






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   __SCREAMING_SNAKE_CASE(	a_	):
							def __init__(     self:      Any       ,	UpperCamelCase:      NestedDataStructureLike[PathLike]       ,	UpperCamelCase:      Optional[NamedSplit] = None       ,	UpperCamelCase:      Optional[Features] = None       ,	UpperCamelCase:      str = None       ,	UpperCamelCase:      bool = False       ,	UpperCamelCase:      bool = False       ,	UpperCamelCase:      Optional[str] = None       ,	UpperCamelCase:      Optional[int] = None       ,	**UpperCamelCase:      Dict       ,	)		->		int:
											super().__init__(
											    UpperCamelCase       ,	split=UpperCamelCase       ,	features=UpperCamelCase       ,	cache_dir=UpperCamelCase       ,	keep_in_memory=UpperCamelCase       ,	streaming=UpperCamelCase       ,	num_proc=UpperCamelCase       ,	**UpperCamelCase       ,	)
											snake_case__									=     field
											snake_case__									=     path_or_paths if isinstance(UpperCamelCase       ,	UpperCamelCase						) else {self.split: path_or_paths}
											snake_case__									=     Json(
											    cache_dir=UpperCamelCase       ,	data_files=UpperCamelCase       ,	features=UpperCamelCase       ,	field=UpperCamelCase       ,	**UpperCamelCase       ,	)


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

															self.builder.download_and_prepare(
															    download_config=UpperCamelCase       ,	download_mode=UpperCamelCase       ,	verification_mode=UpperCamelCase       ,	base_path=UpperCamelCase       ,	num_proc=self.num_proc       ,	)
															snake_case__									=     self.builder.as_dataset(
															    split=self.split       ,	verification_mode=UpperCamelCase       ,	in_memory=self.keep_in_memory						)
											return dataset


class   __SCREAMING_SNAKE_CASE:
							def __init__(     self:      Dict       ,	UpperCamelCase:      Dataset       ,	UpperCamelCase:      Union[PathLike, BinaryIO]       ,	UpperCamelCase:      Optional[int] = None       ,	UpperCamelCase:      Optional[int] = None       ,	**UpperCamelCase:      Optional[Any]       ,	)		->		int:
											if num_proc is not None and num_proc <= 0:
															raise ValueError(F'''num_proc {num_proc} must be an integer > 0.'''						)

											snake_case__									=     dataset
											snake_case__									=     path_or_buf
											snake_case__									=     batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
											snake_case__									=     num_proc
											snake_case__									=     'utf-8'
											snake_case__									=     to_json_kwargs
							def lowerCAmelCase_ (     self:      List[str]						)		->		int:
											snake_case__									=     self.to_json_kwargs.pop('path_or_buf'       ,	UpperCamelCase						)
											snake_case__									=     self.to_json_kwargs.pop('orient'       ,	'records'						)
											snake_case__									=     self.to_json_kwargs.pop('lines'       ,	True if orient == 'records' else False						)
											snake_case__									=     self.to_json_kwargs.pop('index'       ,	False if orient in ['split', 'table'] else True						)
											snake_case__									=     self.to_json_kwargs.pop('compression'       ,	UpperCamelCase						)

											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=UpperCamelCase						) as buffer:
																			snake_case__									=     self._write(file_obj=UpperCamelCase       ,	orient=UpperCamelCase       ,	lines=UpperCamelCase       ,	index=UpperCamelCase       ,	**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.'						)
															snake_case__									=     self._write(
															    file_obj=self.path_or_buf       ,	orient=UpperCamelCase       ,	lines=UpperCamelCase       ,	index=UpperCamelCase       ,	**self.to_json_kwargs						)
											return written
							def lowerCAmelCase_ (     self:      Union[str, Any]       ,	UpperCamelCase:      Tuple						)		->		int:
											snake_case__							,						snake_case__							,						snake_case__							,						snake_case__							,						snake_case__									=     args

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


							def lowerCAmelCase_ (     self:      Tuple       ,	UpperCamelCase:      BinaryIO       ,	UpperCamelCase:      str       ,	UpperCamelCase:      Union[str, Any]       ,	UpperCamelCase:      Optional[int]       ,	**UpperCamelCase:      List[Any]       ,	)		->		int:
											snake_case__									=     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'       ,	):
																			snake_case__									=     self._batch_json((offset, orient, lines, index, to_json_kwargs)						)
																			written += file_obj.write(UpperCamelCase						)
											else:
															snake_case__							,						snake_case__									=     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       ,	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 json from Arrow format'       ,	):
																							written += file_obj.write(UpperCamelCase						)

											return written












def      a_ (      _A      ,   _A  )			->			str:







				"""simple docstring"""
				if number < 0 or shift_amount < 0:
								raise ValueError('both inputs must be positive integers'  )

				snake_case__									=     str(bin(_A  )  )
				binary_number += "0" * shift_amount
				return binary_number
def      a_ (      _A      ,   _A  )			->			str:







				"""simple docstring"""
				if number < 0 or shift_amount < 0:
								raise ValueError('both inputs must be positive integers'  )

				snake_case__									=     str(bin(_A  )  )[2:]
				if shift_amount >= len(_A  ):
								return "0b0"
				snake_case__									=     binary_number[: len(_A  ) - shift_amount]
				return "0b" + shifted_binary_number
def      a_ (      _A      ,   _A  )			->			str:







				"""simple docstring"""
				if number >= 0:  # Get binary representation of positive number
								snake_case__									=     '0' + str(bin(_A  )  ).strip('-'  )[2:]
				else:  # Get binary (2's complement) representation of negative number
								snake_case__									=     len(bin(_A  )[3:]  )  # Find 2's complement of number
								snake_case__									=     bin(abs(_A  ) - (1 << binary_number_length)  )[3:]
								snake_case__									=     (
								    '1' + '0' * (binary_number_length - len(_A  )) + binary_number
								)

				if shift_amount >= len(_A  ):
								return "0b" + binary_number[0] * len(_A  )
				return (
				    "0b"
				    + binary_number[0] * shift_amount
				    + binary_number[: len(_A  ) - shift_amount]
				)


if __name__ == "__main__":
							import doctest

							doctest.testmod()




