selenium模板实现实现滑动验证

Posted 2020-12-03 xingkongyihao

1心得体会

之前还没有听说过selenium模板，现在发现这个模板挺牛逼的。能自动模拟用户操作浏览器，不过缺点就是慢了写，但是不需要自己写cookie、headers这些了，毕竟是用真实的浏览器去模板。主要是好不是很熟练，还需要多敲代码。

2、selenium介绍

selenium是一款自动化测试工具，支持很多主流的浏览器。只要浏览器安装了依赖驱动就行。

下面代码是模拟访问百度操作

1 from selenium import webdriver
2 driver = webdriver.Chrome()
3 driver.get("https://www.baidu.com")

只需简单的代码就可以让浏览器自己访问百度了。当然，这只是简单的操作。

对于用来操作来说，还有输入内容和点击这两个常用的功能

test = driver.find_element_by_xpath(xpath)这个语句可以根据xpath来找到相应的位置.

如果可以点击的话，test.click()  就会自己点击。

如果是需要输入内容的话，test.send_keys()

3.模拟登陆 https://dig.chouti.com并点赞

1、先配置驱动

1 # 配置驱动
2 option = webdriver.ChromeOptions()
3 # driver = webdriver.Chrome(‘/Users/wupeiqi/drivers/chromedriver‘, chrome_options=option)
4 driver = webdriver.Chrome( chrome_options=option)

2、找到登陆按钮并点击

1 # 1. 控制浏览器打开指定页面
2 driver.get("https://dig.chouti.com")
3 
4 
5 # 2. 找到登录按钮
6 btn_login = driver.find_element_by_xpath(‘//*[@id="login-link-a"]‘)
7 # 3. 点击按钮
8 btn_login.click()

3、输入账号和密码

1 # 4. 找到手机标签
2 input_user = driver.find_element_by_xpath(‘//*[@id="mobile"]‘)
3 # 5. 找到密码标签
4 input_pwd = driver.find_element_by_xpath(‘//*[@id="mbpwd"]‘)
5 
6 # 6. 输入用户名
7 input_user.send_keys(‘18879970712‘)
8 # 7. 输入密码
9 input_pwd.send_keys(‘lg970712‘)

4、点击登陆按钮

1 # 8. 点击登录按钮
2 input_submit = driver.find_element_by_xpath(
3     ‘//*[@id="footer-band"]/div[5]/div/div/div[1]/div[2]/div[4]/div[2]/div/span[1]‘)
4 input_submit.click()

5、找到要点赞的新闻并点赞

1 # 9. 点击跳转
2 news = driver.find_element_by_xpath(‘//*[@id="newsContent20696066"]/div[2]/a[1]‘)
3 news.click()
4 driver.execute_script("arguments[0].click();", news)

6、最后关闭驱动

1 # 10.关闭浏览器
2 driver.close()

4、滑动验证

实现滑动验证之前的步骤和前面的一样。登陆网站，找到输入账号和密码的位置输入账号和密码。不过验证的时候就需要滑动验证的，这就需要处理图片了。滑动验证一开始有一张完整的图片，将完整的图片下载下来，然后还有一张不完整的图片，也下载下来。我们需要做的就是对比着两张图片哪里的像素不同，根据不同像素的位置来计算需要滑动多少像素，然后去模拟浏览器去滑动。

