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Issue #11794: Reorganised logging documentation.

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Vinay Sajip 2011-04-08 11:40:38 +01:00
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@ -19,6 +19,8 @@ Currently, the HOWTOs are:
descriptor.rst
doanddont.rst
functional.rst
logging.rst
logging-cookbook.rst
regex.rst
sockets.rst
sorting.rst

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.. _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.) The following section documents this
approach in more detail and includes a working socket receiver which can be
used as a starting point for you to adapt in your own applications.
If you are using a recent version of Python which includes the
:mod:`multiprocessing` module, you could write your own handler which uses the
:class:`Lock` class from this module to serialize access to the file from
your processes. The existing :class:`FileHandler` and subclasses do not make
use of :mod:`multiprocessing` at present, though they may do so in the future.
Note that at present, the :mod:`multiprocessing` module does not provide
working lock functionality on all platforms (see
http://bugs.python.org/issue3770).
.. currentmodule:: logging.handlers
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 much too small as an extreme
example. You would want to set *maxBytes* to an appropriate value.

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@ -0,0 +1,998 @@
=============
Logging HOWTO
=============
:Author: Vinay Sajip <vinay_sajip at red-dove dot com>
.. _logging-basic-tutorial:
.. currentmodule:: logging
Basic Logging Tutorial
----------------------
Logging is a means of tracking events that happen when some software runs. The
software's developer adds logging calls to their code to indicate that certain
events have occurred. An event is described by a descriptive message which can
optionally contain variable data (i.e. data that is potentially different for
each occurrence of the event). Events also have an importance which the
developer ascribes to the event; the importance can also be called the *level*
or *severity*.
When to use logging
^^^^^^^^^^^^^^^^^^^
Logging provides a set of convenience functions for simple logging usage. These
are :func:`debug`, :func:`info`, :func:`warning`, :func:`error` and
:func:`critical`. To determine when to use logging, see the table below, which
states, for each of a set of common tasks, the best tool to use for it.
+-------------------------------------+--------------------------------------+
| Task you want to perform | The best tool for the task |
+=====================================+======================================+
| Display console output for ordinary | :func:`print` |
| usage of a command line script or | |
| program | |
+-------------------------------------+--------------------------------------+
| Report events that occur during | :func:`logging.info` (or |
| normal operation of a program (e.g. | :func:`logging.debug` for very |
| for status monitoring or fault | detailed output for diagnostic |
| investigation) | purposes) |
+-------------------------------------+--------------------------------------+
| Issue a warning regarding a | :func:`warnings.warn` in library |
| particular runtime event | code if the issue is avoidable and |
| | the client application should be |
| | modified to eliminate the warning |
| | |
| | :func:`logging.warning` if there is |
| | nothing the client application can do|
| | about the situation, but the event |
| | should still be noted |
+-------------------------------------+--------------------------------------+
| Report an error regarding a | Raise an exception |
| particular runtime event | |
+-------------------------------------+--------------------------------------+
| Report suppression of an error | :func:`logging.error`, |
| without raising an exception (e.g. | :func:`logging.exception` or |
| error handler in a long-running | :func:`logging.critical` as |
| server process) | appropriate for the specific error |
| | and application domain |
+-------------------------------------+--------------------------------------+
The logging functions are named after the level or severity of the events
they are used to track. The standard levels and their applicability are
described below (in increasing order of severity):
+--------------+---------------------------------------------+
| Level | When it's used |
+==============+=============================================+
| ``DEBUG`` | Detailed information, typically of interest |
| | only when diagnosing problems. |
+--------------+---------------------------------------------+
| ``INFO`` | Confirmation that things are working as |
| | expected. |
+--------------+---------------------------------------------+
| ``WARNING`` | An indication that something unexpected |
| | happened, or indicative of some problem in |
| | the near future (e.g. 'disk space low'). |
| | The software is still working as expected. |
+--------------+---------------------------------------------+
| ``ERROR`` | Due to a more serious problem, the software |
| | has not been able to perform some function. |
+--------------+---------------------------------------------+
| ``CRITICAL`` | A serious error, indicating that the program|
| | itself may be unable to continue running. |
+--------------+---------------------------------------------+
The default level is ``WARNING``, which means that only events of this level
and above will be tracked, unless the logging package is configured to do
otherwise.
