1233 lines
50 KiB
ReStructuredText
1233 lines
50 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 :func:`addHandler` method has no minimum
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or maximum quota for the number of handlers you may add. Sometimes it will be
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beneficial for an application to log all messages of all severities to a text
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file while simultaneously logging errors or above to the console. To set this
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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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.. _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 = 1
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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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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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|
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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()
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|
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if __name__ == '__main__':
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main()
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|
||
First run the server, and then the client. On the client side, nothing is
|
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printed on the console; on the server side, you should see something like::
|
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|
||
About to start TCP server...
|
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59 root INFO Jackdaws love my big sphinx of quartz.
|
||
59 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim.
|
||
69 myapp.area1 INFO How quickly daft jumping zebras vex.
|
||
69 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack.
|
||
69 myapp.area2 ERROR The five boxing wizards jump quickly.
|
||
|
||
Note that there are some security issues with pickle in some scenarios. If
|
||
these affect you, you can use an alternative serialization scheme by overriding
|
||
the :meth:`makePickle` method and implementing your alternative there, as
|
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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
|
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addition to the parameters passed to the logging call. For example, in a
|
||
networked application, it may be desirable to log client-specific information
|
||
in the log (e.g. remote client's username, or IP address). Although you could
|
||
use the *extra* parameter to achieve this, it's not always convenient to pass
|
||
the information in this way. While it might be tempting to create
|
||
:class:`Logger` instances on a per-connection basis, this is not a good idea
|
||
because these instances are not garbage collected. While this is not a problem
|
||
in practice, when the number of :class:`Logger` instances is dependent on the
|
||
level of granularity you want to use in logging an application, it could
|
||
be hard to manage if the number of :class:`Logger` instances becomes
|
||
effectively unbounded.
|
||
|
||
|
||
Using LoggerAdapters to impart contextual information
|
||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||
|
||
An easy way in which you can pass contextual information to be output along
|
||
with logging event information is to use the :class:`LoggerAdapter` class.
|
||
This class is designed to look like a :class:`Logger`, so that you can call
|
||
:meth:`debug`, :meth:`info`, :meth:`warning`, :meth:`error`,
|
||
:meth:`exception`, :meth:`critical` and :meth:`log`. These methods have the
|
||
same signatures as their counterparts in :class:`Logger`, so you can use the
|
||
two types of instances interchangeably.
|
||
|
||
When you create an instance of :class:`LoggerAdapter`, you pass it a
|
||
:class:`Logger` instance and a dict-like object which contains your contextual
|
||
information. When you call one of the logging methods on an instance of
|
||
:class:`LoggerAdapter`, it delegates the call to the underlying instance of
|
||
:class:`Logger` passed to its constructor, and arranges to pass the contextual
|
||
information in the delegated call. Here's a snippet from the code of
|
||
:class:`LoggerAdapter`::
|
||
|
||
def debug(self, msg, *args, **kwargs):
|
||
"""
|
||
Delegate a debug call to the underlying logger, after adding
|
||
contextual information from this adapter instance.
|
||
"""
|
||
msg, kwargs = self.process(msg, kwargs)
|
||
self.logger.debug(msg, *args, **kwargs)
|
||
|
||
The :meth:`process` method of :class:`LoggerAdapter` is where the contextual
|
||
information is added to the logging output. It's passed the message and
|
||
keyword arguments of the logging call, and it passes back (potentially)
|
||
modified versions of these to use in the call to the underlying logger. The
|
||
default implementation of this method leaves the message alone, but inserts
|
||
an 'extra' key in the keyword argument whose value is the dict-like object
|
||
passed to the constructor. Of course, if you had passed an 'extra' keyword
|
||
argument in the call to the adapter, it will be silently overwritten.
|
||
|
||
The advantage of using 'extra' is that the values in the dict-like object are
|
||
merged into the :class:`LogRecord` instance's __dict__, allowing you to use
|
||
customized strings with your :class:`Formatter` instances which know about
|
||
the keys of the dict-like object. If you need a different method, e.g. if you
|
||
want to prepend or append the contextual information to the message string,
|
||
you just need to subclass :class:`LoggerAdapter` and override :meth:`process`
|
||
to do what you need. Here's an example script which uses this class, which
|
||
also illustrates what dict-like behaviour is needed from an arbitrary
|
||
'dict-like' object for use in the constructor::
|
||
|
||
import logging
|
||
|
||
class ConnInfo:
|
||
"""
|
||
An example class which shows how an arbitrary class can be used as
|
||
the 'extra' context information repository passed to a LoggerAdapter.
