自动登录博客园之后台验证码

验证码

#破解博客园后台登录
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

def get_snap():
    driver.save_screenshot('full_snap.png')
    page_snap_obj=Image.open('full_snap.png')
    return page_snap_obj

def get_image():
    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()
    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}

try:
    # 1、输入账号密码回车
    driver = webdriver.Chrome()
    driver.implicitly_wait(3)
    driver.get('https://passport.cnblogs.com/user/signin')

    username = driver.find_element_by_id('input1')
    pwd = driver.find_element_by_id('input2')
    signin = driver.find_element_by_id('signin')

    username.send_keys('******')  #用户名
    pwd.send_keys('******')    #密码
    signin.click()

    # 2、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()

    # 3、获取没有缺口的图片
    image1 = get_image()

    # 4、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()

    # 5、获取有缺口的图片
    image2 = get_image()

    # 6、对比两种图片的像素点，找出位移
    distance = get_distance(image1, image2)

    # 7、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)

    # 8、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()

    time.sleep(10)  # 睡时间长一点，确定登录成功
finally:
    driver.close()





#总结：测试了几下，感觉就是验证码的位置是随机变化的，但是此码给出的信息却是不变的，so，pass

再来：参考

###############优化后的代码（将功能封装成函数调用）#######
from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By #按照什么方式查找，By.ID,By.CSS_SELECTOR
from selenium.webdriver.common.keys import Keys #键盘按键操作
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait #等待页面加载某些元素
from PIL import Image #pip3 install pillow

import time

def get_snap(driver):
    driver.save_screenshot('snap.png')#截图
    snap_obj=Image.open('snap.png')#保存
    return snap_obj

def get_image(driver):
    img=driver.find_element_by_class_name('geetest_canvas_img')
    time.sleep(2) #等待图片加载完毕
    size=img.size
    location=img.location
    #获取图片位置
    left=location['x']
    top=location['y']
    right=left+size['width']
    bottom=top+size['height']

    snap_obj=get_snap(driver)
    image_obj=snap_obj.crop((left,top,right,bottom))#截图操作
    # image_obj.show()
    return image_obj

def get_distance(image1,image2):
    start_x=58#滑块最左侧
    threhold=60#去除伪影响
    # print(image1.size)
    # print(image2.size)
    for x in range(start_x,image1.size[0]):
        for y in range(image1.size[1]):
            rgb1=image1.load()[x,y]
            rgb2=image2.load()[x,y]
            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):
                return x-7#误差范围

def get_tracks(distance):
    distance+=20#故意划过头20像素
    #v=v0+a*t
    #s=v*t+0.5*a*(t**2)

    v0=0
    s=0
    t=0.2
    mid=distance*3/5
    forward_tracks=[]

    while s < distance:
        if s < mid:
            a=2
        else:
            a=-3

        v=v0
        track=v*t+0.5*a*(t**2)
        track=round(track)#取整数
        v0=v+a*t
        s+=track
        forward_tracks.append(track)
    back_tracks=[-1,-1,-1,-2,-2,-2,-3,-3,-2,-2,-1] #20
    return {"forward_tracks":forward_tracks,'back_tracks':back_tracks}


def crack(driver):#封装滑动的函数
    # 2、点击验证人机按钮，弹出没有缺口的图
    button = driver.find_element_by_class_name('geetest_radar_tip_content')
    button.click()

    # 3、针对没有缺口的图片进行截图
    image1 = get_image(driver)

    # 4、点击滑动按钮，弹出有缺口的图
    slider_button = driver.find_element_by_class_name('geetest_slider_button')
    slider_button.click()

