issue_comments: 634867837

This data as json

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/3847#issuecomment-634867837 https://api.github.com/repos/pydata/xarray/issues/3847 634867837 MDEyOklzc3VlQ29tbWVudDYzNDg2NzgzNw== 14808389 2020-05-27T18:48:15Z 2020-05-27T18:48:15Z MEMBER

hmm... using arr.compute() fails while np.array(arr) works. For now, I'm converting all dask arrays to numpy if the dask version is not high enough (I can't do that only for bool_ arrays since they have been converted to float somewhere).

@shoyer: I'm confused, I thought that xr.testing.assert_allclose explicitly supported duck arrays (it calls duck_array_ops.allclose_or_equiv). TBC, what I was talking about was these lines: https://github.com/pydata/xarray/blob/e5cc19cd8f8a69e0743f230f5bf51b7778a0ff96/xarray/testing.py#L124 https://github.com/pydata/xarray/blob/e5cc19cd8f8a69e0743f230f5bf51b7778a0ff96/xarray/testing.py#L132-L135 where the .values always convert to numpy

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   577425749