issue_comments: 510953379

We're at the point where this could be hacked together pretty quickly: 1. We need to remove the explicit casting to NumPy arrays (ala https://github.com/pydata/xarray/pull/2956). Checking for an __array_function__ attribute is probably a good heuristic for duck arrays (it's what dask is using). 2. Internally, we need to use NumPy functions directly (if __array_function__ is enabled) instead of our current Dask/NumPy versions. Fortunately, pretty much all this logic lives in one place, in xarray.core.duck_array_ops. 3. We'll need to think a little bit about indexing in particular. Right now we have special indexing wrappers for NumPy arrays and Dask arrays; we would need to decide how to handle arbitrary array objects (probably by indexing them like NumPy arrays?). Basic indexing should work either way, but indexing with arrays can be a little tricky since few duck-array types support NumPy's full semantics (which are pretty complex).