update user

eda/smart_rank/tag3_update_user_portrait_offline.py

@@ -187,6 +187,7 @@ def _get_all_by_projects(name_lst):
 
 def update_tag3_user_portrait(cl_id):
     user_df = get_tag3_user_log(cl_id)
+    order_df = get_tag3_user_order_log(cl_id)
     if not user_df.empty:
         user_df["first_solutions"] = list(zip(user_df["first_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
         user_df["second_solutions"] = list(zip(user_df["second_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
@@ -240,6 +241,24 @@ def update_tag3_user_portrait(cl_id):
             if k not in forbidden_set:
                 projects_score[k] = v
 
+        paid_business_tags_score = {}
+        validate_business_tags_score = {}
+        if not order_df.empty:
+            paid_order_df = order_df[order_df["event_cn"] == "支付订单"]
+            if not paid_order_df.empty:
+                paid_order_df["business_tags"] = list(zip(paid_order_df["business_tags"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+                paid_order_df["business_tags_dict"] = paid_order_df["business_tags"].apply(lambda x: make_dict_from_pair(x))
+                paid_business_tags_list = paid_order_df["business_tags_dict"].tolist()
+                paid_business_tags_score = merge_values(paid_business_tags_list)
+
+            validate_order_df = order_df[order_df["event_cn"] == "验证订单"]
+            if not validate_order_df.empty:
+                validate_order_df["business_tags"] = list(zip(validate_order_df["business_tags"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+                validate_order_df["business_tags_dict"] = validate_order_df["business_tags"].apply(lambda x: make_dict_from_pair(x))
+                validate_business_tags_list = validate_order_df["business_tags_dict"].tolist()
+                validate_business_tags_score = merge_values(validate_business_tags_list)
+
+
         tmp_res = {}
         if (len(first_demands_score) == 0) and (len(first_solutions_score) == 0) and (len(first_positions_score) == 0) and (
                 len(second_demands_score) == 0) and (len(second_solutions_score) == 0) and (len(second_positions_score) == 0):
@@ -253,7 +272,9 @@ def update_tag3_user_portrait(cl_id):
             "first_positions": first_positions_score,
             "second_positions": second_positions_score,
             "projects": projects_score,
-            "business_tags": business_tags_score
+            "business_tags": business_tags_score,
+            "paid_business_tags": paid_business_tags_score,
+            "validate_business_tags": validate_business_tags_score
         }
         if tmp_res:
             res.update(tmp_res)
@@ -351,7 +372,7 @@ if __name__ == "__main__":
     # update_tag3_user_portrait(cl_id)
 
     cl_id = "867617044159377"
-    print(get_tag3_user_order_log(cl_id))
+    print(update_tag3_user_portrait(cl_id))
 
     # consume_kafka() TODO
     end = datetime.datetime.now()

eda/smart_rank/tool.py

@@ -442,7 +442,8 @@ def get_tag3_user_log(cl_id):
         return pd.DataFrame(columns=columns)
 
 
-def 1get_tag3_user_order_log(cl_id):
+# select log_time, score_type, business_tags, event_cn from kafka_tag3_log where cl_id = '867617044159377' and event_cn in ('支付订单', '验证订单');
+def get_tag3_user_order_log(cl_id):
     columns = [
         "log_time", "score_type", "business_tags", "event_cn"
     ]
@@ -465,6 +466,7 @@ def 1get_tag3_user_order_log(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)
         user_df["business_tags"] = user_df["business_tags"].fillna("")
+        return user_df
     except Exception as e:
         print(e)
         return pd.DataFrame(columns=columns)