merge master

injection/data_sync/tasks.py

@@ -20,6 +20,8 @@ def write_to_es(es_type, pk_list, use_batch_query_set=False):
 
         if es_type == "register_user_tag":
             RegisterUserTag.get_register_user_tag(pk_list)
+        elif es_type == "attention_user_tag":
+            RegisterUserTag.get_user_attention_tag(pk_list)
         else:
             type_info_map = get_type_info_map()
             type_info = type_info_map[es_type]

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:
@@ -274,13 +274,27 @@ class ESPerform(object):
                         "weight": 1
                     }
                 )
+            functions_list += [
+                {
+                    "filter": {"term": {"content_level": 6}},
+                    "weight": 6000
+                },
+                {
+                    "filter": {"term": {"content_level": 5}},
+                    "weight": 5000
+                },
+                {
+                    "filter": {"term": {"content_level": 4}},
+                    "weight": 4000
+                }
+            ]
             q = {
                 "query":{
                     "function_score":{
                         "query": {
                             "bool": {
                                 "must": [
-                                    {"range": {"content_level": {"gte": 3, "lte": 5}}},
+                                    {"range": {"content_level": {"gte": 4, "lte": 6}}},
                                     {"term": {"is_online": True}},
                                     {"term": {"is_deleted": False}},
                                     {"terms": {"tag_list": tag_id}}
@@ -308,7 +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="3,4,5")
+                                                       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))

libs/tools.py

@@ -25,7 +25,7 @@ def tzlc(dt, truncate_to_sec=True):
 
 def get_have_read_topic_id_list(device_id,user_id,query_type):
     try:
-        if user_id and user_id>0:
+        if user_id and int(user_id)>0:
             redis_key = "physical:home_recommend" + ":user_id:" + str(user_id) + ":query_type:" + str(query_type)
         else:
             redis_key = "physical:home_recommend" + ":device_id:" + str(device_id) + ":query_type:" + str(query_type)

linucb/utils/register_user_tag.py

@@ -9,7 +9,7 @@ import traceback
 import json
 import pickle
 from django.conf import settings
-from trans2es.models.tag import AccountUserTag
+from trans2es.models.tag import AccountUserTag,CommunityTagFollow
 from libs.es import ESPerform
 import libs.tools as Tools
 from search.utils.common import *
@@ -30,8 +30,40 @@ class RegisterUserTag(object):
     linucb_user_id_register_tag_topic_id_prefix = "physical:linucb:register_tag_topic_recommend:user_id:"
 
     linucb_register_user_tag_key = "physical:linucb:register_user_tag_info"
+
+    @classmethod
+    def get_user_attention_tag(cls, pk_list):
+        """
+        :remark 获取用户关注标签
+        :param pk_list:
+        :return:
+        """
+        try:
+            user_id_dict = dict()
+            query_results = CommunityTagFollow.objects.filter(pk__in=pk_list,is_deleted=False,is_online=True)
+            for item in query_results:
+                tag_id = item.tag_id
+                user_id = item.user_id
+
+                user_tag_list = CommunityTagFollow.objects.filter(user=user_id,is_deleted=False,is_online=True).values_list("tag_id", flat=True)
+                user_id_dict[user_id] = user_tag_list
+
+            for user_id in user_id_dict:
+                redis_user_tag_id_data = redis_client.hget(cls.linucb_register_user_tag_key, user_id)
+                redis_user_tag_id_list = json.loads(redis_user_tag_id_data) if redis_user_tag_id_data else []
+                redis_user_tag_id_list.extend(user_id_dict[user_id])
+                redis_client.hset(cls.linucb_register_user_tag_key, user_id, json.dumps(list(set(redis_user_tag_id_list))))
+        except:
+            logging.error("catch exception,err_msg:%s" % traceback.format_exc())
+
+
     @classmethod
     def get_register_user_tag(cls,pk_list):
+        """
+        :remark 用户注册时选的标签
+        :param pk_list:
+        :return:
+        """
         try:
             # user_id_set = set()
             user_id_dict = dict()
@@ -43,7 +75,10 @@ class RegisterUserTag(object):
                 user_id_dict[user_id] = user_tag_list
 
