#!/usr/bin/python # -*- coding: UTF-8 -*- '''@auther :mr.qin @IDE:pycharm''' from tool.Common import * from tool.request_data_change_to_StrEncode import request_data_change_to_str from tool.tencent_cloud_mysql_connect import Mysql_operation import time import requests from multiprocessing import Process,Queue,Pool,Manager,Lock import os my_op = Mysql_operation() get_data = '''select order_id,order_sn from order_info limit 100;''' data = my_op.sql_operation(get_data) data_to_str = request_data_change_to_str() lock=Lock() def testDoWeChatNotify(q): fwh_order_dict = {} fwh_order_id_list, fwh_order_sn_list = [], [] if data!=(): for a in data: fwh_order_id=a['order_id'] fwh_order_sn=a['order_sn'] fwh_order_id_list.append(fwh_order_id) fwh_order_sn_list.append(fwh_order_sn) fwh_order_dict['fwh_order_id']=fwh_order_id_list fwh_order_dict['fwh_order_sn']=fwh_order_sn_list # print("put %s to queue...." % (fwh_order_dict)) q.put(fwh_order_dict) return q.qsize()#返回队列数量 def asynchronousPay_process(q,order_id,order_sn): if (data!=()): url_wechat_success_huidiao=fwh_test_api+'/index/Order/doWeChatNotify' data_wechat_success_huidiao=data_to_str.requestDataToStr_firefoxAndChrome_fwh('''order_sn:{} order_id:{} meth_id:4 timestamp:157129653969 sign:0687b01b300b9e300d3996a9d2173f1380973e5a'''.format(order_sn,order_id)) # print(data_wechat_success_huidiao) request_wechat_success_huidiao=requests.post(url=url_wechat_success_huidiao,headers=headers_form_urlencoded,data=data_wechat_success_huidiao) response_wechat_success_huidiao=request_wechat_success_huidiao.json() if '订单状态错误,非待支付订单' in response_wechat_success_huidiao['msg']: print(data_wechat_success_huidiao) # print(request_wechat_success_huidiao.json()) else: print('待支付订单为空') def run_multiprocess(): p = Pool(9) q = Manager().Queue() size = list(range(testDoWeChatNotify(q))) info = q.get() for i in range(len(info['fwh_order_id'])): lock.acquire()#加互斥锁 # print('当前进程{},父进程id{}'.format(os.getpid(),os.getppid())) p.apply_async(func=asynchronousPay_process, args=(q, info['fwh_order_id'][i], info['fwh_order_sn'][i])) lock.release()#解锁 p.close() p.join() if __name__=="__main__": start_time = time.time() # 计算程序开始时间 run_multiprocess() # q=Manager().Queue() # size = list(range(testDoWeChatNotify(q))) # info = q.get() # for i in range(len(info['fwh_order_id'])): # asynchronousPay_process(q,info['fwh_order_id'][i], info['fwh_order_sn'][i]) print('程序耗时{:.2f}'.format(time.time() - start_time)) # 计算程序总耗时思路:与多线程实现思路差不多,但是所用模块不同,多进程用multiprocessing模拟,多线程用therading模块多进程队列使用multiprocessing.Queue()或者multiprocessing.Manager().Queue(),多线程使用queue.Queue(),apply_async方法是apply方法的非阻塞式(异步)版本,Queue引入确实提高了执行速度,亲测:为使用多进程前支付100个订单用了四十多秒,使用之后用了5.x秒,这根电脑的性能会有一些关系!问题: 1.在调试的过程中我想用一个封装一个类来完成,但是调试了很久,都有问题(队列无法公用的问题),忘大佬指教; 2.线程启动的数量更多(进程启动了8个,线程启动了100个),为啥会没有多进程的执行速度快?(同时使用join的情况下),这里修正一下,多线程执行速度会快一些,因为代码跟运行速度不一致所以造成了这种错觉 3.会出现重复请求的请求,但是只会有一次(我创建了八个进程,为什么只会重复一次)
来源:https://www.cnblogs.com/qtclm/p/12116327.html