update sql

eda/smart_rank/tool.py

@@ -380,29 +380,32 @@ def compute_tag3_score(x):
 
 def get_tag3_user_log(cl_id):
     columns = [
-        "log_time", "score_type", "event_cn", "first_solutions", "second_solutions", "first_demands",
-        "second_demands", "first_positions", "second_positions", "projects"
+        "log_time", "score_type", "event_cn", "first_solutions", "second_solutions", "first_demands", "second_demands",
+        "first_positions", "second_positions", "projects"
     ]
-    sql = """select log_time, score_type, event_cn, first_solutions, second_solutions, first_demands,
-             second_demands, first_positions, second_positions, projects
-             from kafka_tag3_log where cl_id = '{}'""".format(cl_id)
-
-    db, cursor = get_jerry_test()
-    cursor.execute(sql)
-    data = list(cursor.fetchall())
-    db.close()
-    cursor.close()
-
-    if data:
-        user_df = pd.DataFrame(data)
-        user_df.columns = columns
-    else:
-        return pd.DataFrame(columns=columns)
+    try:
+        sql = """select log_time, score_type, event_cn, first_solutions, second_solutions, first_demands,
+                 second_demands, first_positions, second_positions, projects
+                 from kafka_tag3_log where cl_id = '{}'""".format(cl_id)
 
-    user_df["days_diff_now"] = round((int(time.time()) - user_df["log_time"].astype(float)) / (24 * 60 * 60))
-    user_df["tag_score"] = user_df.apply(lambda x: compute_tag3_score(x), axis=1)
+        db, cursor = get_jerry_test()
+        cursor.execute(sql)
+        data = list(cursor.fetchall())
+        db.close()
+        cursor.close()
 
-    return user_df
+        if data:
+            user_df = pd.DataFrame(data)
+            user_df.columns = columns
+        else:
+            return pd.DataFrame(columns=columns)
+
+        user_df["days_diff_now"] = round((int(time.time()) - user_df["log_time"].astype(float)) / (24 * 60 * 60))
+        user_df["tag_score"] = user_df.apply(lambda x: compute_tag3_score(x), axis=1)
+        return user_df
+    except Exception as e:
+        print(e)
+        return pd.DataFrame(columns=columns)
 
 
 # CREATE TABLE `user_tag3_portrait` (