15.7. logging — Logging facility for Python - Python 2.7.18 documentation 编辑

Important

This page contains the API reference information. For tutorial information and discussion of more advanced topics, see

• Basic Tutorial

• Advanced Tutorial

• Logging Cookbook

Source code: Lib/logging/__init__.py

New in version 2.3.

This module defines functions and classes which implement a flexible event logging system for applications and libraries.

The key benefit of having the logging API provided by a standard library module is that all Python modules can participate in logging, so your application log can include your own messages integrated with messages from third-party modules.

The module provides a lot of functionality and flexibility. If you are unfamiliar with logging, the best way to get to grips with it is to see the tutorials (see the links on the right).

The basic classes defined by the module, together with their functions, are listed below.

• 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.

15.7.1. Logger Objects

Loggers have the following attributes and methods. Note that Loggers are never instantiated directly, but always through the module-level function logging.getLogger(name). Multiple calls to getLogger() with the same name will always return a reference to the same Logger object.

The name is potentially a period-separated hierarchical value, like foo.bar.baz (though it could also be just plain foo, for example). 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. The logger name hierarchy is analogous to the Python package hierarchy, and identical to it if you organise your loggers on a per-module basis using the recommended construction logging.getLogger(__name__). That’s because in a module, __name__ is the module’s name in the Python package namespace.

class logging.Logger

Logger.propagate

If this evaluates to true, events logged to this logger will be passed to the handlers of higher level (ancestor) loggers, in addition to any handlers attached to this logger. Messages are passed directly to the ancestor loggers’ handlers - neither the level nor filters of the ancestor loggers in question are considered.

If this evaluates to false, logging messages are not passed to the handlers of ancestor loggers.

The constructor sets this attribute to True.

Note

If you attach a handler to a logger and one or more of its ancestors, it may emit the same record multiple times. In general, you should not need to attach a handler to more than one logger - if you just attach it to the appropriate logger which is highest in the logger hierarchy, then it will see all events logged by all descendant loggers, provided that their propagate setting is left set to True. A common scenario is to attach handlers only to the root logger, and to let propagation take care of the rest.

Logger.setLevel(level)

Sets the threshold for this logger to level. Logging messages which are less severe than level will be ignored. When a logger is created, the level is set to NOTSET (which causes all messages to be processed when the logger is the root logger, or delegation to the parent when the logger is a non-root logger). Note that the root logger is created with level WARNING.

The term ‘delegation to the parent’ means that if a logger has a level of NOTSET, its chain of ancestor loggers is traversed until either an ancestor with a level other than NOTSET is found, or the root is reached.

If an ancestor is found with a level other than NOTSET, then that ancestor’s level is treated as the effective level of the logger where the ancestor search began, and is used to determine how a logging event is handled.

If the root is reached, and it has a level of NOTSET, then all messages will be processed. Otherwise, the root’s level will be used as the effective level.

See Logging Levels for a list of levels.

Logger.isEnabledFor(lvl)

Indicates if a message of severity lvl would be processed by this logger. This method checks first the module-level level set by logging.disable(lvl) and then the logger’s effective level as determined by getEffectiveLevel().

Logger.getEffectiveLevel()

Indicates the effective level for this logger. If a value other than NOTSET has been set using setLevel(), it is returned. Otherwise, the hierarchy is traversed towards the root until a value other than NOTSET is found, and that value is returned. The value returned is an integer, typically one of logging.DEBUG, logging.INFO etc.

Logger.getChild(suffix)

Returns a logger which is a descendant to this logger, as determined by the suffix. Thus, logging.getLogger('abc').getChild('def.ghi') would return the same logger as would be returned by logging.getLogger('abc.def.ghi'). This is a convenience method, useful when the parent logger is named using e.g. __name__ rather than a literal string.

New in version 2.7.

Logger.debug(msg, *args, **kwargs)

Logs a message with level DEBUG on this logger. The msg is the message format string, and the args are the arguments which are merged into msg using the string formatting operator. (Note that this means that you can use keywords in the format string, together with a single dictionary argument.)

There are two keyword arguments in kwargs which are inspected: exc_info which, if it does not evaluate as false, causes exception information to be added to the logging message. If an exception tuple (in the format returned by sys.exc_info()) is provided, it is used; otherwise, sys.exc_info() is called to get the exception information.