|
||
"""
|
||
|
||
def __getitem__(self, name):
|
||
"""
|
||
To allow this instance to look like a dict.
|
||
"""
|
||
from random import choice
|
||
if name == 'ip':
|
||
result = choice(['127.0.0.1', '192.168.0.1'])
|
||
elif name == 'user':
|
||
result = choice(['jim', 'fred', 'sheila'])
|
||
else:
|
||
result = self.__dict__.get(name, '?')
|
||
return result
|
||
|
||
def __iter__(self):
|
||
"""
|
||
To allow iteration over keys, which will be merged into
|
||
the LogRecord dict before formatting and output.
|
||
"""
|
||
keys = ['ip', 'user']
|
||
keys.extend(self.__dict__.keys())
|
||
return keys.__iter__()
|
||
|
||
if __name__ == '__main__':
|
||
from random import choice
|
||
levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
|
||
a1 = logging.LoggerAdapter(logging.getLogger('a.b.c'),
|
||
{ 'ip' : '123.231.231.123', 'user' : 'sheila' })
|
||
logging.basicConfig(level=logging.DEBUG,
|
||
format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s')
|
||
a1.debug('A debug message')
|
||
a1.info('An info message with %s', 'some parameters')
|
||
a2 = logging.LoggerAdapter(logging.getLogger('d.e.f'), ConnInfo())
|
||
for x in range(10):
|
||
lvl = choice(levels)
|
||
lvlname = logging.getLevelName(lvl)
|
||
a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters')
|
||
|
||
When this script is run, the output should look something like this::
|
||
|
||
2008-01-18 14:49:54,023 a.b.c DEBUG IP: 123.231.231.123 User: sheila A debug message
|
||
2008-01-18 14:49:54,023 a.b.c INFO IP: 123.231.231.123 User: sheila An info message with some parameters
|
||
2008-01-18 14:49:54,023 d.e.f CRITICAL IP: 192.168.0.1 User: jim A message at CRITICAL level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: jim A message at INFO level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: fred A message at ERROR level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: sheila A message at ERROR level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: jim A message at WARNING level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: fred A message at INFO level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
|
||
2008-01-18 14:49:54,033 d.e.f WARNING IP: 127.0.0.1 User: jim A message at WARNING level with 2 parameters
|
||
|
||
|
||
.. _filters-contextual:
|
||
|
||
Using Filters to impart contextual information
|
||
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
|
||
|
||
You can also add contextual information to log output using a user-defined
|
||
:class:`Filter`. ``Filter`` instances are allowed to modify the ``LogRecords``
|
||
passed to them, including adding additional attributes which can then be output
|
||
using a suitable format string, or if needed a custom :class:`Formatter`.
|
||
|
||
For example in a web application, the request being processed (or at least,
|
||
the interesting parts of it) can be stored in a threadlocal
|
||
(:class:`threading.local`) variable, and then accessed from a ``Filter`` to
|
||
add, say, information from the request - say, the remote IP address and remote
|
||
user's username - to the ``LogRecord``, using the attribute names 'ip' and
|
||
'user' as in the ``LoggerAdapter`` example above. In that case, the same format
|
||
string can be used to get similar output to that shown above. Here's an example
|
||
script::
|
||
|
||
import logging
|
||
from random import choice
|
||
|
||
class ContextFilter(logging.Filter):
|
||
"""
|
||
This is a filter which injects contextual information into the log.
|
||
|
||
Rather than use actual contextual information, we just use random
|
||
data in this demo.
