recommend.py 54 KB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697989910010110210310410510610710810911011111211311411511611711811912012112212312412512612712812913013113213313413513613713813914014114214314414514614714814915015115215315415515615715815916016116216316416516616716816917017117217317417517617717817918018118218318418518618718818919019119219319419519619719819920020120220320420520620720820921021121221321421521621721821922022122222322422522622722822923023123223323423523623723823924024124224324424524624724824925025125225325425525625725825926026126226326426526626726826927027127227327427527627727827928028128228328428528628728828929029129229329429529629729829930030130230330430530630730830931031131231331431531631731831932032132232332432532632732832933033133233333433533633733833934034134234334434534634734834935035135235335435535635735835936036136236336436536636736836937037137237337437537637737837938038138238338438538638738838939039139239339439539639739839940040140240340440540640740840941041141241341441541641741841942042142242342442542642742842943043143243343443543643743843944044144244344444544644744844945045145245345445545645745845946046146246346446546646746846947047147247347447547647747847948048148248348448548648748848949049149249349449549649749849950050150250350450550650750850951051151251351451551651751851952052152252352452552652752852953053153253353453553653753853954054154254354454554654754854955055155255355455555655755855956056156256356456556656756856957057157257357457557657757857958058158258358458558658758858959059159259359459559659759859960060160260360460560660760860961061161261361461561661761861962062162262362462562662762862963063163263363463563663763863964064164264364464564664764864965065165265365465565665765865966066166266366466566666766866967067167267367467567667767867968068168268368468568668768868969069169269369469569669769869970070170270370470570670770870971071171271371471571671771871972072172272372472572672772872973073173273373473573673773873974074174274374474574674774874975075175275375475575675775875976076176276376476576676776876977077177277377477577677777877978078178278378478578678778878979079179279379479579679779879980080180280380480580680780880981081181281381481581681781881982082182282382482582682782882983083183283383483583683783883984084184284384484584684784884985085185285385485585685785885986086186286386486586686786886987087187287387487587687787887988088188288388488588688788888989089189289389489589689789889990090190290390490590690790890991091191291391491591691791891992092192292392492592692792892993093193293393493593693793893994094194294394494594694794894995095195295395495595695795895996096196296396496596696796896997097197297397497597697797897998098198298398498598698798898999099199299399499599699799899910001001100210031004100510061007100810091010101110121013101410151016101710181019102010211022102310241025102610271028102910301031103210331034103510361037103810391040104110421043104410451046104710481049105010511052105310541055105610571058105910601061106210631064106510661067106810691070107110721073107410751076107710781079108010811082108310841085108610871088108910901091109210931094109510961097109810991100110111021103110411051106110711081109111011111112111311141115111611171118111911201121
  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(
  273. size=size, app_type=app_type, mid=mid, uid=uid, ab_code=ab_code, client_info=client_info, params=params
  274. )
  275. else:
  276. rank_result = bottom_strategy(
  277. request_id=request_id, size=size, app_type=app_type, ab_code=ab_code, params=params
  278. )
  279. log_.info({
  280. 'logTimestamp': int(time.time() * 1000),
  281. 'request_id': request_id,
  282. 'mid': mid,
  283. 'uid': uid,
  284. 'operation': 'bottom',
  285. 'bottom_result': rank_result,
  286. 'executeTime': (time.time() - start_bottom) * 1000
  287. })
  288. return rank_result, last_rov_recall_key
  289. def ab_test_op(rank_result, ab_code_list, app_type, mid, uid, **kwargs):
  290. """
  291. 对排序后的结果 按照AB实验进行对应的分组操作
  292. :param rank_result: 排序后的结果
  293. :param ab_code_list: 此次请求参与的 ab实验组
  294. :param app_type: 产品标识
  295. :param mid: mid
  296. :param uid: uid
  297. :param kwargs: 其他参数
  298. :return:
  299. """
  300. # ####### 视频宽高比AB实验
  301. # 对内容精选进行 视频宽高比分发实验
  302. # if config_.AB_CODE['w_h_rate'] in ab_code_list and app_type in config_.AB_TEST.get('w_h_rate', []):
  303. # rank_result = video_rank_by_w_h_rate(videos=rank_result)
  304. # log_.info('app_type: {}, mid: {}, uid: {}, rank_by_w_h_rate_result: {}'.format(
  305. # app_type, mid, uid, rank_result))
  306. # 按position位置排序
  307. if config_.AB_CODE['position_insert'] in ab_code_list and app_type in config_.AB_TEST.get('position_insert', []):
  308. rank_result = video_position_recommend(mid, uid, app_type, rank_result)
  309. print('===========================')
  310. print(rank_result)
  311. log_.info('app_type: {}, mid: {}, uid: {}, rank_by_position_insert_result: {}'.format(
  312. app_type, mid, uid, rank_result))
  313. # 相关推荐强插
  314. # if config_.AB_CODE['relevant_video_op'] in ab_code_list \
  315. # and app_type in config_.AB_TEST.get('relevant_video_op', []):
  316. # head_vid = kwargs['head_vid']
