




import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

SCREAMING_SNAKE_CASE__	:				List[str]  =       {'UserAgent': UserAgent().random}
SCREAMING_SNAKE_CASE__	:				Optional[Any]  =       'https://www.mywaifulist.moe/random'

def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )     ->			None:
       lowerCamelCase       :				Union[str, Any]      			= requests.get(_SCREAMING_SNAKE_CASE			,headers=_SCREAMING_SNAKE_CASE   )
       with open(_SCREAMING_SNAKE_CASE			,"wb"   ) as file:
              file.write(image.content   )

def 					A				(				)     ->			tuple[str, str, str]:
       lowerCamelCase       :				Optional[int]      			= BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE			,headers=_SCREAMING_SNAKE_CASE   ).text			,"html.parser"   )
       lowerCamelCase       :				List[Any]      			= soup.find("meta"			,attrs={"property": "og:title"}   ).attrs["content"]
       lowerCamelCase       :				Union[str, Any]      			= soup.find("meta"			,attrs={"property": "og:image"}   ).attrs["content"]
       lowerCamelCase       :				List[str]      			= soup.find("p"			,id="description"   ).get_text()
       lowerCamelCase			,				lowerCamelCase       :				Optional[int]      			= os.path.splitext(os.path.basename(_SCREAMING_SNAKE_CASE   )   )
       lowerCamelCase       :				Tuple      			= title.strip().replace(" "			,"_"   )
       lowerCamelCase       :				Optional[Any]      			= f'''{image_title}{image_extension}'''
       save_image(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )
       return (title, description, image_title)


if __name__ == "__main__":
       SCREAMING_SNAKE_CASE__  ,  SCREAMING_SNAKE_CASE__  ,  SCREAMING_SNAKE_CASE__	:				Tuple  =       random_anime_character()
       print(f'''{title}\n\n{desc}\n\nImage saved : {image_title}''')












import numpy as np

def 					A				(				_SCREAMING_SNAKE_CASE   )     ->			str:
       lowerCamelCase			,				lowerCamelCase       :				Dict      			= a.shape
       lowerCamelCase       :				Union[str, Any]      			= min(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )
       lowerCamelCase       :				Union[str, Any]      			= np.eye(_SCREAMING_SNAKE_CASE   )
       lowerCamelCase       :				List[Any]      			= a.copy()

       for k in range(t - 1   ):
              # select a column of modified matrix A':
              lowerCamelCase       :				Optional[Any]      			= r[k:, [k]]
              # construct first basis vector
              lowerCamelCase       :				Union[str, Any]      			= np.zeros_like(_SCREAMING_SNAKE_CASE   )
              lowerCamelCase       :				int      			= 1.0
              # determine scaling factor
              lowerCamelCase       :				Any      			= np.linalg.norm(_SCREAMING_SNAKE_CASE   )
              # construct vector v for Householder reflection
              lowerCamelCase       :				List[str]      			= x + np.sign(x[0]   ) * alpha * ea
              v /= np.linalg.norm(_SCREAMING_SNAKE_CASE   )

              # construct the Householder matrix
              lowerCamelCase       :				List[Any]      			= np.eye(m - k   ) - 2.0 * v @ v.T
              # pad with ones and zeros as necessary
              lowerCamelCase       :				Union[str, Any]      			= np.block([[np.eye(_SCREAMING_SNAKE_CASE   ), np.zeros((k, m - k)   )], [np.zeros((m - k, k)   ), q_k]]   )

              lowerCamelCase       :				Any      			= q @ q_k.T
              lowerCamelCase       :				List[Any]      			= q_k @ r

       return q, r


if __name__ == "__main__":
       import doctest

       doctest.testmod()






