diff --git a/auto.py b/auto.py
index 5abb92d..635a528 100644
--- a/auto.py
+++ b/auto.py
@@ -22,7 +22,6 @@ click(_close)
 
 #店内账本
 click(Text("店内账本"))
-# vue2_el > div:nth-child(2) > section > div > div > div.pad30px.mb15.border_b.bgfff.balance_top > div:nth-child(2) > span.gray3.moneynum
 # moneynum = S('//*[@id="vue2_el"]/div[1]/section/div/div/div[3]/div[2]/span[1]')
 moneynum = S('//span[contains(@class, "gray3") and contains(@class, "moneynum")]')
 wait_until(moneynum.exists)
@@ -126,4 +125,4 @@ plus = Text("+")
 confirm = Text("确认")
 # click(confirm)
 # time.sleep(5)
-# kill_browser()
\ No newline at end of file
+kill_browser()
\ No newline at end of file
diff --git a/auto_v2.py b/auto_v2.py
index e9be32f..e27f98d 100644
--- a/auto_v2.py
+++ b/auto_v2.py
@@ -10,7 +10,7 @@ chrome_options.add_experimental_option("mobileEmulation", mobile_emulation)
 #chrome_options.add_experimental_option('excludeSwitches', ['enable-automation'])
 #chrome_options.add_experimental_option('useAutomationExtension', False)
 chrome_options.add_argument('--no-sandbox')
-# chrome_options.add_argument('--headless')
+chrome_options.add_argument('--headless')
 chrome_options.add_argument('user-agent="Mozilla/5.0 (iPhone; CPU iPhone OS 13_2_3 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/13.0.3 Mobile/15E148 Safari/604.1"')
 driver = start_chrome("https://youdian.jindianle.com/", options=chrome_options)
 try:
@@ -49,16 +49,16 @@ try:
     click(pls)
     wait_until(Text('组选').exists)
     click(Text('组选'))
-    # 普通投注-> 取消组3
     result = ['258', '357', '069', '168', '078', '267', '159', '339', '177', '366']
     for index, item in enumerate(result):
         if len(set(item)) == 3:
+            # 普通投注-> 取消组3
             click(Text('普通投注'))
             for i in item:
                 ball_line = S(f'//*[@id="body"]/section/div[3]/div[2]/ul/li[{int(i) + 1}]/p[1]')
                 if ball_line.exists:
-                    print(ball_line.web_element.text)
                     click(ball_line)
+                    print(ball_line.web_element.text)
                 else:
                     print(f"{i}不存在")
             wait_until(Text("组3").exists)
@@ -73,15 +73,18 @@ try:
                 single_ball = S(f'//*[@id="body"]/section/div[3]/div[2]/div[2]/ul/li[{int(item[0]) + 1}]/p')
             click(double_ball)
             click(single_ball)
+            print(f"对子号:{double_ball.web_element.text}")
+            print(f"非对子号:{single_ball.web_element.text}")          
         print(f"{index}: {item}")
         wait_until(Text("下一步").exists)
         click(Text("下一步"))
         if index + 1 != len(result):
             wait_until(Text("+继续添加").exists)
             click(Text("+继续添加"))
-    wait_until(Text("保存").exists)
+    save = Text("保存")
+    wait_until(save.exists)
     click(Text("保存"))
-
+    print(save.web_element.text)
     # # 设置倍数后，再点击一次下一步 
     # plus = Text("+")
     # # click(plus)
diff --git a/jcbf.py b/jcbf.py
new file mode 100644
index 0000000..10f3e8c
--- /dev/null
+++ b/jcbf.py
@@ -0,0 +1,23 @@
+import requests
+from furl import furl
+import time
+import json
+
+file = open("data.json", "w+")
+
+base_url = "https://www.ttyingqiu.com/"
+f = furl(base_url)
+
+f.path = "/static/no_cache/league/zc/jsbf/ttyq2020/jsbf_2022-11-06.json"
+f.args["v"] = int(time.time()*1000)
+print(f.url)
+print(r.status_code)
+print(r.json())
+file.write(json.dumps(r.json()))
+file.close()
+
+
+url = "/static/no_cache/league/zc/jsbf/ttyq2020/jczq/jsbf_2022-11-06.json?v=1667799791084"
+url = "https://www.ttyingqiu.com/static/no_cache/league/zc/jsbf/ttyq2020/jczq/2022-11-06/oz_407_6.json?v=1667799791169"
+
+match_list = data["matchList"]
\ No newline at end of file
diff --git a/pls.py b/pls.py
index 95f4a44..16776ef 100644
--- a/pls.py
+++ b/pls.py
@@ -13,34 +13,34 @@ sum_df = pd.value_counts(sum_list)
 
 # 组三
 group3 = [ i for i in l if len(set(i)) == 2]
-sum_group_dict = {i: [] for i in np.arange(28)}
+sum_group3_dict = {i: [] for i in np.arange(28)}
 for i in group3:
-    
-    sum_group_dict[sum(map(int, list(i)))].append(i)
-
-for i in sum_group_dict.keys():
-    f3 = lambda number: True if '1' not in number else False
-    print(i, -cachesum_group_dict[i])
-# print(sum_group3_dict) 
-# sum_group3 = [ sum(map(int, list(i))) for i in group3]
-# print(pd.value_counts(sum_group3).to_dict())
-for i in range(5, 20):
-    _result = [item for item in sum_group_dict[i]]
+    sum_group3_dict[sum(map(int, list(i)))].append(i)
 # 组六
 group6 = [ i for i in l if len(set(i)) == 3]
-print(len(group6)/220)
 sum_group6_dict = {i: [] for i in np.arange(28)}
 for i in group6:
     sum_group6_dict[sum(map(int, list(i)))].append(i)
+# for i in sum_group3_dict.keys():
+#     f3 = lambda number: True if '7' not in number else False
+#     print(i, list(filter(f3, sum_group3_dict[i])))
+# print(sum_group3_dict) 
+# sum_group3 = [ sum(map(int, list(i))) for i in group3]
+# print(pd.value_counts(sum_group3).to_dict())
+# for i in range(5, 20):
+#     _result = [item for item in sum_group3_dict[i]]
+
+
 for i in sum_group6_dict.keys():
     f1 = lambda number: len([i for i in number if int(i) %2 == 0]) != 0
     f2 = lambda number: len([i for i in number if int(i) %2 == 1]) != 0
-    f3 = lambda number: True if '2' not in number else False
-    f4 = lambda number: True if max(map(int, number)) - min(map(int, number)) != 2 else False
-    f5 = lambda number: True if '3' not in number else False
-    f3 = lambda number: True if '8' not in number else False
-    print(i, sum_group6_dict[i])
-# print(pd.value_counts(sum_group3).to_dict())
+    f3 = lambda number: True if max(map(int, number)) - min(map(int, number)) != 2 else False
+    f4 = lambda number: True if '3' not in number else False
+    f5 = lambda number: True if '4' not in number else False
+    if i in [15, 19]:
+        result = sum_group6_dict[i]+sum_group3_dict[i]
+        print(i, list(filter(f5, result)))
+        # print(i, sum_group3_dict[i])
 
 # 连号
 result = []
diff --git a/sd.py b/sd.py
index 9947fdb..b762fe9 100644
--- a/sd.py
+++ b/sd.py
@@ -3,14 +3,43 @@ import pandas as pd
 
 a = np.arange(1000)
 
+nums = [ f"{i:03d}" for i in a ]
+is_odd = lambda i: True if int(i) % 2 == 1 else False
+is_even = lambda i: True if int(i) % 2 == 0 else False
+
+#奇奇奇
+odd_odd_odd = [i for i in nums if is_odd(i[0]) and is_odd(i[1]) and is_odd(i[2]) ]
+#奇奇偶
+odd_odd_even = [i for i in nums if is_odd(i[0]) and is_odd(i[1]) and is_even(i[2]) ]
+#
+odd_even_odd = [i for i in nums if is_odd(i[0]) and is_even(i[1]) and is_odd(i[2]) ]
+#
+odd_even_even = [i for i in nums if is_odd(i[0]) and is_even(i[1]) and is_even(i[2])]
+#
+even_odd_odd = [i for i in nums if is_even(i[0]) and is_odd(i[1]) and is_odd(i[2]) ]
+#奇奇偶
+even_odd_even = [i for i in nums if is_even(i[0]) and is_odd(i[1]) and is_even(i[2]) ]
+#
+even_even_odd = [i for i in nums if is_even(i[0]) and is_even(i[1]) and is_odd(i[2]) ]
+#
+even_even_even = [i for i in nums if is_even(i[0]) and is_even(i[1]) and is_even(i[2])]
+
+print(len(even_even_even))
+print(len(even_even_odd))
+print(len(odd_odd_even))
+
+f = lambda x: True if '7' not in x and '5' not in x else False
+result = list(filter(f, even_odd_even))
+print(result)
+
 l = set([ f"{i:03d}" for i in a ])
 
 sum_dict = dict()
-print(len(l))
+# print(len(l))
 for i in l:
     _sum = sum(map(int, i))
     v = sum_dict.get(_sum, 0)
     sum_dict[_sum] = v + 1
 
 df = pd.Series(sum_dict)
-print(df.sort_values(ascending=False))
\ No newline at end of file
+# print(df.sort_values(ascending=False))
\ No newline at end of file
diff --git a/sk_test.py b/sk_test.py
new file mode 100644
index 0000000..712ebbd
--- /dev/null
+++ b/sk_test.py
@@ -0,0 +1,34 @@
+import sklearn
+from sklearn import linear_model, tree
+
+# 普通最小二乘法
+reg = linear_model.LinearRegression()
+reg.fit([[0, 0], [1, 1], [2, 2]], [0, 1, 2])
+result = reg.predict([[3, 1]])
+print(reg.coef_)
+print(result)
+
+# 贝叶斯岭回归
+X = [[0., 0.], [1., 1.], [2., 2.], [3., 3.]]
+Y = [0., 1., 2., 3.]
+reg = linear_model.BayesianRidge()
+reg.fit(X, Y)
+result = reg.predict([[1, 0]])
+print(reg.coef_)
+print(result)
+
+# 决策树分类
+X = [[0, 0], [1, 1]]
+Y = [0, 1]
+clf = tree.DecisionTreeClassifier()
+clf = clf.fit(X, Y)
+result = clf.predict([[10., 11.]])
+print(result)
+print(clf.predict_proba([[10., 11.]]))
+# 决策树回归
+X = [[0, 0], [2, 2]]
+Y = [1.5, 6.5]
+clf = tree.DecisionTreeRegressor()
+clf = clf.fit(X, Y)
+result = clf.predict([[1, 2]])
+print(result)