

'''simple docstring'''







class    A__ ( _snake_case     ):
    pass


class    A__ ( _snake_case     ):
    pass


class    A__ :



    def __init__(   self    )  -> Any:





           '''simple docstring'''
           A_		   = [
               [],
               [],
               [],
           ]



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__    )  -> None:





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



    def    snake_case_     (   self    )  -> int:





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







    def __str__(   self    )  -> str:





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


class    A__ :



    def __init__(   self    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = []



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> None:





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



    def    snake_case_     (   self    )  -> int:





           '''simple docstring'''
           if not self.queue:
                  raise UnderFlowError("""The queue is empty"""    )
           else:
                  A_		   = min(self.queue    )
                  self.queue.remove(UpperCamelCase__    )
                  return data







    def __str__(   self    )  -> str:





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

def  UpperCAmelCase__      ( )     ->     Tuple:
       A_		   = 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  UpperCAmelCase__      ( )     ->     Tuple:
       A_		   = 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 multiprocessing
from typing import TYPE_CHECKING, Optional, Union

from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream


if TYPE_CHECKING:
      import sqlitea

      import sqlalchemy


class    A__ ( _snake_case     ):



    def __init__(   self						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__ = None						,			UpperCamelCase__ = None						,			UpperCamelCase__ = False						,			**UpperCamelCase__						,			)  -> Optional[Any]:





           '''simple docstring'''
           super().__init__(features=UpperCamelCase__						,			cache_dir=UpperCamelCase__						,			keep_in_memory=UpperCamelCase__						,			**UpperCamelCase__    )
           A_		   = Sql(
               cache_dir=UpperCamelCase__						,			features=UpperCamelCase__						,			sql=UpperCamelCase__						,			con=UpperCamelCase__						,			**UpperCamelCase__						,			)







    def    snake_case_     (   self    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = None
           A_		   = None
           A_		   = None
           A_		   = None

           self.builder.download_and_prepare(
               download_config=UpperCamelCase__						,			download_mode=UpperCamelCase__						,			verification_mode=UpperCamelCase__						,			base_path=UpperCamelCase__						,			)

           # Build dataset for splits
           A_		   = self.builder.as_dataset(
               split="""train"""						,			verification_mode=UpperCamelCase__						,			in_memory=self.keep_in_memory    )
           return dataset


class    A__ :



    def __init__(   self						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__ = None						,			UpperCamelCase__ = None						,			**UpperCamelCase__						,			)  -> List[Any]:





           '''simple docstring'''
           if num_proc is not None and num_proc <= 0:
                  raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''    )

           A_		   = dataset
           A_		   = name
           A_		   = con
           A_		   = batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           A_		   = num_proc
           A_		   = to_sql_kwargs



    def    snake_case_     (   self    )  -> int:





           '''simple docstring'''
           A_		   = self.to_sql_kwargs.pop("""sql"""						,			UpperCamelCase__    )
           A_		   = self.to_sql_kwargs.pop("""con"""						,			UpperCamelCase__    )
           A_		   = self.to_sql_kwargs.pop("""index"""						,			UpperCamelCase__    )

           A_		   = self._write(index=UpperCamelCase__						,			**self.to_sql_kwargs    )
           return written



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> Union[str, Any]:





           '''simple docstring'''
           A_   ,     A_   ,     A_		   = args
           A_		   = {**to_sql_kwargs, """if_exists""": """append"""} if offset > 0 else to_sql_kwargs
           A_		   = query_table(
               table=self.dataset.data						,			key=slice(UpperCamelCase__						,			offset + self.batch_size    )						,			indices=self.dataset._indices						,			)
           A_		   = batch.to_pandas()
           A_		   = df.to_sql(self.name						,			self.con						,			index=UpperCamelCase__						,			**UpperCamelCase__    )
           return num_rows or len(UpperCamelCase__    )







    def    snake_case_     (   self						,			UpperCamelCase__						,			**UpperCamelCase__    )  -> int:





           '''simple docstring'''
           A_		   = 0

           if self.num_proc is None or self.num_proc == 1:
                  for offset in logging.tqdm(
                      range(0						,			len(self.dataset    )						,			self.batch_size    )						,			unit="""ba"""						,			disable=not logging.is_progress_bar_enabled()						,			desc="""Creating SQL from Arrow format"""						,			):
                         written += self._batch_sql((offset, index, to_sql_kwargs)    )
           else:
                  A_   ,     A_		   = len(self.dataset    ), self.batch_size
                  with multiprocessing.Pool(self.num_proc    ) as pool:
                         for num_rows in logging.tqdm(
                             pool.imap(
                                 self._batch_sql						,			[(offset, index, to_sql_kwargs) for offset in range(0						,			UpperCamelCase__						,			UpperCamelCase__    )]						,			)						,			total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size						,			unit="""ba"""						,			disable=not logging.is_progress_bar_enabled()						,			desc="""Creating SQL from Arrow format"""						,			):
                                written += num_rows

           return written
