实现一个线程是绝对可能的。方法，如下例代码所示:

import sys
import threading
import time


class StopThread(StopIteration):
    pass

threading.SystemExit = SystemExit, StopThread


class Thread2(threading.Thread):

    def stop(self):
        self.__stop = True

    def _bootstrap(self):
        if threading._trace_hook is not None:
            raise ValueError('Cannot run thread with tracing!')
        self.__stop = False
        sys.settrace(self.__trace)
        super()._bootstrap()

    def __trace(self, frame, event, arg):
        if self.__stop:
            raise StopThread()
        return self.__trace


class Thread3(threading.Thread):

    def _bootstrap(self, stop_thread=False):
        def stop():
            nonlocal stop_thread
            stop_thread = True
        self.stop = stop

        def tracer(*_):
            if stop_thread:
                raise StopThread()
            return tracer
        sys.settrace(tracer)
        super()._bootstrap()

###############################################################################


def main():
    test1 = Thread2(target=printer)
    test1.start()
    time.sleep(1)
    test1.stop()
    test1.join()
    test2 = Thread2(target=speed_test)
    test2.start()
    time.sleep(1)
    test2.stop()
    test2.join()
    test3 = Thread3(target=speed_test)
    test3.start()
    time.sleep(1)
    test3.stop()
    test3.join()


def printer():
    while True:
        print(time.time() % 1)
        time.sleep(0.1)


def speed_test(count=0):
    try:
        while True:
            count += 1
    except StopThread:
        print('Count =', count)

if __name__ == '__main__':
    main()

Thread3类运行代码的速度似乎比Thread2类快大约33%。

我对这个游戏已经很晚了，但我一直在与一个类似的问题作斗争，下面的内容似乎为我完美地解决了这个问题，并且让我在守护子线程退出时做一些基本的线程状态检查和清理:

import threading
import time
import atexit

def do_work():

  i = 0
  @atexit.register
  def goodbye():
    print ("'CLEANLY' kill sub-thread with value: %s [THREAD: %s]" %
           (i, threading.currentThread().ident))

  while True:
    print i
    i += 1
    time.sleep(1)

t = threading.Thread(target=do_work)
t.daemon = True
t.start()

def after_timeout():
  print "KILL MAIN THREAD: %s" % threading.currentThread().ident
  raise SystemExit

threading.Timer(2, after_timeout).start()

收益率:

0
1
KILL MAIN THREAD: 140013208254208
'CLEANLY' kill sub-thread with value: 2 [THREAD: 140013674317568]

实现一个线程是绝对可能的。方法，如下例代码所示:

import sys
import threading
import time


class StopThread(StopIteration):
    pass

threading.SystemExit = SystemExit, StopThread


class Thread2(threading.Thread):

    def stop(self):
        self.__stop = True

    def _bootstrap(self):
        if threading._trace_hook is not None:
            raise ValueError('Cannot run thread with tracing!')
        self.__stop = False
        sys.settrace(self.__trace)
        super()._bootstrap()

    def __trace(self, frame, event, arg):
        if self.__stop:
            raise StopThread()
        return self.__trace


class Thread3(threading.Thread):

    def _bootstrap(self, stop_thread=False):
        def stop():
            nonlocal stop_thread
            stop_thread = True
        self.stop = stop

        def tracer(*_):
            if stop_thread:
                raise StopThread()
            return tracer
        sys.settrace(tracer)
        super()._bootstrap()

###############################################################################


def main():
    test1 = Thread2(target=printer)
    test1.start()
    time.sleep(1)
    test1.stop()
    test1.join()
    test2 = Thread2(target=speed_test)
    test2.start()
    time.sleep(1)
    test2.stop()
    test2.join()
    test3 = Thread3(target=speed_test)
    test3.start()
    time.sleep(1)
    test3.stop()
    test3.join()


def printer():
    while True:
        print(time.time() % 1)
        time.sleep(0.1)


def speed_test(count=0):
    try:
        while True:
            count += 1
    except StopThread:
        print('Count =', count)

if __name__ == '__main__':
    main()

