



'''simple docstring'''



import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase_  :							int             =    logging.get_logger(__name__)

lowerCAmelCase_  :							str             =    '▁'

lowerCAmelCase_  :							Tuple             =    {
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
}

lowerCAmelCase_  :							List[Any]             =    {
    'vocab_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json'
        ),
    },
    'spm_file': {
        'facebook/s2t-small-librispeech-asr': (
            'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model'
        )
    },
}

lowerCAmelCase_  :							Tuple             =    {
    'facebook/s2t-small-librispeech-asr': 1024,
}

lowerCAmelCase_  :							Any             =    ['pt', 'fr', 'ru', 'nl', 'ro', 'it', 'es', 'de']

lowerCAmelCase_  :							int             =    {'mustc': MUSTC_LANGS}
class 						lowerCamelCase_				(       snake_case_      ):
						_lowerCAmelCase  : Any						  =					VOCAB_FILES_NAMES
						_lowerCAmelCase  : int						  =					PRETRAINED_VOCAB_FILES_MAP
						_lowerCAmelCase  : str						  =					MAX_MODEL_INPUT_SIZES
						_lowerCAmelCase  : List[Any]						  =					['input_ids', 'attention_mask']

						_lowerCAmelCase  : List[int]						  =					[]







						def __init__(	self :   List[Any]					,     lowerCAmelCase__ :   Union[str, Any]					,     lowerCAmelCase__ :   List[Any]					,     lowerCAmelCase__ :   Optional[int]="<s>"					,     lowerCAmelCase__ :   Dict="</s>"					,     lowerCAmelCase__ :   str="<pad>"					,     lowerCAmelCase__ :   List[Any]="<unk>"					,     lowerCAmelCase__ :   List[Any]=False					,     lowerCAmelCase__ :   Optional[Any]=False					,     lowerCAmelCase__ :   List[Any]=None					,     lowerCAmelCase__ :   Tuple=None					,     lowerCAmelCase__ :   Any = None					,     **lowerCAmelCase__ :   Dict					,     ):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Any         =      {} if sp_model_kwargs is None else sp_model_kwargs

													super().__init__(
													    bos_token=lowerCAmelCase__					,     eos_token=lowerCAmelCase__					,     unk_token=lowerCAmelCase__					,     pad_token=lowerCAmelCase__					,     do_upper_case=lowerCAmelCase__					,     do_lower_case=lowerCAmelCase__					,     tgt_lang=lowerCAmelCase__					,     lang_codes=lowerCAmelCase__					,     sp_model_kwargs=self.sp_model_kwargs					,     **lowerCAmelCase__					,     )
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      do_upper_case
													SCREAMING_SNAKE_CASE       :   str         =      do_lower_case

													SCREAMING_SNAKE_CASE       :   Dict         =      load_json(lowerCAmelCase__					)
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      {v: k for k, v in self.encoder.items()}
													SCREAMING_SNAKE_CASE       :   List[str]         =      spm_file
													SCREAMING_SNAKE_CASE       :   str         =      load_spm(lowerCAmelCase__					,     self.sp_model_kwargs					)

													if lang_codes is not None:
																				SCREAMING_SNAKE_CASE       :   Optional[Any]         =      lang_codes
																				SCREAMING_SNAKE_CASE       :   Optional[int]         =      LANGUAGES[lang_codes]
																				SCREAMING_SNAKE_CASE       :   Optional[Any]         =      [F"""<lang:{lang}>""" for lang in self.langs]
																				SCREAMING_SNAKE_CASE       :   str         =      {lang: self.sp_model.PieceToId(F"""<lang:{lang}>"""					) for lang in self.langs}

																				SCREAMING_SNAKE_CASE       :   List[Any]         =      self.lang_tokens
																				SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      tgt_lang if tgt_lang is not None else self.langs[0]

																				self.set_tgt_lang_special_tokens(self._tgt_lang					)
													else:
																				SCREAMING_SNAKE_CASE       :   Tuple         =      {}







						@property
						def        __lowercase     (	self :   Optional[Any]					):

													"""simple docstring"""
													return len(self.encoder					)







						@property
						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													return self._tgt_lang







						@tgt_lang.setter
						def        __lowercase     (	self :   Optional[int]					,     lowerCAmelCase__ :   Tuple					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[str]         =      new_tgt_lang
													self.set_tgt_lang_special_tokens(lowerCAmelCase__					)







						def        __lowercase     (	self :   Any					,     lowerCAmelCase__ :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   str         =      self.lang_code_to_id[tgt_lang]
													SCREAMING_SNAKE_CASE       :   str         =      [lang_code_id]







						def        __lowercase     (	self :   int					,     lowerCAmelCase__ :   Dict					):

