recommend.py 54 KB

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  1. import json
  2. import time
  3. import multiprocessing
  4. import traceback
  5. import hashlib
  6. from datetime import datetime
  7. import config
  8. from log import Log
  9. from config import set_config
  10. from video_recall import PoolRecall
  11. from video_rank import video_rank, bottom_strategy, video_rank_by_w_h_rate, video_rank_with_old_video, bottom_strategy2
  12. from db_helper import RedisHelper
  13. import gevent
  14. from utils import FilterVideos
  15. import ast
  16. log_ = Log()
  17. config_ = set_config()
  18. def relevant_video_top_recommend(request_id, app_type, mid, uid, head_vid, videos, size):
  19. """
  20. 相关推荐强插 运营给定置顶相关性视频
  21. :param request_id: request_id
  22. :param app_type: 产品标识 type-int
  23. :param mid: mid
  24. :param uid: uid
  25. :param head_vid: 相关推荐头部视频id type-int
  26. :param videos: 当前相关推荐结果 type-list
  27. :param size: 返回视频个数 type-int
  28. :return: rank_result
  29. """
  30. # 获取头部视频对应的相关性视频
  31. key_name = '{}{}'.format(config_.RELEVANT_VIDEOS_WITH_OP_KEY_NAME, head_vid)
  32. redis_helper = RedisHelper()
  33. relevant_videos = redis_helper.get_data_from_redis(key_name=key_name)
  34. if relevant_videos is None:
  35. # 该视频没有指定的相关性视频
  36. return videos
  37. relevant_videos = json.loads(relevant_videos)
  38. # 按照指定顺序排序
  39. relevant_videos_sorted = sorted(relevant_videos, key=lambda x: x['order'], reverse=False)
  40. # 过滤
  41. relevant_video_ids = [int(item['recommend_vid']) for item in relevant_videos_sorted]
  42. filter_helper = FilterVideos(request_id=request_id, app_type=app_type, video_ids=relevant_video_ids, mid=mid, uid=uid)
  43. filtered_ids = filter_helper.filter_videos()
  44. if filtered_ids is None:
  45. return videos
  46. # 获取生效中的视频
  47. now = int(time.time())
  48. relevant_videos_in_effect = [
  49. {'videoId': int(item['recommend_vid']), 'pushFrom': config_.PUSH_FROM['relevant_video_op'],
  50. 'abCode': config_.AB_CODE['relevant_video_op']}
  51. for item in relevant_videos_sorted
  52. if item['start_time'] < now < item['finish_time'] and int(item['recommend_vid']) in filtered_ids
  53. ]
  54. if len(relevant_videos_in_effect) == 0:
  55. return videos
  56. # 与现有排序结果 进行合并重排
  57. # 获取现有排序结果中流量池视频 及其位置
  58. relevant_ids = [item['videoId'] for item in relevant_videos_in_effect]
  59. flow_pool_videos = []
  60. other_videos = []
  61. for i, item in enumerate(videos):
  62. if item.get('pushFrom', None) == config_.PUSH_FROM['flow_recall'] and item.get('videoId') not in relevant_ids:
  63. flow_pool_videos.append((i, item))
  64. elif item.get('videoId') not in relevant_ids:
  65. other_videos.append(item)
  66. else:
  67. continue
  68. # 重排,保持流量池视频位置不变
  69. rank_result = relevant_videos_in_effect + other_videos
  70. for i, item in flow_pool_videos:
  71. rank_result.insert(i, item)
  72. return rank_result[:size]
  73. def video_position_recommend(request_id, mid, uid, app_type, videos):
  74. # videos = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  75. # algo_type=algo_type, client_info=client_info)
  76. redis_helper = RedisHelper()
  77. pos1_vids = redis_helper.get_data_from_redis(config.BaseConfig.RECALL_POSITION1_KEY_NAME)
  78. pos2_vids = redis_helper.get_data_from_redis(config.BaseConfig.RECALL_POSITION2_KEY_NAME)
  79. if pos1_vids is not None:
  80. pos1_vids = ast.literal_eval(pos1_vids)
  81. if pos2_vids is not None:
  82. pos2_vids = ast.literal_eval(pos2_vids)
  83. pos1_vids = [] if pos1_vids is None else pos1_vids
  84. pos2_vids = [] if pos2_vids is None else pos2_vids
  85. pos1_vids = [int(i) for i in pos1_vids]
  86. pos2_vids = [int(i) for i in pos2_vids]
  87. filter_1 = FilterVideos(request_id=request_id, app_type=app_type, video_ids=pos1_vids, mid=mid, uid=uid)
  88. filter_2 = FilterVideos(request_id=request_id, app_type=app_type, video_ids=pos2_vids, mid=mid, uid=uid)
  89. t = [gevent.spawn(filter_1.filter_videos), gevent.spawn(filter_2.filter_videos)]
  90. gevent.joinall(t)
  91. filted_list = [i.get() for i in t]
  92. pos1_vids = filted_list[0]
  93. pos2_vids = filted_list[1]
  94. videos = positon_duplicate(pos1_vids, pos2_vids, videos)
  95. if pos1_vids is not None and len(pos1_vids) >0 :
  96. videos.insert(0, {'videoId': int(pos1_vids[0]), 'rovScore': 100,
  97. 'pushFrom': config_.PUSH_FROM['position_insert'], 'abCode': config_.AB_CODE['position_insert']})
  98. if pos2_vids is not None and len(pos2_vids) >0 :
  99. videos.insert(1, {'videoId': int(pos2_vids[0]), 'rovScore': 100,
  100. 'pushFrom': config_.PUSH_FROM['position_insert'], 'abCode': config_.AB_CODE['position_insert']})
  101. return videos[:10]
  102. def positon_duplicate(pos1_vids, pos2_vids, videos):
  103. s = set()
  104. if pos1_vids is not None and len(pos1_vids) >0:
  105. s.add(int(pos1_vids[0]))
  106. if pos2_vids is not None and len(pos2_vids) >0:
  107. s.add(int(pos2_vids[0]))
  108. l = []
  109. for item in videos:
  110. if item['videoId'] in s:
  111. continue
  112. else:
  113. l.append(item)
  114. return l
  115. def video_recommend(request_id, mid, uid, size, top_K, flow_pool_P, app_type, algo_type, client_info,
  116. expire_time=24*3600, ab_code=config_.AB_CODE['initial'], rule_key='', data_key='',
