





from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml







class     __snake_case       (							yaml.SafeLoader			):





       '''simple docstring'''







       def 							UpperCAmelCase__ (  self :    Optional[int]							,				A :    Dict		):
         __snake_case:						Optional[Any]   =						[self.constructed_objects[key_node] for key_node, _ in node.value]
         __snake_case:						Dict   =						[tuple(A		) if isinstance(A							,				A		) else key for key in keys]
         __snake_case:						Optional[int]   =						Counter(A		)
         __snake_case:						Optional[int]   =						[key for key in counter if counter[key] > 1]
         if duplicate_keys:
           raise TypeError(f'''Got duplicate yaml keys: {duplicate_keys}'''		)






       def 							UpperCAmelCase__ (  self :    Optional[Any]							,				A :    Union[str, Any]							,				A :    Union[str, Any]=False		):
         __snake_case:						int   =						super().construct_mapping(A							,				deep=A		)
         self._check_no_duplicates_on_constructed_node(A		)
         return mapping







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    Tuple[Optional[str], str]:
  __snake_case:						Union[str, Any]   =						list(readme_content.splitlines())
  if full_content and full_content[0] == "---" and "---" in full_content[1:]:
    __snake_case:						Optional[int]   =						full_content[1:].index("""---""") + 1
    __snake_case:						List[Any]   =						"""\n""".join(full_content[1:sep_idx])
    return yamlblock, "\n".join(full_content[sep_idx + 1 :])

  return None, "\n".join(SCREAMING_SNAKE_CASE__)







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       lowerCAmelCase__      		=     {"""train_eval_index"""}  # train-eval-index in the YAML metadata




       @classmethod
       def 							UpperCAmelCase__ (  cls :    Optional[Any]							,				A :    Path		):
         with open(A							,				encoding="""utf-8"""		) as readme_file:
           __snake_case  ,   __snake_case:						int   =						_split_yaml_from_readme(readme_file.read()		)
         if yaml_string is not None:
           return cls.from_yaml_string(A		)
         else:
           return cls()




       def 							UpperCAmelCase__ (  self :    Tuple							,				A :    Path		):
         if path.exists():
           with open(A							,				encoding="""utf-8"""		) as readme_file:
             __snake_case:						Any   =						readme_file.read()
         else:
           __snake_case:						Optional[Any]   =						None
         __snake_case:						Optional[int]   =						self._to_readme(A		)
         with open(A							,				"""w"""							,				encoding="""utf-8"""		) as readme_file:
           readme_file.write(A		)




       def 							UpperCAmelCase__ (  self :    Tuple							,				A :    Optional[str] = None		):
         if readme_content is not None:
           __snake_case  ,   __snake_case:						Dict   =						_split_yaml_from_readme(A		)
           __snake_case:						List[str]   =						"""---\n""" + self.to_yaml_string() + """---\n""" + content
         else:
           __snake_case:						Dict   =						"""---\n""" + self.to_yaml_string() + """---\n"""
         return full_content




       @classmethod
       def 							UpperCAmelCase__ (  cls :    Tuple							,				A :    str		):
         __snake_case:						int   =						yaml.load(A							,				Loader=_NoDuplicateSafeLoader		) or {}

         # Convert the YAML keys to DatasetMetadata fields
         __snake_case:						Tuple   =						{
             (key.replace("""-"""							,				"""_"""		) if key.replace("""-"""							,				"""_"""		) in cls._FIELDS_WITH_DASHES else key): value
             for key, value in metadata_dict.items()
         }
         return cls(**A		)






       def 							UpperCAmelCase__ (  self :    Union[str, Any]		):
         return yaml.safe_dump(
             {
                 (key.replace("""_"""							,				"""-"""		) if key in self._FIELDS_WITH_DASHES else key): value
                 for key, value in self.items()
             }							,				sort_keys=A							,				allow_unicode=A							,				encoding="""utf-8"""							,				).decode("""utf-8"""		)






