


"""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 _A		(		lowercase			,       lowercase						):







    """simple docstring"""
    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 _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    a											=tmp_path / '''cache'''
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        a											=CsvDatasetReader(lowercase			,       cache_dir=lowercase			,       keep_in_memory=lowercase						).read()
    _check_csv_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 _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    a											=tmp_path / '''cache'''
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    a											=features.copy() if features else default_expected_features
    a											=(
        Features({feature: Value(lowercase						) for feature, dtype in features.items()}						) if features is not None else None
    )
    a											=CsvDatasetReader(lowercase			,       features=lowercase			,       cache_dir=lowercase						).read()
    _check_csv_dataset(lowercase			,       lowercase						)
@pytest.mark.parametrize('''split'''			,       [None, NamedSplit('''train'''						), '''train''', '''test''']						)
def _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    a											=tmp_path / '''cache'''
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    a											=CsvDatasetReader(lowercase			,       cache_dir=lowercase			,       split=lowercase						).read()
    _check_csv_dataset(lowercase			,       lowercase						)
    assert dataset.split == split if split else "train"
@pytest.mark.parametrize('''path_type'''			,       [str, list]						)
def _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    if issubclass(lowercase			,       lowercase						):
        a											=csv_path
    elif issubclass(lowercase			,       lowercase						):
        a											=[csv_path]
    a											=tmp_path / '''cache'''
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    a											=CsvDatasetReader(lowercase			,       cache_dir=lowercase						).read()
    _check_csv_dataset(lowercase			,       lowercase						)
def _A		(		lowercase			,       lowercase			,       lowercase=("train",)						):







    """simple docstring"""
    assert isinstance(lowercase			,       lowercase						)
    for split in splits:
        a											=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 _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    a											=tmp_path / '''cache'''
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        a											=CsvDatasetReader({'''train''': csv_path}			,       cache_dir=lowercase			,       keep_in_memory=lowercase						).read()
    _check_csv_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 _A		(		lowercase			,       lowercase			,       lowercase						):







    """simple docstring"""
    a											=tmp_path / '''cache'''
    # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
    a											={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    a											=features.copy() if features else default_expected_features
    a											=(
        Features({feature: Value(lowercase						) for feature, dtype in features.items()}						) if features is not None else None
    )
    a											=CsvDatasetReader({'''train''': csv_path}			,       features=lowercase			,       cache_dir=lowercase						).read()
    _check_csv_datasetdict(lowercase			,       lowercase						)
@pytest.mark.parametrize('''split'''			,       [None, NamedSplit('''train'''						), '''train''', '''test''']						)
def _A		(		lowercase			,       lowercase			,       lowercase						):







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







    """simple docstring"""
    with open(lowercase			,       encoding='''utf-8'''						) as csvfile:
        yield from csv.reader(lowercase						)
def _A		(		lowercase			,       lowercase						):







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

    a											=iter_csv_file(lowercase						)
    a											=iter_csv_file(lowercase						)

    for rowa, rowa in zip(lowercase			,       lowercase						):
        assert rowa == rowa
def _A		(		lowercase			,       lowercase						):







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

    a											=iter_csv_file(lowercase						)
    a											=iter_csv_file(lowercase						)

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





def _A		(		lowercase			,       lowercase						):







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



"""simple docstring"""







import itertools
from pathlib import Path
def _A		(		lowercase						):







    """simple docstring"""
    a											=[tuple(lowercase						) for login in logins]

    a											={char for login in split_logins for char in login}

    for permutation in itertools.permutations(lowercase						):
        a											=True
        for login in logins:
            if not (
                permutation.index(login[0]						)
                < permutation.index(login[1]						)
                < permutation.index(login[2]						)
            ):
                a											=False
                break

        if satisfied:
            return int(''''''.join(lowercase						)						)

    raise Exception('''Unable to find the secret passcode'''						)
def _A		(		lowercase = "keylog.txt"						):







    """simple docstring"""
    a											=Path(lowercase						).parent.joinpath(lowercase						).read_text().splitlines()

    return find_secret_passcode(lowercase						)


if __name__ == "__main__":
       print(F'{solution() = }')