from concurrent.futures import ThreadPoolExecutor import requests import datetime import json import pandas as pd from sqlalchemy import create_engine db_con_str = "mysql+pymysql://%s:%s@%s:%d/%s" % ("data", "hcst@2021", "139.186.27.96", 4000, "jeecg-boot") engine = create_engine(db_con_str, connect_args={'charset': 'utf8'}) def send_request(account_id): url = 'http://139.186.27.96:31018/ai_auto_creative' request_data = json.dumps({"account_id": account_id}) request = requests.post(url, request_data) return json.loads(request.text) # 0、 打印该定时任务被调用的时间 print("*************************", datetime.datetime.now(),"*************************") # 1、获取已有的账号 sql = """ select account_id from ctop_ai_kuaishou_advertiser_strategy where status = 1 """ acc_df = pd.read_sql(sql, engine) acc_list = [int(account_id) for account_id in acc_df['account_id'].unique()] print(acc_list) acc_list = [9864909, 9864904, 9864899, 9864893, 9864888, 9863696] # 2、 5个账户一组进行发送请求 batch_num = 5 for i in range(0, len(acc_list), batch_num): if i + batch_num < len(acc_list): print(tuple(acc_list[i:i+batch_num])) with ThreadPoolExecutor(max_workers=batch_num) as pool: results = pool.map(send_request, tuple(acc_list[i: i+batch_num])) for r in results: print('res = %s' % r) else: with ThreadPoolExecutor(max_workers=batch_num) as pool: print(acc_list[i: len(acc_list)]) results = pool.map(send_request, tuple(acc_list[i: len(acc_list)])) for r in results: print('res = %s' % r)