move to _private (#27058)",
        "code": "def batch(_func=None, max_batch_size=10, batch_wait_timeout_s=0.0):\n    \n    # `_func` will be None in the case when the decorator is parametrized.\n    # See the comment at the end of this function for a detailed explanation.\n    if _func is not None:\n        if not callable(_func):\n            raise TypeError(\n                \"@serve.batch can only be used to decorate functions or methods.\"\n            )\n\n        if not iscoroutinefunction(_func):\n            raise TypeError(\"Functions decorated with @serve.batch must be 'async def'\")\n\n    if not isinstance(max_batch_size, int):\n        if isinstance(max_batch_size, float) and max_batch_size.is_integer():\n            max_batch_size = int(max_batch_size)\n        else:\n            raise TypeError(\"max_batch_size must be integer >= 1\")\n\n    if max_batch_size < 1:\n        raise ValueError(\"max_batch_size must be an integer >= 1\")\n\n    if not isinstance(batch_wait_timeout_s, (float, int)):\n        raise TypeError(\"batch_wait_timeout_s must be a float >= 0\")\n\n    if batch_wait_timeout_s < 0:\n        raise ValueError(\"batch_wait_timeout_s must be a float >= 0\")\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 264,
        "n_words": 121,
        "vocab_size": 78,
        "complexity": 11,
        "nloc": 21,
        "token_counts": 136,
        "n_ast_nodes": 206,
        "n_identifiers": 12,
        "d_id": 28055,
        "documentation": {
            "docstring": "Converts a function to asynchronously handle batches.\n\n    The function can be a standalone function or a class method. In both\n    cases, the function must be `async def` and take a list of objects as\n    its sole argument and return a list of the same length as a result.\n\n    When invoked, the caller passes a single object. These will be batched\n    and executed asynchronously once there is a batch of `max_batch_size`\n    or `batch_wait_timeout_s` has elapsed, whichever occurs first.\n\n    Example:\n    >>> from ray import serve\n    >>> @serve.batch(max_batch_size=50, batch_wait_timeout_s=0.5) # doctest: +SKIP\n    ... async def handle_batch(batch: List[str]): # doctest: +SKIP\n    ...     return [s.lower() for s in batch] # doctest: +SKIP\n\n    >>> async def handle_single(s: str): # doctest: +SKIP\n    ...     # Returns s.lower().\n    ...     return await handle_batch(s) # doctest: +SKIP\n\n    Arguments:\n        max_batch_size: the maximum batch size that will be executed in\n            one call to the underlying function.\n        batch_wait_timeout_s: the maximum duration to wait for\n            `max_batch_size` elements before running the underlying function.\n    ",
            "n_words": 157,
            "vocab_size": 97,
            "n_whitespaces": 253,
            "language": "en"
        }
    },
    {
        "id": 322284,
        "commit_id": "15f0aa8f4515ae6cf2ee3ef71f90d533bc9e61b2",
        "repo": "PaddleNLP",
        "path": "examples/biomedical/cblue/sequence_classification/utils.py",
        "file_name": "utils.py",
        "fun_name": "convert_example",
        "commit_message": "[ehealth] add sequence classification example",
        "code": "def convert_example(example, tokenizer, max_seq_length=512, is_test=False):\n    \n    text_a = example['text_a']\n    text_b = example.get('text_b', None)\n\n    text_a = _tokenize_special_chars(_normalize(text_a))\n    if text_b is not None:\n        text_b = _tokenize_special_chars(_normalize(text_b))\n\n    encoded_inputs = tokenizer(\n        text=text_a,\n        text_pair=text_b,\n        max_seq_len=max_seq_length,\n        return_position_ids=True)\n    input_ids = encoded_inputs['input_ids']\n    token_type_ids = encoded_inputs['token_type_ids']\n    position_ids = encoded_inputs['position_ids']\n\n    if is_test:\n        return input_ids, token_type_ids, position_ids\n    label = np.array([example['label']], dtype='int64')\n    return input_ids, token_type_ids, position_ids, label\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 132,
        "n_words": 54,
        "vocab_size": 37,
        "complexity": 3,
        "nloc": 18,
        "token_counts": 128,
        "n_ast_nodes": 205,
        "n_identifiers": 22,
        "d_id": 118112,
        "documentation": {
            "docstring": "\n    Builds model inputs from a sequence or a pair of sequences for sequence\n    classification tasks by concatenating and adding special tokens. And\n    creates a mask from the two sequences for sequence-pair classification\n    tasks.\n\n    The convention in Electra/EHealth is:\n\n    - single sequence:\n        input_ids:      ``[CLS] X [SEP]``\n        token_type_ids: ``  0   0   0``\n        position_ids:   ``  0   1   2``\n\n    - a senquence pair:\n        input_ids:      ``[CLS] X [SEP] Y [SEP]``\n        token_type_ids: ``  0   0   0   1   1``\n        position_ids:   ``  0   1   2   3   4``\n\n    Args:\n        example (obj:`dict`):\n            A dictionary of input data, containing text and label if it has.\n        tokenizer (obj:`PretrainedTokenizer`):\n            A tokenizer inherits from :class:`paddlenlp.transformers.PretrainedTokenizer`.\n            Users can refer to the superclass for more information.\n        max_seq_length (obj:`int`):\n            The maximum total input sequence length after tokenization.\n            Sequences longer will be truncated, and the shorter will be padded.\n        is_test (obj:`bool`, default to `False`):\n            Whether the example contains label or not.\n\n    Returns:\n        input_ids (obj:`list[int]`):\n            The list of token ids.\n        token_type_ids (obj:`list[int]`):\n            List of sequence pair mask.\n        position_ids (obj:`list[int]`):\n            List of position ids.\n        label(obj:`numpy.array`, data type of int64, optional):\n            The input label if not is_test.\n    ",
            "n_words": 176,
            "vocab_size": 116,
            "n_whitespaces": 457,
            "language": "en"
        }
    },
    {
        "id": 149135,
        "commit_id": "6024fa482e1b09bae8e85b3afc9fc58e483c1512",
        "repo": "freqtrade",
        "path": "freqtrade/edge/edge_positioning.py",
        "file_name": "edge_positioning.py",
        "fun_name": "accepted_pairs",
        "commit_message": "Use brackets to break IF lines",
        "code": "def accepted_pairs(self) -> List[Dict[str, Any]]:\n        \n        final = []\n        for pair, info in self._cached_pairs.items():\n            if (info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and\n                    info.winrate > float(self.edge_config.get('minimum_winrate', 0.60))):\n                final.append({\n                    'Pair': pair,\n                    'Winrate': info.winrate,\n                    'Expectancy': info.expectancy,\n                    'Stoploss': info.stoploss,\n                })\n        return final\n",
        "url": "https://github.com/freqtrade/freqtrade.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 199,
        "n_words": 35,
        "vocab_size": 32,
        "complexity": 4,
        "nloc": 15,
        "token_counts": 107,
        "n_ast_nodes": 168,
        "n_identifiers": 18,
        "d_id": 34375,
        "documentation": {
            "docstring": "\n        return a list of accepted pairs along with their winrate, expectancy and stoploss\n        ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 61416,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "get_remote_url",
        "commit_message": "upd; format",
        "code": "def get_remote_url(cls, location):\n        # type: (str) -> str\n        \n        raise NotImplementedError\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 31,
        "n_words": 10,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 10,
        "n_ast_nodes": 19,
        "n_identifiers": 4,
        "d_id": 12560,
        "documentation": {
            "docstring": "\n        Return the url used at location\n\n        Raises RemoteNotFoundError if the repository does not have a remote\n        url configured.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 47,
            "language": "en"
        }
    },
    {
        "id": 114473,
        "commit_id": "01b47406a29d17781356badb20f49f2fdc24d00e",
        "repo": "mindsdb",
        "path": "mindsdb/api/mysql/mysql_proxy/mysql_proxy.py",
        "file_name": "mysql_proxy.py",
        "fun_name": "answer_drop_tables",
        "commit_message": "'drop table' query",
        "code": "def answer_drop_tables(self, statement):\n        \n        if statement.if_exists is False:\n            for table in statement.tables:\n                if len(table.parts) > 1:\n                    db_name = table.parts[0]\n                else:\n                    db_name = self.session.database\n                if db_name not in ['files', 'mindsdb']:\n                    raise SqlApiException(f\"Cannot delete a table from database '{db_name}'\")\n                table_name = table.parts[-1]\n                dn = self.session.datahub[db_name]\n                if dn.has_table(table_name) is False:\n                    raise SqlApiException(f\"Cannot delete a table from database '{db_name}': table does not exists\")\n\n        for table in statement.tables:\n            if len(table.parts) > 1:\n                db_name = table.parts[0]\n            else:\n                db_name = self.session.database\n            if db_name not in ['files', 'mindsdb']:\n                raise SqlApiException(f\"Cannot delete a table from database '{db_name}'\")\n            table_name = table.parts[-1]\n            dn = self.session.datahub[db_name]\n            if dn.has_table(table_name):\n                if db_name == 'mindsdb':\n                    self.session.datahub['mindsdb'].delete_predictor(table_name)\n                elif db_name == 'files':\n                    self.session.data_store.delete_file(table_name)\n        return SQLAnswer(ANSWER_TYPE.OK)\n",
        "url": "https://github.com/mindsdb/mindsdb.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 491,
        "n_words": 107,
        "vocab_size": 46,
        "complexity": 12,
        "nloc": 28,
        "token_counts": 217,
        "n_ast_nodes": 366,
        "n_identifiers": 22,
        "d_id": 25199,
        "documentation": {
            "docstring": " answer on 'drop table [if exists] {name}'\n            Args:\n                statement: ast\n        ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 44,
            "language": "en"
        }
    },
    {
        "id": 133353,
        "commit_id": "7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065",
        "repo": "ray",
        "path": "python/ray/util/sgd/torch/torch_trainer.py",
        "file_name": "torch_trainer.py",
        "fun_name": "validate",
        "commit_message": "[CI] Format Python code with Black (#21975)\n\nSee #21316 and #21311 for the motivation behind these changes.",
        "code": "def validate(self, num_steps=None, profile=False, reduce_results=True, info=None):\n        \n        worker_stats = self.worker_group.validate(\n            num_steps=num_steps, profile=profile, info=info\n        )\n\n        if reduce_results:\n            return self._process_stats(worker_stats)\n        else:\n            return worker_stats\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 88,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 8,
        "token_counts": 56,
        "n_ast_nodes": 85,
        "n_identifiers": 9,
        "d_id": 29985,
        "documentation": {
            "docstring": "Evaluates the model on the validation data set.\n\n        Args:\n            num_steps (int): Number of batches to compute update steps on\n                per worker. This corresponds also to the number of times\n                ``TrainingOperator.validate_batch`` is called per worker.\n            profile (bool): Returns time stats for the evaluation procedure.\n            reduce_results (bool): Whether to average all metrics across\n                all workers into one dict. If a metric is a non-numerical\n                value (or nested dictionaries), one value will be randomly\n                selected among the workers. If False, returns a list of dicts.\n            info (dict): Optional dictionary passed to the training\n                operator for `validate` and `validate_batch`.\n\n        Returns:\n            A dictionary of metrics for validation.\n                You can provide custom metrics by passing in a custom\n                ``training_operator_cls``.\n        ",
            "n_words": 113,
            "vocab_size": 84,
            "n_whitespaces": 309,
            "language": "en"
        }
    },
    {
        "id": 60284,
        "commit_id": "cc4d0564756ca067516f71718a3d135996525909",
        "repo": "transferlearning",
        "path": "code/deep/BJMMD/caffe/python/caffe/pycaffe.py",
        "file_name": "pycaffe.py",
        "fun_name": "_Net_set_input_arrays",
        "commit_message": "Balanced joint maximum mean discrepancy for deep transfer learning",
        "code": "def _Net_set_input_arrays(self, data, labels):\n    \n    if labels.ndim == 1:\n        labels = np.ascontiguousarray(labels[:, np.newaxis, np.newaxis,\n                                             np.newaxis])\n    return self._set_input_arrays(data, labels)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 77,
        "n_words": 17,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 49,
        "n_ast_nodes": 74,
        "n_identifiers": 9,
        "d_id": 12064,
        "documentation": {
            "docstring": "\n    Set input arrays of the in-memory MemoryDataLayer.\n    (Note: this is only for networks declared with the memory data layer.)\n    ",
            "n_words": 19,
            "vocab_size": 18,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 138087,
        "commit_id": "1510fb2cd631b2776092fb45ee4082e5e65f16f8",
        "repo": "ray",
        "path": "python/ray/tune/tests/test_actor_reuse.py",
        "file_name": "test_actor_reuse.py",
        "fun_name": "test_multi_trial_reuse",
        "commit_message": "[air/tune] Internal resource management 2 - Ray Tune to use new Ray AIR resource manager (#30016)\n\nIncludes/depends on #30777\r\n\r\nTLDR: This PR refactors Ray Tune's resource management to use a central AIR resource management package instead of the tightly coupled PlacementGroupManager.\r\n\r\nRay Tune's resource management currently uses a tightly coupled placement group manager. This leads to a number of shortcomings:\r\n- The tight coupling on the manager side (e.g. PG manager keeps track of trials) prevents re-usability\r\n- The tight coupling on the trial executor side prevents using different resource management strategies (e.g. shared or budget-based)\r\n- It's hard to test independently. Tests for the resource management require a simulated tune setup.\r\n\r\nTo improve stability, extensibility, and maintainability, this PR moves the resource management logic into a central `ray.air.execution.resources` subpackage. The resource management has a simple API that works with `ResourceRequest`s and `AllocatedResources` to manage requested and assigned resources, respectively. The actual resource management can then be anything - per default it is a placement group based manager, but this PR also introduces a PoC budget-based manager that can be plugged in.\r\n\r\nThe PR does not substantially change existing tests, so we can be certain that the new resource model is a fully compatible replacement for the old placement group manager.\r\n\r\nSigned-off-by: Kai Fricke <kai@anyscale.com>",
        "code": "def test_multi_trial_reuse(ray_start_4_cpus_extra):\n    \n    os.environ[\"TUNE_MAX_PENDING_TRIALS_PG\"] = \"2\"\n\n    register_trainable(\"foo2\", MyResettableClass)\n\n    # We sleep here for one second so that the third actor\n    # does not finish training before the fourth can be scheduled.\n    # This helps ensure that both remote runners are re-used and\n    # not just one.\n    [trial1, trial2, trial3, trial4] = tune.run(\n        \"foo2\",\n        config={\n            \"message\": tune.grid_search([\"First\", \"Second\", \"Third\", \"Fourth\"]),\n            \"id\": -1,\n            \"sleep\": 2,\n        },\n        reuse_actors=True,\n        resources_per_trial={\"cpu\": 2},\n    ).trials\n\n    assert trial3.last_result[\"num_resets\"] == 1\n    assert trial4.last_result[\"num_resets\"] == 1\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 176,
        "n_words": 75,
        "vocab_size": 65,
        "complexity": 1,
        "nloc": 15,
        "token_counts": 100,
        "n_ast_nodes": 175,
        "n_identifiers": 18,
        "d_id": 31311,
        "documentation": {
            "docstring": "Test that actors from multiple trials running in parallel will be reused.\n\n    - 2 trials can run at the same time\n    - Trial 3 will be scheduled after trial 1 succeeded, so will reuse actor\n    - Trial 4 will be scheduled after trial 2 succeeded, so will reuse actor\n    ",
            "n_words": 49,
            "vocab_size": 31,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 89350,
        "commit_id": "6fc6106b6a57149a5bae3c0f4677349cfbae1155",
        "repo": "sentry",
        "path": "tests/sentry/api/endpoints/test_project_details.py",
        "file_name": "test_project_details.py",
        "fun_name": "test_get_dynamic_sampling_default_biases",
        "commit_message": "fix(dyn-sampling): Backend code clean up (#42001)\n\nWe are consolidating server-side-sampling and dynamic-sampling flags\r\ninto only dynamic-sampling. The flag is being controlled by plan",
        "code": "def test_get_dynamic_sampling_default_biases(self):\n        \n        with Feature(\n            {\n                self.new_ds_flag: True,\n            }\n        ):\n            response = self.get_success_response(\n                self.organization.slug, self.project.slug, method=\"get\"\n            )\n            assert response.data[\"dynamicSamplingBiases\"] == DEFAULT_BIASES\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 126,
        "n_words": 20,
        "vocab_size": 20,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 50,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 18532,
        "documentation": {
            "docstring": "\n        Tests the case when organization on AM2 plan, but haven't manipulated the bias toggles\n        yet, so they get the default biases.\n        ",
            "n_words": 21,
            "vocab_size": 19,
            "n_whitespaces": 43,
            "language": "en"
        }
    },
    {
        "id": 194460,
        "commit_id": "1830123ba3edf7290b7c6cb1c6f406ccf1d0e5d4",
        "repo": "kivy",
        "path": "kivy/uix/widget.py",
        "file_name": "widget.py",
        "fun_name": "remove_widget",
        "commit_message": "Feature: EventManagerBase (#7658)\n\n* Added EventManagerBase class and event_managers attribute to WindowBase class.\r\n* Added on_motion event to Widget class.\r\n* Updated post_dispatch_input in EventLoopBase to skip non-touch events.\r\n* Using type ids in MouseMotionEventProvider.\r\n* Added on_motion method to Widget subclasses.\r\n* Updated Widget.on_motion method to dispatch to filtered widgets if 'pos' is not in me.profile.\r\n* Changed motion_filter property in Widget to store key to list values.\r\n* Updated Widget.on_motion to not dispatch event to children if widget is disabled.\r\n* Widget: Using flags to control dispatching in on_motion method.\r\n* Widget: Don't dispatch on_motion to children if only self is registered.\r\n* Widget: Removed collision on disabled check from on_motion method.\r\n* Widget: Added docstrings for motion_filter and related methods.\r\n* EventManager: Moved motion event flags to eventmanager/__init__.py module.\r\n* ScreenManager: Overrode the on_motion method.\r\n* WindowBase: Using attributes event_managers and event_managers_dict.\r\n* WindowBase: Added doc for register_event_manager and unregister_event_manager methods.\r\n* Widget: Improved default dispatch to stop after the last registered widgets.\r\n* EventManagerBase: Added initial docs class and module.\r\n* Widget: Added experimental warnings to motion_filter property and to on_motion and (un)register_for_motion_event methods.\r\n* WindowBase: Added docs for event_managers and event_managers_dict attributes.\r\n* MotionEvent: Added type_id and flags to push_attrs list.\r\n* EventManagerBase: Added versionadded tag on all flags.\r\n* EventManagerBase: Use dispatch modes instead of flags.",
        "code": "def remove_widget(self, widget):\n        \n        if widget not in self.children:\n            return\n        self.children.remove(widget)\n        if widget.canvas in self.canvas.children:\n            self.canvas.remove(widget.canvas)\n        elif widget.canvas in self.canvas.after.children:\n            self.canvas.after.remove(widget.canvas)\n        elif widget.canvas in self.canvas.before.children:\n            self.canvas.before.remove(widget.canvas)\n        for type_id in widget.motion_filter:\n            self.unregister_for_motion_event(type_id, widget)\n        widget.funbind('motion_filter', self._update_motion_filter)\n        widget.parent = None\n        widget.dec_disabled(self._disabled_count)\n",
        "url": "https://github.com/kivy/kivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 162,
        "n_words": 37,
        "vocab_size": 29,
        "complexity": 6,
        "nloc": 15,
        "token_counts": 134,
        "n_ast_nodes": 213,
        "n_identifiers": 16,
        "d_id": 46984,
        "documentation": {
            "docstring": "Remove a widget from the children of this widget.\n\n        :Parameters:\n            `widget`: :class:`Widget`\n                Widget to remove from our children list.\n\n    .. code-block:: python\n\n        >>> from kivy.uix.button import Button\n        >>> root = Widget()\n        >>> button = Button()\n        >>> root.add_widget(button)\n        >>> root.remove_widget(button)\n        ",
            "n_words": 39,
            "vocab_size": 31,
            "n_whitespaces": 117,
            "language": "en"
        }
    },
    {
        "id": 12207,
        "commit_id": "a3b71c7208b3cd48aa7bc978c3343a074947e3d9",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/base.py",
        "file_name": "base.py",
        "fun_name": "mixin_base_ppr_parser",
        "commit_message": "fix(parsers): clearify flow args (#4701)",
        "code": "def mixin_base_ppr_parser(parser):\n    \n\n    mixin_essential_parser(parser)\n\n    gp = add_arg_group(parser, title='Base Deployment')\n\n    gp.add_argument(\n        '--extra-search-paths',\n        type=str,\n        default=[],\n        nargs='*',\n        help='Extra search paths to be used when loading modules and finding YAML config files.'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    gp.add_argument(\n        '--timeout-ctrl',\n        type=int,\n        default=int(os.getenv('JINA_DEFAULT_TIMEOUT_CTRL', '60')),\n        help='The timeout in milliseconds of the control request, -1 for waiting forever',\n    )\n\n    parser.add_argument(\n        '--k8s-namespace',\n        type=str,\n        help='Name of the namespace where Kubernetes deployment should be deployed, to be filled by flow name'\n        if _SHOW_ALL_ARGS\n        else argparse.SUPPRESS,\n    )\n\n    gp.add_argument(\n        '--polling',\n        type=str,\n        default=PollingType.ANY.name,\n        help=,\n    )\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 253,
        "n_words": 80,
        "vocab_size": 64,
        "complexity": 3,
        "nloc": 41,
        "token_counts": 123,
        "n_ast_nodes": 202,
        "n_identifiers": 21,
        "d_id": 2215,
        "documentation": {
            "docstring": "Mixing in arguments required by pod/deployment/runtime module into the given parser.\n    :param parser: the parser instance to which we add arguments\n    \n    The polling strategy of the Deployment and its endpoints (when `shards>1`).\n    Can be defined for all endpoints of a Deployment or by endpoint.\n    Define per Deployment:\n    - ANY: only one (whoever is idle) Pod polls the message\n    - ALL: all Pods poll the message (like a broadcast)\n    Define per Endpoint:\n    JSON dict, {endpoint: PollingType}\n    {'/custom': 'ALL', '/search': 'ANY', '*': 'ANY'}\n    \n    ",
            "n_words": 81,
            "vocab_size": 66,
            "n_whitespaces": 119,
            "language": "en"
        }
    },
    {
        "id": 22594,
        "commit_id": "f0af0c43340763724f139fa68aa1e5a9ffe458b4",
        "repo": "Python",
        "path": "calculator.py",
        "file_name": "calculator.py",
        "fun_name": "calc",
        "commit_message": "refactor: clean code\n\nSigned-off-by: slowy07 <slowy.arfy@gmail.com>",
        "code": "def calc(term):\n    \n\n    # This part is for reading and converting arithmetic terms.\n    term = term.replace(\" \", \"\")\n    term = term.replace(\"^\", \"**\")\n    term = term.replace(\"=\", \"\")\n    term = term.replace(\"?\", \"\")\n    term = term.replace(\"%\", \"/100.00\")\n    term = term.replace(\"rad\", \"radians\")\n    term = term.replace(\"mod\", \"%\")\n    term = term.replace(\"aval\", \"abs\")\n\n    functions = [\n        \"sin\",\n        \"cos\",\n        \"tan\",\n        \"pow\",\n        \"cosh\",\n        \"sinh\",\n        \"tanh\",\n        \"sqrt\",\n        \"pi\",\n        \"radians\",\n        \"e\",\n    ]\n\n    # This part is for reading and converting function expressions.\n    term = term.lower()\n\n    for func in functions:\n        if func in term:\n            withmath = \"math.\" + func\n            term = term.replace(func, withmath)\n\n    try:\n\n        # here goes the actual evaluating.\n        term = eval(term)\n\n    # here goes to the error cases.\n    except ZeroDivisionError:\n\n        print(\"Can't divide by 0.  Please try again.\")\n\n    except NameError:\n\n        print(\"Invalid input.  Please try again\")\n\n    except AttributeError:\n\n        print(\"Please check usage method and try again.\")\n    except TypeError:\n        print(\"please enter inputs of correct datatype \")\n\n    return term\n\n",
        "url": "https://github.com/geekcomputers/Python.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 359,
        "n_words": 143,
        "vocab_size": 93,
        "complexity": 7,
        "nloc": 38,
        "token_counts": 182,
        "n_ast_nodes": 345,
        "n_identifiers": 13,
        "d_id": 4373,
        "documentation": {
            "docstring": "\n    input: term of type str\n    output: returns the result of the computed term.\n    purpose: This function is the actual calculator and the heart of the application\n    ",
            "n_words": 26,
            "vocab_size": 20,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 30148,
        "commit_id": "fa2ad657482aca9dc628e6d7062b8badf2706bb6",
        "repo": "spotify-downloader",
        "path": "tests/types/test_song.py",
        "file_name": "test_song.py",
        "fun_name": "test_song_from_dict",
        "commit_message": "v4 init",
        "code": "def test_song_from_dict():\n    \n\n    song = Song.from_dict(\n        {\n            \"name\": \"Ropes\",\n            \"artists\": [\"Dirty Palm\", \"Chandler Jewels\"],\n            \"album_name\": \"Ropes\",\n            \"album_artist\": \"Dirty Palm\",\n            \"genres\": [\"gaming edm\", \"melbourne bounce international\"],\n            \"disc_number\": 1,\n            \"duration\": 188,\n            \"year\": 2021,\n            \"date\": \"2021-10-28\",\n            \"track_number\": 1,\n            \"tracks_count\": 1,\n            \"isrc\": \"GB2LD2110301\",\n            \"song_id\": \"1t2qKa8K72IBC8yQlhD9bU\",\n            \"cover_url\": \"https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332\",\n            \"explicit\": False,\n            \"download_url\": None,\n            \"artist\": \"Dirty Palm\",\n            \"disc_count\": 1,\n            \"copyright\": \"\",\n            \"publisher\": \"\",\n            \"url\": \"https://open.spotify.com/track/1t2qKa8K72IBC8yQlhD9bU\",\n        }\n    )\n\n    assert song.name == \"Ropes\"\n    assert song.artists == [\"Dirty Palm\", \"Chandler Jewels\"]\n    assert song.album_name == \"Ropes\"\n    assert song.album_artist == \"Dirty Palm\"\n    assert song.genres == [\"gaming edm\", \"melbourne bounce international\"]\n    assert song.disc_number == 1\n    assert song.duration == 188\n    assert song.year == 2021\n    assert song.date == \"2021-10-28\"\n    assert song.track_number == 1\n    assert song.tracks_count == 1\n    assert song.isrc == \"GB2LD2110301\"\n    assert song.song_id == \"1t2qKa8K72IBC8yQlhD9bU\"\n    assert (\n        song.cover_url\n        == \"https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332\"\n    )\n    assert song.explicit == False\n",
        "url": "https://github.com/spotDL/spotify-downloader.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 445,
        "n_words": 129,
        "vocab_size": 81,
        "complexity": 1,
        "nloc": 44,
        "token_counts": 206,
        "n_ast_nodes": 384,
        "n_identifiers": 19,
        "d_id": 5349,
        "documentation": {
            "docstring": "\n    Tests if Song.from_dict() works correctly.\n    ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 12,
            "language": "en"
        }
    },
    {
        "id": 44559,
        "commit_id": "99f86ccfa59df6aa1aa33afce5e0b66dd5df9a3d",
        "repo": "airflow",
        "path": "airflow/ti_deps/deps/trigger_rule_dep.py",
        "file_name": "trigger_rule_dep.py",
        "fun_name": "_get_states_count_upstream_ti",
        "commit_message": "Some refactoring work on scheduling code (#21414)",
        "code": "def _get_states_count_upstream_ti(ti, finished_tis):\n        \n        counter = Counter(task.state for task in finished_tis if task.task_id in ti.task.upstream_task_ids)\n        return (\n            counter.get(State.SUCCESS, 0),\n            counter.get(State.SKIPPED, 0),\n            counter.get(State.FAILED, 0),\n            counter.get(State.UPSTREAM_FAILED, 0),\n            sum(counter.values()),\n        )\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 109,
        "n_words": 26,
        "vocab_size": 22,
        "complexity": 3,
        "nloc": 9,
        "token_counts": 86,
        "n_ast_nodes": 127,
        "n_identifiers": 17,
        "d_id": 8298,
        "documentation": {
            "docstring": "\n        This function returns the states of the upstream tis for a specific ti in order to determine\n        whether this ti can run in this iteration\n\n        :param ti: the ti that we want to calculate deps for\n        :param finished_tis: all the finished tasks of the dag_run\n        ",
            "n_words": 45,
            "vocab_size": 33,
            "n_whitespaces": 81,
            "language": "en"
        }
    },
    {
        "id": 259315,
        "commit_id": "ee5a1b69d1dfa99635a10f0a5b54ec263cedf866",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/_birch.py",
        "file_name": "_birch.py",
        "fun_name": "fit",
        "commit_message": "DOC, MNT Typos found by codespell (#22906)",
        "code": "def fit(self, X, y=None):\n        \n\n        # Validating the scalar parameters.\n        check_scalar(\n            self.threshold,\n            \"threshold\",\n            target_type=numbers.Real,\n            min_val=0.0,\n            include_boundaries=\"neither\",\n        )\n        check_scalar(\n            self.branching_factor,\n            \"branching_factor\",\n            target_type=numbers.Integral,\n            min_val=1,\n            include_boundaries=\"neither\",\n        )\n        if isinstance(self.n_clusters, numbers.Number):\n            check_scalar(\n                self.n_clusters,\n                \"n_clusters\",\n                target_type=numbers.Integral,\n                min_val=1,\n            )\n\n        # TODO: Remove deprecated flags in 1.2\n        self._deprecated_fit, self._deprecated_partial_fit = True, False\n        return self._fit(X, partial=False)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 309,
        "n_words": 47,
        "vocab_size": 39,
        "complexity": 2,
        "nloc": 24,
        "token_counts": 113,
        "n_ast_nodes": 171,
        "n_identifiers": 20,
        "d_id": 75706,
        "documentation": {
            "docstring": "\n        Build a CF Tree for the input data.\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix} of shape (n_samples, n_features)\n            Input data.\n\n        y : Ignored\n            Not used, present here for API consistency by convention.\n\n        Returns\n        -------\n        self\n            Fitted estimator.\n        ",
            "n_words": 38,
            "vocab_size": 35,
            "n_whitespaces": 135,
            "language": "en"
        }
    },
    {
        "id": 100289,
        "commit_id": "23d92c1f0d83ce1cdcc51480cfe37af074a981b3",
        "repo": "faceswap",
        "path": "tools/manual/detected_faces.py",
        "file_name": "detected_faces.py",
        "fun_name": "load",
        "commit_message": "Bugfixes\n  - Sort - Fix rare help-text parsing bug\n  - Manual - Fix issue where frame count is incorrect when een > 1 used on extract",
        "code": "def load(self):\n        \n        for key in sorted(self._alignments.data):\n            this_frame_faces = []\n            for item in self._alignments.data[key][\"faces\"]:\n                face = DetectedFace()\n                face.from_alignment(item, with_thumb=True)\n                face.load_aligned(None)\n                _ = face.aligned.average_distance  # cache the distances\n                this_frame_faces.append(face)\n            self._frame_faces.append(this_frame_faces)\n        self._sorted_frame_names = sorted(self._alignments.data)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 161,
        "n_words": 31,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 91,
        "n_ast_nodes": 149,
        "n_identifiers": 19,
        "d_id": 19790,
        "documentation": {
            "docstring": " Load the faces from the alignments file, convert to\n        :class:`~lib.align.DetectedFace`. objects and add to :attr:`_frame_faces`. ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 23,
            "language": "en"
        }
    },
    {
        "id": 65846,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/education/api.py",
        "file_name": "api.py",
        "fun_name": "get_assessment_criteria",
        "commit_message": "style: format code with black",
        "code": "def get_assessment_criteria(course):\n\t\n\treturn frappe.get_all(\n\t\t\"Course Assessment Criteria\",\n\t\tfields=[\"assessment_criteria\", \"weightage\"],\n\t\tfilters={\"parent\": course},\n\t\torder_by=\"idx\",\n\t)\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 6,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 7,
        "token_counts": 34,
        "n_ast_nodes": 72,
        "n_identifiers": 8,
        "d_id": 14035,
        "documentation": {
            "docstring": "Returns Assessmemt Criteria and their Weightage from Course Master.\n\n\t:param Course: Course\n\t",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 222589,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/distutils/ccompiler.py",
        "file_name": "ccompiler.py",
        "fun_name": "new_compiler",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def new_compiler(plat=None, compiler=None, verbose=0, dry_run=0, force=0):\n    \n    if plat is None:\n        plat = os.name\n\n    try:\n        if compiler is None:\n            compiler = get_default_compiler(plat)\n\n        (module_name, class_name, long_description) = compiler_class[compiler]\n    except KeyError:\n        msg = \"don't know how to compile C/C++ code on platform '%s'\" % plat\n        if compiler is not None:\n            msg = msg + \" with '%s' compiler\" % compiler\n        raise DistutilsPlatformError(msg)\n\n    try:\n        module_name = \"distutils.\" + module_name\n        __import__ (module_name)\n        module = sys.modules[module_name]\n        klass = vars(module)[class_name]\n    except ImportError:\n        raise DistutilsModuleError(\n              \"can't compile C/C++ code: unable to load module '%s'\" % \\\n              module_name)\n    except KeyError:\n        raise DistutilsModuleError(\n               \"can't compile C/C++ code: unable to find class '%s' \"\n               \"in module '%s'\" % (class_name, module_name))\n\n    # XXX The None is necessary to preserve backwards compatibility\n    # with classes that expect verbose to be the first positional\n    # argument.\n    return klass(None, dry_run, force)\n\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 329,
        "n_words": 136,
        "vocab_size": 83,
        "complexity": 7,
        "nloc": 26,
        "token_counts": 148,
        "n_ast_nodes": 242,
        "n_identifiers": 24,
        "d_id": 56657,
        "documentation": {
            "docstring": "Generate an instance of some CCompiler subclass for the supplied\n    platform/compiler combination.  'plat' defaults to 'os.name'\n    (eg. 'posix', 'nt'), and 'compiler' defaults to the default compiler\n    for that platform.  Currently only 'posix' and 'nt' are supported, and\n    the default compilers are \"traditional Unix interface\" (UnixCCompiler\n    class) and Visual C++ (MSVCCompiler class).  Note that it's perfectly\n    possible to ask for a Unix compiler object under Windows, and a\n    Microsoft compiler object under Unix -- if you supply a value for\n    'compiler', 'plat' is ignored.\n    ",
            "n_words": 83,
            "vocab_size": 59,
            "n_whitespaces": 113,
            "language": "en"
        }
    },
    {
        "id": 35173,
        "commit_id": "2e11a043374a6229ec129a4765ee4ba7517832b9",
        "repo": "transformers",
        "path": "src/transformers/models/auto/feature_extraction_auto.py",
        "file_name": "feature_extraction_auto.py",
        "fun_name": "register",
        "commit_message": "Register feature extractor (#15634)\n\n* Rework AutoFeatureExtractor.from_pretrained internal\r\n\r\n* Custom feature extractor\r\n\r\n* Add more tests\r\n\r\n* Add support for custom feature extractor code\r\n\r\n* Clean up\r\n\r\n* Add register API to AutoFeatureExtractor",
        "code": "def register(config_class, feature_extractor_class):\n        \n        FEATURE_EXTRACTOR_MAPPING.register(config_class, feature_extractor_class)\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 19,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 16,
        "n_ast_nodes": 27,
        "n_identifiers": 4,
        "d_id": 6418,
        "documentation": {
            "docstring": "\n        Register a new feature extractor for this class.\n\n        Args:\n            config_class ([`PretrainedConfig`]):\n                The configuration corresponding to the model to register.\n            feature_extractor_class ([`FeatureExtractorMixin`]): The feature extractor to register.\n        ",
            "n_words": 26,
            "vocab_size": 20,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 66703,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/patches/v12_0/update_pricing_rule_fields.py",
        "file_name": "update_pricing_rule_fields.py",
        "fun_name": "execute",
        "commit_message": "style: format code with black",
