cpython/Doc/library/logging.rst

:mod:`logging` --- Logging facility for Python
==============================================

.. module:: logging
   :synopsis: Flexible error logging system for applications.


.. moduleauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sectionauthor:: Vinay Sajip <vinay_sajip@red-dove.com>


.. index:: pair: Errors; logging

This module defines functions and classes which implement a flexible error
logging system for applications.

Logging is performed by calling methods on instances of the :class:`Logger`
class (hereafter called :dfn:`loggers`). Each instance has a name, and they are
conceptually arranged in a namespace hierarchy using dots (periods) as
separators. For example, a logger named "scan" is the parent of loggers
"scan.text", "scan.html" and "scan.pdf". Logger names can be anything you want,
and indicate the area of an application in which a logged message originates.

Logged messages also have levels of importance associated with them. The default
levels provided are :const:`DEBUG`, :const:`INFO`, :const:`WARNING`,
:const:`ERROR` and :const:`CRITICAL`. As a convenience, you indicate the
importance of a logged message by calling an appropriate method of
:class:`Logger`. The methods are :meth:`debug`, :meth:`info`, :meth:`warning`,
:meth:`error` and :meth:`critical`, which mirror the default levels. You are not
constrained to use these levels: you can specify your own and use a more general
:class:`Logger` method, :meth:`log`, which takes an explicit level argument.


Logging tutorial
----------------

The key benefit of having the logging API provided by a standard library module
is that all Python modules can participate in logging, so your application log
can include messages from third-party modules.

It is, of course, possible to log messages with different verbosity levels or to
different destinations.  Support for writing log messages to files, HTTP
GET/POST locations, email via SMTP, generic sockets, or OS-specific logging
mechanisms are all supported by the standard module.  You can also create your
own log destination class if you have special requirements not met by any of the
built-in classes.

Simple examples
^^^^^^^^^^^^^^^

.. sectionauthor:: Doug Hellmann
.. (see <http://blog.doughellmann.com/2007/05/pymotw-logging.html>)

Most applications are probably going to want to log to a file, so let's start
with that case. Using the :func:`basicConfig` function, we can set up the
default handler so that debug messages are written to a file (in the example,
we assume that you have the appropriate permissions to create a file called
*example.log* in the current directory)::

   import logging
   LOG_FILENAME = 'example.log'
   logging.basicConfig(filename=LOG_FILENAME,level=logging.DEBUG)

   logging.debug('This message should go to the log file')

And now if we open the file and look at what we have, we should find the log
message::

   DEBUG:root:This message should go to the log file

If you run the script repeatedly, the additional log messages are appended to
the file.  To create a new file each time, you can pass a *filemode* argument to
:func:`basicConfig` with a value of ``'w'``.  Rather than managing the file size
yourself, though, it is simpler to use a :class:`RotatingFileHandler`::

   import glob
   import logging
   import logging.handlers

   LOG_FILENAME = 'logging_rotatingfile_example.out'

   # Set up a specific logger with our desired output level
   my_logger = logging.getLogger('MyLogger')
   my_logger.setLevel(logging.DEBUG)

   # Add the log message handler to the logger
   handler = logging.handlers.RotatingFileHandler(
                 LOG_FILENAME, maxBytes=20, backupCount=5)

   my_logger.addHandler(handler)

   # Log some messages
   for i in range(20):
       my_logger.debug('i = %d' % i)

   # See what files are created
   logfiles = glob.glob('%s*' % LOG_FILENAME)

   for filename in logfiles:
       print(filename)

The result should be 6 separate files, each with part of the log history for the
application::

   logging_rotatingfile_example.out
   logging_rotatingfile_example.out.1
   logging_rotatingfile_example.out.2
   logging_rotatingfile_example.out.3
   logging_rotatingfile_example.out.4
   logging_rotatingfile_example.out.5

The most current file is always :file:`logging_rotatingfile_example.out`,
and each time it reaches the size limit it is renamed with the suffix
``.1``. Each of the existing backup files is renamed to increment the suffix
(``.1`` becomes ``.2``, etc.)  and the ``.6`` file is erased.

Obviously this example sets the log length much much too small as an extreme
example.  You would want to set *maxBytes* to an appropriate value.

Another useful feature of the logging API is the ability to produce different
messages at different log levels.  This allows you to instrument your code with
debug messages, for example, but turning the log level down so that those debug
messages are not written for your production system.  The default levels are
``NOTSET``, ``DEBUG``, ``INFO``, ``WARNING``, ``ERROR`` and ``CRITICAL``.

The logger, handler, and log message call each specify a level.  The log message
is only emitted if the handler and logger are configured to emit messages of
that level or lower.  For example, if a message is ``CRITICAL``, and the logger
is set to ``ERROR``, the message is emitted.  If a message is a ``WARNING``, and
the logger is set to produce only ``ERROR``\s, the message is not emitted::

   import logging
   import sys

   LEVELS = {'debug': logging.DEBUG,
             'info': logging.INFO,
             'warning': logging.WARNING,
             'error': logging.ERROR,
             'critical': logging.CRITICAL}

   if len(sys.argv) > 1:
       level_name = sys.argv[1]
       level = LEVELS.get(level_name, logging.NOTSET)
       logging.basicConfig(level=level)

   logging.debug('This is a debug message')
   logging.info('This is an info message')
   logging.warning('This is a warning message')
   logging.error('This is an error message')
   logging.critical('This is a critical error message')

Run the script with an argument like 'debug' or 'warning' to see which messages
show up at different levels::

   $ python logging_level_example.py debug
   DEBUG:root:This is a debug message
   INFO:root:This is an info message
   WARNING:root:This is a warning message
   ERROR:root:This is an error message
   CRITICAL:root:This is a critical error message

   $ python logging_level_example.py info
   INFO:root:This is an info message
   WARNING:root:This is a warning message
   ERROR:root:This is an error message
   CRITICAL:root:This is a critical error message

You will notice that these log messages all have ``root`` embedded in them.  The
logging module supports a hierarchy of loggers with different names.  An easy
way to tell where a specific log message comes from is to use a separate logger
object for each of your modules.  Each new logger "inherits" the configuration
of its parent, and log messages sent to a logger include the name of that
logger.  Optionally, each logger can be configured differently, so that messages
from different modules are handled in different ways.  Let's look at a simple
example of how to log from different modules so it is easy to trace the source
of the message::

   import logging

   logging.basicConfig(level=logging.WARNING)

   logger1 = logging.getLogger('package1.module1')
   logger2 = logging.getLogger('package2.module2')

   logger1.warning('This message comes from one module')
   logger2.warning('And this message comes from another module')

And the output::

   $ python logging_modules_example.py
   WARNING:package1.module1:This message comes from one module
   WARNING:package2.module2:And this message comes from another module

There are many more options for configuring logging, including different log
message formatting options, having messages delivered to multiple destinations,
and changing the configuration of a long-running application on the fly using a
socket interface.  All of these options are covered in depth in the library
module documentation.

Loggers
^^^^^^^

The logging library takes a modular approach and offers the several categories
of components: loggers, handlers, filters, and formatters.  Loggers expose the
interface that application code directly uses.  Handlers send the log records to
the appropriate destination. Filters provide a finer grained facility for
determining which log records to send on to a handler.  Formatters specify the
layout of the resultant log record.

:class:`Logger` objects have a threefold job.  First, they expose several
methods to application code so that applications can log messages at runtime.
Second, logger objects determine which log messages to act upon based upon
severity (the default filtering facility) or filter objects.  Third, logger
objects pass along relevant log messages to all interested log handlers.

The most widely used methods on logger objects fall into two categories:
configuration and message sending.

* :meth:`Logger.setLevel` specifies the lowest-severity log message a logger
  will handle, where debug is the lowest built-in severity level and critical is
  the highest built-in severity.  For example, if the severity level is info,
  the logger will handle only info, warning, error, and critical messages and
  will ignore debug messages.

* :meth:`Logger.addFilter` and :meth:`Logger.removeFilter` add and remove filter
  objects from the logger object.  This tutorial does not address filters.

With the logger object configured, the following methods create log messages:

* :meth:`Logger.debug`, :meth:`Logger.info`, :meth:`Logger.warning`,
  :meth:`Logger.error`, and :meth:`Logger.critical` all create log records with
  a message and a level that corresponds to their respective method names. The
  message is actually a format string, which may contain the standard string
  substitution syntax of :const:`%s`, :const:`%d`, :const:`%f`, and so on.  The
  rest of their arguments is a list of objects that correspond with the
  substitution fields in the message.  With regard to :const:`**kwargs`, the
  logging methods care only about a keyword of :const:`exc_info` and use it to
  determine whether to log exception information.

* :meth:`Logger.exception` creates a log message similar to
  :meth:`Logger.error`.  The difference is that :meth:`Logger.exception` dumps a
  stack trace along with it.  Call this method only from an exception handler.

* :meth:`Logger.log` takes a log level as an explicit argument.  This is a
  little more verbose for logging messages than using the log level convenience
  methods listed above, but this is how to log at custom log levels.

:func:`getLogger` returns a reference to a logger instance with the specified
name if it is provided, or ``root`` if not.  The names are period-separated
hierarchical structures.  Multiple calls to :func:`getLogger` with the same name
will return a reference to the same logger object.  Loggers that are further
down in the hierarchical list are children of loggers higher up in the list.
For example, given a logger with a name of ``foo``, loggers with names of
``foo.bar``, ``foo.bar.baz``, and ``foo.bam`` are all descendants of ``foo``.
Child loggers propagate messages up to the handlers associated with their
ancestor loggers.  Because of this, it is unnecessary to define and configure
handlers for all the loggers an application uses. It is sufficient to
configure handlers for a top-level logger and create child loggers as needed.


Handlers
^^^^^^^^

:class:`Handler` objects are responsible for dispatching the appropriate log
messages (based on the log messages' severity) to the handler's specified
destination.  Logger objects can add zero or more handler objects to themselves
with an :func:`addHandler` method.  As an example scenario, an application may
want to send all log messages to a log file, all log messages of error or higher
to stdout, and all messages of critical to an email address.  This scenario
requires three individual handlers where each handler is responsible for sending
messages of a specific severity to a specific location.

The standard library includes quite a few handler types; this tutorial uses only
:class:`StreamHandler` and :class:`FileHandler` in its examples.

There are very few methods in a handler for application developers to concern
themselves with.  The only handler methods that seem relevant for application
developers who are using the built-in handler objects (that is, not creating
custom handlers) are the following configuration methods:

* The :meth:`Handler.setLevel` method, just as in logger objects, specifies the
  lowest severity that will be dispatched to the appropriate destination.  Why
  are there two :func:`setLevel` methods?  The level set in the logger
  determines which severity of messages it will pass to its handlers.  The level
  set in each handler determines which messages that handler will send on.

* :func:`setFormatter` selects a Formatter object for this handler to use.

* :func:`addFilter` and :func:`removeFilter` respectively configure and
  deconfigure filter objects on handlers.

Application code should not directly instantiate and use instances of
:class:`Handler`.  Instead, the :class:`Handler` class is a base class that
defines the interface that all handlers should have and establishes some
default behavior that child classes can use (or override).


Formatters
^^^^^^^^^^

Formatter objects configure the final order, structure, and contents of the log
message.  Unlike the base :class:`logging.Handler` class, application code may
instantiate formatter classes, although you could likely subclass the formatter
if your application needs special behavior.  The constructor takes three
optional arguments -- a message format string, a date format string and a style
indicator.

.. method:: logging.Formatter.__init__(fmt=None, datefmt=None, style='%')

If there is no message format string, the default is to use the
raw message.  If there is no date format string, the default date format is::

    %Y-%m-%d %H:%M:%S

with the milliseconds tacked on at the end. The ``style`` is one of `%`, '{'
or '$'. If one of these is not specified, then '%' will be used.

If the ``style`` is '%', the message format string uses
``%(<dictionary key>)s`` styled string substitution; the possible keys are
documented in :ref:`formatter-objects`. If the style is '{', the message format
string is assumed to be compatible with :meth:`str.format` (using keyword
arguments), while if the style is '$' then the message format string should
conform to what is expected by :meth:`string.Template.substitute`.

.. versionchanged:: 3.2
   Added the ``style`` parameter.

The following message format string will log the time in a human-readable
format, the severity of the message, and the contents of the message, in that
order::

    "%(asctime)s - %(levelname)s - %(message)s"

Formatters use a user-configurable function to convert the creation time of a
record to a tuple. By default, :func:`time.localtime` is used; to change this
for a particular formatter instance, set the ``converter`` attribute of the
instance to a function with the same signature as :func:`time.localtime` or
:func:`time.gmtime`. To change it for all formatters, for example if you want
all logging times to be shown in GMT, set the ``converter`` attribute in the
Formatter class (to ``time.gmtime`` for GMT display).


Configuring Logging
^^^^^^^^^^^^^^^^^^^

Programmers can configure logging in three ways:

1. Creating loggers, handlers, and formatters explicitly using Python
   code that calls the configuration methods listed above.
2. Creating a logging config file and reading it using the :func:`fileConfig`
   function.
3. Creating a dictionary of configuration information and passing it
   to the :func:`dictConfig` function.

The following example configures a very simple logger, a console
handler, and a simple formatter using Python code::

    import logging

    # create logger
    logger = logging.getLogger("simple_example")
    logger.setLevel(logging.DEBUG)

    # create console handler and set level to debug
    ch = logging.StreamHandler()
    ch.setLevel(logging.DEBUG)

    # create formatter
    formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")

    # add formatter to ch
    ch.setFormatter(formatter)

    # add ch to logger
    logger.addHandler(ch)

    # "application" code
    logger.debug("debug message")
    logger.info("info message")
    logger.warn("warn message")
    logger.error("error message")
    logger.critical("critical message")

Running this module from the command line produces the following output::

    $ python simple_logging_module.py
    2005-03-19 15:10:26,618 - simple_example - DEBUG - debug message
    2005-03-19 15:10:26,620 - simple_example - INFO - info message
    2005-03-19 15:10:26,695 - simple_example - WARNING - warn message
    2005-03-19 15:10:26,697 - simple_example - ERROR - error message
    2005-03-19 15:10:26,773 - simple_example - CRITICAL - critical message

The following Python module creates a logger, handler, and formatter nearly
identical to those in the example listed above, with the only difference being
the names of the objects::

    import logging
    import logging.config

    logging.config.fileConfig("logging.conf")

    # create logger
    logger = logging.getLogger("simpleExample")

    # "application" code
    logger.debug("debug message")
    logger.info("info message")
    logger.warn("warn message")
    logger.error("error message")
    logger.critical("critical message")

Here is the logging.conf file::

    [loggers]
    keys=root,simpleExample

    [handlers]
    keys=consoleHandler

    [formatters]
    keys=simpleFormatter

    [logger_root]
    level=DEBUG
    handlers=consoleHandler

    [logger_simpleExample]
    level=DEBUG
    handlers=consoleHandler
    qualname=simpleExample
    propagate=0

    [handler_consoleHandler]
    class=StreamHandler
    level=DEBUG
    formatter=simpleFormatter
    args=(sys.stdout,)

    [formatter_simpleFormatter]
    format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
    datefmt=

The output is nearly identical to that of the non-config-file-based example::

    $ python simple_logging_config.py
    2005-03-19 15:38:55,977 - simpleExample - DEBUG - debug message
    2005-03-19 15:38:55,979 - simpleExample - INFO - info message
    2005-03-19 15:38:56,054 - simpleExample - WARNING - warn message
    2005-03-19 15:38:56,055 - simpleExample - ERROR - error message
    2005-03-19 15:38:56,130 - simpleExample - CRITICAL - critical message

You can see that the config file approach has a few advantages over the Python
code approach, mainly separation of configuration and code and the ability of
noncoders to easily modify the logging properties.

Note that the class names referenced in config files need to be either relative
to the logging module, or absolute values which can be resolved using normal
import mechanisms. Thus, you could use either
:class:`handlers.WatchedFileHandler` (relative to the logging module) or
``mypackage.mymodule.MyHandler`` (for a class defined in package ``mypackage``
and module ``mymodule``, where ``mypackage`` is available on the Python import
path).

In Python 3.2, a new means of configuring logging has been introduced, using
dictionaries to hold configuration information. This provides a superset of the
functionality of the config-file-based approach outlined above, and is the
recommended configuration method for new applications and deployments. Because
a Python dictionary is used to hold configuration information, and since you
can populate that dictionary using different means, you have more options for
configuration. For example, you can use a configuration file in JSON format,
or, if you have access to YAML processing functionality, a file in YAML
format, to populate the configuration dictionary. Or, of course, you can
construct the dictionary in Python code, receive it in pickled form over a
socket, or use whatever approach makes sense for your application.

Here's an example of the same configuration as above, in YAML format for
the new dictionary-based approach::

    version: 1
    formatters:
      simple:
        format: format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
    handlers:
      console:
        class: logging.StreamHandler
        level: DEBUG
        formatter: simple
        stream: ext://sys.stdout
    loggers:
      simpleExample:
        level: DEBUG
        handlers: [console]
        propagate: no
    root:
        level: DEBUG
        handlers: [console]

For more information about logging using a dictionary, see
:ref:`logging-config-api`.

.. _library-config:

Configuring Logging for a Library
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

When developing a library which uses logging, some consideration needs to be
given to its configuration. If the using application does not use logging, and
library code makes logging calls, then a one-off message "No handlers could be
found for logger X.Y.Z" is printed to the console. This message is intended
to catch mistakes in logging configuration, but will confuse an application
developer who is not aware of logging by the library.

In addition to documenting how a library uses logging, a good way to configure
library logging so that it does not cause a spurious message is to add a
handler which does nothing. This avoids the message being printed, since a
handler will be found: it just doesn't produce any output. If the library user
configures logging for application use, presumably that configuration will add
some handlers, and if levels are suitably configured then logging calls made
in library code will send output to those handlers, as normal.

