
"""simple docstring"""


import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


_lowercase				 =					[
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.de'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.en'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.fr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.frr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.it'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.simple'''},
    {'''dataset''': '''snli''', '''config_name''': '''plain_text'''},
    {'''dataset''': '''eli5''', '''config_name''': '''LFQA_reddit'''},
    {'''dataset''': '''wiki40b''', '''config_name''': '''en'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.compressed'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.no_index'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.multiset.no_index'''},
    {'''dataset''': '''natural_questions''', '''config_name''': '''default'''},
]






def    _snake_case					(		snake_case__ :  str=True  ):
	if with_config:
		return [
		    {
		        "testcase_name": d["dataset"] + "/" + d["config_name"],
		        "dataset": d["dataset"],
		        "config_name": d["config_name"],
		    }
		    for d in DATASETS_ON_HF_GCP
		]
	else:
		return [
		    {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
		]







@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=_lowercase     )     )
class 					lowerCAmelCase_					(   _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     Optional[Any]   =     None
						_lowerCamelCase:     str   =     None


						def     _SCREAMING_SNAKE_CASE   (			self  :   Tuple	,A_  :   int	,A_  :   Tuple   )  -> Any:
							with TemporaryDirectory() as tmp_dir:
								A     = dataset_module_factory(A_	,cache_dir=A_   )

								A     = import_main_class(dataset_module.module_path	,dataset=A_   )

								A     = builder_cls(
								    cache_dir=A_	,config_name=A_	,hash=dataset_module.hash	,)

								A     = '/'.join(
								    [
								        HF_GCP_BASE_URL,
								        builder_instance._relative_data_dir(with_hash=A_   ).replace(os.sep	,'/'   ),
								        config.DATASET_INFO_FILENAME,
								    ]   )
								A     = cached_path(A_	,cache_dir=A_   )
								self.assertTrue(os.path.exists(A_   )   )






@pytest.mark.integration
def    _snake_case					(		snake_case__ :  Optional[int]  ):
	A     = tmp_path_factory.mktemp('test_hf_gcp'  ) / 'test_wikipedia_simple'
	A     = dataset_module_factory('wikipedia'						,   cache_dir=snake_case__  )
	A     = import_main_class(dataset_module.module_path  )
	A     = builder_cls(
	    cache_dir=snake_case__						,   config_name='20220301.frr'						,   hash=dataset_module.hash						,   )
	# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
	A     = None
	builder_instance.download_and_prepare()
	A     = builder_instance.as_dataset()
	assert ds






@pytest.mark.integration
def    _snake_case					(		snake_case__ :  List[Any]  ):
	A     = dataset_module_factory('wikipedia'						,   cache_dir=snake_case__  )
	A     = import_main_class(dataset_module.module_path						,   dataset=snake_case__  )
	A     = builder_cls(
	    cache_dir=snake_case__						,   config_name='20220301.frr'						,   hash=dataset_module.hash						,   )
	A     = builder_instance.as_streaming_dataset()
	assert ds
	assert isinstance(snake_case__						,   snake_case__  )
	assert "train" in ds
	assert isinstance(ds['train']						,   snake_case__  )
	assert next(iter(ds['train']  )  )



from __future__ import annotations






class      UpperCamelCase:


					def __init__(    self						:		Optional[int]  ,     SCREAMING_SNAKE_CASE						:		str  ,     SCREAMING_SNAKE_CASE						:		str    )      ->						str:




											'''simple docstring'''

											__snake_case		,       __snake_case				=		text, pattern
											__snake_case		,       __snake_case				=		len(SCREAMING_SNAKE_CASE    ), len(SCREAMING_SNAKE_CASE    )


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Optional[Any]  ,     SCREAMING_SNAKE_CASE						:		str    )      ->						int:




											'''simple docstring'''

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


					def 				SCREAMING_SNAKE_CASE_	(    self						:		int  ,     SCREAMING_SNAKE_CASE						:		int    )      ->						int:




											'''simple docstring'''

											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 				SCREAMING_SNAKE_CASE_	(    self						:		List[Any]    )      ->						list[int]:




											'''simple docstring'''

											__snake_case				=		[]
											for i in range(self.textLen - self.patLen + 1    ):
																	__snake_case				=		self.mismatch_in_text(SCREAMING_SNAKE_CASE    )
																	if mismatch_index == -1:
																							positions.append(SCREAMING_SNAKE_CASE    )
																	else:
																							__snake_case				=		self.match_in_pattern(self.text[mismatch_index]    )
																							__snake_case				=		(
																							    mismatch_index - match_index
																							)  # shifting index lgtm [py/multiple-definition]
											return positions




A				:       str      =  'ABAABA'
A				:       Optional[Any]      =  'AB'
A				:       Any      =  BoyerMooreSearch(text, pattern)
A				:       Tuple      =  bms.bad_character_heuristic()

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





