
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 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Optional[int]:
       lowercase							:					Optional[int]	     =				tmp_path / """file.csv"""
       lowercase							:					Dict	     =				textwrap.dedent(
           """\
        header1,header2
        1,2
        10,20
        """    )
       with open(SCREAMING_SNAKE_CASE__ ,     """w"""    ) as f:
              f.write(SCREAMING_SNAKE_CASE__    )
       return str(SCREAMING_SNAKE_CASE__    )







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Any:
       lowercase							:					Optional[Any]	     =				tmp_path / """malformed_file.csv"""
       lowercase							:					Tuple	     =				textwrap.dedent(
           """\
        header1,header2
        1,2
        10,20,
        """    )
       with open(SCREAMING_SNAKE_CASE__ ,     """w"""    ) as f:
              f.write(SCREAMING_SNAKE_CASE__    )
       return str(SCREAMING_SNAKE_CASE__    )







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Optional[int]:
       lowercase							:					Dict	     =				tmp_path / """csv_with_image.csv"""
       lowercase							:					Optional[int]	     =				textwrap.dedent(
           f"\\n        image\n        {image_file}\n        "    )
       with open(SCREAMING_SNAKE_CASE__ ,     """w"""    ) as f:
              f.write(SCREAMING_SNAKE_CASE__    )
       return str(SCREAMING_SNAKE_CASE__    )







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Dict:
       lowercase							:					Union[str, Any]	     =				tmp_path / """csv_with_label.csv"""
       lowercase							:					List[Any]	     =				textwrap.dedent(
           """\
        label
        good
        bad
        good
        """    )
       with open(SCREAMING_SNAKE_CASE__ ,     """w"""    ) as f:
              f.write(SCREAMING_SNAKE_CASE__    )
       return str(SCREAMING_SNAKE_CASE__    )







@pytest.fixture
def 						_snake_case(  SCREAMING_SNAKE_CASE__    )			->   Union[str, Any]:
       lowercase							:					Dict	     =				tmp_path / """csv_with_int_list.csv"""
       lowercase							:					Union[str, Any]	     =				textwrap.dedent(
           """\
        int_list
        1 2 3
        4 5 6
        7 8 9
        """    )
       with open(SCREAMING_SNAKE_CASE__ ,     """w"""    ) as f:
              f.write(SCREAMING_SNAKE_CASE__    )
       return str(SCREAMING_SNAKE_CASE__    )







def 						_snake_case(  SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__ ,     SCREAMING_SNAKE_CASE__    )			->   Optional[int]:
       lowercase							:					Any	     =				Csv()
       lowercase							:					Tuple	     =				csv._generate_tables([[csv_file, malformed_csv_file]]    )
       with pytest.raises(SCREAMING_SNAKE_CASE__ ,     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(SCREAMING_SNAKE_CASE__    ) in record.message
           for record in caplog.records    )







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







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







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


print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
