如果您试图终止整个程序，您可以将线程设置为“守护进程”。看到 Thread.daemon

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。

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.

假设，你想有多个线程的同一个函数，这是IMHO最简单的实现通过id停止一个:

import time
from threading import Thread

def doit(id=0):
    doit.stop=0
    print("start id:%d"%id)
    while 1:
        time.sleep(1)
        print(".")
        if doit.stop==id:
            doit.stop=0
            break
    print("end thread %d"%id)

t5=Thread(target=doit, args=(5,))
t6=Thread(target=doit, args=(6,))

t5.start() ; t6.start()
time.sleep(2)
doit.stop =5  #kill t5
time.sleep(2)
doit.stop =6  #kill t6

这里的好处是，你可以有多个相同或不同的函数，并通过functionname。stop来停止它们

如果你想只有一个线程的函数，那么你不需要记住id。如果做了，就停下来。停止> 0。

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%。

我想补充的一件事是，如果你阅读threading lib Python的官方文档，建议避免使用“恶魔”线程，当你不希望线程突然结束时，带有Paolo Rovelli提到的标志。

来自官方文件:

守护进程线程在关机时突然停止。它们的资源(如打开的文件、数据库事务等)可能无法正确释放。如果您希望线程优雅地停止，请将它们设置为非守护进程，并使用适当的信号机制(如Event)。

我认为创建守护线程取决于您的应用程序，但通常(在我看来)最好避免杀死它们或使它们成为守护线程。在多处理中，您可以使用is_alive()来检查进程状态，并使用“terminate”来完成它们(也可以避免GIL问题)。但有时，当你在Windows中执行代码时，你会发现更多的问题。

并且永远记住，如果你有“活动线程”，Python解释器将运行等待它们。(因为这个守护程序可以帮助你如果不重要的事情突然结束)。