id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
936313924,MDExOlB1bGxSZXF1ZXN0NjgzMDY3OTU5,5571,Rely on NEP-18 to dispatch to dask in duck_array_ops,35968931,closed,0,,,20,2021-07-03T19:24:33Z,2022-07-09T18:12:05Z,2021-09-29T17:48:40Z,MEMBER,,0,pydata/xarray/pulls/5571,"Removes special-casing for dask in `duck_array_ops.py`, instead relying on NEP-18 to call it when the input is a dask array.

Probably actually don't need the `_dask_or_eager_func()` (now `_module_func()`) helper function at all, because all remaining instances look like `pandas_isnull = _module_func(""isnull"", module=pd)`, which could just be `pandas_isnull = pd.isnull`.

Only problem is that I seem to have broken one (parameterized) test: `test_duck_array_ops.py::test_min_count[True-True-None-sum-True-bool_-1]` fails with

```python
    @pytest.mark.parametrize(""dim_num"", [1, 2])
    @pytest.mark.parametrize(""dtype"", [float, int, np.float32, np.bool_])
    @pytest.mark.parametrize(""dask"", [False, True])
    @pytest.mark.parametrize(""func"", [""sum"", ""prod""])
    @pytest.mark.parametrize(""aggdim"", [None, ""x""])
    @pytest.mark.parametrize(""contains_nan"", [True, False])
    @pytest.mark.parametrize(""skipna"", [True, False, None])
    def test_min_count(dim_num, dtype, dask, func, aggdim, contains_nan, skipna):
        if dask and not has_dask:
            pytest.skip(""requires dask"")
    
        da = construct_dataarray(dim_num, dtype, contains_nan=contains_nan, dask=dask)
        min_count = 3
    
        # If using Dask, the function call should be lazy.
        with raise_if_dask_computes():
>           actual = getattr(da, func)(dim=aggdim, skipna=skipna, min_count=min_count)

/home/tegn500/Documents/Work/Code/xarray/xarray/tests/test_duck_array_ops.py:578: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/tegn500/Documents/Work/Code/xarray/xarray/core/common.py:56: in wrapped_func
    return self.reduce(func, dim, axis, skipna=skipna, **kwargs)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/dataarray.py:2638: in reduce
    var = self.variable.reduce(func, dim, axis, keep_attrs, keepdims, **kwargs)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/variable.py:1725: in reduce
    data = func(self.data, **kwargs)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/duck_array_ops.py:328: in f
    return func(values, axis=axis, **kwargs)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/nanops.py:106: in nansum
    a, mask = _replace_nan(a, 0)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/nanops.py:23: in _replace_nan
    mask = isnull(a)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/duck_array_ops.py:83: in isnull
    return pandas_isnull(data)
/home/tegn500/Documents/Work/Code/xarray/xarray/core/duck_array_ops.py:40: in f
    return getattr(module, name)(*args, **kwargs)
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/pandas/core/dtypes/missing.py:127: in isna
    return _isna(obj)
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/pandas/core/dtypes/missing.py:166: in _isna
    return _isna_ndarraylike(np.asarray(obj), inf_as_na=inf_as_na)
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/numpy/core/_asarray.py:102: in asarray
    return array(a, dtype, copy=False, order=order)
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/dask/array/core.py:1502: in __array__
    x = self.compute()
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/dask/base.py:285: in compute
    (result,) = compute(self, traverse=False, **kwargs)
/home/tegn500/miniconda3/envs/py38-mamba/lib/python3.8/site-packages/dask/base.py:567: in compute
    results = schedule(dsk, keys, **kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <xarray.tests.CountingScheduler object at 0x7f0804db2310>
dsk = {('xarray-<this-array>-29953318277423606f95b509ad1a9aa7', 0): array([False, False, False, False], dtype=object), ('xar...pe=object), ('xarray-<this-array>-29953318277423606f95b509ad1a9aa7', 3): array([nan, False, False, nan], dtype=object)}
keys = [[('xarray-<this-array>-29953318277423606f95b509ad1a9aa7', 0), ('xarray-<this-array>-29953318277423606f95b509ad1a9aa7'...array-<this-array>-29953318277423606f95b509ad1a9aa7', 2), ('xarray-<this-array>-29953318277423606f95b509ad1a9aa7', 3)]]
kwargs = {}

    def __call__(self, dsk, keys, **kwargs):
        self.total_computes += 1
        if self.total_computes > self.max_computes:
>           raise RuntimeError(
                ""Too many computes. Total: %d > max: %d.""
                % (self.total_computes, self.max_computes)
            )
E           RuntimeError: Too many computes. Total: 1 > max: 0.

/home/tegn500/Documents/Work/Code/xarray/xarray/tests/__init__.py:118: RuntimeError
```

- [x] Closes #5559
- [x] Tests added
- [x] Passes `pre-commit run --all-files`
- [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst`
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