													"""simple docstring"""
													return self.sp_model.encode(lowerCAmelCase__					,     out_type=lowerCAmelCase__					)







						def        __lowercase     (	self :   Optional[int]					,     lowerCAmelCase__ :   Dict					):

													"""simple docstring"""
													return self.encoder.get(lowerCAmelCase__					,     self.encoder[self.unk_token]					)







						def        __lowercase     (	self :   Tuple					,     lowerCAmelCase__ :   Union[str, Any]					):

													"""simple docstring"""
													return self.decoder.get(lowerCAmelCase__					,     self.unk_token					)







						def        __lowercase     (	self :   Optional[int]					,     lowerCAmelCase__ :   Union[str, Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[str]         =      []
													SCREAMING_SNAKE_CASE       :   List[Any]         =      ""
													for token in tokens:
																				# make sure that special tokens are not decoded using sentencepiece model
																				if token in self.all_special_tokens:
																											SCREAMING_SNAKE_CASE       :   List[str]         =      self.sp_model.decode(lowerCAmelCase__					)
																											out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
																											SCREAMING_SNAKE_CASE       :   List[Any]         =      []
																				else:
																											current_sub_tokens.append(lowerCAmelCase__					)
													SCREAMING_SNAKE_CASE       :   Tuple         =      self.sp_model.decode(lowerCAmelCase__					)
													out_string += decoded.upper() if self.do_upper_case else decoded
													return out_string.strip()







						def        __lowercase     (	self :   Dict					,     lowerCAmelCase__ :   str					,     lowerCAmelCase__ :   Any=None					):

													"""simple docstring"""

													if token_ids_a is None:
																				return self.prefix_tokens + token_ids_a + [self.eos_token_id]
													# We don't expect to process pairs, but leave the pair logic for API consistency
													return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]







						def        __lowercase     (	self :   Union[str, Any]					,     lowerCAmelCase__ :   Dict					,     lowerCAmelCase__ :   Any = None					,     lowerCAmelCase__ :   Optional[int] = False					):

													"""simple docstring"""

													if already_has_special_tokens:
																				return super().get_special_tokens_mask(
																				    token_ids_a=lowerCAmelCase__					,     token_ids_a=lowerCAmelCase__					,     already_has_special_tokens=lowerCAmelCase__					)

													SCREAMING_SNAKE_CASE       :   int         =      [1] * len(self.prefix_tokens					)
													SCREAMING_SNAKE_CASE       :   Dict         =      [1]
													if token_ids_a is None:
																				return prefix_ones + ([0] * len(lowerCAmelCase__					)) + suffix_ones
													return prefix_ones + ([0] * len(lowerCAmelCase__					)) + ([0] * len(lowerCAmelCase__					)) + suffix_ones







						def        __lowercase     (	self :   Dict					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Dict         =      self.encoder.copy()
													vocab.update(self.added_tokens_encoder					)
													return vocab







						def __getstate__(	self :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[Any]         =      self.__dict__.copy()
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      None
													return state







						def __setstate__(	self :   int					,     lowerCAmelCase__ :   List[str]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      d

													# for backward compatibility
													if not hasattr(self					,     '''sp_model_kwargs'''					):
																				SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      {}

													SCREAMING_SNAKE_CASE       :   Tuple         =      load_spm(self.spm_file					,     self.sp_model_kwargs					)







						def        __lowercase     (	self :   Union[str, Any]					,     lowerCAmelCase__ :   List[Any]					,     lowerCAmelCase__ :   Union[str, Any] = None					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Any         =      Path(lowerCAmelCase__					)
													assert save_dir.is_dir(), F"""{save_directory} should be a directory"""
													SCREAMING_SNAKE_CASE       :   Tuple         =      save_dir / (
													    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["vocab_file"]
													)
													SCREAMING_SNAKE_CASE       :   int         =      save_dir / (
													    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["spm_file"]
													)

													save_json(self.encoder					,     lowerCAmelCase__					)

													if os.path.abspath(self.spm_file					) != os.path.abspath(lowerCAmelCase__					) and os.path.isfile(self.spm_file					):
																				copyfile(self.spm_file					,     lowerCAmelCase__					)
													elif not os.path.isfile(self.spm_file					):
																				with open(lowerCAmelCase__					,     '''wb'''					) as fi:
																											SCREAMING_SNAKE_CASE       :   int         =      self.sp_model.serialized_model_proto()
																											fi.write(lowerCAmelCase__					)

													return (str(lowerCAmelCase__					), str(lowerCAmelCase__					))


def        UpperCAmelCase (    A	:					List[str]       ,		A	:					Any					):
							SCREAMING_SNAKE_CASE       :   List[Any]         =      sentencepiece.SentencePieceProcessor(**lowercase__					)
							spm.Load(str(lowercase__					)					)
							return spm
def        UpperCAmelCase (    A	:					Union[str, Any]					):
							with open(lowercase__       ,		'''r'''					) as f:
														return json.load(lowercase__					)






def        UpperCAmelCase (    A	:					str       ,		A	:					Optional[Any]					):
							with open(lowercase__       ,		'''w'''					) as f:
														json.dump(lowercase__       ,		lowercase__       ,		indent=2					)