The second keyword argument is extra which can be used to pass a dictionary which is used to populate the __dict__ of the LogRecord created for the logging event with user-defined attributes. These custom attributes can then be used as you like. For example, they could be incorporated into logged messages. For example:

FORMAT = '%(asctime)-15s %(clientip)s %(user)-8s %(message)s'
logging.basicConfig(format=FORMAT)
d = {'clientip': '192.168.0.1', 'user': 'fbloggs'}
logger = logging.getLogger('tcpserver')
logger.warning('Protocol problem: %s', 'connection reset', extra=d)

would print something like

2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

The keys in the dictionary passed in extra should not clash with the keys used by the logging system. (See the Formatter documentation for more information on which keys are used by the logging system.)

If you choose to use these attributes in logged messages, you need to exercise some care. In the above example, for instance, the Formatter has been set up with a format string which expects ‘clientip’ and ‘user’ in the attribute dictionary of the LogRecord. If these are missing, the message will not be logged because a string formatting exception will occur. So in this case, you always need to pass the extra dictionary with these keys.

While this might be annoying, this feature is intended for use in specialized circumstances, such as multi-threaded servers where the same code executes in many contexts, and interesting conditions which arise are dependent on this context (such as remote client IP address and authenticated user name, in the above example). In such circumstances, it is likely that specialized Formatters would be used with particular Handlers.

Logger.info(msg, *args, **kwargs)

Logs a message with level INFO on this logger. The arguments are interpreted as for debug().

Logger.warning(msg, *args, **kwargs)

Logs a message with level WARNING on this logger. The arguments are interpreted as for debug().

Logger.error(msg, *args, **kwargs)

Logs a message with level ERROR on this logger. The arguments are interpreted as for debug().

Logger.critical(msg, *args, **kwargs)

Logs a message with level CRITICAL on this logger. The arguments are interpreted as for debug().

Logger.log(lvl, msg, *args, **kwargs)

Logs a message with integer level lvl on this logger. The other arguments are interpreted as for debug().

Logger.exception(msg, *args, **kwargs)

Logs a message with level ERROR on this logger. The arguments are interpreted as for debug(), except that any passed exc_info is not inspected. Exception info is always added to the logging message. This method should only be called from an exception handler.

Logger.addFilter(filter)

Adds the specified filter filter to this logger.

Logger.removeFilter(filter)

Removes the specified filter filter from this logger.

Logger.filter(record)

Applies this logger’s filters to the record and returns a true value if the record is to be processed. The filters are consulted in turn, until one of them returns a false value. If none of them return a false value, the record will be processed (passed to handlers). If one returns a false value, no further processing of the record occurs.

Logger.addHandler(hdlr)

Adds the specified handler hdlr to this logger.

Logger.removeHandler(hdlr)

Removes the specified handler hdlr from this logger.

Logger.findCaller()

Finds the caller’s source filename and line number. Returns the filename, line number and function name as a 3-element tuple.

Changed in version 2.4: The function name was added. In earlier versions, the filename and line number were returned as a 2-element tuple.

Logger.handle(record)

Handles a record by passing it to all handlers associated with this logger and its ancestors (until a false value of propagate is found). This method is used for unpickled records received from a socket, as well as those created locally. Logger-level filtering is applied using filter().

Logger.makeRecord(name, lvl, fn, lno, msg, args, exc_info, func=None, extra=None)

This is a factory method which can be overridden in subclasses to create specialized LogRecord instances.

Changed in version 2.5: func and extra were added.

15.7.2. 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.

15.7.3. Handler Objects

Handlers have the following attributes and methods. Note that Handler is never instantiated directly; this class acts as a base for more useful subclasses. However, the __init__() method in subclasses needs to call Handler.__init__().

Handler.__init__(level=NOTSET)

Initializes the Handler instance by setting its level, setting the list of filters to the empty list and creating a lock (using createLock()) for serializing access to an I/O mechanism.

Handler.createLock()

Initializes a thread lock which can be used to serialize access to underlying I/O functionality which may not be threadsafe.

Handler.acquire()

Acquires the thread lock created with createLock().

Handler.release()

Releases the thread lock acquired with acquire().

Handler.setLevel(level)

Sets the threshold for this handler to level. Logging messages which are less severe than level will be ignored. When a handler is created, the level is set to NOTSET (which causes all messages to be processed).

See Logging Levels for a list of levels.

