




import os
import re
import shutil
from argparse import ArgumentParser, Namespace

from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger


a													=			"<<<<<<< This should probably be modified because it mentions: "

a													=			"=======\n>>>>>>>\n"

a													=			[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

a													=			[
    # (pattern, replacement)
    # Order is important here for some replacements
    (r"tfds\.core", r"datasets"),
    (r"tf\.io\.gfile\.GFile", r"open"),
    (r"tf\.([\w\d]+)", r"datasets.Value('\1')"),
    (r"tfds\.features\.Text\(\)", r"datasets.Value('string')"),
    (r"tfds\.features\.Text\(", r"datasets.Value('string'),"),
    (r"features\s*=\s*tfds.features.FeaturesDict\(", r"features=datasets.Features("),
    (r"tfds\.features\.FeaturesDict\(", r"dict("),
    (r"The TensorFlow Datasets Authors", r"The TensorFlow Datasets Authors and the HuggingFace Datasets Authors"),
    (r"tfds\.", r"datasets."),
    (r"dl_manager\.manual_dir", r"self.config.data_dir"),
    (r"self\.builder_config", r"self.config"),
]




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				str:
						return ConvertCommand(args.tfds_path			,     args.datasets_directory       )




class       lowerCamelCase				(		__lowercase     ):






		@staticmethod
		def 				UpperCAmelCase (    _SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			parser.add_parser(
								    """convert"""						,		help="""Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."""						,		)
								train_parser.add_argument(
								    """--tfds_path"""						,		type=_SCREAMING_SNAKE_CASE						,		required=_SCREAMING_SNAKE_CASE						,		help="""Path to a TensorFlow Datasets folder to convert or a single tfds file to convert."""						,		)
								train_parser.add_argument(
								    """--datasets_directory"""						,		type=_SCREAMING_SNAKE_CASE						,		required=_SCREAMING_SNAKE_CASE						,		help="""Path to the HuggingFace Datasets folder."""			)
								train_parser.set_defaults(func=_SCREAMING_SNAKE_CASE			)






		def __init__(    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		*_SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			get_logger("""datasets-cli/converting"""			)

								_UpperCAmelCase      =			tfds_path
								_UpperCAmelCase      =			datasets_directory






		def 				UpperCAmelCase (    self			):
								if os.path.isdir(self._tfds_path			):
														_UpperCAmelCase      =			os.path.abspath(self._tfds_path			)
								elif os.path.isfile(self._tfds_path			):
														_UpperCAmelCase      =			os.path.dirname(self._tfds_path			)
								else:
														raise ValueError("""--tfds_path is neither a directory nor a file. Please check path."""			)

								_UpperCAmelCase      =			os.path.abspath(self._datasets_directory			)

								self._logger.info(F"Converting datasets from {abs_tfds_path} to {abs_datasets_path}"			)

								_UpperCAmelCase      =			[]
								_UpperCAmelCase      =			[]
								_UpperCAmelCase      =			{}

								if os.path.isdir(self._tfds_path			):
														_UpperCAmelCase      =			os.listdir(_SCREAMING_SNAKE_CASE			)
								else:
														_UpperCAmelCase      =			[os.path.basename(self._tfds_path			)]

								for f_name in file_names:
														self._logger.info(F"Looking at file {f_name}"			)
														_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
														_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)

														if not os.path.isfile(_SCREAMING_SNAKE_CASE			) or "__init__" in f_name or "_test" in f_name or ".py" not in f_name:
																				self._logger.info("""Skipping file"""			)
																				continue

														with open(_SCREAMING_SNAKE_CASE						,		encoding="""utf-8"""			) as f:
																				_UpperCAmelCase      =			f.readlines()

														_UpperCAmelCase      =			[]
														_UpperCAmelCase      =			False
														_UpperCAmelCase      =			False
														_UpperCAmelCase      =			[]
														for line in lines:
																				_UpperCAmelCase      =			line

