def train_wrapper()

in decisionai_plugin/common/plugin_service.py [0:0]

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

    def train_wrapper(self, message):
        start = time.time()        

        subscription = message['subscription']
        model_id = message['model_id']
        task_id = message['job_id']
        parameters = message['params']

        model_dir = None

        log.info("Start train wrapper for model %s by %s " % (model_id, subscription))
        try:
            self.tsanaclient.save_training_status(task_id, parameters, ModelState.Pending.name)
            
            model_dir = os.path.join(self.config.model_dir, subscription + '_' + model_id + '_' + str(time.time()))
            os.makedirs(model_dir, exist_ok=True)

            series = None
            if self.config.auto_data_retrieving:
                start_time, end_time = self.get_data_time_range(parameters, True)
                series = self.tsanaclient.get_timeseries_gw(parameters, parameters['seriesSets'], start_time, end_time)
            
            update_state(self.config, subscription, model_id, ModelState.Training)
            self.tsanaclient.save_training_status(task_id, parameters, ModelState.Training.name)
            result, message = self.do_train(model_dir, parameters, series, Context(subscription, model_id, task_id))

            if result == STATUS_SUCCESS:
                    self.train_callback(subscription, model_id, task_id, model_dir, parameters, ModelState.Ready, None)
            else:
                raise Exception(message)
        except Exception as e:
            self.train_callback(subscription, model_id, task_id, None, parameters, ModelState.Failed, str(e))

            result = STATUS_FAIL
        finally:
            if model_dir is not None:
                shutil.rmtree(model_dir, ignore_errors=True)

        total_time = (time.time() - start)
        log.duration("training_task_duration", total_time, model_id=model_id, task_id=task_id, result=result, endpoint=parameters['apiEndpoint'], group_id=parameters['groupId'], group_name=parameters['groupName'].replace(' ', '_'), instance_id=parameters['instance']['instanceId'], instance_name=parameters['instance']['instanceName'].replace(' ', '_'))
        log.count("training_task_count", 1,  model_id=model_id, task_id=task_id, result=result, endpoint=parameters['apiEndpoint'], group_id=parameters['groupId'], group_name=parameters['groupName'].replace(' ', '_'), instance_id=parameters['instance']['instanceId'], instance_name=parameters['instance']['instanceName'].replace(' ', '_'))
        gc.collect()

        return STATUS_SUCCESS, ''