Before modifications

bt_monitor_server.py

@@ -203,6 +203,7 @@ async def send_discovery_messages(mqtt_client, device_names):
         await mqtt_client.publish(topic, json.dumps(msg).encode(), retain=True)
 
 
+
 async def async_main(
     mqtt_info: MqttInfo,
     trackers: List[str],
@@ -237,12 +238,12 @@ async def async_main(
                     logging.debug(f"Got Measurement {measurement}")
                     m = device_decoder(measurement)
                     if m is not None:
-                        logging.debug(f"Decoded Measurement {m}")
+                        logging.info(f"Decoded Measurement {m}")
                         training_data_logger.report_measure(m)
                         feature_vec =feature_accumulator.add_measurement(m)
                         if feature_vec:
                             feature_str={tracker : value for tracker, value in zip(trackers, feature_vec)} 
-                            logging.debug(f"Features: {feature_str}")
+                            logging.info(f"Features: {feature_str}")
                         if feature_vec is not None and classifier is not None:
                             room = classifier(m.device, feature_vec)
                             if room != current_rooms[m.device]:
@@ -250,6 +251,20 @@ async def async_main(
                                 current_rooms[m.device] = room
                             await client.publish(f"my_btmonitor/ml/{m.device}", room.encode())
 
+async def async_main_with_restart(
+    mqtt_info: MqttInfo,
+    trackers: List[str],
+    devices: List[str],
+    classifier,
+    device_decoder: DeviceDecoder,
+    training_data_logger: KnownRoomCsvLogger,
+):
+    while True:
+        try:
+            await async_main(mqtt_info, trackers, devices, classifier, device_decoder, training_data_logger)
+        except Exception as e:
+            print(e)
+            print("restarting...")
 
 def get_classification_func(training_df: pd.DataFrame, log_classifier_scores=True):
     devices_to_track = list(training_df["device"].unique())
@@ -291,5 +306,4 @@ if __name__ == "__main__":
     device_decoder = DeviceDecoder(irk_to_devicename, address_to_name)
     trackers = list(training_df["tracker"].cat.categories)
     devices = list(training_df['device'].cat.categories)
-    asyncio.run(async_main(mqtt_info, trackers, devices, classification_func, device_decoder, training_data_logger))
-
+    asyncio.run(async_main_with_restart(mqtt_info, trackers, devices, classification_func, device_decoder, training_data_logger))