"""simple docstring"""

import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__   )			->						Optional[Any]:
 assert isinstance(lowercase__					,					lowercase__   )
 assert dataset.num_rows == 4
 assert dataset.num_columns == 3
 assert dataset.column_names == ["col_1", "col_2", "col_3"]
 for feature, expected_dtype in expected_features.items():
  assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"					,					[False, True]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Any:
 lowerCAmelCase__   :				Optional[int] 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Dict 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
  lowerCAmelCase__   :				Tuple 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__					,					keep_in_memory=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



@pytest.mark.parametrize(
    "features"					,					[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]					,					)
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Tuple:
 lowerCAmelCase__   :				Union[str, Any] 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Tuple 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				List[Any] 			=				features.copy() if features else default_expected_features
 lowerCAmelCase__   :				int 			=				(
     Features({feature: Value(lowercase__   ) for feature, dtype in features.items()}   ) if features is not None else None
 )
 lowerCAmelCase__   :				Tuple 			=				JsonDatasetReader(lowercase__					,					features=lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



@pytest.mark.parametrize(
    "features"					,					[
        None,
        {"col_3": "float64", "col_1": "string", "col_2": "int64"},
    ]					,					)
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Optional[Any]:
 lowerCAmelCase__   :				Tuple 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Optional[Any] 			=				{"col_3": "float64", "col_1": "string", "col_2": "int64"}
 lowerCAmelCase__   :				List[str] 			=				features.copy() if features else default_expected_features
 lowerCAmelCase__   :				Dict 			=				(
     Features({feature: Value(lowercase__   ) for feature, dtype in features.items()}   ) if features is not None else None
 )
 lowerCAmelCase__   :				Dict 			=				JsonDatasetReader(lowercase__					,					features=lowercase__					,					cache_dir=lowercase__   ).read()
 assert isinstance(lowercase__					,					lowercase__   )
 assert dataset.num_rows == 2
 assert dataset.num_columns == 3
 assert dataset.column_names == ["col_3", "col_1", "col_2"]
 for feature, expected_dtype in expected_features.items():
  assert dataset.features[feature].dtype == expected_dtype



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__   )			->						Tuple:
 # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
 lowerCAmelCase__   :				Any 			=				{"col_2": "int64", "col_3": "float64", "col_1": "string"}
 lowerCAmelCase__   :				Union[str, Any] 			=				features.copy()
 lowerCAmelCase__   :				int 			=				(
     Features({feature: Value(lowercase__   ) for feature, dtype in features.items()}   ) if features is not None else None
 )
 lowerCAmelCase__   :				str 			=				tmp_path / "cache"
 lowerCAmelCase__   :				List[str] 			=				JsonDatasetReader(lowercase__					,					features=lowercase__					,					cache_dir=lowercase__   ).read()
 assert isinstance(lowercase__					,					lowercase__   )
 assert dataset.num_rows == 2
 assert dataset.num_columns == 3
 assert dataset.column_names == ["col_2", "col_3", "col_1"]
 for feature, expected_dtype in expected_features.items():
  assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("split"					,					[None, NamedSplit("train"   ), "train", "test"]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Optional[Any]:
 lowerCAmelCase__   :				Optional[int] 			=				tmp_path / "cache"
 lowerCAmelCase__   :				List[Any] 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				Dict 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__					,					split=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )
 assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"					,					[str, list]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Optional[Any]:
 if issubclass(lowercase__					,					lowercase__   ):
  lowerCAmelCase__   :				Dict 			=				jsonl_path
 elif issubclass(lowercase__					,					lowercase__   ):
  lowerCAmelCase__   :				Tuple 			=				[jsonl_path]
 lowerCAmelCase__   :				Any 			=				tmp_path / "cache"
 lowerCAmelCase__   :				List[str] 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				int 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__=("train",)   )			->						List[str]:
 assert isinstance(lowercase__					,					lowercase__   )
 for split in splits:
  lowerCAmelCase__   :				Dict 			=				dataset_dict[split]
  assert dataset.num_rows == 4
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_1", "col_2", "col_3"]
  for feature, expected_dtype in expected_features.items():
   assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"					,					[False, True]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						List[str]:
 lowerCAmelCase__   :				int 			=				tmp_path / "cache"
 lowerCAmelCase__   :				str 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
  lowerCAmelCase__   :				Dict 			=				JsonDatasetReader({"train": jsonl_path}					,					cache_dir=lowercase__					,					keep_in_memory=lowercase__   ).read()
 _check_json_datasetdict(lowercase__					,					lowercase__   )



