

"""simple docstring"""




class   __lowercase      (     __lowerCamelCase       ):
  pass







class   __lowercase      (     __lowerCamelCase       ):
  pass







class   __lowercase      :

  def __init__(	self		:      Union[str, Any]     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Union[str, Any]        =       [
       [],
       [],
       [],
   ]

  def  __lowercase							(	self		:      Optional[Any]       ,A		:      int       ,A		:      int     ):






   '''simple docstring'''
   try:
    if len(self.queues[priority]     ) >= 100:
     raise OverflowError("""Maximum queue size is 100"""     )
    self.queues[priority].append(A     )
   except IndexError:
    raise ValueError("""Valid priorities are 0, 1, and 2"""     )

  def  __lowercase							(	self		:      Optional[Any]     ):






   '''simple docstring'''
   for queue in self.queues:
    if queue:
     return queue.pop(0     )
   raise UnderFlowError("""All queues are empty"""     )




  def __str__(	self		:      Union[str, Any]     ):






   '''simple docstring'''
   return "\n".join(f"Priority {i}: {q}" for i, q in enumerate(self.queues     )     )







class   __lowercase      :

  def __init__(	self		:      List[str]     ):






   '''simple docstring'''
   UpperCAmelCase__       :	Optional[int]        =       []

  def  __lowercase							(	self		:      Optional[Any]       ,A		:      int     ):






   '''simple docstring'''
   if len(self.queue     ) == 100:
    raise OverFlowError("""Maximum queue size is 100"""     )
   self.queue.append(A     )

  def  __lowercase							(	self		:      Tuple     ):






   '''simple docstring'''
   if not self.queue:
    raise UnderFlowError("""The queue is empty"""     )
   else:
    UpperCAmelCase__       :	List[Any]        =       min(self.queue     )
    self.queue.remove(A     )
    return data




  def __str__(	self		:      Dict     ):






   '''simple docstring'''
   return str(self.queue     )







def 	lowerCAmelCase    (       ):
 '''simple docstring'''





 UpperCAmelCase__       :	List[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(__UpperCamelCase   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(__UpperCamelCase   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
 print(fpq.dequeue()   )
def 	lowerCAmelCase    (       ):
 '''simple docstring'''





 UpperCAmelCase__       :	List[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(__UpperCamelCase   )
 print(epq.dequeue()   )
 print(epq.dequeue()   )
 print(epq.dequeue()   )
 print(epq.dequeue()   )
 print(epq.dequeue()   )
 print(__UpperCamelCase   )
 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


__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"""]						)						)