             for user_id in user_id_dict:
-                redis_client.hset(cls.linucb_register_user_tag_key, user_id, json.dumps(list(user_id_dict[user_id])))
+                redis_user_tag_id_data = redis_client.hget(cls.linucb_register_user_tag_key, user_id)
+                redis_user_tag_id_list = json.loads(redis_user_tag_id_data) if redis_user_tag_id_data else []
+                redis_user_tag_id_list.extend(user_id_dict[user_id])
+                redis_client.hset(cls.linucb_register_user_tag_key, user_id, json.dumps(list(set(redis_user_tag_id_list))))
 
         #         if user_id not in user_id_set:
         #             user_id_set.add(user_id)

linucb/views/collect_data.py

@@ -52,11 +52,8 @@ class CollectData(object):
             logging.error("catch exception,err_msg:%s" % traceback.format_exc())
             return dict()
 
-    def update_recommend_tag_list(self, device_id,user_feature=None,user_id=None,click_topic_tag_list=None):
+    def update_recommend_tag_list(self, device_id,user_feature=None,user_id=None,click_topic_tag_list=None,new_user_click_tag_list = []):
         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)
@@ -82,22 +79,17 @@ 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])
-                     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 = {
-                        "data": json.dumps(recommend_topic_id_list),
-                        "cursor": 0
-                      }
-                     redis_client.hmset(click_recommend_redis_key, click_redis_data_dict)
-
-                total_topic_list = list()
-                tag_topic_id_list = list()
+                        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 = {
+                            "data": json.dumps(recommend_topic_id_list),
+                            "cursor": 0
+                          }
+                        redis_client.hmset(click_recommend_redis_key, click_redis_data_dict)
+
                 tag_id_list = recommend_tag_list[0:100]
 
                 topic_recommend_redis_key = self.linucb_recommend_topic_id_prefix + str(device_id)
@@ -111,9 +103,16 @@ class CollectData(object):
 
                 if len(recommend_topic_id_list)==0 and cursor==0 and len(redis_topic_list)>0:
                     have_read_topic_id_list.extend(redis_topic_list[:2])
-                tag_topic_id_list = ESPerform.get_tag_topic_list(tag_id_list,have_read_topic_id_list)
+                if len(tag_id_list) > 0:
+                 if len(new_user_click_tag_list)>0:
+                     tag_topic_id_list = ESPerform.get_tag_topic_list(new_user_click_tag_list, have_read_topic_id_list)
+                     logging.warning("tag_topic_id_list:%s" % str(new_user_click_tag_list))
+                     logging.warning("tag_id_list:%s" % str(tag_id_list))
+                 else:
+                     tag_topic_id_list = ESPerform.get_tag_topic_list(tag_id_list,have_read_topic_id_list)
+
 
-                if len(recommend_topic_id_list)>0:
+                if len(recommend_topic_id_list)>0 or len(new_user_click_tag_list) > 0:
                     tag_topic_id_list = recommend_topic_id_list + tag_topic_id_list
                     redis_data_dict = {
                         "data": json.dumps(tag_topic_id_list),
@@ -164,8 +163,8 @@ class CollectData(object):
                                 tag_list = list()
                                 click_topic_tag_list = list()
                                 collection_tag_sql_query_results = TopicTag.objects.using(settings.SLAVE_DB_NAME).filter(topic_id=topic_id).values_list("tag_id","is_online","is_collection")
-                                if len(collection_tag_sql_query_results)>0:
-                                 for tag_id,is_online,is_collection in collection_tag_sql_query_results:
+                                # if len(collection_tag_sql_query_results)>0:
+                                for tag_id,is_online,is_collection in collection_tag_sql_query_results:
                                     if is_online and is_collection == 1:
                                         click_topic_tag_list.append(tag_id)
 
