15.7. 模块 logging — Python 的日志记录工具

Important

此页面仅包含API参考信息。有关更多高级主题的教程信息和讨论，请参阅

• 基础教程

• 进阶教程

• Logging Cookbook

源代码: Lib/logging/__init__.py

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2.3 新版功能.

这个模块为应用与库定义了实现灵活的事件日志系统的函数与类.

使用标准库提提供的 logging API 最主要的好处是，所有的 Python 模块都可能参与日志输出，包括你的日志消息和第三方模块的日志消息。

这个模块提供许多强大而灵活的功能。如果你对 logging 不太熟悉的话， 掌握它最好的方式就是查看它对应的教程（详见右侧的链接）。

该模块定义的基础类和函数都列在下面。

• 记录器暴露了应用程序代码直接使用的接口。

• 处理程序将日志记录（由记录器创建）发送到适当的目标。

• 过滤器提供了更精细的附加功能，用于确定要输出的日志记录。

• 格式化程序指定最终输出中日志记录的样式。

15.7.1. Logger 对象

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.

name 是潜在的周期分割层级值, 像``foo.bar.baz`` (例如, 抛出的可以只是明文的``foo``)。Loggers是进一步在子层次列表的更高loggers列表。例如，有个名叫``foo``的logger，名叫``foo.bar``，foo.bar.baz, 和 foo.bam 都是 foo``的衍生logger. logger的名字分级类似Python 包的层级, 并且相同的如果你组织你的loggers在每模块级别基本上使用推荐的结构``logging.getLogger(__name__)。这是因为在模块里，在Python包的命名空间的模块名为``__name__``。

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.

如果等于假，记录消息将不会传递给这个原型记录器的管理器。

构造器将这个属性初始化为 True。

注解

如果你关联了一个管理器*并且*到它自己的一个或多个记录器，它可能发出多次相同的记录。总体来说，你不需要关联管理器到一个或多个记录器 - 如果你只是关联它到一个合适的记录器等级中的最高级别记录器，它将会看到子记录器所有记录的事件，他们的传播剩下的设置为``True``。一个通用场景是只关联管理器到根记录器，并且让传播照顾剩下的.

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.

委派给父级的意思是如果一个记录器的级别设置为NOTSET，遍历其祖先记录器链，直到找到另一个NOTSET级别的祖先或到达根为止。

如果发现某个父级的级别 不是NOTSET ，那么该父级的级别将被视为发起搜索的记录器的有效级别，并用于确定如何处理日志事件。

如果到达根 logger ，并且其级别为NOTSET，则将处理所有消息。否则，将使用根记录器的级别作为有效级别。

参见 日志级别 级别列表。

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()

指示此记录器的有效级别。如果通过 setLevel() 设置了除 NOTSET 以外的值，则返回该值。否则，将层次结构遍历到根，直到找到除 NOTSET 以外的其他值，然后返回该值。返回的值是一个整数，通常为 logging.DEBUG、 logging.INFO 等等。

Logger.getChild(suffix)

返回由后缀确定的，是该记录器的后代的记录器。 因此，logging.getLogger('abc').getChild('def.ghi') 与 logging.getLogger('abc.def.ghi') 将返回相同的记录器。 这是一个便捷方法，当使用如 __name__ 而不是字符串字面值命名父记录器时很有用。

2.7 新版功能.

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.

尽管这可能很烦人，但此功能旨在用于特殊情况，例如在多个上下文中执行相同代码的多线程服务器，并且出现的有趣条件取决于此上下文（例如在上面的示例中就是远程客户端IP地址和已验证用户名）。在这种情况下，很可能将专门的 Formatter 与特定的 Handler 一起使用。

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

在此记录器上记录 INFO 级别的消息。参数解释同 debug()。

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

在此记录器上记录 WARNING 级别的消息。参数解释同 debug()。

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

在此记录器上记录 ERROR 级别的消息。参数解释同 debug()。

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

在此记录器上记录 CRITICAL 级别的消息。参数解释同 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)

将指定的过滤器 filter 添加到此记录器。

Logger.removeFilter(filter)

从此记录器中删除指定的处理程序 filter。

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)

将指定的处理程序 hdlr 添加到此记录器。

Logger.removeHandler(hdlr)

从此记录器中删除指定的处理器 hdlr。

Logger.findCaller()

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

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

Logger.handle(record)

通过将记录传递给与此记录器及其祖先关联的所有处理器来处理（直到某个 propagate 值为 false）。此方法用于从套接字接收的未序列化的以及在本地创建的记录。使用 filter() 进行记录程序级别过滤。

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

这是一种工厂方法，可以在子类中对其进行重写以创建专门的 LogRecord 实例。

在 2.5 版更改: func and extra were added.

