:mod:`logging.config` --- Logging configuration
.. module:: logging.config :synopsis: Configuration of the logging module.
.. moduleauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sectionauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
Source code: :source:`Lib/logging/config.py`
Important
This page contains only reference information. For tutorials, please see
This section describes the API for configuring the logging module.
The following functions configure the logging module. They are located in the :mod:`logging.config` module. Their use is optional --- you can configure the logging module using these functions or by making calls to the main API (defined in :mod:`logging` itself) and defining handlers which are declared either in :mod:`logging` or :mod:`logging.handlers`.
.. function:: dictConfig(config)
Takes the logging configuration from a dictionary. The contents of
this dictionary are described in :ref:`logging-config-dictschema`
below.
If an error is encountered during configuration, this function will
raise a :exc:`ValueError`, :exc:`TypeError`, :exc:`AttributeError`
or :exc:`ImportError` with a suitably descriptive message. The
following is a (possibly incomplete) list of conditions which will
raise an error:
* A ``level`` which is not a string or which is a string not
corresponding to an actual logging level.
* A ``propagate`` value which is not a boolean.
* An id which does not have a corresponding destination.
* A non-existent handler id found during an incremental call.
* An invalid logger name.
* Inability to resolve to an internal or external object.
Parsing is performed by the :class:`DictConfigurator` class, whose
constructor is passed the dictionary used for configuration, and
has a :meth:`configure` method. The :mod:`logging.config` module
has a callable attribute :attr:`dictConfigClass`
which is initially set to :class:`DictConfigurator`.
You can replace the value of :attr:`dictConfigClass` with a
suitable implementation of your own.
:func:`dictConfig` calls :attr:`dictConfigClass` passing
the specified dictionary, and then calls the :meth:`configure` method on
the returned object to put the configuration into effect::
def dictConfig(config):
dictConfigClass(config).configure()
For example, a subclass of :class:`DictConfigurator` could call
``DictConfigurator.__init__()`` in its own :meth:`__init__()`, then
set up custom prefixes which would be usable in the subsequent
:meth:`configure` call. :attr:`dictConfigClass` would be bound to
this new subclass, and then :func:`dictConfig` could be called exactly as
in the default, uncustomized state.
.. versionadded:: 3.2
.. function:: fileConfig(fname, defaults=None, disable_existing_loggers=True, encoding=None)
Reads the logging configuration from a :mod:`configparser`\-format file. The
format of the file should be as described in
:ref:`logging-config-fileformat`.
This function can be called several times from an application, allowing an
end user to select from various pre-canned configurations (if the developer
provides a mechanism to present the choices and load the chosen
configuration).
:param fname: A filename, or a file-like object, or an instance derived
from :class:`~configparser.RawConfigParser`. If a
``RawConfigParser``-derived instance is passed, it is used as
is. Otherwise, a :class:`~configparser.Configparser` is
instantiated, and the configuration read by it from the
object passed in ``fname``. If that has a :meth:`readline`
method, it is assumed to be a file-like object and read using
:meth:`~configparser.ConfigParser.read_file`; otherwise,
it is assumed to be a filename and passed to
:meth:`~configparser.ConfigParser.read`.
:param defaults: Defaults to be passed to the ConfigParser can be specified
in this argument.
:param disable_existing_loggers: If specified as ``False``, loggers which
exist when this call is made are left
enabled. The default is ``True`` because this
enables old behaviour in a
backward-compatible way. This behaviour is to
disable any existing non-root loggers unless
they or their ancestors are explicitly named
in the logging configuration.
:param encoding: The encoding used to open file when *fname* is filename.
.. versionchanged:: 3.4
An instance of a subclass of :class:`~configparser.RawConfigParser` is
now accepted as a value for ``fname``. This facilitates:
* Use of a configuration file where logging configuration is just part
of the overall application configuration.
* Use of a configuration read from a file, and then modified by the using
application (e.g. based on command-line parameters or other aspects
of the runtime environment) before being passed to ``fileConfig``.
.. versionadded:: 3.10
The *encoding* parameter is added.
