forked from UNN/2026-rff_mp
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
from collections import deque
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from typing import Optional
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from source.models.base import Cell, Maze
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from source.strategy.algorithms import PathFindingStrategy
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class BFSStrategy(PathFindingStrategy):
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"""Поиск в ширину (Breadth-First Search).
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Гарантирует кратчайший путь по количеству шагов.
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Сложность: O(V + E) по времени и памяти.
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"""
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def find_path(
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self, maze: Maze, start: Optional[Cell] = None, exit: Optional[Cell] = None
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) -> list[Cell]:
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if start is None:
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start = self._find_start(maze)
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if exit is None:
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exit = self._find_exit(maze)
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came_from: dict[Cell, Optional[Cell]] = {start: None}
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queue: deque[Cell] = deque([start])
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while queue:
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current = queue.popleft()
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if current is exit:
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return self._reconstruct_path(came_from, exit)
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for neighbor in maze.get_neighbors(current.x, current.y):
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if neighbor not in came_from:
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came_from[neighbor] = current
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queue.append(neighbor)
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return [] |