delete prints

predictDiary.py

@@ -23,8 +23,6 @@ def feature_en(user_profile):
     # 虽然预测y，但ffm转化需要y，并不影响预测结果
     data["y"] = 0
     data = data.drop("city_id", axis=1)
-    print(data.head(1))
-    print("特征工程处理结束")
     return data
 
 
@@ -90,7 +88,7 @@ def router(device_id):
 
 
 # 多进程预测
-def multi_predict(predict_list,processes=8):
+def multi_predict(predict_list,processes=12):
     pool = Pool(processes)
     for device_id in predict_list:
         start = time.time()
@@ -101,6 +99,7 @@ def multi_predict(predict_list,processes=8):
     pool.close()
     pool.join()
 
+
 if __name__ == "__main__":
     # TODO 如果耗时小于一分钟，下一次取到的device_id和上一次相同
     while True:
@@ -116,23 +115,6 @@ if __name__ == "__main__":
             predict_list = list(set(device_id_list) & set(old_device_id_list))
             multi_predict(predict_list)
 
-    # while True:
-    #     empty,device_id_list = get_active_users()
-    #     if empty:
-    #         for eachFile in os.listdir("/tmp"):
-    #             if "xlearn" in eachFile:
-    #                 os.remove("/tmp" + "/" + eachFile)
-    #         time.sleep(58)
-    #     else:
-    #         old_device_id_list = pd.read_csv(DIRECTORY_PATH + "data_set_device_id.csv")["device_id"].values.tolist()
-    #         for device_id in device_id_list:
-    #             if device_id in old_device_id_list:
-    #                 start = time.time()
-    #                 router(device_id)
-    #                 end = time.time()
-    #                 print("该用户预测耗时{}秒".format(end - start))
-    #             else:
-    #                 print("该用户不是老用户，不能预测")