code: 
  
  
  import multiprocessing
  import os
  from typing import BinaryIO, Optional, Union
  
  from .. import Dataset, Features, NamedSplit, config
  from ..formatting import query_table
  from ..packaged_modules.csv.csv import Csv
  from ..utils import logging
  from ..utils.typing import NestedDataStructureLike, PathLike
  from .abc import AbstractDatasetReader
  
  
  
  
  
  class 					snake_case__  ( __A       ):
  
  
  
  
  
  	def __init__(  self				,    UpperCamelCase_				,    UpperCamelCase_ = None				,    UpperCamelCase_ = None				,    UpperCamelCase_ = None				,    UpperCamelCase_ = False				,    UpperCamelCase_ = False				,    UpperCamelCase_ = None				,    **UpperCamelCase_				,    )		->			str:
  								"""simple docstring"""
  
  
  
  
  
  
  								super().__init__(
  								    UpperCamelCase_				,    split=UpperCamelCase_				,    features=UpperCamelCase_				,    cache_dir=UpperCamelCase_				,    keep_in_memory=UpperCamelCase_				,    streaming=UpperCamelCase_				,    num_proc=UpperCamelCase_				,    **UpperCamelCase_				,    )
  								a_       :   int			=	path_or_paths if isinstance(UpperCamelCase_				,    UpperCamelCase_							) else {self.split: path_or_paths}
  								a_       :   Dict			=	Csv(
  								    cache_dir=UpperCamelCase_				,    data_files=UpperCamelCase_				,    features=UpperCamelCase_				,    **UpperCamelCase_				,    )
  
  
  
  
  
  	def     A				(  self							)		->			Optional[Any]:
  								"""simple docstring"""
  
  
  
  
  
  
  								if self.streaming:
  															a_       :   Dict			=	self.builder.as_streaming_dataset(split=self.split							)
  								# Build regular (map-style) dataset
  								else:
  															a_       :   Optional[int]			=	None
  															a_       :   Optional[Any]			=	None
  															a_       :   List[str]			=	None
  															a_       :   Dict			=	None
  
  															self.builder.download_and_prepare(
  															    download_config=UpperCamelCase_				,    download_mode=UpperCamelCase_				,    verification_mode=UpperCamelCase_				,    base_path=UpperCamelCase_				,    num_proc=self.num_proc				,    )
  															a_       :   Optional[int]			=	self.builder.as_dataset(
  															    split=self.split				,    verification_mode=UpperCamelCase_				,    in_memory=self.keep_in_memory							)
  								return dataset
  
  
  
  
  
  class 					snake_case__  :
  
  
  
  
  
  	def __init__(  self				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_ = None				,    UpperCamelCase_ = None				,    **UpperCamelCase_				,    )		->			Optional[int]:
  								"""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_       :   int			=	dataset
  								a_       :   Dict			=	path_or_buf
  								a_       :   int			=	batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
  								a_       :   List[Any]			=	num_proc
  								a_       :   str			=	"""utf-8"""
  								a_       :   int			=	to_csv_kwargs
  
  
  
  
  
  	def     A				(  self							)		->			int:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   Dict			=	self.to_csv_kwargs.pop("""path_or_buf"""				,    UpperCamelCase_							)
  								a_       :   Dict			=	self.to_csv_kwargs.pop("""header"""				,    UpperCamelCase_							)
  								a_       :   int			=	self.to_csv_kwargs.pop("""index"""				,    UpperCamelCase_							)
  
  								if isinstance(self.path_or_buf				,    (str, bytes, os.PathLike)							):
  															with open(self.path_or_buf				,    """wb+"""							) as buffer:
  																						a_       :   Tuple			=	self._write(file_obj=UpperCamelCase_				,    header=UpperCamelCase_				,    index=UpperCamelCase_				,    **self.to_csv_kwargs							)
  								else:
  															a_       :   Optional[int]			=	self._write(file_obj=self.path_or_buf				,    header=UpperCamelCase_				,    index=UpperCamelCase_				,    **self.to_csv_kwargs							)
  								return written
  
  
  
  
  
  	def     A				(  self				,    UpperCamelCase_							)		->			Optional[Any]:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   int			=	args
  
  								a_       :   Union[str, Any]			=	query_table(
  								    table=self.dataset.data				,    key=slice(UpperCamelCase_				,    offset + self.batch_size							)				,    indices=self.dataset._indices				,    )
  								a_       :   str			=	batch.to_pandas().to_csv(
  								    path_or_buf=UpperCamelCase_				,    header=header if (offset == 0) else False				,    index=UpperCamelCase_				,    **UpperCamelCase_							)
  								return csv_str.encode(self.encoding							)
  
  
  
  
  
  	def     A				(  self				,    UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    **UpperCamelCase_							)		->			int:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   str			=	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 CSV from Arrow format"""				,    ):
  																						a_       :   List[Any]			=	self._batch_csv((offset, header, index, to_csv_kwargs)							)
  																						written += file_obj.write(UpperCamelCase_							)
  
  								else:
  															a_       :   Dict			=	len(self.dataset							), self.batch_size
  															with multiprocessing.Pool(self.num_proc							) as pool:
  																						for csv_str in logging.tqdm(
  																						    pool.imap(
  																						        self._batch_csv				,    [(offset, header, index, to_csv_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 CSV from Arrow format"""				,    ):
  																													written += file_obj.write(UpperCamelCase_							)
  
  								return written
  
  
  
style_context: 
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: list[int]      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							a_       :   List[Any]			=	len(SCREAMING_SNAKE_CASE_      )
  							if n in (0, 1):
  														return 0
  							return sum(query * (n - i - 1) for i, query in enumerate(sorted(SCREAMING_SNAKE_CASE_      )      )      )
  
  
  if __name__ == "__main__":
  	import doctest
  
  	doctest.testmod()
  
  
  