        "code": "def execute():\n\n\tif not frappe.get_all(\"Pricing Rule\", limit=1):\n\t\treturn\n\n\tfrappe.reload_doc(\"accounts\", \"doctype\", \"pricing_rule_detail\")\n\tdoctypes = {\n\t\t\"Supplier Quotation\": \"buying\",\n\t\t\"Purchase Order\": \"buying\",\n\t\t\"Purchase Invoice\": \"accounts\",\n\t\t\"Purchase Receipt\": \"stock\",\n\t\t\"Quotation\": \"selling\",\n\t\t\"Sales Order\": \"selling\",\n\t\t\"Sales Invoice\": \"accounts\",\n\t\t\"Delivery Note\": \"stock\",\n\t}\n\n\tfor doctype, module in doctypes.items():\n\t\tfrappe.reload_doc(module, \"doctype\", frappe.scrub(doctype))\n\n\t\tchild_doc = frappe.scrub(doctype) + \"_item\"\n\t\tfrappe.reload_doc(module, \"doctype\", child_doc, force=True)\n\n\t\tchild_doctype = doctype + \" Item\"\n\n\t\tfrappe.db.sql(\n\t\t\t.format(\n\t\t\t\tchild_doctype=child_doctype\n\t\t\t)\n\t\t)\n\n\t\tdata = frappe.db.sql(\n\t\t\t.format(\n\t\t\t\tchild_doc=child_doctype\n\t\t\t),\n\t\t\tas_dict=1,\n\t\t)\n\n\t\tvalues = []\n\t\tfor d in data:\n\t\t\tvalues.append(\n\t\t\t\t(\n\t\t\t\t\td.pricing_rule,\n\t\t\t\t\td.name,\n\t\t\t\t\td.parent,\n\t\t\t\t\t\"pricing_rules\",\n\t\t\t\t\td.parenttype,\n\t\t\t\t\td.creation,\n\t\t\t\t\td.modified,\n\t\t\t\t\td.docstatus,\n\t\t\t\t\td.modified_by,\n\t\t\t\t\td.owner,\n\t\t\t\t\tfrappe.generate_hash(\"\", 10),\n\t\t\t\t)\n\t\t\t)\n\n\t\tif values:\n\t\t\tfrappe.db.sql(\n\t\t\t\t.format(\n\t\t\t\t\tvalues=\", \".join([\"%s\"] * len(values))\n\t\t\t\t),\n\t\t\t\ttuple(values),\n\t\t\t)\n\n\tfrappe.reload_doc(\"accounts\", \"doctype\", \"pricing_rule\")\n\n\tfor doctype, apply_on in {\n\t\t\"Pricing Rule Item Code\": \"Item Code\",\n\t\t\"Pricing Rule Item Group\": \"Item Group\",\n\t\t\"Pricing Rule Brand\": \"Brand\",\n\t}.items():\n\t\tfrappe.reload_doc(\"accounts\", \"doctype\", frappe.scrub(doctype))\n\n\t\tfield = frappe.scrub(apply_on)\n\t\tdata = frappe.get_all(\n\t\t\t\"Pricing Rule\",\n\t\t\tfields=[field, \"name\", \"creation\", \"modified\", \"owner\", \"modified_by\"],\n\t\t\tfilters={\"apply_on\": apply_on},\n\t\t)\n\n\t\tvalues = []\n\t\tfor d in data:\n\t\t\tvalues.append(\n\t\t\t\t(\n\t\t\t\t\td.get(field),\n\t\t\t\t\td.name,\n\t\t\t\t\tparentfield.get(field),\n\t\t\t\t\t\"Pricing Rule\",\n\t\t\t\t\td.creation,\n\t\t\t\t\td.modified,\n\t\t\t\t\td.owner,\n\t\t\t\t\td.modified_by,\n\t\t\t\t\tfrappe.generate_hash(\"\", 10),\n\t\t\t\t)\n\t\t\t)\n\n\t\tif values:\n\t\t\tfrappe.db.sql(\n\t\t\t\t.format(\n\t\t\t\t\tdoctype=doctype, field=field, values=\", \".join([\"%s\"] * len(values))\n\t\t\t\t),\n\t\t\t\ttuple(values),\n\t\t\t)\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 99,
        "n_words": 188,
        "vocab_size": 106,
        "complexity": 8,
        "nloc": 100,
        "token_counts": 450,
        "n_ast_nodes": 756,
        "n_identifiers": 40,
        "d_id": 14303,
        "documentation": {
            "docstring": " UPDATE `tab{child_doctype}` SET pricing_rules = pricing_rule\n\t\t\tWHERE docstatus < 2 and pricing_rule is not null and pricing_rule != ''\n\t\t SELECT pricing_rule, name, parent,\n\t\t\t\tparenttype, creation, modified, docstatus, modified_by, owner, name\n\t\t\tFROM `tab{child_doc}` where docstatus < 2 and pricing_rule is not null\n\t\t\tand pricing_rule != '' INSERT INTO\n\t\t\t\t`tabPricing Rule Detail` (`pricing_rule`, `child_docname`, `parent`, `parentfield`, `parenttype`,\n\t\t\t\t`creation`, `modified`, `docstatus`, `modified_by`, `owner`, `name`)\n\t\t\tVALUES {values}  INSERT INTO\n\t\t\t\t`tab{doctype}` ({field}, parent, parentfield, parenttype, creation, modified,\n\t\t\t\t\towner, modified_by, name)\n\t\t\tVALUES {values} ",
            "n_words": 77,
            "vocab_size": 52,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 215998,
        "commit_id": "8168b25fe5906883a07de5bfdfefabc6d1f57784",
        "repo": "salt",
        "path": "tests/pytests/unit/state/test_state_options.py",
        "file_name": "test_state_options.py",
        "fun_name": "test_state_aggregate_option_behavior",
        "commit_message": "fixes saltstack/salt#61478 state_aggregate minion option not respected",
        "code": "def test_state_aggregate_option_behavior(master_opts):\n    \n    minion_opts = salt.config.DEFAULT_MINION_OPTS.copy()\n    possible = [None, True, False, [\"pkg\"]]\n    expected_result = [\n        True,\n        False,\n        [\"pkg\"],\n        True,\n        True,\n        [\"pkg\"],\n        False,\n        True,\n        [\"pkg\"],\n        [\"pkg\"],\n        True,\n        [\"pkg\"],\n    ]\n\n    for idx, combo in enumerate(itertools.permutations(possible, 2)):\n        master_opts[\"state_aggregate\"], minion_opts[\"state_aggregate\"] = combo\n        state_obj = salt.state.BaseHighState\n        state_obj.client = MockBaseHighStateClient(master_opts)\n        return_result = state_obj(minion_opts)._BaseHighState__gen_opts(minion_opts)\n        assert expected_result[idx] == return_result[\"state_aggregate\"]\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 187,
        "n_words": 50,
        "vocab_size": 32,
        "complexity": 2,
        "nloc": 23,
        "token_counts": 132,
        "n_ast_nodes": 209,
        "n_identifiers": 21,
        "d_id": 54314,
        "documentation": {
            "docstring": "\n    Ensure state_aggregate can be overridden on the minion\n    ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 15,
            "language": "en"
        }
    },
    {
        "id": 153044,
        "commit_id": "58bbcc37477866d19c8b092a0e1974a4f0baa586",
        "repo": "modin",
        "path": "modin/core/dataframe/algebra/tree_reduce.py",
        "file_name": "tree_reduce.py",
        "fun_name": "register",
        "commit_message": "REFACTOR-#2656: Update modin to fit algebra (code only) (#3717)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nCo-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com>\r\nCo-authored-by: Alexey Prutskov <alexey.prutskov@intel.com>\r\nCo-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com>\r\nSigned-off-by: Rehan Durrani <rehan@ponder.io>",
        "code": "def register(cls, map_function, reduce_function=None, **kwargs):\n        \n        if reduce_function is None:\n            reduce_function = map_function\n        return cls.call(map_function, reduce_function, **kwargs)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 48,
        "n_words": 16,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 35,
        "n_ast_nodes": 54,
        "n_identifiers": 6,
        "d_id": 35228,
        "documentation": {
            "docstring": "\n        Build TreeReduce function.\n\n        Parameters\n        ----------\n        map_function : callable(pandas.DataFrame) -> [pandas.DataFrame, pandas.Series]\n            Source map function.\n        reduce_function : callable(pandas.DataFrame) -> pandas.Series, optional\n            Source reduce function. If not specified `map_function` will be used.\n        **kwargs : dict\n            Additional parameters to pass to the builder function.\n\n        Returns\n        -------\n        callable\n            Function that takes query compiler and executes passed functions\n            with TreeReduce algorithm.\n        ",
            "n_words": 56,
            "vocab_size": 46,
            "n_whitespaces": 182,
            "language": "en"
        }
    },
    {
        "id": 259640,
        "commit_id": "ade90145c9c660a1a7baf2315185995899b0f356",
        "repo": "scikit-learn",
        "path": "sklearn/manifold/_t_sne.py",
        "file_name": "_t_sne.py",
        "fun_name": "trustworthiness",
        "commit_message": "FIX Raise error when n_neighbors >= n_samples / 2  in manifold.trustworthiness (#23033)\n\nCo-authored-by: Shao Yang Hong <hongsy2006@gmail.com>\r\nCo-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def trustworthiness(X, X_embedded, *, n_neighbors=5, metric=\"euclidean\"):\n    r\n    n_samples = X.shape[0]\n    if n_neighbors >= n_samples / 2:\n        raise ValueError(\n            f\"n_neighbors ({n_neighbors}) should be less than n_samples / 2\"\n            f\" ({n_samples / 2})\"\n        )\n    dist_X = pairwise_distances(X, metric=metric)\n    if metric == \"precomputed\":\n        dist_X = dist_X.copy()\n    # we set the diagonal to np.inf to exclude the points themselves from\n    # their own neighborhood\n    np.fill_diagonal(dist_X, np.inf)\n    ind_X = np.argsort(dist_X, axis=1)\n    # `ind_X[i]` is the index of sorted distances between i and other samples\n    ind_X_embedded = (\n        NearestNeighbors(n_neighbors=n_neighbors)\n        .fit(X_embedded)\n        .kneighbors(return_distance=False)\n    )\n\n    # We build an inverted index of neighbors in the input space: For sample i,\n    # we define `inverted_index[i]` as the inverted index of sorted distances:\n    # inverted_index[i][ind_X[i]] = np.arange(1, n_sample + 1)\n    inverted_index = np.zeros((n_samples, n_samples), dtype=int)\n    ordered_indices = np.arange(n_samples + 1)\n    inverted_index[ordered_indices[:-1, np.newaxis], ind_X] = ordered_indices[1:]\n    ranks = (\n        inverted_index[ordered_indices[:-1, np.newaxis], ind_X_embedded] - n_neighbors\n    )\n    t = np.sum(ranks[ranks > 0])\n    t = 1.0 - t * (\n        2.0 / (n_samples * n_neighbors * (2.0 * n_samples - 3.0 * n_neighbors - 1.0))\n    )\n    return t\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 322,
        "n_words": 173,
        "vocab_size": 115,
        "complexity": 3,
        "nloc": 84,
        "token_counts": 228,
        "n_ast_nodes": 352,
        "n_identifiers": 32,
        "d_id": 75842,
        "documentation": {
            "docstring": "Expresses to what extent the local structure is retained.\n\n    The trustworthiness is within [0, 1]. It is defined as\n\n    .. math::\n\n        T(k) = 1 - \\frac{2}{nk (2n - 3k - 1)} \\sum^n_{i=1}\n            \\sum_{j \\in \\mathcal{N}_{i}^{k}} \\max(0, (r(i, j) - k))\n\n    where for each sample i, :math:`\\mathcal{N}_{i}^{k}` are its k nearest\n    neighbors in the output space, and every sample j is its :math:`r(i, j)`-th\n    nearest neighbor in the input space. In other words, any unexpected nearest\n    neighbors in the output space are penalised in proportion to their rank in\n    the input space.\n\n    Parameters\n    ----------\n    X : ndarray of shape (n_samples, n_features) or (n_samples, n_samples)\n        If the metric is 'precomputed' X must be a square distance\n        matrix. Otherwise it contains a sample per row.\n\n    X_embedded : ndarray of shape (n_samples, n_components)\n        Embedding of the training data in low-dimensional space.\n\n    n_neighbors : int, default=5\n        The number of neighbors that will be considered. Should be fewer than\n        `n_samples / 2` to ensure the trustworthiness to lies within [0, 1], as\n        mentioned in [1]_. An error will be raised otherwise.\n\n    metric : str or callable, default='euclidean'\n        Which metric to use for computing pairwise distances between samples\n        from the original input space. If metric is 'precomputed', X must be a\n        matrix of pairwise distances or squared distances. Otherwise, for a list\n        of available metrics, see the documentation of argument metric in\n        `sklearn.pairwise.pairwise_distances` and metrics listed in\n        `sklearn.metrics.pairwise.PAIRWISE_DISTANCE_FUNCTIONS`. Note that the\n        \"cosine\" metric uses :func:`~sklearn.metrics.pairwise.cosine_distances`.\n\n        .. versionadded:: 0.20\n\n    Returns\n    -------\n    trustworthiness : float\n        Trustworthiness of the low-dimensional embedding.\n\n    References\n    ----------\n    .. [1] Jarkko Venna and Samuel Kaski. 2001. Neighborhood\n           Preservation in Nonlinear Projection Methods: An Experimental Study.\n           In Proceedings of the International Conference on Artificial Neural Networks\n           (ICANN '01). Springer-Verlag, Berlin, Heidelberg, 485-491.\n\n    .. [2] Laurens van der Maaten. Learning a Parametric Embedding by Preserving\n           Local Structure. Proceedings of the Twelth International Conference on\n           Artificial Intelligence and Statistics, PMLR 5:384-391, 2009.\n    ",
            "n_words": 314,
            "vocab_size": 202,
            "n_whitespaces": 550,
            "language": "en"
        }
    },
    {
        "id": 194668,
        "commit_id": "2d9755ad8a82ba0777299cbc1666bed25278db94",
        "repo": "kivy",
        "path": "kivy/tests/test_logger.py",
        "file_name": "test_logger.py",
        "fun_name": "test_kivy_log_mode_marker_on",
        "commit_message": "Support KivyLogMode environment variable for logging testing (#7971)\n\n* Support KivyLogMode for logging testing\r\n\r\nAlso:\r\nRemove unused imports.\r\nRemove Python 2 only code\r\nRun through Black to canonicalize formatting\r\n\r\n* Undo formatting changes\r\n\r\nUndo black.",
        "code": "def test_kivy_log_mode_marker_on():\n    \n    from kivy.logger import previous_stderr\n\n    assert sys.stderr == previous_stderr, \"Kivy.logging override stderr\"\n    assert logging.root.parent is None, \"Kivy.logging override root logger\"\n",
        "url": "https://github.com/kivy/kivy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 33,
        "n_words": 21,
        "vocab_size": 18,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 29,
        "n_ast_nodes": 50,
        "n_identifiers": 9,
        "d_id": 47024,
        "documentation": {
            "docstring": "\n    This is a test of the pytest marker \"logmodetest\".\n    This should only be invoked if the environment variable is properly set\n    (before pytest is run).\n\n    Also, tests that kivy.logger paid attention to the environment variable\n    ",
            "n_words": 35,
            "vocab_size": 27,
            "n_whitespaces": 51,
            "language": "en"
        }
    },
    {
        "id": 100410,
        "commit_id": "c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf",
        "repo": "faceswap",
        "path": "setup.py",
        "file_name": "setup.py",
        "fun_name": "_get_checkfiles_linux",
        "commit_message": "Update code to support Tensorflow versions up to 2.8 (#1213)\n\n* Update maximum tf version in setup + requirements\r\n\r\n* - bump max version of tf version in launcher\r\n- standardise tf version check\r\n\r\n* update keras get_custom_objects  for tf>2.6\r\n\r\n* bugfix: force black text in GUI file dialogs (linux)\r\n\r\n* dssim loss - Move to stock tf.ssim function\r\n\r\n* Update optimizer imports for compatibility\r\n\r\n* fix logging for tf2.8\r\n\r\n* Fix GUI graphing for TF2.8\r\n\r\n* update tests\r\n\r\n* bump requirements.txt versions\r\n\r\n* Remove limit on nvidia-ml-py\r\n\r\n* Graphing bugfixes\r\n  - Prevent live graph from displaying if data not yet available\r\n\r\n* bugfix: Live graph. Collect loss labels correctly\r\n\r\n* fix: live graph - swallow inconsistent loss errors\r\n\r\n* Bugfix: Prevent live graph from clearing during training\r\n\r\n* Fix graphing for AMD",
        "code": "def _get_checkfiles_linux(self):\n        \n        chk = os.popen(\"ldconfig -p | grep -P \\\"libcudnn.so.\\\\d+\\\" | head -n 1\").read()\n        chk = chk.strip().replace(\"libcudnn.so.\", \"\")\n        if not chk:\n            return []\n\n        cudnn_vers = chk[0]\n        header_files = [f\"cudnn_v{cudnn_vers}.h\"] + self._cudnn_header_files\n\n        cudnn_path = os.path.realpath(chk[chk.find(\"=>\") + 3:chk.find(\"libcudnn\") - 1])\n        cudnn_path = cudnn_path.replace(\"lib\", \"include\")\n        cudnn_checkfiles = [os.path.join(cudnn_path, header) for header in header_files]\n        return cudnn_checkfiles\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 133,
        "n_words": 52,
        "vocab_size": 40,
        "complexity": 3,
        "nloc": 11,
        "token_counts": 114,
        "n_ast_nodes": 202,
        "n_identifiers": 18,
        "d_id": 19893,
        "documentation": {
            "docstring": " Return the the files to check for cuDNN locations for Linux by querying\n        the dynamic link loader.\n\n        Returns\n        -------\n        list\n            List of header file locations to scan for cuDNN versions\n        ",
            "n_words": 30,
            "vocab_size": 23,
            "n_whitespaces": 77,
            "language": "en"
        }
    },
    {
        "id": 101515,
        "commit_id": "dc18c74eea0c7837a820d27628cb12b0824fa30e",
        "repo": "faceswap",
        "path": "lib/gui/utils.py",
        "file_name": "utils.py",
        "fun_name": "set_default_options",
        "commit_message": "Bugfix: Preview for extract in batch mode",
        "code": "def set_default_options(self) -> None:\n        \n        default = self.cli_opts.get_option_values()\n        logger.debug(default)\n        self._gui_objects.default_options = default\n        self.project.set_default_options()\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 47,
        "n_words": 12,
        "vocab_size": 10,
        "complexity": 1,
        "nloc": 12,
        "token_counts": 37,
        "n_ast_nodes": 64,
        "n_identifiers": 10,
        "d_id": 20926,
        "documentation": {
            "docstring": " Set the default options for :mod:`lib.gui.projects`\n\n        The Default GUI options are stored on Faceswap startup.\n\n        Exposed as the :attr:`_default_opts` for a project cannot be set until after the main\n        Command Tabs have been loaded.\n        ",
            "n_words": 34,
            "vocab_size": 30,
            "n_whitespaces": 63,
            "language": "en"
        }
    },
    {
        "id": 249389,
        "commit_id": "ba8938b090c7e1908cfa4feac75f08f3bc1183e8",
        "repo": "synapse",
        "path": "scripts-dev/check_pydantic_models.py",
        "file_name": "check_pydantic_models.py",
        "fun_name": "do_lint",
        "commit_message": "Reject non-strict types in Pydantic models (#13502)",
        "code": "def do_lint() -> Set[str]:\n    \n    failures = set()\n\n    with monkeypatch_pydantic():\n        logger.debug(\"Importing synapse\")\n        try:\n            # TODO: make \"synapse\" an argument so we can target this script at\n            # a subpackage\n            module = importlib.import_module(\"synapse\")\n        except ModelCheckerException as e:\n            logger.warning(\"Bad annotation found when importing synapse\")\n            failures.add(format_model_checker_exception(e))\n            return failures\n\n        try:\n            logger.debug(\"Fetching subpackages\")\n            module_infos = list(\n                pkgutil.walk_packages(module.__path__, f\"{module.__name__}.\")\n            )\n        except ModelCheckerException as e:\n            logger.warning(\"Bad annotation found when looking for modules to import\")\n            failures.add(format_model_checker_exception(e))\n            return failures\n\n        for module_info in module_infos:\n            logger.debug(\"Importing %s\", module_info.name)\n            try:\n                importlib.import_module(module_info.name)\n            except ModelCheckerException as e:\n                logger.warning(\n                    f\"Bad annotation found when importing {module_info.name}\"\n                )\n                failures.add(format_model_checker_exception(e))\n\n    return failures\n\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 406,
        "n_words": 93,
        "vocab_size": 61,
        "complexity": 5,
        "nloc": 30,
        "token_counts": 152,
        "n_ast_nodes": 285,
        "n_identifiers": 24,
        "d_id": 72885,
        "documentation": {
            "docstring": "Try to import all of Synapse and see if we spot any Pydantic type coercions.",
            "n_words": 15,
            "vocab_size": 15,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 197316,
        "commit_id": "65be461082dda54c8748922f9c29a19af1279fe1",
        "repo": "sympy",
        "path": "sympy/core/sympify.py",
        "file_name": "sympify.py",
        "fun_name": "kernS",
        "commit_message": "Remove abbreviations in documentation",
        "code": "def kernS(s):\n    \n    hit = False\n    quoted = '\"' in s or \"'\" in s\n    if '(' in s and not quoted:\n        if s.count('(') != s.count(\")\"):\n            raise SympifyError('unmatched left parenthesis')\n\n        # strip all space from s\n        s = ''.join(s.split())\n        olds = s\n        # now use space to represent a symbol that\n        # will\n        # step 1. turn potential 2-arg Muls into 3-arg versions\n        # 1a. *( -> * *(\n        s = s.replace('*(', '* *(')\n        # 1b. close up exponentials\n        s = s.replace('** *', '**')\n        # 2. handle the implied multiplication of a negated\n        # parenthesized expression in two steps\n        # 2a:  -(...)  -->  -( *(...)\n        target = '-( *('\n        s = s.replace('-(', target)\n        # 2b: double the matching closing parenthesis\n        # -( *(...)  -->  -( *(...))\n        i = nest = 0\n        assert target.endswith('(')  # assumption below\n        while True:\n            j = s.find(target, i)\n            if j == -1:\n                break\n            j += len(target) - 1\n            for j in range(j, len(s)):\n                if s[j] == \"(\":\n                    nest += 1\n                elif s[j] == \")\":\n                    nest -= 1\n                if nest == 0:\n                    break\n            s = s[:j] + \")\" + s[j:]\n            i = j + 2  # the first char after 2nd )\n        if ' ' in s:\n            # get a unique kern\n            kern = '_'\n            while kern in s:\n                kern += choice(string.ascii_letters + string.digits)\n            s = s.replace(' ', kern)\n            hit = kern in s\n        else:\n            hit = False\n\n    for i in range(2):\n        try:\n            expr = sympify(s)\n            break\n        except TypeError:  # the kern might cause unknown errors...\n            if hit:\n                s = olds  # maybe it didn't like the kern; use un-kerned s\n                hit = False\n                continue\n            expr = sympify(s)  # let original error raise\n\n    if not hit:\n        return expr\n\n    from .symbol import Symbol\n    rep = {Symbol(kern): 1}",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 868,
        "n_words": 288,
        "vocab_size": 166,
        "complexity": 17,
        "nloc": 53,
        "token_counts": 307,
        "n_ast_nodes": 535,
        "n_identifiers": 29,
        "d_id": 48459,
        "documentation": {
            "docstring": "Use a hack to try keep autosimplification from distributing a\n    a number into an Add; this modification does not\n    prevent the 2-arg Mul from becoming an Add, however.\n\n    Examples\n    ========\n\n    >>> from sympy.core.sympify import kernS\n    >>> from sympy.abc import x, y\n\n    The 2-arg Mul distributes a number (or minus sign) across the terms\n    of an expression, but kernS will prevent that:\n\n    >>> 2*(x + y), -(x + 1)\n    (2*x + 2*y, -x - 1)\n    >>> kernS('2*(x + y)')\n    2*(x + y)\n    >>> kernS('-(x + 1)')\n    -(x + 1)\n\n    If use of the hack fails, the un-hacked string will be passed to sympify...\n    and you get what you get.\n\n    XXX This hack should not be necessary once issue 4596 has been resolved.\n    ",
            "n_words": 121,
            "vocab_size": 82,
            "n_whitespaces": 175,
            "language": "en"
        }
    },
    {
        "id": 215093,
        "commit_id": "f1c37893caf90738288e789c3233ab934630254f",
        "repo": "salt",
        "path": "tests/pytests/unit/modules/test_aixpkg.py",
        "file_name": "test_aixpkg.py",
        "fun_name": "test_install_fail_dnf_try_fileset",
        "commit_message": "Working tests for install",
        "code": "def test_install_fail_dnf_try_fileset():\n    \n\n    bos_net_fake_error = \n\n    dnf_installp_call = MagicMock(\n        side_effect=[\n            {\"retcode\": 1, \"stdout\": \"\", \"stderr\": bos_net_fake_error},\n            {\"retcode\": 0, \"stdout\": \"\"},\n        ]\n    )\n    fileset_pkg_name = \"/cecc/repos/aix72/TL3/BASE/installp/ppc/bos.net\"\n    list_pkgs_mock = MagicMock(\n        side_effect=[\n            {\"bos.net.tcp.tcpdump\": \"7.1.6.3\"},\n            {\"bos.net.tcp.tcpdump\": \"7.2.4.1\"},\n        ]\n    )\n    with patch(\"pathlib.Path.is_file\", return_value=True):\n        with patch.dict(\n            aixpkg.__salt__,\n            {\n                \"cmd.run_all\": dnf_installp_call,\n                \"config.get\": MagicMock(return_value=False),\n            },\n        ), patch.object(aixpkg, \"list_pkgs\", list_pkgs_mock):\n            result = aixpkg.install(fileset_pkg_name)\n            assert dnf_installp_call.call_count == 2\n            libpath_env = {\"LIBPATH\": \"/opt/freeware/lib:/usr/lib\"}\n            dnf_installp_call.assert_any_call(\n                f\"/opt/freeware/bin/dnf install --allowerasing  --assumeyes {fileset_pkg_name}\",\n                env=libpath_env,\n                ignore_retcode=True,\n                python_shell=False,\n            )\n            dnf_installp_call.assert_called_with(\n                \"/usr/sbin/installp -acYXg -d /cecc/repos/aix72/TL3/BASE/installp/ppc bos.net\",\n                python_shell=False,\n            )\n            expected = {\"bos.net.tcp.tcpdump\": {\"old\": \"7.1.6.3\", \"new\": \"7.2.4.1\"}}\n            assert result == expected\n\n",
        "url": "https://github.com/saltstack/salt.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 453,
        "n_words": 89,
        "vocab_size": 67,
        "complexity": 1,
        "nloc": 43,
        "token_counts": 184,
        "n_ast_nodes": 331,
        "n_identifiers": 23,
        "d_id": 53810,
        "documentation": {
            "docstring": "\n    Test install of non-recognized extension, first dnf then fileset\n    AIX generic repository                                                                                                                                                                                                                       12 kB/s | 2.6 kB     00:00\nAIX noarch repository                                                                                                                                                                                                                        12 kB/s | 2.5 kB     00:00    \nAIX 7.2 specific repository                                                                                                                                                                                                                  12 kB/s | 2.5 kB     00:00    \nNo match for argument: bos.net\nError: Unable to find a match: bos.net\n",
            "n_words": 49,
            "vocab_size": 33,
            "n_whitespaces": 709,
            "language": "en"
        }
    },
    {
        "id": 155568,
        "commit_id": "6193b9de78798fc9b2d934e3317debc9bb5d8af5",
        "repo": "dask",
        "path": "dask/diagnostics/profile_visualize.py",
        "file_name": "profile_visualize.py",
        "fun_name": "plot_resources",
        "commit_message": "Handle plot_width / plot_height deprecations (#8544)\n\nBokeh 3.0 will finally deprecates `plot_width` and `plot_height` and expose only `width` and `height` (consistent with every other layout-able).",
        "code": "def plot_resources(results, palette=\"Viridis\", **kwargs):\n    \n    bp = import_required(\"bokeh.plotting\", _BOKEH_MISSING_MSG)\n    from bokeh import palettes\n    from bokeh.models import LinearAxis, Range1d\n\n    defaults = dict(\n        title=\"Profile Results\",\n        tools=\"save,reset,xwheel_zoom,xpan\",\n        toolbar_location=\"above\",\n        width=800,\n        height=300,\n    )\n    # Support plot_width and plot_height for backwards compatibility\n    if \"plot_width\" in kwargs:\n        kwargs[\"width\"] = kwargs.pop(\"plot_width\")\n        if BOKEH_VERSION().major >= 3:\n            warnings.warn(\"Use width instead of plot_width with Bokeh >= 3\")\n    if \"plot_height\" in kwargs:\n        kwargs[\"height\"] = kwargs.pop(\"plot_height\")\n        if BOKEH_VERSION().major >= 3:\n            warnings.warn(\"Use height instead of plot_height with Bokeh >= 3\")\n\n    # Drop `label_size` to match `plot_cache` and `plot_tasks` kwargs\n    if \"label_size\" in kwargs:\n        kwargs.pop(\"label_size\")\n\n    defaults.update(**kwargs)\n\n    if results:\n        t, mem, cpu = zip(*results)\n        left, right = min(t), max(t)\n        t = [i - left for i in t]\n        p = bp.figure(\n            y_range=fix_bounds(0, max(cpu), 100),\n            x_range=fix_bounds(0, right - left, 1),\n            **defaults,\n        )\n    else:\n        t = mem = cpu = []\n        p = bp.figure(y_range=(0, 100), x_range=(0, 1), **defaults)\n    colors = palettes.all_palettes[palette][6]\n    p.line(\n        t,\n        cpu,\n        color=colors[0],\n        line_width=4,\n        legend_label=\"% CPU\",\n    )\n    p.yaxis.axis_label = \"% CPU\"\n    p.extra_y_ranges = {\n        \"memory\": Range1d(\n            *fix_bounds(min(mem) if mem else 0, max(mem) if mem else 100, 100)\n        )\n    }\n    p.line(\n        t,\n        mem,\n        color=colors[2],\n        y_range_name=\"memory\",\n        line_width=4,\n        legend_label=\"Memory\",\n    )\n    p.add_layout(LinearAxis(y_range_name=\"memory\", axis_label=\"Memory (MB)\"), \"right\")\n    p.xaxis.axis_label = \"Time (s)\"\n    return p\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 541,
        "n_words": 190,
        "vocab_size": 124,
        "complexity": 10,
        "nloc": 59,
        "token_counts": 378,
        "n_ast_nodes": 615,
        "n_identifiers": 51,
        "d_id": 36429,
        "documentation": {
            "docstring": "Plot resource usage in a bokeh plot.\n\n    Parameters\n    ----------\n    results : sequence\n        Output of ResourceProfiler.results\n    palette : string, optional\n        Name of the bokeh palette to use, must be a member of\n        bokeh.palettes.all_palettes.\n    **kwargs\n        Other keyword arguments, passed to bokeh.figure. These will override\n        all defaults set by plot_resources.\n\n    Returns\n    -------\n    The completed bokeh plot object.\n    ",
            "n_words": 54,
            "vocab_size": 46,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 64660,
        "commit_id": "3eb5440aa968960528379930cc3c2ba4a4ee544a",
        "repo": "erpnext",
        "path": "erpnext/accounts/report/sales_payment_summary/sales_payment_summary.py",
        "file_name": "sales_payment_summary.py",
        "fun_name": "get_mode_of_payment_details",
        "commit_message": "fix: linters erros on report sales payments summary (#30345)\n\n* fix: wrong values for report and get change amout based on payment TYPE.\r\n\r\n* charcase for select field.\r\n\r\n* fix: linter check erros\r\n\r\n* fix: linters errors\r\n\r\nCo-authored-by: Ankush Menat <ankush@frappe.io>",
        "code": "def get_mode_of_payment_details(filters):\n\tmode_of_payment_details = {}\n\tinvoice_list = get_invoices(filters)\n\tinvoice_list_names = \",\".join('\"' + invoice['name'] + '\"' for invoice in invoice_list)\n\tif invoice_list:\n\t\tinv_mop_detail = frappe.db.sql(.format(invoice_list_names=invoice_list_names), as_dict=1)\n\n\t\tinv_change_amount = frappe.db.sql(.format(invoice_list_names=invoice_list_names), as_dict=1)\n\n\t\tfor d in inv_change_amount:\n\t\t\tfor det in inv_mop_detail:\n\t\t\t\tif det[\"owner\"] == d[\"owner\"] and det[\"posting_date\"] == d[\"posting_date\"] and det[\"mode_of_payment\"] == d[\"mode_of_payment\"]:\n\t\t\t\t\tpaid_amount = det[\"paid_amount\"] - d[\"change_amount\"]\n\t\t\t\t\tdet[\"paid_amount\"] = paid_amount\n\n\t\tfor d in inv_mop_detail:\n\t\t\tmode_of_payment_details.setdefault(d[\"owner\"]+cstr(d[\"posting_date\"]), []).append((d.mode_of_payment,d.paid_amount))\n\n\treturn mode_of_payment_details\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 50,
        "n_words": 65,
        "vocab_size": 41,
        "complexity": 9,
        "nloc": 55,
        "token_counts": 177,
        "n_ast_nodes": 299,
        "n_identifiers": 22,
        "d_id": 13689,
        "documentation": {
            "docstring": "\n\t\t\tselect t.owner,\n\t\t\t       t.posting_date,\n\t\t\t\t   t.mode_of_payment,\n\t\t\t\t   sum(t.paid_amount) as paid_amount\n\t\t\tfrom (\n\t\t\t\tselect a.owner, a.posting_date,\n\t\t\t\tifnull(b.mode_of_payment, '') as mode_of_payment, sum(b.base_amount) as paid_amount\n\t\t\t\tfrom `tabSales Invoice` a, `tabSales Invoice Payment` b\n\t\t\t\twhere a.name = b.parent\n\t\t\t\tand a.docstatus = 1\n\t\t\t\tand a.name in ({invoice_list_names})\n\t\t\t\tgroup by a.owner, a.posting_date, mode_of_payment\n\t\t\t\tunion\n\t\t\t\tselect a.owner,a.posting_date,\n\t\t\t\tifnull(b.mode_of_payment, '') as mode_of_payment, sum(c.allocated_amount) as paid_amount\n\t\t\t\tfrom `tabSales Invoice` a, `tabPayment Entry` b,`tabPayment Entry Reference` c\n\t\t\t\twhere a.name = c.reference_name\n\t\t\t\tand b.name = c.parent\n\t\t\t\tand b.docstatus = 1\n\t\t\t\tand a.name in ({invoice_list_names})\n\t\t\t\tgroup by a.owner, a.posting_date, mode_of_payment\n\t\t\t\tunion\n\t\t\t\tselect a.owner, a.posting_date,\n\t\t\t\tifnull(a.voucher_type,'') as mode_of_payment, sum(b.credit)\n\t\t\t\tfrom `tabJournal Entry` a, `tabJournal Entry Account` b\n\t\t\t\twhere a.name = b.parent\n\t\t\t\tand a.docstatus = 1\n\t\t\t\tand b.reference_type = \"Sales Invoice\"\n\t\t\t\tand b.reference_name in ({invoice_list_names})\n\t\t\t\tgroup by a.owner, a.posting_date, mode_of_payment\n\t\t\t) t\n\t\t\tgroup by t.owner, t.posting_date, t.mode_of_payment\n\t\t\tselect a.owner, a.posting_date,\n\t\t\tifnull(b.mode_of_payment, '') as mode_of_payment, sum(a.base_change_amount) as change_amount\n\t\t\tfrom `tabSales Invoice` a, `tabSales Invoice Payment` b\n\t\t\twhere a.name = b.parent\n\t\t\tand a.name in ({invoice_list_names})\n\t\t\tand b.type = 'Cash'\n\t\t\tand a.base_change_amount > 0\n\t\t\tgroup by a.owner, a.posting_date, mode_of_payment",
            "n_words": 169,
            "vocab_size": 64,
            "n_whitespaces": 142,
            "language": "en"
        }
    },
    {
        "id": 172806,
        "commit_id": "4545f4a20d9ff90b99bbd4e3e34b6de4441d6367",
        "repo": "calibre-web",
        "path": "cps/web.py",
        "file_name": "web.py",
        "fun_name": "adv_search_text",
        "commit_message": "Better epub cover parsing with multiple cover-image items\nCode cosmetics\nrenamed variables\nrefactored xml page generation\nrefactored prepare author",
        "code": "def adv_search_text(q, include_inputs, exclude_inputs, data_value):\n    for inp in include_inputs:\n        q = q.filter(db.Books.data.any(data_value == inp))\n    for excl in exclude_inputs:\n        q = q.filter(not_(db.Books.data.any(data_value == excl)))\n    return q\n\n\n",
        "url": "https://github.com/janeczku/calibre-web.git",
        "language": "Python",
        "ast_errors": "'''",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 47,
        "n_words": 25,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 64,
        "n_ast_nodes": 206,
        "n_identifiers": 19,
        "d_id": 40820,
        "documentation": {
            "docstring": "def adv_search_extension(q, include_extension_inputs, exclude_extension_inputs):\n    for extension in include_extension_inputs:\n        q = q.filter(db.Books.data.any(db.Data.format == extension))\n    for extension in exclude_extension_inputs:\n        q = q.filter(not_(db.Books.data.any(db.Data.format == extension)))\n    return q\n\n",
            "n_words": 24,
            "vocab_size": 17,
            "n_whitespaces": 46,
            "language": "en"
        }
    },
    {
        "id": 319842,
        "commit_id": "d7f7d839f8a6b7d0378dda1e0744739748d71b9c",
        "repo": "paperless-ngx",
        "path": "src/documents/tests/test_api.py",
        "file_name": "test_api.py",
        "fun_name": "test_api_create_invalid_storage_path",
        "commit_message": "Adds invalid storage path format test",
        "code": "def test_api_create_invalid_storage_path(self):\n        \n        response = self.client.post(\n            self.ENDPOINT,\n            json.dumps(\n                {\n                    \"name\": \"Another storage path\",\n                    \"path\": \"Somewhere/{correspdent}\",\n                },\n            ),\n            content_type=\"application/json\",\n        )\n        self.assertEqual(response.status_code, 400)\n        self.assertEqual(StoragePath.objects.count(), 1)\n",
        "url": "https://github.com/paperless-ngx/paperless-ngx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 169,
        "n_words": 22,
        "vocab_size": 22,
        "complexity": 1,
        "nloc": 13,
        "token_counts": 64,
        "n_ast_nodes": 108,
        "n_identifiers": 14,
        "d_id": 117006,
        "documentation": {
            "docstring": "\n        GIVEN:\n            - API request to create a storage paths\n            - Storage path format is incorrect\n        WHEN:\n            - API is called\n        THEN:\n            - Correct HTTP 400 response\n            - No storage path is created\n        ",
            "n_words": 32,
            "vocab_size": 23,
            "n_whitespaces": 116,
            "language": "en"
        }
    },
    {
        "id": 44163,
        "commit_id": "ff3bbc3db24f9f3f4f88033d48859fb08fc3237b",
        "repo": "airflow",
        "path": "airflow/models/base.py",
        "file_name": "base.py",
        "fun_name": "resolve_template_files",
        "commit_message": "Implement enough interface for MappedOperator to be baggable (#20945)",
        "code": "def resolve_template_files(self) -> None:\n        \n        if self.template_ext:\n            for field in self.template_fields:\n                content = getattr(self, field, None)\n                if content is None:\n                    continue\n                elif isinstance(content, str) and any(content.endswith(ext) for ext in self.template_ext):\n                    env = self.get_template_env()\n                    try:\n                        setattr(self, field, env.loader.get_source(env, content)[0])  # type: ignore\n                    except Exception:\n                        self.log.exception(\"Failed to resolve template field %r\", field)\n                elif isinstance(content, list):\n                    env = self.get_template_env()\n                    for i, item in enumerate(content):\n                        if isinstance(item, str) and any(item.endswith(ext) for ext in self.template_ext):\n                            try:\n                                content[i] = env.loader.get_source(env, item)[0]  # type: ignore\n                            except Exception as e:\n                                self.log.exception(e)\n        self.prepare_template()\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 23,
        "n_whitespaces": 476,
        "n_words": 83,
        "vocab_size": 54,
        "complexity": 14,
        "nloc": 22,
        "token_counts": 189,
        "n_ast_nodes": 298,
        "n_identifiers": 26,
        "d_id": 8182,
        "documentation": {
            "docstring": "Getting the content of files for template_field / template_ext.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 245504,
        "commit_id": "af063a6f25ddae4de90646f86b2db824f3d00138",
        "repo": "mmdetection",
        "path": "mmdet/structures/bbox/box_type.py",
        "file_name": "box_type.py",
        "fun_name": "autocast_box_type",
        "commit_message": "[Refactor] Refactor pipelines with boxlist. (#8562)\n\n* Refactor pipelines and data_preprocesser by boxlist\r\n\r\n* Refactor browse_dataset.py\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* Update\r\n\r\n* update\r\n\r\n* Update\r\n\r\n* Change with_box_wrapped to with_boxlist\r\n\r\n* Fix comments\r\n\r\n* Fix commits\r\n\r\n* Update  UT",
        "code": "def autocast_box_type(dst_box_type='hbox') -> Callable:\n    \n    _, box_type_cls = get_box_type(dst_box_type)\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 14,
        "n_words": 8,
        "vocab_size": 8,
        "complexity": 1,
        "nloc": 18,
        "token_counts": 22,
        "n_ast_nodes": 34,
        "n_identifiers": 6,
        "d_id": 70810,
        "documentation": {
            "docstring": "A decorator which automatically casts results['gt_bboxes'] to the\n    destination box type.\n\n    It commenly used in mmdet.datasets.transforms to make the transforms up-\n    compatible with the np.ndarray type of results['gt_bboxes'].\n\n    The speed of processing of np.ndarray and BaseBoxes data are the same:\n\n    - np.ndarray: 0.0509 img/s\n    - BaseBoxes: 0.0551 img/s\n\n    Args:\n        dst_box_type (str): Destination box type.\n    ",
            "n_words": 54,
            "vocab_size": 43,
            "n_whitespaces": 85,
            "language": "en"
        }
    },
    {
        "id": 206055,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/http/multipartparser.py",
        "file_name": "multipartparser.py",
