GLiPy is a Cellular Automaton Game of Life simulation library written in Python.
- Run simulations from
.life,.rlepattern files, or from a remote URL that points to a valid.rle(widely available on LifeWiki) - Create simluations from scratch using the classic rules (B3/S23), or define your own birth/survival rules
- Build entirely new cell and state types from custom rulesets defined by you (see the protocols available in the
cellandstatemodules) - Use the built-in renderer to visualize simulations in your terminal emulator
- Import
glipyinto your own projects to connect to other front-ends or run your own simulation analysis
- Add support for additional algorithm types
- HashLife
- QuickLife
- Add a simple GUI application (CLI/TUI support currently available)
If you want to create new cell/state rules, extend the existing algorithms driving an automaton's evolution, or use your own rendering tools, you might want to use glipy in your own project.
The Cell and CellState classes (see the cell and state modules) inherit from Protocol to provide maximum flexbility. In other words, you do not need to inerit from these classes, or even import them to your project at all. Simply write your own cell or cell state classes which implement the methods defined in the respective protocol class. The MooreCell and ConwayState classes in each module should be observed as examples on how to do this properly.
The Automaton class is responsible for driving a simluation. It is generic over Cell and CellState, meaning it will accept any class which implements the methods necessary to be considered Cell or CellState as described in the previous section (Of course, this is Python, so Automaton will technically accept anything, but if you don't want your static type checker to yell at you, you should implement properly).
I've implemented some rendering capabilities in a separate project, glipy-cli. glipy-cli will render Conway's Game of Life simulations in your terminal emulator.