完整代码如下：

  1 from selenium import webdriver
  2 from selenium.webdriver import ActionChains
  3 from selenium.webdriver.common.by import By
  4 from selenium.webdriver.common.keys import Keys
  5 from selenium.webdriver.support import expected_conditions as EC
  6 from selenium.webdriver.support.wait import WebDriverWait
  7 import os
  8 import shutil
  9 from PIL import Image
 10 import time
 11 
 12 
 13 def get_snap(driver):
 14     driver.save_screenshot(‘full_snap.png‘)
 15     page_snap_obj = Image.open(‘full_snap.png‘)
 16 
 17     return page_snap_obj
 18 
 19 
 20 def get_image(driver):
 21     img = driver.find_element_by_class_name(‘geetest_canvas_img‘)
 22     time.sleep(2)
 23     location = img.location
 24     size = img.size
 25 
 26     left = location[‘x‘]
 27     top = location[‘y‘]
 28     right = left + size[‘width‘]
 29     bottom = top + size[‘height‘]
 30 
 31     page_snap_obj = get_snap(driver)
 32 
 33     image_obj = page_snap_obj.crop((left, top, right, bottom))
 34     # image_obj.show()
 35     with open(‘code.png‘, ‘wb‘) as f:
 36         image_obj.save(f, format=‘png‘)
 37     return image_obj
 38 
 39 
 40 def get_distance(image1, image2):
 41     # start = 0
 42     # threhold = 70
 43     # for i in range(start, image1.size[0]):
 44     #     for j in range(0, image1.size[1]):
 45     #         rgb1 = image1.load()[i, j]
 46     #         rgb2 = image2.load()[i, j]
 47     #         res1 = abs(rgb1[0] - rgb2[0])
 48     #         res2 = abs(rgb1[1] - rgb2[1])
 49     #         res3 = abs(rgb1[2] - rgb2[2])
 50     #         # print(res1,res2,res3)
 51     #         if not (res1 < threhold and res2 < threhold and res3 < threhold):
 52     #             print(111111, i, j)
 53     #             return i - 13
 54     # print(2222, i, j)
 55     # return i - 13
 56     start = 0
 57     threhold = 70
 58     v = []
 59     for i in range(start, image1.size[0]):
 60         for j in range(0, image1.size[1]):
 61             rgb1 = image1.load()[i, j]
 62             rgb2 = image2.load()[i, j]
 63             res1 = abs(rgb1[0] - rgb2[0])
 64             res2 = abs(rgb1[1] - rgb2[1])
 65             res3 = abs(rgb1[2] - rgb2[2])
 66 
 67             if not (res1 < threhold and res2 < threhold and res3 < threhold):
 68                 print(i)
 69                 if i not in v:
 70                     v.append(i)
 71 
 72     stop = 0
 73     for i in range(0, len(v)):
 74         val = i + v[0]
 75         if v[i] != val:
 76             stop = v[i]
 77             break
 78 
 79     width = stop - v[0]
 80     print(stop, v[0], width)
 81     return width
 82 
 83 
 84 def get_tracks(distance):
 85     import random
 86     exceed_distance = random.randint(0, 5)
 87     distance += exceed_distance  # 先滑过一点，最后再反着滑动回来
 88     v = 0
 89     t = 0.2
 90     forward_tracks = []
 91 
 92     current = 0
 93     mid = distance * 3 / 5
 94     while current < distance:
 95         if current < mid:
 96             a = random.randint(1, 3)
 97         else:
 98             a = random.randint(1, 3)
 99             a = -a
100         s = v * t + 0.5 * a * (t ** 2)
101         v = v + a * t
102         current += s
103         forward_tracks.append(round(s))
104 
105     # 反着滑动到准确位置
106     v = 0
107     t = 0.2
108     back_tracks = []
109 
110     current = 0
111     mid = distance * 4 / 5
112     while abs(current) < exceed_distance:
113         if current < mid:
114             a = random.randint(1, 3)
115         else:
116             a = random.randint(-3, -5)
117             a = -a
118         s = -v * t - 0.5 * a * (t ** 2)
119         v = v + a * t
120         current += s
121         back_tracks.append(round(s))
122     return {‘forward_tracks‘: forward_tracks, ‘back_tracks‘: list(reversed(back_tracks))}
123 
124 
125 def crack(driver):  # 破解滑动认证
126     # 1、点击按钮，得到没有缺口的图片
127     button = driver.find_element_by_xpath(‘//*[@id="embed-captcha"]/div/div[2]/div[1]/div[3]‘)
128     button.click()
129 
130     # 2、获取没有缺口的图片
131     image1 = get_image(driver)
132 
133     # 3、点击滑动按钮，得到有缺口的图片
134     button = driver.find_element_by_class_name(‘geetest_slider_button‘)
135     button.click()
136 
137     # 4、获取有缺口的图片
138     image2 = get_image(driver)
139 
140     # 5、对比两种图片的像素点，找出位移
141     distance = get_distance(image1, image2)
142     print(distance)
143     #
144     # 6、模拟人的行为习惯，根据总位移得到行为轨迹
145     tracks = get_tracks(int(distance / 2))
146 
147     # 7、按照行动轨迹先正向滑动，后反滑动
148     button = driver.find_element_by_class_name(‘geetest_slider_button‘)
149     ActionChains(driver).click_and_hold(button).perform()
150 
151     # 正常人类总是自信满满地开始正向滑动，自信地表现是疯狂加速
152     for track in tracks[‘forward_tracks‘]:
153         ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()
154 
155     # 结果傻逼了，正常的人类停顿了一下，回过神来发现，卧槽，滑过了,然后开始反向滑动
156     time.sleep(0.5)
157     for back_track in tracks[‘back_tracks‘]:
158         ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform()
159     #
160     # # 小范围震荡一下，进一步迷惑极验后台，这一步可以极大地提高成功率
161     ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()
162     ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()
163 
164     # # 成功后，骚包人类总喜欢默默地欣赏一下自己拼图的成果，然后恋恋不舍地松开那只脏手
165     time.sleep(0.5)
166     ActionChains(driver).release().perform()
167 
168 
169 def login_luffy(username, password):
170     driver = webdriver.Chrome()
171     driver.set_window_size(960, 800)
172     try:
173         # 1、输入账号密码回车
174         driver.implicitly_wait(3)
175         driver.get(‘https://www.luffycity.com/login‘)
176         input_username = driver.find_element_by_xpath(‘//*[@id="router-view"]/div/div/div[2]/div[2]/input[1]‘)
177         input_pwd = driver.find_element_by_xpath(‘//*[@id="router-view"]/div/div/div[2]/div[2]/input[2]‘)
178 
179         input_username.send_keys(username)
180         input_pwd.send_keys(password)
181 
182         # 2、破解滑动认证
183         crack(driver)
184 
185         time.sleep(10)  # 睡时间长一点，确定登录成功
186     finally:
187         pass
188         # driver.close()
189 
190 
191 if __name__ == ‘__main__‘:
192     login_luffy(username=‘wupeiqi‘, password=‘123123123‘)

破解滑动验证