





from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup




def _a (  SCREAMING_SNAKE_CASE__      :  str = ""       )	->    dict[str, float]:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      List[str]     =						url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
							SCREAMING_SNAKE_CASE__       :      str     =						BeautifulSoup(requests.get(_snake_case       ).text			,				"html.parser"       )
							SCREAMING_SNAKE_CASE__       :      List[str]     =						soup.find_all("td"			,				attrs="titleColumn"       )
							SCREAMING_SNAKE_CASE__       :      Tuple     =						soup.find_all("td"			,				class_="ratingColumn imdbRating"       )
							return {
							    title.a.text: float(rating.strong.text       )
							    for title, rating in zip(_snake_case			,				_snake_case       )
							}




def _a (  SCREAMING_SNAKE_CASE__      :  str = "IMDb_Top_250_Movies.csv"       )	->    None:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Dict     =						get_imdb_top_aaa_movies()
							with open(_snake_case			,				"w"			,				newline=""       ) as out_file:
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						csv.writer(_snake_case       )
														writer.writerow(["Movie title", "IMDb rating"]       )
														for title, rating in movies.items():
																					writer.writerow([title, rating]       )


if __name__ == "__main__":
		write_movies()













import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict




@pytest.mark.parametrize(
    "split_dict"			,				[
        SplitDict(),
        SplitDict({"train": SplitInfo(name="train"			,				num_bytes=13_37			,				num_examples=42			,				dataset_name="my_dataset"       )}       ),
        SplitDict({"train": SplitInfo(name="train"			,				num_bytes=13_37			,				num_examples=42       )}       ),
        SplitDict({"train": SplitInfo()}       ),
    ]			,				)
def _a (  SCREAMING_SNAKE_CASE__      :  SplitDict       )	->    str:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      Dict     =						split_dict._to_yaml_list()
							assert len(SCREAMING_SNAKE_CASE__       ) == len(SCREAMING_SNAKE_CASE__       )
							SCREAMING_SNAKE_CASE__       :      List[Any]     =						SplitDict._from_yaml_list(SCREAMING_SNAKE_CASE__       )
							for split_name, split_info in split_dict.items():
														# dataset_name field is deprecated, and is therefore not part of the YAML dump
														SCREAMING_SNAKE_CASE__       :      str     =						None
														# the split name of split_dict takes over the name of the split info object
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						split_name
							assert split_dict == reloaded







@pytest.mark.parametrize(
    "split_info"			,				[SplitInfo(), SplitInfo(dataset_name=SCREAMING_SNAKE_CASE__       ), SplitInfo(dataset_name="my_dataset"       )]       )
def _a (  SCREAMING_SNAKE_CASE__      :  Any       )	->    Dict:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__       :      str     =						asdict(SplitDict({"train": split_info}       )       )
							assert "dataset_name" in split_dict_asdict["train"]
							assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name






