Summer of languages

This summer’s the summer of languages for me. I’m learning R piecemeal, because I’m working on a data analytics project that requires a lot of statistical analysis: learning a new language is a bother, but the unprecedented amount of statistical packages available for R justifies the investment. I also decided to dive into Julia, despite its youth, mostly because of this:

We want a language that’s open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that’s homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled.

(Did we mention it should be as fast as C?)

Well, that and the fact that Matlab isn’t readily available here at IBM. I could use my Caltech license, but the writing’s on the wall. I might as well train myself in a good alternative for when I no longer have that option. Octave isn’t an option I’m happy with: it looks kludgy, Matlab code doesn’t *actually* run without modification, and the plotting options are embarassingly sad (Gnuplot in 2012? come on).