I replied on capi-sig.
2018-07-31 18:03 GMT+02:00 Antoine Pitrou <solip...@pitrou.net>: > On Tue, 31 Jul 2018 15:34:05 +0200 > Victor Stinner <vstin...@redhat.com> wrote: >> Antoine: would you mind to subscribe to the capi-sig mailing list? As >> expected, they are many interesting points discussed here, but I would >> like to move all C API discussions to capi-sig. I only continue on >> python-dev since you started here (and ignored my request to start >> discussing my idea on capi-sig :-)). > > Well, I responded to your e-mail discussion thread. I see more > messages in this thread here than on capi-sig. ;-) > >> For example, PyPy uses different memory allocators depending on the >> scope and the lifetime of an object. I'm not sure that you can >> implement such optimization if you are stuck with reference counting. > > But what does reference counting have to do with memory allocators > exactly? > >> > OS vendors seem to be doing a fine job AFAICT. And if I want a recent >> > Python I just download Miniconda/Anaconda. >> >> Is it used in production to deploy services? Or is it more used by >> developers? I never used Anaconda. > > I don't know, but there's no hard reason why you couldn't use it to > deploy services (though some people may prefer Docker or other > technologies). > >> > I think you don't realize that the C API is *already* annoying. People >> > started with it mostly because there wasn't a better alternative at the >> > time. You don't need to make it more annoying than it already is ;-) >> > >> > Replacing existing C extensions with something else is entirely a >> > developer time/effort problem, not an attractivity problem. And I'm >> > not sure that porting a C extension to a new C API is more reasonable >> > than porting to Cython entirely. >> >> Do you think that it's doable to port numpy to Cython? It's made of >> 255K lines of C code. > > Numpy is a bit special as it exposes its own C API, so porting it > entirely to Cython would be difficult (how do you expose a C macro in > Cython?). Also, internally it has a lot of macro-generated code for > specialized loop implementations (metaprogramming in C :-)). > > I suppose some bits could be (re)written in Cython. Actually, the > numpy.random module is already a Cython module. > >> > It's just that I disagree that removing the C API will make CPython 2x >> > faster. >> >> How can we make CPython 2x faster? Why everybody, except of PyPy, >> failed to do that? > > Because PyPy spent years working full time on a JIT compiler. It's also > written in (a dialect of) Python, which helps a lot with experimenting > and building abstractions, compared to C or even C++. > > Regards > > Antoine. > _______________________________________________ > Python-Dev mailing list > Python-Dev@python.org > https://mail.python.org/mailman/listinfo/python-dev > Unsubscribe: > https://mail.python.org/mailman/options/python-dev/vstinner%40redhat.com _______________________________________________ Python-Dev mailing list Python-Dev@python.org https://mail.python.org/mailman/listinfo/python-dev Unsubscribe: https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
