




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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Dict:



    """simple docstring"""






    assert isinstance(SCREAMING_SNAKE_CASE_ ,	SCREAMING_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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        UpperCamelCase_      =	CsvDatasetReader(SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ,	keep_in_memory=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_dataset(SCREAMING_SNAKE_CASE_ ,	SCREAMING_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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Optional[int]:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    UpperCamelCase_      =	features.copy() if features else default_expected_features
    UpperCamelCase_      =	(
        Features({feature: Value(SCREAMING_SNAKE_CASE_ ) for feature, dtype in features.items()} ) if features is not None else None
    )
    UpperCamelCase_      =	CsvDatasetReader(SCREAMING_SNAKE_CASE_ ,	features=SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_dataset(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )




@pytest.mark.parametrize("split" ,	[None, NamedSplit("train" ), "train", "test"] )
def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    UpperCamelCase_      =	CsvDatasetReader(SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ,	split=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_dataset(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )
    assert dataset.split == split if split else "train"




@pytest.mark.parametrize("path_type" ,	[str, list] )
def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	str:



    """simple docstring"""






    if issubclass(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ):
        UpperCamelCase_      =	csv_path
    elif issubclass(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ):
        UpperCamelCase_      =	[csv_path]
    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    UpperCamelCase_      =	CsvDatasetReader(SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_dataset(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_=("train",) )->	List[Any]:



    """simple docstring"""






    assert isinstance(SCREAMING_SNAKE_CASE_ ,	SCREAMING_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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Tuple:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        UpperCamelCase_      =	CsvDatasetReader({"train": csv_path} ,	cache_dir=SCREAMING_SNAKE_CASE_ ,	keep_in_memory=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_datasetdict(SCREAMING_SNAKE_CASE_ ,	SCREAMING_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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	List[str]:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    UpperCamelCase_      =	features.copy() if features else default_expected_features
    UpperCamelCase_      =	(
        Features({feature: Value(SCREAMING_SNAKE_CASE_ ) for feature, dtype in features.items()} ) if features is not None else None
    )
    UpperCamelCase_      =	CsvDatasetReader({"train": csv_path} ,	features=SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_datasetdict(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )




@pytest.mark.parametrize("split" ,	[None, NamedSplit("train" ), "train", "test"] )
def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    if split:
        UpperCamelCase_      =	{split: csv_path}
    else:
        UpperCamelCase_      =	{"train": csv_path, "test": csv_path}
    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
    UpperCamelCase_      =	CsvDatasetReader(SCREAMING_SNAKE_CASE_ ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    _check_csv_datasetdict(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	splits=list(path.keys() ) )
    assert all(dataset[split].split == split for split in path.keys() )




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	Dict:



    """simple docstring"""






    with open(SCREAMING_SNAKE_CASE_ ,	encoding="utf-8" ) as csvfile:
        yield from csv.reader(SCREAMING_SNAKE_CASE_ )




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	List[str]:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"tmp.csv" )
    UpperCamelCase_      =	CsvDatasetReader({"train": csv_path} ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    CsvDatasetWriter(dataset["train"] ,	SCREAMING_SNAKE_CASE_ ,	num_proc=1 ).write()

    UpperCamelCase_      =	iter_csv_file(SCREAMING_SNAKE_CASE_ )
    UpperCamelCase_      =	iter_csv_file(SCREAMING_SNAKE_CASE_ )

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




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Tuple:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"tmp.csv" )
    UpperCamelCase_      =	CsvDatasetReader({"train": csv_path} ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    CsvDatasetWriter(dataset["train"] ,	SCREAMING_SNAKE_CASE_ ,	num_proc=2 ).write()

    UpperCamelCase_      =	iter_csv_file(SCREAMING_SNAKE_CASE_ )
    UpperCamelCase_      =	iter_csv_file(SCREAMING_SNAKE_CASE_ )

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




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	str:



    """simple docstring"""






    UpperCamelCase_      =	tmp_path / "cache"
    UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"tmp.csv" )
    UpperCamelCase_      =	CsvDatasetReader({"train": csv_path} ,	cache_dir=SCREAMING_SNAKE_CASE_ ).read()
    with pytest.raises(SCREAMING_SNAKE_CASE_ ):
        CsvDatasetWriter(dataset["train"] ,	SCREAMING_SNAKE_CASE_ ,	num_proc=0 )



def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	float:



    """simple docstring"""






    return -num if num < 0 else num




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    if len(SCREAMING_SNAKE_CASE_ ) == 0:
        raise ValueError("abs_min() arg is an empty sequence" )
    UpperCamelCase_      =	x[0]
    for i in x:
        if abs_val(SCREAMING_SNAKE_CASE_ ) < abs_val(SCREAMING_SNAKE_CASE_ ):
            UpperCamelCase_      =	i
    return j




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    if len(SCREAMING_SNAKE_CASE_ ) == 0:
        raise ValueError("abs_max() arg is an empty sequence" )
    UpperCamelCase_      =	x[0]
    for i in x:
        if abs(SCREAMING_SNAKE_CASE_ ) > abs(SCREAMING_SNAKE_CASE_ ):
            UpperCamelCase_      =	i
    return j




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    if len(SCREAMING_SNAKE_CASE_ ) == 0:
        raise ValueError("abs_max_sort() arg is an empty sequence" )
    return sorted(SCREAMING_SNAKE_CASE_ ,	key=SCREAMING_SNAKE_CASE_ )[-1]




def  lowerCAmelCase(			)->	Any:



    """simple docstring"""






    assert abs_val(0 ) == 0
    assert abs_val(3_4 ) == 3_4
    assert abs_val(-1_0_0_0_0_0_0_0_0_0_0_0 ) == 1_0_0_0_0_0_0_0_0_0_0_0

    UpperCamelCase_      =	[-3, -1, 2, -1_1]
    assert abs_max(SCREAMING_SNAKE_CASE_ ) == -1_1
    assert abs_max_sort(SCREAMING_SNAKE_CASE_ ) == -1_1
    assert abs_min(SCREAMING_SNAKE_CASE_ ) == -1


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 test_abs_val()
 print(abs_val(-34))  # --> 34
