Comment by IshKebab
1 year ago
The only possible advantage I can think of is that you can fit more code on one screen so I guess in theory you can see your context more easily. But that seems pretty minor compared to... well, look at it!
I read a couple of other threads and some people try to claim less code = fewer bugs, but that's pretty clearly nonsense otherwise minifiers would magically fix bugs.
As for why people actually use this (it seems like they really do), my guess would be that it's used for write-only code, similar to regexes.
Like, using a regex you can't deny that you get a lot of power from not many keystrokes, and that's really awesome for stuff you're never going to read again, like searching code in your editor, one throwaway shell commands.
But they also tend to be completely unreadable and error prone and are best avoided in production code.
It's not that any method of reducing code length fixes bugs, it's just happens that optimizing code to be read and worked on by domain experts leads one toward patterns that secondarily end up manifesting as terse expressions. The terseness is certainly shocking if you're not accustomed to it, but it's really not a terminal goal, just a necessary outcome.
The disbelief on first encounter is totally reasonable, but from personal experience, once you've gotten past that and invested the time to really grok the array language paradigms, code like this Whitney style actually ends up feeling more readable than whatever features our current SE culture deems Good and Proper.
There are a whole lot of moving parts to the why and how of these ergonomics, so I don't expect to be able to convince anyone in a simple, short comment, but if you're at all interested and able to suspend disbelief a little bit, it's worth watching some of Aaron Hsu's talks to get more of a taste.
From personal experience with regex, yes the first encounter was shocking, and sure I got past it and now can easily write regexes. But they still aren't more readable than the alternatives. Nor would I encourage their use in production.
I suppose in our new world of LLMs, using as few tokens as possible means you can cram more in a small context window, which could be helpful in various ways.
Maybe someone could produce an LLM which takes a line of vector language code and expands it into the dozen(s) of lines of equivalent pseudo-algol?
(I mean, you could skip the whole hallucination thing and write an exact converter, but that'd be a lot of effort for code that'd probably get used about as much as M-expression to S-expression converters do in the lisp world?)
There are a few articles of using J or APL for ANNs and CNNs out there. Here's one:
> But they [regexes] also tend to be completely unreadable
Regular expressions can be constructed using various syntaxes. Some are optimized for writing them out quickly, and some are not. Choose the latter when going to production, and you'll be fine.
As for K/J/APL - it's similar. You can write incredibly terse code which works wonderfully in a REPL (console). Working in an interactive manner is the default mode of operation for those languages. If you ever worked with Numpy/Pandas or similar, in a REPL, you likely concocted similarly terse monstrosities. Check your %hist the next time you have a chance. Going to production, you naturally rewrite the code instead of just committing the first one-liner that produces the desired results.
And Pandas was inspired by J per a quote in an article I once read about Wes McKinney, but I cant seem to find it online any longer.
Yeah exactly my point. But it seems like some people are using dense K/J/APL code in production which is just mad.