Datasets:

semeru

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code-text-galeras-code-summarization-3k-deduped

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Semeru Lab 7

as_airbyte_message

def as_airbyte_message(self) -> AirbyteMessage: now_millis = datetime.now().timestamp() * 1000.0 trace_exc = self._exception or self stack_trace_str = "".join(traceback.TracebackException.from_exception(trace_exc).format()) trace_message = AirbyteTraceMessage( type=TraceType.ERROR, emitted_at=now_millis, error=AirbyteErrorTraceMessage( message=self.message or "Something went wrong in the connector. See the logs for more details.", internal_message=self.internal_message, failure_type=self.failure_type, stack_trace=stack_trace_str, ), ) return AirbyteMessage(type=MessageType.TRACE, trace=trace_message)

73c7fad7fce952a8c3ba827ca858e4280bd846f3

traced_exception.py

CDK: emit `AirbyteTraceMessage` with exception trace information (#12593)

airbyte

airbyte-cdk/python/airbyte_cdk/utils/traced_exception.py

Python

https://github.com/airbytehq/airbyte.git

_get_model_info

def _get_model_info(self, model_name): # noqa return self.storage.get('models')[model_name]

4b49bf89ad95fcc645a249983efd764c1a73e3bb

lightwood_handler.py

copy from /lightwood_handler branch: added generic serializer for dill support, lw integration functional

mindsdb

mindsdb/integrations/lightwood_handler/lightwood_handler/lightwood_handler.py

Python

https://github.com/mindsdb/mindsdb.git

get_views

def get_views(self): query = f"SELECT * FROM information_schema.views WHERE table_schema NOT IN ('information_schema', 'pg_catalog')" result = self.run_native_query(query) return result

7e3da9157508a5eb38dbfabbd7f08ba8fa6c5a88

postgres_handler.py

Get tables, views, describe

mindsdb

mindsdb/integrations/postgres_handler/postgres_handler.py

Python

https://github.com/mindsdb/mindsdb.git

mod_inverse

def mod_inverse(a, m): r c = None try: a, m = as_int(a), as_int(m) if m != 1 and m != -1: x, _, g = igcdex(a, m) if g == 1: c = x % m except ValueError: a, m = sympify(a), sympify(m) if not (a.is_number and m.is_number): raise TypeError(filldedent()) big = (m > 1) if big not in (S.true, S.false): raise ValueError('m > 1 did not evaluate; try to simplify %s' % m) elif big: c = 1/a if c is None: raise ValueError('inverse of %s (mod %s) does not exist' % (a, m)) return c

f3b08522003f40868afb20304fc0fa5b16d13f6a

numbers.py

Cleanup documentation

sympy

sympy/core/numbers.py

Python

https://github.com/sympy/sympy.git

potentially_ragged_concat

def potentially_ragged_concat(tensors): if len(tensors) == 1: return tensors[0] if isinstance(tensors[0], tf.SparseTensor): return tf.sparse.concat(axis=0, sp_inputs=tensors) elif isinstance(tensors[0], tf.RaggedTensor): return tf.concat(tensors, axis=0) elif not tf.__internal__.tf2.enabled(): return tf.concat(tensors, axis=0) non_batch_shapes = tf.stack([tf.shape(tensor)[1:] for tensor in tensors]) constant_dims = tf.math.reduce_all( non_batch_shapes == non_batch_shapes[:1], axis=0 ) if tf.math.reduce_all(constant_dims).numpy().item(): # All non-batch dims are constant return tf.concat(tensors, axis=0) # First, identify constant inner dimensions by finding the # rightmost dimension that is not constant constant_inner_dimensions = ( constant_dims.numpy().tolist()[::-1].index(False) ) # If there are constant inner dimensions, define a constant inner shape if constant_inner_dimensions == 0: constant_inner_shape = None else: constant_inner_shape = tensors[0].shape[-constant_inner_dimensions:] return tf.ragged.constant( [tensor.numpy() for tensor in tensors], inner_shape=constant_inner_shape ).merge_dims(0, 1)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/training.py

Python

https://github.com/keras-team/keras.git

dag_longest_path

def dag_longest_path(G, weight="weight", default_weight=1, topo_order=None): if not G: return [] if topo_order is None: topo_order = nx.topological_sort(G) dist = {} # stores {v : (length, u)} for v in topo_order: us = [ (dist[u][0] + data.get(weight, default_weight), u) for u, data in G.pred[v].items() ] # Use the best predecessor if there is one and its distance is # non-negative, otherwise terminate. maxu = max(us, key=lambda x: x[0]) if us else (0, v) dist[v] = maxu if maxu[0] >= 0 else (0, v) u = None v = max(dist, key=lambda x: dist[x][0]) path = [] while u != v: path.append(v) u = v v = dist[v][1] path.reverse() return path @not_implemented_for("undirected")

304682fd71ba3bae9c456b004bbabafb96022add

@not_implemented_for("undirected")

dag.py

Add example of topo_order kwarg to dag_longest_path (#5728)

networkx

networkx/algorithms/dag.py

Python

https://github.com/networkx/networkx.git

test_conversation_part_filtering_based_on_conversation

def test_conversation_part_filtering_based_on_conversation(requests_mock, conversation_parts_responses): updated_at = 1650988200 state = {"updated_at": updated_at} expected_record_ids = set() for response_tuple in conversation_parts_responses: requests_mock.register_uri('GET', response_tuple[0], json=response_tuple[1]) if "conversation_parts" in response_tuple[1]: expected_record_ids.update([cp["id"] for cp in response_tuple[1]["conversation_parts"]["conversation_parts"]]) records = [] conversation_parts = ConversationParts(authenticator=NoAuth()) for slice in conversation_parts.stream_slices(sync_mode=SyncMode.incremental, stream_state=state): records.extend(list(conversation_parts.read_records(sync_mode=SyncMode.incremental, stream_slice=slice, stream_state=state))) assert expected_record_ids == {r["id"] for r in records}

1642630461c25e447ede67bb42ba6ea6ec700e52

unit_test.py

🐛 Source Intercom: Fixed filtering of conversation_parts (#12374)

airbyte

airbyte-integrations/connectors/source-intercom/unit_tests/unit_test.py

Python

https://github.com/airbytehq/airbyte.git

get_lexer_for_mimetype

def get_lexer_for_mimetype(_mime, **options): for modname, name, _, _, mimetypes in LEXERS.values(): if _mime in mimetypes: if name not in _lexer_cache: _load_lexers(modname) return _lexer_cache[name](**options) for cls in find_plugin_lexers(): if _mime in cls.mimetypes: return cls(**options) raise ClassNotFound('no lexer for mimetype %r found' % _mime)

f3166e673fe8d40277b804d35d77dcdb760fc3b3

__init__.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * 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

pipenv

pipenv/patched/notpip/_vendor/pygments/lexers/__init__.py

Python

https://github.com/pypa/pipenv.git

_extract_gradient_tags

def _extract_gradient_tags(self): tags = re.finditer( r'<gradient\s+from="([^"]+)"\s+to="([^"]+)"(\s+offset="([^"]+)")?>(.+?)</gradient>', self.original_text, re.S, ) gradientmap = [] for tag in tags: start = self._count_real_chars(self.original_text[: tag.start(0)]) end = start + self._count_real_chars(tag.group(5)) offsets = tag.group(4).split(",") if tag.group(4) else [0] start_offset = int(offsets[0]) if offsets[0] else 0 end_offset = int(offsets[1]) if len(offsets) == 2 and offsets[1] else 0 gradientmap.append( { "start": start, "end": end, "from": tag.group(1), "to": tag.group(2), "start_offset": start_offset, "end_offset": end_offset, }, ) self.text = re.sub("<gradient[^>]+>(.+?)</gradient>", r"\1", self.text, 0, re.S) return gradientmap

902e7eb4f0147b5882a613b67467e38a1d47f01e

text_mobject.py

Hide more private methods from the docs. (#2468) * hide privs from text_mobject.py * hide privs from tex_mobject.py * hide privs from code_mobject.py * hide privs from svg_mobject.py * remove SVGPath and utils from __init__.py * don't import string_to_numbers * hide privs from geometry.py * hide privs from matrix.py * hide privs from numbers.py * hide privs from three_dimensions.py * forgot underscore under set_stroke_width_from_length * there were more i missed * unhidea method that was used in docs * forgot other text2hash * remove svg_path from docs

manim

manim/mobject/svg/text_mobject.py

Python

https://github.com/ManimCommunity/manim.git

get_feature_names_out

def get_feature_names_out(self, input_features=None): input_features = _check_feature_names_in( self, input_features, generate_names=True ) est_name = self.__class__.__name__.lower() names_list = [f"{est_name}_{name}_sqrt" for name in input_features] for j in range(1, self.sample_steps): cos_names = [f"{est_name}_{name}_cos{j}" for name in input_features] sin_names = [f"{est_name}_{name}_sin{j}" for name in input_features] names_list.extend(cos_names + sin_names) return np.asarray(names_list, dtype=object)

67a3feed2fe4e82c1cc129c34b9e223b94a8d531

kernel_approximation.py

ENH Adds get_feature_names_out for AdditiveChi2Sampler (#22137) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/kernel_approximation.py

Python

https://github.com/scikit-learn/scikit-learn.git

scalar_potential_difference

def scalar_potential_difference(field, frame, point1, point2, origin): _check_frame(frame) if isinstance(field, Vector): # Get the scalar potential function scalar_fn = scalar_potential(field, frame) else: # Field is a scalar scalar_fn = field # Express positions in required frame position1 = express(point1.pos_from(origin), frame, variables=True) position2 = express(point2.pos_from(origin), frame, variables=True) # Get the two positions as substitution dicts for coordinate variables subs_dict1 = {} subs_dict2 = {} for i, x in enumerate(frame): subs_dict1[frame[i]] = x.dot(position1) subs_dict2[frame[i]] = x.dot(position2) return scalar_fn.subs(subs_dict2) - scalar_fn.subs(subs_dict1)

9a3ffc6781bd44c47cf49e128ef154389c32876a

fieldfunctions.py

Some pep8 cleanup of sympy.physics.vector.

sympy

sympy/physics/vector/fieldfunctions.py

Python

https://github.com/sympy/sympy.git

prev_lexicographic

def prev_lexicographic(self): i = self.superset_size - 1 indices = Subset.subset_indices(self.subset, self.superset) while i >= 0 and i not in indices: i = i - 1 if i == 0 or i - 1 in indices: indices.remove(i) else: if i >= 0: indices.remove(i) indices.append(i - 1) indices.append(self.superset_size - 1) ret_set = [] super_set = self.superset for i in indices: ret_set.append(super_set[i]) return Subset(ret_set, super_set)

498015021131af4dbb07eb110e5badaba8250c7b

subsets.py

Updated import locations

sympy

sympy/combinatorics/subsets.py

Python

https://github.com/sympy/sympy.git

add_base_argument

def add_base_argument(self, parser, *args, **kwargs): for arg in args: if arg in self.suppressed_base_arguments: kwargs["help"] = argparse.SUPPRESS break parser.add_argument(*args, **kwargs)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

base.py

Refs #33476 -- Reformatted code with Black.

django

django/core/management/base.py

Python

https://github.com/django/django.git

get_holiday

def get_holiday(holiday_list, month): holiday_map = frappe._dict() for d in holiday_list: if d: holiday_map.setdefault( d, frappe.db.sql( , (d, month), ), ) return holiday_map @frappe.whitelist()

494bd9ef78313436f0424b918f200dab8fc7c20b

@frappe.whitelist()

monthly_attendance_sheet.py

style: format code with black

erpnext

erpnext/hr/report/monthly_attendance_sheet/monthly_attendance_sheet.py

Python

https://github.com/frappe/erpnext.git

add_hedge_option

def add_hedge_option(price, implied_volatility, strike, days, side): # Determine delta position given the option delta = calc_delta(price, implied_volatility, strike, days, 0, side) # Determine gamma position given the option gamma = calc_gamma(price, implied_volatility, strike, days, 0) # Determine vega position given the option vega = calc_vega(price, implied_volatility, strike, days, 0) return delta, gamma, vega

54a1b6f545a0016c576e9e00eef5c003d229dacf

hedge_model.py

Feature/hedge (#1768) * [Bug] Incorrect log for reddit keys. #1733 fix * Create new feature-hedge * Significantly improve code of hedge menu * More robust * Robustness * Fix tests * Fix can't multiply sequence by non-int of type 'numpy.float64' error * Temporary fix of singular matrix error. Return first feasible solution * Update Hugo Documentation * Combining menus and cleaning up code * Tidy up call_exp * Update tests Round 1 * Update tests Round 2 * Fix linting error * Fix linting? * Fixed glitch Co-authored-by: JerBouma <[email protected]> Co-authored-by: James Maslek <[email protected]> Co-authored-by: Colin Delahunty <[email protected]> Co-authored-by: colin99d <[email protected]> Co-authored-by: didierlopes.eth <[email protected]>

OpenBBTerminal

openbb_terminal/stocks/options/hedge/hedge_model.py

Python

https://github.com/OpenBB-finance/OpenBBTerminal.git

__radd__

def __radd__(self, other): # In analogy with __rsub__ and __rdiv__, use original order: # we get here from `other + self`. return np.add(other, self)

