html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/5607#issuecomment-881859823,https://api.github.com/repos/pydata/xarray/issues/5607,881859823,IC_kwDOAMm_X840kBzv,167164,2021-07-17T08:51:12Z,2021-07-17T08:51:12Z,NONE,"@shoyer That would either not work, or be needlessly expensive, I think. The message generation might be expensive (e.g. if I want a sum or mean of the differences). With a call back it only happens if it is needed. With a pre-computed message it would be computed every time.. Correct me if I'm wrong.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,945226829
https://github.com/pydata/xarray/pull/5607#issuecomment-881170326,https://api.github.com/repos/pydata/xarray/issues/5607,881170326,IC_kwDOAMm_X840hZeW,167164,2021-07-16T04:37:24Z,2021-07-16T11:35:40Z,NONE,"@TomNicholas My particular use case is that have datasets that are large enough that I can't see the full diff, so might miss major changes. I'm wanting to pass in something like `lambda a, b: f""Largest difference in data is {abs(a-b).max().item()}""`, so I can quickly see if the changes are meaningful. Obviously a more complex function might also be useful, like a summary/describe table output of the differences..

I know I could set the tolerances higher, but the changes are not numerical errors, and I want to see them before updating the test data that they are comparing against.

Entirely possible that there are better ways to do this, of course :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,945226829