  317. # size = kwargs['size']
  318. # rank_result = relevant_video_top_recommend(
  319. # app_type=app_type, mid=mid, uid=uid, head_vid=head_vid, videos=rank_result, size=size
  320. # )
  321. # log_.info('app_type: {}, mid: {}, uid: {}, head_vid: {}, rank_by_relevant_video_op_result: {}'.format(
  322. # app_type, mid, uid, head_vid, rank_result))
  323. return rank_result
  324. def update_redis_data(result, app_type, mid, last_rov_recall_key, top_K, expire_time=24*3600):
  325. """
  326. 根据最终的排序结果更新相关redis数据
  327. :param result: 排序结果
  328. :param app_type: 产品标识
  329. :param mid: mid
  330. :param last_rov_recall_key: 用户上一次在rov召回池对应的位置 redis key
  331. :param top_K: 保证topK为召回池视频 type-int
  332. :param expire_time: 末位视频记录redis过期时间
  333. :return: None
  334. """
  335. # ####### redis数据刷新
  336. try:
  337. redis_helper = RedisHelper()
  338. # log_.info('====== update redis')
  339. if mid and mid != 'null':
  340. # mid为空时,不做预曝光和定位数据更新
  341. # 预曝光数据同步刷新到Redis, 过期时间为0.5h
  342. preview_key_name = f"{config_.PREVIEW_KEY_PREFIX}{app_type}:{mid}"
  343. preview_video_ids = [int(item['videoId']) for item in result]
  344. if preview_video_ids:
  345. # log_.error('key_name = {} \n values = {}'.format(preview_key_name, tuple(preview_video_ids)))
  346. redis_helper.add_data_with_set(key_name=preview_key_name, values=tuple(preview_video_ids), expire_time=30 * 60)
  347. # log_.info('preview redis update success!')
  348. # 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
  349. rov_recall_video = [item['videoId'] for item in result[:top_K]
  350. if item['pushFrom'] == config_.PUSH_FROM['rov_recall']]
  351. if len(rov_recall_video) > 0:
  352. if app_type == config_.APP_TYPE['APP']:
  353. key_name = config_.UPDATE_ROV_KEY_NAME_APP
  354. else:
  355. key_name = config_.UPDATE_ROV_KEY_NAME
  356. if not redis_helper.get_score_with_value(key_name=key_name, value=rov_recall_video[-1]):
  357. redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[-1],
  358. expire_time=expire_time)
  359. # log_.info('last video redis update success!')
  360. # 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
  361. rov_recall_h_video = [item['videoId'] for item in result[:top_K]
  362. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_h']]
  363. if len(rov_recall_h_video) > 0:
  364. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_H_PREFIX}{app_type}:{mid}'
  365. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_h_video[-1],
  366. expire_time=expire_time)
  367. # 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
  368. rov_recall_24h_dup1_video = [item['videoId'] for item in result[:top_K]
  369. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_region_24h']]
  370. if len(rov_recall_24h_dup1_video) > 0:
  371. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP1_24H_PREFIX}{app_type}:{mid}'
  372. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup1_video[-1],
  373. expire_time=expire_time)
  374. # 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
  375. rov_recall_24h_dup2_video = [item['videoId'] for item in result[:top_K]
  376. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h']]
  377. if len(rov_recall_24h_dup2_video) > 0:
  378. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_24H_PREFIX}{app_type}:{mid}'
  379. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup2_video[-1],
  380. expire_time=expire_time)
  381. # 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
  382. rov_recall_24h_dup3_video = [item['videoId'] for item in result[:top_K]
  383. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_24h_dup']]
  384. if len(rov_recall_24h_dup3_video) > 0:
  385. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_24H_PREFIX}{app_type}:{mid}'
  386. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_24h_dup3_video[-1],
  387. expire_time=expire_time)
  388. # 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
  389. rov_recall_48h_dup2_video = [item['videoId'] for item in result[:top_K]
  390. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h']]
  391. if len(rov_recall_48h_dup2_video) > 0:
  392. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP2_48H_PREFIX}{app_type}:{mid}'
  393. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup2_video[-1],
  394. expire_time=expire_time)
  395. # 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
  396. rov_recall_48h_dup3_video = [item['videoId'] for item in result[:top_K]
  397. if item['pushFrom'] == config_.PUSH_FROM['rov_recall_48h_dup']]
  398. if len(rov_recall_48h_dup3_video) > 0:
  399. last_video_key = f'{config_.LAST_VIDEO_FROM_REGION_DUP3_48H_PREFIX}{app_type}:{mid}'
  400. redis_helper.set_data_to_redis(key_name=last_video_key, value=rov_recall_48h_dup3_video[-1],
  401. expire_time=expire_time)
  402. # 将此次分发的流量池视频,对 本地分发数-1 进行记录
  403. if app_type not in [config_.APP_TYPE['LAO_HAO_KAN_VIDEO'], config_.APP_TYPE['ZUI_JING_QI']]:
  404. flow_recall_video = [item for item in result if item['pushFrom'] == config_.PUSH_FROM['flow_recall']]
  405. if flow_recall_video:
  406. update_local_distribute_count(flow_recall_video)
  407. # log_.info('update local distribute count success!')