Events that are tracked can be handled in different ways. The simplest way of
handling tracked events is to print them to the console. Another common way
is to write them to a disk file.
.. _howto-minimal-example:
A simple example
^^^^^^^^^^^^^^^^
A very simple example is::
import logging
logging.warning('Watch out!') # will print a message to the console
logging.info('I told you so') # will not print anything
If you type these lines into a script and run it, you'll see::
WARNING:root:Watch out!
printed out on the console. The ``INFO`` message doesn't appear because the
default level is ``WARNING``. The printed message includes the indication of
the level and the description of the event provided in the logging call, i.e.
'Watch out!'. Don't worry about the 'root' part for now: it will be explained
later. The actual output can be formatted quite flexibly if you need that;
formatting options will also be explained later.
Logging to a file
^^^^^^^^^^^^^^^^^
A very common situation is that of recording logging events in a file, so let's
look at that next::
import logging
logging.basicConfig(filename='example.log',level=logging.DEBUG)
logging.debug('This message should go to the log file')
logging.info('So should this')
logging.warning('And this, too')
And now if we open the file and look at what we have, we should find the log
messages::
DEBUG:root:This message should go to the log file
INFO:root:So should this
WARNING:root:And this, too
This example also shows how you can set the logging level which acts as the
threshold for tracking. In this case, because we set the threshold to
``DEBUG``, all of the messages were printed.
If you want to set the logging level from a command-line option such as::
--log=INFO
and you have the value of the parameter passed for ``--log`` in some variable
*loglevel*, you can use::
getattr(logging, loglevel.upper())
to get the value which you'll pass to :func:`basicConfig` via the *level*
argument. You may want to error check any user input value, perhaps as in the
following example::
# assuming loglevel is bound to the string value obtained from the
# command line argument. Convert to upper case to allow the user to
# specify --log=DEBUG or --log=debug
numeric_level = getattr(logging, loglevel.upper(), None)
if not isinstance(numeric_level, int):
raise ValueError('Invalid log level: %s' % loglevel)
logging.basicConfig(level=numeric_level, ...)
The call to :func:`basicConfig` should come *before* any calls to :func:`debug`,
:func:`info` etc. As it's intended as a one-off simple configuration facility,
only the first call will actually do anything: subsequent calls are effectively
no-ops.
If you run the above script several times, the messages from successive runs
are appended to the file *example.log*. If you want each run to start afresh,
not remembering the messages from earlier runs, you can specify the *filemode*
argument, by changing the call in the above example to::
logging.basicConfig(filename='example.log', filemode='w', level=logging.DEBUG)
The output will be the same as before, but the log file is no longer appended
to, so the messages from earlier runs are lost.
Logging from multiple modules
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If your program consists of multiple modules, here's an example of how you
could organize logging in it::
# myapp.py
import logging
import mylib
def main():
logging.basicConfig(filename='myapp.log', level=logging.INFO)
logging.info('Started')
mylib.do_something()
logging.info('Finished')
if __name__ == '__main__':
main()
::
# mylib.py
import logging
def do_something():
logging.info('Doing something')
If you run *myapp.py*, you should see this in *myapp.log*::
INFO:root:Started
INFO:root:Doing something
INFO:root:Finished
which is hopefully what you were expecting to see. You can generalize this to
multiple modules, using the pattern in *mylib.py*. Note that for this simple
usage pattern, you won't know, by looking in the log file, *where* in your
application your messages came from, apart from looking at the event
description. If you want to track the location of your messages, you'll need
to refer to the documentation beyond the tutorial level -- see
:ref:`logging-advanced-tutorial`.
Logging variable data
^^^^^^^^^^^^^^^^^^^^^
To log variable data, use a format string for the event description message and
append the variable data as arguments. For example::
import logging
logging.warning('%s before you %s', 'Look', 'leap!')
will display::
WARNING:root:Look before you leap!
As you can see, merging of variable data into the event description message
uses the old, %-style of string formatting. This is for backwards
compatibility: the logging package pre-dates newer formatting options such as
:meth:`str.format` and :class:`string.Template`. These newer formatting
options *are* supported, but exploring them is outside the scope of this
tutorial.
