




'''simple docstring'''



from pathlib import Path

import fire
def 					SCREAMING_SNAKE_CASE_					(				__A							:					str			,	__A							:					str			,	__A							:					int    )					->					List[Any]:
   _SCREAMING_SNAKE_CASE			= Path(snake_case_    )
   _SCREAMING_SNAKE_CASE			= Path(snake_case_    )
   dest_dir.mkdir(exist_ok=snake_case_    )
   for path in src_dir.iterdir():
      _SCREAMING_SNAKE_CASE			= [x.rstrip() for x in list(path.open().readlines()    )][:n]
      _SCREAMING_SNAKE_CASE			= dest_dir.joinpath(path.name    )
      print(snake_case_    )
      dest_path.open("w"    ).write("\n".join(snake_case_    )    )


if __name__ == "__main__":
 fire.Fire(minify)








"""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 						__lowercase	(  snake_case_    :    Optional[int]		)  ->str:



    '''simple docstring'''







    __A       :		Tuple							=	tmp_path / '''file.csv'''
    __A       :		Union[str, Any]							=	textwrap.dedent(
        '''\
        header1,header2
        1,2
        10,20
        '''		)
    with open(snake_case_							,'''w'''		) as f:
        f.write(snake_case_		)
    return str(snake_case_		)







@pytest.fixture
def 						__lowercase	(  snake_case_    :    str		)  ->Optional[Any]:



    '''simple docstring'''







    __A       :		List[str]							=	tmp_path / '''malformed_file.csv'''
    __A       :		Optional[Any]							=	textwrap.dedent(
        '''\
        header1,header2
        1,2
        10,20,
        '''		)
    with open(snake_case_							,'''w'''		) as f:
        f.write(snake_case_		)
    return str(snake_case_		)







@pytest.fixture
def 						__lowercase	(  snake_case_    :    Any							,snake_case_    :    Optional[int]		)  ->Optional[Any]:



    '''simple docstring'''







    __A       :		List[str]							=	tmp_path / '''csv_with_image.csv'''
    __A       :		List[str]							=	textwrap.dedent(
        F"""\
        image
        {image_file}
        """		)
    with open(snake_case_							,'''w'''		) as f:
        f.write(snake_case_		)
    return str(snake_case_		)







@pytest.fixture
def 						__lowercase	(  snake_case_    :    Optional[int]		)  ->Tuple:



    '''simple docstring'''







    __A       :		Dict							=	tmp_path / '''csv_with_label.csv'''
    __A       :		int							=	textwrap.dedent(
        '''\
        label
        good
        bad
        good
        '''		)
    with open(snake_case_							,'''w'''		) as f:
        f.write(snake_case_		)
    return str(snake_case_		)







@pytest.fixture
def 						__lowercase	(  snake_case_    :    Dict		)  ->Optional[Any]:



    '''simple docstring'''







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







def 						__lowercase	(  snake_case_    :    List[str]							,snake_case_    :    Optional[int]							,snake_case_    :    Optional[Any]		)  ->Dict:



    '''simple docstring'''







    __A       :		str							=	Csv()
    __A       :		List[Any]							=	csv._generate_tables([[csv_file, malformed_csv_file]]		)
    with pytest.raises(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(snake_case_		) in record.message
        for record in caplog.records		)







@require_pil
def 						__lowercase	(  snake_case_    :    Optional[int]		)  ->Union[str, Any]:



    '''simple docstring'''







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







def 						__lowercase	(  snake_case_    :    Any		)  ->List[Any]:



    '''simple docstring'''







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







def 						__lowercase	(  snake_case_    :    str		)  ->Dict:



    '''simple docstring'''







    __A       :		Optional[int]							=	Csv(encoding='''utf-8'''							,sep=''','''							,converters={'''int_list''': lambda snake_case_		: [int(snake_case_		) for i in x.split()]}		)
    __A       :		Dict							=	csv._generate_tables([[csv_file_with_int_list]]		)
    __A       :		Dict							=	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]]