        "fun_name": "__next__",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def __next__(self):\n        \n        if self._leftover:\n            output = self._leftover\n            self._leftover = b\"\"\n        else:\n            output = next(self._producer)\n            self._unget_history = []\n        self.position += len(output)\n        return output\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 101,
        "n_words": 22,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 48,
        "n_ast_nodes": 82,
        "n_identifiers": 9,
        "d_id": 51343,
        "documentation": {
            "docstring": "\n        Used when the exact number of bytes to read is unimportant.\n\n        Return whatever chunk is conveniently returned from the iterator.\n        Useful to avoid unnecessary bookkeeping if performance is an issue.\n        ",
            "n_words": 30,
            "vocab_size": 26,
            "n_whitespaces": 59,
            "language": "en"
        }
    },
    {
        "id": 265205,
        "commit_id": "fcd1daaf798d62023f999c3e09e035f7b3f47c8f",
        "repo": "netbox",
        "path": "netbox/dcim/models/racks.py",
        "file_name": "racks.py",
        "fun_name": "get_power_utilization",
        "commit_message": "Update power utilization calculations for new cabling model",
        "code": "def get_power_utilization(self):\n        \n        powerfeeds = PowerFeed.objects.filter(rack=self)\n        available_power_total = sum(pf.available_power for pf in powerfeeds)\n        print(f'available_power_total: {available_power_total}')\n        if not available_power_total:\n            return 0\n\n        powerports = []\n        for powerfeed in powerfeeds:\n            powerports.extend([\n                peer for peer in powerfeed.link_peers if isinstance(peer, PowerPort)\n            ])\n\n        allocated_draw = 0\n        for powerport in powerports:\n            allocated_draw += powerport.get_power_draw()['allocated']\n        print(f'allocated_draw: {allocated_draw}')\n\n        return int(allocated_draw / available_power_total * 100)\n\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 190,
        "n_words": 54,
        "vocab_size": 39,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 103,
        "n_ast_nodes": 175,
        "n_identifiers": 23,
        "d_id": 78027,
        "documentation": {
            "docstring": "\n        Determine the utilization rate of power in the rack and return it as a percentage.\n        ",
            "n_words": 15,
            "vocab_size": 14,
            "n_whitespaces": 30,
            "language": "en"
        }
    },
    {
        "id": 176658,
        "commit_id": "26b7de005ac562786f72b24a73af5a59bbab6953",
        "repo": "networkx",
        "path": "networkx/algorithms/connectivity/edge_augmentation.py",
        "file_name": "edge_augmentation.py",
        "fun_name": "k_edge_augmentation",
        "commit_message": "doc: fix typos in docstring and comment (#5647)",
        "code": "def k_edge_augmentation(G, k, avail=None, weight=None, partial=False):\n    \n    try:\n        if k <= 0:\n            raise ValueError(f\"k must be a positive integer, not {k}\")\n        elif G.number_of_nodes() < k + 1:\n            msg = f\"impossible to {k} connect in graph with less than {k + 1} nodes\"\n            raise nx.NetworkXUnfeasible(msg)\n        elif avail is not None and len(avail) == 0:\n            if not nx.is_k_edge_connected(G, k):\n                raise nx.NetworkXUnfeasible(\"no available edges\")\n            aug_edges = []\n        elif k == 1:\n            aug_edges = one_edge_augmentation(\n                G, avail=avail, weight=weight, partial=partial\n            )\n        elif k == 2:\n            aug_edges = bridge_augmentation(G, avail=avail, weight=weight)\n        else:\n            # raise NotImplementedError(f'not implemented for k>2. k={k}')\n            aug_edges = greedy_k_edge_augmentation(\n                G, k=k, avail=avail, weight=weight, seed=0\n            )\n        # Do eager evaulation so we can catch any exceptions\n        # Before executing partial code.\n        yield from list(aug_edges)\n    except nx.NetworkXUnfeasible:\n        if partial:\n            # Return all available edges\n            if avail is None:\n                aug_edges = complement_edges(G)\n            else:\n                # If we can't k-edge-connect the entire graph, try to\n                # k-edge-connect as much as possible\n                aug_edges = partial_k_edge_augmentation(\n                    G, k=k, avail=avail, weight=weight\n                )\n            yield from aug_edges\n        else:\n            raise\n\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
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        "ast_levels": 17,
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        "complexity": 11,
        "nloc": 33,
        "token_counts": 207,
        "n_ast_nodes": 342,
        "n_identifiers": 21,
        "d_id": 42026,
        "documentation": {
            "docstring": "Finds set of edges to k-edge-connect G.\n\n    Adding edges from the augmentation to G make it impossible to disconnect G\n    unless k or more edges are removed. This function uses the most efficient\n    function available (depending on the value of k and if the problem is\n    weighted or unweighted) to search for a minimum weight subset of available\n    edges that k-edge-connects G. In general, finding a k-edge-augmentation is\n    NP-hard, so solutions are not guaranteed to be minimal. Furthermore, a\n    k-edge-augmentation may not exist.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n       An undirected graph.\n\n    k : integer\n        Desired edge connectivity\n\n    avail : dict or a set of 2 or 3 tuples\n        The available edges that can be used in the augmentation.\n\n        If unspecified, then all edges in the complement of G are available.\n        Otherwise, each item is an available edge (with an optional weight).\n\n        In the unweighted case, each item is an edge ``(u, v)``.\n\n        In the weighted case, each item is a 3-tuple ``(u, v, d)`` or a dict\n        with items ``(u, v): d``.  The third item, ``d``, can be a dictionary\n        or a real number.  If ``d`` is a dictionary ``d[weight]``\n        correspondings to the weight.\n\n    weight : string\n        key to use to find weights if ``avail`` is a set of 3-tuples where the\n        third item in each tuple is a dictionary.\n\n    partial : boolean\n        If partial is True and no feasible k-edge-augmentation exists, then all\n        a partial k-edge-augmentation is generated. Adding the edges in a\n        partial augmentation to G, minimizes the number of k-edge-connected\n        components and maximizes the edge connectivity between those\n        components. For details, see :func:`partial_k_edge_augmentation`.\n\n    Yields\n    ------\n    edge : tuple\n        Edges that, once added to G, would cause G to become k-edge-connected.\n        If partial is False, an error is raised if this is not possible.\n        Otherwise, generated edges form a partial augmentation, which\n        k-edge-connects any part of G where it is possible, and maximally\n        connects the remaining parts.\n\n    Raises\n    ------\n    NetworkXUnfeasible\n        If partial is False and no k-edge-augmentation exists.\n\n    NetworkXNotImplemented\n        If the input graph is directed or a multigraph.\n\n    ValueError:\n        If k is less than 1\n\n    Notes\n    -----\n    When k=1 this returns an optimal solution.\n\n    When k=2 and ``avail`` is None, this returns an optimal solution.\n    Otherwise when k=2, this returns a 2-approximation of the optimal solution.\n\n    For k>3, this problem is NP-hard and this uses a randomized algorithm that\n        produces a feasible solution, but provides no guarantees on the\n        solution weight.\n\n    Examples\n    --------\n    >>> # Unweighted cases\n    >>> G = nx.path_graph((1, 2, 3, 4))\n    >>> G.add_node(5)\n    >>> sorted(nx.k_edge_augmentation(G, k=1))\n    [(1, 5)]\n    >>> sorted(nx.k_edge_augmentation(G, k=2))\n    [(1, 5), (5, 4)]\n    >>> sorted(nx.k_edge_augmentation(G, k=3))\n    [(1, 4), (1, 5), (2, 5), (3, 5), (4, 5)]\n    >>> complement = list(nx.k_edge_augmentation(G, k=5, partial=True))\n    >>> G.add_edges_from(complement)\n    >>> nx.edge_connectivity(G)\n    4\n\n    >>> # Weighted cases\n    >>> G = nx.path_graph((1, 2, 3, 4))\n    >>> G.add_node(5)\n    >>> # avail can be a tuple with a dict\n    >>> avail = [(1, 5, {\"weight\": 11}), (2, 5, {\"weight\": 10})]\n    >>> sorted(nx.k_edge_augmentation(G, k=1, avail=avail, weight=\"weight\"))\n    [(2, 5)]\n    >>> # or avail can be a 3-tuple with a real number\n    >>> avail = [(1, 5, 11), (2, 5, 10), (4, 3, 1), (4, 5, 51)]\n    >>> sorted(nx.k_edge_augmentation(G, k=2, avail=avail))\n    [(1, 5), (2, 5), (4, 5)]\n    >>> # or avail can be a dict\n    >>> avail = {(1, 5): 11, (2, 5): 10, (4, 3): 1, (4, 5): 51}\n    >>> sorted(nx.k_edge_augmentation(G, k=2, avail=avail))\n    [(1, 5), (2, 5), (4, 5)]\n    >>> # If augmentation is infeasible, then a partial solution can be found\n    >>> avail = {(1, 5): 11}\n    >>> sorted(nx.k_edge_augmentation(G, k=2, avail=avail, partial=True))\n    [(1, 5)]\n    ",
            "n_words": 592,
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    {
        "id": 208657,
        "commit_id": "a9b523c7047fe12c49373972c6b092ed5fc29e99",
        "repo": "ipython",
        "path": "IPython/sphinxext/ipython_directive.py",
        "file_name": "ipython_directive.py",
        "fun_name": "block_parser",
        "commit_message": "match only pseudo-decorators",
        "code": "def block_parser(part, rgxin, rgxout, fmtin, fmtout):\n    \n    block = []\n    lines = part.split('\\n')\n    N = len(lines)\n    i = 0\n    decorator = None\n    while 1:\n\n        if i==N:\n            # nothing left to parse -- the last line\n            break\n\n        line = lines[i]\n        i += 1\n        line_stripped = line.strip()\n        if line_stripped.startswith('#'):\n            block.append((COMMENT, line))\n            continue\n\n        if any(\n            line_stripped.startswith('@' + pseudo_decorator) for pseudo_decorator in PSEUDO_DECORATORS\n        ):                \n            if decorator:\n                raise RuntimeError(\"Applying multiple pseudo-decorators on one line is not supported\")\n            else:\n                decorator = line_stripped\n                continue\n\n        # does this look like an input line?\n        matchin = rgxin.match(line)\n        if matchin:\n            lineno, inputline = int(matchin.group(1)), matchin.group(2)\n\n            # the ....: continuation string\n            continuation = '   %s:'%''.join(['.']*(len(str(lineno))+2))\n            Nc = len(continuation)\n            # input lines can continue on for more than one line, if\n            # we have a '\\' line continuation char or a function call\n            # echo line 'print'.  The input line can only be\n            # terminated by the end of the block or an output line, so\n            # we parse out the rest of the input line if it is\n            # multiline as well as any echo text\n\n            rest = []\n            while i<N:\n\n                # look ahead; if the next line is blank, or a comment, or\n                # an output line, we're done\n\n                nextline = lines[i]\n                matchout = rgxout.match(nextline)\n                #print \"nextline=%s, continuation=%s, starts=%s\"%(nextline, continuation, nextline.startswith(continuation))\n                if matchout or nextline.startswith('#'):\n                    break\n                elif nextline.startswith(continuation):\n                    # The default ipython_rgx* treat the space following the colon as optional.\n                    # However, If the space is there we must consume it or code\n                    # employing the cython_magic extension will fail to execute.\n                    #\n                    # This works with the default ipython_rgx* patterns,\n                    # If you modify them, YMMV.\n                    nextline = nextline[Nc:]\n                    if nextline and nextline[0] == ' ':\n                        nextline = nextline[1:]\n\n                    inputline += '\\n' +  nextline\n                else:\n                    rest.append(nextline)\n                i+= 1\n\n            block.append((INPUT, (decorator, inputline, '\\n'.join(rest))))\n            continue\n\n        # if it looks like an output line grab all the text to the end\n        # of the block\n        matchout = rgxout.match(line)\n        if matchout:\n            lineno, output = int(matchout.group(1)), matchout.group(2)\n            if i<N-1:\n                output = '\\n'.join([output] + lines[i:])\n\n            block.append((OUTPUT, output))\n            break\n\n    return block\n\n",
        "url": "https://github.com/ipython/ipython.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 52443,
        "documentation": {
            "docstring": "\n    part is a string of ipython text, comprised of at most one\n    input, one output, comments, and blank lines.  The block parser\n    parses the text into a list of::\n\n      blocks = [ (TOKEN0, data0), (TOKEN1, data1), ...]\n\n    where TOKEN is one of [COMMENT | INPUT | OUTPUT ] and\n    data is, depending on the type of token::\n\n      COMMENT : the comment string\n\n      INPUT: the (DECORATOR, INPUT_LINE, REST) where\n         DECORATOR: the input decorator (or None)\n         INPUT_LINE: the input as string (possibly multi-line)\n         REST : any stdout generated by the input line (not OUTPUT)\n\n      OUTPUT: the output string, possibly multi-line\n\n    ",
            "n_words": 98,
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            "language": "en"
        }
    },
    {
        "id": 113264,
        "commit_id": "97d067e614243f06ed1f8e2d389512977fff8828",
        "repo": "nni",
        "path": "nni/compression/pytorch/speedup/compressor.py",
        "file_name": "compressor.py",
        "fun_name": "update_direct_sparsity",
        "commit_message": "Speedup enhancement (#4925)",
        "code": "def update_direct_sparsity(self, node):\n        \n        # this name is consistent with the name returned by named_modules()\n        module_name = node.name\n        _logger.info('Update mask for %s', module_name)\n        unique_name = node.unique_name\n        dummy_input, input_debugname = self._prepare_dummy_input(node)\n        # get the input mask from self.masks\n        # Note: the input mask of the successor nodes are\n        # already created by the predecessor node\n        in_masks = [self.masks[debugname] for debugname in input_debugname]\n        in_constants = [self.constant[debugname]\n                        for debugname in input_debugname]\n        if node.type == 'func':\n            # we cannot get the runable function directly from the jit traced\n            # graph, so we translate it back to python function, Note: the function\n            # is appliable to both cpu/gpu devices, the output tensors will be on the\n            # same device of the input tensors\n            func = jit_to_python_function(node, self)\n            if func is None:\n                # no need to infer the sparsity for this node\n                self.auto_inferences[unique_name] = None\n                return\n            # function doesn't have weights\n            _auto_infer = AutoMaskInference(\n                func, dummy_input, self, in_masks, in_constants=in_constants)\n        else:\n            weight_mask = None\n            if module_name in self.masks:\n                weight_mask = self.masks[module_name]\n            _, module = get_module_by_name(self.bound_model, module_name)\n            _auto_infer = AutoMaskInference(\n                module, dummy_input, self, in_masks, weight_mask, in_constants=in_constants,\n                state_dict=copy.deepcopy(module.state_dict()))\n        self.auto_inferences[unique_name] = _auto_infer\n        _auto_infer.name = node.unique_name\n\n        _auto_infer.update_direct_sparsity()\n        # also save the input debug names into the auto_infer\n        _auto_infer.input_debugname = input_debugname\n        # update the mask tensor and the internal output of the submodules\n        # after manually unpack the tuple/list of tensors, the number of the outputs\n        # of each node should always be one(Except for the TupleUnpack node at the end\n        # of the whole model)\n        assert len(\n            node.outputs) == 1, 'The number of the output should be one after the Tuple unpacked manually'\n\n        out_debugname = node.outputs[0]\n        # update the output mask into self.masks\n        self.masks[out_debugname] = _auto_infer.output_mask\n        self.constant[out_debugname] = _auto_infer.out_constant\n        # update the output result into self.internal_result, so that\n        # the successor nodes can take these output tensors as inputs.\n        self.internal_result[out_debugname] = _auto_infer.output\n        # update the parameter mask of the node\n\n        self.masks[module_name] = _auto_infer.weight_mask\n",
        "url": "https://github.com/microsoft/nni.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 806,
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        "token_counts": 256,
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        "d_id": 24873,
        "documentation": {
            "docstring": "\n        Update the direct sparsity for the target node. Here the direct sparsity\n        means that the sparsity in the output tensor that caused by the sparsity\n        in the input tensors/weight tensors.\n        ",
            "n_words": 30,
            "vocab_size": 18,
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            "language": "en"
        }
    },
    {
        "id": 177122,
        "commit_id": "9b63ca1a0d46a1f50bcc59eda52be02721a134db",
        "repo": "networkx",
        "path": "networkx/readwrite/graph6.py",
        "file_name": "graph6.py",
        "fun_name": "read_graph6",
        "commit_message": "Remove old Appveyor cruft (#5924)\n\n* Remove old Appveyor cruft\r\n\r\n* Fix Windows issue",
        "code": "def read_graph6(path):\n    \n    glist = []\n    for line in path:\n        line = line.strip()\n        if not len(line):\n            continue\n        glist.append(from_graph6_bytes(line))\n    if len(glist) == 1:\n        return glist[0]\n    else:\n        return glist\n\n\n@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")\n@open_file(1, mode=\"wb\")",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "@not_implemented_for(\"directed\")\n@not_implemented_for(\"multigraph\")\n@open_file(1, mode=\"wb\")",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 88,
        "n_words": 30,
        "vocab_size": 25,
        "complexity": 4,
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        "token_counts": 56,
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        "n_identifiers": 11,
        "d_id": 42277,
        "documentation": {
            "docstring": "Read simple undirected graphs in graph6 format from path.\n\n    Parameters\n    ----------\n    path : file or string\n       File or filename to write.\n\n    Returns\n    -------\n    G : Graph or list of Graphs\n       If the file contains multiple lines then a list of graphs is returned\n\n    Raises\n    ------\n    NetworkXError\n        If the string is unable to be parsed in graph6 format\n\n    Examples\n    --------\n    You can read a graph6 file by giving the path to the file::\n\n        >>> import tempfile\n        >>> with tempfile.NamedTemporaryFile(delete=False) as f:\n        ...     _ = f.write(b\">>graph6<<A_\\\\n\")\n        ...     _ = f.seek(0)\n        ...     G = nx.read_graph6(f.name)\n        >>> list(G.edges())\n        [(0, 1)]\n\n    You can also read a graph6 file by giving an open file-like object::\n\n        >>> import tempfile\n        >>> with tempfile.NamedTemporaryFile() as f:\n        ...     _ = f.write(b\">>graph6<<A_\\\\n\")\n        ...     _ = f.seek(0)\n        ...     G = nx.read_graph6(f)\n        >>> list(G.edges())\n        [(0, 1)]\n\n    See Also\n    --------\n    from_graph6_bytes, write_graph6\n\n    References\n    ----------\n    .. [1] Graph6 specification\n           <http://users.cecs.anu.edu.au/~bdm/data/formats.html>\n\n    ",
            "n_words": 145,
            "vocab_size": 83,
            "n_whitespaces": 356,
            "language": "en"
        }
    },
    {
        "id": 21253,
        "commit_id": "2f6a04b89a70879f40a42d7d2ce662468f6e87ca",
        "repo": "pipenv",
        "path": "pipenv/vendor/requirementslib/models/utils.py",
        "file_name": "utils.py",
        "fun_name": "split_ref_from_uri",
        "commit_message": "5132 Vendor in latest requirementslib. (#5151)\n\n* 5132 Vendor in latest requirementslib.",
        "code": "def split_ref_from_uri(uri):\n    # type: (AnyStr) -> Tuple[AnyStr, Optional[AnyStr]]\n    \n    if not isinstance(uri, str):\n        raise TypeError(\"Expected a string, received {0!r}\".format(uri))\n    parsed = _get_parsed_url(uri)\n    path = parsed.path if parsed.path else \"\"\n    scheme = parsed.scheme if parsed.scheme else \"\"\n    ref = None\n    if scheme != \"file\" and (re.match(\"^.*@[^/@]*$\", path) or path.count(\"@\") >= 2):\n        path, _, ref = path.rpartition(\"@\")\n    parsed = parsed._replace(path=path)\n    return (parsed.url, ref)\n\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "token_counts": 111,
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        "n_identifiers": 18,
        "d_id": 3737,
        "documentation": {
            "docstring": "Given a path or URI, check for a ref and split it from the path if it is\n    present, returning a tuple of the original input and the ref or None.\n\n    :param AnyStr uri: The path or URI to split\n    :returns: A 2-tuple of the path or URI and the ref\n    :rtype: Tuple[AnyStr, Optional[AnyStr]]\n    ",
            "n_words": 54,
            "vocab_size": 34,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 292229,
        "commit_id": "beb30a1ff199596163c655e8ae745a0f1649b78a",
        "repo": "core",
        "path": "tests/components/google_travel_time/test_sensor.py",
        "file_name": "test_sensor.py",
        "fun_name": "mock_update_duration_fixture",
        "commit_message": "Add google_travel_time sensor tests (#66568)\n\nCo-authored-by: Paulus Schoutsen <paulus@home-assistant.io>",
        "code": "def mock_update_duration_fixture(mock_update):\n    \n    mock_update.return_value = {\n        \"rows\": [\n            {\n                \"elements\": [\n                    {\n                        \"duration\": {\n                            \"value\": 1560,\n                            \"text\": \"26 mins\",\n                        },\n                        \"distance\": {\"text\": \"21.3 km\"},\n                    }\n                ]\n            }\n        ]\n    }\n    yield mock_update\n\n\n@pytest.fixture(name=\"mock_update_empty\")",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.fixture(name=\"mock_update_empty\")",
        "n_ast_errors": 1,
        "ast_levels": 17,
        "n_whitespaces": 269,
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        "n_identifiers": 6,
        "d_id": 91329,
        "documentation": {
            "docstring": "Mock an update to the sensor returning no duration_in_traffic.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 288842,
        "commit_id": "f23b1750e85f07091eb896a0b12b8f95e5646338",
        "repo": "core",
        "path": "homeassistant/components/homekit_controller/connection.py",
        "file_name": "connection.py",
        "fun_name": "async_process_entity_map",
        "commit_message": "Migrate HomeKit Controller to use stable identifiers (#80064)",
        "code": "async def async_process_entity_map(self) -> None:\n        \n        # Ensure the Pairing object has access to the latest version of the entity map. This\n        # is especially important for BLE, as the Pairing instance relies on the entity map\n        # to map aid/iid to GATT characteristics. So push it to there as well.\n        self.async_detect_workarounds()\n\n        # Migrate to new device ids\n        self.async_migrate_devices()\n\n        # Remove any of the legacy serial numbers from the device registry\n        self.async_remove_legacy_device_serial_numbers()\n\n        self.async_create_devices()\n\n        # Load any triggers for this config entry\n        await async_setup_triggers_for_entry(self.hass, self.config_entry)\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
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        "n_identifiers": 9,
        "d_id": 87991,
        "documentation": {
            "docstring": "\n        Process the entity map and load any platforms or entities that need adding.\n\n        This is idempotent and will be called at startup and when we detect metadata changes\n        via the c# counter on the zeroconf record.\n        ",
            "n_words": 36,
            "vocab_size": 32,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 320956,
        "commit_id": "660e776a15c02f5577d7aca075bb0e3f8b142831",
        "repo": "qutebrowser",
        "path": "scripts/dev/build_release.py",
        "file_name": "build_release.py",
        "fun_name": "patch_mac_app",
        "commit_message": "build-release: Sign macOS .app properly\n\nBased on https://github.com/pyinstaller/pyinstaller/issues/6612\nMight help with #6771.",
        "code": "def patch_mac_app() -> None:\n    \n    dist_path = pathlib.Path('dist')\n    app_path = dist_path / 'qutebrowser.app'\n\n    contents_path = app_path / 'Contents'\n    macos_path = contents_path / 'MacOS'\n    resources_path = contents_path / 'Resources'\n    pyqt_path = macos_path / 'PyQt5'\n\n    # Replace some duplicate files by symlinks\n    framework_path = pyqt_path / 'Qt5' / 'lib' / 'QtWebEngineCore.framework'\n\n    core_lib = framework_path / 'Versions' / '5' / 'QtWebEngineCore'\n    core_lib.unlink()\n    core_target = pathlib.Path(*[os.pardir] * 7, 'MacOS', 'QtWebEngineCore')\n    core_lib.symlink_to(core_target)\n\n    framework_resource_path = framework_path / 'Resources'\n    for file_path in framework_resource_path.iterdir():\n        target = pathlib.Path(*[os.pardir] * 5, file_path.name)\n        if file_path.is_dir():\n            shutil.rmtree(file_path)\n        else:\n            file_path.unlink()\n        file_path.symlink_to(target)\n\n    # Move stuff around to make things signable on macOS\n    # See https://github.com/pyinstaller/pyinstaller/issues/6612\n    pyqt_path_dest = resources_path / pyqt_path.name\n    shutil.move(pyqt_path, pyqt_path_dest)\n    pyqt_path_target = pathlib.Path(\"..\") / pyqt_path_dest.relative_to(contents_path)\n    pyqt_path.symlink_to(pyqt_path_target)\n\n    for path in macos_path.glob(\"Qt*\"):\n        link_path = resources_path / path.name\n        target_path = pathlib.Path(\"..\") / path.relative_to(contents_path)\n        link_path.symlink_to(target_path)\n\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 265,
        "n_words": 128,
        "vocab_size": 81,
        "complexity": 4,
        "nloc": 29,
        "token_counts": 221,
        "n_ast_nodes": 395,
        "n_identifiers": 32,
        "d_id": 117462,
        "documentation": {
            "docstring": "Patch .app to save some space and make it signable.",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 243427,
        "commit_id": "279ddf4ce6c76498ac29df2552a3023b9aaa76c1",
        "repo": "Pillow",
        "path": "src/PIL/ImageOps.py",
        "file_name": "ImageOps.py",
        "fun_name": "expand",
        "commit_message": "Use getpalette() in ImageOps",
        "code": "def expand(image, border=0, fill=0):\n    \n    left, top, right, bottom = _border(border)\n    width = left + image.size[0] + right\n    height = top + image.size[1] + bottom\n    color = _color(fill, image.mode)\n    if image.mode == \"P\" and image.palette:\n        palette = ImagePalette.ImagePalette(palette=image.getpalette())\n        if isinstance(color, tuple):\n            color = palette.getcolor(color)\n    else:\n        palette = None\n    out = Image.new(image.mode, (width, height), color)\n    if palette:\n        out.putpalette(palette.palette)\n    out.paste(image, (left, top))\n    return out\n\n",
        "url": "https://github.com/python-pillow/Pillow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 133,
        "n_words": 61,
        "vocab_size": 45,
        "complexity": 5,
        "nloc": 16,
        "token_counts": 149,
        "n_ast_nodes": 230,
        "n_identifiers": 26,
        "d_id": 70030,
        "documentation": {
            "docstring": "\n    Add border to the image\n\n    :param image: The image to expand.\n    :param border: Border width, in pixels.\n    :param fill: Pixel fill value (a color value).  Default is 0 (black).\n    :return: An image.\n    ",
            "n_words": 32,
            "vocab_size": 28,
            "n_whitespaces": 52,
            "language": "en"
        }
    },
    {
        "id": 135458,
        "commit_id": "30058267363b8de16b809c987bb1f7d7befad24d",
        "repo": "ray",
        "path": "rllib/core/rl_module/torch/tests/test_torch_marl_module.py",
        "file_name": "test_torch_marl_module.py",
        "fun_name": "get_policy_data_from_agent_data",
        "commit_message": "[RLlib] MARLModule, RLModule PR 4/N (N=4) (#29449)\n\nSigned-off-by: Kourosh Hakhamaneshi <kourosh@anyscale.com>",
        "code": "def get_policy_data_from_agent_data(agent_data, policy_map_fn):\n    \n    policy_data = {}\n    for agent_id, data in agent_data.items():\n        policy_id = policy_map_fn(agent_id)\n        policy_data.setdefault(policy_id, {})\n        policy_data[policy_id].setdefault(\"agent_id\", [])\n\n        if data[\"obs\"].ndim == 1:\n            policy_data[policy_id][\"agent_id\"].append(agent_id)\n        else:\n            policy_data[policy_id][\"agent_id\"] += [agent_id] * len(data[\"obs\"])\n\n        for k, v in data.items():\n            policy_data[policy_id].setdefault(k, [])\n            if v.ndim == 1:\n                v = v[None]\n            policy_data[policy_id][k].append(v)\n\n    for policy_id in policy_data:\n        policy_data[policy_id] = {\n            k: np.concatenate(v) if k != \"agent_id\" else v\n            for k, v in policy_data[policy_id].items()\n        }\n\n    return policy_data\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 230,
        "n_words": 67,
        "vocab_size": 47,
        "complexity": 8,
        "nloc": 21,
        "token_counts": 182,
        "n_ast_nodes": 291,
        "n_identifiers": 16,
        "d_id": 30625,
        "documentation": {
            "docstring": "Utility function to get policy data from agent data and policy map function.\n\n    It also keeps track of agent_id for each row so that we can retreive the agent\n    level information after the forward pass.\n\n    Returns:\n        dict of module_id to module data\n    ",
            "n_words": 42,
            "vocab_size": 35,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 44213,
        "commit_id": "bc1f062bdebd5a92b650e2316d4d98d2097388ca",
        "repo": "airflow",
        "path": "dev/assign_cherry_picked_prs_with_milestone.py",
        "file_name": "assign_cherry_picked_prs_with_milestone.py",
        "fun_name": "cli",
        "commit_message": "Add dev tool to review and classify cherry-picked commits (#21032)\n\nUntil we have Towncrier, this is a useful tool to classify commits\r\nto one of three categories (in v*-test) branches\r\n\r\n1) a/add - add to milestone\r\n2) d/doc - doc-only change\r\n3) e/excluded - change that is skipped from changelog (dev tools)\r\n\r\nThis is done via label and milestone assignment.\r\n\r\nWe can also skip the PR or quit.\r\n\r\nInformation about the PR is nicely printed including its current\r\nlabels and URL that allows to quickly review the PR in question.",
        "code": "def cli():\n    ...\n\n\noption_verbose = click.option(\n    \"--verbose\",\n    is_flag=True,\n    help=\"Print verbose information about performed steps\",\n)\n\noption_assume_yes = click.option(\n    \"--assume-yes\",\n    is_flag=True,\n    help=\"Assume yes answer to question\",\n)\n\n\noption_previous_release = click.option(\n    \"--previous-release\",\n    type=str,\n    required=True,\n    help=\"commit reference (for example hash or tag) of the previous release.\",\n)\n\noption_current_release = click.option(\n    \"--current-release\",\n    type=str,\n    required=True,\n    help=\"commit reference (for example hash or tag) of the current release.\",\n)\n\noption_github_token = click.option(\n    \"--github-token\",\n    type=str,\n    required=True,\n    help=textwrap.dedent(\n        \n    ),\n    envvar='GITHUB_TOKEN',\n)\n\noption_limit_pr_count = click.option(\n    \"--limit-pr-count\",\n    type=int,\n    default=None,\n    help=\"Limit PR count processes (useful for testing small subset of PRs).\",\n)\n\noption_dry_run = click.option(\n    \"--dry-run\",\n    is_flag=True,\n    help=\"Do not make any changes, just show what would have been done\",\n)\n\noption_skip_assigned = click.option(\n    \"--skip-assigned\",\n    is_flag=True,\n    help=\"Skip PRs already correctly assigned to the right milestone\",\n)\n\noption_milestone_number = click.option(\n    \"--milestone-number\",\n    type=int,\n    required=True,\n    help=\"Milestone number to set. See https://github.com/apache/airflow/milestones to find milestone id\",\n)\n\noption_print_summary = click.option(\n    \"--print-summary\",\n    is_flag=True,\n    help=\"Produce summary of the changes cherry-picked in the file specified. Implies --skip-assigned\",\n)\n\noption_output_folder = click.option(\n    \"--output-folder\",\n    type=str,\n    help=\"Folder where files with commit hashes will be store. Implies --print-summary and --skip-assigned\",\n)\n\n",
        "url": "https://github.com/apache/airflow.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 285,
        "n_words": 177,
        "vocab_size": 116,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 5,
        "n_ast_nodes": 358,
        "n_identifiers": 24,
        "d_id": 8197,
        "documentation": {
            "docstring": "\n        Github token used to authenticate.\n        You can set omit it if you have GITHUB_TOKEN env variable set\n        Can be generated with:\n        https://github.com/settings/tokens/new?description=Read%20Write%20isssues&scopes=repo",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 50,
            "language": "en"
        }
    },
    {
        "id": 268732,
        "commit_id": "cda16cc5e9aa8703fb4e1ac0a0be6b631d9076cc",
        "repo": "ansible",
        "path": "test/lib/ansible_test/_internal/host_profiles.py",
        "file_name": "host_profiles.py",
        "fun_name": "delete_systemd_cgroup_v1",
        "commit_message": "ansible-test - Improve container management. (#78550)\n\nSee changelogs/fragments/ansible-test-container-management.yml for details.",
        "code": "def delete_systemd_cgroup_v1(self) -> None:\n        \n        # Privileged mode is required to remove the cgroup directories on some hosts, such as Fedora 36 and RHEL 9.0.\n        # The BusyBox find utility will report \"Permission denied\" otherwise, although it still exits with a status code of 0.\n        options = ['--volume', '/sys/fs/cgroup/systemd:/sys/fs/cgroup/systemd:rw', '--privileged']\n        cmd = ['sh', '-c', f'>&2 echo {shlex.quote(self.MARKER)} && {shlex.join(self.delete_systemd_cgroup_v1_command)}']\n\n        try:\n            run_utility_container(self.args, f'ansible-test-cgroup-delete-{self.label}', cmd, options)\n        except SubprocessError as ex:\n            if error := self.extract_error(ex.stderr):\n                if error.endswith(': No such file or directory'):\n                    return\n\n            display.error(str(ex))\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 196,
        "n_words": 80,
        "vocab_size": 75,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 77,
        "n_ast_nodes": 173,
        "n_identifiers": 20,
        "d_id": 79632,
        "documentation": {
            "docstring": "Delete a previously created ansible-test cgroup in the v1 systemd hierarchy.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 248927,
        "commit_id": "0b87eb8e0c8e2dd4a426005dce53dfdd57282475",
        "repo": "synapse",
        "path": "synapse/util/caches/treecache.py",
        "file_name": "treecache.py",
        "fun_name": "iterate_tree_cache_items",
        "commit_message": "Make DictionaryCache have better expiry properties (#13292)",
        "code": "def iterate_tree_cache_items(key, value):\n    \n    if isinstance(value, TreeCacheNode):\n        for sub_key, sub_value in value.items():\n            yield from iterate_tree_cache_items((*key, sub_key), sub_value)\n    else:\n        # we've reached a leaf of the tree.\n        yield key, value\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 69,
        "n_words": 28,
        "vocab_size": 27,
        "complexity": 3,
        "nloc": 6,
        "token_counts": 46,
        "n_ast_nodes": 75,
        "n_identifiers": 8,
        "d_id": 72514,
        "documentation": {
            "docstring": "Helper function to iterate over the leaves of a tree, i.e. a dict of that\n    can contain dicts.\n\n    The provided key is a tuple that will get prepended to the returned keys.\n\n    Example:\n\n        cache = TreeCache()\n        cache[(1, 1)] = \"a\"\n        cache[(1, 2)] = \"b\"\n        cache[(2, 1)] = \"c\"\n\n        tree_node = cache.get((1,))\n\n        items = iterate_tree_cache_items((1,), tree_node)\n        assert list(items) == [((1, 1), \"a\"), ((1, 2), \"b\")]\n\n    Returns:\n        A generator yielding key/value pairs.\n    ",
            "n_words": 70,
            "vocab_size": 57,
            "n_whitespaces": 141,
            "language": "en"
        }
    },
    {
        "id": 268880,
        "commit_id": "b4dca51d0558e788f62a96d1009a07f773a202f4",
        "repo": "keras",
        "path": "keras/metrics/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "deserialize",
        "commit_message": "Refactor disparate metrics-related files into a single metrics folder.\n\nFurther work may be needed to split up the long file with individual metric definitions. However having a single file per metric may be too granular. TBD.\n\nPiperOrigin-RevId: 425248502",
        "code": "def deserialize(config, custom_objects=None):\n  \n  return deserialize_keras_object(\n      config,\n      module_objects=globals(),\n      custom_objects=custom_objects,\n      printable_module_name='metric function')\n\n\n@keras_export('keras.metrics.get')",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export('keras.metrics.get')",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 32,
        "n_words": 11,
        "vocab_size": 11,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 29,
        "n_ast_nodes": 58,
        "n_identifiers": 8,
        "d_id": 79747,
        "documentation": {
            "docstring": "Deserializes a serialized metric class/function instance.\n\n  Args:\n    config: Metric configuration.\n    custom_objects: Optional dictionary mapping names (strings) to custom\n      objects (classes and functions) to be considered during deserialization.\n\n  Returns:\n      A Keras `Metric` instance or a metric function.\n  ",
            "n_words": 36,
            "vocab_size": 33,
            "n_whitespaces": 55,
            "language": "en"
        }
    },
    {
        "id": 39444,
        "commit_id": "1d7341e93d1f03387699fb3c6ae0b6c0e464296f",
        "repo": "recommenders",
        "path": "recommenders/utils/python_utils.py",
        "file_name": "python_utils.py",
        "fun_name": "get_top_k_scored_items",
        "commit_message": "Add new item similarity metrics for SAR (#1754)\n\n* Add mutual information similarity in SAR\r\n\r\n* Add lexicographers mutual information similarity for SAR\r\n\r\n* Add cosine similarity for SAR\r\n\r\n* Add inclusion index for SAR\r\n\r\n* Typos\r\n\r\n* Change SARSingleNode to SAR\r\n\r\n* Convert item similarity matrix to np.array\r\n\r\n* Update\r\n\r\n* Update SAR tests\r\n\r\n* Remove unused imports\r\n\r\n* Add explanations for new similarity metrics",
