Dear list,
I have an R package that's mostly C++ code (using Eigen, but no other
dependencies) and some glue. We wish to re-use the C++ code for a Python
package. Most of the external-facing C++ functions are pretty simple:
essentially they're all variants of:
NumericVector some_matrix_calcu
In my experience, it's usually much easier to have a stand-alone C++
library and add the Rcpp and Boost.Python layer on top of it. As you said,
NumericVector and other classes are not known in the Python world.
You can always hook in into them from Boost.Python to expose them to Python
but a clear
Some folks told me that pybind11, ie at
https://github.com/pybind/pybind11
is the one to use as Boost Python is stagnant. I have no personal experience
with pybind11 though.
The question is a good. This (old) CRAN package has been doing both R and
Python from a joint C++ basis for years:
Hi all,
pybind11 is the best choice here. It goes quite a bit beyond what Boost
Python did, including nice support for Numpy arrays, the buffer protocol
more generally, and an Eigen interface. I've used it quite a bit.
But the real issue will be separating out the guts of your code from the
Rcp
