UPDATE Oct-2013: ============= Originally we had chose python as the main language for this project because it was a natural fit for text processing. However, we eventually reached a point where the simplified output wasn't powerful enough to handle all the nuances of templates and specialization. Since then, we have ported our scripts to C++ so that they can access the Clang AST directly. The C++ version is noticably faster and allows full clang AST access. This python version allows rapid iteration and is more suitable for experimentation. Clang-extract ============= Clang-extract uses clang to parse your header files and then prints out a description of what it parsed. This project was described in a talk a GDC 2012 http://www.gdcvault.com/play/1015586/ (subscription required) It was funded by Havok and is used as the basis of its reflection system. Building -------- * Either in your environment or in the Makefile, set LLVM_DIR to the folder containing a prebuilt LLVM and Clang. * make Test -------- To run clang-extract on a small test: * make test You'll notice the output format is actually python code so you can parse it thus : def parse(text): output = # your output structure def Method(id, recordid, typeid, name, static): # code here for a method, modifids output # more local function definitions here exec text in locals() return output Invoking -------- Run clang-extract --help to see command line options. Notes -------- clang-extract internally creates a file which includes all the input files specified on the command line. You may need to add "-I ." to find the input files. The -A option is useful to pass through annotations which are stored in the output file.