"""simple docstring"""







import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[str]     ,				UpperCAmelCase_       :							Optional[int]    )				->     List[str]:

	'''simple docstring'''





	assert isinstance(UpperCAmelCase_     ,				UpperCAmelCase_    )
	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     __UpperCAmelCase							(       UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							List[str]    )				->     List[str]:

	'''simple docstring'''





	__snake_case     :				Optional[int] 						=					tmp_path / 'cache'
	__snake_case     :				Union[str, Any] 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__snake_case     :				str 						=					CsvDatasetReader(UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_     ,				keep_in_memory=UpperCAmelCase_    ).read()
	_check_csv_dataset(UpperCAmelCase_     ,				UpperCAmelCase_    )
@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     __UpperCAmelCase							(       UpperCAmelCase_       :							Dict     ,				UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							List[str]    )				->     Union[str, Any]:

	'''simple docstring'''





	__snake_case     :				int 						=					tmp_path / 'cache'
	# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
	__snake_case     :				Any 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	__snake_case     :				Union[str, Any] 						=					features.copy() if features else default_expected_features
	__snake_case     :				Optional[Any] 						=					(
	    Features({feature: Value(UpperCAmelCase_    ) for feature, dtype in features.items()}    ) if features is not None else None
	)
	__snake_case     :				List[Any] 						=					CsvDatasetReader(UpperCAmelCase_     ,				features=UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_    ).read()
	_check_csv_dataset(UpperCAmelCase_     ,				UpperCAmelCase_    )
@pytest.mark.parametrize('split'     ,				[None, NamedSplit('train'    ), 'train', 'test']    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							Any     ,				UpperCAmelCase_       :							List[str]    )				->     List[Any]:

	'''simple docstring'''





	__snake_case     :				str 						=					tmp_path / 'cache'
	__snake_case     :				Optional[int] 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	__snake_case     :				Dict 						=					CsvDatasetReader(UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_     ,				split=UpperCAmelCase_    ).read()
	_check_csv_dataset(UpperCAmelCase_     ,				UpperCAmelCase_    )
	assert dataset.split == split if split else "train"
@pytest.mark.parametrize('path_type'     ,				[str, list]    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Any     ,				UpperCAmelCase_       :							Optional[int]     ,				UpperCAmelCase_       :							List[str]    )				->     Optional[int]:

	'''simple docstring'''





	if issubclass(UpperCAmelCase_     ,				UpperCAmelCase_    ):
		__snake_case     :				int 						=					csv_path
	elif issubclass(UpperCAmelCase_     ,				UpperCAmelCase_    ):
		__snake_case     :				Dict 						=					[csv_path]
	__snake_case     :				List[str] 						=					tmp_path / 'cache'
	__snake_case     :				int 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	__snake_case     :				Any 						=					CsvDatasetReader(UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_    ).read()
	_check_csv_dataset(UpperCAmelCase_     ,				UpperCAmelCase_    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]     ,				UpperCAmelCase_       :							Optional[int]     ,				UpperCAmelCase_       :							Optional[Any]=("train",)    )				->     Any:

	'''simple docstring'''





	assert isinstance(UpperCAmelCase_     ,				UpperCAmelCase_    )
	for split in splits:
		__snake_case     :				List[str] 						=					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     __UpperCAmelCase							(       UpperCAmelCase_       :							Union[str, Any]     ,				UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							Tuple    )				->     Union[str, Any]:

	'''simple docstring'''





	__snake_case     :				List[Any] 						=					tmp_path / 'cache'
	__snake_case     :				Tuple 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__snake_case     :				str 						=					CsvDatasetReader({'train': csv_path}     ,				cache_dir=UpperCAmelCase_     ,				keep_in_memory=UpperCAmelCase_    ).read()
	_check_csv_datasetdict(UpperCAmelCase_     ,				UpperCAmelCase_    )
@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     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[int]     ,				UpperCAmelCase_       :							Any     ,				UpperCAmelCase_       :							int    )				->     Optional[int]:

	'''simple docstring'''





	__snake_case     :				Any 						=					tmp_path / 'cache'
	# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
	__snake_case     :				int 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	__snake_case     :				Dict 						=					features.copy() if features else default_expected_features
	__snake_case     :				Any 						=					(
	    Features({feature: Value(UpperCAmelCase_    ) for feature, dtype in features.items()}    ) if features is not None else None
	)
	__snake_case     :				int 						=					CsvDatasetReader({'train': csv_path}     ,				features=UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_    ).read()
	_check_csv_datasetdict(UpperCAmelCase_     ,				UpperCAmelCase_    )
@pytest.mark.parametrize('split'     ,				[None, NamedSplit('train'    ), 'train', 'test']    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Dict     ,				UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							Tuple    )				->     str:

	'''simple docstring'''





	if split:
		__snake_case     :				Optional[int] 						=					{split: csv_path}
	else:
		__snake_case     :				int 						=					{'train': csv_path, 'test': csv_path}
	__snake_case     :				Optional[Any] 						=					tmp_path / 'cache'
	__snake_case     :				Any 						=					{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
	__snake_case     :				List[Any] 						=					CsvDatasetReader(UpperCAmelCase_     ,				cache_dir=UpperCAmelCase_    ).read()
	_check_csv_datasetdict(UpperCAmelCase_     ,				UpperCAmelCase_     ,				splits=list(path.keys()    )    )
	assert all(dataset[split].split == split for split in path.keys()    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[int]    )				->     Optional[int]:

	'''simple docstring'''





	with open(UpperCAmelCase_     ,				encoding='utf-8'    ) as csvfile:
		yield from csv.reader(UpperCAmelCase_    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							List[str]    )				->     Union[str, Any]:

	'''simple docstring'''





	__snake_case     :				Union[str, Any] 						=					tmp_path / 'cache'
	__snake_case     :				Union[str, Any] 						=					os.path.join(UpperCAmelCase_     ,				'tmp.csv'    )
	__snake_case     :				int 						=					CsvDatasetReader({'train': csv_path}     ,				cache_dir=UpperCAmelCase_    ).read()
	CsvDatasetWriter(dataset['train']     ,				UpperCAmelCase_     ,				num_proc=1    ).write()

	__snake_case     :				Union[str, Any] 						=					iter_csv_file(UpperCAmelCase_    )
	__snake_case     :				List[Any] 						=					iter_csv_file(UpperCAmelCase_    )

	for rowa, rowa in zip(UpperCAmelCase_     ,				UpperCAmelCase_    ):
		assert rowa == rowa
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]     ,				UpperCAmelCase_       :							Optional[Any]    )				->     List[str]:

	'''simple docstring'''





	__snake_case     :				Tuple 						=					tmp_path / 'cache'
	__snake_case     :				Union[str, Any] 						=					os.path.join(UpperCAmelCase_     ,				'tmp.csv'    )
	__snake_case     :				Dict 						=					CsvDatasetReader({'train': csv_path}     ,				cache_dir=UpperCAmelCase_    ).read()
	CsvDatasetWriter(dataset['train']     ,				UpperCAmelCase_     ,				num_proc=2    ).write()

	__snake_case     :				int 						=					iter_csv_file(UpperCAmelCase_    )
	__snake_case     :				List[Any] 						=					iter_csv_file(UpperCAmelCase_    )

	for rowa, rowa in zip(UpperCAmelCase_     ,				UpperCAmelCase_    ):
		assert rowa == rowa

def     __UpperCAmelCase							(       UpperCAmelCase_       :							Dict     ,				UpperCAmelCase_       :							List[str]    )				->     str:

	'''simple docstring'''





	__snake_case     :				List[Any] 						=					tmp_path / 'cache'
	__snake_case     :				Dict 						=					os.path.join(UpperCAmelCase_     ,				'tmp.csv'    )
	__snake_case     :				Dict 						=					CsvDatasetReader({'train': csv_path}     ,				cache_dir=UpperCAmelCase_    ).read()
	with pytest.raises(UpperCAmelCase_    ):
		CsvDatasetWriter(dataset['train']     ,				UpperCAmelCase_     ,				num_proc=0    )









"""simple docstring"""







import pytest

from datasets.utils.version import Version
@pytest.mark.parametrize(
    '''other, expected_equality'''			,       [
        (Version('''1.0.0'''						), True),
        ('''1.0.0''', True),
        (Version('''2.0.0'''						), False),
        ('''2.0.0''', False),
        ('''1''', False),
        ('''a''', False),
        (1, False),
        (None, False),
    ]			,       )
def _A		(		lowercase			,       lowercase						):







    """simple docstring"""
    a											=Version('''1.0.0'''						)
    assert (version == other) is expected_equality
    assert (version != other) is not expected_equality
    assert (hash(lowercase						) == hash(lowercase						)) is expected_equality