Edit File: logging-cookbook.txt
.. _logging-cookbook: ================ Logging Cookbook ================ :Author: Vinay Sajip <vinay_sajip at red-dove dot com> This page contains a number of recipes related to logging, which have been found useful in the past. .. currentmodule:: logging Using logging in multiple modules --------------------------------- Multiple calls to ``logging.getLogger('someLogger')`` return a reference to the same logger object. This is true not only within the same module, but also across modules as long as it is in the same Python interpreter process. It is true for references to the same object; additionally, application code can define and configure a parent logger in one module and create (but not configure) a child logger in a separate module, and all logger calls to the child will pass up to the parent. Here is a main module:: import logging import auxiliary_module # create logger with 'spam_application' logger = logging.getLogger('spam_application') logger.setLevel(logging.DEBUG) # create file handler which logs even debug messages fh = logging.FileHandler('spam.log') fh.setLevel(logging.DEBUG) # create console handler with a higher log level ch = logging.StreamHandler() ch.setLevel(logging.ERROR) # create formatter and add it to the handlers formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') fh.setFormatter(formatter) ch.setFormatter(formatter) # add the handlers to the logger logger.addHandler(fh) logger.addHandler(ch) logger.info('creating an instance of auxiliary_module.Auxiliary') a = auxiliary_module.Auxiliary() logger.info('created an instance of auxiliary_module.Auxiliary') logger.info('calling auxiliary_module.Auxiliary.do_something') a.do_something() logger.info('finished auxiliary_module.Auxiliary.do_something') logger.info('calling auxiliary_module.some_function()') auxiliary_module.some_function() logger.info('done with auxiliary_module.some_function()') Here is the auxiliary module:: import logging # create logger module_logger = logging.getLogger('spam_application.auxiliary') class Auxiliary: def __init__(self): self.logger = logging.getLogger('spam_application.auxiliary.Auxiliary') self.logger.info('creating an instance of Auxiliary') def do_something(self): self.logger.info('doing something') a = 1 + 1 self.logger.info('done doing something') def some_function(): module_logger.info('received a call to "some_function"') The output looks like this:: 2005-03-23 23:47:11,663 - spam_application - INFO - creating an instance of auxiliary_module.Auxiliary 2005-03-23 23:47:11,665 - spam_application.auxiliary.Auxiliary - INFO - creating an instance of Auxiliary 2005-03-23 23:47:11,665 - spam_application - INFO - created an instance of auxiliary_module.Auxiliary 2005-03-23 23:47:11,668 - spam_application - INFO - calling auxiliary_module.Auxiliary.do_something 2005-03-23 23:47:11,668 - spam_application.auxiliary.Auxiliary - INFO - doing something 2005-03-23 23:47:11,669 - spam_application.auxiliary.Auxiliary - INFO - done doing something 2005-03-23 23:47:11,670 - spam_application - INFO - finished auxiliary_module.Auxiliary.do_something 2005-03-23 23:47:11,671 - spam_application - INFO - calling auxiliary_module.some_function() 2005-03-23 23:47:11,672 - spam_application.auxiliary - INFO - received a call to 'some_function' 2005-03-23 23:47:11,673 - spam_application - INFO - done with auxiliary_module.some_function() Multiple handlers and formatters -------------------------------- Loggers are plain Python objects. The :func:`addHandler` method has no minimum or maximum quota for the number of handlers you may add. Sometimes it will be beneficial for an application to log all messages of all severities to a text file while simultaneously logging errors or above to the console. To set this up, simply configure the appropriate handlers. The logging calls in the application code will remain unchanged. Here is a slight modification to the previous simple module-based configuration example:: import logging logger = logging.getLogger('simple_example') logger.setLevel(logging.DEBUG) # create file handler which logs even debug messages fh = logging.FileHandler('spam.log') fh.setLevel(logging.DEBUG) # create console handler with a higher log level ch = logging.StreamHandler() ch.setLevel(logging.ERROR) # create formatter and add it to the handlers formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') ch.setFormatter(formatter) fh.setFormatter(formatter) # add the handlers to logger logger.addHandler(ch) logger.addHandler(fh) # 'application' code logger.debug('debug message') logger.info('info message') logger.warn('warn message') logger.error('error message') logger.critical('critical message') Notice that the 'application' code does not care about multiple handlers. All that changed was the addition and configuration of a new handler named *fh*. The ability to create new handlers with higher- or lower-severity filters can be very helpful when writing and testing an application. Instead of using many ``print`` statements for debugging, use ``logger.debug``: Unlike the print statements, which you will have to delete or comment out later, the logger.debug statements can remain intact in the source code and remain dormant until you need them again. At that time, the only change that needs to happen is to modify the severity level of the logger and/or handler to