



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

import yaml



class     lowerCAmelCase_		(  yaml.SafeLoader							):
       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		Optional[Any]:
          UpperCamelCase   :  List[Any]						     =     [self.constructed_objects[key_node] for key_node, _ in node.value]
          UpperCamelCase   :  str						     =     [tuple(SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_	) else key for key in keys]
          UpperCamelCase   :  Optional[Any]						     =     Counter(SCREAMING_SNAKE_CASE_	)
          UpperCamelCase   :  Tuple						     =     [key for key in counter if counter[key] > 1]
          if duplicate_keys:
             raise TypeError(F"""Got duplicate yaml keys: {duplicate_keys}"""	)






       def  snake_case_	(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_=False	)					->		int:
          UpperCamelCase   :  int						     =     super().construct_mapping(SCREAMING_SNAKE_CASE_,      deep=SCREAMING_SNAKE_CASE_	)
          self._check_no_duplicates_on_constructed_node(SCREAMING_SNAKE_CASE_	)
          return mapping






def 		UpperCamelCase     (       snake_case__	:   List[str]     )     ->					Tuple[Optional[str], str]:
   UpperCamelCase   :  Tuple						     =     list(readme_content.splitlines()     )
   if full_content and full_content[0] == "---" and "---" in full_content[1:]:
      UpperCamelCase   :  List[str]						     =     full_content[1:].index('---'     ) + 1
      UpperCamelCase   :  Tuple						     =     '\n'.join(full_content[1:sep_idx]     )
      return yamlblock, "\n".join(full_content[sep_idx + 1 :]     )

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



class     lowerCAmelCase_		(  __UpperCamelCase							):
       # class attributes
       UpperCAmelCase__    : List[str]       					=  {"train_eval_index"}  # train-eval-index in the YAML metadata
       @classmethod
       def  snake_case_	(      cls,      SCREAMING_SNAKE_CASE_	)					->		"DatasetMetadata":
          with open(SCREAMING_SNAKE_CASE_,      encoding='utf-8'	) as readme_file:
             UpperCamelCase   :  List[Any]						     =     _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  snake_case_	(      self,      SCREAMING_SNAKE_CASE_	)					->		Any:
          if path.exists():
             with open(SCREAMING_SNAKE_CASE_,      encoding='utf-8'	) as readme_file:
                UpperCamelCase   :  Any						     =     readme_file.read()
          else:
             UpperCamelCase   :  Any						     =     None
          UpperCamelCase   :  List[str]						     =     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  snake_case_	(      self,      SCREAMING_SNAKE_CASE_ = None	)					->		str:
          if readme_content is not None:
             UpperCamelCase   :  int						     =     _split_yaml_from_readme(SCREAMING_SNAKE_CASE_	)
             UpperCamelCase   :  Dict						     =     '---\n' + self.to_yaml_string() + '---\n' + content
          else:
             UpperCamelCase   :  Optional[Any]						     =     '---\n' + self.to_yaml_string() + '---\n'
          return full_content
       @classmethod
       def  snake_case_	(      cls,      SCREAMING_SNAKE_CASE_	)					->		"DatasetMetadata":
          UpperCamelCase   :  Any						     =     yaml.load(SCREAMING_SNAKE_CASE_,      Loader=_NoDuplicateSafeLoader	) or {}

          # Convert the YAML keys to DatasetMetadata fields
          UpperCamelCase   :  Tuple						     =     {
              (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  snake_case_	(      self	)					->		str:
          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'	)






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

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








from graphs.minimum_spanning_tree_kruskal import kruskal
def 		UpperCamelCase     (       )     ->					Tuple:
   UpperCamelCase   :  List[str]						     =     9
   UpperCamelCase   :  Optional[Any]						     =     [
       [0, 1, 4],
       [0, 7, 8],
       [1, 2, 8],
       [7, 8, 7],
       [7, 6, 1],
       [2, 8, 2],
       [8, 6, 6],
       [2, 3, 7],
       [2, 5, 4],
       [6, 5, 2],
       [3, 5, 14],
       [3, 4, 9],
       [5, 4, 10],
       [1, 7, 11],
   ]

   UpperCamelCase   :  int						     =     kruskal(snake_case__	,					snake_case__     )

   UpperCamelCase   :  List[str]						     =     [
       [7, 6, 1],
       [2, 8, 2],
       [6, 5, 2],
       [0, 1, 4],
       [2, 5, 4],
       [2, 3, 7],
       [0, 7, 8],
       [3, 4, 9],
   ]

   assert sorted(snake_case__     ) == sorted(snake_case__     )



