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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
from trans2es.models.pictorial import CommunityPictorialHomeFeed
from trans2es.models.portrait_stat import LikeDeviceTagStat
from libs.error import logging_exception
import os
from search.views.tag import get_same_tagset_ids
import msgpack
def loads_data(data):
try:
result = json.loads(data)
msg = True
return result,msg
except:
result = msgpack.loads(data)
msg = False
return result,msg
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
gm_logging_name = settings.KAFKA_GM_LOGGING_TOPIC_NAME
cls.consumser_obj = KafkaConsumer(bootstrap_servers=settings.KAFKA_BROKER_LIST)
cls.consumser_obj.subscribe([topic_name, gm_logging_name])
return cls.consumser_obj
class CollectData(object):
def __init__(self):
# lin tag参数
self.linucb_matrix_redis_prefix = "physical:linucb:device_id:"
self.ctr_linucb_matrix_redis_prefix = "ctr_physical:linucb:device_id:"
# lin推荐tag
self.linucb_recommend_redis_prefix = "physical:linucb:tag_recommend:device_id:"
self.ctr_linucb_recommend_redis_prefix = "ctr_physical:linucb:tag_recommend:device_id:"
# 推荐帖子
self.linucb_recommend_topic_id_prefix = "physical:linucb:topic_recommend:device_id:"
self.ctr_linucb_recommend_topic_id_prefix = "ctr_physical:linucb:topic_recommend:device_id:"
# 推荐榜单
self.linucb_recommend_pictorial_id_prefix = "physical:linucb:pictorial_recommend:device_id:"
self.ctr_linucb_recommend_pictorial_id_prefix = "ctr_physical:linucb:pictorial_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, linucb_matrix_prefix):
try:
redis_key = linucb_matrix_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_exception()
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=[], linucb_matrix_prefix=None, linucb_recommend_tag_prefix=None,
linucb_topic_ids_prefix=None, linucb_pictorial_ids_prefix=None):
try:
redis_linucb_tag_data_dict = self._get_user_linucb_info(device_id, linucb_matrix_prefix)
if len(redis_linucb_tag_data_dict) == 0:
recommend_tag_list = list(LinUCB.get_default_tag_list(user_id))
LinUCB.init_device_id_linucb_info(redis_client, linucb_matrix_prefix, device_id, recommend_tag_list)
else:
user_feature = user_feature if user_feature else self.user_feature
linucb_tag_list = list(redis_linucb_tag_data_dict.keys())
(recommend_tag_dict, recommend_tag_set) = LinUCB.linucb_recommend_tag(device_id,
redis_linucb_tag_data_dict,
user_feature, linucb_tag_list)
recommend_tag_list = list(recommend_tag_dict.keys())
if len(recommend_tag_list) > 0:
tag_recommend_redis_key = linucb_recommend_tag_prefix + str(device_id)
redis_client.set(tag_recommend_redis_key, json.dumps(recommend_tag_list))
redis_client.expire(tag_recommend_redis_key, 30*24*60*60)
have_read_topic_id_list = Tools.get_have_read_topic_id_list(device_id,user_id,TopicPageType.HOME_RECOMMEND)
have_read_lin_pictorial_id_list = Tools.get_have_read_lin_pictorial_id_list(device_id, user_id,
TopicPageType.HOME_RECOMMEND)
promote_recommend_topic_id_list = TopicHomeRecommend.objects.using(settings.SLAVE1_DB_NAME).filter(is_online=1).values_list("topic_id",flat=True)
promote_lin_pictorial_id_list = CommunityPictorialHomeFeed.objects.using(settings.SLAVE1_DB_NAME).filter(
is_deleted=0, is_online=1).values_list("pictorial_id", flat=True)
have_read_topic_id_list.extend(promote_recommend_topic_id_list)
have_read_lin_pictorial_id_list.extend(promote_lin_pictorial_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()
recommend_lin_pictorial_id_list = list()
if click_topic_tag_list and len(click_topic_tag_list)>0:
click_topic_tag_list_same_tagset_ids = get_same_tagset_ids(click_topic_tag_list)
recommend_topic_id_list_click,recommend_topic_id_list_click_dict = ESPerform.get_tag_topic_list_dict(click_topic_tag_list_same_tagset_ids,
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[0:20]
pictorial_recommend_redis_key = linucb_pictorial_ids_prefix + str(device_id)
topic_recommend_redis_key = linucb_topic_ids_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:
new_user_click_tag_list_same_tagset_ids = get_same_tagset_ids(new_user_click_tag_list)
tag_topic_id_list,tag_topic_dict = ESPerform.get_tag_topic_list_dict(new_user_click_tag_list_same_tagset_ids, have_read_topic_id_list)
recommend_lin_pictorial_id_list = ESPerform.get_tag_pictorial_id_list(new_user_click_tag_list_same_tagset_ids,
have_read_lin_pictorial_id_list)
else:
tag_id_list_same_tagset_ids = get_same_tagset_ids(tag_id_list)
tag_topic_id_list,tag_topic_dict = ESPerform.get_tag_topic_list_dict(tag_id_list_same_tagset_ids,have_read_topic_id_list)
recommend_lin_pictorial_id_list = ESPerform.get_tag_pictorial_id_list(tag_id_list_same_tagset_ids,
have_read_lin_pictorial_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)
if len(recommend_lin_pictorial_id_list) > 0:
pictorial_data_dict = {
"data": json.dumps(recommend_lin_pictorial_id_list),
"cursor": 0
}
redis_client.hmset(pictorial_recommend_redis_key, pictorial_data_dict)
return True
except:
logging_exception()
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, linucb_matrix_redis_prefix):
try:
user_feature = user_feature if user_feature else self.user_feature
return LinUCB.update_linucb_info(user_feature, reward, tag_id, device_id, linucb_matrix_redis_prefix, redis_client)
except:
logging_exception()
logging.error("update_user_linucb_tag_info error!")
return False
def transfer_old_info2ctr_feature_key(self, device_id):
try:
# 移植老用户的lin标签参数信息到ctr特征策略
ctr_linucb_matrix_redis_prefix_key = self.ctr_linucb_matrix_redis_prefix + str(device_id)
linucb_matrix_redis_prefix_key = self.linucb_matrix_redis_prefix + str(device_id)
if redis_client.exists(ctr_linucb_matrix_redis_prefix_key): #如果新策略存在lin信息，则不需要移植
return True
else:
if redis_client.exists(linucb_matrix_redis_prefix_key):
older_device_info = redis_client.hgetall(linucb_matrix_redis_prefix_key)
redis_client.hmset(ctr_linucb_matrix_redis_prefix_key, older_device_info)
# 移植老用户的lin推荐标签列表信息到ctr特征策略
ctr_linucb_recommend_redis_prefix = self.ctr_linucb_recommend_redis_prefix + str(device_id)
linucb_recommend_redis_prefix = self.linucb_recommend_redis_prefix + str(device_id)
if not redis_client.exists(ctr_linucb_recommend_redis_prefix):
if redis_client.exists(linucb_recommend_redis_prefix):
older_device_info = redis_client.get(linucb_recommend_redis_prefix)
redis_client.set(ctr_linucb_recommend_redis_prefix, older_device_info)
# 移植老用户的lin帖子推荐队列信息到ctr特征策略
linucb_recommend_topic_id_prefix = self.linucb_recommend_topic_id_prefix + str(device_id)
ctr_linucb_recommend_topic_id_prefix = self.ctr_linucb_recommend_topic_id_prefix + str(device_id)
if not redis_client.exists(ctr_linucb_recommend_topic_id_prefix):
if redis_client.exists(linucb_recommend_topic_id_prefix):
older_device_info = redis_client.hgetall(linucb_recommend_topic_id_prefix)
redis_client.hmset(ctr_linucb_recommend_topic_id_prefix, older_device_info)
# 移植老用户的lin榜单推荐队列信息到ctr特征策略
linucb_recommend_pictorial_id_prefix = self.linucb_recommend_pictorial_id_prefix + str(device_id)
ctr_linucb_recommend_pictorial_id_prefix = self.ctr_linucb_recommend_pictorial_id_prefix + str(device_id)
if not redis_client.exists(ctr_linucb_recommend_pictorial_id_prefix):
if redis_client.exists(linucb_recommend_pictorial_id_prefix):
older_device_info = redis_client.hgetall(linucb_recommend_pictorial_id_prefix)
redis_client.hmset(ctr_linucb_recommend_pictorial_id_prefix, older_device_info)
logging.info("transfer_old_info2ctr_feature_key sucess:"+str(device_id))
return True
except:
logging_exception()
logging.error("transfer_old_info2ctr_feature_key error!")
return False
def get_device_tag_ctr(self, device_id, tag_id):
# 获取用户在该tag下的ctr信息
try:
device_tag_ctr = LikeDeviceTagStat.objects.using(settings.SLAVE1_DB_NAME).filter(
device_id=device_id, tag_id=tag_id).values("tag_ctr_30")
if device_tag_ctr:
device_tag_ctr_value = device_tag_ctr[0].get("tag_ctr_30", 0.0)
else:
device_tag_ctr_value = 0.0
logging.info("get_device_tag_ctr" + str(device_id) + str(tag_id))
return device_tag_ctr_value
except:
logging_exception()
logging.error("get_device_tag_ctr error!")
return 0.0
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:
raw_val_dict,msg = loads_data(ori_msg.value)
if msg:
logging.info(ori_msg.value)
if "type" in raw_val_dict and \
(raw_val_dict["type"] in ("on_click_feed_topic_card","on_click_button")):
click_topic_tag_list = list()
if "on_click_feed_topic_card" == raw_val_dict["type"]:
topic_id = 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)
topic_tag_list = list()
click_results = TopicTag.objects.using(settings.SLAVE1_DB_NAME).filter(
topic_id=topic_id, is_online=True).values_list("tag_id", "is_collection")
for tag_id, is_collection in click_results:
# topic_tag_list.append(tag_id)
if is_collection:
topic_tag_list.append(tag_id)
tag_query_results = Tag.objects.using(settings.SLAVE1_DB_NAME).filter(
id__in=topic_tag_list, is_online=True, is_deleted=False, is_category=False).values_list("id",
"is_ai")
for id, is_ai in tag_query_results:
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)))
elif raw_val_dict["type"] == "on_click_button" and "page_name" in \
raw_val_dict["params"] and "button_name" in raw_val_dict["params"] \
and "extra_param" in raw_val_dict["params"]:
if raw_val_dict["params"]["page_name"] == "search_detail" and \
raw_val_dict["params"]["button_name"] == "focus_tag":
tag_name = raw_val_dict["params"]["extra_param"]
device_id = raw_val_dict["device"]["device_id"]
user_id = raw_val_dict["user_id"] if "user_id" in raw_val_dict else None
tag_list = list(Tag.objects.using(settings.SLAVE1_DB_NAME).filter(name=tag_name,is_online=True,is_deleted=False, is_category=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
# 移植老用户的lin信息到ctr特征策略
self.transfer_old_info2ctr_feature_key(device_id)
# 更新不同策略的lin标签参数信息
for tag_id in click_topic_tag_list:
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature,
self.linucb_matrix_redis_prefix)
# 获取tag的ctr信息
device_tag_ctr = self.get_device_tag_ctr(device_id, tag_id)
user_feature_ctr = [device_tag_ctr, device_tag_ctr]
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature_ctr,
self.ctr_linucb_matrix_redis_prefix)
# 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,
linucb_matrix_prefix=self.linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.linucb_recommend_pictorial_id_prefix)
self.update_recommend_tag_list(device_id, user_feature, user_id,
click_topic_tag_list=click_topic_tag_list,
linucb_matrix_prefix=self.ctr_linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.ctr_linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.ctr_linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.ctr_linucb_recommend_pictorial_id_prefix)
# 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:
tag_query_results = list(Tag.objects.using(settings.SLAVE1_DB_NAME).filter(
id__in=tagid_list, is_online=True, is_deleted=False,
is_category=False).values_list("id",flat =True))
is_click = 1
is_vote = 0
reward = 1 if is_click or is_vote else 0
# 移植老用户的lin信息到ctr特征策略
self.transfer_old_info2ctr_feature_key(device_id)
for tag_id in tag_query_results:
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature,
self.linucb_matrix_redis_prefix)
# 获取tag的ctr信息
device_tag_ctr = self.get_device_tag_ctr(device_id, tag_id)
user_feature_ctr = [device_tag_ctr, device_tag_ctr]
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature_ctr,
self.ctr_linucb_matrix_redis_prefix)
# 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=tag_query_results,
linucb_matrix_prefix=self.linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.linucb_recommend_pictorial_id_prefix)
self.update_recommend_tag_list(device_id, user_feature, user_id,
new_user_click_tag_list=tag_query_results,
