logging --- Python 的日志记录工具

源代码： Lib/logging/__init__.py

Important

此页面仅包含 API 参考信息。教程信息和更多高级用法的讨论，请参阅

• 基础教程

• 进阶教程

• 日志操作手册

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这个模块为应用与库实现了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，包括你自己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。

• 处理器将日志记录（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。

• 格式器指定最终输出中日志记录的样式。

记录器对象

记录器有以下的属性和方法。注意 永远 不要直接实例化记录器，应当通过模块级别的函数 logging.getLogger(name) 。多次使用相同的名字调用 getLogger() 会一直返回相同的 Logger 对象的引用。

name 一般是句点分割的层级值, 像``foo.bar.baz`` (尽管也可以只是普通的 foo)。层次结构列表中位于下方的记录器是列表中较高位置的记录器的子级。例如，有个名叫 foo 的记录器，而名字是 foo.bar，foo.bar.baz，和 foo.bam 的记录器都是 foo 的子级。记录器的名字分级类似 Python 包的层级，如果您使用建议的结构 logging.getLogger(__name__) 在每个模块的基础上组织记录器，则与之完全相同。这是因为在模块里，__name__ 是该模块在 Python 包命名空间中的名字。

class logging.Logger

propagate

如果这个属性为真，记录到这个记录器的事件除了会发送到此记录器的所有处理程序外，还会传递给更高级别（祖先）记录器的处理器，此外任何关联到这个记录器的处理器。消息会直接传递给祖先记录器的处理器 —— 不考虑祖先记录器的级别和过滤器。

如果为假，记录消息将不会传递给当前记录器的祖先记录器的处理器。

构造器将这个属性初始化为 True。

注解

如果你将一个处理器附加到一个记录器 和 其一个或多个祖先记录器，它可能发出多次相同的记录。通常，您不需要将一个处理器附加到一个以上的记录器上 —— 如果您将它附加到记录器层次结构中最高的适当记录器上，则它将看到所有后代记录器记录的所有事件，前提是它们的传播设置保留为 True。一种常见的方案是仅将处理程序附加到根记录器，通过传播来处理其余部分。

setLevel(level)

给记录器设置阈值为 level 。日志等级小于 level 会被忽略。严重性为 level 或更高的日志消息将由该记录器的任何一个或多个处理器发出，除非将处理器的级别设置为比 level 更高的级别。

创建记录器时，级别默认设置为 NOTSET （当记录器是根记录器时，将处理所有消息；如果记录器不是根记录器，则将委托给父级）。请注意，根记录器的默认级别为 WARNING。

委派给父级的意思是如果一个记录器的级别设置为 NOTSET，将遍历其祖先记录器，直到找到级别不是 NOTSET 的记录器，或者到根记录器为止。

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。

如果搜索到达根记录器，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。

在 3.2 版更改: 现在 level 参数可以接受形如 'INFO' 的级别字符串表示形式，以代替形如 INFO 的整数常量。 但是请注意，级别在内部存储为整数，并且 getEffectiveLevel() 和 isEnabledFor() 等方法的传入/返回值也为整数。

isEnabledFor(level)

指示此记录器是否将处理级别为 level 的消息。此方法首先检查由 logging.disable(level) 设置的模块级的级别，然后检查由 getEffectiveLevel() 确定的记录器的有效级别。

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。

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。

3.2 新版功能.

debug(msg, *args, **kwargs)

在此纪录器上记录 DEBUG 级别的消息。 msg 是消息格式字符串，而 args 是用于字符串格式化操作合并到 msg 的参数。（请注意，这意味着您可以在格式字符串中使用关键字以及单个字典参数。）当未提供 args 时，不会对 msg 执行 ％ 格式化操作。

在 kwargs 中会检查四个关键字参数： exc_info，stack_info，stacklevel*和*extra。

如果 exc_info 的求值结果不为 false，则它将异常信息添加到日志消息中。如果提供了一个异常元组（按照 sys.exc_info() 返回的格式）或一个异常实例，则将其使用；否则，调用 sys.exc_info() 以获取异常信息。

