zoukankan      html  css  js  c++  java
  • 博客园登录selenium模拟登录

    # 导入模块
    from selenium import webdriver
    from selenium.webdriver import ActionChains
    from selenium.webdriver.common.by import By
    from selenium.webdriver.common.keys import Keys
    from selenium.webdriver.support import expected_conditions as EC
    from selenium.webdriver.support.wait import WebDriverWait
    from PIL import Image
    import time
    class OpenHideLocators:
        # 隐藏的属性需要更改之后才能获取到
        # js = "document.getElementById('checkWay').style.display='block'"
        # js1 = "document.getElementById('js-signin-btn').click()"
        # js="$('.geetest_canvas_fullbg').css('display','block');"
        js="document.getElementsByClassName('geetest_canvas_fullbg')[0].style.display='block'"
        # js1="$('.geetest_canvas_fullbg').css('display','none');"
    def get_snap(driver,save_name):
        now = time.strftime('%Y-%m-%d_%H_%M_%S')
        driver.save_screenshot(save_name)
        page_snap_obj = Image.open(save_name)
        return page_snap_obj
    
    def get_image(driver):
        img = driver.find_element_by_class_name('geetest_canvas_img')
        time.sleep(2)
        location = img.location
        size = img.size
        print(size)
    
        left = location['x']
        top = location['y']
        right = left+size['width']
        bottom = top+size['height']
    
        page_snap_obj = get_snap(driver,'full_snap.png')
        image_obj = page_snap_obj.crop((left, top, right, bottom))
        # image_obj.show()
        return image_obj
    def get_simage(driver):
        img = driver.find_element_by_class_name('geetest_canvas_img')
        time.sleep(2)
        location = img.location
        size = img.size
        print(size)
    
        left = location['x']
        top = location['y']
        right = left+size['width']
        bottom = top+size['height']
    
        page_snap_obj = get_snap(driver,'full_image.png')
        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 = [-1, -1, -1, -2, -3, -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,进入图片页面
        button = driver.find_element_by_class_name('geetest_radar_tip')
        button.click()
        time.sleep(3)
        test=driver.execute_script(OpenHideLocators.js)
        # [0].style.display='block'
        print(test)
        time.sleep(6)
        # 2.获取没有缺口的图片
        image1 = get_simage(driver)
        # driver.execute_script(OpenHideLocators.js1)
        # 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)
        print('对比'+str(distance))
        # 6.模拟人的行为习惯,根据总位移得到的行为轨迹
        tracks = get_tracks(distance)
        print(tracks)
    
        # 7.按照人行动轨迹先正向滑动,后反向滑动
        button = driver.find_element_by_class_name('geetest_slider_button')
        ActionChains(driver).click_and_hold(button).perform()
    
        # 正常人类总是自信满满地开始正向滑动,自信的表现是疯狂加速
        for track in tracks['forward_tracks']:
            ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()
    
        # 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
        time.sleep(0.3)
        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, 这一步可以极大的提高成功率
        time.sleep(0.1)
        ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()
        ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()
    
        # 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
        time.sleep(0.5)
        ActionChains(driver).release().perform()
    
    def login_cnblogs(username,password):
        driver = webdriver.Chrome()
        # 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()
    
        # 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()
        #     pass
    
    
    
    if __name__ == '__main__':
        login_cnblogs(username='dangkai',password='dk137046..')
    目前还在学习中,希望会对大家有所帮助,觉得不错,就点赞支持一下。 另外,转载时请附带链接。谢谢!
  • 相关阅读:
    CocoaPods版本升级
    NSParameterAssert
    layoutSubviews在以下情况下会被调用:
    swift笔记
    提交app时候90475,90474
    大数据基础---Azkaban_Flow_1.0_的使用
    大数据基础---Azkaban_3.x_编译及部署
    大数据基础---Azkaban简介
    大数据基础---Scala隐式转换和隐式参数
    大数据基础---Scala类型参数
  • 原文地址:https://www.cnblogs.com/dangkai/p/9669929.html
Copyright © 2011-2022 走看看