  408. # 限流视频分发数记录
  409. if app_type == config_.APP_TYPE['APP']:
  410. # APP 不计入
  411. return
  412. limit_video_id_list = redis_helper.get_data_from_set(
  413. key_name=f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_SET}{datetime.today().strftime('%Y%m%d')}"
  414. )
  415. if limit_video_id_list is not None:
  416. limit_video_id_list = [int(item) for item in limit_video_id_list]
  417. for item in result:
  418. video_id = item['videoId']
  419. if video_id in limit_video_id_list:
  420. key_name = f"{config_.KEY_NAME_PREFIX_LIMIT_VIDEO_DISTRIBUTE_COUNT}{video_id}"
  421. redis_helper.setnx_key(key_name=key_name, value=0, expire_time=24*2600)
  422. redis_helper.incr_key(key_name=key_name, amount=1, expire_time=24*3600)
  423. except Exception as e:
  424. log_.error("update redis data fail!")
  425. log_.error(traceback.format_exc())
  426. def update_local_distribute_count(videos):
  427. """
  428. 更新本地分发数
  429. :param videos: 视频列表 type-list [{'videoId':'', 'flowPool':'', 'distributeCount': '',
  430. 'rovScore': '', 'pushFrom': 'flow_pool', 'abCode': self.ab_code}, ....]
  431. :return:
  432. """
  433. try:
  434. redis_helper = RedisHelper()
  435. for item in videos:
  436. key_name = f"{config_.LOCAL_DISTRIBUTE_COUNT_PREFIX}{item['videoId']}:{item['flowPool']}"
  437. # 本地记录的分发数 - 1
  438. redis_helper.decr_key(key_name=key_name, amount=1, expire_time=15 * 60)
  439. # if redis_helper.key_exists(key_name=key_name):
  440. # # 该视频本地有记录,本地记录的分发数 - 1
  441. # redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
  442. # else:
  443. # # 该视频本地无记录,接口获取的分发数 - 1
  444. # redis_helper.incr_key(key_name=key_name, amount=int(item['distributeCount']) - 1, expire_time=5 * 60)
  445. except Exception as e:
  446. log_.error('update_local_distribute_count error...')
  447. log_.error(traceback.format_exc())
  448. def get_recommend_params(recommend_type, ab_exp_info, ab_info_data, page_type=0):
  449. """
  450. 根据实验分组给定对应的推荐参数
  451. :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)
  452. :param ab_exp_info: AB实验组参数
  453. :param ab_info_data: app实验组参数
  454. :param page_type: 页面区分参数,默认:0(首页)
  455. :return:
  456. """
  457. top_K = config_.K
  458. flow_pool_P = config_.P
  459. # 不获取人工干预数据标记
  460. no_op_flag = False
  461. old_video_index = -1
  462. # if not ab_exp_info:
  463. # ab_code = config_.AB_CODE['initial']
  464. # expire_time = 24 * 3600
  465. # rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  466. # data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  467. # # old_video_index = -1
  468. # else:
  469. # 默认使用 095 实验的配置
  470. ab_code = config_.AB_EXP_CODE['095'].get('ab_code')
  471. expire_time = 3600
  472. rule_key = config_.AB_EXP_CODE['095'].get('rule_key')
  473. data_key = config_.AB_EXP_CODE['095'].get('data_key')
  474. no_op_flag = True
  475. # 获取实验配置
  476. if ab_exp_info:
  477. ab_exp_code_list = []
  478. config_value_dict = {}
  479. for _, item in ab_exp_info.items():
  480. if not item:
  481. continue
  482. for ab_item in item:
  483. ab_exp_code = ab_item.get('abExpCode', None)
  484. if not ab_exp_code:
  485. continue
  486. ab_exp_code_list.append(str(ab_exp_code))
  487. config_value_dict[str(ab_exp_code)] = ab_item.get('configValue', None)
  488. for code, param in config_.AB_EXP_CODE.items():
  489. if code in ab_exp_code_list:
  490. ab_code = param.get('ab_code')
  491. expire_time = 3600
  492. rule_key = param.get('rule_key')
  493. data_key = param.get('data_key')
  494. no_op_flag = True
  495. break
  496. """
  497. # 推荐条数 10->4 实验
  498. # if config_.AB_EXP_CODE['rec_size_home'] in ab_exp_code_list:
  499. # config_value = config_value_dict.get(config_.AB_EXP_CODE['rec_size_home'], None)
  500. # if config_value:
  501. # config_value = eval(str(config_value))
  502. # else:
  503. # config_value = {}
  504. # log_.info(f'config_value: {config_value}, type: {type(config_value)}')
  505. # size = int(config_value.get('size', 4))
  506. # top_K = int(config_value.get('K', 3))
  507. # flow_pool_P = float(config_value.get('P', 0.3))
  508. # else:
  509. # size = size
  510. # top_K = config_.K
  511. # flow_pool_P = config_.P
  512. # 算法实验相对对照组
  513. # if config_.AB_EXP_CODE['ab_initial'] in ab_exp_code_list:
  514. # ab_code = config_.AB_CODE['ab_initial']
  515. # expire_time = 24 * 3600
  516. # rule_key = config_.RULE_KEY['initial']
  517. # no_op_flag = True
  518. # 小时级更新-规则1 实验
  519. # elif config_.AB_EXP_CODE['rule_rank1'] in ab_exp_code_list:
  520. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank1')
  521. # expire_time = 3600
  522. # rule_key = config_.RULE_KEY['rule_rank1']
  523. # no_op_flag = True
  524. # elif config_.AB_EXP_CODE['rule_rank2'] in ab_exp_code_list:
  525. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank2')
  526. # expire_time = 3600
  527. # rule_key = config_.RULE_KEY['rule_rank2']
  528. # elif config_.AB_EXP_CODE['rule_rank3'] in ab_exp_code_list:
  529. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank3')
  530. # expire_time = 3600
  531. # rule_key = config_.RULE_KEY['rule_rank3']
  532. # no_op_flag = True
  533. # elif config_.AB_EXP_CODE['rule_rank4'] in ab_exp_code_list:
  534. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank4')
  535. # expire_time = 3600
  536. # rule_key = config_.RULE_KEY['rule_rank4']
  537. # elif config_.AB_EXP_CODE['rule_rank5'] in ab_exp_code_list:
  538. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank5')
  539. # expire_time = 3600
  540. # rule_key = config_.RULE_KEY['rule_rank5']
  541. # elif config_.AB_EXP_CODE['day_rule_rank1'] in ab_exp_code_list:
  542. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank1')
  543. # expire_time = 24 * 3600
  544. # rule_key = config_.RULE_KEY_DAY['day_rule_rank1']
  545. # no_op_flag = True
  546. # if config_.AB_EXP_CODE['rule_rank6'] in ab_exp_code_list:
  547. # ab_code = config_.AB_CODE['rank_by_h'].get('rule_rank6')
  548. # expire_time = 3600
  549. # rule_key = config_.RULE_KEY['rule_rank6']
  550. # no_op_flag = True
  551. # elif config_.AB_EXP_CODE['day_rule_rank2'] in ab_exp_code_list:
  552. # ab_code = config_.AB_CODE['rank_by_day'].get('day_rule_rank2')
  553. # expire_time = 24 * 3600
  554. # rule_key = config_.RULE_KEY_DAY['day_rule_rank2']
  555. # no_op_flag = True
  556. # elif config_.AB_EXP_CODE['region_rule_rank1'] in ab_exp_code_list:
  557. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank1')
  558. # expire_time = 3600
  559. # rule_key = config_.RULE_KEY_REGION['region_rule_rank1']
  560. # no_op_flag = True
  561. # elif config_.AB_EXP_CODE['24h_rule_rank1'] in ab_exp_code_list:
  562. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank1')
  563. # expire_time = 3600
  564. # rule_key = config_.RULE_KEY_24H['24h_rule_rank1']
  565. # no_op_flag = True
  566. # elif config_.AB_EXP_CODE['24h_rule_rank2'] in ab_exp_code_list:
  567. # ab_code = config_.AB_CODE['rank_by_24h'].get('24h_rule_rank2')
  568. # expire_time = 3600
  569. # rule_key = config_.RULE_KEY_24H['24h_rule_rank2']
  570. # no_op_flag = True
  571. # elif config_.AB_EXP_CODE['region_rule_rank2'] in ab_exp_code_list:
  572. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank2')
  573. # expire_time = 3600
  574. # rule_key = config_.RULE_KEY_REGION['region_rule_rank2']
  575. # no_op_flag = True
  576. # if config_.AB_EXP_CODE['region_rule_rank3'] in ab_exp_code_list or\
  577. # config_.AB_EXP_CODE['region_rule_rank3_appType_19'] in ab_exp_code_list or\
  578. # config_.AB_EXP_CODE['region_rule_rank3_appType_4'] in ab_exp_code_list or\
  579. # config_.AB_EXP_CODE['region_rule_rank3_appType_6'] in ab_exp_code_list or\
  580. # config_.AB_EXP_CODE['region_rule_rank3_appType_18'] in ab_exp_code_list:
  581. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3')
  582. # expire_time = 3600
  583. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('rule_key')
  584. # data_key = config_.RULE_KEY_REGION['region_rule_rank3'].get('data_key')
  585. # no_op_flag = True
  586. # if config_.AB_EXP_CODE['region_rule_rank4'] in ab_exp_code_list or\
  587. if config_.AB_EXP_CODE['region_rule_rank4_appType_19'] in ab_exp_code_list or \
  588. config_.AB_EXP_CODE['region_rule_rank4_appType_4'] in ab_exp_code_list or\
  589. config_.AB_EXP_CODE['region_rule_rank4_appType_6'] in ab_exp_code_list or\
  590. config_.AB_EXP_CODE['region_rule_rank4_appType_18'] in ab_exp_code_list:
  591. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  592. expire_time = 3600
  593. rule_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('rule_key')
  594. data_key = config_.RULE_KEY_REGION['region_rule_rank4'].get('data_key')
  595. no_op_flag = True
  596. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data1'] in ab_exp_code_list:
  597. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  598. # expire_time = 3600
  599. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('rule_key')
  600. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data1'].get('data_key')
  601. # no_op_flag = True
  602. # elif config_.AB_EXP_CODE['region_rule_rank3_appType_5_data2'] in ab_exp_code_list:
  603. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank3_appType_5_data2')
  604. # expire_time = 3600
  605. # rule_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('rule_key')
  606. # data_key = config_.RULE_KEY_REGION['region_rule_rank3_appType_5_data2'].get('data_key')
  607. # no_op_flag = True
  608. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data3'] in ab_exp_code_list:
  609. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data3')
  610. expire_time = 3600
  611. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('rule_key')
  612. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data3'].get('data_key')
  613. no_op_flag = True
  614. elif config_.AB_EXP_CODE['region_rule_rank4_appType_5_data4'] in ab_exp_code_list:
  615. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_5_data4')
  616. expire_time = 3600
  617. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('rule_key')
  618. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_5_data4'].get('data_key')
  619. no_op_flag = True
  620. elif config_.AB_EXP_CODE['region_rule_rank4_appType_0_data2'] in ab_exp_code_list:
  621. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_0_data2')
  622. expire_time = 3600
  623. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('rule_key')
  624. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_0_data2'].get('data_key')
  625. no_op_flag = True
  626. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data2'] in ab_exp_code_list:
  627. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data2')
  628. # expire_time = 3600
  629. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('rule_key')
  630. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data2'].get('data_key')
  631. # no_op_flag = True
  632. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_19_data3'] in ab_exp_code_list:
  633. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_19_data3')
  634. # expire_time = 3600
  635. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('rule_key')
  636. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_19_data3'].get('data_key')
  637. # no_op_flag = True
  638. elif config_.AB_EXP_CODE['region_rule_rank5_appType_0_data1'] in ab_exp_code_list:
  639. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank5_appType_0_data1')
  640. expire_time = 3600
  641. rule_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('rule_key')
  642. data_key = config_.RULE_KEY_REGION['region_rule_rank5_appType_0_data1'].get('data_key')
  643. no_op_flag = True
  644. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data2'] in ab_exp_code_list:
  645. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data2')
  646. expire_time = 3600
  647. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('rule_key')
  648. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data2'].get('data_key')
  649. no_op_flag = True
  650. elif config_.AB_EXP_CODE['region_rule_rank4_appType_4_data3'] in ab_exp_code_list:
  651. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_4_data3')
  652. expire_time = 3600
  653. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('rule_key')
  654. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_4_data3'].get('data_key')
  655. no_op_flag = True
  656. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data2'] in ab_exp_code_list:
  657. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data2')
  658. expire_time = 3600
  659. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('rule_key')
  660. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data2'].get('data_key')
  661. no_op_flag = True
  662. elif config_.AB_EXP_CODE['region_rule_rank4_appType_6_data3'] in ab_exp_code_list:
  663. ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_6_data3')
  664. expire_time = 3600
  665. rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('rule_key')
  666. data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_6_data3'].get('data_key')
  667. no_op_flag = True
  668. # elif config_.AB_EXP_CODE['region_rule_rank4_appType_18_data2'] in ab_exp_code_list:
  669. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4_appType_18_data2')
  670. # expire_time = 3600
  671. # rule_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('rule_key')
  672. # data_key = config_.RULE_KEY_REGION['region_rule_rank4_appType_18_data2'].get('data_key')
  673. # no_op_flag = True
  674. # elif config_.AB_EXP_CODE['region_rule_rank6_appType_0_data1'] in ab_exp_code_list:
  675. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_0_data1')
