def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return number | (1 << position)



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return number & ~(1 << position)



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return number ^ (1 << position)



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return ((number >> position) & 1) == 1



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return int((number & (1 << position)) != 0       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()




import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


UpperCamelCase_						:     Union[str, Any]	       =							datasets.utils.logging.get_logger(__name__)




@dataclass
class   __lowercase						(						datasets.BuilderConfig       ):
	_A       =   None
	_A       =   "utf-8"
	_A       =   None
	_A       =   None
	_A       =   True  # deprecated
	_A       =   None  # deprecated
	_A       =   10 << 20  # 10MB
	_A       =   None




class   __lowercase						(						datasets.ArrowBasedBuilder       ):
	_A       =   JsonConfig






	def       _a(self				: List[Any]    ) ->			Dict:
							if self.config.block_size is not None:
													logger.warning("The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead"    )
													_lowercase       :	Union[str, Any]           =   self.config.block_size
							if self.config.use_threads is not True:
													logger.warning(
													    "The JSON loader parameter `use_threads` is deprecated and doesn't have any effect anymore."    )
							if self.config.newlines_in_values is not None:
													raise ValueError("The JSON loader parameter `newlines_in_values` is no longer supported"    )
							return datasets.DatasetInfo(features=self.config.features    )






	def       _a(self				: Any      ,	snake_case				: Union[str, Any]    ) ->			List[str]:
							if not self.config.data_files:
													raise ValueError(F"""At least one data file must be specified, but got data_files={self.config.data_files}"""    )
							_lowercase       :	str           =   dl_manager.download_and_extract(self.config.data_files    )
							if isinstance(snake_case      ,	(str, list, tuple)    ):
													_lowercase       :	int           =   data_files
													if isinstance(snake_case      ,	snake_case    ):
																			_lowercase       :	Union[str, Any]           =   [files]
													_lowercase       :	Union[str, Any]           =   [dl_manager.iter_files(snake_case    ) for file in files]
													return [datasets.SplitGenerator(name=datasets.Split.TRAIN      ,	gen_kwargs={"files": files}    )]
							_lowercase       :	Union[str, Any]           =   []
							for split_name, files in data_files.items():
													if isinstance(snake_case      ,	snake_case    ):
																			_lowercase       :	List[Any]           =   [files]
													_lowercase       :	Optional[Any]           =   [dl_manager.iter_files(snake_case    ) for file in files]
													splits.append(datasets.SplitGenerator(name=snake_case      ,	gen_kwargs={"files": files}    )    )
							return splits






	def       _a(self				: List[Any]      ,	snake_case				: pa.Table    ) ->			pa.Table:
							if self.config.features is not None:
													# adding missing columns
													for column_name in set(self.config.features    ) - set(pa_table.column_names    ):
																			_lowercase       :	Any           =   self.config.features.arrow_schema.field(snake_case    ).type
																			_lowercase       :	Optional[Any]           =   pa_table.append_column(snake_case      ,	pa.array([None] * len(snake_case    )      ,	type=snake_case    )    )
													# more expensive cast to support nested structures with keys in a different order
													# allows str <-> int/float or str to Audio for example
													_lowercase       :	str           =   table_cast(snake_case      ,	self.config.features.arrow_schema    )
							return pa_table






	def       _a(self				: str      ,	snake_case				: Tuple    ) ->			Tuple:
							for file_idx, file in enumerate(itertools.chain.from_iterable(snake_case    )    ):
													# If the file is one json object and if we need to look at the list of items in one specific field
													if self.config.field is not None:
																			with open(snake_case      ,	encoding=self.config.encoding      ,	errors=self.config.encoding_errors    ) as f:
																									_lowercase       :	Any           =   json.load(snake_case    )

																			# We keep only the field we are interested in
																			_lowercase       :	List[Any]           =   dataset[self.config.field]

