.

eda/smart_rank/tool.py

@@ -18,6 +18,8 @@ import pandas as pd
 import traceback
 
 
+score_type_map ={'henqiang':15,'jiaoqiang':12,'validate':10,'ruoyixiang':5,'ai_scan':2}
+
 def send_email(app,id,e):
     # 第三方 SMTP 服务
     mail_host = 'smtp.exmail.qq.com'  # 设置服务器
@@ -455,7 +457,7 @@ def connect_mysql():
 def get_user_portrait_log(cl_id):
     # try:
         sql = """select  cl_id,event_cn, first_solutions, second_solutions, first_demands,
-                 second_demands, first_positions, second_positions, projects
+                 second_demands, first_positions, second_positions, projects, score_type
                  from kafka_tag3_log where cl_id = '{}' """.format(cl_id)
         db, cursor = get_jerry_test()
         cursor.execute(sql)
@@ -472,11 +474,11 @@ def user_portrait_action_statistic(cl_id):
     # try:
         ud_dict = {}
         user_df = get_user_portrait_log(cl_id)
-        print('-'*100)
-        print('cl_id',cl_id)
-        print('user_df')
-        print(user_df)
-        print('-' * 100)
+        # print('-'*100)
+        # print('cl_id',cl_id)
+        # print('user_df')
+        # print(user_df)
+        # print('-' * 100)
         if user_df:
             for ud in user_df:
                 ud2_list = ud[2].split("，")
@@ -486,7 +488,7 @@ def user_portrait_action_statistic(cl_id):
                 ud6_list = ud[6].split("，")
                 ud7_list = ud[7].split("，")
                 ud8_list = ud[8].split("，")
-
+                score = score_type_map[ud[9]]
                 if ud[0] in ud_dict.keys():
                     if ud[1] in ud_dict[ud[0]].keys():
                         ud_dict[ud[0]][ud[1]]["first_solutions"].extend(ud2_list)
@@ -496,20 +498,28 @@ def user_portrait_action_statistic(cl_id):
                         ud_dict[ud[0]][ud[1]]["first_positions"].extend(ud6_list)
                         ud_dict[ud[0]][ud[1]]["second_positions"].extend(ud7_list)
                         ud_dict[ud[0]][ud[1]]["projects"].extend(ud8_list)
+                        ud_dict[ud[0]][ud[1]]["score"] = score_type_map[ud[9]]
+
                     elif ud2_list or ud3_list or ud4_list or ud5_list or ud6_list or ud7_list or ud8_list:
                         ud_dict[ud[0]][ud[1]] = {}
                         ud_dict[ud[0]][ud[1]] = {"first_solutions": ud2_list, "second_solutions": ud3_list,
                                                  "first_demands": ud4_list, "second_demands": ud5_list,
                                                  "first_positions": ud6_list, "second_positions": ud7_list,
-                                                 "projects": ud8_list}
+                                                 "projects": ud8_list,"score": score_type_map[ud[9]]}
                 else:
                     ud_dict[ud[0]] = {}
                     ud_dict[ud[0]][ud[1]] = {"first_solutions": ud2_list,"second_solutions": ud3_list,
                                              "first_demands": ud4_list,"second_demands": ud5_list,
                                              "first_positions": ud6_list,"second_positions": ud7_list,
-                                             "projects": ud8_list}
+                                             "projects": ud8_list,"score": score_type_map[ud[9]]}
+        print('*'*100)
+        print(ud_dict)
+        sorted(ud_dict.items(), key=lambda item: item[1][0][7])
+        print('1'*100)
+        print(ud_dict)
         return ud_dict
 
+
     # except Exception as e:
     #     print('user_portrait_action_statistic error')
     #     print(e)