__UpperCAmelCase       :   Any				       =							{
    "image-classification": [],
    "translation": [],
    "image-segmentation": [],
    "fill-mask": [],
    "automatic-speech-recognition": [],
    "token-classification": [],
    "sentence-similarity": [],
    "audio-classification": [],
    "question-answering": [],
    "summarization": [],
    "zero-shot-classification": [],
    "table-to-text": [],
    "feature-extraction": [],
    "other": [],
    "multiple-choice": [],
    "text-classification": [],
    "text-to-image": [],
    "text2text-generation": [],
    "zero-shot-image-classification": [],
    "tabular-classification": [],
    "tabular-regression": [],
    "image-to-image": [],
    "tabular-to-text": [],
    "unconditional-image-generation": [],
    "text-retrieval": [],
    "text-to-speech": [],
    "object-detection": [],
    "audio-to-audio": [],
    "text-generation": [],
    "conversational": [],
    "table-question-answering": [],
    "visual-question-answering": [],
    "image-to-text": [],
    "reinforcement-learning": [],
    "voice-activity-detection": [],
    "time-series-forecasting": [],
    "document-question-answering": [],
}


if __name__ == "__main__":
      from argparse import ArgumentParser

      __UpperCAmelCase       :   Optional[int]				       =							ArgumentParser(usage="Validate the yaml metadata block of a README.md file.")
      ap.add_argument("readme_filepath")
      __UpperCAmelCase       :   List[Any]				       =							ap.parse_args()

      __UpperCAmelCase       :   int				       =							Path(args.readme_filepath)
      __UpperCAmelCase       :   Union[str, Any]				       =							DatasetMetadata.from_readme(readme_filepath)
      print(dataset_metadata)
      dataset_metadata.to_readme(readme_filepath)













import pytest


__UpperCAmelCase       :   Optional[Any]				       =							"__dummy_dataset1__"

__UpperCAmelCase       :   List[str]				       =							"\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_URL + \"wikiann-bn-validation.jsonl\"}\n\n\nclass __DummyDataset1__(datasets.GeneratorBasedBuilder):\n\n    def _info(self):\n        features = datasets.Features(\n            {\n                \"tokens\": datasets.Sequence(datasets.Value(\"string\")),\n                \"ner_tags\": datasets.Sequence(\n                    datasets.features.ClassLabel(\n                        names=[\n                            \"O\",\n                            \"B-PER\",\n                            \"I-PER\",\n                            \"B-ORG\",\n                            \"I-ORG\",\n                            \"B-LOC\",\n                            \"I-LOC\",\n                        ]\n                    )\n                ),\n                \"langs\": datasets.Sequence(datasets.Value(\"string\")),\n                \"spans\": datasets.Sequence(datasets.Value(\"string\")),\n            }\n        )\n        return datasets.DatasetInfo(features=features)\n\n    def _split_generators(self, dl_manager):\n        dl_path = dl_manager.download(URLS)\n        return [\n            datasets.SplitGenerator(datasets.Split.TRAIN, gen_kwargs={\"filepath\": dl_path[\"train\"]}),\n            datasets.SplitGenerator(datasets.Split.VALIDATION, gen_kwargs={\"filepath\": dl_path[\"validation\"]}),\n        ]\n\n    def _generate_examples(self, filepath):\n        with open(filepath, \"r\", encoding=\"utf-8\") as f:\n            for i, line in enumerate(f):\n                yield i, json.loads(line)\n"







@pytest.fixture
def 			A__							(    )   ->    Optional[int]:
  return DATASET_LOADING_SCRIPT_NAME







@pytest.fixture
def 			A__							(    )   ->    Tuple:
  return DATASET_LOADING_SCRIPT_CODE







@pytest.fixture
def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Tuple:
  __snake_case:						List[Any]   =						dataset_loading_script_name
  __snake_case:						Any   =						tmp_path / """datasets""" / script_name
  script_dir.mkdir(parents=SCREAMING_SNAKE_CASE__)
  __snake_case:						int   =						script_dir / F'''{script_name}.py'''
  with open(SCREAMING_SNAKE_CASE__					,					"""w""") as f:
    f.write(SCREAMING_SNAKE_CASE__)
  return str(SCREAMING_SNAKE_CASE__)






