Update alg_growth_3rd_gh_reply_video_v1: clean code

alg_growth_3rd_gh_reply_video_v1.py

@@ -29,24 +29,6 @@ GH_IDS = ('default',)
 
 pd.set_option('display.max_rows', None)
 
-TARGET_GH_IDS = (
-    'gh_250c51d5ce69',
-    'gh_8a29eebc2012',
-    'gh_ff16c412ab97',
-    'gh_1014734791e0',
-    'gh_570967881eae',
-    'gh_a7c21403c493',
-    'gh_7f062810b4e7',
-    'gh_c8060587e6d1',
-    'gh_1da8f62f4a0d',
-    'gh_56b65b7d4520',
-    'gh_eeec7c2e28a5',
-    'gh_7c89d5a3e745',
-    'gh_ee5b4b07ed8b',
-    'gh_0d3c97cc30cc',
-    'gh_c783350a9660',
-)
-
 CDN_IMG_OPERATOR = "?x-oss-process=image/resize,m_fill,w_600,h_480,limit_0/format,jpg/watermark,image_eXNoL3BpYy93YXRlcm1hcmtlci9pY29uX3BsYXlfd2hpdGUucG5nP3gtb3NzLXByb2Nlc3M9aW1hZ2UvcmVzaXplLHdfMTQ0,g_center"
 
 ODS_PROJECT = "loghubods"
@@ -276,33 +258,6 @@ def postprocess_override_by_config(df, dt_version):
     return df
 
 
-def rank_for_base_designate(run_dt, run_hour, stg_key):
-    dt_version = f'{run_dt}{run_hour}'
-    ranked_df = pd.DataFrame()  # 初始化一个空的 DataFrame
-
-    for gh_id in GH_IDS:
-        if gh_id in TARGET_GH_IDS:
-            temp_df = pd.DataFrame({
-                'strategy_key': [stg_key],
-                'dt_version': [dt_version],
-                'gh_id': [gh_id],
-                'sort': [1],
-                'video_id': [13586800],
-                'score': [0.5]
-            })
-        else:
-            temp_df = pd.DataFrame({
-                'strategy_key': [stg_key],
-                'dt_version': [dt_version],
-                'gh_id': [gh_id],
-                'sort': [1],
-                'video_id': [20463342],
-                'score': [0.5]
-            })
-        ranked_df = pd.concat([ranked_df, temp_df], ignore_index=True)
-    return ranked_df
-
-
 def build_and_transfer_data(run_dt, run_hour, project, **kwargs):
     dt_version = f'{run_dt}{run_hour}'
     dry_run = kwargs.get('dry_run', False)
@@ -312,8 +267,6 @@ 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)
-    # 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)
 
     final_rank_df = pd.concat([layer1_rank, layer2_rank, base_rank]).reset_index(drop=True)