





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  (    a     ):


				def __init__(		self ,			UpperCAmelCase_ ,			UpperCAmelCase_ = None ,			UpperCAmelCase_ = None ,			UpperCAmelCase_ = None ,			UpperCAmelCase_ = False ,			UpperCAmelCase_ = False ,			UpperCAmelCase_ = None ,			**UpperCAmelCase_ ,			):
								super().__init__(
								    UpperCAmelCase_ ,			split=UpperCAmelCase_ ,			features=UpperCAmelCase_ ,			cache_dir=UpperCAmelCase_ ,			keep_in_memory=UpperCAmelCase_ ,			streaming=UpperCAmelCase_ ,			num_proc=UpperCAmelCase_ ,			**UpperCAmelCase_ ,			)
								lowerCamelCase									=path_or_paths if isinstance(UpperCAmelCase_ ,			UpperCAmelCase_				) else {self.split: path_or_paths}
								lowerCamelCase									=Csv(
								    cache_dir=UpperCAmelCase_ ,			data_files=UpperCAmelCase_ ,			features=UpperCAmelCase_ ,			**UpperCAmelCase_ ,			)


				def _snake_case							(		self				):
								# 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=UpperCAmelCase_ ,			download_mode=UpperCAmelCase_ ,			verification_mode=UpperCAmelCase_ ,			base_path=UpperCAmelCase_ ,			num_proc=self.num_proc ,			)
												lowerCamelCase									=self.builder.as_dataset(
												    split=self.split ,			verification_mode=UpperCAmelCase_ ,			in_memory=self.keep_in_memory				)
								return dataset




class    __A  :


				def __init__(		self ,			UpperCAmelCase_ ,			UpperCAmelCase_ ,			UpperCAmelCase_ = None ,			UpperCAmelCase_ = None ,			**UpperCAmelCase_ ,			):
								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				):
								lowerCamelCase									=self.to_csv_kwargs.pop("""path_or_buf""" ,			UpperCAmelCase_				)
								lowerCamelCase									=self.to_csv_kwargs.pop("""header""" ,			UpperCAmelCase_				)
								lowerCamelCase									=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:
																lowerCamelCase									=self._write(file_obj=UpperCAmelCase_ ,			header=UpperCAmelCase_ ,			index=UpperCAmelCase_ ,			**self.to_csv_kwargs				)
								else:
												lowerCamelCase									=self._write(file_obj=self.path_or_buf ,			header=UpperCAmelCase_ ,			index=UpperCAmelCase_ ,			**self.to_csv_kwargs				)
								return written


				def _snake_case							(		self ,			UpperCAmelCase_				):
								lowerCamelCase			,	lowerCamelCase			,	lowerCamelCase			,	lowerCamelCase									=args

								lowerCamelCase									=query_table(
								    table=self.dataset.data ,			key=slice(UpperCAmelCase_ ,			offset + self.batch_size				) ,			indices=self.dataset._indices ,			)
								lowerCamelCase									=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 _snake_case							(		self ,			UpperCAmelCase_ ,			UpperCAmelCase_ ,			UpperCAmelCase_ ,			**UpperCAmelCase_				):
								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(UpperCAmelCase_				)

								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 ,			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












def   _lowercase       (    _UpperCAmelCase					)    ->	bool:
				if not isinstance(_UpperCAmelCase      ,   _UpperCAmelCase					):
								lowerCamelCase									=F"""Input value of [number={number}] must be an integer"""
								raise TypeError(_UpperCAmelCase					)
				if number < 0 or number % 2 == 1:
								return False
				lowerCamelCase									=int(number**0.5					)
				return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()