  117. no_op_flag=False, old_video_index=-1, video_id=None, params=None):
  118. """
  119. 首页线上推荐逻辑
  120. :param request_id: request_id
  121. :param mid: mid type-string
  122. :param uid: uid type-string
  123. :param size: 请求视频数量 type-int
  124. :param top_K: 保证topK为召回池视频 type-int
  125. :param flow_pool_P: size-top_K视频为流量池视频的概率 type-float
  126. :param app_type: 产品标识 type-int
  127. :param algo_type: 算法类型 type-string
  128. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  129. :param expire_time: 末位视频记录redis过期时间
  130. :param ab_code: AB实验code
  131. :param video_id: 相关推荐头部视频id
  132. :param params:
  133. :return:
  134. """
  135. # ####### 多进程召回
  136. start_recall = time.time()
  137. # log_.info('====== recall')
  138. '''
  139. cores = multiprocessing.cpu_count()
  140. pool = multiprocessing.Pool(processes=cores)
  141. pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code)
  142. _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  143. pool_list = [
  144. # rov召回池
  145. pool.apply_async(pool_recall.rov_pool_recall, (size,)),
  146. # 流量池
  147. pool.apply_async(pool_recall.flow_pool_recall, (size,))
  148. ]
  149. recall_result_list = [p.get() for p in pool_list]
  150. pool.close()
  151. pool.join()
  152. '''
  153. recall_result_list = []
  154. pool_recall = PoolRecall(request_id=request_id,
  155. app_type=app_type, mid=mid, uid=uid, ab_code=ab_code,
  156. client_info=client_info, rule_key=rule_key, data_key=data_key, no_op_flag=no_op_flag,
  157. params=params)
  158. _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  159. # # 小时级实验
  160. # if ab_code in [code for _, code in config_.AB_CODE['rank_by_h'].items()]:
  161. # t = [gevent.spawn(pool_recall.rule_recall_by_h, size, expire_time),
  162. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  163. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  164. # # 小时级实验
  165. # elif ab_code in [code for _, code in config_.AB_CODE['rank_by_24h'].items()]:
  166. # t = [gevent.spawn(pool_recall.rov_pool_recall_by_h, size, expire_time),
  167. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  168. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  169. # 地域分组实验
  170. if ab_code in [code for _, code in config_.AB_CODE['region_rank_by_h'].items()]:
  171. if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  172. t = [gevent.spawn(pool_recall.rov_pool_recall_with_region, size, expire_time)]
  173. else:
  174. t = [gevent.spawn(pool_recall.rov_pool_recall_with_region, size, expire_time),
  175. gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  176. gevent.spawn(pool_recall.flow_pool_recall, size)]
  177. # 最惊奇相关推荐实验
  178. # elif ab_code == config_.AB_CODE['top_video_relevant_appType_19']:
  179. # t = [gevent.spawn(pool_recall.relevant_recall_19, video_id, size, expire_time),
  180. # gevent.spawn(pool_recall.flow_pool_recall_18_19, size)]
  181. # 最惊奇完整影视实验
  182. # elif ab_code == config_.AB_CODE['whole_movies']:
  183. # t = [gevent.spawn(pool_recall.rov_pool_recall_19, size, expire_time)]
  184. # 最惊奇/老好看实验
  185. # elif app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  186. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  187. # gevent.spawn(pool_recall.flow_pool_recall_18_19, size)]
  188. # # 天级实验
  189. # elif ab_code in [code for _, code in config_.AB_CODE['rank_by_day'].items()]:
  190. # t = [gevent.spawn(pool_recall.rov_pool_recall_by_day, size, expire_time),
  191. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  192. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  193. # 老视频实验
  194. # elif ab_code in [config_.AB_CODE['old_video']]:
  195. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  196. # gevent.spawn(pool_recall.flow_pool_recall, size),
  197. # gevent.spawn(pool_recall.old_videos_recall, size)]
  198. else:
  199. if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  200. t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time)]
  201. else:
  202. t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  203. gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  204. gevent.spawn(pool_recall.flow_pool_recall, size)]
  205. gevent.joinall(t)
  206. recall_result_list = [i.get() for i in t]
  207. # end_recall = time.time()
  208. log_.info({
  209. 'logTimestamp': int(time.time() * 1000),
  210. 'request_id': request_id,
  211. 'mid': mid,
  212. 'uid': uid,
  213. 'operation': 'recall',
  214. 'recall_result': recall_result_list,
  215. 'executeTime': (time.time() - start_recall) * 1000
  216. })
  217. # ####### 排序
  218. start_rank = time.time()
  219. # log_.info('====== rank')
  220. if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  221. if ab_code in [
  222. config_.AB_CODE['rov_rank_appType_18_19'],
  223. config_.AB_CODE['rov_rank_appType_19'],
  224. config_.AB_CODE['top_video_relevant_appType_19']
  225. ]:
  226. data = {
  227. 'rov_pool_recall': recall_result_list[0],
  228. 'flow_pool_recall': recall_result_list[1]
  229. }
  230. else:
  231. data = {
  232. 'rov_pool_recall': recall_result_list[0],
  233. 'flow_pool_recall': []
  234. }
  235. else:
  236. if recall_result_list[1]:
  237. redis_helper = RedisHelper()
  238. quick_flow_pool_P = redis_helper.get_data_from_redis(
  239. key_name=f"{config_.QUICK_FLOWPOOL_DISTRIBUTE_RATE_KEY_NAME_PREFIX}{config_.QUICK_FLOW_POOL_ID}"
  240. )
  241. if quick_flow_pool_P:
  242. flow_pool_P = quick_flow_pool_P
  243. data = {
  244. 'rov_pool_recall': recall_result_list[0],
  245. 'flow_pool_recall': recall_result_list[1]
  246. }
  247. else:
  248. data = {
  249. 'rov_pool_recall': recall_result_list[0],
  250. 'flow_pool_recall': recall_result_list[2]
  251. }
  252. rank_result = video_rank(data=data, size=size, top_K=top_K, flow_pool_P=float(flow_pool_P))
  253. # 老视频实验
  254. # if ab_code in [config_.AB_CODE['old_video']]:
  255. # rank_result = video_rank_with_old_video(rank_result=rank_result, old_video_recall=recall_result_list[2],
  256. # size=size, top_K=top_K, old_video_index=old_video_index)
  257. # end_rank = time.time()
  258. log_.info({
  259. 'logTimestamp': int(time.time() * 1000),
  260. 'request_id': request_id,
  261. 'mid': mid,
  262. 'uid': uid,
  263. 'operation': 'rank',
  264. 'rank_result': rank_result,
  265. 'executeTime': (time.time() - start_rank) * 1000
  266. })
  267. if not rank_result:
  268. # 兜底策略
  269. # log_.info('====== bottom strategy')
  270. start_bottom = time.time()
  271. if ab_code == config_.AB_CODE['region_rank_by_h'].get('abtest_130'):
  272. rank_result = bottom_strategy2(size=size, app_type=app_type, mid=mid, ab_code=ab_code, params=params)
  273. else:
  274. rank_result = bottom_strategy(
  275. request_id=request_id, size=size, app_type=app_type, ab_code=ab_code, params=params
  276. )
  277. log_.info({
  278. 'logTimestamp': int(time.time() * 1000),
  279. 'request_id': request_id,
  280. 'mid': mid,
  281. 'uid': uid,
  282. 'operation': 'bottom',
  283. 'bottom_result': rank_result,
  284. 'executeTime': (time.time() - start_bottom) * 1000
  285. })
  286. return rank_result, last_rov_recall_key
  287. def ab_test_op(rank_result, ab_code_list, app_type, mid, uid, **kwargs):
  288. """
  289. 对排序后的结果 按照AB实验进行对应的分组操作
  290. :param rank_result: 排序后的结果
  291. :param ab_code_list: 此次请求参与的 ab实验组
  292. :param app_type: 产品标识
  293. :param mid: mid
  294. :param uid: uid
  295. :param kwargs: 其他参数
  296. :return:
  297. """
  298. # ####### 视频宽高比AB实验
  299. # 对内容精选进行 视频宽高比分发实验
  300. # if config_.AB_CODE['w_h_rate'] in ab_code_list and app_type in config_.AB_TEST.get('w_h_rate', []):
  301. # rank_result = video_rank_by_w_h_rate(videos=rank_result)
  302. # log_.info('app_type: {}, mid: {}, uid: {}, rank_by_w_h_rate_result: {}'.format(
  303. # app_type, mid, uid, rank_result))
  304. # 按position位置排序
  305. if config_.AB_CODE['position_insert'] in ab_code_list and app_type in config_.AB_TEST.get('position_insert', []):
  306. rank_result = video_position_recommend(mid, uid, app_type, rank_result)
  307. print('===========================')
  308. print(rank_result)
  309. log_.info('app_type: {}, mid: {}, uid: {}, rank_by_position_insert_result: {}'.format(
  310. app_type, mid, uid, rank_result))
  311. # 相关推荐强插
  312. # if config_.AB_CODE['relevant_video_op'] in ab_code_list \
  313. # and app_type in config_.AB_TEST.get('relevant_video_op', []):
  314. # head_vid = kwargs['head_vid']
  315. # size = kwargs['size']
  316. # rank_result = relevant_video_top_recommend(
  317. # app_type=app_type, mid=mid, uid=uid, head_vid=head_vid, videos=rank_result, size=size
  318. # )
  319. # log_.info('app_type: {}, mid: {}, uid: {}, head_vid: {}, rank_by_relevant_video_op_result: {}'.format(
  320. # app_type, mid, uid, head_vid, rank_result))
  321. return rank_result
  322. def update_redis_data(result, app_type, mid, last_rov_recall_key, top_K, expire_time=24*3600):
  323. """
  324. 根据最终的排序结果更新相关redis数据
  325. :param result: 排序结果
  326. :param app_type: 产品标识
  327. :param mid: mid
  328. :param last_rov_recall_key: 用户上一次在rov召回池对应的位置 redis key
  329. :param top_K: 保证topK为召回池视频 type-int
  330. :param expire_time: 末位视频记录redis过期时间
  331. :return: None
  332. """
  333. # ####### redis数据刷新
  334. try:
  335. redis_helper = RedisHelper()
  336. # log_.info('====== update redis')
  337. if mid and mid != 'null':
  338. # mid为空时,不做预曝光和定位数据更新
  339. # 预曝光数据同步刷新到Redis, 过期时间为0.5h
  340. preview_key_name = f"{config_.PREVIEW_KEY_PREFIX}{app_type}:{mid}"
  341. preview_video_ids = [int(item['videoId']) for item in result]
  342. if preview_video_ids:
  343. # log_.error('key_name = {} \n values = {}'.format(preview_key_name, tuple(preview_video_ids)))
  344. redis_helper.add_data_with_set(key_name=preview_key_name, values=tuple(preview_video_ids), expire_time=30 * 60)
  345. # log_.info('preview redis update success!')
  346. # 将此次获取的ROV召回池top_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
  347. rov_recall_video = [item['videoId'] for item in result[:top_K]
  348. if item['pushFrom'] == config_.PUSH_FROM['rov_recall']]
  349. if len(rov_recall_video) > 0:
  350. if app_type == config_.APP_TYPE['APP']:
  351. key_name = config_.UPDATE_ROV_KEY_NAME_APP
  352. else:
  353. key_name = config_.UPDATE_ROV_KEY_NAME
  354. if not redis_helper.get_score_with_value(key_name=key_name, value=rov_recall_video[-1]):
  355. redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[-1],
  356. expire_time=expire_time)
  357. # log_.info('last video redis update success!')
  358. # 将此次获取的 地域分组小时级数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  359. rov_recall_h_video = [item['videoId'] for item in result[:top_K]
  360. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_h']]
  361. if len(rov_recall_h_video) > 0:
  362. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_H_PREFIX}{app_type}:{mid}'
  363. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_h_video[-1],
  364. expire_time=expire_time)
  365. # 将此次获取的 地域分组相对24h数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  366. rov_recall_24h_dup1_video = [item['videoId'] for item in result[:top_K]
  367. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_24h']]
  368. if len(rov_recall_24h_dup1_video) > 0:
  369. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP1_24H_PREFIX}{app_type}:{mid}'
  370. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup1_video[-1],
  371. expire_time=expire_time)
  372. # 将此次获取的 相对24h筛选数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  373. rov_recall_24h_dup2_video = [item['videoId'] for item in result[:top_K]
  374. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h']]
  375. if len(rov_recall_24h_dup2_video) > 0:
  376. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_24H_PREFIX}{app_type}:{mid}'
  377. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup2_video[-1],
  378. expire_time=expire_time)
  379. # 将此次获取的 相对24h筛选后剩余数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  380. rov_recall_24h_dup3_video = [item['videoId'] for item in result[:top_K]
  381. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h_dup']]
  382. if len(rov_recall_24h_dup3_video) > 0:
  383. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_24H_PREFIX}{app_type}:{mid}'
  384. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup3_video[-1],
  385. expire_time=expire_time)
  386. # 将此次获取的 相对48h筛选数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  387. rov_recall_48h_dup2_video = [item['videoId'] for item in result[:top_K]
  388. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h']]
  389. if len(rov_recall_48h_dup2_video) > 0:
  390. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_48H_PREFIX}{app_type}:{mid}'
  391. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup2_video[-1],
  392. expire_time=expire_time)
  393. # 将此次获取的 相对48h筛选后剩余数据列表 中的视频id同步刷新到redis中,方便下次快速定位到召回位置
  394. rov_recall_48h_dup3_video = [item['videoId'] for item in result[:top_K]
  395. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h_dup']]
  396. if len(rov_recall_48h_dup3_video) > 0:
  397. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_48H_PREFIX}{app_type}:{mid}'
  398. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup3_video[-1],
  399. expire_time=expire_time)
  400. # 将此次分发的流量池视频,对 本地分发数-1 进行记录
  401. if app_type not in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  402. flow_recall_video = [item for item in result if item['pushFrom'] == config_.PUSH_FROM['flow_recall']]
  403. if flow_recall_video:
  404. update_local_distribute_count(flow_recall_video)
  405. # log_.info('update local distribute count success!')
  406. # 限流视频分发数记录
  407. if app_type == config_.APP_TYPE['APP']:
  408. # APP 不计入
  409. return
  410. limit_video_id_list = redis_helper.get_data_from_set(
  411. key_name=f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_SET}{datetime.today().strftime('%Y%m%d')}"
  412. )
  413. if limit_video_id_list is not None:
  414. limit_video_id_list = [int(item) for item in limit_video_id_list]
  415. for item in result:
  416. video_id = item['videoId']
  417. if video_id in limit_video_id_list:
  418. key_name = f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_DISTRIBUTE_COUNT}{video_id}"
  419. redis_helper.setnx_key(key_name=key_name, value=0, expire_time=24*2600)
  420. redis_helper.incr_key(key_name=key_name, amount=1, expire_time=24*3600)
  421. except Exception as e:
  422. log_.error("update redis data fail!")
  423. log_.error(traceback.format_exc())
  424. def update_local_distribute_count(videos):
  425. """
  426. 更新本地分发数
  427. :param videos: 视频列表 type-list [{'videoId':'', 'flowPool':'', 'distributeCount': '',
  428. 'rovScore': '', 'pushFrom': 'flow_pool', 'abCode': self.ab_code}, ....]
  429. :return:
  430. """
  431. try:
  432. redis_helper = RedisHelper()
  433. for item in videos:
  434. key_name = f"{config_.LOCAL_DISTRIBUTE_COUNT_PREFIX}{item['videoId']}:{item['flowPool']}"
  435. # 本地记录的分发数 - 1
  436. redis_helper.decr_key(key_name=key_name, amount=1, expire_time=15 * 60)
  437. # if redis_helper.key_exists(key_name=key_name):
  438. # # 该视频本地有记录,本地记录的分发数 - 1
  439. # redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
  440. # else:
  441. # # 该视频本地无记录,接口获取的分发数 - 1
  442. # redis_helper.incr_key(key_name=key_name, amount=int(item['distributeCount']) - 1, expire_time=5 * 60)
  443. except Exception as e:
  444. log_.error('update_local_distribute_count error...')