6d77c591c59b5678f14ae5af2127eebb7d2415bc

core.py

ENH: Adding __array_ufunc__ capability to MaskedArrays. This enables any ufunc numpy operations that are called on a MaskedArray to use the masked version of that function automatically without needing to resort to np.ma.func() calls.

numpy

numpy/ma/core.py

Python

https://github.com/numpy/numpy.git

__getattribute__

def __getattribute__(self, attr): # All module metadata must be garnered from __spec__ in order to avoid # using mutated values. # Stop triggering this method. self.__class__ = types.ModuleType # Get the original name to make sure no object substitution occurred # in sys.modules. original_name = self.__spec__.name # Figure out exactly what attributes were mutated between the creation # of the module and now. attrs_then = self.__spec__.loader_state['__dict__'] attrs_now = self.__dict__ attrs_updated = {} for key, value in attrs_now.items(): # Code that set the attribute may have kept a reference to the # assigned object, making identity more important than equality. if key not in attrs_then: attrs_updated[key] = value elif id(attrs_now[key]) != id(attrs_then[key]): attrs_updated[key] = value self.__spec__.loader.exec_module(self) # If exec_module() was used directly there is no guarantee the module # object was put into sys.modules. if original_name in sys.modules: if id(self) != id(sys.modules[original_name]): raise ValueError(f"module object for {original_name!r} " "substituted in sys.modules during a lazy " "load") # Update after loading since that's what would happen in an eager # loading situation. self.__dict__.update(attrs_updated) return getattr(self, attr)

8198943edd73a363c266633e1aa5b2a9e9c9f526

util.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/importlib/util.py

Python

https://github.com/XX-net/XX-Net.git

_reset_build_compile_trackers

def _reset_build_compile_trackers(model): # Reset build state model.built = False model.inputs = None model.outputs = None # Reset compile state model._is_compiled = False # pylint:disable=protected-access if not tf.compat.v1.executing_eagerly_outside_functions(): model._v1_compile_was_called = False model.optimizer = None @keras_export( "keras.__internal__.models.in_place_subclassed_model_state_restoration", v1=[], )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

@keras_export( "keras.__internal__.models.in_place_subclassed_model_state_restoration", v1=[], )

cloning.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/models/cloning.py

Python

https://github.com/keras-team/keras.git

compress

def compress(self): modules_to_compress = self.get_modules_to_compress() for layer, config in modules_to_compress: module = layer.module if "weight" in config.get("quant_types", []): scale, zero_point = self.calculate_qparams(layer.name, 'weight') module.register_buffer('weight_scale', scale.to(self.device)) module.register_buffer('weight_zero_point', zero_point.to(self.device)) weight = module.weight quantized_weight = self._quantize(weight, module.weight_scale, module.weight_zero_point, module.weight_qmin, module.weight_qmax) delattr(module, 'weight') module.register_buffer('weight', quantized_weight) if "input" in config.get("quant_types", []): scale, zero_point = self.calculate_qparams(layer.name, 'input') module.register_buffer('input_scale', scale.to(self.device)) module.register_buffer('input_zero_point', zero_point.to(self.device)) if "output" in config.get("quant_types", []): scale, zero_point = self.calculate_qparams(layer.name, 'output') module.register_buffer('output_scale', scale.to(self.device)) module.register_buffer('output_zero_point', zero_point.to(self.device)) self.compressed = True super().compress()

d68c786ff81bad19c04619d6a999ff34aaa724e7

observer_quantizer.py

[Compression] remove pruning v1 & refactor directory (#5228)

nni

nni/compression/pytorch/quantization/observer_quantizer.py

Python

https://github.com/microsoft/nni.git

change_logging

def change_logging(request): current_request.set(request) webhooks_queue.set([]) # Connect our receivers to the post_save and post_delete signals. post_save.connect(handle_changed_object, dispatch_uid='handle_changed_object') m2m_changed.connect(handle_changed_object, dispatch_uid='handle_changed_object') pre_delete.connect(handle_deleted_object, dispatch_uid='handle_deleted_object') clear_webhooks.connect(clear_webhook_queue, dispatch_uid='clear_webhook_queue') yield # Disconnect change logging signals. This is necessary to avoid recording any errant # changes during test cleanup. post_save.disconnect(handle_changed_object, dispatch_uid='handle_changed_object') m2m_changed.disconnect(handle_changed_object, dispatch_uid='handle_changed_object') pre_delete.disconnect(handle_deleted_object, dispatch_uid='handle_deleted_object') clear_webhooks.disconnect(clear_webhook_queue, dispatch_uid='clear_webhook_queue') # Flush queued webhooks to RQ flush_webhooks(webhooks_queue.get()) # Clear context vars current_request.set(None) webhooks_queue.set([])

cd8943144bec52ff608ddad3db5d0155832a4a23

context_managers.py

Use context vars instead of thread-local storage for change logging

netbox

netbox/extras/context_managers.py

Python

https://github.com/netbox-community/netbox.git

upgrade

def upgrade(): with op.batch_alter_table("task_instance", schema=None) as batch_op: batch_op.alter_column("pool_slots", existing_type=sa.Integer, nullable=False, server_default='1')

66c342d033bd3cb959b4dc4e7e4b8aad597aab63

8646922c8a04_change_default_pool_slots_to_1.py

Support generating SQL script for upgrades (#20962) This PR attempts to add support for generating sql scripts for upgrade. Example command: `airflow db upgrade --revision-range e8d98d8ss99:78daisdu38d` `airflow db upgrade --range 2.0.0:2.2.3`

airflow

airflow/migrations/versions/8646922c8a04_change_default_pool_slots_to_1.py

Python

https://github.com/apache/airflow.git

gca

def gca(self, **kwargs): if kwargs: _api.warn_deprecated( "3.4", message="Calling gca() with keyword arguments was deprecated " "in Matplotlib %(since)s. Starting %(removal)s, gca() will " "take no keyword arguments. The gca() function should only be " "used to get the current axes, or if no axes exist, create " "new axes with default keyword arguments. To create a new " "axes with non-default arguments, use plt.axes() or " "plt.subplot().") ax = self._axstack.current() return ax if ax is not None else self.add_subplot(**kwargs)

8669c4636ce3b6ac6f4905c365ab41685186da56

figure.py

Rewrite AxesStack independently of cbook.Stack. AxesStack is fairly independent from cbook.Stack: cbook.Stack handles the forward/back/home buttons of the navbar, and therefore additionally maintains a movable "cursor" in the stack; AxesStack, on the other hand, needs to keep track both of "original" order and of "gca" order. Rewriting it from scratch, and using "original" order as main storage order (the "gca" stack being tracked using indices) shortens the implementation and simplifies it (as there's no more need to figure out what the super()calls do).

matplotlib

lib/matplotlib/figure.py

Python

https://github.com/matplotlib/matplotlib.git

run_report

def run_report(job_result, *args, **kwargs): module_name, report_name = job_result.name.split('.', 1) report = get_report(module_name, report_name) try: report.run(job_result) except Exception as e: print(e) job_result.set_status(JobResultStatusChoices.STATUS_ERRORED) job_result.save() logging.error(f"Error during execution of report {job_result.name}")

f13a00b2dd33bffc3048c861b494096df457f212

reports.py

Save old JobResults

netbox

netbox/extras/reports.py

Python

https://github.com/netbox-community/netbox.git

location

def location(self) -> str: location = "" if self.storage: location = ( self.storage.basepath + "/" if not self.storage.basepath.endswith("/") else "" ) if self.path: location += self.path return location

0a59ec9279d929fe6a7199ff7ff7c0b58cffa100

deployments.py

Add location as a computed property of deployments

prefect

src/prefect/deployments.py

Python

https://github.com/PrefectHQ/prefect.git

test_dispatch_key_raises_when_public_and_private_handlers

async def test_dispatch_key_raises_when_public_and_private_handlers(): widget = DuplicateHandlersWidget() with pytest.raises(DuplicateKeyHandlers): await widget.dispatch_key(Key(widget, key="x", char="x")) assert widget.called_by is None

17bc375e080c30d8754dfeccf44f9a607e041e1b

test_message_pump.py

Support for key aliases, key handling tests

textual

tests/test_message_pump.py

Python

https://github.com/Textualize/textual.git

test_unschedule_view_post

def test_unschedule_view_post(self): # Post to the unschedule page response = self.client.post( reverse( "wagtailadmin_pages:revisions_unschedule", args=(self.christmas_event.id, self.this_christmas_revision.id), ) ) # Should be redirected to page history self.assertRedirects( response, reverse("wagtailadmin_pages:history", args=(self.christmas_event.id,)), ) # Check that the page has no approved_schedule self.assertFalse( EventPage.objects.get(id=self.christmas_event.id).approved_schedule ) # Check that the approved_go_live_at has been cleared from the revision self.assertIsNone( self.christmas_event.revisions.get( id=self.this_christmas_revision.id ).approved_go_live_at )

d10f15e55806c6944827d801cd9c2d53f5da4186

test_revisions.py

Reformat with black

wagtail

wagtail/admin/tests/pages/test_revisions.py

Python

https://github.com/wagtail/wagtail.git

_wrap_call_and_conditional_losses

def _wrap_call_and_conditional_losses(layer): # Create function that generates both outputs and losses layer_call = _get_layer_call_method(layer)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

save_impl.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/saving/saved_model/save_impl.py

Python

https://github.com/keras-team/keras.git

_get_no_autofield_sequence_name

def _get_no_autofield_sequence_name(self, table): name_length = self.max_name_length() - 3 return "%s_SQ" % truncate_name(strip_quotes(table), name_length).upper()

9c19aff7c7561e3a82978a272ecdaad40dda5c00

operations.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/oracle/operations.py

Python

https://github.com/django/django.git

_unify_values

def _unify_values(self, section, vars): sectiondict = {} try: sectiondict = self._sections[section] except KeyError: if section != self.default_section: raise NoSectionError(section) from None # Update with the entry specific variables vardict = {} if vars: for key, value in vars.items(): if value is not None: value = str(value) vardict[self.optionxform(key)] = value return _ChainMap(vardict, sectiondict, self._defaults)

8198943edd73a363c266633e1aa5b2a9e9c9f526

configparser.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/configparser.py

Python

https://github.com/XX-net/XX-Net.git

dag_state

def dag_state(args, session=NEW_SESSION): dag = DagModel.get_dagmodel(args.dag_id, session=session) if not dag: raise SystemExit(f"DAG: {args.dag_id} does not exist in 'dag' table") dr = session.query(DagRun).filter_by(dag_id=args.dag_id, execution_date=args.execution_date).one_or_none() out = dr.state if dr else None conf_out = '' if out and dr.conf: conf_out = ', ' + json.dumps(dr.conf) print(str(out) + conf_out) @cli_utils.action_cli

b1ad017cee66f5e042144cc7baa2d44b23b47c4f

@cli_utils.action_cli

dag_command.py

pydocstyle D202 added (#24221)

airflow

airflow/cli/commands/dag_command.py

Python

https://github.com/apache/airflow.git

_search

def _search(self, check_return_type=True) -> Union[SourceReadList, DestinationReadList, ConnectionReadList]: return self._search_fn(self.api_instance, self.search_payload, _check_return_type=check_return_type)

