def test_update_parameters_flattened():
client = CloudMemcacheClient(credentials=credentials.AnonymousCredentials())
# Mock the actual call within the gRPC stub, and fake the request.
with mock.patch.object(
type(client._transport.update_parameters), "__call__"
) as call:
# Designate an appropriate return value for the call.
call.return_value = operations_pb2.Operation(name="operations/op")
# Call the method with a truthy value for each flattened field,
# using the keyword arguments to the method.
response = client.update_parameters(
name="name_value",
update_mask=field_mask.FieldMask(paths=["paths_value"]),
parameters=cloud_memcache.MemcacheParameters(id="id_value"),
)
# Establish that the underlying call was made with the expected
# request object values.
assert len(call.mock_calls) == 1
_, args, _ = call.mock_calls[0]
assert args[0].name == "name_value"
assert args[0].update_mask == field_mask.FieldMask(paths=["paths_value"])
assert args[0].parameters == cloud_memcache.MemcacheParameters(id="id_value")
def update_parameters(
self,
update_mask: Union[Dict, FieldMask],
parameters: Union[Dict, cloud_memcache.MemcacheParameters],
project_id: str,
location: str,
instance_id: str,
retry: Optional[Retry] = None,
timeout: Optional[float] = None,
metadata: Sequence[Tuple[str, str]] = (),
):
"""
Updates the defined Memcached Parameters for an existing Instance. This method only stages the
parameters, it must be followed by apply_parameters to apply the parameters to nodes of
the Memcached Instance.
:param update_mask: Required. Mask of fields to update.
If a dict is provided, it must be of the same form as the protobuf message
:class:`~google.protobuf.field_mask_pb2.FieldMask`
Union[Dict, google.protobuf.field_mask_pb2.FieldMask]
:param parameters: The parameters to apply to the instance.
If a dict is provided, it must be of the same form as the protobuf message
:class:`~google.cloud.memcache_v1beta2.types.cloud_memcache.MemcacheParameters`
:param location: The location of the Cloud Memorystore instance (for example europe-west1)
:param instance_id: The logical name of the Memcached instance in the customer project.
:param project_id: Project ID of the project that contains the instance. If set
to None or missing, the default project_id from the Google Cloud connection is used.
:param retry: A retry object used to retry requests. If ``None`` is specified, requests will not be
retried.
:param timeout: The amount of time, in seconds, to wait for the request to complete. Note that if
``retry`` is specified, the timeout applies to each individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_conn()
metadata = metadata or ()
if isinstance(parameters, dict):
parameters = cloud_memcache.MemcacheParameters(parameters)
elif not isinstance(parameters, cloud_memcache.MemcacheParameters):
raise AirflowException(
"instance is not instance of MemcacheParameters type or python dict"
)
name = CloudMemcacheClient.instance_path(project_id, location,
instance_id)
self.log.info("Staging update to instance: %s", instance_id)
result = client.update_parameters(
name=name,
update_mask=update_mask,
parameters=parameters,
retry=retry,
timeout=timeout,
metadata=metadata,
)
result.result()
self.log.info("Update staged for instance: %s", instance_id)
def test_update_parameters_flattened_error():
client = CloudMemcacheClient(credentials=credentials.AnonymousCredentials())
# Attempting to call a method with both a request object and flattened
# fields is an error.
with pytest.raises(ValueError):
client.update_parameters(
cloud_memcache.UpdateParametersRequest(),
name="name_value",
update_mask=field_mask.FieldMask(paths=["paths_value"]),
parameters=cloud_memcache.MemcacheParameters(id="id_value"),
)
