Closed kmuehlbauer closed 1 week ago
The offending package is numba
which has pinned numpy <2.1 for the current version 0.60.
numba 0.61 will be numpy 2.1 compatible, but isn't yet released.
One short-term solution to unlock CI would be to pin numpy <2.1 in all CI with environments containing numba.
you mean, pin array-api-strict
for now?
That would be one solution, or to pin numpy>=2,<2.1. Not sure what's more reasonable.
if I understand correctly, the issue is that the new version of array-api-strict
requires numpy>=2.1
but the conda-forge
package metadata does not reflect that. So I don't think requiring an older version of numpy
would help, since we'd still get the new (broken) version of array-api-strict
.
The conda-forge array-api-strict
metadata is fixed now.
If the current choice is to pin array-api-strict
or numpy
, I'd constrain the former though.
numpy
is indirectly constrained by numba
, so if the metadata has been fixed there might be nothing we need to do here?
Edit: actually, I misunderstood what you said. I guess it would be best to pin array-api-strict
(or explicitly forbid the broken versions) either way.
Thanks @rgommers, much appreciated.
@keewis The all-but-numba check fails even with numpy=2.1.3 and array-api-strict=2.1.2. See https://github.com/pydata/xarray/actions/runs/11739187309/job/32703227103?pr=9751
I'll look into it, but this might take some time.
@keewis I've pinned array-api-strict<=2.1
in all relevant environments in #9751. Would be good to get this in to unlock CI again. Would also buy you some time to investigate the issues wrt the failing array-api-strict related tests.
What is your issue?
array-api-strict v2.1.2
(released some hours ago) needsnumpy >=2.1
, but the conda-forge package is missing that pin:see:
Some of xarray's dependencies are not available yet for numpy >=2.1, the current environments resolve to numpy 2.0.2. This breaks the tests where array-api-strict is imported.