  676. # expire_time = 3600
  677. # rule_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('rule_key')
  678. # data_key = config_.RULE_KEY_REGION['region_rule_rank6_appType_0_data1'].get('data_key')
  679. # no_op_flag = True
  680. else:
  681. ab_code = config_.AB_CODE['initial']
  682. expire_time = 24 * 3600
  683. rule_key = config_.RULE_KEY_REGION['initial'].get('rule_key')
  684. data_key = config_.RULE_KEY_REGION['initial'].get('data_key')
  685. # # 老好看视频 / 票圈最惊奇 首页/相关推荐逻辑更新实验
  686. # if config_.AB_EXP_CODE['rov_rank_appType_18_19'] in ab_exp_code_list:
  687. # ab_code = config_.AB_CODE['rov_rank_appType_18_19']
  688. # expire_time = 3600
  689. # flow_pool_P = config_.P_18_19
  690. # no_op_flag = True
  691. #
  692. # elif config_.AB_EXP_CODE['rov_rank_appType_19'] in ab_exp_code_list:
  693. # ab_code = config_.AB_CODE['rov_rank_appType_19']
  694. # expire_time = 3600
  695. # top_K = 0
  696. # flow_pool_P = config_.P_18_19
  697. # no_op_flag = True
  698. #
  699. # elif config_.AB_EXP_CODE['top_video_relevant_appType_19'] in ab_exp_code_list and page_type == 2:
  700. # ab_code = config_.AB_CODE['top_video_relevant_appType_19']
  701. # expire_time = 3600
  702. # top_K = 1
  703. # flow_pool_P = config_.P_18_19
  704. # no_op_flag = True
  705. #
  706. # # 票圈最惊奇完整影视资源实验
  707. # elif config_.AB_EXP_CODE['whole_movies'] in ab_exp_code_list:
  708. # ab_code = config_.AB_CODE['whole_movies']
  709. # expire_time = 24 * 3600
  710. # no_op_flag = True
  711. # 老视频实验
  712. # if config_.AB_EXP_CODE['old_video'] in ab_exp_code_list:
  713. # ab_code = config_.AB_CODE['old_video']
  714. # no_op_flag = True
  715. # old_video_index = 2
  716. # else:
  717. # old_video_index = -1
  718. """
  719. # APP实验组
  720. # if ab_info_data:
  721. # ab_info_app = {}
  722. # for page_code, item in json.loads(ab_info_data).items():
  723. # if not item:
  724. # continue
  725. # ab_info_code = item.get('eventId', None)
  726. # if ab_info_code:
  727. # ab_info_app[page_code] = ab_info_code
  728. # print(f"======{ab_info_app}")
  729. #
  730. # # 首页推荐
  731. # if recommend_type == 0:
  732. # if config_.APP_AB_CODE['10003'].get('region_rule_rank6_appType_13_data2') == ab_info_app.get('10003', None):
  733. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank6_appType_13_data2')
  734. # expire_time = 3600
  735. # rule_key = 'rule6'
  736. # data_key = 'data7'
  737. # no_op_flag = True
  738. # else:
  739. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  740. # expire_time = 3600
  741. # rule_key = 'rule3'
  742. # data_key = 'data1'
  743. # no_op_flag = True
  744. # # 相关推荐
  745. # elif recommend_type == 1:
  746. # if config_.APP_AB_CODE['10037'] == ab_info_app.get('10037', None):
  747. # ab_code = config_.AB_CODE['region_rank_by_h'].get('region_rule_rank4')
  748. # expire_time = 3600
  749. # rule_key = 'rule3'
  750. # data_key = 'data1'
  751. # no_op_flag = True
  752. return top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index
  753. def video_homepage_recommend(request_id, mid, uid, size, app_type, algo_type,
  754. client_info, ab_exp_info, params, ab_info_data, version_audit_status):
  755. """
  756. 首页线上推荐逻辑
  757. :param request_id: request_id
  758. :param mid: mid type-string
  759. :param uid: uid type-string
  760. :param size: 请求视频数量 type-int
  761. :param app_type: 产品标识 type-int
  762. :param algo_type: 算法类型 type-string
  763. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  764. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  765. :param params:
  766. :param ab_info_data: app实验分组参数
  767. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  768. :return:
  769. """
  770. # 对 vlog 切换10%的流量做实验
  771. # 对mid进行哈希
  772. # hash_mid = hashlib.md5(mid.encode('utf-8')).hexdigest()
  773. # if app_type in config_.AB_TEST['rank_by_h'] and hash_mid[-1:] in ['8', '0', 'a', 'b']:
  774. # # 简单召回 - 排序 - 兜底
  775. # rank_result, last_rov_recall_key = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  776. # algo_type=algo_type, client_info=client_info,
  777. # expire_time=3600,
  778. # ab_code=config_.AB_CODE['rank_by_h'])
  779. # # ab-test
  780. # result = ab_test_op(rank_result=rank_result,
  781. # ab_code_list=[config_.AB_CODE['position_insert']],
  782. # app_type=app_type, mid=mid, uid=uid)
  783. # # redis数据刷新
  784. # update_redis_data(result=result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  785. # expire_time=3600)
  786. # if app_type == config_.APP_TYPE['APP']:
  787. # # 票圈视频APP
  788. # top_K = config_.K
