






from heapq import heappop, heappush

import numpy as np



def 					_lowerCamelCase(			lowerCAmelCase__				:		np.ndarray    ,    lowerCAmelCase__				:		tuple[int, int]    ,    lowerCAmelCase__				:		tuple[int, int]    ,    lowerCAmelCase__				:		bool    ,    ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	Dict													=   grid.shape
				SCREAMING_SNAKE_CASE_   :	Tuple													=   [-1, 1, 0, 0]
				SCREAMING_SNAKE_CASE_   :	List[str]													=   [0, 0, -1, 1]
				if allow_diagonal:
								dx += [-1, -1, 1, 1]
								dy += [-1, 1, -1, 1]

				SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	int													=   [(0, source)], set()
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   np.full((rows, cols)    ,    np.inf      )
				SCREAMING_SNAKE_CASE_   :	Dict													=   0
				SCREAMING_SNAKE_CASE_   :	List[str]													=   np.empty((rows, cols)    ,    dtype=lowerCAmelCase__      )
				SCREAMING_SNAKE_CASE_   :	Tuple													=   None

				while queue:
								((SCREAMING_SNAKE_CASE_)							,       (SCREAMING_SNAKE_CASE_))   :	List[str]													=   heappop(lowerCAmelCase__      )
								if (x, y) in visited:
												continue
								visited.add((x, y)      )

								if (x, y) == destination:
												SCREAMING_SNAKE_CASE_   :	Optional[int]													=   []
												while (x, y) != source:
																path.append((x, y)      )
																SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	List[Any]													=   predecessors[x, y]
												path.append(lowerCAmelCase__      )  # add the source manually
												path.reverse()
												return matrix[destination], path

								for i in range(len(lowerCAmelCase__      )      ):
												SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   x + dx[i], y + dy[i]
												if 0 <= nx < rows and 0 <= ny < cols:
																SCREAMING_SNAKE_CASE_   :	str													=   grid[nx][ny]
																if next_node == 1 and matrix[nx, ny] > dist + 1:
																				heappush(lowerCAmelCase__    ,    (dist + 1, (nx, ny))      )
																				SCREAMING_SNAKE_CASE_   :	List[str]													=   dist + 1
																				SCREAMING_SNAKE_CASE_   :	Dict													=   (x, y)

				return np.inf, []


if __name__ == "__main__":
				import doctest

				doctest.testmod()







from datetime import datetime

import requests
from bsa import BeautifulSoup

if __name__ == "__main__":
				A        =			input('Enter image url: ').strip()
				print(f"""Downloading image from {url} ...""")
				A        =			BeautifulSoup(requests.get(url).content, 'html.parser')
				# The image URL is in the content field of the first meta tag with property og:image
				A        =			soup.find('meta', {'property': 'og:image'})['content']
				A        =			requests.get(image_url).content
				A        =			f"""{datetime.now():%Y-%m-%d_%H:%M:%S}.jpg"""
				with open(file_name, 'wb') as fp:
								fp.write(image_data)
				print(f"""Done. Image saved to disk as {file_name}.""")