        "code": "def get_top_k_scored_items(scores, top_k, sort_top_k=False):\n    \n\n    # ensure we're working with a dense ndarray\n    if isinstance(scores, sparse.spmatrix):\n        scores = scores.todense()\n\n    if scores.shape[1] < top_k:\n        logger.warning(\n            \"Number of items is less than top_k, limiting top_k to number of items\"\n        )\n    k = min(top_k, scores.shape[1])\n\n    test_user_idx = np.arange(scores.shape[0])[:, None]\n\n    # get top K items and scores\n    # this determines the un-ordered top-k item indices for each user\n    top_items = np.argpartition(scores, -k, axis=1)[:, -k:]\n    top_scores = scores[test_user_idx, top_items]\n\n    if sort_top_k:\n        sort_ind = np.argsort(-top_scores)\n        top_items = top_items[test_user_idx, sort_ind]\n        top_scores = top_scores[test_user_idx, sort_ind]\n\n    return np.array(top_items), np.array(top_scores)\n\n",
        "url": "https://github.com/microsoft/recommenders.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 178,
        "n_words": 89,
        "vocab_size": 71,
        "complexity": 4,
        "nloc": 16,
        "token_counts": 148,
        "n_ast_nodes": 231,
        "n_identifiers": 23,
        "d_id": 7236,
        "documentation": {
            "docstring": "Extract top K items from a matrix of scores for each user-item pair, optionally sort results per user.\n\n    Args:\n        scores (numpy.ndarray): Score matrix (users x items).\n        top_k (int): Number of top items to recommend.\n        sort_top_k (bool): Flag to sort top k results.\n\n    Returns:\n        numpy.ndarray, numpy.ndarray:\n        - Indices into score matrix for each user's top items.\n        - Scores corresponding to top items.\n\n    ",
            "n_words": 61,
            "vocab_size": 45,
            "n_whitespaces": 112,
            "language": "en"
        }
    },
    {
        "id": 69984,
        "commit_id": "586ebd7099fb6fca47cf04f632c8cbf7f0450500",
        "repo": "glances",
        "path": "glances/plugins/glances_plugin.py",
        "file_name": "glances_plugin.py",
        "fun_name": "curse_add_stat",
        "commit_message": "Refactor comment",
        "code": "def curse_add_stat(self, key, width=None, header='', display_key=True, separator='', trailer=''):\n        \n        if key not in self.stats:\n            return []\n\n        # Check if a shortname is defined\n        if key in self.fields_description and 'short_name' in self.fields_description[key]:\n            key_name = self.fields_description[key]['short_name']\n        else:\n            key_name = key\n        if not display_key:\n            key_name = ''\n\n        # Check if unit is defined and get the short unit char in the unit_sort dict\n        if (\n            key in self.fields_description\n            and 'unit' in self.fields_description[key]\n            and self.fields_description[key]['unit'] in fields_unit_short\n        ):\n            # Get the shortname\n            unit_short = fields_unit_short[self.fields_description[key]['unit']]\n        else:\n            unit_short = ''\n\n        # Check if unit is defined and get the unit type unit_type dict\n        if (\n            key in self.fields_description\n            and 'unit' in self.fields_description[key]\n            and self.fields_description[key]['unit'] in fields_unit_type\n        ):\n            # Get the shortname\n            unit_type = fields_unit_type[self.fields_description[key]['unit']]\n        else:\n            unit_type = 'float'\n\n        # Is it a rate ? Yes, compute it thanks to the time_since_update key\n        if (\n            key in self.fields_description\n            and 'rate' in self.fields_description[key]\n            and self.fields_description[key]['rate'] is True\n        ):\n            value = self.stats[key] // self.stats['time_since_update']\n        else:\n            value = self.stats[key]\n\n        if width is None:\n            msg_item = header + '{}'.format(key_name) + separator\n            if unit_type == 'float':\n                msg_value = '{:.1f}{}'.format(value, unit_short) + trailer\n            elif 'min_symbol' in self.fields_description[key]:\n                msg_value = (\n                    '{}{}'.format(\n                        self.auto_unit(int(value), min_symbol=self.fields_description[key]['min_symbol']), unit_short\n                    )\n                    + trailer\n                )\n            else:\n                msg_value = '{}{}'.format(int(value), unit_short) + trailer\n        else:\n            # Define the size of the message\n            # item will be on the left\n            # value will be on the right\n            msg_item = header + '{:{width}}'.format(key_name, width=width - 7) + separator\n            if unit_type == 'float':\n                msg_value = '{:5.1f}{}'.format(value, unit_short) + trailer\n            elif 'min_symbol' in self.fields_description[key]:\n                msg_value = (\n                    '{:>5}{}'.format(\n                        self.auto_unit(int(value), min_symbol=self.fields_description[key]['min_symbol']), unit_short\n                    )\n                    + trailer\n                )\n            else:\n                msg_value = '{:>5}{}'.format(int(value), unit_short) + trailer\n        decoration = self.get_views(key=key, option='decoration')\n        optional = self.get_views(key=key, option='optional')\n\n        return [\n            self.curse_add_line(msg_item, optional=optional),\n            self.curse_add_line(msg_value, decoration=decoration, optional=optional),\n        ]\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 22,
        "n_whitespaces": 1104,
        "n_words": 282,
        "vocab_size": 116,
        "complexity": 19,
        "nloc": 65,
        "token_counts": 475,
        "n_ast_nodes": 797,
        "n_identifiers": 27,
        "d_id": 15223,
        "documentation": {
            "docstring": "Return a list of dict messages with the 'key: value' result\n\n          <=== width ===>\n        __key     : 80.5%__\n        | |       | |    |_ trailer\n        | |       | |_ self.stats[key]\n        | |       |_ separator\n        | |_ key (if display_key is True)\n        |_ header\n\n        Instead of:\n            msg = '  {:8}'.format('idle:')\n            ret.append(self.curse_add_line(msg, optional=self.get_views(key='idle', option='optional')))\n            msg = '{:5.1f}%'.format(self.stats['idle'])\n            ret.append(self.curse_add_line(msg, optional=self.get_views(key='idle', option='optional')))\n\n        Use:\n            ret.extend(self.curse_add_stat('idle', width=15, header='  '))\n\n        ",
            "n_words": 61,
            "vocab_size": 43,
            "n_whitespaces": 215,
            "language": "en"
        }
    },
    {
        "id": 37071,
        "commit_id": "cc034f72eb6137f4c550e911fba67f8a0e1e98fa",
        "repo": "transformers",
        "path": "src/transformers/models/detr/modeling_detr.py",
        "file_name": "modeling_detr.py",
        "fun_name": "loss_labels",
        "commit_message": "Replace assertion with exception (#16720)\n\n* Updated assertions to exceptions\r\n\r\n* updated assertions to exceptions\r\n\r\n* bug fixes\r\n\r\n* fix-copies\r\n\r\n* Update modeling_ctrl.py\r\n\r\n* Update src/transformers/models/ctrl/modeling_tf_ctrl.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/gpt_neo/modeling_gpt_neo.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/gptj/modeling_gptj.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update src/transformers/models/gptj/modeling_tf_gptj.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>\r\n\r\n* Update modeling_led.py\r\n\r\n* Update modeling_led.py\r\n\r\n* Update modeling_led.py\r\n\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def loss_labels(self, outputs, targets, indices, num_boxes):\n        \n        if \"logits\" not in outputs:\n            raise KeyError(\"No logits were found in the outputs\")\n        src_logits = outputs[\"logits\"]\n\n        idx = self._get_src_permutation_idx(indices)\n        target_classes_o = torch.cat([t[\"class_labels\"][J] for t, (_, J) in zip(targets, indices)])\n        target_classes = torch.full(\n            src_logits.shape[:2], self.num_classes, dtype=torch.int64, device=src_logits.device\n        )\n        target_classes[idx] = target_classes_o\n\n        loss_ce = nn.functional.cross_entropy(src_logits.transpose(1, 2), target_classes, self.empty_weight)\n        losses = {\"loss_ce\": loss_ce}\n\n        return losses\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 157,
        "n_words": 58,
        "vocab_size": 48,
        "complexity": 3,
        "nloc": 13,
        "token_counts": 138,
        "n_ast_nodes": 213,
        "n_identifiers": 31,
        "d_id": 6726,
        "documentation": {
            "docstring": "\n        Classification loss (NLL) targets dicts must contain the key \"class_labels\" containing a tensor of dim\n        [nb_target_boxes]\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 153097,
        "commit_id": "1e65a4afd191cf61ba05b80545d23f9b88962f41",
        "repo": "modin",
        "path": "modin/core/dataframe/algebra/default2pandas/groupby.py",
        "file_name": "groupby.py",
        "fun_name": "get_func",
        "commit_message": "FIX-#3197: do not pass lambdas to the backend in GroupBy (#3373)\n\nSigned-off-by: Dmitry Chigarev <dmitry.chigarev@intel.com>",
        "code": "def get_func(cls, key, **kwargs):\n        \n        if \"agg_func\" in kwargs:\n            return cls.inplace_applyier_builder(key, kwargs[\"agg_func\"])\n        elif \"func_dict\" in kwargs:\n            return cls.inplace_applyier_builder(key, kwargs[\"func_dict\"])\n        else:\n            return cls.inplace_applyier_builder(key)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
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        "token_counts": 54,
        "n_ast_nodes": 92,
        "n_identifiers": 5,
        "d_id": 35257,
        "documentation": {
            "docstring": "\n        Extract aggregation function from groupby arguments.\n\n        Parameters\n        ----------\n        key : callable or str\n            Default aggregation function. If aggregation function is not specified\n            via groupby arguments, then `key` function is used.\n        **kwargs : dict\n            GroupBy arguments that may contain aggregation function.\n\n        Returns\n        -------\n        callable\n            Aggregation function.\n\n        Notes\n        -----\n        There are two ways of how groupby aggregation can be invoked:\n            1. Explicitly with query compiler method: `qc.groupby_sum()`.\n            2. By passing aggregation function as an argument: `qc.groupby_agg(\"sum\")`.\n        Both are going to produce the same result, however in the first case actual aggregation\n        function can be extracted from the method name, while for the second only from the method arguments.\n        ",
            "n_words": 106,
            "vocab_size": 78,
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            "language": "en"
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    },
    {
        "id": 269208,
        "commit_id": "c52c11968b096580577c75b169f51c5b39002106",
        "repo": "keras",
        "path": "keras/utils/dataset_utils.py",
        "file_name": "dataset_utils.py",
        "fun_name": "check_validation_split_arg",
        "commit_message": "Updated tests for subset=\"both\"",
        "code": "def check_validation_split_arg(validation_split, subset, shuffle, seed):\n  \n  if validation_split and not 0 < validation_split < 1:\n    raise ValueError(\n        '`validation_split` must be between 0 and 1, received: %s' %\n        (validation_split,))\n  if (validation_split or subset) and not (validation_split and subset):\n    raise ValueError(\n        'If `subset` is set, `validation_split` must be set, and inversely.')\n  if subset not in ('training', 'validation', 'both', None):\n    raise ValueError('`subset` must be either \"training\", '\n                     '\"validation\" or \"both\", received: %s' % (subset,))\n  if validation_split and shuffle and seed is None:\n    raise ValueError(\n        'If using `validation_split` and shuffling the data, you must provide '\n        'a `seed` argument, to make sure that there is no overlap between the '\n        'training and validation subset.')\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
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        "d_id": 79952,
        "documentation": {
            "docstring": "Raise errors in case of invalid argument values.\n\n  Args:\n    validation_split: float between 0 and 1, fraction of data to reserve for\n      validation.\n    subset: One of \"training\", \"validation\" or \"both\". Only used if `validation_split`\n      is set.\n    shuffle: Whether to shuffle the data. Either True or False.\n    seed: random seed for shuffling and transformations.\n  ",
            "n_words": 52,
            "vocab_size": 46,
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        }
    },
    {
        "id": 243990,
        "commit_id": "1516986a616fee8bb741d0ab2be40683045efccd",
        "repo": "mmdetection",
        "path": "mmdet/datasets/custom.py",
        "file_name": "custom.py",
        "fun_name": "prepare_test_img",
        "commit_message": "[Feature] Support OpenImages Dataset (#6331)\n\n* [Feature] support openimage group of eval\r\n\r\n* [Feature] support openimage group of eval\r\n\r\n* support openimage dataset\r\n\r\n* support openimage challenge dataset\r\n\r\n* fully support OpenImages-V6 and OpenImages Challenge 2019\r\n\r\n* Fix some logic error\r\n\r\n* update config file\r\n\r\n* fix get data_infos error\r\n\r\n* fully support OpenImages evaluation\r\n\r\n* update OpenImages config files\r\n\r\n* [Feature] support OpenImages datasets\r\n\r\n* fix bug\r\n\r\n* support load image metas from pipeline\r\n\r\n* fix bug\r\n\r\n* fix get classes logic error\r\n\r\n* update code\r\n\r\n* support get image metas\r\n\r\n* support openimags\r\n\r\n* support collect image metas\r\n\r\n* support Open Images\r\n\r\n* fix openimages logic\r\n\r\n* minor fix\r\n\r\n* add a new function to compute openimages tpfp\r\n\r\n* minor fix\r\n\r\n* fix ci error\r\n\r\n* minor fix\r\n\r\n* fix indication\r\n\r\n* minor fix\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* fix returns\r\n\r\n* minor fix\r\n\r\n* update readme\r\n\r\n* support loading image level labels and fix some logic\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add class names\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* add openimages test unit\r\n\r\n* minor fix\r\n\r\n* minor fix\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* fix logic error\r\n\r\n* minor fix\r\n\r\n* fully support openimages\r\n\r\n* minor fix\r\n\r\n* fix docstring\r\n\r\n* fix docstrings in readthedocs\r\n\r\n* update get image metas script\r\n\r\n* label_description_file -> label_file\r\n\r\n* update openimages readme\r\n\r\n* fix test unit\r\n\r\n* fix test unit\r\n\r\n* minor fix\r\n\r\n* update readme file\r\n\r\n* Update get_image_metas.py",
        "code": "def prepare_test_img(self, idx):\n        \n\n        img_info = self.data_infos[idx]\n        results = dict(img_info=img_info)\n        if self.proposals is not None:\n            results['proposals'] = self.proposals[idx]\n        self.pre_pipeline(results)\n        return self.pipeline(results)\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
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        "n_identifiers": 10,
        "d_id": 70180,
        "documentation": {
            "docstring": "Get testing data after pipeline.\n\n        Args:\n            idx (int): Index of data.\n\n        Returns:\n            dict: Testing data after pipeline with new keys introduced by \\\n                pipeline.\n        ",
            "n_words": 24,
            "vocab_size": 21,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 22111,
        "commit_id": "cd5a9683be69c86c8f3adcd13385a9bc5db198ec",
        "repo": "pipenv",
        "path": "pipenv/patched/pip/_vendor/requests/sessions.py",
        "file_name": "sessions.py",
        "fun_name": "get_redirect_target",
        "commit_message": "Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.",
        "code": "def get_redirect_target(self, resp):\n        \n        # Due to the nature of how requests processes redirects this method will\n        # be called at least once upon the original response and at least twice\n        # on each subsequent redirect response (if any).\n        # If a custom mixin is used to handle this logic, it may be advantageous\n        # to cache the redirect location onto the response object as a private\n        # attribute.\n        if resp.is_redirect:\n            location = resp.headers[\"location\"]\n            # Currently the underlying http module on py3 decode headers\n            # in latin1, but empirical evidence suggests that latin1 is very\n            # rarely used with non-ASCII characters in HTTP headers.\n            # It is more likely to get UTF8 header rather than latin1.\n            # This causes incorrect handling of UTF8 encoded location headers.\n            # To solve this, we re-encode the location in latin1.\n            location = location.encode(\"latin1\")\n            return to_native_string(location, \"utf8\")\n        return None\n",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 305,
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        "vocab_size": 100,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 38,
        "n_ast_nodes": 79,
        "n_identifiers": 8,
        "d_id": 4187,
        "documentation": {
            "docstring": "Receives a Response. Returns a redirect URI or ``None``",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 21600,
        "commit_id": "c69d55f7c82d5ae2cce542bcfb98d043ca4836a0",
        "repo": "pipenv",
        "path": "pipenv/patched/notpip/_vendor/typing_extensions.py",
        "file_name": "typing_extensions.py",
        "fun_name": "get_type_hints",
        "commit_message": "Vendor in pip 22.1.2",
        "code": "def get_type_hints(obj, globalns=None, localns=None, include_extras=False):\n        \n        if hasattr(typing, \"Annotated\"):\n            hint = typing.get_type_hints(\n                obj, globalns=globalns, localns=localns, include_extras=True\n            )\n        else:\n            hint = typing.get_type_hints(obj, globalns=globalns, localns=localns)\n        if include_extras:\n            return hint\n        return {k: _strip_extras(t) for k, t in hint.items()}\n\n\n# Python 3.9+ has PEP 593 (Annotated)\nif hasattr(typing, 'Annotated'):\n    Annotated = typing.Annotated\n    # Not exported and not a public API, but needed for get_origin() and get_args()\n    # to work.\n    _AnnotatedAlias = typing._AnnotatedAlias\n# 3.7-3.8\nelse:",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 172,
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        "token_counts": 88,
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        "d_id": 3948,
        "documentation": {
            "docstring": "Return type hints for an object.\n\n        This is often the same as obj.__annotations__, but it handles\n        forward references encoded as string literals, adds Optional[t] if a\n        default value equal to None is set and recursively replaces all\n        'Annotated[T, ...]', 'Required[T]' or 'NotRequired[T]' with 'T'\n        (unless 'include_extras=True').\n\n        The argument may be a module, class, method, or function. The annotations\n        are returned as a dictionary. For classes, annotations include also\n        inherited members.\n\n        TypeError is raised if the argument is not of a type that can contain\n        annotations, and an empty dictionary is returned if no annotations are\n        present.\n\n        BEWARE -- the behavior of globalns and localns is counterintuitive\n        (unless you are familiar with how eval() and exec() work).  The\n        search order is locals first, then globals.\n\n        - If no dict arguments are passed, an attempt is made to use the\n          globals from obj (or the respective module's globals for classes),\n          and these are also used as the locals.  If the object does not appear\n          to have globals, an empty dictionary is used.\n\n        - If one dict argument is passed, it is used for both globals and\n          locals.\n\n        - If two dict arguments are passed, they specify globals and\n          locals, respectively.\n        ",
            "n_words": 198,
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    },
    {
        "id": 303469,
        "commit_id": "df67a8cd4f8df91a153778009a74be1e3876ca53",
        "repo": "core",
        "path": "homeassistant/components/zha/core/channels/lighting.py",
        "file_name": "lighting.py",
        "fun_name": "color_temp_supported",
        "commit_message": "Fix ZHA light color temp support (#76305)",
        "code": "def color_temp_supported(self) -> bool:\n        \n        return (\n            self.color_capabilities is not None\n            and lighting.Color.ColorCapabilities.Color_temperature\n            in self.color_capabilities\n        ) or self.color_temperature is not None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 74,
        "n_words": 20,
        "vocab_size": 16,
        "complexity": 3,
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        "token_counts": 36,
        "n_ast_nodes": 57,
        "n_identifiers": 9,
        "d_id": 102289,
        "documentation": {
            "docstring": "Return True if the channel supports color temperature.",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 7,
            "language": "en"
        }
    },
    {
        "id": 260786,
        "commit_id": "1aa38c44f60cb729faf217ef85f5cb7d1dd30b46",
        "repo": "scikit-learn",
        "path": "sklearn/multiclass.py",
        "file_name": "multiclass.py",
        "fun_name": "partial_fit",
        "commit_message": "MAINT Parameters validation for OneVsRest estimator  (#24290)\n\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def partial_fit(self, X, y, classes=None):\n        \n        if _check_partial_fit_first_call(self, classes):\n            self._validate_params()\n\n            if not hasattr(self.estimator, \"partial_fit\"):\n                raise ValueError(\n                    (\"Base estimator {0}, doesn't have partial_fit method\").format(\n                        self.estimator\n                    )\n                )\n            self.estimators_ = [clone(self.estimator) for _ in range(self.n_classes_)]\n\n            # A sparse LabelBinarizer, with sparse_output=True, has been\n            # shown to outperform or match a dense label binarizer in all\n            # cases and has also resulted in less or equal memory consumption\n            # in the fit_ovr function overall.\n            self.label_binarizer_ = LabelBinarizer(sparse_output=True)\n            self.label_binarizer_.fit(self.classes_)\n\n        if len(np.setdiff1d(y, self.classes_)):\n            raise ValueError(\n                (\n                    \"Mini-batch contains {0} while classes \" + \"must be subset of {1}\"\n                ).format(np.unique(y), self.classes_)\n            )\n\n        Y = self.label_binarizer_.transform(y)\n        Y = Y.tocsc()\n        columns = (col.toarray().ravel() for col in Y.T)\n\n        self.estimators_ = Parallel(n_jobs=self.n_jobs)(\n            delayed(_partial_fit_binary)(estimator, X, column)\n            for estimator, column in zip(self.estimators_, columns)\n        )\n\n        if hasattr(self.estimators_[0], \"n_features_in_\"):\n            self.n_features_in_ = self.estimators_[0].n_features_in_\n\n        return self\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 493,
        "n_words": 129,
        "vocab_size": 100,
        "complexity": 8,
        "nloc": 28,
        "token_counts": 232,
        "n_ast_nodes": 372,
        "n_identifiers": 40,
        "d_id": 76491,
        "documentation": {
            "docstring": "Partially fit underlying estimators.\n\n        Should be used when memory is inefficient to train all data.\n        Chunks of data can be passed in several iteration.\n\n        Parameters\n        ----------\n        X : (sparse) array-like of shape (n_samples, n_features)\n            Data.\n\n        y : (sparse) array-like of shape (n_samples,) or (n_samples, n_classes)\n            Multi-class targets. An indicator matrix turns on multilabel\n            classification.\n\n        classes : array, shape (n_classes, )\n            Classes across all calls to partial_fit.\n            Can be obtained via `np.unique(y_all)`, where y_all is the\n            target vector of the entire dataset.\n            This argument is only required in the first call of partial_fit\n            and can be omitted in the subsequent calls.\n\n        Returns\n        -------\n        self : object\n            Instance of partially fitted estimator.\n        ",
            "n_words": 110,
            "vocab_size": 84,
            "n_whitespaces": 286,
            "language": "en"
        }
    },
    {
        "id": 101311,
        "commit_id": "9e503bdaa2bfe2baaea50ad2e4bf742f309d9d10",
        "repo": "faceswap",
        "path": "scripts/fsmedia.py",
        "file_name": "fsmedia.py",
        "fun_name": "_get_items",
        "commit_message": "bugfix: debug landmarks",
        "code": "def _get_items(self):\n        \n        postprocess_items = {}\n        # Debug Landmarks\n        if (hasattr(self._args, 'debug_landmarks') and self._args.debug_landmarks):\n            postprocess_items[\"DebugLandmarks\"] = None\n\n        # Face Filter post processing\n        if ((hasattr(self._args, \"filter\") and self._args.filter is not None) or\n                (hasattr(self._args, \"nfilter\") and\n                 self._args.nfilter is not None)):\n\n            if hasattr(self._args, \"detector\"):\n                detector = self._args.detector.replace(\"-\", \"_\").lower()\n            else:\n                detector = \"cv2_dnn\"\n            if hasattr(self._args, \"aligner\"):\n                aligner = self._args.aligner.replace(\"-\", \"_\").lower()\n            else:\n                aligner = \"cv2_dnn\"\n\n            face_filter = dict(detector=detector,\n                               aligner=aligner,\n                               multiprocess=not self._args.singleprocess)\n            filter_lists = {}\n            if hasattr(self._args, \"ref_threshold\"):\n                face_filter[\"ref_threshold\"] = self._args.ref_threshold\n            for filter_type in ('filter', 'nfilter'):\n                filter_args = getattr(self._args, filter_type, None)\n                filter_args = None if not filter_args else filter_args\n                filter_lists[filter_type] = filter_args\n            face_filter[\"filter_lists\"] = filter_lists\n            postprocess_items[\"FaceFilter\"] = {\"kwargs\": face_filter}\n\n        logger.debug(\"Postprocess Items: %s\", postprocess_items)\n        return postprocess_items\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 496,
        "n_words": 108,
        "vocab_size": 67,
        "complexity": 12,
        "nloc": 29,
        "token_counts": 249,
        "n_ast_nodes": 422,
        "n_identifiers": 23,
        "d_id": 20730,
        "documentation": {
            "docstring": " Check the passed in command line arguments for requested actions,\n\n        For any requested actions, add the item to the actions list along with\n        any relevant arguments and keyword arguments.\n\n        Returns\n        -------\n        dict\n            The name of the action to be performed as the key. Any action specific\n            arguments and keyword arguments as the value.\n        ",
            "n_words": 53,
            "vocab_size": 37,
            "n_whitespaces": 118,
            "language": "en"
        }
    },
    {
        "id": 248466,
        "commit_id": "2fc787c341ff540e5880932f116498ec0ed7a2c2",
        "repo": "synapse",
        "path": "synapse/rest/media/v1/media_repository.py",
        "file_name": "media_repository.py",
        "fun_name": "_apply_media_retention_rules",
        "commit_message": "Add config options for media retention (#12732)",
        "code": "async def _apply_media_retention_rules(self) -> None:\n        \n        # Purge remote media\n        if self._media_retention_remote_media_lifetime_ms is not None:\n            # Calculate a threshold timestamp derived from the configured lifetime. Any\n            # media that has not been accessed since this timestamp will be removed.\n            remote_media_threshold_timestamp_ms = (\n                self.clock.time_msec() - self._media_retention_remote_media_lifetime_ms\n            )\n\n            logger.info(\n                \"Purging remote media last accessed before\"\n                f\" {remote_media_threshold_timestamp_ms}\"\n            )\n\n            await self.delete_old_remote_media(\n                before_ts=remote_media_threshold_timestamp_ms\n            )\n\n        # And now do the same for local media\n        if self._media_retention_local_media_lifetime_ms is not None:\n            # This works the same as the remote media threshold\n            local_media_threshold_timestamp_ms = (\n                self.clock.time_msec() - self._media_retention_local_media_lifetime_ms\n            )\n\n            logger.info(\n                \"Purging local media last accessed before\"\n                f\" {local_media_threshold_timestamp_ms}\"\n            )\n\n            await self.delete_old_local_media(\n                before_ts=local_media_threshold_timestamp_ms,\n                keep_profiles=True,\n            )\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 440,
        "n_words": 105,
        "vocab_size": 62,
        "complexity": 3,
        "nloc": 28,
        "token_counts": 93,
        "n_ast_nodes": 170,
        "n_identifiers": 14,
        "d_id": 72294,
        "documentation": {
            "docstring": "\n        Purge old local and remote media according to the media retention rules\n        defined in the homeserver config.\n        ",
            "n_words": 17,
            "vocab_size": 15,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 204364,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/contrib/staticfiles/storage.py",
        "file_name": "storage.py",
        "fun_name": "_url",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def _url(self, hashed_name_func, name, force=False, hashed_files=None):\n        \n        if settings.DEBUG and not force:\n            hashed_name, fragment = name, \"\"\n        else:\n            clean_name, fragment = urldefrag(name)\n            if urlsplit(clean_name).path.endswith(\"/\"):  # don't hash paths\n                hashed_name = name\n            else:\n                args = (clean_name,)\n                if hashed_files is not None:\n                    args += (hashed_files,)\n                hashed_name = hashed_name_func(*args)\n\n        final_url = super().url(hashed_name)\n\n        # Special casing for a @font-face hack, like url(myfont.eot?#iefix\")\n        # http://www.fontspring.com/blog/the-new-bulletproof-font-face-syntax\n        query_fragment = \"?#\" in name  # [sic!]\n        if fragment or query_fragment:\n            urlparts = list(urlsplit(final_url))\n            if fragment and not urlparts[4]:\n                urlparts[4] = fragment\n            if query_fragment and not urlparts[3]:\n                urlparts[2] += \"?\"\n            final_url = urlunsplit(urlparts)\n\n        return unquote(final_url)\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 356,
        "n_words": 94,
        "vocab_size": 60,
        "complexity": 11,
        "nloc": 22,
        "token_counts": 156,
        "n_ast_nodes": 261,
        "n_identifiers": 24,
        "d_id": 50711,
        "documentation": {
            "docstring": "\n        Return the non-hashed URL in DEBUG mode.\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 63403,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py",
        "file_name": "pyparsing.py",
        "fun_name": "parseString",
        "commit_message": "upd; format",
        "code": "def parseString(self, instring, parseAll=False):\n        \n        ParserElement.resetCache()\n        if not self.streamlined:\n            self.streamline()\n            # ~ self.saveAsList = True\n        for e in self.ignoreExprs:\n            e.streamline()\n        if not self.keepTabs:\n            instring = instring.expandtabs()\n        try:\n            loc, tokens = self._parse(instring, 0)\n            if parseAll:\n                loc = self.preParse(instring, loc)\n                se = Empty() + StringEnd()\n                se._parse(instring, loc)\n        except ParseBaseException as exc:\n            if ParserElement.verbose_stacktrace:\n                raise\n            else:\n                # catch and re-raise exception from here, clearing out pyparsing internal stack trace\n                if getattr(exc, '__traceback__', None) is not None:\n                    exc.__traceback__ = self._trim_traceback(exc.__traceback__)\n                raise exc\n        else:\n            return tokens\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 359,
        "n_words": 80,
        "vocab_size": 64,
        "complexity": 8,
        "nloc": 23,
        "token_counts": 141,
        "n_ast_nodes": 233,
        "n_identifiers": 25,
        "d_id": 13288,
        "documentation": {
            "docstring": "\n        Execute the parse expression with the given string.\n        This is the main interface to the client code, once the complete\n        expression has been built.\n\n        Returns the parsed data as a :class:`ParseResults` object, which may be\n        accessed as a list, or as a dict or object with attributes if the given parser\n        includes results names.\n\n        If you want the grammar to require that the entire input string be\n        successfully parsed, then set ``parseAll`` to True (equivalent to ending\n        the grammar with ``StringEnd()``).\n\n        Note: ``parseString`` implicitly calls ``expandtabs()`` on the input string,\n        in order to report proper column numbers in parse actions.\n        If the input string contains tabs and\n        the grammar uses parse actions that use the ``loc`` argument to index into the\n        string being parsed, you can ensure you have a consistent view of the input\n        string by:\n\n        - calling ``parseWithTabs`` on your grammar before calling ``parseString``\n          (see :class:`parseWithTabs`)\n        - define your parse action using the full ``(s, loc, toks)`` signature, and\n          reference the input string using the parse action's ``s`` argument\n        - explictly expand the tabs in your input string before calling\n          ``parseString``\n\n        Example::\n\n            Word('a').parseString('aaaaabaaa')  # -> ['aaaaa']\n            Word('a').parseString('aaaaabaaa', parseAll=True)  # -> Exception: Expected end of text\n        ",
            "n_words": 197,
            "vocab_size": 121,
            "n_whitespaces": 389,
            "language": "en"
        }
    },
    {
        "id": 60607,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/commands/debug.py",
        "file_name": "debug.py",
        "fun_name": "show_actual_vendor_versions",
        "commit_message": "upd; format",
        "code": "def show_actual_vendor_versions(vendor_txt_versions):\n    # type: (Dict[str, str]) -> None\n    \n    for module_name, expected_version in vendor_txt_versions.items():\n        extra_message = ''\n        actual_version = get_vendor_version_from_module(module_name)\n        if not actual_version:\n            extra_message = ' (Unable to locate actual module version, using'\\\n                            ' vendor.txt specified version)'\n            actual_version = expected_version\n        elif parse_version(actual_version) != parse_version(expected_version):\n            extra_message = ' (CONFLICT: vendor.txt suggests version should'\\\n                            ' be {})'.format(expected_version)\n        logger.info('%s==%s%s', module_name, actual_version, extra_message)\n\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 189,
        "n_words": 58,
        "vocab_size": 45,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 71,
        "n_ast_nodes": 126,
        "n_identifiers": 12,
        "d_id": 12219,
        "documentation": {
            "docstring": "Log the actual version and print extra info if there is\n    a conflict or if the actual version could not be imported.\n    ",
            "n_words": 22,
            "vocab_size": 18,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 85881,
        "commit_id": "afbf9a3334ce9cad1a62fced372d7fcee40a3133",
        "repo": "sentry",
        "path": "tests/sentry/notifications/test_notifications.py",
        "file_name": "test_notifications.py",
        "fun_name": "test_sends_resolution_notification",
        "commit_message": "chore(notification): Pass User ID into notification analytics (#38924)\n\nWe pass in the actor_id to notification analytics events but we should\r\nalso include a user_id if the recipient is a user",
        "code": "def test_sends_resolution_notification(self, record_analytics):\n        \n        url = f\"/api/0/issues/{self.group.id}/\"\n        with self.tasks():\n            response = self.client.put(url, format=\"json\", data={\"status\": \"resolved\"})\n        assert response.status_code == 200, response.content\n\n        msg = mail.outbox[0]\n        # check the txt version\n        assert f\"{self.user.username} marked {self.short_id} as resolved\" in msg.body\n        # check the html version\n        assert f\"{self.short_id}</a> as resolved</p>\" in msg.alternatives[0][0]\n\n        attachment, text = get_attachment()\n\n        assert (\n            text\n            == f\"{self.name} marked <http://testserver/organizations/{self.organization.slug}/issues/{self.group.id}/?referrer=activity_notification|{self.short_id}> as resolved\"\n        )\n        assert attachment[\"title\"] == self.group.title\n        assert (\n            attachment[\"footer\"]\n            == f\"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=resolved_activity-slack-user|Notification Settings>\"\n        )\n        assert analytics_called_with_args(\n            record_analytics,\n            \"integrations.email.notification_sent\",\n            user_id=self.user.id,\n            actor_id=self.user.actor_id,\n            organization_id=self.organization.id,\n        )\n        assert analytics_called_with_args(\n            record_analytics,\n            \"integrations.slack.notification_sent\",\n            user_id=self.user.id,\n            actor_id=self.user.actor_id,\n            organization_id=self.organization.id,\n        )\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 387,
        "n_words": 89,
        "vocab_size": 57,
        "complexity": 1,
        "nloc": 32,
        "token_counts": 178,
        "n_ast_nodes": 360,
        "n_identifiers": 34,
        "d_id": 18056,
        "documentation": {
            "docstring": "\n        Test that an email AND Slack notification are sent with\n        the expected values when an issue is resolved.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 276742,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/data_utils.py",
        "file_name": "data_utils.py",
        "fun_name": "get",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def get(self):\n        \n        raise NotImplementedError\n\n\n@keras_export(\"keras.utils.OrderedEnqueuer\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.utils.OrderedEnqueuer\")",
        "n_ast_errors": 1,
        "ast_levels": 7,
        "n_whitespaces": 18,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 2,
        "token_counts": 8,
        "n_ast_nodes": 27,
        "n_identifiers": 4,
        "d_id": 81716,
        "documentation": {
