[2] Implement pathfinding strategies (BFS, DFS, A*) with Strategy pattern
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SavelevMI/docs/data/2-nd-exersize/pathfinding.py
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115
SavelevMI/docs/data/2-nd-exersize/pathfinding.py
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# Стратегии поиска пути: BFS, DFS, A* (Strategy pattern)
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from collections import deque
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import heapq
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class PathFindingStrategy:
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def find_path(self, maze, start, exit_cell):
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raise NotImplementedError
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def _reconstruct_path(self, came_from, start, exit_cell):
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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def get_visited_count(self):
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return getattr(self, '_visited_count', 0)
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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queue = deque()
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queue.append(start)
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came_from = {start: None}
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visited = {start}
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while queue:
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current = queue.popleft()
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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came_from[neighbor] = current
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queue.append(neighbor)
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self._visited_count = len(visited)
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return []
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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stack = [start]
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came_from = {start: None}
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visited = {start}
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while stack:
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current = stack.pop()
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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came_from[neighbor] = current
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stack.append(neighbor)
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self._visited_count = len(visited)
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return []
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class AStarStrategy(PathFindingStrategy):
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def _heuristic(self, cell, exit_cell):
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return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
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def find_path(self, maze, start, exit_cell):
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heap = []
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counter = 0
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start_f = self._heuristic(start, exit_cell)
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heapq.heappush(heap, (start_f, counter, start))
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counter += 1
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came_from = {}
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g_score = {start: 0}
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f_score = {start: start_f}
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visited = set()
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while heap:
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current_f, _, current = heapq.heappop(heap)
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visited.add(current)
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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if current_f > f_score.get(current, float('inf')):
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continue
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for neighbor in maze.get_neighbors(current):
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tentative_g = g_score[current] + 1
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if tentative_g < g_score.get(neighbor, float('inf')):
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g
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new_f = tentative_g + self._heuristic(neighbor, exit_cell)
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f_score[neighbor] = new_f
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heapq.heappush(heap, (new_f, counter, neighbor))
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counter += 1
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self._visited_count = len(visited)
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return []
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