
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        _UpperCamelCase				(					_A  ):






			'''simple docstring'''

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




			def       lowerCAmelCase__	(       self :       Optional[Any]      ):
							# Build iterable dataset
							if self.streaming:
											UpperCamelCase_:							List[Any]	=						self.builder.as_streaming_dataset(split=self.split      )
							# Build regular (map-style) dataset
							else:
											UpperCamelCase_:							Any	=						None
											UpperCamelCase_:							int	=						None
											UpperCamelCase_:							Tuple	=						None
											UpperCamelCase_:							str	=						None

											self.builder.download_and_prepare(
											    download_config=snake_case_						,	download_mode=snake_case_						,	verification_mode=snake_case_						,	base_path=snake_case_						,	num_proc=self.num_proc						,	)
											UpperCamelCase_:							Union[str, Any]	=						self.builder.as_dataset(
											    split=self.split						,	verification_mode=snake_case_						,	in_memory=self.keep_in_memory      )
							return dataset




class        _UpperCamelCase				:






			'''simple docstring'''

			def __init__(       self :       List[str]						,	snake_case_ :       Dataset						,	snake_case_ :       Union[PathLike, BinaryIO]						,	snake_case_ :       Optional[int] = None						,	snake_case_ :       Optional[int] = None						,	**snake_case_ :       Tuple						,	):
							if num_proc is not None and num_proc <= 0:
											raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''      )

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

			def       lowerCAmelCase__	(       self :       Dict      ):
							UpperCamelCase_:							int	=						self.to_json_kwargs.pop("""path_or_buf"""						,	snake_case_      )
							UpperCamelCase_:							Tuple	=						self.to_json_kwargs.pop("""orient"""						,	"""records"""      )
							UpperCamelCase_:							Any	=						self.to_json_kwargs.pop("""lines"""						,	True if orient == """records""" else False      )
							UpperCamelCase_:							Optional[int]	=						self.to_json_kwargs.pop("""index"""						,	False if orient in ["""split""", """table"""] else True      )
							UpperCamelCase_:							Any	=						self.to_json_kwargs.pop("""compression"""						,	snake_case_      )

							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=snake_case_      ) as buffer:
															UpperCamelCase_:							Tuple	=						self._write(file_obj=snake_case_						,	orient=snake_case_						,	lines=snake_case_						,	index=snake_case_						,	**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."""      )
											UpperCamelCase_:							List[Any]	=						self._write(
											    file_obj=self.path_or_buf						,	orient=snake_case_						,	lines=snake_case_						,	index=snake_case_						,	**self.to_json_kwargs      )
							return written

			def       lowerCAmelCase__	(       self :       Dict						,	snake_case_ :       List[str]      ):
							UpperCamelCase_,   UpperCamelCase_,   UpperCamelCase_,   UpperCamelCase_,   UpperCamelCase_:							Optional[int]	=						args

							UpperCamelCase_:							Union[str, Any]	=						query_table(
							    table=self.dataset.data						,	key=slice(snake_case_						,	offset + self.batch_size      )						,	indices=self.dataset._indices						,	)
							UpperCamelCase_:							int	=						batch.to_pandas().to_json(
							    path_or_buf=snake_case_						,	orient=snake_case_						,	lines=snake_case_						,	index=snake_case_						,	**snake_case_      )
							if not json_str.endswith("""\n"""      ):
											json_str += "\n"
							return json_str.encode(self.encoding      )




			def       lowerCAmelCase__	(       self :       Dict						,	snake_case_ :       BinaryIO						,	snake_case_ :       int						,	snake_case_ :       Tuple						,	snake_case_ :       int						,	**snake_case_ :       str						,	):
							UpperCamelCase_:							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 json from Arrow format"""						,	):
															UpperCamelCase_:							Dict	=						self._batch_json((offset, orient, lines, index, to_json_kwargs)      )
															written += file_obj.write(snake_case_      )
							else:
											UpperCamelCase_,   UpperCamelCase_:							int	=						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						,	snake_case_						,	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 json from Arrow format"""						,	):
																			written += file_obj.write(snake_case_      )

							return written








def        A__					(						lowerCamelCase     ,    lowerCamelCase						)  ->	int:
				while second != 0:
								UpperCamelCase_:							Optional[Any]	=						first & second
								first ^= second
								UpperCamelCase_:							Any	=						c << 1
				return first


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							lowerCamelCase_						: List[Any]         =  int(input("""Enter the first number: """).strip())
							lowerCamelCase_						: Tuple         =  int(input("""Enter the second number: """).strip())
							print(F"""{add(first, second) = }""")






