[Numpy-discussion] PyPy wheels (was: NumPy 1.12.0b1 released)

Nathaniel Smith njs at pobox.com
Fri Nov 18 20:53:04 EST 2016


On Nov 18, 2016 3:30 PM, "Ralf Gommers" <ralf.gommers at gmail.com> wrote:
>
>
>
> On Sat, Nov 19, 2016 at 5:24 AM, Nathaniel Smith <njs at pobox.com> wrote:
>>
>> Another thing to think about is that 1.12 on pypy won't pass its test
suite (though it's close), and we're not yet testing new PRs on pypy, so no
guarantees about 1.13 yet. I think on balance these probably aren't reasons
*not* to upload wheels, but it's a funny place where we're talking about
providing "official" builds even though it's not an "officially supported
platform". So we will at least want to be clear about that. And someone
will have to handle the bug reports about the test suite failing :-).
>
>
> Those are good points. We could run PyPy on TravisCI; the PyPy install
and numpy build aren't difficult anymore.

I'm not sure how useful this until the test suite is passing, though, just
because of how travis-ci works.

The main outstanding issue needs some work on the numpy side: basically
UPDATEIFCOPY, as currently conceived, just can't work reliably on pypy,
because it assumes that Python objects get deterministically deallocated as
soon as their reference count drops to zero, and pypy doesn't have
reference counts.

I think fixing this should be straightforward enough, in case anyone wants
to work on it. Every user of UPDATEIFCOPY already has to be aware of the
reference counts and know when the pseudo-"view" array is supposed to be
deallocated. So I think we should define a new UPDATEIFCOPY2 flag, which
acts like the current UPDATEIFCOPY, except that instead of using __del__ to
do the writeback, there's an explicit API call you have to make, like
PyArray_UpdateIfCopy2_Writeback, that checks for the flag and does the
writeback if set. Then we should transition to using this internally, and
probably deprecate UPDATEIFCOPY (though we may never be able to get rid of
it entirely).

-n
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