In Praise of APL (1977)

https://www.jsoftware.com/papers/perlis77.htm

by tosh • 6 months ago

97 59 6 months ago

kholis_ab4• 6 months ago

i love APL, but never ever tried it ... only watched videos of code_report

abrudz2• 6 months ago

I'll be happy to give you a live personalised intro in https://apl.chat or head over to https://challenge.dyalog.com/ for an automated guided introduction (with a chance of winning a prize).

kholis_ab4• 6 months ago

wow, thanks a lot! but my english is not good enough for a live "discussion" unfortunately :(

But maybe later, if you allow, I will contact you!

jodrellblank• 6 months ago

https://tryapl.org/

kholis_ab4• 6 months ago

thanks for this link!

ofalkaed4• 6 months ago

https://xpqz.github.io/learnapl/intro.html is a good place to start learning.

kholis_ab4• 6 months ago

thanks for the link!

singularity2001• 6 months ago

Should be the ultimate final incomprehensible programming language for code agents

ofalkaed4• 6 months ago

ChatGPT is pretty good at correcting my mistakes. Give it a snippet of not quite working code with no explanation and it almost always correctly identifies what I am trying to do and explains where I went wrong. Its corrected code almost never works but its explanation of why my code failed gets me my answer and that is what I really want. A year ago it could not help me in the slightest, it has improved quite a bit. The biggest issue with AI and APL seems to be that it does not quite understand the differences between the various versions of APL and seems to view APL2, Dyalog and GnuAPL as all the same language.

Edit: It probably would be useless to someone at all competent in APL and whose problems are more complex than their own failings.

adrian_b3• 6 months ago

True. Due to its lack of verbosity, APL is not at all forgiving for any substitution or transposition in its symbols, which can cause great differences in program output, so it is quite improbable for LLMs to generate a working program, unless it is identical with one from its training set.

What I have said matches exactly what another poster said about his experience in using a LLM with APL: "Its corrected code almost never works".

The LLM recognizes the problem that must be solved by the code, but it fails to generate the right APL symbol string.

I doubt that here a coding agent that attempts to verify the generated code by compiling it can help, because the LLM will generate eventually some syntactically-correct symbol string, but which will implement a different function than desired.

Only a complete feedback loop, with a battery of varied tests for the executable program produced by the generated code, which can verify if it really implements the desired functionality, can be used to filter the results for a working program.

APL is greatly superior to almost all programming languages that are popular today, for writing expressions involving arrays (this includes expressions that do not involve arrays in other languages, but which could be made simpler by using arrays in APL).

However, the original APL has defects, due mainly to the fact that it was an incomplete programming language, e.g. when compared to the other contemporaneous IBM language, i.e. PL/I.

What one needs is a programming language with modern program structures, data types and data type definition facilities, but also with an expression syntax matching the power of APL expressions.

The fact that in 2026 most programmers continue tho write "for" loops for handling arrays, instead of using array expressions like it was possible in 1966 in APL, 60 years ago, seems an aberration of history. Even in the 1966 PL/I one could use array expressions, even if only expressions that were much simpler than those of APL.

Using symbols instead of keywords, like in APL, is not cryptic for anyone who uses such a language regularly. It is cryptic for those who have not used them. The English-based keywords are somewhat less cryptic only for English speakers, and even for them they can be misleading before they learn their correct meanings.

skruger4• 6 months ago

Whilst LLMs still perform weakly in APL, the situation is improving at pace, and giving it a “skill” to evaluate code makes a dramatic difference. I gave a conference talk about it recently (video): https://youtu.be/H_wdKeJ8gt4

pavlov• 6 months ago

“it is quite improbable for LLMs to generate a working program, unless it is identical with one from its training set”

This is a fascinating result. In some sense it’s like APL is actually the most human programming language, despite being one of the most difficult for ordinarily trained human programmers to pick up.

misja1115• 6 months ago

The virtues of APL that strike the programmer most sharply are its terseness — complicated acts can be described briefly, its flexibility — there are a large number of ways to state even moderately complicated tasks (the language provides choices that match divergent views of algorithm construction), and its composability

I had an introduction to APL in university and what I absolutely hated was this terseness. I guess when you're a mathematician APL is more natural but to me, as a programmer, I much prefer to have some extra verbosity to make my code more (human-)readable.

adrian_b3• 6 months ago

Terseness is easier to remove from a programming language than verbosity.

You can use a source preprocessor to enable you to write APL programs by using keywords instead of any symbols that you do not like. You can also use a source preprocessor to expand any traditional APL source, by converting symbols into keywords, so that it will be easier to read for you.

