我正在使用这个包装器，它可以轻松地将任何函数转换为在线程中运行-照顾它的返回值或异常。它不会增加队列开销。

def threading_func(f):
    """Decorator for running a function in a thread and handling its return
    value or exception"""
    def start(*args, **kw):
        def run():
            try:
                th.ret = f(*args, **kw)
            except:
                th.exc = sys.exc_info()
        def get(timeout=None):
            th.join(timeout)
            if th.exc:
                raise th.exc[0], th.exc[1], th.exc[2] # py2
                ##raise th.exc[1] #py3                
            return th.ret
        th = threading.Thread(None, run)
        th.exc = None
        th.get = get
        th.start()
        return th
    return start

用法示例

def f(x):
    return 2.5 * x
th = threading_func(f)(4)
print("still running?:", th.is_alive())
print("result:", th.get(timeout=1.0))

@threading_func
def th_mul(a, b):
    return a * b
th = th_mul("text", 2.5)

try:
    print(th.get())
except TypeError:
    print("exception thrown ok.")

线程模块注意事项

线程函数的舒适返回值和异常处理是“python”的常见需求，而且threading模块应该已经提供了——可能直接在标准Thread类中。对于简单的任务，ThreadPool有太多的开销——3个管理线程，很多官僚主义。不幸的是，线程的布局最初是从Java中复制的——例如，从仍然无用的构造函数参数组1 (!)

根据上面提到的，下面是适用于Python3的更通用的解决方案。

import threading

class ThreadWithReturnValue(threading.Thread):
    def __init__(self, *init_args, **init_kwargs):
        threading.Thread.__init__(self, *init_args, **init_kwargs)
        self._return = None
    def run(self):
        self._return = self._target(*self._args, **self._kwargs)
    def join(self):
        threading.Thread.join(self)
        return self._return

使用

        th = ThreadWithReturnValue(target=requests.get, args=('http://www.google.com',))
        th.start()
        response = th.join()
        response.status_code  # => 200

这是一个很老的问题，但我想分享一个简单的解决方案，它对我的开发过程有帮助。

这个答案背后的方法论是这样一个事实，即“新的”目标函数，内部是将原始函数的结果(通过__init__函数传递)通过所谓的闭包分配给包装器的结果实例属性。

这允许包装器类保留返回值以供调用者随时访问。

注意:这个方法不需要使用线程的任何mangded方法或私有方法。线程类，虽然没有考虑屈服函数(OP没有提到屈服函数)。

享受吧!

from threading import Thread as _Thread


class ThreadWrapper:
    def __init__(self, target, *args, **kwargs):
        self.result = None
        self._target = self._build_threaded_fn(target)
        self.thread = _Thread(
            target=self._target,
            *args,
            **kwargs
        )

    def _build_threaded_fn(self, func):
        def inner(*args, **kwargs):
            self.result = func(*args, **kwargs)
        return inner

此外，你可以用下面的代码运行pytest(假设你已经安装了它)来演示结果:

import time
from commons import ThreadWrapper


def test():

    def target():
        time.sleep(1)
        return 'Hello'

    wrapper = ThreadWrapper(target=target)
    wrapper.thread.start()

    r = wrapper.result
    assert r is None

    time.sleep(2)

    r = wrapper.result
    assert r == 'Hello'

FWIW，多处理模块使用Pool类提供了一个很好的接口。如果您希望坚持使用线程而不是进程，可以直接使用multiprocessing.pool.ThreadPool类作为替代。

def foo(bar, baz):
  print 'hello {0}'.format(bar)
  return 'foo' + baz

from multiprocessing.pool import ThreadPool
pool = ThreadPool(processes=1)

async_result = pool.apply_async(foo, ('world', 'foo')) # tuple of args for foo

# do some other stuff in the main process

return_val = async_result.get()  # get the return value from your function.

