2026-rff_mp/lab2/maze_solver.py

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from abc import ABC, abstractmethod
from collections import deque
import heapq
import time
class Cell:
def __init__(self, x, y):
self.x = x
self.y = y
self.is_wall = False
self.is_start = False
self.is_exit = False
def is_passable(self):
return not self.is_wall
class Maze:
def __init__(self, width, height):
self.width = width
self.height = height
self.cells = []
self.start = None
self.exit = None
for y in range(height):
row = []
for x in range(width):
row.append(Cell(x, y))
self.cells.append(row)
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 = [
(0, -1),
(0, 1),
(-1, 0),
(1, 0)
]
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
class MazeBuilder(ABC):
@abstractmethod
def build_from_file(self, filename):
pass
class TextFileMazeBuilder(MazeBuilder):
def build_from_file(self, filename):
with open(filename, "r", encoding="utf-8") as file:
lines = [line.rstrip("\n") for line in file]
if not lines:
raise ValueError("Файл лабиринта пустой")
width = len(lines[0])
for line in lines:
if len(line) != width:
raise ValueError("Строки лабиринта имеют разную длину")
maze = Maze(width, len(lines))
for y, line in enumerate(lines):
for x, symbol in enumerate(line):
cell = maze.get_cell(x, y)
if symbol == "#":
cell.is_wall = True
elif symbol == "S":
if maze.start is not None:
raise ValueError("В лабиринте несколько стартов")
maze.start = cell
cell.is_start = True
elif symbol == "E":
if maze.exit is not None:
raise ValueError("В лабиринте несколько выходов")
maze.exit = cell
cell.is_exit = True
elif symbol == " ":
pass
else:
raise ValueError("Неизвестный символ в лабиринте")
if maze.start is None:
raise ValueError("В лабиринте нет старта")
if maze.exit is None:
raise ValueError("В лабиринте нет выхода")
return maze
class PathFindingStrategy(ABC):
@abstractmethod
def find_path(self, maze, start, exit):
pass
class BFSStrategy(PathFindingStrategy):
def find_path(self, maze, start, exit):
if start is None or exit is None:
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):
def find_path(self, maze, start, exit):
if start is None or exit is None:
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):
def heuristic(self, a, b):
return abs(a.x - b.x) + abs(a.y - b.y)
def find_path(self, maze, start, exit):
if start is None or exit is None:
return [], 0
heap = []
counter = 0
heapq.heappush(
heap,
(self.heuristic(start, exit), counter, start, [start])
)
g_score = {start: 0}
visited = set()
while heap:
_, _, current, path = heapq.heappop(heap)
if current in visited:
continue
visited.add(current)
if current == exit:
return path, len(visited)
for neighbor in maze.get_neighbors(current):
new_cost = g_score[current] + 1
if neighbor not in g_score or new_cost < g_score[neighbor]:
g_score[neighbor] = new_cost
counter += 1
priority = new_cost + self.heuristic(
neighbor,
exit
)
heapq.heappush(
heap,
(
priority,
counter,
neighbor,
path + [neighbor]
)
)
return [], len(visited)
class SearchStats:
def __init__(self, path, time_ms, visited_count):
self.path = path
self.time_ms = time_ms
self.visited_count = visited_count
self.path_length = len(path) if path else 0
class MazeSolver:
def __init__(self, maze, strategy=None):
self.maze = maze
self.strategy = strategy
self.observers = []
def attach(self, observer):
self.observers.append(observer)
def detach(self, observer):
self.observers.remove(observer)
def notify(self, event, data=None):
for observer in self.observers:
observer.update(event, data)
def set_strategy(self, strategy):
self.strategy = strategy
def solve(self):
if self.strategy is None:
raise ValueError("Стратегия не установлена")
self.notify("search_started")
start_time = time.perf_counter()
path, visited_count = self.strategy.find_path(
self.maze,
self.maze.start,
self.maze.exit
)
end_time = time.perf_counter()
time_ms = (end_time - start_time) * 1000
self.notify("search_finished", time_ms)
self.notify("path_found", path)
return SearchStats(
path,
time_ms,
visited_count
)
class Observer(ABC):
@abstractmethod
def update(self, event, data=None):
pass
class ConsoleView(Observer):
def update(self, event, data=None):
if event == "search_started":
print("Поиск начат")
elif event == "search_finished":
print(f"Поиск завершен за {data:.3f} мс")
elif event == "path_found":
print(f"Длина пути: {len(data)}")