A do-nothing handler can be simply defined as follows::

    import logging

    class NullHandler(logging.Handler):
        def emit(self, record):
            pass

An instance of this handler should be added to the top-level logger of the
logging namespace used by the library. If all logging by a library *foo* is
done using loggers with names matching "foo.x.y", then the code::

    import logging

    h = NullHandler()
    logging.getLogger("foo").addHandler(h)

should have the desired effect. If an organisation produces a number of
libraries, then the logger name specified can be "orgname.foo" rather than
just "foo".

**PLEASE NOTE:** It is strongly advised that you *do not add any handlers other
than* :class:`NullHandler` *to your library's loggers*. This is because the
configuration of handlers is the prerogative of the application developer who
uses your library. The application developer knows their target audience and
what handlers are most appropriate for their application: if you add handlers
"under the hood", you might well interfere with their ability to carry out
unit tests and deliver logs which suit their requirements.

.. versionadded:: 3.1

The :class:`NullHandler` class was not present in previous versions, but is
now included, so that it need not be defined in library code.



Logging Levels
--------------

The numeric values of logging levels are given in the following table. These are
primarily of interest if you want to define your own levels, and need them to
have specific values relative to the predefined levels. If you define a level
with the same numeric value, it overwrites the predefined value; the predefined
name is lost.

+--------------+---------------+
| Level        | Numeric value |
+==============+===============+
| ``CRITICAL`` | 50            |
+--------------+---------------+
| ``ERROR``    | 40            |
+--------------+---------------+
| ``WARNING``  | 30            |
+--------------+---------------+
| ``INFO``     | 20            |
+--------------+---------------+
| ``DEBUG``    | 10            |
+--------------+---------------+
| ``NOTSET``   | 0             |
+--------------+---------------+

Levels can also be associated with loggers, being set either by the developer or
through loading a saved logging configuration. When a logging method is called
on a logger, the logger compares its own level with the level associated with
the method call. If the logger's level is higher than the method call's, no
logging message is actually generated. This is the basic mechanism controlling
the verbosity of logging output.

Logging messages are encoded as instances of the :class:`LogRecord` class. When
a logger decides to actually log an event, a :class:`LogRecord` instance is
created from the logging message.

Logging messages are subjected to a dispatch mechanism through the use of
:dfn:`handlers`, which are instances of subclasses of the :class:`Handler`
class. Handlers are responsible for ensuring that a logged message (in the form
of a :class:`LogRecord`) ends up in a particular location (or set of locations)
which is useful for the target audience for that message (such as end users,
support desk staff, system administrators, developers). Handlers are passed
:class:`LogRecord` instances intended for particular destinations. Each logger
can have zero, one or more handlers associated with it (via the
:meth:`addHandler` method of :class:`Logger`). In addition to any handlers
directly associated with a logger, *all handlers associated with all ancestors
of the logger* are called to dispatch the message (unless the *propagate* flag
for a logger is set to a false value, at which point the passing to ancestor
handlers stops).

Just as for loggers, handlers can have levels associated with them. A handler's
level acts as a filter in the same way as a logger's level does. If a handler
decides to actually dispatch an event, the :meth:`emit` method is used to send
the message to its destination. Most user-defined subclasses of :class:`Handler`
will need to override this :meth:`emit`.

.. _custom-levels:

Custom Levels
^^^^^^^^^^^^^

Defining your own levels is possible, but should not be necessary, as the
existing levels have been chosen on the basis of practical experience.
However, if you are convinced that you need custom levels, great care should
be exercised when doing this, and it is possibly *a very bad idea to define
custom levels if you are developing a library*. That's because if multiple
library authors all define their own custom levels, there is a chance that
the logging output from such multiple libraries used together will be
difficult for the using developer to control and/or interpret, because a
given numeric value might mean different things for different libraries.


Useful Handlers
---------------

In addition to the base :class:`Handler` class, many useful subclasses are
provided:

#. :class:`StreamHandler` instances send messages to streams (file-like
   objects).

#. :class:`FileHandler` instances send messages to disk files.

.. module:: logging.handlers

#. :class:`BaseRotatingHandler` is the base class for handlers that
   rotate log files at a certain point. It is not meant to be  instantiated
   directly. Instead, use :class:`RotatingFileHandler` or
   :class:`TimedRotatingFileHandler`.

#. :class:`RotatingFileHandler` instances send messages to disk
   files, with support for maximum log file sizes and log file rotation.

#. :class:`TimedRotatingFileHandler` instances send messages to
   disk files, rotating the log file at certain timed intervals.

#. :class:`SocketHandler` instances send messages to TCP/IP
   sockets.

#. :class:`DatagramHandler` instances send messages to UDP
   sockets.

#. :class:`SMTPHandler` instances send messages to a designated
   email address.

#. :class:`SysLogHandler` instances send messages to a Unix
   syslog daemon, possibly on a remote machine.

#. :class:`NTEventLogHandler` instances send messages to a
   Windows NT/2000/XP event log.

#. :class:`MemoryHandler` instances send messages to a buffer
   in memory, which is flushed whenever specific criteria are met.

#. :class:`HTTPHandler` instances send messages to an HTTP
   server using either ``GET`` or ``POST`` semantics.

#. :class:`WatchedFileHandler` instances watch the file they are
   logging to. If the file changes, it is closed and reopened using the file
   name. This handler is only useful on Unix-like systems; Windows does not
   support the underlying mechanism used.

#. :class:`QueueHandler` instances send messages to a queue, such as
   those implemented in the :mod:`queue` or :mod:`multiprocessing` modules.

.. currentmodule:: logging

#. :class:`NullHandler` instances do nothing with error messages. They are used
   by library developers who want to use logging, but want to avoid the "No
   handlers could be found for logger XXX" message which can be displayed if
   the library user has not configured logging. See :ref:`library-config` for
   more information.

.. versionadded:: 3.1

The :class:`NullHandler` class was not present in previous versions.

.. versionadded:: 3.2

The :class:`QueueHandler` class was not present in previous versions.

The :class:`NullHandler`, :class:`StreamHandler` and :class:`FileHandler`
classes are defined in the core logging package. The other handlers are
defined in a sub- module, :mod:`logging.handlers`. (There is also another
sub-module, :mod:`logging.config`, for configuration functionality.)

Logged messages are formatted for presentation through instances of the
:class:`Formatter` class. They are initialized with a format string suitable for
use with the % operator and a dictionary.

For formatting multiple messages in a batch, instances of
:class:`BufferingFormatter` can be used. In addition to the format string (which
is applied to each message in the batch), there is provision for header and
trailer format strings.

When filtering based on logger level and/or handler level is not enough,
instances of :class:`Filter` can be added to both :class:`Logger` and
:class:`Handler` instances (through their :meth:`addFilter` method). Before
deciding to process a message further, both loggers and handlers consult all
their filters for permission. If any filter returns a false value, the message
is not processed further.

The basic :class:`Filter` functionality allows filtering by specific logger
name. If this feature is used, messages sent to the named logger and its
children are allowed through the filter, and all others dropped.

Module-Level Functions
----------------------

In addition to the classes described above, there are a number of module- level
functions.


.. function:: getLogger(name=None)

   Return a logger with the specified name or, if name is ``None``, return a
   logger which is the root logger of the hierarchy. If specified, the name is
   typically a dot-separated hierarchical name like *"a"*, *"a.b"* or *"a.b.c.d"*.
   Choice of these names is entirely up to the developer who is using logging.

   All calls to this function with a given name return the same logger instance.
   This means that logger instances never need to be passed between different parts
   of an application.


.. function:: getLoggerClass()

   Return either the standard :class:`Logger` class, or the last class passed to
   :func:`setLoggerClass`. This function may be called from within a new class
   definition, to ensure that installing a customised :class:`Logger` class will
   not undo customisations already applied by other code. For example::

      class MyLogger(logging.getLoggerClass()):
          # ... override behaviour here


.. function:: debug(msg, *args, **kwargs)

   Logs a message with level :const:`DEBUG` on the root logger. The *msg* is the
   message format string, and the *args* are the arguments which are merged into
   *msg* using the string formatting operator. (Note that this means that you can
   use keywords in the format string, together with a single dictionary argument.)

   There are three keyword arguments in *kwargs* which are inspected: *exc_info*
   which, if it does not evaluate as false, causes exception information to be
   added to the logging message. If an exception tuple (in the format returned by
   :func:`sys.exc_info`) is provided, it is used; otherwise, :func:`sys.exc_info`
   is called to get the exception information.

   The second optional keyword argument is *stack_info*, which defaults to
   False. If specified as True, stack information is added to the logging
   message, including the actual logging call. Note that this is not the same
   stack information as that displayed through specifying *exc_info*: The
   former is stack frames from the bottom of the stack up to the logging call
   in the current thread, whereas the latter is information about stack frames
   which have been unwound, following an exception, while searching for
   exception handlers.

   You can specify *stack_info* independently of *exc_info*, e.g. to just show
   how you got to a certain point in your code, even when no exceptions were
   raised. The stack frames are printed following a header line which says::

       Stack (most recent call last):

   This mimics the `Traceback (most recent call last):` which is used when
   displaying exception frames.

   The third optional keyword argument is *extra* which can be used to pass a
   dictionary which is used to populate the __dict__ of the LogRecord created for
   the logging event with user-defined attributes. These custom attributes can then
   be used as you like. For example, they could be incorporated into logged
   messages. For example::

      FORMAT = "%(asctime)-15s %(clientip)s %(user)-8s %(message)s"
      logging.basicConfig(format=FORMAT)
      d = {'clientip': '192.168.0.1', 'user': 'fbloggs'}
      logging.warning("Protocol problem: %s", "connection reset", extra=d)

   would print something like::

      2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

   The keys in the dictionary passed in *extra* should not clash with the keys used
   by the logging system. (See the :class:`Formatter` documentation for more
   information on which keys are used by the logging system.)

   If you choose to use these attributes in logged messages, you need to exercise
   some care. In the above example, for instance, the :class:`Formatter` has been
   set up with a format string which expects 'clientip' and 'user' in the attribute
   dictionary of the LogRecord. If these are missing, the message will not be
   logged because a string formatting exception will occur. So in this case, you
   always need to pass the *extra* dictionary with these keys.

   While this might be annoying, this feature is intended for use in specialized
   circumstances, such as multi-threaded servers where the same code executes in
   many contexts, and interesting conditions which arise are dependent on this
   context (such as remote client IP address and authenticated user name, in the
   above example). In such circumstances, it is likely that specialized
   :class:`Formatter`\ s would be used with particular :class:`Handler`\ s.

   .. versionadded:: 3.2
      The *stack_info* parameter was added.

.. function:: info(msg, *args, **kwargs)

   Logs a message with level :const:`INFO` on the root logger. The arguments are
   interpreted as for :func:`debug`.


.. function:: warning(msg, *args, **kwargs)

   Logs a message with level :const:`WARNING` on the root logger. The arguments are
   interpreted as for :func:`debug`.


.. function:: error(msg, *args, **kwargs)

   Logs a message with level :const:`ERROR` on the root logger. The arguments are
   interpreted as for :func:`debug`.


.. function:: critical(msg, *args, **kwargs)

   Logs a message with level :const:`CRITICAL` on the root logger. The arguments
   are interpreted as for :func:`debug`.


.. function:: exception(msg, *args)

   Logs a message with level :const:`ERROR` on the root logger. The arguments are
   interpreted as for :func:`debug`. Exception info is added to the logging
   message. This function should only be called from an exception handler.

.. function:: log(level, msg, *args, **kwargs)

   Logs a message with level *level* on the root logger. The other arguments are
   interpreted as for :func:`debug`.

   PLEASE NOTE: The above module-level functions which delegate to the root
   logger should *not* be used in threads, in versions of Python earlier than
   2.7.1 and 3.2, unless at least one handler has been added to the root
   logger *before* the threads are started. These convenience functions call
   :func:`basicConfig` to ensure that at least one handler is available; in
   earlier versions of Python, this can (under rare circumstances) lead to
   handlers being added multiple times to the root logger, which can in turn
   lead to multiple messages for the same event.

.. function:: disable(lvl)

   Provides an overriding level *lvl* for all loggers which takes precedence over
   the logger's own level. When the need arises to temporarily throttle logging
   output down across the whole application, this function can be useful. Its
   effect is to disable all logging calls of severity *lvl* and below, so that
   if you call it with a value of INFO, then all INFO and DEBUG events would be
   discarded, whereas those of severity WARNING and above would be processed
   according to the logger's effective level.


.. function:: addLevelName(lvl, levelName)

   Associates level *lvl* with text *levelName* in an internal dictionary, which is
   used to map numeric levels to a textual representation, for example when a
   :class:`Formatter` formats a message. This function can also be used to define
   your own levels. The only constraints are that all levels used must be
   registered using this function, levels should be positive integers and they
   should increase in increasing order of severity.

   NOTE: If you are thinking of defining your own levels, please see the section
   on :ref:`custom-levels`.

.. function:: getLevelName(lvl)

   Returns the textual representation of logging level *lvl*. If the level is one
   of the predefined levels :const:`CRITICAL`, :const:`ERROR`, :const:`WARNING`,
   :const:`INFO` or :const:`DEBUG` then you get the corresponding string. If you
   have associated levels with names using :func:`addLevelName` then the name you
   have associated with *lvl* is returned. If a numeric value corresponding to one
   of the defined levels is passed in, the corresponding string representation is
   returned. Otherwise, the string "Level %s" % lvl is returned.


.. function:: makeLogRecord(attrdict)

   Creates and returns a new :class:`LogRecord` instance whose attributes are
   defined by *attrdict*. This function is useful for taking a pickled
   :class:`LogRecord` attribute dictionary, sent over a socket, and reconstituting
   it as a :class:`LogRecord` instance at the receiving end.


.. function:: basicConfig(**kwargs)

   Does basic configuration for the logging system by creating a
   :class:`StreamHandler` with a default :class:`Formatter` and adding it to the
   root logger. The functions :func:`debug`, :func:`info`, :func:`warning`,
   :func:`error` and :func:`critical` will call :func:`basicConfig` automatically
   if no handlers are defined for the root logger.

   This function does nothing if the root logger already has handlers
   configured for it.

   PLEASE NOTE: This function should be called from the main thread
   before other threads are started. In versions of Python prior to
   2.7.1 and 3.2, if this function is called from multiple threads,
   it is possible (in rare circumstances) that a handler will be added
   to the root logger more than once, leading to unexpected results
   such as messages being duplicated in the log.

   The following keyword arguments are supported.

   +--------------+---------------------------------------------+
   | Format       | Description                                 |
   +==============+=============================================+
   | ``filename`` | Specifies that a FileHandler be created,    |
   |              | using the specified filename, rather than a |
   |              | StreamHandler.                              |
   +--------------+---------------------------------------------+
   | ``filemode`` | Specifies the mode to open the file, if     |
   |              | filename is specified (if filemode is       |
   |              | unspecified, it defaults to 'a').           |
   +--------------+---------------------------------------------+
   | ``format``   | Use the specified format string for the     |
   |              | handler.                                    |
   +--------------+---------------------------------------------+
   | ``datefmt``  | Use the specified date/time format.         |
   +--------------+---------------------------------------------+
   | ``style``    | If ``format`` is specified, use this style  |
   |              | for the format string. One of '%', '{' or   |
   |              | '$' for %-formatting, :meth:`str.format` or |
   |              | :class:`string.Template` respectively, and  |
   |              | defaulting to '%' if not specified.         |
   +--------------+---------------------------------------------+
   | ``level``    | Set the root logger level to the specified  |
   |              | level.                                      |
   +--------------+---------------------------------------------+
   | ``stream``   | Use the specified stream to initialize the  |
   |              | StreamHandler. Note that this argument is   |
   |              | incompatible with 'filename' - if both are  |
   |              | present, 'stream' is ignored.               |
   +--------------+---------------------------------------------+

   .. versionchanged:: 3.2
      The ``style`` argument was added.


.. function:: shutdown()

   Informs the logging system to perform an orderly shutdown by flushing and
   closing all handlers. This should be called at application exit and no
   further use of the logging system should be made after this call.


.. function:: setLoggerClass(klass)

   Tells the logging system to use the class *klass* when instantiating a logger.
   The class should define :meth:`__init__` such that only a name argument is
   required, and the :meth:`__init__` should call :meth:`Logger.__init__`. This
   function is typically called before any loggers are instantiated by applications
   which need to use custom logger behavior.


.. seealso::

   :pep:`282` - A Logging System
      The proposal which described this feature for inclusion in the Python standard
      library.

   `Original Python logging package <http://www.red-dove.com/python_logging.html>`_
      This is the original source for the :mod:`logging` package.  The version of the
      package available from this site is suitable for use with Python 1.5.2, 2.1.x
      and 2.2.x, which do not include the :mod:`logging` package in the standard
      library.

.. _logger:

Logger Objects
--------------

Loggers have the following attributes and methods. Note that Loggers are never
instantiated directly, but always through the module-level function
``logging.getLogger(name)``.

.. class:: Logger

.. attribute:: Logger.propagate

   If this evaluates to false, logging messages are not passed by this logger or by
   its child loggers to the handlers of higher level (ancestor) loggers. The
   constructor sets this attribute to 1.


.. method:: Logger.setLevel(lvl)

   Sets the threshold for this logger to *lvl*. Logging messages which are less
   severe than *lvl* will be ignored. When a logger is created, the level is set to
   :const:`NOTSET` (which causes all messages to be processed when the logger is
   the root logger, or delegation to the parent when the logger is a non-root
   logger). Note that the root logger is created with level :const:`WARNING`.

   The term "delegation to the parent" means that if a logger has a level of
   NOTSET, its chain of ancestor loggers is traversed until either an ancestor with
   a level other than NOTSET is found, or the root is reached.