Changing the format of displayed messages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
To change the format which is used to display messages, you need to
specify the format you want to use::
import logging
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.DEBUG)
logging.debug('This message should appear on the console')
logging.info('So should this')
logging.warning('And this, too')
which would print::
DEBUG:This message should appear on the console
INFO:So should this
WARNING:And this, too
Notice that the 'root' which appeared in earlier examples has disappeared. For
a full set of things that can appear in format strings, you can refer to the
documentation for :ref:`logrecord-attributes`, but for simple usage, you just
need the *levelname* (severity), *message* (event description, including
variable data) and perhaps to display when the event occurred. This is
described in the next section.
Displaying the date/time in messages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
To display the date and time of an event, you would place '%(asctime)s' in
your format string::
import logging
logging.basicConfig(format='%(asctime)s %(message)s')
logging.warning('is when this event was logged.')
which should print something like this::
2010-12-12 11:41:42,612 is when this event was logged.
The default format for date/time display (shown above) is ISO8601. If you need
more control over the formatting of the date/time, provide a *datefmt*
argument to ``basicConfig``, as in this example::
import logging
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
logging.warning('is when this event was logged.')
which would display something like this::
12/12/2010 11:46:36 AM is when this event was logged.
The format of the *datefmt* argument is the same as supported by
:func:`time.strftime`.
Next Steps
^^^^^^^^^^
That concludes the basic tutorial. It should be enough to get you up and
running with logging. There's a lot more that the logging package offers, but
to get the best out of it, you'll need to invest a little more of your time in
reading the following sections. If you're ready for that, grab some of your
favourite beverage and carry on.
If your logging needs are simple, then use the above examples to incorporate
logging into your own scripts, and if you run into problems or don't
understand something, please post a question on the comp.lang.python Usenet
group (available at http://groups.google.com/group/comp.lang.python) and you
should receive help before too long.
Still here? You can carry on reading the next few sections, which provide a
slightly more advanced/in-depth tutorial than the basic one above. After that,
you can take a look at the :ref:`logging-cookbook`.
.. _logging-advanced-tutorial:
Advanced Logging Tutorial
-------------------------
The logging library takes a modular approach and offers several categories
of components: loggers, handlers, filters, and formatters.
* Loggers expose the interface that application code directly uses.
* Handlers send the log records (created by loggers) to the appropriate
destination.
* Filters provide a finer grained facility for determining which log records
to output.
* Formatters specify the layout of log records in the final output.
Logging is performed by calling methods on instances of the :class:`Logger`
class (hereafter called :dfn:`loggers`). Each instance has a name, and they are
conceptually arranged in a namespace hierarchy using dots (periods) as
separators. For example, a logger named 'scan' is the parent of loggers
'scan.text', 'scan.html' and 'scan.pdf'. Logger names can be anything you want,
and indicate the area of an application in which a logged message originates.
A good convention to use when naming loggers is to use a module-level logger,
in each module which uses logging, named as follows::
logger = logging.getLogger(__name__)
This means that logger names track the package/module hierarchy, and it's
intuitively obvious where events are logged just from the logger name.
The root of the hierarchy of loggers is called the root logger. That's the
logger used by the functions :func:`debug`, :func:`info`, :func:`warning`,
:func:`error` and :func:`critical`, which just call the same-named method of
the root logger. The functions and the methods have the same signatures. The
root logger's name is printed as 'root' in the logged output.
It is, of course, possible to log messages to different destinations. Support
is included in the package for writing log messages to files, HTTP GET/POST
locations, email via SMTP, generic sockets, or OS-specific logging mechanisms
such as syslog or the Windows NT event log. Destinations are served by
:dfn:`handler` classes. You can create your own log destination class if you
have special requirements not met by any of the built-in handler classes.
By default, no destination is set for any logging messages. You can specify
a destination (such as console or file) by using :func:`basicConfig` as in the
tutorial examples. If you call the functions :func:`debug`, :func:`info`,
:func:`warning`, :func:`error` and :func:`critical`, they will check to see
if no destination is set; and if one is not set, they will set a destination
of the console (``sys.stderr``) and a default format for the displayed
message before delegating to the root logger to do the actual message output.
The default format set by :func:`basicConfig` for messages is::
severity:logger name:message
You can change this by passing a format string to :func:`basicConfig` with the
*format* keyword argument. For all options regarding how a format string is
constructed, see :ref:`formatter-objects`.
