我正在用logging.error将Python异常消息打印到日志文件:

import logging
try:
    1/0
except ZeroDivisionError as e:
    logging.error(e)  # ERROR:root:division by zero

是否可以打印有关异常和生成异常的代码的更详细信息,而不仅仅是异常字符串?行号或堆栈跟踪之类的东西会很棒。


当前回答

一点点装饰处理(非常松散的灵感来自可能单子和提升)。您可以安全地删除Python 3.6类型注释,并使用较旧的消息格式化样式。

fallible.py

from functools import wraps
from typing import Callable, TypeVar, Optional
import logging


A = TypeVar('A')


def fallible(*exceptions, logger=None) \
        -> Callable[[Callable[..., A]], Callable[..., Optional[A]]]:
    """
    :param exceptions: a list of exceptions to catch
    :param logger: pass a custom logger; None means the default logger, 
                   False disables logging altogether.
    """
    def fwrap(f: Callable[..., A]) -> Callable[..., Optional[A]]:

        @wraps(f)
        def wrapped(*args, **kwargs):
            try:
                return f(*args, **kwargs)
            except exceptions:
                message = f'called {f} with *args={args} and **kwargs={kwargs}'
                if logger:
                    logger.exception(message)
                if logger is None:
                    logging.exception(message)
                return None

        return wrapped

    return fwrap

演示:

In [1] from fallible import fallible

In [2]: @fallible(ArithmeticError)
    ...: def div(a, b):
    ...:     return a / b
    ...: 
    ...: 

In [3]: div(1, 2)
Out[3]: 0.5

In [4]: res = div(1, 0)
ERROR:root:called <function div at 0x10d3c6ae8> with *args=(1, 0) and **kwargs={}
Traceback (most recent call last):
  File "/Users/user/fallible.py", line 17, in wrapped
    return f(*args, **kwargs)
  File "<ipython-input-17-e056bd886b5c>", line 3, in div
    return a / b

In [5]: repr(res)
'None'

您还可以修改这个解决方案,从except部分返回比None更有意义的内容(甚至可以通过在fallible的参数中指定这个返回值,使解决方案具有泛型)。

其他回答

这个答案是建立在上述优秀答案之上的。

在大多数应用程序中,您不会直接调用logging.exception(e)。很可能你已经为你的应用程序或模块定义了一个自定义记录器,如下所示:

# Set the name of the app or module
my_logger = logging.getLogger('NEM Sequencer')
# Set the log level
my_logger.setLevel(logging.INFO)

# Let's say we want to be fancy and log to a graylog2 log server
graylog_handler = graypy.GELFHandler('some_server_ip', 12201)
graylog_handler.setLevel(logging.INFO)
my_logger.addHandler(graylog_handler)

在这种情况下,只需使用记录器调用异常(e),如下所示:

try:
    1/0
except ZeroDivisionError, e:
    my_logger.exception(e)

记录器。异常将在错误消息旁边输出堆栈跟踪。

例如:

import logging
try:
    1/0
except ZeroDivisionError:
    logging.exception("message")

输出:

ERROR:root:message
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero

@Paulo支票笔记,“注意在python3中你必须调用日志记录。except部分中的异常方法。如果在任意位置调用此方法,可能会得到一个奇怪的异常。医生对此提出了警告。”

如果“调试信息”意味着异常引发时的值,那么logging.exception(…)将不起作用。因此,您需要一个工具来自动记录所有变量值和回溯行。

在盒子外面你会得到log

2020-03-30 18:24:31 main ERROR   File "./temp.py", line 13, in get_ratio
2020-03-30 18:24:31 main ERROR     return height / width
2020-03-30 18:24:31 main ERROR       height = 300
2020-03-30 18:24:31 main ERROR       width = 0
2020-03-30 18:24:31 main ERROR builtins.ZeroDivisionError: division by zero

看看一些pypi工具,我命名为:

tbvaccine traceback-with-variables better-exceptions

其中一些会给你很严重的崩溃信息:

但你可能会在pypi上找到更多

您可以记录堆栈跟踪而不出现异常。

https://docs.python.org/3/library/logging.html#logging.Logger.debug

The second optional keyword argument is stack_info, which defaults to False. If true, stack information is added to the logging message, including the actual logging call. Note that this is not the same stack information as that displayed through specifying exc_info: The former is stack frames from the bottom of the stack up to the logging call in the current thread, whereas the latter is information about stack frames which have been unwound, following an exception, while searching for exception handlers.

例子:

>>> import logging
>>> logging.basicConfig(level=logging.DEBUG)
>>> logging.getLogger().info('This prints the stack', stack_info=True)
INFO:root:This prints the stack
Stack (most recent call last):
  File "<stdin>", line 1, in <module>
>>>

如果你可以处理额外的依赖,那么使用twisted.log,你不必显式地记录错误,而且它还会返回整个回溯和时间到文件或流。