delete prints

diaryQueueUpdate.py

@@ -22,8 +22,6 @@ def get_video_id():
     result = cursor.fetchall()
     df = pd.DataFrame(list(result))
     video_id = df[0].values.tolist()
-    print("video_id候选集")
-    print(video_id[:80])
     db.close()
     return video_id
 
@@ -77,21 +75,17 @@ def save_result(queue_name,queue_arg,device_id):
     score_df["cid"] = queue_arg[0]
     # 去掉cid前面的"diary|"
     score_df["cid"] = score_df["cid"].apply(lambda x:x[6:])
-    print("score_df：")
-    print(score_df.head(1))
-    print(score_df.shape)
+    # print("score_df：")
+    # print(score_df.head(1))
+    # print(score_df.shape)
     if queue_arg[1] != []:
         df_temp = pd.DataFrame(queue_arg[1]).rename(columns={0: "cid"})
         df_temp["score"] = 0
         df_temp = df_temp.sort_index(axis=1,ascending=False)
         df_temp["cid"] = df_temp["cid"].apply(lambda x: x[6:])
-        print("temp_df：")
-        print(df_temp.head(1))
-        print(df_temp.shape)
+
         predict_score_df = score_df.append(df_temp)
-        print("score_df：")
-        print(predict_score_df.head(1))
-        print(predict_score_df.shape)
+
         return predict_score_df
 
     else:
@@ -116,8 +110,6 @@ def update_dairy_queue(score_df,predict_score_df,total_video_id):
 
     video_id = list(set(diary_id)&set(total_video_id))
 
-    print("video_id:")
-    print(video_id)
     if len(video_id)>0:
         not_video = list(set(diary_id) - set(video_id))
         # 为了相加时cid能够匹配，先把cid变成索引
@@ -158,8 +150,7 @@ def update_sql_dairy_queue(queue_name, diary_id,device_id, city_id):
     id_str = str(diary_id[0])
     for i in range(1, len(diary_id)):
         id_str = id_str + "," + str(diary_id[i])
-    print("写入前")
-    print(id_str[:80])
+
     sql = "update device_diary_queue set {}='{}' where device_id = '{}' and city_id = '{}'".format\
         (queue_name,id_str,device_id, city_id)
     cursor.execute(sql)
@@ -197,7 +188,7 @@ def get_queue(device_id, city_id,queue_name):
     cursor.execute(sql)
     result = cursor.fetchall()
     df = pd.DataFrame(list(result))
-    print(df)
+
     if df.empty:
         print("该用户对应的日记为空")
         return False
@@ -218,8 +209,7 @@ def pipe_line(queue_name, queue_arg, device_id,total_video_id):
         return False
     else:
         score_df = score_df.rename(columns={0: "score", 1: "cid"})
-        print("日记打分表")
-        print(score_df.head(1))
+
         diary_queue = update_dairy_queue(score_df, predict_score_df,total_video_id)
         return diary_queue