linucb_matrix_prefix=self.ctr_linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.ctr_linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.ctr_linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.ctr_linucb_recommend_pictorial_id_prefix)
else:
logging.warning("unknown type msg:%s" % raw_val_dict.get("type", "missing type"))
# 用户点击个性化push进linucb
elif "type" in raw_val_dict and raw_val_dict["type"] == "on_click_push":
# 后端已过滤，该tag_ids是帖子/榜单的编辑标签
if "tag_ids" in raw_val_dict["params"]:
tag_ids = raw_val_dict["params"]["tag_ids"]
else:
# todo 客户端埋点bug，后期移除
tag_ids = raw_val_dict["params"].get("tag_ids:", [])
if isinstance(tag_ids, str):
tagid_list = json.loads(tag_ids)
elif isinstance(tag_ids, list):
tagid_list = tag_ids
else:
tagid_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
if len(tagid_list) > 0:
tag_query_results = Tag.objects.using(settings.SLAVE1_DB_NAME).filter(
id__in=tagid_list, is_online=True, is_deleted=False,
is_category=False).values_list("id", flat=True)
is_click = 1
is_vote = 0
reward = 1 if is_click or is_vote else 0
for tag_id in tag_query_results:
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature,
self.linucb_matrix_redis_prefix)
# 获取tag的ctr信息
device_tag_ctr = self.get_device_tag_ctr(device_id, tag_id)
user_feature_ctr = [device_tag_ctr, device_tag_ctr]
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature_ctr,
self.ctr_linucb_matrix_redis_prefix)
self.update_recommend_tag_list(device_id, user_feature, user_id,
linucb_matrix_prefix=self.linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.linucb_recommend_pictorial_id_prefix)
self.update_recommend_tag_list(device_id, user_feature, user_id,
linucb_matrix_prefix=self.ctr_linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.ctr_linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.ctr_linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.ctr_linucb_recommend_pictorial_id_prefix)
logging.info("on_click_push topic type:%s, device_id:%s, tag_ids:%s" %
(raw_val_dict.get("type", "missing type"), str(device_id),
str(tagid_list)))
# 用户点击问题清单进linucb
elif b'content' in raw_val_dict:
data = json.loads(raw_val_dict[b'content'])
if 'SYS' in data and 'APP' in data and 'action' in data['SYS'] and data['SYS']['action'] == "venus/community/skin_check/submit_questions":
device_id = data['SYS']['cl_id']
tagid_list = list(data['APP'].get('answer_tag', []))
user_id = data['SYS'].get('user_id', None)
logging.info("skin_check topic type:%s, device_id:%s, answer_tag:%s" %
(str(data['SYS']['action']), str(device_id), str(tagid_list)))
if len(tagid_list) > 0:
tag_query_results = list(Tag.objects.using(settings.SLAVE1_DB_NAME).filter(
id__in=tagid_list, is_online=True, is_deleted=False,
is_category=False).values_list("id", flat=True))
tag_query_results_multi = [i for i in tagid_list if i in tag_query_results]
is_click = 1
is_vote = 0
reward = 1 if is_click or is_vote else 0
for i in range(5):
for tag_id in tag_query_results_multi:
self.update_user_linucb_tag_info(reward, device_id, tag_id, user_feature,
self.linucb_matrix_redis_prefix)
# 获取tag的ctr信息
device_tag_ctr = self.get_device_tag_ctr(device_id, tag_id)
user_feature_ctr = [device_tag_ctr, device_tag_ctr]
self.update_user_linucb_tag_info(reward, device_id, tag_id,
user_feature_ctr,
self.ctr_linucb_matrix_redis_prefix)
# 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,
linucb_matrix_prefix=self.linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.linucb_recommend_pictorial_id_prefix)
self.update_recommend_tag_list(device_id, user_feature, user_id,
linucb_matrix_prefix=self.ctr_linucb_matrix_redis_prefix,
linucb_recommend_tag_prefix=self.ctr_linucb_recommend_redis_prefix,
linucb_topic_ids_prefix=self.ctr_linucb_recommend_topic_id_prefix,
linucb_pictorial_ids_prefix=self.ctr_linucb_recommend_pictorial_id_prefix)
logging.info("skin_check topic type:%s, device_id:%s, tag_query_results:%s" %
(str(data['SYS']['action']), str(device_id), str(tag_query_results)))
else:
if msg:
logging.warning("unknown type msg:%s" % raw_val_dict.get("type", "missing type"))
except:
logging_exception()
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
# 假设数据库连接异常，强制退出程序，supervisor重启linub
os._exit(0)
return True
except:
logging_exception()
logging.error("catch exception,err_msg:%s" % traceback.format_exc())
return False