Merge branch 'hk' into 'master'

add promote position

See merge request alpha/physical!277

linucb/views/collect_data.py

@@ -8,6 +8,7 @@ import logging
 from linucb.views.linucb import LinUCB
 import json
 from trans2es.models.tag import TopicTag,Tag
+from trans2es.models.topic import TopicHomeRecommend
 import traceback
 from django.conf import settings
 from libs.es import ESPerform
@@ -73,6 +74,9 @@ class CollectData(object):
 
                 have_read_topic_id_list = list()
                 have_read_topic_id_list = Tools.get_have_read_topic_id_list(device_id,-1,TopicPageType.HOME_RECOMMEND)
+                promote_recommend_topic_id_list = list()
+                promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE_DB_NAME).filter(is_online=1).values_list("topic_id")
+                have_read_topic_id_list.extend(promote_recommend_topic_id_list)
 
                 recommend_topic_id_list = list()
                 recommend_topic_id_list_click = list()

search/views/topic.py

@@ -7,10 +7,13 @@ import logging
 import traceback
 import json
 from search.utils.topic import TopicUtils
+from trans2es.models.topic import TopicHomeRecommend
 from libs.es import ESPerform
 from libs.cache import redis_client
 from search.utils.common import *
 from libs.es import ESPerform
+from django.conf import settings
+
 
 
 def get_discover_page_topic_ids(user_id, device_id, size, query_type=TopicPageType.FIND_PAGE):
@@ -72,7 +75,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         if b"data" in recommend_topic_dict:
             recommend_topic_id_list = json.loads(recommend_topic_dict[b"data"])
             cursor = int(str(recommend_topic_dict[b"cursor"], encoding="utf-8"))
-            newcursor = cursor + 5
+            newcursor = cursor + 6
             if len(recommend_topic_id_list) > newcursor:
                 recommend_topic_list = recommend_topic_id_list[cursor:newcursor]
                 redis_client.hset(topic_recommend_redis_key,"cursor",newcursor)
@@ -112,12 +115,36 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         if len(recommend_topic_list)>0:
             size = size-len(recommend_topic_list)
             have_read_topic_id_list.extend(recommend_topic_list)
-        topic_id_list = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=tag_id, offset=offset, size=size,
+
+        have_read_topic_id_list_add_promote = list()
+        have_read_topic_id_list_add_promote.extend(have_read_topic_id_list)
+        promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE_DB_NAME).filter(
+            is_online=1).values_list("topic_id")
+        if len(have_read_topic_id_list)>0:
+          for topic_id in promote_recommend_topic_id_list:
+             have_read_topic_id_list_add_promote.extend(topic_id)
+        topic_id_list = list()
+
+        rank_topic_id_list = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=tag_id, offset=offset, size=size,
                                                            single_size=size,query=query, query_type=query_type,
-                                                           filter_topic_id_list=have_read_topic_id_list,
+                                                           filter_topic_id_list=have_read_topic_id_list_add_promote,
                                                            recommend_tag_list=recommend_topic_list,
                                                            user_similar_score_list=user_similar_score_redis_list,index_type="topic",routing="4,5",attention_tag_list=attention_tag_list)
 
+        if (len(recommend_topic_list) == 6):
+            if (size < 11):
+                topic_id_list.extend(rank_topic_id_list[0:3])
+                topic_id_list.extend(recommend_topic_id_list[0:3])
+                topic_id_list.extend(rank_topic_id_list[3:size])
+                topic_id_list.extend(recommend_topic_id_list[3:6])
+            else:
+                topic_id_list.extend(rank_topic_id_list[0:size - 7])
+                topic_id_list.extend(recommend_topic_id_list[0:3])
+                topic_id_list.extend(rank_topic_id_list[size - 7:size])
+                topic_id_list.extend(recommend_topic_id_list[3:6])
+        else:
+            topic_id_list.extend(rank_topic_id_list)
+
         have_read_group_id_set = set()
         have_read_user_id_set = set()
         unread_topic_id_dict = dict()
@@ -159,7 +186,7 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         #         else:
         #             break
 
-        topic_id_list.extend(recommend_topic_list)
+        # topic_id_list.extend(recommend_topic_list)
         # recommend_topic_list.extend(topic_id_list)
         have_read_topic_id_list.extend(topic_id_list)
         if len(have_read_topic_id_list) > 30000:

trans2es/models/topic.py

@@ -281,3 +281,12 @@ class ExcellentTopic(models.Model):
     create_time = models.DateTimeField(verbose_name=u'创建时间', default=datetime.datetime.fromtimestamp(0))
     update_time = models.DateTimeField(verbose_name=u'更新时间', default=datetime.datetime.fromtimestamp(0))
 
+class TopicHomeRecommend(models.Model):
+    """运营位帖子"""
+
+    class Meta:
+        verbose_name = "运营位帖子"
+        db_table = "topic_home_recommend"
+    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')
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