Life in Python

This project is an implementation of Conway's Game of Life (or Life for short) in Python.

About Life

For information about the game, see About Life. For information about the creator of the game, see About John Conway.

Running the Project

The following is a set of recommended directions for running the project. Note that these directions assume a Python 3 interpreter exists and that it has been associated with the shell command python3. The project was developed and tested with version 3.8.2 of Python. Compatibility with previous versions may exist but is not guaranteed.

• Start a shell session and navigate to the root directory of the project/cloned repo
• Run the command python3 -m venv venv to create a Python 3 virtual environment (venv) using your Python 3 setup
• Run the command source venv/bin/activate to activate the venv
• Run the command pip install --upgrade pip to upgrade pip (the Python package manager)
• Run the command python -m pip install -r requirements.txt to install the required packages

From the root of the project directory, you should now be able to do the following:

• To play the game, run the command ./venv/bin/python3 life.py
• To run all tests, run the command ./venv/bin/python3 -m pytest test/

When you are done, you can deactivate the venv using the command deactivate. If you want to run the game or tests again after deactivating the venv, first reactivate the venv using the command above.

Implementation Details

This section assumes basic familiarity with Life. If you are not familiar with Life but want to read this section, please read the section About Life, or consult a source like Wikipedia on the game.

All source files are well-documented, so explanations of or details about these files will not be supplied here.

Common implementations of Life represent the state of a world as a 2D list of bits or booleans. Typically a live cell is truthy while a dead cell is falsy. While this approach is intuitive, dead calls don't need to be stored, and doing so can have notable costs in terms of memory usage.

An alternative approach is to store only the coordinates of live cells, requiring significantly less memory. By representing coordinates as tuples and storing them in a set, further efficiencies are gained via hashing.

This implementation uses a toroidal grid. As such, objects that leave the screen on one edge will re-enter the screen with the same trajectory and velocity at the equivalent location on the opposing edge.