  445. log_.error(traceback.format_exc())
  446. def get_recommend_params(recommend_type, ab_exp_info, ab_info_data, page_type=0):
  447. """
  448. 根据实验分组给定对应的推荐参数
  449. :param recommend_type: 首页推荐和相关推荐区分参数(0-首页推荐,1-相关推荐)
  450. :param ab_exp_info: AB实验组参数
  451. :param ab_info_data: app实验组参数
  452. :param page_type: 页面区分参数,默认:0(首页)
  453. :return:
  454. """
  455. top_K = config_.K
  456. flow_pool_P = config_.P
  457. # 不获取人工干预数据标记
  458. no_op_flag = False
  459. old_video_index = -1
  460. # if not ab_exp_info:
  461. # ab_code = config_.AB_CODE['initial']
  462. # expire_time = 24 * 3600
  463. # rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  464. # data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  465. # # old_video_index = -1
  466. # else:
  467. # 默认使用 095 实验的配置
  468. ab_code = config_.AB_EXP_CODE['095'].get('ab_code')
  469. expire_time = 3600
  470. rule_key = config_.AB_EXP_CODE['095'].get('rule_key')
  471. data_key = config_.AB_EXP_CODE['095'].get('data_key')
  472. no_op_flag = True
  473. # 获取实验配置
  474. if ab_exp_info:
  475. ab_exp_code_list = []
  476. config_value_dict = {}
  477. for _, item in ab_exp_info.items():
  478. if not item:
  479. continue
  480. for ab_item in item:
  481. ab_exp_code = ab_item.get('abExpCode', None)
  482. if not ab_exp_code:
  483. continue
  484. ab_exp_code_list.append(str(ab_exp_code))
  485. config_value_dict[str(ab_exp_code)] = ab_item.get('configValue', None)
  486. for code, param in config_.AB_EXP_CODE.items():
  487. if code in ab_exp_code_list:
  488. ab_code = param.get('ab_code')
  489. expire_time = 3600
  490. rule_key = param.get('rule_key')
  491. data_key = param.get('data_key')
  492. no_op_flag = True
  493. break
  494. """
  495. # 推荐条数 10->4 实验
  496. # if config_.AB_EXP_CODE['rec_size_home'] in ab_exp_code_list:
  497. # config_value = config_value_dict.get(config_.AB_EXP_CODE['rec_size_home'], None)
  498. # if config_value:
  499. # config_value = eval(str(config_value))
  500. # else:
  501. # config_value = {}
  502. # log_.info(f'config_value: {config_value}, type: {type(config_value)}')
  503. # size = int(config_value.get('size', 4))
  504. # top_K = int(config_value.get('K', 3))
  505. # flow_pool_P = float(config_value.get('P', 0.3))
  506. # else:
  507. # size = size
  508. # top_K = config_.K
  509. # flow_pool_P = config_.P
  510. # 算法实验相对对照组
  511. # if config_.AB_EXP_CODE['ab_initial'] in ab_exp_code_list:
  512. # ab_code = config_.AB_CODE['ab_initial']
  513. # expire_time = 24 * 3600
  514. # rule_key = config_.RULE_KEY['initial']
  515. # no_op_flag = True
  516. # 小时级更新-规则1 实验
  517. # elif config_.AB_EXP_CODE['rule_rank1'] in ab_exp_code_list:
  518. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank1')
  519. # expire_time = 3600
  520. # rule_key = config_.RULE_KEY['rule_rank1']
  521. # no_op_flag = True
  522. # elif config_.AB_EXP_CODE['rule_rank2'] in ab_exp_code_list:
  523. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank2')
  524. # expire_time = 3600
  525. # rule_key = config_.RULE_KEY['rule_rank2']
  526. # elif config_.AB_EXP_CODE['rule_rank3'] in ab_exp_code_list:
  527. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank3')
  528. # expire_time = 3600
  529. # rule_key = config_.RULE_KEY['rule_rank3']
  530. # no_op_flag = True
  531. # elif config_.AB_EXP_CODE['rule_rank4'] in ab_exp_code_list:
  532. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank4')
  533. # expire_time = 3600
  534. # rule_key = config_.RULE_KEY['rule_rank4']
  535. # elif config_.AB_EXP_CODE['rule_rank5'] in ab_exp_code_list:
  536. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank5')
  537. # expire_time = 3600
  538. # rule_key = config_.RULE_KEY['rule_rank5']
  539. # elif config_.AB_EXP_CODE['day_rule_rank1'] in ab_exp_code_list:
  540. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank1')
  541. # expire_time = 24 * 3600
  542. # rule_key = config_.RULE_KEY_DAY['day_rule_rank1']
  543. # no_op_flag = True
  544. # if config_.AB_EXP_CODE['rule_rank6'] in ab_exp_code_list:
  545. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank6')
  546. # expire_time = 3600
  547. # rule_key = config_.RULE_KEY['rule_rank6']
  548. # no_op_flag = True
  549. # elif config_.AB_EXP_CODE['day_rule_rank2'] in ab_exp_code_list:
  550. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank2')
  551. # expire_time = 24 * 3600
  552. # rule_key = config_.RULE_KEY_DAY['day_rule_rank2']
  553. # no_op_flag = True
  554. # elif config_.AB_EXP_CODE['region_rule_rank1'] in ab_exp_code_list:
  555. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank1')
  556. # expire_time = 3600
  557. # rule_key = config_.RULE_KEY_REGION['region_rule_rank1']
  558. # no_op_flag = True
  559. # elif config_.AB_EXP_CODE['24h_rule_rank1'] in ab_exp_code_list:
  560. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank1')
  561. # expire_time = 3600
  562. # rule_key = config_.RULE_KEY_24H['24h_rule_rank1']
  563. # no_op_flag = True
  564. # elif config_.AB_EXP_CODE['24h_rule_rank2'] in ab_exp_code_list:
  565. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank2')
  566. # expire_time = 3600
  567. # rule_key = config_.RULE_KEY_24H['24h_rule_rank2']
  568. # no_op_flag = True
  569. # elif config_.AB_EXP_CODE['region_rule_rank2'] in ab_exp_code_list:
  570. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank2')
  571. # expire_time = 3600
  572. # rule_key = config_.RULE_KEY_REGION['region_rule_rank2']
  573. # no_op_flag = True
  574. # if config_.AB_EXP_CODE['region_rule_rank3'] in ab_exp_code_list or\
  575. # config_.AB_EXP_CODE['region_rule_rank3_appType_19'] in ab_exp_code_list or\
  576. # config_.AB_EXP_CODE['region_rule_rank3_appType_4'] in ab_exp_code_list or\
  577. # config_.AB_EXP_CODE['region_rule_rank3_appType_6'] in ab_exp_code_list or\
  578. # config_.AB_EXP_CODE['region_rule_rank3_appType_18'] in ab_exp_code_list:
  579. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3')
  580. # expire_time = 3600
  581. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('rule_key')
  582. # data_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('data_key')
  583. # no_op_flag = True
  584. # if config_.AB_EXP_CODE['region_rule_rank4'] in ab_exp_code_list or\
