ganja.js VS NATS

Some people's brains just work this way. Here's an example of a somewhat popular and regularly maintained library written in a similar style: https://github.com/enkimute/ganja.js/blob/6e97cb45d780cd7c66...

Once your learn to recognise the commonalities, you'll see examples everywhere. The most extreme and stereotypical version is the billboards written by some homeless people. You can probably picture it already in your mind's eye: A wall of very dense text with little whitespace or structure, and a mix of fonts and colours seemingly at random.

I had a brilliant mathematician friend who wrote like this. He would squeeze and entire semester's worth of study notes into a single sheet of paper, on one side. It was impenetrable gibberish to everyone else, but the colours and 2D positioning let him build a mental mind-map.

For people like this, if you reformat their code even a tiny bit, their mental map is invalidated, and they lose track of it completely and become upset. I discovered this (the hard way) when applying automatic code formatting tools to the codebases I mentioned previously.

Personally, I find this type of thing to be absolutely fascinating, because it's the intersection of many fields of study, and hence is under-studied. There's elements of pedagogy, psychology, literacy, compute science, etc...

It's an open question how we can get large groups of neurodiverse humans to collaborate on a codebase when they don't even "read" or "think" in compatible ways!

I was watching bivector videos and how it could be a viable replacement for matrix algebra in video games and I have been very impressed by the intuitiveness and consistency of the equations. There is this ganja.js for demonstrating the graphics and has a rust generated code https://github.com/enkimute/ganja.js/tree/master/codegen/rust I'm too naive to understand the implementation, but I'm glad a library like ultraviolet is here to start paving the use of Geometric Algebra in computer graphics.

Well I've been on a real Geometric Algebra (aka Clifford Algebra) kick lately, and ran across ganja.js [1]. It's a single no deps file that is...impressive. 120k uncompressed, and with it you can construct any degree algebra (including the more esoteric hyperbolic/parabolic ones), render to canvas, svg or webgl(!). It also includes a clever little DSL parser and interpreter (it overloads the scientific notation to name basis vectors!) that lets you construct more complex things from simple things using various kinds of products.

The author, Steven De Keninck, is quite impressive as well, having got his start in the demoscene some time ago. He has a good video from 2019 that explains why this algebra is better than [matrices, tensors, vectors, complex numbers]. Of particular interest (to me anyway) is the 2D projective geometry.

I don't want to oversell it, but ganja is fucking amazing and there is a great deal I want to do with it. For one, I'd like to recapitulate my physics degree with it.

[1] https://github.com/enkimute/ganja.js

[2] https://www.youtube.com/watch?v=tX4H_ctggYo

Great documentation!

Several message brokers, such as NATS and database queues, are not supported by OpenTelemetry (OTel) SDKs. This article will guide you on how to use context propagation explicitly with these message queues.

https://nats.io/ (Tracker removed)

> Connective Technology for Adaptive Edge & Distributed Systems

> An Introduction to NATS - The first screencast

I guess I don't need to know what it is

During our interview, we referred to NATS quite a few times! If you want to learn more about it, Sebastian suggests this tutorial series.

Pueue dumps the state of the queue to the disk as JSON every time the state changes, so when you have a lot of queued jobs this results in considerable disk io. I actually changed it to compress the state file via zstd which helped quite a bit but then eventually just moved on to running NATS [1] locally.

[1] https://nats.io/

Imagine you have an AI-powered personal alerting chat assistant that interacts using up-to-date data. Whether it's a big move in the stock market that affects your investments, any significant change on your shared SharePoint documents, or discounts on Amazon you were waiting for, the application is designed to keep you informed and alert you about any significant changes based on the criteria you set in advance using your natural language. In this post, we will learn how to build a full-stack event-driven weather alert chat application in Python using pretty cool tools: Streamlit, NATS, and OpenAI. The app can collect real-time weather information, understand your criteria for alerts using AI, and deliver these alerts to the user interface.

Why wasn't NATS[1] used ?

Written in Go, single-binary deployment... there's a lot to love about NATS !

[1]https://nats.io/

require nats.io

About cost, see [1]. Also, S3 prices have been increasing and there's been a bunch of alternative offers for object store from other companies. I think people in here (HN) comment often about increasing costs of AWS offerings.

Distributed systems and consensus are inherently hard problem, but there are a lot of implementations that you can study (like Etcd that you mention, or NATS [2], which I've been playing with and looks super cool so far :-p) if you want to understand the internals, on top of many books and papers released.

Again, I never said it was "easy" to build distributed systems, I just don't think there's any esoteric knowledge to what S3 provides.

--

1: https://en.wikipedia.org/wiki/Economies_of_scale

2: https://nats.io/

I am in a project were nats.io is used. Someone thought, it would be a great idea to link data in an event with data in a response using the response channel name.