																				# Convert imports
																				if "import tensorflow.compat.v2 as tf" in out_line:
																										continue
																				elif "@tfds.core" in out_line:
																										continue
																				elif "builder=self" in out_line:
																										continue
																				elif "import tensorflow_datasets.public_api as tfds" in out_line:
																										_UpperCAmelCase      =			"""import datasets\n"""
																				elif "import tensorflow" in out_line:
																										# order is important here
																										_UpperCAmelCase      =			""""""
																										continue
																				elif "from absl import logging" in out_line:
																										_UpperCAmelCase      =			"""from datasets import logging\n"""
																				elif "getLogger" in out_line:
																										_UpperCAmelCase      =			out_line.replace("""getLogger"""						,		"""get_logger"""			)
																				elif any(expression in out_line for expression in TO_HIGHLIGHT			):
																										_UpperCAmelCase      =			True
																										_UpperCAmelCase      =			list(filter(lambda _SCREAMING_SNAKE_CASE			: e in out_line						,		_SCREAMING_SNAKE_CASE			)			)
																										out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(_SCREAMING_SNAKE_CASE			) + """\n"""			)
																										out_lines.append(_SCREAMING_SNAKE_CASE			)
																										out_lines.append(_SCREAMING_SNAKE_CASE			)
																										continue
																				else:
																										for pattern, replacement in TO_CONVERT:
																																_UpperCAmelCase      =			re.sub(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)

                # Take care of saving utilities (to later move them together with main script)
																				if "tensorflow_datasets" in out_line:
																										_UpperCAmelCase      =			re.match(r"""from\stensorflow_datasets.*import\s([^\.\r\n]+)"""						,		_SCREAMING_SNAKE_CASE			)
																										tfds_imports.extend(imp.strip() for imp in match.group(1			).split(""","""			)			)
																										_UpperCAmelCase      =			"""from . import """ + match.group(1			)

																				# Check we have not forget anything
																				if "tf." in out_line or "tfds." in out_line or "tensorflow_datasets" in out_line:
																										raise ValueError(F"Error converting {out_line.strip()}"			)

																				if "GeneratorBasedBuilder" in out_line or "BeamBasedBuilder" in out_line:
																										_UpperCAmelCase      =			True
																				out_lines.append(_SCREAMING_SNAKE_CASE			)

														if is_builder or "wmt" in f_name:
																				# We create a new directory for each dataset
																				_UpperCAmelCase      =			f_name.replace(""".py"""						,		""""""			)
																				_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
																				_UpperCAmelCase      =			os.path.join(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
																				os.makedirs(_SCREAMING_SNAKE_CASE						,		exist_ok=_SCREAMING_SNAKE_CASE			)
																				self._logger.info(F"Adding directory {output_dir}"			)
																				imports_to_builder_map.update({imp: output_dir for imp in tfds_imports}			)
														else:
																				# Utilities will be moved at the end
																				utils_files.append(_SCREAMING_SNAKE_CASE			)

														if needs_manual_update:
																				with_manual_update.append(_SCREAMING_SNAKE_CASE			)

														with open(_SCREAMING_SNAKE_CASE						,		"""w"""						,		encoding="""utf-8"""			) as f:
																				f.writelines(_SCREAMING_SNAKE_CASE			)
														self._logger.info(F"Converted in {output_file}"			)

								for utils_file in utils_files:
														try:
																				_UpperCAmelCase      =			os.path.basename(_SCREAMING_SNAKE_CASE			)
																				_UpperCAmelCase      =			imports_to_builder_map[f_name.replace(""".py"""						,		""""""			)]
																				self._logger.info(F"Moving {dest_folder} to {utils_file}"			)
																				shutil.copy(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
														except KeyError:
																				self._logger.error(F"Cannot find destination folder for {utils_file}. Please copy manually."			)

								if with_manual_update:
														for file_path in with_manual_update:
																				self._logger.warning(
																				    F"You need to manually update file {file_path} to remove configurations using 'TextEncoderConfig'."			)





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      (		snake_case			,     snake_case       )						->				int:
						assert isinstance(snake_case			,     snake_case       )
						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      (		snake_case			,     snake_case			,     snake_case       )						->				Optional[int]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case			,     keep_in_memory=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




@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      (		snake_case			,     snake_case			,     snake_case       )						->				Optional[Any]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




@pytest.mark.parametrize(
    """features"""			,     [
        None,
        {"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""},
    ]			,     )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				int:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_3""": """float64""", """col_1""": """string""", """col_2""": """int64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						assert isinstance(snake_case			,     snake_case       )
						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      (		snake_case			,     snake_case       )						->				Optional[int]:
						# jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
						_UpperCAmelCase      =			{"""col_2""": """int64""", """col_3""": """float64""", """col_1""": """string"""}
						_UpperCAmelCase      =			features.copy()
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     features=snake_case			,     cache_dir=snake_case       ).read()
						assert isinstance(snake_case			,     snake_case       )
						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      (		snake_case			,     snake_case			,     snake_case       )						->				List[Any]:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case			,     split=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )
						assert dataset.split == split if split else "train"




