mazegen is a python package that creates randomly generated mazes. Curently, it supports the following algorithms:

• Recursive Backtracking Algorithm
• Aldous-Broder Algorithm
• Hunt and Kill Algorithm
• Prims Algorithm

In the future, the project will be available on PyPI so you could use pip. For now, you have to clone the project and add the files to your directory. You will need all the python files to use all the algorithms provided.

The code is OS independent, so it should work on all platforms. To generate mazes, you could do the following:

from mazegen import generate_maze

generate_maze("backtracking", 101, 101, "Maze.png", True)

The first argument is the algorithm used to generate the maze. It is in form of a string and currently could be the following:

• "backtracking"
• "aldous_broder"
• "hunt_and_kill"
• "prims"

Each string corresponds with its algorithm.

The second and third arguments are the height and width respectively. Note that because of how the algorithms work, the height and width must be odd numbers. If even numbers are given, the generator adds 1 to them to make them odd.

The fourth argument is the path where the image is saved. The path is relative to the location of mazegen.py.

The Fith, and last argument, is a boolean which determines if to show the maze in a window after generation. If True, an OpenCV window will open containing the generated maze.

Below you can see gifs of how the mazes are generated and images of the final maze for each algorithm.

Note: Images are upscaled.

from mazegen import generate_maze

generate_maze("backtracking", 55, 55, "Maze.png", True)

from mazegen import generate_maze

generate_maze("aldous_broder", 55, 55, "Maze.png", True)

from mazegen import generate_maze

generate_maze("hunt_and_kill", 55, 55, "Maze.png", True)

from mazegen import generate_maze

generate_maze("prims", 55, 55, "Maze.png", True)

Please note that this is simply a student hobby project. There might be, and certainly are, areas of improvement. All feedbacks are much appreciated.

Here are my plans for the future of this project:

• Adding more algorithms
• Optimizing current algorithms furthermore
• Creating a package of this project and adding it to PyPI