logging doesn't work (wrong implementation)

components/logs_writer.py

@@ -8,6 +8,11 @@
 import logging
 
 def configure_loger(APP_CONFIGS) -> logging.Logger:
+    logger = logging.getLogger(__name__)
+    logger.setLevel(logging.INFO)
+
+    attributes_list = ['asctime', 'levelname', 'message']
+    formatter = logging.Formatter('%(' + ((')s' + db_logs_handler.DEFAULT_SEPARATOR + '%(').join(attributes_list)) + ')s')
 
     if APP_CONFIGS['logs_to_db'] == True:
         database =  os.path.join(APP_CONFIGS['logs_db_path'], 'LOGS.db')
@@ -17,12 +22,6 @@ def configure_loger(APP_CONFIGS) -> logging.Logger:
         sql_handler.setFormatter(formatter)
         logger.addHandler(sql_handler)
 
-    logger = logging.getLogger(__name__)
-    logger.setLevel(logging.INFO)
-
-    attributes_list = ['asctime', 'levelname', 'message'] 
-    formatter = logging.Formatter('%(' + ((')s' + db_logs_handler.DEFAULT_SEPARATOR + '%(').join(attributes_list)) + ')s')
-
     console_handler = logging.StreamHandler()
     console_handler.setLevel(logging.DEBUG)
     console_handler.setFormatter(formatter)

components/noisereducer.py

@@ -22,11 +22,13 @@ def reduce_noise(path_to_audio_file: Union[Text,Path], output_dir: Union[Text,Pa
     wavfile.write(os.path.join(output_dir, ts + "_" + file_name), rate, reduced_noise)
     return None
 
-def cleaner_worker(configs_dict, queue) -> None:
+def cleaner_worker(configs_dict, queue, logger) -> None:
     """ Daemon cleaner worker """
     while True:
         if not queue.empty():
             f_path = queue.get()
+            logger.info(f'{f_path} Clean start')
             reduce_noise(f_path, configs_dict['clean_audio_dir'])
+            logger.info(f'{f_path} Clean end')
             os.remove(f_path)
         pass

components/transcriber.py

@@ -19,12 +19,14 @@ def transcribe_audio(
         json.dump(transcription, out_file, ensure_ascii= False)
     return None
 
-def transcriber_worker(configs_dict, queue) -> None:
+def transcriber_worker(configs_dict, queue, logger) -> None:
     """ Daemon cleaner worker """
     model = SpeechRecognitionModel("jonatasgrosman/wav2vec2-large-xlsr-53-russian")
     while True:
         if not queue.empty():
             f_path = queue.get()
+            logger.info(f'{f_path} Transcribe start')
             transcribe_audio(f_path, configs_dict['output_dir'], model)
+            logger.info(f'{f_path} Transcribe end')
             os.remove(f_path)
         pass

config.yaml

@@ -1,5 +1,5 @@
 #YAML
 working_dir: D:\\WAV2VEC_ASR_WD\
 output_dir: D:\\WAV2VEC_ASR_OUPUT\
-logs_to_db: False # False
+logs_to_db: True # False
 logs_db_path: D:\\WAV2VEC_ASR_DB\ # set path where to store SQLite DB if logs_to_db = True| else None

main.py

@@ -5,6 +5,8 @@
 from components.logs_writer import configure_loger
 import multiprocessing as mp
 
+#TODO: Create correct multiprocessing logging mechanism
+# (https://stackoverflow.com/questions/641420/how-should-i-log-while-using-multiprocessing-in-python)
 APP_CONFIGS = read_configs() # read and validate configuration file
 
 if __name__ == '__main__':
@@ -20,15 +22,15 @@
     watchdog_cleaner_proc.start()
     #watchdog_proc.join()
     # 2) cleaner
-    cleaner = mp.Process(target= cleaner_worker, args= (APP_CONFIGS, queue_to_cleaning))
+    cleaner = mp.Process(target= cleaner_worker, args= (APP_CONFIGS, queue_to_cleaning, logger))
     cleaner.daemon= True
     cleaner.start()
     # 3) watchdog with queue to transcribation
     watchdog_transcribe_proc = mp.Process(target= create_observer, args= (APP_CONFIGS['clean_audio_dir'], queue_to_transcribe))
     watchdog_transcribe_proc.daemon= True
     watchdog_transcribe_proc.start()
     # 4) Russian wav2vec implementation
-    transcriber_proc = mp.Process(target= transcriber_worker, args= (APP_CONFIGS, queue_to_transcribe))
+    transcriber_proc = mp.Process(target= transcriber_worker, args= (APP_CONFIGS, queue_to_transcribe, logger))
     transcriber_proc.daemon= True
     transcriber_proc.start()
     logger.info('Startup success')