





'''simple docstring'''

import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil





@pytest.fixture
def 						UpperCamelCase				(							_lowerCamelCase					:					Union[str, Any]       ):
    A__				=			tmp_path / "file.csv"
    A__				=			textwrap.dedent(
        "\\n        header1,header2\n        1,2\n        10,20\n        "       )
    with open(_lowerCamelCase						,       "w"       ) as f:
        f.write(_lowerCamelCase       )
    return str(_lowerCamelCase       )





@pytest.fixture
def 						UpperCamelCase				(							_lowerCamelCase					:					List[str]       ):
    A__				=			tmp_path / "malformed_file.csv"
    A__				=			textwrap.dedent(
        "\\n        header1,header2\n        1,2\n        10,20,\n        "       )
    with open(_lowerCamelCase						,       "w"       ) as f:
        f.write(_lowerCamelCase       )
    return str(_lowerCamelCase       )





@pytest.fixture
def 						UpperCamelCase				(							_lowerCamelCase					:					Optional[int]						,       _lowerCamelCase					:					Any       ):
    A__				=			tmp_path / "csv_with_image.csv"
    A__				=			textwrap.dedent(
        F"\\n        image\n        {image_file}\n        "       )
    with open(_lowerCamelCase						,       "w"       ) as f:
        f.write(_lowerCamelCase       )
    return str(_lowerCamelCase       )





@pytest.fixture
def 						UpperCamelCase				(							_lowerCamelCase					:					List[Any]       ):
    A__				=			tmp_path / "csv_with_label.csv"
    A__				=			textwrap.dedent(
        "\\n        label\n        good\n        bad\n        good\n        "       )
    with open(_lowerCamelCase						,       "w"       ) as f:
        f.write(_lowerCamelCase       )
    return str(_lowerCamelCase       )





@pytest.fixture
def 						UpperCamelCase				(							_lowerCamelCase					:					Optional[int]       ):
    A__				=			tmp_path / "csv_with_int_list.csv"
    A__				=			textwrap.dedent(
        "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "       )
    with open(_lowerCamelCase						,       "w"       ) as f:
        f.write(_lowerCamelCase       )
    return str(_lowerCamelCase       )





def 						UpperCamelCase				(							_lowerCamelCase					:					str						,       _lowerCamelCase					:					Optional[int]						,       _lowerCamelCase					:					Union[str, Any]       ):
    A__				=			Csv()
    A__				=			csv._generate_tables([[csv_file, malformed_csv_file]]       )
    with pytest.raises(_lowerCamelCase						,       match="Error tokenizing data"       ):
        for _ in generator:
            pass
    assert any(
        record.levelname == "ERROR"
        and "Failed to read file" in record.message
        and os.path.basename(_lowerCamelCase       ) in record.message
        for record in caplog.records       )





@require_pil
def 						UpperCamelCase				(							_lowerCamelCase					:					Optional[Any]       ):
    with open(_lowerCamelCase						,       encoding="utf-8"       ) as f:
        A__				=			f.read().splitlines()[1]
    A__				=			Csv(encoding="utf-8"						,       features=Features({"image": Image()}       )       )
    A__				=			csv._generate_tables([[csv_file_with_image]]       )
    A__				=			pa.concat_tables([table for _, table in generator]       )
    assert pa_table.schema.field("image"       ).type == Image()()
    A__				=			pa_table.to_pydict()["image"]
    assert generated_content == [{"path": image_file, "bytes": None}]





def 						UpperCamelCase				(							_lowerCamelCase					:					List[str]       ):
    with open(_lowerCamelCase						,       encoding="utf-8"       ) as f:
        A__				=			f.read().splitlines()[1:]
    A__				=			Csv(encoding="utf-8"						,       features=Features({"label": ClassLabel(names=["good", "bad"]       )}       )       )
    A__				=			csv._generate_tables([[csv_file_with_label]]       )
    A__				=			pa.concat_tables([table for _, table in generator]       )
    assert pa_table.schema.field("label"       ).type == ClassLabel(names=["good", "bad"]       )()
    A__				=			pa_table.to_pydict()["label"]
    assert generated_content == [ClassLabel(names=["good", "bad"]       ).straint(_lowerCamelCase       ) for label in labels]





def 						UpperCamelCase				(							_lowerCamelCase					:					Tuple       ):
    A__				=			Csv(encoding="utf-8"						,       sep=","						,       converters={"int_list": lambda _lowerCamelCase       : [int(_lowerCamelCase       ) for i in x.split()]}       )
    A__				=			csv._generate_tables([[csv_file_with_int_list]]       )
    A__				=			pa.concat_tables([table for _, table in generator]       )
    assert pa.types.is_list(pa_table.schema.field("int_list"       ).type       )
    A__				=			pa_table.to_pydict()["int_list"]
    assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]










'''simple docstring'''

from __future__ import annotations





def 						UpperCamelCase				(							_lowerCamelCase					:					list[int | str]       ):
    create_state_space_tree(_lowerCamelCase						,       []						,       0						,       [0 for i in range(len(_lowerCamelCase       )       )]       )





def 						UpperCamelCase				(							_lowerCamelCase					:					list[int | str]						,       _lowerCamelCase					:					list[int | str]						,       _lowerCamelCase					:					int						,       _lowerCamelCase					:					list[int]						,       ):

    if index == len(_lowerCamelCase       ):
        print(_lowerCamelCase       )
        return

    for i in range(len(_lowerCamelCase       )       ):
        if not index_used[i]:
            current_sequence.append(sequence[i]       )
            A__				=			True
            create_state_space_tree(_lowerCamelCase						,       _lowerCamelCase						,       index + 1						,       _lowerCamelCase       )
            current_sequence.pop()
            A__				=			False
__lowerCAmelCase							:	list[int | str]			=[3, 1, 2, 4]
generate_all_permutations(sequence)

__lowerCAmelCase							:	list[int | str]			=["A", "B", "C"]



generate_all_permutations(sequence_a)



