[2] add stats(time of compliting maze)

BudakovIS/docs/data/2-nd-exercize/main.py

@@ -1,11 +1,12 @@
 import sys
 from collections import deque
 import heapq
-from typing import List, Dict, Optional
+import time
+from typing import List, Optional
 
 
 class Cell:
-    def __init__(self, x, y):
+    def __init__(self, x: int, y: int):
         self._x = x
         self._y = y
         self._is_wall = False
@@ -13,43 +14,46 @@ class Cell:
         self._is_exit = False
     
     @property
-    def x(self):
+    def x(self) -> int:
         return self._x
     
     @property
-    def y(self):
+    def y(self) -> int:
         return self._y
     
     @property
-    def is_wall(self):
+    def is_wall(self) -> bool:
         return self._is_wall
     
     @is_wall.setter
-    def is_wall(self, value):
+    def is_wall(self, value: bool) -> None:
         self._is_wall = value
     
     @property
-    def is_start(self):
+    def is_start(self) -> bool:
         return self._is_start
     
     @is_start.setter
-    def is_start(self, value):
+    def is_start(self, value: bool) -> None:
         self._is_start = value
     
     @property
-    def is_exit(self):
+    def is_exit(self) -> bool:
         return self._is_exit
     
     @is_exit.setter
-    def is_exit(self, value):
+    def is_exit(self, value: bool) -> None:
         self._is_exit = value
     
-    def is_passable(self):
+    def is_passable(self) -> bool:
         return not self._is_wall
+    
+    def __repr__(self) -> str:
+        return f"Cell({self._x}, {self._y})"
 
 
 class Maze:
-    def __init__(self, width, height):
+    def __init__(self, width: int, height: int):
         self._width = width
         self._height = height
         self._cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
@@ -57,27 +61,27 @@ class Maze:
         self._exit = None
     
     @property
-    def width(self):
+    def width(self) -> int:
         return self._width
     
     @property
-    def height(self):
+    def height(self) -> int:
         return self._height
     
     @property
-    def start(self):
+    def start(self) -> Optional[Cell]:
         return self._start
     
     @property
-    def exit(self):
+    def exit(self) -> Optional[Cell]:
         return self._exit
     
-    def get_cell(self, x, y):
+    def get_cell(self, x: int, y: int) -> Optional[Cell]:
         if 0 <= x < self._width and 0 <= y < self._height:
             return self._cells[y][x]
         return None
     
-    def set_cell(self, x, y, cell_type):
+    def set_cell(self, x: int, y: int, cell_type: str) -> None:
         cell = self.get_cell(x, y)
         if cell is None:
             return
@@ -99,7 +103,7 @@ class Maze:
         elif cell_type == 'path':
             cell.is_wall = False
     
-    def get_neighbors(self, cell):
+    def get_neighbors(self, cell: Cell) -> List[Cell]:
         neighbors = []
         directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
         for dx, dy in directions:
@@ -111,118 +115,136 @@ class Maze:
 
 
 class MazeBuilder:
-    def build_from_file(self, filename):
+    def build_from_file(self, filename: str) -> Maze:
-        raise NotImplementedError("Need to realise in calss")
+        raise NotImplementedError("Need to implement in subclass")
+
 
