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1 row where issue = 792651098 and user = 11861183 sorted by updated_at descending

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  • dklink · 1 ✖

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  • Opening a dataset doesn't display groups. · 1 ✖

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  • NONE 1
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
766198081 https://github.com/pydata/xarray/issues/4840#issuecomment-766198081 https://api.github.com/repos/pydata/xarray/issues/4840 MDEyOklzc3VlQ29tbWVudDc2NjE5ODA4MQ== dklink 11861183 2021-01-23T23:22:11Z 2021-01-23T23:23:41Z NONE

Update: after diving into the way the source code works, it seems group information would actually have to get loaded on the backend loaders; this is a pretty deep code change. The minimal diff seems like it would be to load the group names, then add to the global attrs dictionary {"groups": "group1, group2, ..."}. This way, they would automagically propagate all the way through the codebase to the __repr__ call and show up in the output string. Of course, it's a little clugey, because the names of the groups aren't really an attribute of the underlying file. And if there's already an attribute named 'groups'? Tricky, not sure what the optimal resolution to that is; probably just don't overwrite it and do nothing. But the alternative is creating a representation for "groups" alongside "dimensions", "coordinates", "data variables", and "attributes", and adding machinery for these throughout the code base, changing method signatures, etc, which is really more moving in the direction of Datasets actually supporting groups, which is a whole different undertaking. This is just supposed to be a bit more visibility into the underlying netcdf file. Unsure if this moderate level of cluge is acceptable or not though.

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  Opening a dataset doesn't display groups. 792651098

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