Thanks for the response. I'd interpret it as a valid technical caveat, but it feels somewhat orthogonal to what I was pointing out.

You focus on the 'often inefficient' parenthetical, yet, to me, your response highlights the puzzle nature of the thinking APL encourages. If anything, it shifts the question from 'how do I express this tersely' to a still narrower 'how do I express this tersely in a way the interpreter can also optimize'.

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tosh an hour ago | parent [-]

I think every programming language to a degree has some kind of puzzle aspect

I'm not sure APL has more or less of it compared to other languages

for example in Python, even though the language has a concept of "There should be one-- and preferably only one --obvious way" (PEP 20) it is quite multi paradigm, which I think is a strength of Python

oop, functional, imperative, …

and you get tons of libraries to choose from

e.g. numpy, pandas, polars, pytorch, keras, jax, … etc

but you still also have to figure out the algorithm and data structures you want to use (like in any language)

and you also kinda want to know (if you care about performance) how pytorch differs from numpy and how that differs from using a list with boxed values

Not saying this is not the case with APL

it definitely helps if you are familiar with the APL implementation you're using if you care about performance

I just don't think it's a disadvantage of APL over other languages

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gobdovan 44 minutes ago | parent [-]

Agreed. I think I shouldn't put hard boxes around languages like 'puzzle language' vs 'abstraction/clear thinking language'.

What I was trying to point at was more specific: the way I experience APL thinking tends toward 'expression search' and 'notation compression', which feels, to me at least, somewhat at odds with clarity about the underlying problem. More often than not, I seemed to produce an APL-shaped model of the problem rather than a problem-shaped model expressed in a language.

When I first learned about APL, I was looking for new ways to think about computation. What I found was a language that rewarded deciphering APL programs and generating clever new ones. That is interesting and beautiful, but it was not quite the kind of brain-rewiring I was looking for. My original comment was targeting people in a position similar to mine and trying to set expectations about what they would learn best from APL. APL may change how you think about array expressions and how far they can go, but TLA+ is much closer to what I'd recommend if what you want is clearer thinking about programs, systems and state.

	▲	tosh 27 minutes ago \| parent [-]
		ty for the pointer to TLA+