





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


_UpperCAmelCase       =				[
    {'''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 			_SCREAMING_SNAKE_CASE						(     SCREAMING_SNAKE_CASE						:Union[str, Any]=True       )     ->       Any:
 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=lowerCamelCase__		)		)
class   snake_case_							(						lowerCamelCase__		):
  A_     				=       None
  A_     				=       None






  def  UpperCAmelCase__		(				self					:	int  ,    _snake_case					:	Optional[int]  ,    _snake_case					:	Tuple     )->List[str]:






   '''simple docstring'''

   with TemporaryDirectory() as tmp_dir:
    __lowerCAmelCase	:			int         =  dataset_module_factory(_snake_case  ,    cache_dir=_snake_case     )

    __lowerCAmelCase	:			str         =  import_main_class(dataset_module.module_path  ,    dataset=_snake_case     )

    __lowerCAmelCase	:			DatasetBuilder         =  builder_cls(
        cache_dir=_snake_case  ,    config_name=_snake_case  ,    hash=dataset_module.hash  ,    )

    __lowerCAmelCase	:			List[Any]         =  "/".join(
        [
            HF_GCP_BASE_URL,
            builder_instance._relative_data_dir(with_hash=_snake_case     ).replace(os.sep  ,    """/"""     ),
            config.DATASET_INFO_FILENAME,
        ]     )
    __lowerCAmelCase	:			Dict         =  cached_path(_snake_case  ,    cache_dir=_snake_case     )
    self.assertTrue(os.path.exists(_snake_case     )     )






@pytest.mark.integration
def 			_SCREAMING_SNAKE_CASE						(     SCREAMING_SNAKE_CASE						:Optional[Any]       )     ->       List[str]:
 __lowerCAmelCase	:			int         =  tmp_path_factory.mktemp("""test_hf_gcp"""       ) / "test_wikipedia_simple"
 __lowerCAmelCase	:			Optional[int]         =  dataset_module_factory("""wikipedia"""       ,       cache_dir=_lowerCAmelCase       )
 __lowerCAmelCase	:			Optional[Any]         =  import_main_class(dataset_module.module_path       )
 __lowerCAmelCase	:			DatasetBuilder         =  builder_cls(
     cache_dir=_lowerCAmelCase       ,       config_name="""20220301.frr"""       ,       hash=dataset_module.hash       ,       )
 # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
 __lowerCAmelCase	:			int         =  None
 builder_instance.download_and_prepare()
 __lowerCAmelCase	:			Tuple         =  builder_instance.as_dataset()
 assert ds







@pytest.mark.integration
def 			_SCREAMING_SNAKE_CASE						(     SCREAMING_SNAKE_CASE						:Union[str, Any]       )     ->       Union[str, Any]:
 __lowerCAmelCase	:			List[Any]         =  dataset_module_factory("""wikipedia"""       ,       cache_dir=_lowerCAmelCase       )
 __lowerCAmelCase	:			List[Any]         =  import_main_class(dataset_module.module_path       ,       dataset=_lowerCAmelCase       )
 __lowerCAmelCase	:			DatasetBuilder         =  builder_cls(
     cache_dir=_lowerCAmelCase       ,       config_name="""20220301.frr"""       ,       hash=dataset_module.hash       ,       )
 __lowerCAmelCase	:			Dict         =  builder_instance.as_streaming_dataset()
 assert ds
 assert isinstance(_lowerCAmelCase       ,       _lowerCAmelCase       )
 assert "train" in ds
 assert isinstance(ds["""train"""]       ,       _lowerCAmelCase       )
 assert next(iter(ds["""train"""]       )       )






def   __snake_case    (       _lowerCAmelCase			:			int = 1					,					_lowerCAmelCase			:			int = 1000						)			->    int:
   A_       :					Optional[int]        =      1
   A_       :					int        =      0

   for divide_by_number in range(_lowerCAmelCase					,					digit + 1						):
      A_       :					list[int]        =      []
      A_       :					Union[str, Any]        =      numerator
      for _ in range(1					,					digit + 1						):
         if now_divide in has_been_divided:
            if longest_list_length < len(_lowerCAmelCase						):
               A_       :					Optional[Any]        =      len(_lowerCAmelCase						)
               A_       :					Union[str, Any]        =      divide_by_number
         else:
            has_been_divided.append(_lowerCAmelCase						)
            A_       :					Dict        =      now_divide * 10 % divide_by_number

   return the_digit


# Tests
if __name__ == "__main__":
 import doctest

 doctest.testmod()