.. function:: listen(port=DEFAULT_LOGGING_CONFIG_PORT, verify=None)
Starts up a socket server on the specified port, and listens for new
configurations. If no port is specified, the module's default
:const:`DEFAULT_LOGGING_CONFIG_PORT` is used. Logging configurations will be
sent as a file suitable for processing by :func:`dictConfig` or
:func:`fileConfig`. Returns a :class:`~threading.Thread` instance on which
you can call :meth:`~threading.Thread.start` to start the server, and which
you can :meth:`~threading.Thread.join` when appropriate. To stop the server,
call :func:`stopListening`.
The ``verify`` argument, if specified, should be a callable which should
verify whether bytes received across the socket are valid and should be
processed. This could be done by encrypting and/or signing what is sent
across the socket, such that the ``verify`` callable can perform
signature verification and/or decryption. The ``verify`` callable is called
with a single argument - the bytes received across the socket - and should
return the bytes to be processed, or ``None`` to indicate that the bytes should
be discarded. The returned bytes could be the same as the passed in bytes
(e.g. when only verification is done), or they could be completely different
(perhaps if decryption were performed).
To send a configuration to the socket, read in the configuration file and
send it to the socket as a sequence of bytes preceded by a four-byte length
string packed in binary using ``struct.pack('>L', n)``.
.. _logging-eval-security:
.. note::
Because portions of the configuration are passed through
:func:`eval`, use of this function may open its users to a security risk.
While the function only binds to a socket on ``localhost``, and so does
not accept connections from remote machines, there are scenarios where
untrusted code could be run under the account of the process which calls
:func:`listen`. Specifically, if the process calling :func:`listen` runs
on a multi-user machine where users cannot trust each other, then a
malicious user could arrange to run essentially arbitrary code in a
victim user's process, simply by connecting to the victim's
:func:`listen` socket and sending a configuration which runs whatever
code the attacker wants to have executed in the victim's process. This is
especially easy to do if the default port is used, but not hard even if a
different port is used. To avoid the risk of this happening, use the
``verify`` argument to :func:`listen` to prevent unrecognised
configurations from being applied.
.. versionchanged:: 3.4
The ``verify`` argument was added.
.. note::
If you want to send configurations to the listener which don't
disable existing loggers, you will need to use a JSON format for
the configuration, which will use :func:`dictConfig` for configuration.
This method allows you to specify ``disable_existing_loggers`` as
``False`` in the configuration you send.
.. function:: stopListening() Stops the listening server which was created with a call to :func:`listen`. This is typically called before calling :meth:`join` on the return value from :func:`listen`.
The logging configuration functionality tries to offer convenience, and in part this is done by offering the ability to convert text in configuration files into Python objects used in logging configuration - for example, as described in :ref:`logging-config-dict-userdef`. However, these same mechanisms (importing callables from user-defined modules and calling them with parameters from the configuration) could be used to invoke any code you like, and for this reason you should treat configuration files from untrusted sources with extreme caution and satisfy yourself that nothing bad can happen if you load them, before actually loading them.
Describing a logging configuration requires listing the various
objects to create and the connections between them; for example, you
may create a handler named 'console' and then say that the logger
named 'startup' will send its messages to the 'console' handler.
These objects aren't limited to those provided by the :mod:`logging`
module because you might write your own formatter or handler class.
The parameters to these classes may also need to include external
objects such as sys.stderr. The syntax for describing these
objects and connections is defined in :ref:`logging-config-dict-connections`
below.
The dictionary passed to :func:`dictConfig` must contain the following keys:
- version - to be set to an integer value representing the schema version. The only valid value at present is 1, but having this key allows the schema to evolve while still preserving backwards compatibility.
All other keys are optional, but if present they will be interpreted
as described below. In all cases below where a 'configuring dict' is
mentioned, it will be checked for the special '()' key to see if a
custom instantiation is required. If so, the mechanism described in
:ref:`logging-config-dict-userdef` below is used to create an instance;
otherwise, the context is used to determine what to instantiate.
formatters - the corresponding value will be a dict in which each key is a formatter id and each value is a dict describing how to configure the corresponding :class:`~logging.Formatter` instance.
The configuring dict is searched for the following optional keys which correspond to the arguments passed to create a :class:`~logging.Formatter` object:
formatdatefmtstylevalidate(since version >=3.8)defaults(since version >=3.12)
An optional
classkey indicates the name of the formatter's class (as a dotted module and class name). The instantiation arguments are as for :class:`~logging.Formatter`, thus this key is most useful for instantiating a customised subclass of :class:`~logging.Formatter`. For example, the alternative class might present exception tracebacks in an expanded or condensed format. If your formatter requires different or extra configuration keys, you should use :ref:`logging-config-dict-userdef`.filters - the corresponding value will be a dict in which each key is a filter id and each value is a dict describing how to configure the corresponding Filter instance.
