JavaScript Choices for Haskell Programmers

March 20, 2013

So, I’ve not done any blogging since the ill-fated Midwinter Polyphasic Sleep Experiment. I have a backlog of articles I want to write, but most of those involve some significant investment of time and effort. So you get this instead…

Context

I’ve been doing a lot of JavaScript programming recently. One of the two contracts I’m working on at the moment is for a UK university spin-off called OpenBrain, who are trying to bring Bayesian statistics to the masses by making tools that allow scientists to build complex (or simple!) Bayesian models and have them analysed using Markov chain Monte Carlo methods. All the really clever stuff is in the server-side MCMC inference code, but the user-facing side of things is a web app with a Yesod backend. My mission is to prettify this and make it ready for prime-time.

It’s a fairly complicated application that needs to manage literate Markdown documents describing statistical models, data sets for analysis and a bunch of other stuff. The first thing I looked at was a tool for building statistical models based on dynamical systems represented as systems of ordinary or stochastic differential equations. This tool allows you to give algebraic representations of ODEs or SDEs, which are then rendered as MathML (for prettiness and familiarity), you can do simulations of the systems and visualise the results, you can specify data sets that correspond to observations of system variables, you can set up prior distributions for system parameters, and you can then get some code (in a proprietary Haskell-like language specialised for statistical modelling) that can be used to drive MCMC inference for the parameter values.

All that stuff happens on the client side, except for the listing of the available data sets and the rendering of the model into code. This means that you need client side code for expression parsing, analysis of coupled systems of ODEs and SDEs (to turn them into a canonical form that you can simulate from), numerical integration of ODEs and SDEs, graphing, and a framework to tie it all together. That’s a lot of client side code!

Choices, choices…

My original inclination was to use Fay, both because it’s fun and because the server side is all Haskell, but I was a little anxious that it might be too much of a moving target. There’s a lot of work being done at the moment to make Fay better and more robust, which is great, but I don’t have the resources to contribute to that as well as trying to write something fairly substantial using Fay, with the expectation that my code will rot quite quickly as Fay development proceeds.

None of the other Haskelly options appealed very much, which meant I was left with the prospect of writing a big old pile of JavaScript. The expression parsing stuff wasn’t too painful, mostly because of Jison, a JavaScript almost-clone of Bison that made it easy to write a JavaScript equivalent to my Haskell Parsec parser. And the numerical stuff for simulations wasn’t hard either. But the code for taking a set of ODEs and transforming them into a canonical form that can be numerically integrated? That looked super-simple in Haskell and really horrible in JavaScript1. Case analysis by pattern matching really does work better when you have types to match on…

However, the really tricky part was the user interface side of things. I wanted something responsive: if you’re typing an expression for a differential equation and you introduce a new parameter (σ\sigma, say), I want a UI element for that parameter to appear as you type (and to disappear if you erase all references to σ\sigma). In the simulation panel, I wanted to be able to drag over parameter values to change them and have all the plots update immediately. That sort of responsiveness, using the normal JavaScript event-driven approach to interaction, is going to lead to a big bowl of spaghetti.

Angular it is then

Shortly before this, Michael Snoyman had written a blog article about using Fay with Yesod. He also talked about integrating the AngularJS JavaScript framework with Yesod. As we’d ruled out Fay for the moment, I took a look at Angular. It turns out to be really quite neat. It’s a little hard to explain briefly exactly all that Angular is, but there are two factors that stuck out for me:

  1. Data binding: Angular allows you to associate JavaScript variables with DOM elements (these variables live in nested “scopes”, which are also associated with DOM elements). The binding is bidirectional so that if you have a piece of text bound to a variable and you change the variable, the text changes; if you have an input element bound to a variable and the user changes the contents of the input element, the variable changes. There are various ways of writing code that interacts with this data binding and it’s quite a flexible and sophisticated system.

  2. Directives: you can “extend” the HTML language by defining new attributes, classes or element types. These can have HTML templates associated with them, as well as bits of code that can run at different points during Angular’s “HTML compilation” process. Directives are flexible enough that you can (with a little patience) do more or less anything.

A couple of examples of how these things really help: first, the equation editing input elements are now <equation> tags, where equation is an Angular directive that encapsulates a normal input element (active when the element has the focus), error reporting elements and a MathML rendering of the equation content. All of the equation parsing and event handling associated with the interactions between these three elements is encapsulated within the equation directive. The second example is a <scrubbable> element directive. This is a new kind of input element that shows a MathML rendered equation for a parameter (e.g. σ=28\sigma = 28). Clicking on the element allows the user to edit it, control-clicking resets the original value, and click-dragging continuously (or discretely, if an attribute on the element is set appropriately) varies the value of the parameter. Using data binding, the changing value of the “scrubbed” parameter can be directly communicated to other code: in the dynamical systems simulation page, this is used to trigger re-running of simulations and re-rendering of plots.

All in all, I’m pretty happy with Angular. The documentation is a little patchy, there’s a bit of a learning curve, and doing complicated things can require a bit of experimentation, but it’s a very good system for writing complicated interactive client side JavaScript.

Yesod integration

Furthermore, the integration with Yesod is really great. Michael Snoyman wrote a little yesod-angular module as part of his Yesod client-side experimentation, and it turns out to be really rather nice. I’ve hacked my version around quite a bit to help with managing Angular’s dependency injection mechanism, but that’s about all I’ve had to change. Perhaps the nicest feature is the idea of “commands”. Here, in my Yesod handler, in the bit of code that runs in the Angular monad, I can define commands as, for example

Here, TreeItem is some type with a ToJSON instance so that it can be converted to JSON for transmission back to the client. On the client side, you can call this command as

All the data marshalling is handled by ToJSON and FromJSON instances. On the server side, the code is in Yesod’s Handler monad, so you can do all the kinds of things you might normally do in response to client requests, and everything is nicely encapsulated. It’s a really good system.

Conclusion

Writing a Haskell web app? Dithering about the client side? If you can take the uncertainty of programming against a dynamic and developing interface, go with Fay. A lot of people are investing a lot of time in it, it’s already really good, and it’s going to be great. Can’t stand the uncertainty? Look at Yesod.Angular. It’s in Michael’s yesod-js repository.


  1. To get an idea of the issue here, think about the differential equation y(t)+3y(t)+2y(t)=3sinty''(t) + 3 y'(t) + 2 y(t) = 3 \sin t. If you want to integrate this numerically, you need to break it into the two equations w(t)+3w(t)+2y(t)=3sintw'(t) + 3 w(t) + 2 y(t) = 3 \sin t, y(t)w(t)=0y'(t) - w(t) = 0, where we introduce a new function w(t)w(t) for the first derivative of yy. This is the simplest case. You also get cases where you end up with a matrix equation for the first derivatives. And you need to deal with SDEs. It’s not very hard to do on paper, but writing code to do it systematically in all cases is more challenging.