






"""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


__A		:       Union[str, Any]  				=		[
    {'''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 						lowercase    (				__snake_case				: Union[str, Any]=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=_A							)							)
class 					_UpperCAmelCase       ( _A							):
					SCREAMING_SNAKE_CASE_		:				int							    =   None
					SCREAMING_SNAKE_CASE_		:				Optional[Any]							    =   None




					def   A  (				self     :						List[Any]    ,						A     :						int    ,						A     :						Tuple   )  ->  Tuple:
							with TemporaryDirectory() as tmp_dir:
									lowercase_ : List[Any]							       =   dataset_module_factory(A    ,						cache_dir=A   )

									lowercase_ : Optional[Any]							       =   import_main_class(dataset_module.module_path    ,						dataset=A   )

									lowercase_ : DatasetBuilder							       =   builder_cls(
									    cache_dir=A    ,						config_name=A    ,						hash=dataset_module.hash    ,						)

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



@pytest.mark.integration
def 						lowercase    (				__snake_case				: int	):
		lowercase_ : int							       =   tmp_path_factory.mktemp('''test_hf_gcp'''	) / '''test_wikipedia_simple'''
		lowercase_ : str							       =   dataset_module_factory('''wikipedia'''		,					cache_dir=__snake_case	)
		lowercase_ : List[str]							       =   import_main_class(dataset_module.module_path	)
		lowercase_ : DatasetBuilder							       =   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
		lowercase_ : List[Any]							       =   None
		builder_instance.download_and_prepare()
		lowercase_ : Union[str, Any]							       =   builder_instance.as_dataset()
		assert ds






@pytest.mark.integration
def 						lowercase    (				__snake_case				: List[str]	):
		lowercase_ : Optional[Any]							       =   dataset_module_factory('''wikipedia'''		,					cache_dir=__snake_case	)
		lowercase_ : List[str]							       =   import_main_class(dataset_module.module_path		,					dataset=__snake_case	)
		lowercase_ : DatasetBuilder							       =   builder_cls(
		    cache_dir=__snake_case		,					config_name='''20220301.frr'''		,					hash=dataset_module.hash		,					)
		lowercase_ : str							       =   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 typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader

class     _A       (	__UpperCAmelCase    ):



       def __init__(		self							:     Optional[int]     ,		__SCREAMING_SNAKE_CASE							:     NestedDataStructureLike[PathLike]     ,		__SCREAMING_SNAKE_CASE							:     Optional[NamedSplit] = None     ,		__SCREAMING_SNAKE_CASE							:     Optional[Features] = None     ,		__SCREAMING_SNAKE_CASE							:     str = None     ,		__SCREAMING_SNAKE_CASE							:     bool = False     ,		__SCREAMING_SNAKE_CASE							:     bool = False     ,		__SCREAMING_SNAKE_CASE							:     Optional[int] = None     ,		**__SCREAMING_SNAKE_CASE							:     List[str]     ,		):


           '''simple docstring'''

           super().__init__(
               __SCREAMING_SNAKE_CASE     ,		split=__SCREAMING_SNAKE_CASE     ,		features=__SCREAMING_SNAKE_CASE     ,		cache_dir=__SCREAMING_SNAKE_CASE     ,		keep_in_memory=__SCREAMING_SNAKE_CASE     ,		streaming=__SCREAMING_SNAKE_CASE     ,		num_proc=__SCREAMING_SNAKE_CASE     ,		**__SCREAMING_SNAKE_CASE     ,		)
           __a						       =				path_or_paths if isinstance(__SCREAMING_SNAKE_CASE     ,		__SCREAMING_SNAKE_CASE) else {self.split: path_or_paths}
           __a						       =				Text(
               cache_dir=__SCREAMING_SNAKE_CASE     ,		data_files=__SCREAMING_SNAKE_CASE     ,		features=__SCREAMING_SNAKE_CASE     ,		**__SCREAMING_SNAKE_CASE     ,		)





       def 		_lowerCamelCase			(		self							:     List[str]):


           '''simple docstring'''

           if self.streaming:
               __a						       =				self.builder.as_streaming_dataset(split=self.split)
           # Build regular (map-style) dataset
           else:
               __a						       =				None
               __a						       =				None
               __a						       =				None
               __a						       =				None

               self.builder.download_and_prepare(
                   download_config=__SCREAMING_SNAKE_CASE     ,		download_mode=__SCREAMING_SNAKE_CASE     ,		verification_mode=__SCREAMING_SNAKE_CASE     ,		base_path=__SCREAMING_SNAKE_CASE     ,		num_proc=self.num_proc     ,		)
               __a						       =				self.builder.as_dataset(
                   split=self.split     ,		verification_mode=__SCREAMING_SNAKE_CASE     ,		in_memory=self.keep_in_memory)
           return dataset





