



'''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_       (       _a	):
    """simple docstring"""







    def __init__(    self					:     Optional[Any] ,     snake_case_					:     NestedDataStructureLike[PathLike] ,     snake_case_					:     Optional[NamedSplit] = None ,     snake_case_					:     Optional[Features] = None ,     snake_case_					:     str = None ,     snake_case_					:     bool = False ,     snake_case_					:     bool = False ,     snake_case_					:     Optional[str] = None ,     snake_case_					:     Optional[int] = None ,     **snake_case_					:     List[Any] ,     ):
          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_ ,     )
          snake_case__  :    Any    						=      field
          snake_case__  :    Optional[Any]    						=      path_or_paths if isinstance(snake_case_ ,     snake_case_						) else {self.split: path_or_paths}
          snake_case__  :    Any    						=      Json(
              cache_dir=snake_case_ ,     data_files=snake_case_ ,     features=snake_case_ ,     field=snake_case_ ,     **snake_case_ ,     )




    def lowerCamelCase       (    self					:     int						):
          # Build iterable dataset
          if self.streaming:
                snake_case__  :    int    						=      self.builder.as_streaming_dataset(split=self.split						)
          # Build regular (map-style) dataset
          else:
                snake_case__  :    Union[str, Any]    						=      None
                snake_case__  :    Tuple    						=      None
                snake_case__  :    Tuple    						=      None
                snake_case__  :    List[str]    						=      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 ,     )
                snake_case__  :    Dict    						=      self.builder.as_dataset(
                    split=self.split ,     verification_mode=snake_case_ ,     in_memory=self.keep_in_memory						)
          return dataset







class     UpperCAmelCase_       :
    """simple docstring"""







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

          snake_case__  :    Optional[int]    						=      dataset
          snake_case__  :    int    						=      path_or_buf
          snake_case__  :    Union[str, Any]    						=      batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
          snake_case__  :    int    						=      num_proc
          snake_case__  :    Optional[int]    						=      """utf-8"""
          snake_case__  :    Any    						=      to_json_kwargs




    def lowerCamelCase       (    self					:     List[Any]						):
          snake_case__  :    List[Any]    						=      self.to_json_kwargs.pop("""path_or_buf""" ,     snake_case_						)
          snake_case__  :    List[Any]    						=      self.to_json_kwargs.pop("""orient""" ,     """records"""						)
          snake_case__  :    Any    						=      self.to_json_kwargs.pop("""lines""" ,     True if orient == """records""" else False						)
          snake_case__  :    Union[str, Any]    						=      self.to_json_kwargs.pop("""index""" ,     False if orient in ["""split""", """table"""] else True						)
          snake_case__  :    Tuple    						=      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:
                      snake_case__  :    List[Any]    						=      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."""						)
                snake_case__  :    str    						=      self._write(
                    file_obj=self.path_or_buf ,     orient=snake_case_ ,     lines=snake_case_ ,     index=snake_case_ ,     **self.to_json_kwargs						)
          return written




    def lowerCamelCase       (    self					:     str ,     snake_case_					:     Dict						):
          snake_case__						,				snake_case__						,				snake_case__						,				snake_case__						,				snake_case__  :    Any    						=      args

          snake_case__  :    Optional[int]    						=      query_table(
              table=self.dataset.data ,     key=slice(snake_case_ ,     offset + self.batch_size						) ,     indices=self.dataset._indices ,     )
          snake_case__  :    int    						=      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 lowerCamelCase       (    self					:     Tuple ,     snake_case_					:     BinaryIO ,     snake_case_					:     List[Any] ,     snake_case_					:     str ,     snake_case_					:     Dict ,     **snake_case_					:     Dict ,     ):
          snake_case__  :    Tuple    						=      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""" ,     ):
                      snake_case__  :    List[Any]    						=      self._batch_json((offset, orient, lines, index, to_json_kwargs)						)
                      written += file_obj.write(snake_case_						)
          else:
                snake_case__						,				snake_case__  :    Optional[int]    						=      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 os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


UpperCamelCase__    					=      namedtuple(
    '''_TestCommandArgs''',
    [
        '''dataset''',
        '''name''',
        '''cache_dir''',
        '''data_dir''',
        '''all_configs''',
        '''save_infos''',
        '''ignore_verifications''',
        '''force_redownload''',
        '''clear_cache''',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)





def 					a__       (					lowerCAmelCase__  ,					lowerCAmelCase__						)    ->	Optional[int]:
    return (abs(source - target						) / target) < 0.0_1







@pytest.mark.integration
def 					a__       (					lowerCAmelCase__						)    ->	Optional[int]:
    UpperCAmelCase__			:		str													=				_TestCommandArgs(dataset=lowerCAmelCase__  ,					all_configs=lowerCAmelCase__  ,					save_infos=lowerCAmelCase__						)
    UpperCAmelCase__			:		Tuple													=				TestCommand(*lowerCAmelCase__						)
    test_command.run()
    UpperCAmelCase__			:		List[Any]													=				os.path.join(lowerCAmelCase__  ,					'''README.md'''						)
    assert os.path.exists(lowerCAmelCase__						)
    UpperCAmelCase__			:		List[str]													=				DatasetInfosDict.from_directory(lowerCAmelCase__						)
    UpperCAmelCase__			:		Any													=				DatasetInfosDict(
        {
            '''default''': DatasetInfo(
                features=Features(
                    {
                        '''tokens''': Sequence(Value('''string'''						)						),
                        '''ner_tags''': Sequence(
                            ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']						)						),
                        '''langs''': Sequence(Value('''string'''						)						),
                        '''spans''': Sequence(Value('''string'''						)						),
                    }						)  ,					splits=[
                    {
                        '''name''': '''train''',
                        '''num_bytes''': 2_35_15_63,
                        '''num_examples''': 1_00_00,
                    },
                    {
                        '''name''': '''validation''',
                        '''num_bytes''': 23_84_18,
                        '''num_examples''': 10_00,
                    },
                ]  ,					download_size=3_94_06_80  ,					dataset_size=2_58_99_81  ,					)
        }						)
    assert dataset_infos.keys() == expected_dataset_infos.keys()
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        UpperCAmelCase__						,						UpperCAmelCase__			:		str													=				getattr(dataset_infos['''default''']  ,					lowerCAmelCase__						), getattr(expected_dataset_infos['''default''']  ,					lowerCAmelCase__						)
        if key == "num_bytes":
            assert is_apercent_close(lowerCAmelCase__  ,					lowerCAmelCase__						)
        elif key == "splits":
            assert list(lowerCAmelCase__						) == list(lowerCAmelCase__						)
            for split in result:
                assert result[split].name == expected[split].name
                assert result[split].num_examples == expected[split].num_examples
                assert is_apercent_close(result[split].num_bytes  ,					expected[split].num_bytes						)
        else:
            result == expected