@pytest.mark.parametrize("""path_type"""			,     [str, list]       )
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case       )						->				Any:
						if issubclass(snake_case			,     snake_case       ):
												_UpperCAmelCase      =			jsonl_path
						elif issubclass(snake_case			,     snake_case       ):
												_UpperCAmelCase      =			[jsonl_path]
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			JsonDatasetReader(snake_case			,     cache_dir=snake_case       ).read()
						_check_json_dataset(snake_case			,     snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case=("train",)       )						->				str:
						assert isinstance(snake_case			,     snake_case       )
						for split in splits:
												_UpperCAmelCase      =			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      (		snake_case			,     snake_case			,     snake_case       )						->				str:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
												_UpperCAmelCase      =			JsonDatasetReader({"""train""": jsonl_path}			,     cache_dir=snake_case			,     keep_in_memory=snake_case       ).read()
						_check_json_datasetdict(snake_case			,     snake_case       )




@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      (		snake_case			,     snake_case			,     snake_case       )						->				Tuple:
						_UpperCAmelCase      =			tmp_path / """cache"""
						_UpperCAmelCase      =			{"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
						_UpperCAmelCase      =			features.copy() if features else default_expected_features
						_UpperCAmelCase      =			(
						    Features({feature: Value(snake_case       ) for feature, dtype in features.items()}       ) if features is not None else None
						)
						_UpperCAmelCase      =			JsonDatasetReader({"""train""": jsonl_path}			,     features=snake_case			,     cache_dir=snake_case       ).read()
						_check_json_datasetdict(snake_case			,     snake_case       )




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




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				List[Any]:
						return json.load(snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				List[Any]:
						return [json.loads(snake_case       ) for line in buffer]




class       _A				:






		@pytest.mark.parametrize("""lines, load_json_function"""						,		[(True, load_json_lines), (False, load_json)]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json_function(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								assert isinstance(exported_content[0]						,		_SCREAMING_SNAKE_CASE			)
								assert len(_SCREAMING_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 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		orient=_SCREAMING_SNAKE_CASE			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								if keys:
														if container is dict:
																				assert exported_content.keys() == keys
														else:
																				assert exported_content[0].keys() == keys
								else:
														assert not hasattr(_SCREAMING_SNAKE_CASE						,		"""keys"""			) and not hasattr(exported_content[0]						,		"""keys"""			)
								if len_at:
														assert len(exported_content[len_at]			) == 10
								else:
														assert len(_SCREAMING_SNAKE_CASE			) == 10






		@pytest.mark.parametrize("""lines, load_json_function"""						,		[(True, load_json_lines), (False, load_json)]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		num_proc=2			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json_function(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								assert isinstance(exported_content[0]						,		_SCREAMING_SNAKE_CASE			)
								assert len(_SCREAMING_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 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								with io.BytesIO() as buffer:
														JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		lines=_SCREAMING_SNAKE_CASE						,		orient=_SCREAMING_SNAKE_CASE						,		num_proc=2			).write()
														buffer.seek(0			)
														_UpperCAmelCase      =			load_json(_SCREAMING_SNAKE_CASE			)
								assert isinstance(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			)
								if keys:
														if container is dict:
																				assert exported_content.keys() == keys
														else:
																				assert exported_content[0].keys() == keys
								else:
														assert not hasattr(_SCREAMING_SNAKE_CASE						,		"""keys"""			) and not hasattr(exported_content[0]						,		"""keys"""			)
								if len_at:
														assert len(exported_content[len_at]			) == 10
								else:
														assert len(_SCREAMING_SNAKE_CASE			) == 10






		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE			):
								with pytest.raises(_SCREAMING_SNAKE_CASE			):
														with io.BytesIO() as buffer:
																				JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		num_proc=0			)






		@pytest.mark.parametrize("""compression, extension"""						,		[("""gzip""", """gz"""), ("""bz2""", """bz2"""), ("""xz""", """xz""")]			)
		def 				UpperCAmelCase (    self						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE			):
								_UpperCAmelCase      =			tmp_path_factory.mktemp("""data"""			) / F"test.json.{extension}"
								_UpperCAmelCase      =			str(shared_datadir / F"test_file.json.{extension}"			)
								JsonDatasetWriter(_SCREAMING_SNAKE_CASE						,		_SCREAMING_SNAKE_CASE						,		compression=_SCREAMING_SNAKE_CASE			).write()

								with fsspec.open(_SCREAMING_SNAKE_CASE						,		"""rb"""						,		compression="""infer"""			) as f:
														_UpperCAmelCase      =			f.read()
								with fsspec.open(_SCREAMING_SNAKE_CASE						,		"""rb"""						,		compression="""infer"""			) as f:
														_UpperCAmelCase      =			f.read()
								assert exported_content == original_content