mirror of https://github.com/django/django.git
344 lines
11 KiB
Plaintext
344 lines
11 KiB
Plaintext
.. _logging-how-to:
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================================
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How to configure and use logging
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================================
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.. seealso::
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* :ref:`Django logging reference <logging-ref>`
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* :ref:`Django logging overview <logging-explanation>`
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Django provides a working :ref:`default logging configuration
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<default-logging-configuration>` that is readily extended.
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Make a basic logging call
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=========================
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To send a log message from within your code, you place a logging call into it.
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.. admonition:: Don't be tempted to use logging calls in ``settings.py``.
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The way that Django logging is configured as part of the ``setup()``
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function means that logging calls placed in ``settings.py`` may not work as
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expected, because *logging will not be set up at that point*. To explore
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logging, use a view function as suggested in the example below.
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First, import the Python logging library, and then obtain a logger instance
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with :py:func:`logging.getLogger`. Provide the ``getLogger()`` method with a
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name to identify it and the records it emits. A good option is to use
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``__name__`` (see :ref:`naming-loggers` below for more on this) which will
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provide the name of the current Python module as a dotted path::
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import logging
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logger = logging.getLogger(__name__)
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It's a good convention to perform this declaration at module level.
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And then in a function, for example in a view, send a record to the logger::
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def some_view(request):
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...
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if some_risky_state:
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logger.warning('Platform is running at risk')
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When this code is executed, a :py:class:`~logging.LogRecord` containing that
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message will be sent to the logger. If you're using Django's default logging
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configuration, the message will appear in the console.
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The ``WARNING`` level used in the example above is one of several
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:ref:`logging severity levels <topic-logging-parts-loggers>`: ``DEBUG``,
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``INFO``, ``WARNING``, ``ERROR``, ``CRITICAL``. So, another example might be::
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logger.critical('Payment system is not responding')
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.. important::
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Records with a level lower than ``WARNING`` will not appear in the console
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by default. Changing this behavior requires additional configuration.
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Customize logging configuration
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===============================
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Although Django's logging configuration works out of the box, you can control
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exactly how your logs are sent to various destinations - to log files, external
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services, email and so on - with some additional configuration.
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You can configure:
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* logger mappings, to determine which records are sent to which handlers
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* handlers, to determine what they do with the records they receive
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* filters, to provide additional control over the transfer of records, and
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even modify records in-place
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* formatters, to convert :class:`~logging.LogRecord` objects to a string or
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other form for consumption by human beings or another system
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There are various ways of configuring logging. In Django, the
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:setting:`LOGGING` setting is most commonly used. The setting uses the
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:ref:`dictConfig format <logging-config-dictschema>`, and extends the
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:ref:`default logging configuration <default-logging-definition>`.
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See :ref:`configuring-logging` for an explanation of how your custom settings
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are merged with Django's defaults.
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See the :mod:`Python logging documentation <python:logging.config>` for
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details of other ways of configuring logging. For the sake of simplicity, this
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documentation will only consider configuration via the ``LOGGING`` setting.
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.. _basic-logger-configuration:
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Basic logging configuration
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---------------------------
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When configuring logging, it makes sense to
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Create a ``LOGGING`` dictionary
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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In your ``settings.py``::
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LOGGING = {
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'version': 1, # the dictConfig format version
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'disable_existing_loggers': False, # retain the default loggers
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}
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It nearly always makes sense to retain and extend the default logging
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configuration by setting ``disable_existing_loggers`` to ``False``.
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Configure a handler
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~~~~~~~~~~~~~~~~~~~
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This example configures a single handler named ``file``, that uses Python's
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:class:`~logging.FileHandler` to save logs of level ``DEBUG`` and higher to the
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file ``general.log`` (at the project root):
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.. code-block:: python
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:emphasize-lines: 3-8
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LOGGING = {
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[...]
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'handlers': {
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'file': {
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'class': 'logging.FileHandler',
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'filename': 'general.log',
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},
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},
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}
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Different handler classes take different configuration options. For more
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information on available handler classes, see the
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:class:`~django.utils.log.AdminEmailHandler` provided by Django and the various
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:py:mod:`handler classes <logging.handlers>` provided by Python.
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Logging levels can also be set on the handlers (by default, they accept log
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messages of all levels). Using the example above, adding:
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.. code-block:: python
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:emphasize-lines: 4
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{
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'class': 'logging.FileHandler',
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'filename': 'general.log',
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'level': 'DEBUG',
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}
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would define a handler configuration that only accepts records of level
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``DEBUG`` and higher.
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Configure a logger mapping
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~~~~~~~~~~~~~~~~~~~~~~~~~~
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To send records to this handler, configure a logger mapping to use it for
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example:
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.. code-block:: python
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:emphasize-lines: 3-8
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LOGGING = {
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[...]
