update diaryqueue file

diaryQueueUpdate.py

@@ -137,8 +137,7 @@ def update_dairy_queue(score_df,predict_score_df,total_video_id):
         i = 1
         for j in video_id:
             new_queue.insert(i, j)
-            # TODO 下面的3是测试用的，如果上线后，把3改成5
-            i += 3
+            i += 5
 
         print("分数合并成功")
         return new_queue
@@ -253,24 +252,23 @@ def multi_proecess_update(device_id, city_id, data_set_cid,total_video_id):
     pool.join()
 
 
-def run():
+if __name__ == "__main__":
+    warnings.filterwarnings("ignore")
+    total_number = 0
+    while True:
         data_set_cid = pd.read_csv(DIRECTORY_PATH + "data_set_cid.csv")["cid"].values.tolist()
         total_video_id = get_video_id()
         device_city_list = get_active_users()
-
+        total_number += len(device_city_list)
+        if device_city_list != []:
             for device_city in device_city_list:
                 start = time.time()
-        multi_proecess_update(device_city[0], device_city[1], data_set_cid,total_video_id)
+                multi_proecess_update(device_city[0], device_city[1], data_set_cid, total_video_id)
                 end = time.time()
-        print("更新该用户队列耗时{}秒".format((end-start)))
-    print("end")
+                print("更新该用户队列耗时{}秒".format((end - start)))
+            print("累计预测用户总数：{}".format(total_number))
 
 
-if __name__ == "__main__":
-    warnings.filterwarnings("ignore")
-    # todo 正式上线后把下面while True的代码加上
-    # while True:
-    run()
 
 # # TODO 上线后把预测用户改成多进程预测
 

userProfile.py

@@ -14,15 +14,13 @@ def get_active_users():
     sql = "select device_id,city_id from user_active_time " \
           "where active_time <= '{}' and active_time >= '{}'".format(now_end,now_start)
     df = con_sql(sql)
-    return (("AB20292B-5D15-4C44-9429-1C2FF5ED26F6","beijing"),)
     if df.empty:
         print("当下这一分钟没有活跃用户，不需要预测")
         for eachFile in os.listdir("/tmp"):
             if "xlearn" in eachFile:
                 os.remove("/tmp" + "/" + eachFile)
-        time.sleep(58)
-
-        return False
+        time.sleep(56)
+        return []
     else:
         df = df.rename(columns={0: "device_id", 1: "city_id"})
         old_device_id_list = pd.read_csv(DIRECTORY_PATH + "data_set_device_id.csv")["device_id"].values.tolist()
@@ -30,18 +28,23 @@ def get_active_users():
         df = df.loc[df["device_id"].isin(old_device_id_list)]
         if df.empty:
             print("该列表是新用户，不需要预测")
+            return []
         else:
             # TODO 正式上线后注释下面的只预测尾号是6的代码
             # 只预测尾号是6的ID，这块是测试要求的
-            # device_temp_list = df["device_id"].values.tolist()
-            # predict_list = list(filter(lambda x: str(x)[-1] == "6", device_temp_list))
-            # df = df.loc[df["device_id"].isin(predict_list)]
-            # TODO 上线后把下面的temp删掉
-            # 把刘潇的id加进去
-            df = pd.DataFrame({"device_id":["358035085192742"],"city_id":["beijing"]})
+            device_temp_list = df["device_id"].values.tolist()
+            predict_list = list(filter(lambda x: str(x)[-1] == "6", device_temp_list))
+            if predict_list == []:
+                print('没有尾号是6的用户')
+                return []
+            else:
+                df = df.loc[df["device_id"].isin(predict_list)]
                 device_list = df["device_id"].values.tolist()
                 city_list = df["city_id"].values.tolist()
                 device_city_list = list(zip(device_list, city_list))
+                # TODO 上线后把刘潇的id删除
+                #  把刘潇的id加进去
+                device_city_list.append(("358035085192742", "beijing"))
                 print("当下这一分钟预测用户数量：{}".format(len(device_city_list)))
                 return device_city_list