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/4727#issuecomment-750419141,https://api.github.com/repos/pydata/xarray/issues/4727,750419141,MDEyOklzc3VlQ29tbWVudDc1MDQxOTE0MQ==,2272878,2020-12-23T18:23:20Z,2020-12-23T18:23:20Z,CONTRIBUTOR,"My concern with `assert_identical` is the name.  It implies, to me, that there is no difference at all between the two objects.  It was highly unexpected for me that it didn't do that.  I think at the very least it should be clarified in the documentation that it doesn't do that.

If the default for `assert_identical` isn't change, I wonder whether a new function might be worthwhile.  I am concerned having to append `check_dtype=True` for every test would hurt test clarity.  And there is also the problem with 

Also, just checking dtype won't be sufficient in all cases.  Consider this:

```Python
import numpy as np 
import xarray as xr 

a = xr.DataArray(np.array(1.0, dtype=np.object))                                                                                                                                                                                          
b = xr.DataArray(np.array(1, dtype=np.object))                                                                                                                                                                                            

xr.testing.assert_identical(a, b)  
```

I think for the purpose of testing being able to make sure the result is *exactly* what you expect is important.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,773750763