This project implements Conway's Game of Life and Langton's Ant.
Both are cellular automaton simulations. Uses Rich for terminal visualization.

To install make sure you have Python 3.11 or higher (tested with Python 3.13) and uv installed.

1. Clone the repository:

   git clone https://github.com/paulrobello/rich_life.git
   cd rich_life

2. Install the required dependencies:

   uv sync

To install from PyPI, run any of the following commands:

uv tool install rich-life

pipx install rich-life

rich_life

Run the Game of Life simulation using the following command:

uv run rich_life

You can customize the grid size, number of generations, and neighborhood rules using command-line options:

uv run rich_life --width 50 --height 30 --generations 300 --rules moore

Run the Langton's Ant simulation using the following command:

uv run rich_life --mode ants

Available options:

• --width or -w: Width of the grid (default: half of console height)
• --height or -h: Height of the grid (default: half of console height minus 2)
• --infinite or -i: Enable infinite mode. Simulation grid has no bounds (default: False)
• --generations or -g: Number of generations to simulate (default: 100)
• --mode or -m: Simulation mode (options: 'life' or 'ants', default: 'ants')
• --rules or -r: Neighborhood rules for game of life (options: 'moore' or 'van_neumann', default: 'moore')
• --offset-x or -x: Bord display X-coordinate offset for infinite mode (default: 0)
• --offset-y or -y: Bord display Y-coordinate offset for infinite mode (default: 0)
• --rps or -r: Refresh / generations per second (default: 10)
• --follow or -f: Follow the ant in ANTS mode (default: False)

Keys:

• 'Arrows' / 'WSAD': Pan the grid

To run the tests, use the following command:

uv run pytest tests/test_game_of_life.py

• Version 0.3.1: Updated dependencies and ensured compatibility with Python 3.13
• Version 0.3.0: Added follow mode for Langton's Ant
• Version 0.2.0: Better keyboard handling
• Version 0.1.0: Initial release

Contributions are welcome! Please feel free to submit a Pull Request.

This project is open source and available under the MIT License.

Paul Robello (probello@gmail.com)