 class TextFileMazeBuilder(MazeBuilder):
-    def build_from_file(self, filename):
+    def build_from_file(self, filename: str) -> Maze:
-        with open(filename, 'r') as f:
+        with open(filename, 'r', encoding='utf-8') as f:
-            lines = [line.rstrip('\n')for line in f.readlines()]
+            lines = [line.rstrip('\n') for line in f.readlines()]
+        
+        if not lines:
+            raise ValueError("Файл пуст")
+        
         height = len(lines)
-        width = max(len(line) for line in lines) if height > 0 else 0
+        width = max(len(line) for line in lines)
-        start_en = 0
+        
-        exit_en = 0
+        start_count = 0
+        exit_count = 0
         maze = Maze(width, height)
-
+        
-        for y,line in enumerate(lines):
+        for y, line in enumerate(lines):
             for x, ch in enumerate(line):
-                if ch == "#":
+                if x >= width:
-                    maze.set_cell(x,y,"wall")
+                    continue
-                elif ch == "S":
+                if ch == '#':
-                    maze.set_cell(x,y,"start")
+                    maze.set_cell(x, y, "wall")
-                    start_en+=1
+                elif ch == 'S':
-                elif ch == "E":
+                    maze.set_cell(x, y, "start")
-                    maze.set_cell(x,y,"exit")
+                    start_count += 1
-                    exit_en+=1
+                elif ch == 'E':
+                    maze.set_cell(x, y, "exit")
+                    exit_count += 1
                 else:
                     maze.set_cell(x, y, 'path')
-        if start_en > 1 or exit_en > 1 or start_en==0 or exit_en ==0:
+        
-            sys.exit("Error while reading file(you have too many or no match start and exits)")
+        if start_count != 1 or exit_count != 1:
+            raise ValueError(
+                f"Лабиринт должен иметь ровно один S и один E. "
+                f"Найдено: S={start_count}, E={exit_count}"
+            )
+        
         return maze
 
 
+class PathFindingStrategy:
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        raise NotImplementedError("Subclasses must implement find_path")
+    
+    def _reconstruct_path(self, came_from: dict, start: Cell, exit_cell: Cell) -> List[Cell]:
+        path = []
+        current = exit_cell
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path
 
 
-class BFSStrategy:
+class BFSStrategy(PathFindingStrategy):
-    def find_path(self, maze, start, exit):
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
         queue = deque()
         queue.append(start)
-        came_from={}
+        
-        came_from[start]=None
+        came_from = {start: None}
-        visited = set()
+        visited = {start}
-        visited.add(start)
+        
         while queue:
             current = queue.popleft()
-            if current == exit:
+            
-                return self._reconstruct_path(came_from,start,exit)
+            if current == exit_cell:
-            for neighbors in maze.get_neighbors(current):
+                return self._reconstruct_path(came_from, start, exit_cell)
-                if neighbors not in visited:
+            
-                    visited.add(neighbors)
+            for neighbor in maze.get_neighbors(current):
-                    came_from[neighbors] = current
+                if neighbor not in visited:
-                    queue.append(neighbors)
+                    visited.add(neighbor)
+                    came_from[neighbor] = current
+                    queue.append(neighbor)
+        
         return []
-    def _reconstruct_path(self, came_from, start, exit_cell):
-        path = []
-        current = exit_cell
-        while current is not None:
-            path.append(current)
-            current = came_from.get(current)
 
-        path.reverse()
+
-        return path
+class DFSStrategy(PathFindingStrategy):
-class DFSStrategy:
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-    def find_path(self,maze,start,exit):
+        stack = [start]
-        stack =[]
+        
-        stack.append(start)
+        came_from = {start: None}
-        came_from={}
+        visited = {start}
-        came_from[start]=None
+        
-        visited = set()
-        visited.add(start)
         while stack:
             current = stack.pop()
-            if current == exit:
+            
-                return self._reconstruct_path(came_from,start,exit)
+            if current == exit_cell:
-            for neighbors in maze.get_neighbors(current):
+                return self._reconstruct_path(came_from, start, exit_cell)
-                if neighbors not in visited:
+            
-                    visited.add(neighbors)
+            for neighbor in maze.get_neighbors(current):
-                    came_from[neighbors]= current
+                if neighbor not in visited:
-                    stack.append(neighbors)
+                    visited.add(neighbor)
+                    came_from[neighbor] = current
+                    stack.append(neighbor)
+        
         return []
 
