def run_batchscore_pipeline()

in ml_service/pipelines/run_parallel_batchscore_pipeline.py [0:0]

• 25 lines of code
• 3 McCabe index (conditional complexity)

def run_batchscore_pipeline():
    try:
        env = Env()

        args = parse_args()

        aml_workspace = Workspace.get(
            name=env.workspace_name,
            subscription_id=env.subscription_id,
            resource_group=env.resource_group,
        )

        scoringpipeline = get_pipeline(args.pipeline_id, aml_workspace, env)

        experiment = Experiment(workspace=aml_workspace, name=env.experiment_name)  # NOQA: E501

        run = experiment.submit(
            scoringpipeline,
            pipeline_parameters={
                "model_name": env.model_name,
                "model_version": env.model_version,
                "model_tag_name": " ",
                "model_tag_value": " ",
            },
        )

        run.wait_for_completion(show_output=True)

        if run.get_status() == "Finished":
            copy_output(list(run.get_steps())[0].id, env)

    except Exception as ex:
        print("Error: {}".format(ex))