            "docstring": "Creates a generator to extract data from the queue.\n\n        Skip the data if it is `None`.\n        # Returns\n            Generator yielding tuples `(inputs, targets)`\n                or `(inputs, targets, sample_weights)`.\n        ",
            "n_words": 27,
            "vocab_size": 24,
            "n_whitespaces": 74,
            "language": "en"
        }
    },
    {
        "id": 164924,
        "commit_id": "03fef5f0e35200aa5828975b62782bcf11faa0d2",
        "repo": "pandas",
        "path": "pandas/tests/plotting/common.py",
        "file_name": "common.py",
        "fun_name": "_check_data",
        "commit_message": "TST: Clean tests/plotting (#45992)",
        "code": "def _check_data(self, xp, rs):\n        \n        xp_lines = xp.get_lines()\n        rs_lines = rs.get_lines()\n\n        assert len(xp_lines) == len(rs_lines)\n        for xpl, rsl in zip(xp_lines, rs_lines):\n            xpdata = xpl.get_xydata()\n            rsdata = rsl.get_xydata()\n            tm.assert_almost_equal(xpdata, rsdata)\n\n        tm.close()\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 104,
        "n_words": 29,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 9,
        "token_counts": 73,
        "n_ast_nodes": 119,
        "n_identifiers": 17,
        "d_id": 39621,
        "documentation": {
            "docstring": "\n        Check each axes has identical lines\n\n        Parameters\n        ----------\n        xp : matplotlib Axes object\n        rs : matplotlib Axes object\n        ",
            "n_words": 18,
            "vocab_size": 14,
            "n_whitespaces": 61,
            "language": "en"
        }
    },
    {
        "id": 9617,
        "commit_id": "2e5d23ee0e7fc1fdd7ad2e615fd651655aeb0f5b",
        "repo": "insightface",
        "path": "reconstruction/ostec/external/graphonomy/FaceHairMask/deeplab_xception.py",
        "file_name": "deeplab_xception.py",
        "fun_name": "get_1x_lr_params",
        "commit_message": "Graphonomy Face/Hair Segmentation added",
        "code": "def get_1x_lr_params(model):\n    \n    b = [model.xception_features]\n    for i in range(len(b)):\n        for k in b[i].parameters():\n            if k.requires_grad:\n                yield k\n\n",
        "url": "https://github.com/deepinsight/insightface.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 59,
        "n_words": 17,
        "vocab_size": 14,
        "complexity": 4,
        "nloc": 6,
        "token_counts": 43,
        "n_ast_nodes": 71,
        "n_identifiers": 10,
        "d_id": 1642,
        "documentation": {
            "docstring": "\n    This generator returns all the parameters of the net except for\n    the last classification layer. Note that for each batchnorm layer,\n    requires_grad is set to False in deeplab_resnet.py, therefore this function does not return\n    any batchnorm parameter\n    ",
            "n_words": 37,
            "vocab_size": 33,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 186664,
        "commit_id": "7d9e9a49005de7961e84d2a7c608db57dbab3046",
        "repo": "certbot",
        "path": "certbot-apache/certbot_apache/_internal/override_centos.py",
        "file_name": "override_centos.py",
        "fun_name": "parse_sysconfig_var",
        "commit_message": "Add typing to certbot.apache (#9071)\n\n* Add typing to certbot.apache\r\n\r\nCo-authored-by: Adrien Ferrand <ferrand.ad@gmail.com>",
        "code": "def parse_sysconfig_var(self) -> None:\n        \n        defines = apache_util.parse_define_file(self.sysconfig_filep, \"OPTIONS\")\n        for k, v in defines.items():\n            self.variables[k] = v\n",
        "url": "https://github.com/certbot/certbot.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 48,
        "n_words": 16,
        "vocab_size": 14,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 39,
        "n_ast_nodes": 65,
        "n_identifiers": 10,
        "d_id": 45572,
        "documentation": {
            "docstring": " Parses Apache CLI options from CentOS configuration file ",
            "n_words": 8,
            "vocab_size": 8,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 176653,
        "commit_id": "853fb4b27b547bf11761d73c1a62648701f3679f",
        "repo": "networkx",
        "path": "networkx/algorithms/matching.py",
        "file_name": "matching.py",
        "fun_name": "max_weight_matching",
        "commit_message": "Added docstring examples to matching functions (#5617)\n\nCo-authored-by: Dan Schult <dschult@colgate.edu>\r\nCo-authored-by: Ross Barnowski <rossbar@berkeley.edu>",
        "code": "def max_weight_matching(G, maxcardinality=False, weight=\"weight\"):\n    \n    #\n    # The algorithm is taken from \"Efficient Algorithms for Finding Maximum\n    # Matching in Graphs\" by Zvi Galil, ACM Computing Surveys, 1986.\n    # It is based on the \"blossom\" method for finding augmenting paths and\n    # the \"primal-dual\" method for finding a matching of maximum weight, both\n    # methods invented by Jack Edmonds.\n    #\n    # A C program for maximum weight matching by Ed Rothberg was used\n    # extensively to validate this new code.\n    #\n    # Many terms used in the code comments are explained in the paper\n    # by Galil. You will probably need the paper to make sense of this code.\n    #\n",
        "url": "https://github.com/networkx/networkx.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 151,
        "n_words": 109,
        "vocab_size": 74,
        "complexity": 69,
        "nloc": 165,
        "token_counts": 1118,
        "n_ast_nodes": 38,
        "n_identifiers": 4,
        "d_id": 42021,
        "documentation": {
            "docstring": "Compute a maximum-weighted matching of G.\n\n    A matching is a subset of edges in which no node occurs more than once.\n    The weight of a matching is the sum of the weights of its edges.\n    A maximal matching cannot add more edges and still be a matching.\n    The cardinality of a matching is the number of matched edges.\n\n    Parameters\n    ----------\n    G : NetworkX graph\n      Undirected graph\n\n    maxcardinality: bool, optional (default=False)\n       If maxcardinality is True, compute the maximum-cardinality matching\n       with maximum weight among all maximum-cardinality matchings.\n\n    weight: string, optional (default='weight')\n       Edge data key corresponding to the edge weight.\n       If key not found, uses 1 as weight.\n\n\n    Returns\n    -------\n    matching : set\n        A maximal matching of the graph.\n\n     Examples\n    --------\n    >>> G = nx.Graph()\n    >>> edges = [(1, 2, 6), (1, 3, 2), (2, 3, 1), (2, 4, 7), (3, 5, 9), (4, 5, 3)]\n    >>> G.add_weighted_edges_from(edges)\n    >>> sorted(nx.max_weight_matching(G))\n    [(2, 4), (5, 3)]\n\n    Notes\n    -----\n    If G has edges with weight attributes the edge data are used as\n    weight values else the weights are assumed to be 1.\n\n    This function takes time O(number_of_nodes ** 3).\n\n    If all edge weights are integers, the algorithm uses only integer\n    computations.  If floating point weights are used, the algorithm\n    could return a slightly suboptimal matching due to numeric\n    precision errors.\n\n    This method is based on the \"blossom\" method for finding augmenting\n    paths and the \"primal-dual\" method for finding a matching of maximum\n    weight, both methods invented by Jack Edmonds [1]_.\n\n    Bipartite graphs can also be matched using the functions present in\n    :mod:`networkx.algorithms.bipartite.matching`.\n\n    References\n    ----------\n    .. [1] \"Efficient Algorithms for Finding Maximum Matching in Graphs\",\n       Zvi Galil, ACM Computing Surveys, 1986.\n    ",
            "n_words": 274,
            "vocab_size": 173,
            "n_whitespaces": 429,
            "language": "en"
        }
    },
    {
        "id": 138874,
        "commit_id": "242706922b44d4ba4e395deaf6e98b745474863b",
        "repo": "ray",
        "path": "rllib/utils/numpy.py",
        "file_name": "numpy.py",
        "fun_name": "make_action_immutable",
        "commit_message": "[rllib] Fix linting (#24335)\n\n#24262 broke linting. This fixes this.",
        "code": "def make_action_immutable(obj):\n    \n    if isinstance(obj, np.ndarray):\n        obj.setflags(write=False)\n        return obj\n    elif isinstance(obj, OrderedDict):\n        return MappingProxyType(dict(obj))\n    elif isinstance(obj, dict):\n        return MappingProxyType(obj)\n    else:\n        return obj\n\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 71,
        "n_words": 21,
        "vocab_size": 14,
        "complexity": 4,
        "nloc": 10,
        "token_counts": 59,
        "n_ast_nodes": 96,
        "n_identifiers": 10,
        "d_id": 31541,
        "documentation": {
            "docstring": "Flags actions immutable to notify users when trying to change\n    them.\n\n    Can also be used with any tree-like structure containing either\n    dictionaries, numpy arrays or already immutable objects per se.\n    Note, however that `tree.map_structure()` will in general not\n    include the shallow object containing all others and therefore\n    immutability will hold only for all objects contained in it.\n    Use `tree.traverse(fun, action, top_down=False)` to include\n    also the containing object.\n\n    Args:\n        obj: The object to be made immutable.\n\n    Returns:\n        The immutable object.\n\n    Examples:\n        >>> import tree\n        >>> import numpy as np\n        >>> arr = np.arange(1,10)\n        >>> d = dict(a = 1, b = (arr, arr))\n        >>> tree.traverse(make_action_immutable, d, top_down=False)\n    ",
            "n_words": 106,
            "vocab_size": 79,
            "n_whitespaces": 191,
            "language": "en"
        }
    },
    {
        "id": 268616,
        "commit_id": "cb2e434dd2359a9fe1c00e75431f4abeff7381e8",
        "repo": "ansible",
        "path": "lib/ansible/cli/galaxy.py",
        "file_name": "galaxy.py",
        "fun_name": "execute_list_role",
        "commit_message": "ansible-galaxy install - fix unnecessary api check when installing a role from git repo (#79090)\n\n* delay server api evaluation until a GalaxyRole needs to make an api call for info, list, and install",
        "code": "def execute_list_role(self):\n        \n\n        path_found = False\n        role_found = False\n        warnings = []\n        roles_search_paths = context.CLIARGS['roles_path']\n        role_name = context.CLIARGS['role']\n\n        for path in roles_search_paths:\n            role_path = GalaxyCLI._resolve_path(path)\n            if os.path.isdir(path):\n                path_found = True\n            else:\n                warnings.append(\"- the configured path {0} does not exist.\".format(path))\n                continue\n\n            if role_name:\n                # show the requested role, if it exists\n                gr = GalaxyRole(self.galaxy, self.lazy_role_api, role_name, path=os.path.join(role_path, role_name))\n                if os.path.isdir(gr.path):\n                    role_found = True\n                    display.display('# %s' % os.path.dirname(gr.path))\n                    _display_role(gr)\n                    break\n                warnings.append(\"- the role %s was not found\" % role_name)\n            else:\n                if not os.path.exists(role_path):\n                    warnings.append(\"- the configured path %s does not exist.\" % role_path)\n                    continue\n\n                if not os.path.isdir(role_path):\n                    warnings.append(\"- the configured path %s, exists, but it is not a directory.\" % role_path)\n                    continue\n\n                display.display('# %s' % role_path)\n                path_files = os.listdir(role_path)\n                for path_file in path_files:\n                    gr = GalaxyRole(self.galaxy, self.lazy_role_api, path_file, path=path)\n                    if gr.metadata:\n                        _display_role(gr)\n\n        # Do not warn if the role was found in any of the search paths\n        if role_found and role_name:\n            warnings = []\n\n        for w in warnings:\n            display.warning(w)\n\n        if not path_found:\n            raise AnsibleOptionsError(\"- None of the provided paths were usable. Please specify a valid path with --{0}s-path\".format(context.CLIARGS['type']))\n\n        return 0\n",
        "url": "https://github.com/ansible/ansible.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 742,
        "n_words": 177,
        "vocab_size": 97,
        "complexity": 13,
        "nloc": 41,
        "token_counts": 278,
        "n_ast_nodes": 465,
        "n_identifiers": 33,
        "d_id": 79564,
        "documentation": {
            "docstring": "\n        List all roles installed on the local system or a specific role\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 206662,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/utils/formats.py",
        "file_name": "formats.py",
        "fun_name": "localize_input",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def localize_input(value, default=None):\n    \n    if isinstance(value, str):  # Handle strings first for performance reasons.\n        return value\n    elif isinstance(value, bool):  # Don't treat booleans as numbers.\n        return str(value)\n    elif isinstance(value, (decimal.Decimal, float, int)):\n        return number_format(value)\n    elif isinstance(value, datetime.datetime):\n        format = default or get_format(\"DATETIME_INPUT_FORMATS\")[0]\n        format = sanitize_strftime_format(format)\n        return value.strftime(format)\n    elif isinstance(value, datetime.date):\n        format = default or get_format(\"DATE_INPUT_FORMATS\")[0]\n        format = sanitize_strftime_format(format)\n        return value.strftime(format)\n    elif isinstance(value, datetime.time):\n        format = default or get_format(\"TIME_INPUT_FORMATS\")[0]\n        return value.strftime(format)\n    return value\n\n\n@functools.lru_cache",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@functools.lru_cache",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 174,
        "n_words": 72,
        "vocab_size": 40,
        "complexity": 10,
        "nloc": 19,
        "token_counts": 152,
        "n_ast_nodes": 250,
        "n_identifiers": 20,
        "d_id": 51614,
        "documentation": {
            "docstring": "\n    Check if an input value is a localizable type and return it\n    formatted with the appropriate formatting string of the current locale.\n    ",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 288481,
        "commit_id": "dd1463da287f591652e47b00eee0c5b77f5f5b7c",
        "repo": "core",
        "path": "homeassistant/components/bayesian/binary_sensor.py",
        "file_name": "binary_sensor.py",
        "fun_name": "_process_state",
        "commit_message": "Refactor bayesian observations using dataclass (#79590)\n\n* refactor\r\n\r\n* remove some changes\r\n\r\n* remove typehint\r\n\r\n* improve codestyle\r\n\r\n* move docstring to comment\r\n\r\n* < 88 chars\r\n\r\n* avoid short var names\r\n\r\n* more readable\r\n\r\n* fix rename\r\n\r\n* Update homeassistant/components/bayesian/helpers.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* Update homeassistant/components/bayesian/binary_sensor.py\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>\r\n\r\n* no intermediate\r\n\r\n* comment why set before list\r\n\r\nCo-authored-by: epenet <6771947+epenet@users.noreply.github.com>",
        "code": "def _process_state(self, entity_observation):\n        \n\n        entity = entity_observation.entity_id\n\n        try:\n            if condition.state(self.hass, entity, [STATE_UNKNOWN, STATE_UNAVAILABLE]):\n                return None\n\n            return condition.state(self.hass, entity, entity_observation.to_state)\n        except ConditionError:\n            return None\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 98,
        "n_words": 22,
        "vocab_size": 17,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 55,
        "n_ast_nodes": 84,
        "n_identifiers": 12,
        "d_id": 87639,
        "documentation": {
            "docstring": "Return True if state conditions are met, return False if they are not.\n\n        Returns None if the state is unavailable.\n        ",
            "n_words": 20,
            "vocab_size": 16,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 42462,
        "commit_id": "0fac0c0f8e4618c2bdd3d2137d5fb8a80f581246",
        "repo": "nltk",
        "path": "nltk/metrics/agreement.py",
        "file_name": "agreement.py",
        "fun_name": "pi",
        "commit_message": "Update black to 22.3.0\n\nThe most recent release of Click (8.1.0) was breaking Black. See psf/black#2964",
        "code": "def pi(self):\n        \n        total = 0.0\n        label_freqs = FreqDist(x[\"labels\"] for x in self.data)\n        for k, f in label_freqs.items():\n            total += f**2\n        Ae = total / ((len(self.I) * len(self.C)) ** 2)\n        return (self.avg_Ao() - Ae) / (1 - Ae)\n",
        "url": "https://github.com/nltk/nltk.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 90,
        "n_words": 37,
        "vocab_size": 28,
        "complexity": 3,
        "nloc": 7,
        "token_counts": 81,
        "n_ast_nodes": 128,
        "n_identifiers": 15,
        "d_id": 7551,
        "documentation": {
            "docstring": "Scott 1955; here, multi-pi.\n        Equivalent to K from Siegel and Castellan (1988).\n\n        ",
            "n_words": 12,
            "vocab_size": 12,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 246165,
        "commit_id": "901b264c0c88f39cbfb8b2229e0dc57968882658",
        "repo": "synapse",
        "path": "tests/rest/admin/test_user.py",
        "file_name": "test_user.py",
        "fun_name": "test_user_logout_all",
        "commit_message": "Add type hints to `tests/rest/admin` (#11851)",
        "code": "def test_user_logout_all(self) -> None:\n        \n        # Login in as the user\n        puppet_token = self._get_token()\n\n        # Test that we can successfully make a request\n        channel = self.make_request(\"GET\", \"devices\", b\"{}\", access_token=puppet_token)\n        self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)\n\n        # Logout all with the real user token\n        channel = self.make_request(\n            \"POST\", \"logout/all\", b\"{}\", access_token=self.other_user_tok\n        )\n        self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)\n\n        # The puppet token should still work\n        channel = self.make_request(\"GET\", \"devices\", b\"{}\", access_token=puppet_token)\n        self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body)\n\n        # .. but the real user's tokens shouldn't\n        channel = self.make_request(\n            \"GET\", \"devices\", b\"{}\", access_token=self.other_user_tok\n        )\n        self.assertEqual(HTTPStatus.UNAUTHORIZED, channel.code, msg=channel.json_body)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 226,
        "n_words": 85,
        "vocab_size": 51,
        "complexity": 1,
        "nloc": 17,
        "token_counts": 159,
        "n_ast_nodes": 255,
        "n_identifiers": 15,
        "d_id": 71059,
        "documentation": {
            "docstring": "Tests that the target user calling `/logout/all` does *not* expire\n        the token.\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 336767,
        "commit_id": "039958eae55ff0700cfb42a7e72739575ab341f1",
        "repo": "diffusers",
        "path": "scripts/convert_original_stable_diffusion_to_diffusers.py",
        "file_name": "convert_original_stable_diffusion_to_diffusers.py",
        "fun_name": "create_vae_diffusers_config",
        "commit_message": "Stable diffusion text2img conversion script. (#154)\n\n* begin text2img conversion script\r\n\r\n* add fn to convert config\r\n\r\n* create config if not provided\r\n\r\n* update imports and use UNet2DConditionModel\r\n\r\n* fix imports, layer names\r\n\r\n* fix unet coversion\r\n\r\n* add function to convert VAE\r\n\r\n* fix vae conversion\r\n\r\n* update main\r\n\r\n* create text model\r\n\r\n* update config creating logic for unet\r\n\r\n* fix config creation\r\n\r\n* update script to create and save pipeline\r\n\r\n* remove unused imports\r\n\r\n* fix checkpoint loading\r\n\r\n* better name\r\n\r\n* save progress\r\n\r\n* finish\r\n\r\n* up\r\n\r\n* up\r\n\r\nCo-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>",
        "code": "def create_vae_diffusers_config(original_config):\n    \n    vae_params = original_config.model.params.first_stage_config.params.ddconfig\n    _ = original_config.model.params.first_stage_config.params.embed_dim\n\n    block_out_channels = [vae_params.ch * mult for mult in vae_params.ch_mult]\n    down_block_types = [\"DownEncoderBlock2D\"] * len(block_out_channels)\n    up_block_types = [\"UpDecoderBlock2D\"] * len(block_out_channels)\n\n    config = dict(\n        sample_size=vae_params.resolution,\n        in_channels=vae_params.in_channels,\n        out_channels=vae_params.out_ch,\n        down_block_types=tuple(down_block_types),\n        up_block_types=tuple(up_block_types),\n        block_out_channels=tuple(block_out_channels),\n        latent_channels=vae_params.z_channels,\n        layers_per_block=vae_params.num_res_blocks,\n    )\n    return config\n\n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 124,
        "n_words": 41,
        "vocab_size": 31,
        "complexity": 2,
        "nloc": 17,
        "token_counts": 125,
        "n_ast_nodes": 193,
        "n_identifiers": 28,
        "d_id": 120913,
        "documentation": {
            "docstring": "\n    Creates a config for the diffusers based on the config of the LDM model.\n    ",
            "n_words": 14,
            "vocab_size": 11,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 160410,
        "commit_id": "8fced79a8c60d86aaaaf997aa861589336f7899c",
        "repo": "numpy",
        "path": "numpy/ma/core.py",
        "file_name": "core.py",
        "fun_name": "__isub__",
        "commit_message": "MAINT: Fortify masked in-place ops against promotion warnings\n\nThese warnings are probably optional in the future.  They should\nnot matter much (since the following is an in-place op), but\nthe `np.where` could upcast currently!",
        "code": "def __isub__(self, other):\n        \n        m = getmask(other)\n        if self._mask is nomask:\n            if m is not nomask and m.any():\n                self._mask = make_mask_none(self.shape, self.dtype)\n                self._mask += m\n        elif m is not nomask:\n            self._mask += m\n        other_data = getdata(other)\n        other_data = np.where(self._mask, other_data.dtype.type(0), other_data)\n        self._data.__isub__(other_data)\n        return self\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 151,
        "n_words": 43,
        "vocab_size": 26,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 100,
        "n_ast_nodes": 158,
        "n_identifiers": 17,
        "d_id": 38627,
        "documentation": {
            "docstring": "\n        Subtract other from self in-place.\n\n        ",
            "n_words": 5,
            "vocab_size": 5,
            "n_whitespaces": 20,
            "language": "en"
        }
    },
    {
        "id": 11483,
        "commit_id": "c7ad27e5614dfb2b1684f4718c5508840cd55de0",
        "repo": "jina",
        "path": "jina/parsers/orchestrate/runtimes/head.py",
        "file_name": "head.py",
        "fun_name": "mixin_head_parser",
        "commit_message": "refactor: add disable_reduce args (#4424)",
        "code": "def mixin_head_parser(parser):\n    \n\n    gp = add_arg_group(parser, title='Head')\n\n    gp.add_argument(\n        '--uses-before-address',\n        type=str,\n        help='The address of the uses-before runtime',\n    )\n\n    gp.add_argument(\n        '--uses-after-address',\n        type=str,\n        help='The address of the uses-before runtime',\n    )\n\n    gp.add_argument(\n        '--connection-list',\n        type=str,\n        help='dictionary JSON with a list of connections to configure',\n    )\n\n    gp.add_argument(\n        '--disable-reduce',\n        action='store_true',\n        default=False,\n        help='Disable the built-in reduce mechanism, set this if the reduction is to be handled by the Executor connected to this Head',\n    )\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 186,
        "n_words": 65,
        "vocab_size": 44,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 80,
        "n_ast_nodes": 137,
        "n_identifiers": 11,
        "d_id": 2054,
        "documentation": {
            "docstring": "Mixing in arguments required by head pods and runtimes into the given parser.\n    :param parser: the parser instance to which we add arguments\n    ",
            "n_words": 23,
            "vocab_size": 21,
            "n_whitespaces": 29,
            "language": "en"
        }
    },
    {
        "id": 69682,
        "commit_id": "e5a1189becad071f54c727bc6c0dba16bea2a12f",
        "repo": "erpnext",
        "path": "erpnext/accounts/doctype/bank_reconciliation_tool/bank_reconciliation_tool.py",
        "file_name": "bank_reconciliation_tool.py",
        "fun_name": "get_pe_matching_query",
        "commit_message": "Update bank_reconciliation_tool.py\n\nApplying date filter on transactions and all the bank entries and also gives the filter the bank entries as per reference date. Sorted all transactions and entries as per date in ascending order.\nAlso added posting date columns in all bank entries and default checkbox tick of journal entry, hide the sales invoice and purchase invoice checkbox.",
        "code": "def get_pe_matching_query(amount_condition, account_from_to, transaction):\n\t# get matching payment entries query\n\tfrom_date = frappe.db.get_single_value('Bank Reconciliation Tool','bank_statement_from_date')\n\tto_date = frappe.db.get_single_value('Bank Reconciliation Tool','bank_statement_to_date')\n\tfrom_reference_date = frappe.db.get_single_value('Bank Reconciliation Tool','from_reference_date')\n\tto_reference_date = frappe.db.get_single_value('Bank Reconciliation Tool','to_reference_date')\n\tfiltered_by_reference_date = frappe.db.get_single_value('Bank Reconciliation Tool','filtered_by_reference_date')\n\tif transaction.deposit > 0:\n\t\tcurrency_field = \"paid_to_account_currency as currency\"\n\telse:\n\t\tcurrency_field = \"paid_from_account_currency as currency\"\n\tif (filtered_by_reference_date):\n\t\tpe_data=  f\n\telse:\n\t\tpe_data=  f\n\treturn pe_data\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 45,
        "n_words": 59,
        "vocab_size": 38,
        "complexity": 3,
        "nloc": 65,
        "token_counts": 101,
        "n_ast_nodes": 222,
        "n_identifiers": 15,
        "d_id": 15082,
        "documentation": {
            "docstring": "\n\t\t\tSELECT\n\t\t\t\t(CASE WHEN reference_no=%(reference_no)s THEN 1 ELSE 0 END\n\t\t\t\t+ CASE WHEN (party_type = %(party_type)s AND party = %(party)s ) THEN 1 ELSE 0  END\n\t\t\t\t+ 1 ) AS rank,\n\t\t\t\t'Payment Entry' as doctype,\n\t\t\t\tname,\n\t\t\t\tpaid_amount,\n\t\t\t\treference_no,\n\t\t\t\treference_date,\n\t\t\t\tparty,\n\t\t\t\tparty_type,\n\t\t\t\tposting_date,\n\t\t\t\t{currency_field}\n\t\t\tFROM\n\t\t\t\t`tabPayment Entry`\n\t\t\tWHERE\n\t\t\t\tpaid_amount {amount_condition} %(amount)s\n\t\t\t\tAND docstatus = 1\n\t\t\t\tAND payment_type IN (%(payment_type)s, 'Internal Transfer')\n\t\t\t\tAND ifnull(clearance_date, '') = \"\"\n\t\t\t\tAND {account_from_to} = %(bank_account)s\n\t\t\t\tAND reference_date >= '{from_reference_date}'\n\t\t\t\tAND reference_date <= '{to_reference_date}'\t \n\t\t\t\t\n\t\t\t\n\t\t\tSELECT\n\t\t\t\t(CASE WHEN reference_no=%(reference_no)s THEN 1 ELSE 0 END\n\t\t\t\t+ CASE WHEN (party_type = %(party_type)s AND party = %(party)s ) THEN 1 ELSE 0  END\n\t\t\t\t+ 1 ) AS rank,\n\t\t\t\t'Payment Entry' as doctype,\n\t\t\t\tname,\n\t\t\t\tpaid_amount,\n\t\t\t\treference_no,\n\t\t\t\treference_date,\n\t\t\t\tparty,\n\t\t\t\tparty_type,\n\t\t\t\tposting_date,\n\t\t\t\t{currency_field}\n\t\t\tFROM\n\t\t\t\t`tabPayment Entry`\n\t\t\tWHERE\n\t\t\t\tpaid_amount {amount_condition} %(amount)s\n\t\t\t\tAND docstatus = 1\n\t\t\t\tAND payment_type IN (%(payment_type)s, 'Internal Transfer')\n\t\t\t\tAND ifnull(clearance_date, '') = \"\"\n\t\t\t\tAND {account_from_to} = %(bank_account)s\n\t\t\t\tAND posting_date >= '{from_date}'\n\t\t\t\tAND posting_date <= '{to_date}'\t \n\t\t\t\t\n\t\t\t",
            "n_words": 152,
            "vocab_size": 58,
            "n_whitespaces": 110,
            "language": "en"
        }
    },
    {
        "id": 10563,
        "commit_id": "cea300655ed8be70d74c390ca12e8b09fb741665",
        "repo": "jina",
        "path": "jina/parsers/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "set_client_cli_parser",
        "commit_message": "refactor: use absolute imports (#4167)",
        "code": "def set_client_cli_parser(parser=None):\n    \n    if not parser:\n        from jina.parsers.base import set_base_parser\n\n        parser = set_base_parser()\n\n    from jina.parsers.peapods.runtimes.remote import mixin_client_gateway_parser\n    from jina.parsers.client import (\n        mixin_client_features_parser,\n        mixin_comm_protocol_parser,\n    )\n\n    mixin_client_gateway_parser(parser)\n    mixin_client_features_parser(parser)\n    mixin_comm_protocol_parser(parser)\n\n    return parser\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 83,
        "n_words": 28,
        "vocab_size": 23,
        "complexity": 2,
        "nloc": 13,
        "token_counts": 64,
        "n_ast_nodes": 99,
        "n_identifiers": 13,
        "d_id": 1853,
        "documentation": {
            "docstring": "Set the parser for the cli client\n\n    :param parser: an optional existing parser to build upon\n    :return: the parser\n    ",
            "n_words": 19,
            "vocab_size": 15,
            "n_whitespaces": 28,
            "language": "en"
        }
    },
    {
        "id": 67035,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/projects/report/project_wise_stock_tracking/project_wise_stock_tracking.py",
        "file_name": "project_wise_stock_tracking.py",
        "fun_name": "get_delivered_items_cost",
        "commit_message": "style: format code with black",
        "code": "def get_delivered_items_cost():\n\tdn_items = frappe.db.sql(\n\t\t,\n\t\tas_dict=1,\n\t)\n\n\tsi_items = frappe.db.sql(\n\t\t,\n\t\tas_dict=1,\n\t)\n\n\tdn_item_map = {}\n\tfor item in dn_items:\n\t\tdn_item_map.setdefault(item.project, item.amount)\n\n\tfor item in si_items:\n\t\tdn_item_map.setdefault(item.project, item.amount)\n\n\treturn dn_item_map\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 16,
        "n_words": 31,
        "vocab_size": 19,
        "complexity": 3,
        "nloc": 22,
        "token_counts": 74,
        "n_ast_nodes": 116,
        "n_identifiers": 12,
        "d_id": 14413,
        "documentation": {
            "docstring": "select dn.project, sum(dn_item.base_net_amount) as amount\n\t\tfrom `tabDelivery Note` dn, `tabDelivery Note Item` dn_item\n\t\twhere dn.name = dn_item.parent and dn.docstatus = 1 and ifnull(dn.project, '') != ''\n\t\tgroup by dn.projectselect si.project, sum(si_item.base_net_amount) as amount\n\t\tfrom `tabSales Invoice` si, `tabSales Invoice Item` si_item\n\t\twhere si.name = si_item.parent and si.docstatus = 1 and si.update_stock = 1\n\t\tand si.is_pos = 1 and ifnull(si.project, '') != ''\n\t\tgroup by si.project",
            "n_words": 65,
            "vocab_size": 40,
            "n_whitespaces": 57,
            "language": "en"
        }
    },
    {
        "id": 109724,
        "commit_id": "8387676bc049d7b3e071846730c632e6ced137ed",
        "repo": "matplotlib",
        "path": "lib/matplotlib/axes/_secondary_axes.py",
        "file_name": "_secondary_axes.py",
        "fun_name": "set_location",
        "commit_message": "Clean up code in SecondaryAxis",
        "code": "def set_location(self, location):\n        \n\n        # This puts the rectangle into figure-relative coordinates.\n        if isinstance(location, str):\n            _api.check_in_list(self._locstrings, location=location)\n            self._pos = 1. if location in ('top', 'right') else 0.\n        elif isinstance(location, numbers.Real):\n            self._pos = location\n        else:\n            raise ValueError(\n                f\"location must be {self._locstrings[0]!r}, \"\n                f\"{self._locstrings[1]!r}, or a float, not {location!r}\")\n\n        self._loc = location\n\n        if self._orientation == 'x':\n            # An x-secondary axes is like an inset axes from x = 0 to x = 1 and\n            # from y = pos to y = pos + eps, in the parent's transAxes coords.\n            bounds = [0, self._pos, 1., 1e-10]\n        else:  # 'y'\n            bounds = [self._pos, 0, 1e-10, 1]\n\n        # this locator lets the axes move in the parent axes coordinates.\n        # so it never needs to know where the parent is explicitly in\n        # figure coordinates.\n        # it gets called in ax.apply_aspect() (of all places)\n        self.set_axes_locator(\n            _TransformedBoundsLocator(bounds, self._parent.transAxes))\n",
        "url": "https://github.com/matplotlib/matplotlib.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 363,
        "n_words": 142,
        "vocab_size": 97,
        "complexity": 5,
        "nloc": 17,
        "token_counts": 130,
        "n_ast_nodes": 230,
        "n_identifiers": 19,
        "d_id": 23720,
        "documentation": {
            "docstring": "\n        Set the vertical or horizontal location of the axes in\n        parent-normalized coordinates.\n\n        Parameters\n        ----------\n        location : {'top', 'bottom', 'left', 'right'} or float\n            The position to put the secondary axis.  Strings can be 'top' or\n            'bottom' for orientation='x' and 'right' or 'left' for\n            orientation='y'. A float indicates the relative position on the\n            parent axes to put the new axes, 0.0 being the bottom (or left)\n            and 1.0 being the top (or right).\n        ",
            "n_words": 71,
            "vocab_size": 51,
            "n_whitespaces": 170,
            "language": "en"
        }
    },
    {
        "id": 10804,
        "commit_id": "13edc16d806fb5d77a6849551178ccc75937f25f",
        "repo": "jina",
        "path": "daemon/api/dependencies.py",
        "file_name": "dependencies.py",
        "fun_name": "load_and_dump",
        "commit_message": "refactor: rename pod to deployment (#4230)\n\n* refactor: rename pod to deployment\r\n\r\n* style: fix overload and cli autocomplete\r\n\r\n* fix: undo daemon mistake\r\n\r\n* refactor: leftover cleanup\r\n\r\n* fix: more test fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more fixes\r\n\r\n* fix: more tests\r\n\r\n* fix: fix more tests\r\n\r\n* refactor: fix more tests\r\n\r\n* refactor: more tests fixes\r\n\r\n* refactor: rename pea to pod\r\n\r\n* refactor: adjust docs\r\n\r\n* refactor: complete pea renaming\r\n\r\n* refactor: more fixes\r\n\r\n* fix: pea_type in k8s yamls\r\n\r\n* fix: adjust pod args name\r\n\r\n* refactor: rename peapods parser folder\r\n\r\n* fix: da init\r\n\r\nCo-authored-by: Jina Dev Bot <dev-bot@jina.ai>",
        "code": "def load_and_dump(self) -> None:\n        \n        with ExitStack() as stack:\n            # set env vars\n            stack.enter_context(change_env('JINA_FULL_CLI', 'true'))\n\n            # change directory to `workspace`\n            stack.enter_context(change_cwd(get_workspace_path(self.workspace_id)))\n\n            # load and build\n            f: Flow = Flow.load_config(\n                str(self.localpath()), substitute=True, context=self.envs\n            ).build()\n            # get & set the ports mapping, set `runs_in_docker`\n            port_mapping = []\n            port_mapping.append(\n                PortMapping(\n                    deployment_name='gateway',\n                    pod_name='gateway',\n                    ports=Ports(port_expose=f.port_expose),\n                )\n            )\n            for deployment_name, deployment in f._deployment_nodes.items():\n                runtime_cls = update_runtime_cls(deployment.args, copy=True).runtime_cls\n                if runtime_cls in ['WorkerRuntime'] + list(\n                    GATEWAY_RUNTIME_DICT.values()\n                ):\n                    current_ports = Ports()\n                    for port_name in Ports.__fields__:\n                        setattr(\n                            current_ports,\n                            port_name,\n                            getattr(deployment.args, port_name, None),\n                        )\n\n                    port_mapping.append(\n                        PortMapping(\n                            deployment_name=deployment_name,\n                            pod_name='',\n                            ports=current_ports,\n                        )\n                    )\n                elif (\n                    runtime_cls in ['ContainerRuntime']\n                    and hasattr(deployment.args, 'replicas')\n                    and deployment.args.replicas > 1\n                ):\n                    for pod_args in [deployment.pod_args['head']]:\n                        self._update_port_mapping(\n                            pod_args, deployment_name, port_mapping\n                        )\n\n            self.ports = port_mapping\n            # save to a new file & set it for partial-daemon\n            f.save_config(filename=self.newfile)\n            self.params.uses = self.newname\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 994,
        "n_words": 129,
        "vocab_size": 92,
        "complexity": 8,
        "nloc": 63,
        "token_counts": 267,
        "n_ast_nodes": 436,
        "n_identifiers": 51,
        "d_id": 1916,
        "documentation": {
            "docstring": "\n        every Flow created inside JinaD lives inside a container. It is important to know the\n        list of ports to be published with localhost before actually starting the container.\n\n        1. `load` the flow yaml here.\n            - yaml is stored in `workspace` directory, so we'll `cd` there\n            - yaml might include env vars. so we'll set them (passed via query params)\n        2. `build` the Flow so that `gateway` gets added.\n            - get the list of ports to be published (port_expose, port_in, port_out, port_ctrl)\n            - ports need to be published for gateway & executors that are not `ContainerRuntime` or `JinadRuntime` based\n            - Deployment level args for ports are enough, as we don't need to publish Pod ports\n        3. `save` the Flow config.\n            - saves port configs of all `executors` into the new yaml.\n            - set `JINA_FULL_CLI` envvar, so that `gateway` args are also added.\n            - save the config into a new file.\n        4. pass this new file as filename to `partial-daemon` to start the Flow\n        ",
            "n_words": 162,
            "vocab_size": 103,
            "n_whitespaces": 300,
            "language": "en"
        }
    },
    {
        "id": 322216,
        "commit_id": "621357338437ee420eabbbf5ab19065bc85e73a5",
        "repo": "PaddleNLP",
        "path": "paddlenlp/taskflow/utils.py",
        "file_name": "utils.py",
        "fun_name": "search",
        "commit_message": "Update neural search readme and Add Paddle Serving Support (#1558)\n\n* add recall inference similarity\r\n\r\n* update examples\r\n\r\n* updatea readme\r\n\r\n* update dir name\r\n\r\n* update neural search readme\r\n\r\n* update milvus readme\r\n\r\n* update domain adaptive pretraining readme\r\n\r\n* fix the mistakes\r\n\r\n* update readme\r\n\r\n* add recall Paddle Serving Support\r\n\r\n* update readme\r\n\r\n* update readme and format the code\r\n\r\n* reformat the files\r\n\r\n* move the files\r\n\r\n* reformat the code\r\n\r\n* remove redundant code\r\n\r\nCo-authored-by: Zeyu Chen <chenzeyu01@baidu.com>\r\nCo-authored-by: tianxin <tianxin04@baidu.com>",
        "code": "def search(self, content):\n        \n        result = []\n        length = len(content)\n        for start in range(length):\n            for end in range(start + 1, length + 1):\n                pos = self.tree.get(content[start:end], -1)\n                if pos == -1:\n                    break\n                if pos and (len(result) == 0 or end > result[-1][1]):\n                    result.append((start, end))\n        return result\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleNLP.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 174,