15.7.2. 日志级别

日志记录级别的数值在下表中给出。如果你想要定义自己的级别，并且需要它们具有相对于预定义级别的特定值，那么这些内容可能是你感兴趣的。如果你定义具有相同数值的级别，它将覆盖预定义的值; 预定义的名称丢失。

级别	数值
CRITICAL	50
ERROR	40
WARNING	30
INFO	20
DEBUG	10
NOTSET	0

15.7.3. 处理器对象

Handler 有以下属性和方法。注意不要直接实例化 Handler ；这个类用来派生其他更有用的子类。但是，子类的 __init__() 方法需要调用 Handler.__init__() 。

Handler.__init__(level=NOTSET)

初始化 Handler 实例时，需要设置它的级别，将过滤列表置为空，并且创建锁（通过 createLock() ）来序列化对 I/O 的访问。

Handler.createLock()

初始化一个线程锁，用来序列化对底层的 I/O 功能的访问，底层的 I/O 功能可能不是线程安全的。

Handler.acquire()

使用 createLock() 获取线程锁。

Handler.release()

使用 acquire() 来释放线程锁。

Handler.setLevel(level)

给处理器设置阈值为 level 。日志级别小于 level 将被忽略。创建处理器时，日志级别被设置为 NOTSET （所有的消息都会被处理）。

参见 日志级别 级别列表。

Handler.setFormatter(fmt)

将此处理器的 Formatter 设置为 fmt。

Handler.addFilter(filter)

将指定的过滤器 filter 添加到此处理器。

Handler.removeFilter(filter)

从此处理器中删除指定的过滤器 filter 。

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()

确保所有日志记录从缓存输出。此版本不执行任何操作，并且应由子类实现。

Handler.close()

整理处理器使用的所有资源。此版本不输出，但从内部处理器列表中删除处理器，内部处理器在 shutdown() 被调用时关闭 。子类应确保从重写的 close() 方法中调用此方法。

Handler.handle(record)

经已添加到处理器的过滤器过滤后，有条件地发出指定的日志记录。用获取/释放 I/O 线程锁包装记录的实际发出行为。

Handler.handleError(record)

调用 emit() 期间遇到异常时，应从处理器中调用此方法。如果模块级属性 raiseExceptions 是 False，则异常将被静默忽略。这是大多数情况下日志系统需要的 —— 大多数用户不会关心日志系统中的错误，他们对应用程序错误更感兴趣。但是，你可以根据需要将其替换为自定义处理器。指定的记录是发生异常时正在处理的记录。（raiseExceptions 的默认值是 True，因为这在开发过程中是比较有用的）。

Handler.format(record)

如果设置了格式器则用其对记录进行格式化。否则，使用模块的默认格式器。

Handler.emit(record)

执行实际记录给定日志记录所需的操作。这个版本应由子类实现，因此这里直接引发 NotImplementedError 异常。

有关作为标准随附的处理程序，请参见 logging.handlers。

15.7.4. 格式器对象

Formatter 对象拥有以下的属性和方法。一般情况下，它们负责将 LogRecord 转换为可由人或外部系统解释的字符串。基础的 Formatter 允许指定格式字符串。如果未提供任何值，则使用默认值 '%(message)s' ，它仅将消息包括在日志记录调用中。要在格式化输出中包含其他信息（如时间戳），请阅读下文。

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 属性.

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)

记录的属性字典用作字符串格式化操作的参数。返回结果字符串。在格式化字典之前，需要执行几个准备步骤。 使用 msg % args 计算记录的 message 属性。如果格式化字符串包含 '(asctime)'，则调用 formatTime() 来格式化事件时间。如果有异常信息，则使用 formatException() 将其格式化并附加到消息中。请注意，格式化的异常信息缓存在属性 exc_text 中。这很有用，因为可以对异常信息进行序列化并通过网络发送，但是如果您有不止一个定制了异常信息格式的 Formatter 子类，则应格外小心。在这种情况下，您必须在格式器完成格式化后清除缓存的值，以便下一个处理事件的格式化程序不使用缓存的值，而是重新计算它。

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 对象

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)

是否要记录指定的记录？返回零表示否，非零表示是。如果认为合适，则可以通过此方法就地修改记录。

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 使用过滤器传递上下文信息).

