issues

What happened?

Apparently xarray-2024.2.0 requires xarray.datatree_ module but this module isn't included in sdist tarball.

What did you expect to happen?

No response

Minimal Complete Verifiable Example

Python $ tar -tf /tmp/dist/xarray-2024.2.0.tar.gz | grep datatree_ (empty)

MVCE confirmation

• [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
• [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.
• [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

No response

Environment

n/a

What happened:

The test suite failed: ```pytb =================================== FAILURES =================================== ____ TestDataset.test_resample_loffset _____

self = <xarray.tests.test_dataset.TestDataset object at 0xe6ccde68>

def test_resample_loffset(self):
    times = pd.date_range("2000-01-01", freq="6H", periods=10)
    ds = Dataset(
        {
            "foo": (["time", "x", "y"], np.random.randn(10, 5, 3)),
            "bar": ("time", np.random.randn(10), {"meta": "data"}),
            "time": times,
        }
    )
    ds.attrs["dsmeta"] = "dsdata"

    # Our use of `loffset` may change if we align our API with pandas' changes.
    # ref https://github.com/pydata/xarray/pull/4537
    actual = ds.resample(time="24H", loffset="-12H").mean().bar
    expected_ = ds.bar.to_series().resample("24H").mean()
    expected_.index += to_offset("-12H")
    expected = DataArray.from_series(expected_)

  assert_identical(actual, expected)

E AssertionError: Left and right DataArray objects are not identical E
E Differing values: E L E array([ 0.018477, -0.178807, -0.792644]) E R E array([ 0.018477, -0.178807, -0.792644])

actual = <xarray.DataArray 'bar' (time: 3)> array([ 0.01847694, -0.1788066 , -0.79264435]) Coordinates: * time (time) datetime64[ns] 1999-12-31T12:00:00 ... 2000-01-02T12:00:00 ds = <xarray.Dataset> Dimensions: (time: 10, x: 5, y: 3) Coordinates: * time (time) datetime64[ns] 2000-01-01 ... 2000-01-03T06:00:00 Dimensions without coordinates: x, y Data variables: foo (time, x, y) float64 1.764 0.4002 0.9787 ... 1.117 -1.316 -0.4616 bar (time) float64 -0.06824 1.713 -0.7448 ... -1.08 -1.147 -0.4378 Attributes: dsmeta: dsdata expected = <xarray.DataArray 'bar' (time: 3)> array([ 0.01847694, -0.1788066 , -0.79264435]) Coordinates: * time (time) datetime64[ns] 1999-12-31T12:00:00 ... 2000-01-02T12:00:00 expected_ = time 1999-12-31 12:00:00 0.018477 2000-01-01 12:00:00 -0.178807 2000-01-02 12:00:00 -0.792644 Freq: 24H, Name: bar, dtype: float64 self = <xarray.tests.test_dataset.TestDataset object at 0xe6ccde68> times = DatetimeIndex(['2000-01-01 00:00:00', '2000-01-01 06:00:00', '2000-01-01 12:00:00', '2000-01-01 18:00:00', '2000-01-02 00:00:00', '2000-01-02 06:00:00', '2000-01-02 12:00:00', '2000-01-02 18:00:00', '2000-01-03 00:00:00', '2000-01-03 06:00:00'], dtype='datetime64[ns]', freq='6H')

/var/tmp/portage/dev-python/xarray-0.18.2-r1/work/xarray-0.18.2/xarray/tests/test_dataset.py:3991: AssertionError =============================== warnings summary =============================== ```

What you expected to happen: Test suite passing ;-).

Minimal Complete Verifiable Example:

n/a (xarray test suite problem)

Anything else we need to know?:

This happens on 32-bit i686 system but not on amd64. I suppose it's a precision problem.

Environment:

What happened?

When running the test suite in an environment where both dask and pyarrow are installed, two tests fail (log below):

FAILED xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe_2D - AssertionError: Attributes of DataFrame.iloc[:, 1] (column name="y") are different FAILED xarray/tests/test_dask.py::TestToDaskDataFrame::test_to_dask_dataframe_not_daskarray - AssertionError: DataFrame.index are different

What did you expect to happen?

Tests passing ;-).

Minimal Complete Verifiable Example

Python pip install . pytest 'dask[complete]' python -m pytest xarray/tests/test_dask.py

MVCE confirmation

• [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

```Python ______ TestToDaskDataFrame.test_to_dask_dataframe_2D ______

self = <xarray.tests.test_dask.TestToDaskDataFrame object at 0x7f59a87bce50>

def test_to_dask_dataframe_2D(self):
    # Test if 2-D dataset is supplied
    w = np.random.randn(2, 3)
    ds = Dataset({"w": (("x", "y"), da.from_array(w, chunks=(1, 2)))})
    ds["x"] = ("x", np.array([0, 1], np.int64))
    ds["y"] = ("y", list("abc"))

    # dask dataframes do not (yet) support multiindex,
    # but when it does, this would be the expected index:
    exp_index = pd.MultiIndex.from_arrays(
        [[0, 0, 0, 1, 1, 1], ["a", "b", "c", "a", "b", "c"]], names=["x", "y"]
    )
    expected = pd.DataFrame({"w": w.reshape(-1)}, index=exp_index)
    # so for now, reset the index
    expected = expected.reset_index(drop=False)
    actual = ds.to_dask_dataframe(set_index=False)

    assert isinstance(actual, dd.DataFrame)

  assert_frame_equal(expected, actual.compute())

E AssertionError: Attributes of DataFrame.iloc[:, 1] (column name="y") are different E
E Attribute "dtype" are different E [left]: object E [right]: string[pyarrow]

/tmp/xarray/xarray/tests/test_dask.py:822: AssertionError _____ TestToDaskDataFrame.testto_dask_dataframe_not_daskarray _______

self = <xarray.tests.test_dask.TestToDaskDataFrame object at 0x7f59a87d5750>

def test_to_dask_dataframe_not_daskarray(self):
    # Test if DataArray is not a dask array
    x = np.random.randn(10)
    y = np.arange(10, dtype="uint8")
    t = list("abcdefghij")

    ds = Dataset({"a": ("t", x), "b": ("t", y), "t": ("t", t)})

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

    actual = ds.to_dask_dataframe(set_index=True)
    assert isinstance(actual, dd.DataFrame)

  assert_frame_equal(expected, actual.compute())

/tmp/xarray/xarray/tests/test_dask.py:867:

left = Index(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], dtype='object', name='t') right = Index(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], dtype='string', name='t'), obj = 'DataFrame.index'

def _check_types(left, right, obj: str = "Index") -> None:
    if not exact:
        return

    assert_class_equal(left, right, exact=exact, obj=obj)
    assert_attr_equal("inferred_type", left, right, obj=obj)

    # Skip exact dtype checking when `check_categorical` is False
    if is_categorical_dtype(left.dtype) and is_categorical_dtype(right.dtype):
        if check_categorical:
            assert_attr_equal("dtype", left, right, obj=obj)
            assert_index_equal(left.categories, right.categories, exact=exact)
        return

  assert_attr_equal("dtype", left, right, obj=obj)

E AssertionError: DataFrame.index are different E
E Attribute "dtype" are different E [left]: object E [right]: string[pyarrow]

/tmp/xarray/.venv/lib/python3.11/site-packages/pandas/_testing/asserters.py:250: AssertionError ```

Anything else we need to know?

No response

Environment