

"""simple docstring"""

import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil



@pytest.fixture
def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	Dict:
 lowerCAmelCase__      :							str    =							tmp_path / "text.txt"
 lowerCAmelCase__      :							List[str]    =							textwrap.dedent(
     "\\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n\n        Second paragraph:\n        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.\n        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.\n        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.\n        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.\n        "      )
 with open(lowercase__				,				"w"				,				encoding="utf-8"      ) as f:
  f.write(lowercase__      )
 return str(lowercase__      )



@pytest.fixture
def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	Optional[Any]:
 lowerCAmelCase__      :							Union[str, Any]    =							tmp_path / "text_with_image.txt"
 with open(lowercase__				,				"w"				,				encoding="utf-8"      ) as f:
  f.write(lowercase__      )
 return str(lowercase__      )



@pytest.mark.parametrize("keep_linebreaks"				,				[True, False]      )
def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	int:
 with open(lowercase__				,				encoding="utf-8"      ) as f:
  lowerCAmelCase__      :							str    =							f.read().splitlines(keepends=lowercase__      )
 lowerCAmelCase__      :							Optional[int]    =							Text(keep_linebreaks=lowercase__				,				encoding="utf-8"      )
 lowerCAmelCase__      :							Optional[int]    =							text._generate_tables([[text_file]]      )
 lowerCAmelCase__      :							Optional[int]    =							pa.concat_tables([table for _, table in generator]      ).to_pydict()["text"]
 assert generated_content == expected_content



@require_pil
def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	Optional[Any]:
 with open(lowercase__				,				encoding="utf-8"      ) as f:
  lowerCAmelCase__      :							List[Any]    =							f.read().splitlines()[0]
 lowerCAmelCase__      :							List[Any]    =							Text(encoding="utf-8"				,				features=Features({"image": Image()}      )      )
 lowerCAmelCase__      :							Any    =							text._generate_tables([[text_file_with_image]]      )
 lowerCAmelCase__      :							int    =							pa.concat_tables([table for _, table in generator]      )
 assert pa_table.schema.field("image"      ).type == Image()()
 lowerCAmelCase__      :							Union[str, Any]    =							pa_table.to_pydict()["image"]
 assert generated_content == [{"path": image_file, "bytes": None}]






@pytest.mark.parametrize("sample_by"				,				["line", "paragraph", "document"]      )
def 			SCREAMING_SNAKE_CASE       (   lowercase__				,				lowercase__      ) ->	Dict:
 with open(lowercase__				,				encoding="utf-8"      ) as f:
  lowerCAmelCase__      :							Optional[int]    =							f.read()
 if sample_by == "line":
  lowerCAmelCase__      :							Optional[Any]    =							expected_content.splitlines()
 elif sample_by == "paragraph":
  lowerCAmelCase__      :							Dict    =							expected_content.split("\n\n"      )
 elif sample_by == "document":
  lowerCAmelCase__      :							Optional[int]    =							[expected_content]
 lowerCAmelCase__      :							Optional[int]    =							Text(sample_by=lowercase__				,				encoding="utf-8"				,				chunksize=1_0_0      )
 lowerCAmelCase__      :							Tuple    =							text._generate_tables([[text_file]]      )
 lowerCAmelCase__      :							Optional[int]    =							pa.concat_tables([table for _, table in generator]      ).to_pydict()["text"]
 assert generated_content == expected_content









"""simple docstring"""

from itertools import product



def 			SCREAMING_SNAKE_CASE       (   lowercase__ = 1_5      ) ->	int:
 lowerCAmelCase__      :							float    =							0.0
 lowerCAmelCase__      :							float
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							int
 lowerCAmelCase__      :							tuple[int, ...]

 for series in product(range(2      )				,				repeat=lowercase__      ):
  lowerCAmelCase__      :							Optional[int]    =							series.count(1      )
  lowerCAmelCase__      :							Dict    =							num_turns - num_blue
  if num_red >= num_blue:
   continue
  lowerCAmelCase__      :							Dict    =							1.0
  for ind, col in enumerate(lowercase__				,				2      ):
   if col == 0:
    prob *= (ind - 1) / ind
   else:
    prob *= 1 / ind

  total_prob += prob

 return int(1 / total_prob      )


if __name__ == "__main__":
    print(f"{solution() = }")






