






"""simple docstring"""
import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

snake_case   :   List[Any]    		=		{"""UserAgent""": UserAgent().random}
snake_case   :   List[str]    		=		"""https://www.mywaifulist.moe/random"""


def        A	(							__snake_case:   str   ,    __snake_case:   str     )						->		None:

       """simple docstring"""





       __magic_name__										=						requests.get(__snake_case   ,    headers=__snake_case     )
       with open(__snake_case   ,    'wb'     ) as file:
              file.write(image.content     )


def        A	(							)						->		tuple[str, str, str]:

       """simple docstring"""





       __magic_name__										=						BeautifulSoup(requests.get(__snake_case   ,    headers=__snake_case     ).text   ,    'html.parser'     )
       __magic_name__										=						soup.find('meta'   ,    attrs={'property': 'og:title'}     ).attrs['content']
       __magic_name__										=						soup.find('meta'   ,    attrs={'property': 'og:image'}     ).attrs['content']
       __magic_name__										=						soup.find('p'   ,    id='description'     ).get_text()
       __magic_name__							,     __magic_name__										=						os.path.splitext(os.path.basename(__snake_case     )     )
       __magic_name__										=						title.strip().replace(' '   ,    '_'     )
       __magic_name__										=						F"""{image_title}{image_extension}"""
       save_image(__snake_case   ,    __snake_case     )
       return (title, description, image_title)


if __name__ == "__main__":
 snake_case		, snake_case		, snake_case   :   Union[str, Any]    		=		random_anime_character()
 print(f"""{title}\n\n{desc}\n\nImage saved : {image_title}""")







"""simple docstring"""
from typing import TYPE_CHECKING

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


snake_case   :   Optional[int]    		=		{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		["""SplinterTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		[
     """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """SplinterForQuestionAnswering""",
     """SplinterForPreTraining""",
     """SplinterLayer""",
     """SplinterModel""",
     """SplinterPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
 from .tokenization_splinter import SplinterTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_splinter_fast import SplinterTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_splinter import (
      SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
      SplinterForPreTraining,
      SplinterForQuestionAnswering,
      SplinterLayer,
      SplinterModel,
      SplinterPreTrainedModel,
  )


else:
 import sys

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