How to use the pm4py.objects.log.importer.xes.factory.import_log function in pm4py

new_trace_start, avg_events_in_log, std_var_events_in_log, trace_ids_in_log, traces_in_log

logger = logging.getLogger(__name__)


def import_log_csv(path):
    return conversion_factory.apply(
        import_event_stream(path),                           # https://pm4py.fit.fraunhofer.de/documentation/1.2
        parameters={constants.PARAMETER_CONSTANT_CASEID_KEY: "case:concept:name",     # this tells the importer
                    constants.PARAMETER_CONSTANT_ACTIVITY_KEY: "concept:name",        # how to parse the csv
                    constants.PARAMETER_CONSTANT_TIMESTAMP_KEY: "time:timestamp"}     # and which are the caseID
    )                                                                                 # concept name and timestamp

import_log = {
    '.csv': import_log_csv,
    '.xes': import_log_xes
}

export_log = {
    '.csv': export_log_csv,
    '.xes': export_log_xes
}


def create_log(log, name: str, folder='cache/log_cache/', import_in_cache=True):
    logger.info('\tCreating new file (' + name + ') in memory')
    if import_in_cache:
        name = create_unique_name(name)
    path = folder + name
    if import_in_cache:
        if isinstance(log, EventLog):
            export_log[pathlib.Path(name).suffixes[0]](log, path)

def progetto_padova():
    JOB = Job.objects.get_or_create(
        status=JobStatuses.CREATED.value,
        type=JobTypes.PREDICTION.value,
        split=Split.objects.get_or_create(  # this creates the split of the log
            type=SplitTypes.SPLIT_DOUBLE.value,
            train_log=create_log(  # this imports the log
                import_log(BASE_DIR + RELATIVE_TRAIN_PATH),
                RELATIVE_TRAIN_PATH,
                BASE_DIR,
                import_in_cache=False
            ),
            test_log=create_log(  # this imports the log
                import_log(BASE_DIR + RELATIVE_VALIDATION_PATH),
                RELATIVE_VALIDATION_PATH,
                BASE_DIR,
                import_in_cache=False
            )
        )[0],
        encoding=Encoding.objects.get_or_create(  # this defines the encoding method
            data_encoding=DataEncodings.LABEL_ENCODER.value,
            value_encoding=ValueEncodings.SIMPLE_INDEX.value,
            add_elapsed_time=False,
            add_remaining_time=False,
            add_executed_events=False,
            add_resources_used=False,
            add_new_traces=False,
            prefix_length=5,
            padding=True,
            task_generation_type=TaskGenerationTypes.ALL_IN_ONE.value,