feat: Add endpoind_id arg to Endpoint#create

google/cloud/aiplatform/models.py

@@ -198,6 +198,7 @@ def network(self) -> Optional[str]:
     def create(
         cls,
         display_name: Optional[str] = None,
+        endpoint_id: Optional[str] = None,
         description: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
         metadata: Optional[Sequence[Tuple[str, str]]] = (),
@@ -215,6 +216,17 @@ def create(
                 Optional. The user-defined name of the Endpoint.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
+            endpoint_id (str):
+                Optional. The ID to use for endpoint, which will become
+                the final component of the endpoint resource name. If
+                not provided, Vertex AI will generate a value for this
+                ID.
+
+                This value should be 1-10 characters, and valid
+                characters are /[0-9]/. When using HTTP/JSON, this field
+                is populated based on a query string argument, such as
+                ``?endpoint_id=12345``. This is the fallback for fields
+                that are not included in either the URI or the body.
             project (str):
                 Required. Project to retrieve endpoint from. If not set, project
                 set in aiplatform.init will be used.
@@ -276,6 +288,7 @@ def create(
         return cls._create(
             api_client=api_client,
             display_name=display_name,
+            endpoint_id=endpoint_id,
             project=project,
             location=location,
             description=description,
@@ -297,6 +310,7 @@ def _create(
         display_name: str,
         project: str,
         location: str,
+        endpoint_id: Optional[str] = None,
         description: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
         metadata: Optional[Sequence[Tuple[str, str]]] = (),
@@ -321,6 +335,17 @@ def _create(
             location (str):
                 Required. Location to retrieve endpoint from. If not set, location
                 set in aiplatform.init will be used.
+            endpoint_id (str):
+                Optional. The ID to use for endpoint, which will become
+                the final component of the endpoint resource name. If
+                not provided, Vertex AI will generate a value for this
+                ID.
+
+                This value should be 1-10 characters, and valid
+                characters are /[0-9]/. When using HTTP/JSON, this field
+                is populated based on a query string argument, such as
+                ``?endpoint_id=12345``. This is the fallback for fields
+                that are not included in either the URI or the body.
             description (str):
                 Optional. The description of the Endpoint.
             labels (Dict[str, str]):
@@ -368,6 +393,7 @@ def _create(
         operation_future = api_client.create_endpoint(
             parent=parent,
             endpoint=gapic_endpoint,
+            endpoint_id=endpoint_id,
             metadata=metadata,
             timeout=create_request_timeout,
         )

tests/unit/aiplatform/test_endpoints.py

@@ -547,6 +547,7 @@ def test_init_aiplatform_with_encryption_key_name_and_create_endpoint(
         create_endpoint_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             endpoint=expected_endpoint,
+            endpoint_id=None,
             metadata=(),
             timeout=None,
         )
@@ -573,13 +574,39 @@ def test_create(self, create_endpoint_mock, sync):
         create_endpoint_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             endpoint=expected_endpoint,
+            endpoint_id=None,
             metadata=(),
             timeout=None,
         )
 
         expected_endpoint.name = _TEST_ENDPOINT_NAME
         assert my_endpoint._gca_resource == expected_endpoint
 
+    @pytest.mark.usefixtures("get_endpoint_mock")
+    @pytest.mark.parametrize("sync", [True, False])
+    def test_create_with_endpoint_id(self, create_endpoint_mock, sync):
+        my_endpoint = models.Endpoint.create(
+            display_name=_TEST_DISPLAY_NAME,
+            endpoint_id=_TEST_ID,
+            description=_TEST_DESCRIPTION,
+            sync=sync,
+            create_request_timeout=None,
+        )
+        if not sync:
+            my_endpoint.wait()
+
+        expected_endpoint = gca_endpoint.Endpoint(
+            display_name=_TEST_DISPLAY_NAME,
+            description=_TEST_DESCRIPTION,
+        )
+        create_endpoint_mock.assert_called_once_with(
+            parent=_TEST_PARENT,
+            endpoint=expected_endpoint,
+            endpoint_id=_TEST_ID,
+            metadata=(),
+            timeout=None,
+        )
+
     @pytest.mark.usefixtures("get_endpoint_mock")
     @pytest.mark.parametrize("sync", [True, False])
     def test_create_with_timeout(self, create_endpoint_mock, sync):
@@ -599,6 +626,7 @@ def test_create_with_timeout(self, create_endpoint_mock, sync):
         create_endpoint_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             endpoint=expected_endpoint,
+            endpoint_id=None,
             metadata=(),
             timeout=180.0,
         )
@@ -642,6 +670,7 @@ def test_create_with_description(self, create_endpoint_mock, sync):
         create_endpoint_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             endpoint=expected_endpoint,
+            endpoint_id=None,
             metadata=(),
             timeout=None,
         )
@@ -665,6 +694,7 @@ def test_create_with_labels(self, create_endpoint_mock, sync):
         create_endpoint_mock.assert_called_once_with(
             parent=_TEST_PARENT,
             endpoint=expected_endpoint,
+            endpoint_id=None,
             metadata=(),
             timeout=None,
         )