用户冷启动增加新good click灰度实验

eda/smart_rank/gm_feed_cold_start.py

@@ -71,7 +71,7 @@ def search_diary_by_match_phrase(tag_names, city_tag_id, version):
     return diary_ids
 
 
-def search_topic_by_match_phrase(tag_names):
+def search_topic_by_match_phrase(tag_names, version=0):
     q = dict()
     total_query_should_list = list()
     for tag_name in tag_names:
@@ -98,11 +98,17 @@ def search_topic_by_match_phrase(tag_names):
     q["_source"] = {
         "includes": ["id"]
     }
-    q["sort"] = [
-        {"is_video": {"order": "asc"}},
-        {"tractate_score": {"order": "desc"}},
-        {"good_click": {"order": "desc"}}
-    ]
+    if version:
+        q["sort"] = [
+            {"is_video": {"order": "asc"}},
+            {"tractate_score": {"order": "desc"}},
+            {"good_click": {"order": "desc"}}
+        ]
+    else:
+        q["sort"] = [
+            {"is_video": {"order": "asc"}},
+            {"tractate_score": {"order": "desc"}}
+        ]
     es_res = es_query("tractate", q, offset=0, size=200)
     topic_list = []
     for topic_info in es_res['hits']['hits']:
@@ -162,6 +168,7 @@ if __name__ == "__main__":
     # hot_search_word_qa_queue_key = "coldstart:hot:search:word:qa:queue"
     # hot_search_word_diary_queue_key = "coldstart:hot:search:word:diary:queue"
     light_clinic_beauty_topic_queue_key = "coldstart:light:clinic:beauty:topic:queue"
+    light_clinic_beauty_topic_queue_grey_key = "coldstart:light:clinic:beauty:topic:queue:grey"
     light_clinic_beauty_qa_queue_key = "coldstart:light:clinic:beauty:qa:queue"
     light_clinic_beauty_qa_queue_grey_key = "coldstart:light:clinic:beauty:qa:queue:grey"
     light_clinic_beauty_diary_queue_key = "coldstart:light:clinic:beauty:diary:queue"
@@ -205,7 +212,9 @@ if __name__ == "__main__":
 
     # 队列存储
     light_clinic_beauty_topic_queue = search_topic_by_match_phrase(light_clinic_beauty)
+    light_clinic_beauty_topic_grey_queue = search_topic_by_match_phrase(light_clinic_beauty, version=1)
     redis_client.rpush(light_clinic_beauty_topic_queue_key, *light_clinic_beauty_topic_queue)
+    redis_client.rpush(light_clinic_beauty_topic_queue_grey_key, *light_clinic_beauty_topic_grey_queue)
     print("轻医美词更新的帖子队列长度：%s" % str(len(light_clinic_beauty_topic_queue)))
 
     light_clinic_beauty_qa_queue = search_qa_by_match_phrase(light_clinic_beauty)