Using symbols instead of keywords is a minor feature of APL, which was inherited from the standard mathematical notation, from which APL was derived.

The important features of APL are the expression syntax and the set of available operators, not the symbols used for them.

Moreover, if you have difficulties in following complicated expressions, you can always break them in smaller subexpressions.

When someone presents an "incomprehensible" APL program, they show a huge expresion without comments.

A decent APL program, like in any other programming language, would need good comments, but here comments are frequently desirable at the level of subexpressions.

misja1115• 6 months ago

A decent APL program, like in any other programming language, would need good comments, but here comments are frequently desirable at the level of subexpressions.

I guess that might be true for APL, for other programming languages that's not true at all. The ideal program is clear enough to be self explanatory. Of course there might be some implementation choices that need a comment. Or in some cases the problem is so difficult that this is not possible.

But readability should be the goal and most of the time this is feasible without comments. E.g. by using descriptive variable and function names. And by breaking up your program into logical and cohesive parts, using functions, objects, modules or whatever construct your language is offering.

runeks• 6 months ago

I find APL very difficult to read. Incidentally, I am told (by stack overflow) that the APL expression "A B C" can have at least four different meanings depending on context[1]. I suspect there's a connection here.

[1] https://stackoverflow.com/a/75694187

skruger4• 6 months ago

Yes, it's either an array (if A, B and C are arrays), a function derived via the dyadic operator B, with operands A and C being either arrays or functions, a dyadic function call of the dyadic function B (A and C are arrays), or the sequential monadic application of functions A and B to array C, or a derived function as the tacit fork (A, B and C are functions). Did I miss anything?

abrudz2• 6 months ago

Yes, it can also a fork where A is an array while B and C are function and a tacit atop where either B is a monadic operator and A its array or function operand or A is a function and C is a monadic operator with B being its array or function operand. Finally, it can be a single derived function where B and C are monadic operators while A is B's array or function operand.

yvdriess• 6 months ago

And they could be 0- or 1- indexed? :P

UncleEntity• 6 months ago

> Did I miss anything?

Derived operators?

And, 'A B C' as an array isn't valid (ISO) APL but an extension, the 'array syntax' only covers numbers and the parser is supposed to treat is as a single token.

Your useless information of the day...

JaumeGreen• 6 months ago

One of my list of dream projects that I might never have time to do, and so feel free to "steal" the idea, would be a eink notepad in where you could code in APL or similar.

APL was born as a mathematical notation, pertaining to the blackboard, so it makes sense to write it using a writing implement. Its terseness would make it ideal for the handwriting world, it's REPL implementation would give quick feedback loops, you could move around input and output streams.

You could be in a sofa, writing the solution, expending most of your energy thinking, not writing, once you got used to the new way of thinking and the vocabulary.

If you haven't tested any array language I would recommend you try to solve things using one, and check existing solutions so you can see how to think differently. Some problems are naturally easier with this approach, some are harder.

icen• 6 months ago

You might be interested in this then: https://mlajtos.mu/posts/new-kind-of-paper

I’ve not used it myself, but it appears to be the thing you’re wanting?

kkylin• 6 months ago

I've had the same dream! thanks for the pointer.

bunderbunder4• 6 months ago

I would probably just go for an Android eink tablet like the ones made by Bigme and Onyx Boox.

It looks like there are a few APL implementations for Android out there, or you could use a remote editor or terminal app to access an APL implementation running elsewhere.

mlajtos• 6 months ago

You are exactly right that the original vision of APL was a handwritten, non-ambiguous, consistent, and executable math notation. This was never accomplished.

In 2021, I made a prototype calculator designed for iPad and Pencil and wrote four essays called "New Kind of Paper" describing this concept. The video demonstration of the prototype [Demo] sums up pretty well how it might be used.

In 2024, Apple released Math Notes, which implements this concept for standard math notation. My "review" of it is at [MathNotes]. In short, it is currently a preview of a damn great tool, but its future depends on notation and expressivity.

APL is a language from 2066, created in 1966. While its semantics make more sense now due to machine learning, syntactically it remains alien to most people. Backus' FP/FL and Iverson's J are more approachable to current programmers, but still not there. In New Kind of Paper, I created a tiny language called Fluent, which is nowhere near the ambition of any language mentioned, but it is intentionally designed to be handwritten. A week ago, I open-sourced it. [Fluent]

There is plenty of work left to do, but it is a good start.

