Comment by crabmusket | Hacker News Reader

Comment by crabmusket | Hacker News Reader

Something I rarely see addressed in articles about reactivity systems is how the desired syntax/developer experience affects the algorithms.

For example, I think all the algorithms discussed in this article require knowing the graph topology up front. Even dynamic dependencies need to be known ahead of time, unless I'm misreading.

However, take Vue's reactivity for example. Here's a simple input and output:

    const input = ref(1);
    const output = computed(() => ref.value + 1);

Without actually attempting to evaluate the closure that defines `output`, there's no way of knowing what it depends on.*

My working understanding of such systems, which I think are more or less similar to all the new "signals" libraries popping up in JS, is that they are... Pull-push systems? First, the UI code (i.e. the HTML or JSX template functions) request the value of an output. The reactivity system evaluates the graph (pull), recording dependencies as it goes.

Then, later, when an input changes, it can use the graph it built up to update (push) dirty states and work out which of the currently-live output nodes need to be re-evaluated.

*The only other approach would be to analyse the syntax of the source code itself to create that static dependency graph. Which I understand is what e.g. Svelte does.

Yeah, the UX/DX of the turning these algorithms into something usable is really interesting, and something I didn't get to talk much about.

With the variations on the push algorithm, you do kind of need to know the graph topology ahead of time, at least to be able to traverse it efficiently and correctly (this is the topological sorting thing). But for pull (and therefore for push-pull), the dependencies can be completely dynamic - in a programming language, you can call `eval` or something, or in a spreadsheet you could use `indirect` to generate cell references dynamically. For push-pull specifically, when you evaluate a node you would generally delete all of its upstream connections (i.e. for each cell it depends on currently, remove that dependency) and then rebuild that node's connections to the graph while evaluating it.

Signals libraries are exactly where I found this concept, and they work basically like you describe. I think this is a big part of what makes signals work so well in comparison to, say, RxJS - they're basically the same concept (here's a new reactive primitive, let's model our data in terms of this primitive and then plug that into the UI, so we can separate business logic from rendering logic more cleanly), but the behaviour of a signal is often easier to understand because it's not built from different combinators but just described in "ordinary" code. In effect, if observables are monads that need to be wired together with the correct combinators, then signals are do-notation.

With your push-pull algorithm, were you considering that the graph had already been built up, e.g. by an earlier pull phase? And the push-pull bit is just for subsequent updates? If so, then I think I'm following :).

I've been working in the context of reactivity on the backend where you're often loading up the calculations "from scratch" in a request.

I agree with your monad analogy! We looked into using something like Rx in the name of not reinventing the wheel. If you build out your calculation graph in a DSL like that, then you can do more analysis of the graph structure. But as you said in the article, it can get complicated. And Rx and co are oriented towards "push" flows where you always need to process every input event. In our context, you don't necessarily care about every input if the user makes a bunch of changes at once; it's very acceptable to e.g. debounce the end result.

With push-pull, assuming you set up the dependency chain on pull, you need an initial pull to give you your initial values and wire up the graph, and then every time an update comes in you use the push phase to determine what should be changed, and the pull phase to update it consistently.

do-notation -> dot-notation, right?

Do-notation in the sense of Haskell's monadic do blocks: https://en.wikibooks.org/wiki/Haskell/do_notation

aha. thanks! TIL

Svelte 5 does runtime dependency wiring afaik.

From what I understand, Svelte 4 calculated dependencies at compile time. Whereas Svelte 5 does it automatically at runtime based on which values are accessed in tracking contexts (effect / computed value callbacks). This means objects marked as reactive have to be wrapped in proxies to intercept gets / sets. And plain values have to be transformed to objects at compile time. The deps are also recalculated after every update, so accessing state in conditionals can cause funkiness.

But after working with Svelte 5 daily for a few months, I don't think I like the implicitness. For one, reactivity doesn't show up in type signatures. So I have to remember whats reactive and what's not. Another is that making plain values (string, numbers, etc) reactive is really a trap. The reactivity doesn't cross file boundaries so you have to do weird things like exporting a getter / setter instead of the variable.

I agree with all of that. With reactive systems I prefer just making objects deeply reactive and using them as view models, while limiting the amount of derived / computed values. Both Vue and Mobx work well for this.

I've worked through the same process in SolidJS, which had the dynamic dependency tracking from the beginning.

I agree that not seeing reactivity in the type system can be irritating. In theory, you can wrap reactive elements in `Computed` objects (Angular's signals have this, I believe) so you can follow them a bit better, but the problem is that you can still accidentally end up with implicitly reactive values, so it only works as a kind of opt-in "here be reactivity" signal, and you can't guarantee that just because you can't see a `Computed`, that reactivity has been ruled out.

That said, I find I eventually built up a good intuition for where reactivity would be, usually with the logic that functions were reactive and single values weren't, kind of like thunks in other contexts. For me, at least, it feels much simpler to have this implicit tracking, because then I don't need to define dependencies explicitly, but I can generally see them in my code.

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