

"""simple docstring"""





class   UpperCAmelCase_			(					__SCREAMING_SNAKE_CASE):
      pass





class   UpperCAmelCase_			(					__SCREAMING_SNAKE_CASE):
      pass





class   UpperCAmelCase_			:


      def __init__(     self							) ->      Tuple:
             lowercase__    :	List[Any]     					=			[
                 [],
                 [],
                 [],
             ]


      def 	_UpperCAmelCase (     self	,    a	,    a							) ->      Dict:
             try:
                    if len(self.queues[priority]							) >= 1_0_0:
                           raise OverflowError('Maximum queue size is 100'							)
                    self.queues[priority].append(_a							)
             except IndexError:
                    raise ValueError('Valid priorities are 0, 1, and 2'							)


      def 	_UpperCAmelCase (     self							) ->      str:
             for queue in self.queues:
                    if queue:
                           return queue.pop(0							)
             raise UnderFlowError('All queues are empty'							)


      def __str__(     self							) ->      str:
             return "\n".join(f"""Priority {i}: {q}""" for i, q in enumerate(self.queues							)							)





class   UpperCAmelCase_			:


      def __init__(     self							) ->      Tuple:
             lowercase__    :	Union[str, Any]     					=			[]


      def 	_UpperCAmelCase (     self	,    a							) ->      Union[str, Any]:
             if len(self.queue							) == 1_0_0:
                    raise OverFlowError('Maximum queue size is 100'							)
             self.queue.append(_a							)


      def 	_UpperCAmelCase (     self							) ->      Any:
             if not self.queue:
                    raise UnderFlowError('The queue is empty'							)
             else:
                    lowercase__    :	List[Any]     					=			min(self.queue							)
                    self.queue.remove(_a							)
                    return data


      def __str__(     self							) ->      Dict:
             return str(self.queue							)





def        a_  (   ):





       '''simple docstring'''

       lowercase__    :	Any     					=			FixedPriorityQueue()
       fpq.enqueue(0     ,				10  )
       fpq.enqueue(1     ,				70  )
       fpq.enqueue(0     ,				100  )
       fpq.enqueue(2     ,				1  )
       fpq.enqueue(2     ,				5  )
       fpq.enqueue(1     ,				7  )
       fpq.enqueue(2     ,				4  )
       fpq.enqueue(1     ,				64  )
       fpq.enqueue(0     ,				128  )
       print(lowerCAmelCase__  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(lowerCAmelCase__  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )
       print(fpq.dequeue()  )





def        a_  (   ):





       '''simple docstring'''

       lowercase__    :	str     					=			ElementPriorityQueue()
       epq.enqueue(10  )
       epq.enqueue(70  )
       epq.enqueue(100  )
       epq.enqueue(1  )
       epq.enqueue(5  )
       epq.enqueue(7  )
       epq.enqueue(4  )
       epq.enqueue(64  )
       epq.enqueue(128  )
       print(lowerCAmelCase__  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(lowerCAmelCase__  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )
       print(epq.dequeue()  )


if __name__ == "__main__":
       fixed_priority_queue()
       element_priority_queue()


"""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     :		Any											=					[
    {"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_  (   _lowerCAmelCase						:				Optional[Any]=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=_a))
class   UpperCAmelCase_			(					_a):
      lowerCamelCase__	:					str										=						None
      lowerCamelCase__	:					Optional[Any]										=						None


      def 	_UpperCAmelCase (     self	,    a	,    a							) ->      List[Any]:
             with TemporaryDirectory() as tmp_dir:
                    lowercase__    :	List[str]     					=			dataset_module_factory(a	,    cache_dir=a							)

                    lowercase__    :	List[Any]     					=			import_main_class(dataset_module.module_path	,    dataset=a							)

                    lowercase__    :	DatasetBuilder     					=			builder_cls(
                        cache_dir=a	,    config_name=a	,    hash=dataset_module.hash	,    )

                    lowercase__    :	Union[str, Any]     					=			'/'.join(
                        [
                            HF_GCP_BASE_URL,
                            builder_instance._relative_data_dir(with_hash=a							).replace(os.sep	,    '/'							),
                            config.DATASET_INFO_FILENAME,
                        ]							)
                    lowercase__    :	Union[str, Any]     					=			cached_path(a	,    cache_dir=a							)
                    self.assertTrue(os.path.exists(a							)							)





@pytest.mark.integration
def        a_  (   _lowerCAmelCase						:				str  ):





       '''simple docstring'''

       lowercase__    :	Union[str, Any]     					=			tmp_path_factory.mktemp('test_hf_gcp'  ) / 'test_wikipedia_simple'
       lowercase__    :	int     					=			dataset_module_factory('wikipedia'     ,				cache_dir=_lowerCAmelCase  )
       lowercase__    :	Optional[int]     					=			import_main_class(dataset_module.module_path  )
       lowercase__    :	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
       lowercase__    :	Optional[int]     					=			None
       builder_instance.download_and_prepare()
       lowercase__    :	Optional[int]     					=			builder_instance.as_dataset()
       assert ds






@pytest.mark.integration
def        a_  (   _lowerCAmelCase						:				Optional[Any]  ):





       '''simple docstring'''

       lowercase__    :	Optional[int]     					=			dataset_module_factory('wikipedia'     ,				cache_dir=_lowerCAmelCase  )
       lowercase__    :	List[str]     					=			import_main_class(dataset_module.module_path     ,				dataset=_lowerCAmelCase  )
       lowercase__    :	DatasetBuilder     					=			builder_cls(
           cache_dir=_lowerCAmelCase     ,				config_name='20220301.frr'     ,				hash=dataset_module.hash     ,				)
       lowercase__    :	Union[str, 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']  )  )