        "n_words": 45,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 11,
        "token_counts": 100,
        "n_ast_nodes": 156,
        "n_identifiers": 13,
        "d_id": 118098,
        "documentation": {
            "docstring": "Backward maximum matching\n\n        Args:\n            content (str): string to be searched\n        Returns:\n            List[Tuple]: list of maximum matching words, each element represents \n                the starting and ending position of the matching string.\n        ",
            "n_words": 29,
            "vocab_size": 24,
            "n_whitespaces": 88,
            "language": "en"
        }
    },
    {
        "id": 67056,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/regional/doctype/gst_settings/gst_settings.py",
        "file_name": "gst_settings.py",
        "fun_name": "send_gstin_reminder",
        "commit_message": "style: format code with black",
        "code": "def send_gstin_reminder(party_type, party):\n\t\n\tfrappe.has_permission(party_type, throw=True)\n\temail = _send_gstin_reminder(party_type, party)\n\tif email:\n\t\tfrappe.msgprint(_(\"Reminder to update GSTIN Sent\"), title=\"Reminder sent\", indicator=\"green\")\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 14,
        "n_words": 19,
        "vocab_size": 19,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 46,
        "n_ast_nodes": 78,
        "n_identifiers": 12,
        "d_id": 14421,
        "documentation": {
            "docstring": "Send GSTIN reminder to one party (called from Customer, Supplier form)",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 321126,
        "commit_id": "0877fb0d78635692e481c8bde224fac5ad0dd430",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/webengine/tabhistory.py",
        "file_name": "tabhistory.py",
        "fun_name": "serialize",
        "commit_message": "Run scripts/dev/rewrite_enums.py",
        "code": "def serialize(items):\n    \n    data = QByteArray()\n    stream = QDataStream(data, QIODevice.OpenModeFlag.ReadWrite)\n    cur_user_data = None\n\n    current_idx = None\n\n    for i, item in enumerate(items):\n        if item.active:\n            if current_idx is not None:\n                raise ValueError(\"Multiple active items ({} and {}) \"\n                                 \"found!\".format(current_idx, i))\n            current_idx = i\n            cur_user_data = item.user_data\n\n    if items:\n        if current_idx is None:\n            raise ValueError(\"No active item found!\")\n    else:\n        current_idx = -1\n\n    ### src/core/web_contents_adapter.cpp serializeNavigationHistory\n    #                                          sample data:\n    # kHistoryStreamVersion\n    stream.writeInt(HISTORY_STREAM_VERSION)  # \\x00\\x00\\x00\\x03\n    # count\n    stream.writeInt(len(items))              # \\x00\\x00\\x00\\x01\n    # currentIndex\n    stream.writeInt(current_idx)             # \\x00\\x00\\x00\\x00\n\n    for item in items:\n        _serialize_item(item, stream)\n\n    stream.device().reset()\n    qtutils.check_qdatastream(stream)\n    return stream, data, cur_user_data\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 337,
        "n_words": 91,
        "vocab_size": 60,
        "complexity": 7,
        "nloc": 25,
        "token_counts": 143,
        "n_ast_nodes": 246,
        "n_identifiers": 26,
        "d_id": 117553,
        "documentation": {
            "docstring": "Serialize a list of TabHistoryItems to a data stream.\n\n    Args:\n        items: An iterable of TabHistoryItems.\n\n    Return:\n        A (stream, data, user_data) tuple.\n            stream: The reset QDataStream.\n            data: The QByteArray with the raw data.\n            cur_user_data: The user data for the current item or None.\n\n    Warning:\n        If 'data' goes out of scope, reading from 'stream' will result in a\n        segfault!\n    ",
            "n_words": 57,
            "vocab_size": 49,
            "n_whitespaces": 130,
            "language": "en"
        }
    },
    {
        "id": 72960,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/api/v2/views.py",
        "file_name": "views.py",
        "fun_name": "check_query_parameters",
        "commit_message": "Reformat with black",
        "code": "def check_query_parameters(self, queryset):\n        \n        query_parameters = set(self.request.GET.keys())\n\n        # All query parameters must be either a database field or an operation\n        allowed_query_parameters = set(\n            self.get_available_fields(queryset.model, db_fields_only=True)\n        ).union(self.known_query_parameters)\n        unknown_parameters = query_parameters - allowed_query_parameters\n        if unknown_parameters:\n            raise BadRequestError(\n                \"query parameter is not an operation or a recognised field: %s\"\n                % \", \".join(sorted(unknown_parameters))\n            )\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 161,
        "n_words": 49,
        "vocab_size": 41,
        "complexity": 2,
        "nloc": 11,
        "token_counts": 69,
        "n_ast_nodes": 117,
        "n_identifiers": 18,
        "d_id": 15918,
        "documentation": {
            "docstring": "\n        Ensure that only valid query parameters are included in the URL.\n        ",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 93686,
        "commit_id": "2fbf550ec05c8501cbc9eca62e73526e717dcbdf",
        "repo": "sentry",
        "path": "src/sentry/integrations/jira/client.py",
        "file_name": "client.py",
        "fun_name": "request",
        "commit_message": "ref(Jira): Split Jira Cloud and Jira Server (#37034)\n\n* Split Jira Cloud and Jira Server",
        "code": "def request(self, method, path, data=None, params=None, **kwargs):\n        \n        request_spec = self.request_hook(method, path, data, params, **kwargs)\n        if \"headers\" not in request_spec:\n            request_spec[\"headers\"] = {}\n\n        # Force adherence to the GDPR compliant API conventions.\n        # See\n        # https://developer.atlassian.com/cloud/jira/platform/deprecation-notice-user-privacy-api-migration-guide\n        request_spec[\"headers\"][\"x-atlassian-force-account-id\"] = \"true\"\n        return self._request(**request_spec)\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 107,
        "n_words": 40,
        "vocab_size": 35,
        "complexity": 2,
        "nloc": 6,
        "token_counts": 68,
        "n_ast_nodes": 113,
        "n_identifiers": 10,
        "d_id": 19008,
        "documentation": {
            "docstring": "\n        Use the request_hook method for our specific style of Jira to\n        add authentication data and transform parameters.\n        ",
            "n_words": 17,
            "vocab_size": 17,
            "n_whitespaces": 39,
            "language": "en"
        }
    },
    {
        "id": 264840,
        "commit_id": "8bc6d8cb231ad45cd8b97ffb26cc3d989c60c277",
        "repo": "netbox",
        "path": "netbox/dcim/signals.py",
        "file_name": "signals.py",
        "fun_name": "nullify_connected_endpoints",
        "commit_message": "Introduce CablePath.retrace() to handle deleted cables",
        "code": "def nullify_connected_endpoints(instance, **kwargs):\n    \n    model = instance.termination_type.model_class()\n    model.objects.filter(pk=instance.termination_id).update(_link_peer_type=None, _link_peer_id=None)\n",
        "url": "https://github.com/netbox-community/netbox.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 17,
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        "vocab_size": 8,
        "complexity": 1,
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        "token_counts": 41,
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        "n_identifiers": 13,
        "d_id": 77858,
        "documentation": {
            "docstring": "\n    Disassociate the Cable from the termination object.\n    ",
            "n_words": 7,
            "vocab_size": 6,
            "n_whitespaces": 14,
            "language": "en"
        }
    },
    {
        "id": 178646,
        "commit_id": "840959fbec6d897aa7e51f63e1c34e46402ced8b",
        "repo": "Nuitka",
        "path": "nuitka/Caching.py",
        "file_name": "Caching.py",
        "fun_name": "getModuleImportableFilesHash",
        "commit_message": "Optimization: Make experimental caching bytecode demotion work.",
        "code": "def getModuleImportableFilesHash(full_name):\n    \n    package_name = full_name.getPackageName()\n\n    paths = getPackageSearchPath(None)\n\n    if package_name is not None:\n        paths += getPackageSearchPath(package_name)\n\n    all_suffixes = getAllModuleSuffixes()\n\n    result_hash = Hash()\n\n    for path in paths:\n        if not os.path.isdir(path):\n            continue\n\n        for fullname, filename in listDir(path):\n            if isPackageDir(fullname) or filename.endswith(all_suffixes):\n                result_hash.updateFromValues(filename, b\"\\0\")\n\n    return result_hash.asHexDigest()\n",
        "url": "https://github.com/Nuitka/Nuitka.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 125,
        "n_words": 43,
        "vocab_size": 33,
        "complexity": 7,
        "nloc": 14,
        "token_counts": 96,
        "n_ast_nodes": 159,
        "n_identifiers": 20,
        "d_id": 42780,
        "documentation": {
            "docstring": "Calculate hash value of packages importable for a module of this name.",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 11,
            "language": "en"
        }
    },
    {
        "id": 100713,
        "commit_id": "afec52309326304f4323029039e49bfcf928ef43",
        "repo": "faceswap",
        "path": "lib/gui/analysis/stats.py",
        "file_name": "stats.py",
        "fun_name": "get_summary_stats",
        "commit_message": "Bugfixes:\n  - Stats graph - Handle NaNs in data\n  - logger - de-elevate matplotlib font messages",
        "code": "def get_summary_stats(self) -> List[dict]:\n        \n        logger.debug(\"Compiling sessions summary data\")\n        self._get_time_stats()\n        self._get_per_session_stats()\n        if not self._per_session_stats:\n            return self._per_session_stats\n\n        total_stats = self._total_stats()\n        retval = self._per_session_stats + [total_stats]\n        retval = self._format_stats(retval)\n        logger.debug(\"Final stats: %s\", retval)\n        return retval\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 113,
        "n_words": 32,
        "vocab_size": 26,
        "complexity": 2,
        "nloc": 22,
        "token_counts": 71,
        "n_ast_nodes": 122,
        "n_identifiers": 13,
        "d_id": 20168,
        "documentation": {
            "docstring": " Compile the individual session statistics and calculate the total.\n\n        Format the stats for display\n\n        Returns\n        -------\n        list\n            A list of summary statistics dictionaries containing the Session ID, start time, end\n            time, elapsed time, rate, batch size and number of iterations for each session id\n            within the loaded data as well as the totals.\n        ",
            "n_words": 53,
            "vocab_size": 39,
            "n_whitespaces": 122,
            "language": "en"
        }
    },
    {
        "id": 49823,
        "commit_id": "f4d6e64cdc132ae868699a0ba442f4ab1d304a14",
        "repo": "PaddleHub",
        "path": "modules/image/text_to_image/disco_diffusion_cnclip_vitb16/reverse_diffusion/model/nn.py",
        "file_name": "nn.py",
        "fun_name": "zero_module",
        "commit_message": "add disco_diffusion_cnclip_vitb16 module",
        "code": "def zero_module(module):\n    \n    for p in module.parameters():\n        p.detach().zero_()\n    return module\n\n",
        "url": "https://github.com/PaddlePaddle/PaddleHub.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 25,
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        "vocab_size": 9,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 26,
        "n_ast_nodes": 46,
        "n_identifiers": 6,
        "d_id": 9933,
        "documentation": {
            "docstring": "\n    Zero out the parameters of a module and return it.\n    ",
            "n_words": 10,
            "vocab_size": 10,
            "n_whitespaces": 17,
            "language": "en"
        }
    },
    {
        "id": 19569,
        "commit_id": "3387881a6d4fc2d8bdc0f05c484cb2f7222acfb8",
        "repo": "pipenv",
        "path": "pipenv/utils/shell.py",
        "file_name": "shell.py",
        "fun_name": "normalize_drive",
        "commit_message": "Code reorg utils into utils module reduces complexity (#4990)\n\n* Split apart the massive utils.py into a utils module",
        "code": "def normalize_drive(path):\n    \n    if os.name != \"nt\" or not isinstance(path, str):\n        return path\n\n    drive, tail = os.path.splitdrive(path)\n    # Only match (lower cased) local drives (e.g. 'c:'), not UNC mounts.\n    if drive.islower() and len(drive) == 2 and drive[1] == \":\":\n        return f\"{drive.upper()}{tail}\"\n\n    return path\n\n\n@contextmanager",
        "url": "https://github.com/pypa/pipenv.git",
        "language": "Python",
        "ast_errors": "@contextmanager",
        "n_ast_errors": 1,
        "ast_levels": 11,
        "n_whitespaces": 74,
        "n_words": 43,
        "vocab_size": 36,
        "complexity": 6,
        "nloc": 7,
        "token_counts": 61,
        "n_ast_nodes": 123,
        "n_identifiers": 13,
        "d_id": 3025,
        "documentation": {
            "docstring": "Normalize drive in path so they stay consistent.\n\n    This currently only affects local drives on Windows, which can be\n    identified with either upper or lower cased drive names. The case is\n    always converted to uppercase because it seems to be preferred.\n\n    See: <https://github.com/pypa/pipenv/issues/1218>\n    ",
            "n_words": 43,
            "vocab_size": 40,
            "n_whitespaces": 58,
            "language": "en"
        }
    },
    {
        "id": 37451,
        "commit_id": "1f9e862507704774334dc22a84724e74f52232b7",
        "repo": "transformers",
        "path": "utils/check_repo.py",
        "file_name": "check_repo.py",
        "fun_name": "check_models_are_tested",
        "commit_message": "Update check_models_are_tested to deal with Windows path (#16973)\n\n* fix\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: ydshieh <ydshieh@users.noreply.github.com>\r\nCo-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>",
        "code": "def check_models_are_tested(module, test_file):\n    \n    # XxxPreTrainedModel are not tested\n    defined_models = get_models(module)\n    tested_models = find_tested_models(test_file)\n    if tested_models is None:\n        if test_file.replace(os.path.sep, \"/\") in TEST_FILES_WITH_NO_COMMON_TESTS:\n            return\n        return [\n            f\"{test_file} should define `all_model_classes` to apply common tests to the models it tests. \"\n            + \"If this intentional, add the test filename to `TEST_FILES_WITH_NO_COMMON_TESTS` in the file \"\n            + \"`utils/check_repo.py`.\"\n        ]\n    failures = []\n    for model_name, _ in defined_models:\n        if model_name not in tested_models and model_name not in IGNORE_NON_TESTED:\n            failures.append(\n                f\"{model_name} is defined in {module.__name__} but is not tested in \"\n                + f\"{os.path.join(PATH_TO_TESTS, test_file)}. Add it to the all_model_classes in that file.\"\n                + \"If common tests should not applied to that model, add its name to `IGNORE_NON_TESTED`\"\n                + \"in the file `utils/check_repo.py`.\"\n            )\n    return failures\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 299,
        "n_words": 121,
        "vocab_size": 74,
        "complexity": 6,
        "nloc": 21,
        "token_counts": 89,
        "n_ast_nodes": 185,
        "n_identifiers": 20,
        "d_id": 6780,
        "documentation": {
            "docstring": "Check models defined in module are tested in test_file.",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 88664,
        "commit_id": "e1c5b9ca3bdeadcfdb328dc42740923038d6eb94",
        "repo": "sentry",
        "path": "tests/sentry/sentry_metrics/consumers/test_slicing_router.py",
        "file_name": "test_slicing_router.py",
        "fun_name": "test_with_slicing",
        "commit_message": "feat(indexer): Allow routing of messages (#40776)\n\n### Context\r\nIn order to support slicing in Snuba, the upstream dependency of Snuba\r\ni.e. Sentry metrics indexer needs to route messages to different slices.\r\nThe current implementation is hardcoded to send messages on a single\r\ndestination topic.\r\n\r\n### Implementation\r\nThe way to support sending messages to different slices is by creating a\r\nnew abstraction called RoutingProducer. The routing producer handles all\r\nthe kafka specifics and delegates the routing decision to an abstract\r\n`MessageRouter`. The `MessageRouter` returns a route which encapsulates\r\nthe producer and topic on which the data would be sent.\r\n\r\nThe `SlicingRouter` will use information about slicing from config and\r\npopulate all the sliced producers and topics. It will then rely on the\r\npresence of `org_id` in the Kafkapayload header to make decisions on how\r\nto route the message. The routing decision is similar to what is made in\r\nSnuba.\r\n\r\n**The current PR does not plug in the code with the consumer. There\r\nwould be a separate PR which would handle that.**\r\n\r\nCo-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>",
        "code": "def test_with_slicing(metrics_message, setup_slicing) -> None:\n    \n    org_id = metrics_message.payload.routing_header.get(\"org_id\")\n    router = SlicingRouter(\"sliceable\")\n    route = router.get_route_for_message(metrics_message)\n    if int(org_id) % SENTRY_SLICING_LOGICAL_PARTITION_COUNT < 128:\n        assert route.topic.name == \"sliced_topic_0\"\n    elif int(org_id) % SENTRY_SLICING_LOGICAL_PARTITION_COUNT < 256:\n        assert route.topic.name == \"sliced_topic_1\"\n    else:\n        assert False, \"unexpected org_id\"\n    router.shutdown()\n\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 85,
        "n_words": 40,
        "vocab_size": 30,
        "complexity": 3,
        "nloc": 15,
        "token_counts": 83,
        "n_ast_nodes": 144,
        "n_identifiers": 16,
        "d_id": 18423,
        "documentation": {
            "docstring": "\n    With partitioning settings, the SlicingRouter should route to the correct topic\n    based on the org_id header.\n    ",
            "n_words": 16,
            "vocab_size": 14,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 156079,
        "commit_id": "cccb9d8d8e33a891396b1275c2448c352ef40c27",
        "repo": "dask",
        "path": "dask/core.py",
        "file_name": "core.py",
        "fun_name": "get_dependencies",
        "commit_message": "absolufy-imports - No relative - PEP8 (#8796)\n\nConversation in https://github.com/dask/distributed/issues/5889",
        "code": "def get_dependencies(dsk, key=None, task=no_default, as_list=False):\n    \n    if key is not None:\n        arg = dsk[key]\n    elif task is not no_default:\n        arg = task\n    else:\n        raise ValueError(\"Provide either key or task\")\n\n    return keys_in_tasks(dsk, [arg], as_list=as_list)\n\n",
        "url": "https://github.com/dask/dask.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 68,
        "n_words": 32,
        "vocab_size": 26,
        "complexity": 3,
        "nloc": 8,
        "token_counts": 59,
        "n_ast_nodes": 92,
        "n_identifiers": 9,
        "d_id": 36541,
        "documentation": {
            "docstring": "Get the immediate tasks on which this task depends\n\n    Examples\n    --------\n    >>> inc = lambda x: x + 1\n    >>> add = lambda x, y: x + y\n    >>> dsk = {'x': 1,\n    ...        'y': (inc, 'x'),\n    ...        'z': (add, 'x', 'y'),\n    ...        'w': (inc, 'z'),\n    ...        'a': (add, (inc, 'x'), 1)}\n\n    >>> get_dependencies(dsk, 'x')\n    set()\n\n    >>> get_dependencies(dsk, 'y')\n    {'x'}\n\n    >>> get_dependencies(dsk, 'z')  # doctest: +SKIP\n    {'x', 'y'}\n\n    >>> get_dependencies(dsk, 'w')  # Only direct dependencies\n    {'z'}\n\n    >>> get_dependencies(dsk, 'a')  # Ignore non-keys\n    {'x'}\n\n    >>> get_dependencies(dsk, task=(inc, 'x'))  # provide tasks directly\n    {'x'}\n    ",
            "n_words": 92,
            "vocab_size": 61,
            "n_whitespaces": 190,
            "language": "en"
        }
    },
    {
        "id": 73815,
        "commit_id": "d10f15e55806c6944827d801cd9c2d53f5da4186",
        "repo": "wagtail",
        "path": "wagtail/core/models/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "start",
        "commit_message": "Reformat with black",
        "code": "def start(self, page, user):\n        \n        state = WorkflowState(\n            page=page,\n            workflow=self,\n            status=WorkflowState.STATUS_IN_PROGRESS,\n            requested_by=user,\n        )\n        state.save()\n        state.update(user=user)\n        workflow_submitted.send(sender=state.__class__, instance=state, user=user)\n\n        next_task_data = None\n        if state.current_task_state:\n            next_task_data = {\n                \"id\": state.current_task_state.task.id,\n                \"title\": state.current_task_state.task.name,\n            }\n        log(\n            instance=page,\n            action=\"wagtail.workflow.start\",\n            data={\n                \"workflow\": {\n                    \"id\": self.id,\n                    \"title\": self.name,\n                    \"status\": state.status,\n                    \"next\": next_task_data,\n                    \"task_state_id\": state.current_task_state.id\n                    if state.current_task_state\n                    else None,\n                }\n            },\n            revision=page.get_latest_revision(),\n            user=user,\n        )\n\n        return state\n",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 459,
        "n_words": 57,
        "vocab_size": 47,
        "complexity": 3,
        "nloc": 34,
        "token_counts": 166,
        "n_ast_nodes": 260,
        "n_identifiers": 27,
        "d_id": 16126,
        "documentation": {
            "docstring": "Initiates a workflow by creating an instance of ``WorkflowState``",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 61400,
        "commit_id": "f638f5d0e6c8ebed0e69a6584bc7f003ec646580",
        "repo": "transferlearning",
        "path": ".venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py",
        "file_name": "versioncontrol.py",
        "fun_name": "unpack",
        "commit_message": "upd; format",
        "code": "def unpack(self, location, url):\n        # type: (str, HiddenText) -> None\n        \n        if os.path.exists(location):\n            rmtree(location)\n        self.obtain(location, url=url)\n",
        "url": "https://github.com/jindongwang/transferlearning.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 54,
        "n_words": 15,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 4,
        "token_counts": 34,
        "n_ast_nodes": 56,
        "n_identifiers": 9,
        "d_id": 12546,
        "documentation": {
            "docstring": "\n        Clean up current location and download the url repository\n        (and vcs infos) into location\n\n        :param url: the repository URL starting with a vcs prefix.\n        ",
            "n_words": 24,
            "vocab_size": 20,
            "n_whitespaces": 53,
            "language": "en"
        }
    },
    {
        "id": 261808,
        "commit_id": "8256a48519b7ff0a29c46862de533cefa9ad7f48",
        "repo": "scikit-learn",
        "path": "sklearn/metrics/cluster/_supervised.py",
        "file_name": "_supervised.py",
        "fun_name": "mutual_info_score",
        "commit_message": "MAINT Parameters validation for metrics.mutual_info_score (#25243)",
        "code": "def mutual_info_score(labels_true, labels_pred, *, contingency=None):\n    \n    if contingency is None:\n        labels_true, labels_pred = check_clusterings(labels_true, labels_pred)\n        contingency = contingency_matrix(labels_true, labels_pred, sparse=True)\n    else:\n        contingency = check_array(\n            contingency,\n            accept_sparse=[\"csr\", \"csc\", \"coo\"],\n            dtype=[int, np.int32, np.int64],\n        )\n\n    if isinstance(contingency, np.ndarray):\n        # For an array\n        nzx, nzy = np.nonzero(contingency)\n        nz_val = contingency[nzx, nzy]\n    else:\n        # For a sparse matrix\n        nzx, nzy, nz_val = sp.find(contingency)\n\n    contingency_sum = contingency.sum()\n    pi = np.ravel(contingency.sum(axis=1))\n    pj = np.ravel(contingency.sum(axis=0))\n\n    # Since MI <= min(H(X), H(Y)), any labelling with zero entropy, i.e. containing a\n    # single cluster, implies MI = 0\n    if pi.size == 1 or pj.size == 1:\n        return 0.0\n\n    log_contingency_nm = np.log(nz_val)\n    contingency_nm = nz_val / contingency_sum\n    # Don't need to calculate the full outer product, just for non-zeroes\n    outer = pi.take(nzx).astype(np.int64, copy=False) * pj.take(nzy).astype(\n        np.int64, copy=False\n    )\n    log_outer = -np.log(outer) + log(pi.sum()) + log(pj.sum())\n    mi = (\n        contingency_nm * (log_contingency_nm - log(contingency_sum))\n        + contingency_nm * log_outer\n    )\n    mi = np.where(np.abs(mi) < np.finfo(mi.dtype).eps, 0.0, mi)\n    return np.clip(mi.sum(), 0.0, None)\n\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 344,
        "n_words": 157,
        "vocab_size": 111,
        "complexity": 5,
        "nloc": 32,
        "token_counts": 312,
        "n_ast_nodes": 488,
        "n_identifiers": 43,
        "d_id": 77010,
        "documentation": {
            "docstring": "Mutual Information between two clusterings.\n\n    The Mutual Information is a measure of the similarity between two labels\n    of the same data. Where :math:`|U_i|` is the number of the samples\n    in cluster :math:`U_i` and :math:`|V_j|` is the number of the\n    samples in cluster :math:`V_j`, the Mutual Information\n    between clusterings :math:`U` and :math:`V` is given as:\n\n    .. math::\n\n        MI(U,V)=\\\\sum_{i=1}^{|U|} \\\\sum_{j=1}^{|V|} \\\\frac{|U_i\\\\cap V_j|}{N}\n        \\\\log\\\\frac{N|U_i \\\\cap V_j|}{|U_i||V_j|}\n\n    This metric is independent of the absolute values of the labels:\n    a permutation of the class or cluster label values won't change the\n    score value in any way.\n\n    This metric is furthermore symmetric: switching :math:`U` (i.e\n    ``label_true``) with :math:`V` (i.e. ``label_pred``) will return the\n    same score value. This can be useful to measure the agreement of two\n    independent label assignments strategies on the same dataset when the\n    real ground truth is not known.\n\n    Read more in the :ref:`User Guide <mutual_info_score>`.\n\n    Parameters\n    ----------\n    labels_true : array-like of shape (n_samples,), dtype=integral\n        A clustering of the data into disjoint subsets, called :math:`U` in\n        the above formula.\n\n    labels_pred : array-like of shape (n_samples,), dtype=integral\n        A clustering of the data into disjoint subsets, called :math:`V` in\n        the above formula.\n\n    contingency : {array-like, sparse matrix} of shape \\\n            (n_classes_true, n_classes_pred), default=None\n        A contingency matrix given by the :func:`contingency_matrix` function.\n        If value is ``None``, it will be computed, otherwise the given value is\n        used, with ``labels_true`` and ``labels_pred`` ignored.\n\n    Returns\n    -------\n    mi : float\n       Mutual information, a non-negative value, measured in nats using the\n       natural logarithm.\n\n    See Also\n    --------\n    adjusted_mutual_info_score : Adjusted against chance Mutual Information.\n    normalized_mutual_info_score : Normalized Mutual Information.\n\n    Notes\n    -----\n    The logarithm used is the natural logarithm (base-e).\n    ",
            "n_words": 267,
            "vocab_size": 152,
            "n_whitespaces": 446,
            "language": "en"
        }
    },
    {
        "id": 280118,
        "commit_id": "2851235d5bc1c6603a97d7efffc7649b0a84b826",
        "repo": "keras",
        "path": "keras/optimizers/optimizer_experimental/optimizer.py",
        "file_name": "optimizer.py",
        "fun_name": "_load_own_variables",
        "commit_message": "Use a single h5 file for all numerical state in the model.\nThe modular design enables us to easily swap out the h5 file storage with any other form of storage (e.g. npz or tensorstore) in the future. Just implement a new IOHandler for the new storage system.\n\nPiperOrigin-RevId: 479718541",
        "code": "def _load_own_variables(self, store):\n        \n        for i, variable in enumerate(self.variables()):\n            variable.assign(store[str(i)])\n\n\nbase_optimizer_keyword_args = \n\n\n@keras_export(\n    \"keras.optimizers.Optimizer\",\n    \"keras.optimizers.experimental.Optimizer\",\n    v1=[],\n)",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\n    \"keras.optimizers.Optimizer\",\n    \"keras.optimizers.experimental.Optimizer\",\n    v1=[],\n)",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 48,
        "n_words": 16,
        "vocab_size": 16,
        "complexity": 2,
        "nloc": 3,
        "token_counts": 34,
        "n_ast_nodes": 86,
        "n_identifiers": 12,
        "d_id": 83263,
        "documentation": {
            "docstring": "Set the state of this optimizer object.name: String. The name to use\n        for momentum accumulator weights created by\n        the optimizer.\n      weight_decay: Float, defaults to None. If set, weight decay is applied.\n      clipnorm: Float. If set, the gradient of each weight is individually\n        clipped so that its norm is no higher than this value.\n      clipvalue: Float. If set, the gradient of each weight is clipped to be no\n        higher than this value.\n      global_clipnorm: Float. If set, the gradient of all weights is clipped so\n        that their global norm is no higher than this value.\n      use_ema: Boolean, defaults to False. If True, exponential moving average\n        (EMA) is applied. EMA consists of computing an exponential moving\n        average of the weights of the model (as the weight values change after\n        each training batch), and periodically overwriting the weights with\n        their moving average.\n      ema_momentum: Float, defaults to 0.99. Only used if `use_ema=True`. This is  # noqa: E501\n        the momentum to use when computing the EMA of the model's weights:\n        `new_average = ema_momentum * old_average + (1 - ema_momentum) *\n        current_variable_value`.\n      ema_overwrite_frequency: Int or None, defaults to None. Only used if\n        `use_ema=True`. Every `ema_overwrite_frequency` steps of iterations, we\n        overwrite the model variable by its moving average. If None, the optimizer  # noqa: E501\n         does not overwrite model variables in the middle of training, and you\n        need to explicitly overwrite the variables at the end of training\n        by calling `optimizer.finalize_variable_values()` (which updates the model  # noqa: E501\n        variables in-place). When using the built-in `fit()` training loop, this\n        happens automatically after the last epoch, and you don't need to do\n        anything.\n      jit_compile: Boolean, defaults to True. If True, the optimizer will use XLA  # noqa: E501\n        compilation. If no GPU device is found, this flag will be ignored.\n      **kwargs: keyword arguments only used for backward compatibility.",
            "n_words": 298,
            "vocab_size": 151,
            "n_whitespaces": 494,
            "language": "en"
        }
    },
    {
        "id": 96684,
        "commit_id": "cfdb7fdc1fef7f8a364bbfef050cdcfc66c82371",
        "repo": "sentry",
        "path": "tests/sentry/release_health/test_metrics_sessions_v2.py",
        "file_name": "test_metrics_sessions_v2.py",
        "fun_name": "test_sessions_metrics_equal_num_keys",
        "commit_message": "fix(metrics): Zero-fill response when there's no data [INGEST-941] (#32157)\n\nWhen there isn't any metrics data, the `groups` of the response is empty.\r\nHowever, the absence of data must be represented with an appropriate value.\r\nFor example, `count_unique(user)` must return `0` when there aren't any\r\nusers, instead of returning no data. The value representing the absence of\r\ndata is `0` for sums and counts, and `None` for everything else\r\n(such as `p50`).",
        "code": "def test_sessions_metrics_equal_num_keys(self):\n        \n        empty_groupbyes = [\"project\", \"release\", \"environment\", \"session.status\"]\n        interval_days = \"1d\"\n\n        for groupby in empty_groupbyes:\n            with patch(\n                \"sentry.api.endpoints.organization_sessions.release_health\",\n                SessionsReleaseHealthBackend(),\n            ):\n                sessions_data = result_sorted(self.get_sessions_data(groupby, interval_days))\n\n            with patch(\n                \"sentry.release_health.metrics_sessions_v2.indexer.resolve\", MockIndexer().resolve\n            ), patch(\n                \"sentry.api.endpoints.organization_sessions.release_health\",\n                MetricsReleaseHealthBackend(),\n            ):\n                metrics_data = result_sorted(self.get_sessions_data(groupby, interval_days))\n\n            errors = compare_results(\n                sessions=sessions_data,\n                metrics=metrics_data,\n                rollup=interval_days * 24 * 60 * 60,  # days to seconds\n            )\n            assert len(errors) == 0\n",
        "url": "https://github.com/getsentry/sentry.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 325,
        "n_words": 58,
        "vocab_size": 45,
        "complexity": 2,
        "nloc": 22,
        "token_counts": 114,
        "n_ast_nodes": 195,
        "n_identifiers": 20,
        "d_id": 19338,
        "documentation": {
            "docstring": "\n        Tests whether the number of keys in the metrics implementation of\n        sessions data is the same as in the sessions implementation.\n\n        Runs twice. Firstly, against sessions implementation to populate the\n        cache. Then, against the metrics implementation, and compares with\n        cached results.\n        ",
            "n_words": 41,
            "vocab_size": 29,
            "n_whitespaces": 84,
            "language": "en"
        }
    },
    {
        "id": 335246,
        "commit_id": "71289ba06ea897270ad6de0ea7ff641f4a7b246c",
        "repo": "diffusers",
        "path": "src/diffusers/optimization.py",
        "file_name": "optimization.py",
        "fun_name": "get_linear_schedule_with_warmup",
        "commit_message": "add lr schedule utils",
        "code": "def get_linear_schedule_with_warmup(optimizer, num_warmup_steps, num_training_steps, last_epoch=-1):\n    \n",
        "url": "https://github.com/huggingface/diffusers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 6,
        "n_whitespaces": 8,
        "n_words": 5,
        "vocab_size": 5,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 26,
        "n_ast_nodes": 24,
        "n_identifiers": 5,
        "d_id": 120727,
        "documentation": {
            "docstring": "\n    Create a schedule with a learning rate that decreases linearly from the initial lr set in the optimizer to 0, after\n    a warmup period during which it increases linearly from 0 to the initial lr set in the optimizer.\n\n    Args:\n        optimizer ([`~torch.optim.Optimizer`]):\n            The optimizer for which to schedule the learning rate.\n        num_warmup_steps (`int`):\n            The number of steps for the warmup phase.\n        num_training_steps (`int`):\n            The total number of training steps.\n        last_epoch (`int`, *optional*, defaults to -1):\n            The index of the last epoch when resuming training.\n\n    Return:\n        `torch.optim.lr_scheduler.LambdaLR` with the appropriate schedule.\n    ",
            "n_words": 90,
            "vocab_size": 57,
            "n_whitespaces": 185,
            "language": "en"
        }
    },
    {
        "id": 200579,
        "commit_id": "22174995eac1f437c5f4abe0232760877daf586f",
        "repo": "sympy",
        "path": "sympy/tensor/tensor.py",
        "file_name": "tensor.py",
        "fun_name": "_dedupe_indices",
        "commit_message": "TensMul._dedupe_indices: remove index_structure arg\n\n_get_generator_for_dummy_indices is a staticmethod, and so I can just\ncall _IndexStructure._get_generator_for_dummy_indices",
        "code": "def _dedupe_indices(new, exclude):\n        \n        exclude = set(exclude)\n        dums_new = set(get_dummy_indices(new))\n\n        conflicts = dums_new.intersection(exclude)\n        if len(conflicts) == 0:\n            return None\n\n        \n        exclude.update(dums_new)\n        self_args_free = [(i, None) for i in exclude]\n        gen = _IndexStructure._get_generator_for_dummy_indices(self_args_free)\n        repl = {}\n        for d in conflicts:\n            if -d in repl.keys():\n                continue\n            newname = gen(d.tensor_index_type)\n            new_d = d.func(newname, *d.args[1:])\n            repl[d] = new_d\n            repl[-d] = -new_d\n\n        if len(repl) == 0:\n            return None\n\n        new_renamed = new._replace_indices(repl)\n        return new_renamed\n",
        "url": "https://github.com/sympy/sympy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 257,
        "n_words": 66,
        "vocab_size": 44,
        "complexity": 6,
        "nloc": 26,
        "token_counts": 148,
        "n_ast_nodes": 240,
        "n_identifiers": 25,
        "d_id": 49714,
        "documentation": {
            "docstring": "\n        exclude: set\n        new: TensExpr\n\n        If ``new`` has any dummy indices that are in ``exclude``, return a version\n        of new with those indices replaced. If no replacements are needed,\n        return None\n\n        \n        ``self_args_free`` is to be passed to ``_IndexStructure._get_generator_for_dummy_indices()``.\n        Since the latter does not use the index position for anything, we just\n        set it as ``None`` here.\n        ",
            "n_words": 55,
            "vocab_size": 48,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 209068,
        "commit_id": "eb1e56d676c78ccbd5a3c820b931ac50f6a5a4f8",
        "repo": "scapy",
        "path": "scapy/layers/tls/handshake.py",
        "file_name": "handshake.py",
        "fun_name": "tls_session_update",
        "commit_message": "TLS1.3: wrong parsing size of random_bytes (#3539)\n\nCo-authored-by: dim0x69 <github@3or.de>",
        "code": "def tls_session_update(self, msg_str):\n        \n        super(TLS13ClientHello, self).tls_session_update(msg_str)\n        s = self.tls_session\n\n        if self.sidlen and self.sidlen > 0:\n            s.sid = self.sid\n            s.middlebox_compatibility = True\n\n        self.random_bytes = msg_str[6:38]\n        s.client_random = self.random_bytes\n        if self.ext:\n            for e in self.ext:\n                if isinstance(e, TLS_Ext_SupportedVersion_CH):\n                    for ver in sorted(e.versions, reverse=True):\n                        # RFC 8701: GREASE of TLS will send unknown versions\n                        # here. We have to ignore them\n                        if ver in _tls_version:\n                            self.tls_session.advertised_tls_version = ver\n                            break\n                if isinstance(e, TLS_Ext_SignatureAlgorithms):\n                    s.advertised_sig_algs = e.sig_algs\n\n\n###############################################################################\n#   ServerHello                                                               #\n###############################################################################\n\n",
