Adjust type of ChemicalFormulaFeaturizer.powers.

The backend is opening up the type of powers to be floats. As such, this
commit will deserialize powers as a list of floats. However, to preserve
backwards compatability, the type of powers will be preserved, and a
new field (powers_float) with the list as floats is introduced. In
v4.0.0, the type of 'powers' will be changed, and 'powers_float' will be
deprecated before its removal in v5.0.0.

src/citrine/__version__.py

@@ -1 +1 @@
-__version__ = "3.5.4"
+__version__ = "3.6.0"

src/citrine/informatics/predictors/chemical_formula_featurizer.py

@@ -1,4 +1,5 @@
-from typing import List, Optional
+from typing import List, Optional, Union
+from warnings import warn
 
 from citrine._rest.resource import Resource
 from citrine._serialization import properties
@@ -133,7 +134,7 @@ class ChemicalFormulaFeaturizer(Resource["ChemicalFormulaFeaturizer"], Predictor
     input_descriptor = properties.Object(ChemicalFormulaDescriptor, 'input')
     features = properties.List(properties.String, 'features')
     excludes = properties.List(properties.String, 'excludes', default=[])
-    powers = properties.List(properties.Integer, 'powers')
+    _powers = properties.List(properties.Float, 'powers')
 
     typ = properties.String('type', default='ChemicalFormulaFeaturizer', deserializable=False)
 
@@ -152,5 +153,23 @@ def __init__(self,
         self.excludes = excludes if excludes is not None else []
         self.powers = powers if powers is not None else [1]
 
+    @property
+    def powers(self) -> List[int]:
+        """The list of powers when computing generalized weighted means of element properties."""
+        warn("The type of 'powers' will change to a list of floats in v4.0.0. To retrieve them as "
+             "floats now, use 'powers_float'.")
+        return [int(p) for p in self._powers]
+
+    @powers.setter
+    def powers(self, value: List[Union[int, float]]):
+        self._powers = value
+
+    @property
+    def powers_float(self) -> List[float]:
+        """Powers when computing generalized weighted means of element properties."""
+        warn("'powers_float' will be deprecated in v4.0.0 for 'powers', and removed in v5.0.0",
+             PendingDeprecationWarning)
+        return self._powers
+
     def __str__(self):
         return '<ChemicalFormulaFeaturizer {!r}>'.format(self.name)

tests/informatics/test_predictors.py

@@ -259,7 +259,10 @@ def test_chemical_featurizer(chemical_featurizer):
     assert chemical_featurizer.input_descriptor == ChemicalFormulaDescriptor("formula")
     assert chemical_featurizer.features == ["standard"]
     assert chemical_featurizer.excludes == []
-    assert chemical_featurizer.powers == [1, 2]
+    with pytest.warns(UserWarning):
+        assert chemical_featurizer.powers == [1, 2]
+    with pytest.warns(PendingDeprecationWarning):
+        assert chemical_featurizer.powers_float == [1.0, 2.0]
 
     assert str(chemical_featurizer) == "<ChemicalFormulaFeaturizer 'Chemical featurizer'>"