The logging module has been a part of Python’s Standard Library since version 2.3. It is succinctly described in PEP 282. The documentation is notoriously hard to read, except for the basic logging tutorial.

As an alternative, loguru provides an approach for logging, nearly as simple as using a simple print statement.

Logging serves two purposes:

  • Diagnostic logging records events related to the application’s operation. If a user calls in to report an error, for example, the logs can be searched for context.
  • Audit logging records events for business analysis. A user’s transactions can be extracted and combined with other user details for reports or to optimize a business goal.

… or Print?

The only time that print is a better option than logging is when the goal is to display a help statement for a command line application. Other reasons why logging is better than print:

  • The log record, which is created with every logging event, contains readily available diagnostic information such as the file name, full path, function, and line number of the logging event.
  • Events logged in included modules are automatically accessible via the root logger to your application’s logging stream, unless you filter them out.
  • Logging can be selectively silenced by using the method logging.Logger.setLevel() or disabled by setting the attribute logging.Logger.disabled to True.

Logging in a Library

Notes for configuring logging for a library are in the logging tutorial. Because the user, not the library, should dictate what happens when a logging event occurs, one admonition bears repeating:


It is strongly advised that you do not add any handlers other than NullHandler to your library’s loggers.

Best practice when instantiating loggers in a library is to only create them using the __name__ global variable: the logging module creates a hierarchy of loggers using dot notation, so using __name__ ensures no name collisions.

Here is an example of the best practice from the requests source – place this in your __init__.py:

import logging

Logging in an Application

The twelve factor app, an authoritative reference for good practice in application development, contains a section on logging best practice. It emphatically advocates for treating log events as an event stream, and for sending that event stream to standard output to be handled by the application environment.

There are at least three ways to configure a logger:

  • Using an INI-formatted file:
    • Pro: possible to update configuration while running, using the function logging.config.listen() to listen on a socket.
    • Con: less control (e.g. custom subclassed filters or loggers) than possible when configuring a logger in code.
  • Using a dictionary or a JSON-formatted file:
    • Pro: in addition to updating while running, it is possible to load from a file using the json module, in the standard library since Python 2.6.
    • Con: less control than when configuring a logger in code.
  • Using code:
    • Pro: complete control over the configuration.
    • Con: modifications require a change to the source code.

Example Configuration via an INI File

Let us say that the file is named logging_config.ini. More details for the file format are in the logging configuration section of the logging tutorial.






format=%(asctime)s %(name)-12s %(levelname)-8s %(message)s

Then use logging.config.fileConfig() in the code:

import logging
from logging.config import fileConfig

logger = logging.getLogger()
logger.debug('often makes a very good meal of %s', 'visiting tourists')

Example Configuration via a Dictionary

As of Python 2.7, you can use a dictionary with configuration details. PEP 391 contains a list of the mandatory and optional elements in the configuration dictionary.

import logging
from logging.config import dictConfig

logging_config = dict(
    version = 1,
    formatters = {
        'f': {'format':
              '%(asctime)s %(name)-12s %(levelname)-8s %(message)s'}
    handlers = {
        'h': {'class': 'logging.StreamHandler',
              'formatter': 'f',
              'level': logging.DEBUG}
    root = {
        'handlers': ['h'],
        'level': logging.DEBUG,


logger = logging.getLogger()
logger.debug('often makes a very good meal of %s', 'visiting tourists')

Example Configuration Directly in Code

import logging

logger = logging.getLogger()
handler = logging.StreamHandler()
formatter = logging.Formatter(
        '%(asctime)s %(name)-12s %(levelname)-8s %(message)s')

logger.debug('often makes a very good meal of %s', 'visiting tourists')