@pytest.mark.parametrize(
    "features"					,					[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]					,					)
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						List[str]:
 lowerCAmelCase__   :				str 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Union[str, Any] 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				str 			=				features.copy() if features else default_expected_features
 lowerCAmelCase__   :				Dict 			=				(
     Features({feature: Value(lowercase__   ) for feature, dtype in features.items()}   ) if features is not None else None
 )
 lowerCAmelCase__   :				List[Any] 			=				JsonDatasetReader({"train": jsonl_path}					,					features=lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_datasetdict(lowercase__					,					lowercase__   )



@pytest.mark.parametrize("split"					,					[None, NamedSplit("train"   ), "train", "test"]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Dict:
 if split:
  lowerCAmelCase__   :				int 			=				{split: jsonl_path}
 else:
  lowerCAmelCase__   :				str 			=				"train"
  lowerCAmelCase__   :				Tuple 			=				{"train": jsonl_path, "test": jsonl_path}
 lowerCAmelCase__   :				Any 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Dict 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				int 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_datasetdict(lowercase__					,					lowercase__					,					splits=list(path.keys()   )   )
 assert all(dataset[split].split == split for split in path.keys()   )



def       SCREAMING_SNAKE_CASE							( lowercase__   )			->						List[Any]:
 return json.load(lowercase__   )



def       SCREAMING_SNAKE_CASE							( lowercase__   )			->						Optional[int]:
 return [json.loads(lowercase__   ) for line in buffer]






class 			__a					:





       """simple docstring"""


       @pytest.mark.parametrize("lines, load_json_function"			,					[(True, load_json_lines), (False, load_json)]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				int 			=				load_json_function(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        assert isinstance(exported_content[0]			,					snake_case   )
        assert len(snake_case   ) == 10






       @pytest.mark.parametrize(
           "orient, container, keys, len_at"			,					[
               ("records", list, {"tokens", "labels", "answers", "id"}, None),
               ("split", dict, {"columns", "data"}, "data"),
               ("index", dict, set("0123456789"   ), None),
               ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
               ("values", list, None, None),
               ("table", dict, {"schema", "data"}, "data"),
           ]			,					)
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					orient=snake_case   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				Optional[Any] 			=				load_json(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        if keys:
         if container is dict:
          assert exported_content.keys() == keys
         else:
          assert exported_content[0].keys() == keys
        else:
         assert not hasattr(snake_case			,					"keys"   ) and not hasattr(exported_content[0]			,					"keys"   )
        if len_at:
         assert len(exported_content[len_at]   ) == 10
        else:
         assert len(snake_case   ) == 10






       @pytest.mark.parametrize("lines, load_json_function"			,					[(True, load_json_lines), (False, load_json)]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					num_proc=2   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				int 			=				load_json_function(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        assert isinstance(exported_content[0]			,					snake_case   )
        assert len(snake_case   ) == 10






       @pytest.mark.parametrize(
           "orient, container, keys, len_at"			,					[
               ("records", list, {"tokens", "labels", "answers", "id"}, None),
               ("split", dict, {"columns", "data"}, "data"),
               ("index", dict, set("0123456789"   ), None),
               ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
               ("values", list, None, None),
               ("table", dict, {"schema", "data"}, "data"),
           ]			,					)
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					orient=snake_case			,					num_proc=2   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				Tuple 			=				load_json(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        if keys:
         if container is dict:
          assert exported_content.keys() == keys
         else:
          assert exported_content[0].keys() == keys
        else:
         assert not hasattr(snake_case			,					"keys"   ) and not hasattr(exported_content[0]			,					"keys"   )
        if len_at:
         assert len(exported_content[len_at]   ) == 10
        else:
         assert len(snake_case   ) == 10






       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case   ):





        """simple docstring"""

        with pytest.raises(snake_case   ):
         with io.BytesIO() as buffer:
          JsonDatasetWriter(snake_case			,					snake_case			,					num_proc=0   )






       @pytest.mark.parametrize("compression, extension"			,					[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        lowerCAmelCase__   :				Any 			=				tmp_path_factory.mktemp("data"   ) / F"""test.json.{extension}"""
        lowerCAmelCase__   :				str 			=				str(shared_datadir / F"""test_file.json.{extension}"""   )
        JsonDatasetWriter(snake_case			,					snake_case			,					compression=snake_case   ).write()

        with fsspec.open(snake_case			,					"rb"			,					compression="infer"   ) as f:
         lowerCAmelCase__   :				Optional[int] 			=				f.read()
        with fsspec.open(snake_case			,					"rb"			,					compression="infer"   ) as f:
         lowerCAmelCase__   :				Optional[int] 			=				f.read()
        assert exported_content == original_content