debug. .. _multiple-destinations: Logging to multiple destinations -------------------------------- Let's say you want to log to console and file with different message formats and in differing circumstances. Say you want to log messages with levels of DEBUG and higher to file, and those messages at level INFO and higher to the console. Let's also assume that the file should contain timestamps, but the console messages should not. Here's how you can achieve this:: import logging # set up logging to file - see previous section for more details logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s', datefmt='%m-%d %H:%M', filename='/temp/myapp.log', filemode='w') # define a Handler which writes INFO messages or higher to the sys.stderr console = logging.StreamHandler() console.setLevel(logging.INFO) # set a format which is simpler for console use formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s') # tell the handler to use this format console.setFormatter(formatter) # add the handler to the root logger logging.getLogger('').addHandler(console) # Now, we can log to the root logger, or any other logger. First the root... logging.info('Jackdaws love my big sphinx of quartz.') # Now, define a couple of other loggers which might represent areas in your # application: logger1 = logging.getLogger('myapp.area1') logger2 = logging.getLogger('myapp.area2') logger1.debug('Quick zephyrs blow, vexing daft Jim.') logger1.info('How quickly daft jumping zebras vex.') logger2.warning('Jail zesty vixen who grabbed pay from quack.') logger2.error('The five boxing wizards jump quickly.') When you run this, on the console you will see :: root : INFO Jackdaws love my big sphinx of quartz. myapp.area1 : INFO How quickly daft jumping zebras vex. myapp.area2 : WARNING Jail zesty vixen who grabbed pay from quack. myapp.area2 : ERROR The five boxing wizards jump quickly. and in the file you will see something like :: 10-22 22:19 root INFO Jackdaws love my big sphinx of quartz. 10-22 22:19 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim. 10-22 22:19 myapp.area1 INFO How quickly daft jumping zebras vex. 10-22 22:19 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack. 10-22 22:19 myapp.area2 ERROR The five boxing wizards jump quickly. As you can see, the DEBUG message only shows up in the file. The other messages are sent to both destinations. This example uses console and file handlers, but you can use any number and combination of handlers you choose. Configuration server example ---------------------------- Here is an example of a module using the logging configuration server:: import logging import logging.config import time import os # read initial config file logging.config.fileConfig('logging.conf') # create and start listener on port 9999 t = logging.config.listen(9999) t.start() logger = logging.getLogger('simpleExample') try: # loop through logging calls to see the difference # new configurations make, until Ctrl+C is pressed while True: logger.debug('debug message') logger.info('info message') logger.warn('warn message') logger.error('error message') logger.critical('critical message') time.sleep(5) except KeyboardInterrupt: # cleanup logging.config.stopListening() t.join() And here is a script that takes a filename and sends that file to the server, properly preceded with the binary-encoded length, as the new logging configuration:: #!/usr/bin/env python import socket, sys, struct with open(sys.argv[1], 'rb') as f: data_to_send = f.read() HOST = 'localhost' PORT = 9999 s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) print('connecting...') s.connect((HOST, PORT)) print('sending config...') s.send(struct.pack('>L', len(data_to_send))) s.send(data_to_send) s.close() print('complete') .. _network-logging: Sending and receiving logging events across a network ----------------------------------------------------- Let's say you want to send logging events across a network, and handle them at the receiving end. A simple way of doing this is attaching a :class:`SocketHandler` instance to the root logger at the sending end:: import logging, logging.handlers rootLogger = logging.getLogger('') rootLogger.setLevel(logging.DEBUG) socketHandler = logging.handlers.SocketHandler('localhost', logging.handlers.DEFAULT_TCP_LOGGING_PORT) # don't bother with a formatter, since a socket handler sends the event as # an unformatted pickle rootLogger.addHandler(socketHandler) # Now, we can log to the root logger, or any other logger. First the root... logging.info('Jackdaws love my big sphinx of quartz.') # Now, define a couple of other loggers which might represent areas in your # application: logger1 = logging.getLogger('myapp.area1') logger2 = logging.getLogger('myapp.area2') logger1.debug('Quick zephyrs blow, vexing daft Jim.') logger1.info('How quickly daft jumping zebras vex.') logger2.warning('Jail zesty vixen who grabbed pay from quack.') logger2.error('The five boxing wizards jump quickly.') At the receiving end, you can set up a receiver using the :mod:`SocketServer` module. Here is a basic working example:: import pickle import logging import logging.handlers import SocketServer import struct class LogRecordStreamHandler(SocketServer.StreamRequestHandler): """Handler for a streaming logging request. This basically logs the record using whatever logging policy is configured locally. """ def handle(self): """ Handle