并发。Futures模块使得在单独的线程(或进程)中工作并处理任何由此产生的异常变得简单:

import concurrent.futures
import shutil

def copytree_with_dots(src_path, dst_path):
    with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
        # Execute the copy on a separate thread,
        # creating a future object to track progress.
        future = executor.submit(shutil.copytree, src_path, dst_path)

        while future.running():
            # Print pretty dots here.
            pass

        # Return the value returned by shutil.copytree(), None.
        # Raise any exceptions raised during the copy process.
        return future.result()

并发。futures包含在Python 3.2中，并可作为早期版本的反向移植futures模块使用。

类似于RickardSjogren的方法，没有Queue, sys等，但也没有一些信号监听器:直接执行一个异常处理程序，对应于一个异常块。

#!/usr/bin/env python3

import threading

class ExceptionThread(threading.Thread):

    def __init__(self, callback=None, *args, **kwargs):
        """
        Redirect exceptions of thread to an exception handler.

        :param callback: function to handle occured exception
        :type callback: function(thread, exception)
        :param args: arguments for threading.Thread()
        :type args: tuple
        :param kwargs: keyword arguments for threading.Thread()
        :type kwargs: dict
        """
        self._callback = callback
        super().__init__(*args, **kwargs)

    def run(self):
        try:
            if self._target:
                self._target(*self._args, **self._kwargs)
        except BaseException as e:
            if self._callback is None:
                raise e
            else:
                self._callback(self, e)
        finally:
            # Avoid a refcycle if the thread is running a function with
            # an argument that has a member that points to the thread.
            del self._target, self._args, self._kwargs, self._callback

只有自我。_callback和run()中的except块是普通threading.Thread之外的。

我认为其他的解决方案有点复杂，如果你唯一想要的是真正看到某个异常，而不是完全无视和盲目。

解决方案是创建一个自定义线程，从主线程获取记录器并记录任何异常。

class ThreadWithLoggedException(threading.Thread):
    """
    Similar to Thread but will log exceptions to passed logger.

    Args:
        logger: Logger instance used to log any exception in child thread

    Exception is also reachable via <thread>.exception from the main thread.
    """

    def __init__(self, *args, **kwargs):
        try:
            self.logger = kwargs.pop("logger")
        except KeyError:
            raise Exception("Missing 'logger' in kwargs")
        super().__init__(*args, **kwargs)
        self.exception = None

    def run(self):
        try:
            if self._target is not None:
                self._target(*self._args, **self._kwargs)
        except Exception as exception:
            thread = threading.current_thread()
            self.exception = exception
            self.logger.exception(f"Exception in child thread {thread}: {exception}")
        finally:
            del self._target, self._args, self._kwargs

例子:

logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
logger.addHandler(logging.StreamHandler())

def serve():
    raise Exception("Earth exploded.")

th = ThreadWithLoggedException(target=serve, logger=logger)
th.start()

主线程输出:

Exception in child thread <ThreadWithLoggedException(Thread-1, started 139922384414464)>: Earth exploded.
Traceback (most recent call last):
  File "/core/utils.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/myapp.py", line 105, in serve
    raise Exception("Earth exploded.")
Exception: Earth exploded.

使用裸例外并不是一个好的实践，因为您通常会获得比您讨价还价时更多的东西。

我建议修改except以只捕获您想要处理的异常。我不认为引发它有预期的效果，因为当你在外层try中实例化TheThread时，如果它引发一个异常，赋值永远不会发生。

相反，你可能只想提醒它，然后继续前进，比如:

def run(self):
    try:
       shul.copytree(self.sourceFolder, self.destFolder)
    except OSError, err:
       print err

然后，当异常被捕获时，您可以在那里处理它。然后，当外部try从TheThread捕获异常时，您知道它不是您已经处理过的异常，并将帮助您隔离流程流。

这是一个棘手的小问题，我想提出我的解决方案。我发现了一些其他的解决方案(异步。例如IO)看起来很有前途，但也呈现出一些黑盒子。队列/事件循环方法将您与某个实现联系在一起。然而，并发期货的源代码只有大约1000行，很容易理解。它让我很容易地解决了我的问题:创建临时的工作线程，而不需要太多的设置，并且能够在主线程中捕获异常。

我的解决方案使用并发期货API和线程API。它允许你创建一个worker，给你线程和未来。这样，你就可以加入线程来等待结果:

worker = Worker(test)
thread = worker.start()
thread.join()
print(worker.future.result())

.．.或者你可以让worker在完成时发送一个回调:

worker = Worker(test)
thread = worker.start(lambda x: print('callback', x))

.．.或者你可以循环直到事件完成:

worker = Worker(test)
thread = worker.start()

while True:
    print("waiting")
    if worker.future.done():
        exc = worker.future.exception()
        print('exception?', exc)
        result = worker.future.result()
        print('result', result)           
        break
    time.sleep(0.25)

代码如下:

from concurrent.futures import Future
import threading
import time

class Worker(object):
    def __init__(self, fn, args=()):
        self.future = Future()
        self._fn = fn
        self._args = args

    def start(self, cb=None):
        self._cb = cb
        self.future.set_running_or_notify_cancel()
        thread = threading.Thread(target=self.run, args=())
        thread.daemon = True #this will continue thread execution after the main thread runs out of code - you can still ctrl + c or kill the process
        thread.start()
        return thread

    def run(self):
        try:
            self.future.set_result(self._fn(*self._args))
        except BaseException as e:
            self.future.set_exception(e)

        if(self._cb):
            self._cb(self.future.result())

.．.和测试函数:

def test(*args):
    print('args are', args)
    time.sleep(2)
    raise Exception('foo')

问题是thread_obj.start()立即返回。您所生成的子线程在它自己的上下文中使用自己的堆栈执行。在那里发生的任何异常都在子线程的上下文中，并且在它自己的堆栈中。我现在能想到的一种将此信息传递给父线程的方法是使用某种消息传递，因此您可以研究一下。

试试这个尺寸:

import sys
import threading
import queue


class ExcThread(threading.Thread):

    def __init__(self, bucket):
        threading.Thread.__init__(self)
        self.bucket = bucket

    def run(self):
        try:
            raise Exception('An error occured here.')
        except Exception:
            self.bucket.put(sys.exc_info())


def main():
    bucket = queue.Queue()
    thread_obj = ExcThread(bucket)
    thread_obj.start()

    while True:
        try:
            exc = bucket.get(block=False)
        except queue.Empty:
            pass
        else:
            exc_type, exc_obj, exc_trace = exc
            # deal with the exception
            print exc_type, exc_obj
            print exc_trace

        thread_obj.join(0.1)
        if thread_obj.isAlive():
            continue
        else:
            break


if __name__ == '__main__':
    main()