diff --git a/komissarovgo/docs2/data2/maze_lab/strategies.py b/komissarovgo/docs2/data2/maze_lab/strategies.py
new file mode 100644
index 0000000..c5ff2e6
--- /dev/null
+++ b/komissarovgo/docs2/data2/maze_lab/strategies.py
@@ -0,0 +1,141 @@
+from abc import ABC, abstractmethod
+from collections import deque
+import heapq
+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
+    
+    @property
+    @abstractmethod
+    def name(self) -> str:
+        pass
+
+
+class BFSStrategy(PathFindingStrategy):
+    
+    @property
+    def name(self) -> str:
+        return "BFS"
+    
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        if start == exit_cell:
+            return [start]
+        
+        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, start, exit_cell)
+            
+            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]], 
+                          start: Cell, exit_cell: Cell) -> List[Cell]:
+        path = []
+        current = exit_cell
+        while current is not None:
+            path.append(current)
+            current = parent.get(current)
+        path.reverse()
+        return path
+
+
+class DFSStrategy(PathFindingStrategy):
+    
+    @property
+    def name(self) -> str:
+        return "DFS"
+    
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        if start == exit_cell:
+            return [start]
+        
+        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):
+    
+    @property
+    def name(self) -> str:
+        return "A*"
+    
+    def _heuristic(self, cell: Cell, target: Cell) -> int:
+        return abs(cell.x - target.x) + abs(cell.y - target.y)
+    
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        if start == exit_cell:
+            return [start]
+        
+        counter = 0
+        open_set = [(0, counter, start)]
+        came_from: Dict[Cell, Optional[Cell]] = {start: None}
+        
+        g_score = {start: 0}
+        f_score = {start: self._heuristic(start, exit_cell)}
+        closed_set = set()
+        
+        while open_set:
+            current_f, _, current = heapq.heappop(open_set)
+            
+            if current in closed_set:
+                continue
+            
+            if current == exit_cell:
+                return self._reconstruct_path(came_from, start, exit_cell)
+            
+            closed_set.add(current)
+            
+            for neighbor in maze.get_neighbors(current):
+                if neighbor in closed_set:
+                    continue
+                
+                tentative_g = g_score[current] + 1
+                
+                if neighbor not in g_score or tentative_g < g_score[neighbor]:
+                    came_from[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    f_score[neighbor] = tentative_g + self._heuristic(neighbor, exit_cell)
+                    counter += 1
+                    heapq.heappush(open_set, (f_score[neighbor], counter, neighbor))
+        
+        return []
+    
+    def _reconstruct_path(self, came_from: Dict[Cell, Optional[Cell]], 
+                          start: Cell, exit_cell: Cell) -> List[Cell]:
+        path = []
+        current = exit_cell
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path
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