[NKoP]: https://mlajtos.mu/posts/new-kind-of-paper

[MathNotes]: https://mlajtos.mu/posts/new-kind-of-paper-5

[Fluent]: https://news.ycombinator.com/item?id=46649223

[Demo]: https://youtu.be/y5Tpp_y2TBk

Thanks for coming to my TED talk.

baruchel• 6 months ago

I’ve practiced array languages extensively myself, including for code golfing, and I fully understand the intellectual joy they can provide. But as I’ve gotten older, I’ve come to see a deep mismatch between what these languages present as “elegant” and what I find truly elegant from a computer science perspective.

Sure, realizing that the foobar of x is nothing more than the transpose of the 15th foo of x, combined via an inner product with the 7th bar of x raised to the power of baz, can be an ineffable intellectual delight. But actually computing that, rather than writing a “boring” loop, feels horrible to me. To my eyes, a “boring” piece of code written by Dijkstra in some Algol-like language contains more beauty than all these dazzling sleights of hand that hide zillions of loops under the rug while pretending that the actual computation doesn’t matter.

bunderbunder4• 6 months ago

On the other hand, whenever I see Python code that does calculations over arrays of data with nested loops instead of using numpy, it always takes me a distressing amount of time to see what the code is actually doing and that the bug is because of a typo buried deep in that 100 lines of code that caused one of the inner products to be incorrect.

veqq• 6 months ago

Array languages are more conceptually simple. What do you concretely mean to mock with:

realizing that the foobar of x is nothing more than the transpose of the 15th foo of x, combined via an inner product with the 7th bar of x raised to the power of baz

t-32• 6 months ago

It's not like array languages don't do any optimizations... Denying the programmer the ability to be clever by manually writing loops makes some things easier and simpler for the compiler as well.

meken• 6 months ago

I enjoyed the FBAPP acroymn. There should be a modern day equivalent.

kstrauser4• 6 months ago

I’d like to play with an array language because I’ve never used one. I don’t want to pay for it; this is just for fun and as an experiment. I also want to run it locally in a shell, writing it in a local editor, not working in a web UI. And while popularity isn’t everything, and none of these are exactly Python levels of widespread, I also don’t want to find myself learning a cool one along with 3 other people in the world and then find out all other array language programmers do things completely differently. (Analogy: I don’t want the equivalent experience of picking Haskell as my first ever PL.)

This topic tends to bring up a few, like APL itself, J, K, and BQN. Given those (soft!) constraints, what’s the one I want to start hacking around with?

vegabook• 6 months ago

there's also a Forth-meets-APL project called uiua [https://www.uiua.org/]

kstrauser4• 6 months ago

That may require a little more mental bandwidth than I can summon right now. It looks incredibly cool, though.

invalidOrTaken• 6 months ago

I haven't tried the others, but J meets all those requirements.

RodgerTheGreat• 6 months ago

Yep. J has a small userbase, but it isn't fragmented into dialects like K or even APL, J uses ASCII characters instead of requiring a custom font/keyboard layout, J is FOSS, J has extensive learning materials, and J is reasonably batteries-included and suitable for making practical nontrivial programs.

I like K better than J aesthetically, but it's harder to recommend to beginners due to the fragmentation of the ecosystem.

kstrauser4• 6 months ago

I keep getting nudged in that direction. I'll check it out, thanks!

skruger4• 6 months ago

I faced exactly this situation a few years ago - I went with APL as the “OG”, but it probably doesn’t matter that much. Learning k or j once you know APL is much easier. I wrote a bit about this (apl and k)

https://xpqz.github.io/learnapl

https://xpqz.github.io/kbook

kstrauser4• 6 months ago

Oh, perfect. Thanks for the links!

gsinclair• 6 months ago

I believe Uiua is an excellent one to look at first. It’s simpler than the others you mentioned without sacrificing any power (that I know of). You can type in meaningful words which then appear as cute glyphs, rather than learning new ways of entering things. Each glyph has only one meaning whereas APL (and I think the others) assign context-dependent meanings to some glyphs.

i-blis• 6 months ago

J is, within the APL family of languages, the one I have always found the most useful. I reach for it as I used to reach for my HP calculator in the past, to quickly compute or numerically model things. I always have it running in a terminal window.

Contrary to popular belief, its learning curve isn't steep. I once introduced it to high school freshmen who had no real experience with programming. I recommend the series of booklets by Kenneth Iverson himself: Arithmetic, Algebra, Calculus — there is even a Concrete Mathematics companion to accompany the book of the same name by Graham, Knuth et alii. They're all available for download on the site.

In Praise of APL (1977)

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