




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 SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Union[str, Any]:



       """simple docstring"""

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







@pytest.fixture
def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Optional[Any]:



       """simple docstring"""

       A__       =    tmp_path / '''malformed_file.csv'''
       A__       =    textwrap.dedent(
           '''\
        header1,header2
        1,2
        10,20,
        '''						)
       with open(lowercase_ ,				'''w'''						) as f:
              f.write(lowercase_						)
       return str(lowercase_						)







@pytest.fixture
def SCREAMING_SNAKE_CASE				(       lowercase_ ,				lowercase_						)   ->       str:



       """simple docstring"""

       A__       =    tmp_path / '''csv_with_image.csv'''
       A__       =    textwrap.dedent(
           f"""\
        image
        {image_file}
        """						)
       with open(lowercase_ ,				'''w'''						) as f:
              f.write(lowercase_						)
       return str(lowercase_						)







@pytest.fixture
def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       List[str]:



       """simple docstring"""

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







@pytest.fixture
def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Tuple:



       """simple docstring"""

       A__       =    tmp_path / '''csv_with_int_list.csv'''
       A__       =    textwrap.dedent(
           '''\
        int_list
        1 2 3
        4 5 6
        7 8 9
        '''						)
       with open(lowercase_ ,				'''w'''						) as f:
              f.write(lowercase_						)
       return str(lowercase_						)







def SCREAMING_SNAKE_CASE				(       lowercase_ ,				lowercase_ ,				lowercase_						)   ->       Dict:



       """simple docstring"""

       A__       =    Csv()
       A__       =    csv._generate_tables([[csv_file, malformed_csv_file]]						)
       with pytest.raises(lowercase_ ,				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(lowercase_						) in record.message
           for record in caplog.records						)







@require_pil
def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Union[str, Any]:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Tuple:



       """simple docstring"""

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







def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Tuple:



       """simple docstring"""

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






"""simple docstring"""







import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs




@pytest.mark.parametrize(
    "kwargs, expected"  ,						[
        ({"num_shards": 0, "max_num_jobs": 1}, []),
        ({"num_shards": 10, "max_num_jobs": 1}, [range(10   )]),
        ({"num_shards": 10, "max_num_jobs": 10}, [range(lowerCAmelCase_  ,						i + 1   ) for i in range(10   )]),
        ({"num_shards": 1, "max_num_jobs": 10}, [range(1   )]),
        ({"num_shards": 10, "max_num_jobs": 3}, [range(0  ,						4   ), range(4  ,						7   ), range(7  ,						10   )]),
        ({"num_shards": 3, "max_num_jobs": 10}, [range(0  ,						1   ), range(1  ,						2   ), range(2  ,						3   )]),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						   =				_distribute_shards(**lowerCAmelCase_   )
					assert out == expected




@pytest.mark.parametrize(
    "gen_kwargs, max_num_jobs, expected"  ,						[
        ({"foo": 0}, 10, [{"foo": 0}]),
        ({"shards": [0, 1, 2, 3]}, 1, [{"shards": [0, 1, 2, 3]}]),
        ({"shards": [0, 1, 2, 3]}, 4, [{"shards": [0]}, {"shards": [1]}, {"shards": [2]}, {"shards": [3]}]),
        ({"shards": [0, 1]}, 4, [{"shards": [0]}, {"shards": [1]}]),
        ({"shards": [0, 1, 2, 3]}, 2, [{"shards": [0, 1]}, {"shards": [2, 3]}]),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						   =				_split_gen_kwargs(lowerCAmelCase_  ,						lowerCAmelCase_   )
					assert out == expected




@pytest.mark.parametrize(
    "gen_kwargs, expected"  ,						[
        ({"foo": 0}, 1),
        ({"shards": [0]}, 1),
        ({"shards": [0, 1, 2, 3]}, 4),
        ({"shards": [0, 1, 2, 3], "foo": 0}, 4),
        ({"shards": [0, 1, 2, 3], "other": (0, 1)}, 4),
        ({"shards": [0, 1, 2, 3], "shards2": [0, 1]}, RuntimeError),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					if expected is RuntimeError:
										with pytest.raises(lowerCAmelCase_   ):
															_number_of_shards_in_gen_kwargs(lowerCAmelCase_   )
					else:
										__SCREAMING_SNAKE_CASE						   =				_number_of_shards_in_gen_kwargs(lowerCAmelCase_   )
										assert out == expected
