recommend.py 56 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. result = {}
  136. # ####### 多进程召回
  137. start_recall = time.time()
  138. # log_.info('====== recall')
  139. '''
  140. cores = multiprocessing.cpu_count()
  141. pool = multiprocessing.Pool(processes=cores)
  142. pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code)
  143. _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  144. pool_list = [
  145. # rov召回池
  146. pool.apply_async(pool_recall.rov_pool_recall, (size,)),
  147. # 流量池
  148. pool.apply_async(pool_recall.flow_pool_recall, (size,))
  149. ]
  150. recall_result_list = [p.get() for p in pool_list]
  151. pool.close()
  152. pool.join()
  153. '''
  154. recall_result_list = []
  155. pool_recall = PoolRecall(request_id=request_id,
  156. app_type=app_type, mid=mid, uid=uid, ab_code=ab_code,
  157. client_info=client_info, rule_key=rule_key, data_key=data_key, no_op_flag=no_op_flag,
  158. params=params)
  159. # _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  160. # # 小时级实验
  161. # if ab_code in [code for _, code in config_.AB_CODE['rank_by_h'].items()]:
  162. # t = [gevent.spawn(pool_recall.rule_recall_by_h, size, expire_time),
  163. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  164. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  165. # # 小时级实验
  166. # elif ab_code in [code for _, code in config_.AB_CODE['rank_by_24h'].items()]:
  167. # t = [gevent.spawn(pool_recall.rov_pool_recall_by_h, size, expire_time),
  168. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  169. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  170. # 地域分组实验
  171. # if ab_code in [code for _, code in config_.AB_CODE['region_rank_by_h'].items()]:
  172. if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  173. t = [gevent.spawn(pool_recall.rov_pool_recall_with_region, size, expire_time)]
  174. else:
  175. t = [gevent.spawn(pool_recall.rov_pool_recall_with_region, size, expire_time),
  176. gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  177. gevent.spawn(pool_recall.flow_pool_recall, size)]
  178. # 最惊奇相关推荐实验
  179. # elif ab_code == config_.AB_CODE['top_video_relevant_appType_19']:
  180. # t = [gevent.spawn(pool_recall.relevant_recall_19, video_id, size, expire_time),
  181. # gevent.spawn(pool_recall.flow_pool_recall_18_19, size)]
  182. # 最惊奇完整影视实验
  183. # elif ab_code == config_.AB_CODE['whole_movies']:
  184. # t = [gevent.spawn(pool_recall.rov_pool_recall_19, size, expire_time)]
  185. # 最惊奇/老好看实验
  186. # elif app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  187. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  188. # gevent.spawn(pool_recall.flow_pool_recall_18_19, size)]
  189. # # 天级实验
  190. # elif ab_code in [code for _, code in config_.AB_CODE['rank_by_day'].items()]:
  191. # t = [gevent.spawn(pool_recall.rov_pool_recall_by_day, size, expire_time),
  192. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  193. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  194. # 老视频实验
  195. # elif ab_code in [config_.AB_CODE['old_video']]:
  196. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  197. # gevent.spawn(pool_recall.flow_pool_recall, size),
  198. # gevent.spawn(pool_recall.old_videos_recall, size)]
  199. # else:
  200. # if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  201. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time)]
  202. # else:
  203. # t = [gevent.spawn(pool_recall.rov_pool_recall, size, expire_time),
  204. # gevent.spawn(pool_recall.flow_pool_recall, size, config_.QUICK_FLOW_POOL_ID),
  205. # gevent.spawn(pool_recall.flow_pool_recall, size)]
  206. gevent.joinall(t)
  207. recall_result_list = [i.get() for i in t]
  208. # end_recall = time.time()
  209. # log_.info({
  210. # 'logTimestamp': int(time.time() * 1000),
  211. # 'request_id': request_id,
  212. # 'mid': mid,
  213. # 'uid': uid,
  214. # 'operation': 'recall',
  215. # 'recall_result': recall_result_list,
  216. # 'executeTime': (time.time() - start_recall) * 1000
  217. # })
  218. result['recallResult'] = recall_result_list
  219. result['recallTime'] = (time.time() - start_recall) * 1000
  220. # ####### 排序
  221. start_rank = time.time()
  222. # log_.info('====== rank')
  223. if app_type in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  224. if ab_code in [
  225. config_.AB_CODE['rov_rank_appType_18_19'],
  226. config_.AB_CODE['rov_rank_appType_19'],
  227. config_.AB_CODE['top_video_relevant_appType_19']
  228. ]:
  229. data = {
  230. 'rov_pool_recall': recall_result_list[0],
  231. 'flow_pool_recall': recall_result_list[1]
  232. }
  233. else:
  234. data = {
  235. 'rov_pool_recall': recall_result_list[0],
  236. 'flow_pool_recall': []
  237. }
  238. else:
  239. if recall_result_list[1]:
  240. redis_helper = RedisHelper()
  241. quick_flow_pool_P = redis_helper.get_data_from_redis(
  242. key_name=f"{config_.QUICK_FLOWPOOL_DISTRIBUTE_RATE_KEY_NAME_PREFIX}{config_.QUICK_FLOW_POOL_ID}"
  243. )
