"""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


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 			__UpperCAmelCase    (	lowercase=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=__snake_case      )      )
class 				a (						__snake_case      ):
    _snake_case   :     Dict   							=							None
    _snake_case   :     Union[str, Any]   							=							None


    def    lowerCAmelCase_     (    self		:     Dict      , __lowerCAmelCase		:     Union[str, Any]      , __lowerCAmelCase		:     str    ):
      with TemporaryDirectory() as tmp_dir:
        _UpperCAmelCase         =					dataset_module_factory(__lowerCAmelCase      , cache_dir=__lowerCAmelCase    )

        _UpperCAmelCase         =					import_main_class(dataset_module.module_path      , dataset=__lowerCAmelCase    )

        _UpperCAmelCase         =					builder_cls(
            cache_dir=__lowerCAmelCase      , config_name=__lowerCAmelCase      , hash=dataset_module.hash      , )

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






@pytest.mark.integration
def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					tmp_path_factory.mktemp("""test_hf_gcp"""						) / 'test_wikipedia_simple'
  _UpperCAmelCase         =					dataset_module_factory("""wikipedia"""      ,cache_dir=SCREAMING_SNAKE_CASE_						)
  _UpperCAmelCase         =					import_main_class(dataset_module.module_path						)
  _UpperCAmelCase         =					builder_cls(
      cache_dir=SCREAMING_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
  _UpperCAmelCase         =					None
  builder_instance.download_and_prepare()
  _UpperCAmelCase         =					builder_instance.as_dataset()
  assert ds






@pytest.mark.integration
def 			__UpperCAmelCase    (	lowercase						):







  """simple docstring"""
  _UpperCAmelCase         =					dataset_module_factory("""wikipedia"""      ,cache_dir=SCREAMING_SNAKE_CASE_						)
  _UpperCAmelCase         =					import_main_class(dataset_module.module_path      ,dataset=SCREAMING_SNAKE_CASE_						)
  _UpperCAmelCase         =					builder_cls(
      cache_dir=SCREAMING_SNAKE_CASE_      ,config_name="""20220301.frr"""      ,hash=dataset_module.hash      ,)
  _UpperCAmelCase         =					builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_						)
  assert "train" in ds
  assert isinstance(ds["""train"""]      ,SCREAMING_SNAKE_CASE_						)
  assert next(iter(ds["""train"""]						)						)



def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str	,     SCREAMING_SNAKE_CASE_		:    str			):



     '''simple docstring'''





     if len(SCREAMING_SNAKE_CASE_			) != len(SCREAMING_SNAKE_CASE_			):
          raise ValueError('String lengths must match!'			)

     lowercase__    :   Union[str, Any]      =       0

     for chara, chara in zip(SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_			):
          if chara != chara:
               count += 1

     return count


if __name__ == "__main__":
       import doctest

       doctest.testmod()