  789. # flow_pool_P = config_.P
  790. # # 简单召回 - 排序 - 兜底
  791. # rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  792. # mid=mid, uid=uid, app_type=app_type,
  793. # size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  794. # algo_type=algo_type, client_info=client_info,
  795. # expire_time=12 * 3600, params=params)
  796. # # ab-test
  797. # # result = ab_test_op(rank_result=rank_result,
  798. # # ab_code_list=[config_.AB_CODE['position_insert']],
  799. # # app_type=app_type, mid=mid, uid=uid)
  800. # # redis数据刷新
  801. # update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  802. # top_K=top_K, expire_time=12 * 3600)
  803. #
  804. # else:
  805. param_st = time.time()
  806. # 特殊mid 和 小程序审核版本推荐处理
  807. if mid in get_special_mid_list() or version_audit_status == 1:
  808. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  809. return rank_result
  810. # 普通mid推荐处理
  811. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  812. get_recommend_params(recommend_type=0, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data)
  813. log_.info({
  814. 'logTimestamp': int(time.time() * 1000),
  815. 'request_id': request_id,
  816. 'app_type': app_type,
  817. 'mid': mid,
  818. 'uid': uid,
  819. 'operation': 'get_recommend_params',
  820. 'executeTime': (time.time() - param_st) * 1000
  821. })
  822. # 简单召回 - 排序 - 兜底
  823. get_result_st = time.time()
  824. rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  825. mid=mid, uid=uid, app_type=app_type,
  826. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  827. algo_type=algo_type, client_info=client_info,
  828. ab_code=ab_code, expire_time=expire_time,
  829. rule_key=rule_key, data_key=data_key,
  830. no_op_flag=no_op_flag, old_video_index=old_video_index,
  831. params=params)
  832. log_.info({
  833. 'logTimestamp': int(time.time() * 1000),
  834. 'request_id': request_id,
  835. 'app_type': app_type,
  836. 'mid': mid,
  837. 'uid': uid,
  838. 'operation': 'get_recommend_result',
  839. 'executeTime': (time.time() - get_result_st) * 1000
  840. })
  841. # ab-test
  842. # result = ab_test_op(rank_result=rank_result,
  843. # ab_code_list=[config_.AB_CODE['position_insert']],
  844. # app_type=app_type, mid=mid, uid=uid)
  845. # redis数据刷新
  846. update_redis_st = time.time()
  847. update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  848. top_K=top_K)
  849. log_.info({
  850. 'logTimestamp': int(time.time() * 1000),
  851. 'request_id': request_id,
  852. 'app_type': app_type,
  853. 'mid': mid,
  854. 'uid': uid,
  855. 'operation': 'update_redis_data',
  856. 'executeTime': (time.time() - update_redis_st) * 1000
  857. })
  858. return rank_result
  859. def video_relevant_recommend(request_id, video_id, mid, uid, size, app_type, ab_exp_info, client_info,
  860. page_type, params, ab_info_data, version_audit_status):
  861. """
  862. 相关推荐逻辑
  863. :param request_id: request_id
  864. :param video_id: 相关推荐的头部视频id
  865. :param mid: mid type-string
  866. :param uid: uid type-string
  867. :param size: 请求视频数量 type-int
  868. :param app_type: 产品标识 type-int
  869. :param ab_exp_info: ab实验分组参数 [{"expItemId":1, "configValue":{"size":4, "K":3, ...}}, ...]
  870. :param client_info: 地域参数
  871. :param page_type: 页面区分参数 1:详情页;2:分享页
  872. :param params:
  873. :param ab_info_data: app实验分组参数
  874. :param version_audit_status: 小程序版本审核参数:1-审核中,2-审核通过
  875. :return: videos type-list
  876. """
  877. param_st = time.time()
  878. # 特殊mid 和 小程序审核版本推荐处理
  879. if mid in get_special_mid_list() or version_audit_status == 1:
  880. rank_result = special_mid_recommend(request_id=request_id, mid=mid, uid=uid, app_type=app_type, size=size)
  881. return rank_result
  882. # 普通mid推荐处理
  883. top_K, flow_pool_P, ab_code, rule_key, data_key, expire_time, no_op_flag, old_video_index = \
  884. get_recommend_params(recommend_type=1, ab_exp_info=ab_exp_info, ab_info_data=ab_info_data, page_type=page_type)
  885. log_.info({
  886. 'logTimestamp': int(time.time() * 1000),
  887. 'request_id': request_id,
  888. 'app_type': app_type,
  889. 'mid': mid,
  890. 'uid': uid,
  891. 'operation': 'get_recommend_params',
  892. 'executeTime': (time.time() - param_st) * 1000
  893. })
  894. # 简单召回 - 排序 - 兜底
  895. get_result_st = time.time()
  896. rank_result, last_rov_recall_key = video_recommend(request_id=request_id,
  897. mid=mid, uid=uid, app_type=app_type,
  898. size=size, top_K=top_K, flow_pool_P=flow_pool_P,
  899. algo_type='', client_info=client_info,
  900. ab_code=ab_code, expire_time=expire_time,
