





'''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_  (						__lowerCamelCase					:					Optional[int] ):
   lowercase_			:Union[str, Any]    			= tmp_path / "file.csv"
   lowercase_			: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 							UpperCAmelCase_  (						__lowerCamelCase					:					str ):
   lowercase_			:Optional[Any]    			= tmp_path / "malformed_file.csv"
   lowercase_			:Union[str, 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 							UpperCAmelCase_  (						__lowerCamelCase					:					int	,__lowerCamelCase					:					Any ):
   lowercase_			:int    			= tmp_path / "csv_with_image.csv"
   lowercase_			:Any    			= textwrap.dedent(
       F'\\n        image\n        {image_file}\n        ' )
   with open(__lowerCamelCase	,"w" ) as f:
      f.write(__lowerCamelCase )
   return str(__lowerCamelCase )
@pytest.fixture
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Optional[int] ):
   lowercase_			:Dict    			= tmp_path / "csv_with_label.csv"
   lowercase_			:Dict    			= 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 							UpperCAmelCase_  (						__lowerCamelCase					:					List[Any] ):
   lowercase_			:List[str]    			= tmp_path / "csv_with_int_list.csv"
   lowercase_			:List[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 							UpperCAmelCase_  (						__lowerCamelCase					:					Union[str, Any]	,__lowerCamelCase					:					Dict	,__lowerCamelCase					:					Any ):
   lowercase_			:str    			= Csv()
   lowercase_			:str    			= 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 							UpperCAmelCase_  (						__lowerCamelCase					:					Optional[Any] ):
   with open(__lowerCamelCase	,encoding="utf-8" ) as f:
      lowercase_			:Any    			= f.read().splitlines()[1]
   lowercase_			:Dict    			= Csv(encoding="utf-8"	,features=Features({"image": Image()} ) )
   lowercase_			:Dict    			= csv._generate_tables([[csv_file_with_image]] )
   lowercase_			:List[str]    			= pa.concat_tables([table for _, table in generator] )
   assert pa_table.schema.field("image" ).type == Image()()
   lowercase_			:Union[str, Any]    			= pa_table.to_pydict()["image"]
   assert generated_content == [{"path": image_file, "bytes": None}]
def 							UpperCAmelCase_  (						__lowerCamelCase					:					List[str] ):
   with open(__lowerCamelCase	,encoding="utf-8" ) as f:
      lowercase_			:Optional[Any]    			= f.read().splitlines()[1:]
   lowercase_			:Optional[Any]    			= Csv(encoding="utf-8"	,features=Features({"label": ClassLabel(names=["good", "bad"] )} ) )
   lowercase_			:Dict    			= csv._generate_tables([[csv_file_with_label]] )
   lowercase_			:Tuple    			= pa.concat_tables([table for _, table in generator] )
   assert pa_table.schema.field("label" ).type == ClassLabel(names=["good", "bad"] )()
   lowercase_			:Dict    			= pa_table.to_pydict()["label"]
   assert generated_content == [ClassLabel(names=["good", "bad"] ).straint(__lowerCamelCase ) for label in labels]


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









'''simple docstring'''


lowerCAmelCase					:     str												='''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

lowerCAmelCase					:     int												=[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
lowerCAmelCase					:     List[str]												={
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}


