Удалить SmirnovaVYu/docs/data/strategies.py

SmirnovaVYu/docs/data/strategies.py

@@ -1,99 +0,0 @@
-from abc import ABC, abstractmethod
-from collections import deque
-from heapq import heappush, heappop
-from typing import List, Dict, Optional
-from models import Cell, Maze
-
-
-class PathFindingStrategy(ABC):
-    
-    @abstractmethod
-    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-        pass
-
-
-class BFSStrategy(PathFindingStrategy):
-    
-    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-        queue = deque([start])
-        visited = {start}
-        parent: Dict[Cell, Optional[Cell]] = {start: None}
-        
-        while queue:
-            current = queue.popleft()
-            
-            if current == exit_cell:
-                return self._reconstruct_path(parent, current)
-            
-            for neighbor in maze.get_neighbors(current):
-                if neighbor not in visited:
-                    visited.add(neighbor)
-                    parent[neighbor] = current
-                    queue.append(neighbor)
-        
-        return []
-    
-    def _reconstruct_path(self, parent: Dict[Cell, Optional[Cell]], current: Cell) -> List[Cell]:
-        path = []
-        while current is not None:
-            path.append(current)
-            current = parent.get(current)
-        return list(reversed(path))
-
-
-class DFSStrategy(PathFindingStrategy):
-    
-    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-        stack = [(start, [start])]
-        visited = {start}
-        
-        while stack:
-            current, path = stack.pop()
-            
-            if current == exit_cell:
-                return path
-            
-            for neighbor in maze.get_neighbors(current):
-                if neighbor not in visited:
-                    visited.add(neighbor)
-                    stack.append((neighbor, path + [neighbor]))
-        
-        return []
-
-
-class AStarStrategy(PathFindingStrategy):
-    
-    def _heuristic(self, cell: Cell, exit_cell: Cell) -> int:
-        return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
-    
-    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
-        counter = 0
-        open_set = [(self._heuristic(start, exit_cell), counter, start)]
-        
-        g_score: Dict[Cell, float] = {start: 0}
-        parent: Dict[Cell, Optional[Cell]] = {start: None}
-        
-        while open_set:
-            _, _, current = heappop(open_set)
-            
-            if current == exit_cell:
-                return self._reconstruct_path(parent, current)
-            
-            for neighbor in maze.get_neighbors(current):
-                tentative_g = g_score[current] + 1
-                
-                if neighbor not in g_score or tentative_g < g_score[neighbor]:
-                    parent[neighbor] = current
-                    g_score[neighbor] = tentative_g
-                    counter += 1
-                    f = tentative_g + self._heuristic(neighbor, exit_cell)
-                    heappush(open_set, (f, counter, neighbor))
-        
-        return []
-    
-    def _reconstruct_path(self, parent: Dict[Cell, Optional[Cell]], current: Cell) -> List[Cell]:
-        path = []
-        while current is not None:
-            path.append(current)
-            current = parent.get(current)
-        return list(reversed(path))