Hacker News Reader

Numpy does have much better scientific capabilities, so you can use vanilla Python for the basic coding and Numpy routines when you need them.

APL uses arrays for everything though. I just wish it had taken off more on the scientific front instead of the financial side as the linear algebra stuff isn't nearly as fleshed out as Matlab/Numpy/Mathematica.

I started writing a program that transformed J source to numpy. For just the basic verbs it was surprisingly easy. I think this is because arrays are arrays and we only have one way to think about linear algebra.

similar background (started my career in APL, only language i've ever used that had its own keyboard)

also NumPy, and Nd4j via scala bindings

of course NumPy and Nd4j are libaries

i strongly recommend Julia as an array-oriented programming language

particularly because it has quite a few other features to recommend it

Julia follows the Matlab syntax conventions more closely than NumPy (or R) which i think was a good design choice