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standardize and consolidate wheel installations in testing scripts #16575
standardize and consolidate wheel installations in testing scripts #16575
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It wasn't caused by this PR, but let's get these extras fixed here since they aren't quite right. pylibcudf doesn't have a pandas-tests extra. It does have a test extra, but I wouldn't expect it to be needed in this test run.
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It looks like with this combined approach of installation, even though you're explicitly specifying to install pylibcudf that package doesn't get included in dependency resolution for cudf. The two step process might be necessary, or you can switch to adding
--find-links
to the command.There was a problem hiding this comment.
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I do see the failure at https://github.com/rapidsai/cudf/actions/runs/10425017056/job/28875933840?pr=16575.
But did you notice that the CUDA 11.8 version of that same job, using the same script, succeeded?
(build link)
If this method of dependency resolution didn't work, I'd have expected those jobs to both fail in the same way. I'm going to merge in latest
branch-24.10
+ apply your suggestion, let's see what happens on a re-run.There was a problem hiding this comment.
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Good point, that thought flashed in and out of my brain while reviewing your PR and left no trace 😂 let's see what we see.
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It is still failing, so there is something strange happening here.
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ah, thanks!! I hadn't noticed the different
pip
versions!!That's totally it.
I was able to reproduce the failure locally.
code to do that (click me)
Inspected the package metadata with
pkginfo
, didn't see any issues... names, versions, and dependency lists all looked correct.Upgraded
pip
(to 24.2) and tried again:That succeeded 🎉
This makes me think we should be running
pip install --upgrade pip
every time the images at https://github.com/rapidsai/ci-imgs are rebuilt. Can you think of strong reason we shouldn't do that? If not, I'll put up a PR proposing that and see what others say.There was a problem hiding this comment.
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The main argument against updating pip unconditionally everywhere is that we shouldn't require our users to always have the latest version of pip to be able to install our software. This has come up before in devcontainers, for instance, where the latest version of pip available as a system-installable package is significantly older than the latest version available from PyPI, and the question is raised whether it's really a good idea to require a newer one.
For now, for the purpose of CI I think it's OK to always update so that at least we have consistent behavior. At some point we might want to introduce some form of testing to ensure that our packages are actually installable with different versions of pip, though. We have in the past done things (e.g. the rapids-dask-dependency shenanigans) that ultimately require a fairly new version of pip, which could be an onerous constraint on some users.
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Thanks, ok yeah that makes sense.
I've opened rapidsai/ci-imgs#171 proposing upgrading
pip
in the wheel CI images.I agree. This type of thing should be tested directly (similar to rapidsai/build-planning#81) if we want to have high confidence in it.
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Now that the new CI images are published (https://github.com/rapidsai/ci-imgs/actions/runs/10457672191), I've restarted CI here. Merge latest
branch-24.10
into this (figured I might as well, to get a bit more useful test coverage, if I'm going to re-run so many jobs anyway).Hopefully with newer
pip
across all the CI images, this newer, stricter pattern for these scripts will work.There was a problem hiding this comment.
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🎉 looks like that worked!
https://github.com/rapidsai/cudf/actions/runs/10458119570/job/28961862201?pr=16575
Thanks a lot for the help, @vyasr !