Logging

    Python programmers will often use print() in their code as a quick and convenient debugging tool. Using the logging framework is only a little more effort than that, but it’s much more elegant and flexible. As well as being useful for debugging, logging can also provide you with more - and better structured - information about the state and health of your application.

    Django uses and extends Python’s builtin module to perform system logging. This module is discussed in detail in Python’s own documentation; this section provides a quick overview.

    A Python logging configuration consists of four parts:

    Loggers

    A logger is the entry point into the logging system. Each logger is a named bucket to which messages can be written for processing.

    A logger is configured to have a log level. This log level describes the severity of the messages that the logger will handle. Python defines the following log levels:

    • DEBUG: Low level system information for debugging purposes
    • INFO: General system information
    • WARNING: Information describing a minor problem that has occurred.
    • ERROR: Information describing a major problem that has occurred.
    • CRITICAL: Information describing a critical problem that has occurred.

    Each message that is written to the logger is a Log Record. Each log record also has a log level indicating the severity of that specific message. A log record can also contain useful metadata that describes the event that is being logged. This can include details such as a stack trace or an error code.

    When a message is given to the logger, the log level of the message is compared to the log level of the logger. If the log level of the message meets or exceeds the log level of the logger itself, the message will undergo further processing. If it doesn’t, the message will be ignored.

    Once a logger has determined that a message needs to be processed, it is passed to a Handler.

    Handlers

    The handler is the engine that determines what happens to each message in a logger. It describes a particular logging behavior, such as writing a message to the screen, to a file, or to a network socket.

    Like loggers, handlers also have a log level. If the log level of a log record doesn’t meet or exceed the level of the handler, the handler will ignore the message.

    A logger can have multiple handlers, and each handler can have a different log level. In this way, it is possible to provide different forms of notification depending on the importance of a message. For example, you could install one handler that forwards ERROR and CRITICAL messages to a paging service, while a second handler logs all messages (including ERROR and CRITICAL messages) to a file for later analysis.

    Filters

    A filter is used to provide additional control over which log records are passed from logger to handler.

    By default, any log message that meets log level requirements will be handled. However, by installing a filter, you can place additional criteria on the logging process. For example, you could install a filter that only allows ERROR messages from a particular source to be emitted.

    Filters can also be used to modify the logging record prior to being emitted. For example, you could write a filter that downgrades ERROR log records to WARNING records if a particular set of criteria are met.

    Filters can be installed on loggers or on handlers; multiple filters can be used in a chain to perform multiple filtering actions.

    Formatters

    Ultimately, a log record needs to be rendered as text. Formatters describe the exact format of that text. A formatter usually consists of a Python formatting string containing LogRecord attributes; however, you can also write custom formatters to implement specific formatting behavior.

    The logging system handles potentially sensitive information. For example, the log record may contain information about a web request or a stack trace, while some of the data you collect in your own loggers may also have security implications. You need to be sure you know:

    • what information is collected
    • where it will subsequently be stored
    • how it will be transferred
    • who might have access to it.

    The built-in deserves a mention in the context of security. If its include_html option is enabled, the email message it sends will contain a full traceback, with names and values of local variables at each level of the stack, plus the values of your Django settings (in other words, the same level of detail that is exposed in a web page when DEBUG is True).

    It’s generally not considered a good idea to send such potentially sensitive information over email. Consider instead using one of the many third-party services to which detailed logs can be sent to get the best of multiple worlds – the rich information of full tracebacks, clear management of who is notified and has access to the information, and so on.

    Python’s logging library provides several techniques to configure logging, ranging from a programmatic interface to configuration files. By default, Django uses the .

    In order to configure logging, you use LOGGING to define a dictionary of logging settings. These settings describe the loggers, handlers, filters and formatters that you want in your logging setup, and the log levels and other properties that you want those components to have.

    By default, the setting is merged with Django’s default logging configuration using the following scheme.

