chore: add Feature creation

PiperOrigin-RevId: 635593604

tests/unit/vertexai/test_feature_group.py

@@ -60,6 +60,7 @@
     _TEST_FG3_ENTITY_ID_COLUMNS,
     _TEST_FG3_LABELS,
     _TEST_FG_LIST,
+    _TEST_FG1_F1,
     _TEST_FG1_F1_ID,
     _TEST_FG1_F1_PATH,
     _TEST_FG1_F1_DESCRIPTION,
@@ -125,6 +126,18 @@ def delete_fg_mock():
         yield delete_fg_mock
 
 
+@pytest.fixture
+def create_feature_mock():
+    with patch.object(
+        feature_registry_service_client.FeatureRegistryServiceClient,
+        "create_feature",
+    ) as create_feature_mock:
+        create_feature_lro_mock = mock.Mock(ga_operation.Operation)
+        create_feature_lro_mock.result.return_value = _TEST_FG1_F1
+        create_feature_mock.return_value = create_feature_lro_mock
+        yield create_feature_mock
+
+
 def fg_eq(
     fg_to_check: FeatureGroup,
     name: str,
@@ -363,3 +376,69 @@ def test_get_feature(get_fg_mock, get_feature_mock):
         labels=_TEST_FG1_F1_LABELS,
         point_of_contact=_TEST_FG1_F1_POINT_OF_CONTACT,
     )
+
+
+@pytest.mark.parametrize("create_request_timeout", [None, 1.0])
+@pytest.mark.parametrize("sync", [True, False])
+def test_create_feature(
+    get_fg_mock,
+    create_feature_mock,
+    get_feature_mock,
+    fg_logger_mock,
+    create_request_timeout,
+    sync,
+):
+    aiplatform.init(project=_TEST_PROJECT, location=_TEST_LOCATION)
+
+    fg = FeatureGroup(_TEST_FG1_ID)
+    feature = fg.create_feature(
+        _TEST_FG1_F1_ID,
+        description=_TEST_FG1_F1_DESCRIPTION,
+        labels=_TEST_FG1_F1_LABELS,
+        point_of_contact=_TEST_FG1_F1_POINT_OF_CONTACT,
+        create_request_timeout=create_request_timeout,
+        sync=sync,
+    )
+
+    if not sync:
+        feature.wait()
+
+    expected_feature = types.feature.Feature(
+        description=_TEST_FG1_F1_DESCRIPTION,
+        labels=_TEST_FG1_F1_LABELS,
+        point_of_contact=_TEST_FG1_F1_POINT_OF_CONTACT,
+    )
+    create_feature_mock.assert_called_once_with(
+        parent=_TEST_FG1_PATH,
+        feature=expected_feature,
+        feature_id=_TEST_FG1_F1_ID,
+        metadata=(),
+        timeout=create_request_timeout,
+    )
+
+    feature_eq(
+        feature,
+        name=_TEST_FG1_F1_ID,
+        resource_name=_TEST_FG1_F1_PATH,
+        project=_TEST_PROJECT,
+        location=_TEST_LOCATION,
+        description=_TEST_FG1_F1_DESCRIPTION,
+        labels=_TEST_FG1_F1_LABELS,
+        point_of_contact=_TEST_FG1_F1_POINT_OF_CONTACT,
+    )
+
+    fg_logger_mock.assert_has_calls(
+        [
+            call("Creating Feature"),
+            call(
+                f"Create Feature backing LRO: {create_feature_mock.return_value.operation.name}"
+            ),
+            call(
+                "Feature created. Resource name: projects/test-project/locations/us-central1/featureGroups/my_fg1/features/my_fg1_f1"
+            ),
+            call("To use this Feature in another session:"),
+            call(
+                "feature = aiplatform.Feature('projects/test-project/locations/us-central1/featureGroups/my_fg1/features/my_fg1_f1')"
+            ),
+        ]
+    )

vertexai/resources/preview/feature_store/feature_group.py

@@ -26,6 +26,7 @@
 from google.cloud.aiplatform import base, initializer
 from google.cloud.aiplatform import utils
 from google.cloud.aiplatform.compat.types import (
+    feature as gca_feature,
     feature_group as gca_feature_group,
     io as gca_io,
 )
@@ -252,6 +253,111 @@ def get_feature(self, feature_id: str) -> Feature:
         """
         return Feature(f"{self.resource_name}/features/{feature_id}")
 