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'loggers': {
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'': {
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'level': 'DEBUG',
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'handlers': ['file'],
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},
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},
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}
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The mapping's name determines which log records it will process. This
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configuration (``''``) is *unnamed*. That means that it will process records
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from *all* loggers (see :ref:`naming-loggers` below on how to use the mapping
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name to determine the loggers for which it will process records).
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It will forward messages of levels ``DEBUG`` and higher to the handler named
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``file``.
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Note that a logger can forward messages to multiple handlers, so the relation
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between loggers and handlers is many-to-many.
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If you execute::
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logger.debug('Attempting to connect to API')
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in your code, you will find that message in the file ``general.log`` in the
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root of the project.
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Configure a formatter
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~~~~~~~~~~~~~~~~~~~~~
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By default, the final log output contains the message part of each :class:`log
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record <logging.LogRecord>`. Use a formatter if you want to include additional
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data. First name and define your formatters - this example defines
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formatters named ``verbose`` and ``simple``:
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.. code-block:: python
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:emphasize-lines: 3-12
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LOGGING = {
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[...]
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'formatters': {
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'verbose': {
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'format': '{name} {levelname} {asctime} {module} {process:d} {thread:d} {message}',
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'style': '{',
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},
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'simple': {
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'format': '{levelname} {message}',
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'style': '{',
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},
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},
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}
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The ``style`` keyword allows you to specify ``{`` for :meth:`str.format` or
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``$`` for :class:`string.Template` formatting; the default is ``$``.
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See :ref:`logrecord-attributes` for the :class:`~logging.LogRecord` attributes
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you can include.
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To apply a formatter to a handler, add a ``formatter`` entry to the handler's
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dictionary referring to the formatter by name, for example:
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.. code-block:: python
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:emphasize-lines: 5
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'handlers': {
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'file': {
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'class': 'logging.FileHandler',
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'filename': 'general.log',
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'formatter': 'verbose',
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},
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},
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.. _naming-loggers:
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Use logger namespacing
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~~~~~~~~~~~~~~~~~~~~~~
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The unnamed logging configuration ``''`` captures logs from any Python
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application. A named logging configuration will capture logs only from loggers
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with matching names.
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The namespace of a logger instance is defined using
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:py:func:`~logging.getLogger`. For example in ``views.py`` of ``my_app``::
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logger = logging.getLogger(__name__)
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will create a logger in the ``my_app.views`` namespace. ``__name__`` allows you
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to organize log messages according to their provenance within your project's
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applications automatically. It also ensures that you will not experience name
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collisions.
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A logger mapping named ``my_app.views`` will capture records from this logger:
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.. code-block:: python
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:emphasize-lines: 4
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LOGGING = {
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[...]
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'loggers': {
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'my_app.views': {
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...
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},
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},
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}
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A logger mapping named ``my_app`` will be more permissive, capturing records
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from loggers anywhere within the ``my_app`` namespace (including
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``my_app.views``, ``my_app.utils``, and so on):
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.. code-block:: python
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:emphasize-lines: 4
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LOGGING = {
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[...]
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'loggers': {
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'my_app': {
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...
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},
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},
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}
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You can also define logger namespacing explicitly::
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logger = logging.getLogger('project.payment')
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and set up logger mappings accordingly.
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.. _naming-loggers-hierarchy:
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Using logger hierarchies and propagation
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Logger naming is *hierarchical*. ``my_app`` is the parent of ``my_app.views``,
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which is the parent of ``my_app.views.private``. Unless specified otherwise,
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logger mappings will propagate the records they process to their parents - a
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record from a logger in the ``my_app.views.private`` namespace will be handled
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by a mapping for both ``my_app`` and ``my_app.views``.
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To manage this behavior, set the propagation key on the mappings you define::
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LOGGING = {
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[...]
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'loggers': {
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'my_app': {
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[...]
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},
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'my_app.views': {
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[...]
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},
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'my_app.views.private': {
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[...]
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'propagate': False,
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},
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},
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}
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``propagate`` defaults to ``True``. In this example, the logs from
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``my_app.views.private`` will not be handled by the parent, but logs from
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``my_app.views`` will.
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Configure responsive logging
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----------------------------
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Logging is most useful when it contains as much information as possible, but
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not information that you don't need - and how much you need depends upon what
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you're doing. When you're debugging, you need a level of information that would
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be excessive and unhelpful if you had to deal with it in production.
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You can configure logging to provide you with the level of detail you need,
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when you need it. Rather than manually change configuration to achieve this, a
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better way is to apply configuration automatically according to the
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environment.
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For example, you could set an environment variable ``DJANGO_LOG_LEVEL``
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appropriately in your development and staging environments, and make use of it
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in a logger mapping thus::
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'level': os.getenv('DJANGO_LOG_LEVEL', 'WARNING')
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\- so that unless the environment specifies a lower log level, this
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configuration will only forward records of severity ``WARNING`` and above to
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its handler.
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Other options in the configuration (such as the ``level`` or ``formatter``
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option of handlers) can be similarly managed.
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