python之线程池map()方法传递多参数list

import concurrent.futures

 with concurrent.futures.ThreadPoolExecutor() as pool:
      res = pool.map(craw, uid_list)
      print(res)

    def test_case_09(self):
        """5000用户并发助力"""
        # 通过yaml配置文件封装方法 获取uid_list
        uid_list = YamlHandler(YamlThePath().number_new).get_uid_list()
        # add_ticket获取5000账号登陆状态
        with concurrent.futures.ThreadPoolExecutor() as pool:
            pool.map(AccountAccess().add_ticket, uid_list)
        # 5000账号线程池方法助力用户
        with concurrent.futures.ThreadPoolExecutor() as pool:
            pool.map(PreheatMethod().help, [(uid, self.A, 1) for uid in uid_list])
        # 获取用户被助力次数
        response = PreheatMethod().init(self.A)
        print(f"当前用户被助力次数 :{response['data']['userInfo']['helpedCount']}次")

    def add_ticket(self, uid):
        """
        获取单独用户t票
        :param uid: 单独用户uid
        :return:
        """
        self.data['url'] = apiAddress().get_ticket
        self.data['host'] = ApiAddress().host
        self.params['uid'] = str(uid)
        self.params['type'] = 0
        self.data['params'] = JSON.dumps(self.params)
        res = r().post(url=ApiAddress().ticket, data=self.data)
        print(f'获取t票结果：{uid}{res}')
        return uid

    def help(self, agrs):
        """
        助力用户
        :param agrs: uid:当前用户uid to_uid:助力用户uid count:助力次数
        :return:
        """
        uid, to_uid, count = agrs
        self.attrs['toUid'] = str(to_uid)
        self.attrs['count'] = count
        response = r().response(uid, self.code, "help", **self.attrs)
        logger.info(f'help response uid:{uid} to_uid:{to_uid}\n{response}')
        return response

with concurrent.futures.ThreadPoolExecutor() as pool:
            pool.map(PreheatMethod().help, [(uid, self.A, 1) for uid in uid_list])

[(uid, self.A, 1) for uid in uid_list]