Hi, 2016-01-25 23:28 GMT+01:00 Andrew Barnert <abarn...@yahoo.com>: > On Jan 25, 2016, at 13:43, Victor Stinner <victor.stin...@gmail.com> wrote: >> >> According to microbenchmarks, the most promising optimizations are >> functions inlining (Python function calls are slow :-/) and specialize >> the code for the type of arguments. > > Can you specialize a function with a C API function, or only with bytecode? > I'm not sure how much benefit you'd get out of specializing list vs. generic > iterable or int vs. whatever from an AST transform, but substituting raw C > code, on the other hand...
As I wrote in the first part of my email, I redesigned to API to make it more generic. One of my change was to change PyFunction_Specialize() to not only accept code objects, but any callable object. The PEP 510 even contains an example using a builtin function as the specialized code: https://www.python.org/dev/peps/pep-0510/#using-builtin-function "On a microbenchmark, calling the C builtin takes 95 ns, whereas the original bytecode takes 155 ns (+60 ns): 1.6 times as fast. Calling directly chr(65) takes 76 ns." You can design an AST optimizer to compile some functions to C and then register them as specialized code at runtime. I have a side project to use Cython and/or pythran to specialize some functions using type annotation on parameters. Victor _______________________________________________ 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
