




from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader


class        UpperCamelCase_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    def __init__(    self   :			str      ,				UpperCAmelCase__   :			pyspark.sql.DataFrame      ,				UpperCAmelCase__   :			Optional[NamedSplit] = None      ,				UpperCAmelCase__   :			Optional[Features] = None      ,				UpperCAmelCase__   :			bool = True      ,				UpperCAmelCase__   :			str = None      ,				UpperCAmelCase__   :			bool = False      ,				UpperCAmelCase__   :			str = None      ,				UpperCAmelCase__   :			bool = True      ,				UpperCAmelCase__   :			str = "arrow"      ,				**UpperCAmelCase__   :			str      ,				)		->Tuple:





           '''simple docstring'''

           super().__init__(
               split=UpperCAmelCase__      ,				features=UpperCAmelCase__      ,				cache_dir=UpperCAmelCase__      ,				keep_in_memory=UpperCAmelCase__      ,				streaming=UpperCAmelCase__      ,				**UpperCAmelCase__      ,				)
           A__   				=					load_from_cache_file
           A__   				=					file_format
           A__   				=					Spark(
               df=UpperCAmelCase__      ,				features=UpperCAmelCase__      ,				cache_dir=UpperCAmelCase__      ,				working_dir=UpperCAmelCase__      ,				**UpperCAmelCase__      ,				)





    def  SCREAMING_SNAKE_CASE							(    self   :			Optional[int])		->Tuple:





           '''simple docstring'''

           if self.streaming:
                  return self.builder.as_streaming_dataset(split=self.split)
           A__   				=					None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
           self.builder.download_and_prepare(
               download_mode=UpperCAmelCase__      ,				file_format=self._file_format      ,				)
           return self.builder.as_dataset(split=self.split)








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"""))


