

import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version

def 		UpperCamelCase      (*lowercase_:				Optional[int]					,   lowercase_:				Optional[Union[Dict, Any]] = None					,   lowercase_:				Dict=True					,   lowercase_:				Tuple=2      )  ->   Dict:
	from .. import __version__

	A__							:					Dict       =	take_from
	A__							:					str       =	()
	if not isinstance(args[0]					,   lowercase_      ):
		A__							:					int       =	(args,)

	for attribute, version_name, message in args:
		if version.parse(version.parse(lowercase_      ).base_version      ) >= version.parse(lowercase_      ):
			raise ValueError(
			    f"""The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers'"""
			    f""" version {__version__} is >= {version_name}"""      )

		A__							:					Any       =	None
		if isinstance(lowercase_					,   lowercase_      ) and attribute in deprecated_kwargs:
			values += (deprecated_kwargs.pop(lowercase_      ),)
			A__							:					List[str]       =	f"""The `{attribute}` argument is deprecated and will be removed in version {version_name}."""
		elif hasattr(lowercase_					,   lowercase_      ):
			values += (getattr(lowercase_					,   lowercase_      ),)
			A__							:					Optional[Any]       =	f"""The `{attribute}` attribute is deprecated and will be removed in version {version_name}."""
		elif deprecated_kwargs is None:
			A__							:					int       =	f"""`{attribute}` is deprecated and will be removed in version {version_name}."""

		if warning is not None:
			A__							:					int       =	warning + """ """ if standard_warn else """"""
			warnings.warn(warning + message					,   lowercase_					,   stacklevel=lowercase_      )

	if isinstance(lowercase_					,   lowercase_      ) and len(lowercase_      ) > 0:
		A__							:					Union[str, Any]       =	inspect.getouterframes(inspect.currentframe()      )[1]
		A__							:					Optional[Any]       =	call_frame.filename
		A__							:					Optional[int]       =	call_frame.lineno
		A__							:					Any       =	call_frame.function
		A__     ,     A__							:					List[str]       =	next(iter(deprecated_kwargs.items()      )      )
		raise TypeError(f"""{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`"""      )

	if len(lowercase_      ) == 0:
		return
	elif len(lowercase_      ) == 1:
		return values[0]
	return values






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


A_ :				Tuple						 =    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__:     List[str]													= JsonConfig






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






					def 						__A    (				self					, A__    ):
						if self.config.features is not None:
							# adding missing columns
							for column_name in set(self.config.features    ) - set(pa_table.column_names    ):
								A__							:					Optional[Any]       =	self.config.features.arrow_schema.field(A__    ).type
								A__							:					str       =	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
							A__							:					Optional[int]       =	table_cast(A__					, self.config.features.arrow_schema    )
						return pa_table






					def 						__A    (				self					, A__    ):
						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:
									A__							:					Optional[Any]       =	json.load(A__    )

								# We keep only the field we are interested in
								A__							:					Optional[int]       =	dataset[self.config.field]

								# We accept two format: a list of dicts or a dict of lists
								if isinstance(A__					, (list, tuple)    ):
									A__							:					Union[str, Any]       =	set().union(*[row.keys() for row in dataset]    )
									A__							:					Any       =	{col: [row.get(A__    ) for row in dataset] for col in keys}
								else:
									A__							:					Any       =	dataset
								A__							:					Any       =	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:
									A__							:					List[str]       =	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
									A__							:					List[str]       =	max(self.config.chunksize // 32					, 16 << 10    )
									A__							:					Any       =	(
									    self.config.encoding_errors if self.config.encoding_errors is not None else """strict"""
									)
									while True:
										A__							:					Dict       =	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":
											A__							:					List[Any]       =	batch.decode(self.config.encoding					, errors=A__    ).encode("""utf-8"""    )
										try:
											while True:
												try:
													A__							:					str       =	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:
													A__							:					Optional[Any]       =	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:
													A__							:					str       =	set().union(*[row.keys() for row in dataset]    )
													A__							:					List[str]       =	{col: [row.get(A__    ) for row in dataset] for col in keys}
													A__							:					int       =	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