  244. if quick_flow_pool_P:
  245. flow_pool_P = quick_flow_pool_P
  246. data = {
  247. 'rov_pool_recall': recall_result_list[0],
  248. 'flow_pool_recall': recall_result_list[1]
  249. }
  250. else:
  251. data = {
  252. 'rov_pool_recall': recall_result_list[0],
  253. 'flow_pool_recall': recall_result_list[2]
  254. }
  255. rank_result = video_rank(data=data, size=size, top_K=top_K, flow_pool_P=float(flow_pool_P))
  256. # 老视频实验
  257. # if ab_code in [config_.AB_CODE['old_video']]:
  258. # rank_result = video_rank_with_old_video(rank_result=rank_result, old_video_recall=recall_result_list[2],
  259. # size=size, top_K=top_K, old_video_index=old_video_index)
  260. # end_rank = time.time()
  261. # log_.info({
  262. # 'logTimestamp': int(time.time() * 1000),
  263. # 'request_id': request_id,
  264. # 'mid': mid,
  265. # 'uid': uid,
  266. # 'operation': 'rank',
  267. # 'rank_result': rank_result,
  268. # 'executeTime': (time.time() - start_rank) * 1000
  269. # })
  270. result['rankResult'] = rank_result
  271. result['rankTime'] = (time.time() - start_rank) * 1000
  272. if not rank_result:
  273. # 兜底策略
  274. # log_.info('====== bottom strategy')
  275. start_bottom = time.time()
  276. rank_result = bottom_strategy2(
  277. size=size, app_type=app_type, mid=mid, uid=uid, ab_code=ab_code, client_info=client_info, params=params
  278. )
  279. # if ab_code == config_.AB_CODE['region_rank_by_h'].get('abtest_130'):
  280. # rank_result = bottom_strategy2(
  281. # size=size, app_type=app_type, mid=mid, uid=uid, ab_code=ab_code, client_info=client_info, params=params
  282. # )
  283. # else:
  284. # rank_result = bottom_strategy(
  285. # request_id=request_id, size=size, app_type=app_type, ab_code=ab_code, params=params
  286. # )
  287. # log_.info({
  288. # 'logTimestamp': int(time.time() * 1000),
  289. # 'request_id': request_id,
  290. # 'mid': mid,
  291. # 'uid': uid,
  292. # 'operation': 'bottom',
  293. # 'bottom_result': rank_result,
  294. # 'executeTime': (time.time() - start_bottom) * 1000
  295. # })
  296. result['bottomResult'] = rank_result
  297. result['bottomTime'] = (time.time() - start_bottom) * 1000
  298. result['rankResult'] = rank_result
  299. return result
  300. # return rank_result, last_rov_recall_key
  301. def ab_test_op(rank_result, ab_code_list, app_type, mid, uid, **kwargs):
  302. """
  303. 对排序后的结果 按照AB实验进行对应的分组操作
  304. :param rank_result: 排序后的结果
  305. :param ab_code_list: 此次请求参与的 ab实验组
  306. :param app_type: 产品标识
  307. :param mid: mid
  308. :param uid: uid
  309. :param kwargs: 其他参数
  310. :return:
  311. """
  312. # ####### 视频宽高比AB实验
  313. # 对内容精选进行 视频宽高比分发实验
  314. # if config_.AB_CODE['w_h_rate'] in ab_code_list and app_type in config_.AB_TEST.get('w_h_rate', []):
  315. # rank_result = video_rank_by_w_h_rate(videos=rank_result)
  316. # log_.info('app_type: {}, mid: {}, uid: {}, rank_by_w_h_rate_result: {}'.format(
  317. # app_type, mid, uid, rank_result))
  318. # 按position位置排序
  319. if config_.AB_CODE['position_insert'] in ab_code_list and app_type in config_.AB_TEST.get('position_insert', []):
  320. rank_result = video_position_recommend(mid, uid, app_type, rank_result)
  321. print('===========================')
  322. print(rank_result)
  323. log_.info('app_type: {}, mid: {}, uid: {}, rank_by_position_insert_result: {}'.format(
  324. app_type, mid, uid, rank_result))
  325. # 相关推荐强插
  326. # if config_.AB_CODE['relevant_video_op'] in ab_code_list \
  327. # and app_type in config_.AB_TEST.get('relevant_video_op', []):
  328. # head_vid = kwargs['head_vid']
  329. # size = kwargs['size']
  330. # rank_result = relevant_video_top_recommend(
  331. # app_type=app_type, mid=mid, uid=uid, head_vid=head_vid, videos=rank_result, size=size
  332. # )
  333. # log_.info('app_type: {}, mid: {}, uid: {}, head_vid: {}, rank_by_relevant_video_op_result: {}'.format(
  334. # app_type, mid, uid, head_vid, rank_result))
  335. return rank_result
  336. def update_redis_data(result, app_type, mid, top_K, expire_time=24*3600):
  337. """
  338. 根据最终的排序结果更新相关redis数据
  339. :param result: 排序结果
  340. :param app_type: 产品标识
  341. :param mid: mid
  342. :param last_rov_recall_key: 用户上一次在rov召回池对应的位置 redis key
  343. :param top_K: 保证topK为召回池视频 type-int
  344. :param expire_time: 末位视频记录redis过期时间
  345. :return: None
  346. """
  347. # ####### redis数据刷新
  348. try:
  349. redis_helper = RedisHelper()
  350. # log_.info('====== update redis')
  351. if mid and mid != 'null':
  352. # mid为空时,不做预曝光和定位数据更新
  353. # 预曝光数据同步刷新到Redis, 过期时间为0.5h
  354. preview_key_name = f"{config_.PREVIEW_KEY_PREFIX}{app_type}:{mid}"
  355. preview_video_ids = [int(item['videoId']) for item in result]
  356. if preview_video_ids:
  357. # log_.error('key_name = {} \n values = {}'.format(preview_key_name, tuple(preview_video_ids)))
  358. redis_helper.add_data_with_set(key_name=preview_key_name, values=tuple(preview_video_ids), expire_time=30 * 60)
  359. # log_.info('preview redis update success!')