multiple requests - each expected to be a 4-byte length, followed by the LogRecord in pickle format. Logs the record according to whatever policy is configured locally. """ while True: chunk = self.connection.recv(4) if len(chunk) < 4: break slen = struct.unpack('>L', chunk)[0] chunk = self.connection.recv(slen) while len(chunk) < slen: chunk = chunk + self.connection.recv(slen - len(chunk)) obj = self.unPickle(chunk) record = logging.makeLogRecord(obj) self.handleLogRecord(record) def unPickle(self, data): return pickle.loads(data) def handleLogRecord(self, record): # if a name is specified, we use the named logger rather than the one # implied by the record. if self.server.logname is not None: name = self.server.logname else: name = record.name logger = logging.getLogger(name) # N.B. EVERY record gets logged. This is because Logger.handle # is normally called AFTER logger-level filtering. If you want # to do filtering, do it at the client end to save wasting # cycles and network bandwidth! logger.handle(record) class LogRecordSocketReceiver(SocketServer.ThreadingTCPServer): """ Simple TCP socket-based logging receiver suitable for testing. """ allow_reuse_address = 1 def __init__(self, host='localhost', port=logging.handlers.DEFAULT_TCP_LOGGING_PORT, handler=LogRecordStreamHandler): SocketServer.ThreadingTCPServer.__init__(self, (host, port), handler) self.abort = 0 self.timeout = 1 self.logname = None def serve_until_stopped(self): import select abort = 0 while not abort: rd, wr, ex = select.select([self.socket.fileno()], [], [], self.timeout) if rd: self.handle_request() abort = self.abort def main(): logging.basicConfig( format='%(relativeCreated)5d %(name)-15s %(levelname)-8s %(message)s') tcpserver = LogRecordSocketReceiver() print('About to start TCP server...') tcpserver.serve_until_stopped() if __name__ == '__main__': main() First run the server, and then the client. On the client side, nothing is printed on the console; on the server side, you should see something like:: About to start TCP server... 59 root INFO Jackdaws love my big sphinx of quartz. 59 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim. 69 myapp.area1 INFO How quickly daft jumping zebras vex. 69 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack. 69 myapp.area2 ERROR The five boxing wizards jump quickly. Note that there are some security issues with pickle in some scenarios. If these affect you, you can use an alternative serialization scheme by overriding the :meth:`makePickle` method and implementing your alternative there, as well as adapting the above script to use your alternative serialization. .. _context-info: Adding contextual information to your logging output ---------------------------------------------------- Sometimes you want logging output to contain contextual information in addition to the parameters passed to the logging call. For example, in a networked application, it may be desirable to log client-specific information in the log (e.g. remote client's username, or IP address). Although you could use the *extra* parameter to achieve this, it's not always convenient to pass the information in this way. While it might be tempting to create :class:`Logger` instances on a per-connection basis, this is not a good idea because these instances are not garbage collected. While this is not a problem in practice, when the number of :class:`Logger` instances is dependent on the level of granularity you want to use in logging an application, it could be hard to manage if the number of :class:`Logger` instances becomes effectively unbounded. Using LoggerAdapters to impart contextual information ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ An easy way in which you can pass contextual information to be output along with logging event information is to use the :class:`LoggerAdapter` class. This class is designed to look like a :class:`Logger`, so that you can call :meth:`debug`, :meth:`info`, :meth:`warning`, :meth:`error`, :meth:`exception`, :meth:`critical` and :meth:`log`. These methods have the same signatures as their counterparts in :class:`Logger`, so you can use the two types of instances interchangeably. When you create an instance of :class:`LoggerAdapter`, you pass it a :class:`Logger` instance and a dict-like object which contains your contextual information. When you call one of the logging methods on an instance of :class:`LoggerAdapter`, it delegates the call to the underlying instance of :class:`Logger` passed to its constructor, and arranges to pass the contextual information in the delegated call. Here's a snippet from the code of :class:`LoggerAdapter`:: def debug(self, msg, *args, **kwargs): """ Delegate a debug call to the underlying logger, after adding contextual information from this adapter instance. """ msg, kwargs = self.process(msg, kwargs) self.logger.debug(msg, *args, **kwargs) The :meth:`process` method of :class:`LoggerAdapter` is where the contextual information is added to the logging output. It's passed the message and keyword arguments of the logging call, and it passes back (potentially) modified versions of these to use in the call to the underlying logger. The default implementation of this method leaves the message alone, but inserts an 'extra' key in the keyword argument whose value is the dict-like object passed to the constructor. Of course, if you had passed an 