change sql for test

diaryQueueUpdate.py

@@ -205,7 +205,8 @@ def update_dairy_queue(score_df):
         return diary_id
     else:
         score_df = score_df.sort_values(by="score", ascending=False)
-
+        print("排序后")
+        print(score_df["cid"].values.tolist())
         return score_df["cid"].values.tolist()
 
 
@@ -216,7 +217,8 @@ def update_sql_dairy_queue(queue_name, diary_id):
     cursor = db.cursor()
     ## 去除diary_id 前面的"diary|"
     diary_id = json.dumps(list(map(lambda x:x[6:],diary_id)))
-
+    print("写入前")
+    print(diary_id)
     sql = "update device_diary_queue set {}='{}' where device_id = '{}'".format(queue_name, diary_id, device_id)
     cursor.execute(sql)
     db.close()
@@ -240,7 +242,7 @@ def user_update(device_id):
     if not_empty:
         name_dict = {"native_queue": native_queue_list, "nearby_queue": nearby_queue_list,
                      "nation_queue": nation_queue_list, "megacity_queue": megacity_queue_list}
-        pool = Pool(4)
+        pool = Pool(1)
         for key in name_dict.keys():
             pool.apply_async(multi_update, (key, name_dict,native_queue_list,))
         pool.close()
@@ -258,7 +260,7 @@ if __name__ == "__main__":
         old_device_id_list = pd.read_csv(DIRECTORY_PATH + "data_set_device_id.csv")["device_id"].values.tolist()
         # 求活跃用户和老用户的交集，也就是只预测老用户
         predict_list = list(set(device_id_list) & set(old_device_id_list))
-        predict_list.extend(["B2F0665E-4375-4169-8FE3-8A26A1CFE248","AB20292B-5D15-4C44-9429-1C2FF5ED26F6","358035085192742"])
+        predict_list.extend(["358035085192742"])
 
         # 只预测尾号是6的ID，这块也可以在数据库取数据时过滤一下
         # predict_list = list(filter(lambda x:str(x)[-1] == "6", predict_list))
@@ -269,6 +271,7 @@ if __name__ == "__main__":
         if predict_list != []:
             for device_id in predict_list:
                 user_update(device_id)
+
         else:
             print("该列表是新用户，不需要预测")
         end = time.time()