Article
Hack of the week #9 – Python logging
14/6/22
Inovácie a vývoj
Logging is important part of each project. With logs, developer or customers are able to see events happened in the past.
Article
Hack of the week #9 – Python logging
Inovácie a vývoj
June 14, 2022
Logging is important part of each project. With logs, developer or customers are able to see events happened in the past.
Hack of the week #9 – Python logging
Inovácie a vývoj
June 14, 2022
Article
Hack of the week #9 – Python logging
Logging is important part of each project. With logs, developer or customers are able to see events happened in the past.
Inovácie a vývoj
June 14, 2022
Logging is important part of each project. With logs, developer or customers are able to see events happened in the past.
Small example: lets say, customer calls you that two week old transactions were not processed and are still stuck in the system. You as a developer thanks to the logging easily detected where the problem was and fixed it.
Python built-in logging library comes with multiple settings:
- multiple log levels (info, warning, error ...)
- logging possible to different streams (files, rotating files, sockets, standard out ...)
- endless possibilities setting up information log can contain
In the code below, the singleton logging class is implemented:
import logging
class Logs:
"""
this is singleton class
"""
_singleton = None
def __init__(self, logger_name):
if self.__initialized:
return
self.__initialized = True
self.__logger_name = logger_name
stream_log_handler = logging.StreamHandler
log_formatter = logging.Formatter(u'%(asctime)s - %(name)s - %(levelname)s - %(process)d - %(message)s
stream_log_handler.setFormatter(log_formatter)
self.logger = logging.getLogger(logger_name)
self.logger.addHandler(stream_log_handler)
self.logger.setLevel(logging.DEBUG)
def __new__(cls, logger_name):
if not cls._singleton:
cls._singleton = super(Logs, cls).__new__(cls)
cls._singleton.__initialized = False
return cls._singleton
@classmethod
def create_logger(cls, logger_name):
logger = cls(logger_name)
return logger.logger
I am setting the logger:
- output to the stream only (standard output) - I am using this setting for GCP projects, as this logs are stored by Google, there is no need to store them to the files separately
- use format: u'%(asctime)s - %(name)s - %(levelname)s - %(process)d - %(message)s'
- set logging level to debug - meaning that lover level info log message will not be logged
Then, wherever in the project you can log using this snippet:
from classes.logs import Logs
logger = Logs.create_logger()
if __name__ == '__main__':
logger.debug("Hello world!")
And thats it. Hope the ones, which were not logging until now, will start :)))