@@ -203,7 +202,7 @@ class CollectData(object):
                                     exposure_cards_list = list()
                                 device_id = raw_val_dict["device"]["device_id"]
                                 user_id = raw_val_dict["user_id"] if "user_id" in raw_val_dict else None
-
+                                logging.warning("type msg:%s" % raw_val_dict.get("type"))
                                 exposure_topic_id_list = list()
                                 for item in exposure_cards_list:
                                     if "card_id" not in item:
@@ -217,14 +216,14 @@ class CollectData(object):
                                 topic_tag_id_dict = dict()
                                 tag_list = list()
                                 exposure_sql_query_results = TopicTag.objects.using(settings.SLAVE_DB_NAME).filter(topic_id__in=exposure_topic_id_list).values_list("topic_id","tag_id","is_online","is_collection")
+                                # if len(exposure_sql_query_results)>0:
                                 for topic_id,tag_id,is_online,is_collection in exposure_sql_query_results:
-                                    if is_online and is_collection ==1:
-                                                tag_list.append(tag_id)
-
+                                    if is_online and is_collection == 1:
+                                        tag_list.append(tag_id)
                                     if is_online:
                                         tag_sql_query_results = Tag.objects.using(settings.SLAVE_DB_NAME).filter(
-                                            id=tag_id).values_list("id", "is_ai")
-                                        for id, is_ai in tag_sql_query_results:
+                                            id=tag_id).values_list("id", "collection", "is_ai")
+                                        for id, collection, is_ai in tag_sql_query_results:
                                             if (is_ai == 1) and id not in tag_list:
                                                 tag_list.append(id)
 
@@ -244,6 +243,31 @@ class CollectData(object):
 
                                 # 更新该用户的推荐tag数据，放在 更新完成user tag行为信息之后
                                 self.update_recommend_tag_list(device_id, user_feature, user_id)
+                            elif "type" in raw_val_dict and "interest_choice_click_next" == raw_val_dict["type"]:
+                                if isinstance(raw_val_dict["params"]["tagid_list"],str):
+                                    tagid_list = json.loads(raw_val_dict["params"]["tagid_list"])
+                                elif isinstance(raw_val_dict["params"]["tagid_list"],list):
+                                    tagid_list = raw_val_dict["params"]["tagid_list"]
+                                else:
+                                    tagid_list = list()
+                                logging.warning("unknown type msg:%s" % raw_val_dict.get("type", "missing type"))
+                                logging.info(
+                                    "consume click topic_id:%s,device_id:%s" % (
+                                    str(tagid_list), str(device_id)))
+                                device_id = raw_val_dict["device"]["device_id"]
+                                user_id = raw_val_dict["user_id"] if "user_id" in raw_val_dict else None
+
+                                # if len(exposure_sql_query_results)>0:
+                                if len(tagid_list) > 0:
+                                   is_click = 1
+                                   is_vote = 0
+
+                                   reward = 1 if is_click or is_vote else 0
+                                   for tag_id in tagid_list:
+                                      self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature)
+
+                                # 更新该用户的推荐tag数据，放在 更新完成user tag行为信息之后
+                                   self.update_recommend_tag_list(device_id, user_feature, user_id,new_user_click_tag_list=tagid_list)
                             else:
                                 logging.warning("unknown type msg:%s" % raw_val_dict.get("type", "missing type"))
                         except:

search/views/group.py

@@ -225,9 +225,10 @@ def pictorial_topic_sort(pictorial_id=-1, offset=0, size=10):
                 }
             },
             "sort":[
-                {"total_vote_num":{"order":"desc"}},
+                {"total_vote_num": {"order": "desc"}},
                 {"create_time": {"order": "desc"}}
             ]
+
         }
         pict_pictorial_ids_list =[]
         # 获取es链接对象