Loggers
^^^^^^^
:class:`Logger` objects have a threefold job. First, they expose several
methods to application code so that applications can log messages at runtime.
Second, logger objects determine which log messages to act upon based upon
severity (the default filtering facility) or filter objects. Third, logger
objects pass along relevant log messages to all interested log handlers.
The most widely used methods on logger objects fall into two categories:
configuration and message sending.
These are the most common configuration methods:
* :meth:`Logger.setLevel` specifies the lowest-severity log message a logger
will handle, where debug is the lowest built-in severity level and critical
is the highest built-in severity. For example, if the severity level is
INFO, the logger will handle only INFO, WARNING, ERROR, and CRITICAL messages
and will ignore DEBUG messages.
* :meth:`Logger.addHandler` and :meth:`Logger.removeHandler` add and remove
handler objects from the logger object. Handlers are covered in more detail
in :ref:`handler-basic`.
* :meth:`Logger.addFilter` and :meth:`Logger.removeFilter` add and remove filter
objects from the logger object. Filters are covered in more detail in
:ref:`filter`.
You don't need to always call these methods on every logger you create. See the
last two paragraphs in this section.
With the logger object configured, the following methods create log messages:
* :meth:`Logger.debug`, :meth:`Logger.info`, :meth:`Logger.warning`,
:meth:`Logger.error`, and :meth:`Logger.critical` all create log records with
a message and a level that corresponds to their respective method names. The
message is actually a format string, which may contain the standard string
substitution syntax of :const:`%s`, :const:`%d`, :const:`%f`, and so on. The
rest of their arguments is a list of objects that correspond with the
substitution fields in the message. With regard to :const:`**kwargs`, the
logging methods care only about a keyword of :const:`exc_info` and use it to
determine whether to log exception information.
* :meth:`Logger.exception` creates a log message similar to
:meth:`Logger.error`. The difference is that :meth:`Logger.exception` dumps a
stack trace along with it. Call this method only from an exception handler.
* :meth:`Logger.log` takes a log level as an explicit argument. This is a
little more verbose for logging messages than using the log level convenience
methods listed above, but this is how to log at custom log levels.
:func:`getLogger` returns a reference to a logger instance with the specified
name if it is provided, or ``root`` if not. The names are period-separated
hierarchical structures. Multiple calls to :func:`getLogger` with the same name
will return a reference to the same logger object. Loggers that are further
down in the hierarchical list are children of loggers higher up in the list.
For example, given a logger with a name of ``foo``, loggers with names of
``foo.bar``, ``foo.bar.baz``, and ``foo.bam`` are all descendants of ``foo``.
Loggers have a concept of *effective level*. If a level is not explicitly set
on a logger, the level of its parent is used instead as its effective level.
If the parent has no explicit level set, *its* parent is examined, and so on -
all ancestors are searched until an explicitly set level is found. The root
logger always has an explicit level set (``WARNING`` by default). When deciding
whether to process an event, the effective level of the logger is used to
determine whether the event is passed to the logger's handlers.
Child loggers propagate messages up to the handlers associated with their
ancestor loggers. Because of this, it is unnecessary to define and configure
handlers for all the loggers an application uses. It is sufficient to
configure handlers for a top-level logger and create child loggers as needed.
(You can, however, turn off propagation by setting the *propagate*
attribute of a logger to *False*.)
.. _handler-basic:
Handlers
^^^^^^^^
:class:`~logging.Handler` objects are responsible for dispatching the
appropriate log messages (based on the log messages' severity) to the handler's
specified destination. Logger objects can add zero or more handler objects to
themselves with an :func:`addHandler` method. As an example scenario, an
application may want to send all log messages to a log file, all log messages
of error or higher to stdout, and all messages of critical to an email address.
This scenario requires three individual handlers where each handler is
responsible for sending messages of a specific severity to a specific location.
The standard library includes quite a few handler types (see
:ref:`useful-handlers`); the tutorials use mainly :class:`StreamHandler` and
:class:`FileHandler` in its examples.
There are very few methods in a handler for application developers to concern
themselves with. The only handler methods that seem relevant for application
developers who are using the built-in handler objects (that is, not creating
custom handlers) are the following configuration methods:
* The :meth:`Handler.setLevel` method, just as in logger objects, specifies the
lowest severity that will be dispatched to the appropriate destination. Why
are there two :func:`setLevel` methods? The level set in the logger
determines which severity of messages it will pass to its handlers. The level
set in each handler determines which messages that handler will send on.
