Performance Issues with A* Pathfinding Algorithm Implementation in Python - Slow Response Times
After trying multiple solutions online, I still can't figure this out... I'm currently working on implementing the A* pathfinding algorithm in Python for a grid-based game. While my algorithm seems to find the path correctly, I'm experiencing significant performance issues, especially on larger grids. For instance, when I test it on a grid of size 100x100, the response time can exceed 5 seconds, which isn’t acceptable for real-time gameplay. Here's the critical section of my code: ```python import heapq class Node: def __init__(self, position, g=0, h=0): self.position = position # (x, y) self.g = g # cost from start to this node self.h = h # heuristic cost to goal self.f = g + h def __lt__(self, other): return self.f < other.f def a_star(start, goal, grid): open_list = [] closed_list = set() start_node = Node(start) goal_node = Node(goal) heapq.heappush(open_list, start_node) while open_list: current_node = heapq.heappop(open_list) if current_node.position == goal_node.position: return reconstruct_path(current_node) closed_list.add(current_node.position) for direction in [(0, 1), (1, 0), (0, -1), (-1, 0)]: neighbor_pos = (current_node.position[0] + direction[0], current_node.position[1] + direction[1]) if neighbor_pos in closed_list or not is_valid(neighbor_pos, grid): continue g_cost = current_node.g + 1 h_cost = heuristic(neighbor_pos, goal_node.position) neighbor_node = Node(neighbor_pos, g_cost, h_cost) if neighbor_node not in open_list: heapq.heappush(open_list, neighbor_node) return [] # No path found ``` I suspect that the way I'm managing the open and closed lists might be causing unnecessary overhead. I also noticed that the `is_valid` and `heuristic` functions might not be optimized. My heuristic is the Manhattan distance, which seems appropriate for grid-based movement. I've tried using a more efficient priority queue, but performance barely improved. Also, I ensured that I'm not checking neighbors that are out of bounds. Is there a best practice or optimization technique that I might be missing? How can I significantly improve the speed of my A* implementation in this scenario? My development environment is Ubuntu. Is there a better approach?