56bf982cb96f831fe04f5e44a92ee4a669b9e16a

resources.py

🐙 octavia-cli: `apply` connections (#10881)

airbyte

octavia-cli/octavia_cli/apply/resources.py

Python

https://github.com/airbytehq/airbyte.git

_resize

def _resize(self, image, shorter=800, longer=1333, size_divisor=32, resample=Image.BICUBIC): if not isinstance(image, Image.Image): image = self.to_pil_image(image) w, h = image.size min_size = shorter max_size = longer scale = min_size / min(w, h) if h < w: newh, neww = min_size, scale * w else: newh, neww = scale * h, min_size if max(newh, neww) > max_size: scale = max_size / max(newh, neww) newh = newh * scale neww = neww * scale newh, neww = int(newh + 0.5), int(neww + 0.5) newh, neww = newh // size_divisor * size_divisor, neww // size_divisor * size_divisor return self.resize(image, size=(neww, newh), resample=resample)

ac227093e41cecb07c7e0f2fc9a504850907bd06

feature_extraction_vilt.py

Add ViLT (#14895) * First commit * Add conversion script * Make conversion script work for base model * More improvements * Update conversion script, works for vqa * Add indexing argument to meshgrid * Make conversion script work for ViltForPreTraining * Add ViltForPreTraining to docs * Fix device issue * Add processor * Add MinMaxResize to feature extractor * Implement call method of ViltProcessor * Fix tests * Add integration test * Add loss calculation for VQA * Improve tests * Improve some more tests * Debug tests * Small improvements * Add support for attention_mask * Remove mask_it * Add pixel_mask * Add tests for ViltFeatureExtractor * Improve tests * Add ViltForNaturalLanguageVisualReasoning * Add ViltForNaturalLanguageVisualReasoning to conversion script * Minor fixes * Add support for image_embeds, update docstrings to markdown * Update docs to markdown * Improve conversion script * Rename ViltForPreTraining to ViltForMaskedLM * Improve conversion script * Convert docstrings to markdown * Fix code example of retrieval model * Properly convert masked language model * Add integration test for nlvr * Fix code quality * Apply suggestions from code review * Add copied from statements * Fix pretrained_config_archive_map * Fix docs * Add model to README * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> * Apply more suggestions from code review * Make code more readable * Add ViltForNaturalLanguageVisualReasoning to the tests * Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering * Replace pixel_values_2 by single tensor * Add hidden_states and attentions * Fix one more test * Fix all tests * Update year * Fix rebase issues * Fix another rebase issue * Remove ViltForPreTraining from auto mapping * Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval * Make it possible to use BertTokenizerFast in the processor * Use BertTokenizerFast by default * Rename ViltForNaturalLanguageVisualReasoning, define custom model output Co-authored-by: Sylvain Gugger <[email protected]>

transformers

src/transformers/models/vilt/feature_extraction_vilt.py

Python

https://github.com/huggingface/transformers.git

test_instance_url_mismatch

def test_instance_url_mismatch(self): self.plugin.set_option("instance_url", "https://hellboy.atlassian.net", self.project) group = self.create_group(message="Hello world", culprit="foo.bar") plugin_issue = GroupMeta.objects.create( key=f"{self.plugin.slug}:tid", group_id=group.id, value="SEN-1" ) with self.tasks(): self.installation.migrate_issues() assert not ExternalIssue.objects.filter( organization_id=self.organization.id, integration_id=self.integration.id, key=plugin_issue.value, ).exists() assert GroupMeta.objects.filter( key=f"{self.plugin.slug}:tid", group_id=group.id, value="SEN-1" ).exists()

f5e5a3b1ed97383e0699aff9eb0363e9eb5db479

test_integration.py

feat(Jira): Plugin issue migration endpoint (#37577) * feat(jira): Plugin issue migration endpoint

sentry

tests/sentry/integrations/jira/test_integration.py

Python

https://github.com/getsentry/sentry.git

create_experiment

def create_experiment(workspace, experiment_name): logger.debug("create: experiment_name {}".format(experiment_name)) exp = Experiment(workspace=workspace, name=experiment_name) return exp

f1b06e2f758b5b4a965f7bf428d006621d19c0b0

submit_azureml_pytest.py

changed folder structure for aml tests

recommenders

tests/ci/aml_tests_old/submit_azureml_pytest.py

Python

https://github.com/microsoft/recommenders.git

test_localtaskjob_essential_attr

def test_localtaskjob_essential_attr(self, dag_maker): with dag_maker('test_localtaskjob_essential_attr'): op1 = EmptyOperator(task_id='op1') dr = dag_maker.create_dagrun() ti = dr.get_task_instance(task_id=op1.task_id) job1 = LocalTaskJob(task_instance=ti, ignore_ti_state=True, executor=SequentialExecutor()) essential_attr = ["dag_id", "job_type", "start_date", "hostname"] check_result_1 = [hasattr(job1, attr) for attr in essential_attr] assert all(check_result_1) check_result_2 = [getattr(job1, attr) is not None for attr in essential_attr] assert all(check_result_2)

49e336ae0302b386a2f47269a6d13988382d975f

test_local_task_job.py

Replace usage of `DummyOperator` with `EmptyOperator` (#22974) * Replace usage of `DummyOperator` with `EmptyOperator`

airflow

tests/jobs/test_local_task_job.py

Python

https://github.com/apache/airflow.git

decode

def decode(s): return urllib.parse.parse_qsl(s, keep_blank_values=True, errors="surrogateescape")

b3587b52b25077f68116b9852b041d33e7fc6601

url.py

make it black!

mitmproxy

mitmproxy/net/http/url.py

Python

https://github.com/mitmproxy/mitmproxy.git

test_collapse_event

def test_collapse_event(self) -> None: client = self.get_client_descriptor() queue = client.event_queue queue.push({"type": "restart", "server_generation": 1, "timestamp": "1"}) # Verify the server_generation event is stored as a virtual event self.assertEqual( queue.virtual_events, {"restart": {"id": 0, "type": "restart", "server_generation": 1, "timestamp": "1"}}, ) # And we can reconstruct newest_pruned_id etc. self.verify_to_dict_end_to_end(client) queue.push({"type": "unknown", "timestamp": "1"}) self.assertEqual(list(queue.queue), [{"id": 1, "type": "unknown", "timestamp": "1"}]) self.assertEqual( queue.virtual_events, {"restart": {"id": 0, "type": "restart", "server_generation": 1, "timestamp": "1"}}, ) # And we can still reconstruct newest_pruned_id etc. correctly self.verify_to_dict_end_to_end(client) # Verify virtual events are converted to real events by .contents() self.assertEqual( queue.contents(), [ {"id": 0, "type": "restart", "server_generation": 1, "timestamp": "1"}, {"id": 1, "type": "unknown", "timestamp": "1"}, ], ) # And now verify to_dict after pruning queue.prune(0) self.verify_to_dict_end_to_end(client) queue.prune(1) self.verify_to_dict_end_to_end(client)

b0ce4f1bce8031881addecb1e86073483517f392

test_event_queue.py

docs: Fix many spelling mistakes. Signed-off-by: Anders Kaseorg <[email protected]>

zulip

zerver/tests/test_event_queue.py

Python

https://github.com/zulip/zulip.git

test_get_primary_key_column

def test_get_primary_key_column(self): testable_column_strings = ( ("id", "id"), ("[id]", "id"), ("`id`", "id"), ('"id"', "id"), ("[id col]", "id col"), ("`id col`", "id col"), ('"id col"', "id col"), ) with connection.cursor() as cursor: for column, expected_string in testable_column_strings: sql = "CREATE TABLE test_primary (%s int PRIMARY KEY NOT NULL)" % column with self.subTest(column=column): try: cursor.execute(sql) field = connection.introspection.get_primary_key_column( cursor, "test_primary" ) self.assertEqual(field, expected_string) finally: cursor.execute("DROP TABLE test_primary")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

test_introspection.py

Refs #33476 -- Reformatted code with Black.

django

tests/backends/sqlite/test_introspection.py

Python

https://github.com/django/django.git

print_help

def print_help(self): colored = self.ticker and self.selected_date help_text = f print(help_text)

5a5c7193db3cf15ee7bb881ba912b8289aa83a80

options_controller.py

Volatility surface (#1176) * Add a 3D volatility surface from yfinance data * Update _index.md * other tests

OpenBBTerminal

gamestonk_terminal/stocks/options/options_controller.py

Python

https://github.com/OpenBB-finance/OpenBBTerminal.git

list_installed_files

def list_installed_files(self): for result in self._get_records(): yield result

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

database.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/distlib/database.py

Python

https://github.com/jindongwang/transferlearning.git

test_dataset

def test_dataset(ray_start_4_cpus, use_local): model_creator = mlp_identity.model_creator optimizer_creator = mlp_identity.optimizer_creator dataset_creator = mlp_identity.dataset_creator DatasetOperator = TrainingOperator.from_creators( model_creator=model_creator, optimizer_creator=optimizer_creator, loss_creator=nn.MSELoss, ) trainer = TorchTrainer( training_operator_cls=DatasetOperator, use_local=use_local, num_workers=2, ) dataset = dataset_creator() for i in range(5): trainer.train(dataset=dataset, num_steps=100) x = mlp_identity.to_mat(0.5) prediction = float(trainer.get_model()(x)[0][0]) assert 0.4 <= prediction <= 0.6 trainer.shutdown() @pytest.mark.parametrize("use_local", [True, False])

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

@pytest.mark.parametrize("use_local", [True, False])

test_torch_2.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

python/ray/util/sgd/tests/test_torch_2.py

Python

https://github.com/ray-project/ray.git

_is_current

def _is_current(self, file_path, zip_path): timestamp, size = self._get_date_and_size(self.zipinfo[zip_path]) if not os.path.isfile(file_path): return False stat = os.stat(file_path) if stat.st_size != size or stat.st_mtime != timestamp: return False # check that the contents match zip_contents = self.loader.get_data(zip_path) with open(file_path, 'rb') as f: file_contents = f.read() return zip_contents == file_contents

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

__init__.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/pkg_resources/__init__.py

Python

https://github.com/jindongwang/transferlearning.git

load

def load(self): # Try to scan config file model_config_fpaths = list(self.model_fpath.parent.rglob("*.json")) if len(model_config_fpaths)>0 and model_config_fpaths[0].exists(): with model_config_fpaths[0].open("r", encoding="utf-8") as f: hparams.loadJson(json.load(f)) self._model = Tacotron(embed_dims=hparams.tts_embed_dims, num_chars=len(symbols), encoder_dims=hparams.tts_encoder_dims, decoder_dims=hparams.tts_decoder_dims, n_mels=hparams.num_mels, fft_bins=hparams.num_mels, postnet_dims=hparams.tts_postnet_dims, encoder_K=hparams.tts_encoder_K, lstm_dims=hparams.tts_lstm_dims, postnet_K=hparams.tts_postnet_K, num_highways=hparams.tts_num_highways, dropout=hparams.tts_dropout, stop_threshold=hparams.tts_stop_threshold, speaker_embedding_size=hparams.speaker_embedding_size).to(self.device) self._model.load(self.model_fpath, self.device) self._model.eval() if self.verbose: print("Loaded synthesizer \"%s\" trained to step %d" % (self.model_fpath.name, self._model.state_dict()["step"]))

0536874dec68e68969502ce1774168552727fa17

inference.py

Add config file for pretrained

MockingBird

synthesizer/inference.py

Python

https://github.com/babysor/MockingBird.git

paste

def paste(self, im, box=None): if box is not None: warnings.warn( "The box parameter is deprecated and will be removed in Pillow 10 " "(2023-07-01).", DeprecationWarning, ) # convert to blittable im.load() image = im.im if image.isblock() and im.mode == self.__mode: block = image else: block = image.new_block(self.__mode, im.size) image.convert2(block, image) # convert directly between buffers _pyimagingtkcall("PyImagingPhoto", self.__photo, block.id) # -------------------------------------------------------------------- # BitmapImage

a724be66bef4b692994e5defa22ba3f1b2a1f771

ImageTk.py

Deprecated PhotoImage.paste() box parameter

Pillow

src/PIL/ImageTk.py

Python

https://github.com/python-pillow/Pillow.git

test_sensor_arrival_time_custom_timestamp

async def test_sensor_arrival_time_custom_timestamp(hass): assert hass.states.get("sensor.google_travel_time").state == "27" @pytest.mark.usefixtures("mock_update")

beb30a1ff199596163c655e8ae745a0f1649b78a

@pytest.mark.usefixtures("mock_update")

test_sensor.py

Add google_travel_time sensor tests (#66568) Co-authored-by: Paulus Schoutsen <[email protected]>

core

tests/components/google_travel_time/test_sensor.py

Python

https://github.com/home-assistant/core.git

col

def col (loc, strg): s = strg return 1 if 0 < loc < len(s) and s[loc-1] == '\n' else loc - s.rfind("\n", 0, loc)

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

pyparsing.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/pyparsing.py

Python

https://github.com/jindongwang/transferlearning.git

ensure_future

def ensure_future(coro_or_future, *, loop=None): return _ensure_future(coro_or_future, loop=loop)

8198943edd73a363c266633e1aa5b2a9e9c9f526

tasks.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/tasks.py

Python

https://github.com/XX-net/XX-Net.git

_discover_secrets_backends

def _discover_secrets_backends(self) -> None: for provider_package, provider in self._provider_dict.items(): if provider.data.get("secrets-backends"): for secrets_backends_class_name in provider.data["secrets-backends"]: if _sanity_check(provider_package, secrets_backends_class_name, provider): self._secrets_backend_class_name_set.add(secrets_backends_class_name)

b5a786b38148295c492da8ab731d5e2f6f86ccf7

providers_manager.py

Suppress import errors for providers from sources (#22579) When 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.

airflow

airflow/providers_manager.py

Python

https://github.com/apache/airflow.git

test_sends_note_notification

def test_sends_note_notification(self): # leave a comment url = f"/api/0/issues/{self.group.id}/comments/" with self.tasks(): response = self.client.post(url, format="json", data={"text": "blah blah"}) assert response.status_code == 201, response.content msg = mail.outbox[0] # check the txt version assert "blah blah" in msg.body # check the html version assert "blah blah</p></div>" in msg.alternatives[0][0] attachment, text = get_attachment() # check the Slack version assert text == f"New comment by {self.name}" assert attachment["title"] == f"{self.group.title}" assert ( attachment["title_link"] == f"http://testserver/organizations/{self.organization.slug}/issues/{self.group.id}/?referrer=note_activity-slack" ) assert attachment["text"] == "blah blah" assert ( attachment["footer"] == f"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=note_activity-slack-user|Notification Settings>" )

