Even though I use Python every day, and I have used scipy often, I still reach for Octave whenever I need a quick calculation that I don't feel like turning into a big project.
And yeah, it's nice that matrices are first-class objects. Sometimes I miss 1-dimensional arrays or sensible strings, but it's not a big deal, and for quick, short things, the Octave syntax is still a lot easier to deal with than Python.
Most of Octave's users describe themselves as "not a programmer", despite using a programming language, so I think there's still room for this kind of software in the world.
- the existence of tools for working with strings and dictionaries doesn't take away from numpy at all
- I have never been offended by a programming language or felt like an outsider while using numpy
I agree with this philosophy! But that is certainly not at all the case with python, where fancy strings and even fancier dictionaries are readily available at the language level, instead of being implemented as separate libraries that you have to import.
If Python did not support strings nor dictionaries as basic data types, you might have a point. But it does, and it chooses to ignore multidimensional arrays and their basic operations. This is weird, and even a bit offensive when all you need to do is dealing with such arrays of numbers. You always feel like an "outsider", unlike when you program in octave or julia, for example.