def _feed_articles(self, channel_id, timestamp, feed_count):
"""
获取推荐文章
:param channel_id: 频道id
:param feed_count: 推荐数量
:param timestamp: 时间戳
:return: [{article_id, trace_params}, ...], timestamp
"""
req = user_reco_pb2.User()
if g.user_id:
req.user_id = str(g.user_id)
elif g.anonymous_id:
req.user_id = str(g.anonymous_id)
else:
req.user_id = ''
req.channel_id = channel_id
req.article_num = feed_count
req.time_stamp = timestamp
stub = user_reco_pb2_grpc.UserRecommendStub(current_app.rpc_reco)
try:
resp = stub.user_recommend(req, timeout=5)
except Exception as e:
current_app.logger.error(e)
return [], timestamp
# 曝光埋点参数
trace_exposure = resp.exposure
if len(resp.recommends) > 0 and trace_exposure:
write_trace_log(trace_exposure, channel_id=channel_id)
return resp.recommends, resp.time_stamp
def _feed_articles(self, channel_id, feed_count):
"""
获取推荐文章
:param channel_id: 频道id
:param feed_count: 推荐数量
:return: [{article_id, trace_params}, ...]
"""
req = user_reco_pb2.User()
if g.user_id:
req.user_id = str(g.user_id)
elif g.anonymous_id:
req.user_id = str(g.anonymous_id)
else:
req.user_id = ''
req.channel_id = channel_id
req.article_num = feed_count
stub = user_reco_pb2_grpc.UserRecommendStub(current_app.rpc_reco)
resp = stub.user_recommend(req)
# 曝光埋点参数
trace_exposure = resp.exposure
write_trace_log(trace_exposure, channel_id=channel_id)
return resp.recommends
def post(self):
"""
用户收藏文章
"""
req_parser = RequestParser()
req_parser.add_argument('target', type=parser.article_id, required=True, location='json')
req_parser.add_argument('Trace', type=inputs.regex(r'^.+$'), required=False, location='headers')
args = req_parser.parse_args()
target = args.target
# 记录埋点日志
if args.Trace:
article = cache_article.ArticleInfoCache(target).get()
write_trace_log(args.Trace, channel_id=article['ch_id'])
ret = 1
try:
collection = Collection(user_id=g.user_id, article_id=target)
db.session.add(collection)
db.session.commit()
except IntegrityError:
db.session.rollback()
ret = Collection.query.filter_by(user_id=g.user_id, article_id=target, is_deleted=True) \
.update({'is_deleted': False})
db.session.commit()
if ret > 0:
cache_user.UserArticleCollectionsCache(g.user_id).clear()
cache_statistic.ArticleCollectingCountStorage.incr(target)
cache_statistic.UserArticleCollectingCountStorage.incr(g.user_id)
return {'target': target}, 201
def get(self, article_id):
"""
获取文章详情
:param article_id: int 文章id
"""
qs_parser = RequestParser()
qs_parser.add_argument('Trace',
type=inputs.regex(r'^.+$'),
required=False,
location='headers')
args = qs_parser.parse_args()
# 从缓存层中查询文章数据
article_cache = ArticleInfoCache(article_id)
if article_cache.exists():
article_dict = article_cache.get()
# 向埋点日志中写入推荐系统需要的埋点信息
if args.Trace:
write_trace_log(args.Trace)
# TODO 从缓存层中查询 文章内容/关注/评论/点赞情况
# TODO 通过RPC向推荐系统索取相关文章推荐
return article_dict
else:
return {'messsage': 'Invalid article'}, 400
def post(self):
req_parser = RequestParser()
req_parser.add_argument('Trace',
type=inputs.regex(r'^.+$'),
required=True,
location='headers')
req_parser.add_argument('duration',
type=inputs.natural,
required=True,
location='json')
req_parser.add_argument('art_id',
type=parser.article_id,
required=True,
location='json')
args = req_parser.parse_args()
article = cache_article.ArticleInfoCache(args.art_id).get()
write_trace_log(args.Trace, args.duration, channel_id=article['ch_id'])
return {'message': 'OK'}, 201
def get(self, article_id):
"""
获取文章详情
:param article_id: int 文章id
"""
# 写入埋点日志
qs_parser = RequestParser()
qs_parser.add_argument('Trace', type=inputs.regex(r'^.+$'), required=False, location='headers')
args = qs_parser.parse_args()
user_id = g.user_id
# 查询文章数据
exist = cache_article.ArticleInfoCache(article_id).exists()
if not exist:
abort(404, message='The article does not exist.')
article = cache_article.ArticleDetailCache(article_id).get()
# 推荐系统所需埋点
if args.Trace:
write_trace_log(args.Trace, channel_id=article['ch_id'])
article['is_followed'] = False
article['attitude'] = None
# 增加用户是否收藏了文章
article['is_collected'] = False
if user_id:
# 非匿名用户添加用户的阅读历史
try:
cache_user.UserReadingHistoryStorage(user_id).save(article_id)
except ConnectionError as e:
current_app.logger.error(e)
# 查询关注
# article['is_followed'] = cache_user.UserFollowingCache(user_id).determine_follows_target(article['aut_id'])
article['is_followed'] = cache_user.UserRelationshipCache(user_id).determine_follows_target(article['aut_id'])
# 查询登录用户对文章的态度（点赞or不喜欢）
try:
# article['attitude'] = cache_article.ArticleUserAttitudeCache(user_id, article_id).get()
article['attitude'] = cache_user.UserArticleAttitudeCache(user_id).get_article_attitude(article_id)
except SQLAlchemyError as e:
current_app.logger.error(e)
article['attitude'] = -1
# 增加用户是否收藏了文章
article['is_collected'] = cache_user.UserArticleCollectionsCache(g.user_id).determine_collect_target(article_id)
# 获取相关文章推荐
article['recomments'] = []
try:
similar_articles = self._feed_similar_articles(article_id)
for _article_id in similar_articles:
_article = cache_article.ArticleInfoCache(_article_id).get()
article['recomments'].append({
'art_id': _article['art_id'],
'title': _article['title']
})
except Exception as e:
current_app.logger.error(e)
# 更新阅读数
cache_statistic.ArticleReadingCountStorage.incr(article_id)
cache_statistic.UserArticlesReadingCountStorage.incr(article['aut_id'])
return article