12-基于selenium实现12306模拟登录，及京东登录滑动缺口验证模拟登录

流程分析：

• 使用selenium打开登录页面
• 对当前selenium打开的这张页面进行截图
• 对当前图片的局部区域（验证码图片区域）进行截图
  • 这样验证码图片和模拟登录进行所显示的图片一一对应（如果我们对图片发起请求每次请求都不一样无法准确定位及点击）
• 使用超级鹰识别验证码图片（坐标）

对当前selenium打开的这张页面进行截图

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("location:",location)
size = code_img_ele.size # 验证码标签对应的长和宽
print("size",size)

定位验证码图片左上角及右下角得坐标

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("location:",location)
size = code_img_ele.size # 验证码标签对应的长和宽
print("size",size)
# # 左下角和右下角坐标
rangle = (int(location["x"]),int(location["y"]),int(location["x"] + size["width"]),int(location["y"] + size["height"]))
print(rangle)

根据坐标区域进行裁剪

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("location:",location)
size = code_img_ele.size # 验证码标签对应的长和宽
print("size",size)
# # 左下角和右下角坐标
rangle = (int(location["x"]),int(location["y"]),int(location["x"] + size["width"]),int(location["y"] + size["height"]))
print(rangle)
# 至此验证码图片的区域我们就确定下来了
i = Image.open("aa.png")
code_img_name = 'C:/Users/gpc/Desktop/python/Chaojiying_Python/12306.png'
# crop 根据指定区域进行图片裁剪
frame = i.crop(rangle)
frame.save(code_img_name)# 保存

将验证码图片提交给超级鹰

超级鹰的使用方法可参考： 07-爬虫验证码破解实战

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
bro.maximize_window()  # 窗口最大化
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("location:",location)
size = code_img_ele.size # 验证码标签对应的长和宽
print("size",size)
# # 左下角和右下角坐标
rangle = (int(location["x"]),int(location["y"]),int(location["x"] + size["width"]),int(location["y"] + size["height"]))
print(rangle)
# 至此验证码图片的区域我们就确定下来了
i = Image.open("aa.png")
code_img_name = 'C:/Users/gpc/Desktop/python/Chaojiying_Python/12306.png'
# crop 根据指定区域进行图片裁剪
frame = i.crop(rangle)
frame.save(code_img_name)# 保存

# 将验证码图片提交给超级鹰进行识别
yanzhengma = chaojiying.Chaojiying_Client.tranformImgCode()
print(yanzhengma)

点击验证码并登录账号

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
bro.maximize_window()  # 窗口最大化
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("验证码图片左上角坐标:",location)
size = code_img_ele.size # 验证码标签对应的高和宽
print("验证码图片的高和宽:",size)
# # 左上角和右下角坐标
rangle = (int(location["x"]),int(location["y"]),int(location["x"] + size["width"]),int(location["y"] + size["height"]))
print("验证码图片左上角和右下角坐标:",rangle)
# 至此验证码图片的区域我们就确定下来了
i = Image.open("aa.png")
code_img_name = 'C:/Users/gpc/Desktop/python/Chaojiying_Python/12306.png'
# crop 根据指定区域进行图片裁剪
frame = i.crop(rangle)
frame.save(code_img_name)# 保存

# 将验证码图片提交给超级鹰进行识别
yanzhengma = chaojiying.Chaojiying_Client.tranformImgCode()
print("超级鹰识别出来的待点击的坐标值:",yanzhengma)

all_list = [] # 存储即将被点击的点坐标 [[x1,y1],[x2,y2]]
if "|" in yanzhengma:
    list_1 = yanzhengma.split("|")
    count_1 = len(list_1)
    for i in range(count_1):
        xy_list = []
        x = int(list_1[i].split(",")[0])
        y = int(list_1[i].split(",")[1])
        xy_list.append(x)
        xy_list.append(y)
        all_list.append(xy_list)
else:
    x = int(yanzhengma.split(",")[0])
    y = int(yanzhengma.split(",")[1])
    xy_list = []
    xy_list.append(x)
    xy_list.append(y)
    all_list.append(xy_list)

print(all_list)

# 遍历位置列表,使用动作链对每一个列表元素对应的x，y指定的位置进行点击操作
for l in all_list:
    x = l[0]
    y = l[1]
    ActionChains(bro).move_to_element_with_offset(code_img_ele,x,y).click().perform()#动作链
    time.sleep(0.5)

# 输入用户名密码
bro.find_element_by_id('J-userName').send_keys('18398141111')
time.sleep(1)
bro.find_element_by_id('J-password').send_keys('11111')
time.sleep(1)
bro.find_element_by_id('J-login').click()

