




import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader



class    _a     (				lowercase__							):






							"""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[str] = None							,	a				:     Optional[int] = None							,	**a				:     Tuple							,	)	->Any:
													super().__init__(
													    a							,	split=a							,	features=a							,	cache_dir=a							,	keep_in_memory=a							,	streaming=a							,	num_proc=a							,	**a							,	)
													SCREAMING_SNAKE_CASE__     :				int   =					field
													SCREAMING_SNAKE_CASE__     :				int   =					path_or_paths if isinstance(a							,	a    ) else {self.split: path_or_paths}
													SCREAMING_SNAKE_CASE__     :				Tuple   =					Json(
													    cache_dir=a							,	data_files=a							,	features=a							,	field=a							,	**a							,	)






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

																			self.builder.download_and_prepare(
																			    download_config=a							,	download_mode=a							,	verification_mode=a							,	base_path=a							,	num_proc=self.num_proc							,	)
																			SCREAMING_SNAKE_CASE__     :				List[Any]   =					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				:     Optional[Any]							,	a				:     Dataset							,	a				:     Union[PathLike, BinaryIO]							,	a				:     Optional[int] = None							,	a				:     Optional[int] = None							,	**a				:     Any							,	)	->Any:
													if num_proc is not None and num_proc <= 0:
																			raise ValueError(f"""num_proc {num_proc} must be an integer > 0."""    )

													SCREAMING_SNAKE_CASE__     :				Tuple   =					dataset
													SCREAMING_SNAKE_CASE__     :				List[str]   =					path_or_buf
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
													SCREAMING_SNAKE_CASE__     :				Any   =					num_proc
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					"utf-8"
													SCREAMING_SNAKE_CASE__     :				Any   =					to_json_kwargs

							def      A_  (      self				:     Union[str, Any]    )	->int:
													SCREAMING_SNAKE_CASE__     :				Tuple   =					self.to_json_kwargs.pop("path_or_buf"							,	a    )
													SCREAMING_SNAKE_CASE__     :				List[str]   =					self.to_json_kwargs.pop("orient"							,	"records"    )
													SCREAMING_SNAKE_CASE__     :				Any   =					self.to_json_kwargs.pop("lines"							,	True if orient == "records" else False    )
													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					self.to_json_kwargs.pop("index"							,	False if orient in ["split", "table"] else True    )
													SCREAMING_SNAKE_CASE__     :				Any   =					self.to_json_kwargs.pop("compression"							,	a    )

													if compression not in [None, "infer", "gzip", "bz2", "xz"]:
																			raise NotImplementedError(f"""`datasets` currently does not support {compression} compression"""    )

													if isinstance(self.path_or_buf							,	(str, bytes, os.PathLike)    ):
																			with fsspec.open(self.path_or_buf							,	"wb"							,	compression=a    ) as buffer:
																									SCREAMING_SNAKE_CASE__     :				Optional[int]   =					self._write(file_obj=a							,	orient=a							,	lines=a							,	index=a							,	**self.to_json_kwargs    )
													else:
																			if compression:
																									raise NotImplementedError(
																									    f"""The compression parameter is not supported when writing to a buffer, but compression={compression}"""
																									    " was passed. Please provide a local path instead."    )
																			SCREAMING_SNAKE_CASE__     :				Any   =					self._write(
																			    file_obj=self.path_or_buf							,	orient=a							,	lines=a							,	index=a							,	**self.to_json_kwargs    )
													return written

							def      A_  (      self				:     List[Any]							,	a				:     int    )	->str:
													SCREAMING_SNAKE_CASE__     :				Dict   =					args

													SCREAMING_SNAKE_CASE__     :				str   =					query_table(
													    table=self.dataset.data							,	key=slice(a							,	offset + self.batch_size    )							,	indices=self.dataset._indices							,	)
													SCREAMING_SNAKE_CASE__     :				Dict   =					batch.to_pandas().to_json(
													    path_or_buf=a							,	orient=a							,	lines=a							,	index=a							,	**a    )
													if not json_str.endswith("\n"    ):
																			json_str += "\n"
													return json_str.encode(self.encoding    )






