


"""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 			UpperCamelCase_     (			__SCREAMING_SNAKE_CASE):

	"""simple docstring"""





	def __init__(			self      :    Optional[Any]      ,      UpperCAmelCase__      :    Any      ,      UpperCAmelCase__      :    List[Any] = None      ,      UpperCAmelCase__      :    Any = None      ,      UpperCAmelCase__      :    Tuple = None      ,      UpperCAmelCase__      :    Tuple = False      ,      UpperCAmelCase__      :    int = False      ,      UpperCAmelCase__      :    Tuple = None      ,      UpperCAmelCase__      :    Tuple = None      ,      **UpperCAmelCase__      :    List[str]      ,      )	->     Union[str, Any]:
						super().__init__(
						    _a      ,      split=_a      ,      features=_a      ,      cache_dir=_a      ,      keep_in_memory=_a      ,      streaming=_a      ,      num_proc=_a      ,      **_a      ,      )
						__SCREAMING_SNAKE_CASE						       =    field
						__SCREAMING_SNAKE_CASE						       =    path_or_paths if isinstance(_a      ,      _a       ) else {self.split: path_or_paths}
						__SCREAMING_SNAKE_CASE						       =    Json(
						    cache_dir=_a      ,      data_files=_a      ,      features=_a      ,      field=_a      ,      **_a      ,      )




	def   UpperCAmelCase_				(			self      :    int       )	->     List[str]:
						# Build iterable dataset
						if self.streaming:
											__SCREAMING_SNAKE_CASE						       =    self.builder.as_streaming_dataset(split=self.split       )
						# Build regular (map-style) dataset
						else:
											__SCREAMING_SNAKE_CASE						       =    None
											__SCREAMING_SNAKE_CASE						       =    None
											__SCREAMING_SNAKE_CASE						       =    None
											__SCREAMING_SNAKE_CASE						       =    None

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




class 			UpperCamelCase_     :

	"""simple docstring"""





	def __init__(			self      :    Optional[int]      ,      UpperCAmelCase__      :    List[str]      ,      UpperCAmelCase__      :    Any      ,      UpperCAmelCase__      :    List[str] = None      ,      UpperCAmelCase__      :    Dict = None      ,      **UpperCAmelCase__      :    int      ,      )	->     Union[str, Any]:
						if num_proc is not None and num_proc <= 0:
											raise ValueError(F"""num_proc {num_proc} must be an integer > 0."""       )

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




	def   UpperCAmelCase_				(			self      :    Dict       )	->     Tuple:
						__SCREAMING_SNAKE_CASE						       =    self.to_json_kwargs.pop("path_or_buf"      ,      _a       )
						__SCREAMING_SNAKE_CASE						       =    self.to_json_kwargs.pop("orient"      ,      "records"       )
						__SCREAMING_SNAKE_CASE						       =    self.to_json_kwargs.pop("lines"      ,      True if orient == "records" else False       )
						__SCREAMING_SNAKE_CASE						       =    self.to_json_kwargs.pop("index"      ,      False if orient in ["split", "table"] else True       )
						__SCREAMING_SNAKE_CASE						       =    self.to_json_kwargs.pop("compression"      ,      _a       )

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




	def   UpperCAmelCase_				(			self      :    str      ,      UpperCAmelCase__      :    Optional[Any]       )	->     str:
						__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    args

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




	def   UpperCAmelCase_				(			self      :    Optional[int]      ,      UpperCAmelCase__      :    List[Any]      ,      UpperCAmelCase__      :    Tuple      ,      UpperCAmelCase__      :    int      ,      UpperCAmelCase__      :    Any      ,      **UpperCAmelCase__      :    Optional[int]      ,      )	->     Optional[int]:
						__SCREAMING_SNAKE_CASE						       =    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"      ,      ):
																__SCREAMING_SNAKE_CASE						       =    self._batch_json((offset, orient, lines, index, to_json_kwargs)       )
																written += file_obj.write(_a       )
						else:
											__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    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      ,      _a      ,      _a       )]      ,      )      ,      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(_a       )

						return written




"""simple docstring"""







def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


					return " ".join(
					    "".join(word[::-1]       ) if len(lowerCAmelCase_       ) > 4 else word for word in sentence.split()       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(reverse_long_words('''Hey wollef sroirraw'''))
