






from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
__A      =				0

__A      =				[
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

__A      =				[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

__A      =				tuple[int, int]





class 						SCREAMING_SNAKE_CASE				:





							"""simple docstring"""

							def __init__(  self:   Union[str, Any]		,     __A:   int		,     __A:   int		,     __A:   int		,     __A:   int		,     __A:   int		,     __A:   Node | None		,     )    ->				None:
												_A								= pos_x
												_A								= pos_y
												_A								= (pos_y, pos_x)
												_A								= goal_x
												_A								= goal_y
												_A								= g_cost
												_A								= parent
												_A								= self.calculate_heuristic()
												_A								= self.g_cost + self.h_cost

							def       __A (  self:   int   )    ->				float:
												_A								= self.pos_x - self.goal_x
												_A								= self.pos_y - self.goal_y
												if HEURISTIC == 1:
																	return abs(__A   ) + abs(__A   )
												else:
																	return sqrt(dy**2 + dx**2   )



							def __lt__(  self:   List[str]		,     __A:   Node   )    ->				bool:
												return self.f_cost < other.f_cost





class 						SCREAMING_SNAKE_CASE				:





							"""simple docstring"""

							def __init__(  self:   Optional[int]		,     __A:   TPosition		,     __A:   TPosition   )    ->				str:
												_A								= Node(start[1]		,     start[0]		,     goal[1]		,     goal[0]		,     0		,     __A   )
												_A								= Node(goal[1]		,     goal[0]		,     goal[1]		,     goal[0]		,     9_99_99		,     __A   )

												_A								= [self.start]
												_A								= []

												_A								= False

							def       __A (  self:   Optional[Any]   )    ->				list[TPosition]:
												while self.open_nodes:
																	# Open Nodes are sorted using __lt__
																	self.open_nodes.sort()
																	_A								= self.open_nodes.pop(0   )

																	if current_node.pos == self.target.pos:
																						return self.retrace_path(__A   )

																	self.closed_nodes.append(__A   )
																	_A								= self.get_successors(__A   )

																	for child_node in successors:
																						if child_node in self.closed_nodes:
																											continue

																						if child_node not in self.open_nodes:
																											self.open_nodes.append(__A   )
																						else:
																											# retrieve the best current path
																											_A								= self.open_nodes.pop(self.open_nodes.index(__A   )   )

																											if child_node.g_cost < better_node.g_cost:
																																self.open_nodes.append(__A   )
																											else:
																																self.open_nodes.append(__A   )

												return [self.start.pos]

							def       __A (  self:   str		,     __A:   Node   )    ->				list[Node]:
												_A								= []
												for action in delta:
																	_A								= parent.pos_x + action[1]
																	_A								= parent.pos_y + action[0]
																	if not (0 <= pos_x <= len(grid[0]   ) - 1 and 0 <= pos_y <= len(__A   ) - 1):
																						continue

																	if grid[pos_y][pos_x] != 0:
																						continue

																	successors.append(
																	    Node(
																	        __A		,     __A		,     self.target.pos_y		,     self.target.pos_x		,     parent.g_cost + 1		,     __A		,     )   )
												return successors



							def       __A (  self:   str		,     __A:   Node | None   )    ->				list[TPosition]:
												_A								= node
												_A								= []
												while current_node is not None:
																	path.append((current_node.pos_y, current_node.pos_x)   )
																	_A								= current_node.parent
												path.reverse()
												return path





class 						SCREAMING_SNAKE_CASE				:





							"""simple docstring"""

							def __init__(  self:   Union[str, Any]		,     __A:   TPosition		,     __A:   TPosition   )    ->				None:
												_A								= AStar(__A		,     __A   )
												_A								= AStar(__A		,     __A   )
												_A								= False

							def       __A (  self:   Tuple   )    ->				list[TPosition]:
												while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
																	self.fwd_astar.open_nodes.sort()
																	self.bwd_astar.open_nodes.sort()
																	_A								= self.fwd_astar.open_nodes.pop(0   )
																	_A								= self.bwd_astar.open_nodes.pop(0   )

																	if current_bwd_node.pos == current_fwd_node.pos:
																						return self.retrace_bidirectional_path(
																						    __A		,     __A   )

																	self.fwd_astar.closed_nodes.append(__A   )
																	self.bwd_astar.closed_nodes.append(__A   )

																	_A								= current_bwd_node
																	_A								= current_fwd_node

																	_A								= {
																	    self.fwd_astar: self.fwd_astar.get_successors(__A   ),
																	    self.bwd_astar: self.bwd_astar.get_successors(__A   ),
																	}

																	for astar in [self.fwd_astar, self.bwd_astar]:
																						for child_node in successors[astar]:
																											if child_node in astar.closed_nodes:
																																continue

																											if child_node not in astar.open_nodes:
																																astar.open_nodes.append(__A   )
																											else:
																																# retrieve the best current path
																																_A								= astar.open_nodes.pop(
																																    astar.open_nodes.index(__A   )   )

																																if child_node.g_cost < better_node.g_cost:
																																					astar.open_nodes.append(__A   )
																																else:
																																					astar.open_nodes.append(__A   )

												return [self.fwd_astar.start.pos]



							def       __A (  self:   List[str]		,     __A:   Node		,     __A:   Node   )    ->				list[TPosition]:
												_A								= self.fwd_astar.retrace_path(__A   )
												_A								= self.bwd_astar.retrace_path(__A   )
												bwd_path.pop()
												bwd_path.reverse()
												_A								= fwd_path + bwd_path
												return path


if __name__ == "__main__":
				# all coordinates are given in format [y,x]
				__A      =				(0, 0)
				__A      =				(len(grid) - 1, len(grid[0]) - 1)
				for elem in grid:
								print(elem)

				__A      =				time.time()
				__A      =				AStar(init, goal)
				__A      =				a_star.search()
				__A      =				time.time() - start_time
				print(f'AStar execution time = {end_time:f} seconds')

				__A      =				time.time()
				__A      =				BidirectionalAStar(init, goal)
				__A      =				time.time() - bd_start_time
				print(f'BidirectionalAStar execution time = {bd_end_time:f} seconds')











def      __A					(     _lowercase					,			_lowercase					,			_lowercase					,			_lowercase ):

					'''simple docstring'''







					_A							,_A								= len(_lowercase ), len(grid[0] )
					if (
					    min(_lowercase					,			_lowercase ) < 0
					    or row == row_length
					    or col == col_length
					    or (row, col) in visit
					    or grid[row][col] == 1
					):
										return 0
					if row == row_length - 1 and col == col_length - 1:
										return 1

					visit.add((row, col) )

					_A								= 0
					count += depth_first_search(_lowercase					,			row + 1					,			_lowercase					,			_lowercase )
					count += depth_first_search(_lowercase					,			row - 1					,			_lowercase					,			_lowercase )
					count += depth_first_search(_lowercase					,			_lowercase					,			col + 1					,			_lowercase )
					count += depth_first_search(_lowercase					,			_lowercase					,			col - 1					,			_lowercase )

					visit.remove((row, col) )
					return count


if __name__ == "__main__":
				import doctest

				doctest.testmod()



