


'''simple docstring'''

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 :       Optional[int]										= datasets.utils.logging.get_logger(__name__)


@dataclass
class 					a__ (       datasets.BuilderConfig					):







				"""simple docstring"""



				__UpperCamelCase			:						Optional[datasets.Features]		=		None
				__UpperCamelCase			:						str		=		"utf-8"
				__UpperCamelCase			:						Optional[str]		=		None
				__UpperCamelCase			:						Optional[str]		=		None
				__UpperCamelCase			:						bool		=		True  # deprecated
				__UpperCamelCase			:						Optional[int]		=		None  # deprecated
				__UpperCamelCase			:						int		=		10 << 20  # 10MB
				__UpperCamelCase			:						Optional[bool]		=		None


class 					a__ (       datasets.ArrowBasedBuilder					):







				"""simple docstring"""



				__UpperCamelCase			:						Optional[Any]		=		JsonConfig




				def     _snake_case     (self						):
										if self.config.block_size is not None:
																logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''						)
																__lowerCAmelCase											= 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     _snake_case     (self				,	__lowercase						):
										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}"""						)
										__lowerCAmelCase											= dl_manager.download_and_extract(self.config.data_files						)
										if isinstance(_a				,	(str, list, tuple)						):
																__lowerCAmelCase											= data_files
																if isinstance(_a				,	_a						):
																						__lowerCAmelCase											= [files]
																__lowerCAmelCase											= [dl_manager.iter_files(_a						) for file in files]
																return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,	gen_kwargs={'''files''': files}						)]
										__lowerCAmelCase											= []
										for split_name, files in data_files.items():
																if isinstance(_a				,	_a						):
																						__lowerCAmelCase											= [files]
																__lowerCAmelCase											= [dl_manager.iter_files(_a						) for file in files]
																splits.append(datasets.SplitGenerator(name=_a				,	gen_kwargs={'''files''': files}						)						)
										return splits




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




				def     _snake_case     (self				,	__lowercase						):
										for file_idx, file in enumerate(itertools.chain.from_iterable(_a						)						):
																# 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(_a				,	encoding=self.config.encoding				,	errors=self.config.encoding_errors						) as f:
																												__lowerCAmelCase											= json.load(_a						)

																						# We keep only the field we are interested in
																						__lowerCAmelCase											= dataset[self.config.field]

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

																# If the file has one json object per line
																else:
																						with open(_a				,	'''rb'''						) as f:
																												__lowerCAmelCase											= 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
																												__lowerCAmelCase											= max(self.config.chunksize // 32				,	16 << 10						)
																												__lowerCAmelCase											= (
																												    self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
																												)
																												while True:
																																		__lowerCAmelCase											= f.read(self.config.chunksize						)
																																		if not batch:
																																								break
																																		# Finish current line
																																		try:
																																								batch += f.readline()
																																		except (AttributeError, io.UnsupportedOperation):
																																								batch += readline(_a						)
																																		# PyArrow only accepts utf-8 encoded bytes
																																		if self.config.encoding != "utf-8":
																																								__lowerCAmelCase											= batch.decode(self.config.encoding				,	errors=_a						).encode('''utf-8'''						)
																																		try:
																																								while True:
																																														try:
																																																				__lowerCAmelCase											= paj.read_json(
																																																				    io.BytesIO(_a						)				,	read_options=paj.ReadOptions(block_size=_a						)						)
																																																				break
																																														except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																																																				if (
																																																				    isinstance(_a				,	pa.ArrowInvalid						)
																																																				    and "straddling" not in str(_a						)
																																																				    or block_size > len(_a						)
																																																				):
																																																										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(_a						)} 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(
																																														    _a				,	encoding=self.config.encoding				,	errors=self.config.encoding_errors						) as f:
																																																				__lowerCAmelCase											= json.load(_a						)
																																								except json.JSONDecodeError:
																																														logger.error(F"""Failed to read file \'{file}\' with error {type(_a						)}: {e}"""						)
																																														raise e
																																								# If possible, parse the file as a list of json objects and exit the loop
																																								if isinstance(_a				,	_a						):  # list is the only sequence type supported in JSON
																																														try:
																																																				__lowerCAmelCase											= set().union(*[row.keys() for row in dataset]						)
																																																				__lowerCAmelCase											= {col: [row.get(_a						) for row in dataset] for col in keys}
																																																				__lowerCAmelCase											= pa.Table.from_pydict(_a						)
																																														except (pa.ArrowInvalid, AttributeError) as e:
																																																				logger.error(F"""Failed to read file \'{file}\' with error {type(_a						)}: {e}"""						)
																																																				raise ValueError(F"""Not able to read records in the JSON file at {file}."""						) from None
																																														yield file_idx, self._cast_table(_a						)
																																														break
																																								else:
																																														logger.error(F"""Failed to read file \'{file}\' with error {type(_a						)}: {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(_a						)
																																		batch_idx += 1





"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     list			) ->      bool:
		if not isinstance(lowerCAmelCase__    ,					lowerCAmelCase__			):
				raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''			)
		if len(lowerCAmelCase__			) == 0:
				raise ValueError('''Input list must be a non empty list'''			)
		if len(lowerCAmelCase__			) == 1:
				return True
		__a           =			series[1] - series[0]
		for index in range(len(lowerCAmelCase__			) - 1			):
				if series[index + 1] - series[index] != common_diff:
						return False
		return True

def        lowercase							(		lowerCAmelCase__ :     list			) ->      float:
		if not isinstance(lowerCAmelCase__    ,					lowerCAmelCase__			):
				raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''			)
		if len(lowerCAmelCase__			) == 0:
				raise ValueError('''Input list must be a non empty list'''			)
		__a           =			0
		for val in series:
				answer += val
		return answer / len(lowerCAmelCase__			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()






