modify home_recommend

libs/es.py

@@ -264,7 +264,7 @@ class ESPerform(object):
             return True
 
     @classmethod
-    def get_tag_topic_list(cls,tag_id,have_read_topic_id_list):
+    def get_tag_topic_list(cls,tag_id,have_read_topic_id_list,size=100):
         try:
             functions_list = list()
             for id in tag_id:
@@ -322,7 +322,7 @@ class ESPerform(object):
                     }
                 }
             result_dict = ESPerform.get_search_results(ESPerform.get_cli(), sub_index_name="topic", query_body=q,
-                                                       offset=0, size=100,routing="4,5,6")
+                                                       offset=0, size=size,routing="4,5,6")
 
             topic_id_list = [item["_source"]["id"] for item in result_dict["hits"]]
             logging.info("topic_id_list:%s"%str(topic_id_list))

linucb/views/collect_data.py

@@ -54,9 +54,6 @@ class CollectData(object):
 
     def update_recommend_tag_list(self, device_id,user_feature=None,user_id=None,click_topic_tag_list=None):
         try:
-            recommend_tag_set = set()
-            recommend_tag_list = list()
-            recommend_tag_dict = dict()
             redis_linucb_tag_data_dict = self._get_user_linucb_info(device_id)
             if len(redis_linucb_tag_data_dict) == 0:
                 recommend_tag_list = LinUCB.get_default_tag_list(user_id)
@@ -82,12 +79,9 @@ class CollectData(object):
                 if click_topic_tag_list:
                     if len(click_topic_tag_list)>0:
                      recommend_topic_id_list_click = ESPerform.get_tag_topic_list(click_topic_tag_list,
-                                                                                 have_read_topic_id_list)
+                                                                                 have_read_topic_id_list,size=2)
                     if len(recommend_topic_id_list_click) > 0:
-                     num = min(len(recommend_topic_id_list_click), 2)
-                     logging.info("recommend_topic_id_list:%s" % (str(num)))
-                     for i in range(0,num):
-                        recommend_topic_id_list.append(recommend_topic_id_list_click[i])
+                        recommend_topic_id_list.extend(recommend_topic_id_list_click)
                         have_read_topic_id_list.extend(recommend_topic_id_list)
                         click_recommend_redis_key = self.click_recommend_redis_key_prefix + str(device_id)
                         click_redis_data_dict = {
@@ -96,8 +90,6 @@ class CollectData(object):
                           }
                         redis_client.hmset(click_recommend_redis_key, click_redis_data_dict)
 
-                total_topic_list = list()
-                tag_topic_id_list = list()
                 tag_id_list = recommend_tag_list[0:100]
 
                 topic_recommend_redis_key = self.linucb_recommend_topic_id_prefix + str(device_id)

search/views/topic.py

@@ -94,6 +94,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
             redis_user_similar_score_redis_val) if redis_user_similar_score_redis_val else []
 
 
+        if query is None:
             redis_tag_data = redis_client.hget("physical:linucb:register_user_tag_info", user_id)
             attention_tag_list = json.loads(redis_tag_data) if redis_tag_data else []
             if len(recommend_topic_list)>0:
@@ -115,7 +116,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
                                                            recommend_tag_list=recommend_topic_list,
                                                            user_similar_score_list=user_similar_score_redis_list,index_type="topic",routing="4,5,6",attention_tag_list=attention_tag_list)
 
-        if (len(recommend_topic_list) == 6):
+        if len(recommend_topic_list) == 6 and query is None:
             if (size < 11):
                 topic_id_list.extend(rank_topic_id_list[0:3])
                 topic_id_list.extend(recommend_topic_list[0:3])
@@ -129,8 +130,6 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         else:
             topic_id_list.extend(rank_topic_id_list)
 
-        logging.info("attention_tag_list:%s"%(str(topic_id_list)))
-
         have_read_topic_id_list.extend(topic_id_list)
         if len(have_read_topic_id_list) > 30000:
             cut_len = len(have_read_topic_id_list)-30000

trans2es/mapping/topic.json

@@ -51,6 +51,7 @@
         "analyzer": "gm_default_index",
         "search_analyzer": "gm_default_index"
     },
-    "is_excellent":{"type": "long"}
+    "is_excellent":{"type": "long"},
+    "is_operation_home_recommend": {"type": "boolean"} //是否首页运营推荐
   }
 }

trans2es/models/topic.py

@@ -290,3 +290,4 @@ class TopicHomeRecommend(models.Model):
     id = models.IntegerField(verbose_name=u"id",primary_key=True)
     topic_id = models.IntegerField(verbose_name=u"帖子ID")
     is_online = models.BooleanField(verbose_name=u'是否上线')
+    is_deleted = models.BooleanField(verbose_name=u'是否删除')

trans2es/utils/topic_transfer.py

@@ -9,7 +9,7 @@ import time
 import re
 import datetime
 from trans2es.models.user import User
-from trans2es.models.topic import ExcellentTopic
+from trans2es.models.topic import ExcellentTopic,TopicHomeRecommend
 
 class TopicTransfer(object):
 
@@ -121,6 +121,11 @@ class TopicTransfer(object):
                 else:
                     res["is_excellent"] = 0
 
+            res["is_operation_home_recommend"] = False
+            operation_home_recommend = TopicHomeRecommend.objects.filter(topic_id=instance.id).first()
+            if operation_home_recommend and operation_home_recommend.is_online and not operation_home_recommend.is_deleted:
+                res["is_operation_home_recommend"] = True
+
             logging.info("test topic transfer time cost,time0:%d,time1:%d,time2:%d,time3:%d,time4:%d" % (time0,time1,time2,time3,time4))
             return res
         except: