On 07/06/2019 11:41 am, Jeroen Demeyer wrote:
Hello,
I'm starting this thread to brainstorm for using vectorcall to speed up
creating instances of Python classes.
Currently the following happens when creating an instance of a Python
class X using X(.) and assuming that __new__ and __init__ are Python
functions and that the metaclass of X is simply "type":
1. type_call (the tp_call wrapper for type) is invoked with arguments
(X, args, kwargs).
2. type_call calls slot_tp_new with arguments (X, args, kwargs).
3. slot_tp_new calls X.__new__, prepending X to the args tuple. A new
object obj is returned.
4. type_call calls slot_tp_init with arguments (obj, args, kwargs).
5. slot_tp_init calls type(obj).__init__ method, prepending obj to the
args tuple. A new object obj is returned.
In the worst case, no less than 6 temporary objects are needed just to
pass arguments around:
1. An args tuple and kwargs dict for tp_call
3. An args array with X prepended and a kwnames tuple for __new__
5. An args array with obj prepended and a kwnames tuple for __init__
This is clearly not as efficient as it could be.
An obvious solution would be to introduce variants of tp_new and tp_init
using the vectorcall protocol. Assuming PY_VECTORCALL_ARGUMENTS_OFFSET
is used, all 6 temporary allocations could be dropped. The
implementation could be in the form of two new slots tp_vector_new and
tp_vector_init. Since we're just dealing with type slots here (as
opposed to offsets in an object structure), this should be easier to
implement than PEP 590 itself.
Relatively few classes override __new__, which means that object.__new__
can be inlined. Something like this (which needs a bit of cleaning up):
https://github.com/markshannon/cpython/commit/9ff46e3ba0747f386f9519933910d63d5caae6ee
Cheers,
Mark.
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