Merge branch 'gyz' into 'master'

Gyz

See merge request alpha/physical!481

libs/es.py

@@ -411,7 +411,7 @@ class ESPerform(object):
                     }
                 },
                 "_source": {
-                    "include": ["id", "user_id"]
+                    "include": ["id", "user_id", "latest_reply_time"]
                 },
                 "sort": [
                     {"latest_reply_time": {"order": "desc"}},
@@ -440,8 +440,15 @@ class ESPerform(object):
             for item in result_dict["hits"]:
                 topic_id_dict[str(item["_source"]["id"])] = item["_source"]["user_id"]
 
+            topic_id_dict_latest_reply_time = list()
+            for item in result_dict["hits"]:
+                topic_id_dict_latest_reply_time.append([item["_source"]["id"], item["_source"]["latest_reply_time"]])
+
             logging.info("topic_id_list:%s" % str(topic_id_dict))
 
+            logging.info("linucb_tag_id_list_2_same_tagset_ids:" + str(tag_id))
+            logging.info("linucb_tag_id_list_2_same_tagset_ids_2_topics_detail:" + str(topic_id_dict_latest_reply_time))
+
             return topic_id_list, topic_id_dict
         except:
             logging.error("catch exception,err_msg:%s" % traceback.format_exc())

linucb/views/linucb.py

@@ -11,6 +11,7 @@ import json
 import pickle
 from django.conf import settings
 from libs.error import logging_exception
+from gm_logging.general import log_maidian
 
 class LinUCB:
     d = 2
@@ -150,8 +151,12 @@ class LinUCB:
                 ori_redis_tag_data = redis_cli.hget(redis_key, tag_id)
 
                 if not ori_redis_tag_data:
+                    log_dict = {"device_id": device_id, "tag_id": tag_id, "ltype": "create", "biz_type": "lin_tag"}
+                    log_maidian(log_dict, 'physical')
                     LinUCB.init_device_id_linucb_info(redis_client, redis_prefix, device_id,[tag_id])
                 else:
+                    log_dict = {"device_id": device_id, "tag_id": tag_id, "ltype": "update", "biz_type": "lin_tag"}
+                    log_maidian(log_dict, 'physical')
                     ori_redis_tag_dict = pickle.loads(ori_redis_tag_data)
                     new_Aa_matrix = ori_redis_tag_dict["Aa"] + np.dot(xa, xaT)
                     new_AaI_matrix = np.linalg.solve(new_Aa_matrix, np.identity(cls.d))