GitHub - arrxy/libprocessing: An experimental implementation of the Processing API in Rust

libprocessing is an experimental native library with the goal of supporting the implementation of the core Processing API in a variety of languages. The library is written in the Rust programming language and built on top of the Bevy game engine. libprocessing uses WebGPU as its rendering backend and is designed to (eventually) support desktop, mobile, and web targets.

You can learn more about this project from this talk at LibreGraphicsMeeting 2026

Getting started

mewnala (the python library)

Inside of our processing_pyo3 crate we have created a python package that you can easily install with pip. Again, we are still very nascent, but let us know what kinds of snags you may run into while getting this set up. Try running the examples in the processing_pyo3 examples directory.

We are big fans of uv and this is the easiest way to get started using mewnala

Setting up uv on linux or macOS

curl -LsSf https://astral.sh/uv/install.sh | sh

For Windows users:

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Install a mewnala

# Initialize a project with uv
uv init mewnala-sketchbook && cd mewnala-sketchbook

# add the package
uv add mewnala

# run a sketch
uv run sketch.py

Rust (libprocessing)

You'll need to install the Rust toolchain to work on this project. Most users will want to install Rust via rustup, which helps manage Rust toolchain versions.

Build commands

This project uses just as a command runner:

Run just to see available commands.

Building for web

The processing_wasm crate provides WebAssembly bindings that expose a JavaScript API mirroring the C FFI.

Requirements

Install wasm-pack:

You'll also need the wasm32 target:

rustup target add wasm32-unknown-unknown

Build

This outputs the package to target/wasm/.

Run the example

Contributing

We want your help building this library!

One place we could really use some help is with porting Processing examples to using mewnala, and then reporting where you get stuck or where things could be easier. Check out the effort here: https://github.com/processing/processing-examples-mewnala.

You can see a list of outstanding tasks in our issues. However, while we're still in the early phases, consider checking in with us first in the #devs-chat channel on Discord to coordinate our efforts.

You can read our project design principles here.