Squashed commit of the following:

commit bc39877
Merge: 507b1f6 278d2e6
Author: dcherian <[email protected]>
Date:   Tue Oct 29 09:36:30 2019 -0600

    Merge remote-tracking branch 'upstream/master' into dask-tokenize

    * upstream/master:
      upgrade black verison to 19.10b0 (pydata#3456)
      Remove outdated code related to compatibility with netcdftime (pydata#3450)
      Remove deprecated behavior from dataset.drop docstring (pydata#3451)
      jupyterlab dark theme (pydata#3443)
      Drop groups associated with nans in group variable (pydata#3406)
      Allow ellipsis (...) in transpose (pydata#3421)
      Another groupby.reduce bugfix. (pydata#3403)
      add icomoon license (pydata#3448)
      change ALL_DIMS to equal ellipsis (pydata#3418)
      Escaping dtypes (pydata#3444)
      Html repr (pydata#3425)

commit 507b1f6
Author: dcherian <[email protected]>
Date:   Tue Oct 29 09:34:47 2019 -0600

    Fix window test

commit 4ab6a66
Author: dcherian <[email protected]>
Date:   Thu Oct 24 14:30:57 2019 -0600

    Implement __dask_tokenize__

doc/whats-new.rst

@@ -94,6 +94,8 @@ Internal Changes
 
 - Use Python 3.6 idioms throughout the codebase. (:pull:3419)
   By `Maximilian Roos <https://github.com/max-sixty>`_
+- Implement :py:func:`__dask_tokenize__` for xarray objects.
+  By `Deepak Cherian <https://github.com/dcherian>`_ and `Guido Imperiale <https://github.com/crusaderky>`_.
 
 .. _whats-new.0.14.0:
 

xarray/core/dataarray.py

@@ -754,6 +754,9 @@ def reset_coords(
             dataset[self.name] = self.variable
             return dataset
 
+    def __dask_tokenize__(self):
+        return (DataArray, self._variable, self._coords, self._name)
+
     def __dask_graph__(self):
         return self._to_temp_dataset().__dask_graph__()
 

xarray/core/dataset.py

@@ -649,6 +649,9 @@ def load(self, **kwargs) -> "Dataset":
 
         return self
 
+    def __dask_tokenize__(self):
+        return (Dataset, self._variables, self._coord_names, self._attrs)
+
     def __dask_graph__(self):
         graphs = {k: v.__dask_graph__() for k, v in self.variables.items()}
         graphs = {k: v for k, v in graphs.items() if v is not None}

xarray/core/variable.py

@@ -390,6 +390,9 @@ def compute(self, **kwargs):
         new = self.copy(deep=False)
         return new.load(**kwargs)
 
+    def __dask_tokenize__(self):
+        return Variable, self._dims, self.data, self._attrs
+
     def __dask_graph__(self):
         if isinstance(self._data, dask_array_type):
             return self._data.__dask_graph__()
@@ -1967,6 +1970,9 @@ def __init__(self, dims, data, attrs=None, encoding=None, fastpath=False):
         if not isinstance(self._data, PandasIndexAdapter):
             self._data = PandasIndexAdapter(self._data)
 
+    def __dask_tokenize__(self):
+        return (IndexVariable, self._dims, self._data.array, self._attrs)
+
     def load(self):
         # data is already loaded into memory for IndexVariable
         return self

xarray/tests/test_dask.py

@@ -1,5 +1,6 @@
 import operator
 import pickle
+import sys
 from contextlib import suppress
 from distutils.version import LooseVersion
 from textwrap import dedent
@@ -23,11 +24,14 @@
     raises_regex,
 )
 from ..core.duck_array_ops import lazy_array_equiv
+from .test_backends import create_tmp_file
 
 dask = pytest.importorskip("dask")
 da = pytest.importorskip("dask.array")
 dd = pytest.importorskip("dask.dataframe")
 
+ON_WINDOWS = sys.platform == "win32"
+
 
 class CountingScheduler:
     """ Simple dask scheduler counting the number of computes.
@@ -1221,3 +1225,57 @@ def test_lazy_array_equiv():
             "no_conflicts",
         ]:
             xr.merge([lons1, lons2], compat=compat)
+
+
+@pytest.mark.parametrize("obj", [make_da(), make_ds()])
+@pytest.mark.parametrize(
+    "transform",
+    [
+        lambda x: x.reset_coords(),
+        lambda x: x.reset_coords(drop=True),
+        lambda x: x.isel(x=1),
+        lambda x: x.attrs.update(new_attrs=1),
+        lambda x: x.assign_coords(cxy=1),
+        lambda x: x.rename({"x": "xnew"}),
+        lambda x: x.rename({"cxy": "cxynew"}),
+    ],
+)
+def test_normalize_token_not_identical(obj, transform):
+    with raise_if_dask_computes():
+        assert not dask.base.tokenize(obj) == dask.base.tokenize(transform(obj))
+    assert not dask.base.tokenize(obj.compute()) == dask.base.tokenize(
+        transform(obj.compute())
+    )
+
+
+@pytest.mark.parametrize("transform", [lambda x: x, lambda x: x.compute()])
+def test_normalize_differently_when_data_changes(transform):
+    obj = transform(make_ds())
+    new = obj.copy(deep=True)
+    new["a"] *= 2
+    with raise_if_dask_computes():
+        assert not dask.base.tokenize(obj) == dask.base.tokenize(new)
+
+    obj = transform(make_da())
+    new = obj.copy(deep=True)
+    new *= 2
+    with raise_if_dask_computes():
+        assert not dask.base.tokenize(obj) == dask.base.tokenize(new)
+
+
+@pytest.mark.parametrize(
+    "transform", [lambda x: x, lambda x: x.copy(), lambda x: x.copy(deep=True)]
+)
+@pytest.mark.parametrize(
+    "obj", [make_da(), make_ds(), make_da().indexes["x"], make_ds().variables["a"]]
+)
+def test_normalize_token_identical(obj, transform):
+    with raise_if_dask_computes():
+        assert dask.base.tokenize(obj) == dask.base.tokenize(transform(obj))
+
+
+def test_normalize_token_netcdf_backend(map_ds):
+    with create_tmp_file(allow_cleanup_failure=ON_WINDOWS) as tmp_file:
+        map_ds.to_netcdf(tmp_file)
+        read = xr.open_dataset(tmp_file)
+        assert not dask.base.tokenize(map_ds) == dask.base.tokenize(read)

xarray/tests/test_sparse.py

@@ -22,6 +22,7 @@
     )
 
 sparse = pytest.importorskip("sparse")
+dask = pytest.importorskip("dask")
 
 
 def assert_sparse_equal(a, b):
@@ -849,3 +850,14 @@ def test_chunk():
     dsc = ds.chunk(2)
     assert dsc.chunks == {"dim_0": (2, 2)}
     assert_identical(dsc, ds)
+
+
+def test_normalize_token():
+    s = sparse.COO.from_numpy(np.array([0, 0, 1, 2]))
+    a = DataArray(s)
+    dask.base.tokenize(a)
+    assert isinstance(a.data, sparse.COO)
+
+    ac = a.chunk(2)
+    dask.base.tokenize(ac)
+    assert isinstance(ac.data._meta, sparse.COO)