* :func:`setFormatter` selects a Formatter object for this handler to use.
* :func:`addFilter` and :func:`removeFilter` respectively configure and
deconfigure filter objects on handlers.
Application code should not directly instantiate and use instances of
:class:`Handler`. Instead, the :class:`Handler` class is a base class that
defines the interface that all handlers should have and establishes some
default behavior that child classes can use (or override).
Formatters
^^^^^^^^^^
Formatter objects configure the final order, structure, and contents of the log
message. Unlike the base :class:`logging.Handler` class, application code may
instantiate formatter classes, although you could likely subclass the formatter
if your application needs special behavior. The constructor takes two
optional arguments -- a message format string and a date format string.
.. method:: logging.Formatter.__init__(fmt=None, datefmt=None)
If there is no message format string, the default is to use the
raw message. If there is no date format string, the default date format is::
%Y-%m-%d %H:%M:%S
with the milliseconds tacked on at the end.
The message format string uses ``%(<dictionary key>)s`` styled string
substitution; the possible keys are documented in :ref:`logrecord-attributes`.
The following message format string will log the time in a human-readable
format, the severity of the message, and the contents of the message, in that
order::
'%(asctime)s - %(levelname)s - %(message)s'
Formatters use a user-configurable function to convert the creation time of a
record to a tuple. By default, :func:`time.localtime` is used; to change this
for a particular formatter instance, set the ``converter`` attribute of the
instance to a function with the same signature as :func:`time.localtime` or
:func:`time.gmtime`. To change it for all formatters, for example if you want
all logging times to be shown in GMT, set the ``converter`` attribute in the
Formatter class (to ``time.gmtime`` for GMT display).
Configuring Logging
^^^^^^^^^^^^^^^^^^^
.. currentmodule:: logging.config
Programmers can configure logging in three ways:
1. Creating loggers, handlers, and formatters explicitly using Python
code that calls the configuration methods listed above.
2. Creating a logging config file and reading it using the :func:`fileConfig`
function.
3. Creating a dictionary of configuration information and passing it
to the :func:`dictConfig` function.
For the reference documentation on the last two options, see
:ref:`logging-config-api`. The following example configures a very simple
logger, a console handler, and a simple formatter using Python code::
import logging
# create logger
logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)
# create console handler and set level to debug
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# add formatter to ch
ch.setFormatter(formatter)
# add ch to logger
logger.addHandler(ch)
# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
Running this module from the command line produces the following output::
$ python simple_logging_module.py
2005-03-19 15:10:26,618 - simple_example - DEBUG - debug message
2005-03-19 15:10:26,620 - simple_example - INFO - info message
2005-03-19 15:10:26,695 - simple_example - WARNING - warn message
2005-03-19 15:10:26,697 - simple_example - ERROR - error message
2005-03-19 15:10:26,773 - simple_example - CRITICAL - critical message
The following Python module creates a logger, handler, and formatter nearly
identical to those in the example listed above, with the only difference being
the names of the objects::
import logging
import logging.config
logging.config.fileConfig('logging.conf')
# create logger
logger = logging.getLogger('simpleExample')
# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
Here is the logging.conf file::
[loggers]
keys=root,simpleExample
[handlers]
keys=consoleHandler
[formatters]
keys=simpleFormatter
[logger_root]
level=DEBUG
handlers=consoleHandler
[logger_simpleExample]
level=DEBUG
handlers=consoleHandler
qualname=simpleExample
propagate=0
[handler_consoleHandler]
class=StreamHandler
level=DEBUG
formatter=simpleFormatter
args=(sys.stdout,)
[formatter_simpleFormatter]
format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
datefmt=
The output is nearly identical to that of the non-config-file-based example::
$ python simple_logging_config.py
2005-03-19 15:38:55,977 - simpleExample - DEBUG - debug message
2005-03-19 15:38:55,979 - simpleExample - INFO - info message
2005-03-19 15:38:56,054 - simpleExample - WARNING - warn message
2005-03-19 15:38:56,055 - simpleExample - ERROR - error message
2005-03-19 15:38:56,130 - simpleExample - CRITICAL - critical message
You can see that the config file approach has a few advantages over the Python
code approach, mainly separation of configuration and code and the ability of
noncoders to easily modify the logging properties.
