rov-server/recommend.py

import time
import multiprocessing
import traceback

from datetime import datetime
from log import Log
from config import set_config
from video_recall import PoolRecall
from video_rank import video_rank, bottom_strategy
from db_helper import RedisHelper
import gevent

log_ = Log()
config_ = set_config()


def video_recommend(mid, uid, size, app_type, algo_type):
    """
    首页线上推荐逻辑
    :param mid: mid type-string
    :param uid: uid type-string
    :param size: 请求视频数量 type-int
    :param app_type: 产品标识  type-int
    :param algo_type: 算法类型  type-string
    :return:
    """
    ab_code = config_.AB_CODE
    # ####### 多进程召回
    start_recall = time.time()
    log_.info('====== recall')
    '''     
    cores = multiprocessing.cpu_count()
    pool = multiprocessing.Pool(processes=cores)
    pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code)
    _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
    pool_list = [
        # rov召回池
        pool.apply_async(pool_recall.rov_pool_recall, (size,)),
        # 流量池
        pool.apply_async(pool_recall.flow_pool_recall, (size,))
    ]
    recall_result_list = [p.get() for p in pool_list]
    pool.close()
    pool.join()
    '''
    recall_result_list = []
    pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code)
    _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
    t = [gevent.spawn(pool_recall.rov_pool_recall, size), gevent.spawn(pool_recall.flow_pool_recall, size) ]
    gevent.joinall(t)
    recall_result_list = [i.get() for i in t]

    end_recall = time.time()
    log_.info('mid: {}, uid: {}, recall: {}, execute time = {}ms'.format(
        mid, uid, recall_result_list, (end_recall - start_recall) * 1000))

    # ####### 排序
    start_rank = time.time()
    log_.info('====== rank')
    data = {
        'rov_pool_recall': recall_result_list[0],
        'flow_pool_recall': recall_result_list[1]
    }
    rank_result = video_rank(data=data, size=size)
    end_rank = time.time()
    log_.info('mid: {}, uid: {}, rank_result: {}, execute time = {}ms'.format(
        mid, uid, rank_result, (end_rank - start_rank) * 1000))

    if not rank_result:
        # 兜底策略
        log_.info('====== bottom strategy')
        start_bottom = time.time()
        rank_result = bottom_strategy(size=size, app_type=app_type, ab_code=ab_code)
        end_bottom = time.time()
        log_.info('mid: {}, uid: {}, bottom strategy result: {}, execute time = {}ms'.format(
            mid, uid, rank_result, (end_bottom - start_bottom) * 1000))

    # ####### redis数据刷新
    log_.info('====== update redis')
    # 预曝光数据同步刷新到Redis, 过期时间为0.5h
    redis_helper = RedisHelper()
    preview_key_name = config_.PREVIEW_KEY_PREFIX + '{}.{}'.format(app_type, mid)
    preview_video_ids = [int(item['videoId']) for item in rank_result]
    if preview_video_ids:
        log_.error('key_name = {} \n values = {}'.format(preview_key_name, tuple(preview_video_ids)))
        redis_helper.add_data_with_set(key_name=preview_key_name, values=tuple(preview_video_ids), expire_time=30*60)
        log_.info('preview redis update success!')

    # 将此次获取的ROV召回池config_.K末位视频id同步刷新到Redis中，方便下次快速定位到召回位置，过期时间为1天
    rov_recall_video = [item['videoId'] for item in rank_result if item['pushFrom'] == 'recall_pool']
    if 0 < len(rov_recall_video) <= config_.K:
        redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[-1])
    elif len(rov_recall_video) > config_.K:
        redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[config_.K - 1])
    log_.info('last video redis update success!')

    # 将此次分发的流量池视频，对 本地分发数-1 进行记录
    flow_recall_video = [item for item in rank_result if item['pushFrom'] == 'flow_pool']
    if flow_recall_video:
        update_local_distribute_count(flow_recall_video)
        log_.info('update local distribute count success!')

    return rank_result


def update_local_distribute_count(videos):
    """
    更新本地分发数
    :param videos: 视频列表 type-list [{'videoId':'', 'flowPool':'', 'distributeCount': '',
                                    'rovScore': '', 'pushFrom': 'flow_pool', 'abCode': self.ab_code}, ....]
    :return:
    """
    try:
        redis_helper = RedisHelper()
        for item in videos:
            key_name = '{}{}.{}'.format(config_.LOCAL_DISTRIBUTE_COUNT_PREFIX, item['videoId'], item['flowPool'])
            # 本地记录的分发数 - 1
            redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)

            # if redis_helper.key_exists(key_name=key_name):
            #     # 该视频本地有记录，本地记录的分发数 - 1
            #     redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
            # else:
            #     # 该视频本地无记录，接口获取的分发数 - 1
            #     redis_helper.incr_key(key_name=key_name, amount=int(item['distributeCount']) - 1, expire_time=5 * 60)

    except Exception as e:
        log_.error('update_local_distribute_count error...')
        log_.error(traceback.format_exc())


def video_relevant_recommend(mid, uid, size, app_type):
    """
    相关推荐逻辑
    :param mid: mid type-string
    :param uid: uid type-string
    :param size: 请求视频数量 type-int
    :param app_type: 产品标识  type-int
    :param algo_type: 算法类型  type-string
    :return: videos type-list
    """
    videos = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type, algo_type='')
    return videos


if __name__ == '__main__':
    videos = [{'videoId': '12345', 'flowPool': '133#442#2', 'distributeCount': 10}]
    update_local_distribute_count(videos)