strategies

romanovpv/task 2/docs/data/main.py

@@ -1,12 +1,16 @@
 import model
 from builders import (TextFileMazeBuilder)
+from strategies import (
+    BFSStrategy,
+    DFSStrategy,
+    AStarStrategy
+    )
 
 builder = TextFileMazeBuilder()
 maze = builder.buildFromFile("maze.txt")
-maze.printMaze()
+strategy = DFSStrategy()
-print()
+path = strategy.findPath(maze, maze.start, maze.exit)
-print("Старт:")
+print(f"Метод: {strategy}")
-print(maze.start)
+print("Путь:\n")
-print()
+for cell in path:
-print("Выход:")
+    print(f"({cell.x},{cell.y})")
-print(maze.exit)

romanovpv/task 2/docs/data/strategies.py

@@ -0,0 +1,174 @@
+from abc import ABC, abstractmethod
+from collections import deque
+import heapq
+
+class PathFindingStrategy(ABC):
+    @abstractmethod
+    def findPath(self, maze, start, exit_cell):
+        pass
+    def restorePath(
+            self,
+            parent,
+            start,
+            exit_cell
+    ):
+        path = []
+        current = exit_cell
+        while current != start:
+            path.append(current)
+            current = parent[current]
+        path.append(start)
+        path.reverse()
+        return path
+class BFSStrategy(PathFindingStrategy):
+    def findPath(
+            self,
+            maze,
+            start,
+            exit_cell
+    ):
+        queue = deque([start])
+        visited = {start}
+        parent = {}
+        while queue:
+            current = queue.popleft()
+            if current == exit_cell:
+                return self.restorePath(
+                    parent,
+                    start,
+                    exit_cell
+                )
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(
+                        neighbor
+                    )
+                    parent[
+                        neighbor
+                    ] = current
+                    queue.append(
+                        neighbor
+                    )
+        return []
+
+class DFSStrategy(PathFindingStrategy):
+    def findPath(
+            self,
+            maze,
+            start,
+            exit_cell
+    ):
+        stack = [start]
+        visited = {start}
+        parent = {}
+        while stack:
+            current = stack.pop()
+            if current == exit_cell:
+                return self.restorePath(
+                    parent,
+                    start,
+                    exit_cell
+                )
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(
+                        neighbor
+                    )
+                    parent[
+                        neighbor
+                    ] = current
+
+                    stack.append(
+                        neighbor
+                    )
+        return []
+    
+class AStarStrategy(PathFindingStrategy):
+    def heuristic(
+            self,
+            cell,
+            exit_cell
+    ):
+        return (
+                abs(
+                    cell.x
+                    - exit_cell.x
+                )
+                +
+                abs(
+                    cell.y
+                    - exit_cell.y
+                )
+        )
+    def findPath(
+            self,
+            maze,
+            start,
+            exit_cell
+    ):
+        pq = []
+        heapq.heappush(
+            pq,
+            (
+                0,
+                id(start),
+                start
+            )
+        )
+        parent = {}
+        g_score = {
+            start: 0
+        }
+        visited = set()
+        while pq:
+            _, _, current = (
+                heapq.heappop(
+                    pq
+                )
+            )
+            if current in visited:
+                continue
+            visited.add(
+                current
+            )
+            if current == exit_cell:
+                return self.restorePath(
+                    parent,
+                    start,
+                    exit_cell
+                )
+            for neighbor in maze.getNeighbors(current):
+                new_cost = (
+                        g_score[current]
+                        + 1
+                )
+                if (
+                        neighbor
+                        not in g_score
+                        or
+                        new_cost <
+                        g_score[neighbor]
+                ):
+                    g_score[
+                        neighbor
+                    ] = new_cost
+                    parent[
+                        neighbor
+                    ] = current
+                    priority = (
+                            new_cost
++
+                            self.heuristic(
+                                neighbor,
+                                exit_cell
+                            )
+                    )
+                    heapq.heappush(
+                        pq,
+                        (
+                            priority,
+                            id(neighbor),
+                            neighbor
+                        )
+                    )
+        return []