用户冷启动全量使用轻医美标签，去掉灰度实验

eda/smart_rank/gm_feed_cold_start.py

@@ -142,41 +142,42 @@ if __name__ == "__main__":
 
     # 清空历史数据
     redis_client = redis.StrictRedis.from_url('redis://:ReDis!GmTx*0aN9@172.16.40.173:6379')
-    hot_search_word_topic_queue_key = "coldstart:hot:search:word:topic:queue"
-    hot_search_word_qa_queue_key = "coldstart:hot:search:word:qa:queue"
-    hot_search_word_diary_queue_key = "coldstart:hot:search:word:diary:queue"
+    # hot_search_word_topic_queue_key = "coldstart:hot:search:word:topic:queue"
+    # 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_qa_queue_key = "coldstart:light:clinic:beauty:qa:queue"
     light_clinic_beauty_diary_queue_key = "coldstart:light:clinic:beauty:diary:queue"
     card_types = ['topic', 'qa']  # 日记有400多个城市，且是hmset，因此不用重置
-    word_refers = ['coldstart:hot:search:word', 'coldstart:light:clinic:beauty']
+    # word_refers = ['coldstart:hot:search:word', 'coldstart:light:clinic:beauty']
+    word_refers = ['coldstart:light:clinic:beauty']
     for card_type in card_types:
         for word_refer in word_refers:
             key = word_refer + ':' + card_type + ':' + 'queue'
             redis_client.delete(key)
 
-    # 热搜词的候选队列
-    hot_search_word_key = "user:service_coldstart_tags2_name"
-    hot_search_word = redis_client.hgetall(hot_search_word_key)
-    hot_search_word = [str(tag, 'utf-8') for tag in hot_search_word]
-    hot_search_word_diary_queue = dict()
-
-    # 队列存储
-    hot_search_word_topic_queue = search_topic_by_match_phrase(hot_search_word)
-    redis_client.rpush(hot_search_word_topic_queue_key, *hot_search_word_topic_queue)
-    # redis_client.lrange(hot_search_word_topic_queue_key, 0, 3)
-    print("热搜词更新的帖子队列长度：%s" % str(len(hot_search_word_topic_queue)))
-
-    hot_search_word_qa_queue = search_qa_by_match_phrase(hot_search_word)
-    redis_client.rpush(hot_search_word_qa_queue_key, *hot_search_word_qa_queue)
-    print("热搜词更新的问答队列长度：%s" % str(len(hot_search_word_qa_queue)))
-    # redis_client.lrange(hot_search_word_qa_queue_key, 0, 3)
-
-    for city_tag_id in all_city_tag_id:
-        diary_queue = search_diary_by_match_phrase(hot_search_word, city_tag_id)
-        hot_search_word_diary_queue.update({city_tag_id: json.dumps(diary_queue)})
-    redis_client.hmset(hot_search_word_diary_queue_key, hot_search_word_diary_queue)
-    print("热搜词更新的日记队列长度：%s" % str(len(diary_queue)))
+    # # 热搜词的候选队列
+    # hot_search_word_key = "user:service_coldstart_tags2_name"
+    # hot_search_word = redis_client.hgetall(hot_search_word_key)
+    # hot_search_word = [str(tag, 'utf-8') for tag in hot_search_word]
+    # hot_search_word_diary_queue = dict()
+    #
+    # # 队列存储
+    # hot_search_word_topic_queue = search_topic_by_match_phrase(hot_search_word)
+    # redis_client.rpush(hot_search_word_topic_queue_key, *hot_search_word_topic_queue)
+    # # redis_client.lrange(hot_search_word_topic_queue_key, 0, 3)
+    # print("热搜词更新的帖子队列长度：%s" % str(len(hot_search_word_topic_queue)))
+    #
+    # hot_search_word_qa_queue = search_qa_by_match_phrase(hot_search_word)
+    # redis_client.rpush(hot_search_word_qa_queue_key, *hot_search_word_qa_queue)
+    # print("热搜词更新的问答队列长度：%s" % str(len(hot_search_word_qa_queue)))
+    # # redis_client.lrange(hot_search_word_qa_queue_key, 0, 3)
+    #
+    # for city_tag_id in all_city_tag_id:
+    #     diary_queue = search_diary_by_match_phrase(hot_search_word, city_tag_id)
+    #     hot_search_word_diary_queue.update({city_tag_id: json.dumps(diary_queue)})
+    # redis_client.hmset(hot_search_word_diary_queue_key, hot_search_word_diary_queue)
+    # print("热搜词更新的日记队列长度：%s" % str(len(diary_queue)))
 
     # 轻医美的候选队列
     light_clinic_beauty_key = "user:service_coldstart_tags3"