1730c481f1a8a71446326fa1ff72e10663016385

test_notifications.py

fix(notifications): Use `metrics_key` (#34572)

sentry

tests/sentry/notifications/test_notifications.py

Python

https://github.com/getsentry/sentry.git

connect

def connect(self) -> HandlerStatusResponse: url = self.connection_args.get('url') try: ckan = rc(url) self.is_connected = True self.ckan = ckan except Exception as e: return HandlerStatusResponse(False, f'Failed to connect to CKAN: {e}') self.connection = ckan return HandlerStatusResponse(True)

75686f43be1d82794e50277acefda517eced0b6c

ckan_handler.py

Add CKAN Handler for MindsDB

mindsdb

mindsdb/integrations/handlers/ckan_handler/ckan_handler.py

Python

https://github.com/mindsdb/mindsdb.git

unbatch

def unbatch(batches_struct): flat_batches = tree.flatten(batches_struct) out = [] for batch_pos in range(len(flat_batches[0])): out.append( tree.unflatten_as( batches_struct, [flat_batches[i][batch_pos] for i in range(len(flat_batches))], ) ) return out

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

space_utils.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

rllib/utils/spaces/space_utils.py

Python

https://github.com/ray-project/ray.git

sample

def sample(self, n_samples=1): check_is_fitted(self) if n_samples < 1: raise ValueError( "Invalid value for 'n_samples': %d . The sampling requires at " "least one sample." % (self.n_components) ) _, n_features = self.means_.shape rng = check_random_state(self.random_state) n_samples_comp = rng.multinomial(n_samples, self.weights_) if self.covariance_type == "full": X = np.vstack( [ rng.multivariate_normal(mean, covariance, int(sample)) for (mean, covariance, sample) in zip( self.means_, self.covariances_, n_samples_comp ) ] ) elif self.covariance_type == "tied": X = np.vstack( [ rng.multivariate_normal(mean, self.covariances_, int(sample)) for (mean, sample) in zip(self.means_, n_samples_comp) ] ) else: X = np.vstack( [ mean + rng.standard_normal(size=(sample, n_features)) * np.sqrt(covariance) for (mean, covariance, sample) in zip( self.means_, self.covariances_, n_samples_comp ) ] ) y = np.concatenate( [np.full(sample, j, dtype=int) for j, sample in enumerate(n_samples_comp)] ) return (X, y)

254ea8c453cd2100ade07644648f1f00392611a6

_base.py

ENH Replaced RandomState with Generator compatible calls (#22271)

scikit-learn

sklearn/mixture/_base.py

Python

https://github.com/scikit-learn/scikit-learn.git

test_adapter_recovery

async def test_adapter_recovery(hass, one_adapter): called_start = 0 called_stop = 0 _callback = None mock_discovered = []

0e2ebfe5c45716250280186234123f170e3bd08c

test_scanner.py

Move bluetooth watchdog into the scanner base class (#83888)

core

tests/components/bluetooth/test_scanner.py

Python

https://github.com/home-assistant/core.git

test_ohe_infrequent_two_levels_user_cats_one_frequent

def test_ohe_infrequent_two_levels_user_cats_one_frequent(kwargs): X_train = np.array([["a"] * 5 + ["e"] * 30], dtype=object).T ohe = OneHotEncoder( categories=[["c", "d", "a", "b"]], sparse=False, handle_unknown="infrequent_if_exist", **kwargs, ).fit(X_train) X_test = [["a"], ["b"], ["c"], ["d"], ["e"]] expected = np.array([[1, 0], [0, 1], [0, 1], [0, 1], [0, 1]]) X_trans = ohe.transform(X_test) assert_allclose(expected, X_trans) # 'a' is dropped drops = ["first", "if_binary", ["a"]] X_test = [["a"], ["c"]] for drop in drops: ohe.set_params(drop=drop).fit(X_train) assert_allclose([[0], [1]], ohe.transform(X_test))

7f0006c8aad1a09621ad19c3db19c3ff0555a183

test_encoders.py

ENH Adds infrequent categories to OneHotEncoder (#16018) * ENH Completely adds infrequent categories * STY Linting * STY Linting * DOC Improves wording * DOC Lint * BUG Fixes * CLN Address comments * CLN Address comments * DOC Uses math to description float min_frequency * DOC Adds comment regarding drop * BUG Fixes method name * DOC Clearer docstring * TST Adds more tests * FIX Fixes mege * CLN More pythonic * CLN Address comments * STY Flake8 * CLN Address comments * DOC Fix * MRG * WIP * ENH Address comments * STY Fix * ENH Use functiion call instead of property * ENH Adds counts feature * CLN Rename variables * DOC More details * CLN Remove unneeded line * CLN Less lines is less complicated * CLN Less diffs * CLN Improves readiabilty * BUG Fix * CLN Address comments * TST Fix * CLN Address comments * CLN Address comments * CLN Move docstring to userguide * DOC Better wrapping * TST Adds test to handle_unknown='error' * ENH Spelling error in docstring * BUG Fixes counter with nan values * BUG Removes unneeded test * BUG Fixes issue * ENH Sync with main * DOC Correct settings * DOC Adds docstring * DOC Immprove user guide * DOC Move to 1.0 * DOC Update docs * TST Remove test * DOC Update docstring * STY Linting * DOC Address comments * ENH Neater code * DOC Update explaination for auto * Update sklearn/preprocessing/_encoders.py Co-authored-by: Roman Yurchak <[email protected]> * TST Uses docstring instead of comments * TST Remove call to fit * TST Spelling error * ENH Adds support for drop + infrequent categories * ENH Adds infrequent_if_exist option * DOC Address comments for user guide * DOC Address comments for whats_new * DOC Update docstring based on comments * CLN Update test with suggestions * ENH Adds computed property infrequent_categories_ * DOC Adds where the infrequent column is located * TST Adds more test for infrequent_categories_ * DOC Adds docstring for _compute_drop_idx * CLN Moves _convert_to_infrequent_idx into its own method * TST Increases test coverage * TST Adds failing test * CLN Careful consideration of dropped and inverse_transform * STY Linting * DOC Adds docstrinb about dropping infrequent * DOC Uses only * DOC Numpydoc * TST Includes test for get_feature_names_out * DOC Move whats new * DOC Address docstring comments * DOC Docstring changes * TST Better comments * TST Adds check for handle_unknown='ignore' for infrequent * CLN Make _infrequent_indices private * CLN Change min_frequency default to None * DOC Adds comments * ENH adds support for max_categories=1 * ENH Describe lexicon ordering for ties * DOC Better docstring * STY Fix * CLN Error when explicity dropping an infrequent category * STY Grammar Co-authored-by: Joel Nothman <[email protected]> Co-authored-by: Roman Yurchak <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

scikit-learn

sklearn/preprocessing/tests/test_encoders.py

Python

https://github.com/scikit-learn/scikit-learn.git

test_decrease_stock_multiple_lines_deallocate_stock_raises_error

def test_decrease_stock_multiple_lines_deallocate_stock_raises_error(order_with_lines): # given order_line_1 = order_with_lines.lines.first() order_line_2 = order_with_lines.lines.last() allocation_1 = order_line_1.allocations.first() allocation_2 = order_line_2.allocations.first() stock_quantity = 100 allocation_1_qty_allocated = 10 allocation_2_qty_allocated = 80 stock_1 = allocation_1.stock stock_2 = allocation_2.stock stock_1.quantity = stock_quantity stock_2.quantity = stock_quantity Stock.objects.bulk_update([stock_1, stock_2], ["quantity"]) allocation_1.quantity_allocated = allocation_1_qty_allocated allocation_1.order_line = order_line_1 warehouse_pk_1 = stock_1.warehouse.pk allocation_2.quantity_allocated = allocation_2_qty_allocated allocation_2.order_line = order_line_2 warehouse_pk_2 = stock_2.warehouse.pk Allocation.objects.bulk_update( [allocation_1, allocation_2], ["quantity_allocated", "order_line"] ) line_1_qty = 50 line_2_qty = 20 # when decrease_stock( [ OrderLineInfo( line=order_line_1, quantity=line_1_qty, variant=order_line_1.variant, warehouse_pk=warehouse_pk_1, ), OrderLineInfo( line=order_line_2, quantity=line_2_qty, variant=order_line_2.variant, warehouse_pk=warehouse_pk_2, ), ], manager=get_plugins_manager(), ) # then stock_1.refresh_from_db() assert stock_1.quantity == stock_quantity - line_1_qty stock_2.refresh_from_db() assert stock_2.quantity == stock_quantity - line_2_qty allocation_1.refresh_from_db() assert allocation_1.quantity_allocated == 0 allocation_2.refresh_from_db() assert allocation_2.quantity_allocated == allocation_2_qty_allocated - line_2_qty

c052f59016d82568a675e2c202ea1363f9e355ff

test_stock_management.py

Fix incorrect stock allocation (#8963) * Fix incorrect stock allocation * Drop unused restock_order_lines order utils

saleor

saleor/warehouse/tests/test_stock_management.py

Python

https://github.com/saleor/saleor.git

verify_local_collection

def verify_local_collection(local_collection, remote_collection, artifacts_manager): # type: (Candidate, Candidate | None, ConcreteArtifactsManager) -> CollectionVerifyResult result = CollectionVerifyResult(local_collection.fqcn) b_collection_path = to_bytes(local_collection.src, errors='surrogate_or_strict') display.display("Verifying '{coll!s}'.".format(coll=local_collection)) display.display( u"Installed collection found at '{path!s}'". format(path=to_text(local_collection.src)), ) modified_content = [] # type: list[ModifiedContent] verify_local_only = remote_collection is None # partial away the local FS detail so we can just ask generically during validation get_json_from_validation_source = functools.partial(_get_json_from_installed_dir, b_collection_path) get_hash_from_validation_source = functools.partial(_get_file_hash, b_collection_path) if not verify_local_only: # Compare installed version versus requirement version if local_collection.ver != remote_collection.ver: err = ( "{local_fqcn!s} has the version '{local_ver!s}' but " "is being compared to '{remote_ver!s}'".format( local_fqcn=local_collection.fqcn, local_ver=local_collection.ver, remote_ver=remote_collection.ver, ) ) display.display(err) result.success = False return result manifest_file = os.path.join(to_text(b_collection_path, errors='surrogate_or_strict'), MANIFEST_FILENAME) signatures = list(local_collection.signatures) if verify_local_only and local_collection.source_info is not None: signatures = [info["signature"] for info in local_collection.source_info["signatures"]] + signatures elif not verify_local_only and remote_collection.signatures: signatures = list(remote_collection.signatures) + signatures keyring_configured = artifacts_manager.keyring is not None if not keyring_configured and signatures: display.warning( "The GnuPG keyring used for collection signature " "verification was not configured but signatures were " "provided by the Galaxy server. " "Configure a keyring for ansible-galaxy to verify " "the origin of the collection. " "Skipping signature verification." ) elif keyring_configured: if not verify_file_signatures( local_collection.fqcn, manifest_file, signatures, artifacts_manager.keyring, artifacts_manager.required_successful_signature_count, artifacts_manager.ignore_signature_errors, ): result.success = False return result display.vvvv(f"GnuPG signature verification succeeded, verifying contents of {local_collection}") if verify_local_only: # since we're not downloading this, just seed it with the value from disk manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME) elif keyring_configured and remote_collection.signatures: manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME) else: # fetch remote b_temp_tar_path = ( # NOTE: AnsibleError is raised on URLError artifacts_manager.get_artifact_path if remote_collection.is_concrete_artifact else artifacts_manager.get_galaxy_artifact_path )(remote_collection) display.vvv( u"Remote collection cached as '{path!s}'".format(path=to_text(b_temp_tar_path)) ) # partial away the tarball details so we can just ask generically during validation get_json_from_validation_source = functools.partial(_get_json_from_tar_file, b_temp_tar_path) get_hash_from_validation_source = functools.partial(_get_tar_file_hash, b_temp_tar_path) # Verify the downloaded manifest hash matches the installed copy before verifying the file manifest manifest_hash = get_hash_from_validation_source(MANIFEST_FILENAME) _verify_file_hash(b_collection_path, MANIFEST_FILENAME, manifest_hash, modified_content) display.display('MANIFEST.json hash: {manifest_hash}'.format(manifest_hash=manifest_hash)) manifest = get_json_from_validation_source(MANIFEST_FILENAME) # Use the manifest to verify the file manifest checksum file_manifest_data = manifest['file_manifest_file'] file_manifest_filename = file_manifest_data['name'] expected_hash = file_manifest_data['chksum_%s' % file_manifest_data['chksum_type']] # Verify the file manifest before using it to verify individual files _verify_file_hash(b_collection_path, file_manifest_filename, expected_hash, modified_content) file_manifest = get_json_from_validation_source(file_manifest_filename) collection_dirs = set() collection_files = { os.path.join(b_collection_path, b'MANIFEST.json'), os.path.join(b_collection_path, b'FILES.json'), } # Use the file manifest to verify individual file checksums for manifest_data in file_manifest['files']: name = manifest_data['name'] if manifest_data['ftype'] == 'file': collection_files.add( os.path.join(b_collection_path, to_bytes(name, errors='surrogate_or_strict')) ) expected_hash = manifest_data['chksum_%s' % manifest_data['chksum_type']] _verify_file_hash(b_collection_path, name, expected_hash, modified_content) if manifest_data['ftype'] == 'dir': collection_dirs.add( os.path.join(b_collection_path, to_bytes(name, errors='surrogate_or_strict')) ) # Find any paths not in the FILES.json for root, dirs, files in os.walk(b_collection_path): for name in files: full_path = os.path.join(root, name) path = to_text(full_path[len(b_collection_path) + 1::], errors='surrogate_or_strict') if full_path not in collection_files: modified_content.append( ModifiedContent(filename=path, expected='the file does not exist', installed='the file exists') ) for name in dirs: full_path = os.path.join(root, name) path = to_text(full_path[len(b_collection_path) + 1::], errors='surrogate_or_strict') if full_path not in collection_dirs: modified_content.append( ModifiedContent(filename=path, expected='the directory does not exist', installed='the directory exists') ) if modified_content: result.success = False display.display( 'Collection {fqcn!s} contains modified content ' 'in the following files:'. format(fqcn=to_text(local_collection.fqcn)), ) for content_change in modified_content: display.display(' %s' % content_change.filename) display.v(" Expected: %s\n Found: %s" % (content_change.expected, content_change.installed)) else: what = "are internally consistent with its manifest" if verify_local_only else "match the remote collection" display.display( "Successfully verified that checksums for '{coll!s}' {what!s}.". format(coll=local_collection, what=what), ) return result