  360. # # 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
  361. # rov_recall_video = [item['videoId'] for item in result[:top_K]
  362. # if item['pushFrom'] == config_.PUSH_FROM['rov_recall']]
  363. # if len(rov_recall_video) > 0:
  364. # if app_type == config_.APP_TYPE['APP']:
  365. # key_name = config_.UPDATE_ROV_KEY_NAME_APP
  366. # else:
  367. # key_name = config_.UPDATE_ROV_KEY_NAME
  368. # if not redis_helper.get_score_with_value(key_name=key_name, value=rov_recall_video[-1]):
  369. # redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[-1],
  370. # expire_time=expire_time)
  371. # log_.info('last video redis update success!')
  372. # 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
  373. rov_recall_h_video = [item['videoId'] for item in result[:top_K]
  374. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_h']]
  375. if len(rov_recall_h_video) > 0:
  376. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_H_PREFIX}{app_type}:{mid}'
  377. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_h_video[-1],
  378. expire_time=expire_time)
  379. # 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
  380. rov_recall_24h_dup1_video = [item['videoId'] for item in result[:top_K]
  381. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_24h']]
  382. if len(rov_recall_24h_dup1_video) > 0:
  383. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP1_24H_PREFIX}{app_type}:{mid}'
  384. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup1_video[-1],
  385. expire_time=expire_time)
  386. # 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
  387. rov_recall_24h_dup2_video = [item['videoId'] for item in result[:top_K]
  388. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h']]
  389. if len(rov_recall_24h_dup2_video) > 0:
  390. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_24H_PREFIX}{app_type}:{mid}'
  391. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup2_video[-1],
  392. expire_time=expire_time)
  393. # 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
  394. rov_recall_24h_dup3_video = [item['videoId'] for item in result[:top_K]
  395. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h_dup']]
  396. if len(rov_recall_24h_dup3_video) > 0:
  397. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_24H_PREFIX}{app_type}:{mid}'
  398. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup3_video[-1],
  399. expire_time=expire_time)
  400. # 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
  401. rov_recall_48h_dup2_video = [item['videoId'] for item in result[:top_K]
  402. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h']]
  403. if len(rov_recall_48h_dup2_video) > 0:
  404. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_48H_PREFIX}{app_type}:{mid}'
  405. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup2_video[-1],
  406. expire_time=expire_time)
  407. # 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
  408. rov_recall_48h_dup3_video = [item['videoId'] for item in result[:top_K]
  409. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h_dup']]
  410. if len(rov_recall_48h_dup3_video) > 0:
  411. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_48H_PREFIX}{app_type}:{mid}'
  412. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup3_video[-1],
  413. expire_time=expire_time)
  414. # 将此次分发的流量池视频,对 本地分发数-1 进行记录
  415. if app_type not in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  416. flow_recall_video = [item for item in result if item['pushFrom'] == config_.PUSH_FROM['flow_recall']]
  417. if flow_recall_video:
  418. update_local_distribute_count(flow_recall_video)
  419. # log_.info('update local distribute count success!')
  420. # 限流视频分发数记录
  421. if app_type == config_.APP_TYPE['APP']:
  422. # APP 不计入
  423. return
  424. limit_video_id_list = redis_helper.get_data_from_set(
  425. key_name=f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_SET}{datetime.today().strftime('%Y%m%d')}"
  426. )
  427. if limit_video_id_list is not None:
  428. limit_video_id_list = [int(item) for item in limit_video_id_list]
  429. for item in result:
  430. video_id = item['videoId']
  431. if video_id in limit_video_id_list:
  432. key_name = f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_DISTRIBUTE_COUNT}{video_id}"
  433. redis_helper.setnx_key(key_name=key_name, value=0, expire_time=24*2600)
  434. redis_helper.incr_key(key_name=key_name, amount=1, expire_time=24*3600)
  435. except Exception as e:
  436. log_.error("update redis data fail!")
  437. log_.error(traceback.format_exc())
  438. def update_local_distribute_count(videos):
  439. """
  440. 更新本地分发数
  441. :param videos: 视频列表 type-list [{'videoId':'', 'flowPool':'', 'distributeCount': '',
  442. 'rovScore': '', 'pushFrom': 'flow_pool', 'abCode': self.ab_code}, ....]
  443. :return:
  444. """
  445. try:
  446. redis_helper = RedisHelper()
  447. for item in videos:
  448. key_name = f"{config_.LOCAL_DISTRIBUTE_COUNT_PREFIX}{item['videoId']}:{item['flowPool']}"
  449. # 本地记录的分发数 - 1
  450. redis_helper.decr_key(key_name=key_name, amount=1, expire_time=15 * 60)
  451. # if redis_helper.key_exists(key_name=key_name):
  452. # # 该视频本地有记录,本地记录的分发数 - 1
  453. # redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
  454. # else:
  455. # # 该视频本地无记录,接口获取的分发数 - 1
  456. # redis_helper.incr_key(key_name=key_name, amount=int(item['distributeCount']) - 1, expire_time=5 * 60)
  457. except Exception as e:
  458. log_.error('update_local_distribute_count error...')
