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/5559#issuecomment-872502631,https://api.github.com/repos/pydata/xarray/issues/5559,872502631,MDEyOklzc3VlQ29tbWVudDg3MjUwMjYzMQ==,2448579,2021-07-01T19:41:14Z,2021-07-01T19:41:14Z,MEMBER,"> And the solution would be to just call the method on the duck array without any kind of type checking first?

Or `np.method(array)`","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,935062144
https://github.com/pydata/xarray/issues/5559#issuecomment-872499933,https://api.github.com/repos/pydata/xarray/issues/5559,872499933,MDEyOklzc3VlQ29tbWVudDg3MjQ5OTkzMw==,35968931,2021-07-01T19:35:43Z,2021-07-01T19:35:43Z,MEMBER,So this is actually an xarray problem not a dask/pint problem? And the solution would be to just call the method on the duck array without any kind of type checking first?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,935062144
https://github.com/pydata/xarray/issues/5559#issuecomment-872477132,https://api.github.com/repos/pydata/xarray/issues/5559,872477132,MDEyOklzc3VlQ29tbWVudDg3MjQ3NzEzMg==,2448579,2021-07-01T18:56:41Z,2021-07-01T18:59:27Z,MEMBER,"> Is it correct that xarray ends up calling dask.array.mean() on the pint.Quantity(dask.Array) object inside the DataArray? 

Yes that's correct. See
https://github.com/pydata/xarray/blob/c472f8a4c79f872edb9dcd7825f786ecb9aff5c0/xarray/core/duck_array_ops.py#L49-L51

It may be time to update this method since we now depend on a minimum numpy version that supports NEP-18.

cc @shoyer 

EDIT: You get there from `_create_nan_agg_method`: https://github.com/pydata/xarray/blob/c472f8a4c79f872edb9dcd7825f786ecb9aff5c0/xarray/core/duck_array_ops.py#L347","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,935062144
https://github.com/pydata/xarray/issues/5559#issuecomment-872441814,https://api.github.com/repos/pydata/xarray/issues/5559,872441814,MDEyOklzc3VlQ29tbWVudDg3MjQ0MTgxNA==,3460034,2021-07-01T17:57:32Z,2021-07-01T18:05:19Z,CONTRIBUTOR,"Is it correct that xarray ends up calling `dask.array.mean()` on the `pint.Quantity(dask.Array)` object inside the `DataArray`? I took a guess at that since I can replicate what is happening inside the `DataArray` with

```python
import dask.array as da

da = xr.DataArray([1,2,3], attrs={'units': 'metres'})

chunked = da.chunk(1).pint.quantify()

da.mean(chunked.variable._data)
```

Also, the Dask warning `Passing an object to dask.array.from_array which is already a Dask collection. This can lead to unexpected behavior.` is a big red flag that the Pint Quantity is making its way into Dask internals where it should not end up.

If so, I think this gets into a thorny issue with duck array handling in Dask. It was decided in https://github.com/dask/dask/pull/6393 that deliberately calling Dask array operations like `elemwise` (so, presumably by extension, `blockwise` and the reductions in `dask.array.reductions` like `mean()`) on a non-Dask array implies that the user wants to turn that array into a dask array. This get problematic, however, for upcast types like Pint Quantities that wrap Dask Arrays, since then you can get `dask.Array(pint.Quantity(dask.Array))`, which is what I think is going on here?

If this all checks out, I believe this becomes a Dask issue to improve upcast type/duck Dask array handling.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,935062144