Drop the additional numpy 1.16 test #778
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
see: * zarr-developers#774 which drops Python 3.6 * zarr-developers#749 which bumps h5py to 3.2
|
All tests are green except for the one 1.16.x build which was removed here (and therefore is blocked) Merging to try to get other PRs green. If there are any objections to dropping this particular test, we can resurrect without impacting end-users. |
|
NumPy 1.20 is the current version (and has already seen a few patch releases). Plus NumPy 1.21 already had RC 2 come out over a week ago (so is probably coming out soon). Given the pace of NumPy releases, where NumPy is at version-wise, and the general ease of installing NumPy these days, bumping to 1.17 seems pretty reasonable. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Builds that are pinned to the 1.16.x numpy series are starting to fail. Dropping those in favor of 1.17.x numpy to keep as much backwards compatibility as possible.
see: