2357 lines
93 KiB
ReStructuredText
2357 lines
93 KiB
ReStructuredText
.. _logging-cookbook:
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================
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Logging Cookbook
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================
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:Author: Vinay Sajip <vinay_sajip at red-dove dot com>
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This page contains a number of recipes related to logging, which have been found
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useful in the past.
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.. currentmodule:: logging
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Using logging in multiple modules
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---------------------------------
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Multiple calls to ``logging.getLogger('someLogger')`` return a reference to the
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same logger object. This is true not only within the same module, but also
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across modules as long as it is in the same Python interpreter process. It is
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true for references to the same object; additionally, application code can
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define and configure a parent logger in one module and create (but not
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configure) a child logger in a separate module, and all logger calls to the
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child will pass up to the parent. Here is a main module::
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import logging
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import auxiliary_module
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# create logger with 'spam_application'
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logger = logging.getLogger('spam_application')
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logger.setLevel(logging.DEBUG)
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# create file handler which logs even debug messages
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fh = logging.FileHandler('spam.log')
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fh.setLevel(logging.DEBUG)
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# create console handler with a higher log level
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ch = logging.StreamHandler()
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ch.setLevel(logging.ERROR)
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# create formatter and add it to the handlers
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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fh.setFormatter(formatter)
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ch.setFormatter(formatter)
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# add the handlers to the logger
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logger.addHandler(fh)
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logger.addHandler(ch)
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logger.info('creating an instance of auxiliary_module.Auxiliary')
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a = auxiliary_module.Auxiliary()
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logger.info('created an instance of auxiliary_module.Auxiliary')
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logger.info('calling auxiliary_module.Auxiliary.do_something')
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a.do_something()
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logger.info('finished auxiliary_module.Auxiliary.do_something')
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logger.info('calling auxiliary_module.some_function()')
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auxiliary_module.some_function()
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logger.info('done with auxiliary_module.some_function()')
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Here is the auxiliary module::
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import logging
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# create logger
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module_logger = logging.getLogger('spam_application.auxiliary')
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class Auxiliary:
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def __init__(self):
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self.logger = logging.getLogger('spam_application.auxiliary.Auxiliary')
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self.logger.info('creating an instance of Auxiliary')
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def do_something(self):
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self.logger.info('doing something')
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a = 1 + 1
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self.logger.info('done doing something')
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def some_function():
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module_logger.info('received a call to "some_function"')
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The output looks like this::
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2005-03-23 23:47:11,663 - spam_application - INFO -
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creating an instance of auxiliary_module.Auxiliary
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2005-03-23 23:47:11,665 - spam_application.auxiliary.Auxiliary - INFO -
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creating an instance of Auxiliary
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2005-03-23 23:47:11,665 - spam_application - INFO -
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created an instance of auxiliary_module.Auxiliary
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2005-03-23 23:47:11,668 - spam_application - INFO -
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calling auxiliary_module.Auxiliary.do_something
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2005-03-23 23:47:11,668 - spam_application.auxiliary.Auxiliary - INFO -
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doing something
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2005-03-23 23:47:11,669 - spam_application.auxiliary.Auxiliary - INFO -
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done doing something
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2005-03-23 23:47:11,670 - spam_application - INFO -
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finished auxiliary_module.Auxiliary.do_something
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2005-03-23 23:47:11,671 - spam_application - INFO -
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calling auxiliary_module.some_function()
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2005-03-23 23:47:11,672 - spam_application.auxiliary - INFO -
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received a call to 'some_function'
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2005-03-23 23:47:11,673 - spam_application - INFO -
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done with auxiliary_module.some_function()
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Multiple handlers and formatters
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--------------------------------
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Loggers are plain Python objects. The :meth:`~Logger.addHandler` method has no
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minimum or maximum quota for the number of handlers you may add. Sometimes it
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will be beneficial for an application to log all messages of all severities to a
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text file while simultaneously logging errors or above to the console. To set
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this up, simply configure the appropriate handlers. The logging calls in the
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application code will remain unchanged. Here is a slight modification to the
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previous simple module-based configuration example::
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import logging
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logger = logging.getLogger('simple_example')
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logger.setLevel(logging.DEBUG)
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# create file handler which logs even debug messages
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fh = logging.FileHandler('spam.log')
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fh.setLevel(logging.DEBUG)
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# create console handler with a higher log level
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ch = logging.StreamHandler()
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ch.setLevel(logging.ERROR)
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# create formatter and add it to the handlers
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formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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ch.setFormatter(formatter)
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fh.setFormatter(formatter)
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# add the handlers to logger
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logger.addHandler(ch)
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logger.addHandler(fh)
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# 'application' code
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logger.debug('debug message')
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logger.info('info message')
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logger.warn('warn message')
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logger.error('error message')
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logger.critical('critical message')
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Notice that the 'application' code does not care about multiple handlers. All
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that changed was the addition and configuration of a new handler named *fh*.
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The ability to create new handlers with higher- or lower-severity filters can be
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very helpful when writing and testing an application. Instead of using many
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``print`` statements for debugging, use ``logger.debug``: Unlike the print
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statements, which you will have to delete or comment out later, the logger.debug
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statements can remain intact in the source code and remain dormant until you
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need them again. At that time, the only change that needs to happen is to
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modify the severity level of the logger and/or handler to debug.
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.. _multiple-destinations:
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Logging to multiple destinations
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--------------------------------
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Let's say you want to log to console and file with different message formats and
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in differing circumstances. Say you want to log messages with levels of DEBUG
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and higher to file, and those messages at level INFO and higher to the console.
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Let's also assume that the file should contain timestamps, but the console
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messages should not. Here's how you can achieve this::
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import logging
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# set up logging to file - see previous section for more details
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logging.basicConfig(level=logging.DEBUG,
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format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
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datefmt='%m-%d %H:%M',
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filename='/temp/myapp.log',
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filemode='w')
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# define a Handler which writes INFO messages or higher to the sys.stderr
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console = logging.StreamHandler()
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console.setLevel(logging.INFO)
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# set a format which is simpler for console use
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formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s')
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# tell the handler to use this format
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console.setFormatter(formatter)
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# add the handler to the root logger
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logging.getLogger('').addHandler(console)
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# Now, we can log to the root logger, or any other logger. First the root...
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logging.info('Jackdaws love my big sphinx of quartz.')
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# Now, define a couple of other loggers which might represent areas in your
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# application:
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logger1 = logging.getLogger('myapp.area1')
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logger2 = logging.getLogger('myapp.area2')
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logger1.debug('Quick zephyrs blow, vexing daft Jim.')
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logger1.info('How quickly daft jumping zebras vex.')
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logger2.warning('Jail zesty vixen who grabbed pay from quack.')
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logger2.error('The five boxing wizards jump quickly.')
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When you run this, on the console you will see ::
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root : INFO Jackdaws love my big sphinx of quartz.
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myapp.area1 : INFO How quickly daft jumping zebras vex.
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myapp.area2 : WARNING Jail zesty vixen who grabbed pay from quack.
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myapp.area2 : ERROR The five boxing wizards jump quickly.
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and in the file you will see something like ::
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10-22 22:19 root INFO Jackdaws love my big sphinx of quartz.
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10-22 22:19 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim.
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10-22 22:19 myapp.area1 INFO How quickly daft jumping zebras vex.
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10-22 22:19 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack.
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10-22 22:19 myapp.area2 ERROR The five boxing wizards jump quickly.
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As you can see, the DEBUG message only shows up in the file. The other messages
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are sent to both destinations.
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This example uses console and file handlers, but you can use any number and
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combination of handlers you choose.
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Configuration server example
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----------------------------
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Here is an example of a module using the logging configuration server::
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import logging
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import logging.config
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import time
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import os
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# read initial config file
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logging.config.fileConfig('logging.conf')
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# create and start listener on port 9999
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t = logging.config.listen(9999)
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t.start()
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logger = logging.getLogger('simpleExample')
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try:
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# loop through logging calls to see the difference
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# new configurations make, until Ctrl+C is pressed
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while True:
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logger.debug('debug message')
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logger.info('info message')
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logger.warn('warn message')
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logger.error('error message')
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logger.critical('critical message')
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time.sleep(5)
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except KeyboardInterrupt:
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# cleanup
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logging.config.stopListening()
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t.join()
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And here is a script that takes a filename and sends that file to the server,
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properly preceded with the binary-encoded length, as the new logging
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configuration::
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#!/usr/bin/env python
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import socket, sys, struct
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with open(sys.argv[1], 'rb') as f:
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data_to_send = f.read()
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HOST = 'localhost'
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PORT = 9999
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s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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print('connecting...')
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s.connect((HOST, PORT))
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print('sending config...')
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s.send(struct.pack('>L', len(data_to_send)))
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s.send(data_to_send)
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s.close()
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print('complete')
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Dealing with handlers that block
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--------------------------------
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.. currentmodule:: logging.handlers
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Sometimes you have to get your logging handlers to do their work without
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blocking the thread you're logging from. This is common in Web applications,
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though of course it also occurs in other scenarios.
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A common culprit which demonstrates sluggish behaviour is the
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:class:`SMTPHandler`: sending emails can take a long time, for a
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number of reasons outside the developer's control (for example, a poorly
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performing mail or network infrastructure). But almost any network-based
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handler can block: Even a :class:`SocketHandler` operation may do a
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DNS query under the hood which is too slow (and this query can be deep in the
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socket library code, below the Python layer, and outside your control).
