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2 rows where "closed_at" is on date 2022-11-30, type = "pull" and user = 43316012 sorted by updated_at descending

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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1377097243 PR_kwDOAMm_X84_J8JL 7051 Add parse_dims func headtr1ck 43316012 closed 0     6 2022-09-18T15:36:59Z 2022-12-08T20:10:01Z 2022-11-30T23:36:33Z COLLABORATOR   0 pydata/xarray/pulls/7051

This PR adds a utils.parse_dims function for parsing one or more dimensions. Currently every function that accepts multiple dimensions does this by itself.

I decided to first see if it would be useful to centralize the dimension parsing and collect inputs before adding it to other functions.

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    xarray 13221727 pull
1421441672 PR_kwDOAMm_X85BcmP0 7209 Optimize some copying headtr1ck 43316012 closed 0     8 2022-10-24T21:00:21Z 2022-12-08T20:09:49Z 2022-11-30T23:36:56Z COLLABORATOR   0 pydata/xarray/pulls/7209
  • [x] Potentially closes #7181
  • [x] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst

I have passed along some more memo dicts, which could prevent some double deep-copying of the same data (don't know how exactly, but who knows :P) Also, I have found some copy calls that did not pass along the deep argument (I am not sure if that breaks things, lets find out). And finally I have found some places where shallow copies are enough.

All together it should improve the performance a lot when copying things around.

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    xarray 13221727 pull

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