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Python 3.8 Test Summary Info

FAILED xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe
FAILED xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe_2D
FAILED xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe_coordinates

[keewis]

this fails because pandas changed the way they treat dask arrays passed to their constructor: we now get a series of object dtype filled with 0d dask arrays.

We can work around that by computing x before passing it to pandas.DataFrame in the to_dask_dataframe tests:

expected_pd = pd.DataFrame({"a": x.compute(), "b": y}, index=pd.Index(t, name="t"))

or by assigning the initial numpy array to x and converting it to a dask array immediately before passing it to the xr.Dataset constructor:

x = np.random.randn(10)
# ...
ds = xr.Dataset({"a": ("t", da.from_array(x, chunks=4)), "b": ("t", y), "t": ("t", t)})

(and something similar for the other two failing tests)

But maybe we should just ask the pandas devs whether that was intentional?

[dcherian]

But maybe we should just ask the pandas devs whether that was intentional?

cc @TomAugspurger

[TomAugspurger]

I'm not sure offhand. Maybe best to post an issue on the pandas tracker.