import argparse
import os
import re


SCREAMING_SNAKE_CASE			:						str				  =		"""src/transformers"""

# Pattern that looks at the indentation in a line.
SCREAMING_SNAKE_CASE			:						Optional[int]				  =		re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
SCREAMING_SNAKE_CASE			:						List[Any]				  =		re.compile(R"""^\s*\"([^\"]+)\":""")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
SCREAMING_SNAKE_CASE			:						Optional[int]				  =		re.compile(R"""^\s*_import_structure\[\"([^\"]+)\"\]""")
# Pattern that matches `"key",` and puts `key` in group 0.
SCREAMING_SNAKE_CASE			:						Tuple				  =		re.compile(R"""^\s*\"([^\"]+)\",\s*$""")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
SCREAMING_SNAKE_CASE			:						int				  =		re.compile(R"""\[([^\]]+)\]""")



def 	__A		(      _A       ):



 """simple docstring"""


 __a							=	_re_indent.search(_UpperCAmelCase       )
 return "" if search is None else search.groups()[0]



def 	__A		(      _A				,					_A=""				,					_A=None				,					_A=None       ):



 """simple docstring"""


 __a							=	0
 __a							=	code.split("\n"       )
 if start_prompt is not None:
  while not lines[index].startswith(_UpperCAmelCase       ):
   index += 1
  __a							=	["\n".join(lines[:index]       )]
 else:
  __a							=	[]

 # We split into blocks until we get to the `end_prompt` (or the end of the block).
 __a							=	[lines[index]]
 index += 1
 while index < len(_UpperCAmelCase       ) and (end_prompt is None or not lines[index].startswith(_UpperCAmelCase       )):
  if len(lines[index]       ) > 0 and get_indent(lines[index]       ) == indent_level:
   if len(_UpperCAmelCase       ) > 0 and get_indent(current_block[-1]       ).startswith(indent_level + " "       ):
    current_block.append(lines[index]       )
    blocks.append("\n".join(_UpperCAmelCase       )       )
    if index < len(_UpperCAmelCase       ) - 1:
     __a							=	[lines[index + 1]]
     index += 1
    else:
     __a							=	[]
   else:
    blocks.append("\n".join(_UpperCAmelCase       )       )
    __a							=	[lines[index]]
  else:
   current_block.append(lines[index]       )
  index += 1

 # Adds current block if it's nonempty.
 if len(_UpperCAmelCase       ) > 0:
  blocks.append("\n".join(_UpperCAmelCase       )       )

 # Add final block after end_prompt if provided.
 if end_prompt is not None and index < len(_UpperCAmelCase       ):
  blocks.append("\n".join(lines[index:]       )       )

 return blocks



def 	__A		(      _A       ):



 """simple docstring"""


 def _inner(_A       ):
  return key(_UpperCAmelCase       ).lower().replace("_"				,					""       )

 return _inner



def 	__A		(      _A				,					_A=None       ):



 """simple docstring"""


 def noop(_A       ):
  return x

 if key is None:
  __a							=	noop
 # Constants are all uppercase, they go first.
 __a							=	[obj for obj in objects if key(_UpperCAmelCase       ).isupper()]
 # Classes are not all uppercase but start with a capital, they go second.
 __a							=	[obj for obj in objects if key(_UpperCAmelCase       )[0].isupper() and not key(_UpperCAmelCase       ).isupper()]
 # Functions begin with a lowercase, they go last.
 __a							=	[obj for obj in objects if not key(_UpperCAmelCase       )[0].isupper()]

 __a							=	ignore_underscore(_UpperCAmelCase       )
 return sorted(_UpperCAmelCase				,					key=_UpperCAmelCase       ) + sorted(_UpperCAmelCase				,					key=_UpperCAmelCase       ) + sorted(_UpperCAmelCase				,					key=_UpperCAmelCase       )



def 	__A		(      _A       ):



 """simple docstring"""


 def _replace(_A       ):
  __a							=	match.groups()[0]
  if "," not in imports:
   return f"""[{imports}]"""
  __a							=	[part.strip().replace("\""				,					""       ) for part in imports.split(","       )]
  # We will have a final empty element if the line finished with a comma.
  if len(keys[-1]       ) == 0:
   __a							=	keys[:-1]
  return "[" + ", ".join([f"""\"{k}\"""" for k in sort_objects(_UpperCAmelCase       )]       ) + "]"

 __a							=	import_statement.split("\n"       )
 if len(_UpperCAmelCase       ) > 3:
  # Here we have to sort internal imports that are on several lines (one per name):
  # key: [
  #     "object1",
  #     "object2",
  #     ...
  # ]