Handler.setFormatter(fmt)

Sets the Formatter for this handler to fmt.

Handler.addFilter(filter)

Adds the specified filter filter to this handler.

Handler.removeFilter(filter)

Removes the specified filter filter from this handler.

Handler.filter(record)

Applies this handler’s filters to the record and returns a true value if the record is to be processed. The filters are consulted in turn, until one of them returns a false value. If none of them return a false value, the record will be emitted. If one returns a false value, the handler will not emit the record.

Handler.flush()

Ensure all logging output has been flushed. This version does nothing and is intended to be implemented by subclasses.

Handler.close()

Tidy up any resources used by the handler. This version does no output but removes the handler from an internal list of handlers which is closed when shutdown() is called. Subclasses should ensure that this gets called from overridden close() methods.

Handler.handle(record)

Conditionally emits the specified logging record, depending on filters which may have been added to the handler. Wraps the actual emission of the record with acquisition/release of the I/O thread lock.

Handler.handleError(record)

This method should be called from handlers when an exception is encountered during an emit() call. If the module-level attribute raiseExceptions is False, exceptions get silently ignored. This is what is mostly wanted for a logging system - most users will not care about errors in the logging system, they are more interested in application errors. You could, however, replace this with a custom handler if you wish. The specified record is the one which was being processed when the exception occurred. (The default value of raiseExceptions is True, as that is more useful during development).

Handler.format(record)

Do formatting for a record - if a formatter is set, use it. Otherwise, use the default formatter for the module.

Handler.emit(record)

Do whatever it takes to actually log the specified logging record. This version is intended to be implemented by subclasses and so raises a NotImplementedError.

For a list of handlers included as standard, see logging.handlers.

15.7.4. Formatter Objects

Formatter objects have the following attributes and methods. They are responsible for converting a LogRecord to (usually) a string which can be interpreted by either a human or an external system. The base Formatter allows a formatting string to be specified. If none is supplied, the default value of '%(message)s' is used, which just includes the message in the logging call. To have additional items of information in the formatted output (such as a timestamp), keep reading.

A Formatter can be initialized with a format string which makes use of knowledge of the LogRecord attributes - such as the default value mentioned above making use of the fact that the user’s message and arguments are pre-formatted into a LogRecord’s message attribute. This format string contains standard Python %-style mapping keys. See section String Formatting Operations for more information on string formatting.

The useful mapping keys in a LogRecord are given in the section on LogRecord attributes.

class logging.Formatter(fmt=None, datefmt=None)

Returns a new instance of the Formatter class. The instance is initialized with a format string for the message as a whole, as well as a format string for the date/time portion of a message. If no fmt is specified, '%(message)s' is used. If no datefmt is specified, the ISO8601 date format is used.

format(record)

The record’s attribute dictionary is used as the operand to a string formatting operation. Returns the resulting string. Before formatting the dictionary, a couple of preparatory steps are carried out. The message attribute of the record is computed using msg % args. If the formatting string contains '(asctime)', formatTime() is called to format the event time. If there is exception information, it is formatted using formatException() and appended to the message. Note that the formatted exception information is cached in attribute exc_text. This is useful because the exception information can be pickled and sent across the wire, but you should be careful if you have more than one Formatter subclass which customizes the formatting of exception information. In this case, you will have to clear the cached value after a formatter has done its formatting, so that the next formatter to handle the event doesn’t use the cached value but recalculates it afresh.

formatTime(record, datefmt=None)

This method should be called from format() by a formatter which wants to make use of a formatted time. This method can be overridden in formatters to provide for any specific requirement, but the basic behavior is as follows: if datefmt (a string) is specified, it is used with time.strftime() to format the creation time of the record. Otherwise, the ISO8601 format is used. The resulting string is returned.

This function uses a user-configurable function to convert the creation time to a tuple. By default, time.localtime() is used; to change this for a particular formatter instance, set the converter attribute to a function with the same signature as time.localtime() or 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.

formatException(exc_info)

Formats the specified exception information (a standard exception tuple as returned by sys.exc_info()) as a string. This default implementation just uses traceback.print_exception(). The resulting string is returned.

