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


SCREAMING_SNAKE_CASE__		:					List[str]						=					[
    {"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     _a				(      lowercase__  :			Dict=True ):







					'''simple docstring'''


					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=UpperCAmelCase_						)						)
class       snake_case					(      UpperCAmelCase_						):
		lowercase_			=     None
		lowercase_			=     None




		def 	__lowercase(      self     :	Dict     , a_     :	Optional[Any]     , a_     :	Optional[Any]				)->       List[Any]:




							"""simple docstring"""
							with TemporaryDirectory() as tmp_dir:
												SCREAMING_SNAKE_CASE__				:				List[Any]			=		dataset_module_factory(_lowercase     , cache_dir=_lowercase				)

												SCREAMING_SNAKE_CASE__				:				Dict			=		import_main_class(dataset_module.module_path     , dataset=_lowercase				)

												SCREAMING_SNAKE_CASE__				:				Dict			=		builder_cls(
												    cache_dir=_lowercase     , config_name=_lowercase     , hash=dataset_module.hash     , )

												SCREAMING_SNAKE_CASE__				:				List[str]			=		'/'.join(
												    [
												        HF_GCP_BASE_URL,
												        builder_instance._relative_data_dir(with_hash=_lowercase				).replace(os.sep     , '/'				),
												        config.DATASET_INFO_FILENAME,
												    ]				)
												SCREAMING_SNAKE_CASE__				:				int			=		cached_path(_lowercase     , cache_dir=_lowercase				)
												self.assertTrue(os.path.exists(_lowercase				)				)







@pytest.mark.integration
def     _a				(      lowercase__  :			str ):







					'''simple docstring'''


					SCREAMING_SNAKE_CASE__				:				int			=		tmp_path_factory.mktemp('test_hf_gcp' ) / 'test_wikipedia_simple'
					SCREAMING_SNAKE_CASE__				:				List[str]			=		dataset_module_factory('wikipedia'     ,  cache_dir=UpperCamelCase__ )
					SCREAMING_SNAKE_CASE__				:				Tuple			=		import_main_class(dataset_module.module_path )
					SCREAMING_SNAKE_CASE__				:				List[str]			=		builder_cls(
					    cache_dir=UpperCamelCase__     ,  config_name='20220301.frr'     ,  hash=dataset_module.hash     ,  )
					# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
					SCREAMING_SNAKE_CASE__				:				List[Any]			=		None
					builder_instance.download_and_prepare()
					SCREAMING_SNAKE_CASE__				:				Optional[int]			=		builder_instance.as_dataset()
					assert ds







@pytest.mark.integration
def     _a				(      lowercase__  :			str ):







					'''simple docstring'''


					SCREAMING_SNAKE_CASE__				:				Tuple			=		dataset_module_factory('wikipedia'     ,  cache_dir=UpperCamelCase__ )
					SCREAMING_SNAKE_CASE__				:				Optional[int]			=		import_main_class(dataset_module.module_path     ,  dataset=UpperCamelCase__ )
					SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		builder_cls(
					    cache_dir=UpperCamelCase__     ,  config_name='20220301.frr'     ,  hash=dataset_module.hash     ,  )
					SCREAMING_SNAKE_CASE__				:				str			=		builder_instance.as_streaming_dataset()
					assert ds
					assert isinstance(UpperCamelCase__     ,  UpperCamelCase__ )
					assert "train" in ds
					assert isinstance(ds['train']     ,  UpperCamelCase__ )
					assert next(iter(ds['train'] ) )




def     _a				(      lowercase__  :			int     ,  lowercase__  :			int ):







     '''simple docstring'''


     return int((input_a, input_a).count(0 ) != 0 )







def     _a				(      ):







     '''simple docstring'''


     assert nand_gate(0     ,  0 ) == 1
     assert nand_gate(0     ,  1 ) == 1
     assert nand_gate(1     ,  0 ) == 1
     assert nand_gate(1     ,  1 ) == 0


if __name__ == "__main__":
      print(nand_gate(0, 0))
      print(nand_gate(0, 1))
      print(nand_gate(1, 0))
      print(nand_gate(1, 1))