        "url": "https://github.com/secdev/scapy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 18,
        "n_whitespaces": 410,
        "n_words": 76,
        "vocab_size": 53,
        "complexity": 9,
        "nloc": 17,
        "token_counts": 126,
        "n_ast_nodes": 201,
        "n_identifiers": 25,
        "d_id": 52590,
        "documentation": {
            "docstring": "\n        Either for parsing or building, we store the client_random\n        along with the raw string representing this handshake message.\n        ",
            "n_words": 18,
            "vocab_size": 17,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 195279,
        "commit_id": "b1acb681207559da56a787ba96e16f0e23697d92",
        "repo": "ParlAI",
        "path": "projects/fits/agents/director_bb2.py",
        "file_name": "director_bb2.py",
        "fun_name": "_reshape_tensor",
        "commit_message": "Patch 8322 (#4709)\n\n* add dafetymix teacher\r\n\r\n* safety_mix teacher\r\n\r\n* safety_mix teacher pos and neg teachers\r\n\r\n* add tests for teacher\r\n\r\n* add license info\r\n\r\n* improvement\r\n\r\n* add task list\r\n\r\n* add task list and lint\r\n\r\n* add init.py\r\n\r\n* adding some patch to director\r\n\r\n* seeker changes\r\n\r\n* th\r\n\r\n* 3\r\n\r\n* jing\r\n\r\n* changes\r\n\r\n* z and r\r\n\r\n* remove .opts\r\n\r\n* fix docs\r\n\r\n* add contrractions\r\n\r\n* lint\r\n\r\nCo-authored-by: Dexter Ju <da.ju.fr@gmail.com>\r\nCo-authored-by: Jing Xu <jingxu23@fb.com>",
        "code": "def _reshape_tensor(self, new_len, tensor, indices):\n        \n        reshaped_tensor = torch.zeros(new_len, device=tensor.device, dtype=tensor.dtype)\n        reshaped_tensor[indices] = tensor\n        return reshaped_tensor\n",
        "url": "https://github.com/facebookresearch/ParlAI.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 43,
        "n_words": 15,
        "vocab_size": 13,
        "complexity": 1,
        "nloc": 4,
        "token_counts": 40,
        "n_ast_nodes": 60,
        "n_identifiers": 10,
        "d_id": 47242,
        "documentation": {
            "docstring": "\n        This method reshapes the tensor back to the batch size.\n\n        Args:\n            batch: batch being processed in this iteration.\n            tensor: vector (shape: b' X 1), where b' <= b.\n            indices: indices of (either classification or generation) exs for which the loss was computed.\n\n        Returns:\n            reshaped tensor of shape: b X 1.\n        ",
            "n_words": 50,
            "vocab_size": 43,
            "n_whitespaces": 123,
            "language": "en"
        }
    },
    {
        "id": 223611,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/email/_parseaddr.py",
        "file_name": "_parseaddr.py",
        "fun_name": "getphraselist",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def getphraselist(self):\n        \n        plist = []\n\n        while self.pos < len(self.field):\n            if self.field[self.pos] in self.FWS:\n                self.pos += 1\n            elif self.field[self.pos] == '\"':\n                plist.append(self.getquote())\n            elif self.field[self.pos] == '(':\n                self.commentlist.append(self.getcomment())\n            elif self.field[self.pos] in self.phraseends:\n                break\n            else:\n                plist.append(self.getatom(self.phraseends))\n\n        return plist\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 193,
        "n_words": 35,
        "vocab_size": 26,
        "complexity": 6,
        "nloc": 14,
        "token_counts": 119,
        "n_ast_nodes": 196,
        "n_identifiers": 13,
        "d_id": 57004,
        "documentation": {
            "docstring": "Parse a sequence of RFC 2822 phrases.\n\n        A phrase is a sequence of words, which are in turn either RFC 2822\n        atoms or quoted-strings.  Phrases are canonicalized by squeezing all\n        runs of continuous whitespace into one space.\n        ",
            "n_words": 37,
            "vocab_size": 30,
            "n_whitespaces": 66,
            "language": "en"
        }
    },
    {
        "id": 246588,
        "commit_id": "64c73c6ac88a740ee480a0ad1f9afc8596bccfa4",
        "repo": "synapse",
        "path": "tests/rest/client/test_login.py",
        "file_name": "test_login.py",
        "fun_name": "test_login_appservice_wrong_as",
        "commit_message": "Add type hints to `tests/rest/client` (#12066)",
        "code": "def test_login_appservice_wrong_as(self) -> None:\n        \n        self.register_appservice_user(AS_USER, self.service.token)\n\n        params = {\n            \"type\": login.LoginRestServlet.APPSERVICE_TYPE,\n            \"identifier\": {\"type\": \"m.id.user\", \"user\": AS_USER},\n        }\n        channel = self.make_request(\n            b\"POST\", LOGIN_URL, params, access_token=self.another_service.token\n        )\n\n        self.assertEquals(channel.result[\"code\"], b\"403\", channel.result)\n",
        "url": "https://github.com/matrix-org/synapse.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 110,
        "n_words": 28,
        "vocab_size": 27,
        "complexity": 1,
        "nloc": 11,
        "token_counts": 83,
        "n_ast_nodes": 136,
        "n_identifiers": 17,
        "d_id": 71281,
        "documentation": {
            "docstring": "Test that as users cannot login with wrong as token",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 10555,
        "commit_id": "cea300655ed8be70d74c390ca12e8b09fb741665",
        "repo": "jina",
        "path": "jina/importer.py",
        "file_name": "importer.py",
        "fun_name": "__exit__",
        "commit_message": "refactor: use absolute imports (#4167)",
        "code": "def __exit__(self, exc_type, exc_val, traceback):\n        if exc_type == ModuleNotFoundError:\n            missing_module = self._pkg_name or exc_val.name\n            with open(os.path.join(__resources_path__, 'extra-requirements.txt')) as fp:\n                for v in fp:\n                    if (\n                        v.strip()\n                        and not v.startswith('#')\n                        and v.startswith(missing_module)\n                        and ':' in v\n                    ):\n                        missing_module, install_tags = v.split(':')\n                        self._tags.append(missing_module)\n                        self._tags.extend(vv.strip() for vv in install_tags.split(','))\n                        break\n\n            if self._tags:\n                from jina.helper import colored\n\n                req_msg = colored('fallback to default behavior', color='yellow')\n                if self._required:\n                    req_msg = colored('and it is required', color='red')\n                err_msg = f\n\n                avail_tags = ' '.join(\n                    colored(f'[{tag}]', attrs='bold') for tag in self._tags\n                )\n                err_msg += (\n                    f'\\n\\nTo enable this feature, use {colored(\"pip install jina[TAG]\", attrs=\"bold\")}, '\n                    f'where {colored(\"[TAG]\", attrs=\"bold\")} is one of {avail_tags}.\\n'\n                )\n\n            else:\n                err_msg = f'{exc_val.msg}'\n\n            if self._required:\n                if self._verbose:\n                    if self._logger:\n                        self._logger.critical(err_msg)\n                        if self._help_text:\n                            self._logger.error(self._help_text)\n                    else:\n                        warnings.warn(err_msg, RuntimeWarning, stacklevel=2)\n                raise exc_val\n            else:\n                if self._verbose:\n                    if self._logger:\n                        self._logger.warning(err_msg)\n                        if self._help_text:\n                            self._logger.info(self._help_text)\n                    else:\n                        warnings.warn(err_msg, RuntimeWarning, stacklevel=2)\n                return True  # suppress the error\n\n",
        "url": "https://github.com/jina-ai/jina.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 19,
        "n_whitespaces": 992,
        "n_words": 143,
        "vocab_size": 101,
        "complexity": 19,
        "nloc": 49,
        "token_counts": 296,
        "n_ast_nodes": 565,
        "n_identifiers": 46,
        "d_id": 1848,
        "documentation": {
            "docstring": "Python package \"{colored(missing_module, attrs='bold')}\" is not installed, {req_msg}.\n                    You are trying to use a feature not enabled by your current Jina installation.",
            "n_words": 22,
            "vocab_size": 21,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 118584,
        "commit_id": "704eab3478cf69847825b23dabf15813a8ac9fa2",
        "repo": "streamlit",
        "path": "lib/tests/server_test_case.py",
        "file_name": "server_test_case.py",
        "fun_name": "_patch_app_session",
        "commit_message": "Rename and refactor `Report` machinery (#4141)\n\nThis refactor renames (almost) everything related to the outdated \"report\" concept with more precise concepts that we use throughout our code, primarily \"script run\", \"session\", and \"app\".",
        "code": "def _patch_app_session(self):\n        \n\n        return mock.patch(\n            \"streamlit.server.server.AppSession\",\n            # new_callable must return a function, not an object, or else\n            # there will only be a single AppSession mock. Hence the lambda.\n            new_callable=lambda: self._create_mock_app_session,\n        )\n",
        "url": "https://github.com/streamlit/streamlit.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 96,
        "n_words": 31,
        "vocab_size": 28,
        "complexity": 1,
        "nloc": 5,
        "token_counts": 22,
        "n_ast_nodes": 40,
        "n_identifiers": 6,
        "d_id": 26307,
        "documentation": {
            "docstring": "Mock the Server's AppSession import. We don't want\n        actual sessions to be instantiated, or scripts to be run.\n        ",
            "n_words": 18,
            "vocab_size": 16,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 66418,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/manufacturing/doctype/production_plan/production_plan.py",
        "file_name": "production_plan.py",
        "fun_name": "get_sales_orders",
        "commit_message": "style: format code with black",
        "code": "def get_sales_orders(self):\n\tso_filter = item_filter = \"\"\n\tbom_item = \"bom.item = so_item.item_code\"\n\n\tdate_field_mapper = {\n\t\t\"from_date\": (\">=\", \"so.transaction_date\"),\n\t\t\"to_date\": (\"<=\", \"so.transaction_date\"),\n\t\t\"from_delivery_date\": (\">=\", \"so_item.delivery_date\"),\n\t\t\"to_delivery_date\": (\"<=\", \"so_item.delivery_date\"),\n\t}\n\n\tfor field, value in date_field_mapper.items():\n\t\tif self.get(field):\n\t\t\tso_filter += f\" and {value[1]} {value[0]} %({field})s\"\n\n\tfor field in [\"customer\", \"project\", \"sales_order_status\"]:\n\t\tif self.get(field):\n\t\t\tso_field = \"status\" if field == \"sales_order_status\" else field\n\t\t\tso_filter += f\" and so.{so_field} = %({field})s\"\n\n\tif self.item_code and frappe.db.exists(\"Item\", self.item_code):\n\t\tbom_item = self.get_bom_item() or bom_item\n\t\titem_filter += \" and so_item.item_code = %(item_code)s\"\n\n\topen_so = frappe.db.sql(\n\t\tf,\n\t\tself.as_dict(),\n\t\tas_dict=1,\n\t)\n\n\treturn open_so\n\n\n@frappe.whitelist()",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "@frappe.whitelist()",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 67,
        "n_words": 93,
        "vocab_size": 59,
        "complexity": 9,
        "nloc": 38,
        "token_counts": 158,
        "n_ast_nodes": 329,
        "n_identifiers": 20,
        "d_id": 14183,
        "documentation": {
            "docstring": "\n\t\tselect distinct so.name, so.transaction_date, so.customer, so.base_grand_total\n\t\tfrom `tabSales Order` so, `tabSales Order Item` so_item\n\t\twhere so_item.parent = so.name\n\t\t\tand so.docstatus = 1 and so.status not in (\"Stopped\", \"Closed\")\n\t\t\tand so.company = %(company)s\n\t\t\tand so_item.qty > so_item.work_order_qty {so_filter} {item_filter}\n\t\t\tand (exists (select name from `tabBOM` bom where {bom_item}\n\t\t\t\t\tand bom.is_active = 1)\n\t\t\t\tor exists (select name from `tabPacked Item` pi\n\t\t\t\t\twhere pi.parent = so.name and pi.parent_item = so_item.item_code\n\t\t\t\t\t\tand exists (select name from `tabBOM` bom where bom.item=pi.item_code\n\t\t\t\t\t\t\tand bom.is_active = 1)))\n\t\t",
            "n_words": 80,
            "vocab_size": 49,
            "n_whitespaces": 68,
            "language": "en"
        }
    },
    {
        "id": 38166,
        "commit_id": "afe5d42d8d1d80af911ed980c2936bfe887078f6",
        "repo": "transformers",
        "path": "src/transformers/data/processors/glue.py",
        "file_name": "glue.py",
        "fun_name": "_create_examples",
        "commit_message": "Black preview (#17217)\n\n* Black preview\r\n\r\n* Fixup too!\r\n\r\n* Fix check copies\r\n\r\n* Use the same version as the CI\r\n\r\n* Bump black",
        "code": "def _create_examples(self, lines, set_type):\n        \n        examples = []\n        for i, line in enumerate(lines):\n            if i == 0:\n                continue\n            guid = f\"{set_type}-{i}\"\n            text_a = line[3]\n            text_b = line[4]\n            label = None if set_type == \"test\" else line[0]\n            examples.append(InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))\n        return examples\n\n",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 150,
        "n_words": 41,
        "vocab_size": 34,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 83,
        "n_ast_nodes": 137,
        "n_identifiers": 14,
        "d_id": 6924,
        "documentation": {
            "docstring": "Creates examples for the training, dev and test sets.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 220831,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/asyncio/tasks.py",
        "file_name": "tasks.py",
        "fun_name": "_wait",
        "commit_message": "add python 3.10.4 for windows",
        "code": "async def _wait(fs, timeout, return_when, loop):\n    \n    assert fs, 'Set of Futures is empty.'\n    waiter = loop.create_future()\n    timeout_handle = None\n    if timeout is not None:\n        timeout_handle = loop.call_later(timeout, _release_waiter, waiter)\n    counter = len(fs)\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 57,
        "n_words": 32,
        "vocab_size": 27,
        "complexity": 8,
        "nloc": 24,
        "token_counts": 132,
        "n_ast_nodes": 80,
        "n_identifiers": 12,
        "d_id": 56138,
        "documentation": {
            "docstring": "Internal helper for wait().\n\n    The fs argument must be a collection of Futures.\n    ",
            "n_words": 13,
            "vocab_size": 13,
            "n_whitespaces": 19,
            "language": "en"
        }
    },
    {
        "id": 100303,
        "commit_id": "c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf",
        "repo": "faceswap",
        "path": "lib/gui/analysis/event_reader.py",
        "file_name": "event_reader.py",
        "fun_name": "get_timestamps",
        "commit_message": "Update code to support Tensorflow versions up to 2.8 (#1213)\n\n* Update maximum tf version in setup + requirements\r\n\r\n* - bump max version of tf version in launcher\r\n- standardise tf version check\r\n\r\n* update keras get_custom_objects  for tf>2.6\r\n\r\n* bugfix: force black text in GUI file dialogs (linux)\r\n\r\n* dssim loss - Move to stock tf.ssim function\r\n\r\n* Update optimizer imports for compatibility\r\n\r\n* fix logging for tf2.8\r\n\r\n* Fix GUI graphing for TF2.8\r\n\r\n* update tests\r\n\r\n* bump requirements.txt versions\r\n\r\n* Remove limit on nvidia-ml-py\r\n\r\n* Graphing bugfixes\r\n  - Prevent live graph from displaying if data not yet available\r\n\r\n* bugfix: Live graph. Collect loss labels correctly\r\n\r\n* fix: live graph - swallow inconsistent loss errors\r\n\r\n* Bugfix: Prevent live graph from clearing during training\r\n\r\n* Fix graphing for AMD",
        "code": "def get_timestamps(self, session_id=None):\n        \n\n        logger.debug(\"Getting timestamps: (session_id: %s, is_training: %s)\",\n                     session_id, self._is_training)\n        retval = {}\n        for idx in [session_id] if session_id else self.session_ids:\n            self._check_cache(idx)\n            data = self._cache.get_data(idx, \"timestamps\")\n            if not data:\n                continue\n            retval[idx] = data[idx][\"timestamps\"]\n        logger.debug({k: v.shape for k, v in retval.items()})\n        return retval\n\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 164,
        "n_words": 43,
        "vocab_size": 37,
        "complexity": 5,
        "nloc": 12,
        "token_counts": 98,
        "n_ast_nodes": 157,
        "n_identifiers": 17,
        "d_id": 19800,
        "documentation": {
            "docstring": " Read the timestamps from the TensorBoard logs.\n\n        As loss timestamps are slightly different for each loss, we collect the timestamp from the\n        `batch_loss` key.\n\n        Parameters\n        ----------\n        session_id: int, optional\n            The Session ID to return the timestamps for. Set to ``None`` to return all session\n            timestamps. Default ``None``\n\n        Returns\n        -------\n        dict\n            The session id(s) as key with list of timestamps per step as value\n        ",
            "n_words": 63,
            "vocab_size": 48,
            "n_whitespaces": 160,
            "language": "en"
        }
    },
    {
        "id": 202528,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/custom_pk/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_querysets_related_name",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_querysets_related_name(self):\n        \n        self.assertQuerysetEqual(\n            self.business.employees.all(),\n            [\n                \"Fran Bones\",\n                \"Dan Jones\",\n            ],\n            str,\n        )\n        self.assertQuerysetEqual(\n            self.fran.business_set.all(),\n            [\n                \"Sears\",\n            ],\n            lambda b: b.name,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 189,
        "n_words": 21,
        "vocab_size": 17,
        "complexity": 1,
        "nloc": 16,
        "token_counts": 57,
        "n_ast_nodes": 93,
        "n_identifiers": 11,
        "d_id": 50147,
        "documentation": {
            "docstring": "\n        Custom pk doesn't affect related_name based lookups\n        ",
            "n_words": 7,
            "vocab_size": 7,
            "n_whitespaces": 22,
            "language": "en"
        }
    },
    {
        "id": 243966,
        "commit_id": "301d4a2d4cfe1cdb62608e2892924be3e67e3098",
        "repo": "mmdetection",
        "path": "mmdet/core/visualization/image.py",
        "file_name": "image.py",
        "fun_name": "draw_bboxes",
        "commit_message": "[Feature] Support visualization for Panoptic Segmentation (#7041)\n\n* First commit of v2\r\n\r\n* split the functions\r\n\r\n* Support to show panoptic result\r\n\r\n* temp\r\n\r\n* Support to show gt\r\n\r\n* support show gt\r\n\r\n* fix lint\r\n\r\n* Support to browse datasets\r\n\r\n* Fix unit tests\r\n\r\n* Fix findContours\r\n\r\n* fix comments\r\n\r\n* Fix pre-commit\r\n\r\n* fix lint\r\n\r\n* Add the type of an argument",
        "code": "def draw_bboxes(ax, bboxes, color='g', alpha=0.8, thickness=2):\n    \n    polygons = []\n    for i, bbox in enumerate(bboxes):\n        bbox_int = bbox.astype(np.int32)\n        poly = [[bbox_int[0], bbox_int[1]], [bbox_int[0], bbox_int[3]],\n                [bbox_int[2], bbox_int[3]], [bbox_int[2], bbox_int[1]]]\n        np_poly = np.array(poly).reshape((4, 2))\n        polygons.append(Polygon(np_poly))\n    p = PatchCollection(\n        polygons,\n        facecolor='none',\n        edgecolors=color,\n        linewidths=thickness,\n        alpha=alpha)\n    ax.add_collection(p)\n\n    return ax\n\n",
        "url": "https://github.com/open-mmlab/mmdetection.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 139,
        "n_words": 43,
        "vocab_size": 37,
        "complexity": 2,
        "nloc": 16,
        "token_counts": 153,
        "n_ast_nodes": 222,
        "n_identifiers": 26,
        "d_id": 70168,
        "documentation": {
            "docstring": "Draw bounding boxes on the axes.\n\n    Args:\n        ax (matplotlib.Axes): The input axes.\n        bboxes (ndarray): The input bounding boxes with the shape\n            of (n, 4).\n        color (list[tuple] | matplotlib.color): the colors for each\n            bounding boxes.\n        alpha (float): Transparency of bounding boxes. Default: 0.8.\n        thickness (int): Thickness of lines. Default: 2.\n\n    Returns:\n        matplotlib.Axes: The result axes.\n    ",
            "n_words": 54,
            "vocab_size": 39,
            "n_whitespaces": 127,
            "language": "en"
        }
    },
    {
        "id": 37637,
        "commit_id": "1ac698744c4dbdf1495d303246d08ffacdf4f5b8",
        "repo": "transformers",
        "path": "src/transformers/models/yolos/feature_extraction_yolos.py",
        "file_name": "feature_extraction_yolos.py",
        "fun_name": "prepare_coco_detection",
        "commit_message": "Add YOLOS (#16848)\n\n* First draft\r\n\r\n* Add YolosForObjectDetection\r\n\r\n* Make forward pass work\r\n\r\n* Add mid position embeddings\r\n\r\n* Add interpolation of position encodings\r\n\r\n* Add expected values\r\n\r\n* Add YOLOS to tests\r\n\r\n* Add integration test\r\n\r\n* Support tiny model as well\r\n\r\n* Support all models in conversion script\r\n\r\n* Remove mid_pe_size attribute\r\n\r\n* Make more tests pass\r\n\r\n* Add model to README and fix config\r\n\r\n* Add copied from statements\r\n\r\n* Rename base_model_prefix to vit\r\n\r\n* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP\r\n\r\n* Apply suggestions from code review\r\n\r\n* Apply more suggestions from code review\r\n\r\n* Convert remaining checkpoints\r\n\r\n* Improve docstrings\r\n\r\n* Add YolosFeatureExtractor\r\n\r\n* Add feature extractor to docs\r\n\r\n* Add corresponding tests\r\n\r\n* Fix style\r\n\r\n* Fix docs\r\n\r\n* Apply suggestion from code review\r\n\r\n* Fix bad rebase\r\n\r\n* Fix some more bad rebase\r\n\r\n* Fix missing character\r\n\r\n* Improve docs and variable names\r\n\r\nCo-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>",
        "code": "def prepare_coco_detection(self, image, target, return_segmentation_masks=False):\n        \n        w, h = image.size\n\n        image_id = target[\"image_id\"]\n        image_id = np.asarray([image_id], dtype=np.int64)\n\n        # get all COCO annotations for the given image\n        anno = target[\"annotations\"]\n\n        anno = [obj for obj in anno if \"iscrowd\" not in obj or obj[\"iscrowd\"] == 0]\n\n        boxes = [obj[\"bbox\"] for obj in anno]\n        # guard against no boxes via resizing\n        boxes = np.asarray(boxes, dtype=np.float32).reshape(-1, 4)\n        boxes[:, 2:] += boxes[:, :2]\n        boxes[:, 0::2] = boxes[:, 0::2].clip(min=0, max=w)\n        boxes[:, 1::2] = boxes[:, 1::2].clip(min=0, max=h)\n\n        classes = [obj[\"category_id\"] for obj in anno]\n        classes = np.asarray(classes, dtype=np.int64)\n\n        if return_segmentation_masks:\n            segmentations = [obj[\"segmentation\"] for obj in anno]\n            masks = self.convert_coco_poly_to_mask(segmentations, h, w)\n\n        keypoints = None\n        if anno and \"keypoints\" in anno[0]:\n            keypoints = [obj[\"keypoints\"] for obj in anno]\n            keypoints = np.asarray(keypoints, dtype=np.float32)\n            num_keypoints = keypoints.shape[0]\n            if num_keypoints:\n                keypoints = keypoints.reshape((-1, 3))\n\n        keep = (boxes[:, 3] > boxes[:, 1]) & (boxes[:, 2] > boxes[:, 0])\n        boxes = boxes[keep]\n        classes = classes[keep]\n        if return_segmentation_masks:\n            masks = masks[keep]\n        if keypoints is not None:\n            keypoints = keypoints[keep]\n\n        target = {}\n        target[\"boxes\"] = boxes\n        target[\"class_labels\"] = classes\n        if return_segmentation_masks:\n            target[\"masks\"] = masks\n        target[\"image_id\"] = image_id\n        if keypoints is not None:\n            target[\"keypoints\"] = keypoints\n\n        # for conversion to coco api\n        area = np.asarray([obj[\"area\"] for obj in anno], dtype=np.float32)\n        iscrowd = np.asarray([obj[\"iscrowd\"] if \"iscrowd\" in obj else 0 for obj in anno], dtype=np.int64)\n        target[\"area\"] = area[keep]\n        target[\"iscrowd\"] = iscrowd[keep]\n\n        target[\"orig_size\"] = np.asarray([int(h), int(w)], dtype=np.int64)\n        target[\"size\"] = np.asarray([int(h), int(w)], dtype=np.int64)\n\n        return image, target\n\n    # Copied from transformers.models.detr.feature_extraction_detr.DetrFeatureExtractor.prepare_coco_panoptic",
        "url": "https://github.com/huggingface/transformers.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 629,
        "n_words": 242,
        "vocab_size": 121,
        "complexity": 19,
        "nloc": 45,
        "token_counts": 528,
        "n_ast_nodes": 832,
        "n_identifiers": 32,
        "d_id": 6843,
        "documentation": {
            "docstring": "\n        Convert the target in COCO format into the format expected by DETR.\n        ",
            "n_words": 12,
            "vocab_size": 10,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 70176,
        "commit_id": "4046fbb18cf16be684ada228314c1f328779a3c1",
        "repo": "glances",
        "path": "glances/secure.py",
        "file_name": "secure.py",
        "fun_name": "secure_popen",
        "commit_message": "Fix typos\n\nFound via `codespell -S ./venv,./glances/outputs,*.svg -L hart,bu,te,statics`",
        "code": "def secure_popen(cmd):\n    \n    ret = ''\n\n    # Split by multiple commands '&&'\n    for c in cmd.split('&&'):\n        ret += __secure_popen(c)\n\n    return ret\n\n",
        "url": "https://github.com/nicolargo/glances.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 42,
        "n_words": 20,
        "vocab_size": 18,
        "complexity": 2,
        "nloc": 5,
        "token_counts": 27,
        "n_ast_nodes": 51,
        "n_identifiers": 6,
        "d_id": 15402,
        "documentation": {
            "docstring": "A more or less secure way to execute system commands\n\n    Multiple command should be separated with a &&\n\n    :return: the result of the commands\n    ",
            "n_words": 24,
            "vocab_size": 22,
            "n_whitespaces": 33,
            "language": "en"
        }
    },
    {
        "id": 153603,
        "commit_id": "605efa618e7994681f57b11d04d417f353ef8d50",
        "repo": "modin",
        "path": "modin/pandas/base.py",
        "file_name": "base.py",
        "fun_name": "at",
        "commit_message": "DOCS-#3099: Fix `BasePandasDataSet` docstrings warnings (#4333)\n\nCo-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru>\r\nSigned-off-by: Alexander Myskov <alexander.myskov@intel.com>",
        "code": "def at(self, axis=None):  # noqa: PR01, RT01, D200\n        \n        from .indexing import _LocIndexer\n\n        return _LocIndexer(self)\n",
        "url": "https://github.com/modin-project/modin.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 7,
        "n_whitespaces": 36,
        "n_words": 14,
        "vocab_size": 14,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 20,
        "n_ast_nodes": 37,
        "n_identifiers": 5,
        "d_id": 35484,
        "documentation": {
            "docstring": "\n        Get a single value for a row/column label pair.\n        ",
            "n_words": 9,
            "vocab_size": 8,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 205763,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/db/models/query.py",
        "file_name": "query.py",
        "fun_name": "update",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def update(self, **kwargs):\n        \n        self._not_support_combined_queries(\"update\")\n        if self.query.is_sliced:\n            raise TypeError(\"Cannot update a query once a slice has been taken.\")\n        self._for_write = True\n        query = self.query.chain(sql.UpdateQuery)\n        query.add_update_values(kwargs)\n        # Clear any annotations so that they won't be present in subqueries.\n        query.annotations = {}\n        with transaction.mark_for_rollback_on_error(using=self.db):\n            rows = query.get_compiler(self.db).execute_sql(CURSOR)\n        self._result_cache = None\n        return rows\n\n    update.alters_data = True\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 154,
        "n_words": 52,
        "vocab_size": 43,
        "complexity": 2,
        "nloc": 12,
        "token_counts": 90,
        "n_ast_nodes": 162,
        "n_identifiers": 23,
        "d_id": 51201,
        "documentation": {
            "docstring": "\n        Update all elements in the current QuerySet, setting all the given\n        fields to the appropriate values.\n        ",
            "n_words": 16,
            "vocab_size": 13,
            "n_whitespaces": 38,
            "language": "en"
        }
    },
    {
        "id": 102011,
        "commit_id": "1d1face00d9476896e7857d3976afce383585d1b",
        "repo": "faceswap",
        "path": "scripts/extract.py",
        "file_name": "extract.py",
        "fun_name": "_identity_from_extracted",
        "commit_message": "Update Face Filter\n  - Remove old face filter\n  - plugins.extract.pipeline: Expose plugins directly\n  - Change `is_aligned` from plugin level to ExtractMedia level\n  - Allow extract pipeline to take faceswap aligned images\n  - Add ability for recognition plugins to accept aligned faces as input\n  - Add face filter to recognition plugin\n  - Move extractor pipeline IO ops to own class",
        "code": "def _identity_from_extracted(cls, filename) -> Tuple[np.ndarray, bool]:\n        \n        if os.path.splitext(filename)[-1].lower() != \".png\":\n            logger.info(\"'%s' not a png. Returning empty array\", filename)\n            return np.array([]), False\n\n        meta = read_image_meta(filename)\n        if \"itxt\" not in meta or \"alignments\" not in meta[\"itxt\"]:\n            logger.debug(\"'%s' does not contain faceswap data. Returning empty array\", filename)\n            return np.array([]), False\n\n        align: \"PNGHeaderAlignmentsDict\" = meta[\"itxt\"][\"alignments\"]\n        if \"identity\" not in align or \"vggface2\" not in align[\"identity\"]:\n            logger.debug(\"'%s' does not contain identity data. Returning empty array\", filename)\n            return np.array([]), True\n\n        retval = np.array(align[\"identity\"][\"vggface2\"])\n        logger.debug(\"Obtained identity for '%s'. Shape: %s\", filename, retval.shape)\n\n        return retval, True\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 217,
        "n_words": 88,
        "vocab_size": 52,
        "complexity": 6,
        "nloc": 31,
        "token_counts": 166,
        "n_ast_nodes": 285,
        "n_identifiers": 20,
        "d_id": 21385,
        "documentation": {
            "docstring": " Test whether the given image is a faceswap extracted face and contains identity\n        information. If so, return the identity embedding\n\n        Parameters\n        ----------\n        filename: str\n            Full path to the image file to load\n\n        Returns\n        -------\n        :class:`numpy.ndarray`\n            The identity embeddings, if they can be obtained from the image header, otherwise an\n            empty array\n        bool\n            ``True`` if the image is a faceswap extracted image otherwise ``False``\n        ",
            "n_words": 63,
            "vocab_size": 46,
            "n_whitespaces": 171,
            "language": "en"
        }
    },
    {
        "id": 280200,
        "commit_id": "e6f739a31247c43a86c37c33b0b8b2ba6be6a5f6",
        "repo": "keras",
        "path": "keras/saving/experimental/saving_lib.py",
        "file_name": "saving_lib.py",
        "fun_name": "save_model",
        "commit_message": "- Add standalone weights file saving/loading functionality.\n- Switch to in-memory, single write / single read archive saving for better performance.\n- Remove ability to pick between zipping or not zipping a Keras saved artifact: it's always a zip archive now.\n\nPiperOrigin-RevId: 483705728",
        "code": "def save_model(model, filepath, weights_format=\"h5\"):\n    \n    if not filepath.endswith(\".keras\"):\n        raise ValueError(\n            \"Invalid filename: expected a `.keras` extension. \"\n            f\"Received: filepath={filepath}\"\n        )\n    if weights_format == \"h5\" and h5py is None:\n        raise ImportError(\"h5py must be installed in order to save a model.\")\n\n    if not model.built:\n        warnings.warn(\n            \"You are saving a model that has not yet been built. \"\n            \"It might not contain any weights yet. \"\n            \"Consider building the model first by calling it \"\n            \"on some data.\",\n            stacklevel=2,\n        )\n    saving_v3_enabled_value = getattr(_SAVING_V3_ENABLED, \"value\", False)\n    _SAVING_V3_ENABLED.value = True\n\n    serialized_model_dict = serialize_keras_object(model)\n    config_json = json.dumps(serialized_model_dict)\n    metadata_json = json.dumps(\n        {\n            \"keras_version\": keras.__version__,\n            \"date_saved\": datetime.datetime.now().strftime(\"%Y-%m-%d@%H:%M:%S\"),\n        }\n    )\n    try:\n        with zipfile.ZipFile(filepath, \"w\") as zf:\n\n            with zf.open(_METADATA_FILENAME, \"w\") as f:\n                f.write(metadata_json.encode())\n            with zf.open(_CONFIG_FILENAME, \"w\") as f:\n                f.write(config_json.encode())\n\n            if weights_format == \"h5\":\n                weights_store = H5IOStore(\n                    _VARS_FNAME + \".h5\", archive=zf, mode=\"w\"\n                )\n            elif weights_format == \"npz\":\n                weights_store = NpzIOStore(\n                    _VARS_FNAME + \".npz\", archive=zf, mode=\"w\"\n                )\n            else:\n                raise ValueError(\n                    \"Unknown weights_format. Expected 'h5' or 'npz'. \"\n                    f\"Received: {weights_format}\"\n                )\n\n            asset_store = DiskIOStore(_ASSETS_DIRNAME, archive=zf, mode=\"w\")\n\n            _save_state(\n                model,\n                weights_handler=weights_store,\n                assets_handler=asset_store,\n                inner_path=\"\",\n                visited_trackables=set(),\n            )\n            weights_store.close()\n            asset_store.close()\n\n    except Exception as e:\n        raise e\n    finally:\n        _SAVING_V3_ENABLED.value = saving_v3_enabled_value\n\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 17,
        "n_whitespaces": 770,
        "n_words": 181,
        "vocab_size": 129,
        "complexity": 9,
        "nloc": 59,
        "token_counts": 291,
        "n_ast_nodes": 521,
        "n_identifiers": 54,
        "d_id": 83285,
        "documentation": {
            "docstring": "Save a zip-archive representing a Keras model to the given filepath.\n\n    The zip-based archive contains the following structure:\n\n    - JSON-based configuration file (config.json): Records of model, layer, and\n        other trackables' configuration.\n    - NPZ-based trackable state files, found in respective directories, such as\n        model/states.npz, model/dense_layer/states.npz, etc.\n    - Metadata file.\n\n    The states of Keras trackables (layers, optimizers, loss, and metrics) are\n    automatically saved as long as they can be discovered through the attributes\n    returned by `dir(Model)`. Typically, the state includes the variables\n    associated with the trackable, but some specially purposed layers may\n    contain more such as the vocabularies stored in the hashmaps. The trackables\n    define how their states are saved by exposing `save_state()` and\n    `load_state()` APIs.\n\n    For the case of layer states, the variables will be visited as long as\n    they are either 1) referenced via layer attributes, or 2) referenced via a\n    container (list, tuple, or dict), and the container is referenced via a\n    layer attribute.\n    ",
            "n_words": 155,
            "vocab_size": 106,
            "n_whitespaces": 217,
            "language": "en"
        }
    },
    {
        "id": 165545,
        "commit_id": "eb2abb86616978ef6e4971b600849ccabc686de4",
        "repo": "pandas",
        "path": "pandas/core/arrays/sparse/dtype.py",
        "file_name": "dtype.py",
        "fun_name": "update_dtype",
        "commit_message": "CLN: address xfails (#46287)",
        "code": "def update_dtype(self, dtype) -> SparseDtype:\n        \n        cls = type(self)\n        dtype = pandas_dtype(dtype)\n\n        if not isinstance(dtype, cls):\n            if not isinstance(dtype, np.dtype):\n                raise TypeError(\"sparse arrays of extension dtypes not supported\")\n\n            fvarr = astype_nansafe(np.array(self.fill_value), dtype)\n            # NB: not fv_0d.item(), as that casts dt64->int\n            fill_value = fvarr[0]\n            dtype = cls(dtype, fill_value=fill_value)\n\n        return dtype\n",
        "url": "https://github.com/pandas-dev/pandas.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 153,
        "n_words": 48,
        "vocab_size": 36,
        "complexity": 3,
        "nloc": 47,
        "token_counts": 80,
        "n_ast_nodes": 130,
        "n_identifiers": 14,
        "d_id": 39677,
        "documentation": {
            "docstring": "\n        Convert the SparseDtype to a new dtype.\n\n        This takes care of converting the ``fill_value``.\n\n        Parameters\n        ----------\n        dtype : Union[str, numpy.dtype, SparseDtype]\n            The new dtype to use.\n\n            * For a SparseDtype, it is simply returned\n            * For a NumPy dtype (or str), the current fill value\n              is converted to the new dtype, and a SparseDtype\n              with `dtype` and the new fill value is returned.\n\n        Returns\n        -------\n        SparseDtype\n            A new SparseDtype with the correct `dtype` and fill value\n            for that `dtype`.\n\n        Raises\n        ------\n        ValueError\n            When the current fill value cannot be converted to the\n            new `dtype` (e.g. trying to convert ``np.nan`` to an\n            integer dtype).\n\n\n        Examples\n        --------\n        >>> SparseDtype(int, 0).update_dtype(float)\n        Sparse[float64, 0.0]\n\n        >>> SparseDtype(int, 1).update_dtype(SparseDtype(float, np.nan))\n        Sparse[float64, nan]\n        ",
            "n_words": 116,
            "vocab_size": 71,
            "n_whitespaces": 357,
            "language": "en"
        }
    },
    {
        "id": 280501,
        "commit_id": "5a105aadbdc6fde2c2529280c4789864adbb81c7",
        "repo": "keras",
        "path": "keras/optimizers/__init__.py",
        "file_name": "__init__.py",
        "fun_name": "convert_to_legacy_optimizer",
        "commit_message": "Move new optimizer out of optimizer_experimental/ directory.\n\nPiperOrigin-RevId: 488998585",