15.7.5. Filter Objects

Filters can be used by Handlers and Loggers for more sophisticated filtering than is provided by levels. The base filter class only allows events which are below a certain point in the logger hierarchy. For example, a filter initialized with ‘A.B’ will allow events logged by loggers ‘A.B’, ‘A.B.C’, ‘A.B.C.D’, ‘A.B.D’ etc. but not ‘A.BB’, ‘B.A.B’ etc. If initialized with the empty string, all events are passed.

class logging.Filter(name='')

Returns an instance of the Filter class. If name is specified, it names a logger which, together with its children, will have its events allowed through the filter. If name is the empty string, allows every event.

filter(record)

Is the specified record to be logged? Returns zero for no, nonzero for yes. If deemed appropriate, the record may be modified in-place by this method.

Note that filters attached to handlers are consulted before an event is emitted by the handler, whereas filters attached to loggers are consulted whenever an event is logged (using debug(), info(), etc.), before sending an event to handlers. This means that events which have been generated by descendant loggers will not be filtered by a logger’s filter setting, unless the filter has also been applied to those descendant loggers.

You don’t actually need to subclass Filter: you can pass any instance which has a filter method with the same semantics.

Although filters are used primarily to filter records based on more sophisticated criteria than levels, they get to see every record which is processed by the handler or logger they’re attached to: this can be useful if you want to do things like counting how many records were processed by a particular logger or handler, or adding, changing or removing attributes in the LogRecord being processed. Obviously changing the LogRecord needs to be done with some care, but it does allow the injection of contextual information into logs (see Using Filters to impart contextual information).

15.7.6. LogRecord Objects

LogRecord instances are created automatically by the Logger every time something is logged, and can be created manually via makeLogRecord() (for example, from a pickled event received over the wire).

class logging.LogRecord(name, level, pathname, lineno, msg, args, exc_info, func=None)

Contains all the information pertinent to the event being logged.

The primary information is passed in msg and args, which are combined using msg % args to create the message field of the record.

Parameters

• name – The name of the logger used to log the event represented by this LogRecord. Note that this name will always have this value, even though it may be emitted by a handler attached to a different (ancestor) logger.

• level – The numeric level of the logging event (one of DEBUG, INFO etc.) Note that this is converted to two attributes of the LogRecord: levelno for the numeric value and levelname for the corresponding level name.

• pathname – The full pathname of the source file where the logging call was made.

• lineno – The line number in the source file where the logging call was made.

• msg – The event description message, possibly a format string with placeholders for variable data.

• args – Variable data to merge into the msg argument to obtain the event description.

• exc_info – An exception tuple with the current exception information, or None if no exception information is available.

• func – The name of the function or method from which the logging call was invoked.

Changed in version 2.5: func was added.

getMessage()

Returns the message for this LogRecord instance after merging any user-supplied arguments with the message. If the user-supplied message argument to the logging call is not a string, str() is called on it to convert it to a string. This allows use of user-defined classes as messages, whose __str__ method can return the actual format string to be used.

15.7.7. LogRecord attributes

The LogRecord has a number of attributes, most of which are derived from the parameters to the constructor. (Note that the names do not always correspond exactly between the LogRecord constructor parameters and the LogRecord attributes.) These attributes can be used to merge data from the record into the format string. The following table lists (in alphabetical order) the attribute names, their meanings and the corresponding placeholder in a %-style format string.

Changed in version 2.5: funcName was added.

Changed in version 2.6: processName was added.

15.7.8. LoggerAdapter Objects

LoggerAdapter instances are used to conveniently pass contextual information into logging calls. For a usage example, see the section on adding contextual information to your logging output.

New in version 2.6.

class logging.LoggerAdapter(logger, extra)

Returns an instance of LoggerAdapter initialized with an underlying Logger instance and a dict-like object.

process(msg, kwargs)

Modifies the message and/or keyword arguments passed to a logging call in order to insert contextual information. This implementation takes the object passed as extra to the constructor and adds it to kwargs using key ‘extra’. The return value is a (msg, kwargs) tuple which has the (possibly modified) versions of the arguments passed in.

In addition to the above, LoggerAdapter supports the following methods of Logger: debug(), info(), warning(), error(), exception(), critical(), log() and isEnabledFor(). These methods have the same signatures as their counterparts in Logger, so you can use the two types of instances interchangeably for these calls.

Changed in version 2.7: The isEnabledFor() method was added to LoggerAdapter. This method delegates to the underlying logger.

