
'''simple docstring'''



import bsa
import requests
def       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_  )   ->   dict[str, str]:




   """simple docstring"""
   return {
       "name": soup.ha.a.text,
       "genre": soup.find("""span"""			,					class_="""genre"""  ).text.strip(),
       "rating": soup.strong.text,
       "page_link": F"https://www.imdb.com{soup.a.get('href'  )}",
   }
def       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_ = 5  )   ->   tuple:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE          = int(float(SCREAMING_SNAKE_CASE_  )  )
   if num_movies < 1:
      return ()
   _SCREAMING_SNAKE_CASE          = (
       """https://www.imdb.com/search/title?title_type="""
       F"feature&sort=num_votes,desc&count={num_movies}"
   )
   _SCREAMING_SNAKE_CASE          = bsa.BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE_  ).content			,					"""html.parser"""  )
   return tuple(
       get_movie_data_from_soup(SCREAMING_SNAKE_CASE_  )
       for movie in source.find_all("""div"""			,					class_="""lister-item mode-advanced"""  )  )


if __name__ == "__main__":
     import json

     UpperCamelCase__					:						str											=     int(input("How many movies would you like to see? "))
     print(
         ", ".join(
             json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
         )
     )








'''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       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_  )   ->   Union[str, Any]:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE          = tmp_path / """text.txt"""
   _SCREAMING_SNAKE_CASE          = textwrap.dedent(
       """\
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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




   """simple docstring"""
   _SCREAMING_SNAKE_CASE          = tmp_path / """text_with_image.txt"""
   with open(SCREAMING_SNAKE_CASE_			,					"""w"""			,					encoding="""utf-8"""  ) as f:
      f.write(SCREAMING_SNAKE_CASE_  )
   return str(SCREAMING_SNAKE_CASE_  )
@pytest.mark.parametrize("""keep_linebreaks"""			,					[True, False]  )
def       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_			,					SCREAMING_SNAKE_CASE_  )   ->   int:




   """simple docstring"""
   with open(SCREAMING_SNAKE_CASE_			,					encoding="""utf-8"""  ) as f:
      _SCREAMING_SNAKE_CASE          = f.read().splitlines(keepends=SCREAMING_SNAKE_CASE_  )
   _SCREAMING_SNAKE_CASE          = Text(keep_linebreaks=SCREAMING_SNAKE_CASE_			,					encoding="""utf-8"""  )
   _SCREAMING_SNAKE_CASE          = text._generate_tables([[text_file]]  )
   _SCREAMING_SNAKE_CASE          = pa.concat_tables([table for _, table in generator]  ).to_pydict()["""text"""]
   assert generated_content == expected_content
@require_pil
def       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_  )   ->   List[str]:




   """simple docstring"""
   with open(SCREAMING_SNAKE_CASE_			,					encoding="""utf-8"""  ) as f:
      _SCREAMING_SNAKE_CASE          = f.read().splitlines()[0]
   _SCREAMING_SNAKE_CASE          = Text(encoding="""utf-8"""			,					features=Features({"""image""": Image()}  )  )
   _SCREAMING_SNAKE_CASE          = text._generate_tables([[text_file_with_image]]  )
   _SCREAMING_SNAKE_CASE          = pa.concat_tables([table for _, table in generator]  )
   assert pa_table.schema.field("""image"""  ).type == Image()()
   _SCREAMING_SNAKE_CASE          = pa_table.to_pydict()["""image"""]
   assert generated_content == [{"path": image_file, "bytes": None}]







@pytest.mark.parametrize("""sample_by"""			,					["""line""", """paragraph""", """document"""]  )
def       lowerCAmelCase_		( SCREAMING_SNAKE_CASE_			,					SCREAMING_SNAKE_CASE_  )   ->   List[Any]:




   """simple docstring"""
   with open(SCREAMING_SNAKE_CASE_			,					encoding="""utf-8"""  ) as f:
      _SCREAMING_SNAKE_CASE          = f.read()
   if sample_by == "line":
      _SCREAMING_SNAKE_CASE          = expected_content.splitlines()
   elif sample_by == "paragraph":
      _SCREAMING_SNAKE_CASE          = expected_content.split("""\n\n"""  )
   elif sample_by == "document":
      _SCREAMING_SNAKE_CASE          = [expected_content]
   _SCREAMING_SNAKE_CASE          = Text(sample_by=SCREAMING_SNAKE_CASE_			,					encoding="""utf-8"""			,					chunksize=1_00  )
   _SCREAMING_SNAKE_CASE          = text._generate_tables([[text_file]]  )
   _SCREAMING_SNAKE_CASE          = pa.concat_tables([table for _, table in generator]  ).to_pydict()["""text"""]
   assert generated_content == expected_content