The configuring dict is searched for the key
name(defaulting to the empty string) and this is used to construct a :class:`logging.Filter` instance.handlers - the corresponding value will be a dict in which each key is a handler id and each value is a dict describing how to configure the corresponding Handler instance.
The configuring dict is searched for the following keys:
class(mandatory). This is the fully qualified name of the handler class.level(optional). The level of the handler.formatter(optional). The id of the formatter for this handler.filters(optional). A list of ids of the filters for this handler... versionchanged:: 3.11 ``filters`` can take filter instances in addition to ids.
All other keys are passed through as keyword arguments to the handler's constructor. For example, given the snippet:
handlers: console: class : logging.StreamHandler formatter: brief level : INFO filters: [allow_foo] stream : ext://sys.stdout file: class : logging.handlers.RotatingFileHandler formatter: precise filename: logconfig.log maxBytes: 1024 backupCount: 3
the handler with id
consoleis instantiated as a :class:`logging.StreamHandler`, usingsys.stdoutas the underlying stream. The handler with idfileis instantiated as a :class:`logging.handlers.RotatingFileHandler` with the keyword argumentsfilename='logconfig.log', maxBytes=1024, backupCount=3.loggers - the corresponding value will be a dict in which each key is a logger name and each value is a dict describing how to configure the corresponding Logger instance.
The configuring dict is searched for the following keys:
level(optional). The level of the logger.propagate(optional). The propagation setting of the logger.filters(optional). A list of ids of the filters for this logger... versionchanged:: 3.11 ``filters`` can take filter instances in addition to ids.
handlers(optional). A list of ids of the handlers for this logger.
The specified loggers will be configured according to the level, propagation, filters and handlers specified.
root - this will be the configuration for the root logger. Processing of the configuration will be as for any logger, except that the
propagatesetting will not be applicable.incremental - whether the configuration is to be interpreted as incremental to the existing configuration. This value defaults to
False, which means that the specified configuration replaces the existing configuration with the same semantics as used by the existing :func:`fileConfig` API.If the specified value is
True, the configuration is processed as described in the section on :ref:`logging-config-dict-incremental`.disable_existing_loggers - whether any existing non-root loggers are to be disabled. This setting mirrors the parameter of the same name in :func:`fileConfig`. If absent, this parameter defaults to
True. This value is ignored if incremental isTrue.
It is difficult to provide complete flexibility for incremental configuration. For example, because objects such as filters and formatters are anonymous, once a configuration is set up, it is not possible to refer to such anonymous objects when augmenting a configuration.
Furthermore, there is not a compelling case for arbitrarily altering the object graph of loggers, handlers, filters, formatters at run-time, once a configuration is set up; the verbosity of loggers and handlers can be controlled just by setting levels (and, in the case of loggers, propagation flags). Changing the object graph arbitrarily in a safe way is problematic in a multi-threaded environment; while not impossible, the benefits are not worth the complexity it adds to the implementation.
Thus, when the incremental key of a configuration dict is present
and is True, the system will completely ignore any formatters and
filters entries, and process only the level
settings in the handlers entries, and the level and
propagate settings in the loggers and root entries.
Using a value in the configuration dict lets configurations to be sent over the wire as pickled dicts to a socket listener. Thus, the logging verbosity of a long-running application can be altered over time with no need to stop and restart the application.
The schema describes a set of logging objects - loggers, handlers, formatters, filters - which are connected to each other in an object graph. Thus, the schema needs to represent connections between the objects. For example, say that, once configured, a particular logger has attached to it a particular handler. For the purposes of this discussion, we can say that the logger represents the source, and the handler the destination, of a connection between the two. Of course in the configured objects this is represented by the logger holding a reference to the handler. In the configuration dict, this is done by giving each destination object an id which identifies it unambiguously, and then using the id in the source object's configuration to indicate that a connection exists between the source and the destination object with that id.