.. currentmodule:: logging
Note that the class names referenced in config files need to be either relative
to the logging module, or absolute values which can be resolved using normal
import mechanisms. Thus, you could use either
:class:`~logging.handlers.WatchedFileHandler` (relative to the logging module) or
``mypackage.mymodule.MyHandler`` (for a class defined in package ``mypackage``
and module ``mymodule``, where ``mypackage`` is available on the Python import
path).
In Python 2.7, a new means of configuring logging has been introduced, using
dictionaries to hold configuration information. This provides a superset of the
functionality of the config-file-based approach outlined above, and is the
recommended configuration method for new applications and deployments. Because
a Python dictionary is used to hold configuration information, and since you
can populate that dictionary using different means, you have more options for
configuration. For example, you can use a configuration file in JSON format,
or, if you have access to YAML processing functionality, a file in YAML
format, to populate the configuration dictionary. Or, of course, you can
construct the dictionary in Python code, receive it in pickled form over a
socket, or use whatever approach makes sense for your application.
Here's an example of the same configuration as above, in YAML format for
the new dictionary-based approach::
version: 1
formatters:
simple:
format: format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
handlers:
console:
class: logging.StreamHandler
level: DEBUG
formatter: simple
stream: ext://sys.stdout
loggers:
simpleExample:
level: DEBUG
handlers: [console]
propagate: no
root:
level: DEBUG
handlers: [console]
For more information about logging using a dictionary, see
:ref:`logging-config-api`.
What happens if no configuration is provided
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If no logging configuration is provided, it is possible to have a situation
where a logging event needs to be output, but no handlers can be found to
output the event. The behaviour of the logging package in these
circumstances is dependent on the Python version.
For Python 2.x, the behaviour is as follows:
* If *logging.raiseExceptions* is *False* (production mode), the event is
silently dropped.
* If *logging.raiseExceptions* is *True* (development mode), a message
'No handlers could be found for logger X.Y.Z' is printed once.
.. _library-config:
Configuring Logging for a Library
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
When developing a library which uses logging, you should take care to
document how the library uses logging - for example, the names of loggers
used. Some consideration also needs to be given to its logging configuration.
If the using application does not use logging, and library code makes logging
calls, then (as described in the previous section) events of severity
``WARNING`` and greater will be printed to ``sys.stderr``. This is regarded as
the best default behaviour.
If for some reason you *don't* want these messages printed in the absence of
any logging configuration, you can attach a do-nothing handler to the top-level
logger for your library. This avoids the message being printed, since a handler
will be always be found for the library's events: it just doesn't produce any
output. If the library user configures logging for application use, presumably
that configuration will add some handlers, and if levels are suitably
configured then logging calls made in library code will send output to those
handlers, as normal.
A do-nothing handler is included in the logging package:
:class:`~logging.NullHandler` (since Python 2.7). An instance of this handler
could be added to the top-level logger of the logging namespace used by the
library (*if* you want to prevent your library's logged events being output to
``sys.stderr`` in the absence of logging configuration). If all logging by a
library *foo* is done using loggers with names matching 'foo.x', 'foo.x.y',
etc. then the code::
import logging
logging.getLogger('foo').addHandler(logging.NullHandler())
should have the desired effect. If an organisation produces a number of
libraries, then the logger name specified can be 'orgname.foo' rather than
just 'foo'.
**PLEASE NOTE:** It is strongly advised that you *do not add any handlers other
than* :class:`~logging.NullHandler` *to your library's loggers*. This is
because the configuration of handlers is the prerogative of the application
developer who uses your library. The application developer knows their target
audience and what handlers are most appropriate for their application: if you
add handlers 'under the hood', you might well interfere with their ability to
carry out unit tests and deliver logs which suit their requirements.
Logging Levels
--------------
The numeric values of logging levels are given in the following table. These are
primarily of interest if you want to define your own levels, and need them to
have specific values relative to the predefined levels. If you define a level
with the same numeric value, it overwrites the predefined value; the predefined
name is lost.