        "code": "def convert_to_legacy_optimizer(optimizer):\n    \n    if not isinstance(optimizer, base_optimizer.Optimizer):\n        raise ValueError(\n            \"`convert_to_legacy_optimizer` should only be called \"\n            \"on instances of `tf.keras.optimizers.Optimizer`, but \"\n            f\"received {optimizer} of type {type(optimizer)}.\"\n        )\n    optimizer_name = optimizer.__class__.__name__.lower()\n    config = optimizer.get_config()\n    # Remove fields that only exist in experimental optimizer.\n    keys_to_remove = [\n        \"weight_decay\",\n        \"use_ema\",\n        \"ema_momentum\",\n        \"ema_overwrite_frequency\",\n        \"jit_compile\",\n        \"is_legacy_optimizer\",\n    ]\n    for key in keys_to_remove:\n        config.pop(key, None)\n    # Learning rate can be a custom LearningRateSchedule, which is stored as\n    # a dict in config, and cannot be deserialized.\n    if isinstance(\n        optimizer._learning_rate, learning_rate_schedule.LearningRateSchedule\n    ):\n        config[\"learning_rate\"] = optimizer._learning_rate\n    legacy_optimizer_config = {\n        \"class_name\": optimizer_name,\n        \"config\": config,\n    }\n    return deserialize(legacy_optimizer_config, use_legacy_optimizer=True)\n\n\n@keras_export(\"keras.optimizers.get\")",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.optimizers.get\")",
        "n_ast_errors": 1,
        "ast_levels": 14,
        "n_whitespaces": 266,
        "n_words": 98,
        "vocab_size": 82,
        "complexity": 4,
        "nloc": 28,
        "token_counts": 113,
        "n_ast_nodes": 220,
        "n_identifiers": 23,
        "d_id": 83358,
        "documentation": {
            "docstring": "Convert experimental optimizer to legacy optimizer.\n\n    This function takes in a `tf.keras.optimizers.experimental.Optimizer`\n    instance and converts it to the corresponding\n    `tf.keras.optimizers.legacy.Optimizer` instance.\n    For example, `tf.keras.optimizers.experimental.Adam(...)` to\n    `tf.keras.optimizers.legacy.Adam(...)`.\n\n    Args:\n        optimizer: An instance of `tf.keras.optimizers.experimental.Optimizer`.\n    ",
            "n_words": 32,
            "vocab_size": 29,
            "n_whitespaces": 60,
            "language": "en"
        }
    },
    {
        "id": 277089,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/utils/tf_utils.py",
        "file_name": "tf_utils.py",
        "fun_name": "is_symbolic_tensor",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def is_symbolic_tensor(tensor):\n    \n    if isinstance(tensor, tf.Tensor):\n        return hasattr(tensor, \"graph\")\n    elif is_extension_type(tensor):\n        component_tensors = tf.nest.flatten(tensor, expand_composites=True)\n        return any(hasattr(t, \"graph\") for t in component_tensors)\n    elif isinstance(tensor, tf.Variable):\n        # Variables that are output of a Keras Layer in Functional API mode\n        # should be considered symbolic.\n        # TODO(omalleyt): We need a better way to check this in order to\n        # enable `run_eagerly=True` for Models containing Layers that\n        # return Variables as outputs.\n        return (\n            getattr(tensor, \"_keras_history\", False)\n            or not tf.executing_eagerly()\n        )\n    elif isinstance(tensor, tuple(_user_convertible_tensor_types)):\n        tensor = ops.convert_to_tensor_or_composite(tensor)\n        return is_symbolic_tensor(tensor)\n    else:\n        return False\n\n\n@keras_export(\"keras.__internal__.utils.register_symbolic_tensor_type\", v1=[])",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "@keras_export(\"keras.__internal__.utils.register_symbolic_tensor_type\", v1=[])",
        "n_ast_errors": 1,
        "ast_levels": 13,
        "n_whitespaces": 220,
        "n_words": 90,
        "vocab_size": 68,
        "complexity": 7,
        "nloc": 16,
        "token_counts": 113,
        "n_ast_nodes": 205,
        "n_identifiers": 22,
        "d_id": 81861,
        "documentation": {
            "docstring": "Returns whether a tensor is symbolic (from a TF graph) or an eager tensor.\n\n    A Variable can be seen as either: it is considered symbolic\n    when we are in a graph scope, and eager when we are in an eager scope.\n\n    Args:\n      tensor: A tensor instance to test.\n\n    Returns:\n      True for symbolic tensors, False for eager tensors.\n    ",
            "n_words": 57,
            "vocab_size": 41,
            "n_whitespaces": 82,
            "language": "en"
        }
    },
    {
        "id": 100532,
        "commit_id": "bdbbad4d310fb606b6f412aa81e9f57ccd994e97",
        "repo": "faceswap",
        "path": "lib/gpu_stats/_base.py",
        "file_name": "_base.py",
        "fun_name": "sys_info",
        "commit_message": "Refactor lib.gpu_stats (#1218)\n\n* inital gpu_stats refactor\r\n\r\n* Add dummy CPU Backend\r\n\r\n* Update Sphinx documentation",
        "code": "def sys_info(self) -> GPUInfo:\n        \n        return GPUInfo(vram=self._vram,\n                       driver=self._driver,\n                       devices=self._device_names,\n                       devices_active=self._active_devices)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 89,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 35,
        "n_ast_nodes": 54,
        "n_identifiers": 11,
        "d_id": 19996,
        "documentation": {
            "docstring": " dict: GPU Stats that are required for system information logging.\n\n        The dictionary contains the following data:\n\n            **vram** (`list`): the total amount of VRAM in Megabytes for each GPU as pertaining to\n            :attr:`_handles`\n\n            **driver** (`str`): The GPU driver version that is installed on the OS\n\n            **devices** (`list`): The device name of each GPU on the system as pertaining\n            to :attr:`_handles`\n\n            **devices_active** (`list`): The device name of each active GPU on the system as\n            pertaining to :attr:`_handles`\n        ",
            "n_words": 75,
            "vocab_size": 42,
            "n_whitespaces": 167,
            "language": "en"
        }
    },
    {
        "id": 272032,
        "commit_id": "84afc5193d38057e2e2badf9c889ea87d80d8fbf",
        "repo": "keras",
        "path": "keras/feature_column/base_feature_layer.py",
        "file_name": "base_feature_layer.py",
        "fun_name": "_normalize_feature_columns",
        "commit_message": "Reformatting the codebase with black.\n\nPiperOrigin-RevId: 450093126",
        "code": "def _normalize_feature_columns(feature_columns):\n    \n    if isinstance(\n        feature_columns, tf.__internal__.feature_column.FeatureColumn\n    ):\n        feature_columns = [feature_columns]\n\n    if isinstance(feature_columns, collections.abc.Iterator):\n        feature_columns = list(feature_columns)\n\n    if isinstance(feature_columns, dict):\n        raise ValueError(\"Expected feature_columns to be iterable, found dict.\")\n\n    for column in feature_columns:\n        if not isinstance(column, tf.__internal__.feature_column.FeatureColumn):\n            raise ValueError(\n                \"Items of feature_columns must be a FeatureColumn. \"\n                \"Given (type {}): {}.\".format(type(column), column)\n            )\n    if not feature_columns:\n        raise ValueError(\"feature_columns must not be empty.\")\n    name_to_column = {}\n    for column in feature_columns:\n        if column.name in name_to_column:\n            raise ValueError(\n                \"Duplicate feature column name found for columns: {} \"\n                \"and {}. This usually means that these columns refer to \"\n                \"same base feature. Either one must be discarded or a \"\n                \"duplicated but renamed item must be inserted in \"\n                \"features dict.\".format(column, name_to_column[column.name])\n            )\n        name_to_column[column.name] = column\n\n    return sorted(feature_columns, key=lambda x: x.name)\n",
        "url": "https://github.com/keras-team/keras.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 360,
        "n_words": 125,
        "vocab_size": 81,
        "complexity": 9,
        "nloc": 29,
        "token_counts": 160,
        "n_ast_nodes": 266,
        "n_identifiers": 21,
        "d_id": 80944,
        "documentation": {
            "docstring": "Normalizes the `feature_columns` input.\n\n    This method converts the `feature_columns` to list type as best as it can. In\n    addition, verifies the type and other parts of feature_columns, required by\n    downstream library.\n\n    Args:\n      feature_columns: The raw feature columns, usually passed by users.\n\n    Returns:\n      The normalized feature column list.\n\n    Raises:\n      ValueError: for any invalid inputs, such as empty, duplicated names, etc.\n    ",
            "n_words": 59,
            "vocab_size": 50,
            "n_whitespaces": 95,
            "language": "en"
        }
    },
    {
        "id": 159776,
        "commit_id": "66a61b03658f3c9f312505dcf7eab07e4cf91ac6",
        "repo": "numpy",
        "path": "numpy/lib/tests/test_io.py",
        "file_name": "test_io.py",
        "fun_name": "test_loadtxt_converter_with_unicode_dtype",
        "commit_message": "Port over tests from npreadtext test suite\n\n- Add test for parsing scientific notation.\n- Add multiple-char comment test.\n- Port over tests for structured dtypes.\n- Add tests for exceptions on skiprows/max_rows.\n- port over ndmin tests.\n- Make structured data reusable, add unpack tests.\n- Port over delimiter tests.\n- Port over maxrows test w/ various dtypes.\n- Port over test of exception msg on parse failure.\n- Port over test for converters w/neg indices.\n- Port over usecols tests\n- Port over unicode tests.\n- Port over more converter tests.\n- Port over test for large rows.\n- Port over test for string-len discovery.\n- Port over float conversion accuracy test.\n- Port over bool test.\n- Add test for implicit float->int conversion.\n- Port over complex parsing tests.\n- Port over tests for reading from generator.\n- Port over object cleanup test.\n- Port over bytes incompat test.\n- Port over converters tests.\n\nCo-authored-by: Warren Weckesser <warren.weckesser@gmail.com>\nCo-authored-by: Sebastian Berg <sebastian@sipsolutions.net>",
        "code": "def test_loadtxt_converter_with_unicode_dtype():\n    \n    txt = StringIO('abc,def\\nrst,xyz')\n    conv = bytes.upper\n    res = np.loadtxt(txt, dtype=np.dtype(\"U3\"), converters=conv, delimiter=\",\")\n    expected = np.array([['ABC', 'DEF'], ['RST', 'XYZ']])\n    assert_equal(res, expected)\n\n",
        "url": "https://github.com/numpy/numpy.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 12,
        "n_whitespaces": 40,
        "n_words": 22,
        "vocab_size": 19,
        "complexity": 1,
        "nloc": 6,
        "token_counts": 67,
        "n_ast_nodes": 118,
        "n_identifiers": 15,
        "d_id": 38421,
        "documentation": {
            "docstring": "\n    With the default 'bytes' encoding, tokens are encoded prior to being passed\n    to the converter. This means that the output of the converter may be bytes\n    instead of unicode as expected by `read_rows`.\n\n    This test checks that outputs from the above scenario are properly decoded\n    prior to parsing by `read_rows`.\n    ",
            "n_words": 50,
            "vocab_size": 37,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 127516,
        "commit_id": "96cceb08e8bf73df990437002e25883c5a72d30c",
        "repo": "ray",
        "path": "python/ray/tune/execution/placement_groups.py",
        "file_name": "placement_groups.py",
        "fun_name": "required_resources",
        "commit_message": "[tune] Raise error in PGF if head and worker bundles are empty (#28445)\n\nScheduling empty placement groups is not supported by Ray core (see e.g. #28443), so we shouldn't allow them to be created in the first place.\r\n\r\nIf we need fully empty resource requests, we can include this in the upcoming execution/resource refactor.\r\n\r\nSigned-off-by: Kai Fricke <kai@anyscale.com>",
        "code": "def required_resources(self) -> Dict[str, float]:\n        \n        return _sum_bundles(self._bundles)\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 8,
        "n_whitespaces": 21,
        "n_words": 7,
        "vocab_size": 7,
        "complexity": 1,
        "nloc": 3,
        "token_counts": 20,
        "n_ast_nodes": 33,
        "n_identifiers": 7,
        "d_id": 28458,
        "documentation": {
            "docstring": "Returns a dict containing the sums of all resources",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 308196,
        "commit_id": "0ac581a0b1fa438a53f048adfab9b787884a63f6",
        "repo": "core",
        "path": "tests/components/webostv/test_media_player.py",
        "file_name": "test_media_player.py",
        "fun_name": "test_supported_features_ignore_cache",
        "commit_message": "Cleanup EntityFeature in tests (#78859)",
        "code": "async def test_supported_features_ignore_cache(hass, client):\n    \n    mock_restore_cache(\n        hass,\n        [\n            State(\n                ENTITY_ID,\n                STATE_OFF,\n                attributes={\n                    ATTR_SUPPORTED_FEATURES: SUPPORT_WEBOSTV | SUPPORT_WEBOSTV_VOLUME,\n                },\n            )\n        ],\n    )\n    await setup_webostv(hass)\n\n    supported = (\n        SUPPORT_WEBOSTV | SUPPORT_WEBOSTV_VOLUME | MediaPlayerEntityFeature.VOLUME_SET\n    )\n    attrs = hass.states.get(ENTITY_ID).attributes\n\n    assert attrs[ATTR_SUPPORTED_FEATURES] == supported\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 190,
        "n_words": 37,
        "vocab_size": 30,
        "complexity": 1,
        "nloc": 19,
        "token_counts": 69,
        "n_ast_nodes": 107,
        "n_identifiers": 18,
        "d_id": 106957,
        "documentation": {
            "docstring": "Test ignore cached supported features if device is on at startup.",
            "n_words": 11,
            "vocab_size": 11,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 320860,
        "commit_id": "265b018c172f8c1f6d9e7f8850256363f0629f82",
        "repo": "qutebrowser",
        "path": "qutebrowser/browser/commands.py",
        "file_name": "commands.py",
        "fun_name": "search_next",
        "commit_message": "Add a SearchMatch helper class",
        "code": "def search_next(self, count=1):\n        \n        tab = self._current_widget()\n        window_text = self._tabbed_browser.search_text\n        window_options = self._tabbed_browser.search_options\n\n        if window_text is None:\n            raise cmdutils.CommandError(\"No search done yet.\")\n\n        tab.scroller.before_jump_requested.emit()\n\n        if window_text is not None and window_text != tab.search.text:\n            tab.search.clear()\n            tab.search.search(window_text, **window_options)\n            count -= 1\n\n        if count == 0:\n            return\n\n        cb = functools.partial(self._search_cb, tab=tab,\n                               old_match=tab.search.match,\n                               options=window_options, text=window_text,\n                               prev=False)\n\n        for _ in range(count - 1):\n            tab.search.next_result()\n        tab.search.next_result(result_cb=cb)\n",
        "url": "https://github.com/qutebrowser/qutebrowser.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 291,
        "n_words": 58,
        "vocab_size": 48,
        "complexity": 6,
        "nloc": 20,
        "token_counts": 154,
        "n_ast_nodes": 243,
        "n_identifiers": 30,
        "d_id": 117401,
        "documentation": {
            "docstring": "Continue the search to the ([count]th) next term.\n\n        Args:\n            count: How many elements to ignore.\n        ",
            "n_words": 15,
            "vocab_size": 13,
            "n_whitespaces": 40,
            "language": "en"
        }
    },
    {
        "id": 207420,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/admin_utils/test_logentry.py",
        "file_name": "test_logentry.py",
        "fun_name": "test_logentry_change_message_localized_datetime_input",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_logentry_change_message_localized_datetime_input(self):\n        \n        post_data = {\n            \"site\": self.site.pk,\n            \"title\": \"Changed\",\n            \"hist\": \"Some content\",\n            \"created_0\": \"12/03/2008\",\n            \"created_1\": \"11:54\",\n        }\n        with translation.override(\"fr\"):\n            change_url = reverse(\n                \"admin:admin_utils_article_change\", args=[quote(self.a1.pk)]\n            )\n            response = self.client.post(change_url, post_data)\n            self.assertRedirects(\n                response, reverse(\"admin:admin_utils_article_changelist\")\n            )\n        logentry = LogEntry.objects.filter(\n            content_type__model__iexact=\"article\"\n        ).latest(\"id\")\n        self.assertEqual(logentry.get_change_message(), \"Changed Title and History.\")\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 16,
        "n_whitespaces": 243,
        "n_words": 43,
        "vocab_size": 39,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 113,
        "n_ast_nodes": 206,
        "n_identifiers": 24,
        "d_id": 51961,
        "documentation": {
            "docstring": "\n        Localized date/time inputs shouldn't affect changed form data detection.\n        ",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 24,
            "language": "en"
        }
    },
    {
        "id": 300693,
        "commit_id": "4e9bc9eaffd464f192d187a01771a86699b2f932",
        "repo": "core",
        "path": "tests/util/test_dt.py",
        "file_name": "test_dt.py",
        "fun_name": "test_find_next_time_expression_microseconds",
        "commit_message": "Small cleanups to find_next_time_expression and addition of tests (#71845)",
        "code": "def test_find_next_time_expression_microseconds():\n    \n    hour_minute_second = (None, \"5\", \"10\")\n    test_time = datetime(2022, 5, 13, 0, 5, 9, tzinfo=dt_util.UTC)\n    matching_hours, matching_minutes, matching_seconds = _get_matches(\n        *hour_minute_second\n    )\n    next_time = dt_util.find_next_time_expression_time(\n        test_time, matching_seconds, matching_minutes, matching_hours\n    )\n    assert next_time == datetime(2022, 5, 13, 0, 5, 10, tzinfo=dt_util.UTC)\n    next_time_last_microsecond_plus_one = next_time.replace(\n        microsecond=999999\n    ) + timedelta(seconds=1)\n    time_after = dt_util.find_next_time_expression_time(\n        next_time_last_microsecond_plus_one,\n        matching_seconds,\n        matching_minutes,\n        matching_hours,\n    )\n    assert time_after == datetime(2022, 5, 13, 1, 5, 10, tzinfo=dt_util.UTC)\n\n",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 10,
        "n_whitespaces": 154,
        "n_words": 66,
        "vocab_size": 36,
        "complexity": 1,
        "nloc": 20,
        "token_counts": 139,
        "n_ast_nodes": 197,
        "n_identifiers": 19,
        "d_id": 99553,
        "documentation": {
            "docstring": "Test finding next time expression with microsecond clock drift.",
            "n_words": 9,
            "vocab_size": 9,
            "n_whitespaces": 8,
            "language": "en"
        }
    },
    {
        "id": 259765,
        "commit_id": "0822851f5cb17827939a7d7b4f8c84f43184ae89",
        "repo": "scikit-learn",
        "path": "sklearn/cluster/tests/test_bisect_k_means.py",
        "file_name": "test_bisect_k_means.py",
        "fun_name": "test_float32_float64_equivalence",
        "commit_message": "FEA Bisecting K-Means (#20031)\n\nCo-authored-by: Gael Varoquaux <gael.varoquaux@normalesup.org>\r\nCo-authored-by: Tom Dupré la Tour <tom.dupre-la-tour@m4x.org>\r\nCo-authored-by: Julien Jerphanion <git@jjerphan.xyz>\r\nCo-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>",
        "code": "def test_float32_float64_equivalence(is_sparse):\n    \n    rng = np.random.RandomState(0)\n    X = rng.rand(10, 2)\n\n    if is_sparse:\n        X[X < 0.8] = 0\n        X = sp.csr_matrix(X)\n\n    km64 = BisectingKMeans(n_clusters=3, random_state=0).fit(X)\n    km32 = BisectingKMeans(n_clusters=3, random_state=0).fit(X.astype(np.float32))\n\n    assert_allclose(km32.cluster_centers_, km64.cluster_centers_)\n    assert_array_equal(km32.labels_, km64.labels_)\n",
        "url": "https://github.com/scikit-learn/scikit-learn.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 69,
        "n_words": 31,
        "vocab_size": 24,
        "complexity": 2,
        "nloc": 10,
        "token_counts": 108,
        "n_ast_nodes": 167,
        "n_identifiers": 22,
        "d_id": 75910,
        "documentation": {
            "docstring": "Check that the results are the same between float32 and float64.",
            "n_words": 11,
            "vocab_size": 10,
            "n_whitespaces": 10,
            "language": "en"
        }
    },
    {
        "id": 296896,
        "commit_id": "5d1ca73a3491f0abf5925e01465c4525a49dafef",
        "repo": "core",
        "path": "tests/components/google/test_calendar.py",
        "file_name": "test_calendar.py",
        "fun_name": "test_all_day_reader_access",
        "commit_message": "Add create and delete for Google Calendar events (#83034)\n\n* Add Google Calendar create/delete support\r\n\r\nIncludes editing for recurring events\r\n\r\n* Fix default calendar access role\r\n\r\n* Formatting improvements\r\n\r\n* Address other details that have changed due to local sync\r\n\r\n* Update tests/components/google/test_calendar.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update tests/components/google/test_calendar.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Update tests/components/google/test_calendar.py\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>\r\n\r\n* Increase test coverage\r\n\r\nCo-authored-by: Martin Hjelmare <marhje52@gmail.com>",
        "code": "async def test_all_day_reader_access(hass, mock_events_list_items, component_setup):\n    \n    week_from_today = dt_util.now().date() + datetime.timedelta(days=7)\n    end_event = week_from_today + datetime.timedelta(days=1)\n    event = {\n        **TEST_EVENT,\n        \"start\": {\"date\": week_from_today.isoformat()},\n        \"end\": {\"date\": end_event.isoformat()},\n    }\n    mock_events_list_items([event])\n\n    assert await component_setup()\n\n    state = hass.states.get(TEST_ENTITY)\n    assert state.name == TEST_ENTITY_NAME\n    assert state.state == STATE_OFF\n    assert dict(state.attributes) == {\n        \"friendly_name\": TEST_ENTITY_NAME,\n        \"message\": event[\"summary\"],\n        \"all_day\": True,\n        \"offset_reached\": False,\n        \"start_time\": week_from_today.strftime(DATE_STR_FORMAT),\n        \"end_time\": end_event.strftime(DATE_STR_FORMAT),\n        \"location\": event[\"location\"],\n        \"description\": event[\"description\"],\n    }\n\n\n@pytest.mark.parametrize(\"calendar_access_role\", [\"reader\", \"freeBusyReader\"])",
        "url": "https://github.com/home-assistant/core.git",
        "language": "Python",
        "ast_errors": "@pytest.mark.parametrize(\"calendar_access_role\", [\"reader\", \"freeBusyReader\"])",
        "n_ast_errors": 1,
        "ast_levels": 12,
        "n_whitespaces": 177,
        "n_words": 65,
        "vocab_size": 52,
        "complexity": 1,
        "nloc": 23,
        "token_counts": 167,
        "n_ast_nodes": 312,
        "n_identifiers": 29,
        "d_id": 95868,
        "documentation": {
            "docstring": "Test that reader / freebusy reader access can load properly.",
            "n_words": 10,
            "vocab_size": 9,
            "n_whitespaces": 9,
            "language": "en"
        }
    },
    {
        "id": 101037,
        "commit_id": "7b9fc0454d982a2425ec44e90e5b05a87d149953",
        "repo": "faceswap",
        "path": "scripts/train.py",
        "file_name": "train.py",
        "fun_name": "_set_resize_callback",
        "commit_message": "Live Preview - Replace cv2 with matplotlib viewer",
        "code": "def _set_resize_callback(self):\n        \n        if self._full_size:\n            logger.debug(\"Setting resize callback for actual size display\")\n            for fig, size in self._images.values():\n                self._resize_ids.append((fig, fig.canvas.mpl_connect(\"resize_event\",\n                                                                     self._on_resize)))\n                fig.set_size_inches(size)\n        else:\n            logger.debug(\"Removing resize callback for screen-fit display\")\n            for fig, cid in self._resize_ids:\n                fig.canvas.mpl_disconnect(cid)\n            self._resize_ids = []\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 15,
        "n_whitespaces": 225,
        "n_words": 36,
        "vocab_size": 27,
        "complexity": 4,
        "nloc": 12,
        "token_counts": 90,
        "n_ast_nodes": 151,
        "n_identifiers": 17,
        "d_id": 20476,
        "documentation": {
            "docstring": " Sets the resize callback if displaying preview at actual size or removes it if\n        displaying at screen-fit size. ",
            "n_words": 18,
            "vocab_size": 15,
            "n_whitespaces": 26,
            "language": "en"
        }
    },
    {
        "id": 220242,
        "commit_id": "8198943edd73a363c266633e1aa5b2a9e9c9f526",
        "repo": "XX-Net",
        "path": "python3.10.4/Lib/ast.py",
        "file_name": "ast.py",
        "fun_name": "block",
        "commit_message": "add python 3.10.4 for windows",
        "code": "def block(self, *, extra = None):\n        \n        self.write(\":\")\n        if extra:\n            self.write(extra)\n        self._indent += 1\n        yield\n        self._indent -= 1\n",
        "url": "https://github.com/XX-net/XX-Net.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 9,
        "n_whitespaces": 70,
        "n_words": 17,
        "vocab_size": 15,
        "complexity": 2,
        "nloc": 7,
        "token_counts": 38,
        "n_ast_nodes": 67,
        "n_identifiers": 5,
        "d_id": 55949,
        "documentation": {
            "docstring": "A context manager for preparing the source for blocks. It adds\n        the character':', increases the indentation on enter and decreases\n        the indentation on exit. If *extra* is given, it will be directly\n        appended after the colon character.\n        ",
            "n_words": 37,
            "vocab_size": 30,
            "n_whitespaces": 65,
            "language": "en"
        }
    },
    {
        "id": 137681,
        "commit_id": "e76ccee69aaa7583be1a9d81cf7b2aa72cf25647",
        "repo": "ray",
        "path": "python/ray/util/spark/utils.py",
        "file_name": "utils.py",
        "fun_name": "get_avail_mem_per_ray_worker_node",
        "commit_message": "Ray on spark implementation (#28771)\n\nREP: ray-project/enhancements#14",
        "code": "def get_avail_mem_per_ray_worker_node(spark, object_store_memory_per_node):\n    \n    num_cpus_per_spark_task = int(\n        spark.sparkContext.getConf().get(\"spark.task.cpus\", \"1\")\n    )\n",
        "url": "https://github.com/ray-project/ray.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 25,
        "n_words": 9,
        "vocab_size": 9,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 83,
        "n_ast_nodes": 49,
        "n_identifiers": 8,
        "d_id": 31216,
        "documentation": {
            "docstring": "\n    Return the available heap memory and object store memory for each ray worker.\n    NB: We have one ray node per spark task.\n    ",
            "n_words": 22,
            "vocab_size": 20,
            "n_whitespaces": 32,
            "language": "en"
        }
    },
    {
        "id": 65553,
        "commit_id": "494bd9ef78313436f0424b918f200dab8fc7c20b",
        "repo": "erpnext",
        "path": "erpnext/buying/doctype/supplier_scorecard_variable/supplier_scorecard_variable.py",
        "file_name": "supplier_scorecard_variable.py",
        "fun_name": "get_total_accepted_amount",
        "commit_message": "style: format code with black",
        "code": "def get_total_accepted_amount(scorecard):\n\t\n\tsupplier = frappe.get_doc(\"Supplier\", scorecard.supplier)\n\n\t# Look up all PO Items with delivery dates between our dates\n\tdata = frappe.db.sql(\n\t\t,\n\t\t{\"supplier\": supplier.name, \"start_date\": scorecard.start_date, \"end_date\": scorecard.end_date},\n\t\tas_dict=0,\n\t)[0][0]\n\n\tif not data:\n\t\tdata = 0\n\treturn data\n\n",
        "url": "https://github.com/frappe/erpnext.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 27,
        "n_words": 38,
        "vocab_size": 33,
        "complexity": 2,
        "nloc": 20,
        "token_counts": 68,
        "n_ast_nodes": 114,
        "n_identifiers": 12,
        "d_id": 13930,
        "documentation": {
            "docstring": "Gets the total amount (in company currency) accepted in the period (based on Purchase Receipts)\n\t\t\tSELECT\n\t\t\t\tSUM(pr_item.qty * pr_item.base_rate)\n\t\t\tFROM\n\t\t\t\t`tabPurchase Receipt Item` pr_item,\n\t\t\t\t`tabPurchase Receipt` pr\n\t\t\tWHERE\n\t\t\t\tpr.supplier = %(supplier)s\n\t\t\t\tAND pr.posting_date BETWEEN %(start_date)s AND %(end_date)s\n\t\t\t\tAND pr_item.docstatus = 1\n\t\t\t\tAND pr_item.parent = pr.name",
            "n_words": 45,
            "vocab_size": 38,
            "n_whitespaces": 34,
            "language": "en"
        }
    },
    {
        "id": 80081,
        "commit_id": "3d484e133dbf59ebc36da9a40172a454315b95b7",
        "repo": "wagtail",
        "path": "wagtail/admin/templatetags/wagtailadmin_tags.py",
        "file_name": "wagtailadmin_tags.py",
        "fun_name": "icon",
        "commit_message": "Update icon template to allow `classname`\n\n- Preserve the existing `class_name` behaviour in most other cases\n- Update only docs reference to use `classname`\n- Relates to #6107 & #6028",
        "code": "def icon(name=None, classname=None, title=None, wrapped=False, class_name=None):\n    \n    if not name:\n        raise ValueError(\"You must supply an icon name\")\n\n    return {\n        \"name\": name,\n        # supporting class_name for backwards compatibility\n        \"classname\": classname or class_name or \"icon\",\n        \"title\": title,\n        \"wrapped\": wrapped,\n    }\n\n\n@register.filter()",
        "url": "https://github.com/wagtail/wagtail.git",
        "language": "Python",
        "ast_errors": "@register.filter()",
        "n_ast_errors": 1,
        "ast_levels": 10,
        "n_whitespaces": 91,
        "n_words": 38,
        "vocab_size": 36,
        "complexity": 4,
        "nloc": 9,
        "token_counts": 56,
        "n_ast_nodes": 106,
        "n_identifiers": 9,
        "d_id": 17004,
        "documentation": {
            "docstring": "\n    Abstracts away the actual icon implementation.\n\n    Usage:\n        {% load wagtailadmin_tags %}\n        ...\n        {% icon name=\"cogs\" classname=\"icon--red\" title=\"Settings\" %}\n\n    :param name: the icon name/id, required (string)\n    :param classname: defaults to 'icon' if not provided (string)\n    :param title: accessible label intended for screen readers (string)\n    :return: Rendered template snippet (string)\n    ",
            "n_words": 48,
            "vocab_size": 38,
            "n_whitespaces": 91,
            "language": "en"
        }
    },
    {
        "id": 202523,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "tests/custom_pk/tests.py",
        "file_name": "tests.py",
        "fun_name": "test_querysets",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def test_querysets(self):\n        \n        self.assertQuerysetEqual(\n            Employee.objects.filter(pk=123),\n            [\n                \"Dan Jones\",\n            ],\n            str,\n        )\n\n        self.assertQuerysetEqual(\n            Employee.objects.filter(employee_code=123),\n            [\n                \"Dan Jones\",\n            ],\n            str,\n        )\n\n        self.assertQuerysetEqual(\n            Employee.objects.filter(pk__in=[123, 456]),\n            [\n                \"Fran Bones\",\n                \"Dan Jones\",\n            ],\n            str,\n        )\n\n        self.assertQuerysetEqual(\n            Employee.objects.all(),\n            [\n                \"Fran Bones\",\n                \"Dan Jones\",\n            ],\n            str,\n        )\n\n        self.assertQuerysetEqual(\n            Business.objects.filter(name=\"Sears\"), [\"Sears\"], lambda b: b.name\n        )\n        self.assertQuerysetEqual(\n            Business.objects.filter(pk=\"Sears\"),\n            [\n                \"Sears\",\n            ],\n            lambda b: b.name,\n        )\n",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 482,
        "n_words": 55,
        "vocab_size": 24,
        "complexity": 1,
        "nloc": 41,
        "token_counts": 157,
        "n_ast_nodes": 250,
        "n_identifiers": 14,
        "d_id": 50144,
        "documentation": {
            "docstring": "\n        Both pk and custom attribute_name can be used in filter and friends\n        ",
            "n_words": 12,
            "vocab_size": 11,
            "n_whitespaces": 27,
            "language": "en"
        }
    },
    {
        "id": 100497,
        "commit_id": "adb5975c94f0fb10296ef7f0c8d087d03a436e3c",
        "repo": "faceswap",
        "path": "lib/gui/display_analysis.py",
        "file_name": "display_analysis.py",
        "fun_name": "_set_session_summary",
        "commit_message": "Graph popup - Always open in same position",
        "code": "def _set_session_summary(self, message):\n        \n        if self._thread is None:\n            logger.debug(\"Setting session summary. (message: '%s')\", message)\n            self._thread = LongRunningTask(target=self._summarise_data,\n                                           args=(Session, ),\n                                           widget=self)\n            self._thread.start()\n            self.after(1000, lambda msg=message: self._set_session_summary(msg))\n        elif not self._thread.complete.is_set():\n            logger.debug(\"Data not yet available\")\n            self.after(1000, lambda msg=message: self._set_session_summary(msg))\n        else:\n            logger.debug(\"Retrieving data from thread\")\n            result = self._thread.get_result()\n            if result is None:\n                logger.debug(\"No result from session summary. Clearing analysis view\")\n                self._clear_session()\n                return\n            self._summary = result\n            self._thread = None\n            self.set_info(f\"Session: {message}\")\n            self._stats.tree_insert_data(self._summary)\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 13,
        "n_whitespaces": 366,
        "n_words": 66,
        "vocab_size": 47,
        "complexity": 4,
        "nloc": 22,
        "token_counts": 168,
        "n_ast_nodes": 283,
        "n_identifiers": 24,
        "d_id": 19968,
        "documentation": {
            "docstring": " Set the summary data and info message.\n\n        Parameters\n        ----------\n        message: str\n            The information message to set\n        ",
            "n_words": 16,
            "vocab_size": 16,
            "n_whitespaces": 56,
            "language": "en"
        }
    },
    {
        "id": 206249,
        "commit_id": "9c19aff7c7561e3a82978a272ecdaad40dda5c00",
        "repo": "django",
        "path": "django/template/defaultfilters.py",
        "file_name": "defaultfilters.py",
        "fun_name": "slice_filter",
        "commit_message": "Refs #33476 -- Reformatted code with Black.",
        "code": "def slice_filter(value, arg):\n    \n    try:\n        bits = []\n        for x in str(arg).split(\":\"):\n            if not x:\n                bits.append(None)\n            else:\n                bits.append(int(x))\n        return value[slice(*bits)]\n\n    except (ValueError, TypeError):\n        return value  # Fail silently.\n\n\n@register.filter(is_safe=True, needs_autoescape=True)",
        "url": "https://github.com/django/django.git",
        "language": "Python",
        "ast_errors": "@register.filter(is_safe=True, needs_autoescape=True)",
        "n_ast_errors": 1,
        "ast_levels": 16,
        "n_whitespaces": 118,
        "n_words": 29,
        "vocab_size": 28,
        "complexity": 4,
        "nloc": 11,
        "token_counts": 66,
        "n_ast_nodes": 132,
        "n_identifiers": 16,
        "d_id": 51440,
        "documentation": {
            "docstring": "\n    Return a slice of the list using the same syntax as Python's list slicing.\n    ",
            "n_words": 14,
            "vocab_size": 12,
            "n_whitespaces": 21,
            "language": "en"
        }
    },
    {
        "id": 186022,
        "commit_id": "853d05631d69044c17dfbc568bb887128d704a1a",
        "repo": "textual",
        "path": "src/textual/widgets/_list_view.py",
        "file_name": "_list_view.py",
        "fun_name": "clear",
        "commit_message": "PR feedback",
        "code": "def clear(self) -> AwaitRemove:\n        \n        await_remove = self.query(\"ListView > ListItem\").remove()\n        self.index = None\n        return await_remove\n",
        "url": "https://github.com/Textualize/textual.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 11,
        "n_whitespaces": 42,
        "n_words": 14,
        "vocab_size": 12,
        "complexity": 1,
        "nloc": 10,
        "token_counts": 27,
        "n_ast_nodes": 49,
        "n_identifiers": 7,
        "d_id": 45298,
        "documentation": {
            "docstring": "Clear all items from the ListView.\n\n        Returns:\n            AwaitRemove: An awaitable that yields control to the event loop until\n                the DOM has been updated to reflect all children being removed.\n        ",
            "n_words": 29,
            "vocab_size": 25,
            "n_whitespaces": 69,
            "language": "en"
        }
    },
    {
        "id": 100607,
        "commit_id": "0f7ee1603f093e70496da1585f137f268c0c5f87",
        "repo": "faceswap",
        "path": "scripts/train.py",
        "file_name": "train.py",
        "fun_name": "_get_images",
        "commit_message": "training - Enable resize in popup preview image",
        "code": "def _get_images(self):\n        \n        logger.debug(\"Getting image paths\")\n        images = {}\n        for side in (\"a\", \"b\"):\n            image_dir = getattr(self._args, f\"input_{side}\")\n            if not os.path.isdir(image_dir):\n                logger.error(\"Error: '%s' does not exist\", image_dir)\n                sys.exit(1)\n\n            images[side] = get_image_paths(image_dir, \".png\")\n            if not images[side]:\n                logger.error(\"Error: '%s' contains no images\", image_dir)\n                sys.exit(1)\n            # Validate the first image is a detected face\n            test_image = next(img for img in images[side])\n            meta = read_image_meta(test_image)\n            logger.debug(\"Test file: (filename: %s, metadata: %s)\", test_image, meta)\n            if \"itxt\" not in meta or \"alignments\" not in meta[\"itxt\"]:\n                logger.error(\"The input folder '%s' contains images that are not extracted faces.\",\n                             image_dir)\n                logger.error(\"You can only train a model on faces generated from Faceswap's \"\n                             \"extract process. Please check your sources and try again.\")\n                sys.exit(1)\n\n            logger.info(\"Model %s Directory: '%s' (%s images)\",\n                        side.upper(), image_dir, len(images[side]))\n        logger.debug(\"Got image paths: %s\", [(key, str(len(val)) + \" images\")\n                                             for key, val in images.items()])\n        self._validate_image_counts(images)\n        return images\n",
        "url": "https://github.com/deepfakes/faceswap.git",
        "language": "Python",
        "ast_errors": "",
        "n_ast_errors": 0,
        "ast_levels": 14,
        "n_whitespaces": 525,
        "n_words": 138,
        "vocab_size": 105,
        "complexity": 8,
        "nloc": 27,
        "token_counts": 219,
        "n_ast_nodes": 375,
        "n_identifiers": 29,
        "d_id": 20070,
        "documentation": {
            "docstring": " Check the image folders exist and contains valid extracted faces. Obtain image paths.\n\n        Returns\n        -------\n        dict\n            The image paths for each side. The key is the side, the value is the list of paths\n            for that side.\n        ",
            "n_words": 37,
            "vocab_size": 27,
            "n_whitespaces": 88,
            "language": "en"
        }
    }
]