julia

I keep saying that the more programming languages you know, the more you will understand all the others you know - I’m now at the point where I want to solve every problem I see in a handful of different languages. They all offer different functionality, and some are certainly more suited to particular problems than others, but there’s a world of difference between two characters and importing from two libraries.

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.

Another day, another short riddle to be solved with several programming languages! This one is nice because solving it doesn’t need a lot of code, but it uses some interesting aspects of evaluation.

I’ve tried to get this same image transformation working at least three times now, but I can finally celebrate that it’s working! I’ve been (re-)learning Julia and I still love the language, so it was time to take my learning to the next level and actually build a package.

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.

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.

With Functional Programming, we write functions which take arguments and do something with or based on those arguments. You might not think there’s much to learn about given that tiny description of “an argument to a function” but the syntax and mechanics of different languages is actually widely variable and intricate.

I’ve been following the drama of the RustConf Keynote Fiasco (RKNF, per @fasterthanlime) from a great distance - I’m not involved in that community beyond starting to learn the language. But the controversial topic itself Compile-Time Reflection seemed like something interesting I could learn something about.

I’ve been working my way through Exercism exercises in a variety of languages because I strongly believe every language you learn something about teaches you about all the others you know, and makes for useful comparisons between what features they offer. I was Learning Me a Haskell for Great Good (there’s a guide/book by that name) and something about Pattern Matching just seemed extremely familiar.