第二个可选关键字参数是 stack_info，默认为 False。如果为 True，则将堆栈信息添加到日志消息中，包括实际的日志调用。请注意，这与通过指定 exc_info 显示的堆栈信息不同：前者是从堆栈底部到当前线程中的日志记录调用的堆栈帧，而后者是在搜索异常处理程序时，跟踪异常而打开的堆栈帧的信息。

您可以独立于 exc_info 来指定 stack_info，例如，即使在未引发任何异常的情况下，也可以显示如何到达代码中的特定点。堆栈帧在标题行之后打印：

Stack (most recent call last):

这模仿了显示异常帧时所使用的 Traceback (most recent call last): 。

第三个可选关键字参数是 stacklevel，默认为 1。如果大于 1，则在为日志记录事件创建的 LogRecord 中计算行号和函数名时，将跳过相应数量的堆栈帧。可以在记录帮助器时使用它，以便记录的函数名称，文件名和行号不是帮助器的函数/方法的信息，而是其调用方的信息。此参数是 warnings 模块中的同名等效参数。

第四个关键字参数是 extra ，传递一个字典，该字典用于填充为日志记录事件创建的、带有用户自定义属性的 LogRecord 中的__dict__ 。然后可以按照需求使用这些自定义属性。例如，可以将它们合并到已记录的消息中：

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)

输出类似于

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.)

如果在已记录的消息中使用这些属性，则需要格外小心。例如，在上面的示例中，Formatter 已设置了格式字符串，其在 LogRecord 的属性字典中键值为 “clientip” 和 “user”。如果缺少这些内容，则将不会记录该消息，因为会引发字符串格式化异常。因此，在这种情况下，您始终需要使用这些键传递 extra 字典。

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 3.2 版更改: 增加了 stack_info 参数。

在 3.5 版更改: The exc_info parameter can now accept exception instances.

在 3.8 版更改: 增加了 stacklevel 参数。

info(msg, *args, **kwargs)

在此记录器上记录 INFO 级别的消息。参数解释同 debug()。

warning(msg, *args, **kwargs)

在此记录器上记录 WARNING 级别的消息。参数解释同 debug()。

注解

有一个功能上与 warning 一致的方法 warn。由于 warn 已被弃用，请不要使用它 —— 改为使用 warning。

error(msg, *args, **kwargs)

在此记录器上记录 ERROR 级别的消息。参数解释同 debug()。

critical(msg, *args, **kwargs)

在此记录器上记录 CRITICAL 级别的消息。参数解释同 debug()。

log(level, msg, *args, **kwargs)

在此记录器上记录 level 整数代表的级别的消息。参数解释同 debug()。

exception(msg, *args, **kwargs)

在此记录器上记录 ERROR 级别的消息。参数解释同 debug()。异常信息将添加到日志消息中。仅应从异常处理程序中调用此方法。

addFilter(filter)

将指定的过滤器 filter 添加到此记录器。

removeFilter(filter)

从此记录器中删除指定的过滤器 filter。

filter(record)

将此记录器的过滤器应用于记录，如果记录能被处理则返回 True。过滤器会被依次使用，直到其中一个返回假值为止。如果它们都不返回假值，则记录将被处理（传递给处理器）。如果返回任一为假值，则不会对该记录做进一步处理。

addHandler(hdlr)

将指定的处理器 hdlr 添加到此记录器。

removeHandler(hdlr)

从此记录器中删除指定的处理器 hdlr。

findCaller(stack_info=False, stacklevel=1)

查找调用源的文件名和行号，以 文件名，行号，函数名称和堆栈信息 4元素元组的形式返回。堆栈信息将返回 None，除非 stack_info 为 True。

stacklevel 参数用于调用 debug() 和其他 API。如果大于 1，则多余部分将用于跳过堆栈帧，然后再确定要返回的值。当从帮助器/包装器代码调用日志记录 API 时，这通常很有用，以便事件日志中的信息不是来自帮助器/包装器代码，而是来自调用它的代码。