15.7.9. Thread Safety

The logging module is intended to be thread-safe without any special work needing to be done by its clients. It achieves this though using threading locks; there is one lock to serialize access to the module’s shared data, and each handler also creates a lock to serialize access to its underlying I/O.

If you are implementing asynchronous signal handlers using the signal module, you may not be able to use logging from within such handlers. This is because lock implementations in the threading module are not always re-entrant, and so cannot be invoked from such signal handlers.

15.7.10. Module-Level Functions

In addition to the classes described above, there are a number of module- level functions.

logging.getLogger([name])

Return a logger with the specified name or, if no name is specified, return a logger which is the root logger of the hierarchy. If specified, the name is typically a dot-separated hierarchical name like “a”, “a.b” or “a.b.c.d”. Choice of these names is entirely up to the developer who is using logging.

All calls to this function with a given name return the same logger instance. This means that logger instances never need to be passed between different parts of an application.

logging.getLoggerClass()

Return either the standard Logger class, or the last class passed to setLoggerClass(). This function may be called from within a new class definition, to ensure that installing a customized Logger class will not undo customizations already applied by other code. For example:

class MyLogger(logging.getLoggerClass()):
    # ... override behaviour here

logging.debug(msg[, *args[, **kwargs]])

Logs a message with level DEBUG on the root logger. The msg is the message format string, and the args are the arguments which are merged into msg using the string formatting operator. (Note that this means that you can use keywords in the format string, together with a single dictionary argument.)

There are two keyword arguments in kwargs which are inspected: exc_info which, if it does not evaluate as false, causes exception information to be added to the logging message. If an exception tuple (in the format returned by sys.exc_info()) is provided, it is used; otherwise, sys.exc_info() is called to get the exception information.

The other optional keyword argument is extra which can be used to pass a dictionary which is used to populate the __dict__ of the LogRecord created for the logging event with user-defined attributes. These custom attributes can then be used as you like. For example, they could be incorporated into logged messages. For example:

FORMAT = "%(asctime)-15s %(clientip)s %(user)-8s %(message)s"
logging.basicConfig(format=FORMAT)
d = {'clientip': '192.168.0.1', 'user': 'fbloggs'}
logging.warning("Protocol problem: %s", "connection reset", extra=d)

would print something like:

2006-02-08 22:20:02,165 192.168.0.1 fbloggs  Protocol problem: connection reset

The keys in the dictionary passed in extra should not clash with the keys used by the logging system. (See the Formatter documentation for more information on which keys are used by the logging system.)

If you choose to use these attributes in logged messages, you need to exercise some care. In the above example, for instance, the Formatter has been set up with a format string which expects ‘clientip’ and ‘user’ in the attribute dictionary of the LogRecord. If these are missing, the message will not be logged because a string formatting exception will occur. So in this case, you always need to pass the extra dictionary with these keys.

While this might be annoying, this feature is intended for use in specialized circumstances, such as multi-threaded servers where the same code executes in many contexts, and interesting conditions which arise are dependent on this context (such as remote client IP address and authenticated user name, in the above example). In such circumstances, it is likely that specialized Formatters would be used with particular Handlers.

Changed in version 2.5: extra was added.

logging.info(msg[, *args[, **kwargs]])

Logs a message with level INFO on the root logger. The arguments are interpreted as for debug().

logging.warning(msg[, *args[, **kwargs]])

Logs a message with level WARNING on the root logger. The arguments are interpreted as for debug().

logging.error(msg[, *args[, **kwargs]])

Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug().

logging.critical(msg[, *args[, **kwargs]])

Logs a message with level CRITICAL on the root logger. The arguments are interpreted as for debug().

logging.exception(msg[, *args[, **kwargs]])

Logs a message with level ERROR on the root logger. The arguments are interpreted as for debug(), except that any passed exc_info is not inspected. Exception info is always added to the logging message. This function should only be called from an exception handler.

logging.log(level, msg[, *args[, **kwargs]])

Logs a message with level level on the root logger. The other arguments are interpreted as for debug().

