rstats

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.

Plotly has a nice way of making click-events available to the calling language, but it doesn’t quite work simply when using subplot(). This isn’t a post about a new feature, but I didn’t quickly find a resource for it so I’ll add my findings to make it easier for the next person.

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.

Don’t show me puzzles, unless you want to be responsible for me staying up too late solving them. I’m far too easily nerd-sniped. This one was certainly the most complex I’ve ever solved. Quite complicated too, but definitely the most complex (you’ll see).

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.

Updated: 2022-09-04

I took a very long time to post about the last Australian Signals Directorate (then DSD) decryption, so this time I’ll be a lot more punctual. This article was published today announcing that ASD have collaborated to release a new 50c coin containing a decryption challenge.

The new ASD 50c coin

I’ve long been interested in exactly how R works - not quite enough for me to learn all the internals, but I was surprised that I could not find a clear guide towards exactly how vectorization works at the deepest level.

I occasionally like to participate in an odd sport known as ‘code golf’ where the aim is to write some code to achieve a given task using the smallest number of characters.

The tradtional way to cheat at golf is to lower your score

I just finished ‘Code: The Hidden Language of Computer Hardware and Software’ by Charles Petzold which was a really well-written (in my opinion) guided journey from flashing a light in morse code through to building a whole computer, and everything needed along the way.

The section on encoding instructions for the processor (built up from logic gates) - assembly instructions as a human readable version of the machine code - was particularly interesting to me, and as I was describing this to a colleague I remembered that it’s not the first time I’ve played with assembly…

x86 assembly instructions

I saw this post on Reddit’s r/dataisbeautiful showing this plot of streaming services market share, comparing 2020 to 2021

US Streaming Services Market Share, 2020 vs 2021

and thought it looked like a good candidate for trying out some plot improvement techniques.