+    def create_feature(
+        self,
+        name: str,
+        version_column_name: Optional[str] = None,
+        description: Optional[str] = None,
+        labels: Optional[Dict[str, str]] = None,
+        point_of_contact: Optional[str] = None,
+        project: Optional[str] = None,
+        location: Optional[str] = None,
+        credentials: Optional[auth_credentials.Credentials] = None,
+        request_metadata: Optional[Sequence[Tuple[str, str]]] = None,
+        create_request_timeout: Optional[float] = None,
+        sync: bool = True,
+    ) -> Feature:
+        """Creates a new feature.
+
+        Args:
+            name: The name of the feature.
+            version_column_name:
+                The name of the BigQuery Table/View column hosting data for this
+                version. If no value is provided, will use feature_id.
+            description: Description of the feature.
+            labels:
+                The labels with user-defined metadata to organize your Features.
+                Label keys and values can be no longer than 64 characters
+                (Unicode codepoints), can only contain lowercase letters,
+                numeric characters, underscores and dashes. International
+                characters are allowed.
+
+                See https://goo.gl/xmQnxf for more information on and examples
+                of labels. No more than 64 user labels can be associated with
+                one Feature (System labels are excluded)." System reserved label
+                keys are prefixed with "aiplatform.googleapis.com/" and are
+                immutable.
+            point_of_contact:
+                Entity responsible for maintaining this feature. Can be comma
+                separated list of email addresses or URIs.
+            project:
+                Project to create feature in. If unset, the project set in
+                aiplatform.init will be used.
+            location:
+                Location to create feature in. If not set, location set in
+                aiplatform.init will be used.
+            credentials:
+                Custom credentials to use to create this feature. Overrides
+                credentials set in aiplatform.init.
+            request_metadata:
+                Strings which should be sent along with the request as metadata.
+            create_request_timeout:
+                The timeout for the create request in seconds.
+            sync:
+                Whether to execute this creation synchronously. If False, this
+                method will be executed in concurrent Future and any downstream
+                object will be immediately returned and synced when the Future
+                has completed.
+
+        Returns:
+            Feature - the Feature resource object.
+        """
+
+        gapic_feature = gca_feature.Feature()
+
+        if version_column_name:
+            gapic_feature.version_column_name = version_column_name
+
+        if description:
+            gapic_feature.description = description
+
+        if labels:
+            utils.validate_labels(labels)
+            gapic_feature.labels = labels
+
+        if point_of_contact:
+            gapic_feature.point_of_contact = point_of_contact
+
+        if request_metadata is None:
+            request_metadata = ()
+
+        api_client = self.__class__._instantiate_client(
+            location=location, credentials=credentials
+        )
+
+        create_feature_lro = api_client.create_feature(
+            parent=self.resource_name,
+            feature=gapic_feature,
+            feature_id=name,
+            metadata=request_metadata,
+            timeout=create_request_timeout,
+        )
+
+        _LOGGER.log_create_with_lro(Feature, create_feature_lro)
+
+        created_feature = create_feature_lro.result()
+
+        _LOGGER.log_create_complete(Feature, created_feature, "feature")
+
+        feature_obj = Feature(
+            name=created_feature.name,
+            project=project,
+            location=location,
+            credentials=credentials,
+        )
+
+        return feature_obj
+
     @property
     def source(self) -> FeatureGroupBigQuerySource:
         return FeatureGroupBigQuerySource(