ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_accessor_dt.TestDatetimeAccessor object at 0x12718c7f0>

    def test_total_seconds(self) -> None:
        # Subtract a value in the middle of the range to ensure that some values
        # are negative
>       delta = self.data.time - np.datetime64("2000-01-03")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_dt.py#x1B[0m:107: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:250: in __sub__
    return self._binary_op(other, operator.sub)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:671: in __sub__
    from xarray.namedarray._array_api import subtract
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_accessor_dt.TestDatetimeAccessor object at 0x12718ee00>

    def test_strftime(self) -> None:
>       assert (
            "2000-01-01 01:00:00" == self.data.time.dt.strftime("%Y-%m-%d %H:%M:%S")[1]
        )

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_dt.py#x1B[0m:140: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:295: in __eq__
    return self._binary_op(other, nputils.array_eq)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/nputils.py#x1B[0m:113: in array_eq
    return _ensure_bool_is_ndarray(self == other, self, other)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:742: in __eq__
    from xarray.namedarray._array_api import equal
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestZarrDirectoryStore object at 0x1470c9780>

    def test_write_read_select_write(self) -> None:
        # Test for https://github.com/pydata/xarray/issues/4084
        ds = create_test_data()
    
        # NOTE: using self.roundtrip, which uses open_dataset, will not trigger the bug.
        with self.create_zarr_target() as initial_store:
            ds.to_zarr(initial_store, mode="w", **self.version_kwargs)
            ds1 = xr.open_zarr(initial_store, **self.version_kwargs)
    
            # Combination of where+squeeze triggers error on write.
>           ds_sel = ds1.where(ds1.coords["dim3"] == "a", drop=True).squeeze("dim3")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:3070: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:295: in __eq__
    return self._binary_op(other, nputils.array_eq)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/nputils.py#x1B[0m:113: in array_eq
    return _ensure_bool_is_ndarray(self == other, self, other)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:742: in __eq__
    from xarray.namedarray._array_api import equal
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestH5NetCDFData object at 0x12f52a980>

    def test_isel_dataarray(self) -> None:
        # Make sure isel works lazily. GH:issue:1688
        in_memory = create_test_data()
        with self.roundtrip(in_memory) as on_disk:
>           expected = in_memory.isel(dim2=in_memory["dim2"] < 3)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:800: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:283: in __lt__
    return self._binary_op(other, operator.lt)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:762: in __lt__
    from xarray.namedarray._array_api import less
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestZarrWriteEmpty object at 0x14663a740>

    def test_isel_dataarray(self) -> None:
        # Make sure isel works lazily. GH:issue:1688
        in_memory = create_test_data()
        with self.roundtrip(in_memory) as on_disk:
>           expected = in_memory.isel(dim2=in_memory["dim2"] < 3)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:800: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:283: in __lt__
    return self._binary_op(other, operator.lt)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:762: in __lt__
    from xarray.namedarray._array_api import less
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
self = <xarray.tests.test_backends.TestH5NetCDFData object at 0x12f5328f0>

    def test_dropna(self) -> None:
        # regression test for GH:issue:1694
        a = np.random.randn(4, 3)
        a[1, 1] = np.nan
        in_memory = xr.Dataset(
            {"a": (("y", "x"), a)}, coords={"y": np.arange(4), "x": np.arange(3)}
        )
    
        assert_identical(
>           in_memory.dropna(dim="x"), in_memory.isel(x=slice(None, None, 2))
        )

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:848: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/util/deprecation_helpers.py#x1B[0m:116: in inner
    return func(*args, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:6494: in dropna
    count += np.asarray(array.count(dims))
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_aggregations.py#x1B[0m:76: in count
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (y: 4, x: 3)> Size: 96B
array([[ 1.76405235,  0.40015721,  0.97873798],
       [ 2.2408932 ,         nan, -0.97727788],
       [ 0.95008842, -0.15135721, -0.10321885],
       [ 0.4105985 ,  0.14404357,  1.45427351]])
dims = ('y',), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
self = <xarray.tests.test_backends.TestZarrWriteEmpty object at 0x146636e60>

    def test_dropna(self) -> None:
        # regression test for GH:issue:1694
        a = np.random.randn(4, 3)
        a[1, 1] = np.nan
        in_memory = xr.Dataset(
            {"a": (("y", "x"), a)}, coords={"y": np.arange(4), "x": np.arange(3)}
        )
    
        assert_identical(
>           in_memory.dropna(dim="x"), in_memory.isel(x=slice(None, None, 2))
        )

