




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       A      (		_lowerCAmelCase		):
     """simple docstring"""

     def __init__(     self	: Any						,	A__	: NestedDataStructureLike[PathLike]						,	A__	: Optional[NamedSplit] = None						,	A__	: Optional[Features] = None						,	A__	: str = None						,	A__	: bool = False						,	A__	: bool = False						,	A__	: Optional[int] = None						,	**A__	: List[str]						,	)					->							Optional[int]:
           super().__init__(
               A__						,	split=A__						,	features=A__						,	cache_dir=A__						,	keep_in_memory=A__						,	streaming=A__						,	num_proc=A__						,	**A__						,	)
           lowerCamelCase__   	=					path_or_paths if isinstance(A__						,	A__      ) else {self.split: path_or_paths}
           lowerCamelCase__   	=					Csv(
               cache_dir=A__						,	data_files=A__						,	features=A__						,	**A__						,	)




     def 			__snake_case (     self	: str      )					->							Tuple:
           # Build iterable dataset
           if self.streaming:
                 lowerCamelCase__   	=					self.builder.as_streaming_dataset(split=self.split      )
           # Build regular (map-style) dataset
           else:
                 lowerCamelCase__   	=					None
                 lowerCamelCase__   	=					None
                 lowerCamelCase__   	=					None
                 lowerCamelCase__   	=					None

                 self.builder.download_and_prepare(
                     download_config=A__						,	download_mode=A__						,	verification_mode=A__						,	base_path=A__						,	num_proc=self.num_proc						,	)
                 lowerCamelCase__   	=					self.builder.as_dataset(
                     split=self.split						,	verification_mode=A__						,	in_memory=self.keep_in_memory      )
           return dataset






class       A      :
     """simple docstring"""

     def __init__(     self	: str						,	A__	: Dataset						,	A__	: Union[PathLike, BinaryIO]						,	A__	: Optional[int] = None						,	A__	: Optional[int] = None						,	**A__	: Tuple						,	)					->							Union[str, Any]:
           if num_proc is not None and num_proc <= 0:
                 raise ValueError(F"""num_proc {num_proc} must be an integer > 0."""      )

           lowerCamelCase__   	=					dataset
           lowerCamelCase__   	=					path_or_buf
           lowerCamelCase__   	=					batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           lowerCamelCase__   	=					num_proc
           lowerCamelCase__   	=					'utf-8'
           lowerCamelCase__   	=					to_csv_kwargs




     def 			__snake_case (     self	: Optional[int]      )					->							int:
           lowerCamelCase__   	=					self.to_csv_kwargs.pop('path_or_buf'						,	A__      )
           lowerCamelCase__   	=					self.to_csv_kwargs.pop('header'						,	A__      )
           lowerCamelCase__   	=					self.to_csv_kwargs.pop('index'						,	A__      )

           if isinstance(self.path_or_buf						,	(str, bytes, os.PathLike)      ):
                 with open(self.path_or_buf						,	'wb+'      ) as buffer:
                       lowerCamelCase__   	=					self._write(file_obj=A__						,	header=A__						,	index=A__						,	**self.to_csv_kwargs      )
           else:
                 lowerCamelCase__   	=					self._write(file_obj=self.path_or_buf						,	header=A__						,	index=A__						,	**self.to_csv_kwargs      )
           return written




     def 			__snake_case (     self	: Any						,	A__	: Union[str, Any]      )					->							int:
           lowerCamelCase__	,		lowerCamelCase__	,		lowerCamelCase__	,		lowerCamelCase__   	=					args

           lowerCamelCase__   	=					query_table(
               table=self.dataset.data						,	key=slice(A__						,	offset + self.batch_size      )						,	indices=self.dataset._indices						,	)
           lowerCamelCase__   	=					batch.to_pandas().to_csv(
               path_or_buf=A__						,	header=header if (offset == 0) else False						,	index=A__						,	**A__      )
           return csv_str.encode(self.encoding      )




     def 			__snake_case (     self	: Any						,	A__	: BinaryIO						,	A__	: Union[str, Any]						,	A__	: str						,	**A__	: Union[str, Any]      )					->							int:
           lowerCamelCase__   	=					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'						,	):
                       lowerCamelCase__   	=					self._batch_csv((offset, header, index, to_csv_kwargs)      )
                       written += file_obj.write(A__      )

           else:
                 lowerCamelCase__	,		lowerCamelCase__   	=					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						,	A__						,	A__      )]						,	)						,	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(A__      )

           return written





def       lowerCAmelCase_      (	lowerCamelCase:							str    )       ->      int:


      '''simple docstring'''




      lowerCamelCase__   	=					str(lowerCamelCase    ).strip()
      if not bin_string:
            raise ValueError('Empty string was passed to the function'    )
      lowerCamelCase__   	=					bin_string[0] == '-'
      if is_negative:
            lowerCamelCase__   	=					bin_string[1:]
      if not all(char in '01' for char in bin_string    ):
            raise ValueError('Non-binary value was passed to the function'    )
      lowerCamelCase__   	=					0
      for char in bin_string:
            lowerCamelCase__   	=					2 * decimal_number + int(lowerCamelCase    )
      return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
      from doctest import testmod

      testmod()