search/views/tag.py

@@ -118,8 +118,8 @@ def choice_push_tag(device_id, user_id):
                 redis_push_tag_dict.popitem(tag_id)
 
         redis_push_tag_list = list(redis_push_tag_dict.keys())
-        account_user_tag_list = AccountUserTag.objects.filter(user=user_id).values_list("tag_id",flat=True)
-        community_tag_follow_list = CommunityTagFollow.objects.filter(user_id=user_id).values_list("tag_id",flat=True)
+        account_user_tag_list = list(AccountUserTag.objects.filter(user=user_id).values_list("tag_id",flat=True))
+        community_tag_follow_list = list(CommunityTagFollow.objects.filter(user_id=user_id).values_list("tag_id",flat=True))
 
         linucb_recommend_redis_prefix = "physical:linucb:tag_recommend:device_id:"
         tag_recommend_redis_key = linucb_recommend_redis_prefix + str(device_id)
@@ -134,10 +134,10 @@ def choice_push_tag(device_id, user_id):
         if len(unread_tag_list)>0:
             for tag_id in unread_tag_list:
                 valid_tag_topic_num = TopicTag.objects.filter(tag_id=tag_id,is_online=True).count()
-                if valid_tag_topic_num>100:
+                if valid_tag_topic_num>0:
                     ret_tag_set.add(tag_id)
                     redis_push_tag_dict[tag_id] = now_sec
-                    if len(ret_tag_set)>=2:
+                    if len(ret_tag_set)>=1:
                         break
 
         redis_client.set(redis_push_tag_key, json.dumps(redis_push_tag_dict))

search/views/topic.py

@@ -30,7 +30,7 @@ def get_discover_page_topic_ids(user_id, device_id, size, query_type=TopicPageTy
 
         recommend_topic_ids = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=0, offset=0, size=size,single_size=size,
                                                            query_type=query_type,
-                                                           filter_topic_id_list=have_read_topic_id_list,index_type="topic",routing="4,5")
+                                                           filter_topic_id_list=have_read_topic_id_list,index_type="topic",routing="4,5,6")
 
 
         have_read_topic_id_list.extend(recommend_topic_ids)
@@ -63,25 +63,14 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         redis_field_list = [b'have_read_topic_list']
         redis_field_val_list = redis_client.hmget(redis_key, redis_field_list)
 
-        topic_recommend_redis_key = "physical:linucb:topic_recommend:device_id:" + str(device_id)
-
-        recommend_topic_list=list()
-        recommend_topic_dict = redis_client.hgetall(topic_recommend_redis_key)
-        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 + 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)
-
+        # 获取已读帖子
         have_read_topic_id_list = list()
 
         if redis_field_val_list[0]:
             if query is None:
                 have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
             else:
-                if offset>0:
+                if offset>0: # 首次搜索时不需要过滤已读
                     have_read_topic_id_list = list(json.loads(redis_field_val_list[0]))
 
         user_similar_score_redis_key = "physical:user_similar_score:user_id:" + str(user_id)
@@ -89,30 +78,45 @@ def get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query
         user_similar_score_redis_list = json.loads(
             redis_user_similar_score_redis_val) if redis_user_similar_score_redis_val else []
 