 
-    def _reconstruct_path(self, came_from, start, exit_cell):
+class AStarStrategy(PathFindingStrategy):
-        path = []
+    def _heuristic(self, cell: Cell, exit_cell: Cell) -> int:
-        current = exit_cell
+        return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
-        while current is not None:
+    
-            path.append(current)
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-            current = came_from.get(current)
-
-        path.reverse()
-        return path
-        
-
-class AStarStrategy:
-    def _heuristic(self, cell,exit_cell):
-        return abs(cell.x -exit_cell.x)+abs(cell.y-exit_cell.y)
-    def find_path(self,maze, start, exit_cell):
         heap = []
         counter = 0
-        start_f = 0 + self._heuristic(start,exit_cell)
+        
+        start_f = self._heuristic(start, exit_cell)
         heapq.heappush(heap, (start_f, counter, start))
-        counter +=1
+        counter += 1
-
+        
         came_from = {}
         g_score = {start: 0}
         f_score = {start: start_f}
-
+        
         while heap:
             current_f, _, current = heapq.heappop(heap)
-            if current==exit_cell:
+            
+            if current == exit_cell:
                 return self._reconstruct_path(came_from, start, exit_cell)
-            if current_f>f_score.get(current, float("inf")):
+            
+            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
@@ -230,28 +252,65 @@ class AStarStrategy:
                     f_score[neighbor] = new_f
                     heapq.heappush(heap, (new_f, counter, neighbor))
                     counter += 1
+        
         return []
-    def _reconstruct_path(self, came_from, start, exit_cell):
+
-        path = []
+
-        current = exit_cell
+class SearchStats:
-        while current is not None:
+    def __init__(self, time_ms: float, visited_cells: int, path_length: int):
-            path.append(current)
+        self.time_ms = time_ms
-            current = came_from.get(current)
+        self.visited_cells = visited_cells
-        path.reverse()
+        self.path_length = path_length
-        return path
+    
+    def __repr__(self) -> str:
+        return f"SearchStats(time={self.time_ms:.3f}ms, visited={self.visited_cells}, path_length={self.path_length})"
+
+
+class MazeSolver:
+    
+    def __init__(self, maze: Maze):
+        self._maze = maze
+        self._strategy = None
+    
+    def set_strategy(self, strategy: PathFindingStrategy) -> None:
+        self._strategy = strategy
+    
+    def solve(self) -> Optional[SearchStats]:
+        if self._strategy is None:
+            print("Ошибка: стратегия не установлена")
+            return None
+        
+        start_time = time.perf_counter()
+        
+        path = self._strategy.find_path(self._maze, self._maze.start, self._maze.exit)
+        
+        end_time = time.perf_counter()
+        time_ms = (end_time - start_time) * 1000
+        
+        visited_cells = 0
+        
+        return SearchStats(time_ms, visited_cells, len(path))
+
 
 if __name__ == "__main__":
     builder = TextFileMazeBuilder()
     maze = builder.build_from_file("maze1.txt")
+    
     print(f"Лабиринт {maze.width}x{maze.height}")
     print(f"Старт: ({maze.start.x}, {maze.start.y})")
     print(f"Выход: ({maze.exit.x}, {maze.exit.y})")
-    bfs = BFSStrategy()
+    print("-" * 40)
-    path = bfs.find_path(maze, maze.start, maze.exit)
+    
-    print(f"BFS: путь найден, длина = {len(path)}")
+    solver = MazeSolver(maze)
-    dfs = DFSStrategy()
+    
-    path = dfs.find_path(maze, maze.start, maze.exit)
+    solver.set_strategy(BFSStrategy())
-    print(f"DFS: путь найден, длинна = {len(path)}")
+    stats = solver.solve()
-    astar = AStarStrategy()
+    print(f"BFS: {stats}")
-    path = astar.find_path(maze, maze.start, maze.exit)
+    
-    print(f"A*: путь найден, длина = {len(path)}")
+    solver.set_strategy(DFSStrategy())
+    stats = solver.solve()
+    print(f"DFS: {stats}")
+    
+    solver.set_strategy(AStarStrategy())
+    stats = solver.solve()
+    print(f"A*: {stats}")