Python获取多进程执行的返回值实现

import multiprocessing
from multiprocessing import Pool


info_manager = multiprocessing.Manager()
info_lock = info_manager.Lock()
info_dict = info_manager.dict()


def add(n):
    global info_dict, info_lock 
    
    s = 0
    for i in range(n+1):
        s += i
    
    info_lock.acquire()
    info_dict[n] = s
    info_lock.release()
    
    print("In task %d: %d -> %d" % (n, n, s))


def calculate():
    pool = Pool(processes=4) 

    tasks = range(10)
    for n in tasks:
        pool.apply_async(add, (n,))
        
    pool.close()
    pool.join()
    
    
def print_result():
    global info_dict
    
    key_list = sorted(info_dict.keys())
    
    for key in key_list:
        print("%s: %s" % (key, info_dict[key])) 
    
    
if __name__ == '__main__':
    calculate()
    print_result()

import multiprocessing
from multiprocessing import Pool

def add(n):
    s = 0
    for i in range(n+1):
        s += i
    return (n, s)


def calculate():
    pool = Pool(processes=4)

    tasks = range(10)
    result_list = list()
    info_dict = dict()
    
    for n in tasks:
        result_list.append(pool.apply_async(add, (n,)))
        
    pool.close()
    pool.join()
    
    for result in result_list:
        k, v = result.get()
        info_dict[k] = v
        
    return info_dict
    
    
def print_result():
    info_dict = calculate()
    
    key_list = sorted(info_dict.keys())
    
    for key in key_list:
        print("%s: %s" % (key, info_dict[key])) 
    
    
if __name__ == '__main__':
    calculate()
    print_result()

get([timeout])
    Return the result when it arrives. 
    If timeout is not None and the result does not arrive within timeout seconds 
    then multiprocessing.TimeoutError is raised. 
    If the remote call raised an exception then that exception will be reraised by get().