R is a language for statistical computing. For the past few months, I’ve been tasked with cutting a prototype modelling tool from R to a .NET framework that does something similar in a previous project here. Though I’ve skirted around the edge of R on occasion with my succession of contracts, this project is the first time where I had to really go deep.
There was pain, and its source was primarily assuming that R was ‘just another language’, similar enough to the set of languages I’m familiar with that I’d be fine.
It’s not, and I wasn’t.
If you’re experienced with other programming languages and are coming to R for the first time, here be dragons. If you’re considering going to another language from R, for the love of efficient computation, leave your dragons there with R.
What follows is a number of insights I’ve gained in contrasting R against the more ‘traditional’ languages out there. They’re essentially breaches of the rule of least surprise, where ‘no surprise’ is a baseline of ‘I can expect this assumption to hold regardless of programming language’.