Python多进程并发(multiprocessing)

<p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;">由于Python设计的限制(我说的是咱们常用的CPython)。最多只能用满1个CPU核心。</p><p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;">Python提供了非常好用的多进程包multiprocessing，你只需要定义一个函数，Python会替你完成其他所有事情。借助这个包，可以轻松完成从单进程到并发执行的转换。</p><p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;"><span style="word-wrap: break-word; margin: 0px; padding: 0px; border: 0px; vertical-align: baseline;">2、使用进程池</span></p><p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;">是的，你没有看错，不是线程池。它可以让你跑满多核CPU，而且使用方法非常简单。</p><p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;">注意要用apply_async，如果落下async，就变成阻塞版本了。</p><p style="word-wrap: break-word; margin-top: 0px; margin-bottom: 1.71429rem; padding-top: 0px; padding-bottom: 0px; font-size: 14px; border: 0px; vertical-align: baseline; color: rgb(68, 68, 68); font-family: Helvetica, Arial, sans-serif;">processes=4是最多并发进程数量。</p>

import multiprocessingimport timedef example_case(messges):for x in range(3):print(messges)time.sleep(1)return "done " + messgesif __name__ == "__main__":multiprocessing.freeze_support()pool = multiprocessing.Pool(processes=4)result = []for i in range(5):msg = "hello %d" % iresult.append(pool.apply_async(example_case, (msg,)))print("begin")pool.close()pool.join()for res in result:print(res.get())print("Sub-process(es) done.")