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One solution is to use a two-part approach. For the first part, attach only a
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:class:`QueueHandler` to those loggers which are accessed from
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performance-critical threads. They simply write to their queue, which can be
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sized to a large enough capacity or initialized with no upper bound to their
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size. The write to the queue will typically be accepted quickly, though you
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will probably need to catch the :exc:`queue.Full` exception as a precaution
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in your code. If you are a library developer who has performance-critical
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threads in their code, be sure to document this (together with a suggestion to
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attach only ``QueueHandlers`` to your loggers) for the benefit of other
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developers who will use your code.
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The second part of the solution is :class:`QueueListener`, which has been
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designed as the counterpart to :class:`QueueHandler`. A
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:class:`QueueListener` is very simple: it's passed a queue and some handlers,
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and it fires up an internal thread which listens to its queue for LogRecords
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sent from ``QueueHandlers`` (or any other source of ``LogRecords``, for that
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matter). The ``LogRecords`` are removed from the queue and passed to the
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handlers for processing.
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The advantage of having a separate :class:`QueueListener` class is that you
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can use the same instance to service multiple ``QueueHandlers``. This is more
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resource-friendly than, say, having threaded versions of the existing handler
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classes, which would eat up one thread per handler for no particular benefit.
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An example of using these two classes follows (imports omitted)::
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que = queue.Queue(-1) # no limit on size
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queue_handler = QueueHandler(que)
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handler = logging.StreamHandler()
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listener = QueueListener(que, handler)
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root = logging.getLogger()
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root.addHandler(queue_handler)
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formatter = logging.Formatter('%(threadName)s: %(message)s')
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handler.setFormatter(formatter)
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listener.start()
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# The log output will display the thread which generated
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# the event (the main thread) rather than the internal
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# thread which monitors the internal queue. This is what
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# you want to happen.
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root.warning('Look out!')
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listener.stop()
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which, when run, will produce::
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MainThread: Look out!
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.. versionchanged:: 3.5
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Prior to Python 3.5, the :class:`QueueListener` always passed every message
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received from the queue to every handler it was initialized with. (This was
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because it was assumed that level filtering was all done on the other side,
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where the queue is filled.) From 3.5 onwards, this behaviour can be changed
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by passing a keyword argument ``respect_handler_level=True`` to the
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listener's constructor. When this is done, the listener compares the level
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of each message with the handler's level, and only passes a message to a
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handler if it's appropriate to do so.
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.. _network-logging:
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Sending and receiving logging events across a network
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-----------------------------------------------------
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Let's say you want to send logging events across a network, and handle them at
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the receiving end. A simple way of doing this is attaching a
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:class:`SocketHandler` instance to the root logger at the sending end::
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import logging, logging.handlers
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rootLogger = logging.getLogger('')
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rootLogger.setLevel(logging.DEBUG)
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socketHandler = logging.handlers.SocketHandler('localhost',
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logging.handlers.DEFAULT_TCP_LOGGING_PORT)
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# don't bother with a formatter, since a socket handler sends the event as
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# an unformatted pickle
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rootLogger.addHandler(socketHandler)
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# Now, we can log to the root logger, or any other logger. First the root...
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logging.info('Jackdaws love my big sphinx of quartz.')
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# Now, define a couple of other loggers which might represent areas in your
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# application:
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logger1 = logging.getLogger('myapp.area1')
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logger2 = logging.getLogger('myapp.area2')
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logger1.debug('Quick zephyrs blow, vexing daft Jim.')
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logger1.info('How quickly daft jumping zebras vex.')
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logger2.warning('Jail zesty vixen who grabbed pay from quack.')
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logger2.error('The five boxing wizards jump quickly.')
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At the receiving end, you can set up a receiver using the :mod:`socketserver`
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module. Here is a basic working example::
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import pickle
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import logging
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import logging.handlers
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import socketserver
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import struct
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class LogRecordStreamHandler(socketserver.StreamRequestHandler):
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"""Handler for a streaming logging request.
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This basically logs the record using whatever logging policy is
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configured locally.
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"""
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def handle(self):
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"""
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Handle multiple requests - each expected to be a 4-byte length,
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followed by the LogRecord in pickle format. Logs the record
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according to whatever policy is configured locally.
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"""
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while True:
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chunk = self.connection.recv(4)
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if len(chunk) < 4:
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break
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slen = struct.unpack('>L', chunk)[0]
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chunk = self.connection.recv(slen)
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while len(chunk) < slen:
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chunk = chunk + self.connection.recv(slen - len(chunk))
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obj = self.unPickle(chunk)
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record = logging.makeLogRecord(obj)
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self.handleLogRecord(record)
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def unPickle(self, data):
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return pickle.loads(data)
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def handleLogRecord(self, record):
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# if a name is specified, we use the named logger rather than the one
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# implied by the record.
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if self.server.logname is not None:
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name = self.server.logname
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else:
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name = record.name
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logger = logging.getLogger(name)
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# N.B. EVERY record gets logged. This is because Logger.handle
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# is normally called AFTER logger-level filtering. If you want
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# to do filtering, do it at the client end to save wasting
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# cycles and network bandwidth!
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logger.handle(record)
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class LogRecordSocketReceiver(socketserver.ThreadingTCPServer):
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"""
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Simple TCP socket-based logging receiver suitable for testing.
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"""
|
||
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allow_reuse_address = True
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|
||
def __init__(self, host='localhost',
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port=logging.handlers.DEFAULT_TCP_LOGGING_PORT,
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handler=LogRecordStreamHandler):
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socketserver.ThreadingTCPServer.__init__(self, (host, port), handler)
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self.abort = 0
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self.timeout = 1
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self.logname = None
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|
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def serve_until_stopped(self):
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import select
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||
abort = 0
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while not abort:
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rd, wr, ex = select.select([self.socket.fileno()],
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[], [],
|
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self.timeout)
|
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if rd:
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self.handle_request()
|
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abort = self.abort
|
||
|
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def main():
|
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logging.basicConfig(
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format='%(relativeCreated)5d %(name)-15s %(levelname)-8s %(message)s')
|
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tcpserver = LogRecordSocketReceiver()
|
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print('About to start TCP server...')
|
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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:`~handlers.SocketHandler.makePickle` method and implementing your
|
||
alternative there, as well as adapting the above script to use your alternative
|
||
serialization.
|
||
|
||
|
||
.. _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:`~LoggerAdapter.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:`~LoggerAdapter.process` to do what you need. Here is a simple example::
|
||
|
||
class CustomAdapter(logging.LoggerAdapter):
|
||
"""
|
||
This example adapter expects the passed in dict-like object to have a
|
||
'connid' key, whose value in brackets is prepended to the log message.
|
||
"""
|
||
def process(self, msg, kwargs):
|
||
return '[%s] %s' % (self.extra['connid'], msg), kwargs
|
||
|
||
which you can use like this::
|
||
|
||
logger = logging.getLogger(__name__)
|
||
adapter = CustomAdapter(logger, {'connid': some_conn_id})
|
||
|
||
Then any events that you log to the adapter will have the value of
|
||
``some_conn_id`` prepended to the log messages.
|
||
|
||
Using objects other than dicts to pass contextual information
|
||
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|
||
|
||
You don't need to pass an actual dict to a :class:`LoggerAdapter` - you could
|
||
pass an instance of a class which implements ``__getitem__`` and ``__iter__`` so
|
||
that it looks like a dict to logging. This would be useful if you want to
|
||
generate values dynamically (whereas the values in a dict would be constant).
|
||
|
||
|
||
.. _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)
|
||
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:`~handlers.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.)
|
||
:ref:`This section <network-logging>` 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:`~multiprocessing.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
|
||
https://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 this 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('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 Exception:
|
||
import sys, traceback
|
||
print('Whoops! Problem:', file=sys.stderr)
|
||
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()
|
||
|
||
A variant of the above script keeps the logging in the main process, in a
|
||
separate thread::
|
||
|
||
import logging
|
||
import logging.config
|
||
import logging.handlers
|
||
from multiprocessing import Process, Queue
|
||
import random
|
||
import threading
|
||
import time
|
||
|
||
def logger_thread(q):
|
||
while True:
|
||
record = q.get()
|
||
if record is None:
|
||
break
|
||
logger = logging.getLogger(record.name)
|
||
logger.handle(record)
|
||
|
||
|
||
def worker_process(q):
|
||
qh = logging.handlers.QueueHandler(q)
|
||
root = logging.getLogger()
|
||
root.setLevel(logging.DEBUG)
|
||
root.addHandler(qh)
|
||
levels = [logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR,
|
||
logging.CRITICAL]
|
||
loggers = ['foo', 'foo.bar', 'foo.bar.baz',
|
||
'spam', 'spam.ham', 'spam.ham.eggs']
|
||
for i in range(100):
|
||
lvl = random.choice(levels)
|
||
logger = logging.getLogger(random.choice(loggers))
|
||
logger.log(lvl, 'Message no. %d', i)
|
||
|
||
if __name__ == '__main__':
|
||
q = Queue()
|
||
d = {
|
||
'version': 1,
|
||
'formatters': {
|
||
'detailed': {
|
||
'class': 'logging.Formatter',
|
||
'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
|
||
}
|
||
},
|
||
'handlers': {
|
||
'console': {
|
||
'class': 'logging.StreamHandler',
|
||
'level': 'INFO',
|
||
},
|
||
'file': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog.log',
|
||
'mode': 'w',
|
||
'formatter': 'detailed',
|
||
},
|
||
'foofile': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog-foo.log',
|
||
'mode': 'w',
|
||
'formatter': 'detailed',
|
||
},
|
||
'errors': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog-errors.log',
|
||
'mode': 'w',
|
||
'level': 'ERROR',
|
||
'formatter': 'detailed',
|
||
},
|
||
},
|
||
'loggers': {
|
||
'foo': {
|
||
'handlers': ['foofile']
|
||
}
|
||
},
|
||
'root': {
|
||
'level': 'DEBUG',
|
||
'handlers': ['console', 'file', 'errors']
|
||
},
|
||
}
|
||
workers = []
|
||
for i in range(5):
|
||
wp = Process(target=worker_process, name='worker %d' % (i + 1), args=(q,))
|
||
workers.append(wp)
|
||
wp.start()
|
||
logging.config.dictConfig(d)
|
||
lp = threading.Thread(target=logger_thread, args=(q,))
|
||
lp.start()
|
||
# At this point, the main process could do some useful work of its own
|
||
# Once it's done that, it can wait for the workers to terminate...
|
||
for wp in workers:
|
||
wp.join()
|
||
# And now tell the logging thread to finish up, too
|
||
q.put(None)
|
||
lp.join()
|
||
|
||
This variant shows how you can e.g. apply configuration for particular loggers
|
||
- e.g. the ``foo`` logger has a special handler which stores all events in the
|
||
``foo`` subsystem in a file ``mplog-foo.log``. This will be used by the logging
|
||
machinery in the main process (even though the logging events are generated in
|
||
the worker processes) to direct the messages to the appropriate destinations.
|
||
|
||
Using file rotation
|
||
-------------------
|
||
|
||
.. sectionauthor:: Doug Hellmann, Vinay Sajip (changes)
|
||
.. (see <http://blog.doughellmann.com/2007/05/pymotw-logging.html>)
|
||
|
||
Sometimes you want to let a log file grow to a certain size, then open a new
|
||
file and log to that. You may want to keep a certain number of these files, and
|
||
when that many files have been created, rotate the files so that the number of
|
||
files and the size of the files both remain bounded. For this usage pattern, the
|
||
logging package provides a :class:`~handlers.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 too small as an extreme
|
||
example. You would want to set *maxBytes* to an appropriate value.
|
||
|
||
.. _format-styles:
|
||
|
||
Use of alternative formatting styles
|
||
------------------------------------
|
||
|
||
When logging was added to the Python standard library, the only way of
|
||
formatting messages with variable content was to use the %-formatting
|
||
method. Since then, Python has gained two new formatting approaches:
|
||
:class:`string.Template` (added in Python 2.4) and :meth:`str.format`
|
||
(added in Python 2.6).
|
||
|
||
Logging (as of 3.2) provides improved support for these two additional
|
||
formatting styles. The :class:`Formatter` class been enhanced to take an
|
||
additional, optional keyword parameter named ``style``. This defaults to
|
||
``'%'``, but other possible values are ``'{'`` and ``'$'``, which correspond
|
||
to the other two formatting styles. Backwards compatibility is maintained by
|
||
default (as you would expect), but by explicitly specifying a style parameter,
|
||
you get the ability to specify format strings which work with
|
||
:meth:`str.format` or :class:`string.Template`. Here's an example console
|
||
session to show the possibilities:
|
||
|
||
.. code-block:: pycon
|
||
|
||
>>> import logging
|
||
>>> root = logging.getLogger()
|
||
>>> root.setLevel(logging.DEBUG)
|
||
>>> handler = logging.StreamHandler()
|
||
>>> bf = logging.Formatter('{asctime} {name} {levelname:8s} {message}',
|
||
... style='{')
|
||
>>> handler.setFormatter(bf)
|
||
>>> root.addHandler(handler)
|
||
>>> logger = logging.getLogger('foo.bar')
|
||
>>> logger.debug('This is a DEBUG message')
|
||
2010-10-28 15:11:55,341 foo.bar DEBUG This is a DEBUG message
|
||
>>> logger.critical('This is a CRITICAL message')
|
||
2010-10-28 15:12:11,526 foo.bar CRITICAL This is a CRITICAL message
|
||
>>> df = logging.Formatter('$asctime $name ${levelname} $message',
|
||
... style='$')
|
||
>>> handler.setFormatter(df)
|
||
>>> logger.debug('This is a DEBUG message')
|
||
2010-10-28 15:13:06,924 foo.bar DEBUG This is a DEBUG message
|
||
>>> logger.critical('This is a CRITICAL message')
|
||
2010-10-28 15:13:11,494 foo.bar CRITICAL This is a CRITICAL message
|
||
>>>
|
||
|
||
Note that the formatting of logging messages for final output to logs is
|
||
completely independent of how an individual logging message is constructed.
|
||
That can still use %-formatting, as shown here::
|
||
|
||
>>> logger.error('This is an%s %s %s', 'other,', 'ERROR,', 'message')
|
||
2010-10-28 15:19:29,833 foo.bar ERROR This is another, ERROR, message
|
||
>>>
|
||
|
||
Logging calls (``logger.debug()``, ``logger.info()`` etc.) only take
|
||
positional parameters for the actual logging message itself, with keyword
|
||
parameters used only for determining options for how to handle the actual
|
||
logging call (e.g. the ``exc_info`` keyword parameter to indicate that
|
||
traceback information should be logged, or the ``extra`` keyword parameter
|
||
to indicate additional contextual information to be added to the log). So
|
||
you cannot directly make logging calls using :meth:`str.format` or
|
||
:class:`string.Template` syntax, because internally the logging package
|
||
uses %-formatting to merge the format string and the variable arguments.
|
||
There would no changing this while preserving backward compatibility, since
|
||
all logging calls which are out there in existing code will be using %-format
|
||
strings.
|
||
|
||
There is, however, a way that you can use {}- and $- formatting to construct
|
||
your individual log messages. Recall that for a message you can use an
|
||
arbitrary object as a message format string, and that the logging package will
|
||
call ``str()`` on that object to get the actual format string. Consider the
|
||
following two classes::
|
||
|
||
class BraceMessage:
|
||
def __init__(self, fmt, *args, **kwargs):
|
||
self.fmt = fmt
|
||
self.args = args
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
return self.fmt.format(*self.args, **self.kwargs)
|
||
|
||
class DollarMessage:
|
||
def __init__(self, fmt, **kwargs):
|
||
self.fmt = fmt
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
from string import Template
|
||
return Template(self.fmt).substitute(**self.kwargs)
|
||
|
||
Either of these can be used in place of a format string, to allow {}- or
|
||
$-formatting to be used to build the actual "message" part which appears in the
|
||
formatted log output in place of "%(message)s" or "{message}" or "$message".
|
||
It's a little unwieldy to use the class names whenever you want to log
|
||
something, but it's quite palatable if you use an alias such as __ (double
|
||
underscore – not to be confused with _, the single underscore used as a
|
||
synonym/alias for :func:`gettext.gettext` or its brethren).
|
||
|
||
The above classes are not included in Python, though they're easy enough to
|
||
copy and paste into your own code. They can be used as follows (assuming that
|
||
they're declared in a module called ``wherever``):
|
||
|
||
.. code-block:: pycon
|
||
|
||
>>> from wherever import BraceMessage as __
|
||
>>> print(__('Message with {0} {name}', 2, name='placeholders'))
|
||
Message with 2 placeholders
|
||
>>> class Point: pass
|
||
...
|
||
>>> p = Point()
|
||
>>> p.x = 0.5
|
||
>>> p.y = 0.5
|
||
>>> print(__('Message with coordinates: ({point.x:.2f}, {point.y:.2f})',
|
||
... point=p))
|
||
Message with coordinates: (0.50, 0.50)
|
||
>>> from wherever import DollarMessage as __
|
||
>>> print(__('Message with $num $what', num=2, what='placeholders'))
|
||
Message with 2 placeholders
|
||
>>>
|
||
|
||
While the above examples use ``print()`` to show how the formatting works, you
|
||
would of course use ``logger.debug()`` or similar to actually log using this
|
||
approach.
|
||
|
||
One thing to note is that you pay no significant performance penalty with this
|
||
approach: the actual formatting happens not when you make the logging call, but
|
||
when (and if) the logged message is actually about to be output to a log by a
|
||
handler. So the only slightly unusual thing which might trip you up is that the
|
||
parentheses go around the format string and the arguments, not just the format
|
||
string. That's because the __ notation is just syntax sugar for a constructor
|
||
call to one of the XXXMessage classes.
|
||
|
||
If you prefer, you can use a :class:`LoggerAdapter` to achieve a similar effect
|
||
to the above, as in the following example::
|
||
|
||
import logging
|
||
|
||
class Message(object):
|
||
def __init__(self, fmt, args):
|
||
self.fmt = fmt
|
||
self.args = args
|
||
|
||
def __str__(self):
|
||
return self.fmt.format(*self.args)
|
||
|
||
class StyleAdapter(logging.LoggerAdapter):
|
||
def __init__(self, logger, extra=None):
|
||
super(StyleAdapter, self).__init__(logger, extra or {})
|
||
|
||
def log(self, level, msg, *args, **kwargs):
|
||
if self.isEnabledFor(level):
|
||
msg, kwargs = self.process(msg, kwargs)
|
||
self.logger._log(level, Message(msg, args), (), **kwargs)
|
||
|
||
logger = StyleAdapter(logging.getLogger(__name__))
|
||
|
||
def main():
|
||
logger.debug('Hello, {}', 'world!')
|
||
|
||
if __name__ == '__main__':
|
||
logging.basicConfig(level=logging.DEBUG)
|
||
main()
|
||
|
||
The above script should log the message ``Hello, world!`` when run with
|
||
Python 3.2 or later.
|
||
|
||
|
||
.. currentmodule:: logging
|
||
|
||
.. _custom-logrecord:
|
||
|
||
Customizing ``LogRecord``
|
||
-------------------------
|
||
|
||
Every logging event is represented by a :class:`LogRecord` instance.
|
||
When an event is logged and not filtered out by a logger's level, a
|
||
:class:`LogRecord` is created, populated with information about the event and
|
||
then passed to the handlers for that logger (and its ancestors, up to and
|
||
including the logger where further propagation up the hierarchy is disabled).
|
||
Before Python 3.2, there were only two places where this creation was done:
|
||
|
||
* :meth:`Logger.makeRecord`, which is called in the normal process of
|
||
logging an event. This invoked :class:`LogRecord` directly to create an
|
||
instance.
|
||
* :func:`makeLogRecord`, which is called with a dictionary containing
|
||
attributes to be added to the LogRecord. This is typically invoked when a
|
||
suitable dictionary has been received over the network (e.g. in pickle form
|
||
via a :class:`~handlers.SocketHandler`, or in JSON form via an
|
||
:class:`~handlers.HTTPHandler`).
|
||
|
||
This has usually meant that if you need to do anything special with a
|
||
:class:`LogRecord`, you've had to do one of the following.
|
||
|
||
* Create your own :class:`Logger` subclass, which overrides
|
||
:meth:`Logger.makeRecord`, and set it using :func:`~logging.setLoggerClass`
|
||
before any loggers that you care about are instantiated.
|
||
* Add a :class:`Filter` to a logger or handler, which does the
|
||
necessary special manipulation you need when its
|
||
:meth:`~Filter.filter` method is called.
|
||
|
||
The first approach would be a little unwieldy in the scenario where (say)
|
||
several different libraries wanted to do different things. Each would attempt
|
||
to set its own :class:`Logger` subclass, and the one which did this last would
|
||
win.
|
||
|
||
The second approach works reasonably well for many cases, but does not allow
|
||
you to e.g. use a specialized subclass of :class:`LogRecord`. Library
|
||
developers can set a suitable filter on their loggers, but they would have to
|
||
remember to do this every time they introduced a new logger (which they would
|
||
do simply by adding new packages or modules and doing ::
|
||
|
||
logger = logging.getLogger(__name__)
|
||
|
||
at module level). It's probably one too many things to think about. Developers
|
||
could also add the filter to a :class:`~logging.NullHandler` attached to their
|
||
top-level logger, but this would not be invoked if an application developer
|
||
attached a handler to a lower-level library logger – so output from that
|
||
handler would not reflect the intentions of the library developer.
|
||
|
||
In Python 3.2 and later, :class:`~logging.LogRecord` creation is done through a
|
||
factory, which you can specify. The factory is just a callable you can set with
|
||
:func:`~logging.setLogRecordFactory`, and interrogate with
|
||
:func:`~logging.getLogRecordFactory`. The factory is invoked with the same
|
||
signature as the :class:`~logging.LogRecord` constructor, as :class:`LogRecord`
|
||
is the default setting for the factory.
|
||
|
||
This approach allows a custom factory to control all aspects of LogRecord
|
||
creation. For example, you could return a subclass, or just add some additional
|
||
attributes to the record once created, using a pattern similar to this::
|
||
|
||
old_factory = logging.getLogRecordFactory()
|
||
|
||
def record_factory(*args, **kwargs):
|
||
record = old_factory(*args, **kwargs)
|
||
record.custom_attribute = 0xdecafbad
|
||
return record
|
||
|
||
logging.setLogRecordFactory(record_factory)
|
||
|
||
This pattern allows different libraries to chain factories together, and as
|
||
long as they don't overwrite each other's attributes or unintentionally
|
||
overwrite the attributes provided as standard, there should be no surprises.
|
||
However, it should be borne in mind that each link in the chain adds run-time
|
||
overhead to all logging operations, and the technique should only be used when
|
||
the use of a :class:`Filter` does not provide the desired result.
|
||
|
||
|
||
.. _zeromq-handlers:
|
||
|
||
Subclassing QueueHandler - a ZeroMQ example
|
||
-------------------------------------------
|
||
|
||
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 - a ZeroMQ example
|
||
--------------------------------------------
|
||
|
||
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))
|
||
|
||
|
||
.. seealso::
|
||
|
||
Module :mod:`logging`
|
||
API reference for the logging module.
|
||
|
||
Module :mod:`logging.config`
|
||
Configuration API for the logging module.
|
||
|
||
Module :mod:`logging.handlers`
|
||
Useful handlers included with the logging module.
|
||
|
||
:ref:`A basic logging tutorial <logging-basic-tutorial>`
|
||
|
||
:ref:`A more advanced logging tutorial <logging-advanced-tutorial>`
|
||
|
||
|
||
An example dictionary-based configuration
|
||
-----------------------------------------
|
||
|
||
Below is an example of a logging configuration dictionary - it's taken from
|
||
the `documentation on the Django project <https://docs.djangoproject.com/en/1.3/topics/logging/#configuring-logging>`_.
|
||
This dictionary is passed to :func:`~config.dictConfig` to put the configuration into effect::
|
||
|
||
LOGGING = {
|
||
'version': 1,
|
||
'disable_existing_loggers': True,
|
||
'formatters': {
|
||
'verbose': {
|
||
'format': '%(levelname)s %(asctime)s %(module)s %(process)d %(thread)d %(message)s'
|
||
},
|
||
'simple': {
|
||
'format': '%(levelname)s %(message)s'
|
||
},
|
||
},
|
||
'filters': {
|
||
'special': {
|
||
'()': 'project.logging.SpecialFilter',
|
||
'foo': 'bar',
|
||
}
|
||
},
|
||
'handlers': {
|
||
'null': {
|
||
'level':'DEBUG',
|
||
'class':'django.utils.log.NullHandler',
|
||
},
|
||
'console':{
|
||
'level':'DEBUG',
|
||
'class':'logging.StreamHandler',
|
||
'formatter': 'simple'
|
||
},
|
||
'mail_admins': {
|
||
'level': 'ERROR',
|
||
'class': 'django.utils.log.AdminEmailHandler',
|
||
'filters': ['special']
|
||
}
|
||
},
|
||
'loggers': {
|
||
'django': {
|
||
'handlers':['null'],
|
||
'propagate': True,
|
||
'level':'INFO',
|
||
},
|
||
'django.request': {
|
||
'handlers': ['mail_admins'],
|
||
'level': 'ERROR',
|
||
'propagate': False,
|
||
},
|
||
'myproject.custom': {
|
||
'handlers': ['console', 'mail_admins'],
|
||
'level': 'INFO',
|
||
'filters': ['special']
|
||
}
|
||
}
|
||
}
|
||
|
||
For more information about this configuration, you can see the `relevant
|
||
section <https://docs.djangoproject.com/en/1.6/topics/logging/#configuring-logging>`_
|
||
of the Django documentation.
|
||
|
||
.. _cookbook-rotator-namer:
|
||
|
||
Using a rotator and namer to customize log rotation processing
|
||
--------------------------------------------------------------
|
||
|
||
An example of how you can define a namer and rotator is given in the following
|
||
snippet, which shows zlib-based compression of the log file::
|
||
|
||
def namer(name):
|
||
return name + ".gz"
|
||
|
||
def rotator(source, dest):
|
||
with open(source, "rb") as sf:
|
||
data = sf.read()
|
||
compressed = zlib.compress(data, 9)
|
||
with open(dest, "wb") as df:
|
||
df.write(compressed)
|
||
os.remove(source)
|
||
|
||
rh = logging.handlers.RotatingFileHandler(...)
|
||
rh.rotator = rotator
|
||
rh.namer = namer
|
||
|
||
These are not "true" .gz files, as they are bare compressed data, with no
|
||
"container" such as you’d find in an actual gzip file. This snippet is just
|
||
for illustration purposes.
|
||
|
||
A more elaborate multiprocessing example
|
||
----------------------------------------
|
||
|
||
The following working example shows how logging can be used with multiprocessing
|
||
using configuration files. The configurations are fairly simple, but serve to
|
||
illustrate how more complex ones could be implemented in a real multiprocessing
|
||
scenario.
|
||
|
||
In the example, the main process spawns a listener process and some worker
|
||
processes. Each of the main process, the listener and the workers have three
|
||
separate configurations (the workers all share the same configuration). We can
|
||
see logging in the main process, how the workers log to a QueueHandler and how
|
||
the listener implements a QueueListener and a more complex logging
|
||
configuration, and arranges to dispatch events received via the queue to the
|
||
handlers specified in the configuration. Note that these configurations are
|
||
purely illustrative, but you should be able to adapt this example to your own
|
||
scenario.
|
||
|
||
Here's the script - the docstrings and the comments hopefully explain how it
|
||
works::
|
||
|
||
import logging
|
||
import logging.config
|
||
import logging.handlers
|
||
from multiprocessing import Process, Queue, Event, current_process
|
||
import os
|
||
import random
|
||
import time
|
||
|
||
class MyHandler:
|
||
"""
|
||
A simple handler for logging events. It runs in the listener process and
|
||
dispatches events to loggers based on the name in the received record,
|
||
which then get dispatched, by the logging system, to the handlers
|
||
configured for those loggers.
|
||
"""
|
||
def handle(self, record):
|
||
logger = logging.getLogger(record.name)
|
||
# The process name is transformed just to show that it's the listener
|
||
# doing the logging to files and console
|
||
record.processName = '%s (for %s)' % (current_process().name, record.processName)
|
||
logger.handle(record)
|
||
|
||
def listener_process(q, stop_event, config):
|
||
"""
|
||
This could be done in the main process, but is just done in a separate
|
||
process for illustrative purposes.
