




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 		_A(       UpperCamelCase__							:			List[Any]=True				)    -> Union[str, Any]:
							'''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 a (     UpperCAmelCase_  ):
						"""simple docstring"""

						UpperCamelCase_	:       List[str]       	=		None
						UpperCamelCase_	:       List[str]       	=		None






						def     UpperCAmelCase_      ( self :     Dict				,							lowerCamelCase__ :     Optional[Any]				,							lowerCamelCase__ :     Optional[Any]				)    ->						Optional[int]:
													"""simple docstring"""


													with TemporaryDirectory() as tmp_dir:
																				__lowercase      =    dataset_module_factory(_lowercase				,							cache_dir=_lowercase				)

																				__lowercase      =    import_main_class(dataset_module.module_path				,							dataset=_lowercase				)

																				__lowercase      =    builder_cls(
																				    cache_dir=_lowercase				,							config_name=_lowercase				,							hash=dataset_module.hash				,							)

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







@pytest.mark.integration
def 		_A(       UpperCamelCase__							:			Dict				)    -> Dict:
							'''simple docstring'''


							__lowercase      =    tmp_path_factory.mktemp('''test_hf_gcp'''				) / '''test_wikipedia_simple'''
							__lowercase      =    dataset_module_factory('''wikipedia'''				,       cache_dir=UpperCamelCase__				)
							__lowercase      =    import_main_class(dataset_module.module_path				)
							__lowercase      =    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
							__lowercase      =    None
							builder_instance.download_and_prepare()
							__lowercase      =    builder_instance.as_dataset()
							assert ds







@pytest.mark.integration
def 		_A(       UpperCamelCase__							:			Dict				)    -> Tuple:
							'''simple docstring'''


							__lowercase      =    dataset_module_factory('''wikipedia'''				,       cache_dir=UpperCamelCase__				)
							__lowercase      =    import_main_class(dataset_module.module_path				,       dataset=UpperCamelCase__				)
							__lowercase      =    builder_cls(
							    cache_dir=UpperCamelCase__				,       config_name='''20220301.frr'''				,       hash=dataset_module.hash				,       )
							__lowercase      =    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 __future__ import annotations







def 		_A(       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			int				)    -> tuple[float, list[float]]:
							'''simple docstring'''


							__lowercase      =    list(range(len(UpperCamelCase__				)				)				)
							__lowercase      =    [v / w for v, w in zip(UpperCamelCase__				,       UpperCamelCase__				)]
							index.sort(key=lambda UpperCamelCase__				: ratio[i]				,       reverse=UpperCamelCase__				)

							__lowercase      =    0
							__lowercase      =    [0] * len(UpperCamelCase__				)
							for i in index:
														if weight[i] <= capacity:
																					__lowercase      =    1
																					max_value += value[i]
																					capacity -= weight[i]
														else:
																					__lowercase      =    capacity / weight[i]
																					max_value += value[i] * capacity / weight[i]
																					break

							return max_value, fractions


if __name__ == "__main__":
			import doctest

			doctest.testmod()