So, for example, consider the following YAML snippet:
formatters:
brief:
# configuration for formatter with id 'brief' goes here
precise:
# configuration for formatter with id 'precise' goes here
handlers:
h1: #This is an id
# configuration of handler with id 'h1' goes here
formatter: brief
h2: #This is another id
# configuration of handler with id 'h2' goes here
formatter: precise
loggers:
foo.bar.baz:
# other configuration for logger 'foo.bar.baz'
handlers: [h1, h2](Note: YAML used here because it's a little more readable than the equivalent Python source form for the dictionary.)
The ids for loggers are the logger names which would be used
programmatically to obtain a reference to those loggers, e.g.
foo.bar.baz. The ids for Formatters and Filters can be any string
value (such as brief, precise above) and they are transient,
in that they are only meaningful for processing the configuration
dictionary and used to determine connections between objects, and are
not persisted anywhere when the configuration call is complete.
The above snippet indicates that logger named foo.bar.baz should
have two handlers attached to it, which are described by the handler
ids h1 and h2. The formatter for h1 is that described by id
brief, and the formatter for h2 is that described by id
precise.
The schema supports user-defined objects for handlers, filters and formatters. (Loggers do not need to have different types for different instances, so there is no support in this configuration schema for user-defined logger classes.)
Objects to be configured are described by dictionaries
which detail their configuration. In some places, the logging system
will be able to infer from the context how an object is to be
instantiated, but when a user-defined object is to be instantiated,
the system will not know how to do this. In order to provide complete
flexibility for user-defined object instantiation, the user needs
to provide a 'factory' - a callable which is called with a
configuration dictionary and which returns the instantiated object.
This is signalled by an absolute import path to the factory being
made available under the special key '()'. Here's a concrete
example:
formatters:
brief:
format: '%(message)s'
default:
format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
datefmt: '%Y-%m-%d %H:%M:%S'
custom:
(): my.package.customFormatterFactory
bar: baz
spam: 99.9
answer: 42The above YAML snippet defines three formatters. The first, with id
brief, is a standard :class:`logging.Formatter` instance with the
specified format string. The second, with id default, has a
longer format and also defines the time format explicitly, and will
result in a :class:`logging.Formatter` initialized with those two format
strings. Shown in Python source form, the brief and default
formatters have configuration sub-dictionaries:
{
'format' : '%(message)s'
}
and:
{
'format' : '%(asctime)s %(levelname)-8s %(name)-15s %(message)s',
'datefmt' : '%Y-%m-%d %H:%M:%S'
}
respectively, and as these dictionaries do not contain the special key
'()', the instantiation is inferred from the context: as a result,
standard :class:`logging.Formatter` instances are created. The
configuration sub-dictionary for the third formatter, with id
custom, is:
{
'()' : 'my.package.customFormatterFactory',
'bar' : 'baz',
'spam' : 99.9,
'answer' : 42
}
and this contains the special key '()', which means that
user-defined instantiation is wanted. In this case, the specified
factory callable will be used. If it is an actual callable it will be
used directly - otherwise, if you specify a string (as in the example)
the actual callable will be located using normal import mechanisms.
The callable will be called with the remaining items in the
configuration sub-dictionary as keyword arguments. In the above
example, the formatter with id custom will be assumed to be
returned by the call:
my.package.customFormatterFactory(bar='baz', spam=99.9, answer=42)
Warning
The values for keys such as bar, spam and answer in
the above example should not be configuration dictionaries or references such
as cfg://foo or ext://bar, because they will not be processed by the
configuration machinery, but passed to the callable as-is.
The key '()' has been used as the special key because it is not a
valid keyword parameter name, and so will not clash with the names of
the keyword arguments used in the call. The '()' also serves as a
mnemonic that the corresponding value is a callable.
.. versionchanged:: 3.11 The ``filters`` member of ``handlers`` and ``loggers`` can take filter instances in addition to ids.
You can also specify a special key '.' whose value is a dictionary is a
mapping of attribute names to values. If found, the specified attributes will
be set on the user-defined object before it is returned. Thus, with the
following configuration:
{
'()' : 'my.package.customFormatterFactory',
'bar' : 'baz',
'spam' : 99.9,
'answer' : 42,
'.' {
'foo': 'bar',
'baz': 'bozz'
}
}
the returned formatter will have attribute foo set to 'bar' and
attribute baz set to 'bozz'.
Warning
The values for attributes such as foo and baz in
the above example should not be configuration dictionaries or references such
as cfg://foo or ext://bar, because they will not be processed by the
configuration machinery, but set as attribute values as-is.