																			# We accept two format: a list of dicts or a dict of lists
																			if isinstance(snake_case      ,	(list, tuple)    ):
																									_lowercase       :	Optional[int]           =   set().union(*[row.keys() for row in dataset]    )
																									_lowercase       :	Union[str, Any]           =   {col: [row.get(snake_case    ) for row in dataset] for col in keys}
																			else:
																									_lowercase       :	List[Any]           =   dataset
																			_lowercase       :	int           =   pa.Table.from_pydict(snake_case    )
																			yield file_idx, self._cast_table(snake_case    )

													# If the file has one json object per line
													else:
																			with open(snake_case      ,	"rb"    ) as f:
																									_lowercase       :	Union[str, Any]           =   0
																									# Use block_size equal to the chunk size divided by 32 to leverage multithreading
																									# Set a default minimum value of 16kB if the chunk size is really small
																									_lowercase       :	Dict           =   max(self.config.chunksize // 32      ,	16 << 10    )
																									_lowercase       :	int           =   (
																									    self.config.encoding_errors if self.config.encoding_errors is not None else "strict"
																									)
																									while True:
																															_lowercase       :	Tuple           =   f.read(self.config.chunksize    )
																															if not batch:
																																					break
																															# Finish current line
																															try:
																																					batch += f.readline()
																															except (AttributeError, io.UnsupportedOperation):
																																					batch += readline(snake_case    )
																															# PyArrow only accepts utf-8 encoded bytes
																															if self.config.encoding != "utf-8":
																																					_lowercase       :	Union[str, Any]           =   batch.decode(self.config.encoding      ,	errors=snake_case    ).encode("utf-8"    )
																															try:
																																					while True:
																																											try:
																																																	_lowercase       :	Optional[Any]           =   paj.read_json(
																																																	    io.BytesIO(snake_case    )      ,	read_options=paj.ReadOptions(block_size=snake_case    )    )
																																																	break
																																											except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																																																	if (
																																																	    isinstance(snake_case      ,	pa.ArrowInvalid    )
																																																	    and "straddling" not in str(snake_case    )
																																																	    or block_size > len(snake_case    )
																																																	):
																																																							raise
																																																	else:
																																																							# Increase the block size in case it was too small.
																																																							# The block size will be reset for the next file.
																																																							logger.debug(
																																																							    F"""Batch of {len(snake_case    )} bytes couldn't be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}."""    )
																																																							block_size *= 2
																															except pa.ArrowInvalid as e:
																																					try:
																																											with open(
																																											    snake_case      ,	encoding=self.config.encoding      ,	errors=self.config.encoding_errors    ) as f:
																																																	_lowercase       :	Any           =   json.load(snake_case    )
																																					except json.JSONDecodeError:
																																											logger.error(F"""Failed to read file '{file}' with error {type(snake_case    )}: {e}"""    )
																																											raise e
																																					# If possible, parse the file as a list of json objects and exit the loop
																																					if isinstance(snake_case      ,	snake_case    ):  # list is the only sequence type supported in JSON
																																											try:
																																																	_lowercase       :	int           =   set().union(*[row.keys() for row in dataset]    )
																																																	_lowercase       :	Dict           =   {col: [row.get(snake_case    ) for row in dataset] for col in keys}
																																																	_lowercase       :	str           =   pa.Table.from_pydict(snake_case    )
																																											except (pa.ArrowInvalid, AttributeError) as e:
																																																	logger.error(F"""Failed to read file '{file}' with error {type(snake_case    )}: {e}"""    )
																																																	raise ValueError(F"""Not able to read records in the JSON file at {file}."""    ) from None
																																											yield file_idx, self._cast_table(snake_case    )
																																											break
																																					else:
																																											logger.error(F"""Failed to read file '{file}' with error {type(snake_case    )}: {e}"""    )
																																											raise ValueError(
																																											    F"""Not able to read records in the JSON file at {file}. """
																																											    F"""You should probably indicate the field of the JSON file containing your records. """
																																											    F"""This JSON file contain the following fields: {str(list(dataset.keys()    )    )}. """
																																											    F"""Select the correct one and provide it as `field='XXX'` to the dataset loading method. """    ) from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																															yield (file_idx, batch_idx), self._cast_table(snake_case    )
																															batch_idx += 1




