add

ai_test.py

@@ -11,8 +11,13 @@ param_dict={}
 # param_detail = {"device_id": 'xx',"size": 10,"offset":0, "query": "双眼皮","user_city_tag_id": 328,
 #                 "is_officer":False,"filters":{}}
 
-param_dict["method"]="doris/search/bangdan"
-param_detail = {"device_id": '2',"size": 10,"offset":0, "user_city_tag_id": -1,"is_officer":False,"unit_ids":[]}
+# param_dict["method"]="doris/search/bangdan"
+# param_detail = {"device_id": '2',"size": 10,"offset":0, "user_city_tag_id": -1,"is_officer":False,"unit_ids":[]}
+diary_list = [9462756,9462737,9462730,9462719]
+
+param_dict["method"]="doris/search/diary_score"
+param_detail = {"diary_list": diary_list}
+
 
 
 # a = [105, 2941, 780, 102, 873, 2060, 187, 2935, 2108, 912, 928, 2059, 4437, 822, 2866, 2778, 824, 821, 2938]

make_data.py

@@ -16,7 +16,6 @@ def hospital():
           "left join statistic_merchant_rank_factor m on b.merchant_id = m.merchant_id " \
           "where api.doctor_type = 1 and h.date = '{}' and m.partition_date = '{}';".format(date_str,date_str)
 
-
     db = pymysql.connect(host='172.16.30.141', port=3306, user='work', passwd='BJQaT9VzDcuPBqkd', db='zhengxing')
     cursor = db.cursor()
     cursor.execute(sql)
@@ -50,12 +49,12 @@ def hospital():
     df.loc[df["doctor_discount_30_days"] < 0, ["doctor_discount_30_days"]] = 0
     df.loc[df["expand_rechange_amount_30"] < 0, ["expand_rechange_amount_30"]] = 0
 
-    df.loc[df["tmp"] <= 1500, ["tmp"]] = 1500
+    df.loc[df["tmp"] <= 3000, ["tmp"]] = 3000
 
     df["commission"] = df["doctor_discount_30_days"]/df["tmp"]
     df["cpt"] = df["expand_rechange_amount_30"]/df["tmp"]
 
-    df.loc[df["all_exposure"] <= 1500, ["ctr"]] = 0.01
+    df.loc[df["all_exposure"] <= 3000, ["ctr"]] = 0.01
     df.loc[df["ctr"] < 0.01, ["ctr"]] = 0.01
     df.loc[df["ctr"] > 0.2, ["ctr"]] = 0.2
     df.loc[df["cpt"] > 10, ["cpt"]] = 10
@@ -75,7 +74,7 @@ def hospital():
     data = data.drop_duplicates()
 
     print(data.shape)
-    data.to_csv('/tmp/25_hospital.csv',index=False)
+    data.to_csv('/tmp/26_hospital.csv',index=False)
 
 
 def new_doctor():
@@ -112,7 +111,7 @@ def new_doctor():
     print("all_exposure")
     print(df.shape)
     df["tmp"] = df["service_pv_30"] + df["mexpert_pv_30"] +df["organization_pv_30"]
-    df.loc[df["tmp"] <= 1500, ["tmp"]] = 1500
+    df.loc[df["tmp"] <= 3000, ["tmp"]] = 3000
 
     df["ctr"] = df["service_exposure_pv_30"] / df["all_exposure"] * df["service_ctr_30"] + \
                 df["expert_exposure_pv_30"]/df["all_exposure"] * (df["expert_pv_30"] / df["expert_exposure_pv_30"])
@@ -123,7 +122,7 @@ def new_doctor():
     df["commission"] = df["doctor_discount_30_days"]/df["tmp"]
     df["pv_ad"] = df["expand_rechange_amount_30"]/df["tmp"]
 
-    df.loc[df["all_exposure"] <= 1500, ["ctr"]] = 0.01
+    df.loc[df["all_exposure"] <= 3000, ["ctr"]] = 0.01
     df.loc[df["ctr"] < 0.01, ["ctr"]] = 0.01
     df.loc[df["ctr"] > 0.2, ["ctr"]] = 0.2
     df.loc[df["commission"] > 10, ["commission"]] = 10
@@ -142,15 +141,11 @@ def new_doctor():
 
     data = data.drop_duplicates()
     print(data.shape)
-    data.to_csv('/tmp/25_doctor.csv',index=False)
+    data.to_csv('/tmp/26_doctor.csv',index=False)
     print("doctor end")
 
 
 if __name__ == "__main__":
-    # doctor()
-    # hospital()
-    # old()
-
     new_doctor()
     hospital()