


'''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  lowerCAmelCase_						(       snake_case__      ):





		"""simple docstring"""



		def __init__(					self     :							List[str]				,							SCREAMING_SNAKE_CASE__     :							NestedDataStructureLike[PathLike]				,							SCREAMING_SNAKE_CASE__     :							Optional[NamedSplit] = None				,							SCREAMING_SNAKE_CASE__     :							Optional[Features] = None				,							SCREAMING_SNAKE_CASE__     :							str = None				,							SCREAMING_SNAKE_CASE__     :							bool = False				,							SCREAMING_SNAKE_CASE__     :							bool = False				,							SCREAMING_SNAKE_CASE__     :							Optional[str] = None				,							SCREAMING_SNAKE_CASE__     :							Optional[int] = None				,							**SCREAMING_SNAKE_CASE__     :							Optional[int]				,							):





							'''simple docstring'''

							super().__init__(
							    SCREAMING_SNAKE_CASE__				,							split=SCREAMING_SNAKE_CASE__				,							features=SCREAMING_SNAKE_CASE__				,							cache_dir=SCREAMING_SNAKE_CASE__				,							keep_in_memory=SCREAMING_SNAKE_CASE__				,							streaming=SCREAMING_SNAKE_CASE__				,							num_proc=SCREAMING_SNAKE_CASE__				,							**SCREAMING_SNAKE_CASE__				,							)
							__a       =   field
							__a       =   path_or_paths if isinstance(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						) else {self.split: path_or_paths}
							__a       =   Json(
							    cache_dir=SCREAMING_SNAKE_CASE__				,							data_files=SCREAMING_SNAKE_CASE__				,							features=SCREAMING_SNAKE_CASE__				,							field=SCREAMING_SNAKE_CASE__				,							**SCREAMING_SNAKE_CASE__				,							)


		def __a						(					self     :							str						):





							'''simple docstring'''

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

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


class  lowerCAmelCase_						:





		"""simple docstring"""



		def __init__(					self     :							Optional[Any]				,							SCREAMING_SNAKE_CASE__     :							Dataset				,							SCREAMING_SNAKE_CASE__     :							Union[PathLike, BinaryIO]				,							SCREAMING_SNAKE_CASE__     :							Optional[int] = None				,							SCREAMING_SNAKE_CASE__     :							Optional[int] = None				,							**SCREAMING_SNAKE_CASE__     :							Optional[int]				,							):





							'''simple docstring'''

							if num_proc is not None and num_proc <= 0:
												raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''						)

							__a       =   dataset
							__a       =   path_or_buf
							__a       =   batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
							__a       =   num_proc
							__a       =   """utf-8"""
							__a       =   to_json_kwargs

		def __a						(					self     :							Optional[int]						):





							'''simple docstring'''

							__a       =   self.to_json_kwargs.pop("""path_or_buf"""				,							SCREAMING_SNAKE_CASE__						)
							__a       =   self.to_json_kwargs.pop("""orient"""				,							"""records"""						)
							__a       =   self.to_json_kwargs.pop("""lines"""				,							True if orient == """records""" else False						)
							__a       =   self.to_json_kwargs.pop("""index"""				,							False if orient in ["""split""", """table"""] else True						)
							__a       =   self.to_json_kwargs.pop("""compression"""				,							SCREAMING_SNAKE_CASE__						)

							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=SCREAMING_SNAKE_CASE__						) as buffer:
																	__a       =   self._write(file_obj=SCREAMING_SNAKE_CASE__				,							orient=SCREAMING_SNAKE_CASE__				,							lines=SCREAMING_SNAKE_CASE__				,							index=SCREAMING_SNAKE_CASE__				,							**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."""						)
												__a       =   self._write(
												    file_obj=self.path_or_buf				,							orient=SCREAMING_SNAKE_CASE__				,							lines=SCREAMING_SNAKE_CASE__				,							index=SCREAMING_SNAKE_CASE__				,							**self.to_json_kwargs						)
							return written

		def __a						(					self     :							Union[str, Any]				,							SCREAMING_SNAKE_CASE__     :							List[str]						):





							'''simple docstring'''

							__a ,						__a ,						__a ,						__a ,						__a       =   args

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


		def __a						(					self     :							List[Any]				,							SCREAMING_SNAKE_CASE__     :							BinaryIO				,							SCREAMING_SNAKE_CASE__     :							Dict				,							SCREAMING_SNAKE_CASE__     :							Dict				,							SCREAMING_SNAKE_CASE__     :							List[Any]				,							**SCREAMING_SNAKE_CASE__     :							Dict				,							):





							'''simple docstring'''

							__a       =   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"""				,							):
																	__a       =   self._batch_json((offset, orient, lines, index, to_json_kwargs)						)
																	written += file_obj.write(SCREAMING_SNAKE_CASE__						)
							else:
												__a ,						__a       =   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				,							SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)]				,							)				,							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(SCREAMING_SNAKE_CASE__						)

							return written










'''simple docstring'''







SCREAMING_SNAKE_CASE_      =			0  # The first color of the flag.
SCREAMING_SNAKE_CASE_      =			1  # The second color of the flag.
SCREAMING_SNAKE_CASE_      =			2  # The third color of the flag.
SCREAMING_SNAKE_CASE_      =			(red, white, blue)




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					list:
     """simple docstring"""




     if not sequence:
          return []
     if len(__SCREAMING_SNAKE_CASE		) == 1:
          return list(__SCREAMING_SNAKE_CASE		)
     __a       =   0
     __a       =   len(__SCREAMING_SNAKE_CASE		) - 1
     __a       =   0
     while mid <= high:
          if sequence[mid] == colors[0]:
               __a ,						__a       =   sequence[mid], sequence[low]
               low += 1
               mid += 1
          elif sequence[mid] == colors[1]:
               mid += 1
          elif sequence[mid] == colors[2]:
               __a ,						__a       =   sequence[high], sequence[mid]
               high -= 1
          else:
               __a       =   F'''The elements inside the sequence must contains only {colors} values'''
               raise ValueError(__SCREAMING_SNAKE_CASE		)
     return sequence


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 SCREAMING_SNAKE_CASE_      =			input('Enter numbers separated by commas:\n').strip()
 SCREAMING_SNAKE_CASE_      =			[int(item.strip()) for item in user_input.split(',')]
 print(f"""{dutch_national_flag_sort(unsorted)}""")






