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by tylermw 1803 days ago
Once your Rcpp code is compiled, it's almost indistinguishable from base R (when you're calling it). All R functions eventually end up calling R primitives written in C, and Rcpp just simplifies the process of writing and linking C/C++ code into the R interpreter.

The only difficulty with Rcpp-based R packages is you have to ensure the target system can compile the code, which means having a suitable compiler available.
2 comments
krastanov 1803 days ago
I wonder how much does it differ from python's use of C or Cython (I have only superficial R skills). The prototypical example of why Python's C prevents interoperability is how the introspection needed by Jax or Tensorflow (e.g. for automatic GPU usage or automatic differentiation) fails when working on Scipy functions implemented in C.

For instance, I imagine there is an R library that makes it easy to automatically run R code on a GPU. Can that library also work with Rcpp functions?

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oxinabox 1803 days ago
> it's almost indistinguishable from base R (when you're calling it).

I am very surprised by this. Given how R is extremely dynamic. and has things like lazy-evaluation, that you can rewrite before it is called with substitute. Which I am sure some packages are using in scary and beautiful ways.

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