   If an ancestor is found with a level other than NOTSET, then that ancestor's
   level is treated as the effective level of the logger where the ancestor search
   began, and is used to determine how a logging event is handled.

   If the root is reached, and it has a level of NOTSET, then all messages will be
   processed. Otherwise, the root's level will be used as the effective level.


.. method:: Logger.isEnabledFor(lvl)

   Indicates if a message of severity *lvl* would be processed by this logger.
   This method checks first the module-level level set by
   ``logging.disable(lvl)`` and then the logger's effective level as determined
   by :meth:`getEffectiveLevel`.


.. method:: Logger.getEffectiveLevel()

   Indicates the effective level for this logger. If a value other than
   :const:`NOTSET` has been set using :meth:`setLevel`, it is returned. Otherwise,
   the hierarchy is traversed towards the root until a value other than
   :const:`NOTSET` is found, and that value is returned.


.. method:: Logger.getChild(suffix)

   Returns a logger which is a descendant to this logger, as determined by the suffix.
   Thus, ``logging.getLogger('abc').getChild('def.ghi')`` would return the same
   logger as would be returned by ``logging.getLogger('abc.def.ghi')``. This is a
   convenience method, useful when the parent logger is named using e.g. ``__name__``
   rather than a literal string.

   .. versionadded:: 3.2


.. method:: Logger.debug(msg, *args, **kwargs)

   Logs a message with level :const:`DEBUG` on this logger. The *msg* is the
   message format string, and the *args* are the arguments which are merged into
   *msg* using the string formatting operator. (Note that this means that you can
   use keywords in the format string, together with a single dictionary argument.)

   There are three keyword arguments in *kwargs* which are inspected: *exc_info*
   which, if it does not evaluate as false, causes exception information to be
   added to the logging message. If an exception tuple (in the format returned by
   :func:`sys.exc_info`) is provided, it is used; otherwise, :func:`sys.exc_info`
   is called to get the exception information.

   The second optional keyword argument is *stack_info*, which defaults to
   False. If specified as True, stack information is added to the logging
   message, including the actual logging call. Note that this is not the same
   stack information as that displayed through specifying *exc_info*: The
   former is stack frames from the bottom of the stack up to the logging call
   in the current thread, whereas the latter is information about stack frames
   which have been unwound, following an exception, while searching for
   exception handlers.

   You can specify *stack_info* independently of *exc_info*, e.g. to just show
   how you got to a certain point in your code, even when no exceptions were
   raised. The stack frames are printed following a header line which says::

       Stack (most recent call last):

   This mimics the `Traceback (most recent call last):` which is used when
   displaying exception frames.

   The third keyword argument is *extra* which can be used to pass a
   dictionary which is used to populate the __dict__ of the LogRecord created for
   the logging event with user-defined attributes. These custom attributes can then
   be used as you like. For example, they could be incorporated into logged
   messages. For example::

      FORMAT = "%(asctime)-15s %(clientip)s %(user)-8s %(message)s"
      logging.basicConfig(format=FORMAT)
      d = { 'clientip' : '192.168.0.1', 'user' : 'fbloggs' }
      logger = logging.getLogger("tcpserver")
      logger.warning("Protocol problem: %s", "connection reset", extra=d)

   would print something like  ::

      2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

   The keys in the dictionary passed in *extra* should not clash with the keys used
   by the logging system. (See the :class:`Formatter` documentation for more
   information on which keys are used by the logging system.)

   If you choose to use these attributes in logged messages, you need to exercise
   some care. In the above example, for instance, the :class:`Formatter` has been
   set up with a format string which expects 'clientip' and 'user' in the attribute
   dictionary of the LogRecord. If these are missing, the message will not be
   logged because a string formatting exception will occur. So in this case, you
   always need to pass the *extra* dictionary with these keys.

   While this might be annoying, this feature is intended for use in specialized
   circumstances, such as multi-threaded servers where the same code executes in
   many contexts, and interesting conditions which arise are dependent on this
   context (such as remote client IP address and authenticated user name, in the
   above example). In such circumstances, it is likely that specialized
   :class:`Formatter`\ s would be used with particular :class:`Handler`\ s.

   .. versionadded:: 3.2
      The *stack_info* parameter was added.


.. method:: Logger.info(msg, *args, **kwargs)

   Logs a message with level :const:`INFO` on this logger. The arguments are
   interpreted as for :meth:`debug`.


.. method:: Logger.warning(msg, *args, **kwargs)

   Logs a message with level :const:`WARNING` on this logger. The arguments are
   interpreted as for :meth:`debug`.


.. method:: Logger.error(msg, *args, **kwargs)

   Logs a message with level :const:`ERROR` on this logger. The arguments are
   interpreted as for :meth:`debug`.


.. method:: Logger.critical(msg, *args, **kwargs)

   Logs a message with level :const:`CRITICAL` on this logger. The arguments are
   interpreted as for :meth:`debug`.


.. method:: Logger.log(lvl, msg, *args, **kwargs)

   Logs a message with integer level *lvl* on this logger. The other arguments are
   interpreted as for :meth:`debug`.


.. method:: Logger.exception(msg, *args)

   Logs a message with level :const:`ERROR` on this logger. The arguments are
   interpreted as for :meth:`debug`. Exception info is added to the logging
   message. This method should only be called from an exception handler.


.. method:: Logger.addFilter(filt)

   Adds the specified filter *filt* to this logger.


.. method:: Logger.removeFilter(filt)

   Removes the specified filter *filt* from this logger.


.. method:: Logger.filter(record)

   Applies this logger's filters to the record and returns a true value if the
   record is to be processed.


.. method:: Logger.addHandler(hdlr)

   Adds the specified handler *hdlr* to this logger.


.. method:: Logger.removeHandler(hdlr)

   Removes the specified handler *hdlr* from this logger.


.. method:: Logger.findCaller(stack_info=False)

   Finds the caller's source filename and line number. Returns the filename, line
   number, function name and stack information as a 4-element tuple. The stack
   information is returned as *None* unless *stack_info* is *True*.


.. method:: Logger.handle(record)

   Handles a record by passing it to all handlers associated with this logger and
   its ancestors (until a false value of *propagate* is found). This method is used
   for unpickled records received from a socket, as well as those created locally.
   Logger-level filtering is applied using :meth:`~Logger.filter`.


.. method:: Logger.makeRecord(name, lvl, fn, lno, msg, args, exc_info, func=None, extra=None, sinfo=None)

   This is a factory method which can be overridden in subclasses to create
   specialized :class:`LogRecord` instances.

.. method:: Logger.hasHandlers()

   Checks to see if this logger has any handlers configured. This is done by
   looking for handlers in this logger and its parents in the logger hierarchy.
   Returns True if a handler was found, else False. The method stops searching
   up the hierarchy whenever a logger with the "propagate" attribute set to
   False is found - that will be the last logger which is checked for the
   existence of handlers.

.. versionadded:: 3.2

The :meth:`hasHandlers` method was not present in previous versions.

.. _minimal-example:

Basic example
-------------

The :mod:`logging` package provides a lot of flexibility, and its configuration
can appear daunting.  This section demonstrates that simple use of the logging
package is possible.

The simplest example shows logging to the console::

   import logging

   logging.debug('A debug message')
   logging.info('Some information')
   logging.warning('A shot across the bows')

If you run the above script, you'll see this::

   WARNING:root:A shot across the bows

Because no particular logger was specified, the system used the root logger. The
debug and info messages didn't appear because by default, the root logger is
configured to only handle messages with a severity of WARNING or above. The
message format is also a configuration default, as is the output destination of
the messages - ``sys.stderr``. The severity level, the message format and
destination can be easily changed, as shown in the example below::

   import logging

   logging.basicConfig(level=logging.DEBUG,
                       format='%(asctime)s %(levelname)s %(message)s',
                       filename='myapp.log',
                       filemode='w')
   logging.debug('A debug message')
   logging.info('Some information')
   logging.warning('A shot across the bows')

The :meth:`basicConfig` method is used to change the configuration defaults,
which results in output (written to ``myapp.log``) which should look
something like the following::

   2004-07-02 13:00:08,743 DEBUG A debug message
   2004-07-02 13:00:08,743 INFO Some information
   2004-07-02 13:00:08,743 WARNING A shot across the bows

This time, all messages with a severity of DEBUG or above were handled, and the
format of the messages was also changed, and output went to the specified file
rather than the console.

.. XXX logging should probably be updated for new string formatting!

Formatting uses the old Python string formatting - see section
:ref:`old-string-formatting`. The format string takes the following common
specifiers. For a complete list of specifiers, consult the :class:`Formatter`
documentation.

+-------------------+-----------------------------------------------+
| Format            | Description                                   |
+===================+===============================================+
| ``%(name)s``      | Name of the logger (logging channel).         |
+-------------------+-----------------------------------------------+
| ``%(levelname)s`` | Text logging level for the message            |
|                   | (``'DEBUG'``, ``'INFO'``, ``'WARNING'``,      |
|                   | ``'ERROR'``, ``'CRITICAL'``).                 |
+-------------------+-----------------------------------------------+
| ``%(asctime)s``   | Human-readable time when the                  |
|                   | :class:`LogRecord` was created.  By default   |
|                   | this is of the form "2003-07-08 16:49:45,896" |
|                   | (the numbers after the comma are millisecond  |
|                   | portion of the time).                         |
+-------------------+-----------------------------------------------+
| ``%(message)s``   | The logged message.                           |
+-------------------+-----------------------------------------------+

To change the date/time format, you can pass an additional keyword parameter,
*datefmt*, as in the following::

   import logging

   logging.basicConfig(level=logging.DEBUG,
                       format='%(asctime)s %(levelname)-8s %(message)s',
                       datefmt='%a, %d %b %Y %H:%M:%S',
                       filename='/temp/myapp.log',
                       filemode='w')
   logging.debug('A debug message')
   logging.info('Some information')
   logging.warning('A shot across the bows')

which would result in output like ::

   Fri, 02 Jul 2004 13:06:18 DEBUG    A debug message
   Fri, 02 Jul 2004 13:06:18 INFO     Some information
   Fri, 02 Jul 2004 13:06:18 WARNING  A shot across the bows

The date format string follows the requirements of :func:`strftime` - see the
documentation for the :mod:`time` module.

If, instead of sending logging output to the console or a file, you'd rather use
a file-like object which you have created separately, you can pass it to
:func:`basicConfig` using the *stream* keyword argument. Note that if both
*stream* and *filename* keyword arguments are passed, the *stream* argument is
ignored.

Of course, you can put variable information in your output. To do this, simply
have the message be a format string and pass in additional arguments containing
the variable information, as in the following example::

   import logging

   logging.basicConfig(level=logging.DEBUG,
                       format='%(asctime)s %(levelname)-8s %(message)s',
                       datefmt='%a, %d %b %Y %H:%M:%S',
                       filename='/temp/myapp.log',
                       filemode='w')
   logging.error('Pack my box with %d dozen %s', 5, 'liquor jugs')

which would result in ::

   Wed, 21 Jul 2004 15:35:16 ERROR    Pack my box with 5 dozen liquor jugs


.. _multiple-destinations:

Logging to multiple destinations
--------------------------------

Let's say you want to log to console and file with different message formats and
in differing circumstances. Say you want to log messages with levels of DEBUG
and higher to file, and those messages at level INFO and higher to the console.
Let's also assume that the file should contain timestamps, but the console
messages should not. Here's how you can achieve this::

   import logging

   # set up logging to file - see previous section for more details
   logging.basicConfig(level=logging.DEBUG,
                       format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
                       datefmt='%m-%d %H:%M',
                       filename='/temp/myapp.log',
                       filemode='w')
   # define a Handler which writes INFO messages or higher to the sys.stderr
   console = logging.StreamHandler()
   console.setLevel(logging.INFO)
   # set a format which is simpler for console use
   formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s')
   # tell the handler to use this format
   console.setFormatter(formatter)
   # add the handler to the root logger
   logging.getLogger('').addHandler(console)

   # Now, we can log to the root logger, or any other logger. First the root...
   logging.info('Jackdaws love my big sphinx of quartz.')

   # Now, define a couple of other loggers which might represent areas in your
   # application:

   logger1 = logging.getLogger('myapp.area1')
   logger2 = logging.getLogger('myapp.area2')

   logger1.debug('Quick zephyrs blow, vexing daft Jim.')
   logger1.info('How quickly daft jumping zebras vex.')
   logger2.warning('Jail zesty vixen who grabbed pay from quack.')
   logger2.error('The five boxing wizards jump quickly.')

When you run this, on the console you will see ::

   root        : INFO     Jackdaws love my big sphinx of quartz.
   myapp.area1 : INFO     How quickly daft jumping zebras vex.
   myapp.area2 : WARNING  Jail zesty vixen who grabbed pay from quack.
   myapp.area2 : ERROR    The five boxing wizards jump quickly.

and in the file you will see something like ::

   10-22 22:19 root         INFO     Jackdaws love my big sphinx of quartz.
   10-22 22:19 myapp.area1  DEBUG    Quick zephyrs blow, vexing daft Jim.
   10-22 22:19 myapp.area1  INFO     How quickly daft jumping zebras vex.
   10-22 22:19 myapp.area2  WARNING  Jail zesty vixen who grabbed pay from quack.
   10-22 22:19 myapp.area2  ERROR    The five boxing wizards jump quickly.

As you can see, the DEBUG message only shows up in the file. The other messages
are sent to both destinations.

This example uses console and file handlers, but you can use any number and
combination of handlers you choose.

.. _logging-exceptions:

Exceptions raised during logging
--------------------------------

The logging package is designed to swallow exceptions which occur while logging
in production. This is so that errors which occur while handling logging events
- such as logging misconfiguration, network or other similar errors - do not
cause the application using logging to terminate prematurely.

:class:`SystemExit` and :class:`KeyboardInterrupt` exceptions are never
swallowed. Other exceptions which occur during the :meth:`emit` method of a
:class:`Handler` subclass are passed to its :meth:`handleError` method.

The default implementation of :meth:`handleError` in :class:`Handler` checks
to see if a module-level variable, :data:`raiseExceptions`, is set. If set, a
traceback is printed to :data:`sys.stderr`. If not set, the exception is swallowed.

**Note:** The default value of :data:`raiseExceptions` is ``True``. This is because
during development, you typically want to be notified of any exceptions that
occur. It's advised that you set :data:`raiseExceptions` to ``False`` for production
usage.

.. _context-info:

Adding contextual information to your logging output
----------------------------------------------------

Sometimes you want logging output to contain contextual information in
addition to the parameters passed to the logging call. For example, in a
networked application, it may be desirable to log client-specific information
in the log (e.g. remote client's username, or IP address). Although you could
use the *extra* parameter to achieve this, it's not always convenient to pass
the information in this way. While it might be tempting to create
:class:`Logger` instances on a per-connection basis, this is not a good idea
because these instances are not garbage collected. While this is not a problem
in practice, when the number of :class:`Logger` instances is dependent on the
level of granularity you want to use in logging an application, it could
be hard to manage if the number of :class:`Logger` instances becomes
effectively unbounded.


Using LoggerAdapters to impart contextual information
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

An easy way in which you can pass contextual information to be output along
with logging event information is to use the :class:`LoggerAdapter` class.
This class is designed to look like a :class:`Logger`, so that you can call
:meth:`debug`, :meth:`info`, :meth:`warning`, :meth:`error`,
:meth:`exception`, :meth:`critical` and :meth:`log`. These methods have the
same signatures as their counterparts in :class:`Logger`, so you can use the
two types of instances interchangeably.

When you create an instance of :class:`LoggerAdapter`, you pass it a
:class:`Logger` instance and a dict-like object which contains your contextual
information. When you call one of the logging methods on an instance of
:class:`LoggerAdapter`, it delegates the call to the underlying instance of
:class:`Logger` passed to its constructor, and arranges to pass the contextual
information in the delegated call. Here's a snippet from the code of
:class:`LoggerAdapter`::

    def debug(self, msg, *args, **kwargs):
        """
        Delegate a debug call to the underlying logger, after adding
        contextual information from this adapter instance.
        """
        msg, kwargs = self.process(msg, kwargs)
        self.logger.debug(msg, *args, **kwargs)

The :meth:`process` method of :class:`LoggerAdapter` is where the contextual
information is added to the logging output. It's passed the message and
keyword arguments of the logging call, and it passes back (potentially)
modified versions of these to use in the call to the underlying logger. The
default implementation of this method leaves the message alone, but inserts
an "extra" key in the keyword argument whose value is the dict-like object
passed to the constructor. Of course, if you had passed an "extra" keyword
argument in the call to the adapter, it will be silently overwritten.