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:848: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/util/deprecation_helpers.py#x1B[0m:116: in inner
    return func(*args, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:6494: in dropna
    count += np.asarray(array.count(dims))
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_aggregations.py#x1B[0m:76: in count
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (y: 4, x: 3)> Size: 96B
array([[ 1.76405235,  0.40015721,  0.97873798],
       [ 2.2408932 ,         nan, -0.97727788],
       [ 0.95008842, -0.15135721, -0.10321885],
       [ 0.4105985 ,  0.14404357,  1.45427351]])
dims = ('y',), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.str_'>

    def test_contains_broadcast(dtype) -> None:
        values = xr.DataArray(["Foo", "xYz", "fOOomMm__fOo", "MMM_"], dims="X").astype(
            dtype
        )
        pat_str = xr.DataArray(["FOO|mmm", "Foo", "MMM"], dims="Y").astype(dtype)
        pat_re = xr.DataArray([re.compile(x) for x in pat_str.data], dims="Y")
    
        # case insensitive using regex
        result = values.str.contains(pat_str, case=False)
        expected = xr.DataArray(
            [
                [True, True, False],
                [False, False, False],
                [True, True, True],
                [True, False, True],
            ],
            dims=["X", "Y"],
        )
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        # case sensitive using regex
        result = values.str.contains(pat_str)
        expected = xr.DataArray(
            [
                [False, True, False],
                [False, False, False],
                [False, False, False],
                [False, False, True],
            ],
            dims=["X", "Y"],
        )
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
>       result = values.str.contains(pat_re)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:181: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1491: in contains
    is_compiled_re = _contains_compiled_re(pat)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:104: in _contains_compiled_re
    return _contains_obj_type(pat=pat, checker=re.Pattern)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 3)> Size: 24B
array([True, True, True], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.bytes_'>

    def test_contains_broadcast(dtype) -> None:
        values = xr.DataArray(["Foo", "xYz", "fOOomMm__fOo", "MMM_"], dims="X").astype(
            dtype
        )
        pat_str = xr.DataArray(["FOO|mmm", "Foo", "MMM"], dims="Y").astype(dtype)
        pat_re = xr.DataArray([re.compile(x) for x in pat_str.data], dims="Y")
    
        # case insensitive using regex
        result = values.str.contains(pat_str, case=False)
        expected = xr.DataArray(
            [
                [True, True, False],
                [False, False, False],
                [True, True, True],
                [True, False, True],
            ],
            dims=["X", "Y"],
        )
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        # case sensitive using regex
        result = values.str.contains(pat_str)
        expected = xr.DataArray(
            [
                [False, True, False],
                [False, False, False],
                [False, False, False],
                [False, False, True],
            ],
            dims=["X", "Y"],
        )
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
>       result = values.str.contains(pat_re)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:181: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1491: in contains
    is_compiled_re = _contains_compiled_re(pat)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:104: in _contains_compiled_re
    return _contains_obj_type(pat=pat, checker=re.Pattern)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 3)> Size: 24B
array([True, True, True], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestZarrWriteEmpty object at 0x14663a350>

    def test_append_overwrite_values(self) -> None:
        # regression for GH1215
        data = create_test_data()
        with create_tmp_file(allow_cleanup_failure=False) as tmp_file:
            self.save(data, tmp_file, mode="w")
            data["var2"][:] = -999
>           data["var9"] = data["var2"] * 3

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:1346: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:253: in __mul__
    return self._binary_op(other, operator.mul)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:676: in __mul__
    from xarray.namedarray._array_api import multiply
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
def test_replace_callable() -> None:
        values = xr.DataArray(["fooBAD__barBAD"])
    
        # test with callable
        repl = lambda m: m.group(0).swapcase()
        result = values.str.replace("[a-z][A-Z]{2}", repl, n=2)
        exp = xr.DataArray(["foObaD__baRbaD"])
        assert result.dtype == exp.dtype
        assert_equal(result, exp)
    