    If the disable_existing_loggers key in the dictConfig is set to True (which is the dictConfig default if the key is missing) then all loggers from the default configuration will be disabled. Disabled loggers are not the same as removed; the logger will still exist, but will silently discard anything logged to it, not even propagating entries to a parent logger. Thus you should be very careful using 'disable_existing_loggers': True; it’s probably not what you want. Instead, you can set disable_existing_loggers to False and redefine some or all of the default loggers; or you can set LOGGING_CONFIG to None and .

    Logging is configured as part of the general Django setup() function. Therefore, you can be certain that loggers are always ready for use in your project code.

    The full documentation for dictConfig format is the best source of information about logging configuration dictionaries. However, to give you a taste of what is possible, here are several examples.

    To begin, here’s a small configuration that will allow you to output all log messages to the console:

    This configures the parent root logger to send messages with the WARNING level and higher to the console handler. By adjusting the level to INFO or DEBUG you can display more messages. This may be useful during development.

    Next we can add more fine-grained logging. Here’s an example of how to make the logging system print more messages from just the named logger:

    settings.py

    By default, this config sends messages from the django logger of level INFO or higher to the console. This is the same level as Django’s default logging config, except that the default config only displays log records when DEBUG=True. Django does not log many such INFO level messages. With this config, however, you can also set the environment variable DJANGO_LOG_LEVEL=DEBUG to see all of Django’s debug logging which is very verbose as it includes all database queries.

    You don’t have to log to the console. Here’s a configuration which writes all logging from the django named logger to a local file:

    settings.py

    If you use this example, be sure to change the 'filename' path to a location that’s writable by the user that’s running the Django application.

    settings.py

    This logging configuration does the following things:

    • Defines two formatters:

      • simple, that outputs the log level name (e.g., DEBUG) and the log message.

        The format string is a normal Python formatting string describing the details that are to be output on each logging line. The full list of detail that can be output can be found in .

      • verbose, that outputs the log level name, the log message, plus the time, process, thread and module that generate the log message.

    • Defines two filters:

      • project.logging.SpecialFilter, using the alias special. If this filter required additional arguments, they can be provided as additional keys in the filter configuration dictionary. In this case, the argument foo will be given a value of bar when instantiating SpecialFilter.
      • django.utils.log.RequireDebugTrue, which passes on records when DEBUG is True.

    • Defines two handlers:

      • , a , which prints any INFO (or higher) message to sys.stderr. This handler uses the simple output format.
      • mail_admins, an AdminEmailHandler, which emails any ERROR (or higher) message to the site . This handler uses the special filter.

    • Configures three loggers:

      • django, which passes all messages to the console handler.
      • django.request, which passes all ERROR messages to the mail_admins handler. In addition, this logger is marked to not propagate messages. This means that log messages written to django.request will not be handled by the django logger.
      • myproject.custom, which passes all messages at INFO or higher that also pass the special filter to two handlers – the console, and mail_admins. This means that all INFO level messages (or higher) will be printed to the console; ERROR and CRITICAL messages will also be output via email.

    If you don’t want to use Python’s dictConfig format to configure your logger, you can specify your own configuration scheme.

    The LOGGING_CONFIG setting defines the callable that will be used to configure Django’s loggers. By default, it points at Python’s function. However, if you want to use a different configuration process, you can use any other callable that takes a single argument. The contents of LOGGING will be provided as the value of that argument when logging is configured.

    If you don’t want to configure logging at all (or you want to manually configure logging using your own approach), you can set to None. This will disable the configuration process for Django’s default logging.

    Setting to None only means that the automatic configuration process is disabled, not logging itself. If you disable the configuration process, Django will still make logging calls, falling back to whatever default logging behavior is defined.

    Here’s an example that disables Django’s logging configuration and then manually configures logging:

    settings.py

    Note that the default configuration process only calls LOGGING_CONFIG once settings are fully-loaded. In contrast, manually configuring the logging in your settings file will load your logging config immediately. As such, your logging config must appear after any settings on which it depends.