The advantage of using "extra" is that the values in the dict-like object are
merged into the :class:`LogRecord` instance's __dict__, allowing you to use
customized strings with your :class:`Formatter` instances which know about
the keys of the dict-like object. If you need a different method, e.g. if you
want to prepend or append the contextual information to the message string,
you just need to subclass :class:`LoggerAdapter` and override :meth:`process`
to do what you need. Here's an example script which uses this class, which
also illustrates what dict-like behaviour is needed from an arbitrary
"dict-like" object for use in the constructor::

   import logging

   class ConnInfo:
       """
       An example class which shows how an arbitrary class can be used as
       the 'extra' context information repository passed to a LoggerAdapter.
       """

       def __getitem__(self, name):
           """
           To allow this instance to look like a dict.
           """
           from random import choice
           if name == "ip":
               result = choice(["127.0.0.1", "192.168.0.1"])
           elif name == "user":
               result = choice(["jim", "fred", "sheila"])
           else:
               result = self.__dict__.get(name, "?")
           return result

       def __iter__(self):
           """
           To allow iteration over keys, which will be merged into
           the LogRecord dict before formatting and output.
           """
           keys = ["ip", "user"]
           keys.extend(self.__dict__.keys())
           return keys.__iter__()

   if __name__ == "__main__":
       from random import choice
       levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
       a1 = logging.LoggerAdapter(logging.getLogger("a.b.c"),
                                  { "ip" : "123.231.231.123", "user" : "sheila" })
       logging.basicConfig(level=logging.DEBUG,
                           format="%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s")
       a1.debug("A debug message")
       a1.info("An info message with %s", "some parameters")
       a2 = logging.LoggerAdapter(logging.getLogger("d.e.f"), ConnInfo())
       for x in range(10):
           lvl = choice(levels)
           lvlname = logging.getLevelName(lvl)
           a2.log(lvl, "A message at %s level with %d %s", lvlname, 2, "parameters")

When this script is run, the output should look something like this::

   2008-01-18 14:49:54,023 a.b.c DEBUG    IP: 123.231.231.123 User: sheila   A debug message
   2008-01-18 14:49:54,023 a.b.c INFO     IP: 123.231.231.123 User: sheila   An info message with some parameters
   2008-01-18 14:49:54,023 d.e.f CRITICAL IP: 192.168.0.1     User: jim      A message at CRITICAL level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f INFO     IP: 192.168.0.1     User: jim      A message at INFO level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f WARNING  IP: 192.168.0.1     User: sheila   A message at WARNING level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f ERROR    IP: 127.0.0.1       User: fred     A message at ERROR level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f ERROR    IP: 127.0.0.1       User: sheila   A message at ERROR level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f WARNING  IP: 192.168.0.1     User: sheila   A message at WARNING level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f WARNING  IP: 192.168.0.1     User: jim      A message at WARNING level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f INFO     IP: 192.168.0.1     User: fred     A message at INFO level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f WARNING  IP: 192.168.0.1     User: sheila   A message at WARNING level with 2 parameters
   2008-01-18 14:49:54,033 d.e.f WARNING  IP: 127.0.0.1       User: jim      A message at WARNING level with 2 parameters


.. _filters-contextual:

Using Filters to impart contextual information
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

You can also add contextual information to log output using a user-defined
:class:`Filter`. ``Filter`` instances are allowed to modify the ``LogRecords``
passed to them, including adding additional attributes which can then be output
using a suitable format string, or if needed a custom :class:`Formatter`.

For example in a web application, the request being processed (or at least,
the interesting parts of it) can be stored in a threadlocal
(:class:`threading.local`) variable, and then accessed from a ``Filter`` to
add, say, information from the request - say, the remote IP address and remote
user's username - to the ``LogRecord``, using the attribute names 'ip' and
'user' as in the ``LoggerAdapter`` example above. In that case, the same format
string can be used to get similar output to that shown above. Here's an example
script::

    import logging
    from random import choice

    class ContextFilter(logging.Filter):
        """
        This is a filter which injects contextual information into the log.

        Rather than use actual contextual information, we just use random
        data in this demo.
        """

        USERS = ['jim', 'fred', 'sheila']
        IPS = ['123.231.231.123', '127.0.0.1', '192.168.0.1']

        def filter(self, record):

            record.ip = choice(ContextFilter.IPS)
            record.user = choice(ContextFilter.USERS)
            return True

    if __name__ == "__main__":
       levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
       a1 = logging.LoggerAdapter(logging.getLogger("a.b.c"),
                                  { "ip" : "123.231.231.123", "user" : "sheila" })
       logging.basicConfig(level=logging.DEBUG,
                           format="%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s")
       a1 = logging.getLogger("a.b.c")
       a2 = logging.getLogger("d.e.f")

       f = ContextFilter()
       a1.addFilter(f)
       a2.addFilter(f)
       a1.debug("A debug message")
       a1.info("An info message with %s", "some parameters")
       for x in range(10):
           lvl = choice(levels)
           lvlname = logging.getLevelName(lvl)
           a2.log(lvl, "A message at %s level with %d %s", lvlname, 2, "parameters")

which, when run, produces something like::

    2010-09-06 22:38:15,292 a.b.c DEBUG    IP: 123.231.231.123 User: fred     A debug message
    2010-09-06 22:38:15,300 a.b.c INFO     IP: 192.168.0.1     User: sheila   An info message with some parameters
    2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1       User: sheila   A message at CRITICAL level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f ERROR    IP: 127.0.0.1       User: jim      A message at ERROR level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f DEBUG    IP: 127.0.0.1       User: sheila   A message at DEBUG level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f ERROR    IP: 123.231.231.123 User: fred     A message at ERROR level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 192.168.0.1     User: jim      A message at CRITICAL level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1       User: sheila   A message at CRITICAL level with 2 parameters
    2010-09-06 22:38:15,300 d.e.f DEBUG    IP: 192.168.0.1     User: jim      A message at DEBUG level with 2 parameters
    2010-09-06 22:38:15,301 d.e.f ERROR    IP: 127.0.0.1       User: sheila   A message at ERROR level with 2 parameters
    2010-09-06 22:38:15,301 d.e.f DEBUG    IP: 123.231.231.123 User: fred     A message at DEBUG level with 2 parameters
    2010-09-06 22:38:15,301 d.e.f INFO     IP: 123.231.231.123 User: fred     A message at INFO level with 2 parameters


.. _multiple-processes:

Logging to a single file from multiple processes
------------------------------------------------

Although logging is thread-safe, and logging to a single file from multiple
threads in a single process *is* supported, logging to a single file from
*multiple processes* is *not* supported, because there is no standard way to
serialize access to a single file across multiple processes in Python. If you
need to log to a single file from multiple processes, one way of doing this is
to have all the processes log to a :class:`SocketHandler`, and have a separate
process which implements a socket server which reads from the socket and logs
to file. (If you prefer, you can dedicate one thread in one of the existing
processes to perform this function.) The following section documents this
approach in more detail and includes a working socket receiver which can be
used as a starting point for you to adapt in your own applications.

If you are using a recent version of Python which includes the
:mod:`multiprocessing` module, you could write your own handler which uses the
:class:`Lock` class from this module to serialize access to the file from
your processes. The existing :class:`FileHandler` and subclasses do not make
use of :mod:`multiprocessing` at present, though they may do so in the future.
Note that at present, the :mod:`multiprocessing` module does not provide
working lock functionality on all platforms (see
http://bugs.python.org/issue3770).

.. currentmodule:: logging.handlers

Alternatively, you can use a ``Queue`` and a :class:`QueueHandler` to send
all logging events to one of the processes in your multi-process application.
The following example script demonstrates how you can do this; in the example
a separate listener process listens for events sent by other processes and logs
them according to its own logging configuration. Although the example only
demonstrates one way of doing it (for example, you may want to use a listener
thread rather than a separate listener process - the implementation would be
analogous) it does allow for completely different logging configurations for
the listener and the other processes in your application, and can be used as
the basis for code meeting your own specific requirements::

    # You'll need these imports in your own code
    import logging
    import logging.handlers
    import multiprocessing

    # Next two import lines for this demo only
    from random import choice, random
    import time

    #
    # Because you'll want to define the logging configurations for listener and workers, the
    # listener and worker process functions take a configurer parameter which is a callable
    # for configuring logging for that process. These functions are also passed the queue,
    # which they use for communication.
    #
    # In practice, you can configure the listener however you want, but note that in this
    # simple example, the listener does not apply level or filter logic to received records.
    # In practice, you would probably want to do ths logic in the worker processes, to avoid
    # sending events which would be filtered out between processes.
    #
    # The size of the rotated files is made small so you can see the results easily.
    def listener_configurer():
        root = logging.getLogger()
        h = logging.handlers.RotatingFileHandler('/tmp/mptest.log', 'a', 300, 10)
        f = logging.Formatter('%(asctime)s %(processName)-10s %(name)s %(levelname)-8s %(message)s')
        h.setFormatter(f)
        root.addHandler(h)

    # This is the listener process top-level loop: wait for logging events
    # (LogRecords)on the queue and handle them, quit when you get a None for a
    # LogRecord.
    def listener_process(queue, configurer):
        configurer()
        while True:
            try:
                record = queue.get()
                if record is None: # We send this as a sentinel to tell the listener to quit.
                    break
                logger = logging.getLogger(record.name)
                logger.handle(record) # No level or filter logic applied - just do it!
            except (KeyboardInterrupt, SystemExit):
                raise
            except:
                import sys, traceback
                print >> sys.stderr, 'Whoops! Problem:'
                traceback.print_exc(file=sys.stderr)

    # Arrays used for random selections in this demo

    LEVELS = [logging.DEBUG, logging.INFO, logging.WARNING,
              logging.ERROR, logging.CRITICAL]

    LOGGERS = ['a.b.c', 'd.e.f']

    MESSAGES = [
        'Random message #1',
        'Random message #2',
        'Random message #3',
    ]

    # The worker configuration is done at the start of the worker process run.
    # Note that on Windows you can't rely on fork semantics, so each process
    # will run the logging configuration code when it starts.
    def worker_configurer(queue):
        h = logging.handlers.QueueHandler(queue) # Just the one handler needed
        root = logging.getLogger()
        root.addHandler(h)
        root.setLevel(logging.DEBUG) # send all messages, for demo; no other level or filter logic applied.

    # This is the worker process top-level loop, which just logs ten events with
    # random intervening delays before terminating.
    # The print messages are just so you know it's doing something!
    def worker_process(queue, configurer):
        configurer(queue)
        name = multiprocessing.current_process().name
        print('Worker started: %s' % name)
        for i in range(10):
            time.sleep(random())
            logger = logging.getLogger(choice(LOGGERS))
            level = choice(LEVELS)
            message = choice(MESSAGES)
            logger.log(level, message)
        print('Worker finished: %s' % name)

    # Here's where the demo gets orchestrated. Create the queue, create and start
    # the listener, create ten workers and start them, wait for them to finish,
    # then send a None to the queue to tell the listener to finish.
    def main():
        queue = multiprocessing.Queue(-1)
        listener = multiprocessing.Process(target=listener_process,
                                           args=(queue, listener_configurer))
        listener.start()
        workers = []
        for i in range(10):
            worker = multiprocessing.Process(target=worker_process,
                                           args=(queue, worker_configurer))
            workers.append(worker)
            worker.start()
        for w in workers:
            w.join()
        queue.put_nowait(None)
        listener.join()

    if __name__ == '__main__':
        main()


.. currentmodule:: logging


.. _network-logging:

Sending and receiving logging events across a network
-----------------------------------------------------

Let's say you want to send logging events across a network, and handle them at
the receiving end. A simple way of doing this is attaching a
:class:`SocketHandler` instance to the root logger at the sending end::

   import logging, logging.handlers

   rootLogger = logging.getLogger('')
   rootLogger.setLevel(logging.DEBUG)
   socketHandler = logging.handlers.SocketHandler('localhost',
                       logging.handlers.DEFAULT_TCP_LOGGING_PORT)
   # don't bother with a formatter, since a socket handler sends the event as
   # an unformatted pickle
   rootLogger.addHandler(socketHandler)

   # Now, we can log to the root logger, or any other logger. First the root...
   logging.info('Jackdaws love my big sphinx of quartz.')

   # Now, define a couple of other loggers which might represent areas in your
   # application:

   logger1 = logging.getLogger('myapp.area1')
   logger2 = logging.getLogger('myapp.area2')

   logger1.debug('Quick zephyrs blow, vexing daft Jim.')
   logger1.info('How quickly daft jumping zebras vex.')
   logger2.warning('Jail zesty vixen who grabbed pay from quack.')
   logger2.error('The five boxing wizards jump quickly.')

At the receiving end, you can set up a receiver using the :mod:`socketserver`
module. Here is a basic working example::

   import pickle
   import logging
   import logging.handlers
   import socketserver
   import struct


   class LogRecordStreamHandler(socketserver.StreamRequestHandler):
       """Handler for a streaming logging request.

       This basically logs the record using whatever logging policy is
       configured locally.
       """

       def handle(self):
           """
           Handle multiple requests - each expected to be a 4-byte length,
           followed by the LogRecord in pickle format. Logs the record
           according to whatever policy is configured locally.
           """
           while True:
               chunk = self.connection.recv(4)
               if len(chunk) < 4:
                   break
               slen = struct.unpack(">L", chunk)[0]
               chunk = self.connection.recv(slen)
               while len(chunk) < slen:
                   chunk = chunk + self.connection.recv(slen - len(chunk))
               obj = self.unPickle(chunk)
               record = logging.makeLogRecord(obj)
               self.handleLogRecord(record)

       def unPickle(self, data):
           return pickle.loads(data)

       def handleLogRecord(self, record):
           # if a name is specified, we use the named logger rather than the one
           # implied by the record.
           if self.server.logname is not None:
               name = self.server.logname
           else:
               name = record.name
           logger = logging.getLogger(name)
           # N.B. EVERY record gets logged. This is because Logger.handle
           # is normally called AFTER logger-level filtering. If you want
           # to do filtering, do it at the client end to save wasting
           # cycles and network bandwidth!
           logger.handle(record)

   class LogRecordSocketReceiver(socketserver.ThreadingTCPServer):
       """simple TCP socket-based logging receiver suitable for testing.
       """

       allow_reuse_address = 1

       def __init__(self, host='localhost',
                    port=logging.handlers.DEFAULT_TCP_LOGGING_PORT,
                    handler=LogRecordStreamHandler):
           socketserver.ThreadingTCPServer.__init__(self, (host, port), handler)
           self.abort = 0
           self.timeout = 1
           self.logname = None

       def serve_until_stopped(self):
           import select
           abort = 0
           while not abort:
               rd, wr, ex = select.select([self.socket.fileno()],
                                          [], [],
                                          self.timeout)
               if rd:
                   self.handle_request()
               abort = self.abort

   def main():
       logging.basicConfig(
           format="%(relativeCreated)5d %(name)-15s %(levelname)-8s %(message)s")
       tcpserver = LogRecordSocketReceiver()
       print("About to start TCP server...")
       tcpserver.serve_until_stopped()

   if __name__ == "__main__":
       main()

First run the server, and then the client. On the client side, nothing is
printed on the console; on the server side, you should see something like::

   About to start TCP server...
      59 root            INFO     Jackdaws love my big sphinx of quartz.
      59 myapp.area1     DEBUG    Quick zephyrs blow, vexing daft Jim.
      69 myapp.area1     INFO     How quickly daft jumping zebras vex.
      69 myapp.area2     WARNING  Jail zesty vixen who grabbed pay from quack.
      69 myapp.area2     ERROR    The five boxing wizards jump quickly.

Note that there are some security issues with pickle in some scenarios. If
these affect you, you can use an alternative serialization scheme by overriding
the :meth:`makePickle` method and implementing your alternative there, as
well as adapting the above script to use your alternative serialization.

.. _arbitrary-object-messages:

Using arbitrary objects as messages
-----------------------------------

In the preceding sections and examples, it has been assumed that the message
passed when logging the event is a string. However, this is not the only
possibility. You can pass an arbitrary object as a message, and its
:meth:`__str__` method will be called when the logging system needs to convert
it to a string representation. In fact, if you want to, you can avoid
computing a string representation altogether - for example, the
:class:`SocketHandler` emits an event by pickling it and sending it over the
wire.

Dealing with handlers that block
--------------------------------

.. currentmodule:: logging.handlers

Sometimes you have to get your logging handlers to do their work without
blocking the thread you’re logging from. This is common in Web applications,
though of course it also occurs in other scenarios.

A common culprit which demonstrates sluggish behaviour is the
:class:`SMTPHandler`: sending emails can take a long time, for a
number of reasons outside the developer’s control (for example, a poorly
performing mail or network infrastructure). But almost any network-based
handler can block: Even a :class:`SocketHandler` operation may do a
DNS query under the hood which is too slow (and this query can be deep in the
socket library code, below the Python layer, and outside your control).

One solution is to use a two-part approach. For the first part, attach only a
:class:`QueueHandler` to those loggers which are accessed from
performance-critical threads. They simply write to their queue, which can be
sized to a large enough capacity or initialized with no upper bound to their
size. The write to the queue will typically be accepted quickly, though you
will probably need to catch the :ref:`queue.Full` exception as a precaution
in your code. If you are a library developer who has performance-critical
threads in their code, be sure to document this (together with a suggestion to
attach only ``QueueHandlers`` to your loggers) for the benefit of other
developers who will use your code.

The second part of the solution is :class:`QueueListener`, which has been
designed as the counterpart to :class:`QueueHandler`.  A
:class:`QueueListener` is very simple: it’s passed a queue and some handlers,
and it fires up an internal thread which listens to its queue for LogRecords
sent from ``QueueHandlers`` (or any other source of ``LogRecords``, for that
matter). The ``LogRecords`` are removed from the queue and passed to the
handlers for processing.

The advantage of having a separate :class:`QueueListener` class is that you
can use the same instance to service multiple ``QueueHandlers``. This is more
resource-friendly than, say, having threaded versions of the existing handler
classes, which would eat up one thread per handler for no particular benefit.

An example of using these two classes follows (imports omitted)::

    que = queue.Queue(-1) # no limit on size
    queue_handler = QueueHandler(que)
    handler = logging.StreamHandler()
    listener = QueueListener(que, handler)
    root = logging.getLogger()
    root.addHandler(queue_handler)
    formatter = logging.Formatter('%(threadName)s: %(message)s')
    handler.setFormatter(formatter)
    listener.start()
    # The log output will display the thread which generated
    # the event (the main thread) rather than the internal
    # thread which monitors the internal queue. This is what
    # you want to happen.
    root.warning('Look out!')
    listener.stop()

which, when run, will produce::

    MainThread: Look out!


Optimization
------------

Formatting of message arguments is deferred until it cannot be avoided.
However, computing the arguments passed to the logging method can also be
expensive, and you may want to avoid doing it if the logger will just throw
away your event. To decide what to do, you can call the :meth:`isEnabledFor`
method which takes a level argument and returns true if the event would be
created by the Logger for that level of call. You can write code like this::

    if logger.isEnabledFor(logging.DEBUG):
        logger.debug("Message with %s, %s", expensive_func1(),
                                            expensive_func2())

so that if the logger's threshold is set above ``DEBUG``, the calls to
:func:`expensive_func1` and :func:`expensive_func2` are never made.

