不区分app权重的地域召回子策略离线数据生产

config.py

@@ -262,6 +262,8 @@ class BaseConfig(object):
                       'view_type': 'preview'},
             'rule4': {'cal_score_func': 2, 'return_count': 100, 'platform_return_rate': 0.001,
                       'view_type': 'preview', 'merge_func': 2},
+            'rule66': {'cal_score_func': 2, 'return_count': 100, 'platform_return_rate': 0.001,
+                      'view_type': 'preview'},
             # # 无回流人群
             # 'rule5': {'return_count': 100, 'platform_return_rate': 0.001,
             #           'view_type': 'preview', 'click_score_rate': 0.7},
@@ -294,6 +296,7 @@ class BaseConfig(object):
             # {'data': 'data1', 'rule': 'rule7'},
             # {'data': 'data1', 'rule': 'rule8'},
             {'data': 'videos5', 'rule': 'rule4'},  # [内容精选]
+            {'data': 'rule66', 'rule': 'rule66'},
         ]
     }
 
@@ -312,7 +315,7 @@ class BaseConfig(object):
                       'platform_return_rate': 0.001, 'merge_func': 2},
             'rule5': {'view_type': 'preview', 'return_count': 21, 'score_rule': 0,
                       'platform_return_rate': 0.001, 'merge_func': 2},
-            'rule66': {'view_type': 'preview', 'return_count': 21, 'score_rule': 0,
+            'rule66': {'view_type': 'video-show', 'return_count': 21, 'score_rule': 0,
                       'platform_return_rate': 0.001},
             # # 无回流人群
             # 'rule6': {'view_type': 'video-show', 'return_count': 21, 'score_rule': 0,
@@ -488,7 +491,7 @@ class BaseConfig(object):
                        'score_func': 'back_rate_rank_weighting'},
             'rule66': {
                 'view_type': 'video-show-region', 'platform_return_rate': 0.001,
-                'region_24h_rule_key': 'rule66', '24h_rule_key': 'rule66', 'h_rule_key': 'rule66'
+                'region_24h_rule_key': 'rule66', '24h_rule_key': 'rule66'
             },
         },
         'data_params': DATA_PARAMS,

rule_rank_h_by_24h.py

@@ -358,11 +358,6 @@ def rank_by_h(now_date, now_h, rule_params, project, table):
             video_rank_h(df=df_merged, now_date=now_date, now_h=now_h,
                          rule_key=rule_key, param=rule_param, data_key=data_key,
                          notify_backend=notify_backend)
-        elif merge_func == 66:
-            score_df = cal_score(df=feature_df, param=rule_param)
-            video_rank_h(df=score_df, now_date=now_date, now_h=now_h,
-                         rule_key=rule_key, param=rule_param, data_key=data_key,
-                         notify_backend=notify_backend)
         else:
             df_list = [feature_df[feature_df['apptype'] == apptype] for apptype, _ in data_param.items()]
             df_merged = reduce(merge_df, df_list)