def put_actions(
self,
dataset_arn: "capo_personalize_events.types.arn.Arn",
actions: "capo_personalize_events.types.action_list.ActionList",
*,
config_overrides: Optional[PersonalizeEventsClientConfig] = None,
) -> None:
"""<p>Adds one or more actions to an Actions dataset. For more information see <a href="https://docs.aws.amazon.com/personalize/latest/dg/importing-actions.html">Importing actions individually</a>. </p>
Args:
dataset_arn: <p>The Amazon Resource Name (ARN) of the Actions dataset you are adding the action or actions to.</p>
actions: <p>A list of action data.</p>
Raises:
capo_personalize_events.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
capo_personalize_events.errors.resource_in_use_exception.ResourceInUseException: <p>The specified resource is in use.</p>
capo_personalize_events.errors.resource_not_found_exception.ResourceNotFoundException: <p>Could not find the specified resource.</p>
capo_personalize_events.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_personalize_events.types.put_actions_request.PutActionsRequest]",
) -> OperationResponse[None]:
import capo_personalize_events._operations.amazon_personalize_events.put_actions
output, http_response = (
capo_personalize_events._operations.amazon_personalize_events.put_actions.put_actions(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
def _redact_input(
input_: "capo_personalize_events.types.put_actions_request.PutActionsRequest",
) -> dict[str, Any]:
import capo_personalize_events.types.put_actions_request
return capo_personalize_events.types.put_actions_request.redact_sensitive(
input_
)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("PutActions", redact_input=_redact_input)
)
input_: capo_personalize_events.types.put_actions_request.PutActionsRequest = {
"dataset_arn": dataset_arn,
"actions": actions,
}
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output