        # test regex named groups
        values = xr.DataArray(["Foo Bar Baz"])
        pat = r"(?P<first>\w+) (?P<middle>\w+) (?P<last>\w+)"
        repl = lambda m: m.group("middle").swapcase()
        result = values.str.replace(pat, repl)
        exp = xr.DataArray(["bAR"])
        assert result.dtype == exp.dtype
        assert_equal(result, exp)
    
        # test broadcast
        values = xr.DataArray(["Foo Bar Baz"], dims=["x"])
        pat = r"(?P<first>\w+) (?P<middle>\w+) (?P<last>\w+)"
        repl2 = xr.DataArray(
            [
                lambda m: m.group("first").swapcase(),
                lambda m: m.group("middle").swapcase(),
                lambda m: m.group("last").swapcase(),
            ],
            dims=["Y"],
        )
>       result = values.str.replace(pat, repl2)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:417: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1931: in replace
    elif not _contains_callable(repl):  # pragma: no cover
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:109: in _contains_callable
    return _contains_obj_type(pat=pat, checker=callable)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 3)> Size: 24B
array([True, True, True], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
def test_replace_unicode() -> None:
        # flags + unicode
        values = xr.DataArray([b"abcd,\xc3\xa0".decode("utf-8")])
        expected = xr.DataArray([b"abcd, \xc3\xa0".decode("utf-8")])
        pat = re.compile(r"(?<=\w),(?=\w)", flags=re.UNICODE)
        result = values.str.replace(pat, ", ")
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        # broadcast version
        values = xr.DataArray([b"abcd,\xc3\xa0".decode("utf-8")], dims=["X"])
        expected = xr.DataArray(
            [[b"abcd, \xc3\xa0".decode("utf-8"), b"BAcd,\xc3\xa0".decode("utf-8")]],
            dims=["X", "Y"],
        )
        pat2 = xr.DataArray(
            [re.compile(r"(?<=\w),(?=\w)", flags=re.UNICODE), r"ab"], dims=["Y"]
        )
        repl = xr.DataArray([", ", "BA"], dims=["Y"])
>       result = values.str.replace(pat2, repl)

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:442: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1934: in replace
    is_compiled_re = _contains_compiled_re(pat)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:104: in _contains_compiled_re
    return _contains_obj_type(pat=pat, checker=re.Pattern)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 2)> Size: 16B
array([True, False], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.str_'>

    def test_replace_compiled_regex(dtype) -> None:
        values = xr.DataArray(["fooBAD__barBAD"], dims=["x"]).astype(dtype)
    
        # test with compiled regex
        pat = re.compile(dtype("BAD[_]*"))
        result = values.str.replace(pat, "")
        expected = xr.DataArray(["foobar"], dims=["x"]).astype(dtype)
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        result = values.str.replace(pat, "", n=1)
        expected = xr.DataArray(["foobarBAD"], dims=["x"]).astype(dtype)
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        # broadcast
        pat2 = xr.DataArray(
            [re.compile(dtype("BAD[_]*")), re.compile(dtype("AD[_]*"))], dims=["y"]
        )
>       result = values.str.replace(pat2, "")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:466: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1934: in replace
    is_compiled_re = _contains_compiled_re(pat)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:104: in _contains_compiled_re
    return _contains_obj_type(pat=pat, checker=re.Pattern)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (y: 2)> Size: 16B
array([True, True], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.bytes_'>

    def test_replace_compiled_regex(dtype) -> None:
        values = xr.DataArray(["fooBAD__barBAD"], dims=["x"]).astype(dtype)
    
        # test with compiled regex
        pat = re.compile(dtype("BAD[_]*"))
        result = values.str.replace(pat, "")
        expected = xr.DataArray(["foobar"], dims=["x"]).astype(dtype)
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        result = values.str.replace(pat, "", n=1)
        expected = xr.DataArray(["foobarBAD"], dims=["x"]).astype(dtype)
        assert result.dtype == expected.dtype
        assert_equal(result, expected)
    