-
-        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 []
-        logging.info("attention_tag_list:%s"%(str(attention_tag_list)))
-        if len(recommend_topic_list)>0:
-            size = size-len(recommend_topic_list)
-            have_read_topic_id_list.extend(recommend_topic_list)
-
-        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",flat=True)
-
-        for topic_id in promote_recommend_topic_id_list:
-            have_read_topic_id_list_add_promote.append(topic_id)
+        attention_tag_list = list()
+        recommend_topic_list = list()
+        if query is None:
+            # linucb 推荐帖子
+            topic_recommend_redis_key = "physical:linucb:topic_recommend:device_id:" + str(device_id)
+
+            recommend_topic_dict = redis_client.hgetall(topic_recommend_redis_key)
+            if b"data" in recommend_topic_dict:
+                recommend_topic_id_list = json.loads(recommend_topic_dict[b"data"])
+                # 推荐帖子是强插的，要保证推荐帖子不在已读里
+                recommend_topic_id_list = list(set(recommend_topic_id_list) - set(have_read_topic_id_list))
+                cursor = int(str(recommend_topic_dict[b"cursor"], encoding="utf-8"))
+                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)
+
+            # 用户关注标签
+            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:
+                size = size-len(recommend_topic_list)
+                have_read_topic_id_list.extend(recommend_topic_list)
+
+            # 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",flat=True)
+            #
+            # for topic_id in promote_recommend_topic_id_list:
+            #     have_read_topic_id_list_add_promote.append(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,
+        rank_topic_id_list = TopicUtils.get_recommend_topic_ids(user_id=user_id, tag_id=tag_id, offset=0, size=size,
                                                            single_size=size,query=query, query_type=query_type,
-                                                           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)
+                                                           filter_topic_id_list=have_read_topic_id_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])
@@ -126,8 +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
@@ -242,7 +244,7 @@ def home_query(device_id="", tag_id=-1, user_id=-1, query="", offset=0, size=10)
         if not isinstance(device_id, str):
             device_id = ""
 
-        recommend_topic_ids = get_home_recommend_topic_ids(user_id, device_id, tag_id, offset, size, query)
+        recommend_topic_ids = get_home_recommend_topic_ids(user_id, device_id, tag_id, offset=offset, size=size, query=query)
         return {"recommend_topic_ids": recommend_topic_ids}
     except:
         logging.error("catch exception,err_msg:%s" % traceback.format_exc())
@@ -251,7 +253,7 @@ def home_query(device_id="", tag_id=-1, user_id=-1, query="", offset=0, size=10)
 
 @bind("physical/search/topic_detail_page_recommend")
 def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pictorial_id=-1, topic_user_id=-1,
-                                filter_topic_user_id=False, offset=0, size=10,topic_tag_list =[]):
+                                filter_topic_user_id=False, offset=0, size=10):
     """
     :remark:帖子详情页推荐策略，缺少第一个卡片策略
     :param user_id:
@@ -264,34 +266,30 @@ def topic_detail_page_recommend(device_id="", user_id=-1, topic_id=-1, topic_pic
         if not isinstance(user_id, int):
             user_id = -1
 
-        # redis_key = "physical:topic_detail_page_recommend" + ":user_id:" + str(user_id) + ":device_id:" + str(device_id)
-        # have_read_topic_redis_data = redis_client.get(redis_key)
-        # have_read_topic_list = json.loads(have_read_topic_redis_data) if have_read_topic_redis_data else []
+        redis_key = "physical:topic_detail_page_recommend" + ":user_id:" + str(user_id) + ":device_id:" + str(device_id)
+        have_read_topic_redis_data = redis_client.get(redis_key)
+        have_read_topic_list = json.loads(have_read_topic_redis_data) if have_read_topic_redis_data else []
 
         # 获取es链接对象
-        # es_cli_obj = ESPerform.get_cli()
-        # have_read_topic_list = list()
-        # # 获取帖子标签列表
-        # topic_tag_list = TopicUtils.get_topic_tag_id_list(topic_id, es_cli_obj)
+        es_cli_obj = ESPerform.get_cli()
 
-        # result_list = TopicUtils.get_topic_detail_recommend_list(user_id, topic_id, topic_tag_list, topic_pictorial_id,
-        #                                                          topic_user_id, filter_topic_user_id,
-        #                                                          have_read_topic_list, offset, size, es_cli_obj,index_type="topic",routing="4,5")
-
-        result_list = TopicUtils.get_recommend_topic_ids(user_id,tag_id=-1,single_size=size,offset=offset,size=size,topic_user_id=topic_user_id,current_topic_id=topic_id,topic_tag_list=topic_tag_list)
+        # 获取帖子标签列表
+        topic_tag_list = TopicUtils.get_topic_tag_id_list(topic_id, es_cli_obj)
 
