# 破解博客园登录验证# 1.输入用户名与密码并点击登录# 2.探出滑动验证，获取有缺口与完整的图片# 3.通过像素点进行对比，获取滑动距离# 4.模拟人的行为轨迹# 5.开始滑动

'''''''''破解极验滑动验证破解极验滑动验证博客园登录url:    https://account.cnblogs.com/signin?returnUrl=https%3A%2F%2Fwww.cnblogs.com%2F

代码逻辑:1、输入用户名与密码，并点击登录2、弹出滑动验证，获取有缺口与完整的图片3、通过像素点进行比对，获取滑动位移距离4、模拟人的行为轨迹5、开始滑动

'''from selenium import webdriver  # 用来驱动浏览器的from selenium.webdriver import ActionChains  # 破解滑动验证码的时候用的 可以拖动图片import timefrom PIL import Image  # pip3 install pillowimport random

# 截图图片函数def cut_image(driver):    # 获取整个页面图片，图片名字为'snap.png'    driver.save_screenshot('snap.png')

    # 获取滑动小画图    image = driver.find_element_by_class_name('geetest_canvas_img')    print(image.location)    print(image.size)

    # 获取小图片的左上右下的位置    left = image.location['x']    top = image.location['y']    right = left + image.size['width']    buttom = top + image.size['height']    print(left, top, right, buttom)

    # 调用open方法打开全屏图片并赋值给image_obj对象    image_obj = Image.open('snap.png')

    # 通过image_obj对象对小图片进行截取    # box: The crop rectangle, as a (left, upper, right, lower)-tuple.    img = image_obj.crop((left, top, right, buttom))    # 打开截取后的小图片    # img.show()    return img

# 获取完整图片def get_image1(driver):    time.sleep(2)

    # 修改document文档树，把完整图片的display属性修改为block    js_code = '''        var x = document.getElementsByClassName("geetest_canvas_fullbg")[0].style.display = "block";    '''

    # 执行js代码    driver.execute_script(js_code)

    # 截取图片    image = cut_image(driver)

    return image

# 获取有缺口图片def get_image2(driver):    time.sleep(2)

    # 修改document文档树，把完整图片的display属性修改为block    js_code = '''        var x = document.getElementsByClassName("geetest_canvas_fullbg")[0].style.display = "none";    '''

    # 执行js代码    driver.execute_script(js_code)

    # 截取图片    image = cut_image(driver)

    return image

# 获取滑块滑动距离def get_distance(image1, image2):    # 小滑块右侧位置    start = 60

    # 像素差    num = 60    print(image1.size)    for x in range(start, image1.size[0]):        for y in range(image1.size[1]):

            # 获取image1完整图片每一个坐标的像素点            rgb1 = image1.load()[x, y]

            # 获取image2缺口图片每一个坐标的像素点            rgb2 = image2.load()[x, y]            # (60, 86, 40) (60, 86, 40) rgb            print(rgb1, rgb2)

            # abs获取绝对值， 像素点比较的值            r = abs(rgb1[0] - rgb2[0])            g = abs(rgb1[1] - rgb2[1])            b = abs(rgb1[2] - rgb2[2])

            # 如果条件成立，则找到缺口位置            if not (r < num and g < num and b < num):                # 有误差 - 7像素                return x - 7

# 模拟人的滑动轨迹def get_strck_move(distance):    distance += 20

    '''    滑动行为轨迹    加速公式:        v = v0 + a * t

    路程公式:        s = v0 * t + 0.5 * a * (t ** 2)    '''

    # 初速度    v0 = 0

    # 时间    t = 0.2

    # 位置    s = 0

    # 滑动轨迹列表 向前滑动列表    move_list = []

    # 中间值,作为加减速度的位置    mid = distance / 5 * 3

    # 加减速度列表    v_list = [1, 2, 3, 4]

    # 循环位移    while s < distance:        if s < mid:            # 随机获取一个加速度            a = v_list[random.randint(0, len(v_list) - 1)]

        else:            # 随机获取一个减速度            a = -v_list[random.randint(0, len(v_list) - 1)]

        '''        匀加速\减速运行        v = v0 + a * t

        位移:        s = v * t + 0.5 * a * (t**2)        '''        # 获取初始速度        v = v0

        # 路程公式:        s1 = v * t + 0.5 * a * (t ** 2)        s1 = round(s1)  # 取整

        # 加速公式:        # v = v0 + a * t        m_v = v + a * t

        # 把当前加/减速度赋值给初始速度，以便下一次计算        v0 = m_v

        # 把位移添加到滑动列表中        move_list.append(s1)

        # 修改滑动初始距离        s += s1

    # 后退列表, 自定义后退滑动轨迹,必须是负值    back_list = [-1, -1, -2, -3, -2, -1, -1, -2, -3, -2, -1, -1]

    return {'move_list': move_list, 'back_list': back_list}

def main():    driver = webdriver.Chrome()    driver.implicitly_wait(10)    driver.get('https://account.cnblogs.com/signin?returnUrl=https%3A%2F%2Fwww.cnblogs.com%2F')

    # 1、输入用户名与密码，并点击登录    user_input = driver.find_element_by_id('LoginName')    user_input.send_keys('大蜘蛛007')    time.sleep(0.2)

    pwd_input = driver.find_element_by_id('Password')    pwd_input.send_keys('@bb18861558365')    time.sleep(2)

    login_submit = driver.find_element_by_id('submitBtn')    login_submit.click()

    # 2、获取完整的图片    image1 = get_image1(driver)

    # 3、获取有缺口图片    image2 = get_image2(driver)

    # 4、比对两张图片，获取滑动距离    distance = get_distance(image1, image2)    print(distance)

    # 5、模拟人的滑动轨迹    move_dict = get_strck_move(distance)    # 获取前进滑动轨迹    move_list = move_dict['move_list']    # 获取后退滑动轨迹    back_list = move_dict['back_list']

    # 6、开始滑动    move_tag = driver.find_element_by_class_name('geetest_slider_button')    # 点击摁住滑动按钮    ActionChains(driver).click_and_hold(move_tag).perform()

    # 向前滑动    for move in move_list:        ActionChains(driver).move_by_offset(xoffset=move, yoffset=0).perform()        time.sleep(0.1)

    time.sleep(0.1)

    # 向后滑动    for back in back_list:        ActionChains(driver).move_by_offset(xoffset=back, yoffset=0).perform()        time.sleep(0.1)

    # 制作微妙晃动    ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()    ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()

    time.sleep(0.1)

    # 释放滑动按钮    ActionChains(driver).release().perform()

    time.sleep(100)

if __name__ == '__main__':    main()