On Tue, 21 Apr 2015 18:27:50 +0300 Paul Sokolovsky <pmis...@gmail.com> wrote: > Let me try: MicroPython already uses type annotations for statically > typed functions. E.g. > > def add(x:int, y:int): > return x + y > > will translate the function to just 2 machine instructions.
That's quite nice. > Oh really, you care to support single-precisions in Numba? Numba is quite specialized. In our area, single-precision arithmetic can sometimes give double the speed on modern CPUs (especially when LLVM is able to vectorize the code). The speedup can be even larger on a GPU (where double-precision execution resources are scarce). I agree it doesn't make sense for a general-purpose Python compiler. > Anyway, back to your example, it would be done like: > > SFloat = float > DFloat = float > > For a random tool out there, "SFloat" and "DFloat" would be just > aliases to floats, but Numba will know they have additional semantics > behind them. (That assumes that typedefs like SFloat can be accessed in > symbolic form - that's certainly possible if you have your own > parser/VM, but might worth to think how to do it on "CPython" level). Fortunately, we don't have our own parser :-) We work from the CPython bytecode. 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/archive%40mail-archive.com
