

import requests
from bsa import BeautifulSoup

def 	lowerCamelCase__	(   _a							,     _a):
	SCREAMING_SNAKE_CASE				: str			       =    (
	    "https://www.horoscope.com/us/horoscopes/general/"
	    f"horoscope-general-daily-{day}.aspx?sign={zodiac_sign}"
	)
	SCREAMING_SNAKE_CASE				: List[Any]			       =    BeautifulSoup(requests.get(_a).content							,     "html.parser")
	return soup.find("div"							,     class_="main-horoscope").p.text


if __name__ == "__main__":
			print('Daily Horoscope. \n')
			print(
			    'enter your Zodiac sign number:\n',
			    '1. Aries\n',
			    '2. Taurus\n',
			    '3. Gemini\n',
			    '4. Cancer\n',
			    '5. Leo\n',
			    '6. Virgo\n',
			    '7. Libra\n',
			    '8. Scorpio\n',
			    '9. Sagittarius\n',
			    '10. Capricorn\n',
			    '11. Aquarius\n',
			    '12. Pisces\n',
			)
			a_         =      int(input('number> ').strip())
			print('choose some day:\n', 'yesterday\n', 'today\n', 'tomorrow\n')
			a_         =      input('enter the day> ')
			a_         =      horoscope(zodiac_sign, day)
			print(horoscope_text)


from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers






class _UpperCamelCase							:
			'''simple docstring'''







			def __init__(     self							:	Optional[int] , a							:	Any		)							->    None:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: List[str]			       =    vocab
				SCREAMING_SNAKE_CASE				: str			       =    normalizers.BertNormalizer(
				    clean_text=a , handle_chinese_chars=a , strip_accents=a , lowercase=a , )
				try:
					import rjieba
				except ImportError:
					raise ImportError(
					    "You need to install rjieba to use RoFormerTokenizer. "
					    "See https://pypi.org/project/rjieba/ for installation."		)
				SCREAMING_SNAKE_CASE				: Union[str, Any]			       =    rjieba
			def 							__UpperCamelCase	(     self							:	Optional[int] , a							:	int , a							:	NormalizedString		)							->    List[NormalizedString]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: Dict			       =    []

				# this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
				for token, start, end in self.jieba.tokenize(str(a		) , hmm=a		):
					if token in self.vocab:
						splits.append(normalized_string[start:end]		)
					else:
						SCREAMING_SNAKE_CASE				: Any			       =    self.normalizers.normalize_str(a		).split()
						for token in token_list:
							if token:
								SCREAMING_SNAKE_CASE				: Optional[int]			       =    start + len(a		)
								splits.append(normalized_string[start:end]		)
								SCREAMING_SNAKE_CASE				: List[Any]			       =    end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

				return splits






			def 							__UpperCamelCase	(     self							:	Optional[int] , a							:	PreTokenizedString		)							->    Tuple:

				"""simple docstring"""

				pretok.split(self.jieba_split		)