



'''simple docstring'''





__a  			=						{str(digit): digit**5 for digit in range(10)}





def 		__snake_case(							_lowerCAmelCase						)						->					int:
      return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCAmelCase						)						)





def 		__snake_case(							)						->					int:
      return sum(
          number
          for number in range(1_000	,  1_000_000						)
          if number == digits_fifth_powers_sum(_lowerCAmelCase						)						)


if __name__ == "__main__":
       print(solution())





'''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  			=						[
    {"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(							_lowerCAmelCase=True						)						->					Dict:
      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      ):
    """simple docstring"""







    lowercase   =						None
    lowercase   =						None




    def lowerCamelCase			(       self   :	List[Any]					,	snake_case_   :	Union[str, Any]					,	snake_case_   :	Optional[int]		):
          with TemporaryDirectory() as tmp_dir:
                snake_case__    :       Dict       		= dataset_module_factory(snake_case_					,	cache_dir=snake_case_		)

                snake_case__    :       Optional[int]       		= import_main_class(dataset_module.module_path					,	dataset=snake_case_		)

                snake_case__    :       DatasetBuilder       		= builder_cls(
                    cache_dir=snake_case_					,	config_name=snake_case_					,	hash=dataset_module.hash					,	)

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





@pytest.mark.integration
def 		__snake_case(							_lowerCAmelCase						)						->					Tuple:
      snake_case__    :       Optional[int]       		= tmp_path_factory.mktemp("""test_hf_gcp"""						) / """test_wikipedia_simple"""
      snake_case__    :       Dict       		= dataset_module_factory("""wikipedia"""	,  cache_dir=_lowerCAmelCase						)
      snake_case__    :       Dict       		= import_main_class(dataset_module.module_path						)
      snake_case__    :       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
      snake_case__    :       Any       		= None
      builder_instance.download_and_prepare()
      snake_case__    :       Union[str, Any]       		= builder_instance.as_dataset()
      assert ds





@pytest.mark.integration
def 		__snake_case(							_lowerCAmelCase						)						->					List[str]:
      snake_case__    :       Optional[int]       		= dataset_module_factory("""wikipedia"""	,  cache_dir=_lowerCAmelCase						)
      snake_case__    :       List[str]       		= import_main_class(dataset_module.module_path	,  dataset=_lowerCAmelCase						)
      snake_case__    :       DatasetBuilder       		= builder_cls(
          cache_dir=_lowerCAmelCase	,  config_name="""20220301.frr"""	,  hash=dataset_module.hash	,  )
      snake_case__    :       Any       		= 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"""]						)						)
