我对这个问题的解决方案是将函数和线程包装在一个类中。不需要使用池、队列或c类型变量传递。它也是非阻塞的。而是检查状态。参见代码末尾如何使用它的示例。

import threading

class ThreadWorker():
    '''
    The basic idea is given a function create an object.
    The object can then run the function in a thread.
    It provides a wrapper to start it,check its status,and get data out the function.
    '''
    def __init__(self,func):
        self.thread = None
        self.data = None
        self.func = self.save_data(func)

    def save_data(self,func):
        '''modify function to save its returned data'''
        def new_func(*args, **kwargs):
            self.data=func(*args, **kwargs)

        return new_func

    def start(self,params):
        self.data = None
        if self.thread is not None:
            if self.thread.isAlive():
                return 'running' #could raise exception here

        #unless thread exists and is alive start or restart it
        self.thread = threading.Thread(target=self.func,args=params)
        self.thread.start()
        return 'started'

    def status(self):
        if self.thread is None:
            return 'not_started'
        else:
            if self.thread.isAlive():
                return 'running'
            else:
                return 'finished'

    def get_results(self):
        if self.thread is None:
            return 'not_started' #could return exception
        else:
            if self.thread.isAlive():
                return 'running'
            else:
                return self.data

def add(x,y):
    return x +y

add_worker = ThreadWorker(add)
print add_worker.start((1,2,))
print add_worker.status()
print add_worker.get_results()

这是我根据@Kindall的回答创建的版本。

这个版本使得您所要做的就是输入带有参数的命令来创建新线程。

这是用Python 3.8做的:

from threading import Thread
from typing import Any

def test(plug, plug2, plug3):
    print(f"hello {plug}")
    print(f'I am the second plug : {plug2}')
    print(plug3)
    return 'I am the return Value!'

def test2(msg):
    return f'I am from the second test: {msg}'

def test3():
    print('hello world')

def NewThread(com, Returning: bool, *arguments) -> Any:
    """
    Will create a new thread for a function/command.

    :param com: Command to be Executed
    :param arguments: Arguments to be sent to Command
    :param Returning: True/False Will this command need to return anything
    """
    class NewThreadWorker(Thread):
        def __init__(self, group = None, target = None, name = None, args = (), kwargs = None, *,
                     daemon = None):
            Thread.__init__(self, group, target, name, args, kwargs, daemon = daemon)
            
            self._return = None
        
        def run(self):
            if self._target is not None:
                self._return = self._target(*self._args, **self._kwargs)
        
        def join(self):
            Thread.join(self)
            return self._return
    
    ntw = NewThreadWorker(target = com, args = (*arguments,))
    ntw.start()
    if Returning:
        return ntw.join()

if __name__ == "__main__":
    print(NewThread(test, True, 'hi', 'test', test2('hi')))
    NewThread(test3, True)

一种常见的解决方案是用装饰器来包装函数foo

result = queue.Queue()

def task_wrapper(*args):
    result.put(target(*args))

那么整个代码可能是这样的

result = queue.Queue()

def task_wrapper(*args):
    result.put(target(*args))

threads = [threading.Thread(target=task_wrapper, args=args) for args in args_list]

for t in threads:
    t.start()
    while(True):
        if(len(threading.enumerate()) < max_num):
            break
for t in threads:
    t.join()
return result

Note

一个重要的问题是返回值可能是无序的。 (事实上，返回值不一定保存到队列中，因为您可以选择任意线程安全的数据结构)

如上所述，多处理池比基本线程要慢得多。使用一些回答中提出的队列是一种非常有效的替代方法。我已经将它与字典一起使用，以便能够运行许多小线程，并通过将它们与字典结合来恢复多个答案:

#!/usr/bin/env python3

import threading
# use Queue for python2
import queue
import random

LETTERS = 'abcdefghijklmnopqrstuvwxyz'
LETTERS = [ x for x in LETTERS ]

NUMBERS = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

def randoms(k, q):
    result = dict()
    result['letter'] = random.choice(LETTERS)
    result['number'] = random.choice(NUMBERS)
    q.put({k: result})

threads = list()
q = queue.Queue()
results = dict()

for name in ('alpha', 'oscar', 'yankee',):
    threads.append( threading.Thread(target=randoms, args=(name, q)) )
    threads[-1].start()
_ = [ t.join() for t in threads ]
while not q.empty():
    results.update(q.get())

print(results)

最好的方法…定义一个全局变量，然后在线程函数中更改该变量。没有可以传递或取回的东西

from threading import Thread

# global var
radom_global_var = 5

def function():
    global random_global_var
    random_global_var += 1

domath = Thread(target=function)
domath.start()
domath.join()
print(random_global_var)

# result: 6

使用队列:

import threading, queue

def calc_square(num, out_queue1):
  l = []
  for x in num:
    l.append(x*x)
  out_queue1.put(l)


arr = [1,2,3,4,5,6,7,8,9,10]
out_queue1=queue.Queue()
t1=threading.Thread(target=calc_square, args=(arr,out_queue1))
t1.start()
t1.join()
print (out_queue1.get())