        # broadcast
        pat2 = xr.DataArray(
            [re.compile(dtype("BAD[_]*")), re.compile(dtype("AD[_]*"))], dims=["y"]
        )
>       result = values.str.replace(pat2, "")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:466: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:1934: in replace
    is_compiled_re = _contains_compiled_re(pat)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:104: in _contains_compiled_re
    return _contains_obj_type(pat=pat, checker=re.Pattern)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:88: in _contains_obj_type
    return _apply_str_ufunc(func=checker, obj=pat).all()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1358: in all
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (y: 2)> Size: 16B
array([True, True], dtype=object)
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestH5NetCDFData object at 0x12f531de0>

    def test_append_overwrite_values(self) -> None:
        # regression for GH1215
        data = create_test_data()
        with create_tmp_file(allow_cleanup_failure=False) as tmp_file:
            self.save(data, tmp_file, mode="w")
            data["var2"][:] = -999
>           data["var9"] = data["var2"] * 3

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:1346: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:253: in __mul__
    return self._binary_op(other, operator.mul)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:676: in __mul__
    from xarray.namedarray._array_api import multiply
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

NameError: name 'dims' is not defined
self = <xarray.tests.test_backends.TestZarrWriteEmpty object at 0x14510b760>
group = None

    @pytest.mark.parametrize("group", [None, "group1"])
    def test_write_persistence_modes(self, group) -> None:
        original = create_test_data()
    
        # overwrite mode
        with self.roundtrip(
            original,
            save_kwargs={"mode": "w", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # don't overwrite mode
        with self.roundtrip(
            original,
            save_kwargs={"mode": "w-", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # make sure overwriting works as expected
        with self.create_zarr_target() as store:
            self.save(original, store)
            # should overwrite with no error
            self.save(original, store, mode="w", group=group)
            with self.open(store, group=group) as actual:
                assert_identical(original, actual)
                with pytest.raises(ValueError):
                    self.save(original, store, mode="w-")
    
        # check append mode for normal write
        with self.roundtrip(
            original,
            save_kwargs={"mode": "a", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # check append mode for append write
        ds, ds_to_append, _ = create_append_test_data()
        with self.create_zarr_target() as store_target:
            ds.to_zarr(store_target, mode="w", group=group, **self.version_kwargs)
            ds_to_append.to_zarr(
                store_target, append_dim="time", group=group, **self.version_kwargs
            )
>           original = xr.concat([ds, ds_to_append], dim="time")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:2562: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/concat.py#x1B[0m:277: in concat
    return _dataset_concat(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/concat.py#x1B[0m:667: in _dataset_concat
    combined_var = concat_vars(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:2992: in concat
    return Variable.concat(variables, dim, positions, shortcut, combine_attrs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1741: in concat
    axis = first_var.get_axis_num(dim)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <xarray.Variable (lat: 3, lon: 3, time: 3)> Size: 216B
array([[[0.27059024, 0.72030174, 0.63106838],
        [0.728267... 0.98608612, 0.49313505],
        [0.75439345, 0.94027823, 0.00539805],
        [0.50539587, 0.48977873, 0.47407012]]])
dim = 'time'

    def get_axis_num(self, dim: Hashable | Iterable[Hashable]) -> int | tuple[int, ...]:
        """Return axis number(s) corresponding to dimension(s) in this array.
    
        Parameters
        ----------
        dim : str or iterable of str
            Dimension name(s) for which to lookup axes.
    
        Returns
        -------
        int or tuple of int
            Axis number or numbers corresponding to the given dimensions.
        """
>       if dims is _default:
#x1B[1m#x1B[31mE       NameError: name 'dims' is not defined#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1082: NameError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.str_'>

    def test_extract_extractall_findall_empty_raises(dtype) -> None:
        pat_str = dtype(r".*")
        pat_re = re.compile(pat_str)
    
        value = xr.DataArray([["a"]], dims=["X", "Y"]).astype(dtype)
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
            value.str.extract(pat=pat_str, dim="ZZ")
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
            value.str.extract(pat=pat_re, dim="ZZ")
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
>           value.str.extractall(pat=pat_str, group_dim="XX", match_dim="YY")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:565: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:2236: in extractall
    .max()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1502: in max
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (X: 1, Y: 1)> Size: 8B
array([[2]])
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestH5NetCDFData object at 0x12f532050>

    def test_append_with_invalid_dim_raises(self) -> None:
        data = create_test_data()
        with create_tmp_file(allow_cleanup_failure=False) as tmp_file:
            self.save(data, tmp_file, mode="w")
>           data["var9"] = data["var2"] * 3