  459. log_.error(traceback.format_exc())
  460. def get_recommend_params(recommend_type, ab_exp_info, ab_info_data, page_type=0):
  461. """
  462. 根据实验分组给定对应的推荐参数
  463. :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)
  464. :param ab_exp_info: AB实验组参数
  465. :param ab_info_data: app实验组参数
  466. :param page_type: 页面区分参数,默认:0(首页)
  467. :return:
  468. """
  469. top_K = config_.K
  470. flow_pool_P = config_.P
  471. # 不获取人工干预数据标记
  472. no_op_flag = False
  473. old_video_index = -1
  474. # if not ab_exp_info:
  475. # ab_code = config_.AB_CODE['initial']
  476. # expire_time = 24 * 3600
  477. # rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  478. # data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  479. # # old_video_index = -1
  480. # else:
  481. # 默认使用 095 实验的配置
  482. ab_code = config_.AB_EXP_CODE['095'].get('ab_code')
  483. expire_time = 3600
  484. rule_key = config_.AB_EXP_CODE['095'].get('rule_key')
  485. data_key = config_.AB_EXP_CODE['095'].get('data_key')
  486. no_op_flag = True
  487. # 获取实验配置
  488. if ab_exp_info:
  489. ab_exp_code_list = []
  490. config_value_dict = {}
  491. for _, item in ab_exp_info.items():
  492. if not item:
  493. continue
  494. for ab_item in item:
  495. ab_exp_code = ab_item.get('abExpCode', None)
  496. if not ab_exp_code:
  497. continue
  498. ab_exp_code_list.append(str(ab_exp_code))
  499. config_value_dict[str(ab_exp_code)] = ab_item.get('configValue', None)
  500. if '136' in ab_exp_code_list:
  501. if user_type == 'click':
  502. param = config_.AB_EXP_CODE.get('136')
  503. ab_code = param.get('ab_code')
  504. expire_time = 3600
  505. rule_key = param.get('rule_key')
  506. data_key = param.get('data_key')
  507. no_op_flag = True
  508. elif '137' in ab_exp_code_list:
  509. if user_type == 'share':
  510. param = config_.AB_EXP_CODE.get('137')
  511. ab_code = param.get('ab_code')
  512. expire_time = 3600
  513. rule_key = param.get('rule_key')
  514. data_key = param.get('data_key')
  515. no_op_flag = True
  516. else:
  517. for code, param in config_.AB_EXP_CODE.items():
  518. if code in ab_exp_code_list:
  519. ab_code = param.get('ab_code')
  520. expire_time = 3600
  521. rule_key = param.get('rule_key')
  522. data_key = param.get('data_key')
  523. no_op_flag = True
  524. break
  525. """
  526. # 推荐条数 10->4 实验
  527. # if config_.AB_EXP_CODE['rec_size_home'] in ab_exp_code_list:
  528. # config_value = config_value_dict.get(config_.AB_EXP_CODE['rec_size_home'], None)
  529. # if config_value:
  530. # config_value = eval(str(config_value))
  531. # else:
  532. # config_value = {}
  533. # log_.info(f'config_value: {config_value}, type: {type(config_value)}')
  534. # size = int(config_value.get('size', 4))
  535. # top_K = int(config_value.get('K', 3))
  536. # flow_pool_P = float(config_value.get('P', 0.3))
  537. # else:
  538. # size = size
  539. # top_K = config_.K
  540. # flow_pool_P = config_.P
  541. # 算法实验相对对照组
  542. # if config_.AB_EXP_CODE['ab_initial'] in ab_exp_code_list:
  543. # ab_code = config_.AB_CODE['ab_initial']
  544. # expire_time = 24 * 3600
  545. # rule_key = config_.RULE_KEY['initial']
  546. # no_op_flag = True
  547. # 小时级更新-规则1 实验
  548. # elif config_.AB_EXP_CODE['rule_rank1'] in ab_exp_code_list:
  549. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank1')
  550. # expire_time = 3600
  551. # rule_key = config_.RULE_KEY['rule_rank1']
  552. # no_op_flag = True
  553. # elif config_.AB_EXP_CODE['rule_rank2'] in ab_exp_code_list:
  554. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank2')
  555. # expire_time = 3600
  556. # rule_key = config_.RULE_KEY['rule_rank2']
  557. # elif config_.AB_EXP_CODE['rule_rank3'] in ab_exp_code_list:
  558. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank3')
  559. # expire_time = 3600
  560. # rule_key = config_.RULE_KEY['rule_rank3']
  561. # no_op_flag = True
  562. # elif config_.AB_EXP_CODE['rule_rank4'] in ab_exp_code_list:
  563. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank4')
  564. # expire_time = 3600
  565. # rule_key = config_.RULE_KEY['rule_rank4']
  566. # elif config_.AB_EXP_CODE['rule_rank5'] in ab_exp_code_list:
  567. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank5')
  568. # expire_time = 3600
  569. # rule_key = config_.RULE_KEY['rule_rank5']
  570. # elif config_.AB_EXP_CODE['day_rule_rank1'] in ab_exp_code_list:
  571. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank1')
  572. # expire_time = 24 * 3600
  573. # rule_key = config_.RULE_KEY_DAY['day_rule_rank1']
  574. # no_op_flag = True
  575. # if config_.AB_EXP_CODE['rule_rank6'] in ab_exp_code_list:
  576. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank6')
  577. # expire_time = 3600
  578. # rule_key = config_.RULE_KEY['rule_rank6']
  579. # no_op_flag = True
  580. # elif config_.AB_EXP_CODE['day_rule_rank2'] in ab_exp_code_list:
  581. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank2')
  582. # expire_time = 24 * 3600
  583. # rule_key = config_.RULE_KEY_DAY['day_rule_rank2']
  584. # no_op_flag = True
  585. # elif config_.AB_EXP_CODE['region_rule_rank1'] in ab_exp_code_list:
  586. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank1')
  587. # expire_time = 3600
  588. # rule_key = config_.RULE_KEY_REGION['region_rule_rank1']
  589. # no_op_flag = True
