Since I am still a bit on the fence with the deprecation (see also
below), to mostly make the following Python integer conversions an
error (for now deprecation):
np.uint8(-1)
np.array(50000, dtype=np.int8)
I have created a Poll about the change in case anyone wants to give
feedback but formulate arguments in a mail:
https://discuss.scientific-python.org/t/deprecation-of-assigning-converting-out-of-bounds-python-integers/580
Cheers,
Sebastian
PS: One tangential reason why I am bringing it up, is that I am
struggling with the notion of "casting safety" for these Python
integers. I will bring this up again also, but it is not directly
related.
On Tue, 2022-10-11 at 14:00 +0200, Sebastian Berg wrote:
> Hi all,
>
> just to mention it, there is a PR ready on this:
>
> https://github.com/numpy/numpy/pull/22385
>
> it necessecitates some changes to the NumPy test suite and will do
> similar at least for SciPy downstream
> I currently suspect we will give it a shot soon, but am not opposed
> at
> all with discussing especially allowing:
>
> np.uint8(-1)
>
> i.e. using the negative range of the corresponding signed integer
> explicitly for the `np.uint8`, `np.uint16`. But still disallow it
> for
> other operations like `np.array([-1], dtype=np.uint8)`.
>
> As I said, my main interest is pushing NEP 50 related change:
>
> https://github.com/numpy/numpy/pull/21875
>
> which this will simplify. If this PR seems tricky to move forward,
> that is fine, but I would like to push that PR without the
> simplification. (Decoupling this change from NEP 50 at some
> complexity
> cost.)
>
> Cheers,
>
> Sebastian
>
>
>
> On Tue, 2022-10-04 at 17:24 +0200, Ralf Gommers wrote:
> > On Thu, Sep 29, 2022 at 10:10 AM Sebastian Berg
> > <sebast...@sipsolutions.net>
> > wrote:
> >
> > > On Wed, 2022-09-28 at 16:44 -0700, Stefan van der Walt wrote:
> > > > Hi Sebastian,
> > > >
> > > > On Wed, Sep 28, 2022, at 12:11, Sebastian Berg wrote:
> > > > > np.array([1, 2], dtype="uint8") + (-1)
> > > > >
> > > > > which currently returns an "int16" array must raise an
> > > > > error.
> > > > > This
> > > > > is
> > > > > because we want to return a uint8 array but the -1 cannot be
> > > > > represented well by -1.
> > > >
> > > > Did you mean: the -1 is not representable in uint8?
> > >
> > > Sorry yes. With NEP 50, we do not look at the value (initially)
> > > so
> > > determine that the operation must be handled as:
> > >
> > > uint8 + uint8 -> uint8
> > >
> > > We then try to convert the -1 to uint8. That conversion would
> > > raise an
> > > error, because previously the result was an int16.
> > > (This is to prevent silent unexpected result changes and seemed
> > > like
> > > the more reasonable behavior.)
> > >
> > > On the other hand, assignments like:
> > >
> > > uint8_arr[0] = -1
> > > np.array([-1], dtype=np.uint8)
> > >
> > > do happily convert the -1 to `uint8`, currently. If we keep
> > > allowing
> > > these, we have two slightly different conversions: one that
> > > fails
> > > and
> > > one that does not.
> > >
> > > This is fine, but maybe we actually want it to always fail in the
> > > future?
> > >
> >
> > It seems better to always raise an exception indeed. So if it
> > simplifies
> > your PR to do that now, I'd say go for it.
> >
> > Cheers,
> > Ralf
> > _______________________________________________
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> > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
> > Member address: sebast...@sipsolutions.net
>
>
> _______________________________________________
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