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partition的redis key 增加过期时间

zhangbo před 5 měsíci
rodič
revize
93880b68c2

+ 1 - 1
write_redis/alg_recsys_feature_08_vidh24predv2_redis.py

@@ -170,7 +170,7 @@ def main():
     redis_helper.set_data_to_redis(
         key_name=REDIS_PREFIX + "partition",
         value=partition,
-        expire_time=EXPIRE_TIME
+        expire_time=EXPIRE_TIME*3
     )
 
 if __name__ == '__main__':

+ 8 - 7
write_redis/分析-模拟在线打分的AUC.py

@@ -24,7 +24,7 @@ def func_make_data(file_path: str):
         '日期', '小时', 'rank',
         '曝光量', '分享次数', '多层回流人数', 'return_rate', 'return_cnt',
         'str', 'rosn', 'rovn', 'vovh24',
-        'score_552', 'score_562', 'score_567',
+        'score_563', 'score_562', 'score_567',
          'fmrov', 'hasreturnrovscore', 'vov_score_562', 'vov_score_567'
     ]:
         df[col] = pd.to_numeric(df[col], errors='coerce')
@@ -34,6 +34,7 @@ def func_make_data(file_path: str):
         else:
             df[col] = df[col].astype(str)
     df["score_552_offline"] = df["fmrov"] * (1 + df["hasreturnrovscore"])
+    df["score_563_offline"] = df["fmrov"] * (1 + df["hasreturnrovscore"]) + 0.1 * df["vov_score_563"]
     df["score_562_offline"] = df["fmrov"] * (1 + df["hasreturnrovscore"]) * (1 + 1 * df["vov_score_562"])
     df["score_567_offline"] = df["fmrov"] * (1 + df["hasreturnrovscore"]) + 0.05 * df["vov_score_567"]
     df.fillna(0, inplace=True)
@@ -75,26 +76,26 @@ def func(df, rank_limit, col_a, col_b):
 try:
     date_train = sys.argv[1]
 except Exception as e:
-    date_train = "~/Downloads/20241109_top1000(1).csv"
+    date_train = "~/Downloads/20241115_top1000.csv"
 df = func_make_data(date_train)
 for rank_limit in [100, 500, 1000]:
     print("date_train:rank_limit:{}-{}".format(date_train, rank_limit))
-    df_01 = func(df, rank_limit, "vovh24", "score_552")
+    df_01 = func(df, rank_limit, "vovh24", "score_563")
     df_02 = func(df, rank_limit, "vovh24", "score_562")
     df_03 = func(df, rank_limit, "vovh24", "score_567")
-    df_04 = func(df, rank_limit, "rovn", "score_552")
+    df_04 = func(df, rank_limit, "rovn", "score_563")
     df_05 = func(df, rank_limit, "rovn", "score_562")
     df_06 = func(df, rank_limit, "rovn", "score_567")
-    df_07 = func(df, rank_limit, "vovh24", "score_552_offline")
+    df_07 = func(df, rank_limit, "vovh24", "score_563_offline")
     df_08 = func(df, rank_limit, "vovh24", "score_562_offline")
     df_09 = func(df, rank_limit, "vovh24", "score_567_offline")
-    df_10 = func(df, rank_limit, "rovn", "score_552_offline")
+    df_10 = func(df, rank_limit, "rovn", "score_563_offline")
     df_11 = func(df, rank_limit, "rovn", "score_562_offline")
     df_12 = func(df, rank_limit, "rovn", "score_567_offline")
     df_list = [df_01, df_02, df_03, df_04, df_05, df_06, df_07, df_08, df_09, df_10, df_11, df_12]
     df_merged = pd.concat(df_list, axis=1)
     df_select = df_merged.iloc[:, [0] + [3*i+2 for i in range(len(df_list))]]
-    df_select.to_csv("产品4_20241109_top1000-相关性-top{}.csv".format(rank_limit), index=False)
+    df_select.to_csv("产品0_20241115_top1000-相关性-top{}.csv".format(rank_limit), index=False)
 
 
 

+ 3 - 3
write_redis/分析-自身在线打分的AUC.py

@@ -72,7 +72,7 @@ def func(df, rank_limit, col_a, col_b):
 try:
     date_train = sys.argv[1]
 except Exception as e:
-    date_train = "~/Downloads/20241105.csv"
+    date_train = "~/Downloads/20241116.csv"
 df = func_make_data(date_train)
 for rank_limit in [100, 500, 1000]:
     print("date_train:rank_limit:{}-{}".format(date_train, rank_limit))
@@ -80,13 +80,13 @@ for rank_limit in [100, 500, 1000]:
     df_02 = func(df, rank_limit, "rovn", "score")
     df_list = []
     for df_tmp in [df_01, df_02]:
-        for experiment in ["552", "562", "567"]:
+        for experiment in ["563", "562", "567"]:
             df_list.append(
                 df_tmp[df_tmp["实验组"] == experiment].reset_index(drop=True)
             )
     df_merged = pd.concat(df_list, axis=1)
     df_select = df_merged.iloc[:, [0] + [3*i+2 for i in range(len(df_list))]]
-    df_select.to_csv("20241105-相关性-top{}.csv".format(rank_limit), index=False)
+    df_select.to_csv("20241116-相关性-top{}.csv".format(rank_limit), index=False)