C Foreign Function Interface for Python. Interact with almost any C code from Python, based on C-like declarations that you can often copy-paste from header files or documentation.
- What’s New
- Installation and Status
- Using the ffi/lib objects
- CFFI Reference
- Preparing and Distributing modules
- ffi.cdef(): declaring types and functions
- ffi.dlopen(): loading libraries in ABI mode
- ffi.set_source(): preparing out-of-line modules
- Letting the C compiler fill the gaps
- ffi.compile() etc.: compiling out-of-line modules
- ffi.include(): combining multiple CFFI interfaces
- ffi.cdef() limitations
- Debugging dlopen’ed C libraries
- ffi.verify(): in-line API-mode
- Upgrading from CFFI 0.9 to CFFI 1.0
- Using CFFI for embedding
The interface is based on LuaJIT’s FFI, and follows a few principles:
- The goal is to call C code from Python without learning a 3rd language: existing alternatives require users to learn domain specific language (Cython, SWIG) or API (ctypes). The CFFI design requires users to know only C and Python, minimizing the extra bits of API that need to be learned.
- Keep all the Python-related logic in Python so that you don’t need to write much C code (unlike CPython native C extensions).
- The preferred way is to work at the level of the API (Application Programming Interface): the C compiler is called from the declarations you write to validate and link to the C language constructs. Alternatively, it is also possible to work at the ABI level (Application Binary Interface), the way ctypes work. However, on non-Windows platforms, C libraries typically have a specified C API but not an ABI (e.g. they may document a “struct” as having at least these fields, but maybe more).
- Try to be complete. For now some C99 constructs are not supported, but all C89 should be, including macros (and including macro “abuses”, which you can manually wrap in saner-looking C functions).
- Attempt to support both PyPy and CPython, with a reasonable path for other Python implementations like IronPython and Jython.
- Note that this project is not about embedding executable C code in Python, unlike Weave. This is about calling existing C libraries from Python.
Get started by reading the overview.