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() 进行记录器级别过滤。

makeRecord(name, level, fn, lno, msg, args, exc_info, func=None, extra=None, sinfo=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。

hasHandlers()

检查此记录器是否配置了任何处理器。通过在此记录器及其记录器层次结构中的父级中查找处理器完成此操作。如果找到处理器则返回 True，否则返回 False。只要找到 “propagate” 属性设置为假值的记录器，该方法就会停止搜索层次结构 —— 其将是最后一个检查处理器是否存在的记录器。

3.2 新版功能.

在 3.7 版更改: 现在可以对处理器进行序列化和反序列化。

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

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__() 。

class logging.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。

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。

acquire()

使用 createLock() 获取线程锁。

release()

使用 acquire() 来释放线程锁。

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。

在 3.2 版更改: level 形参现在接受像 'INFO' 这样的字符串形式的级别表达方式，也可以使用像 INFO 这样的整数常量。

setFormatter(fmt)

将此处理器的 Formatter 设置为 fmt。

addFilter(filter)

将指定的过滤器 filter 添加到此处理器。

removeFilter(filter)

从此处理器中删除指定的过滤器 filter 。

filter(record)

将此处理器的过滤器应用于记录，在要处理记录时返回 True 。依次查询过滤器，直到其中一个返回假值为止。如果它们都不返回假值，则将发出记录。如果返回一个假值，则处理器将不会发出记录。

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。

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。

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。

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）。

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。

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列表，请参见 logging.handlers。

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。

格式器可以使用格式化字符串来初始化，该字符串利用 LogRecord 的属性 —— 例如上述默认值，用户的消息和参数预先格式化为 LogRecord 的 message 属性后被使用。此格式字符串包含标准的 Python %-s 样式映射键。有关字符串格式的更多信息，请参见 printf 风格的字符串格式化。

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

class logging.Formatter(fmt=None, datefmt=None, style='%')

返回 Formatter 类的新实例。实例将使用整个消息的格式字符串以及消息的日期/时间部分的格式字符串进行初始化。如果未指定 fmt ，则使用 '%(message)s'。如果未指定 datefmt，则使用 formatTime() 文档中描述的格式。

The style parameter can be one of '%', '{' or '$' and determines how the format string will be merged with its data: using one of %-formatting, str.format() or string.Template. See Using particular formatting styles throughout your application for more information on using {- and $-formatting for log messages.

在 3.2 版更改: style 参数已加入.

在 3.8 版更改: The validate parameter was added. Incorrect or mismatched style and fmt will raise a ValueError. For example: logging.Formatter('%(asctime)s - %(message)s', style='{').

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。

如果栈信息可用，它将被添加在异常信息之后，如有必要请使用 formatStack() 来转换它。

formatTime(record, datefmt=None)

此方法应由想要使用格式化时间的格式器中的 format() 调用。可以在格式器中重写此方法以提供任何特定要求，但是基本行为如下：如果指定了 datefmt （字符串），则将其用于 time.strftime() 来格式化记录的创建时间。否则，使用格式 '%Y-%m-%d %H:%M:%S,uuu'，其中 uuu 部分是毫秒值，其他字母根据 time.strftime() 文档。这种时间格式的示例为 2003-01-23 00:29:50,411。返回结果字符串。

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.

在 3.3 版更改: Previously, the default format was hard-coded as in this example: 2010-09-06 22:38:15,292 where the part before the comma is handled by a strptime format string ('%Y-%m-%d %H:%M:%S'), and the part after the comma is a millisecond value. Because strptime does not have a format placeholder for milliseconds, the millisecond value is appended using another format string, '%s,%03d' --- and both of these format strings have been hardcoded into this method. With the change, these strings are defined as class-level attributes which can be overridden at the instance level when desired. The names of the attributes are default_time_format (for the strptime format string) and default_msec_format (for appending the millisecond value).