|
||
|
||
This initialises logging according to the specified configuration,
|
||
starts the listener and waits for the main process to signal completion
|
||
via the event. The listener is then stopped, and the process exits.
|
||
"""
|
||
logging.config.dictConfig(config)
|
||
listener = logging.handlers.QueueListener(q, MyHandler())
|
||
listener.start()
|
||
if os.name == 'posix':
|
||
# On POSIX, the setup logger will have been configured in the
|
||
# parent process, but should have been disabled following the
|
||
# dictConfig call.
|
||
# On Windows, since fork isn't used, the setup logger won't
|
||
# exist in the child, so it would be created and the message
|
||
# would appear - hence the "if posix" clause.
|
||
logger = logging.getLogger('setup')
|
||
logger.critical('Should not appear, because of disabled logger ...')
|
||
stop_event.wait()
|
||
listener.stop()
|
||
|
||
def worker_process(config):
|
||
"""
|
||
A number of these are spawned for the purpose of illustration. In
|
||
practice, they could be a heterogeneous bunch of processes rather than
|
||
ones which are identical to each other.
|
||
|
||
This initialises logging according to the specified configuration,
|
||
and logs a hundred messages with random levels to randomly selected
|
||
loggers.
|
||
|
||
A small sleep is added to allow other processes a chance to run. This
|
||
is not strictly needed, but it mixes the output from the different
|
||
processes a bit more than if it's left out.
|
||
"""
|
||
logging.config.dictConfig(config)
|
||
levels = [logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR,
|
||
logging.CRITICAL]
|
||
loggers = ['foo', 'foo.bar', 'foo.bar.baz',
|
||
'spam', 'spam.ham', 'spam.ham.eggs']
|
||
if os.name == 'posix':
|
||
# On POSIX, the setup logger will have been configured in the
|
||
# parent process, but should have been disabled following the
|
||
# dictConfig call.
|
||
# On Windows, since fork isn't used, the setup logger won't
|
||
# exist in the child, so it would be created and the message
|
||
# would appear - hence the "if posix" clause.
|
||
logger = logging.getLogger('setup')
|
||
logger.critical('Should not appear, because of disabled logger ...')
|
||
for i in range(100):
|
||
lvl = random.choice(levels)
|
||
logger = logging.getLogger(random.choice(loggers))
|
||
logger.log(lvl, 'Message no. %d', i)
|
||
time.sleep(0.01)
|
||
|
||
def main():
|
||
q = Queue()
|
||
# The main process gets a simple configuration which prints to the console.
|
||
config_initial = {
|
||
'version': 1,
|
||
'formatters': {
|
||
'detailed': {
|
||
'class': 'logging.Formatter',
|
||
'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
|
||
}
|
||
},
|
||
'handlers': {
|
||
'console': {
|
||
'class': 'logging.StreamHandler',
|
||
'level': 'INFO',
|
||
},
|
||
},
|
||
'root': {
|
||
'level': 'DEBUG',
|
||
'handlers': ['console']
|
||
},
|
||
}
|
||
# The worker process configuration is just a QueueHandler attached to the
|
||
# root logger, which allows all messages to be sent to the queue.
|
||
# We disable existing loggers to disable the "setup" logger used in the
|
||
# parent process. This is needed on POSIX because the logger will
|
||
# be there in the child following a fork().
|
||
config_worker = {
|
||
'version': 1,
|
||
'disable_existing_loggers': True,
|
||
'handlers': {
|
||
'queue': {
|
||
'class': 'logging.handlers.QueueHandler',
|
||
'queue': q,
|
||
},
|
||
},
|
||
'root': {
|
||
'level': 'DEBUG',
|
||
'handlers': ['queue']
|
||
},
|
||
}
|
||
# The listener process configuration shows that the full flexibility of
|
||
# logging configuration is available to dispatch events to handlers however
|
||
# you want.
|
||
# We disable existing loggers to disable the "setup" logger used in the
|
||
# parent process. This is needed on POSIX because the logger will
|
||
# be there in the child following a fork().
|
||
config_listener = {
|
||
'version': 1,
|
||
'disable_existing_loggers': True,
|
||
'formatters': {
|
||
'detailed': {
|
||
'class': 'logging.Formatter',
|
||
'format': '%(asctime)s %(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
|
||
},
|
||
'simple': {
|
||
'class': 'logging.Formatter',
|
||
'format': '%(name)-15s %(levelname)-8s %(processName)-10s %(message)s'
|
||
}
|
||
},
|
||
'handlers': {
|
||
'console': {
|
||
'class': 'logging.StreamHandler',
|
||
'level': 'INFO',
|
||
'formatter': 'simple',
|
||
},
|
||
'file': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog.log',
|
||
'mode': 'w',
|
||
'formatter': 'detailed',
|
||
},
|
||
'foofile': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog-foo.log',
|
||
'mode': 'w',
|
||
'formatter': 'detailed',
|
||
},
|
||
'errors': {
|
||
'class': 'logging.FileHandler',
|
||
'filename': 'mplog-errors.log',
|
||
'mode': 'w',
|
||
'level': 'ERROR',
|
||
'formatter': 'detailed',
|
||
},
|
||
},
|
||
'loggers': {
|
||
'foo': {
|
||
'handlers': ['foofile']
|
||
}
|
||
},
|
||
'root': {
|
||
'level': 'DEBUG',
|
||
'handlers': ['console', 'file', 'errors']
|
||
},
|
||
}
|
||
# Log some initial events, just to show that logging in the parent works
|
||
# normally.
|
||
logging.config.dictConfig(config_initial)
|
||
logger = logging.getLogger('setup')
|
||
logger.info('About to create workers ...')
|
||
workers = []
|
||
for i in range(5):
|
||
wp = Process(target=worker_process, name='worker %d' % (i + 1),
|
||
args=(config_worker,))
|
||
workers.append(wp)
|
||
wp.start()
|
||
logger.info('Started worker: %s', wp.name)
|
||
logger.info('About to create listener ...')
|
||
stop_event = Event()
|
||
lp = Process(target=listener_process, name='listener',
|
||
args=(q, stop_event, config_listener))
|
||
lp.start()
|
||
logger.info('Started listener')
|
||
# We now hang around for the workers to finish their work.
|
||
for wp in workers:
|
||
wp.join()
|
||
# Workers all done, listening can now stop.
|
||
# Logging in the parent still works normally.
|
||
logger.info('Telling listener to stop ...')
|
||
stop_event.set()
|
||
lp.join()
|
||
logger.info('All done.')
|
||
|
||
if __name__ == '__main__':
|
||
main()
|
||
|
||
|
||
Inserting a BOM into messages sent to a SysLogHandler
|
||
-----------------------------------------------------
|
||
|
||
`RFC 5424 <http://tools.ietf.org/html/rfc5424>`_ requires that a
|
||
Unicode message be sent to a syslog daemon as a set of bytes which have the
|
||
following structure: an optional pure-ASCII component, followed by a UTF-8 Byte
|
||
Order Mark (BOM), followed by Unicode encoded using UTF-8. (See the `relevant
|
||
section of the specification <http://tools.ietf.org/html/rfc5424#section-6>`_.)
|
||
|
||
In Python 3.1, code was added to
|
||
:class:`~logging.handlers.SysLogHandler` to insert a BOM into the message, but
|
||
unfortunately, it was implemented incorrectly, with the BOM appearing at the
|
||
beginning of the message and hence not allowing any pure-ASCII component to
|
||
appear before it.
|
||
|
||
As this behaviour is broken, the incorrect BOM insertion code is being removed
|
||
from Python 3.2.4 and later. However, it is not being replaced, and if you
|
||
want to produce RFC 5424-compliant messages which include a BOM, an optional
|
||
pure-ASCII sequence before it and arbitrary Unicode after it, encoded using
|
||
UTF-8, then you need to do the following:
|
||
|
||
#. Attach a :class:`~logging.Formatter` instance to your
|
||
:class:`~logging.handlers.SysLogHandler` instance, with a format string
|
||
such as::
|
||
|
||
'ASCII section\ufeffUnicode section'
|
||
|
||
The Unicode code point U+FEFF, when encoded using UTF-8, will be
|
||
encoded as a UTF-8 BOM -- the byte-string ``b'\xef\xbb\xbf'``.
|
||
|
||
#. Replace the ASCII section with whatever placeholders you like, but make sure
|
||
that the data that appears in there after substitution is always ASCII (that
|
||
way, it will remain unchanged after UTF-8 encoding).
|
||
|
||
#. Replace the Unicode section with whatever placeholders you like; if the data
|
||
which appears there after substitution contains characters outside the ASCII
|
||
range, that's fine -- it will be encoded using UTF-8.
|
||
|
||
The formatted message *will* be encoded using UTF-8 encoding by
|
||
``SysLogHandler``. If you follow the above rules, you should be able to produce
|
||
RFC 5424-compliant messages. If you don't, logging may not complain, but your
|
||
messages will not be RFC 5424-compliant, and your syslog daemon may complain.
