lab notes
The work on the scheduler is to support async effect handlers. It won't do at all, if a network request always blocks the evaluation of the computational graph. So I embarked on it about two weeks ago. Right now, the API looks like this (subject to change). There&
lab notes
This was a tough past week. I was working on supporting async handlers, even if the reactive part was synchronous. I didn't want the graph to have to wait on network requests. This turned out to be tough. Also I got food poisoning this past week. The design
lab notes
I made good progress on the reactive engine. * Simplified the requirements for define a handler. * Started work on the scheduler * No longer need to handler to ability type checking method, by converting from protocols into abstract base classes. This was one example of where AI lead me astray. I also
lab notes
I spent a good part of this week writing and rewriting a blog post, as part of my commitment to publish more this year. I wrote about 10k words, only to keep about 4k of them. Must be the sunk cost fallacy, because it feels bad to delete entire pages
lab notes
With the release of OpenAI's Deep Research and its testimonies on Twitter, I finally slapped down $200/month for Pro subscription. Deep research is what I do all the time by hand anyway, I figured I'd get a lot of mileage out of it. The second
lab notes
I'd finished up looking into reactivity (with the exception of data type enforced reactivity, like differential dataflow), and I pulled out code with pedagogical sample code implementing signals and autotracking. * iamwilhelm/pedago_signals: A pedagogical implementation of hybrid push-pull signals in Python * iamwilhelm/pedago_autotracking: A pedagogical implementation
lab notes
I'm a little indisposed this week, but I did find some time here and there to do research into effects. I spent the time reading and watching a talk about effects by Oleg Kiselyov. The short version is that side-effects can be formulated as a communication protocol between
lab notes
I'm back, after a little hiatus from writing the notes. Last time, I discovered that I should have been looking more deeply into other reactive models before I embarked on a functional component (React-like) model to model data pipelines. The impedance mismatch should have been indicative that something
lab notes
Last week, I started looking at Signals. When I stepped back and looked at the entire front-end ecosystem, it seemed like many of them outside of React (Solid, Vue, Svelte, Preact), converged on some variation of Signals. There is even a Javascript proposal to include Signals in the language. Given
lab notes
One of my main goals is to make non-CRUD backend pipelines more visible. I didn't think nodes and wires programming was the way to go, but unconsciously, I envisioned just showing the results of a cell next to the cell, like regular computational notebooks. But my underlying assumption
lab notes
I've been a bit anxious about the pace of progress these last three weeks. I wanted to strike a balance between making practical progress and having a sound basis. This last week, I struggled with breaking from structured programming. * What do algebraic effects buy you? * What is the
lab notes
This past week, I worked through more confusion on my part. * Consolidated the representation of an algebraic effect with the React-like components (Fibers) * Worked out a solution for resuming fibers after getting a result back from from the algebraic effect. (Then block) * Use a data description of all cells (Epx)