  # We may have to ignore one or two lines on each side.
  __a							=	2 if lines[1].strip() == "[" else 1
  __a							=	[(i, _re_strip_line.search(_UpperCAmelCase       ).groups()[0]) for i, line in enumerate(lines[idx:-idx]       )]
  __a							=	sort_objects(_UpperCAmelCase				,					key=lambda _A       : x[1]       )
  __a							=	[lines[x[0] + idx] for x in sorted_indices]
  return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]       )
 elif len(_UpperCAmelCase       ) == 3:
  # Here we have to sort internal imports that are on one separate line:
  # key: [
  #     "object1", "object2", ...
  # ]
  if _re_bracket_content.search(lines[1]       ) is not None:
   __a							=	_re_bracket_content.sub(_replace				,					lines[1]       )
  else:
   __a							=	[part.strip().replace("\""				,					""       ) for part in lines[1].split(","       )]
   # We will have a final empty element if the line finished with a comma.
   if len(keys[-1]       ) == 0:
    __a							=	keys[:-1]
   __a							=	get_indent(lines[1]       ) + ", ".join([f"""\"{k}\"""" for k in sort_objects(_UpperCAmelCase       )]       )
  return "\n".join(_UpperCAmelCase       )
 else:
  # Finally we have to deal with imports fitting on one line
  __a							=	_re_bracket_content.sub(_replace				,					_UpperCAmelCase       )
  return import_statement



def 	__A		(      _A				,					_A=True       ):



 """simple docstring"""


 with open(_UpperCAmelCase				,					encoding="utf-8"       ) as f:
  __a							=	f.read()

 if "_import_structure" not in code:
  return

 # Blocks of indent level 0
 __a							=	split_code_in_indented_blocks(
     _UpperCAmelCase				,					start_prompt="_import_structure = {"				,					end_prompt="if TYPE_CHECKING:"       )

 # We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
 for block_idx in range(1				,					len(_UpperCAmelCase       ) - 1       ):
  # Check if the block contains some `_import_structure`s thingy to sort.
  __a							=	main_blocks[block_idx]
  __a							=	block.split("\n"       )

  # Get to the start of the imports.
  __a							=	0
  while line_idx < len(_UpperCAmelCase       ) and "_import_structure" not in block_lines[line_idx]:
   # Skip dummy import blocks
   if "import dummy" in block_lines[line_idx]:
    __a							=	len(_UpperCAmelCase       )
   else:
    line_idx += 1
  if line_idx >= len(_UpperCAmelCase       ):
   continue

  # Ignore beginning and last line: they don't contain anything.
  __a							=	"\n".join(block_lines[line_idx:-1]       )
  __a							=	get_indent(block_lines[1]       )
  # Slit the internal block into blocks of indent level 1.
  __a							=	split_code_in_indented_blocks(_UpperCAmelCase				,					indent_level=_UpperCAmelCase       )
  # We have two categories of import key: list or _import_structure[key].append/extend
  __a							=	_re_direct_key if "_import_structure = {" in block_lines[0] else _re_indirect_key
  # Grab the keys, but there is a trap: some lines are empty or just comments.
  __a							=	[(pattern.search(_UpperCAmelCase       ).groups()[0] if pattern.search(_UpperCAmelCase       ) is not None else None) for b in internal_blocks]
  # We only sort the lines with a key.
  __a							=	[(i, key) for i, key in enumerate(_UpperCAmelCase       ) if key is not None]
  __a							=	[x[0] for x in sorted(_UpperCAmelCase				,					key=lambda _A       : x[1]       )]

  # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
  __a							=	0
  __a							=	[]
  for i in range(len(_UpperCAmelCase       )       ):
   if keys[i] is None:
    reorderded_blocks.append(internal_blocks[i]       )
   else:
    __a							=	sort_objects_in_import(internal_blocks[sorted_indices[count]]       )
    reorderded_blocks.append(_UpperCAmelCase       )
    count += 1

        # And we put our main block back together with its first and last line.
  __a							=	"\n".join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]       )

 if code != "\n".join(_UpperCAmelCase       ):
  if check_only:
   return True
  else:
   print(f"""Overwriting {file}."""       )
   with open(_UpperCAmelCase				,					"w"				,					encoding="utf-8"       ) as f:
    f.write("\n".join(_UpperCAmelCase       )       )



def 	__A		(      _A=True       ):



 """simple docstring"""


 __a							=	[]
 for root, _, files in os.walk(_UpperCAmelCase       ):
  if "__init__.py" in files:
   __a							=	sort_imports(os.path.join(_UpperCAmelCase				,					"__init__.py"       )				,					check_only=_UpperCAmelCase       )
   if result:
    __a							=	[os.path.join(_UpperCAmelCase				,					"__init__.py"       )]
 if len(_UpperCAmelCase       ) > 0:
  raise ValueError(f"""Would overwrite {len(_UpperCAmelCase       )} files, run `make style`."""       )


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE			:						Dict				  =		argparse.ArgumentParser()
  parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
  SCREAMING_SNAKE_CASE			:						List[str]				  =		parser.parse_args()

  sort_imports_in_all_inits(check_only=args.check_only)




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




