





'''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	(	a    : int     ) ->int:
 snake_case				=			tmp_path / '''file.csv'''
 snake_case				=			textwrap.dedent(
     '''\
        header1,header2
        1,2
        10,20
        '''     )
 with open(a					,   '''w'''     ) as f:
  f.write(a     )
 return str(a     )

@pytest.fixture
def    __UpperCamelCase	(	a    : Tuple     ) ->Tuple:
 snake_case				=			tmp_path / '''malformed_file.csv'''
 snake_case				=			textwrap.dedent(
     '''\
        header1,header2
        1,2
        10,20,
        '''     )
 with open(a					,   '''w'''     ) as f:
  f.write(a     )
 return str(a     )

@pytest.fixture
def    __UpperCamelCase	(	a    : List[str]					,   a    : List[str]     ) ->Any:
 snake_case				=			tmp_path / '''csv_with_image.csv'''
 snake_case				=			textwrap.dedent(
     f"""\
        image
        {image_file}
        """     )
 with open(a					,   '''w'''     ) as f:
  f.write(a     )
 return str(a     )

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

@pytest.fixture
def    __UpperCamelCase	(	a    : int     ) ->Any:
 snake_case				=			tmp_path / '''csv_with_int_list.csv'''
 snake_case				=			textwrap.dedent(
     '''\
        int_list
        1 2 3
        4 5 6
        7 8 9
        '''     )
 with open(a					,   '''w'''     ) as f:
  f.write(a     )
 return str(a     )

def    __UpperCamelCase	(	a    : str					,   a    : Dict					,   a    : Tuple     ) ->List[str]:
 snake_case				=			Csv()
 snake_case				=			csv._generate_tables([[csv_file, malformed_csv_file]]     )
 with pytest.raises(a					,   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(a     ) in record.message
     for record in caplog.records     )

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

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






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








'''simple docstring'''







_lowercase       						=			{
    'Pillow': 'Pillow',
    'accelerate': 'accelerate>=0.11.0',
    'compel': 'compel==0.1.8',
    'black': 'black~=23.1',
    'datasets': 'datasets',
    'filelock': 'filelock',
    'flax': 'flax>=0.4.1',
    'hf-doc-builder': 'hf-doc-builder>=0.3.0',
    'huggingface-hub': 'huggingface-hub>=0.13.2',
    'requests-mock': 'requests-mock==1.10.0',
    'importlib_metadata': 'importlib_metadata',
    'invisible-watermark': 'invisible-watermark',
    'isort': 'isort>=5.5.4',
    'jax': 'jax>=0.2.8,!=0.3.2',
    'jaxlib': 'jaxlib>=0.1.65',
    'Jinja2': 'Jinja2',
    'k-diffusion': 'k-diffusion>=0.0.12',
    'torchsde': 'torchsde',
    'note_seq': 'note_seq',
    'librosa': 'librosa',
    'numpy': 'numpy',
    'omegaconf': 'omegaconf',
    'parameterized': 'parameterized',
    'protobuf': 'protobuf>=3.20.3,<4',
    'pytest': 'pytest',
    'pytest-timeout': 'pytest-timeout',
    'pytest-xdist': 'pytest-xdist',
    'ruff': 'ruff>=0.0.241',
    'safetensors': 'safetensors',
    'sentencepiece': 'sentencepiece>=0.1.91,!=0.1.92',
    'scipy': 'scipy',
    'onnx': 'onnx',
    'regex': 'regex!=2019.12.17',
    'requests': 'requests',
    'tensorboard': 'tensorboard',
    'torch': 'torch>=1.4',
    'torchvision': 'torchvision',
    'transformers': 'transformers>=4.25.1',
    'urllib3': 'urllib3<=2.0.0',
}