我偷了kindall的答案，稍微整理了一下。

关键部分是为join()添加*args和**kwargs，以便处理超时

class threadWithReturn(Thread):
    def __init__(self, *args, **kwargs):
        super(threadWithReturn, self).__init__(*args, **kwargs)
        
        self._return = None
    
    def run(self):
        if self._Thread__target is not None:
            self._return = self._Thread__target(*self._Thread__args, **self._Thread__kwargs)
    
    def join(self, *args, **kwargs):
        super(threadWithReturn, self).join(*args, **kwargs)
        
        return self._return

更新答案如下

这是我得到最多好评的答案，所以我决定更新可以在py2和py3上运行的代码。

此外，我看到许多对这个问题的回答都显示出对Thread.join()缺乏理解。有些完全不能处理timeout参数。但是当你有(1)一个可以返回None的目标函数并且(2)你也将timeout参数传递给join()时，还有一种极端情况你应该注意。请参阅“TEST 4”以理解这个极端情况。

ThreadWithReturn类，用于py2和py3:

import sys
from threading import Thread
from builtins import super    # https://stackoverflow.com/a/30159479

_thread_target_key, _thread_args_key, _thread_kwargs_key = (
    ('_target', '_args', '_kwargs')
    if sys.version_info >= (3, 0) else
    ('_Thread__target', '_Thread__args', '_Thread__kwargs')
)

class ThreadWithReturn(Thread):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self._return = None
    
    def run(self):
        target = getattr(self, _thread_target_key)
        if target is not None:
            self._return = target(
                *getattr(self, _thread_args_key),
                **getattr(self, _thread_kwargs_key)
            )
    
    def join(self, *args, **kwargs):
        super().join(*args, **kwargs)
        return self._return

一些示例测试如下所示:

import time, random

# TEST TARGET FUNCTION
def giveMe(arg, seconds=None):
    if not seconds is None:
        time.sleep(seconds)
    return arg

# TEST 1
my_thread = ThreadWithReturn(target=giveMe, args=('stringy',))
my_thread.start()
returned = my_thread.join()
# (returned == 'stringy')

# TEST 2
my_thread = ThreadWithReturn(target=giveMe, args=(None,))
my_thread.start()
returned = my_thread.join()
# (returned is None)

# TEST 3
my_thread = ThreadWithReturn(target=giveMe, args=('stringy',), kwargs={'seconds': 5})
my_thread.start()
returned = my_thread.join(timeout=2)
# (returned is None) # because join() timed out before giveMe() finished

# TEST 4
my_thread = ThreadWithReturn(target=giveMe, args=(None,), kwargs={'seconds': 5})
my_thread.start()
returned = my_thread.join(timeout=random.randint(1, 10))

你能确定我们在测试4中可能遇到的极端情况吗?

问题是我们期望giveMe()返回None(参见TEST 2)，但我们也期望join()在超时时返回None。

None表示:

(1)这就是giveMe()返回的，或者

(2) join()超时

这个例子很简单，因为我们知道giveMe()总是返回None。但在真实的实例中(目标可能返回None或其他内容)，我们希望显式地检查发生了什么。

下面是如何解决这种极端情况:

# TEST 4
my_thread = ThreadWithReturn(target=giveMe, args=(None,), kwargs={'seconds': 5})
my_thread.start()
returned = my_thread.join(timeout=random.randint(1, 10))

if my_thread.isAlive():
    # returned is None because join() timed out
    # this also means that giveMe() is still running in the background
    pass
    # handle this based on your app's logic
else:
    # join() is finished, and so is giveMe()
    # BUT we could also be in a race condition, so we need to update returned, just in case
    returned = my_thread.join()

我发现做到这一点的最短和最简单的方法是利用Python类及其动态属性。您可以使用threading.current_thread()从派生线程的上下文中检索当前线程，并将返回值赋给一个属性。

import threading

def some_target_function():
    # Your code here.
    threading.current_thread().return_value = "Some return value."

your_thread = threading.Thread(target=some_target_function)
your_thread.start()
your_thread.join()

return_value = your_thread.return_value
print(return_value)