
'''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 		A_							(						_lowerCAmelCase :     Optional[Any]				):



      """simple docstring"""




      _lowerCamelCase					: Tuple		    = tmp_path / "file.csv"
      _lowerCamelCase					: Optional[int]		    = 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 		A_							(						_lowerCAmelCase :     List[Any]				):



      """simple docstring"""




      _lowerCamelCase					: Any		    = tmp_path / "malformed_file.csv"
      _lowerCamelCase					: 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 		A_							(						_lowerCAmelCase :     Any					,						_lowerCAmelCase :     Dict				):



      """simple docstring"""




      _lowerCamelCase					: int		    = tmp_path / "csv_with_image.csv"
      _lowerCamelCase					: int		    = textwrap.dedent(
          F'\\n        image\n        {image_file}\n        '				)
      with open(_lowerCAmelCase					,						"w"				) as f:
            f.write(_lowerCAmelCase				)
      return str(_lowerCAmelCase				)







@pytest.fixture
def 		A_							(						_lowerCAmelCase :     List[str]				):



      """simple docstring"""




      _lowerCamelCase					: Dict		    = tmp_path / "csv_with_label.csv"
      _lowerCamelCase					: int		    = 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 		A_							(						_lowerCAmelCase :     Dict				):



      """simple docstring"""




      _lowerCamelCase					: Dict		    = tmp_path / "csv_with_int_list.csv"
      _lowerCamelCase					: 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 		A_							(						_lowerCAmelCase :     List[Any]					,						_lowerCAmelCase :     int					,						_lowerCAmelCase :     Tuple				):



      """simple docstring"""




      _lowerCamelCase					: List[Any]		    = Csv()
      _lowerCamelCase					: Any		    = 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 		A_							(						_lowerCAmelCase :     Union[str, Any]				):



      """simple docstring"""




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







def 		A_							(						_lowerCAmelCase :     List[Any]				):



      """simple docstring"""




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







def 		A_							(						_lowerCAmelCase :     str				):



      """simple docstring"""




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




from __future__ import annotations

from math import pow, sqrt

def      __lowercase(						UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__			):


      """simple docstring"""



      if (resistance, reactance, impedance).count(0			) != 1:
            raise ValueError("One and only one argument must be 0"			)
      if resistance == 0:
            return {"resistance": sqrt(pow(UpperCAmelCase__ , 2			) - pow(UpperCAmelCase__ , 2			)			)}
      elif reactance == 0:
            return {"reactance": sqrt(pow(UpperCAmelCase__ , 2			) - pow(UpperCAmelCase__ , 2			)			)}
      elif impedance == 0:
            return {"impedance": sqrt(pow(UpperCAmelCase__ , 2			) + pow(UpperCAmelCase__ , 2			)			)}
      else:
            raise ValueError("Exactly one argument must be 0"			)


if __name__ == "__main__":
     import doctest

     doctest.testmod()