import sys
from collections import deque
import heapq
import time
import os

class Cell:
    """клетка лабиринта"""
    def __init__(self, x, y, is_wall=False, is_start=False, is_exit=False):
        self.x = x
        self.y = y
        self.is_wall = is_wall
        self.is_start = is_start
        self.is_exit = is_exit
    
    def is_passable(self):
        return not self.is_wall
    
    def __repr__(self):
        return f"Cell({self.x}, {self.y})"


class Maze:
    """лабиринт"""
    def __init__(self, width, height):
        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
    
    def get_cell(self, x, y):
        if 0 <= x < self.width and 0 <= y < self.height:
            return self.cells[y][x]
        return None
    
    def get_neighbors(self, cell):
        neighbors = []
        directions = [(-1, 0), (1, 0), (0, -1), (0, 1)]
        for dx, dy in directions:
            neighbor = self.get_cell(cell.x + dx, cell.y + dy)
            if neighbor and neighbor.is_passable():
                neighbors.append(neighbor)
        return neighbors
    
    def set_start(self, x, y):
        cell = self.get_cell(x, y)
        if cell:
            cell.is_start = True
            self.start = cell
    
    def set_exit(self, x, y):
        cell = self.get_cell(x, y)
        if cell:
            cell.is_exit = True
            self.exit = cell



class MazeBuilder:
    """интерфейс строителя лабиринта"""
    
    def buildFromFile(self, filename):
        raise NotImplementedError


class TextFileMazeBuilder(MazeBuilder):
    """загрузка лабиринта из текстового файла"""
    
    def buildFromFile(self, filename):
        with open(filename, 'r', encoding='utf-8') as f:
            lines = [line.rstrip('\n') for line in f.readlines()]
        
        height = len(lines)
        width = max(len(line) for line in lines) if height > 0 else 0
        
        for i in range(height):
            if len(lines[i]) < width:
                lines[i] = lines[i] + ' ' * (width - len(lines[i]))
        
        maze = Maze(width, height)
        start_count = 0
        exit_count = 0
        
        for y, line in enumerate(lines):
            for x, ch in enumerate(line):
                if ch == '#':
                    maze.get_cell(x, y).is_wall = True
                elif ch == 'S':
                    maze.set_start(x, y)
                    start_count += 1
                elif ch == 'E':
                    maze.set_exit(x, y)
                    exit_count += 1
                else:
                    maze.get_cell(x, y).is_wall = False
        
        if start_count != 1 or exit_count != 1:
            raise ValueError(f"Ошибка: S={start_count}, E={exit_count} (нужно по одному)")
        
        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)
    


class MazeSolver:
    """решатель лабиринта - оркестратор, использующий стратегию"""
    
    def __init__(self, maze):
        self.maze = maze
        self._strategy = None
    
    def setStrategy(self, strategy):
        """динамическая смена стратегии поиска"""
        self._strategy = strategy
        print(f"  Стратегия изменена на: {strategy.get_name()}")
    
    def solve(self):
        """
        решение лабиринта с использованием текущей стратегии.
        возвращает SearchStats (время, посещённые клетки, длина пути)
        """
        if self._strategy is None:
            raise ValueError("Стратегия не установлена. Используйте setStrategy()")
        
        
        start_time = time.perf_counter()
        
      
        path, visited = self._strategy.findPath(self.maze, self.maze.start, self.maze.exit)
        
        
        end_time = time.perf_counter()
        time_ms = (end_time - start_time) * 1000
        
        
        stats = SearchStats(
            time_ms=time_ms,
            visited_cells=visited,
            path_length=len(path) if path else 0
        )
        
        return path, stats