python

Continuing my theme of learning all the languages, I took the opportunity of a programming puzzle to try out the same approach in a handful of different languages to compare how they work.

In this post I explore some differences between R, python, julia, and APL in terms of mutability, and try to make something that probably shouldn’t exist.

I keep hearing the assertion that “writing APL/Haskell/etc… makes you think differently” and I kept wondering why I agreed with the statement but at the same time didn’t think too much of it. I believe I’ve figured out that it’s because I happened to have been using Array-aware languages this whole time! It turns out R is an even better language for beginners than I thought.

One thing that has really caught my attention as I learn more programming languages is the idea of generators or infinite sequences of values. Yes, infinite. Coming from R, that seems unlikely, but in at least several other languages, it’s entirely possible thanks to iterators and lazy evaluation.

I’ve been learning at least one new programming language per month through Exercism and the #12in23 challenge. I’ve keep saying, every time you learn a new language, you learn something about all the others you know. Plus, once you know \(N\) languages, the \(N+1^{\rm th}\) is significantly easier. This post covers a calculation I came across in Haskell, and how I can now do the same in a lot of other languages - and perhaps can’t as easily in others.

I’ve had the impression lately that everyone is learning Rust and there’s plenty of great material out there to make that easier. {gifski} is perhaps the most well-known example of an R package wrapping a Rust Cargo crate. I don’t really know any system language particularly well, so I figured I’d wade into it and see what it’s like.