






"""simple docstring"""

from __future__ import annotations


class 						__lowerCamelCase							:





		'''simple docstring'''






		def __init__(  self				:      str		,     a_				:      str		,     a_				:      str      ):
				lowerCAmelCase_							,      lowerCAmelCase_  :				Union[str, Any]   							=     text, pattern
				lowerCAmelCase_							,      lowerCAmelCase_  :				Optional[Any]   							=     len(SCREAMING_SNAKE_CASE_      ), len(SCREAMING_SNAKE_CASE_      )





		def   lowerCamelCase			(  self				:      Union[str, Any]		,     a_				:      str      ):

				for i in range(self.patLen - 1		,     -1		,     -1      ):
						if char == self.pattern[i]:
								return i
				return -1





		def   lowerCamelCase			(  self				:      str		,     a_				:      int      ):

				for i in range(self.patLen - 1		,     -1		,     -1      ):
						if self.pattern[i] != self.text[current_pos + i]:
								return current_pos + i
				return -1





		def   lowerCamelCase			(  self				:      Optional[int]      ):
				# searches pattern in text and returns index positions
				lowerCAmelCase_  :				str   							=     []
				for i in range(self.textLen - self.patLen + 1      ):
						lowerCAmelCase_  :				List[Any]   							=     self.mismatch_in_text(SCREAMING_SNAKE_CASE_      )
						if mismatch_index == -1:
								positions.append(SCREAMING_SNAKE_CASE_      )
						else:
								lowerCAmelCase_  :				Tuple   							=     self.match_in_pattern(self.text[mismatch_index]      )
								lowerCAmelCase_  :				Union[str, Any]   							=     (
								    mismatch_index - match_index
								)  # shifting index lgtm [py/multiple-definition]
				return positions







lowercase__  			=					"""ABAABA"""
lowercase__  			=					"""AB"""
lowercase__  			=					BoyerMooreSearch(text, pattern)
lowercase__  			=					bms.bad_character_heuristic()

if len(positions) == 0:
					print("""No match found""")
else:
					print("""Pattern found in following positions: """)
					print(positions)


import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset




@pytest.mark.parametrize('''dataset_size'''		,  [None, 400 * 2**20, 600 * 2**20]   )
@pytest.mark.parametrize('''input_in_memory_max_size'''		,  ['''default''', 0, 100 * 2**20, 900 * 2**20]   )
def 							a		(				snake_case__:   int		,  snake_case__:   Dict		,  snake_case__:   Dict   ):


				'''simple docstring'''
				if input_in_memory_max_size != "default":
								monkeypatch.setattr(datasets.config		,  '''IN_MEMORY_MAX_SIZE'''		,  snake_case__   )
				lowercase_	    =   datasets.config.IN_MEMORY_MAX_SIZE
				if input_in_memory_max_size == "default":
								assert in_memory_max_size == 0
				else:
								assert in_memory_max_size == input_in_memory_max_size
				if dataset_size and in_memory_max_size:
								lowercase_	    =   dataset_size < in_memory_max_size
				else:
								lowercase_	    =   False
				lowercase_	    =   is_small_dataset(snake_case__   )
				assert result == expected