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:1355: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:253: in __mul__
    return self._binary_op(other, operator.mul)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:4749: in _binary_op
    f(self.variable, other_variable_or_arraylike)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:676: in __mul__
    from xarray.namedarray._array_api import multiply
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.bytes_'>

    def test_extract_extractall_findall_empty_raises(dtype) -> None:
        pat_str = dtype(r".*")
        pat_re = re.compile(pat_str)
    
        value = xr.DataArray([["a"]], dims=["X", "Y"]).astype(dtype)
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
            value.str.extract(pat=pat_str, dim="ZZ")
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
            value.str.extract(pat=pat_re, dim="ZZ")
    
        with pytest.raises(ValueError, match="No capture groups found in pattern."):
>           value.str.extractall(pat=pat_str, group_dim="XX", match_dim="YY")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:565: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:2236: in extractall
    .max()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1502: in max
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (X: 1, Y: 1)> Size: 8B
array([[2]])
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

NameError: name 'dims' is not defined
self = <xarray.tests.test_backends.TestZarrWriteEmpty object at 0x14510b5b0>
group = 'group1'

    @pytest.mark.parametrize("group", [None, "group1"])
    def test_write_persistence_modes(self, group) -> None:
        original = create_test_data()
    
        # overwrite mode
        with self.roundtrip(
            original,
            save_kwargs={"mode": "w", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # don't overwrite mode
        with self.roundtrip(
            original,
            save_kwargs={"mode": "w-", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # make sure overwriting works as expected
        with self.create_zarr_target() as store:
            self.save(original, store)
            # should overwrite with no error
            self.save(original, store, mode="w", group=group)
            with self.open(store, group=group) as actual:
                assert_identical(original, actual)
                with pytest.raises(ValueError):
                    self.save(original, store, mode="w-")
    
        # check append mode for normal write
        with self.roundtrip(
            original,
            save_kwargs={"mode": "a", "group": group},
            open_kwargs={"group": group},
        ) as actual:
            assert_identical(original, actual)
    
        # check append mode for append write
        ds, ds_to_append, _ = create_append_test_data()
        with self.create_zarr_target() as store_target:
            ds.to_zarr(store_target, mode="w", group=group, **self.version_kwargs)
            ds_to_append.to_zarr(
                store_target, append_dim="time", group=group, **self.version_kwargs
            )
>           original = xr.concat([ds, ds_to_append], dim="time")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:2562: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/concat.py#x1B[0m:277: in concat
    return _dataset_concat(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/concat.py#x1B[0m:667: in _dataset_concat
    combined_var = concat_vars(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:2992: in concat
    return Variable.concat(variables, dim, positions, shortcut, combine_attrs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1741: in concat
    axis = first_var.get_axis_num(dim)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <xarray.Variable (lat: 3, lon: 3, time: 3)> Size: 216B
array([[[0.22191874, 0.89823848, 0.19997297],
        [0.901056... 0.11934181, 0.34869584],
        [0.22087265, 0.60153981, 0.42224052],
        [0.82268364, 0.91110839, 0.06194036]]])
dim = 'time'

    def get_axis_num(self, dim: Hashable | Iterable[Hashable]) -> int | tuple[int, ...]:
        """Return axis number(s) corresponding to dimension(s) in this array.
    
        Parameters
        ----------
        dim : str or iterable of str
            Dimension name(s) for which to lookup axes.
    
        Returns
        -------
        int or tuple of int
            Axis number or numbers corresponding to the given dimensions.
        """
>       if dims is _default:
#x1B[1m#x1B[31mE       NameError: name 'dims' is not defined#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1082: NameError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.str_'>

    def test_extract_broadcast(dtype) -> None:
        value = xr.DataArray(
            ["a_Xy_0", "ab_xY_10", "abc_Xy_01"],
            dims=["X"],
        ).astype(dtype)
    
        pat_str = xr.DataArray(
            [r"(\w+)_Xy_(\d*)", r"(\w+)_xY_(\d*)"],
            dims=["Y"],
        ).astype(dtype)
        pat_compiled = value.str._re_compile(pat=pat_str)
    
        expected_list = [
            [["a", "0"], ["", ""]],
            [["", ""], ["ab", "10"]],
            [["abc", "01"], ["", ""]],
        ]
        expected = xr.DataArray(expected_list, dims=["X", "Y", "Zz"]).astype(dtype)
    
