在python 2.7中並行運行函數以在其他函數的末尾使用函數的輸出

Question

我是 python 的新手，從未使用過它的並行處理模塊，如threading或multiprocess 。 我正在處理一個實時代碼問題，其中一個函數的輸出用作一個函數的輸入。 有一個大功能需要將近 3 秒才能完成。 這就像一個程序，一個人向接待處提交一些文件，當他的文件被驗證時，他被引導到其他地方進行不同的檢查。 如果在這些檢查結束時文件驗證的結果可用，則程序將失敗。

def parallel_running_function(*args):
     """It is the function which will take 3 seconds to complete"""
     output = "various documents matching and verification"
     return output

def check_1(*args):
    """ check one for the task"""

def check_2(*args):
    """ check two for the task"""

def check_3(*args):
    """ check three for the task"""

def check_4(*args):
    """ check 4 for the task"""


def main_function():

    output = parallel_running_function() # need to run this function 
                                        #parallel with other functions
    output_1 = check_1()
    output_2 = check_2()
    output_3 = check_3()
    output_4 = check_4()
    if output:
       "program is successful"
    else:
        "program is failed"

    I need the output of parallel running function is here along with the other executed functions. If I don't get the output of that function here then program will be failed or ll give some wrong result.

我正在使用 python 2.7。 我已經using threading python 的using threading 、 subprocess和multiprocessing模塊閱讀了多篇關於這個問題的帖子，但我無法得到這個問題的具體解決方案。 我從其他帖子中得到的似乎是我需要使用multiprocessing模塊。 有人可以告訴我我應該如何克服這個問題。

Answer 1

你可以這樣做：

import multiprocessing

pool = None

def parallel_running_function(*args):
     """It is the function which will take 3 seconds to complete"""
     output = "various documents matching and verification"
     return output

def check_1(*args):
    """ check one for the task"""

def check_2(*args):
    """ check two for the task"""

def check_3(*args):
    """ check three for the task"""

def check_4(*args):
    """ check 4 for the task"""


def main_function():

    res = pool.apply_async(parallel_running_function)

    res_1 = pool.apply_async(check_1)
    res_2 = pool.apply_async(check_2)
    res_3 = pool.apply_async(check_3)
    res_4 = pool.apply_async(check_4)

    output = res.get()
    output_1 = res_1.get()
    output_2 = res_2.get()
    output_3 = res_3.get()
    output_4 = res_4.get()

    if output:
       print "program is successful"
    else:
        print "program is failed"


if __name__ == '__main__':
    pool = multiprocessing.Pool(processes=4)
    main_function()

調用 get 時主進程將阻塞，但其他進程仍將運行。