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Handle zarr 3.1.0 #766
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Handle zarr 3.1.0 #766
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Co-authored-by: Mark Kittisopikul <[email protected]>
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #766 +/- ##
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+ Coverage 99.96% 100.00% +0.03%
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Files 64 64
Lines 2789 2804 +15
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+ Hits 2788 2804 +16
+ Misses 1 0 -1
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LGTM - the new API should definitely be made private, and it would be good to see at least one CI run against Zarr 3.0.x to make sure we're retaining support there.
what's the easiest way to set up a test matrix that includes multiple zarr versions that can be run locally easily? Maybe we need to bite the bullet and bring in #704 |
For now, can we not just have one test run on the GH Actions CI that tests against |
sure! can you write it? |
I added pixi + hatch to pyproject.toml exclusively for running the zarr-python tests against two different versions of zarr-python. We can always add to this later. |
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Big 👍 for pixi
here. A couple of things:
- I think we shouldn't commit a lockfile, see inline comment
- In the test logs the version of Zarr the tests are run with isn't printed, meaning it's not possible to verify tests are being run against 3.0.x and latest zarr. Can you print the Zarr version somehow?
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I think we don't want to commit a lockfile, because we want to be continuously testing against latest versions of dependencies instead of continually bumping versions in a lockfile (since number of new dependecy versions that are fine is > number of new dependency versions that will break us)
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To me it does not make sense to not commit the lockfile, especially for conda where you would lose fast solved dependencies and reproducibility for development and PRs checks. Trying to unpick why a build failed without a known good-state can be a nightmare.
I agree that checking against latest versions is very useful but probably better served as separate CI build that use pixi update
to get latest versions on merge to main and/or on a schedule.
dependencies = [ | ||
"zarr=={matrix:zarr}" | ||
] | ||
numpy="==2.2" |
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numpy="==2.2" | |
numpy="==2.2" |
Does this need pinning, or can it just be plain numpy
?
Implements a data type adapter layer for
numcodecs.zarr3
. Ensures that zarr data structures get the right data type.this hopefully fixes the breakage caused by the zarr 3.1 release.
TODO: