"""simple docstring"""


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        __UpperCAmelCase						(     __lowerCAmelCase     ):

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






				def 		_a     (				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=_lowerCamelCase     ,			download_mode=_lowerCamelCase     ,			verification_mode=_lowerCamelCase     ,			base_path=_lowerCamelCase     ,			num_proc=self.num_proc     ,			)
																lowerCamelCase__ =self.builder.as_dataset(
																    split=self.split     ,			verification_mode=_lowerCamelCase     ,			in_memory=self.keep_in_memory				)
										return dataset






class        __UpperCAmelCase						:

				def __init__(				self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase = None     ,			_lowerCamelCase = None     ,			**_lowerCamelCase     ,			):
										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 		_a     (				self				):
										lowerCamelCase__ =self.to_csv_kwargs.pop("path_or_buf"     ,			_lowerCamelCase				)
										lowerCamelCase__ =self.to_csv_kwargs.pop("header"     ,			_lowerCamelCase				)
										lowerCamelCase__ =self.to_csv_kwargs.pop("index"     ,			_lowerCamelCase				)

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

				def 		_a     (				self     ,			_lowerCamelCase				):
										lowerCamelCase__ ,				lowerCamelCase__ ,				lowerCamelCase__ ,				lowerCamelCase__ =args

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






				def 		_a     (				self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			**_lowerCamelCase				):
										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(_lowerCamelCase				)

										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     ,			_lowerCamelCase     ,			_lowerCamelCase				)]     ,			)     ,			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(_lowerCamelCase				)

										return written



"""simple docstring"""


def       lowerCamelCase_			( __lowerCAmelCase    )							-> bool:




						'''simple docstring'''



						if not isinstance(__lowerCAmelCase       ,   __lowerCAmelCase    ):
												raise ValueError("Input series is not valid, valid series - [2, 4, 8]"    )
						if len(__lowerCAmelCase    ) == 0:
												raise ValueError("Input list must be a non empty list"    )
						if len(__lowerCAmelCase    ) == 1:
												return True
						try:
												lowerCamelCase__ =series[1] / series[0]
												for index in range(len(__lowerCAmelCase    ) - 1    ):
																		if series[index + 1] / series[index] != common_ratio:
																								return False
						except ZeroDivisionError:
												return False
						return True





def       lowerCamelCase_			( __lowerCAmelCase    )							-> float:




						'''simple docstring'''



						if not isinstance(__lowerCAmelCase       ,   __lowerCAmelCase    ):
												raise ValueError("Input series is not valid, valid series - [2, 4, 8]"    )
						if len(__lowerCAmelCase    ) == 0:
												raise ValueError("Input list must be a non empty list"    )
						lowerCamelCase__ =1
						for value in series:
												answer *= value
						return pow(__lowerCAmelCase       ,   1 / len(__lowerCAmelCase    )    )


if __name__ == "__main__":
	import doctest

	doctest.testmod()


