






import requests
from bsa import BeautifulSoup





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  str:


	"""simple docstring"""



	a		=			(
	    '''https://www.horoscope.com/us/horoscopes/general/'''
	    f"""horoscope-general-daily-{day}.aspx?sign={zodiac_sign}"""
	)
	a		=			BeautifulSoup(requests.get(snake_case_  ).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""",
				)
				UpperCamelCase__						:      Optional[Any]								=					int(input("""number> """).strip())
				print("""choose some day:\n""", """yesterday\n""", """today\n""", """tomorrow\n""")
				UpperCamelCase__						:      int								=					input("""enter the day> """)
				UpperCamelCase__						:      Any								=					horoscope(zodiac_sign, day)
				print(horoscope_text)













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__						:      int								=					{
    """configuration_fsmt""": ["""FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FSMTConfig"""],
    """tokenization_fsmt""": ["""FSMTTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__						:      Any								=					["""FSMTForConditionalGeneration""", """FSMTModel""", """PretrainedFSMTModel"""]


if TYPE_CHECKING:
				from .configuration_fsmt import FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP, FSMTConfig
				from .tokenization_fsmt import FSMTTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_fsmt import FSMTForConditionalGeneration, FSMTModel, PretrainedFSMTModel

else:
				import sys

				UpperCamelCase__						:      List[Any]								=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





