Pin Numpy to less than 1.25 in CI #10306
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We are not (should not be) fundamentally incompatible with Numpy 1.25, there are just new deprecation warnings and seemingly some behavioural changes that are causing flakiness in the isometry CI. This temporarily pins Numpy to allow people to continue working while we address the root cause.
jakelishman
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mtreinish
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Jun 19, 2023
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I think we left |
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Most of the Numpy 1.25 CI failures are just extra deprecation warnings, and we'd have been fine to release with them. The isometry stuff is producing completely invalid decompositions, though, which we can't release with. We may need to upgrade the constraint to a requirement if we can't get it sorted. |
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We are not (should not be) fundamentally incompatible with Numpy 1.25, there are just new deprecation warnings and seemingly some behavioural changes that are causing flakiness in the isometry CI. This temporarily pins Numpy to allow people to continue working while we address the root cause. (cherry picked from commit b8a4448)
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* Pin Numpy to less than 1.25 in CI (#10306) We are not (should not be) fundamentally incompatible with Numpy 1.25, there are just new deprecation warnings and seemingly some behavioural changes that are causing flakiness in the isometry CI. This temporarily pins Numpy to allow people to continue working while we address the root cause. (cherry picked from commit b8a4448) * Try pinning python patch version to fix macOS 3.17 failure The macOS python 3.7 job has started failing with a cryptic pip error. It looks like pip is failing to resolve package versions correctly for python-cosntraint when installing terra. This commit is attempting to avoid the failure by pinning the python version we install, because the image updated the version used since the last successful job. * Pin only macOS Python version --------- Co-authored-by: Jake Lishman <jake.lishman@ibm.com> Co-authored-by: Matthew Treinish <mtreinish@kortar.org>
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Summary
We are not (should not be) fundamentally incompatible with Numpy 1.25, there are just new deprecation warnings and seemingly some behavioural changes that are causing flakiness in the isometry CI. This temporarily pins Numpy to allow people to continue working while we address the root cause.
Details and comments
Workaround #10305.