def _create_feature(column, entity, granularity, owner, serving_store,
warehouse_store):
"""Create Feature object.
Args:
column (pandas.Series): data column
entity (str): entity name
granularity (feast.types.Granularity_pb2.Granularity): granularity of
the feature
owner (str): owner of the feature
serving_store (feast.sdk.resources.feature.DataStore): Defaults to None.
Serving store to write the features in this instance to.
warehouse_store (feast.sdk.resources.feature.DataStore): Defaults to None.
Warehouse store to write the features in this instance to.
Returns:
feast.sdk.resources.Feature: feature for this data column
"""
feature = Feature(name=column.name,
entity=entity,
granularity=granularity,
owner=owner,
value_type=dtype_to_value_type(column.dtype))
if serving_store is not None:
feature.serving_store = serving_store
if warehouse_store is not None:
feature.warehouse_store = warehouse_store
return feature
def dummy_feature(self):
my_feature = Feature(name="my_feature",
entity="my_entity",
value_type=ValueType.BYTES,
owner="*****@*****.**",
description="test feature",
uri="github.com/feature_repo")
return my_feature
def test_create_feature(self):
col = pd.Series([1] * 3, dtype='int32', name="test")
expected = Feature(name="test",
entity="test",
owner="person",
value_type=ValueType.INT32)
actual = _create_feature(col, "test", "person", None, None)
assert actual.id == expected.id
assert actual.value_type == expected.value_type
assert actual.owner == expected.owner
def test_apply_single_feature(self, client, mocker):
my_feature = Feature(name="test",
entity="test", granularity=Granularity.NONE)
grpc_stub = core.CoreServiceStub(grpc.insecure_channel(""))
with mocker.patch.object(grpc_stub, 'ApplyFeature',
return_value=CoreServiceTypes.ApplyFeatureResponse(
featureId="test.none.test")):
client._core_service_stub = grpc_stub
id = client.apply(my_feature)
assert id == "test.none.test"
def dummy_feature(self):
warehouse_data_store = Datastore(id="BIGQUERY1", options={})
serving_data_store = Datastore(id="REDIS1", options={})
my_feature = Feature(name="my_feature",
entity="my_entity",
value_type=ValueType.BYTES,
owner="*****@*****.**",
description="test feature",
uri="github.com/feature_repo",
warehouse_store=warehouse_data_store,
serving_store=serving_data_store)
return my_feature
def test_create_feature_with_stores(self):
col = pd.Series([1] * 3, dtype='int32', name="test")
expected = Feature(name="test",
entity="test",
owner="person",
value_type=ValueType.INT32,
serving_store=Datastore(id="SERVING"),
warehouse_store=Datastore(id="WAREHOUSE"))
actual = _create_feature(col, "test", "person",
Datastore(id="SERVING"),
Datastore(id="WAREHOUSE"))
assert actual.id == expected.id
assert actual.value_type == expected.value_type
assert actual.owner == expected.owner
assert actual.serving_store == expected.serving_store
assert actual.warehouse_store == expected.warehouse_store