



def 		UpperCamelCase     (       snake_case__	:   str	,					snake_case__	:   str     )     ->					List[str]:

   if not (isinstance(UpperCAmelCase_	,					UpperCAmelCase_     ) and isinstance(UpperCAmelCase_	,					UpperCAmelCase_     )):
      raise ValueError('longest_common_substring() takes two strings for inputs'     )

   UpperCamelCase   :  Optional[int]						     =     len(UpperCAmelCase_     )
   UpperCamelCase   :  int						     =     len(UpperCAmelCase_     )

   UpperCamelCase   :  Union[str, Any]						     =     [[0] * (texta_length + 1) for _ in range(texta_length + 1     )]
   UpperCamelCase   :  str						     =     0
   UpperCamelCase   :  List[str]						     =     0

   for i in range(1	,					texta_length + 1     ):
      for j in range(1	,					texta_length + 1     ):
         if texta[i - 1] == texta[j - 1]:
            UpperCamelCase   :  str						     =     1 + dp[i - 1][j - 1]
            if dp[i][j] > ans_length:
               UpperCamelCase   :  Optional[Any]						     =     i
               UpperCamelCase   :  Union[str, Any]						     =     dp[i][j]

   return texta[ans_index - ans_length : ans_index]


if __name__ == "__main__":
    import doctest

    doctest.testmod()








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     lowerCAmelCase_		(  a__							):
       def __init__(      self,      SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ = None,      SCREAMING_SNAKE_CASE_ = None,      SCREAMING_SNAKE_CASE_ = True,      SCREAMING_SNAKE_CASE_ = None,      SCREAMING_SNAKE_CASE_ = False,      SCREAMING_SNAKE_CASE_ = None,      SCREAMING_SNAKE_CASE_ = True,      SCREAMING_SNAKE_CASE_ = "arrow",      **SCREAMING_SNAKE_CASE_,      )					->		int:
          super().__init__(
              split=SCREAMING_SNAKE_CASE_,      features=SCREAMING_SNAKE_CASE_,      cache_dir=SCREAMING_SNAKE_CASE_,      keep_in_memory=SCREAMING_SNAKE_CASE_,      streaming=SCREAMING_SNAKE_CASE_,      **SCREAMING_SNAKE_CASE_,      )
          UpperCamelCase   :  Any						     =     load_from_cache_file
          UpperCamelCase   :  Any						     =     file_format
          UpperCamelCase   :  str						     =     Spark(
              df=SCREAMING_SNAKE_CASE_,      features=SCREAMING_SNAKE_CASE_,      cache_dir=SCREAMING_SNAKE_CASE_,      working_dir=SCREAMING_SNAKE_CASE_,      **SCREAMING_SNAKE_CASE_,      )






       def  snake_case_	(      self	)					->		Tuple:
          if self.streaming:
             return self.builder.as_streaming_dataset(split=self.split	)
          UpperCamelCase   :  Dict						     =     None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
          self.builder.download_and_prepare(
              download_mode=SCREAMING_SNAKE_CASE_,      file_format=self._file_format,      )
          return self.builder.as_dataset(split=self.split	)



