feat(todo): 完善测试的算法

data.py

@@ -1,3 +1,6 @@
+import logging
+import traceback
+
 from  keras.models import Sequential
 from  keras.layers import Dense, Dropout, Embedding
 from  keras.layers import InputLayer
@@ -10,7 +13,25 @@ import os
 import numpy
 import time, datetime
 
-def get_collect(region = "all"):
+regions = [
+    "all",
+   "Region_Arab",
+   "Region_China",
+   "Region_English",
+   "Region_Germany",
+   "Region_India",
+   "Region_Indonesia",
+   "Region_Japan",
+   "Region_Philippines",
+   "Region_Portuguese",
+   "Region_Russian",
+   "Region_Spanish",
+   "Region_Thailand",
+   "Region_Turkey",
+   "Region_Vietnam",
+]
+
+def get_collect():
     collect = {} 
     loadfile = "./collect.pickle"
 
@@ -18,66 +39,120 @@ def get_collect(region = "all"):
         collect = pickle.load(open(loadfile, 'rb'))
     except Exception as e:
         print(e)
+        try:
+        
         # 打开数据库连接
-        db = pymysql.connect(host="sg-board1.livenono.com", port=3306,user="root",passwd="Nono-databoard",db="databoard",charset="utf8")
+            db = pymysql.connect(host="sg-board1.livenono.com", port=3306,user="root",passwd="Nono-databoard",db="databoard",charset="utf8")
-        
+            
-        # 使用 cursor() 方法创建一个游标对象 cursor
+            # 使用 cursor() 方法创建一个游标对象 cursor
-        cursor = db.cursor()
+            cursor = db.cursor()
-        today = time.strftime("%Y-%m-%d", time.localtime())
+            today = time.strftime("%Y-%m-%d", time.localtime())
-         
+            
-        # 使用 execute()  方法执行 SQL 查询 
+            for region in regions:
-        cursor.execute('''SELECT coin, extra_coins, pay_users, create_at from pay_items_hour pih where region = "%s" and platform="all" and create_at <= %s''',region , today)
-        collect_pay = {}
-        for row in cursor.fetchall():
-            # print(row)
-            coin, extra_coins, pay_users, create_at = row
-            d = str(create_at.date())
-            if d in collect_pay:
-                collect_pay[d].append(row)
-            else:
-                collect_pay[d] = [ row ] 
-        # print(dir(create_at), create_at.timestamp(), create_at.date())
-        print('共查找出', cursor.rowcount, '条数据')
-        deletelist = []
-        for k in collect_pay:
-            if len(collect_pay[k]) != 24:
-                deletelist.append(k)
 
-        for k in deletelist:
+                # 使用 execute()  方法执行 SQL 查询 
-            del collect_pay[k]
+                cursor.execute('''SELECT coin, extra_coins, pay_users, create_at from pay_items_hour pih where region = %s and country = "all" and platform="all" and create_at >= "2021-02-23" and create_at <= %s''',(region , today))
+                collect_pay = []
+                
+                for row in cursor.fetchall():
+                    # print(row)
+                    coin, extra_coins, pay_users, create_at = row
+                    rowlist = [coin, extra_coins, pay_users, create_at.hour, create_at]
+                    # print(dir(create_at), create_at.hour)
+                    collect_pay.append(rowlist)
+                    # d = str(create_at.date())
+                    # if d in collect_pay:
+                    #     collect_pay.append(row)
+                    # else:
+                    #     collect_pay[d] = [ row ] 
+                # print(dir(create_at), create_at.timestamp(), create_at.date())
+                print('共查找出', cursor.rowcount, '条数据')
 
-        querydate= []
-        for k in collect_pay:
-            querydate.append(k)
-        
-        querydate.sort()
-        cursor.execute(
-            '''SELECT coin, users, create_at from gift_items_hour pih where region = "all" and create_at >= %s and create_at <= %s''',
-            (querydate[0], querydate[-1]),
-            )
 
-        collect_gift = {}
-        for row in cursor.fetchall():
-    
-            coin, users, create_at = row
-            d = str(create_at.date())
-            if d in collect_gift:
-                collect_gift[d].append(row)
-            else:
-                collect_gift[d] = [ row ] 
 
-        for k in collect_pay:
+                # if cursor.rowcount <= 500: 
-            l = collect_pay[k]
+                #     collect["pay-" + region] = None
-            l.sort(key=lambda x:x[3])
+                #     collect["gift-" + region] = None
+                #     continue
 
-        for k in collect_gift:
+                # deletelist = []
-            l = collect_gift[k]
+                # for k in collect_pay:
-            l.sort(key=lambda x:x[2])
+                #     if len(collect_pay[k]) != 24:
+                #         deletelist.append(k)
 
