This is for you #astronomy geeks out there. A package containing a bunch of technical algorithms used in astronomy. If you’re writing the next best solar eclipse automation app, this is for you!

Look at this interesting graph showing code “survival” over time. It reflects an almost too “textbook” pattern, with older code getting refactored out of existence. The chart comes from the tool linked here.

DHH declares system tests to be a failed experiment in the attached document. This is surprising to me but then not surprising. Surprised because intuitively it seems that system tests should be better for the stated reasons. And politically because it seems that the Ruby world had accepted that unit tests are easy to write but too brittle. And system tests were more real-life and robust. But not surprised because I have always found system tests a pain to write. But I don’t have large scale experience with that so I tended to agree with the world that system tests (aka end-to-end tests) were better. So here comes #DHH to argue that system tests have failed!

I admit I get confused by the various packages in this family of related low or no JavaScript goodies released by DHH. Hotwire, Stimulus, Hotwire Stimulus (something different, I guess). Some come with rails, some compete with each other. No matter, I love them all. I love the idea of not having to write and debug JavaScript. Here’s an article with code that shows a great use case.

A nice deconstruction of a refactoring gone bad. The article makes good points and I agree that Uncle Bob’s (tm) refactoring is not great. Oh but apparently a ghost writer wrote that chapter. Now in defense of the book, it was written many years ago and we’ve all gotten a lot smarter about what it means to write Clean Code (tm). Here’s the article:

Another reason why I believe being the founder of a well funded startup is not risky. If the startup is indeed well funded then you as a founder or employee can count on your salary for say between one and three years. No matter what revenue or earnings are, because they are not expected at the very start. Compare that with a job at an established company where layoffs can come out of nowhere and affect anyone. Not sure which is riskier … it depends … but in my opinion the startup is not clearly riskier. See the attached article for an explanation of one factor, but not the only factor.

Wow a brand new web framework! Where did this spring from, apparently fully formed, out of nowhere? Or am I not hanging out in the right neighborhood? Take a look at the attached site!

The attached article shows nice code examples on how to put arrows pointing at specific points in your graph

This reminds me of the oil barron”s secret to great wealth: “wake up early. Work late. Strike oil”.

Rust is an interesting language no doubt. I’ve written about it before. The attached article does a nice job of laying out the pros and cons, and it rings true to me.

There are now several new and different ways for us to try and get back the magic of #heroku #git-push deployments. The attached link shows a new entrant that’s worth a look

RAG, RAG, RAG. It seems everyone is talking about it. The attached article has a nice hands on scenario to help me understand what RAG is all about.

This article helped me understand a little more about RAG.

Insights about communication across layers in an organization. Pretty sensible advice.

Yes we all do it. Debugging with print statements. This ruby package makes our print statements more informative and findable. Check it out!

I've been doing a lot of setting up lately. Between K3S, Docker, Robots and so on. I've become good friends with the shell, yaml files, bash scripts, and much more. This article shows a nice one-liner approach:

For a while now I’ve seen mentions of the Tailwind css library. I’ve been a Bootstrap guy forever. The attached article is a good explainer to learn about Tailwind and Rails. (The world of tech never stops even for a moment)

I think many technology savvy people are way underestimating the usefulness of large language models, LLMs, like ChatGPT, the best known LLM. But there are others. And they are improving and changing on a weekly basis. But my respect and admiration for their capabilities also makes me (helplessly) worry about how they WILL be used to cause serious harm in the future. The attached article is a great run down of current capabilities of these systems.

An amazing tour de force in mathematical visualization. Honestly I can follow the first half and then I am lost. But I really appreciate the creative and beautiful animations.

This article is part of a series on … testing with python! It is an excellent overview of mocking, explaining the why, but more importantly showing lots of examples and assessing how well and conveniently they work. Worth reading.