


'''simple docstring'''

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       a__				( __A      ):







    """simple docstring"""



    def __init__(self       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = None       ,			__lowercase = None       ,			__lowercase = False       ,			__lowercase = False       ,			__lowercase = None       ,			__lowercase = None       ,			**__lowercase       ,			):
          super().__init__(
              __lowercase       ,			split=__lowercase       ,			features=__lowercase       ,			cache_dir=__lowercase       ,			keep_in_memory=__lowercase       ,			streaming=__lowercase       ,			num_proc=__lowercase       ,			**__lowercase       ,			)
          __lowerCAmelCase							       =				field
          __lowerCAmelCase							       =				path_or_paths if isinstance(__lowercase       ,			__lowercase		) else {self.split: path_or_paths}
          __lowerCAmelCase							       =				Json(
              cache_dir=__lowercase       ,			data_files=__lowercase       ,			features=__lowercase       ,			field=__lowercase       ,			**__lowercase       ,			)




    def 					_snake_case  (self		):
          # Build iterable dataset
          if self.streaming:
                __lowerCAmelCase							       =				self.builder.as_streaming_dataset(split=self.split		)
          # Build regular (map-style) dataset
          else:
                __lowerCAmelCase							       =				None
                __lowerCAmelCase							       =				None
                __lowerCAmelCase							       =				None
                __lowerCAmelCase							       =				None

                self.builder.download_and_prepare(
                    download_config=__lowercase       ,			download_mode=__lowercase       ,			verification_mode=__lowercase       ,			base_path=__lowercase       ,			num_proc=self.num_proc       ,			)
                __lowerCAmelCase							       =				self.builder.as_dataset(
                    split=self.split       ,			verification_mode=__lowercase       ,			in_memory=self.keep_in_memory		)
          return dataset


class       a__				:







    """simple docstring"""



    def __init__(self       ,			__lowercase       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = None       ,			**__lowercase       ,			):
          if num_proc is not None and num_proc <= 0:
                raise ValueError(F"""num_proc {num_proc} must be an integer > 0."""		)

          __lowerCAmelCase							       =				dataset
          __lowerCAmelCase							       =				path_or_buf
          __lowerCAmelCase							       =				batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
          __lowerCAmelCase							       =				num_proc
          __lowerCAmelCase							       =				'''utf-8'''
          __lowerCAmelCase							       =				to_json_kwargs




    def 					_snake_case  (self		):
          __lowerCAmelCase							       =				self.to_json_kwargs.pop('''path_or_buf'''       ,			__lowercase		)
          __lowerCAmelCase							       =				self.to_json_kwargs.pop('''orient'''       ,			'''records'''		)
          __lowerCAmelCase							       =				self.to_json_kwargs.pop('''lines'''       ,			True if orient == '''records''' else False		)
          __lowerCAmelCase							       =				self.to_json_kwargs.pop('''index'''       ,			False if orient in ['''split''', '''table'''] else True		)
          __lowerCAmelCase							       =				self.to_json_kwargs.pop('''compression'''       ,			__lowercase		)

          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=__lowercase		) as buffer:
                      __lowerCAmelCase							       =				self._write(file_obj=__lowercase       ,			orient=__lowercase       ,			lines=__lowercase       ,			index=__lowercase       ,			**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.'''		)
                __lowerCAmelCase							       =				self._write(
                    file_obj=self.path_or_buf       ,			orient=__lowercase       ,			lines=__lowercase       ,			index=__lowercase       ,			**self.to_json_kwargs		)
          return written




    def 					_snake_case  (self       ,			__lowercase		):
          __lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase							       =				args

          __lowerCAmelCase							       =				query_table(
              table=self.dataset.data       ,			key=slice(__lowercase       ,			offset + self.batch_size		)       ,			indices=self.dataset._indices       ,			)
          __lowerCAmelCase							       =				batch.to_pandas().to_json(
              path_or_buf=__lowercase       ,			orient=__lowercase       ,			lines=__lowercase       ,			index=__lowercase       ,			**__lowercase		)
          if not json_str.endswith('''\n'''		):
                json_str += "\n"
          return json_str.encode(self.encoding		)




    def 					_snake_case  (self       ,			__lowercase       ,			__lowercase       ,			__lowercase       ,			__lowercase       ,			**__lowercase       ,			):
          __lowerCAmelCase							       =				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'''       ,			):
                      __lowerCAmelCase							       =				self._batch_json((offset, orient, lines, index, to_json_kwargs)		)
                      written += file_obj.write(__lowercase		)
          else:
                __lowerCAmelCase       ,					__lowerCAmelCase							       =				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       ,			__lowercase       ,			__lowercase		)]       ,			)       ,			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(__lowercase		)

          return written





'''simple docstring'''

from PIL import Image

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase):

						def brightness(lowerCamelCase) -> float:
												return 1_2_8 + level + (c - 1_2_8)

						if not -2_55.0 <= level <= 2_55.0:
												raise ValueError('''level must be between -255.0 (black) and 255.0 (white)''')
						return img.point(lowerCamelCase)


if __name__ == "__main__":
	# Load image
	with Image.open("""image_data/lena.jpg""") as img:
		# Change brightness to 100
		_UpperCAmelCase				: str							    =				change_brightness(img, 1_0_0)
		brigt_img.save("""image_data/lena_brightness.png""", format="""png""")

