Status Functions

A Status Function is a user-defined Python function used to enable and manage the exchange of simulation observations between the Engines involved in the simulation, and a Python script (referred to in the following as the Master Script) that controls an NRP Core experiment (using the NRP Core Python Client). A diagram showing the data exchange flows in this case can be found here.

The Status Function can be used with the run_until_timeout() call available in the Python client, in which case it allows to work with episodic simulations and to generate trajectories that consist of observations from multiple timesteps. It can also be used together with the run_loop(1) call, where the simulation is executed step-by-step, and the observations are returned continuously. In the case of running the simulation using the former, the Status Function provides a mechanism (the done flag) of signaling the end of an episode and giving the control back to the Master Script.

Status Function definition

A Status Function is quite similar to the Transceiver Functions used by NRP Core. However, there is one important difference between the two insofar as the Status Function is not assigned to any particular engine. As such, the status function is called on every Simulation Timestep of NRP-core instead of an Engine Timestep. Furthermore, there may also be only one Status Function defined per simulation.

To define a Status Function, one decorates a regular Python function with a special decorator, which is provided by NRP Core Python modules:

from nrp_core import *

def status_function(client_data):

Input arguments

The Status Function can accept DataPacks from both engines and preprocessing functions as arguments. Defining these extra parameters is done in the same way as in the Transceiver Functions - by using proper decorators and adding the keywords as parameters to the function definition.

@EngineDataPack(keyword1, id1)        # DataPack coming directly from an engine
@PreprocessedDataPack(keyword2, id2)  # DataPack coming from a Preprocessing Function
def status_function(keyword1, keyword2):

Return values

Status Function returns observations, that may be accumulated by NRP Core and form trajectories. Observations are stored in RawData objects, that are very similar to DataPacks. The main difference is that RawData objects don’t require any identifiers - they aren’t assigned to any particular engine, and they don’t have a name themselves. The RawData classes are generated automatically, and there’s one RawData class corresponding to each DataPack class. For example, the JsonRawData Python class corresponds to JsonDataPack Python class. They are both available in the same Python module. The data of RawData objects can be accessed in the same way as in the corresponding DataPack class.

Observations are returned from the Status Function on every iteration, but they are not always sent back to the Master Script immediately. They can be stored internally by NRP Core and sent back only when arbitrary simulation conditions are met - for example a predefined number of iterations has passed, or an agent has reached a certain position in the simulation world. These conditions should be evaluated inside of the Status Function, and a boolean flag with the result of this evaluation should be returned. The flag is called the done flag. If it’s set to True, the simulation will be stopped, the control will return to the Master Script, together with all observations stored in the trajectory buffer of the NRP Core (including the observations from the current iteration). If the flag is set to False, then the observations from the current iteration will be appended to the trajectory buffer of the NRP Core. Multiple RawData objects can be returned in each iteration. The order of observations in thetrajectory buffer is preserved.

The return value should be a tuple that consists of the done flag and a list of RawData objects, which form the observation for the current iteration. The list can be empty when there is no data that should be passed to the Master Script.

Below is an example Status Function that returns a single JsonRawData object on each iteration. The done flag will be set to True on the 4th iteration (the iteration counter starts at 0), which will trigger return of the trajectory data back to the Master Script.

from nrp_core import *
from import JsonRawData

def status_function():
    iteration = getSimulationIteration()

    done_flag = (iteration == 3)

    ret = JsonRawData()["iteration"] = iteration

    return done_flag, [ret]


A set of example Status Functions can be found in examples/status_function_test directory:

  • - shows how to return observations using JSON objects.

  • - shows how to return observations using protobuf objects.

  • - shows how to return observations using mixed JSON and protobuf objects.


In order to link a Status Function to a simulation, one needs to use the StatusFunction parameter in the simulation configuration. The parameters that describe a Status Function are the same as for Transceiver Functions.

Example Status Function configuration (must be a part of the simulation schema):

    "Name": "status_function",
    "FileName": ""