re-frame VS Sonic Pi

This article always reminds me of this excerpt from re-frame’s docs [0]:

> Now, you think and design abstractly for a living, and that repetition will feel uncomfortable. It will call to you like a Siren: "refaaaaactoooor meeeee". "Maaaake it DRYYYY". So here's my tip: tie yourself to the mast and sail on. That repetition is good. It is serving a purpose. Just sail on.

[0]: https://github.com/day8/re-frame/blob/master/docs/correcting...

* Single-Page App: shadow-cljs for the build concerns (https://github.com/thheller/shadow-cljs), Reagent with Re-frame for complex/large app (https://reagent-project.github.io and https://github.com/day8/re-frame). Even if we now prefer using HTMX (https://htmx.org) and server-side rendering (Hiccup way of manipulating HTML is just amazing, https://github.com/weavejester/hiccup).

Big and/or complete projects that use re-frame The main list: https://github.com/day8/re-frame/blob/master/docs/External-Resources.md

Reflet is a set of tools for building Re-frame + React based web apps with graph and non-graph data models. This includes:

https://github.com/day8/re-frame

Notably the author of re-frame has been weary of hooks.

I think that’s for a good reason. The approach in re frame feels like the best way to manage state so far for a react based app. Everything that changes state flows through an event. State can only be observed through subscriptions. Side effects are isolated to their own type of event. Debugging and testing are so straight forward with these concepts.

Redux got close but it has two problems in my mind. Like hooks, it encapsulates for no good reason. Put the state in one thing that you can observe holistically before and after pure events. It also has too much boiler plate.

The cljs stack I hear about a lot (and use) is ShadowCLJS with reagent (https://reagent-project.github.io/) and re-frame (https://day8.github.io/re-frame/). ShadowCLJS is more of a build tool, but is really well documented and easy to use. Reagent is basically react but a simpler API, and re-frame is a layer on top of that provides data subscriptions and event-handlers to manage app state. It's overkill for some apps but I find it's actually super easy to work with and not as much complexity as I thought.

For backend there is luminus (https://luminusweb.com/) or Kit (https://kit-clj.github.io/). They are basically project templates that wire together a ton of popular solutions for various things - database access, migrations, security, html templating, etc. Also includes frontend frameworks like re-frame if you want.

Reflet aims to be a natural progression on top of Re-frame to support complex, data driven requirements. In that sense, it is both easy to learn, but powerful. You could say it's sort of like Re-frame++ (or Fulcro for Re-frame). Its main design goals are:

At my current client we're working on having a frontend architecture for writing SPAs in JavaScript similar to re-frame's one: an event-driven bus with effects and coeffects for state management[1] (commands) and subscriptions using reselect's selectors (queries).

Some of us had worked with effects and coeffects before while developing SPAs with re-frame and had experienced how good it is. After working with re-frame, when you come to horizon, you realize how a good architecture can make a dramatic difference in clarity, testability, understandability and easiness of change.

https://youtu.be/geeK1-jjlhY (talk about an initial prototype with re-frame and the decision to do a rewrite in Clojure)

I have wondered what grooves it could come with using https://sonic-pi.net/

Something fascinating about seeing a 'score' for generative music written out as a sort of specification like that.

There's enough detail there that you can take those instructions and reimplement your own version of it, and you'll end up with essentially the same 'piece of music', but certainly a different interpretation of it. Because while the score lays out some details precisely, it leaves other choices less clear. What does 'all inversions' really mean when enumerating chords? Does it include open, spread voicings? What durations should we choose from for our random waveforms? How short is 'short' when deciding to repeat? And of course, what wave synths should you use, and how should you modulate them?

All those are similar to the decisions a traditional instrumentalist makes when interpreting a sheet music score for performance - here, a generative music coder can follow this 'score' and produce a program that represents their own interpretation of the piece.

Coding it up in Sonic Pi (https://sonic-pi.net/) was a fun exercise, and I feel like I was able to produce something along the lines of what the composer intended. It carries the same kind of mood that the recording in the video has. But it's my own 'performance' of the work, if that makes sense (even if it's actually Sonic Pi 'performing' it at runtime...)

All of which got me thinking about the relationship more generally between specification, and implementation. Considering different programmers' implementations of algorithms as individual 'performances' of scores from the overall design - and then thinking about developers building elements of a larger system architecture as individual performers working to deliver their part of the performance as part of a band or orchestra. Some groups, maybe they're directed by a conductor-architect; others maybe are improvisers, riffing off one another and occasionally stepping up to deliver a solo. And some are maybe solid session performers, showing up and delivering strong but unflashy performances to a producer's specification.

So overall, a nice meditative coding exercise for a Sunday afternoon, and a shift in perspective. Thanks for sharing it.

On a seriously light-hearted note, Herve Aniglo, talked about teaching children to code with music using Sonic PI, a language agnostic platform that helps you learn recursions, looping, circuit breaking and functional programming by creating simple tunes.

https://www.youtube.com/playlist?list=PLPYzvS8A_rTYEba_4SDvR...

- Sonic Pi is built on-top of SuperCollider, but it's MUCH easier to get started with making bleeps and bloops. Sam Aaron, who originally created Overtone (a Clojure front-end for SuperCollider) created Sonic Pi initially to teach kids computer programming and music, but now it's turning into a pretty nice live-coding setup. The language is basically a DSL extension of Ruby, and although it's very elegant, I feel like it's a little nerfed in terms of a full language when compared to SCLang, so I'm sticking with the latter for now. High recommend checking it out if you're new to making music or code. https://sonic-pi.net/

- This 'Intro To Live Coding' vid from Alex McLean is great. Gives a good overview of a few fun tools out there that I won't mention here for sake of time (check out Gibber and Hydra for web-based coding things. Gibber is really slick). Alex invented Tidal Cycles, which I feel is like god-tier in terms of power and conciseness. Maybe I'll tinker with Tidal someday, but I want to start with SC.

Strange dice that it seems to mostly be c++, sponsored by 3 prominent elixir shops, with an original OSC server implementation by Joe Armstrong.

https://github.com/sonic-pi-net/sonic-pi/tree/dev/app/server...

There is a programming language+IDE called SonicPI. It's designed to create music by writing code. You can install the program from the lin, then ask chatGPT to generate some sonic PI code that produces some nice melody. Then just copy the code and paste it into the sonicPI program, and run it by clicking the run button. Here's a conversation for example