



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 (     lowerCamelCase__       ):




				def __init__(							self						,				_snake_case						,				_snake_case = None						,				_snake_case = None						,				_snake_case = None						,				_snake_case = False						,				_snake_case = False						,				_snake_case = None						,				_snake_case = None						,				**_snake_case						,				):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





									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=_snake_case						,				download_mode=_snake_case						,				verification_mode=_snake_case						,				base_path=_snake_case						,				num_proc=self.num_proc						,				)
														_lowerCAmelCase						=    self.builder.as_dataset(
														    split=self.split						,				verification_mode=_snake_case						,				in_memory=self.keep_in_memory		)
									return dataset





class 					__lowerCAmelCase :




				def __init__(							self						,				_snake_case						,				_snake_case						,				_snake_case = None						,				_snake_case = None						,				**_snake_case						,				):



									"""simple docstring"""





									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		):



									"""simple docstring"""





									_lowerCAmelCase						=    self.to_json_kwargs.pop("""path_or_buf"""						,				_snake_case		)
									_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"""						,				_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=_snake_case		) as buffer:
																			_lowerCAmelCase						=    self._write(file_obj=_snake_case						,				orient=_snake_case						,				lines=_snake_case						,				index=_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."""		)
														_lowerCAmelCase						=    self._write(
														    file_obj=self.path_or_buf						,				orient=_snake_case						,				lines=_snake_case						,				index=_snake_case						,				**self.to_json_kwargs		)
									return written




				def 							snake_case   (							self						,				_snake_case		):



									"""simple docstring"""





									_lowerCAmelCase						=    args

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




				def 							snake_case   (							self						,				_snake_case						,				_snake_case						,				_snake_case						,				_snake_case						,				**_snake_case						,				):



									"""simple docstring"""





									_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(_snake_case		)
									else:
														_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						,				_snake_case						,				_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(_snake_case		)

									return written







"""simple docstring"""






import re
def      lowerCamelCase       (     _UpperCamelCase		:      str							)		->       str:

							'''simple docstring'''



							if len(re.findall("""[ATCG]"""       ,			_UpperCamelCase							)							) != len(_UpperCamelCase							):
														raise ValueError("""Invalid Strand"""							)

							return dna.translate(dna.maketrans("""ATCG"""       ,			"""TAGC"""							)							)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