+--------------+---------------+
| Level | Numeric value |
+==============+===============+
| ``CRITICAL`` | 50 |
+--------------+---------------+
| ``ERROR`` | 40 |
+--------------+---------------+
| ``WARNING`` | 30 |
+--------------+---------------+
| ``INFO`` | 20 |
+--------------+---------------+
| ``DEBUG`` | 10 |
+--------------+---------------+
| ``NOTSET`` | 0 |
+--------------+---------------+
Levels can also be associated with loggers, being set either by the developer or
through loading a saved logging configuration. When a logging method is called
on a logger, the logger compares its own level with the level associated with
the method call. If the logger's level is higher than the method call's, no
logging message is actually generated. This is the basic mechanism controlling
the verbosity of logging output.
Logging messages are encoded as instances of the :class:`~logging.LogRecord`
class. When a logger decides to actually log an event, a
:class:`~logging.LogRecord` instance is created from the logging message.
Logging messages are subjected to a dispatch mechanism through the use of
:dfn:`handlers`, which are instances of subclasses of the :class:`Handler`
class. Handlers are responsible for ensuring that a logged message (in the form
of a :class:`LogRecord`) ends up in a particular location (or set of locations)
which is useful for the target audience for that message (such as end users,
support desk staff, system administrators, developers). Handlers are passed
:class:`LogRecord` instances intended for particular destinations. Each logger
can have zero, one or more handlers associated with it (via the
:meth:`~Logger.addHandler` method of :class:`Logger`). In addition to any
handlers directly associated with a logger, *all handlers associated with all
ancestors of the logger* are called to dispatch the message (unless the
*propagate* flag for a logger is set to a false value, at which point the
passing to ancestor handlers stops).
Just as for loggers, handlers can have levels associated with them. A handler's
level acts as a filter in the same way as a logger's level does. If a handler
decides to actually dispatch an event, the :meth:`~Handler.emit` method is used
to send the message to its destination. Most user-defined subclasses of
:class:`Handler` will need to override this :meth:`~Handler.emit`.
.. _custom-levels:
Custom Levels
^^^^^^^^^^^^^
Defining your own levels is possible, but should not be necessary, as the
existing levels have been chosen on the basis of practical experience.
However, if you are convinced that you need custom levels, great care should
be exercised when doing this, and it is possibly *a very bad idea to define
custom levels if you are developing a library*. That's because if multiple
library authors all define their own custom levels, there is a chance that
the logging output from such multiple libraries used together will be
difficult for the using developer to control and/or interpret, because a
given numeric value might mean different things for different libraries.
.. _useful-handlers:
Useful Handlers
---------------
In addition to the base :class:`Handler` class, many useful subclasses are
provided:
#. :class:`StreamHandler` instances send messages to streams (file-like
objects).
#. :class:`FileHandler` instances send messages to disk files.
#. :class:`~handlers.BaseRotatingHandler` is the base class for handlers that
rotate log files at a certain point. It is not meant to be instantiated
directly. Instead, use :class:`~handlers.RotatingFileHandler` or
:class:`~handlers.TimedRotatingFileHandler`.
#. :class:`~handlers.RotatingFileHandler` instances send messages to disk
files, with support for maximum log file sizes and log file rotation.
#. :class:`~handlers.TimedRotatingFileHandler` instances send messages to
disk files, rotating the log file at certain timed intervals.
#. :class:`~handlers.SocketHandler` instances send messages to TCP/IP
sockets.
#. :class:`~handlers.DatagramHandler` instances send messages to UDP
sockets.
#. :class:`~handlers.SMTPHandler` instances send messages to a designated
email address.
#. :class:`~handlers.SysLogHandler` instances send messages to a Unix
syslog daemon, possibly on a remote machine.
#. :class:`~handlers.NTEventLogHandler` instances send messages to a
Windows NT/2000/XP event log.
#. :class:`~handlers.MemoryHandler` instances send messages to a buffer
in memory, which is flushed whenever specific criteria are met.
#. :class:`~handlers.HTTPHandler` instances send messages to an HTTP
server using either ``GET`` or ``POST`` semantics.
#. :class:`~handlers.WatchedFileHandler` instances watch the file they are
logging to. If the file changes, it is closed and reopened using the file
name. This handler is only useful on Unix-like systems; Windows does not
support the underlying mechanism used.
