selenium模板实现实现滑动验证

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

from selenium import webdriver
driver = webdriver.Chrome()
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

# 配置驱动
option = webdriver.ChromeOptions()
# driver = webdriver.Chrome('/Users/wupeiqi/drivers/chromedriver', chrome_options=option)
driver = webdriver.Chrome( chrome_options=option)

2、找到登陆按钮并点击

# 1. 控制浏览器打开指定页面
driver.get("https://dig.chouti.com")


# 2. 找到登录按钮
btn_login = driver.find_element_by_xpath('//*[@id="login-link-a"]')
# 3. 点击按钮
btn_login.click()

3、输入账号和密码

# 4. 找到手机标签
input_user = driver.find_element_by_xpath('//*[@id="mobile"]')
# 5. 找到密码标签
input_pwd = driver.find_element_by_xpath('//*[@id="mbpwd"]')

# 6. 输入用户名
input_user.send_keys('18879970712')
# 7. 输入密码
input_pwd.send_keys('lg970712')

4、点击登陆按钮

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

5、找到要点赞的新闻并点赞

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

6、最后关闭驱动

# 10.关闭浏览器
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：

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
import os
import shutil
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)
    location = img.location
    size = img.size

    left = location['x']
    top = location['y']
    right = left + size['width']
    bottom = top + size['height']

    page_snap_obj = get_snap(driver)

    image_obj = page_snap_obj.crop((left, top, right, bottom))
    # image_obj.show()
    with open('code.png', 'wb') as f:
        image_obj.save(f, format='png')
    return image_obj


def get_distance(image1, image2):
    # start = 0
    # threhold = 70
    # for i in range(start, image1.size[0]):
    #     for j in range(0, 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):
    #             print(111111, i, j)
    #             return i - 13
    # print(2222, i, j)
    # return i - 13
    start = 0
    threhold = 70
    v = []
    for i in range(start, image1.size[0]):
        for j in range(0, 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])

            if not (res1 < threhold and res2 < threhold and res3 < threhold):
                print(i)
                if i not in v:
                    v.append(i)

    stop = 0
    for i in range(0, len(v)):
        val = i + v[0]
        if v[i] != val:
            stop = v[i]
            break

    width = stop - v[0]
    print(stop, v[0], width)
    return width


def get_tracks(distance):
    import random
    exceed_distance = random.randint(0, 5)
    distance += exceed_distance  # 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 = random.randint(1, 3)
        else:
            a = random.randint(1, 3)
            a = -a
        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
    v = 0
    t = 0.2
    back_tracks = []

    current = 0
    mid = distance * 4 / 5
    while abs(current) < exceed_distance:
        if current < mid:
            a = random.randint(1, 3)
        else:
            a = random.randint(-3, -5)
            a = -a
        s = -v * t - 0.5 * a * (t ** 2)
        v = v + a * t
        current += s
        back_tracks.append(round(s))
    return {'forward_tracks': forward_tracks, 'back_tracks': list(reversed(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_xpath('//*[@id="embed-captcha"]/div/div[2]/div[1]/div[3]')
    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)
    print(distance)
    #
    # 6、模拟人的行为习惯，根据总位移得到行为轨迹
    tracks = get_tracks(int(distance / 2))

    # 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
    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(0.5)
    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，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_luffy(username, password):
    driver = webdriver.Chrome()
    driver.set_window_size(960, 800)
    try:
        # 1、输入账号密码回车
        driver.implicitly_wait(3)
        driver.get('https://www.luffycity.com/login')
        input_username = driver.find_element_by_xpath('//*[@id="router-view"]/div/div/div[2]/div[2]/input[1]')
        input_pwd = driver.find_element_by_xpath('//*[@id="router-view"]/div/div/div[2]/div[2]/input[2]')

        input_username.send_keys(username)
        input_pwd.send_keys(password)

        # 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:
        pass
        # driver.close()


if __name__ == '__main__':
    login_luffy(username='wupeiqi', password='123123123')