def METHOD_NAME(bucket_name, start_date, end_date):
    """
    iterate over waze files in google cloud bucket, parse them and insert them to db
    param bucket_name: google cloud bucket name
    param start_date: date to start fetch waze files
    param end_date: date to end fetch waze files
    return: parsed Dataframe
    """
    blobs = []
    total_ingested_alerts = 0
    total_ingested_traffic = 0
    dates_range = pd.date_range(start=start_date, end=end_date, freq="D")
    prefixs = ["waze-api-dumps-TGeoRSS/{}/".format(d.strftime("%Y/%-m/%-d")) for d in dates_range]
    storage_client = storage.Client()
    for prefix in prefixs:
        blobs.extend(storage_client.list_blobs(bucket_name, prefix=prefix, delimiter="/"))
    bulk_size = 50
    bulk_jsons = []
    for waze_file in blobs:
        waze_data = waze_file.download_as_string()
        waze_json = json.loads(waze_data)
        bulk_jsons.append(waze_json)
        if len(bulk_jsons) % bulk_size == 0:
            alerts_count, jams_count = _ingest_waze_jsons(bulk_jsons, True)
            total_ingested_alerts += alerts_count
            total_ingested_traffic += jams_count
            bulk_jsons = []
    # ingest remaining
    alerts_count, jams_count = _ingest_waze_jsons(bulk_jsons, True)
    total_ingested_alerts += alerts_count
    total_ingested_traffic += jams_count
    logger.info(f"Ingested {total_ingested_alerts} alerts, {jams_count} jams")