Feat(algo): Implements A* Search algorithm for detecting the best and…

FinalMazeCodingChallenge_AstarAlgo/a_star.py

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+from priority_queue import PriorityQueue
+
+from helpers import offsets, create_maze, is_legal_pos, get_path
+
+def heuristic(a, b): # this is what makes this algorithm more effecicent than Dijkstra algo
+  x1,y1 = a
+  x2, y2 = b
+  return abs(x1 - x2) + abs(y1 - y2)
+
+
+def print_maze_with_path(maze, path):
+  for i in range(len(maze)):
+    for j in range(len(maze[0])):
+      if(i, j) in path:
+        print("* ", end="")
+      else:
+        print(f"{maze[i][j]}", end= "")
+    print()
+
+
+#* g value is the cost from the start to current
+def a_star(maze, start, goal):
+  pq = PriorityQueue()
+  predecessor = {start:None}
+  g_values = {start: 0}
+  pq.put(start,0)
+
+  while not pq.is_empty():
+    current = pq.get()
+    if current == goal:
+      return get_path(predecessor, start, goal)
+
+    for direction in ["up", "right", "down", "left"]:
+      x, y = offsets[direction]
+      neighbour = (current[0] + x , current[1]+y)
+
+      if is_legal_pos(maze, neighbour) and neighbour not in g_values:
+        g_tentative = g_values[current] + 1
+        g_values[neighbour] = g_tentative
+        f_value = g_tentative + heuristic(goal, neighbour)
+        pq.put(neighbour, f_value)
+        predecessor[neighbour] = current
+
+  return None
+
+
+# testing 
+if __name__ == "__main__":
+
+  myMaze = create_maze();
+    # Find and print path
+  start = (0, 0)
+  goal = (3, 3)
+  path = a_star(myMaze, start, goal)
+
+  if path:
+    print("Path found!")
+    print("Path coordinates:", path)
+    print("\nMaze with path marked (*):")
+    print_maze_with_path(myMaze, path)  # Fixed: Don't print the function itself
+  else:
+    print("No path found!")
+