




'''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_	):





      """simple docstring"""



      _snake_case		:	int					     =     tmp_path / "file.csv"
      _snake_case		:	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_	):





      """simple docstring"""



      _snake_case		:	str					     =     tmp_path / "malformed_file.csv"
      _snake_case		:	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_			,      lowerCAmelCase_	):





      """simple docstring"""



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




@pytest.fixture
def    _a    (							lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	Optional[int]					     =     tmp_path / "csv_with_label.csv"
      _snake_case		:	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    _a    (							lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	Optional[int]					     =     tmp_path / "csv_with_int_list.csv"
      _snake_case		:	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_			,      lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	Optional[int]					     =     Csv()
      _snake_case		:	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    _a    (							lowerCAmelCase_	):





      """simple docstring"""



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




def    _a    (							lowerCAmelCase_	):





      """simple docstring"""



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




def    _a    (							lowerCAmelCase_	):





      """simple docstring"""



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









'''simple docstring'''

import math

from numpy import inf
from scipy.integrate import quad




def    _a    (							lowerCAmelCase_	):





      """simple docstring"""



      if num <= 0:
            raise ValueError('''math domain error'''	)

      return quad(lowerCAmelCase_			,      0			,      lowerCAmelCase_			,      args=(lowerCAmelCase_)	)[0]




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      return math.pow(lowerCAmelCase_			,      z - 1	) * math.exp(-x	)


if __name__ == "__main__":
   from doctest import testmod

   testmod()


