


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__(				UpperCAmelCase__				):







						'''simple docstring'''




						def __init__(					self ,    __lowercase ,    __lowercase = None ,    __lowercase = None ,    __lowercase = None ,    __lowercase = False ,    __lowercase = False ,    __lowercase = None ,    **__lowercase ,    )       ->     Any:
										super().__init__(
										    __lowercase ,    split=__lowercase ,    features=__lowercase ,    cache_dir=__lowercase ,    keep_in_memory=__lowercase ,    streaming=__lowercase ,    num_proc=__lowercase ,    **__lowercase ,    )
										lowerCAmelCase_			:   int     					=					path_or_paths if isinstance(__lowercase ,    __lowercase				) else {self.split: path_or_paths}
										lowerCAmelCase_			:   Tuple     					=					Csv(
										    cache_dir=__lowercase ,    data_files=__lowercase ,    features=__lowercase ,    **__lowercase ,    )




						def     lowercase_			(					self				)       ->     List[Any]:
										# Build iterable dataset
										if self.streaming:
														lowerCAmelCase_			:   List[Any]     					=					self.builder.as_streaming_dataset(split=self.split				)
										# Build regular (map-style) dataset
										else:
														lowerCAmelCase_			:   Optional[Any]     					=					None
														lowerCAmelCase_			:   Union[str, Any]     					=					None
														lowerCAmelCase_			:   Tuple     					=					None
														lowerCAmelCase_			:   Union[str, Any]     					=					None

														self.builder.download_and_prepare(
														    download_config=__lowercase ,    download_mode=__lowercase ,    verification_mode=__lowercase ,    base_path=__lowercase ,    num_proc=self.num_proc ,    )
														lowerCAmelCase_			:   List[Any]     					=					self.builder.as_dataset(
														    split=self.split ,    verification_mode=__lowercase ,    in_memory=self.keep_in_memory				)
										return dataset







class 					snake_case__:







						'''simple docstring'''




						def __init__(					self ,    __lowercase ,    __lowercase ,    __lowercase = None ,    __lowercase = None ,    **__lowercase ,    )       ->     str:
										if num_proc is not None and num_proc <= 0:
														raise ValueError(f"""num_proc {num_proc} must be an integer > 0."""				)

										lowerCAmelCase_			:   List[str]     					=					dataset
										lowerCAmelCase_			:   Tuple     					=					path_or_buf
										lowerCAmelCase_			:   Optional[int]     					=					batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
										lowerCAmelCase_			:   Dict     					=					num_proc
										lowerCAmelCase_			:   Optional[Any]     					=					'''utf-8'''
										lowerCAmelCase_			:   Optional[Any]     					=					to_csv_kwargs




						def     lowercase_			(					self				)       ->     int:
										lowerCAmelCase_			:   Tuple     					=					self.to_csv_kwargs.pop('''path_or_buf''' ,    __lowercase				)
										lowerCAmelCase_			:   List[str]     					=					self.to_csv_kwargs.pop('''header''' ,    __lowercase				)
										lowerCAmelCase_			:   List[Any]     					=					self.to_csv_kwargs.pop('''index''' ,    __lowercase				)

										if isinstance(self.path_or_buf ,    (str, bytes, os.PathLike)				):
														with open(self.path_or_buf ,    '''wb+'''				) as buffer:
																		lowerCAmelCase_			:   Optional[Any]     					=					self._write(file_obj=__lowercase ,    header=__lowercase ,    index=__lowercase ,    **self.to_csv_kwargs				)
										else:
														lowerCAmelCase_			:   List[Any]     					=					self._write(file_obj=self.path_or_buf ,    header=__lowercase ,    index=__lowercase ,    **self.to_csv_kwargs				)
										return written




						def     lowercase_			(					self ,    __lowercase				)       ->     Tuple:
										lowerCAmelCase_					,	lowerCAmelCase_					,	lowerCAmelCase_					,	lowerCAmelCase_			:   Optional[Any]     					=					args

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




						def     lowercase_			(					self ,    __lowercase ,    __lowercase ,    __lowercase ,    **__lowercase				)       ->     int:
										lowerCAmelCase_			:   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''' ,    ):
																		lowerCAmelCase_			:   Union[str, Any]     					=					self._batch_csv((offset, header, index, to_csv_kwargs)				)
																		written += file_obj.write(__lowercase				)

										else:
														lowerCAmelCase_					,	lowerCAmelCase_			:   List[str]     					=					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 ,    __lowercase ,    __lowercase				)] ,    ) ,    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(__lowercase				)

										return written



def       lowerCAmelCase			(		lowerCAmelCase_			)->			int:
				lowerCAmelCase_			:   Optional[int]     					=					len(lowerCAmelCase_			)
				if n in (0, 1):
								return 0
				return sum(query * (n - i - 1) for i, query in enumerate(sorted(lowerCAmelCase_			)			)			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()