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I don't think the points you highlighted above matter fundamentally: they don't handle memory management for you, and that's the difficulty, especially at the l

by cdavid 13y ago

I don't think the points you highlighted above matter fundamentally: they don't handle memory management for you, and that's the difficulty, especially at the language boundary. What is interesting for me in Lua is the stack-based argument passing and the GC: it avoids leaking the reference counting and the binary representation of objects (I think, I am rather clueless when it comes to Lua). Wrapping things like crypto, file format and co is relatively trivial, because not much crosses the language barrier. Now, when you need to handle non native object life cycle, that's another matter, and I don't see how cffi makes it any easier than cython

_dps 13y ago
This thread has probably gone too long, and I thank you for your time and comments so far. I will close by saying that, while I agree with you that CFFI doesn't make the problem of writing memory-safe C extensions to the Python VM any easier, I also believe that almost no one (aside from people like Numpy developers) actually need to write a Python extension. They just write extensions (or use Cython, or Ctypes) because that's "the way" to call C from Python. In my personal experience 90+% of the Python+C problems in the world are just about calling an existing piece of C code and maybe mapping some structs or arrays into Python types; these workflows rarely involve instantiating complex objects on the Python side. For my work habits neither CPython, Ctypes, nor Cython are optimized for this extremely common use case. CFFI solves these problems for me better than any of those alternatives, and if someone offered me a Python 4.0 with CFFI and no GIL at the cost of harder-to-use extension mechanisms I'd jump on it; I suspect that a significant portion of the people who do Python/C interop work would feel similarly. I also do realize that such a change could make projects like Numpy harder to build.

by cdavid 13y ago

_dps 13y ago

This thread has probably gone too long, and I thank you for your time and comments so far. I will close by saying that, while I agree with you that CFFI doesn't make the problem of writing memory-safe C extensions to the Python VM any easier, I also believe that almost no one (aside from people like Numpy developers) actually need to write a Python extension. They just write extensions (or use Cython, or Ctypes) because that's "the way" to call C from Python. In my personal experience 90+% of the Python+C problems in the world are just about calling an existing piece of C code and maybe mapping some structs or arrays into Python types; these workflows rarely involve instantiating complex objects on the Python side. For my work habits neither CPython, Ctypes, nor Cython are optimized for this extremely common use case. CFFI solves these problems for me better than any of those alternatives, and if someone offered me a Python 4.0 with CFFI and no GIL at the cost of harder-to-use extension mechanisms I'd jump on it; I suspect that a significant portion of the people who do Python/C interop work would feel similarly. I also do realize that such a change could make projects like Numpy harder to build.