=================================== FAILURES ===================================
____________ test_repartition_npartitions[<lambda>1-float-5-1-True] ____________
[gw37] linux -- Python 3.10.7 /nix/store/bnqsrgcx271flnlhnb9pxps4nyjrydk4-python3-3.10.7/bin/python3.10
use_index = True, n = 1, k = 5, dtype = <class 'float'>
transform = <function <lambda> at 0xfffe6066f760>
    @pytest.mark.parametrize("use_index", [True, False])
    @pytest.mark.parametrize("n", [1, 2, 4, 5])
    @pytest.mark.parametrize("k", [1, 2, 4, 5])
    @pytest.mark.parametrize("dtype", [float, "M8[ns]"])
    @pytest.mark.parametrize("transform", [lambda df: df, lambda df: df.x])
    def test_repartition_npartitions(use_index, n, k, dtype, transform):
        df = pd.DataFrame(
            {"x": [1, 2, 3, 4, 5, 6] * 10, "y": list("abdabd") * 10},
            index=pd.Series([10, 20, 30, 40, 50, 60] * 10, dtype=dtype),
        )
        df = transform(df)
        a = dd.from_pandas(df, npartitions=n, sort=use_index)
        b = a.repartition(k)
        assert_eq(a, b)
        assert b.npartitions == k
        parts = dask.get(b.dask, b.__dask_keys__())
>       assert all(map(len, parts))
E       assert False
E        +  where False = all(<map object at 0xfffe406cb8e0>)
E        +    where <map object at 0xfffe406cb8e0> = map(len, (10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\n10.0    1\nName: x, dtype: i...0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\n60.0    6\nName: x, dtype: int64))
dask/dataframe/tests/test_dataframe.py:2153: AssertionError
____________ test_repartition_npartitions[<lambda>0-float-5-1-True] ____________
[gw66] linux -- Python 3.10.7 /nix/store/bnqsrgcx271flnlhnb9pxps4nyjrydk4-python3-3.10.7/bin/python3.10
use_index = True, n = 1, k = 5, dtype = <class 'float'>
transform = <function <lambda> at 0xfffec252c700>
    @pytest.mark.parametrize("use_index", [True, False])
    @pytest.mark.parametrize("n", [1, 2, 4, 5])
    @pytest.mark.parametrize("k", [1, 2, 4, 5])
    @pytest.mark.parametrize("dtype", [float, "M8[ns]"])
    @pytest.mark.parametrize("transform", [lambda df: df, lambda df: df.x])
    def test_repartition_npartitions(use_index, n, k, dtype, transform):
        df = pd.DataFrame(
            {"x": [1, 2, 3, 4, 5, 6] * 10, "y": list("abdabd") * 10},
            index=pd.Series([10, 20, 30, 40, 50, 60] * 10, dtype=dtype),
        )
        df = transform(df)
        a = dd.from_pandas(df, npartitions=n, sort=use_index)
        b = a.repartition(k)
        assert_eq(a, b)
        assert b.npartitions == k
        parts = dask.get(b.dask, b.__dask_keys__())
>       assert all(map(len, parts))
E       assert False
E        +  where False = all(<map object at 0xfffec1265a50>)
E        +    where <map object at 0xfffec1265a50> = map(len, (      x  y\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1  a\n10.0  1....0  5  b\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d\n60.0  6  d))
dask/dataframe/tests/test_dataframe.py:2153: AssertionError