[2] Implement pathfinding strategies (BFS, DFS, A*) with Strategy pattern

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SavelevMI 2026-05-21 14:09:02 +00:00
parent 28c4c61a68
commit 6005f2f8b2

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# Стратегии поиска пути: BFS, DFS, A* (Strategy pattern)
from collections import deque
import heapq
class PathFindingStrategy:
def find_path(self, maze, start, exit_cell):
raise NotImplementedError
def _reconstruct_path(self, came_from, start, exit_cell):
path = []
current = exit_cell
while current is not None:
path.append(current)
current = came_from.get(current)
path.reverse()
return path
def get_visited_count(self):
return getattr(self, '_visited_count', 0)
class BFSStrategy(PathFindingStrategy):
def find_path(self, maze, start, exit_cell):
queue = deque()
queue.append(start)
came_from = {start: None}
visited = {start}
while queue:
current = queue.popleft()
if current == exit_cell:
self._visited_count = len(visited)
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)
self._visited_count = len(visited)
return []
class DFSStrategy(PathFindingStrategy):
def find_path(self, maze, start, exit_cell):
stack = [start]
came_from = {start: None}
visited = {start}
while stack:
current = stack.pop()
if current == exit_cell:
self._visited_count = len(visited)
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)
self._visited_count = len(visited)
return []
class AStarStrategy(PathFindingStrategy):
def _heuristic(self, cell, exit_cell):
return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
def find_path(self, maze, start, exit_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}
visited = set()
while heap:
current_f, _, current = heapq.heappop(heap)
visited.add(current)
if current == exit_cell:
self._visited_count = len(visited)
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
self._visited_count = len(visited)
return []