




from typing import List

import numpy as np







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> int:



       """simple docstring"""

       A__   				=					{key: len(lowercase_		) for key, value in gen_kwargs.items() if isinstance(lowercase_				,       lowercase_		)}
       if len(set(lists_lengths.values()		)		) > 1:
              raise RuntimeError(
                  (
                      '''Sharding is ambiguous for this dataset: '''
                      + '''we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'''
                      + '''\n'''.join(f"""\t- key {key} has length {length}""" for key, length in lists_lengths.items()		)
                      + '''\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '''
                      + '''and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'''
                  )		)
       A__   				=					max(lists_lengths.values()				,       default=0		)
       return max(1				,       lowercase_		)







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> List[range]:



       """simple docstring"""

       A__   				=					[]
       for group_idx in range(lowercase_		):
              A__   				=					num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
              if num_shards_to_add == 0:
                     break
              A__   				=					shards_indices_per_group[-1].stop if shards_indices_per_group else 0
              A__   				=					range(lowercase_				,       start + num_shards_to_add		)
              shards_indices_per_group.append(lowercase_		)
       return shards_indices_per_group







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> List[dict]:



       """simple docstring"""

       A__   				=					_number_of_shards_in_gen_kwargs(lowercase_		)
       if num_shards == 1:
              return [dict(lowercase_		)]
       else:
              A__   				=					_distribute_shards(num_shards=lowercase_				,       max_num_jobs=lowercase_		)
              return [
                  {
                      key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
                      if isinstance(lowercase_				,       lowercase_		)
                      else value
                      for key, value in gen_kwargs.items()
                  }
                  for group_idx in range(len(lowercase_		)		)
              ]







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> dict:



       """simple docstring"""

       return {
           key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
           if isinstance(gen_kwargs_list[0][key]				,       lowercase_		)
           else gen_kwargs_list[0][key]
           for key in gen_kwargs_list[0]
       }







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> dict:



       """simple docstring"""

       A__   				=					{len(lowercase_		) for value in gen_kwargs.values() if isinstance(lowercase_				,       lowercase_		)}
       A__   				=					{}
       for size in list_sizes:
              A__   				=					list(range(lowercase_		)		)
              rng.shuffle(indices_per_size[size]		)
       # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
       A__   				=					dict(lowercase_		)
       for key, value in shuffled_kwargs.items():
              if isinstance(lowercase_				,       lowercase_		):
                     A__   				=					[value[i] for i in indices_per_size[len(lowercase_		)]]
       return shuffled_kwargs








def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> float:



       """simple docstring"""

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

              return "".join(lowercase_		)

       # matching characters
       A__   				=					get_matched_characters(lowercase_				,       lowercase_		)
       A__   				=					get_matched_characters(lowercase_				,       lowercase_		)
       A__   				=					len(lowercase_		)

       # transposition
       A__   				=					(
           len([(ca, ca) for ca, ca in zip(lowercase_				,       lowercase_		) if ca != ca]		) // 2
       )

       if not match_count:
              A__   				=					0.0
       else:
              A__   				=					(
                  1
                  / 3
                  * (
                      match_count / len(lowercase_		)
                      + match_count / len(lowercase_		)
                      + (match_count - transpositions) / match_count
                  )
              )

       # common prefix up to 4 characters
       A__   				=					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"""))


