
'''simple docstring'''
import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowercase__						=		{"UserAgent": UserAgent().random}
lowercase__						=		"https://www.mywaifulist.moe/random"




def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )     ->       None:


		'''simple docstring'''


		snake_case     :					List[Any]     =	requests.get(SCREAMING_SNAKE_CASE__   ,					headers=SCREAMING_SNAKE_CASE__ )
		with open(SCREAMING_SNAKE_CASE__   ,					'''wb''' ) as file:
				file.write(image.content )




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


		'''simple docstring'''


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


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




'''simple docstring'''
import numpy as np




def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__ )     ->       Optional[Any]:


		'''simple docstring'''


		snake_case ,snake_case     :					str     =	a.shape
		snake_case     :					Union[str, Any]     =	min(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )
		snake_case     :					List[Any]     =	np.eye(SCREAMING_SNAKE_CASE__ )
		snake_case     :					Union[str, Any]     =	a.copy()

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

				# construct the Householder matrix
				snake_case     :					Tuple     =	np.eye(m - k ) - 2.0 * v @ v.T
				# pad with ones and zeros as necessary
				snake_case     :					int     =	np.block([[np.eye(SCREAMING_SNAKE_CASE__ ), np.zeros((k, m - k) )], [np.zeros((m - k, k) ), q_k]] )

				snake_case     :					int     =	q @ q_k.T
				snake_case     :					Dict     =	q_k @ r

		return q, r


if __name__ == "__main__":
						import doctest

						doctest.testmod()