Note

The above module-level convenience functions, which delegate to the root logger, call basicConfig() to ensure that at least one handler is available. Because of this, they should not be used in threads, in versions of Python earlier than 2.7.1 and 3.2, unless at least one handler has been added to the root logger before the threads are started. In earlier versions of Python, due to a thread safety shortcoming in basicConfig(), this can (under rare circumstances) lead to handlers being added multiple times to the root logger, which can in turn lead to multiple messages for the same event.

logging.disable(lvl)

Provides an overriding level lvl for all loggers which takes precedence over the logger’s own level. When the need arises to temporarily throttle logging output down across the whole application, this function can be useful. Its effect is to disable all logging calls of severity lvl and below, so that if you call it with a value of INFO, then all INFO and DEBUG events would be discarded, whereas those of severity WARNING and above would be processed according to the logger’s effective level. If logging.disable(logging.NOTSET) is called, it effectively removes this overriding level, so that logging output again depends on the effective levels of individual loggers.

logging.addLevelName(lvl, levelName)

Associates level lvl with text levelName in an internal dictionary, which is used to map numeric levels to a textual representation, for example when a Formatter formats a message. This function can also be used to define your own levels. The only constraints are that all levels used must be registered using this function, levels should be positive integers and they should increase in increasing order of severity.

Note

If you are thinking of defining your own levels, please see the section on Custom Levels.

logging.getLevelName(lvl)

Returns the textual representation of logging level lvl. If the level is one of the predefined levels CRITICAL, ERROR, WARNING, INFO or DEBUG then you get the corresponding string. If you have associated levels with names using addLevelName() then the name you have associated with lvl is returned. If a numeric value corresponding to one of the defined levels is passed in, the corresponding string representation is returned. Otherwise, the string “Level %s” % lvl is returned.

Note

Integer levels should be used when e.g. setting levels on instances of Logger and handlers. This function is used to convert between an integer level and the level name displayed in the formatted log output by means of the %(levelname)s format specifier (see LogRecord attributes).

logging.makeLogRecord(attrdict)

Creates and returns a new LogRecord instance whose attributes are defined by attrdict. This function is useful for taking a pickled LogRecord attribute dictionary, sent over a socket, and reconstituting it as a LogRecord instance at the receiving end.

logging.basicConfig([**kwargs])

Does basic configuration for the logging system by creating a StreamHandler with a default Formatter and adding it to the root logger. The functions debug(), info(), warning(), error() and critical() will call basicConfig() automatically if no handlers are defined for the root logger.

This function does nothing if the root logger already has handlers configured for it.

Changed in version 2.4: Formerly, basicConfig() did not take any keyword arguments.

Note

This function should be called from the main thread before other threads are started. In versions of Python prior to 2.7.1 and 3.2, if this function is called from multiple threads, it is possible (in rare circumstances) that a handler will be added to the root logger more than once, leading to unexpected results such as messages being duplicated in the log.

The following keyword arguments are supported.

Format	Description
filename	Specifies that a FileHandler be created, using the specified filename, rather than a StreamHandler.
filemode	If filename is specified, open the file in this mode. Defaults to 'a'.
format	Use the specified format string for the handler.
datefmt	Use the specified date/time format, as accepted by time.strftime().
level	Set the root logger level to the specified level.
stream	Use the specified stream to initialize the StreamHandler. Note that this argument is incompatible with filename - if both are present, stream is ignored.

logging.shutdown()

Informs the logging system to perform an orderly shutdown by flushing and closing all handlers. This should be called at application exit and no further use of the logging system should be made after this call.

logging.setLoggerClass(klass)

Tells the logging system to use the class klass when instantiating a logger. The class should define __init__() such that only a name argument is required, and the __init__() should call Logger.__init__(). This function is typically called before any loggers are instantiated by applications which need to use custom logger behavior.

15.7.11. Integration with the warnings module

The captureWarnings() function can be used to integrate logging with the warnings module.

logging.captureWarnings(capture)

This function is used to turn the capture of warnings by logging on and off.

If capture is True, warnings issued by the warnings module will be redirected to the logging system. Specifically, a warning will be formatted using warnings.formatwarning() and the resulting string logged to a logger named 'py.warnings' with a severity of WARNING.

If capture is False, the redirection of warnings to the logging system will stop, and warnings will be redirected to their original destinations (i.e. those in effect before captureWarnings(True) was called).

See also

Module logging.config

Configuration API for the logging module.

Module logging.handlers

Useful handlers included with the logging module.

PEP 282 - A Logging System

The proposal which described this feature for inclusion in the Python standard library.

Original Python logging package

This is the original source for the logging package. The version of the package available from this site is suitable for use with Python 1.5.2, 2.1.x and 2.2.x, which do not include the logging package in the standard library.