-        collect["pay"] = collect_pay
+                # for k in deletelist:
-        collect["gift"] = collect_gift
+                #     del collect_pay[k]
+
+                # querydate= []
+                # for k in collect_pay:
+                #     querydate.append(k)
+                
+                
+
+                # querydate.sort()
+                cursor.execute(
+                    '''SELECT coin, users, create_at from gift_items_hour pih where region = %s and country = "all" and create_at >= "2021-02-23" and create_at <= %s''',
+                    (region, today),
+                    )
+
+                collect_gift = []
+                for row in cursor.fetchall():
+            
+                    coin, users, create_at = row
+                    rowlist = [coin, users, create_at.hour, create_at]
+                    collect_gift.append(rowlist)
+
+                    # d = str(create_at.date())
+                    # if d in collect_gift:
+                    #     collect_gift[d].append(row)
+                    # else:
+                    #     collect_gift[d] = [ row ] 
+
+  
+                collect_pay.sort(key=lambda x:x[-1])
+                collect_gift.sort(key=lambda x:x[-1])
+                # for k in collect_gift:
+                #     l = collect_gift[k]
+                #     l.sort(key=lambda x:x[2])
+                yesterday = {}
+                for v in collect_pay:
+                    print(v[-1])
+                    date = (v[-1].date() - datetime.timedelta(days=1)).__str__()
+                    print(date)
+                    if date not in yesterday:
+                        cursor.execute(
+                            '''SELECT coin, extra_coins, pay_users, create_at from pay_items_day pid where region = %s and country = "all" and platform="all" and create_at = %s''',
+                            (region , date),
+                            )
+                        row = cursor.fetchone()
+                        coin, extra_coins, pay_users, create_at = row
+                        yesterday[date] = coin + extra_coins
+                    v.insert(-2, yesterday[date])
+                    
+                yesterday = {}
+                for v in collect_gift:
+                    print(v[-1])
+                    date = (v[-1].date() - datetime.timedelta(days=1)).__str__()
+                    print(date)
+                    if date not in yesterday:
+                        cursor.execute(
+                            '''SELECT coin, users, create_at from gift_items_day where region = %s and country = "all" and create_at = %s''',
+                            (region , date),
+                            )
+                        row = cursor.fetchone()
+                        coin, users, create_at = row
+                        yesterday[date] = coin 
+                    v.insert(-2, yesterday[date])
+
+                collect["pay-" + region] = collect_pay
+                collect["gift-" + region] = collect_gift
+        except Exception as e:
+            # print(e)
+            logging.error(traceback.format_exc())
+            
 
         pickle.dump(collect, open(loadfile, 'wb+'))
+    
     finally:
         return collect
 
@@ -93,11 +168,13 @@ def load_pay_data(textNum = 80, region = "all"):
     x_train = []
     y_train = []
 
-    collect_pay = []
+    rkey = "pay-" + region
-    for k in collect["pay"]:
+    collect_pay = collect[rkey]
-        collect_pay.append(collect["pay"][k])
+     
+    # for k in collect[rkey]:
+        # collect_pay.append(collect[rkey][k])
     
-    collect_pay.sort(key=lambda x:x[0][3])
+    # collect_pay.sort(key=lambda x:x[0][3])
     lastday_v = collect_pay[0]
     for cur_v in collect_pay[1:]:
     
@@ -105,9 +182,6 @@ def load_pay_data(textNum = 80, region = "all"):
         users = 0
         last_total_coin = 0
 
-        for v2 in lastday_v:
-            last_total_coin += v2[0] + v2[1]
-
         count = 0
         for v1, v2 in zip(cur_v,lastday_v):
             total_coin += v1[0] + v1[1]
@@ -120,7 +194,7 @@ def load_pay_data(textNum = 80, region = "all"):
             # print(compare)
     
             # 时刻. 前一个小时 时刻. 当前支付总币数. 当前支付总币数 昨天币数
-            x_train.append([count  ,total_coin / last_total_coin , total_coin])
+            x_train.append([v1[-2]  ,total_coin / v1[-3] , total_coin])
             count+=1
 
         for i in range(count):
@@ -141,16 +215,18 @@ def load_pay_data(textNum = 80, region = "all"):
 
     return x_train, y_train, tx_train, ty_train, input_shape
 
-def load_gift_data(textNum = 80):
+def load_gift_data(textNum = 80, region = "all"):
 
     collect = get_collect()
 
     x_train = []
     y_train = []
 
+
+    rkey = "gift-" + region
     collect_gift = []
-    for k in collect["gift"]:
+    for k in collect[rkey]:
-        collect_gift.append(collect["gift"][k])
+        collect_gift.append(collect[rkey][k])
     
     collect_gift.sort(key=lambda x:x[0][2])
     lastday_v = collect_gift[0]

train_pay.py

@@ -17,7 +17,8 @@ from data import load_pay_data
 
 if __name__ == "__main__":
 
-    x_train, y_train, tx_train, ty_train, input_shape = load_pay_data(80)
+    region = "Region_Arab"
+    x_train, y_train, tx_train, ty_train, input_shape = load_pay_data(80, region)
 
     
     model = Sequential()
@@ -31,7 +32,7 @@ if __name__ == "__main__":
     model.compile(loss = 'mse', optimizer = 'adam')
 
     model.fit(x_train, y_train, batch_size=96, epochs=1200)
-    model.save("./predict_pay")
+    model.save("./predict_pay_" + region)
 
     p_data = model.predict(tx_train)
     for i in range(len(p_data)):