#bro.quit()#退出

滑动模块破解

加入动作链滑动代码如下

# -*- coding: utf-8 -*-
from selenium import webdriver
import time
from PIL import Image
from Chaojiying_Python import chaojiying
from selenium.webdriver import ActionChains


bro = webdriver.Chrome()
url = "https://kyfw.12306.cn/otn/resources/login.html"
bro.get(url)
bro.implicitly_wait(5) #静默等待最大5秒，保证页面加载完毕
bro.maximize_window()  # 窗口最大化
time.sleep(1)
bro.find_element_by_xpath("/html/body/div[2]/div[2]/ul/li[2]/a").click()
bro.save_screenshot('aa.png')# save_screenshot 将当前页面进行截图保存

# 确定验证码图片对应的左上角和右下角坐标（裁剪的区域就确定了）
code_img_ele = bro.find_element_by_xpath('//*[@id="J-loginImg"]')
location = code_img_ele.location #  验证码图片左上角的坐标 ｘ，ｙ
print("验证码图片左上角坐标:",location)
size = code_img_ele.size # 验证码标签对应的高和宽
print("验证码图片的高和宽:",size)
# # 左上角和右下角坐标
rangle = (int(location["x"]),int(location["y"]),int(location["x"] + size["width"]),int(location["y"] + size["height"]))
print("验证码图片左上角和右下角坐标:",rangle)
# 至此验证码图片的区域我们就确定下来了
i = Image.open("aa.png")
code_img_name = 'C:/Users/gpc/Desktop/python/Chaojiying_Python/12306.png'
# crop 根据指定区域进行图片裁剪
frame = i.crop(rangle)
frame.save(code_img_name)# 保存

# 将验证码图片提交给超级鹰进行识别
yanzhengma = chaojiying.Chaojiying_Client.tranformImgCode()
print("超级鹰识别出来的待点击的坐标值:",yanzhengma)

all_list = [] # 存储即将被点击的点坐标 [[x1,y1],[x2,y2]]
if "|" in yanzhengma:
    list_1 = yanzhengma.split("|")
    count_1 = len(list_1)
    for i in range(count_1):
        xy_list = []
        x = int(list_1[i].split(",")[0])
        y = int(list_1[i].split(",")[1])
        xy_list.append(x)
        xy_list.append(y)
        all_list.append(xy_list)
else:
    x = int(yanzhengma.split(",")[0])
    y = int(yanzhengma.split(",")[1])
    xy_list = []
    xy_list.append(x)
    xy_list.append(y)
    all_list.append(xy_list)

print("被点击的坐标位置:",all_list)

# 遍历位置列表,使用动作链对每一个列表元素对应的x，y指定的位置进行点击操作
for l in all_list:
    x = l[0]
    y = l[1]
    ActionChains(bro).move_to_element_with_offset(code_img_ele,x,y).click().perform()#动作链
    time.sleep(0.5)

# 输入用户名密码
bro.find_element_by_id('J-userName').send_keys('18398141111')
time.sleep(1)
bro.find_element_by_id('J-password').send_keys('11111')
time.sleep(1)
bro.find_element_by_id('J-login').click()

# 加入动作链
div_tag = bro.find_element_by_xpath('//*[@id="nc_1_wrapper"]')

# 对div_tag进行滑动操作
action = ActionChains(bro) #实例化一个动作对象
action.click_and_hold(div_tag) # 点击且长按不放

for i in range(6):
    # perform 让动作链立即执行
    action.move_by_offset(20,0).perform() #偏移x20像素，y0像素
    time.sleep(0.1)
action.release()




#bro.quit()#退出

结果如下：

京东缺口滑动验证码

# -*- coding: utf-8 -*-
from collections import Counter
from PIL import Image
from selenium import webdriver
import time
from selenium.webdriver.common.action_chains import ActionChains

class JDlogin():
    def __init__(self):#定义函数，链接登录页面
        self.driver = driver = webdriver.Chrome()#启动调试工具
        self.driver.get('https://passport.jd.com/new/login.aspx')#获取JD登陆页面
        self.driver.implicitly_wait(5)  # 静默等待最大5秒，保证页面加载完毕
        time.sleep(2)


    def get_picture(self):#获取图片
    #通过xpath寻找按键点击“账户登陆”
        self.driver.find_element_by_xpath('.//div[@class="login-tab login-tab-r"]/a').click()
        time.sleep(1)
        #定位账号输入框
        self.driver.find_element_by_xpath('.//input[@id="loginname"]').send_keys('账号')
        time.sleep(1)
        #定位密码输入框
        self.driver.find_element_by_xpath('.//input[@id="nloginpwd"]').send_keys('密码')
        time.sleep(1)
        #定位登陆按钮，并点击，此时会展示出验证码图片
        self.driver.find_element_by_xpath('.//div[@class="login-btn"]/a').click()
        time.sleep(1)
        #通过修改JS隐藏滑块并截屏获取验证码图片，保存至当前目录，名为slice.png（双层图也是这么干，不过ClassName与xpath需要改动）
        js = 'document.getElementsByClassName("JDJRV-smallimg")[0].style.display="none"'
        self.driver.execute_script(js)
        slice_path = './slice.png'
        self.driver.find_element_by_xpath('.//div[@class="JDJRV-bigimg"]').screenshot(slice_path)
        time.sleep(1)
        #停止1秒后恢复JS改动，回到页面最初状态（双层图亦然）
        js = 'document.getElementsByClassName("JDJRV-smallimg")[0].style.display="block"'
        self.driver.execute_script(js)

