




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

import yaml




class    _A					(		yaml.SafeLoader  ):






		def 					UpperCAmelCase			(     self    ,		_SCREAMING_SNAKE_CASE      ):
								_UpperCAmelCase	     =      [self.constructed_objects[key_node] for key_node, _ in node.value]
								_UpperCAmelCase	     =      [tuple(__SCREAMING_SNAKE_CASE      ) if isinstance(__SCREAMING_SNAKE_CASE    ,		__SCREAMING_SNAKE_CASE      ) else key for key in keys]
								_UpperCAmelCase	     =      Counter(__SCREAMING_SNAKE_CASE      )
								_UpperCAmelCase	     =      [key for key in counter if counter[key] > 1]
								if duplicate_keys:
														raise TypeError(F"Got duplicate yaml keys: {duplicate_keys}"      )






		def 					UpperCAmelCase			(     self    ,		_SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE=False      ):
								_UpperCAmelCase	     =      super().construct_mapping(__SCREAMING_SNAKE_CASE    ,		deep=__SCREAMING_SNAKE_CASE      )
								self._check_no_duplicates_on_constructed_node(__SCREAMING_SNAKE_CASE      )
								return mapping




def 							_SCREAMING_SNAKE_CASE   (		snake_case							)    ->					Dict:
						_UpperCAmelCase	     =      list(readme_content.splitlines()							)
						if full_content and full_content[0] == "---" and "---" in full_content[1:]:
												_UpperCAmelCase	     =      full_content[1:].index("""---"""							) + 1
												_UpperCAmelCase	     =      '''\n'''.join(full_content[1:sep_idx]							)
												return yamlblock, "\n".join(full_content[sep_idx + 1 :]							)

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




class    _A					(		UpperCamelCase_  ):
		__a            =							{"""train_eval_index"""}  # train-eval-index in the YAML metadata






		@classmethod
		def 					UpperCAmelCase			(     cls    ,		_SCREAMING_SNAKE_CASE      ):







								with open(__SCREAMING_SNAKE_CASE    ,		encoding="""utf-8"""      ) as readme_file:
														_UpperCAmelCase	     =      _split_yaml_from_readme(readme_file.read()      )
								if yaml_string is not None:
														return cls.from_yaml_string(__SCREAMING_SNAKE_CASE      )
								else:
														return cls()






		def 					UpperCAmelCase			(     self    ,		_SCREAMING_SNAKE_CASE      ):







								if path.exists():
														with open(__SCREAMING_SNAKE_CASE    ,		encoding="""utf-8"""      ) as readme_file:
																				_UpperCAmelCase	     =      readme_file.read()
								else:
														_UpperCAmelCase	     =      None
								_UpperCAmelCase	     =      self._to_readme(__SCREAMING_SNAKE_CASE      )
								with open(__SCREAMING_SNAKE_CASE    ,		"""w"""    ,		encoding="""utf-8"""      ) as readme_file:
														readme_file.write(__SCREAMING_SNAKE_CASE      )






		def 					UpperCAmelCase			(     self    ,		_SCREAMING_SNAKE_CASE = None      ):







								if readme_content is not None:
														_UpperCAmelCase	     =      _split_yaml_from_readme(__SCREAMING_SNAKE_CASE      )
														_UpperCAmelCase	     =      '''---\n''' + self.to_yaml_string() + '''---\n''' + content
								else:
														_UpperCAmelCase	     =      '''---\n''' + self.to_yaml_string() + '''---\n'''
								return full_content






		@classmethod
		def 					UpperCAmelCase			(     cls    ,		_SCREAMING_SNAKE_CASE      ):
								_UpperCAmelCase	     =      yaml.load(__SCREAMING_SNAKE_CASE    ,		Loader=_NoDuplicateSafeLoader      ) or {}

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






		def 					UpperCAmelCase			(     self      ):
								return yaml.safe_dump(
								    {
								        (key.replace("""_"""    ,		"""-"""      ) if key in self._FIELDS_WITH_DASHES else key): value
								        for key, value in self.items()
								    }    ,		sort_keys=__SCREAMING_SNAKE_CASE    ,		allow_unicode=__SCREAMING_SNAKE_CASE    ,		encoding="""utf-8"""    ,		).decode("""utf-8"""      )



a    				=      {
    "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

				a    				=      ArgumentParser(usage="Validate the yaml metadata block of a README.md file.")
				ap.add_argument("readme_filepath")
				a    				=      ap.parse_args()

				a    				=      Path(args.readme_filepath)
				a    				=      DatasetMetadata.from_readme(readme_filepath)
				print(dataset_metadata)
				dataset_metadata.to_readme(readme_filepath)

def 				SCREAMING_SNAKE_CASE_   (      UpperCamelCase__			,		UpperCamelCase__		):

      def get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		) -> str:
            UpperCamelCase__     : Union[str, Any]											=					[]
            UpperCamelCase__     : Union[str, Any]											=					min(len(_stra		)			,		len(_stra		)		) // 2
            for i, l in enumerate(_stra		):
                  UpperCamelCase__     : Optional[int]											=					int(max(0			,		i - limit		)		)
                  UpperCamelCase__     : List[str]											=					int(min(i + limit + 1			,		len(_stra		)		)		)
                  if l in _stra[left:right]:
                        matched.append(UpperCamelCase__		)
                        UpperCamelCase__     : List[str]											=					f'''{_stra[0:_stra.index(UpperCamelCase__		)]} {_stra[_stra.index(UpperCamelCase__		) + 1:]}'''

            return "".join(UpperCamelCase__		)

      # matching characters
      UpperCamelCase__     : Any											=					get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		)
      UpperCamelCase__     : Union[str, Any]											=					get_matched_characters(UpperCamelCase__			,		UpperCamelCase__		)
      UpperCamelCase__     : List[Any]											=					len(UpperCamelCase__		)

      # transposition
      UpperCamelCase__     : str											=					(
          len([(ca, ca) for ca, ca in zip(UpperCamelCase__			,		UpperCamelCase__		) if ca != ca]		) // 2
      )

      if not match_count:
            UpperCamelCase__     : Union[str, Any]											=					0.0
      else:
            UpperCamelCase__     : Optional[int]											=					(
                1
                / 3
                * (
                    match_count / len(UpperCamelCase__		)
                    + match_count / len(UpperCamelCase__		)
                    + (match_count - transpositions) / match_count
                )
            )

      # common prefix up to 4 characters
      UpperCamelCase__     : Dict											=					0
      for ca, ca in zip(stra[:4]			,		stra[:4]		):
            if ca == ca:
                  prefix_len += 1
            else:
                  break

      return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    print(jaro_winkler("hello", "world"))