  585. if config_.AB_EXP_CODE['region_rule_rank4_appType_19'] in ab_exp_code_list or \
  586. config_.AB_EXP_CODE['region_rule_rank4_appType_4'] in ab_exp_code_list or\
  587. config_.AB_EXP_CODE['region_rule_rank4_appType_6'] in ab_exp_code_list or\
  588. config_.AB_EXP_CODE['region_rule_rank4_appType_18'] in ab_exp_code_list:
  589. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  590. expire_time = 3600
  591. rule_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('rule_key')
  592. data_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('data_key')
  593. no_op_flag = True
  594. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data1'] in ab_exp_code_list:
  595. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  596. # expire_time = 3600
  597. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('rule_key')
  598. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('data_key')
  599. # no_op_flag = True
  600. # elif config_.AB_EXP_CODE['region_rule_rank3_appType_5_data2'] in ab_exp_code_list:
  601. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3_appType_5_data2')
  602. # expire_time = 3600
  603. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('rule_key')
  604. # data_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('data_key')
  605. # no_op_flag = True
  606. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data3'] in ab_exp_code_list:
  607. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data3')
  608. expire_time = 3600
  609. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('rule_key')
  610. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('data_key')
  611. no_op_flag = True
  612. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data4'] in ab_exp_code_list:
  613. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data4')
  614. expire_time = 3600
  615. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('rule_key')
  616. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('data_key')
  617. no_op_flag = True
  618. elif config_.AB_EXP_CODE['region_rule_rank4_appType_0_data2'] in ab_exp_code_list:
  619. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_0_data2')
  620. expire_time = 3600
  621. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('rule_key')
  622. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('data_key')
  623. no_op_flag = True
  624. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data2'] in ab_exp_code_list:
  625. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data2')
  626. # expire_time = 3600
  627. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('rule_key')
  628. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('data_key')
  629. # no_op_flag = True
  630. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data3'] in ab_exp_code_list:
  631. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data3')
  632. # expire_time = 3600
  633. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('rule_key')
  634. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('data_key')
  635. # no_op_flag = True
  636. elif config_.AB_EXP_CODE['region_rule_rank5_appType_0_data1'] in ab_exp_code_list:
  637. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank5_appType_0_data1')
  638. expire_time = 3600
  639. rule_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('rule_key')
  640. data_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('data_key')
  641. no_op_flag = True
  642. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data2'] in ab_exp_code_list:
  643. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data2')
  644. expire_time = 3600
  645. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('rule_key')
  646. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('data_key')
  647. no_op_flag = True
  648. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data3'] in ab_exp_code_list:
  649. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data3')
  650. expire_time = 3600
  651. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('rule_key')
  652. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('data_key')
  653. no_op_flag = True
  654. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data2'] in ab_exp_code_list:
  655. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data2')
  656. expire_time = 3600
  657. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('rule_key')
  658. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('data_key')
  659. no_op_flag = True
  660. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data3'] in ab_exp_code_list:
  661. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data3')
  662. expire_time = 3600
  663. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('rule_key')
  664. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('data_key')
  665. no_op_flag = True
  666. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_18_data2'] in ab_exp_code_list:
  667. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_18_data2')
  668. # expire_time = 3600
  669. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('rule_key')
  670. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('data_key')
  671. # no_op_flag = True
  672. # elif config_.AB_EXP_CODE['region_rule_rank6_appType_0_data1'] in ab_exp_code_list:
  673. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_0_data1')
  674. # expire_time = 3600
  675. # rule_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('rule_key')
  676. # data_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('data_key')
  677. # no_op_flag = True
  678. else:
  679. ab_code = config_.AB_CODE['initial']
  680. expire_time = 24 * 3600
  681. rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  682. data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  683. # # 老好看视频 / 票圈最惊奇 首页/相关推荐逻辑更新实验
  684. # if config_.AB_EXP_CODE['rov_rank_appType_18_19'] in ab_exp_code_list:
  685. # ab_code = config_.AB_CODE['rov_rank_appType_18_19']
  686. # expire_time = 3600
  687. # flow_pool_P = config_.P_18_19
  688. # no_op_flag = True
  689. #
  690. # elif config_.AB_EXP_CODE['rov_rank_appType_19'] in ab_exp_code_list:
  691. # ab_code = config_.AB_CODE['rov_rank_appType_19']
  692. # expire_time = 3600
  693. # top_K = 0