Handlers are configured in alphabetical order of their keys, and a configured
handler replaces the configuration dictionary in (a working copy of) the
handlers dictionary in the schema. If you use a construct such as
cfg://handlers.foo, then initially handlers['foo'] points to the
configuration dictionary for the handler named foo, and later (once that
handler has been configured) it points to the configured handler instance.
Thus, cfg://handlers.foo could resolve to either a dictionary or a handler
instance. In general, it is wise to name handlers in a way such that dependent
handlers are configured _after_ any handlers they depend on; that allows
something like cfg://handlers.foo to be used in configuring a handler that
depends on handler foo. If that dependent handler were named bar,
problems would result, because the configuration of bar would be attempted
before that of foo, and foo would not yet have been configured.
However, if the dependent handler were named foobar, it would be configured
after foo, with the result that cfg://handlers.foo would resolve to
configured handler foo, and not its configuration dictionary.
There are times where a configuration needs to refer to objects
external to the configuration, for example sys.stderr. If the
configuration dict is constructed using Python code, this is
straightforward, but a problem arises when the configuration is
provided via a text file (e.g. JSON, YAML). In a text file, there is
no standard way to distinguish sys.stderr from the literal string
'sys.stderr'. To facilitate this distinction, the configuration
system looks for certain special prefixes in string values and
treat them specially. For example, if the literal string
'ext://sys.stderr' is provided as a value in the configuration,
then the ext:// will be stripped off and the remainder of the
value processed using normal import mechanisms.
The handling of such prefixes is done in a way analogous to protocol
handling: there is a generic mechanism to look for prefixes which
match the regular expression ^(?P<prefix>[a-z]+)://(?P<suffix>.*)$
whereby, if the prefix is recognised, the suffix is processed
in a prefix-dependent manner and the result of the processing replaces
the string value. If the prefix is not recognised, then the string
value will be left as-is.
As well as external objects, there is sometimes also a need to refer
to objects in the configuration. This will be done implicitly by the
configuration system for things that it knows about. For example, the
string value 'DEBUG' for a level in a logger or handler will
automatically be converted to the value logging.DEBUG, and the
handlers, filters and formatter entries will take an
object id and resolve to the appropriate destination object.
However, a more generic mechanism is needed for user-defined
objects which are not known to the :mod:`logging` module. For
example, consider :class:`logging.handlers.MemoryHandler`, which takes
a target argument which is another handler to delegate to. Since
the system already knows about this class, then in the configuration,
the given target just needs to be the object id of the relevant
target handler, and the system will resolve to the handler from the
id. If, however, a user defines a my.package.MyHandler which has
an alternate handler, the configuration system would not know that
the alternate referred to a handler. To cater for this, a generic
resolution system allows the user to specify:
handlers:
file:
# configuration of file handler goes here
custom:
(): my.package.MyHandler
alternate: cfg://handlers.fileThe literal string 'cfg://handlers.file' will be resolved in an
analogous way to strings with the ext:// prefix, but looking
in the configuration itself rather than the import namespace. The
mechanism allows access by dot or by index, in a similar way to
that provided by str.format. Thus, given the following snippet:
handlers:
email:
class: logging.handlers.SMTPHandler
mailhost: localhost
fromaddr: my_app@domain.tld
toaddrs:
- support_team@domain.tld
- dev_team@domain.tld
subject: Houston, we have a problem.in the configuration, the string 'cfg://handlers' would resolve to
the dict with key handlers, the string 'cfg://handlers.email
would resolve to the dict with key email in the handlers dict,
and so on. The string 'cfg://handlers.email.toaddrs[1] would
resolve to 'dev_team@domain.tld' and the string
'cfg://handlers.email.toaddrs[0]' would resolve to the value
'support_team@domain.tld'. The subject value could be accessed
using either 'cfg://handlers.email.subject' or, equivalently,
'cfg://handlers.email[subject]'. The latter form only needs to be
used if the key contains spaces or non-alphanumeric characters. If an
index value consists only of decimal digits, access will be attempted
using the corresponding integer value, falling back to the string
value if needed.
Given a string cfg://handlers.myhandler.mykey.123, this will
resolve to config_dict['handlers']['myhandler']['mykey']['123'].