|
||
"""
|
||
|
||
USERS = ['jim', 'fred', 'sheila']
|
||
IPS = ['123.231.231.123', '127.0.0.1', '192.168.0.1']
|
||
|
||
def filter(self, record):
|
||
|
||
record.ip = choice(ContextFilter.IPS)
|
||
record.user = choice(ContextFilter.USERS)
|
||
return True
|
||
|
||
if __name__ == '__main__':
|
||
levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
|
||
logging.basicConfig(level=logging.DEBUG,
|
||
format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s')
|
||
a1 = logging.getLogger('a.b.c')
|
||
a2 = logging.getLogger('d.e.f')
|
||
|
||
f = ContextFilter()
|
||
a1.addFilter(f)
|
||
a2.addFilter(f)
|
||
a1.debug('A debug message')
|
||
a1.info('An info message with %s', 'some parameters')
|
||
for x in range(10):
|
||
lvl = choice(levels)
|
||
lvlname = logging.getLevelName(lvl)
|
||
a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters')
|
||
|
||
which, when run, produces something like::
|
||
|
||
2010-09-06 22:38:15,292 a.b.c DEBUG IP: 123.231.231.123 User: fred A debug message
|
||
2010-09-06 22:38:15,300 a.b.c INFO IP: 192.168.0.1 User: sheila An info message with some parameters
|
||
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1 User: sheila A message at CRITICAL level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f ERROR IP: 127.0.0.1 User: jim A message at ERROR level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f DEBUG IP: 127.0.0.1 User: sheila A message at DEBUG level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f ERROR IP: 123.231.231.123 User: fred A message at ERROR level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 192.168.0.1 User: jim A message at CRITICAL level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1 User: sheila A message at CRITICAL level with 2 parameters
|
||
2010-09-06 22:38:15,300 d.e.f DEBUG IP: 192.168.0.1 User: jim A message at DEBUG level with 2 parameters
|
||
2010-09-06 22:38:15,301 d.e.f ERROR IP: 127.0.0.1 User: sheila A message at ERROR level with 2 parameters
|
||
2010-09-06 22:38:15,301 d.e.f DEBUG IP: 123.231.231.123 User: fred A message at DEBUG level with 2 parameters
|
||
2010-09-06 22:38:15,301 d.e.f INFO IP: 123.231.231.123 User: fred A message at INFO level with 2 parameters
|
||
|
||
|
||
.. _multiple-processes:
|
||
|
||
Logging to a single file from multiple processes
|
||
------------------------------------------------
|
||
|
||
Although logging is thread-safe, and logging to a single file from multiple
|
||
threads in a single process *is* supported, logging to a single file from
|
||
*multiple processes* is *not* supported, because there is no standard way to
|
||
serialize access to a single file across multiple processes in Python. If you
|
||
need to log to a single file from multiple processes, one way of doing this is
|
||
to have all the processes log to a :class:`SocketHandler`, and have a separate
|
||
process which implements a socket server which reads from the socket and logs
|
||
to file. (If you prefer, you can dedicate one thread in one of the existing
|
||
processes to perform this function.) :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:`Lock` class from this module to serialize access to the file from
|
||
your processes. The existing :class:`FileHandler` and subclasses do not make
|
||
use of :mod:`multiprocessing` at present, though they may do so in the future.
|
||
Note that at present, the :mod:`multiprocessing` module does not provide
|
||
working lock functionality on all platforms (see
|
||
http://bugs.python.org/issue3770).
|
||
|
||
.. currentmodule:: logging.handlers
|
||
|
||
Alternatively, you can use a ``Queue`` and a :class:`QueueHandler` to send
|
||
all logging events to one of the processes in your multi-process application.
|
||
The following example script demonstrates how you can do this; in the example
|
||
a separate listener process listens for events sent by other processes and logs
|
||
them according to its own logging configuration. Although the example only
|
||
demonstrates one way of doing it (for example, you may want to use a listener
|
||
thread rather than a separate listener process -- the implementation would be
|
||
analogous) it does allow for completely different logging configurations for
|
||
the listener and the other processes in your application, and can be used as
|
||
the basis for code meeting your own specific requirements::
|
||
|
||
# You'll need these imports in your own code
|
||
import logging
|
||
import logging.handlers
|
||
import multiprocessing
|
||
|
||
# Next two import lines for this demo only
|
||
from random import choice, random
|
||
import time
|
||
|
||
#
|
||
# Because you'll want to define the logging configurations for listener and workers, the
|
||
# listener and worker process functions take a configurer parameter which is a callable
|
||
# for configuring logging for that process. These functions are also passed the queue,
|
||
# which they use for communication.
|
||
#
|
||
# In practice, you can configure the listener however you want, but note that in this
|
||
# simple example, the listener does not apply level or filter logic to received records.
|
||
# In practice, you would probably want to do 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 (KeyboardInterrupt, SystemExit):
|
||
raise
|
||
except:
|
||
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:`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:
|
||
string.Template (added in Python 2.4) and str.format (added in Python 2.6).
|
||
|
||
Logging now (as of 3.2) provides improved support for these two additional
|
||
formatting styles. The :class:`Formatter` class been enhanced for Python 3.2 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(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".
|
||
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} {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)
|
||
>>> from wherever import DollarMessage as __
|
||
>>> 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.
|
||
|
||
|
||
.. _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:`~logging.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/1.3/topics/logging/#configuring-logging>`_
|
||
of the Django documentation.
|