  694. # flow_pool_P = config_.P_18_19
  695. # no_op_flag = True
  696. #
  697. # elif config_.AB_EXP_CODE['top_video_relevant_appType_19'] in ab_exp_code_list and page_type == 2:
  698. # ab_code = config_.AB_CODE['top_video_relevant_appType_19']
  699. # expire_time = 3600
  700. # top_K = 1
  701. # flow_pool_P = config_.P_18_19
  702. # no_op_flag = True
  703. #
  704. # # 票圈最惊奇完整影视资源实验
  705. # elif config_.AB_EXP_CODE['whole_movies'] in ab_exp_code_list:
  706. # ab_code = config_.AB_CODE['whole_movies']
  707. # expire_time = 24 * 3600
  708. # no_op_flag = True
  709. # 老视频实验
  710. # if config_.AB_EXP_CODE['old_video'] in ab_exp_code_list:
  711. # ab_code = config_.AB_CODE['old_video']
  712. # no_op_flag = True
  713. # old_video_index = 2
  714. # else:
  715. # old_video_index = -1
  716. """
  717. # APP实验组
  718. # if ab_info_data:
  719. # ab_info_app = {}
  720. # for page_code, item in json.loads(ab_info_data).items():
  721. # if not item:
  722. # continue
  723. # ab_info_code = item.get('eventId', None)
  724. # if ab_info_code:
  725. # ab_info_app[page_code] = ab_info_code
  726. # print(f"======{ab_info_app}")
  727. #
  728. # # 首页推荐
  729. # if recommend_type == 0:
  730. # if config_.APP_AB_CODE['10003'].get('region_rule_rank6_appType_13_data2') == ab_info_app.get('10003', None):
  731. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_13_data2')
  732. # expire_time = 3600
  733. # rule_key = 'rule6'
  734. # data_key = 'data7'
  735. # no_op_flag = True
  736. # else:
  737. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  738. # expire_time = 3600
  739. # rule_key = 'rule3'
  740. # data_key = 'data1'
  741. # no_op_flag = True
  742. # # 相关推荐
  743. # elif recommend_type == 1:
  744. # if config_.APP_AB_CODE['10037'] == ab_info_app.get('10037', None):
  745. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  746. # expire_time = 3600
  747. # rule_key = 'rule3'
  748. # data_key = 'data1'
  749. # no_op_flag = True
  750. return top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index
  751. def video_homepage_recommend(request_id, mid, uid, size, app_type, algo_type,
  752. client_info, ab_exp_info, params, ab_info_data, version_audit_status):
  753. """
  754. 首页线上推荐逻辑
  755. :param request_id: request_id
  756. :param mid: mid type-string
  757. :param uid: uid type-string
  758. :param size: 请求视频数量 type-int
  759. :param app_type: 产品标识 type-int
  760. :param algo_type: 算法类型 type-string
  761. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  762. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  763. :param params:
  764. :param ab_info_data: app实验分组参数
  765. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  766. :return:
  767. """
  768. # 对 vlog 切换10%的流量做实验
  769. # 对mid进行哈希
  770. # hash_mid = hashlib.md5(mid.encode('utf-8')).hexdigest()
  771. # if app_type in config_.AB_TEST['rank_by_h'] and hash_mid[-1:] in ['8', '0', 'a', 'b']:
  772. # # 简单召回 - 排序 - 兜底
  773. # rank_result, last_rov_recall_key = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  774. # algo_type=algo_type, client_info=client_info,
  775. # expire_time=3600,
  776. # ab_code=config_.AB_CODE['rank_by_h'])
  777. # # ab-test
  778. # result = ab_test_op(rank_result=rank_result,
  779. # ab_code_list=[config_.AB_CODE['position_insert']],
  780. # app_type=app_type, mid=mid, uid=uid)
  781. # # redis数据刷新
  782. # update_redis_data(result=result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  783. # expire_time=3600)
  784. # if app_type == config_.APP_TYPE['APP']:
  785. # # 票圈视频APP
  786. # top_K = config_.K
  787. # flow_pool_P = config_.P
  788. # # 简单召回 - 排序 - 兜底
  789. # rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  790. # mid=mid, uid=uid, app_type=app_type,
  791. # size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  792. # algo_type=algo_type, client_info=client_info,
  793. # expire_time=12 * 3600, params=params)
  794. # # ab-test
  795. # # result = ab_test_op(rank_result=rank_result,
  796. # # ab_code_list=[config_.AB_CODE['position_insert']],
  797. # # app_type=app_type, mid=mid, uid=uid)
  798. # # redis数据刷新
  799. # update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  800. # top_K=top_K, expire_time=12 * 3600)
  801. #
  802. # else:
  803. param_st = time.time()
  804. # 特殊mid 和 小程序审核版本推荐处理
  805. if mid in get_special_mid_list() or version_audit_status == 1:
  806. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  807. return rank_result
  808. # 普通mid推荐处理
  809. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  810. get_recommend_params(recommend_type=0, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data)
  811. log_.info({
  812. 'logTimestamp': int(time.time() * 1000),
  813. 'request_id': request_id,
  814. 'app_type': app_type,
  815. 'mid': mid,
  816. 'uid': uid,
  817. 'operation': 'get_recommend_params',
  818. 'executeTime': (time.time() - param_st) * 1000
  819. })
  820. # 简单召回 - 排序 - 兜底
  821. get_result_st = time.time()
  822. rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  823. mid=mid, uid=uid, app_type=app_type,
  824. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  825. algo_type=algo_type, client_info=client_info,
  826. ab_code=ab_code, expire_time=expire_time,
  827. rule_key=rule_key, data_key=data_key,
  828. no_op_flag=no_op_flag, old_video_index=old_video_index,
  829. params=params)
  830. log_.info({
  831. 'logTimestamp': int(time.time() * 1000),
  832. 'request_id': request_id,
  833. 'app_type': app_type,
  834. 'mid': mid,
  835. 'uid': uid,
  836. 'operation': 'get_recommend_result',
  837. 'executeTime': (time.time() - get_result_st) * 1000
  838. })
  839. # ab-test
  840. # result = ab_test_op(rank_result=rank_result,
  841. # ab_code_list=[config_.AB_CODE['position_insert']],
  842. # app_type=app_type, mid=mid, uid=uid)
  843. # redis数据刷新
  844. update_redis_st = time.time()
  845. update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  846. top_K=top_K)
  847. log_.info({
  848. 'logTimestamp': int(time.time() * 1000),
  849. 'request_id': request_id,
  850. 'app_type': app_type,
  851. 'mid': mid,
  852. 'uid': uid,
  853. 'operation': 'update_redis_data',
  854. 'executeTime': (time.time() - update_redis_st) * 1000
  855. })
  856. return rank_result
