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- import datetime
- import traceback
- from threading import Timer
- from utils import RedisHelper, data_check, get_feature_data, send_msg_to_feishu
- from config import set_config
- from log import Log
- config_, _ = set_config()
- log_ = Log()
- redis_helper = RedisHelper()
- features = [
- 'apptype',
- 'videoid',
- 'sharerate_all',
- 'sharerate_ad'
- ]
- def predict_video_share_rate(video_initial_df, dt, data_key, data_param):
- """预估视频有广告时分享率"""
- # 获取对应的视频特征
- video_df = video_initial_df.copy()
- video_df['apptype'] = video_df['apptype'].astype(int)
- video_df = video_df[video_df['apptype'] == int(data_param)]
- video_df['sharerate_all'].fillna(0, inplace=True)
- video_df['sharerate_ad'].fillna(0, inplace=True)
- video_df['sharerate_all'] = video_df['sharerate_all'].astype(float)
- video_df['sharerate_ad'] = video_df['sharerate_ad'].astype(float)
- # 获取有广告时所有视频近30天的分享率
- ad_all_videos_share_rate = video_df[video_df['videoid'] == 'allvideos']['sharerate_ad'].values[0]
- video_df = video_df[video_df['videoid'] != 'allvideos']
- # 计算视频有广告时分享率
- video_df['video_ad_share_rate'] = \
- video_df['sharerate_ad'] * float(ad_all_videos_share_rate) / video_df['sharerate_all']
- video_df['video_ad_share_rate'].fillna(0, inplace=True)
- video_df = video_df[video_df['video_ad_share_rate'] != 0]
- # 结果写入redis
- key_name = f"{config_.KEY_NAME_PREFIX_AD_VIDEO}{data_key}:{dt}"
- redis_data = {}
- for index, item in video_df.iterrows():
- redis_data[int(item['videoid'])] = item['video_ad_share_rate']
- group_ad_share_rate_mean = video_df['video_ad_share_rate'].mean()
- redis_data[-1] = group_ad_share_rate_mean
- if len(redis_data) > 0:
- redis_helper = RedisHelper()
- redis_helper.add_data_with_zset(key_name=key_name, data=redis_data, expire_time=2 * 24 * 3600)
- return video_df
- def update_videos_data(project, table, dt, update_params):
- """预估视频有广告时分享率"""
- # 获取视频特征
- video_initial_df = get_feature_data(project=project, table=table, features=features, dt=dt)
- for data_key, data_param in update_params.items():
- log_.info(f"data_key = {data_key} update start...")
- predict_video_share_rate(video_initial_df=video_initial_df, dt=dt, data_key=data_key, data_param=data_param)
- log_.info(f"data_key = {data_key} update end!")
- def timer_check():
- try:
- update_params = config_.AD_VIDEO_DATA_PARAMS
- project = config_.ad_model_data['videos_share_rate'].get('project')
- table = config_.ad_model_data['videos_share_rate'].get('table')
- now_date = datetime.datetime.today()
- dt = datetime.datetime.strftime(now_date, '%Y%m%d')
- log_.info(f"now_date: {dt}")
- now_min = datetime.datetime.now().minute
- # 查看当前更新的数据是否已准备好
- data_count = data_check(project=project, table=table, dt=dt)
- if data_count > 0:
- log_.info(f"ad video data count = {data_count}")
- # 数据准备好,进行更新
- update_videos_data(project=project, table=table, dt=dt, update_params=update_params)
- log_.info(f"ad video data update end!")
- # elif now_min > 45:
- # log_.info('ad video data is None!')
- # send_msg_to_feishu(
- # webhook=config_.FEISHU_ROBOT['server_robot'].get('webhook'),
- # key_word=config_.FEISHU_ROBOT['server_robot'].get('key_word'),
- # msg_text=f"rov-offline{config_.ENV_TEXT} - 视频分享率数据未准备好!\n"
- # f"traceback: {traceback.format_exc()}"
- # )
- else:
- # 数据没准备好,1分钟后重新检查
- Timer(60, timer_check).start()
- except Exception as e:
- log_.error(f"视频分享率预测数据更新失败, exception: {e}, traceback: {traceback.format_exc()}")
- send_msg_to_feishu(
- webhook=config_.FEISHU_ROBOT['server_robot'].get('webhook'),
- key_word=config_.FEISHU_ROBOT['server_robot'].get('key_word'),
- msg_text=f"rov-offline{config_.ENV_TEXT} - 视频分享率预测数据更新失败\n"
- f"exception: {e}\n"
- f"traceback: {traceback.format_exc()}"
- )
- if __name__ == '__main__':
- timer_check()
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