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!

引用

如果您的应用程序以其他方式记录日志-不使用日志模块?

现在，traceback可以用在这里。

import traceback

def log_traceback(ex, ex_traceback=None):
    if ex_traceback is None:
        ex_traceback = ex.__traceback__
    tb_lines = [ line.rstrip('\n') for line in
                 traceback.format_exception(ex.__class__, ex, ex_traceback)]
    exception_logger.log(tb_lines)

在Python 2中使用它: 试一试: #你的函数调用在这里 Exception as ex: _， _， ex_traceback = sys.exc_info() ex_traceback log_traceback(例) 在Python 3中使用它: 试一试: X = get_number() Exception as ex: log_traceback(特异)

使用exc_info选项可能更好，允许你选择错误级别(如果你使用exception，它将总是在错误级别):

try:
    # do something here
except Exception as e:
    logging.critical(e, exc_info=True)  # log exception info at CRITICAL log level

我把所有的函数都包在我的自定义设计的日志记录器周围:

import json
import timeit
import traceback
import sys
import unidecode

def main_writer(f,argument):
  try:
    f.write(str(argument))
  except UnicodeEncodeError:
    f.write(unidecode.unidecode(argument))


def logger(*argv,logfile="log.txt",singleLine = False):
  """
  Writes Logs to LogFile
  """
  with open(logfile, 'a+') as f:
    for arg in argv:
      if arg == "{}":
        continue
      if type(arg) == dict and len(arg)!=0:
        json_object = json.dumps(arg, indent=4, default=str)
        f.write(str(json_object))
        f.flush()
        """
        for key,val in arg.items():
          f.write(str(key) + " : "+ str(val))
          f.flush()
        """
      elif type(arg) == list and len(arg)!=0:
        for each in arg:
          main_writer(f,each)
          f.write("\n")
          f.flush()
      else:
        main_writer(f,arg)
        f.flush()
      if singleLine==False:
        f.write("\n")
    if singleLine==True:
      f.write("\n")

def tryFunc(func, func_name=None, *args, **kwargs):
  """
  Time for Successfull Runs
  Exception Traceback for Unsuccessful Runs
  """
  stack = traceback.extract_stack()
  filename, codeline, funcName, text = stack[-2]
  func_name = func.__name__ if func_name is None else func_name # sys._getframe().f_code.co_name # func.__name__
  start = timeit.default_timer()
  x = None
  try:
    x = func(*args, **kwargs)
    stop = timeit.default_timer()
    # logger("Time to Run {} : {}".format(func_name, stop - start))
  except Exception as e:
    logger("Exception Occurred for {} :".format(func_name))
    logger("Basic Error Info :",e)
    logger("Full Error TraceBack :")
    # logger(e.message, e.args)
    logger(traceback.format_exc())
  return x

def bad_func():
  return 'a'+ 7

if __name__ == '__main__':
    logger(234)
    logger([1,2,3])
    logger(['a','b','c'])
    logger({'a':7,'b':8,'c':9})
    tryFunc(bad_func)

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)

日志记录有一个好处。SiggyF的答案没有显示的异常是，你可以传递一个任意的消息，日志仍然会显示所有异常细节的完整跟踪:

import logging
try:
    1/0
except ZeroDivisionError:
    logging.exception("Deliberate divide by zero traceback")

默认情况下(在最近的版本中)只是将错误打印到sys. log行为。Stderr，它看起来像这样:

>>> import logging
>>> try:
...     1/0
... except ZeroDivisionError:
...     logging.exception("Deliberate divide by zero traceback")
... 
ERROR:root:Deliberate divide by zero traceback
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
ZeroDivisionError: integer division or modulo by zero