Update alg_growth_3rd_gh_reply_video_v1: enable base rank

alg_growth_3rd_gh_reply_video_v1.py

@@ -168,7 +168,7 @@ def rank_for_layer2(run_dt, run_hour, project, stats_table, rank_table):
     sampled_dfs.append(sampled_df)
 
     # 基础过滤for账号
-    df = stats_df.query('day0_return > 100')
+    df = stats_df.query('send_count > 200 and score > 0')
 
     # fallback to base if necessary
     base_strategy_df = get_last_strategy_result(
@@ -215,10 +215,11 @@ def rank_for_base(run_dt, run_hour, project, stats_table, rank_table, stg_key):
 
     stats_with_strategy_df = stats_df \
         .merge(
-        base_strategy_df,
-        on=['gh_id', 'video_id'],
-        how='left') \
-        .query('strategy_key.notna() or score > 0.1')
+            base_strategy_df,
+            on=['gh_id', 'video_id'],
+            how='outer') \
+        .query('strategy_key.notna() or (send_count > 500 and score > 0.05)') \
+        .fillna({'score': 0.0})
 
     # 合并default和分账号数据
     grouped_stats_df = pd.concat([default_stats_df, stats_with_strategy_df]).reset_index()
@@ -310,9 +311,9 @@ def build_and_transfer_data(run_dt, run_hour, project, **kwargs):
 
     layer1_rank = rank_for_layer1(run_dt, run_hour, ODS_PROJECT, EXPLORE_POOL_TABLE, gh_df)
     layer2_rank = rank_for_layer2(run_dt, run_hour, ODS_PROJECT, GH_REPLY_STATS_TABLE, ODPS_RANK_RESULT_TABLE)
-    # base_rank = rank_for_base(run_dt, run_hour, ODS_PROJECT, GH_REPLY_STATS_TABLE, ODPS_RANK_RESULT_TABLE,BASE_GROUP_NAME)
+    base_rank = rank_for_base(run_dt, run_hour, ODS_PROJECT, GH_REPLY_STATS_TABLE, ODPS_RANK_RESULT_TABLE,BASE_GROUP_NAME)
     # layer2_rank = rank_for_base_designate(run_dt, run_hour, EXPLORE2_GROUP_NAME)
-    base_rank = rank_for_base_designate(run_dt, run_hour, BASE_GROUP_NAME)
+    # base_rank = rank_for_base_designate(run_dt, run_hour, BASE_GROUP_NAME)
 
     final_rank_df = pd.concat([layer1_rank, layer2_rank, base_rank]).reset_index(drop=True)