We often need to incorporate into our workflow some code written in different languages; mostly C/C++ or Fortran, and also from R, MATLAB, or Octave. Python excels at allowing code from all these other sources to run from within; care must be taken to convert different numerical types to something that Python understands, but this is pretty much the only issue we encounter.

If you are working with SciPy, it is because your Python ecosystem has available compilers for C and Fortran programs. Otherwise, SciPy could have not been installed on your system. Also, given its popularity, it is highly probably that your computer environment has MATLAB/Octave available. Accordingly, this has driven the selection of topics listed later in this chapter. We left to the interested reader to find out how interface with R and many other software is available out there for numerical computing. Two alternatives to do that with R are the packages PypeR (http://bioinfo...