虽然它相当古老，但对一些人来说这可能是一个方便的解决方案:

一个扩展线程模块功能的小模块—— 允许一个线程在另一个线程的上下文中引发异常 线程。通过触发SystemExit，你最终可以杀死python线程。

import threading
import ctypes     

def _async_raise(tid, excobj):
    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(excobj))
    if res == 0:
        raise ValueError("nonexistent 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(tid, 0)
        raise SystemError("PyThreadState_SetAsyncExc failed")

class Thread(threading.Thread):
    def raise_exc(self, excobj):
        assert self.isAlive(), "thread must be started"
        for tid, tobj in threading._active.items():
            if tobj is self:
                _async_raise(tid, excobj)
                return

        # the thread was alive when we entered the loop, but was not found 
        # in the dict, hence it must have been already terminated. should we raise
        # an exception here? silently ignore?

    def terminate(self):
        # must raise the SystemExit type, instead of a SystemExit() instance
        # due to a bug in PyThreadState_SetAsyncExc
        self.raise_exc(SystemExit)

因此，它允许“线程在另一个线程的上下文中引发异常”，通过这种方式，被终止的线程可以处理终止，而无需定期检查中止标志。

然而，根据其原始来源，这段代码有一些问题。

The exception will be raised only when executing python bytecode. If your thread calls a native/built-in blocking function, the exception will be raised only when execution returns to the python code. There is also an issue if the built-in function internally calls PyErr_Clear(), which would effectively cancel your pending exception. You can try to raise it again. Only exception types can be raised safely. Exception instances are likely to cause unexpected behavior, and are thus restricted. For example: t1.raise_exc(TypeError) and not t1.raise_exc(TypeError("blah")). IMHO it's a bug, and I reported it as one. For more info, http://mail.python.org/pipermail/python-dev/2006-August/068158.html I asked to expose this function in the built-in thread module, but since ctypes has become a standard library (as of 2.5), and this feature is not likely to be implementation-agnostic, it may be kept unexposed.

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]

多处理。进程可以p.terminate()

如果我想杀死一个线程，但不想使用标志/锁/信号/信号量/事件/任何东西，我就把线程提升到完整的进程。对于只使用几个线程的代码，开销并没有那么糟糕。

例如，这可以方便地终止执行阻塞I/O的助手“线程”

转换很简单:在相关代码中替换所有线程。多线程线程。进程和所有队列。多处理队列。排队并将p.t terminate()所需的调用添加到想要杀死子进程p的父进程中

关于多处理，请参阅Python文档。

例子:

import multiprocessing
proc = multiprocessing.Process(target=your_proc_function, args=())
proc.start()
# Terminate the process
proc.terminate()  # sends a SIGTERM

另一种方法是使用signal.pthread_kill发送一个停止信号。

from signal import pthread_kill, SIGTSTP
from threading import Thread
from itertools import count
from time import sleep

def target():
    for num in count():
        print(num)
        sleep(1)

thread = Thread(target=target)
thread.start()
sleep(5)
pthread_kill(thread.ident, SIGTSTP)

结果

0
1
2
3
4

[14]+  Stopped

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。

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%。