Merge branch 'feature_20231204_yangxiaohui_add_lr_v1' of algorithm/rov-offline into master

ad_out_v1_set_config.py

@@ -10,37 +10,21 @@ log_ = Log()
 redis_helper = RedisHelper()
 
 if __name__ == '__main__':
-    dt = '20231203'
-    data_key = 'test_lr_v1'
-    key_name = f"{config_.KEY_NAME_PREFIX_AD_GROUP}{data_key}:{dt}"
-    redis_data = {
-        'yxh': 0.3,
-        'zb': 0.13213231231,
-    }
-    redis_data = {
-        'mz': 0.2,
-        'zb': 0.6666,
-    }
-    print(key_name)
-    #redis_helper.add_data_with_zset(key_name=key_name, data=redis_data, expire_time=2 * 24 * 3600)
-    print(redis_helper.get_score_with_value(key_name=key_name, value='zb'))
-    print(redis_helper.get_score_with_value(key_name=key_name, value='mz'))
-    print(redis_helper.get_score_with_value(key_name='ad:users:group:predict:share:rate:test_lr_v1:20231129', value='16537775'))
-    
     model_key = 'ad_out_v1'
-    KEY_NAME_PREFIX_AD_OUT_MODEL_CONFIG = 'ad:out:model:config:'
     abtest_id = '173'
-    abtest_config_tag = 'u'
-    config_key_prefix = f"{KEY_NAME_PREFIX_AD_OUT_MODEL_CONFIG}{model_key}:{abtest_id}:{abtest_config_tag}"
-    threshold_key = f"{config_key_prefix}:threshold"
-    use_mean_key = f"{config_key_prefix}:use_mean"
-    threshold = redis_helper.get_data_from_redis(key_name=threshold_key)
-    use_mean = redis_helper.get_data_from_redis(key_name=use_mean_key)
-    print('threshold:', threshold, type(threshold))
-    print('use_mean:', use_mean, type(use_mean))
-    expire_time = 30 * 24 * 3600
-    redis_helper.set_data_to_redis(threshold_key, 0.4, expire_time)
-    redis_helper.set_data_to_redis(use_mean_key, 1, expire_time)
-    print(threshold_key)
-    print(use_mean_key)
+    abtest_config_tag_list = ['u', 'v']
+    for abtest_config_tag in abtest_config_tag_list :
+        config_key_prefix = f"{config_.KEY_NAME_PREFIX_AD_OUT_MODEL_CONFIG}{model_key}:{abtest_id}:{abtest_config_tag}"
+        threshold_key = f"{config_key_prefix}:threshold"
+        use_mean_key = f"{config_key_prefix}:use_mean"
+        print(threshold_key)
+        threshold = redis_helper.get_data_from_redis(key_name=threshold_key)
+        use_mean = redis_helper.get_data_from_redis(key_name=use_mean_key)
+        print('threshold:', threshold, type(threshold))
+        print('use_mean:', use_mean, type(use_mean))
+        expire_time = 30 * 24 * 3600
+        redis_helper.set_data_to_redis(threshold_key, 0.27, expire_time)
+        redis_helper.set_data_to_redis(use_mean_key, 'false', expire_time)
+        print(threshold_key)
+        print(use_mean_key)
 

config.py

@@ -2358,10 +2358,13 @@ class BaseConfig(object):
         },
     }
 
-    # 有广告时的用户跳出分数预测结果存放 redis key 前缀，完整格式：ad:out:model:score:user:{model_key}:{date}
+    # 有广告时的用户跳出模型离线分数 redis key 前缀，完整格式：ad:out:model:score:user:{model_key}:{mid}
     KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_USER = 'ad:out:model:score:user:'
-    # 有广告时的视频跳出分数预测结果存放 redis key 前缀，完整格式：ad:out:model:score:video:{model_key}:{date}
+    # 有广告时的视频跳出模型离线分数 redis key 前缀，完整格式：ad:out:model:score:video:{model_key}:{videoid}
     KEY_NAME_PREFIX_AD_OUT_MODEL_SCORE_ITEM = 'ad:out:model:score:item:'
+    # 有广告时的视频跳出模型策略配置  redis key 前缀，完整格式：ad:out:model:config:{model_key}:{abtest_id}:{abtest_config_tag}:{config}
+    KEY_NAME_PREFIX_AD_OUT_MODEL_CONFIG = 'ad:out:model:config:'
+
     # 用户组有广告时的分享率预测结果存放 redis key 前缀，完整格式：ad:users:group:predict:share:rate:{user_data_key}:{user_rule_key}:{date}
     KEY_NAME_PREFIX_AD_GROUP = 'ad:users:group:predict:share:rate:'
     # 视频有广告时的分享率预测结果存放 redis key 前缀，完整格式：ad:video:predict:share:rate:{video_data_key}:{date}