debug

ad_video_data_update.py

@@ -81,7 +81,7 @@ def predict_video_share_rate(video_initial_df, dt, data_key, data_param, top10_a
     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)
-    log_.info(f"video_df: {video_df}")
+    # log_.info(f"video_df: {video_df}")
     video_df = video_df[video_df['video_ad_share_rate'] != 0]
     log_.info(f"video_df filtered 0 length: {len(video_df)}")
     # 结果写入redis
@@ -98,6 +98,7 @@ def predict_video_share_rate(video_initial_df, dt, data_key, data_param, top10_a
         for abnormal_video_id in top10_abnormal_video_ids:
             print(abnormal_video_id, group_ad_share_rate_mean, group_ad_share_rate_mean * abnormal_video_param)
             redis_data[int(abnormal_video_id)] = group_ad_share_rate_mean * abnormal_video_param
+    log_.info(f"redis_data count: {len(redis_data)}")
     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)

config.py

@@ -1040,7 +1040,7 @@ class BaseConfig(object):
                   'user': {'data': 'user0', 'rule': 'rule1'}},
         '243-b': {'video': {'data': 'data1'},
                   'user': {'data': 'user0', 'rule': 'rule2'}},
-        '243-c': {'video': {'data': 'video3'},
+        '243-c': {'video': {'data': 'videos3'},
                   'user': {'data': 'user3', 'rule': 'rule1'}},  # 所有广告类型本端数据
     }