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

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!

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)

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

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。