4 releases
Uses new Rust 2024
| new 0.1.5 | Nov 6, 2025 |
|---|---|
| 0.1.4 | Oct 24, 2025 |
| 0.1.3 | Oct 22, 2025 |
| 0.1.0 | Oct 3, 2025 |
#2 in #studio
8,820 downloads per month
Used in 2 crates
(via kcl-lib)
155KB
3.5K
SLoC
EZPZ
Constraint solver for use in Zoo Design Studio, or wherever you want to use it.
Overview
This project has 3 Rust crates:
kcl-ezpz: The core constraint solver libraryezpz-cli: A CLI tool that lets you easily solve, analyze and benchmark constraint systems usingkcl-ezpz.ezpz-wasm: A WebAssembly library that wrapskcl-ezpzand exposes a few core functions. Intended for the ezpz maintainers to check ifkcl-ezpzcompiles and works in WebAssembly, and to benchmark its performance vs. native code.- Users probably won't need to use this library yourself, it's really intended as a sample application for the maintainers to test with.
- Users should probably integrate
kcl-ezpzinto your web projects directly.
Development
New developers should read CONTRIBUTING.md
Using the CLI
The CLI lets you pass a constraint problem file (described below) and analyze it, solve it, visualize the solution and benchmark how long it took.
Here's a quick video demo:
https://github.com/user-attachments/assets/62a2d4ab-490f-48e5-aa0a-7a2b192fc938
First, install it. From this repo's root, run:
cargo install --path ezpz-cli
Then you can use it like this, by passing it a constraint problem file:
$ ezpz --filepath myconstraints.txt
Problem size: 2000 rows, 2000 vars
Iterations needed: 2
Solved in 2943μs (mean over 100 iterations)
i.e. 339 solves per second
You can also add the --gnuplot option to visualize the resulting points in a gnuplot window, or --gnuplot-png-path points.png to write the visualization to a PNG at the given path instead. If you'd rather print the final points to stdout and process them in your own tool, use --show-points instead.
Constraint problem files
ezpz defines a text format for writing out constraint problems. You don't have to use this format -- you can use the Rust library directly -- but it's a very convenient format. It looks like this:
# constraints
point p
point q
p.x = 0
p.y = 0
q.y = 0
vertical(p, q)
# guesses
p roughly (3, 4)
q roughly (5, 6)
There's two sections, Constraints and Guesses. You define each point (like p and q) and once defined, you can write constraints that use them. For example, you can fix a point's X or Y component (p.x = 0). Or you can relate two points, e.g. vertical(p, q).
For more examples, see the test_cases/ directory.
Dependencies
~15MB
~322K SLoC