


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						( UpperCAmelCase_						:		List[str]						):




      """simple docstring"""





      a						:str 							=       tmp_path / '''file.csv'''
      a						:List[str] 							=       textwrap.dedent(
          '''\
        header1,header2
        1,2
        10,20
        '''						)
      with open(UpperCAmelCase_ ,  '''w'''						) as f:
            f.write(UpperCAmelCase_						)
      return str(UpperCAmelCase_						)
@pytest.fixture
def 				__lowerCamelCase						( UpperCAmelCase_						:		List[str]						):




      """simple docstring"""





      a						:Optional[Any] 							=       tmp_path / '''malformed_file.csv'''
      a						:Optional[Any] 							=       textwrap.dedent(
          '''\
        header1,header2
        1,2
        10,20,
        '''						)
      with open(UpperCAmelCase_ ,  '''w'''						) as f:
            f.write(UpperCAmelCase_						)
      return str(UpperCAmelCase_						)
@pytest.fixture
def 				__lowerCamelCase						( UpperCAmelCase_						:		Optional[Any] ,  UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:List[Any] 							=       tmp_path / '''csv_with_image.csv'''
      a						:Tuple 							=       textwrap.dedent(
          F'''\
        image
        {image_file}
        '''						)
      with open(UpperCAmelCase_ ,  '''w'''						) as f:
            f.write(UpperCAmelCase_						)
      return str(UpperCAmelCase_						)
@pytest.fixture
def 				__lowerCamelCase						( UpperCAmelCase_						:		Optional[int]						):




      """simple docstring"""





      a						:List[Any] 							=       tmp_path / '''csv_with_label.csv'''
      a						:Dict 							=       textwrap.dedent(
          '''\
        label
        good
        bad
        good
        '''						)
      with open(UpperCAmelCase_ ,  '''w'''						) as f:
            f.write(UpperCAmelCase_						)
      return str(UpperCAmelCase_						)
@pytest.fixture
def 				__lowerCamelCase						( UpperCAmelCase_						:		int						):




      """simple docstring"""





      a						:int 							=       tmp_path / '''csv_with_int_list.csv'''
      a						:Tuple 							=       textwrap.dedent(
          '''\
        int_list
        1 2 3
        4 5 6
        7 8 9
        '''						)
      with open(UpperCAmelCase_ ,  '''w'''						) as f:
            f.write(UpperCAmelCase_						)
      return str(UpperCAmelCase_						)
def 				__lowerCamelCase						( UpperCAmelCase_						:		List[Any] ,  UpperCAmelCase_						:		Optional[Any] ,  UpperCAmelCase_						:		Optional[Any]						):




      """simple docstring"""





      a						:str 							=       Csv()
      a						:Optional[int] 							=       csv._generate_tables([[csv_file, malformed_csv_file]]						)
      with pytest.raises(UpperCAmelCase_ ,  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(UpperCAmelCase_						) in record.message
          for record in caplog.records						)
@require_pil
def 				__lowerCamelCase						( UpperCAmelCase_						:		str						):




      """simple docstring"""





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




      """simple docstring"""





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






def 				__lowerCamelCase						( UpperCAmelCase_						:		Tuple						):




      """simple docstring"""





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









from __future__ import annotations
def 				__lowerCamelCase						( UpperCAmelCase_						:		dict ,  UpperCAmelCase_						:		str						):




      """simple docstring"""





      a							,				a						:Optional[Any] 							=       set(UpperCAmelCase_						), [start]

      while stack:
            a						:Optional[int] 							=       stack.pop()
            explored.add(UpperCAmelCase_						)
            # Differences from BFS:
            # 1) pop last element instead of first one
            # 2) add adjacent elements to stack without exploring them
            for adj in reversed(graph[v]						):
                  if adj not in explored:
                        stack.append(UpperCAmelCase_						)
      return explored


snake_case				:    Optional[int]       				=     {
    '''A''': ['''B''', '''C''', '''D'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F'''],
    '''D''': ['''B''', '''D'''],
    '''E''': ['''B''', '''F'''],
    '''F''': ['''C''', '''E''', '''G'''],
    '''G''': ['''F'''],
}

if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(depth_first_search(G, '''A'''))