    # 5、针对有缺口的图片进行截图
    image2 = get_image(driver)

    # 6、对比两张图片，找出缺口，即滑动的位移
    distance = get_distance(image1, image2)
    # print(distance)

    # 7、按照人的行为行为习惯，把总位移切成一段段小的位移
    traks_dic = get_tracks(distance)

    # 8、按照位移移动
    slider_button = driver.find_element_by_class_name('geetest_slider_button')
    ActionChains(driver).click_and_hold(slider_button).perform()  # 按住不放手
    # 先向前移动
    forward_tracks = traks_dic["forward_tracks"]
    back_tracks = traks_dic["back_tracks"]
    for forward_track in forward_tracks:
        ActionChains(driver).move_by_offset(xoffset=forward_track, yoffset=0).perform()

    # 短暂停顿，发现傻逼，移过了
    time.sleep(0.2)

    # 先向后移动
    for back_track in back_tracks:
        ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform()
    # 抖一抖
    ActionChains(driver).move_by_offset(xoffset=-4, yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()
    time.sleep(0.1)
    ActionChains(driver).move_by_offset(xoffset=-2, yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()
    time.sleep(0.3)
    ActionChains(driver).release().perform()  # 松开鼠标



def login_cnblogs(username,pwd):
    driver = webdriver.Chrome()  # 谷歌浏览器driver = webdriver.Chrome()#谷歌浏览器
    try:

        driver.get('https://passport.cnblogs.com/user/signin')#博客园
        driver.implicitly_wait(10)#隐形等待10秒

        #1、输入账号、密码，然后点击登陆
        input_user=driver.find_element_by_id('input1')
        input_pwd=driver.find_element_by_id('input2')
        login_button=driver.find_element_by_id('signin')

        input_user.send_keys(username)#输入账号
        input_pwd.send_keys(pwd)#输入密码
        login_button.click()#点击登录按钮
        # 调用 封装滑动的函数
        crack(driver)

        time.sleep(10)
    finally:
        driver.close()

if __name__ == '__main__':
    login_cnblogs(username='脚本小孩',pwd='*****')

还是出错，原因在第4个def  
“

def get_tracks(distance):
    distance+=20#故意划过头20像素

”  待解惑

 

 

继续啊

#首先要安装Pillow       pip3 install pillow
#Pillow:基于PIL，处理python 3.x的图形图像库.因为PIL只能处理到python 2.x，而这个模块能处理Python3.x，目前用它做图形的很多.

# 破解滑动验证码自动登录博客园
###########思路整理##########

from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By #按照什么方式查找，By.ID,By.CSS_SELECTOR
from selenium.webdriver.common.keys import Keys #键盘按键操作
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait #等待页面加载某些元素
from PIL import Image #pip3 install pillow

import time

def get_snap(driver):
    driver.save_screenshot('snap.png')#截图
    snap_obj=Image.open('snap.png')#保存
    return snap_obj

def get_image(driver):
    img=driver.find_element_by_class_name('geetest_canvas_img')
    time.sleep(2) #等待图片加载完毕
    size=img.size
    location=img.location
    #获取图片位置
    left=location['x']
    top=location['y']
    right=left+size['width']
    bottom=top+size['height']

    snap_obj=get_snap(driver)
    image_obj=snap_obj.crop((left,top,right,bottom))#截图操作
    # image_obj.show()
    return image_obj

def get_distance(image1,image2):
    start_x=58#滑块最左侧
    threhold=60#去除伪影响
    # print(image1.size)
    # print(image2.size)
    for x in range(start_x,image1.size[0]):
        for y in range(image1.size[1]):
            rgb1=image1.load()[x,y]
            rgb2=image2.load()[x,y]
            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):
                return x-7#误差范围

def get_tracks(distance):
    distance+=20#故意划过头20像素
    #v=v0+a*t
    #s=v*t+0.5*a*(t**2)

    v0=0
    s=0
    t=0.2
    mid=distance*3/5
    forward_tracks=[]

    while s < distance:
        if s < mid:
            a=2
        else:
            a=-3

        v=v0
        track=v*t+0.5*a*(t**2)
        track=round(track)#取整数
        v0=v+a*t
        s+=track
        forward_tracks.append(track)
    back_tracks=[-1,-1,-1,-2,-2,-2,-3,-3,-2,-2,-1] #20
    return {"forward_tracks":forward_tracks,'back_tracks':back_tracks}

try:
    driver = webdriver.Chrome()#谷歌浏览器
    driver.get('https://passport.cnblogs.com/user/signin')#博客园
    driver.implicitly_wait(10)#隐形等待10秒