There are other optimizations which can be made for specific applications which
need more precise control over what logging information is collected. Here's a
list of things you can do to avoid processing during logging which you don't
need:

+-----------------------------------------------+----------------------------------------+
| What you don't want to collect                | How to avoid collecting it             |
+===============================================+========================================+
| Information about where calls were made from. | Set ``logging._srcfile`` to ``None``.  |
+-----------------------------------------------+----------------------------------------+
| Threading information.                        | Set ``logging.logThreads`` to ``0``.   |
+-----------------------------------------------+----------------------------------------+
| Process information.                          | Set ``logging.logProcesses`` to ``0``. |
+-----------------------------------------------+----------------------------------------+

Also note that the core logging module only includes the basic handlers. If
you don't import :mod:`logging.handlers` and :mod:`logging.config`, they won't
take up any memory.

.. _handler:

Handler Objects
---------------

Handlers have the following attributes and methods. Note that :class:`Handler`
is never instantiated directly; this class acts as a base for more useful
subclasses. However, the :meth:`__init__` method in subclasses needs to call
:meth:`Handler.__init__`.


.. method:: Handler.__init__(level=NOTSET)

   Initializes the :class:`Handler` instance by setting its level, setting the list
   of filters to the empty list and creating a lock (using :meth:`createLock`) for
   serializing access to an I/O mechanism.


.. method:: Handler.createLock()

   Initializes a thread lock which can be used to serialize access to underlying
   I/O functionality which may not be threadsafe.


.. method:: Handler.acquire()

   Acquires the thread lock created with :meth:`createLock`.


.. method:: Handler.release()

   Releases the thread lock acquired with :meth:`acquire`.


.. method:: Handler.setLevel(lvl)

   Sets the threshold for this handler to *lvl*. Logging messages which are less
   severe than *lvl* will be ignored. When a handler is created, the level is set
   to :const:`NOTSET` (which causes all messages to be processed).


.. method:: Handler.setFormatter(form)

   Sets the :class:`Formatter` for this handler to *form*.


.. method:: Handler.addFilter(filt)

   Adds the specified filter *filt* to this handler.


.. method:: Handler.removeFilter(filt)

   Removes the specified filter *filt* from this handler.


.. method:: Handler.filter(record)

   Applies this handler's filters to the record and returns a true value if the
   record is to be processed.


.. method:: Handler.flush()

   Ensure all logging output has been flushed. This version does nothing and is
   intended to be implemented by subclasses.


.. method:: Handler.close()

   Tidy up any resources used by the handler. This version does no output but
   removes the handler from an internal list of handlers which is closed when
   :func:`shutdown` is called. Subclasses should ensure that this gets called
   from overridden :meth:`close` methods.


.. method:: Handler.handle(record)

   Conditionally emits the specified logging record, depending on filters which may
   have been added to the handler. Wraps the actual emission of the record with
   acquisition/release of the I/O thread lock.


.. method:: Handler.handleError(record)

   This method should be called from handlers when an exception is encountered
   during an :meth:`emit` call. By default it does nothing, which means that
   exceptions get silently ignored. This is what is mostly wanted for a logging
   system - most users will not care about errors in the logging system, they are
   more interested in application errors. You could, however, replace this with a
   custom handler if you wish. The specified record is the one which was being
   processed when the exception occurred.


.. method:: Handler.format(record)

   Do formatting for a record - if a formatter is set, use it. Otherwise, use the
   default formatter for the module.


.. method:: Handler.emit(record)

   Do whatever it takes to actually log the specified logging record. This version
   is intended to be implemented by subclasses and so raises a
   :exc:`NotImplementedError`.


.. _stream-handler:

StreamHandler
^^^^^^^^^^^^^

The :class:`StreamHandler` class, located in the core :mod:`logging` package,
sends logging output to streams such as *sys.stdout*, *sys.stderr* or any
file-like object (or, more precisely, any object which supports :meth:`write`
and :meth:`flush` methods).


.. currentmodule:: logging

.. class:: StreamHandler(stream=None)

   Returns a new instance of the :class:`StreamHandler` class. If *stream* is
   specified, the instance will use it for logging output; otherwise, *sys.stderr*
   will be used.


   .. method:: emit(record)

      If a formatter is specified, it is used to format the record. The record
      is then written to the stream with a trailing newline. If exception
      information is present, it is formatted using
      :func:`traceback.print_exception` and appended to the stream.


   .. method:: flush()

      Flushes the stream by calling its :meth:`flush` method. Note that the
      :meth:`close` method is inherited from :class:`Handler` and so does
      no output, so an explicit :meth:`flush` call may be needed at times.

.. versionchanged:: 3.2
   The ``StreamHandler`` class now has a ``terminator`` attribute, default
   value ``"\n"``, which is used as the terminator when writing a formatted
   record to a stream. If you don't want this newline termination, you can
   set the handler instance's ``terminator`` attribute to the empty string.

.. _file-handler:

FileHandler
^^^^^^^^^^^

The :class:`FileHandler` class, located in the core :mod:`logging` package,
sends logging output to a disk file.  It inherits the output functionality from
:class:`StreamHandler`.


.. class:: FileHandler(filename, mode='a', encoding=None, delay=False)

   Returns a new instance of the :class:`FileHandler` class. The specified file is
   opened and used as the stream for logging. If *mode* is not specified,
   :const:`'a'` is used.  If *encoding* is not *None*, it is used to open the file
   with that encoding.  If *delay* is true, then file opening is deferred until the
   first call to :meth:`emit`. By default, the file grows indefinitely.


   .. method:: close()

      Closes the file.


   .. method:: emit(record)

      Outputs the record to the file.

.. _null-handler:

NullHandler
^^^^^^^^^^^

.. versionadded:: 3.1

The :class:`NullHandler` class, located in the core :mod:`logging` package,
does not do any formatting or output. It is essentially a "no-op" handler
for use by library developers.


.. class:: NullHandler()

   Returns a new instance of the :class:`NullHandler` class.


   .. method:: emit(record)

      This method does nothing.

   .. method:: handle(record)

      This method does nothing.

   .. method:: createLock()

      This method returns ``None`` for the lock, since there is no
      underlying I/O to which access needs to be serialized.


See :ref:`library-config` for more information on how to use
:class:`NullHandler`.

.. _watched-file-handler:

WatchedFileHandler
^^^^^^^^^^^^^^^^^^

.. currentmodule:: logging.handlers

The :class:`WatchedFileHandler` class, located in the :mod:`logging.handlers`
module, is a :class:`FileHandler` which watches the file it is logging to. If
the file changes, it is closed and reopened using the file name.

A file change can happen because of usage of programs such as *newsyslog* and
*logrotate* which perform log file rotation. This handler, intended for use
under Unix/Linux, watches the file to see if it has changed since the last emit.
(A file is deemed to have changed if its device or inode have changed.) If the
file has changed, the old file stream is closed, and the file opened to get a
new stream.

This handler is not appropriate for use under Windows, because under Windows
open log files cannot be moved or renamed - logging opens the files with
exclusive locks - and so there is no need for such a handler. Furthermore,
*ST_INO* is not supported under Windows; :func:`stat` always returns zero for
this value.


.. class:: WatchedFileHandler(filename[,mode[, encoding[, delay]]])

   Returns a new instance of the :class:`WatchedFileHandler` class. The specified
   file is opened and used as the stream for logging. If *mode* is not specified,
   :const:`'a'` is used.  If *encoding* is not *None*, it is used to open the file
   with that encoding.  If *delay* is true, then file opening is deferred until the
   first call to :meth:`emit`.  By default, the file grows indefinitely.


   .. method:: emit(record)

      Outputs the record to the file, but first checks to see if the file has
      changed.  If it has, the existing stream is flushed and closed and the
      file opened again, before outputting the record to the file.

.. _rotating-file-handler:

RotatingFileHandler
^^^^^^^^^^^^^^^^^^^

The :class:`RotatingFileHandler` class, located in the :mod:`logging.handlers`
module, supports rotation of disk log files.


.. class:: RotatingFileHandler(filename, mode='a', maxBytes=0, backupCount=0, encoding=None, delay=0)

   Returns a new instance of the :class:`RotatingFileHandler` class. The specified
   file is opened and used as the stream for logging. If *mode* is not specified,
   ``'a'`` is used.  If *encoding* is not *None*, it is used to open the file
   with that encoding.  If *delay* is true, then file opening is deferred until the
   first call to :meth:`emit`.  By default, the file grows indefinitely.

   You can use the *maxBytes* and *backupCount* values to allow the file to
   :dfn:`rollover` at a predetermined size. When the size is about to be exceeded,
   the file is closed and a new file is silently opened for output. Rollover occurs
   whenever the current log file is nearly *maxBytes* in length; if *maxBytes* is
   zero, rollover never occurs.  If *backupCount* is non-zero, the system will save
   old log files by appending the extensions ".1", ".2" etc., to the filename. For
   example, with a *backupCount* of 5 and a base file name of :file:`app.log`, you
   would get :file:`app.log`, :file:`app.log.1`, :file:`app.log.2`, up to
   :file:`app.log.5`. The file being written to is always :file:`app.log`.  When
   this file is filled, it is closed and renamed to :file:`app.log.1`, and if files
   :file:`app.log.1`, :file:`app.log.2`, etc.  exist, then they are renamed to
   :file:`app.log.2`, :file:`app.log.3` etc.  respectively.


   .. method:: doRollover()

      Does a rollover, as described above.


   .. method:: emit(record)

      Outputs the record to the file, catering for rollover as described
      previously.

.. _timed-rotating-file-handler:

TimedRotatingFileHandler
^^^^^^^^^^^^^^^^^^^^^^^^

The :class:`TimedRotatingFileHandler` class, located in the
:mod:`logging.handlers` module, supports rotation of disk log files at certain
timed intervals.


.. class:: TimedRotatingFileHandler(filename, when='h', interval=1, backupCount=0, encoding=None, delay=False, utc=False)

   Returns a new instance of the :class:`TimedRotatingFileHandler` class. The
   specified file is opened and used as the stream for logging. On rotating it also
   sets the filename suffix. Rotating happens based on the product of *when* and
   *interval*.

   You can use the *when* to specify the type of *interval*. The list of possible
   values is below.  Note that they are not case sensitive.

   +----------------+-----------------------+
   | Value          | Type of interval      |
   +================+=======================+
   | ``'S'``        | Seconds               |
   +----------------+-----------------------+
   | ``'M'``        | Minutes               |
   +----------------+-----------------------+
   | ``'H'``        | Hours                 |
   +----------------+-----------------------+
   | ``'D'``        | Days                  |
   +----------------+-----------------------+
   | ``'W'``        | Week day (0=Monday)   |
   +----------------+-----------------------+
   | ``'midnight'`` | Roll over at midnight |
   +----------------+-----------------------+

   The system will save old log files by appending extensions to the filename.
   The extensions are date-and-time based, using the strftime format
   ``%Y-%m-%d_%H-%M-%S`` or a leading portion thereof, depending on the
   rollover interval.

   When computing the next rollover time for the first time (when the handler
   is created), the last modification time of an existing log file, or else
   the current time, is used to compute when the next rotation will occur.

   If the *utc* argument is true, times in UTC will be used; otherwise
   local time is used.

   If *backupCount* is nonzero, at most *backupCount* files
   will be kept, and if more would be created when rollover occurs, the oldest
   one is deleted. The deletion logic uses the interval to determine which
   files to delete, so changing the interval may leave old files lying around.

   If *delay* is true, then file opening is deferred until the first call to
   :meth:`emit`.


   .. method:: doRollover()

      Does a rollover, as described above.


   .. method:: emit(record)

      Outputs the record to the file, catering for rollover as described above.


.. _socket-handler:

SocketHandler
^^^^^^^^^^^^^

The :class:`SocketHandler` class, located in the :mod:`logging.handlers` module,
sends logging output to a network socket. The base class uses a TCP socket.


.. class:: SocketHandler(host, port)

   Returns a new instance of the :class:`SocketHandler` class intended to
   communicate with a remote machine whose address is given by *host* and *port*.


   .. method:: close()

      Closes the socket.


   .. method:: emit()

      Pickles the record's attribute dictionary and writes it to the socket in
      binary format. If there is an error with the socket, silently drops the
      packet. If the connection was previously lost, re-establishes the
      connection. To unpickle the record at the receiving end into a
      :class:`LogRecord`, use the :func:`makeLogRecord` function.


   .. method:: handleError()

      Handles an error which has occurred during :meth:`emit`. The most likely
      cause is a lost connection. Closes the socket so that we can retry on the
      next event.


   .. method:: makeSocket()

      This is a factory method which allows subclasses to define the precise
      type of socket they want. The default implementation creates a TCP socket
      (:const:`socket.SOCK_STREAM`).


   .. method:: makePickle(record)

      Pickles the record's attribute dictionary in binary format with a length
      prefix, and returns it ready for transmission across the socket.

      Note that pickles aren't completely secure. If you are concerned about
      security, you may want to override this method to implement a more secure
      mechanism. For example, you can sign pickles using HMAC and then verify
      them on the receiving end, or alternatively you can disable unpickling of
      global objects on the receiving end.

   .. method:: send(packet)

      Send a pickled string *packet* to the socket. This function allows for
      partial sends which can happen when the network is busy.


.. _datagram-handler:

DatagramHandler
^^^^^^^^^^^^^^^

The :class:`DatagramHandler` class, located in the :mod:`logging.handlers`
module, inherits from :class:`SocketHandler` to support sending logging messages
over UDP sockets.


.. class:: DatagramHandler(host, port)

   Returns a new instance of the :class:`DatagramHandler` class intended to
   communicate with a remote machine whose address is given by *host* and *port*.


   .. method:: emit()

      Pickles the record's attribute dictionary and writes it to the socket in
      binary format. If there is an error with the socket, silently drops the
      packet. To unpickle the record at the receiving end into a
      :class:`LogRecord`, use the :func:`makeLogRecord` function.


   .. method:: makeSocket()

      The factory method of :class:`SocketHandler` is here overridden to create
      a UDP socket (:const:`socket.SOCK_DGRAM`).


   .. method:: send(s)

      Send a pickled string to a socket.


.. _syslog-handler:

SysLogHandler
^^^^^^^^^^^^^

The :class:`SysLogHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to a remote or local Unix syslog.


.. class:: SysLogHandler(address=('localhost', SYSLOG_UDP_PORT), facility=LOG_USER, socktype=socket.SOCK_DGRAM)

   Returns a new instance of the :class:`SysLogHandler` class intended to
   communicate with a remote Unix machine whose address is given by *address* in
   the form of a ``(host, port)`` tuple.  If *address* is not specified,
   ``('localhost', 514)`` is used.  The address is used to open a socket.  An
   alternative to providing a ``(host, port)`` tuple is providing an address as a
   string, for example "/dev/log". In this case, a Unix domain socket is used to
   send the message to the syslog. If *facility* is not specified,
   :const:`LOG_USER` is used. The type of socket opened depends on the
   *socktype* argument, which defaults to :const:`socket.SOCK_DGRAM` and thus
   opens a UDP socket. To open a TCP socket (for use with the newer syslog
   daemons such as rsyslog), specify a value of :const:`socket.SOCK_STREAM`.

   Note that if your server is not listening on UDP port 514,
   :class:`SysLogHandler` may appear not to work. In that case, check what
   address you should be using for a domain socket - it's system dependent.
   For example, on Linux it's usually "/dev/log" but on OS/X it's
   "/var/run/syslog". You'll need to check your platform and use the
   appropriate address (you may need to do this check at runtime if your
   application needs to run on several platforms). On Windows, you pretty
   much have to use the UDP option.

   .. versionchanged:: 3.2
      *socktype* was added.


   .. method:: close()

      Closes the socket to the remote host.


   .. method:: emit(record)

      The record is formatted, and then sent to the syslog server. If exception
      information is present, it is *not* sent to the server.


   .. method:: encodePriority(facility, priority)

      Encodes the facility and priority into an integer. You can pass in strings
      or integers - if strings are passed, internal mapping dictionaries are
      used to convert them to integers.

      The symbolic ``LOG_`` values are defined in :class:`SysLogHandler` and
      mirror the values defined in the ``sys/syslog.h`` header file.

