novikovsd/maze.py

@@ -196,8 +196,42 @@ class AStarStrategy(PathFindingStrategy):
         return []
 
 class SearchStats:
+    def __init__(self, time_ms: float, visited_cells: int, path_length: int):
+        self.time_ms = time_ms
+        self.visited_cells = visited_cells
+        self.path_length = path_length
+
+    def __repr__(self):
+        return f"Stats(time={self.time_ms:.2f}ms, visited={self.visited_cells}, path_len={self.path_length})"
 
 class MazeSolver:
+    def __init__(self, maze: Maze, strategy: PathFindingStrategy):
+        self.maze = maze
+        self.strategy = strategy
+        self.observers = []
+
+    def set_strategy(self, strategy: PathFindingStrategy):
+        self.strategy = strategy
+
+    def attach(self, observer):
+        self.observers.append(observer)
+
+    def detach(self, observer):
+        self.observers.remove(observer)
+
+    def notify(self, event: str, data: Any = None):
+        for obs in self.observers:
+            obs.update(event, data)
+
+    def solve(self) -> Tuple[List[Cell], SearchStats]:
+        start_time = time.perf_counter()
+        path = self.strategy.find_path(self.maze, self.maze.start, self.maze.exit)
+        end_time = time.perf_counter()
+        elapsed_ms = (end_time - start_time) * 1000.0
+        visited_cells = getattr(self.strategy, 'last_visited', len(path) if path else 0)
+        stats = SearchStats(elapsed_ms, visited_cells, len(path))
+        self.notify("solved", {"path": path, "stats": stats})
+        return path, stats
 
 class Observer(ABC):