  590. # elif config_.AB_EXP_CODE['24h_rule_rank1'] in ab_exp_code_list:
  591. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank1')
  592. # expire_time = 3600
  593. # rule_key = config_.RULE_KEY_24H['24h_rule_rank1']
  594. # no_op_flag = True
  595. # elif config_.AB_EXP_CODE['24h_rule_rank2'] in ab_exp_code_list:
  596. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank2')
  597. # expire_time = 3600
  598. # rule_key = config_.RULE_KEY_24H['24h_rule_rank2']
  599. # no_op_flag = True
  600. # elif config_.AB_EXP_CODE['region_rule_rank2'] in ab_exp_code_list:
  601. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank2')
  602. # expire_time = 3600
  603. # rule_key = config_.RULE_KEY_REGION['region_rule_rank2']
  604. # no_op_flag = True
  605. # if config_.AB_EXP_CODE['region_rule_rank3'] in ab_exp_code_list or\
  606. # config_.AB_EXP_CODE['region_rule_rank3_appType_19'] in ab_exp_code_list or\
  607. # config_.AB_EXP_CODE['region_rule_rank3_appType_4'] in ab_exp_code_list or\
  608. # config_.AB_EXP_CODE['region_rule_rank3_appType_6'] in ab_exp_code_list or\
  609. # config_.AB_EXP_CODE['region_rule_rank3_appType_18'] in ab_exp_code_list:
  610. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3')
  611. # expire_time = 3600
  612. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('rule_key')
  613. # data_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('data_key')
  614. # no_op_flag = True
  615. # if config_.AB_EXP_CODE['region_rule_rank4'] in ab_exp_code_list or\
  616. if config_.AB_EXP_CODE['region_rule_rank4_appType_19'] in ab_exp_code_list or \
  617. config_.AB_EXP_CODE['region_rule_rank4_appType_4'] in ab_exp_code_list or\
  618. config_.AB_EXP_CODE['region_rule_rank4_appType_6'] in ab_exp_code_list or\
  619. config_.AB_EXP_CODE['region_rule_rank4_appType_18'] in ab_exp_code_list:
  620. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  621. expire_time = 3600
  622. rule_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('rule_key')
  623. data_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('data_key')
  624. no_op_flag = True
  625. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data1'] in ab_exp_code_list:
  626. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  627. # expire_time = 3600
  628. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('rule_key')
  629. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('data_key')
  630. # no_op_flag = True
  631. # elif config_.AB_EXP_CODE['region_rule_rank3_appType_5_data2'] in ab_exp_code_list:
  632. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3_appType_5_data2')
  633. # expire_time = 3600
  634. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('rule_key')
  635. # data_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('data_key')
  636. # no_op_flag = True
  637. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data3'] in ab_exp_code_list:
  638. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data3')
  639. expire_time = 3600
  640. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('rule_key')
  641. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('data_key')
  642. no_op_flag = True
  643. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data4'] in ab_exp_code_list:
  644. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data4')
  645. expire_time = 3600
  646. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('rule_key')
  647. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('data_key')
  648. no_op_flag = True
  649. elif config_.AB_EXP_CODE['region_rule_rank4_appType_0_data2'] in ab_exp_code_list:
  650. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_0_data2')
  651. expire_time = 3600
  652. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('rule_key')
  653. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('data_key')
  654. no_op_flag = True
  655. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data2'] in ab_exp_code_list:
  656. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data2')
  657. # expire_time = 3600
  658. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('rule_key')
  659. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('data_key')
  660. # no_op_flag = True
  661. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data3'] in ab_exp_code_list:
  662. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data3')
  663. # expire_time = 3600
  664. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('rule_key')
  665. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('data_key')
  666. # no_op_flag = True
  667. elif config_.AB_EXP_CODE['region_rule_rank5_appType_0_data1'] in ab_exp_code_list:
  668. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank5_appType_0_data1')
  669. expire_time = 3600
  670. rule_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('rule_key')
  671. data_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('data_key')
  672. no_op_flag = True
  673. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data2'] in ab_exp_code_list:
  674. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data2')
  675. expire_time = 3600
  676. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('rule_key')
  677. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('data_key')
  678. no_op_flag = True
  679. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data3'] in ab_exp_code_list:
