Generates Python Extension modules from Cython PXD files.
One important application of Cython is to wrap C++ classes for using them in Python. As Cythons syntax is quite similar to the syntax of Python writing a wrapper can be learned easily. Further Cython prevents you from many typical errors which might get in your way if you write such a wrapper in C++.
This wrapping process typically consist of four steps:
Rewrite parts of the header files of your C++ library in so called
.pxdfiles. These give Cython information for calling the library and for error checking the code written in the following step.
Write Cython code which wraps the C++ library. This code resists in one or more
.pyxfiles to C++ code with Cython.
Use distutils to compile and link the C++ code to the final Python extension module.
Depending on the size of your library step 2 can be tedious and the code will consist of many similar code blocks with only minor differences.
This is where
autowrap comes into play:
autowrap replaces step 2 by
.pxd files with Cythons own parser and generating correct
code for step 3. In order to steer and configure this process the
can be annotated using special formatted comments.
We assume that you installed
autowrap already, so running
$ autowrap --help
does not fail.
Please see docs/README.md for further documentation.
Wrapping of template classes with their public methods and attributes,enums, free functions and static methods.
Included converters from Python data types to (many) STL containers and back. As this is version 0.2, not all STL containers are supported. We plan full support of nested STL containers.
Manually written Cython code can be incorporated for wrapping code which
autowrapcan not handle (yet), and for enriching the API of the wrapped library. As this is done by writing Cython instead of C/C++ code, we get all benefits which Cython shows compared to C/C++.
Writing a code generator for handling all thinkable APIs is hard, and results in a difficult and hard to understand code base. We prefer a maintainable code generator which handles 95% of all use cases, where the remaining 5% are still wrapped manually.
For achieving a pythonic API, converters for library specific data types can be implemented easily. These converters are written in Python and Cython, not in C/C++ code using the C-API of CPython.
autowraprelies on Cython, so we get automatic conversion of C++ exceptions to Python exceptions and wrapper code with correct reference counting. Using distutils we do not have to care to much about the build process on the targeted platform.
Support for generating some special methods, as
__copy__and numerical comparison operators.
Many thanks go to:
Hannes Roest, ETH Zürich, for contributing new ideas, patches, fruitful discussions and writing the first draft of this README.
Lars Gustav Malmström, ETH Zürich, for getting the ball rolling.
The developers of Cython for providing such a powerful and high quality tool.
Thanks to https://github.com/hendrik-cliqz for implementing the "no-gil" annotation.