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-... 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 <sebastian@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 _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: sebastian@sipsolutions.net

_______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: sebastian@sipsolutions.net