




"""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 					a__				(       snake_case__       )		->      int:
			lowerCamelCase       =      tmp_path / """file.csv"""
			lowerCamelCase       =      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 					a__				(       snake_case__       )		->      Any:
			lowerCamelCase       =      tmp_path / """malformed_file.csv"""
			lowerCamelCase       =      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 					a__				(       snake_case__ ,				snake_case__       )		->      Optional[Any]:
			lowerCamelCase       =      tmp_path / """csv_with_image.csv"""
			lowerCamelCase       =      textwrap.dedent(
			    F'\\n        image\n        {image_file}\n        '       )
			with open(snake_case__ ,				"""w"""       ) as f:
						f.write(snake_case__       )
			return str(snake_case__       )



@pytest.fixture
def 					a__				(       snake_case__       )		->      Any:
			lowerCamelCase       =      tmp_path / """csv_with_label.csv"""
			lowerCamelCase       =      textwrap.dedent(
			    """\
        label
        good
        bad
        good
        """       )
			with open(snake_case__ ,				"""w"""       ) as f:
						f.write(snake_case__       )
			return str(snake_case__       )



@pytest.fixture
def 					a__				(       snake_case__       )		->      Union[str, Any]:
			lowerCamelCase       =      tmp_path / """csv_with_int_list.csv"""
			lowerCamelCase       =      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 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      Any:
			lowerCamelCase       =      Csv()
			lowerCamelCase       =      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 					a__				(       snake_case__       )		->      Optional[Any]:
			with open(snake_case__ ,				encoding="""utf-8"""       ) as f:
						lowerCamelCase       =      f.read().splitlines()[1]
			lowerCamelCase       =      Csv(encoding="""utf-8""" ,				features=Features({"""image""": Image()}       )       )
			lowerCamelCase       =      csv._generate_tables([[csv_file_with_image]]       )
			lowerCamelCase       =      pa.concat_tables([table for _, table in generator]       )
			assert pa_table.schema.field("""image"""       ).type == Image()()
			lowerCamelCase       =      pa_table.to_pydict()["""image"""]
			assert generated_content == [{"path": image_file, "bytes": None}]



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



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









"""simple docstring"""




from collections.abc import Sequence



def 					a__				(       snake_case__ ,				snake_case__ = False       )		->      float:
			if not arr:
						return 0

			lowerCamelCase       =      0 if allow_empty_subarrays else float("""-inf"""       )
			lowerCamelCase       =      0.0
			for num in arr:
						lowerCamelCase       =      max(0 if allow_empty_subarrays else num ,				curr_sum + num       )
						lowerCamelCase       =      max(snake_case__ ,				snake_case__       )

			return max_sum


if __name__ == "__main__":
					from doctest import testmod

					testmod()

					lowerCAmelCase							:    Optional[int]  							=							[-2, 1, -3, 4, -1, 2, 1, -5, 4]
					print(F"""{max_subarray_sum(nums) = }""")



