






'''simple docstring'''







from __future__ import annotations

UpperCamelCase     :   Dict	      =		[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def     A__      (					__lowerCAmelCase		:      list[list[int]] ,     __lowerCAmelCase		:      list[int] ,     __lowerCAmelCase		:      list[int] ,     __lowerCAmelCase		:      int ,     __lowerCAmelCase		:      list[list[int]] ,     ):
						lowerCamelCase__								=	[
						    [0 for col in range(len(grid[0]    )    )] for row in range(len(__lowerCAmelCase    )    )
						]  # the reference grid
						lowerCamelCase__								=	1
						lowerCamelCase__								=	[
						    [0 for col in range(len(grid[0]    )    )] for row in range(len(__lowerCAmelCase    )    )
						]  # the action grid

						lowerCamelCase__								=	init[0]
						lowerCamelCase__								=	init[1]
						lowerCamelCase__								=	0
						lowerCamelCase__								=	g + heuristic[x][y]  # cost from starting cell to destination cell
						lowerCamelCase__								=	[[f, g, x, y]]

						lowerCamelCase__								=	False  # flag that is set when search is complete
						lowerCamelCase__								=	False  # flag set if we can't find expand

						while not found and not resign:
												if len(__lowerCAmelCase    ) == 0:
																		raise ValueError("""Algorithm is unable to find solution"""    )
												else:  # to choose the least costliest action so as to move closer to the goal
																		cell.sort()
																		cell.reverse()
																		lowerCamelCase__								=	cell.pop()
																		lowerCamelCase__								=	next_cell[2]
																		lowerCamelCase__								=	next_cell[3]
																		lowerCamelCase__								=	next_cell[1]

																		if x == goal[0] and y == goal[1]:
																								lowerCamelCase__								=	True
																		else:
																								for i in range(len(__lowerCAmelCase    )    ):  # to try out different valid actions
																														lowerCamelCase__								=	x + DIRECTIONS[i][0]
																														lowerCamelCase__								=	y + DIRECTIONS[i][1]
																														if xa >= 0 and xa < len(__lowerCAmelCase    ) and ya >= 0 and ya < len(grid[0]    ):
																																				if closed[xa][ya] == 0 and grid[xa][ya] == 0:
																																										lowerCamelCase__								=	g + cost
																																										lowerCamelCase__								=	ga + heuristic[xa][ya]
																																										cell.append([fa, ga, xa, ya]    )
																																										lowerCamelCase__								=	1
																																										lowerCamelCase__								=	i
						lowerCamelCase__								=	[]
						lowerCamelCase__								=	goal[0]
						lowerCamelCase__								=	goal[1]
						invpath.append([x, y]    )  # we get the reverse path from here
						while x != init[0] or y != init[1]:
												lowerCamelCase__								=	x - DIRECTIONS[action[x][y]][0]
												lowerCamelCase__								=	y - DIRECTIONS[action[x][y]][1]
												lowerCamelCase__								=	xa
												lowerCamelCase__								=	ya
												invpath.append([x, y]    )

						lowerCamelCase__								=	[]
						for i in range(len(__lowerCAmelCase    )    ):
												path.append(invpath[len(__lowerCAmelCase    ) - 1 - i]    )
						return path, action


if __name__ == "__main__":
							UpperCamelCase     :   List[Any]	      =		[
							    [0, 1, 0, 0, 0, 0],
							    [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
							    [0, 1, 0, 0, 0, 0],
							    [0, 1, 0, 0, 1, 0],
							    [0, 0, 0, 0, 1, 0],
							]

							UpperCamelCase     :   List[Any]	      =		[0, 0]
							# all coordinates are given in format [y,x]
							UpperCamelCase     :   int	      =		[len(grid) - 1, len(grid[0]) - 1]
							UpperCamelCase     :   Dict	      =		1

							# the cost map which pushes the path closer to the goal
							UpperCamelCase     :   Tuple	      =		[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
							for i in range(len(grid)):
														for j in range(len(grid[0])):
																					UpperCamelCase     :   str	      =		abs(i - goal[0]) + abs(j - goal[1])
																					if grid[i][j] == 1:
																												# added extra penalty in the heuristic map
																												UpperCamelCase     :   Any	      =		99

							UpperCamelCase      ,    UpperCamelCase     :   int	      =		search(grid, init, goal, cost, heuristic)

							print('ACTION MAP')
							for i in range(len(action)):
														print(action[i])

							for i in range(len(path)):
														print(path[i])









from __future__ import annotations

from typing import Any






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if not postfix_notation:
								return 0

				lowercase__  					=     {'''+''', '''-''', '''*''', '''/'''}
				lowercase__  					=     []

				for token in postfix_notation:
								if token in operations:
												lowercase__					,		lowercase__  					=     stack.pop(), stack.pop()
												if token == "+":
																stack.append(a + b							)
												elif token == "-":
																stack.append(a - b							)
												elif token == "*":
																stack.append(a * b							)
												else:
																if a * b < 0 and a % b != 0:
																				stack.append(a // b + 1							)
																else:
																				stack.append(a // b							)
								else:
												stack.append(int(lowerCamelCase_							)							)

				return stack.pop()


if __name__ == "__main__":
							import doctest

							doctest.testmod()




