2026-rff_mp/BudakovIS/docs/data/2-nd-exercize/main.py

import sys
from collections import deque
import heapq
import time
from typing import List, Optional


class Cell:
    def __init__(self, x: int, y: int):
        self._x = x
        self._y = y
        self._is_wall = False
        self._is_start = False
        self._is_exit = False
    
    @property
    def x(self) -> int:
        return self._x
    
    @property
    def y(self) -> int:
        return self._y
    
    @property
    def is_wall(self) -> bool:
        return self._is_wall
    
    @is_wall.setter
    def is_wall(self, value: bool) -> None:
        self._is_wall = value
    
    @property
    def is_start(self) -> bool:
        return self._is_start
    
    @is_start.setter
    def is_start(self, value: bool) -> None:
        self._is_start = value
    
    @property
    def is_exit(self) -> bool:
        return self._is_exit
    
    @is_exit.setter
    def is_exit(self, value: bool) -> None:
        self._is_exit = value
    
    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: int, height: int):
        self._width = width
        self._height = height
        self._cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
        self._start = None
        self._exit = None
    
    @property
    def width(self) -> int:
        return self._width
    
    @property
    def height(self) -> int:
        return self._height
    
    @property
    def start(self) -> Optional[Cell]:
        return self._start
    
    @property
    def exit(self) -> Optional[Cell]:
        return self._exit
    
    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: int, y: int, cell_type: str) -> None:
        cell = self.get_cell(x, y)
        if cell is None:
            return
        
        if cell_type == 'wall':
            cell.is_wall = True
        elif cell_type == 'start':
            if self._start:
                self._start.is_start = False
            cell.is_start = True
            cell.is_wall = False
            self._start = cell
        elif cell_type == 'exit':
            if self._exit:
                self._exit.is_exit = False
            cell.is_exit = True
            cell.is_wall = False
            self._exit = cell
        elif cell_type == 'path':
            cell.is_wall = False
    
    def get_neighbors(self, cell: Cell) -> List[Cell]:
        neighbors = []
        directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
        for dx, dy in directions:
            nx, ny = cell.x + dx, cell.y + dy
            neighbor = self.get_cell(nx, ny)
            if neighbor and neighbor.is_passable():
                neighbors.append(neighbor)
        return neighbors


class MazeBuilder:
    def build_from_file(self, filename: str) -> Maze:
        raise NotImplementedError("Need to implement in subclass")


class TextFileMazeBuilder(MazeBuilder):
    def build_from_file(self, filename: str) -> Maze:
        with open(filename, 'r', encoding='utf-8') as f:
            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)
        
        start_count = 0
        exit_count = 0
        maze = Maze(width, height)
        
        for y, line in enumerate(lines):
            for x, ch in enumerate(line):
                if x >= width:
                    continue
                if ch == '#':
                    maze.set_cell(x, y, "wall")
                elif ch == 'S':
                    maze.set_cell(x, y, "start")
                    start_count += 1
                elif ch == 'E':
                    maze.set_cell(x, y, "exit")
                    exit_count += 1
                else:
                    maze.set_cell(x, y, 'path')
        
        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(PathFindingStrategy):
    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
        queue = deque()
        queue.append(start)
        
        came_from = {start: None}
        visited = {start}
        
        while queue:
            current = queue.popleft()
            
            if current == exit_cell:
                return self._reconstruct_path(came_from, start, exit_cell)
            
            for neighbor in maze.get_neighbors(current):
                if neighbor not in visited:
                    visited.add(neighbor)
                    came_from[neighbor] = current
                    queue.append(neighbor)
        
        return []


class DFSStrategy(PathFindingStrategy):
    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
        stack = [start]
        
        came_from = {start: None}
        visited = {start}
        
        while stack:
            current = stack.pop()
            
            if current == exit_cell:
                return self._reconstruct_path(came_from, start, exit_cell)
            
            for neighbor in maze.get_neighbors(current):
                if neighbor not in visited:
                    visited.add(neighbor)
                    came_from[neighbor] = current
                    stack.append(neighbor)
        
        return []


class AStarStrategy(PathFindingStrategy):
    def _heuristic(self, cell: Cell, exit_cell: Cell) -> int:
        return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
    
    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
        heap = []
        counter = 0
        
        start_f = self._heuristic(start, exit_cell)
        heapq.heappush(heap, (start_f, counter, start))
        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:
                return self._reconstruct_path(came_from, start, exit_cell)
            
            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_cell)
                    f_score[neighbor] = new_f
                    heapq.heappush(heap, (new_f, counter, neighbor))
                    counter += 1
        
        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) -> 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})")
    print("-" * 40)
    
    solver = MazeSolver(maze)
    
    solver.set_strategy(BFSStrategy())
    stats = solver.solve()
    print(f"BFS: {stats}")
    
    solver.set_strategy(DFSStrategy())
    stats = solver.solve()
    print(f"DFS: {stats}")
    
    solver.set_strategy(AStarStrategy())
    stats = solver.solve()
    print(f"A*: {stats}")