add print for test

diaryQueueUpdate.py

@@ -13,7 +13,7 @@ from config import *
 def test_con_sql(device_id):
     db = pymysql.connect(host='rm-m5e842126ng59jrv6.mysql.rds.aliyuncs.com', port=3306, user='doris',
                          passwd='o5gbA27hXHHm', db='doris_prod')
-    print("连接成功")
+
     cursor = db.cursor()
     sql = "select native_queue,nearby_queue,nation_queue,megacity_queue from device_diary_queue " \
           "where device_id = '{}';".format(device_id)
@@ -31,7 +31,7 @@ def test_con_sql(device_id):
         megacity_queue = df.loc[0, "megacity_queue"].split(",")
         megacity_queue = list(map(lambda x: "diary|" + str(x), megacity_queue))
         db.close()
-
+        print("成功获取日记队列")
         return native_queue, nearby_queue, nation_queue, megacity_queue
     else:
         print("该用户对应的日记队列为空")
@@ -50,6 +50,7 @@ def get_native_queue(device_id):
         native_queue = df.loc[0,0].split(",")
         native_queue = list(map(lambda x:"diary|"+str(x),native_queue))
         db.close()
+        print("成功获取native_queue")
         return native_queue
     else:
         return None
@@ -70,6 +71,7 @@ def feature_en(x_list, device_id):
     data["minute"] = data["minute"].astype("category")
     # 虽然预测y，但ffm转化需要y，并不影响预测结果
     data["y"] = 0
+    print("done 特征工程")
 
     return data
 
@@ -81,6 +83,7 @@ def transform_ffm_format(df,queue_name):
         data = ffm_format_pandas.native_transform(df)
         predict_file_name = DIRECTORY_PATH + "result/{0}_{1}.csv".format(device_id, queue_name)
         data.to_csv(predict_file_name, index=False, header=None)
+        print("done ffm")
         return predict_file_name
 
 
@@ -98,6 +101,7 @@ def predict(queue_name, x_list):
     save_result(queue_name, x_list)
 
 
+
 def save_result(queue_name, x_list):
     score_df = pd.read_csv(DIRECTORY_PATH + "result/output{0}_{1}.csv".format(device_id,queue_name), header=None)
     score_df = score_df.rename(columns={0: "score"})