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7月5号第二次直播学习笔记

程序员文章站 2024-01-21 14:17:40
一:alex更浓的鸡汤 alex为我们分享了他自己的职业发展历程,为我们点出一些职场上的重要关注点,很是收益,尤其是那一句‘你为什么不受到关注’印象深刻,最后alex指出思维的升级和改变给自己的重要意义,深受启发,感谢! 二:Selenium基础知识点的学习 Selenium是一个第三方模块,可以完 ......

一:alex更浓的鸡汤

  alex为我们分享了他自己的职业发展历程,为我们点出一些职场上的重要关注点,很是收益,尤其是那一句‘你为什么不受到关注’印象深刻,最后alex指出思维的升级和改变给自己的重要意义,深受启发,感谢!

二:Selenium基础知识点的学习

  Selenium是一个第三方模块,可以完全模拟用户在浏览器上操作(在浏览器上点点点)。

  1,安装

    - pip install selenium

  2,优缺点

    -无需查看和确定请求头请求体等数据细节,直接模拟人点击浏览器的行为

    -但效率不高

  3,依赖驱动:

       Firefox
        https://github.com/mozilla/geckodriver/releases
      Chrome
        http://chromedriver.storage.googleapis.com/index.html

  4,与selenium相关的基本操作

from selenium import webdriver

# 配置驱动
#驱动一定要自己下载并放在一个目录,否则会出错
option = webdriver.ChromeOptions() driver = webdriver.Chrome('/Users/wupeiqi/drivers/chromedriver', chrome_options=option) # 1. 控制浏览器打开指定页面 driver.get("https://dig.chouti.com/all/hot/recent/1") # 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() # 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('13121758648') # 7. 输入密码 input_pwd.send_keys('woshiniba') # 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() print(driver.get_cookies()) # # 9. 点击跳转 # news = driver.find_element_by_xpath('//*[@id="newsContent20646261"]/div[1]/a[1]') # # news.click() # driver.execute_script("arguments[0].click();", news) # 10.管理浏览器 # driver.close()

三:破解路飞官网滑动验证码

  peiqi老师为我们带来的精彩的讲解,从__main__的主函数调用开始,先讲了图片的截取和距离的测算,接下来分析了怎么模拟人类行为的滑动过程,通过速度和加速度的空值实现,而且会故意制造匹配之后的小幅振动行为,最后点击确定就可以破解该验证码,重点是像素的选择和速度的调节,感谢!

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 * 2, top * 2, right * 2, bottom * 2))
    # 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('/Users/wupeiqi/drivers/chromedriver')
    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')

 

  四:总结

    通过selenium模拟人类单机浏览器的行为,破解滑动验证码,让我有get到了爬虫的一个本领,首先需要掌握selenium点击行为的一般模式,最后可以好好的参考peiqi老师的代码,作为模板用到以后的工作中,很有帮助,谢谢!下一步想再学学其他验证码的破解方式,多多益善!