  901. rule_key=rule_key, data_key=data_key, no_op_flag=no_op_flag,
  902. old_video_index=old_video_index, video_id=video_id,
  903. params=params)
  904. log_.info({
  905. 'logTimestamp': int(time.time() * 1000),
  906. 'request_id': request_id,
  907. 'app_type': app_type,
  908. 'mid': mid,
  909. 'uid': uid,
  910. 'operation': 'get_recommend_result',
  911. 'executeTime': (time.time() - get_result_st) * 1000
  912. })
  913. # ab-test
  914. # result = ab_test_op(rank_result=rank_result,
  915. # ab_code_list=[config_.AB_CODE['position_insert'], config_.AB_CODE['relevant_video_op']],
  916. # app_type=app_type, mid=mid, uid=uid, head_vid=video_id, size=size)
  917. # redis数据刷新
  918. update_redis_st = time.time()
  919. update_redis_data(result=rank_result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key,
  920. top_K=top_K)
  921. log_.info({
  922. 'logTimestamp': int(time.time() * 1000),
  923. 'request_id': request_id,
  924. 'app_type': app_type,
  925. 'mid': mid,
  926. 'uid': uid,
  927. 'operation': 'update_redis_data',
  928. 'executeTime': (time.time() - update_redis_st) * 1000
  929. })
  930. return rank_result
  931. def special_mid_recommend(request_id, mid, uid, app_type, size,
  932. ab_code=config_.AB_CODE['special_mid'],
  933. push_from=config_.PUSH_FROM['special_mid'],
  934. expire_time=24*3600):
  935. redis_helper = RedisHelper()
  936. # 特殊mid推荐指定视频列表
  937. pool_recall = PoolRecall(request_id=request_id, app_type=app_type,
  938. mid=mid, uid=uid, ab_code=ab_code)
  939. # 获取相关redis key
  940. special_key_name, redis_date = pool_recall.get_pool_redis_key(pool_type='special')
  941. # 用户上一次在rov召回池对应的位置
  942. last_special_recall_key = f'{config_.LAST_VIDEO_FROM_SPECIAL_POOL_PREFIX}{app_type}:{mid}:{redis_date}'
  943. value = redis_helper.get_data_from_redis(last_special_recall_key)
  944. if value:
  945. idx = redis_helper.get_index_with_data(special_key_name, value)
  946. if not idx:
  947. idx = 0
  948. else:
  949. idx += 1
  950. else:
  951. idx = 0
  952. recall_result = []
  953. # 每次获取的视频数
  954. get_size = size * 5
  955. # 记录获取频次
  956. freq = 0
  957. while len(recall_result) < size:
  958. freq += 1
  959. if freq > config_.MAX_FREQ_FROM_ROV_POOL:
  960. break
  961. # 获取数据
  962. data = redis_helper.get_data_zset_with_index(key_name=special_key_name,
  963. start=idx, end=idx + get_size - 1,
  964. with_scores=True)
  965. if not data:
  966. break
  967. # 获取视频id,并转换类型为int,并存储为key-value{videoId: score}
  968. # 添加视频源参数 pushFrom, abCode
  969. temp_result = [{'videoId': int(value[0]), 'rovScore': value[1],
  970. 'pushFrom': push_from, 'abCode': ab_code}
  971. for value in data]
  972. recall_result.extend(temp_result)
  973. idx += get_size
  974. # 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
  975. if mid and recall_result:
  976. # mid为空时,不做记录
  977. redis_helper.set_data_to_redis(key_name=last_special_recall_key,
  978. value=recall_result[:size][-1]['videoId'],
  979. expire_time=expire_time)
  980. return recall_result[:size]
  981. def get_special_mid_list():
  982. redis_helper = RedisHelper()
  983. special_mid_list = redis_helper.get_data_from_set(key_name=config_.KEY_NAME_SPECIAL_MID)
  984. if special_mid_list:
  985. return special_mid_list
  986. else:
  987. return []
  988. if __name__ == '__main__':
  989. videos = [
  990. {"videoId": 10136461, "rovScore": 99.971, "pushFrom": "recall_pool", "abCode": 10000},
  991. {"videoId": 10239014, "rovScore": 99.97, "pushFrom": "recall_pool", "abCode": 10000},
  992. {"videoId": 9851154, "rovScore": 99.969, "pushFrom": "recall_pool", "abCode": 10000},
  993. {"videoId": 10104347, "rovScore": 99.968, "pushFrom": "recall_pool", "abCode": 10000},
  994. {"videoId": 10141507, "rovScore": 99.967, "pushFrom": "recall_pool", "abCode": 10000},
  995. {"videoId": 10292817, "flowPool": "2#6#2#1641780979606", "rovScore": 53.926690610816486,
  996. "pushFrom": "flow_pool", "abCode": 10000},
  997. {"videoId": 10224932, "flowPool": "2#5#1#1641800279644", "rovScore": 53.47890460059617, "pushFrom": "flow_pool",
  998. "abCode": 10000},
  999. {"videoId": 9943255, "rovScore": 99.966, "pushFrom": "recall_pool", "abCode": 10000},
  1000. {"videoId": 10282970, "flowPool": "2#5#1#1641784814103", "rovScore": 52.682815076325575,
  1001. "pushFrom": "flow_pool", "abCode": 10000},
  1002. {"videoId": 10282205, "rovScore": 99.965, "pushFrom": "recall_pool", "abCode": 10000}
  1003. ]
  1004. res = relevant_video_top_recommend(app_type=4, mid='', uid=1111, head_vid=123, videos=videos, size=10)
  1005. print(res)