b439e41a915ccec0ccbabecc966919ea406db74e

__init__.py

expand ansible-doc coverage (#74963) * Expand ansible-doc to tests/filters and fix existing issues enable filter/test docs if in single file or companion yaml add docs for several filters/tests plugins allow .yml companion for docs for other plugins, must be colocated verify plugins are valid (not modules, cannot) fix 'per collection' filtering limit old style deprecation (_ prefix) to builtin/legacy start move to pathlib for saner path handling moved some funcitons, kept backwards compat shims with deprecation notice Co-authored-by: Abhijeet Kasurde <[email protected]> Co-authored-by: Felix Fontein <[email protected]> Co-authored-by: Sandra McCann <[email protected]>

ansible

lib/ansible/galaxy/collection/__init__.py

Python

https://github.com/ansible/ansible.git

traverse_by

def traverse_by(self, fixers, traversal): if not fixers: return for node in traversal: for fixer in fixers[node.type]: results = fixer.match(node) if results: new = fixer.transform(node, results) if new is not None: node.replace(new) node = new

8198943edd73a363c266633e1aa5b2a9e9c9f526

refactor.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/lib2to3/refactor.py

Python

https://github.com/XX-net/XX-Net.git

test_appo_compilation_use_kl_loss

def test_appo_compilation_use_kl_loss(self): config = ppo.appo.DEFAULT_CONFIG.copy() config["num_workers"] = 1 config["use_kl_loss"] = True num_iterations = 2 for _ in framework_iterator(config, with_eager_tracing=True): trainer = ppo.APPOTrainer(config=config, env="CartPole-v0") for i in range(num_iterations): results = trainer.train() check_train_results(results) print(results) check_compute_single_action(trainer) trainer.stop()

8ebc50f844f42e283f125792d630ea6d0a2a7000

test_appo.py

[RLlib] Issue 21334: Fix APPO when kl_loss is enabled. (#21855)

ray

rllib/agents/ppo/tests/test_appo.py

Python

https://github.com/ray-project/ray.git

intercept_unary_unary

async def intercept_unary_unary(self, continuation, client_call_details, request): if context.get_value(_SUPPRESS_INSTRUMENTATION_KEY): return await continuation(client_call_details, request) method = client_call_details.method.decode("utf-8") with self._start_span( method, end_on_exit=False, record_exception=False, set_status_on_exception=False, ) as span: new_details = self.propagate_trace_in_details(client_call_details) continuation_with_args = functools.partial( continuation, new_details, request ) return await self._wrap_unary_response(continuation_with_args, span)

107631e955b21db8a4ddb3bee02130de3650d032

_aio_client.py

feat(instrumentation): add OpenTelemetry tracing and metrics with basic configurations (#5175)

jina

jina/serve/instrumentation/_aio_client.py

Python

https://github.com/jina-ai/jina.git

from_current_timezone

def from_current_timezone(value): if settings.USE_TZ and value is not None and timezone.is_naive(value): current_timezone = timezone.get_current_timezone() try: if not timezone._is_pytz_zone( current_timezone ) and timezone._datetime_ambiguous_or_imaginary(value, current_timezone): raise ValueError("Ambiguous or non-existent time.") return timezone.make_aware(value, current_timezone) except Exception as exc: raise ValidationError( _( "%(datetime)s couldn’t be interpreted " "in time zone %(current_timezone)s; it " "may be ambiguous or it may not exist." ), code="ambiguous_timezone", params={"datetime": value, "current_timezone": current_timezone}, ) from exc return value

9c19aff7c7561e3a82978a272ecdaad40dda5c00

utils.py

Refs #33476 -- Reformatted code with Black.

django

django/forms/utils.py

Python

https://github.com/django/django.git

active

def active(self) -> Optional[Scope]: ctx = current_context() return ctx.scope

6ad012ef89c966cbb3616c1be63d964db48d49ca

scopecontextmanager.py

More type hints for `synapse.logging` (#13103) Completes type hints for synapse.logging.scopecontextmanager and (partially) for synapse.logging.opentracing.

synapse

synapse/logging/scopecontextmanager.py

Python

https://github.com/matrix-org/synapse.git

isocalendar

def isocalendar(self): return self._get_values().isocalendar().set_index(self._parent.index)

5531195f6f0d87817a704b288008809a3c98a304

accessors.py

fix-ci-isocalendar (#46690)

pandas

pandas/core/indexes/accessors.py

Python

https://github.com/pandas-dev/pandas.git

update

def update(self, user=None, next_task=None): if self.status != self.STATUS_IN_PROGRESS: # Updating a completed or cancelled workflow should have no effect return try: current_status = self.current_task_state.status except AttributeError: current_status = None if current_status == TaskState.STATUS_REJECTED: self.status = self.STATUS_NEEDS_CHANGES self.save() workflow_rejected.send(sender=self.__class__, instance=self, user=user) else: if not next_task: next_task = self.get_next_task() if next_task: if ( (not self.current_task_state) or self.current_task_state.status != self.current_task_state.STATUS_IN_PROGRESS ): # if not on a task, or the next task to move to is not the current task (ie current task's status is # not STATUS_IN_PROGRESS), move to the next task self.current_task_state = next_task.specific.start(self, user=user) self.save() # if task has auto-approved, update the workflow again if ( self.current_task_state.status != self.current_task_state.STATUS_IN_PROGRESS ): self.update(user=user) # otherwise, continue on the current task else: # if there is no uncompleted task, finish the workflow. self.finish(user=user)

d10f15e55806c6944827d801cd9c2d53f5da4186

__init__.py

Reformat with black

wagtail

wagtail/core/models/__init__.py

Python

https://github.com/wagtail/wagtail.git

new_name

def new_name(self, template="xxx_todo_changeme"): name = template while name in self.used_names: name = template + str(next(self.numbers)) self.used_names.add(name) return name

8198943edd73a363c266633e1aa5b2a9e9c9f526

fixer_base.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/lib2to3/fixer_base.py

Python

https://github.com/XX-net/XX-Net.git

getxmp

def getxmp(self): for segment, content in self.applist: if segment == "APP1": marker, xmp_tags = content.rsplit(b"\x00", 1) if marker == b"http://ns.adobe.com/xap/1.0/": return self._getxmp(xmp_tags) return {}

601c9d8515dba996af3f0b96d1a671619de37f10

JpegImagePlugin.py

Fix return in docs

Pillow

src/PIL/JpegImagePlugin.py

Python

https://github.com/python-pillow/Pillow.git

alias

def alias(self, *args, **kwargs): self._not_support_combined_queries("alias") return self._annotate(args, kwargs, select=False)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

query.py

Refs #33476 -- Reformatted code with Black.

django

django/db/models/query.py

Python

https://github.com/django/django.git

agg

def agg(self, agg): assert isinstance(agg, str) agg_exprs = OrderedDict() for col in self.columns: agg_exprs[col] = AggregateExpr(agg, self.ref(col)) return self.__constructor__( columns=self.columns, dtypes=self._dtypes_for_exprs(agg_exprs), op=GroupbyAggNode(self, [], agg_exprs, {"sort": False}), index_cols=None, force_execution_mode=self._force_execution_mode, )

e5b1888cd932909e49194d58035da34b210b91c4

dataframe.py

FEAT-#4946: Replace OmniSci with HDK (#4947) Co-authored-by: Iaroslav Igoshev <[email protected]> Signed-off-by: Andrey Pavlenko <[email protected]>

modin

modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py

Python

https://github.com/modin-project/modin.git

get_feature_names_out

def get_feature_names_out(self, input_features=None): powers = self.powers_ input_features = _check_feature_names_in(self, input_features) feature_names = [] for row in powers: inds = np.where(row)[0] if len(inds): name = " ".join( "%s^%d" % (input_features[ind], exp) if exp != 1 else input_features[ind] for ind, exp in zip(inds, row[inds]) ) else: name = "1" feature_names.append(name) return np.asarray(feature_names, dtype=object)

279388d9ed2ea83194dd45a2d78161be30b43aa7

_polynomial.py

DOC Improve get_feature_names_out docstrings (#22718) Co-authored-by: Thomas J. Fan <[email protected]>

scikit-learn

sklearn/preprocessing/_polynomial.py

Python

https://github.com/scikit-learn/scikit-learn.git

revert_challenge_config

def revert_challenge_config(self) -> None: self.revert_temporary_config() self.new_vhost = None self.parser.load()

16aad35d31a887dab157f9d4f5e0fe9218d06064

configurator.py

Fully type certbot-nginx module (#9124) * Work in progress * Fix type * Work in progress * Work in progress * Work in progress * Work in progress * Work in progress * Oups. * Fix typing in UnspacedList * Fix logic * Finish typing * List certbot-nginx as fully typed in tox * Fix lint * Fix checks * Organize imports * Fix typing for Python 3.6 * Fix checks * Fix lint * Update certbot-nginx/certbot_nginx/_internal/configurator.py Co-authored-by: alexzorin <[email protected]> * Update certbot-nginx/certbot_nginx/_internal/configurator.py Co-authored-by: alexzorin <[email protected]> * Fix signature of deploy_cert regarding the installer interface * Update certbot-nginx/certbot_nginx/_internal/obj.py Co-authored-by: alexzorin <[email protected]> * Fix types * Update certbot-nginx/certbot_nginx/_internal/parser.py Co-authored-by: alexzorin <[email protected]> * Precise type * Precise _coerce possible inputs/outputs * Fix type * Update certbot-nginx/certbot_nginx/_internal/http_01.py Co-authored-by: ohemorange <[email protected]> * Fix type * Remove an undesirable implementation. * Fix type Co-authored-by: alexzorin <[email protected]> Co-authored-by: ohemorange <[email protected]>

certbot

certbot-nginx/certbot_nginx/_internal/configurator.py

Python

https://github.com/certbot/certbot.git

execute

def execute(): frappe.reload_doc("Accounts", "doctype", "Salary Component Account") if frappe.db.has_column("Salary Component Account", "default_account"): rename_field("Salary Component Account", "default_account", "account") doctype_list = [ {"module": "HR", "doctype": "Employee Advance"}, {"module": "HR", "doctype": "Leave Encashment"}, {"module": "Payroll", "doctype": "Additional Salary"}, {"module": "Payroll", "doctype": "Employee Benefit Application"}, {"module": "Payroll", "doctype": "Employee Benefit Claim"}, {"module": "Payroll", "doctype": "Employee Incentive"}, {"module": "Payroll", "doctype": "Employee Tax Exemption Declaration"}, {"module": "Payroll", "doctype": "Employee Tax Exemption Proof Submission"}, {"module": "Payroll", "doctype": "Income Tax Slab"}, {"module": "Payroll", "doctype": "Payroll Entry"}, {"module": "Payroll", "doctype": "Retention Bonus"}, {"module": "Payroll", "doctype": "Salary Structure"}, {"module": "Payroll", "doctype": "Salary Structure Assignment"}, {"module": "Payroll", "doctype": "Salary Slip"}, ] for item in doctype_list: frappe.reload_doc(item["module"], "doctype", item["doctype"]) # update company in employee advance based on employee company for dt in [ "Employee Incentive", "Leave Encashment", "Employee Benefit Application", "Employee Benefit Claim", ]: frappe.db.sql( .format( doctype=dt ) ) # update exchange rate for employee advance frappe.db.sql("update `tabEmployee Advance` set exchange_rate=1") # get all companies and it's currency all_companies = frappe.db.get_all( "Company", fields=["name", "default_currency", "default_payroll_payable_account"] ) for d in all_companies: company = d.name company_currency = d.default_currency default_payroll_payable_account = d.default_payroll_payable_account if not default_payroll_payable_account: default_payroll_payable_account = frappe.db.get_value( "Account", { "account_name": _("Payroll Payable"), "company": company, "account_currency": company_currency, "is_group": 0, }, ) # update currency in following doctypes based on company currency doctypes_for_currency = [ "Employee Advance", "Leave Encashment", "Employee Benefit Application", "Employee Benefit Claim", "Employee Incentive", "Additional Salary", "Employee Tax Exemption Declaration", "Employee Tax Exemption Proof Submission", "Income Tax Slab", "Retention Bonus", "Salary Structure", ] for dt in doctypes_for_currency: frappe.db.sql( .format(doctype=dt), (company_currency, company), ) # update fields in payroll entry frappe.db.sql( , (company_currency, default_payroll_payable_account, company), ) # update fields in Salary Structure Assignment frappe.db.sql( , (company_currency, default_payroll_payable_account, company), ) # update fields in Salary Slip frappe.db.sql( , (company_currency, company), )

494bd9ef78313436f0424b918f200dab8fc7c20b

updates_for_multi_currency_payroll.py

style: format code with black

erpnext

erpnext/patches/v13_0/updates_for_multi_currency_payroll.py

Python

https://github.com/frappe/erpnext.git

get_libdir

def get_libdir(self): # Module unavailable if not self.available: raise ValueError(f"Module {self.name} {self.version} is unavailable!") # Module has no associated shared libraries if not self.sharedlibs: return None for lib in self.sharedlibs: path = findSystemLibrary(lib) if path: return os.path.normpath(os.path.dirname(path)) raise ValueError(f"Could not resolve any shared library of {self.name} {self.version}: {self.sharedlibs}!")

684bfac8adcf254fec5777f212c13eb62181f900

gi.py

hooks: refactor GObject introspection (gi) hooks The modules imported from gi.repository are marked as runtime modules by their corresponding pre-safe-import-module hooks. Therefore, their standard hooks are always loaded and executed, regardless of whether the modue is actually importable or not. In PyInstaller v5, this behavior triggers errors in hooks for GI modules that are not importable, because the new `isolated` framework propagates the errors instead of swallowing them. While these errors could be caught and demoted to warnings to match the old behavior, it would be better hooks checked whether module is importable before doing any processing at all. To that end, we introduce new class, `GiModuleInfo` that, as part of its initialization, allows us to: - perform availability check - obtain data previously returned by `get_gi_typelibs` - obtain data previously returned by `get_gi_libdir` using a single isolated import attempt (instead of one being performed in each of those steps). In addition, if passed `hook_api` as an optional argument, the `GiModuleInfo` can use hook configuration API to override the GI module version to be collected (which allows the standard use pattern to be removed from the hook itself). The old `get_gi_typelibs` and `get_gi_libdir` functions now internally use `GiModuleInfo` to provide backward compatible behavior to (potential) exetnal user. All `gi` hooks are ported to the `GiModuleInfo` and now become no-op if the module is not available. In addition, hooks are cleaned up/refactored so that all processing is performed either in the loading stage ("simple" hooks that do not require access to hook configuration API) or in the `hook()` function (hooks that require access to hook configuration API), but not in the mixture of the two.

pyinstaller

PyInstaller/utils/hooks/gi.py

Python

https://github.com/pyinstaller/pyinstaller.git

ratio

def ratio(self): matches = sum(triple[-1] for triple in self.get_matching_blocks()) return _calculate_ratio(matches, len(self.a) + len(self.b))

8198943edd73a363c266633e1aa5b2a9e9c9f526

difflib.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/difflib.py

Python

https://github.com/XX-net/XX-Net.git

_linear_eq_to_dict_inner

def _linear_eq_to_dict_inner(eqs, syms): syms = set(syms) eqsdict, ind = [], [] for eq in eqs: c, eqdict = _lin_eq2dict(eq, syms) eqsdict.append(eqdict) ind.append(c) return eqsdict, ind

041eeb41b6a083dd106a0e6316d6f07e2248cd61

linsolve.py

linear_coeffs has nonstrict option

sympy

sympy/polys/matrices/linsolve.py

Python

https://github.com/sympy/sympy.git

construct_actor_groups

def construct_actor_groups(actors): actor_groups = _group_actors_by_python_class(actors) stats_by_group = { name: _get_actor_group_stats(group) for name, group in actor_groups.items() } summarized_actor_groups = {} for name, group in actor_groups.items(): summarized_actor_groups[name] = { "entries": group, "summary": stats_by_group[name], } return summarized_actor_groups

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

actor_utils.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

dashboard/modules/actor/actor_utils.py

Python

https://github.com/ray-project/ray.git

test_change_view_history_link

def test_change_view_history_link(self): url = reverse( "admin:%s_modelwithstringprimarykey_change" % ModelWithStringPrimaryKey._meta.app_label, args=(quote(self.pk),), ) response = self.client.get(url) self.assertEqual(response.status_code, 200) expected_link = reverse( "admin:%s_modelwithstringprimarykey_history" % ModelWithStringPrimaryKey._meta.app_label, args=(quote(self.pk),), ) self.assertContains( response, '<a href="%s" class="historylink"' % escape(expected_link) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

https://github.com/django/django.git

generate_dimino

def generate_dimino(self, af=False): idn = list(range(self.degree)) order = 0 element_list = [idn] set_element_list = {tuple(idn)} if af: yield idn else: yield _af_new(idn) gens = [p._array_form for p in self.generators] for i in range(len(gens)): # D elements of the subgroup G_i generated by gens[:i] D = element_list[:] N = [idn] while N: A = N N = [] for a in A: for g in gens[:i + 1]: ag = _af_rmul(a, g) if tuple(ag) not in set_element_list: # produce G_i*g for d in D: order += 1 ap = _af_rmul(d, ag) if af: yield ap else: p = _af_new(ap) yield p element_list.append(ap) set_element_list.add(tuple(ap)) N.append(ap) self._order = len(element_list)

498015021131af4dbb07eb110e5badaba8250c7b

perm_groups.py

Updated import locations

sympy

sympy/combinatorics/perm_groups.py

Python

https://github.com/sympy/sympy.git

size

def size(self) -> DataFrame | Series: result = self.grouper.size() if self.axis == 1: return DataFrame( data=np.tile(result.values, (self.obj.shape[0], 1)), columns=result.index, index=self.obj.index, ) # GH28330 preserve subclassed Series/DataFrames through calls if issubclass(self.obj._constructor, Series): result = self._obj_1d_constructor(result, name=self.obj.name) else: result = self._obj_1d_constructor(result) if not self.as_index: # Item "None" of "Optional[Series]" has no attribute "reset_index" result = result.rename("size").reset_index() # type: ignore[union-attr] return self._reindex_output(result, fill_value=0)

15a06d3d9e7656afff239da7a295a7b684456680

groupby.py

BUG: groupby.size and groupby.transform('size') incorrect for axis=1 (#45987)

pandas

pandas/core/groupby/groupby.py

Python

https://github.com/pandas-dev/pandas.git

_iter_requires_txt_entries

def _iter_requires_txt_entries(self) -> Iterator[RequiresEntry]: content = self._dist.read_text("requires.txt") if content is None: return extra = marker = "" # Section-less entries don't have markers. for line in content.splitlines(): line = line.strip() if not line or line.startswith("#"): # Comment; ignored. continue if line.startswith("[") and line.endswith("]"): # A section header. extra, _, marker = line.strip("[]").partition(":") continue yield RequiresEntry(requirement=line, extra=extra, marker=marker)

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

_dists.py

Vendor in pip 22.1.2

pipenv

pipenv/patched/notpip/_internal/metadata/importlib/_dists.py

Python

https://github.com/pypa/pipenv.git

named_parameters

def named_parameters(self, *args, **kwargs): arch = kwargs.pop('arch', False) for name, p in super().named_parameters(*args, **kwargs): if any(name == par_name for par_name in self._arch_parameter_names): if arch: yield name, p else: if not arch: yield name, p

14d2966b9e91ae16dcc39de8f41017a75cec8ff9

differentiable.py

Valuechoice oneshot lightning (#4602)

nni

nni/retiarii/oneshot/pytorch/supermodule/differentiable.py

Python

https://github.com/microsoft/nni.git

get_stats

def get_stats(self) -> SystemStats: deleted = self.db.query(Message.deleted, func.count()).group_by(Message.deleted) nthreads = self.db.query(None, func.count(Message.id)).filter(Message.parent_id.is_(None)) query = deleted.union_all(nthreads) result = {k: v for k, v in query.all()} return SystemStats( all=result.get(True, 0) + result.get(False, 0), active=result.get(False, 0), deleted=result.get(True, 0), message_trees=result.get(None, 0), )

ef3a35ff9c9da7aab45e6f40103f32558f861e9b

prompt_repository.py

fixes

Open-Assistant

backend/oasst_backend/prompt_repository.py

Python

https://github.com/LAION-AI/Open-Assistant.git

make_sampling_table

def make_sampling_table(size, sampling_factor=1e-5): gamma = 0.577 rank = np.arange(size) rank[0] = 1 inv_fq = rank * (np.log(rank) + gamma) + 0.5 - 1. / (12. * rank) f = sampling_factor * inv_fq return np.minimum(1., f / np.sqrt(f)) @keras_export('keras.preprocessing.sequence.skipgrams')

f1aa8b7d2a0c89591c5c42eca5b6f013114a7bbd

@keras_export('keras.preprocessing.sequence.skipgrams')

sequence.py

Copy sequence utils from keras_preprocessing directly into core keras PiperOrigin-RevId: 424915569

keras

keras/preprocessing/sequence.py

Python

https://github.com/keras-team/keras.git

execute

def execute(): company = frappe.get_all("Company", filters={"country": "India"}) if not company: return frappe.reload_doc("Payroll", "doctype", "payroll_period") frappe.reload_doc("Payroll", "doctype", "employee_tax_exemption_declaration") frappe.reload_doc("Payroll", "doctype", "employee_tax_exemption_proof_submission") frappe.reload_doc("Payroll", "doctype", "employee_tax_exemption_declaration_category") frappe.reload_doc("Payroll", "doctype", "employee_tax_exemption_proof_submission_detail") frappe.reload_doc("accounts", "doctype", "tax_category") for doctype in ["Sales Invoice", "Delivery Note", "Purchase Invoice"]: frappe.db.sql( , doctype, ) make_custom_fields() frappe.db.sql( ) frappe.db.sql( )

494bd9ef78313436f0424b918f200dab8fc7c20b

sync_india_custom_fields.py

style: format code with black

erpnext

erpnext/patches/v8_7/sync_india_custom_fields.py

Python

https://github.com/frappe/erpnext.git

run

def run(self, request, pk): # Check that the user has permission to run reports. if not request.user.has_perm('extras.run_report'): raise PermissionDenied("This user does not have permission to run reports.") # Check that at least one RQ worker is running if not Worker.count(get_connection('default')): raise RQWorkerNotRunningException() # Retrieve and run the Report. This will create a new JobResult. report = self._retrieve_report(pk) report_content_type = ContentType.objects.get(app_label='extras', model='report') job_result = JobResult.enqueue_job( run_report, report.full_name, report_content_type, request.user, job_timeout=report.job_timeout ) report.result = job_result serializer = serializers.ReportDetailSerializer(report, context={'request': request}) return Response(serializer.data) # # Scripts #

36d6ae33d15e93cc552827cdea363a9c00c7f823

views.py

Allow setting individual timeouts on scripts and reports

netbox

netbox/extras/api/views.py

Python

https://github.com/netbox-community/netbox.git

test_purge_room_and_not_block

def test_purge_room_and_not_block(self) -> None: # Test that room is not purged with self.assertRaises(AssertionError): self._is_purged(self.room_id) # Test that room is not blocked self._is_blocked(self.room_id, expect=False) # Assert one user in room self._is_member(room_id=self.room_id, user_id=self.other_user) channel = self.make_request( "DELETE", self.url.encode("ascii"), content={"block": False, "purge": True}, access_token=self.admin_user_tok, ) self.assertEqual(200, channel.code, msg=channel.json_body) self.assertEqual(None, channel.json_body["new_room_id"]) self.assertEqual(self.other_user, channel.json_body["kicked_users"][0]) self.assertIn("failed_to_kick_users", channel.json_body) self.assertIn("local_aliases", channel.json_body) self._is_purged(self.room_id) self._is_blocked(self.room_id, expect=False) self._has_no_members(self.room_id)

c97042f7eef3748e17c90e48a4122389a89c4735

test_room.py

Use literals in place of `HTTPStatus` constants in tests (#13469)

synapse

tests/rest/admin/test_room.py

Python

https://github.com/matrix-org/synapse.git

get_next_connection

async def get_next_connection(self): return await self._get_next_connection(num_retries=3)

d21870ac47fc1594b45a5f01ee48cddf5c18b2ff

networking.py

fix: fix reconnect issues (#4941)

jina

jina/serve/networking.py

Python

https://github.com/jina-ai/jina.git

load_data_for_viz

def load_data_for_viz(load_type, model_file_statistics, dtype=int, ground_truth_split=2) -> Dict[str, Any]: supported_load_types = dict( load_json=load_json, load_from_file=partial(load_from_file, dtype=dtype, ground_truth_split=ground_truth_split), ) loader = supported_load_types[load_type] # Loads training stats from JSON file(s). try: stats_per_model = [loader(stats_f) for stats_f in model_file_statistics] except (TypeError, AttributeError): logger.exception(f"Unable to open model statistics file {model_file_statistics}!") raise return stats_per_model