							def      A_  (      self				:     str							,	a				:     BinaryIO							,	a				:     Optional[Any]							,	a				:     List[Any]							,	a				:     str							,	**a				:     Optional[int]							,	)	->int:
													SCREAMING_SNAKE_CASE__     :				List[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 json from Arrow format"							,	):
																									SCREAMING_SNAKE_CASE__     :				int   =					self._batch_json((offset, orient, lines, index, to_json_kwargs)    )
																									written += file_obj.write(a    )
													else:
																			SCREAMING_SNAKE_CASE__     :				Any   =					len(self.dataset    ), self.batch_size
																			with multiprocessing.Pool(self.num_proc    ) as pool:
																									for json_str in logging.tqdm(
																									    pool.imap(
																									        self._batch_json							,	[(offset, orient, lines, index, to_json_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 json from Arrow format"							,	):
																															written += file_obj.write(a    )

													return written






def       UpperCAmelCase							(     _lowerCamelCase      :  int			,   _lowerCamelCase      :  bool = False     ):





						'''simple docstring'''


						if n == 2:
												return True
						if not n % 2 or n < 2:
												return False
						if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
												return False
						if n > 3_317_044_064_679_887_385_961_981 and not allow_probable:
												raise ValueError(
												    "Warning: upper bound of deterministic test is exceeded. "
												    "Pass allow_probable=True to allow probabilistic test. "
												    "A return value of True indicates a probable prime."     )
						# array bounds provided by analysis
						SCREAMING_SNAKE_CASE__     :				List[str]   =					[
						    2_047,
						    1_373_653,
						    25_326_001,
						    3_215_031_751,
						    2_152_302_898_747,
						    3_474_749_660_383,
						    341_550_071_728_321,
						    1,
						    3_825_123_056_546_413_051,
						    1,
						    1,
						    318_665_857_834_031_151_167_461,
						    3_317_044_064_679_887_385_961_981,
						]

						SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
						for idx, _p in enumerate(_lowerCamelCase			,   1     ):
												if n < _p:
																		# then we have our last prime to check
																		SCREAMING_SNAKE_CASE__     :				Dict   =					primes[:idx]
																		break
						SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__     :				Dict   =					n - 1, 0
						# break up n -1 into a power of 2 (s) and
						# remaining odd component
						# essentially, solve for d * 2 ** s == n - 1
						while d % 2 == 0:
												d //= 2
												s += 1
						for prime in plist:
												SCREAMING_SNAKE_CASE__     :				str   =					False
												for r in range(_lowerCamelCase     ):
																		SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					pow(_lowerCamelCase			,   d * 2**r			,   _lowerCamelCase     )
																		# see article for analysis explanation for m
																		if (r == 0 and m == 1) or ((m + 1) % n == 0):
																								SCREAMING_SNAKE_CASE__     :				str   =					True
																								# this loop will not determine compositeness
																								break
												if pr:
																		continue
												# if pr is False, then the above loop never evaluated to true,
												# and the n MUST be composite
												return False
						return True







def       UpperCAmelCase							(     ):





						'''simple docstring'''


						assert not miller_rabin(561     )
						assert miller_rabin(563     )
						# 2047

						assert not miller_rabin(838_201     )
						assert miller_rabin(838_207     )
						# 1_373_653

						assert not miller_rabin(17_316_001     )
						assert miller_rabin(17_316_017     )
						# 25_326_001

						assert not miller_rabin(3_078_386_641     )
						assert miller_rabin(3_078_386_653     )
						# 3_215_031_751

						assert not miller_rabin(1_713_045_574_801     )
						assert miller_rabin(1_713_045_574_819     )
						# 2_152_302_898_747

						assert not miller_rabin(2_779_799_728_307     )
						assert miller_rabin(2_779_799_728_327     )
						# 3_474_749_660_383

						assert not miller_rabin(113_850_023_909_441     )
						assert miller_rabin(113_850_023_909_527     )
						# 341_550_071_728_321

						assert not miller_rabin(1_275_041_018_848_804_351     )
						assert miller_rabin(1_275_041_018_848_804_391     )
						# 3_825_123_056_546_413_051

						assert not miller_rabin(79_666_464_458_507_787_791_867     )
						assert miller_rabin(79_666_464_458_507_787_791_951     )
						# 318_665_857_834_031_151_167_461

						assert not miller_rabin(552_840_677_446_647_897_660_333     )
						assert miller_rabin(552_840_677_446_647_897_660_359     )
						# 3_317_044_064_679_887_385_961_981
						# upper limit for probabilistic test


if __name__ == "__main__":
				test_miller_rabin()