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I have fairly large C++ library with several sub-libraries that support it, and I need to turn the whole thing into a python extension. I'm using distutils because it needs to be cross-platform, but if there's a better tool I'm open to suggestions.

Is there a way to make distutils first compile the sub-libraries, and link them in when it creates an extension from the main library?

+6  A: 

Hi there

I do just this with a massive C++ library in our product. There are several tools out there that can help you automate the task of writing bindings: the most popular is SWIG, which has been around a while, is used in lots of projects, and generally works very well.

The biggest thing against SWIG (in my opinion) is that the C++ codebase of SWIG itself is really rather crufty to put it mildly. It was written before the STL and has it's own semi-dynamic type system which is just old and creaky now. This won't matter much unless you ever have to get stuck in and make some modifications to the core (I once tried to add doxygen -> docstring conversion) but if you ever do, good luck to you! People also say that SWIG generated code is not that efficient, which may be true but for me I've never found the SWIG calls themselves to be enough of a bottleneck to worry about it.

There are other tools you can use if SWIG doesn't float your boat: boost.python is also popular and could be a good option if you already use boost libraries in your C++ code. The downside is that it is heavy on compile times since it is pretty much all c++ template based.

Both these tools require you to do some work up-front in order to define what will be exposed and quite how it will be done. For SWIG you provide interface files which are like C++ headers but stripped down, and with some extra directives to tell SWIG how to translate complex types etc. Writing these interfaces can be tedious, so you may want to look at something like pygccxml to help you auto-generate them for you.

The author of that package actually wrote another extension which you might like: py++. This package does two things: it can autogenerate binding definitions that can then be fed to boost.python to generate python bindings: basically it is the full solution for most people. You might want to start there if you no particulrly special or difficult requirements to meet.

Some other questions that might prove useful as a reference:

You may also find this comparison of binding generation tools for Python handy. As Alex points out in the comments though, its rather old now but at least gives you some idea of the landscape...

In terms of how to drive the build, you may want to look at a more advanced built tool that distutils: if you want to stick with Python I would highly recommend Waf as a framework (others will tell you SCons is the way to go, but believe me it's slow as hell: I've been there and back already!)...it takes a little learning, but when you get your head around it is extremely powerful. And since it's pure Python it will integrate perfectly with any other Python code you have as part of your build process (say for example you use Py++ in the end)...

jkp
Note that the CERN report you quote as "this comparisson" is over 6 years old, and so must be taken with a BIG grain of salt (!). SIP, in particular, has evolved **a lot** in these many years, so it's well worthy of consideration today.
Alex Martelli