This looks really well done.
I wonder what the motivation is to do this when R is so mature (especially in the availability of specialized packages), and available through RPy.
I wonder what the motivation is to do this when R is so mature (especially in the availability of specialized packages), and available through RPy.
The bigger picture reason "why not R" is that R is not very suitable for building production systems. I started building this library while working for AQR, a quant hedge fund, and needed to have statistical computing building blocks integrated with a much larger system. R is a mediocre programming language and has very weak general purpose libraries. But amazingly good data visualization and mature statistics libraries indeed. Using R as a black box (e.g. via RPy, Rcpp, or RJava) is a good idea in theory, but recovering from and dealing with errors/exceptions with real world data is a very thorny problem. Plus maintaining a big pile of R code is kind of a nightmare (believe me, been there, done that!).
Looking forward to checking this out.