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Comment by burgerdev | Hacker News Reader

At first I was wondering how he managed to write a compiler in 750 loc. Then I noticed it's for APL, which I would call terse:

  Y0←{⊃,/((⍳≢⊃n⍵)((⊣sts¨(⊃l),¨∘⊃s),'}',nl,⊣ste¨(⊃n)var¨∘⊃r)⍵),'}',nl}

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Does anyone here program APL? I've tried to look into it occasionally because the idea of powerful, concise syntax appeals to me, but the unfamiliar syntax was always too much to get my head around within a reasonable amount of time. I'm curious to know whether it really does become second nature after a while, in the same way that some of us might read a printf format string or regular expression quite fluently after many years of working with them.

I program in K, a close relative, and I have done some tinkering with APL. The symbols actually don't take long to memorize- perhaps a few days of practice. It's a bit like learning to read prose. At first you have to sound out words letter by letter, but eventually you're able to "see" words and phrases built out of common patterns of symbols. I see ,/f' and think flatmap, ~~': and think heads of uniform runs, {x@<x} and think sort up, etc.

A dense expression can still take a while to puzzle out sometimes, but certainly no longer than the equivalent logic spelled out in a more verbose language across many lines.

What's it like looking for a K job?

In my experience, if you do enough open source stuff with K, jobs find you.

I've looked at some of the ascii APL relatives, and my impression was that they are probably great for working with numbers, but seem like they'd be bad for working with text and other things. Am I missing something here?

K relaxes the traditional APL constraints on "rectangular data", which makes it comparatively quite good at dealing with text manipulation. I frequently use K for working with text and it works nicely. Anything you can represent as a list structure can have all the traditional APL-ish tools brought to bear on it.

As for "other things", here are a few K sketches I've written recently:

- generate random island shorelines:

http://johnearnest.github.io/ok/ike/ike.html?gist=629a86c257...

- animated holiday card:

http://johnearnest.github.io/ok/ike/ike.html?gist=e5fdbb8724...

- an implementation of the arcade game "Snake":

http://johnearnest.github.io/ok/ike/ike.html?gist=ead275c529...

And that's just me! There are many interesting examples and essays here: http://www.nsl.com

I programmed in APL circa 1980-83. It's not a normal programming language in that you don't use it to solve the same kinds of problems as you'd solve in Pascal or Fortran (then) or Python or C (now). Lisp and Smalltalk are a little like that. If you pick a problem they're good at, they're very good indeed, but if you're writing something they don't do, they're just Pascal/Python with funny syntax and nonstandard libraries.

APL really encourages code golfing. It's barely readable in the best of circumstances, so there's a lot of temptation to compress code. Er, it's readable, but it's like reading a regular expression. You read it character by character, not line by line.

The other thing APL encourages is writing dimensionality independent code. Just as a good C programmer will write a function to concatenate two strings that works independent of the strings' sizes, a good APL programmer will write a function to accept arrays of arbitrary dimensionality where that can make sense. That's because it was not uncommon to have intermediate results of 3, 4 or 5 dimensions. Also, most of the built-in operators do something useful with higher-dimensioned inputs.

So yes, it becomes second nature, more or less. But at the same time, it restricts the kinds of problems you think about solving with it.

Today I would not recommend APL for any purpose except studying its place in computing history.

Respectfully, the APL of today is not the APL of the 80's. APL is tremendously well suited to many of the problems that face other programming languages, such as the parallel programming usability problem. Modern dfns based APL has incorporated lessons learned from languages liked Scheme (Lisp) to make function syntax and control flow more functional.

And APL has been and continues to be used to solve problems from web programming to graph processing and everything in between. While it finds immediately obvious advantage in numerically dense calculation heavy code, my research is specifically interested in demonstrating and scaling APL beyond the "status quo" of what people think APL is good for. The Co-dfns compiler mentioned in these threads is precisely such a counterpoint, demonstrating how to leverage APL in a domain space traditionally dominated by OOP and Lisp style languages, and more recently by certainly highly typed languages such as Agda or maybe Haskell.

The difference is that good APL is often more or less "parallel ready" out of the box. Good code in other languages is often anything but. I am working through making the case that "parallel first" languages such as APL are actually pedagogically and programmatically better than "serial first" languages. To this end I have conducted at least one exploratory pilot study on the matter:

http://video.dyalog.com/Dyalog13/?v=kIItfQJEVdM

Actually, most of those 750 LoC is C++ code for the runtime, written in a style to match the semantic density of the rest of the code, as well as code for calling off to the various C compilers on various operating systems. The core compiler (between the parser and final code generator pass) is around 90 lines and is written is a particular style of APL code.

He also replaces long names with short ones, so it's more like an obsession. First commit I clicked on was replacing "penv" with "p" just to make it shorter.

That wouldn't affect line count.

It would if you have a max length rule for lines and some need to broken up.

It does affect deleted/added lines. You can quickly have several dozed deletions and additions renaming a single variable.

There's a specific reason I made that switch, which for a long time had appeared to be a silly change. Eventually I realized that "penv" as a name was so different from the rest of the naming conventions that it was causing cognitive dissonance in my programming that was taking me out of the flow and making it more difficult to work with the code. Move to the name "p" did shorten the code, but more importantly, brought more consistency, predictability, and regularity into the code base. It is a case of synergizing simplicity and brevity and how they work together.

That's ok, but documenting naming conventions is equally as important. How else are you going to remember them when some time passes or how someone else is going to understand them.

I would tend to agree. It's certainly a generally good rule of thumb. However, I've honestly struggled to find a way to document the naming conventions that is useful. Every time I've wondered about a particular name, it's faster for me to go to the definition sight of that name than to seek documentation, and the documentation for the naming conventions might exceed the size of most of the compiler, simply because it's hard to write out all of the aesthetic and stylistic choices that are almost self enforcing through an overwhelming pressure of context when you're actually programming in the code. Basically, while I am a huge fan of documentation, with this style and the approach I'm taking, I've found it exceptionally difficult to create up to date, meaningful, and reliable documentation of any sort that isn't totally useless. Now, I do have public API documentation, but internal developer docs have not proven to be helpful at all for any reason in this compiler. I've tried on multiple occasions to make it happen, and it just doesn't work here. If you have a way to do so, or even maybe if you want to talk with me and make it happen, all the better, but when the code base changes so fast all the time, it's just very hard to keep documenting this fluid thing that keeps changing. In some ways that includes the naming conventions.

I'm quite open to people providing ideas on how to properly document this project outside of "big idea" documentation that I'm currently doing with the paper publications. I've yet to be able to find anything that works. The standard best practices don't seem to flow well at all, but maybe I've missed something.

For something in a more... conventional language, here's a compiler/interpreter for a C subset in ~500 lines:

https://news.ycombinator.com/item?id=8558822

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