+        result_list = TopicUtils.get_topic_detail_recommend_list(user_id, topic_id, topic_tag_list, topic_pictorial_id,
+                                                                 topic_user_id, filter_topic_user_id,
+                                                                 have_read_topic_list, offset, size, es_cli_obj,index_type="topic",routing="4,5,6")
         recommend_topic_ids_list = list()
-        recommend_topic_ids_list.extend(result_list)
-        # if len(result_list) > 0:
-        #     recommend_topic_ids_list = [item["_source"]["id"] for item in result_list]
-        #
-        # have_read_topic_list.extend(recommend_topic_ids_list)
-        #
-        # have_read_topic_len = len(have_read_topic_list)
-        # if have_read_topic_len > 5000:
-        #     have_read_topic_list = have_read_topic_list[(have_read_topic_len - 5000):]
-        #
-        # redis_client.set(redis_key, json.dumps(have_read_topic_list))
+        if len(result_list) > 0:
+            recommend_topic_ids_list = [item["_source"]["id"] for item in result_list]
+
+        have_read_topic_list.extend(recommend_topic_ids_list)
+
+        have_read_topic_len = len(have_read_topic_list)
+        if have_read_topic_len > 5000:
+            have_read_topic_list = have_read_topic_list[(have_read_topic_len - 5000):]
+
+        redis_client.set(redis_key, json.dumps(have_read_topic_list))
         return {"recommend_topic_ids": recommend_topic_ids_list}
     except:
         logging.error("catch exception,err_msg:%s" % traceback.format_exc())
@@ -355,7 +353,7 @@ def query_topic_by_user_similarity(topic_similarity_score_dict, offset=0, size=1
 
         must_topic_id_list = list(topic_similarity_score_dict.keys())
         topic_id_list = TopicUtils.get_recommend_topic_ids(tag_id=0, user_id=-1, offset=offset, size=size,single_size=size,
-                                                           must_topic_id_list=must_topic_id_list,index_type="topic",routing="4,5")
+                                                           must_topic_id_list=must_topic_id_list,index_type="topic",routing="4,5,6")
 
         return {"recommend_topic_ids": topic_id_list}
     except:

trans2es/mapping/topic-high-star.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/mapping/topic-star-routing.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/mapping/topic-v1.json

 {
   "dynamic":"strict",
+  "_routing": {"required": true},
   "properties": {
     "id":{"type":"long"},
     "is_online":{"type":"boolean"},//上线
     "is_deleted":{"type":"boolean"},
     "vote_num":{"type":"long"},
-    "total_vote_num":{"type":"long","default":0},
+    "total_vote_num":{"type":"long"},
     "reply_num":{"type":"long"},
     "name":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
     "description":{"type":"text","analyzer":"gm_default_index","search_analyzer":"gm_default_index"},
@@ -49,7 +50,8 @@
         "type": "text",
         "analyzer": "gm_default_index",
         "search_analyzer": "gm_default_index"
-    }
-
+    },
+    "is_excellent":{"type": "long"},
+    "is_operation_home_recommend": {"type": "boolean"} //是否首页运营推荐
   }
 }

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

@@ -197,8 +197,8 @@ class Topic(models.Model):
                 offline_score += 6.0
             elif self.content_level == '4':
                 offline_score += 5.0
-            elif self.content_level == '3':
-                offline_score += 2.0
+            elif self.content_level == '6':
+                offline_score += 100.0
 
             # exposure_count = ActionSumAboutTopic.objects.using(settings.SLAVE_DB_NAME).filter(topic_id=self.id, data_type=1).count()
             # click_count = ActionSumAboutTopic.objects.using(settings.SLAVE_DB_NAME).filter(topic_id=self.id, data_type=2).count()
@@ -289,4 +289,5 @@ class TopicHomeRecommend(models.Model):
         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')
\ No newline at end of file
+    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: