

from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup

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

def 						UpperCamelCase					(lowercase_: str = "IMDb_Top_250_Movies.csv"					)     ->      None:
	A__							:    Optional[int]        =		get_imdb_top_aaa_movies()
	with open(lowercase_    ,      """w"""    ,      newline=""""""					) as out_file:
		A__							:    int        =		csv.writer(lowercase_					)
		writer.writerow(["""Movie title""", """IMDb rating"""]					)
		for title, rating in movies.items():
			writer.writerow([title, rating]					)


if __name__ == "__main__":
	write_movies()






import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


A_       : Any         =			namedtuple(
    '_TestCommandArgs',
    [
        'dataset',
        'name',
        'cache_dir',
        'data_dir',
        'all_configs',
        'save_infos',
        'ignore_verifications',
        'force_redownload',
        'clear_cache',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)

def 						UpperCamelCase					(lowercase_: Any    ,      lowercase_: List[str]					)     ->      Optional[int]:
	return (abs(source - target					) / target) < 0.01


@pytest.mark.integration
def 						UpperCamelCase					(lowercase_: str					)     ->      str:
	A__							:    List[str]        =		_TestCommandArgs(dataset=lowercase_    ,      all_configs=lowercase_    ,      save_infos=lowercase_					)
	A__							:    int        =		TestCommand(*lowercase_					)
	test_command.run()
	A__							:    Optional[Any]        =		os.path.join(lowercase_    ,      """README.md"""					)
	assert os.path.exists(lowercase_					)
	A__							:    Dict        =		DatasetInfosDict.from_directory(lowercase_					)
	A__							:    str        =		DatasetInfosDict(
	    {
	        """default""": DatasetInfo(
	            features=Features(
	                {
	                    """tokens""": Sequence(Value("""string"""					)					),
	                    """ner_tags""": Sequence(
	                        ClassLabel(names=["""O""", """B-PER""", """I-PER""", """B-ORG""", """I-ORG""", """B-LOC""", """I-LOC"""]					)					),
	                    """langs""": Sequence(Value("""string"""					)					),
	                    """spans""": Sequence(Value("""string"""					)					),
	                }					)    ,      splits=[
	                {
	                    """name""": """train""",
	                    """num_bytes""": 2351563,
	                    """num_examples""": 10000,
	                },
	                {
	                    """name""": """validation""",
	                    """num_bytes""": 238418,
	                    """num_examples""": 1000,
	                },
	            ]    ,      download_size=3940680    ,      dataset_size=2589981    ,      )
	    }					)
	assert dataset_infos.keys() == expected_dataset_infos.keys()
	for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
		A__   ,   A__							:    Optional[Any]        =		getattr(dataset_infos["""default"""]    ,      lowercase_					), getattr(expected_dataset_infos["""default"""]    ,      lowercase_					)
		if key == "num_bytes":
			assert is_apercent_close(lowercase_    ,      lowercase_					)
		elif key == "splits":
			assert list(lowercase_					) == list(lowercase_					)
			for split in result:
				assert result[split].name == expected[split].name
				assert result[split].num_examples == expected[split].num_examples
				assert is_apercent_close(result[split].num_bytes    ,      expected[split].num_bytes					)
		else:
			result == expected



