步骤一:点击按钮，弹出没有缺口的图片 #步骤二：获取步骤一的图片 #步骤三：点击滑动按钮，弹出带缺口的图片 #步骤四：获取带缺口的图片 #步骤五：对比两张图片的所有RBG像素点，得到不一样像素点的x值，即要移动的距离 #步骤六：模拟人的行为习惯（先匀加速拖动后匀减速拖动），把需要拖动的总距离分成一段一段小的轨迹 #步骤七：按照轨迹拖动，完全验证 #步骤八：完成登录 from selenium import webdriver from selenium.webdriver import ActionChains from PIL import Image import time def get_snap(driver): driver.save_screenshot('full_snap.png') page_snap_obj = Image.open('full_snap.png') return page_snap_obj def get_image(driver): img = driver.find_element_by_class_name('geetest_canvas_img') time.sleep(2) # 获取图片元素坐标 location = img.location # 获取图片大小 size = img.size left = location['x'] top = location['y'] right = left+size['width'] bottom = top+size['height'] # 获取截屏图片对象 page_snap_obj = get_snap(driver) # crop处理裁剪后的图片-->获取裁剪后的图片对象 image_obj = page_snap_obj.crop((left, top, right, bottom)) # image_obj.show() return image_obj def get_distance(image1, image2): start = 57 threhold = 60 for i in range(start, image1.size[0]): for j in range(image1.size[1]): rgb1 = image1.load()[i, j] rgb2 = image2.load()[i, j] res1 = abs(rgb1[0]-rgb2[0]) res2 = abs(rgb1[1]-rgb2[1]) res3 = abs(rgb1[2]-rgb2[2]) # print(res1,res2,res3) if not (res1 < threhold and res2 < threhold and res3 < threhold): return i-7 return i-7 def get_tracks(distance): distance += 20 #先滑过一点，最后再反着滑动回来 v = 0 t = 0.2 forward_tracks = [] current = 0 mid = distance*3/5 while current < distance: if current < mid: a = 2 else: a = -3 s = v*t+0.5*a*(t**2) v = v+a*t current += s forward_tracks.append(round(s)) #反着滑动到准确位置 back_tracks = [-3, -3, -2, -2, -2, -2, -2, -1, -1, -1] #总共等于-20 return {'forward_tracks': forward_tracks, 'back_tracks': back_tracks} def crack(driver): # 破解滑动认证 # 1、点击按钮，得到没有缺口的图片 button = driver.find_element_by_class_name('geetest_radar_tip') button.click() # 2、获取没有缺口的图片 image1 = get_image(driver) # 3、点击滑动按钮，得到有缺口的图片 button = driver.find_element_by_class_name('geetest_slider_button') button.click() # 4、获取有缺口的图片 image2 = get_image(driver) # 5、对比两种图片的像素点，找出位移 distance = get_distance(image1, image2) # 6、模拟人的行为习惯，根据总位移得到行为轨迹 tracks = get_tracks(distance) print(tracks) # 7、按照行动轨迹先正向滑动，后反滑动 button = driver.find_element_by_class_name('geetest_slider_button') ActionChains(driver).click_and_hold(button).perform() # 正向滑动 for track in tracks['forward_tracks']: ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() # 开始反向滑动 time.sleep(0.5) for back_track in tracks['back_tracks']: ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform() # 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 ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform() ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() # 成功后，然后松开手 time.sleep(0.5) ActionChains(driver).release().perform() def login_cnblogs(username, password): driver = webdriver.Chrome(executable_path=r'E:chenweilearning爬虫chromedriver_win32chromedriver.exe') try: # 1、输入账号密码回车 driver.implicitly_wait(3) driver.get('https://passport.cnblogs.com/user/signin') input_username = driver.find_element_by_id('input1') input_pwd = driver.find_element_by_id('input2') signin = driver.find_element_by_id('signin') input_username.send_keys(username) input_pwd.send_keys(password) signin.click() button = driver.find_element_by_class_name('close') button.click() # 2、破解滑动认证 crack(driver) time.sleep(10) # 睡时间长一点，确定登录成功 finally: driver.close() if __name__ == '__main__': login_cnblogs(username='xxxxx',password='xxxx')