  680. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data3')
  681. expire_time = 3600
  682. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('rule_key')
  683. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('data_key')
  684. no_op_flag = True
  685. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data2'] in ab_exp_code_list:
  686. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data2')
  687. expire_time = 3600
  688. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('rule_key')
  689. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('data_key')
  690. no_op_flag = True
  691. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data3'] in ab_exp_code_list:
  692. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data3')
  693. expire_time = 3600
  694. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('rule_key')
  695. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('data_key')
  696. no_op_flag = True
  697. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_18_data2'] in ab_exp_code_list:
  698. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_18_data2')
  699. # expire_time = 3600
  700. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('rule_key')
  701. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('data_key')
  702. # no_op_flag = True
  703. # elif config_.AB_EXP_CODE['region_rule_rank6_appType_0_data1'] in ab_exp_code_list:
  704. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_0_data1')
  705. # expire_time = 3600
  706. # rule_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('rule_key')
  707. # data_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('data_key')
  708. # no_op_flag = True
  709. else:
  710. ab_code = config_.AB_CODE['initial']
  711. expire_time = 24 * 3600
  712. rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  713. data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  714. # # 老好看视频 / 票圈最惊奇 首页/相关推荐逻辑更新实验
  715. # if config_.AB_EXP_CODE['rov_rank_appType_18_19'] in ab_exp_code_list:
  716. # ab_code = config_.AB_CODE['rov_rank_appType_18_19']
  717. # expire_time = 3600
  718. # flow_pool_P = config_.P_18_19
  719. # no_op_flag = True
  720. #
  721. # elif config_.AB_EXP_CODE['rov_rank_appType_19'] in ab_exp_code_list:
  722. # ab_code = config_.AB_CODE['rov_rank_appType_19']
  723. # expire_time = 3600
  724. # top_K = 0
  725. # flow_pool_P = config_.P_18_19
  726. # no_op_flag = True
  727. #
  728. # elif config_.AB_EXP_CODE['top_video_relevant_appType_19'] in ab_exp_code_list and page_type == 2:
  729. # ab_code = config_.AB_CODE['top_video_relevant_appType_19']
  730. # expire_time = 3600
  731. # top_K = 1
  732. # flow_pool_P = config_.P_18_19
  733. # no_op_flag = True
  734. #
  735. # # 票圈最惊奇完整影视资源实验
  736. # elif config_.AB_EXP_CODE['whole_movies'] in ab_exp_code_list:
  737. # ab_code = config_.AB_CODE['whole_movies']
  738. # expire_time = 24 * 3600
  739. # no_op_flag = True
  740. # 老视频实验
  741. # if config_.AB_EXP_CODE['old_video'] in ab_exp_code_list:
  742. # ab_code = config_.AB_CODE['old_video']
  743. # no_op_flag = True
  744. # old_video_index = 2
  745. # else:
  746. # old_video_index = -1
  747. """
  748. # APP实验组
  749. # if ab_info_data:
  750. # ab_info_app = {}
  751. # for page_code, item in json.loads(ab_info_data).items():
  752. # if not item:
  753. # continue
  754. # ab_info_code = item.get('eventId', None)
  755. # if ab_info_code:
  756. # ab_info_app[page_code] = ab_info_code
  757. # print(f"======{ab_info_app}")
  758. #
  759. # # 首页推荐
  760. # if recommend_type == 0:
  761. # if config_.APP_AB_CODE['10003'].get('region_rule_rank6_appType_13_data2') == ab_info_app.get('10003', None):
  762. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_13_data2')
  763. # expire_time = 3600
  764. # rule_key = 'rule6'
  765. # data_key = 'data7'
  766. # no_op_flag = True
  767. # else:
  768. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  769. # expire_time = 3600
  770. # rule_key = 'rule3'
  771. # data_key = 'data1'
  772. # no_op_flag = True
  773. # # 相关推荐
  774. # elif recommend_type == 1:
  775. # if config_.APP_AB_CODE['10037'] == ab_info_app.get('10037', None):
  776. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  777. # expire_time = 3600
  778. # rule_key = 'rule3'
  779. # data_key = 'data1'
  780. # no_op_flag = True
  781. return top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index
  782. def video_homepage_recommend(request_id, mid, uid, size, app_type, algo_type,
  783. client_info, ab_exp_info, params, ab_info_data, version_audit_status):
  784. """
  785. 首页线上推荐逻辑
  786. :param request_id: request_id
  787. :param mid: mid type-string
  788. :param uid: uid type-string
  789. :param size: 请求视频数量 type-int
  790. :param app_type: 产品标识 type-int
  791. :param algo_type: 算法类型 type-string
  792. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  793. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  794. :param params:
  795. :param ab_info_data: app实验分组参数
  796. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  797. :return:
  798. """
  799. # 对 vlog 切换10%的流量做实验
  800. # 对mid进行哈希
  801. # hash_mid = hashlib.md5(mid.encode('utf-8')).hexdigest()
  802. # if app_type in config_.AB_TEST['rank_by_h'] and hash_mid[-1:] in ['8', '0', 'a', 'b']:
  803. # # 简单召回 - 排序 - 兜底
