






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_  (		SCREAMING_SNAKE_CASE__    ):


						'''simple docstring'''




						def __init__(		self						, _SCREAMING_SNAKE_CASE						, _SCREAMING_SNAKE_CASE = None						, _SCREAMING_SNAKE_CASE = None						, _SCREAMING_SNAKE_CASE = None						, _SCREAMING_SNAKE_CASE = False						, _SCREAMING_SNAKE_CASE = False						, _SCREAMING_SNAKE_CASE = None						, **_SCREAMING_SNAKE_CASE						, )       -> int:
								super().__init__(
								    _SCREAMING_SNAKE_CASE						, split=_SCREAMING_SNAKE_CASE						, features=_SCREAMING_SNAKE_CASE						, cache_dir=_SCREAMING_SNAKE_CASE						, keep_in_memory=_SCREAMING_SNAKE_CASE						, streaming=_SCREAMING_SNAKE_CASE						, num_proc=_SCREAMING_SNAKE_CASE						, **_SCREAMING_SNAKE_CASE						, )
								snake_case_ :							Any         =				path_or_paths if isinstance(_SCREAMING_SNAKE_CASE						, _SCREAMING_SNAKE_CASE ) else {self.split: path_or_paths}
								snake_case_ :							Optional[int]         =				Csv(
								    cache_dir=_SCREAMING_SNAKE_CASE						, data_files=_SCREAMING_SNAKE_CASE						, features=_SCREAMING_SNAKE_CASE						, **_SCREAMING_SNAKE_CASE						, )






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

										self.builder.download_and_prepare(
										    download_config=_SCREAMING_SNAKE_CASE						, download_mode=_SCREAMING_SNAKE_CASE						, verification_mode=_SCREAMING_SNAKE_CASE						, base_path=_SCREAMING_SNAKE_CASE						, num_proc=self.num_proc						, )
										snake_case_ :							Any         =				self.builder.as_dataset(
										    split=self.split						, verification_mode=_SCREAMING_SNAKE_CASE						, in_memory=self.keep_in_memory )
								return dataset




class 						UpperCAmelCase_  :


						'''simple docstring'''




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

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






						def 					_lowerCAmelCase				(		self )       -> int:
								snake_case_ :							Dict         =				self.to_csv_kwargs.pop("path_or_buf"						, _SCREAMING_SNAKE_CASE )
								snake_case_ :							int         =				self.to_csv_kwargs.pop("header"						, _SCREAMING_SNAKE_CASE )
								snake_case_ :							Tuple         =				self.to_csv_kwargs.pop("index"						, _SCREAMING_SNAKE_CASE )

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






						def 					_lowerCAmelCase				(		self						, _SCREAMING_SNAKE_CASE )       -> int:
								snake_case_       ,				snake_case_       ,				snake_case_       ,				snake_case_ :							List[Any]         =				args

								snake_case_ :							Optional[Any]         =				query_table(
								    table=self.dataset.data						, key=slice(_SCREAMING_SNAKE_CASE						, offset + self.batch_size )						, indices=self.dataset._indices						, )
								snake_case_ :							Optional[Any]         =				batch.to_pandas().to_csv(
								    path_or_buf=_SCREAMING_SNAKE_CASE						, header=header if (offset == 0) else False						, index=_SCREAMING_SNAKE_CASE						, **_SCREAMING_SNAKE_CASE )
								return csv_str.encode(self.encoding )






						def 					_lowerCAmelCase				(		self						, _SCREAMING_SNAKE_CASE						, _SCREAMING_SNAKE_CASE						, _SCREAMING_SNAKE_CASE						, **_SCREAMING_SNAKE_CASE )       -> int:
								snake_case_ :							List[Any]         =				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"						, ):
												snake_case_ :							Tuple         =				self._batch_csv((offset, header, index, to_csv_kwargs) )
												written += file_obj.write(_SCREAMING_SNAKE_CASE )

								else:
										snake_case_       ,				snake_case_ :							Optional[int]         =				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						, _SCREAMING_SNAKE_CASE						, _SCREAMING_SNAKE_CASE )]						, )						, 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(_SCREAMING_SNAKE_CASE )

								return written








import math

def    lowerCAmelCase__		(			_a				:	int			):

		if 1 < number < 4:
				# 2 and 3 are primes
				return True
		elif number < 2 or number % 2 == 0 or number % 3 == 0:
				# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
				return False

		# All primes number are in format of 6k +/- 1
		for i in range(5     ,					int(math.sqrt(_a			) + 1			)     ,					6			):
				if number % i == 0 or number % (i + 2) == 0:
						return False
		return True

def    lowerCAmelCase__		(			_a				:	int = 60_08_51_47_51_43			):

		try:
				snake_case_ :							int         =				int(_a			)
		except (TypeError, ValueError):
				raise TypeError("Parameter n must be int or castable to int."			)
		if n <= 0:
				raise ValueError("Parameter n must be greater than or equal to one."			)
		snake_case_ :							Dict         =				0
		if is_prime(_a			):
				return n
		while n % 2 == 0:
				n //= 2
		if is_prime(_a			):
				return n
		for i in range(3     ,					int(math.sqrt(_a			)			) + 1     ,					2			):
				if n % i == 0:
						if is_prime(n // i			):
								snake_case_ :							List[Any]         =				n // i
								break
						elif is_prime(_a			):
								snake_case_ :							str         =				i
		return max_number


if __name__ == "__main__":
							print(F"""{solution() = }""")