'extra' keyword argument in the call to the adapter, it will be silently overwritten. The advantage of using 'extra' is that the values in the dict-like object are merged into the :class:`LogRecord` instance's __dict__, allowing you to use customized strings with your :class:`Formatter` instances which know about the keys of the dict-like object. If you need a different method, e.g. if you want to prepend or append the contextual information to the message string, you just need to subclass :class:`LoggerAdapter` and override :meth:`process` to do what you need. Here's an example script which uses this class, which also illustrates what dict-like behaviour is needed from an arbitrary 'dict-like' object for use in the constructor:: import logging class ConnInfo: """ An example class which shows how an arbitrary class can be used as the 'extra' context information repository passed to a LoggerAdapter. """ def __getitem__(self, name): """ To allow this instance to look like a dict. """ from random import choice if name == 'ip': result = choice(['127.0.0.1', '192.168.0.1']) elif name == 'user': result = choice(['jim', 'fred', 'sheila']) else: result = self.__dict__.get(name, '?') return result def __iter__(self): """ To allow iteration over keys, which will be merged into the LogRecord dict before formatting and output. """ keys = ['ip', 'user'] keys.extend(self.__dict__.keys()) return keys.__iter__() if __name__ == '__main__': from random import choice levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL) a1 = logging.LoggerAdapter(logging.getLogger('a.b.c'), { 'ip' : '123.231.231.123', 'user' : 'sheila' }) logging.basicConfig(level=logging.DEBUG, format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s') a1.debug('A debug message') a1.info('An info message with %s', 'some parameters') a2 = logging.LoggerAdapter(logging.getLogger('d.e.f'), ConnInfo()) for x in range(10): lvl = choice(levels) lvlname = logging.getLevelName(lvl) a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters') When this script is run, the output should look something like this:: 2008-01-18 14:49:54,023 a.b.c DEBUG IP: 123.231.231.123 User: sheila A debug message 2008-01-18 14:49:54,023 a.b.c INFO IP: 123.231.231.123 User: sheila An info message with some parameters 2008-01-18 14:49:54,023 d.e.f CRITICAL IP: 192.168.0.1 User: jim A message at CRITICAL level with 2 parameters 2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: jim A message at INFO level with 2 parameters 2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters 2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: fred A message at ERROR level with 2 parameters 2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: sheila A message at ERROR level with 2 parameters 2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters 2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: jim A message at WARNING level with 2 parameters 2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: fred A message at INFO level with 2 parameters 2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters 2008-01-18 14:49:54,033 d.e.f WARNING IP: 127.0.0.1 User: jim A message at WARNING level with 2 parameters .. _filters-contextual: Using Filters to impart contextual information ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ You can also add contextual information to log output using a user-defined :class:`Filter`. ``Filter`` instances are allowed to modify the ``LogRecords`` passed to them, including adding additional attributes which can then be output using a suitable format string, or if needed a custom :class:`Formatter`. For example in a web application, the request being processed (or at least, the interesting parts of it) can be stored in a threadlocal (:class:`threading.local`) variable, and then accessed from a ``Filter`` to add, say, information from the request - say, the remote IP address and remote user's username - to the ``LogRecord``, using the attribute names 'ip' and 'user' as in the ``LoggerAdapter`` example above. In that case, the same format string can be used to get similar output to that shown above. Here's an example script:: import logging from random import choice class ContextFilter(logging.Filter): """ This is a filter which injects contextual information into the log. Rather than use actual contextual information, we just use random data in this demo. """ USERS = ['jim', 'fred', 'sheila'] IPS = ['123.231.231.123', '127.0.0.1', '192.168.0.1'] def filter(self, record): record.ip = choice(ContextFilter.IPS) record.user = choice(ContextFilter.USERS) return True if __name__ == '__main__': levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL) 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 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. 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. 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 2.6 and 2.7, 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 2.7.4 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:: u'ASCII section\ufeffUnicode section' The Unicode code point ``u'\ufeff'``, when encoded using UTF-8, will be encoded as a UTF-8 BOM -- the byte-string ``'\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. If the formatted message is Unicode, it *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=set([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.