#. :class:`NullHandler` instances do nothing with error messages. They are used
by library developers who want to use logging, but want to avoid the 'No
handlers could be found for logger XXX' message which can be displayed if
the library user has not configured logging. See :ref:`library-config` for
more information.
.. versionadded:: 2.7
The :class:`NullHandler` class.
The :class:`NullHandler`, :class:`StreamHandler` and :class:`FileHandler`
classes are defined in the core logging package. The other handlers are
defined in a sub- module, :mod:`logging.handlers`. (There is also another
sub-module, :mod:`logging.config`, for configuration functionality.)
Logged messages are formatted for presentation through instances of the
:class:`Formatter` class. They are initialized with a format string suitable for
use with the % operator and a dictionary.
For formatting multiple messages in a batch, instances of
:class:`BufferingFormatter` can be used. In addition to the format string (which
is applied to each message in the batch), there is provision for header and
trailer format strings.
When filtering based on logger level and/or handler level is not enough,
instances of :class:`Filter` can be added to both :class:`Logger` and
:class:`Handler` instances (through their :meth:`addFilter` method). Before
deciding to process a message further, both loggers and handlers consult all
their filters for permission. If any filter returns a false value, the message
is not processed further.
The basic :class:`Filter` functionality allows filtering by specific logger
name. If this feature is used, messages sent to the named logger and its
children are allowed through the filter, and all others dropped.
.. _logging-exceptions:
Exceptions raised during logging
--------------------------------
The logging package is designed to swallow exceptions which occur while logging
in production. This is so that errors which occur while handling logging events
- such as logging misconfiguration, network or other similar errors - do not
cause the application using logging to terminate prematurely.
:class:`SystemExit` and :class:`KeyboardInterrupt` exceptions are never
swallowed. Other exceptions which occur during the :meth:`emit` method of a
:class:`Handler` subclass are passed to its :meth:`handleError` method.
The default implementation of :meth:`handleError` in :class:`Handler` checks
to see if a module-level variable, :data:`raiseExceptions`, is set. If set, a
traceback is printed to :data:`sys.stderr`. If not set, the exception is swallowed.
**Note:** The default value of :data:`raiseExceptions` is ``True``. This is because
during development, you typically want to be notified of any exceptions that
occur. It's advised that you set :data:`raiseExceptions` to ``False`` for production
usage.
.. currentmodule:: logging
.. _arbitrary-object-messages:
Using arbitrary objects as messages
-----------------------------------
In the preceding sections and examples, it has been assumed that the message
passed when logging the event is a string. However, this is not the only
possibility. You can pass an arbitrary object as a message, and its
:meth:`__str__` method will be called when the logging system needs to convert
it to a string representation. In fact, if you want to, you can avoid
computing a string representation altogether - for example, the
:class:`SocketHandler` emits an event by pickling it and sending it over the
wire.
Optimization
------------
Formatting of message arguments is deferred until it cannot be avoided.
However, computing the arguments passed to the logging method can also be
expensive, and you may want to avoid doing it if the logger will just throw
away your event. To decide what to do, you can call the :meth:`isEnabledFor`
method which takes a level argument and returns true if the event would be
created by the Logger for that level of call. You can write code like this::
if logger.isEnabledFor(logging.DEBUG):
logger.debug('Message with %s, %s', expensive_func1(),
expensive_func2())
so that if the logger's threshold is set above ``DEBUG``, the calls to
:func:`expensive_func1` and :func:`expensive_func2` are never made.
There are other optimizations which can be made for specific applications which
need more precise control over what logging information is collected. Here's a
list of things you can do to avoid processing during logging which you don't
need:
+-----------------------------------------------+----------------------------------------+
| What you don't want to collect | How to avoid collecting it |
+===============================================+========================================+
| Information about where calls were made from. | Set ``logging._srcfile`` to ``None``. |
+-----------------------------------------------+----------------------------------------+
| Threading information. | Set ``logging.logThreads`` to ``0``. |
+-----------------------------------------------+----------------------------------------+
| Process information. | Set ``logging.logProcesses`` to ``0``. |
+-----------------------------------------------+----------------------------------------+
Also note that the core logging module only includes the basic handlers. If
you don't import :mod:`logging.handlers` and :mod:`logging.config`, they won't
take up any memory.
.. 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 logging cookbook <logging-cookbook>`