#将获得的验证码图片进行处理（灰度化、二值化、降噪）
#双层图可以直接进行两张图片的比较，而单层图则需要处理之后进行自身比较，本案例为单层图事例

    def shape(self, w, h, image):  # 二值化，将所有的点位，全部换成0或255
        tem = 0
        for x in range(w):
            for y in range(h):
                tem += image.getpixel((x, y))
        pixel_ave = tem / w / h * 0.7
        for x in range(w):
            for y in range(h):
                p = image.getpixel((x, y))
                if p < pixel_ave:
                    image.putpixel((x, y), 0)
                else:
                    image.putpixel((x, y), 255)
        return image

    def reducenoise(self, image):#降噪处理
        w, h = image.size
        for x in range(0, 40):  # 处理最左边
            for y in range(h):
                image2 = image.putpixel((x, y), 255)
        return image

    def make_picture(self):  # 处理图片，灰度化与二值化、降噪
        im = Image.open('slice.png')
        im2 = im.convert("L")
        w, h = im2.size
        im3 = self.shape(w, h, im2)
        im4 = self.reducenoise(im3)
        return im3

#计算验证图片左边边界到缺口左边边界的距离（即滑块拖动距离）

    def get_juli(self, image):  # 计算距离
        w, h = image.size
        ls = []
        for i in range(31, w - 31):#图片最左边放置滑块，缺口坐标x不可能小于31
            for j in range(10, h):
                if image.getpixel((i, j)) < 100:
                    count = 0
                    for k in range(i, i + 31):
                        if image.getpixel((k, j)) < 100:
                            count += 1
                        else:
                            break
                    if count > 27: ls.append(i)

        return Counter(ls).most_common(1)[0][0]

#设计拖动轨迹
    def get_track(self, distance):  # 设计拖动轨迹
        ls = [1]
        while 1:
            i = ls[-1] * 2
            ls.append(i)
            if sum(ls) > distance * 0.7:
                break

        ls.append(int(distance - sum(ls)))

        return ls
    
#通过selenium执行拖动滑块的指令，实现验证登陆
    def drog_btn(self, track):  # 拖动滑块
    #定位滑块
        ele = self.driver.find_element_by_xpath('.//div[@class="JDJRV-slide-inner JDJRV-slide-btn"]')
        #设计拖动动作链（点击且不放）
        ActionChains(self.driver).click_and_hold(ele).perform()
        #根据设计的轨迹，实现滑块拖动
        for i in track:
            ActionChains(self.driver).move_by_offset(i, 0).perform()#鼠标从当前位置移动到某个坐标
    #睡眠0.25秒，伪装成人的等一下松开鼠标的操作
            time.sleep(0.25)
        #释放滑块，类似于松开鼠标
        ActionChains(self.driver).release().perform()
        time.sleep(2)





    def check(self):#再次尝试
        self.get_picture()
        image = self.make_picture()
        distance = self.get_juli(image)
        track = self.get_track(distance)
        self.drog_btn(track)


if __name__ == '__main__':
    login = JDlogin()
    login.get_picture()
    image = login.make_picture()
    distance = login.get_juli(image)
    track = login.get_track(distance)
    login.drog_btn(track)
    time_int = 0
    while time_int < 5:
        input("是否需要再次尝试")
        login.driver.refresh()
        login.check()
        time_int += 1

ActionChains动作链方法列表

click(on_element=None) ——单击鼠标左键
click_and_hold(on_element=None) ——点击鼠标左键，不松开
context_click(on_element=None) ——点击鼠标右键
double_click(on_element=None) ——双击鼠标左键
drag_and_drop(source, target) ——拖拽到某个元素然后松开
drag_and_drop_by_offset(source, xoffset, yoffset) ——拖拽到某个坐标然后松开
key_down(value, element=None) ——按下某个键盘上的键
key_up(value, element=None) ——松开某个键
move_by_offset(xoffset, yoffset) ——鼠标从当前位置移动到某个坐标
move_to_element(to_element) ——鼠标移动到某个元素
move_to_element_with_offset(to_element, xoffset, yoffset) ——移动到距某个元素（左上角坐标）多少距离的位置
perform() ——执行链中的所有动作
release(on_element=None) ——在某个元素位置松开鼠标左键
send_keys(*keys_to_send) ——发送某个键到当前焦点的元素
send_keys_to_element(element, *keys_to_send) ——发送某个键到指定元素