Реализован этап 3, добавлен A*, некоторые исправления

MusinAA/docs/Report 1.ipynb

@@ -140,7 +140,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.14.3"
+   "version": "3.14.5"
   }
  },
  "nbformat": 4,

MusinAA/task2/strategyObjects/AStar.py

@@ -1,9 +1,45 @@
+import heapq
+from itertools import count
+
 from task2.strategyObjects.pathFindingStrategy import PathFindingStrategy
+from task2.strategyObjects.util import restorePath
 
 from task2.mazeObjects.maze import Maze
 from task2.mazeObjects.cell import Cell
 
 class AStar(PathFindingStrategy):
     """Алгоритм с эвристикой (etc. манхэттенское расстояние) – компромисс между скоростью и оптимальностью."""
+    def heuristic(self, first: Cell, second: Cell) -> int:
+        return abs(first.x - second.x) + abs(first.y - second.y)
+
     def findPath(self, maze: Maze, start: Cell, exit: Cell):
-        ...
+        tie_breaker = count()
+        start_heuristic = self.heuristic(start, exit)
+        heap: list[tuple[int, int, int, Cell]] = [
+            (start_heuristic, start_heuristic, next(tie_breaker), start)
+        ]
+        g_score: dict[Cell, int] = {start: 0}
+        parents: dict[Cell, Cell | None] = {start: None}
+        visited: set[Cell] = set()
+
+        while heap:
+            _, _, _, current = heapq.heappop(heap)
+            if current in visited:
+                continue
+            visited.add(current)
+
+            if current == exit:
+                return restorePath(parents, exit)
+
+            for neighbor in maze.getNeighbors(current):
+                tentative_score = g_score[current]
+                if tentative_score < g_score.get(neighbor, 10**12):
+                    g_score[neighbor] = tentative_score
+                    parents[neighbor] = current
+                    heuristic = self.heuristic(neighbor, exit)
+                    priority = tentative_score + heuristic
+                    heapq.heappush(
+                        heap,
+                        (priority, heuristic, next(tie_breaker), neighbor),
+                    )
+        return []

MusinAA/task2/strategyObjects/BFS.py

@@ -31,4 +31,4 @@ class BFS(PathFindingStrategy):
                 visited[hood] = visited[current] + 1
                 parents[hood] = current
                 q.put(hood)
-        return restorePath(parents, start, exit)
+        return restorePath(parents, exit)

MusinAA/task2/strategyObjects/DFS.py

@@ -31,4 +31,4 @@ class DFS(PathFindingStrategy):
                 parents[hood] = current
                 stack.append(hood)
         
-        return restorePath(parents, start, exit)
+        return restorePath(parents, exit)

MusinAA/task2/strategyObjects/pathFindingStrategy.py

@@ -10,3 +10,4 @@ class PathFindingStrategy(ABC):
     @abstractmethod
     def findPath(self, maze: Maze, start: Cell, exit: Cell):
         """Возвращает список клеток пути от старта до выхода включительно. Пути нет - пустой список."""
+        raise NotImplementedError

MusinAA/task2/strategyObjects/util.py

@@ -1,7 +1,7 @@
 from task2.mazeObjects.maze import Maze
 from task2.mazeObjects.cell import Cell
 
-def restorePath(parents: dict, start: Cell, exit: Cell) -> list[Cell]|None:
+def restorePath(parents: dict, exit: Cell) -> list[Cell]|None:
     path = []
     current = exit
     while current: