feat: add read_mask to ListPipelineJobsRequest in aiplatform v1 pipeline_service

google/cloud/aiplatform_v1beta1/__init__.py

@@ -164,6 +164,9 @@
 from .types.featurestore_online_service import ReadFeatureValuesRequest
 from .types.featurestore_online_service import ReadFeatureValuesResponse
 from .types.featurestore_online_service import StreamingReadFeatureValuesRequest
+from .types.featurestore_online_service import WriteFeatureValuesPayload
+from .types.featurestore_online_service import WriteFeatureValuesRequest
+from .types.featurestore_online_service import WriteFeatureValuesResponse
 from .types.featurestore_service import BatchCreateFeaturesOperationMetadata
 from .types.featurestore_service import BatchCreateFeaturesRequest
 from .types.featurestore_service import BatchCreateFeaturesResponse
@@ -1012,6 +1015,9 @@
     "Value",
     "VizierServiceClient",
     "WorkerPoolSpec",
+    "WriteFeatureValuesPayload",
+    "WriteFeatureValuesRequest",
+    "WriteFeatureValuesResponse",
     "WriteTensorboardExperimentDataRequest",
     "WriteTensorboardExperimentDataResponse",
     "WriteTensorboardRunDataRequest",

google/cloud/aiplatform_v1beta1/gapic_metadata.json

@@ -291,6 +291,11 @@
               "methods": [
                 "streaming_read_feature_values"
               ]
+            },
+            "WriteFeatureValues": {
+              "methods": [
+                "write_feature_values"
+              ]
             }
           }
         },
@@ -306,6 +311,11 @@
               "methods": [
                 "streaming_read_feature_values"
               ]
+            },
+            "WriteFeatureValues": {
+              "methods": [
+                "write_feature_values"
+              ]
             }
           }
         }

google/cloud/aiplatform_v1beta1/services/featurestore_online_serving_service/async_client.py

@@ -457,6 +457,129 @@ async def sample_streaming_read_feature_values():
         # Done; return the response.
         return response
 
+    async def write_feature_values(
+        self,
+        request: Union[
+            featurestore_online_service.WriteFeatureValuesRequest, dict
+        ] = None,
+        *,
+        entity_type: str = None,
+        payloads: Sequence[
+            featurestore_online_service.WriteFeatureValuesPayload
+        ] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> featurestore_online_service.WriteFeatureValuesResponse:
+        r"""Writes Feature values of one or more entities of an
+        EntityType.
+        The Feature values are merged into existing entities if
+        any. The Feature values to be written must have
+        timestamp within the online storage retention.
+
+        .. code-block:: python
+
+            from google.cloud import aiplatform_v1beta1
+
+            async def sample_write_feature_values():
+                # Create a client
+                client = aiplatform_v1beta1.FeaturestoreOnlineServingServiceAsyncClient()
+
+                # Initialize request argument(s)
+                payloads = aiplatform_v1beta1.WriteFeatureValuesPayload()
+                payloads.entity_id = "entity_id_value"
+
+                request = aiplatform_v1beta1.WriteFeatureValuesRequest(
+                    entity_type="entity_type_value",
+                    payloads=payloads,
+                )
+
+                # Make the request
+                response = await client.write_feature_values(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesRequest, dict]):
+                The request object. Request message for
+                [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.WriteFeatureValues].
+            entity_type (:class:`str`):
+                Required. The resource name of the EntityType for the
+                entities being written. Value format:
+                ``projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}``.
+                For example, for a machine learning model predicting
+                user clicks on a website, an EntityType ID could be
+                ``user``.
+
+                This corresponds to the ``entity_type`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            payloads (:class:`Sequence[google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesPayload]`):
+                Required. The entities to be written. Up to 100,000
+                feature values can be written across all ``payloads``.
+
+                This corresponds to the ``payloads`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+
+        Returns:
+            google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesResponse:
+                Response message for
+                [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.WriteFeatureValues].
+
+        """
+        # Create or coerce a protobuf request object.
+        # Quick check: If we got a request object, we should *not* have
+        # gotten any keyword arguments that map to the request.
+        has_flattened_params = any([entity_type, payloads])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        request = featurestore_online_service.WriteFeatureValuesRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if entity_type is not None:
+            request.entity_type = entity_type
+        if payloads:
+            request.payloads.extend(payloads)
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = gapic_v1.method_async.wrap_method(
+            self._client._transport.write_feature_values,
+            default_timeout=None,
+            client_info=DEFAULT_CLIENT_INFO,
+        )
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata(
+                (("entity_type", request.entity_type),)
+            ),
+        )
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
     async def list_operations(
         self,
         request: operations_pb2.ListOperationsRequest = None,

google/cloud/aiplatform_v1beta1/services/featurestore_online_serving_service/client.py

@@ -671,6 +671,131 @@ def sample_streaming_read_feature_values():
         # Done; return the response.
         return response
 
+    def write_feature_values(
+        self,
+        request: Union[
+            featurestore_online_service.WriteFeatureValuesRequest, dict
+        ] = None,
+        *,
+        entity_type: str = None,
+        payloads: Sequence[
+            featurestore_online_service.WriteFeatureValuesPayload
+        ] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: float = None,
+        metadata: Sequence[Tuple[str, str]] = (),
+    ) -> featurestore_online_service.WriteFeatureValuesResponse:
+        r"""Writes Feature values of one or more entities of an
+        EntityType.
+        The Feature values are merged into existing entities if
+        any. The Feature values to be written must have
+        timestamp within the online storage retention.
+
+        .. code-block:: python
+
+            from google.cloud import aiplatform_v1beta1
+
+            def sample_write_feature_values():
+                # Create a client
+                client = aiplatform_v1beta1.FeaturestoreOnlineServingServiceClient()
+
+                # Initialize request argument(s)
+                payloads = aiplatform_v1beta1.WriteFeatureValuesPayload()
+                payloads.entity_id = "entity_id_value"
+
+                request = aiplatform_v1beta1.WriteFeatureValuesRequest(
+                    entity_type="entity_type_value",
+                    payloads=payloads,
+                )
+
+                # Make the request
+                response = client.write_feature_values(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesRequest, dict]):
+                The request object. Request message for
+                [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.WriteFeatureValues].
+            entity_type (str):
+                Required. The resource name of the EntityType for the
+                entities being written. Value format:
+                ``projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}``.
+                For example, for a machine learning model predicting
+                user clicks on a website, an EntityType ID could be
+                ``user``.
+
+                This corresponds to the ``entity_type`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            payloads (Sequence[google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesPayload]):
+                Required. The entities to be written. Up to 100,000
+                feature values can be written across all ``payloads``.
+
+                This corresponds to the ``payloads`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, str]]): Strings which should be
+                sent along with the request as metadata.
+
+        Returns:
+            google.cloud.aiplatform_v1beta1.types.WriteFeatureValuesResponse:
+                Response message for
+                [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.WriteFeatureValues].
+
+        """
+        # Create or coerce a protobuf request object.
+        # Quick check: If we got a request object, we should *not* have
+        # gotten any keyword arguments that map to the request.
+        has_flattened_params = any([entity_type, payloads])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # Minor optimization to avoid making a copy if the user passes
+        # in a featurestore_online_service.WriteFeatureValuesRequest.
+        # There's no risk of modifying the input as we've already verified
+        # there are no flattened fields.
+        if not isinstance(
+            request, featurestore_online_service.WriteFeatureValuesRequest
+        ):
+            request = featurestore_online_service.WriteFeatureValuesRequest(request)
+            # If we have keyword arguments corresponding to fields on the
+            # request, apply these.
+            if entity_type is not None:
+                request.entity_type = entity_type
+            if payloads is not None:
+                request.payloads = payloads
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[self._transport.write_feature_values]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata(
+                (("entity_type", request.entity_type),)
+            ),
+        )
+
+        # Send the request.
+        response = rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
     def __enter__(self):
         return self
 

google/cloud/aiplatform_v1beta1/services/featurestore_online_serving_service/transports/base.py

@@ -141,6 +141,11 @@ def _prep_wrapped_messages(self, client_info):
                 default_timeout=5.0,
                 client_info=client_info,
             ),
+            self.write_feature_values: gapic_v1.method.wrap_method(
+                self.write_feature_values,
+                default_timeout=None,
+                client_info=client_info,
+            ),
         }
 
     def close(self):
@@ -176,6 +181,18 @@ def streaming_read_feature_values(
     ]:
         raise NotImplementedError()
 
+    @property
+    def write_feature_values(
+        self,
+    ) -> Callable[
+        [featurestore_online_service.WriteFeatureValuesRequest],
+        Union[
+            featurestore_online_service.WriteFeatureValuesResponse,
+            Awaitable[featurestore_online_service.WriteFeatureValuesResponse],
+        ],
+    ]:
+        raise NotImplementedError()
+
     @property
     def list_operations(
         self,

google/cloud/aiplatform_v1beta1/services/featurestore_online_serving_service/transports/grpc.py

@@ -300,6 +300,39 @@ def streaming_read_feature_values(
             )
         return self._stubs["streaming_read_feature_values"]
 
+    @property
+    def write_feature_values(
+        self,
+    ) -> Callable[
+        [featurestore_online_service.WriteFeatureValuesRequest],
+        featurestore_online_service.WriteFeatureValuesResponse,
+    ]:
+        r"""Return a callable for the write feature values method over gRPC.
+
+        Writes Feature values of one or more entities of an
+        EntityType.
+        The Feature values are merged into existing entities if
+        any. The Feature values to be written must have
+        timestamp within the online storage retention.
+
+        Returns:
+            Callable[[~.WriteFeatureValuesRequest],
+                    ~.WriteFeatureValuesResponse]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "write_feature_values" not in self._stubs:
+            self._stubs["write_feature_values"] = self.grpc_channel.unary_unary(
+                "/google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService/WriteFeatureValues",
+                request_serializer=featurestore_online_service.WriteFeatureValuesRequest.serialize,
+                response_deserializer=featurestore_online_service.WriteFeatureValuesResponse.deserialize,
+            )
+        return self._stubs["write_feature_values"]
+
     def close(self):
         self.grpc_channel.close()