      **Priorities**

      +--------------------------+---------------+
      | Name (string)            | Symbolic value|
      +==========================+===============+
      | ``alert``                | LOG_ALERT     |
      +--------------------------+---------------+
      | ``crit`` or ``critical`` | LOG_CRIT      |
      +--------------------------+---------------+
      | ``debug``                | LOG_DEBUG     |
      +--------------------------+---------------+
      | ``emerg`` or ``panic``   | LOG_EMERG     |
      +--------------------------+---------------+
      | ``err`` or ``error``     | LOG_ERR       |
      +--------------------------+---------------+
      | ``info``                 | LOG_INFO      |
      +--------------------------+---------------+
      | ``notice``               | LOG_NOTICE    |
      +--------------------------+---------------+
      | ``warn`` or ``warning``  | LOG_WARNING   |
      +--------------------------+---------------+

      **Facilities**

      +---------------+---------------+
      | Name (string) | Symbolic value|
      +===============+===============+
      | ``auth``      | LOG_AUTH      |
      +---------------+---------------+
      | ``authpriv``  | LOG_AUTHPRIV  |
      +---------------+---------------+
      | ``cron``      | LOG_CRON      |
      +---------------+---------------+
      | ``daemon``    | LOG_DAEMON    |
      +---------------+---------------+
      | ``ftp``       | LOG_FTP       |
      +---------------+---------------+
      | ``kern``      | LOG_KERN      |
      +---------------+---------------+
      | ``lpr``       | LOG_LPR       |
      +---------------+---------------+
      | ``mail``      | LOG_MAIL      |
      +---------------+---------------+
      | ``news``      | LOG_NEWS      |
      +---------------+---------------+
      | ``syslog``    | LOG_SYSLOG    |
      +---------------+---------------+
      | ``user``      | LOG_USER      |
      +---------------+---------------+
      | ``uucp``      | LOG_UUCP      |
      +---------------+---------------+
      | ``local0``    | LOG_LOCAL0    |
      +---------------+---------------+
      | ``local1``    | LOG_LOCAL1    |
      +---------------+---------------+
      | ``local2``    | LOG_LOCAL2    |
      +---------------+---------------+
      | ``local3``    | LOG_LOCAL3    |
      +---------------+---------------+
      | ``local4``    | LOG_LOCAL4    |
      +---------------+---------------+
      | ``local5``    | LOG_LOCAL5    |
      +---------------+---------------+
      | ``local6``    | LOG_LOCAL6    |
      +---------------+---------------+
      | ``local7``    | LOG_LOCAL7    |
      +---------------+---------------+

   .. method:: mapPriority(levelname)

      Maps a logging level name to a syslog priority name.
      You may need to override this if you are using custom levels, or
      if the default algorithm is not suitable for your needs. The
      default algorithm maps ``DEBUG``, ``INFO``, ``WARNING``, ``ERROR`` and
      ``CRITICAL`` to the equivalent syslog names, and all other level
      names to "warning".

.. _nt-eventlog-handler:

NTEventLogHandler
^^^^^^^^^^^^^^^^^

The :class:`NTEventLogHandler` class, located in the :mod:`logging.handlers`
module, supports sending logging messages to a local Windows NT, Windows 2000 or
Windows XP event log. Before you can use it, you need Mark Hammond's Win32
extensions for Python installed.


.. class:: NTEventLogHandler(appname, dllname=None, logtype='Application')

   Returns a new instance of the :class:`NTEventLogHandler` class. The *appname* is
   used to define the application name as it appears in the event log. An
   appropriate registry entry is created using this name. The *dllname* should give
   the fully qualified pathname of a .dll or .exe which contains message
   definitions to hold in the log (if not specified, ``'win32service.pyd'`` is used
   - this is installed with the Win32 extensions and contains some basic
   placeholder message definitions. Note that use of these placeholders will make
   your event logs big, as the entire message source is held in the log. If you
   want slimmer logs, you have to pass in the name of your own .dll or .exe which
   contains the message definitions you want to use in the event log). The
   *logtype* is one of ``'Application'``, ``'System'`` or ``'Security'``, and
   defaults to ``'Application'``.


   .. method:: close()

      At this point, you can remove the application name from the registry as a
      source of event log entries. However, if you do this, you will not be able
      to see the events as you intended in the Event Log Viewer - it needs to be
      able to access the registry to get the .dll name. The current version does
      not do this.


   .. method:: emit(record)

      Determines the message ID, event category and event type, and then logs
      the message in the NT event log.


   .. method:: getEventCategory(record)

      Returns the event category for the record. Override this if you want to
      specify your own categories. This version returns 0.


   .. method:: getEventType(record)

      Returns the event type for the record. Override this if you want to
      specify your own types. This version does a mapping using the handler's
      typemap attribute, which is set up in :meth:`__init__` to a dictionary
      which contains mappings for :const:`DEBUG`, :const:`INFO`,
      :const:`WARNING`, :const:`ERROR` and :const:`CRITICAL`. If you are using
      your own levels, you will either need to override this method or place a
      suitable dictionary in the handler's *typemap* attribute.


   .. method:: getMessageID(record)

      Returns the message ID for the record. If you are using your own messages,
      you could do this by having the *msg* passed to the logger being an ID
      rather than a format string. Then, in here, you could use a dictionary
      lookup to get the message ID. This version returns 1, which is the base
      message ID in :file:`win32service.pyd`.

.. _smtp-handler:

SMTPHandler
^^^^^^^^^^^

The :class:`SMTPHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to an email address via SMTP.


.. class:: SMTPHandler(mailhost, fromaddr, toaddrs, subject, credentials=None)

   Returns a new instance of the :class:`SMTPHandler` class. The instance is
   initialized with the from and to addresses and subject line of the email. The
   *toaddrs* should be a list of strings. To specify a non-standard SMTP port, use
   the (host, port) tuple format for the *mailhost* argument. If you use a string,
   the standard SMTP port is used. If your SMTP server requires authentication, you
   can specify a (username, password) tuple for the *credentials* argument.


   .. method:: emit(record)

      Formats the record and sends it to the specified addressees.


   .. method:: getSubject(record)

      If you want to specify a subject line which is record-dependent, override
      this method.

.. _memory-handler:

MemoryHandler
^^^^^^^^^^^^^

The :class:`MemoryHandler` class, located in the :mod:`logging.handlers` module,
supports buffering of logging records in memory, periodically flushing them to a
:dfn:`target` handler. Flushing occurs whenever the buffer is full, or when an
event of a certain severity or greater is seen.

:class:`MemoryHandler` is a subclass of the more general
:class:`BufferingHandler`, which is an abstract class. This buffers logging
records in memory. Whenever each record is added to the buffer, a check is made
by calling :meth:`shouldFlush` to see if the buffer should be flushed.  If it
should, then :meth:`flush` is expected to do the needful.


.. class:: BufferingHandler(capacity)

   Initializes the handler with a buffer of the specified capacity.


   .. method:: emit(record)

      Appends the record to the buffer. If :meth:`shouldFlush` returns true,
      calls :meth:`flush` to process the buffer.


   .. method:: flush()

      You can override this to implement custom flushing behavior. This version
      just zaps the buffer to empty.


   .. method:: shouldFlush(record)

      Returns true if the buffer is up to capacity. This method can be
      overridden to implement custom flushing strategies.


.. class:: MemoryHandler(capacity, flushLevel=ERROR, target=None)

   Returns a new instance of the :class:`MemoryHandler` class. The instance is
   initialized with a buffer size of *capacity*. If *flushLevel* is not specified,
   :const:`ERROR` is used. If no *target* is specified, the target will need to be
   set using :meth:`setTarget` before this handler does anything useful.


   .. method:: close()

      Calls :meth:`flush`, sets the target to :const:`None` and clears the
      buffer.


   .. method:: flush()

      For a :class:`MemoryHandler`, flushing means just sending the buffered
      records to the target, if there is one. The buffer is also cleared when
      this happens. Override if you want different behavior.


   .. method:: setTarget(target)

      Sets the target handler for this handler.


   .. method:: shouldFlush(record)

      Checks for buffer full or a record at the *flushLevel* or higher.


.. _http-handler:

HTTPHandler
^^^^^^^^^^^

The :class:`HTTPHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to a Web server, using either ``GET`` or
``POST`` semantics.


.. class:: HTTPHandler(host, url, method='GET', secure=False, credentials=None)

   Returns a new instance of the :class:`HTTPHandler` class. The *host* can be
   of the form ``host:port``, should you need to use a specific port number.
   If no *method* is specified, ``GET`` is used. If *secure* is True, an HTTPS
   connection will be used. If *credentials* is specified, it should be a
   2-tuple consisting of userid and password, which will be placed in an HTTP
   'Authorization' header using Basic authentication. If you specify
   credentials, you should also specify secure=True so that your userid and
   password are not passed in cleartext across the wire.


   .. method:: emit(record)

      Sends the record to the Web server as a percent-encoded dictionary.


.. _queue-handler:


QueueHandler
^^^^^^^^^^^^

The :class:`QueueHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to a queue, such as those implemented in the
:mod:`queue` or :mod:`multiprocessing` modules.

Along with the :class:`QueueListener` class, :class:`QueueHandler` can be used
to let handlers do their work on a separate thread from the one which does the
logging. This is important in Web applications and also other service
applications where threads servicing clients need to respond as quickly as
possible, while any potentially slow operations (such as sending an email via
:class:`SMTPHandler`) are done on a separate thread.

.. class:: QueueHandler(queue)

   Returns a new instance of the :class:`QueueHandler` class. The instance is
   initialized with the queue to send messages to. The queue can be any queue-
   like object; it's used as-is by the :meth:`enqueue` method, which needs
   to know how to send messages to it.


   .. method:: emit(record)

      Enqueues the result of preparing the LogRecord.

   .. method:: prepare(record)

      Prepares a record for queuing. The object returned by this
      method is enqueued.

      The base implementation formats the record to merge the message
      and arguments, and removes unpickleable items from the record
      in-place.

      You might want to override this method if you want to convert
      the record to a dict or JSON string, or send a modified copy
      of the record while leaving the original intact.

   .. method:: enqueue(record)

      Enqueues the record on the queue using ``put_nowait()``; you may
      want to override this if you want to use blocking behaviour, or a
      timeout, or a customised queue implementation.


.. versionadded:: 3.2

The :class:`QueueHandler` class was not present in previous versions.

.. queue-listener:

QueueListener
^^^^^^^^^^^^^

The :class:`QueueListener` class, located in the :mod:`logging.handlers`
module, supports receiving logging messages from a queue, such as those
implemented in the :mod:`queue` or :mod:`multiprocessing` modules. The
messages are received from a queue in an internal thread and passed, on
the same thread, to one or more handlers for processing.

Along with the :class:`QueueHandler` class, :class:`QueueListener` can be used
to let handlers do their work on a separate thread from the one which does the
logging. This is important in Web applications and also other service
applications where threads servicing clients need to respond as quickly as
possible, while any potentially slow operations (such as sending an email via
:class:`SMTPHandler`) are done on a separate thread.

.. class:: QueueListener(queue, *handlers)

   Returns a new instance of the :class:`QueueListener` class. The instance is
   initialized with the queue to send messages to and a list of handlers which
   will handle entries placed on the queue. The queue can be any queue-
   like object; it's passed as-is to the :meth:`dequeue` method, which needs
   to know how to get messages from it.

   .. method:: dequeue(block)

      Dequeues a record and return it, optionally blocking.

      The base implementation uses ``get()``. You may want to override this
      method if you want to use timeouts or work with custom queue
      implementations.

   .. method:: prepare(record)

      Prepare a record for handling.

      This implementation just returns the passed-in record. You may want to
      override this method if you need to do any custom marshalling or
      manipulation of the record before passing it to the handlers.

   .. method:: handle(record)

      Handle a record.

      This just loops through the handlers offering them the record
      to handle. The actual object passed to the handlers is that which
      is returned from :meth:`prepare`.

   .. method:: start()

      Starts the listener.

      This starts up a background thread to monitor the queue for
      LogRecords to process.

   .. method:: stop()

      Stops the listener.

      This asks the thread to terminate, and then waits for it to do so.
      Note that if you don't call this before your application exits, there
      may be some records still left on the queue, which won't be processed.

.. versionadded:: 3.2

The :class:`QueueListener` class was not present in previous versions.

.. _zeromq-handlers:

Subclassing QueueHandler
^^^^^^^^^^^^^^^^^^^^^^^^

You can use a :class:`QueueHandler` subclass to send messages to other kinds
of queues, for example a ZeroMQ "publish" socket. In the example below,the
socket is created separately and passed to the handler (as its 'queue')::

    import zmq # using pyzmq, the Python binding for ZeroMQ
    import json # for serializing records portably

    ctx = zmq.Context()
    sock = zmq.Socket(ctx, zmq.PUB) # or zmq.PUSH, or other suitable value
    sock.bind('tcp://*:5556') # or wherever

    class ZeroMQSocketHandler(QueueHandler):
        def enqueue(self, record):
            data = json.dumps(record.__dict__)
            self.queue.send(data)

    handler = ZeroMQSocketHandler(sock)


Of course there are other ways of organizing this, for example passing in the
data needed by the handler to create the socket::

    class ZeroMQSocketHandler(QueueHandler):
        def __init__(self, uri, socktype=zmq.PUB, ctx=None):
            self.ctx = ctx or zmq.Context()
            socket = zmq.Socket(self.ctx, socktype)
            socket.bind(uri)
            QueueHandler.__init__(self, socket)

        def enqueue(self, record):
            data = json.dumps(record.__dict__)
            self.queue.send(data)

        def close(self):
            self.queue.close()

Subclassing QueueListener
^^^^^^^^^^^^^^^^^^^^^^^^^

You can also subclass :class:`QueueListener` to get messages from other kinds
of queues, for example a ZeroMQ "subscribe" socket. Here's an example::

    class ZeroMQSocketListener(QueueListener):
        def __init__(self, uri, *handlers, **kwargs):
            self.ctx = kwargs.get('ctx') or zmq.Context()
            socket = zmq.Socket(self.ctx, zmq.SUB)
            socket.setsockopt(zmq.SUBSCRIBE, '') # subscribe to everything
            socket.connect(uri)

        def dequeue(self):
            msg = self.queue.recv()
            return logging.makeLogRecord(json.loads(msg))

.. _formatter-objects:

Formatter Objects
-----------------

.. currentmodule:: logging

:class:`Formatter`\ s have the following attributes and methods. They are
responsible for converting a :class:`LogRecord` to (usually) a string which can
be interpreted by either a human or an external system. The base
:class:`Formatter` allows a formatting string to be specified. If none is
supplied, the default value of ``'%(message)s'`` is used.

A Formatter can be initialized with a format string which makes use of knowledge
of the :class:`LogRecord` attributes - such as the default value mentioned above
making use of the fact that the user's message and arguments are pre-formatted
into a :class:`LogRecord`'s *message* attribute.  This format string contains
standard Python %-style mapping keys. See section :ref:`old-string-formatting`
for more information on string formatting.

Currently, the useful mapping keys in a :class:`LogRecord` are:

+-------------------------+-----------------------------------------------+
| Format                  | Description                                   |
+=========================+===============================================+
| ``%(name)s``            | Name of the logger (logging channel).         |
+-------------------------+-----------------------------------------------+
| ``%(levelno)s``         | Numeric logging level for the message         |
|                         | (:const:`DEBUG`, :const:`INFO`,               |
|                         | :const:`WARNING`, :const:`ERROR`,             |
|                         | :const:`CRITICAL`).                           |
+-------------------------+-----------------------------------------------+
| ``%(levelname)s``       | Text logging level for the message            |
|                         | (``'DEBUG'``, ``'INFO'``, ``'WARNING'``,      |
|                         | ``'ERROR'``, ``'CRITICAL'``).                 |
+-------------------------+-----------------------------------------------+
| ``%(pathname)s``        | Full pathname of the source file where the    |
|                         | logging call was issued (if available).       |
+-------------------------+-----------------------------------------------+
| ``%(filename)s``        | Filename portion of pathname.                 |
+-------------------------+-----------------------------------------------+
| ``%(module)s``          | Module (name portion of filename).            |
+-------------------------+-----------------------------------------------+
| ``%(funcName)s``        | Name of function containing the logging call. |
+-------------------------+-----------------------------------------------+
| ``%(lineno)d``          | Source line number where the logging call was |
|                         | issued (if available).                        |
+-------------------------+-----------------------------------------------+
| ``%(created)f``         | Time when the :class:`LogRecord` was created  |
|                         | (as returned by :func:`time.time`).           |
+-------------------------+-----------------------------------------------+
| ``%(relativeCreated)d`` | Time in milliseconds when the LogRecord was   |
|                         | created, relative to the time the logging     |
|                         | module was loaded.                            |
+-------------------------+-----------------------------------------------+
| ``%(asctime)s``         | Human-readable time when the                  |
|                         | :class:`LogRecord` was created.  By default   |
|                         | this is of the form "2003-07-08 16:49:45,896" |
|                         | (the numbers after the comma are millisecond  |
|                         | portion of the time).                         |
+-------------------------+-----------------------------------------------+
| ``%(msecs)d``           | Millisecond portion of the time when the      |
|                         | :class:`LogRecord` was created.               |
+-------------------------+-----------------------------------------------+
| ``%(thread)d``          | Thread ID (if available).                     |
+-------------------------+-----------------------------------------------+
| ``%(threadName)s``      | Thread name (if available).                   |
+-------------------------+-----------------------------------------------+
| ``%(process)d``         | Process ID (if available).                    |
+-------------------------+-----------------------------------------------+
| ``%(processName)s``     | Process name (if available).                  |
+-------------------------+-----------------------------------------------+
| ``%(message)s``         | The logged message, computed as ``msg %       |
|                         | args``.                                       |
+-------------------------+-----------------------------------------------+


.. class:: Formatter(fmt=None, datefmt=None)

   Returns a new instance of the :class:`Formatter` class.  The instance is
   initialized with a format string for the message as a whole, as well as a
   format string for the date/time portion of a message.  If no *fmt* is
   specified, ``'%(message)s'`` is used.  If no *datefmt* is specified, the
   ISO8601 date format is used.

   .. method:: format(record)

      The record's attribute dictionary is used as the operand to a string
      formatting operation. Returns the resulting string. Before formatting the
      dictionary, a couple of preparatory steps are carried out. The *message*
      attribute of the record is computed using *msg* % *args*. If the
      formatting string contains ``'(asctime)'``, :meth:`formatTime` is called
      to format the event time. If there is exception information, it is
      formatted using :meth:`formatException` and appended to the message. Note
      that the formatted exception information is cached in attribute
      *exc_text*. This is useful because the exception information can be
      pickled and sent across the wire, but you should be careful if you have
      more than one :class:`Formatter` subclass which customizes the formatting
      of exception information. In this case, you will have to clear the cached
      value after a formatter has done its formatting, so that the next
      formatter to handle the event doesn't use the cached value but
      recalculates it afresh.

      If stack information is available, it's appended after the exception
      information, using :meth:`formatStack` to transform it if necessary.