  857. def video_relevant_recommend(request_id, video_id, mid, uid, size, app_type, ab_exp_info, client_info,
  858. page_type, params, ab_info_data, version_audit_status):
  859. """
  860. 相关推荐逻辑
  861. :param request_id: request_id
  862. :param video_id: 相关推荐的头部视频id
  863. :param mid: mid type-string
  864. :param uid: uid type-string
  865. :param size: 请求视频数量 type-int
  866. :param app_type: 产品标识 type-int
  867. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  868. :param client_info: 地域参数
  869. :param page_type: 页面区分参数 1:详情页;2:分享页
  870. :param params:
  871. :param ab_info_data: app实验分组参数
  872. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  873. :return: videos type-list
  874. """
  875. param_st = time.time()
  876. # 特殊mid 和 小程序审核版本推荐处理
  877. if mid in get_special_mid_list() or version_audit_status == 1:
  878. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  879. return rank_result
  880. # 普通mid推荐处理
  881. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  882. get_recommend_params(recommend_type=1, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data, page_type=page_type)
  883. log_.info({
  884. 'logTimestamp': int(time.time() * 1000),
  885. 'request_id': request_id,
  886. 'app_type': app_type,
  887. 'mid': mid,
  888. 'uid': uid,
  889. 'operation': 'get_recommend_params',
  890. 'executeTime': (time.time() - param_st) * 1000
  891. })
  892. # 简单召回 - 排序 - 兜底
  893. get_result_st = time.time()
  894. rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  895. mid=mid, uid=uid, app_type=app_type,
  896. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  897. algo_type='', client_info=client_info,
  898. ab_code=ab_code, expire_time=expire_time,
  899. rule_key=rule_key, data_key=data_key, no_op_flag=no_op_flag,
  900. old_video_index=old_video_index, video_id=video_id,
  901. params=params)
  902. log_.info({
  903. 'logTimestamp': int(time.time() * 1000),
  904. 'request_id': request_id,
  905. 'app_type': app_type,
  906. 'mid': mid,
  907. 'uid': uid,
  908. 'operation': 'get_recommend_result',
  909. 'executeTime': (time.time() - get_result_st) * 1000
  910. })
  911. # ab-test
  912. # result = ab_test_op(rank_result=rank_result,
  913. # ab_code_list=[config_.AB_CODE['position_insert'], config_.AB_CODE['relevant_video_op']],
  914. # app_type=app_type, mid=mid, uid=uid, head_vid=video_id, size=size)
  915. # redis数据刷新
  916. update_redis_st = time.time()
  917. update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  918. top_K=top_K)
  919. log_.info({
  920. 'logTimestamp': int(time.time() * 1000),
  921. 'request_id': request_id,
  922. 'app_type': app_type,
  923. 'mid': mid,
  924. 'uid': uid,
  925. 'operation': 'update_redis_data',
  926. 'executeTime': (time.time() - update_redis_st) * 1000
  927. })
  928. return rank_result
  929. def special_mid_recommend(request_id, mid, uid, app_type, size,
  930. ab_code=config_.AB_CODE['special_mid'],
  931. push_from=config_.PUSH_FROM['special_mid'],
  932. expire_time=24*3600):
  933. redis_helper = RedisHelper()
  934. # 特殊mid推荐指定视频列表
  935. pool_recall = PoolRecall(request_id=request_id, app_type=app_type,
  936. mid=mid, uid=uid, ab_code=ab_code)
  937. # 获取相关redis key
  938. special_key_name, redis_date = pool_recall.get_pool_redis_key(pool_type='special')
  939. # 用户上一次在rov召回池对应的位置
  940. last_special_recall_key = f'{config_.LAST_VIDEO_FROM_SPECIAL_POOL_PREFIX}{app_type}:{mid}:{redis_date}'
  941. value = redis_helper.get_data_from_redis(last_special_recall_key)
  942. if value:
  943. idx = redis_helper.get_index_with_data(special_key_name, value)
  944. if not idx:
  945. idx = 0
  946. else:
  947. idx += 1
  948. else:
  949. idx = 0
  950. recall_result = []
  951. # 每次获取的视频数
  952. get_size = size * 5
  953. # 记录获取频次
  954. freq = 0
  955. while len(recall_result) < size:
  956. freq += 1
  957. if freq > config_.MAX_FREQ_FROM_ROV_POOL:
  958. break
  959. # 获取数据
  960. data = redis_helper.get_data_zset_with_index(key_name=special_key_name,
  961. start=idx, end=idx + get_size - 1,
  962. with_scores=True)
  963. if not data:
  964. break
  965. # 获取视频id,并转换类型为int,并存储为key-value{videoId: score}
  966. # 添加视频源参数 pushFrom, abCode
  967. temp_result = [{'videoId': int(value[0]), 'rovScore': value[1],
  968. 'pushFrom': push_from, 'abCode': ab_code}
  969. for value in data]
  970. recall_result.extend(temp_result)
  971. idx += get_size
  972. # 将此次获取的末位视频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
  973. if mid and recall_result:
  974. # mid为空时,不做记录
  975. redis_helper.set_data_to_redis(key_name=last_special_recall_key,
  976. value=recall_result[:size][-1]['videoId'],
  977. expire_time=expire_time)
  978. return recall_result[:size]
  979. def get_special_mid_list():
  980. redis_helper = RedisHelper()
  981. special_mid_list = redis_helper.get_data_from_set(key_name=config_.KEY_NAME_SPECIAL_MID)
  982. if special_mid_list:
  983. return special_mid_list
  984. else:
  985. return []
  986. if __name__ == '__main__':
  987. videos = [
  988. {"videoId": 10136461, "rovScore": 99.971, "pushFrom": "recall_pool", "abCode": 10000},
  989. {"videoId": 10239014, "rovScore": 99.97, "pushFrom": "recall_pool", "abCode": 10000},
  990. {"videoId": 9851154, "rovScore": 99.969, "pushFrom": "recall_pool", "abCode": 10000},
  991. {"videoId": 10104347, "rovScore": 99.968, "pushFrom": "recall_pool", "abCode": 10000},
  992. {"videoId": 10141507, "rovScore": 99.967, "pushFrom": "recall_pool", "abCode": 10000},
  993. {"videoId": 10292817, "flowPool": "2#6#2#1641780979606", "rovScore": 53.926690610816486,
  994. "pushFrom": "flow_pool", "abCode": 10000},
  995. {"videoId": 10224932, "flowPool": "2#5#1#1641800279644", "rovScore": 53.47890460059617, "pushFrom": "flow_pool",
  996. "abCode": 10000},
  997. {"videoId": 9943255, "rovScore": 99.966, "pushFrom": "recall_pool", "abCode": 10000},
  998. {"videoId": 10282970, "flowPool": "2#5#1#1641784814103", "rovScore": 52.682815076325575,
  999. "pushFrom": "flow_pool", "abCode": 10000},
  1000. {"videoId": 10282205, "rovScore": 99.965, "pushFrom": "recall_pool", "abCode": 10000}
  1001. ]
  1002. res = relevant_video_top_recommend(app_type=4, mid='', uid=1111, head_vid=123, videos=videos, size=10)
  1003. print(res)