issue_comments: 657895835

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https://github.com/pydata/xarray/pull/4221#issuecomment-657895835 https://api.github.com/repos/pydata/xarray/issues/4221 657895835 MDEyOklzc3VlQ29tbWVudDY1Nzg5NTgzNQ== 3460034 2020-07-14T00:22:09Z 2020-07-14T00:22:09Z CONTRIBUTOR

Also, a broader discussion that's I've seen hinted to in the past, but is brought to the forefront by this PR: how should xarray be checking for general duck array types it can wrap?

Right now, it looks like there is a mix of

python is_array_like(data) and python hasattr(data, "__array_function__") or isinstance(data, dask_array_type)

and it would be nice to bring consistency. However, both these checks seem like they'd let too many types through. For example, is_array_like as currently implemented would still let through too much, such as MemoryCachedArray and xarray Variables/DataArrays, and __array_function__ doesn't truly indicate a NumPy duck array on its own (and it really only works to only capture downcast types right now since xarray does not yet implement __array_function__ itself, #3917).

 
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