To try it out:
var Cassowary = require'./index.js'
For the time being, see the 'browser' directory for usage examples (the API is, more or less, the same).
Cassowary is an algorithm that computes flexible, responsive layouts quickly without resorting to piles of imperative code. Just describe the preferred relationships between values, noting which constraints are more important than others, and Cassowary figures out an optimal solution based on the current inputs. When the inputs or constraints change, Cassowary is particularly efficient at computing a new answer quickly based on the last-known solution. These properties together make it ideal for use in layout systems -- indeed, it's the algorithm at the center of Apple's new automatic layout system for Cocoa.
This version dramatically improves the performance of the original translation, removes external library dependencies, and improves hackability. The solver core can now be used inside web workers, at the command line, and directly in modern browsers.
For civil discussion of this port and constraint-based UIs, join the Overconstrained mailing list.
Constraint solvers are iterative algorithms that work towards ever more ideal solutions, often using some variant of Dantzig's simplex method. They are primarialy of interest in situations where it's possible to easily set up a set of rules which you would like a solution to adhere to, but when it is very difficult to consider all of the possible solutions yourself.
Cassowary and other hierarchial constraint toolkits add a unique mechanism for deciding between sets of rules that might conflict in determining which of a set of possible solutions are "better". By allowing constraint authors to specify weights for the constraints, the toolkit can decide in terms of stronger constraints over weaker ones, allowing for more optimal solutions. These sorts of situations arise all the time in UI programming; e.g.: "I'd like this to be it's natural width, but only if that's smaller than 600px, and never let it get smaller than 200px". Constraint solvers offer a way out of the primordial mess of nasty conditionals and brittle invalidations.
If all of this sounds like it's either deeply esoteric or painfully academic, you might start by boning up on what optimizers like this do and what they're good for. I recommend John W. Chinneck's "Practical Optimization: A Gentle Introduction" and the Cassowary paper that got me into all of this: "Constraint Cascading Style Sheets for the Web"