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.

formatStack(stack_info)

Formats the specified stack information (a string as returned by traceback.print_stack(), but with the last newline removed) as a string. This default implementation just returns the input value.

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.

在 3.2 版更改: You don't need to create specialized Filter classes, or use other classes with a filter method: you can use a function (or other callable) as a filter. The filtering logic will check to see if the filter object has a filter attribute: if it does, it's assumed to be a Filter and its filter() method is called. Otherwise, it's assumed to be a callable and called with the record as the single parameter. The returned value should conform to that returned by filter().

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).

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, sinfo=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.

• sinfo -- A text string representing stack information from the base of the stack in the current thread, up to the logging call.

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.

在 3.2 版更改: The creation of a LogRecord has been made more configurable by providing a factory which is used to create the record. The factory can be set using getLogRecordFactory() and setLogRecordFactory() (see this for the factory's signature).

This functionality can be used to inject your own values into a LogRecord at creation time. You can use the following pattern:

old_factory = logging.getLogRecordFactory()

def record_factory(*args, **kwargs):
    record = old_factory(*args, **kwargs)
    record.custom_attribute = 0xdecafbad
    return record

logging.setLogRecordFactory(record_factory)

With this pattern, multiple factories could be chained, and as long as they don't overwrite each other's attributes or unintentionally overwrite the standard attributes listed above, there should be no surprises.

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.

If you are using {}-formatting (str.format()), you can use {attrname} as the placeholder in the format string. If you are using $-formatting (string.Template), use the form ${attrname}. In both cases, of course, replace attrname with the actual attribute name you want to use.

In the case of {}-formatting, you can specify formatting flags by placing them after the attribute name, separated from it with a colon. For example: a placeholder of {msecs:03d} would format a millisecond value of 4 as 004. Refer to the str.format() documentation for full details on the options available to you.

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.
文件名	%(filename)s	Filename portion of pathname.
funcName	%(funcName)s	Name of function containing the logging call.
levelname	%(levelname)s	Text logging level for the message ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL').
levelno	%(levelno)s	Numeric logging level for the message (DEBUG, INFO, WARNING, ERROR, CRITICAL).
lineno	%(lineno)d	Source line number where the logging call was issued (if available).
message	%(message)s	The logged message, computed as msg % args. This is set when Formatter.format() is invoked.
module	%(module)s	模块 (filename 的名称部分)。
msecs	%(msecs)d	Millisecond portion of the time when the LogRecord was created.
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.
stack_info	不需要格式化。	Stack frame information (where available) from the bottom of the stack in the current thread, up to and including the stack frame of the logging call which resulted in the creation of this record.
thread	%(thread)d	线程ID（如果可用）
threadName	%(threadName)s	线程名（如果可用）

在 3.1 版更改: 添加了 processName

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.

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(), isEnabledFor(), getEffectiveLevel(), setLevel() and hasHandlers(). These methods have the same signatures as their counterparts in Logger, so you can use the two types of instances interchangeably.

在 3.2 版更改: The isEnabledFor(), getEffectiveLevel(), setLevel() and hasHandlers() methods were added to LoggerAdapter. These methods delegate to the underlying logger.

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.

模块级别函数

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

logging.getLogger(name=None)

Return a logger with the specified name or, if name is None, 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.getLogRecordFactory()

Return a callable which is used to create a LogRecord.

3.2 新版功能: This function has been provided, along with setLogRecordFactory(), to allow developers more control over how the LogRecord representing a logging event is constructed.

See setLogRecordFactory() for more information about the how the factory is called.

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 three 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()) or an exception instance is provided, it is used; otherwise, sys.exc_info() is called to get the exception information.

