多处理超时？

Question

我搜索了 StackOverflow，虽然我发现了很多关于此的问题，但我还没有找到适合我情况的答案/不是一个强大的 Python 程序员来调整他们的答案以满足我的需要。

我看这里无济于事：

kill a function after a certain time in windows

Python: kill or terminate subprocess when timeout

signal.alarm replacement in Windows [Python]

我正在使用多处理同时运行多个 SAP 窗口以提取报告。设置为按计划每 5 分钟运行一次。每隔一段时间，其中一个报告就会由于 GUI 界面而停滞不前，而且永远不会结束。我没有收到错误或异常，它只是永远停止。我想要的是有一个超时功能，在这部分在 SAP 中执行的代码期间，如果它需要超过 4 分钟，它会超时，关闭 SAP，跳过其余代码，并等待下一个计划报告时间。

我使用的是 Windows Python 2.7

import multiprocessing
from multiprocessing import Manager, Process
import time
import datetime

### OPEN SAP ###
def start_SAP():
   print 'opening SAP program'

### REPORTS IN SAP ###
def report_1(q, lock):
   while True:  # logic to get shared queue
       if not q.empty():
           lock.acquire()
           k = q.get()
           time.sleep(1)
           lock.release()
           break
       else:
           time.sleep(1)
   print 'running report 1'

def report_2(q, lock):
   while True:  # logic to get shared queue
       if not q.empty():
           lock.acquire()
           k = q.get()
           time.sleep(1)
           lock.release()
           break
       else:
           time.sleep(1)
   print 'running report 2'

def report_3(q, lock):
   while True:  # logic to get shared queue
       if not q.empty():
           lock.acquire()
           k = q.get()
           time.sleep(1)
           lock.release()
           break
       else:
           time.sleep(1)

   time.sleep(60000) #mimicking the stall for report 3 that takes longer than allotted time
   print 'running report 3'

def report_N(q, lock):
   while True:  # logic to get shared queue
       if not q.empty():
           lock.acquire()
           k = q.get()
           time.sleep(1)
           lock.release()
           break
       else:
           time.sleep(1)
   print 'running report N'

### CLOSES SAP ###
def close_SAP():
   print 'closes SAP'

def format_file():
   print 'formatting files'

def multi_daily_pull():

    lock = multiprocessing.Lock()  # creating a lock in multiprocessing

    shared_list = range(6)  # creating a shared list for all functions to use
    q = multiprocessing.Queue()  # creating an empty queue in mulitprocessing
    for n in shared_list:  # putting list into the queue
        q.put(n)
    print 'Starting process at ', time.strftime('%m/%d/%Y %H:%M:%S')

    print 'Starting SAP Pulls at ', time.strftime('%m/%d/%Y %H:%M:%S')

    StartSAP = Process(target=start_SAP)
    StartSAP.start()
    StartSAP.join()

    report1= Process(target=report_1, args=(q, lock))
    report2= Process(target=report_2, args=(q, lock))
    report3= Process(target=report_3, args=(q, lock))
    reportN= Process(target=report_N, args=(q, lock))

    report1.start()
    report2.start()
    report3.start()
    reportN.start()

    report1.join()
    report2.join()
    report3.join()
    reportN.join()

    EndSAP = Process(target=close_SAP)
    EndSAP.start()
    EndSAP.join()

    formatfile = Process(target=format_file)
    formatfile .start()
    formatfile .join()

if __name__ == '__main__':
    multi_daily_pull()

Answer 1

一种方法是使用Process.join() 方法接受的可选超时参数。这将使它最多只阻塞调用线程。

我还设置了每个 Process 实例的 daemon 属性，这样即使它启动的某个进程仍在“运行”（或已挂起），您的主线程也能够终止。

最后一点，您不需要multiprocessing.Lock 来控制对multiprocessing.Queue 的访问，因为它们会自动处理这方面的事情，所以我将其删除。出于其他原因，您可能仍然想要一个，例如控制对 stdout 的访问，以便从各种进程打印到它不会重叠并弄乱输出到屏幕的内容。

import multiprocessing
from multiprocessing import Process
import time
import datetime

def start_SAP():
    print 'opening SAP program'

### REPORTS IN SAP ###
def report_1(q):
    while True:  # logic to get shared queue
        if q.empty():
            time.sleep(1)
        else:
            k = q.get()
            time.sleep(1)
            break

    print 'report 1 finished'

def report_2(q):
    while True:  # logic to get shared queue
        if q.empty():
            time.sleep(1)
        else:
            k = q.get()
            time.sleep(1)
            break

    print 'report 2 finished'

def report_3(q):
    while True:  # logic to get shared queue
        if q.empty():
            time.sleep(1)
        else:
            k = q.get()
            time.sleep(60000) # Take longer than allotted time
            break

    print 'report 3 finished'


def report_N(q):
    while True:  # logic to get shared queue
        if q.empty():
            time.sleep(1)
        else:
            k = q.get()
            time.sleep(1)
            break

    print 'report N finished'

def close_SAP():
    print 'closing SAP'

def format_file():
    print 'formatting files'

def multi_daily_pull():
    shared_list = range(6)  # creating a shared list for all functions to use
    q = multiprocessing.Queue()  # creating an empty queue in mulitprocessing
    for n in shared_list:  # putting list into the queue
        q.put(n)
    print 'Starting process at ', time.strftime('%m/%d/%Y %H:%M:%S')

    print 'Starting SAP Pulls at ', time.strftime('%m/%d/%Y %H:%M:%S')

    StartSAP = Process(target=start_SAP)
    StartSAP.start()
    StartSAP.join()

    report1 = Process(target=report_1, args=(q,))
    report1.daemon = True
    report2 = Process(target=report_2, args=(q,))
    report2.daemon = True
    report3 = Process(target=report_3, args=(q,))
    report3.daemon = True
    reportN = Process(target=report_N, args=(q,))
    reportN.daemon = True

    report1.start()
    report2.start()
    report3.start()
    reportN.start()

    report1.join(30)
    report2.join(30)
    report3.join(30)
    reportN.join(30)

    EndSAP = Process(target=close_SAP)
    EndSAP.start()
    EndSAP.join()

    formatfile = Process(target=format_file)
    formatfile .start()
    formatfile .join()

if __name__ == '__main__':
    multi_daily_pull()