  804. # rank_result, last_rov_recall_key = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  805. # algo_type=algo_type, client_info=client_info,
  806. # expire_time=3600,
  807. # ab_code=config_.AB_CODE['rank_by_h'])
  808. # # ab-test
  809. # result = ab_test_op(rank_result=rank_result,
  810. # ab_code_list=[config_.AB_CODE['position_insert']],
  811. # app_type=app_type, mid=mid, uid=uid)
  812. # # redis数据刷新
  813. # update_redis_data(result=result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  814. # expire_time=3600)
  815. # if app_type == config_.APP_TYPE['APP']:
  816. # # 票圈视频APP
  817. # top_K = config_.K
  818. # flow_pool_P = config_.P
  819. # # 简单召回 - 排序 - 兜底
  820. # rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  821. # mid=mid, uid=uid, app_type=app_type,
  822. # size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  823. # algo_type=algo_type, client_info=client_info,
  824. # expire_time=12 * 3600, params=params)
  825. # # ab-test
  826. # # result = ab_test_op(rank_result=rank_result,
  827. # # ab_code_list=[config_.AB_CODE['position_insert']],
  828. # # app_type=app_type, mid=mid, uid=uid)
  829. # # redis数据刷新
  830. # update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  831. # top_K=top_K, expire_time=12 * 3600)
  832. #
  833. # else:
  834. recommend_result = {}
  835. param_st = time.time()
  836. # 特殊mid 和 小程序审核版本推荐处理
  837. if mid in get_special_mid_list() or version_audit_status == 1:
  838. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  839. recommend_result['videos'] = rank_result
  840. return recommend_result
  841. # 普通mid推荐处理
  842. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  843. get_recommend_params(recommend_type=0, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data)
  844. # log_.info({
  845. # 'logTimestamp': int(time.time() * 1000),
  846. # 'request_id': request_id,
  847. # 'app_type': app_type,
  848. # 'mid': mid,
  849. # 'uid': uid,
  850. # 'operation': 'get_recommend_params',
  851. # 'executeTime': (time.time() - param_st) * 1000
  852. # })
  853. recommend_result['getRecommendParamsTime'] = (time.time() - param_st) * 1000
  854. # 简单召回 - 排序 - 兜底
  855. get_result_st = time.time()
  856. result = video_recommend(request_id=request_id,
  857. mid=mid, uid=uid, app_type=app_type,
  858. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  859. algo_type=algo_type, client_info=client_info,
  860. ab_code=ab_code, expire_time=expire_time,
  861. rule_key=rule_key, data_key=data_key,
  862. no_op_flag=no_op_flag, old_video_index=old_video_index,
  863. params=params)
  864. # log_.info({
  865. # 'logTimestamp': int(time.time() * 1000),
  866. # 'request_id': request_id,
  867. # 'app_type': app_type,
  868. # 'mid': mid,
  869. # 'uid': uid,
  870. # 'operation': 'get_recommend_result',
  871. # 'executeTime': (time.time() - get_result_st) * 1000
  872. # })
  873. recommend_result['recommendOperation'] = result
  874. rank_result = result.get('rankResult')
  875. recommend_result['videos'] = rank_result
  876. recommend_result['getRecommendResultTime'] = (time.time() - get_result_st) * 1000
  877. # ab-test
  878. # result = ab_test_op(rank_result=rank_result,
  879. # ab_code_list=[config_.AB_CODE['position_insert']],
  880. # app_type=app_type, mid=mid, uid=uid)
  881. # redis数据刷新
  882. update_redis_st = time.time()
  883. update_redis_data(result=rank_result, app_type=app_type, mid=mid, top_K=top_K)
  884. # log_.info({
  885. # 'logTimestamp': int(time.time() * 1000),
  886. # 'request_id': request_id,
  887. # 'app_type': app_type,
  888. # 'mid': mid,
  889. # 'uid': uid,
  890. # 'operation': 'update_redis_data',
  891. # 'executeTime': (time.time() - update_redis_st) * 1000
  892. # })
  893. recommend_result['updateRedisDataTime'] = (time.time() - update_redis_st) * 1000
  894. return recommend_result
  895. # return rank_result
  896. def video_relevant_recommend(request_id, video_id, mid, uid, size, app_type, ab_exp_info, client_info,
  897. page_type, params, ab_info_data, version_audit_status):
  898. """
  899. 相关推荐逻辑
  900. :param request_id: request_id
  901. :param video_id: 相关推荐的头部视频id
  902. :param mid: mid type-string
  903. :param uid: uid type-string
  904. :param size: 请求视频数量 type-int
  905. :param app_type: 产品标识 type-int
  906. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  907. :param client_info: 地域参数
  908. :param page_type: 页面区分参数 1:详情页;2:分享页
  909. :param params:
  910. :param ab_info_data: app实验分组参数
  911. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  912. :return: videos type-list
  913. """
  914. recommend_result = {}
  915. param_st = time.time()
  916. # 特殊mid 和 小程序审核版本推荐处理
  917. if mid in get_special_mid_list() or version_audit_status == 1:
  918. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  919. recommend_result['videos'] = rank_result
  920. return recommend_result
  921. # return rank_result
  922. # 普通mid推荐处理
  923. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  924. get_recommend_params(recommend_type=1, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data, page_type=page_type)
  925. # log_.info({
  926. # 'logTimestamp': int(time.time() * 1000),
  927. # 'request_id': request_id,
  928. # 'app_type': app_type,
  929. # 'mid': mid,
  930. # 'uid': uid,
  931. # 'operation': 'get_recommend_params',
  932. # 'executeTime': (time.time() - param_st) * 1000
  933. # })