If the string is specified as cfg://handlers.myhandler.mykey[123],
the system will attempt to retrieve the value from
config_dict['handlers']['myhandler']['mykey'][123], and fall back
to config_dict['handlers']['myhandler']['mykey']['123'] if that
fails.
Import resolution, by default, uses the builtin :func:`__import__` function to do its importing. You may want to replace this with your own importing mechanism: if so, you can replace the :attr:`importer` attribute of the :class:`DictConfigurator` or its superclass, the :class:`BaseConfigurator` class. However, you need to be careful because of the way functions are accessed from classes via descriptors. If you are using a Python callable to do your imports, and you want to define it at class level rather than instance level, you need to wrap it with :func:`staticmethod`. For example:
from importlib import import_module from logging.config import BaseConfigurator BaseConfigurator.importer = staticmethod(import_module)
You don't need to wrap with :func:`staticmethod` if you're setting the import callable on a configurator instance.
If you want to configure a :class:`~logging.handlers.QueueHandler`, noting that this
is normally used in conjunction with a :class:`~logging.handlers.QueueListener`, you
can configure both together. After the configuration, the QueueListener instance
will be available as the :attr:`~logging.handlers.QueueHandler.listener` attribute of
the created handler, and that in turn will be available to you using
:func:`~logging.getHandlerByName` and passing the name you have used for the
QueueHandler in your configuration. The dictionary schema for configuring the pair
is shown in the example YAML snippet below.
handlers:
qhand:
class: logging.handlers.QueueHandler
queue: my.module.queue_factory
listener: my.package.CustomListener
handlers:
- hand_name_1
- hand_name_2
...The queue and listener keys are optional.
If the queue key is present, the corresponding value can be one of the following:
- An actual instance of :class:`queue.Queue` or a subclass thereof. This is of course only possible if you are constructing or modifying the configuration dictionary in code.
- A string that resolves to a callable which, when called with no arguments, returns
the :class:`queue.Queue` instance to use. That callable could be a
:class:`queue.Queue` subclass or a function which returns a suitable queue instance,
such as
my.module.queue_factory(). - A dict with a
'()'key which is constructed in the usual way as discussed in :ref:`logging-config-dict-userdef`. The result of this construction should be a :class:`queue.Queue` instance.
If the queue key is absent, a standard unbounded :class:`queue.Queue` instance is
created and used.
If the listener key is present, the corresponding value can be one of the following:
- A subclass of :class:`logging.handlers.QueueListener`. This is of course only possible if you are constructing or modifying the configuration dictionary in code.
- A string which resolves to a class which is a subclass of
QueueListener, such as'my.package.CustomListener'. - A dict with a
'()'key which is constructed in the usual way as discussed in :ref:`logging-config-dict-userdef`. The result of this construction should be a callable with the same signature as theQueueListenerinitializer.
If the listener key is absent, :class:`logging.handlers.QueueListener` is used.
The values under the handlers key are the names of other handlers in the
configuration (not shown in the above snippet) which will be passed to the queue
listener.
Any custom queue handler and listener classes will need to be defined with the same initialization signatures as :class:`~logging.handlers.QueueHandler` and :class:`~logging.handlers.QueueListener`.
.. versionadded:: 3.12
The configuration file format understood by :func:`fileConfig` is based on
:mod:`configparser` functionality. The file must contain sections called
[loggers], [handlers] and [formatters] which identify by name the
entities of each type which are defined in the file. For each such entity, there
is a separate section which identifies how that entity is configured. Thus, for
a logger named log01 in the [loggers] section, the relevant
configuration details are held in a section [logger_log01]. Similarly, a
handler called hand01 in the [handlers] section will have its
configuration held in a section called [handler_hand01], while a formatter
called form01 in the [formatters] section will have its configuration
specified in a section called [formatter_form01]. The root logger
configuration must be specified in a section called [logger_root].
Note
The :func:`fileConfig` API is older than the :func:`dictConfig` API and does not provide functionality to cover certain aspects of logging. For example, you cannot configure :class:`~logging.Filter` objects, which provide for filtering of messages beyond simple integer levels, using :func:`fileConfig`. If you need to have instances of :class:`~logging.Filter` in your logging configuration, you will need to use :func:`dictConfig`. Note that future enhancements to configuration functionality will be added to :func:`dictConfig`, so it's worth considering transitioning to this newer API when it's convenient to do so.
Examples of these sections in the file are given below.