>       res_str = value.str.extract(pat=pat_str, dim="Zz")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:862: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:2052: in extract
    .max()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1502: in max
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 2)> Size: 16B
array([2, 2])
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError

ModuleNotFoundError: No module named 'array_api_compat'
self = <xarray.tests.test_backends.TestH5NetCDFData object at 0x12f5bf790>

    def test_write_groups(self) -> None:
        data1 = create_test_data()
>       data2 = data1 * 2

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_backends.py#x1B[0m:1493: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_typed_ops.py#x1B[0m:41: in __mul__
    return self._binary_op(other, operator.mul)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7777: in _binary_op
    ds = self._calculate_binary_op(g, other, join=align_type)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7846: in _calculate_binary_op
    new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataset.py#x1B[0m:7846: in <dictcomp>
    new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars}
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:676: in __mul__
    from xarray.namedarray._array_api import multiply
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/__init__.py#x1B[0m:11: in <module>
    from xarray.namedarray._array_api._constants import e, inf, nan, newaxis, pi
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_constants.py#x1B[0m:3: in <module>
    _xp = _maybe_default_namespace()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

xp = None

    def _maybe_default_namespace(xp: ModuleType | None = None) -> ModuleType:
        if xp is None:
            # import array_api_strict as xpd
>           import array_api_compat.numpy as xpd
#x1B[1m#x1B[31mE           ModuleNotFoundError: No module named 'array_api_compat'#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/_array_api/_utils.py#x1B[0m:22: ModuleNotFoundError

AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?
dtype = <class 'numpy.bytes_'>

    def test_extract_broadcast(dtype) -> None:
        value = xr.DataArray(
            ["a_Xy_0", "ab_xY_10", "abc_Xy_01"],
            dims=["X"],
        ).astype(dtype)
    
        pat_str = xr.DataArray(
            [r"(\w+)_Xy_(\d*)", r"(\w+)_xY_(\d*)"],
            dims=["Y"],
        ).astype(dtype)
        pat_compiled = value.str._re_compile(pat=pat_str)
    
        expected_list = [
            [["a", "0"], ["", ""]],
            [["", ""], ["ab", "10"]],
            [["abc", "01"], ["", ""]],
        ]
        expected = xr.DataArray(expected_list, dims=["X", "Y", "Zz"]).astype(dtype)
    
>       res_str = value.str.extract(pat=pat_str, dim="Zz")

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/tests/test_accessor_str.py#x1B[0m:862: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/accessor_str.py#x1B[0m:2052: in extract
    .max()
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/_aggregations.py#x1B[0m:1502: in max
    return self.reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/dataarray.py#x1B[0m:3831: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/core/variable.py#x1B[0m:1668: in reduce
    result = super().reduce(
#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:1301: in reduce
    axis_ = _dims_to_axis(self, d, axislike)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = <xarray.Variable (Y: 2)> Size: 16B
array([2, 2])
dims = (<Default.token: 0>,), axis = None

    def _dims_to_axis(
        x: NamedArray[Any, Any], dims: _Dim | _Dims | Default, axis: _AxisLike | None
    ) -> _AxisLike | None:
        """
        Convert dims to axis indices.
    
        Examples
        --------
        >>> narr = NamedArray(("x", "y"), np.array([[1, 2, 3], [5, 6, 7]]))
        >>> _dims_to_axis(narr, ("y",), None)
        (1,)
        >>> _dims_to_axis(narr, None, 0)
        (0,)
        >>> _dims_to_axis(narr, None, None)
        """
        _assert_either_dim_or_axis(dims, axis)
    
        if dims is not _default:
>           return x._dims_to_axes(dims)
#x1B[1m#x1B[31mE           AttributeError: 'Variable' object has no attribute '_dims_to_axes'. Did you mean: '_dim_to_axis'?#x1B[0m

#x1B[1m#x1B[31m/Users/runner/work/xarray/xarray/xarray/namedarray/core.py#x1B[0m:155: AttributeError