How to use the pm4py.objects.log.exporter.xes.factory.export_log_as_string function in pm4py

trace = log[int(trace_id)]
    for key in log.attributes.keys():
        eventlog.attributes[key] = log.attributes[key]
    for index in range(len(trace)):
        new_trace = Trace(trace[0:index])
        for key in trace.attributes:
            new_trace.attributes[key] = trace.attributes[key]
        eventlog.append(new_trace)
    replay_job.case_id = trace_id
    replay_job.event_number = len(trace)
    replay_job.save()
    try:
        logger.error("Sending request for replay_prediction task.")
        r = requests.post(
            url="http://127.0.0.1:8000/runtime/replay_prediction/",
            data=export_log_as_string(eventlog),
            params={'jobId': replay_job.id, 'training_job': training_initial_job.id},
            headers={'Content-Type': 'text/plain', 'charset': 'UTF-8'}
        )
        requests_list.append(str(r))
    except Exception as e:
        requests_list.append(str(e))
        logger.warning(str(e))

    return requests_list

for t in times[2::5]:
        filtered_eventlog = timestamp_filter.apply_events(eventlog, times[0].replace(tzinfo=None),
                                                          t.replace(tzinfo=None))
        trace_list = list()
        event_number = dict()
        for trace in filtered_eventlog:
            trace_list.append(trace.attributes['concept:name'])
            event_number[trace.attributes['concept:name']] = len(trace)
        replay_job.case_id = trace_list
        replay_job.event_number = event_number
        replay_job.save()
        try: #TODO check logger usage
            logger.info("Sending request for replay_prediction task.")
            r = requests.post(
                url="http://server:8000/runtime/replay_prediction/",
                data=export_log_as_string(filtered_eventlog),
                params={'jobId': replay_job.id, 'training_job': training_initial_job.id},
                headers={'Content-Type': 'text/plain', 'charset': 'UTF-8'}
            )
            requests_list.append(str(r))
        except Exception as e:
            requests_list.append(str(e))
            logger.warning(str(e))

    training_log, test_log, additional_columns = get_train_test_log(replay_job.split)
    training_df, _ = encode_label_logs(training_log, test_log, replay_job, additional_columns=additional_columns)

    gold_values = dict(zip(training_df['trace_id'], training_df['label']))
    parent_id = replay_job.id
    final_job = duplicate_orm_row(replay_job)
    final_job.parent_job = Job.objects.filter(pk=parent_id)[0]
    final_job.gold_value = gold_values