Codecademy Logo

Logging

Setting the Logging Level

Setting the logging level for the logger object will allow all messages at and above that level to be produced in the output stream. The logging level can be set by using setLevel(). If no level is manually set, the default level logging.WARNING is used.

import logging


logger.setLevel(logging.INFO)

Formatting Options for Logging

Formatting of logged messages can be changed by using the Formatter class. Information like timestamps, function names, and line numbers can be included in the logged message.

import logging


formatter = logging.Formatter('[%(asctime)s] %(message)s')

Logging to File and Console

Log messages can be directed to both files and the console by adding FileHandler and StreamHandler handler objects to the logger.

While logging to console is helpful if needing to review debugging log messages in real-time, logging to a file allows for the logged messages to exist well after the program execution has occurred.

import logging
import sys


file_handler = logging.FileHandler("program.log")
stream_handler = logging.StreamHandler(sys.stdout)

Configuring the Logger with basicConfig

For a simple, one-liner configuration of the logger, there is a basicConfig() method that will allow for adding handlers, setting formatting options for the logged messages, and setting the log level for the logger.

import logging


logging.basicConfig(filename='program.log', level=logging.DEBUG, format= '[%(asctime)s] %(levelname)s - %(message)s')

Using the Logging Module

Logging messages and exceptions is important for debugging applications and for logging important information that generates during execution. The proper method for logging these messages is the logging module.

import logging

Logging Levels

There are six logging levels associated with the logging module:

  • NOTSET, which has a numeric value of 0
  • DEBUG, which has a numeric value of 10
  • INFO, which has a numeric value of 20
  • WARNING, which has a numeric value of 30
  • ERROR, which has a numeric value of 40
  • CRITICAL, which has a numeric value of 50
import logging


logging.DEBUG
logging.INFO
logging.WARNING
logging.ERROR
logging.CRITICAL
logging.NOTSET
Next

Learn more on Codecademy

Course

Learn Advanced Python 3

Learn the basics of functional programming, concurrent programming, deployment, and more in this advanced Python course.
With Certificate
Advanced
6 hours
Career path

Data Engineer

A data engineer builds the pipelines to connect data input to analysis.
Includes 17 Courses
With Certificate
Beginner Friendly
90 hours