


'''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  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       int								=      tmp_path / "file.csv"
		_UpperCAmelCase		:       Any								=      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  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       str								=      tmp_path / "malformed_file.csv"
		_UpperCAmelCase		:       Any								=      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  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase   ):
		_UpperCAmelCase		:       Any								=      tmp_path / "csv_with_image.csv"
		_UpperCAmelCase		:       Optional[Any]								=      textwrap.dedent(
		    F"""\
        image
        {image_file}
        """   )
		with open(__lowerCAmelCase      , "w"   ) as f:
				f.write(__lowerCAmelCase   )
		return str(__lowerCAmelCase   )






@pytest.fixture
def  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       Optional[int]								=      tmp_path / "csv_with_label.csv"
		_UpperCAmelCase		:       Any								=      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  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       Optional[int]								=      tmp_path / "csv_with_int_list.csv"
		_UpperCAmelCase		:       Any								=      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  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase   ):
		_UpperCAmelCase		:       Optional[int]								=      Csv()
		_UpperCAmelCase		:       int								=      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  __lowerCAmelCase (__lowerCAmelCase   ):
		with open(__lowerCAmelCase      , encoding="utf-8"   ) as f:
				_UpperCAmelCase		:       List[Any]								=      f.read().splitlines()[1]
		_UpperCAmelCase		:       Optional[int]								=      Csv(encoding="utf-8"      , features=Features({"image": Image()}   )   )
		_UpperCAmelCase		:       Dict								=      csv._generate_tables([[csv_file_with_image]]   )
		_UpperCAmelCase		:       Tuple								=      pa.concat_tables([table for _, table in generator]   )
		assert pa_table.schema.field("image"   ).type == Image()()
		_UpperCAmelCase		:       str								=      pa_table.to_pydict()["image"]
		assert generated_content == [{"path": image_file, "bytes": None}]






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






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







'''simple docstring'''


def  __lowerCAmelCase ():
		_UpperCAmelCase		:       str								=      0
		for i in range(1      , 1_001   ):
				total += i**i
		return str(__lowerCAmelCase   )[-10:]


if __name__ == "__main__":
						print(solution())



