On Mon, Apr 30, 2012 at 4:55 PM, Nathaniel Smith <n...@pobox.com> wrote: > On Mon, Apr 30, 2012 at 9:49 PM, Dag Sverre Seljebotn > <d.s.seljeb...@astro.uio.no> wrote: >> JIT is really the way to go. It is one thing that a JIT could optimize the >> case where you pass a callback to a function and inline it run-time. But >> even if it doesn't get that fancy, it'd be great to just be able to write >> something like "cython.eval(s)" and have that be compiled (I guess you could >> do that now, but the sheer overhead of the C compiler and all the .so files >> involved means nobody would sanely use that as the main way of stringing >> together something like pandas). > > The overhead of running a fully optimizing compiler over pandas on > every import is pretty high, though. You can come up with various > caching mechanisms, but they all mean introducing some kind of compile > time/run time distinction. So I'm skeptical we'll just be able to get > rid of that concept, even in a brave new LLVM/PyPy/Julia world. > > -- Nathaniel > _______________________________________________ > cython-devel mailing list > cython-devel@python.org > http://mail.python.org/mailman/listinfo/cython-devel
I'd be perfectly OK with just having to compile pandas's "data engine" and generate loads of C/C++ code. JIT-compiling little array expressions would be cool too. I've got enough of an itch that I might have to start scratching pretty soon. _______________________________________________ cython-devel mailing list cython-devel@python.org http://mail.python.org/mailman/listinfo/cython-devel
