import time
import csv
from abc import ABC, abstractmethod
from collections import deque
from typing import List, Dict, Optional, Tuple
import heapq


#Модель лабиринта

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
        self.weight = 1  
    
    def is_passable(self) -> bool:
        return not self.is_wall
    
    def __lt__(self, other):
        return (self.x, self.y) < (other.x, other.y)
    
    def __repr__(self):
        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 y in range(height)] for x in range(width)]
        self.start: Optional[Cell] = None
        self.exit: Optional[Cell] = None
    
    def get_cell(self, x: int, y: int) -> Optional[Cell]:
        if 0 <= x < self.width and 0 <= y < self.height:
            return self.cells[x][y]
        return None
    
    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


#Постройка лабиринта 

class MazeBuilder(ABC):
    
    @abstractmethod
    def build_from_string_list(self, lines: List[str]) -> Maze:
        pass


class TextMazeBuilder(MazeBuilder):
    
    def build_from_string_list(self, lines: List[str]) -> Maze:
        
        height = len(lines)
        width = len(lines[0]) if height > 0 else 0
        maze = Maze(width, height)
        
        for y, line in enumerate(lines):
            for x, char in enumerate(line):
                cell = maze.get_cell(x, y)
                
                if char == '#':
                    cell.is_wall = True
                elif char == 'S':
                    cell.is_start = True
                    maze.start = cell
                elif char == 'E':
                    cell.is_exit = True
                    maze.exit = cell
                elif char == 'W':
                    cell.weight = 3
                elif char == 'D':
                    cell.weight = 2
        
        return maze


#Стратегии поиска пути 

class PathFindingStrategy(ABC):
    
    def __init__(self):
        self.visited_count = 0
    
    @abstractmethod
    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
        pass
    
    def _reconstruct_path(self, came_from: Dict, start: Cell, exit: Cell) -> List[Cell]:
        if exit not in came_from:
            return []
        
        path = []
        current = exit
        
        while current != start:
            path.append(current)
            current = came_from[current]
        
        path.append(start)
        path.reverse()
        return path


class BFSStrategy(PathFindingStrategy):
    
    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
        self.visited_count = 0
        queue = deque([start])
        came_from = {start: None}
        
        while queue:
            current = queue.popleft()
            self.visited_count += 1
            
            if current == exit:
                break
            
            for neighbor in maze.get_neighbors(current):
                if neighbor not in came_from:
                    queue.append(neighbor)
                    came_from[neighbor] = current
        
        return self._reconstruct_path(came_from, start, exit)


class DFSStrategy(PathFindingStrategy):
    
    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
        self.visited_count = 0
        stack = [start]
        came_from = {start: None}
        
        while stack:
            current = stack.pop()
            self.visited_count += 1
            
            if current == exit:
                break
            
            for neighbor in maze.get_neighbors(current):
                if neighbor not in came_from:
                    stack.append(neighbor)
                    came_from[neighbor] = current
        
        return self._reconstruct_path(came_from, start, exit)


class AStarStrategy(PathFindingStrategy):
    
    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
        self.visited_count = 0
        
        def heuristic(a: Cell, b: Cell) -> int:
            return abs(a.x - b.x) + abs(a.y - b.y)
        
        priority_queue = []
        heapq.heappush(priority_queue, (0, start))
        came_from = {start: None}
        g_score = {start: 0}
        
        while priority_queue:
            _, current = heapq.heappop(priority_queue)
            self.visited_count += 1
            
            if current == exit:
                break
            
            for neighbor in maze.get_neighbors(current):
                tentative_g_score = g_score[current] + neighbor.weight
                
                if neighbor not in g_score or tentative_g_score < g_score[neighbor]:
                    came_from[neighbor] = current
                    g_score[neighbor] = tentative_g_score
                    f_score = tentative_g_score + heuristic(neighbor, exit)
                    heapq.heappush(priority_queue, (f_score, neighbor))
        
        return self._reconstruct_path(came_from, start, exit)


class DijkstraStrategy(PathFindingStrategy):
    
    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
        self.visited_count = 0
        
        priority_queue = []
        heapq.heappush(priority_queue, (0, start))
        came_from = {start: None}
        g_score = {start: 0}
        
        while priority_queue:
            current_g, current = heapq.heappop(priority_queue)
            self.visited_count += 1
            
            if current == exit:
                break
            
            for neighbor in maze.get_neighbors(current):
                tentative_g_score = g_score[current] + neighbor.weight
                
                if neighbor not in g_score or tentative_g_score < g_score[neighbor]:
                    came_from[neighbor] = current
                    g_score[neighbor] = tentative_g_score
                    heapq.heappush(priority_queue, (tentative_g_score, neighbor))
        
        return self._reconstruct_path(came_from, start, exit)


#Оркестратор поиска

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 __str__(self):
        return f"Time: {self.time_ms:.3f}ms | Visited: {self.visited_cells} | Path length: {self.path_length}"


class Observer(ABC):
    
    @abstractmethod
    def update(self, event: str):
        pass


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 add_observer(self, observer: Observer):
        self.observers.append(observer)
    
    def _notify(self, event: str):
        for observer in self.observers:
            observer.update(event)
    
    def solve(self) -> Tuple[List[Cell], SearchStats]:
        self._notify("Search started")
        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
        
        stats = SearchStats(time_ms, self.strategy.visited_count, len(path))
        self._notify("Search completed")
        
        return path, stats


#Визуализация

class ConsoleView(Observer):
    
    def update(self, event: str):
        print(f"[Event] {event}")
    
    def render(self, maze: Maze, path: List[Cell]):
        path_set = set(path)
        
        for y in range(maze.height):
            row = ""
            for x in range(maze.width):
                cell = maze.get_cell(x, y)
                
                if cell == maze.start:
                    row += "S"
                elif cell == maze.exit:
                    row += "E"
                elif cell in path_set:
                    row += "*"
                elif cell.is_wall:
                    row += "#"
                elif cell.weight == 3:
                    row += "W"  # Болото
                elif cell.weight == 2:
                    row += "D"  # Песок
                else:
                    row += "."
            print(row)


