



_UpperCAmelCase	       =	256
# Modulus to hash a string
_UpperCAmelCase	       =	1_000_003
def 		UpperCamelCase     (       snake_case__	:   Tuple	,					snake_case__	:   Tuple     )     ->					Optional[Any]:
   UpperCamelCase   :  int						     =     len(_A     )
   UpperCamelCase   :  Union[str, Any]						     =     len(_A     )
   if p_len > t_len:
      return False

   UpperCamelCase   :  int						     =     0
   UpperCamelCase   :  Optional[Any]						     =     0
   UpperCamelCase   :  int						     =     1

   # Calculating the hash of pattern and substring of text
   for i in range(_A     ):
      UpperCamelCase   :  int						     =     (ord(pattern[i]     ) + p_hash * alphabet_size) % modulus
      UpperCamelCase   :  int						     =     (ord(text[i]     ) + text_hash * alphabet_size) % modulus
      if i == p_len - 1:
         continue
      UpperCamelCase   :  List[Any]						     =     (modulus_power * alphabet_size) % modulus

   for i in range(0	,					t_len - p_len + 1     ):
      if text_hash == p_hash and text[i : i + p_len] == pattern:
         return True
      if i == t_len - p_len:
         continue
      # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
      UpperCamelCase   :  Dict						     =     (
          (text_hash - ord(text[i]     ) * modulus_power) * alphabet_size
          + ord(text[i + p_len]     )
      ) % modulus
   return False
def 		UpperCamelCase     (       )     ->					List[str]:
   UpperCamelCase   :  str						     =     'abc1abc12'
   UpperCamelCase   :  Union[str, Any]						     =     'alskfjaldsabc1abc1abc12k23adsfabcabc'
   UpperCamelCase   :  Union[str, Any]						     =     'alskfjaldsk23adsfabcabc'
   assert rabin_karp(_A	,					_A     ) and not rabin_karp(_A	,					_A     )

   # Test 2)
   UpperCamelCase   :  Union[str, Any]						     =     'ABABX'
   UpperCamelCase   :  Any						     =     'ABABZABABYABABX'
   assert rabin_karp(_A	,					_A     )

   # Test 3)
   UpperCamelCase   :  List[Any]						     =     'AAAB'
   UpperCamelCase   :  int						     =     'ABAAAAAB'
   assert rabin_karp(_A	,					_A     )

   # Test 4)
   UpperCamelCase   :  Any						     =     'abcdabcy'
   UpperCamelCase   :  str						     =     'abcxabcdabxabcdabcdabcy'
   assert rabin_karp(_A	,					_A     )

   # Test 5)
   UpperCamelCase   :  Any						     =     'Lü'
   UpperCamelCase   :  List[str]						     =     'Lüsai'
   assert rabin_karp(_A	,					_A     )
   UpperCamelCase   :  int						     =     'Lue'
   assert not rabin_karp(_A	,					_A     )
   print('Success.'     )


if __name__ == "__main__":
    test_rabin_karp()








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	)



