issues: 587895591

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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
587895591 MDU6SXNzdWU1ODc4OTU1OTE= 3891 Keep attrs by default? (keep_attrs) 5635139 open 0     14 2020-03-25T18:17:35Z 2023-09-22T02:27:50Z   MEMBER      

I've held this view in low confidence for a while and wanted to socialize it to see whether there's something to it: Should we keep attrs in operations by default?

Advantages: - I think most of the time people want to keep attrs after operations - Is that right? Are there cases where it wouldn't be a reasonable default? e.g. good points here for not always keeping coords around - It's easy to remove them with a (currently unimplemented) drop_attrs method when people do want to remove them

Disadvantages: - Backward incompatible change with an expensive deprecate cycle (would be impractical to have a deprecation warning every time someone ran a function on an object with attrs I think? At least without adding a once filter warning) - ?

Here are some existing relevant discussions: - https://github.com/pydata/xarray/issues/3815#issuecomment-603974527 - https://github.com/pydata/xarray/issues/688 - https://github.com/pydata/xarray/pull/2482 - https://github.com/pydata/xarray/issues/3304

I think this is an easy situation to get into: - We make an incorrect-but-insignificant design decision; e.g. some methods don't keep attrs - We want to change that, but avoid breaking backward-compatibility - So we add kwargs and eventually a global config - But now we have a global config that requires global context and lots of kwargs! :(

I'm up for leaning towards breaking changes if it makes the library better: I think xarray will grow immensely, and so the narrow immediate pain is worth the broader future positive impact. Clearly if the immediate pain stops xarray growing, then it's not a good tradeoff.

 
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