|
||
|
||
|
||
Implementing structured logging
|
||
-------------------------------
|
||
|
||
Although most logging messages are intended for reading by humans, and thus not
|
||
readily machine-parseable, there might be cirumstances where you want to output
|
||
messages in a structured format which *is* capable of being parsed by a program
|
||
(without needing complex regular expressions to parse the log message). This is
|
||
straightforward to achieve using the logging package. There are a number of
|
||
ways in which this could be achieved, but the following is a simple approach
|
||
which uses JSON to serialise the event in a machine-parseable manner::
|
||
|
||
import json
|
||
import logging
|
||
|
||
class StructuredMessage(object):
|
||
def __init__(self, message, **kwargs):
|
||
self.message = message
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
return '%s >>> %s' % (self.message, json.dumps(self.kwargs))
|
||
|
||
_ = StructuredMessage # optional, to improve readability
|
||
|
||
logging.basicConfig(level=logging.INFO, format='%(message)s')
|
||
logging.info(_('message 1', foo='bar', bar='baz', num=123, fnum=123.456))
|
||
|
||
If the above script is run, it prints::
|
||
|
||
message 1 >>> {"fnum": 123.456, "num": 123, "bar": "baz", "foo": "bar"}
|
||
|
||
Note that the order of items might be different according to the version of
|
||
Python used.
|
||
|
||
If you need more specialised processing, you can use a custom JSON encoder,
|
||
as in the following complete example::
|
||
|
||
from __future__ import unicode_literals
|
||
|
||
import json
|
||
import logging
|
||
|
||
# This next bit is to ensure the script runs unchanged on 2.x and 3.x
|
||
try:
|
||
unicode
|
||
except NameError:
|
||
unicode = str
|
||
|
||
class Encoder(json.JSONEncoder):
|
||
def default(self, o):
|
||
if isinstance(o, set):
|
||
return tuple(o)
|
||
elif isinstance(o, unicode):
|
||
return o.encode('unicode_escape').decode('ascii')
|
||
return super(Encoder, self).default(o)
|
||
|
||
class StructuredMessage(object):
|
||
def __init__(self, message, **kwargs):
|
||
self.message = message
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
s = Encoder().encode(self.kwargs)
|
||
return '%s >>> %s' % (self.message, s)
|
||
|
||
_ = StructuredMessage # optional, to improve readability
|
||
|
||
def main():
|
||
logging.basicConfig(level=logging.INFO, format='%(message)s')
|
||
logging.info(_('message 1', set_value={1, 2, 3}, snowman='\u2603'))
|
||
|
||
if __name__ == '__main__':
|
||
main()
|
||
|
||
When the above script is run, it prints::
|
||
|
||
message 1 >>> {"snowman": "\u2603", "set_value": [1, 2, 3]}
|
||
|
||
Note that the order of items might be different according to the version of
|
||
Python used.
|
||
|
||
|
||
.. _custom-handlers:
|
||
|
||
.. currentmodule:: logging.config
|
||
|
||
Customizing handlers with :func:`dictConfig`
|
||
--------------------------------------------
|
||
|
||
There are times when you want to customize logging handlers in particular ways,
|
||
and if you use :func:`dictConfig` you may be able to do this without
|
||
subclassing. As an example, consider that you may want to set the ownership of a
|
||
log file. On POSIX, this is easily done using :func:`shutil.chown`, but the file
|
||
handlers in the stdlib don't offer built-in support. You can customize handler
|
||
creation using a plain function such as::
|
||
|
||
def owned_file_handler(filename, mode='a', encoding=None, owner=None):
|
||
if owner:
|
||
if not os.path.exists(filename):
|
||
open(filename, 'a').close()
|
||
shutil.chown(filename, *owner)
|
||
return logging.FileHandler(filename, mode, encoding)
|
||
|
||
You can then specify, in a logging configuration passed to :func:`dictConfig`,
|
||
that a logging handler be created by calling this function::
|
||
|
||
LOGGING = {
|
||
'version': 1,
|
||
'disable_existing_loggers': False,
|
||
'formatters': {
|
||
'default': {
|
||
'format': '%(asctime)s %(levelname)s %(name)s %(message)s'
|
||
},
|
||
},
|
||
'handlers': {
|
||
'file':{
|
||
# The values below are popped from this dictionary and
|
||
# used to create the handler, set the handler's level and
|
||
# its formatter.
|
||
'()': owned_file_handler,
|
||
'level':'DEBUG',
|
||
'formatter': 'default',
|
||
# The values below are passed to the handler creator callable
|
||
# as keyword arguments.
|
||
'owner': ['pulse', 'pulse'],
|
||
'filename': 'chowntest.log',
|
||
'mode': 'w',
|
||
'encoding': 'utf-8',
|
||
},
|
||
},
|
||
'root': {
|
||
'handlers': ['file'],
|
||
'level': 'DEBUG',
|
||
},
|
||
}
|
||
|
||
In this example I am setting the ownership using the ``pulse`` user and group,
|
||
just for the purposes of illustration. Putting it together into a working
|
||
script, ``chowntest.py``::
|
||
|
||
import logging, logging.config, os, shutil
|
||
|
||
def owned_file_handler(filename, mode='a', encoding=None, owner=None):
|
||
if owner:
|
||
if not os.path.exists(filename):
|
||
open(filename, 'a').close()
|
||
shutil.chown(filename, *owner)
|
||
return logging.FileHandler(filename, mode, encoding)
|
||
|
||
LOGGING = {
|
||
'version': 1,
|
||
'disable_existing_loggers': False,
|
||
'formatters': {
|
||
'default': {
|
||
'format': '%(asctime)s %(levelname)s %(name)s %(message)s'
|
||
},
|
||
},
|
||
'handlers': {
|
||
'file':{
|
||
# The values below are popped from this dictionary and
|
||
# used to create the handler, set the handler's level and
|
||
# its formatter.
|
||
'()': owned_file_handler,
|
||
'level':'DEBUG',
|
||
'formatter': 'default',
|
||
# The values below are passed to the handler creator callable
|
||
# as keyword arguments.
|
||
'owner': ['pulse', 'pulse'],
|
||
'filename': 'chowntest.log',
|
||
'mode': 'w',
|
||
'encoding': 'utf-8',
|
||
},
|
||
},
|
||
'root': {
|
||
'handlers': ['file'],
|
||
'level': 'DEBUG',
|
||
},
|
||
}
|
||
|
||
logging.config.dictConfig(LOGGING)
|
||
logger = logging.getLogger('mylogger')
|
||
logger.debug('A debug message')
|
||
|
||
To run this, you will probably need to run as ``root``::
|
||
|
||
$ sudo python3.3 chowntest.py
|
||
$ cat chowntest.log
|
||
2013-11-05 09:34:51,128 DEBUG mylogger A debug message
|
||
$ ls -l chowntest.log
|
||
-rw-r--r-- 1 pulse pulse 55 2013-11-05 09:34 chowntest.log
|
||
|
||
Note that this example uses Python 3.3 because that's where :func:`shutil.chown`
|
||
makes an appearance. This approach should work with any Python version that
|
||
supports :func:`dictConfig` - namely, Python 2.7, 3.2 or later. With pre-3.3
|
||
versions, you would need to implement the actual ownership change using e.g.
|
||
:func:`os.chown`.
|
||
|
||
In practice, the handler-creating function may be in a utility module somewhere
|
||
in your project. Instead of the line in the configuration::
|
||
|
||
'()': owned_file_handler,
|
||
|
||
you could use e.g.::
|
||
|
||
'()': 'ext://project.util.owned_file_handler',
|
||
|
||
where ``project.util`` can be replaced with the actual name of the package
|
||
where the function resides. In the above working script, using
|
||
``'ext://__main__.owned_file_handler'`` should work. Here, the actual callable
|
||
is resolved by :func:`dictConfig` from the ``ext://`` specification.
|
||
|
||
This example hopefully also points the way to how you could implement other
|
||
types of file change - e.g. setting specific POSIX permission bits - in the
|
||
same way, using :func:`os.chmod`.
|
||
|
||
Of course, the approach could also be extended to types of handler other than a
|
||
:class:`~logging.FileHandler` - for example, one of the rotating file handlers,
|
||
or a different type of handler altogether.
|
||
|
||
|
||
.. currentmodule:: logging
|
||
|
||
.. _formatting-styles:
|
||
|
||
Using particular formatting styles throughout your application
|
||
--------------------------------------------------------------
|
||
|
||
In Python 3.2, the :class:`~logging.Formatter` gained a ``style`` keyword
|
||
parameter which, while defaulting to ``%`` for backward compatibility, allowed
|
||
the specification of ``{`` or ``$`` to support the formatting approaches
|
||
supported by :meth:`str.format` and :class:`string.Template`. Note that this
|
||
governs the formatting of logging messages for final output to logs, and is
|
||
completely orthogonal to how an individual logging message is constructed.
|
||
|
||
Logging calls (:meth:`~Logger.debug`, :meth:`~Logger.info` etc.) only take
|
||
positional parameters for the actual logging message itself, with keyword
|
||
parameters used only for determining options for how to handle the logging call
|
||
(e.g. the ``exc_info`` keyword parameter to indicate that traceback information
|
||
should be logged, or the ``extra`` keyword parameter to indicate additional
|
||
contextual information to be added to the log). So you cannot directly make
|
||
logging calls using :meth:`str.format` or :class:`string.Template` syntax,
|
||
because internally the logging package uses %-formatting to merge the format
|
||
string and the variable arguments. There would no changing this while preserving
|
||
backward compatibility, since all logging calls which are out there in existing
|
||
code will be using %-format strings.
|
||
|
||
There have been suggestions to associate format styles with specific loggers,
|
||
but that approach also runs into backward compatibility problems because any
|
||
existing code could be using a given logger name and using %-formatting.
|
||
|
||
For logging to work interoperably between any third-party libraries and your
|
||
code, decisions about formatting need to be made at the level of the
|
||
individual logging call. This opens up a couple of ways in which alternative
|
||
formatting styles can be accommodated.
|
||
|
||
|
||
Using LogRecord factories
|
||
^^^^^^^^^^^^^^^^^^^^^^^^^
|
||
|
||
In Python 3.2, along with the :class:`~logging.Formatter` changes mentioned
|
||
above, the logging package gained the ability to allow users to set their own
|
||
:class:`LogRecord` subclasses, using the :func:`setLogRecordFactory` function.
|
||
You can use this to set your own subclass of :class:`LogRecord`, which does the
|
||
Right Thing by overriding the :meth:`~LogRecord.getMessage` method. The base
|
||
class implementation of this method is where the ``msg % args`` formatting
|
||
happens, and where you can substitute your alternate formatting; however, you
|
||
should be careful to support all formatting styles and allow %-formatting as
|
||
the default, to ensure interoperability with other code. Care should also be
|
||
taken to call ``str(self.msg)``, just as the base implementation does.
|
||
|
||
Refer to the reference documentation on :func:`setLogRecordFactory` and
|
||
:class:`LogRecord` for more information.
|
||
|
||
|
||
Using custom message objects
|
||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||
|
||
There is another, perhaps simpler way that you can use {}- and $- formatting to
|
||
construct your individual log messages. You may recall (from
|
||
:ref:`arbitrary-object-messages`) that when logging you can use an arbitrary
|
||
object as a message format string, and that the logging package will call
|
||
:func:`str` on that object to get the actual format string. Consider the
|
||
following two classes::
|
||
|
||
class BraceMessage(object):
|
||
def __init__(self, fmt, *args, **kwargs):
|
||
self.fmt = fmt
|
||
self.args = args
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
return self.fmt.format(*self.args, **self.kwargs)
|
||
|
||
class DollarMessage(object):
|
||
def __init__(self, fmt, **kwargs):
|
||
self.fmt = fmt
|
||
self.kwargs = kwargs
|
||
|
||
def __str__(self):
|
||
from string import Template
|
||
return Template(self.fmt).substitute(**self.kwargs)
|
||
|
||
Either of these can be used in place of a format string, to allow {}- or
|
||
$-formatting to be used to build the actual "message" part which appears in the
|
||
formatted log output in place of “%(message)s” or “{message}” or “$message”.
|
||
If you find it a little unwieldy to use the class names whenever you want to log
|
||
something, you can make it more palatable if you use an alias such as ``M`` or
|
||
``_`` for the message (or perhaps ``__``, if you are using ``_`` for
|
||
localization).
|
||
|
||
Examples of this approach are given below. Firstly, formatting with
|
||
:meth:`str.format`::
|
||
|
||
>>> __ = BraceMessage
|
||
>>> print(__('Message with {0} {1}', 2, 'placeholders'))
|
||
Message with 2 placeholders
|
||
>>> class Point: pass
|
||
...
|
||
>>> p = Point()
|
||
>>> p.x = 0.5
|
||
>>> p.y = 0.5
|
||
>>> print(__('Message with coordinates: ({point.x:.2f}, {point.y:.2f})', point=p))
|
||
Message with coordinates: (0.50, 0.50)
|
||
|
||
Secondly, formatting with :class:`string.Template`::
|
||
|
||
>>> __ = DollarMessage
|
||
>>> print(__('Message with $num $what', num=2, what='placeholders'))
|
||
Message with 2 placeholders
|
||
>>>
|
||
|
||
One thing to note is that you pay no significant performance penalty with this
|
||
approach: the actual formatting happens not when you make the logging call, but
|
||
when (and if) the logged message is actually about to be output to a log by a
|
||
handler. So the only slightly unusual thing which might trip you up is that the
|
||
parentheses go around the format string and the arguments, not just the format
|
||
string. That’s because the __ notation is just syntax sugar for a constructor
|
||
call to one of the ``XXXMessage`` classes shown above.
|
||
|
||
|
||
.. _filters-dictconfig:
|
||
|
||
.. currentmodule:: logging.config
|
||
|
||
Configuring filters with :func:`dictConfig`
|
||
-------------------------------------------
|
||
|
||
You *can* configure filters using :func:`~logging.config.dictConfig`, though it
|
||
might not be obvious at first glance how to do it (hence this recipe). Since
|
||
:class:`~logging.Filter` is the only filter class included in the standard
|
||
library, and it is unlikely to cater to many requirements (it's only there as a
|
||
base class), you will typically need to define your own :class:`~logging.Filter`
|
||
subclass with an overridden :meth:`~logging.Filter.filter` method. To do this,
|
||
specify the ``()`` key in the configuration dictionary for the filter,
|
||
specifying a callable which will be used to create the filter (a class is the
|
||
most obvious, but you can provide any callable which returns a
|
||
:class:`~logging.Filter` instance). Here is a complete example::
|
||
|
||
import logging
|
||
import logging.config
|
||
import sys
|
||
|
||
class MyFilter(logging.Filter):
|
||
def __init__(self, param=None):
|
||
self.param = param
|
||
|
||
def filter(self, record):
|
||
if self.param is None:
|
||
allow = True
|
||
else:
|
||
allow = self.param not in record.msg
|
||
if allow:
|
||
record.msg = 'changed: ' + record.msg
|
||
return allow
|
||
|
||
LOGGING = {
|
||
'version': 1,
|
||
'filters': {
|
||
'myfilter': {
|
||
'()': MyFilter,
|
||
'param': 'noshow',
|
||
}
|
||
},
|
||
'handlers': {
|
||
'console': {
|
||
'class': 'logging.StreamHandler',
|
||
'filters': ['myfilter']
|
||
}
|
||
},
|
||
'root': {
|
||
'level': 'DEBUG',
|
||
'handlers': ['console']
|
||
},
|
||
}
|
||
|
||
if __name__ == '__main__':
|
||
logging.config.dictConfig(LOGGING)
|
||
logging.debug('hello')
|
||
logging.debug('hello - noshow')
|
||
|
||
This example shows how you can pass configuration data to the callable which
|
||
constructs the instance, in the form of keyword parameters. When run, the above
|
||
script will print::
|
||
|
||
changed: hello
|
||
|
||
which shows that the filter is working as configured.
|
||
|
||
A couple of extra points to note:
|
||
|
||
* If you can't refer to the callable directly in the configuration (e.g. if it
|
||
lives in a different module, and you can't import it directly where the
|
||
configuration dictionary is), you can use the form ``ext://...`` as described
|
||
in :ref:`logging-config-dict-externalobj`. For example, you could have used
|
||
the text ``'ext://__main__.MyFilter'`` instead of ``MyFilter`` in the above
|
||
example.
|
||
|
||
* As well as for filters, this technique can also be used to configure custom
|
||
handlers and formatters. See :ref:`logging-config-dict-userdef` for more
|
||
information on how logging supports using user-defined objects in its
|
||
configuration, and see the other cookbook recipe :ref:`custom-handlers` above.
|
||
|
||
|
||
.. _custom-format-exception:
|
||
|
||
Customized exception formatting
|
||
-------------------------------
|
||
|
||
There might be times when you want to do customized exception formatting - for
|
||
argument's sake, let's say you want exactly one line per logged event, even
|
||
when exception information is present. You can do this with a custom formatter
|
||
class, as shown in the following example::
|
||
|
||
import logging
|
||
|
||
class OneLineExceptionFormatter(logging.Formatter):
|
||
def formatException(self, exc_info):
|
||
"""
|
||
Format an exception so that it prints on a single line.
|
||
"""
|
||
result = super(OneLineExceptionFormatter, self).formatException(exc_info)
|
||
return repr(result) # or format into one line however you want to
|
||
|
||
def format(self, record):
|
||
s = super(OneLineExceptionFormatter, self).format(record)
|
||
if record.exc_text:
|
||
s = s.replace('\n', '') + '|'
|
||
return s
|
||
|
||
def configure_logging():
|
||
fh = logging.FileHandler('output.txt', 'w')
|
||
f = OneLineExceptionFormatter('%(asctime)s|%(levelname)s|%(message)s|',
|
||
'%d/%m/%Y %H:%M:%S')
|
||
fh.setFormatter(f)
|
||
root = logging.getLogger()
|
||
root.setLevel(logging.DEBUG)
|
||
root.addHandler(fh)
|
||
|
||
def main():
|
||
configure_logging()
|
||
logging.info('Sample message')
|
||
try:
|
||
x = 1 / 0
|
||
except ZeroDivisionError as e:
|
||
logging.exception('ZeroDivisionError: %s', e)
|
||
|
||
if __name__ == '__main__':
|
||
main()
|
||
|
||
When run, this produces a file with exactly two lines::
|
||
|
||
28/01/2015 07:21:23|INFO|Sample message|
|
||
28/01/2015 07:21:23|ERROR|ZeroDivisionError: integer division or modulo by zero|'Traceback (most recent call last):\n File "logtest7.py", line 30, in main\n x = 1 / 0\nZeroDivisionError: integer division or modulo by zero'|
|
||
|
||
While the above treatment is simplistic, it points the way to how exception
|
||
information can be formatted to your liking. The :mod:`traceback` module may be
|
||
helpful for more specialized needs.
|
||
|
||
.. _spoken-messages:
|
||
|
||
Speaking logging messages
|
||
-------------------------
|
||
|
||
There might be situations when it is desirable to have logging messages rendered
|
||
in an audible rather than a visible format. This is easy to do if you have text-
|
||
to-speech (TTS) functionality available in your system, even if it doesn't have
|
||
a Python binding. Most TTS systems have a command line program you can run, and
|
||
this can be invoked from a handler using :mod:`subprocess`. It's assumed here
|
||
that TTS command line programs won't expect to interact with users or take a
|
||
long time to complete, and that the frequency of logged messages will be not so
|
||
high as to swamp the user with messages, and that it's acceptable to have the
|
||
messages spoken one at a time rather than concurrently, The example implementation
|
||
below waits for one message to be spoken before the next is processed, and this
|
||
might cause other handlers to be kept waiting. Here is a short example showing
|
||
the approach, which assumes that the ``espeak`` TTS package is available::
|
||
|
||
import logging
|
||
import subprocess
|
||
import sys
|
||
|
||
class TTSHandler(logging.Handler):
|
||
def emit(self, record):
|
||
msg = self.format(record)
|
||
# Speak slowly in a female English voice
|
||
cmd = ['espeak', '-s150', '-ven+f3', msg]
|
||
p = subprocess.Popen(cmd, stdout=subprocess.PIPE,
|
||
stderr=subprocess.STDOUT)
|
||
# wait for the program to finish
|
||
p.communicate()
|
||
|
||
def configure_logging():
|
||
h = TTSHandler()
|
||
root = logging.getLogger()
|
||
root.addHandler(h)
|
||
# the default formatter just returns the message
|
||
root.setLevel(logging.DEBUG)
|
||
|
||
def main():
|
||
logging.info('Hello')
|
||
logging.debug('Goodbye')
|
||
|
||
if __name__ == '__main__':
|
||
configure_logging()
|
||
sys.exit(main())
|
||
|
||
When run, this script should say "Hello" and then "Goodbye" in a female voice.
|
||
|
||
The above approach can, of course, be adapted to other TTS systems and even
|
||
other systems altogether which can process messages via external programs run
|
||
from a command line.
|
||
|
||
|
||
.. _buffered-logging:
|
||
|
||
Buffering logging messages and outputting them conditionally
|
||
------------------------------------------------------------
|
||
|
||
There might be situations where you want to log messages in a temporary area
|
||
and only output them if a certain condition occurs. For example, you may want to
|
||
start logging debug events in a function, and if the function completes without
|
||
errors, you don't want to clutter the log with the collected debug information,
|
||
but if there is an error, you want all the debug information to be output as well
|
||
as the error.
|
||
|
||
Here is an example which shows how you could do this using a decorator for your
|
||
functions where you want logging to behave this way. It makes use of the
|
||
:class:`logging.handlers.MemoryHandler`, which allows buffering of logged events
|
||
until some condition occurs, at which point the buffered events are ``flushed``
|
||
- passed to another handler (the ``target`` handler) for processing. By default,
|
||
the ``MemoryHandler`` flushed when its buffer gets filled up or an event whose
|
||
level is greater than or equal to a specified threshold is seen. You can use this
|
||
recipe with a more specialised subclass of ``MemoryHandler`` if you want custom
|
||
flushing behavior.
|
||
|
||
The example script has a simple function, ``foo``, which just cycles through
|
||
all the logging levels, writing to ``sys.stderr`` to say what level it's about
|
||
to log at, and then actually logging a message that that level. You can pass a
|
||
parameter to ``foo`` which, if true, will log at ERROR and CRITICAL levels -
|
||
otherwise, it only logs at DEBUG, INFO and WARNING levels.
|
||
|
||
The script just arranges to decorate ``foo`` with a decorator which will do the
|
||
conditional logging that's required. The decorator takes a logger as a parameter
|
||
and attaches a memory handler for the duration of the call to the decorated
|
||
function. The decorator can be additionally parameterised using a target handler,
|
||
a level at which flushing should occur, and a capacity for the buffer. These
|
||
default to a :class:`~logging.StreamHandler` which writes to ``sys.stderr``,
|
||
``logging.ERROR`` and ``100`` respectively.
|
||
|
||
Here's the script::
|
||
|
||
import logging
|
||
from logging.handlers import MemoryHandler
|
||
import sys
|
||
|
||
logger = logging.getLogger(__name__)
|
||
logger.addHandler(logging.NullHandler())
|
||
|
||
def log_if_errors(logger, target_handler=None, flush_level=None, capacity=None):
|
||
if target_handler is None:
|
||
target_handler = logging.StreamHandler()
|
||
if flush_level is None:
|
||
flush_level = logging.ERROR
|
||
if capacity is None:
|
||
capacity = 100
|
||
handler = MemoryHandler(capacity, flushLevel=flush_level, target=target_handler)
|
||
|
||
def decorator(fn):
|
||
def wrapper(*args, **kwargs):
|
||
logger.addHandler(handler)
|
||
try:
|
||
return fn(*args, **kwargs)
|
||
except Exception:
|
||
logger.exception('call failed')
|
||
raise
|
||
finally:
|
||
super(MemoryHandler, handler).flush()
|
||
logger.removeHandler(handler)
|
||
return wrapper
|
||
|
||
return decorator
|
||
|
||
def write_line(s):
|
||
sys.stderr.write('%s\n' % s)
|
||
|
||
def foo(fail=False):
|
||
write_line('about to log at DEBUG ...')
|
||
logger.debug('Actually logged at DEBUG')
|
||
write_line('about to log at INFO ...')
|
||
logger.info('Actually logged at INFO')
|
||
write_line('about to log at WARNING ...')
|
||
logger.warning('Actually logged at WARNING')
|
||
if fail:
|
||
write_line('about to log at ERROR ...')
|
||
logger.error('Actually logged at ERROR')
|
||
write_line('about to log at CRITICAL ...')
|
||
logger.critical('Actually logged at CRITICAL')
|
||
return fail
|
||
|
||
decorated_foo = log_if_errors(logger)(foo)
|
||
|
||
if __name__ == '__main__':
|
||
logger.setLevel(logging.DEBUG)
|
||
write_line('Calling undecorated foo with False')
|
||
assert not foo(False)
|
||
write_line('Calling undecorated foo with True')
|
||
assert foo(True)
|
||
write_line('Calling decorated foo with False')
|
||
assert not decorated_foo(False)
|
||
write_line('Calling decorated foo with True')
|
||
assert decorated_foo(True)
|
||
|
||
When this script is run, the following output should be observed::
|
||
|
||
Calling undecorated foo with False
|
||
about to log at DEBUG ...
|
||
about to log at INFO ...
|
||
about to log at WARNING ...
|
||
Calling undecorated foo with True
|
||
about to log at DEBUG ...
|
||
about to log at INFO ...
|
||
about to log at WARNING ...
|
||
about to log at ERROR ...
|
||
about to log at CRITICAL ...
|
||
Calling decorated foo with False
|
||
about to log at DEBUG ...
|
||
about to log at INFO ...
|
||
about to log at WARNING ...
|
||
Calling decorated foo with True
|
||
about to log at DEBUG ...
|
||
about to log at INFO ...
|
||
about to log at WARNING ...
|
||
about to log at ERROR ...
|
||
Actually logged at DEBUG
|
||
Actually logged at INFO
|
||
Actually logged at WARNING
|
||
Actually logged at ERROR
|
||
about to log at CRITICAL ...
|
||
Actually logged at CRITICAL
|
||
|
||
As you can see, actual logging output only occurs when an event is logged whose
|
||
severity is ERROR or greater, but in that case, any previous events at lower
|
||
severities are also logged.
|
||
|
||
You can of course use the conventional means of decoration::
|
||
|
||
@log_if_errors(logger)
|
||
def foo(fail=False):
|
||
...
|
||
|
||
|
||
.. _utc-formatting:
|
||
|
||
Formatting times using UTC (GMT) via configuration
|
||
--------------------------------------------------
|
||
|
||
Sometimes you want to format times using UTC, which can be done using a class
|
||
such as `UTCFormatter`, shown below::
|
||
|
||
import logging
|
||
import time
|
||
|
||
class UTCFormatter(logging.Formatter):
|
||
converter = time.gmtime
|
||
|
||
and you can then use the ``UTCFormatter`` in your code instead of
|
||
:class:`~logging.Formatter`. If you want to do that via configuration, you can
|
||
use the :func:`~logging.config.dictConfig` API with an approach illustrated by
|
||
the following complete example::
|
||
|
||
import logging
|
||
import logging.config
|
||
import time
|
||
|
||
class UTCFormatter(logging.Formatter):
|
||
converter = time.gmtime
|
||
|
||
LOGGING = {
|
||
'version': 1,
|
||
'disable_existing_loggers': False,
|
||
'formatters': {
|
||
'utc': {
|
||
'()': UTCFormatter,
|
||
'format': '%(asctime)s %(message)s',
|
||
},
|
||
'local': {
|
||
'format': '%(asctime)s %(message)s',
|
||
}
|
||
},
|
||
'handlers': {
|
||
'console1': {
|
||
'class': 'logging.StreamHandler',
|
||
'formatter': 'utc',
|
||
},
|
||
'console2': {
|
||
'class': 'logging.StreamHandler',
|
||
'formatter': 'local',
|
||
},
|
||
},
|
||
'root': {
|
||
'handlers': ['console1', 'console2'],
|
||
}
|
||
}
|
||
|
||
if __name__ == '__main__':
|
||
logging.config.dictConfig(LOGGING)
|
||
logging.warning('The local time is %s', time.asctime())
|
||
|
||
When this script is run, it should print something like::
|
||
|
||
2015-10-17 12:53:29,501 The local time is Sat Oct 17 13:53:29 2015
|
||
2015-10-17 13:53:29,501 The local time is Sat Oct 17 13:53:29 2015
|
||
|
||
showing how the time is formatted both as local time and UTC, one for each
|
||
handler.
|