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# -*- coding: UTF-8 -*-
# !/usr/bin/env python
from kafka import KafkaConsumer
import random
from libs.cache import redis_client
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
from search.utils.common import *
import libs.tools as Tools
class KafkaManager(object):
consumser_obj = None
@classmethod
def get_kafka_consumer_ins(cls, topic_name=None):
if not cls.consumser_obj:
topic_name = settings.KAFKA_TOPIC_NAME if not topic_name else topic_name
cls.consumser_obj = KafkaConsumer(topic_name,bootstrap_servers=settings.KAFKA_BROKER_LIST)
# cls.consumser_obj.subscribe([topic_name])
return cls.consumser_obj
class CollectData(object):
def __init__(self):
self.linucb_matrix_redis_prefix = "physical:linucb:device_id:"
#废弃
self.linucb_recommend_redis_prefix = "physical:linucb:tag_recommend:device_id:"
#推荐帖子
self.linucb_recommend_topic_id_prefix = "physical:linucb:topic_recommend:device_id:"
self.tag_topic_id_redis_prefix = "physical:tag_id:topic_id_list:"
self.click_recommend_redis_key_prefix = "physical:click_recommend:device_id:"
# 默认
self.user_feature = [0,1]
def _get_user_linucb_info(self, device_id):
try:
redis_key = self.linucb_matrix_redis_prefix + str(device_id)
# dict的key为标签ID，value为4个矩阵
redis_linucb_tag_data_dict = redis_client.hgetall(redis_key)
return redis_linucb_tag_data_dict
except:
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,new_user_click_tag_list = []):
try:
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)
LinUCB.init_device_id_linucb_info(redis_client, self.linucb_matrix_redis_prefix,device_id,recommend_tag_list)
else:
user_feature = user_feature if user_feature else self.user_feature
(recommend_tag_dict,recommend_tag_set) = LinUCB.linucb_recommend_tag(device_id,redis_linucb_tag_data_dict,user_feature,list(redis_linucb_tag_data_dict.keys()))
recommend_tag_list = list(recommend_tag_dict.keys())
if len(recommend_tag_list) > 0:
tag_recommend_redis_key = self.linucb_recommend_redis_prefix + str(device_id)
redis_client.set(tag_recommend_redis_key, json.dumps(recommend_tag_list))
redis_client.expire(tag_recommend_redis_key, 7*24*60*60)
have_read_topic_id_list = Tools.get_have_read_topic_id_list(device_id,user_id,TopicPageType.HOME_RECOMMEND)
promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE_DB_NAME).filter(is_online=1).values_list("topic_id",flat=True)
have_read_topic_id_list.extend(promote_recommend_topic_id_list)
recommend_topic_id_list = list()
recommend_topic_id_list_dict = dict()
recommend_topic_id_list_click = list()
recommend_topic_id_list_click_dict = dict()
if click_topic_tag_list and len(click_topic_tag_list)>0:
recommend_topic_id_list_click,recommend_topic_id_list_click_dict = ESPerform.get_tag_topic_list_dict(click_topic_tag_list,
have_read_topic_id_list,size=2)
if len(recommend_topic_id_list_click) > 0:
recommend_topic_id_list.extend(recommend_topic_id_list_click)
recommend_topic_id_list_dict.update(recommend_topic_id_list_click_dict)
# have_read_topic_id_list.extend(recommend_topic_id_list_click)
# click_recommend_redis_key = self.click_recommend_redis_key_prefix + str(device_id)
# click_redis_data_dict = {
# "data": json.dumps(recommend_topic_id_list),
# "datadict":json.dumps(recommend_topic_id_list_dict),
# "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)
# redis_topic_data_dict = redis_client.hgetall(topic_recommend_redis_key)
# redis_topic_list = list()
# cursor = -1
# if b"data" in redis_topic_data_dict:
# redis_topic_list = json.loads(redis_topic_data_dict[b"data"]) if redis_topic_data_dict[
# b"data"] else []
# cursor = int(str(redis_topic_data_dict[b"cursor"], encoding="utf-8"))
# 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])
if len(new_user_click_tag_list)>0:
tag_topic_id_list,tag_topic_dict = ESPerform.get_tag_topic_list_dict(new_user_click_tag_list, have_read_topic_id_list)
else:
tag_topic_id_list,tag_topic_dict = ESPerform.get_tag_topic_list_dict(tag_id_list,have_read_topic_id_list)
if len(recommend_topic_id_list)>0 or len(tag_topic_id_list)>0 or len(new_user_click_tag_list) > 0:
tag_topic_id_list = recommend_topic_id_list + tag_topic_id_list
tag_topic_dict.update(recommend_topic_id_list_dict)
redis_data_dict = {
"data": json.dumps(tag_topic_id_list),
"datadict":json.dumps(tag_topic_dict),
"cursor":0
}
redis_client.hmset(topic_recommend_redis_key,redis_data_dict)
return True
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
return False
def update_user_linucb_tag_info(self, reward, device_id, tag_id, user_feature=None):
try:
user_feature = user_feature if user_feature else self.user_feature
return LinUCB.update_linucb_info(user_feature, reward, tag_id, device_id,self.linucb_matrix_redis_prefix,redis_client)
except:
logging.error("update_user_linucb_tag_info error!")
return False
def consume_data_from_kafka(self,topic_name=None):
try:
user_feature = [1,1]
kafka_consumer_obj = KafkaManager.get_kafka_consumer_ins(topic_name)
while True:
msg_dict = kafka_consumer_obj.poll(timeout_ms=100)
for msg_key in msg_dict:
consume_msg = msg_dict[msg_key]
for ori_msg in consume_msg:
try:
logging.info(ori_msg)
raw_val_dict = json.loads(ori_msg.value)
if "type" in raw_val_dict and \
(raw_val_dict["type"] in ("on_click_feed_topic_card","tag_zone_click_focus")):
click_topic_tag_list = list()
if "on_click_feed_topic_card" == raw_val_dict["type"]:
topic_id = raw_val_dict["params"]["business_id"] or raw_val_dict["params"]["topic_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
logging.info("consume topic_id:%s,device_id:%s" % (str(topic_id), str(device_id)))
topic_tag_list = list(TopicTag.objects.using(settings.SLAVE_DB_NAME).filter(topic_id=topic_id,is_online=True).values_list("tag_id",flat=True))
tag_query_results = Tag.objects.using(settings.SLAVE_DB_NAME).filter(id__in=topic_tag_list,is_online=True,is_deleted=False).values_list("id","collection","is_ai")
for id,collection,is_ai in tag_query_results:
if collection and is_ai:
click_topic_tag_list.append(id)
logging.info("positive tag_list,device_id:%s,topic_id:%s,tag_list:%s" % (
str(device_id), str(topic_id), str(click_topic_tag_list)))
else:
tag_name = raw_val_dict["params"]["query"]
query_type = raw_val_dict["params"]["type"]
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 query_type=="do":
tag_list = list(Tag.objects.using(settings.SLAVE_DB_NAME).filter(name=tag_name,is_online=True,is_deleted=False).values_list("id",flat=True))
click_topic_tag_list.extend(tag_list)
logging.info("query tag attention,positive tag_list,device_id:%s,query_name:%s,tag_list:%s" % (
str(device_id), tag_name, str(click_topic_tag_list)))
logging.info("click_topic_tag_list:%s"%(str(click_topic_tag_list)))
is_click = 1
is_vote = 0
reward = 1 if is_click or is_vote else 0
for tag_id in click_topic_tag_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
if len(click_topic_tag_list)>0:
self.update_recommend_tag_list(device_id, user_feature, user_id,click_topic_tag_list=click_topic_tag_list)
elif "type" in raw_val_dict and "page_precise_exposure" == raw_val_dict["type"]:
if isinstance(raw_val_dict["params"]["exposure_cards"],str):
exposure_cards_list = json.loads(raw_val_dict["params"]["exposure_cards"])
elif isinstance(raw_val_dict["params"]["exposure_cards"],list):
exposure_cards_list = raw_val_dict["params"]["exposure_cards"]
else:
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:
continue
exposure_topic_id = item["card_id"]
logging.info(
"consume exposure topic_id:%s,device_id:%s" % (str(exposure_topic_id), str(device_id)))
if exposure_topic_id:
exposure_topic_id_list.append(exposure_topic_id)
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:
tag_sql_query_results = Tag.objects.using(settings.SLAVE_DB_NAME).filter(
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)
if topic_id not in topic_tag_id_dict:
topic_tag_id_dict[topic_id] = list()
topic_tag_id_dict[topic_id].append(tag_id)
is_click = 0
is_vote = 0
reward = 1 if is_click or is_vote else 0
logging.info("negative tag_list,device_id:%s,topic_tag_id_dict:%s" % (
str(device_id), str(topic_tag_id_dict)))
for tag_id in tag_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)
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"))
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:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
return True
except:
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
return False