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1 row where author_association = "MEMBER", issue = 1151751524 and user = 5635139 sorted by updated_at descending

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  • max-sixty · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1052626478 https://github.com/pydata/xarray/issues/6308#issuecomment-1052626478 https://api.github.com/repos/pydata/xarray/issues/6308 IC_kwDOAMm_X84-vc4u max-sixty 5635139 2022-02-26T21:16:05Z 2022-02-26T21:16:05Z MEMBER

Very much agree with the goal!

I wonder whether there's a broader approach with something like xr.describe — i.e. give lots of useful info about the metadata of the array, including any warnings. It's not that performance sensitive, so it would be fine to throw lots of things in there.

Either way, I'm a +1

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  xr.doctor(): diagnostics on a Dataset / DataArray ? 1151751524

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CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);
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