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/4208#issuecomment-656068407,https://api.github.com/repos/pydata/xarray/issues/4208,656068407,MDEyOklzc3VlQ29tbWVudDY1NjA2ODQwNw==,6213168,2020-07-09T11:18:15Z,2020-07-09T11:19:28Z,MEMBER,"> Is it acceptable for a Pint Quantity to always have the Dask collection interface defined (i.e., be a duck Dask array), even when its magnitude (what it wraps) is not a Dask Array?

I think there are already enough headaches with ``__iter__`` being always defined and confusing libraries such as pandas (https://github.com/hgrecco/pint/issues/1128).
I don't see why pint should be explicitly aware of dask (except in unit tests)? It should only deal with generic NEP18-compatible libraries (numpy, dask, sparse, cupy, etc.).

> How should xarray check for a duck Dask Array?

We should ask the dask team to formalize what defines a ""dask-array-like"", like they already did with dask collections, and implement their definition in xarray.
I'd personally make it ""whatever defines a numpy-array-like AND has a chunks method AND the chunks method returns a tuple"".","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,653430454