15.7.6. LogRecord 属性

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.

参数

• 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 – 进行日志记录调用的文件的完整路径名。

• lineno – 记录调用所在源文件中的行号。

• 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.

在 2.5 版更改: 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 属性

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.

属性名称	格式	描述
args	不需要格式化。	The tuple of arguments merged into msg to produce message, or a dict whose values are used for the merge (when there is only one argument, and it is a dictionary).
asctime	%(asctime)s	Human-readable time when the LogRecord was created. By default this is of the form ‘2003-07-08 16:49:45,896’ (the numbers after the comma are millisecond portion of the time).
created	%(created)f	Time when the LogRecord was created (as returned by time.time()).
exc_info	不需要格式化。	Exception tuple (à la sys.exc_info) or, if no exception has occurred, None.
filename	%(filename)s	Filename portion of pathname.
funcName	%(funcName)s	函数名包括调用日志记录.
levelname	%(levelname)s	消息文本记录级别 ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL').
levelno	%(levelno)s	消息数字记录级别 (DEBUG, INFO, WARNING, ERROR, CRITICAL).
lineno	%(lineno)d	Source line number where the logging call was issued (if available).
module 模块	%(module)s	模块 (filename 的名称部分)。
msecs	%(msecs)d	Millisecond portion of the time when the LogRecord was created.
message	%(message)s	The logged message, computed as msg % args. This is set when Formatter.format() is invoked.
msg	不需要格式化。	The format string passed in the original logging call. Merged with args to produce message, or an arbitrary object (see 使用任意对象作为消息).
名称	%(name)s	Name of the logger used to log the call.
pathname	%(pathname)s	Full pathname of the source file where the logging call was issued (if available).
process	%(process)d	进程ID（如果可用）
processName	%(processName)s	进程名（如果可用）
relativeCreated	%(relativeCreated)d	Time in milliseconds when the LogRecord was created, relative to the time the logging module was loaded.
thread	%(thread)d	线程ID（如果可用）
threadName	%(threadName)s	线程名（如果可用）

在 2.5 版更改: funcName was added.

在 2.6 版更改: 添加了 processName

15.7.8. LoggerAdapter 对象

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.

2.6 新版功能.

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.

在 2.7 版更改: The isEnabledFor() method was added to LoggerAdapter. This method delegates to the underlying logger.

15.7.9. 线程安全

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. 模块级别函数

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.

尽管这可能很烦人，但此功能旨在用于特殊情况，例如在多个上下文中执行相同代码的多线程服务器，并且出现的有趣条件取决于此上下文（例如在上面的示例中就是远程客户端IP地址和已验证用户名）。在这种情况下，很可能将专门的 Formatter 与特定的 Handler 一起使用。

在 2.5 版更改: 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().

注解

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.

注解

If you are thinking of defining your own levels, please see the section on 自定义级别.

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.

注解

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 属性).

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.

在 2.4 版更改: Formerly, basicConfig() did not take any keyword arguments.

注解

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.

支持以下关键字参数。

格式	描述
filename	使用指定的文件名而不是 StreamHandler 创建 FileHandler。
filemode	If filename is specified, open the file in this mode. Defaults to 'a'.
format	处理器使用的指定格式字符串。
datefmt	Use the specified date/time format, as accepted by time.strftime().
level	设置根记录器级别去指定 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. 与警告模块集成

captureWarnings() 函数可用来将 logging 和 warnings 模块集成。

logging.captureWarnings(capture)

此函数用于打开和关闭日志系统对警告的捕获。

如果 capture 是 True，则 warnings 模块发出的警告将重定向到日志记录系统。具体来说，将使用 warnings.formatwarning() 格式化警告信息，并将结果字符串使用 WARNING 等级记录到名为 'py.warnings' 的记录器中。

如果 capture 是 False，则将停止将警告重定向到日志记录系统，并且将警告重定向到其原始目标（即在 captureWarnings(True) 调用之前的有效目标）。

参见

模块 logging.config

日志记录模块的配置 API 。

模块 logging.handlers

日志记录模块附带的有用处理程序。

PEP 282 - Logging 系统

该提案描述了Python标准库中包含的这个特性。

Original Python logging package

这是该 logging 包的原始来源。该站点提供的软件包版本适用于 Python 1.5.2、2.1.x 和 2.2.x，它们不被 logging 包含在标准库中。