Integrate Python And C++

by

Interfacing Python with C/C++ is not an easy task.

Here I copy/paste a previous answer on a previous question for the different methods to write a python extension. Featuring Boost.Python, SWIG, Pybindgen…

  • You can write an extension yourself in C or C++ with the Python C-API.

    In a word: don’t do that except for learning how to do it. It’s very difficult to do it correctly. You will have to increment and decrement references by hand and write a lot of code just to expose one function, with very few benefits.

  • Swig:

    pro: you can generate bindings for many scripting languages.

    cons: I don’t like the way the parser works. I don’t know if they’ve made some progress but two years ago the C++ parser was quite limited. Most of the time I had to copy/paste my .h headers to add some % characters and to give extra hints to the swig parser.

    I also needed to deal with the Python C-API from time to time for (not so) complicated type conversions.

    I’m not using it anymore.

  • Boost.Python:

    pro:
    It’s a very complete library. It allows you to do almost everything that is possible with the C-API, but in C++. I never had to write a C-API code with this library. I also never encountered a bug due to the library. Code for bindings either works like a charm or refuses to compile.

    It’s probably one of the best solutions currently available if you already have some C++ library to bind. But if you only have a small C function to rewrite, I would probably try with Cython.

    cons: if you don’t have a precompiled Boost.Python library you’re going to use Bjam (sort of a replacement of make). I really hate Bjam and its syntax.

    Python libraries created with B.P tend to become obese. It also takes a lot of time to compile them.

  • Py++: it’s Boost.Python made easy. Py++ uses a C++ parser to read your code and then generates Boost.Python code automatically. You also have a great support from its author (no it’s not me 😉 ).

    cons: only the problems due to Boost.Python itself.

    Edit this project looks discontinued. While probably still working it may be better to consider switching.

  • Pybindgen:

    It generates the code dealing with the C-API. You can either describe functions and classes in a Python file, or let Pybindgen read your headers and generate bindings automatically (for this it uses pygccxml, a python library wrote by the author of Py++).

    cons: it’s a young project, with a smaller team than Boost.Python. There are still some limitations: you cannot expose your own C++ exceptions, you cannot use multiple inheritance for your C++ classes.

    Anyway it’s worth trying!

  • Pyrex and Cython:

    Here you don’t write real C/C++ but a mix between Python and C. This intermediate code will generate a regular Python module.

Edit Jul 22 2013: Now Py++ looks discontinued, I’m now looking for a good alternative. I’m currently experimenting with Cython for my C++ library. This language is a mix between Python and C. Within a Cython function you can use either Python or C/C++ entities (functions, variables, objects, …).

Cython is quite easy to learn, has very good performance, and you can even avoid C/C++ completely if you don’t have to interface legacy C++ libraries.

However for C++ it comes with some problems. It is less “automagic” than Py++ was, so it’s probably better for stable C++ API (which is now the case of my library). The biggest problem I see with Cython is with C++ polymorphism. With Py++/boost:python I was able to define a virtual method in C++, override it in Python, and have the Python version called within C++. With Cython it’s still doable but you need to explicitly use the C-Python API.

Edit 2017-10-06:

There is a new one, pybind11, similar to Boost.Python but with some potential advantages. For example it uses C++11 language features to make it simpler to create new bindings. Also it is a header-only library, so there is nothing to compile before using it, and no library to link.

I played with it a little bit and it was indeed quite simple and pleasant to use. My only fear is that like Boot.Python it could lead to long compilation time and large libraries. I haven’t done any benchmark yet.

More Related Contents:

  1. Adding some python flavor to C++ [closed]
  2. Calling C/C++ from Python? [closed]
  3. Convert Python program to C/C++ code?
  4. Calling a python method from C/C++, and extracting its return value
  5. Py_Initialize fails – unable to load the file system codec
  6. How can I implement a C++ class in Python, to be called by C++?
  7. How to use C++ classes with ctypes?
  8. Why are Python Programs often slower than the Equivalent Program Written in C or C++?
  9. How do I compile a Visual Studio project from the command-line?
  10. Calling python from a c++ program for distribution
  11. Benchmarking (python vs. c++ using BLAS) and (numpy)
  12. Compile the Python interpreter statically?
  13. How To catch python stdout in c++ code
  14. Equivalent C++ to Python generator pattern
  15. How would you implement a basic event-loop?
  16. How to create a DLL with SWIG from Visual Studio 2010
  17. Translating python dictionary to C++
  18. Remove C and C++ comments using Python?
  19. c++11 regex slower than python
  20. Writing robust (color and size invariant) circle detection with OpenCV (based on Hough transform or other features)
  21. Is Python faster and lighter than C++? [closed]
  22. How to return array from C++ function to Python using ctypes
  23. Can Cython code be compiled to a dll so C++ application can call it?
  24. FileStorage for OpenCV Python API
  25. How to handle C++ return type std::vector in Python ctypes?
  26. Boost.Python: Wrap functions to release the GIL
  27. Extending Python with C/C++
  28. CPython is bytecode interpreter?
  29. How can I enumerate/list all installed applications in Windows XP?
  30. C++ GDB Python Pretty Printing Tutorial?

Leave a Comment