3 этап

nikolaevda/task2/Zadanie2.py

@@ -98,4 +98,185 @@ class TextFileMazeBuilder(MazeBuilder):
         if start_count != 1 or exit_count != 1:
             raise ValueError(f"Ошибка: S={start_count}, E={exit_count} (нужно по одному)")
         
-        return maze
+        return maze
+    
+class SearchStats:
+    """статистика поиска"""
+    def __init__(self, time_ms=0, visited_cells=0, path_length=0):
+        self.time_ms = time_ms
+        self.visited_cells = visited_cells
+        self.path_length = path_length
+    
+    def __str__(self):
+        return f"Время: {self.time_ms:.2f} мс, Посещено: {self.visited_cells}, Длина пути: {self.path_length}"
+
+
+class PathFindingStrategy:
+    """интерфейс стратегии поиска пути"""
+    
+    def findPath(self, maze, start, exit):
+        raise NotImplementedError
+    
+    def get_name(self):
+        raise NotImplementedError
+
+
+class BFSStrategy(PathFindingStrategy):
+    """BFS - гарантирует кратчайший путь"""
+    
+    def get_name(self):
+        return "BFS (Поиск в ширину)"
+    
+    def findPath(self, maze, start, exit):
+        from collections import deque
+        
+        if not start or not exit:
+            return [], 0
+        
+        queue = deque([(start, [start])])
+        visited = {start}
+        
+        while queue:
+            current, path = queue.popleft()
+            
+            if current == exit:
+                return path, len(visited)
+            
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    queue.append((neighbor, path + [neighbor]))
+        
+        return [], len(visited)
+
+
+class DFSStrategy(PathFindingStrategy):
+    """DFS - быстрый, но не обязательно кратчайший"""
+    
+    def get_name(self):
+        return "DFS (Поиск в глубину)"
+    
+    def findPath(self, maze, start, exit):
+        if not start or not exit:
+            return [], 0
+        
+        stack = [(start, [start])]
+        visited = {start}
+        
+        while stack:
+            current, path = stack.pop()
+            
+            if current == exit:
+                return path, len(visited)
+            
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    stack.append((neighbor, path + [neighbor]))
+        
+        return [], len(visited)
+
+
+class AStarStrategy(PathFindingStrategy):
+    """алгоритм A Star - оптимальный и быстрый с эвристикой"""
+    
+    def get_name(self):
+        return "A Star"
+    
+    def _heuristic(self, a, b):
+        return abs(a.x - b.x) + abs(a.y - b.y)
+    
+    def findPath(self, maze, start, exit):
+        if not start or not exit:
+            return [], 0
+        
+        import heapq
+        
+        heap = []
+        counter = 0
+        start_f = self._heuristic(start, exit)
+        heapq.heappush(heap, (start_f, counter, start))
+        
+        came_from = {}
+        g_score = {start: 0}
+        f_score = {start: start_f}
+        visited = set()
+        visited.add(start)
+        
+        while heap:
+            current_f, _, current = heapq.heappop(heap)
+            
+            if current == exit:
+                path = []
+                while current in came_from:
+                    path.append(current)
+                    current = came_from[current]
+                path.append(start)
+                path.reverse()
+                return path, len(visited)
+            
+            if current_f > f_score.get(current, float('inf')):
+                continue
+            
+            for neighbor in maze.get_neighbors(current):
+                tentative_g = g_score[current] + 1
+                
+                if tentative_g < g_score.get(neighbor, float('inf')):
+                    came_from[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    new_f = tentative_g + self._heuristic(neighbor, exit)
+                    f_score[neighbor] = new_f
+                    counter += 1
+                    heapq.heappush(heap, (new_f, counter, neighbor))
+                    visited.add(neighbor)
+        
+        return [], len(visited)
+
+
+class DijkstraStrategy(PathFindingStrategy):
+    """алгоритм Дейкстры"""
+    
+    def get_name(self):
+        return "Дейкстра (Dijkstra)"
+    
+    def findPath(self, maze, start, exit):
+        if not start or not exit:
+            return [], 0
+        
+        import heapq
+        
+        heap = []
+        counter = 0
+        heapq.heappush(heap, (0, counter, start))
+        
+        distances = {start: 0}
+        came_from = {}
+        visited = set()
+        visited.add(start)
+        
+        while heap:
+            current_dist, _, current = heapq.heappop(heap)
+            
+            if current == exit:
+                path = []
+                while current in came_from:
+                    path.append(current)
+                    current = came_from[current]
+                path.append(start)
+                path.reverse()
+                return path, len(visited)
+            
+            if current_dist > distances.get(current, float('inf')):
+                continue
+            
+            for neighbor in maze.get_neighbors(current):
+                new_dist = current_dist + 1
+                
+                if new_dist < distances.get(neighbor, float('inf')):
+                    distances[neighbor] = new_dist
+                    came_from[neighbor] = current
+                    counter += 1
+                    heapq.heappush(heap, (new_dist, counter, neighbor))
+                    visited.add(neighbor)
+        
+        return [], len(visited)