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/issues/6726#issuecomment-1280072309,https://api.github.com/repos/pydata/xarray/issues/6726,1280072309,IC_kwDOAMm_X85MTFp1,90008,2022-10-16T22:33:17Z,2022-10-16T22:33:17Z,CONTRIBUTOR,"In developing https://github.com/pydata/xarray/pull/7172, there are also some places where class types are used to check for features:
https://github.com/pydata/xarray/blob/main/xarray/core/pycompat.py#L35

Dask and sparse and big contributors due to their need to resolve the class name in question.

Ultimately. I think it is important to maybe constrain the problem.

Are we ok with 100 ms over numpy + pandas? 20 ms?

On my machines, the 0.5 s that xarray is close to seems long... but everytime I look at it, it seems to ""just be a python problem"".
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1284475176
https://github.com/pydata/xarray/issues/6726#issuecomment-1223863010,https://api.github.com/repos/pydata/xarray/issues/6726,1223863010,IC_kwDOAMm_X85I8qri,883786,2022-08-23T10:17:46Z,2022-08-23T10:17:46Z,CONTRIBUTOR,Some other projects are considering lazy imports as well: https://scientific-python.org/specs/spec-0001/,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1284475176