def __init__()

in model/topology/heron/queueing_models.py [0:0]

• 12 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self, graph_client: GremlinClient, metrics_client: MetricsClient, paths, topology_id: str,
                 cluster: str, environ: str, start: dt.datetime, end: dt.datetime, other_kwargs: dict):
        """
        This function initializes relevant variables to calculate queue related metrics
        given an M/M/c model.
        """

        super().__init__(metrics_client, paths, topology_id, cluster, environ, start, end, other_kwargs)

        # ensure that paths are populated
        if len(self.paths) == 0:
            raise Exception("Topology paths are unavailable")

        # Get the service time for all elements
        service_times: pd.DataFrame = self.metrics_client.get_service_times(
            topology_id, cluster, environ, start, end, **other_kwargs)

        # Drop the system streams
        self.service_times = (service_times[~service_times["stream"].str.contains("__")])

        # Get arrival rates per ms for all instances
        # We should not be using this any more.
        arrival_rate: pd.DataFrame = self.metrics_client.get_tuple_arrivals_at_stmgr(
            topology_id, cluster, environ, start, end, **other_kwargs)

        # Finding mean waiting time and validating queue size
        self.service_rate = convert_service_times_to_rates(service_times)
        self.arrival_rate = convert_arr_rate_to_mean_arr_rate(arrival_rate)