Thread3类运行代码的速度似乎比Thread2类快大约33%。

你不应该在没有与线程合作的情况下强行终止线程。

杀死一个线程消除了try/finally阻塞设置的任何保证，所以你可能会让锁锁定，文件打开等等。

唯一可以认为强制终止线程是一个好主意的情况是快速终止程序，但绝不是单个线程。

在Python和任何语言中，突然终止线程通常都是一种糟糕的模式。考虑以下情况:

线程持有一个必须正确关闭的关键资源 线程创建了其他几个线程，这些线程也必须被杀死。

如果你能负担得起(如果你在管理自己的线程)，处理这个问题的好方法是有一个exit_request标志，每个线程都会定期检查它，看看它是否到了退出的时候。

例如:

import threading

class StoppableThread(threading.Thread):
    """Thread class with a stop() method. The thread itself has to check
    regularly for the stopped() condition."""

    def __init__(self,  *args, **kwargs):
        super(StoppableThread, self).__init__(*args, **kwargs)
        self._stop_event = threading.Event()

    def stop(self):
        self._stop_event.set()

    def stopped(self):
        return self._stop_event.is_set()

在这段代码中，当您希望线程退出时，应该在线程上调用stop()，并使用join()等待线程正确退出。线程应该定期检查停止标志。

然而，在某些情况下，您确实需要终止一个线程。例如，当您正在包装一个外部库时，该库正忙于长时间的调用，并且您希望中断它。

下面的代码允许(有一些限制)在Python线程中引发异常:

def _async_raise(tid, exctype):
    '''Raises an exception in the threads with id tid'''
    if not inspect.isclass(exctype):
        raise TypeError("Only types can be raised (not instances)")
    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(tid),
                                                     ctypes.py_object(exctype))
    if res == 0:
        raise ValueError("invalid thread id")
    elif res != 1:
        # "if it returns a number greater than one, you're in trouble,
        # and you should call it again with exc=NULL to revert the effect"
        ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(tid), None)
        raise SystemError("PyThreadState_SetAsyncExc failed")

class ThreadWithExc(threading.Thread):
    '''A thread class that supports raising an exception in the thread from
       another thread.
    '''
    def _get_my_tid(self):
        """determines this (self's) thread id

        CAREFUL: this function is executed in the context of the caller
        thread, to get the identity of the thread represented by this
        instance.
        """
        if not self.isAlive():
            raise threading.ThreadError("the thread is not active")

        # do we have it cached?
        if hasattr(self, "_thread_id"):
            return self._thread_id

        # no, look for it in the _active dict
        for tid, tobj in threading._active.items():
            if tobj is self:
                self._thread_id = tid
                return tid

        # TODO: in python 2.6, there's a simpler way to do: self.ident

        raise AssertionError("could not determine the thread's id")

    def raiseExc(self, exctype):
        """Raises the given exception type in the context of this thread.

        If the thread is busy in a system call (time.sleep(),
        socket.accept(), ...), the exception is simply ignored.

        If you are sure that your exception should terminate the thread,
        one way to ensure that it works is:

            t = ThreadWithExc( ... )
            ...
            t.raiseExc( SomeException )
            while t.isAlive():
                time.sleep( 0.1 )
                t.raiseExc( SomeException )

        If the exception is to be caught by the thread, you need a way to
        check that your thread has caught it.

        CAREFUL: this function is executed in the context of the
        caller thread, to raise an exception in the context of the
        thread represented by this instance.
        """
        _async_raise( self._get_my_tid(), exctype )

(根据Tomer Filiba的《Killable Threads》改编。关于PyThreadState_SetAsyncExc返回值的引用似乎来自旧版本的Python。)

正如文档中所指出的，这不是一个神奇的子弹，因为如果线程在Python解释器之外忙，它将不会捕获中断。

这段代码的一个良好使用模式是让线程捕获特定的异常并执行清理。这样，您可以中断任务，但仍然可以进行适当的清理。

如果您确实需要终止子任务的能力，请使用另一种实现。Multiprocessing和gevent都支持不加选择地杀死一个“线程”。

Python的线程不支持取消。不要尝试。你的代码很可能死锁、损坏或泄漏内存，或者有其他意想不到的“有趣的”难以调试的效果，这种情况很少发生，而且不确定。