def handle(self, *args, sudo_pwd="", **kwargs):
tmux_server = libtmux.Server()
tmux_session = tmux_server.find_where(
{"session_name": settings.TMUX_SESSION_NAME}
)
restart_frequency = (
settings.PROCESS_RESTART_INTERVAL_IN_SECONDS
/ settings.STATUS_MONITORING_INTERVAL_IN_SECONDS
)
logger.info(
"I will restart processes after %d status check(s)..." % restart_frequency
)
monitoring_count = 0
while True:
start_time = time.time()
monitor_tmux_windows(tmux_session)
sleep_until_interval_is_complete(
start_time, settings.STATUS_MONITORING_INTERVAL_IN_SECONDS
)
monitoring_count += 1
if monitoring_count == restart_frequency:
restart_airomon_ng(tmux_session, sudo_pwd)
monitoring_count = 0
print()
def aggregate_data_to_db():
logger.info(f"{settings.TERM_LBL} Starting to aggregate event data ...")
while True:
start_time = time.time()
recent_hour = get_most_recent_hour()
look_back_until = recent_hour - timedelta(
hours=7 * 24) # catch up until a week of yet unaggregated data
# This aggregates all unaggregated hours/days up until the preceding one, plus the currently active one.
with transaction.atomic():
for hour in get_unaggregated_hours(
look_back_until, recent_hour -
timedelta(hours=1)) + [get_most_recent_hour()]:
seen_by_hour = aggregate_hour(hour)
seen_by_hour.save()
logger.info(f"Saved {seen_by_hour}")
for day in get_unaggregated_days(
look_back_until, recent_hour - timedelta(hours=24)) + [
get_most_recent_hour().replace(hour=0)
]:
seen_by_day = aggregate_day(day)
seen_by_day.save()
logger.info(f"Saved {seen_by_day}")
sleep_until_interval_is_complete(start_time,
settings.UPLOAD_INTERVAL_IN_SECONDS)
print()
def sensor_data_to_db(tmp_path: str):
logger.info(
f"{settings.TERM_LBL} Starting to transfer the sensor input to db ...")
sensor = get_sensor()
while True:
start_time = time.time()
sensor_data_df = sensor.get_latest_reading_as_df(tmp_path)
# check if expected columns are given
for expected_column in ("observable_id", "time_seen", "value",
"observations"):
if expected_column not in sensor_data_df.columns:
logger.error(
"The sensor module function 'get_latest_reading_as_df' did not return a dataframe"
" with the column %s."
" Instead, the dataframe only has these columns: %s",
expected_column, sensor_data_df.columns)
# hash observable IDs if wanted
sensor_data_df["observable_id"] = sensor_data_df["observable_id"].map(
lambda x: hash_observable_ids(str(x)))
update_database_with_new_and_updated_observables(sensor_data_df)
sleep_until_interval_is_complete(
start_time, settings.SENSOR_LOG_INTERVAL_IN_SECONDS)
print()
def csv_file_to_db(tmp_path: str, csv_filename_prefix: str):
logger.info(f"{settings.TERM_LBL} Starting to watch the airodump file ...")
while True:
start_time = time.time()
airodump_df = read_airodump_csv_and_return_df(tmp_path,
csv_filename_prefix)
update_database_with_new_and_updated_devices(airodump_df)
sleep_until_interval_is_complete(
start_time, settings.AIRODUMP_LOG_INTERVAL_IN_SECONDS)
print()
def handle(self, *args, **kwargs):
box_settings = BoxSettings.objects.first()
if box_settings is None:
logger.error(
f"{settings.TERM_LBL} No box settings found. Upload attempt aborted ..."
)
return
logger.info(
f"{settings.TERM_LBL} Starting the uploader against {box_settings.server_url} ..."
)
while True:
start_time = time.time()
if settings.UPLOAD_EVENTS is True:
upload_latest_events()
upload_latest_aggregations()
upload_tmux_status()
sleep_until_interval_is_complete(
start_time, settings.UPLOAD_INTERVAL_IN_SECONDS)
print()