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>
>>>

如果你看一下这个代码示例(适用于Python 2和3)，你会看到下面可以提取的函数定义

方法 行号 代码的上下文 文件路径

对于整个堆栈跟踪，无论是否有异常:

def sentry_friendly_trace(get_last_exception=True):
    try:
        current_call = list(map(frame_trans, traceback.extract_stack()))
        alert_frame = current_call[-4]
        before_call = current_call[:-4]

        err_type, err, tb = sys.exc_info() if get_last_exception else (None, None, None)
        after_call = [alert_frame] if err_type is None else extract_all_sentry_frames_from_exception(tb)

        return before_call + after_call, err, alert_frame
    except:
        return None, None, None

当然，这个函数依赖于上面链接的整个要点，特别是extract_all_sentry_frames_from_exception()和frame_trans()，但是异常信息提取总共不到60行。

希望有帮助!

在日志模块(如果是自定义模块)中启用stack_info。

api_logger.exceptionLog("*Input your Custom error message*",stack_info=True)

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>
>>>

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)。

如果您使用普通日志—所有日志记录都应该符合这条规则:一条记录=一行。遵循这条规则，您可以使用grep和其他工具来处理日志文件。

但是回溯信息是多行的。所以我的答案是zangw在这篇文章中提出的解决方案的扩展版本。问题是回溯行内部可能有\n，所以我们需要做额外的工作来消除这些行结束符:

import logging


logger = logging.getLogger('your_logger_here')

def log_app_error(e: BaseException, level=logging.ERROR) -> None:
    e_traceback = traceback.format_exception(e.__class__, e, e.__traceback__)
    traceback_lines = []
    for line in [line.rstrip('\n') for line in e_traceback]:
        traceback_lines.extend(line.splitlines())
    logger.log(level, traceback_lines.__str__())

在这之后(当你分析你的日志时)，你可以从你的日志文件中复制/粘贴所需的回溯行，并这样做:

ex_traceback = ['line 1', 'line 2', ...]
for line in ex_traceback:
    print(line)

利润!