  934. recommend_result['getRecommendParamsTime'] = (time.time() - param_st) * 1000
  935. # 简单召回 - 排序 - 兜底
  936. get_result_st = time.time()
  937. result = video_recommend(request_id=request_id,
  938. mid=mid, uid=uid, app_type=app_type,
  939. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  940. algo_type='', client_info=client_info,
  941. ab_code=ab_code, expire_time=expire_time,
  942. rule_key=rule_key, data_key=data_key, no_op_flag=no_op_flag,
  943. old_video_index=old_video_index, video_id=video_id,
  944. params=params)
  945. # log_.info({
  946. # 'logTimestamp': int(time.time() * 1000),
  947. # 'request_id': request_id,
  948. # 'app_type': app_type,
  949. # 'mid': mid,
  950. # 'uid': uid,
  951. # 'operation': 'get_recommend_result',
  952. # 'executeTime': (time.time() - get_result_st) * 1000
  953. # })
  954. recommend_result['recommendOperation'] = result
  955. rank_result = result.get('rankResult')
  956. recommend_result['videos'] = rank_result
  957. recommend_result['getRecommendResultTime'] = (time.time() - get_result_st) * 1000
  958. # ab-test
  959. # result = ab_test_op(rank_result=rank_result,
  960. # ab_code_list=[config_.AB_CODE['position_insert'], config_.AB_CODE['relevant_video_op']],
  961. # app_type=app_type, mid=mid, uid=uid, head_vid=video_id, size=size)
  962. # redis数据刷新
  963. update_redis_st = time.time()
  964. update_redis_data(result=rank_result, app_type=app_type, mid=mid, top_K=top_K)
  965. # log_.info({
  966. # 'logTimestamp': int(time.time() * 1000),
  967. # 'request_id': request_id,
  968. # 'app_type': app_type,
  969. # 'mid': mid,
  970. # 'uid': uid,
  971. # 'operation': 'update_redis_data',
  972. # 'executeTime': (time.time() - update_redis_st) * 1000
  973. # })
  974. recommend_result['updateRedisDataTime'] = (time.time() - update_redis_st) * 1000
  975. return recommend_result
  976. # return rank_result
  977. def special_mid_recommend(request_id, mid, uid, app_type, size,
  978. ab_code=config_.AB_CODE['special_mid'],
  979. push_from=config_.PUSH_FROM['special_mid'],
  980. expire_time=24*3600):
  981. redis_helper = RedisHelper()
  982. # 特殊mid推荐指定视频列表
  983. pool_recall = PoolRecall(request_id=request_id, app_type=app_type,
  984. mid=mid, uid=uid, ab_code=ab_code)
  985. # 获取相关redis key
  986. special_key_name, redis_date = pool_recall.get_pool_redis_key(pool_type='special')
  987. # 用户上一次在rov召回池对应的位置
  988. last_special_recall_key = f'{config_.LAST_VIDEO_FROM_SPECIAL_POOL_PREFIX}{app_type}:{mid}:{redis_date}'
  989. value = redis_helper.get_data_from_redis(last_special_recall_key)
  990. if value:
  991. idx = redis_helper.get_index_with_data(special_key_name, value)
  992. if not idx:
  993. idx = 0
  994. else:
  995. idx += 1
  996. else:
  997. idx = 0
  998. recall_result = []
  999. # 每次获取的视频数
  1000. get_size = size * 5
  1001. # 记录获取频次
  1002. freq = 0
  1003. while len(recall_result) < size:
  1004. freq += 1
  1005. if freq > config_.MAX_FREQ_FROM_ROV_POOL:
  1006. break
  1007. # 获取数据
  1008. data = redis_helper.get_data_zset_with_index(key_name=special_key_name,
  1009. start=idx, end=idx + get_size - 1,
  1010. with_scores=True)
  1011. if not data:
  1012. break
  1013. # 获取视频id,并转换类型为int,并存储为key-value{videoId: score}
  1014. # 添加视频源参数 pushFrom, abCode
  1015. temp_result = [{'videoId': int(value[0]), 'rovScore': value[1],
  1016. 'pushFrom': push_from, 'abCode': ab_code}
  1017. for value in data]
  1018. recall_result.extend(temp_result)
  1019. idx += get_size
  1020. # 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
  1021. if mid and recall_result:
  1022. # mid为空时,不做记录
  1023. redis_helper.set_data_to_redis(key_name=last_special_recall_key,
  1024. value=recall_result[:size][-1]['videoId'],
  1025. expire_time=expire_time)
  1026. return recall_result[:size]
  1027. def get_special_mid_list():
  1028. redis_helper = RedisHelper()
  1029. special_mid_list = redis_helper.get_data_from_set(key_name=config_.KEY_NAME_SPECIAL_MID)
  1030. if special_mid_list:
  1031. return special_mid_list
  1032. else:
  1033. return []
  1034. if __name__ == '__main__':
  1035. videos = [
  1036. {"videoId": 10136461, "rovScore": 99.971, "pushFrom": "recall_pool", "abCode": 10000},
  1037. {"videoId": 10239014, "rovScore": 99.97, "pushFrom": "recall_pool", "abCode": 10000},
  1038. {"videoId": 9851154, "rovScore": 99.969, "pushFrom": "recall_pool", "abCode": 10000},
  1039. {"videoId": 10104347, "rovScore": 99.968, "pushFrom": "recall_pool", "abCode": 10000},
  1040. {"videoId": 10141507, "rovScore": 99.967, "pushFrom": "recall_pool", "abCode": 10000},
  1041. {"videoId": 10292817, "flowPool": "2#6#2#1641780979606", "rovScore": 53.926690610816486,
  1042. "pushFrom": "flow_pool", "abCode": 10000},
  1043. {"videoId": 10224932, "flowPool": "2#5#1#1641800279644", "rovScore": 53.47890460059617, "pushFrom": "flow_pool",
  1044. "abCode": 10000},
  1045. {"videoId": 9943255, "rovScore": 99.966, "pushFrom": "recall_pool", "abCode": 10000},
  1046. {"videoId": 10282970, "flowPool": "2#5#1#1641784814103", "rovScore": 52.682815076325575,
  1047. "pushFrom": "flow_pool", "abCode": 10000},
  1048. {"videoId": 10282205, "rovScore": 99.965, "pushFrom": "recall_pool", "abCode": 10000}
  1049. ]
  1050. res = relevant_video_top_recommend(app_type=4, mid='', uid=1111, head_vid=123, videos=videos, size=10)
  1051. print(res)