Deprecate allow_lazy

doc/whats-new.rst

@@ -81,6 +81,9 @@ Bug fixes
   By `Deepak Cherian <https://github.com/dcherian>`_.
 - Sync with cftime by removing `dayofwk=-1` for cftime>=1.0.4.
   By `Anderson Banihirwe <https://github.com/andersy005>`_.
+- Rolling reduction operations now longer compute dask arrays by default. (:issue:3161).
+  In addition, the ``allow_lazy`` kwarg to ``reduce`` is deprecated.
+  By `Deepak Cherian <https://github.com/dcherian>`_.
 - Fix :py:meth:`xarray.core.groupby.DataArrayGroupBy.reduce` and
   :py:meth:`xarray.core.groupby.DatasetGroupBy.reduce` when reducing over multiple dimensions.
   (:issue:`3402`). By `Deepak Cherian <https://github.com/dcherian/>`_

xarray/core/common.py

@@ -43,14 +43,12 @@ def _reduce_method(cls, func: Callable, include_skipna: bool, numeric_only: bool
         if include_skipna:
 
             def wrapped_func(self, dim=None, axis=None, skipna=None, **kwargs):
-                return self.reduce(
-                    func, dim, axis, skipna=skipna, allow_lazy=True, **kwargs
-                )
+                return self.reduce(func, dim, axis, skipna=skipna, **kwargs)
 
         else:
 
             def wrapped_func(self, dim=None, axis=None, **kwargs):  # type: ignore
-                return self.reduce(func, dim, axis, allow_lazy=True, **kwargs)
+                return self.reduce(func, dim, axis, **kwargs)
 
         return wrapped_func
 
@@ -83,20 +81,13 @@ def _reduce_method(cls, func: Callable, include_skipna: bool, numeric_only: bool
 
             def wrapped_func(self, dim=None, skipna=None, **kwargs):
                 return self.reduce(
-                    func,
-                    dim,
-                    skipna=skipna,
-                    numeric_only=numeric_only,
-                    allow_lazy=True,
-                    **kwargs,
+                    func, dim, skipna=skipna, numeric_only=numeric_only, **kwargs
                 )
 
         else:
 
             def wrapped_func(self, dim=None, **kwargs):  # type: ignore
-                return self.reduce(
-                    func, dim, numeric_only=numeric_only, allow_lazy=True, **kwargs
-                )
+                return self.reduce(func, dim, numeric_only=numeric_only, **kwargs)
 
         return wrapped_func
 

xarray/core/dataset.py

@@ -4022,7 +4022,7 @@ def reduce(
         keep_attrs: bool = None,
         keepdims: bool = False,
         numeric_only: bool = False,
-        allow_lazy: bool = False,
+        allow_lazy: bool = None,
         **kwargs: Any,
     ) -> "Dataset":
         """Reduce this dataset by applying `func` along some dimension(s).

xarray/core/groupby.py

@@ -585,9 +585,7 @@ def _first_or_last(self, op, skipna, keep_attrs):
             return self._obj
         if keep_attrs is None:
             keep_attrs = _get_keep_attrs(default=True)
-        return self.reduce(
-            op, self._group_dim, skipna=skipna, keep_attrs=keep_attrs, allow_lazy=True
-        )
+        return self.reduce(op, self._group_dim, skipna=skipna, keep_attrs=keep_attrs)
 
     def first(self, skipna=None, keep_attrs=None):
         """Return the first element of each group along the group dimension

xarray/core/variable.py

@@ -1,5 +1,6 @@
 import functools
 import itertools
+import warnings
 from collections import defaultdict
 from datetime import timedelta
 from distutils.version import LooseVersion
@@ -1425,7 +1426,7 @@ def reduce(
         axis=None,
         keep_attrs=None,
         keepdims=False,
-        allow_lazy=False,
+        allow_lazy=None,
         **kwargs,
     ):
         """Reduce this array by applying `func` along some dimension(s).
@@ -1466,7 +1467,17 @@ def reduce(
 
         if dim is not None:
             axis = self.get_axis_num(dim)
+
+        if allow_lazy is not None:
+            warnings.warn(
+                "allow_lazy will be deprecated in version 0.16.0. It is now True by default.",
+                DeprecationWarning,
+            )
+        else:
+            allow_lazy = True
+
         input_data = self.data if allow_lazy else self.values
+
         if axis is not None:
             data = func(input_data, axis=axis, **kwargs)
         else:

xarray/tests/test_dask.py

@@ -217,6 +217,8 @@ def test_reduce(self):
         self.assertLazyAndAllClose((u < 1).all("x"), (v < 1).all("x"))
         with raises_regex(NotImplementedError, "dask"):
             v.median()
+        with raise_if_dask_computes():
+            v.reduce(np.mean)
 
     def test_missing_values(self):
         values = np.array([0, 1, np.nan, 3])
@@ -488,7 +490,17 @@ def test_groupby(self):
         v = self.lazy_array
 
         expected = u.groupby("x").mean(...)
-        actual = v.groupby("x").mean(...)
+        with raise_if_dask_computes():
+            actual = v.groupby("x").mean(...)
+        self.assertLazyAndAllClose(expected, actual)
+
+    def test_rolling(self):
+        u = self.eager_array
+        v = self.lazy_array
+
+        expected = u.rolling(x=2).mean()
+        with raise_if_dask_computes():
+            actual = v.rolling(x=2).mean()
         self.assertLazyAndAllClose(expected, actual)
 
     def test_groupby_first(self):
@@ -500,7 +512,8 @@ def test_groupby_first(self):
         with raises_regex(NotImplementedError, "dask"):
             v.groupby("ab").first()
         expected = u.groupby("ab").first()
-        actual = v.groupby("ab").first(skipna=False)
+        with raise_if_dask_computes():
+            actual = v.groupby("ab").first(skipna=False)
         self.assertLazyAndAllClose(expected, actual)
 
     def test_reindex(self):

xarray/tests/test_variable.py

@@ -1477,6 +1477,10 @@ def test_reduce(self):
 
         with raises_regex(ValueError, "cannot supply both"):
             v.mean(dim="x", axis=0)
+        with pytest.warns(DeprecationWarning, match="allow_lazy will be deprecated"):
+            v.mean("x", allow_lazy=True)
+        with pytest.warns(DeprecationWarning, match="allow_lazy will be deprecated"):
+            v.mean("x", allow_lazy=False)
 
     def test_quantile(self):
         v = Variable(["x", "y"], self.d)