   .. method:: formatTime(record, datefmt=None)

      This method should be called from :meth:`format` by a formatter which
      wants to make use of a formatted time. This method can be overridden in
      formatters to provide for any specific requirement, but the basic behavior
      is as follows: if *datefmt* (a string) is specified, it is used with
      :func:`time.strftime` to format the creation time of the
      record. Otherwise, the ISO8601 format is used.  The resulting string is
      returned.


   .. method:: formatException(exc_info)

      Formats the specified exception information (a standard exception tuple as
      returned by :func:`sys.exc_info`) as a string. This default implementation
      just uses :func:`traceback.print_exception`. The resulting string is
      returned.

   .. method:: formatStack(stack_info)

      Formats the specified stack information (a string as returned by
      :func:`traceback.print_stack`, but with the last newline removed) as a
      string. This default implementation just returns the input value.

.. _filter:

Filter Objects
--------------

``Filters`` can be used by ``Handlers`` and ``Loggers`` for more sophisticated
filtering than is provided by levels. The base filter class only allows events
which are below a certain point in the logger hierarchy. For example, a filter
initialized with "A.B" will allow events logged by loggers "A.B", "A.B.C",
"A.B.C.D", "A.B.D" etc. but not "A.BB", "B.A.B" etc. If initialized with the
empty string, all events are passed.


.. class:: Filter(name='')

   Returns an instance of the :class:`Filter` class. If *name* is specified, it
   names a logger which, together with its children, will have its events allowed
   through the filter. If *name* is the empty string, allows every event.


   .. method:: filter(record)

      Is the specified record to be logged? Returns zero for no, nonzero for
      yes. If deemed appropriate, the record may be modified in-place by this
      method.

Note that filters attached to handlers are consulted whenever an event is
emitted by the handler, whereas filters attached to loggers are consulted
whenever an event is logged to the handler (using :meth:`debug`, :meth:`info`,
etc.) This means that events which have been generated by descendant loggers
will not be filtered by a logger's filter setting, unless the filter has also
been applied to those descendant loggers.

You don't actually need to subclass ``Filter``: you can pass any instance
which has a ``filter`` method with the same semantics.

.. versionchanged:: 3.2
   You don't need to create specialized ``Filter`` classes, or use other
   classes with a ``filter`` method: you can use a function (or other
   callable) as a filter. The filtering logic will check to see if the filter
   object has a ``filter`` attribute: if it does, it's assumed to be a
   ``Filter`` and its :meth:`~Filter.filter` method is called. Otherwise, it's
   assumed to be a callable and called with the record as the single
   parameter. The returned value should conform to that returned by
   :meth:`~Filter.filter`.

Other uses for filters
^^^^^^^^^^^^^^^^^^^^^^

Although filters are used primarily to filter records based on more
sophisticated criteria than levels, they get to see every record which is
processed by the handler or logger they're attached to: this can be useful if
you want to do things like counting how many records were processed by a
particular logger or handler, or adding, changing or removing attributes in
the LogRecord being processed. Obviously changing the LogRecord needs to be
done with some care, but it does allow the injection of contextual information
into logs (see :ref:`filters-contextual`).

.. _log-record:

LogRecord Objects
-----------------

:class:`LogRecord` instances are created automatically by the :class:`Logger`
every time something is logged, and can be created manually via
:func:`makeLogRecord` (for example, from a pickled event received over the
wire).


.. class:: LogRecord(name, lvl, pathname, lineno, msg, args, exc_info, func=None, sinfo=None)

   Contains all the information pertinent to the event being logged.

   The primary information is passed in :attr:`msg` and :attr:`args`, which
   are combined using ``msg % args`` to create the :attr:`message` field of the
   record.

   .. attribute:: args

      Tuple of arguments to be used in formatting :attr:`msg`.

   .. attribute:: exc_info

      Exception tuple (à la :func:`sys.exc_info`) or ``None`` if no exception
      information is available.

   .. attribute:: func

      Name of the function of origin (i.e. in which the logging call was made).

   .. attribute:: lineno

      Line number in the source file of origin.

   .. attribute:: lvl

      Numeric logging level.

   .. attribute:: message

      Bound to the result of :meth:`getMessage` when
      :meth:`Formatter.format(record)<Formatter.format>` is invoked.

   .. attribute:: msg

      User-supplied :ref:`format string<string-formatting>` or arbitrary object
      (see :ref:`arbitrary-object-messages`) used in :meth:`getMessage`.

   .. attribute:: name

      Name of the logger that emitted the record.

   .. attribute:: pathname

      Absolute pathname of the source file of origin.

   .. attribute:: stack_info

      Stack frame information (where available) from the bottom of the stack
      in the current thread, up to and including the stack frame of the
      logging call which resulted in the creation of this record.

   .. method:: getMessage()

      Returns the message for this :class:`LogRecord` instance after merging any
      user-supplied arguments with the message. If the user-supplied message
      argument to the logging call is not a string, :func:`str` is called on it to
      convert it to a string. This allows use of user-defined classes as
      messages, whose ``__str__`` method can return the actual format string to
      be used.

.. _logger-adapter:

LoggerAdapter Objects
---------------------

:class:`LoggerAdapter` instances are used to conveniently pass contextual
information into logging calls. For a usage example , see the section on
`adding contextual information to your logging output`__.

__ context-info_

.. class:: LoggerAdapter(logger, extra)

  Returns an instance of :class:`LoggerAdapter` initialized with an
  underlying :class:`Logger` instance and a dict-like object.

  .. method:: process(msg, kwargs)

    Modifies the message and/or keyword arguments passed to a logging call in
    order to insert contextual information. This implementation takes the object
    passed as *extra* to the constructor and adds it to *kwargs* using key
    'extra'. The return value is a (*msg*, *kwargs*) tuple which has the
    (possibly modified) versions of the arguments passed in.

In addition to the above, :class:`LoggerAdapter` supports the following
methods of :class:`Logger`, i.e. :meth:`debug`, :meth:`info`, :meth:`warning`,
:meth:`error`, :meth:`exception`, :meth:`critical`, :meth:`log`,
:meth:`isEnabledFor`, :meth:`getEffectiveLevel`, :meth:`setLevel`,
:meth:`hasHandlers`. These methods have the same signatures as their
counterparts in :class:`Logger`, so you can use the two types of instances
interchangeably.

.. versionchanged:: 3.2
   The :meth:`isEnabledFor`, :meth:`getEffectiveLevel`, :meth:`setLevel` and
   :meth:`hasHandlers` methods were added to :class:`LoggerAdapter`.  These
   methods delegate to the underlying logger.


Thread Safety
-------------

The logging module is intended to be thread-safe without any special work
needing to be done by its clients. It achieves this though using threading
locks; there is one lock to serialize access to the module's shared data, and
each handler also creates a lock to serialize access to its underlying I/O.

If you are implementing asynchronous signal handlers using the :mod:`signal`
module, you may not be able to use logging from within such handlers. This is
because lock implementations in the :mod:`threading` module are not always
re-entrant, and so cannot be invoked from such signal handlers.


Integration with the warnings module
------------------------------------

The :func:`captureWarnings` function can be used to integrate :mod:`logging`
with the :mod:`warnings` module.

.. function:: captureWarnings(capture)

   This function is used to turn the capture of warnings by logging on and
   off.

   If *capture* is ``True``, warnings issued by the :mod:`warnings` module will
   be redirected to the logging system. Specifically, a warning will be
   formatted using :func:`warnings.formatwarning` and the resulting string
   logged to a logger named "py.warnings" with a severity of `WARNING`.

   If *capture* is ``False``, the redirection of warnings to the logging system
   will stop, and warnings will be redirected to their original destinations
   (i.e. those in effect before `captureWarnings(True)` was called).


Configuration
-------------


.. _logging-config-api:

Configuration functions
^^^^^^^^^^^^^^^^^^^^^^^

The following functions configure the logging module. They are located in the
:mod:`logging.config` module.  Their use is optional --- you can configure the
logging module using these functions or by making calls to the main API (defined
in :mod:`logging` itself) and defining handlers which are declared either in
:mod:`logging` or :mod:`logging.handlers`.

.. function:: dictConfig(config)

    Takes the logging configuration from a dictionary.  The contents of
    this dictionary are described in :ref:`logging-config-dictschema`
    below.

    If an error is encountered during configuration, this function will
    raise a :exc:`ValueError`, :exc:`TypeError`, :exc:`AttributeError`
    or :exc:`ImportError` with a suitably descriptive message.  The
    following is a (possibly incomplete) list of conditions which will
    raise an error:

    * A ``level`` which is not a string or which is a string not
      corresponding to an actual logging level.
    * A ``propagate`` value which is not a boolean.
    * An id which does not have a corresponding destination.
    * A non-existent handler id found during an incremental call.
    * An invalid logger name.
    * Inability to resolve to an internal or external object.

    Parsing is performed by the :class:`DictConfigurator` class, whose
    constructor is passed the dictionary used for configuration, and
    has a :meth:`configure` method.  The :mod:`logging.config` module
    has a callable attribute :attr:`dictConfigClass`
    which is initially set to :class:`DictConfigurator`.
    You can replace the value of :attr:`dictConfigClass` with a
    suitable implementation of your own.

    :func:`dictConfig` calls :attr:`dictConfigClass` passing
    the specified dictionary, and then calls the :meth:`configure` method on
    the returned object to put the configuration into effect::

          def dictConfig(config):
              dictConfigClass(config).configure()

    For example, a subclass of :class:`DictConfigurator` could call
    ``DictConfigurator.__init__()`` in its own :meth:`__init__()`, then
    set up custom prefixes which would be usable in the subsequent
    :meth:`configure` call. :attr:`dictConfigClass` would be bound to
    this new subclass, and then :func:`dictConfig` could be called exactly as
    in the default, uncustomized state.

.. function:: fileConfig(fname[, defaults])

   Reads the logging configuration from a :mod:`configparser`\-format file named
   *fname*. This function can be called several times from an application,
   allowing an end user to select from various pre-canned
   configurations (if the developer provides a mechanism to present the choices
   and load the chosen configuration). Defaults to be passed to the ConfigParser
   can be specified in the *defaults* argument.


.. function:: listen(port=DEFAULT_LOGGING_CONFIG_PORT)

   Starts up a socket server on the specified port, and listens for new
   configurations. If no port is specified, the module's default
   :const:`DEFAULT_LOGGING_CONFIG_PORT` is used. Logging configurations will be
   sent as a file suitable for processing by :func:`fileConfig`. Returns a
   :class:`Thread` instance on which you can call :meth:`start` to start the
   server, and which you can :meth:`join` when appropriate. To stop the server,
   call :func:`stopListening`.

   To send a configuration to the socket, read in the configuration file and
   send it to the socket as a string of bytes preceded by a four-byte length
   string packed in binary using ``struct.pack('>L', n)``.


.. function:: stopListening()

   Stops the listening server which was created with a call to :func:`listen`.
   This is typically called before calling :meth:`join` on the return value from
   :func:`listen`.


.. _logging-config-dictschema:

Configuration dictionary schema
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Describing a logging configuration requires listing the various
objects to create and the connections between them; for example, you
may create a handler named "console" and then say that the logger
named "startup" will send its messages to the "console" handler.
These objects aren't limited to those provided by the :mod:`logging`
module because you might write your own formatter or handler class.
The parameters to these classes may also need to include external
objects such as ``sys.stderr``.  The syntax for describing these
objects and connections is defined in :ref:`logging-config-dict-connections`
below.

Dictionary Schema Details
"""""""""""""""""""""""""

The dictionary passed to :func:`dictConfig` must contain the following
keys:

* *version* - to be set to an integer value representing the schema
  version.  The only valid value at present is 1, but having this key
  allows the schema to evolve while still preserving backwards
  compatibility.

All other keys are optional, but if present they will be interpreted
as described below.  In all cases below where a 'configuring dict' is
mentioned, it will be checked for the special ``'()'`` key to see if a
custom instantiation is required.  If so, the mechanism described in
:ref:`logging-config-dict-userdef` below is used to create an instance;
otherwise, the context is used to determine what to instantiate.

* *formatters* - the corresponding value will be a dict in which each
  key is a formatter id and each value is a dict describing how to
  configure the corresponding Formatter instance.

  The configuring dict is searched for keys ``format`` and ``datefmt``
  (with defaults of ``None``) and these are used to construct a
  :class:`logging.Formatter` instance.

* *filters* - the corresponding value will be a dict in which each key
  is a filter id and each value is a dict describing how to configure
  the corresponding Filter instance.

  The configuring dict is searched for the key ``name`` (defaulting to the
  empty string) and this is used to construct a :class:`logging.Filter`
  instance.

* *handlers* - the corresponding value will be a dict in which each
  key is a handler id and each value is a dict describing how to
  configure the corresponding Handler instance.

  The configuring dict is searched for the following keys:

  * ``class`` (mandatory).  This is the fully qualified name of the
    handler class.

  * ``level`` (optional).  The level of the handler.

  * ``formatter`` (optional).  The id of the formatter for this
    handler.

  * ``filters`` (optional).  A list of ids of the filters for this
    handler.

  All *other* keys are passed through as keyword arguments to the
  handler's constructor.  For example, given the snippet::

      handlers:
        console:
          class : logging.StreamHandler
          formatter: brief
          level   : INFO
          filters: [allow_foo]
          stream  : ext://sys.stdout
        file:
          class : logging.handlers.RotatingFileHandler
          formatter: precise
          filename: logconfig.log
          maxBytes: 1024
          backupCount: 3

  the handler with id ``console`` is instantiated as a
  :class:`logging.StreamHandler`, using ``sys.stdout`` as the underlying
  stream.  The handler with id ``file`` is instantiated as a
  :class:`logging.handlers.RotatingFileHandler` with the keyword arguments
  ``filename='logconfig.log', maxBytes=1024, backupCount=3``.

* *loggers* - the corresponding value will be a dict in which each key
  is a logger name and each value is a dict describing how to
  configure the corresponding Logger instance.

  The configuring dict is searched for the following keys:

  * ``level`` (optional).  The level of the logger.

  * ``propagate`` (optional).  The propagation setting of the logger.

  * ``filters`` (optional).  A list of ids of the filters for this
    logger.

  * ``handlers`` (optional).  A list of ids of the handlers for this
    logger.

  The specified loggers will be configured according to the level,
  propagation, filters and handlers specified.

* *root* - this will be the configuration for the root logger.
  Processing of the configuration will be as for any logger, except
  that the ``propagate`` setting will not be applicable.

* *incremental* - whether the configuration is to be interpreted as
  incremental to the existing configuration.  This value defaults to
  ``False``, which means that the specified configuration replaces the
  existing configuration with the same semantics as used by the
  existing :func:`fileConfig` API.

  If the specified value is ``True``, the configuration is processed
  as described in the section on :ref:`logging-config-dict-incremental`.

* *disable_existing_loggers* - whether any existing loggers are to be
  disabled. This setting mirrors the parameter of the same name in
  :func:`fileConfig`. If absent, this parameter defaults to ``True``.
  This value is ignored if *incremental* is ``True``.

.. _logging-config-dict-incremental:

Incremental Configuration
"""""""""""""""""""""""""

It is difficult to provide complete flexibility for incremental
configuration.  For example, because objects such as filters
and formatters are anonymous, once a configuration is set up, it is
not possible to refer to such anonymous objects when augmenting a
configuration.

Furthermore, there is not a compelling case for arbitrarily altering
the object graph of loggers, handlers, filters, formatters at
run-time, once a configuration is set up; the verbosity of loggers and
handlers can be controlled just by setting levels (and, in the case of
loggers, propagation flags).  Changing the object graph arbitrarily in
a safe way is problematic in a multi-threaded environment; while not
impossible, the benefits are not worth the complexity it adds to the
implementation.

Thus, when the ``incremental`` key of a configuration dict is present
and is ``True``, the system will completely ignore any ``formatters`` and
``filters`` entries, and process only the ``level``
settings in the ``handlers`` entries, and the ``level`` and
``propagate`` settings in the ``loggers`` and ``root`` entries.

Using a value in the configuration dict lets configurations to be sent
over the wire as pickled dicts to a socket listener. Thus, the logging
verbosity of a long-running application can be altered over time with
no need to stop and restart the application.

.. _logging-config-dict-connections:

Object connections
""""""""""""""""""

The schema describes a set of logging objects - loggers,
handlers, formatters, filters - which are connected to each other in
an object graph.  Thus, the schema needs to represent connections
between the objects.  For example, say that, once configured, a
particular logger has attached to it a particular handler.  For the
purposes of this discussion, we can say that the logger represents the
source, and the handler the destination, of a connection between the
two.  Of course in the configured objects this is represented by the
logger holding a reference to the handler.  In the configuration dict,
this is done by giving each destination object an id which identifies
it unambiguously, and then using the id in the source object's
configuration to indicate that a connection exists between the source
and the destination object with that id.

So, for example, consider the following YAML snippet::

    formatters:
      brief:
        # configuration for formatter with id 'brief' goes here
      precise:
        # configuration for formatter with id 'precise' goes here
    handlers:
      h1: #This is an id
       # configuration of handler with id 'h1' goes here
       formatter: brief
      h2: #This is another id
       # configuration of handler with id 'h2' goes here
       formatter: precise
    loggers:
      foo.bar.baz:
        # other configuration for logger 'foo.bar.baz'
        handlers: [h1, h2]

(Note: YAML used here because it's a little more readable than the
equivalent Python source form for the dictionary.)

The ids for loggers are the logger names which would be used
programmatically to obtain a reference to those loggers, e.g.
``foo.bar.baz``.  The ids for Formatters and Filters can be any string
value (such as ``brief``, ``precise`` above) and they are transient,
in that they are only meaningful for processing the configuration
dictionary and used to determine connections between objects, and are
not persisted anywhere when the configuration call is complete.

The above snippet indicates that logger named ``foo.bar.baz`` should
have two handlers attached to it, which are described by the handler
ids ``h1`` and ``h2``. The formatter for ``h1`` is that described by id
``brief``, and the formatter for ``h2`` is that described by id
``precise``.


.. _logging-config-dict-userdef:

User-defined objects
""""""""""""""""""""

The schema supports user-defined objects for handlers, filters and
formatters.  (Loggers do not need to have different types for
different instances, so there is no support in this configuration
schema for user-defined logger classes.)

Objects to be configured are described by dictionaries
which detail their configuration.  In some places, the logging system
will be able to infer from the context how an object is to be
instantiated, but when a user-defined object is to be instantiated,
the system will not know how to do this.  In order to provide complete
flexibility for user-defined object instantiation, the user needs
to provide a 'factory' - a callable which is called with a
configuration dictionary and which returns the instantiated object.
This is signalled by an absolute import path to the factory being
made available under the special key ``'()'``.  Here's a concrete
example::

    formatters:
      brief:
        format: '%(message)s'
      default:
        format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
        datefmt: '%Y-%m-%d %H:%M:%S'
      custom:
          (): my.package.customFormatterFactory
          bar: baz
          spam: 99.9
          answer: 42

The above YAML snippet defines three formatters.  The first, with id
``brief``, is a standard :class:`logging.Formatter` instance with the
specified format string.  The second, with id ``default``, has a
longer format and also defines the time format explicitly, and will
result in a :class:`logging.Formatter` initialized with those two format
strings.  Shown in Python source form, the ``brief`` and ``default``
formatters have configuration sub-dictionaries::

    {
      'format' : '%(message)s'
    }

and::

    {
      'format' : '%(asctime)s %(levelname)-8s %(name)-15s %(message)s',
      'datefmt' : '%Y-%m-%d %H:%M:%S'
    }

respectively, and as these dictionaries do not contain the special key
``'()'``, the instantiation is inferred from the context: as a result,
standard :class:`logging.Formatter` instances are created.  The
configuration sub-dictionary for the third formatter, with id
``custom``, is::

  {
    '()' : 'my.package.customFormatterFactory',
    'bar' : 'baz',
    'spam' : 99.9,
    'answer' : 42
  }

and this contains the special key ``'()'``, which means that
user-defined instantiation is wanted.  In this case, the specified
factory callable will be used. If it is an actual callable it will be
used directly - otherwise, if you specify a string (as in the example)
the actual callable will be located using normal import mechanisms.
The callable will be called with the **remaining** items in the
configuration sub-dictionary as keyword arguments.  In the above
example, the formatter with id ``custom`` will be assumed to be
returned by the call::

    my.package.customFormatterFactory(bar='baz', spam=99.9, answer=42)

The key ``'()'`` has been used as the special key because it is not a
valid keyword parameter name, and so will not clash with the names of
the keyword arguments used in the call.  The ``'()'`` also serves as a
mnemonic that the corresponding value is a callable.


.. _logging-config-dict-externalobj:

Access to external objects
""""""""""""""""""""""""""

There are times where a configuration needs to refer to objects
external to the configuration, for example ``sys.stderr``.  If the
configuration dict is constructed using Python code, this is
straightforward, but a problem arises when the configuration is
provided via a text file (e.g. JSON, YAML).  In a text file, there is
no standard way to distinguish ``sys.stderr`` from the literal string
``'sys.stderr'``.  To facilitate this distinction, the configuration
system looks for certain special prefixes in string values and
treat them specially.  For example, if the literal string
``'ext://sys.stderr'`` is provided as a value in the configuration,
then the ``ext://`` will be stripped off and the remainder of the
value processed using normal import mechanisms.

The handling of such prefixes is done in a way analogous to protocol
handling: there is a generic mechanism to look for prefixes which
match the regular expression ``^(?P<prefix>[a-z]+)://(?P<suffix>.*)$``
whereby, if the ``prefix`` is recognised, the ``suffix`` is processed
in a prefix-dependent manner and the result of the processing replaces
the string value.  If the prefix is not recognised, then the string
value will be left as-is.


.. _logging-config-dict-internalobj:

Access to internal objects
""""""""""""""""""""""""""

As well as external objects, there is sometimes also a need to refer
to objects in the configuration.  This will be done implicitly by the
configuration system for things that it knows about.  For example, the
string value ``'DEBUG'`` for a ``level`` in a logger or handler will
automatically be converted to the value ``logging.DEBUG``, and the
``handlers``, ``filters`` and ``formatter`` entries will take an
object id and resolve to the appropriate destination object.

However, a more generic mechanism is needed for user-defined
objects which are not known to the :mod:`logging` module.  For
example, consider :class:`logging.handlers.MemoryHandler`, which takes
a ``target`` argument which is another handler to delegate to. Since
the system already knows about this class, then in the configuration,
the given ``target`` just needs to be the object id of the relevant
target handler, and the system will resolve to the handler from the
id.  If, however, a user defines a ``my.package.MyHandler`` which has
an ``alternate`` handler, the configuration system would not know that
the ``alternate`` referred to a handler.  To cater for this, a generic
resolution system allows the user to specify::

    handlers:
      file:
        # configuration of file handler goes here

      custom:
        (): my.package.MyHandler
        alternate: cfg://handlers.file

The literal string ``'cfg://handlers.file'`` will be resolved in an
analogous way to strings with the ``ext://`` prefix, but looking
in the configuration itself rather than the import namespace.  The
mechanism allows access by dot or by index, in a similar way to
that provided by ``str.format``.  Thus, given the following snippet::

    handlers:
      email:
        class: logging.handlers.SMTPHandler
        mailhost: localhost
        fromaddr: my_app@domain.tld
        toaddrs:
          - support_team@domain.tld
          - dev_team@domain.tld
        subject: Houston, we have a problem.

in the configuration, the string ``'cfg://handlers'`` would resolve to
the dict with key ``handlers``, the string ``'cfg://handlers.email``
would resolve to the dict with key ``email`` in the ``handlers`` dict,
and so on.  The string ``'cfg://handlers.email.toaddrs[1]`` would
resolve to ``'dev_team.domain.tld'`` and the string
``'cfg://handlers.email.toaddrs[0]'`` would resolve to the value
``'support_team@domain.tld'``. The ``subject`` value could be accessed
using either ``'cfg://handlers.email.subject'`` or, equivalently,
``'cfg://handlers.email[subject]'``.  The latter form only needs to be
used if the key contains spaces or non-alphanumeric characters.  If an
index value consists only of decimal digits, access will be attempted
using the corresponding integer value, falling back to the string
value if needed.

Given a string ``cfg://handlers.myhandler.mykey.123``, this will
resolve to ``config_dict['handlers']['myhandler']['mykey']['123']``.
If the string is specified as ``cfg://handlers.myhandler.mykey[123]``,
the system will attempt to retrieve the value from
``config_dict['handlers']['myhandler']['mykey'][123]``, and fall back
to ``config_dict['handlers']['myhandler']['mykey']['123']`` if that
fails.

.. _logging-config-fileformat:

Configuration file format
^^^^^^^^^^^^^^^^^^^^^^^^^

The configuration file format understood by :func:`fileConfig` is based on
:mod:`configparser` functionality. The file must contain sections called
``[loggers]``, ``[handlers]`` and ``[formatters]`` which identify by name the
entities of each type which are defined in the file. For each such entity, there
is a separate section which identifies how that entity is configured.  Thus, for
a logger named ``log01`` in the ``[loggers]`` section, the relevant
configuration details are held in a section ``[logger_log01]``. Similarly, a
handler called ``hand01`` in the ``[handlers]`` section will have its
configuration held in a section called ``[handler_hand01]``, while a formatter
called ``form01`` in the ``[formatters]`` section will have its configuration
specified in a section called ``[formatter_form01]``. The root logger
configuration must be specified in a section called ``[logger_root]``.

Examples of these sections in the file are given below. ::

   [loggers]
   keys=root,log02,log03,log04,log05,log06,log07

   [handlers]
   keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09

   [formatters]
   keys=form01,form02,form03,form04,form05,form06,form07,form08,form09

The root logger must specify a level and a list of handlers. An example of a
root logger section is given below. ::

   [logger_root]
   level=NOTSET
   handlers=hand01

The ``level`` entry can be one of ``DEBUG, INFO, WARNING, ERROR, CRITICAL`` or
``NOTSET``. For the root logger only, ``NOTSET`` means that all messages will be
logged. Level values are :func:`eval`\ uated in the context of the ``logging``
package's namespace.

The ``handlers`` entry is a comma-separated list of handler names, which must
appear in the ``[handlers]`` section. These names must appear in the
``[handlers]`` section and have corresponding sections in the configuration
file.

For loggers other than the root logger, some additional information is required.
This is illustrated by the following example. ::

   [logger_parser]
   level=DEBUG
   handlers=hand01
   propagate=1
   qualname=compiler.parser

The ``level`` and ``handlers`` entries are interpreted as for the root logger,
except that if a non-root logger's level is specified as ``NOTSET``, the system
consults loggers higher up the hierarchy to determine the effective level of the
logger. The ``propagate`` entry is set to 1 to indicate that messages must
propagate to handlers higher up the logger hierarchy from this logger, or 0 to
indicate that messages are **not** propagated to handlers up the hierarchy. The
``qualname`` entry is the hierarchical channel name of the logger, that is to
say the name used by the application to get the logger.

Sections which specify handler configuration are exemplified by the following.
::

   [handler_hand01]
   class=StreamHandler
   level=NOTSET
   formatter=form01
   args=(sys.stdout,)

The ``class`` entry indicates the handler's class (as determined by :func:`eval`
in the ``logging`` package's namespace). The ``level`` is interpreted as for
loggers, and ``NOTSET`` is taken to mean "log everything".

The ``formatter`` entry indicates the key name of the formatter for this
handler. If blank, a default formatter (``logging._defaultFormatter``) is used.
If a name is specified, it must appear in the ``[formatters]`` section and have
a corresponding section in the configuration file.

The ``args`` entry, when :func:`eval`\ uated in the context of the ``logging``
package's namespace, is the list of arguments to the constructor for the handler
class. Refer to the constructors for the relevant handlers, or to the examples
below, to see how typical entries are constructed. ::

   [handler_hand02]
   class=FileHandler
   level=DEBUG
   formatter=form02
   args=('python.log', 'w')

   [handler_hand03]
   class=handlers.SocketHandler
   level=INFO
   formatter=form03
   args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)

   [handler_hand04]
   class=handlers.DatagramHandler
   level=WARN
   formatter=form04
   args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)

   [handler_hand05]
   class=handlers.SysLogHandler
   level=ERROR
   formatter=form05
   args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)

   [handler_hand06]
   class=handlers.NTEventLogHandler
   level=CRITICAL
   formatter=form06
   args=('Python Application', '', 'Application')

   [handler_hand07]
   class=handlers.SMTPHandler
   level=WARN
   formatter=form07
   args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')

   [handler_hand08]
   class=handlers.MemoryHandler
   level=NOTSET
   formatter=form08
   target=
   args=(10, ERROR)

   [handler_hand09]
   class=handlers.HTTPHandler
   level=NOTSET
   formatter=form09
   args=('localhost:9022', '/log', 'GET')

Sections which specify formatter configuration are typified by the following. ::

   [formatter_form01]
   format=F1 %(asctime)s %(levelname)s %(message)s
   datefmt=
   class=logging.Formatter

The ``format`` entry is the overall format string, and the ``datefmt`` entry is
the :func:`strftime`\ -compatible date/time format string.  If empty, the
package substitutes ISO8601 format date/times, which is almost equivalent to
specifying the date format string ``"%Y-%m-%d %H:%M:%S"``.  The ISO8601 format
also specifies milliseconds, which are appended to the result of using the above
format string, with a comma separator.  An example time in ISO8601 format is
``2003-01-23 00:29:50,411``.

The ``class`` entry is optional.  It indicates the name of the formatter's class
(as a dotted module and class name.)  This option is useful for instantiating a
:class:`Formatter` subclass.  Subclasses of :class:`Formatter` can present
exception tracebacks in an expanded or condensed format.


Configuration server example
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Here is an example of a module using the logging configuration server::

    import logging
    import logging.config
    import time
    import os

    # read initial config file
    logging.config.fileConfig("logging.conf")

    # create and start listener on port 9999
    t = logging.config.listen(9999)
    t.start()

    logger = logging.getLogger("simpleExample")

    try:
        # loop through logging calls to see the difference
        # new configurations make, until Ctrl+C is pressed
        while True:
            logger.debug("debug message")
            logger.info("info message")
            logger.warn("warn message")
            logger.error("error message")
            logger.critical("critical message")
            time.sleep(5)
    except KeyboardInterrupt:
        # cleanup
        logging.config.stopListening()
        t.join()

And here is a script that takes a filename and sends that file to the server,
properly preceded with the binary-encoded length, as the new logging
configuration::

    #!/usr/bin/env python
    import socket, sys, struct

    data_to_send = open(sys.argv[1], "r").read()

    HOST = 'localhost'
    PORT = 9999
    s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    print("connecting...")
    s.connect((HOST, PORT))
    print("sending config...")
    s.send(struct.pack(">L", len(data_to_send)))
    s.send(data_to_send)
    s.close()
    print("complete")


More examples
-------------

Multiple handlers and formatters
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Loggers are plain Python objects.  The :func:`addHandler` method has no minimum
or maximum quota for the number of handlers you may add.  Sometimes it will be
beneficial for an application to log all messages of all severities to a text
file while simultaneously logging errors or above to the console.  To set this
up, simply configure the appropriate handlers.  The logging calls in the
application code will remain unchanged.  Here is a slight modification to the
previous simple module-based configuration example::

    import logging

    logger = logging.getLogger("simple_example")
    logger.setLevel(logging.DEBUG)
    # create file handler which logs even debug messages
    fh = logging.FileHandler("spam.log")
    fh.setLevel(logging.DEBUG)
    # create console handler with a higher log level
    ch = logging.StreamHandler()
    ch.setLevel(logging.ERROR)
    # create formatter and add it to the handlers
    formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
    ch.setFormatter(formatter)
    fh.setFormatter(formatter)
    # add the handlers to logger
    logger.addHandler(ch)
    logger.addHandler(fh)

    # "application" code
    logger.debug("debug message")
    logger.info("info message")
    logger.warn("warn message")
    logger.error("error message")
    logger.critical("critical message")

Notice that the "application" code does not care about multiple handlers.  All
that changed was the addition and configuration of a new handler named *fh*.

The ability to create new handlers with higher- or lower-severity filters can be
very helpful when writing and testing an application.  Instead of using many
``print`` statements for debugging, use ``logger.debug``: Unlike the print
statements, which you will have to delete or comment out later, the logger.debug
statements can remain intact in the source code and remain dormant until you
need them again.  At that time, the only change that needs to happen is to
modify the severity level of the logger and/or handler to debug.


Using logging in multiple modules
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

It was mentioned above that multiple calls to
``logging.getLogger('someLogger')`` return a reference to the same logger
object.  This is true not only within the same module, but also across modules
as long as it is in the same Python interpreter process.  It is true for
references to the same object; additionally, application code can define and
configure a parent logger in one module and create (but not configure) a child
logger in a separate module, and all logger calls to the child will pass up to
the parent.  Here is a main module::

    import logging
    import auxiliary_module

    # create logger with "spam_application"
    logger = logging.getLogger("spam_application")
    logger.setLevel(logging.DEBUG)
    # create file handler which logs even debug messages
    fh = logging.FileHandler("spam.log")
    fh.setLevel(logging.DEBUG)
    # create console handler with a higher log level
    ch = logging.StreamHandler()
    ch.setLevel(logging.ERROR)
    # create formatter and add it to the handlers
    formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
    fh.setFormatter(formatter)
    ch.setFormatter(formatter)
    # add the handlers to the logger
    logger.addHandler(fh)
    logger.addHandler(ch)

    logger.info("creating an instance of auxiliary_module.Auxiliary")
    a = auxiliary_module.Auxiliary()
    logger.info("created an instance of auxiliary_module.Auxiliary")
    logger.info("calling auxiliary_module.Auxiliary.do_something")
    a.do_something()
    logger.info("finished auxiliary_module.Auxiliary.do_something")
    logger.info("calling auxiliary_module.some_function()")
    auxiliary_module.some_function()
    logger.info("done with auxiliary_module.some_function()")

Here is the auxiliary module::

    import logging

    # create logger
    module_logger = logging.getLogger("spam_application.auxiliary")

    class Auxiliary:
        def __init__(self):
            self.logger = logging.getLogger("spam_application.auxiliary.Auxiliary")
            self.logger.info("creating an instance of Auxiliary")
        def do_something(self):
            self.logger.info("doing something")
            a = 1 + 1
            self.logger.info("done doing something")

    def some_function():
        module_logger.info("received a call to \"some_function\"")

The output looks like this::

    2005-03-23 23:47:11,663 - spam_application - INFO -
       creating an instance of auxiliary_module.Auxiliary
    2005-03-23 23:47:11,665 - spam_application.auxiliary.Auxiliary - INFO -
       creating an instance of Auxiliary
    2005-03-23 23:47:11,665 - spam_application - INFO -
       created an instance of auxiliary_module.Auxiliary
    2005-03-23 23:47:11,668 - spam_application - INFO -
       calling auxiliary_module.Auxiliary.do_something
    2005-03-23 23:47:11,668 - spam_application.auxiliary.Auxiliary - INFO -
       doing something
    2005-03-23 23:47:11,669 - spam_application.auxiliary.Auxiliary - INFO -
       done doing something
    2005-03-23 23:47:11,670 - spam_application - INFO -
       finished auxiliary_module.Auxiliary.do_something
    2005-03-23 23:47:11,671 - spam_application - INFO -
       calling auxiliary_module.some_function()
    2005-03-23 23:47:11,672 - spam_application.auxiliary - INFO -
       received a call to "some_function"
    2005-03-23 23:47:11,673 - spam_application - INFO -
       done with auxiliary_module.some_function()