    #1、输入账号、密码，然后点击登陆
    input_user=driver.find_element_by_id('input1')
    input_pwd=driver.find_element_by_id('input2')
    login_button=driver.find_element_by_id('signin')

    input_user.send_keys('脚本小孩')#输入账号
    input_pwd.send_keys('********')#输入密码
    login_button.click()#点击登录按钮

    #2、点击验证人机按钮，弹出没有缺口的图
    button=driver.find_element_by_class_name('geetest_radar_tip_content')
    button.click()

    #3、针对没有缺口的图片进行截图
    image1=get_image(driver)

    #4、点击滑动按钮，弹出有缺口的图
    slider_button=driver.find_element_by_class_name('geetest_slider_button')
    slider_button.click()

    #5、针对有缺口的图片进行截图
    image2=get_image(driver)

    #6、对比两张图片，找出缺口，即滑动的位移
    distance=get_distance(image1,image2)
    # print(distance)

    #7、按照人的行为行为习惯，把总位移切成一段段小的位移
    traks_dic=get_tracks(distance)

    #8、按照位移移动
    slider_button=driver.find_element_by_class_name('geetest_slider_button')
    ActionChains(driver).click_and_hold(slider_button).perform()#按住不放手
    #先向前移动
    forward_tracks=traks_dic["forward_tracks"]
    back_tracks=traks_dic["back_tracks"]
    for forward_track in forward_tracks:
        ActionChains(driver).move_by_offset(xoffset=forward_track,yoffset=0).perform()

    #短暂停顿，发现傻逼，移过了
    time.sleep(0.2)

    # 先向后移动
    for back_track in back_tracks:
        ActionChains(driver).move_by_offset(xoffset=back_track,yoffset=0).perform()
    # 抖一抖
    ActionChains(driver).move_by_offset(xoffset=-4,yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3,yoffset=0).perform()
    time.sleep(0.1)
    ActionChains(driver).move_by_offset(xoffset=-2,yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3,yoffset=0).perform()
    time.sleep(0.3)
    ActionChains(driver).release().perform()#松开鼠标


    time.sleep(10)
finally:
    driver.close()

 

补充：

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

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()
    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_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()

if __name__ == '__main__':
    login_cnblogs(username='linhaifeng',password='xxxx')

修订版

 

参考网址：https://www.cnblogs.com/linhaifeng/articles/7802150.html#top

有一句话感触颇深，因为我也一直是这样认为的，比如说，，，数学，我一直都认为数学只是一种学习的工具
我学习数学很多时候只是想去做某件事，或者想去了解这件事的原理，想把他弄通透罢了

 

那么网上的学习软件，或者编程也好，本质不变，但是当程序员的性质变了，目的不变，

 

引用：

也就不修改说明说明了

ps:破解图片验证码的核心在于模拟人的行为，
自笔者在老男孩授课以来，上述的破解思路已经分享给很多人，
相应地网络上也已经有很多copy版，
极验后台的也在不断学习用户的破解行为，
但归根结底只要我们将破解行为模拟地足够像人，极验就拿我们没有办法，

上面引用的话也在说，核心在于模拟人的行为，那么计算机的本质是什么呢？不就是解法生产力。。。。解放思想嘛

那么爬虫的本质是什么?????   

我觉得现在我自学这些东西的目的在于什么？？

或者说我想要达到什么高度。。。。。

如果不知道，我想可以先放下了，想搞搞有目的有性质的东西——比如数学