Conway's Game Of Life in APL

It has an incredible amount of elegant power for some things (see [VIDEO] if you want to immediately fall in love). But I've found that trying to use it for most things just isn't worthwhile. It feels like cheating every time I have to escape from its array programming core to the more familiar flow control structures that only came along in later versions of APL. I think it makes a good puzzle language (i.e. the fun comes from figuring out _how_ to say something rather that just raw getting stuff done), but unfortunately, it's even more of a puzzle to figure out how code that someone else wrote works. For full context: I've spent more time using J than APL itself.

While we wait for the site to come back up please enjoy this amazing video showing Conway's Game of Life in APL: [VIDEO]

The following video is probably reasonably well known, and I wish that I had a more intelligent commentary than to say that it blows my mind, but it does I think bear out the point of expressivity rather well. [VIDEO] Conway's Game of Life in some 50 characters of APL.

Try watching this video; it will only take you 8 minutes, but within 3 minutes you should have an idea of why array languages are different from having an ndarray library available in Rust or having typeclasses in Haskell: [VIDEO] After you watch that you will of course suspect that APL and other array languages like J are a sort of DSL for things like numerical linear algebra, which is of course what Numpy and Octave are. (Even though the Game of Life isn't linear algebra, it's very clearly matrix-based, so it doesn't seem that far off.) Dyalog has posted some other videos demonstrating the use of their proprietary APL for different things, but I think a more interesting one is [LINK] , by J inventor Roger Hui. This is an hour and a half, but it demonstrates some approaches to reducing different problems to multidimensional arrays, of pointers ("boxes") in some cases. This ought to be enough to convince you that there's an alien kind of thinking here, quite different from the Haskell and Rust approaches, that can be applied to a wide variety of problems. Now, I'm not Stevan Apter, so I'm not going to try to convince you that this alien kind of thinking is better . But it's clearly different , and different ways of thinking work best in different situations.

> Here's a video that really illustrates the power of this paradigm: [VIDEO] Amazing game of life code!

For an infinitely more relaxing experience of life in APL, may I recommend: [VIDEO] I've watched it many times but I still expect him to mention happy little trees :)

I always liked this example: Conway's Game of Life in One Line of APL [VIDEO] It's esoteric as one-liners tend to be, but I think it's a fascinating glimpse.

I think the key to understanding APL is realizing that it’s not built for Programmers; it’s built for Mathematicians. Here’s a fine half-hour introduction to APL in action: [LINK] 1:00-2:00 is the motivation for APL—or any DSL—in a nutshell. (“conversational computing”, “users who are [not] professional programmers”) Or, if you’re happy to sit back and see math magic happen: [VIDEO] For all its mechanical advances over the last 40 years, it’s shocking how far our technology has regressed philosophically.