
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


_lowercase											=    [
    {"""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_	(					UpperCAmelCase_	:     int=True				)			->						Union[str, 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=A       )       )
class 			lowercase_		(      A       ):
       __lowerCamelCase				       =						None
       __lowerCamelCase				       =						None


       def 	_snake_case				(    self						,       __A						,       __A				)						->    Optional[Any]:
              with TemporaryDirectory() as tmp_dir:
                     SCREAMING_SNAKE_CASE_							:				str		=dataset_module_factory(__A						,       cache_dir=__A				)

                     SCREAMING_SNAKE_CASE_							:				Optional[Any]		=import_main_class(dataset_module.module_path						,       dataset=__A				)

                     SCREAMING_SNAKE_CASE_							:				DatasetBuilder		=builder_cls(
                         cache_dir=__A						,       config_name=__A						,       hash=dataset_module.hash						,       )

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






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

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


from math import isqrt, loga
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     int				)			->						list[int]:
       SCREAMING_SNAKE_CASE_							:				int		=[True] * max_number
       for i in range(2			,							isqrt(max_number - 1				) + 1				):
              if is_prime[i]:
                     for j in range(i**2			,							UpperCAmelCase_			,							UpperCAmelCase_				):
                            SCREAMING_SNAKE_CASE_							:				Dict		=False

       return [i for i in range(2			,							UpperCAmelCase_				) if is_prime[i]]
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     int = 8_0_0_8_0_0			,							UpperCAmelCase_	:     int = 8_0_0_8_0_0				)			->						int:
       SCREAMING_SNAKE_CASE_							:				str		=degree * loga(UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				List[Any]		=int(UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				int		=calculate_prime_numbers(UpperCAmelCase_				)

       SCREAMING_SNAKE_CASE_							:				int		=0
       SCREAMING_SNAKE_CASE_							:				List[Any]		=0
       SCREAMING_SNAKE_CASE_							:				Any		=len(UpperCAmelCase_				) - 1
       while left < right:
              while (
                  prime_numbers[right] * loga(prime_numbers[left]				)
                  + prime_numbers[left] * loga(prime_numbers[right]				)
                  > upper_bound
              ):
                     right -= 1
              hybrid_integers_count += right - left
              left += 1

       return hybrid_integers_count


if __name__ == "__main__":
 print(F"{solution() = }")
