Some "perfect" maze generating and solving in Python.
Written during Hacker School, Batch[4], Fall 2012.
dfs_maze.py generates and solves a perfect maze, step by step. Starting with cells, each containing 4 walls, visit cells and knock down walls to add unvisited cells to the network until all cells have been visited.
Run this command:
python dfs_maze.py
Optionally, to specify the maze dimensions you can pass in the desired number of rows and columns. This command creates a maze with 3 rows and 4 columns.
python dfs_maze.py 3 4
The solver solves the maze from the top left corner to the bottom right corner. The solved maze will look something like this:
+ -- + -- + -- + -- +
| [] | xx xx xx |
+ + -- + -- + +
| [] [] [] [] |
+ -- + -- + -- + +
| [] |
+ -- + -- + -- + -- +
- Walls denoted by
--and| - Solution path marked by
[] - Paths visited but not in solution marked by
xx
random_kruskal_maze.py generates (but doesn't solve... yet!) a perfect maze using a randomized version of Kruskal's minimum spanning tree algorithm. Start out with all walls and randomly knock down walls if they separate cells in disjoint sets until only one set remains.
Run this command:
python random_kruskal_maze.py
Or with specified numbers of rows and columns:
python random_kruskal_maze.py <rows> <cols>
Sample 6 x 8 maze:
_ _ _ _ _ _ _ _
| _ _ | | | |
| |_ |_ | | _|
| |_ _ | _ _| |
|_|_ _ |_ _ _ |
|_ _ _| _| | |
|_ _ _ _ _ _|_ _|
- Walls denoted by
-and|
-
ThinkLabrynth's Maze Classification
-
Wikipedia article on maze generating algorithms
-
MazeWorks How to Build a Maze
- write solver for kruskal
- try other algorithms
- allow human solving