第二个可选关键字参数是 stack_info，默认为 False。如果为 True，则将堆栈信息添加到日志消息中，包括实际的日志调用。请注意，这与通过指定 exc_info 显示的堆栈信息不同：前者是从堆栈底部到当前线程中的日志记录调用的堆栈帧，而后者是在搜索异常处理程序时，跟踪异常而打开的堆栈帧的信息。

您可以独立于 exc_info 来指定 stack_info，例如，即使在未引发任何异常的情况下，也可以显示如何到达代码中的特定点。堆栈帧在标题行之后打印：

Stack (most recent call last):

这模仿了显示异常帧时所使用的 Traceback (most recent call last): 。

The third 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 3.2 版更改: 增加了 stack_info 参数。

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().

注解

There is an obsolete function warn which is functionally identical to warning. As warn is deprecated, please do not use it - use warning instead.

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(). Exception info is 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(level=CRITICAL)

Provides an overriding level level 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 level 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.

Note that if you have defined any custom logging level higher than CRITICAL (this is not recommended), you won't be able to rely on the default value for the level parameter, but will have to explicitly supply a suitable value.

在 3.7 版更改: The level parameter was defaulted to level CRITICAL. See Issue #28524 for more information about this change.

logging.addLevelName(level, levelName)

Associates level level 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(level)

Returns the textual representation of logging level level. 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 level 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' % level is returned.

注解

Levels are internally integers (as they need to be compared in the logging logic). 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).

在 3.4 版更改: In Python versions earlier than 3.4, this function could also be passed a text level, and would return the corresponding numeric value of the level. This undocumented behaviour was considered a mistake, and was removed in Python 3.4, but reinstated in 3.4.2 due to retain backward compatibility.

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, unless the keyword argument force is set to True.

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().
style	If format is specified, use this style for the format string. One of '%', '{' or '$' for printf-style, str.format() or string.Template respectively. Defaults to '%'.
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, a ValueError is raised.
handlers	If specified, this should be an iterable of already created handlers to add to the root logger. Any handlers which don't already have a formatter set will be assigned the default formatter created in this function. Note that this argument is incompatible with filename or stream - if both are present, a ValueError is raised.
force	如果将此关键字参数指定为 true，则在执行其他参数指定的配置之前，将移除并关闭附加到根记录器的所有现有处理器。

在 3.2 版更改: 增加了 style 参数。

在 3.3 版更改: The handlers argument was added. Additional checks were added to catch situations where incompatible arguments are specified (e.g. handlers together with stream or filename, or stream together with filename).

在 3.8 版更改: 增加了 force 参数。

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.

When the logging module is imported, it registers this function as an exit handler (see atexit), so normally there's no need to do that manually.

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. After this call, as at any other time, do not instantiate loggers directly using the subclass: continue to use the logging.getLogger() API to get your loggers.

logging.setLogRecordFactory(factory)

Set a callable which is used to create a LogRecord.

参数

factory -- The factory callable to be used to instantiate a log record.

3.2 新版功能: This function has been provided, along with getLogRecordFactory(), to allow developers more control over how the LogRecord representing a logging event is constructed.

The factory has the following signature:

factory(name, level, fn, lno, msg, args, exc_info, func=None, sinfo=None, **kwargs)

名称

日志记录器名称

level

日志记录级别（数字）。

fn

进行日志记录调用的文件的完整路径名。

lno

记录调用所在文件中的行号。

msg

日志消息。

args

日志记录消息的参数。

exc_info

异常元组，或 None 。

func

调用日志记录调用的函数或方法的名称。

sinfo

A stack traceback such as is provided by traceback.print_stack(), showing the call hierarchy.

kwargs

其他关键字参数。

模块级属性

logging.lastResort

A "handler of last resort" is available through this attribute. This is a StreamHandler writing to sys.stderr with a level of WARNING, and is used to handle logging events in the absence of any logging configuration. The end result is to just print the message to sys.stderr. This replaces the earlier error message saying that "no handlers could be found for logger XYZ". If you need the earlier behaviour for some reason, lastResort can be set to None.

3.2 新版功能.

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

logging.config 模块

日志记录模块的配置 API 。

logging.handlers 模块

日志记录模块附带的有用处理器。

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。