#Экспериментальная часть

def create_test_mazes() -> Dict[str, Maze]:
    builder = TextMazeBuilder()
    mazes = {}
    
    #Маленький лабиринт 10x10 с простым путём
    small_maze = [
        "S.........",
        "#####.####",
        "..........",
        "####.#####",
        "..........",
        "#.#######.",
        "..........",
        "######.###",
        "..........",
        ".........E"
    ]
    mazes["Small (10x10)"] = builder.build_from_string_list(small_maze)
    
    #Пустой лабиринт 50x50
    empty_maze = ["." * 50 for _ in range(50)]
    empty_maze[0] = "S" + empty_maze[0][1:]
    empty_maze[-1] = empty_maze[-1][:-1] + "E"
    mazes["Empty (50x50)"] = builder.build_from_string_list(empty_maze)
    
    #Средний лабиринт 50x50 с тупиками
    medium_maze = []
    for y in range(50):
        if y == 0:
            row = "S" + "." * 49
        elif y == 49:
            row = "." * 49 + "E"
        elif y % 2 == 1:
            row = "#" * 45 + "." * 5 if y % 4 == 1 else "." * 5 + "#" * 45
        else:
            row = "." * 50
        medium_maze.append(row)
    mazes["Medium with dead ends (50x50)"] = builder.build_from_string_list(medium_maze)
    
    # Большой лабиринт 100x100
    large_maze = []
    for y in range(100):
        if y == 0:
            row = "S" + "." * 99
        elif y == 99:
            row = "." * 99 + "E"
        elif y % 2 == 1:
            row = ("#" * 9 + ".") * 10
        else:
            row = "." * 100
        large_maze.append(row)
    mazes["Large (100x100)"] = builder.build_from_string_list(large_maze)
    
    # Лабиринт без выхода
    no_exit_maze = [
        "S....#....",
        "##########",
        "##########",
        "##########",
        "##########",
        "##########",
        "##########",
        "##########",
        "##########",
        "######...E"
    ]
    mazes["No exit (10x10)"] = builder.build_from_string_list(no_exit_maze)
    
    return mazes


def run_experiments() -> None:
    mazes = create_test_mazes()
    
    strategies = {
        "BFS": BFSStrategy(),
        "DFS": DFSStrategy(),
        "A*": AStarStrategy(),
        "Dijkstra": DijkstraStrategy()
    }
    
    results = []
    
    print("=" * 80)
    print("ЗАПУСК ЭКСПЕРИМЕНТОВ ПО СРАВНЕНИЮ АЛГОРИТМОВ ПОИСКА ПУТИ")
    print("=" * 80)
    
    for maze_name, maze in mazes.items():
        print(f"\nТестирование: {maze_name}")
        print("-" * 60)
        
        for strategy_name, strategy in strategies.items():
            solver = MazeSolver(maze, strategy)
            
            runs = 5
            total_time = 0
            path = []
            stats = None
            
            for _ in range(runs):
                path, stats = solver.solve()
                total_time += stats.time_ms
            
            avg_time = total_time / runs
            
            results.append([
                maze_name,
                strategy_name,
                f"{avg_time:.4f}",
                stats.visited_cells,
                stats.path_length
            ])
            
            print(f"  {strategy_name:10} -> "
                  f"Время: {avg_time:8.3f}мс | "
                  f"Посещено: {stats.visited_cells:5} | "
                  f"Длина пути: {stats.path_length:3}")
    
    with open("results_all.csv", "w", newline="", encoding="utf-8") as csvfile:
        writer = csv.writer(csvfile)
        writer.writerow(["Лабиринт", "Стратегия", "Время (мс)", 
                        "Посещено клеток", "Длина пути"])
        writer.writerows(results)
    
    print("\n" + "=" * 80)
    print("Все эксперименты завершены!")
    print("Результаты сохранены в файл 'results_all.csv'")
    print("=" * 80)


def demonstrate_visualization() -> None:
    """Демонстрация визуализации и паттерна Observer."""
    builder = TextMazeBuilder()
    
    maze_data = [
        "S...#.....",
        ".###.####.",
        ".....#....",
        "####.#####",
        ".....#....",
        ".#######..",
        "..........",
        "######.###",
        "..........",
        ".........E"
    ]
    
    maze = builder.build_from_string_list(maze_data)
    strategy = AStarStrategy()
    solver = MazeSolver(maze, strategy)
    
    console_view = ConsoleView()
    solver.add_observer(console_view)
    
    print("\nДЕМОНСТРАЦИЯ ВИЗУАЛИЗАЦИИ")
    print("=" * 40)
    
    path, stats = solver.solve()
    
    print("\nНайденный путь:")
    console_view.render(maze, path)
    print(f"\nСтатистика: {stats}")
    print(f"   Время: {stats.time_ms:.3f}мс")
    print(f"   Посещено клеток: {stats.visited_cells}")
    print(f"   Длина пути: {stats.path_length}")


if __name__ == "__main__":
    demonstrate_visualization()
    
    run_experiments()