
'''simple docstring'''





import requests
from bsa import BeautifulSoup





def 							snake_case				(		UpperCAmelCase   ,	UpperCAmelCase						)->      str:







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










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE__       			=				{
    """configuration_markuplm""": ["""MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarkupLMConfig"""],
    """feature_extraction_markuplm""": ["""MarkupLMFeatureExtractor"""],
    """processing_markuplm""": ["""MarkupLMProcessor"""],
    """tokenization_markuplm""": ["""MarkupLMTokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__       			=				["""MarkupLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__       			=				[
							    """MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MarkupLMForQuestionAnswering""",
							    """MarkupLMForSequenceClassification""",
							    """MarkupLMForTokenClassification""",
							    """MarkupLMModel""",
							    """MarkupLMPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
							from .feature_extraction_markuplm import MarkupLMFeatureExtractor
							from .processing_markuplm import MarkupLMProcessor
							from .tokenization_markuplm import MarkupLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_markuplm_fast import MarkupLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_markuplm import (
														    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MarkupLMForQuestionAnswering,
														    MarkupLMForSequenceClassification,
														    MarkupLMForTokenClassification,
														    MarkupLMModel,
														    MarkupLMPreTrainedModel,
														)


else:
							import sys

							SCREAMING_SNAKE_CASE__       			=				_LazyModule(__name__, globals()["""__file__"""], _import_structure)

