ad_video_data_upate.py 3.5 KB

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  1. import datetime
  2. import traceback
  3. from threading import Timer
  4. from utils import RedisHelper, data_check, get_feature_data, send_msg_to_feishu
  5. from config import set_config
  6. from log import Log
  7. config_, _ = set_config()
  8. log_ = Log()
  9. redis_helper = RedisHelper()
  10. features = [
  11. 'apptype',
  12. 'videoid',
  13. 'sharerate_all',
  14. 'sharerate_ad'
  15. ]
  16. def predict_video_share_rate(project, table, dt, app_type):
  17. """预估视频有广告时分享率"""
  18. # 获取视频特征
  19. video_df = get_feature_data(project=project, table=table, features=features, dt=dt)
  20. video_df['apptype'] = video_df['apptype'].astype(int)
  21. video_df = video_df[video_df['apptype'] == app_type]
  22. video_df['sharerate_all'] = video_df['sharerate_all'].astype(float)
  23. video_df['sharerate_ad'] = video_df['sharerate_ad'].astype(float)
  24. # 获取有广告时所有视频近30天的分享率
  25. ad_all_videos_share_rate = video_df[video_df['videoid'] == 'allvideos']['sharerate_ad']
  26. video_df = video_df[video_df['videoid'] != 'allvideos']
  27. # 计算视频有广告时分享率
  28. video_df['video_ad_share_rate'] = \
  29. video_df['sharerate_ad'] * float(ad_all_videos_share_rate) / video_df['sharerate_all']
  30. # 结果写入redis
  31. key_name = f"{config_.KEY_NAME_PREFIX_AD_VIDEO}{dt}"
  32. redis_data = {}
  33. for item in video_df:
  34. redis_data[item['videoid']] = item['video_ad_share_rate']
  35. if len(redis_data) > 0:
  36. redis_helper = RedisHelper()
  37. redis_helper.add_data_with_zset(key_name=key_name, data=redis_data, expire_time=2 * 24 * 3600)
  38. return video_df
  39. def timer_check():
  40. try:
  41. app_type = config_.APP_TYPE['VLOG']
  42. project = config_.ad_model_data['videos_share_rate'].get('project')
  43. table = config_.ad_model_data['videos_share_rate'].get('table')
  44. now_date = datetime.datetime.today()
  45. dt = datetime.datetime.strftime(now_date, '%Y%m%d')
  46. log_.info(f"now_date: {dt}")
  47. now_min = datetime.datetime.now().minute
  48. # 查看当前更新的数据是否已准备好
  49. data_count = data_check(project=project, table=table, dt=dt)
  50. if data_count > 0:
  51. log_.info(f"ad video data count = {data_count}")
  52. # 数据准备好,进行更新
  53. predict_video_share_rate(project=project, table=table, dt=dt, app_type=app_type)
  54. log_.info(f"ad video data update end!")
  55. elif now_min > 45:
  56. log_.info('ad video data is None!')
  57. send_msg_to_feishu(
  58. webhook=config_.FEISHU_ROBOT['server_robot'].get('webhook'),
  59. key_word=config_.FEISHU_ROBOT['server_robot'].get('key_word'),
  60. msg_text=f"rov-offline{config_.ENV_TEXT} - 视频分享率数据未准备好!\n"
  61. f"traceback: {traceback.format_exc()}"
  62. )
  63. else:
  64. # 数据没准备好,1分钟后重新检查
  65. Timer(60, timer_check).start()
  66. except Exception as e:
  67. log_.error(f"视频分享率预测数据更新失败, exception: {e}, traceback: {traceback.format_exc()}")
  68. send_msg_to_feishu(
  69. webhook=config_.FEISHU_ROBOT['server_robot'].get('webhook'),
  70. key_word=config_.FEISHU_ROBOT['server_robot'].get('key_word'),
  71. msg_text=f"rov-offline{config_.ENV_TEXT} - 视频分享率预测数据更新失败\n"
  72. f"exception: {e}\n"
  73. f"traceback: {traceback.format_exc()}"
  74. )
  75. if __name__ == '__main__':
  76. timer_check()