Mastering Dyalog APL

Mastering Dyalog APL
mastering.dyalog.com

That said, learning APL isn't about learning the symbols any more than learning mathematics is not about learning the meaning of the various symbols it uses. To continue with that parallel, it also isn't about memorizing formulas. It is about using the tools to solve problems and, over time, changing the way you solve problems...now in 3D.

I learned APL in the early 80's and used it professionally for about ten years. The way I think of solving problems is fundamentally different in many ways because of this experience.

Anyway, I had a fun time a while ago translating APL programs to NumPy. At some point you get what APL is all about, and you can move on with life without too many regrets. Turns out most of the time it's more like a puzzle to get an (often inefficient) terse implementation by torturing some linear algebra operators.

If you're after a language that's OSS, has terse notation, and rewires your brain by helping you think more clearly instead of puzzle-solving, TLA+ is the answer.

Edit: if you're curious to see at a glance what APL is all about:

APL code:

(2=+⌿0=∘.|⍨⍳N)/⍳N Equivalent NUMPY code:

```

R = np.arange(1, N + 1) # ⍳N

divides = (R[None, :] % R[:, None]) == 0 # 0=∘.|⍨⍳N

divisor_counts = divides.sum(axis=0) # +⌿

result = R[divisor_counts == 2] # (2=...)/⍳N

```

As you can see, the famous prime generator is not even the Eratostenes' sieve, but a simple N^2 divisor counting computation.