[loggers]
keys=root,log02,log03,log04,log05,log06,log07
[handlers]
keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09
[formatters]
keys=form01,form02,form03,form04,form05,form06,form07,form08,form09The root logger must specify a level and a list of handlers. An example of a root logger section is given below.
[logger_root]
level=NOTSET
handlers=hand01The level entry can be one of DEBUG, INFO, WARNING, ERROR, CRITICAL or
NOTSET. For the root logger only, NOTSET means that all messages will be
logged. Level values are :ref:`evaluated <func-eval>` in the context of the logging
package's namespace.
The handlers entry is a comma-separated list of handler names, which must
appear in the [handlers] section. These names must appear in the
[handlers] section and have corresponding sections in the configuration
file.
For loggers other than the root logger, some additional information is required. This is illustrated by the following example.
[logger_parser]
level=DEBUG
handlers=hand01
propagate=1
qualname=compiler.parserThe level and handlers entries are interpreted as for the root logger,
except that if a non-root logger's level is specified as NOTSET, the system
consults loggers higher up the hierarchy to determine the effective level of the
logger. The propagate entry is set to 1 to indicate that messages must
propagate to handlers higher up the logger hierarchy from this logger, or 0 to
indicate that messages are not propagated to handlers up the hierarchy. The
qualname entry is the hierarchical channel name of the logger, that is to
say the name used by the application to get the logger.
Sections which specify handler configuration are exemplified by the following.
[handler_hand01]
class=StreamHandler
level=NOTSET
formatter=form01
args=(sys.stdout,)The class entry indicates the handler's class (as determined by :func:`eval`
in the logging package's namespace). The level is interpreted as for
loggers, and NOTSET is taken to mean 'log everything'.
The formatter entry indicates the key name of the formatter for this
handler. If blank, a default formatter (logging._defaultFormatter) is used.
If a name is specified, it must appear in the [formatters] section and have
a corresponding section in the configuration file.
The args entry, when :ref:`evaluated <func-eval>` in the context of the logging
package's namespace, is the list of arguments to the constructor for the handler
class. Refer to the constructors for the relevant handlers, or to the examples
below, to see how typical entries are constructed. If not provided, it defaults
to ().
The optional kwargs entry, when :ref:`evaluated <func-eval>` in the context of the
logging package's namespace, is the keyword argument dict to the constructor
for the handler class. If not provided, it defaults to {}.
[handler_hand02]
class=FileHandler
level=DEBUG
formatter=form02
args=('python.log', 'w')
[handler_hand03]
class=handlers.SocketHandler
level=INFO
formatter=form03
args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)
[handler_hand04]
class=handlers.DatagramHandler
level=WARN
formatter=form04
args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)
[handler_hand05]
class=handlers.SysLogHandler
level=ERROR
formatter=form05
args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)
[handler_hand06]
class=handlers.NTEventLogHandler
level=CRITICAL
formatter=form06
args=('Python Application', '', 'Application')
[handler_hand07]
class=handlers.SMTPHandler
level=WARN
formatter=form07
args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')
kwargs={'timeout': 10.0}
[handler_hand08]
class=handlers.MemoryHandler
level=NOTSET
formatter=form08
target=
args=(10, ERROR)
[handler_hand09]
class=handlers.HTTPHandler
level=NOTSET
formatter=form09
args=('localhost:9022', '/log', 'GET')
kwargs={'secure': True}Sections which specify formatter configuration are typified by the following.
[formatter_form01]
format=F1 %(asctime)s %(levelname)s %(message)s %(customfield)s
datefmt=
style=%
validate=True
defaults={'customfield': 'defaultvalue'}
class=logging.FormatterThe arguments for the formatter configuration are the same as the keys in the dictionary schema :ref:`formatters section <logging-config-dictschema-formatters>`.
The defaults entry, when :ref:`evaluated <func-eval>` in the context of
the logging package's namespace, is a dictionary of default values for
custom formatting fields. If not provided, it defaults to None.
Note
Due to the use of :func:`eval` as described above, there are potential security risks which result from using the :func:`listen` to send and receive configurations via sockets. The risks are limited to where multiple users with no mutual trust run code on the same machine; see the :func:`listen` documentation for more information.
.. seealso::
Module :mod:`logging`
API reference for the logging module.
Module :mod:`logging.handlers`
Useful handlers included with the logging module.