4f40ffec8e81eb3f6385243498babe1409a675be

visualize.py

Changes learning_curves to use "step" or "epoch" as x-axis label. (#2578) * Started building dataclasses for model training output. * Adds EvaluationFrequency to training stats, dataclasses for training results. * Adds x_label, x_step to learning_curves. * fix x axis when using checkpoints_per_epoch. * Fixes CLI test by making dataclass JSON-serializable and implementing __contains__. * Adds default value for EvaluationFrequency, maybe fixes test_learning_curves with only training metrics. * Fixes kfold CV. * Fixes viz tests, restoring original functionality of load_data_for_viz * Adds todos to deprecate.

ludwig

ludwig/visualize.py

Python

https://github.com/ludwig-ai/ludwig.git

check_input_folder

def check_input_folder(self) -> Optional[cv2.VideoCapture]: err = None loadtype = self.__class__.__name__ if not self.folder: err = f"ERROR: A {loadtype} folder must be specified" elif not os.path.exists(self.folder): err = f"ERROR: The {loadtype} location {self.folder} could not be found" if err: logger.error(err) sys.exit(0) if (loadtype == "Frames" and os.path.isfile(self.folder) and os.path.splitext(self.folder)[1].lower() in _video_extensions): logger.verbose("Video exists at: '%s'", self.folder) # type: ignore retval = cv2.VideoCapture(self.folder) # pylint: disable=no-member # TODO ImageIO single frame seek seems slow. Look into this # retval = imageio.get_reader(self.folder, "ffmpeg") else: logger.verbose("Folder exists at '%s'", self.folder) # type: ignore retval = None return retval

e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1

media.py

Alignments Tool - Typing, Documentation + Re-org

faceswap

tools/alignments/media.py

Python

https://github.com/deepfakes/faceswap.git

generate_heatmap

def generate_heatmap(logits, num_classes): keypoint_colours = np.array([plt.cm.spectral(x) for x in np.linspace(0, 1, num_classes + 1)])[ ..., :3].astype(np.float32) prediction = tf.nn.softmax(logits) heatmap = tf.matmul(tf.reshape(prediction, (-1, num_classes + 1)), keypoint_colours) heatmap = tf.reshape(heatmap, (tf.shape(prediction)[0], tf.shape(prediction)[1], tf.shape(prediction)[2], 3)) return heatmap

7375ee364e0df2a417f92593e09557f1b2a3575a

utils.py

initialize ostec

insightface

reconstruction/ostec/external/landmark_detector/utils.py

Python

https://github.com/deepinsight/insightface.git

update_worker_pea_args

def update_worker_pea_args(self): self.peas_args['peas'] = self._set_peas_args(self.args)

933415bfa1f9eb89f935037014dfed816eb9815d

__init__.py

feat: star routing (#3900) * feat(proto): adjust proto for star routing (#3844) * feat(proto): adjust proto for star routing * feat(proto): generate proto files * feat(grpc): refactor grpclet interface (#3846) * feat: refactor connection pool for star routing (#3872) * feat(k8s): add more labels to k8s deployments * feat(network): refactor connection pool * feat(network): refactor k8s pool * feat: star routing graph gateway (#3877) * feat: star routing - refactor grpc data runtime (#3887) * feat(runtimes): refactor grpc dataruntime * fix(tests): adapt worker runtime tests * fix(import): fix import * feat(proto): enable sending multiple lists (#3891) * feat: star routing gateway (#3893) * feat: star routing gateway all protocols (#3897) * test: add streaming and prefetch tests (#3901) * feat(head): new head runtime for star routing (#3899) * feat(head): new head runtime * feat(head): new head runtime * style: fix overload and cli autocomplete * feat(network): improve proto comments Co-authored-by: Jina Dev Bot <[email protected]> * feat(worker): merge docs in worker runtime (#3905) * feat(worker): merge docs in worker runtime * feat(tests): assert after clean up * feat(tests): star routing runtime integration tests (#3908) * fix(tests): fix integration tests * test: test runtimes fast slow request (#3910) * feat(zmq): purge zmq, zed, routing_table (#3915) * feat(zmq): purge zmq, zed, routing_table * style: fix overload and cli autocomplete * feat(zmq): adapt comment in dependency list * style: fix overload and cli autocomplete * fix(tests): fix type tests Co-authored-by: Jina Dev Bot <[email protected]> * test: add test gateway to worker connection (#3921) * feat(pea): adapt peas for star routing (#3918) * feat(pea): adapt peas for star routing * style: fix overload and cli autocomplete * feat(pea): add tests * feat(tests): add failing head pea test Co-authored-by: Jina Dev Bot <[email protected]> * feat(tests): integration tests for peas (#3923) * feat(tests): integration tests for peas * feat(pea): remove _inner_pea function * feat: star routing container pea (#3922) * test: rescue tests (#3942) * fix: fix streaming tests (#3945) * refactor: move docker run to run (#3948) * feat: star routing pods (#3940) * feat(pod): adapt pods for star routing * feat(pods): adapt basepod to star routing * feat(pod): merge pod and compound pod * feat(tests): fix tests * style: fix overload and cli autocomplete * feat(test): add container pea int test * feat(ci): remove more unnecessary tests * fix(tests): remove jinad runtime * feat(ci): remove latency tracking * fix(ci): fix ci def * fix(runtime): enable runtime to be exited * fix(tests): wrap runtime test in process * fix(runtimes): remove unused runtimes * feat(runtimes): improve cancel wait * fix(ci): build test pip again in ci * fix(tests): fix a test * fix(test): run async in its own process * feat(pod): include shard in activate msg * fix(pea): dont join * feat(pod): more debug out * feat(grpc): manage channels properly * feat(pods): remove exitfifo * feat(network): add simple send retry mechanism * fix(network): await pool close * fix(test): always close grpc server in worker * fix(tests): remove container pea from tests * fix(tests): reorder tests * fix(ci): split tests * fix(ci): allow alias setting * fix(test): skip a test * feat(pods): address comments Co-authored-by: Jina Dev Bot <[email protected]> * test: unblock skipped test (#3957) * feat: jinad pea (#3949) * feat: jinad pea * feat: jinad pea * test: remote peas * test: toplogy tests with jinad * ci: parallel jobs * feat(tests): add pod integration tests (#3958) * feat(tests): add pod integration tests * fix(tests): make tests less flaky * fix(test): fix test * test(pea): remote pea topologies (#3961) * test(pea): remote pea simple topology * test: remote pea topologies * refactor: refactor streamer result handling (#3960) * feat(k8s): adapt K8s Pod for StarRouting (#3964) * test: optimize k8s test * test: increase timeout and use different namespace * test: optimize k8s test * test: build and load image when needed * test: refactor k8s test * test: fix image name error * test: fix k8s image load * test: fix typoe port expose * test: update tests in connection pool and handling * test: remove unused fixture * test: parameterize docker images * test: parameterize docker images * test: parameterize docker images * feat(k8s): adapt k8s pod for star routing * fix(k8s): dont overwrite add/remove function in pool * fix(k8s): some fixes * fix(k8s): some more fixes * fix(k8s): linting * fix(tests): fix tests * fix(tests): fix k8s unit tests * feat(k8s): complete k8s integration test * feat(k8s): finish k8s tests * feat(k8s): fix test * fix(tests): fix test with no name * feat(k8s): unify create/replace interface * feat(k8s): extract k8s port constants * fix(tests): fix tests * fix(tests): wait for runtime being ready in tests * feat(k8s): address comments Co-authored-by: bwanglzu <[email protected]> * feat(flow): adapt Flow for StarRouting (#3986) * feat(flow): add routes * feat(flow): adapt flow to star routing * style: fix overload and cli autocomplete * feat(flow): handle empty topologies * feat(k8s): allow k8s pool disabling * style: fix overload and cli autocomplete * fix(test): fix test with mock * fix(tests): fix more tests * feat(flow): clean up tests * style: fix overload and cli autocomplete * fix(tests): fix more tests * feat: add plot function (#3994) * fix(tests): avoid hanging tests * feat(flow): add type hinting * fix(test): fix duplicate exec name in test * fix(tests): fix more tests * fix(tests): enable jinad test again * fix(tests): random port fixture * fix(style): replace quotes Co-authored-by: Jina Dev Bot <[email protected]> Co-authored-by: Joan Fontanals <[email protected]> * feat(ci): bring back ci (#3997) * feat(ci): enable ci again * style: fix overload and cli autocomplete * feat(ci): add latency tracking * feat(ci): bring back some tests * fix(tests): remove invalid port test * feat(ci): disable daemon and distributed tests * fix(tests): fix entrypoint in hub test * fix(tests): wait for gateway to be ready * fix(test): fix more tests * feat(flow): do rolling update and scale sequentially * fix(tests): fix more tests * style: fix overload and cli autocomplete * feat: star routing hanging pods (#4011) * fix: try to handle hanging pods better * test: hanging pods test work * fix: fix topology graph problem * test: add unit test to graph * fix(tests): fix k8s tests * fix(test): fix k8s test * fix(test): fix k8s pool test * fix(test): fix k8s test * fix(test): fix k8s connection pool setting * fix(tests): make runtime test more reliable * fix(test): fix routes test * fix(tests): make rolling update test less flaky * feat(network): gurantee unique ports * feat(network): do round robin for shards * fix(ci): increase pytest timeout to 10 min Co-authored-by: Jina Dev Bot <[email protected]> Co-authored-by: Joan Fontanals <[email protected]> * fix(ci): fix ci file * feat(daemon): jinad pod for star routing * Revert "feat(daemon): jinad pod for star routing" This reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92. * feat(daemon): remote jinad pod support (#4042) * feat(daemon): add pod tests for star routing * feat(daemon): add remote pod test * test(daemon): add remote pod arguments test * test(daemon): add async scale test * test(daemon): add rolling update test * test(daemon): fix host * feat(proto): remove message proto (#4051) * feat(proto): remove message proto * fix(tests): fix tests * fix(tests): fix some more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * feat(proto): put docs back in data * fix(proto): clean up * feat(proto): clean up * fix(tests): skip latency tracking * fix(test): fix hub test * fix(tests): fix k8s test * fix(test): some test clean up * fix(style): clean up style issues * feat(proto): adjust for rebase * fix(tests): bring back latency tracking * fix(tests): fix merge accident * feat(proto): skip request serialization (#4074) * feat: add reduce to star routing (#4070) * feat: add reduce on shards to head runtime * test: add reduce integration tests with fixed order * feat: add reduce on needs * chore: get_docs_matrix_from_request becomes public * style: fix overload and cli autocomplete * docs: remove undeterministic results warning * fix: fix uses_after * test: assert correct num docs after reducing in test_external_pod * test: correct asserts after reduce in test_rolling_update * fix: no reduce if uses_after_address is set * fix: get_docs_from_request only if needed * fix: fix tests after merge * refactor: move reduce from data_request_handler to head * style: fix overload and cli autocomplete * chore: apply suggestions * fix: fix asserts * chore: minor test fix * chore: apply suggestions * test: remove flow tests with external executor (pea) * fix: fix test_expected_messages_routing * fix: fix test_func_joiner * test: adapt k8s test Co-authored-by: Jina Dev Bot <[email protected]> * fix(k8s): fix static pool config * fix: use custom protoc doc generator image (#4088) * fix: use custom protoc doc generator image * fix(docs): minor doc improvement * fix(docs): use custom image * fix(docs): copy docarray * fix: doc building local only * fix: timeout doc building * fix: use updated args when building ContainerPea * test: add container PeaFactory test * fix: force pea close on windows (#4098) * fix: dont reduce if uses exist (#4099) * fix: dont use reduce if uses exist * fix: adjust reduce tests * fix: adjust more reduce tests * fix: fix more tests * fix: adjust more tests * fix: ignore non jina resources (#4101) * feat(executor): enable async executors (#4102) * feat(daemon): daemon flow on star routing (#4096) * test(daemon): add remote flow test * feat(daemon): call scale in daemon * feat(daemon): remove tail args and identity * test(daemon): rename scalable executor * test(daemon): add a small delay in async test * feat(daemon): scale partial flow only * feat(daemon): call scale directly in partial flow store * test(daemon): use asyncio sleep * feat(daemon): enable flow level distributed tests * test(daemon): fix jinad env workspace config * test(daemon): fix pod test use new port rolling update * feat(daemon): enable distribuetd tests * test(daemon): remove duplicate tests and zed runtime test * test(daemon): fix stores unit test * feat(daemon): enable part of distributed tests * feat(daemon): enable part of distributed tests * test: correct test paths * test(daemon): add client test for remote flows * test(daemon): send a request with jina client * test(daemon): assert async generator * test(daemon): small interval between tests * test(daemon): add flow test for container runtime * test(daemon): add flow test for container runtime * test(daemon): fix executor name * test(daemon): fix executor name * test(daemon): use async client fetch result * test(daemon): finish container flow test * test(daemon): enable distributed in ci * test(daemon): enable distributed in ci * test(daemon): decare flows and pods * test(daemon): debug ci if else * test(daemon): debug ci if else * test(daemon): decare flows and pods * test(daemon): correct test paths * test(daemon): add small delay for async tests * fix: star routing fixes (#4100) * docs: update docs * fix: fix Request.__repr__ * docs: update flow remarks * docs: fix typo * test: add non_empty_fields test * chore: remove non_empty_fields test * feat: polling per endpoint (#4111) * feat(polling): polling per endpoint configurable * fix: adjust tests * feat(polling): extend documentation * style: fix overload and cli autocomplete * fix: clean up * fix: adjust more tests * fix: remove repeat from flaky test * fix: k8s test * feat(polling): address pr feedback * feat: improve docs Co-authored-by: Jina Dev Bot <[email protected]> * feat(grpc): support connect grpc server via ssl tunnel (#4092) * feat(grpc): support ssl grpc connect if port is 443 * fix(grpc): use https option instead of detect port automatically * chore: fix typo * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <[email protected]> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <[email protected]> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <[email protected]> * test(networking): add test for peapods networking * fix: address comments Co-authored-by: Joan Fontanals <[email protected]> * feat(polling): unify polling args (#4113) * fix: several issues for jinad pods (#4119) * fix: activate for jinad pods * fix: dont expose worker pod in partial daemon * fix: workspace setting * fix: containerized flows * fix: hub test * feat(daemon): remote peas on star routing (#4112) * test(daemon): fix request in peas * test(daemon): fix request in peas * test(daemon): fix sync async client test * test(daemon): enable remote peas test * test(daemon): replace send message to send request * test(daemon): declare pea tests in ci * test(daemon): use pea args fixture * test(daemon): head pea use default host * test(daemon): fix peas topologies * test(daemon): fix pseudo naming * test(daemon): use default host as host * test(daemon): fix executor path * test(daemon): add remote worker back * test(daemon): skip local remote remote topology * fix: jinad pea test setup * fix: jinad pea tests * fix: remove invalid assertion Co-authored-by: jacobowitz <[email protected]> * feat: enable daemon tests again (#4132) * feat: enable daemon tests again * fix: remove bogy empty script file * fix: more jinad test fixes * style: fix overload and cli autocomplete * fix: scale and ru in jinad * fix: fix more jinad tests Co-authored-by: Jina Dev Bot <[email protected]> * fix: fix flow test * fix: improve pea tests reliability (#4136) Co-authored-by: Joan Fontanals <[email protected]> Co-authored-by: Jina Dev Bot <[email protected]> Co-authored-by: Deepankar Mahapatro <[email protected]> Co-authored-by: bwanglzu <[email protected]> Co-authored-by: AlaeddineAbdessalem <[email protected]> Co-authored-by: Zhaofeng Miao <[email protected]>

jina

jina/peapods/pods/__init__.py

Python

https://github.com/jina-ai/jina.git

to_local_object_without_private_data_child

def to_local_object_without_private_data_child(self) -> SingleEntityPhiTensor: public_shape = getattr(self, "public_shape", None) public_dtype = getattr(self, "public_dtype", None) return Tensor( child=SingleEntityPhiTensor( child=FixedPrecisionTensor(value=None), entity=self.entity, min_vals=self.min_vals, # type: ignore max_vals=self.max_vals, # type: ignore scalar_manager=self.scalar_manager, ), public_shape=public_shape, public_dtype=public_dtype, )

a90188ecc017971b64778aa0ff41127a9d5d9d44

single_entity_phi.py

working fpt for SMPC+DP

PySyft

packages/syft/src/syft/core/tensor/autodp/single_entity_phi.py

Python

https://github.com/OpenMined/PySyft.git

_measurements

def _measurements(self): ismeasured = {} for i,g in enumerate(self._gates()): if getattr(g,'measurement',False): for target in g.targets: if target in ismeasured: if ismeasured[target] > i: ismeasured[target] = i else: ismeasured[target] = i return ismeasured

55c2eba0fc6eefa30c07e2e76795c1df89488b11

circuitplot.py

Update documentation

sympy

sympy/physics/quantum/circuitplot.py

Python

https://github.com/sympy/sympy.git

parse_example_proto_and_decode

def parse_example_proto_and_decode(example_serialized): image_buffer, label = _parse_example_proto(example_serialized) image_buffer = tf.reshape(image_buffer, shape=[]) image_buffer = tf.io.decode_jpeg(image_buffer, channels=NUM_CHANNELS) return image_buffer, label

02f911ce78137cb63ecb685a8ef8e56dcb60062c

tf_utils.py

Benchmarking Ray Data bulk ingest as input file size changes. (#29296) This PR adds a benchmark which takes work from https://github.com/anyscale/air-benchmarks and makes it run as a release test. Full metrics are stored in Databricks. Signed-off-by: Cade Daniel <[email protected]>

ray

release/air_tests/air_benchmarks/mlperf-train/tf_utils.py

Python

https://github.com/ray-project/ray.git

get_currency

def get_currency(filters): company = get_appropriate_company(filters) company_currency = get_company_currency(company) presentation_currency = ( filters["presentation_currency"] if filters.get("presentation_currency") else company_currency ) report_date = filters.get("to_date") if not report_date: fiscal_year_to_date = get_from_and_to_date(filters.get("to_fiscal_year"))["to_date"] report_date = formatdate(get_datetime_str(fiscal_year_to_date), "dd-MM-yyyy") currency_map = dict( company=company, company_currency=company_currency, presentation_currency=presentation_currency, report_date=report_date, ) return currency_map

494bd9ef78313436f0424b918f200dab8fc7c20b

utils.py

style: format code with black

erpnext

erpnext/accounts/report/utils.py

Python

https://github.com/frappe/erpnext.git

test_query_order_fields_order_with_new_id_by_anonymous_user

def test_query_order_fields_order_with_new_id_by_anonymous_user(order, api_client): # given variables = {"id": graphene.Node.to_global_id("Order", order.pk)} # when response = api_client.post_graphql(QUERY_ORDER_FIELDS_BY_ID, variables) # then content = get_graphql_content(response) assert content["data"]["order"] assert ( content["data"]["order"]["billingAddress"]["streetAddress1"] == order.billing_address.street_address_1 ) assert ( content["data"]["order"]["shippingAddress"]["streetAddress1"] == order.shipping_address.street_address_1 ) assert content["data"]["order"]["userEmail"] == order.user_email

71c19c951bcfba66fa9a9ee5809a46ad3af8f11f

test_order.py

Allow fetching by id all order data for new orders (#9728)

saleor

saleor/graphql/order/tests/test_order.py

Python

https://github.com/saleor/saleor.git

mkdtemp

def mkdtemp(self): d = tempfile.mkdtemp() self.tempdirs.append(d) return d

8198943edd73a363c266633e1aa5b2a9e9c9f526

support.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/tests/support.py

Python

https://github.com/XX-net/XX-Net.git

__str__

def __str__(self): call_str = f'db.{self.collection}' for step in self.pipeline: args_str = [] for arg in step['args']: args_str.append(MongoJSONEncoder().encode(arg)) call_str += f'.{step["method"]}({",".join(args_str)})' return call_str

d5b6d8cf5bd69a1f3427bac153fa09159dfe96d0

mongodb_query.py

added converters: - mongo to str - str to mongo creating predictor from sql using mongo data tests

mindsdb

mindsdb/integrations/handlers/mongodb_handler/utils/mongodb_query.py

Python

https://github.com/mindsdb/mindsdb.git

pairwise

def pairwise(iterable): # type: (Iterable[Any]) -> Iterator[Tuple[Any, Any]] iterable = iter(iterable) return zip_longest(iterable, iterable)

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

misc.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/utils/misc.py

Python

https://github.com/jindongwang/transferlearning.git

complete_code

def complete_code(accelerator, model, tokenizer, dataloader, n_tasks, batch_size=20, **gen_kwargs): gen_token_dict = defaultdict(list) # dict of list of generated tokens for step, batch in tqdm(enumerate(dataloader)): with torch.no_grad(): gen_kwargs["stopping_criteria"][0].start_length = batch["ids"].shape[-1] generated_tokens = accelerator.unwrap_model(model).generate( input_ids=batch["ids"][:, : batch["input_len"]], num_return_sequences=batch_size, **gen_kwargs ) # each task is generated batch_size times generated_tasks = batch["task_id"].repeat(batch_size) generated_tokens = accelerator.pad_across_processes( generated_tokens, dim=1, pad_index=tokenizer.pad_token_id ) generated_tokens, generated_tasks = accelerator.gather((generated_tokens, generated_tasks)) generated_tokens = generated_tokens.cpu().numpy() generated_tasks = generated_tasks.cpu().numpy() for task, generated_tokens in zip(generated_tasks, generated_tokens): gen_token_dict[task].append(generated_tokens) code_gens = [[] for _ in range(n_tasks)] for task, generated_tokens in gen_token_dict.items(): for s in generated_tokens: gen_code = tokenizer.decode(s, skip_special_tokens=True, clean_up_tokenization_spaces=True) code_gens[task].append(remove_last_block(gen_code)) return code_gens

4868a830db5f19f56712f540979d637368221d50

human_eval.py

Jia multi gpu eval (#16428) * add simple multi gpu complet * add human_eval_multi_gpu * use copy strategy to distribute across gpu, to avoid padding * add doc string * update code style * use task id to arrange output * truncate input to avoid zero pad * Stop the copy mechanism * update style * restore copies to scale better in distributed mode * update style * replace human eval * Apply suggestions from code review 1. Tokenize all input at the same time 2. use attention_mask to get the input length 3. other small fixes Co-authored-by: Leandro von Werra <[email protected]> * correct typo and update docstring * update code style * remove num sample division constraint * remove max len calculation * use accelerator.gather once to speed up * use accelerate set_seed; update accelerate version * correct gather bug Co-authored-by: Leandro von Werra <[email protected]>

transformers

examples/research_projects/codeparrot/scripts/human_eval.py

Python

https://github.com/huggingface/transformers.git

delegate_command

def delegate_command(args, host_state, exclude, require): # type: (EnvironmentConfig, HostState, t.List[str], t.List[str]) -> None con = host_state.controller_profile.get_origin_controller_connection() working_directory = host_state.controller_profile.get_working_directory() host_delegation = not isinstance(args.controller, OriginConfig) if host_delegation: if data_context().content.collection: content_root = os.path.join(working_directory, data_context().content.collection.directory) else: content_root = os.path.join(working_directory, 'ansible') ansible_bin_path = os.path.join(working_directory, 'ansible', 'bin') with tempfile.NamedTemporaryFile(prefix='ansible-source-', suffix='.tgz') as payload_file: create_payload(args, payload_file.name) con.extract_archive(chdir=working_directory, src=payload_file) else: content_root = working_directory ansible_bin_path = ANSIBLE_BIN_PATH command = generate_command(args, host_state.controller_profile.python, ansible_bin_path, content_root, exclude, require) if isinstance(con, SshConnection): ssh = con.settings else: ssh = None options = [] if isinstance(args, IntegrationConfig) and args.controller.is_managed and all(target.is_managed for target in args.targets): if not args.allow_destructive: options.append('--allow-destructive') with support_container_context(args, ssh) as containers: # type: t.Optional[ContainerDatabase] if containers: options.extend(['--containers', json.dumps(containers.to_dict())]) # Run unit tests unprivileged to prevent stray writes to the source tree. # Also disconnect from the network once requirements have been installed. if isinstance(args, UnitsConfig) and isinstance(con, DockerConnection): pytest_user = 'pytest' writable_dirs = [ os.path.join(content_root, ResultType.JUNIT.relative_path), os.path.join(content_root, ResultType.COVERAGE.relative_path), ] con.run(['mkdir', '-p'] + writable_dirs) con.run(['chmod', '777'] + writable_dirs) con.run(['chmod', '755', working_directory]) con.run(['chmod', '644', os.path.join(content_root, args.metadata_path)]) con.run(['useradd', pytest_user, '--create-home']) con.run(insert_options(command, options + ['--requirements-mode', 'only'])) container = con.inspect() networks = container.get_network_names() if networks is not None: for network in networks: con.disconnect_network(network) else: display.warning('Network disconnection is not supported (this is normal under podman). ' 'Tests will not be isolated from the network. Network-related tests may misbehave.') options.extend(['--requirements-mode', 'skip']) con.user = pytest_user success = False try: con.run(insert_options(command, options)) success = True finally: if host_delegation: download_results(args, con, content_root, success)

a06fa496d3f837cca3c437ab6e9858525633d147

delegation.py

ansible-test - Code cleanup and refactoring. (#77169) * Remove unnecessary PyCharm ignores. * Ignore intentional undefined attribute usage. * Add missing type hints. Fix existing type hints. * Fix docstrings and comments. * Use function to register completion handler. * Pass strings to display functions. * Fix CompositeAction handling of dest argument. * Use consistent types in expressions/assignments. * Use custom function to keep linters happy. * Add missing raise for custom exception. * Clean up key/value type handling in cloud plugins. * Use dataclass instead of dict for results. * Add custom type_guard function to check lists. * Ignore return type that can't be checked (yet). * Avoid changing types on local variables.